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

**Authors:** Shiyu Yan, Wenhao Li, Miaobing Zheng, Jinlang Lyu, Shuang Zhou, Hui Wang, Yan Li, Haijun Wang

PMC · DOI: 10.3390/nu17101701 · Nutrients · 2025-05-16

## TL;DR

This study examines how compliance with a childhood obesity intervention changes over time and finds that parental and child compliance patterns are linked to better health outcomes.

## Contribution

The study introduces the use of group-based trajectory modeling to analyze longitudinal compliance patterns in childhood obesity interventions.

## Key findings

- Parental and child compliance trajectories are associated with improvements in obesity-related outcomes like waist circumference and body fat percentage.
- Parents with higher education levels and those with daughters are more likely to show low compliance.
- Children with younger mothers and parents with poor compliance are more likely to show decreasing compliance over time.

## 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.

## Linked entities

- **Diseases:** obesity (MONDO:0011122)

## Full-text entities

- **Diseases:** Obesity (MESH:D009765)

## Full text

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## Figures

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## References

42 references — full list in the complete paper: https://tomesphere.com/paper/PMC12114602/full.md

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Source: https://tomesphere.com/paper/PMC12114602