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评估源自美国社区调查的社会经济指数中的不确定性。

Estimating uncertainty in a socioeconomic index derived from the American community survey.

作者信息

Boscoe Francis P, Liu Bian, Lafantasie Jordana, Niu Li, Lee Furrina F

机构信息

Pumphandle, LLC, Camden, ME, USA.

New York State Department of Health, Albany, NY, USA.

出版信息

SSM Popul Health. 2022 May 17;18:101078. doi: 10.1016/j.ssmph.2022.101078. eCollection 2022 Jun.

Abstract

Socioeconomic indexes are widely used in public health to facilitate neighborhood-scale analyses. Although they are calculated with high levels of precision, they are rarely reported with accompanying measures of uncertainty (e.g., 90% confidence intervals). Here we use the variance replicate tables that accompany the United States Census Bureau's American Community Survey to report confidence intervals around the Yost Index, a socioeconomic index comprising seven variables that is frequently used in cancer surveillance. The Yost Index is reported as a percentile score from 1 (most affluent) to 100 (most deprived). We find that the average uncertainty for a census tract in the United States is plus or minus 8 percentiles, with the uncertainty a function of the value of the index itself. Scores at the extremes of the distribution are more precise and scores near the center are less precise. Less-affluent tracts have greater uncertainty than corresponding more-affluent tracts. Fewer than 50 census tracts of 72,793 nationally have unusual distributions of socioeconomic conditions that render the index uninformative. We demonstrate that the uncertainty in a census-based socioeconomic index is calculable and can be incorporated into any analysis using such an index.

摘要

社会经济指标在公共卫生领域被广泛应用,以促进邻里层面的分析。尽管这些指标的计算精度很高,但很少会报告其不确定性度量(例如90%置信区间)。在此,我们利用美国人口普查局美国社区调查所附带的方差复制表,来报告约斯特指数(Yost Index)的置信区间。约斯特指数是一种社会经济指标,由七个变量组成,常用于癌症监测。约斯特指数以百分制分数报告,范围从1(最富裕)到100(最贫困)。我们发现,美国一个普查区的平均不确定性为正负8个百分点,不确定性是指数本身数值的一个函数。分布两端的分数更精确,而中心附近的分数则不太精确。较贫困的普查区比较富裕的相应普查区具有更大的不确定性。在全国72,793个普查区中,只有不到50个普查区的社会经济状况分布异常,导致该指数失去参考价值。我们证明,基于普查的社会经济指标中的不确定性是可以计算的,并且可以纳入使用该指标的任何分析中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ceef/9130578/2938ecee988a/gr1.jpg

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