# Do alcoholic beverages, obesity and other nutritional factors modify the risk of familial colorectal cancer? A systematic review.

Anthony Fardet, Nathalie Pecollo, Mathilde Touvier, Paule Latino-Martel

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Anthony Fardet, Nathalie Pecollo, Mathilde Touvier, Paule Latino-Martel. Do alcoholic beverages, obesity and other nutritional factors modify the risk of familial colorectal cancer? A systematic review.. Critical Reviews in Oncology/Hematology, 2017, 119, pp.94-112. 10.1016/j.critrevonc.2017.09.001. hal-01628671

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Submitted on 26 May 2020

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# Do alcoholic beverages, obesity and other nutritional factors modify the risk of familial colorectal cancer? A systematic review

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Anthony Fardetª, Nathalie Druesne-Pecolloᵇ,ᶜ, Mathilde Touvierᵇ,ᶜ, Paule Latino-Martelᵇ,ᶜ,\*

## ARTICLE INFO

**Keywords:**

Colorectal cancer

Family history

Lynch syndrome

Foods

Diet

Alcoholic beverages

Red meat

Processed meat

Physical activity

Dietary patterns

Prevention

## ABSTRACT

**Purpose:** Individuals with family history of colorectal cancer are at higher risk of colorectal cancer than the general population. Until now, guidelines for familial colorectal cancer risk have only pointed at early diagnosis efforts via screening tests and surveillance, and payed scarce or no attention to lowering exposure to modifiable risk factors, notably nutritional factors.

**Methods:** We conducted a systematic review of epidemiological studies investigating the associations between nutritional factors, family history of colorectal cancer, and colorectal cancer risk. From the 5312 abstracts identified until December 2016, 184 full text articles were examined for eligibility. Finally, 31 articles (21 from case-control studies, 9 from cohort studies and 1 from an intervention study) met inclusion criteria and were analyzed.

**Results:** Mainly, the combinations of family history of colorectal cancer and higher consumptions of alcoholic beverages, red or processed meat, or overweight/obesity increase the risk of colorectal cancer. Consistently, a strong increase is observed with the combinations of family history of colorectal cancer and unhealthy dietary patterns/lifestyles. Statistically significant interactions between these nutritional factors, family history of colorectal cancer and colorectal cancer risk are reported. Other data are inconclusive and additional prospective studies are needed.

**Conclusions:** For the first time, our findings highlight that addressing high consumption of alcoholic beverages, red or processed meat, and overweight/obesity, and more largely the exposure to multiple unhealthy dietary/ nutritional behaviors could offer new perspectives of prevention to individuals with family history of colorectal cancer. A better information of these patients and of health professionals on these nutritional modifiable risk factors is recommended.

## 1. Introduction

It is well recognized that subjects with family history (FH) of colorectal cancer (CRC) are at higher risk of CRC (Slattery and Kerber, 1994; Kerber et al., 1998). The overall risk is increased two-fold in subjects with a first-degree relative with CRC, the risk increasing with the number of relatives affected (Potter et al., 1993). Both inherited genetic alterations and acquired lifestyle factors are thought to be involved in such an increased risk but the interaction between them has been quite poorly studied (Keku et al., 2003).

Genetic factors associated with FH of CRC are mainly those

encountered in familial adenomatous polyposis (FAP) and Lynch Syndrome (LS), also known as hereditary nonpolyposis colon cancer (HNPCC). It is estimated that 1–3% of all CRC are due to LS (Aaltonen et al., 1998). The high cancer risk in LS is caused by pathogenic germline mutations in genes involved in or influencing DNA mismatch repair (MMR), i.e., hMLH1, hMSH2, hMSH6, PMS2, or EPCAM (Abdel-Rahman et al., 2006; Ligtenberg et al., 2009). FAP is caused by APC (Adenomatous Polyposis Coli) gene defects on chromosome 5q21, i.e., a flaw in the body's tumor suppressor genes that prevent development of tumors (Cruz-Correa and Giardiello, 2003). FAP accounts for approximately 1% of cases of CRC (Cruz-Correa and Giardiello, 2003).

<footnote>ª INRA, UMR 1019, UNH, CRNH Auvergne, F-63000 Clermont-Ferrand & Clermont University, University of Auvergne, Human Nutrition Unit, BP 10448, F-63000 Clermont-Ferrand, France</footnote>

<footnote>ᵇ Sorbonne Paris Cité Epidemiology and Statistics Research Centre (CRESS), Inserm U1153, Inra U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Bobigny, France</footnote>

<footnote>ᶜ French Network for Nutrition and Cancer Research (NACRe Network), France</footnote>

<footnote>Abbreviations: CC, Colon Cancer; CRC, Colorectal Cancer; FH, Family History; HNPCC, Hereditary Non-Polyposis Colorectal Cancer; LS, Lynch Syndrome</footnote>

<footnote>\* Corresponding author at: Sorbonne Paris Cité Epidemiology and Statistics Research Centre (CRESS), Inserm U1153, Inra U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Bobigny, France.</footnote>

<footnote>E-mail address: paule.latino-martel@inra.fr (P. Latino-Martel).</footnote>
The Western-type dietary pattern has been shown as contributing to the development of CRC in the general population (Magalhães et al., 2012). It is characterized by high consumptions of animal-based, ultra-processed, refined and energy-dense foods. Based on the systematic review of the scientific literature and the evaluation of the level of evidence, dietary recommendations have been established to improve CRC prevention: higher physical activity, higher intake of foods containing dietary fiber, reduced consumption of red and/or processed meats and alcoholic drinks, reduced body and abdominal fatness (WCRF/AICR, 2011; Latino-Martel et al., 2016; WCRF/AICR, 2017). Interestingly, Western diet has also been reported to modulate the CRC risk associated with a FH of CRC (Slattery et al., 2000). However, compared to sporadic CRC, only very few studies have assessed the influence of lifestyle factors on familial CRC: as reviewed in 2013 by van Duijnhoven et al. in the case of LS, “most investigations have focused on smoking habits and body fatness, which both seem to increase the risk of colorectal tumors in LS. Other lifestyle factors, such as physical activity, alcohol or diet have not or only scarcely been studied in relation to colorectal tumors in persons with LS. It is, therefore, difficult to draw firm conclusions from the current literature” (van Duijnhoven et al., 2013).

A few studies compared health behaviors among subjects with or without FH of CRC. For example, Townsend et al. showed in a Californian population-based study that men and women with a FH of CRC are less likely to maintain a healthy weight and to consume five or more servings of fruits and vegetables per day, than those without a FH of cancer (Townsend et al., 2013). In another Californian population-based study, it was shown that individuals with a FH have lower odds of adherence to lifestyle recommendations (Bostean et al., 2013). Authors suggested that this may reflect either “shared behavioral risks within families, or the lack of knowledge about how certain lifestyle behaviors impact personal cancer risk” (Bostean et al., 2013). In another recent study, Spanish individuals with a FH of CRC exhibited no better health-related behaviors than people without FH of CRC (Martinez-Ochoa et al., 2012). Conversely, with data from the 2008 Oregon Behavioral Risk Factor Surveillance System, a FH of CRC has been significantly associated with respondents reporting lifestyle changes (in eating habits or physical activity) to prevent CRC (OR, 2.6; 95% CI, 1.7–4.0) (Zlot et al., 2012).

To better inform subjects with FH of CRC on factors that could modulate their risk of CRC and help them favor preventive behaviors, there is a need to better understand the role of lifestyle behaviors, especially dietary factors. Therefore, the objective of this systematic review was to provide an overview of the literature on human studies, both observational and interventional, that examined the association between nutritional factors and CRC risk in individuals with FH of CRC, and/or the joint effect of nutritional factors and FH of CRC on CRC risk as compared to non-exposed subjects without FH of CRC. Since FH of CRC and hereditary syndromes predisposing to CRC are not totally disjoint situations, we have evaluated studies on individuals with FH of CRC together with those on individuals with known or suspected hereditary syndromes.

## 2. Methods

The PRISMA protocol/checklist was followed for the systematic review (Moher et al., 2009).

### 2.1. Literature search strategy

We conducted a first search in Medline and Embase databases (up to August 2013), without publication date or language restrictions, by combining the medical subject headings (Medline) or indexed terms (Embase) and corresponding entry terms for colorectal cancers, FH (or hereditary syndromes) and nutritional factors (Supplementary Material 1). After removal of duplicates, no additional eligible article has been

identified via the Embase database. Therefore an updated search (up to December 2016) was conducted in Medline only. We also hand-searched reference lists from retrieved articles and reviews on the related topic.

### 2.2. Study selection

Abstracts or full-text manuscripts were identified and reviewed independently by two investigators, with all discrepancies resolved through discussion.

Studies were included if they met the following inclusion criteria: original research article, case-control, cohort or intervention study design, conducted on subjects with FH of colorectal cancer, with colorectal cancer as outcome and report of the odds ratio (OR), risk ratio (RR) or hazard ratio (HR) and 95% confidence interval (CI) for nutritional factors exposure. According to our inclusion criteria, studies whose outcomes were colorectal adenomas or polyps, and studies which did not provide any risk estimate were excluded. Only published peer-reviewed studies were included. No age restriction or minimum length of follow-up was required. In case of duplicate publications, the selection was based on completeness of the information.

### 2.3. Data extraction

Using a standardized data collection form, the following information was extracted for each article by one investigator and verified by a second investigator: first author's last name, publication year, study characteristics (design, country, recruitment, and mean follow-up periods for prospective studies), participants characteristics (sample size, mean age, sex, cancer site, number of cases, FH of CRC), exposure (nutritional factor, exposure assessment), comparisons and corresponding ORs, RR s or HRs and 95% CIs, control for confounding (adjustment for covariates), and potential bias. When available, data for subjects without FH within the same population sample was also recorded.

## 3. Results

### 3.1. Characteristics of the studies

Fig. 1 shows the flow chart of the selection process. From the 5312 abstracts provided by searches in Medline and Embase databases, 184 full text articles were identified and examined. Among the thirty-one potentially relevant full-text publications identified, we excluded one

<figure><img src="image_3.png" /><figcaption>Fig. 1. Flow chart of the study selection process.</figcaption></figure>
<table><caption>**Table 1**

Characteristics of the studies examining the relationship between nutritional factors and colorectal cancer risk in populations with FH of colorectal cancer.</caption><thead><tr><th>Location, recruitment period, follow-up</th><th>Total cases/ total controls<sup>a</sup></th><th>Sex, Mean age (y)</th><th>Cancer site</th><th>Family history of cancer (degree, number of cases/ controls)</th><th>Nutritional factor</th><th>Control for confounding factors (adjustment)</th><th>Exposure assessment</th><th>Comment</th><th>First author, publication year (ref)</th></tr></thead><tbody><tr><td colspan="10"><strong>Case-control studies</strong></td></tr><tr><td>USA, 1991–1994</td><td></td><td></td><td></td><td></td><td>This data set is common to five articles (Slattery et al., 1997b, Slattery et al., 1997a, Slattery et al., 1997c, Caan et al., 1998, Slattery et al., 2000 and Slattery et al., 2003): there is a potential overlap for two articles reporting results on Western diet, but in one article results concerned CRC (Slattery et al., 2003) and in the other one they concerned CC and analyses were stratified by age category (Slattery et al., 2000); an overlap between results on physical activity from two articles (Slattery et al., 2003; Slattery et al., 1997a) cannot be excluded.</td></tr><tr><td>1993/ 2400</td><td>M + F, 30–79</td><td>CC</td><td>Yes (in first degree relatives, 310/228)/ No</td><td>Saturated, monounsaturated and polyunsaturated fatty acids – in combination with FH</td><td></td><td>Age at diagnosis or selection, total energy intake, dietary fiber, cholesterol, calcium, BMI, physical activity and use of NSAIDs</td><td>Adaptation of the CARDIA diet history questionnaire</td><td>Potential recall bias for exposures and FH of CRC (Slattery et al., 1997b)</td><td></td></tr><tr><td>1993/NA</td><td>M + F, 30–79</td><td>CC</td><td>Yes (in first degree relatives, NA/NA)/No</td><td>Lifetime vigorous activity level</td><td></td><td>Age at selection or diagnosis, BMI, energy intake, dietary fiber, dietary calcium, FH of a first-degree relative with colorectal cancer (for everyone combined only), and use of aspirin and/or NSAIDs</td><td>Adaptation of the CARDIA physical activity history</td><td>Potential recall bias for exposures and FH of CRC (Slattery et al., 1997a)</td><td></td></tr><tr><td>1993/ 2410</td><td>M + F, 30–79</td><td>CC</td><td>Yes (in first degree relatives, 364/252)/ No</td><td>Energy consumption – in combination with FH</td><td></td><td>Age, body mass index, physical activity, use of NSAIDs/aspirin, dietary fiber, cholesterol, and calcium</td><td>Validated CARDIA diet history</td><td>Potential recall bias for exposures and FH of CRC (Slattery et al., 1997c)</td><td></td></tr><tr><td>1983/ 2400</td><td>M + F, 30–79</td><td>CC</td><td>Yes (in first degree relatives, NA/NA)/No</td><td>BMI, WHR</td><td></td><td>Age at selection, ever regularly used aspirin and/or NSAIDs, intake of dietary energy, fiber and calcium and category of long-term vigorous leisure activity</td><td>Adaptation of the CARDIA diet history questionnaire</td><td>Potential recall bias for exposures and FH of CRC. OR and CI are not provided for WHR.</td><td></td></tr><tr><td>1624/ 1963</td><td>M + F, 30–79</td><td>CC</td><td>Yes (in first degree relatives, 266/183)/ No</td><td>Western diet (including 9 foods for women and 13 foods for men), eggs, refined grains, sugar, red meat, processed meat, fast-food meat – in combination with FH</td><td></td><td>Age, sex, calories, BMI, long-term vigorous physical activity, and usual number of cigarettes smoked per day</td><td>Adaptation of the CARDIA diet history questionnaire</td><td>Potential recall bias for exposures and FH of CRC. (Slattery et al., 2000)</td><td></td></tr><tr><td>2260/ 2749</td><td>M + F, 30–79</td><td>CRC</td><td>Yes (in first degree relatives, 299/230)/ No</td><td>Prudent diet (including 5 foods), BMI, Western diet (including 9 foods for women and 13 foods for men), physical activity – in combination with FH</td><td></td><td>All variables in same model and mutually adjusted for age, sex, and study</td><td>Adaptation of the CARDIA diet history questionnaire</td><td>Potential recall bias for exposures and FH of CRC. (Slattery et al., 2003)</td><td></td></tr><tr><td>USA (Hawaii), 1987–1991</td><td>1192/ 1192</td><td>M + F, controls: 58, cases: 66 (medians)</td><td>CRC</td><td>Yes (in first degree relatives, 169/75)/No</td><td>Total calories, calories from fat, saturated fat, P/S ratio, beef, processed meats, eggs, chicken without skin, margarine, total calcium, NSP, total carotenoids, methionine, legumes and soy, total vegetables, broccoli, ethanol, BMI, healthy and unhealthy lifestyles (including both dietary factors, smoking, BMI and physical activity) – in combination with FH or not</td><td>Age, alcoholic drinks/week, pack-years of cigarette smoking, lifetime recreational physical activity, Quelete index 5 years ago, dietary fiber, calcium intake, egg intake, and total calories. Calories from fat and calories from other sources were additionally adjusted for each other. All of the nutrients were adjusted for calories by the method of residuals</td><td>Validated food frequency questionnaire based on more than 282 food items. The reference period for the diet questionnaire was the 3-year period before the onset of symptoms for the cases and the 3-year period before interview for the controls</td><td>Potential recall bias for exposures and FH of CRC. (Le Marchand et al., 1999)</td><td></td></tr></tbody></table>

Italy, 1985–1992 The data set for subjects with FH is common to Refs. Fernandez et al. (1997) and Fernandez et al. (2002): there is an overlap for some nutritional factors, i.e. red meat, seasoning fats, β-carotene and ascorbic acid. (continued on next page)
<table><caption>Table 1 (continued)</caption><thead><tr><th>Location, recruitment period, follow-up<sup>a</sup></th><th>Total cases/total controls<sup>b</sup></th><th>Sex, Mean age (y)</th><th>Cancer site</th><th>Family history of cancer (degree, number of cases/ controls)</th><th>Nutritional factor</th><th>Control for confounding factors (adjustment)</th><th>Exposure assessment</th><th>Comment</th><th>First author, publication year (ref)</th></tr></thead><tbody><tr><td colspan="10"><strong>Case-control studies</strong></td></tr><tr><td></td><td>112/108</td><td>M + F, controls: 56, cases: 61 (medians)</td><td>CRC</td><td>Yes (in first degree relatives, 112/108)</td><td>Alcohol, coffee, pasta, pastries, red meat, poultry, raw ham, ham, canned meat, cheese, cabbages, spinach, tomatoes, peppers, lettuce, total vegetables, citrus fruits, melon, butter, seasoning fats, retinol, β-carotene, ascorbic acid, calcium, vitamin D, vitamin E, folate and methionine</td><td>Gender, age and area of residence. Allowance for other potential confounding variables (i.e. years of schooling, body mass index, total energy intake) did not substantially modify any of the estimates</td><td>Weekly frequency of consumption</td><td>Potential recall bias for exposures and FH of CRC. Small number of cases. Hospital-based controls. Limited number of food items. Over-representation of smokers in the control group.</td><td>(Fernandez et al., 1997)</td></tr><tr><td></td><td>1584/2879</td><td>M + F, controls: 55, cases: 62 (medians)</td><td>CRC</td><td>Yes (in first degree relatives, 112/108)/No</td><td>Red meat, seasoning fats, daily meal frequency, β-carotene, ascorbic acid, adult life dietary risk score – in combination with FH or not</td><td>Age, sex, area of residence, education, and total energy intake</td><td>Food frequency questionnaire to collect information on the weekly frequency of consumption of 29 indicator foods</td><td>Potential recall bias for exposures and FH of CRC. Limited number of food items.</td><td>(Fernandez et al., 2002)</td></tr><tr><td>Italy, 1992–1996</td><td>This data set is common to references (Negri et al., 1998, Tavani et al., 1998, La Vecchia et al., 1999, Fernandez et al., 2004 and Turati et al., 2011).</td><td>M + F, controls: 58, cases: 62 (medians)</td><td>CRC</td><td>Yes (in first degree relatives, 187/146)/No</td><td>Total fiber</td><td>Center, sex, age, education, physical activity and intake of proteins, fats, carbohydrates, and alcohol</td><td>Interviewer-administered food frequency questionnaire (based on 78 foods, groups of foods, or dishes divided into 6 sections) to assess the usual diet during the 2 years preceding diagnosis (for cases) or hospital admission (for controls)</td><td>Potential recall bias for exposures and FH of CRC. Hospital-based controls</td><td>(Negri et al., 1998)</td></tr><tr><td></td><td>1953/4154</td><td>M + F, controls: 56, cases: 61–62 (medians)</td><td>CRC</td><td>Yes (NA,NA/NA)/No</td><td>Alcohol</td><td>Center, age, sex, education, physical activity, smoking status and intake of and intake of β-carotene, vitamin C and total energy</td><td>Validated food-frequency questionnaire including 78 questions</td><td>Potential recall bias for exposures and FH of CRC. Hospital-based controls</td><td>(Tavani et al., 1998)</td></tr><tr><td></td><td>1225/4154</td><td>M + F, controls: 58, cases: 62 (medians)</td><td>CC</td><td>Yes (in first degree relatives, 134/146)/No</td><td>Physical activity, energy, vegetable, meal frequency</td><td>Center, age, sex, education, level of occupational physical activity, total energy intake, meal frequency, and FH of colorectal cancer</td><td>Validated food frequency section including 78 foods or food groups</td><td>Potential recall bias for exposures and FH of CRC. Hospital-based controls</td><td>(La Vecchia et al., 1999)</td></tr><tr><td></td><td>1225/4154</td><td>M + F, controls: 58, cases: 62 (medians)</td><td>CC</td><td>Yes (in first degree relatives, 134/146)/No</td><td>Risk factor score (including education, occupational physical activity, daily meal frequency, intake of fiber, intake of calcium, and intake of β-carotene) – in combination with FH</td><td>Age, sex, center, and total energy intake</td><td>Validated questionnaire comprising 78 foods, food groups, or recipes and allowing the estimation of energy intake as well as of several micronutrients</td><td>Potential recall bias for exposures and FH of CRC. Hospital-based controls</td><td>(Fernandez et al., 2004)</td></tr><tr><td></td><td>1953/4154</td><td>M + F, 20–74</td><td>CRG, CC, RC</td><td>Yes (in first degree relatives (187/146)/No</td><td>CRG, CC, RC</td><td>Age, sex, center, education, occupational physical activity, and tertiles of consumption of all the remaining dietary patterns (i.e. ‘animal products’, ‘unsaturated fats (animal source)’, ‘unsaturated fats (vegetable source)’, and ‘starch-rich’ or ‘vitamins and fiber’ when</td><td>Validated food frequency questionnaire with satisfactory reproducibility and validity based on 78 foods, groups of foods, recipes, and 5 alcoholic beverages</td><td>Potential recall bias for exposures and FH of CRC. Hospital-based controls</td><td>(Turati et al., 2011)</td></tr></tbody></table>

(continued on next page)
<table><caption>Table 1 (continued)</caption><thead><tr><th>Location, recruitment period, follow-up<sup>a</sup></th><th>Total cases/ total controls<sup>b</sup></th><th>Sex, Mean age (y)</th><th>Cancer site</th><th>Family history of cancer (degree, number of cases/ controls)</th><th>Nutritional factor</th><th>Control for confounding factors (adjustment)</th><th>Exposure assessment</th><th>Comment</th><th>First author, publication year (ref)</th></tr></thead><tbody><tr><td colspan="10"><strong>Case-control studies</strong></td></tr><tr><td>Japan, 1979–1987</td><td>3327/ 14884</td><td>M, ≥ 20</td><td>CC, RC</td><td>Yes (in parents, siblings and grandparents, NA/NA)/No</td><td>Beer – in combination with FH and occupation</td><td></td><td>Age, residence, smoking habits</td><td>The registry has routinely collected data on occupation, marital status, FH of cancer (parents, siblings and grandparents) and the questions about smoking and drinking have been included in the report format since 1980</td><td>(Kato et al., 1990)</td></tr><tr><td>Japan, 1988–1998</td><td>1352/ 50706</td><td>M + F, 18–79</td><td>CRC</td><td>Yes (in first degree relatives, 124/2456)/ No</td><td>Pickled vegetables, fruits, raw vegetables, green tea, preference for coffee, miso soup, milk, eastern type breakfast, preference for oily foods, bean curd, carrots, pumpkin, cabbage, lettuce, potatoes, egg, chicken, beef, pork, sausage, instant foods, frozen foods, salted fishes, cooked fishes, physical exercise, alcohol</td><td>Age and sex</td><td>Self-administered questionnaire Including items on demography, medical history, FH of disease in parents and siblings, smoking and drinking habits, dietary habits, physical exercise, bowel habits, and reproductive history</td><td>Potential recall bias for exposures and FH of CRC. Controls with other sites of cancer. Limited number of confounding factors controlled</td><td>(Huang et al., 2004)</td></tr><tr><td>Canada, 1997–2000, 2003–2006</td><td>2696/ 2668</td><td>M + F, 20–74</td><td>CRC</td><td>Yes (high/ intermediate risk group according to Amsterdam-Bethesda criteria, 878/NA)/No</td><td>BMI (2 y ago, or since age 20 y), weight gain since age 20 y</td><td>Age and sex</td><td>Age, province, history of hypercholesterolemia/ hypertriglyceridemia, education, and history of colon screening endoscopy</td><td>Self-administered personal history questionnaire</td><td>(Campbell et al., 2007)</td></tr><tr><td>Pays-Bas, 1999–2002</td><td>145/103</td><td>M + F, 18–75</td><td>CRC</td><td>Yes (family fulfilling the Amsterdam criteria for HNPCC, 145/103)</td><td>Total energy intake, total vegetables and fruit, vegetables, fruits, cereals, total meat, red meat, poultry, fish, dairy products, alcohol, fat, protein, carbohydrates, dietary fiber, calcium, vitamin C, total energy intake</td><td>Age at last colonoscopy, sex, total energy intake, carrier status, and cigarette smoking. Alcohol and nutrients are also adjusted on total energy intake by the residual method</td><td>Validated, semiquantitative food frequency questionnaire (based on 79 food items) that was originally developed for the Dutch cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)</td><td>Potential recall bias for exposures. Subjects recruited by the population-based Ontario cancer registry</td><td>(Diergaarde et al., 2007)</td></tr><tr><td>Australia, 1980–1981</td><td>702/710</td><td>M + F, controls: 64.8, cases: 65.7</td><td>CRC</td><td>Yes (in male siblings, 11/17)/No</td><td>Beer – in combination with FH</td><td>Age and sex</td><td>Dietary questionnaire which included alcohol intake and tobacco consumption</td><td>Potential recall bias for exposures and FH of CRC. Limited number of confounding factors controlled</td><td>(Kune et al., 1989)</td></tr><tr><td>USA, Australia and Canada, 1997–2007</td><td>188/274</td><td>M + F, controls: 55 (M) and 54 (F), cases: 56 (M) and 55 (F)</td><td>CRC</td><td>Yes (in first degree relatives, 80/116)/No</td><td>BMI (recent)</td><td>Age and sex</td><td>Recent BMI was calculated from self-reported height and weight approximately 1 year before CRC diagnosis for cases subjects, or before</td><td>Potential recall bias for exposures and FH of CRC. Small number of cases. Cases with high MSI (microsatellite instability) CRC, recruited and</td><td>(Campbell et al., 2010)</td></tr></tbody></table>

