Download Dietary and Urinary Metabonomic Factors Possibly Accounting for

Original Article
Dietary and Urinary Metabonomic Factors Possibly
Accounting for Higher Blood Pressure of Black Compared
With White Americans
Results of International Collaborative Study on Macro-/Micronutrients
and Blood Pressure
Jeremiah Stamler, Ian J. Brown, Ivan K.S. Yap, Queenie Chan, Anisha Wijeyesekera,
Isabel Garcia-Perez, Marc Chadeau-Hyam, Timothy M.D. Ebbels, Maria De Iorio,
Joram Posma, Martha L. Daviglus, Mercedes Carnethon, Elaine Holmes, Jeremy K. Nicholson,
Paul Elliott, for the INTERMAP Research Group
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Abstract—Black compared with non-Hispanic white Americans have higher systolic and diastolic blood pressure and rates of
prehypertension/hypertension. Reasons for these adverse findings remain obscure. Analyses here focused on relations of
foods/nutrients/urinary metabolites and higher black blood pressure for 369 black compared with 1190 non-Hispanic white
Americans aged 40 to 59 years from 8 population samples. Multiple linear regression, standardized data from four 24-hour
dietary recalls per person, two 24-hour urine collections, and 8 blood pressure measurements were used to quantitate the
role of foods, nutrients, and metabolites in higher black blood pressure. Compared with non-Hispanic white Americans,
blacks’ average systolic/diastolic pressure was higher by 4.7/3.4 mm Hg (men) and 9.0/4.8 mm Hg (women). Control
for higher body mass index of black women reduced excess black systolic/diastolic pressure to 6.8/3.8 mm Hg. Lesser
intake of vegetables, fruits, grains, vegetable protein, glutamic acid, starch, fiber, minerals, and potassium, and higher
intake of processed meats, pork, eggs, and sugar-sweetened beverages, along with higher cholesterol and higher Na/K
ratio, related to in higher black blood pressure. Control for 11 nutrient and 10 non-nutrient correlates reduced higher
black systolic/diastolic pressure to 2.3/2.3 mm Hg (52% and 33% reduction in men) and to 5.3/2.8 mm Hg (21% and 27%
reduction in women). Control for foods/urinary metabolites had little further influence on higher black blood pressure.
Less favorable multiple nutrient intake by blacks than non-Hispanic white Americans accounted, at least in part, for higher
black blood pressure. Improved dietary patterns can contribute to prevention/control of more adverse black blood pressure
levels. (Hypertension. 2013;62:00-00.) Online Data Supplement
•
Key Words: African American
■
blood pressure
A
dverse blood pressure (BP) is an established major risk
factor for cardiovascular diseases. Repeated US population surveys, including the International Collaborative Study
on Macro-/Micronutrients and Blood Pressure (INTERMAP),
document that BP is higher in black (African Americans:
AA) than non-Hispanic white Americans (NHWA).1–3
Etiopathogenesis of this BP difference remains unexplained,
that is, it continues to be—theoretically and practically—a
major unsolved challenge for cardiovascular disease research.
■
eating
■
nutrients
Here, we hypothesize that multiple black–NHWA differences in
food/nutrient intake and urinary metabolites account for higher
AA BP; we use INTERMAP data to test this hypothesis.3–6
Methods
Population Samples, Field Methods (1996–1999)
Participants were 369 AA and 1190 NHWA women and men aged 40
to 59 years recruited as 8 stratified random US population samples
(Table S1 in the online-only Data Supplement). Participants attended
Received June 4, 2013; first decision June 17, 2013; revision accepted September 5, 2013.
From the Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL (J.S., M.L.D., M.C.); Department
of Epidemiology and Biostatistics, School of Public Health (I.J.B., Q.C., M.C.-H., M.D.I., P.E.), and Section of Computational and Systems Medicine,
Department of Surgery and Cancer (I.K.S.Y., A.W., I.G.-P., T.M.D.E., J.P., E.H., J.K.N.), Faculty of Medicine, Imperial College London, United Kingdom;
Department of Life Sciences, School of Pharmacy and Health Sciences, International Medical University, Kuala Lumpur, Malaysia (I.K.S.Y.); Department
of Statistical Science, University College, London, United Kingdom (M.D.I.); and MRC-HPA Centre for Environment and Health, Imperial College
London, United Kingdom (Q.C., A.W., I.G.-P., M.C.-H., T.M.D.E., J.P., E.H., J.K.N., P.E.).
The online-only Data Supplement is available with this article at http://hyper.ahajournals.org/lookup/suppl/doi:10.1161/HYPERTENSIONAHA.
113.01810/-/DC1.
Correspondence to Jeremiah Stamler, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, 680 N Lake Shore
Dr, Suite 1400, Chicago, IL 60611. E-mail [email protected]
© 2013 American Heart Association, Inc.
Hypertension is available at http://hyper.ahajournals.org
DOI: 10.1161/HYPERTENSIONAHA.113.01810
1
2 Hypertension December 2013
4 times—2 visits on consecutive days, 2 further visits on consecutive
days on average 3 weeks later.3 Demographic data were obtained
by interviewer-administered questionnaire. Height and weight were
measured at 2 visits. Each participant provided two 24-hour urine
collections; aliquots were air-freighted to the Central Laboratory
(Leuven, Belgium) for urinary biochemistry and to Imperial College
London for proton nuclear magnetic resonance spectroscopy.6
Dietary data were collected and computerized by a certified interviewer using the multipass 24-hour recall method.3,7 Institutional
ethics committee approval was obtained for each site; all participants
gave written informed consent.
BP Measurements
Systolic and diastolic BP (SBP, DBP; first and fifth Korotkoff sounds)
were measured twice per visit by a certified technician using a random-zero sphygmomanometer—participant seated for ≥5 minutes in
a quiet room, bladder empty, arm at heart level.3
Statistical Methods
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Measurements per person were averaged for BP and nutrients across
the 4 visits; for 24-hour urinary excretions, across the 2 collections.3,7
Interethnic differences were assessed for statistical significance by
Student t test or χ2 test. Approximate reliability—observed univariate
regression coefficient as percent of theoretical true coefficient—was
estimated for relevant variables.8,9
Based on AA–NHWA differences in dietary and urinary variables,
multiple linear regression was used to examine relations of these traits
to interethnic differences in BP.5,6,10 Model A included age, sex, sample, and an indicator for AA; model B added other nondietary factors;
model C added body mass index (BMI). Then each dietary/urinary
factor was added to model C separately; percentage reduction from
the model C AA–NHWA BP difference was calculated to ­assess the
influence of the added variable on higher BP of AA. Finally, ­dietary/
urinary variables were included in combinations to assess joint impact
on higher AA BP.
Results
Descriptive Statistics
AA had higher average BP than NHWA and higher prevalence rates of hypertension (Table S2). AA women had higher
average BMI and rates of overweight/obesity than NHWA
women. AA and NHWA of both sexes differed in intake of
multiple foods/nutrients (Tables S2 and S3).
AA Intake Lower, Foods/Nutrients With Possible Favorable
Relation to BP
AA had lower intake of total and raw vegetables, fresh fruits,
pasta/rice, total grains, vegetable protein, glutamic acid,
starch, fiber, Ca, Mg, P, K, Fe, and nonheme Fe.
AA Intake Higher, Foods/Nutrients With Possible Adverse
Relation to BP
AA had higher intake of processed meats, pork, eggs, sugarsweetened beverages, dietary cholesterol, total sugars, fructose/glucose/sucrose, glycine, and Na/K ratio.
AA intakes were relatively favorable for only a few foods/
nutrients:
1.AA intake higher, foods/nutrients with possible favorable relation to BP: fish/fish roe/shellfish, poultry, polyunsaturated fatty acids, polyunsaturated fatty acid/saturated fatty acid ratio, oleic acid.
2.AA intake lower, foods/nutrients with possible adverse
relation to BP: cream, cheese, dairy product recipes, and
alcoholic beverages.
Urinary Metabolites
The median urinary 600-MHz proton nuclear magnetic resonance spectra for AA and NHWA subsamples are shown in the
Figure. Urinary metabolites significantly12 higher in AA than in
NHWA included creatinine, 3-hydroxyisovalerate, N-acetyls of
glycoprotein fragments, dimethylglycine, lysine, N-acetyl neuraminic acid, leucine, dimethylamine, taurine, and 2-hydroxyisobutyrate; metabolites significantly higher in NHWA included
trimethylamine, N-methyl nicotinic acid, hippurate, and succinate (Table 1). Hippurate and N-methyl nicotinic acid as quantified in 24-hour excretions are shown in Table S4.
Figure. Median urinary proton nuclear magnetic resonance spectrum of INTERMAP US black and non-Hispanic white American (NHWA)
participants (top), based on the first urine collection (n=1455). Manhattan plot indicating the significant spectral variables (bottom).
