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Article(id=1321169744347123853, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169735128043598, articleNumber=null, orderNo=null, doi=10.11847/zgggws1146638, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1733932800000, receivedDateStr=2024-12-12, revisedDate=1742659200000, revisedDateStr=2025-03-23, acceptedDate=1747152000000, acceptedDateStr=2025-05-14, onlineDate=1792921013199, onlineDateStr=2026-10-25, pubDate=1752076800000, pubDateStr=2025-07-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792921013199, onlineIssueDateStr=2026-10-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792921013199, creator=13701087609, updateTime=1792921013199, updator=13701087609, issue=Issue{id=1321169735128043598, tenantId=1146029695717560320, journalId=1319373219989389464, year='2025', volume='41', issue='7', pageStart='769', pageEnd='896', issueExtLink='null', onlineDate='null', pubDate='1752076800000', pubDateStr='2025-07-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792921011000, creator='13701087609', updateTime=1792921011000, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=809, endPage=816, ext={EN=ArticleExt(id=1321169744590393486, articleId=1321169744347123853, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Research on the equity and spatial correlation of human resource allocation in China′s elderly care institutions from 2014 to 2022: a longitudinal study, columnId=1320427686514770171, journalTitle=Chinese Journal of Public Health, columnName=Survey and Report, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the staffing levels and personnel structure of elderly care institutions in China from 2014 to 2022, assess their equity and spatial distribution, and provide recommendations for optimizing the allocation of human resources in these institutions.

Methods

Panel data on employees in elderly care institutions from 31 provinces in China were collected. Changes in the proportion of male and female employees, the proportion of professional and technical personnel, and the proportion of employees aged 65 and older were calculated for each province from 2014 to 2022. The Theil index and Dagum Gini coefficient, weighted by the elderly population, were used to assess trends in equity and their decomposition effects. Global and local Moran′s I were employed to calculate the spatial clustering of human resources in elderly care institutions across China.

Results

The total number of human resources in elderly care institutions increased by 68.92%, but the number of staff per thousand elderly people showed a negative growth trend. In 2022, the proportion of employees with a bachelor′s degree or above was 8.42%, the proportion of professional and technical personnel was 75.23%, the proportion of employees aged 56 and older was 20.45%, and the proportion of female employees was 62.36%. The regional equity of human resource allocation in elderly care institutions improved, with the overall Theil index decreasing from 0.11 in 2014 to 0.05 in 2022, and the Dagum Gini coefficient decreasing from 0.41 in 2014 to 0.39 in 2022. Spatial autocorrelation analysis revealed a positive spatial clustering trend for human resources in elderly care institutions. The global Moran′s I increased from 0.273 in 2014 to 0.390 in 2022 (P < 0.01 for each year). Local Moran′s I scatter plots showed "high-high" and "low-low" clustering patterns among regions.

Conclusions

The total human resources in China′s elderly care institutions lag behind the growth of the elderly population. While equity has improved, there is a trend of positive spatial clustering. Future efforts should focus on both expanding capacity and improving quality, increasing the proportion of highly qualified and skilled personnel, and promoting inter-regional mobility of human resources in elderly care institutions.

, authors=Linning WANG, Sida WANG, Anqi JING, Wenbo LI, Xiaoyun LU, Yun LU, authorsList=Linning WANG, Sida WANG, Anqi JING, Wenbo LI, Xiaoyun LU, Yun LU, authorCompany=null, correspAuthors=Yun LU, authorNote=null, correspAuthorsNote=
LU Yun, E-mail:
, copyrightStatement=Copyright © 2025 Chinese Journal of Public Health. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321169749531283631, articleId=1321169744347123853, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=2014—2022年中国养老机构人力资源配置公平性及空间相关性, columnId=1320427686770622717, journalTitle=中国公共卫生, columnName=调查报告与分析, runingTitle=null, highlight=null, articleAbstract=
目的

分析2014—2022年我国养老机构人力资源配置水平和人员结构，从时空角度测算其公平性和聚集性，为优化我国养老机构人力资源配置提供建议。

方法

收集我国31个省份养老机构从业人员的面板数据，计算2014—2022年各省份养老机构年末从业人员的性别比例、专业技术人员占比、≥65岁从业人员占比的变化情况，以老年人口数量为权重计算泰尔指数和Dagum基尼系数变化趋势及分解效应，采用全局和局部莫兰指数计算我国养老机构人力资源在空间上的聚集程度。

结果

我国的养老机构人力资源总量增长率达68.92%，但每千名老人拥有的养老机构人力资源数量呈现负增长。2022年我国养老机构从业人员的大学本科及以上学历占比为8.42%，专业技术技能人员占比为75.23%，≥56岁人员占比为20.45%，女性人员占比为62.36%。我国养老机构人力资源配置区域公平性有所提升，总体泰尔指数由2014年的0.11下降至2022年的0.05，Dagum基尼系数由2014年的0.41下降至2022年的0.39。空间相关性分析结果显示，养老机构人力资源在空间上呈现正向聚集增加的趋势，全局莫兰指数从2014年的0.273上升至2022年的0.390（每年度均P<0.01），局部莫兰散点图显示区域间呈现“高–高”和“低–低”的聚集现象。

结论

我国养老机构人力资源配置总量落后于老年人口增长，公平性有所提升，但存在空间正向聚集趋势，未来兼顾扩容和提质，着力提升养老机构从业人员队伍素质、增加技术人员的占比、促进养老机构人力资源跨区域流动。

