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
서계순 (서울금옥초등학교)
저널정보
한국식품영양학회 한국식품영양학회지 한국식품영양학회지 제29권 제6호
발행연도
2016.12
수록면
1,058 - 1,069 (12page)

이용수

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

초록· 키워드

오류제보하기
This study is intended to research workers’ health, diet and the demand of nutrition education service in Seoul and Gyeonggi-do province. We implemented the survey from September 2012 through August 2013, and analyzed the data from 589 workers’ questionnaires out of 890. For the analysis of the compiled data, we utilized the SPSS version 18.0 statistical package program. The study showed that majority of the workers participated in the survey consisted of 447 male (75.9%) and 142 female (24.1%). BMI showed that these men were overweight (24.5±2.72) and women were normal weight (22.2± 2.70). Participants often diagnosed with hypertension or hyperlipidemia. In terms of health status, 34.5% answered satisfactory, the most concerned illness was high blood pressure, and the bad eating habits were often associated with general overeating and excessive intake of salt. 65.5% of participants had a meal three times per day. 49.4% of male participants had a meal less than 15 minutes and 66.2% of female participants had a meal between 15 and 30 minutes. The average of workers who needed to nutrition education is 3.74+0.85. The most desired way of learning was through counseling (36.7%), with overweight and weight management identified as the most interested topics. A relatively high portion (80%) passed the nutrition knowledge assessment test. According to the survey the highest rate of full-time employment is 85.2% which showed in small work places (the number of people on meal plan was 100~300), however the lowest rate of full-time employment showed 70.0% in large workplaces (the number of people on meal plan was within 1,000).

목차

등록된 정보가 없습니다.

참고문헌 (27)

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