Article(id=1240950903973401370, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202311395, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1700496000000, receivedDateStr=2023-11-21, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773795351259, onlineDateStr=2026-03-18, pubDate=1712678400000, pubDateStr=2024-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773795351259, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773795351259, creator=13701087609, updateTime=1773795351259, updator=13701087609, issue=Issue{id=1240950898113966774, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='7', pageStart='1153', pageEnd='1344', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773795349862, creator=13701087609, updateTime=1773795519367, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240951609136567133, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240951609136567134, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1277, endPage=1283, ext={EN=ArticleExt(id=1240950904300557084, articleId=1240950903973401370, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the relationship between health-related behaviors and chronic comorbidities of the elderly living alone in China, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To understand the current situation and characteristics of chronic disease comorbidities among the elderly living alone in China, to analyze their comorbidity patterns, and to explore the relationship between health-related behaviors and chronic comorbidity in the elderly living alone, so as to provide basis for co-prevention and co-management of multiple diseases in the elderly.

Methods

Based on the data of the 2018 Chinese longitudinal healthy longevity survey (CLHLS), the network map was used to identify the common binary co-disease patterns of chronic diseases in the elderly living alone, and the Gephi software was used to visualize the chronic disease co-disease network of the elderly. Using Apriorism algorithm, the association rules were used to analyze the correlation between health-related behaviors and co-diseases of the elderly living alone, and multi-factor Logistic regression model was used to analyze the correlation between chronic diseases and health-related behaviors of the elderly living alone.

Results

A total of 1 905 elderly people living alone over 65 years were included, of whom 766 suffered from two or more chronic diseases, and the co-morbidity of chronic diseases was 40.2%. A total of 45 meaningful binary co-disease patterns with strong links were identified through network map analysis, of which 10 were related to hypertension and 7 were related to heart disease. The strong association rules among the association rules of health-related behaviors and co-diseases of the elderly living alone were poor sleep quality, no physical activity, no exercise, and no outdoor activity. The multivariate Logistic regression model showed that the elderly living alone with smoking (OR=1.791, 95%CI: 1.205-2.664) and alcohol consumption (OR=1.597, 95%CI: 1.084-2.353) had an increased risk of chronic co-disease compared with those without chronic diseases. Elderly people living alone with exercise (OR=0.132, 95%CI: 0.100-0.175), outdoor activities (OR=0.047,95%CI: 0.035-0.063), good sleep quality (OR=0.469, 95%CI: 0.319-0.688), and adequate sleep (OR=0.648, 95%CI: 0.484-0.867) had a lower risk of chronic comorbidity.

Conclusion

The comorbidity pattern of the elderly living alone in China is complex and related to health-related behaviors. The risk of comorbidity in the elderly can be reduced by improving health-related behaviors, such as increasing exercise and outdoor activities and adjusting sleep duration and sleep quality.

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目的

了解我国独居老年人慢性病共病现状和特征,分析其共病模式,探索健康相关行为与独居老年人慢性病共病的关联,旨在为老年人多病共防和共管提供依据。

方法

采用2018年中国老年健康影响因素跟踪调查(Chinese longitudinal healthy longevity survey,CLHLS)数据,使用网络图识别独居老年人慢性病共病中常见的二元共病模式,并运用Gephi软件对老年人慢性病共病网络进行可视化;运用Apriori算法,通过关联规则分析健康相关行为与独居老年人共病情况的关联性,使用多因素logistic回归模型分析独居老年人慢性病共病与健康相关行为的关联大小。

结果

共纳入1 905名65岁以上的独居老年人,其中766人患有两种及以上慢性疾病,慢性病共病率为40.2%。通过网络图分析共发现45种有意义的具有中强链接的二元共病模式,其中10种与高血压有关,7种与心脏病有关。独居老年人健康相关行为与共病情况的关联规则中的强关联规则为睡眠质量差、无体力活动、无锻炼、无户外活动;多因素logistic回归模型显示:与无慢性病共病的独居老年人相比,会吸烟(OR=1.791,95%CI:1.205~2.664)与饮酒(OR =1.597,95%CI:1.084~2.353)的独居老年人慢性病共病风险增加;有锻炼(OR=0.132,95%CI:0.100~0.175)、有户外活动(OR=0.047,95%CI:0.035~0.063)、睡眠质量好(OR=0.469,95%CI:0.319~0.688)、睡眠充足(OR=0.648,95%CI:0.484~0.867)健康促进行为的独居老年人慢性病共病风险降低。

结论

我国独居老年人的共病模式复杂,且与健康相关行为存在关联,可通过改善健康相关行为、比如增加锻炼和户外活动以及调整睡眠时长和睡眠质量等针对性干预措施降低老年人的共病风险。

