| 金奕辰,程杨杨,周亚冠,张悦,王慧,徐小林.中国中老年人群4种血脂标志物与心血管代谢性共病进展的关联研究[J].中华流行病学杂志,2024,45(7):923-931 |
| 中国中老年人群4种血脂标志物与心血管代谢性共病进展的关联研究 |
| Associations between 4 lipid biomarkers and cardiometabolic multimorbidity development in middle aged and old adults in China |
| 收稿日期:2023-11-23 出版日期:2024-07-13 |
| DOI：10.3760/cma.j.cn112338-20231123-00314 |
| 中文关键词: 心血管代谢性共病 糖尿病 心血管疾病 脂质标志物 中老年人 |
| 英文关键词: Cardiometabolic multimorbidity Diabetes mellitus Cardiovascular disease Lipid biomarker Middle aged and old adults |
| 基金项目:中央高校基本科研业务费专项资金;浙江省智能预防医学重点实验室2023年种子基金 |
| 作者 | 单位 | E-mail | | 金奕辰 | 浙江大学公共卫生学院, 杭州 310058 | | | 程杨杨 | 浙江省智能预防医学重点实验室, 杭州 310058 | | | 周亚冠 | 浙江大学公共卫生学院, 杭州 310058
浙江省智能预防医学重点实验室, 杭州 310058 | | | 张悦 | 浙江大学公共卫生学院, 杭州 310058
浙江省智能预防医学重点实验室, 杭州 310058 | | | 王慧 | 浙江大学公共卫生学院, 杭州 310058
浙江省智能预防医学重点实验室, 杭州 310058 | | | 徐小林 | 浙江大学公共卫生学院, 杭州 310058
浙江省智能预防医学重点实验室, 杭州 310058
昆士兰大学医学院公共卫生学院, 昆士兰布里斯班 4072 | xiaolin.xu@zju.edu.cn |
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| 中文摘要: |
| 目的 分析中国≥45岁中老年人血脂标志物与心血管代谢性共病（CMM）进展的纵向关联，并探究血脂异常聚集程度及异常组合的效应差异。方法 基于中国健康与养老追踪调查2011-2018年的数据，采用logistic回归分析TC、LDL-C、HDL-C、TG（4种血脂标志物）、血脂异常聚集程度及组合与CMM进展、不同进展模式之间的关联性。采用限制性立方样条曲线探索4种血脂标志物水平与CMM进展之间的剂量-反应关系。结果 在6 522名研究对象中，共有590名（9.05%）在随访过程中发生了CMM进展。控制混杂因素后，4种血脂异常人群均更可能发生CMM进展（高TC：OR=1.33，95%CI：1.03~1.71；高LDL-C：OR=1.35，95%CI：1.05~1.75；低HDL-C：OR=1.45，95%CI：1.19~1.77；高TG：OR=1.50，95%CI：1.20~1.88）。LDL-C水平与CMM进展呈U形剂量-反应关系（非线性P=0.022）。血脂异常的聚集性与CMM进展有关，≥3种血脂异常人群的CMM进展可能性最高（OR=2.02，95%CI：1.33~3.06），各组合中，高TC+高LDL-C+低HDL-C的CMM进展可能性最高（OR=3.54，95%CI：1.40~8.67）。高TC和高LDL-C对无疾病到CMM进展有显著效应，低HDL-C与无疾病到糖尿病、无疾病到CMM、糖尿病患者继发心血管疾病（CVD）、CVD患者继发糖尿病4种进展模式有显著关联，高TG与无疾病到糖尿病、无疾病到CMM、糖尿病患者继发CVD 3种进展模式有显著关联。结论 在中国中老年人群中，4种血脂异常均为CMM进展的独立危险因素，LDL-C水平与CMM进展呈U形曲线。血脂异常的聚集性与CMM进展有关。低HDL-C、高TG与多种心血管代谢性疾病进展模式均显著关联。 |
| 英文摘要: |
| Objective To estimate the longitudinal association between serum lipid biomarkers and the development of cardiometabolic multimorbidity (CMM) in middle-aged and old adults (≥45) in China, while examining effect differences among degree of dyslipidemia aggregation and various dyslipidemia combination patterns. Methods Based on data from the China Health and Retirement Longitudinal Study (2011-2018), logistic regression analysis was used to evaluate the associations of TC, LDL-C, HDL-C, TG (4 forms of dyslipidemias), degree and pattern of dyslipidemia combination with CMM. We also used restricted cubic splines to show the dose-response associations between 4 lipid biomarkers and CMM development. Results Of the 6 522 participants included, 590 (9.05%) developed CMM. After adjusting for covariates, all 4 forms of dyslipidemias were positively associated with CMM development (high TC: OR=1.33, 95%CI: 1.03-1.71; high LDL-C: OR=1.35, 95%CI: 1.05-1.75; low HDL-C: OR=1.45, 95%CI: 1.19-1.77; high TG: OR=1.50, 95%CI: 1.20-1.88). The U-shaped dose-response relationship between LDL-C and CMM development was observed (P for non-linear =0.022). The odds of CMM increased with the increase of dyslipidemias forms, which was highest in those with ≥3 forms of dyslipidemias (OR=2.02, 95%CI: 1.33-3.06). In various dyslipidemia form combinations, the possibility of CMM development was highest in those with high TC, high LDL-C and low HDL-C (OR=3.54, 95%CI: 1.40-8.67). High TC and high LDL-C were significantly associated with CMM development in people without cardiometabolic diseases. Low HDL-C was positively associated with diabetes and CMM development in participants without cardiometabolic diseases, cardiovascular disease (CVD) followed by diabetes, and diabetes followed by CVD. High TG was positively associated with diabetes and CMM in participants without cardiometabolic diseases, and diabetes followed by CVD. Conclusions A total of 4 forms of dyslipidemia were all independently associated with CMM development in middle-aged and old adults in China. The dose-response relationship between LDL-C level and CMM development was U-shaped. The aggregation of 4 forms of dyslipidemia were associated with the development of CMM. Low HDL-C and high TG were significantly associated with multiple patterns of cardiometabolic diseases development. |
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