Article(id=1241102740005376168, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202404207, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1712937600000, receivedDateStr=2024-04-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773831551790, onlineDateStr=2026-03-18, pubDate=1721836800000, pubDateStr=2024-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773831551790, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773831551790, creator=13701087609, updateTime=1773831551790, updator=13701087609, issue=Issue{id=1241102730337505325, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='14', pageStart='2497', pageEnd='2688', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773831549486, creator=13701087609, updateTime=1773831697291, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241103350322745680, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241103350322745681, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2535, endPage=2540, ext={EN=ArticleExt(id=1241102740374474941, articleId=1241102740005376168, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=A Study on the quality of life and its influencing factors of urban and rural residents among five cities of Hubei Province, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the quality of life (QOL) and its related factors among residents, and to explore the contribution of each factors to QOL by Shapley method, so as to provide references for health policy making.

Methods

Questionnaire survey was conducted in 5 cities of Hubei Province from July to August 2021 by stratified random sampling to measure the QOL of 1 387 residents according to SF-12 scale, multivariate regression model and Shapley decomposition method were applied to analyze the influencing factors and its contribution to QOL.

Results

The scores of residents’ physical component summary (PCS) and mental component summary (MCS) were 71.04±17.43 and 75.70±12.51 respectively. Age≥60 (β=-6.073), employment status (retirement (β=-12.752), unemployed (β=-7.292)), annual income (50 000-100 000 Yuan (β=3.516), >100 000 Yuan (β=6.169)), no chronic disease history (β=9.202), and no physical exercise (β=-3.182) had significant effects on PCS (P<0.05), whereas married (β=2.106), employment status (retirement (β=-6.788),unemployed (β=-5.174)), personal annual income >100 000 Yuan (β=3.842), without medical insurance (β=-4.455), no chronic disease history (β=3.450) and no physical exercise (β=-2.056) had significant effects on MCS (P<0.05). Shapley decomposition results showed that employment, chronic medical history and income were the main influencing factors of residents’ quality of life. The variables contributing to PCS were chronic disease history (32%), age (25%), employment status (24%),income (12%) and weekly exercise (7%). The factors mainly contributing to MCS were employment status (35%), chronic disease history (21%), income (18%), weekly exercise (12%).

Conclusion

The overall quality of life of residents in survey areas of Hubei is good. Employment status, chronic disease history, income and weekly exercise are main influencing factors of residents’ quality of life. Increasing income levels, strengthening chronic disease management, and improving health behaviors may improve residents’ quality of life.

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目的

探讨居民生命质量及其影响因素,运用Shapley法分析各影响因素对生命质量的贡献度,为相关政策的制定提供科学依据。

方法

采用分层随机抽样方法于2021年7—8月对湖北省五城市城乡居民进行问卷调查,依据SF-12量表调查居民的生命质量,用多元回归模型和Shapley分解法分析生命质量影响因素及其贡献程度。

结果

共调查1 387人,调查地区居民的生理健康(Physical Component Summary,PCS)得分为71.04±17.43,心理健康(Mental Component Summary, MCS)得分为75.70±12.51。年龄≥60(β=-6.073)、就业情况( 离退休(β=-12.752),无业(β=-7.292))、个人年收入(5~10万(β=3.516),>10万(β=6.169))、无慢性病史(β=9.202)、很少锻炼(β=-3.182)对居民生理健康产生显著影响(P<0.05),在婚(β=2.106)、就业情况(离退休(β=-6.788),无业(β=-5.174))、个人年收入>10万(β=3.842)、无医保(β=-4.455)、无慢性病史(β=3.450)、很少锻炼(β=-2.056)对居民心理健康有显著影响(P<0.05)。影响PCS的变量按贡献率排序为慢性病史(32%)、年龄(25%)、就业情况(24%)、个人年收入(12%)、每周锻炼(7%);对MCS贡献率较大的因素依次为就业情况(35%)、慢性病史(21%)、个人年收入(18%)、每周锻炼(12%)。

结论

湖北部分地区居民整体生命质量良好,就业情况、慢性病史、年收入和每周锻炼是居民生命质量的主要影响因素。提高收入水平,加强慢性病防控,促进健康生活方式,有助于居民生命质量的提高。

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雷晓盛,E-mail:
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雷晓盛(1970—),女,硕士,教授,研究方向:卫生管理

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Population and Development, 2018, 24(3): 85-95., articleTitle=Factors affect Chinese health——related quality oflife and the effectiveness of healthcare reforms, refAbstract=null)], funds=[Fund(id=1241102748939244195, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, awardId=20ZD054, language=CN, fundingSource=湖北省高校哲学社会科学研究重大项目(20ZD054), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241102744002548038, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, xref=1., ext=[AuthorCompanyExt(id=1241102744010936646, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, companyId=1241102744002548038, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Management, Hubei University of Chinese Medicine, Wuhan, Hubei 430060, China), AuthorCompanyExt(id=1241102744019325256, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, companyId=1241102744002548038, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.湖北中医药大学管理学院,湖北 武汉 430060)]), AuthorCompany(id=1241102744094822735, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, xref=2., ext=[AuthorCompanyExt(id=1241102744103211343, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, companyId=1241102744094822735, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.南京中医药大学护理学院)])], figs=[ArticleFig(id=1241102746179392032, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=EN, label=Fig.1, caption=Decomposition of factors affecting the PCS, figureFileSmall=UgfHnK5mr9gqCjpbSSRJjg==, figureFileBig=QhoXCampwxuXaJrFTWdB9A==, tableContent=null), ArticleFig(id=1241102746271666730, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=CN, label=图1, caption=各影响因素对居民PCS的贡献率, figureFileSmall=UgfHnK5mr9gqCjpbSSRJjg==, figureFileBig=QhoXCampwxuXaJrFTWdB9A==, tableContent=null), ArticleFig(id=1241102746527519302, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=EN, label=Fig.2, caption=Decomposition of factors affecting the MCS, figureFileSmall=ECoWMU2t6hUTEcAUvAJ2UQ==, figureFileBig=H2ZmeJBIs5QBmu0Lb57nCA==, tableContent=null), ArticleFig(id=1241102746632376914, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=CN, label=图2, caption=各影响因素对居民MCS的贡献率, figureFileSmall=ECoWMU2t6hUTEcAUvAJ2UQ==, figureFileBig=H2ZmeJBIs5QBmu0Lb57nCA==, tableContent=null), ArticleFig(id=1241102746712068695, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=EN, label=Table 1, caption=

Scores and correlation of QOL and its various dimensions for residents

, figureFileSmall=null, figureFileBig=null, tableContent=
维 度平均值标准差相关系数
PCSMCS
GH躯体健康48.9323.310.367a0.353a
PF生理功能82.0424.320.627a0.497a
RP生理职能77.9521.500.774a0.553a
BP躯体疼痛75.2525.060.787a0.468a
RE情感职能80.7919.270.767a0.648a
MH精神健康71.7613.880.547a0.669a
VT活力状况68.8921.690.310a0.693a
SF社会功能81.3520.590.418a0.644a
PCS生理健康71.0417.431.0000.631a
MCS心理健康75.7012.510.631a1.000
), ArticleFig(id=1241102748222018146, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=CN, label=表1, caption=

居民生命质量、各维度评分及其相关关系

, figureFileSmall=null, figureFileBig=null, tableContent=
维 度平均值标准差相关系数
PCSMCS
GH躯体健康48.9323.310.367a0.353a
PF生理功能82.0424.320.627a0.497a
RP生理职能77.9521.500.774a0.553a
BP躯体疼痛75.2525.060.787a0.468a
RE情感职能80.7919.270.767a0.648a
MH精神健康71.7613.880.547a0.669a
VT活力状况68.8921.690.310a0.693a
SF社会功能81.3520.590.418a0.644a
PCS生理健康71.0417.431.0000.631a
MCS心理健康75.7012.510.631a1.000
), ArticleFig(id=1241102748343652972, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=EN, label=Table 2, caption=

