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.

Processed meat intake and incidence of colorectal cancer: a systematic review and meta-analysis of prospective observational studies

Abstract

The objective was to use accumulated evidence to explore the association between processed meat intake and risk of colorectal cancer (CRC) and to investigate the reliability of associations by evaluating patterns of risk by study population characteristics and research quality parameters. We included 29 observational prospective cohort studies with relative risk estimates and 95% confidence intervals for CRC according to various levels of processed meat consumption. Risk of bias was assessed using Risk Of Bias In Non-randomized Studies—of Interventions (ROBINS-I) tool. Data sources were PubMed and Embase up to January 2017. The summary relative risks for high versus low processed meat consumption and risk of CRC, colon, and rectal cancer were 1.13 (95% CI: 1.01, 1.26), 1.19 (95% CI: 1.09, 1.31), and 1.21 (95% CI: 0.98, 1.49), respectively. Similar estimates were observed for the dose-response analyses. Heterogeneity across studies was detected in most analytical models. The overall judgment showed that two out of 29 studies had a moderate risk of bias, 25 had a serious risk of bias, and 2 had a critical risk of bias. The bias domains most often rated critical were bias due to risk of confounding, bias due to missing data, and selective outcome reporting bias. Although this meta-analysis indicates a modest association between processed meat intake and an increased risk of CRC, our assessment of internal validity warrants a cautious interpretation of these results, as most of the included studies were judged to have serious or critical risks of bias.

Introduction

Globally, colorectal cancer (CRC) is the third most common cancer type among men and second most common type among women, with a total of 1.36 million incident cases and ~694,000 deaths per year [1]. Many modifiable risk factors for CRC have been identified; especially low physical activity level, overweight or obese status, low fiber intake, high alcohol consumption, and tobacco smoking have been shown to have adverse effect on risk of CRC [2,3,4,5]. Recently, the International Agency for Research on Cancer (IARC) concluded that there is sufficient evidence to support that consumption of processed meat causes CRC [6]. This conclusion is echoed in multiple previously published meta-analyses [7,8,9,10,11,12,13,14,15]. More recently, the World Cancer Research Fund, which included some of the same members from the IARC working group, also reported that processed meat intake was associated with an increased risk of CRC (dose-response RR for 50 g/day increment: 1.18, 95% confidence interval (CI): 1.10, 1.28) [16]. However, the summary results seem to vary by cancer site, sex, and country of origin [7,8,9,10, 12, 13, 17], which likely reflects differences in cultural and lifestyle factors. In addition, the reliability and validity of the results due to limitations in study quality may impact the associations reported across the literature.

Due to the several methodological inconsistencies (e.g., various definitions of processed meat) and methodological limitations in many of the previously published meta-analyses, such as not registering study protocol a priori [7, 8, 10,11,12,13,14,15], lack of transparency regarding duplicate study selection and data extraction [7, 8, 10,11,12,13,14], lack of a comprehensive literature search [7,8,9, 11,12,13], lack of risk of bias assessment of the primary studies in a systematic manner [7,8,9,10,11,12,13,14], or lack of quality assessment in the formulation of the conclusion [7,8,9,10,11,12,13,14,15], it is important to quantitatively assess the association between intake of processed meat and the risk of CRC from the available evidence by following the methodological standards from the Cochrane Collaboration and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [18].

On this background, the objective of the present systematic review and meta-analysis was to update the evidence [7,8,9,10,11,12,13] on the association between processed meat intake and risk of CRC and investigate whether the internal validity based on a quality assessment of the included primary prospective cohort studies modified the reported main associations. Furthermore, the objective was to explore whether the reported results varied by cancer site, sex, or country of origin of the study population.

Methods

We performed a systematic review and meta-analysis of results from prospective cohort studies that reported data on the association between processed meat intake and risk of developing CRC. This work was performed in accordance with the guidelines of the Cochrane Collaboration and PRISMA [18]. The study protocol was prespecified and registered in advance in PROSPERO (CRD42017054499). The literature search, selection of studies for inclusion, data extraction, and quality assessment were performed independently by two reviewers (MNH, JFR). Disagreements were resolved either by discussion or by consulting a third reviewer (BLH).

Search strategy

An electronic literature search was performed using MEDLINE via PubMed and Embase via Ovid. The search strategy was conducted using medical subject heading and text words related to population, exposure, and outcome. The following keywords were used: “meat,” and terms for CRC (“colon,” “rectal,” “colorectal,” “sigmoid,” “transverse.” The search was limited to title/abstract, human, adults (≥18 years), and publication date between April 1, 2011 and January 5, 2017. The search strategy is presented in Supplementary Table 1. Screening the reference lists of included studies supplemented the electronic database search to identify additional potential publications. For the study protocol, we identified bibliographies of eight meta-analyses pertaining to processed meat consumption and CRC, and these were examined to select eligible cohort studies published prior to April 1, 2011 [7,8,9,10,11,12,13,14].

