Modeling Data with Excess Zeros and Measurement Error: Application to Evaluating Relationships between Episodically Consumed Foods and Health Outcomes

Summary Dietary assessment of episodically consumed foods gives rise to nonnegative data that have excess zeros and measurement error. Tooze et al. (2006, Journal of the American Dietetic Association 106 , 1575–1587) describe a general statistical approach (National Cancer Institute method) for modeling such food intakes reported on two or more 24‐hour recalls (24HRs) and demonstrate its use to estimate the distribution of the food's usual intake in the general population. In this article, we propose an extension of this method to predict individual usual intake of such foods and to evaluate the relationships of usual intakes with health outcomes. Following the regression calibration approach for measurement error correction, individual usual intake is generally predicted as the conditional mean intake given 24HR‐reported intake and other covariates in the health model. One feature of the proposed method is that additional covariates potentially related to usual intake may be used to increase the precision of estimates of usual intake and of diet‐health outcome associations. Applying the method to data from the Eating at America's Table Study, we quantify the increased precision obtained from including reported frequency of intake on a food frequency questionnaire (FFQ) as a covariate in the calibration model. We then demonstrate the method in evaluating the linear relationship between log blood mercury levels and fish intake in women by using data from the National Health and Nutrition Examination Survey, and show increased precision when including the FFQ information. Finally, we present simulation results evaluating the performance of the proposed method in this context.     

Evaluation of a two‐part regression calibration to adjust for dietary exposure measurement error in the Cox proportional hazards model: A simulation study

Dietary questionnaires are prone to measurement error, which bias the perceived association between dietary intake and risk of disease. Short‐term measurements are required to adjust for the bias in the association. For foods that are not consumed daily, the short‐term measurements are often characterized by excess zeroes. Via a simulation study, the performance of a two‐part calibration model that was developed for a single‐replicate study design was assessed by mimicking leafy vegetable intake reports from the multicenter European Prospective Investigation into Cancer and Nutrition (EPIC) study. In part I of the fitted two‐part calibration model, a logistic distribution was assumed; in part II, a gamma distribution was assumed. The model was assessed with respect to the magnitude of the correlation between the consumption probability and the consumed amount (hereafter, cross‐part correlation), the number and form of covariates in the calibration model, the percentage of zero response values, and the magnitude of the measurement error in the dietary intake. From the simulation study results, transforming the dietary variable in the regression calibration to an appropriate scale was found to be the most important factor for the model performance. Reducing the number of covariates in the model could be beneficial, but was not critical in large‐sample studies. The performance was remarkably robust when fitting a one‐part rather than a two‐part model. The model performance was minimally affected by the cross‐part correlation.     

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.     

Understanding reporting bias in the dietary recall data of 11-year-old girls

Objective: This study describes patterns of bias in self‐reported dietary recall data of girls by examining differences among girls classified as under‐reporters, plausible reporters, and over‐reporters on weight, dietary patterns, and psychosocial characteristics. Research Methods and Procedures: Participants included 176 girls at age 11 and their parents. Girls’ weight and height were measured. Three 24‐hour dietary recalls and responses to psychosocial measures were collected. Plausibility cut‐offs for reported energy intake as a percentage of predicted energy requirements were used to divide the sample into under‐reporters, plausible reporters, and over‐reporters. Differences among these three groups on dietary and psychosocial variables were assessed to examine possible sources of bias in reporting. Results: Using a ±1 standard deviation cut‐off for energy intake plausibility, 50% of the sample was categorized as plausible reporters, 34% as under‐reporters, and 16% as over‐reporters. Weight status of under‐reporters was significantly higher than that of plausible reporters and over‐reporters. With respect to reported dietary intake, under‐reporters were no different from plausible reporters on intakes of foods with higher nutrient densities and lower energy densities and were significantly lower than plausible reporters on intakes of foods with lower nutrient densities and higher energy densities. Over‐reporters reported significantly higher intakes of all food groups and the majority of subgroups, relative to plausible reporters. Under‐reporters had significantly higher levels of weight concern and dietary restraint than both plausible reporters and over‐reporters. Discussion: Techniques to categorize plausible and implausible reporters can and should be used to provide an improved understanding of the nature of error in children's dietary intake data and account for this error in analysis and interpretation.     

