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Article(id=1241342451747704841, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241342451043061769, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202307398, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1690128000000, receivedDateStr=2023-07-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773888703523, onlineDateStr=2026-03-19, pubDate=1708790400000, pubDateStr=2024-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773888703523, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773888703523, creator=13701087609, updateTime=1773888703523, updator=13701087609, issue=Issue{id=1241342451043061769, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='4', pageStart='577', pageEnd='768', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773888703356, creator=13701087609, updateTime=1773893026321, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241360582939562716, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241342451043061769, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241360582939562717, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241342451043061769, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=691, endPage=696, ext={EN=ArticleExt(id=1241342452146163725, articleId=1241342451747704841, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Quality of life assessment of elderly in rural areas and its spatial variations, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To study the quality-of-life level and its differentiation characteristics of elderly people in rural areas of China.

Methods

Based on the China Health and Retirement Longitudinal Study in 2018, we constructed an indicator system for evaluating the quality of life of rural elderly people from four levels: individual, family, society, and policy. The entropy method was used to objectively assign weights and calculate the quality-of-life score. The evaluation results were analyzed from three aspects: population characteristics, spatial correlation, and spatial distribution.

Results

Marital status (F=35.27, P<0.001) and educational level (F=10.80, P<0.001) had a significant impact on the quality of life of rural elderly people. The distribution of quality of life was spatially correlated (I=0.432, P<0.001). There are a total of 16 provinces (accounting for 57.142%) with quality levels in the middle, low, and low-level regions, mainly located in the central and western regions.

Conclusion

More than half of the rural elderly in provinces have a quality of life in areas with a moderate or lower level, exhibiting a positive spatial clustering feature, roughly showing a distribution pattern of high in the east and low in the west. Special attention should be paid to the quality of life of unmarried, widowed, low educated, and central and western provinces.

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目的

分析我国农村高龄老人的生活质量水平及其分异特征。

方法

基于中国健康与养老追踪调查 （CHARLS）2018年调查数据，从个人、家庭、社会、政策4个层面构建评价农村高龄老人生活质量的指标体系，采用熵值法进行客观赋权后计算生活质量得分，从人口特征、空间相关、空间分布3个层面对评价结果展开具体分析。

结果

婚姻状况（F=35.27，P<0.001）、受教育水平（F=10.80，P<0.001）对农村高龄老人生活质量影响显著，生活质量的分布具有空间相关性（I=0.432，P<0.001），质量水平处于中等、中低及低水平区的省份共计16个（占比57.142%），主要位于中西部地区。

结论

超半数省份的农村高龄老人生活质量在中等及以下水平区域，具有正向空间集聚特征，大致呈东高西低分布态势，应重点关注未婚、丧偶、受教育水平低、中西部省份的人群生活质量。

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王春玲，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=OhfUJPWcQlfDcuaktG0a4Q==, magXml=b03asPLTR7L9y9apPR71Lw==, pdfUrl=null, pdf=26JRBuJXnIfSJR7H37ve/w==, pdfFileSize=987275, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=eGkoE2U9w9ZpiSxJR+yjng==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=q15e12kfT46Sy7L/qeHteA==, mapNumber=null, authorCompany=null, fund=null, authors=

王春玲（1996—），女，硕士，高校教师，研究方向：养老保障、老年护理

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王春玲（1996—），女，硕士，高校教师，研究方向：养老保障、老年护理

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王春玲（1996—），女，硕士，高校教师，研究方向：养老保障、老年护理

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On Economic Problems, 2020, (11): 111-118., articleTitle=Construction and measurement of regional high-quality development evaluation system, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1241342456189472883, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, xref=null, ext=[AuthorCompanyExt(id=1241342456202055797, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, companyId=1241342456189472883, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Shanghai Sipo Polytechnic, Shanghai 200120, China), AuthorCompanyExt(id=1241342456210444406, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, companyId=1241342456189472883, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=上海思博职业技术学院，上海 200120)])], figs=[ArticleFig(id=1241342459138068700, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Fig.1, caption=Moran scatter plot of the quality of life of elderly people in rural areas, figureFileSmall=7wPX0gpH1p8IKga4JDtzmg==, figureFileBig=eGkoE2U9w9ZpiSxJR+yjng==, tableContent=null), ArticleFig(id=1241342459234537698, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=CN, label=图1, caption=农村高龄老人生活质量的Moran散点图, figureFileSmall=7wPX0gpH1p8IKga4JDtzmg==, figureFileBig=eGkoE2U9w9ZpiSxJR+yjng==, tableContent=null), ArticleFig(id=1241342459469418737, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Table 1, caption=

