Literature DB >> 27039281

Lunch-time food choices in preschoolers: Relationships between absolute and relative intakes of different food categories, and appetitive characteristics and weight.

S Carnell1, K Pryor2, L A Mais3, S Warkentin3, L Benson4, R Cheng5.   

Abstract

Children's appetitive characteristics measured by parent-report questionnaires are reliably associated with body weight, as well as behavioral tests of appetite, but relatively little is known about relationships with food choice. As part of a larger preloading study, we served 4-5year olds from primary school classes five school lunches at which they were presented with the same standardized multi-item meal. Parents completed Child Eating Behavior Questionnaire (CEBQ) sub-scales assessing satiety responsiveness (CEBQ-SR), food responsiveness (CEBQ-FR) and enjoyment of food (CEBQ-EF), and children were weighed and measured. Despite differing preload conditions, children showed remarkable consistency of intake patterns across all five meals with day-to-day intra-class correlations in absolute and percentage intake of each food category ranging from 0.78 to 0.91. Higher CEBQ-SR was associated with lower mean intake of all food categories across all five meals, with the weakest association apparent for snack foods. Higher CEBQ-FR was associated with higher intake of white bread and fruits and vegetables, and higher CEBQ-EF was associated with greater intake of all categories, with the strongest association apparent for white bread. Analyses of intake of each food group as a percentage of total intake, treated here as an index of the child's choice to consume relatively more or relatively less of each different food category when composing their total lunch-time meal, further suggested that children who were higher in CEBQ-SR ate relatively more snack foods and relatively less fruits and vegetables, while children with higher CEBQ-EF ate relatively less snack foods and relatively more white bread. Higher absolute intakes of white bread and snack foods were associated with higher BMI z score. CEBQ sub-scale associations with food intake variables were largely unchanged by controlling for daily metabolic needs. However, descriptive comparisons of lunch intakes with expected amounts based on metabolic needs suggested that overweight/obese boys were at particularly high risk of overeating. Parents' reports of children's appetitive characteristics on the CEBQ are associated with differential patterns of food choice as indexed by absolute and relative intake of various food categories assessed on multiple occasions in a naturalistic, school-based setting, without parents present.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Ad libitum intake; Appetitive traits; Macronutrient intake; Meal-time; School meals; Test meal

Mesh:

Year:  2016        PMID: 27039281      PMCID: PMC4899113          DOI: 10.1016/j.physbeh.2016.03.028

Source DB:  PubMed          Journal:  Physiol Behav        ISSN: 0031-9384


  52 in total

1.  Tracking of dietary intake patterns of Chinese from childhood to adolescence over a six-year follow-up period.

Authors:  Youfa Wang; Margaret E Bentley; Fengying Zhai; Barry M Popkin
Journal:  J Nutr       Date:  2002-03       Impact factor: 4.798

2.  Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids.

Authors:  Paula Trumbo; Sandra Schlicker; Allison A Yates; Mary Poos
Journal:  J Am Diet Assoc       Date:  2002-11

3.  Eating patterns and obesity in children. The Bogalusa Heart Study.

Authors:  Theresa A Nicklas; Su-Jau Yang; Tom Baranowski; Issa Zakeri; Gerald Berenson
Journal:  Am J Prev Med       Date:  2003-07       Impact factor: 5.043

4.  Stability and continuity of parentally reported child eating behaviours and feeding practices from 2 to 5 years of age.

Authors:  C Farrow; J Blissett
Journal:  Appetite       Date:  2011-09-29       Impact factor: 3.868

5.  Child eating behavior outcomes of an early feeding intervention to reduce risk indicators for child obesity: the NOURISH RCT.