, authors=王琳宁, 王思达, 经安琪, 李文博, 陆筱筠, 路云*, *, authorsList=王琳宁, 王思达, 经安琪, 李文博, 陆筱筠, 路云, authorCompany=null, correspAuthors=路云, authorNote=

王琳宁（1999—），博士在读，研究方向：医药卫生政策

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路云，E-mail：
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王琳宁（1999—），博士在读，研究方向：医药卫生政策

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养老机构劳动力配置的逻辑框架及有效性研究——来自湖北省117家机构的调查证据[J]. 江西财经大学学报, 2021(4): 73-85., articleTitle=null, refAbstract=null), Reference(id=1321169757047476462, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169744347123853, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=7, rfOrder=6, authorNames=null, journalName=null, refType=null, unstructuredReference=李淑云, 宋久存, 李志强. 辽西地区养老护理人员现状调查[J]. 中国公共卫生, 2014, 30(8): 1069-1072., articleTitle=null, refAbstract=null), Reference(id=1321169757102002415, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169744347123853, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=8, rfOrder=7, authorNames=null, journalName=null, refType=null, unstructuredReference=Dagum C. 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注：图中Moran散点图的4个象限，代表局部空间聚集的四类模式：第1象限表示该区域为高值区且其相邻地域也为高值区域；第2象限表示该区域为低值区但其相邻地域为高值区域；第3象限表示该区域为低值区且其相邻地域为低值区域；第4象限表示该区域为高值区但其相邻地域为低值区域；其中第一和第三象限区域为空间正相关；第二和第四象限为空间负相关。

, figureFileSmall=z6wiiUAVvYwiJH+JhlSCUw==, figureFileBig=3OL0E0M4KIa0s4KS1JQiug==, tableContent=null), ArticleFig(id=1321169753943691483, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169744347123853, language=EN, label=Tab.1, caption=

Changes in the number of human resources among the areas of eastern, northeast, middle and west part in elderly care institutions in 2014 and 2022

, figureFileSmall=null, figureFileBig=null, tableContent=
地区省（自治区、直辖市）养老机构年末从业人员数/人每千名老人拥有的养老机构从业人员数/人
2014年2022年增长率/%2014年2022年增长率/%
东部
北京市133731874440.168.815.54−37.09
福建省433011327161.591.822.1719.17
广东省216353346754.692.952.69−8.95
海南省137714313.922.411.21−50.01
河北省188852897453.423.322.44−26.65
江苏省287524852268.763.633.11−14.19
山东省272774474464.042.942.57−12.67
上海市220433057138.6911.376.46−43.20
天津市6156688811.894.212.90−31.09
浙江省189223162267.124.333.15−27.24
东北部黑龙江省88751454363.862.992.57−13.94
吉林省725216307124.863.143.8221.68
辽宁省169532160627.453.852.51−34.73
中部安徽省863126315204.891.652.6560.90
河南省1881839537110.102.762.69−2.59
湖北省166202475748.963.382.54−24.83
湖南省120162389298.831.992.1910.23
江西省118191768249.613.412.93−14.26
山西省72161113154.252.812.16−23.34
西部甘肃省2640410855.611.381.20−13.33
广西壮族自治区612016460168.951.642.4248.18
贵州省26387676190.980.991.6062.23
内蒙古自治区6589844428.153.422.34−31.58
宁夏回族自治区8232606216.652.223.3550.59
青海省771751−2.592.251.21−46.53
陕西省76991261263.812.332.12−8.95
四川省179992625345.861.921.69−11.82
西藏自治区6271321110.694.356.0037.90
新疆维吾尔自治区4727650737.663.632.93−19.31
云南省36359576163.441.071.7159.39
重庆市82321487480.692.362.474.59
合计33345056324868.922.952.62−11.04
), ArticleFig(id=1321169754023383260, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169744347123853, language=CN, label=表1, caption=

2014和2022年养老机构人力资源数量变化

, figureFileSmall=null, figureFileBig=null, tableContent=
地区省（自治区、直辖市）养老机构年末从业人员数/人每千名老人拥有的养老机构从业人员数/人
2014年2022年增长率/%2014年2022年增长率/%
东部
北京市133731874440.168.815.54−37.09
福建省433011327161.591.822.1719.17
广东省216353346754.692.952.69−8.95
海南省137714313.922.411.21−50.01
河北省188852897453.423.322.44−26.65
江苏省287524852268.763.633.11−14.19
山东省272774474464.042.942.57−12.67
上海市220433057138.6911.376.46−43.20
天津市6156688811.894.212.90−31.09
浙江省189223162267.124.333.15−27.24
东北部黑龙江省88751454363.862.992.57−13.94
吉林省725216307124.863.143.8221.68
辽宁省169532160627.453.852.51−34.73
中部安徽省863126315204.891.652.6560.90
河南省1881839537110.102.762.69−2.59
湖北省166202475748.963.382.54−24.83
湖南省120162389298.831.992.1910.23
江西省118191768249.613.412.93−14.26
山西省72161113154.252.812.16−23.34
西部甘肃省2640410855.611.381.20−13.33
广西壮族自治区612016460168.951.642.4248.18
贵州省26387676190.980.991.6062.23
内蒙古自治区6589844428.153.422.34−31.58
宁夏回族自治区8232606216.652.223.3550.59
青海省771751−2.592.251.21−46.53
陕西省76991261263.812.332.12−8.95
四川省179992625345.861.921.69−11.82
西藏自治区6271321110.694.356.0037.90
新疆维吾尔自治区4727650737.663.632.93−19.31
云南省36359576163.441.071.7159.39
重庆市82321487480.692.362.474.59
合计33345056324868.922.952.62−11.04
), ArticleFig(id=1321169754119852253, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169744347123853, language=EN, label=Tab.2, caption=