Evaluation index system of life quality of the elderly in rural areas

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标二级指标问题等级/单位属性
个人层面生理健康慢性病数量项负向
自评健康状况1～5级正向
身体疼痛程度1～5级负向
心理健康孤独程度1～4级负向
情绪低落程度1～4级负向
对未来希望感1～4级正向
家庭层面经济条件家庭存款数额元正向
家庭生活支出元/月正向
家庭关系子女关系满意度1～5级正向
婚姻关系满意度1～5级正向
居住条件室内整洁度1～5级正向
房屋建筑面积平方米正向
社会层面社会交往社交活动次数次/月正向
生存环境空气质量满意度1～5级正向
政策层面养老保障养老金收入元/月正向
医疗保障医疗服务满意度1～5级正向
), ArticleFig(id=1241342459561693433, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=CN, label=表1, caption=

农村高龄老人生活质量评价指标体系

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标二级指标问题等级/单位属性
个人层面生理健康慢性病数量项负向
自评健康状况1～5级正向
身体疼痛程度1～5级负向
心理健康孤独程度1～4级负向
情绪低落程度1～4级负向
对未来希望感1～4级正向
家庭层面经济条件家庭存款数额元正向
家庭生活支出元/月正向
家庭关系子女关系满意度1～5级正向
婚姻关系满意度1～5级正向
居住条件室内整洁度1～5级正向
房屋建筑面积平方米正向
社会层面社会交往社交活动次数次/月正向
生存环境空气质量满意度1～5级正向
政策层面养老保障养老金收入元/月正向
医疗保障医疗服务满意度1～5级正向
), ArticleFig(id=1241342459691716866, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Table 2, caption=

Description of variables after truncation

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名观测值均值标准差最小值最大值
慢性病数量（项）1 8041.7510.97815
家庭存款数额（元）1 80415 325.41037 187.0700250 000
家庭生活支出（元/月）1 8041 430.6891 473.948508 000
房屋建筑面积（平方米）1 804102.69954.40720360
社交活动次数（次/月）1 8040.6310.86904
养老金收入（元/月）1 804114.869277.51701 708
), ArticleFig(id=1241342459804963084, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=CN, label=表2, caption=

缩尾后变量描述表

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名观测值均值标准差最小值最大值
慢性病数量（项）1 8041.7510.97815
家庭存款数额（元）1 80415 325.41037 187.0700250 000
家庭生活支出（元/月）1 8041 430.6891 473.948508 000
房屋建筑面积（平方米）1 804102.69954.40720360
社交活动次数（次/月）1 8040.6310.86904
养老金收入（元/月）1 804114.869277.51701 708
), ArticleFig(id=1241342459897237778, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Table 3, caption=

Indicator Weights and Descriptive Statistics

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标二级指标问题权重最小值最大值均值标准差
个人层面(0.468)生理健康(0.197)慢性病数量0.055151.7510.978
自评健康状况0.055153.0320.965
身体疼痛程度0.087151.5540.497
心理健康(0.37)孤独程度0.106141.8041.117
情绪低落程度0.104141.9291.090
对未来希望感0.160142.4001.236
家庭层面(0.344)经济条件(0.085)家庭存款数额0.0360250 00015 325.41037 187.070
家庭生活支出0.049508 0001 430.6891 473.948
家庭关系(0.068)子女关系满意度0.040152.4970.847
婚姻关系满意度0.028153.5781.688
居住条件(0.104)室内整洁度0.073153.1941.263
房屋建筑面积0.03120360102.69954.407
社会层面(0.070)社会交往社交活动次数0.030040.6310.869
生存环境空气质量满意度0.040152.760.866
政策层面(0.107)养老保障养老金收入0.04201 708114.869277.517
医疗保障医疗服务满意度0.065152.5741.123
), ArticleFig(id=1241342459993706779, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=CN, label=表3, caption=

