中国全科医学 ›› 2025, Vol. 28 ›› Issue (02): 183-192.DOI: 10.12114/j.issn.1007-9572.2024.0177

• 论著 • 上一篇    下一篇

糖尿病发病时间趋势及其与中国内脏脂肪指数的关系:一项前瞻性队列研究

刘庆平, 柯居中, 宋家慧, 高娇娇, 李智韬, 王小楠, 邱桦, 周弋, 阮晓楠, 吴抗*()   

  1. 200132 上海市浦东新区疾病预防控制中心慢性病防治科 复旦大学浦东预防医学研究院
  • 收稿日期:2024-06-10 修回日期:2024-08-20 出版日期:2025-01-15 发布日期:2024-10-28
  • 通讯作者: 吴抗

  • 作者贡献:

    刘庆平提出研究理念,负责数据整理,统计分析,论文撰写;柯居中、宋家慧负责数据整理,提供统计学设计思路,协助论文修改;高娇娇、李智韬、王小楠负责数据整理;邱桦负责数据整理,统计学设计,分析可行性;周弋、阮晓楠负责思路指导;吴抗负责编辑与修改论文,对文章监督管理和审查。

  • 基金资助:
    浦东新区卫生健康委员会青年科技项目(PW2021B-02); 浦东新区疾病预防控制中心业务研发平台慢性病流行病学(DXZB-2024-01); 上海市加强公共卫生体系建设三年行动计划重点学科(GWVI-11.1-02)

Trend of Onset Time of Diabetes Mellitus and Its Correlation with Chinese Visceral Adiposity Index: a Prospective Cohort Study

LIU Qingping, KE Juzhong, SONG Jiahui, GAO Jiaojiao, LI Zhitao, WANG Xiaonan, QIU Hua, ZHOU Yi, RUAN Xiaonan, WU Kang*()   

  1. Department of Chronic Disease, Pudong New Area Center for Disease Control and Prevention/Fudan University Pudong Institute of Preventive Medicine, Shanghai 200132, China
  • Received:2024-06-10 Revised:2024-08-20 Published:2025-01-15 Online:2024-10-28
  • Contact: WU Kang

摘要: 背景 糖尿病仍是全球重大公共卫生问题,横断面研究发现内脏脂肪与糖尿病患病密切相关,但糖尿病发病时间趋势及其与中国内脏脂肪指数(CVAI)关系的前瞻性队列研究较少。 目的 通过前瞻性队列研究分析上海市浦东新区居民糖尿病发病时间趋势及其与CVAI的关系,为其科学防治提供依据。 方法 本研究为前瞻性队列研究。选取2013年1—7月参与浦东新区慢性病危险因素监测项目的12个乡镇街道的35个村、居委的居民5 236人为研究队列。收集其基线资料,内容包括CVAI、内脏脂肪指数(VAI)、BMI、腰围(WC)、腰臀比(WHR)、腰高比(WHtR)、身体形态指数(ABSI)和身体肥胖指数(BAI),分别于2016年和2019年进行追踪随访;截至随访结束(2019年10月),通过问卷调查、实验室检查、医疗系统就诊信息和生命统计信息系统判断该研究队列糖尿病新发情况。依据基线CVAI、VAI、BMI、WC、WHR、WHtR、ABSI、BAI四分位数将纳入人群分别分为第Q1~Q4四分位数:CVAI各组人数依次为1 306、1 307、1 307、1 307人;VAI各组人数依次为1 300、1 316、1 306、1 306例;BMI各组人数依次为1 305、1 302、1 312、1 311人;WC各组人数依次为1 302、1 273、1 287、1 367人;WHR各组人数依次为1 180、1 203、1 332、1 514人;WHtR各组人数依次为1 199、1 393、1 400、1 237人;ABSI各组人数依次为1 316、1 302、1 302、1 308人;BAI各组人数依次为1 310、1 304、1 308、1 307人。采用多因素Cox回归分析CVAI和其他肥胖指标与糖尿病发病的关系;采用受试者工作特征曲线(ROC曲线)比较CVAI与其他肥胖指标的预测作用。 结果 浦东新区居民2013—2016年糖尿病发病密度为33.55/1 000人年,2017—2019年糖尿病发病密度为23.25/1 000人年,随着年龄的增长,糖尿病总发病密度呈现出升高趋势(2013—2016年:χ2=28.503,P趋势<0.001;2017—2019年:χ2=25.600,P趋势<0.001)。截至2016年,基线CVAI四分位数越高,糖尿病累积发病率(CVAI:χ2=131.865,P趋势<0.001)和发病密度(CVAI:χ2=100.105,P趋势<0.001)均越高。调整相关混杂因素后的多因素Cox回归分析结果显示,与CVAI处于Q1相比,CVAI处于Q4的男性糖尿病的发病风险增加79.4%(HR=1.794,95%CI=1.044~3.083,P<0.05),女性糖尿病的发病风险增加371.2%(HR=4.712,95%CI=2.601~8.538,P<0.05)。ROC曲线结果显示,在预测男性糖尿病发病情况中,CVAI对男性糖尿病预测的ROC曲线下面积(AUC)为0.600(95%CI=0.561~0.640),识别男性糖尿病的约登指数为0.181,截断值为104.118;Delong检验结果显示,CVAI对女性糖尿病预测的准确性最高(AUC=0.699),且在识别女性糖尿病时有最大的约登指数值0.317,最佳截断值为104.609。 结论 2013—2019年上海市浦东新区居民糖尿病发病密度随年龄的增长呈升高趋势;且相较于其他肥胖指标,CVAI可作为预测糖尿病发病风险的指标。

