Division of General Medicine, Columbia University Irving Medical Center, New York, New York.
Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena.
JAMA Netw Open. 2024 Apr 1;7(4):e248584. doi: 10.1001/jamanetworkopen.2024.8584.
The benefit of adding social determinants of health (SDOH) when estimating atherosclerotic cardiovascular disease (ASCVD) risk is unclear.
To examine the association of SDOH at both individual and area levels with ASCVD risks, and to assess if adding individual- and area-level SDOH to the pooled cohort equations (PCEs) or the Predicting Risk of CVD Events (PREVENT) equations improves the accuracy of risk estimates.
DESIGN, SETTING, AND PARTICIPANTS: This cohort study included participants data from 4 large US cohort studies. Eligible participants were aged 40 to 79 years without a history of ASCVD. Baseline data were collected from 1995 to 2007; median (IQR) follow-up was 13.0 (9.3-15.0) years. Data were analyzed from September 2023 to February 2024.
Individual- and area-level education, income, and employment status.
ASCVD was defined as the composite outcome of nonfatal myocardial infarction, death from coronary heart disease, and fatal or nonfatal stroke.
A total of 26 316 participants were included (mean [SD] age, 61.0 [9.1] years; 15 494 women [58.9%]; 11 365 Black [43.2%], 703 Chinese American [2.7%], 1278 Hispanic [4.9%], and 12 970 White [49.3%]); 11 764 individuals (44.7%) had at least 1 adverse individual-level SDOH and 10 908 (41.5%) had at least 1 adverse area-level SDOH. A total of 2673 ASCVD events occurred during follow-up. SDOH were associated with increased risk of ASCVD at both the individual and area levels, including for low education (individual: hazard ratio [HR], 1.39 [95% CI, 1.25-1.55]; area: HR, 1.31 [95% CI, 1.20-1.42]), low income (individual: 1.35 [95% CI, 1.25-1.47]; area: HR, 1.28 [95% CI, 1.17-1.40]), and unemployment (individual: HR, 1.61 [95% CI, 1.24-2.10]; area: HR, 1.25 [95% CI, 1.14-1.37]). Adding area-level SDOH alone to the PCEs did not change model discrimination but modestly improved calibration. Furthermore, adding both individual- and area-level SDOH to the PCEs led to a modest improvement in both discrimination and calibration in non-Hispanic Black individuals (change in C index, 0.0051 [95% CI, 0.0011 to 0.0126]; change in scaled integrated Brier score [IBS], 0.396% [95% CI, 0.221% to 0.802%]), and improvement in calibration in White individuals (change in scaled IBS, 0.274% [95% CI, 0.095% to 0.665%]). Adding individual-level SDOH to the PREVENT plus area-level social deprivation index (SDI) equations did not improve discrimination but modestly improved calibration in White participants (change in scaled IBS, 0.182% [95% CI, 0.040% to 0.496%]), Black participants (0.187% [95% CI, 0.039% to 0.501%]), and women (0.289% [95% CI, 0.115% to 0.574%]).
In this cohort study, both individual- and area-level SDOH were associated with ASCVD risk; adding both individual- and area-level SDOH to the PCEs modestly improved discrimination and calibration for estimating ASCVD risk for Black individuals, and adding individual-level SDOH to PREVENT plus SDI also modestly improved calibration. These findings suggest that both individual- and area-level SDOH may be considered in future development of ASCVD risk assessment tools, particularly among Black individuals.
重要性：在估计动脉粥样硬化性心血管疾病（ASCVD）风险时，添加社会决定因素（SDOH）的益处尚不清楚。
目的：本研究旨在评估个体和地区层面的 SDOH 与 ASCVD 风险的相关性，并评估将个体和地区层面的 SDOH 添加到汇总队列方程（PCE）或预测 CVD 事件风险（PREVENT）方程中是否可以提高风险估计的准确性。
设计、设置和参与者：这是一项队列研究，纳入了来自 4 项美国大型队列研究的数据。合格的参与者年龄在 40 至 79 岁之间，无 ASCVD 病史。基线数据收集于 1995 年至 2007 年；中位（IQR）随访时间为 13.0（9.3-15.0）年。数据分析于 2023 年 9 月至 2024 年 2 月进行。
暴露因素：个体和地区层面的教育、收入和就业状况。
主要结果和措施：ASCVD 定义为非致死性心肌梗死、冠心病死亡和致命或非致命性卒中的复合结局。
研究结果：共纳入 26316 名参与者（平均[SD]年龄 61.0[9.1]岁；15494 名女性[58.9%]；11365 名黑人[43.2%]，703 名华裔美国人[2.7%]，1278 名西班牙裔[4.9%]，12970 名白人[49.3%]）；11764 人（44.7%）至少存在 1 项不利的个体层面 SDOH，10908 人（41.5%）至少存在 1 项不利的地区层面 SDOH。在随访期间共发生 2673 例 ASCVD 事件。SDOH 与个体和地区层面的 ASCVD 风险增加相关，包括低教育水平（个体：风险比[HR]，1.39[95%CI，1.25-1.55]；地区：HR，1.31[95%CI，1.20-1.42]）、低收入（个体：1.35[95%CI，1.25-1.47]；地区：HR，1.28[95%CI，1.17-1.40]）和失业（个体：HR，1.61[95%CI，1.24-2.10]；地区：HR，1.25[95%CI，1.14-1.37]）。单独将地区层面的 SDOH 添加到 PCE 中并未改变模型的区分度，但适度提高了校准度。此外，将个体和地区层面的 SDOH 同时添加到 PCE 中，可适度提高非西班牙裔黑人个体的区分度和校准度（C 指数的变化，0.0051[95%CI，0.0011-0.0126]；标准化综合 Brier 评分[IBS]的变化，0.396%[95%CI，0.221%-0.802%]），并提高白人个体的校准度（标准化 IBS 的变化，0.274%[95%CI，0.095%-0.665%]）。将个体层面的 SDOH 添加到 PREVENT 加地区社会剥夺指数（SDI）方程中并未提高区分度，但适度提高了白人参与者的校准度（标准化 IBS 的变化，0.182%[95%CI，0.040%-0.496%]）、黑人参与者（0.187%[95%CI，0.039%-0.501%]）和女性（0.289%[95%CI，0.115%-0.574%]）的校准度。
结论和意义：在这项队列研究中，个体和地区层面的 SDOH 均与 ASCVD 风险相关；将个体和地区层面的 SDOH 同时添加到 PCE 中可适度提高黑人个体 ASCVD 风险的预测准确性，并将个体层面的 SDOH 添加到 PREVENT 加 SDI 中也可适度提高校准度。这些发现表明，在未来开发 ASCVD 风险评估工具时，可能需要考虑个体和地区层面的 SDOH，尤其是在黑人个体中。
