Suppr超能文献

心血管健康与骨质疏松性骨折之间的关联:一项基于全国人口的研究。

Association between cardiovascular health and osteoporotic fractures: a national population-based study.

作者信息

Ou Jun, Wang Tingting, Lei Ridan, Sun Mengting, Ruan Xiaorui, Wei Jianhui, Qin Jiabi

机构信息

Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, NO. 172 Tong Zi Po Road, Yuelu District, Changsha, 410006, Hunan, China.

Nanhua Hospital, Health School of Nuclear Industry, University of South China, NO. 336 Dong Feng South Road, ZhuHui District, Hengyang, 421002, Hunan, China.

出版信息

Sci Rep. 2025 Jan 30;15(1):3844. doi: 10.1038/s41598-025-88020-5.

Abstract

Osteoporotic fractures are a major public health concern, particularly among the aging population, as they significantly contribute to morbidity, mortality, and reduced quality of life. While cardiovascular health (CVH) has traditionally been linked to cardiovascular disease outcomes, emerging evidence suggests it may also influence bone health. This study investigates the association between CVH, as measured by the Life's Essential 8 (LE8) score, and the prevalence of osteoporotic fractures in U.S. adults. This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. A total of 17,606 adults aged 20 and above were included in the analysis after excluding participants with missing data on CVH or osteoporotic fractures. CVH was assessed using the LE8 score, which incorporates eight modifiable cardiovascular health metrics: diet, physical activity, tobacco use, sleep, body mass index (BMI), lipid levels, blood glucose, and blood pressure. The primary outcome, osteoporotic fractures, was identified through self-reported data confirmed by a physician. Weighted multivariate logistic regression models were used to estimate the association between CVH and the prevalence of osteoporotic fractures, adjusting for demographic and health-related covariates. Participants with higher CVH scores had a lower prevalence of osteoporotic fractures. In the fully adjusted model, each 1-point increase in the LE8 score was associated with a 1% reduction in the odds of osteoporotic fractures (OR = 0.99, 95% CI: 0.98-0.99). Compared to participants with low CVH levels, those with moderate CVH had a 22% lower odds of osteoporotic fractures (OR = 0.78, 95% CI 0.70-0.87), and those with high CVH had a 34% lower odds (OR = 0.66, 95% CI 0.56-0.79). A significant linear trend was observed across different CVH levels (P for trend < 0.001). Subgroup analyses revealed that the inverse relationship between CVH and osteoporotic fractures was consistent across different demographic and health-related subgroups. This study highlights a significant inverse association between cardiovascular health and osteoporotic fractures in U.S. adults. These findings suggest that maintaining a high level of cardiovascular health, as measured by the LE8 score, may be important in reducing the risk of osteoporotic fractures. Public health strategies that integrate cardiovascular and bone health interventions may enhance overall health outcomes and reduce the societal burden of both cardiovascular diseases and osteoporosis.

摘要

骨质疏松性骨折是一个重大的公共卫生问题,在老年人群中尤为突出,因为它们会显著增加发病率、死亡率,并降低生活质量。传统上,心血管健康(CVH)一直与心血管疾病的结局相关,但新出现的证据表明,它也可能影响骨骼健康。本研究调查了以生命基本8项(LE8)评分衡量的CVH与美国成年人骨质疏松性骨折患病率之间的关联。这项横断面研究利用了2005年至2018年国家健康与营养检查调查(NHANES)的数据。在排除CVH或骨质疏松性骨折数据缺失的参与者后,共有17606名20岁及以上的成年人纳入分析。使用LE8评分评估CVH,该评分纳入了八项可改变的心血管健康指标:饮食、身体活动、吸烟、睡眠、体重指数(BMI)、血脂水平、血糖和血压。主要结局骨质疏松性骨折通过医生确认的自我报告数据确定。使用加权多变量逻辑回归模型来估计CVH与骨质疏松性骨折患病率之间的关联,并对人口统计学和健康相关协变量进行调整。CVH评分较高的参与者骨质疏松性骨折的患病率较低。在完全调整模型中,LE8评分每增加1分,骨质疏松性骨折的几率降低1%(OR = 0.99,95%CI:0.98 - 0.99)。与CVH水平低的参与者相比,CVH水平中等的参与者骨质疏松性骨折的几率低22%(OR = 0.78,95%CI 0.70 - 0.87),CVH水平高的参与者骨质疏松性骨折的几率低34%(OR = 0.66,95%CI 0.56 - 0.79)。在不同的CVH水平上观察到显著的线性趋势(趋势P < 0.001)。亚组分析显示,CVH与骨质疏松性骨折之间的负相关关系在不同的人口统计学和健康相关亚组中是一致的。本研究强调了美国成年人心血管健康与骨质疏松性骨折之间存在显著的负相关。这些发现表明,以LE8评分衡量,维持高水平的心血管健康对于降低骨质疏松性骨折的风险可能很重要。整合心血管和骨骼健康干预措施的公共卫生策略可能会改善整体健康结局,并减轻心血管疾病和骨质疏松症的社会负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bf/11782481/910e89f457e7/41598_2025_88020_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验