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Background: Risk factors for birth defects are frequently investigated using data limited to liveborn infants. By conditioning on survival, results of such studies may be distorted by selection bias, also described as "livebirth bias." However, the implications of livebirth bias on risk estimation remain poorly understood.Objectives: We sought to quantify livebirth bias and to investigate the conditions under which it arose.Methods: We used data on 3994 birth defects cases and 11 829 controls enrolled in the National Birth Defects Prevention Study to compare odds ratio (OR) estimates of the relationship between three established risk factors (antiepileptic drug use, smoking, and multifetal pregnancy) and four birth defects (anencephaly, spina bifida, omphalocele, and cleft palate) when restricted to livebirths as compared to among livebirths, stillbirths, and elective terminations. Exposures and birth defects represented varying strengths of association with livebirth; all controls were liveborn. We performed a quantitative bias analysis to evaluate the sensitivity of our results to excluding terminated and stillborn controls.Results: Cases ranged from 33% liveborn (anencephaly) to 99% (cleft palate). Smoking and multifetal pregnancy were associated with livebirth among anencephaly (crude OR [cOR] 0.61 and cOR 3.15, respectively) and omphalocele cases (cOR 2.22 and cOR 5.22, respectively). For analyses of the association between exposures and birth defects, restricting to livebirths produced negligible differences in estimates except for anencephaly and multifetal pregnancy, which was twofold higher among livebirths (adjusted OR [aOR] 4.93) as among all pregnancy outcomes (aOR 2.44). Within tested scenarios, bias analyses suggested that results were not sensitive to the restriction to liveborn controls.Conclusions: Selection bias was generally limited except for high mortality defects in the context of exposures strongly associated with livebirth. Findings indicate that substantial livebirth bias is unlikely to affect studies of risk factors for most birth defects. [ABSTRACT FROM AUTHOR]

Brisk walking for three or more hours per week can lower the risk of heart attack in women as much as vigorous exercise. This was one of the conclusions of the Nurses' Health Study, which has followed 121,700 nurses since 1976. Women who walked briskly for three or more hours per week were 30% to 40% less likely to have a heart attack compared to women who were sedentary. Sedentary women who became active in middle age also lowered their risk compared to those who remained sedentary.

Objective: We examined lifestyle factors with midlife weight change according to history of gestational diabetes mellitus (GDM) in a large longitudinal female cohort.Research Design and Methods: In the Nurses' Health Study II, we categorized changes in lifestyle within 4-year periods and estimated their associations with concurrent changes in body weight (kilograms) among parous women after age 40 years by GDM history status (N = 54,062; 5.3% with a history of GDM) for the following: diet quality (Alternate Healthy Eating Index [AHEI]), leisure-time physical activity (PA), alcohol consumption, and smoking status.Results: Over a median follow-up of 13 years, average 4-year weight gain was 1.10 and 1.33 kg for women with and without prior GDM, respectively. Women with improved diet quality had favorable 4-year weight change, particularly those with a history of GDM (AHEI change [95% CI] from low to high -2.97 kg [-4.34, -1.60] vs. -1.19 kg [-1.41, -0.96] for GDM vs. non-GDM, respectively; P heterogeneity = 0.04). Increasing PA was associated with weight maintenance for GDM women only (PA increase [95% CI] from low to high 0.26 kg [-0.25, 0.77] vs. 0.90 kg [0.80, 1.01] for GDM vs. non-GDM, respectively; P heterogeneity = 0.02). For both GDM and non-GDM women, weight change did not differ significantly with change in alcohol consumption, while women who quit smoking had significant weight gain (4.38 kg for GDM and 3.85 kg for non-GDM).Conclusions: Improvements in diet quality and PA were related to less weight gain in midlife among parous women, and the benefit of such improvements on weight management was particularly pronounced among women with a history of GDM. [ABSTRACT FROM AUTHOR]