指标权重及描述性统计

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标二级指标问题权重最小值最大值均值标准差
个人层面(0.468)生理健康(0.197)慢性病数量0.055151.7510.978
自评健康状况0.055153.0320.965
身体疼痛程度0.087151.5540.497
心理健康(0.37)孤独程度0.106141.8041.117
情绪低落程度0.104141.9291.090
对未来希望感0.160142.4001.236
家庭层面(0.344)经济条件(0.085)家庭存款数额0.0360250 00015 325.41037 187.070
家庭生活支出0.049508 0001 430.6891 473.948
家庭关系(0.068)子女关系满意度0.040152.4970.847
婚姻关系满意度0.028153.5781.688
居住条件(0.104)室内整洁度0.073153.1941.263
房屋建筑面积0.03120360102.69954.407
社会层面(0.070)社会交往社交活动次数0.030040.6310.869
生存环境空气质量满意度0.040152.760.866
政策层面(0.107)养老保障养老金收入0.04201 708114.869277.517
医疗保障医疗服务满意度0.065152.5741.123
), ArticleFig(id=1241342460157284638, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Table 4, caption=

Quality of life scores of the elderly in rural areas under different population characteristics and comparative analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
人口特征人数个人层面家庭层面社会层面政策层面生活质量得分标准差F值P值
生理心理经济家庭居住社交环境养老医疗
性别0.1500.699
男90913.63523.4101.1423.1534.1290.2722.2420.2323.74151.94811.375
女89512.58621.3751.0072.9634.3130.2692.2510.3294.10449.19611.977
年龄段1.4700.221
75～791 04812.96222.5241.0463.0434.2920.292.2450.2743.89250.56411.947
80～8454213.29222.0571.1273.0974.1520.2682.2230.3033.93850.44911.534
85～8918913.45622.7251.0983.0124.0700.1792.3370.2494.02851.15311.507
≥902513.05422.2551.0183.2633.880.1862.2090.2823.97449.96110.704
婚姻状况35.270<0.001
已婚1 09013.34223.5531.1793.1304.3130.2682.2270.2903.86152.16111.318
离异1813.44124.1360.8213.3263.8740.2582.1750.1594.46952.4119.056
丧偶68812.77220.5800.9232.9354.1120.2752.2790.2694.01248.15012.073
未婚810.81618.2380.6313.3981.7260.1582.3850.1413.23340.7258.384
受教育水平10.800<0.001
文盲1 04712.69120.9120.7943.0033.9390.2232.3510.3054.14148.35411.630
小学39213.63023.1691.0823.1134.2290.2642.1670.3283.60951.58210.930
初中19313.71624.6611.2863.1634.7010.3482.0440.2133.66853.8019.778
≥高中17213.84527.1812.5323.1625.3750.4912.0260.0983.57358.26112.034
), ArticleFig(id=1241342460287308069, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=CN, label=表4, caption=

不同人口特征下农村高龄老人生活质量得分及比较分析

, figureFileSmall=null, figureFileBig=null, tableContent=
人口特征人数个人层面家庭层面社会层面政策层面生活质量得分标准差F值P值
生理心理经济家庭居住社交环境养老医疗
性别0.1500.699
男90913.63523.4101.1423.1534.1290.2722.2420.2323.74151.94811.375
女89512.58621.3751.0072.9634.3130.2692.2510.3294.10449.19611.977
年龄段1.4700.221
75～791 04812.96222.5241.0463.0434.2920.292.2450.2743.89250.56411.947
80～8454213.29222.0571.1273.0974.1520.2682.2230.3033.93850.44911.534
85～8918913.45622.7251.0983.0124.0700.1792.3370.2494.02851.15311.507
≥902513.05422.2551.0183.2633.880.1862.2090.2823.97449.96110.704
婚姻状况35.270<0.001
已婚1 09013.34223.5531.1793.1304.3130.2682.2270.2903.86152.16111.318
离异1813.44124.1360.8213.3263.8740.2582.1750.1594.46952.4119.056
丧偶68812.77220.5800.9232.9354.1120.2752.2790.2694.01248.15012.073
未婚810.81618.2380.6313.3981.7260.1582.3850.1413.23340.7258.384
受教育水平10.800<0.001
文盲1 04712.69120.9120.7943.0033.9390.2232.3510.3054.14148.35411.630
小学39213.63023.1691.0823.1134.2290.2642.1670.3283.60951.58210.930
初中19313.71624.6611.2863.1634.7010.3482.0440.2133.66853.8019.778
≥高中17213.84527.1812.5323.1625.3750.4912.0260.0983.57358.26112.034
), ArticleFig(id=1241342460463468844, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Table 5, caption=

Results of local Moran index I test on quality of life of the elderly in rural areas