Metabolites higher in black individuals compared with NHWA are shown in red; metabolites higher in NHWA individuals compared with
blacks are shown in blue. 1 indicates leucine; 2, 3-hydroxyisovalerate; 3, 2-hydroxyisobutyrate; 4, N-acetyls of glycoprotein fragments; 5,
N-acetyl neuraminic acid; 6, succinate; 7, dimethylamine; 8, trimethylamine; 9, dimethylglycine; 10, lysine; 11, creatinine; 12, hippurate;
and 13, N-methyl nicotinic acid.
Stamler et al Nutrition and Black Blood Pressure 3
Table 1. Proton Nuclear Magnetic Resonance–Derived Urinary Metabolites Differing Significantly* Between Black and NHWA
Participants, All and by Gender
Minimum P Value†
All
Metabolites
Chemical Shifts,
ppm (Multiplicity)
Men
Women
First
Collection
Second
Collection
First
Collection
Second
Collection
First
Collection
Second
Collection
Higher in blacks (154 men and 184 women)
Creatinine
3.05 (s); 4.05 (s)
3.8×10–25
1.8×10–20
4.4×10–13
1.1×10–11
5.8×10–14
9.3×10–10
3-Hydroxyisovalerate
1.27 (s); 2.37 (s)
1.0×10–23
4.6×10–24
4.1×10–13
3.6×10–17
1.8×10–11
4.3×10–9
1.6×10
1.5×10
3.9×10
1.5×10
–12
1.4×10
3.1×10–12
…
4.1×10–15
2.2×10–11
…
…
…
…
4.3×10–10
2.7×10–9
…
…
…
N-acetyls of glycoprotein
fragments
Dimethylglycine
2.02–2.04 (s)
2.93 (s); 3.72 (s)
–22
–19
5.2×10–18
9.7×10–18
4.2×10
–12
…
–9
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Lysine
3.02 (t)
1.3×10
N-acetyl neuraminic
acid
2.06 (s)
2.9×10–14
3.0×10–11
Leucine
0.96 (d)
1.7×10–10
3.9×10–11
…
…
…
Dimethylamine
2.73 (s)
3.3×10
–10
4.7×10–9
4.1×10–10
1.7×10–11
…
…
2-Hydroxyisobutyrate
1.36 (s)
5.3×10–10
8.6×10–8
…
…
…
…
2.6×10–15
9.5×10–12
9.8×10–8
4.0×10–9
…
…
1.2×10
4.1×10
2.2×10–7
…
…
–9
–15
Higher in NHWA (594 men and 523 women)
Trimethylamine
2.87 (s)
N-methyl nicotinic
acid
4.44 (s); 8.84 (t);
9.13 (s)
3.1×10
Hippurate
3.98 (d); 7.55 (t);
7.64 (t); 7.84 (d)
5.9×10–10
3.1×10–9
…
…
…
…
Succinate
2.41 (s)
1.5×10–9
4.0×10–10
…
…
3.9×10–9
3.4×10–8
–13
–10
–8
d indicates doublet; NHWA, non-Hispanic white Americans; s, singlet; and t, triplet.
*Mean population differences in peak intensity for spectral variables were assessed for statistical significance using family wise error rate <0.01 (P<4×10–6 for group
mean population differences by Student t test) for the 2 urine collections considered separately.
†Minimum P values for mean population differences in peak intensity assigned to a particular metabolite, obtained separately for first and second urine collections,
give a ranking of the discriminatory strength of the metabolites.
Partial Correlations
Partial correlation coefficients >0.5 (adjusted for age, sex,
sample) were recorded for many pairs of foods/nutrients
(Table S5).
Reliability of Data
For foods, 29 of 68 reliability estimates were >50%, without
apparent pattern across sex/ethnic strata (Table S6). Nutrient
reliability estimates were generally higher than for foods; 75
of 108 were >50%, somewhat lower for AA than for NHWA.
Reliability estimates were high for hippurate, N-methyl nicotinic acid, SBP, and DBP.
Relation of Foods, Nutrients, and Urinary
Metabolites to Higher AA BP
With control for possible nondietary confounders, SBP/DBP
was significantly higher for AA than NHWA by 4.7/3.4 mm Hg
(men) and 9.0/4.8 mm Hg (women) (Table S6; row B). With
BMI in the model (Table S7; row C), these differences remained
about the same for men; for women, they were reduced to
6.8/3.8 mm Hg.
Foods Considered Singly
Of 17 foods with significantly different intakes by AA and
NHWA, most had only a small influence on higher BP of AA
(Table S7).
Nutrients and Urinary Metabolites Considered Singly
Addition of individual nutrients to the regression model generally led to greater influences on SBP and DBP (Table S7)
than addition of individual foods; 24-hour urinary K excretion
(inversely related to BP and lower in AA than NHWA) produced the largest effect in men, that is, reduction of AA SBP
by 1.2 mm Hg (26%) and DBP by 0.8 mm Hg (24%), but without effect in women. Dietary glycine (% total protein; directly
related to BP and higher in AA) had a similar SBP effect in
men and the largest effect in women. Inclusion of Ca, Mg, P
singly (inversely related to BP and lower in AA than NHWA)
produced 0.5 to 0.6 mm Hg (>10%) reduction in higher SBP
of AA men and qualitatively similar effects for AA women.
With inclusion of urinary hippurate, which is lower in AA
men (Table S4) and inversely related to BP, higher SBP and
DBP of AA men and women was reduced by only 0.1 mm Hg
(Table S7). With addition of N-methyl nicotinic acid to the
model, which is lower in AA than NHWA men and women
(reportedly not related to BP), higher SBP and DBP of AA
men and women were increased, not decreased.
Foods, Nutrients, and Urinary Metabolites in Combination
With 10 foods considered together (all with significantly
less favorable intake by AA than NHWA), effects on higher
AA SBP/DBP were modest (Table 2; row D). With 13 nutrients combined (most with significantly less favorable intake
4 Hypertension December 2013
Table 2. Relation of Combinations of Foods/Nutrients/Urinary Metabolites, Significantly Different in Blacks and NHWA, to Higher
BP of Blacks than NHWA, by Gender
SBP, mm Hg
Model
BP Difference
Z-Score
DBP, mm Hg
% Change From C*
BP Difference
Z-Score
% Change From C*
Men (n=165 blacks, 620 NHWA)
A: age, sample
5.41
4.40
3.46
3.94
B: A plus medical history of CVD/diabetes
mellitus, family history of hypertension, physical
activity, special diet, supplement use
4.68
3.80
3.38
3.84
C: B plus BMI
4.76
4.04
3.43
4.05
3.64
3.00)
−23.5
2.88
3.28
−16.1
E1: C plus vegetable protein, glutamic acid
(%kcal), starch, fiber, Ca, nonheme Fe, riboflavin,
urinary K, Σ long-chain PFA, dietary cholesterol,
glycine (%protein), 14-day alcohol, urinary Na
2.28
1.72
−52.1
2.31
2.41
−32.7
E2: as E1 except removing 14-day alcohol and
urinary Na
2.51
1.89
−47.3
2.43
2.53
−29.2
E3: as E1 except glutamic acid as %protein
(instead of %kcal)
2.77
2.12
−41.9
2.61
2.75
−24.1
E4: as E1 except Mg instead of Ca
2.41
1.82
−49.4
2.44
2.55
−28.9
Combination of foods
D: C plus raw vegetables, fresh fruit, pasta/rice,
total grains, eggs, sugar-sweetened beverages,
cream/cheese/ice cream/milk and cheese recipes,
pork, processed meats, alcoholic beverages
Combinations of nutrients
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E5: as E1 except P instead of Ca
2.39
1.81
−49.9
2.41
2.52
−29.8
E6: as E1 except urinary Na/K ratio instead of
urinary K and Na
2.47
1.88
−48.1
2.51
2.63
−27.0
E7: E1 plus Mg, P
2.29
1.72
−52.0
2.33
2.42
−32.2
F1: including variables with largest SBP
differences for men, D plus E1
2.17
1.62
−54.3
2.17
2.04
−36.7
F2: as F1, excluding variables with partial
correlation >0.5†
2.25
1.69
−52.7
2.14
2.21
−37.8
3.12
3.57
7.6
3.09
3.44
Combinations of foods/nutrients
Men with quantitated urinary metabolites (n=146 blacks, 578 NHWA)
Combinations of nutrients and urinary metabolite variables
G: as C except based on above n
3.81
3.15
H: G plus hippurate, N-methylnicotinic acid
4.10
3.29
−0.8
I: as E1 except based on above n
2.05
1.51
−46.2
2.46
2.50
−21.1
J: I plus hippurate, N-methyl nicotinic acid
2.44
1.78
−36.0
2.55
2.56
−18.2
A: age, sample
9.66
8.02
5.03
6.52
B: A plus medical history of CVD/diabetes
mellitus, family history of hypertension, physical
activity, special diet, supplement use
9.00
7.42
4.83
6.20
C: B plus BMI
6.76
5.76
3.77
4.87
6.18
4.74
−8.5
3.58
4.14
−5.2
5.31
3.82
−21.4
2.76
3.01
−26.8
Women (n=204 blacks, 570 NHWA)
Combination of foods
D: C plus raw vegetables, fresh fruit, pasta/rice,
total grains, eggs, sugar-sweetened beverages,
cream/cheese/ice cream/milk and cheese recipes,
pork, processed meats, alcoholic beverages
