Rossato Sinara L, Fuchs Sandra C
Rev Saude Publica. 2014 Oct;48(5):845-50. doi: 10.1590/s0034-8910.2014048005154.
Epidemiological studies have shown the effect of diet on the incidence of chronic diseases; however, proper planning, designing, and statistical modeling are necessary to obtain precise and accurate food consumption data. Evaluation methods used for short-term assessment of food consumption of a population, such as tracking of food intake over 24h or food diaries, can be affected by random errors or biases inherent to the method. Statistical modeling is used to handle random errors, whereas proper designing and sampling are essential for controlling biases. The present study aimed to analyze potential biases and random errors and determine how they affect the results. We also aimed to identify ways to prevent them and/or to use statistical approaches in epidemiological studies involving dietary assessments.
流行病学研究已经表明饮食对慢性病发病率的影响；然而，要获得精确且准确的食物消费数据，需要进行恰当的规划、设计以及统计建模。用于短期评估人群食物消费的评估方法，比如24小时食物摄入量追踪或食物日记，可能会受到该方法固有的随机误差或偏差的影响。统计建模用于处理随机误差，而恰当的设计和抽样对于控制偏差至关重要。本研究旨在分析潜在的偏差和随机误差，并确定它们如何影响结果。我们还旨在确定预防这些偏差和随机误差的方法，以及在涉及饮食评估的流行病学研究中运用统计方法的方式。
