GW26-e3901 Prevalence and risk factors of hypertension among pre- and post-menopausal women: a cross-sectional study in a rural area of northeast China

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY(2015)

Cited 0|Views12
No score
Abstract
a b s t r a c t Objectives: The aim of this study was to assess the prevalence and risk factors of hypertension in pre- menopausal women (Pre-MW) and post-menopausal women (Post-MW) and determine whether years since menopause (YSM) is associated with hypertension. Methods: A cross-sectional study was conducted with 6324 women over 35 years of age (2616 Pre-MW and 3708 Post-MW). Questionnaires, measurements and blood biochemical indexes were collected. Results: The overall prevalence of hypertension among women in rural northeast China was 48.8%, and it increased with age. Post-MW had a higher prevalence of hypertension than Pre-MW (62.4% vs. 29.7%, P u003c 0.01). After controlling for confounding variables, overweight (OR = 1.97, 95% CI: 1.72-2.25), obe- sity (OR = 2.97, 95% CI: 2.30-3.84), diabetes mellitus (OR = 2.13, 95% CI: 1.73-2.62), high triglycerides (OR = 1.41, 95% CI: 1.20-1.65), and history of cardiovascular diseases in first-degree relatives (OR = 1.60, 95% CI: 1.42-1.81) were associated with hypertension in all participants. However, abdominal obesity (OR = 1.29, 95% CI: 1.05-1.58) was associated with higher odds among Post-MW only. Hypertension was associated with being postmenopausal (OR = 1.22; 95% CI: 1.03-1.46), and the risk of hypertension reached a peak level in the u003c5-year group (OR = 1.29; 95% CI, 1.07-1.57). Conclusions: Postmenopausal status was an independent risk factor for hypertension. The risk of hyper- tension was highest in Post-MW with u003c5 YSM and then decreased. Other risk factors of hypertension were body mass index (BMI), abdominal obesity, a family history of cardiovascular disease among first-degree relatives, a personal history of diabetes, and high TG.
More
Translated text
Key words
hypertension,prevalence,women,risk factors,post-menopausal,cross-sectional
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined