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ZIP-Code-based versus Tract-based Income Measures as Long-Term Risk-adjusted Mortality Predictors

机译:基于邮政编码和基于行的收入度量作为长期风险调整后的死亡率预测指标

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摘要

There is a well-established, strong association between socioeconomic position and mortality. Public health mortality analyses thus routinely consider the confounding effect of socioeconomic position when possible. Particularly in the absence of personally reported data, researchers often use area-based measures to estimate the effects of socioeconomic position. Data are limited regarding the relative merits of measures based on US Census tract versus ZIP code (postal code). ZIP-code measures have more within-unit variation but are also more easily obtained. The current study reports on 293,138 middle-aged men screened in 14 states in 1973–1975 for the Multiple Risk Factor Intervention Trial and having 25-year mortality follow-up. In risk-adjusted proportional hazards models containing either ZIP-code-based or tract-based median household income, all-cause mortality hazard ratios were 1.16 (95% confidence interval: 1.14, 1.17) per $10,000 less ZIP-code-based income and 1.15 (95% confidence interval: 1.13, 1.16) per $10,000 less tract-based income; adding either income variable to a risk-adjusted model improved model fit substantially. Both were significant independent predictors in a combined model; tract-based income was a slightly stronger mortality predictor (hazard ratios = 1.05 and 1.11 for ZIP-code-based and tract-based income, respectively). These patterns held across various causes of death, for both Blacks and non-Blacks, and with or without adjustment for ZIP-code-based income diversity or tract-based proportion below poverty.
机译:在社会经济地位和死亡率之间建立了牢固的联系。因此,公共卫生死亡率分析通常会尽可能考虑社会经济地位的混杂影响。特别是在没有个人报告的数据的情况下,研究人员经常使用基于区域的方法来估计社会经济地位的影响。关于基于美国人口普查与邮政编码(邮政编码)的措施的相对优缺点的数据有限。邮政编码度量单位内变化更大,但也更容易获得。当前的研究报道了1973–1975年在14个州筛查的293,138名中年男性,进行了多危险因素干预试验,并进行了25年的随访。在包含基于邮政编码或基于区域的家庭中位数收入的风险调整比例风险模型中,每10,000美元减去基于邮政编码的收入,全因死亡率风险比率为1.16(95%置信区间:1.14、1.17),每$ 10,000(基于地区收入)减去1.15(95%置信区间:1.13、1.16);将任何收入变量添加到经过风险调整的模型中,都可以大大改善模型的拟合度。在组合模型中,两者都是重要的独立预测因子。基于管道的收入是死亡率预测指标略强(基于邮政编码的收入和基于管道的收入的危险比分别为1.05和1.11)。这些模式适用于黑人和非黑人的各种死亡原因,并且对基于邮政编码的收入多样性或低于贫困线的人口比例进行了调整或未进行调整。

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