Monitoring Eating Across Locations (MEAL) - Timing, Intake, and Mealtime Evaluation (TIME)

NCT07095166 | Recruiting

• 1 other identifier: STUDY00026981
• Study Type: interventional
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

Increased availability of high-energy dense foods has contributed to a pediatric obesity epidemic, with 23% of United States children currently presenting with the disease. How children eat contributes to both overconsumption and greater adiposity. However, it is unclear if laboratory measures of children's eating style generalize to the home environment, where children consume two thirds of their total energy. The study will 1) test if child eating styles observed in the lab generalize to more ecologically valid home environments and 2) identify aspects of home food environment that amplify obesogenic eating behaviors. We will assess laboratory and home eating styles (e.g., bite rate) in 100 prepubertal 6-9-year-old children to constrain variability in energy requirements. Children will be video-recorded while consuming identical study-provided meals at home and in the laboratory (counter-balanced order) in addition to a 'typical' meal at home. To study how adiposity relates to "obesogenic" styles of eating, gold standard dual x-ray absorptiometry will be used.

Conditions

Pediatric Obesity

Keywords

eating behavior; meal microstructure; child; obesity

Outcome Measures

Primary Outcomes (11)

• Child body mass index

  child height and weight will be measured

  Day 1

• Food intake in grams during a standard meal

  Intake in grams from standard meal

  Day 1 and Day 2 or 3 depending on randomization

• Food intake in kcal during a standard meal

  Intake in kcal during a standard meal

  Day 1 and Day 2 or 3 depending on randomization

• Video coding of standard meal

  A digital recording of the child eating a standard meal will be saved. The study team have developed a behavior coding protocol to measure child meal microstructure (e.g., bites, bite size, meal duration) and have also validated a computational model to assess cumulative intake curves from video coded bite data.

  Day 1 and Day 2 or 3 depending on randomization

• Food intake in grams during a snack buffet when not hungry

  Intake in grams during a snack buffet using a standard eating in the absence of hunger paradigm (i.e., non-homeostatic intake)

  Day 1

• Food intake in kcal during a snack buffet when not hungry

  Intake in kcal during a snack buffet using a standard eating in the absence of hunger paradigm (i.e., non-homeostatic intake)

  Day 1

• Body Composition

  Dual-energy X-ray absorptiometry to assess body composition including fat mass and fat-free mass in children

  Day 1

• Food intake in grams during a Study Meal

  Intake in grams from Study Meal

  Day 2 or 3 depending on randomization and home meal administration

• Food intake in kcal during the Study Meal

  Intake in kcal during the Study Meal

  Day 2 or 3 depending on randomization and home meal administration

• Video coding of the study meal

  A digital recording of the child eating a Study Meal will be saved. The study team have developed a behavior coding protocol to measure child meal microstructure (e.g., bites, bite size, meal duration) and have also validated a computational model to assess cumulative intake curves from video coded bite data.

  Day 2 or 3 depending on randomization and home meal administration

• Video coding of home meals

  Digital recordings of the child eating a typical meals at home. The study team have developed a behavior coding protocol to measure child meal microstructure (e.g., bites, bite size, meal duration) and have also validated a computational model to assess cumulative intake curves from video coded bite data.

  Week 1 and Week 2

Study Arms (1)

Home vs Lab Eating Behavior

EXPERIMENTAL

Examine differences in participants' eating at home versus in the lab

Behavioral: Meal Location

Interventions

Meal Location BEHAVIORAL

The location at which the child will eat the experimental meal - home or lab

Home vs Lab Eating Behavior

Eligibility Criteria

• Age: 6 Years - 9 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)

You may qualify if:

• children must be between the ages of 6-9 years-old
• children are of good health with no learning disabilities (e.g., ADHD, determined by parent report)
• children are not on any medications known to impact body weight, taste, food intake, behavior, or blood flow
• parents report that children like and are willing to eat study foods

You may not qualify if:

• Children are not within the age requirements (\<6 years old or \> 9 years old)
• If children are taking cold or allergy medication, or other medications known to influence cognitive function, taste, appetite, or blood flow.
• If children don't speak English.
• If children are colorblind.
• If children have a learning disability, ADD/ADHD, language delays, autism or other neurological or psychological conditions.
• If children have a pre-existing medical condition such as type I or type II diabetes, rheumatoid arthritis, Cushing's syndrome, Down's syndrome, severe lactose intolerance, Prader-Willi syndrome, HIV, cancer, renal failure, or cerebral palsy.
• If children are allergic to foods or ingredients used in the study.
• child received an X-ray in the previous year (to avoid excess radiation exposure due to the DXA scans performed in the research)

Sponsors & Collaborators

• Penn State University: lead

Study Sites (1)

Pennsylvania State University

State College, Pennsylvania, 16801, United States

RECRUITING

Related Publications (7)

• Neuwald NV, Pearce AL, Cunningham PM, Setzenfand MN, Koczwara L, Rolls BJ, Keller KL. Food switching at a meal is positively associated with change in adiposity among children at high-familial risk for obesity. Appetite. 2025 Apr 1;208:107915. doi: 10.1016/j.appet.2025.107915. Epub 2025 Feb 25.

