Abstract
Background:
Few weight management interventions target young children with obesity from low-income minority families.
Objective:
To conduct a nonrandomized, pragmatic, pilot study of an adapted, evidence-based, weight management program (Kids N Fitness [KNF]) customized for children ages 3–7 years (Kids N Fitness Jr. [KNF-JR]) on changes in adiposity, nutrition, and physical activity behaviors.
Methods:
One hundred eighty children (ages 3–16) with ≥85th percentile BMI and their parents participated in one of two 6-week weight management interventions dependent on the child's age: KNF-JR: 3–7 or regular KNF: 8–16. Comparisons were made between baseline anthropometrics and health questionnaire responses, and those from weeks 6 to 18. Two-sample tests for equality of proportions with continuity were used to measure proportions of success between KNF-JR and KNF.
Results:
At week 6, both cohorts showed a mean decrease in BMI z-score (zBMI) of −0.02 (p = 0.3 for KNF-JR [n = 43]; p = 0.02 for KNF [n = 59], with no significant group differences. Among program completers, 75% of KNF-JR and 83% of KNF maintained or lowered zBMI at week 18 (within-group difference p < 0.01). On average across all participants, at week 18 vs. baseline, improvements occurred in screen time (p < 0.01 KNF-JR, p < 0.02 KNF), sweetened beverage intake (p < 0.01 KNF-JR, p = 0.03 KNF), physical activity (p < 0.01 KNF-JR and KNF), and water (p = 0.01 KNF-JR, non-significant KNF) and vegetable (p < 0.01 KNF-JR, p = 0.02 KNF) consumption.
Conclusion:
This pilot demonstrated that an evidence-based weight management program can be adapted for all age groups and results in improved BMI status. Larger, randomized controlled trials are needed to verify effectiveness and sustained impact.
Keywords: body mass index z-score, family-centered interventions, minority, pediatric obesity, weight management, young children
Introduction
Early childhood obesity is a serious public health concern in the United States.1 Between 2011 and 2016, its prevalence among children ages 2–5 years increased from 8.9% to 13.9%, and from 17.5% to 18.4% in children ages 6–11 years.2,3 Obesity rates are highest among black, Hispanic and lower socioeconomic status youth.4–6 Preschool-aged children with obesity are up to five times more likely to remain obese into adulthood,5,6 placing them at higher risk for many chronic conditions such as diabetes and cardiovascular disease.7–12
Current recommendations for addressing childhood obesity promote family-based, multicomponent interventions, which address nutrition education, physical activity, and eating behaviors.13–17 One such program is Kids N Fitness© (KNF), an evidence-based, family-centered weight management program created in 2000 by a multidisciplinary team at Children's Hospital Los Angeles (CHLA) for youth with overweight and obesity between ages 8 and 16 and their families.18,19 The program curriculum consists of nutrition education, physical activity, and goal-setting. It is grounded in a socioecological framework20,21 and Health Belief Model22 where participants are assisted in identifying individual, family, and community barriers and strategies toward their health.
KNF predominately serves low-income, minority populations and has been culturally tailored to focus on urban Hispanic and African American communities with over 3000 families participating to date. It has been disseminated in clinics, after-school programs, churches, and camps. Participants typically show reduced BMI z-score (zBMI), body fat percentage, and/or waist circumference; one study showed significant improvements in blood pressure, lipids, postprandial glucose, and leptin levels among children with pre-existing metabolic syndrome.18,19 In addition, improvements have been observed in nutrition knowledge, behavior change, and activity levels.23,24
Recognizing the importance of addressing childhood obesity in younger children and the paucity of weight management interventions for minority and low-income preschool-aged children,13,25,26 KNF was adapted for children between ages 3 and 7 years and their parents. This pilot study evaluates the implementation of Kids N Fitness Jr. (KNF-JR) to assess its impact on the following: (1) adiposity, (2) nutrition knowledge, and (3) health-promoting behaviors compared to older youth who completed the traditional KNF curriculum. We hypothesized that KNF-JR participants would have a significant decrease in their zBMI and demonstrate improvements in health-promoting behaviors similar to trends seen in older youth who complete the program.27–29
Materials and Methods
Intervention Design
The KNF curriculum was adapted for children ages 3–7 by a team of endocrinologists, registered dietitians, health educators, and research professionals. After an extensive literature review into best practices for health education for young children, newly developed activities and delivery modes were practiced and refined on a preschool class of children ages 4–6.
Like KNF, KNF-JR is a 6-week program. Each weekly 90-minute session includes whole-family nutrition education, followed by play-based physical activity for the youth and concurrent parent support sessions, along with weekly goal-setting and self-monitoring. Topics include understanding food groups and the food label, “the stoplight diet,”30 energy balance, mindful eating, portions, healthy strategies for dining out, a market tour for healthy shopping, and culturally tailored healthy cooking. Parent topics include health risks of obesity, cost- and time-effective meal preparation, and strategies for role-modeling, setting limits, and reinforcing positive behaviors. A healthy snack and take-home incentive that promotes healthful living (e.g., water bottle and pedometer) conclude each session. The program's physical activities do not rely on costly equipment or space, and are replicable at home.
At each session, families are assigned a healthy goal for the week. Goals include eating breakfast, increasing water intake and decreasing juice or soda, walking 10,000 steps, and eating five portions of fruits and vegetables each day. In addition, children (with parental assistance) document their eating and physical activity behaviors daily with a 12 multiple-choice question logbook. Instructors score completed logbooks weekly, providing children with feedback and stickers. The materials and course are in English and Spanish.