Linear measurement error models with restricted sampling

The relationship between nutrient consumption and chronic disease risk is the focus of a large number of epidemiological studies where food frequency questionnaires (FFQ) and food records are commonly used to assess dietary intake. However, these self-assessment tools are known to involve substantial random error for most nutrients, and probably important systematic error as well. Study subject selection in dietary intervention studies is sometimes conducted in two stages. At the first stage, FFQ-measured dietary intakes are observed and at the second stage another instrument, such as a 4-day food record, is administered only to participants who have fulfilled a prespecified criterion that is based on the baseline FFQ-measured dietary intake (e.g., only those reporting percent energy intake from fat above a prespecified quantity). Performing analysis without adjusting for this truncated sample design and for the measurement error in the nutrient consumption assessments will usually provide biased estimates for the population parameters. In this work we provide a general statistical analysis technique for such data with the classical additive measurement error that corrects for the two sources of bias. The proposed technique is based on multiple imputation for longitudinal data. Results of a simulation study along with a sensitivity analysis are presented, showing the performance of the proposed method under a simple linear regression model.     

SIMEX for correction of dietary exposure effects with Box-Cox transformed data

Modelling dietary data, and especially 24-hr dietary recall (24HDR) data, is a challenge. Ignoring the inherent measurement error (ME) leads to biased effect estimates when the association between an exposure and an outcome is investigated. We propose an adapted simulation extrapolation (SIMEX) algorithm for modelling dietary exposures. For this purpose, we exploit the ME model of the NCI method where we assume the assumption of normally distributed errors of the reported intake on the Box-Cox transformed scale and of unbiased recalls on the original scale. According to the SIMEX algorithm, remeasurements of the observed data with additional ME are generated in order to estimate the association between the level of ME and the resulting effect estimate. Subsequently, this association is extrapolated to the case of zero ME to obtain the corrected estimate. We show that the proposed method fulfils the key property of the SIMEX approach, that is, that the MSE of the generated data will converge to zero if the ME variance converges to zero. Furthermore, the method is applied to real 24HDR data of the I.Family study to correct the effects of salt and alcohol intake on blood pressure. In a simulation study, the method is compared with the NCI method resulting in effect estimates with either smaller MSE or smaller bias in certain situations. In addition, we found our method to be more informative and easier to implement. Therefore, we conclude that the proposed method is useful to promote the dissemination of ME correction methods in nutritional epidemiology.     

Intake of dietary fats and colorectal cancer risk: Prospective findings from the UK Dietary Cohort Consortium

Introduction: Epidemiologic evidence for an association between colorectal cancer (CRC) risk and total dietary fat, saturated fat (SF), monounsaturated fat (MUFA) and polyunsaturated fat (PUFA) is inconsistent. Previous studies have used food frequency questionnaires (FFQ) to assess diet, but data from food diaries may be less prone to severe measurement error than data from FFQ. Methods: We conducted a case–control study nested within seven prospective UK cohort studies, comprising 579 cases of incident CRC and 1996 matched controls. Standardized dietary data from 4- to 7-day food diaries and from FFQ were used to estimate odds ratios for CRC risk associated with intake of fat and subtypes of fat using conditional logistic regression. We also calculated multivariate measurement error corrected odds ratios for CRC using repeated food diary measurements. Results: We observed no associations between intakes of total dietary fat or types of fat and CRC risk, irrespective of whether dietary data were obtained using food diaries or FFQ. Conclusion: Our results do not support the hypothesis that intakes of total dietary fat, SF, MUFA or PUFA are linked to risk of CRC.     

Adherence to a Mediterranean diet and energy, macro-, and micronutrient intakes in older persons

The Mediterranean-type diet combines several foods and nutrients already individually proposed as potential protective factors against adverse health outcomes, such as cardiovascular diseases. The aim of the present study was to describe the association between adherence to a Mediterranean diet (MeDi) and intake of energy, macronutrients, and micronutrients. The study sample consisted of 1,595 individuals from Bordeaux, France, included in 2001–2002 in the Three-City Study. Adherence to a MeDi (scored as 0 to 9) was computed from a food frequency questionnaire (FFQ). Total energy intake (EI) and nutrient intake were evaluated on a 24 h recall. Statistical analyses were stratified by gender. Both in men and women, greater MeDi adherence was associated with higher total vegetal protein, polyunsaturated fatty acids (PUFA), notably n???6 PUFA, and lower total saturated fat intakes, as expressed in percentage of EI. Higher total monounsaturated fat and oleic acid intakes (% EI) were observed with greater MeDi adherence in men. Women with the highest MeDi adherence exhibited a higher mean carbohydrate, polysaccharide, and total n???3 PUFA intakes (% EI). The consumption of fibers; vitamins B6, C, and E; folate; magnesium; potassium; and iron increased with greater MeDi adherence, both in men and women. However, consumption of calcium significantly decreased with greater MeDi adherence in women, while the ratio of n???6/n???3 PUFA precursors increased. This cross-sectional study provides the nutrient-related basis of the Mediterranean-type diet of French elderly community dwellers, which might participate to its well-documented beneficial effects on health.     

