Download What Is the Influence of Weight Change on Forearm Bone Mineral

American Journal of Epidemiology
Copyright ª 2006 by the Johns Hopkins Bloomberg School of Public Health
All rights reserved; printed in U.S.A.
Vol. 164, No. 9
DOI: 10.1093/aje/kwj268
Advance Access publication August 3, 2006
Original Contribution
What Is the Influence of Weight Change on Forearm Bone Mineral Density in
Peri- and Postmenopausal Women? The Health Study of Nord-Trøndelag, Norway
Siri Forsmo1, Jørn Aaen2, Berit Schei1, and Arnulf Langhammer1
1
2
Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway.
Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
Received for publication April 18, 2005; accepted for publication April 5, 2006.
Weight loss in the elderly increases bone loss and the risk of fractures, especially at the hip and spine. The
influence of weight change on non-weight-bearing parts of the skeleton is less well known. The purpose of this
study was to investigate an association between weight change during the peri- and postmenopausal years and
forearm bone mineral density (BMD). Among 8,856 women aged 45–60 years attending the first Health Study of
Nord-Trøndelag, Norway (HUNT I, 1984–1986), a random sample of 2,795 women was invited to forearm densitometry (single x-ray absorptiometry technology) at HUNT II (1995–1997), after a mean period of 11.3 years. A total
of 2,005 women (mean age: 65.1 years) were eligible. The mean weight had increased 3.4 kg; the gain was greater
in the youngest women. A total of 382 women (19.1%) had lost and 1,331 women (66.3%) had gained weight.
Weight change explained little of the BMD variance, 0.7% and 0.4% for weight loss and weight gain, respectively.
Weight loss was an independent and statistically significant negative predictor of BMD, adjusted for body weight,
age, age at menopause, smoking, and ovarian hormone treatment, particularly among women with a baseline body
mass index greater than 25 kg/m2. No independent association between weight gain and forearm BMD was found.
body weight changes; bone density; cohort studies; densitometry; forearm; menopause; women
Abbreviations: BMD, bone mineral density; HUNT, the Health Study of Nord-Trøndelag, Norway.
decrease the risk of forearm fractures in elderly women
(5). In retrospective data, weight gain may even increase
the forearm fracture risk (10). Other studies have found no
association between weight change and wrist fractures (11).
As a non-weight-bearing part of the skeleton, the distal
radius is less influenced by changing mechanical strain due
to weight gain or loss. Body weight is, however, a strong and
positive predictor of forearm BMD in postmenopausal
women (12, 13). Whether there is an effect of weight change
on BMD, independent of body weight at baseline, or of
weight at follow-up is not known.
The distal forearm consists of both cortical and cancellous bone. At the ultradistal radius, cancellous bone makes
up to 80 percent of the total (14). Cancellous bone has
a higher metabolic activity than does cortical bone and is
Bone mineral density (BMD) is positively associated with
body weight, and low body weight is a risk factor of fractures. Weight loss has been shown to increase axillary bone
loss in the elderly (1). Weight loss also increases the risk of
fractures, especially at the hip (2–4). The bone effects of
intentional weight loss do not seem to differ from unintentional weight loss (5). Among important risk factors for forearm fractures are low BMD, a history of falling, and previous
fractures (6, 7). Very few lifestyle factors have been linked
to increased risk of wrist fractures; one exception is physical
activity that is positively associated with Colles’ fracture,
possibly because of the greater risk of falling (8, 9).
The influence of weight change on the risk of forearm
fractures in women is not clear. Self-reported weight gain
between the ages of 25 and 50 years has been found to
Correspondence to Dr. Siri Forsmo, Department of Public Health and General Practice, Medisinsk-teknisk senter, N-7489 Trondheim, Norway
(e-mail: [email protected]).
890
Am J Epidemiol 2006;164:890–897
Weight Change and Forearm Bone Density in Midlife Women
891
more influenced by factors such as menopause-related,
reduced-estrogen availability. More cancellous than cortical
bone mass is lost with aging (15, 16). Menopause is frequently associated with weight gain, although the physiologic causes are unclear. Weight gain is related partially to
the decline in sex hormones, partially to normal aging, and
partially to a more sedentary lifestyle (17–19). Menopause
may also be associated with changes in body composition
and fat distribution (20).
The average body weight in general has increased over
the last decades, especially in the United States, but also
worldwide, with increasing weight-related morbidity (21,
22). Data from Norway also show the same pattern (23).
On the other hand, weight loss is also associated with health
hazards, especially in an elderly population (24).
The purpose of this study was to investigate whether there
is an association between weight change and forearm BMD
during the peri- and postmenopausal years in a populationbased cohort of Norwegian women followed for more than
11 years. A more specific purpose was to explore whether
the association between weight gain or weight loss and forearm BMD was independent of body weight, or if the BMD
response to weight changes differed according to body size
at baseline.
Among all participants at HUNT I (baseline), a total of
8,856 women were aged 45–60 years, and their age-cohort
participation rate was 95.3 percent. Forearm bone density
was included at the physical examination in HUNT II for
preplanned subsets of the female population: 35 percent of
those aged 50–59 years, 5 percent of the age group 60–64
years, and 100 percent of the women aged 65 years or older.
