Table 1.
The characteristics of included studies and involved participants
| Study | Region | Sample size | Age (years) | Sex | Exposure definition | Comparisons | Follow-up (years) | Adjustment factors | Outcome | Study quality |
|---|---|---|---|---|---|---|---|---|---|---|
| Nomura 1990 (JAH) [23] | USA | 7,990 | ≥ 18 | Men and women | FFQ | Quintiles | 17.5 | Age | GC | 6 |
| Bostick 1994 (IWHS) [24, 25] | USA | 35,216 | 55–69 | Women | FFQ | Quintiles | 5.0 | Age, EI, height, parity, vitamin E, vitamin A | CC, PC | 8 |
| Kato 1997 (NYUWHS)[26] | USA | 14,727 | 34–65 | Women | FFQ | Quartiles | 7.1 | Age, EI, history of rectal colon polyps | CRC | 6 |
| Singh 1998 (AHS) [27] | USA | 32,051 | ≥ 25 | Men and women | FFQ | Median | 6.0 | Age, sex, BMI, PI,parental history of CC, smoking,alcohol, aspirin use | CC | 7 |
| Galanis 1998 (JRH) [28] | USA | 11,907 | ≥ 18 | Men and women | FFQ | Median | 14.8 | Age, education, Japanese place of birth, smoking,alcohol | GC | 7 |
| Knekt 1999 (FMCHES)[29, 30] | Finland | 9,985 | 15–99 | Men and women | Dietary history | Quartiles | 24.0 | Age, sex, municipality, smoking, EI | CRC, GC, CC, RC | 6 |
| Pietinen 1999 (ATBC) [31, 32] | Finland | 27,111 | 50–69 | Men | FFQ | Quartiles | 8.0 | Age, supplement group, smoking, BMI,alcohol,education, PA, calcium intake | CRC, PC | 9 |
| Isaksson 2002 (STR) [33] | Sweden | 21,884 | 56 | Men and women | FFQ | Tertiles | 16.0 | Age, sex, smoking | PC | 6 |
| Flood 2003 (BCDDP) [34] | USA | 45,496 | 61.9 | Women | FFQ | Quintiles | 8.5 | EI, total meat intake | CRC | 8 |
| Michaud 2003 (NHS)[25] | USA | 88,802 | 30–55 | Women | FFQ | Quintiles | 18.0 | Age, smoking, BMI, history of diabetes,EI, height, PA,menopausal status | PC, RC, CC, CRC, HCC | 8 |
| Lin 2004 (WHS) [36] | USA | 37,547 | ≥ 45 | Women | FFQ | Quintiles | 8.7 | Age, random treatment assignment, BMI,family history of CRC,history of colorectal polyps, PA, smoking,alcohol, HRT,EI | CRC | 8 |
| Wei 2004 (HPFS) [37–40] | USA | 46,632 | 40–75 | Men | FFQ | Quintiles | 14.0 | Age, family history,BMI, PA,alcohol, calcium intake, folate intake,height, smoking,history of endoscopy,beef/pork/lamb as amain dish | RC, CC, CRC, HCC | 8 |
| English 2004 (MCCS) [41] | Australia | 37,112 | 27–75 | Men and women | FFQ | Quartiles | 9.0 | Age, sex, country of birth, EI, fat intake, cereal product intake | CRC, RC, CC | 9 |
| Chao 2005 (CPS II) [42, 43] | USA | 148,610 | 50–74 | Men and women | FFQ | Quintiles | 9.0 | Age, EI,education, BMI,smoking, PA, multivitamin use, aspirin use, beer,wine,liquor, HRT,fruit intake, vegetable intake, high-fiber grain food intake | RC, CC, PC | 9 |
| Larsson 2005 (SMC) [44–46] | Sweden | 61,433 | 40–75 | Women | FFQ | Quartiles | 13.9 | Age, BMI, education, EI, alcohol, saturated fat intake, calcium intake, folate intake, fruit intake, vegetable intake, whole-grain food intake | CRC, RC, GC, PC | 7 |
| Norat 2005 (EPIC) [47, 51] | Europe | 478,040 | 21–83 | Men and women | FFQ | Quintiles | 4.8 | Age, sex, center,EI,height, weight,PA,smoking, dietary fiber intake, alcohol intake | CRC, RC, CC, GC, EC, PC, HCC | 9 |
| Sauvaget 2005 (LSS) [52] | Japan | 38,576 | 34–98 | Men and women | FFQ | Tertiles | 20.0 | Age, sex, city, radiation dose, smoking, education | GC | 7 |
| Nöthlings 2005 (MEC) [53–55] | USA | 190,545 | 45–75 | Men and women | FFQ | Quintiles | 7.0 | Age, sex, ethnicity, history of diabetes,family history of PC,smoking, EI | PC, CRC | 8 |