Combinations of nutrients
E1: C plus vegetable protein, glutamic acid
(%kcal), starch, fiber, Ca, nonheme Fe, riboflavin,
urinary K, Σ long-chain PFA, dietary cholesterol,
glycine (%protein), 14-day alcohol, urinary Na
(continued)
Stamler et al Nutrition and Black Blood Pressure 5
Table 2. Continued
Systolic BP, mm Hg
Diastolic BP, mm Hg
BP Difference
Z-Score
% Change From C*
BP Difference
Z-Score
% Change From C*
E2: as E1 except removing 14-day alcohol and
urinary Na
5.22
3.78
−22.8
2.61
2.86
−30.9
E3: as E1 except glutamic acid as %protein
(instead of %kcal)
5.42
3.90
−19.8
2.78
3.02
−26.2
E4: as E1 except Mg instead of Ca
5.46
3.94
−19.2
2.80
3.05
−25.8
Model
E5: as E1 except P instead of Ca
5.39
3.89
−20.2
2.73
2.98
−27.6
E6: as E1 except urinary Na/K ratio instead of
urinary K and Na
5.13
3.69
−24.1
2.65
2.88
−29.7
E7: E1 plus Mg, P
5.40
3.87
−20.2
2.84
3.09
−24.6
F1: including variables with largest SBP
differences for women, D plus E6
5.38
3.79
−20.4
3.04
3.23
−19.4
F2: as F1, excluding variables with partial
correlation >0.5‡
5.14
3.68
−24.0
2.83
3.06
−25.0
3.78
4.60
Combinations of foods/nutrients
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Women with quantitated urinary metabolites (n=188 blacks, 514 NHWA)
Combinations of nutrients and urinary metabolite variables
G: as C except based on above n
6.80
5.48
H: G plus hippurate, N-methyl nicotinic acid
6.92
5.52
1.6
4.01
4.83
6.0
I: as E1 except based on above n
5.37
3.63
−21.1
2.77
2.82
−26.8
J: I plus hippurate, N-methyl nicotinic acid
5.33
3.60
−21.7
2.80
2.86
−26.0
Units for nutrients are %kcal, g/1000 kcal, or mg/1000 kcal; for glutamic acid and glycine, % total protein; for urinary hippurate and N-methyl nicotinic acid, mmol/24
h. Z-score=regression coefficient/SE. |Z| ≥1.96, uncorrected P≤0.05; |Z| ≥2.58, uncorrected P≤0.01; |Z| ≥3.29, uncorrected P≤0.001. Σ indicates sum; BMI, body mass
index; BP, blood pressure; Ca, calcium; CVD, cardiovascular diseases; DBP, diastolic blood pressuure; Fe, iron; K, potassium; Mg, magnesium; Na, sodium; NHWA, nonHispanic white Americans; P, phosphorus; PFA, polyunsaturated fatty acids; SBP, systolic blood pressure; and SFA, saturated fatty acids.
*For rows H, I, and J, % change from row G.
†Model F2 (men) includes raw vegetables, fresh fruit, pasta/rice, eggs, sugar-sweetened beverages, cream/cheese/ice cream/milk and cheese recipes, pork,
processed meats, vegetable protein, glutamic acid (%kcal), riboflavin, urinary K, Σ long-chain PFA, glycine (%protein), 14-day alcohol, urinary Na.
‡Model F2 (women) includes raw vegetables, fresh fruit, pasta/rice, total grains, sugar- sweetened beverages, cream/cheese/ice cream/milk and cheese recipes,
pork, processed meats, alcoholic beverages, glutamic acid (%kcal), cholesterol, riboflavin, glycine (%protein), urinary Na/K ratio.
by AA than NHWA), effects on higher AA BP were larger,
particularly for men; for example, male SBP/DBP difference
reduced to 2.3/2.3 mm Hg (Z-scores, 1.72 and 2.41), as well as
a decrease of 2.2/1.1 mm Hg (−52% and −33%; Table 2; row
E1). Female AA SBP/DBP differences remained substantial,
with nutrient-related smaller effect of 1.5/1.0 mm Hg (−21%
and −27%). No significant gender interaction was found (data
not tabulated).
Combinations of nutrients and foods yielded little or no
additional reduction in higher AA BP (Table 2; row F2). With
the 2 quantified urinary metabolites in the model together
(without and with nutrients), higher AA SBP/DBP was not
reduced (Table 2; rows H, J).
Discussion
The main finding here on higher SBP/DBP of AA than NHWA
was that less favorable multiple nutrient intake by AA than
NHWA accounted, in part, for higher AA SBP/DBP. These
include vegetable protein and its main amino acid (glutamic
acid), starch, fiber, K, Ca or Mg or P, nonheme Fe; in addition,
dietary cholesterol and glycine.11–25
To the best of our knowledge, these INTERMAP findings
are unique. The Atherosclerosis Risk in Communities (ARIC)
population study, involving >8000 nonhypertensive women
and men aged 45 to 64 years, reported that whites consuming ≥3 daily servings of low-fat milk, compared with those
consuming <1, had a 2.7 mm Hg smaller SBP increase with
9-year follow-up, an association not prevailing for AA.26 No
data were revealed on relations of dietary variables to BP
differences between AAs and whites. The CARDIA study
reported that with 10-year follow-up, intake of low-fat dairy
products was associated with lower incidence of high BP
in AA and whites.27 The study did not assess whether these
or other foods/nutrients related to higher AA BP. The third
National Health and Nutrition Survey (NHANES III; 1988–
1994) reported lower serum 25-hydroxy vitamin D in AA than
NHWA and an inverse relation of 25-hydroxy vitamin D to
BP.28 These differences were estimated to explain about half
the greater AA BP prevalence. No dietary data were revealed.
If the INTERMAP findings here are reproducible, supporting the inference that they are etiologically significant,
they have important implications, especially need for greater
efforts to improve AA nutrition. For example, AA nutrition
would be enhanced importantly by adoption of dietary recommendations for prevention/control of adverse BP, used in
such studies as the Dietary Approaches to Stop Hypertension
(DASH)-low Na trial or the Optimal Macronutrient Intake
Trial for Heart Health (OMNIHEART) plus low Na.15,16 To
6 Hypertension December 2013
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extend their use among AA, specific factors influencing AA
diet need to be considered, for example, ethnic traditions,
lower average income, and reduced accessibility to modern
supermarkets.29 For AA women, there is a particular need to
reduce their higher BMI, with known relation to higher BP.
Metabolome-wide association analysis revealed 12 urinary metabolites that differed significantly between AA and
NHWA. Hippurate (higher in NHWA) is a gut microbial
cometabolite produced by bacterial metabolism of plant phenols30,31; hippurate was related inversely to BP in INTERMAP
participants.6 Observed differences in dimethylamine and
dimethylglycine (both higher in AA) also likely relate to
interethnic microbiotal differences.33 Creatinine and guanidinoacetate (involved in creatinine metabolism) were higher in
AA than NHWA. Creatinine excretion is related to muscle
turnover34; these metabolite differences could reflect greater
AA physical activity and muscle mass. Lower AA excretion
of N-methyl nicotinic acid, a product of nicotinic acid/nicotinamide metabolism, could reflect lower AA dietary intake
of niacin and tryptophan (observed; data not tabulated).
Trimethylamine (lower in AA) is linked to dietary cholineinduced atherosclerosis35; this difference could reflect lower
AA dietary intake of B-complex vitamins.
Multiple nutrients accounted only in part for higher AA
BP. This may reflect regression dilution bias and other limitations in the nutrient data, despite their quality.5,9 In this
regard, 2 previous INTERMAP investigations—on higher BP
of less educated Americans, and higher BP of northern than
southern Chinese—showed that multiple nutrients accounted
completely for higher BP.13,25 Thus, the fact here that multiple
foods/nutrients/metabolites apparently accounted only in part
for higher AA BP suggests that other traits may operate, for
example, in utero influences, early-life dietary patterns, psychosocial factors, and genetic factors.36–40
Study Strengths
Findings here are solidly based, with participants from 8 diverse
US random samples and dietary/metabolite/BP data collected
by standardized, quality-controlled repetitive methods.