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郑建中,E-mail:
佟岩,E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点,除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=2+cM32m46rIv8LPFNLOLag==, magXml=jTz6J8mz4+D6shuI/G2dfA==, pdfUrl=null, pdf=Z9gk3ypZAR7eOyoPZOORbg==, pdfFileSize=872632, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=zq780WvXVob42IQn/9UZJw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=iKBpBKrfBp99i/iNzIwxhw==, mapNumber=null, authorCompany=null, fund=null, authors=

马文骏(1998—),男,硕士在读,研究方向:老年人慢性病、老年人共病、疾病负担等

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马文骏(1998—),男,硕士在读,研究方向:老年人慢性病、老年人共病、疾病负担等

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马文骏(1998—),男,硕士在读,研究方向:老年人慢性病、老年人共病、疾病负担等

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The impact of leisure activities on Chinese elderly's cognitive function[J]. Journal of Psychological Science, 2017, 40(2): 380-387., articleTitle=The impact of leisure activities on Chinese elderly's cognitive function, refAbstract=null), Reference(id=1240972181308493935, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, doi=null, pmid=null, pmcid=null, year=null, volume=28, issue=4, pageStart=1087, pageEnd=1099, url=null, language=null, rfNumber=[25], rfOrder=40, authorNames=Mai S, Cai J, Zheng W, journalName=Psychol Health Med, refType=null, unstructuredReference=Mai S, Cai J, Zheng W, et al. Path analysis of social engagement, loneliness and cognitive function among Chinese older adults[J]. Psychol Health Med, 28(4): 1087-1099., articleTitle=Path analysis of social engagement, loneliness and cognitive function among Chinese older adults, refAbstract=null)], funds=[Fund(id=1240972175470023644, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, awardId=2020AAC03504, language=CN, fundingSource=宁夏自然科学基金项目(2020AAC03504), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1240972166741676630, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, xref=1., ext=[AuthorCompanyExt(id=1240972166745870936, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, companyId=1240972166741676630, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Social Medicine and Health Management, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001,China), AuthorCompanyExt(id=1240972166754259545, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, companyId=1240972166741676630, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.山西医科大学公共卫生学院社会医学与卫生事业管理教研室,山西 太原 030001)]), AuthorCompany(id=1240972166854922853, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, xref=2., ext=[AuthorCompanyExt(id=1240972166863311462, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, companyId=1240972166854922853, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.石嘴山市疾病预防控制中心,宁夏 石嘴山753000)])], figs=[ArticleFig(id=1240972172458513302, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=EN, label=Figure 1, caption=Heat map of associations with binary co-morbidity patterns in older adults living alone, figureFileSmall=Fz1JzpKMHoAP9eMyP+UbCQ==, figureFileBig=E2pfAehBYCPF4r7B9l5U+A==, tableContent=null), ArticleFig(id=1240972172630479770, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=CN, label=图1, caption=独居老年人二元共病模式关联热图, figureFileSmall=Fz1JzpKMHoAP9eMyP+UbCQ==, figureFileBig=E2pfAehBYCPF4r7B9l5U+A==, tableContent=null), ArticleFig(id=1240972172764697507, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=EN, label=Table 1, caption=

Variable assignments

, figureFileSmall=null, figureFileBig=null, tableContent=
变量赋值
性别男=1,女=2
年龄(岁)65~74=1,75~84=2,≥85=3
户籍城镇=1,乡村=2
吸烟有抽烟史=1,无抽烟史=2
饮酒饮酒史=1,无饮酒史=2
睡眠质量睡眠质量好=1,睡眠质量差=2
睡眠时长(h/d)睡眠时间充足≥7=1,睡眠时间不足<7=2
锻炼有锻炼=1,无锻炼=2
体力劳动有体力劳动史=1,无体力劳动史=2
户外社交活动有户外社交活动=1,无户外社交活动=2
慢性病共病有共病=1,无共病=2
), ArticleFig(id=1240972172903109547, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=CN, label=表1, caption=

变量赋值

, figureFileSmall=null, figureFileBig=null, tableContent=
变量赋值
性别男=1,女=2
年龄(岁)65~74=1,75~84=2,≥85=3
户籍城镇=1,乡村=2
吸烟有抽烟史=1,无抽烟史=2
饮酒饮酒史=1,无饮酒史=2
睡眠质量睡眠质量好=1,睡眠质量差=2
睡眠时长(h/d)睡眠时间充足≥7=1,睡眠时间不足<7=2
锻炼有锻炼=1,无锻炼=2
体力劳动有体力劳动史=1,无体力劳动史=2
户外社交活动有户外社交活动=1,无户外社交活动=2
慢性病共病有共病=1,无共病=2
), ArticleFig(id=1240972173012161457, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=EN, label=Table 2, caption=

