Vaezghasemi Masoud, Ng Nawi, Eriksson Malin, Subramanian S V
Unit of Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, SE-901 87, Umeå, Sweden.
Umeå Center for Global Health Research, Umeå University, Umeå, Sweden.
Int J Equity Health. 2016 Jul 7;15(1):102. doi: 10.1186/s12939-016-0388-7.
Most of the research investigating the effect of social context on individual health outcomes has interpreted context in terms of the residential environment. In these studies, individuals are nested within their neighbourhoods or communities, disregarding the intermediate household level that lies between individuals and their residential environment. Households are an important determinant of health yet they are rarely included at the contextual level in research examining association between body mass index (BMI) and the social determinants of health. In this study, our main aim was to provide a methodological demonstration of multilevel analysis, which disentangles the simultaneous effects of households and districts as well as their associated predictors on BMI over time.
Using both two- and three-level multilevel analysis, we utilized data from all four cross-sections of the Indonesian Family life Survey (IFLS) 1993 to 2007-8.
We found that: (i) the variation in BMI attributable to districts decreased from 4.3 % in 1993 to 1.5 % in 1997-98, and remained constant until 2007-08, while there was an alarming increase in the variation of BMI attributable to households, from 10 % in 2000 to 15 % in 2007-08; (ii) ignoring the household level did not change the relative variance contribution of districts on BMI, but ignoring the district level resulted in overestimation of household effects, and (iii) households' characteristics (socioeconomic status, size, and place of residence) did not attenuate the variation of BMI at the household-level.
Estimating the relative importance of multiple social settings allows us to better understand and unpack the variation in clustered or hieratical data in order to make valid and robust inferences. Our findings will help direct investment of limited public health resources to the appropriate context in order to reduce health risk (variation in BMI) and promote population health.
大多数研究社会环境对个体健康结果影响的研究都从居住环境的角度来解释环境。在这些研究中，个体嵌套于其邻里或社区之中，而忽略了介于个体与其居住环境之间的中间家庭层面。家庭是健康的重要决定因素，但在研究体重指数（BMI）与健康的社会决定因素之间的关联时，它们很少被纳入背景层面进行考量。在本研究中，我们的主要目的是提供一个多水平分析的方法示范，该分析能够理清家庭和地区的同时效应以及它们相关的预测因素随时间对BMI的影响。
我们使用两水平和三水平多水平分析，利用了1993年至2007 - 2008年印度尼西亚家庭生活调查（IFLS）所有四个横截面的数据。
我们发现：（i）归因于地区的BMI变异从1993年的4.3%降至1997 - 1998年的1.5%，并一直保持到2007 - 2008年，而归因于家庭的BMI变异则惊人地增加，从2000年的10%增至2007 - 2008年的15%；（ii）忽略家庭层面并未改变地区对BMI的相对方差贡献，但忽略地区层面会导致对家庭效应的高估，以及（iii）家庭特征（社会经济地位、规模和居住地点）并未减弱家庭层面BMI的变异。
估计多个社会环境的相对重要性使我们能够更好地理解和剖析聚类或分层数据中的变异，以便做出有效且可靠的推断。我们的研究结果将有助于将有限的公共卫生资源投入到适当的环境中，以降低健康风险（BMI的变异）并促进人群健康。