Study Limitations
Data are cross-sectional, subject to random regression dilution bias despite multiple measurements, and—in regard
to the dietary data to nonrandom biases inherent in the
methodology.9
Perspectives
Delineation of factors responsible for the more adverse BP
patterns of AA compared with other Americans is a major,
long-term, unresolved research challenge. Its importance
relates not only to the need to overcome this inequality in
health of AA. It also stems from the likelihood that resolving this problem will clarify understanding on the etiopathogenesis of epidemic prehypertension/hypertension in all strata
of the population. The INTERMAP data reported here show
that about one fourth (SBP, women) to one half (SBP, men)
of higher BP of AA is attributable to less favorable intake of
multiple nutrients by AA , and that greater obesity among AA
women also is a significant factor. Improved eating patterns
can help prevent/control adverse AA BP patterns.
Acknowledgments
We dedicate this article to our longtime colleague Prof Hugo
Kesteloot, who died on October 5, 2010. Proton nuclear magnetic
resonance signal processing and inhouse software were developed by
Drs Cloarec, Ebbels, Veselkov, Keun, and Rantalainen (Department
of Surgery and Cancer, Imperial College London). This observational
study is registered at www.ClinicalTrials.gov as NCT00005271.
Sources of Funding
Supported by grants (R01-HL50490 and R01-HL84228) from
the National Heart, Lung, and Blood Institute, National Institutes
of Health (NIH), and by the NIH Office on Dietary Supplements
(Bethesda, MD); also by national agencies in Japan, People’s
Republic of China, and the United Kingdom.
Disclosures
None.
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Novelty and Significance
What Is New?
Summary
• To the best of our knowledge, the data here are the first reported on mul-
Data here from the population-based US samples of the International Collaborative Study on Macro-/Micronutrients and Blood
Pressure (INTERMAP) study support the conclusion that the inordinately high rates of prehypertension/hypertension, common among
blacks, can be ameliorated by improved nutrition.
tiple foods/nutrients/urinary metabolites that apparently account, at least
in part, for the more adverse blood pressure patterns of blacks compared
with non-Hispanic white Americans.
What Is Relevant?
• These data point the way to specific dietary enhancements for the prevention/control of adverse BP patterns in blacks.
Downloaded from http://hyper.ahajournals.org/ by guest on May 5, 2017
Dietary and Urinary Metabonomic Factors Possibly Accounting for Higher Blood
Pressure of Black Compared With White Americans: Results of International
Collaborative Study on Macro-/Micronutrients and Blood Pressure
Jeremiah Stamler, Ian J. Brown, Ivan K.S. Yap, Queenie Chan, Anisha Wijeyesekera, Isabel
Garcia-Perez, Marc Chadeau-Hyam, Timothy M.D. Ebbels, Maria De Iorio, Joram Posma,
Martha L. Daviglus, Mercedes Carnethon, Elaine Holmes, Jeremy K. Nicholson and Paul Elliott
Hypertension. published online October 7, 2013;
Hypertension is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231
Copyright © 2013 American Heart Association, Inc. All rights reserved.
Print ISSN: 0194-911X. Online ISSN: 1524-4563
The online version of this article, along with updated information and services, is located on the
World Wide Web at:
http://hyper.ahajournals.org/content/early/2013/10/07/HYPERTENSIONAHA.113.01810
Data Supplement (unedited) at:
http://hyper.ahajournals.org/content/suppl/2013/10/07/HYPERTENSIONAHA.113.01810.DC1
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ONLINE DATA SUPPLEMENT
Dietary and Urinary Metabonomic Factors Possibly Accounting for
Higher Blood Pressure of African-Americans Compared to White Americans
– – The INTERMAP Study
Jeremiah Stamler, Ian J. Brown, Ivan K.S. Yap, Queenie Chan, Anisha Wijeyesekera,
Isabel Garcia-Perez, Marc Chadeau-Hyam, Timothy Ebbels, Maria De Iorio, Joram
Posma, Martha L. Daviglus, Mercedes Carnethon, Elaine Holmes, Jeremy Nicholson,
Paul Elliott,
for the INTERMAP Research Group
1
SUPPLEMENTARY METHODS
Metabolome-Wide Analysis by 1H NMR Spectroscopy
Preparation of urine specimens: Urine specimens were thawed completely prior
to mixing. 500 µL of urine were mixed with 250 µL of phosphate buffer for urinary pH
stabilization (pH 7.4) and 75 µL of the sodium 3-trimethylsilyl-(2,2,3,3-2H4)-1-propionate
(TSP) in D2O. TSP served as a chemical shift reference, and D2O served as a fieldfrequency lock for the NMR spectrometer. The resulting solution was then transferred
into a 96-well plate and left to stand for 10 min. before centrifuging at 1,500 g for a
further 10 min. to remove any precipitate prior to NMR analysis.
1
H NMR spectroscopic analysis: The urine specimens were analyzed by 1H NMR
spectroscopy at 600 MHz using a Bruker DRX-600 spectrometer (Bruker Biospin,
Rheinstetten, Germany) operating in flow injection mode. Urine specimens were
automatically delivered to the spectrometer by a Gilson robot incorporated into the
Bruker Efficient Sample Transfer (BEST) system. One-dimensional (1D) 1H NMR
spectra of urine were acquired using a standard 1D pulse sequence (recycle delay-90°t1-90°-tm-90°-acquisition) with water presaturation during both the recycle delay (2s) and
the mixing time, tm, of 150ms. The 90° pulse length was set to ~10µs and an acquisition
time of 2.73s was used. In total, 64 transients were collected into 32K data points using
a spectral width of 20 ppm.
1
H NMR data pre-processing: All free induction decays were multiplied by an
exponential function equivalent to a 0.3 Hz line-broadening factor prior to Fourier
transformation. The spectra were referenced and corrected for phase and baseline
distortion. The spectral region δ 4.5 - 6.4 containing residual water and urea resonances
was removed prior to normalisation by probabilistic quotient method (S1). The
remaining spectrum (δ 0.5 - 9.5, excluding δ 4.5 - 6.4) was digitized to 7,100 variables
(bin width 0.005 ppm). Principal component analysis (PCA) was performed on the
pareto-scaled NMR dataset to identify metabolic outliers. PCA was done separately for
first and second urine specimens, and participants whose scores mapped outside of the
95% Hotelling’s T2 ellipse (S2) in either collection were excluded. Of 1,559 AA and
NHWA INTERMAP participants, 1H NMR spectra were not acquired for one of the two
urine collections from 13 participants and a further 91 participants were excluded
following the PCA outlier analysis, leaving 1,455 individuals for the present report: 338
AA and 1,117 NHWA.
Statistical methods: Logistic regression (MATLAB R2011a, MathWorks, Natick,
MA), adjusted for age, gender, and sample, was used to identify urinary metabolites
discriminating AA and NHWA participants among the subsample excluding metabolic
outliers (N=338 AA, N=1,117 NHWA). Analyses were done separately for first and
second 24-hour urine collections. Mean inter-ethnic differences in peak intensity for
7,100 spectral variables were assessed for statistical significance using a conservative
Family Wise Error Rate of <0.01 to minimize false positive findings, corresponding to P
<4×10-6 for group mean inter-ethnic differences for each of the two urine collections
considered separately (S3). Each discriminatory metabolite comprises multiple spectral
variables at 0.005 ppm resolution; the minimum P-value for mean differences between
AA and NHWA in peak intensity among the spectral variables assigned to a particular
metabolite was obtained separately for the first and second urine collections. This gave
2
a ranking of the discriminatory strength of the metabolites. A spectral variable was
found to be significant if the p-value was <4×10-6 for both urine collections, the
regression coefficients for both urine collections had the same sign and both adjacent
spectral variables were significant according the previous rules as well.
Structural identification of discriminatory metabolites was achieved by 2dimensional NMR analyses (S4), statistical total correlation spectroscopy (STOCSY)
(S5), addition of known standards to the urine specimens, solid phase extraction
chromatography, and mass spectrometry.
SUPPLEMENTARY REFERENCES
S1. Dieterle F, Ross A, Schlotterbeck G, Senn H. Probabalistic quotient normalization
as robust method to account for dilution of complex biological mixtures.
Application in 1H NMR metabonomics. Anal Chem. 2006;78:4281-4290.
S2. Hotelling H. The generalization of Student’s ratio. Ann Math Stat. 1931;2:360378.
S3. Chadeau-Hyam M, Ebbels TMD, Brown IJ, Chan Q, Stamler J, Huang CC,
Daviglus ML, Ueshima H, Zhao L, Holmes E, Nicholson JK, Elliott P, De Iorio M.
Metabolic profiling and the metabolome-wide association study: significance level
for biomarker identification. J Proteome Res. 2010;9:4620-4627.
S4. Holmes E, Loo RL, Cloarec O, Coen M, Tang H, Maibaum E, Bruce S, Chan Q,
Elliott P, Stamler J, Wilson ID, Lindon JC, Nicholson JK. Detection of urinary drug
metabolite (xenometabolome) signatures in molecular epidemiology studies via
statistical total correlation (NMR) spectroscopy. Anal Chem. 2007;79:2629-2640.
