A brief conceptual tutorial on multilevel analysis in social epidemiology:: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health
A brief conceptual tutorial on multilevel analysis in social epidemiology:: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health
复制标题
DOI：
10.1136/jech.2004.028035
复制
发表时间：
2005-12-01
影响因子：
6.3
通讯作者：
Råstam, L
中科院分区：
文献类型：
--
作者：
Merlo, J;Chaix, B;Råstam, L
研究目的：采用概念方法而非数学方法，本文提出了多水平回归分析(MLRA)与社会流行病学概念之间的联系。以前已经解释过，社区内个人健康状况集群的概念对于将社会流行病学中的背景现象付诸实施是有用的。已经表明，MLRA允许调查邻里健康方面的差异，而不考虑任何特定的邻里特征，而只考虑每个人所属邻里的信息。本文阐述了如何分析跨水平的(邻里-个体)交互作用，如何调查邻里特征与个人健康之间的关联，以及如何使用聚类的概念来解释这些关联和健康方面的地理差异。设计和参与者：使用与收缩压(SBP)相关的假设数据进行MLRA，这些数据来自一座虚拟城市39个社区的25000名受试者。分析个体特征(年龄、体重指数(BMI)、降压药使用、收入)或邻里特征(邻里收入)与SBP的关系。结果：SBP个体差异约8%位于邻里水平。社区内个体SBP的差异性和聚集性随着个体BMI的增加而增大。邻里低收入除了个体特征的影响外，还与SBP的升高有关，并解释了BMI正常人群中22%的邻里SBP差异。这种邻里收入效应在超重人群中更为强烈。结论：方差测量与了解健康的地理和个体差异有关，并补充了邻里特征与健康之间的关联性测量所传达的信息。
Study objective: Using a conceptual rather than a mathematical approach, this article proposed a link between multilevel regression analysis (MLRA) and social epidemiological concepts. It has been previously explained that the concept of clustering of individual health status within neighbourhoods is useful for operationalising contextual phenomena in social epidemiology. It has been shown that MLRA permits investigating neighbourhood disparities in health without considering any particular neighbourhood characteristic but only information on the neighbourhood to which each person belongs. This article illustrates how to analyse cross level (neighbourhood-individual) interactions, how to investigate associations between neighbourhood characteristics and individual health, and how to use the concept of clustering when interpreting those associations and geographical differences in health.Design and participants: A MLRA was performed using hypothetical data pertaining to systolic blood pressure (SBP) from 25 000 subjects living in the 39 neighbourhoods of an imaginary city. Associations between individual characteristics (age, body mass index (BMI), use of antihypertensive drug, income) or neighbourhood characteristic (neighbourhood income) and SBP were analysed.Results: About 8% of the individual differences in SBP were located at the neighbourhood level. SBP disparities and clustering of individual SBP within neighbourhoods increased along individual BMI. Neighbourhood low income was associated with increased SBP over and above the effect of individual characteristics, and explained 22% of the neighbourhood differences in SBP among people of normal BMI. This neighbourhood income effect was more intense in overweight people.Conclusions: Measures of variance are relevant to understanding geographical and individual disparities in health, and complement the information conveyed by measures of association between neighbourhood characteristics and health.