Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Associations between food patterns defined by cluster analysis and colorectal cancer incidence in the NIH–AARP diet and health study

European Journal of Clinical Nutrition volume 63, pages 707–717 (2009)Cite this article

Abstract

Background/Objectives:

To examine associations between food patterns, constructed with cluster analysis, and colorectal cancer incidence within the National Institutes of Health–AARP Diet and Health Study.

Subjects/Methods:

A prospective cohort, aged 50–71 years at baseline in 1995–1996, followed until the end of 2000. Food patterns were constructed, separately in men (n=293 576) and women (n=198 730), with 181 food variables (daily intake frequency per 1000 kcal) from a food frequency questionnaire. Four large clusters were identified in men and three in women. Cox proportional hazards regression examined associations between patterns and cancer incidence.

Results:

In men, a vegetable and fruit pattern was associated with reduced colorectal cancer incidence (multivariate hazard ratio, HR: 0.85; 95% confidence interval, CI: 0.76, 0.94), when compared to less salutary food choices. Both the vegetable and fruit pattern and a fat-reduced foods pattern were associated with reduced rectal cancer incidence in men. In women, a similar vegetable and fruit pattern was associated with colorectal cancer protection (age-adjusted HR: 0.82; 95% CI: 0.70, 0.95), but the association was not statistically significant in multivariate analysis.

Conclusions:

These results, together with findings from previous studies support the hypothesis that micronutrient dense, low-fat, high-fiber food patterns protect against colorectal cancer.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  • Aldenderfer MS, Blashfield RK (1984). Cluster Analysis. Quantitative Applications in the Social Sciences. Sage Publications: California.

    Google Scholar 

  • Austin GL, Adair LS, Galanko JA, Martin CF, Satia JA, Sandler RS (2007). A diet high in fruits and low in meats reduces the risk of colorectal adenomas. J Nutr 137, 999–1004.

    Article  CAS  Google Scholar 

  • Bingham SA, Day NE, Luben R, Ferrari P, Slimani N, Norat T et al. (2003). Dietary fibre in food and protection against colorectal cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC): an observational study. Lancet 361, 1496–1501.

    Article  Google Scholar 

  • Byers T, Gieseker K (1997). Issues in the design and interpretation of studies of fatty acids and cancer in humans. Am J Clin Nutr 66 (Suppl), 1541S–1547S.

    Article  CAS  Google Scholar 

  • Cox DR (1972). Regression models and life tables. J R Stat Soc B 34, 187–220.

    Google Scholar 

  • Dixon LB, Balder HF, Virtanen MJ, Rashidkhani B, Mannisto S, Krogh V et al. (2004). Dietary patterns associated with colon and rectal cancer: results from the Dietary Patterns and Cancer (DIETSCAN) Project. Am J Clin Nutr 80, 1003–1011.

    Article  CAS  Google Scholar 

  • Engeset D, Alsaker E, Ciampi A, Lund E (2005). Dietary patterns and lifestyle factors in the Norwegian EPIC cohort: the Norwegian Women and Cancer (NOWAC) study. Eur J Clin Nutr 59, 675–684.

    Article  CAS  Google Scholar 

  • Flood A, Rastogi T, Wirfält E, Mitrou PN, Reedy J, Subar AF et al. (2008). Dietary patterns as identified by factor analysis and colorectal cancer among middle aged Americans. Am J Clin Nutr 88, 176–184.

    Article  CAS  Google Scholar 

  • Fung T, Hu FB, Fuchs C, Giovannucci E, Hunter DJ, Stampfer MJ et al. (2003). Major dietary patterns and the risk of colorectal cancer in women. Arch Intern Med 163, 309–314.

    Article  Google Scholar 

  • Giovannucci E (2002). Epidemiologic studies of folate and colorectal neoplasia: a review. J Nutr 132, 2350S–2355S.

