Literature DB >> 28963008

Neighborhood socioeconomic disadvantage and body mass index among residentially stable mid-older aged adults: Findings from the HABITAT multilevel longitudinal study.

Jerome N Rachele1, Anne Kavanagh2, Wendy J Brown3, Aislinn M Healy4, Christina J Schmid5, Gavin Turrell6.   

Abstract

Despite a body of evidence on the relationship between neighborhood socioeconomic disadvantage and body mass index (BMI), few studies have examined this relationship over time among ageing populations. This study examined associations between level of neighborhood socioeconomic disadvantage and the rate of change in BMI over time. The sample included 11,035 participants aged between 40 and 65years at baseline from the HABITAT study, residing in 200 neighborhoods in Brisbane, Australia. Data were collected biennially over four waves from 2007 to 2013. Self-reported height and weight were used to calculate BMI, while neighborhood disadvantage was measured using a census-based composite index. All models were adjusted for age, education, occupation, and household income. Analyses were conducted using multilevel linear regression models. BMI increased over time at a rate of 0.08kg/m2 (95% CI 0.02, 0.13) and 0.17kg/m2 (95% CI 0.11, 0.29) per wave for men and women respectively. Both men and women residing in the most disadvantaged neighborhoods had a higher average BMI than their counterparts living in the least disadvantaged neighborhoods. There were no evident differences in the rate of BMI change over time by level of neighborhood disadvantage. The findings suggest that by mid-older age, the influence of neighborhood socioeconomic conditions over time on BMI may have already played out. Future research should endeavor to identify the genesis of neighborhood socioeconomic inequalities in BMI, the determinants of these inequalities, and then suitable approaches to intervening.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Body mass index; Longitudinal; Multilevel modelling; Neighborhood disadvantage; Obesity; Residence characteristics; Social class

Mesh:

Year:  2017        PMID: 28963008     DOI: 10.1016/j.ypmed.2017.09.017

Source DB:  PubMed          Journal:  Prev Med        ISSN: 0091-7435            Impact factor:   4.018


  4 in total

1.  Neighbourhood disadvantage, geographic remoteness and body mass index among immigrants to Australia: A national cohort study 2006-2014.

Authors:  Karen Menigoz; Andrea Nathan; Kristiann C Heesch; Gavin Turrell
Journal:  PLoS One       Date:  2018-01-23       Impact factor: 3.240

2.  Neighborhood socioeconomic characteristics, healthcare spatial access, and emergency department visits for ambulatory care sensitive conditions for elderly.

Authors:  Yuxia Huang; Pamela Meyer; Lei Jin
Journal:  Prev Med Rep       Date:  2018-09-05

3.  Association of Neighborhood-Level Disadvantage With Cerebral and Hippocampal Volume.

Authors:  Jack F V Hunt; William Buckingham; Alice J Kim; Jennifer Oh; Nicholas M Vogt; Erin M Jonaitis; Tenah K Hunt; Megan Zuelsdorff; Ryan Powell; Derek Norton; Robert A Rissman; Sanjay Asthana; Ozioma C Okonkwo; Sterling C Johnson; Amy J H Kind; Barbara B Bendlin
Journal:  JAMA Neurol       Date:  2020-04-01       Impact factor: 18.302

4.  Neighbourhood effects on obesity: scoping review of time-varying outcomes and exposures in longitudinal designs.

Authors:  Laurence Letarte; Sonia Pomerleau; André Tchernof; Laurent Biertho; Edward Owen D Waygood; Alexandre Lebel
Journal:  BMJ Open       Date:  2020-03-25       Impact factor: 2.692

  4 in total

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