Co-morbidity rates and distribution of different characteristics of elderly people living alone in China

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分组人数构成比(%)慢性病共病共病率(%)χ2P
年龄(岁)65~7429515.4912716843.0516.738<0.001
75~8464033.6029234845.63
≥8597050.9234762335.77
性别64633.9123840836.844.6120.034
1 25966.0952873141.94
户籍城市44023.1025318757.5071.144<0.001
农村1 46576.9051395235.02
吸烟39220.5817521744.644.0340.049
1 51379.4259192239.06
饮酒33517.5915817747.168.1770.005
1 57082.4160896238.73
锻炼1 17361.5726391022.42401.804<0.001
没有73238.4350322968.72
体力劳动1 41174.0752488737.1421.375<0.001
没有49425.9324225248.99
户外社交活动1 05255.2214390913.59692.327<0.001
没有85344.7862323073.04
睡眠质量1 59383.625831 01036.6052.793<0.001
不好31216.3818312958.65
睡眠时长不足70236.8536633652.1465.773<0.001
充足1 20363.1540080333.25
), ArticleFig(id=1240972173251236791, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=CN, label=表2, caption=

我国不同特征独居老年人的共病率及分布情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分组人数构成比(%)慢性病共病共病率(%)χ2P
年龄(岁)65~7429515.4912716843.0516.738<0.001
75~8464033.6029234845.63
≥8597050.9234762335.77
性别64633.9123840836.844.6120.034
1 25966.0952873141.94
户籍城市44023.1025318757.5071.144<0.001
农村1 46576.9051395235.02
吸烟39220.5817521744.644.0340.049
1 51379.4259192239.06
饮酒33517.5915817747.168.1770.005
1 57082.4160896238.73
锻炼1 17361.5726391022.42401.804<0.001
没有73238.4350322968.72
体力劳动1 41174.0752488737.1421.375<0.001
没有49425.9324225248.99
户外社交活动1 05255.2214390913.59692.327<0.001
没有85344.7862323073.04
睡眠质量1 59383.625831 01036.6052.793<0.001
不好31216.3818312958.65
睡眠时长不足70236.8536633652.1465.773<0.001
充足1 20363.1540080333.25
), ArticleFig(id=1240972173372871616, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=EN, label=Table 3, caption=

Results of the association analysis between health-related behaviors and co-morbidities

, figureFileSmall=null, figureFileBig=null, tableContent=
前项后项支持度(%)置信度(%)提升度
睡眠质量差、无体力活动、无锻炼、无户外社交活动共病1.57596.6672.404
睡眠质量差、喝酒、无锻炼、无户外社交活动共病1.52296.5522.401
睡眠质量差、无体力劳动、睡眠不充足、无锻炼、无户外社交活动共病1.52296.5522.401
睡眠质量差、喝酒、睡眠不充足、无锻炼、无户外社交活动共病1.36596.1542.391
抽烟、喝酒、睡眠不充足、无锻炼共病1.31296.0002.387
), ArticleFig(id=1240972173557421000, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=CN, label=表3, caption=

健康相关行为与共病的关联规则分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
前项后项支持度(%)置信度(%)提升度
睡眠质量差、无体力活动、无锻炼、无户外社交活动共病1.57596.6672.404
睡眠质量差、喝酒、无锻炼、无户外社交活动共病1.52296.5522.401
睡眠质量差、无体力劳动、睡眠不充足、无锻炼、无户外社交活动共病1.52296.5522.401
睡眠质量差、喝酒、睡眠不充足、无锻炼、无户外社交活动共病1.36596.1542.391
抽烟、喝酒、睡眠不充足、无锻炼共病1.31296.0002.387
), ArticleFig(id=1240972173704221644, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=EN, label=Table 4, caption=

Logistic regression analysis of health-related behaviors and chronic disease co-morbidity among elderly living alone in China

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分组β WaldOR值(95%CIP
年龄(岁)65~740.8870.19720.3832.429(1.652~3.570)<0.001
75~840.6850.15419.6561.983(1.465~2.684)<0.001
≥8511111
性别-0.3510.1744.0760.704(0.51~0.990)0.043
11111
户籍城镇1.7390.1794.0765.691(4.008~8.082)<0.001
农村11111
吸烟0.5830.2028.2901.791(1.205~2.664)0.004
11111
饮酒0.4680.1985.6081.597(1.084~2.353)0.018
11111
锻炼-2.0220.143198.5540.132(0.100~0.175)<0.001
没有11111
体力劳动-0.2840.1662.9250.753(0.543~1.042)0.087
没有11111
户外社交活动-3.0550.152406.3440.047(0.035~0.063)<0.001
没有11111
睡眠质量-0.7580.19614.9420.469(0.319~0.688)<0.001
不好11111
睡眠时长充足-0.4340.1498.5250.648(0.484~0.867)0.004
不足11111
), ArticleFig(id=1240972173859410902, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950903973401370, language=CN, label=表4, caption=