This involved 2,795 women from the baseline cohort, of
whom 2,188 (78.3 percent) women attended and had forearm bone density measurements.
All women in this study were menopausal at their examination in HUNT II, and menopause was defined as no
menstrual bleeding within the last 12 months prior to the
examination. The lifestyle and reproductive variables used
for this study are based on the questionnaires used in HUNT
II, because no reproductive data were collected at baseline.
All women who reported treatment for hyper- or hypothyroidism, which totaled 174, were excluded from the analyses. Additional exclusions included the eight women for
whom weight and height data from one or both of the examinations were missing. Finally, three women had no
BMD data registered. These exclusions left 2,005 women
whose mean age was 65.1 (range: 55–71) years as eligible
for the analyses. No data were available with which to determine whether or not weight change between baseline and
follow-up was intentional.
MATERIALS AND METHODS
Bone mineral density
The Health Study of Nord-Trøndelag, Norway (HUNT),
is a multipurpose health survey focusing on the total population in the rural county of Nord-Trøndelag in mid-Norway
(25). The first data collection (HUNT I) took place between
1984 and 1986; the second observation (HUNT II) was during 1995–1997. On both occasions, all county citizens over
the age of 19 years were invited to participate, and the total
potential numbers included 85,100 and 92,936, respectively.
The overall participation rate was 88.1 percent in 1984–
1986 and 71.2 percent in 1995–1997, with somewhat better
rates for women than for men (26, 27).
With the exception of body weight and height that were
measured at both baseline and follow-up, all other variables
used for this analysis are from the follow-up study (HUNT
II). At both evaluations, data collection was carried out by
practically identical protocols. A comprehensive health questionnaire was sent by mail along with an invitation for a
general health examination (27). The questionnaire form included questions about general health and lifestyle, and the
participants were requested to bring it to the physical examination. A second, more detailed questionnaire concerning
illnesses, symptoms, medical treatment, socioeconomic factors, lifestyle and, for women, reproductive factors was distributed after the examination, to be completed at home and
returned by mail. The physical examinations at both HUNT I
and HUNT II involved measurements of blood pressure,
height, weight, and blood glucose. Height (in centimeters)
and weight (in kilograms) were measured without shoes and
with participants wearing only light clothing. Forearm densitometry was included as part of one of several substudies,
but only in HUNT II.
BMD (in grams/centimeter squared, transformed to milligrams/centimeter squared for these analyses) was measured at the distal forearm and ultradistal radius of the
nondominant arm by three different single energy x-ray
bone densitometers (DTX 100; Osteometer Meditech A/S,
Copenhagen, Denmark). Daily calibration of the densitometers was performed with equipment-specific phantoms. A
cross-calibration study among the three devices was carried
out and did not reveal significant differences. All sites for
measurement were manually controlled and corrected. The
densitometry procedure and quality assessments have been
described in detail previously (13, 28).
Am J Epidemiol 2006;164:890–897
Analysis
Weight change was calculated as the difference in kilograms between body weight at follow-up (HUNT II) and at
baseline (HUNT I). Negative values therefore indicated
weight loss, and positive values meant weight gain. The
choice to study change in body weight instead of change
in body weight for height (body mass index) or relative
weight change (percentage) was based on the fact that
BMD is more strongly related to absolute weight than to
other anthropometric measures. This was confirmed in preliminary analyses and is in accordance with other studies
(12). A change in weight of 1-kg gain or loss was defined as
stable body weight. For most purposes, weight change was
stratified in weight loss, stable weight, and weight gain. For
some of the bivariate analyses, however, weight change was
categorized into five groups: weight loss; stable weight; and
weight gain of 1.1–4.0, 4.1–7.0, and >7.0 kg. These
892 Forsmo et al.
cutpoints were chosen because they provided weight change
groups with adequate numbers for stratified analyses. Body
mass index was calculated as body weight (kg)/height (m)2 ,
measured at baseline and in follow-up. Women’s age at
follow-up was used in these analyses. The interval between
baseline and follow-up was quantified in years to one
decimal point. Other covariates from follow-up included
smoking, history of cancer or diabetes, ovarian hormone
treatment (estradiol with or without progesterone/progestin),
and age at menopause. A total of 534 women (26.6 percent)
did not answer the ovarian hormone treatment question.
These women did not differ significantly in BMD or anthropometric data from those who reported no use of ovarian
hormone treatment, but they were older than the women
reporting ever ovarian hormone treatment use. It was assumed that nonresponse was because the question was irrelevant for these women; thus, for the multivariate analyses,
the nonresponders were categorized as never users. The other
ovarian hormone treatment categories were current and prior
use. Smoking was calculated as pack-years, that is, (daily
cigarettes 3 years of smoking)/20. The history of smoking
was categorized as current, prior, and never smokers as
reported at follow-up.
Bivariate associations for continuous data were analyzed
by independent and paired sample t tests. Odds ratios for
dichotomous variables were calculated by logistic regression. In order to determine the separate associations of
weight gain and weight loss with BMD, we used two multiple linear regression models, one for weight loss and the
other for weight gain. The models included final weight,
age, ovarian hormone treatment, pack-years of smoking,
and age at menopause; all are variables with a linear association with BMD. The interval between baseline and
follow-up was not a statistically significant predictor and
was omitted from the models. Similar analyses were also
performed, adjusting for baseline instead of final body
weight and for medical conditions that could induce weight
change, such as diabetes and cancer.
The analyses documented an interaction between body
weight and weight change. In order to assess whether the
effect of weight loss or gain differed according to body mass
index at baseline, we carried out multiple linear regression
in stratified models of body mass index less than or equal to
25.0 kg/m2 and body mass index greater than 25.0 kg/m2.
This cutoff represented the median baseline body mass
index. All models were tested for collinearity and heteroscedasticity. The final multiple regression analyses were performed without residual outliers (3 standard deviations), at
the maximum 21 cases (1 percent). The results are presented
as regression coefficients (change in BMD (milligrams/centimeter squared) per unit change of the explanatory variable). All statistical tests were two sided, and the analyses
were carried out with SPSS, version 13.0, software (29).
Ethics
The HUNT study was approved by the Regional Committee for Medical Research Ethics and by the Norwegian
Data Inspectorate.
RESULTS
Selected characteristics of the prospective cohort of the
2,005 women who had forearm BMD measurements at
follow-up are shown in table 1. The mean body weight in
this population of midlife women had increased by 3.4 kg
over the 11.3 years of follow-up, and 66.3 percent of the
women had gained weight. A total of 382 women (19.1 percent) had lost more than 1 kg of body weight. These women
were older at the BMD examination than were the women
with stable or increased weight; the mean age was 67.1
years (95 percent confidence interval: 66.6, 67.5) for those
who had lost weight and 65.5 years (95 percent confidence
interval: 65.2, 65.7) for those with stable and increased
weight (pooled together). However, the women who had lost
weight had the highest mean body weight at baseline. Their
mean weight loss was 5.2 kg that corresponded to an average relative loss of 7.3 percent of body weight. The mean
forearm BMD was statistically significantly lower in women
with a history of weight loss or stable weight than the BMD
for women with weight gain (table 1). No difference in age
at menopause between the weight-change categories was
found with the differences in time since menopause being
explained by the differences in age between these groups.
Women with weight gain reported statistically significantly
more ovarian hormone therapy use than did women with
stable weight (p ¼ 0.003). However, compared with women
with weight loss, women with weight gain were not statistically significantly more likely to use ovarian hormone
treatment (p ¼ 0.07). Current smoking was more frequent
in the groups of women with either weight loss or stable
weight than in the women who had weight gain (table 1). In
a logistic regression model adjusting for age, the odds ratio
of weight loss among current smokers was 1.95 (95 percent
confidence interval: 1.5, 2.5) compared with never smokers.
A diagnosis of diabetes was more frequent in the women
who had lost weight. No association was present between
weight change and a history of cancer (table 1).
Body weight at baseline and follow-up in two strata
of baseline body mass index (25.0 and >25.0 kg/m2) and
by categories of weight change is presented in table 2.
The women with baseline body mass index greater than 25.0
kg/m2 had lost 2.1 kg more weight (95 percent confidence
interval: 1.4, 2.8) than did the women with body mass index
less than or equal to 25.0 kg/m2 at baseline. This explained
the difference in total weight change between the two strata
of baseline body mass index. Figure 1 shows the mean BMD
at the distal forearm according to five categories of weight
change, stratified by baseline body mass index (25.0 and
>25.0 kg/m2). Women with baseline body mass index
greater than 25.0 kg/m2 had on average higher BMD than
did the women with baseline body mass index less than or
equal to 25.0 kg/m2. Weight gain, however, seemed to be
positively associated with BMD for both body mass index
strata before controlling for other covariates. The most noticeable BMD difference between the two body mass index
strata was found in women who had lost weight. Women in
the lowest body mass index stratum had almost 10 percent
lower BMD than did women with baseline body mass index
greater than 25.0 kg/m2. It should, however, be noted that the
Am J Epidemiol 2006;164:890–897
Weight Change and Forearm Bone Density in Midlife Women
893
TABLE 1. Characteristics of 2,005 women by category of body weight change between baseline at
HUNT* I (1984–1986) and follow-up at HUNT II (1995–1997), an average period of 11.3 yearsy
Category of weight change, from baseline to
follow-up (11.3 years)
Total
(n ¼ 2,005)
p valuez
Weight loss§
(n ¼ 382)
Stable weight§
(n ¼ 292)
Weight gain§
(n ¼ 1,331)
Continuous data, mean (SD*)
2
Distal BMD* (mg/cm )
385.7 (68.9)
373.9 (68.7)
373.7 (67.0)
391.7 (68.6)
Ultradistal BMD (mg/cm2)
287.9 (62.5)
277.4 (63.5)
277.0 (61.8)
293.4 (61.8)
0.001
Age at baseline (years)
54.5 (4.9)
55.6 (4.2)
55.4 (4.6)
53.9 (5.1)
0.001
Age at follow-up (years)
65.8 (5.1)
67.1 (4.5)
66.5 (4.7)
65.2 (5.3)
0.001
0.001
Duration of baseline follow-up
(years)
11.3 (1.3)
11.5 (1.3)
11.2 (1.3)
11.3 (1.2)
0.003
Weight at baseline (kg)
68.0 (11.1)
70.4 (13.0)
66.7 (10.9)
67.6 (10.4)
0.001
Weight at follow-up (kg)
71.4 (12.2)
65.2 (12.0)
66.8 (11.0)
74.2 (11.5)
0.001
Weight change (kg)
3.4 (6.2)
5.2 (4.1)
0.1 (0.7)
6.6 (4.4)
0.001
2
BMI* at baseline (kg/m )
25.7 (4.0)
26.6 (4.8)
25.3 (4.0)
25.5 (3.7)
0.001
BMI at follow-up (kg/m2)
27.4 (4.4)
25.2 (4.5)
25.8 (4.1)
28.3 (4.1)
0.001
BMI change (kg/m2)
1.7 (2.3)
1.4 (1.6)
0.5 (0.6)
2.9 (1.7)
0.001
Age at menopause (years)
49.3 (4.1)
49.1 (3.8)
49.4 (3.8)
49.3 (4.2)
NS*
Years since menopause (no.)
