Skip to main content

Advertisement

Springer Nature Link
Log in

Association of dietary patterns derived by reduced-rank regression with colorectal cancer risk and mortality

  • Original Contribution
  • Published:
European Journal of Nutrition Aims and scope Submit manuscript

Abstract

Purpose

Unhealthy dietary patterns contribute to an increased risk of colorectal cancer (CRC). Limited prior research has used reduced rank regression (RRR) to assess dietary patterns relative to CRC risk. This study aimed to identify dietary patterns derived by RRR and assess their associations with CRC risk and mortality.

Methods

We used data from the multicentre Prostate, Lung, Colorectal, and Ovarian Cancer Screening (PLCO) trial. Dietary intake was assessed using a Dietary History Questionnaire. In the RRR intake of fibre, folate, and the percentage of energy from carbohydrates, saturated and unsaturated fatty acids were used as response variables. Cox models and competing risk survival regression, with age as the time scale, were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for CRC risk and mortality, respectively.

Results

The median follow-up time for CRC risk (n = 1044) and mortality (n = 499) was 9.4 years (Interquartile Range: 8. 0, 10.1) and 16.9 years (11.9, 18.6), respectively. Two dietary patterns were identified: the first was characterised by high carbohydrate, folate and low fatty acid intake, and the second by high fibre and unsaturated fatty acid. Compared to participants in the first tertile of the high fibre and unsaturated fatty acid pattern, those in the third tertile had a lower risk of CRC (HR = 0.88; 95% CI: 0.76, 1.03), and colon cancer (HR = 0.85; 95% CI: 0.72, 1.01). Conversely, the high carbohydrate, high folate and low fatty acid pattern had no association with CRC outcomes. None of the dietary patterns showed associations with rectal cancer or CRC mortality.

Conclusion

A diet enriched with high fibre and unsaturated fatty acids may reduce the risk of CRC. These results highlight the potential protective effect of adequate fibre intake in conjunction with high consumption of unsaturated fatty acids against CRC.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
€34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

The data presented in this manuscript can be accessed from the NCI upon request.

References

  1. Rawla P, Sunkara T, Barsouk A (2019) Epidemiology of colorectal cancer: incidence, mortality, survival, and risk factors. Prz Gastroenterol 14(2):89–103

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Siegel RL, Wagle NS, Cercek A, Smith RA, Jemal A (2023) Colorectal cancer statistics, 2023. Cancer J Clin 73(3):233–254

    Article  Google Scholar 

  3. Xi Y, Xu P (2021) Global colorectal cancer burden in 2020 and projections to 2040. Transl Oncol 14(10):101174

    Article  PubMed  PubMed Central  Google Scholar 

  4. Valle L (2014) Genetic predisposition to colorectal cancer: where we stand and future perspectives. World J Gastroenterology: WJG 20(29):9828

    Article  CAS  PubMed Central  Google Scholar 

  5. Munteanu I, Mastalier B (2014) Genetics of colorectal cancer. J Med Life 7(4):507

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Shaw E, Farris MS, Stone CR, Derksen JW, Johnson R, Hilsden RJ et al (2018) Effects of physical activity on colorectal cancer risk among family history and body mass index subgroups: a systematic review and meta-analysis. BMC Cancer 18:1–15

    Article  Google Scholar 

  7. Parsa N (2012) Environmental factors inducing human cancers. Iran J Public Health 41(11):1

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Elizabeth L, Machado P, Zinöcker M, Baker P, Lawrence M (2020) Ultra-processed foods and health outcomes: a narrative review. Nutrients 12(7):1955

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Lotfi K, Salari-Moghaddam A, Yousefinia M, Larijani B, Esmaillzadeh A (2021) Dietary intakes of monounsaturated fatty acids and risk of mortality from all causes, cardiovascular disease and cancer: a systematic review and dose-response meta-analysis of prospective cohort studies. Ageing Res Rev 72:101467

    Article  CAS  PubMed  Google Scholar 

  10. Hu J, Wang J, Li Y, Xue K, Kan J (2023) Use of Dietary fibers in reducing the risk of several Cancer types: an Umbrella Review. Nutrients 15(11):2545

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Arayici ME, Mert-Ozupek N, Yalcin F, Basbinar Y, Ellidokuz H (2022) Soluble and insoluble Dietary Fiber Consumption and Colorectal Cancer risk: a systematic review and Meta-analysis. Nutr Cancer 74(7):2412–2425

    Article  CAS  PubMed  Google Scholar 

  12. Fu H, He J, Li C, Deng Z, Chang H (2023) Folate intake and risk of colorectal cancer: a systematic review and up-to-date meta-analysis of prospective studies. Eur J Cancer Prev 32(2):103–112

    Article  PubMed  Google Scholar 

  13. Agnoli C, Pounis G, Krogh V (2019) Dietary pattern analysis. Analysis in Nutrition Research: Elsevier; pp. 75–101

  14. Part D (2020) Chapter 8: Dietary Patterns. Guidelines Advisory Committee. 2020-07

  15. Zhao J, Li Z, Gao Q, Zhao H, Chen S, Huang L et al (2021) A review of statistical methods for dietary pattern analysis. Nutr J 20(1):1–18

    Article  Google Scholar 

  16. Hu FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13(1):3–9

    Article  CAS  PubMed  Google Scholar 

  17. Hoffmann K, Zyriax B-C, Boeing H, Windler E (2004) A dietary pattern derived to explain biomarker variation is strongly associated with the risk of coronary artery disease. Am J Clin Nutr 80(3):633–640

    Article  CAS  PubMed  Google Scholar 

  18. Moazzen S, van der Sloot KWJ, Bock GHd, Alizadeh BZ (2021) Systematic review and meta-analysis of diet quality and colorectal cancer risk: is the evidence of sufficient quality to develop recommendations? Crit Rev Food Sci Nutr 61(16):2773–2782

    Article  CAS  PubMed  Google Scholar 

  19. Steck SE, Guinter M, Zheng J, Thomson CA (2015) Index-based dietary patterns and colorectal cancer risk: a systematic review. Adv Nutr 6(6):763–773

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Morze J, Danielewicz A, Przybyłowicz K, Zeng H, Hoffmann G, Schwingshackl L (2021) An updated systematic review and meta-analysis on adherence to mediterranean diet and risk of cancer. Eur J Nutr 60(3):1561–1586

    Article  CAS  PubMed  Google Scholar 

  21. Mohseni R, Mohseni F, Alizadeh S, Abbasi S (2020) The association of dietary approaches to stop hypertension (DASH) diet with the risk of colorectal cancer: a meta-analysis of observational studies. Nutr Cancer 72(5):778–790

    Article  CAS  PubMed  Google Scholar 

  22. Yusof AS, Isa ZM, Shah SA (2012) Dietary patterns and risk of colorectal cancer: a systematic review of cohort studies (2000–2011). Asian Pac J Cancer Prev 13(9):4713–4717

    Article  PubMed  Google Scholar 

  23. Feng Y-L, Shu L, Zheng P-F, Zhang X-Y, Si C-J, Yu X-L et al (2017) Dietary patterns and colorectal cancer risk: a meta-analysis. Eur J Cancer Prev 26(3):201–211

    Article  PubMed  Google Scholar 

  24. Kesse E, Clavel-Chapelon F, Boutron-Ruault M-C (2006) Dietary patterns and risk of colorectal tumors: a cohort of French women of the National Education System (E3N). Am J Epidemiol 164(11):1085–1093

    Article  CAS  PubMed  Google Scholar 

  25. Jafari Nasab S, Ghanavati M, Bahrami A, Rafiee P, Sadeghi A, Clark CC et al (2021) Dietary nutrient patterns and the risk of colorectal cancer and colorectal adenomas: a case-control study. Eur J Cancer Prev 30(1):46–52

