Promoting The Self-Regulation Of Energy Intake In Latino Preschoolers: A Family Focused Obesity Prevention Program
Phase: NA
Conditions: Obesity
Sponsor: Baylor College of Medicine

Promoting The Self-Regulation of Energy Intake in Latino Preschoolers: A Family Focused 
Obesity Prevention Program 
 
 
NCT number: NCT01513343 
Document Date: 3/4/2022 
 

Complete Title: Promoting the Self-Regulation of Energy Intake in Latino Preschoolers: A 
Family Focused Obesity Prevention Program 
Short Title: Promoting the Self-Regulation of Energy Intake (SEEDs) 
Drug or Device Name(s): N/A 
FDA IND/IDE (if applicable): N/A 
Funding Source: US Department of Agriculture, Agriculture and Food Research Initiative 
Grant #: USDA 2011-68001-30009   
Study Principal Investigator: Sheryl O. Hughes 
Protocol Date: March 4, 2022 
 
STUDY PROTOCOL AND STATISTICAL ANALYSIS PLAN 
 
BACKGROUND AND RATIONALE 
 
Childhood overweight and obesity have increased significantly in the past 3 decades.1 Rates of 
overweight in the US have more than doubled in younger children; more than 26% of preschool 
aged children are currently overweight or obese.2 Obese children are at an increased risk for poor 
socio-emotional development and problematic medical conditions.3 During the first 5 years of 
life, an increase in weight velocity from 2 to 5 years is the strongest predictor of obesity in early 
adulthood.4 Childhood obesity rates are particularly high in low-income, minority populations.2 
Targeting young children and their families from high-risk groups may help to curb the obesity 
epidemic. 
 
During the first 5 years of life, children learn what, when and how much to eat and what foods 
they prefer.5 Programs developed to prevent childhood obesity in school aged children have had 
moderate success and limited long term impact.6-8 The focus on school age children instead of 
early in life and the lack of inclusion of parents and the family may diminish sustainability of 
behavior change in these programs. The current study will develop and evaluate a novel 
approach to obesity prevention that will incorporate the family and focus on the self-regulation 
of eating in young children. The primary goal of the study will be to encourage and assist parents 
in recognizing and supporting their children to pay attention to their internal cues of fullness and 
satiety. 
 
Experimental studies with preschoolers can inform childhood obesity prevention efforts at an 
early age. Preschool children have the ability to regulate energy intake during meals9,10 and 
across successive meals over 24-hours11 by starting and stopping eating in response to internal 
cues of hunger and fullness. Additionally, though intake at meals was considerably variable, total 
daily energy intake was tightly regulated.11,12 Older children showed poorer compensation 
compared to younger children; thus, children may lose this ability as they grow older.13,14 
Individual differences in this ability have been linked to feeding behaviors. For example, parents 
who reported higher control in feeding had children who showed a lessened ability to self-
regulate their eating.15 Feeding practices, such as encouraging eating when the child is not 
hungry, providing inadequate exposure to novel foods, and serving excessive portion sizes, may 
deter children from attending to internal fullness cues. 
 
Individual differences in child eating self-regulation have been linked to child weight.15-17 Eating 

in absence of hunger (EAH) was associated with higher child and adolescent weight18-21 and poor 
satiety responsiveness was associated with greater weight status among children ages 3-11.22-24 
Children with poorer eating self-regulation are at a greater risk for childhood obesity.  
 
Experimental studies show how children come to prefer novel foods. When exposing young 
children to novel foods, an effect of the amount of exposure on choice and liking was shown.25,26 
It took 8 to 15 or more exposures for children to learn to prefer novel foods25 with results being 
replicated in a social marketing study27 and more naturalistic settings.28 Exposing children to 
novel foods may increase willingness to consume foods such as vegetables; however, most 
parents stop serving new foods to children considerably short of the 8 to 15 recommended 
exposures.27,29  
 
Experimental studies on portion sizes have implications for childhood obesity. Children seen in 
conditions of varying entrée portion size and energy content ate 34% more calories at a single 
meal when served a larger, more energy-dense portion.30 When serving children 3 main entrees 
and a snack over a 24-hour period, total energy intake was 140 kcal greater or 12% higher in the 
large portion condition (double the reference size) relative to the reference condition.31 In an 
observational study in a naturalistic setting, the average kcal of food parents served their 
preschool children for dinner (median = 565 kcal) was greater than the average kcal of food 
parents consumed themselves during the same meal (median = 547 kcal).32 The amount served to 
the child was significantly associated with the amount consumed (r = 0.88). Large portions 
typically served to young children may contribute to childhood obesity.  
 
Routines and structure are associated with better child outcomes; thus home eating routines may 
be important in creating family structure that supports healthful child eating.33,34 Preschool 
children experiencing 3 common household routines which included family dinners had a 40% 
lower prevalence of obesity.35 Unconscious drivers of food choice and intake are also prevalent 
in the larger environment (food advertising, billboards, arrangement of food in the grocery store) 
which may encourage food choices without reasoned awareness of the long term impact on 
childhood obesity.36  
 
It should be noted that numerous programs have been developed to prevent obesity in children, 
mostly in school settings. Some of these programs have had moderate success;6,8 however, the 
growing consensus is that they are of limited effectiveness for the following reasons: 1) 
interventions during the school years do not address child eating patterns developed early in life; 
2) interventions that do not involve parents or families limit the sustainability of behavior 
change; and 3) interventions that focus on only nutrition education and physical activity neglect 
important parental feeding behaviors that can reduce the likelihood of childhood obesity (e.g., 
encouraging preferences for healthy foods, facilitating self-regulation of energy intake, serving 
appropriate child-sized portions, establishing mealtime routines, and addressing food cues in the 
larger environment). Although researchers have begun to develop, evaluate, and disseminate 
family-based obesity prevention programs,5,37,38 few comprehensive obesity prevention programs 
currently exist that focus on the role that parents play in the development of children’s food 
preferences, food selection, and self-regulation of energy intake. Additionally, even fewer 
programs currently exist for preschoolers designed to specifically address the needs of low-
income, minority families.7  

 
The Strategies for Effective Eating Development—SEEDS prevention program will add to the 
field by focusing on the role parents play in the development of child food preferences, food 
selection, and self-regulation of energy intake—known risk factors for childhood obesity in low-
income families with preschoolers. To our knowledge, there are currently no prevention 
programs that address these issues in low-income families. SEEDS will incorporate a dialogue 
approach to adult learning39 and a well-known theoretical approach for behavior change—Self 
Determination Theory.40 The child curriculum will focus specifically on developing food 
preferences, and encouraging self-regulation of energy intake. These same issues will be targeted 
in the parent curriculum along with other parenting behaviors associated with child weight status 
(serving appropriate child-sized portions, establishing mealtime routines, and addressing food 
cues in the environment). Fostering behavior change by delivering similar content to both parents 
and children is expected to increase program impact. 
 
STUDY OBJECTIVE 
 
The goal of this study is to develop and test the efficacy of a scientifically-based, culturally 
competent seven-session parent directed, obesity prevention program focused on parental 
feeding strategies that support young children's self-regulation of intake. 
 
STUDY DESIGN 
 
A randomized controlled trial will be implemented across 2 sites (Houston, an urban city in 
Texas; and Pasco, an agricultural community in Washington) to examine the efficacy of the 
SEEDS childhood obesity prevention program. The prevention arm will receive parent and child 
program curriculums separately over 7 weeks for a total of 7 lessons. One lesson will be held 
each week with parent and child lessons held simultaneously. Each lesson will last about an 
hour. A combined family lesson (parent and child together) will be held before the parent and 
child lessons. All lessons will be held after the school day in Spanish at Head Start centers in 
Houston, TX and similar early education centers in Pasco, WA. The control arm will receive no 
curriculum. Approximately 8 to 10 families will participate in each of the prevention and control 
conditions at each wave. Parents will be asked if they could read and write in English or Spanish 
during eligibility screening so that assistance can be made available at the data collection 
sessions for those who need help completing the questionnaires. Participants in the prevention 
and control arms will complete the same assessments prior to the prevention program (pretest), 
after the program (posttest), and at 6- and 12-month follow-ups. Participants will be 
compensated $40 at pretest, $50 at posttest, $60 at 6 months, and $85 at 12 months.  
 