16.5 (6.5)
17.9 (5.9)
17.2 (5.6)
15.9 (6.8)
0.001
Smoking{ (pack-years)
9.8 (10.9)
11.3 (11.5)
9.7 (9.8)
9.4 (11.0)
0.04
Categorical data
Current smokers (%) (n ¼ 453)
22.7
33.2
27.7
18.5
0.001
OHT* (current or prior)# (%)
(n ¼ 292)
19.9
16.7
12.8
22.2
NS
Diabetes mellitus (%) (n ¼ 92)
4.6
10.5
3.4
3.2
0.001
History of cancer (%) (n ¼ 146)
7.3
7.6
6.8
7.3
NS
* HUNT, the Health Study of Nord-Trøndelag, Norway; SD, standard deviation; BMD, bone mineral density; BMI,
body mass index; NS, not statistically significant (p > 0.05); OHT, ovarian hormone treatment.
y Unless noted, all data were measured at HUNT II (follow-up). Bone mineral density was measured at the
forearm.
z Two samples of the t test or chi-square test of differences between the categories of weight loss and weight
gain.
§ Categories of weight change: weight loss, >1-kg loss; stable weight, 1 kg; weight gain, >1-kg increase.
{ Smoking in pack-years among 946 current or previous smokers at follow-up.
# History of ovarian hormone treatment among 1,471 women who answered the question.
TABLE 2. Body weight at baseline (HUNT* I, 1984–1986) and follow-up (HUNT II, 1995–1997) and the magnitude of weight change with
95% confidence intervals in the categories of weight loss, stable weight, and weight gain between baseline and follow-up, an average
period of 11.3 years, and by two strata of body mass index at baseline
Baseline BMI* 25 kg/m2
Weight
changey
Weight loss
Baseline BMI >25 kg/m2
Body weight at baseline and follow-up
and weight change (kg)
Body weight at baseline and follow-up
and weight change (kg)
No.
No.
162
Baseline
Follow-up
Change
95% confidence
interval
59.3
55.2
4.0
4.4, 3.6
220
Baseline
Follow-up
Change
95% confidence
interval
78.6
72.5
6.1
6.8, 5.5
Stable weight
154
59.1
59.2
0.1
0.0, 0.2
138
75.1
75.2
0.1
0.0, 0.2
Weight gain
672
60.5
67.1
6.5
6.2, 6.8
659
74.8
81.6
6.7
6.4, 7.1
Total
988
60.1
63.9
3.8
3.4, 4.1
1,017
75.7
78.7
3.0
2.6, 3.5
* HUNT, the Health Study of Nord-Trøndelag, Norway; BMI, body mass index.
y Categories of weight change: weight loss, >1-kg loss; stable weight, 1 kg; weight gain, >1-kg increase.
Am J Epidemiol 2006;164:890–897
894 Forsmo et al.
FIGURE 1. The curves show the mean distal-forearm bone mineral density by categories of weight change during the 11.3 years between
baseline at HUNT I (1984–1986) and follow-up at HUNT II (1995–1997). (Vertical bars denote 95% confidence intervals). These data are stratified
according to body mass index (BMI) at baseline. The solid curve represents the mean bone mineral density in 1,013 women with a baseline body
mass index greater than 25 kg/m2, and the dashed line shows the mean bone mineral density in 992 women with a baseline body mass index less
than or equal to 25 kg/m2. The light, dotted bars show the mean weight at baseline, and the dark, diagonally striped bars show the mean weight at
follow-up in the categories of weight change, with 95% confidence intervals (vertical bars). HUNT, the Health Study of Nord-Trøndelag, Norway.
difference in body weight at the time of densitometry was
17.2 kg between these two groups (table 2). The women with
weight loss in the lower baseline body mass index group had
statistically significantly lower BMD than did women with
stable weight or weight gain within the same body mass
index stratum. The same pattern was found for BMD measured at the ultradistal radius.
