Analyzed the data: NM TN. Wrote the paper: NM TN. Review: PF MJ BBM GS ER. Interpretation of results: NM TN PF MJ BBM GS ER. Commented on the analysis and interpretation of the findings: CCD KO AO AT FCC MCBR AR RK BT HB MMB AT DT PL DP VP SP RT PV PS FvD PHMP AH DE CAG MJS MD CN EA JRQ ES UE LN RP KTK NW TJK FLC VF PAW SCC. Approved the manuscript: CCD KO AO AT FCC MCBR AR RK BT HB MMB AT DT PL DP VP SP RT PV PS FvD PHMP AH DE CAG MJS MD CN EA JRQ ES UE LN RP KTK NW TJK FLC VF PAW SCC.
The authors have declared that no competing interests exist.
Earlier analyses within the EPIC study showed that dietary fibre intake was inversely associated with colorectal cancer risk, but results from some large cohort studies do not support this finding. We explored whether the association remained after longer follow-up with a near threefold increase in colorectal cancer cases, and if the association varied by gender and tumour location.
After a mean follow-up of 11.0 years, 4,517 incident cases of colorectal cancer were documented. Total, cereal, fruit, and vegetable fibre intakes were estimated from dietary questionnaires at baseline. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models stratified by age, sex, and centre, and adjusted for total energy intake, body mass index, physical activity, smoking, education, menopausal status, hormone replacement therapy, oral contraceptive use, and intakes of alcohol, folate, red and processed meats, and calcium. After multivariable adjustments, total dietary fibre was inversely associated with colorectal cancer (HR per 10 g/day increase in fibre 0.87, 95% CI: 0.79–0.96). Similar linear associations were observed for colon and rectal cancers. The association between total dietary fibre and risk of colorectal cancer risk did not differ by age, sex, or anthropometric, lifestyle, and dietary variables. Fibre from cereals and fibre from fruit and vegetables were similarly associated with colon cancer; but for rectal cancer, the inverse association was only evident for fibre from cereals.
Our results strengthen the evidence for the role of high dietary fibre intake in colorectal cancer prevention.
A possible protective association between dietary fibre intake and colorectal cancer was first proposed by Burkitt in 1971.
Differing adjustments for colorectal cancer risk factors which may confound the dietary fibre relationship (such as dietary folate) has been proposed as a possible explanation for the variable results observed between studies.
EPIC is an ongoing multicentre prospective cohort study designed to investigate the associations between diet, lifestyle, genetic and environmental factors and various types of cancer. A detailed description of the methods has previously been published.
Dietary information over the previous 12 months was obtained at study baseline using country/centre specific dietary questionnaires. The relative validity and reproducibility of the questionnaires has previously been published.
Lifestyle questionnaires were used to obtain information on education (used as a proxy for socioeconomic status), smoking status and intensity, alcohol consumption, physical activity levels, oral contraceptive use, menopausal status, and menopausal hormone use. Height and weight were measured at the baseline examination in all centres apart from part of Oxford and all of the France and Norway sub-cohorts, where measurements were self reported via the lifestyle questionnaire.
Population cancer registries were used in Denmark, Italy, the Netherlands, Norway, Spain, Sweden and the United Kingdom to identify incident cancers. In France, Germany and Greece cancer cases were identified through active follow-up, directly through study participants or next of kin, and confirmed by a combination of methods including health insurance records, and cancer and pathology registries. Loss to follow-up across all countries was low (<2%). Complete follow-up censoring dates varied amongst centres, ranging between 2005 and 2010.
Cancer incidence data were coded in accordance with the 10th Revision of the International Classification of Diseases (ICD-10) and the second revision of the International Classification of Disease for Oncology (ICDO-2). Proximal colon cancer included those within the caecum, appendix, ascending colon, hepatic flexure, transverse colon, and splenic flexure (C18.0–18.5). Distal colon cancer included those within the descending (C18.6) and sigmoid (C18.7) colon. Overlapping (C18.0) and unspecified (C18.9) lesions of the colon were grouped among colon cancers only. Cancer of the rectum included cancer occurring at the rectosigmoid junction (C19) and rectum (C20).
Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. Age was the primary time variable in all models. Time at entry was age at recruitment. Exit time was age at whichever of the following came first: colorectal cancer diagnosis, death, or the date at which follow-up was considered complete in each centre. To control for differing follow-up procedures, questionnaire design, and other differences across centres, models were stratified by study centre. Models were also stratified by sex and age at recruitment in 1-year categories. Possible non-proportionality was assessed using an analysis of Schoenfeld residuals;
Analyses for colorectal, colon, proximal colon, distal colon, and rectal cancers were conducted for both sexes combined and in men and women separately. All models were adjusted for total energy intake (kcal/day; continuous); body mass index (BMI; kg/m2; continuous); physical activity (inactive, moderately inactive, moderately active, active, or missing); smoking status and intensity (never; current, 1–15 cigarettes per day; current, 16–25 cigarettes per day; current, 16+ cigarettes per day; former, quit ≤10 years; former, quit 11–20 years; former, quit 20+ years; current, pipe/cigar/occasional; current/former, missing; or unknown); education level (none/primary school completed, technical/professional school, secondary school, longer education - including university, or unknown); menopausal status (premenopausal, postmenopausal, perimenopausal/unknown menopausal status, or surgical postmenopausal); ever use of oral contraceptives (yes, no, or unknown); ever use of menopausal hormones (yes, no, or unknown); and intakes of alcohol (g/day), folate (µg/day), red and processed meats (g/day), and calcium (mg/day) (all continuous). Possible adjustment for waist circumference instead of BMI was assessed in a subset of the cohort in which measurements were available, but the risk estimates were virtually unchanged; and accordingly, we adjusted for BMI that was available for most participants. We also analysed the association modelling fibre from different food sources (cereal, fruit, and vegetable). These models included the same covariates as detailed above, with additional mutual adjustment for the other fibre sources. Fruit and vegetable fibre intakes were combined to give similar intake categories to the cereal fibre analysis. The relationship between fibre from legumes and colorectal cancer was also assessed, but due to low intakes in the cohort, the results are not shown. In sensitivity analyses, the results were adjusted for total energy using the residual method.
To evaluate whether the total dietary fibre and colorectal cancer relationship varied according to anthropometric, lifestyle, and other dietary variables, we included interaction terms in the model. The statistical significance of the cross-product terms were evaluated using the likelihood ratio test. Interaction terms inputted into the statistical model were fibre intake (continuous; per 10 g/day) with age at recruitment (<55 years, 55 to 65 years, or >65 years); BMI (underweight = <18.5 kg/m2; normal = 18.5 to <25 kg m2; overweight = 25.0 to <30 kg/m2; or obese = ≥30 kg/m2); waist circumference, using categories from a previous EPIC analysis on anthropometry and colorectal cancer
Cox proportional hazard restricted cubic spline models were used to explore possible deviation from non-linear associations, with five knots specified at the median of each fibre intake quintile.
To improve comparability of data across study centres and to partially correct the relative risk estimates for the measurement error of dietary intakes, a linear regression calibration model was used utilising the 24-hdr taken at baseline from a subset of the cohort (n = 34,436 in this analysis).
Statistical tests used in the analysis were all two-sided and a
After a mean follow-up of 11.0±2.8 years, 4,517 colorectal cancer cases were documented amongst the 477,312 participants. Of the 4,517 colorectal cancers, 2,869 were colon (1,266 distal; 1,298 proximal; and 305 overlapping or unspecified), and 1,648 were rectal cancers. The total person-years and distribution of colorectal cancer cases by country are shown in
Number of participants | Total person-years | Number of colorectalcancer cases | Total dietary fibre intake(g/day) |
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Country | Men | Women | Men | Women | Men | Women | Men | Women |
France | – | 67,385 | – | 699,360 | – | 423 | – | 20.0 (8.7) |
Italy | 14,029 | 30,512 | 158,917 | 341,489 | 173 | 245 | 25.5 (10.7) | 19.6 (8.9) |
Spain | 15,148 | 24,854 | 182,965 | 299,617 | 185 | 144 | 26.1 (12.7) | 20.7 (11.1) |
United Kingdom | 22,852 | 52,543 | 252,096 | 586,301 | 324 | 404 | 23.3 (10.3) | 19.4 (9.3) |
The Netherlands | 9,639 | 26,866 | 115,570 | 315,683 | 82 | 305 | 25.1 (11.5) | 21.3 (8.7) |
Greece | 10,807 | 15,225 | 99,108 | 148,604 | 61 | 44 | 23.9 (14.8) | 17.6 (10.4) |
Germany | 21,172 | 27,411 | 208,509 | 272,105 | 265 | 172 | 23.0 (10.2) | 20.4 (8.8) |
Sweden | 22,309 | 26,375 | 289,623 | 349,308 | 339 | 313 | 19.3 (8.5) | 16.7 (6.9) |
Denmark | 26,294 | 28,722 | 284,721 | 316,745 | 475 | 353 | 26.0 (11.0) | 23.1 (9.8) |
Norway | – | 35,169 | – | 342,279 | – | 210 | – | 19.1 (8.3) |
All EPIC | 142,250 | 335,062 | 1,591,508 | 3,671,490 | 1,904 | 2,613 | 23.7 (11.4) | 19.8 (9.1) |
Data are mean and (SD) of dietary fibre intake information collected from 24-hour dietary recalls (n = 34,436 participants).