    Article  CAS  PubMed  Google Scholar 

  26. Tucker KL (2010) Dietary patterns, approaches, and multicultural perspective. Appl Physiol Nutr Metab 35(2):211–218

    Article  PubMed  Google Scholar 

  27. Schulz CA, Oluwagbemigun K, Nöthlings U (2021) Advances in dietary pattern analysis in nutritional epidemiology. Eur J Nutr 60(8):4115–4130. https://doi.org/10.1007/s00394-021-02545-9

  28. Pot GK, Stephen AM, Dahm CC, Key TJ, Cairns BJ, Burley VJ et al (2014) Dietary patterns derived with multiple methods from food diaries and breast cancer risk in the UK Dietary Cohort Consortium. Eur J Clin Nutr 68(12):1353–1358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Melaku YA, Gill TK, Taylor AW, Adams R, Shi Z (2018) A comparison of principal component analysis, partial least-squares and reduced-rank regressions in the identification of dietary patterns associated with bone mass in ageing australians. Eur J Nutr 57:1969–1983

    Article  PubMed  Google Scholar 

  30. U.S. Department of Agriculture and U.S. Department of Health and Human Services (2023) Dietary Guidelines for Americans, 2020–2025. 9th Edition. https://www.dietaryguidelines.gov/ available on September 21

  31. Fan L, Cai Y, Wang H, Zhang H, Chen C, Zhang M, Lu Z, Li Y, Zhang F, Ning C, Wang W (2023) Saturated fatty acid intake, genetic risk and colorectal cancer incidence: a large‐scale prospective cohort study. Int J Cancer 153(3):499–511

  32. Fan L, Cai Y, Wang H, Zhang H, Chen C, Zhang M et al (2023) Saturated fatty acid intake, genetic risk and colorectal cancer incidence: a large-scale prospective cohort study. Int J Cancer 153(3):499–511. https://doi.org/10.1002/ijc.34544

  33. Shekari S, Fathi S, Roumi Z, Akbari ME, Tajadod S, Afsharfar M et al (2022) Association between dietary intake of fatty acids and colorectal cancer, a case-control study. Front Nutr 9:856408

    Article  PubMed  PubMed Central  Google Scholar 

  34. Xu AA, Kennedy LK, Hoffman K, White DL, Kanwal F, El-Serag HB et al (2022) Dietary fatty acid intake and the colonic gut microbiota in humans. Nutrients 14(13):2722

    Article  PubMed  PubMed Central  Google Scholar 

  35. Black A, Huang W-Y, Wright P, Riley T, Mabie J, Mathew S et al (2015) PLCO: evolution of an epidemiologic resource and opportunities for future studies. Rev Recen Clin Trial 10(3):238–245

    Article  Google Scholar 

  36. Guinter MA, McLain AC, Merchant AT, Sandler DP, Steck SE (2018) A dietary pattern based on estrogen metabolism is associated with breast cancer risk in a prospective cohort of postmenopausal women. Int J Cancer 143(3):580–590

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Xiao Y, Wang Y, Gu H, Xu Z, Tang Y, He H et al (2023) Adherence to the Paleolithic diet and paleolithic-like lifestyle reduce the risk of colorectal cancer in the United States: a prospective cohort study. J Translational Med 21(1):482

    Article  Google Scholar 

  38. Zhong G-C, Li Z, You A-J, Zhu Q, Wang C-R, Yang P-F (2023) Plant-based diets and the risk of pancreatic cancer: a large prospective multicenter study. Am J Clin Nutr 117(2):235–242

    Article  PubMed  Google Scholar 

  39. Li Z, Wang K, Shivappa N, Hébert JR, Chen H, Liu H et al (2022) Inflammatory potential of diet and colorectal carcinogenesis: a prospective longitudinal cohort. Br J Cancer 126(12):1735–1743

    Article  PubMed  PubMed Central  Google Scholar 

  40. Agricultural Health Study Questionnaires & Study Data. https://aghealth.nih.gov/collaboration/questionnaires.html. Access on 11 December 2023 [