Comparison of QOL with different characteristics of residents

, figureFileSmall=null, figureFileBig=null, tableContent=
变 量人数(%)PCSMCS
均值T/FP均值T/FP
性别1.660.098-0.150.882
男性696(52.10)71.8175.65
女性640(47.90)70.2175.76
年龄107.820.00021.550.000
<45767(57.41)75.1676.63
45~59412(30.84)69.7176.29
≥60157(11.75)54.4169.63
是否在婚-0.710.479-3.380.001
未在婚992(74.25)70.4373.60
在婚344(25.75)71.2576.44
居住地1.080.279-0.530.594
城市727(54.42)71.4275.55
农村609(45.58)70.3675.92
医保状况-1.650.099-3.490.001
1 289(96.48)66.6769.25
47(3.52)71.1775.92
教育程度32.320.00011.180.000
小学及以下207(15.49)64.0972.66
初中/高中723(54.12)70.4775.49
大专及以上406(30.39)75.6677.64
就业情况132.460.00047.920.000
在业1 008(75.45)74.9477.55
离退休108(8.08)53.0769.19
无业220(16.47)62.0170.43
个人年收入36.020.00015.010.000
<3万370(27.69)63.7472.63
3~<5万455(34.06)71.9875.46
5~10万385(28.82)74.7877.72
>10万126(9.43)77.5179.46
慢性病-12.060.000-6.520.000
330(24.70)60.3871.85
1 006(75.30)74.5676.96
是否吸烟5.030.0071.820.163
吸烟403(30.16)70.8675.16
已戒烟133(9.96)66.6774.32
不吸烟800 (59.88)71.8576.20
是否喝酒1.950.0510.820.414
535 (40.04)72.1976.05
801 (59.96)70.2875.47
每周锻炼5.260.0004.480.000
877(65.64)72.9376.81
459(34.36)67.4373.58
), ArticleFig(id=1241102748461093497, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=CN, label=表2, caption=

不同特征居民生命质量的比较

, figureFileSmall=null, figureFileBig=null, tableContent=
变 量人数(%)PCSMCS
均值T/FP均值T/FP
性别1.660.098-0.150.882
男性696(52.10)71.8175.65
女性640(47.90)70.2175.76
年龄107.820.00021.550.000
<45767(57.41)75.1676.63
45~59412(30.84)69.7176.29
≥60157(11.75)54.4169.63
是否在婚-0.710.479-3.380.001
未在婚992(74.25)70.4373.60
在婚344(25.75)71.2576.44
居住地1.080.279-0.530.594
城市727(54.42)71.4275.55
农村609(45.58)70.3675.92
医保状况-1.650.099-3.490.001
1 289(96.48)66.6769.25
47(3.52)71.1775.92
教育程度32.320.00011.180.000
小学及以下207(15.49)64.0972.66
初中/高中723(54.12)70.4775.49
大专及以上406(30.39)75.6677.64
就业情况132.460.00047.920.000
在业1 008(75.45)74.9477.55
离退休108(8.08)53.0769.19
无业220(16.47)62.0170.43
个人年收入36.020.00015.010.000
<3万370(27.69)63.7472.63
3~<5万455(34.06)71.9875.46
5~10万385(28.82)74.7877.72
>10万126(9.43)77.5179.46
慢性病-12.060.000-6.520.000
330(24.70)60.3871.85
1 006(75.30)74.5676.96
是否吸烟5.030.0071.820.163
吸烟403(30.16)70.8675.16
已戒烟133(9.96)66.6774.32
不吸烟800 (59.88)71.8576.20
是否喝酒1.950.0510.820.414
535 (40.04)72.1976.05
801 (59.96)70.2875.47
每周锻炼5.260.0004.480.000
877(65.64)72.9376.81
459(34.36)67.4373.58
), ArticleFig(id=1241102748612088454, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=EN, label=Table 3, caption=

