| Disentangling Basal and Accumulated Body Mass for Cross-population Comparisons |
| Authors: |
Daniel J. Hruschka, Craig Hadley, and Alexandra Brewis |
| Source: |
American Journal of Physical Anthropology, 153(4): 542–550; DOI: 10.1002/ajpa.22452 |
| Topic(s): |
Body Mass Index (BMI)
Economics
Ethnicity
Nutrition
Women's health
Youth
|
| Country: |
More than one region
Multiple Regions
|
| Published: |
APR 2014 |
| Abstract: |
Measures of human body mass confound 1) well-established population differences in body form and 2) exposure to obesogenic environments, posing challenges for using body mass index (BMI) in crosspopulation studies of body form, energy reserves, and obesity-linked disease risk. We propose a method for decomposing population BMI by estimating basal BMI (bBMI) among young adults living in extremely poor, rural households where excess body mass accumulation is uncommon. We test this method with nationally representative, cross-sectional Demographic and Health
Surveys (DHS) collected from 69,916 rural women (20–24 years) in 47 low-income countries. Predicting BMI by household wealth, we estimate country-level bBMI as the average BMI of young women (20–24 years) living in rural households with total assets <400 USD per capita. Above 400 USD per capita, BMI increases with both wealth and age. Below this point, BMI hits a baseline floor showing little effect of either age or wealth. Between-country variation in bBMI (range of 4.3 kg m22) is reliable across decades and age groups (R250.83–0.88). Country-level estimates of bBMI show no relation to diabetes prevalence or country-level GDP (R2<0.05), supporting its independence from excess body mass. Residual BMI (average BMI minus bBMI) shows better fit with both country-level GDP (R250.55 vs. 0.40) and diabetes prevalence (R250.23 vs. 0.17) than does conventional BMI. This method produces reliable estimates of bBMI across a wide range of nationally representative samples, providing a new approach to investigating population variation in body mass.
KEY WORDS body mass index; ethnicity; lean mass; fat-free mass |
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