FACILITATORS 
 
Bilingual staff members will lead the face-to-face groups (i.e., parent, child, and family lessons). 
Parent facilitators will be required to have a graduate degree in psychology or education to 
optimize behavior change that is integrated into the program content. Child facilitators will be 
required to have training or experience in early childhood education. Family lessons will be co-
facilitated by the parent and child facilitators. Facilitator training will include a 2-day intensive 
training session guided by study investigators which will include coverage of the program 

content, delivery of the lessons in practice sessions, and training to maximize participant 
engagement and involvement based on education principles. These principles will be reinforced 
during 2 follow-up training sessions to be held for the facilitators throughout the randomized 
controlled trial. These follow-up training sessions will include maintaining intervention fidelity 
and discussions regarding challenging questions or comments from parents that the facilitators 
experienced and ways to address them. 
 
ASSESSMENT STAFF 
 
A separate set of bi-lingual staff blind to the conditions (prevention and control) will be hired 
and trained to conduct assessments. An undergraduate or master’s level degree will be required. 
To ensure consistency in training, all assessment staff will attend intensive training. 
 
PARTICIPANT ELIGIBILITY AND RECRUITMENT 
 
Families (parent/child dyads) will be recruited from Head Start centers in Houston, Texas and 
childcare centers serving families with low incomes in Pasco, Washington. The Pasco centers 
will be similar to Head Start in that they provide free services and support for families with low 
incomes. The goal of these centers is to ensure that all children enter kindergarten ready to 
succeed. Children who are 3 to 5 years of age with their parent identifying as Hispanic will be 
considered eligible. Exclusion criteria include: parent under the age of 18 and parent and/or child 
had major food allergies, diabetes, or were on special diets, including those who were vegetarian. 
Upon completion of pretest assessments, the project coordinator at each site will use a computer-
based randomization tool to assign participants to 1 of 2 arms using simple randomization. 
Research staff members will work closely with the child development centers regarding 
recruitment procedures. Recruitment activities will be conducted during registration of children 
at the centers, parent meetings and drop off and pick up times. Specifically, research staff will 
explain the goal and activities of the study to interested parents and parents will complete 
informed consent procedures should they choose to participate in the study. The parent who is 
primarily involved in feeding the preschool child will be designated as the target parent. The 
study will be reviewed and approved by the Institutional Review Boards at Baylor College of 
Medicine and Washington State University. Parents will provide informed consent for 
themselves and their children before taking part in the study and assent will be obtained from the 
children as well. 
 
PROGRAM FIDELITY 
 
Observers trained in the curriculum content will conduct fidelity observations on 40% of the 
lessons. Based upon observer availability, the observations will be distributed across parent, 
child and family sessions. Facilitators will not be notified in advance that they would be 
observed. Observers will be different from the facilitators delivering the curriculum. Fidelity will 
be defined as the number of ‘yes’ responses reported by the observer (signifying that the 
facilitator adhered to the lesson component as described in the curriculum) divided by the total 
number of possible responses (i.e., yes, some, and no). 
 
MEASURES 

 
Data collections for both the prevention and control arms will be conducted in small group 
settings led by trained staff members of Hispanic descent who are proficient in reading, 
speaking, and writing in English and Spanish. Data collectors will be blinded to participant group 
allocation. For parents with low literacy skills, data collectors will read the questions to the 
parents and recorded their responses. Child assessments will be completed at the same time as 
the parents in a separate room. Most measures are validated for use with preschoolers and 
Hispanic samples. 
 
Parent Feeding Measures (Practices, Styles, and Knowledge) 
 
Food Parenting Inventory (FPI). The FPI is a parent-report measure of feeding practices with 
16 subscales assessing 3 higher level feeding constructs: 1) Encourage Trying New Foods (offer 
new foods, encourage exploration of new foods, urge child to eat new foods, and repeated 
presentation of new foods), 2) Mealtime Structure (family meals, regular timing of meals and 
snacks, inconsistent mealtimes, indifferent feeding, child involvement in food preparation, parent 
decides portion sizes, and serving measured portions) and 3) External Control (pressure to eat, 
restriction, food as reward, responsiveness to child’s fullness cues, and monitoring).41 
 
Caregiver’s Feeding Styles Questionnaire (CFSQ). The CFSQ is a parent-report questionnaire 
developed to measure feeding styles in parents with low incomes.42 The questionnaire was 
developed for use with parents of children ages 3 to 11. Parents indicate how often they use 7 
child-centered (e.g., reasoning, complimenting) and 12 parent-centered (e.g., demands, threats) 
feeding directives. Two feeding style dimension scores of demandingness and responsiveness are 
derived from the child-centered and parent-centered items. Parents are classified into 4 feeding 
style categories of authoritarian, authoritative, indulgent, and uninvolved. Evidence of test-retest 
reliability, internal consistency, convergent and predictive validity has been demonstrated in 
Hispanic samples and samples with low incomes.42-44 
 
Feeding Knowledge Questionnaire (FKQ). The FKQ was developed for the current study to 
assess the degree to which parents learned the program content. Forty items measure the main 
messages of the program. Sixteen items refer to ‘best practices’ feeding knowledge,11 items refer 
to common misconceptions about feeding, and 11 questions measure parents’ efficacy about 
feeding their child. Other program content is measured as well: 1) exposure to new foods and 2) 
child and parent roles during feeding. 
 
Child Eating Behavior Measures (Self-regulation, Trying New Foods, and Fruit and 
Vegetable Consumption) 
 
Compensation Protocol. Observed trials of children’s response to changes in energy density in 
a meal (compensation trials) will be used to assess child eating self-regulation.15 On 2 separate 
days, children will participate in a two-part meal consisting of 1 of 2 versions of a “drink 
preload” and a standard meal. On each day, the drink preload will be either high (152 kcal) or 
low (3 kcal) in energy. The standard meal, containing about 595 calories or 40% of the daily 
food requirements for 3- to 5-year-olds, will be served 30 minutes later. Consumption will be 
measured by weighing the foods prior to and after the standard meal based on manufacturers’ 

information.15,46 An eating self-regulation score (COMPX) will be calculated by determining 
how each child adjusted his/her intake at the meal based upon the 2 preloads. COMPX has been 
used successfully to evaluate an intervention to improve children’s self-regulation of energy 
intake.47 This measure has been used with preschool aged children;48 it has not been used 
previously with Hispanic samples. 
 
Eating in the Absence of Hunger (EAH). Child eating self-regulation will also be measured by 
the EAH task developed by Fisher and Birch.49 On the day the child receives the high energy 
preload drink as part of the compensation task and approximately 10-15 minutes after finishing 
the standard meal, the child will be presented with sweet and savory snacks along with age 
appropriate toys. Children will be left with the food and toys for 10 minutes and will be told they 
can eat what they want, sit quietly, and/or play with the toys. This task will be administered in 
the centers to several children at once, although children will complete the task individually 
through the use of portable screens creating a separate assessment area for each child. Remaining 
snacks will be measured and total kcal consumed will be calculated. Scores will reflect the total 
number of kcal eaten in the absence of hunger. This assessment has been used predominately 
with White children and has been validated with preschoolers; a few studies have used the EAH 
task with Hispanic children.50 
 
Child Eating Behavior Questionnaire (CEBQ). The CEBQ is a parent-report measure 
assessing 8 dimensions of child eating behaviors.51 Validity and reliability have been 
demonstrated.51 For this study, only the subscales of food responsiveness, emotional overeating, 
and satiety responsiveness are targeted because they are considered parent-report measures of 
child eating behaviors related to eating self-regulation. The CEBQ has shown adequate validity 
and reliability51 and has been used successfully with Hispanic parents of preschoolers with low-
income levels.52 
 
Child Tasting Panel Observation. A standardized food tasting protocol, developed by Sullivan 
and Birch53 and modified by Moding, Bellows, Grimm, & Johnson,54 will be administered to 
measure taste preferences (Yummy, Just OK, or Yucky) and children’s willingness to try new 
foods (1 = tried; 0 = refused). Each child will be asked to try bite-sized samples of 9 familiar and 
novel foods from a variety of food groups including broccoli, beets, couscous, garbanzo beans, 
gouda cheese, grapefruit, kale, okra, and papaya. Each food will be served in a small two-ounce 
cup and include 3 small pieces of the food. This assessment tool was developed for a large, 3-
year longitudinal study of preschoolers in Colorado (41% Hispanic).54  
 
Food Preferences Questionnaire (FPQ). The variety of fruit and vegetables consumed by the 
children will be measured by a food preference questionnaire adapted from Skinner and 
colleagues.29 Parents will report on their child’s food consumption from 112 food and drink 
items using 3 categories: never tried it, tried – liked it, or tried – did not like it. Similar measures 
have been used successfully by the Food and Drug Administration in the Total Diet Study.29 
Only data on the fruit and vegetables will be analyzed given the program emphasis on trying fruit 
and vegetables, and the fact that the vast majority of foods in the questionnaire are fruit and 
vegetables. Two measures will be examined: the total number of vegetables tried out of 50 and 
the total number of fruits tried out of 27. This questionnaire has been used predominately with 
White samples.29 

 
Anthropometrics. Trained staff, following standardized procedures, will measure parent and 
child heights (to the nearest 0.1 cm) and weights (to the nearest 0.1 kg).55 Two height and weight 
measures will be averaged for each parent and child. Age- and gender-specific BMI z-scores for 
each child will be calculated. Children will be classified into healthy weight (5th to < 85th 
percentile), overweight (≥ 85th to < 95th percentile), and obese (≥ 95th percentile) according to 
Centers for Disease Control and Prevention standards.56 BMI scores will be calculated for the 
parent and classified as low and normal weight (BMI < 24.9), overweight (BMI ≥ 25 to <30) or 
obese (BMI ≥ 30). 
 
DATA ANALYSES 
 
All analyses will be intention-to-treat analyses—that is, data from parents and children will be 
analyzed based upon the condition to which they will be initially assigned, regardless of the 
number of classes they attended. This approach, although it reduces power, maintains the internal 
validity of the RCT design.57 Because participants will be nested within classes, the intraclass 
correlations (ICC’s) will be first examined for each dependent variable to determine if a 
statistical approach controlling for such nesting will be necessary. All outcome variables (except 
for child weight status) will be examined using multilevel analyses with the SPSS (version 25) 
Mixed Models Program. The SPSS Mixed Model program does not provide measures of effect 
sizes; however, 95% confidence intervals will be included for precision. Child sex, child age in 
months, and child BMIz at pre-test will be control variables in all of the multilevel analyses. 
Significant condition by time interactions will be followed up with simple main effects analyses 
and multi-level analyses comparing pairs of time points. The main analyses will be conducted on 
participants who have data at all 4 time points. Paired comparisons will use all available data. 
Most of the missing data will be addressed by calculating the subscale scores using the mean of 
the non-missing items in that particular subscale. If greater than 25% of a subscale’s items are 
blank, then the score will be considered missing. The multilevel models also will be rerun 
examining (1 at a time) possible program moderators: child age, child sex, child BMI status, and 
location (Houston versus Pasco). Moderation will be tested by examining the significance of the 
moderator by condition by time interactions.  
 
Finally, to examine dosage effects, the multilevel analyses will be rerun for those variables 
showing significant condition by time interactions. In these analyses, only data from parents in 
the prevention conduction at post-test, 6-months, and 12-months will be examined to determine 
if the number of sessions parents attended predict their subsequent responses on questionnaire 
assessments (the pre-test assessments will not be included in these analyses because these 
sessions occurred before parents attend any classes). In conducting these analyses, the condition 
variable will be replaced by a variable assessing the number of lessons attended (values ranging 
from 0 to 7). To determine if the dosage effects vary by time point, a separate set of analyses will 
include the “lessons attended by time” interaction as a predictor (along with the corresponding 
main effects).  
 
A multinomial logistic regression will be used to examine the effects of the program on 
children’s BMI category (i.e., healthy weight, overweight, and obese). This regression will 
examine the main effect of condition, controlling for the same variables as in the multilevel 

analyses (i.e., child sex, child age in months, and child BMI z-score at pretest).  
 
To control for Type I error, the critical p values for each assessment will be determined with the 
unweighted Bonferroni method,58 dividing the critical value of p < .05 by the number of 
comparisons conducted for a given assessment. As discussed in Shaffer,58 corrections for 
familywise error involve correcting alphas separately for each family of hypotheses. Although 
defining families is a rather straightforward process in a simple experiment (e.g., 1 family in a 
study with a single dependent variable and 1 independent variable with several levels), Shaffer 
argues that defining families becomes more complicated (and potentially more problematic) in 
large, more complex studies where alpha corrections can substantially lower statistical power 
(i.e., increase Type II error). To balance concerns about Type I and Type II error, a family will 
therefore be defined as the set of measures derived from a particular outcome assessment, and an 
alpha correction procedure will then be used (the unweighted Bonferroni) to control for error-
rates within families. The resulting critical p values will be: FPI, 0.05/16 = 0.003; CFSQ, 0.05/3 
= 0.017; FKQ, 0.05/6 = 0.008; compensation trials, 0.05/1 = 0.05; EAH, 0.05/1 = 0.05; FPQ, 
0.05/2 = 0.025; CEBQ, 0.05/8 = 0.006; BMI, 0.05/2 = 0.025. Only results that meet these critical 
values will be reported in the primary analyses. To minimize the probability of Type II error, 
these critical values will be applied only to p values for the simple main effects analyses of time 
given the limited power of condition by time interactions in this type of design.59  
 
Finally, exploratory analyses will be run on variables that show condition by time interactions in 
the pre-post analyses reported by Hughes and colleagues45 but do not show significant 
interactions in the current study. Because the smaller samples at follow-up may reduce the power 
to find significant time by condition interactions at 6- and 12-months, simple main effects 
analyses of time were be run separately for the control and prevention groups to determine if the 
condition effects found in earlier pre-post analyses16 persisted for the variables in the current 
study. 
 
REFERENCES 
 
1. 
Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in 
the United States, 2011-2012. JAMA. Feb 26 2014;311(8):806-814. 
2. 
Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body 
mass index among US children and adolescents, 1999-2010. JAMA. Feb 1 
2012;307(5):483-490. 
3. 
Williams J, Wake M, Hesketh K, Maher E, Waters E. Health-related quality of life of 
overweight and obese children. JAMA. Jan 5 2005;293(1):70-76. 
4. 
McCarthy A, Hughes R, Tilling K, Davies D, Smith GD, Ben-Shlomo Y. Birth weight; 
postnatal, infant, and childhood growth; and obesity in young adulthood: evidence from 
the Barry Caerphilly Growth Study. Am J Clin Nutr. 2007;86(4):907. 
5. 
Birch LL, Ventura AK. Preventing childhood obesity: What works? Int. J. Obesity. 
2009;33(S1):S74-S81. 
6. 
Khambalia AZ, Dickinson S, Hardy LL, Gill T, Baur LA. A synthesis of existing 
systematic reviews and meta‐analyses of school‐based behavioural interventions for 
controlling and preventing obesity. Obes Rev. 2012;13(3):214-233. 

7. 
Kuhl ES, Clifford LM, Stark LJ. Obesity in preschoolers: behavioral correlates and 
directions for treatment. Obesity. 2012;20(1):3-29. 
8. 
Wang Y, Wu Y, Wilson RF, et al. Childhood obesity prevention programs: comparative 
effectiveness review and meta-analysis. Rockville, MD: Agency for Healthcare Research 
and Quality (US); 2013. 
9. 
Birch LL, Deysher M. Conditioned and unconditioned caloric compensation: evidence 
for self-regulation of food intake in young children. Learn. Motiv. 1985;16:341-355. 
10. 
Birch LL, Deysher M. Caloric compensation and sensory specific satiety: evidence for 
self regulation of food intake by young children. Appetite. 1986;7:323-331. 
11. 
Birch LL, Johnson SL, Andresen G, Peters JC, Schulte MC. The variability of young 
children's energy intake. N Engl J Med. 1991;324:232-235. 
12. 
Birch LL, Johnson SL, Jones MB, Peters JC. Effects of a nonenergy fat substitute on 
children's energy and macronutrient intake. Am J Clin Nutr. 1993;58:326-333. 
13. 
Cecil JE, Palmer CN, Wrieden W, et al. Energy intakes of children after preloads: 
adjustment, not compensation. Am J Clin Nutr. Aug 2005;82(2):302-308. 
14. 
Johnson SL, Taylor-Holloway LA. Non-Hispanic white and Hispanic elementary school 
children's self-regulation of energy intake. Am J Clin Nutr. 2006;83:1276-1282. 
15. 
Johnson SL, Birch LL. Parents' and children's adiposity and eating style. Pediatrics. 
1994;94:653-661. 
16. 
Faith MS, Pietrobelli A, Heo M, et al. A twin study of self-regulatory eating in early 
childhood: estimates of genetic and environmental influence, and measurement 
considerations. Int. J. Obesity. 2012;36:931-937. 
17. 
Kral TVE, Allison DB, Birch LL, Stallings VA, Moore RH, Faith MS. Caloric 
compensation and eating in the absence of hunger in 5- to 12-y-old weight-discordant 
siblings. Am J Clin Nutr. 2012;96:574-583. 
18. 
Butte NF, Cai G, Cole SA, et al. Metabolic and behavioral predictors of weight gain in 
Hispanic children: the Viva la Familia Study. Am J Clin Nutr. 2007;85:1478-1485. 
19. 
Faith MS, Berkowitz RI, Stallings VA, Kerns J, Storey M, Stunkard AJ. Eating in the 
absence of hunger: a genetic marker for childhood obesity in prepubertal boys? Obesity 
(Silver Spring). 2006;14:131-138. 
20. 
Fisher JO, Birch LL. Eating in the absence of hunger and overweight in girls from 5 to 7 
y of age. Am J Clin Nutr. 2002;76:226-231. 
21. 
Hill C, Llewellyn CH, Saxton J, et al. Adiposity and 'eating in the absence of hunger' in 
children. Int. J. Obesity. 2008;32:1499-1505. 
22. 
Carnell S, Wardle J. Appetite and adiposity in children: evidence for a behavioral 
susceptibility theory of obesity. Am J Clin Nutr. 2008;88:22-29. 
23. 
Viana V, Sinde S, Saxton J. Children's Eating Behaviour Questionnaire: associations with 
BMI in Portuguese children. British Journal of Nutrition. 2008;100(2):445-450. 
24. 
Webber L, Hill C, Saxton J, Van Jaarsveld C, Wardle J. Eating behaviour and weight in 
children. Int. J. Obesity. 2009;33(1):21. 
25. 
Birch LL, Marlin DW. I don't like it; I never tried it: effects of exposure on two-year-old 
children's food preferences. Appetite. Dec 1982;3(4):353-360. 
26. 
Birch LL, McPhee L, Shoba BC, Pirok E, Steinberg L. What kind of exposure reduces 
children's food neophobia? Looking vs. tasting. Appetite. Dec 1987;9(3):171-178. 
27. 
Johnson SL, Bellows L, Beckstrom L, Anderson J. Evaluation of a social marketing 
campaign targeting preschool children. Am J Health Behav. 2007;31(1):44-55. 

28. 
Cooke L. The importance of exposure for healthy eating in childhood: a review. J Hum 
Nutr Diet. Aug 2007;20(4):294-301. 
29. 
Skinner JD, Carruth BR, Bounds W, Ziegler PJ. Children's food preferences: a 
longitudinal analysis. J. Am. Diet. Assoc. 2002;102(11):1638-1647. 
30. 
Fisher JO. Effects of age on children's intake of large and self-selected food portions. 
Obesity. 2007;15(2):403-412. 
31. 
Fisher JO, Arreola A, Birch LL, Rolls BJ. Portion size effects on daily energy intake in 
low-income Hispanic and African American children and their mothers. Am J Clin Nutr. 
2007;86(6):1709-1716. 
32. 
Johnson SL, Hughes SO, Cui X, et al. Portion sizes for children are predicted by parental 
characteristics and the amounts parents serve themselves. Am J Clin Nutr. 
2014;99(4):763. 
33. 
Hughes S, O’Connor T, Power T. Parenting and children’s eating patterns: examining 
control in a broader context. Int J Child Adolesc Health. 2008;1:323-330. 
34. 
Spagnola M, Fiese BH. Family routines and rituals: a context for development in the lives 
of young children. Infants Young Child. 2007;20(4):284-299. 
35. 
Anderson SE, Whitaker RC. Household routines and obesity in US preschool-aged 
children. Pediatrics. 2010-03-01 00:00:00 2010;125(3):420-428. 
36. 
Wansink B. Environmental factors that increase the food intake and consumption volume 
of unknowing consumers. Annu. Rev. Nutr. 2004;24:455-479. 
37. 
Dattilo AM, Birch L, Krebs NF, Lake A, Taveras EM, Saavedra JM. Need for early 
interventions in the prevention of pediatric overweight: a review and upcoming 
directions. J Obes. 2012;2012:123023-123018. 
38. 
Krishnamoorthy JS, Hart C, Jelalian E. The Epidemic of Childhood Obesity: Review of 
Research and Implications for Public Policy. Social Policy Report. Volume 20, Number 
2. Society for Research in Child Development. 2006;20. 
39. 
Norris J. From Telling to Teaching: A Dialogue Approach to Adult Learning. North 
Myrtle Beach, SC: Learning by Dialogue; 2003. 
40. 
Ryan RM, Deci EL. Self-Determination theory and the facilitation of intrinsic motivation, 
social development, and well-being. Am Psychol. 2000;55(1):68-78. 
41. 
Power TG, Johnson SL, Beck AD, Martinez AD, Hughes SO. The Food Parenting 
Inventory: factor structure, reliability, and validity in a low-income, Latina sample. 
Appetite. Mar 1 2019;134:111-119. 
42. 
Hughes SO, Power TG, Fisher JO, Mueller S, Nicklas TA. Revisiting a neglected 
construct: parenting styles in a child-feeding context. Appetite. 2005;44:83-92. 
43. 
Hughes SO, Power TG, Papaioannou MA, et al. Emotional climate, feeding practices, 
and feeding styles: an observational analysis of the dinner meal in Head Start families. 
The international journal of behavioral nutrition and physical activity. 2011;8:60. 
44. 
Hughes SO, Shewchuk RM, Baskin ML, Nicklas TA, Qu H. Indulgent feeding style and 
children's weight status in preschool. J Dev Behav Pediatr. Oct 2008;29(5):403-410. 
45. 
Hughes SO, Power TG, Beck A, et al. Short-term effects of an obesity prevention 
program among low-income Hispanic families with preschoolers. J Nutr Educ Behav. 
Mar 2020;52(3):224-239. 
46. 
Johnson SL, Taylor-Holloway LA. Non-Hispanic white and Hispanic elementary school 
children's self-regulation of energy intake. Am. J. Clin. Nutr. 2006;83:1276-1282. 

47. 
Johnson SL. Improving preschoolers' self-regulation of energy intake. Pediatrics. 
2000;106:1429-1435. 
48. 
Birch LL, Deysher M. Conditioned and unconditioned caloric compensation: evidence 
for self-regulation of food intake in young children. Learn Motiv. 1985;16:341-355. 
49. 
Fisher JO, Birch LL. Restricting access to foods and children's eating. Appetite. 
1999;32(3):405-419. 
50. 
Lansigan RK, Emond JA, Gilbert-Diamond D. Understanding eating in the absence of 
hunger among young children: a systematic review of existing studies. Appetite. 
2015;85:36-47. 
51. 
Wardle J, Guthrie CA, Sanderson S, Rapoport L. Development of the Children's Eating 
Behaviour Questionnaire. J Child Psychol Psychiatry. 2001;42(7):963-970. 
52. 
Frankel LA, O'Connor TM, Chen TA, Nicklas T, Power TG, Hughes SO. Parents' 
perceptions of preschool children's ability to regulate eating. Feeding style differences. 
Appetite. May 2014;76:166-174. 
53. 
Sullivan SA, Birch LL. Pass the sugar, pass the salt: experience dictates preference. Dev 
Psychol. 1990;26(4):546. 
54. 
Moding KJ, Bellows LL, Grimm KJ, Johnson SL. A longitudinal examination of the role 
of sensory exploratory behaviors in young children's acceptance of new foods. Physiol 
Behav. May 1 2020;218:112821. 
55. 
Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Reference 
Manual. Champaign, IL: Human Kinetics Books; 1998. 
56. 
Centers for Disease Control and Prevention. Defining Childhood Obesity. 2018; 
https://www.cdc.gov/obesity/childhood/defining.html. Accessed August 27, 2020. 
57. 
McCoy CE. Understanding the intention-to-treat principle in randomized controlled 
trials. West J Emerg Med. Oct 2017;18(6):1075-1078. 
58. 
Shaffer JP. Multiple hypothesis testing. Annu Rev Psychol. 1995;46(1):561-584. 
59. 
Brookes ST, Whitely E, Egger M, Smith GD, Mulheran PA, Peters TJ. Subgroup 
analyses in randomized trials: risks of subgroup-specific analyses; power and sample size 
for the interaction test. J. Clin. Epidemiol. Mar 2004;57(3):229-236.