(continued on next page)
<table><caption>Table 1 (continued)</caption><thead><tr><th></th><th>Total cases/ total controls<sup>b</sup></th><th>Sex, Mean age (y)</th><th>Cancer site</th><th>Family history of cancer (degree, number of cases/ controls)</th><th>Nutritional factor</th><th>Control for confounding factors (adjustment)</th><th>Exposure assessment</th><th>Comment</th><th>First author, publication year (ref)</th></tr></thead><tbody><tr><td colspan="10">Case-control studies</td></tr><tr><td>USA, Canada</td><td>3350/ 3504</td><td>M + F, controls: 57.8, cases: 59.4</td><td>CRC</td><td>Yes (MMR gene mutation carriers, 243/350)/No</td><td>Non processed red meat, processed red meat, total processed meats, total pan-fried meat, total oven-broiled meat, total grilled meat</td><td>Age, BMI, gender, race, saturated fat, dietary fiber, center, vegetables, physical activity, and total calorie intake</td><td>Validated food frequency questionnaire for 200 food items and more than 100 nutrients</td><td>genetically characterized by the Colon cancer family registry: potential overlap with the sample of another study (Win et al., 2011) for Canadian subjects</td><td>(Joshi et al., 2015)</td></tr><tr><td>Cohort studies</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>USA (Iowa), 1986, 10 years</td><td>241/ 34975</td><td>F, 61.7</td><td>CC</td><td>Yes (in first degree relatives, 61/4178)/ No</td><td>Total fruit & vegetable, total vegetable, total fruit, green leafy vegetables, cruciferous vegetables, legumes, fruit and vegetables high in vitamin C, dietary fiber, garlic, total dairy, high fat dairy, low fat dairy, high sucrose foods, total meat, red meat, white meat, nitrate meat (bacon, hot dogs, processed meats), total calcium, dietary calcium, supplemental calcium, total vitamin C, dietary vitamin C, supplemental vitamin C, total vitamin A, dietary vitamin A, supplemental vitamin A, carotene, total vitamin E, dietary vitamin E, supplemental vitamin E, total vitamin D, dietary vitamin D, supplemental vitamin D and folate</td><td>Age at baseline, total energy intake, and history of rectal colon polyps</td><td>Semiquantitative food-item frequency questionnaire</td><td>Potential recall bias for exposures. Data on meat subtypes also provided. Potential overlap with the sample of another study for subjects from Hawaii (Le Marchand et al., 1999), but analyses are different</td><td>(Sellers et al., 1998)</td></tr><tr><td>USA (NHS), 1980, 16 years</td><td>535/ 88223</td><td>F, 46.7–46.8</td><td>CC</td><td>Yes (in first degree relatives, 107/6849)/ No</td><td>Total folates, folates from food sources only, multivitamin supplement use in 1980, methionine, alcohol – in combination with FH or not</td><td>Age, pack-years of smoking before age 30 years, body-mass index, regular vigorous exercise, regular aspirin use, screening endoscopy, beef, pork, or lamb as a main dish, alcohol consumption, and energy-adjusted levels of methionine</td><td>61-item semiquantitative food frequency questionnaire to assess diet as well as supplemental vitamin use</td><td>Potential selection bias and recall bias for FH of CRC. Data on the duration of vitamin use or elevated folate intake also available</td><td>(Fuchs et al., 2002)</td></tr><tr><td>USA (NHS and HPPS), 1976 (females) and 1986 (males), 26 years (females)</td><td>1801/ 133350</td><td>M + F, 52.5–54.4</td><td>CC</td><td>Yes (in parents and siblings, 484/NA)/No</td><td>Alcohol – in combination with FH or not</td><td>Pack-years of smoking before age 30 y, BMI, history of endoscopy, use of aspirin, and intakes of energy, calcium, folate, and red meat; in the NHS: information on methionine</td><td>≈ 60–130-item semiquantitative food frequency questionnaire each 4 years</td><td>Potential selection bias and recall bias for FH of CRC. Data on women were likely to overlap with those from Fuchs et al. (continued on next page)</td><td>(Cho et al., 2012)</td></tr></tbody></table>
<table><caption>Table 1 (continued)</caption><thead><tr><th>Location, recruitment period, follow-up<sup>a</sup></th><th>Total cases/total controls<sup>b</sup></th><th>Sex, Mean age (y)</th><th>Cancer site</th><th>Family history of cancer (degree, number of cases/ controls)</th><th>Nutritional factor</th><th>Control for confounding factors (adjustment)</th><th>Exposure assessment</th><th>Comment</th><th>First author, publication year (ref)</th></tr></thead><tbody><tr><td colspan="10">Case-control studies and 20 years (males)</td></tr><tr><td>USA, Australia, New Zealand, Canada, 1997–2007, 5 years</td><td>695/1848</td><td>M + F, MMR gene mutation carriers: 44.0–44.9, non-carriers: 51.9–56.8</td><td>CRC</td><td>Yes (MMR gene mutation carriers, 659/665)/No</td><td>BMI at age 20 years</td><td>menopausal status and use of postmenopausal hormone therapy: FH of colorectal cancer in parents and siblings</td><td>Standardised personal interviews, telephone interviews or mailed questionnaires</td><td>Retrospective study, Potential selection and recall bias for exposures. Subjects recruited and genetically characterized by the Colon cancer family registry: potential overlap with the sample of another article (Campbell et al., 2010) for Canadian subjects</td><td>(Win et al., 2011)</td></tr><tr><td>Netherlands, 2006–2008, 28 months (median)</td><td>131/339</td><td>M + F, 39.1–60.7</td><td>CRC</td><td>Yes (individuals with Lynch syndrome, 122/326)</td><td>Folate, vitamins B2, B6, B12, methionine</td><td>Age, sex, number of colonoscopies during person-time, NSAID use, physical activity, and mutually adjusted on other vitamins</td><td>Validated 183-item semi-quantitative self-administered food frequency questionnaire</td><td>Potential selection bias. Small number of cases. Analyses for MTHFR C677T genotype are also provided</td><td>(Jung et al., 2014)</td></tr><tr><td>Taiwan, 2002–2012, 12,529 total person-time</td><td>147/154</td><td>M + F, 41 (median)</td><td>CRC</td><td>Yes (individuals with MMR gene mutations fulfilling the Amsterdam II criteria for Lynch syndrome, 147/154)</td><td>Regular physical activity, alcohol drinking, tea, coffee, meat, vegetable, fruit, seafood and staple food intakes</td><td>Mutated MMR genes, year of birth</td><td>Interviews by trained professional nurses. Usually dietary intake of 14 food items, for 5 y preceding the date of study registry</td><td>Retrospective study. Potential selection and recall bias for exposures. Limited number of food items. Separate analyses for MLH1 or MSH2 germline mutation carriers also provided</td><td>(Kamiza et al., 2015)</td></tr><tr><td>International centers (northern Europe, UK, other regions), 1999–2005, 55.7 months</td><td>55/882</td><td>M + F, 45.2</td><td>CRC</td><td>Yes (individuals with Lynch syndrome, 54/842)</td><td>BMI</td><td>Age, starch, aspirin, geographic region, mismatch repair gene, and sex</td><td>BMI was calculated from height and weight reported by participants at recruitment</td><td>Potential selection bias. Self-reported height and weight. Small number of cases. Separate analyses for men and women also provided</td><td>(Movahedi et al., 2015)</td></tr><tr><td>USA, Canada, Australia, New Zealand, 1997–2012, up to 80,420 person-years</td><td>744/1222</td><td>M + F, 41.8</td><td>CRC</td><td>Yes (individuals with Lynch syndrome, 744/1222)</td><td>Multivitamin supplement, calcium supplement, acid folique</td><td>Ascertainment, education, country, sex, number of screening colonoscopies, regular physical activity, cigarette smoking and intake of aspirin and/or ibuprofen</td><td>Data collection at the time of recruitment, using standardized questionnaires via personal interviews, telephone interviews or mails</td><td>Retrospective study. Potential selection and recall bias for exposures. Separate analyses for men and women also provided.</td><td>(Chau et al., 2016)</td></tr><tr><td>USA, Canada, Australia, New Zealand, 1997–2012</td><td>769/1156</td><td>M + F, 42.2</td><td>CRC</td><td>Yes (MMR gene mutation carriers, 769/1156)</td><td>Average daily ethanol intake from any alcoholic beverage</td><td>Country, education, ascertainment, sex, BMI at age 20, diabetes status, regular physical activity, smoking status, and intakes of aspirin or ibuprofen, multivitamin, calcium and folic</td><td>At the time of baseline recruitment, standardized questionnaires were used to collect self-reported information</td><td>Potential selection bias. Analyses for ethanol intake from beer, wine or spirits, and for colon and rectum cancers separately, also provided.</td><td>(Dashti et al., 2016)</td></tr></tbody></table>

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Kamiza et al., 2015; Win et al., 2011), or individuals with LS (Movahedi et al., 2015; Jung et al., 2014; Chau et al., 2016; Mathers et al., 2012). The number of cases in subjects with FH of CRC varied between 11–878 across articles, representing 1–100% of total cases. In four articles, this information was not available.

Nineteen articles analyzed the risk of cancer associated with the exposure to nutritional factors in subjects with FH of CRC (Fernandez et al., 1997; Huang et al., 2004; Diergaarde et al., 2007; Tavani et al., 1998; Caan et al., 1998; Campbell et al., 2010; Campbell et al., 2007; Joshi et al., 2015; Fernandez et al., 2002; Slattery et al., 1997a; La Vecchia et al., 1999; Negri et al., 1998; Dashti et al., 2016; Cho et al., 2012; Movahedi et al., 2015; Sellers et al., 1998; Kamiza et al., 2015; Win et al., 2011; Mathers et al., 2012), among which eleven articles also compared the results with those obtained in subjects without FH of CRC. Twelve articles (Slattery et al., 2000; Le Marchand et al., 1999; Kune et al., 1989; Kato et al., 1990; Slattery et al., 2003; Fernandez et al., 2002; Turati et al., 2011; Fernandez et al., 2004; Slattery et al., 1997b; Slattery et al., 1997c; Cho et al., 2012; Fuchs et al., 2002) examined the modification of cancer risk associated with the combination of nutritional factors and FH of CRC as compared to subjects without FH whose exposure is null or low, termed as "non-exposed" in the following sections.

Since the limited number and heterogeneity of articles regarding study design, nutritional factors studied, exposure categories, reference group and data analysis did not allow a quantitative evaluation by meta-analysis, a qualitative synthesis was performed. Main results of the selected articles, for the nutritional factors already known to modify CRC risk in the general population, are presented in Table 2 (nineteen articles corresponding to case-control studies, seven to cohort studies and one to an intervention study). Results for various other factors can be found in Supplemental Table 1.

## 3.2. Risk factors

The nutritional factors known to increase CRC risk in the general population with a level of evidence graded as convincing or probable are alcoholic beverages, red and processed meat, and overweight and obesity (WCRF/AICR, 2011; Latino-Martel et al., 2016; WCRF/AICR, 2017).

### 3.2.1. Alcoholic beverages

Eleven articles, seven from case-control studies (Fernandez et al., 1997; Le Marchand et al., 1999; Huang et al., 2004; Diergaarde et al., 2007; Tavani et al., 1998; Kune et al., 1989; Kato et al., 1990), one from a retrospective cohort study on (Kamiza et al., 2015) and three from prospective cohort studies (Dashti et al., 2016; Cho et al., 2012; Fuchs et al., 2002) provided results on alcoholic beverages (beer drinking), alcohol drinking or alcohol intake (in g/day) and CRC risk. Two studies concerned MMR gene mutation carriers (Kamiza et al., 2015; Dashti et al., 2016). As previously mentioned, a potential overlap between two articles has been identified (Cho et al., 2012; Fuchs et al., 2002).

Among the seven articles with analyses on subjects with FH of CRC, five (Fernandez et al., 1997; Huang et al., 2004; Diergaarde et al., 2007; Tavani et al., 1998; Kamiza et al., 2015) reported no association between alcohol consumption and CRC risk and two (Dashti et al., 2016; Cho et al., 2012) reported an increased risk. Three of them also mentioned results obtained in subjects without FH of CRC: no association (Tavani et al., 1998; Cho et al., 2012) and an increase of risk (Huang et al., 2004) for current drinkers (versus never drinkers).

The modification of cancer risk associated with the combination of alcohol and FH of CRC as compared to non-exposed subjects without FH, was examined in five articles (Le Marchand et al., 1999; Kune et al., 1989; Kato et al., 1990; Cho et al., 2012; Fuchs et al., 2002): the combination was associated with a significant increased risk for higher beer drinking (Kune et al., 1989; Kato et al., 1990). It was associated with a significant increased risk for higher alcohol intake in both gender

(Cho et al., 2012) and in men (Le Marchand et al., 1999); in women the increase was significant in one study (Fuchs et al., 2002) and borderline significant in another one (Le Marchand et al., 1999). Three of these articles (Kune et al., 1989; Cho et al., 2012; Fuchs et al., 2002) mentioned that the risk of CRC observed for the combination was higher than the one observed for FH alone. A significant interaction between FH of CRC, alcohol and risk of CRC was reported in men only (Le Marchand et al., 1999) and in women (Fuchs et al., 2002). All five articles also mentioned results obtained in subjects without FH of CRC: an increase of cancer risk in two articles (Kune et al., 1989; Kato et al., 1990), a borderline significant increase in men in one article (Huang et al., 2004) and no association in two articles (Cho et al., 2012; Fuchs et al., 2002).

