Dataset Information

The accuracy of the Goldberg method for classifying misreporters of energy intake on a food frequency questionnaire and 24-h recalls: comparison with doubly labeled water.

ABSTRACT: BACKGROUND/OBJECTIVES:Adults often misreport dietary intake; the magnitude varies by the methods used to assess diet and classify participants. The objective was to quantify the accuracy of the Goldberg method for categorizing misreporters on a food frequency questionnaire (FFQ) and two 24-h recalls (24HRs). SUBJECTS/METHODS:We compared the Goldberg method, which uses an equation to predict total energy expenditure (TEE), with a criterion method that uses doubly labeled water (DLW), in a study of 451 men and women. Underreporting was classified using recommended cut points and calculated values. Sensitivity and specificity, positive predictive value (PPV) and negative predictive value and the area under the receiver operating characteristic curve (AUC) were calculated. Predictive models of underreporting were contrasted for the Goldberg and DLW methods. RESULTS:AUCs were 0.974 and 0.972 on the FFQ, and 0.961 and 0.938 on the 24HR for men and women, respectively. The sensitivity of the Goldberg method was higher for the FFQ (92%) than the 24HR (50%); specificity was higher for the 24HR (99%) than the FFQ (88%); PPV was high for the 24HR (92%) and FFQ (88%). Simulation studies indicate attenuation in odds ratio estimates and reduction of power in predictive models. CONCLUSIONS:Although use of the Goldberg method may lead to bias and reduction in power in predictive models of underreporting, the method has high predictive value for both the FFQ and the 24HR. Thus, in the absence of objective measures of TEE or physical activity, the Goldberg method is a reasonable approach to characterize underreporting.

SUBMITTER: Tooze JA

PROVIDER: S-EPMC3319469 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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The accuracy of the Goldberg method for classifying misreporters of energy intake on a food frequency questionnaire and 24-h recalls: comparison with doubly labeled water.

Tooze J A JA Krebs-Smith S M SM Troiano R P RP Subar A F AF

European journal of clinical nutrition 20111130 5

<h4>Background/objectives</h4>Adults often misreport dietary intake; the magnitude varies by the methods used to assess diet and classify participants. The objective was to quantify the accuracy of the Goldberg method for categorizing misreporters on a food frequency questionnaire (FFQ) and two 24-h recalls (24HRs).<h4>Subjects/methods</h4>We compared the Goldberg method, which uses an equation to predict total energy expenditure (TEE), with a criterion method that uses doubly labeled water (DLW ...[more]

PMID: 22127332

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Project description:BackgroundAlthough prior evidence indicates that water intake is important for health, the ability to accurately measure community-dwelling intake is limited. Only a few studies have evaluated self-reported water intake against an objective recovery biomarker.ObjectivesThe aim was to compare preformed water intakes (all sources including food) by multiple Automated Self-Administered 24-h recalls (ASA24s), food frequency questionnaires (FFQs), and 4-d food records (4DFRs) against a recovery biomarker, doubly labeled water (DLW), to assess measurement error.MethodsOver 1 y, 1082 women and men (50%), aged 50 to 74 y, were asked to complete 6 ASA24s, 2 FFQs, 2 unweighted 4DFRs, and an administration of DLW (n = 686). Geometric means of water intake by self-report tools were compared with DLW. Attenuation factors and correlation coefficients between self-reported and the recovery biomarker (DLW) were estimated.ResultsMean water intakes by DLW were 2777 mL/d (interquartile range, 2350 to 3331) in women and 3243 mL/d (interquartile range, 2720 to 3838) in men. Compared with DLW, water intake was underestimated by 18% to 31% on ASA24s and 43% to 44% on 4DFRs. Estimated geometric means from FFQs differed from DLW by -1% to +13%. For a single ASA24, FFQ, and 4DFR, attenuation factors were 0.28, 0.27, and 0.32 and correlation coefficients were 0.46, 0.48, and 0.49, respectively. Repeated use of 6 ASA24s, 2 FFQs, and 2 4DFRs improved attenuation factors to 0.43, 0.32, and 0.39 and correlation coefficients to 0.58, 0.53, and 0.54, respectively.ConclusionsFFQs may better estimate population means for usual water intake compared with ASA24 and 4DFR. Similar attenuation factors and correlation coefficients across all self-report tools indicate that researchers have 3 feasible options if the goal is understanding intake-disease relationships. The findings are useful for planning future nutrition studies that set policy priorities for populations and to understand the health impact of water. This trial was registered at clinicaltrials.gov as NCT03268577.

