Neighborhood socioeconomic disadvantage and body mass index among residentially stable mid-older aged adults: Findings from the HABITAT multilevel longitudinal study
Rachele, Jerome N., Kavanagh, Anne, Brown, Wendy J., Healy, Aislinn M., Schmid, Christina J. and Turrell, Gavin 2017. Neighborhood socioeconomic disadvantage and body mass index among residentially stable mid-older aged adults: Findings from the HABITAT multilevel longitudinal study. Preventive Medicine. 105, pp. 271 - 274. https://doi.org/10.1016/j.ypmed.2017.09.017
|Authors||Rachele, Jerome N., Kavanagh, Anne, Brown, Wendy J., Healy, Aislinn M., Schmid, Christina J. and Turrell, Gavin|
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 65 years 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 0.08 kg/m2 (95% CI 0.02, 0.13) and 0.17 kg/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.
|Keywords||body mass index; obesity; multilevel modelling; longitudinal; neighborhood disadvantage; residence characteristics; social class|
|Journal citation||105, pp. 271 - 274|
|Digital Object Identifier (DOI)||https://doi.org/10.1016/j.ypmed.2017.09.017|
|Open access||Open access|
|Page range||271 - 274|
|Research Group||Institute for Health and Ageing|
|Author's accepted manuscript|
Authors accepted manuscript.
|Place of publication||Netherlands|
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