Adaptations for KNF-JR included the following: shortened didactic class time with concise messaging, increased hands-on participation, and a greater emphasis on educating parents as they are the primary decision-makers and influencers for this age group. Lessons incorporated active games, crafts, songs, and story-telling that reinforced session objectives. Sample activities included the following: creating healthy MyPlate collages and relay races separating healthy and unhealthy foods into “green light” and “red light” containers. Children helped prepare snacks and ate together providing peer influence to try new foods. The KNF-JR classes were offered on Saturday mornings instead of early evenings to accommodate the earlier schedules of younger children. Handouts with strategies for picky eaters and a calendar with child-friendly active challenges were incorporated into the family workbook. The adaptation summary is described in Table 1.
Table 1.
Regular KNF and KNF Junior Program Comparison and Adaptations
| Regular KNF | KNF junior | |
|---|---|---|
| Participants | Children ages 8–16 years and parents | Children ages 3–7 years and parents |
| Length | 45-minute family nutrition education 45-minute youth physical activity, with simultaneous parent support group |
15- to 20-minute family nutrition education 75-minute child active play and health-themed crafts and games, with simultaneous in-depth parent nutrition education and support group |
| Setting | Weekday evenings from 5:30 to 7:00 pm Department education classroom or conference room at hospital |
Saturday mornings from 10:00 to 11:30 am Preschool setting at hospital's child development center |
| Snacks | Snacks prepared by staff and served to families at the end of class | Children help prepare snacks, serve and eat with parents, or sit and eat together with peers |
| Nutrition education delivery | Interactive didactic utilizing both PowerPoint presentation and small group activities | Play-based activities to demonstrate nutrition education concepts Arts and crafts Storytelling and songs |
| Materials | Notebook and handouts creating a 60-page workbook of nutrition resources | Supplemental handouts added to the KNF workbook specific to recommended nutrition and portions for younger children, picky-eating, and age-appropriate suggestions for active play Stuffed vegetables and fruit character toys used for active games; fruit and vegetable stickers used as positive reinforcement for participation and behavior |
| Physical activity | Circuit-training Relays Sports drills—soccer, basketball Yoga Team games |
Freeze dance Adventure expedition Animal yoga Celery, celery, cookie (duck, duck, goose) Breakfast music parade |
KNF, Kids N Fitness.
Study Design
A quasi-experimental, pragmatic, pilot study was completed to evaluate feasibility, acceptability, and effectiveness of implementing KNF-JR in younger children. The study was approved by the CHLA Institutional Review Board. Informed consent was obtained for all participants. Data were collected at baseline, week 6 (end of intervention), and week 18 (postintervention).
Participants
Youth were referred by medical providers, school nurses, and Head Start coordinators, or self-referred by a parent. Recruitment flyers were posted at CHLA and on local health and wellness listservs. Inclusion criteria included the following: (1) age 3–16, (2) BMI ≥85th percentile, (3) at least one parent willing to participate, and (4) ability to communicate in English or Spanish. Exclusion criteria included the following: (1) medical conditions that prevented physical activity; (2) inability to participate in a group setting due to behavioral issues or developmental disabilities; (3) diabetes, hypertension, cardiac or renal disease, or other medical condition that might affect blood pressure; and 4) on medications or a diet known to influence blood pressure, blood glucose, or weight.
Families were recruited between December 2012 and July 2018. Interested families were scheduled for the informed consent and a baseline visit. Children ages 3–7 were placed in the KNF-JR group and youth ages 8–16 in the KNF group. Cohorts were scheduled when there were at least 20 new referrals in either age group.
Measures
Anthropometrics
Anthropometric measures were obtained for the participant and at least one parent at baseline and 6 and 18 weeks. Weight, height, body fat percentage, fat mass, and basal metabolic rate measurements were obtained for KNF participants and all parents using a Tanita Body Composition Analyzer (Model TBF-215, Tokyo, Japan). A body composition analyzer scale was not validated for use in children under 7; thus, in KNF-JR participants, height and weight were measured to the nearest 0.1 cm using a calibrated stadiometer (Quick Medical, Issaquah, WA) and calibrated scale (Welch Allyn, Skaneateles Falls, NY). BMI was calculated as weight [kg]/height [m2] and zBMI was calculated by expressing a child's BMI relative to children of the same sex and age using CDC growth charts.31 Blood pressure was obtained thrice using an automated device (Criticon Dinamap Monitor, Tampa, FL) and averaged. Waist circumference was measured by making two marks on the top of the participant's iliac crest while supine, and then connecting the marks with a Gulick II tape measure (Country Technology, Inc., Gays Mills, WI) when upright.
Questionnaires
Parents completed a Health Knowledge and Behavior Questionnaire (HKBQ) for themselves and as their child's proxy at baseline, 6 weeks, and 3 months postintervention. The study-specific questionnaire assessed nutrition- and activity-related knowledge, attitudes, and behaviors, and 21 common barriers to maintaining a healthy weight. See Supplementary Data for copy. It was adapted from the Coordinated Approach to Childrens Health (CATCH) and School Physical Activity and Nutrition (SPAN) surveys.32,33 The questionnaire sections consisted of the following: (1) demographics, (2) nutrition label-reading knowledge, (3) nutrition knowledge, (4) parental eating habits, (5) child eating habits, and (6) child food and physical activity behavior over the past week.
Statistical Analysis
The study's primary outcome of interest was zBMI change at weeks 6 and 18 compared to baseline. Paired t-tests were used for normally distributed continuous parameters in two-paired groups (time points), as a per protocol analysis. Categorical variables were presented as counts and percent, and continuous variables as means and standard deviations (SDs). Baseline nutrition knowledge was evaluated as a potential moderator of intervention efficacy. Question groupings measuring healthy behaviors, food-label reading, and nutrition knowledge were given a percentage score “correct” or “positive,” and score changes over time were analyzed by paired t-tests.
