Women with Adverse Pregnancy Outcomes Have Higher Odds of Midlife Stroke: The Population Assessment of Tobacco and Health Study.
Eliza C MillerNatalie A BelloRindcy DavisAlexander M FriedmanMitchell S V ElkindRonald WapnerSarah E TomPublished in: Journal of women's health (2002) (2021)
Background: A history of adverse pregnancy outcomes (APOs) is associated with increased risk of future cardiovascular disease, including stroke. Few large U.S. population-based surveys included data on APOs. Methods: The Population Assessment of Tobacco and Health study is a nationally representative survey of 45,971 U.S. respondents. Female respondents ≥50 years old who reported pregnancy history at the 2013-2014 baseline interview were included in this cross-sectional analysis (n = 3,175; weighted n = 35,783,619). The primary exposure was a history of ≥1 APO, including preterm delivery, low birth weight, preeclampsia, placental abruption, and stillbirth. The primary outcomes were (1) stroke before age 60 and (2) any stroke. We used weighted logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for the association between APO and stroke, adjusting for age, race/ethnicity, socioeconomic status, parity, and vascular risk factors. Results: Among stroke-free respondents, 15% reported ≥1 APO. Among women who reported a stroke before age 60, 39% reported ≥1 APO (p < 0.001); among women reporting stroke at any age, 25% reported ≥1 APO (p = 0.01). Controlling for covariates, women with APOs had increased odds of stroke before age 60 (adjusted OR 2.66, 95% CI 1.49, 4.75). The association of APOs with stroke at any age was not significant after controlling for covariates (adjusted OR 1.57, 95% CI 0.93, 2.64). Conclusion: In this analysis of U.S. nationally representative survey data, APOs were independently associated with midlife stroke. Women with APOs have higher odds of midlife stroke and warrant targeted prevention strategies.
Keyphrases
- atrial fibrillation
- pregnancy outcomes
- cardiovascular disease
- cross sectional
- healthcare
- pregnant women
- public health
- low birth weight
- magnetic resonance imaging
- mental health
- cerebral ischemia
- magnetic resonance
- machine learning
- polycystic ovary syndrome
- computed tomography
- metabolic syndrome
- big data
- climate change
- insulin resistance
- deep learning
- brain injury
- current status
- subarachnoid hemorrhage
- data analysis