  PMID: 40010570 BACKGROUND

• Neuwald NV, Pearce AL, Adise S, Rolls BJ, Keller KL. Switching between foods: A potential behavioral phenotype of hedonic hunger and increased obesity risk in children. Physiol Behav. 2023 Oct 15;270:114312. doi: 10.1016/j.physbeh.2023.114312. Epub 2023 Aug 4.

  PMID: 37543104 BACKGROUND

• Fogel A, Fries LR, McCrickerd K, Goh AT, Quah PL, Chan MJ, Toh JY, Chong YS, Tan KH, Yap F, Shek LP, Meaney MJ, Broekman BFP, Lee YS, Godfrey KM, Fong Chong MF, Forde CG. Oral processing behaviours that promote children's energy intake are associated with parent-reported appetitive traits: Results from the GUSTO cohort. Appetite. 2018 Jul 1;126:8-15. doi: 10.1016/j.appet.2018.03.011. Epub 2018 Mar 15.

  PMID: 29551400 BACKGROUND

• Fogel A, Goh AT, Fries LR, Sadananthan SA, Velan SS, Michael N, Tint MT, Fortier MV, Chan MJ, Toh JY, Chong YS, Tan KH, Yap F, Shek LP, Meaney MJ, Broekman BFP, Lee YS, Godfrey KM, Chong MFF, Forde CG. A description of an 'obesogenic' eating style that promotes higher energy intake and is associated with greater adiposity in 4.5year-old children: Results from the GUSTO cohort. Physiol Behav. 2017 Jul 1;176:107-116. doi: 10.1016/j.physbeh.2017.02.013. Epub 2017 Feb 14.

  PMID: 28213204 BACKGROUND

• Fogel A, Goh AT, Fries LR, Sadananthan SA, Velan SS, Michael N, Tint MT, Fortier MV, Chan MJ, Toh JY, Chong YS, Tan KH, Yap F, Shek LP, Meaney MJ, Broekman BFP, Lee YS, Godfrey KM, Chong MFF, Forde CG. Faster eating rates are associated with higher energy intakes during an ad libitum meal, higher BMI and greater adiposity among 4.5-year-old children: results from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) cohort. Br J Nutr. 2017 Apr;117(7):1042-1051. doi: 10.1017/S0007114517000848. Epub 2017 May 2.

  PMID: 28462734 BACKGROUND

• Pearce AL, Cevallos MC, Romano O, Daoud E, Keller KL. Child meal microstructure and eating behaviors: A systematic review. Appetite. 2022 Jan 1;168:105752. doi: 10.1016/j.appet.2021.105752. Epub 2021 Oct 16.

  PMID: 34662600 BACKGROUND

• Pearce AL, Adise S, Roberts NJ, White C, Geier CF, Keller KL. Individual differences in the influence of taste and health impact successful dietary self-control: A mouse tracking food choice study in children. Physiol Behav. 2020 Sep 1;223:112990. doi: 10.1016/j.physbeh.2020.112990. Epub 2020 Jun 4.

  PMID: 32505786 BACKGROUND

MeSH Terms

Conditions

Pediatric Obesity; Feeding Behavior; Obesity

Condition Hierarchy (Ancestors)

Overweight; Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Behavior, Animal; Behavior

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PI

Study Record Dates

• First Submitted: July 9, 2025
• First Posted: July 31, 2025
• Study Start: November 15, 2025
• Primary Completion (Estimated): June 15, 2027
• Study Completion (Estimated): October 15, 2027
• Last Updated: March 6, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ANALYTIC CODE
• Time Frame: IPD will be available at the end of the study and be available in perpetuity
• Access Criteria: De-identified IPD will be openly available while identifiable IPD will be available through a restricted access repository called Databrary. identifiable data shared with Databrary will only be viewable and downloadable to authorized users who have been granted secure access by Databrary's administrators. Only researchers with Principal Investigator status from institutions with Institutional Review Boards or similar review entities, or researchers affiliated with Principal Investigators, will be authorized for access. Authorized users will be required to sign a user agreement that specifies that they will: (1) be responsible for maintaining the confidentiality of the data; (2) abide by ethical principles for treatment of human subjects as mandated by their local Institutional Review Boards; (3) agree not use the data for commercial purposes; and (4) treat data in Databrary with the same high standards of care that they would treat data collected in their own laboratories.

Locations

US (1)