Quintile of dietary fibre intake | Q1 | Q2 | Q3 | Q4 | Q5 | |||||
|
<17.9 | 17.9–<21.0 | 21.0–<23.6 | 23.6–<27.5 | ≥27.5 | |||||
|
<16.4 | 16.4–<20.1 | 20.1–<23.6 | 23.6–<28.5 | ≥28.5 | |||||
|
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|
21,675 | 22,590 | 25,834 | 31,664 | 40,487 | |||||
|
328 | 296 | 392 | 400 | 488 | |||||
51.8 | 10.1 | 51.8 | 10.0 | 52.1 | 10.0 | 52.5 | 10.1 | 52.5 | 10.3 | |
26.4 | 3.7 | 26.6 | 3.6 | 26.6 | 3.6 | 26.7 | 3.6 | 26.3 | 3.7 | |
|
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Longer education inclu. uni. (%) | 21.2 | 23.9 | 25.7 | 26.8 | 31.1 | |||||
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Never (%) | 25.8 | 30.0 | 31.7 | 33.5 | 39.0 | |||||
Current (%) | 40.9 | 33.8 | 30.7 | 27.5 | 21.4 | |||||
|
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Active (%) | 21.4 | 22.4 | 23.5 | 24.1 | 27.3 | |||||
2,366 | 681 | 2,423 | 665 | 2,443 | 668 | 2,434 | 654 | 2,386 | 651 | |
116.2 | 59.6 | 108.9 | 54.5 | 103.3 | 53.1 | 96.7 | 52.1 | 81.3 | 55.1 | |
1037 | 384 | 1029 | 342 | 1034 | 330 | 1,043 | 329 | 1,084 | 340 | |
249.1 | 66.3 | 278.8 | 64.7 | 301.2 | 68.6 | 326.8 | 75.1 | 394.4 | 125 | |
30.8 | 32.6 | 24.2 | 24.7 | 20.9 | 21.6 | 18 | 19.2 | 13.9 | 15.7 | |
|
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73,788 | 72,873 | 69,628 | 63,798 | 54,975 | |||||
|
583 | 543 | 559 | 502 | 426 | |||||
50.2 | 9.7 | 50.7 | 9.6 | 51.1 | 9.5 | 51.3 | 9.6 | 50.8 | 10.8 | |
24.7 | 4.4 | 25 | 4.5 | 25.1 | 4.5 | 25.1 | 4.4 | 24.9 | 4.4 | |
|
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Longer education inclu. uni. (%) | 22.0 | 22.1 | 21.9 | 22.3 | 25.4 | |||||
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Never (%) | 49.8 | 55.7 | 57.1 | 57.7 | 59.3 | |||||
Current (%) | 27.8 | 20.8 | 17.9 | 16.1 | 12.6 | |||||
|
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Active (%) | 11.6 | 12.0 | 13.2 | 15.1 | 19.3 | |||||
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Yes % | 58.9 | 56.8 | 56.5 | 56.7 | 57.2 | |||||
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Yes (%) | 22.5 | 23.3 | 24.7 | 25.9 | 25.5 | |||||
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Postmenopausal (%) | 39.9 | 41.2 | 44.2 | 45.9 | 46.2 | |||||
1920 | 561 | 1961 | 549 | 1950 | 538 | 1926 | 522 | 1890 | 520 | |
78.4 | 41.2 | 71.4 | 37.5 | 67.1 | 37.1 | 61.5 | 37.5 | 46.5 | 38.2 | |
979 | 342 | 956 | 296 | 960 | 295 | 978 | 301 | 1023 | 310 | |
244.3 | 66.3 | 278 | 67.9 | 301 | 75.8 | 329 | 87.8 | 406 | 138 | |
11.6 | 15.8 | 8.4 | 11.5 | 7.0 | 9.9 | 6.2 | 8.8 | 5.3 | 7.8 |
Mean and standard deviation.