Authors:  Lynne Allison Daniels; Kimberley Margaret Mallan; Diana Battistutta; Jan Maree Nicholson; Josephine Emma Meedeniya; Jordana Kim Bayer; Anthea Magarey
Journal:  Obesity (Silver Spring)       Date:  2014-01-23       Impact factor: 5.002

6.  Development of the Children's Eating Behaviour Questionnaire.

Authors:  J Wardle; C A Guthrie; S Sanderson; L Rapoport
Journal:  J Child Psychol Psychiatry       Date:  2001-10       Impact factor: 8.982

7.  Measuring behavioural susceptibility to obesity: validation of the child eating behaviour questionnaire.

Authors:  Susan Carnell; Jane Wardle
Journal:  Appetite       Date:  2006-09-07       Impact factor: 3.868

8.  Validation of energy intake by 24-hour multiple pass recall: comparison with total energy expenditure in children aged 5-7 years.

Authors:  Colette Montgomery; John J Reilly; Diane M Jackson; Louise A Kelly; Christine Slater; James Y Paton; Stan Grant
Journal:  Br J Nutr       Date:  2005-05       Impact factor: 3.718

9.  Is food portion size a risk factor of childhood overweight?

Authors:  S Lioret; J-L Volatier; L Lafay; M Touvier; B Maire
Journal:  Eur J Clin Nutr       Date:  2007-11-21       Impact factor: 4.016

10.  The tracking of dietary intakes of children and adolescents in Sweden over six years: the European Youth Heart Study.

Authors:  Emma Patterson; Julia Wärnberg; John Kearney; Michael Sjöström
Journal:  Int J Behav Nutr Phys Act       Date:  2009-12-11       Impact factor: 6.457

View more
  7 in total

1.  Ecological factors and childhood eating behaviours at 5 years of age: findings from the ROLO longitudinal birth cohort study.

Authors:  Anna Delahunt; Marie C Conway; Eileen C O'Brien; Aisling A Geraghty; Linda M O'Keeffe; Sharleen L O'Reilly; Ciara M McDonnell; Patricia M Kearney; John Mehegan; Fionnuala M McAuliffe
Journal:  BMC Pediatr       Date:  2022-06-27       Impact factor: 2.567

2.  Exploring the relationship between appetitive behaviours, executive function, and weight status among preschool children.

Authors:  Kyung E Rhee; Michael Manzano; Stanny Goffin; David Strong; Kerri N Boutelle
Journal:  Pediatr Obes       Date:  2021-02-02       Impact factor: 3.910

3.  Concurrent Validity of the Adult Eating Behavior Questionnaire in a Canadian Sample.

Authors:  Tamara R Cohen; Lisa Kakinami; Hugues Plourde; Claudia Hunot-Alexander; Rebecca J Beeken
Journal:  Front Psychol       Date:  2021-12-02

4.  Associations of mothers' and fathers' structure-related food parenting practices and child food approach eating behaviors during the COVID pandemic.

Authors:  Elena Jansen; Kimberly Smith; Gita Thapaliya; Jennifer Sadler; Anahys Aghababian; Susan Carnell
Journal:  Physiol Behav       Date:  2022-05-02

5.  Eating Behavior Associated with Food Intake in European Adolescents Participating in the HELENA Study.

Authors:  Ivie Maneschy; Luis A Moreno; Azahara I Ruperez; Andrea Jimeno; María L Miguel-Berges; Kurt Widhalm; Anthony Kafatos; Cristina Molina-Hidalgo; Dénes Molnar; Fréderic Gottrand; Cinzia Le Donne; Yannis Manios; Evangelia Grammatikaki; Marcela González-Gross; Mathilde Kersting; Jean Dallongeville; Sonia Gómez-Martinez; Stefaan De Henauw; Alba M Santaliestra-Pasías
Journal:  Nutrients       Date:  2022-07-24       Impact factor: 6.706

6.  Extending the Together, We Inspire Smart Eating Curriculum to Intergenerational Nutrition Education: A Pilot Study.

Authors:  Rachel M Scrivano; Jill J Juris; Shannon E Jarrott; Jennifer M Lobb
Journal:  Int J Environ Res Public Health       Date:  2022-07-22       Impact factor: 4.614

Review 7.  "Food" and "non-food" self-regulation in childhood: a review and reciprocal analysis.

Authors:  Catherine G Russell; Alan Russell
Journal:  Int J Behav Nutr Phys Act       Date:  2020-03-10       Impact factor: 6.457

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.