A Trial to Increase Child Vegetable Intake Through Behavioral Strategies

A Controlled-intervention Trial to Increase Child Vegetable Intake Through Parent-implemented Behavioral Strategies

A community nutrition trial among a diverse low-income population that tested the effect of parent-child cooking nutrition intervention on vegetable intake among 9-12 children.

Study Overview

• Status: Completed
• Conditions: Obesity, Childhood
• Intervention / Treatment: Behavioral: Parent-led behavioral strategies

Detailed Description

This study was a nonrandomized, controlled trial to determine whether a series of 6 weekly parent-child vegetable cooking skills classes and parent-led strategies informed by behavioral economics (1/week) (intervention group) improved dietary and non-dietary outcomes of a racially and ethnically diverse sample of low-income children (ages 9-12) more than a vegetable cooking skills program alone (control group).

• Study Type: Interventional
• Enrollment (Actual): 103
• Phase: Not Applicable

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 9 years and older (ADULT, OLDER_ADULT, CHILD)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Participant child must be 9-12 years old
• Parent must be the main food preparer for the household
• The family must qualify for some form of public assistance
• Have a phone
• Must not have participated in a previous Cooking Matters for Families in the past 3 years
• Be able to read, speak, and understand English (or Spanish for Spanish-only courses).

Exclusion criteria:

*No exclusions other than those that do not meet inclusion criteria

Study Plan

How is the study designed?

Design Details

• Primary Purpose: PREVENTION
• Allocation: NON_RANDOMIZED
• Interventional Model: PARALLEL
• Masking: SINGLE

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
EXPERIMENTAL: Intervention; The intervention consisted of an enhanced Cooking Matters® for Families program that included behavioral strategies derived from behavioral economics, to be implemented by parents at home for increasing vegetable intake of low-income 9-12 year old children	Behavioral: Parent-led behavioral strategies; Intervention parents participated in an additional 20-25-min segment led by the nutrition educator during which the week's behavioral strategy was introduced. The following six behavioral strategies were introduced (one each week) as a segment of each cooking skills session: 1) have your child help prepare vegetables for meals (Child Help), 2) use a plate that shows the amount of vegetables to include for a meal (My Plate), 3) make vegetables visible and accessible by removing other foods from the dining area during the meal and leaving the vegetables (Make Avail/Visible), 4) serve at least 2 vegetables with the meal (Serve 2), 5) serve vegetables before the meal (Serve First), and 6) use a bigger spoon to serve the vegetables (Big Spoon).
NO_INTERVENTION: Control; The control arm consisted of the enhanced Cooking Matters® for Families program alone--without lessons about the behavioral strategies for the parents

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
change in # of vegetable servings consumed by child measured by averaging vegetable serving data extracted from 3, 24-hr recalls.	Number of vegetable servings were assessed from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone from each child, using Nutrition Data System for Research (NDSR®)software). The 3, 24-hr recalls were averaged to come up with an aggregate # of vegetable servings.	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)
change in # of vegetable servings consumed by child measured by averaging vegetable serving data extracted from 3, 24-hr recalls.	Number of vegetable servings were assessed from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone from each child, using Nutrition Data System for Research (NDSR®)software). The 3, 24-hr recalls were averaged to come up with an aggregate # of vegetable servings.	change from baseline to 6 months post-baseline
change in # of vegetable servings consumed by child measured by averaging vegetable serving data extracted from 3, 24-hr recalls.	Number of vegetable servings were assessed from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone from each child, using Nutrition Data System for Research (NDSR®)software). The 3, 24-hr recalls were averaged to come up with an aggregate # of vegetable servings.	change from baseline to 12 months post-baseline