S5. Cloarec, O, Dumas ME, Craig, A, Barton RH, Trygg J, Hudson J, Blancher C,
Gauguier D, Lindon JC, Holmes E, Nicholson J. Statistical total correlation
spectroscopy: an exploratory approach for latent biomarker identification from
metabolic 1H NMR data sets. Anal Chem. 2005;77:1282-1289.
3
SUPPLEMENTARY TABLES
Online Table S1. U.S. INTERMAP population samples by age, gender, and ethnicity
Sample
Non-Hispanic White Americans
African Americans
Gender
Male
Female
Male
Female
Age
40-49 50-59 40-49 50-59 40-49 50-59 40-49 50-59
Baltimore
31
36
32
35
38
38
30
33
Chicago
39
71
38
65
19
6
25
6
Jackson
41
59
30
41
18
5
33
22
Minneapolis
47
47
51
42
13
16
12
22
Pittsburgh
57
62
58
58
8
2
5
6
Corpus Christi
65
65
58
62
1
1
7
3
4
Online Table S2. Descriptive statistics - - blood pressure, other variables, food/food subgroup intakes, African Americans (AA) and
non-Hispanic White Americans (NHWA) by gender
Variable
Men
Women
African American Non-Hispanic White
African American Non-Hispanic White
(N=165)
American (N=620)
(N=204)
American (N=570)
Mean or % (SD)
Mean or % (SD)
P-value* Mean or % (SD) Mean or % (SD)
P-value*
Systolic blood pressure, mm Hg
124.2
(15.3)
120.0
(12.2)
123.9
(15.7)
114.5
(13.8)
0.0002
4.3×10-15
Diastolic blood pressure, mm Hg
78.4
(11.0)
75.9
(9.1)
75.1
(9.9)
70.6
(8.8)
0.003
1.9×10-9
Hypertension†, %
38.2
25.6
46.6
20.0
0.001
2.2×10-13
Severe hypertension‡, %
28.5
19.5
40.2
17.5
0.01
5.9×10-11
Antihypertensive drug treatment, %
26.7
19.0
38.2
17.2
0.03
7.6×10-10
Age, years
48.0
(5.5)
49.3
(5.3)
48.7
(5.6)
49.6
(5.5)
0.004
0.05
-6
14.3
(2.4)
14.9
(2.7)
Education, years
14.7
(2.9)
15.9
(3.1)
0.01
3.6×10
2
Body mass index, kg/m
29.5
(5.5)
29.1
(5.1)
31.2
(6.9)
27.8
(6.3)
0.33
1.5×10-10
Physical activity,
hours/day moderate or heavy
4.2
(3.3)
3.3
(3.1)
3.3
(2.9)
2.8
(2.8)
0.002
0.05
Special diet, %
21.2
12.4
24.5
23.2
0.004
0.70
CVD/diabetes diagnosis, %
18.8
13.1
18.6
14.0
0.06
0.12
Current drinker, %
65.5
79.0
49.0
77.4
0.0003
3.6×10-14
14-day alcohol, drinkers only,
g/24-h
15.1
(23.8)
13.3
(16.3)
5.0
(9.8)
5.6
(8.4)
0.34
0.52
Energy, kcal/24-h
2635
(722)
2640
(682)
1896
(494)
1884
(468)
0.93
0.76
Foods with possible favorable relation to blood pressure – lower intake in AA than NHWA
Total vegetables, g/1,000 kcal
107.2
(60.2)
127.2
(65.6)
133.9
(79.6)
144.5
(74.9)
0.0004
0.09
Raw vegetables, g/1,000 kcal
20.0
(23.2)
29.9
(32.6)
30.4
(39.5)
39.4
(38.7)
0.0003
0.005
Fresh fruit, g/1,000 kcal
42.1
(54.0)
53.0
(64.8)
57.4
(73.5)
73.2
(67.9)
0.047
0.005
Pasta/rice, g/1,000 kcal
31.1
(34.7)
29.8
(30.0)
26.4
(27.8)
33.7
(32.8)
0.64
0.004
Total grains, g/1,000 kcal
89.0
(40.4)
97.3
(36.4)
85.0
(33.8)
106.2
(37.0)
0.01
1.9×10-12
Bread/rolls/biscuits, g/1,000 kcal
30.7
(16.3)
38.2
(21.0) 2.7×10-5
31.4
(19.7)
39.4
(22.6)
1.1×10-5
Foods with possible unfavorable relation to blood pressure – higher intake in AA than NHWA
Processed meats, g/1,000 kcal
11.1
(12.0)
9.9
(11.9)
10.3
(13.5)
6.9
(9.4)
0.27
0.0001
Pork, g/1,000 kcal
10.0
(13.2)
8.5
(11.8)
10.0
(15.5)
6.3
(9.9)
0.17
0.0001
Eggs, g/1,000 kcal
12.5
(13.1)
9.9
(9.9)
12.4
(12.7)
9.4
(9.1)
0.005
0.0003
Continued on next page
5
Online Table S2. continued, page 2
Fruit juices/drinks, g/1,000 kcal
122.5
(122.7)
69.9
(102.1) 2.5×10-8
Sugar-sweetened beverages,
g/1,000 kcal
210.1
(165.6)
126.3
(150.9) 8.9×10-10
Foods with possible favorable relation to blood pressure – higher intake in AA than NHWA
Fish/fish roe/shellfish, g/1,000 kcal
10.2
(16.3)
7.5
(12.8)
0.02
Poultry, g/1,000 kcal
27.6
(22.6)
17.1
(16.8) 7.6×10-11
Foods with possible unfavorable relation to blood pressure – lower intake in AA than NHWA
Cream, g/1,000 kcal
1.6
(3.5)
3.0
(6.1)
0.005
Cheese, g/1,000 kcal
6.8
(6.4)
13.1
(12.1) 1.8×10-10
Cream/cheese/ice-cream/milk &
cheese recipes, g/1,000 kcal
19.0
(22.1)
25.7
(21.2)
0.0004
Alcoholic beverages, g/1,000 kcal
70.3
(165.1)
72.5
(143.8)
0.87
110.1
(126.0)
66.4
(118.6)
1.0×10-5
194.7
(166.7)
76.7
(108.0)
3.3×10-28
9.9
30.1
(14.6)
(23.7)
8.5
17.8
(13.7)
(17.0)
0.24
7.5×10-15
1.7
9.2
(4.2)
(9.3)
3.5
15.6
(6.7)
(14.8)
0.0003
1.2×10-8
18.9
23.8
(22.0)
(117.3)
28.5
28.7
(23.7)
(88.0)
5.4×10-7
0.53
Foods not included since they were not significantly different for AA compared to NHWA of both genders and/or their possible
relation to BP remains undefined: animal fat; beef; cooked vegetables; cocoa, milk-type beverages; diet beverages; egg recipes;
fish, fish roe; fresh meat excluding poultry, fish; fresh meat/poultry; frozen yogurt; fruits, dried; fruits, sweetened; game meat; ice
cream/ice milk/sherbet/milk shake; imitation eggs; lamb; margarines; mature dried beans/peas; meat/poultry/fish recipes; milk;
milk/cheese recipes; milk/yogurt/frozen yogurt/cocoa; non-alcoholic beverages including soda, excluding tea/coffee; nuts/nut
butters; nuts/legumes; oils; polyunsaturated vegetable fat dairy products; ready-to-eat cereals; salad dressing; saturated vegetable
fat dairy products; shellfish; shortening; snacks/sweets; sweet breads/rolls/pancakes; table spreads; total animal
fats/margarines/table spreads/oils/shortening/salad dressing; total fresh meat/fish; total fruits; veal; vegetable recipes; vegetarian
meat substitutes/related products.
* From Student’s t-test or χ2 test.
†
Hypertension is systolic blood pressure ≥140 mm Hg, and/or diastolic blood pressure ≥90 mm Hg, and/or antihypertensive drug
treatment for high blood pressure.
‡
Severe hypertension is systolic blood pressure ≥160 mm Hg, and/or diastolic blood pressure ≥100, and/or antihypertensive drug
treatment for high blood pressure.
