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            "title": "A bivariate measurement error model for nitrogen and potassium intakes to evaluate the performance of regression calibration in the European Prospective Investigation into Cancer and Nutrition study",
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                    "lastName": "Bueno-de-Mesquita"
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                    "firstName": "P H M",
                    "lastName": "Peeters"
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                    "firstName": "C L",
                    "lastName": "Parr"
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                    "firstName": "T",
                    "lastName": "Braaten"
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                    "lastName": "Dorronsoro"
                },
                {
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                    "firstName": "T",
                    "lastName": "Berenguer"
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            "abstractNote": "OBJECTIVES\n\nWithin the European Prospective Investigation into Cancer and Nutrition (EPIC) study, the performance of 24-h dietary recall (24-HDR) measurements as reference measurements in a linear regression calibration model is evaluated critically at the individual (within-centre) and aggregate (between-centre) levels by using unbiased estimates of urinary measurements of nitrogen and potassium intakes.\n\n\nMETHODS\n\nBetween 1995 and 1999, 1072 study subjects (59% women) from 12 EPIC centres volunteered to collect 24-h urine samples. Log-transformed questionnaire, 24-HDR and urinary measurements of nitrogen and potassium intakes were analysed in a multivariate measurement error model to estimate the validity of coefficients and error correlations in self-reported dietary measurements. In parallel, correlations between means of 24-HDR and urinary measurements were computed. Linear regression calibration models were used to estimate the regression dilution (attenuation) factors.\n\n\nRESULTS\n\nAfter adjustment for sex, centre, age, body mass index and height, the validity coefficients for 24-HDRs were 0.285 (95% confidence interval: 0.194, 0.367) and 0.371 (0.291, 0.446) for nitrogen and potassium intakes, respectively. The attenuation factors estimated in a linear regression calibration model were 0.368 (0.228, 0.508) for nitrogen and 0.500 (0.361, 0.639) for potassium intakes; only the former was different from the estimate obtained using urinary measurements in the measurement error model. The aggregate-level correlation coefficients between means of urinary and 24-HDR measurements were 0.838 (0.637, 0.932) and 0.756 (0.481, 0.895) for nitrogen and potassium intakes, respectively.\n\n\nCONCLUSIONS\n\nThis study suggests that 24-HDRs can be used as reference measurements at the individual and aggregate levels for potassium intake, whereas, for nitrogen intake, good performance is observed for between-centre calibration, but some limitations are apparent at the individual level.",
            "publicationTitle": "European Journal of Clinical Nutrition",
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            "pages": "S179-187",
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            "journalAbbreviation": "Eur J Clin Nutr",
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                    "lastName": "Jacobs"
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                    "firstName": "J D",
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            "date": "Dec 15, 1991",
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            "publicationTitle": "Cancer Epidemiology Biomarkers & Prevention",
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                    "lastName": "Ferrari"
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            "title": "The impact of dietary measurement error on planning sample size required in a cohort study",
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                    "firstName": "L S",
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            "abstractNote": "Dietary measurement error has two consequences relevant to epidemiologic studies: first, a proportion of subjects are misclassified into the wrong groups, and second, the distribution of reported intakes is wider than the distribution of true intakes. While the first effect has been dealt with by several other authors, the second effect has not received as much attention. Using a simple errors-in-measurement model, the authors investigate the implications of measurement error for the distribution of fat intake. They then show how the inference of a more narrow distribution of true intakes affects the calculation of sample size for a cohort study. The authors give an example of the calculation for a cohort study investigating dietary fat and colorectal cancer. This shows that measurement error has a profound effect on sample size, requiring a six- to eightfold increase over the number required in the absence of error, if the correlation coefficient between reported and true intakes is 0.65. Reliable detection of a relative risk of 1.36 between a true intake of greater than 47.5% calories from fat and less than 25% calories from fat would require approximately one million subjects.",
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            "version": 5,
            "itemType": "journalArticle",
            "title": "Uses and limitations of statistical accounting for random error correlations, in the validation of dietary questionnaire assessments",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Rudolf",
                    "lastName": "Kaaks"
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                {
                    "creatorType": "author",
                    "firstName": "Pietro",
                    "lastName": "Ferrari"
                },
                {
                    "creatorType": "author",
                    "firstName": "Antonio",
                    "lastName": "Ciampi"
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                {
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                    "firstName": "Martyn",
                    "lastName": "Plummer"
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                {
                    "creatorType": "author",
                    "firstName": "Elio",
                    "lastName": "Riboli"
