Introduction.虽然已经确定了NIH的种族资助差距,关于机构的社区人口统计与NIH资助之间的联系知之甚少。我们试图评估机构邮政编码特征与NIH资金之间的关联。方法。我们将2011-2021年NIHRePORTER数据库与人口普查数据相关联。我们计算了每个机构的资金,并将机构分为四分位数。我们将自变量定义为机构邮政编码级别的种族/民族(怀特,黑色,和西班牙裔),和社会经济地位(家庭收入,高中毕业率,和失业率)。我们使用序数回归模型来评估机构邮政编码特征与拨款四分位数之间的关联。结果。我们包括了3,971个邮政编码的731,548笔赠款(271,495,839,744美元)。资金四分位数的资金金额(以百万美元计)为第四-0.25,第三-1.1,第二-3.8,第一-43.5。使用序数回归,我们发现失业率上升(OR=1.03[1.02,1.05]),提高高中毕业率(OR=3.6[1.6,8.4]),白人比例下降(OR=0.4[0.3,0.5]),黑人比例增加(OR=1.3[0.9,1.8]),西班牙裔/拉丁裔比例增加(OR=2.5[1.7,3.5])和更高的拨款资金四分位数。我们发现家庭收入和拨款资金四分位数之间没有关联。结论。我们发现邮政编码人口统计不足以评估NIH的资金差距,机构邮政编码人口统计和研究者人口统计之间的关联尚不清楚。评估和改善赠款资金差距,需要更好的授予接收者数据可访问性和透明度。
Introduction. While racial
NIH funding disparities have been identified, little is known about the link between community demographics of institutions and
NIH funding. We sought to evaluate the association between institution zip code characteristics and
NIH funding. Methods. We linked the 2011-2021
NIH RePORTER database to Census data. We calculated the funding to each institution and stratified institutions into funding quartiles. We defined out independent variables as institution ZIP code level race/ethnicity (White, Black, and Hispanic), and socioeconomic status (household income, high school graduation rate, and unemployment rate). We used ordinal regression models to evaluate the association between institution ZIP code characteristics and grant funding quartile. Results. We included 731,548 grants (US$271,495,839,744) from 3,971 ZIP codes. The funding amounts in millions of U.S. dollars for the funding quartiles were fourth - 0.25, third - 1.1, second - 3.8, first - 43.5. Using ordinal regression, we found an association between increasing unemployment rate (OR = 1.03 [1.02, 1.05]), increasing high school graduation rate (OR = 3.6 [1.6, 8.4]), decreasing proportion of White people (OR = 0.4 [0.3, 0.5]), increasing proportion of Black people (OR = 1.3 [0.9, 1.8]), and increasing proportion of Hispanic/Latine people (OR = 2.5 [1.7, 3.5]) and higher grant funding quartiles. We found no association between household income and grant funding quartile. Conclusion. We found ZIP code demographics to be inadequate for evaluating
NIH funding disparities, and the association between institution ZIP code demographics and investigator demographics is unclear. To evaluate and improve grant funding disparities, better grant recipient data accessibility and transparency are needed.