Mi Xiaomeng, Xiong Suting, Xu Wenguo, Yao Fang, Huang Jie, Cui Lan, Qin Yu, Su Jian, Xu Wenchao, Tao Ran, Zhou Jinyi
Chronic Non-Communicable Disease Prevention and Control Section, Changzhou Center for Disease Control and Prevention, Changzhou Institute for Advanced Study of Public Health, Nanjing Medical University, Changzhou, China.
Chronic Non-Communicable Disease Prevention and Control Section, Nantong Center for Disease Control and Prevention, Nantong, China.
Front Cardiovasc Med. 2025 Aug 22;12:1634134. doi: 10.3389/fcvm.2025.1634134. eCollection 2025.
Identifying and understanding different dyslipidemia patterns is crucial for maintaining the cardiovascular health of older adults. Therefore, this study aimed to investigate the dyslipidemia profiles of the elderly population from communities in an Eastern Chinese province, focusing on dyslipidemia subtypes and patterns, and exploring the associated demographic and health-related factors.
A cross-sectional survey was conducted in communities in an Eastern Chinese province. Dyslipidemia patterns were defined using 4-digit binary codes for abnormal TC, TG, LDL-C, and HDL-C. Correspondence analysis explored subtype-pattern associations to reveal common combinations. Binary and multinomial logistic regressions, with Bonferroni correction, examined relationships between factors and dyslipidemia patterns.
Among 44,304 participants (31.5% dyslipidemia), correspondence analysis delineated patterns across Hyper_TC, Hyper_TG, Hyper_LDL, and Hypo_HDL subtypes, including Hyper_TC/LDL co-occurrence and Hyper_TG/Hypo_HDL independence, varying by gender. Multifactorial analyses revealed gender-based effects of age, education, income, and lifestyle, but consistent risks from comorbidities and urban-rural factors. Dyslipidemia subtype patterns and risk factor associations are thus gender- and pattern-specific.
This study provided an in-depth analysis of dyslipidemia subtype patterns among community-dwelling elderly in Eastern China. The findings emphasized that considering gender- and pattern-specific risk factors is crucial in the prevention and management of dyslipidemia among older adults.
识别和了解不同的血脂异常模式对于维护老年人的心血管健康至关重要。因此,本研究旨在调查中国东部某省社区老年人群的血脂异常情况,重点关注血脂异常亚型和模式,并探索相关的人口统计学和健康相关因素。
在中国东部某省的社区进行了一项横断面调查。血脂异常模式采用四位二进制编码定义,用于表示总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白胆固醇(LDL-C)和高密度脂蛋白胆固醇(HDL-C)异常。对应分析探索亚型与模式之间的关联,以揭示常见组合。采用二元和多项逻辑回归,并进行Bonferroni校正,检验因素与血脂异常模式之间的关系。
在44304名参与者中(31.5%患有血脂异常),对应分析描绘了高TC、高TG、高LDL和低HDL亚型的模式,包括高TC/LDL共现和高TG/低HDL独立,且因性别而异。多因素分析揭示了年龄、教育程度、收入和生活方式的性别差异效应,但合并症和城乡因素带来的风险是一致的。因此,血脂异常亚型模式和危险因素关联具有性别和模式特异性。
本研究对中国东部社区居住老年人的血脂异常亚型模式进行了深入分析。研究结果强调,在老年人血脂异常的预防和管理中,考虑性别和模式特异性危险因素至关重要。