Selection of studies

The articles identified in our literature search were imported to EndNote X7.4, and duplicates were removed. Selection of studies was performed by, first, selecting relevant articles after screening all titles and abstracts, and second, reviewing the full texts of the articles identified in the first step. Only articles published in English language were considered eligible.

To be considered eligible, studies were required to utilize a prospective cohort design that reported data for the association (relative risk (RR) estimates with corresponding 95% CI) between processed meat intake and incident CRC in otherwise healthy adult human populations. Thus, studies of patient populations with pre-existing diseases, conditions, or metabolic disorders were excluded. Studies published only as abstracts, editorials, or commentaries, as well as case–control studies, cross-sectional surveys, ecologic assessments, case reports, and case series were excluded. Mechanistic studies and experimental animal studies were excluded as well.

Other than separating studies and results within studies by fresh red meat intake versus processed meat intake (which is the focus of this review), we did not base study inclusion on restrictive definitions for processed meat because of the between-study variability in how processed meat is defined. Typically, processed meat is defined as red or white meat that has undergone some form of preservation or processing (e.g. smoking, fermentation, salting, baking, sterilization), and studies were considered eligible if they used the term “processed meat” and/or were referring to common processed meat items such as bacon, ham, sausages, cold cuts or luncheon meats, cured meat, minced meat, hamburgers, as well as some country-specific products (e.g. blood pudding in Sweden).

Data extraction

Relevant information from the included studies was extracted using a predefined data extraction template developed for this systematic review and meta-analysis. From each identified article, we extracted the first author’s name, publication year, study cohort and region, sex and age of the study population, number of cases and noncases, years of follow-up, person years for the population, dietary assessment method, portion size, cancer site(s) investigated, percentiles or categories, and the risk estimates and corresponding 95% CI for each category of processed meat intake and covariates. Furthermore, RR estimates from the most fully adjusted multivariable models were extracted. We also extracted information on funding and conflict of interest of the included studies. Finally, we extracted the definition of processed meat and created a matrix to capture the heterogeneity of the definitions across studies.

Critical appraisal of the individual studies

A quality assessment was undertaken using Cochrane's Risk Of Bias In Non-randomized Studies—of Interventions (ROBINS-I) assessment tool [19]. This instrument is tailored to evaluate the internal validity of nonrandomized studies by assessing the risk of bias within seven domains using signaling questions: (1) bias due to confounding, (2) bias in selection of participants into study, (3) bias in classification of interventions, (4) bias due to departure from intended interventions, (5) bias due to missing data, (6) bias in measurement of outcomes, and (7) bias in selection of the reported results. To evaluate the first domain (bias due to confounding), the evidence based key confounders that we selected comprised: age, sex, family history of CRC, BMI/overweight, energy intake, alcohol, and smoking [20]. Additional confounders were also considered, such as fiber intake and physical activity [20], but these were optional to be accounted for in the included studies. A conclusion within each domain was reached by categorizing the risk of bias to either low, moderate, serious, or critical.

Statistical methods

The RR estimate (i.e. hazard ratio, rate ratio, risk ratio, or odds ratio) for the highest intake category versus the lowest intake category and their corresponding 95% CI from each eligible study were extracted and subsequently log transformed. Meta-analyses using random effects inverse variance weighted averages with a moment estimate of between studies variance, separately for CRC, colon, and rectal cancer outcomes were performed, with the extent of inconsistency (statistical heterogeneity) evaluated using I2 statistics.

For the independent variable, all units of processed meat intake were rescaled into g/day. Like previous systematic reviews [9, 21,22,23], we defined portion sizes and servings per day as 50 g/day. When median intake of processed meat was not reported in the categories, the midpoint of each intake category was used. Also, when the highest or lowest intake category was open-ended, we used the half-way point of the width of the adjacent close-ended category to estimate midpoints.

When multiple publications were available from the same cohort, we only considered the most recent publication for the meta-analysis, except for the studies being part of the EPIC study, where the combined results from the separate cohorts were prioritized [15, 16].

In the linear dose-response analysis we combined (log-) hazard ratios per 50 g/day increase in intake. The dose-response estimates were either reported in the studies or computed from the categorical data by using the method of generalized least squares for trend estimation proposed by Greenland et al. [24,25,26]. The primary meta-analysis models consisted of data from cohort studies of specific cancer sites (colorectal, colon [total only], rectal), men and women combined, and region of study origin combined. In one study, the results were stratified according to family history of CRC [27], and here the estimates of sporadic CRC were selected for the present synthesis.

Studies reporting hazard ratios separately for men and women were considered as independent studies (or units) for the meta-analysis. The analyses and forest plots were produced in Stata SE version 13.1 (StatCorp LP).

Post hoc analyses were performed to explore the robustness of the findings using meta-regression analyses to examine the association between sex and study geographical region and log(HR) for the outcomes (CRC, colon, and rectal cancer), separately, using a random effects model and reporting the regression coefficient and 95% CI.

