School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Callaghan, New South Wales, Australia.
Clinical Research Design, IT, and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute (HMRI), New Lambton Heights, New South Wales, Australia.
Obes Rev. 2019 Jul;20(7):964-982. doi: 10.1111/obr.12845. Epub 2019 Mar 13.
Maximizing the benefits of investments in obesity research requires effective interventions to be adopted and disseminated broadly across populations (scaled-up). However, interventions often need considerable adaptation to enable implementation at scale, a process that can reduce the effects of interventions. A systematic review was undertaken for trials that sought to deliver an obesity intervention to populations on a larger scale than a preceding randomized controlled trial (RCT) that established its efficacy. Ten scaled-up obesity interventions (six prevention and four treatment) were included. All trials made adaptations to interventions as part of the scale-up process, with mode of delivery adaptations being most common. A meta-analysis of body mass index (BMI)/BMI z score (zBMI) from three prevention RCTs found no significant benefit of scaled-up interventions relative to control (standardized mean difference [SMD] = 0.03; 95% CI, -0.09 to 0.15, P = 0.639 - I = 0.0%). All four treatment interventions reported significant improvement on all measures of weight status. Pooled BMI/zBMI data from prevention trials found significantly lower effects among scaled-up intervention trials than those reported in pre-scale-up efficacy trials (SMD = -0.11; 95% CI, -0.20 to -0.02, P = 0.018 - I = 0.0%). Across measures of weight status, physical activity/sedentary behaviour, and nutrition, the effects reported in scaled-up interventions were typically 75% or less of the effects reported in pre-scale-up efficacy trials. The findings underscore the challenge of scaling-up obesity interventions.
为了使肥胖症研究的投资效益最大化,需要在人群中广泛推广和传播有效的干预措施(扩大规模)。然而,干预措施通常需要进行大量的调整,以便在大规模实施时能够实现,而这个过程可能会降低干预措施的效果。因此,我们进行了一项系统综述,旨在评估那些试图在先前已证实其有效性的随机对照试验(RCT)的基础上,将肥胖干预措施推广至更大人群的试验。共有 10 项扩大规模的肥胖干预措施(6 项预防措施和 4 项治疗措施)被纳入研究。所有试验都对干预措施进行了调整,以适应扩大规模的需要,其中最常见的是交付方式的调整。对 3 项预防 RCT 的体重指数(BMI)/BMI z 评分(zBMI)进行的 meta 分析发现,与对照组相比,扩大规模的干预措施并没有显著的获益(标准化均数差[SMD] = 0.03;95%置信区间,-0.09 至 0.15,P = 0.639 - I² = 0.0%)。所有 4 项治疗干预措施均报告了所有体重状态指标的显著改善。来自预防试验的汇总 BMI/zBMI 数据发现,与预扩大规模的有效性试验相比,扩大规模的干预试验的效果显著降低(SMD = -0.11;95%置信区间,-0.20 至 -0.02,P = 0.018 - I² = 0.0%)。在体重状态、身体活动/久坐行为和营养方面的各项指标中,扩大规模的干预措施的效果通常为预扩大规模的有效性试验报告的效果的 75%或以下。这些发现凸显了扩大肥胖症干预措施规模所面临的挑战。