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莫兰指数分析地区IiE(Ii)sd(Ii)zp-value
全局莫兰检验0.432-0.0370.1044.524<0.001
局部莫兰检验北京4.102-0.0370.5038.226<0.001
上海3.991-0.0370.6266.437<0.001
江苏0.928-0.0370.3392.8480.002
天津0.080-0.0370.4290.2730.392
福建0.120-0.0370.3080.5110.305
浙江0.386-0.0370.5030.8400.200
新疆0.289-0.0370.5030.6470.259
山东0.234-0.0370.6260.4330.332
江西0.055-0.0370.6260.1480.441
河北0.028-0.0370.4290.1510.440
广东0.006-0.0370.3770.1130.455
内蒙古-0.023-0.0370.3390.0400.484
河南-0.015-0.0370.4290.0500.480
贵州0.075-0.0370.3080.3640.358
湖南-0.038-0.0370.429-0.0030.499
陕西-0.024-0.0370.3390.0400.484
广西0.105-0.0370.3390.4200.337
吉林0.138-0.0370.3390.5160.303
黑龙江0.102-0.0370.4290.3240.373
辽宁0.258-0.0370.4290.6880.246
山西0.339-0.0370.3770.9950.160
四川0.554-0.0370.3391.7460.040
重庆0.403-0.0370.4291.0260.152
甘肃0.500-0.0370.6260.8580.195
云南0.161-0.0370.3080.6430.260
湖北0.521-0.0370.3391.6470.050
安徽1.417-0.0370.5032.8900.002
青海2.163-0.0370.6263.516<0.001
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农村高龄老人生活质量的局部莫兰指数I检验结果

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莫兰指数分析地区IiE(Ii)sd(Ii)zp-value
全局莫兰检验0.432-0.0370.1044.524<0.001
局部莫兰检验北京4.102-0.0370.5038.226<0.001
上海3.991-0.0370.6266.437<0.001
江苏0.928-0.0370.3392.8480.002
天津0.080-0.0370.4290.2730.392
福建0.120-0.0370.3080.5110.305
浙江0.386-0.0370.5030.8400.200
新疆0.289-0.0370.5030.6470.259
山东0.234-0.0370.6260.4330.332
江西0.055-0.0370.6260.1480.441
河北0.028-0.0370.4290.1510.440
广东0.006-0.0370.3770.1130.455
内蒙古-0.023-0.0370.3390.0400.484
河南-0.015-0.0370.4290.0500.480
贵州0.075-0.0370.3080.3640.358
湖南-0.038-0.0370.429-0.0030.499
陕西-0.024-0.0370.3390.0400.484
广西0.105-0.0370.3390.4200.337
吉林0.138-0.0370.3390.5160.303
黑龙江0.102-0.0370.4290.3240.373
辽宁0.258-0.0370.4290.6880.246
山西0.339-0.0370.3770.9950.160
四川0.554-0.0370.3391.7460.040
重庆0.403-0.0370.4291.0260.152
甘肃0.500-0.0370.6260.8580.195
云南0.161-0.0370.3080.6430.260
湖北0.521-0.0370.3391.6470.050
安徽1.417-0.0370.5032.8900.002
青海2.163-0.0370.6263.516<0.001
), ArticleFig(id=1241342460706738496, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Table 6, caption=

Scores of the quality of life of the elderly in rural areas by province

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省份个人层面家庭层面社会层面政策层面生活质量得分
生理健康心理健康经济条件家庭关系居住条件社会交往生存环境养老保障医疗保障
北京14.35529.2085.6803.3346.0110.7541.4341.0003.11764.893
上海15.81724.6091.5532.7604.8180.4222.4101.6034.52658.517
江苏13.38025.8701.1493.0224.5000.2592.2170.3184.12954.844
天津14.49522.8021.8763.2704.6310.1212.1511.2233.92554.496
福建13.95224.1540.9252.9505.0450.1962.2650.2453.68453.416
浙江14.29823.4801.2543.1783.9390.3502.2220.6634.02453.408
新疆10.41124.5241.5192.8086.5080.1412.7610.1364.58053.387
山东13.64223.9271.1002.9413.9450.2392.3100.1934.51052.808
江西13.48623.7871.2633.1524.0470.3152.1750.2883.65852.171
河北13.09523.6421.4022.9604.3860.2752.0660.1074.07652.009
广东13.48623.0881.1303.0394.8010.3042.1290.4423.57851.995
内蒙古12.39323.1271.5793.0564.8740.3172.3130.4073.81051.876
河南13.47323.2670.8303.0823.5970.3202.3390.1554.28451.348
湖南13.10122.7460.8393.0584.1550.3672.3350.3423.63750.581
陕西13.46122.1031.3723.0294.6750.2751.9790.1383.23350.265
广西12.90622.5831.1892.9744.0100.3712.2620.1723.60650.072
吉林12.89422.1121.2043.1184.6990.1772.4290.1563.23350.021
黑龙江11.64522.4851.9102.8784.7560.3772.2950.0793.46449.889
辽宁13.45421.0950.9232.8244.8330.2021.9240.1653.67149.091
贵州13.34620.0180.8053.2704.9320.3382.3520.1633.94048.826
山西13.45620.8420.8712.9434.5640.2272.0570.1263.62748.713
四川12.71021.2900.8243.0973.9390.2182.2030.3533.83848.472
重庆11.74522.1350.8823.3843.3080.1922.0080.9133.72348.290
甘肃11.88020.8970.7673.2224.1360.1572.4100.1694.57248.210
云南12.50019.9840.7443.2204.2850.1142.4250.1934.10547.570
湖北12.93419.9600.8333.2384.0990.1932.1610.1733.83547.428
安徽12.37319.5570.6082.9103.4510.2772.6380.2074.45346.475
青海12.48113.6121.1232.0755.3370.4222.2590.2365.25342.799
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各省份农村高龄老人生活质量分项得分表