我国独居老年人健康相关行为与慢性病共病的logistic回归分析

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变量分组β WaldOR值(95%CIP
年龄(岁)65~740.8870.19720.3832.429(1.652~3.570)<0.001
75~840.6850.15419.6561.983(1.465~2.684)<0.001
≥8511111
性别-0.3510.1744.0760.704(0.51~0.990)0.043
11111
户籍城镇1.7390.1794.0765.691(4.008~8.082)<0.001
农村11111
吸烟0.5830.2028.2901.791(1.205~2.664)0.004
11111
饮酒0.4680.1985.6081.597(1.084~2.353)0.018
11111
锻炼-2.0220.143198.5540.132(0.100~0.175)<0.001
没有11111
体力劳动-0.2840.1662.9250.753(0.543~1.042)0.087
没有11111
户外社交活动-3.0550.152406.3440.047(0.035~0.063)<0.001
没有11111
睡眠质量-0.7580.19614.9420.469(0.319~0.688)<0.001
不好11111
睡眠时长充足-0.4340.1498.5250.648(0.484~0.867)0.004
不足11111
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我国独居老年人健康相关行为与慢性病共病的关联研究
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马文骏 1 , 佟岩 1, 2 , 王妍菲 1 , 曹力晶 1 , 李京鸿 1 , 郑建中 1
现代预防医学 | 健康与社会行为 2024,51(7): 1277-1283
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现代预防医学 | 健康与社会行为 2024, 51(7): 1277-1283
我国独居老年人健康相关行为与慢性病共病的关联研究
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马文骏1, 佟岩1, 2 , 王妍菲1, 曹力晶1, 李京鸿1, 郑建中1
作者信息
  • 1.山西医科大学公共卫生学院社会医学与卫生事业管理教研室,山西 太原 030001
  • 2.石嘴山市疾病预防控制中心,宁夏 石嘴山753000
  • 马文骏(1998—),男,硕士在读,研究方向:老年人慢性病、老年人共病、疾病负担等

通讯作者:

郑建中,E-mail:
佟岩,E-mail:
Study on the relationship between health-related behaviors and chronic comorbidities of the elderly living alone in China
Wen-jun MA1, Yan TONG1, 2 , Yan-fei WANG1, Li-jing CAO1, Jing-hong LI1, Jian-zhong ZHENG1
Affiliations
  • Department of Social Medicine and Health Management, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001,China
出版时间: 2024-04-10 doi: 10.20043/j.cnki.MPM.202311395
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目的

了解我国独居老年人慢性病共病现状和特征,分析其共病模式,探索健康相关行为与独居老年人慢性病共病的关联,旨在为老年人多病共防和共管提供依据。

方法

采用2018年中国老年健康影响因素跟踪调查(Chinese longitudinal healthy longevity survey,CLHLS)数据,使用网络图识别独居老年人慢性病共病中常见的二元共病模式,并运用Gephi软件对老年人慢性病共病网络进行可视化;运用Apriori算法,通过关联规则分析健康相关行为与独居老年人共病情况的关联性,使用多因素logistic回归模型分析独居老年人慢性病共病与健康相关行为的关联大小。

结果

共纳入1 905名65岁以上的独居老年人,其中766人患有两种及以上慢性疾病,慢性病共病率为40.2%。通过网络图分析共发现45种有意义的具有中强链接的二元共病模式,其中10种与高血压有关,7种与心脏病有关。独居老年人健康相关行为与共病情况的关联规则中的强关联规则为睡眠质量差、无体力活动、无锻炼、无户外活动;多因素logistic回归模型显示:与无慢性病共病的独居老年人相比,会吸烟(OR=1.791,95%CI:1.205~2.664)与饮酒(OR =1.597,95%CI:1.084~2.353)的独居老年人慢性病共病风险增加;有锻炼(OR=0.132,95%CI:0.100~0.175)、有户外活动(OR=0.047,95%CI:0.035~0.063)、睡眠质量好(OR=0.469,95%CI:0.319~0.688)、睡眠充足(OR=0.648,95%CI:0.484~0.867)健康促进行为的独居老年人慢性病共病风险降低。

结论

我国独居老年人的共病模式复杂,且与健康相关行为存在关联,可通过改善健康相关行为、比如增加锻炼和户外活动以及调整睡眠时长和睡眠质量等针对性干预措施降低老年人的共病风险。

慢性病共病  /  独居老年人  /  关联规则  /  Logistic回归  /  健康相关行为
Objective

To understand the current situation and characteristics of chronic disease comorbidities among the elderly living alone in China, to analyze their comorbidity patterns, and to explore the relationship between health-related behaviors and chronic comorbidity in the elderly living alone, so as to provide basis for co-prevention and co-management of multiple diseases in the elderly.

