The association of osteoporosis and cardiovascular disease risk score based on the Framingham and ACC/AHA risk prediction models: a cross-sectional analysis of Bushehr Elderly Health Program

Journal of Diabetes & Metabolic Disorders(2023)

引用 0|浏览3
暂无评分
摘要
Background The association between osteoporosis and cardiovascular disease, two major health problems, has been reported in some studies. In this study was aimed to investigate the relationship between osteoporosis and the CVD risk score based on Framingham and American College of Cardiology and the American Heart Association (ACC/AHA) prediction models in the population over 60 years old. Methods A cross-sectional analysis was conducted on data from 2389 men and women participating in the Bushehr Elderly Health (BEH) program. Osteoporosis was defended as T-score ≤ − 2.5 at any site (total hip, femoral neck and lumbar spine (L1-L4). Based on Framingham and ACC/AHA risk scores, participants were categorized as non-high risk (< 20%) or high-risk (≥ 20%). Logistic regression model, was applied to investigate the relationship between osteoporosis and cardiovascular disease risk scores. All comparisons were stratified by sex. Results Considering the cut point of ≥ 20% for CVD risk, 36.7% of women and 66.2% of men were categorized as having high risk of CVD in ACC/AHA model. These values in women and men based on the Framingham model were 30% and 35.7%, respectively. In general, there was a negative significant correlation between BMD in the femoral neck, total hip and TBS except for the spine with the CVD risk score in both models. After adjusting for confounding variables, a significant positive association was observed between osteoporosis only at femoral neck with CVD risk score ≥ 20% based on ACC/AHA in both genders. Conclusion The ACC/AHA model is effective in identifying the CVD risk difference between individuals with and without osteoporosis.
更多
查看译文
关键词
cardiovascular disease risk score,osteoporosis,acc/aha risk prediction models,health,cross-sectional
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要