Factors Influencing Unmet Healthcare Needs among Older Korean Women.
Jung A ChoiOksoo KimPublished in: International journal of environmental research and public health (2021)
The purpose of this study was to determine factors that influence the unmet healthcare needs of older women in Korea and to examine differences in the reasons for these unmet healthcare needs according to age and residential area. We analyzed data from the 2018 Korea Community Health Survey and enrolled 42,698 older Korean women in this study. Residential area, living arrangement, income, education, basic livelihood subsidy, activity of daily living, subjective health status, hypertension and diabetes, unmet healthcare needs, and the reasons healthcare needs were not met were assessed. Logistic regression analysis was performed to identify factors that influenced unmet healthcare needs. Chi-square tests were used to identify reasons for unmet healthcare needs according to age group and residential area. Of the participants, 4151 (9.7%) reported unmet healthcare needs over the past year. The primary reason participants could not use health services was "inconvenient transportation" (38.4%), followed by "financial burden" (28.4%) and "symptoms not severe" (16.8%). There were significant differences in "financial burden", "difficulty making appointments", "inconvenient transportation", and "symptoms not severe" according to both age group and residential area. Factors that influenced unmet healthcare needs were residential area, living alone, lower family income, lower educational level, basic livelihood subsidy, difficult activities of daily living, hypertension and diabetes, and poor subjective health. Older women in Korea living alone in urban and rural areas had more unmet healthcare needs of than those who lived with other people. To address the unmet healthcare needs of older Korean women, transportation and medical facilities need to be improved or established.
Keyphrases
- healthcare
- physical activity
- mental health
- type diabetes
- blood pressure
- health information
- air pollution
- metabolic syndrome
- pregnant women
- risk factors
- machine learning
- adipose tissue
- climate change
- polycystic ovary syndrome
- insulin resistance
- quality improvement
- artificial intelligence
- depressive symptoms
- community dwelling
- human health