Methods

Based on the data of the 2018 Chinese longitudinal healthy longevity survey (CLHLS), the network map was used to identify the common binary co-disease patterns of chronic diseases in the elderly living alone, and the Gephi software was used to visualize the chronic disease co-disease network of the elderly. Using Apriorism algorithm, the association rules were used to analyze the correlation between health-related behaviors and co-diseases of the elderly living alone, and multi-factor Logistic regression model was used to analyze the correlation between chronic diseases and health-related behaviors of the elderly living alone.

Results

A total of 1 905 elderly people living alone over 65 years were included, of whom 766 suffered from two or more chronic diseases, and the co-morbidity of chronic diseases was 40.2%. A total of 45 meaningful binary co-disease patterns with strong links were identified through network map analysis, of which 10 were related to hypertension and 7 were related to heart disease. The strong association rules among the association rules of health-related behaviors and co-diseases of the elderly living alone were poor sleep quality, no physical activity, no exercise, and no outdoor activity. The multivariate Logistic regression model showed that the elderly living alone with smoking (OR=1.791, 95%CI: 1.205-2.664) and alcohol consumption (OR=1.597, 95%CI: 1.084-2.353) had an increased risk of chronic co-disease compared with those without chronic diseases. Elderly people living alone with exercise (OR=0.132, 95%CI: 0.100-0.175), outdoor activities (OR=0.047,95%CI: 0.035-0.063), good sleep quality (OR=0.469, 95%CI: 0.319-0.688), and adequate sleep (OR=0.648, 95%CI: 0.484-0.867) had a lower risk of chronic comorbidity.

Conclusion

The comorbidity pattern of the elderly living alone in China is complex and related to health-related behaviors. The risk of comorbidity in the elderly can be reduced by improving health-related behaviors, such as increasing exercise and outdoor activities and adjusting sleep duration and sleep quality.

