Female-Specific Risk Factors for CVD: The Impact of Adverse Pregnancy Outcomes on Subsequent Mental Health and CVD Risk

项目总结/摘要 女性特有和女性主导的风险因素为改善心血管疾病提供了机会。 疾病（CVD）的预防和筛查。妊娠并发症是未来的风险标志 通过妊娠的心脏代谢"压力测试"发现CVD，可用于早期CVD 在确定的风险因素（慢性高血压、高胆固醇血症、2型糖尿病）发生之前进行预防 糖尿病）。有先兆子痫病史的妇女（一种涉及高血压的疾病， 怀孕）或早产（<37周妊娠）有两倍的风险未来心血管疾病。心理健康 创伤后应激障碍（PTSD）和抑郁症等疾病在女性中的发病率是男性的两倍 与男性一样，也与心血管疾病风险增加有关。虽然现有的研究和轶事 有证据表明，急性不良妊娠结局（APO;先兆子痫和早产）可 对一些妇女来说是一个创伤性事件，并加速了精神健康状况的发展 怀孕后，缺乏严格的流行病学研究。在多大程度上，APO和心理健康 条件可能共同导致女性CVD也是未知的。这个项目将利用 互补人群和方法学方法，包括观察性流行病学 护士健康研究2和3（NHS 2/3）前瞻性队列研究中的分析， 电子健康记录（EHR）从马萨诸塞州总布里格姆卫生系统的定量 使用机器学习进行预测建模，并招募近期急性APO患者参与 定性访谈。本研究将通过以下方式解决文献中的空白：1）评估 在有APO病史的女性中观察到的CVD风险增加是由以下因素引起的： 使用NHS 2/3的数据，研究怀孕后心理健康状况的发展; 2）在临床上确定 EHR中影响心理健康风险的相关风险和弹性因素 急性APO后的状况;以及3）阐明APO与随后的PTSD之间的关系 通过半结构化定性患者访谈继发于APO相关创伤。 除了对女性一生中心血管疾病风险的积累产生新的见解外， 将通过培养以下方面的新技能，为我发展成为一名独立调查员提供重要培训： 1)使用EHR数据的机器学习，2）定性研究和3）精神病学流行病学。鉴于我 强大的生殖和心血管流行病学背景，我的世界级指导团队，以及 个性化的培训计划，以提高我的技能，我很好地准备完成拟议的研究。 该职业发展奖提供的培训、指导和受保护的时间将独一无二地 使我成为一名领先的流行病学家，致力于改善女性的心血管健康。

PROJECT SUMMARY/ABSTRACT Female-specific and female-predominant risk factors provide opportunities to improve cardiovascular disease (CVD) prevention and screening in women. Pregnancy complications are risk markers for future CVD revealed through the cardiometabolic “stress test” of pregnancy, which can be leveraged for early CVD prevention before the onset of established risk factors (chronic hypertension, hypercholesterolemia, type 2 diabetes). Women with a history of preeclampsia (a condition involving high blood pressure during pregnancy) or preterm delivery (<37 weeks’ gestation) have twice the risk of future CVD. Mental health conditions, such as posttraumatic stress disorder (PTSD) and depression, are twice as common in women as in men and are also associated with increased CVD risk. Although existing studies and anecdotal evidence suggest that acute adverse pregnancy outcomes (APOs; preeclampsia and preterm delivery) can constitute a traumatic event for some women and precipitate the development of mental health conditions after pregnancy, rigorous epidemiologic studies are lacking. The extent to which APOs and mental health conditions may jointly contribute to CVD in women is also unknown. This project will draw on the strengths of complementary populations and methodologic approaches, including observational epidemiologic analyses within the Nurses’ Health Study 2 and 3 (NHS2/3) prospective cohort studies and leveraging electronic health records (EHR) from the Mass General Brigham health system for both quantitative prediction modeling using machine learning and to recruit patients with recent acute APOs to participate in qualitative interviews. This research will address the gaps in the literature by: 1) evaluating the extent to which the increased CVD risk observed among women with a history of APOs is accounted for by the development of mental health conditions after pregnancy using data from NHS2/3; 2) identifying clinically relevant risk and resilience factors from the EHR that influence the risk of developing mental health conditions after an acute APO; and 3) elucidating the relationship between APOs and subsequent PTSD secondary to APO-related trauma through semi-structured qualitative patient interviews. In addition to generating new insights into the accumulation of CVD risk across a woman’s life, this proposal will provide crucial training for my development into an independent investigator by cultivating new skills in: 1) machine learning using EHR data, 2) qualitative research, and 3) psychiatric epidemiology. Given my strong background in reproductive and cardiovascular epidemiology, my world-class mentoring team, and personalized training plan to advance my skillset, I am well equipped to accomplish the proposed research. The training, mentorship, and protected time provided by this Career Development Award will uniquely position me as a leading epidemiologist equipped to improve the cardiovascular health of women.