  41. National Cancer Institute. PLCO - the cancer data access system, Washington DC National Cancer Institute  https://cdas.cancer.gov/learn/plco/early-qx/ [

  42. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S et al (2001) Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the eating at America’s table study. Am J Epidemiol 154(12):1089–1099

    Article  CAS  PubMed  Google Scholar 

  43. Thompson FE, Subar AF, Brown CC, Smith AF, Sharbaugh CO, Jobe JB et al (2002) Cognitive research enhances accuracy of food frequency questionnaire reports: results of an experimental validation study. J Am Diet Assoc 102(2):212–225

    Article  PubMed  Google Scholar 

  44. Tippett Kand Cypel Y (1997) Design, Operation The Continuing Survey of Food Intakes by individuals and the Diet and Health Knowledge Survey, 1994–96. US Department of Agriculture, Springfiled. Agricultural Research Service, Nationwide Food Surveys Report. 96–1

  45. Bowman SA, Friday JE, Moshfegh AJ (2008) MyPyramid Equivalents Database, 2.0 for USDA survey foods, 2003–2004: documentation and user guide. US Department of Agriculture

  46. ClinicalTrials.gov (2022) Screening for Colorectal Cancer in Older Patients (PLCO Screening Trial). https://classic.clinicaltrials.gov/ct2/show/study/NCT01696981#wrapper

  47. Kitahara CM, Trabert B, Katki HA, Chaturvedi AK, Kemp TJ, Pinto LA et al (2014) Body mass index, physical activity, and serum markers of inflammation, immunity, and insulin resistance. Cancer Epidemiol Biomarkers Prev 23(12):2840–2849

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Wolin KY, GRUBB R III, Ragard L, Mabie J, Andriole GL et al (2015) Physical activity and benign prostatic hyperplasia-related outcomes and nocturia. Med Sci Sports Exerc 47(3):581

    Article  PubMed  PubMed Central  Google Scholar 

  49. WHO G. Global physical activity questionnaire (GPAQ) analysis guide. Geneva: World Health Organization (2012) 1–22

  50. Virostko J, Capasso A, Yankeelov TE, Goodgame B (2019) Recent trends in the age at diagnosis of colorectal cancer in the US National Cancer Data Base, 2004-2015. Cancer 125(21):3828–3835

    Article  PubMed  Google Scholar 

  51. Baraibar I, Ros J, Saoudi N, Salvà F, García A, Castells M et al (2023) Sex and gender perspectives in colorectal cancer. ESMO open 8(2):101204

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Liu L, Shi Y, Li T, Qin Q, Yin J, Pang S et al (2016) Leisure time physical activity and cancer risk: evaluation of the WHO’s recommendation based on 126 high-quality epidemiological studies. Br J Sports Med 50(6):372–378

    Article  PubMed  Google Scholar 

  53. Komaki Y, Komaki F, Micic D, Ido A, Sakuraba A (2017) Risk of colorectal cancer in chronic liver diseases: a systematic review and meta-analysis. Gastrointest Endosc 86(1):93–104 e5

    Article  PubMed  Google Scholar 

  54. Johnston L, Carey F (2020) Pathology of colorectal polyps and cancer. Surg (Oxford) 38(1):12–17

    Article  Google Scholar 

  55. Shu L, Shen X-M, Li C, Zhang X-Y, Zheng P-F (2017) Dietary patterns are associated with type 2 diabetes mellitus among middle-aged adults in Zhejiang Province, China. Nutr J 16(1):1–9

    Article  CAS  Google Scholar 

  56. Ndanuko RN, Tapsell LC, Charlton KE, Neale EP, Batterham MJ (2016) Dietary patterns and blood pressure in adults: a systematic review and meta-analysis of randomized controlled trials. Adv Nutr 7(1):76–89

