Naska Androniki, Lagiou Areti, Lagiou Pagona
Department of Hygiene, Epidemiology and Medical Statistics School of Medicine, National and Kapodistrian University of Athens, 75 M. Asias Street, Goudi, GR-115 27, Athens, Greece.
Department of Public Health and Community Health,, School of Health Professions, Athens Technological Educational Institute (TEI Athens), Ag. Spyridonos, Aigaleo GR-122 43, Athens, Greece.
F1000Res. 2017 Jun 16;6:926. doi: 10.12688/f1000research.10703.1. eCollection 2017.
Self-reported dietary intake is assessed by methods of real-time recording (food diaries and the duplicate portion method) and methods of recall (dietary histories, food frequency questionnaires, and 24-hour dietary recalls). Being less labor intensive, recall methods are more frequently employed in nutritional epidemiological investigations. However, sources of error, which include the participants' inability to fully and accurately recall their intakes as well as limitations inherent in the food composition databases applied to convert the reported food consumption to energy and nutrient intakes, may limit the validity of the generated information. The use of dietary biomarkers is often recommended to overcome such errors and better capture intra-individual variability in intake; nevertheless, it has its own challenges. To address measurement error associated with dietary questionnaires, large epidemiological investigations often integrate sub-studies for the validation and calibration of the questionnaires and/or administer a combination of different assessment methods (e.g. administration of different questionnaires and assessment of biomarker levels). Recent advances in the omics field could enrich the list of reliable nutrition biomarkers, whereas new approaches employing web-based and smart phone applications could reduce respondent burden and, possibly, reporting bias. Novel technologies are increasingly integrated with traditional methods, but some sources of error still remain. In the analyses, food and nutrient intakes always need to be adjusted for total daily energy intake to account for errors related to reporting.
自我报告的饮食摄入量通过实时记录方法(食物日记和双份食物法)和回忆方法(饮食史、食物频率问卷和24小时饮食回忆)进行评估。由于劳动强度较低,回忆方法在营养流行病学调查中使用更为频繁。然而,误差来源,包括参与者无法完全准确地回忆其摄入量,以及应用于将报告的食物摄入量转换为能量和营养素摄入量的食物成分数据库中固有的局限性,可能会限制所生成信息的有效性。人们经常建议使用饮食生物标志物来克服此类误差,并更好地捕捉个体内部摄入量的变异性;然而,它也有自身的挑战。为了解决与饮食问卷相关的测量误差,大型流行病学调查通常会纳入子研究以对问卷进行验证和校准,和/或采用不同评估方法的组合(例如,使用不同的问卷并评估生物标志物水平)。组学领域的最新进展可以丰富可靠营养生物标志物的清单,而采用基于网络和智能手机应用程序的新方法可以减轻受访者的负担,并可能减少报告偏差。新技术越来越多地与传统方法相结合,但一些误差来源仍然存在。在分析中,食物和营养素摄入量总是需要根据每日总能量摄入量进行调整,以考虑与报告相关的误差。