(Hypertension. 1997;30:1511-1516.)
© 1997 American Heart Association, Inc.
Articles |
From the Department of Preventive Medicine and Epidemiology (J.S.K., A.L., A.E.L., R.S.C.), Loyola University Stritch School of Medicine, Maywood, Ill; the Department of Preventive and Social Medicine (M.C.A.), University College Hospital, Ibadan, Oyo State, Nigeria; the Department of Physiology (J.M.), University of Zimbabwe, Harare, Zimbabwe; and the Tropical Metabolism Research Unit (T.F., R.W.), University of the West Indies, Mona, Jamaica.
Correspondence and reprint requests to Jay S. Kaufman, PhD, Department of Research Planning and Evaluation, Carolinas Medical Center, PO Box 32861, Charlotte, NC 28232-2861. E-mail jkaufma{at}orion.it.luc.edu
| Abstract |
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Key Words: blood pressure body mass index Africa epidemiology
| Introduction |
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Although the question is often framed in terms of "obesity," defined by BMI cutpoints, correlations between BMI and blood pressure have been observed even in very lean populations, including groups in Africa,7,8 Asia,9,10 and South America.11 Large studies of low-BMI groups in Asia appear to show a monotonic relationship between BMI and blood pressure among groups for whom treatment and other potential confounders are rare.12,13 These studies also show a consistently steeper slope of blood pressure with BMI for men than for women. These observations present both an opportunity and a challenge for biological inference. If body fat is the operative characteristic, for example, then why should women, who have a higher percentage of body fat than men at any given BMI value, have a shallower slope of blood pressure with BMI?
Interpreting the blood pressureBMI relationship is further complicated by the suggestion from some studies of a threshold effect below which there appears to be no correlation between the variables.14 Some of these studies have relatively small samples and therefore limited power to detect a true relationship.15 It is not surprising, therefore, that the threshold is suggested most commonly for women, who tend to exhibit weaker correlations between BMI and blood pressure in all studies. Some authors have suggested that for women in unindustrialized settings there is no identifiable association between blood pressure and BMI, even at levels that would be considered obese (ie, 30 kg/m2).16,17 Even in studies with substantial statistical power, however, analyses are seldom conducted that explore the consistency of the blood pressureBMI correlation across the range of BMI values. Despite significant overall slopes or linear correlations, therefore, thresholds are not directly contradicted by any of the published data of which we are aware.
We sought to explore nonlinearity (eg, thresholds) in the relationship between blood pressure and BMI in a pooled sample of individuals from low-BMI populations in Africa and the Caribbean. Specifically, we wished to replicate the finding of Bunker et al14 of a threshold BMI below which there is no association between BMI and blood pressure, in contrast to other studies that propose a roughly linear pattern of association. Additional goals of the study were to assess any relationship between mean blood pressure in a population and the magnitude of association between BMI and blood pressure, to compare the magnitude of association for men and women, and to use these observed patterns to further biological inferences concerning the mechanisms through which BMI is predictive of blood pressure.
| Methods |
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Multivariate linear regression was used to estimate age-adjusted slopes of blood pressure with BMI. Age-adjusted means for blood pressure and BMI were computed using direct standardization based on the proportions in each age decile in the combined superpopulation. Although it has been the most common analytical strategy, we avoided categorization of BMI because of the consequent loss of power and the bias associated with choice of categorization points.24 Rather, we depicted the sex- and age-specific associations between blood pressure and BMI using "lowess" kernel smoothing (bandwidth=0.5) in each sex by age-category strata.25 To avoid misinterpretation of erratic behavior in regions with sparse data, plots were constructed from these analyses by using values from the 5th to 95th percentiles of BMI in each gender group. Finally, the threshold hypothesis was tested using splined linear regression with a single change point.24 The location of this singular knot was selected by searching iteratively over the range of BMI values to minimize the covariate-adjusted sum of square errors. All analyses were conducted using Stata Statistical Software.26
| Results |
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The linear slopes of blood pressure with BMI, adjusted for age, for SBP
and DBP by site and gender are shown in Table 2
. All sites had positive slope
estimates, and all but one were significantly different from zero at
the P<.05 level with the available sample sizes.
Age-adjusted slopes for SBP ranged from 0.40 to 1.70 for men and 0.15
to 1.04 for women. For DBP, the ranges were 0.48 to 1.24 for men and
0.33 to 0.77 for women. In every site, slopes were steeper for men than
women, with the male/female ratio ranging from 1.06 to 2.98 for SBP and
1.40 to 1.86 for DBP. There was a positive correlation between
age-adjusted slope of BMI and mean blood pressure in a population. For
SBP, for example, the coefficient was equal to 0.52 (Fig 1
). Mean SBPs by continuous BMI, age
category, and gender are shown in Figs 2
and 3
(analyses for DBP were
similar and were omitted for the sake of brevity). For men, there was a
roughly linear association between SBP and BMI in all age groups, with
a slope that is approximately constant at nearly 1.0 across the age
range, shifted only by a constant. For women, on the other hand, the
younger age categories resemble the plots for men, albeit with a more
modest slope and a flattening out at lower BMI values; women aged 45
years and above had a more distinct leveling or even possible upturn at
BMI values lower than about 21 kg/m.2 On the basis
of these analyses, we determined that we could pool the age
strata for men and adjust for age, since ANCOVA assumptions apply (ie,
parallel lines in each age strata). For women, the distinct shapes in
younger versus older women suggest an age modification in the blood
pressureBMI relationship that warrants stratification of the women
into two groups at age 45.
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To further clarify the potential threshold in the relationship between blood pressure and BMI among women, we used iterative searching with a spline regression model with a single variable knot. Running the possible knot locations from the 5th to the 95th percentile of BMI values for each of the three groups (men, younger women, and older women) led to a minimum age-adjusted residual sum of squares with the knot at a BMI value of 21.0 kg/m2 for both groups of women. For men, the criterion was met at the extreme BMI value, further indicating that no change point was indicated in that group.
Estimates from linear regression for men and spline regression with a
knot at 21.0 for both groups of women are shown in Table 3
. Differences between younger and older
women appear to be less dramatic once age has been adjusted for within
each category. Both age groups show a significant slope above the
threshold and essentially no slope below the threshold (Fig 4
). When the two groups of women were
combined, we found a slope estimate below the threshold of essentially
zero (ß=-0.21; 95% CI, -0.63 to 0.21) and an estimate above the
threshold of ß=0.57 (95% CI, 0.44 to 0.70). These slopes are also
significantly different (P=.002). Table 3
also shows results
for a trimmed regression in which the most extreme values (upper and
lower 5%) are omitted. This restriction increases the magnitude of the
estimates both above and below the knot and accentuates the statistical
difference between the slopes.
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| Discussion |
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While the outcome we observed is relatively straightforward on a descriptive level, its interpretation is less so. The pathophysiological significance of relative weight has never been well defined. In addition to greater fat stores and its associated direct metabolic consequences, persons with higher BMI values consume more sodium27,28 and engage in less physical activity.29 To make matters more complex, changes in body composition and fat distribution are not linear with BMI and vary by gender. A recent study by our group using bioelectric impedance analysis demonstrated a curvilinear relationship between BMI and percent body fat in these same populations.30 Of course women have twice the percent body fat at a given BMI than men and appear to regulate related hormones, like leptin, at a different level.31
A number of metabolic consequences of obesity have been proposed as the blood pressureelevating mechanism.2 Increasing weight has been shown to increase salt retention;32,33 and insulin resistance is proposed by some to be a cause of hypertension; adipose tissue produces substantial amounts of AGT, and we recently documented a correlation between BMI and AGT, and between blood pressure and AGT, independent of BMI in Nigerian and Jamaican population samples.34,35 Physical activity can have a substantial effect on blood pressure.36 We have recently shown a strong inverse correlation between energy expended in physical activity and fat stores in this same Nigerian population using the doubly labeled water technique.37 BMI should therefore be viewed conceptually as a proxy for other causal exposures; whether it is diet, hormone changes, physical activity, or other factors that link increasing relative weight to rises in blood pressure cannot be determined at the present. It is clear from the data in this study, however, that obesity, per se, is not required for this association to be manifest, since for men at least BMI values <21 kg/m2 appear linearly related to blood pressure.
It would seem most reasonable to view the BMIblood pressure relationship over the broadest range as sigmoid in shape. At the lowest extreme, blood pressure cannot approach zero, but must asymptote above a SBP of 80 to 100 mm Hg. By the same token, the cardiovascular system cannot sustain pressures much greater than 200 mm Hg for long periods of time. From that perspective, it would appear that for women, but not men, the lower range of that sigmoid curve is reached at a BMI of roughly 21. For men, on the other hand, the curve appears to have undergone a leftward shift and this flattening of the slope is not seen. A leftward shift would also be consistent with the steeper slope among men. Whether these gender differences are related to sexual dimorphism in body composition cannot be stated. At the same time, whether the patterns we observed are unique to this population, or even this sample, can only be determined by comparative studies. Our relatively large sample size and replication in multiple distinct samples lend consistency to the data, however.
In summary, we have investigated in further detail the relationship between BMI and blood pressure at the lower ranges of relative weight. A diminution of the slope between these two variables is apparent for women but not men. At the same time, this slope is only half as steep for women. The underlying mechanistic processes that link changes in relative weight to its physiological consequences for blood pressure regulation deserve to be better studied. Modeling this relationship with greater precision remains an important challenge for epidemiologists. Studies that measure body composition directly and provide information on physiological intermediates should be particularly useful.
| Selected Abbreviations and Acronyms |
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| Acknowledgments |
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Received April 11, 1997; first decision April 30, 1997; accepted June 13, 1997.
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