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
저널정보
대한가정의학회 Korean Journal of Family Medicine Korean Journal of Family Medicine 제38권 제3호
발행연도
2017.1
수록면
141 - 147 (7page)

이용수

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

이 논문의 연구 히스토리 (2)

초록· 키워드

오류제보하기
Background: Sarcopenia is an age-related loss of muscle mass and strength. Coffee has antioxidant and anti-in-flammatory properties that have been shown to be inversely related to the mechanism of sarcopenia. While there have been some studies on the effect of coffee on sarcopenia in animals, studies on the topic in humans are rare. Therefore, we investigated this relationship in elderly Korean men.Methods: The cross-sectional data were derived from the 2008–2011 Korea National Health and Nutrition Exami-nation Survey. After applying the exclusion criteria, the study sample consisted of 1,781 men who were at least 60 years of age. Study participants were identified as having sarcopenia if their appendicular skeletal muscle mass di-vided by height squared was less than two standard deviations below the gender-specific mean of this value for young adults. Daily coffee consumption amounts were categorized as <1 cup, 1 cup, 2 cups, and ≥3 cups.Results: Compared to the group of individuals who drank less than one cup of coffee a day, people who consumed at least 3 cups (adjusted odds ratio, 0.43; 95% confidence interval, 0.20 to 0.94) showed significantly decreased sar-copenia; however, the decrease was not significant when the daily coffee consumption was 1 or 2 cups. In multivar-iate logistic regression models, significant associations were observed between sarcopenia and coffee consumption (P for trend=0.039).Conclusion: The results of this study suggest that consuming at least 3 cups of coffee per day was associated with a lower prevalence of sarcopenia in elderly Korean elderly men.

목차

등록된 정보가 없습니다.

참고문헌 (24)

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