江苏省南通市35~75岁居民慢性代谢性疾病共病模式分析

Analyses of comorbidity mode of chronic metabolic diseases among residents aged 35-75 years in Nantong City, Jiangsu Province

  • 摘要: 目的 分析江苏省南通市35~75岁居民慢性代谢性疾病共病模式及影响因素,为共病的防控提供理论支持。方法 选择2021—2024年南通市心脑血管疾病综合防控项目中35~75岁常住居民为研究对象。通过聚类分析和关联规则探究慢性代谢性疾病的共病模式,通过logistic回归分析慢性代谢性疾病共病的影响因素。结果 南通市35~75岁居民慢性代谢性疾病共病患病率为47.40%,基于疾病计数的二元共病模式中高血压+血脂异常患病率最高为6.25%,三元共病模式中高血压+血脂异常+肥胖症患病率最高为4.01%。关联规则显示二元、三元共病模式中,肥胖症+高血压和肥胖症+血脂异常+高血压的置信度最高分别为72.70%和74.54%。肾功能不全在聚类分析中单成一簇。logistic回归分析显示,与非共病组人群相比,男性(OR=2.22 , 95%CI:1.69-2.91)、高龄(45~54岁OR=1.38, 95%CI:1.02~1.88;55~64岁OR=1.59, 95%CI:1.14~2.23;65~75岁OR=2.34, 95%CI:1.58~3.47)、低体力运动(OR=1.26, 95%CI:1.10~1.65)是患代谢性疾病共病的影响因素。结论 南通市35~75岁居民慢性代谢性疾病共病模式中,高血压、糖尿病、血脂异常相互影响,肥胖症患者更易患高血压、血脂异常等疾病。针对缺乏体力活动、男性、高龄等人群,应加强慢性代谢性疾病的防控。

     

    Abstract: Objective To analyze the comorbidity patterns of chronic metabolic diseases and their influencing factors among people aged 35-75 years old in Nantong City of Jiangsu Province, and to provide theoretical support for the prevention and control of comorbidities. Methods The permanent residents aged 35-75 years from the Comprehensive Prevention and Control Project of Cardiovascular and Cerebrovascular Diseases in Nantong City from 2021 to 2024 were selected as the research subjects. Clustering analysis and association rule were used to investigate the comorbidity patterns of chronic metabolic diseases, and their influencing factors were identified through logistic regression analyses. Results The prevalence of comorbidity of chronic metabolic diseases among residents aged 35-75 years in Nantong City was 47.40%. Among comorbidity patterns based on disease counts, the prevalence of hypertension+dyslipidemia was highest in binary patterns (6.25%), while that of hypertension+dyslipidemia+obesity was highest in ternary patterns (4.01%). Association rules showed that in both binary and ternary comorbidity patterns, the confidence was highest for obesity+hypertension (72.70%) and obesity+dyslipidemia+hypertension (74.54%), .Renal insufficiency formed an independent cluster in cluster analyses. Logistic regression analyses revealed that, compared with the non-comorbidity group, males (OR=2.22, 95% CI: 1.69–2.91), advanced age (45–54 years, OR=1.38, 95% CI: 1.02–1.88; 55–64 years, OR=1.59, 95% CI: 1.14–2.23; 65–75 years, OR=2.34, 95% CI: 1.58–3.47), and low physical activity (OR=1.26, 95% CI: 1.10–1.65) were influencing factors for metabolic disease comorbidity.. Conclusion In the comorbidity patterns of chronic metabolic diseases among individuals aged 35-75 years in Nantong City, hypertension, diabetes mellitus, and dyslipidemia interact with each other. Individuals with obesity are more prone to diseases such as hypertension and dyslipidemia. Prevention and control of chronic metabolic diseases should be strengthened for males, individuals with low physical activity and advanced age.

     

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