Section on Cardiovascular Medicine, Department of Medicine, Wake Forest University School of Medicine, Winston-Salem, NC (A.H., A.I., J.Y., D.H., M.D.S.).
Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC (H.C.).
Circ Cardiovasc Qual Outcomes. 2023 Jul;16(7):e009304. doi: 10.1161/CIRCOUTCOMES.122.009304. Epub 2023 Jul 5.
Social determinants of health contribute to disparate cardiovascular outcomes, yet they have not been operationalized into the current paradigm of cardiovascular risk assessment.
Data from the Multi-Ethnic Study of Atherosclerosis, which includes participants from 6 US field centers, were used to create an index of baseline Social Disadvantage Score (SDS) to explore its association with incident atherosclerotic cardiovascular disease (ASCVD) and all-cause mortality and impact on ASCVD risk prediction. SDS, which ranges from 0 to 4, was calculated by tallying the following social factors: (1) household income less than the federal poverty level; (2) educational attainment less than a high school diploma; (3) single-living status; and (4) experience of lifetime discrimination. Cox models were used to examine the association between SDS and each outcome with adjustment for traditional cardiovascular risk factors. Changes in the discrimination and reclassification of ASCVD risk by incorporating SDS into the pooled cohort equations were examined.
A total of 6434 participants (mean age, 61.9±10.2 years; female 52.8%; non-white 60.9%) had available SDS 1733 (26.9%) with SDS 0; 2614 (40.6%) with SDS 1; 1515 (23.5%) with SDS 2; and 572 (8.9%) with SDS ≥3. In total, 775 incident ASCVD events and 1573 deaths were observed over a median follow-up of 17.0 years. Increasing SDS was significantly associated with incident ASCVD and all-cause mortality after adjusting for traditional risk factors (ASCVD: per unit increase in SDS hazard ratio, 1.15 [95% CI, 1.07-1.24]; mortality: per unit increase in SDS hazard ratio, 1.13 [95% CI, 1.08-1.19]). Adding SDS to pooled cohort equations components in a Cox model for 10-year ASCVD risk prediction did not significantly improve discrimination (=0.208) or reclassification (=0.112).
Although SDS is independently associated with incident ASCVD and all-cause mortality, it does not improve 10-year ASCVD risk prediction beyond pooled cohort equations.
健康的社会决定因素导致心血管结局存在差异，但它们尚未被纳入当前的心血管风险评估模式。
使用来自 6 个美国现场中心的多民族动脉粥样硬化研究的数据，创建基线社会劣势评分（SDS）指数，以探讨其与动脉粥样硬化性心血管疾病（ASCVD）和全因死亡率的相关性，并评估其对 ASCVD 风险预测的影响。SDS 的范围为 0 到 4，通过计算以下社会因素的总和来计算：（1）家庭收入低于联邦贫困线；（2）未完成高中学业；（3）单身生活状态；（4）经历过终身歧视。Cox 模型用于检验 SDS 与每种结局之间的关联，调整了传统心血管风险因素。通过将 SDS 纳入汇总队列方程，检验了 ASCVD 风险的判别和重新分类的变化。
共有 6434 名参与者（平均年龄 61.9±10.2 岁；女性 52.8%；非白人 60.9%）可获得 SDS，其中 SDS0 为 1733 人（26.9%），SDS1 为 2614 人（40.6%），SDS2 为 1515 人（23.5%），SDS≥3 为 572 人（8.9%）。在中位随访 17.0 年期间，共观察到 775 例 ASCVD 事件和 1573 例死亡。在调整传统风险因素后，SDS 增加与 ASCVD 事件和全因死亡率显著相关（ASCVD：每单位 SDS 危险比增加 1.15[95%CI，1.07-1.24]；死亡率：每单位 SDS 危险比增加 1.13[95%CI，1.08-1.19]）。在 Cox 模型中，将 SDS 添加到用于 10 年 ASCVD 风险预测的汇总队列方程组件中，并不会显著提高判别力（=0.208）或重新分类（=0.112）。
尽管 SDS 与 ASCVD 事件和全因死亡率独立相关，但它不能提高汇总队列方程之外的 10 年 ASCVD 风险预测。
