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

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. Multilev...

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Main Authors: Xiaoqi Feng, Andrew Wilson
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0141499
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spelling doaj-34cdfae1697f402da415ddd79cbab9792021-03-03T19:58:17ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011010e014149910.1371/journal.pone.0141499Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.Xiaoqi FengAndrew WilsonDo 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.https://doi.org/10.1371/journal.pone.0141499
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoqi Feng
Andrew Wilson
spellingShingle Xiaoqi Feng
Andrew Wilson
Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.
PLoS ONE
author_facet Xiaoqi Feng
Andrew Wilson
author_sort Xiaoqi Feng
title Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.
title_short Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.
title_full Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.
title_fullStr Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.
title_full_unstemmed Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.
title_sort getting bigger, quicker? gendered socioeconomic trajectories in body mass index across the adult lifecourse: a longitudinal study of 21,403 australians.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description 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.
url https://doi.org/10.1371/journal.pone.0141499
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