Drewnowski Adam, Aggarwal Anju, Tang Wesley, Moudon Anne Vernez
Center for Public Health Nutrition, University of Washington, Seattle, Washington, USA.
Obesity (Silver Spring). 2015 Mar;23(3):671-6. doi: 10.1002/oby.20989. Epub 2015 Feb 13.
Lower socio economic status (SES) has been linked with higher obesity rates but not with weight gain. This study examined whether SES can predict short-term weight change.
The Seattle Obesity Study II was based on an observational cohort of 440 adults. Weights and heights were measured at baseline and at 1 year. Self-reported education and incomes were obtained by questionnaire. Home addresses were linked to tax parcel property values from the King County, Washington, tax assessor. Associations among SES variables, prevalent obesity, and 1-year weight change were examined using multivariable linear regressions.
Low residential property values at the tax parcel level predicted prevalent obesity at baseline and at 1 year. Living in the top quartile of house prices reduced obesity risk by 80% at both time points. At 1 year, about 38% of the sample lost >1 kg body weight; 32% maintained (± 1 kg); and 30% gained >1 kg. In adjusted models, none of the baseline SES measures had any impact on 1-year weight change.
SES variables, including tax parcel property values, predicted prevalent obesity but did not predict short-term weight change. These findings, based on longitudinal cohort data, suggest other mechanisms are involved in short-term weight change.
社会经济地位(SES)较低与较高的肥胖率相关,但与体重增加无关。本研究探讨了SES是否能预测短期体重变化。
西雅图肥胖研究II基于对440名成年人的观察性队列研究。在基线和1年时测量体重和身高。通过问卷调查获取自我报告的教育程度和收入。家庭住址与华盛顿州金县税务评估员的税务地块房产价值相关联。使用多变量线性回归分析SES变量、肥胖患病率和1年体重变化之间的关联。
税务地块层面的低住宅房产价值预测了基线和1年时的肥胖患病率。在两个时间点,居住在房价最高四分位数区域可使肥胖风险降低80%。1年时,约38%的样本体重减轻超过1千克;32%维持不变(±1千克);30%体重增加超过1千克。在调整模型中,基线SES指标均对1年体重变化无任何影响。
SES变量,包括税务地块房产价值,可预测肥胖患病率,但不能预测短期体重变化。基于纵向队列数据的这些发现表明,短期体重变化涉及其他机制。