Abstract Background Globally, subsistence-level societies are experiencing rapid urbanization and concomitant increases in cardiometabolic diseases. Generalized measures to quantify lifestyle transitions will facilitate the identification of the most potent drivers of changing health within and between populations, enabling the identification of vulnerable communities, and aiding in the creation of effective policies to minimize disease. Methods We developed ten scales a priori to quantify unique facets of lifestyle (e.g. urban infrastructure, market integration) from cross-sectional data in two Indigenous, transitioning subsistence groups undergoing rapid change in very different ecological and sociopolitical contexts: Turkana pastoralists of northwest Kenya (n = 3692) and Orang Asli mixed subsistence practitioners of Peninsular Malaysia (n = 1119). We tested the extent to which these lifestyle scales predicted 16 measures of cardiometabolic health in each group. We also used factor analysis to decompose lifestyle data post hoc into salient axes, sensitivity analyses to identify the most important drivers of health, and sex-stratified analyses to investigate whether facets of lifestyle differentially impacted cardiometabolic health among males and females. Results Cardiometabolic health was best predicted by measures that quantified urban infrastructure and market-derived material wealth compared to metrics encompassing diet, mobility, or acculturation, and these results were highly consistent across Turkana and Orang Asli and across sexes. Factor analysis results were also highly consistent between the two groups, revealing that lifestyle variation decomposes into two distinct axes–representing the built environment and diet–which change at different paces and have different relationships with health. Conclusion Our analyses revealed surprising generalizability: in both the Turkana and Orang Asli, measures of local infrastructure and built environment better predicted cardiometabolic health than other facets of lifestyle that are seemingly more proximate to health, such as diet. We hypothesize that this is because the built environment impacts unmeasured proximate drivers like physical activity and broader access to market goods, and because it serves as a proxy duration of market integration. Our results support the usage of relatively simple and easy to characterize features of the built environment as a cross-cultural tool in the investigation of lifestyle impacts on cardiometabolic health.
Watowich et al. (Wed,) studied this question.
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