以交織性探討社會經濟和環境因素與臺灣民眾醫療服務利用之關係

Abstract

背景：影響醫療服務利用的因素多元，其中包括健康的決定因子以及空氣污染程度，空氣污染又與社會經濟政策有關聯，並且會因為不同社會、文化和經濟等結構，而對民眾造成不同程度的健康風險。本研究透過交織性（intersectionality）的概念，分析不同影響因素與醫療服務利用頻率之間的關係。 目的與方法：本研究以交織性作為框架，探討臺灣18歲以上民眾性別、年齡、月收入與PM2.5濃度的交織性，對臺灣民眾醫療服務利用之影響，並識別出高醫療服務利用的風險族群特性，採用中央研究院「學術調查研究資料庫」（Social Research Data Archive，簡稱SRDA）中「臺灣社會變遷基本調查計畫 2019 第七期第五次：科技與風險組」，以及行政院環保署「空氣品質監測報告（108年版）」部分資料進行次級資料分析。本研究選用2019年之資料，排除遺漏個案後，最後納入1691人。本研究使用SPSS 25統計軟體，並以羅吉斯迴歸和決策樹進行統計分析。 結果：本研究羅吉斯迴歸結果顯示，年齡與高醫療服務利用呈現正向關係，月收入與高醫療服務利用呈現負向關係，性別、PM2.5濃度與高醫療服務利用則呈現不顯著；然而透過決策樹CHAID分析，結果顯示，性別、年齡和月收入對於高醫療服務利用則有交織性影響，年齡66歲以上者是高醫療服務利用的最高風險族群，且年齡46至65歲且月收入20000元以下者是高醫療服務利用的次高風險族群，此外，在年齡18至45歲者當中，女性較男性有更高比例成為高醫療服務利用族群。 建議：依據本研究結果提出以下未來研究建議：1.納入更多影響醫療服務利用之因素探討，如對醫生的信任、對疾病預防的知識、有無慢性病史等。2.探討不同醫療服務利用類型，如門診、住院、急診等，更細緻的了解在交織性的框架之下，社會與環境因素對不同醫療服務利用類型有何影響。

Background: Multiple factors affect the utilization of medical services, such as determinants of health and air pollution problem. Air pollution is related to sociopolitical policies and poses different health risks to the population due to different social, cultural and economic structures. Through the concept of intersectionality, this study analyses the relationship between different factors and the frequency of health care utilization. Objectives and methods: This study uses the intersectionality as a framework to explore the influence of the intersectionality of gender, age, monthly income and PM2.5 concentration on people over 18 years of age on the health care utilization, to identify risk group of high frequency health care utilization. This study uses the 'Social Research Data Archive' (SRDA) of the Academia Sinica, 2019 Taiwan Social Change Survey (Round 7, Year 5): Technology and Risk Society and Environmental Protection Administration, Air Quality Annual Report of Taiwan, 2019.This study uses SPSS 25 , and logistic regression and decision tree. After excluding missing data, a total of 1691 people were finally included in the secondary data analysis. Results: The results of logistic regression showed that age was positively related to high frequency health care utilization, the monthly income was negatively related to high frequency health care utilization. Gender, PM2.5 concentration and high frequency health care utilization showed no significant difference. However, The results of CHAID analysis of decision tree showed that gender, age and monthly income are significant factors to high frequency health care utilization. Those who are over 66 years old are the highest risk group for high frequency health care utilization, followed by those who are aged 46 to 65 with a monthly income of less than NTD 20,000. Furthermore, among people aged 18 to 45, females are more likely to be frequent medical user than males. Suggestions: Based on the research results, research suggestions are proposed: 1. Include more factors affecting health care utilization , such as trust in doctors, knowledge of disease prevention, and history of chronic diseases. 2. Explore different types of health care utilization, such as outpatient, inpatient, emergency, to understand how socioeconomic and environmental factors affect different types of health care utilization under the framework of intersectionality.