Trends across time in socioeconomic differences in body mass index: a comparison of population and individual-level approaches

Author:

Wright LiamORCID,Staatz Charis Bridger,Silverwood Richard J,Bann DavidORCID

Abstract

AbstractBackgroundSocioeconomic differences in body mass index (BMI) have widened alongside the obesity epidemic. However, the utility of socioeconomic position (SEP) indicators at the individual level remains uncertain, as does the potential temporal variation in their predictive value. Examining this is important in light of the increasing incorporation of SEP indicators into predictive algorithms and the possibility that SEP has become a more important predictor of BMI over time. We thus investigated SEP differences in BMI over three decades of the obesity epidemic in England and compared population-wide (SEP group differences in mean BMI) and individual-level (out-of-sample prediction of individuals’ BMI) approaches.MethodsWe used repeated cross-sectional data from the Health Survey for England, 1991-2019. BMI (kg/m2) was measured objectively, and SEP was measured via educational attainment and neighborhood index of deprivation (IMD). We ran random forest models for each survey year and measure of SEP adjusting for age and sex.ResultsThe mean and variance of BMI increased within each SEP group over the study period. Mean differences in BMI by SEP group also increased across time: differences between lowest and highest education groups were 1.0 kg/m2(0.4, 1.6) in 1991 and 1.5 kg/m2(0.9, 1.8) in 2019. At the individual level, the predictive capacity of SEP was low, though increased in later years: including education in models improved predictive accuracy (mean absolute error) by 0.14% (−0.9, 1.08) in 1991 and 1.06% (0.17, 1.84) in 2019. Similar patterns were obtained when analyzing obesity, specifically.ConclusionSEP has become increasingly important at the population (group difference) and individual (prediction) levels. However, predictive ability remains low, suggesting limited utility of including SEP in prediction algorithms. Assuming links are causal, abolishing SEP differences in BMI could have a large effect on population health but would neither reverse the obesity epidemic nor explain the vast majority of individual differences in BMI.

Publisher

Cold Spring Harbor Laboratory

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