### 3.2.2. Overweight and obesity

Eight articles, five from case-control studies (Le Marchand et al., 1999; Caan et al., 1998; Slattery et al., 2003; Campbell et al., 2010; Campbell et al., 2007), one from a retrospective cohort study (Win et al., 2011) and one from a prospective cohort study (Movahedi et al., 2015) provided results on BMI (by category or dose-response at different ages or periods) and CRC risk. One article concerned subjects with high/intermediate risk, according to Amsterdam/Besthesda criteria (Campbell et al., 2007), one included MMR gene mutation carriers (Win et al., 2011) and one individuals with LS (Movahedi et al., 2015). As previously mentioned, an overlap between samples of two articles (Campbell et al., 2010; Win et al., 2011) cannot be excluded.

The analyses concerned subjects with FH of CRC in five articles: in three studies, higher BMI at age 20 y (Win et al., 2011) or 30–54 y (Caan et al., 1998) or at recruitment (Movahedi et al., 2015) was significantly associated with CRC risk; in one study the association was significant for three indicators (BMI 2 years ago, BMI at age 20 y or weight gain since age 20 y) in men but not in women (Campbell et al., 2007), whereas no association was observed for recent BMI with a smaller number of men and women combined (Campbell et al., 2010). Similar results were reported in subjects without FH (Caan et al., 1998; Campbell et al., 2010; Win et al., 2011).

The modification of cancer risk associated with the combination of higher BMI and FH of CRC as compared to non-exposed subjects without FH, was examined in two studies (Le Marchand et al., 1999; Slattery et al., 2003): the combination was associated with a significant increased risk in one study (Slattery et al., 2003), and in men but not in women in the other study (Le Marchand et al., 1999). Both studies reported similar results in subjects without FH, the size of the effect being smaller.

### 3.2.3. Red and processed meat

Nine articles, seven from case-control studies (Slattery et al., 2000; Fernandez et al., 1997; Le Marchand et al., 1999; Huang et al., 2004; Diergaarde et al., 2007; Joshi et al., 2015; Fernandez et al., 2002), one from a retrospective cohort study (Kamiza et al., 2015) and one from a women prospective cohort study (Sellers et al., 1998), provided results on meat, especially red meat and processed meat and CRC risk. One study concerned subjects fulfilling the Amsterdam criteria for HNPCC (Diergaarde et al., 2007) and two MMR gene mutation carriers (Joshi et al., 2015; Kamiza et al., 2015). An overlap has been identified between samples of two articles on red meat (Fernandez et al., 1997; Fernandez et al., 2002): since the exposure is expressed in portions per week in the more recent study (Fernandez et al., 2002) whereas expressed as high versus low in the other one (Fernandez et al., 1997), only results from this recent study (Fernandez et al., 2002) are presented.

The analyses concerned subjects with FH of CRC in six articles: in one case-control study (Fernandez et al., 2002), high consumption of red meat was significantly associated with an increased risk of CRC, whereas for ham and canned meat, the risk increase was borderline significant; in one retrospective cohort study (Joshi et al., 2015), a
<table><caption>**Table 2**

Odds ratios, relative risks or hazard ratios from studies reporting associations between nutritional factors and colorectal cancer risk in populations with FH of colorectal cancer.</caption><thead><tr><th>First author, publication year (ref)</th><th>Family history of cancer (number of cases)</th><th>Nutritional factor</th><th>Comparison</th><th>Sub-group</th><th>OR, HR or RR (95% CI)</th></tr></thead><tbody><tr><td rowspan="2">Alcoholic beverages (Kune et al., 1989)</td><td>FH (11) combined</td><td>Drink beer</td><td>No (FH) vs No (no FH)</td><td></td><td>1.07 (0.4-3.1)</td></tr><tr><td>No FH (305)</td><td>Drink beer</td><td>Yes (FH) vs No (no FH)</td><td></td><td>10.5 (2.0-55)</td></tr><tr><td rowspan="2">(Kato et al., 1990)</td><td>FH (NA) combined</td><td>Drink beer + low/moderate occupation level</td><td>Yes vs No</td><td>CC</td><td>1.50 (1.1-2.1)</td></tr><tr><td>No FH (NA)</td><td>Drink beer + low/moderate occupation level</td><td>Yes vs No</td><td>CC</td><td>10.07 (4.77-21.29)</td></tr><tr><td rowspan="2">(Fernandez et al., 1997) (Tavani et al., 1998)</td><td>FH (112)</td><td>Alcohol</td><td>&gt; 4 vs 0 drinks/day</td><td>CC</td><td>6.69 (3.12-14.36)</td></tr><tr><td>FH (NA)</td><td>Alcohol</td><td>High vs Never drinker</td><td>RC</td><td>2.44 (1.84-3.23)</td></tr><tr><td rowspan="2">(Le Marchand et al., 1999)</td><td>No FH (NA)</td><td>Alcohol</td><td>High vs Never drinker</td><td>RC</td><td>2.14 (1.65-2.78)</td></tr><tr><td>FH (M:90-F:72) combined</td><td>Ethanol</td><td>&gt; 8.7 (FH) vs &lt; 0.4 (no FH) g/day</td><td>M</td><td>0.8 (0.3-2.0)</td></tr><tr><td></td><td></td><td></td><td>&gt; 0.13 (FH) vs &lt; 0 (no FH) g/day</td><td>F</td><td>0.97 (0.33-2.88)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>0.95 (0.76-1.18)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>5.7 (2.4-13.2)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>2.7 (1.0-6.9)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Significant interaction between FH and ethanol (p = 0.03)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.2 (0.9-1.7)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.3 (0.9-2.0)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.91 (1.32-2.85)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>3.79 (2.13-6.76)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Significant interaction between FH and alcohol (p = 0.004)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>0.88 (0.56-1.39)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>0.89 (0.52-1.52)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.32 (1.11-1.57)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.0 (0.5-2.0)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>2.02 (1.30-3.13)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.38 (1.06-1.80)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>2.80 (2.00-3.91)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.23 (0.96-1.57)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>0.92 (0.62-1.36)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.55 (1.11-2.15)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.56 (1.11-2.18)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.25 (0.77-2.04)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.79 (1.12-2.87)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.02 (0.95-1.10)</td></tr><tr><td rowspan="2">(Fuchs et al., 2002)</td><td>No FH (M:603-F:420)</td><td>Ethanol</td><td>&gt; 8.7 vs &lt; 0.4 g/day</td><td>M</td><td></td></tr><tr><td>FH (107) combined</td><td>Alcohol</td><td>&gt; 0.13 vs &lt; 0 g/day</td><td>F</td><td></td></tr><tr><td></td><td></td><td></td><td>0 (FH) vs 0 (no FH) g/day</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td>&gt; 30 (FH) vs 0 (no FH) g/day</td><td></td><td></td></tr><tr><td rowspan="2">(Huang et al., 2004)</td><td>No FH (428)</td><td>Alcohol</td><td>&gt; 30 vs 0 g/day</td><td></td><td></td></tr><tr><td>FH (124)</td><td>Alcohol</td><td>Current vs never drinker</td><td></td><td></td></tr><tr><td rowspan="2">(Diergaarde et al., 2007)</td><td>No FH (1228)</td><td>Alcohol</td><td>Current vs never drinker</td><td></td><td></td></tr><tr><td>FH (145)</td><td>Alcohol</td><td>≥ 12.8 vs ≤ 2.6 g/day</td><td></td><td></td></tr><tr><td rowspan="2">(Cho et al., 2012)</td><td>FH (424)</td><td>Alcohol</td><td>≥ 30 vs 0 g/day</td><td></td><td></td></tr><tr><td>FH (424) combined</td><td>Alcohol</td><td>0 (FH) vs 0 g/day (no FH)</td><td></td><td></td></tr><tr><td></td><td>No FH (1377)</td><td>Alcohol</td><td>≥ 30 (FH) vs 0 g/day (no FH)</td><td></td><td></td></tr><tr><td rowspan="2">(Kamiza et al., 2015) (Dashti et al., 2016)</td><td>FH (147)</td><td>Alcohol drinking</td><td>≥ 30 (FH) vs 0 g/day</td><td></td><td></td></tr><tr><td>FH (769)</td><td>Average daily ethanol intake from any alcoholic beverage</td><td>Ever vs Never</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td>Ever user vs Abstainer</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td>&gt; 0 to ≤ 14 g vs Abstainer</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td>&gt; 14grams to ≤ 28 g vs Abstainer</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td>&gt; 28 g vs Abstainer</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td>Per 14 g/day</td><td></td><td></td></tr><tr><td rowspan="2">Overweight and obesity (Caan et al., 1998)</td><td>FH (NA)</td><td>BMI (30-54y)</td><td>T3 vs T1</td><td>M</td><td>7.76 (2.60-23.10)</td></tr><tr><td>No FH (NA)</td><td>BMI (30-54y)</td><td>T3 vs T1</td><td>F</td><td>4.85 (2.33-10.12)</td></tr><tr><td></td><td>FH (NA)</td><td>WHR</td><td>T3 vs T1</td><td>M</td><td>1.70 (1.25-2.32)</td></tr><tr><td></td><td></td><td></td><td></td><td>F</td><td>1.53 (1.22-1.92)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>No significant interaction with FH was found for either age group of men or women</td></tr><tr><td rowspan="2">(Le Marchand et al., 1999)</td><td>FH (M:90-F:72) combined</td><td>BMI 5 years ago</td><td>&gt; 25.4 vs &lt; 23.0</td><td>M</td><td>3.6 (1.7-7.6)</td></tr><tr><td>No FH (M:603-F:420)</td><td>BMI 5 years ago</td><td>&gt; 24.6 vs &lt; 21.3</td><td>F</td><td>1.7 (0.7-4.6)</td></tr><tr><td></td><td></td><td></td><td>&gt; 25.4 vs &lt; 23.0</td><td>M</td><td>2.2 (1.5-3.1)</td></tr><tr><td></td><td></td><td></td><td>&gt; 24.6 vs &lt; 21.3</td><td>F</td><td>1.3 (0.8-1.9)</td></tr><tr><td rowspan="2">(Slattery et al., 2003)</td><td>FH (299) combined</td><td>BMI</td><td>&gt; 29 (FH) vs &lt; 25 (no FH)</td><td>F</td><td>2.76 (1.94-3.92)</td></tr><tr><td>No FH (1978)</td><td>BMI</td><td>&gt; 29 vs 25</td><td>F</td><td>1.27 (1.09-1.47)</td></tr><tr><td rowspan="2">(Campbell et al., 2007)</td><td>FH (878)</td><td>BMI 2 y ago</td><td>≥ 30 vs 18.5-24.99</td><td>M</td><td>0.85 (0.62-1.16)</td></tr><tr><td></td><td>BMI at age 20 y</td><td>≥ 30 vs 18.5-24.99</td><td>F</td><td>1.83 (1.33-2.51)</td></tr><tr><td></td><td></td><td></td><td>≥ 21 vs 1-5 kg</td><td>F</td><td>0.81 (0.38-1.72)</td></tr><tr><td></td><td></td><td></td><td></td><td>M</td><td>1.92 (1.02-3.63)</td></tr><tr><td></td><td></td><td></td><td></td><td>F</td><td>1.21 (0.85-1.73)</td></tr><tr><td></td><td></td><td></td><td></td><td>M</td><td>1.72 (1.22-2.41)</td></tr></tbody></table>