Changes in the human resource structure among the areas of eastern, northeast, middle and west part of elderly care institutions in 2014 and 2022

, figureFileSmall=null, figureFileBig=null, tableContent=
地区省（自治区、直辖市）大学本科及以上占比/%专业技术技能人员占比/%≥56岁人员占比/%女性人员占比/%
2014年2022年2014年2022年2014年2022年2014年2022年
东部北京市14.049.6067.4482.429.2521.8463.8265.36
福建省11.029.0858.0673.988.2924.4245.9162.78
广东省9.5711.4761.2678.274.9616.4163.9070.64
海南省9.598.8758.2472.126.107.8359.3362.54
河北省7.975.8470.1280.964.3718.9155.7568.14
江苏省9.5311.0572.6081.3010.4619.2157.5959.28
山东省13.708.0971.1070.654.6432.1354.4970.93
上海市3.866.2447.7781.6912.5028.8071.3975.62
天津市10.0711.2859.1877.116.2223.6270.4262.70
浙江省7.076.9665.0693.0610.9032.0658.9472.98
东北部黑龙江省6.317.6745.7267.884.5715.7348.3953.18
吉林省9.383.3943.3466.313.3411.4337.4538.71
辽宁省13.927.2853.3467.277.3121.3458.4464.01
中部安徽省5.345.9948.4566.518.8519.2248.5548.86
河南省5.986.1347.7972.666.2819.9150.2853.85
湖北省7.106.9061.0173.266.0818.5155.7960.77
湖南省11.9711.3158.0773.685.6614.6550.6559.04
江西省3.684.4346.7068.524.4326.3738.0554.03
山西省10.288.9654.0673.904.5718.9945.1460.78
西部甘肃省15.9511.7151.1470.964.435.8446.8653.80
广西壮族自治区11.4914.7967.7680.285.2112.1070.9269.88
贵州省14.6711.4138.3264.132.3111.5746.7461.43
内蒙古自治区8.749.9855.1773.647.0014.9951.2456.94
宁夏回族自治区19.2014.2460.0279.555.228.8665.8671.57
青海省12.719.5944.2370.173.374.7948.2542.74
陕西省8.5211.8961.3773.095.4412.6452.4658.24
四川省7.288.0142.2765.537.1917.5745.2158.20
西藏自治区1.599.2437.8072.754.782.8867.6258.97
新疆维吾尔自治区8.238.1570.9383.711.679.7059.1967.33
云南省10.2613.1346.9375.764.5410.0356.0465.07
重庆市8.196.9748.4973.6911.2226.4047.3365.02
合计9.028.4258.2275.237.0120.4555.3262.36
), ArticleFig(id=1321169754212126942, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169744347123853, language=CN, label=表2, caption=

2014和2022年养老机构人力资源结构变化

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地区省（自治区、直辖市）大学本科及以上占比/%专业技术技能人员占比/%≥56岁人员占比/%女性人员占比/%
2014年2022年2014年2022年2014年2022年2014年2022年
东部北京市14.049.6067.4482.429.2521.8463.8265.36
福建省11.029.0858.0673.988.2924.4245.9162.78
广东省9.5711.4761.2678.274.9616.4163.9070.64
海南省9.598.8758.2472.126.107.8359.3362.54
河北省7.975.8470.1280.964.3718.9155.7568.14
江苏省9.5311.0572.6081.3010.4619.2157.5959.28
山东省13.708.0971.1070.654.6432.1354.4970.93
上海市3.866.2447.7781.6912.5028.8071.3975.62
天津市10.0711.2859.1877.116.2223.6270.4262.70
浙江省7.076.9665.0693.0610.9032.0658.9472.98
东北部黑龙江省6.317.6745.7267.884.5715.7348.3953.18
吉林省9.383.3943.3466.313.3411.4337.4538.71
辽宁省13.927.2853.3467.277.3121.3458.4464.01
中部安徽省5.345.9948.4566.518.8519.2248.5548.86
河南省5.986.1347.7972.666.2819.9150.2853.85
湖北省7.106.9061.0173.266.0818.5155.7960.77
湖南省11.9711.3158.0773.685.6614.6550.6559.04
江西省3.684.4346.7068.524.4326.3738.0554.03
山西省10.288.9654.0673.904.5718.9945.1460.78
西部甘肃省15.9511.7151.1470.964.435.8446.8653.80
广西壮族自治区11.4914.7967.7680.285.2112.1070.9269.88
贵州省14.6711.4138.3264.132.3111.5746.7461.43
内蒙古自治区8.749.9855.1773.647.0014.9951.2456.94
宁夏回族自治区19.2014.2460.0279.555.228.8665.8671.57
青海省12.719.5944.2370.173.374.7948.2542.74
陕西省8.5211.8961.3773.095.4412.6452.4658.24
四川省7.288.0142.2765.537.1917.5745.2158.20
西藏自治区1.599.2437.8072.754.782.8867.6258.97
新疆维吾尔自治区8.238.1570.9383.711.679.7059.1967.33
云南省10.2613.1346.9375.764.5410.0356.0465.07
重庆市8.196.9748.4973.6911.2226.4047.3365.02
合计9.028.4258.2275.237.0120.4555.3262.36
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Theil index and decomposition of human resource allocation in elderly care institutions in China from 2014 to 2022