Validation of overweight children's fruit and vegetable intake using plasma carotenoids

Assessing dietary intake in children is difficult and limited validated tools exist. Plasma carotenoids are nutritional biomarkers of fruit and vegetable intake and therefore suitable to validate reported dietary intakes. The aim of this study was to examine the comparative validity of a food frequency questionnaire (FFQ), completed by parents reporting child fruit and vegetable intake compared to plasma carotenoid concentrations. A sample of children aged 5-12 years (n = 93) from a range of weight categories were assessed. Dietary intake was measured using a 137-item semi-quantitative FFQ. Plasma carotenoids were measured using reverse phase high-performance liquid chromatography. Pearson correlation coefficients between reported dietary intake of carotenoids and plasma carotenoid concentrations were strongest after adjustment for BMI (beta-carotene (r = 0.56, P < 0.05), alpha-carotene (r = 0.51, P < 0.001), cryptoxanthin (r = 0.32, P < 0.001)). Significantly lower levels (P < 0.05) of all plasma carotenoids, except lutein, were found among overweight and obese children when compared to healthy weight children. Parental report of children's carotenoid intakes, using a FFQ can be used to provide a relative validation of fruit and vegetable intake. The lower plasma carotenoid concentrations found in overweight and obese children requires further investigation.     

Vitamin D Intake,Month the Mammogram Was Taken and Mammographic Density in Norwegian Women Aged 50–69

BackgroundThe role of vitamin D in breast cancer etiology is unclear. There is some, but inconsistent, evidence that vitamin D is associated with both breast cancer risk and mammographic density (MD). We evaluated the associations of MD with month the mammogram was taken, and with vitamin D intake, in a population of women from Norway—a country with limited sunlight exposure for a large part of the year.Methods3114 women aged 50–69, who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004 or 2006/07, completed risk factor and food frequency (FFQ) questionnaires. Dietary and total (dietary plus supplements) vitamin D, calcium and energy intakes were estimated by the FFQ. Month when the mammogram was taken was recorded on the mammogram. Percent MD was assessed using a computer assisted method (Madena, University of Southern California) after digitization of the films. Linear regression models were used to investigate percent MD associations with month the mammogram was taken, and vitamin D and calcium intakes, adjusting for age, body mass index (BMI), study year, estrogen and progestin therapy (EPT), education, parity, calcium intakes and energy intakes.ResultsThere was no statistical significant association between the month the mammogram was taken and percent MD. Overall, there was no association between percent MD and quartiles of total or dietary vitamin D intakes, or of calcium intake. However, analysis restricted to women aged <55 years revealed a suggestive inverse association between total vitamin D intake and percent MD (p for trend = 0.03).ConclusionOverall, we found no strong evidence that month the mammogram was taken was associated with percent MD. We found no inverse association between vitamin D intake and percent MD overall, but observed a suggestive inverse association between dietary vitamin D and MD for women less than 55 years old.     

Correcting for measurement error in fractional polynomial models using Bayesian modelling and regression calibration,with an application to alcohol and mortality

Exposure measurement error can result in a biased estimate of the association between an exposure and outcome. When the exposure–outcome relationship is linear on the appropriate scale (e.g. linear, logistic) and the measurement error is classical, that is the result of random noise, the result is attenuation of the effect. When the relationship is non‐linear, measurement error distorts the true shape of the association. Regression calibration is a commonly used method for correcting for measurement error, in which each individual's unknown true exposure in the outcome regression model is replaced by its expectation conditional on the error‐prone measure and any fully measured covariates. Regression calibration is simple to execute when the exposure is untransformed in the linear predictor of the outcome regression model, but less straightforward when non‐linear transformations of the exposure are used. We describe a method for applying regression calibration in models in which a non‐linear association is modelled by transforming the exposure using a fractional polynomial model. It is shown that taking a Bayesian estimation approach is advantageous. By use of Markov chain Monte Carlo algorithms, one can sample from the distribution of the true exposure for each individual. Transformations of the sampled values can then be performed directly and used to find the expectation of the transformed exposure required for regression calibration. A simulation study shows that the proposed approach performs well. We apply the method to investigate the relationship between usual alcohol intake and subsequent all‐cause mortality using an error model that adjusts for the episodic nature of alcohol consumption.     