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Min M, Li-Fa X, Dong H, Jing W, Ming-Jie B (2017) Dietary patterns and overweight/obesity: a review article. Iran J Public Health 46(7):869

    Google Scholar 

  58. Mandic M, Li H, Safizadeh F, Niedermaier T, Hoffmeister M, Brenner H (2023) Is the association of overweight and obesity with colorectal cancer underestimated? An umbrella review of systematic reviews and meta-analyses. Eur J Epidemiol 38(2):135–144

    Article  PubMed  PubMed Central  Google Scholar 

  59. Ta HDK, Nguyen NN, Ho DKN, Nguyen HD, Ni Y-C, Yee KX et al (2023) Association of diabetes mellitus with early-onset colorectal cancer: A systematic review and meta-analysis of 19 studies including 10 million individuals and 30,000 events. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 17(8):102828

  60. Xuan K, Zhao T, Sun C, Patel AS, Liu H, Chen X et al (2021) The association between hypertension and colorectal cancer: a meta-analysis of observational studies. Eur J Cancer Prev 30(1):84–96

    Article  CAS  PubMed  Google Scholar 

  61. World Health Organization (2023) Saturated fatty acid and trans-fatty acid intake for adults and children: WHO guideline. Saturated fatty acid and trans-fatty acid intake for adults and children. WHO guideline

  62. Humphreys KJ, Conlon MA, Young GP, Topping DL, Hu Y, Winter JM et al (2014) Dietary manipulation of oncogenic microRNA expression in human rectal mucosa: a randomized trial. Cancer Prev Res 7(8):786–795

    Article  CAS  Google Scholar 

  63. Seidelmann SB, Claggett B, Cheng S, Henglin M, Shah A, Steffen LM et al (2018) Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet Public Health 3(9):e419–e28

    Article  PubMed  PubMed Central  Google Scholar 

  64. World Cancer Research Fund International (2018) Diet, nutrition, physical activity and cancer: a global perspective: a summary of the Third Expert Report. World Cancer Research Fund International

  65. Włodarczyk J, Włodarczyk M, Zielińska M, Jędrzejczak B, Dziki Ł, Fichna J (2021) Blockade of fructose transporter protein GLUT5 inhibits proliferation of colon cancer cells: proof of concept for a new class of anti-tumor therapeutics. Pharmacol Rep 73(3):939–945

    Article  PubMed  PubMed Central  Google Scholar 

  66. Jiao J, Xu J-Y, Zhang W, Han S, Qin L-Q (2015) Effect of dietary fiber on circulating C-reactive protein in overweight and obese adults: a meta-analysis of randomized controlled trials. Int J Food Sci Nutr 66(1):114–119

    Article  CAS  PubMed  Google Scholar 

  67. Krishnamurthy VMR, Wei G, Baird BC, Murtaugh M, Chonchol MB, Raphael KL et al (2012) High dietary fiber intake is associated with decreased inflammation and all-cause mortality in patients with chronic kidney disease. Kidney Int 81(3):300–306

    Article  CAS  PubMed  Google Scholar 

  68. Song M, Garrett WS, Chan AT (2015) Nutrients, foods, and colorectal cancer prevention. Gastroenterology 148(6):1244–1260 e16

    Article  CAS  PubMed  Google Scholar 

  69. Bojková B, Winklewski PJ, Wszedybyl-Winklewska M (2020) Dietary fat and cancer—which is good, which is bad, and the body of evidence. Int J Mol Sci 21(11):4114

    Article  PubMed  PubMed Central  Google Scholar 

  70. Gleissman H, Johnsen JI, Kogner P (2010) Omega-3 fatty acids in cancer, the protectors of good and the killers of evil? Exp Cell Res 316(8):1365–1373

    Article  CAS  PubMed  Google Scholar 

  71. Denova-Gutierrez E, Tucker KL, Flores M, Barquera S, Salmeron J (2016) Dietary patterns are associated with predicted cardiovascular disease risk in an urban Mexican adult population. J Nutr 146(1):90–97

    Article  PubMed  Google Scholar 

  72. Abdel-Qadir H, Fang J, Lee DS, Tu JV, Amir E, Austin PC et al (2018) Importance of considering competing risks in time-to-event analyses: application to stroke risk in a retrospective cohort study of elderly patients with atrial fibrillation. Circulation: Cardiovasc Qual Outcomes 11(7):e004580

    Google Scholar 

  73. Nobbs HM, Yaxley A, Thomas J, Delaney C, Koczwara B, Luszcz M et al (2016) Do dietary patterns in older age influence the development of cancer and cardiovascular disease: a longitudinal study of ageing. Clin Nutr 35(2):528–535

    Article  PubMed  Google Scholar 

  74. White IR, Royston P (2009) Imputing missing covariate values for the Cox model. Stat Med 28(15):1982–1998

    Article  PubMed  PubMed Central  Google Scholar 

  75. Andersen K, Mariosa D, Adami H-O, Held C, Ingelsson E, Lagerros YT et al (2014) Dose–response relationship of total and leisure time physical activity to risk of heart failure: a prospective cohort study. Circulation: Heart Fail 7(5):701–708

    Google Scholar 

  76. Cornish R, Macleod J, Carpenter J, Tilling K (2017) Multiple imputation using linked proxy outcome data resulted in important bias reduction and efficiency gains: a simulation study. Emerg Themes Epidemiol 14(1):1–13

    Article  Google Scholar 

  77. Graham JW, Olchowski AE, Gilreath TD (2007) How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci 8:206–213

    Article  PubMed  Google Scholar 

  78. Little R, Rubin D (1987) Multiple imputation for nonresponse in surveys. John Wiley Sons Inc Doi 10:9780470316696

    Google Scholar 

  79. Jakobsen JC, Gluud C, Wetterslev J, Winkel P (2017) When and how should multiple imputation be used for handling missing data in randomised clinical trials–a practical guide with flowcharts. BMC Med Res Methodol 17(1):1–10

    Article  Google Scholar 

  80. StataCorp (2021) Stata: Release 17. Statistical Software. StataCorp LLC, College Station, TX

    Google Scholar 

  81. Posit team. RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston MA (2023) URL http://www.posit.co/ [

  82. Van Buuren S, Groothuis-Oudshoorn K (2011) Mice: Multivariate imputation by chained equations in R. J Stat Softw 45:1–67

    Article  Google Scholar 

  83. Fine JP, Gray RJ (1999) A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 94(446):496–509

    Article  Google Scholar 

  84. Willemsen RF, McNeil J, Heer E, Johnson ST, Friedenreich CM, Brenner DR (2022) Dietary patterns with combined and site-specific cancer incidence in Alberta’s tomorrow project cohort. Eur J Clin Nutr 76(3):360–372

    Article  CAS  PubMed  Google Scholar 

  85. Cho YA, Lee J, Oh JH, Chang HJ, Sohn DK, Shin A et al (2018) Inflammatory dietary pattern, IL-17F genetic variant, and the risk of Colorectal Cancer. Nutrients. 10(6)

  86. Fung TT, Hu FB, Schulze M, Pollak M, Wu T, Fuchs CS et al (2012) A dietary pattern that is associated with C-peptide and risk of colorectal cancer in women. Cancer Causes Control 23:959–965

    Article  PubMed  PubMed Central  Google Scholar 

  87. Weikert C, Schulze MB (2016) Evaluating dietary patterns: the role of reduced rank regression. Curr Opin Clin Nutr Metab Care 19(5):341–346

    Article  CAS  PubMed  Google Scholar 

  88. Xie Y, Ren YW, Li XL, Li ZN (2020) A review of the associations between Dietary Fiber Intake and Cancer Prevention or Prognosis. J Nutritional Oncol 5(3):123–131

    Article  Google Scholar 

  89. World Cancer Research Fund/American Institute for Cancer Research. Diet, nutrition, physical activity and cancer: aglobal perspective. Continuous Update Project Expert Report (2018) https://www.wcrf.org/wp-content/uploads/2021/02/Summary-of-Third-Expert-Report-2018.pdf accessed on April 14, 2022

  90. Grasgruber P, Hrazdira E, Sebera M, Kalina T (2018) Cancer incidence in Europe: an ecological analysis of nutritional and other environmental factors. Front Oncol 8:151

    Article  PubMed  PubMed Central  Google Scholar 

  91. Zelenskiy S, Thompson CL, Tucker TC, Li L (2014) High dietary glycemic load is associated with increased risk of colon cancer. Nutr Cancer 66(3):362–368

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Higginbotham S, Zhang Z-F, Lee I-M, Cook NR, Giovannucci E, Buring JE et al (2004) Dietary glycemic load and risk of colorectal cancer in the women’s Health Study. J Natl Cancer Inst 96(3):229–233

    Article  CAS  PubMed  Google Scholar 

  93. Sieri S, Krogh V, Agnoli C, Ricceri F, Palli D, Masala G et al (2015) Dietary glycemic index and glycemic load and risk of colorectal cancer: results from the EPIC-Italy study. Int J Cancer 136(12):2923–2931

    Article  CAS  PubMed  Google Scholar 

  94. Lu Y, Li D, Wang L, Zhang H, Jiang F, Zhang R et al (2023) Comprehensive Investigation on associations between Dietary Intake and blood levels of fatty acids and colorectal Cancer risk. Nutrients 15(3):730

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Hanson S, Thorpe G, Winstanley L, Abdelhamid AS, Hooper L (2020) Omega-3, omega-6 and total dietary polyunsaturated fat on cancer incidence: systematic review and meta-analysis of randomised trials. Br J Cancer 122(8):1260–1270

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Hébert JR, Frongillo EA, Adams SA, Turner-McGrievy GM, Hurley TG, Miller DR et al (2016) Perspective: randomized controlled trials are not a panacea for diet-related research. Adv Nutr 7(3):423–432

    Article  PubMed  PubMed Central  Google Scholar 

  97. Zeilstra D, Younes JA, Brummer RJ, Kleerebezem M (2018) Perspective: fundamental limitations of the randomized controlled trial method in nutritional research: the example of probiotics. Adv Nutr 9(5):561–571

    Article  PubMed  PubMed Central  Google Scholar 

  98. Ioannidis JP (2019) Unreformed nutritional epidemiology: a lamp post in the dark forest. Eur J Epidemiol 34:327–331

    Article  PubMed  Google Scholar 

  99. Tristan Asensi M, Napoletano A, Sofi F, Dinu M (2023) Low-Grade inflammation and Ultra-processed Foods Consumption: a review. Nutrients 15:1546

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Clemente-Suárez VJ, Beltrán-Velasco AI, Redondo-Flórez L, Martín-Rodríguez A, Tornero-Aguilera JF (2023) Global impacts of western Diet and its effects on Metabolism and Health: a narrative review. Nutrients 15(12):2749

    Article  PubMed  PubMed Central  Google Scholar 

  101. Chassard C, Lacroix C (2013) Carbohydrates and the human gut microbiota. Curr Opin Clin Nutr Metabolic Care 16(4):453–460

    Article  CAS  Google Scholar 

  102. Oliphant K, Allen-Vercoe E (2019) Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health. Microbiome. 7: 91. PUBMED; 2019

  103. Florea N, Perde D, Shami A (2022) ROLE OF THE GUT MICROBIOTA IN NUTRITION AND HEALTH. Sci Collect «InterConf» 107:363–366

    Google Scholar 

  104. Mora-Flores LP, Moreno-Terrazas Casildo R, Fuentes-Cabrera J, Pérez-Vicente HA, de Anda-Jáuregui G, Neri-Torres EE (2023) The role of Carbohydrate Intake on the gut microbiome: a weight of evidence systematic review. Microorganisms 11(7):1728

