Goode James P, Smith Kylie J, Kilpatrick Michelle, Breslin Monique, Oddy Wendy H, Dwyer Terence, Venn Alison J, Magnussen Costan G
Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
Oxford Martin School and Nuffield Department of Obstetrics and Gynaecology, George Institute for Global Health, University of Oxford, Oxford, United Kingdom.
Front Nutr. 2021 Apr 7;8:624305. doi: 10.3389/fnut.2021.624305. eCollection 2021.
Qualitative food frequency questionnaires (Q-FFQ) omit portion size information from dietary assessment. This restricts researchers to consumption frequency data, limiting investigations of dietary composition (i.e., energy-adjusted intakes) and misreporting. To support such researchers, we provide an instructive example of Q-FFQ energy intake estimation that derives typical portion size information from a reference survey population and evaluates misreporting. A sample of 1,919 Childhood Determinants of Adult Health Study (CDAH) participants aged 26-36 years completed a 127-item Q-FFQ. We assumed sex-specific portion sizes for Q-FFQ items using 24-h dietary recall data from the 2011-2012 Australian National Nutrition and Physical Activity Survey (NNPAS) and compiled energy density values primarily using the Australian Food Composition Database. Total energy intake estimation was daily equivalent frequency × portion size (g) × energy density (kJ/g) for each Q-FFQ item, summed. We benchmarked energy intake estimates against a weighted sample of age-matched NNPAS respondents ( = 1,383). Median (interquartile range) energy intake was 9,400 (7,580-11,969) kJ/day in CDAH and 9,055 (6,916-11,825) kJ/day in weighted NNPAS. Median energy intake to basal metabolic rate ratios were 1.43 (1.15-1.78) in CDAH and 1.35 (1.03-1.74) in weighted NNPAS, indicating notable underreporting in both samples, with increased levels of underreporting among the overweight and obese. Using the Goldberg and predicted total energy expenditure methods for classifying misreporting, 65 and 41% of CDAH participants had acceptable/plausible energy intake estimates, respectively. Excluding suspected CDAH misreporters improved the plausibility of energy intake estimates, concordant with expected body weight associations. This process can assist researchers wanting an estimate of energy intake from a Q-FFQ and to evaluate misreporting, broadening the scope of diet-disease investigations that depend on consumption frequency data.
定性食物频率问卷(Q-FFQ)在膳食评估中省略了食物分量信息。这使得研究人员只能获取食物消费频率数据,限制了对膳食组成(即能量调整摄入量)的调查以及对误报情况的研究。为了帮助这些研究人员,我们提供了一个Q-FFQ能量摄入量估算的指导性示例,该示例从参考调查人群中得出典型的食物分量信息,并对误报情况进行评估。1919名年龄在26至36岁的成人健康儿童决定因素研究(CDAH)参与者完成了一份包含127个条目的Q-FFQ。我们利用2011 - 2012年澳大利亚国家营养与身体活动调查(NNPAS)的24小时膳食回忆数据,为Q-FFQ项目设定了按性别划分的食物分量,并主要使用澳大利亚食物成分数据库编制能量密度值。每个Q-FFQ项目的总能量摄入量估算为每日等效频率×食物分量(克)×能量密度(千焦/克),然后求和。我们将能量摄入量估算值与年龄匹配的NNPAS受访者加权样本(n = 1383)进行了对比。CDAH参与者的能量摄入量中位数(四分位间距)为9400(7580 - 11969)千焦/天,加权NNPAS样本为9055(6916 - 11825)千焦/天。CDAH参与者的能量摄入量中位数与基础代谢率之比为1.43(1.15 - 1.78),加权NNPAS样本为1.35(1.03 - 1.74),这表明两个样本中都存在明显的低报情况,超重和肥胖者的低报程度更高。使用戈德堡法和预测总能量消耗法对误报情况进行分类,分别有65%和41%的CDAH参与者的能量摄入量估算值可接受/合理。排除疑似误报的CDAH参与者后,能量摄入量估算的合理性得到改善,这与预期的体重关联相符。这个过程可以帮助想要从Q-FFQ估算能量摄入量并评估误报情况的研究人员,拓宽依赖消费频率数据的饮食与疾病调查的范围。