Relative Validity of Three Food Frequency Questionnaires for Assessing Dietary Intakes of Guatemalan Schoolchildren

ObjectiveTo determine the relative validity of three food frequency questionnaires (FFQs) compared with results from 24-hour dietary recalls for measuring dietary intakes in Guatemalan schoolchildren.DesignA cross-sectional study of primary caregivers (mothers or grandmothers) of 6–11 year-old children. Caregivers completed one of three constructed FFQs to measure the child’s dietary consumption in the last week: FFQ1 did not incorporate portion sizes; FFQ2 provided portion sizes; and FFQ3 incorporated pictures of median portion sizes. During the same week, each caregiver also completed three 24-hour dietary recalls. Results from the FFQ were compared with corresponding results from the 24-hour dietary recalls.SettingSanta Catarina Pinula, peri-urban Guatemala City.SubjectsCaregivers (n = 145) of 6–11 year-old children: 46 completed FFQ1, 49 completed FFQ2, and 50 completed FFQ3.ResultsThe mean values for all nutrients obtained from the 24-hour dietary recall were lower than for those obtained from the FFQs, excluding folic acid in FFQ3, cholesterol and zinc in FFQ2, and cholesterol, folic acid, magnesium, potassium, sodium, and zinc in FFQ1. Energy-adjusted Pearson correlation coefficients ranged from 0.07 (protein) to 0.54 (cholesterol) for FFQ1 and from 0.05 to 0.74 for FFQ2 and FFQ3. Agreement by both methods (FFQ and 24-hour dietary recalls) of classifying children into the same or adjacent quartiles of energy-adjusted nutrient consumption ranged from 62.0% for cholesterol to 95.9% for vitamin B12 across all three FFQs.ConclusionsOur FFQs had moderate to good relative validity in measuring energy and nutrient intakes for 6–11 year-old Guatemalan children. More evidence is needed to evaluate their reproducibility and applicability in similar populations.     

Validity of a self-administered food frequency questionnaire in the assessment of heterocyclic amine intake using 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) levels in hair

Several case-control studies have reported possible associations between heterocyclic amine (HCA) intake and the risk of cancer. The validity of questionnaires used to assess HCA intake has hardly been examined, however; in particular, no biomarker able to serve as an independent measure of habitual HCA intake has been established. In this study, we examined the validity of HCA intake estimated from a food frequency questionnaire (FFQ) using 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) level in hair as a reference method. Study subjects were 20 volunteers (7 men and 13 women) aged 25-57 years residing in Tokyo or neighboring cities in Japan. The subjects completed the FFQ, and gave 3-5g of hair twice at an interval of 1-3 months for use in establishing validity. Results showed that intakes of PhIP, MeIQ, Trp-P-1, and total HCA by the FFQ were significantly correlated with PhIP levels in hair when adjustment was made for melanin content (r=0.47, r=0.50, r=0.55, and r=0.51, respectively). The present study indicates that HCA intake estimated from this FFQ provides a reasonable ranking of individuals to allow the analysis of associations between HCA intake and risk of cancer in large-scale epidemiological studies.     

Estimating energy and nutrient intakes in studies of human fertility.

Two methods of dietary recording, the 24-hr recall and the weighed dietary intake methods, are considered appropriate for estimating energy and nutrient intakes in studies of human fertility. The former method gives lower estimates than the latter, although weighed intakes may underestimate true intakes. Examination of food intakes of pregnant, lactating, and non-pregnant, non-lactating New Guinean women shows their diet to be less homogeneous than is generally assumed for groups in developing countries. As a result direct observations of food intake for a limited number of days are not sufficiently accurate for the estimation of intake of most of the nutrients examined. Rather the study design should reflect the variability of intakes of the nutrients and groups under consideration.     