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省份个人层面家庭层面社会层面政策层面生活质量得分
生理健康心理健康经济条件家庭关系居住条件社会交往生存环境养老保障医疗保障
北京14.35529.2085.6803.3346.0110.7541.4341.0003.11764.893
上海15.81724.6091.5532.7604.8180.4222.4101.6034.52658.517
江苏13.38025.8701.1493.0224.5000.2592.2170.3184.12954.844
天津14.49522.8021.8763.2704.6310.1212.1511.2233.92554.496
福建13.95224.1540.9252.9505.0450.1962.2650.2453.68453.416
浙江14.29823.4801.2543.1783.9390.3502.2220.6634.02453.408
新疆10.41124.5241.5192.8086.5080.1412.7610.1364.58053.387
山东13.64223.9271.1002.9413.9450.2392.3100.1934.51052.808
江西13.48623.7871.2633.1524.0470.3152.1750.2883.65852.171
河北13.09523.6421.4022.9604.3860.2752.0660.1074.07652.009
广东13.48623.0881.1303.0394.8010.3042.1290.4423.57851.995
内蒙古12.39323.1271.5793.0564.8740.3172.3130.4073.81051.876
河南13.47323.2670.8303.0823.5970.3202.3390.1554.28451.348
湖南13.10122.7460.8393.0584.1550.3672.3350.3423.63750.581
陕西13.46122.1031.3723.0294.6750.2751.9790.1383.23350.265
广西12.90622.5831.1892.9744.0100.3712.2620.1723.60650.072
吉林12.89422.1121.2043.1184.6990.1772.4290.1563.23350.021
黑龙江11.64522.4851.9102.8784.7560.3772.2950.0793.46449.889
辽宁13.45421.0950.9232.8244.8330.2021.9240.1653.67149.091
贵州13.34620.0180.8053.2704.9320.3382.3520.1633.94048.826
山西13.45620.8420.8712.9434.5640.2272.0570.1263.62748.713
四川12.71021.2900.8243.0973.9390.2182.2030.3533.83848.472
重庆11.74522.1350.8823.3843.3080.1922.0080.9133.72348.290
甘肃11.88020.8970.7673.2224.1360.1572.4100.1694.57248.210
云南12.50019.9840.7443.2204.2850.1142.4250.1934.10547.570
湖北12.93419.9600.8333.2384.0990.1932.1610.1733.83547.428
安徽12.37319.5570.6082.9103.4510.2772.6380.2074.45346.475
青海12.48113.6121.1232.0755.3370.4222.2590.2365.25342.799
), ArticleFig(id=1241342460937425228, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=EN, label=Table 7, caption=

Distribution and Quantity Proportion of Provinces in Different Horizontal Regions

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水平区东部地区中部地区西部地区数量百分比（%）
高水平区北京、上海27.143%
中高水平区天津、江苏、福建、浙江、山东、河北、广东内蒙古、江西新疆1035.714%
中等水平区黑龙江、吉林、河南、湖南陕西、广西621.428%
中低水平区辽宁山西、安徽、湖北四川、重庆、贵州、云南、甘肃932.143%
低水平区青海13.571%
), ArticleFig(id=1241342461084225881, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342451747704841, language=CN, label=表7, caption=

