DESCRIPTION (provided by applicant): Currently available cardiovascular (CVD) risk scores in women usually include risk factors which are gender- neutral and often lead to underestimate of CVD risk. There are factors in the life course of women that are unique and gender-specific which relate to long-term CVD risk. Pregnancy is considered a "cardiometabolic stress test" such that adverse pregnancy factors/outcomes in a woman, predict future CVD risk factors and incident CVD. The American Heart Association and American College of Cardiology Effectiveness-Based Guidelines for CVD Prevention in Women recommend taking a pregnancy history for CVD risk stratification, however it is unclear which pregnancy factors are independently related to CVD when taken together. Specific pregnancy factors that have been demonstrated to predict CVD risk factors and CVD include pregnancy- induced hypertension or pre-eclampsia, gestational diabetes, having a small for gestational age infant, a low or very high number of pregnancies, pre-term delivery, stillbirth and a history of subfertility. We believe thata pregnancy risk score derived from these candidate pregnancy factors will help medical caregivers determine which specific factors in a woman's pregnancy history are most important as far as predicting future CVD risk factors and future CVD. A pregnancy risk score may help providers with personalized, earlier referral for upstream risk factor modification and may also allow a woman to assess her own CVD risk. In this proposal, we have the following three research goals: 1. To determine which subset of pregnancy related factors is related to blood pressure, oral glucose tolerance test and lipid profile, in the V¿sterbotten Intervention Programme (VIP) when linked to the Swedish Population Registers (estimated n=16,041). 2. Utilize a multiple- marker approach to develop and validate a pregnancy factor risk index in the Swedish Population Registers (estimated n=800,000) and 3. To determine whether the pregnancy factor risk score (developed in specific AIM 2) improves CVD risk stratification (discrimination, calibration and net reclassification) above and beyond established CVD risk factors among women using the VIP dataset linked to Swedish Population Register.