Chronic comorbidity  /  Elderly people living alone  /  Association rules  /  Logistic regression  /  Health-related behaviors
马文骏, 佟岩, 王妍菲, 曹力晶, 李京鸿, 郑建中. 我国独居老年人健康相关行为与慢性病共病的关联研究. 现代预防医学, 2024 , 51 (7) : 1277 -1283 . DOI: 10.20043/j.cnki.MPM.202311395
Wen-jun MA, Yan TONG, Yan-fei WANG, Li-jing CAO, Jing-hong LI, Jian-zhong ZHENG. Study on the relationship between health-related behaviors and chronic comorbidities of the elderly living alone in China[J]. Modern Preventive Medicine, 2024 , 51 (7) : 1277 -1283 . DOI: 10.20043/j.cnki.MPM.202311395
自2015年我国进入人口老龄化迅速发展时期后,老年人口数量持续增长,养老负担不断加重[1]。独居老年人是指因丧偶、未婚、离异、分居等未与子女、配偶或亲人一起居住而独自生活的老年人群体[2],他们作为弱势群体面临着严峻的健康问题,且健康问题未受重视。最新的全国人口普查数据显示:2020年我国60岁及以上的独居老人为3 163万人,高龄、女性老年人面临更加严峻的独居形势[3],在目前的人口、社会和经济发展背景下,独居老年人口不断增加的趋势将难以逆转,独居将成为大多数国民步入老年期以后不可避免的一段个体生命历程或家庭生命周期[4],慢性病共病是指同一患者同时患有两种及以上慢性病[5],相关研究表明独居老年人群患慢性病共病的风险大于非独居老年人[6],慢性病共病的发生严重影响独居老年人的健康水平,加重独居老年人的心理、经济负担与全球疾病的负担[7],然而独居老年人作为一个特殊的老年人群体,其健康不容易得到重视。
为了应对日益严峻的老龄化挑战,党在二十大报告中提出要实施“积极应对人口老龄化国家战略,发展养老事业和养老产业,优化孤寡老人服务,推动实现全体老年人享有基本养老服务”的战略,这为新时代我国老龄事业发展和老龄工作开展提供了根本遵循。既往研究发现吸烟、酗酒、体力活动和睡眠情况等健康相关行为与老年人共病存在关联[8-9]。改善健康相关行为有助于预防疾病的发生或者延缓疾病进程,降低死亡率,提高人群的生命质量[10],有利于我国实现健康老龄化。我国独居老年人的健康相关行为与共病的关联研究亟待关注。因此,本研究通过了解我国独居老年人的共病现状及其分布特征,分析独居老年人慢性病共病模式,探讨健康相关行为与独居老年人慢性病共病与的关联,以期推进独居老年人的健康生活方式,减少共病的危险因素,减缓或者避免独居老年人共病的发生,为制定独居老年人健康管理策略提供参考。
本研究数据采用中国老年人健康影响因素跟踪调查(Chinese longitudinal healthy longevity survey,CLHLS)项目,由北京大学健康老龄与发展研究中心提供,调查范围涵盖23个省、市、自治区,并且在调研省份中随机选取了近50%的市或县进行调查,其调查质量较高,具有良好代表性[11]。本研究选择年龄≥65岁的独居老年人(问卷基本情况中“您现在与谁住在一起?”选择为“独居”的)作为研究对象,并根据研究目的对独居老年人基本信息、健康相关行为和共病情况等关键指标回答缺失或无效的样本数据进行剔除,最终纳入分析的有效样本量为1 905人。
中国老年人健康影响因素跟踪调查内容包括基本状况、对现状的评价及性格情绪特征、一般能力、生活方式、日常活动能力、个人背景及家庭结构、生理健康七大部分。本文选用基本状况、生活方式、个人背景及家庭结构三部分。从基本状况中选取性别、年龄、户籍三个变量。从生活方式中选取吸烟、饮酒、睡眠质量(由研究对象通过问卷自评)、睡眠时长(每天睡眠时间的平均值)、锻炼(指有目的的健身活动,如散步,打球,跑步等)、体力劳动(指靠体力进行生产劳动)、户外社交活动(指广场舞、串门等社交类活动)七个变量。从生理健康中选取老年人的慢性病患病情况(包括高血压、糖尿病、心脏病、中风及脑血管疾病、支气管炎、白内障、青光眼、肿瘤、胃肠溃疡、帕金森、关节炎、血脂异常、风湿或类风湿、肾炎和肝炎共15种老年人常见的慢性疾病,患有其中两种及以上慢性病则判定为有共病)。各变量具体赋值见表1
关联规则基于频繁项集特性,采取层次顺序搜索的循环方法来完成频繁项集的挖掘工作,可用来挖掘大量数据中不同疾病之间的关联或者因果关系[12]。本研究运用关联规则探究健康相关行为与慢性病共病的关联。支持度、置信度和提升度是其常用的评价指标。以A代表与健康相关的行为,B代表患有慢性病共病,支持度是指A和B所包括的项集同时出现的概率。支持度越高,说明A和B同时出现的概率越高,关联程度越高。置信度是指A出现的前提下,B出现的条件概率,置信度衡量关联规则的可靠程度,置信度越高,说明出现A后出现B的可能性越大,关联规则更可信。提升度是指在发生A的基础上,出现B的条件概率是出现B的非条件概率的倍数,说明A对B的影响程度。当提升度大于1时,表示正相关[13]