In the multiple linear regression models shown in table 3
and table 4, there was an inverse association between BMD
and both weight loss and weight gain, when adjustment was
made for body weight at follow-up along with other covariates. Weight change explained less than 1 percent of the
total BMD variance with contributions of 0.7 and 0.4 percent for weight loss and gain, respectively. When performing the same analysis but adjusting for baseline instead of
follow-up body weight, we found that weight gain was positively associated with BMD, but the association was not
statistically significant. For weight loss, the association remained inverse and statistically significant. This indicates
that weight loss has a negative effect on forearm BMD,
whereas the effect of weight gain is explained by the body
weight at baseline.
Because of the interaction between baseline weight and
weight change (p ¼ 0.04), multiple linear regression was
performed by use of models stratified for baseline body
mass index (25.0 kg/m2 vs. >25.0 kg/m2). An independent
and inverse association between weight loss and BMD was
found in women with baseline body mass index greater than
25.0 (regression coefficient: 1.84, p ¼ 0.04). This association was not present for women with baseline body mass
index less than or equal to 25.0 kg/m2. However, in the latter
group of women, there was an inverse and statistically significant association between weight gain and BMD, but only
when adjustment was made for body weight at follow-up.
This observation is thus not independent of baseline weight.
These results indicate that the negative effect of weight loss
on forearm BMD can be demonstrated only in women who
were overweight (body mass index >25 kg/m2) at baseline.
A history of cancer was not a confounder in the multiple
linear regression models, whereas a diagnosis of diabetes
was a statistically significant positive predictor of BMD in
women who had lost weight (data not shown). When eliminating the 92 women reporting diabetes from the multivariate analyses, we found that the inverse association between
weight loss and BMD became stronger.
DISCUSSION
This population-based study shows that women’s weight
loss through the peri- and postmenopausal years adversely
affects forearm BMD. This was particularly the case for
women with a relatively high body mass index at baseline.
The apparent inverse association between weight gain and
BMD was explained by a lower weight at baseline. In
women having lost weight, however, the inverse association
Am J Epidemiol 2006;164:890–897
Weight Change and Forearm Bone Density in Midlife Women
TABLE 3. Multiple linear regression of bone mineral density
measured at the distal forearm and ultradistal radius in a model
of 382 women with weight loss greater than 1 kg during the 11.3
years between baseline (HUNT* I, 1984–1986) and follow-up
(HUNT II, 1995–1997)y
Predictors
Distal forearm,
R 2 ¼ 26.0%
Weight loss (kg)
Body weight at BMD (kg)
Age at BMD (years)
Age at menopause
(years)
Smoking (pack-years)
OHT* (never/prior/
current)
TABLE 4. Multiple linear regression of bone mineral density
measured at the distal forearm and ultradistal radius in a model
of 1,331 women with weight gain greater than 1 kg during 11.3
years between baseline (HUNT* I, 1984–1986) and follow-up
(HUNT II, 1995–1997)y
Predictors
p value
BMD
(mg/cm2)
455.1
<0.001
368.9
<0.001
Constant
1.6
<0.033
1.5
<0.042
Weight gain (kg)
1.8
<0.001
1.6
<0.001
Body weight at BMD (kg)
4.7
<0.001
4.4
<0.001
Age at BMD (years)
<0.003
Age at menopause
(years)
BMD*
(mg/cm2)
Constant
Ultradistal radius,
R 2 ¼ 22.3%
2.3
<0.003
0.6
<0.067
13.2
<0.039
2.2
p value
NS*
Smoking (pack-years)
NS
OHT* (never/prior/
current)
* HUNT, the Health Study of Nord-Trøndelag, Norway; BMD, bone
mineral density; NS, not statistically significant; OHT, ovarian hormone therapy.
y The complete model is presented.
between weight change and BMD was independent of body
weight whether at baseline or at follow-up. Predicted BMD
at a given body weight will thus be lower in women with
a history of substantial weight loss than in women with
a smaller loss, despite a higher mean weight in the former
group. This indicates that weight loss is negative for BMD,
even in non-weight-bearing bones.
The strengths of this study are its population-based design
and high participation rate. The women invited to densitometry, although a subset of the age-stratified population, were
selected at random. They did not differ concerning anthropometric measures from other women of similar age who
participated in HUNT. A study of nonresponders in HUNT
II did not reveal any important selection biases except for
a slightly higher prevalence of current smokers in those who
did not attend (26, 27). In this study, smokers had lower
body weight than did nonsmokers, and smoking was more
prevalent among women with weight loss. However, smoking was included as a covariate in the multivariate analyses,
and thus, we do not think that selection represented a major
bias to the final result. This study involved only middle-aged
and elderly women, and therefore the results cannot be generalized to the entire adult population.
We have no information about the causes for weight loss,
whether it was deliberate or due to medical conditions or
treatment. The women with weight loss greater than 1 kg
between baseline and follow-up had the highest mean
weight at baseline, and women with a baseline body mass
index greater than 25.0 kg/m2 had lost more than did those
with a body mass index less than or equal to 25.0 kg/m2.
This may indicate that weight loss was intentional for the
majority of women losing weight, although the effect of
regression toward the mean should not be ignored. A recent
study rejected the hypothesis that intentional weight loss is
Am J Epidemiol 2006;164:890–897
895
Distal forearm,
R 2 ¼ 21.0%
Ultradistal radius,
R 2 ¼ 20.0%
BMD*
(mg/cm2)
p value
BMD
(mg/cm2)
p value
542.6
<0.001
411.6
<0.001
1.4
<0.001
1.0
<0.010
1.5
<0.001
1.3
<0.001
4.9
<0.001
4.2
<0.001
1.3
<0.001
1.2
<0.001
0.6
<0.001
0.6
<0.001
5.9
<0.030
7.3
<0.030
* HUNT, the Health Study of Nord-Trøndelag, Norway; BMD, bone
mineral density; OHT, ovarian hormone therapy.
y The complete model is presented.
less detrimental than unintentional weight loss, at least in
elderly women (5). The possibility remains, however, that
during deliberate weight loss the women will increase physical activity and be more conscientious about nutrient intake
than during unintentional weight loss and that these behavior changes could minimize the negative effect of weight
loss on the skeleton. This was not explored in our study.
Some medical conditions could explain weight change,
and we excluded women reporting treatment for thyroid
diseases from all analyses. The women with diabetes in this
age span mainly have diabetes type 2 (30), and these women
had slightly higher BMD as has been shown in other crosssectional studies (31). However, more rapid bone loss in
diabetic women has recently been reported (32). Weight loss
was more frequent in women with diabetes than in those
without it. Elimination of the women reporting diabetes
from the analyses increased the inverse effect of weight loss
on BMD. Hence, the possibility remains that subclinical
illness could explain both weight loss and low BMD, as
has been discussed by Ensrud et al. (5). These authors also
observed that hip fracture risk was unchanged over time
when following a cohort of elderly women with a history
of both intentional and unintentional weight loss (5). One
would have expected the association between weight loss
and fractures to diminish with time if subclinical pathology
had provided the explanation for the weight loss.
The interval between the two weight measurements in
this study was rather large. With only these two points in
time, we are not able to assess the influence of rapid weight
loss compared with slower loss or the effects of weight
cycling that seems to be associated with reduced BMD at
the radius in obese premenopausal women (33).
Weight loss has been shown to induce a higher rate of
bone loss in premenopausal women (34, 35) and in the
elderly (1, 36). In this study, BMD was not measured at
896 Forsmo et al.
baseline, and the influence of weight change on bone loss
could not be assessed. Body weight is a strong positive predictor of BMD and of peak bone mass (37). Further, women
with low body mass index experience more rapid bone loss
(36, 38). The results of this study indirectly suggest that
weight loss increases bone loss. The rather unexpected result that the independent negative effect of weight loss on
forearm BMD could be demonstrated only among women
with relatively high body size at baseline may be explained
by somewhat higher relative weight loss than in women of
smaller size. It is also possible that the influence of weight
loss on bone is more discernible in women with an increased
BMD related to their higher body weight. These women,
however, do still benefit from a relatively high body weight
that explains that their forearm BMD values were significantly higher than for the more slender women with a history
of weight loss.
When considering these results, one should take into account that the impact of weight loss on BMD was rather
small. For a predicted difference of 1 standard deviation in
forearm BMD in women with baseline body mass index
greater than 25 kg/m2, the difference in weight loss must
be 33 kg, given the same body weight at follow-up. This
would, however, increase the forearm fracture risk by 50
percent (7). Bauer et al. (12) found that each 10-kg weight
loss was associated with 3.9 percent lower bone mass (12).
This is comparable with our results that showed that a 10-kg
loss was associated with 4.1 percent lower BMD.
Mechanisms are unclear for the adverse effect of weight
loss on the skeleton. Reduced mechanical strain due to reduced body weight is one hypothesis. This should, however,
not count as much for the forearm as for the weight-bearing
parts of the skeleton. Reduced conversion of circulating
androgens to estrogen due to less adipose tissue is another
explanation. Serum leptin could represent a plausible mediator between body fat and bone (39). There are, however,
conflicting results about whether this mechanism relates to
the mature skeleton and the distal radius (40, 41). Alternatively, weight loss could induce changes in insulin-like
growth factors and sex-hormone binding globulin that
would alter the bioavailability of estrogen (42, 43).
About two thirds of the women in this cohort had gained
weight, with the younger women gaining more than the
older women. Although we found a positive crude association between weight gain and forearm BMD, there was no
effect of weight gain independent of body weight. Trovas
et al. (44) found a positive correlation between weight gain
and lumbar spine BMD; however, these authors did not
adjust for body weight or body mass index as either final
weight or at baseline. When assessing the effect of weight
change on BMD, we found it important to adjust for body
weight. The positive crude association between weight gain
and BMD found in this study was explained mainly by age,
as the younger women, with more weight gain, had higher
BMD than did older women. The negative association of
weight gain with BMD that appeared when adjustment was
made for current weight may indicate that BMD is associated with weight history throughout adult life. It is possible
that the women with a history of midlife weight gain follow
a different profile of bone change than do women whose
weight remains stable in midlife. Their baseline BMD might
have been lower, but bone loss was reduced because of
weight gain, as has been found in other studies (1, 36). This
was seen particularly in women whose baseline body mass
index was less than or equal to 25 kg/m2.
