Socioeconomic status in health research - One size does not fit all

被引:1598
作者
Braveman, PA
Cubbin, C
Egerter, S
Chideya, S
Marchi, KS
Metzler, M
Posner, S
机构
[1] Univ Calif San Francisco, Ctr Social Dispar Hlth, San Francisco, CA 94143 USA
[2] Univ Calif San Francisco, Dept Family & Community Med, San Francisco, CA 94143 USA
[3] Ctr Dis Control & Prevent, Epidem Intelligence Serv, Atlanta, GA USA
[4] Ctr Dis Control & Prevent, Natl Ctr Chron Dis Prevent & Hlth Promot, Div Adult & Community Hlth, Atlanta, GA USA
[5] Ctr Dis Control & Prevent, Natl Ctr Chron Dis Prevent & Hlth Promot, Div Reprod Hlth, Atlanta, GA USA
来源
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION | 2005年 / 294卷 / 22期
关键词
D O I
10.1001/jama.294.22.2879
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Problems with measuring socioeconomic status (SES-frequently included in clinical and public health studies as a control variable and less frequently as the variable(s) of main interest-could affect research findings and conclusions, with implications for practice and policy. We critically examine standard SES measurement approaches, illustrating problems with examples from new analyses and the literature. For example, marked racial/ethnic differences in income at a given educational level and in wealth at a given income level raise questions about the socioeconomic comparability of individuals who are similar on education or income alone. Evidence also shows that conclusions about nonsocioeconomic causes of racial/ethnic differences in health may depend on the measure eg, income, wealth, education, occupation, neighborhood socioeconomic characteristics, or past socioeconomic experiences-used to "control for SES," suggesting that findings from studies that have measured limited aspects of SES should be reassessed. We recommend an outcome- and social group-specific approach to SES measurement that involves (1) considering plausible explanatory pathways and mechanisms, (2) measuring as much relevant socioeconomic information as possible, (3) specifying the particular socioeconomic factors measured (rather than SES overall), and (4) systematically considering how potentially important unmeasured socioeconomic factors may affect conclusions. Better SES measures are needed in data sources, but improvements could be made by using existing information more thoughtfully and acknowledging its limitations.
引用
收藏
页码:2879 / 2888
页数:10
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