Results

Literature search

Through the literature search for the period April 1, 2011 and January 5, 2017, we identified 1387 records after removing duplicates. Screening of titles and abstracts lead to the exclusion of 1246 records. Additional duplicate articles (k = 99) were excluded as well. Forty-two articles remained eligible for the full-text assessment. At this stage, we further excluded 37 articles. A complete list of reasons for exclusion is given in Supplementary Table 2. In total, we identified seven eligible prospective cohort studies through this updated literature search. From the bibliographies of the eight meta-analyses pertaining to processed meat consumption and CRC, we identified 22 eligible studies published before April 1, 2011, leaving us with 29 eligible studies for the present systematic review [27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55], of which a total of 17 represented nonoverlapping independent study populations.

Fifteen of the seventeen studies were eligible for the dose-response meta-analysis, since two studies were excluded from the meta-analysis due to insufficient reporting on the intake of processed meat [34, 50]. The flow of information through the different phases of the systematic review is presented in Fig. 1.

Fig. 1
figure1

Flowchart of literature search and selection of studies.

Cohort study characteristics

Among the study populations from included studies, 13 were from the United States (US) [27,28,29,30,31,32,33,34,35,36,37,38,39], 11 were from Europe [40,41,42,43,44,45,46,47,48,49,50], 4 were from Asia [51,52,53,54], and 1 was from Australia [55] (Table 1). The publication year ranged from 1990 to 2015. All studies used validated food frequency questionnaires (FFQ) to ascertain dietary information. The most common classification of processed meat was as a food group, defined either by referring to preservation methodology [40, 41, 43, 47, 54], by listing individual food items [28, 30,31,32,33,34, 42, 45, 46, 48, 51, 55] or with no further definition [29, 35,36,37,38,39, 44, 49, 53] (Supplementary Table 3). The extent of covariate adjustment varied between the studies. Only five studies adjusted for all the preselected key covariates (age, sex, family history of CRC, BMI/overweight, energy intake, alcohol, and smoking) [31, 35,36,37, 46]. Only two of those adjusted for fiber and physical activity [35, 36]. Among all the included studies, only ten studies adjusted for socioeconomic status (education) [30, 31, 34, 37, 42, 43, 45, 49, 52, 54].

Table 1 Summary of prospective cohort studies on processed meat consumption and colorectal cancer.

Risk of bias within the studies

Risk of bias for each study across each of the seven risk of bias domains were assessed, and the results are shown in Table 2. As none of the studies were intervention studies all studies had a moderate rather than low risk based on this first of the seven risk domains. Furthermore, the majority of the studies ended up being graded with an overall serious risk of bias, suggesting that these studies have some important limitations, mainly due to lack of appropriate control for confounding [27,28,29,30, 32,33,34,35,36,37,38, 40,41,42,43,44,45, 47,48,49,50,51,52,53, 55]. Cross et al. [31] and Lin et al. [46] were the only two studies that were graded with an overall moderate risk of bias, indicating that these two studies were sound for a cohort study. Finally, two studies were graded with an overall critical risk of bias [39, 54], indicating that these studies suffered from severe methodological limitations, and were not deemed suitable to provide valid results, and thus, should be excluded from any synthesis.

Table 2 Summary table of the risk of bias using ROBINS-I.

The majority of the studies did not state whether there were competing interest in relation to conflict of interest [29, 30, 32,33,34, 38,39,40,41, 44,45,46,47, 50, 54, 55] (Supplementary Table 4).

Syntheses of results

Overall, nine studies were included in the model of high versus low intake of processed meat [32, 36, 43, 45,46,47, 49, 52, 55], resulting in a summary risk estimate for CRC of 1.13 (95% CI: 1.01, 1.26) with moderate heterogeneity (I2: 30.5%) (Fig. 2).

Fig. 2
figure2

Forrest plot of hazard ratio of colorectal, colon, and rectal cancer with high versus low processed meat intake.

High intake of processed meat was also associated with colon cancer risk (Colon, HR: 1.19; 95% CI: 1.09, 1.31) with low heterogeneity (I2: 0%). For rectal cancer, the summary estimate was similar to that of colon cancer, but the association was not significant (Rectal, HR: 1.21; 95% CI: 0.98, 1.49), and the model had moderate heterogeneity (I2: 47.2%) (Fig. 2). Similar results were seen in the dose-response analyses (CRC, HR per 50 g/day increase: 1.15; 95% CI: 1.06, 1.24; Colon, HR per 50 g/day increase: 1.25; 95% CI: 1.15, 1.37; Rectal HR per 50 g/day increase: 1.18; 95% CI: 1.04, 1.33; k = 10) (Fig. 3).

Fig. 3
figure3

Forrest plot of hazard ratio of colorectal, colon and, rectal cancer with 50 g/day increase in processed meat intake.

