Assessment of dietary behavior of Chinese children using nutrition quotient for children

Huang, Yann-Chang; Kim, Hye Young

doi:10.4163/jnh.2014.47.5.342

Cited by 19 publications

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“…기 개발한 어린이 영양지수 (nutrition quotient for children) 16,17 는 다수의 연구자들 및 공공기관에서 어린이 및 청소년 대 상의 식생활 및 식행동 평가와 영양교육 효과 평가 등에 활 용되고 있다. [18][19][20][21][22][23] 최근에는 취학전아동 (nutrition quotient for preschoolers: NQ-P) 24 , 청소년 (nutrition quotient for adolescents: NQ-A) 25 1) High: 75% ≤ NQ-P percentile ≤ 100%, Medium: 25% ≤ NQ-P percentile < 75%, Low: 0% ≤ NQ-P percentile < 25% 2) mean ± SD…”

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Development of Nutrition Quotient for Korean adults: item selection and validation of factor structure

et al. 2018

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Purpose: This study was conducted to develop a nutrition quotient (NQ) to assess overall dietary quality and food behaviors of Korean adults. Methods: The NQ was developed in three steps: item generation, item reduction, and validation. Candidate items of the NQ checklist were derived from a systematic literature review, expert in-depth interviews, statistical analyses of the Korea National Health and Nutrition Examination Survey (2010~2013) data, and national nutrition policies and recommendations. A total of 368 adults (19~64 years) participated in a one-day dietary record survey and responded to 43 items in the food behavior checklist. Pearson's correlation coefficients between responses to the checklist items and nutritional intake status of the adults were calculated. Item reduction was performed, and 24 items were selected for a nationwide survey. A total of 1,053 nationwide adult subjects completed the checklist questionnaires. Exploratory and confirmatory factor analyses were performed to develop a final NQ model. Results: The 21 checklist items were used as final items for NQ. Checklist items were composed of four factors: nutrition balance (seven items), food diversity (three items), moderation for the amount of food intake (six items), and dietary behavior (five items). The four-factor structure accounted for 41.8% of the total variance. Indicator tests of the NQ model suggested an adequate model fit (GRI = 0.9693, adjusted GFI = 0.9617, RMR = 0.0054, SRMR = 0.0897, p < 0.05), and item loadings were significant for all subscales. Standardized path coefficients were used as weights of the items. The NQ and four-factor scores were calculated according to the obtained weights of the questionnaire items. Conclusion: NQ for adults would be a useful tool for assessing adult dietary quality and food behavior. Further investigations of adult NQ are needed to reflect changes in their food behavior, environment, and prevalence of chronic diseases.

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