To determine program impact on zBMI change, a proportion analysis was done on completers who maintained or reduced zBMI at 6 weeks and 18 weeks vs. youth who increased zBMI. One-sample proportion tests with continuity correction were done for the two groups to examine program effect on zBMI reduction with the hypothesis that success rate was equal to 0.5 with a 95% confidence interval. Two-sample tests for equality of proportions with continuity were used to measure proportions of success between KNF-JR and KNF.
A bivariate analysis of familial baseline characteristics such as ethnicity, income level, educational attainment, and baseline weight of youth participants was completed. Based on the distribution, a Pearson chi-square test was performed across different categories and an independent t-test conducted for the effect-of-interest on KNF groups. For nonparametric statistics, the Mann–Whitney U test (Wilcoxon rank-sum test) was performed. p-Value tests to screen for an association of potential predictors of change in zBMI from baseline to 6 weeks were done with categorical risk factors using the Pearson chi-square test and continuous risk factors using the Mann–Whitney U test when there was non-normal distribution. A 5% significance level was used for all tests. All analyses were conducted using SAS 9.4 (StataCorp, College Station, TX). Retention was measured with attendance-tracking, with program completers defined as attending four or more classes.
Results
Recruitment
From 551 total referrals, we made contact with 358 families, of which 315 child-parent dyads were eligible and 180 provided informed consent to participate (Fig. 1). Common reasons for families declining participation were as follows: transportation issues, scheduling conflicts due to parents' work or child's sports team participation, or wanting individual weight management assistance. Based on the child's age at consent, 72 were assigned to KNF-JR and 108 to KNF.
Figure 1.
Enrollment and retention in KNF programs. KNF, Kids N Fitness; KNF-JR, Kids N Fitness Jr.
Participants
Baseline data were collected on all 180 participants and their parents (Table 2). Participants were predominantly Hispanic (80%) and low income. Most referrals originated from participant's health providers. Parent referrals made up 32% (n = 117) of youth who would comprise the older cohort (ages 8–16) compared to only 6% (n = 28) of younger aged children (ages 3–7). Participants in KNF-JR had significantly higher mean zBMI at baseline compared to participants in the KNF group (+2.50 vs. +2.25, p = 0.0002). Twenty-seven subjects completed baseline measurements (8 KNF-JR and 16 KNF), but never attended any class.
Table 2.
Baseline Characteristics of Youth and Parents
| n (%) | KNF |
KNF junior |
pc | |
|---|---|---|---|---|
| n (%) or mean SDa | n (%) or mean SDa | |||
| Total youth | 180 (100) | 108 (60) | 72 (20) | |
| Female | 98 (54.4) | 56 (51.8) | 42 (58.3) | 0.4 |
| Male | 82 (45.5) | 52 (48.1) | 30 (41.6) | |
| Age | 180 (100) | 11.63 (2.3) | 5.93 (1.2) | <0.01 |
| Race/Ethnicity | 175 (100) | 105 (60) | 70 (40) | 0.1 |
| Hispanic or Latinx | 140 (80) | 84 (80) | 56 (80) | |
| African American or Black | 8 (4.57) | 7 (6.6) | 1 (1.4) | |
| White | 8 (4.57) | 6 (5.7) | 2 (2.8) | |
| Asian | 2 (1.14) | 2 (1.9) | 0 (0.0) | |
| American Indian | 1 (0.57) | 0 (0.0) | 1 (1.4) | |
| Some other race | 2 (1.14) | 1 (0.9) | 1 (1.4) | |
| Mix | 14 (8.00) | 5 (4.7) | 9 (12.8) | |
| BMI | 177 (100) | 30.17 (5.5) | 24.13 (4.3) | <0.01 |
| zBMI | 177 (100) | 2.25 (0.5)b | 2.50 (0.7)b | 0.02 d |
| BMI percentile | 177 (100) | 99.00 (2.0)b | 99.00 (0.7)b | <0.01 d |
| Waist circumference | 174 (100) | 99.91 (14.4) | 78.07 (10.9) | <0.01 |
| Total parents | 184 (100) | 108 (58.7) | 76 (41.3) | |
| Parent age | 178 (100) | 39.90 (7.81) | 37.11 (8.69) | 0.03 |
| Parent gender | 179 (100) | 0.6 | ||
| Female | 152 (84.9) | 89 (83.9) | 63 (86.3) | |
| Male | 27 (15.0) | 19 (17.9) | 13 (17.1) | |
| Parent BMI | 159 (100) | 32.0 (6.4) | 33.2 (6.5) | 0.2 |
| Parent body fat% | 159 (100) | 38.3 (7.5) | 39.8 (8.2) | 0.2 |
| Parent waist circumference | 152 (100) | 104.4 (14.2) | 108.5 (16.9) | 0.1 |
| Parent race | 175 (100) | 106 (60.5) | 69 (39.4) | 0.4 |
| Hispanic or Latinx | 141 (80.5) | 85 (80.1) | 56 (81.1) | |
| African American or Black | 10 (5.7) | 8 (7.5) | 2 (2.9) | |
| White | 11 (6.2) | 7 (6.6) | 4 (5.8) | |
| Asian | 2 (1.1) | 2 (1.8) | 0 (0) | |
| American Indian | 1 (0.5) | 0 (0.0) | 1 (1.4) | |
| Some other race | 2 (1.1) | 1 (0.9) | 1 (1.4) | |