In the stratified analyses of the association between processed meat intake and the risk of developing CRC, association were neither significant among women (CRC, HR per 50 g/day increment: 1.06; 95% CI: 0.82, 1.35) or men (CRC, HR per 50 g/day increment: 1.05; 95% CI: 0.86, 1.27). Moreover, sub-group analyses of data from studies conducted in European study populations indicated an association (CRC, HR per 50 g/day increment: 1.15; 95% CI: 1.05, 1.26), but not in study populations from Asian-Pacific regions (CRC, HR per 50 g/day increment: 1.20; 95% CI: 0.84, 1.72) or in study populations from studies conducted in the U.S. (CRC, HR per 50 g/day increment: 1.14; 95% CI: 0.93, 1.39) (Table 3). However, post hoc analyses showed that neither sex nor study geographical region was significantly associated with the risk of CRC (Supplementary Table 5).

Table 3 Summary of the dose-response meta-analysis per 50 g/day increment.

The summary association was significant between processed meat intake and the risk of developing colon cancer among men, (Colon, HR per 50 g/day increment: 1.23; 95% CI: 1.13, 1.34), but not among women (Colon, HR per 50 g/day increment: 1.12; 95% CI: 0.68, 1.83). Analyses of data on colon cancer from studies conducted in Asian-Pacific regions were not significant (Colon, HR per 50 g/day increment: 1.52; 95% CI: 0.89, 2.61), but processed meat was associated with colon cancer in study populations from both Europe (Colon, HR per 50 g/day increment: 1.18; 95% CI: 1.04, 1.34) and the U.S (Colon, HR per 50 g/day increment: 1.27; 95% CI: 1.13, 1.43). However, post hoc analyses showed that neither sex or study geographical region were significantly associated with the risk of colon cancer (Supplementary Table 5).

Processed meat intake was not associated with rectal cancer in either men or women (Men, Rectal, HR per 50 g/day increment: 0.48; 95% CI: 0.13, 1.72; Women, Rectal HR per 50 g/day increment: 0.95; 95% CI: 0.60, 1.51). Significant summary associations on rectal cancer were observed in studies conducted in the U.S. (Rectal HR: 1.25; 95% CI: 1.01, 1.55), but not European study populations (Rectal, HR per 50 g/day increment: 1.17; 95% CI: 0.88, 1.54) or in study populations from Asian-Pacific regions (Rectal HR per 50 g/day increment: 1.29; 95% CI: 0.74, 2.26). However, post hoc analyses showed that neither sex or study geographical region were significantly associated with the risk of rectal cancer (Supplementary Table 5).

From visual inspection of funnel plots, we did not detect evidence of publication bias (Supplementary Fig. 1).

Discussion

In this systematic review of 29 original peer-reviewed prospective cohort studies, we found an increased risk of colorectal and colon cancer, but not of rectal cancer, associated with higher intakes of processed meat in the overall meta-analysis. However, the results stratified by sex and geographic region of the study population varied. Based on our risk of bias assessment, we found that most studies had moderate to critical risk of bias. The heterogeneity in the meta-analyses was moderate to low. Although the stratified analyses showed differences in results related to differences in sex and study geographical region, the meta-regression did not confirm this, but this may be due to the limited ability to detect sources of heterogeneity, when only few studies are included in the analyses (k = 9–12).

It cannot be excluded that the size of found associations were overestimated, due to risk of bias in confounding, risk of bias due to missing data, and selective outcome reporting bias. Furthermore, the differences in the processed meat definition across studies may also have contributed to the observed heterogeneity. However, meta-regression could not be performed to confirm this, due to lack of appropriate differentially reporting of data.

The finding of the associations between processed meat and risk of CRC is in line with the recent expert reports from AICR and WCRF, along with the previous reported systematic reviews and meta-analyses [6,7,8,9,10,11,12,13,14,15,16]. However, only one other review has, to our knowledge, systematically assessed the risk of bias for each of the included studies [15]. This previous review also concluded that the quality of the included original studies was low, but the authors did not further present the methodological issues related to the included studies. The results of our risk of bias assessment highlighted some methodological challenges within and between the studies, especially in relation to confounding. The evaluation of risk of bias due to confounding in ROBINS-I is based on a prespecified listing of the confounding domains that are relevant to all or most of the studies eligible for the review.

The studies all used validated FFQ, and most studies used medical registries to ascertain CRC outcome(s). However, the various limitations listed below should be taken into consideration when evaluating results. It is commonly known that FFQ administered in prospective studies are subject to measurement error that can result in misclassification of exposure [56, 57]. These errors may be a result of either challenge in recalling the consumption, misreporting, i.e., under and/or over reporting the intake, incomplete food list, incomplete information on portion size, incomplete information on cooking practices, etc. Across the included studies the reported estimated mean intakes of processed meat were generally lower, compared with the mean intake reported in the EPIC study [47], suggesting that underreporting or cultural differences may have been present, and as a consequence, the significant association detected in the original studies, and hence in the present meta-analysis may have been inflated.

Strengths and limitations related to the systematic review

Our systematic review and meta-analysis was performed using transparent methods and a priori defined criteria in accordance with the guidelines of the Cochrane Collaboration and PRISMA [18], including protocol registration and duplicate study selection, data extraction and quality assessment. Nevertheless, it was necessary to exclude several studies for numerous reasons. First, there were many studies with overlapping/updated use of the same cohort material. Second, studies that were graded with a critical risk of bias assessment, were recommended by ROBINS-I to be excluded from any synthesis. Third, some studies could not be included in the meta-analysis, because the exposure measure could not be converted into g/day, for instance when the reporting was dichotomized into a simple yes/no, never/ever, or intake reported without giving a frequency measure [34, 50].

We used ROBINS-I which is specifically developed to assess risk of bias of the results in nonrandomized studies [19]. The tool is based on the Cochrane risk of bias tool for randomized trials and provides a systematic guideline to evaluate the internal validity of each primary observational study. We do, however, acknowledge some limitations in this assessment tool. When using ROBINS-I, we found it challenging to assess the risk of bias due to time-varying exposure(s). If intake was constant, neither the individuals in the highest consumption category, nor the individuals in the lowest consumption category, would change their processed meat intake during the follow-up time. However, other studies have suggested that a dietary pattern including meat seems to have poor stability over time (>7 years) [58, 59], and repeated measurement may be advocated for future studies.

Conclusion

Based on this systematic review and meta-analysis of several large prospective cohort studies with long follow-up, the results suggest that a high consumption of processed meat is associated with increased risk of CRC, and although results vary by sex and study geographical region, neither sex of study geographical region could explain the associations in the meta-regression analyses. However, findings should be interpreted with some caution because our risk of bias tool (ROBINS-I) identified several important areas of methodological bias that may have impacted the results of the primary studies, and therefore also of the meta-result. Indeed, the results may be inflated by bias due to confounding, selection bias, or bias in diet reporting. More high-quality longitudinal observational studies that account for and/or stratify by modifying factors are therefore needed on the subject.

References

  1. 1.

    Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136:E359–86.

    CAS  Article  Google Scholar 

  2. 2.

    Wei EK, Colditz GA, Giovannucci EL, Fuchs CS, Rosner BA. Cumulative risk of colon cancer up to age 70 years by risk factor status using data from the Nurses’ Health Study. Am J Epidemiol. 2009;170:863–72.

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Kirkegaard H, Johnsen NF, Christensen J, Frederiksen K, Overvad K, Tjonneland A. Association of adherence to lifestyle recommendations and risk of colorectal cancer: a prospective Danish cohort study. BMJ. 2010;341:c5504.

    PubMed  PubMed Central  Google Scholar 

  4. 4.

    Liang PS, Chen TY, Giovannucci E. Cigarette smoking and colorectal cancer incidence and mortality: systematic review and meta-analysis. Int J Cancer. 2009;124:2406–15.

    CAS  PubMed  Google Scholar 

  5. 5.

    Fedirko V, Tramacere I, Bagnardi V, Rota M, Scotti L, Islami F, et al. Alcohol drinking and colorectal cancer risk: an overall and dose-response meta-analysis of published studies. Ann Oncol. 2011;22:1958–72.

    CAS  PubMed  Google Scholar 

  6. 6.

    International Agency for Research on Cancer. Red meat and processed meat. ume 114. Lyon, France: IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; 2018. p. 1–502.

    Google Scholar 

  7. 7.

    Larsson SC, Wolk A. Meat consumption and risk of colorectal cancer: a meta-analysis of prospective studies. Int J Cancer. 2006;119:2657–64.

    CAS  PubMed  Google Scholar 

  8. 8.

    Alexander DD, Miller AJ, Cushing CA, Lowe KA. Processed meat and colorectal cancer: a quantitative review of prospective epidemiologic studies. Eur J Cancer Prev. 2010;19:328–41.

    PubMed  Google Scholar 

  9. 9.

    Chan DS, Lau R, Aune D, Vieira R, Greenwood DC, Kampman E, et al. Red and processed meat and colorectal cancer incidence: meta-analysis of prospective studies. PLoS ONE. 2011;6:e20456.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Huxley RR, Ansary-Moghaddam A, Clifton P, Czernichow S, Parr CL, Woodward M. The impact of dietary and lifestyle risk factors on risk of colorectal cancer: a quantitative overview of the epidemiological evidence. Int J Cancer. 2009;125:171–80.

    CAS  PubMed  Google Scholar 

  11. 11.

    Johnson CM, Wei C, Ensor JE, Smolenski DJ, Amos CI, Levin B, et al. Meta-analyses of colorectal cancer risk factors. Cancer Causes Control. 2013;24:1207–22.

    PubMed  PubMed Central  Google Scholar 

  12. 12.

    Norat T, Lukanova A, Ferrari P, Riboli E. Meat consumption and colorectal cancer risk: dose-response meta-analysis of epidemiological studies. Int J Cancer. 2002;98:241–56.

    CAS  PubMed  Google Scholar 

  13. 13.

    Pham NM, Mizoue T, Tanaka K, Tsuji I, Tamakoshi A, Matsuo K, et al. Meat consumption and colorectal cancer risk: an evaluation based on a systematic review of epidemiologic evidence among the Japanese population. Jpn J Clin Oncol. 2014;44:641–50.

    PubMed  Google Scholar 

  14. 14.

    Sandhu MS, White IR, McPherson K. Systematic review of the prospective cohort studies on meat consumption and colorectal cancer risk: a meta-analytical approach. Cancer Epidemiol Biomark Prev. 2001;10:439–46.

    CAS  Google Scholar 

  15. 15.

    Zhao Z, Feng Q, Yin Z, Shuang J, Bai B, Yu P, et al. Red and processed meat consumption and colorectal cancer risk: a systematic review and meta-analysis. Oncotarget. 2017;8:83306–14.

    PubMed  PubMed Central  Google Scholar 

  16. 16.

    Vieira AR, Abar L, Chan DSM, Vingeliene S, Polemiti E, Stevens C, et al. Foods and beverages and colorectal cancer risk: a systematic review and meta-analysis of cohort studies, an update of the evidence of the WCRF-AICR Continuous Update Project. Ann Oncol. 2017;28:1788–802.

    CAS  PubMed  Google Scholar 

  17. 17.

    Li F, Duan F, Zhao X, Song C, Cui S, Dai L. Red meat and processed meat consumption and nasopharyngeal carcinoma risk: a dose-response meta-analysis of observational studies. Nutr Cancer. 2016;68:1034–43.

    CAS  PubMed  Google Scholar 

  18. 18.

    Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4:1.

    PubMed  PubMed Central  Google Scholar 

  19. 19.

    The Risk Of Bias In Non-randomized Studies—of Interventions (ROBINS-I) assessment tool. 2016. https://sitesgooglecom/site/riskofbiastool/.

  20. 20.

    Brenner H, Kloor M, Pox CP. Colorectal cancer. Lancet. 2014;383:1490–502.

    PubMed  Google Scholar 

  21. 21.

    Yang L, Dong J, Jiang S, Shi W, Xu X, Huang H, et al. Red and processed meat consumption increases risk for non-hodgkin lymphoma: a PRISMA-compliant meta-analysis of observational studies. Medicine. 2015;94:e1729.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Wang X, Lin X, Ouyang YY, Liu J, Zhao G, Pan A, et al. Red and processed meat consumption and mortality: dose-response meta-analysis of prospective cohort studies. Public Health Nutr. 2016;19:893–905.

    PubMed  Google Scholar 

  23. 23.

    O’Sullivan TA, Hafekost K, Mitrou F, Lawrence D. Food sources of saturated fat and the association with mortality: a meta-analysis. Am J Public Health. 2013;103:e31–42.

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Orsini N, Bellocco R, Greenland S. Generalized least squares for trend estimation of summarized dose-response data. Stata J. 2006;6:40–57.

    Google Scholar 

  25. 25.

    Greenland S, Longnecker MP. Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. Am J Epidemiol. 1992;135:1301–9.

    CAS  PubMed  Google Scholar 

  26. 26.

    Berlin JA, Longnecker MP, Greenland S. Meta-analysis of epidemiologic dose-response data. Epidemiology. 1993;4:218–28.

    CAS  PubMed  Google Scholar 

  27. 27.

    Sellers TA, Bazyk AE, Bostick RM, Kushi LH, Olson JE, Anderson KE, et al. Diet and risk of colon cancer in a large prospective study of older women: an analysis stratified on family history (Iowa, United States). Cancer Causes Control. 1998;9:357–67.

    CAS  PubMed  Google Scholar 

  28. 28.

    Bernstein AM, Song M, Zhang X, Pan A, Wang M, Fuchs CS, et al. Processed and unprocessed red meat and risk of colorectal cancer: analysis by tumor location and modification by time. PLoS ONE. 2015;10:e0135959.

    PubMed  PubMed Central  Google Scholar 

  29. 29.

    Bostick RM, Potter JD, Kushi LH, Sellers TA, Steinmetz KA, McKenzie DR, et al. Sugar, meat, and fat intake, and non-dietary risk factors for colon cancer incidence in Iowa women (United States). Cancer Causes Control. 1994;5:38–52.

    CAS  PubMed  Google Scholar 

  30. 30.

    Chao A, Thun MJ, Connell CJ, McCullough ML, Jacobs EJ, Flanders WD, et al. Meat consumption and risk of colorectal cancer. J Am Med Assoc. 2005;293:172–82.

    CAS  Google Scholar 

  31. 31.

    Cross AJ, Leitzmann MF, Gail MH, Hollenbeck AR, Schatzkin A, Sinha R. A prospective study of red and processed meat intake in relation to cancer risk. PLoS Med. 2007;4:e325.

    PubMed  PubMed Central  Google Scholar 

  32. 32.

    Flood A, Velie EM, Sinha R, Chaterjee N, Lacey JV Jr., Schairer C, et al. Meat, fat, and their subtypes as risk factors for colorectal cancer in a prospective cohort of women. Am J Epidemiol. 2003;158:59–68.

    PubMed  Google Scholar 

  33. 33.

    Giovannucci E, Rimm EB, Stampfer MJ, Colditz GA, Ascherio A, Willett WC. Intake of fat, meat, and fiber in relation to risk of colon cancer in men. Cancer Res. 1994;54:2390–7.

    CAS  PubMed  Google Scholar 

  34. 34.

    Kato I, Akhmedkhanov A, Koenig K, Toniolo PG, Shore RE, Riboli E. Prospective study of diet and female colorectal cancer: the New York University Women’s Health Study. Nutr Cancer. 1997;28:276–81.

    CAS  PubMed  Google Scholar 

  35. 35.

    Nothlings U, Yamamoto JF, Wilkens LR, Murphy SP, Park SY, Henderson BE, et al. Meat and heterocyclic amine intake, smoking, NAT1 and NAT2 polymorphisms, and colorectal cancer risk in the multiethnic cohort study. Cancer Epidemiol Biomark Prev. 2009;18:2098–106.

    Google Scholar 

  36. 36.

    Ollberding NJ, Wilkens LR, Henderson BE, Kolonel LN, Le ML. Meat consumption, heterocyclic amines and colorectal cancer risk: the Multiethnic Cohort Study. Int J Cancer. 2012;131:E1125–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Ruder EH, Thiebaut AC, Thompson FE, Potischman N, Subar AF, Park Y, et al. Adolescent and mid-life diet: risk of colorectal cancer in the NIH-AARP Diet and Health Study. Am J Clin Nutr. 2011;94:1607–19.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Wei EK, Giovannucci E, Wu K, Rosner B, Fuchs CS, Willett WC, et al. Comparison of risk factors for colon and rectal cancer. Int J Cancer. 2004;108:433–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Willett WC, Stampfer MJ, Colditz GA, Rosner BA, Speizer FE. Relation of meat, fat, and fiber intake to the risk of colon cancer in a prospective study among women. N. Engl J Med. 1990;323:1664–72.

    CAS  PubMed  Google Scholar 

  40. 40.

    Brink M, Weijenberg MP, de Goeij AF, Roemen GM, Lentjes MH, de Bruine AP, et al. Meat consumption and K-ras mutations in sporadic colon and rectal cancer in The Netherlands Cohort Study. Br J Cancer. 2005;92:1310–20.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Balder HF, Vogel J, Jansen MC, Weijenberg MP, van den Brandt PA, Westenbrink S, et al. Heme and chlorophyll intake and risk of colorectal cancer in the Netherlands cohort study. Cancer Epidemiol Biomark Prev. 2006;15:717–25.

    CAS  Google Scholar 

  42. 42.

    Egeberg R, Olsen A, Christensen J, Halkjaer J, Jakobsen MU, Overvad K, et al. Associations between red meat and risks for colon and rectal cancer depend on the type of red meat consumed. J Nutr. 2013;143:464–72.

    CAS  PubMed  Google Scholar 

  43. 43.

    Gilsing AM, Schouten LJ, Goldbohm RA, Dagnelie PC, van den Brandt PA, Weijenberg MP. Vegetarianism, low meat consumption and the risk of colorectal cancer in a population based cohort study. Sci Rep. 2015;5:13484.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Goldbohm RA, van den Brandt PA, van V, Brants HA, Dorant E, Sturmans F, et al. A prospective cohort study on the relation between meat consumption and the risk of colon cancer. Cancer Res. 1994;54:718–23.

    CAS  PubMed  Google Scholar 

  45. 45.

    Larsson SC, Rafter J, Holmberg L, Bergkvist L, Wolk A. Red meat consumption and risk of cancers of the proximal colon, distal colon and rectum: the Swedish Mammography Cohort. Int J Cancer. 2005;113:829–34.

    CAS  PubMed  Google Scholar 

  46. 46.

    Lin J, Zhang SM, Cook NR, Lee IM, Buring JE. Dietary fat and fatty acids and risk of colorectal cancer in women. Am J Epidemiol. 2004;160:1011–22.

    PubMed  Google Scholar 

  47. 47.

    Norat T, Bingham S, Ferrari P, Slimani N, Jenab M, Mazuir M, et al. Meat, fish, and colorectal cancer risk: the European Prospective Investigation into cancer and nutrition. J Natl Cancer Inst. 2005;97:906–16.

    PubMed  PubMed Central  Google Scholar 

  48. 48.

    Parr CL, Hjartaker A, Lund E, Veierod MB. Meat intake, cooking methods and risk of proximal colon, distal colon and rectal cancer: the Norwegian Women and Cancer (NOWAC) cohort study. Int J Cancer. 2013;133:1153–63.

    CAS  PubMed  Google Scholar 

  49. 49.

    Pietinen P, Malila N, Virtanen M, Hartman TJ, Tangrea JA, Albanes D, et al. Diet and risk of colorectal cancer in a cohort of Finnish men. Cancer Causes Control. 1999;10:387–96.

    CAS  PubMed  Google Scholar 

  50. 50.

    Tiemersma EW, Kampman E, Bueno de Mesquita HB, Bunschoten A, van Schothorst EM, Kok FJ, et al. Meat consumption, cigarette smoking, and genetic susceptibility in the etiology of colorectal cancer: results from a Dutch prospective study. Cancer Causes Control. 2002;13:383–93.

    PubMed  Google Scholar 

  51. 51.

    Oba S, Shimizu N, Nagata C, Shimizu H, Kametani M, Takeyama N, et al. The relationship between the consumption of meat, fat, and coffee and the risk of colon cancer: a prospective study in Japan. Cancer Lett. 2006;244:260–7.

    CAS  PubMed  Google Scholar 

  52. 52.

    Sato Y, Nakaya N, Kuriyama S, Nishino Y, Tsubono Y, Tsuji I. Meat consumption and risk of colorectal cancer in Japan: the Miyagi Cohort Study. Eur J Cancer Prev. 2006;15:211–8.

    PubMed  Google Scholar 

  53. 53.

    Takachi R, Tsubono Y, Baba K, Inoue M, Sasazuki S, Iwasaki M, et al. Red meat intake may increase the risk of colon cancer in Japanese, a population with relatively low red meat consumption. Asia Pac J Clin Nutr. 2011;20:603–12.

    CAS  PubMed  Google Scholar 

  54. 54.

    Lee SA, Shu XO, Yang G, Li H, Gao YT, Zheng W. Animal origin foods and colorectal cancer risk: a report from the Shanghai Women’s Health Study. Nutr Cancer. 2009;61:194–205.

    PubMed  PubMed Central  Google Scholar 

  55. 55.

    English DR, MacInnis RJ, Hodge AM, Hopper JL, Haydon AM, Giles GG. Red meat, chicken, and fish consumption and risk of colorectal cancer. Cancer Epidemiol Biomark Prev. 2004;13:1509–14.

    Google Scholar 

  56. 56.

    Moghames P, Hammami N, Hwalla N, Yazbeck N, Shoaib H, Nasreddine L, et al. Validity and reliability of a food frequency questionnaire to estimate dietary intake among Lebanese children. Nutr J. 2016;15:4.

    PubMed  PubMed Central  Google Scholar 

  57. 57.

    Adamson AJ, Collerton J, Davies K, Foster E, Jagger C, Stamp E, et al. Nutrition in advanced age: dietary assessment in the Newcastle 85+ study. Eur J Clin Nutr. 2009;63 Suppl 1 :S6–18.

    PubMed  Google Scholar 

  58. 58.

    Weismayer C, Anderson JG, Wolk A. Changes in the stability of dietary patterns in a study of middle-aged Swedish women. J Nutr. 2006;136:1582–7.

    CAS  PubMed  Google Scholar 

  59. 59.

    Mishra GD, McNaughton SA, Bramwell GD, Wadsworth ME. Longitudinal changes in dietary patterns during adult life. Br J Nutr. 2006;96:735–44.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank Ahmed Saaid for performing Supplementary Table 3, which is indexing the definitions of processed meat types provided by the included studies. Moreover, the authors thank Katrine Rasmussen and Nanna Katrine Andersen for contributing to development of the search strategy.

Funding

The Parker Institute, Bispebjerg and Frederiksberg Hospital is supported by a core grant from the Oak Foundation (OCAY-13-309). MatPrat—the Norwegian consumer organization consulting on meat and egg consumption provided support for MNH, JFR, RJ and DDA. The sources of support had no influence on the content of the manuscript.

Author information

Affiliations

Authors

Contributions

Designed research: MNH, JFR, RJ, RC, PF, BLH. Conducted research: MNH, JR. Provided essential reagents or provided essential materials: MNH, JFR. Analyzed data or performed statistical analysis: MNH, JFR, PF. Wrote paper: MNH with contributions from all authors. Had primary responsibility for final content: MNH

Corresponding author

Correspondence to M. N. Händel.

Ethics declarations

Conflict of interest

MNH, JFR and RJ: Support from MatPrat paid to the Parker Institute; SMN: None; RC: None; DDA: Partial support from MatPrat; PF: None; BLH: None.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Händel, M.N., Rohde, J.F., Jacobsen, R. et al. Processed meat intake and incidence of colorectal cancer: a systematic review and meta-analysis of prospective observational studies. Eur J Clin Nutr 74, 1132–1148 (2020). https://doi.org/10.1038/s41430-020-0576-9

Download citation

Further reading

Search

Quick links