    Article  CAS  Google Scholar 

  • Giovannucci E, Stampfer MJ, Colditz G, Rimm EB, Willett WC (1992). Relationship of diet to risk of colorectal adenoma in men. J Natl Cancer Inst 84, 91–98.

    Article  CAS  Google Scholar 

  • Greenwood DC, Cade JE, Draper A, Barrett JH, Calvert C, Greenhalgh A (2000). Seven unique food consumption patterns identified among women in the UK Women's Cohort Study. Eur J Clin Nutr 54, 314–320.

    Article  CAS  Google Scholar 

  • Harnack L, Nicodemus K, Jacobs D, Folsom AR (2002). An evaluation of the Dietary Guidelines for Americans in relation to cancer occurrence. Am J Clin Nutr 76, 889–896.

    Article  CAS  Google Scholar 

  • Hebert JR, Ma Y, Clemow L, Ockene IS, Saperia G, Stanek Jr E et al. (1997). Gender differences in social desirability and social approval bias in dietary self-report. Am J Epidemiol 146, 1046–1055.

    Article  CAS  Google Scholar 

  • Hu FB (2002). Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13, 3–9.

    Article  CAS  Google Scholar 

  • Hulshof KF, Wedel M, Lowik MR, Kok FJ, Kistemaker C, Hermus RJ et al. (1992). Clustering of dietary variables and other lifestyle factors (Dutch Nutritional Surveillance System). J Epidemiol Commun Health 46, 417–424.

    Article  CAS  Google Scholar 

  • Jacques PF, Tucker KL (2001). Are dietary patterns useful for understanding the role of diet in chronic disease? Am J Clin Nutr 73, 1–2.

    Article  CAS  Google Scholar 

  • Kant AK (2004). Dietary patterns and health outcomes. J Am Diet Assoc 104, 615–635.

    Article  Google Scholar 

  • Kipnis V, Subar AF, Midthune D, Freedman LS, Ballard-Barbash R, Troiano RP et al. (2003). Structure of dietary measurement error: results of the OPEN biomarker study. Am J Epidemiol 158, 14–21.

    Article  Google Scholar 

  • Larsson SC, Bergkvist L, Rutegard J, Giovannucci E, Wolk A (2006). Calcium and dairy food intakes are inversely associated with colorectal cancer risk in the Cohort of Swedish Men. Am J Clin Nutr 83, 667–673.

    Article  CAS  Google Scholar 

  • Macintyre S, Anderson A (1997). Socio-demographic and psycho-social variables. In: Margetts BM, Nelson M (eds). Design concepts in Nutitional Epidemiology, 2nd edn. Oxford University Press: Oxford, pp 273–288.

    Chapter  Google Scholar 

  • McCann SE, Marshall JR, Brasure JR, Graham S, Freudenheim JL (2001). Analysis of patterns of food intake in nutritional epidemiology: food classification in principal components analysis and the subsequent impact on estimates for endometrial cancer. Public Health Nutr 4, 989–997.

    CAS  PubMed  Google Scholar 

  • Michaud DS, Midthune D, Hermansen S, Leitzmann M, Harlan LC, Kipnis V et al. (2005). Comparison of cancer registry case ascertainment with SEER estimates and self-reporting in a subset of the NIH–AARP Diet and Health Study. J Registry Manag 32, 70–75.

    Google Scholar 

  • Mizoue T, Yamaji T, Tabata S, Yamaguchi K, Shimizu E, Mineshita M et al. (2005). Dietary patterns and colorectal adenomas in Japanese men: the Self-Defense Forces Health Study. Am J Epidemiol 161, 338–345.

    Article  Google Scholar 

  • Newby PK, Tucker KL (2004). Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev 62, 177–203.

    Article  CAS  Google Scholar 

  • Norat T, Bingham S, Ferrari P, Slimani N, Jenab M, Mazuir M et al. (2005). Meat, fish, and colorectal cancer risk: the European Prospective Investigation into cancer and nutrition. J Natl Cancer Inst 97, 906–916.

    Article  Google Scholar 

  • Norat T, Riboli E (2003). Dairy products and colorectal cancer. A review of possible mechanisms and epidemiological evidence. Eur J Clin Nutr 57, 1–17.

    Article  CAS  Google Scholar 

  • O'Doherty Jensen K, Holm L (1999). Preferences, quantities and concerns: socio-cultural perspectives on the gendered consumption of foods. Eur J Clin Nutr 53, 351–359.

    Article  CAS  Google Scholar 

  • Patterson RE, Haines PS, Popkin BM (1994). Health lifestyle patterns of US adults. Prev Med 23, 453–460.

    Article  CAS  Google Scholar 

  • Randall E, Marshall JR, Brasure J, Graham S (1992). Dietary patterns and colon cancer in Western New York. Nutr Cancer 18, 265–276.

    Article  CAS  Google Scholar 

  • Reedy J, Haines PS, Campbell MK (2005). The influence of health behavior clusters on dietary change. Prev Med 41, 268–275.

    Article  Google Scholar 

  • Reedy J, Mitrou PN, Krebs-Smith SM, Wirfalt E, Flood A, Kipnis V et al. (2008). Index-based dietary patterns and risk of colorectal cancer: the NIH–AARP Diet and Health Study. Am J Epidemiol 168, 38–48.

    Article  CAS  Google Scholar 

  • Rouillier P, Senesse P, Cottet V, Valleau A, Faivre J, Boutron-Ruault MC (2005). Dietary patterns and the adenomacarcinoma sequence of colorectal cancer. Eur J Nutr 44, 311–318.

    Article  CAS  Google Scholar 

  • Schatzkin A, Dorgan J, Swanson C, Potischman N (1995). Diet and cancer: future etiologic research. Environ Health Perspect 103, 171–175.

    PubMed  PubMed Central  Google Scholar 

  • Schatzkin A, Subar AF, Thompson FE, Harlan LC, Tangrea J, Hollenbeck AR et al. (2001). Design and serendipity in establishing a large cohort with wide dietary intake distributions: the National Institutes of Health-American Association of Retired Persons Diet and Health Study. Am J Epidemiol 154, 1119–1125.

    Article  CAS  Google Scholar 

  • Slattery ML, Boucher KM, Caan BJ, Potter JD, Ma KN (1998). Eating patterns and colon cancer. Am J Epidemiol 148, 4–16.

    Article  CAS  Google Scholar 

  • Subar AF, Midthune D, Kulldorff M, Brown CC, Thompson FE, Kipnis V et al. (2000). Evaluation of alternative approaches to assign nutrient values to food groups in food frequency questionnaires. Am J Epidemiol 152, 279–286.

    Article  CAS  Google Scholar 

  • Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S et al. (2001a). Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America's Table Study. Am J Epidemiol 154, 1089–1099.

    Article  CAS  Google Scholar 

  • Subar AF, Thompson FE, Smith AF, Jobe JB, Ziegler RG, Potischman N et al. (1995). Improving food frequency questionnaires: a qualitative approach using cognitive interviewing. J Am Diet Assoc 95, 781–788.

    Article  CAS  Google Scholar 

  • Subar AF, Ziegler RG, Thompson FE, Johnson CC, Weissfeld JL, Reding D et al. (2001b). Is shorter always better? Relative importance of questionnaire length and cognitive ease on response rates and data quality for two dietary questionnaires. Am J Epidemiol 153, 404–409.

    Article  CAS  Google Scholar 

  • Terry P, Hu FB, Hansen H, Wolk A (2001). Prospective study of major dietary patterns and colorectal cancer risk in women. Am J Epidemiol 154, 1143–1149.

    Article  CAS  Google Scholar 

  • Thompson FE, Kipnis V, Midthune D, Freedman LS, Carroll R, Subar AF et al. (2008). Performance of a food-frequency questionnaire in the US NIH–AARP (National Institutes of Health–American Association of Retired Persons) Diet and Health Study. Public Health Nutr 11, 183–195.

