Chetwynd Ellen, Demirci Jill, Yourkavitch Jennifer
Department of Family Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Department of Health Promotion and Development, School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA.
J Hum Lact. 2025 Feb;41(1):22-25. doi: 10.1177/08903344241305669. Epub 2024 Dec 18.
Exclusive breastfeeding, as recommended by the World Health Organization (WHO) for the first 6 months of life, is a critical metric for evaluating maternal and infant feeding practices and health outcomes. Despite its importance, inconsistencies in defining and measuring breastfeeding exclusivity present challenges for research comparability and interpretation. Equally, research design, outcomes of interest, and study resources are necessary considerations when collecting and analyzing exclusive breastfeeding data, and may require the adaption of standardized questions and techniques to individual situations. This paper explores key considerations for researchers when operationalizing and measuring exclusive breastfeeding. We address the nuances of point prevalence and since-birth measures, highlighting their influence on study outcomes and data interpretation. Statistical approaches for analyzing exclusivity data, including logistic regression, survival analysis, and Kaplan-Meier methods, are also discussed. By outlining best practices for precise definitions, tailored data collection, and transparent reporting, this paper aims to provide an overview for precise definition, effective data collection, and clear interpretation.
世界卫生组织（WHO）建议在生命的前6个月进行纯母乳喂养，这是评估母婴喂养方式和健康结果的一项关键指标。尽管其很重要，但在定义和衡量纯母乳喂养方面存在的不一致给研究的可比性和解读带来了挑战。同样，在收集和分析纯母乳喂养数据时，研究设计、感兴趣的结果以及研究资源都是需要考虑的因素，可能需要根据具体情况调整标准化问题和技术。本文探讨了研究人员在实施和衡量纯母乳喂养时的关键考虑因素。我们阐述了点患病率和自出生以来的测量方法的细微差别，强调了它们对研究结果和数据解读的影响。还讨论了分析纯母乳喂养数据的统计方法，包括逻辑回归、生存分析和Kaplan-Meier方法。通过概述精确界定、量身定制的数据收集和透明报告的最佳做法，本文旨在为精确界定、有效数据收集和清晰解读提供一个概述。
