基于健康生态学模型的我国老年人慢性病共病影响因素研究

摘要： 背景 我国人口老龄化问题严重，慢性病共病现象日趋普遍。 目的 以健康生态学模型为基础，系统了解我国老年人发生慢性病共病的影响因素，为我国老年人慢性病共病问题防控提供参考。 方法 于2021年3月，在中国健康与养老追踪调查（CHARLS）的2018年追踪数据库中选取年龄≥60岁的样本（n=10 779），剔除研究涉及变量有缺失的样本后，最终纳入样本7 354例。以是否发生慢性病共病（患≥2种慢性病）为因变量，根据健康生态学模型的5个维度纳入自变量，采用多因素Logistic回归模型分析老年人发生慢性病共病的影响因素。 结果 老年人的慢性病共病发生率为65.16%（4 792/7 354），患2种慢性病者居多〔32.16%（1 541/4 792）〕，其中发生率最高的二元慢性病共病组合为高血压+关节炎或风湿病〔16.42%（253/1 541）〕。多因素Logistic回归分析结果显示：对于老年人的慢性病共病发生风险，女性高于男性〔OR（95%CI）=1.371（1.177，1.596）〕，>70岁者高于60~70岁者〔OR（95%CI）=1.189（1.061，1.333）〕，夜晚睡眠时间为6~8 h者和>8 h者低于<6 h者〔OR（95%CI）分别为0.759（0.678，0.850）、0.686（0.572，0.821）〕，午睡时间为0.5~1.0 h者和>1.0 h者高于<0.5 h者〔OR（95%CI）分别为1.238（1.102，1.391）、1.219（1.604，1.396）〕，对健康感到一般和不太满意者高于非常满意者〔OR（95%CI）分别为1.755（1.537，2.004）、5.890（4.930，7.037）〕，城市户口者高于农村户口者〔OR（95%CI）=1.167（1.036，1.315）〕，居住在中部和西部地区者高于东部地区者〔OR（95%CI）分别为1.311（1.158，1.483）、1.491（1.315，1.692）〕，正在工作者低于曾经工作过者〔OR（95%CI）=0.768（0.680，0.866）〕，人均年收入>5万元者高于<2万元者〔OR（95%CI）=1.413（1.009，1.978）〕。 结论 我国老年人的慢性病共病发生率较高，慢性病共病的影响因素是多层次、多维度的，不同的影响因素之间有着复杂的关系，建议从个体到环境多维度加强对慢性病的干预和管理，提高人群健康水平。

关键词: 慢性病共病, 老年人, 健康生态学模型, 健康社会决定因素, 健康生活方式, 患病率, 影响因素分析

Abstract:

Background

The problem of population aging is serious in China, and chronic diseases comorbidity is becoming more and more common.

Objective

Based on the health ecology model, to systematically understand the main influencing factors of chronic disease comorbidity among the elderly in China, and to provide scientific reference for the prevention and control of chronic disease comorbidity among the elderly in China.

Methods

Based on the follow-up data of China Health and Retirement Longitudinal Study (CHARLS) 2018, a total of 10 779 samples aged ≥60 years were selected in March 2021. After excluding the samples with missing data and unqualified data, a total of 7 354 samples was included in this study. With the occurrence of chronic comorbidities (having ≥2 chronic conditions) as the dependent variable and the inclusion of independent variables according to the 5 dimensions of the health ecology model, a multivariate Logistic regression model was used to analyze the influencing factors of chronic disease comorbidity in the elderly.

Results

Among the elderly≥60 years old in China, the comorbidity rate of chronic diseases was 65.16% (4 792/7 354) , with 32.16% (1 541/4 792) patients suffered from two kinds of chronic diseases, and the diseases with the largest combination of two comorbidities were hypertension with arthritis or rheumatism〔16.42% (253/1 541) 〕. The results of the multivariate Logistic analysis showed that for the risk of comorbidities of chronic diseases in the elderly, females were higher than that in males〔OR (95%CI) =1.371 (1.177, 1.596) 〕, those over 70 years old were higher than those aged 60-70 years old〔OR (95%CI) =1.189 (1.061, 1.333) 〕, those who slept for 6-8 hours or more than 8 hours at night were lower than those who slept for less than 6 hours at night〔OR (95%CI) =0.759 (0.678, 0.850) , OR (95%CI) =0.686 (0.572, 0.821) 〕, those who took nap time of 0.5-1.0 h and over 1.0 h were higher than those of less than 0.5 h 〔OR (95%CI) =1.238 (1.102, 1.391) , OR (95%CI) =1.219 (1.604, 1.396) 〕, those who felt general and less satisfied with their health were higher than those who were very satisfied〔OR (95%CI) =1.755 (1.537, 2.004) , OR (95%CI) =5.890 (4.930, 7.037) 〕, those who registered in urban areas were higher than those in the rural areas〔OR (95%CI) =1.167 (1.036, 1.315) 〕, those living in the central and western regions were higher than those in the eastern region〔OR (95%CI) =1.311 (1.158, 1.483) , OR (95%CI) =1.491 (1.315, 1.692) 〕, those who were working were lower than those who had worked〔OR (95%CI) =0.768 (0.680, 0.866) 〕, and those with annual income > 50 000 per capita were higher than that of less than 20 000 yuan〔OR (95%CI) =1.413 (1.009, 1.978) 〕.

Conclusion

The incidence of chronic diseases comorbidity is higher in the elderly in China. The influencing factors of comorbidity of chronic diseases are multi-level and multi-dimensional. There are complex relationships between different influencing factors, which suggest strengthening multi-dimensional intervention and management of chronic diseases from individual to environment, so as to improve the health level of the population.

Key words: Multiple chronic conditions, Aged, Health ecology model, Social determinants of health, Healthy lifestyle, Prevalence, Root cause analysis

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