各水平区省份分布及数量占比

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水平区东部地区中部地区西部地区数量百分比（%）
高水平区北京、上海27.143%
中高水平区天津、江苏、福建、浙江、山东、河北、广东内蒙古、江西新疆1035.714%
中等水平区黑龙江、吉林、河南、湖南陕西、广西621.428%
中低水平区辽宁山西、安徽、湖北四川、重庆、贵州、云南、甘肃932.143%
低水平区青海13.571%
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农村高龄老人生活质量评价及其空间分异
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王春玲
现代预防医学 | 健康与社会行为 2024,51(4): 691-696
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现代预防医学 | 健康与社会行为 2024, 51(4): 691-696
农村高龄老人生活质量评价及其空间分异
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王春玲
作者信息
  • 上海思博职业技术学院，上海 200120

    • 王春玲（1996—），女，硕士，高校教师，研究方向：养老保障、老年护理

通讯作者:

王春玲，E-mail：
Quality of life assessment of elderly in rural areas and its spatial variations
Chun-ling WANG
Affiliations
  • Shanghai Sipo Polytechnic, Shanghai 200120, China
出版时间: 2024-02-25 doi: 10.20043/j.cnki.MPM.202307398
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摘要
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目的

分析我国农村高龄老人的生活质量水平及其分异特征。

方法

基于中国健康与养老追踪调查 （CHARLS）2018年调查数据，从个人、家庭、社会、政策4个层面构建评价农村高龄老人生活质量的指标体系，采用熵值法进行客观赋权后计算生活质量得分，从人口特征、空间相关、空间分布3个层面对评价结果展开具体分析。

结果

婚姻状况（F=35.27，P<0.001）、受教育水平（F=10.80，P<0.001）对农村高龄老人生活质量影响显著，生活质量的分布具有空间相关性（I=0.432，P<0.001），质量水平处于中等、中低及低水平区的省份共计16个（占比57.142%），主要位于中西部地区。

结论

超半数省份的农村高龄老人生活质量在中等及以下水平区域，具有正向空间集聚特征，大致呈东高西低分布态势，应重点关注未婚、丧偶、受教育水平低、中西部省份的人群生活质量。

农村  /  高龄老人  /  生活质量  /  空间相关  /  熵值法
Objective

To study the quality-of-life level and its differentiation characteristics of elderly people in rural areas of China.

Methods

Based on the China Health and Retirement Longitudinal Study in 2018, we constructed an indicator system for evaluating the quality of life of rural elderly people from four levels: individual, family, society, and policy. The entropy method was used to objectively assign weights and calculate the quality-of-life score. The evaluation results were analyzed from three aspects: population characteristics, spatial correlation, and spatial distribution.

Results

Marital status (F=35.27, P<0.001) and educational level (F=10.80, P<0.001) had a significant impact on the quality of life of rural elderly people. The distribution of quality of life was spatially correlated (I=0.432, P<0.001). There are a total of 16 provinces (accounting for 57.142%) with quality levels in the middle, low, and low-level regions, mainly located in the central and western regions.

Conclusion

More than half of the rural elderly in provinces have a quality of life in areas with a moderate or lower level, exhibiting a positive spatial clustering feature, roughly showing a distribution pattern of high in the east and low in the west. Special attention should be paid to the quality of life of unmarried, widowed, low educated, and central and western provinces.

