Literature DB >> 27247727

Development of dietary pattern evaluation tool for adults and correlation with Dietary Quality Index.

Yeo Do Lee1, Kyung Won Kim2, Kyung-Suk Choi3, Misung Kim1, Yeo Jin Cho1, Cheongmin Sohn1.   

Abstract

BACKGROUND/
OBJECTIVES: As the prevalence of chronic diseases has risen, the need for straightforward diagnostic tools for monitoring nutrition status to improve nutrition counseling and disease prevention has likewise increased. This study developed an easily usable dietary behavior pattern diagnosis checklist and investigated its correlation with dietary quality index. SUBJECTS/
METHODS: A draft dietary pattern evaluation tool was generated by analyzing previous studies. The draft questionnaire comprised 61 questions for assessing dietary habits. A survey was administered to 320 adults (19 to 64 years old) using the dietary pattern evaluation tool and 24-hour-recall method between March and May of 2014 in Jeonbuk province and the metropolitan area. Principal component analysis with varimax rotation was performed to identify dietary behavior patterns. Nutritional analysis was conducted using CAN-Pro 4.0, and the Diet Quality Index-International (DQI-I) was calculated to assess dietary quality. The correlation between dietary pattern scores and DQI-I scores was also analyzed.
RESULTS: The factor analysis resulted in a total of 34 questions mapped to four main dietary behavior patterns: "high fat and calorie" pattern (12 questions), "overeating/binge" pattern (nine questions), "dietary impulse" pattern (eight questions), and "unbalanced food intake" pattern (five questions). The four dietary behavior patterns were negatively correlated with DQI-I adequacy and total scores (P < 0.01).
CONCLUSIONS: The dietary pattern evaluation tool developed in this study can be used to diagnose a client's dietary behavior problems and is available as a nutrition counseling tool in the field.

Entities:  

Keywords:  Aadult; nutritional assessment; nutritional quality

Year:  2016        PMID: 27247727      PMCID: PMC4880730          DOI: 10.4162/nrp.2016.10.3.305

Source DB:  PubMed          Journal:  Nutr Res Pract        ISSN: 1976-1457            Impact factor:   1.926


  7 in total

1.  The Eating Behavior Patterns Questionnaire predicts dietary fat intake in African American women.

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Journal:  J Am Diet Assoc       Date:  2003-03

2.  The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States.

Authors:  Soowon Kim; Pamela S Haines; Anna Maria Siega-Riz; Barry M Popkin
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Review 3.  Indexes of overall diet quality: a review.

Authors:  A K Kant
Journal:  J Am Diet Assoc       Date:  1996-08

4.  Perceived effects of stress on food choice.

Authors:  G Oliver; J Wardle
Journal:  Physiol Behav       Date:  1999-05

5.  Diet quality index: capturing a multidimensional behavior.

Authors:  R E Patterson; P S Haines; B M Popkin
Journal:  J Am Diet Assoc       Date:  1994-01

6.  Diet quality and dietary diversity in France: implications for the French paradox.

Authors:  A Drewnowski; S A Henderson; A B Shore; C Fischler; P Preziosi; S Hercberg
Journal:  J Am Diet Assoc       Date:  1996-07

7.  The Healthy Eating Index: design and applications.

Authors:  E T Kennedy; J Ohls; S Carlson; K Fleming
Journal:  J Am Diet Assoc       Date:  1995-10
  7 in total
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