Diez-Roux A V, Kiefe C I, Jacobs D R, Haan M, Jackson S A, Nieto F J, Paton C C, Schulz R
Division of General Medicine, Columbia College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
Ann Epidemiol. 2001 Aug;11(6):395-405. doi: 10.1016/s1047-2797(01)00221-6.
There is growing interest in incorporating area indicators into epidemiologic analyses. Using data from the 1990 U.S. Census linked to individual-level data from three epidemiologic studies, we investigated how different area indicators are interrelated, how measures for different sized areas compare, and the relation between area and individual-level social position indicators.
The interrelations between 13 area indicators of wealth/income, education, occupation, and other socioenvironmental characteristics were investigated using correlation coefficients and factor analyses. The extent to which block-group measures provide information distinct from census tract measures was investigated using intraclass correlation coefficients. Loglinear models were used to investigate associations between area and individual-level indicators.
Correlations between area measures were generally in the 0.5--0.8 range. In factor analyses, six indicators of income/wealth, education, and occupation loaded on one factor in most geographic sites. Correlations between block-group and census tract measures were high (correlation coefficients 0.85--0.96). Most of the variability in block-group indicators was between census tracts (intraclass correlation coefficients 0.72--0.92). Although individual-level and area indicators were associated, there was evidence of important heterogeneity in area of residence within individual-level income or education categories. The strength of the association between individual and area measures was similar in the three studies and in whites and blacks, but blacks were much more likely to live in more disadvantaged areas than whites.
Area measures of wealth/income, education, and occupation are moderately to highly correlated. Differences between using census tract or block-group measures in contextual investigations are likely to be relatively small. Area and individual-level indicators are far from perfectly correlated and provide complementary information on living circumstances. Differences in the residential environments of blacks and whites may need to be taken into account in interpreting race differences in epidemiologic studies.
将地区指标纳入流行病学分析的兴趣与日俱增。利用与三项流行病学研究的个体层面数据相链接的1990年美国人口普查数据，我们调查了不同地区指标之间的相互关系、不同规模地区的测量指标如何比较，以及地区与个体层面社会地位指标之间的关系。
使用相关系数和因子分析研究了13个关于财富/收入、教育、职业及其他社会环境特征的地区指标之间的相互关系。使用组内相关系数研究了街区组测量指标相对于普查区测量指标所提供信息的独特程度。使用对数线性模型研究地区与个体层面指标之间的关联。
地区测量指标之间的相关性一般在0.5 - 0.8范围内。在因子分析中，在大多数地理区域，收入/财富、教育和职业的六个指标加载在一个因子上。街区组与普查区测量指标之间的相关性很高（相关系数为0.85 - 0.96）。街区组指标的大部分变异性存在于普查区之间（组内相关系数为0.72 - 0.92）。尽管个体层面和地区指标相关，但有证据表明在个体层面的收入或教育类别中，居住地区存在重要的异质性。在三项研究以及白人和黑人中，个体与地区测量指标之间关联的强度相似，但黑人比白人更有可能生活在更贫困的地区。
财富/收入、教育和职业的地区测量指标具有中等至高的相关性。在背景调查中使用普查区或街区组测量指标的差异可能相对较小。地区和个体层面指标远非完全相关，并且提供了关于生活环境的补充信息。在解释流行病学研究中的种族差异时，可能需要考虑黑人和白人居住环境的差异。
