Empirical evidence of correlated biases in dietary assessment instruments and its implications
ABSTRACT Multiple-day food records or 24-hour recalls are currently used as "reference" instruments to calibrate food frequency questionnaires (FFQs) and to adjust findings from nutritional epidemiologic studies for measurement error. The common adjustment is based on the critical requirements that errors in the reference instrument be independent of those in the FFQ and of true intake. When data on urinary nitrogen level, a valid reference biomarker for nitrogen intake, are used, evidence suggests that a dietary report reference instrument does not meet these requirements. In this paper, the authors introduce a new model that includes, for both the FFQ and the dietary report reference instrument, group-specific biases related to true intake and correlated person-specific biases. Data were obtained from a dietary assessment validation study carried out among 160 women at the Dunn Clinical Nutrition Center, Cambridge, United Kingdom, in 1988-1990. Using the biomarker measurements and dietary report measurements from this study, the authors compare the new model with alternative measurement error models proposed in the literature and demonstrate that it provides the best fit to the data. The new model suggests that, for these data, measurement error in the FFQ could lead to a 51% greater attenuation of true nutrient effect and the need for a 2.3 times larger study than would be estimated by the standard approach. The implications of the results for the ability of FFQ-based epidemiologic studies to detect important diet-disease associations are discussed.
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ABSTRACT: To validate 24 h dietary recall of fruit intake by measuring the total 24 h excretion of 10 different flavonoids in 24 h urine during an intervention with free fruit at workplaces. Employees at workplaces offering a free-fruit program, consisting of daily free and easy access to fresh fruit, and controls employees at workplaces with no free-fruit program were enrolled in this validation study (n=103). Dietary intake was assessed by using a 24 h dietary recall questionnaire at baseline and approximately 5 months later. Ten flavonoids, quercetin, isorhamnetin, tamarixetin, kaempferol, hesperetin, naringenin, eriodictyol, daidzein, genistein, and phloretin, were measured using HPLC-electrospray ionization-MS. The 24 h urinary excretion of total flavonoids and the estimated intake of fruits were significantly correlated (r (s)=0.31, P<0.01). The dietary intake of citrus fruits and citrus juices was significantly correlated with total excretion of citrus specific flavonoids (r (s)=0.28, P<0.01), and orange was positively correlated with naringenin (r (s)=0.24, P<0.01) and hesperetin (r (s)=0.24, P<0.01). Phloretin in urine was correlated with apple intake (r (s)=0.22, P<0.01) and also with overall estimated intake of fruit (r (s)=0.22, P<0.01). This study shows that a 24 h dietary recall can be used as a valid estimate of the intake of fruits in agreement with an objective biomarker of fruit intake in free fruit at workplace interventions.European journal of clinical nutrition 10/2010; 64(10):1222-8. DOI:10.1038/ejcn.2010.130 · 2.95 Impact Factor
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ABSTRACT: We propose a semiparametric Bayesian method for handling measurement error in nutritional epidemiological data. Our goal is to estimate nonparametrically the form of association between a disease and exposure variable while the true values of the exposure are never observed. Motivated by nutritional epidemiological data, we consider the setting where a surrogate covariate is recorded in the primary data, and a calibration data set contains information on the surrogate variable and repeated measurements of an unbiased instrumental variable of the true exposure. We develop a flexible Bayesian method where not only is the relationship between the disease and exposure variable treated semiparametrically, but also the relationship between the surrogate and the true exposure is modeled semiparametrically. The two nonparametric functions are modeled simultaneously via B-splines. In addition, we model the distribution of the exposure variable as a Dirichlet process mixture of normal distributions, thus making its modeling essentially nonparametric and placing this work into the context of functional measurement error modeling. We apply our method to the NIH-AARP Diet and Health Study and examine its performance in a simulation study.Biometrics 09/2009; 66(2):444-54. DOI:10.1111/j.1541-0420.2009.01309.x · 1.52 Impact Factor
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ABSTRACT: Few strong and consistent associations have arisen from observational studies of dietary consumption in relation to chronic disease risk. Measurement error in self-reported dietary assessment may be obscuring many such associations. Attempts to correct for measurement error have mostly used a second self-report assessment in a subset of a study cohort to calibrate the self-report assessment used throughout the cohort, under the dubious assumption of uncorrelated measurement errors between the two assessments. The use, instead, of objective biomarkers of nutrient consumption to produce calibrated consumption estimates provides a promising approach to enhance study reliability. As summarized here, we have recently applied this nutrient biomarker approach to examine energy, protein, and percent of energy from protein, in relation to disease incidence in Women's Health Initiative cohorts, and find strong associations that are not evident without biomarker calibration. A major bottleneck for the broader use of a biomarker-calibration approach is the rather few nutrients for which a suitable biomarker has been developed. Some methodologic approaches to the development of additional pertinent biomarkers, including the possible use of a respiratory quotient from indirect calorimetry for macronutrient biomarker development, and the potential of human feeding studies for the evaluation of a range of urine- and blood-based potential biomarkers, will briefly be described.Statistics in Biosciences 05/2009; 1(1):112-123. DOI:10.1007/s12561-009-9003-4