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Cheng X, Zheng J, Lin A, Xia H, Zhang Z, Gao Q et al (2020) A review: roles of carbohydrates in human diseases through regulation of imbalanced intestinal microbiota. J Funct Foods 74:104197

    Article  CAS  Google Scholar 

  106. Zehiroglu C, Ozturk Sarikaya SB (2019) The importance of antioxidants and place in today’s scientific and technological studies. J Food Sci Technol 56:4757–4774

    Article  PubMed  PubMed Central  Google Scholar 

  107. Bardelčíková A, Šoltys J, Mojžiš J (2023) Oxidative stress, inflammation and colorectal Cancer: an overview. Antioxidants 12(4):901

    Article  PubMed  PubMed Central  Google Scholar 

  108. Zhang P (2022) Influence of foods and nutrition on the gut microbiome and implications for intestinal health. Int J Mol Sci 23(17):9588

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Tremaroli V, Bäckhed F (2012) Functional interactions between the gut microbiota and host metabolism. Nature 489(7415):242–249

    Article  CAS  PubMed  Google Scholar 

  110. Komninou D, Ayonote A, Richie JP Jr, Rigas B (2003) Insulin resistance and its contribution to colon carcinogenesis. Experimental Biology Med 228(4):396–405

    Article  CAS  Google Scholar 

  111. Halvorsen BL, Carlsen MH, Phillips KM, Bøhn SK, Holte K, Jacobs DR Jr et al (2006) Content of redox-active compounds (ie, antioxidants) in foods consumed in the United States. Am J Clin Nutr 84(1):95–135

    Article  CAS  PubMed  Google Scholar 

  112. Rahaman MM, Hossain R, Herrera-Bravo J, Islam MT, Atolani O, Adeyemi OS et al (2023) Natural antioxidants from some fruits, seeds, foods, natural products, and associated health benefits: an update. Food Sci Nutr 11(4):1657–1670

    Article  PubMed  PubMed Central  Google Scholar 

  113. Chaudhary P, Janmeda P, Docea AO, Yeskaliyeva B, Abdull Razis AF, Modu B et al (2023) Oxidative stress, free radicals and antioxidants: potential crosstalk in the pathophysiology of human diseases. Front Chem 11:1158198

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Zegeye Abebe is thankful for the scholarship provided by the Australian Government Research Training Program. The authors express their gratitude to the National Cancer Institute for providing access to the data collected during the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial (PLCO-1166). The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by NCI.

Funding

No specific fund was secured for this study. YAM and MMW are supported by a National Health and Medical Research Council of Australia (NHMRC) Investigator Grants (2009776 and 2009050, respectively).

Author information

Authors and Affiliations

  1. Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, 5042, Australia

    Zegeye Abebe, Molla Mesele Wassie, Phuc D. Nguyen, Amy C. Reynolds & Yohannes Adama Melaku

  2. Department of Human Nutrition, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, P. O. Box 196, Gondar, Ethiopia

    Zegeye Abebe

  3. Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia

    Yohannes Adama Melaku

Authors
  1. Zegeye Abebe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Molla Mesele Wassie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Phuc D. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amy C. Reynolds
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yohannes Adama Melaku
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ZA, MMW, PDN, ACR, YAM designed the analysis; ZA conducted the analysis and wrote the draft manuscript; MMW, ACR and YAM revised and edited the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Zegeye Abebe.

Ethics declarations

Ethical approval

The usage of the CRC data in the PLCO study was authorised by the National Cancer Institute (PLCO-1166) and the Human Research Ethics Committee of Flinders University (project number 6435).

Competing interests

All authors declare that they have no competing interests.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abebe, Z., Wassie, M.M., Nguyen, P.D. et al. Association of dietary patterns derived by reduced-rank regression with colorectal cancer risk and mortality. Eur J Nutr 64, 33 (2025). https://doi.org/10.1007/s00394-024-03513-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00394-024-03513-9

Keywords

Search

Navigation