Childhood Obesity
Conditions
Keywords
Obesity, Intervention, Preschool, Management, Children
Brief summary
The PKU-FeeD trial is a cluster-randomized controlled trial conducted in Jinan, Shandong Province, China. This study aims to: 1) Develop and evaluate a digital health-assisted, multidisciplinary intervention for preschool children with obesity, assessing its effectiveness and cost-effectiveness. 2) Investigate how lifestyle-based interventions influence the composition and function of the gut microbiota in obese preschoolers, and elucidate the mechanisms by which these interventions may modulate gut microbiota to affect obesity-related metabolic phenotypes.
Detailed description
Childhood obesity has become a global public health challenge, and early prevention and management are crucial to curbing its epidemic. However, compared to school-aged children, evidence on effective obesity interventions for preschoolers remains limited and inconsistent. While preventive approaches may have broader population-level implications, targeted management interventions may be more cost-effective in settings with lower obesity prevalence but rising trends, providing foundational evidence for future preventive strategies. The gut microbiota plays a key role in host energy metabolism and metabolic homeostasis, and its dysbiosis is strongly linked to obesity. Diet and physical activity, as core components of lifestyle interventions, may significantly shape gut microbial ecology, potentially influencing host metabolism and obesity-related outcomes. However, due to challenges in sample collection, existing studies on gut microbiota in children are scarce, with small sample sizes, and few intervention studies have established causal relationships. The interplay between healthy lifestyle interventions, gut microbiota, and childhood obesity remains understudied, and the underlying mechanisms require further exploration. Thus, this trial seeks to: 1) determine effectiveness of a digital health-supported, comprehensive intervention for preschool obesity management. 2) Elucidate causal relationships between dietary behaviors, gut microbiota, and obesity in preschoolers.
Interventions
BEHAVIORALFamily engaged, enhanced Diet intervention
The family component includes health education via books, lectures, and short videos, parenting skills training, regular monitoring of child growth, and behavior goal setting through the mobile health platform. Motivational interviewing via telephone provides tailored behavioral support. Kindergartens assist in health education, supervise dietary intake and physical activity, monitor children's growth monthly, and maintain communication with families. Hospitals provide targeted health counseling and facilitate clinic access as needed. The mobile health platform integrates modules for health education, smart growth curve tracking, behavior goal management, and home-school-hospital collaboration.
Sponsors
Peking University
Shandong Maternal and Child Health Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
SINGLE (Outcomes Assessor)
Masking description
Randomization will be performed after the baseline survey. The assessors measuring childrens' health indicators will be blinded at follow-up phases.
Eligibility
Sex/Gender
ALL
Age
4 Years to 6 Years
Healthy volunteers
No
Inclusion criteria
* The child's primary caregivers can proficiently use smart phones. * Child is expected to remain in the same kindergarten for at least one year. * No use of antibiotics or probiotic supplements, no acute stress events (e.g., trauma or severe infection), gastrointestinal symptoms (e.g., abdominal pain, constipation, diarrhea), or vaccinations within the 3 months prior to stool sample collection. * Parents voluntarily agree to participate in the study and provide written informed consent.
Exclusion criteria
* Obesity caused by genetic factors, diseases (e.g., endocrine disorders, central nervous system damage), or medication use. * History of major organ diseases, including cardiovascular, pulmonary, hepatic, or renal conditions (e.g., heart disease, hypertension, asthma). * Children following special diets (e.g., vegetarians). * Children with pathological eating disorders or medical conditions that limit physical activity.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| children's BMI-Z change | at end of the 9-month intervention | Calculated based on height and weight using WHO standards. The primary outcome is the difference between two arms in the change of children's BMI-Z scores from baseline to the end of the intervention. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| children's BMI-Z change | at 21-month follow-up. | Calculated based on height and weight using WHO standards. The primary outcome is the difference between two arms in the change of children's BMI-Z scores from baseline to follow-up. |
| Body Mass Index (BMI) | at the end of the 9-month intervention; at 21-month follow-up. | BMI is calculated from measured height and weight. |
| Waist Circumference | at the end of the 9-month intervention; at 21-month follow-up | Waist circumference is measured at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest to evaluate central adiposity. |
| waist-to-Height Ratio, WHtR | at the end of the 9-month intervention; at 21-month follow-up. | Calculated by dividing waist circumference by height, used as an indicator of fat distribution and risk for metabolic complications. |
| Systolic and Diastolic Blood Pressures | at the end of the 9-month intervention; at 21-month follow-up. | Blood pressure is measured using an electronic sphygmomanometer with the child seated after resting, to assess cardiovascular health. |
| Body Composition | at the end of the 9-month intervention | Body fat percentage is assessed using a bioelectrical impedance analyzer (MC-780A, TANITA, Tokyo, Japan). |
| Prevalence and Incidence of Overweight/Obesity | at the end of the 9-month intervention; at 21-month follow-up | The proportion of children classified as overweight or obese according to WHO and Chinese standards, including newly identified cases at follow-up. |
| Dietary Intake | at the end of the 9-month intervention | Total energy intake, macronutrient distribution, and food group consumption will be assessed using three consecutive 24-hour dietary recalls. Changes in dietary quality and structure will be evaluated. |
| Children's Eating Behaviors | at the end of the 9-month intervention | Assessed using the Children's Eating Behavior Questionnaire (CEBQ), measuring dimensions such as food responsiveness, satiety responsiveness, and emotional eating |
| Parental Feeding Practices (CPCFBS) | at the end of the 9-month intervention | Measured using the Chinese Preschooler's Caregivers Feeding Behavior Scale (CPCFBS), evaluating dimensions such as monitoring, pressure to eat, and food restriction. |
| Time Spent in Physical Activity | at the end of the 9-month intervention | 1)Children will wear an ActiGraph accelerometer for 7 consecutive days. Time spent in light, moderate, and vigorous physical activity will be calculated to evaluate changes in physical activity patterns. 2) Evaluated using the Children's Leisure Activities Study Survey (CLASS), assessing the amount and type of physical activity and sedentary behavior, including screen time. |
| Sedentary Behavior and Screen Time | at the end of the 9-month intervention | 1)Children will wear an ActiGraph accelerometer for 7 consecutive days. Time spent in light, moderate, and vigorous physical activity will be calculated to evaluate changes in physical activity patterns. 2) Evaluated using the Children's Leisure Activities Study Survey (CLASS), assessing the amount and type of physical activity and sedentary behavior, including screen time. |
| Gut Microbial Composition | at the end of the 9-month intervention | Stool samples will be collected at baseline and post-intervention. Gut microbial composition is measured by 16S rRNA sequencing |
Countries
China
Contacts
PRINCIPAL_INVESTIGATORHaijun Wang, PhD
Peking University
Outcome results
None listed