| Mix | 8 (4.5) | 3 (2.8) | 5 (7.2) | |
| Household income | 168 (100) | 104 (61.9) | 64 (38.1) | 0.7 |
| Less than $10,000 | 47 (27.9) | 32 (30.7) | 15 (23.4) | |
| $10,000 to $29,999 | 57 (33.9) | 36 (34.6) | 21 (32.8) | |
| $30,000 to $49,999 | 34 (20.2) | 20 (19.2) | 14 (21.8) | |
| $50,000 to $89,999 | 16 (9.5) | 7 (6.5) | 9 (14.0) | |
| $90,000+ | 14 (8.3) | 9 (8.6) | 5 (7.81) | |
| Highest education level | 175 (100) | 106 (60.5) | 69 (39.4) | 0.04 |
| Up to 8th grade | 32 (18.2) | 24 (22.6) | 8 (11.5) | |
| Some high school (HS) | 20 (11.4) | 16 (15.0) | 4 (5.8) | |
| HS diploma or graduate equivalency degree | 35 (20.0) | 18 (16.9) | 17 (24.6) | |
| Some college | 41 (23.4) | 19 (17.9) | 22 (31.8) | |
| Associates | 17 (9.7) | 10 (9.4) | 7 (10.1) | |
| Bachelor's | 22 (12.5) | 15 (14.1) | 7 (10.1) | |
| Master's/professional | 6 (3.4) | 2 (1.8) | 4 (5.8) | |
| Doctorate | 2 (1.1) | 2 (1.8) | 0 (0.0) | |
| Marital status | 164 (100) | 99 (60.3) | 65 (39.6) | 0.2 |
| Single | 70 (42.6) | 43 (43.4) | 27 (41.5) | |
| Married | 58 (35.3) | 35 (35.3) | 23 (35.3) | |
| Divorced/separated | 7 (4.2) | 6 (6.0) | 1 (1.5) | |
| Widowed | 12 (7.3) | 8 (8.0) | 4 (6.1) | |
| Living with partner | 16 (9.7) | 6 (6.0) | 10 (15.3) | |
| Other | 1 (0.6) | 1 (1.0) | 0 (0.0) |
Bolded numbers on this “p” column represents “statistically significant.”
Categorical variables presented as counts and percent, while continuous variables were presented as mean and SD.
Continuous variables were presented as median and interquartile range, while there is non-normal distribution
p-Value test for association between KNF status and categorical risk factors is chi-square test, while p-value test for association between KNF status and continuous risk factors is using independent t-test. All are using 0.05 as significant level.
p-Value test for association between KNF status and continuous risk factors is using Mann–Whitney U test (Wilcoxon rank-sum test) while there is non-normal distribution. All use 0.05 as significance level.
SD, standard deviation; zBMI, BMI z-score.
Retention
Of the 153 youth, 69% in KNF-JR and 65% in KNF completed the intervention (attended a minimum of four of six classes), with 39% of KNF-JR and 37% KNF participants attending all six sessions.
Anthropometrics
Compared to baseline, KNF-JRs experienced a mean zBMI decrease of −0.02 SD (p = 0.3, n = 43) at week 6 and of −0.05 SD (p = 0.08, n = 33) at week 18. In comparison, KNF participants decreased mean zBMI by −0.02 SD (p = 0.02, n = 59) at week 6 with a further −0.01 SD (p = 0.1) reduction at week 18 (Table 3). There was no significant difference in change in zBMI between KNF-JR and KNF at baseline and week 6 (p = 0.4). Based on the proportion analysis, 31 of 43 KNF-JRs (72%, p < 0.01) and 44 out of 59 of KNF participants (74%, p < 0.01) maintained or decreased zBMI at 6 weeks. In addition, 25 of 33 participants in KNF-JR (75%, p < 0.01) and 26 of 31 in KNF (83%, p < 0.01) maintained or decreased zBMI at week 18. No individual baseline characteristics or demographics predicted change in zBMI or completion status (p > 0.5 for all demographic characteristics and anthropometric measures). Data were unavailable regarding families who consented, but never attended any class.
Table 3.
Comparison of Change in zBMI Across 6-Week Intervention Period and at 3-Month Follow-Up of KNF-JR to KNF Cohorts, and Change in Body Fat Percentage and Fat Mass for KNF
| Baseline (B) Mean (±SD) | Week 6 Mean (±SD) | Week 18 (FU) Mean (±SD) | Difference across visits (p-value) |
||
|---|---|---|---|---|---|
| B to post | B to FU | ||||
| zBMI | |||||
| KNF-JR B to Post (n = 43) B to FU (n = 33) |
2.51 (± 0.6) |
2.49 (± 0.5) |
2.46 (± 0.4) |
0.3 | 0.08 |
| KNF B to Post (n = 59) B to FU (n = 32) |
2.17 (± 0.4) |
2.15 (± 0.4) |
2.14 (± 0.4) |
0.02 | 0.1 |
| Waist circumference | |||||
| KNF-JR B to Post (n = 42) B to FU (n = 34) |
78.55 (± 10.7) |
77.93 (± 10.6) |
80.09 (± 9.4) |
0.06 | 0.5 |
| KNF B to Post (n = 60) B to FU (n = 32) |
99.6 (± 15.0) |
99.58 (± 15.2) |
98.47 (± 15.8) |
0.9 | 0.4 |
| Body fat percentagea | |||||
| KNF B to Post (n = 59) B to FU (n = 31) |
40.0% (±7.9) |
39.1% (±8.0) |
38.8% (±9.2) |
0.01 <0.01 |
0.6 |
| Fat massa | |||||
| KNF B to Post (n = 59) B to FU (n = 31) |
29.61 (±14.0) |
28.63 (±12.9) |
29.22 (±15.1) |
0.01 | 0.1 |
Body fat percentage and fat mass were only measured for KNFular participants. At the time of study, there was not a validated bioimpedance scale for children younger than 7 years of age.
KNF-JR, Kids N Fitness Jr.
