臺灣樂齡學習需求人口與樂齡學習中心資源配置差異分析：應用空間群聚與地理可近性方法評估

A Study on Resource Allocation Comparing the Elderly Population in Need of Learning Centers and Elderly Learning Centers in Taiwan: Evaluating by Spatial Clustering and Geographic Accessibility

蔡明璋(Ming-Chang Tsai) ； 曾明性(Ming-Hseng Tseng) ； 吳慧卿(Hui-Ching Wu)

《人口學刊》 56期 (2018/06) Pp. 35-80

https://doi.org/10.6191/JPS.201806_56.0002

摘要

提升高齡者生活品質，除醫療照護，學習提高心智靈活，聯結社會網絡，有助活躍老化目標，因此，樂齡資源地理可近性是影響學習與社會參與的重要因素之一。為瞭解樂齡學習需求人口分佈與樂齡學習中心資源分佈供需配置妥適性，本文以臺灣本島為分析範圍，2009年及2017年樂齡學習中心為資源提供點，各村里55歲以上非失能人口為需求人口，運用空間群聚、線性相關、三階段地理可近性分析進行探討。研究發現樂齡學習需求人口疏密度與樂齡學習中心數量空間配置妥適性有待改善。首先，從空間群聚及相關分析發現，2017年資源供需線性相關性低於2009年，顯示縣市資源供給量雖增加，卻未與需求人口空間疏密趨勢相符。其次，三階段地理可近性分析發現，資源擁有率最低（臺北市、桃園市、新北市、嘉義市、新竹市），資源取得最短距離平均值最大（臺東縣、南投縣、花蓮縣、嘉義縣、宜蘭縣）存在縣市差異，顯示「一鄉鎮一中心」政策未將同縣市各村里需求人口取得資源距離差異納入評估。本文基於資料來源均能由政府開放資料取得，分析方法簡易、不須繁複路網分析等兩大考量，提出一套快速簡捷特性，針對社區資源（村里層級）地理可近性初步政策評估分析法，研究成果期能提供樂齡學習資源政策規劃參酌。

關鍵字

活躍老化 ； 樂齡學習人口 ； 樂齡學習中心 ； 空間群聚 ； 地理可近性

並列摘要

Improving the elderly's motivation to learn will help achieve the goals of ＂healthy aging＂ and ＂active aging.＂ Improving the quality of life of the elderly requires not only medical care but also increased opportunities for social participation through social activities aiming to improve mental flexibility, and linking social support networks, thereby enhancing mental health. Therefore, the geographic accessibility of learning resources is one of the most important factors influencing the elderly's ability to participate socially. In this study, methods of spatial clustering analysis and linear correlation were applied, and a new three-step method for assessing geographic accessibility was proposed. All data were derived from the Taiwanese government's open data of 2009 and 2017. The data on resource supply points were based on the number of elderly learning centers. The amount of the population in need of elderly learning centers was calculated from the non-disabled population aged 55 years or older in 2017. Results of this study showed an inconsistency between the density of the population in need of learning centers and the geographical distribution of elderly learning centers. Firstly, according to spatial clustering analysis and linear correlation, the correlation coefficient was lower in 2017 than in 2009. Secondly, the lowest resource ownership rates of elderly learning centers were in the larger cities (Taipei City, Taoyuan City, New Taipei City, Chiayi City, and Hsinchu City). The largest average values of the nearest distances to services were in the countryside (Taitung County, Nantou County, Hualien County, Chiayi County, and Yilan County). These results showed that policies should be redesigned based on different counties' situations. This study was based on open governmental data and proposed an easy assessment method with no need for complicated network analysis. Our methodology and results illustrate possibilities for elderly learning policy planning and implementation to reduce elderly learning centers' resourceallocation inequality and enhance the geographic accessibility of elderly learning.

並列關鍵字

active aging ； elderly learning population ； elderly learning center ； spatial clustering ； geographic accessibility

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