陕西省居民慢性病共病模式潜在类别分析

Latent class analysis of multimorbidity patterns of chronic diseases among residents in Shaanxi Province

摘要

目的 探索陕西省居民慢性病患病现状和共病模式,为加强慢性病共病的健康管理提供参考依据。方法 使用西北区域自然人群队列的陕西省数据,选择调查对象自我报告被乡/区级或以上医院医师明确诊断的慢性病共26项作为外显变量进行潜在类别分析识别共病模式。结果 37 273名调查对象纳入分析,其中男性占比37.0%,年龄范围(53.58±9.77)岁。所有研究对象中19.5%患单一慢性病,16.5%患2种及以上慢性病。潜在类别分析将陕西省人群分为5类潜在共病模式:心血管疾病组(5.0%)、消化道疾病组(2.4%)、精神心理类疾病组(0.6%)、慢性呼吸道疾病组(0.5%)和低共病负荷组(91.5%)。不同性别、年龄组间慢性病共病模式存在差异。男性共病模式分别为低共病负荷组(90.3%)、心血管疾病组(5.9%)、多种疾病组(3.1%)、精神心理类疾病组(0.7%)；女性共病模式分别为低共病负荷组(92.0%)、心血管疾病组(4.7%)、多种疾病组(2.3%)、慢性呼吸道疾病组(0.5%)和精神心理疾病组(0.5%)。60岁及以上人群分别为低共病负荷组(72.1%)、心血管疾病组(24.3%)和多种疾病组(3.6%)；60岁以下人群分别为低共病负荷组(85.3%)、心血管疾病组(11.0%)、多种疾病组(3.0%)和精神心理疾病组(0.7%)。结论 陕西省居民慢性病共病模式有明显的分类特征,在不同年龄、性别组内存在差异,但心血管疾病共病为最主要的共病模式,应针对不同类别人群进行差异性干预。

Abstract

Objective To explore the prevalence and multimorbidity patterns of chronic diseases among residents in Shaanxi Province, so as to provide reference for strengthening the health management of multimorbidity. Methods A total of 26 chronic diseases diagnosed by doctors of hospitals at township or district level or above were selected as the explicit variables for latent class analysis to identify the multimorbidity pattern, using the data from Shaanxi Province of The China Northwest Cohort Study. Results A total of 37 273 survey subjects were included in the analysis, among whom 37.0% were male, and the age range was 53.58±9.77 years old. Among all the research subjects, 19.5% had a single chronic disease and 16.5% had two or more chronic diseases. Latent class analysis divided the population in Shaanxi Province into five potential multimorbidity patterns: cardiovascular disease group (5.0%), digestive tract disease group (2.4%), mental and psychological disease group (0.6%), chronic respiratory disease group (0.5%), and low multimorbidity burden group (91.5%). The multimorbidity patterns of chronic diseases differed among different genders and age groups. The multimorbidity patterns of men were respectively the low multimorbidity burden group (90.3%), the cardiovascular disease group (5.9%), the multiple disease group (3.1%), and the mental and psychological disease group (0.7%). The multimorbidity patterns of women were respectively the low multimorbidity burden group (92.0%), the cardiovascular disease group (4.7%), the multiple disease group (2.3%), the chronic respiratory disease group (0.5%), and the mental and psychological disease group (0.5%). People aged 60 and above fell into respectively the low multimorbidity burden group (72.1%), the cardiovascular disease group (24.3%), and the multiple disease group (3.6%). The population under 60 years old was divided into the low multimorbidity burden group (85.30%), the cardiovascular disease group (11.0%), the multiple disease group (3.0%), and the mental and psychological disease group (0.7%). Conclusion The multimorbidity patterns of chronic diseases among residents in Shaanxi Province have obvious classification characteristics, and there are differences among different age and gender groups. However, multimorbidity of cardiovascular diseases is the main multimorbidity pattern, and differential intervention should be carried out for different groups of people.

关键词

慢性病共病 / 潜在类别分析 / 共病模式

Key words

multimorbidity of chronic diseases / latent class analysis / multimorbidity pattern

参考文献

[1] 王峻霞, 丁令智, 简金洋, 等 . 基于CHARLS数据库的中国老年人慢性病共病现状及影响因素分析[J]. 应用预防医学, 2023, 29(3): 151—154, 160.

[2] WANG J X, DING L Z, JIAN J Y, et al. Analysis of current situation and influencing factors of chronic disease comorbidity among the elderly in China based on CHARLS[J]. Journal of Applied Preventive Medicine, 2023, 29(3): 151—154, 160.