Parent Anthropometrics
Parents had mean baseline BMIs of 33.2 and 32.0 kg/m2 (KNF-JR and KNF, respectively), with no significant change in BMI at week 6 or 18 in either group (p = 0.5 and p = 0.3).
Results from the HKBQ
KNF-JR parents increased food label literacy by 11% (p = 0.01) and reported improvements in their child choosing the healthier option at weeks 6 (+17.6%, p < 0.01) and 18 (+20.7%, p < 0.01) (Table 4). Notably, KNF-JRs increased their daily consumption of vegetables from 1.7 (±1.6) to 2.5 (±1.6) (p < 0.01) servings and water from 3.7 (±1.8) glasses to 4.5 (±1.2) (p < 0.01), and reduced sugar-sweetened beverages from 1.5 (±1.3) to 0.8 (±0.9) glasses/day (p < 0.01) and sweets servings from 3.2 (±1.4) times/week to 2.3 (±1.3) (p < 0.01). Screen time decreased from an average of 3.3 (±2.0) hours/day at baseline to 2.4 (±2.3) hours at week 6 (p < 0.02) and 1.9 (±1.4) hours/day (p < 0.01) at week 18. Conversely, outdoor active play time (p = 0.01) and time that the family exercised together (p < 0.01) increased. The average time that children were physically active for ≥20 minutes increased from 2.8 (±2.0) to 4.7 (±1.6) times/week (p < 0.01). At 3 months postintervention, the majority of these behaviors had been maintained and/or improved (Table 4).
Table 4.
Health Knowledge and Behavioral Changes for Kids N Fitness Junior
| |
Baseline vs. week 6 post |
Baseline vs. 18 week follow-up |
||||||
|---|---|---|---|---|---|---|---|---|
| |
Baseline |
Post-week 6 |
|
|
Baseline |
3 Months postintervention |
|
|
| Independent variable | n | n (%) or |
n (%) or |
pb | n | n (%) or |
n (%) or |
pb |
| Mean (SD)a | Mean (SD)a | Mean (SD)a | Mean (SD)a | |||||
| Number of perceived barriers toward being healthy | 34 | 4.58 (2.50) | 3.26 (2.23) | 0.0014 | 28 | 4.61 (2.17) | 3.36 (2.36) | 0.0301 |
| Food label knowledge score* | 33 | 53% (21.8) | 65% (31.1) | 0.0137 | 32 | 53% (27.9) | 68% (23.2) | 0.0083 |
| Nutrition knowledge score | 42 | 64% (14.0) | 67% (16.5) | 0.1416 | 34 | 62% (11.8) | 69% (14.1) | 0.0461 |
| Parental eating habits score** | 40 | 79% (20.5) | 90% (16.1) | 0.0107 | 31 | 80% (24.9) | 90% (14.6) | 0.0165 |
| Child's eating habits score** | 38 | 60% (30.2) | 77% (27.2) | 0.0013 | 31 | 59% (29.4) | 80% (25.1) | 0.0027 |
| In the past 7 days, how many times did your child | ||||||||
| Exercise for ≥20 minutes? | 40 | 2.85 (2.09) | 4.75 (1.66) | <0.0001 | 31 | 2.65 (2.01) | 4.87 (1.28) | <0.0001 |
| Play outdoors? | 38 | 4.07 (1.97) | 4.82 (1.97) | 0.01 | 32 | 3.94 (1.95) | 5.25 (1.08) | 0.0003 |
| Do physical activity together with you? | 40 | 2.28 (2.00) | 3.38 (2.29) | 0.0026 | 32 | 2.16 (1.89) | 3.09 (2.16) | 0.0166 |
| Eat sweets (cake, cookies, candies, etc.)? | 37 | 3.22 (1.40) | 2.30 (1.39) | 0.0004 | 29 | 3.34 (1.08) | 2.45 (1.15) | 0.0024 |
| In the past 24 hours, how many times did your child | ||||||||
| Eat vegetables? | 38 | 1.74 (1.57) | 2.50 (1.67) | 0.0016 | 32 | 1.71 (1.21) | 2.66 (1.71) | 0.0037 |
| Drink a glass of water? | 40 | 3.77 (1.88) | 4.49 (1.27) | 0.0184 | 32 | 3.84 (1.86) | 4.19 (1.27) | 0.2122 |
| Drink a glass of juice or soda? | 39 | 1.51 (1.34) | 0.85 (0.93) | 0.0021 | 32 | 1.53 (1.46) | 0.59 (0.67) | 0.0008 |
| Spend in hours watching TV, on the computer, playing video games, or on a phone? | 40 | 3.38 (2.05) | 2.45 (2.29) | 0.0293 | 31 | 3.35 (2.21) | 1.97 (1.40) | 0.0034 |
Consists of three knowledge questions regarding different elements of understanding a food label.
Both the child and parent eating habits section of the survey consists of nine questions with pictures of two choices of similar foods, one healthier than the other. Parents are asked to circle which food “you (or your child) would choose more often” for breakfast, for snack, for dinner, and to drink. The score is averaged.
Categorical variables were presented as counts and percent, while continuous variables were presented as mean and standard deviation.
p-Value test for mean difference between two groups is using Paired t-test. All of them are using 0.05 as significant level.
The top 3 barriers to being healthy cited by KNF-JR parents included the following: “My child… really loves to eat and is always hungry” (65%); “gets angry when I feed him/her something he/she doesn't like” (39%); and “eats out of boredom” (36%). The barriers most cited by parents of the older children were as follows: “My child watches too much TV, computer, or iPad” (69%), “really loves to eat and is always hungry” (60%), and “doesn't like to be active” (50%). KNF-JR parents at baseline selected on average 4.5 (±2.5) barriers. At program end, the average number of barriers was reduced to 3.2 (±2.2) (p < 0.01). KNF parents reported similarly significant improvements in eating habits and increased activity.