Multivariate stepwise regression analysis of factors affecting the QOL

, figureFileSmall=null, figureFileBig=null, tableContent=
维度自变量β系数(95%CI标准误TP
生理健康年龄(岁,以<45岁为参照)
45~59-1.379(-3.310~0.553)0.984-1.400.162
≥60-6.073(-9.642~-2.504)1.819-3.340.001
就业情况(以在业为参照)
离退休-12.752(-16.603~-8.902)1.963-6.500.000
无业-7.292(-9.950~-4.635)1.355-5.380.000
个人年收入(以<3万为参照)
3~<5万1.718(-0.643~4.080)1.2041.430.154
5~10万3.516(1.026~6.007)1.2692.770.006
>10万6.169(2.881~9.456)1.6763.680.000
慢性病史(以是为参照)
9.202(7.129~11.275)1.0568.710.000
每周锻炼(以是为参照)
-3.182(-4.939~-1.425)0.896-3.550.000
心理健康是否在婚(以否为参照)
2.106(0.613~3.599)0.7612.770.006
就业情况(以在业为参照)
离退休-6.788(-9.324~-4.252)1.293-5.250.000
无业-5.174(-7.199~-3.150)1.032-5.010.000
个人年收入(以<3万为参照)
3~<5万-0.246(-2.077~1.584)0.933-0.260.792
5~10万1.392(-0.541~3.326)0.9861.410.158
>10万3.842(1.267~6.417)1.3132.930.003
医保状况(以有医保为参照)
-4.455(-7.981~-0.929)1.797-2.480.013
慢性病史(以是为参照)
3.450(1.909~4.990)0.7854.390.000
每周锻炼(以是为参照)
-2.056(-3.428~-0.684)1.699-2.940.003
), ArticleFig(id=1241102748750500496, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102740005376168, language=CN, label=表3, caption=

居民生命质量影响因素的多元逐步回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
维度自变量β系数(95%CI标准误TP
生理健康年龄(岁,以<45岁为参照)
45~59-1.379(-3.310~0.553)0.984-1.400.162
≥60-6.073(-9.642~-2.504)1.819-3.340.001
就业情况(以在业为参照)
离退休-12.752(-16.603~-8.902)1.963-6.500.000
无业-7.292(-9.950~-4.635)1.355-5.380.000
个人年收入(以<3万为参照)
3~<5万1.718(-0.643~4.080)1.2041.430.154
5~10万3.516(1.026~6.007)1.2692.770.006
>10万6.169(2.881~9.456)1.6763.680.000
慢性病史(以是为参照)
9.202(7.129~11.275)1.0568.710.000
每周锻炼(以是为参照)
-3.182(-4.939~-1.425)0.896-3.550.000
心理健康是否在婚(以否为参照)
2.106(0.613~3.599)0.7612.770.006
就业情况(以在业为参照)
离退休-6.788(-9.324~-4.252)1.293-5.250.000
无业-5.174(-7.199~-3.150)1.032-5.010.000
个人年收入(以<3万为参照)
3~<5万-0.246(-2.077~1.584)0.933-0.260.792
5~10万1.392(-0.541~3.326)0.9861.410.158
>10万3.842(1.267~6.417)1.3132.930.003
医保状况(以有医保为参照)
-4.455(-7.981~-0.929)1.797-2.480.013
慢性病史(以是为参照)
3.450(1.909~4.990)0.7854.390.000
每周锻炼(以是为参照)
-2.056(-3.428~-0.684)1.699-2.940.003
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湖北省五城市城乡居民生命质量及其影响因素研究
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雷晓盛 1 , 徐爱军 2 , 周利琴 1
现代预防医学 | 流行病与统计方法 2024,51(14): 2535-2540
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现代预防医学 | 流行病与统计方法 2024, 51(14): 2535-2540
湖北省五城市城乡居民生命质量及其影响因素研究
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雷晓盛1 , 徐爱军2, 周利琴1
作者信息
  • 1.湖北中医药大学管理学院,湖北 武汉 430060
  • 2.南京中医药大学护理学院
  • 雷晓盛(1970—),女,硕士,教授,研究方向:卫生管理

通讯作者:

雷晓盛,E-mail:
A Study on the quality of life and its influencing factors of urban and rural residents among five cities of Hubei Province
Xiao-sheng LEI1 , Ai-jun XU2, Li-qin ZHOU1
Affiliations
  • School of Management, Hubei University of Chinese Medicine, Wuhan, Hubei 430060, China
出版时间: 2024-07-25 doi: 10.20043/j.cnki.MPM.202404207
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目的

探讨居民生命质量及其影响因素,运用Shapley法分析各影响因素对生命质量的贡献度,为相关政策的制定提供科学依据。

方法

采用分层随机抽样方法于2021年7—8月对湖北省五城市城乡居民进行问卷调查,依据SF-12量表调查居民的生命质量,用多元回归模型和Shapley分解法分析生命质量影响因素及其贡献程度。

结果

共调查1 387人,调查地区居民的生理健康(Physical Component Summary,PCS)得分为71.04±17.43,心理健康(Mental Component Summary, MCS)得分为75.70±12.51。年龄≥60(β=-6.073)、就业情况( 离退休(β=-12.752),无业(β=-7.292))、个人年收入(5~10万(β=3.516),>10万(β=6.169))、无慢性病史(β=9.202)、很少锻炼(β=-3.182)对居民生理健康产生显著影响(P<0.05),在婚(β=2.106)、就业情况(离退休(β=-6.788),无业(β=-5.174))、个人年收入>10万(β=3.842)、无医保(β=-4.455)、无慢性病史(β=3.450)、很少锻炼(β=-2.056)对居民心理健康有显著影响(P<0.05)。影响PCS的变量按贡献率排序为慢性病史(32%)、年龄(25%)、就业情况(24%)、个人年收入(12%)、每周锻炼(7%);对MCS贡献率较大的因素依次为就业情况(35%)、慢性病史(21%)、个人年收入(18%)、每周锻炼(12%)。

结论

湖北部分地区居民整体生命质量良好,就业情况、慢性病史、年收入和每周锻炼是居民生命质量的主要影响因素。提高收入水平,加强慢性病防控,促进健康生活方式,有助于居民生命质量的提高。

SF-12量表  /  生命质量  /  影响因素  /  Shapley分解法
Objective

To analyze the quality of life (QOL) and its related factors among residents, and to explore the contribution of each factors to QOL by Shapley method, so as to provide references for health policy making.

Methods

Questionnaire survey was conducted in 5 cities of Hubei Province from July to August 2021 by stratified random sampling to measure the QOL of 1 387 residents according to SF-12 scale, multivariate regression model and Shapley decomposition method were applied to analyze the influencing factors and its contribution to QOL.

Results

The scores of residents’ physical component summary (PCS) and mental component summary (MCS) were 71.04±17.43 and 75.70±12.51 respectively. Age≥60 (β=-6.073), employment status (retirement (β=-12.752), unemployed (β=-7.292)), annual income (50 000-100 000 Yuan (β=3.516), >100 000 Yuan (β=6.169)), no chronic disease history (β=9.202), and no physical exercise (β=-3.182) had significant effects on PCS (P<0.05), whereas married (β=2.106), employment status (retirement (β=-6.788),unemployed (β=-5.174)), personal annual income >100 000 Yuan (β=3.842), without medical insurance (β=-4.455), no chronic disease history (β=3.450) and no physical exercise (β=-2.056) had significant effects on MCS (P<0.05). Shapley decomposition results showed that employment, chronic medical history and income were the main influencing factors of residents’ quality of life. The variables contributing to PCS were chronic disease history (32%), age (25%), employment status (24%),income (12%) and weekly exercise (7%). The factors mainly contributing to MCS were employment status (35%), chronic disease history (21%), income (18%), weekly exercise (12%).

Conclusion

The overall quality of life of residents in survey areas of Hubei is good. Employment status, chronic disease history, income and weekly exercise are main influencing factors of residents’ quality of life. Increasing income levels, strengthening chronic disease management, and improving health behaviors may improve residents’ quality of life.

SF-12 scale  /  Quality of life  /  Influencing factors  /  Shapley decomposition
雷晓盛, 徐爱军, 周利琴. 湖北省五城市城乡居民生命质量及其影响因素研究. 现代预防医学, 2024 , 51 (14) : 2535 -2540 . DOI: 10.20043/j.cnki.MPM.202404207
Xiao-sheng LEI, Ai-jun XU, Li-qin ZHOU. A Study on the quality of life and its influencing factors of urban and rural residents among five cities of Hubei Province[J]. Modern Preventive Medicine, 2024 , 51 (14) : 2535 -2540 . DOI: 10.20043/j.cnki.MPM.202404207
随着社会经济的快速发展和人民生活水平的提高,人们不仅关注长寿,还追求生活质量的提高。我国健康中国战略提出到2030年要有效控制主要健康危险因素,从而持续提升居民健康水平[1]。在此背景下,了解居民生命质量及其影响因素,对于提高居民健康水平具有重要意义,可为有效制定卫生干预措施和改善居民生命质量提供决策依据。
生命质量(Quality of life)是指个体与价值观、经济文化环境相关联的健康状况的主观感受(WHO)[2],它综合描述个体生理、心理和社会方面的健康状况[3]。SF-12量表是SF-36的简表,是测量生命质量常用的工具,在实践中被证明具有良好的信度和效度[4-5]。Shapley值法是一种变量分解方法,可以综合衡量各个因素对生命质量的影响程度,从而全面评估各因素对生命质量的实际影响。尽管目前我国对生命质量及其影响因素有较多的研究,但运用分解法量化解释各因素影响程度的研究较少。本研究基于SF-12量表对湖北省五城市城乡居民进行问卷抽样调查,评估居民健康相关生命质量,探讨其影响因素,并应用Shapley分解法对各影响因素的贡献程度进行量化分析,有助于政策制定中根据各影响因素的贡献,确定采取干预措施的优先次序,从而促进居民生命质量的进一步提高。
2021年7—8月运用分层整群多阶段抽样,选取湖北省襄阳市、荆州市、孝感市、荆门市、潜江市,每个城市分别抽取城市社区和农村村庄1个,孝感市抽取2个社区,共选择7个社区和6个村庄。在抽中的社区和村庄以年满16岁具有自主能力居民作为调查对象,随机发放不少于100份调查问卷。共发出调查问卷1 387份,剔除空白、无效问卷,有效回收问卷为1 336份,问卷有效回收率为96.3%。调查排除标准:有重大疾病、无独立行为能力者。本研究获得湖北中医药大学医学伦理委员会审批,审查批准号:2024005。调查对象填写知情同意后回答问卷。
居民健康状况调查采用自编问卷和SF-12量表进行。调查内容包括调查对象人口学特征(性别、年龄、婚姻状况、居住地)、社会经济状况(年均收入、教育程度、就业状况、医保状况)、个人健康及生活方式(是否患有慢性病、是否抽烟、是否喝酒、是否每周锻炼)及生命质量等。
生命质量评价采用SF-12调查表。量表分为生理健康(Physical Component Summary,PCS)和心理健康(Mental Component Summary,MCS)两部分。共有12条陈述句、8个维度,应用Likert量表赋值打分,将量表得分转换为百分制,分数越高,表明健康状况较好。本研究中,SF-12量表的Cronbach α系数为0.784,对SF-12量表8个维度进行验证性因子分析,得出KMO=0.792,Bartlett’s球形检验P<0.001。总体看,量表具有较好的信度和效度。
应用SPSS 19.0和STATA 16.0进行数据统计分析。计量资料描述统计用表达;比较不同人口社会学特征居民生命质量的差异,两分类变量用t检验,多分类变量用方差分析。应用线性回归法对生命质量得分进行多因素分析,检验标准为α=0.05。采用Shapley值分解法量化分析各因素对生命质量的影响程度。Sharply值法是博弈理论中的一个概念,是公平分配成员贡献的方法。通过对所有组合进行考虑,计算每个成员在合作中的边际贡献,并根据权重因子进行加权求和,更客观评价每个参与成员的贡献。本文中,采用此方法计算各影响因素对居民生命质量的贡献率,为卫生政策制定提供基础。
共调查1 336人,其中男性696人,占52.1%,女性640人,占47.9%。调查对象平均年龄42.5岁,年龄范围为16~89岁。45岁以下占57.4%,45岁以上占42.6%。74.3%在婚,25.7%未在婚(包括未婚、离婚和丧偶)。城市居民占比54.4%,农村居民占比45.6%。调查对象中54%为初中或高中文化程度,小学及以下占15.5%, 大专及以上文化者占30.4%。75.4%调查对象有工作,8.1%为离退休人员, 16.5%为无职业者。个人年收入3万以下占27.7%,3-5万占34.1%,5万以上占38.2%。调查对象中96.5%有医疗保险;慢性病患者占总人数的24.7%;59.9%的居民不吸烟,10%已戒烟;60%不喝酒;65.6%每周锻炼(表2)。