6
Online Table S3. Descriptive statistics - - nutrient intakes, AA and NHWA by gender
Variable
Men
African American
Non-Hispanic White
African American
(N=165)
American (N=620)
(N=204)
Mean or % (SD)
Mean or %
(SD)
P-value* Mean or % (SD)
Nutrients with possible favorable relation to blood pressure – lower intake in AA than NHWA
Vegetable protein, %kcal
4.4
(1.7)
5.0
(1.5)
4.5
(1.3)
4.3×10-5
-7
Glutamic acid, %kcal
2.8
(0.5)
3.0
(0.6)
2.8
(0.6)
4.2×10
-15
19.1
(1.5)
Glutamic acid, %protein
19.0
(1.4)
20.1
(1.6)
1.4×10
-5
Starch, %kcal
19.9
(5.4)
21.9
(5.0)
19.8
(5.0)
1.2×10
-6
Total dietary fiber, g/1,000 kcal
7.6
(3.4)
8.9
(3.3)
8.2
(3.4)
5.2×10
-15
Calcium, mg/1,000 kcal
288.9
(107.3)
382.3
(138.4) 3.1×10
308.8
(114.4)
-12
Magnesium, mg/1,000 kcal
125.4
(37.0)
147.6
(35.1)
130.4
(37.6)
2.3×10
Iron, mg/1,000 kcal
6.9
(3.1)
7.8
(2.9)
7.0
(2.3)
0.0003
Non-heme iron, mg/1,000 kcal
6.3
(3.1)
7.3
(2.9)
6.5
(2.2)
0.0001
-12
Phosphorus, mg/1,000 kcal
523.9
(103.3)
600.9
(125.7) 1.0×10
534.4
(117.5)
-7
Riboflavin, mg/1,000 kcal
0.82
(0.26)
0.94
(0.24)
0.82
(0.24)
2.3×10
Vitamin D, µg/1,000 kcal
2.0
(1.5)
2.4
(1.3)
2.1
(1.6)
0.004
-18
Urinary potassium, mmol/24-h
55.5
(17.9)
71.7
(21.2)
44.2
(15.9)
1.2×10
Nutrients with possible unfavorable relation to blood pressure – higher intake in AA than NHWA
Dietary cholesterol, mg/1,000 kcal
140.7
(62.1)
123.6
(52.9)
141.9
(64.1)
0.0004
-20
Arachidonic acid, %kcal
0.08
(0.04)
0.05
(0.03)
0.08
(0.05)
4.2×10
Estimated total sugars, %kcal
28.6
(8.7)
26.6
(8.4)
29.8
(8.5)
0.007
-6
Σ fructose, glucose, sucrose, %kcal
24.2
(8.8)
20.7
(8.4)
25.1
(8.6)
2.7×10
Glycine, %kcal
0.7
(0.2)
0.6
(0.2)
0.7
(0.2)
0.0006
-34
Glycine, %protein
4.5
(0.4)
4.1
(0.4)
4.5
(0.5)
6.1×10
-17
Ratio, urinary sodium/potassium
3.55
(1.28)
2.75
(0.98)
3.69
(1.53)
1.6×10
Nutrients with possible favorable relation to blood pressure – higher intake in AA than NHWA
Total PFA, %kcal
7.3
(2.7)
6.8
(2.1)
7.5
(2.5)
0.006
Total Omega-3 PFA, %kcal
0.8
(0.4)
0.7
(0.3)
0.8
(0.4)
0.01
-5
Σ long chain PFA, %kcal
0.10
(0.17)
0.05
(0.09)
0.09
(0.12)
2.2×10
Total Omega-6 PFA, %kcal
6.6
(2.5)
6.2
(2.0)
6.8
(2.2)
0.01
Linoleic acid, %kcal
6.5
(2.5)
6.1
(2.0)
6.7
(2.2)
0.02
Oleic acid, %kcal
12.0
(2.5)
11.8
(2.7)
12.0
(2.69)
0.32
Ratio, PFA/SFA
0.76
(0.31)
0.69
(0.27)
0.80
(0.32)
0.003
Women
Non-Hispanic White
American (N=570)
Mean or %
(SD)
P-value*
5.4
3.1
20.6
23.2
9.9
430.1
159.7
8.3
7.8
629.9
1.02
2.6
56.8
(1.4)
(0.5)
(1.5)
(5.0)
(3.4)
(147.4)
(39.0)
(2.8)
(2.8)
(127.9)
(0.26)
(1.4)
(17.9)
8.2×10-15
4.7×10-11
2.2×10-30
6.4×10-16
1.5×10-9
7.7×10-25
1.5×10-19
3.3×10-8
3.6×10-10
1.0×10-19
6.1×10-19
1.5×10-5
2.9×10-18
117.4
0.05
27.7
20.8
0.6
3.9
2.68
(48.6)
(0.03)
(7.2)
(6.9)
(0.2)
(0.4)
(0.98)
2.2×10-8
8.8×10-25
0.0007
1.6×10-12
8.5×10-8
9.5×10-50
3.2×10-25
6.6
0.7
0.06
6.0
5.9
11.1
0.71
(2.1)
(0.4)
(0.09)
(2.0)
(2.0)
(2.7)
(0.28)
5.2×10-7
0.045
0.002
4.0×10-7
9.5×10-7
4.4×10-5
0.0004
Continued on next page
Online Table S3. continued, page 2
Nutrients with possible unfavorable relation to blood pressure – lower intake in AA than NHWA
None
Abbreviations: Σ, sum of; SFA, saturated fatty acids; PFA, polyunsaturated fatty acids.
Heavy physical activity: hours/day of heavy activity, work and leisure; special diet: weight loss, weight gain, vegetarian, saltreduced, diabetic, fat-modified, or other; CVD-DM diagnosis: history of heart attack, other heart disease, stroke, or diabetes; all
nutrients are from four 24-hour dietary recalls/person.
Nutrients not included since they were not significantly different for AA compared to NHWA of both genders and/or their possible
relation to BP remains undefined: 14-day alcohol, all; alanine; animal protein; arginine; aspartic acid; beta-carotene; cystine;
fructose; galactose; glucose; histidine; isoleucine; Keys dietary lipid score; lactose; leucine; linolenic acid; lysine; maltose;
methionine; phenylalanine; proline; retinol; selenium; serine; sucrose; threonine; total available carbohydrate; total fatty acids; total
monounsaturated fatty acids; total protein, total SFA; tryptophan; tyrosine; urinary Na; valine; vitamin A; vitamin C; vitamin E.
* From Student’s t-test or χ2 test.
7
Online Table S4. Quantitated urinary hippurate and N-methyl nicotinic acid*, by ethnic group and
gender
Variable
African American Non-Hispanic White
P-value†
(N AA / N NHWA)
Mean
(SD)
Mean
(SD)
Men (146/578)
Hippurate, mmol/24-h
2.91
1.51
4.08
2.28
4.7×10-9
N-methyl nicotinic acid, mmol/24-h
0.24
0.21
0.42
0.31
2.1×10-10
Women (188/514)
Hippurate, mmol/24-h
2.32
1.45
3.30
2.01
1.6×10-9
N-methyl nicotinic acid, mmol/24-h
0.19
0.17
0.30
0.25
5.3×10-8
* quantified via integration of signals relative to the creatinine CH2 signal (δ 4.06), with creatinine
measured by the Jaffé reaction (7).
†
From Student’s t-test.