Discussion
The majority of children in the adapted KNF-JR program experienced modest zBMI reductions at weeks 6 and 18, similar to trends seen in KNF. This modest decrease is comparable to many studies of this age range, despite variance in intervention length and intensity.34–40 For older youth, the goal of lifestyle modification treatment is to achieve a zBMI reduction of 0.2–0.3 SD, which is associated with improvement in obesity-related comorbidities.41 However, for preschool-aged children, weight maintenance has been recommended as the first treatment goal, given that the anticipated height increase then results in BMI percentile reduction and associated improved health outcomes.42 In this study, the high percentage of participants who maintained or lowered their zBMI by program end (72% KNF-JR, 75% KNF) and at 18 weeks (75% KNF-JR, 83% KNF) is promising in considering sustainability of behavior change across ages.
A unique feature of our intervention is the weekly logbook as a self-monitoring tool to develop awareness of and track behavior changes, which are often precursors to weight loss. Similar to previous KNF studies, families in both groups improved their food label knowledge and healthy behaviors.18,19,23,24 These outcomes lend support to the core KNF curriculum having impact in improving health behaviors even when adapted for a younger age.
Another encouraging outcome was the relatively high retention rate, suggesting that both programs were well accepted by families. Poor attendance is a frequent challenge in family-based pediatric weight management programs, with attrition ranging from 49% to 83%, whereas KNF-JR and KNF attrition rates were 31% and 35%, respectively.43–47 In exit interviews, many families attributed their engagement and adherence to the positive group setting in which children exercised alongside peers who looked like them and families learned together, held each other accountable, and provided support.
Interestingly, KNF-JR received only one-third of all referrals, suggesting what other literature has corroborated—that parents and clinicians are less likely to recognize and/or address obesity in young children compared to older children unless it is severe.48–50 This was substantiated by the significantly higher mean baseline zBMI for KNF-JR compared to KNF youth.
Our findings add to the emerging body of literature exploring the impact of obesity treatment programs in minority, preschool-aged children. Like the KNFJR/KNF curricula, many programs include family involvement, cultural tailoring, lifestyle modification, physical activity, and nutrition education.40,51 Barkin et al. reported successful outcomes in absolute BMI among low-income Latino preschool-aged children in a 12-week community-based program.39 However, only 45% of their cohort had obesity, whereas 80% of KNF-JRs had a BMI ≥98th%ile. Another multidisciplinary program, studied by Wickel et al., of predominantly Hispanic 2- to 6-year olds with obesity and severe obesity, showed encouraging impact with significant decrease in %BMIp95 (p = 0.017), delivered in six clinical visits over 12 months by health professionals.38 Conversely, the KNF-JR/KNF interventions provide 13.5 hours of curriculum content (half of the recommended 26 hours in clinical practice guidelines), yet are delivered in a more intensive timeframe over 6 weeks. The KNFJR/KNF programs utilize a “train the trainer” component that enables the curricula to be taught by health educators rather than high-level, high-cost health professionals. This approach allows KNFJR/KNF to be more accessible, especially in underresourced communities.
While these results are encouraging, certain study limitations should be noted. This was a pragmatic pilot study to evaluate implementation of this adapted intervention compared to the standard curriculum. While the KNF subjects were used as a comparison cohort, this study was not randomized and had no nontreatment control group. The study was only 18 weeks and thus could not evaluate long-term impact of this intervention. Another shortcoming was the large number of participants lost to follow-up. Families with a positive experience in the program may have been more likely to return for follow-up measurements, possibly biasing our results. The use of zBMI also likely weakened our ability to measure subtle weight changes. Existing literature indicates that zBMI may not be an accurate tool for monitoring adiposity change in very young children with obesity, particularly those >97th BMI percentile.52–54
Conclusions
The KNF curriculum is an evidence-based weight management program proven to be feasible and effective in reducing zBMI in children and adolescents. Retention for both cohorts was high, suggesting that this intervention, which harnesses family participation, addresses challenges, and is culturally and socially sensitive, may result in an improved engagement. Given the paucity of interventions targeting early childhood obesity in minority and low-income populations, the data and curriculum elements from the KNF-JR pilot help illuminate what may be effective in improving obesity trends in demographics highly impacted by this medical condition. Additional research is warranted to find effective programs that meet the needs of underserved pediatric communities.
Ethics Approval and Consent to Participate
The study protocol has been reviewed and approved by the Children's Hospital Los Angeles Institutional Review Board (CCI-12-00312).
Availability of Data and Material
The datasets from this study will be available from the corresponding author on written request.
Supplementary Material
Acknowledgments
Ms. Mei Yu Yeh and Ji Hoon Ryoo, Ph.D, performed the statistical analyses, and helped interpret results. Anita Britt, Ph.D, former Executive Director of Children's Hospital Los Angeles' Childcare Development Center (CDC), allowed us to test certain KNF-JR lesson plans on a CDC preschool class and provided consultation on the new delivery modalities of the KNF-JR curriculum.
Disclaimer
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders.
Authors' Contributions
Ms. M.L.-I. was responsible for conceptualization and design of the study, analysis and interpretation of data, drafting the initial article, critically reviewing and revising of the article, obtaining funding, and supervision. Ms. B.M. and Ms. S.G. helped draft the initial article and critically reviewed and revised the article. Dr. A.P.V., Dr. M.E.G., Ms. G.F., and Ms. E.I. helped critically review and revise the article. All authors approved the final article as submitted and agree to be accountable for all aspects of the work.