[3] KERNICK D, CHEW—GRAHAM C A, O'FLYNN N. Clinical assessment and management of multimorbidity: nice guideline[J]. Br J Gen Pract, 2017, 67(658): 235-236.

[4] 许明璐, 杨萧含, 刘倩楠, 等 . 老年人慢性病共病关联规则分析[J]. 实用临床医药杂志, 2024, 28(13): 103-108.

[5] XU M L, YANG X H, LIU Q N, et al. Analysis in association rules of chronic diseases in the elderly people[J]. J Clin Med Pract, 2024, 28(13): 103-108.

[6] 刘贝贝, 田庆丰, 郭金玲. 我国中老年人群慢性病患病现状及共病模式分析[J]. 医学与社会, 2022, 35(8): 58-61, 66.

[7] LIU B B, TIAN Q F, GUO J L. Analysis of chronic diseases and comorbidities in middle—aged and elderly population in China[J]. Med Soc (Berkeley), 2022, 35(8): 58-61, 66.

[8] 黎艳娜, 王艺桥. 我国老年人慢性病共病现状及模式研究[J]. 中国全科医学, 2021, 24(31): 3955—3962, 3978.

[9] LI Y N, WANG Y Q. Prevalence and patterns of multimorbidity among Chinese elderly people[J]. Chin Gen Pract, 2021, 24(31): 3955—3962, 3978.

[10] 崔春子, 杨土保. 我国中老年人群慢性病共病模式及影响因素探究———基于系统聚类和Apriori算法[J]. 中国卫生统计, 2023, 40(2): 172-177.

[11] CUI C Z, YANG T B. The exploration of the prevalence and the determinants of the chronic disease multimorbidity patterns among Chinese middle—aged and elderly population: based on hierarchical clustering analysis and Apriori algorithm[J]. Chin J Health Stat, 2023, 40(2): 172-177.

[12] 闫妍, 剌媛媛, 贺鹭, 等 . 潜在类别分析在探究60岁以上老年人的多病模式和相关因素的应用[J]. 中国卫生统计, 2022, 39(5): 702-706.

[13] YAN Y, LA Y Y, HE L, et al. Application of latent classes analysis in exploring the multimorbidity and related factors of the elderly over 60 years old[J]. Chin J Health Stat, 2022, 39(5): 702-706.

[14] 刘恒, 马浇, 黄浩, 等 . 陕西成年人慢性病共病现状及其影响因素和共病模式研究[J]. 西安交通大学学报(医学版), 2023, 44(3): 473-480.

[15] LIU H, MA J, HUANG H, et al. Prevalence, associated factors and patterns of multimorbidity of non—communicable diseases among adults in Shaanxi Province[J]. J Xi'an Jiaotong Univ (Med Sci), 2023, 44(3): 473-480.

[16] KIRCHBERGER I, MEISINGER C, HEIER M, et al. Patterns of multimorbidity in the aged population. Results from the KORA—age study[J]. PLoS One, 2012, 7(1): e30556.

[17] WANG D, LI D, MISHRA S R, et al. Association between marital relationship and multimorbidity in middle—aged adults: a longitudinal study across the US, UK, Europe, and China[J]. Maturitas, 2022, 155: 32-39.

[18] 温忠麟, 谢晋艳, 王惠惠. 潜在类别模型的原理、步骤及程序[J]. 华东师范大学学报(教育科学版), 2023, 41(1): 1-15.

[19] WEN Z L, XIE J Y, WANG H H. Principles, procedures and programs of latent class models[J]. J East China Norm Univ (Ed Sci), 2023, 41(1): 1-15.

[20] 曾宪华, 肖琳, 张岩波. 潜在类别分析原理及实例分析[J]. 中国卫生统计, 2013, 30(6): 815-817.

[21] ZENG X H, XIAO L, ZHANG Y B. Principle of latent class analysis and case analysis[J]. Chin J Health Stat, 2013, 30(6): 815-817.

[22] 孙明希, 温启邦, 涂华康, 等 . 4种慢性病共病模式及运动与全因死亡的相关性研究[J]. 中华流行病学杂志, 2022, 43(12): 1952-1958.

[23] SUN M X, WEN Q B, TU H K, et al. Associations between multimorbidity patterns of 4 chronic diseases and physical activity with all—cause mortality[J]. Chin J Epidemiol, 2022, 43(12): 1952-1958.

