2008-2018年中国老年人社区为老服务需求变化轨迹及影响因素潜变量增长模型分析  

Change trajectory and influencing factors of community-based elderly service demand among Chinese older residents:a latent growth modeling analysis 0n CHHLS data of 2008-2018

作　　者：姜茂敏 涂爱仙[2] JIANG Maomin;TU Aixian(Department of Public Administration,School of Public Afairs,Xiamen University Xiamen 361005,China;School of Management,Hainan Medical University,Haikou 571199,China)

机构地区：[1]厦门大学公共事务学院公共管理系,厦门361005 [2]海南医学院管理学院,海口571199

出　　处：《中国公共卫生》2024年第3期296-301,共6页Chinese Journal of Public Health

基　　金：国家自然科学基金(72274023);海南省自然科学基金高层次人才项目(720RC621);海南医学院引进人才科研启动项目(XRC202127)。

摘　　要：目的 分析2008-2018年中国老年人社区为老服务需求发展轨迹及影响因素,为发展多层次养老服务体系及促进健康老龄化的实现提供参考依据。方法 收集中国老年健康影响因素跟踪调查(CLHLS)2008、2011、2014和2018年相关数据,应用Mplus 8.3构建潜变量增长模型(LGM),采用无条件最小二乘法测量不包含协变量的社区为老服务需求的变化轨迹,并构建有条件的LGM分析2008-2018年中国老年人社区为老服务需求变化轨迹及影响因素。结果 中国老年人2008、2011、2014和2018年社区为老服务需求得分分别为(4.89±2.27)、(5.49±1.94)、(5.38±2.06)和(5.21±2.05)分,不同年份老年人社区为老服务需求得分差异无统计学意义(P> 0.05)。无条件LGM分析结果显示,二次函数无条件LGM为中国老年人社区为老服务需求发展轨迹的最优模型,且社区为老服务需求的初始水平显著> 0(截距=4.91,P <0.01),在2008-2011年呈上升趋势(斜率=0.38,P <0.01),而2011-2018年则呈下降趋势(斜率=-0.12,P <0.01)。有条件LGM分析结果显示,年龄(β=0.026)、婚姻状况的截距(β=0.260)、居住地(β=-0.567)和教育年限(β=0.224)对中国老年人社区为老服务需求的截距均有显著影响(均P <0.05);其中年龄和教育年限对斜率1均呈正向预测(β1=0.021,0.018,均P <0.05),对斜率2的预测均不显著(均P> 0.05);婚姻状况截距和斜率对斜率1均呈正向预测(β1=0.118,0.021,均P <0.05),对斜率2亦均呈正向预测(β2=0.146,0.049,均P <0.05);居住地对斜率1和斜率2均呈正向预测(β1=0.707,β2=0.046,均P <0.05)。结论 中国老年人2008-2018年社区为老服务需求呈曲线增长的变化轨迹,初始水平及增长速度均存在个体差异,年龄、婚姻状况、居住地和教育年限是中国老年人社区为老服务需求水平及增长速度的主要影响因素。Objective To investigate developmental trajectory and influencing factors of the demand for community-based elderly services among older residents during 2008-2018 in China for evidence-based improvement of elderly service system and promotion of healthy aging.Methods The data on 2454 residents aged 65 years and above at baseline were collected from four waves of the Chinese Longitudinal Healthy Longevity Survey(CLHLS)conducted in 2008,2011,2014,and 2018.The demand for community-based elderly services was assessed using an 8-point scale,representing eight care service items that could potentially be provided by communities.Mplus 8.3 was utilized to construct a latent growth modeling(LGM).The unconditional least squares method was employed to assess the trajectory of changes in demand for community-based elderly services without covariates,while a conditional LGM with covariates was developed to analyze the trajectory of changes in the demand and its influencing factors among the elderly population in China from 2008 to 2018.Results The mean overall scores for demand of community-based elderly services among surveyed elder residents in 2008,2011,2014,and 2018 were found to be 4.89±2.27,5.49±1.94,5.38±2.06 and 5.38±2.06 respectively with no significant difference observed between the yearly scores(P>0.05).The results of the unconditional LGM analysis results indicate that the quadratic function LGM without constraints is the optimal model for fitting developmental trajectories of item-specific demand for community-based elderly services among older adults from 2008 to 2018.The initial demand was significantly greater than 0(intercept=4.91,P<0.01).The constructed model revealed an upward trend from 2008 to 2011(slope=0.38,P<0.01),followed by a downward trend from 2011 to 2018(slope=-0.12,P<0.01).The results of conditional LGM analysis demonstrated that age(β=0.026),intercept of marital status(β=0.260),place of residence(β=-0.567),and years of education(β=0.224)significantly influenced the intercept of demand

关 键 词：社区为老服务需求 变化轨迹 影响因素 潜变量增长模型(LGM) 老年人 中国 

分 类 号：D669.3[政治法律—政治学] D669.6[政治法律—中外政治制度]