Geographic and Racial Variation in Premature Mortality in the US: Analyzing the Disparities
Geographic and Racial Variation in Premature Mortality in the US: Analyzing the Disparities
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DOI：
10.1371/journal.pone.0032930
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发表时间：
2012-04-17
期刊：
影响因子：
3.7
通讯作者：
Fuchs, Victor R.
中科院分区：
文献类型：
--
作者：
Cullen, Mark R.;Cummins, Clint;Fuchs, Victor R.
出生时的预期寿命，根据美国时期寿命表估计，已被证明有系统地和广泛的地区和种族的差异。我们使用相同的表格来估计从出生到70岁的生存概率（S-70），这是一种对差异更敏感的死亡率指标，并且对于小人群计算更可靠，以描述变异并更详细地确定其来源，以评估这种变异的模式。对美国每个有足够白人和黑人人口的县的S-70的未调整概率进行检查，发现每个种族性别组的地理差异很大。例如，出生在百分之十最健康的县的白色男性有77%的机会活到70岁，但如果出生在百分之十最不健康的县，只有61%的机会。白色妇女和黑人男女也面临着类似的地域差异。此外，在每个县内，黑人和白人之间的S-70存在很大差异，男性平均为17个百分点，女性为12个百分点。在每个种族性别组的线性回归中，几乎所有的地理变异都是由一组共同的22个社会经济和环境变量来解释的，这些变量是根据先前怀疑的对死亡率的影响来选择的; R-2范围从白色男性的0.86到黑人女性的0.72。对每个县内黑人和白人生存机会的分析表明，同样的变量也是S-70中种族差距的主要原因。当在黑人男性预测方程中用每个解释变量的实际白色男性值代替黑人，以评估解释变量在黑人-白色生存差异中的作用时，县一级的剩余黑人-白色差异显著缩小至平均-2.4%（+/-2.4）;对于女性，平均差异为-3.7%（+/-2.3）。
Life expectancy at birth, estimated from United States period life tables, has been shown to vary systematically and widely by region and race. We use the same tables to estimate the probability of survival from birth to age 70 (S-70), a measure of mortality more sensitive to disparities and more reliably calculated for small populations, to describe the variation and identify its sources in greater detail to assess the patterns of this variation. Examination of the unadjusted probability of S-70 for each US county with a sufficient population of whites and blacks reveals large geographic differences for each race-sex group. For example, white males born in the ten percent healthiest counties have a 77 percent probability of survival to age 70, but only a 61 percent chance if born in the ten percent least healthy counties. Similar geographical disparities face white women and blacks of each sex. Moreover, within each county, large differences in S-70 prevail between blacks and whites, on average 17 percentage points for men and 12 percentage points for women. In linear regressions for each race-sex group, nearly all of the geographic variation is accounted for by a common set of 22 socio-economic and environmental variables, selected for previously suspected impact on mortality; R-2 ranges from 0.86 for white males to 0.72 for black females. Analysis of black-white survival chances within each county reveals that the same variables account for most of the race gap in S-70 as well. When actual white male values for each explanatory variable are substituted for black in the black male prediction equation to assess the role explanatory variables play in the black-white survival difference, residual black-white differences at the county level shrink markedly to a mean of -2.4% (+/-2.4); for women the mean difference is -3.7% (+/-2.3).