深圳市居民外周动脉疾病患病现况及与肥胖状态关系研究

The prevalence of peripheral arterial disease and its relationship with obesity status among residents in Shenzhen City

目的 对深圳市居民外周动脉疾病(peripheral arterial disease,PAD)患病现况进行分析,并探索其与不同肥胖状态的关系,为了解PAD在我国的患病情况提供数据支持,为制定防控政策进而预防PAD提供依据。方法 2021年4月至2021年12月,采用多阶段分层随机抽样方法,在深圳市10个区抽取54个社区居委会作为调查点,选取年龄≥18岁的常住居民作为研究对象,通过问卷调查、体格检查和实验室检查的方法进行数据收集。采用R软件包拟合广义可加模型并进行作图,采用logistic回归模型分析各肥胖状态分组和PAD的关联。结果 6 230名研究对象中PAD患病率为6.21%,PAD患病率随年龄增长而增加,18~<25岁年龄组PAD患病率最低(4.67%),85岁及以上年龄组PAD患病率最高(33.33%)。此外,随着体质量指数(body mass index, BMI)或腰围的增加,PAD的患病率也增加。多因素logistic回归模型分析显示,按BMI值进行分类的全身性肥胖(overall obesity, OO)和以腰围进行分类的中心型肥胖(central obesity,CO)均可能增加PAD风险(OO统计值OR=2.63,95%CI:1.97~3.50;CO统计值OR=2.32,95%CI:1.79~2.99);将BMI和腰围结合进行分类时,与既非OO也非CO的人相比,既为OO又为CO的人患PAD的风险显著升高(OR=2.61,95%CI:1.99~3.44)。结论 深圳成年人中PAD发病情况不容乐观,老年人需要额外关注。无论是基于BMI值的OO还是基于腰围的CO,均为PAD独立危险因素,联合使用BMI和腰围分组有助于更好地对PAD高危人群进行分级分组管理。

Objective To analyze the prevalence of peripheral arterial disease(PAD)among residents in Shenzhen and explore its relationship with different obesity statuses,to provide data support for understanding the prevalence of PAD in China and a basis for formulating prevention and control policies to prevent PAD.Methods From April 2021 to December 2021,a multi-stage stratified random sampling method was used to select permanent residents aged 18 years or older from 54 community neighborhood committees in Shenzhen as the study population.Data were collected using questionnaires,physical examinations,and laboratory tests.A generalized additive model was fitted and plotted using the R package,and logistic regression models were used to analyze the association between different obesity status groups and PAD.Results Among the 6230 study subjects,the prevalence of PAD in the study population was 6.21%,and the prevalence of PAD increased with age,with the lowest rate of 4.67%in the 18-<25 age group and the highest rate of 33.33%in the≥85 age group.In addition,the prevalence of PAD increased with increasing body mass index(BMI)or waist circumference.Analysis of multifactorial logistic regression models showed that both overall obesity(OO)classified by BMI and central obesity(CO)classified by waist circumference may increase the risk of PAD(OO statistic value OR=2.63,95%CI:1.97-3.50;CO statistic value OR=2.32,95%CI:1.79-2.99).When combining BMI and waist circumference classification,compared to those who were neither OO nor CO,individuals who were both OO and CO had a significantly higher risk of PAD(OR=2.61,95%CI:1.99-3.44).Conclusions The prevalence of PAD among adults in Shenzhen is not optimistic,and the elderly need additional attention.Both OO based on BMI and CO based on waist circumference are independent risk factors for PAD.The joint use of BMI and waist circumference grouping helps to better classify and manage people at risk of PAD.