Food and nutrient intakes were sourced from dietary questionnaires and are adjusted for total energy unless stated otherwise.
For colorectal cancer, higher total dietary fibre intake was associated with a statistically significantly reduced risk in the basic model which was adjusted for total energy intake, and stratified by age, sex, and centre (Q5 vs.Q1, HR 0.76, 95% CI: 0.68–0.85,
Quintile of total fibre intake | Uncalibrated | Calibrated | ||||||||||
Fibre intake range (g/day) | 1 | 2 | 3 | 4 | 5 | HR (95% CI)per 10 g/dayincrease | HR (95% CI)per 10 g/dayincrease | |||||
<16.4 | 16.4–<20.1 | 20.1–<23.6 | 23.6–<28.5 | ≥28.5 | ||||||||
|
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931 | 918 | 912 | 914 | 842 | ||||||||
Basic |
1.00 | 0.95 (0.87–1.04) | 0.91 (0.83–1.01) | 0.88 (0.80–0.98) | 0.76 (0.68–0.85) | <0.001 | ||||||
Multivariable |
1.00 | 0.98 (0.89–1.08) | 0.96 (0.86–1.06) | 0.94 (0.84–1.05) | 0.83 (0.72–0.96) | 0.013 | 0.90 (0.84–0.96) | 0.87 (0.79–0.96) | ||||
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611 | 582 | 586 | 571 | 519 | ||||||||
Basic |
1.00 | 0.93 (0.82–1.04) | 0.91 (0.80–1.03) | 0.86 (0.76–0.98) | 0.74 (0.64–0.86) | <0.001 | ||||||
Multivariable |
1.00 | 0.94 (0.84–1.06) | 0.94 (0.83–1.07) | 0.91 (0.79–1.04) | 0.80 (0.67–0.95) | 0.017 | 0.89 (0.81–0.97) | 0.88 (0.80–0.97) | ||||
|
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267 | 250 | 290 | 244 | 247 | ||||||||
Basic |
1.00 | 0.93 (0.78–1.11) | 1.06 (0.89–1.26) | 0.89 (0.73–1.08) | 0.86 (0.69–1.07) | 0.16 | ||||||
Multivariable |
1.00 | 0.95 (0.79–1.14) | 1.10 (0.91–1.33) | 0.93 (0.75–1.15) | 0.92 (0.71–1.20) | 0.51 | 0.91 (0.80–1.03) | 0.83 (0.75–0.92) | ||||
|
||||||||||||
286 | 262 | 241 | 263 | 214 | ||||||||
Basic |
1.00 | 0.88 (0.74–1.05) | 0.80 (0.66–0.95) | 0.84 (0.69–1.01) | 0.65 (0.52–0.82) | <0.001 | ||||||
Multivariable |
1.00 | 0.90 (0.75–1.07) | 0.83 (0.68–1.00) | 0.88 (0.71–1.09) | 0.70 (0.53–0.92) | 0.021 | 0.88 (0.77–1.00) | 0.98 (0.88–1.08) | ||||
|
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320 | 336 | 326 | 343 | 323 | ||||||||
Basic |
1.00 | 1.00 (0.85–1.17) | 0.92 (0.79–1.09) | 0.92 (0.78–1.09) | 0.79 (0.65–0.96) | 0.012 | ||||||
Multivariable |
1.00 | 1.04 (0.88–1.22) | 0.99 (0.83–1.17) | 1.00 (0.83–1.21) | 0.90 (0.72–1.14) | 0.34 | 0.92 (0.82–1.02) | 0.87 (0.79–0.96) |
Basic model - Cox regression using total energy intake (continuous), and stratified by age (1-year categories), sex, and centre.
