中国全科医学 ›› 2026, Vol. 29 ›› Issue (22): 3138-3145.DOI: 10.12114/j.issn.1007-9572.2025.0442

• 论著 • 上一篇    下一篇

脂质累积指数与成年人代谢综合征发病关系的前瞻性队列研究

张骥, 李凌, 周婕, 吴延莉, 吉维, 刘涛*()   

  1. 550004 贵州省贵阳市,贵州省疾病预防控制中心慢性病防治研究所监测科
  • 收稿日期:2025-10-10 修回日期:2026-04-10 出版日期:2026-08-05 发布日期:2026-07-08
  • 通讯作者: 刘涛

  • 作者贡献:

    张骥提出主要研究目标,负责数据统计、文章构思和撰写;李凌、周婕、吴延莉负责数据收集;周婕、吴延莉协助整理数据和统计学处理;吉维负责修订论文;刘涛负责文章的质量控制与审查,对论文进行指导并整体负责。

  • 基金资助:
    贵州省科技计划项目(黔科合支撑〔2018〕2819); 贵州省卫生健康委省级重点建设学科项目; 贵州省卫生健康委培育在西南地区有影响力的重点优势学科项目

A Prospective Cohort Study on Relationship between Lipid Accumulation Product and Incidence of Metabolic Syndrome in Adults

ZHANG Ji, LI Ling, ZHOU Jie, WU Yanli, JI Wei, LIU Tao*()   

  1. Department of Chronic Disease Monitoring, Institute of Chronic Disease Prevention and Control, Guizhou Center for Disease Control and Prevention, Guiyang 550004, China
  • Received:2025-10-10 Revised:2026-04-10 Published:2026-08-05 Online:2026-07-08
  • Contact: LIU Tao

摘要: 背景 代谢综合征(MetS)严重影响机体健康,脂质蓄积指数(LAP)能反映人体内脏脂肪的蓄积程度。既往关于LAP与MetS关系的研究多为横断面研究,队列研究证据较少,LAP的预测能力在各研究中存在差异,其预测MetS发生的价值需进一步探讨。 目的 分析LAP长期暴露与MetS发病风险的关系,探讨该指标对MetS的预测效果,为MetS的早期预防提供依据。 方法 本研究使用贵州省自然人群队列研究数据。该队列于2010年11月—2012年12月建立,并于2016年4月—2020年10月对基线研究对象完成一次随访。根据基线LAP水平将研究对象分为4组:Q1组(LAP<8.52,n=1 003),Q2组(8.52≤LAP<15.44,n=1 001),Q3组(15.44≤LAP<27.85,n=1 006),Q4组(LAP≥27.85,n=1 003)。使用Cox比例风险回归模型分析总人群和不同性别人群中LAP与MetS的关系,计算HR及95%CI,采用限制性立方样条分析LAP与MetS发生的剂量反应关系,绘制LAP预测MetS的受试者工作特征(ROC)曲线,评估该指标的预测效果。 结果 共纳入4 013例研究对象,其中男1 803例(44.93%),女2 210例(55.07%),基线平均年龄为(43.7±14.6)岁,平均BMI为(22.45±2.84)kg/m2,中位随访时间为6.54年,随访期间889例发生MetS。总人群、男性和女性的MetS发生率分别为31.62/千人年、33.36/千人年和30.19/千人年。Cox比例风险回归模型分析显示:在调整相关混杂因素后,随着LAP增加,MetS发病风险呈现上升趋势(P趋势<0.05)。在总人群中,与Q1组比较,Q2组(aHR=1.26,95%CI=1.02~1.57)、Q3组(aHR=1.35,95%CI=1.08~1.68)、Q4组(aHR=1.55,95%CI=1.24~1.94)MetS发病风险均逐渐升高(P<0.05)。在男性人群中,与Q1组比较,Q2组(aHR=1.45,95%CI=1.09~1.93)、Q3组(aHR=1.52,95%CI=1.12~2.05)、Q4组(aHR=1.56,95%CI=1.13~2.10)均增加了MetS的发病风险(P<0.05)。在女性人群中,与Q1组比较,仅Q4组(aHR=1.44,95%CI=1.03~2.01)增加了MetS的发病风险(P<0.05)。限制性立方样条结果表明,在总人群(P总趋势<0.05,P非线性=0.069)和男性人群(P总趋势<0.05,P非线性=0.255)中LAP与MetS风险呈线性剂量反应关系,女性人群(P总趋势<0.05,P非线性=0.038)中LAP与MetS发病风险呈非线性剂量反应关系。绘制LAP预测MetS发病风险的时间依赖性ROC曲线,结果显示LAP预测连续暴露7、8、9年后,总人群发生MetS的AUC分别为0.56、0.56、0.57,男性发生MetS的AUC分别为0.55、0.55、0.59,女性发生MetS的AUC分别为0.57、0.58、0.57。 结论 LAP水平升高会增加全人群及不同性别人群MetS的发病风险,但其对未来发生MetS的预测效能较低,并非理想的预测指标,应进一步探索更具预测价值的指标。