Rural areas  /  Elderly people  /  Quality of life  /  Spatial correlation  /  Entropy method
王春玲. 农村高龄老人生活质量评价及其空间分异. 现代预防医学, 2024 , 51 (4) : 691 -696 . DOI: 10.20043/j.cnki.MPM.202307398
Chun-ling WANG. Quality of life assessment of elderly in rural areas and its spatial variations[J]. Modern Preventive Medicine, 2024 , 51 (4) : 691 -696 . DOI: 10.20043/j.cnki.MPM.202307398
正文
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新时代发展背景对我国老龄事业发展提出了更高要求，习近平总书记强调：未来我国老龄工作的目标是“提高老年人生活和生命质量、维护老年人尊严和权利”[1]。如何保障高龄老人的健康水平和生活质量成为应对老龄化公共卫生事业的重要内容[2]。“生活质量”一词最早出现在《丰裕社会》中[3],是一个综合性概念，涉及物质、精神生活等各个方面[4]。农村高龄老人作为所有年龄段中最需要倾斜式照顾的人群，现有研究主要集中在健康状况、日常照料需求、赡养困境因素分析等方面[5-7]，而对其生活质量的研究相对较少，仅限于社会参与、居住距离、医疗服务等因素对生活质量的影响分析等[8-9]。鉴此，文章基于CHARLS 2018年调查对我国农村高龄老人生活质量展开评价，了解其生活质量水平、不同人口特征下的生活质量差异以及地理空间分异特征，以期为如何提升我国农村高龄老人生活质量提供路径参考。
1　对象与方法
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1.1　研究对象
使用中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS) 2018年数据，借鉴以往研究将高龄老人年龄界定为75岁及以上[10-11],剔除关键变量的缺失值后, 得到有效观测数1 804个。
1.2　研究方法
1.2.1　评价指标
生活质量是关系到个人、家庭、社会和政府的系统工程[12]，作为综合性概念，它既包括个体的个人层面和家庭层面，又包括个体在其中活动的社会环境和政府政策[13]。本文采用基于结构层面的系统方法，将不同指标归纳到个人层面、家庭层面、社会层面和政策层面中以全面评价生活质量，每个层面均有二级指标及相对应的问题来衡量，详见表1。
1.2.2　熵值法
为克服极端值的影响，对慢性病数量、家庭存款数额、家庭生活支出、房屋建筑面积、社交活动次数、养老金收入6个指标在STATA 15.1上进行1%分位的双边缩尾处理后取对数，缩尾后的变量描述如表2所示。
（1）建立评价指标的初始矩阵
假设有m个农村地区的高龄老人，每个人的生活质量评价指标体系由n个评价因子构成，由此建立农村高龄老人生活质量评价指标矩阵X：
（2）无量纲化处理
为消除量纲差异对评价结果的影响，先进行标准化处理：
x’ij表示无量纲化后的第i个农村高龄老人第j项评价指标的值，xmin和xmax分别表示x’ij的最小值和最大值。②式表示xj的指标越大，表示高龄老人的生活质量越高；③式表示xj的指标越小，表示高龄老人的生活质量越高。为避免后续求对数值无意义情况出现，对所有无量纲化结果都做平移（+1）处理[14]。
（3）计算指标的信息熵值和信息效用值
首先，根据无量纲化结果计算第j项指标下第i个老人的比重yij，建立比重矩阵Y={yij}m*n。
其次，计算第j项指标的信息熵值ej，其中k为常数，，m=1 804，代表所有观测数。
再次，根据熵值ej得出信息效用值dj，dj越大，对评价结果的重要性越大，指标权重也越大。
（4）计算评价指标权重
第j项指标的权重wj为：
经过上述步骤与运算，得到农村高龄老人生活质量评价指标的权重，相关指标权重和描述性统计如表3所示。
（5）计算样本评价值
Uij表示第i个样本第j项指标的得分；Zi表示第i个样本生活质量的总得分，是第i个样本在16个指标上的得分总和；n为指标个数；wj为第j个指标的权重。Zi值越大，表示生活质量越高。
1.3　统计学方法
采用STATA 15.1进行数据处理与分析，运用熵值法对农村高龄老人生活质量展开评价，之后借助多因素方差分析、莫兰指数、Jenks自然断点分级法探究农村高龄老人生活质量在人口特征、空间相关、空间分布上的差异，检验水准α=0.05。
2　结果
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2.1　人口特征分析
如表4，结果显示农村高龄老人生活质量在婚姻状况、受教育水平不同组间差异具有统计学意义（P<0.05）。未婚的农村高龄老人生活质量得分最低，比得分最高组（离异老人）低约11.686分。受教育水平越高，农村高龄老人生活质量得分越高；高中及以上受教育水平的农村高龄老人生活质量得分最高，比文盲组高9.907分、比小学组高6.679分、比初中组高4.460分。
2.2　空间分析
2.2.1　空间相关分析
通过STATA 15.1计算全局莫兰指数和局部莫兰指数，结果如表5所示，全局莫兰指数I对应的P值小于0.001，表示非常显著，可强烈拒绝无空间自相关性的原假设，即我国农村高龄老人生活质量在各省份间存在较强空间相关关系，对应的莫兰指数为0.432，指数大于0即存在正的空间相关关系；在局部莫兰指数检验中，P值小于0.05的省份有北京、上海、江苏、四川、安徽、青海，莫兰指数均为较大的正值，表明这些省份与邻近省份具有相关性，这与全局莫兰指数检验结果一致。