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            "abstractNote": "OBJECTIVE\n\nTo examine statistical models that account for correlation between random errors of different dietary assessment methods, in dietary validation studies.\n\n\nSETTING\n\nIn nutritional epidemiology, sub-studies on the accuracy of the dietary questionnaire measurements are used to correct for biases in relative risk estimates induced by dietary assessment errors. Generally, such validation studies are based on the comparison of questionnaire measurements (Q) with food consumption records or 24-hour diet recalls (R). In recent years, the statistical analysis of such studies has been formalized more in terms of statistical models. This made the need of crucial model assumptions more explicit. One key assumption is that random errors must be uncorrelated between measurements Q and R, as well as between replicate measurements R1 and R2 within the same individual. These assumptions may not hold in practice, however. Therefore, more complex statistical models have been proposed to validate measurements Q by simultaneous comparisons with measurements R plus a biomarker M, accounting for correlations between the random errors of Q and R.\n\n\nCONCLUSIONS\n\nThe more complex models accounting for random error correlations may work only for validation studies that include markers of diet based on physiological knowledge about the quantitative recovery, e.g. in urine, of specific elements such as nitrogen or potassium, or stable isotopes administered to the study subjects (e.g. the doubly labelled water method for assessment of energy expenditure). This type of marker, however, eliminates the problem of correlation of random errors between Q and R by simply taking the place of R, thus rendering complex statistical models unnecessary.",
            "publicationTitle": "Public Health Nutrition",
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            "date": "Dec 2002",
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            "partTitle": "",
            "pages": "969-976",
            "series": "",
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            "journalAbbreviation": "Public Health Nutr",
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            "title": "Calibration of the dietary questionnaire for a multiethnic cohort in Hawaii and Los Angeles",
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                    "firstName": "D O",
                    "lastName": "Stram"
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            "abstractNote": "The performance of the dietary questionnaire used in a multiethnic cohort study in Hawaii and Los Angeles was assessed in a calibration substudy that compared diet reported from the questionnaire with three 24-hour dietary recalls. For the calibration substudy, subjects from each of eight subgroups defined by sex and ethnic group (African-American, Japanese-American, Latino, and White) were chosen randomly from among the cohort members, and each participant's previous day's diet was assessed by telephone recall on three occasions over approximately 2 months. After completing the three 24-hour recalls, each calibration subject was sent a second questionnaire; 1,606 persons completed three recalls and a second questionnaire (127 to 267 per ethnic-sex group). This report describes correlation coefficients and calibration slopes for the relation between the 24-hour recalls and second questionnaire values for a selected set of macro- and micronutrients, as absolute intakes, nutrient densities, and calorie-adjusted nutrients. In all subgroups, estimates of the correlation between the questionnaire and 24-hour recalls were greater after energy adjustment (average correlations ranged from 0.57-0.74 for nutrient densities and from 0.55-0.74 for calorie-adjusted nutrients) than when absolute nutrient values were used (average range 0.26-0.57). For absolute nutrient intakes, the correlations were greatest for Whites, somewhat lower for Japanese-Americans and Latinos, and lowest for African-Americans. After energy adjustment, the difference between subgroups were diminished, and the correlations were generally highly satisfactory.",
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                    "firstName": "R",
                    "lastName": "Kaaks"
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            "abstractNote": "The European Prospective Investigation into Cancer and Nutrition (EPIC), which covers a large cohort of half a million men and women from 23 European centres in 10 Western European countries, was designed to study the relationship between diet and the risk of chronic diseases, particularly cancer. Information on usual individual dietary intake was assessed using different validated dietary assessment methods across participating countries. In order to adjust for possible systematic over- or underestimation in dietary intake measurements and correct for attenuation bias in relative risk estimates, a calibration approach was developed. This approach involved an additional dietary assessment common across study populations to re-express individual dietary intakes according to the same reference scale. A single 24-hour diet recall was therefore collected, as the EPIC reference calibration method, from a stratified random sample of 36 900 subjects from the entire EPIC cohort, using a software program (EPIC-SOFT) specifically designed to standardise the dietary measurements across study populations. This paper describes the design and populations of the calibration sub-studies set up in the EPIC centres. In addition, to assess whether the calibration sub-samples were representative of the entire group of EPIC cohorts, a series of subjects' characteristics known possibly to influence dietary intakes was compared in both population groups. This was the first time that calibration sub-studies had been set up in a large multi-centre European study. These studies showed that, despite certain inherent methodological and logistic constraints, a study design such as this one works relatively well in practice. The average response in the calibration study was 78.3% and ranged from 46.5% to 92.5%. The calibration population differed slightly from the overall cohort but the differences were small for most characteristics and centres. The overall results suggest that, after adjustment for age, dietary intakes estimated from calibration samples can reasonably be interpreted as representative of the main cohorts in most of the EPIC centres.",
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