    Article  Google Scholar 

  • Tucker KL, Dallal GE, Rush D (1992). Dietary patterns of elderly Boston-area residents defined by cluster analysis. J Am Diet Assoc 92, 1487–1491.

    CAS  PubMed  Google Scholar 

  • Willett WC, Howe GR, Kushi LH (1997). Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 65 (Suppl), 1220S–1228S.

    Article  CAS  Google Scholar 

  • Wirfält E, Hedblad B, Gullberg B, Mattisson I, Andrén C, Rosander U et al. (2001). Food patterns and components of the metabolic syndrome in men and women. A cross-sectional study within the Malm' Diet and Cancer cohort. Am J Epidemiol 154, 1150–1159.

    Article  Google Scholar 

  • World Cancer Research Fund/American Institute for Cancer Research (2007). Food, Nutrition, Physical Activity and the prevention of Cancer: A Global Perspective. AICR: Washington, DC.

Download references

Acknowledgements

This research was supported by the Intramural Research Program of the NIH, National Cancer Institute. Cancer incidence data from the Atlanta metropolitan area were collected by the Georgia Center for Cancer Statistics, Department of Epidemiology, Rollins School of Public Health, Emory University. Cancer incidence data from California were collected by the California Department of Health Services, Cancer Surveillance Section. Cancer incidence data from the Detroit metropolitan area were collected by the Michigan Cancer Surveillance Program, Community Health Administration, State of Michigan. The Florida cancer incidence data used in this report were collected by the Florida Cancer Data System under contract to the Department of Health (DOH). The views expressed herein are solely those of the authors and do not necessarily reflect those of the contractor or DOH. Cancer incidence data from Louisiana were collected by the Louisiana Tumor Registry, Louisiana State University Medical Center in New Orleans. Cancer incidence data from New Jersey were collected by the New Jersey State Cancer Registry, Cancer Epidemiology Services, New Jersey State Department of Health and Senior Services. Cancer incidence data from North Carolina were collected by the North Carolina Central Cancer Registry. Cancer incidence data from Pennsylvania were supplied by the Division of Health Statistics and Research, Pennsylvania Department of Health, Harrisburg, Pennsylvania. The Pennsylvania Department of Health specifically disclaims responsibility for any analyses, interpretations or conclusions. We are indebted to the participants in the NIH–AARP Diet and Health Study for their outstanding cooperation. Funding was also received from the Swedish Cancer Foundation (contract 05 0128 to EW) and the Swedish Council for Working Life and Social Research (contract 2005-1703 to EW).

Author information

Authors and Affiliations

  1. Department of Clinical Sciences (Malmö), Nutrition Epidemiology, Lund University, Malmö, Sweden

    E Wirfält

  2. National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    D Midthune, J Reedy, P Mitrou, A F Subar, M Leitzmann, T Mouw, A Schatzkin & V Kipnis

  3. Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

    P Mitrou

  4. Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis, MN, USA

    A Flood

  5. AARP, Washington, DC, USA

    A R Hollenbeck

Authors
  1. E Wirfält
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D Midthune
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J Reedy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. P Mitrou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. A Flood
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. A F Subar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M Leitzmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. T Mouw
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. A R Hollenbeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. A Schatzkin
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. V Kipnis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E Wirfält.

Appendices

Appendix 1

Table A1

Table a1 Description of six food pattern clusters in men (n=293 576) of the AARP cohort 1995–2000
Full size table

Appendix 2

Table A2

Table a2 Description of nine food pattern clusters in women (n=198 730) of the NIH–AARP cohort 1995–2000
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wirfält, E., Midthune, D., Reedy, J. et al. Associations between food patterns defined by cluster analysis and colorectal cancer incidence in the NIH–AARP diet and health study. Eur J Clin Nutr 63, 707–717 (2009). https://doi.org/10.1038/ejcn.2008.40

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ejcn.2008.40

Keywords

This article is cited by

Search

Advanced search

Quick links