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Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment

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  • Davillas, Apostolos
  • Jones, Andrew M.

Abstract

We use nationally representative English data to examine regional variations in body mass index (BMI) and waist circumference (WC), and to explore their underlying sources. Beyond our “at the mean” analysis, Shapley decomposition combined with unconditional quantile regression analysis allow us to explore the relative contribution of small-area level proxies of the obesogenic environment as opposed to our set of individual-level characteristics, across the whole adiposity distribution. We find that the regional BMI differences, that are more evident towards the right tails of its distribution, are fully accounted for by the neighbourhood obesogenic environment. The latter exerts an independent contribution to excess adiposity over and above the potential mediating role of individual-level lifestyle and socio-economic position (SEP). Overall, the relative contribution of demographics (age and gender) becomes less evident moving to higher quantiles of the BMI distribution, while that of obesogenic environment, individual-level lifestyle and SEP measures becoming more relevant. The neighbourhood obesogenic environment is also much more relevant in the tails of the WC distribution. The role of the obesogenic environment on excess adiposity is more pronounced for women than men. Overall, our results highlight that policies that aim to tackle excess adiposity should address both people and places.

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  • Davillas, Apostolos & Jones, Andrew M., 2020. "Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment," Economics & Human Biology, Elsevier, vol. 38(C).
    • Handle: RePEc:eee:ehbiol:v:38:y:2020:i:c:s1570677x20300344
    DOI: 10.1016/j.ehb.2020.100887
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    Cited by:

    1. Sun, Hongye & Kim, Giseung, 2021. "The composite impact of ICT industry on lowering carbon intensity: From the perspective of regional heterogeneity," Technology in Society, Elsevier, vol. 66(C).
    2. Davillas, Apostolos & Jones, Andrew M, 2020. "Ex ante inequality of opportunity in health, decomposition and distributional analysis of biomarkers," Journal of Health Economics, Elsevier, vol. 69(C).
    3. Nie, Peng & Ding, Lanlin & Jones, Andrew M., 2020. "Inequality of Opportunity in Bodyweight among Middle-Aged and Older Chinese: A Distributional Approach," IZA Discussion Papers 13421, Institute of Labor Economics (IZA).
    4. Davillas, Apostolos & Benzeval, Michaela, 2016. "Alternative measures to BMI: Exploring income-related inequalities in adiposity in Great Britain," Social Science & Medicine, Elsevier, vol. 166(C), pages 223-232.
    5. Davillas, Apostolos & Pudney, Stephen, 2020. "Biomarkers as precursors of disability," Economics & Human Biology, Elsevier, vol. 36(C).
    6. Aránzazu Hernández-Yumar & Maria Wemrell & Ignacio Abásolo-Alessón & Beatriz González López-Valcárcel & Juan Merlo, 2023. "Impact of the Economic Crisis on Body Mass Index in Spain: An Intersectional Multilevel Analysis Using a Socioeconomic and Regional Perspective," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(4), pages 1-31, August.
    7. Dolton, Peter J. & Tafesse, Wiktoria, 2022. "Childhood obesity, is fast food exposure a factor?," Economics & Human Biology, Elsevier, vol. 46(C).

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    More about this item

    Keywords

    Adiposity; Obesogenic environment; Regional inequality; Decomposition analysis;
    All these keywords.

    JEL classification:

    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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