The Association Among Individual and Contextual Factors and Unmet Healthcare Needs in South Korea: A Multilevel Study Using National Data.
- Author:
Seung Eun LEE
1
;
Miyeon YEON
;
Chul Woung KIM
;
Tae Ho YOON
Author Information
- Publication Type:Original Article
- Keywords: Health services accessibility; Utilization; Residence characteristics; Multilevel analysis; Health surveys
- MeSH: Adult; Delivery of Health Care*; Employment; Health Services Accessibility; Health Surveys; Humans; Korea*; Multilevel Analysis; Population Groups; Residence Characteristics
- From:Journal of Preventive Medicine and Public Health 2016;49(5):308-322
- CountryRepublic of Korea
- Language:English
- Abstract: OBJECTIVES: The objective of this study is to investigate associations between contextual characteristics and unmet healthcare needs in South Korea after accounting for individual factors. METHODS: The present study used data from the 2012 Korean Community Health Survey (KCHS) of 228 902 adults residing within 253 municipal districts in South Korea. A multilevel analysis was conducted to investigate how contextual characteristics, defined by variables that describe the regional deprivation, degree of urbanity, and healthcare supply, are associated with unmet needs after controlling for individual-level variables. RESULTS: Of the surveyed Korean adults, 12.1% reported experiencing unmet healthcare needs in the past. This figure varied with the 253 districts surveyed, ranging from 2.6% to 26.2%. A multilevel analysis found that the association between contextual characteristics and unmet needs varied according to the factors that caused the unmet needs. The degree of urbanity was associated with unmet need due to "financial burden" (odds ratio [OR], 0.53; 95% confidence interval [CI], 0.42 to 0.66 for rural vs. metropolitan), but not unmet need due to "service not available when needed." There were no significant associations between these unmet need measures and regional deprivation. Among individual-level variables, income level showed the highest association with unmet need due to "financial burden" (OR, 5.63; 95% CI, 4.76 to 6.66), while employment status showed a strong association with unmet need due to "service not available when needed." CONCLUSIONS: Our finding suggests that different policy interventions should be considered for each at-risk population group to address the root cause of unmet healthcare needs.
