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基于家庭的行为减肥治疗方案中父母自我监测模式的预测因素。

Predictors of parent self-monitoring patterns in a family-based behavioral weight loss treatment program.

机构信息

Department of Pediatrics, University of California, San Diego, CA, USA.

Herbert Wertheim School of Public Health and Longevity Science, University of California, San Diego, CA, USA.

出版信息

Int J Obes (Lond). 2024 Oct;48(10):1457-1464. doi: 10.1038/s41366-024-01574-8. Epub 2024 Jul 15.

Abstract

OBJECTIVE

Self-monitoring dietary intake is a critical component of family-based intensive health behavior and lifestyle treatment for pediatric obesity, but adherence rates are often low. This study identifies predictors of parent self-monitoring rates during treatment.

METHODS

A secondary analysis of parent self-monitoring data from a randomized controlled trial involving 150 parent-child dyads. Patterns of self-monitoring were identified using a latent class mixed model approach. Logistic regression analyses evaluated predictors of self-monitoring patterns.

RESULTS

Latent class models identified two trajectory groups: a high consistent self-monitoring group and a low-decreasing self-monitoring group. When compared to parents in the low group, parents in the high group lost more weight throughout treatment. Children in the high group had a similar trajectory for weight loss; however, the groups were not statistically different. Higher levels of family chaos and poorer family problem-solving skills were associated with higher odds of being in the low group.

CONCLUSION

This study identified two patterns of rates of parent self-monitoring, which were associated with parent weight loss and were differentiated by family chaos and poor problem-solving. These findings suggest that families with high levels of chaos and poor problem-solving could benefit from early intervention to improve outcomes in pediatric obesity treatment programs.

TRIAL REGISTRATION

Clinicaltrials.gov Identifier: NCT01197443.

摘要

目的

自我监测饮食摄入是基于家庭的密集健康行为和生活方式治疗儿童肥胖的关键组成部分,但依从率往往较低。本研究旨在确定治疗期间父母自我监测率的预测因素。

方法

对涉及 150 对父母-子女的随机对照试验中的父母自我监测数据进行二次分析。使用潜在类别混合模型方法确定自我监测模式。逻辑回归分析评估了自我监测模式的预测因素。

结果

潜在类别模型确定了两个轨迹组:高一致自我监测组和低-递减自我监测组。与低组的父母相比,高组的父母在整个治疗过程中体重减轻更多。高组儿童的体重减轻轨迹相似,但两组无统计学差异。家庭混乱程度较高和家庭解决问题能力较差与处于低组的可能性较高相关。

结论

本研究确定了父母自我监测率的两种模式,与父母体重减轻相关,并且通过家庭混乱和解决问题能力差来区分。这些发现表明,家庭混乱程度较高和解决问题能力较差的家庭可能需要早期干预,以改善儿童肥胖治疗计划的结果。

试验注册

Clinicaltrials.gov 标识符:NCT01197443。

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