[24] ZOU S, WANG Z, BHURA M, et al. Prevalence and associated socioeconomic factors of multimorbidity in 10 regions of China: an analysis of 0.5 million adults[J]. J Public Health (Oxf), 2022, 44(1): 36-50.

[25] 倪梓涵, 雒敏. 基于安德森模型的中老年人慢性病共病影响因素研究[J]. 中国卫生事业管理, 2024, 41(3): 339-343.

[26] NI Z H, LUO M. Studying on the influencing factors of chronic disease comorbidity in middle—aged and elderly people based on Anderson impurity model[J]. Chin Health Serv Manag, 2024, 41(3): 339-343.

[27] 马春芳, 汤榕, 杨晓花, 等 . 基于健康社会决定因素的宁夏中老年人慢性病共病的影响因素研究[J]. 中国全科医学, 2024, 27(4): 447-453.

[28] MA C F, TANG R, YANG X H, et al. Influencing factors of multimorbidity among middle—aged and elderly people in Ningxia based on social determinants of health[J]. Chin Gen Pract, 2024, 27(4): 447-453.

[29] WANG S B, D'ARCY C, YU Y Q, et al. Prevalence and patterns of multimorbidity in northeastern China: a cross—sectional study[J]. Public Health, 2015, 129(11): 1539-1546.

[30] 赵叶茂. 四川省老年人慢性病共病模式及其相关因素研究[D]. 成都: 成都医学院, 2022.

[31] ZHAO Y M. Study on chronic disease multimorbidity and its relevant factors among the elderly in Sichuan Province[D]. Chengdu: Chengdu Medical College, 2022.

[32] 程杨杨, 曹志, 侯洁, 等 . 中国中老年人群慢性病现状调查与共病关联分析[J]. 中华疾病控制杂志, 2019, 23(6): 625-629.

[33] CHENG Y Y, CAO Z, HOU J, et al. Investigation and association analysis of multimorbidity in middle—aged and elderly population in China[J]. Chin J Dis Control Prev, 2019, 23(6): 625-629.

[34] TRIOLO F, HARBER—ASCHAN L, BELVEDERI MURRI M, et al. The complex interplay between depression and multimorbidity in late life: risks and pathways[J]. Mech Ageing Dev, 2020, 192: 111383.

[35] READ J R, SHARPE L, MODINI M, et al. Multimorbidity and depression: a systematic review and meta—analysis[J]. J Affect Disord, 2017, 221: 36-46.

[36] 施博文, 熊巨洋. 慢性病共病对中国老年人健康相关生命质量的影响研究[J]. 人口与发展, 2024, 30(1): 120-128.

[37] SHI B W, XIONG J Y. Study on the impact of multiple chronic conditions on health—related quality of life of Chinese elderly[J]. Popul Dev, 2024, 30(1): 120-128.

[38] 潘晔, 刘志辉, 胡倩倩, 等 . 中国老年人慢性病多病共存模式的研究[J]. 中国全科医学, 2023, 26(29): 3608-3615.

[39] PAN Y, LIU Z H, HU Q Q, et al. Patterns of coexistence of multiple chronic conditions among Chinese elderly[J]. Chin Gen Pract, 2023, 26(29): 3608-3615.

[40] 罗纯薇, 陆菊萍, 许学进. 上海市嘉定镇40岁及以上居民慢性阻塞性肺疾病筛查结果及其关联因素分析[J]. 中华全科医师杂志, 2024, 23(10): 1021-1028.

[41] LUO C W, LU J P, XU X J. Analysis on screening results for chronic obstructive pulmonary disease among residents over 40 years in Shanghai Jiading town[J]. Chin J Gen Pract, 2024, 23(10): 1021-1028.

[42] 肖汉, 聂秀红, 陈功, 等 . 湖北省15岁及以上居民慢性呼吸系统疾病患病现状调查[J]. 重庆医学, 2015, 44(22): 3102-3104.

[43] XIAO H, NIE X H, CHEN G, et al. Prevalence and influential factors of chronic respiratory system diseases among residents over 15 years old in Hubei province[J]. Chongqing Med, 2015, 44(22): 3102-3104.

基金资助

国家重点研发计划“精准医学研究”重点专项资助项目(2017YFC0907200)

国家重点研发计划“精准医学研究”重点专项资助项目(2017YFC0907201)

陕西省自然科学基础研究计划项目(2024-JC-YB-1446)