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Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy

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  • Aránzazu Hernández-Yumar
  • Maria Wemrell
  • Ignacio Abásolo Alessón
  • Beatriz González López-Valcárcel
  • George Leckie
  • Juan Merlo

Abstract

Many studies have demonstrated the existence of simple, unidimensional socioeconomic gradients in body mass index (BMI). However, in the present paper we move beyond such traditional analyses by simultaneously considering multiple demographic and socioeconomic dimensions. Using the Spanish National Health Survey 2011–2012, we apply intersectionality theory and multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to analyze 14,190 adults nested within 108 intersectional strata defined by combining categories of gender, age, income, educational achievement and living situation. We develop two multilevel models to obtain information on stratum-specific BMI averages and the degree of clustering of BMI within strata expressed by the intra-class correlation coefficient (ICC). The first model is a simple variance components analysis that provides a detailed mapping of the BMI disparities in the population and measures the accuracy of stratum membership to predict individual BMI. The second model includes the variables used to define the intersectional strata as a way to identify stratum-specific interactions. The first model suggests moderate but meaningful clustering of individual BMI within the intersectional strata (ICC = 12.4%). Compared with the population average (BMI = 26.07 Kg/m2), the stratum of cohabiting 18-35-year-old females with medium income and high education presents the lowest BMI (-3.7 Kg/m2), while cohabiting 36-64-year-old females with low income and low education show the highest BMI (+2.6 Kg/m2). In the second model, the ICC falls to 1.9%, suggesting the existence of only very small stratum specific interaction effects. We confirm the existence of a socioeconomic gradient in BMI. Compared with traditional analyses, the intersectional MAIHDA approach provides a better mapping of socioeconomic and demographic inequalities in BMI. Because of the moderate clustering, public health policies aiming to reduce BMI in Spain should not solely focus on the intersectional strata with the highest BMI, but should also consider whole population polices.

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  • Aránzazu Hernández-Yumar & Maria Wemrell & Ignacio Abásolo Alessón & Beatriz González López-Valcárcel & George Leckie & Juan Merlo, 2018. "Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-23, December.
    • Handle: RePEc:plo:pone00:0208624
    DOI: 10.1371/journal.pone.0208624
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    References listed on IDEAS

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    Cited by:

    1. Alvarez, Camila H. & Evans, Clare Rosenfeld, 2021. "Intersectional environmental justice and population health inequalities: A novel approach," Social Science & Medicine, Elsevier, vol. 269(C).
    2. 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.
    3. Evans, Clare & Leckie, George & Subramanian, SV & Bell, Andrew & Merlo, Juan, 2024. "A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)," SocArXiv 635hx, Center for Open Science.
    4. Anna Persmark & Maria Wemrell & Sofia Zettermark & George Leckie & S V Subramanian & Juan Merlo, 2019. "Precision public health: Mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-21, August.
    5. Daniel Holman & Alan Walker, 2021. "Understanding unequal ageing: towards a synthesis of intersectionality and life course analyses," European Journal of Ageing, Springer, vol. 18(2), pages 239-255, June.
    6. Wilkes, Rima & Karimi, Aryan, 2024. "What does the MAIHDA method explain?," Social Science & Medicine, Elsevier, vol. 345(C).
    7. Evans, Clare R. & Nieves, Christina I. & Erickson, Natasha & Borrell, Luisa N., 2023. "Intersectional inequities in the birthweight gap between twin and singleton births: A random effects MAIHDA analysis of 2012–2018 New York City birth data," Social Science & Medicine, Elsevier, vol. 331(C).
    8. Philipp Jaehn & Emily Mena & Sibille Merz & Robert Hoffmann & Antje Gößwald & Alexander Rommel & Christine Holmberg & on behalf of the ADVANCE GENDER study group, 2020. "Non-response in a national health survey in Germany: An intersectionality-informed multilevel analysis of individual heterogeneity and discriminatory accuracy," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-17, August.

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