| Berndt 2006 (CLUE II) [56] | USA | 1,583 | 48.5 | Men and women | FFQ | Tertiles | 13.5 | Age, race, EI | CRC | 6 |
| Kabat 2007 (CNBSS) [57] | Canada | 49,654 | 40–59 | Women | FFQ | Quintiles | 16.4 | Age, BMI, menopausalstatus, OC use, HRT,dietary fat intake, fiber intake, folic acid intake, EI,smoking, alcohol, education, PA | CRC, RC, CC | 7 |
| Cross 2007 (NIH-AARP) [58–63] | USA | 494,036 | 50–71 | Men and women | FFQ | Quintiles | 8.2 | Age, sex, education, marital status, family history of cancer, race, BMI, smoking, PA, EI, alcohol, fruit and vegetable intake | ES, GC, CRC, HCC, PC | 9 |
| Butler 2008 (SCHS) [64, 65] | Singapore | 61,321 | 45–74 | Men and women | FFQ | Quartiles | 10.0 | Age, sex, dialect group,interview year, history of diabetes, smoking,BMI, alcohol,education, PA, family history of CRC, EI | CRC, HCC | 8 |
| Lee 2009 (SWHS) [66] | China | 73,224 | 40–70 | Women | FFQ | Quintiles | 7.4 | Age, education,income, survey season,tea intake, NSAID use,EI, fiber intake | CRC, RC, CC | 8 |
| Heinen 2009 (NLCS) [67-69 | Netherlands | 3,980 | 55–69 | Men and women | FFQ | Quintiles | 13.3 | Age, energy intake, sex, smoking, alcohol, history of diabetes, history of hypertension, BMI,vegetable intake, fruit intake | PC, GC, EC, CRC, RC, CC | 7 |
| Wie 2014 (CSEC) [70] | Korea | 8,024 | 48.4 | Men and women | 3-days food records | Median | 7.0 | Age, sex, EI, BMI, PA,smoking,alcohol use, income,education, marital status | CRC, GC | 7 |
| Nomura 2016 (BWHS) [71, 72] | USA | 49,103 | 21–69 | Women | FFQ | Tertiles | 15.1 | Age, geographic regionof residence, EI, smoking, family history of CRC, education,menopausal status,diabetes, insulin use,aspirin use,colonoscopy, sigmoidoscopy, alcohol, BMI | CRC, CC, PC | 8 |
| Hastert 2016 (VITAL) [73] | USA | 66,920 | 50–76 | Men and women | FFQ | Median | 7.6 | Age, education,race/ethnicity, receipt of colonoscopy orsigmoidoscopy, family history of CC or RC, NSAID use, history of cancer other than CRC, EI | CRC | 7 |
| Jones 2017 (UKWCS) [74] | UK | 32,154 | 52 | Women | FFQ | Quintiles | 17.4 | Age, BMI, EI, PA, smoking,socioeconomic status,family history of CRC | CRC, RC, CC | 8 |
| Wada 2017 (Takayama) [75] | Japan | 30,331 | ≥ 35 | Men and women | FFQ | Quartiles | 16.0 | Age, height, BMI,PA,smoking, education,aspirin use, alcohol, fiber intake,calcium intake, vitamin D intake, EI | CRC, RC, CC | 7 |
| Pang 2018 (CKB) [76] | China | 512,891 | 30–79 | Men and women | FFQ | Median | 9.0 | Age, sex, study area, education, smoking,alcohol, BMI, PA | PC | 8 |
| Diallo 2018 (NSS) [77, 78] | France | 61,476 | ≥ 35 | Men and women | 24-hour dietary records | Quintiles | 4.1 | Age, sex, EI,alcohol, number of 24-hour dietary records, smoking,education, PA, height, BMI,family history of cancer, lipids intake,fruit intake, vegetable intake, number of children, red meat intake, processed meat intake | CRC | 7 |
| Islam 2019 (pooled 6 studies) [79, 80] | Japan | 232,403 | 40–79 | Men and women | FFQ | Quartiles | ≥ 10.0 |
Age, area, history of diabetes, BMI,smoking, alcohol, PA, EI, calcium intake, fiber intake |
CRC, RC, CC | 7 |
| Mehta 2020 (Sister study) [81] | USA and Puerto Rico | 48,704 | 35–74 | Women | FFQ | Quartiles | 8.7 | EI, BMI,education, PA, race/ethnicity,family history of CRC | CRC, RC, CC | 7 |