调查居民的PCS均分为71.04±17.43,MCS均分为75.70±12.51;PCS、MCS与生命质量各维度得分均有显著相关关系(P<0.001)。各维度得分中,以生理功能得分最高82.04±24.32分,得分最低的是躯体健康48.93±23.31分,其次是精力状况68.89±21.69分。(表1)。
年龄<45岁、大专及以上教育程度、在就业、较高收入、无慢性病、每周锻炼者,PCS和MCS得分均较高(P<0.05);不吸烟者PCS得分较高(P<0.05),在婚、有医保MCS得分较高(P<0.05)。具体见表2
分别以生理健康(PCS)和心理健康(MCS)为因变量,将社会人口学及生活方式等变量作为自变量进行回归分析。检测自变量VIF值介于1~2之间,可排除数据之间多重共线性。分析表明, 60岁以下、在业、每周锻炼、年收入≥5万、无慢性病者生理健康得分较高。在婚、在业、有医疗保险、每周锻炼、年收入>10万、无慢性病者心理健康得分较高。(见表3
在生理健康的影响因素中,人口学因素贡献率为25%、社会经济因素36%、个人健康及生活方式贡献率为39%。以上各因素的构成变量中,对生理健康贡献率较大的变量依次为慢性病史(32%)、年龄(25%)、就业情况(24%)、个人年收入(12%)和每周锻炼(7%)(见图1)。在心理健康的影响因素中,人口学因素贡献率为8%、社会经济因素贡献率为59%、个人健康及生活方式贡献率为33%。其中对心理健康解释贡献率最大的变量为就业情况(35%),其次是慢性病史(21%)、个人年收入(18%)和每周锻炼(12%)(见图2)。
调查结果表明,调查对象生理健康得分为71.04±17.43,心理健康得分为75.70±12.51,与以往的研究结果相比,调查地区居民总体上生命质量良好[6-7],且心理健康优于生理健康。多因素回归分析显示,社会经济因素(就业情况、收入)、个人健康及生活方式(慢性病史、每周锻炼)对生命质量具有显著影响。另外,年龄对居民生理健康产生影响,婚姻状况及医疗保障状况对心理健康有一定影响。
就业状况和收入水平对居民生命质量有较大影响。在业人群生命质量得分明显高于无业和退休人群。原因可能是就业能够减少经济压力和孤独心理,带来较好的生活和保健条件,同时增加活动频率,从而相应减少了慢性疾病。随着收入增长,居民生命质量提高。经济状况较好的居民,生命质量较好,这与司光林等研究结果一致 [8-10]。原因是随着收入水平提高,居民对健康进行更多的投资,获取健康的能力也相应提高,包括拥有安全的食物、充足的营养、高质量的医疗卫生服务等,从而更好的自我保健和预防疾病。
慢性病对居民生命质量有较大的负面影响,这与包思敏等研究结论相一致[11-12]。2019年我国慢性病致死人数占总死亡数的88.5%,慢性病依然是危害国民健康的重要因素。因此,普及健康教育,预防慢性疾病;同时提高基层卫生服务的质量,加强社区卫生机构对慢性病的防治具有重要意义。
每周锻炼是生命质量的保护因素。每周锻炼的居民生命质量较高,经常锻炼不仅能够强身健体,预防疾病,而且有利于提高居民心理健康。本次调查中65.6%的居民每周锻炼,尽管居民锻炼率高于国家第六次卫生服务调查的49.9%,但是社区仍需进一步改善体育运动设施,建设健康社区支持环境,并对居民锻炼进行科学指导。
居民的健康生命质量仍需进一步提高。本次调查中居民的躯体健康(GH)评分最低,仅为48.93分,部分居民存在亚健康状况。因此,应重点关注居民生理健康的改善。年龄对居民生理健康有显著影响,随着年龄升高,老年人群生理健康水平下降[13-14]。研究发现,老年人、低收入人群及慢性病患者生命质量得分较低,建议相关政策的制定应关注老年人口、低收入及慢性病患者[15]。完善社会保障体系建设,促进就业,加强慢性病防控,推行健康生活方式,提高居民健康素养,将有助于改善居民健康状况,促进健康中国战略目标的实施。
  • 湖北省高校哲学社会科学研究重大项目(20ZD054)
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2024年第51卷第14期
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doi: 10.20043/j.cnki.MPM.202404207
  • 接收时间:2024-04-13
  • 首发时间:2026-03-18
  • 出版时间:2024-07-25
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  • 收稿日期:2024-04-13
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湖北省高校哲学社会科学研究重大项目(20ZD054)
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    1.湖北中医药大学管理学院,湖北 武汉 430060
    2.南京中医药大学护理学院

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