Reproducibility and Relative Validity of a Food Frequency Questionnaire Developed for Adults in Taizhou,China

Objective

To evaluate the reproducibility and validity of a food frequency questionnaire (FFQ) developed to investigate the relationship between dietary factors and diseases in the adult Chinese population in East China.

Methods

A total of 78 males and 129 females aged 30–75 years completed four inconsecutive 24-hour dietary recalls (24-HRs, served as a reference method) and two FFQs (FFQ1 and FFQ2) over a nine-month interval. The reproducibility of the FFQ was estimated with correlation coefficients, cross-classification, and weighted kappa statistic. The validity was assessed by comparing the data obtained from FFQ and 24-HRs.

Results

The median nutrient intakes assessed with FFQs were higher than the average of four 24-HRs. For the food groups, Spearman, Pearson, and intraclass correlation coefficients between FFQ1 and FFQ2 ranged from 0.23 to 0.61, 0.27 to 0.64, and 0.26 to 0.65, respectively. For total energy and nutrient intakes, the corresponding coefficients ranged from 0.25 to 0.61, 0.28 to 0.64, and 0.28 to 0.62, respectively. The correlations between FFQ1 and FFQ2 for most nutrients decreased after adjustment with total energy intake. More than 70% of the subjects were classified into the same and adjacent categories by both FFQs. For food groups, the crude, energy-adjusted, and de-attenuated Spearman correlation coefficients between FFQ2 and the 24-HRs ranged from 0.17 to 0.59, 0.10 to 0.57, and 0.11 to 0.64, respectively. For total energy and nutrient intakes, the corresponding coefficients ranged from 0.20 to 0.58, 0.08 to 0.54, and 0.09 to 0.56, respectively. More than 67% of the subjects were classified into the same and adjacent categories by both instruments. Both weighted kappa statistic and Bland-Altman Plots showed reasonably acceptable agreement between the FFQ2 and 24-HRs.

Conclusion

The FFQ developed for adults in the Taizhou area is reasonably reliable and valid for assessment of most food and nutrient intakes.     

The impact of stratification by implausible energy reporting status on estimates of diet‐health relationships

The food frequency questionnaire (FFQ) is known to be prone to measurement error. Researchers have suggested excluding implausible energy reporters (IERs) of FFQ total energy when examining the relationship between a health outcome and FFQ‐reported intake to obtain less biased estimates of the effect of the error‐prone measure of exposure; however, the statistical properties of stratifying by IER status have not been studied. Under certain assumptions, including nondifferential error, we show that when stratifying by IER status, the attenuation of the estimated relative risk in the stratified models will be either greater or less in both strata (implausible and plausible reporters) than for the nonstratified model, contrary to the common belief that the attenuation will be less among plausible reporters and greater among IERs. Whether there is more or less attenuation depends on the pairwise correlations between true exposure, observed exposure, and the stratification variable. Thus exclusion of IERs is inadvisable but stratification by IER status can sometimes help. We also address the case of differential error. Examples from the Observing Protein and Energy Nutrition Study and simulations illustrate these results.     

Allowing for never and episodic consumers when correcting for error in food record measurements of dietary intake

Food records, including 24-hour recalls and diet diaries, are considered to provide generally superior measures of long-term dietary intake relative to questionnaire-based methods. Despite the expense of processing food records, they are increasingly used as the main dietary measurement in nutritional epidemiology, in particular in sub-studies nested within prospective cohorts. Food records are, however, subject to excess reports of zero intake. Measurement error is a serious problem in nutritional epidemiology because of the lack of gold standard measurements and results in biased estimated diet-disease associations. In this paper, a 3-part measurement error model, which we call the never and episodic consumers (NEC) model, is outlined for food records. It allows for both real zeros, due to never consumers, and excess zeros, due to episodic consumers (EC). Repeated measurements are required for some study participants to fit the model. Simulation studies are used to compare the results from using the proposed model to correct for measurement error with the results from 3 alternative approaches: a crude approach using the mean of repeated food record measurements as the exposure, a linear regression calibration (RC) approach, and an EC model which does not allow real zeros. The crude approach results in badly attenuated odds ratio estimates, except in the unlikely situation in which a large number of repeat measurements is available for all participants. Where repeat measurements are available for all participants, the 3 correction methods perform equally well. However, when only a subset of the study population has repeat measurements, the NEC model appears to provide the best method for correcting for measurement error, with the 2 alternative correction methods, in particular the linear RC approach, resulting in greater bias and loss of coverage. The NEC model is extended to include adjustment for measurements from food frequency questionnaires, enabling better estimation of the proportion of never consumers when the number of repeat measurements is small. The methods are applied to 7-day diary measurements of alcohol intake in the EPIC-Norfolk study.     

