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Urinary excretion of dithiocarbamates and self-reported Cruciferous vegetable intake: application of the ‘method of triads’ to a food-specific biomarker

Published online by Cambridge University Press:  02 January 2007

Jay H Fowke ,
James R Hebert  and
Jed W Fahey
Jay H Fowke*
Affiliation:
Vanderbilt–Ingram Cancer Center, Vanderbilt Center for Health Services Research, and Department of General and Internal Medicine, Vanderbilt University Medical Center, Vanderbilt University, 6110 Medical Center East, Nashville, TN 37232-8300, USA
James R Hebert
Affiliation:
Department of Epidemiology and Biostatistics and the Nutrition Research Center, Norman J Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
Jed W Fahey
Affiliation:
Department of Pharmacology and Molecular Sciences, School of Medicine, and Center for Human Nutrition, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
*
*Corresponding author: Email Jay.Fowke@vanderbilt.edu
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Abstract

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Objective:

Greater intake of Cruciferous vegetables (e.g. broccoli) may prevent cancer at several sites. Urinary excretion of isothiocyanate conjugates (dithiocarbamates, DTC) provides a specific biomarker of Cruciferous vegetable consumption suitable for epidemiological investigations. However, no gold-standard referent is available for evaluating urinary DTC levels as an estimator of Cruciferous vegetable consumption. We compared urinary DTC levels to intake as measured by two self-reported dietary assessment techniques.

Design:

Cruciferous vegetable consumption was measured before and after a behavioural dietary intervention using multiple 24-hour recalls (24HR), a food-counting questionnaire (VFQ) and urinary DTC excretion levels. Analysis included a structural equation approach (Method of Triads) combining these three assessment techniques to estimate the relationship between DTC level and the study population's ‘true’ Cruciferous vegetable intake.

Setting:

The intervention curriculum assisted participants in consuming about 2 servings per day for a 6-week period. Participants attended four classes emphasising problem-solving skills, dietary counselling and vegetable preparation skills. There were no dietary restrictions.

Subjects:

Thirty-three healthy, free-living, post-menopausal women.

Results:

Although few participants reported Cruciferae consumption prior to the intervention, 30 participants reported Cruciferae consumption after the intervention (Post-intervention). Urinary DTC levels were correlated with estimated intake derived from either the 24HR ( r = 0.57; 95% confidence interval (95% CI) 0.28, 0.76) or VFQ ( r = 0.49; 95% CI 0.17, 0.71). The validity coefficient (Method of Triads) between urinary DTC excretion and an index of true Cruciferous intake was stronger than the Pearson correlation ( rv = 0.65; 95% CI 0.35, 0.90), and comparable to estimates derived from the 24HR ( rv = 0.82; 95% CI 0.65, 1.00) or VFQ ( rv = 0.76; 95% CI 0.47, 0.92) method. These associations were not affected by adjustment for body mass index, energy intake, or social approval or desirability response sets.

Conclusions:

Food-frequency questionnaires (FFQ) suitable for large epidemiological studies may not be designed to measure all Cruciferae, and cannot capture exposure to phytochemicals derived from those vegetables. Urinary DTC measurement was significantly correlated with Cruciferae intake derived from two dietary assessment approaches, and urinary DTC levels could supplement traditional FFQ data by providing an index of recent Cruciferous vegetable intake not susceptible to reporting biases.

Keywords

BiomarkerDietary assessmentInterventionReliabilityValidity
Type
Research Article
Information
Public Health Nutrition , Volume 5 , Issue 6 , December 2002 , pp. 791 - 799
Copyright
Copyright © CABI Publishing 2002

References

1Michaud, DS, Spiegelman, D, Clinton, SK, Rimm, EB, Willett, WC, Giovannucci, EL. Fruit and vegetable intake and incidence of bladder cancer in a male prospective cohort. J. Natl. Cancer Inst. 1999; 91: 605–13.CrossRefGoogle Scholar
2Verhoeven, DT, Goldbohm, RA, van Poppel, G, Verhagen, H, van den Brandt, PA. Epidemiological studies of Brassica vegetables and cancer risk. Cancer Epidemiol. Biomark. Prev. 1996; 5: 733–48.Google Scholar
3Lin, HJ, Probst-Hensch, NM, Louie, AD, Kau, IH, Witte, JS, Ingles, SA, Frankl, HD, Lee, ER, Haile, RW. Glutathione transferase null geonotype, broccoli, and lower prevalence of colorectal adenomas. Cancer Epidemiol. Biomark. Prev. 1998; 7: 647–52.Google Scholar
4Hebert, JR, Peterson, KE, Hurley, TG, Stoddard, AM, Cohen, N, Field, AE, Sorensen, GT. The effect of social desirability trait on self-reported dietary measures among multi-ethnic female health center employees. Ann. Epidemiol. 2001; 11: 417–27.Google Scholar
5Hebert, JR, Clemow, L, Pbert, L, Ockene, IS, Ockene, JK. Social desirability bias in dietary self-report may compromise the validity of dietary intake measures. Int. J. Epidemiol. 1995; 24: 389–98.Google Scholar
6Shapiro, TA, Fahey, JW, Wade, KL, Stephenson, KK, Talalay, P. Chemoprotective glucosinolates and isothiocyanates of broccoli sprouts: metabolism and excretion in humans. Cancer Epidemiol. Biomark. Prev. 2001; 10: 501–8.Google Scholar
7Kaaks, RJ. Biochemical markers as additional measurements in studies of the accuracy of dietary questionnaire measurements: conceptual issues. Am. J. Clin. Nutr. 1997; 65: 1232–9.Google Scholar
8Ye, L, Dinkova-Kostova, AT, Wade, KL, Zhang, Y, Shapiro, T, Talalay, P. Quantitative determination of dithiocarbamates in human plasma, serum erythrocytes, and urine: pharmacokinetics of broccoli sprout isothiocyanates in humans. Clin. Chim. Acta 2002; 316: 43–53.Google Scholar
9Zhang, Y, Wade, KL, Prestera, T, Talalay, P. Quantitative determination of isothiocyanates, dithiocarbamates, carbon disulfide, and related thiocarbonyl compounds by cyclocondensation of 1,2-benzenedithiol. Anal. Biochem. 1996; 239: 160–7.CrossRefGoogle ScholarPubMed
10Shapiro, TA, Fahey, JW, Wade, KL, Stephenson, KK, Talalay, P. Human metabolism and excretion of cancer chemoprotective glucosinolates and isothiocyanates of Cruciferous vegetables. Cancer Epidemiol. Biomark. Prev. 1998; 7: 1091–100.Google Scholar
11Seow, A, Shi, C-Y, Chung, F-L, Jiao, D, Hankin, JH, Lee, H-P, Coetzee, GA, Yu, MC. Urinary total isothiocyanate (ITC) in a population-based sample of middle-aged and older Chinese in Singapore: relationship with dietary total ITC and glutathione S-transferase M1/T1/P1 genotypes. Cancer Epidemiol. Biomark. Prev. 1998; 7: 775–81.Google Scholar
12London, SJ, Yuan, J-M, Chung, F-L, Gao, Y-T, Coetzee, GA, Ross, RK, Yu, MC. Isothiocyanates, glutathione S-transferase M1 and T1 polymorphisms, and lung-cancer risk: a prospective study of men in Shanghai, China. Lancet 2000; 356: 724–9.CrossRefGoogle Scholar
13Fowke, JH, Longcope, C, Hebert, JR. Brassica vegetable consumption shifts estrogen metabolism in healthy postmenopausal women. Cancer Epidemiol. Biomark. Prev. 2000; 9: 773–9.Google Scholar
14Nugon-Baudon, L, Rabot, S. Glucosinolates and glucosinolate derivatives: implications for protection against chemical carcinogenesis. Nutr. Res. Rev. 1994; 7: 205–31.Google Scholar
15Hebert, JR, Ockene, IS, Hurley, TG, Luippold, R, Well, AD, Harmatz, MG. Development and testing of a seven-day dietary recall. J. Clin. Epidemiol. 1997; 50: 925–37.CrossRefGoogle ScholarPubMed
16Buzzard, IM, Faucett, CL, Jeffrey, RW, McBane, L, McGovern, P, Baxter, JS, Shapiro, AC, Blackburn, GL, Chlebowski, RT, Elashoff, RM, Wynder, EL. Monitoring dietary change in a low-fat diet intervention study: advantages of using 24-hour dietary recalls vs food records. J. Am. Diet. Assoc. 1996; 96: 574–9.Google Scholar
17Marlowe, D, Crowne, D. Social desirability and responses to perceived situational demands. J. Consult. Clin. Psychol. 1961; 25: 109–15.CrossRefGoogle ScholarPubMed
18Martin, HJ. A revised measure of approval motivation and its relationship to social desirability. J. Pers. Assess. 1984; 48: 508–16.Google Scholar
19Kleinbaum, DG, Kupper, LL, Muller, KE. Applied Regression Analysis and Other Multivariable Methods. Boston, MA: PWS-Kent Publishing, 1988.Google Scholar
20Ocké, MC, Kaaks, RJ. Biochemical markers of additional measurements in dietary validity studies: application of the method of triads with examples from the European Prospective Investigation into Cancer and Nutrition. Am. J. Clin. Nutr. 1997; 65: 1240–5.Google Scholar
21Decarli, A, Franceschi, S, Ferraroni, M, Gnagnarella, P, Parpinel, MT, LaVecchia, C, Negri, E, Salvini, S, Falcini, F, Giacosa, A. Validation of a food-frequency questionnaire to assess dietary intakes in cancer studies in Italy: results for specific nutrients. Ann. Epidemiol. 1996; 6: 110–8.CrossRefGoogle ScholarPubMed
22Salvini, S, Hunter, DJ, Sampson, L, Stempfer, M, Colditz, GA, Rosner, B, Willett, WC. Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption. Int. J. Epidemiol. 1989; 18: 858–67.CrossRefGoogle ScholarPubMed
23Kaaks, R, Riboli, E, Estève, J. Estimating the accuracy of dietary questionnaire assessments: validation in terms of structural equation models. Stats. Med. 1994; 13: 127–42.Google Scholar
24Marshall, JR, Lanza, E, Bloch, A, Caan, G, Caggiula, A, Quandt, S, Iber, F, Kikendall, W, Slattery, M, Sowell, A. Indexes of food and nutrient intakes as predictors of serum concentrations of nutrients: the problem of inadequate discriminant validity. Am. J. Clin. Nutr. 1997; 65: 1269–74.CrossRefGoogle ScholarPubMed
25Ocke, MC, Bueno-de-Mesquita, HB, Pols, MA, Smit, HA, van Staveren, WA, Kranhout, D. The Dutch EPIC food frequency questionnaire. II. Relative validity and reproducibility for nutrients. Int. J. Epidemiol. 1997; 26: S49–58.CrossRefGoogle ScholarPubMed
26Willett, W. Nutritional Epidemiology. New York: Oxford University Press, 1990.Google Scholar
27Katsouyanni, K, Rimm, EB, Gnardellis, C, Trichopoulos, D, Polychronopoulos, E, Trichopoulou, A. Reproducibility and relative validity of an extensive semi-quantitative food frequency questionnaire using dietary records and biochemical markers among Greek schoolteachers. Int. J. Epidemiol. 1997; 26: S118–27.Google Scholar
28Howard, LA, Jeffrey, EH, Wallig, MA, Klein, BP. Retention of phytochemicals in fresh and processed broccoli. J. Food Sci. 1997; 62: 1098–100.CrossRefGoogle Scholar
29Fowke, JH, Fahey, JW, Stephenson, K, Hebert, JR. Using isothiocyanate excretion as a biological marker of Brassica consumption: evaluating the sources of variability. Public Health Nutr. 2001; 4: 837–46.Google Scholar
30Fahey, JW, Stephenson, KK. Cancer chemoprotective effects of cruciferous vegetables. Horticult. Sci. 1999; 34: 1159–63.Google Scholar