Multivariable model - Cox regression using total energy intake (continuous), body mass index (continuous), physical activity index (inactive, moderately inactive, moderately active, active, or missing), smoking status and intensity (never; current, 1–15 cigarettes per day; current, 16–25 cigarettes per day; current, 16+ cigarettes per day; former, quit ≤10 years; former, quit 11–20 years; former, quit 20+ years; current, pipe/cigar/occasional; current/former, missing; unknown), education status (none, primary school completed, technical/professional school, secondary school, longer education including university, or not specified), ever use of contraceptive pill (yes, no, or unknown), ever use of menopausal hormone therapy (yes, no, or unknown), menopausal status (premenopausal, postmenopausal, perimenopausal/unknown menopausal status, or surgical postmenopausal), and intakes of alcohol, folate, red and processed meat, and calcium (all continuous), and stratified by age (1-year categories), sex, and centre.
No significant heterogeneity was seen for the associations between total dietary fibre with colon and rectal cancers (
Hazard ratios were estimated by Cox proportional hazard models adjusted for total energy intake (continuous), body mass index (continuous), physical activity index (inactive, moderately inactive, moderately active, active, or missing), smoking status and intensity (never; current, 1–15 cigarettes per day; current, 16–25 cigarettes per day; current, 16+ cigarettes per day; former, quit ≤10 years; former, quit 11–20 years; former, quit 20+ years; current, pipe/cigar/occasional; current/former, missing; unknown), education status (none, primary school completed, technical/professional school, secondary school, longer education including university, or not specified), ever use of contraceptive pill (yes, no, or unknown), ever use of menopausal hormone therapy (yes, no, or unknown), menopausal status (premenopausal, postmenopausal, perimenopausal/unknown menopausal status, or surgical postmenopausal), and intakes of alcohol, folate, red and processed meat, and calcium (all continuous), and stratified by age (1-year categories), sex, and centre. *Uncalibrated model shown.
In analyses by fibre food source and colorectal cancer risk - after mutual adjustment for fibre from the other food sources - inverse associations were observed for cereal fibre (HR per 10 g/day 0.89; 95% CI 0.82–0.97), and for fibre from fruits and vegetables combined (HR per 10 g/day 0.91; 95% CI 0.83–1.00) (
Quintile of fibre intake | ||||||||
1 | 2 | 3 | 4 | 5 |
|
|||
Cereal fibre (g/day) | <4.64 | 4.64–<6.72 | 6.72–<8.97 | 8.97–<12.3 | ≥12.3 | HR (95% CI) per 10 g/day increase | ||
Colorectum | 857 | 921 | 972 | 918 | 849 | |||
Basic | 1.00 | 1.06 (0.96–1.16) | 1.05 (0.95–1.16) | 0.95 (0.85–1.05) | 0.83 (0.73–0.93) | <0.001 | ||
Multivariable | 1.00 | 1.07 (0.97–1.17) | 1.07 (0.96–1.18) | 0.97 (0.87–1.09) | 0.87 (0.77–0.99) | 0.003 | 0.89 (0.82–0.97) | |
Colon | 550 | 613 | 608 | 572 | 526 | |||
Basic | 1.00 | 1.03 (0.91–1.16) | 1.05 (0.93–1.18) | 0.91 (0.80–1.04) | 0.86 (0.74–0.99) | 0.006 | ||
Multivariable | 1.00 | 1.03 (0.92–1.17) | 1.06 (0.93–1.20) | 0.92 (0.81–1.06) | 0.88 (0.76–1.03) | 0.032 | 0.89 (0.80–0.99) | |
Rectum | 307 | 308 | 364 | 346 | 323 | |||
Basic | 1.00 | 1.11 (0.94–1.31) | 1.05 (0.88–1.24) | 1.01 (0.85–1.21) | 0.78 (0.64–0.95) | 0.001 | ||
Multivariable | 1.00 | 1.13 (0.96–1.34) | 1.08 (0.91–1.29) | 1.07 (0.89–1.28) | 0.86 (0.70–1.06) | 0.031 | 0.89 (0.78–1.01) | |
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Colorectum | 969 | 993 | 904 | 849 | 775 | |||
Basic | 1.00 | 1.02 (0.93–1.12) | 0.94 (0.86–1.04) | 0.92 (0.83–1.02) | 0.90 (0.80–1.00) | 0.016 | ||
Multivariable | 1.00 | 1.05 (0.95–1.15) | 0.98 (0.89–1.09) | 0.96 (0.86–1.08) | 0.94 (0.82–1.07) | 0.19 | 0.91 (0.83–1.00) | |
Colon | 623 | 616 | 555 | 558 | 501 | |||
Basic | 1.00 | 0.95 (0.84–1.06) | 0.84 (0.75–0.95) | 0.86 (0.76–0.97) | 0.81 (0.70–0.93) | 0.002 | ||
Multivariable | 1.00 | 0.97 (0.86–1.09) | 0.87 (0.77–0.99) | 0.89 (0.77–1.02) | 0.83 (0.70–0.98) | 0.022 | 0.89 (0.79–0.99) | |
Rectum | 346 | 377 | 349 | 291 | 274 | |||
Basic | 1.00 | 1.15 (0.99–1.34) | 1.14 (0.98–1.34) | 1.04 (0.88–1.23) | 1.08 (0.89–1.29) | 0.89 | ||
Multivariable | 1.00 | 1.19 (1.02–1.39) | 1.21 (1.03–1.42) | 1.11 (0.92–1.33) | 1.17 (0.94–1.45) | 0.40 | 0.96 (0.82–1.12) |
Basic model - Cox regression using total energy intake (continuous), and stratified by age (1-year categories), sex, and centre.
