Department of Medicine, Section of General Internal Medicine Boston University Chobanian and Avedisian School of Medicine Boston MA USA.
GenderCare Center Boston Medical Center Boston MA USA.
J Am Heart Assoc. 2024 Nov 19;13(22):e036898. doi: 10.1161/JAHA.124.036898. Epub 2024 Nov 7.
Seven million lesbian, gay, and bisexual (LGB) adults will be aged >50 years by 2030; assessing and addressing their risk for cardiovascular disease is critical.
We analyzed a nationwide cohort using the Veterans Health Administration data. Sexual orientation (SO) was classified via a validated natural language processing algorithm. Prevalent atherosclerotic cardiovascular disease (ASCVD) (history of acute myocardial infarction, ischemic stroke, or revascularization) was identified via ( and ) codes. The index date was the date of the first primary care appointment on or after October 1, 2009. We ascertained covariates and prevalent ASCVD in the year following the index date; the baseline date was 1 year after the index date. We calculated sample statistics by sex and SO and used logistic regression analyses to assess associations between SO and prevalent ASCVD. Of 1 102 193 veterans with natural language processing-defined SO data, 170 861 were classified as LGB. Prevalent ASCVD was present among 25 031 (4105 LGB). Adjusting for age, sex, race, and Hispanic ethnicity, LGB veterans had 1.24 [1.19-1.28] greater odds of prevalent ASCVD versus non-LGB identified veterans. This association remained significant upon additional adjustment for the ASCVD risk factors substance use, anxiety, and depression (odds ratio [OR],1.17 [95% CI, 1.13-1.21]). Among a subset with self-reported SO, findings were consistent (OR, 1.53 [95% CI, 1.20-1.95]).
This is one of the first studies to examine cardiovascular risk factors and disease of the veteran population stratified by natural language processing-defined SO. Future research must explore psychological, behavioral, and physiological mechanisms that result in poorer cardiovascular health among LGB veterans.
到 2030 年,将有 700 万同性恋、双性恋和变性(LGB)成年人年龄超过 50 岁;评估和解决他们的心血管疾病风险至关重要。
我们使用退伍军人健康管理局的数据对全国性队列进行了分析。通过验证后的自然语言处理算法对性取向(SO)进行分类。通过 (和) 代码确定现患动脉粥样硬化性心血管疾病(ASCVD)(急性心肌梗死、缺血性卒中和血运重建史)。索引日期为 2009 年 10 月 1 日或之后首次初级保健预约的日期。我们在索引日期后的一年中确定了协变量和现患 ASCVD;基线日期为索引日期后 1 年。我们按性别和 SO 计算样本统计数据,并使用逻辑回归分析评估 SO 与现患 ASCVD 之间的关联。在有自然语言处理定义 SO 数据的 1102193 名退伍军人中,有 170861 人被归类为 LGB。25031 人(4105 人为 LGB)患有现患 ASCVD。在调整年龄、性别、种族和西班牙裔后,LGB 退伍军人与非 LGB 退伍军人相比,现患 ASCVD 的可能性增加 1.24 [1.19-1.28]。在进一步调整物质使用、焦虑和抑郁等 ASCVD 风险因素后,这种关联仍然显著(比值比[OR],1.17 [95% CI,1.13-1.21])。在具有自我报告 SO 的亚组中,结果一致(OR,1.53 [95% CI,1.20-1.95])。
这是第一项使用自然语言处理定义的 SO 分层检查退伍军人人群心血管风险因素和疾病的研究之一。未来的研究必须探索导致 LGB 退伍军人心血管健康状况较差的心理、行为和生理机制。