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<table><caption>Table 2 (continued)</caption><thead><tr><th>First author, publication year (ref)</th><th>Family history of cancer (number of cases)</th><th>Nutritional factor</th><th>Comparison</th><th>Sub-group</th><th>OR, HR or RR (95% CI)</th></tr></thead><tbody><tr><td rowspan="10">(Campbell et al., 2010)</td><td rowspan="3">No FH (1141)</td><td>BMI 2 y ago</td><td>≥30 vs 18.5-24.99</td><td>F</td><td>0.93 (0.70-1.24)</td></tr><tr><td>BMI at age 20 y</td><td>≥30 vs 18.5-24.99</td><td>M</td><td>1.74 (1.28-2.36)</td></tr><tr><td>Weight gain since age 20 y</td><td>≥21 vs 1-5 kg</td><td>F</td><td>1.04 (0.50-2.15)</td></tr><tr><td rowspan="3">FH (80)</td><td>BMI (recent)</td><td>≥30 vs 18.5-24.99 kg/m²</td><td>M</td><td>1.78 (0.90-3.53)</td></tr><tr><td>BMI (recent)</td><td>Per 5 kg/m²</td><td>F</td><td>1.05 (0.76-1.44)</td></tr><tr><td>BMI (recent)</td><td>≥30 vs 18.5-24.99 kg/m²</td><td>M</td><td>1.65 (1.18-2.29)</td></tr><tr><td rowspan="3">(Win et al., 2011)</td><td rowspan="2">MMR gene mutation carriers (659)</td><td>Per 5 kg/m²</td><td>0.85 (0.29-2.47)</td><td></td></tr><tr><td>Obese vs Normal</td><td>0.90 (0.60-1.33)</td><td></td></tr><tr><td>Non-carriers (36)</td><td>Per 5 kg/m²</td><td>0.68 (0.30-1.55)</td><td></td></tr><tr><td rowspan="3">(Movahedi et al., 2015)</td><td rowspan="2">FH (54)</td><td>BMI at age 20 years</td><td>Per 5 kg/m²</td><td>0.95 (0.70-1.31)</td><td></td></tr><tr><td>BMI at age 20 years</td><td>Per 5 kg/m²</td><td>1.30 (1.08-1.58)</td><td></td></tr><tr><td></td><td>BMI</td><td>Obese vs Normal</td><td>1.64 (1.02-2.64)</td><td></td></tr><tr><td></td><td></td><td></td><td>Obese vs Normal</td><td>3.00 (0.60-14.97)</td><td></td></tr><tr><td></td><td></td><td></td><td>Per unit of BMI</td><td>1.07 (1.02-1.13)</td><td></td></tr><tr><td></td><td></td><td></td><td>Overweight (25-29.99) vs &lt; 25</td><td>1.09 (0.57-2.11)</td><td></td></tr><tr><td></td><td></td><td></td><td>Obese (≥30) vs &lt; 25</td><td>2.34 (1.1-4.67)</td><td></td></tr><tr><td rowspan="10">(Red and processed meat (Fernandez et al., 1997))</td><td rowspan="3">FH (112)</td><td>Red meat</td><td>High vs Low</td><td></td><td>2.9 (1.4-6.0)</td></tr><tr><td>Raw ham</td><td>High vs Low</td><td></td><td>2.1 (0.9-4.9)</td></tr><tr><td>Ham</td><td>High vs Low</td><td></td><td>2.6 (1.0-6.8)</td></tr><tr><td rowspan="6">(Sellers et al., 1998)</td><td rowspan="2">FH (61)</td><td>Canned meat</td><td>Intermediate/high vs Low</td><td></td><td>1.9 (1.0-3.3)</td></tr><tr><td>Red meat</td><td>> 7 vs ≤3.5 servings/week</td><td></td><td>1.0 (0.5-2.1)</td></tr><tr><td rowspan="2">No FH (180)</td><td>Total meat</td><td>> 15 vs ≤10 servings/week</td><td></td><td>0.8 (0.4-1.8)</td></tr><tr><td>Nitrate meat</td><td>> 1.5 vs ≤0.5 servings/week</td><td></td><td>0.8 (0.4-1.6)</td></tr><tr><td rowspan="3">(Le Marchand et al., 1999)</td><td rowspan="2">FH (M:90-F:72) combined</td><td>Red meat</td><td>> 7 vs ≤3.5 servings/week</td><td></td><td>1.3 (0.8-2.0)</td></tr><tr><td>Total meat</td><td>> 15 vs ≤10 servings/week</td><td></td><td>1.2 (0.8-1.9)</td></tr><tr><td></td><td>Nitrate meat</td><td>> 1.5 vs 0.5 servings/week</td><td></td><td>1.0 (0.7-1.4)</td></tr><tr><td></td><td></td><td>Beef</td><td>> 32.3 (FH) vs &lt; 13.8 (no FH) g/day</td><td>M</td><td>7.6 (3.0-19.0)</td></tr><tr><td></td><td></td><td></td><td>> 25.2 (FH) vs &lt; 11.9 (no FH) g/day</td><td>F</td><td>2.6 (1.0-6.8)</td></tr><tr><td rowspan="10">(Slattery et al., 2000)</td><td rowspan="3">No FH (M:603-F:420)</td><td>Processed meats</td><td>High (FH) vs &lt; Low (no FH)</td><td>M</td><td>4.5 (2.1-9.4)</td></tr><tr><td>Beef</td><td>High (FH) vs &lt; Low (no FH)</td><td>F</td><td>1.5 (0.6-3.7)</td></tr><tr><td>Processed meats</td><td>> 32.3 vs &lt; 13.8 g/day</td><td>M</td><td>1.4 (0.9-2.1)</td></tr><tr><td rowspan="2">FH (266) combined</td><td>Red meat</td><td>> 25.2 vs &lt; 11.9 g/day</td><td>F</td><td>0.9 (0.6-1.4)</td></tr><tr><td>Fast-food meat</td><td>High vs Low</td><td>M</td><td>1.8 (1.2-2.7)</td></tr><tr><td rowspan="3">No FH (1358)</td><td>Red meat</td><td>High vs Low</td><td>F</td><td>1.3 (0.8-2.1)</td></tr><tr><td>Fast-food meat</td><td>High (FH) vs Low (no FH)</td><td>Y</td><td>2.8 (1.0-7.8)</td></tr><tr><td>High vs Low</td><td>High (FH) vs Low (no FH)</td><td>I</td><td>2.4 (0.9-6.1)</td></tr><tr><td rowspan="3">(Slattery et al., 2000)</td><td>Red meat</td><td>High (FH) vs Low (no FH)</td><td>I</td><td>1.7 (0.9-3.1)</td></tr><tr><td>Fast-food meat</td><td>High (FH) vs Low (no FH)</td><td>Y</td><td>7.5 (2.0-28.1)</td></tr><tr><td>High vs Low</td><td>High (FH) vs Low (no FH)</td><td>I</td><td>2.5 (1.2-5.4)</td></tr><tr><td rowspan="3">(Slattery et al., 2000)</td><td>Red meat</td><td>High (FH) vs Low (no FH)</td><td>O</td><td>1.3 (0.9-2.3)</td></tr><tr><td>Fast-food meat</td><td>High (FH) vs Low (no FH)</td><td>Y</td><td>2.1 (0.7-5.9)</td></tr><tr><td>High vs Low</td><td>High (FH) vs Low (no FH)</td><td>I</td><td>1.8 (0.8-4.0)</td></tr><tr><td rowspan="3">(Slattery et al., 2000)</td><td>Red meat</td><td>High vs Low</td><td>O</td><td>1.3 (0.7-2.3)</td></tr><tr><td>Fast-food meat</td><td>High vs Low</td><td>Y</td><td>0.7 (0.4-1.3)</td></tr><tr><td>High vs Low</td><td>High (FH) vs Low (no FH)</td><td>I</td><td>1.1 (0.7-1.7)</td></tr><tr><td rowspan="3">(Slattery et al., 2000)</td><td>Red meat</td><td>High vs Low</td><td>O</td><td>1.2 (0.8-1.6)</td></tr><tr><td>Fast-food meat</td><td>High vs Low</td><td>Y</td><td>1.0 (0.6-1.8)</td></tr><tr><td>High vs Low</td><td>High (FH) vs Low (no FH)</td><td>I</td><td>1.3 (0.9-2.0)</td></tr><tr><td rowspan="3">(Slattery et al., 2000)</td><td>Red meat</td><td>High vs Low</td><td>O</td><td>1.2 (0.9-1.6)</td></tr><tr><td>Fast-food meat</td><td>High vs Low</td><td>O</td><td>1.2 (0.9-1.6)</td></tr></tbody></table>

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<table><caption>Table 2 (continued)</caption><thead><tr><th>First author, publication year (ref)</th><th>Family history of cancer (number of cases)</th><th>Nutritional factor</th><th>Comparison</th><th>Sub-group</th><th>OR, HR or RR (95% CI)</th></tr></thead><tbody><tr><td></td><td></td><td>Fast-food meat</td><td>High vs Low</td><td>Y</td><td>0.9 (0.5-1.5)</td></tr><tr><td></td><td></td><td></td><td></td><td>I</td><td>1.0 (0.7-1.5)</td></tr><tr><td></td><td></td><td></td><td></td><td>O</td><td>1.4 (1.0-1.9)</td></tr><tr><td>(Fernandez et al., 2002)</td><td>FH (112)</td><td>Red meat</td><td>≥5 vs ≤2 portions/week</td><td></td><td>3.2 (1.4-6.9)</td></tr><tr><td></td><td>No FH (1472)</td><td>Red meat</td><td>≥5 vs ≤2 portions/week</td><td></td><td>1.8 (1.5-2.2)</td></tr><tr><td>(Huang et al., 2004)</td><td>FH (124)</td><td>Beef</td><td>≥3 vs &lt; 3 times/week</td><td></td><td>0.97 (0.51-1.85)</td></tr><tr><td></td><td></td><td>Sausage</td><td>≥3 vs &lt; 3 times/week</td><td></td><td>0.86 (0.43-1.72)</td></tr><tr><td></td><td>No FH (1228)</td><td>Pork</td><td>≥3 vs &lt; 3 times/week</td><td></td><td>1.15 (0.61-2.15)</td></tr><tr><td></td><td></td><td>Beef</td><td>≥3 vs &lt; 3 times/week</td><td></td><td>0.94 (0.76-1.17)</td></tr><tr><td></td><td></td><td>Sausage</td><td>≥3 vs &lt; 3 times/week</td><td></td><td>1.11 (0.92-1.34)</td></tr><tr><td>(Diergaarde et al., 2007)</td><td>FH (145)</td><td>Pork</td><td>≥3 vs &lt; 3 times/week</td><td></td><td>1.07 (0.88-1.31)</td></tr><tr><td></td><td></td><td>Total meat</td><td>≥114.8 vs ≤73.3 g/day</td><td></td><td>1.0 (0.5-2.1)</td></tr><tr><td></td><td></td><td>Red meat</td><td>≥71.4 vs ≤46.2 g/day</td><td></td><td>0.8 (0.4-1.6)</td></tr><tr><td>(Joshi et al., 2015)</td><td>FH (243)</td><td>Total non-processed red meat</td><td>10.81-16.04 vs 0-10.81 g/<br>1000Kcal/day</td><td></td><td>0.9 (0.6-1.4)</td></tr><tr><td></td><td></td><td></td><td>16.04-21.11 vs 0-10.81 g/<br>1000Kcal/day</td><td></td><td>1.1 (0.7-1.7)</td></tr><tr><td></td><td></td><td></td><td>21.12-28.19 vs 0-10.81 g/<br>1000Kcal/day</td><td></td><td>1.0 (0.6-1.5)</td></tr><tr><td></td><td></td><td></td><td>28.19-102.43 vs 0-10.81 g/<br>1000Kcal/day</td><td></td><td>1.0 (0.6-1.7)</td></tr><tr><td></td><td></td><td>Processed red meat</td><td>3.97-6.74 vs 0-3.97 g/1000 kcal/<br>day</td><td></td><td>1.3 (0.9-2.0)</td></tr><tr><td></td><td></td><td></td><td>6.75-9.53 vs 0-3.97 g/1000 kcal/<br>day</td><td></td><td>0.9 (0.5-1.3)</td></tr><tr><td></td><td></td><td></td><td>9.53-13.86 vs 0-3.97 g/1000 kcal/<br>day</td><td></td><td>0.8 (0.5-1.3)</td></tr><tr><td></td><td></td><td></td><td>13.87-122.42 vs 0-3.97 g/<br>1000 kcal/day</td><td></td><td>1.1 (0.7-1.8)</td></tr><tr><td></td><td></td><td>Total processed meat (red meat + poultry)</td><td>4.43-7.35 vs 0-4.43 g/1000 kcal/<br>day</td><td></td><td>1.3 (0.8-1.9)</td></tr><tr><td></td><td></td><td></td><td>7.36-10.62 vs 0-4.43 g/1000 kcal/<br>day</td><td></td><td>1.1 (0.7-1.8)</td></tr><tr><td></td><td></td><td></td><td>10.63-15.29 vs 0-4.43 g/<br>1000 kcal/day</td><td></td><td>0.8 (0.5-1.3)</td></tr><tr><td></td><td></td><td></td><td>15.29-152.04 vs 0-4.43 g/<br>1000 kcal/day</td><td></td><td>1.2 (0.7-1.8)</td></tr><tr><td></td><td></td><td>Total pan-fried meat intake</td><td>0.05-0.12 vs 0-0.05 g/1000 kcal/<br>day</td><td></td><td>1.3 (0.9-2.0)</td></tr><tr><td></td><td></td><td></td><td>0.12-0.21 vs 0-0.05 g/1000 kcal/<br>day</td><td></td><td>1.3 (0.9-2.0)</td></tr><tr><td></td><td></td><td></td><td>0.21-5.96 vs 0-0.05 g/1000 kcal/<br>day</td><td></td><td>1.5 (1.0-2.3)</td></tr><tr><td></td><td></td><td>Total oven-broiled meat intake</td><td>0.01-0.05 vs 0-0 g/1000 kcal/day</td><td></td><td>0.8 (0.5-1.2)</td></tr><tr><td></td><td></td><td></td><td>0.05-0.1 vs 0-0 g/1000 kcal/day</td><td></td><td>0.8 (0.5-1.2)</td></tr><tr><td></td><td></td><td>Total grilled meat intake</td><td>0.1-3.97 vs 0-0 g/1000 kcal/day</td><td></td><td>1.3 (0.9-1.8)</td></tr><tr><td></td><td></td><td></td><td>0.01-0.07 vs 0-0 g/1000 kcal/day</td><td></td><td>1.0 (0.7-1.5)</td></tr><tr><td></td><td></td><td>Total non-processed red meat</td><td>0.07-0.15 vs 0-0 g/1000 kcal/day</td><td></td><td>1.1 (0.7-1.6)</td></tr><tr><td></td><td>FH (876)</td><td></td><td>0.15-4.97 vs 0-0 g/1000 kcal/day</td><td></td><td>1.0 (0.6-1.4)</td></tr><tr><td></td><td></td><td></td><td>10.81-16.04 vs 0-10.81 g/<br>1000Kcal/day</td><td></td><td>0.8 (0.6-1.0)</td></tr><tr><td></td><td></td><td></td><td>16.04-21.11 vs 0-10.81 g/<br>1000Kcal/day</td><td></td><td>1.0 (0.8-1.3)</td></tr><tr><td></td><td></td><td></td><td>21.12-28.19 vs 0-10.81 g/<br>1000Kcal/day</td><td></td><td>0.8 (0.7-1.1)</td></tr></tbody></table>