Aims The aim of this study was to explore the association of pregnancy loss (PL) with the incidence of cardiovascular disease (CVD) and examine the extent to which this relation is mediated by subsequent metabolic disorders. Methods and results We followed 95 465 ever-gravid women participating in the Nurses' Health Study II between 1993 and 2017. Cox proportional hazards models were used to estimate the hazard ratios (HRs) of CVD, including coronary heart disease (CHD), and stroke, according to the occurrence of PL. A mediation analysis was conducted to explore the intermediating effect of subsequent type 2 diabetes, hypertension, or hypercholesterolaemia. During 2 205 392 person-years of follow-up (mean 23.10 years), 2225 (2.3%) incident CVD cases were documented. After adjusting for confounding factors, PL was associated with an HR of 1.21 [95% confidence interval (CI) 1.10–1.33] for CVD during follow-up. A similar association was observed for CHD (HR 1.20; 95% CI 1.07–1.35) and stroke (HR 1.23; 95% CI 1.04–1.44). The risk of CVD increased with the number of PLs [HR 1.18 (95% CI 1.06–1.31) for 1 and 1.34 (95% CI 1.13–1.59) for ≥2 times] and was greater for PL occurring early in reproductive lifespan [HR 1.40 (95% CI 1.21–1.62) for age ≤23 years, 1.25 (95% CI 1.09–1.43) for age 24–29 years, and 1.03 (95% CI 0.88–1.19) for age ≥30 years]. Hypertension, hypercholesterolaemia, and type 2 diabetes all explained <1.80% of the association between PL and CVD. Conclusion PL was associated with a greater CVD risk, independently of subsequent development of metabolic disorders. [ABSTRACT FROM AUTHOR]

Obesity and weight gain may increase a woman's risk of stroke. This is one of the conclusions of the Nurses' Health Study, which has followed 116,759 nurses since 1976. As of 1992, there were 866 strokes in the group, 403 of which were caused by a blood clot that blocked blood flow to the brain (ischemic strokes) and 260 of which were hemorrhagic strokes. The risk of ischemic stroke rose as a woman's body mass index (BMI) rose and was more than twice as high in women with a BMI of 32 or greater. Weight gain also increased the risk of ischemic stroke., Objective. -- To examine the associations of body mass index (BMI) and weight change with risk of stroke in women. Setting and Design. -- Prospective cohort study among US female registered nurses participating in the Nurses&apos; Health Study. Participants. -- A total of 116 759 women aged 30 to 55 years in 1976 who were free from diagnosed coronary heart disease, stroke, and cancer. Main Outcome Measure. -- Incidence of ischemic stroke, hemorrhagic stroke (subarachnoid or intraparenchymal hemorrhage), and total stroke. Results. -- During 16 years of follow-up, 866 total strokes (including 403 ischemic strokes and 269 hemorrhagic strokes) were documented. In multivariate analyses adjusted for age, smoking, postmenopausal hormone use, and menopausal status, women with increased BMI ([is greater than or equal to]27 kg/[m.sup.2]) had significantly increased risk of ischemic stroke, with relative risks (RRs) of 1.75 (95% confidence interval [Cl], 1.17-2.59) for BMI of 27 to 28.9 kg/[m.sup.2]; 1.90 (95% Cl, 1.28-2.82) for BMI of 29 to 31.9 kg/[m.sup.2]; and 2.37 (95% Cl, 1.60-3.50) for BMI of 32 kg/[m.sup.2] or more (P for trend [is less than] .001), as compared with those with a BMI of less than 21 kg/[m.sup.2]. For hemorrhagic stroke there was a nonsignificant inverse relation between obesity and hemorrhagic stroke, with the highest risk among women in the leanest BMI category (P for trend = .20). For total stroke the RRs were somewhat attenuated compared with those for ischemic stroke but remained elevated for women with higher BMI (P for trend [is less than] .001). In multivariate analyses that also adjusted for BMI at age 18 years, weight gain from age 18 years until 1976 was associated with an RR for ischemic stroke of 1.69 (95% Cl, 1.26-2.29) for a gain of 11 to 19.9 kg and 2.52 (95% Cl, 1.80-3.52) for a gain of 20 kg or more (P for trend [is less than] .001), as compared with women who maintained stable weight (loss or gain [is less than] 5 kg). Although weight change was not related to risk of hemorrhagic stroke (P for trend=.20), a direct relationship was observed between weight gain and total stroke risk (P for trend [is less than] .001). Conclusions. -- These prospective data indicate that both obesity and weight gain in women are important risk factors for ischemic and total stroke but not hemorrhagic stroke. The relationship between obesity and total stroke depends on the distribution of stroke subtypes in the population.

