背景:尽管社会人口统计学特征与健康差异有关,不同社会和人口因素的相对预测价值在很大程度上仍然未知.这项研究旨在描述我们所有参与者的社会人口统计学特征,并评估每个因素对与高发病率和死亡率相关的慢性疾病的预测价值。
方法:我们使用来自“我们所有人”研究计划的去识别调查数据进行了横截面分析,它收集了社会,人口统计学,以及自2018年5月以来居住在美国的成年人的健康信息。社会人口统计学数据包括自我报告的年龄,性别,性别,性取向,种族/民族,收入,教育,健康保险,初级保健提供者(PCP)状态,和健康素养得分。我们分析了自我报告的高血压患病率,冠状动脉疾病,任何癌症,皮肤癌,肺部疾病,糖尿病,肥胖,和慢性肾病。最后,我们使用来自逻辑回归的每个预测因子的充分性指数评估了每个社会人口统计学因素对预测每种慢性疾病的相对重要性.
结果:在此分析的372,050名参与者中,中位年龄为53岁,59.8%的人报告了女性性行为,最常见的种族/族裔类别是白人(54.0%),黑色(19.9%),西班牙裔/拉丁裔(16.7%)。被认定为亚洲人的参与者,中东/北非,怀特最有可能报告年收入超过20万美元,高级学位,雇主或工会保险,而被认定为黑人的参与者,西班牙裔,夏威夷原住民/太平洋岛民最有可能报告年收入低于10,000美元,低于高中学历,医疗补助保险。我们发现年龄最能预测高血压,冠状动脉疾病,任何癌症,皮肤癌,糖尿病,肥胖,和慢性肾病。保险类型最能预测肺部疾病。值得注意的是,没有两种健康状况对社会人口统计学因素具有相同的重要性.
结论:年龄是评估慢性病的最佳预测指标,但是收入的相对预测价值,教育,健康保险,PCP状态,种族/民族,和性取向是高度可变的不同健康状况。确定特定疾病中差异最大的社会人口群体可以指导未来的干预措施以促进健康公平。
Although sociodemographic characteristics are associated with health disparities, the relative predictive value of different social and demographic factors remains largely unknown. This study aimed to describe the sociodemographic characteristics of All of Us participants and evaluate the predictive value of each factor for chronic diseases associated with high morbidity and mortality.
We performed a cross-sectional analysis using de-identified survey data from the All of Us Research Program, which has collected social, demographic, and health information from adults living in the United States since May 2018. Sociodemographic data included self-reported age, sex, gender, sexual orientation, race/ethnicity, income, education, health insurance, primary care provider (PCP) status, and health literacy scores. We analyzed the self-reported prevalence of hypertension, coronary artery disease, any cancer, skin cancer, lung disease, diabetes, obesity, and chronic kidney disease. Finally, we assessed the relative importance of each sociodemographic factor for predicting each chronic disease using the adequacy index for each predictor from logistic regression.
Among the 372,050 participants in this analysis, the median age was 53 years, 59.8% reported female sex, and the most common racial/ethnic categories were White (54.0%), Black (19.9%), and Hispanic/Latino (16.7%). Participants who identified as Asian, Middle Eastern/North African, and White were the most likely to report annual incomes greater than $200,000, advanced degrees, and employer or union insurance, while participants who identified as Black, Hispanic, and Native Hawaiian/Pacific Islander were the most likely to report annual incomes less than $10,000, less than a high school education, and Medicaid insurance. We found that age was most predictive of hypertension, coronary artery disease, any cancer, skin cancer, diabetes, obesity, and chronic kidney disease. Insurance type was most predictive of lung disease. Notably, no two health conditions had the same order of importance for sociodemographic factors.
Age was the best predictor for the assessed chronic diseases, but the relative predictive value of income, education, health insurance, PCP status, race/ethnicity, and sexual orientation was highly variable across health conditions. Identifying the sociodemographic groups with the largest disparities in a specific disease can guide future interventions to promote health equity.