Johnston Bradley C, Rozga Mary, Guyatt Gordon H, Hand Rosa K, Handu Deepa, Klatt Kevin C, Bala Malgorzata M
Department of Nutrition, College of Agriculture and Life Sciences, Texas A&M University, College Station, Texas, USA.
Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, Texas, USA.
BMJ Nutr Prev Health. 2025 Apr 7;8(1):e000832. doi: 10.1136/bmjnph-2023-000832. eCollection 2025.
Despite evidence that nutrition can play a substantial role in curbing the burden of chronic disease, findings reported in the nutrition literature have been plagued with debate and uncertainty, including questions about the confidence we can place in evidence from observational studies, the validity of dietary intake data, and the applicability of randomised trials to real-world patients or members of the public. Structured nutrition users' guides (NUGs) to evaluate common research study designs (ie, randomised trials, cohort studies, systematic reviews and clinical practice guidelines) addressing nutrition questions will help clinicians and their patients, as well as health service workers and policy-makers, use the evidence to make more informed decisions on disease management and prevention. In addition, NUGs will provide comprehensive teaching materials for nutrition trainees on how to appraise, interpret and apply the research evidence. We hereby introduce a series of structured NUGs for the literature on nutrients, foods and dietary patterns and programmes. Each article will address three key components when assessing different study designs used to assess nutrition interventions or exposures, including (1) assessing the methodological quality of the study, (2) interpreting study results (magnitude and precision of treatment or exposure effects for outcomes of benefit and harm) and (3) applying the results to unique patient or population scenarios based on their health-related values and preferences related to the potential benefits, harms, convenience and cost of an intervention. This series of articles will serve to empower clinicians, health service workers and health policy-makers to better understand the validity, interpretability and applicability of the nutrition literature, while also helping practitioners and their clients make more evidence-based, value-sensitive and preference-sensitive nutrition decisions.
尽管有证据表明营养在减轻慢性病负担方面可发挥重要作用,但营养文献中报道的研究结果一直饱受争议且存在不确定性,包括我们对观察性研究证据的可信度、饮食摄入数据的有效性以及随机试验对现实世界患者或公众的适用性等问题。结构化的营养用户指南(NUGs)用于评估针对营养问题的常见研究设计(即随机试验、队列研究、系统评价和临床实践指南),这将有助于临床医生及其患者,以及卫生服务工作者和政策制定者利用这些证据就疾病管理和预防做出更明智的决策。此外,NUGs将为营养专业学员提供关于如何评估、解释和应用研究证据的综合教学材料。我们在此介绍一系列针对营养素、食物、饮食模式和计划文献的结构化NUGs。每篇文章在评估用于评估营养干预或暴露的不同研究设计时将涉及三个关键要素,包括(1)评估研究的方法学质量,(2)解释研究结果(有益和有害结局的治疗或暴露效应的大小和精确度),以及(3)根据患者或人群与干预潜在益处、危害、便利性和成本相关的健康相关价值观和偏好,将结果应用于独特的患者或人群情况。这一系列文章将有助于临床医生、卫生服务工作者和卫生政策制定者更好地理解营养文献的有效性、可解释性和适用性,同时也帮助从业者及其客户做出更基于证据、对价值敏感和对偏好敏感的营养决策。
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