8
Online Table S5. Partial correlations* of foods, nutrients, urinary metabolites, r > 0.5, AA and NHWA women and men combined (N=1,559†)
Variable
Partial correlation, r >0.5
Foods
Total vegetables
Fiber (0.57), beta-carotene (0.51)
Fresh fruit
Fiber (0.57), vitamin C (0.57)
Total grains
Vegetable protein (0.58), glutamic acid %protein (0.52), starch (0.79)
Eggs
Cholesterol (0.83)
Sugar-sweetened beverages
Estimated total sugars (0.53), Σ fructose, glucose, sucrose (0.63), fructose (0.73), glucose (0.72)
Fish, fish roe, shellfish
Σ long chain PFA (0.79)
Poultry
Arachidonic acid (0.52), glycine %kcal (0.53)
Cheese
Tyrosine (0.51)
Alcoholic beverages
14-day alcohol, all (0.70), 14-day alcohol, drinkers only (0.70)
Nutrients
Vegetable protein
Starch (0.66), fiber (0.77), magnesium (0.63), non-heme iron (0.51), total grains (0.58), methionine (-0.56),
lysine (-0.55)
Glutamic acid, %kcal
Phosphorus (0.74), glycine %kcal (0.72), selenium (0.65), animal protein (0.72), total protein (0.92)
Glutamic acid, %protein
Starch (0.52), arachidonic acid (-0.51), glycine %kcal (-0.55), glycine %protein (-0.62), total grains (0.52),
animal protein (-0.55), proline (0.80), phenylalanine (0.59), alanine (-0.78), threonine (-0.66),
methionine (-0.51), lysine (-0.70), arginine (-0.53), aspartic acid (-0.70), total fresh meat, fish (-0.63),
fresh meat, poultry (-0.60)
Starch
Vegetable protein (0.66), glutamic acid %protein (0.52), total grains (0.79), lysine (-0.51)
Fiber
Vegetable protein (0.77), magnesium (0.77), total vegetables (0.57), fresh fruit (0.57)
Calcium
Phosphorus (0.80), riboflavin (0.69), vitamin D (0.64), glycine %protein (-0.60), lactose (0.86),
proline (0.53), leucine (0.62), valine (0.71), tyrosine (0.65), isoleucine (0.57), milk (0.82),
milk, yogurt, frozen yogurt, cocoa (0.84)
Magnesium
Vegetable protein (0.63), fiber (0.77), iron (0.55), non-heme iron (0.56), phosphorus (0.66)
Iron
Magnesium (0.55), riboflavin (0.62), ready-to-eat cereals (0.67)
Non-heme iron
Vegetable protein (0.51), magnesium (0.56), riboflavin (0.62), ready-to-eat cereals (0.69)
Phosphorus
Glutamic acid %kcal (0.74), calcium (0.80), magnesium (0.66), riboflavin (0.72), vitamin D (0.63),
animal protein (0.52), total protein (0.68), lactose (0.68), valine (0.55), isoleucine (0.50), milk (0.67),
milk, yogurt, frozen yogurt, cocoa (0.69)
Riboflavin
Calcium (0.69), iron (0.62), non-heme iron (0.62), phosphorus (0.72), vitamin D (0.61), retinol (0.66),
lactose (0.64), milk (0.64), milk, yogurt, frozen yogurt, cocoa (0.65), ready-to-eat cereals (0.60)
continued on next page
9
Online Table S5. continued, page 2
Vitamin D
Calcium (0.64), phosphorus (0.63), riboflavin (0.61), lactose (0.71), valine (0.51), isoleucine (0.50),
milk (0.75), milk, yogurt, frozen yogurt, cocoa (0.73)
Cholesterol
Arachidonic acid (0.63), eggs (0.83), methionine (0.51)
Arachidonic acid
Glutamic acid %protein (-0.51), cholesterol (0.63), glycine %kcal (0.57), poultry (0.52),
animal protein (0.55), proline (-0.53), alanine (0.57), methionine (0.54), lysine (0.50),
total fresh meat, fish (0.60), fresh meat, poultry (0.51)
Estimated total sugars
Sugar-sweetened beverages (0.53), total fatty acids (-0.52)
Σ fructose, glucose, sucrose
Sugar-sweetened beverages (0.63)
Glycine, %kcal
Glutamic acid %kcal (0.72), glutamic acid %protein (-0.55), arachidonic acid (0.57), poultry (0.53),
selenium (0.58), animal protein (0.86), total protein (0.90), proline (-0.57), alanine (0.63), threonine (0.52),
lysine (0.58), total fresh meat, fish (0.86), fresh meat, poultry (0.79)
Glycine, %protein
Glutamic acid %protein (-0.62), calcium (-0.60), proline (-0.71), phenylalanine (-0.62), serine (-0.60),
alanine (0.84), arginine (0.69), aspartic acid (0.54), tyrosine (-0.55), total fresh meat, fish (0.58),
fresh meat, poultry (0.57)
Total PFA
Oleic acid (0.52), total MFA (0.51), vitamin E (0.50),
total animal fats, margarines, table spreads, oils, shortening, salad dressing (0.62)
Σ long chain PFA
Fish, fish roe, shellfish (0.79), fish, fish roe (0.78)
Total Omega-6 PFA
Oleic acid (0.53), vitamin E (0.51),
total animal fats, margarines, table spreads, oils, shortening, salad dressing (0.61)
Linoleic acid
Oleic acid (0.53), vitamin E (0.51),
total animal fats, margarines, table spreads, oils, shortening, salad dressing (0.61)
Oleic acid
Total PFA (0.52), total Omega-6 FA (0.53), linoleic acid (0.53), total SFA (0.68),
total available carbohydrate (-0.67)
Urinary metabolites
Hippurate
N-methylnicotinic acid (0.63)
Abbreviations: Σ, sum of; MFA, monounsaturated fatty acids; PFA, polyunsaturated fatty acids; SFA, saturated fatty acids.
Units are: g/1,000 kcal (foods, food subgroups), %kcal or amount/1,000 kcal (nutrients); %kcal or %protein (glutamic acid, glycine);
mmol/24-hour (urinary metabolites).
* 125 variables were included in the partial correlation matrix, adjusted for age, gender, sample. 32 variables from Online Tables 1 and 2
and Table 2 with correlations >0.5 are listed here. No correlations >0.5 were observed for raw vegetables; pasta, rice; bread, rolls, biscuits;
processed meats; pork; fruit juices, drinks; cream; cream, cheese, ice-cream, milk and cheese recipes; urinary potassium; urinary
sodium/potassium ratio; total Omega-3 PFA; PFA/SFA ratio. List excludes correlations between sums or ratios and their constituent
variables.
†
N for urinary metabolites is 1,426, 91.5% of these participants.
10
Online Table S6. Reliability data – foods, nutrients, two quantitated urinary metabolites, systolic and diastolic blood pressure
Variable
Men
Women
AA (N=165)
NHWA (N=620)
AA (N=204)
NHWA (N=570)
†
Ratio*
(% )
Ratio
(%)
Ratio
(%)
Ratio
(%)
Foods with possible favorable relation to blood pressure – lower intake in AA than NHWA
Total vegetables
1.68
(54.4)
1.47
(57.7)
2.28
(46.7)
1.49
(57.3)
Vegetables, raw
5.55
(26.5)
2.61
(43.4)
2.80
(41.6)
1.41
(58.7)
Fruit, fresh
1.16
(63.3)
0.85
(70.3)
1.91
(51.2)
1.67
(54.5)
Pasta, rice
1.12
(64.1)
3.28
(37.9)
(-)
4.03
(33.1)
Total grains
1.29
(60.9)
1.97
(50.4)
4.01
(33.3)
2.71
(42.5)
Bread, rolls, biscuits, related
products
5.08
(28.3)
1.44
(58.1)
1.61
(55.5)
1.84
(52.1)
Foods with possible unfavorable relation to blood pressure – higher intake in AA than NHWA
Processed meats
11.68
(14.6)
5.35
(27.2)
2.55
(43.9)
4.46
(31.0)
Pork
8.32
(19.4)
9.36
(17.6)
4.09
(32.9)
(-)
Eggs
2.15
(48.2)
3.50
(36.4)
7.66
(20.7)
5.20
(27.8)
Fruit juice, drinks
1.25
(61.5)
0.65
(75.4)
1.40
(58.7)
0.65
(75.5)
Sugar sweetened beverages
0.68
(74.6)
0.44
(82.1)
0.60
(76.9)
0.75
(72.7)
Foods with possible favorable relation to blood pressure – higher intake in AA than NHWA
Fish, fish roe, shellfish
15.84
(11.2)
3.46
(36.6)
(-)
5.11
(28.1)
Poultry
2.69
(42.6)
7.46
(21.1)
4.86
(29.2)
6.98
(22.3)
Foods with possible unfavorable relation to blood pressure – lower intake in AA than NHWA
Cream
3.09
(39.3)
1.59
(55.7)
2.03
(49.6)
1.76
(53.1)
Cheese
9.02
(18.2)
3.87
(34.1)
5.47
(26.8)
2.61
(43.4)
Cream, cheese, ice cream,
milk & cheese recipes
1.30
(60.6)
2.82
(41.5)
2.39
(45.6)
3.51
(36.3)
Alcoholic beverages
0.21
(90.5)
0.54
(78.7)
0.23
(89.6)
0.27
(87.9)
continued on next page
11
Online Table S6. continued, page 2
Nutrients with possible favorable relation to blood pressure – lower intake in AA than NHWA
Vegetable protein
0.86
(70.0)
0.84
(70.5)
1.23
(61.9)
Glutamic acid, %kcal
1.95
(50.6)
1.31
(60.4)
1.73
(53.7)
Glutamic acid, %protein
4.13
(32.6)
1.97
(50.3)
2.31
(46.4)
Starch
1.05
(65.5)
1.42
(58.5)
1.22
(62.2)
Total dietary fiber
0.74
(73.0)
0.72
(73.5)
0.88
(69.4)
Calcium
2.31
(46.4)
0.82
(70.9)
1.64
(55.0)
Magnesium
0.76
(72.5)
0.90
(69.1)
1.22
(62.1)
Iron
1.31
(60.5)
1.03
(65.9)
3.35
(37.4)
Non-heme iron
1.27
(61.1)
1.01
(66.5)
2.82
(41.5)
Phosphorus
2.07
(49.2)
0.85
(70.1)
1.14
(63.7)
Riboflavin
1.95
(50.7)
0.87
(69.7)
2.42
(45.2)
Vitamin D
4.93
(28.8)
1.57
(56.0)
1.74
(53.5)
Urinary potassium
1.03
(65.9)
0.78
(72.0)
0.64
(75.7)
Nutrients with possible unfavorable relation to blood pressure – higher intake in AA than NHWA
Dietary cholesterol
2.10
(48.7)
1.89
(51.4)
2.09
(48.9)
Arachidonic acid
5.43
(26.9)
2.70
(42.5)
6.59
(23.3)
Estimated total sugars
0.67
(74.8)
0.53
(79.2)
0.77
(72.2)
Σ fructose, glucose, sucrose
0.62
(76.3)
0.50
(80.0)
0.61
(76.5)
Glycine, %kcal
1.97
(50.4)
1.78
(53.0)
2.50
(44.4)
Glycine, %protein
2.77
(42.0)
1.80
(52.6)
3.18
(38.6)
Ratio, urinary
sodium/potassium
1.37
(59.3)
1.26
(61.4)
1.48
(57.5)
Nutrients with possible favorable relation to blood pressure – higher intake in AA than NHWA
Total PFA
1.35
(59.7)
1.87
(51.7)
2.00
(50.0)
Total Omega-3 PFA
2.10
(48.8)
2.20
(47.7)
1.84
(52.1)
Σ long chain PFA
5.76
(25.8)
5.54
(26.5)
3.72
(35.0)
Total Omega-6 PFA
1.47
(57.6)
1.85
(52.0)
2.15
(48.2)
Linoleic acid
1.47
(57.7)
1.84
(52.0)
2.15
(48.2)
Oleic acid
1.82
(52.4)
1.45
(58.0)
1.46
(57.8)
Ratio, PFA/SFA
1.65
(54.8)
2.39
(45.6)
2.18
(47.9)
continued on next page
12
1.21
2.11
3.29
1.55
0.90
1.15
0.94
1.28
1.23
1.40
1.40
1.42
0.68
(62.4)
(48.6)
(37.8)
(56.4)
(68.9)
(63.5)
(68.0)
(60.9)
(61.8)
(58.8)
(58.9)
(58.5)
(74.5)
2.99
3.72
0.85
0.85
2.18
1.87
(40.1)
(35.0)
(70.1)
(70.2)
(47.8)
(51.6)
1.66
(54.6)
1.88
1.07
5.93
1.89
1.89
1.11
2.81
(51.5)
(65.0)
(25.2)
(51.4)
(51.4)
(64.3)
(41.6)
Online Table S6. continued, page 3
Nutrients with possible unfavorable relation to blood pressure – lower intake in AA than NHWA
None
Other variables‡
Urinary sodium
2.17
(48.0)
1.10
(64.5)
1.20
(62.5)
14-day alcohol, all
0.16
(92.7)
0.29
(87.2)
0.28
(87.8)
§
Urinary metabolites
Urinary hippurate
1.26
(61.4)
0.69
(74.3)
0.66
(75.1)
Urinary N-methyl nicotinic acid
0.53
(79.0)
0.31
(86.5)
0.46
(81.2)
Blood pressure
Systolic blood pressure
0.18
(91.6)
0.20
(91.0)
0.20
(91.1)
Diastolic blood pressure
0.25
(88.9)
0.21
(90.3)
0.28
(87.8)
1.74
0.39
(53.5)
(83.7)
0.61
0.25
(76.7)
(89.1)
0.18
0.22
(91.7)
(90.2)
Abbreviations: Σ, sum of; MFA, monounsaturated fatty acids; PFA, polyunsaturated fatty acids; SFA, saturated fatty acids.
