Department of Public Health Sciences, The University of Chicago, Chicago, Illinois, USA.
Department of Pediatrics, The University of Chicago, Chicago, Illinois, USA.
Health Serv Res. 2023 Aug;58(4):873-881. doi: 10.1111/1475-6773.14102. Epub 2022 Nov 29.
To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level.
The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments.
The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity.
DATA COLLECTION/EXTRACTION METHODS: The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments.
The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago.
The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.
开发和验证一种新的社会决定因素健康（SDoH）生态衡量标准，可在邮政编码或县一级计算。
从美国国家卫生机构以及州和城市公共卫生部门收集了最新发布的二手、公开可用数据。
使用多维项目反应理论，从美国邮政编码级别的调查数据中构建社会脆弱性指标（SVM），并使用包括全因死亡率（2016 年）、COVID-19 疫苗接种（2021 年）和哮喘急诊就诊（2018 年）在内的结果进行验证。SVM 还与现有的疾病控制与预防中心的社会脆弱性指数（SVI）进行了比较，以确定收敛有效性和差异预测有效性。
数据收集/提取方法：数据直接从美国国家卫生机构以及州和城市公共卫生部门在线发布的公共文件中收集。
SVM 得分与全国按年龄调整的县全因死亡率之间的相关性为 r = 0.68。这种相关性表明 SVM 具有强大的有效性，并通过解释方差的近四倍增加（46%对 12%）优于 SVI。SVM 还与加利福尼亚州和芝加哥市的邮政编码级健康结果高度相关（r≥0.60）。
SVM 提供了一种测量工具，改进了现有的 SDoH 综合衡量标准的性能，并且具有广泛的公共卫生适用性，可能有助于指导未来的政策和干预措施。SVM 提供了一种单一的 SDoH 衡量标准，可以更好地量化与健康结果的关联。
