移动健康对东南亚地区国家初级卫生保健机构中有非传染性疾病风险或患有非传染性疾病的个人改变饮食习惯和身体活动的有效性——一项系统综述和荟萃分析

IF 0.2 Q4 MEDICINE, GENERAL & INTERNAL International Journal of Noncommunicable Diseases Pub Date : 2022-10-01 DOI:10.4103/jncd.jncd_59_22
B. Banerjee, D. Dutt, I. Saha, B. Paul, A. Lachyan
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引用次数: 0

摘要

背景:非传染性疾病(NCDs)正在增加,其中一些行为风险因素是主要关注的问题。mHealth已被发现能有效地改变这些行为模式。目的:评估mHealth技术在东南亚地区国家初级保健环境中对患有非传染性疾病或其危险因素的个体的饮食习惯和体育活动的改变的有效性。材料和方法:进行了系统回顾和荟萃分析,主要结果是mHealth在改善饮食习惯和增加体育活动方面的有效性。文章从PubMed、Cochrane Central、Google Scholar和Pre-print服务器检索,然后进行正向和反向搜索。评估纳入研究的质量和偏倚风险。使用RevMan v.5.4.1软件进行荟萃分析。异质性采用χ2检验进行检验,并采用I2统计量进行测量,最终结果为Forest图。结果:七项研究中的九份出版物符合审查条件,其中七份在印度进行,两份在孟加拉国进行。所有研究都采用了不同的mHealth干预措施。大多数研究报告了在社区/工作场所减少饮食不足/不当和体育活动不足/改善方面的有益效果,但有两项研究报告没有明显影响,这两项研究都来自孟加拉国。荟萃分析显示,干预组和对照组在饮食能量减少和水果/蔬菜增加的汇总估计方面存在统计学显著差异。尽管水果/蔬菜研究之间不存在异质性,但这两项研究的质量和偏倚都有所降低。关于饮食能量摄入的研究除了具有较高的偏倚风险外,还具有较高的统计异质性。因此,对结果的解释需要谨慎。没有观察到对增加体力活动的影响。结论:mHealth干预措施在促进行为改变方面具有巨大潜力。然而,在其潜在规模扩大之前,还需要更多的研究。
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Effectiveness of mHealth for modification of dietary habits and physical activity among individuals at risk or suffering from noncommunicable diseases in primary healthcare settings in South East Asian Region countries – A systematic review and meta-analysis
Background: Noncommunicable diseases (NCDs) are increasing, for which some behavioral risk factors are major concerns. mHealth has been found to be effective in changing these behavioral patterns. Objective: To assess effectiveness of mHealth technology in modification of dietary habits and physical activity, among individuals having NCDs or their risk factors, in primary healthcare settings in South East Asian Region Countries. Materials and Methods: A systematic review and meta-analysis was done with the primary outcome as effectiveness of mHealth for improving dietary practices and increasing physical activity. Articles were retrieved from PubMed, Cochrane Central, Google Scholar, and Pre-print servers followed by forward and backward searching. Quality and risk of bias of included studies were assessed. Meta-analysis was performed using RevMan v. 5.4.1 software. Heterogeneity was tested using χ2 test and measured using I2 statistic, with Forest plots as the final outcome. Results: Nine publications from seven studies, of which seven were conducted in India and two in Bangladesh, qualified for the review. All studies used varied mHealth interventions. Most studies reported beneficial effects in reducing inadequate/improper diet and insufficient/improving physical activity, at community/workplace settings, except two studies reporting no apparent impact, both being from Bangladesh. Meta-analysis revealed statistically significant differences between intervention and control groups for pooled estimates of reduced dietary energy and increased fruits/vegetables. Although heterogeneity is absent between studies considered for fruits/vegetables, both studies were compromised in quality and bias. Studies on dietary energy intake had high statistical heterogeneity, in addition to having high risk of bias. Hence, the results need to be interpreted with caution. No effect was observed on increasing physical activity. Conclusion: mHealth interventions have huge potential to facilitate behavior change. However, more research is needed before its potential scale-up.
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