Multivariable model - Cox regression using total energy intake (continuous), body mass index (continuous), physical activity index (inactive, moderately inactive, moderately active, active, or missing), smoking status and intensity (never; current, 1–15 cigarettes per day; current, 16–25 cigarettes per day; current, 16+ cigarettes per day; former, quit ≤10 years; former, quit 11–20 years; former, quit 20+ years; current, pipe/cigar/occasional; current/former, missing; unknown), education status (none, primary school completed, technical/professional school, secondary school, longer education including university, or not specified), ever use of contraceptive pill (yes, no, or unknown), ever use of menopausal hormone therapy (yes, no, or unknown), menopausal status (premenopausal, postmenopausal, perimenopausal/unknown menopausal status, or surgical postmenopausal), and intakes of alcohol, folate, red and processed meat, calcium, and mutual adjustment for fibre from other sources (all continuous), and stratified by age (1-year categories), sex, and centre.
This analysis of the EPIC cohort, after a longer term follow-up of 11 years in which 4,517 cases accrued, further strengthens the evidence that dietary fibre is inversely associated with colorectal cancer risk. The inverse association of total fibre with colorectal cancer risk was of similar magnitude in men and women, and for colon and rectal cancers. No strong evidence of different associations across the distal and proximal regions of the colon was observed. These results support our previous conclusion, of the potential of reducing colorectal cancer incidence by increasing fibre intake from cereal, fruit, and vegetable food sources.
The association of total fibre intake with colorectal cancer has been observed in several prospective studies.
The extent to which confounding variables inter-relate and influence the fibre-colorectal cancer relationship may vary between studies. These differences impact on study risk estimates and could explain some of the disparities in results. However, the magnitude of the risk estimate changes between the least adjusted and multivariable adjusted models in our analysis and the Pooling Project analysis are similar, therefore differences in adjustment strategies are unlikely to explain the difference in results. Although residual confounding cannot be discounted, interaction analyses and models with different levels of adjustment revealed limited evidence that our inverse associations were caused by this. We observed non-significant interactions for BMI, waist circumference, age at recruitment, smoking, educational level attained, physical activity level, and intakes of alcohol, red and processed meat, calcium, and folate.
Dietary measurement error could also account for the lack of associations observed in some studies. This may cause modest dietary associations to be attenuated towards the null.
In our previous analyses, the inverse associations were not attributable to fibre from a particular source.
A limitation of our study is that diet was only assessed at baseline, and that any potential dietary changes during follow-up are unaccounted for. However, the consistency of the inverse association of fibre intake with colorectal cancer risk observed throughout the duration of follow-up indicates that regression dilution is unlikely to have impacted upon our results. Strengths of our study include its large-scale prospective design, the large number of colorectal cancer cases, the possibility of controlling for the main potential confounders, and the partial correction for the effect of dietary assessment measurement error through regression calibration.
In conclusion, after 11 years of follow-up, this analysis of EPIC data confirmed the inverse associations between dietary fibre intake and colorectal cancer. These results strengthen the evidence for the recommendation of increasing the consumption of fibre rich foods for colorectal cancer prevention.
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We thank the European Prospective Investigation on Cancer and Nutrition (The EPIC project: