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Health Disparities in
Endocrine Disorders:
Biological, Clinical, and
Nonclinical Factors
An Endocrine Society Scientific Statement
Health Disparities in Endocrine Disorders: Biological,
Clinical, and Nonclinical Factors
An Endocrine Society Scientific Statement
The Endocrine Society Scientific Statements are designed
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concerning the scientific basis of disease and its application
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within The Endocrine Society.
Scientific Statement No. 4 should be cited as follows:
Golden SH et al. 2012 Health Disparities in Endocrine
Disorders: Biological, Clinical, and Nonclinical Factors:
An Endocrine Society Scientific Statement
J Clin Endocrinol Metab 97:E1579-E1639
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Health Disparities in
Endocrine Disorders:
Biological, Clinical, and
Nonclinical Factors
An Endocrine Society Scientific Statement
Sherita Hill Golden, Arleen Brown, Jane A. Cauley, Marshall H. Chin,
Tiffany L. Gary-Webb, Catherine Kim, Julie Ann Sosa, Anne E. Sumner,
and Blair Anton
Executive Summary: Health Disparities in Endocrine
Disorders: Biological, Clinical, and Nonclinical
Factors–An Endocrine Society Scientific Statement
Sherita Hill Golden, Arleen Brown, Jane A. Cauley, Marshall H. Chin,
Tiffany L. Gary-Webb, Catherine Kim, Julie Ann Sosa, Anne E. Sumner,
and Blair Anton
Department of Medicine (S.H.G.), Johns Hopkins University School of Medicine, Baltimore, Maryland
21287; Department of Epidemiology (S.H.G.), Johns Hopkins Bloomberg School of Public Health,
Baltimore, Maryland 21205; Welch Medical Library (B.A.), Johns Hopkins University, Baltimore, Maryland
21205; Geffen School of Medicine at the University of California, Los Angeles (A.B.), Division of General
Internal Medicine and Health Services Research, Los Angeles, California 90095; Department of
Epidemiology (J.A.C.), University of Pittsburgh Graduate School of Public Health, Pittsburgh,
Pennsylvania 15213; Department of Medicine (M.H.C.), Chicago Center for Diabetes Translation
Research, University of Chicago, Chicago, Illinois 60637; Department of Epidemiology (T.L.G.-W.),
Columbia University Mailman School of Public Health, New York, New York 10032; Departments of
Medicine and Obstetrics and Gynecology (C.K.), University of Michigan, Ann Arbor, Michigan 48105;
Departments of Surgery (Endocrine Surgery and Surgical Oncology) and Medicine (Oncology) (J.A.S.),
Yale University School of Medicine, New Haven, Connecticut 06520; and Diabetes, Obesity and
Endocrinology Branch (A.E.S.), National Institute of Diabetes, Digestive and Kidney Disease, National
Institutes of Health, Bethesda, Maryland 20827
H
ealth disparities among population subgroups in disease burden, comorbidities, and outcomes exist
throughout the world, making disparities one of the most
pressing issues facing science and medicine today. Although reasons for health disparities may vary across diseases and regions, there are a number of common contributing factors. The statement focuses on population
differences in the highly prevalent endocrine diseases of
type 2 diabetes mellitus and related conditions (prediabetes and diabetic complications), gestational diabetes, metabolic syndrome with a focus on obesity and dyslipidemia,
thyroid disorders, osteoporosis, and vitamin D deficiency
(1). Global prevalence data are presented when available,
but the Scientific Statement relies heavily on information
available on population differences in endocrine diseases
within the United States.
For each disease, the statement presents biological differences related to race, ethnicity, and/or sex, including
biological pathways and responses, genetics, and certain
individual demographic factors and health behaviors and
their role in endocrine health disparities. Each diseasespecific section also includes a discussion of additional
factors that contribute to endocrine health disparities and
have been well documented for U.S. populations, such as
income, education, geography, and other measures of socioeconomic status.
The statement also presents a conceptual framework,
adapted from Warnecke et al. (2, 3), which recognizes
population-level determinants of health outcomes as distinct from, yet intertwined with, individual-level determinants of health (see Fig. 3). The model identifies proximate, intermediate, and distal factors that influence health
outcomes. Proximate determinants of health include biological and genetic pathways, biological responses, individual health behaviors, and individual demographic and
social factors. Intermediate determinants include neighborhood- or community-level physical and social environments, as well as the health care delivery environment. The
health care delivery environment addresses access to care,
quality of care, provider characteristics, and aspects of the
ISSN Print 0021-972X ISSN Online 1945-7197
Printed in U.S.A.
Copyright © 2012 by The Endocrine Society
doi: 10.1210/jc.2012-2043 Received April 23, 2012. Accepted June 6, 2012.
Abbreviations: BMD, Bone mineral density; BMI, body mass index; CVD, cardiovascular
disease; ESRD, end-stage renal disease; GDM, gestational diabetes mellitus; GWAS, genome-wide association study; HbA1c, glycosylated hemoglobin; HDL, high-density lipoprotein; HLA, human leukocyte antigen; NHB, non-Hispanic Black; NHW, non-Hispanic
White; SMBG, self-monitoring of blood glucose; SNP, single nucleotide polymorphism;
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
jcem.endojournals.org
i
ii
patient-provider relationship. Distal determinants include
population social conditions (e.g. poverty, discrimination,
prejudice) and policies that affect social conditions, and
the organizations and institutions that determine or influence such policies.
Finally, the statement concludes by summarizing the
literature on health care interventions to improve the care
or outcomes of racial/ethnic minorities with diabetes. We
chose diabetes because this condition captures the diverse
set of factors previously described in the conceptual model
for disparities, because many interventions have attempted to reduce diabetes disparities, and finally because
most lessons from the diabetes literature are likely transferable to other endocrine conditions. Health care can implement disparity interventions at one or more levels of
influence: patients, providers, microsystems (immediate
health care environment and delivery team), health care
organization, community, and policy (4). See Tables 10
and 11 in Scientific Statement for summary of future research needs related to race/ethnic and sex disparities in
endocrine disorders. Understanding the biological, clinical, and nonclinical contributors to disparities in endocrine disorders will allow the design of effective interventions to reduce these disparities and improve public health.
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
tribution are important contributors to diabetes risk in
certain Asian populations, and Japanese-Americans
and Filipinos have more visceral fat at similar levels of
BMI and waist circumference compared to NHWs (5).
Glucose metabolism and insulin resistance
• Race/ethnic differences in glucose metabolism and homeostasis are summarized in Table 3.
• Insulin resistance is a key contributor to type 2 diabetes
risk in NHB, Mexican-American, Asian-American, and
Native American populations. Compared with their
NHW counterparts and independent of adiposity, NHBs,
Mexican-Americans, Asian-Americans, and Native
Americans have greater insulin resistance (6).
• Studies in non-Mexican Hispanic-Americans have
yielded conflicting results. Glucose metabolic features
differ among Hispanic-Americans from different countries of origin. This may explain the higher prevalence
of type 2 diabetes in Mexican-Americans compared
with those of Cuban-American and South American
descent.
• Asian-Americans have lower ␤-cell insulin secretion
compared with NHWs (6). The reduced ␤-cell function
in Asian-Americans may also explain why they are at
high risk for diabetes at lower levels of BMI (7).
Diabetes Mellitus and Prediabetes
Genetics
Disparities by race/ethnicity
Epidemiology
• Race/ethnic differences in the prevalence and incidence
of diabetes and prediabetes are summarized on pp.
E1581–E1582 and in Table 1.
Race/ethnic differences in biological factors
Obesity and fat distribution
• Obesity is one of the strongest risk factors for developing type 2 diabetes, and the race/ethnic differences in the
prevalence of obesity and overweight are summarized
on pp. E1582–E1583.
• Race/ethnic differences in obesity contribute to the
higher risk of type 2 diabetes in non-Hispanic Blacks
(NHBs) and Mexican-Americans; however, NHB
women have greater subcutaenous fat compared with
visceral fat than non-Hispanic White (NHW) women at
a given body mass index (BMI) and waist circumference
and may therefore develop type 2 diabetes at a higher
BMI than NHW women.
• Among Asian-Americans, there is variation in the prevalence of overweight and obesity depending on the
country of origin (Table 2). Differences in body fat dis-
• Table 4 summarizes results of studies that have linked
gene variants with a 15–20% increased risk of diabetes
along with their proposed pathways (8). The GenomeWide Association Study (GWAS) Catalog of the National
Human Genome Research Institute (www.genome.gov)
summarizes currently identified loci and their nearby
genes.
• Although most of the early studies focused on individuals of European descent, several recent studies have
demonstrated that these susceptibility loci are also present and associated with increased type 2 diabetes risk in
ethnic minority populations. The limited amount of
data in non-European ancestry populations does not
suggest that the genetic architecture of type 2 diabetes
differs across race/ethnic groups.
• Until recently, there were no GWAS analyses in nonEuropean populations; however, several studies have
identified novel diabetes-associated single nucleotide
polymorphisms (SNPs) in specific race/ethnic groups (Table 5). Future GWAS analyses should include Native
American, Hispanic-American, and NHB populations.
• Because genetic admixture may mask differences attributable to race/ethnicity, future genetic studies
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
should also use ancestral markers to account for
admixture.
Individual race/ethnic differences in nonbiological
factors
Acculturation
• Acculturation in Hispanic-American immigrants results in an increase in dietary habits that promote obesity (9). The association of acculturation with type 2
diabetes, however, is mixed and inconsistent. Although
acculturation appears to promote obesity, its association with diabetes may be offset by its positive influence
on physical activity and access to care, in that screening
and intervention occur sooner (9).
• Japanese immigrants to the United States have a 3-fold
higher rate of type 2 diabetes compared with their native Japanese counterparts (6).
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iii
cortisol exposure can contribute to abdominal adiposity and insulin resistance (12).
• Maternal psychological stress and fetal overexposure to
cortisol lead to the same metabolic abnormalities as
fetal undernutrition (11).
• Epigenetic changes in the pattern of cellular gene expression may influence how a fetus adapts to an adverse
intrauterine environment (11). In the future, studies in
humans that examine genetic methylation patterns will
help determine how epigenetic changes contribute to
the role of the fetal environment in race/ethnic differences in future risk of obesity and type 2 diabetes (13).
Disparities by sex
• The prevalence of diabetes mellitus has increased over
the past decade in both women and men and is similar
in both sexes (14).
Health behaviors
• Physical inactivity: NHBs, Native Americans, and
Alaska Natives report less leisure-time physical activity
than NHWs (10). Mexican-American women report
less leisure-time physical activity than NHW and NHB
women (10). There are sparse data currently on physical activity in Asian-American populations (5).
• Smoking: Native Americans and Alaska Natives have a
higher prevalence of smoking than NHWs (10). NHBs
and NHWs have similar smoking rates, whereas Mexican-Americans have significantly lower smoking rates.
In Asian-Americans, there is variation in rates of smoking, with the highest prevalence among Korean men and
the lowest prevalence among Asian Indian men (5).
Interface of environmental and clinical/biological
factors: epigenetics and early life events
• Low birth weight, fetal undernutrition, and maternalfetal stress appear to be unique contributors to elevated
diabetes and metabolic risk in NHBs. NHBs have lower
birth weight than NHWs, which may be related to maternal conditions during pregnancy, including stressful
life events, depressive and anxiety symptoms, economic
inequality (e.g. lower income and education, less access
to health care in NHBs), racial discrimination, residential segregation, neighborhood-level poverty, and maternal hypertension (11).
• Smaller birth weight is linked to insulin resistance and
diabetes, abdominal pattern of fat distribution, higher
blood pressure, abnormal lipid profiles, and increased
cardiovascular disease (CVD) risk (11). Studies have
also linked low birth weight with elevated cortisol reactivity in childhood and adolescence (11). And chronic
Complications of Diabetes Mellitus
Disparities by race/ethnicity
Epidemiology
• Race/ethnic differences in the prevalence and incidence
of microvascular and macrovascular complications of
diabetes are summarized on pp. E1590 –E1591 and pp.
E1591–E1592, respectively. Overall, ethnic minorities
appear to be disproportionately affected by microvascular complications and mortality associated with diabetes, likely related to poorer glycemic and CVD risk
factor control; however, there are some notable
paradoxes.
X NHBs with diabetes have a lower incidence of CVD
than NHWs with diabetes; however, once they have
CVD, they are more likely to die.
X NHBs have a higher rate of end-stage renal disease
(ESRD) secondary to diabetic nephropathy but are
less likely to die on dialysis than NHWs.
• NHBs, Native Americans and Alaska Natives, and Hispanic-Americans are 2.3, 1.9, and 1.5 times more likely
to die from diabetes than NHWs (15). And whereas
Asian-Americans, overall, are 20% less likely to die
from diabetes than NHWs, there are variations among
subgroups.
Race/ethnic differences in biological factors contributing to complications
Glycemic control
• Several systematic reviews and meta-analyses have
shown that ethnic minorities with type 2 diabetes have
iv
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
worse glycemic control than NHWs, which likely contributes to the higher risk of microvascular complications seen in these populations (16 –18).
• The proportion of diabetic ethnic minorities with poor
glycemic control, defined as glycemia above a specific
threshold, was significantly higher among NHBs, Hispanic-Americans, Native Americans, Asian-Americans, and Pacific Islanders (16).
• Although discussed more in the context of using glycosylated hemoglobin (HbA1c) as a diagnostic criteria
for diabetes, recent studies have suggested that nonglycemic factors may contribute to the higher HbA1c at
similar levels of fasting glucose seen in NHBs, HispanicAmericans, Asian-Americans, and Native Americans,
compared with NHWs (19). However, HbA1c is similarly associated with prevalence and risk of microvascular and macrovascular complications and mortality
among NHBs and NHWs with diabetes (20 –22), lending credence to true differences in glycemia between the
two race/ethnic groups. Because conflicting evidence is
evolving about the contribution of nonglycemic factors
to HbA1c levels in minorities with diabetes, caution
should be used in applying HbA1c as the only measure
to assess either diabetes diagnosis or management.
Cardiovascular risk factors
Blood pressure
• Hypertension is an important risk factor for diabetic
nephropathy/ESRD and peripheral arterial disease, and
likely contributes to the higher prevalence of these complications in certain ethnic groups.
X NHBs have a higher prevalence of hypertension than
NHWs (10).
X Mexican-American women have a higher prevalence of hypertension than NHW women; however,
the prevalence of hypertension is similar among men
in the two race/ethnic groups (10).
X Native Americans and Alaska Natives have a
lower prevalence of hypertension compared with
NHWs and NHBs; however, there are regional
differences (10).
• In a previous systematic review, among U.S. adults with
type 2 diabetes, NHBs had higher systolic and diastolic
blood pressure and a higher percentage of individuals
with hypertension (16) than NHWs.
• Studies of blood pressure control and hypertension
prevalence comparing NHWs to Native Americans and
Asian-Americans with diabetes are lacking.
• Research to date from clinical trials indicates that control of reversible risk factors, including hypertension, is
equally effective in lowering the risk of nephropathy
and CVD in minority and NHW populations (23).
Lipids
• In a prior systematic review comparing low-density lipoprotein cholesterol between minority populations
and NHWs with type 2 diabetes, Hispanic-Americans
had slightly lower low-density lipoprotein cholesterol
than NHBs and NHWs. In this review, there were no studies comparing lipid control in NHWs with Native Americans and Asian-Americans with type 2 diabetes (24).
• As summarized in the Metabolic Syndrome section,
NHBs have lower triglycerides than NHWs (25), which
may explain their lower risk of macrovascular disease;
however, they generally have a higher prevalence of low
high-density lipoprotein (HDL) cholesterol, a strong
CVD risk factor (25).
Genetics
• As noted in the prior section on genetics and type 2
diabetes risk, few GWAS analyses have been performed
in ethnic minority populations.
• A GWAS for diabetic nephropathy genes in NHBs identified several candidate genes, including RPS 12,
LIMK2, and SFI1 (26).
• A GWAS for diabetic nephropathy in Japanese individuals with type 2 diabetes identified the SLC12A3 and
engulfment and cell motility 1 genes as candidate genes
for susceptibility to diabetic nephropathy in this population (27).
Epigenetics
• Low birth weight has been suggested as a potential contributor to diabetic nephropathy (24).
• Animal studies have associated low birth weight with
postpartum alterations in the anatomical structure and
function of the kidneys and pancreas, which can predispose to renal damage (24). And human studies have
associated low birth weight with an increased odds of
ESRD (24).
Individual race/ethnic differences in nonbiological
factors contributing to complications
Health behaviors
Self-monitoring of blood glucose (SMBG)
• Although some studies have shown no differences in
SMBG by race/ethnicity, several have shown lower
rates among NHBs, Hispanic-Americans, and AsianAmericans, compared with NHWs. Two studies found
no difference in SMBG frequency in Native Americans
compared with NHWs (28).
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
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v
• There are several barriers to SMBG, including inconvenience and intrusiveness, pain, lower socioeconomic
position, education level, social class, and living in a
high poverty area, many of which are disproportionately prevalent in ethnic minority groups (28).
• Lipid abnormalities are more severe in women, particularly low-density lipoprotein cholesterol particle size
and triglyceride levels (30), although reports conflict as
to whether lipid control is worse among women with
diabetes than men with diabetes (37– 40).
Physical activity and smoking
Other biological factors
• As summarized earlier, ethnic minorities are less likely
to engage in leisure-time physical activity, which can
contribute to worse glycemic control and a propensity
to developing microvascular complications (10).
• Native Americans and Alaska Natives have a higher
prevalence of smoking than NHWs (10), which can
contribute to their higher risk of peripheral arterial disease and amputations.
• NHBs and NHWs have similar smoking rates, whereas
Mexican-Americans have significantly lower smoking
rates. Therefore, smoking may not explain ethnic differences in peripheral arterial disease in these
populations.
• Postulated mechanisms for sex differences include endothelial dysfunction and adipokine activity due to dimorphic sex hormone status. However, the reasons for
these sex differences remain largely speculative.
Disparities by sex
Epidemiology
• Sex differences in the prevalence and incidence of microvascular and macrovascular complications of diabetes are summarized on pp. E1594 –E1595 and p.
E1595, respectively.
• Diabetes increases risk of coronary heart disease in
women more than in men (29 –32). Absolute coronary
disease mortality is also higher in diabetic women than
in diabetic men, after adjustment for other CVD risk
factors.
• Men are more likely to undergo diabetes-related lower
extremity amputation and have higher rates of peripheral arterial disease compared with women (33, 34).
• All-cause mortality and CVD mortality both decreased
in diabetic men from 1971–2000. However, all-cause
mortality increased in diabetic women with no significant change in CVD mortality (35); women with diabetes had higher overall mortality than men with diabetes (35).
Sex differences in biological factors contributing to
complications
Glycemic control and cardiovascular risk factors
• The proportion of women with diabetes and elevated
HbA1c levels (ⱖ9.0%) declined to a significantly greater extent than the proportion of men between 1988–2002 (36).
• The increased risk of CVD in women conferred by diabetes may be due to the presence of other CVD risk factors,
including age, hypertension, and dyslipidemia (30).
Sex differences in nonbiological factors contributing
to complications
Treatment
• Women with type 2 diabetes are less likely to use aspirin
than men (36, 41).
Gestational Diabetes Mellitus (GDM)
Epidemiology of race/ethnic disparities
• Race/ethnic differences in the prevalence and incidence
of GDM are summarized on pp. E1596 –E1597.
Race/ethnic differences in clinical outcomes in
GDM
• Hispanic women are more likely to receive medical
management (as opposed to lifestyle changes only) than
NHBs or NHWs (42).
• Hispanic women are less likely to have gestational hypertension, preterm delivery, low-birth-weight infants,
and neonatal intensive care unit admissions, but more
likely to have babies with shoulder dystocia than NHW or
NHB women (42). NHB and NHW women with GDM
have similar perinatal processes and outcomes (42).
• Hispanic and Asian women with GDM had lower odds
of cesarean delivery than NHW women, and Asian
women had lower odds of macrosomia than NHW
women (43).
• NHB women with GDM have poorer outcomes than
NHW women with GDM.
X NHB women have higher odds of cesarean delivery
and intrauterine fetal demise (43).
X GDM in NHBs was more likely to confer greater
birth weight (44).
X NHB women had a lower prevalence of episiotomy
but a greater likelihood of cesarean delivery and
low-birth-weight infants (45). Macrosomia is more
common among Native Hawaiian/Pacific-Islanders
vi
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
and Filipinas compared with Japanese, Chinese, and
NHW mothers with GDM (46).
• Caribbean and Sub-Saharan African women show a
larger impact of GDM upon perinatal events compared
with North Africans (47).
• South Asians had the highest prevalence of GDM, while
experiencing the smallest relative effects of GDM upon
macrosomia and cesarean deliveries (47).
• GDM conferred greater risk for future diabetes for
NHB women than for other racial/ethnic groups, even
after consideration of BMI (48).
Nonbiological factors contributing to racial/ethnic
disparities in GDM
Health behaviors
• Although studies have linked dietary content and physical activity to GDM, studies have not examined their
relative contribution by race/ethnicity.
Socioeconomic status
• Studies have associated lower socioeconomic status
with greater prevalence of GDM apart from race/ethnicity (56, 57).
Country of nativity
Biological factors contributing to racial/ethnic
disparities in GDM
Genetics
• No studies have reported on the contribution of the
genetic polymorphisms to racial/ethnic differences in
GDM in U.S. populations.
• The BetaGene study has found a link between polymorphisms of GCK and G6PC2 and impaired insulin
secretion among Mexican-American women with histories of GDM and Finns with a similar impairment
(49). The BetaGene study also found a link between
polymorphisms in IGF2BP2 (50), TCF7L2 (51),
PPARG2 (52), and HNF4A (52) and altered insulin
sensitivity in women with histories of GDM.
• International studies have linked specific polymorphisms to GDM incidence; these associations vary by
race/ethnicity.
X The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study linked GCK and TCF7L2 polymorphisms with increased glucose levels and increased risk of GDM in Thai women (53).
X The HAPO Study also found an association between
the GCK variant and greater birth weight, fat mass,
skin-fold thicknesses in NHW Europeans, but not
Thai women, and the study linked the TCF7L2 variant with these outcomes in Europeans, but not Thai
women (53).
• Parental ancestry has also been associated with increased risk of GDM (54, 55).
• Foreign-born women have a greater prevalence of
GDM than women born in the United States, and this
disparity has increased from the 1990s to early 2000s
(56, 58, 59). In two studies, most of these births occurred to Hispanic women, the majority of whom were
from Mexico (56, 59).
• Foreign nativity increased the odds for GDM in women
of most racial/ethnic groups and subgroups of Hispanics, as well as among Chinese and Filipino women (58).
However, the risk conferred by nativity may differ between race/ethnic groups.
X Hedderson et al. (60) found a link between foreign
nativity and a greater risk of GDM among NHB,
South Asian, Filipino, Pacific Islander, Chinese,
Mexican, and NHW women.
X Foreign-born Japanese and Korean women actually
had a lower risk of GDM than Japanese and Korean
women born in the United States (60).
Geographic region
• Within the United States, the prevalence of GDM increased markedly in the western, northeastern, and
midwestern states, primarily due to the increase in
GDM births among NHBs (61).
• Regional differences might represent differences in
screening practices and prenatal care delivery and/or
regional increases in obesity (61).
Health care access and delivery
• Among women who had histories of GDM, Hispanic
women were more likely than NHW women to lack
health insurance and a primary care provider and to
report poor or only fair health (62).
Obesity
• Obesity is a significant risk factor for GDM in all racial/
ethnic groups.
• As with type 2 diabetes, the BMI cut-points for Asians
may be lower than in other racial/ethnic groups.
Metabolic Syndrome
Definition and epidemiology
• Definitions of the metabolic syndrome are summarized
on p. E1599 and in Table 7.
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
• Race/ethnic differences in the epidemiology of the metabolic syndrome are summarized on pp. E-1599 –E1600.
Race/ethnic and sex differences in body fat
distribution—implications for defining metabolic
syndrome
Non-Hispanic blacks
• Although emerging evidence demonstrates that the
waist circumference of risk might be similar in NHB
and NHW men, the waist circumference that predicts
visceral fat, insulin resistance, and cardiometabolic
risk may be higher in NHB than NHW women (63,
64). At a similar waist circumference, NHB women
have less visceral adipose tissue than NHW women
(65– 67).
Asian-Americans
jcem.endojournals.org
vii
els, and high lipoprotein lipase all contribute to lower
triglyceride levels in NHBs (71–74).
Low HDL cholesterol
• On a population-basis, HDL cholesterol levels are
higher in NHBs than NHWs; however, insulin-resistant
NHBs often have low HDL cholesterol levels even when
triglyceride is not elevated (25, 75, 76).
• Presumably, in NHBs, hepatic lipase, the enzyme that
clears HDL cholesterol particles from the circulation,
remains active in response to the hyperinsulinemia of
insulin resistance. Therefore, low HDL cholesterol may
be a factor in the development of type 2 diabetes or
CVD in NHBs, even in the absence of elevated triglyceride levels.
• Shifting emphasis from elevated triglyceride to low
HDL cholesterol in screening for metabolic risk in
NHBs is worthy of investigation.
• Studies suggest that metabolic risk occurs at lower waist
circumference in Asian-Americans (68).
Thyroid Disorders
X A recent study in Asian Indians suggested modified
waist circumference cut-points of 90 cm for men
and 85 cm for women because these values predicted the presence of other metabolic syndrome
components (i.e. dyslipidemia, dysglycemia, and
hypertension) (69).
X A study of Japanese-Americans suggested that more
appropriate waist circumference cut-points for Japanese-Americans were 87–90 cm for men and 80 –90
cm for women (68). Table 8 summarizes suggested
race/ethnic-specific waist circumference and BMI
cutoffs for defining adiposity components of the
metabolic syndrome.
Race/ethnic differences in lipoproteins—implications
for defining metabolic syndrome
Hypertriglyceridemia
• In NHWs, an elevated triglyceride level is one of the
most common features of the metabolic syndrome;
however, in NHBs and West Africans, the most common features of the metabolic syndrome are low HDL
cholesterol, hypertension, and central obesity, not elevated triglycerides (25).
• Use of hypertriglyceridemia as a diagnostic criterion for
metabolic syndrome could potentially lead to underrecognition of metabolic risk in NHBs.
• Triglyceride levels are usually normal in insulin-resistant NHB (70). The current belief is that low hepatic fat,
low visceral adipose tissue, low apolipoprotein CIII lev-
Racial/ethnic differences in benign thyroid
disorders
Epidemiology
• Race/ethnic differences in the prevalence of hypothyroidism and hyperthyroidism, and autoimmune thyroid disease are summarized on p. E1603.
• NHBs have significantly lower mean TSH concentrations than NHWs in all populations (P ⬍ 0.01) (77). It
has been debated whether the lower TSH levels are of
clinical significance, or whether they present simply a
normal shift in biochemical values, with no untoward
consequences for the individuals.
Biological factors contributing to race/ethnic disparities
Iodine intake
• In the National Health and Nutrition Examination Survey, NHBs had persistently lower urinary iodine concentrations than NHWs and Hispanic-Americans (78,
79), likely due to variations in their dietary intake.
These data suggest that NHB individuals may not
achieve iodine sufficiency according to World Health
Organization criteria.
Genetics
• Studies have reported genetic susceptibility to Graves’
disease associated with human leukocyte antigens
(HLA) in NHWs (80), and studies have shown that
specific loci differ by race.
viii
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
• Neither DQB1*0301 allele nor DR3 specificity was
present in NHB patients with Graves’ disease, but these
were present in NHWs. The discordance of the results
between NHWs and NHBs in the United States may be
attributable to the ethnic diversity of HLA genotypes,
or the complex interaction of HLA molecules with environmental factors.
Thyroid Cancer
Epidemiology
• Race/ethnic differences in the prevalence and incidence
of thyroid cancer are summarized on p. E1604.
• The incidence of thyroid cancer in the United States has
been increasing over the last 50 yr for women and men of
every racial background, except Native Americans (81).
Race/ethnic differences in clinical outcomes
• Although the prevalence and incidence of thyroid cancer is similar by race/ethnicity, survival from thyroid
cancer differs by race/ethnicity.
X NHB patients are more likely than NHWs to be diagnosed with anaplastic thyroid cancer, to have tumors greater than 4 cm, and to be diagnosed with
follicular nodules (all P ⬍ 0.0001) (82).
X NHB patients have lower 5-yr survival compared
with NHWs (96 vs. 97%; P ⬍ 0.006) (82).
X After thyroidectomy, the mean length of stay was
significantly longer for NHBs than for NHWs (83).
NHBs trended toward higher overall complication
rates, compared with NHWs and Hispanic-Americans. Mean total costs were significantly lower for
NHWs, compared with those for NHBs and
Hispanic-Americans.
• Race/ethnic differences also exist in the administration of
postoperative radioactive iodine. Compliance with American Thyroid Association thyroid cancer treatment guidelines for differentiated thyroid cancer was lowest in patients over age 65 yr and among NHBs (P ⬍ 0.001) (84).
Biological factors
disparities
Genetics
contributing
to
race/ethnic
• Research has linked the BRAF somatic mutation with an
aggressive tumor phenotype in papillary thyroid cancer,
older age, and higher recurrence rates (85). A meta-analysis of 1168 patients with papillary thyroid cancer showed
no differences in BRAF status by race/ethnicity, suggesting that genetic factors do not contribute to race/ethnic
differences in thyroid cancer survival (86).
Nonbiological factors contributing to race/ethnic
disparities
Socioeconomic status and access to care
• Tumors were more advanced by stage, and extrathyroidal extension was more prevalent in patients at a
public hospital where 96% of patients were ethnic minorities and only 2% of patients had insurance. Public
hospital patients were three times more likely to present
with advanced disease than those at the university hospital (87).
• Minority populations also lack access to adequate surgical care for thyroid cancer. In one study, the majority
of Hispanic-Americans (55%) and NHBs (52%) had
surgery by the lowest-volume surgeons (one to nine
cases per year), compared with only 44% of NHWs.
Highest-volume surgeons (⬎100 cases per year) performed 5% of thyroidectomies, but 90% of their patients were white (P ⬍ 0.001) (83).
• NHB patients were significantly less likely than NHW
patients to be operated on by a high-volume surgeon at a
high-volume hospital for nine out of 10 procedures analyzed, whereas Hispanic and Asian-American patients
had similar access to low-volume surgeons and hospitals
for four and five of the procedures, respectively (88).
Sex differences in benign thyroid disease and
thyroid cancer
Epidemiology
• Sex differences in the epidemiology of hypothyroidism,
hyperthyroidism, autoimmune thyroid disease, and
thyroid cancer are summarized on pp. E1605–E1606.
• Overall, autoimmune thyroid disease and thyroid cancer are more prevalent in women than men, although
thyroid cancer survival is higher in women (89).
Biological factors contributing to sex disparities in
thyroid cancer
Genetics
• Sex association with BRAF mutation has been controversial and weak (90, 91). A meta-analysis of 12 studies
with a total of 1168 patients (male:female ratio, 259:
909) did not show a significant difference in mutation
rate by sex, suggesting that genetics contributes little to
the sex disparity in thyroid cancer (86).
Sex hormones
• Papillary thyroid cancer expresses estrogen receptors, mediating the effects of estrogen systemically. Estradiol promotes thyroid cancer cell proliferation, when compared
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
with cells treated with testosterone or untreated cells, and
tamoxifen attenuated the growth-promoting effect (92).
• Evidence indicates that chorionic gonadotropin, which has a
close homology with TSH, causes rapid growth of thyroid
tumors (benign or malignant) during pregnancy (93).
Obesity
• A pooled analysis of five prospective studies reported a
positive association of BMI and an increased risk of
thyroid cancer in both men and women, whereas height
was a risk factor in women but not in men (94). There
is a positive association between increasing body fat
and cancer risk (95, 96). Because obesity is more common in women, this may contribute to the sex disparity.
• Studies have linked obesity with increased circulating
hormone levels (including estrogens, androgens, insulin, and IGF-I), and studies link attained height with
increased IGF-I. Estrogen may increase the risk of thyroid cancer through increased cell proliferation,
whereas IGF-I is a potent mitogen and inhibitor of apoptosis, and its effects on thyroid growth are amplified
by TSH (97, 98).
Osteoporosis and Fracture Risk
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ix
Biological and clinical factors contributing to race/
ethnic disparities
Race/ethnic differences in BMD
• BMD is a significant predictor of fracture risk and could
account for at least some of the ethnic differences in
fractures observed in population studies. Age-adjusted
mean femoral neck BMD is approximately 10% higher
in NHB women and 6.5% higher in Mexican-American
women (101). NHB men have a 10.7% higher femoral
neck BMD, but there was no difference in BMD in
NHW men or Mexican-American men (101).
• When studies adjust BMD for ethnic differences in anthropometric and lifestyle factors that affect BMD,
with careful adjustment for body weight, lumbar spine
BMD is similar in NHB, Chinese-American, and Japanese-American women, all of whom have higher spine
BMD than NHW women (102). For femoral neck
BMD, adjustment for these same factors (most importantly body weight) reduces the advantage of NHB
women, compared with other groups, and eliminates
differences among Chinese-American, Japanese-American, and NHW women (102).
• Lifestyle and anthropometric factors account for some
of the ethnic variation in BMD, although additional
ethnic variation in BMD remains unexplained.
Epidemiology
• Race/ethnic differences in the epidemiology of osteoporosis and fracture rates are summarized on pp.
E1607–E1609.
• With the exception of Asian-American women, minority women have higher bone mineral density (BMD)
than NHW women (Fig. 1), which translates into a reduced fracture risk in minority women (Fig. 2). AsianAmerican women also have lower fracture risk than
NHW, despite the lower BMD.
Race/ethnic differences in clinical outcomes:
mortality and disability after osteoporotic
fractures
• Mortality after hip fracture is higher among NHB
women than among NHW women (99). The factors
contributing to the higher mortality rate among NHB
women after a hip fracture are not completely understood but could reflect their older age at the time of
fracture, greater comorbidity, or disparities in health
care.
• One small study suggests that the percentage of patients
with hip fracture who were nonambulatory at the time
of their discharge was six times higher among NHB
women than among NHW women (100).
Skeletal risk factors for fracture
Bone mineral density
• For NHBs, at least 27–36% of their lower fracture risk
is due to their higher BMD (103). For Hispanic-Americans, based on Women’s Health Initiative (WHI) data,
BMD explains at least 17% of their lower fracture risk.
There are no data to address this in Asian-Americans.
• The Study of Osteoporotic Fractures did a follow-up for
6.1 yr of 7334 NHW women (age, 67–99 yr) and 636
NHB women (age, 65–94 yr) (104). At every level of
BMD, the fracture rate was lower in NHB vs. NHW
women.
• In the National Osteoporosis Risk Assessment Study,
the relative hazard of fracture was significantly lower in
NHB (48%) and Asian-American women (68%), compared with NHW women, independent of BMD, Tscore, body weight, and other fracture risk factors (105,
106).
• In the WHI, the risk of fracture was significantly lower
in NHB (49%), Asian-American (34%), and HispanicAmerican (33%) women compared with NHW women
(107). In a subset of women with BMD measurements,
adding BMD to the models did attenuate the risk; however, fracture risk remained significantly lower in
x
NHBs and Hispanic-Americans, even after adjusting
for BMD (107).
• Although BMD is higher in NHB than NHW women,
low BMD is still a risk factor for fracture in NHBs
(103).
Other skeletal traits— bone geometry and structure
• Women with shorter hip axis length have a lower risk
of fracture (108). The mean hip axis length was also
significantly shorter in NHB and Asian-American
women and may also contribute to their lower fracture
rates (109).
• NHB women have longer, narrower femurs on average
with smaller medullary cavities than NHW women
(110). The thicker cortices in NHB women could also
contribute to greater mechanical strength. NHB
women also had greater section modulus, an index of
strength suggesting that the spatial distribution of bone
is such that their bones can resist greater loads compared with NHW women.
• Higher BMD in Mexican-American women was due to
a smaller size of bone, not greater bone mineral content.
NHBs, Mexican-Americans, and Native Americans all
had greater section modulus than NHWs, which could
contribute to their lower fracture rates (111).
• NHB, Japanese-American, and Chinese-American
women all had significantly higher composite strength
indices than NHW women (112). Studies observed
these differences despite the lower areal BMD in Japanese and Chinese women and the higher body weight in
NHB compared with NHW women. These indices may
contribute to ethnic differences in fracture.
• Studies have also described ethnic differences in rates of
bone turnover (113), although these patterns do not
necessarily parallel ethnic differences in BMD.
Menopause
• In the Study of Women Across the Nation, lumbar spine
BMD loss was most rapid in Japanese-American and
Chinese-American women, intermediate in NHW
women, and slowest in NHB women (P ⬍ 0.001) (114).
Cumulative, transmenopausal changes were greatest
for Chinese-American and Japanese-American women
and lowest for NHB women (115). However, the absolute difference in bone loss by race/ethnicity was statistically significant but small—1–2%. Therefore, it is
unlikely that this amount of bone loss at menopause
could explain racial/ethnic differences in fracture rates.
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
tion comes from a single paper from the WHI that focused on all clinical fractures in women only, and BMD
was not measured in all women (116).
• To our knowledge, there is essentially no information
on risk factors for fracture in non-white men, other than
a small study of 39 NHB men, nine of whom had a
fracture. The only risk factor that was significant was
older age among the NHB men who experienced fractures (117). The data we summarized below are from
the WHI, unless otherwise indicated. These data are
also summarized in Table 9.
Body weight and height
• The association between weight and fracture may be
strongest for hip fractures; in two case-control studies
in NHB women, those who were underweight (118)
and in the lowest quintile of BMI (119) had a significantly increased risk of hip fracture. The Hispanic Established Populations for Epidemiologic Studies of the
Elderly study did not link BMI to hip fracture (120).
• The underlying mechanism for this association could
reflect additional fat at the hip resulting in weaker impact of the fall on the hip.
• Obesity has been associated with higher endogenous
estradiol levels and lower SHBG (121), both of which
have been linked to hip fracture risk (122).
• The WHI showed a significant association between
height greater than 162 cm and an increased risk of all
clinical fractures in NHWs and Hispanic-Americans
(107). There was a similar trend in Asian-American
women, although not statistically significant. There
was no association between height and fracture risk in
NHB or Native American women (Table 9).
Prior fracture history
• The WHI linked prior fracture history with an increased
fracture risk in all race/ethnic groups (Table 9) (107).
Parental history of fracture and ancestry
• The WHI linked parental history of any fracture with an
increased risk of fracture in all race/ethnic groups, although it was not consistently statistically significant
(Table 9) (107).
• Using ancestry informative markers, studies have
linked a greater amount of European admixture with
lower BMD and weaker hip geometry in NHBs (123,
124).
Nonskeletal risk factors for fracture
Medication use
• There are limited data on nonskeletal risk factors for
fracture in multiethnic women. Most of the informa-
• The WHI linked corticosteroid use for more than 2 yr
with an increased risk of fracture in all race/ethnic
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
groups, except Asian-Americans, although it was not
statistically significant in NHBs or Native Americans
(107).
• In a case-control study of NHB women, postmenopausal estrogen therapy for at least 1 yr was protective
against fractures in members of this population under
75 yr of age (119). The WHI linked current hormone
therapy use with a lower risk of fracture in Asian-American and Native American women (107).
Medical comorbidities
• In NHB women, the WHI linked a history of stroke with
a 3-fold increased risk of fracture (119).
• In Hispanic-American women, the WHI linked the presence of diabetes with an increased fracture risk (125).
Parity
• In Asian-American women, the WHI linked having at
least five pregnancies with a significantly higher risk of
fracture (107).
Treatment efficacy
• There is no evidence that treatment efficacy varies by
race, although the “evidence” is incomplete. A single
trial of alendronate administered to 65 NHB women
with T-scores less than ⫺3.0 showed that alendronate
treatment increases BMD at all sites. The magnitude of
the effect was similar to trials of NHW women (126).
• Vitamin D3 supplement of 2000 IU/d was sufficient to
raise 25-hydroxyvitamin D levels to greater than 50 nmol/
liter in almost all postmenopausal NHB women (127).
• As part of the WHI Hormone Trials, there was no evidence that the beneficial effect of hormone therapy on
fracture reduction differed by race/ethnicity (128, 129).
Nonbiological factors contributing to race/ethnic
disparities
Sociodemographic factors
• Fracture rates in the WHI increased with age in all race/
ethnic groups; however, in NHB women, rates did not
increase until after 75 yr of age (107).
• In NHB women, the WHI linked having at least a high
school education with a higher risk of fracture (107).
Health behaviors
• The WHI did not link smoking with fracture in any
ethnic group, but the prevalence of smoking was low in
the WHI women (107).
• Alcohol consumption was unrelated to fracture risk in
all race/ethnic groups in the WHI (107). In two case-
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xi
control studies in NHB women, higher alcohol consumption was associated with an increased risk of fracture (118, 119).
History of falls
• The WHI linked a history of falls with a significantly
higher risk of fracture in all race/ethnic groups, but the
association was much stronger in NHB and HispanicAmerican women (Table 9) (107).
Disparities in screening and treatment
• A much lower proportion of NHBs undergo BMD testing despite universal access (130).
• Significantly fewer NHB women than NHW women
were referred for dual-energy x-ray absorptiometry, although they had similar risk estimates (131). Physicians
were less likely to mention osteoporosis in the medical
records of the NHB women or to recommend calcium
or vitamin D supplementation, compared with NHW
women.
• NHB women with a history of fracture are also less
likely to receive a diagnosis of osteoporosis (132).
• NHBs are also substantially less likely to receive prescription osteoporosis medications than NHWs, even
after adjusting for socioeconomic factors or clinical risk
factors for fractures (133).
• At every level of predicted hip fracture risk, the percentage of women receiving osteoporosis therapies is
lower among NHB women (130).
Vitamin D Deficiency
Epidemiology
• Race/ethnic differences in vitamin D deficiency are
summarized on p. E1613.
• Overall, vitamin D levels are lower in NHBs compared
with NHWs.
Biological contributors to race/ethnic disparities
• NHBs are at higher risk for vitamin D deficiency because the high melanin concentration in their skin reduces the capacity to synthesize vitamin D (134).
• Studies have associated obesity with vitamin D deficiency, which researchers believe is caused by deposition of vitamin D into adipose tissue, decreasing the
bioavailability of the vitamin (134). Studies examining
whether differences in adiposity contribute to race/ethnic differences in vitamin D deficiency have been conflicting (134, 135).
xii
• Genetics: A recent study examined the association of vitamin D levels with 94 SNPs in five vitamin D pathway
genes in a case-control study of NHBs and NHWs and
found statistically significant associations between three
SNPs, only in NHBs (rs2298849 and rs2282679 in the
vitamin D binding protein group-specific component, and
rs10877012 in the CYP27B1 gene) (136). Overall, these
three SNPs only accounted for 4.6% of the variation in
serum vitamin D levels in NHBs, indicating the importance of nongenetic factors (136).
Nonbiological contributors to race/ethnic
disparities
• In both NHBs and NHWs, studies have associated lack
of vitamin D supplementation with lower vitamin D
levels (134, 137); even among NHB men and women
taking vitamin D supplements, the prevalence of vitamin D deficiency is higher than in NHWs (134, 135).
• Studies have linked levels of dairy intake with vitamin
D deficiency in NHBs, with less than three servings of
milk or cereal each week associated with deficiency in
NHB women and higher milk consumption associated
with less deficiency in NHB men (134, 135).
• In NHB men, higher levels of intentional physical activity were associated with a lower likelihood of vitamin
D deficiency (135).
• Among NHB women, studies associated urban residence with vitamin D deficiency, which may be related
to less outdoor activity and sun exposure, or more exposure to environmental pollutants that decrease the
skin’s synthesis of vitamin D (134).
Executive Summary Conclusion
We summarized important areas for future research in
areas of race/ethnic and sex disparities in endocrine disorders in Tables 10 and 11. Several themes emerged in the
statement, including a need for basic science and translational studies to explore underlying molecular mechanisms that may contribute to endocrine health disparities,
in addition to the need to explore the etiology in clinical,
population-based, and health services research studies.
Compared with NHW populations, NHB populations
have worse outcomes and higher mortality from certain
disorders despite having a lower (e.g. macrovascular complications of diabetes mellitus and osteoporotic fractures)
or similar (e.g. thyroid cancer) incidence of these disorders. This is likely related to inadequate access to highquality health care among minority populations. In contrast, NHBs with diabetic nephropathy have lower
mortality on dialysis than NHWs, despite a higher inci-
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
dence of ESRD. Understanding the factors contributing to
outcomes and survival will be beneficial in improving outcomes for all race/ethnic groups.
Obesity is an important contributor to diabetes risk in
minority populations and to sex disparities in thyroid cancer, suggesting that population interventions targeting
weight loss may favorably impact a number of endocrine
disorders. There are important implications regarding the
definition of obesity in different race/ethnic groups, including potential underestimation of disease risk in AsianAmericans and overestimation in NHB women. Ethnicspecific cut-points for central obesity should be
determined so that clinicians can adequately assess metabolic risk.
Sex disparities exist in certain endocrine disorders, with
autoimmune thyroid disease and cardiovascular complications of diabetes being more common in women than
men. The etiology of these sex differences remains unclear
and requires further investigation.
A major gap in our current understanding of race/ethnic disparities in endocrine disorders is a failure of most
studies to specify Hispanic-American and Asian-American subgroups. Where these data are available, clear ethnic-specific differences exist within Hispanic and Asian
subgroups, particularly related to diabetes and obesity
risk. In general, there are few data on endocrine disorders
in Native Americans and Alaska Natives.
There is little evidence that genetic differences contribute significantly to race/ethnic disparities in the endocrine
disorders examined, but significant heterogeneity and admixture among populations may mask genetic differences
in GWAS studies. The incorporation of ancestral markers
into future genetic studies will help to more specifically
address the contribution of race/ethnicity to disease risk.
More data are needed on race/ethnic differences in response to various treatments for endocrine disorders to
enable more patient-specific treatment regimens.
Our improved awareness and knowledge of interventions
regarding disparities in diabetes should be expanded to other
endocrine disorders for which disparities exist. Multilevel
interventions have reduced disparities in diabetes care, and
these successes can be modeled to design similar interventions for other endocrine diseases. Specifically, it is important
to study whether social determinants of disease contribute
significantly to disparities in vitamin D deficiency and poor
outcomes after thyroid cancer diagnosis and osteoporotic
fractures in minority populations.
Finally, increasing the representation of ethnic minorities in both the clinical and research sectors will help to
raise awareness and prioritize research funding and policy
development to reduce endocrine disparities.
J Clin Endocrinol Metab, September 2012, 97(9):i–xvii
jcem.endojournals.org
Acknowledgments
We thank Jose Florez, M.D., and James Meigs, M.D., MPH, for
assistance in identifying appropriate literature for the diabetes
genetics section. We thank Eric Vohr for his technical writing and
organization expertise in finalizing our statement. We thank Ivy
Garner and Claire Twose for their expertise in information management and referencing assistance. We thank The Endocrine
Society and Loretta Doan, Ph.D., for their support and guidance
in preparing this statement.
Address all correspondence and requests for reprints to: Dr.
Sherita Hill Golden, Johns Hopkins University School of Medicine, Division of Endocrinology and Metabolism, 1830 East
Monument Street, Suite 333, Baltimore, Maryland 21287.
E-mail: [email protected].
S.H.G. was supported by a Program Project Grant for the
Johns Hopkins Center to Eliminate Cardiovascular Health Disparities from the National Heart, Lung, and Blood Institute
(P50HL0105187). A.B. was supported by the National Center
for Research Resources (Grant UL1RR033176), which is now at
the National Center for Advancing Translational Sciences
(Grant UL1TR000124). M.H.C. is supported by a Midcareer
Investigator Award in Patient-Oriented Research (K24
DK071933) from the National Institute of Diabetes, Digestive
and Kidney Diseases (NIDDK) and the Chicago Center for Diabetes Translation Research (P30 DK092949). C.K. is supported
by Grants R01DK083297 and K23DK071552 through the
NIDDK. A.E.S. is supported by the intramural program of
NIDDK, National Institutes of Health (NIH).
The content is solely the responsibility of the authors and does
not necessarily represent the official views of the NIH.
Disclosure Summary: S.H.G., A.B., T.L.G.-W., C.K., A.E.S.,
and B.A. have nothing to declare. J.A.C. receives consultant honorarium from Merck and Company, Inc., and Novartis. M.H.C.
receives grant funding from Merck Company Foundation. J.A.S.
received honorarium from Veracyte for a one time visiting
speaker engagement.
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J C E M
S c i e n t i f i c
O N L I N E
S t a t e m e n t
Health Disparities in Endocrine Disorders: Biological,
Clinical, and Nonclinical Factors—An Endocrine
Society Scientific Statement
Sherita Hill Golden, Arleen Brown, Jane A. Cauley, Marshall H. Chin,
Tiffany L. Gary-Webb, Catherine Kim, Julie Ann Sosa, Anne E. Sumner, and Blair Anton*
Objective: The aim was to provide a scholarly review of the published literature on biological, clinical,
and nonclinical contributors to race/ethnic and sex disparities in endocrine disorders and to identify
current gaps in knowledge as a focus for future research needs.
Participants in Development of Scientific Statement: The Endocrine Society’s Scientific Statement
Task Force (SSTF) selected the leader of the statement development group (S.H.G.). She selected an
eight-member writing group with expertise in endocrinology and health disparities, which was approved by the Society. All discussions regarding the scientific statement content occurred via teleconference or written correspondence. No funding was provided to any expert or peer reviewer, and all
participants volunteered their time to prepare this Scientific Statement.
Evidence: The primary sources of data on global disease prevalence are from the World Health Organization. A comprehensive literature search of PubMed identified U.S. population-based studies. Search
strategies combining Medical Subject Headings terms and keyword terms and phrases defined two concepts: 1) racial, ethnic, and sex differences including specific populations; and 2) the specific endocrine
disorderorcondition.Thesearchidentifiedsystematicreviews,meta-analyses,largecohortandpopulationbased studies, and original studies focusing on the prevalence and determinants of disparities in endocrine
disorders.
Consensus Process: The writing group focused on population differences in the highly prevalent
endocrine diseases of type 2 diabetes mellitus and related conditions (prediabetes and diabetic complications), gestational diabetes, metabolic syndrome with a focus on obesity and dyslipidemia, thyroid
disorders, osteoporosis, and vitamin D deficiency. Authors reviewed and synthesized evidence in their
areas of expertise. The final statement incorporated responses to several levels of review: 1) comments
of the SSTF and the Advocacy and Public Outreach Core Committee; and 2) suggestions offered by the
Council and members of The Endocrine Society.
Conclusions: Several themes emerged in the statement, including a need for basic science, populationbased, translational and health services studies to explore underlying mechanisms contributing to endocrine health disparities. Compared to non-Hispanic whites, non-Hispanic blacks have worse outcomes and
highermortalityfromcertaindisordersdespitehavingalower(e.g.macrovascularcomplicationsofdiabetes
mellitus and osteoporotic fractures) or similar (e.g. thyroid cancer) incidence of these disorders. Obesity is
an important contributor to diabetes risk in minority populations and to sex disparities in thyroid cancer,
suggesting that population interventions targeting weight loss may favorably impact a number of endocrine disorders. There are important implications regarding the definition of obesity in different race/ethnic
groups, including potential underestimation of disease risk in Asian-Americans and overestimation in nonHispanic black women. Ethnic-specific cut-points for central obesity should be determined so that clinicians
can adequately assess metabolic risk. There is little evidence that genetic differences contribute significantly
to race/ethnic disparities in the endocrine disorders examined. Multilevel interventions have reduced disparities in diabetes care, and these successes can be modeled to design similar interventions for other
endocrine diseases. (J Clin Endocrinol Metab 97: E1579–E1639, 2012)
ISSN Print 0021-972X ISSN Online 1945-7197
Printed in U.S.A.
Copyright © 2012 by The Endocrine Society
doi: 10.1210/jc.2012-2043 Received April 23, 2012. Accepted June 6, 2012.
First Published Online June 22, 2012
* Author affiliations are shown at the bottom of the next page.
Abbreviations: BMD, Bone mineral density; BMI, body mass index; CI, confidence interval; CVD,
cardiovascular disease; DXA, dual-energy x-ray absorptiometry; ESRD, end-stage renal disease;
GDM, gestational diabetes mellitus; GWAS, genome-wide association study; HbA1c, glycosylated
hemoglobin; HDL-C, high-density lipoprotein cholesterol; HLA, human leukocyte antigen; HR, hazard ratio; IRR, incidence rate ratio; NHB, non-Hispanic black; NHW, non-Hispanic white; 25(OH)D,
25-hydroxyvitaminD;OR,oddsratio;RR,relativerisk;SMBG,self-monitoringofbloodglucose;SNP,
single nucleotide polymorphism; TG, triglyceride; VAT, visceral adipose tissue; WC, waist
circumference.
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Endocrine Health Disparities
ifferences in the incidence, prevalence, mortality, and
burden of diseases and other adverse health conditions among specific population groups exist throughout
the world, in developed and developing nations alike. Such
disparities in disease burden, comorbidities, and outcomes
are a feature of many of the world’s most prevalent disorders, including endocrine diseases. The underlying reasons for disparities vary depending on the condition in
question and on the geographical region in which the disparities are identified. Nonetheless, regardless of region,
there are a number of common factors contributing to
these disparities. The global nature of health disparities
makes this one of the most pressing issues facing science
and medicine today.
This Scientific Statement will focus on population
differences in adult endocrine disorders that, due to very
high prevalence, the medical community has identified
as significant public health burdens. These disorders
include diabetes mellitus and related conditions (prediabetes and diabetic complications), gestational diabetes, metabolic syndrome with a focus on obesity and
dyslipidemia, thyroid disorders, osteoporosis, and vitamin D deficiency (1). Because 95% of diabetes mellitus in
the United States is characterized as type 2 diabetes (2) and
type 2 diabetes presents a significant public health burden
with race/ethnic disparities, in this statement we focus on
type 2 diabetes.
Global prevalence data will be presented when it is
available, but a comprehensive focus on worldwide disparities in these endocrine disorders is beyond the scope of
this statement. Instead, we rely on information available
on population differences in endocrine diseases within the
United States. Nonetheless, global statistics on obesity will
be included, but discussion of obesity will be in the context
of type 2 diabetes and the metabolic syndrome. Health
disparities in hormone-sensitive cancers and pediatric endocrine disorders are also beyond the scope of this statement. We will also not address health disparities in pituitary and reproductive endocrine disorders and endocrine
hypertension because there are not yet sufficient population-based data to determine the presence of race/ethnic
differences (1). Essential hypertension is an enormous
public health concern; however, its management significantly overlaps with the fields of cardiology and nephrology. This statement will focus on disorders specifically
managed by endocrinologists.
D
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
Even as we address biological differences related to
race, ethnicity, or sex, we also discuss factors that contribute to health disparities and have been well documented for U.S. populations in reports from the Institute
of Medicine. The Institute of Medicine report “Unequal
Treatment” (3) published in 2002 remains the most comprehensive study of racial and ethnic disparities in health
care in the United States. The report examined issues related to the health system, the provider, and the patient
and assessed the extent of racial/ethnic differences in
health care. For the 10 yr since its publication, racial and
ethnic disparities in health and health care have persisted,
especially type 2 diabetes and related complications and
outcomes for thyroid cancers and metabolic bone disease.
Data suggest that racial and/or ethnic minorities in the
United States have less access to preventative care, treatment, and surgery, and as a result, they experience delayed
diagnoses and more advanced disease at presentation.
Combined, these factors contribute to disparate health
outcomes (4).
In this statement, we also examine the impact of sex on
endocrine disorders, particularly disorders that occur disproportionately in women (i.e. cardiovascular complications of diabetes, autoimmune thyroid disease, thyroid
cancer, and osteoporosis). As we do this, we will use the
term “sex” to describe health outcomes specific to being
male or female according to reproductive organs and chromosomal complement, as opposed to “gender,” which refers to a person’s self-representation as male or female (5).
An Institute of Medicine report published in 2001, entitled
“Exploring the Biological Contributions of Human
Health: Does Sex Matter?” (5) highlighted the effect sex
has on health care disparities. The report looked at the
importance of promoting research on sex at the cellular
level; determining how sex differences influence health,
illness, and longevity across the lifespan; considering sex as
a biological variable in all biomedical and health-related research; making sex-specific data more readily available; designing longitudinal studies so that sex-specific analyses can
be conducted; and reducing the potential for discrimination
based on sex difference (5).
Disparities due to income, education, geography, and
other measures of socioeconomic status that may influence access to care will be discussed, where relevant, because these vulnerabilities often co-occur, making it dif-
Department of Medicine (S.H.G.), Johns Hopkins University School of Medicine, Baltimore, Maryland 21287; Department of Epidemiology (S.H.G.), Johns Hopkins Bloomberg School of Public
Health, Baltimore, Maryland 21287; Welch Medical Library (B.A.), Johns Hopkins University, Baltimore, Maryland 21287; Geffen School of Medicine at the University of California, Los Angeles
(A.B.), Division of General Internal Medicine and Health Services Research, Los Angeles, California 90095; Department of Epidemiology (J.A.C.), University of Pittsburgh Graduate School of Public
Health, Pittsburgh, Pennsylvania 15213; Department of Medicine (M.H.C.), Chicago Center for Diabetes Translation Research, University of Chicago, Chicago, Illinois 60637; Department of
Epidemiology (T.L.G.-W.), Columbia University Mailman School of Public Health, New York, New York 10032; Departments of Medicine and Obstetrics and Gynecology (C.K.), University of
Michigan, Ann Arbor, Michigan 48105; Departments of Surgery (Endocrine Surgery and Surgical Oncology) and Medicine (Oncology) (J.A.S.), Yale University School of Medicine, New Haven,
Connecticut 06520; and Diabetes, Obesity and Endocrinology Branch (A.E.S.), National Institute of Diabetes, Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland 20827
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
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ficult to disentangle potential biological contributions
from other social influences on health disparities.
disparities in endocrine disorders. We limited all searches
to the English language.
Definitions of Race and Ethnicity
Diabetes Mellitus and Prediabetes
We use Williams’ definition of ethnicity as “a complex
multidimensional construct reflecting the confluence of
biological factors and geographical origins, culture, economic, political, and legal factors, as well as racism” (6).
The concepts of “race” and “ethnicity” play important
roles in understanding disparities in health and health care
and are essential to the rigorous monitoring of progress
toward eliminating these inequities (7, 8).
Overall, there was significant variation in the precise
terms used to define specific race/ethnic groups in the literature reviewed. For consistency, we have used the terms
“non-Hispanic black” to refer to individuals of African
descent born and/or residing in the United States; “nonHispanic white” for nonminority individuals; “HispanicAmerican” for individuals of Mexican, South American,
Cuban, or Puerto Rican descent born and/or residing in
the United States; “Asian-American” for individuals of
South Asian (e.g. Indian), East Asian (e.g. Japanese, Chinese, Korean), Southeast Asian (e.g. Cambodian, Vietnamese, Laotian, Thai), and Pacific Island (e.g. Filipino)
descent born and/or residing in the United States; and
“Native American” to refer to American Indians and
Alaska Natives. We recognize that these categories may be
arbitrary and sometimes contain heterogeneous groups.
We have indicated in the text when studies were more
specific in defining ethnic subgroups, particularly for
Asian and Hispanic individuals. We also recognize that
some individuals within every ethnic subgroup may be a
mixture of native born and foreign born.
Disparities by race/ethnicity
Literature Search Strategy
The primary sources of data on global disease prevalence
are from the World Health Organization (WHO). In addition, we conducted a comprehensive literature search of
PubMed to identify U.S. population-based studies. We
used a combination of Medical Subject Headings (controlled vocabulary) terms and keyword terms and phrases
to develop search strategies to define two concepts: the
first was a search filter, defining racial, ethnic, and sex
differences including specific populations; the second described a specific endocrine disorder or condition. We applied the filter to each separate disorder to optimize consistency. We identified systematic reviews, meta-analyses,
large cohort and population-based studies, and original
studies that focused on the prevalence and determinants of
Epidemiology
Diabetes mellitus. More than 346 million people worldwide have diabetes mellitus, and it is predicted to become
the seventh leading cause of death by the year 2030
(http://www.who.int/features/factfiles/diabetes/en/index.html).
A 2010 comparison of 223 countries by the WHO showed that
Nauru, the United Arab Emirates, and Saudi Arabia have the
highest prevalence of diabetes, whereas Mongolia,
Rwanda, and Iceland have the lowest (http://www.
allcountries.org/ranks/diabetes_prevalence_country_
ranks.html). Additional WHO analysis has shown that
prevalence rates are similar across income groupings
of countries (ranging from 8% in adults of both sexes
25 yr and older in the low-income countries to 10% in
the same demographic in the upper middle-income
countries) (http://www.who.int/nmh/publications/ncd_
report_chapter1.pdf), but death from diabetes is higher
in low- and middle-income countries, with roughly
80% of deaths from diabetes occurring in these countries (http://www.who.int/features/factfiles/diabetes/
en/index.html).
In the United States, roughly 25.8 million individuals
(8.3% of U.S. population) have diabetes mellitus (http://
www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf). Although
18.8 million are diagnosed, another 7 million remain
undiagnosed (http://www.cdc.gov/diabetes/pubs/pdf/ndfs_
2011.pdf). These undiagnosed individuals have an elevated
fasting plasma glucose but lack a prior physician diagnosis.
The prevalence of diagnosed diabetes in adults over 20 yr of
age (summarized in Table 1) is highest among non-Hispanic
blacks (NHBs) (12.6%), Mexican-Americans (13.3%),
Puerto Rican-Americans (13.8%), and Native Americans
(16.1%) (http://www.cdc.gov/diabetes/pubs/pdf/ndfs_
2011.pdf). The prevalence of diagnosed diabetes is similar
among non-Hispanic whites (NHWs), Asian-Americans,
Cuban-Americans, Central Americans, and South Americans. It is important to note that diabetes prevalence in
Hispanic-Americans is influenced by the country of origin
and primarily driven by the high prevalence in people of
Mexican and Puerto Rican descent. Similarly, diabetes
prevalence is lowest in Alaska Natives (5.5%) but very
high in Native Americans (approaching 33%) (http://
www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf). In the
National Health and Nutrition Examination Survey
(NHANES), over 40% of NHWs and Mexican-Ameri-
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Endocrine Health Disparities
TABLE 1. Age-adjusted prevalence of diagnosed
diabetes mellitus in the United States by race/ethnicity in
adults ⱖ20 yr of age
Race/ethnic group
NHWs
Asian-Americans
Hispanic-Americans overall
Cuban, Central, and South Americans
Mexican-Americans
Puerto Rican-Americans
NHBs
Native Americans and Alaska Natives
Age-adjusted
prevalence (%)
7.1
8.4
11.8
7.6
13.3
13.8
12.6
16.1
Reproduced from National diabetes fact sheet: national estimates and
general information on diabetes and prediabetes in the U.S., 2011.
U.S. Department of Health and Human Services, Centers for Disease
Control and Prevention, Atlanta, 2011 (12), with permission.
cans with diabetes were undiagnosed, whereas 24% of
NHBs were undiagnosed (13), suggesting race/ethnic bias
in diagnoses based on fasting glucose vs. known physician
diagnosis. Estimates based only on physician diagnosis
may underestimate diabetes in certain race/ethnic groups.
In addition, a recent study suggested that using glycosylated hemoglobin (HbA1c) to determine diabetes prevalence may lead to an underestimate in some race/ethnic
groups (14) and an overestimate in others (15) (see Glycemic Control section under Race/Ethnic Differences in
Biological Factors Contributing to Complications).
As of 2010, approximately 1.9 million individuals over
20 yr of age in the United States developed incident diabetes (12). Compared with NHWs, the risk of incident
diabetes was 18% higher in Asian-Americans, 66% higher
in Hispanic-Americans, and 77% higher in NHBs (12). A
significantly higher risk in Mexican-Americans (87%) and
Puerto Rican-Americans (94%) drove the higher risk
among Hispanic-Americans, compared with NHWs (12).
The risk of developing diabetes is similar in Cuban-Americans, Central Americans, and South Americans, compared with NHWs (12).
The National Health Interview Survey contains the
only estimates of the prevalence of type 2 diabetes in
Asian-Americans in the United States. It revealed that
there is significant ethnic variation in the prevalence of
type 2 diabetes, which is highest among Asian-Indians
(close to 15%) and Filipinos (close to 10%) and lowest and
among Koreans, Vietnamese, and Chinese (3–7%) in the
United States (16), consistent with the known higher diabetes prevalence in individuals living in India, South Asia,
and the Philippines (10).
Prediabetes. Prediabetes is an important risk factor for
developing type 2 diabetes and cardiovascular disease
(CVD). The age-adjusted prevalence of prediabetes in
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
adults 20 yr of age or older in 2005–2008 (based on fasting
glucose or HbA1c) was similar among NHWs, NHBs, and
Mexican-Americans, at approximately 35% (12). Based
on fasting glucose only, 20% of Native Americans 15 yr of
age or older had prediabetes in 2001–2004 (12).
The Diabetes Prevention Program enrolled approximately 3000 multiethnic individuals with impaired glucose tolerance diagnosed using a 75-g oral glucose tolerance test. In this important study, the risk of incident
diabetes (approximately 11%) was the same in NHBs,
Asian-Americans and Pacific Islanders, NHWs, HispanicAmericans, and Native Americans (17). These data suggest that once individuals progress from normal glucose
tolerance to impaired glucose tolerance, the risk for further progression to diabetes is the same across ethnic
groups. Thus, the progression from normal glucose tolerance to impaired glucose tolerance rather than from impaired glucose tolerance to diabetes appears to account for
race/ethnic differences in type 2 diabetes risk.
Race/ethnic differences in biological factors
Obesity and fat distribution. Obesity is one of the strongest risk factors for developing type 2 diabetes and is a
major, and growing, public health problem (2). In 2008
worldwide prevalence statistics, the WHO estimated that
500 million adults 20 and older were obese, a figure representing more than one in 10 individuals worldwide
(http://www.who.int/mediacentre/factsheets/fs311/en/).
The 2010 WHO prevalence data show the highest rates of
obesity in Nauru, Cook Islands, and Micronesia for men
aged 15 yr and older, and in Nauru, Tonga, and Micronesia among women of the same age (https://apps.
who.int/infobase/Comparisons.aspx?l⫽&NodeVal⫽
WGIE_BMI_5_cd.0704&). The United States ranked
fifth highest in male obesity, at 44.2%, and 12th in female
obesity (tied with Jamaica), at 48.3%.
In the United States, obesity prevalence varies by race/
ethnicity. Recent data from the 2009 –2010 NHANES
showed that the age-adjusted prevalence of obesity in adults
20 yr of age and older [body mass index (BMI) greater than
or equal to 30 kg/m2] was highest among NHBs (49.5%),
followed by Mexican-Americans (40.4%) and NHWs
(34.3%) (20). Of note, the prevalence of grade 2 (BMI of
at least 35 kg/m2) and grade 3 obesity (BMI greater than
or equal to 40 kg/m2) was highest among NHBs (26%
for grade 2, and 13.1% for grade 3), compared with
NHWs (14.4% for grade 2, and 5.7% for grade 3) and
Mexican-Americans (14.9% for grade 2, and 5.4% for
grade 3) (20). In general, as discussed below (see Race/
ethnic and sex differences in body fat distribution—
implications for defining metabolic syndrome section
under Metabolic Syndrome), NHB and Mexican-Amer-
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
TABLE 2. Age-adjusted prevalence of overweight and
obesity by Asian-American ethnicity from the National
Health Interview Survey (16)
Race/ethnic group
Chinese
Filipino
Asian Indian
Japanese
Vietnamese
Korean
Other Asian and Native
Hawaiian or other
Pacific Islander
Age-adjusted
overweight
prevalence (%)
21.8
33.0
34.4
25.9
19.1
27.3
29.2
Age-adjusted
obesity
prevalence (%)
4.2
14.1
6.0
8.7
5.3
2.8
12.5
ican women are more affected by obesity and have had a
greater rise in obesity prevalence over the last 12 yr than
NHB and Mexican-American men and NHW men and
women. Race/ethnic differences in obesity contribute to
the higher risk of type 2 diabetes in NHBs and MexicanAmericans; however, as discussed further below (see Race/
ethnic and sex differences in body fat distribution—implications for defining metabolic syndrome section under
Metabolic Syndrome), NHB women have greater sc fat
compared with visceral fat than NHW women at a given
BMI and waist circumference (WC) and may therefore
develop type 2 diabetes at a higher BMI than NHW
women. Although there are less data on Native Americans
and Alaska Natives, data from the 2007 National Health
Interview Survey showed that both groups have a higher
prevalence of obesity (33.2%) than their NHW counterparts (24.8%) (21), which likely contributes to their
higher risk of type 2 diabetes.
Among Asian-Americans, there is variation in the prevalence of overweight and obesity (Table 2). Although
Asian Indians in the United States have one of the highest
prevalence of type 2 diabetes, their prevalence of obesity
is only 6%; however, they have a 30 to 35% prevalence of
overweight. In contrast, Filipinos have a similarly high
prevalence of type 2 diabetes, and also have a high prevalence of obesity. Compared with Chinese and Vietnamese
individuals, Asian Indians and Filipinos in the United
States have the highest rates of overweight (BMI, 25 to
⬍30 kg/m2). These data suggest that body weight alone is
not the only contributor to increased diabetes risk in
Asian-Americans. Differences in body fat distribution are
important contributors to diabetes risk in Japanese-Americans, a well-studied Asian population. Despite a lower
average BMI in participants in the Japanese-American
Community Diabetes Study, compared with the overall
U.S. population, there was a higher incidence of type 2
diabetes in Japanese-Americans (16). This study linked
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larger visceral abdominal fat in this population with incident diabetes, independent of age, sex, and sc fat (16).
Similarly, visceral adiposity is an important determinant
of diabetes risk in Filipinos. In the University of San Diego
Filipino Health Study, Filipino women had more visceral
adipose at each level of WC and a higher prevalence of type
2 diabetes than NHWs (16).
Glucose metabolism and insulin resistance. The higher
prevalence of type 2 diabetes in minorities compared with
NHW populations is partially attributable to differences
in glucose metabolism and homeostasis (22), as summarized in Table 3. Compared with their NHW counterparts
and independent of adiposity, NHBs have greater hyperinsulinemia (23–25) and insulin resistance, assessed by the
iv glucose tolerance test (23, 26 –28), hyperglycemic
clamp (29), or homeostasis model assessment of insulin
resistance (30). The majority of studies that have assessed
a measure of ␤-cell function indicate that, compared with
NHWs, NHBs augment insulin secretion to compensate
for insulin resistance (23, 26 –31).
The majority of studies have shown that, compared
with NHWs, Hispanic-Americans of Mexican descent
also have greater hyperinsulinemia (23, 32) and insulin
resistance, as assessed by the iv glucose tolerance test (23),
hyperglycemic clamp (29), or homeostasis model assessment of insulin resistance (31), independent of adiposity.
Although most studies show increased ␤-cell insulin secretion (23, 29, 31), one study found no difference between the two race groups (33). Studies in non-Mexican
Hispanic-Americans have yielded conflicting results. A
study of Cuban-Americans showed a greater insulin response to an oral glucose tolerance test, compared with
NHWs, independent of percentage body fat (24); however, another study of non-Mexican Hispanic-Americans
showed no difference in insulin sensitivity or ␤-cell function between the two groups (30).
Few studies have been conducted in Asian-Americans and
Native Americans. With the exception of one study that
found lower insulin resistance (31), research has indicated
that Asian-Americans have greater insulin resistance than
NHWs, assessed by the hyperglycemic clamp (29) and homeostatic model assessment insulin sensitivity (30), after adjustment for adiposity. One study showed a compensatory
higher degree of ␤-cell insulin secretion (29); however, two
studies showed lower ␤-cell insulin secretion compared with
NHWs (30, 31). The reduced ␤-cell insulin response, in the
setting of insulin resistance, likely contributes to the increased risk of diabetes seen in Asian-Americans. Finally,
the Strong Heart Study assessed Native Americans using
the iv glucose tolerance test and compared their insulin
sensitivity to results from the Insulin Resistance Athero-
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TABLE 3. Features of glucose metabolism in minority populations relative to NHWs
Findings relative to
NHWs
First author, year
(Ref.)
NHBs
Haffner, 1996
(23)
Donahue, 1997
(24)
Chiu, 2001 (29)
Carnethon, 2002
(25)
Jensen, 2002
(31)
Torrens, 2004
(30)
Albu, 2005 (26)
Population
Method of assessing glucose
metabolism
IRAS; n ⫽ 288 NHBs, 435 NHWs
nondiabetic
Miami Community Health Study;
n ⫽ 159 NHBs, 207 NHWs
n ⫽ 28 NHBs, 45 NHWs
2-h OGTT; insulin-modified frequently
sampled iv glucose tolerance test
75-g OGTT (insulin area under the curve)
ARIC Study; n ⫽ 13,416 NHB and
NHW nondiabetic men and
women
First-degree relatives of
individuals with type 2 diabetes;
n ⫽ 55 NHBs, 217 NHWs
Fasting insulin
SWAN study; nondiabetic preand perimenopausal women;
n ⫽ 746 NHBs, 1,359 NHWs
n ⫽ 32 NHB women, 28 NHW
women
2-h OGTT; HOMA-IR estimated insulin
resistance; ratio of incremental insulin
to glucose responses over first 30
min (⌬I30/⌬G30)
HOMA %S (insulin sensitivity), HOMA %␤
(␤-cell function)
Intravenous glucose tolerance test
n ⫽ 55 NHBs, 85 NHWs; healthy,
obese nondiabetic individuals
Intravenous glucose tolerance test
Chow, 2011 (28)
n ⫽ 17 NHB women, 17 NHW
women; healthy, obese
Insulin-modified frequently sampled iv
glucose tolerance test
n ⫽ 464 Hispanic-Americans, 676
NHWs; normal glucose
tolerance
Fasting, 1-h and 2-h glucose insulin from
OGTT
Haffner, 1996
(23)
IRAS; n ⫽ 363 HispanicAmericans, 435 NHWs;
nondiabetic
2-h OGTT; insulin-modified frequently
sampled iv glucose tolerance test
Donahue, 1997
(24)
Miami Community Health Study;
n ⫽ 128 Cuban-Americans,
207 NHWs
n ⫽ 20 Mexican-Americans, 45
NHWs
First-degree relatives of
individuals with type 2 diabetes;
n ⫽ 193 Hispanic-American,
217 NHWs
n ⫽ 172 Mexican-Americans, 60
NHWs; NGT or diabetes
75-g OGTT (insulin area under the curve)
Chiu, 2001 (29)
Jensen, 2002
(31)
Ferrannini, 2003
(33)
Torrens, 2004
(30)
SWAN study; nondiabetic preand perimenopausal women;
n ⫽ 218 non-MexicanAmerican Latinos, 1,359 NHWs
2-h postload
glucose
Hyperglycemic clamp
Rasouli, 2007
(27)
Hispanic-Americans
Boyko, 1991 (32)
Fasting
glucose
Hyperglycemic clamp
2-h OGTT, HOMA-IR estimated insulin
resistance, ratio of incremental insulin
to glucose responses over first 30
min (⌬I30/⌬G30)
Insulin sensitivity of glucose uptake by
clamp technique; endogenous glucose
production by 3-关3H兴 glucose infusion;
insulin secretory response to oral
glucose
HOMA %S (insulin sensitivity); HOMA %␤
(␤-cell function)
(Continued)
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TABLE 3. Continued
Findings relative to
NHWs
Fasting
insulin
2-h
post-load
insulin
Insulin-mediated glucose
disposal or other measures
of insulin sensitivity
AIR or other
measure of
␤-cell function
1
1
2
1
Differences persisted after adjustment for obesity, body
fat distribution, and behavioral factors
Persisted after adjustment for percentage body fat
2
1
Persisted after adjustment for age, sex, BMI, WHR, and
blood pressure
Fasting insulin was significantly higher among
nonobese NHB compared to NHW women, but there
was no difference among men
Adjustment for HOMA-IR explained difference in AIR
between Hispanics and NHWs
1
1
1
1
1
1
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
1
2
No difference
No difference
No difference
Other
Difference in HOMA %S and HOMA %␤ persisted
after adjustment for WC, presence of IFG, TG, and
site
Difference in insulin sensitivity persisted after adjustment for
weight, height, and MRI-assessed intramuscular adipose
tissue, but was attenuated after adjustment for MRIassessed skeletal muscle volume. Differences in AIR
persisted after multivariable adjustment
NHBs also had higher disposition index but lower
maximum disposition index than age-, sex-, and
BMI-matched NHWs
NHB women had higher free fatty acid clearance after
adjusting for fat mass. Additional adjustment for AIR
attenuated the association
Differences in fasting, 1-h, and 2-h insulin persisted
after adjustment for age, sex, BMI, WHR, family
history of diabetes, and glucose. 1 Fasting and 1-h
and 2-h glucose-stimulated C-peptide and C-peptide:
insulin molar ratio greater in Hispanics than NHWs
Differences in 2-h insulin and AIR persisted after
adjustment for obesity, body fat distribution, and
behavioral factors, but differences in insulin
sensitivity index did not persist
Persisted after adjustment for percentage body fat
Persisted after adjustment for age, sex, BMI, WHR, and
blood pressure
Difference in insulin resistance persisted after
adjustment for BMI. Adjustment for HOMA-IR
explained difference in AIR between Hispanics and
NHWs
Persisted after adjustment for BMI, age, diabetes, and
family history of diabetes
Lack of difference in HOMA %S persisted after
adjustment for WC, presence of IFG, TG, and site
(Continued)
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TABLE 3. Continued
Findings relative to
NHWs
First author, year
(Ref.)
Asian-Americans and
Pacific Islanders
Chiu, 2001 (29)
Jensen, 2002 (31)
Torrens, 2004 (30)
Native Americans
Resnick, 2002 (34)
Method of assessing glucose
metabolism
Population
n ⫽ 28 Asian-Americans, 45
NHWs
First-degree relatives of
individuals with type 2 diabetes;
n ⫽ 66 Asian-Americans, 217
NHWs
Hyperglycemic clamp
SWAN study; nondiabetic pre- and
perimenopausal women; n ⫽ 210
Chinese-Americans, 255 JapaneseAmericans, 1,359 NHWs
HOMA %S (insulin sensitivity), HOMA %␤
(␤-cell function)
Strong Heart Study; n ⫽ 61
Native Americans (compared to
NHWs in IRAS)
Frequently sampled iv glucose tolerance
test
Fasting
glucose
2-h postload
glucose
2-h OGTT; HOMA-IR estimated insulin
resistance; ratio of incremental insulin
to glucose responses over first 30
min (⌬I30/⌬G30)
AIR, Acute insulin response; ARIC, Atherosclerosis Risk in Communities Study; HOMA-IR, homeostatic model assessment of insulin resistance; IFG,
impaired fasting glucose; IRAS, Insulin Resistance Atherosclerosis Study; MRI, magnetic resonance imaging; NGT, normal glucose tolerance; OGTT,
oral glucose tolerance test; SWAN, Study of Women Across the Nation; WHR, waist-hip ratio; 1, increased compared to NHWs; 2, decreased
compared to NHWs.
sclerosis Study of nondiabetic and diabetic NHWs, NHBs,
and Hispanic-Americans (34). For Native Americans, the
study showed reduced insulin sensitivity, relative to
NHWs, in those without diabetes and reduced insulin sensitivity, relative to NHWs, NHBs, and Hispanic-Americans, in those with diabetes (34). Similarly, a separate
study showed reduced insulin sensitivity for nondiabetic
Pima Indians relative to NHWs (35).
Although beyond the scope of this statement, there are
metabolic studies that have attempted to identify contributors to ethnic differences in insulin sensitivity by race/
ethnicity, many of which have focused on differences between NHB and NHW women. Studies have shown that,
compared with NHW women, NHB women who were fed
a high-fat diet failed to shift metabolism to increase fat
oxidation or decrease carbohydrate metabolism, despite
increases in their insulin levels (36). This “metabolic inflexibility” may contribute to their higher risk of obesity
and insulin resistance. Reduced fat oxidation can promote
accumulation of lipids in skeletal muscle and development
of insulin resistance (37). Compared with NHW women,
NHB women have reduced muscle oxidative capacity associated with insulin resistance, suggesting the presence of
skeletal muscle mitochondrial dysfunction as a potential
contributor to insulin resistance (38, 39). A recent study
suggested that lower levels of 25-hydroxyvitamin D in
NHBs, compared with NHWs, explained differences in
insulin sensitivity between the two races. Whether these
hypothesized mechanisms are operative in other race/ethnic groups requires further research in clinical and population-based studies.
Genetics. Recent reviews have chronicled the ongoing
evolution of research on susceptibility genes for type 2
diabetes. Association studies initially revealed susceptibility genes in common coding variants in PPARG and
KCNJ11; however, genome-wide association studies
(GWAS) (the current systematic approach to identifying
type 2 diabetes susceptibility genes) have been most successful (40). Table 4 summarizes results of studies that
have linked gene variants with 15–20% increased risk
of diabetes along with their proposed pathways (40). In
2010, there were approximately 40 confirmed loci for
which variants increase risk of type 2 diabetes (40). The
GWAS Catalog of the National Human Genome Research Institute (www.genome.gov) summarizes currently identified loci and their nearby genes.
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
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TABLE 3. Continued
Findings relative to
NHWs
Fasting
insulin
2-h
post-load
insulin
Insulin-mediated glucose
disposal or other measures
of insulin sensitivity
AIR or other
measure of
␤-cell function
2
1
1
2
2
2
2
Although most of the early studies focused on individuals of European descent, several recent studies have demonstrated that these susceptibility loci are also present and
associated with increased type 2 diabetes risk in ethnic
minority populations. To date, the limited amount of data
in non-European ancestry populations does not suggest
that the genetic architecture of type 2 diabetes differs
across race/ethnic groups. Two large GWAS analyses in
multiethnic populations have found that common variants discovered in European populations are also significantly associated with type 2 diabetes in ethnic minorities
(41). In one study, 14 of 19 allelic variants, reproducibly
associated with type 2 diabetes in European populations,
had a significant link to type 2 diabetes in NHBs, Hispanic-Americans, Japanese-Americans, and Native Hawaiians (41). The other study (which pooled data from 39
multiethnic population-based studies, case-control
studies, and clinical trials) showed a significant link
between a composite genetic score of single nucleotide
polymorphisms (SNP) from new and established type 2
diabetes signals and diabetes risk in NHB, HispanicAmerican, and Asian-American populations (42). A
study in NHANES III (examining 16 novel fasting glucose-associated SNP in multiple genes in NHWs, Mexican-Americans, and NHBs) showed that whereas allele
Other
Persisted after adjustment for age, sex, BMI, WHR, and
blood pressure
Less insulin resistance for Asian-Americans compared
to NHWs and other ethnic groups (NHB, HispanicAmerican); persisted after adjustment for BMI. AIR
was lower in Asian-Americans compared to other
ethnic groups but was attenuated after adjustment
for HOMA-IR
Difference in HOMA %S persisted after adjustment for
WC, presence of IFG, and site, but was attenuated
after adjustment for TG. Differences in HOMA %␤
persisted after multivariable adjustment
Mean insulin sensitivity index of nondiabetic Native
Americans was lower than that of nondiabetic
counterparts in IRAS (with exception of some
Hispanic-Americans). The insulin sensitivity index of
diabetic Native Americans was lower than that of all
diabetic IRAS participants
frequency varied by race/ethnicity, there was a significant link between a weighted genetic score and increased fasting glucose and odds for impaired fasting
glucose in all ethnicities (43). Together, these data suggest that common genetic variants contribute similarly
to diabetes risk across race/ethnicities.
Until recently, there were no GWAS analyses in nonEuropean populations; however, several studies have
identified novel diabetes-associated SNP in specific race/
ethnic groups (Table 5). In a study of individuals from
Mexico City and Mexican-Americans from Texas, there
were signals for type 2 diabetes corresponding to previously described regions; however, the study identified additional loci that were not replicated in the Diabetes Genetics Replication and Meta-Analysis Consortium,
suggesting novel loci that may be linked to type 2 diabetes
risk in Hispanic populations (44). As summarized in Table
4, recent GWAS analyses in South Asians, East Asians, and
NHBs have identified new loci linked with type 2 diabetes
in those race/ethnic groups (45– 47).
Individual race/ethnic differences in nonbiological
factors
Acculturation. Acculturation is “the process by which immigrants adopt the attitudes, values, customs, beliefs, and
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Endocrine Health Disparities
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TABLE 4. Genes with GWAS-identified genetic loci
associated with insulin secretion and resistance and
conferring a 15–20% increased risk of type 2 diabetes
Genes
Genes associated with reduced
insulin secretion
Reduced ␤-cell mass
␤-cell dysfunction
Genes associated with insulin
resistance
Obesity
Insulin resistance unrelated
to obesity
CDKAL1, CDKN2A, CDKN2B
MTNR1B, TCF7L2, KCNJ11
FTO
IRS1, PPARG
behaviors of a new culture” and contributes to health behaviors, obesity, and type 2 diabetes in immigrant populations (48). In Hispanic-American immigrants, studies
have linked acculturation with a change in lifestyle
choices, including poorer nutrition and more tobacco use.
However, studies have also linked acculturation with a
higher socioeconomic position, more access to health care,
and more leisure-time physical activity, which may have
differential effects on health outcomes (48). Studies have
shown that acculturation in Hispanic-American immigrants results in an increase in dietary habits that promote
obesity, such as a higher consumption of sugar and sugar-
sweetened beverages, higher solid fat intake, higher sugar
intake, more eating out, and more fast food consumption.
Studies have also shown higher sodium intake, higher salty
snack consumption, and a lower fruit and vegetable intake
(48). A study comparing obesity trends in U.S.-born vs.
immigrant Hispanic-Americans in NHANES showed that
from 1995 to 2005, obesity rates increased significantly
more in age-matched U.S.-born individuals relative to immigrants (49). The association of acculturation with type
2 diabetes, however, is mixed and inconsistent. Although
acculturation appears to promote obesity, its association
with diabetes may be offset by its positive influence on
physical activity and access to care, in that screening and
intervention occur sooner (48). The Multi-Ethnic Study of
Atherosclerosis links greater acculturation with a higher
prevalence of diabetes among non-Mexican-origin Hispanic-Americans, but not among Mexican-origin Hispanic-Americans (50). The association in non-Mexican-origin
Hispanic-Americans was independent of socioeconomic
status and partially attenuated with adjustment for BMI
and diet (50).
Acculturation and the duration of time in the United
States might also influence the degree of obesity in Asian
immigrants. Japanese individuals genetically predisposed
to diabetes have a higher rate of incident diabetes in an
TABLE 5. Novel GWAS-identified loci associated with type 2 diabetes in non-European populations
Population
South Asians (45)
East Asians (46)
Loci with strong associations
Loci with moderate associations
NHBs (47)
Loci with strong associations
Loci with nominal associations
Newly
Associated
identified SNP Chromosome
gene(s)
rs3923113
2
GRB14
rs16861329
3
ST6GAL1
VPS26A
HMC20A
AP3S2
HNF4A
Associated physiological
function
Associated with insulin sensitivity
Associated with pancreatic ␤-cell
function
rs1802295
rs7178572
rs2028299
rs4812829
10
15
15
20
rs6815464
rs7041847
4
9
rs6017317
rs6467136
rs831581
rs9470794
rs3786897
rs1535500
20
7
3
6
19
6
rs16955379
rs17797882
16
16
FITM2-R3HDML-HNF4A
GCC1-PAX4
PSMD6
ZFAND3
PEPD
KCNK16
May regulate glucose-independent
insulin secretion in the pancreas
CMIP
WWOX
Rs7560163
Rs7542900
Rs4659485
Rs2722769
Rs7107217
2
1
2
11
11
RBM43, RND3
SLC44A3, F3
RYR2, MTR
GALNTL4, LOC729013
TMEM45B, BARX2
MAEA
GLIS3
Associated with pancreatic ␤-cell
function
Associated with pancreatic ␤-cell
development, insulin gene
expression, and glucose
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obesity-promoting environment. This is evidenced by Japanese immigrants to the United States having a 3-fold
higher rate of type 2 diabetes compared with their native
Japanese counterparts (22). The Multi-Ethnic Study of
Atherosclerosis, however, did not link acculturation with
type 2 diabetes prevalence in Chinese-Americans (50). The
role of acculturation in the development of obesity and
type 2 diabetes in other Asian-American subgroups is
unclear.
Health behaviors. Physical activity is an important intervention for reducing diabetes risk in all race/ethnic groups
(17). NHBs, Native Americans, and Alaska Natives report
less leisure-time physical activity than NHWs (51). Mexican-American women report less leisure-time physical activity than NHW and NHB women (51). Thus, lower levels of physical activity in ethnic minority populations is an
important contributor to their elevated risk of obesity and
subsequent diabetes. There are sparse data currently on
physical activity in Asian-American populations (16).
Smoking is a risk factor for development of type 2 diabetes (52). Native Americans and Alaska Natives have a
higher prevalence of smoking that NHWs (51). NHBs and
NHWs have similar smoking rates, whereas MexicanAmericans have significantly lower smoking rates. Thus,
higher rates of smoking may contribute to the elevated
diabetes risk seen in Native American populations. In
Asian-Americans, there is variation in rates of smoking,
with the highest prevalence among Korean men and the
lowest prevalence among Asian Indian men (16). It is unclear whether smoking contributes to diabetes risk in other
Asian-American subgroups.
Interface of environmental and clinical/biological
factors: epigenetics and early life events
As recently reviewed (53), early life conditions, such as
prenatal undernutrition and stress, maternal stress, or maternal obesity during pregnancy, can modify the developmental biology in offspring, leading to a future increased
risk of developing obesity and type 2 diabetes. Overweight
and diabetic women give birth to overweight, diabetesprone offspring, likely through intrauterine influences on
development, which might explain higher rates of diabetes
in South Asian and Native American populations (53);
however, additional work, summarized below, has shown
low birth weight to be strongly associated with type 2
diabetes risk.
NHBs have lower birth weight than NHWs, which
may be related to maternal conditions during pregnancy, including stressful life events, depressive and
anxiety symptoms, economic inequality (e.g. lower income and education, less access to health care in NHBs),
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racial discrimination, residential segregation, and
neighborhood-level poverty (53). Maternal hypertension, which is more prevalent in NHB women, can also
lead to low birth weight (53). Low birth weight seems
to be unique to NHBs because infants born to women of
other minority races/ethnicities in similar socioeconomic circumstances are not small compared with
NHWs (54).
In response to undernutrition, researchers believe that
the fetus will slow its growth rate and modify the structure
and function of organs and systems involved in metabolism, leading to metabolic dysfunction after birth (53).
Animal studies have shown that restricting nutritional intake in pregnant rats, mice, or sheep or directly restricting
blood flow to the fetus increases offspring blood pressure,
cholesterol, abdominal fat deposition, and diabetes risk
(53). Human studies have demonstrated similar findings,
linking smaller birth weight to insulin resistance and diabetes, abdominal pattern of fat distribution, higher blood
pressure, abnormal lipid profiles, and increased CVD risk
(53). Studies have also linked low birth weight with elevated cortisol reactivity in childhood and adolescence
(53). And chronic cortisol exposure can contribute to abdominal adiposity and insulin resistance (55).
Maternal psychological stress and fetal overexposure
to cortisol lead to the same metabolic abnormalities as
fetal undernutrition (53). Under normal conditions,
placental 11-␤ hydroxysteroid dehydrogenase protects
the fetus from maternal cortisol by converting cortisol
to inactive cortisone. However, in a severely stressed
mother, excessive stress hormones can reduce the effectiveness of this protection, exposing the fetus to maternal cortisol (53). This can lead to offspring with elevated blood pressure, stress reactivity, abdominal
adiposity, insulin resistance, and other diabetes and
CVD precursors (53).
Epigenetic changes in the pattern of cellular gene expression may influence how a fetus adapts to an adverse
intrauterine environment (53). Epigenetic changes are
those that “modify patterns of gene expression without
changing the nucleotide sequence of its DNA” and may
represent an adaptation to a significant prior stressor (53).
Restricting the protein intake of pregnant rats resulted in
decreased methylation of the promoter region of the glucocorticoid receptor in offspring liver cells, increased glucocorticoid gene expression, and increased hepatic glucocorticoid receptor expression. As a result, these offspring
had a heightened hepatic response to stress hormones,
causing increased gluconeogenesis in response to stress
(53). The same model saw a decrease in methylation of
the angiotensinogen receptor gene in the offspring adrenal glands, leading to increased systolic blood pres-
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Endocrine Health Disparities
sure (53). In human studies of holocaust survivors with
posttraumatic stress disorders, their disease severity
predicts the pattern of cortisol secretion in their offspring. Similarly, the offspring of women who were
pregnant in Manhattan on September 11, 2001, show
altered hypothalamic-pituitary-adrenal axis activity in
childhood (53). In the future, studies in humans that
examine genetic methylation patterns will help us determine how epigenetic changes contribute to the role of
the fetal environment in race/ethnic differences in future
risk of obesity and type 2 diabetes (56).
Summary, implications, and future research needs
The literature shows that insulin resistance is a key
contributor to type 2 diabetes risk in NHB, MexicanAmerican, Asian-American, and Native American populations, indicating that diabetes prevention and treatment strategies should focus on improving insulin
sensitivity. Basic science studies are needed to determine
whether race/ethnic differences in insulin signaling contribute to the lower insulin sensitivity in minority populations. Because studies suggest that Asian-Americans
have reduced ␤-cell function, this represents an additional prevention and treatment target for this population. The reduced ␤-cell function in Asian-Americans
may also explain why they are at high risk for diabetes
at lower levels of BMI (30). Finally, the available literature suggests that there may be differences in glucose
metabolic features among Hispanic-Americans from
different countries of origin. This may explain the
higher prevalence of type 2 diabetes in Mexican-Americans compared with those of Cuban-American and
South American descent; however, because few studies
have included non-Mexican Hispanic-American populations or specified the countries of origin, additional
research is needed to further evaluate the presence of
and contributors to these metabolic differences.
Genetic studies suggest that susceptibility loci for
type 2 diabetes discovered in European populations are
also operative in ethnic minority populations and that
race/ethnic differences are unlikely to be explained by
genetic variation; however, recent GWAS analyses have
revealed potential ethnic-specific loci. Future GWAS
analyses should include Native American, HispanicAmerican, and NHB populations. Also, because genetic
admixture may mask differences attributable to race/
ethnicity, future genetic studies should also use ancestral markers to account for admixture. Nonclinical factors, such as acculturation and health behaviors, also
appear to be important contributors to obesity and diabetes risk in ethnic minority populations and warrant
further study because they may be targets for future
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
preventive interventions. Finally, low birth weight, fetal
undernutrition, and maternal-fetal stress appear to be
unique contributors to elevated diabetes and metabolic
risk in NHBs and represent a potential early target for
diabetes preventive interventions.
Disparities by sex
The prevalence of diabetes mellitus has increased over
the past decade in both women and men (57). Factors that
have driven this trend include increasing obesity [affecting
53% of the diabetic population in 2007 (58)] and sedentary lifestyle [affecting 33% of the diabetic population in
2007 (59)]. In 2009, 6.6% of men had diabetes compared
with 5.9% of women (57), with a similar median age of
onset of 60 to 70 yr. However, diabetes most commonly
affects NHB women (60). We have already reviewed disparities by race/ethnicity.
Complications of Diabetes Mellitus
Disparities by race/ethnicity
Microvascular complications
Epidemiology.
Retinopathy. Ethnic minority populations are more likely
than NHWs to experience diabetic retinopathy and visual
impairment. The presence of any diabetic retinopathy is
46% higher in NHBs and 84% higher in Mexican-Americans, compared with NHWs. NHBs and Mexican-Americans are also more likely to have moderate to severe retinopathy (61). Compared with NHWs, the risk of visual
impairment secondary to retinopathy is 4-fold higher in
NHBs; and Hispanic-Americans have higher rates of severe vision-threatening diabetic retinopathy than NHWs
(62). Although both of these populations have high rates
of diabetic retinopathy, there is some suggestion that the
phenotype of disease may be different in NHBs and Hispanic-Americans. In one study, both groups had a similar
prevalence of clinically significant macular edema and diabetic retinopathy grades; however, Hispanic-Americans
had more prevalent intraretinal hemorrhages involving a
greater area of the retina (63). Studies are inconsistent in
determining whether the observed differences between
NHBs and Hispanic-Americans, and NHWs can be explained by ethnic differences in risk factors such as diabetes duration, glycemic control, blood pressure, socioeconomic status, access to care, and health behaviors (64).
Although fewer studies have been conducted in Native
Americans, the Strong Heart Study showed a high
(45.3%) prevalence of retinopathy among diabetic Native
American individuals, indicating a similar or higher prevalence than in non-Native American populations (65).
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
Nephropathy. Although the incidence of end-stage renal
disease (ESRD) secondary to diabetes has declined or remained stable in most race/ethnic groups in the United
States over the last 15 yr (66), ESRD continues to disproportionately affect minority populations. Data from the
U.S. Renal Data System show that, compared with
NHWs, age- and sex-adjusted incidence of ESRD secondary to diabetes is 3.8 times higher for NHBs, 3.5 times
higher for Native Americans, and 1.5 times higher for
Asian-Americans (67). The higher risk in Asian-Americans occurs over the age of 45 yr, whereas among the other
race/ethnic groups the risk is higher compared with
NHWs across all age groups (67). The difference in ESRD
rates between NHB and Native American diabetic
women, and nondiabetic NHW women, was greater than
a similar comparison between men in these groups (67).
Among Native Americans with type 2 diabetes, incident
nephropathy and progression to ESRD are greater when
compared with NHWs (67). The incidence of ESRD is also
higher in Hispanic-Americans than in NHWs (67). Despite the higher incidence and prevalence of ESRD in
NHBs, they surprisingly have lower mortality on dialysis
compared with NHWs (22).
Neuropathy. One prior comprehensive review did not find
significant differences in the prevalence of neuropathy in
NHBs and Hispanic-Americans compared with NHWs
(64). This literature, however, is hampered by varying definitions of neuropathy and cultural and language barriers
that can affect interpretation of the tests (68). We sum-
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marized the estimated prevalence of diabetic neuropathy
by race/ethnic group in Table 6. Among Native Americans, there are regional differences in prevalence, with the
highest rates being in those from Arizona (68). In the San
Luis Valley Diabetes Study, Hispanic-Americans had a
nonsignificantly lower rate of neuropathy than NHWs,
although the incidence of neuropathy was similar among
the two groups (68). In the National Health Interview
Survey, rates were similar among all three race/ethnic
groups (Table 6), although there was a nonsignificant
trend for Mexican-Americans and NHBs to have a higher
prevalence with a diabetes duration greater than or equal
to 15 yr (68). In the Appropriate Blood Pressure Control
in Diabetes trial, sensorimotor neuropathy prevalence was
higher in NHWs than Hispanic-Americans and NHBs;
however, autonomic neuropathy was slightly higher in
Hispanic-Americans (68).
Macrovascular complications
Epidemiology.
Cardiovascular disease (coronary heart disease, stroke,
and congestive heart failure). In 2009, there was no significant difference in the age-adjusted prevalence of coronary
heart disease or stroke between NHBs (34.4%) and NHWs
(33.6%) who were over the age of 35 yr (66) and had diabetes
mellitus. Compared with NHWs, however, Hispanic-Americans had the lowest prevalence of CVD (26.6%), and that
trend has been present from 1997 through 2009 (66). In a
comprehensive review, after adjustment for multiple confounders and CVD risk factors, Asian-Americans, Hispanic-
TABLE 6. Prevalence of diabetic neuropathy by race/ethnicity (68)
Population
Native Americans: Hopi
and Navajo Indians
Study
Native Americans
Arizona
Oklahoma
Dakotas
Hispanic Americans
Strong Heart Study
Mexican Americans, NHBs
and NHWs
Hispanic-Americans
National Health
Interview Survey
ABCD Trial
San Luis Valley Diabetes
Study
Neuropathy assessment
Subjective symptoms, absent deep
tendon reflexes, decreased sensory
perception
Monofilament testing (5 of 10 areas
incorrect)
Symptoms, absent knee or ankle deep
tendon reflexes, absent sensation to
iced tuning fork
Questionnaire
Neurological symptom score,
neurological disability score,
autonomic function testing, and
quantitative testing of vibration and
thermal perception
NHBs
NHWs
ABCD, Appropriate blood pressure control in non-insulin-dependent diabetes mellitus.
Prevalence
12%
22%
8%
9%
23.3/100 persons (vs. 31.6/100
persons in NHWs)
⬃25% in all groups
35% (sensorimotor neuropathy);
51% (autonomic neuropathy)
37% (sensorimotor neuropathy);
45% (autonomic neuropathy)
47% (sensorimotor neuropathy);
44% (autonomic neuropathy)
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Endocrine Health Disparities
Americans, and NHBs had a lower risk of CVD than NHWs
(64). Despite their lower rate of disease, however, NHBs with
diabetes have a higher CVD mortality rate (22), and Hispanic-Americans with diabetes and hyperglycemia have
higher mortality after acute stroke (69). We were unable to
identify good population-based data on CVD outcomes in
Native Americans with diabetes. Overall, Native Americans
have a 2-fold greater likelihood of coronary heart disease
compared with NHWs (70).
Peripheral arterial disease/amputations. Certain ethnic
minorities with diabetes suffer from a higher burden of
lower extremity amputations than NHWs, although one
study found that race/ethnicity did not predict lower extremity amputation (71). Because the prevalence of neuropathy is similar among race/ethnic groups, we can assume that the higher rates of amputation are secondary to
peripheral arterial disease; however, many studies do not
make this distinction (72). In a comprehensive review,
NHBs had higher rates of lower extremity amputation
than NHWs; however, several studies pointed to differences in risk factors as the reason for this outcome (64).
Native Americans also had a higher risk of lower extremity
amputation than NHWs; this disparity persisted despite
an adjustment for risk factors (64). In contrast, compared
with NHWs, Asian-Americans had a lower risk of amputation in multivariable models (64). Data in HispanicAmericans are mixed, with some studies showing an increased risk, some showing a lower risk, and others
indicating no difference when compared with NHWs (64).
Mortality
According to data from the Centers for Disease Control, NHBs, Native Americans and Alaska Natives, and
Hispanic-Americans are 2.3, 1.9, and 1.5 times more
likely to die from diabetes than NHWs (70). And whereas
Asian-Americans overall are 20% less likely to die from
diabetes than NHWs, there are variations among subgroups. Native Hawaiians and Filipinos living in Hawaii
are 5.7 and 3.0 times more likely to die from diabetes than
NHWs living in Hawaii (70).
Race/ethnic differences in biological factors
contributing to complications
Glycemic control. Hyperglycemia is an important, modifiable risk factor in preventing all diabetic microvascular
complications (73, 74). Several systematic reviews and
meta-analyses have shown that ethnic minorities with type
2 diabetes have worse glycemic control than NHWs,
which likely contributes to the higher risk of microvascular complications seen in these populations. In one review
of 21 studies, three studies showed a mean HbA1c or gly-
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
cated hemoglobin at least 1% higher among diabetic ethnic minorities than diabetic NHWs, and all but two studies
showed a significantly higher HbA1c in diabetic ethnic minorities (75). Compared with diabetic NHWs, the HbA1c
in diabetic NHBs was approximately 0.6% higher (76),
and in diabetic Hispanic-Americans it was approximately
0.5% higher (77). The proportion of diabetic ethnic minorities with poor glycemic control, defined as glycemia
above a specific threshold, was significantly higher among
NHBs, Hispanic-Americans, Native Americans, and
Asian-Americans and Pacific Islanders (75).
Treatment is also an important contributor to HbA1c
levels. A recent study showed that intensive insulin therapy using three daily injections resulted in comparable
HbA1c outcomes across race/ethnicity (NHWs, NHBs,
Hispanic-Americans, and Asian-Americans), although
Asian-Americans and Hispanic-Americans required
higher weight-adjusted insulin doses (78). A study assessing the willingness of patients with type 2 diabetes
on oral agents to initiate insulin therapy found that minorities were less willing to initiate insulin therapy compared with NHWs, a concept coined as “psychological
insulin resistance” (79). We summarize several other factors related to health care access and delivery that may
contribute to race/ethnic disparities in glycemic control in
diabetes in the Conceptual Framework for Health and
Health Care Disparities section.
Although discussed more in the context of using HbA1c
as a diagnostic criterion in nondiabetic individuals, recent
studies have suggested that nonglycemic factors may contribute to the higher HbA1c at similar levels of fasting glucose seen in NHBs, Hispanic-Americans, Asian-Americans, and Native Americans, compared with NHWs (15).
Suggested factors include variations in erythrocyte membrane permeability to glucose, regulation of glucose transport across the erythrocyte membrane, glycolytic rates,
differences in nonenzymatic glycosylation reactions, and
deglycation (15). Although genetic factors may contribute
to race/ethnic differences in HbA1c levels, the Atherosclerosis Risk in Communities Study showed that for NHBs
the percentage of European ancestry explained less than
1% of the variance in HbA1c, and socioeconomic factors,
and metabolic factors (including fasting glucose) accounted for a significantly larger percentage of the variance (80).
Two recent studies have examined the effect glycemia
has on HbA1c differences in NHBs and NHWs with diabetes (81, 82). In one study, using data from NHANES III
and the Screening for Impaired Glucose Tolerance Studies,
NHBs with diabetes had significantly higher HbA1c than
NHWs with diabetes, which persisted after adjustment for
plasma glucose and other factors that correlate with
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
HbA1c. This result challenged whether HbA1c should be
used to indicate risk for complications, measure quality of
care, and evaluate disparities in health (81). A subsequent
study, using data from the Atherosclerosis Risk in Communities Study, however, came up with a different conclusion and supports HbA1c as an indicator of significantly
higher levels of glycemia in minority populations (82).
This study attributed the higher HbA1c in NHBs with diabetes (compared with NHWs with diabetes) to higher
fasting glucose and other covariates (82). In addition, nontraditional glycemic markers, glycated albumin and fructosamine, which are not subject to the effects of erythrocyte turnover and hemoglobin glycation, were also
significantly elevated in NHBs with diabetes, compared
with NHWs with diabetes (82). Thus, these data support
more hyperglycemia in NHBs with diabetes. In individuals
with diabetes, true differences in glycemia are likely much
more relevant than glucose-independent mechanisms in
explaining HbA1c variations (83). Also, the fact that HbA1c
is similarly associated with prevalence and risk of microvascular and macrovascular complications, and mortality,
among NHBs and NHWs with diabetes (84 – 86) lends
credence to true differences in glycemia between the two
race/ethnic groups. Because conflicting evidence is evolving about the contribution of nonglycemic factors to
HbA1c levels in minorities with diabetes, caution should be
used in applying HbA1c as the only measure to assess either
diabetes diagnosis or management.
Cardiovascular risk factors.
Blood pressure. Hypertension is an important risk factor
for diabetic nephropathy/ESRD and peripheral arterial
disease, and likely contributes to the higher prevalence of
these complications in certain ethnic groups. NHBs have
a higher prevalence of hypertension than NHWs (51). And
Mexican-American women have a higher prevalence of
hypertension than NHW women; however, the prevalence
of hypertension is similar among men in the two race/
ethnic groups (51). In general, Native Americans and
Alaska Natives have a lower prevalence of hypertension
compared with NHWs and NHBs; however, there are regional differences, with Native Americans in Montana
having a higher hypertension prevalence than non-Native
American groups in Montana (51).
A previous systematic review assessed control of CVD risk
factors, specifically among U.S. adults with type 2 diabetes,
and found disparities by race/ethnicity (75). Ten studies
showed significant blood pressure differences between ethnic
minorities and NHWs, with NHBs having higher systolic
and diastolic blood pressure and a higher percentage of
individuals with hypertension (75). The average blood
pressure exceeded the recommended target of 130/80
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mm Hg for all ethnic groups in most instances, and the
percentage of individuals with inadequate blood pressure
control (⬎140/90 mm Hg) was higher in NHBs and Hispanic-Americans than NHWs (75). Unfortunately, NHBs
and Hispanic-Americans with type 2 diabetes are less likely
to have their blood pressure checked, which is a missed opportunity for preventive intervention (67). Studies of blood
pressure control and hypertension prevalence comparing
NHWs to Native Americans and Asian-Americans with diabetes are lacking. Research to date from clinical trials indicates
that control of reversible risk factors, including hypertension, is
equally effective in lowering the risk of nephropathy and CVD
in minority and NHW populations (87).
Lipids. In a prior systematic review comparing low-density lipoprotein cholesterol between minority populations
and NHWs with type 2 diabetes, only two studies showed
ethnic differences, with Hispanic-Americans having
slightly lower low-density lipoprotein cholesterol than
NHBs and NHWs. Overall, low-density lipoprotein cholesterol control was moderate to poor in all race/ethnic
groups. In this review, there were no studies comparing
lipid control in NHWs with Native Americans and AsianAmericans with type 2 diabetes (67). As summarized in
Metabolic Syndrome, NHBs have lower triglycerides (TG)
than NHWs (88), which may explain their lower risk of
macrovascular disease; however, they generally have a
higher prevalence of low high-density lipoprotein cholesterol, a strong CVD risk factor (88).
Genetics. As noted in the prior section on genetics and type
2 diabetes risk, few GWAS analyses have been performed in
ethnic minority populations. A GWAS for diabetic nephropathy genes in NHBs identified several candidate genes, including RPS 12, LIMK2, and SFI1 (89). A GWAS for diabetic
nephropathy in Japanese individuals with type 2 diabetes
identified the SLC12A3 and engulfment and cell motility 1
genes as candidate genes for susceptibility to diabetic nephropathy in this population (90). We are unaware of GWAS
for other diabetic complications in ethnic minority populations. Therefore, this is a potential area for future research.
Epigenetics. Just as studies have linked low birth weight
with an increased risk of type 2 diabetes and hypertension
in adulthood (67), they have also suggested that it is a
potential contributor to diabetic nephropathy. NHBs
have lower birth weight than NHWs, likely due to environmental and behavioral factors discussed previously
(53). Animal studies have associated low birth weight with
postpartum alterations in the anatomical structure and
function of the kidneys and pancreas, which can predispose to renal damage (67). And human studies have as-
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Endocrine Health Disparities
sociated low birth weight with increased odds of ESRD
(67). This increased risk of kidney disease may be due to
the smaller and reduced number of nephrons present in the
kidneys of prenatally undernourished individuals (53).
Individual race/ethnic differences in nonbiological
factors contributing to complications
Health behaviors.
Self-monitoring of blood glucose (SMBG). The medical
community recommends SMBG for patients using multiple daily insulin injections to achieve glycemic targets (2).
Major clinical trials of insulin-treated patients, which
have included SMBG as part of the multifactorial treatment interventions, have demonstrated significant reductions in diabetes complications (2). SMBG is important in
preventing hypoglycemia and adjusting medications, nutrition therapy, and exercise regimens. A systematic review found that SMBG rates were generally poor among
all patients with diabetes, although SMBG was more
frequent in diabetic individuals taking insulin compared with those who were not (91). Although some
studies have shown no differences in SMBG by race/
ethnicity, several have shown lower rates among NHBs,
Hispanic-Americans, and Asian-Americans, compared
with NHWs. Two studies found no difference in SMBG
frequency in Native Americans compared with NHWs
(91). There are several barriers to SMBG, including inconvenience and intrusiveness, pain, lower socioeconomic position, education level, social class, and living
in a high poverty area, many of which are disproportionately prevalent in ethnic minority groups (91). One
study found that NHBs and Hispanic-Americans did
not perform SMBG due to financial concerns (92). Addressing these barriers will be important in reducing
disparities in diabetes self-management behaviors.
Physical activity and smoking. As summarized earlier,
ethnic minorities are less likely to engage in leisure-time
physical activity, which can contribute to worse glycemic
control and a propensity to developing microvascular
complications (51). In addition, Native Americans and
Alaska Natives have a higher prevalence of smoking than
NHWs (51), which can contribute to their higher risk of
peripheral arterial disease and amputations. NHBs and
NHWs have similar smoking rates, whereas MexicanAmericans have significantly lower smoking rates. Therefore, smoking may not explain ethnic differences in peripheral arterial disease in these populations.
Depression. Depression is a well-established comorbidity
of type 2 diabetes that has an adverse effect on health
behaviors, glycemic control, and complications (93–95).
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Among individuals with diabetes, those with depression
have poor adherence to self-management behaviors compared with those without depression (96). Although there
are few studies of the prevalence of depression in minorities with diabetes, one study found that depression was
more prevalent in minorities with diabetes, particularly
Native Americans and Alaska Natives (97). Although another study found similar rates of depressive symptoms
among NHWs, NHBs, and Hispanic-Americans, NHBs
were less likely to report physician diagnosis or treatment
with pharmacotherapy, suggesting that the presence of
depression may be underdiagnosed and undertreated in
NHBs with diabetes (98).
Summary and future research
Overall, ethnic minorities appear to be disproportionately affected by microvascular complications and mortality associated with diabetes. This is likely related to
poorer glycemic and CVD risk factor control; however,
there are some notable paradoxes in NHBs. First, the reason for the lower incidence of CVD in NHBs with diabetes
is unclear. Whether diabetes raises the risk of CVD in
NHWs more than in NHBs or whether NHBs have higher
CVD mortality in the prediabetic state before their diagnosis of diabetes requires further research. Second, although NHBs have a lower incidence of macrovascular
complications, they are more likely to die once they have
CVD. This may be related to poor CVD risk-factor control
or lack of access to appropriate care, as discussed in the
Conceptual Framework for Health and Health Care Disparities section. Further basic, translation, and clinical research studies are needed to elucidate the higher CVD
mortality rate in NHBs with diabetes. Third, whereas
NHBs have a higher rate of ESRD secondary to diabetic
nephropathy, they are less likely to die on dialysis than
NHWs. The reasons for this are unclear, but some hypotheses include: better overall health of NHBs who
survive to ESRD and are offered or elect to initiate dialysis, compared with NHWs; more organ-limited kidney disease with less overall atherosclerosis in NHBs,
compared with NHWs; and race/ethnic differences in
handling of inflammation (99). We need additional
studies to elucidate the mechanisms contributing to this
survival difference.
Disparities by sex
Microvascular complications
Epidemiology
Retinopathy. National survey data suggest that women
with diabetes have visual impairment more often than men
with diabetes, although this is not necessarily all attribut-
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able to retinopathy (100). Roy et al. (101) examined the
prevalence of retinopathy among adults with type 1 diabetes. There were significant age-by-race-by-sex interactions. NHB women over 50 yr of age were the subgroup
most likely to have severe retinopathy and self-reported
blindness (101). In contrast, NHW women were more
likely to have retinopathy than NHW men, but NHW men
were more likely to have severe retinopathy (101). A
pooled-analysis including adults with type 2 diabetes
(102) did not observe differences by age and sex, although
there were some modest differences by race/ethnicity. In
an exposure unique to women, diabetic retinopathy can
transiently worsen during pregnancy, particularly in
women with rapid glucose changes preconception (103).
Nephropathy. Women with diabetes appear similarly
likely to undergo albuminuria screening as men (104).
Overall, studies have not linked female sex with poorer
outcomes; within race/ethnicity, men have slightly higher
rates of ESRD than women (105). Men with diabetic kidney disease are also more likely to have elevated blood
glucose levels than women (106).
Neuropathy. Similar to the last report of diabetic neuropathy in the NHANES (1999 –2002), which found no sex
differences (107), recent reports on diabetic neuropathy
have found no significant sex differences (108). However,
Gregg et al. (109) noted that, regardless of diabetes diagnosis, peripheral neuropathy was more common in men
than women and was more common among diabetic compared with nondiabetic adults (110). But the study did not
note sex differences in peripheral neuropathy between diabetic men and diabetic women (109, 110). The QT interval on the electrocardiogram may be less sensitive for
detecting autonomic neuropathy in women compared
with men (111).
Macrovascular complications
Epidemiology.
Cardiovascular disease (coronary heart disease, stroke,
and congestive heart failure). Diabetes increases the risk of
coronary heart disease in women more than in men, a
finding that has been consistent across multiple studies
(112–114) and holds true in national discharge data as of
2006 (115). Of note, absolute coronary disease mortality
is also higher in diabetic women than in diabetic men, after
adjustment for other CVD risk factors. Although sex differences were present in the early 1990s, Champney et al.
(116) found recently that diabetic women and men had
equivalent outcomes after percutaneous intervention in
one large hospital-based series. In national hospital discharge data, rates of congestive heart failure appear sim-
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ilar in men and women after age adjustment (117). In the
United States, hospital discharge data showed no difference in stroke hospitalizations between men and women
between 1988 and 2006 (118). Two large prospective
studies from the United Kingdom conflict about the risk of
stroke in diabetic women compared with men (119, 120).
Peripheral arterial disease/amputations. Men are more
likely to undergo diabetes-related lower extremity amputations (121). The sex gap narrowed in the early 2000s,
although diabetic men still had higher amputation rates
than diabetic women in 2006 (122). Hospital discharge
data suggest significantly higher rates of peripheral arterial disease in men than in women (123).
Gregg et al. (109, 110) linked male sex and diabetes
with more frequent lower extremity disease (defined as
ulcers, peripheral neuropathy, and peripheral arterial disease), although the study did not report sex differences in
adults with diabetes. Dorsey et al. (124) also noted that
diabetic men were significantly more likely than diabetic
women to report lower extremity disease.
Mortality
Gregg et al. (125) examined mortality trends in men
and women with diabetes from 1971–2000. All-cause
mortality and CVD mortality both decreased in diabetic
men. However, all-cause mortality increased in diabetic
women with no significant change in CVD mortality
(125); women with diabetes actually had higher overall
mortality than men with diabetes (125).
Sex differences in biological factors contributing to
complications
Glycemic control and cardiovascular risk factors.
Between 1988 and 2002, Saaddine et al. (126) found that
the proportion of women with diabetes and elevated
HbA1c levels (ⱖ9.0%) declined to a significantly greater
extent than that of men. The majority of women in this
study had type 2 diabetes. The increased risk of CVD in
women conferred by diabetes may be due to the presence
of other CVD risk factors, including age, hypertension,
and dyslipidemia (113). In particular, lipid abnormalities
are more severe in women, particularly low-density lipoprotein cholesterol particle size and TG levels (113).
Sex differences in nonbiological factors contributing
to complications
Over the past 20 yr, lipid measurement and elevated
lipid levels, performance of eye exams, aspirin use, smoking cessation, and foot exams improved in both men and
women in national studies (126, 127). However, women
with type 2 diabetes are less likely to use aspirin than men
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Endocrine Health Disparities
(126, 128). Aspirin is beneficial in secondary prevention of
CVD in individuals with diabetes, although its role in primary CVD prevention remains controversial (129). Reports conflict as to whether lipid control is worse among
women with diabetes than men with diabetes. In a study
of several managed care plans, Bird et al. (130) found that
women with diabetes had higher lipid levels than men with
diabetes. In contrast, Ferrara et al. (131) did not find differences in blood pressure control or lipid control or medication management between men and women with diabetes or the subgroup of diabetic adults with CVD. Kim et
al. (132) also did not find sex differences in treatment of
lipid abnormalities in adults with diabetes, although
women were more likely to have elevated lipid levels.
However, Wexler et al. did find that women were less
likely to have adequate lipid or systolic blood pressure
control (133). Some of these differences may explain the
differences in CVD complications in diabetes by sex.
Summary and future research
The most marked sex differences in diabetic complications are for coronary disease and peripheral arterial disease. Although men with diabetes suffer from these conditions more frequently, the impact of diabetes is
significantly higher for coronary disease and lower for
peripheral arterial disease. Postulated mechanisms for sex
differences include endothelial dysfunction and adipokine
activity due to dimorphic sex hormone status. Less aggressive treatment with anticoagulants may also play a
role. However, the reasons for these sex differences remain
largely speculative. In particular, the reasons for differential effects of CVD risk factors on different arterial beds
remain unknown. Future basic, translational, and clinical
research studies are needed to elucidate the differential
impact of diabetes on these two vascular beds.
Perhaps the most striking finding regarding sex differences in complications is the interactions with race/ethnicity. Most of the investigation into the reasons for disparities focuses not only upon sex, but also how its effects
are modified by race/ethnicity. In particular, we need to
investigate both the clinical and nonclinical factors by sex
and race/ethnicity to better understand the reasons for
disparities in either. Ultimately, these disparities can shed
light on mechanisms in disadvantaged groups as well as
pathophysiology in general.
Gestational Diabetes Mellitus (GDM)
Definition
The medical community broadly defines GDM as glucose intolerance, first recognized during pregnancy (134),
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that is likely due to a failure of pancreatic ␤-cells to compensate for the increased insulin resistance that occurs
during pregnancy (135) and possibly to the antagonistic
effects of progesterone on insulin action (136). In less than
10% of women, GDM probably represents type 2 diabetes
that was unrecognized before pregnancy (137). The literature uses prevalence and incidence estimates interchangeably. The reasons for this are: 1) GDM is limited to pregnancy; 2) most women do not conceive twice in the same
year; and 3) of those who do conceive more than once a
year, most women are not diagnosed with GDM before
their second trimester. However, for a small proportion of
women who conceive twice in the same year and do not
carry a full-term pregnancy, incidence estimates may be
slightly higher than prevalence estimates. For the purposes
of this statement, we refer to prevalence and incidence
interchangeably.
Epidemiology of GDM
In the late 1990s to early 2000s, studies from New York
and southern California reported the overall prevalence of
GDM at approximately 5 to 8% (138 –141). As with type
2 diabetes mellitus and obesity, the prevalence of GDM
increased in the 1990s (138). However, GDM prevalence
may have stabilized between 1999 and 2005; in a report
from Kaiser Southern California, Lawrence et al. (139)
found that GDM prevalence remained stable at 7.5 per
100 births in 1999 to 7.4 per 100 births in 2005. Simultaneously, preconception diabetes affected 10% of
women in 1999 and increased to 21% of women in 2005
(139). The increase in preconception type 2 diabetes occurred in all racial/ethnic groups (139). The results are also
concerning because they suggest that the severity of insulin
resistance and ␤-cell failure may be occurring earlier in life
than previously noted, leading to an earlier age of diagnosis of type 2 diabetes and more frequent diabetes in the
reproductive years.
Population-based studies have consistently demonstrated that GDM prevalence is higher in Hispanics,
Asians, and Native Americans compared with non-NHWs
and non-NHBs (138 –140, 142–147). Unlike type 2 diabetes, estimates of GDM have not usually been markedly
elevated in NHBs, compared with NHWs (138 –140, 142–
147). This lack of difference does not seem to be due to
different ages at delivery or to a different prevalence of
preconception type 2 diabetes (143).
There is heterogeneity among subgroups of race/ethnicity. In an examination of birth certificates in New York
City, Thorpe et al. (138) noted that Mexican women under
35 yr of age had an increased prevalence of GDM, when
compared with women under 35 from Puerto Rico, the
Dominican Republic, and other Central American or
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South American countries. However, among women 35 yr
of age, Puerto Rican women had a higher prevalence of
GDM (138). In addition, there is significant heterogeneity
between subgroups of Asians. South Asians, including
women from India and Pakistan, tend to have the highest
prevalence of GDM (143, 145). However, reports vary
regarding the risk among Southeast Asians (143, 145, 148,
149), including women from Cambodia, Vietnam, Laos,
Thailand, or the Philippines, as well as East Asians such as
Koreans, Japanese, and Chinese (143, 145, 147, 148). Japanese women consistently have a lower GDM prevalence
than other Asians (143, 145, 147, 148).
Race/ethnic differences in clinical outcomes in
GDM
Among women with GDM, there are racial/ethnic differences in pregnancy processes and outcomes. Berggren et
al. (150) found that Hispanics were more likely to receive
medical management (as opposed to lifestyle changes
only) than NHBs or NHWs (150). Hispanic women were
less likely to have gestational hypertension, preterm delivery, low birth weight infants, and neonatal intensive
care unit admissions, but more likely to have shoulder
dystocia than NHW or NHB women (150). The study
noted that NHB and NHW women have similar perinatal
processes and outcomes (150). Esakoff et al. (151) found
that Hispanics and Asians with GDM actually had lower
odds of cesarean delivery than NHW women, and Asians
had lower odds of macrosomia than NHW women.
Other reports have found that NHB women with GDM
have poorer outcomes than NHW women. Esakoff et al.
(151) found that NHB women had higher odds of cesarean
delivery and intrauterine fetal demise than NHW women.
Hunt et al. (152) examined birth certificates, inpatient and
outpatient records in South Carolina and found that GDM
in NHBs was more likely to confer greater birth weight
than GDM in NHWs. This racial/ethnic difference persisted after adjustments for age, education, prenatal care,
smoking, and hypertension. Nicholson et al. (153) examined the association between NHB race/ethnicity and delivery procedures among GDM women. NHB women had
a lower prevalence of episiotomy but a greater likelihood
of cesarean delivery and low birth weight infants than
NHWs (153). This finding was attenuated but persisted
after adjustment for multiple factors including demographics, parity, payer source, hospital teaching, volume,
teaching status, and other comorbid conditions (such as
hypertension, macrosomia, and fetal heart abnormalities)
(153). These analyses suggest that race/ethnicity is independently associated with the care GDM women receive at
their delivery, either through local variations or other differences in disease severity.
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The racial/ethnic differences reported in subgroups of
Asians for risk of GDM may extend to risk of complications for GDM. Silva et al. (154) found that macrosomia
was more common among Native Hawaiian/Pacific Islanders and Filipinas compared with Japanese, Chinese,
and NHW mothers. Their analyses suggested that maternal weight conferred different risk for macrosomia, with
similar maternal weights associated with greater odds of
macrosomia in Filipinas, compared with NHWs. In a report from New York City, Mocarski and Savitz (155)
found racial/ethnic differences in outcomes between subgroups of NHBs. Caribbean and sub-Saharan African
women tended to show a larger impact of GDM upon
perinatal events compared with North Africans. In the
same report, these investigators noted that South Asians
had the highest prevalence of GDM, while experiencing
the smallest relative effects of GDM upon macrosomia
and cesarean deliveries (155).
Women with GDM are at increased risk for future
diabetes, and this risk may vary by race/ethnicity (156).
In an analysis of pregnancies from southern California,
GDM conferred greater risk for diabetes for NHB
women than for other racial/ethnic groups, even after
consideration of BMI. Because women of NHB race/
ethnicity have a similar prevalence of GDM to NHW
women, despite having a poorer diabetes risk factor profile (lower socioeconomic status, stronger family history
for diabetes, greater BMI), it is possible that NHB women
who actually develop GDM may be at high risk for diabetes (156). Self-rated health and quality of life are poorer
in women with GDM compared with women without
GDM (157, 158). However, studies have yet to report
comparisons by race/ethnicity.
Biological factors contributing to racial/ethnic
disparities in GDM
Genetics
SNP that confer increased risk for impaired insulin
secretion and sensitivity may explain some of the racial/
ethnic differences. No studies have reported on the contribution of the polymorphisms to racial/ethnic differences in GDM in U.S. populations. The BetaGene study
has found a link between polymorphisms of GCK and
G6PC2 and impaired insulin secretion among MexicanAmerican women with histories of GDM and Finns with
a similar impairment (159). In addition, the BetaGene
study found a link between polymorphisms in IGF2BP2
(160), TCF7L2 (161), PPARG2 (162), and HNF4A (162)
and altered insulin sensitivity in women with histories of
GDM.
Recently, international studies have linked specific
polymorphisms to GDM incidence; these associations
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Endocrine Health Disparities
vary by race/ethnicity. The Hyperglycemia and Adverse
Pregnancy Outcome Study linked GCK and TCF7L2 polymorphisms with increased glucose levels and increased
risk of GDM in Thai women (163). The study also found
an association between the GCK variant and greater birth
weight, fat mass, skin-fold thicknesses in NHW Europeans, but not Thai people, and the study linked the TCF7L2
variant with these outcomes in Europeans, but not Thai
people (163).
Caughey et al. (164) found that having a mother or
father of Asian or Hispanic race/ethnicity increased the
odds of GDM roughly 30% compared with having an
NHW parent. In a similar population, a study by Nystrom
et al. (165) suggested that having two Asian parents resulted in greater odds of GDM when compared with having one Asian parent or two NHW parents, which had the
lowest odds of GDM.
Obesity
Obesity is a significant risk factor for GDM in all racial/
ethnic groups. As with type 2 diabetes, the BMI cut-points
for Asians may be lower than in other racial/ethnic groups.
Hunsberger et al. found that Asians with both high and
low body mass indices had greater odds of GDM (144).
However, even after adjustment for BMI during pregnancy, Hedderson et al. found that the greater risk in
Asians and the relatively low risk in NHBs persisted (143).
Nonbiological factors contributing to racial/ethnic
disparities in GDM
Health behaviors
Although studies have linked dietary content and physical activity to GDM, studies have not examined their relative contribution by race/ethnicity. Reports from the
Nurses’ Health Study II have indicated that higher
prepregnancy intake from animal fat and cholesterol
(166), dietary heme iron (167), meat (168), low fiber and
high glycemic load foods (169), and sugar-sweetened beverages (170) all increase risk of GDM, but the majority of
the population was NHW, and investigation by race/ethnicity was not possible. Similarly, the same group has
found that pregravid physical activity is a risk factor, but
racial/ethnic comparisons were not possible (171).
Socioeconomic status
Studies have associated lower socioeconomic status
with greater prevalence of GDM apart from race/ethnicity. Devlin et al. (146) in Minnesota found that a 7%
annual increase in GDM among women with a highschool education compared with a 4% annual increase
among those with a college education. Adjustment for socioeconomic status tends to reduce racial/ethnic differ-
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ences. Hunsberger et al. (144) found that women with less
than a high school education had 70% greater odds of
having GDM than women with at least a high school education, and that being below the poverty limit also increased the odds of GDM apart from race/ethnicity. However, adjustment for both of these factors tended to reduce
the differences in GDM prevalence seen between Hispanic
vs. NHWs, and NHBs vs. NHWs (144). Of note, even in
multivariable models, racial/ethnic differences persisted.
Country of nativity
Foreign-born women also have a greater prevalence of
GDM than women born in the United States, and this
disparity has increased from the 1990s to early 2000s
(146, 172, 173). In two studies, most of these births occurred to Hispanic women, the majority of whom were
from Mexico (146, 173). In New York City, Savitz et al.
(172) found that foreign nativity increased the odds for
GDM in women of most racial/ethnic groups and subgroups of Hispanics, as well as among Chinese and Filipinos. However, the risk conferred by nativity may differ
between race/ethnic groups. Hedderson et al. (143) found
a link between foreign nativity and a greater risk of GDM
among NHB, South Asian, Filipino, Pacific Islander, Chinese, Mexican, and NHW women, but foreign born Japanese and Korean women actually had a lower risk of
GDM than Japanese and Korean women born in the
United States.
Geographic region
Within the United States, there is regional variation in
the prevalence of GDM. In an analysis of the National
Hospital Discharge Survey, which is based on ICD-9
codes, Getahun et al. (174) found that the prevalence of
GDM increased markedly in the western, northeastern,
and midwestern United States, primarily due to the increase in GDM births among NHBs. They speculate that
these regional differences might represent differences in
screening practices and prenatal care delivery and/or regional increases in obesity (174). On a smaller geographical scale, one study did not find an association between
neighborhood food environment and GDM prevalence in
New York City, although the study did not examine associations by race/ethnicity (175).
Health care access and delivery
There are race/ethnic differences in access to care
among women with histories of GDM (176). Kim et al.
(176) found that among women who had histories of
GDM, Hispanic women were more likely than NHW
women to lack health insurance and a primary care provider, and to report poor or only fair health. Such differ-
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ences suggest that there could be differences in screening
and prenatal counseling among women with GDM, with
subsequent impact upon outcomes, as summarized above,
although studies have not yet examined this question.
Summary, implications, and future research
The investigation of racial/ethnic disparities in GDM
prevalence should focus upon the prevalence of significant
SNP in the BetaGene study in other populations at highrisk for GDM (particularly Asians in the United States).
Studies examining gene-environment interactions, specifically the contribution of clinical factors such as adiposity,
activity, and diet in combination with polymorphisms,
could shed additional light upon the racial/ethnic disparities in both prevalence and complications.
Almost no epidemiologic studies examine the relative
contribution of social and economic factors to racial/ethnic disparities in GDM. These factors include traditional
markers of socioeconomic status, as well as mental stress,
the built environment, and the impact of intrauterine glucose intolerance. Further investigation of the contribution
of these factors is clearly needed. Finally, future studies
should examine the documented disparities in access to
care among women with histories of GDM. This would
help determine the impact of these disparities on screening
for GDM, the quality of care women with GDM receive,
and the additional impact upon outcomes and quality of
life.
Metabolic Syndrome
The metabolic syndrome is considered to be an antecedent
to CVD and type 2 diabetes; thus, the identification and
treatment of the metabolic syndrome might delay or prevent the onset of both CVD and type 2 diabetes (177).
However, the metabolic syndrome is a controversial construct. In 2005, the American Diabetes Association and
the European Association for the Study of Diabetes declared in a joint statement that the widespread use of the
metabolic syndrome was premature and that clinicians
“should evaluate and treat all CVD risk factors without
regard to whether a patient meets the criteria for diagnosis
of the metabolic syndrome” (178). We are not entering
into the debate on the utility of the metabolic syndrome as
a clinical construct, but we will address whether the metabolic syndrome is an effective tool to identify minority
individuals at risk for CVD or type 2 diabetes. We will
focus primarily on data presented from NHANES, which
includes NHB, NHW, and Mexican-American populations. Within NHANES datasets, members of the medical
community have questioned the usefulness of the meta-
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bolic syndrome in identifying high-risk individuals most
often in relation to NHBs (179 –183). We will examine
possible etiologies for why the metabolic syndrome may
be a less successful screening program in NHBs than
NHWs or Mexican-Americans.
Definition
The metabolic syndrome (originally called Syndrome
X) is based on principles first set forth by Gerald Reaven’s
Banting Lecture in 1988, where he described a cluster of
metabolic risk factors related to insulin resistance (184).
Since that time, the medical community has given the syndrome different names and definitions. Without a uniform
definition, researchers could not make comparisons
across studies. To rectify this situation, the International
Diabetes Federation; National Heart, Lung, and Blood
Institute; American Heart Association; World Health Federation; International Atherosclerosis Society, and International Association for the Study of Obesity released a
joint statement in 2009 titled, “Harmonizing the Metabolic Syndrome” (177). The six organizations agreed that:
1) insulin resistance was the underlying cause of metabolic
syndrome, CVD, and type 2 diabetes; 2) the metabolic
syndrome was an important tool to use to screen for future
risk of CVD and type 2 diabetes; and 3) there needed to be
a uniform, worldwide definition. Their definition of the
metabolic syndrome requires any three of five factors,
each of which are considered to be closely linked to insulin
resistance: central obesity, low high-density lipoprotein
cholesterol (HDL-C), hypertriglyceridemia, hypertension,
and fasting hyperglycemia (Table 7). The Endocrine Society was not part of the 2009 joint statement for harmonizing the metabolic syndrome, but in 2008 The Endocrine Society issued a clinical practice guideline endorsing
the use of the metabolic syndrome as a tool for the primary
prevention of CVD and type 2 diabetes (185).
Epidemiology
In two different NHANES datasets, separated by 15 yr
(1988 to 1994, and 2003 to 2006), NHB men had a lower
prevalence of the metabolic syndrome than NHW or Mexican-American men (183, 186). In the 1988 to 1994 survey, the prevalence of metabolic syndrome in NHB,
NHW, and Mexican-American men was 14, 21, and 24%,
respectively. In 2003 to 2006, the prevalence of metabolic
syndrome rose in all three groups to 26, 38, and 34%,
respectively, but still remained significantly lower in NHB
men than NHW or Mexican-American men. Because the
prevalence of type 2 diabetes and CVD is higher in NHBs
than NHWs and Mexican-Americans (187), one would
anticipate that the prevalence of the metabolic syndrome
would also be higher. Even as there is much speculation as
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TABLE 7. Criteria for clinical diagnosis of the metabolic
syndrome (177)
Measure
Elevated WCa
Categorical cut-points
Population-and countryspecific definitions
Elevated TG (drug treatment for ⱖ150 mg/dl (1.7 mmol/liter)
elevated TG is an alternate
indicator)b
⬍40 mg/dl (1.0 mmol/liter)
Reduced HDL-C (drug
in males; ⬍50 mg/dl (1.3
treatment for reduced HDL-C
mmol/liter) in females
is an alternate indicator)b
Systolic ⱖ130 and/or
Elevated blood pressure
diastolic ⱖ85 mm Hg
(antihypertensive drug
treatment in a patient with a
history of hypertension is an
alternate indicator)
Elevated fasting glucosec (drug ⱖ100 mg/dl
treatment of elevated
glucose is an alternate
indicator)
Reprinted from K. G. Alberti et al.: Harmonizing the metabolic
syndrome: a joint interim statement of the International Diabetes
Federation Task Force on Epidemiology and Prevention; National Heart,
Lung, and Blood Institute; American Heart Association; World Heart
Federation; International Atherosclerosis Society; and International
Association for the Study of Obesity. Circulation 120:1640 –1645,
2009 (177), with permission. © American Heart Association, Inc.
a
It is recommended that the International Diabetes Federation (IDF)
cut-points be used for non-Europeans and either the IDF or American
Heart Association/National Heart, Lung, and Blood Institute cut-points
used for people of European origin until more data are available.
b
The most commonly used drugs for elevated TG and reduced HDL-C
are fibrates and nicotinic acid. A patient taking one of these drugs can
be presumed to have high TG and low HDL-C. High-dose ␻-3 fatty
acids presumes high TG.
c
Most patients with type 2 diabetes mellitus will have the metabolic
syndrome by the proposed criteria.
to why the prevalence of the metabolic syndrome is lower
in NHB men than NHW or Mexican-American men, the
overall consensus is that the metabolic syndrome is not
reflective of metabolic risk in NHB men (181).
As with men, the prevalence of CVD and type 2 diabetes is higher in NHB women than NHW women
(187). Yet in NHANES from 1988 –1994 the prevalence
of metabolic syndrome was similar in NHBs and NHWs
and higher in Mexican-Americans (20.9, 22.9, and
27.2%, respectively) (183). In the 2003–2006 dataset,
the prevalence of metabolic syndrome increased in each
group to 38.2, 31.3, and 41.9%, respectively (186). It is
possible that the high prevalence of metabolic syndrome
in the later survey is affected by the confounding effect
of obesity. Between these two NHANES surveys, NHB
women had a relatively greater rise in the prevalence of
obesity than NHW women (20).
Asian-Americans have a high prevalence of metabolic
syndrome despite several subpopulations having a lower
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BMI, and the prevalence varies by the criteria used to define adiposity, as discussed below (see Race/ethnic and sex
differences in body fat distribution—implications for defining metabolic syndrome section under Metabolic
Syndrome). Using the 2002 National Cholesterol Education Program definition of metabolic syndrome, the prevalence among overweight individuals was higher in AsianAmericans (Asian Indians, Chinese, Filipino, Japanese,
Korean, and Vietnamese) compared with NHWs (48 vs.
25%, respectively) (188). Among Asian subgroups, the
prevalence of metabolic syndrome was highest among
Asian Indians and Filipinos in every BMI category (188).
Native Americans also have a very high prevalence of metabolic syndrome regardless of the definition used, ranging
from 44 to 59% in men and 53 to 73% in women.
The metabolic syndrome has engendered major international support because studies in largely NHW cohorts
have demonstrated that the syndrome carries twice the
risk of CVD and five times the risk of type 2 diabetes (177,
181, 189). It is widely assumed that the prevalence of the
metabolic syndrome will vary directly with the prevalence
of CVD and type 2 diabetes in each population. However,
as reviewed below (see Race/ethnic and sex differences in
body fat distribution—implications for defining metabolic syndrome section under Metabolic Syndrome), this
is not the case for NHBs because two of the metabolic
syndrome components, WC and TG, are significantly different in NHBs than NHWs (180, 182, 190 –193). The
impact of these two components on defining metabolic
syndrome in NHBs may lead to an over- or underdiagnosis
of metabolic risk in this population.
Race/ethnic and sex differences in body fat
distribution—implications for defining metabolic
syndrome
Non-Hispanic Blacks
Accumulating evidence suggests that the relationship of
BMI to health is not the same in NHB women as it is in
NHW women (194 –196). For example, Fontaine et al.
(194), in a combined analysis of data from NHANES surveys performed from 1971 to 1992, showed that the BMI
associated with years of life lost secondary to obesity in
NHW women was 28 kg/m2, compared with 38 kg/m2 in
NHB women.
Because WC is highly correlated with BMI, a greater
rise in the prevalence of obesity could result in relatively
more NHB than NHW women meeting the WC criteria of
at least 88 cm. Yet it is unclear whether 88 cm is even the
proper WC threshold to diagnose central obesity in NHB
women. In Scottish women, a WC cutoff of 88 cm (which
the U.S. medical community widely uses) predicts, by linear regression, a BMI of 30 kg/m2. Because visceral adi-
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pose tissue (VAT) is the fat depot most often associated
with insulin resistance (197), the metabolic syndrome uses
WC in its definition as an inexpensive visceral fat proxy.
Although emerging evidence demonstrates that the WC of
risk might be similar in NHB and NHW men, the WC of
risk may be higher in NHB than NHW women (191, 192).
At similar WC, NHB women have less VAT than NHW
women (190, 193, 198). In a study of NHB, the WC that
predicted insulin resistance in NHB women was 98 cm, or
a full 10 cm higher than the recommended threshold of 88
cm (193). In the same cohort, the WC that predicted insulin resistance in NHB men was 102 cm, or identical to
the WC currently used for NHW men (193). In a crosssectional evaluation of Pennington Center Longitudinal
Study data of over 6000 NHB and NHW individuals, the
optimal WC cutoff to predict cardiometabolic risk was 97
cm in NHB women and 92 cm in NHW women (192). For
both NHB men and NHW men, the optimal WC threshold
to predict cardiometabolic risk was 99 cm. Therefore, the
major race difference in metabolic risk associated with
WC appears to be a function of sex, with differences in
women but not men. And whereas the medical community
has not yet agreed upon the exact WC associated with
metabolic risk in NHB women, it seems as though the WC
that predicts VAT, insulin resistance, and cardiometabolic
risk factors appears to be higher in NHB women than
NHW women (191, 192).
Asian-Americans
As in NHBs, current BMI and WC criteria derived from
NHWs may not adequately identify Asian-Americans at
increased risk for metabolic disorders. In a study of 43,507
Asian-Americans, including Asian Indians, Chinese, Filipino, Japanese, Korean, and Vietnamese Americans, the
prevalence of metabolic syndrome, according to 2002 National Cholesterol Education Program criteria, was significantly higher in Asian-Americans than NHWs at every
BMI category (188). This higher prevalence of metabolic
syndrome appeared to be driven by higher prevalence of
hyperglycemia, diabetes, low HDL-C, and hypertriglyceridemia (188). In this study, a comparable metabolic syndrome prevalence for NHWs with BMI greater than or
equal to 25 kg/m2 occurred at a lower BMI for AsianAmericans (19.6 kg/m2 for women and 19.9 kg/m2 for
men), suggesting that the current BMI ranges for defining
overweight/obesity underestimate metabolic risk in Asian
populations (188). Similarly, studies suggest that metabolic risk occurs at lower WC in Asian-Americans. In a
study of South Asians in Texas, more individuals were
identified as overweight and obese when researchers used
the International Diabetes Federation criteria (WC ⱖ90
cm in men and ⱖ80 cm in women), compared with the
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National Cholesterol Education Program criteria (WC
ⱖ102 cm for men and ⱖ88 cm for women) (199). A recent
study in Asian Indians suggested modified WC cut-points
of 90 cm for men and 85 cm for women because these
values predicted the presence of other metabolic syndrome
components (i.e. dyslipidemia, dysglycemia, and hypertension) (200). A study of Japanese-Americans similarly
suggests that lower WC cut-points are needed for this
Asian subpopulation. They determined the accuracy of the
International Diabetes Federation definition of metabolic
syndrome in identifying at least two nonadipose syndrome
components based on various WC cut-points (199). Their
data suggested that more appropriate WC cut-points for
Japanese-Americans were 87–90 cm for men and 80 –90
cm for women (199). In addition, the optimal cut-points
varied by age, particularly in women, with optimal cutpoints of 80.8 and 89 cm in women age 56 or younger and
women older than 57 yr, respectively, and 90 and 87.1 cm
in men age 56 or younger and men older than 57 yr, respectively (199). More studies are necessary to examine
how these alternative cut-points predict risk of type 2 diabetes and CVD in Asian-Americans.
Race/ethnic differences in
lipoproteins—implications for defining metabolic
syndrome
Hypertriglyceridemia
The medical community chose fasting TG levels as a
metabolic syndrome component because of their strong,
positive association with insulin resistance (184, 201). In
NHWs, elevated TG is one of the most common features
of the metabolic syndrome; however, in NHBs and West
Africans, the most common features of the metabolic syndrome are low HDL-C, hypertension, and central obesity,
not elevated TG (88). Use of hypertriglyceridemia as a
diagnostic criterion for metabolic syndrome could potentially lead to underrecognition of metabolic risk in NHBs.
Increased VAT, hepatic fat accumulation, and hyperinsulinemia all contribute to the hypertriglyceridemia of
insulin resistance (202, 203). However, studies show that
TG levels are usually normal in insulin-resistant NHBs
(180). The current belief is that low hepatic fat, low VAT,
low apolipoprotein CIII levels, and high lipoprotein lipase
all contribute to lower TG levels in NHBs (204 –207).
Hepatic fat is a major source of fatty acids that are ultimately reesterified into TG and secreted into the circulation as very low-density lipoprotein-TG. Because NHBs
have lower hepatic fat than NHWs, it is likely that NHBs
secrete less very low-density lipoprotein-TG. This requires
further study. VAT is an important source of free fatty
acids to the liver for TG synthesis. Because NHBs have less
VAT than NHWs, low VAT contribute to low TG in
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Endocrine Health Disparities
NHBs. Lipoprotein lipase is the enzyme that clears TG
from the circulation, and therefore high lipoprotein lipase
activity could be a major factor leading to normal TG
levels in insulin-resistant NHBs. As reviewed in the Diabetes Mellitus and Prediabetes section, NHBs have more
insulin resistance than NHWs, despite low TG in NHBs.
Further basic and translational research studies of the
pathways that allow TG to be normal in the presence of
insulin resistance could lead to the development of therapeutic interventions for populations that do not experience this benefit.
Low HDL-C
The other lipid component of the metabolic syndrome
is low HDL-C. It is well known that on a population basis,
HDL-C levels are higher in NHBs than NHWs; however,
insulin-resistant NHBs often have low HDL-C levels, even
when TG is not elevated (88, 208, 209). For example,
NHBs and Africans, with insulin resistance and/or the
metabolic syndrome, usually have normal TG levels but
low HDL-C (88, 208). Presumably, in NHBs, hepatic
lipase, the enzyme that clears HDL-C particles from the
circulation, remains active in response to the hyperinsulinemia of insulin resistance. Therefore, low HDL-C may
be a factor in development of type 2 diabetes or CVD in
NHBs, even in the absence of elevated TG levels. This
raises the possibility that in NHBs, shifting emphasis from
elevated TG to low HDL-C in screening for metabolic risk
is worthy of investigation.
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Summary and implications
Compared with NHWs and Mexican-Americans, NHB
men and women have a higher prevalence of type 2 diabetes and CVD, particularly hypertension, stroke, and
congestive heart failure (187). Furthermore, in NHBs, the
prevalence of CVD is higher than the prevalence of the
metabolic syndrome (186, 187). This observation, combined with the doubts raised about the effectiveness of the
metabolic syndrome in NHBs (181), means that the use of
the metabolic syndrome to identify risk in NHBs is problematic. Similarly, current criteria used to define obesity
and elevated WC associated with the metabolic syndrome
may underestimate diabetes and CVD risk in Asian-Americans, which is why Alberti et al. (177) have suggested
ethnic-specific WC criteria for consideration (Table 8).
The Black Women’s Health Study (http://www.bu.edu/
bwhs/) and the Jackson Heart Study (www.jsums.edu/
jhs/) collected data on metabolic risk in NHBs, analogous
to data collected in NHWs in the Framingham Heart,
Nurse’s Health, and Physician’s Health studies. Indeed,
the Black Women’s Health Study, initiated in 1995, has
yielded critically important information on obesity, cancer, and CVD in NHB women; however, researchers did
not design the study to specifically address the prevalence
or predictive value of the metabolic syndrome in NHBs.
The Jackson Heart Study, which began enrollment in
2000, is a longitudinal study of CVD risk in over 5000
NHBs from the tri-county region of Jackson, Mississippi.
It is anticipated that the Jackson Heart Study will contrib-
TABLE 8. Current recommended WC thresholds for abdominal obesity by organization
Recommended WC threshold for abdominal
obesity (cm)
Europid
Caucasian
Population
Organization (Ref.)
IDF (4)
WHO (7)
United States
Canada
European
Asian (including Japanese)
Asian
Japanese
China
Middle East, Mediterranean
Sub-Saharan African
Ethnic Central and South American
AHA/NHLBI (ATP III) (5)a
Health Canada (8, 9)
European Cardiovascular Societies (10)
IDF (4)
WHO (11)
Japanese Obesity Society (12)
Cooperative Task Force (13)
IDF (4)
IDF (4)
IDF (4)
Men
ⱖ94
ⱖ94 (increased risk)
ⱖ102 (still higher risk)
ⱖ102
ⱖ102
ⱖ102
ⱖ90
ⱖ90
ⱖ85
ⱖ85
ⱖ94
ⱖ94
ⱖ90
Women
ⱖ80
ⱖ80 (increased risk)
ⱖ88 (still higher risk)
ⱖ88
ⱖ88
ⱖ88
ⱖ80
ⱖ80
ⱖ90
ⱖ80
ⱖ80
ⱖ80
ⱖ80
AHA/NHLBI, American Heart Association/National Heart, Lung, and Blood Institute; IDF, International Diabetes Federation. 关Reprinted from K. G.
Alberti et al.: Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology
and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis
Society; and International Association for the Study of Obesity. Circulation 120:1640 –1645, 2009 (177), with permission. © American Heart
Association, Inc.兴.
a
Recent AHA/NHLBI guidelines for metabolic syndrome recognize an increased risk for CVD and diabetes at WC thresholds of ⱖ94 cm in men and
ⱖ80 cm in women and identify these as optional cut-points for individuals or populations with increased insulin resistance.
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
ute to erasing the information gap on the efficacy of the
metabolic syndrome in NHBs. Within this context one can
use the Jackson Heart Study, as well as other smaller studies of NHBs, to determine whether ethnic-specific values
for TG and the WC of risk can be identified. We need
similar population-based studies of Asian-Americans to
define WC cut-points that identify those at risk for type 2
diabetes and CVD. In the meantime, health care providers
need to appreciate that in NHBs and Asian-Americans, the
absence of the metabolic syndrome, as it is currently formulated, does not mean the absence of risk. To address
type 2 diabetes and CVD health disparities in NHBs, the
medical community should emphasize direct screening
and intervention for hypertension and hyperglycemia.
Thyroid Disorders
Thyroid disorders are common in the United States (1),
with up to 5% of the population reporting abnormalities
in thyroid function or the development of nodules. In autopsy studies, 80% of patients had thyroid nodules (4).
Given the potential public health implications of thyroid
disease, studies assessing racial, ethnic, sex, and age differences among patients are important to inform health
care providers of individual patient needs and to advise
health care policies to ensure equal treatment.
Racial/ethnic differences in benign thyroid
disorders
Epidemiology
Hypothyroidism and hyperthyroidism. The NHANES
measured serum TSH and total serum T4 to evaluate thyroid function and measured thyroid antibodies to gauge
autoimmune thyroid disease (210). In more than 17,300
people over 12 yr of age, the study showed that 4.6% had
hypothyroidism and 1.3% had hyperthyroidism. NHBs
had significantly lower mean TSH concentrations than
NHWs in all populations (P ⬍ 0.01). The percentage of
NHBs with TSH greater than or equal to 4.5 mIU/liter
(hypothyroidism) was significantly lower than in NHWs
(P ⬍ 0.001), whereas the percentage with TSH less than
0.4 mIU/liter (hyperthyroidism) was significantly higher
in NHBs than NHWs (P ⬍ 0.01). It has been debated
whether the lower TSH levels are of clinical significance or
whether they present simply a normal shift in biochemical
values, with no untoward consequences for the individuals. This shift may, in fact, lead to overdiagnosis of subclinical hyperthyroidism and overtreatment of otherwise
healthy and normal NHB individuals.
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Autoimmune thyroid disease. Positive antithyroid antibody levels were present in 11.5 to 13.0% of individuals.
A higher percentage of NHWs had positive antibodies
(14.3%) compared with NHBs (5.3%) and HispanicAmericans (10.9%; all P ⬍ 0.001) (210). These data suggest that NHWs may be at higher risk of autoimmune
thyroid disease, which a prior study indicated. Okayasu et
al. (211) evaluated autopsy material from American subjects and found that over 41% of NHW females over 20
yr old and 20% of NHW males had chronic lymphocytic
thyroiditis, compared with 17% of NHB females and 8%
of NHB males. Asian-Americans had rates of thyroiditis
similar to those in NHBs.
In the women in the Health and Retirement Study, Rogers et al. (212) examined the prevalence of autoimmune
disease, including thyroiditis and Graves’ disease, by age
and race/ethnicity. They found that younger women were
at higher risk of developing Graves’ disease, whereas older
women were more likely to have thyroiditis. They found
no significant racial and ethnic differences among women
in the prevalence of autoimmune disease, except for a 1.87
times higher likelihood in women of Jewish descent.
Biological factors contributing to
race/ethnic disparities
Iodine intake. Since 1971, NHANES has used urinary
iodine concentrations to monitor dietary iodine in the
United States because extremes in iodine intake are associated with the development of goiter (deficiency) and
thyroid cancer (excess) (213, 214). The general U.S.
population over 6 yr old had median urinary iodine
concentrations of 164 mg/liter [95% confidence interval (CI), 154 –174] in 2005–2006 and 164 mg/liter (95%
CI, 154 –173) in 2007–2008, which appeared unchanged
from the surveys conducted since 2000. NHBs had persistently lower urinary iodine concentrations than NHWs
and Hispanic-Americans. These differences among racial
groups are likely due to variations in their dietary intake.
These data suggest that NHB individuals may not achieve
iodine sufficiency according to WHO criteria. The authors
concluded that comprehensive assessments of iodine sufficiency in the general population should be continued
because it would likely influence development of thyroid
disease.
Genetics. Studies have reported genetic susceptibility to
Graves’ disease associated with human leukocyte antigens
(HLA) in NHWs (215), and studies have shown that specific loci differ by race. Chen et al. (216) studied a group
of NHB patients with adult-onset Graves’ disease and racially matched controls, seeking HLA and CTLA-4 associations. They included the major alleles of DRB1, DQB1,
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DQA1, the four subtypes of DRB3, and the presence of
DRB4, and CTLA-4 gene polymorphisms. They studied
39 NHBs and 47 racially matched controls. They found
that neither the DQB1*0301 allele nor DR3 specificity
were present in NHB patients with Graves’ disease but
were present in NHWs. The discordance of the results
between NHWs and NHBs in the United States may be
attributable to the ethnic diversity of HLA genotypes or
the complex interaction of HLA molecules with environmental factors, which may lead to pathogenic processes.
Thyroid cancer
Epidemiology
Thyroid cancer is the most common malignancy of the
endocrine system worldwide. Kilfoy et al. (217) examined
trends in the worldwide incidence of thyroid cancer from
1973–2002 and found that thyroid cancer incidence increased in all countries examined except Sweden, with an
average increase of 48% among males and 67% among
females. Data from the period of 1998 –2002 showed a
5-fold global geographic variation among incidence rates
for men and a 10-fold variation for women. The highest
incidences were among U.S. whites for both men and
women, and the lowest incidences were in Uganda for men
and women (217).
The incidence of thyroid cancer in the United States has
been increasing over the last 50 yr for women and men of
every racial background, except Native Americans (218).
Although the prevalence and incidence of thyroid cancer
is similar by race/ethnicity, survival from thyroid cancer
differs by race/ethnicity. Hollenbeak et al. (219) examined
the Surveillance, Epidemiology and End Result (SEER)
database to determine 5-yr survival rates for patients with
thyroid cancer by race. They included 25,210 NHW and
1,692 NHB patients between 1992 and 2006. They found
that NHB patients were 2.3 times more likely than NHWs
to be diagnosed with anaplastic thyroid cancer, two times
more likely to have tumors greater than 4 cm, and 1.8
times more likely to be diagnosed with follicular nodules
(all P ⬍ 0.0001). NHB patients also had lower 5-yr survival compared with NHWs (96 vs. 97%; P ⬍ 0.006).
They could not analyze surgeon volume data. The authors
concluded that the differences observed likely stemmed
from later disease presentation in NHB patients, and possibly genetic predisposition to more aggressive forms of
thyroid cancer.
In a study of thyroid cancer incidence in Asian-American women from the California Cancer Registry, HornRoss et al. (220) found that age-adjusted incidence rates of
papillary thyroid cancer among Filipino (13.7 per
100,000) and Vietnamese (12.7 per 100,000) women
were more than double those of Japanese women (6.2 per
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
100,000). U.S.-born Chinese [incidence rate ratio (IRR) ⫽
0.48; 95% CI, 0.40 – 0.59] and Filipino women (IRR ⫽
0.74; 95% CI, 0.58 – 0.96) had significantly higher rates
than those who were foreign-born, but the opposite was
observed for Japanese women (IRR ⫽ 1.55; 95% CI,
1.17–2.08). The age-specific incidence among all foreignborn Asian women and U.S.-born Japanese women
showed a steady increase in the incidence of thyroid cancer
until age 70. However, among U.S.-born Asian women,
elevated incidence rates during their reproductive years
were evident (220).
In a study of the Indian Health Service patient database
from 1999 –2004, Weir et al. (221) examined various cancer rates in Native Americans compared with NHWs. Specifically related to thyroid cancer, they found that Native
Americans had a lower relative risk (RR) of 0.71 when
compared with NHWs, but these rates varied across Indian Health Service regions. The authors concluded that
more studies are needed to address unique genetic, social,
cultural, and environmental aspects of Native Americans.
Thyroidectomy is the main treatment for thyroid cancer. Sosa et al. (4) measured the effects of race and ethnicity
on clinical and economic outcomes after thyroidectomy in
patients with benign and malignant thyroid disease. This
study used the Health Care Utilization Project National
Inpatient Sample and included 16,878 patients who underwent thyroidectomy. They found that 71% of patients
were NHWs, 14% NHB, 9% Hispanic-American, and
6% other. Mean length of stay was longer for NHBs (2.5
d) than for NHWs (1.8 d; P ⬍ 0.001). NHBs trended
toward higher overall complication rates (4.9%), compared with NHWs (3.8%) and Hispanic-Americans
(3.6%; P ⬍ 0.056). Mean total costs were significantly
lower for NHWs, compared with those for NHBs and
Hispanic-Americans.
Racial differences were noted not only in the extent of
surgery, but also in administration of postoperative radioactive iodine. Famakinwa et al. (222) examined adherence to
the American Thyroid Association (ATA) thyroid cancer
treatment guidelines in the United States. Using the SEER
database, the researchers assessed compliance with ATA
guideline recommendations 26 and 27 (extent of surgery)
and 32 (postoperative radioiodine administration) in a retrospective fashion. Among 52,964 patients with differentiated thyroid cancer, 71% of patients underwent treatment in
compliance with the surgical recommendations, but only
62% had radioactive iodine treatment in compliance with
recommendations (222). Compliance was lowest in patients
over age 65 yr and among NHBs (P ⬍ 0.001) (222). The
authors concluded that focus should be directed to dissemination of evidence-based recommendations and improved
access for elderly and minority patients.
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Biological factors contributing to race/ethnic
disparities
Genetics. Molecular studies point to several point mutations, which may play a role in papillary thyroid cancer.
The most pertinent somatic mutation is BRAF V600E.
Research has linked it with an aggressive tumor phenotype
in papillary thyroid cancer, including larger tumors, more
extrathyroidal extension, and local and distant metastases. Researchers have also linked the BRAF mutation with
older age and higher recurrence rates (223). A meta-analysis of 1168 patients with papillary thyroid cancer showed
no differences in BRAF status by race/ethnicity, suggesting
that genetic factors do not contribute to race/ethnic differences in thyroid cancer survival (224).
patients were significantly less likely than NHW patients
to be operated on by a high-volume surgeon at a highvolume hospital for nine of 10 procedures analyzed,
whereas Hispanic and Asian-American patients had similar access to low-volume surgeons and hospitals for four
and five of the procedures, respectively. Explanations for
this access inequity could include systematic barriers, such
as geographic location and financial reasons, as well as the
known paucity of high-volume surgeons overall. NHW
patients also may have access to better-informed referral
networks. The literature has not extensively examined referral patterns; thus, we need future studies to inform policies aimed at addressing possible inequities based on patient race or ethnicity.
Nonbiological factors contributing to race/ethnic
disparities
Socioeconomic status and access to care. Research has indicated disparities in stage at presentation and has associated this with socioeconomic and insurance status and
ethnicity. Lim et al. (225) reported a retrospective review
of a large public hospital and a university teaching hospital
at New York University of 419 patients with differentiated
thyroid cancer. The authors found that 96% of patients at
the public hospital were ethnic minorities, mostly Asians
and Hispanic-Americans, compared with 16% at the university hospital. Only 2% of patients had insurance at the
public hospital, compared with 85% at the university hospital. Tumors were more advanced by stage, and extrathyroidal extension was more prevalent in patients at the public hospital. Public hospital patients were three times more
likely to present with advanced disease than those at the
university hospital. This poor access to adequate medical
care contributes to the higher risk of complications and
mortality from thyroid cancer in minority populations.
Minority populations also lack access to adequate surgical care for thyroid cancer. In one study, the majority of
Hispanic-Americans (55%) and NHBs (52%) had surgery
by the lowest-volume surgeons (one to nine cases per year),
compared with only 44% of NHWs. Highest-volume surgeons (⬎100 cases per year) performed 5% of thyroidectomies, but 90% of their patients were white (P ⬍ 0.001) (4).
These findings suggest that whereas health care professionals
consider thyroidectomy safe, significant racial disparities exist in short-term clinical and economic outcomes. Inequities
appear to result at least in part from racial differences in
access to experienced surgeons, as discussed below.
Epstein et al. (226) identified access issues for minority
patients in a study examining the use of high-volume hospitals and surgeons for 10 types of surgeries, including
cardiovascular, cancer, and orthopedic procedures, in
New York City. Among 133,821 patients examined, NHB
Summary, implications, and future research
There are a few notable differences in thyroid function
in NHBs compared with NHWs, including lower TSH and
iodine concentration in NHBs. We need additional studies
to determine whether lower TSH levels have clinical implications for NHBs and whether the lower iodine concentrations increase their risk of goiter and hypothyroidism. The etiology of differences in thyroid cancer incidence
in Asian-Americans based on their country of origin, and in
Native Americans based on their region of residence in the
United States, also requires further study. Finally, the medical
community needs to develop policies to increase minority
access to high-volume surgeons and earlier intervention in
centers with appropriate endocrine and surgical expertise, so
as to improve clinical outcomes and reduce mortality in minorities with thyroid cancer (especially NHBs).
Sex differences in benign thyroid disease
Epidemiology
Hypothyroidism and hyperthyroidism. In NHANES,
among individuals with no thyroid disease, mean TSH
concentration and the percentage of individuals with TSH
greater than or equal to 4.5 mIU/liter (hypothyroidism)
were significantly higher in females than males (P ⬍ 0.01).
The percentage of individuals with TSH less than 0.4 (hyperthyroidism) was significantly higher in females than
males (P ⬍ 0.05).
Autoimmune thyroid disease. The overall prevalence of
positive antithyroid antibodies was significantly higher
in females (17.0%) than males (8.7%) and increased
with age. Females over 80 yr old had a 30.2% rate of
positive antibodies compared with 12.3% of males over
80 yr old (210).
NHW females had a 55% increase in the prevalence of
thyroiditis from the first decade onward, compared with
minimal age effect in NHW males (211). The predomi-
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Endocrine Health Disparities
nance of female patients presenting with autoimmune thyroid disease is significant. Jacobson et al. (227) reported
that 95% of patients with thyroiditis and 88% of patients
with Graves’ disease are women. This may play a potential
role in the development of thyroid cancer because
Hashimoto’s thyroiditis recently has been noted as a possible risk factor for harboring thyroid cancer (228).
Sex differences in thyroid cancer
Epidemiology
Thyroid cancer is the seventh most common malignancy in women, but it is not among the most common 15
cancers in men (229). It is 2.9 times more common in
women than in men (female:male ratio, 16.3:5.7). Over
the last 10 yr, localized disease had the greatest increase in
incidence (5.2/100,000 in 1999 to 9.6/100,000 in 2008),
but more advanced thyroid cancer also has increased in
incidence (218). Differentiated thyroid cancer, including
papillary and follicular histologies, accounts for 80% of
the cases. There are sex differences in the incidence of
specific histological subtypes of thyroid cancer. The rate
of differentiated thyroid cancer in women is three times
higher than in men. Age-specific incidence rises at the beginning of the reproductive years, with a peak incidence for
women between ages 40 and 50 yr; in men, the peak is between ages 60 and 70 yr. By age 85 yr, the sex incidence
equalizes. Women have an earlier age at diagnosis, but men
have more aggressive disease, with a higher mortality rate
(1.9 per 100,000 persons for women; 3.9 per 100,000 persons for men) (229). The more aggressive types of thyroid
cancer, anaplastic thyroid cancer and medullary thyroid cancer, have similar rates of incidence in men and women.
Biological factors contributing to sex disparities in
thyroid cancer
Genetics. Sex association with BRAF mutation has been
controversial and weak. Xu et al. (230) analyzed 80 tumor
samples and observed that BRAF V600E mutation in men
with papillary thyroid cancer was 64% compared with
27% in women. In another study of 203 patients with
papillary thyroid cancer, BRAF V600E mutation was
present in 91% of men (n ⫽ 35) compared with 70% of
women (n ⫽ 168) (231). A meta-analysis of 12 studies
with a total of 1168 patients (male:female ratio, 259:909)
did not show a significant difference in mutation rate by
sex, with 50% of the males and 49% of the females with
papillary thyroid cancer having the BRAF V600E mutation. This suggests that genetics contributes little to the sex
disparity in thyroid cancer (224).
Sex hormones. Research indicates that sex hormones influence the higher incidence of differentiated thyroid can-
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
cer in women and may play a role in the observed sex
disparity. Papillary thyroid cancer expresses estrogen receptors, mediating the effects of estrogen systemically. Lee
et al. (232) investigated the effects of estradiol and testosterone on cell proliferation in papillary thyroid cancer
cells. They showed that estradiol promotes cell proliferation, when compared with cells treated with testosterone
or untreated cells, and that tamoxifen attenuated the
growth-promoting effect (232). Researchers have made
similar molecular observations in patients who are pregnant. Chorionic gonadotropin has a close homology with
TSH, and evidence indicates that chorionic gonadotropin
causes rapid growth of thyroid tumors (benign or malignant) during pregnancy (233)
Obesity. Several studies examining possible environmental factors predisposing for thyroid cancer have focused on
the impact of obesity, as well as patient height and anthropometric factors such as physical activity. BMI is particularly important as a possible risk factor because obesity has increased in the United States. BMI and weight
gain vary widely among Americans of different sex, ethnic,
socioeconomic, cultural, and educational backgrounds, as
previously reviewed. In a study using NHANES data to
measure BMI and body fat composition in the U.S. population, Heo et al. (234) noted that, on average, women
had higher BMI than men, and that NHB and Hispanic
women had significantly higher BMI and percentage of
body fat than NHW women (BMI, 31.2 and 28.9 vs. 27.7
kg/m2, respectively; P ⬍ 0.0001), whereas there was no
difference between men of different races.
A pooled analysis of five prospective studies reported a
positive association of BMI and an increased risk of thyroid cancer in both men and women, whereas height was
a risk factor in women but not in men (235). Studies also
have examined weight in early adulthood and weight gain
from early adulthood to middle age in relation to risk,
finding a positive association between increasing body fat
and cancer risk (236, 237).
Associations of obesity and physical activity with thyroid cancer risk are plausible and could contribute to sex
differences. Studies have linked obesity with increased circulating hormone levels (including estrogens, androgens,
insulin, and IGF-I), and studies link attained height with
increased IGF-I. Estrogen may increase the risk of thyroid
cancer through increased cell proliferation, whereas IGF-I
is a potent mitogen and inhibitor of apoptosis, and its
effects on thyroid growth are amplified by TSH (238,
239). Physical activity contributes to energy balance, may
affect the levels of steroid hormones and insulin, and may
improve insulin sensitivity, thereby modifying and reducing the risk of thyroid cancer (240, 241).
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
jcem.endojournals.org
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pectancy have been greater for minority
populations. Given the increase in life
expectancy among NHB populations
and Hispanics, the number of fractures
will increase in these groups. In 2005,
12% of all fractures occurred in minority populations. By 2025, this percentage will rise to 21% (242).
Epidemiology
Osteoporosis prevalence by bone
mineral density (BMD)
The NHANES 2005–2006 estimated
the prevalence of osteoporosis (T-score,
FIG. 1. Prevalence of osteopenia and osteoporosis by race/ethnicity. [Adapted from E.
Barrett-Connor et al.: Osteoporosis and fracture risk in women of different ethnic groups.
ⱖ2.5) and osteopenia (T-score, 1 to less
J Bone Miner Res 20:185–194, 2005 (446), with permission. © The American Society for Bone
than ⫺2.5) among U.S. adults age 50 and
and Mineral Research.]
older (243). The study used 20- to 29-yrold NHW women from NHANES III as
Summary, implications, and future research
the referent group for both men and women. The prevalence
Autoimmune thyroid disease and thyroid cancer are
of osteopenia was 52, 36, and 38% among NHW, NHB, and
more common in women than in men; however, women
Mexican-American women, respectively, and 33, 22, and
are diagnosed at a younger age and have less aggressive
34% among NHW, NHB, and Mexican-American men.
disease and lower mortality from thyroid cancer than men.
The prevalence of osteoporosis was similar in NHWs and
Genetics is likely not a significant contributor to this sex
Mexican-Americans, with lower rates among NHBs. For
difference, but estrogen may play an important role in
promoting proliferation of thyroid cancer cells. Finally, men, the prevalence of osteoporosis in NHW men was 2%.
sex difference in obesity, which is more common in Insufficient data were available to estimate the prevalence of
women, may also increase thyroid cancer risk through osteoporosis in NHB or Mexican-American men.
The National Osteoporosis Risk Assessment is an obhormonal effects on thyroid cancer cells, and further basic
servational
study of women carried out in the late 1990s.
science research is needed to elucidate these mechanisms.
Primary
care
physicians identified women age 50 or older.
Preventing and treating obesity may also have a beneficial
Women underwent BMD testing using a variety of peripheffect in lowering thyroid cancer risk in women.
eral devices. The study calculated T-scores from the normative populations used by the manufacturers. This study
is unique in that it includes multiple ethnicities. The prevOsteoporosis and Fracture Risk
alence of osteopenia and osteoporosis was lowest in NHB
Osteoporotic fractures are a major public health problem. women. Despite lower fracture rates, the prevalence of
Such fractures result in morbidity, disability, mortality osteopenia and osteoporosis was higher in Asian and Hisand reduced quality of life. Understanding osteoporotic panic women compared with NHWs. Native American
fractures is important for improving health care delivery women also had higher prevalence than NHWs (Fig. 1).
and reducing fractures. Ethnicity and race are important
factors that affect the incidence, risk factors, and treat- Fracture rates
ment outcomes for these types of fractures. Understanding Non-Hispanic Blacks. There are marked differences in the
ethnic and racial influences on osteoporotic fractures is sex-specific rates of hip and other fractures in the United
critical to decreasing the burden of such fractures on pa- States across race/ethnicity. Many publications have contients and society. Because there are sparse data on osteo- sistently shown lower rates of hip fracture in NHBs comporosis and fracture risk in men, and most data in men are pared with NHWs: the rate of hip fracture in the United
summarized by race/ethnicity, we will also discuss sex dif- States is about 50 – 60% lower in NHB women compared
with NHW women, and 30 – 40% lower in NHB men
ferences in this section.
Given the current demographic trends leading to an compared with NHW men. Recent data from Medicare
increase in the number of persons older than 65 yr, the (2000 –2005) showed lower rates of all types of fractures
numbers of fractures will increase even if fracture incident in NHBs compared with NHWs, with some variability by
rates remain stable. Moreover, improvements in life ex- fracture site (Fig. 2; reviewed in Ref. 244). Sex differences
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Endocrine Health Disparities
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
Asian-Americans. Hip fracture rates in
Asian-Americans are lower compared
with NHWs, but the rate ratio varies
markedly across studies and within different subgroups of the Asian population. Hip fracture incidence data are
available for Asian-Americans in California (10), the Medicare population (250,
253), Japanese in Hawaii (254), and
from New York City hospital discharge
data (251).
There are limited data on non-hip
fractures in Asian-Americans. In the
Women’s Health Initiative (WHI), the inFIG. 2. Fracture IRR among Medicare beneficiaries 2000 –2005 by race/ethnicity. White:
cidence of all clinical fractures in AsianReferent group. [Adapted from A. J. Taylor et al.: Clinical and demographic factors associated
with fractures among older Americans. Osteoporos Int 22:1263–1274, 2011 (447), with
Americans was 1,200 per 100,000, compermission. © National Osteoporosis Foundation.]
pared with 2,000 per 100,000 in NHWs.
The relative hazard of fracture in Asianare greater for NHWs than NHBs. In both NHBs and Americans compared with NHWs was 0.59 (95% CI, 0.53–
NHWs, fracture incidence increases with age.
0.65) (255). In NORA, the relative hazard of fractures in
Vertebral fractures are the hallmark of osteoporosis.
Asian-American vs. NHW women was 0.41 (95% CI,
Only 25 to 33% of all vertebral fractures come to medical
0.21–1.79) in multivariate models, including BMD
attention (245, 246). As shown in Fig. 2, clinical vertebral
T-score (252). In a later publication, holding HR for Tfractures are about 75% lower in NHBs compared with
score constant for all ethnic groups, Asian-Americans had
NHWs. Less is known about radiographic vertebral fraca significantly lower HR for fracture (HR, 0.32; 95% CI,
tures: a single study of older women reported a 33% lower
0.15– 0.66) (256). Using the recent Medicare data, the
prevalence among NHBs compared with NHWs (247).
incidence of hip and distal radius fracture was about 35%
Hispanic-Americans. The ratio of hip fracture in Mexi- lower in Asians compared with NHWs. The data showed
can-Americans living in California compared with NHWs smaller differences for clinical spine fractures (Fig. 2).
living in California was 0.35 in women and 0.45 in men
(248, 249). A similar ratio of hip fracture rates using the
Medicare data and assigning ethnicity by surname was
considerably higher (0.72 in women and 0.77 in men)
(250). Zingmond et al. (249) updated their earlier paper
and showed that hip fracture rates doubled in California
Hispanic-Americans from 1983 to 2000. Results from a
later study of hip fracture hospitalizations in New York
City reported a rate ratio of 0.34 in Hispanic-American
women and 0.25 in Hispanic-American men compared
with NHWs (251). Some diversity within Hispanic-American subgroups is evident, with higher rates in MexicanAmericans compared with Cuban-Americans and Puerto
Rican-Americans (250). In the most recent data from
Medicare, the rate of hip and spine fracture was about
31% lower among Hispanics compared with NHWs.
However, the incidence of distal radius and tibia/fibula
fracture was more similar in the two ethnic groups. In the
National Osteoporosis Risk Assessment (NORA) study,
multivariate models, including adjustment for BMD Tscore, yielded a hazard ratio (HR) of fracture of 0.91 (95%
CI, 0.72–1.16) in Hispanics vs. NHWs, indicating a similar risk (252).
Native Americans. In the WHI, during a mean of 7.6 yr,
five of 417 (0.4%) Native American women experienced
a hip fracture. To our knowledge, there is no other information on hip fractures in Native Americans. There are
limited data on non-hip fracture rates in Native Americans. In the WHI, the incidence of fracture was similar in
Native Americans compared with NHWs. The age-adjusted relative hazard of fracture in Native Americans was
1.03 (95% CI, 0.85–1.25) compared with NHWs (255).
In NORA, the multivariable-adjusted (including BMD)
relative hazard of fractures comparing Native Americans
to NHW women was 0.89 (95% CI, 0.59 –1.34) (252). To
our knowledge there are no data on Native American men
or within different Native American tribes.
Mortality and disability after osteoporotic fractures
Studies have linked both hip and vertebral fractures
with an increased risk of mortality (257), but mortality
after hip fracture is higher among NHB women than
among NHW women (258). The factors contributing to
the higher mortality rate among NHB women after a hip
fracture are not completely understood, but could reflect
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
their older age at the time of fracture, greater comorbidity, or
disparities in health care. Indeed, the average number of diagnoses at admission to the hospital at the time of hip fracture is
greater among NHB women than NHW women (259).
Hip fractures have serious consequences regarding mobility and independent living. About 50% of women are
unable to achieve their prefracture walking ability after
their hip fracture (260). Most of the research on the consequences of hip fracture has been carried out in NHW
patients, but one small study suggests that the percentage
of patients with hip fracture who were nonambulatory at
the time of their discharge was six times higher among
NHB women than among NHW women (259). We need
more data on the consequences of osteoporosis in populations that are not NHW.
Biological and clinical factors contributing to race/
ethnic disparities
Race/ethnic differences in BMD
BMD is a significant predictor of fracture risk and could
account for at least some of the ethnic differences in fractures observed in population studies. Age-adjusted mean
femoral neck BMD is approximately 10% higher in NHB
women and 6.5% higher in Mexican-American women
compared with NHW women (243). NHB men have a
10.7% higher femoral neck BMD, but there was no difference in BMD in NHW men or Mexican-American men
(243). Unadjusted lumbar spine and femoral neck BMD
are higher in premenopausal and early perimenopausal
NHB women, next highest in NHW women, and lowest in
Chinese- and Japanese-American women (261). When
studies adjust BMD for ethnic differences in anthropometric and lifestyle factors that affect BMD, with careful
adjustment for body weight, lumbar spine BMD is similar
in NHB, Chinese-American, and Japanese-American
women, all of whom have higher spine BMD than NHW
women (261). For femoral neck BMD, adjustment for
these same factors (most importantly body weight) reduces the advantage of NHB women, compared with
other groups, and eliminates differences among ChineseAmerican, Japanese-American, and NHW women (261).
Lifestyle and anthropometric factors account for some of
the ethnic variation in BMD, although additional ethnic
variation in BMD remains unexplained.
Skeletal risk factors for fracture
Bone mineral density. For NHBs, at least 27 to 36% of
their lower fracture risk is due to their higher BMD (247).
For Hispanic-Americans, based on WHI data, BMD explains at least 17% of their lower fracture risk. There are
no data to address this in Asian-Americans. The Study of
Osteoporotic Fractures did a follow-up for 6.1 yr of 7334
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NHW women (age, 67–99 yr) and 636 NHB women (age,
65–94 yr) (262). At every level of BMD, the fracture rate
was lower in NHB than NHW women. In age-adjusted
models, NHBs had a 64% lower risk of fracture compared
with NHWs. The addition of femoral neck BMD to the
model attenuated the effect such that the risk of fracture
was 51% lower in NHBs. This suggests that approximately one third of the lower fracture risk in NHBs could
be explained by BMD; however, NHB women still had a
lower fracture risk even after adjusting for BMD and other
risk factors. In this same study, the prevalence of morphometric vertebral fractures was 67% lower in NHB compared with NHW women, which was attenuated but still
significantly lower after adjustment for femoral neck
BMD (247).
In the NORA Study, the relative hazard of fracture was
significantly lower in NHB (48% lower) and Asian-American (68% lower) women, compared with NHW women,
independent of BMD, T-score, body weight, and other
fracture risk factors (248, 250). In the WHI, the risk of
fracture was significantly lower in NHB (49%), AsianAmerican (34%), and Hispanic-American (33%) women
compared with NHW women (263). The addition of fracture risk factors, including body weight, to the models had
little effect, suggesting that these risk factors could not
explain the race/ethnic differences in fracture. In a subset
of women with BMD measurements, adding BMD to the
models did attenuate the risk reduction by about 33% in
NHBs and 17% in Hispanic-Americans; however, fracture risk remained significantly lower in NHBs and Hispanic-Americans, even after adjusting for BMD (263).
Finally, it should be noted that although BMD is higher
in NHB than NHW women, low BMD is still a risk factor
for fracture in NHBs. In the Study of Osteoporotic Fractures, lower BMD resulted in a greater likelihood of prevalent vertebral fracture in both NHW and NHB women
(247). The study linked a 1 SD decrease in femoral neck
BMD with a 47% increased odds of prevalent vertebral
fracture in NHB women and an 80% increased odds of
prevalent vertebral fracture in NHW women (P value ⫽
0.14 for interaction) (247).
Other skeletal traits— bone geometry and structure. Race/
ethnic differences in fracture rates appear independent of
BMD. Asian women have lower fracture rates than
NHWs, despite their similar areal BMD. Several investigators have described additional differences in bone size
and geometry that could also contribute to ethnic differences in fracture rates. Studies have linked hip axis length,
measured by dual-energy x-ray absorptiometry (DXA)
scanners as the distance from the greater trochanter
through the femoral neck to the inner pelvic brim near the
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Endocrine Health Disparities
acetabulum for the femoral head, with hip fractures.
Women with shorter hip axis length have a lower risk of
fracture (256). The mean hip axis length was also significantly shorter in NHB and Asian-American women and
may also contribute to their lower fracture rates (264).
Hip structural analysis, developed by Beck et al. (265),
estimates multiple dimensional and geometric variables using DXA. Results suggested some important race/ethnic variation. NHB women have longer, narrower femurs on average, with smaller medullary cavities than NHW women
(266). The thicker cortices in NHB women could also contribute to greater mechanical strength. NHB women also had
greater section modulus, an index of strength suggesting that
the spatial distribution of bone is such that their bones can
resist greater loads compared with NHW women.
Studies have also described geometric differences for
Mexican-American and Native American women (267).
Higher BMD in Mexican-American women was due to a
smaller size of bone, not greater bone mineral content.
NHBs, Mexican-Americans, and Native Americans all
had greater section modulus than NHWs, which could
contribute to their lower fracture rates.
More recently, composite indices of femoral neck
strength, which integrate body size and bone size with
bone density, may capture the major structural contributions to bone strength relative to bone loads applied to
bone during falls (268). NHB, Chinese-American, and
Japanese-American women all had significantly higher
composite strength indices than NHW women (268).
Studies observed these differences despite the lower areal
BMD in Japanese-American and Chinese-American
women and the higher body weight in NHB compared
with NHW women. These indices may contribute to ethnic differences in fracture.
Studies have also described ethnic differences in rates of
bone turnover (269), although these patterns do not necessarily parallel ethnic differences in BMD.
Menopause. The most important risk factor for bone loss in
women in midlife is the menopause. The Study of Women’s
Health Across the Nation (SWAN) enrolled 1902 NHB,
NHW, Chinese-American, and Japanese-American women
into a longitudinal study of BMD changes during the menopause (270). BMD loss accelerated markedly in the late perimenopause in each race/ethnic group. Lumbar spine BMD
loss was most rapid in Japanese-American and ChineseAmerican women, intermediate in NHW women, and
slowest in NHB women (P ⬍ 0.001). However, the definition of menopausal status was imprecise, and the time in
which bone loss decelerates after the final menstrual period could not be determined. Therefore, a follow-up report from the SWAN described changes in BMD in rela-
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
tionship to the final menstrual period in a subset of women
for whom researchers could determine the final menstrual
period. Cumulative, transmenopausal changes were greatest for Chinese-American and Japanese-American women
and lowest for NHB women (271). However, the absolute
difference in bone loss by race/ethnicity was statistically
significant but small—1 to 2%. Therefore, it is unlikely
that this amount of bone loss at menopause could explain
racial/ethnic differences in fracture rates. Nevertheless,
the age at menopause may differ across race/ethnicity. In
some studies, an earlier age of menopause was observed
among NHB women (272). In SWAN, there was no difference in age at menopause for NHB women, but a much
greater proportion of NHB women underwent a surgical
menopause, which might influence osteoporosis risk
(273). If this is true, then it could mean that NHB women
are entering menopause at an earlier age, which could
increase their risk for osteoporosis over time.
Nonskeletal risk factors for fracture
There are limited data on nonskeletal risk factors for
fracture in multiethnic women. Most of the information
comes from a single paper from the WHI that focused on
all clinical fractures in women only, and BMD was not
measured in all women (255). To our knowledge, there is
essentially no information on risk factors for fracture in
non-white men, other than a small study of 39 NHB men,
nine of whom had a fracture. The only risk factor that was
significant was older age among the NHB men who experienced fractures (274). The data we summarize below
are from the WHI, unless otherwise indicated.
Body weight and height. The WHI did not link weight to
any clinical fractures in any race/ethnic group; however,
WHI women were on average overweight or obese, so
there was not much variability in body weight. In another
study, however, low body weight was a risk factor for
nonvertebral fractures (275). The association between
weight and fracture may be strongest for hip fractures; in
two case-control studies in NHB women, those who were
underweight (276) and in the lowest quintile of BMI (277)
had a significantly increased risk of hip fracture. The Hispanic Established Populations for Epidemiologic Studies
of the Elderly study did not link BMI to hip fracture (253).
The underlying mechanism for this association could reflect additional fat at the hip resulting in weaker impact
and greater absorption of the force of the fall in more obese
women. In addition, obesity is associated with higher endogenous estradiol levels and lower SHBG (278), both of
which have been linked to hip fracture risk (279).
The WHI showed a significant association between
height greater than 162 cm and an increased risk of all
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TABLE 9. Nonskeletal risk factors for fracture risk by race/ethnicity from the Women’s Health Initiative and other
studies
Risk factor
Clinical risk factors
Low body weight/BMI
Increased height
Previous fracture
Parental fracture history
Corticosteroid use
Current hormone therapy use
Parity (⬎5 pregnancies)
Nonclinical risk factors
Sociodemographic factors
Age
Education (at least high
school)
Health behaviors
Smoking
Alcohol use
History of at least two falls
NHWs
NHBs
Hispanic- Americans
Asian- Americans
Native Americans
⫾
⫾
Low BMI
OR ⫽ 13.5 (4.2, 43.3)
⫺
⫾
⫾
⫾
1
HR ⫽ 1.56 (1.11, 2.17)
1
HR ⫽ 1.86 (1.39, 2.50)
1
HR ⫽ 1.28 (1.04, 1.58)
1
HR ⫽ 3.88 (1.89, 7.99)
⫺
⫾
HR ⫽ 1.46 (0.85, 2.52)
1
HR ⫽ 1.50 (1.10, 2.05)
⫾
HR ⫽ 1.21 (0.96, 1.53)
⫺
HR ⫽ 0.73 (0.10, 5.27)
2
HR ⫽ 0.7 (0.5, 0.8)
1
HR ⫽ 1.8 (1.1, 3.0)
⫺
1
HR ⫽ 1.14 (1.10, 1.18)
1
HR ⫽ 1.55 (1.49, 1.61)
1
HR ⫽ 1.18 (1.15, 1.22)
1
HR ⫽ 1.43 (1.22, 1.68)
⫺
⫺
1
HR ⫽ 1.74 (1.38, 2.20)
⫾
HR ⫽ 1.14 (0.96, 1.36)
⫾
HR ⫽ 1.54 (0.82, 2.90)
⫾
OR ⫽ 0.1 (⬍0.1, 0.5)
⫺
1
⫺
1
1
⫺
⫺
1
HR ⫽ 1.27 (1.22, 2.32)
⫺
1
HR ⫽ 2.89 (1.47, 5.66)
⫾
HR ⫽ 1.58 (0.94, 2.67)
⫾
HR ⫽ 2.75 (0.26, 28.9)
2
HR ⫽ 0.5 (0.3, 0.9)
⫺
1
1
1
HR ⫽ 1.22 (1.0, 1.5)
⫺
⫺
⫺
⫺
⫾
1
HR ⫽ 1.7 (1.9, 2.0)
⫺
⫺
1
HR ⫽ 1.8 (1.4, 2.3)
⫺
⫺
1
HR ⫽ 1.4 (1.1, 1.9)
⫺
⫺
⫺
HR ⫽ 1.38 (0.75, 2.55)
Data on risk are indicated where available. Data in parentheses represent 95% CI.
⫾, Data inconsistent regarding risk; ⫺, no association with fracture risk; 1, associated with increased fracture risk; 2, associated with decreased
fracture risk.
clinical fractures in NHWs and Hispanic-Americans
(263). There was a similar trend in Asian-American
women, although not statistically significant. There was
no association between height and fracture risk in NHB or
Native American women (Table 9).
Prior fracture history. The WHI linked prior fracture history with an increased fracture risk in all race/ethnic
groups (Table 9) (263).
Parental history of fracture and ancestry. The WHI linked
parental history of any fracture with an increased risk of
fracture in all race/ethnic groups, although it was not consistently statistically significant, perhaps reflecting the low
power in some groups (Table 9) (263).
Individuals will self-identify with one race/ethnic group
despite differences in admixture. In one study, the distribution of European ancestry among U.S. NHBs ranged from
0.1 to 89.95%, with a median of 18.7% (280). Using ancestry informative markers, studies have linked a greater
amount of European admixture with lower BMD and
weaker hip geometry in NHBs (280, 281). In the future,
greater emphasis of these ancestral markers may improve our
understanding of the impact of race and ethnic variability.
Medication use. The WHI linked corticosteroid use for
more than 2 yr with an increased risk of fracture in all
race/ethnic groups, except Asian-Americans, although it
was not statistically significant in NHBs or Native Americans (263). This analysis did not evaluate the risk by race/
ethnic group associated with shorter courses of corticosteroids. Recent guidelines indicate that fracture risk is
increased with 3 months or more of daily use of at least 5
mg of prednisolone or its equivalent (282); however, future studies are needed to determine whether this shorter
exposure similarly predicts fracture risk in minority and
NHW women. In a case-control study of NHB women,
postmenopausal estrogen therapy for at least 1 yr was
protective against fractures in members of this population
under 75 yr of age (277). The WHI linked current hormone therapy use with a lower risk of fracture in AsianAmerican and Native American women (263).
Medical comorbidities. In NHB women, the WHI linked
a history of stroke with a 3-fold increased risk of fracture
(277). In Hispanic-American women, the WHI linked the
presence of diabetes with an increased fracture risk (283).
Parity. In Asian-American women, the WHI linked having
at least five pregnancies with a significantly higher risk of
fracture (263).
Treatment efficacy
The majority of women enrolled in randomized controlled trials of osteoporosis medication efficacy have been
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Endocrine Health Disparities
NHW, largely due to enrollment criteria based on BMD or
prevalent fracture status. However, there is no evidence
that treatment efficacy varies by race, although the “evidence” is by far incomplete. A single trial of alendronate
given to 65 NHB women with T-scores less than ⫺3.0
showed that alendronate treatment increases BMD at all
sites. The magnitude of the effect was similar to trials of
NHW women (284). Vitamin D3 supplement of 2000 IU/d
was sufficient to raise 25-hydroxyvitamin D [25(OH)D]
levels to greater than 50 nmol/liter in almost all postmenopausal NHB women (285). Finally, as part of the WHI
Hormone Trials, there was no evidence that the beneficial
effect of hormone therapy on fracture reduction differed
by race/ethnicity (286, 287).
Nonbiological factors contributing to race/ethnic
disparities
Sociodemographic factors
Fracture rates in the WHI increased with age in all race/
ethnic groups; however, in NHB women, rates did not
increase until after 75 yr of age (263). In NHB women, the
WHI linked having at least a high school education with
a higher risk of fracture (263).
Health behaviors
The WHI did not link smoking with fracture in any
ethnic group, but the prevalence of smoking was low in the
WHI women, and thus they had low power (263). Alcohol
consumption was unrelated to fracture risk in all race/
ethnic groups in the WHI, but the study stratified intake at
one or more drinks per day, and not at the FRAX level of
three or more drinks per day (263). In two case-control
studies in NHB women, higher alcohol consumption was
associated with an increased risk of fracture (276, 277).
History of falls
The WHI linked a history of falls with a significantly
higher risk of fracture in all race/ethnic groups, but the
association was much stronger in NHB and HispanicAmerican women (Table 9) (263).
Disparities in screening and treatment
Congress passed the Bone Mass Measurement Act in
1997 providing DXA reimbursement for qualified Medicare beneficiaries. Yet, despite almost universal access for
women, at least for BMD testing (an approved indication
is estrogen deficiency), few older Americans take advantage of this screening test. Using Medicare claims data
from 2000 –2005, Curtis et al. (288) showed that the proportion of 65-yr-old women who underwent central DXA
increased from 8.4% in 1999 to 12.9% in 2005. Corresponding proportions of men were 0.6 to 1.7%, respec-
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tively. Nevertheless, a much lower proportion of NHBs
underwent testing: for all years, 31.3% of NHW women
vs. 15.3% of NHB women; and 4.6% of NHW men vs.
1.9% of NHB men. A retrospective chart review also reported that significantly fewer NHB women than NHW
women were referred for DXA, although they had similar
risk estimates (289). Physicians were also less likely to
mention osteoporosis in the medical records of the NHB
women or to recommend calcium or vitamin D supplementation, compared with NHW women.
NHB women with a history of fracture are also less
likely to receive a diagnosis of osteoporosis. Using Medicare claims data (2000 –2005), among women with a history of fracture, 33% of NHB women had an osteoporosis
claim, compared with 59% of NHWs, 74% of AsianAmericans, and 58% of Hispanic-Americans (290). The
data showed similar race/ethnic differences for men, but
the overall proportion of men with an osteoporosis diagnosis was much lower than women. These results suggest
suboptimal recognition and management of osteoporosis
among NHB women and men.
NHBs were also substantially less likely to receive prescription osteoporosis medications than NHWs, even after adjusting for socioeconomic factors or clinical risk factors for fractures (291). In a large population-based cohort
of almost 25,000 participants, the odds of NHBs receiving
osteoporosis medication were 56% lower than that of
NHWs. These results are similar to smaller studies that
also showed disparity in screening and counseling in
NHBs compared with NHWs (292, 293).
New treatment guidelines from the National Osteoporosis Foundation suggest that more than 40% of NHB women
and more than 60% of Hispanic-American women older
than 80 yr meet the guidelines for treatment (294), yet treatment disparities are evident. New treatment guidelines suggest that women with a 10-yr probability of hip fracture of
3% or greater should be recommended for therapy. However, roughly 20% of NHW women and less than 12% of
NHB women who meet this guideline receive treatment.
At every level of predicted hip fracture risk, the percentage
of women receiving osteoporosis therapies is lower among
NHB women (288).
Summary, implications, and future research
Although there are race/ethnic differences in osteoporosis and osteopenia as well as fracture risk, fracture risk
factors common to all race/ethnicities include increasing
age, prior fracture history, and history of falls, indicating
that these factors identify all women at increased risk.
Fracture risk also increases with the number of risk factors
in women of every race/ethnic group (247, 255) and in
older men (295). Thus, targeting older men and women
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with multiple risk factors for interventions is warranted to
reduce fractures. Sex differences in fracture risk are greater
for NHWs; however, there are little data on osteoporosis
and fracture risk in minority men—a clear gap in the literature and an important area for future research.
With the exception of Asian-American women, minority women have higher BMD than NHW women, which
translates into a reduced fracture risk in minority women.
Asian-American women also have lower fracture risk than
NHWs, despite the lower BMD. Studies suggest that differences in non-BMD skeletal traits may be protective in
minority women. We need future research to determine
whether these novel traits— bone size, bone geometry, hip
axis length— differentially predict fracture risk in NHW
and minority women, compared with BMD. In addition,
the medical community needs to develop intervention
strategies to preserve BMD in NHW women and protect
them from the osteoporotic fractures. Genetic studies may
shed light on whether certain genetic polymorphisms contribute to race/ethnic differences in BMD. In a prior review
of studies examining racial contributors to differences in
BMD, 15 of 40 articles suggested that genetic or inherited
factors contributed, but studies did not include genetic
data (296). Future studies should also determine whether
race/ethnic differences in social or behavioral factors contribute to race/ethnic differences in BMD because these
factors have been infrequently examined (296).
Despite the lower relative risk of fractures in minority
women, their absolute risk of fracture is still substantial.
In addition, NHB women suffer higher mortality and disability after fracture than NHW women. We need further
research to determine the contributors to this morbidity
difference. Fractures are more common in minority
women than the combined number of myocardial infarctions, coronary heart disease deaths, and breast cancers
(297). Using annualized incidence rates for all fractures,
breast cancer, myocardial infarction, and coronary heart
disease deaths observed in the Observational Study of the
WHI, more NHB, Asian-American, Hispanic-American,
and Native American women experience a fracture in 1 yr
than the combined number of those who experience breast
cancer and a composite CVD end-point. Thus, we need
interventions to increase osteoporosis screening and treatment in minority women to prevent fractures and their
associated morbidities.
Vitamin D deficiency
Epidemiology
Vitamin D is important for bone health as well as other
metabolic disorders (298). The Institute of Medicine re-
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leased new dietary reference intakes for calcium and vitamin D in November 2010. The Institute defined four
categories of vitamin D status based on serum 25(OH)D
levels: risk of deficiency (⬍30 nmol/liter), risk of inadequacy (30 – 49 nmol/liter), sufficiency (50 –125 nmol/liter), and possibly harmful (⬎125 nmol/liter). In the United
States from 2001–2006, 8% of persons age 1 yr and over
were at risk of 25(OH)D deficiency, 24% were at risk of
inadequacy, 67% were sufficient, and 1% had possibly
harmful levels (299).
The season-adjusted prevalence of risk of deficiency, by
age, ranged from 1 to 8% in men and 1 to 12% in women.
The season-adjusted prevalence of risk of inadequacy, by
age, ranged from 9 to 28% in men and 11 to 28% in
women. Men were less likely to be deficient than women.
The prevalence of risk of deficiency varied by race/ethnicity and was 3, 32, and 9% for NHWs, NHBs, and Mexican-Americans, respectively. There were also race/ethnic
differences in the prevalence of risk for inadequacy: 18,
41, and 33% for NHWs, NHBs, and Mexican-Americans.
NHANES III (1988 –1994) and NHANES (2001–
2004) assessed serum 25(OH)D status of the U.S. population, and the prevalence of risk of deficiency and
inadequacy increased from the earlier to the later study.
Age-adjusted mean 25(OH)D levels were lower in
NHBs compared with NHWs at every level of percentage body fat (300). Differences between NHWs and
NHBs were greater among those ages 12–29 yr than
among those age 70 yr and older, primarily due to lower
mean levels among NHWs age 70 yr and older. The
NHANES finding of lower 25(OH)D among NHBs is
consistent with most other studies (301).
Higher 25(OH)D levels have been linked to a decreased
risk of fracture in NHW women. In multivariable models,
compared with 25(OH)D levels of less than 20 ng/ml,
higher levels were associated with a lower risk of fracture
in NHW women—for 25(OH)D levels of 20 to 30 ng/ml,
odds ratio (OR) ⫽ 0.82 (95% CI, 0.58 to 1.16), and for
25(OH)D levels greater than 30 ng/ml, OR ⫽ 0.56 (95%
CI, 0.35 to 0.90). In contrast, higher 25(OH)D levels
(greater than 20 ng/ml) compared with levels of less
than 20 ng/ml were associated with a higher risk of
fracture in NHB women (OR ⫽ 1.45; 95% CI, 0.99 to
7.80; P trend ⫽ 0.04). These results suggest divergent
associations between 25(OH)D for skeletal health by
race/ethnicity and warrant further investigation in future studies to confirm or refute these findings. The
optimal level of 25(OH)D for skeletal health may differ
in NHW and NHB women (302).
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Biological contributors to race/ethnic disparities
The etiology of lower vitamin D levels in NHBs compared with NHWs is likely multifactorial. NHBs are at
higher risk for vitamin D deficiency because the high melanin concentration in their skin reduces the capacity to
synthesize vitamin D (303). Studies have associated obesity with vitamin D deficiency, which researchers believe
is caused by deposition of vitamin D into adipose tissue,
decreasing the vitamin’s bioavailability (303). Studies examining whether differences in adiposity contribute to
race/ethnic differences in vitamin D deficiency have been
conflicting. A study in women of childbearing age linked
lower BMI with hypovitaminosis D in NHB women (303);
however, it also linked obesity with hypovitaminosis D in
both NHB and NHW older women (304) and NHB men
(305). Genetic factors might also determine vitamin D levels.
A systematic review identified several genetic variants that
influence serum vitamin D levels—two SNP in vitamin D
binding protein group-specific component (rs4588, rs7041),
one SNP in the vitamin D receptor (rs10735810), and
one SNP in a cytochrome P450 enzyme CYP27B1
(rs10877012) (306). Although this study did not look specifically at variation by race/ethnicity, a recent study examined the association of vitamin D levels with 94 SNP in
five vitamin D pathway genes in a case-control study of
NHBs and NHWs (307). They found statistically significant associations with three SNP, only in NHBs
(rs2298849 and rs2282679 in the vitamin D binding protein group-specific component, and rs10877012 in the
CYP27B1 gene) (307). The study associated a higher genetic score with lower vitamin D levels and a greater odds
of vitamin D insufficiency; however, overall, these three
SNP only accounted for 4.6% of the variation in serum
vitamin D levels in NHBs, indicating the importance of
nongenetic factors (307).
Nonbiological contributors to race/ethnic
disparities
In both NHBs and NHWs, studies have associated
lack of vitamin D supplementation with lower vitamin
D levels (303, 304); even among NHB men and women
taking vitamin D supplements, the prevalence of vitamin D deficiency is higher than in NHWs (303, 305).
Studies have linked levels of dairy intake with vitamin
D deficiency in NHBs, with less than three servings of
milk or cereal each week being associated with deficiency in NHB women and higher milk consumption
being associated with less deficiency in NHB men (303,
305). In NHB men, higher levels of intentional physical
activity were associated with a lower likelihood of vitamin D deficiency (305). Finally, the environment can
also be an important determinant of vitamin D levels.
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Among NHB women, studies associated urban residence with vitamin D deficiency, which may be related
to less outdoor activity and sun exposure or more exposure to environmental pollutants that decrease the
skin’s synthesis of vitamin D (303).
Summary, implications, and future research
Vitamin D deficiency is a common endocrine disorder, particularly among NHBs. The etiology of the race/
ethnic differences is multifactorial, with biological, behavioral, and environmental contributors. Genetic
factors likely only play a minor role in race/ethnic differences in vitamin D levels. We need intervention strategies to increase vitamin D supplementation use among
NHBs, and we need additional research to determine
why vitamin D deficiency still occurs among NHBs taking vitamin D supplementation. Basic science research
is necessary to determine molecular contributors to differences in vitamin D synthesis and metabolism by race/
ethnicity. Finally, we need future population-based
studies to determine the prevalence of vitamin D deficiency in other race/ethnic groups, including AsianAmericans and Native Americans.
Conceptual Framework for Health and
Health Care Disparities
Our conceptual framework, adapted from Warnecke et al.
(308), combines a population health framework with a
quality of care framework to elucidate the causes of disparities in endocrine conditions and to guide our approach
to understanding and eliminating these disparities (308,
309). In this section, we will focus on how our framework
explains race/ethnic disparities in diabetes and its complications because that is where much work has been focused;
however, the framework is also relevant to other endocrine conditions, and we will highlight its application to
those disorders where appropriate.
This framework recognizes population-level determinants of health outcomes as distinct from, yet intertwined
with, individual-level determinants of health (Fig. 3). The
model identifies proximate, intermediate, and distal factors that influence health. Proximate determinants of
health include biological and genetic pathways, biological
responses, individual health behaviors, and individual demographic and social factors. Genetic ancestry, epigenetic
changes induced by environmental stress, and allostatic
load (reviewed below under Proximate factor: biological
pathways and responses), induce biological responses that
may increase disease risk. It is important to note, however,
that to date there is little evidence of genetic factors that
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cial conditions, and the organizations
and institutions that determine or influence such policies.
Our disease-specific sections have
focused on biological pathways and responses, genetics, and certain individual
demographic and health behaviors and
their role in race/ethnic disparities in diabetes, thyroid disease, and osteoporosis
and fracture risk. In the sections below,
we begin with the individual level most
proximal factors we have not previously
addressed and then discuss the role of intermediate and distal factors in contributing to endocrine disparities, using diabetes as the exemplar condition.
Proximate factor: biological
pathways and responses
The concept of allostatic load—impact
of chronic stress on biological systems
Seyle first suggested that chronic stress
might have a cumulative damaging effect
on human biological systems (311, 448).
Researchers introduced the concept of allostasis to describe
the capacity of an organism to adapt to a changing environment or stressful challenge to support homeostatic systems
essential to life (311, 312). Allostatic load summarizes the
cumulative impact of physiological wear and tear related to adaptations that predispose individuals to disease
(311). McEwen (313) described four maladaptive stress
patterns, which can occur alone or in combination: 1) excessive and repeated stimulation over time; 2) inability to
habituate to stressful stimuli; 3) inability to sufficiently
recover from heightened, activated responses; and 4)
inadequate response of a primary system, resulting in
compensatory mechanisms. The biological systems involved in adaptation that mediate the link between
stress and physiological functions are the hypothalamic-pituitary-adrenal axis, autonomic nervous system,
and immune system (311, 314). Measuring mediators
and/or outcomes related to alterations in these systems
reflects potential indices of physiological dysfunction
(311, 314). Researchers developed allostatic load scores
to estimate stress-induced physiological dysfunction by
summing the number of parameters for which individuals fall into the highest-risk quartile (311). Examples
of physiological parameters include cardiovascular
(systolic and diastolic blood pressure, cholesterol measures), metabolic (WC, HbA1c), hypothalamic-pituitary-adrenal axis (dehydroepiandrosterone sulfate,
cortisol), autonomic function (heart rate, urinary cat-
FIG. 3. Conceptual framework model for disparities in endocrine disorders. [Adapted from
R. B. Warnecke et al.: Approaching health disparities from a population perspective: the
National Institutes of Health Centers for Population Health and Health Disparities. Am J Public
Health 98:1608 –1615, 2008 (308), with permission. © American Public Health Association.
explain disparities in rates of type 2 diabetes (310) or thyroid disease, as we already reviewed. Biological responses
include poor glycemic control, obesity, hyperlipidemia,
poor blood pressure control, and longer-term complications of diabetes, including CVD, renal disease, and
stroke. Among the individual behaviors that influence disease risk or outcomes are diet, tobacco and alcohol use,
medication adherence, and disease self-management.
Individual demographic characteristics affect the individual’s capacity to respond to environmental challenges and include factors such as age, race/ethnicity,
language, literacy, cultural beliefs, education, income,
social support, and acculturation.
The intermediate determinants of health include
neighborhood- or community-level physical and social
environments, as well as the health care delivery environment. The physical context includes factors such as
neighborhood disorder and accessible recreational facilities and healthy foods. The social context includes
factors that may mitigate or intensify distal effects, such
as community-level poverty, resources, or social interactions; and the health care delivery context includes
access to care, quality of care, provider characteristics,
and aspects of the patient-provider relationship. We hypothesize these intermediate determinants to be the
mechanism through which the distal social and policy
factors influence individual behavior. Finally, the distal
factors include population social conditions (e.g. poverty, discrimination, prejudice), policies that affect so-
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Endocrine Health Disparities
echolamines), and immune function (cytokines, albumin) (311). In the MacArthur studies, high allostatic
load scores predicted incident CVD and all-cause mortality, independent of socioeconomic status and baseline morbidity (449, 450).
Several studies have examined race/ethnic and sex differences in allostatic load using data from NHANES.
NHB populations have significantly higher allostatic load
than NHW populations, after adjusting for socioeconomic status, with NHB women being most adversely affected (315–317). In one study, NHB women 40 – 49 yr
old had allostatic load scores 1.14 times greater than
NHW women 50 –59 yr old, suggesting adverse physiological effects in NHB women at a younger age (315).
Allostatic load in Hispanic-Americans depends on their
country of nativity. U.S.-born Mexican-Americans have
higher allostatic load scores than those born in Mexico
who subsequently immigrate to the United States (315,
318, 319), suggesting that acculturation may be associated with maladaptation to stressors; however, in one
study that measured differences in acculturation, these differences did not explain this disparate association. Recent
results from the Boston Puerto Rican Health Study significantly associated increasing categories of allostatic load
with several endocrine disorders, including abdominal
obesity and diabetes (320). Thus, differences in stress exposure and subsequent higher allostatic load in minorities,
related to socioeconomic status, acculturation, physical or
social environment, or chronic discrimination, might contribute to disparities in development of and outcomes for
endocrine disorders and requires further study.
Proximate factors: individual demographic
characteristics
Individual risk behaviors
Most agree that racial/ethnic and socioeconomic differences in health behaviors and self-care behaviors are a
main reason for disparities in health among adults with
diabetes (321). A complex range of self-care behaviors is
required to manage diabetes, among them dietary restrictions, regular exercise, adherence to and management of
multiple medications and dosing schedules, SMBG, periodic examination of the feet, and maintaining glycemic
control during intercurrent illness. Among adults with diabetes, studies associate minority race/ethnicity, low income, less education, and living in a poverty area with
higher rates of smoking (322–325), lower rates of SMBG
(326 –329), less vigorous exercise (322, 324, 330, 331),
poorer adherence to medications (332), and underuse of
recommended preventive health screening (333, 334).
Although one study (332) suggested that an important
mediator of the association between minority status and
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poorer glycemic control was poorer adherence to medication among NHBs and Hispanic-Americans, other research did not find this association between race and adherence (335). The lack of consistent findings suggests that
more work is needed to understand the causal pathways
underlying disparities in diabetes control.
Socioeconomic status
The well-known socioeconomic gradient in health certainly applies to diabetes on the individual and aggregate
level. Diabetes incidence data using the NHANES I Epidemiologic Follow-Up Study (1971–1992), showed a
strong inverse relationship with income, education, and
occupational status (336). Women who had more than 16
yr of education had a much lower risk for incident diabetes
compared with women who had less than 9 yr of education
(HR, 0.26; 95% CI, 0.13– 0.54). Among men, these trends
were evident but much less consistent. A meta-analysis of
21 studies showed that there is an increased risk of type 2
diabetes when comparing the lowest to the highest groups
in terms of education (RR ⫽ 1.41), occupation (RR ⫽
1.31), and income (RR ⫽ 1.40) (337). Likewise, national
data from the National Health Interview Survey showed
that, among people with diabetes, CVD prevalence was
higher, and all-cause mortality was 28% higher for those
with the lowest educational levels, compared with the
highest (338, 339). As already reviewed, lower socioeconomic status is also associated with a higher prevalence
of gestational diabetes (144). Socioeconomic status is
also associated with poor metabolic control in non-U.S.
countries. In Germany, the United Kingdom, and Spain,
individuals of lower socioeconomic status had higher
HbA1c, worse dyslipidemia, and higher rates of obesity
(340). Even independent of race, sex, and lifestyle factors, allostatic load is negatively associated with education and income, suggesting one potential mechanism
through which socioeconomic stress may increase metabolic disease risk (341).
Language barriers
Spanish-speaking Hispanics in the United States are less
likely than those who speak English to have a regular
source of care. They also receive less screening, report
lower rates of use of preventive services (342–344), and
are less satisfied with their health care (345), when compared with either NHWs or English-speaking Latinos. In
a study of a managed care population, patients with type
2 diabetes who reported difficulty with English monitored
their blood sugars less frequently than persons with no
language barriers (328).
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Social support and competing demands for time
Evidence is strong for a relationship between having
supportive social ties and better physical and mental
health (346) and, conversely, between social isolation and
greater morbidity and mortality (347). In the aggregate,
among persons with diabetes, studies have associated
higher levels of social support with better self-management, including adherence to recommended diet and exercise regimens, better glycemic control (348), and less
vulnerability to social stressors (349). Social support may
be particularly important for minority or low-income patients with diabetes. For example, NHBs with diabetes rely
more heavily on informal social networks to meet their
disease management needs (348), and poorer persons are
more likely to be socially isolated and to have fewer supportive social ties (350). Although empiric data are sparse
on how social support influences health outcomes for persons with diabetes, better self-management skills and improved access (through the health-seeking behaviors of the
persons themselves or their social network) and quality
(because of better communication with physicians) likely
play a role. On the other hand, social ties may result in
detrimental effects, as in the case of obligations that result
in financial expenditures, demands on time, and criticism
from social contacts (351). In addition, the health care
needs of persons who are caregivers for disabled elders can
compete with the physical and emotional needs of their
dependents, and these caregivers often fail to obtain adequate health care for themselves (352). These effects are
likely accentuated among the poor, NHBs, and possibly
other ethnic minorities, among whom the caregiver role is
common (353).
Health beliefs and perceptions
Race/ethnic differences in self-perception may lead to
disparities in endocrine disorders. This has been studied
most in the area of obesity and how it relates to body
image. In NHBs, there is less stigma associated with overweight and obesity, and prior studies show that NHB
women accept a body image considered overweight and
larger than that preferred by NHW women (354, 355).
Despite the higher prevalence of overweight and obesity in
NHB women, they report higher levels of body image satisfaction than NHW women (356, 357). This comfort
with a larger body size may increase the risk for obesityrelated disorders and create a disconnect between patients
and physicians regarding an ideal body weight.
Intermediate factors: physical and social contexts
Neighborhood socioeconomic and physical
characteristics
The medical community increasingly recognizes the
contribution of factors above and beyond individual be-
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havior as major contributors to health. An explosion of
research within the field of public health has investigated
how these upstream factors might contribute to diabetes
and related conditions. For social inequalities on a macrolevel, there is solid evidence that energy-dense foods cost
less, and that healthier diets, consumed more by affluent
persons, cost more (358). For example, the energy cost of
fresh produce is 10 times as much as that of vegetable oils
and sugar. Studies have consistently shown that minority
and disadvantaged populations live in inferior neighborhood environments with respect to food stores, places to
exercise, esthetic problems (such as vacant houses), and
traffic or crime-related safety. Studies have shown that
these inferior neighborhood environments are independently associated with individuals’ diet quality and with
walking and exercise behaviors (359, 360).
Studies directly associate disadvantaged and minority
neighborhoods with poor health outcomes through a
number of different pathways, including aspects of the
physical environment such as lack of healthy food stores
and places to exercise, and aspects of the social environment including psychosocial stressors related to crime and
limited social cohesion (359, 360). Studies have also associated lower neighborhood socioeconomic status with
worse allostatic load. One study showed how this association is stronger in NHBs than NHWs and MexicanAmericans. Overall, communities with lower socioeconomic status have fewer resources available that promote
healthy behaviors and facilitate good health. The last 15 yr
of research on neighborhood environments has focused
mostly on obesity or behaviors that influence obesity (diet
and physical activity) (361). Overall, studies show consistent findings for the food environment, demonstrating
that poor access to supermarkets was associated with
higher BMI (362). For physical activity, studies associated
greater neighborhood walkability and better access to recreational resources with lower BMI (363). Review articles
done specifically for NHB (359) and disadvantaged (360)
populations show consistent results with the general population, but comment that more research is needed. These
review articles also provide evidence for intervention targets that might be useful for reducing health disparities
in these populations. Although sparse, there is some
evidence linking the neighborhood environment directly to clinical outcome such as diabetes. Two studies
from the Multi-Ethnic Study of Atherosclerosis associated better neighborhood access to physical activity and
food resources with lower insulin resistance (364) and
type 2 diabetes (365). There are also studies that link the
perception of neighborhood problems among people
with diabetes with more smoking, physical inactivity,
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and poorer control of blood pressure, after adjusting for
individual factors (366).
Poor persons, particularly those with a chronic condition like diabetes, are more likely to experience multiple
dimensions of neighborhood disadvantage, and management of a chronic disease may be much more difficult in
low socioeconomic status areas (367). Many believe that
several community-level characteristics contribute to disparities in diabetes management. Price disincentives to eating healthy food are greater in poorer than in wealthier
neighborhoods (368), and low-income communities have
fewer supermarkets than more affluent neighborhoods
(369, 370). Moreover, access to foods recommended for
adults with diabetes (e.g. fresh fruits and vegetables, whole
grains, diet sodas, and low-fat milk), is limited in lowincome and predominantly minority areas (371, 372).
Ease of access to parks and recreational facilities and the
safety of the neighborhood may influence the ability or
willingness of persons with diabetes to engage in regular
exercise, another important strategy in diabetes management. Transportation may be an underappreciated element in managing diabetes and other endocrine disorders
because lack of transportation is an important barrier to
receiving appropriate health services (373) and may also
influence other environmental factors, such as access to
food, health care, and social networks (374).
Social relationships within communities
Much of the research conducted on the social environment has demonstrated the benefits of social cohesion and
social capital in neighborhoods. For example, collective
efficacy is the willingness of people to intervene for the
good of the community, and the linkage of mutual trust
within a community (375). Studies have linked collective
efficacy to better neighborhood outcomes including lower
crime, as well as better health outcomes such as rates of
overweight and obesity and overall mortality (375). Another study by Christakis and Fowler (376) looked at social networks and found not only that obese persons were
in discernible clusters, but also that a person’s chance of
becoming obese was 57% greater if he or she had a friend
who became obese in a given time interval. Furthermore,
an experimental study that randomized public housing
residents to receive vouchers to move to lower poverty
areas found that these respondents reported less neighborhood poverty, more collective efficacy, and lower rates
of obesity and diabetes (377).
Intermediate factors: health care system context
Characteristics of the health care system
Because racial/ethnic minorities may be clustered in certain health care systems (378) or within a few facilities
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associated with a health care network, the kinds of systems
in which minority patients receive their care might explain
disparities in care and outcomes for diabetes and endocrine disorders (379, 380).
Health care organizations can promote access (for example, by reducing financial barriers to care), and many
features of health care organizations can improve diabetes
outcomes and/or reduce diabetes disparities (381–383)
(see Interventions Shown to Be Effective in Reducing Disparities in Clinical Processes and Outcomes: Diabetes as
an Exemplar Condition). Health system factors, however,
also have the potential to negatively affect access, process,
and health behaviors and to worsen health outcomes, particularly for minority or socioeconomically disadvantaged
patients. Management of specialty referrals through a
gatekeeper may lead to more appropriate referral patterns
(384, 385), but restrictions on referrals to specialists that
are differentially applied to patients who are poorer, lesseducated, or have lower literacy levels may adversely influence health. Furthermore, although health care organizations may promote intensive diabetes management,
data from two recent studies found little evidence that
obtaining care in health care systems with more intensive
diabetes management (e.g. through referral systems, diabetes registries, or provider feedback) or through intensive
quality improvement efforts, reduced racial/ethnic or socioeconomic disparities in quality of care. This suggests
that the reduction of many disparities requires more tailored approaches (386, 387).
Some financial and organizational arrangements may
pose greater obstacles for persons of lower socioeconomic
status. Many studies have focused on patient copayments,
and low-income persons might be particularly sensitive to
even modest changes in cost sharing because they spend a
higher proportion of their income on out-of-pocket expenses than do higher-income enrollees (388). Specifically, studies have associated the introduction of new or
higher copayments for glucometer strips with lower rates
of SMBG among lower income patients (325, 328).
Financial incentives for physicians and physician organizations may affect clinical outcomes, and these effects
may be more pronounced for low socioeconomic status
patients. For example, more-educated patients and those
who do not face language barriers may be more effective
at negotiating with clinicians or health plans to have their
needs met in the face of potential disincentives to provide
care (389); and wealthier patients have a greater ability to
purchase alternate health care. Recent evidence also suggests that physician organizations located in lower socioeconomic status communities may receive lower pay-forperformance incentive bonuses than those in wealthier
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
communities, even after adjusting for other characteristics
of the organization (390).
Health care access and health insurance
Inadequate access to care (e.g. due to a lack of health
insurance) may be an important contributor to the current
state of disparities in outcomes for endocrine disorders.
Diabetic adults with only a primary or secondary education have more contacts with their general practitioner
and dieticians but fewer visits with specialists (e.g. endocrinologists) or diabetes nurses, and they undergo fewer
assessments of their body weight and receive fewer influenza vaccinations (391).
For persons with diabetes, access to health insurance is
important for the receipt of high-quality care (326, 392,
393). Although over 90% of patients with diabetes have
some form of health insurance (394, 395), a much greater
proportion of minorities than NHWs with diabetes lacked
insurance (394, 395). Compared to those with insurance,
uninsured adults with diabetes receive fewer recommended processes of care, including dilated eye examinations, foot examinations, and other preventive health care
services (326); have poorer intermediate and longer-term
outcomes, such as poorer glycemic control (396); and have
higher odds of developing diabetic eye disease (397).
Among Latinos with diabetes, studies have shown that
lack of insurance results in higher rates of microvascular
complications (398). Similarly, thyroid cancer patients
seen at a public hospital were significantly less likely to
have health insurance and more likely to present with advanced thyroid cancer compared with those seen at a university hospital (225).
The persistence of some disparities, even in managed
care settings (378) and in countries with universal health
insurance coverage (329, 331, 399 – 401), suggests that
neither access to care nor having insurance is sufficient to
improve diabetes outcomes. In a meta-analysis of studies
conducted in the Organization for Economic Cooperation
and Development countries with universal health care systems, certain race/ethnic groups were not adequately controlled (340). In New Zealand, Europeans had better glycemic control than other ethnic groups, and in the United
Kingdom, non-European women with gestational diabetes had worse glycemic control than their European counterparts (340).
Quality of care
Studies have associated race and ethnicity (378, 395,
402, 403), income (404 – 407), and education (326, 408)
with gradients in processes of diabetes care. In one national study, minorities with diabetes were less likely to
have a lipid test and a dilated ophthalmological examina-
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tion than were NHWs (409). In contrast, another study
found that ethnic disparities in quality and access to care
can be substantially reduced, if not eliminated, within
health care organizations that provide uniform care to
large populations (403). Still, although there have been
exceptions, reports from diverse settings indicate that the
quality of diabetes care for socially disadvantaged persons
is inferior to that of more affluent persons (326, 407, 410).
Even in countries with universal health care, race/ethnic
inequalities exist in the quality of care that patients with
diabetes receive. Diabetic individuals in the United Kingdom living in high immigrant areas were less likely to be
prescribed oral diabetic agents (340). In New Zealand,
“other Asians” were less likely to be prescribed aspirin,
antihypertensives, or insulin compared with Europeans,
and Maoris and Pacific Islanders were less likely treated
with diet changes and statins compared with Europeans
(340). Studies have been mixed regarding the use of
preventive services among minority populations in the
Organization for Economic Cooperation and Development countries, with some showing great use of ophthalmological screening and preventive services (e.g.
black Africans and Afro-Caribbeans vs. Europeans in
the United Kingdom, and aboriginals vs. non-aboriginals in Canada), and others showing less use in minority
populations (e.g. minority populations vs. Europeans in
the United Kingdom) (340).
Similarly, minority patients with other endocrine disorders receive lower quality of care. Minority patients
with thyroid cancer receive inadequate surgical care (4)
and are less likely to be operated on by a high-volume,
experienced surgeon (226), contributing to poorer clinical
outcomes. Among women who meet DXA screening criteria for osteoporosis, NHB women are significantly less
likely to be referred for screening, less likely to have osteoporosis mentioned in their medical record, and less
likely to have their physicians recommend calcium or vitamin D supplementation (289). NHB women are also less
likely to be prescribed osteoporosis medications (288).
Provider characteristics and patient-provider
relationships
Patient-provider communication. Effective communication between patients and providers (411, 412) and shared
decision-making (413, 414) positively influence health behaviors and the process and outcomes of care for persons
with diabetes. NHB patients experience lower quality patient-provider communication. Although evidence links
patients’ ratings of providers’ general and diabetes-specific communication with self-care for diabetes (415, 416),
communication is more likely to be suboptimal for lower
socioeconomic status patients. For example, physicians
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Endocrine Health Disparities
are more likely to adopt a more directive, less participatory
approach with less-educated patients, who are then less
likely to have their expectations met (344).
Languagebarriersandhealthliteracyandnumeracy.Language barriers appear to influence diabetes self-care behaviors and outcomes, and a provider’s ability to successfully communicate with patients may counter the effects of
inadequate English proficiency and poor comprehension
of verbal instructions (417). Health literacy is “the ability
to read and comprehend prescription bottles, appointment slips, and the other essential health-related materials
required to successfully function as a patient” (418). Persons with type 2 diabetes who have low functional health
literacy are less likely to know the symptoms of hypoglycemia, have more difficulty understanding physicians’ explanations, have lower rates of shared decision-making,
and have poorer glycemic control (389, 419 – 421). Although low health literacy poses risks for health outcomes
for patients with diabetes, there is recent evidence to suggest that using strategies such as the “teach-back” technique, in which a patient repeats in his or her own words
what needs to be done once he or she leaves the clinician’s
office, can increase patients’ understanding of the medical
information conveyed despite their low literacy (422).
Poor health numeracy is also an important contributor
to race/ethnic disparities in glycemic control. Diabetesrelated numeracy assesses calculation, interpretation of
tables, graphs, or figures, and application of numeracy
skills to solve problems and perform diabetes self-management care (423). Low diabetes-related numeracy is associated with NHB race and poor glycemic control, regardless of race. Adjusting for diabetes-related numeracy
explained the difference in poorer glycemic control in
NHBs compared with NHWs. Interventions to improve
numeracy may reduce race/ethnic disparities in diabetes
outcomes (423).
Discrimination and trust in health care providers. Stereotypes about the behaviors or health of low socioeconomic
status or disadvantaged minority patients and provider
bias against these patients, even when unintentional or
subtle, may influence the provider’s willingness or ability
to provide counseling on healthy behaviors and disease
management, reinforce the tendency of patients of low
socioeconomic status not to engage in these behaviors,
lead to differential treatment of minority patients, and
affect patient health through internalized racism (3, 424 –
426). These attitudes not only interfere with the provision
of care but may also reduce a patient’s confidence and
self-efficacy, further undermining treatment, behavior,
and adherence (427).
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In one study, 8% of minority patients with diabetes
reported discrimination by their doctors or the office staff
due to their race, education, or income, and patients who
reported racial discrimination in health care settings also
reported worse health and glycemic control (428). In another study, however, researchers eliminated the association between discrimination and poor glycemic control
after adjustment for health status and sociodemographic
factors such as race/ethnicity and insurance. Studies have
linked the provision of culturally competent care with better rapport, trust, and exchange of information (417). Patients’ and providers’ attitudes may influence each other
reciprocally; if patients convey mistrust, demonstrate
poor adherence, and refuse treatment, providers are likely
to become less engaged in the treatment process and less
clinically aggressive (3).
Distal factors: policies and social conditions
A broad range of federal, state, health care system, and
clinical policies affect patients with diabetes, their clinicians, the hospitals and clinics where they seek care, their
insurers, and the public health systems that implement
diabetes prevention and control (429). For example, at the
clinic level, a policy that required office staff to request
that patients with diabetes remove their shoes in the examination room increased rates of foot exams by 60%
(430). At the health plan or provider group level, implementation of the six integrated elements of the “Chronic
Care Model” (self-management support, delivery system
design, decision support, clinical information systems,
structured health care organization, and community interactions) has improved processes of care, outcomes, and
provider satisfaction (431– 433). The most widely studied
policies are related to reimbursement. Federal policies,
such as the Balanced Budget Act in 1997 and the Medicare
Modernization Act in 2003, expanded coverage for medications and for care outside the hospital setting. For patients with diabetes, policies such as these resulted in enhanced reimbursement for diabetes self-management
training, and higher levels of coverage for prescription
medications, diabetes supplies, and prescription medications. As discussed in the Osteoporosis and Fracture Risk
section, the Bone Mass Measurement Act passed by Congress in 1997 provided DXA reimbursement for qualified
Medicare beneficiaries; however, only a small proportion
of eligible patients take advantage of osteoporosis screening, especially NHBs (291). This suggests that having policies in place may not be entirely adequate to change
practice.
Health care is implementing a range of policies that may
have direct or indirect impact on diabetes outcomes. For
example, New York City’s “A1c Registry” requires man-
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datory reporting of HbA1c test results. We will need to
closely monitor the effect of this population-based registry
on provider and patient behavior and levels of glycemic
control (434). The Affordable Care Act, by improving
support for the patient-centered medical home model
(http://www.nachc.com/client/documents/CHCs%20ROI%
20final%2011%2015%20v.pdf and http://www.pcpcc.net/
joint-principles), has the potential to improve the quality of primary care and patient and provider experiences (437). The impact of the patient-centered medical home model on diabetes
processes and outcomes requires further study, particularly in
safety net settings, such as community clinics (http://www.
fqhcmedicalhome.com/demooverview.aspx and Ref. 439).
Policies that support the integration of community and health
care system interventions to address both the medical and nonmedical factors that contribute to diabetes risk and outcomes
might also be a promising approach to addressing health disparities (440). We need additional studies, however, to understand the impact of these new and emerging policies on diabetes
disparities.
Finally, social conditions can have a significant impact
on population-wide metabolic outcomes. Between 1989
and 1995, Cuba experienced a prolonged economic crisis
secondary to a significant reduction in imports, local fuel
supply, agricultural products, and many food items (441).
These changes led to decreased per capita daily energy
intake (from 2899 to 1863 calories) and increased walking
and cycling due to lack of public transportation (441).
During this period, there was a significant increase in the
percentage of physically active individuals and normalweight individuals and a significant decline in the percentage of overweight individuals (441). In addition, there
were significant declines in the deaths secondary to diabetes and CVD as well as all-cause mortality (441). These
data highlight the impact of social conditions on metabolic
disorders and suggest that population-wide approaches to
reducing caloric intake and increasing physical activity
might have beneficial effects.
Interventions Shown to Be Effective in
Reducing Disparities in Clinical Processes
and Outcomes: Diabetes as an Exemplar
Condition
A growing body of evidence identifies interventions that
reduce disparities in health care or improve the outcomes
of minority populations. Here, we summarize the literature on health care interventions to improve the care or
outcomes of racial/ethnic minorities with diabetes. We
chose diabetes because this condition captures the diverse
set of factors previously described in the conceptual model
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for disparities; because many interventions have attempted to reduce diabetes disparities; and finally because
most lessons from the diabetes literature are likely transferable to other endocrine conditions.
Health care can implement disparity interventions at
one or more levels of influence: patients, providers, microsystems (immediate health care environment and delivery team), health care organization, community, and
policy (442). A key maxim of implementation science is
that the local context is critical. Although it is possible to
draw general lessons from the literature, the translation of
these findings into real-world practice requires adaptation
to local culture, resources, incentives, patient preferences,
and provider buy-in.
Lessons from the diabetes disparities intervention
literature
Peek et al. (383) reviewed the diabetes disparities intervention literature between 1985 and 2006, and Baig et
al. (443) updated that review between 2006 and 2009.
These reviews summarize each individual study and have
found themes of successful interventions that target different levels of influence.
Patient
Successful interventions tended to leverage interpersonal connections such as face-to-face encounters, social
networks, family, peer support groups, and community
health workers, rather than technological, computerbased ties. Culturally tailored interventions were more effective than generic patient self-management education
and have resulted in improved glycemic control and diabetes-related knowledge (444).
Provider
Similarly to patients, interventions incorporating inperson feedback were more effective than computerized
decision-support reminders in changing provider behavior and improving diabetes outcomes. Cultural competency training for providers, combined with diabetes performance reports stratified by patient race/ethnicity, have
improved provider awareness of disparities, but not diabetes process and outcome measures (445).
Microsystem/health care organization
Care management interventions were effective. Key
components of these programs include patient education
that tackles barriers to adherence, ancillary services such
as laboratory testing or linkage to home health, and addressing fundamental problems like transportation to the
clinic. Also, when nurse and community health workers
managed patients with treatment algorithms or had phy-
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Endocrine Health Disparities
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TABLE 10. Summary recommendations for future research
Race/ethnic disparities
Diabetes mellitus
Future research needs: biological and clinical factors
Inclusion of specific ethnic subgroups in studies of diabetes
epidemiology and physiology.
Elucidate reasons for differences in diabetes prevalence and incidence
and glucose metabolism in Cuban, Central, and South Americans
compared to Mexican- and Puerto Rican-Americans.
Elucidate reasons for differences in diabetes prevalence and incidence
among different Asian-American subgroups and the contribution of
acculturation and immigrant status.
Elucidate other nonobesity contributors to the higher insulin resistance
seen in minority populations compared to NHWs because these
differences are independent of adiposity.
Basic science investigations needed to determine whether race/ethnic
differences in insulin signaling contribute to greater insulin
resistance in minority populations.
GWAS needed in minority populations
Design studies targeting perinatal prevention of fetal undernutrition and
fetal-maternal stress as a diabetes preventive strategy in NHBs.
Future research needs: nonbiological factors
Determination of the contribution of acculturation to obesity and
diabetes risk in Asian- and Hispanic-Americans.
Elucidation of diet, physical activity, and health behavior differences in
minority populations compared to NHWs and their contributions to
ethnic differences in diabetes risk.
Diabetes complications
Future research needs: epidemiology of complications
Epidemiological data summarizing prevalence and incidence of lower
extremity amputation and arterial disease in Asian-Americans.
Exploration of etiology of regional differences in diabetes and diabetes
complication rates in Native Americans.
Exploration of the etiology of heterogeneity in diabetes complications
among Asian-American subgroups.
Sex disparities
Future research needs
Determine whether the risk of type 2 diabetes
occurs at different BMI and WC thresholds
in NHB vs. NHW women.
Future research needs
Elucidation of the etiology for higher coronary
heart disease risk and lower peripheral arterial
disease risk in women compared to men with
diabetes.
Determination of reason for sex
differences on the effects of CVD risk
factors in different arterial beds
through basic science and clinical
research studies.
Studies of clinical and nonclinical contributors
to diabetic complications stratified by sex
and race/ethnicity, as suggested above.
Exploration of contributors to higher diabetes mortality in minority
populations compared to NHWs.
Future research needs: biological and clinical factors
Studies of prevalence and control of glycemic and cardiovascular risk
factors in minorities with diabetes mellitus.
Basic science, clinical, and population-based research studies to evaluate
multifaceted (glycemic and nonglycemic) causes of ethnic variations
in HbA1c, especially in Asian, Hispanic, and Native American
populations (analogous to studies comparing NHBs and NHWs).
Basic science and clinical research studies to examine the contribution of
low birth weight, fetal undernutrition, and fetal-maternal stress to
microvascular complications in NHBs with diabetes mellitus.
Basic science, clinical, and translation research studies to determine the
etiology of the survival advantage of NHBs on dialysis for diabetic
nephropathy, which may lead to better understanding of how to
improve survival in dialysis patients of other race/ethnicities.
Basic, clinical, and population-based research studies to determine the
contributors to the higher risk of microvascular but lower risk of
macrovascular complications among NHBs with diabetes.
Future research needs: nonbiological factors
Development of policies and interventions to remove barriers to selfmonitoring of blood glucose in ethnic minorities with diabetes mellitus.
(Continued)
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TABLE 10. Continued
Race/ethnic disparities
GDM
Future research needs: biological factors
Determine the prevalence of significant polymorphisms in the BetaGene
Study in other high-risk populations for GDM, especially AsianAmericans.
Examine gene-environment interactions with clinical factors—adiposity,
physical activity, and diet.
Future research needs: nonbiological factors
Determine contribution of social and economic factors to race/ethnic
disparities in GDM: socioeconomic status, mental stress, built
environment.
Examine the contribution of documented disparities in access to care in
women with prior GDM on screening for GDM and type 2 diabetes,
quality of care, and quality of life.
Metabolic syndrome
Future research needs
Determine whether current metabolic syndrome criteria similarly predict
type 2 diabetes and CVD in NHBs and NHWs.
Determine whether race/ethnic-specific cutoffs for TG in the metabolic
syndrome definition better identify NHBs at risk for metabolic
disorders.
Determine whether race/ethnic-specific cutoffs for WC in the metabolic
syndrome definition better identify Asian-Americans at risk for
metabolic disorders.
Thyroid disorders
Future research needs
Determine whether the lower TSH in NHBs translates into bone and
cardiac effects compared to NHWs.
Determine whether the lower iodine concentration in NHBs is clinically
significant and contributes to development of goiter and
hypothyroidism.
Determine the etiology of differences in thyroid cancer incidence in
Asian-Americans based on country of origin and in Native Americans
based on region of residence in the U.S.
Develop interventions and policies to increase minority access to high
volume surgeons and earlier intervention in centers with endocrine
and surgical expertise.
Assess molecular pathways for thyroid cancer at a mutational level to
determine whether there are differences by race, which may suggest
different prognoses and targeted therapies.
Osteoporosis/metabolic bone disease
Future research needs
Determine non-BMD contributors to lower fracture rates in minority
women compared to NHWs.
Sex disparities
Future research needs
Determine whether race/ethnic-specific cutoffs
for WC in the metabolic syndrome definition
better identify NHB women at risk for
metabolic disorders.
Future research needs
Determine the etiology of the higher
prevalence and incidence of autoimmune
thyroid disease in women compared to men
through basic science and clinical research
studies.
Determine whether lifestyle interventions to
promote weight loss and physical activity in
obese women will lower the risk of thyroid
cancer.
Determine the etiology of compromised
thyroid cancer survival in men as targets for
future interventions.
Future research needs
Generate data on fracture rates, risk factors
for fracture, and incidence of disability and
morbidity associated with fracture in
minority men.
Vitamin D deficiency
Determine whether there are genetic factors or differences in cell signaling
that contribute to the higher BMD in certain minority populations
compared to NHBs.
Determine the etiology of the lower fracture risk in Asian-American
women compared to NHW women despite lower BMD.
Determine whether novel skeletal traits— bone size, bone geometry, hip
axis length— differentially predict fracture risk in NHW and minority
women compared to BMD.
(Continued)
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Endocrine Health Disparities
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TABLE 10. Continued
Race/ethnic disparities
Develop intervention strategies to preserve BMD in NHW women and
protect them from the osteoporotic fractures.
Determine why NHB women suffer higher mortality and disability after
fracture than NHW women.
Develop interventions strategies to increase osteoporosis screening,
diagnosis, and treatment in minority women to prevent fractures
and their associated morbidities.
Develop intervention strategies to increase vitamin D supplementation in
NHBs.
Conduct basic and translation science studies to determine whether race/
ethnic differences in molecular signaling or vitamin D metabolism
contribute to lower levels in NHBs.
Determine the prevalence of vitamin D deficiency in minority populations,
particularly Asian and Native Americans.
sician support, they were more effective in improving processes and outcomes than if they served solely as care managers. Disease management has improved diabetes care
and outcomes. Components of disease management include: 1) identification of the diabetes population, for example through patient registries; 2) practice guidelines; 3)
use of health information technology to track and monitor
patients; and 4) care management. Although not specifically focused on disparities or minority populations, the
Centers for Disease Control and Prevention’s systematic
reviews of diabetes case management and disease management from 2002 also support the use of these two interventions
(http://www.thecommunityguide.org/diabetes/
casemgmt.html and http://www.thecommunityguide.org/
diabetes/diseasemgmt.html).
Community/Health Care System
A Centers for Disease Control and Prevention REACH
2010 initiative in Charleston and Georgetown, South Carolina, that integrated community and health care interventions, is one of the few efforts that not only improved
minority health care, but also reduced racial and ethnic
disparities in care (9). This ambitious initiative included
patient education and empowerment, community coalition building and advocacy, community health workers,
provider audit and feedback, quality improvement, and
case management. An intervention on the south side of
Chicago incorporating culturally tailored patient education and shared decision-making, a quality improvement
collaborative, provider training in behavioral change, and
community partnerships shows early signs of improved
diabetes care and outcomes (440). Such combined community health care system approaches have been relatively
uncommon, but are likely to increase with the emergence
of policies incentivizing global payment approaches, including accountable care organizations and bundled episodes of payment.
Sex disparities
Policy
Studies are lacking that examine policies to reduce diabetes disparities such as financial incentives (10). A payfor-performance scheme introduced into United Kingdom
primary care practices improved outcomes for all ethnic
groups, but widened some disparities (11). However, it is
difficult to make global conclusions about pay-for-performance because schemes can vary by factors such as the
amount of the incentive, whether the individual provider
or group is incentivized, whether payment is based upon
attaining an absolute threshold of performance or relative
improvement, and whether any safeguards are implemented such as rules to discourage cherry picking of wellinsured, relatively healthy, advantaged patients.
Lessons from the general disparities intervention
literature
The Robert Wood Johnson Foundation Finding Answers: Disparities Research for Change Program found six
cross-cutting themes of successful disparity interventions
based on 12 systematic reviews of conditions such as
CVD, depression, diabetes, and asthma (12). These
themes are: 1) target multiple barriers a patient faces
rather than rely on a single solution; 2) culturally tailor the
intervention; 3) use multidisciplinary teams; 4) employ
interactive, skills-based patient training rather than passive learning approaches; 5) use patient navigators who
can help patients work their way through the medical system; and 6) involve family and community. These themes
emphasize a comprehensive, tailored approach to addressing the multiple factors impacting disparities.
A roadmap for reducing racial and ethnic
disparities in health care
For a disparity intervention to be successfully implemented, health care providers, staff, and administrators
must view the intervention within a wider roadmap of the
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
process for improving quality of care and reducing disparities (12). The roadmap draws upon key principles of
implementation science and translational research:
1) Recognize disparities and commit to reducing them.
Create readiness to change on the part of the individual provider and organization. Raise awareness
using cultural competency training and individual
provider performance data stratified by patient
race/ethnicity.
2) Implement a basic quality improvement structure
and process.
3) Make equity an integral component of quality improvement efforts. Do not marginalize disparity intervention efforts.
4) Design the intervention(s). Adapt the intervention(s)
to the local environment.
5) Implement, evaluate, and adjust the intervention(s).
Revise interventions after pilot testing.
6) Sustain the intervention(s). Institutionalize the intervention(s) into standard practice, and align incentives appropriately.
Conclusion
We summarized important areas for future research in
areas of race/ethnic and sex disparities in endocrine disorders based on our literature review for this statement in
Table 10. We also summarize in Table 11 areas for future
research to address race/ethnic disparities in diabetes generated from the 2011 Strategic Planning Report of the
Diabetes Mellitus Interagency Coordinating Committee
(18, 19) that supplement those highlighted by our review.
Several important themes emerged in examining our current understanding of disparities in endocrine disorders.
Compared with NHW populations, there are certain disorders for which NHB populations have a lower incidence
(e.g. macrovascular complications of diabetes mellitus
and osteoporotic fractures) or a similar incidence (e.g. thyroid cancer); however, once they have the disorder, NHBs
have worse outcomes and higher mortality. This is likely
related to inadequate access to high-quality health care
among minority populations. In contrast, NHBs with diabetic nephropathy have lower mortality on dialysis than
NHWs, despite a higher incidence of ESRD. Understanding the factors contributing to better survival will be beneficial in extending dialysis survival for other race/ethnic
groups. Although osteoporotic fractures are more common in NHW women, preventive interventions should
target all race/ethnic groups to reduce the morbidity and
mortality associated with fractures. In addition to exploring the etiology for these disparities in clinical, population-
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TABLE 11. Research needs related to reducing
disparities in diabetes and diabetes complications from
the 2011 Diabetes Mellitus Interagency Coordinating
Committee
Diabetes mellitus
Identify racial and ethnic differences in the interactions
among antenatal care, diet, gestational glycemic burden,
and other aspects of the intrauterine environment, and the
risk of diabetes and obesity in childhood, adolescence, and
adulthood.
Determine what behavioral strategies work well to promote
and sustain effective lifestyle change in minority individuals
at high risk for developing diabetes.
Determine what behavioral strategies are effective in
promoting and sustaining adherence to diabetes treatment
regimens in individuals belonging to racial and ethnic
minority groups, to improve health outcomes.
Determine how the outcomes of the Diabetes Prevention
Program can be translated in diverse settings and
populations to prevent type 2 diabetes in youth and adults.
Determine the best approaches to optimize cardiometabolic
risk reduction in diverse populations with prediabetes or
type 2 diabetes.
Determine health care interventions that are effective at
reducing disparities in diabetes outcomes.
Determine when culturally tailored interventions are
necessary and more effective, as opposed to using more
general interventions, in reducing health disparities in
diabetes outcomes.
Determine how health communication science can be
harnessed for the reduction of health disparities in the
prevention and control of diabetes.
Determine how multilevel interventions, combining policy/
marketing, community, organization, delivery system,
provider, and patient/family components, can be
implemented and sustained to improve diabetes care and
outcomes.
Diabetes complications
Identify nontraditional biological risk factors that contribute
to underlying race/ethnic disparities in the development of
diabetes and its complications.
Determine the ⬙nonbiological⬙ (i.e. environmental, social,
cultural, and economic) factors across the lifespan that
affect diabetes prevalence and progression to
complications in different ethnic and racial groups.
Develop novel interventions to address the racial/ethnic
disparities in diabetes incidence, complication rates, and
mortality, and that take into account pharmacogenomics,
environmental, social, cultural, and economic factors.
Reproduced from two chapters in Complete Diabetes Research
Strategic Plan (http://www2.niddk.nih.gov/AboutNIDDK/ReportsAnd
StrategicPlanning/DiabetesPlan/PlanPosting.htm): Special Needs for
Special Populations (18) and Clinical Research to Practice: Translational
Research (19).
based, and health services research studies, basic science
and translational studies are also needed to explore underlying molecular mechanisms that may contribute to
disparities.
Obesity is an important contributor, not only to diabetes risk in minority populations, but also to sex disparities in thyroid cancer, which is more common in women.
This suggests that population interventions targeting
weight loss may have a favorable impact, even on nondiabetes-related endocrine disorders. Our statement also
highlights important implications regarding the definition
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Endocrine Health Disparities
of obesity in different race/ethnic groups. Fat distribution
is an important determinant of risk of metabolic disorders
such as type 2 diabetes and CVD, and there is evidence that
current cut-points for WC may underestimate disease risk
in Asian-Americans and overestimate disease risk on NHB
women. We need future studies to define ethnic-specific
cut-points for central obesity. Although we did not address obesity as a stand-alone disorder in this statement,
there is growing understanding of the neuroendocrine regulation of appetite and energy expenditure that contribute
to obesity (435); however, basic science and translational
studies are needed to determine whether these mechanisms
differ by race/ethnicity.
Sex disparities exist in certain endocrine disorders, with
autoimmune thyroid disease and cardiovascular complications of diabetes being more common in women than
men. The etiology of these sex differences remains unclear
and warrants further basic and clinical research. NHW
females suffer osteoporotic fractures more frequently than
their male counterparts; however, data on the prevalence
and incidence of osteoporotic fractures in minority men
are lacking, suggesting a need for further investigation
given the aging of our population.
A major gap in our current understanding of race/ethnic disparities in endocrine disorders is a failure of most
studies to specify Hispanic-American and Asian-American subgroups. In this statement, we have attempted to
specify ethnic subgroups where they were identified in
certain studies; however, the majority of studies did not
clearly define subgroups. Where these data are available,
there are clear ethnic-specific differences within Hispanic
and Asian subgroups, particularly related to diabetes and
obesity risk. Thus, it is imperative that future studies accurately identify ethnic subgroups. In general, except for
diabetes, there are few data on endocrine disorders in Native Americans and Alaska Natives, an important population for future research as well.
For the endocrine disorders discussed in this statement,
there is little evidence that genetic differences are a significant contributor to race/ethnic disparities; however, there
is likely significant heterogeneity and admixture among
populations, which may mask genetic differences in
GWAS studies. As recently reviewed, however, there are
emerging techniques to overcome these challenges in performing GWAS studies in minority populations (436). Future genetic studies should incorporate ancestral markers
to account for admixture and more specifically address the
contribution of race/ethnicity to disease risk and disparities. There is a paucity of data on race/ethnic differences in
responses to various treatments for endocrine disorders,
and determining whether these differences exist will allow
us to implement more patient-specific treatment regimens.
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
Our improved awareness and knowledge of interventions regarding disparities in diabetes needs to be expanded to other endocrine disorders for which race/ethnic
disparities exist. Specifically, it is important to study
whether social determinants of disease presented in our
health disparities framework, specifically the physical and
community context, are important contributors to disparities in vitamin D deficiency and poor outcomes after thyroid cancer diagnosis and osteoporotic fractures in minority populations. In the field of diabetes, multilevel
interventions targeting the patient, provider, health care
organization, community and health care system, and policy have reduced disparities in diabetes care and improved
quality of care. These successes can be used as a roadmap
for designing similar interventions to improve quality of
care for endocrine disorders where there is currently a
gap—specifically reducing mortality and improving outcomes after thyroid cancer treatment and osteoporotic
fractures. Understanding the biological, clinical, and nonclinical contributors to disparities in endocrine disorders
will allow the design of effective interventions to reduce
these disparities and improve public health.
Finally, according to a 2010 American Association of
Medical Colleges survey, just under 27% of our current
endocrine workforce is represented by minority physicians—16.9% Asian, 5.7% Hispanic, 3.6% NHB, and
0.3% Native American or Alaska Native— despite several
endocrine disorders having a higher burden in these populations (438). Increasing the representation of ethnic minorities in both the clinical and research sectors of endocrinology and diabetes will help to raise awareness and
prioritize research funding and policy development to reduce endocrine disparities.
Acknowledgments
We thank Jose Florez, M.D., and James Meigs, M.D., MPH, for
assistance in identifying appropriate literature for the diabetes
genetics section. We thank Eric Vohr for his technical writing and
organization expertise in finalizing our statement. We thank Ivy
Garner and Claire Twose for their expertise in information management and referencing assistance. We thank The Endocrine
Society and Loretta Doan, Ph.D., for their support and guidance
in preparing this statement.
Address all correspondence and requests for reprints to:
Dr. Sherita Hill Golden, Johns Hopkins University School of
Medicine, Division of Endocrinology and Metabolism, 1830
East Monument Street, Suite 333, Baltimore, Maryland
21287. E-mail: [email protected].
S.H.G. was supported by a Program Project Grant for the
Johns Hopkins Center to Eliminate Cardiovascular Health Disparities from the National Heart, Lung, and Blood Institute (P50
HL0105187). A.B. was supported by the National Center for
J Clin Endocrinol Metab, September 2012, 97(9):E1579 –E1639
Research Resources (Grant UL1RR033176), which is now at the
National Center for Advancing Translational Sciences (Grant
UL1TR000124). M.H.C. is supported by a Midcareer Investigator Award in Patient-Oriented Research (K24 DK071933)
from the National Institute of Diabetes, Digestive and Kidney
Diseases (NIDDK) and the Chicago Center for Diabetes Translation Research (P30 DK092949). C.K. is supported by Grants
R01DK083297 and K23DK071552 through the NIDDK. A.E.S.
is supported by the intramural program of NIDDK, National
Institutes of Health (NIH).
The content is solely the responsibility of the authors and does
not necessarily represent the official views of the NIH.
Disclosure Summary: S.H.G., A.B., T.L.G.-W., C.K., A.E.S.,
and B.A. have nothing to declare. J.A.C. receives consultant honorarium from Merck and Company, Inc., and Novartis. M.H.C.
receives grant funding from Merck Company Foundation. J.A.S.
received honorarium from Veracyte for a one time visiting
speaker engagement.
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