Project description:BackgroundStatistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers. The objective of this study is to determine the added value of Food Frequency Questionnaire (FFQ) data allowing distinguishing the never-consumers from the non-consumers while modeling the usual intake distribution.MethodsThree food items with a different proportion of never-consumers were selected from the database of the Belgian food consumption survey of 2004 (N = 3200). The usual intake distribution for these food items was modeled with the Statistical Program for Analysis of Dietary Exposure (SPADE) and modeling parameters were extracted. These parameters were used to simulate (a) a new database with two 24-h recalls per respondent and (b) a "true" usual intake distribution. The usual intake distribution from the new database was obtained by modeling the 24-h recalls with SPADE, once without and once with the inclusion of the FFQ data on the never-consumers. Ratios were calculated for the different percentiles of the usual intake distribution: the modeled usual intake (g/day) (for both SPADE with and without the inclusion of FFQ data on never-consumers) was divided by the corresponding percentile of the simulated "true" usual intake (g/day). The closer the ratio is to one, the better the model fits the data.ResultsInclusion of the FFQ information to identify the never-consumers did not improve the estimation of the higher percentiles of the usual intake distribution. However, taking into account this FFQ information improved the estimation of the lower percentiles of the usual intake distribution even when the proportion of never-consumers was low.ConclusionsThe inclusion of FFQ information to identify the never-consumers is beneficial when interested in the whole usual intake distribution or in the lower percentiles only, no matter how low the proportion of never-consumers for that food item may be. However, when interest is only in the higher percentiles of the usual intake distribution, inclusion of FFQ information to identify the never-consumers will have no benefit.

Project description:Inaccuracies in energy intake (EI) measurement hinder identification of risk factors that predict weight gain and evaluation of obesity prevention and treatment interventions. Research has used objective measures of EI to identify underreporting correlates, producing mixed results, suggesting the need to examine novel potential correlates.With the use of an objective measure of EI from doubly labeled water (DLW) this report examined multiple potential underreporting correlates.Adolescents from 2 studies (study 1, n = 91; mean age: 18.4 ± 0.58 y; 100% female; study 2, n = 162; mean age: 15.2 ± 1.99 y; 82 female adolescents; 80 male adolescents) completed a DLW assessment of EI, a food-frequency questionnaire, and measures of perceived pressure for thinness, thin-ideal internalization, body dissatisfaction, dieting, food-cue reactivity, eating disorder symptoms, socioeconomic status, and neural response to food; BMI (in kg/m(2)) was measured over a 2-y follow-up.Elevated BMI correlated with underreported EI in study 1 (r = 0.26, P < 0.05) and study 2 (r = 0.20, P = 0.01), as did male sex in study 2 (r = 0.24, P < 0.01); the other survey measures did not. Underreporting correlated negatively (r = -0.29; uncorr P < 0.001) with responsivity of brain regions implicated in motor control to palatable food receipt and positively (r = 0.31; uncorr P < 0.001) with responsivity of a region implicated in taste processing to cues signaling impending milkshake receipt. Underreporting did not predict future change in BMI in either study.Findings document marked underreporting and replicate evidence that BMI correlates positively with underreporting and extends this literature by revealing that several novel factors were unrelated to underreporting and further that neural responsivity to food correlated with underreporting, suggesting that adolescents who showed reduced responsivity in a motor control region to food receipt and elevated responsivity of gustatory regions to anticipated palatable food receipt showed greater underreporting. This trial was registered at clinicaltrials.gov as NCT00433680 and NCT02084836.

Dataset Information

The accuracy of the Goldberg method for classifying misreporters of energy intake on a food frequency questionnaire and 24-h recalls: comparison with doubly labeled water.

Publications

The accuracy of the Goldberg method for classifying misreporters of energy intake on a food frequency questionnaire and 24-h recalls: comparison with doubly labeled water.

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