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  • 1.
    Manasatchakun, Pornpun
    et al.
    School of Healthcare and Social Welfare, Mälardalen University, Eskilstuna, Sweden & Boromarajonani College of Nursing Udon Thani, Udon Thani, Thailand.
    Chotiga, Pleumjit
    Boromarajonani College of Nursing Chiang Mai, Chiang Mai, Thailand.
    Hochwälder, Jacek
    School of Healthcare and Social Welfare, Mälardalen University, Eskilstuna, Sweden.
    Roxberg, Åsa
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI). School of Healthcare and Social Welfare, Mälardalen University, Eskilstuna, Sweden & VID Specialized University, Bergen, Norway .
    Sandborgh, Maria
    School of Healthcare and Social Welfare, Mälardalen University, Eskilstuna, Sweden.
    Asp, Margareta
    School of Healthcare and Social Welfare, Mälardalen University, Eskilstuna, Sweden.
    Factors associated with Healthy Aging among older persons in Northeastern Thailand2016In: Journal of Cross-Cultural Gerontology, ISSN 0169-3816, E-ISSN 1573-0719, Vol. 31, no 4, p. 369-384Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to describe factors associated with perceived health and healthy aging among older people in northeastern Thailand. Thailand’s aging population is growing and facing an increasing old-age dependency ratio. Northeastern Thailand, known as Isan, is a region in which the number of older residents is projected to grow rapidly. Older people in this region are likely to confront great threats to their health and well-being. These issues require appropriate attention and actions to promote healthyaging. However, healthy aging in this region has not been studied. A cross-sectional study was conducted on a sample of 453 older people, aged 60 years or older. Participants completed the Healthy Aging Instrument (HAI) and provided relevant demographic characteristics. Mann-Whitney U tests, Kruskal-Wallis tests and multiple regression models were used to analyze the data. Through comparative analyses, significant differences in HAI scores were observed for the following factors: marital status, residential area, disability, income level, and perceived meaningfulness in life. In the multiple regression models, residential area, disability, and marital status explained 24.30 % of the variance in HAI scores. Health promotion strategies and future targeted intervention programs should consider the importance of these factors. © 2016 The Author(s)

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