| Nguyen 2020 (SMHS) [82] | China | 60,161 | 40–74 | Men | FFQ | Quartiles | 8.1 | Sex, age, education,income levels,smoking, alcohol intake,multivitamin use, family history ofCRC, BMI, PA, EI,metabolic condition | CRC, RC, CC | 8 |
| Barrubes 2020 (PREDIMED) [83] | Spain | 7,216 | 55–80 | Men and women | FFQ | Quartiles | 6.0 | Age, sex, intervention group, smoking, family history of cancer,education, history of diabetes, EI,aspirin use, weight, PA, plant food intake, fast food and processed food intake, sugar-sweetened beverage intake, alcohol | CRC | 6 |
| O’Sullivan 2020 (ATP) [84] | Canada | 26,460 | 50.9 | Men and women | Diet history questionnaire | Tertiles | 13.2 | Age, sex, BMI, fruit and vegetable intake,alcohol, PA, smoking,ethnicity, household income, education,family history of CRC, red or processed meat intake | CRC | 7 |
| Mejborn 2020 (DNSDPA) [85] | Denmark | 6,282 | 54.0 | Men and women | 7-day pre-coded food diaries | Tertiles | 10.8 | Sex, education,ethnicity, smoking,PA,alcohol, BMI,EI | CRC | 6 |
| Zhang 2020 (PLCO) [86] | USA | 95,962 | 55–74 | Men and women | Diet history questionnaire | Tertiles | 8.9 | Age, sex, race, education, smoking, aspirin use, history of diabetes, family history of PC, EI,PA, weight, diet rich in whole grains,vegetables, fruit, and beans, ultra-processed food intake, sugar-sweetened drink intake,alcohol, breastfeeding | PC | 9 |
| Knuppel 2020 (UK Biobank) [87–90] | UK | 474,996 | 37–73 | Men and women | FFQ | Quintiles | 6.9 | Age, region, ethnicity, deprivation,qualification, employment, living with spouse/partner, height, smoking, PA, alcohol, fruit and vegetable intake, cereal fiber intake, cheese intake,milk added to tea/coffee/cereal, oily fish intake, non-oily fish intake, menopausal status, parity, HRT, OC use | EC, GC, CRC, CC, RC, HCC, PC | 8 |
| Collatuzzo 2022 (GCS) [91] | Iran | 50,045 | 40–75 | Men and women | FFQ | Quintiles | 12.0 | Age, sex, BMI, ethnicity, place of residence, education and hot tea consumption | PC, EC, GC | 7 |
*AHS Adventist Health Study, ATBC Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study, ATP Alberta’s Tomorrow Project, BCDDP Breast Cancer Detection Demonstration Project, BMI Body mass index, CC Colon cancer, CKB China Kadoorie Biobank, CNBSS Canadian National BreastScreening Study, CRC Colorectal cancer, CSEC CancerScreening Examination Cohort of the National Cancer Centerof Korea, EI Energy intake, EPIC European Prospective Investigation into Cancerand Nutrition, FFQ Food-frequency questionnaire, GC Gastric cancer, GCS Golestan Cohort Study, HPFS Health Professionals Follow Up Study, HRT Hormone replacement therapy, IWHS Iowa Women’s Health Study, JAH Japanese Ancestry in Hawaii, JRH Japanese residents of Hawaii, LSS Life Span Study, MCCS Melbourne Collaborative Cohort Study, MEC Multiethnic Cohort Study, NHS Nurses’ Health Study, NIH-AARP National Institutes of Health-American Association for Retired Persons, NLCS Netherlands Cohort Study, NSS NutriNet-Sante Study, NYUWHS New York University Women’s Health Study, PA Physical activity, PC Pancreatic cancer, PLCO Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, PREDIMED Spanish PREvencion con DIeta MEDiterranea, RC Rectal cancer, SCHS Singapore Chinese Health Study, SMC Swedish Mammography Cohort, STR Swedish Twin Registry, SWHS Shanghai Women’s Health Study, UKWCS UK Women’s Cohort Study, VITAL VITamins And Lifestyle, WHS Women’s Health Study