Multiparity is associated with poorer cardiovascular health among women from the Multi-Ethnic Study of Atherosclerosis

Am J Obstet Gynecol. 2019 Dec;221(6):631.e1-631.e16. doi: 10.1016/j.ajog.2019.07.001. Epub 2019 Jul 5.

Abstract

Background: Multiparity is associated with a greater risk of incident cardiovascular disease. However, the relationship of parity with cardiovascular health, as measured by the American Heart Association Life's Simple 7 metrics, is uncertain.

Objective: We aimed to examine the association between parity and ideal cardiovascular health among 3430 women, aged 45-84 years, free of clinical cardiovascular disease enrolled in the Multi-Ethnic Study of Atherosclerosis.

Study design: The Multi-Ethnic Study of Atherosclerosis is a prospective cohort study that recruited middle-aged to older women and men from 6 centers in the United States between 2000 and 2002. The study population comprised 38% White, 28% Black, 23% Hispanic, and 11% Chinese American subjects. Parity (total number of live births) was self-reported and categorized as 0, 1-2, 3-4 and ≥5. The Life's Simple 7 metrics, defined according to American Heart Association criteria, include health behaviors (smoking, physical activity, body mass index, diet) and health factors (blood pressure, total cholesterol, and blood glucose). We categorized each metric into ideal (2 points), intermediate (1 point), and poor (0 points). A total cardiovascular health score of 0-8 was considered inadequate; 9-10, average; and 11-14, optimal. We used multinomial logistic regression to examine the cross-sectional association between parity and the cardiovascular health score, adjusted for sociodemographics, field site, hormone therapy, and menopause.

Results: The mean (standard deviation) age was 62 (10) years. The mean (standard deviation) cardiovascular health score was lower with higher parity (8.9 [2.3], 8.7 [2.3], 8.5 [2.2], and 7.8 [2.0] for 0, 1-2, 3-4, and ≥5 live births, respectively). In comparison to inadequate cardiovascular health scores, the adjusted odds of average cardiovascular health scores were significantly lower for all parity categories relative to nulliparity (prevalence odds ratios [OR] for parity of 1-2, 0.64 [95% confidence interval 0.49-0.83]; 3-4, 0.65 [0.49-0.86]; ≥5, 0.64 [0.45-0.91]). Women with ≥5 live births had a lower prevalence of optimal cardiovascular health scores (OR 0.50 [0.30-0.83]). In the fully adjusted models, the association between parity and each Life's Simple 7 metric was only statistically significant for body mass index. Women with ≥5 live births had lower prevalence of ideal body mass index (OR 0.52 [0.35-0.80]). In addition, the test for interaction showed that the association between parity and cardiovascular health was not modified by race/ethnicity (P = .81 for average cardiovascular health scores and P = .20 for optimal cardiovascular health scores).

Conclusion: Multiparity was associated with poorer cardiovascular health, especially for women with ≥5 live births. More research is required to explore the mechanisms by which parity may worsen cardiovascular health.

Keywords: Life’s Simple 7; ideal cardiovascular health metrics; live births; parity; pregnancy.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • American Heart Association
  • Asian / statistics & numerical data
  • Black or African American / statistics & numerical data
  • Blood Glucose / metabolism*
  • Blood Pressure / physiology*
  • Body Mass Index*
  • Cardiovascular Diseases / epidemiology
  • Cardiovascular Diseases / metabolism
  • Cardiovascular Diseases / physiopathology
  • Cholesterol / metabolism*
  • Diet / statistics & numerical data*
  • Ethnicity / statistics & numerical data
  • Exercise*
  • Female
  • Hispanic or Latino / statistics & numerical data
  • Humans
  • Middle Aged
  • Odds Ratio
  • Parity*
  • Risk Factors
  • Smoking / epidemiology*
  • United States / epidemiology
  • White People / statistics & numerical data

Substances

  • Blood Glucose
  • Cholesterol