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Estimating the severity distribution of disease in South Korea using EQ-5D-3L: a cross-sectional study.
Ock, Minsu; Jo, Min-Woo; Gong, Young-Hoon; Lee, Hyeon-Jeong; Lee, Jiho; Sim, Chang Sun.
Afiliação
  • Ock M; Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, South Korea. ohohoms@naver.com.
  • Jo MW; Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, South Korea. mdjominwoo@gmail.com.
  • Gong YH; Department of Preventive Medicine, Korea University College of Medicine, Seoul, South Korea. drzero00@naver.com.
  • Lee HJ; Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, South Korea. trueprsc@hanmail.net.
  • Lee J; Department of Occupational and Environmental Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, 877 Bangeojinsunhwan-doro, Dong-gu, Ulsan, 682-714, South Korea. oemdoc@naver.com.
  • Sim CS; Department of Occupational and Environmental Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, 877 Bangeojinsunhwan-doro, Dong-gu, Ulsan, 682-714, South Korea. zzz0202@naver.com.
BMC Public Health ; 16: 234, 2016 Mar 08.
Article em En | MEDLINE | ID: mdl-26956897
ABSTRACT

BACKGROUND:

There is a paucity of data on the distribution of disease severity. In this study, we estimated disease severity distributions in South Korea using two EQ-5D-3L population surveys.

METHODS:

A total of 110 health states for 35 diseases with 2-5 severity levels (e.g., mild, moderate, severe) were included in this study. A general population of 360 participants from the areas surrounding Seoul and Gyunggi evaluated these health states using EQ-5D-3L via face-to-face interviews and a paper questionnaire. The EQ-5D indices were used to measure the severity levels of health states and used as the cutoff points for the disease severity distributions. Finally, these cutoff points were applied to disease prevalence data with EQ-5D-3L, which were obtained from the Korean National Health and Nutrition Examination Surveys (KNHNES) and Korean Community Health Survey, in order to estimate the disease severity distributions.

RESULTS:

The severity distributions of 8 diseases were estimated, including asthma, angina, stroke, chronic obstructive pulmonary disease, major depressive disorder, musculoskeletal problems in the legs, anemia, and allergic rhinitis and conjunctivitis. For example, the EQ-5D indices for chronic obstructive pulmonary disease severity were 0.929, 0.742, and 0.620, and the cut-off points were 0.835 (between mild and moderate) and 0.681 (between moderate and severe). Using these cutoff points, the distributions of chronic obstructive pulmonary disease severity were 66.5 % (mild), 23.3 % (moderate), and 10.1 % (severe) according to KNHNES.

CONCLUSIONS:

The estimated severity distributions in this study can be used as a valid calculation of the disease burden in the general population.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Índice de Gravidade de Doença / Inquéritos e Questionários Tipo de estudo: Observational_studies / Prevalence_studies / Qualitative_research / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: BMC Public Health Assunto da revista: SAUDE PUBLICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Coréia do Sul

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Índice de Gravidade de Doença / Inquéritos e Questionários Tipo de estudo: Observational_studies / Prevalence_studies / Qualitative_research / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: BMC Public Health Assunto da revista: SAUDE PUBLICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Coréia do Sul