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年份总泰尔指数组内组间东部东北中部西部
指数贡献率/%指数贡献率/%指数贡献率/%指数贡献率/%指数贡献率/%指数贡献率/%
20140.110.070.660.040.340.100.490.010.100.030.230.060.19
20150.100.060.620.040.380.090.510.010.100.030.210.050.19
20160.110.060.610.040.390.090.500.040.120.020.200.050.18
20170.100.060.610.040.390.090.500.040.120.020.200.040.19
20180.120.080.670.040.330.120.490.040.120.020.200.060.18
20190.080.060.690.030.310.090.480.050.110.010.230.050.18
20200.070.040.630.020.370.070.460.030.100.010.250.030.18
20210.050.040.680.020.320.060.460.020.090.000.250.030.19
20220.050.030.710.010.290.050.460.020.090.000.250.030.20
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2014—2022我国养老机构人力资源配置的泰尔指数及分解

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年份总泰尔指数组内组间东部东北中部西部
指数贡献率/%指数贡献率/%指数贡献率/%指数贡献率/%指数贡献率/%指数贡献率/%
20140.110.070.660.040.340.100.490.010.100.030.230.060.19
20150.100.060.620.040.380.090.510.010.100.030.210.050.19
20160.110.060.610.040.390.090.500.040.120.020.200.050.18
20170.100.060.610.040.390.090.500.040.120.020.200.040.19
20180.120.080.670.040.330.120.490.040.120.020.200.060.18
20190.080.060.690.030.310.090.480.050.110.010.230.050.18
20200.070.040.630.020.370.070.460.030.100.010.250.030.18
20210.050.040.680.020.320.060.460.020.090.000.250.030.19
20220.050.030.710.010.290.050.460.020.090.000.250.030.20
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Dagum Gini coefficient and its decomposition of human resource allocation in elderly care institutions in China from 2014 to 2022

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年份总体贡献率/%
区域内Gw区域间Gb超变密度Gt
20140.4122.3858.2319.39
20150.4122.0060.8917.12
20160.4122.2560.6117.14
20170.4021.8160.5017.69
20180.4121.7160.5317.76
20190.4022.2758.6919.04
20200.4021.8157.9820.21
20210.3922.3757.3320.30
20220.3923.0155.0821.91
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2014—2022年我国养老机构人力资源配置的Dagum基尼系数及分解

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年份总体贡献率/%
区域内Gw区域间Gb超变密度Gt
20140.4122.3858.2319.39
20150.4122.0060.8917.12
20160.4122.2560.6117.14
20170.4021.8160.5017.69
20180.4121.7160.5317.76
20190.4022.2758.6919.04
20200.4021.8157.9820.21
20210.3922.3757.3320.30
20220.3923.0155.0821.91
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Decomposition results of intra-regional and inter-regional Dagum Gini coefficients of human resource allocation in elderly care institutions in China from 2014 to 2022

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年份区域内Gw区域间Gb
东北东部中部西部东北部–东部东北部–中部东北部–西部东部–中部东部–西部中部–西部
20140.1960.3140.1820.4500.3560.2070.4350.3190.5880.468
20150.2190.3280.1460.3970.3660.2050.4230.3430.5930.425
20160.1200.3340.1560.4310.3160.1490.4640.3500.6010.436
20170.0850.3140.1560.4190.3020.1540.4580.3640.5870.413
20180.0850.3230.1510.4310.3030.1430.4700.3610.6030.430
20190.0660.3230.1940.4260.3240.1550.4280.3190.5900.460
20200.0330.3230.1970.4160.3210.1900.4160.2900.5830.504
20210.0670.3200.1920.4070.3440.2050.3700.2930.5650.476
20220.0900.3280.1960.4160.3460.2160.3670.2950.5520.473
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2014—2022我国养老机构人力资源配置Dagum基尼系数的区域内和区域间分解结果

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年份区域内Gw区域间Gb
东北东部中部西部东北部–东部东北部–中部东北部–西部东部–中部东部–西部中部–西部
20140.1960.3140.1820.4500.3560.2070.4350.3190.5880.468
20150.2190.3280.1460.3970.3660.2050.4230.3430.5930.425
20160.1200.3340.1560.4310.3160.1490.4640.3500.6010.436
20170.0850.3140.1560.4190.3020.1540.4580.3640.5870.413
20180.0850.3230.1510.4310.3030.1430.4700.3610.6030.430
20190.0660.3230.1940.4260.3240.1550.4280.3190.5900.460
20200.0330.3230.1970.4160.3210.1900.4160.2900.5830.504
20210.0670.3200.1920.4070.3440.2050.3700.2930.5650.476
20220.0900.3280.1960.4160.3460.2160.3670.2950.5520.473
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Global Moran′s I test results of human resource allocation in elderly care institutions in China from 2014 to 2022

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年份全局莫兰指数标准差Z值P值
20140.2730.1192.5630.010
20150.3010.1182.8380.004
20160.3150.1172.9620.003
20170.2920.1182.7460.006
20180.3460.1183.2050.001
20190.3330.1183.0990.002
20200.3780.1193.4610.001
20210.3910.1193.566<0.001
20220.3900.1193.560<0.001
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2014—2022年我国养老机构人力资源配置的全局莫兰指数检验结果

