{"title":"Association of ideal cardiovascular health and history of gestational diabetes mellitus in NHANES 2007–2018","authors":"","doi":"10.1016/j.diabres.2024.111857","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Population-based studies of ideal cardiovascular health (CVH) and gestational diabetes mellitus (GDM) are scarce.</p></div><div><h3>Methods</h3><p>We conducted a cross-sectional analysis of 2007–2018 National Health Examination and Nutrition Survey women aged ≥ 20 years, who had data on Life’s Simple 7 (LS7) metrics and self-reported GDM history. Each LS7 metric was assigned a score of 0 (non-ideal) and 1(ideal) and summed to obtain total ideal CVH scores (0–7). We used logistic regression models to assess associations between LS7 ideal CVH scores (0–7) and GDM history, accounting for socio-demographic factors.</p></div><div><h3>Results</h3><p>Among 9199 women (mean age: 46 years, 8 % with a GDM history), there was a progressive decrease in the odds of past GDM history across increasing ideal CVH scores. Compared to females with 0–1 ideal CVH scores, females with ideal CVH scores of 3, 4 and 5–7 had an associated 39 % lower [odds ratio: 0.61 (95 % CI: 0.41–0.90)], 50 % lower [0.50 (0.33–0.76)] and 66 % lower [0.34 (0.20–0.56)] odds of past GDM history, respectively. There were notable racial/ethnic and citizenship/nativity differences in these associations.</p></div><div><h3>Conclusions</h3><p>Women with higher ideal CVH scores had lower odds of GDM history. Our findings underscore the importance of optimizing cardiometabolic health among women with GDM history.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":null,"pages":null},"PeriodicalIF":6.1000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes research and clinical practice","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168822724007678","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Population-based studies of ideal cardiovascular health (CVH) and gestational diabetes mellitus (GDM) are scarce.
Methods
We conducted a cross-sectional analysis of 2007–2018 National Health Examination and Nutrition Survey women aged ≥ 20 years, who had data on Life’s Simple 7 (LS7) metrics and self-reported GDM history. Each LS7 metric was assigned a score of 0 (non-ideal) and 1(ideal) and summed to obtain total ideal CVH scores (0–7). We used logistic regression models to assess associations between LS7 ideal CVH scores (0–7) and GDM history, accounting for socio-demographic factors.
Results
Among 9199 women (mean age: 46 years, 8 % with a GDM history), there was a progressive decrease in the odds of past GDM history across increasing ideal CVH scores. Compared to females with 0–1 ideal CVH scores, females with ideal CVH scores of 3, 4 and 5–7 had an associated 39 % lower [odds ratio: 0.61 (95 % CI: 0.41–0.90)], 50 % lower [0.50 (0.33–0.76)] and 66 % lower [0.34 (0.20–0.56)] odds of past GDM history, respectively. There were notable racial/ethnic and citizenship/nativity differences in these associations.
Conclusions
Women with higher ideal CVH scores had lower odds of GDM history. Our findings underscore the importance of optimizing cardiometabolic health among women with GDM history.
期刊介绍:
Diabetes Research and Clinical Practice is an international journal for health-care providers and clinically oriented researchers that publishes high-quality original research articles and expert reviews in diabetes and related areas. The role of the journal is to provide a venue for dissemination of knowledge and discussion of topics related to diabetes clinical research and patient care. Topics of focus include translational science, genetics, immunology, nutrition, psychosocial research, epidemiology, prevention, socio-economic research, complications, new treatments, technologies and therapy.