Institute for Hospital Management, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P.R. China.
Department of Medical Affairs, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences,Beijing, P.R. China.
Inquiry. 2023 Jan-Dec;60:469580231159751. doi: 10.1177/00469580231159751.
The demand for elderly care services (DECS) in Chinese Cities is one of the most concerned issues. The aim of this study was to understand the spatial and temporal evolution and external factors of DECS in Chinese cities and support the formulation of elderly care policies. We collected Baidu Index data for 287 prefecture-level and above cities and 31 provinces in China from January 1, 2012 to December 31, 2020. The Thiel Index was employed to describe the differences of DECS at different regional levels, and multiple linear regression was used to explore the external factors affecting DECS by calculating the variance inflation factor (VIF) to identify multicollinearity. The DECS of Chinese cities increased from 0.48 million in 2012 to 0.96 million in 2020, and the Thiel Index decreased from 0.5237 in 2012 to 0.2211 in 2020. Per capital GDP, number of primary beds, proportion of population aged 65 and over, number of primary care visits, and proportion of illiterate population over the age of 15 have significant influences on DECS ( < .05). DECS was on the rise in Chinese cities, with significant regional differences. At the provincial level, regional differences were influenced by level of economic development, primary care provision, aging population, educational attainment, and health status. It is suggested to pay more attention to DECS in small and medium-sized cities or regions, to strengthen primary care, and to improve the health literacy and health status of the elderly population.
中国城市对养老服务(DECS)的需求是最受关注的问题之一。本研究旨在了解中国城市养老服务的时空演变及外在因素,为养老政策的制定提供支持。我们收集了 2012 年 1 月 1 日至 2020 年 12 月 31 日期间中国 31 个省和 287 个地级市的百度指数数据。泰尔指数用于描述不同区域水平养老服务的差异,多元线性回归通过计算方差膨胀因子(VIF)来探索影响养老服务的外在因素,以识别多重共线性。中国城市养老服务从 2012 年的 0.48 万增长到 2020 年的 0.96 万,泰尔指数从 2012 年的 0.5237 下降到 2020 年的 0.2211。人均国内生产总值、基层床位数、65 岁及以上人口比例、基层医疗卫生机构诊疗人次数、15 岁及以上文盲人口比例对养老服务有显著影响( < .05)。中国城市养老服务呈上升趋势,区域差异显著。在省级层面上,区域差异受经济发展水平、基层医疗服务提供、人口老龄化、教育程度和健康状况的影响。建议关注中小城市或地区的养老服务,加强基层医疗服务,提高老年人口的健康素养和健康状况。