Funding Information
This project was supported by endowment funds from the Flora L. Thornton Foundation and grants from the Safeway Foundation and the Sugar Ray Leonard Family Foundation. The funding agencies are not involved in the design, data collection, analysis, interpretation, or writing.
Author Disclosure Statement
No competing financial interests exist.
Supplementary Material
References
- 1. Childhood Obesity Facts—Prevalence of Childhood Obesity in the United States. Updated June 24, 2019. Available at https://www.cdc.gov/obesity/data/childhood.html Last accessed November 19, 2020.
- 2. Skinner AC, Ravanbakht SN, Skelton JA, et al. Prevalence of obesity and severe obesity in US children, 1999-2016. Pediatrics 2018;141:e20173459. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Hales CM, Fryar CD, Carroll MD, et al. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007–2008 to 2015–2016. JAMA 2018;16:1723–1725. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. National Center for Health Statistics (US). Health, United States, 2011: With Special Feature on Socioeconomic Status and Health. Hyattsville (MD): National Center for Health Statistics (US); 2012 May. Report No.: 2012-1232. PMID: 22812021. [PubMed] [Google Scholar]
- 5. Cunningham SA, Kramer MR, Narayan KM. Incidence of childhood obesity in the United States. N Engl J Med 2014;370:1660–1661. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. (CDC) CfDCaP. Vital signs: Obesity among low-income, preschool-aged children—United States, 2008–2011. MMWR Morb Mortal Wkly Rep 2013;62:629–634. [PMC free article] [PubMed] [Google Scholar]
- 7. Kelsey MM, Zaepfel A, Bjornstad P, Nadeau KJ. Age-related consequences of childhood obesity. Gerontology 2014;60:222–228. [DOI] [PubMed] [Google Scholar]
- 8. Ward ZJ, Long MW, Resch SC, et al. Simulation of growth trajectories of childhood obesity into adulthood. N Engl J Med 2017;377:2145–2153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Lindberg L, Danielsson P, Persson M, et al. Association of childhood obesity with risk of early all-cause and cause-specific mortality: A Swedish prospective cohort study. PLoS Med 2020;17:e1003078. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Parsons TJ, Power C, Logan S, Summerbell CD. Childhood predictors of adult obesity: A systematic review. Int J Obes Relat Metab Disord 1999;23 Suppl 8:S1–S107. [PubMed] [Google Scholar]
- 11. Singh AS, Mulder C, Twisk JW, et al. Tracking of childhood overweight into adulthood: A systematic review of the literature. Obes Rev 2008;9:474–488. [DOI] [PubMed] [Google Scholar]
- 12. Rundle AG, Factor-Litvak P, Suglia SF, et al. Tracking of obesity in childhood into adulthood: Effects on body mass index and fat mass index at age 50. Child Obes 2020;16:226–233. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Foster BA, Farragher J, Parker P, Sosa ET. Treatment interventions for early childhood obesity: A systematic review. Acad Pediatr 2015;15:353–361. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Berge JM, Everts JC. Family-based interventions targeting childhood obesity: A meta-analysis. Child Obes 2011;7:110–121. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Barlow SE, Committee E. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: Summary report. Pediatrics 2007;120 Suppl 4:S164–S192. [DOI] [PubMed] [Google Scholar]
- 16. Styne DM, Arslanian SA, Connor EL, et al. Pediatric obesity-assessment, treatment, and prevention: An endocrine society clinical practice guideline. J Clin Endocrinol Metab 2017;102:709–757. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Seo DC, Sa J. A meta-analysis of obesity interventions among U.S. minority children. J Adolesc Health 2010;46:309–323. [DOI] [PubMed] [Google Scholar]
- 18. Monzavi R, Dreimane D, Geffner ME, et al. Improvement in risk factors for metabolic syndrome and insulin resistance in overweight youth who are treated with lifestyle intervention. Pediatrics 2006;117:e1111–e1118. [DOI] [PubMed] [Google Scholar]
- 19. Dreimane D, Safani D, MacKenzie M, et al. Feasibility of a hospital-based, family-centered intervention to reduce weight gain in overweight children and adolescents. Diabetes Res Clin Pract 2007;75:159–168. [DOI] [PubMed] [Google Scholar]
- 20. Bronfenbrenner U. Ecological models of human development. Read Dev Child 1994;2:37–43. [Google Scholar]
- 21. Quick V, Martin-Biggers J, Povis GA, et al. A socio-ecological examination of weight-related characteristics of the home environment and lifestyles of households with young children. Nutrients 2017;9:604. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Rosenstock IM, Strecher VJ, Becker MH. Social learning theory and the Health Belief Model. Health Educ Q 1988;15:175–183. [DOI] [PubMed] [Google Scholar]
- 23. Wright K, Norris K, Newman Giger J, Suro Z. Improving healthy dietary behaviors, nutrition knowledge, and self-efficacy among underserved school children with parent and community involvement. Child Obes 2012;8:347–356. [DOI] [PubMed] [Google Scholar]
- 24. Wright K, Suro Z. Using community—Academic partnerships and a comprehensive school-based program to decrease health disparities in activity in school-aged children. J Prev Interv Community 2014;42:125–139. [DOI] [PubMed] [Google Scholar]
- 25. Towner EK, Clifford LM, McCullough MB, et al. Treating obesity in preschoolers: A review and recommendations for addressing critical gaps. Pediatr Clin North Am 2016;63:481–510. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Monasta L, Batty GD, Macaluso A, et al. Interventions for the prevention of overweight and obesity in preschool children: A systematic review of randomized controlled trials. Obes Rev 2011;12:e107–e118. [DOI] [PubMed] [Google Scholar]