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<table><caption>Table 2 (continued)</caption><thead><tr><th>First author, publication year (ref)</th><th>Family history of cancer (number of cases)</th><th>Nutritional factor</th><th>Comparison</th><th>Sub-group</th><th>OR, HR or RR (95% CI)</th></tr></thead><tbody><tr><td rowspan="10"></td><td rowspan="10"></td><td rowspan="10">Processed red meat</td><td>1000Kcal/day</td><td></td><td>0.8 (0.6-1.0)</td></tr><tr><td>28.19-102.43 vs 0-10.81 g/</td><td></td><td></td></tr><tr><td>1000Kcal/day</td><td></td><td></td></tr><tr><td>3.97-6.74 vs 0-3.97 g/1000 kcal/</td><td></td><td>0.9 (0.7-1.2)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>6.75-9.53 vs 0-3.97 g/1000 kcal/</td><td></td><td>0.9 (0.7-1.1)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>9.53-13.86 vs 0-3.97 g/1000 kcal/</td><td></td><td>1.1 (0.8-1.4)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>13.87-122.42 vs 0-3.97 g/</td><td></td><td>1.1 (0.8-1.4)</td></tr><tr><td>1000 kcal/day</td><td></td><td></td></tr><tr><td>4.43-7.35 vs 0-4.43 g/1000 kcal/</td><td></td><td>1.0 (0.8-1.3)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>7.36-10.62 vs 0-4.43 g/1000 kcal/</td><td></td><td>0.9 (0.7-1.2)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>10.63-15.29 vs 0-4.43 g/</td><td></td><td>1.1 (0.9-1.4)</td></tr><tr><td>1000 kcal/day</td><td></td><td></td></tr><tr><td>15.29-152.04 vs 0-4.43 g/</td><td></td><td>1.2 (0.9-1.5)</td></tr><tr><td>1000 kcal/day</td><td></td><td></td></tr><tr><td>0.05-0.12 vs 0-0.05 g/1000 kcal/</td><td></td><td>1.0 (0.8-1.3)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>0.12-0.21 vs 0-0.05 g/1000 kcal/</td><td></td><td>1.0 (0.8-1.3)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>0.21-5.96 vs 0-0.05 g/1000 kcal/</td><td></td><td>1.1 (0.8-1.3)</td></tr><tr><td>day</td><td></td><td></td></tr><tr><td>0.01-0.05 vs 0-0 g/1000 kcal/day</td><td></td><td>1.1 (0.9-1.3)</td></tr><tr><td>0.05-0.1 vs 0-0 g/1000 kcal/day</td><td></td><td>1.0 (0.8-1.2)</td></tr><tr><td>0.1-3.97 vs 0-0 g/1000 kcal/day</td><td></td><td>1.1 (0.9-1.4)</td></tr><tr><td>0.01-0.07 vs 0-0 g/1000kcal/day</td><td></td><td>0.9 (0.8-1.2)</td></tr><tr><td>0.07-0.15 vs 0-0 g/1000kcal/day</td><td></td><td>0.9 (0.7-1.1)</td></tr><tr><td>0.15-4.97 vs 0-0 g/1000kcal/day</td><td></td><td>1.0 (0.8-1.2)</td></tr><tr><td>Medium vs Low</td><td></td><td>1.10 (0.75-1.62)</td></tr><tr><td>High vs Low</td><td></td><td>0.99 (0.65-1.52)</td></tr><tr><td rowspan="10"></td><td rowspan="10">Total processed meat (red meat + poultry)</td><td rowspan="10"></td><td>High vs None</td><td></td><td>0.89 (0.52-1.53)</td></tr><tr><td>High vs None</td><td></td><td>0.59 (0.49-0.72)</td></tr><tr><td>&gt; 7632 (FH) vs &lt; 1152 (no FH) h</td><td>M</td><td>2.6 (1.2-5.5)</td></tr><tr><td>&gt; 1152 (FH) vs 0 (no FH) h</td><td>F</td><td>2.1 (0.9-4.8)</td></tr><tr><td>&gt; 7632 vs &lt; 1152 h</td><td>M</td><td>0.6 (0.4-0.8)</td></tr><tr><td>&gt; 1152 vs 0 h</td><td>F</td><td>0.7 (0.5-1.1)</td></tr><tr><td>Low vs high</td><td></td><td>1.05 (0.53-2.07)</td></tr><tr><td>Low vs high</td><td></td><td>1.46 (1.20-1.77)</td></tr><tr><td>Low (FH) vs High (no FH)</td><td></td><td>2.64 (1.78-3.92)</td></tr><tr><td>Low vs High</td><td></td><td>1.71 (1.42-2.05)</td></tr><tr><td>≥3 vs &lt; 3 times/month</td><td></td><td>0.96 (0.64-1.44)</td></tr><tr><td>≥3 vs &lt; 3 times/month</td><td></td><td>0.76 (0.66-0.87)</td></tr><tr><td>Yes vs No</td><td></td><td>0.58 (0.40-0.86)</td></tr><tr><td rowspan="10"></td><td rowspan="10">Total pan-fried meat intake</td><td rowspan="10"></td><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical exercise</td><td></td><td></td></tr><tr><td>Physical exercise</td><td></td><td></td></tr><tr><td>Regular physical activity</td><td></td><td></td></tr><tr><td>Regular physical activity</td><td></td><td></td></tr><tr><td rowspan="5">(Kamiza et al., 2015)</td><td rowspan="5">FH (147)</td><td rowspan="5">FH (NA)</td><td rowspan="5">No FH (NA)</td><td>80th vs 20th percentiles</td><td></td><td>0.77 (0.43-1.38)</td></tr><tr><td>80th vs 20th percentiles</td><td></td><td>0.66 (0.58-0.76)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>1.2 (0.6-2.6)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>0.8 (0.5-1.2)</td></tr><tr><td>&gt; 20.1 (FH) vs 13.3 (no FH) g/</td><td>M</td><td>1.8 (0.8-4.2)</td></tr><tr><td rowspan="5">(Kamiza et al., 1997a)</td><td rowspan="5">FH (M:90-F:72) combined</td><td rowspan="5">(Le Marchand et al., 1999)</td><td rowspan="5">No FH (M:603-F:420)</td><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical exercise</td><td></td><td></td></tr><tr><td>Physical exercise</td><td></td><td></td></tr><tr><td rowspan="5">(La Vecchia et al., 1999)</td><td rowspan="5">FH (134)</td><td rowspan="5">No FH (1091)</td><td rowspan="5">FH (299) combined</td><td>80th vs 20th percentiles</td><td></td><td>0.77 (0.43-1.38)</td></tr><tr><td>80th vs 20th percentiles</td><td></td><td>0.66 (0.58-0.76)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>1.2 (0.6-2.6)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>0.8 (0.5-1.2)</td></tr><tr><td>&gt; 20.1 (FH) vs 13.3 (no FH) g/</td><td>M</td><td>1.8 (0.8-4.2)</td></tr><tr><td rowspan="5">(Slattery et al., 2003)</td><td rowspan="5">FH (124)</td><td rowspan="5">No FH (1978)</td><td rowspan="5">(Huang et al., 2004)</td><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td rowspan="5">(Kamiza et al., 2015)</td><td rowspan="5">FH (147)</td><td rowspan="5">FH (1228)</td><td rowspan="5">(Le Marchand et al., 1999)</td><td>80th vs 20th percentiles</td><td></td><td>0.77 (0.43-1.38)</td></tr><tr><td>80th vs 20th percentiles</td><td></td><td>0.66 (0.58-0.76)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>1.2 (0.6-2.6)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>0.8 (0.5-1.2)</td></tr><tr><td>&gt; 20.1 (FH) vs 13.3 (no FH) g/</td><td>M</td><td>1.8 (0.8-4.2)</td></tr><tr><td rowspan="5">(Sellers et al., 1998)</td><td rowspan="5">FH (61)</td><td rowspan="5">No FH (180)</td><td rowspan="5">(Le Marchand et al., 1999)</td><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time vigorous activity level</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Life time recreational physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td>Physical activity</td><td></td><td></td></tr><tr><td rowspan="5">(Negri et al., 1998)</td><td rowspan="5">FH (NA)</td><td rowspan="5">No FH (NA)</td><td rowspan="5">(Le Marchand et al., 1999)</td><td>80th vs 20th percentiles</td><td></td><td>0.77 (0.43-1.38)</td></tr><tr><td>80th vs 20th percentiles</td><td></td><td>0.66 (0.58-0.76)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>1.2 (0.6-2.6)</td></tr><tr><td>&gt; 22.59 vs ≤16.17 g/day</td><td></td><td>0.8 (0.5-1.2)</td></tr><tr><td>&gt; 20.1 (FH) vs 13.3 (no FH) g/</td><td>M</td><td>1.8 (0.8-4.2)</td></tr></tbody></table>

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<table><caption>Table 2 (continued)</caption><thead><tr><th>First author, publication year (ref)</th><th>Family history of cancer (number of cases)</th><th>Nutritional factor</th><th>Comparison</th><th>Sub-group</th><th>OR, HR or RR (95% CI)</th></tr></thead><tbody><tr><td rowspan="10">(Slattery et al., 2000)</td><td>No FH (M603-F:420)</td><td rowspan="3">NSP</td><td>day<br/>> 17.5 (FH) vs &lt; 13.0 (no FH) g/day</td><td>F</td><td>2.4 (0.9-6.4)</td></tr><tr><td rowspan="2">FH (266) combined</td><td>> 20.1 vs &lt; 13.3 g/day</td><td>M</td><td>0.6 (0.4-0.9)</td></tr><tr><td>> 17.5 vs &lt; 13.0 g/day</td><td>F</td><td>0.7 (0.5-1.1)</td></tr><tr><td rowspan="2">No FH (1358)</td><td>High (FH) vs Low (no FH)</td><td>Y</td><td>3.8 (1.1-12.7)</td></tr><tr><td>High vs Low</td><td>I</td><td>7.1 (2.4-20.6)</td></tr><tr><td>(Diergaarde et al., 2007)</td><td>FH (145)</td><td rowspan="3">Refined grains</td><td>High vs Low</td><td>O</td><td>1.6 (0.9-3.2)</td></tr><tr><td>(Mathers et al., 2012)</td><td>Lynch syndrome (53)</td><td>≥73.6 vs ≤34.0 g/day</td><td>Y</td><td>0.9 (0.5-1.8)</td></tr><tr><td rowspan="2">Dairy products (Fernandez et al., 1997)</td><td>Cereals</td><td>≥27.5 vs ≤22.6 g/day</td><td>I</td><td>1.5 (1.0-2.2)</td></tr><tr><td>(Sellers et al., 1998)</td><td>Lynch syndrome (53)</td><td>30 g/day vs placebo</td><td>O</td><td>1.4 (0.6-2.8)</td></tr><tr><td rowspan="10">(Huang et al., 2004)</td><td>No FH (180)</td><td rowspan="3">Resisted grains</td><td>High vs Low</td><td>O</td><td>0.5 (0.2-1.0)</td></tr><tr><td rowspan="2">FH (61)</td><td>≥73.6 vs ≤34.0 g/day</td><td>1.40 (0.78-2.56)</td><td></td></tr><tr><td>≥27.5 vs ≤22.6 g/day</td><td></td><td></td></tr><tr><td rowspan="2">FH (112)</td><td>Total calcium</td><td>Calcium</td><td>1.9 (0.9-4.2)</td><td></td></tr><tr><td rowspan="10">(Diergaarde et al., 2007)</td><td rowspan="2">No FH (180)</td><td>Cheese</td><td>High vs Low</td><td>3.5 (1.3-9.9)</td><td></td></tr><tr><td>Total calcium</td><td>> 1,296.6 vs ≤ 820.7 mg/day</td><td>1.2 (0.6-2.2)</td><td></td></tr><tr><td rowspan="2">FH (61)</td><td>Dietary calcium</td><td>> 964.7 vs ≤ 615 mg/day</td><td>0.8 (0.4-1.7)</td><td></td></tr><tr><td>Total dairy</td><td>> 20 vs ≤ 10 servings/week</td><td>0.7 (0.4-1.4)</td><td></td></tr><tr><td rowspan="2">No FH (180)</td><td>High fat dairy</td><td>> 9 vs ≤ 4.5 servings/week</td><td>0.7 (0.4-1.3)</td><td></td></tr><tr><td>Low fat dairy</td><td>> 7 vs ≤ 2.5 servings/week</td><td>0.9 (0.5-1.6)</td><td></td></tr><tr><td rowspan="2">FH (M90-F:72) combined</td><td>Total calcium</td><td>> 1,296.6 vs ≤ 820.7 mg/day</td><td>0.5 (0.3-0.7)</td><td></td></tr><tr><td>Dietary calcium</td><td>> 964.7 vs ≤ 615 mg/day</td><td>0.7 (0.4-1.0)</td><td></td></tr><tr><td rowspan="2">(Le Marchand et al., 1999)</td><td>Total dairy</td><td>> 20 vs ≤ 10 servings/week</td><td>0.7 (0.4-1.0)</td><td></td></tr><tr><td>High fat dairy</td><td>> 9 vs ≤ 4.5 servings/week</td><td>0.9 (0.6-1.3)</td><td></td></tr><tr><td rowspan="2">FH (M90-F:72) combined</td><td>Low fat dairy</td><td>> 7 vs ≤ 2.5 servings/week</td><td>0.8 (0.5-1.1)</td><td></td></tr><tr><td>Total calcium</td><td>> 907 (FH) vs &lt; 553 (no FH) mg/day</td><td>1.4 (0.6-3.0)</td><td></td></tr><tr><td rowspan="10">(Slattery et al., 2000)</td><td>No FH (M603-F:420)</td><td rowspan="3">Summary variable for lifestyle risk factors<sup>b</sup></td><td>> 1055 (FH) vs &lt; 521 (no FH) mg/day</td><td>F</td><td>1.2 (0.4-3.2)</td></tr><tr><td>FH (124)</td><td>> 907 vs &lt; 553 mg/day</td><td>M</td><td>0.7 (0.5-1.0)</td></tr><tr><td>No FH (1228)</td><td>> 1055 vs 521 mg/day</td><td>F</td><td>1.1 (0.7-1.7)</td></tr><tr><td rowspan="2">FH (145)</td><td>Milk</td><td>> 1/day vs &lt; 1/day</td><td></td><td>0.73 (0.50-1.06)</td></tr><tr><td>Milk</td><td>> 1/day vs &lt; 1/day</td><td></td><td>0.88 (0.78-0.99)</td></tr><tr><td rowspan="2">FH (266) combined</td><td>Calcium</td><td>> 1214.9 vs ≤972.1 mg/day</td><td></td><td>0.8 (0.4-1.6)</td></tr><tr><td>Dairy products</td><td>> 457.3 vs ≤245.7 g/day</td><td></td><td>1.6 (0.8-3.4)</td></tr><tr><td rowspan="10">(Fernandez et al., 2002)</td><td>No FH (1358)</td><td rowspan="3">Summary variable for lifestyle risk factors<sup>b</sup></td><td>Unhealthy (FH) vs Healthy (no FH)</td><td>M</td><td>11.7 (5.8-23.9)</td></tr><tr><td>FH (112) combined</td><td>Unhealthy vs Healthy</td><td>F</td><td>8.3 (4.1-17.0)</td></tr><tr><td>No FH (1472)</td><td>High (FH) vs Low (no FH)</td><td>M</td><td>4.8 (3.2-7.2)</td></tr><tr><td rowspan="2">FH (299) combined</td><td>Adult Life Dietary Risk Score<sup>b</sup></td><td>High vs Low</td><td>F</td><td>3.1 (1.9-5.2)</td></tr><tr><td>Adult Life Dietary Risk Score<sup>b</sup></td><td>High vs Low</td><td>Y</td><td>14.0 (3.9-50.1)</td></tr><tr><td rowspan="2">(Slattery et al., 2003)</td><td>Adult Life Dietary Risk Score<sup>b</sup></td><td>Low (FH) vs High (no FH)</td><td>I</td><td>7.7 (2.0-29.1)</td></tr><tr><td>Prudent diet</td><td></td><td>O</td><td>1.6 (0.8-3.2)</td></tr></tbody></table>