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年份全局莫兰指数标准差Z值P值
20140.2730.1192.5630.010
20150.3010.1182.8380.004
20160.3150.1172.9620.003
20170.2920.1182.7460.006
20180.3460.1183.2050.001
20190.3330.1183.0990.002
20200.3780.1193.4610.001
20210.3910.1193.566<0.001
20220.3900.1193.560<0.001
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2014—2022年中国养老机构人力资源配置公平性及空间相关性
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王琳宁 , 王思达 , 经安琪 , 李文博 , 陆筱筠 , 路云 *, *
中国公共卫生 | 调查报告与分析 2025,41(7): 809-816
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中国公共卫生 |调查报告与分析 2025 , 41 (7) : 809 -816
2014—2022年中国养老机构人力资源配置公平性及空间相关性
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王琳宁, 王思达, 经安琪, 李文博, 陆筱筠, 路云*, *
作者信息
  • 中国药科大学国际医药商学院，南京 211198
通讯作者:
路云，E-mail：
作者简介:

王琳宁（1999—），博士在读，研究方向：医药卫生政策

Research on the equity and spatial correlation of human resource allocation in China′s elderly care institutions from 2014 to 2022: a longitudinal study
Linning WANG, Sida WANG, Anqi JING, Wenbo LI, Xiaoyun LU, Yun LU
Affiliations
  • School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing 211198, China
    • Corresponding Author:
    LU Yun, E-mail:
出版时间: 2025-07-10 doi: 10.11847/zgggws1146638
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摘要
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目的

分析2014—2022年我国养老机构人力资源配置水平和人员结构，从时空角度测算其公平性和聚集性，为优化我国养老机构人力资源配置提供建议。

方法

收集我国31个省份养老机构从业人员的面板数据，计算2014—2022年各省份养老机构年末从业人员的性别比例、专业技术人员占比、≥65岁从业人员占比的变化情况，以老年人口数量为权重计算泰尔指数和Dagum基尼系数变化趋势及分解效应，采用全局和局部莫兰指数计算我国养老机构人力资源在空间上的聚集程度。

结果

我国的养老机构人力资源总量增长率达68.92%，但每千名老人拥有的养老机构人力资源数量呈现负增长。2022年我国养老机构从业人员的大学本科及以上学历占比为8.42%，专业技术技能人员占比为75.23%，≥56岁人员占比为20.45%，女性人员占比为62.36%。我国养老机构人力资源配置区域公平性有所提升，总体泰尔指数由2014年的0.11下降至2022年的0.05，Dagum基尼系数由2014年的0.41下降至2022年的0.39。空间相关性分析结果显示，养老机构人力资源在空间上呈现正向聚集增加的趋势，全局莫兰指数从2014年的0.273上升至2022年的0.390（每年度均P<0.01），局部莫兰散点图显示区域间呈现“高–高”和“低–低”的聚集现象。

结论

我国养老机构人力资源配置总量落后于老年人口增长，公平性有所提升，但存在空间正向聚集趋势，未来兼顾扩容和提质，着力提升养老机构从业人员队伍素质、增加技术人员的占比、促进养老机构人力资源跨区域流动。

养老机构  /  人力资源  /  空间分布  /  公平性
Objective

To analyze the staffing levels and personnel structure of elderly care institutions in China from 2014 to 2022, assess their equity and spatial distribution, and provide recommendations for optimizing the allocation of human resources in these institutions.

Methods

Panel data on employees in elderly care institutions from 31 provinces in China were collected. Changes in the proportion of male and female employees, the proportion of professional and technical personnel, and the proportion of employees aged 65 and older were calculated for each province from 2014 to 2022. The Theil index and Dagum Gini coefficient, weighted by the elderly population, were used to assess trends in equity and their decomposition effects. Global and local Moran′s I were employed to calculate the spatial clustering of human resources in elderly care institutions across China.

Results

The total number of human resources in elderly care institutions increased by 68.92%, but the number of staff per thousand elderly people showed a negative growth trend. In 2022, the proportion of employees with a bachelor′s degree or above was 8.42%, the proportion of professional and technical personnel was 75.23%, the proportion of employees aged 56 and older was 20.45%, and the proportion of female employees was 62.36%. The regional equity of human resource allocation in elderly care institutions improved, with the overall Theil index decreasing from 0.11 in 2014 to 0.05 in 2022, and the Dagum Gini coefficient decreasing from 0.41 in 2014 to 0.39 in 2022. Spatial autocorrelation analysis revealed a positive spatial clustering trend for human resources in elderly care institutions. The global Moran′s I increased from 0.273 in 2014 to 0.390 in 2022 (P < 0.01 for each year). Local Moran′s I scatter plots showed "high-high" and "low-low" clustering patterns among regions.

