Factors Contributing to Missed Visits for Medical Care among Human Immunodeficiency Virus-Infected Adults in Seoul, Korea.
10.3346/jkms.2018.33.e261
- Author:
Cho Ryok KANG
1
;
Ji Hwan BANG
;
Sung Il CHO
Author Information
1. Environmental Health Division, Seoul Metropolitan Government, Seoul, Korea.
- Publication Type:Original Article
- Keywords:
HIV;
Acquired Immune Deficiency Syndrome;
HIV Medical Care;
Retention in Care;
Metropolitan Seoul;
Age Group
- MeSH:
Acquired Immunodeficiency Syndrome;
Adult*;
Cross-Sectional Studies;
Education;
HIV;
Humans*;
Korea*;
Odds Ratio;
Risk Factors;
Seoul*;
Social Class
- From:Journal of Korean Medical Science
2018;33(42):e261-
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: It is important that patients with human immunodeficiency virus (HIV) remain under medical care to improve their health and to reduce the potential for HIV transmission. We explored factors associated with missed visits for HIV medical care according to age group. METHODS: Data were derived from a city-wide, cross-sectional survey of 812 HIV-infected adults in Seoul. Multiple logistic analyses were used to explore predictors of missed visits. RESULTS: Of the 775 subjects, 99.3% were treated with antiretroviral therapy (ART) and 12.5% had missed a scheduled appointment for HIV medical care during the past 12 months. Compared with the group aged ≥ 50 years, the 20–34-years and 35–49-years groups were strongly associated with missed visits (adjusted odds ratio [aOR], 5.0 and 2.2, respectively). When divided by age group, lower education level (aOR, 3.0) in subjects aged 20–34 years, low income (aOR, 3.5), National Medical Aid beneficiary (aOR, 0.3), and treatment interruption due to side effects of ART (aOR, 3.4) in subjects aged 35–49 years, and National Medical Aid beneficiary (aOR, 7.1) in subjects aged ≥ 50 years were associated with missed visits. CONCLUSION: In conclusion, younger age was a strong predictor of missed visits for HIV medical care. However, the risk factors differed according to age group, and the strongest predictor in each age group was related to socioeconomic status.
