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在存在未测量混杂因素的情况下,重新评估补充营养援助计划参与度与体重指数之间的关联。

Re-evaluating associations between the Supplemental Nutrition Assistance Program participation and body mass index in the context of unmeasured confounders.

机构信息

Quantitative Sciences Unit, Stanford University School of Medicine, 1070 Arastradero Rd #3C3104 MC 5559, Palo Alto, CA 94304, United States.

General Internal Medicine and Diabetes, Massachusetts General Hospital, 50 Staniford St., 9th Floor, Boston, MA 02114, United States.

出版信息

Soc Sci Med. 2017 Nov;192:112-124. doi: 10.1016/j.socscimed.2017.09.020. Epub 2017 Sep 21.

Abstract

OBJECTIVE

To evaluate the association between participation in the Supplemental Nutrition Assistance Program (SNAP) and body mass index (BMI) in the presence of unmeasured confounding.

METHODS

We applied new matching methods to determine whether previous reports of associations between SNAP participation and BMI were robust to unmeasured confounders. We applied near-far matching, which strengthens standard matching by combining it with instrumental variables analysis, to the nationally-representative National Household Food Acquisition and Purchasing Survey (FoodAPS, N = 10,360, years 2012-13).

RESULTS

In ordinary least squares regressions controlling for individual demographic and socioeconomic characteristics, SNAP was associated with increased BMI (+1.23 kg/m, 95% CI: 0.84, 1.63). While propensity-score-based analysis replicated this finding, using instrumental variables analysis and particularly near-far matching to strengthen the instruments' discriminatory power revealed the association between SNAP and BMI was likely confounded by unmeasured covariates (+0.21 kg/m, 95% CI: -3.88, 4.29).

CONCLUSIONS

Previous reports of an association between SNAP and obesity should be viewed with caution, and use of near-far matching may assist similar assessments of health effects of social programs.

摘要

目的

在存在未测量混杂因素的情况下,评估补充营养援助计划(SNAP)参与度与体重指数(BMI)之间的关联。

方法

我们应用新的匹配方法来确定之前关于 SNAP 参与度与 BMI 之间关联的报告是否对未测量的混杂因素具有稳健性。我们应用近远匹配法,通过将其与工具变量分析相结合,对具有全国代表性的全国家庭食品获取和采购调查(FoodAPS,N=10360,2012-13 年)进行了分析。

结果

在控制个体人口统计学和社会经济特征的普通最小二乘法回归中,SNAP 与 BMI 增加相关(+1.23kg/m,95%置信区间:0.84,1.63)。虽然基于倾向评分的分析复制了这一发现,但使用工具变量分析,特别是近远匹配来增强工具的判别能力,表明 SNAP 与 BMI 之间的关联可能受到未测量协变量的混杂(+0.21kg/m,95%置信区间:-3.88,4.29)。

结论

之前关于 SNAP 与肥胖之间关联的报告应谨慎看待,并且近远匹配的使用可能有助于对社会计划对健康影响的类似评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e7b/5815398/f7b24feafd59/nihms935194f3.jpg

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本文引用的文献

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Near-Far Matching in R: The nearfar Package.R语言中的近远匹配:nearfar包
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Near/far matching: a study design approach to instrumental variables.近/远匹配:一种工具变量的研究设计方法。
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