Conclusions

The total human resources in China′s elderly care institutions lag behind the growth of the elderly population. While equity has improved, there is a trend of positive spatial clustering. Future efforts should focus on both expanding capacity and improving quality, increasing the proportion of highly qualified and skilled personnel, and promoting inter-regional mobility of human resources in elderly care institutions.

elderly care institutions  /  human resources  /  spatial distribution  /  equity
王琳宁, 王思达, 经安琪, 李文博, 陆筱筠, 路云. 2014—2022年中国养老机构人力资源配置公平性及空间相关性. 中国公共卫生, 2025 , 41 (7) : 809 -816 . DOI: 10.11847/zgggws1146638
Linning WANG, Sida WANG, Anqi JING, Wenbo LI, Xiaoyun LU, Yun LU. Research on the equity and spatial correlation of human resource allocation in China′s elderly care institutions from 2014 to 2022: a longitudinal study[J]. Chinese Journal of Public Health, 2025 , 41 (7) : 809 -816 . DOI: 10.11847/zgggws1146638
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随着我国社会老龄化程度越来越高，在“银发时代”与“小家庭”模式的交叠期，以大家庭为核心的传统家庭成员照护已经无法满足大量独居老人的日间照料、看护服务等养老需求[1–2]。专业化、个性化的养老服务机构，能够更好地满足老年人的养老需求，同时也缓解了家庭的照护压力[3]。然而，养老服务工作劳动强度大、沟通难度高、社会地位低等因素导致养老服务从业人员数量少且流动性高，人力资源缺口成为制约我国养老机构发展的瓶颈[4]。有关老年人养老服务的卫生人力资源研究采用护士数、医生数等宏观指标，无法精准评价专门为老年人提供养老服务的人力水平[5]。另有部分学者聚焦单一地区的养老人力资源，对养老机构进行小样本数据调研分析，缺乏全国层面的大样本宏观数据分析[6–7]。本研究选取2014—2022年中国内地31个省（自治区、直辖市）的跨期面板数据，从劳动素养、专业程度、年龄结构、性别比例等维度分析养老机构人力资源结构变化，利用泰尔指数和Dagum基尼系数分析公平性，采用全局和局部莫兰指数研究空间聚集特征。
1　资料与方法
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1.1　资料来源
选择31个省级行政区（自治区、直辖市）为分析样本，根据国家统计局对省份区域的划分标准，将其划分为东、中、西与东北部4个区域，各包含10、6、12和3个省份。养老机构从业人员数量及结构数据来自2015—2023年发布的《中国民政统计年鉴》。老年人口指≥65岁人口数量，数据来源于2015—2023年的《中国人口普查年鉴》。根据《中国民政统计年鉴》的界定口径，养老机构包括社会福利院、农村特困人员救助供养机构和其他各类养老机构。本研究所使用的数据来源均为公开数据。
1.2　方法
1.2.1　泰尔指数
泰尔指数是衡量区域内和区域间均衡性的熵值指标，泰尔指数的数值越大表明越不均衡，总体泰尔指数可以被分解为区域内的组内泰尔指数和区域间的组间泰尔指数。本研究的泰尔指数计算公式为：
$ \begin{split}{T}_{{P}}= & {T}_{{WR}}+{T}_{{BR}}= \\ &\sum\nolimits_{\mathrm{i}}\left(\frac{{{Y}}_{\mathrm{i}}}{{{Y}}}\right){T}_{{p}}+\sum\nolimits_{\mathrm{i}}\left(\frac{{{{Y}}}_{\mathrm{i}}}{{{Y}}}\right)\mathrm{l}\mathrm{o}\mathrm{g}\left(\frac{{{Y}}_{\mathrm{i}}/{{Y}}}{{{P}}_{\mathrm{i}}/{{P}}}\right)\end{split} $
$ {{T}}_{{P}} $为总体泰尔指数，$ {{T}}_{{WR}} $为组内泰尔指数，$ {{T}}_{{B}{R}} $为组间泰尔指数，Y代表养老机构年末从业人员人数，P代表≥65岁老年人口数量。
1.2.2　Dagum基尼系数
基尼系数由 Camilohe和Dagum（1997）提出，是常见的测算区域不平等度的方法，且解决了传统基尼系数不可进行地区分解的问题[8]。Dagum基尼系数可以分解为组内系数、组间系数和超变密度系数，系数越大说明区域公平性越差。组内系数反映各地区内部水平的差距、组间系数反映各地区之间水平的差距、超变密度系数反映各地区交叉重叠现象[9]。使用Dagum基尼系数测度养老机构人力资源水平，弥补了泰尔指数无法考虑样本之间交叉重叠的缺陷，能够更好地识别地区差异。本研究的Dagum基尼系数的计算及分解，参照文献进行[10]。
1.2.3　莫兰指数
泰尔指数和基尼指数侧重于度量属性变量的区域差异，不能分析空间分布格局的差异；而全局和局部莫兰指数因为集合了空间权重，可以对资源配置的空间异质性和聚集性进行定量分析。全局莫兰指数用来表示所有省份养老机构人力资源在空间上与周边省份的平均关联性。其取值–1～1，为正数时表示所有省份养老机构人力资源呈现空间分布的正向聚集，且数值越大正向聚集效应越强；当其为负数时，则结论相反；而当其为0时表示所有省份养老机构人力资源在空间上随机分布。全局莫兰指数的计算式和显著性Z检验如下：