运用STATA 15.1绘制局部Moran散点图，如图1所示。H-H表示生活质量高的区域被同是高的区域包围，L-L表示生活质量低的区域被同是低的区域包围，H-L表示生活质量高的区域被低的区域包围，L-H表示生活质量低的区域被高的区域包围。结果显示我国农村高龄老人生活质量整体呈空间正相关性，散点大致落于一、三象限，第一象限散点最多，第三象限次之。北京、上海、江苏、广东等10个省份位于第一象限，是高生活质量的农村高龄老人分布集聚地区（H-H），即农村高龄老人生活质量高的区域与同是高生活质量的区域单元产生集聚；同样为正相关关系的黑龙江、辽宁、四川等9个省份位于第三象限，是低生活质量的农村高龄老人集聚地区（L-L）。湖南、陕西2省跨越了第一象限和第二象限，内蒙古、河南2省大致位于第四象限，说明其对周边省份的吸引能力有限。整体而言，我国农村高龄老人生活质量在空间分布上存在着较为明显的相关性、呈现空间集聚的特征。
2.2.2　空间分布分析
为进一步了解农村高龄老人生活质量的空间分布特征，通过ArcGis 14.1将全国地域数据与各省份农村高龄老人生活质量的矢量数据（表6）相连接，采用Jenks自然断点分级法将生活质量得分划分为五种类型：高水平区、中高水平区、中等水平区、中低水平区和低水平区，见表7。由于CHARLS调查地域选择和数据筛选的限制，西藏、宁夏、海南、香港、澳门和台湾的数据没有给出。
结果显示，农村高龄老人生活质量得分最高的是北京市（64.893），其次为上海市的（58.517），青海省农村高龄老人生活质量得分最低（42.799），与得分最高的北京相差22.094分，差距悬殊。分水平区域看，北京、上海2地处于高水平区，占比7.143%；中高水平区有天津、江苏、福建、浙江等10地，占比35.714%；中等水平区有黑龙江、吉林、河南、湖南、陕西、广西6个省份，占比21.428%；中低水平区有辽宁、山西、安徽、湖北、四川、重庆、贵州、云南、甘肃9个省份，占比32.143%；低水平区仅有青海1个省份，占比3.571%。生活质量得分处于中等、中低及低水平区的省份共计16个、合计占比57.142%，表明我国大多数省份农村高龄老人生活质量较低。整体而言，北京、上海地区农村高龄老人生活质量领跑全国、东部沿海省份紧跟其后、西部诸省仍在努力追赶，中等偏下水平的省份占比偏多需引起关注。
3　讨论
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3.1　农村高龄老人生活质量存在群组差异，应加强对丧偶、未婚、受教育水平低的人群关怀
丧偶和未婚的农村高龄老人因缺少伴侣陪伴，面临独自生活和缺乏有效社会支持的问题。对此，应鼓励其积极参与社交活动并定期组织志愿者、社工走访高龄老人，为其提供精神慰藉和其他实际帮助以疏解心理压力；受教育水平低的农村高龄老人由于缺乏知识和技能，更难理解和应对生活的变化，对此可为其提供简单的医疗保健知识、电子设备使用等培训，帮助其学习基本生活技能以提高生活自理能力和自信心。
3.2　农村高龄老人生活质量存在空间相关性且呈空间集聚的特征，北京、上海对周边地区有明显的正向溢出效应
北京、上海作为最发达城市，凭借良好的医疗条件、居住环境、养老设施等，生活质量遥遥领先其他省份且对周边地区产生了溢出效应，间接提升了周边地区农村高龄老人生活质量。应加强养老服务资源的配置和优化力度，实现区域内养老服务资源的最大化均衡利用；尤其对低低集聚的省份，需加强基础设施建设，提供更便利的交通、医疗等生活条件，探索移动服务模式以减少农村高龄老人因地理位置限制等而面临的生活困难。
3.3　农村高龄老人生活质量处于中等、中低及低水平区省份合计占比57.142%，空间分布大致呈东高西低的态势，自东向西阶梯式递减
针对东部地区农村高龄老人生活质量普遍较高的现实，可更多地提供老年心理咨询、老年交友等助力老年人实现自我方面的帮助；针对中西部地区农村高龄老人生活质量较低的情况，要通过政府资金支持和社会投入，提高养老设施、医疗卫生资源的覆盖率和质量，也要加大对农村高龄老人的救助和扶贫力度，更多帮助经济困难的农村高龄老人；充分发挥相邻省份间的空间相关作用，促进东中西部地区农村高龄老人生活质量的协调发展。
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2024年第51卷第4期
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doi: 10.20043/j.cnki.MPM.202307398
  • 接收时间：2023-07-24
  • 首发时间：2026-03-19
  • 出版时间：2024-02-25
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  • 收稿日期：2023-07-24
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    上海思博职业技术学院，上海 200120

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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
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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