Next Article in Journal
The Role of G Protein-Coupled Receptors in the Regulation of Orthopaedic Diseases by Gut Microbiota
Previous Article in Journal
Eating Disorder Symptoms and Energy Deficiency Awareness in Adolescent Artistic Gymnasts: Evidence of a Knowledge Gap
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Identifying Longitudinal Compliance Patterns and Determinants in a Multifaceted Childhood Obesity Intervention Using Group-Based Trajectory Modeling

by
Shiyu Yan
1,2,
Wenhao Li
3,
Miaobing Zheng
4,
Jinlang Lyu
1,2,
Shuang Zhou
1,2,
Hui Wang
1,2,
Yan Li
5,* and
Haijun Wang
1,2,*
1
Department of Maternal and Child Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
2
Peking University Health Science Center-Weifang Joint Research Center for Maternal and Child Health, Beijing 100191, China
3
Institute of Child Health Care, Jinan Children’s Hospital, Jinan 250022, China
4
Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong 3217, Australia
5
Department of Pediatrics, Shandong Maternal and Child Health Hospital, Jinan 250000, China
*
Authors to whom correspondence should be addressed.
Nutrients 2025, 17(10), 1701; https://doi.org/10.3390/nu17101701 (registering DOI)
Submission received: 13 April 2025 / Revised: 10 May 2025 / Accepted: 14 May 2025 / Published: 16 May 2025
(This article belongs to the Section Nutrition and Obesity)

Abstract

Background/Objectives: Identifying the factors influencing compliance is essential to improve the effectiveness of interventions. However, no study has examined factors that influence the longitudinal patterns of obesity intervention compliance. We aim to identify the longitudinal trajectories of parental and child compliance using group-based trajectory modeling (GBTM) and assess the influencing factors. Methods: The Diet, ExerCIse, and CarDiovascular hEalth Children (DECIDE-Children) was a 9-month app-assisted obesity prevention intervention targeted 8–10-year-old children. Altogether, 684 child–parent pairs from the intervention group were included. Parents were required to use the mobile app to learn health knowledge, monitor children’s diet and exercise behaviors, manage children’s weight, and received the assessment results. Parental compliance was assessed as the monthly usage times and duration of the mobile app. For child compliance, we used data recorded by parents in the “behavior monitoring” module. We employed group-based trajectory modeling (GBTM) to identify distinct trajectories of parental and child compliance and examined their associations with childhood obesity outcomes. Univariate and multivariate logistic regressions were performed to identify the influencing factors associated with the identified compliance groups. Results: Distinct trajectory groups of parental and child compliance were identified. The compliance trajectories of parents and children are related to the extent of changes in the child’s obesity-related outcomes (waist circumference, waist-to-hip ratio, and body fat percentage. p < 0.05). A majority of parents were classified into the “relatively low compliance” group. Parents in this group was associated with having a daughter (OR: 1.95, 95% CI: 1.17, 3.31) and the father having a higher education level (OR: 1.65, 95% CI: 1.05, 2.60). For children, 20.2% were assigned to the “decreasing compliance” group. Children in this group were more likely to have a younger mother (OR: 1.05, 95% CI: 1.01, 1.10) and parents with poorer compliance (OR: 2.36, 95% CI: 1.16, 5.47). Conclusions: Both student and parental compliance were shown to influence the effectiveness of childhood obesity interventions, highlighting the need to prioritize the assessment and promotion of compliance in such interventions. Child sex, paternal educational level, and maternal age were identified as significant factors associated with compliance, while the level of family involvement was found to play a pivotal role in fostering healthy behaviors in children. These findings suggest that future intervention strategies should place greater emphasis on engaging families and providing targeted supervision and support for populations at risk of lower compliance in order to enhance intervention outcomes.
Keywords: obesity; intervention; compliance; trajectory; influencing factors obesity; intervention; compliance; trajectory; influencing factors

Share and Cite

MDPI and ACS Style

Yan, S.; Li, W.; Zheng, M.; Lyu, J.; Zhou, S.; Wang, H.; Li, Y.; Wang, H. Identifying Longitudinal Compliance Patterns and Determinants in a Multifaceted Childhood Obesity Intervention Using Group-Based Trajectory Modeling. Nutrients 2025, 17, 1701. https://doi.org/10.3390/nu17101701

AMA Style

Yan S, Li W, Zheng M, Lyu J, Zhou S, Wang H, Li Y, Wang H. Identifying Longitudinal Compliance Patterns and Determinants in a Multifaceted Childhood Obesity Intervention Using Group-Based Trajectory Modeling. Nutrients. 2025; 17(10):1701. https://doi.org/10.3390/nu17101701

Chicago/Turabian Style

Yan, Shiyu, Wenhao Li, Miaobing Zheng, Jinlang Lyu, Shuang Zhou, Hui Wang, Yan Li, and Haijun Wang. 2025. "Identifying Longitudinal Compliance Patterns and Determinants in a Multifaceted Childhood Obesity Intervention Using Group-Based Trajectory Modeling" Nutrients 17, no. 10: 1701. https://doi.org/10.3390/nu17101701

APA Style

Yan, S., Li, W., Zheng, M., Lyu, J., Zhou, S., Wang, H., Li, Y., & Wang, H. (2025). Identifying Longitudinal Compliance Patterns and Determinants in a Multifaceted Childhood Obesity Intervention Using Group-Based Trajectory Modeling. Nutrients, 17(10), 1701. https://doi.org/10.3390/nu17101701

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop