Design of dietary questionnaires to study the relationships between diet and cancer prevalence in Colombia
Keywords:
diet, nutritional epidemiology, neoplasms, nutritional transition, Colombia
Abstract
Introduction. In Colombia, cancer ranks third as a cause of death in the adult population. Thirty-five percent of cancer deaths are attributable to dietary factors and that 90% of colorectal cancers can be prevented by appropriate diets.Objective. A dietary questionnaire was developed to study the relationship between diet and cancer for five cities in Colombia (Barranquilla, Cartagena, Santa Marta, Bogotá and Bucaramanga and its metropolitan area), based on 24-hour dietary survey data accumulated by the National Survey of Nutritional Status-2005.
Material and methods. Each questionnaire had 3 sections and involved six stages in its development. A checklist representing thirteen nutrients was formulated by means of the method of the variance maximization (Max_r ®); it was supplemented with nine categories of consumption frequency. The two complementary sections inquired about the consumption of food, number of meals per day, and methods of preparation, related with cancer development.
Results. Between 22 and 32 foods were discriminated for each questionnaire. Only nine foods were common in the checklists of each of the five cities. Nine of the thirteen nutrients are represented with correlations higher than 0.80, with a minimum 0.47 and a maximum of 1.0.
Conclusions. For the first time in Colombia specific questionnaires were developed to study the diet-cancer relationship. The checklist was comprehensive and it incorporated between-person variability, as well as the habits and food culture of each city. We propose nine analysis alternatives for the questionnaire. The questionnaires will prove useful in epidemiological research, although they require calibration with studies of reproducibility and validity.
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References
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35. Herrán OF, Bautista LE, Quintero DC. Tabla de composición de alimentos consumidos en Bucaramanga. Segunda edición. Bucaramanga: Universidad Industrial de Santander; 2003.
36. Hansen Gaurth R, Wyse BW. Expression of nutrient allowances per 1,000 kilocalories. J Am Diet Assoc. 1980;76:223-7.
37. Williams CD, Satia JA, Adair LS, Stevens J, Galanko J, Keku TO, et al. Dietary patterns, food groups, and rectal cancer risk in whites and African-Americans. Cancer Epidemiol Biomarkers Prev. 2009;18:1552-61.
38. Bond TG, Fox CM. Applying the Rasch Model: Fundamental measurement in the human sciences. 2 edition. London: Lawrence Erlbaum Associates Publishers; 2007.
2. Ministerio de la Protección Social, Organización Panamericana de la Salud. Situación de Salud en Colombia: indicadores básicos 2007. Bogotá, D.C.: Ministerio de la Protección Social; 2008.
3. Ochoa FL, Montoya LP. Carga de cáncer en Colombia. Rev Colomb Cacerol. 2007;11:168-73.
4. Ochoa FL, Montoya LP. Mortalidad por cáncer en Colombia. Cuando aumentar no es mejorar. Rev CES Med. 2003;17:7-22.
5. Piñeros M, Murillo R. Incidencia de cáncer en Colombia: importancia de las fuentes de información en la obtención de cifras estimativas. Rev Colomb Cancerol. 2004;8:5-14.
6. Murillo R, Piñeros M, Hernández G. Atlas de mortalidad por cáncer en Colombia. Bogotá D.C.: Imprenta Nacional de Colombia; 2003.
7. Organización Mundial de la Salud. Food, nutrition and the prevention of cancer: A global perspective, 2003. Publicación científica y técnica No. 583. Washington D.C.: Organización Mundial de la Salud; 2003.
8. Organización Mundial de la Salud. Dieta, nutrición y prevención de enfermedades crónicas, 2003. Publicación científica y técnica No. 916. Washington D.C.: Organización Mundial de la Salud; 2003.
9. Willet WC. Nutritional epidemiology. 2 edition. New York: Oxford University Press; 1998.
10. Margetts BM, Nelson M. Design concepts in nutritional epidemiology. 2 edition. New York: Oxford University Press; 1996.
11. Bowman BA, Russell RM. Conocimientos actuales sobre nutrición. 8 edición. Publicación científica y técnica número 592. Washington D.C.: Organización Mundial de la Salud; 2003.
12. Bautista L, Herrán OF, Pryer JA. Development and simulated validation of a food-frequency questionnaire for the Colombian population. Public Health Nutr. 2005:8:181-8.
13. Herrán OF, Ardila MF. Validity and reproducibility of two semi-quantitative Alcohol frequency questionnaires for Colombian population. Public Health Nutr. 2006;9:763-70.
14. Kipnis V, Freedman LS. Impact of exposure measurement error in nutritional epidemiology. J Natl Cancer Inst. 2008;100:1658-9.
15. Kaaks R, Riboli E, van Staveren W. Calibration of dietary intake measurements in prospective cohort studies. Am J Epidemiol. 1995;142:548-56.
16. Rosner B, Willett WC, Spiegelman DN. Correction of logistic regression relative risk estimates and confidence intervals for systematic with in-person measurement error. Stat Med. 1989;8:1051-69.
17. Rosner B, Spiegelman D, Willett WC. Correction of logistic regression relative risk estimates and confidence intervals for measurement error: the case of multiple covariates measured with error. Am J Epidemiol. 1990;132:734-45.
18. Kristal AR, Peters U, Potter JD. Is it time to abandon the food frequency questionnaire? Cancer Epidemiol Biomarkers Prev. 2005;14:2826-8.
19. Freudenheim JL, Marshall JR. The problem of profound mismeasurement and the power of epidemiologic studies of diet and cancer. Nutr Cancer. 1988;11:243-50.
20. Kipnis V, Midthune D, Freedman LS, Bingham S, Schatzkin A, Subar A, et al. Empirical evidence of correlated biases in dietary assessment instruments and its implications. Am J Epidemiol. 2001;153:394-403.
21. Kaaks R, Ferrari P, Ciampi A, Plummer M, Riboli E. Uses and limitations of statistical accounting for random error correlations, in the validation of dietary questionnaire assessments. Public Health Nutr. 2002;5:969-76.
22. Tooze JA, Midthune D, Dodd KW, Freedman LS, Krebs-Smith SM, Subar AF, et al. A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution. J Am Diet Assoc. 2006;106:1575-87.
23. Instituto Colombiano de Bienestar Familiar. Encuesta Nacional de la Situación Nutricional en Colombia, 2005. Bogotá D.C.: ICBF; 2005.
24. Ochoa FL, Montoya LP. Mortalidad por cáncer en Colombia 2001. Rev CES Med. 2004;18:19-36.
25. Mark SD, Thomas DG, Decarli A. Measurement of exposure to nutrients: an approach to the selection of informative foods. Am J Epidemiol. 1996;143:514-21.
26. Thomas DG. Software Max r 2.1. Bethesda: National Cancer Institute; 1996.
27. Stryker WS, Salvini S, Stampfer MJ, Sampson L, Colditz GA, Willett WC. Contributions of specific foods to absolute intake and between-person variation of nutrient consumption. J Am Diet Assoc. 1991;91:172-8.
28. Decarli A, Ferrarroni M, Palli D. A reduced questionnaire to investigate the Mediterranean diet in epidemiologic studies. Epidemiology. 1994;5:251-6.
29. Herrán OF, Gamboa EM, Prada GE. Diseño y eficacia de pruebas para determinar la deficiencia de hierro. Rev Chil Nutr. 2006;33:518-26.
30. Herrán OF, Quintero DC, Ardila MF. Sources and magnitude of the variation in the diet of Bucaramanga, Colombia. Rev Chil Nutr. 2006;33:55-64.
31. Willett WC. Diet and cancer: One view at the start of the millennium. Cancer Epidemiol Biomarkers Prev. 2001;10:3-8.
32. Lauritsen J. Software FoodCalc v. 1.3. Diet, cancer and health project. Copenhague: Danish Cancer Society; 1998.
33. Stata Corporation. Software STATA/SE v. 10 (StataCorp. 2007. Stata Statistical Sofware: Release 10. College Station, TX: Stata Corporation). Texas: Stata Press; 2007.
34. Fritsch HM, Salgado-Martínez H. Manual de encuestas de dieta. Perspectivas en salud pública, No. 23. Cuernavaca: Instituto Nacional de Salud Pública; 1996.
35. Herrán OF, Bautista LE, Quintero DC. Tabla de composición de alimentos consumidos en Bucaramanga. Segunda edición. Bucaramanga: Universidad Industrial de Santander; 2003.
36. Hansen Gaurth R, Wyse BW. Expression of nutrient allowances per 1,000 kilocalories. J Am Diet Assoc. 1980;76:223-7.
37. Williams CD, Satia JA, Adair LS, Stevens J, Galanko J, Keku TO, et al. Dietary patterns, food groups, and rectal cancer risk in whites and African-Americans. Cancer Epidemiol Biomarkers Prev. 2009;18:1552-61.
38. Bond TG, Fox CM. Applying the Rasch Model: Fundamental measurement in the human sciences. 2 edition. London: Lawrence Erlbaum Associates Publishers; 2007.
How to Cite
1.
Herrán OF, Ardila MF, Rojas MP, Hernández GA. Design of dietary questionnaires to study the relationships between diet and cancer prevalence in Colombia. biomedica [Internet]. 2010 Mar. 1 [cited 2024 May 11];30(1):116-25. Available from: https://revistabiomedica.org/index.php/biomedica/article/view/159
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