$ I=\dfrac{{\displaystyle\sum }_{i=1}^{N}{\displaystyle\sum }_{j=1}^{N}{w}_{ij}\left({x}_{i}-\tilde {x}\right)\left({x}_{j}-\tilde {x}\right)}{{S}^2{\displaystyle\sum }_{i=1}^{N}{\displaystyle\sum }_{j=1}^{N}{w}_{ij}} $
$ Z=\frac{I-E（I）}{\sqrt{var（I）}} $
其中N为本研究纳入的省份个数为31，$ {w}_{ij} $为设定的空间权重矩阵，$ {x}_{i} $为统计量数值，$ \tilde{x} $为统计量的均值。本研究空间权重矩阵设置为31个省级行政区的地理相邻空间权重矩阵，当2个省份在地理上为相邻地区时矩阵元素设置为1，不相邻时为0。由于海南省在地理位置上与其余省份无接壤，但其与广东省经济贸易往来密切，参考已有发表文献将海南省在空间相邻矩阵中设置为与广东省相邻[11]。局部莫兰指数是全局莫兰指数的进一步分解，是从局域空间角度来探析某一省域单元与其邻近省域养老机构人力资源在空间上的关联状态和异质性。局部莫兰指数的计算公式如下。$ {x}_{i} $为统计量数值，$ \tilde{x} $为统计量的均值，$ {w}_{ij} $为空间权重矩阵，与全局莫兰指数一样使用地理相邻空间矩阵：
$ {I}_{i}=\frac{\left({x}_{i}-\tilde{x}\right){\displaystyle\sum }_{j=1}^{n}{w}_{ij}\left({x}_{j}-\tilde{x}\right)}{{\displaystyle\sum }_{i=1}^{n}{\left({x}_{i}-\tilde{x}\right)}^{2}} $
局部莫兰指数可通过莫兰散点图进行可视化呈现，莫兰散点图中的每个点对应每个省份的局部莫兰指数值。横轴表示每个省份养老机构人力资源经过标准化处理后的值，计算公式为$ Z=\dfrac{{X}_{i}-\overline{x}}{S} $；纵轴表示每个省份的空间滞后值，计算公式为$ \displaystyle\sum_{j=1}^NW_{ij}Z_j $
1.3　统计分析
数据资料的整理、录入、养老机构人力资源配置水平分析通过Excel 2022软件完成，运用Stata 17.0软件测算泰尔指数及Dagum基尼系数，并进行空间相关性分析。
2　结　果
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2.1　养老机构人力资源的数量变化（表1）
2014年养老机构年末从业人员人数为333 450人，2022年增长至563 248人，增长率达68.92%，但青海出现了负增长。当考虑老年人口的增长，以每千名老人计算拥有的养老机构从业人员数从2014年的2.95下降至2.62，增长率为–11.04%，仅有10个省份呈现正增长。表明我国的养老机构人力资源虽然在总体数量上有所增加，但增长的速度落后于老年人口的增长数量。
2.2　养老机构人力资源的结构变化（表2）
从劳动素养上看，我国养老机构从业人员中拥有大学本科及以上学历的2014年为30 082人，2022年为47 408人，虽然总量有所提升，但占比有所下降，2014年占比为9.02%，2022年占比为8.42%。从专业程度上看，专业技术技能人员占比有所提升，从2014年的58.22%提升至75.23%。从年龄结构上看，≥56岁从业人员从2014年的7.01%上升至20.45%。从性别比例上看，女性从业人员多于男性，2014年的女性占比为55.32%，2022年为62.36%。
2.3　养老机构人力资源配置区域公平性分析
2.3.1　泰尔指数
以我国≥65岁人口数量作为泰尔指数的权重，测算我国养老机构人力资源配置的公平性现状（表3）。总泰尔指数从2014年的0.11下降到2022年的0.05，说明基于老年人口数量来看，我国养老机构人力资源配置的区域公平性有所提升。从分解效应看，组内泰尔指数的贡献率高于组间泰尔指数，东部区域的贡献率高于其他区域。
2.3.2　Dagum基尼系数（表4）
由于泰尔指数未考虑区域交叉的扰动影响，进一步采用Dagum基尼系数测度我国养老机构人力资源配置的区域均衡性。结果与泰尔指数呈现结果相似，观察期内我国养老机构人力资源配置的总体Dagum基尼系数有一定的下降趋势，但下降的幅度不明显，由2014年的0.41降低至2022年的0.39，进一步说明我国养老机构人力资源的区域配置均衡性有小幅提升。与泰尔指数显示的结果不同的是，Dagum基尼系数显示区域配置的不均衡性主要来自区域间的差异，所有年份的贡献率均>55%，区域内和区域交叉的影响水平均约为20%。
2.3.3　Dagum基尼系数分解（表5）
将Dagum基尼系数进一步按区域分解来观察区域内部不同省份养老机构人力资源的配置公平性差异。结果显示，观察期内大部分年份的区域内基尼系数由高到低分别为西部、东部、中部、东北部。从年份趋势变化来看，其中东北和东部的区域内基尼系数随年份波动不大，中部有所升高，西部近年开始呈现“倒V”型变化趋势。区域间交叉的Dagum基尼系数结果显示，所有年份“东部–西部”交叠影响最大，“东北部–中部”交叠影响最小，其余区域的交叠影响随年份波动变化。
2.4　空间相关性分析
2.4.1　全局空间相关性
进一步细化研究区域分级，从省份层面利用空间相邻权重测算全局莫兰指数。表6结果显示，我国养老机构人力资源配置的全局莫兰指数从2014年的0.273上升至2022年的0.390，且均至少在1%的水平下通过了显著性检验。表明我国的养老机构人力资源的区域分布不是随机的，存在显著聚集效应，且聚集性有所增强。
2.4.2　局部空间相关性（图1）
