日本建築学会環境系論文集
Online ISSN : 1881-817X
Print ISSN : 1348-0685
ISSN-L : 1348-0685
住環境によるソーシャル・キャピタルの醸成が要介護リスクに与える影響の階層構造モデル
宮﨑 笑里安藤 真太朗伊香賀 俊治
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ジャーナル フリー

2021 年 86 巻 782 号 p. 399-408

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In Japan, healthcare and nursing care expenses for the elderly are increasing year by year, and extending healthy life expectancy is therefore desirable. Social capital (SC) is a measure of the degree of social interaction and has been gaining attention as a health-related Previous studies have shown that few people have poor subjective health in areas with good SC scores. Thus, a living environment that fosters SC might facilitate the improvement and maintenance of health status. The purpose of this study was to clarify the effects of living environment, such as facilities and community outreach efforts, on nursing care risk as mediated by SC. A questionnaire survey was carried out for 3 weeks from September to October 2018.Participants were adults in three elementary school districts in Niihama City, Ehime Prefecture, Japan Survey contents included SC, neighborhood environment, residential environment, and health status. A total of 7,220 questionnaires were distributed, and 2,693 were correctly completed (valid response rate = 37.3%) The number of samples used for analysis was 2,053.

Of respondents over 65 years of age, 26.8% were at high risk of needing long-term care. Mann-Whitney U test was performed to verify the impact of SC on risk of needing long-term care. Logistic regression analysis was performed using participant attributes such as sex and household composition as moderator effects. The aim was to clarify the effects of living environment such as facilities and community outreach on the risk of needing long-term care via SC.

The analysis model considered factors including age, sex, educational attainment, and length of residence in the area.

The odds ratio (OR) of requiring long-term care for low SC compared with high SC was 1.91 (p <0.01). Next, I examined the relationship between SC and the living environment based on the “Facilities” and “Activity participation,” or “Communication” items of living environment. The OR of SC for neighborhood environment factors ranged from 1.3 to 2.4 (p <0.05), and the OR of SC for housing environment factors ranged from 1.3 to 3.0 (p <0.05).

Finally, path analysis was performed. An index for the housing and neighborhood environments was determined as the total score of the items that showed the relationships between SC and the housing and neighborhood environments, as analyzed previously. The determination coefficient for the risk of needing long-term care was 0.19.

In summary, the facilities of the living environment affected SC directly or via the community items and finally affected the risk of needing long-term care. A study limitation is that the results were based solely on data that covered one target area. In the future, we plan to conduct questionnaire surveys in other regions using statistical data and to analyze responses considering regional characteristics.

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