In summary, weight gain during the peri- and postmenopausal years was common in this cohort of 2,005 middleaged women followed over a period of more than 11 years.
Weight loss had a small, but inverse and independent effect
on forearm bone mineral density. This was found particularly in women with a body mass index greater than 25
kg/m2 at baseline. This study did not document an independent effect of weight gain on forearm BMD; the observed
inverse association was explained by their lower body weight
at baseline.
ACKNOWLEDGMENTS
The study was supported by grants from the Norwegian
Women’s Public Health Association, the Norwegian Research Council, the Norwegian Osteoporosis Foundation,
and the Association of Health and Rehabilitation.
The authors are grateful to W. Dana Flanders and Jerilynn
C. Prior who assisted with revisions of the manuscript.
The Health Study of Nord-Trøndelag is a collaboration
among the HUNT Research Centre, the Norwegian University of Science and Technology, the Norwegian Institute
of Public Health, and the Nord-Trøndelag County Council.
Conflict of interest: none declared.
REFERENCES
1. Hannan MT, Felson DT, Dawson-Hughes B, et al. Risk factors
for longitudinal bone loss in elderly men and women: the
Framingham Osteoporosis Study. J Bone Miner Res 2000;
15:710–20.
2. Fahramand BY, Michaëlsson K, Baron JA, et al. Body size
and hip fracture risk. Epidemiology 2000;11:214–19.
3. Meyer HE, Tverdal A, Falch JA. Risk factors for hip fracture in
middle-aged Norwegian women and men. Am J Epidemiol
1993;137:1203–11.
4. Ensrud KE, Cauley J, Lipschutz R, et al. Weight change and
fractures in older women. Study of Osteoporotic Fractures
Research Group. Arch Intern Med 1997;157:857–63.
5. Ensrud KE, Ewing SK, Stone KL, et al. Intentional and unintentional weight loss increase bone loss and hip fracture risk
in older women. J Am Geriatr Soc 2003;51:1740–7.
6. Vogt MT, Cauley JA, Tomaino MM, et al. Distal radius fractures in older women: a 10 year follow-up study of descriptive
characteristics and risk factors. The Study of Osteoporotic
Fractures. J Am Geriatr Soc 2002;50:97–103.
7. Nguyen TV, Center JR, Sambrook PN, et al. Risk factors for
proximal humerus, forearm, and wrist fractures in elderly men
and women. Am J Epidemiol 2001;153:587–95.
8. Silman AJ. Risk factors for Colles’ fracture in men and
women: results from the European Prospective Osteoporosis
Study. Osteoporos Int 2003;14:213–18.
9. Keegan THM, Kelsey JL, King AC, et al. Characteristics of
fallers who fracture at the foot, distal forearm, proximal
Am J Epidemiol 2006;164:890–897
Weight Change and Forearm Bone Density in Midlife Women
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
humerus, and shaft of the tibia/fibula compared with fallers
who do not fracture. Am J Epidemiol 2004;159:192–203.
Gunnes M, Lehmann AH, Mellström D, et al. The relationship
between anthropometric measurements and fractures in
women. Bone 1996;19:407–13.
Margolis KL, Ensrud KE, Schreiner PJ, et al. Body size and
the risk for clinical fractures in older women. Ann Intern Med
2000;133:123–7.
Bauer DC, Browner WS, Cauley JA, et al. Factors associated
with appendicular bone mass in older women. Ann Intern Med
1993;118:657–65.
Forsmo S, Langhammer A, Forsen L, et al. Forearm bone
mineral density in an unselected population—the HUNT
study, Norway. Osteoporos Int 2005;16:562–7.
Augat P, Fuerst T, Genant HK. Quantitative bone mineral
assessment at the forearm: a review. Osteoporos Int 1998;8:
299–310.
Prior J, Vigna YM, Barr SI, et al. Ovulatory premenopausal
women lose cancellous spinal bone: a five year prospective
study. Bone 1996;18:261–7.
Mundy GR. Bone remodelling and mechanisms of bone loss
in osteoporosis. In: Meunier PJ, ed. Osteoporosis, diagnosis
and management. London, United Kingdom: Martin Dunitz,
1998:17–35.
Macdonald HM, New SA, Campbell MK, et al. Longitudinal
changes in perimenopausal and early postmenopausal women:
effects of dietary energy intake, energy expenditure, dietary
calcium intake and hormone replacement therapy. Int J Obes
Relat Metab Disord 2003;27:669–76.
Dubnov G, Brzezinski A, Berry EM. Weight control and the
management of obesity after menopause: the role of physical
activity. Maturitas 2003;44:89–101.
Sternfeldt B, Wang H, Quesenberry CP Jr, et al. Physical
activity and changes in weight and waist circumference in
midlife women: findings from the Study of Women’s Health
across the Nation. Am J Epidemiol 2004;160:912–22.