局部莫兰指数能够进一步探究空间聚集效应，即受到周围省份的影响情况，为了更直观地展示局部莫兰指数的结果，按年度绘制了局部莫兰指数的散点图，本研究仅展示2014、2017、2020和2022年的情况。4个年份的莫兰散点图结果均显示出一、三象限聚集的态势，即“高–高”和“低–低”区域聚集，印证了上述全局莫兰指数的结果，表明我国养老机构人力资源高的省份同样被养老机构人力资源高的省份包围，而养老机构人力资源低的省份同样被养老机构人力资源低的省份包围。
3　讨　论
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本研究结果显示，我国养老机构人力资源数量总体上升，但仍有结构优化空间。我国养老机构人力资源配置的绝对数量从2014年的333 450人增长至2022年的563 248人，增长率达68.92%。但其绝对数量的显著扩容仍然无法匹配老年人口的增长速度，2014年每千名老人拥有的养老机构从业人员数为2.95，2022年每千名老人拥有的养老机构从业人员数下降至2.62，揭示了我国人口结构同时面临老年人口增加和适龄劳动力减少的双重压力，已有研究与此结论相似[12]。从人力资源结构来看，养老机构从业人员整体呈现学历低、女性多、老龄化的特征，但从业人员的专业化水平提升显著，2014年专业技术技能人员占比仅为58.22%，2022年提升至75.23%。未来我国养老机构人力资源的建设要兼顾“扩容”和“提质”，提升总量和提高质量双管齐下。扩容方面重点在“开源”，各地政府要加强人才队伍建设，支持城乡未继续升学的初高中毕业生、农村转移就业劳动者、城镇登记失业人员等从事养老服务业。“提质”方面重在结构性调整，加强养老机构从业人员的专业技术水平等级建设，可在《养老护理员国家职业技能标准（2019年版）》设置的5个职业技能等级基础上，鼓励具备条件的养老机构结合实践技能水平，在高级技师等级之上增设特级技师和首席技师，在初级工之下补设学徒工，进一步细化专业技术水平能力评级，拓宽养老服务从业人员的成长通道。此外政府和企业还可对高学历、高技术养老服务人才到养老机构就业的，单设入职奖励基金，解决人才落户、教育和医疗等需求。
按老年人口数量计算的泰尔指数和Dagum基尼系数的结果均显示，2014—2022年我国养老机构人力资源配置的公平性得到提升。在中共中央、国务院《“健康中国2030”规划纲要》的长期规划下，为应对老年人口远期增长，《“十四五”国家老龄事业发展和养老服务体系规划》《全国老龄办关于加强养老服务人才队伍建设的意见》均关注区域均衡发展，指出要促进养老服务人才供给不足的地区与劳务输出大省之间的人力资源合作，这些政策从顶层设计上加强了对养老机构人力资源在区域之间流动配置的宏观引领和调控。此外，各地区积极落实国家政策指导方针也在客观上促进了养老机构人力资源配置的公平性，例如，为响应《国务院办公厅关于推进养老服务发展的意见》（国办发〔2019〕5号）对推动养老服务供给结构不断优化与提高养老服务质量的部署，武汉市、郑州市、青岛市等地区相继出台《养老机构管理办法》，明确指出养老机构要重视养老服务专业人才队伍建设工作，截至2024年1月，全国所有省份均已出台基本养老服务实施方案和清单，各地因地制宜出台吸引养老服务从业人员的政策，已经一定程度上促进了我国养老机构人力资源配置的区域公平性。但Dagum基尼系数的分解结果显示，西部与东部区域内部的养老机构人力资源配置不公平性最大，主要原因在于这两个区域内部各省份的发展水平存在较大差异，如西部人口大省四川的老年人数量显著多于其他西部省份，东部区域的福建省老年人口数量则处于东部的较低水平；而中部区域的劳动人口增长和老年人口增加较为平均，区域差异性较小，养老需求和养老机构人力资源较为匹配。
虽然我国养老机构人力资源配置的公平性有所提升，但人力资源配置在空间上存在正向聚集的效应。通过构建空间相邻矩阵测度每一年份我国养老机构人力资源配置的全局莫兰指数和局部莫兰指数，结果显示全局和局部空间效应均存在正向聚集，表现为省份之间的显著正向相关，即我国养老机构人力资源配置高的省份相邻省份的养老机构人力资源配置也较高，而养老机构人力资源配置低的省份相邻省份的养老机构人力资源配置也较低。全局莫兰指数从2014年的0.273增长至2022年的0.390，提示了空间正向聚集在时序上存在增强趋势。以散点图呈现局部莫兰指数的相关性检验结果，发现散点多分布在一、三象限，即“高–高”聚集和“低–低”聚集，进一步验证了全局莫兰指数的检验结果。我国养老机构人力资源配置的聚集现象可能与养老机构的空间分布有关，如已有学者通过研究发现河南省养老服务机构在空间上基本也呈集聚分布特征[13]。同时，这样的现象与其他的卫生人力资源分布也相似，比如医药领域的卫生人才、护理人才、全科医生等人力资源也呈现了随年份正向聚集效应逐渐增强的时空分布特征[14–15]。根据卫生规划理论，由于我国幅员辽阔，无法做到省份间发展绝对均衡，应在一个特定的区域范围内综合区位供需情况合理配置养老机构和人力资源，从而在区域内发展形成一定的空间聚集性。区域化联合发展也是一种较好的发展模式，应该主动把握养老机构人力资源聚集的规模效应，如以长三角、珠三角等区域为综合试点地区，通过建立养老人力资源培养区域联合体，促进区域内的人力资源流动。

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2025年第41卷第7期
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doi: 10.11847/zgggws1146638
  • 接收时间：2024-12-12
  • 首发时间：2026-10-25
  • 出版时间：2025-07-10
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  • 收稿日期：2024-12-12
  • 修回日期：2025-03-23
  • 录用日期：2025-05-14
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    中国药科大学国际医药商学院，南京 211198

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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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