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
change in liking of vegetables by child (liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"))	Each child rated his/her liking of 37 different vegetables.The liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"). This type of liking rating scale has been validated for testing with children. (Kroll, B.J. 1990. Evaluating rating scales for sensory testing with children. Food Technology, 44(11), 78-86.) An aggregate vegetable liking score representing mean liking rating across all vegetables was calculated for each child.	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)
change in liking of vegetables by child ( liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"))	Each child rated his/her liking of 37 different vegetables.The liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"). This type of liking rating scale has been validated for testing with children. (Kroll, B.J. 1990. Evaluating rating scales for sensory testing with children. Food Technology, 44(11), 78-86.) An aggregate vegetable liking score representing mean liking rating across all vegetables was calculated for each child.	change from baseline to 6-months post baseline
change in liking of vegetables by child ( liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"))	Each child rated his/her liking of 37 different vegetables.The liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"). This type of liking rating scale has been validated for testing with children. (Kroll, B.J. 1990. Evaluating rating scales for sensory testing with children. Food Technology, 44(11), 78-86.) An aggregate vegetable liking score representing mean liking rating across all vegetables was calculated for each child.	change from baseline to 12-months post baseline
change in number different of vegetables tried by child	Each child was asked the question "Have you ever tried (name of vegetable)" with following response options: Yes/No/Don't know. An aggregate score per child was tabulated by summing all "yes" answers.	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)
change in number different of vegetables tried by child	Each child was asked the question "Have you ever tried (name of vegetable)" with following response options: Yes/No/Don't know. An aggregate score per child was tabulated by summing all "yes" answers.	change from baseline to 6-months post-baseline
change in number different of vegetables tried by child	Each child was asked the question "Have you ever tried (name of vegetable)" with following response options: Yes/No/Don't know. An aggregate score per child was tabulated by summing all "yes" answers.	change from baseline to 12-months post-baseline
change in number of available vegetables in the child's home	Each of the child's parent was asked to complete a validated Home Food Inventory developed by Fulkerson and colleagues [Fulkerson JA, Nelson MC, Lytle L, Moe S, Heitzler C, Pasch KE. The validation of a home food inventory. Int J Behav Nutr Phys Act. 2008;5:55. doi:10.1186/1479-5868-5-55], to self-report the availability of different vegetables currently in their home. Response options for each question asking if the vegetable was currently in the home were "yes /no/ don't know" . Final number of available vegetables in the home was calculated by summing the number of vegetables for which the parent answered "yes."	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)
change in number of available vegetables in the child's home	Each of the child's parent was asked to complete a validated Home Food Inventory developed by Fulkerson and colleagues [Fulkerson JA, Nelson MC, Lytle L, Moe S, Heitzler C, Pasch KE. The validation of a home food inventory. Int J Behav Nutr Phys Act. 2008;5:55. doi:10.1186/1479-5868-5-55], to self-report the availability of different vegetables currently in their home. Response options for each question asking if the vegetable was currently in the home were "yes /no/ don't know" .Final number of available vegetables in the home was calculated by summing the number of vegetables for which the parent answered "yes."	change from baseline to 6-months post baseline
change in number of available vegetables in the child's home	Each of the child's parent was asked to complete a validated Home Food Inventory developed by Fulkerson and colleagues [Fulkerson JA, Nelson MC, Lytle L, Moe S, Heitzler C, Pasch KE. The validation of a home food inventory. Int J Behav Nutr Phys Act. 2008;5:55. doi:10.1186/1479-5868-5-55], to self-report the availability of different vegetables currently in their home. Response options for each question asking if the vegetable was currently in the home were "yes /no/ don't know" . Final number of available vegetables in the home was calculated by summing the number of vegetables for which the parent answered "yes."	change from baseline to 12-months post baseline
change in child's body mass index (as measured by collected height (m) and weight (kg) from child)	Child Body Mass Index (BMI) was calculated from collected height and weight of child that were combined to report BMI in kg/m^2	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)
change in child's body mass index (as measured by collected height (m) and weight (kg) from child)	Child Body Mass Index (BMI) was calculated from collected height and weight of child that were combined to report BMI in kg/m^2	change from baseline to 6-months post baseline
change in child's body mass index (as measured by collected height (m) and weight (kg) from child)	Child Body Mass Index (BMI) was calculated from collected height and weight of child that were combined to report BMI in kg/m^2	change from baseline to 12-months post baseline
change in child's Healthy Eating Index 2010 score (a measure of dietary quality)	Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient. NDSR data was imported into a SAS® program (version 9.4) (SAS Institute Inc. Cary, NC 2014), created by National Institutes of Health-NCI, Division of Cancer Control & Population Studies that calculated a Healthy Eating Index 2010 score, a validated measure of dietary quality, for each child (Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HAB, Kuczynski KJ, et al. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013;113:569-80..	change from baseline to immediate post-intervention (i.e, 9 weeks post-baseline)
change in child's Healthy Eating Index 2010 score (a measure of dietary quality)	Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient. NDSR data was imported into a SAS® program (version 9.4) (SAS Institute Inc. Cary, NC 2014), created by National Institutes of Health-NCI, Division of Cancer Control & Population Studies that calculated a Healthy Eating Index 2010 score, a validated measure of dietary quality, for each child.	change from baseline to 6-months post baseline
change in child's Healthy Eating Index 2010 score (a measure of dietary quality)	Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient. NDSR data was imported into a SAS® program (version 9.4) (SAS Institute Inc. Cary, NC 2014), created by National Institutes of Health-NCI, Division of Cancer Control & Population Studies that calculated a Healthy Eating Index 2010 score, a validated measure of dietary quality, for each child.	change from baseline to 12-months post baseline
change in child's dietary energy (in kilocalories) intake	Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient (e.g., dietary energy in kilocalories)	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)
change in child's dietary energy (in kilocalories) intake	Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient (e.g., dietary energy in kilocalories)	change from baseline to 6-months post-baseline
change in child's dietary energy (in kilocalories) intake	Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient (e.g., dietary energy in kilocalories)	change from baseline to 12-months post-baseline
change in child cooking skills self-efficacy as measured by a validated survey to measure child cooking self-efficacy	Child cooking skills self-efficacy was measured using scales that have shown internal consistency and test-retest reliability in a psychometric evaluation of a cooking-based nutrition education intervention among low-income 9-11 year old children (Cronbach α = ≥ 0.74, test-retest r ≥ 0.66).(Lohse B, Cunningham-Sabo L, Walters LM, Stacey JE. Valid and Reliable Measures of Cognitive Behaviors toward Fruits and Vegetables for Children Aged 9 to 11 Years. J Nutr Educ Behav. 2011;43:42-49. doi:10.1016/j.jneb.2009.12.006). Response options for the child self-efficacy questions: 1 = YES! - 5 = NO!). The child-self-efficacy scale was calculated by summing 8 items measuring self-efficacy. A lower score indicated greater self-efficacy and more positive attitudes toward cooking.	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)
change in adult cooking skills confidence as measured by a validated survey to measure adult cooking confidence. Response options for the cooking confidence questions: (4 items, 1 = not at all confident - 5 = very confident).	Parents completed the Cooking Matters for Families Before and After Course Survey to assess change in cooking skills confidence. Internal consistency and ability of the scales to reflect positive self-reported changes were previously among low-income adults (Pinard CA, Uvena LM, Quam JB, Smith TM, Yaroch AL. Development and testing of a revised cooking matters for adults survey. Am J Health Behav. 2015;39(6):866-873. doi:10.5993/AJHB.39.6.14). Response options for the 4 cooking confidence questions: (4 items, 1 = not at all confident - 5 = very confident). An aggregate score for each parent was tabulated by averaging the 4 questions. A higher score indicated greater cooking skills confidence.	change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention)

Collaborators and Investigators

• Sponsor: University of Minnesota
• Investigators: Principal Investigator: Marla Reicks, PhD, University of Minnesota

Publications and helpful links

General Publications

• Overcash F, Ritter A, Mann T, Mykerezi E, Redden J, Rendahl A, Vickers Z, Reicks M. Impacts of a Vegetable Cooking Skills Program Among Low-Income Parents and Children. J Nutr Educ Behav. 2018 Sep;50(8):795-802. doi: 10.1016/j.jneb.2017.10.016. Epub 2017 Dec 12.
• Overcash FM, Reicks M, Ritter A, Leak TM, Swenson A, Vickers Z. Children Residing in Low-Income Households Like a Variety of Vegetables. Foods. 2018 Jul 20;7(7):116. doi: 10.3390/foods7070116.
• Overcash FM, Vickers Z, Ritter AE, Mann T, Mykerezi E, Redden J, Rendahl AK, Davey C, Reicks M. An in-home intervention of parent-implemented strategies to increase child vegetable intake: results from a non-randomized cluster-allocated community trial. BMC Public Health. 2019 Jul 4;19(1):881. doi: 10.1186/s12889-019-7079-4.

Study record dates

Study Major Dates

• Study Start (ACTUAL): September 24, 2014
• Primary Completion (ACTUAL): May 2, 2017
• Study Completion (ACTUAL): May 2, 2017

Study Registration Dates

• First Submitted: August 14, 2018
• First Submitted That Met QC Criteria: August 17, 2018
• First Posted (ACTUAL): August 22, 2018

Study Record Updates

• Last Update Posted (ACTUAL): July 12, 2019
• Last Update Submitted That Met QC Criteria: July 10, 2019
• Last Verified: July 1, 2019

More Information

Terms related to this study

• Keywords: intervention; child vegetable intake; behavioral strategy
• Additional Relevant MeSH Terms: Overnutrition; Nutrition Disorders; Overweight; Body Weight; Obesity; Pediatric Obesity
• Other Study ID Numbers: 1111S06501

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Although there is no formal plan in place, the investigative team will share any of the information with other researchers (study protocol, statistical analysis plan, informed consent form, analytic code/data). We are in the process of publishing the results of our trial in a peer-reviewed journal.
• IPD Sharing Time Frame: No time frame
• IPD Sharing Access Criteria: Email Study Contact
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ICF; ANALYTIC_CODE; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No