Literature DB >> 21730218

E-KINDEX: a dietary screening tool to assess children's obesogenic dietary habits.

Chrystalleni Lazarou1, Demosthenes B Panagiotakos, George Spanoudis, Antonia-Leda Matalas.   

Abstract

BACKGROUND: To date, no published dietary indices have evaluated the overall effects of various dietary components, beliefs, and practices on the development of obesity in children.
OBJECTIVE: To develop a dietary index that contains dietary characteristics and practices implicated in the development of obesity.
METHODS: The proposed index (i.e., the E-KINDEX [Electronic Kids Dietary Index]) incorporates 3 subindices: (1) a food groups intake index (13 items), (2) an index related to eating beliefs and behaviors (8 items), and (3) an index that evaluates dietary practices (9 items). The theoretical overall score ranges from 1 (worst) to 87 (best). For validation of the E-KINDEX, multiple linear and logistic regression analyses were applied that had as dependent outcomes various body composition indices of 622 children (9-13 years) from the CYKIDS (Cyprus Kids) study. In all models, adjustments were made for age, gender, physical activity level, TV viewing time, socioeconomic status, breastfeeding, and parental obesity status.
RESULTS: The highest E-KINDEX category (>60 points) was associated with 85% less likelihood of a child being obese or overweight (odds ratio [OR], 0.15; 95% confidence interval [CI], 0.05-0.41) and 86% less likelihood of having a waist circumference ≥75th percentile (OR, 0.14; 95% CI, 0.05-0.43). The correct classification rate of E-KINDEX (C-statistic) against excess body fat percentage was 84% (CI, 0.74-0.94). Moreover, for a single SD increase in the index score (i.e., 7.81 units), a decrease of 2.31 ± 0.23 kg/m(2) in body mass index (BMI), of 2.23 ± 0.35 in percent of body fat (BF%), and of 2.16 ± 0.61 cm in waist circumference was observed. Similar results were found during 1-year follow-up of study participants. In particular, baseline E-KINDEX levels were inversely associated with children's BMI at 1-year follow-up (p = 0.024). Latent class analysis showed that the index has good discriminative value for only 68% of the total sample.
CONCLUSION: The proposed E-KINDEX could be helpful in dietary assessment and in further research in the field of childhood obesity.

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Year:  2011        PMID: 21730218     DOI: 10.1080/07315724.2011.10719949

Source DB:  PubMed          Journal:  J Am Coll Nutr        ISSN: 0731-5724            Impact factor:   3.169


  8 in total

Review 1.  Use of dietary indexes among children in developed countries.

Authors:  Chrystalleni Lazarou; P K Newby
Journal:  Adv Nutr       Date:  2011-06-28       Impact factor: 8.701

2.  Diet quality indices and their associations with health-related outcomes in children and adolescents: an updated systematic review.

Authors:  Phoebe Dalwood; Skye Marshall; Tracy L Burrows; Ashleigh McIntosh; Clare E Collins
Journal:  Nutr J       Date:  2020-10-24       Impact factor: 3.271

3.  Diet quality of Norwegian children at 3 and 7 years: changes, predictors and longitudinal association with weight.

Authors:  Line Marlene Nylund Sørensen; Geir Aamodt; Anne Lise Brantsæter; Helle Margrete Meltzer; Eleni Papadopoulou
Journal:  Int J Obes (Lond)       Date:  2021-08-30       Impact factor: 5.095

4.  Healthy and Sustainable Dietary Patterns in Children and Adolescents: A Systematic Review.

Authors:  Beatriz Teixeira; Cláudia Afonso; Sara Rodrigues; Andreia Oliveira
Journal:  Adv Nutr       Date:  2022-08-01       Impact factor: 11.567

5.  The Need for Early Referral: Characteristics of Children and Adolescents Who Are Overweight and Obese Attending a Multidisciplinary Weight Management Service.

Authors:  Jacqueline L Walker; Rebecca Malley; Robyn Littlewood; Sandra Capra
Journal:  Children (Basel)       Date:  2017-10-31

6.  Development and validation of the FiberScreen: A short questionnaire to screen fibre intake in adults.

Authors:  Iris Rijnaarts; Nicole de Roos; Erwin G Zoetendal; Nicole de Wit; Ben J M Witteman
Journal:  J Hum Nutr Diet       Date:  2021-08-29       Impact factor: 2.995

Review 7.  Lifestyle Screening Tools for Children in the Community Setting: A Systematic Review.

Authors:  Anne Krijger; Sovianne Ter Borg; Liset Elstgeest; Caroline van Rossum; Janneke Verkaik-Kloosterman; Elly Steenbergen; Hein Raat; Koen Joosten
Journal:  Nutrients       Date:  2022-07-14       Impact factor: 6.706

8.  Validity of the Australian Recommended Food Score as a diet quality index for Pre-schoolers.

Authors:  Tracy L Burrows; Kate Collins; Jane Watson; Maya Guest; May M Boggess; Melinda Neve; Megan Rollo; Kerith Duncanson; Clare E Collins
Journal:  Nutr J       Date:  2014-09-02       Impact factor: 3.271

  8 in total

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