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超重和肥胖成年人体重管理的移动应用程序和网络应用程序:最新综合评价与荟萃分析

Mobile and Web Apps for Weight Management in Overweight and Obese Adults: An Updated Umbrella Review and Meta-Analysis.

作者信息

Couto Felipe da Fonseca Silva, de Almeida Carlos Podalirio Borges

机构信息

Professional Master's Program in Family Health (PROFSAÚDE), Institute of Health and Biological Studies, Federal University of the South and Southeast of Pará (UNIFESSPA), Avenida dos Ipês, s/n, Cidade Universitária, Loteamento Cidade Jardim, Marabá 68508-970, Pará, Brazil.

出版信息

Int J Environ Res Public Health. 2025 Jul 21;22(7):1152. doi: 10.3390/ijerph22071152.


DOI:10.3390/ijerph22071152
PMID:40724217
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12294216/
Abstract

Obesity is a global epidemic with substantial health and economic impacts, making scalable weight management strategies essential. A comprehensive synthesis of eHealth interventions for weight management is needed to guide clinical practice. This umbrella review evaluated mobile and web-based interventions for weight loss in adults with overweight or obesity, compared to conventional or non-intervention controls. Systematic reviews were identified across five electronic databases from inception to February 2025. Two reviewers independently selected studies and assessed methodological quality using AMSTAR 2. Pooled estimates were calculated using random-effects models. Eleven systematic reviews (261 primary studies, 62,407 participants) were included. Mobile app interventions yielded a significant reduction in body weight (MD = -1.32 kg; I = 82%), as did long-term eHealth interventions (MD = -1.13 kg; I = 76%). Most meta-analyses showed high heterogeneity. Web-based interventions showed no significant effect. In conclusion, mobile apps and long-term eHealth interventions resulted in modest but statistically significant reductions in body weight, body mass index, and waist circumference. The evidence for web-based approaches remains inconclusive. Further research should focus on low-resource settings, primary care, and the integration of emerging technologies such as artificial intelligence. (PROSPERO CRD42025644218).

摘要

肥胖是一种具有重大健康和经济影响的全球性流行病,因此需要可扩展的体重管理策略。需要对电子健康干预措施进行全面综合,以指导体重管理的临床实践。本系统综述评估了与传统或无干预对照相比,针对超重或肥胖成年人的基于移动设备和网络的减肥干预措施。从开始到2025年2月,在五个电子数据库中进行了系统综述。两名评审员独立选择研究,并使用AMSTAR 2评估方法学质量。使用随机效应模型计算合并估计值。纳入了11项系统综述(261项原始研究,62407名参与者)。移动应用程序干预使体重显著减轻(MD = -1.32 kg;I = 82%),长期电子健康干预也是如此(MD = -1.13 kg;I = 76%)。大多数荟萃分析显示异质性较高。基于网络的干预措施未显示出显著效果。总之,移动应用程序和长期电子健康干预导致体重、体重指数和腰围适度但有统计学意义的降低。基于网络方法的证据仍然不明确。进一步的研究应侧重于资源匮乏地区、初级保健以及人工智能等新兴技术的整合。(PROSPERO CRD42025644218)

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本文引用的文献

[1]
The Role of Artificial Intelligence in Obesity Risk Prediction and Management: Approaches, Insights, and Recommendations.

Medicina (Kaunas). 2025-2-19

[2]
Umbrella review of social inequality in digital interventions targeting dietary and physical activity behaviors.

NPJ Digit Med. 2025-1-6

[3]
The Effectiveness of Digital Health Lifestyle Interventions on Weight Loss in People With Prediabetes: A Systematic Review, Meta-Analysis, and Meta-Regression.

J Diabetes Sci Technol. 2024-11-7

[4]
Global health impacts of high BMI: A 30-Year analysis of trends and disparities across regions and Demographics.

Diabetes Res Clin Pract. 2024-11

[5]
Effects of Mobile Applications on Weight-Related, Behavior and Metabolic Outcomes for Adults with Overweight and Obesity: A Systematic Review and Meta-Analysis.

Stud Health Technol Inform. 2024-7-24

[6]
Effects of mHealth Practice Patterns on Improving Metabolic Syndrome Using the Information-Motivation-Behavioral Skills Model.

Nutrients. 2024-7-1

[7]
Burden of disease and direct costs to the health system attributable to high body mass index in Brazil.

Public Health. 2024-8

[8]
Effectiveness of an Artificial Intelligence-Assisted App for Improving Eating Behaviors: Mixed Methods Evaluation.

J Med Internet Res. 2024-5-7

[9]
Early outcomes of referrals to the English National Health Service Digital Weight Management Programme.

Obesity (Silver Spring). 2024-6

[10]
Effectiveness and Implementation of a Text Messaging mHealth Intervention to Prevent Childhood Obesity in Mexico in the COVID-19 Context: Mixed Methods Study.

JMIR Mhealth Uhealth. 2024-4-9

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