网络图是一种用来表示数据之间关系的图表,通常由节点和边组成,节点代表变量,边代表数据之间的关系,可以显示数据之间的关联、依赖和相似性等信息。本文采用SPSS Modeler18.0中的网络图分析独居老年人慢性病共病中的二元共病模式。以慢性病作为节点,以两个慢性病共患情况作为边,共患率作为边的权重,利用Gephi可视化工具构建独居老年人的无向加权共病网络热图,热图中圆圈面积越大,表明疾病权重越大,疾病出现的次数越多;连线越粗,表明所连接的两种疾病共患率越大,两者共患率越高。
应用Excel 2013对CLHLS数据库的数据进行导出和整合,采用SPSS 27.0进行数据整理和描述性分析,计数资料采用频数和构成比表示,计量资料使用()表示,采用χ2检验比较不同特征老年人的共病率以及健康相关行为的分布情况。采用SPSS Modeler 18.0中Apriori算法,通过关联规则分析老年人慢性病共病和健康相关行为的关联性。采用多因素 logistic回归模型分析独居老年人健康相关行为与慢性病共病之间的关联大小。检验水准α=0.05(双侧)。
本研究中研究对象共1 905人,平均年龄为(85.40±9.78)岁;男性646人(33.91%),女性1 259人(66.09%);城镇户口440人(23.10%),农村户口1 465人(76.90%);392(20.58%)人吸烟;335人(17.59%)饮酒;1 173人(61.57%)锻炼身体;1 411人(74.07%)会进行体力劳动;1 052人(55.22%)会参加户外社交活动;312人(16.38%)自评睡眠质量差;睡眠时长不足(<7 h/d)的有702人(36.85%),睡眠时长充足(≥7 h/d)的有1 203(63.15%)人。比较不同特征老年人慢性病共病分布,结果显示不同年龄、性别、户籍和不同健康相关行为的慢性病共病分布差异具有统计学意义(P<0.05),年龄在75~84岁、女性、城市户籍、吸烟、饮酒、无锻炼、无体力劳动、无户外社交活动、睡眠质量差和睡眠不充足的独居老年人共病率较高。见表2
经过统计整理,纳入的1 905名独居老年人中,有766位患有两种及以上的慢性疾病,共病率为40.2%。其中二元慢性病共病患者共有390位,占所有慢性病共病患者的50.91%,最常见的二元共病模式为“高血压+心脏病”,占16.92%,其次是“高血压+糖尿病”,占11.54%,以及“高血压+中风及脑血管疾病”和“高血压+白内障”,占9.5%。三元及以上慢性病共病患者共有376位,占所有慢性病共病患者的49.09%,最常见的慢性病共病模式为“高血压+心脏病+关节炎”,占15.69%,其次是“高血压+心脏病+糖尿病”,占15.16%。
通过SPSS Modeler中的网络图对独居老年人的慢性病共病进行分析,共识别出45条二元慢性病中强连接,权重排名前五的二元慢病组合分别是“高血压+心脏病、高血压+白内障、高血压+关节炎、高血压+糖尿病和高血压+中风及脑血管疾病”,高血压在所有二元慢病组合中出现的频率最高,使用Gephi软件对关联分析结果进行可视化处理,所有纳入的慢性病可视化图谱见图1
一般根据经验值设置阈值得到适当数量的关联规则,故参考以往研究[14],以最小支持度设为1%,最小置信度为90%,提升度>1作为标准,纳入吸烟、饮酒、睡眠质量、睡眠时长、锻炼、体力劳动、户外社交活动这七个健康相关行为,结果共产生25条关联规则。按照置信度进行排序,结果显示,同时具有睡眠质量差、无体力活动、不锻炼和没有户外社交活动人这四类情况的独居老年人发生慢性病共病的可能性最高,需对此类人群增加关注。七个健康相关行为均在前项的不同组合中出现并且支持度与提升度都>1,说明这七个健康相关行为均与独居老年人共病之间存在关联性,关联规则置信度排名前五项结果见表3
以是否共病(共病=1,非共病=2)为因变量,将独居老年人性别、户籍、年龄以及与独居老年人共病存在相关联的七个健康相关行为作为自变量,构建多因素logistic回归模型。在控制了性别、户籍、年龄等人口学变量后模型结果显示健康相关行为中吸烟、饮酒、锻炼、户外社交活动、睡眠质量和睡眠时长与独居老年人慢性病共病的关联具有统计学意义(P<0.05)。
与不患共病的独居老年人相比,吸烟(OR=1.791,95%CI:1.205~2.664)、饮酒(OR=1.597,95%CI:1.084~ 2.353)更容易患有共病;有锻炼(OR=0.132,95%CI:0.100~0.175)、有户外社交活动(OR=0.047,95%CI:0.035~0.063)、睡眠质量好(OR=0.469,95%CI:0.319~0.688)、睡眠充足(OR=0.648,95%CI:0.484~0.867)的独居老年人慢性病共病风险降低。见表4
本研究应用2018年中国老年健康影响因素跟踪调查数据(CLHLS数据库),对我国65岁以上老年人群体中的弱势群体——独居老年人进行了慢性病共病模式及慢性病共病与健康相关行为的关联研究。本研究结果显示我国65岁以上独居老年人的共病率为40.2%,低于王峻霞等人[8]对中国60岁以上老年人的共病调查结果(44.5%)和徐小兵等人[14]的研究结果(45.92%),高于刘秀秀[15]在绵阳市的研究(13.54%),以及全国第六次卫生服务统计调查(23.8%)[16]。这可能与不同研究中研究对象的年龄、地区、样本量以及纳入共病统计的慢性病的种类和数量不同等有关,但本研究提示我国独居老年人慢性病共病率较高,其慢性病相关问题不容忽视。
既往研究发现“高血压+糖尿病”是老年人群体中最常见的二元共病模式[17],但在本研究中发现“高血压+心脏病”的二元共病模式在独居老年人中更为常见,独居老年人的共病模式大多数与高血压和心脏病有关。因此,在对独居老年人进行慢性病防治时,应需更加注意患者的血压及心脏问题,减少患者与高血压、心脏病相关的危险因素。同时,二元共病关联结果中我们的研究发现:高血压与心脏病、白内障、关节炎都具有较高的权重,提示该类疾病共患率较高,因此在对患有心脏病的独居老年人进行健康管理时,需同时注重这三种慢性疾病的预防,及时采取一些慢性病的健康管理和干预措施,以预防相关慢性病共病的发生。
在健康相关行为与共病关联规则分析的研究结果中,包含睡眠质量差和睡眠不充足这两个因素,且关联置信度较高。近年来,睡眠质量差这一因素在中国老年人中的发生率从2008年的34.87%上升到了2018年的47.67%,且有研究表明睡眠质量差与患有多种慢性病有关联[18]。夏高艳等人[19]的研究发现睡眠质量差和睡眠不充足的社区老年人与慢性病共病罹患风险增加有关。这可能是因为睡眠质量差与老年人身体虚弱有显著关系,长期的睡眠质量差会导致身体的免疫功能降低和内分泌失调等情况,导致身体虚弱,而慢性病与老年人身体虚弱的发生呈正相关,虚弱会导致多种慢性病的产生[20]。其次一项卢森堡的研究中发现睡眠时间短与慢性病的数量显著相关,且睡眠时间的缩短和慢性疾病的数量会随着年龄的增长而增加,在老年人群中这种情况更为普遍[21]。因此正常的睡眠时长和良好的睡眠质量对于预防慢性病共病的发生具有重要意义。我国有关独居老年人的睡眠研究较少,但是独居老年人因为自身的特殊原因,长期处于孤独的状态之中,一项国外的研究发现长期的孤独会导致睡眠质量受损与睡眠障碍[22],因此独居老年人更容易变得睡眠质量差和睡眠时间不充足,睡眠问题对独居老年人健康的影响可能更严重,同时多元logistic回归模型结果也表明相比于睡眠质量差、睡眠时间不足的独居老年人群,睡眠质量好、睡眠时间充足的独居老年人更不易患共病,因此建议在对独居老年人群进行健康指导与管理时,需更关注独居老年人的睡眠问题,可将睡眠情况纳入独居老年人健康监测的一环,能更全面的评估健康情况。
健康相关行为的关联规则结果显示锻炼与慢性病共病之间存在关联,多元logistic回归的结果也表明,相比于不锻炼的独居老年人,参与锻炼的独居老年人患慢性病共病的风险更低。缺少锻炼更容易发生慢性病共病,WHO的一份报告指出锻炼不足会导致患各类慢性病的风险增加20%~30%,是慢性病发病的主要危险因素之一。崔春子等人[23]的研究表明锻炼是高血压共病模式的保护因素之一,因此锻炼对于以高血压为主的共病模式的独居老年人群来说尤为重要。建议对独居老年人提供更多专业、科学的指导,丰富和完善锻炼设施,正确引导独居老年人更多的参与锻炼,从而降低患共病的风险。同时户外社交活动作为一种与健康密切相关的健康相关行为已经被证明能有效减少老年人的认知衰退从而促进老年人的身心健康,减少共病的发生[24],本文研究也表明相比于不参与户外社交活动的独居老年人,参与户外社交活动的独居老年人患慢性病共病的风险更低。独居老人因为自身的特殊情况,缺少家庭支持、他人关心和正确的生活引导而处于孤独的状态,相关研究显示孤独感与社会参与度呈负相关[25],独居老年人可能会由于常年的孤独而更不愿意参与户外社交活动。亟需社会加强对独居老年人的关心与引导,多开展一些适合独居老年人参与的户外社交活动,并引导他们积极参与。吸烟与饮酒一直以来都是危害人群健康的两大不良健康相关行为,在独居老年人群中加强与戒烟戒酒相关的健康教育,通过减少相应的不良行为,从而有效减少慢性病共病的发生。
综上所述,中国独居老年人慢性病共病情况较为复杂,多病共存严重威胁中国独居老年人的身体健康。根据本次研究结果建议相关健康机构以高血压和心脏病等重点疾病为突破口,针对不同特征的独居老年人设计个性化的共病管理方式,同时明确共病模式,结合个体患病情况给予科学的慢病指导,并加强健康检测,实施慢性病综合防控,降低独居老年人的患慢性病共病风险。健康相关行为在独居老年人与共病的关联中扮演了重要的角色,为了减少独居老年人的共病情况,社团组织、社区和基层医疗机构作为提高老年人户外活动和社会参与的重要部门,可积极开展如广场舞和社区食堂之类的活动增加独居老年人群的户外社交活动和锻炼时间,给予独居老年人群更多的社会支持与家庭支持,加强对独居老年人群健康的关注。独居老年人自身也需要戒烟戒酒,适当参与运动与锻炼,养成良好的睡眠作息,并积极参加户外活动,从而有效提高自己的身心健康与生命质量。
  • 宁夏自然科学基金项目(2020AAC03504)
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2024年第51卷第7期
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doi: 10.20043/j.cnki.MPM.202311395
  • 接收时间:2023-11-21
  • 首发时间:2026-03-18
  • 出版时间:2024-04-10
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  • 收稿日期:2023-11-21
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宁夏自然科学基金项目(2020AAC03504)
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    1.山西医科大学公共卫生学院社会医学与卫生事业管理教研室,山西 太原 030001
    2.石嘴山市疾病预防控制中心,宁夏 石嘴山753000

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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