A history of preterm or small (SGA) or large (LGA) for gestational age offspring is associated with smoking and unfavorable levels of BMI, blood pressure, glucose and lipids. Whether and to what extent the excess cardiovascular risk observed in women with these pregnancy complications is explained by conventional cardiovascular risk factors (CVRFs) is not known. We examined the association between a history of SGA, LGA or preterm birth and cardiovascular disease among 23,284 parous women and quantified the contribution of individual CVRFs to the excess cardiovascular risk using an inverse odds weighting approach. The hazard ratios (HR) between SGA and LGA offspring and CVD were 1.30 (95% confidence interval (CI) 1.15, 1.48) and 0.89 (95% CI 0.76, 1.03), respectively. Smoking explained 49% and blood pressure may have explained ≈12% of the excess cardiovascular risk in women with SGA offspring. Women with preterm birth had a 24% increased risk of CVD (HR 1.24, 95% CI 1.06, 1.45), but we found no evidence for CVRFs explaining any of this excess cardiovascular risk. While smoking explains a substantial proportion of excess cardiovascular risk in women with SGA offspring and blood pressure may explain a small proportion in these women, we found no evidence that conventional CVRFs explain any of the excess cardiovascular risk in women with preterm birth. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Menstrual cycle dysfunction has been associated with many endocrine-related diseases, but evidence linking menstrual cycle dysfunction with gestational diabetes mellitus (GDM) is scant. The current study investigated the association of pre-pregnancy menstrual cycle regularity and length during adolescence, early adulthood and mid-adulthood with the subsequent risk of GDM. Methods: Between 1993 and 2009, we followed 10,906 premenopausal women participating in the Nurses' Health Study II who reported menstrual cycle characteristics during adolescence (age 14–17 years), early adulthood (age 18–22 years) and mid-adulthood (age 29–46 years). Incident GDM was ascertained from a self-reported questionnaire regarding physician diagnosis. Log-binomial models with generalised estimating equations were used to estimate the RRs and 95% CI for the associations between menstrual cycle characteristics and GDM. Results: We documented 578 incident cases of GDM among 14,418 pregnancies over a 16 year follow-up. After adjusting for potential confounders, women reporting always having irregular menstrual cycles during mid-adulthood had a 65% (95% CI 21, 125%) higher risk of GDM than women reporting very regular cycles. GDM risk was also greater among women reporting that their cycles were usually ≥32 days during mid-adulthood, compared with women reporting cycles between 26 and 31 days (RR 1.42 [95% CI 1.15, 1.75]). The risk of GDM was greater for women whose cycles changed from regular early in their reproductive years to irregular or from <32 days to ≥32 days during mid-adulthood, compared with women whose cycles remained <32 days or regular, respectively. Conclusions/interpretation: Women whose cycles were long or irregular during mid-adulthood, but not in adolescence or young adulthood, were at higher risk of GDM. [ABSTRACT FROM AUTHOR]

Primary means of reducing the risk of coronary heart disease in women include not smoking, lowering total cholesterol levels, engaging in physical activity, and treating high blood pressure and obesity. Women who smoke have 2 to 4 times the risk of coronary heart disease than women who do not. Decreasing levels of low-density lipoprotein and increasing levels of high-density lipoprotein reduce the risk. Women who are physically active may have 60% to 70% lower risk than inactive women. Moderate alcohol intake, antioxidant vitamins, and aspirin may also lower the risk. The use of oral contraceptives, sudden and early menopause, and removal of the ovaries increase the risk. However, normal menopause does not suddenly increase risk. Hormone replacement following menopause may help reduce risk, but may not benefit other aspects of women's health. Studies have shown that treating serious hypertension reduces CHD risk, however treating mild hypertension may not. Diabetes mellitus increases the risk of death from coronary heart disease by 3 to 7 times in women.

The ubiquity of smartphones, with their increasingly sophisticated array of sensors, presents an unprecedented opportunity for researchers to collect longitudinal, diverse, temporally-dense data about human behavior while minimizing participant burden. Researchers increasingly make use of smartphones for "digital phenotyping," the collection and analysis of raw phone sensor and log data to study the lived experiences of subjects in their natural environments using their own devices. While digital phenotyping has shown promise in fields such as psychiatry and neuroscience, there are fundamental gaps in our knowledge about data collection and non-collection (i.e., missing data) in smartphone-based digital phenotyping. In this meta-study using individual-level data from six different studies, we examined accelerometer and GPS sensor data of 211 participants, amounting to 29,500 person-days of observation, using Bayesian hierarchical negative binomial regression with study- and user-level random intercepts. Sensitivity analyses including alternative model specification and stratified models were conducted. We found that iOS users had lower GPS non-collection than Android users. For GPS data, rates of non-collection did not differ by race/ethnicity, education, age, or gender. For accelerometer data, Black participants had higher rates of non-collection, but rates did not differ by sex, education, or age. For both sensors, non-collection increased by 0.5% to 0.9% per week. These results demonstrate the feasibility of using smartphone-based digital phenotyping across diverse populations, for extended periods of time, and within diverse cohorts. As smartphones become increasingly embedded in everyday life, the insights of this study will help guide the design, planning, and analysis of digital phenotyping studies. [ABSTRACT FROM AUTHOR]