Units are: g/1,000 kcal (foods, food subgroups), %kcal or amount/1,000 kcal (nutrients); %kcal or %protein (glutamic acid, glycine);
mmol/24-hour (urinary NMR metabolites); mm Hg (blood pressure).
* Ratio is intra-individual variance divided by inter-individual variance, for dietary variables and blood pressure this was calculated from
mean values of visits 1 and 2 and visits 3 and 4 (to account for higher correlation between values on consecutive days); for urinary
variables, from the first and second collections. It was not possible to calculate the ratio for variables and population substrata where a large
proportion of participants reported zero intake (9-11).
†
Observed coefficient from univariate regression as a percentage of ‘true’ theoretical coefficient, calculated from the formula
1/[1+(ratio/2)]×100.
‡
Variables did not differ significantly between AA and NHWA but were included here due to their important established effects on blood
pressure.
§
N for hippurate and N-methyl nicotinic acid is 146 AA and 578 NHWA men, 188 AA and 514 NHWA women.
13
Online Table S7. Relation of individual food/food subgroup intakes, significantly different in AA and NHWA, to higher BP of AA than NHWA,
considered singly, by gender
Model
Systolic BP
Diastolic BP
BP
% change
BP
% change
difference (Z score)
from C
difference (Z score) from C
Men (N=165 AA, 620 NHWA)
A: age, sample
5.41
(4.40)
3.46
(3.94)
B: A + medical history of CVD/diabetes,
4.68
(3.80)
3.38
(3.84)
family history of hypertension, physical
activity, special diet, supplement use
C: B + BMI
4.76
(4.04)
3.43
(4.05)
Foods with possible favorable relation to blood pressure – lower intake in AA than NHWA
C + Total vegetables
4.50
(3.78)
-5.6
3.31
(3.88)
-3.6
C + Vegetables, raw
4.48
(3.78)
-5.9
3.26
(3.83)
-5.0
C + Fruit, fresh
4.65
(3.95)
-2.4
3.40
(4.01)
-1.1
C + Pasta/rice
4.79
(4.06)
0.7
3.43
(4.05)
-0.1
C + Total grains
4.61
(3.91)
-3.1
3.39
(3.99)
-1.2
C + Bread/rolls/biscuits/related products
4.90
(4.11)
2.8
3.49
(4.07)
1.6
Foods with possible unfavorable relation to blood pressure – higher intake in AA than NHWA
C + Processed meats
4.68
(3.99)
-1.6
3.41
(4.03)
-0.7
C + Pork
4.72
(3.99)
-1.0
3.37
(3.97)
-2.0
C + Eggs
4.68
(3.94)
-1.7
3.42
(4.00)
-0.6
C + Fruit juices/drinks
4.91
(4.11)
3.1
3.45
(4.02)
0.5
C + Sugar sweetened beverages
4.34
(3.64)
-9.0
3.23
(3.76)
-6.1
Foods with possible favorable relation to blood pressure – higher intake in AA than NHWA
C + Fish/fish roe/shellfish
4.76
(4.03)
-0.1
3.44
(4.05)
0.1
C + Poultry
4.98
(4.13)
4.6
3.78
(4.37)
10.0
Foods with possible unfavorable relation to blood pressure – lower intake in AA than NHWA
C + Cream
4.87
(4.12)
2.3
3.50
(4.12)
2.0
C + Cheese
4.76
(3.94)
-0.1
3.45
(3.98)
0.6
C + Cream/cheese/ice cream/milk &
cheese recipes
4.71
(3.97)
-1.1
3.49
(4.10)
1.7
C + Alcoholic beverages
4.62
(3.94)
-3.0
3.35
(3.97)
-2.4
continued on next page
14
Online Table S7. continued, page 2
Women (N=204 AA, 570 NHWA)
A: age, sample
9.66
(8.02)
5.03
B: A + medical history of CVD/diabetes,
9.00
(7.42)
4.83
family history of hypertension, physical
activity, special diet, supplement use
C: B + BMI
6.76
(5.76)
3.77
Foods with possible favorable relation to blood pressure – lower intake in AA than NHWA
C + Total vegetables
6.75
(5.75)
-0.1
3.77
C + Vegetables, raw
6.71
(5.71)
-0.7
3.76
C + Fruit, fresh
6.69
(5.70)
-1.0
3.75
C + Pasta/rice
6.53
(5.56)
-3.4
3.66
C + Total grains
6.27
(5.19)
-7.3
3.41
C + Bread/rolls/biscuits/related products
7.13
(6.00)
5.5
3.84
Foods with possible unfavorable relation to blood pressure – higher intake in AA than NHWA
C + Processed meats
6.47
(5.49)
-4.3
3.66
C + Pork
7.05
(5.98)
4.3
3.94
C + Eggs
6.63
(5.62)
-1.9
3.76
C + Fruit juices/drinks
7.13
(6.03)
5.5
4.01
C + Sugar sweetened beverages
6.46
(5.17)
-4.4
3.78
Foods with possible favorable relation to blood pressure – higher intake in AA than NHWA
C + Fish/fish roe/shellfish
6.82
(5.82)
0.9
3.80
C + Poultry
6.65
(5.52)
-1.7
3.72
Foods with possible unfavorable relation to blood pressure – lower intake in AA than NHWA
C + Cream
6.80
(5.77)
0.6
3.81
C + Cheese
6.74
(5.65)
-0.3
3.68
C + Cream/cheese/ice cream/milk &
6.68
(5.61)
-1.2
3.79
cheese recipes
C + Alcoholic beverages
6.74
(5.75)
-0.3
3.76
(6.52)
(6.20)
(4.87)
(4.87)
(4.85)
(4.83)
(4.72)
(4.28)
(4.89)
0.0
-0.3
-0.7
-2.9
-9.6
1.8
(4.70)
(5.06)
(4.83)
(5.14)
(4.58)
-2.8
4.4
-0.2
6.4
0.2
(4.90)
(4.68)
0.7
-1.4
(4.90)
(4.67)
(4.82)
1.0
-2.4
0.4
(4.86)
-0.4
Unit for foods is g/1,000 kcal.
Z score = regression coefficient/standard error. |Z| ≥ 1.96, uncorrected P ≤ 0.05; |Z| ≥ 2.58, uncorrected P≤0.01; |Z| ≥ 3.29, uncorrected
P≤0.001.
15