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在复杂适应性世界中扩大母乳喂养项目。

Scaling up breastfeeding programmes in a complex adaptive world.

作者信息

Pérez-Escamilla Rafael, Hall Moran Victoria

机构信息

Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, USA.

Maternal and Infant Nutrition and Nurture Unit, Brook Building, University of Central Lancashire, Preston, UK.

出版信息

Matern Child Nutr. 2016 Jul;12(3):375-80. doi: 10.1111/mcn.12335. Epub 2016 May 10.

Abstract

The 2016 Breastfeeding Lancet Series continues to provide unequivocal evidence regarding the numerous benefits that optimal breastfeeding practices offer to children and women worldwide and the major savings that improving these practices can have as a result of their major public health benefits. Unfortunately, this knowledge remains underutilized as there has been little progress scaling up effective breastfeeding programmes globally. Improving the uptake and scaling up of effective national breastfeeding programmes that are potent enough to improve exclusive breastfeeding duration should be a top priority for all countries. Complex analysis systems longitudinal research is needed to understand how best to empower decision makers to achieve this goal through well-validated participatory decision-making tools to help their countries assess baseline needs, including costs, as well as progress with their scaling-up efforts. Sound systems thinking frameworks and scaling-up models are now available to guide and research prospectively future scaling-up efforts that can be replicated, with proper adaptations, across countries.

摘要

《柳叶刀》2016年母乳喂养系列文章继续提供了明确证据,表明最佳母乳喂养做法能给全球儿童和妇女带来诸多益处,且由于这些做法具有重大公共卫生效益,改善这些做法能带来可观的节省。不幸的是,这方面的知识仍未得到充分利用,因为全球在扩大有效母乳喂养项目方面进展甚微。加强有效国家母乳喂养项目的推广,使其足以提高纯母乳喂养时长,应成为所有国家的首要任务。需要复杂的分析系统和纵向研究,以了解如何通过经过充分验证的参与式决策工具,最好地赋能决策者实现这一目标,帮助各国评估基线需求,包括成本,以及扩大规模努力的进展情况。现在已有完善的系统思维框架和扩大规模模型,可前瞻性地指导和研究未来的扩大规模努力,这些努力经过适当调整后可在各国复制。

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