关键词: 糖尿病, 中国内脏脂肪指数, 浦东新区, 前瞻性队列研究, 影响因素分析

Abstract:

Background

Diabetes mellitus is a global public health issue. Cross sectional studies have found that visceral fat is closely related to the prevalence of diabetes mellites, while prospective cohort studies on the trend of onset time of diabetes mellitus and its correlation with Chinese visceral adiposity index (CVAI) are scant.

Objective

To analyze the trend of onset time of diabetes mellitus and its correlation with CVAI in Pudong New Area, Shanghai, residents by the prospective cohort study, thus providing evidence for the scientific prevention and treatment of diabetes mellitus.

Methods

This was a prospective cohort study involving 5 236 residents from 12 townships and 35 village committees who participated in the chronic disease risk factor monitoring project in Pudong New Area, from January to July, 2013. Baseline data were collected, including CVAI, visceral adiposity index (VAI), body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), a body shape index (ABSI), and body adiposity index (BAI). Follow-up was conducted in 2016 and 2019. By the end of follow-up in October 2019, the incidence of new onset of diabetes mellitus in this cohort was calculated through questionnaire survey, laboratory testing, medical system visit information and vital statistics information system. According to the baseline quartile, the CVAI, VAI, BMI, WC, WHR, WHtR, ABSI, and BAI of the included population were divided into Q1 to Q4 quartiles. The number of cases in CVAI Q1-Q4 groups was 1 306, 1 307, 1 307, and 1 307, respectively. The number of cases in VAI Q1-Q4 groups was 1 300, 1 316, 1 306, and 1 306, respectively. The number of cases in BMI Q1-Q4 groups was 1 305, 1 302, 1 312, and 1 311, respectively. The number of cases in WC Q1-Q4 groups was 1 302, 1 273, 1 287, and 1 367, respectively. The number of cases in WHR Q1-Q4 groups was 1 180, 1 203, 1 332, and 1 514, respectively. The number of cases in WHtR Q1-Q4 groups was 1 199, 1 393, 1 400, and 1 237, respectively. The number of cases in ABSI Q1-Q4 groups was 1 316, 1 302, 1 302, and 1 308 respectively. The number of cases in BAI Q1-Q4 groups was 1 310, 1 304, 1 308, and 1 307, respectively. The multivariable Cox regression analysis was used to analyze the correlation of CVAI and other obesity indicators with the onset of diabetes mellitus. The predictive potential of CVAI and other obesity indicators in diabetes mellitus was assessed using receiver operator characteristic (ROC) curves.

Results

The incidence density of diabetes mellitus in Pudong New Area was 33.55/1 000 person-years from 2013 to 2016, and 23.25/ 1 000 person-years from 2017 to 2019. With aging, the total incidence density of diabetes mellitus showed an increasing trend (2013-2016: χ2=28.503, Ptrend<0.001; 2017-2019: χ2=25.600, Ptrend<0.001). By 2016, the baseline CVAI quartile was positively correlated with the cumulative incidence of diabetes mellitus (CVAI: χ2=131.865, Ptrend<0.001) and the incidence density (CVAI: χ2=100.105, Ptrend<0.001). Mutivariable Cox regression analysis after adjusting for relevant confounders showed that compared with CVAI in Q1, the risk of diabetes mellitus in men with CVAI in Q4 increased by 79.4% (HR=1.794, 95%CI=1.044-3.083, P<0.05). Women had a 371.2% increased risk of diabetes mellitus (HR=4.712, 95%CI=2.601-8.538, P<0.05). ROC curve results showed that in predicting the incidence of male diabetes, the area under the ROC curve (AUC) of CVAI for male diabetes was 0.600 (95%CI=0.561-0.640), with the Youden index of 0.181, and the cutoff value of 104.118. Delong test showed that CVAI had the highest accuracy in predicting female diabetes mellitus (AUC=0.699), with the Youden index of 0.317, and the optimal cutoff value of 104.609.

Conclusion

From 2013 to 2019, the incidence density of diabetes mellitus increased with the increased age in Pudong New Area, Shanghai. Compared with other obesity indicators, CVAI can be used as an indicator to predict the risk of diabetes mellitus.

Key words: Diabetes mellitus, Chinese visceral adiposity index, Pudong New Area, Prospective cohort study, Root cause analysis

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