青岛某社区老年人肥胖代谢亚型分布构成比及影响因素分析

Analysis of the Composition Ratio and Influencing Factors of Obesity Metabolic Subtypes in the Elderly in a Community in Qingdao

摘要: 背景和目的：肥胖会显著增加高血压、糖尿病、心脑血管疾病等患病风险，增加全因死亡风险。不同肥胖代谢亚型所伴有的代谢性疾病指标改变及发生各类疾病的风险不同。体重正常代谢异常(MONW)人群体重指数(BMI)在正常范围内，但有多重代谢性疾病风险，代谢正常性肥胖(MHO)人群总体体脂水平属于肥胖，但其发生心血管及代谢病的风险却较低，因此针对不同亚型进行相应干预具有一定的临床意义。本研究拟通过探讨青岛某社区老年人群中不同肥胖代谢亚型的流行病学分布特征及其影响因素，为疾病的早期识别和干预提供科学依据。方法：2021年06月至12月，以青岛某社区60岁及以上常住老年人为研究对象开展现场调查，通过问卷调查、体格检查、实验室生化分析等收集相关资料。根据体重指数(BMI)和代谢指标如甘油三酯(TG)、高密度脂蛋白(HDL-C)、血压、空腹血糖(FPG)等进行肥胖代谢亚型的分类，分为体重正常代谢正常(MHNW)、体重正常代谢异常(MONW)、代谢正常性肥胖(MHO)、代谢异常性肥胖(MAO)等四组，采用logistic回归分析不同肥胖代谢亚型的影响因素。结果：共纳入10,208例(69.04 ± 6.531岁)，其中男性4145例(40.6%)，女性6063例(59.3%)；MHNW组2965例(29.05%)，MONW组4552例(44.59%)，MHO组639例(6.26%)，MAO组2052例(20.10%)。MHO患病率随年龄增长降低；总人群和女性的MONW患病率随年龄增长升高，男性MONW患病率在70~79岁组达峰，即48.4%。Logistic回归结果表明：相较于MHNW组，MONW组与年龄、性别、吸烟、经常饮酒、适度或剧烈的锻炼相关；MHO组与年龄、性别、吸烟相关。结论：青岛地区老年人群MONW和MHO两种肥胖代谢亚型患病率较高，且具有不同的影响因素。针对该两种亚型制定不同的干预措施，对于老年肥胖高危人群的疾病早期干预、治疗有着重要意义，同时也为卫生决策部门制定老年肥胖的防治策略提供循证科学依据。

Abstract: Background and Objective: Obesity can significantly increase the risk of hypertension, diabetes, cardiovascular and cerebrovascular diseases, and increase the risk of all-cause death. The changes of metabolic disease indexes and the risk of various diseases associated with different subtypes of obesity are different. The body mass index (BMI) of people with metabolically obese normal weight (MONW) is within the normal range, but there is a risk of multiple metabolic diseases. The total body fat level of people with metabolically healthy overweight (MHO) is obese, but the risk of cardi-ovascular and metabolic diseases is low. Therefore, corresponding intervention for different sub-types has certain clinical significance. This study aims to explore the epidemiological distribution characteristics and influencing factors of different obesity metabolic subtypes in an elderly popula-tion in a community in Qingdao, and provide scientific basis for early identification and intervention of the disease. Methods: From June to December 2021, on-site survey was carried out on the elderly aged 60 and above in a community in Qingdao, and relevant data were collected through question-naire surveys, physical examinations, laboratory biochemical analysis, etc. According to body mass index (BMI) and metabolic index triglycerides (TG), high-density lipoprotein (HDL-C), blood pres-sure, fasting blood glucose (FPG), etc., obesity metabolism subtypes were classified into four classi-fication groups: Metabolically healthy and normal weight (MHNW), Metabolically obese normal weight (MONW), Metabolically healthy overweight (MHO), and Metabolically abnormal overweight (MAO). Based on this, the prevalence of different obesity metabolic subtypes was analyzed, and lo-gistic regression was used to analyze the influencing factors of different obesity metabolic subtypes. Results: A total of 10,208 elderly people (69.04 ± 6.531 years old) were included, including 4145 males (40.6%) and 6063 females (59.3%). There were 2965 cases (29.05%) in the MHNW group, 4552 cases (44.59%) in the MONW group, 639 cases (6.26%) in the MHO group, and 2052 cases (20.10%) in the MAO group. The prevalence of MHO decreased with age. The prevalence of MONW increased with age in both the general population and women. The prevalence of MONW in men peaked in the 70~79 years old group (48.4%). Logistic regression analysis showed that compared with MHNW group, MONW group was associated with age, gender, smoking, regular drinking, mod-erate or vigorous exercise; MHO was associated with age, gender and smoking. Conclusion: The prevalence of MONW and MHO was high in the elderly population in Qingdao and had different in-fluencing factors. The development of different intervention measures for the two subtypes is of great significance for the early intervention and treatment of obesity in the high-risk elderly popu-lation, and also provides evidence-based scientific basis for health policy makers to formulate pre-vention and treatment strategies for obesity in the elderly.