- 27. Boles RE, Scharf C, Stark LJ. Developing a treatment program for obesity in preschool-age children: Preliminary data. Childrens Health Care 2010;39:34–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Skinner JD, Carruth BR, Wendy B, Ziegler PJ. Children's food preferences: A longitudinal analysis. J Am Diet Assoc 2002;102:1638–1647. [DOI] [PubMed] [Google Scholar]
- 29. Savage JS, Fisher JO, Birch LL. Parental influence on eating behavior: Conception to adolescence. J Law Med Ethics 2007;35:22–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Epstein LH, Squires S. The Stoplight Diet for Children: An Eight-Week Program for Parents and Children, 1st ed. Little, Brown: Boston, MA, 1988:xiii, p. 232. [Google Scholar]
- 31. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC growth charts: United States. Adv Data 2000;314:1–27. [PubMed] [Google Scholar]
- 32. Kelder S, Hoelscher DM, Barroso CS, et al. The CATCH Kids Club: A pilot after-school study for improving elementary students' nutrition and physical activity. Public Health Nutr 2005;8:133–140. [DOI] [PubMed] [Google Scholar]
- 33. Thiagarajah K, Fly AD, Hoelscher DM, et al. Validating the food behavior questions from the elementary school SPAN questionnaire. J Nutr Educ Behav 2008;40:305–310. [DOI] [PubMed] [Google Scholar]
- 34. Stark LJ, Spear S, Boles R, et al. A pilot randomized controlled trial of a clinic and home-based behavioral intervention to decrease obesity in preschoolers. Obesity (Silver Spring) 2011;19:134–141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Quattrin T, Roemmich JN, Paluch R, et al. Efficacy of family-based weight control program for preschool children in primary care. Pediatrics 2012;130:660–666. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Barkin SL, Heerman WJ, Sommer EC, et al. Effect of a behavioral intervention for underserved preschool-age children on change in body mass index: A randomized clinical trial. JAMA 2018;320:450–460. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Crespo NC, Talavera GA, Campbell NR, et al. A randomized controlled trial to prevent obesity among Latino paediatric patients. Pediatr Obes 2018;13:697–704. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Wickel EE, Ali L, Hawkins H, Hemming E. Results of a referral-based weight management program targeted toward children aged 2 to 6 years with obesity or severe obesity. BMC Pediatr 2019;19:504. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Barkin SL, Gesell SB, Po'e EK, Escarfuller J, et al. Culturally tailored, family-centered, behavioral obesity intervention for Latino-American preschool-aged children. Pediatrics 2012;130:445–456. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Ling J, Robbins LB, Wen F, Zhang N. Lifestyle interventions in preschool children: A meta-analysis of effectiveness. Am J Prev Med 2017;53:102–112. [DOI] [PubMed] [Google Scholar]
- 41. Grossman DC, Bibbins-Domingo K, Curry SJ, et al. Screening for obesity in children and adolescents: US preventive services task force recommendation statement. US Preventive Services Task Force. JAMA 2017;317:2417–2426. [DOI] [PubMed] [Google Scholar]
- 42. Spear BA, Sarah Barlow SE, Ervin C, et al. Recommendations for treatment of child and adolescent overweight and obesity. Pediatrics 2007;120 (Supplement 4):S254–S288. [DOI] [PubMed] [Google Scholar]
- 43. Williams NA, Coday M, Somes G, et al. Risk factors for poor attendance in a family-based pediatric obesity intervention program for young children. J Dev Behav Pediatr 2010;31:705–712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44. Cote MP, Byczkowski T, Kotagal U. Service quality and attrition: An examination of a pediatric obesity program. Int J Qual Health Care 2004;16:165–173. [DOI] [PubMed] [Google Scholar]
- 45. Skelton JA, DeMattia LG, Flores G. A pediatric weight management program for high-risk populations: A preliminary analysis. Obesity (Silver Spring) 2008;16:1698–1701. [DOI] [PubMed] [Google Scholar]
- 46. Skelton JA, Martin S, Irby MB. Satisfaction and attrition in paediatric weight management. Clin Obes 2016;6:143–153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Kirk S, Zeller M, Claytor R, et al. The relationship of health outcomes to improvement in BMI in children and adolescents. Obes Res 2005;13:876–882. [DOI] [PubMed] [Google Scholar]
- 48. O'Brien SH, Holubkov R, Reis EC. Identification, evaluation, and management of obesity in an academic primary care center. Pediatrics 2004;114:e154–e159. [DOI] [PubMed] [Google Scholar]
- 49. Jain A, Sherman SN, Chamberlin LA, et al. Why don't low-income mothers worry about their preschoolers being overweight? Pediatrics 2001;107:1138–1146. [DOI] [PubMed] [Google Scholar]
- 50. Taveras EM, Hohman KH, Price SN, et al. Correlates of participation in a pediatric primary care-based obesity prevention intervention. Obesity (Silver Spring) 2011;19:449–452. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Colquitt JL, Loveman E, O'Malley C, et al. Diet, physical activity, and behavioural interventions for the treatment of overweight or obesity in preschool children up to the age of 6 years. Cochrane Database Syst Rev 2016;3:CD012105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52. Flegal KM, Wei R, Ogden CL, et al. Characterizing extreme values of body mass index-for-age by using the 2000 Centers for Disease Control and Prevention growth charts. Am J Clin Nutr 2009;90:1314–1320. [DOI] [PubMed] [Google Scholar]
- 53. Vanderwall C, Eickhoff J, Randall Clark R, Carrel AL. BMI z-score in obese children is a poor predictor of adiposity changes over time. BMC Pediatr 2018;18:187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54. Freedman DS, Butte NF, Taveras EM, et al. The limitations of transforming very high body mass indexes into z-scores among 8.7 million 2- to 4-year-old children. J Pediatr 2017;188:50–56.e1. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets from this study will be available from the corresponding author on written request.