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The effect of contextual factors on unintentional injury hospitalization: from the Korea National Hospital Discharge Survey

  • 주제(키워드) Contextual effect , Hospitalization , Multilevel analysis , Unintentional injury
  • 주제(기타) Public, Environmental & Occupational Health
  • 설명문(일반) [Lee, Hye Ah] Ewha Womans Univ, Mokdong Hosp, Clin Trial Ctr, Seoul, South Korea; [Han, Hyejin; Lee, Seonhwa; Park, Bomi; Park, Bo Hyun; Park, Hyesook] Ewha Womans Univ, Dept Prevent Med, Coll Med, 1071 Anyangcheon Ro, Seoul 158710, South Korea; [Lee, Won Kyung] Inha Univ, Sch Med, Dept Social & Prevent Med, Incheon, South Korea; [Park, Ju Ok] Hallym Univ, Coll Med, Dept Emergency Med, Hwaseong, South Korea; [Park, Ju Ok] Dongtan Sacred Heart Hosp, Hwaseong, South Korea; [Hong, Sungok; Kim, Young Taek] Korea Ctr Dis Control & Prevent, Div Chron Dis Control, Cheongju, South Korea
  • 등재 SCIE, SCOPUS
  • 발행기관 BIOMED CENTRAL LTD
  • 발행년도 2018
  • URI http://www.dcollection.net/handler/ewha/000000151482
  • 본문언어 영어
  • Published As http://dx.doi.org/10.1186/s12889-018-5249-4

초록/요약

Background: It has been suggested that health risks are affected by geographical area, but there are few studies on contextual effects using multilevel analysis, especially regarding unintentional injury. This study investigated trends in unintentional injury hospitalization rates over the past decade in Korea, and also examined community-level risk factors while controlling for individual-level factors. Methods: Using data from the 2004 to 2013 Korea National Hospital Discharge Survey (KNHDS), trends in age-adjusted injury hospitalization rate were conducted using the Joinpoint Regression Program. Based on the 2013 KNHDS, we collected community-level factors by linking various data sources and selected dominant factors related to injury hospitalization through a stepwise method. Multilevel analysis was performed to assess the community-level factors while controlling for individual-level factors. Results: In 2004, the age-adjusted unintentional injury hospitalization rate was 1570.1 per 100,000 population and increased to 1887.1 per 100,000 population in 2013. The average annual percent change in rate of hospitalizations due to unintentional injury was 2.31% (95% confidence interval: 1.8-2.9). It was somewhat higher for females than for males (3.25% vs. 1.64%, respectively). Both community-and individual-level factors were found to significantly influence unintentional injury hospitalization risk. As community-level risk factors, finance utilization capacity of the local government and neighborhood socioeconomic status, were independently associated with unintentional injury hospitalization after controlling for individual-level factors, and accounted for 19.9% of community-level variation in unintentional injury hospitalization. Conclusion: Regional differences must be considered when creating policies and interventions. Further studies are required to evaluate specific factors related to injury mechanism.

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