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Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians

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  • Xiaoqi Feng
  • Andrew Wilson

Abstract

Do socioeconomic inequities in body mass index (BMI) widen across the adult lifecourse? BMI data for 29,104 male and 32,454 female person-years aged 15 years and older (21,403 persons in total) were extracted from the Household, Income and Labour Dynamics in Australia between 2006 and 2012. Multilevel linear regression was used to examine age and gender specific trajectories in BMI by quintiles of neighborhood socioeconomic circumstance. Models were adjusted for probable sources of confounding, including couple status, number of children resident, if somebody in the household had been pregnant in the last 12 months, the highest level of education achieved, the average household gross income, and the percentage of time in the last year spent unemployed. Approximately 9.6% of BMI variation was observed between neighborhoods. High neighborhood disadvantage was associated with 2.09 kg/m2 heavier BMI (95%CI 1.82, 2.36). At age 15-24y, socioeconomic inequity in BMI was already evident among men and women especially (22.6 kg/m2 among women in the most affluent areas compared with 25.4 kg/m2 among the most disadvantaged). Among women only, the socioeconomic gap widened from 2.8 kg/m2 at age 15-24y to 3.2 kg/m2 by age 35-44y. Geographical factors may contribute to more rapid weight gain among women living in disadvantaged neighborhoods.

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  • Xiaoqi Feng & Andrew Wilson, 2015. "Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-9, October.
    • Handle: RePEc:plo:pone00:0141499
    DOI: 10.1371/journal.pone.0141499
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    1. Mark Wooden & Simon Freidin & Nicole Watson, 2002. "The Household, Income and Labour Dynamics in Australia (HILDA)Survey: Wave 1," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 35(3), pages 339-348, September.
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    3. Geronimus, A.T. & Hicken, M. & Keene, D. & Bound, J., 2006. ""Weathering" and age patterns of allostatic load scores among blacks and whites in the United States," American Journal of Public Health, American Public Health Association, vol. 96(5), pages 826-833.
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    1. Yea-Li-A Song & Jae-Hyun Park, 2022. "Differences in Body Mass Index Trajectories and Their Classification, Sociodemographic Characteristics, and Health Behaviors between People with and without Disabilities Using Korea Health Panel Surve," IJERPH, MDPI, vol. 19(5), pages 1-13, February.
    2. Letarte, Laurence & Samadoulougou, Sekou & McKay, Rachel & Quesnel-Vallée, Amélie & Waygood, E.O.D. & Lebel, Alexandre, 2022. "Neighborhood deprivation and obesity: Sex-specific effects of cross-sectional, cumulative and residential trajectory indicators," Social Science & Medicine, Elsevier, vol. 306(C).

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