Systematic assessment of the correlations of household income with infectious, biochemical, physiological, and environmental factors in the United States, 1999-2006.
Systematic assessment of the correlations of household income with infectious, biochemical, physiological, and environmental factors in the United States, 1999-2006.
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DOI：
10.1093/aje/kwu277
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发表时间：
2015-02-01
影响因子：
5
通讯作者：
Rehkopf, David H
中科院分区：
文献类型：
--
作者：
Patel, Chirag J;Ioannidis, John P A;Rehkopf, David H
要更充分地了解疾病的社会流行病学，就需要系统地详细说明社会因素与健康指标之间的关系。在本研究中，我们调查了美国国家健康和营养调查（NHANES）（1999-2006）参与者的收入和330项生理，生化和环境健康指标之间的相关性。我们结合了来自3个调查波（各种指标n = 249- 23，649）的数据，以寻找收入的线性和非线性（二次）相关性，并在独立的测试数据集（n = 255- 7，855）中验证了显著（P < 0.00015）相关性。我们验证了330个因素中的66个，包括传染性（例如，甲型肝炎），生化（例如，类胡萝卜素，高密度脂蛋白胆固醇），生理的（例如，大腿长度），和环境（例如，铅、可替宁）措施。我们只发现了少量的年龄，种族/民族和性别的关联修改，黑人没有关联修改。目前的研究是描述性的，而不是因果关系。我们的系统调查表明，收入在健康风险因素中占有关键地位。未来的研究可以利用这些相关性来更好地为疾病途径的理论和研究提供信息，并利用这些发现来了解收入的混淆何时最有可能引入偏见。
A fuller understanding of the social epidemiology of disease requires an extended description of the relationships between social factors and health indicators in a systematic manner. In the present study, we investigated the correlations between income and 330 indicators of physiological, biochemical, and environmental health in participants in the US National Health and Nutrition Examination Survey (NHANES) (1999-2006). We combined data from 3 survey waves (n = 249-23,649 for various indicators) to search for linear and nonlinear (quadratic) correlates of income, and we validated significant (P < 0.00015) correlations in an independent testing data set (n = 255-7,855). We validated 66 out of 330 factors, including infectious (e.g., hepatitis A), biochemical (e.g., carotenoids, high-density lipoprotein cholesterol), physiological (e.g., upper leg length), and environmental (e.g., lead, cotinine) measures. We found only a modest amount of association modification by age, race/ethnicity, and gender, and there was no association modification for blacks. The present study is descriptive, not causal. We have shown in our systematic investigation the crucial place income has in relation to health risk factors. Future research can use these correlations to better inform theory and studies of pathways to disease, as well as utilize these findings to understand when confounding by income is most likely to introduce bias.