Jensen LB, Vestergaard P, Hermann AP, et al. Hormone replacement therapy dissociates fat mass and bone mass, and
tends to reduce weight gain in early postmenopausal women:
a randomized controlled 5-year clinical trial of the Danish
Osteoporosis Prevention Study. J Bone Miner Res 2003;18:
333–42.
Mokdad AH, Serdula MK, Dietz WH, et al. The spread of
the obesity epidemic in the United States, 1991–98. JAMA
1999;282:1519–22.
Kopelman PG. Obesity as a medical problem. Nature 2000;
404:635–43.
Drøyvold WB, Holmen J, Krüger Ø, et al. Leisure time
physical activity and change in body mass index: an 11-year
follow-up study of 9357 normal weight healthy women 20–49
years old. J Womens Health 2004;13:55–62.
Wedick NM, Barrett-Connor E, Knoke JD, et al. The relationship between weight loss and all-cause mortality in older
men and women with and without diabetes mellitus: the
Rancho Bernardo Study. J Am Geriatr Soc 2002;50:1810–15.
The Nord-Trøndelag Health Study. Verdal, Norway: Norwegian University of Science and Technology, 2005. (http://
www.hunt.ntnu.no/index.php?side¼english).
Langhammer A, Johnsen R, Holmen J, et al. Cigarette smoking gives more respiratory symptoms among women than
among men. The Nord-Trøndelag Health Study (HUNT).
J Epidemiol Community Health 2000;54:917–22.
Holmen J, Midthjell K, Krüger Ø, et al. The Nord-Trøndelag
Health Study 1995–97 (HUNT 2): objectives, contents,
Am J Epidemiol 2006;164:890–897
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
897
methods and participation. Norsk Epidemiologi 2003;13:
19–32. (http://www.medisin.ntnu.no/ism/nofe/norepid/
2003(1)%2005-Holmen.pdf).
Forsmo S, Schei B, Langhammer A, et al. How do reproductive and lifestyle factors influence bone density in distal and
ultradistal radius of early postmenopausal women? The NordTrøndelag Health Survey, Norway. Osteoporosis Int 2001;
12:222–9.
SPSS for Windows, version 13.0. Chicago, IL: SPSS, Inc,
2005. (http://www.spss.com/spss/).
Midthjell K, Krüger Ø, Holmen J, et al. Rapid changes in
the prevalence of obesity and known diabetes in an adult
Norwegian population. The Nord-Trøndelag Health Surveys 1984–86 and 1995–97. Diabetes Care 1999;22:
1813–20.
Strotmeyer ES, Cauley JA, Schwartz AV, et al. Diabetes is
associated independently of body composition with bone
mineral density and bone volume in older white and black men
and women. The Health, Aging and Body Composition Study.
J Bone Miner Res 2004;19:1084–91.
Schwartz AV, Sellmeyer DE, Strotmeyer ES, et al. Diabetes
and bone loss at the hip in older black and white adults. J Bone
Miner Res 2005;20:596–603.
Fogelholm M, Sievänen H, Heinonen A, et al. Association
between weight cycling history and bone mineral density in
premenopausal women. Osteoporos Int 1997;7:354–8.
Salamone LM, Cauley JA, Black DM, et al. Effect of a
lifestyle intervention on bone mineral density in premenopausal women: a randomized trial. Am J Clin Nutr 1999;70:
97–103.
Hui SL, Perkins AJ, Zhou L, et al. Bone loss at the femoral
neck in premenopausal white women: effects of weight change
and sex-hormone levels. J Clin Endocrinol Metab 2002;87:
1539–43.
Nguyen TV, Sambrook PN, Eisman JA. Bone loss, physical
activity and weight change in elderly women: the Dubbo
Osteoporosis Epidemiology Study. J Bone Miner Res 1998;
13:1458–67.
Hawker GA, Forsmo S, Cadarette SM, et al. Correlates of
forearm bone mineral density in young Norwegian women: the
Nord-Trøndelag Health Study. Am J Epidemiol 2002;156:
418–27.
Ravn P, Cizza G, Bjarnason NH, et al. Low body mass index is
an important risk factor for low bone mass and increased bone
loss in early postmenopausal women. J Bone Miner Res
1999;14:1622–7.
Westerterp KR. Weight loss and bone mineral content.
(Editorial). Obes Res 2002;10:559.
Rauch F, Blum WF, Klein K, et al. Does leptin have an
effect on bone in adult women? Calcif Tissue Int 1998;63:
456–8.
Pasco JA, Henry MJ, Kotowicz MA, et al. Serum leptin levels
are associated with bone mass in nonobese women. J Clin
Endocrinol Metab 2001;86:1884–7.
Keen RW. Effects of lifestyle interventions on bone health.
Lancet 1999;354:1923–4.
Pfeilschifter J, Scheidt-Nave C, Leidig-Bruckner G, et al.
Relationship between circulating insulin-like growth factor
components and sex hormones in a population-based sample
of 50- to 80-year-old men and women. J Clin Endocrinol
Metab 1996;81:2534–40.
Trovas G, Lyritis GP, Galanos A, et al. Influence of weight gain
on spine mineral density in postmenopausal women. Calcif
Tissue Int 1999;64:380–3.