(continued on next page)
<table><caption>Table 2 (continued)</caption><thead><tr><th>First author, publication year (ref)</th><th>Family history of cancer (number of cases)</th><th>Nutritional factor</th><th>Comparison</th><th>Sub-group</th><th>OR, HR or RR (95% CI)</th></tr></thead><tbody><tr><td></td><td></td><td>Western diet</td><td>High (FH) vs Low (no FH)</td><td></td><td>3.59 (2.29–5.62)<br>Significant interaction between FH and Western diet (p multiplicative = 0.03)</td></tr><tr><td rowspan="4">(Fernandez et al., 2004)<br>(Turati et al., 2011)</td><td>No FH (1978)</td><td>Prudent diet</td><td>Low vs High</td><td></td><td>1.17 (0.97–1.42)</td></tr><tr><td>FH (134) combined</td><td>Western diet</td><td>High vs Low</td><td></td><td>1.45 (1.18–1.77)</td></tr><tr><td>No FH (1091)</td><td>Risk factor score<sup>b</sup></td><td>High (FH) vs Low (no FH)</td><td></td><td>7.08 (4.68–10.71)</td></tr><tr><td>FH (187) combined</td><td>Risk factor score<sup>b</sup></td><td>High vs Low</td><td></td><td>2.27 (1.89–2.73)</td></tr><tr><td></td><td></td><td>'Starch-rich' dietary pattern</td><td>High (FH) vs Low (no FH)</td><td>CRC</td><td>4.00 (3.03–5.27)</td></tr><tr><td></td><td></td><td>'Vitamins & fiber' dietary pattern</td><td>Low (FH) vs High (no FH)</td><td>CC</td><td>4.63 (3.39–6.31)</td></tr><tr><td rowspan="4">No FH (1766)</td><td rowspan="4"></td><td rowspan="4">'Starch-rich' dietary pattern</td><td rowspan="4">High vs Low</td><td>CRC</td><td>3.74 (2.85–4.91)</td></tr><tr><td>CC</td><td>3.89 (2.87–5.27)</td></tr><tr><td>RC</td><td>3.32 (2.24–4.94)</td></tr><tr><td>CRC</td><td>1.38 (1.19–1.61)</td></tr><tr><td></td><td></td><td></td><td></td><td>CC</td><td>1.42 (1.19–1.70)</td></tr><tr><td></td><td></td><td></td><td></td><td>RC</td><td>1.31 (1.05–1.64)</td></tr><tr><td></td><td></td><td></td><td></td><td>CRC</td><td>1.29 (1.12–1.48)</td></tr><tr><td></td><td></td><td>'Vitamins & fiber' dietary pattern</td><td>Low vs High</td><td>CC</td><td>1.19 (1.01–1.41)</td></tr><tr><td></td><td></td><td></td><td></td><td>RC</td><td>1.49 (1.21–1.82)</td></tr></tbody></table>

Abbreviations: NA: not available; M: males; F: females; T: tertiles; CC: colon cancer; RC: rectal cancer; Y: younger age i.e. ≤ 55 years; intermediate age i.e. 56–66 years; O: older age i.e. ≥ 67 years; FH: Family History; NSAIDs: non-steroidal anti-inflammatory drugs; NSP: non-starch polysaccharides; WHR: waist-to-hip ratio.

<sup>b</sup>For case-control studies only.

<sup>c</sup>The "Adult life dietary risk score" included red meatseasoning fats, β-carotene and ascorbic acid consumption, and daily meal frequency (Fernandez et al., 2002). The "Summary variable for lifestyle risk factors" included 13 lifestyle variables related to nutrition, smoking and physical activity (Le Marchand et al., 1999). The "Risk factor score" included education level, number of meal/day, occupational physical activity, and fiber, calcium and β-carotene intakes (Fernandez et al., 2004).
borderline significant increase of CRC risk was associated with pan-fried meat but not with other meat categories (non-processed red meat, processed red meat, total processed meats, oven-broiled meat and grilled meat); in the four other studies, there was no association for beef, pork or sausage studied separately (Huang et al., 2004), red meat (Diergaarde et al., 2007; Sellers et al., 1998), “nitrate meat” (Sellers et al., 1998) or total meat (Kamiza et al., 2015). In the three studies which also mentioned results obtained in subjects without FH of CRC (Huang et al., 2004; Joshi et al., 2015; Sellers et al., 1998), there was no association.

The modification of cancer risk associated with the combination of red meat or processed meat consumption and FH of CRC as compared to non-exposed subjects without FH, was examined in two studies (Slattery et al., 2000; Le Marchand et al., 1999): the combination was associated with a significant increased risk for beef (Le Marchand et al., 1999), processed meat in men (Le Marchand et al., 1999), and processed meat in young and intermediate age subjects (Slattery et al., 2000); it was associated with a borderline significant increased risk for red meat in younger subjects (Slattery et al., 2000) and beef in women (Le Marchand et al., 1999). A significant interaction was reported between FH of CRC, beef and CRC risk in men (Le Marchand et al., 1999). These studies also mentioned results obtained in subjects without FH of CRC: an increased risk was observed only for processed meat in men (Le Marchand et al., 1999) and for fast-food meat in older subjects (Slattery et al., 2000).

### 3.3. Protective factors

The nutritional factors known to decrease CRC risk in the general population with a level of evidence graded as convincing or probable are physical activity, foods containing dietary fiber, and milk and dairy products (WCRF/AICR, 2011; Latino-Martel et al., 2016; WCRF/AICR, 2017).

#### 3.3.1. Physical activity

Five case-control articles (Le Marchand et al., 1999; Huang et al., 2004; Slattery et al., 2003; Slattery et al., 1997a; La Vecchia et al., 1999) and one retrospective cohort study on MMR gene mutation carriers (Kamiza et al., 2015) provided results on physical activity (total, regular, recreational, vigorous activity level, frequency or duration) and CRC risk. An overlap between samples of two articles (Slattery et al., 2003; Slattery et al., 1997a) could not be excluded (cf. Table 1).

The retrospective cohort study reported a significant decrease of CRC associated with regular physical activity (Kamiza et al., 2015). Three case-control studies (Huang et al., 2004; Slattery et al., 1997a; La Vecchia et al., 1999) reported no association between physical activity and CRC risk in subjects with FH of CRC, whereas they mentioned a significant inverse association in subjects without FH of CRC.

The modification of cancer risk associated with the combination of physical activity and FH of CRC as compared to non-exposed subjects without FH, was examined in two studies (Le Marchand et al., 1999; Slattery et al., 2003): the combination was associated with a significant decreased risk in one study (Slattery et al., 2003), and surprisingly with an increased risk in men, but not in women, in the other study (Le Marchand et al., 1999). These studies also mentioned results obtained in subjects without FH of CRC, i.e. an inverse association in the population of the first study with a lower size of effect (Slattery et al., 2003), and in men but not in women in the second study (Slattery et al., 2003).

#### 3.3.2. Dietary fiber

Five articles, three from case-control studies (Le Marchand et al., 1999; Diergaarde et al., 2007; Negri et al., 1998) including one study on subjects fulfilling the Amsterdam criteria for HNPCC (Diergaarde et al., 2007), one from a women cohort (Sellers et al., 1998) and one from an intervention study on individuals with LS (Mathers et al., 2012), provided results on dietary fiber (total, non-starch polysaccharides or

resistant starch) and CRC risk.

The analyses concerned subjects with FH of CRC in three studies: no association between dietary fiber and CRC risk was observed in one case-control study (Negri et al., 1998) and the cohort study (Sellers et al., 1998), whereas a borderline significant decrease was reported in one case-control study (Diergaarde et al., 2007). No association was observed with cereals (Diergaarde et al., 2007). In the intervention study, a high daily intake of resistant starch (30 g) for up to four years had no effect on CRC risk compared to placebo in subjects with LS (Mathers et al., 2012).

In one study (Le Marchand et al., 1999) the combination of non-starch polysaccharide and FH of CRC as compared to non-exposed subjects without FH, was not associated with CRC risk, whereas a decreased risk was observed in subjects without FH, in men but not in women.

Conversely, in one additional case-control study (Slattery et al., 2000), high intake of refined grains combined with FH of CRC increased CRC risk in young and intermediate age subjects.

#### 3.3.3. Dairy products

Five articles, four from case-control studies (Fernandez et al., 1997; Le Marchand et al., 1999; Huang et al., 2004; Diergaarde et al., 2007) including one study on subjects fulfilling the Amsterdam criteria for HNPCC (Diergaarde et al., 2007), and one from a women cohort study (Sellers et al., 1998), provided results on dairy products (total dairy, milk, cheese, calcium) and CRC risk.

The analyses concerned subjects with FH of CRC in four studies: no association was observed for dairy products (total, high fat or low fat), milk, and total, dietary or supplemental calcium intake (Fernandez et al., 1997; Huang et al., 2004; Diergaarde et al., 2007; Sellers et al., 1998); a significant increased risk of CRC was reported in one study for high cheese consumption (Fernandez et al., 1997). Three studies mentioned also results in subjects without FH: a decreased risk associated with milk (Huang et al., 2004) and total dairy products (Sellers et al., 1998); a borderline significant decreased risk (Sellers et al., 1998) or no association (Le Marchand et al., 1999) for calcium.

In one study (Le Marchand et al., 1999) the combination of total calcium intake and FH of CRC as compared to non-exposed subjects without FH, was not associated with CRC risk; no association with total calcium intake was observed in subjects without FH of CRC.

#### 3.3.4. Dietary patterns and dietary risk factor scores

For the general population, the level of evidence of the association between dietary patterns and CRC risk has been judged as “limited-no conclusion” (WCRF/AICR, 2011).