Inaccuracies in self-reported intake identified by comparison with the doubly labelled water method

To test the accuracy of self-reported energy intake, reported intake was compared with measured energy expenditure. Results from nine studies were reviewed in which intake data were obtained by recall or weighed record for at least 7 days. Expenditure was measured for 7 days or more by the doubly labelled water method. Individual differences between reported intake and expenditure were large (range +25 to -76%). Group mean differences were smaller. Lean, nonathletic groups living in industrialized countries demonstrated the smallest mean difference between self-reported energy intakes and expenditure (0 to -20%). Obese populations demonstrated the largest mean differences (-35 and -50%), but women living in the Gambia and elite athletes also demonstrated large mean differences. Most of the difference appears to be due to under-reporting, but some subjects lost weight during the reporting period indicating that some of the difference was due to undereating. Because the greatest bias was observed in obese subjects, current methods for self-reported energy intake are not recommended for use in obesity research.     

Impact of Interviewer's Body Mass Index on Underreporting Energy Intake in Overweight and Obese Women

Objective: To determine if overweight and obese women provide more accurate reports of their energy intake by 1) in‐person recall with an obese interviewer, 2) in‐person recall with a lean interviewer, or 3) telephone recall with an unknown interviewer. Research Methods and Procedures: Eighty‐eight overweight and obese women participated in this study. Subjects completed one telephone‐administered multiple‐pass 24‐hour recall (MP24R) with an unknown interviewer and were then randomly assigned to an in‐person MP24R with either a lean or obese interviewer to gather reported energy intake (rEI). Basal metabolic rate (BMR) was measured using a Deltrac monitor, and physical activity (EEPA) was estimated using a Caltrac accelerometer. Therefore, estimated energy expenditure was determined by: estTEE = (BMR + EEPA) × 1.10. Results: No significant differences were found between the two in‐person interview modes for subject age, weight, body mass index, percentage of body fat, total energy expenditure, rEI, and misreporting of energy intake. In‐person recall data were combined for comparison with the telephone recalls. No significant difference was found between the in‐person and telephone recalls for rEI and misreporting. Mean reported energy intake was significantly lower than estimated total energy expenditure for the telephone recalls and combined (lean and obese modes) in‐person recalls. Conclusions: This study found that interviewer body mass index had no impact on self‐reported energy intake during an in‐person MP24R, and that telephone recall data were comparable with in‐person recalls. Underreporting was a widespread problem (～26%) for all modes in this sample.     

Energy Intake and Physical Activity in Pima Indians: Comparison with Energy Expenditure Measured by Doubly-Labeled Water

To test the validity of survey techniques for measuring diet and activity patterns of Pima Indians, sequential 24-hour recalls, a food frequency ques tionnaire (FFQ), and an activity questionnaire were compared to free-living energy expenditure. Total energy expenditure (TEE) measured by doubly labeled water was 13.27 ± 2.95 MJ/d for the 12 males (mean±SD: 35 ± 14 yr; 97 ± 35 kg; 32 + 9% body fat) and 11.67 ± 1.85 MJ/d for the 9 females (31 ± 13 yr; 106 ± 32 kg; 49 ± 6% body fat). Energy intake assessed by 24-hour recall was 13.59 ± 7.81 MJ/d for men and 9.29 ± 2.77 MJ/d for women, compared to 12.84 ± 2.85 and 9.40 ± 2.61 MJ/d for men and women, respectively, by FFQ. Both dietary methods indicated significant underreporting by women when compared to TEE. Energy intake assessed by FFQ was significantly correlated with TEE (r=0.48, p=0.03). This was true with 24-hour recall energy intake only when data from two extremely large alcohol consumers were eliminated (r=0.64, p=0.03, N=19). Although a low level of activity was apparent, the activity questionnaire produced significant correlations with measurements of energy expenditure and therefore represents an important tool for examining the relationship between physical activity and diseases.