关键词: 代谢综合征, 脂质蓄积指数, 队列研究, 发病率, 预测

Abstract:

Background

Metabolic Syndrome (MetS) exerts a significant adverse impact on human health, while the Lipid Accumulation Product (LAP) is capable of reflecting the degree of visceral fat accumulation in the human body. Previous studies investigating the relationship between LAP and MetS have mostly been cross-sectional studies, with a lack of evidence from cohort studies. Additionally, the predictive ability of LAP varies across different studies, and its value in predicting the future incidence of MetS requires further exploration.

Objective

To analyze the relationship between long-term exposure to the LAP and the risk of developing MetS, and to explore the predictive performance of this index for MetS, thereby providing evidence for the early prevention of MetS.

Methods

This study utilized data from the Guizhou Natural Population Cohort Study. The cohort was established between November 2010 and December 2012, and a follow-up survey was conducted on the baseline participants from April 2016 to October 2020. Participants were divided into 4 groups (Q1 to Q4) based on their baseline LAP levels: Q1 (LAP<8.52, n=1 003), Q2 (8.52≤LAP<15.44, n=1 001), Q3 (15.44≤LAP<27.85, n=1 006), and Q4 (LAP≥ 27.85, n=1 003). Cox proportional hazards models were used to analyze the relationship between LAP and MetS in the total population and in subgroups stratified by sex. Hazard ratios (HR) and their corresponding 95% confidence intervals (95%CI) were calculated. Restricted cubic splines were applied to evaluate the dose-response relationship between LAP and the incidence of MetS. Additionally, time-dependent receiver operating characteristic (ROC) curves for LAP in predicting MetS were plotted to assess the predictive performance of this index.

Results

A total of 4 013 study subjects were enrolled, including 1 803 males (44.93%) and 2 210 females (55.07%). The baseline mean age was (43.7±14.6) years, with a mean BMI of (22.45±2.84) kg/m2. The median follow-up duration was 6.54 years, during which 889 cases of MetS were observed. The MetS incidence rates in the overall population, males, and females were 31.62 per 1 000 person-years, 33.36 per 1 000 person-years, and 30.19 per 1 000 person-years, respectively. Cox proportional hazards regression analysis showed that after adjusting for relevant confounding factors, the risk of MetS increased with the elevation of the LAP (P for trend<0.05). In the total population, compared with the Q1 group, the adjusted hazard ratios (aHRs) or MetS risk were gradually elevated in the Q2 (aHR=1.26, 95%CI=1.02-1.57), Q3 (aHR=1.35, 95%CI=1.08-1.68), and Q4 (aHR=1.55, 95%CI=1.24-1.94) (P<0.05). In the male, compared with the Q1 group, the Q2 (aHR=1.45, 95%CI=1.09-1.93), Q3 (aHR=1.52, 95%CI=1.12-2.05), Q4 (aHR=1.56, 95%CI=1.13-2.10) all exhibited an increased risk of MetS (P<0.05). In the female, however, a significant increase in MetS risk was only observed in the Q4 (aHR=1.44, 95%CI=1.03-2.01) relative to the Q1 group (P<0.05). Result s from restricted cubic splines indicated a linear dose-response relationship between LAP and MetS risk in the total population (Poverall<0.05, Pnonlinear=0.069) and the male subgroup (Poverall<0.05, Pnonlinear=0.255), while a non-linear dose-response relationship was observed in the female subgroup (Poverall<0.05, Pnonlinear=0.038). The results of time-dependent ROC curves showed that for the prediction of MetS after 7, 8, and 9 years of LAP exposure, the AUC values in the total population were 0.56, 0.56, and 0.57, respectively, in males, the AUC values were 0.55, 0.55, and 0.59, respectively, and in females, the AUC values were 0.57, 0.58, and 0.57, respectively.

Conclusion

Elevated LAP levels increase the risk of MetS in the general population and across different sex groups. However, its predictive efficacy for future MetS development is limited, making it an suboptimal prognostic marker. Thus, more indicators with higher predictive value should be explored.

Key words: Metabolic syndrome, Lipid accumulation product, Cohort studies, Incidence, Forecasting