The present systematic review permitted to identify six articles from case-cohort studies estimating the association between either dietary patterns (Slattery et al., 2000; Slattery et al., 2003; Turati et al., 2011), with a potential overlap between two articles (Slattery et al., 2000; Slattery et al., 2003) (cf. Table 1), or integrative dietary variables or scores (Le Marchand et al., 1999; Fernandez et al., 2002; Fernandez et al., 2004) in combination with FH of CRC, as compared to non-exposed subjects without FH (cf. Table 2): the combination was associated with a strong significant increase of CRC risk (risk estimate comprised between 2.7 and 14, according to studies), for subjects with high compliance with Western (Slattery et al., 2000; Slattery et al., 2003) or starch-rich (Turati et al., 2011) dietary patterns, or low compliance with prudent (Slattery et al., 2000) or vitamins and fiber rich (Turati et al., 2011) dietary patterns, or for subjects with “unhealthy” dietary lifestyles estimated by a higher summary variable of lifestyle risk (Le Marchand et al., 1999), adult life dietary risk score (Fernandez et al., 2002), or risk factor score (Fernandez et al., 2004). A significant interaction between FH of CRC, Western diet and risk of CRC was reported in one article (Slattery et al., 2003), and between FH of CRC, age Western diet and risk of colon cancer in another one (Slattery et al., 2000). All studies reported similar results in subjects without FH, the
size of the effect being about two to five times smaller.

### 3.4. Other factors

Fourteen articles, nine from case-control (Slattery et al., 2000; Fernandez et al., 1997; Le Marchand et al., 1999; Huang et al., 2004; Diergaarde et al., 2007; Fernandez et al., 2002; La Vecchia et al., 1999; Slattery et al., 1997b,c), two from retrospective cohort studies (Kamiza et al., 2015; Chau et al., 2016) and three from prospective cohort studies (two of which were restricted to women) (Fuchs et al., 2002; Sellers et al., 1998; Jung et al., 2014) provided data on other nutritional factors, i.e. foods/beverages or single nutrients not associated with CRC risk in the general population, with a convincing or probable level of evidence (WCRF/AICR, 2011). Analyses concerned subjects with FH in nine articles (Fernandez et al., 1997; Huang et al., 2004; Diergaarde et al., 2007; La Vecchia et al., 1999; Fuchs et al., 2002; Sellers et al., 1998; Jung et al., 2014; Kamiza et al., 2015; Chau et al., 2016), and the combinations of nutritional factors and FH of CRC in seven articles (Latino-Martel et al., 2016; Slattery et al., 2000; Le Marchand et al., 1999; Fernandez et al., 2002; Slattery et al., 1997b; Slattery et al., 1997c; Fuchs et al., 2002). For each factor, very few studies were available. Results are presented in the Supplemental Table 1. For most of these factors, results are not significant or not consistent between studies. Significant and consistent results were observed only for two cohort studies, one prospective population-based and one retrospective in LS individuals, suggesting a decrease of CRC risk in subjects with FH of CRC associated with multivitamin supplement use (Fuchs et al., 2002; Chau et al., 2016).

### 4. Discussion

This is the first systematic review of the association between nutritional factors and familial CRC risk. We have identified few studies and most of them have a retrospective design. The scientific literature is thus rather limited, as compared with the numerous epidemiological studies and meta-analyses available for nutritional factors and sporadic CRC in the general population (WCRF/AICR, 2011; Latino-Martel et al., 2016; WCRF/AICR, 2017).

Our qualitative analysis provides evidence that combinations of FH of CRC and higher consumptions of alcoholic beverages, red or processed meat, or overweight/obesity increase considerably the risk of CRC. At least, five articles from four independent studies reported that the risk of CRC observed for the combination 'alcoholic beverages plus FH of CRC' was higher than the one observed for FH alone (Kune et al., 1989; Kato et al., 1990; Fernandez et al., 2002; Cho et al., 2012; Fuchs et al., 2002), suggesting that the joint effect is not driven by the effect of FH only. Moreover, statistically significant interactions with FH of CRC were reported for alcohol in men (Le Marchand et al., 1999) and in women (Fuchs et al., 2002), for beef in men (Le Marchand et al., 1999), and for Western diet (Slattery et al., 2000; Slattery et al., 2003), especially in one study where the interaction was qualified as multiplicative, the combined effect being higher than the product of individual effects (Slattery et al., 2003). Such potential multiplicative interactions between nutritional risk factors and FH of CRC deserve to be further studied in other studies.

In contrast, no significant association was observed between the combinations of FH of CRC and individual factors like physical activity, dietary fiber or dairy products, and the risk of CRC. The number of studies was very low (one or two), thus to confirm the absence of association or not, further studies are needed.

In subjects with FH of CRC, the CRC risk estimates for the exposures to each of these nutritional factors alone (not combined with FH of CRC) were mostly not significant, excepted for overweight/obesity. The absence of association could be due either to the very low number of subjects with FH not exposed, in the reference group, or to a low independent effect (from HF of CRC) of the nutritional exposures. In

contrast with the other nutritional risk factors, the effect observed with overweight/obesity in most studies suggests that it is independent of FH of CRC. Concerning the sole intervention study identified, testing the effect of resistant starch in LS patients, the absence of association observed suggests that chemoprevention by this nutritional factor may not be a promising approach actually.

Overall, results related to individuals with LS (Diergaarde et al., 2007; Campbell et al., 2007; Joshi et al., 2015; Dashti et al., 2016; Movahedi et al., 2015; Jung et al., 2014; Kamiza et al., 2015; Win et al., 2011; Chau et al., 2016; Mathers et al., 2012) did not clearly differ from those related to individuals with family history in first degree relatives. We did not identify any discrepancy according to the population country or ethnicity. Sometimes, contrasted results according to gender or age group were reported, but they should be confirmed by additional studies.

Consistently with the results observed for alcoholic beverages, red or processed meat, or overweight/obesity, separately, the combination of unhealthy dietary patterns/lifestyles and FH of CRC strongly increased the risk of CRC. This important effect was observed even if the indicators were heterogeneous, i.e. including 3–13 food/beverage/nutrient variables (Slattery et al., 2000; Le Marchand et al., 1999; Diergaarde et al., 2007; Slattery et al., 1997a; Turati et al., 2011), other nutritional factors like physical activity (Le Marchand et al., 1999; Fernandez et al., 2004), energy and BMI (Le Marchand et al., 1999), daily meal frequency (Fernandez et al., 2002; Fernandez et al., 2004), smoking (Le Marchand et al., 1999) and education level (Fernandez et al., 2004).

In the general population, it has already been observed that high adherence to a Western or a healthy dietary pattern modifies CRC risk (Magalhães et al., 2012; Kyro et al., 2013). For instance, in the recent meta-analysis of Feng et al. including 40 observational studies (Feng et al., 2017), a western dietary pattern was associated with an increased risk of CRC (OR = 1.40; CI 95% = 1.26–1.56; P < 0.00001), and conversely a healthy dietary pattern was associated with a decreased risk (OR = 0.75; CI 95% = 0.68–0.83; P < 0.00001). In comparison, as emphasized by our qualitative analysis, the joint effect of FH of CRC and unhealthy dietary patterns/scores is associated with a strong increase of CRC risk, the risk estimate ranging from 2.7 to 14. This indicates that, in agreement with real life, combined nutritional factors may be more efficient against CRC risk than isolated ones. This also suggests that, in subjects with FH or CRC who are exposed to multiple nutritional risk factors, the probability that one (or several) risk factor (s) interact/act in synergy with one (or several) specific inherited genetic polymorphism(s) or single mutation(s) is very high. Although family history of disease is generally used as a proxy of genetic predisposition to the disease in patients who have not been unequivocally characterized as genetically susceptible, familial cancers could result from inherited genes (either penetrant inherited syndromes or low-penetrance genes), shared environmental/lifestyle factors, or some combination of these. In particular, interactions between genetic polymorphisms and dietary risk factors have already been reported (Druesne-Pecollo et al., 2009; Hu et al., 2015; Baroudi and Benammar-Elgaaied, 2016).

As documented by population-based studies (Townsend et al., 2013; Bostean et al., 2013; Martinez-Ochoa et al., 2012; Touvier et al., 2014) or surveys in medical services (Akhtar et al., 2008; Bronner et al., 2013; Anderson et al., 2016) from different countries, people with a FH of cancer including FH of CRC generally do not adopt healthy behaviors such as decrease of alcohol consumption, healthy dietary habits, weight control, or more physical activity and they have lower adherence to recommendations than the general population. Behaviors may differ depending on prevalent exposures in each country, but in some populations they may be worrying: for instance, it has been reported that Californian men with FH of CRC (N = 1538) were less likely to maintain a healthy weight and consume five or more servings of fruits and vegetables than those without FH (Townsend et al., 2013); French
women with family history of cancer (N = 8970) consumed more alcohol than women without such family history (p = 0.009) (Touvier et al., 2014).

A higher prevalence of unhealthy behaviors may reflect a process of intergenerational transmission of lifestyle behaviors. Another hypothesis could be that subjects are unaware of the relevance of improving their lifestyle behaviors (Akhtar et al., 2008), or if aware of it that they are unable to implement healthy changes. Recently, in-depth interviews revealed that lifestyle advice would be welcome by patients with family history of cancer, but that endorsement requires a sensitive and flexible approach (Anderson et al., 2016). Furthermore, people who perceive themselves to be at high risk for hereditary CRC are more likely to engage in health protective behaviors.

Until now, guidelines for familial CRC risk have only pointed at early diagnosis efforts via screening tests and surveillance (Zlot et al., 2012; Vasen et al., 2009; Cairns et al., 2010). Unfortunately, they payed scarce or no attention to the reduction of CRC risk by lowering exposure to risk factors. Therefore, based on this review of the literature, we recommend to reinforce health professionals and patients' knowledge on nutritional modifiable risk factors

To improve cancer prevention in the general population three main objectives have been defined: to reduce alcoholic beverages consumption, to have a balanced and diversified diet and to be physically active (Latino-Martel et al., 2016). For people with FH of CRC, this updated state of knowledge emphasizes the importance to address notably high consumption of alcoholic beverages, red or processed meat, and overweight/obesity, and more largely the exposure to multiple unhealthy dietary/nutritional behaviors. It must be noted that the reduction of overweight and obesity can be divided in two objectives “to have a balanced and diversified diet” and “to be physically active” (Latino-Martel et al., 2016). Therefore, the three main objectives defined for the general population also make sense for individuals with FH or CRC.

## 5. Strengths and limitations of the review

The presented study has several methodological strengths, namely 1) the focused review question; 2) a comprehensive and systematic literature search; 3) the use of explicit and reproducible eligibility criteria; and 4) selection and extraction of data in duplicate.

Concerning limitations, this systematic review did not provide a quantitative evaluation of data. Moreover, epidemiological data were mainly obtained from retrospective studies which are prone to recall bias. The included studies had other obvious limits: low number of subjects with FH of CRC, and heterogeneity according to the exposure categories, and/or adjustment variables. In addition, several studies were based on potentially overlapping populations which made it difficult to summarize the current findings for some factors.

One publication which mentioned a result concerning alcohol use and CRC risk in patients with LS could not be included since the risk estimate was not provided (Watson et al., 2004). More generally, although our systematic review was comprehensive, a publication bias could not be excluded.

## 6. Research needs

Based on this systematic review, it clearly appears that well designed studies are warranted to allow a quantitative evaluation by meta-analysis. In particular, more population-based prospective cohort studies with large sample size, precise reporting of nutritional factors and other lifestyle factors as in the NutriNet-Santé cohort (Touvier et al., 2014), and sufficient follow-up are needed to better investigate the interaction between FH of CRC and lifestyle factors on CRC risk. Since associations may differ between men and women, the influence of gender should be further investigated. Interaction between nutritional factors and subcategories of FH of CRC, i.e. family history of early-onset CRC, could also be studied. Since the mechanisms of such interactions

are still unknown, they could be studied using a nutrigenomic approach. In addition, more prospective cohort studies of LS individuals or MMR gene mutation carriers are needed.

## 7. Conclusions

We have reviewed available studies on nutritional factors and familial CRC risk. This review provides evidence for an increased risk of CRC resulting from a joint effect of FH of CRC and some nutritional risk factors: alcoholic beverages, red or processed meat, and overweight/obesity. Moreover, the combinations of unhealthy dietary patterns/lifestyles and FH of CRC strongly increase the risk of CRC. Although limited, these data are consistent. Therefore, addressing these modifiable nutritional risk factors offers new perspectives of prevention to subjects with moderate or high risk of CRC that henceforward should be integrated in guidelines for familial CRC. Health professionals are strongly encouraged to communicate them to relatives of CRC patients.

This review also shows that other data are inconclusive and it highlights the need for additional prospective studies.

## Funding

The NACRe Network is financially supported by the French National Cancer Institute (INCa) and the not-for-profit ARC Foundation for research on cancer (Fondation ARC). The views expressed in this publication do not necessarily represent the position of these organizations.

## Conflicts of interest

None of the author had a financial relationship to disclose.

## Authorship

AF, NDP and PLM designed the literature search strategy; AF and PLM performed the study selection; AF performed data extraction and PLM verified data extraction; AF and PLM analyzed the literature and wrote the draft of the manuscript. AF, NDP, MT and PLM contributed to the data interpretation, read and approved the final manuscript.

## Acknowledgements

The authors thank Emilie Barrandon and Juliette Bigey, and Christel Courcelle and Julie Ginhac, from the NACRe network, for their contribution to editing abstracts and obtaining full text articles, and to selecting abstracts according to inclusion criteria, respectively.

## Appendix A. Supplementary data

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.critrevonc.2017.09.001.

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