메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Aqeela Zahra (University of Hail) 박재현 (성균관대학교)
저널정보
대한의학회 Journal of Korean Medical Science Journal of Korean Medical Science Vol.33 No.40
발행연도
2018.1
수록면
1 - 13 (13page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Background: Exposure to secondhand smoke (SHS) is one of the biggest health hazards. Quantifying the related burden of disease (BOD) is a powerful tool for making evidence-based policies. This study calculated the BOD due to SHS at sub-national level using the most recent statistics of Korea. Methods: SHS related diseases were selected by the systematic review of previous studies. Population attributable fraction (PAF) was calculated by using the standard formula using prevalence of exposure derived from Community Health Survey (CHS) 2013. SHS burden was calculated by multiplying nonsmoker's disability adjusted life years (DALYs) with PAF of SHS Results: SHS burden at sub-national level ranged between 460 DALYs in Cheonan to 5 DALYs in Pyeongtaek, Songtan region. Median of DALY was highest in districts of metropolitan cities and lowest in small towns and rural areas. Twelve out of fifteen regions with highest DALY per 1,000 were small towns and rural areas. Gender and age standardized DALY was highest in Seogwipo (west) in Jeju-do (1.66/1,000) and lowest in Dong-gu, Ulsan (0.17/1,000). Conclusion: There were substantial variations between regions according to BOD. Regional governments should implement policies according to specific situation in each region and regular monitoring should be done by calculating BOD. Big cities need to focus more on control of active and SHS prevalence. Resources in small towns and rural areas need to be allocated more towards implementation of screening programs, early diagnosis and treatment of diseases especially in the elderly population.

목차

등록된 정보가 없습니다.

참고문헌 (28)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0