Patterning of individual heterogeneity in body mass index: evidence from 57 low- and middle-income countries

Modeling variation at population level has become increasingly valued, but no clear application exists for modeling differential variation in health between individuals within a given population. We applied Goldstein’s method (in: Everrit, Howell (eds) Encyclopedia of statistics in behavioral science, Wiley, Hoboken, 2005) to model individual heterogeneity in body mass index (BMI) as a function of basic sociodemographic characteristics, each independently and jointly. Our analytic sample consisted of 643,315 non-pregnant women aged 15–49 years pooled from the latest Demographic Health Surveys (rounds V, VI, or VII; years 2005–2014) across 57 low- and middle-income countries. Individual variability in BMI ranged from 9.8 (95% CI: 9.8, 9.9) for the youngest to 23.2 (95% CI: 22.9, 23.5) for the oldest age group; 14.2 (95% CI: 14.1, 14.3) for those with no formal education to 19.7 (95% CI: 19.5, 19.9) for those who have completed higher education; and 13.6 (95% CI: 13.5, 13.7) for the poorest quintile to 20.1 (95% CI: 20.0, 20.2) for the wealthiest quintile group. Moreover, variability in BMI by age was also different for different socioeconomic groups. Empirically testing the fundamental assumption of constant variance and identifying groups with systematically large differentials in health experiences have important implications for reducing health disparity.