Table 1.
The characteristics of the included studies in the meta-analysis
| Author | Year | Location | Study design | Sex (n%) | Follow up duration | Sample size and characteristics | Mean Age | Method of analysis | invasive or non-invasive | diet components | Dietary patterns investigated and associated risk |
| Schulpen, et al | 2019 | Netherlands | Cohort |
Men 48% Women 52% |
20.3 years |
2049 cases 4,084 sub cohort members |
55–69 | Trichopoulou | 996 invasive/1053 non-invasive | Proxy of MD: vegetables, legumes, fruits, nuts, whole grains, fish, the ratio of MUFA to saturated fatty acids | MD (HR = 1.00, 95% CI:0.92,1.09) total |
| Witlox, et al | 2020 | European Countries | Cohort |
Men 47% Women 53% |
6,577,179 person years | 3639 cases/642,583 non-case | younger than 70 years | Trichopoulou | 1480 non-invasive/945 invasive | fruits, vegetables, legumes and cereals, moderate-to-high consumption of fish, moderate consumption of alcohol (mostly wine), low-to-moderate consumption of milk and dairy products, and low consumption of meat and meat products | MD (HR = 0.85,95% CI: 0.77, 0.93) |
| Bravi, et al | 2018 | Italy | Case–control |
Men 85% Women 15% |
NA | 690 cases/665 controls | 25–84 | Trichopoulou | 268 non-invasive/ 192 pT1/ 159 invasive/ 307 moderately or well differentiated/ 312undifferentiated or poorly differentiated | olive oil, fruits, vegetables, legumes, and whole grain cereals | MD (OR = 0.66,95% CI:0.47–0.93) |
| Buckland, et al | 2014 | EPIC | Cohort |
Men 30% Women 70% |
11 years |
1575 cases 475,737 non cases |
51.2 6 ± 9.9 | Trichopoulou | 430 were aggressive and 413 were non-aggressive UCC tumors and for 582 subject’s tumor aggressiveness was unknown (n 5 52) or not validated (n 5 530) | fruit, nuts and seeds, vegetables, legumes, fish, olive oil and cereals (dairy products and meat, calculated as a function of energy) | MD (HR = 0.84, 95% CI: 0.69, 1.03) |
| Brinkman, et al | 2011 | Belgium | Case–control |
Men69% Women 31% |
NA | 200 cases/386 controls | cases 67.6 ± 9.9 controls 64.2 ± 9.6 | PCA | no data | dietary fat, meat, olive oil, fish, eggs, milk, cheese, margarine | WD (OR: 1.11, 95% CI:0.67–1.83) |
| Dugué, et al | 2016 | Australia | Cohort |
Men 41% Women 59% |
21.3 years | 379 Cases/37063 Non-cases | 27 to 76 | Trichopoulou | 165 invasive/ 214 superficial | MD: vegetables, fruits, cereals, legumes, and fish | MD:( HR = 0.97, 95% CI: 0.88–1.08 |
| Dianatinasab, et al | 2020 | Australia, European Countries and united states | Cohort |
Men 33% Women 67% |
11.4 years | 3401cases /577 367 non-cases | 52.7 years (± 10.2) for cases and 60.5 (± 7.3) 52.6 (± 10.1) for controls | priori | 1365 no muscle-invasive / 874 muscle-invasive | Cream, Egg, Red and processed meet, Butter, Margarine, Animal fat, Pasta, Sugar, Dressing, Dips, Vegetables, Fruits, Fluid | WD (HR = 1.54, 95% CI: 1.37–1.72) |
| Westhoff, et al | 2018 | Texas | Cohort |
Men 80% Women 20% |
median of 65.7 months | 595 case | no restrictions on age | factor analysis | only 595 non-invasive selected then 120 progressed to muscle-invasive bladder cancer during study | western: Cornbread, Black eyed peas, Fried chicken, Fried fish, Okra, Gravy, Canned chili, green beans, French fries, bacon, corn, hamburgers, beef, pork, potato, sausages, wine/ fruit and vegetables | WD (HR = 1.48,95% CI:1.06–2.06) |
| Stefani, et al | 2008 | Uruguay | Case–control |
Men 88% Women 12% |
NA | 255 cases/501 controls | 30–89 | factor analysis | no data | sweet beverage: coffee, tea, and added sugar/western patter: red meat, fried eggs, potatoes, and red wine/prudent pattern: fresh vegetables, cooked vegetables, and fruits | WD (OR = 2.35, 95% CI 1.42–3.89 MD (OR = 1.06, 95% CI 0.67–1.68) |
| Shivappa, et al | 2019 | Iran | Case–control |
Men 92% Women 8% |
NA | 56 cases/109 controls | 48–73 | Multivariate analyses | no data | bread, rice, meat, fish and | Dietary inflammatory index (DII) score > –0.12 (OR = 2.46; 95% CI:1.12–5.41) among current/ex-smokers (OR DII (> –0.12/ –0.12) 3.30; 95% CI¼1.07–10.16 |
| Abufaraj, et al | 2019 | United States | Cohort |
Men 20% Women 80% |
23 years | 1,042 cases/ 218,074 non-case | 25–75 | EDIP score assessment | no data | red meat, processed meat, all vegetables, fish, high energy beverages, carbonated beverages, low energy beverages, tomatoes, beer; wine; tea; coffee; dark yellow vegetables, snacks; fruit juice; and pizza | DII (RR = 0.92, 95% CI: 0.75–1.12) |
| Shivappa, et al | 2017 | Italy | Case–control |
Men 84% Women 16% |
NA | 690 cases/665 controls | 25–80 | factor analysis | 460 noninvasive/159 invasive/ 307 moderately or well differentiated/ 312undifferentiated or poorly differentiated | carbohydrates, proteins, fats, alcohol, fibers, cholesterol, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, omega 3, omega 6, niacin, thiamin, riboflavin, vitamin B6, iron, zinc, vitamin A, vitamin C, vitamin D, vitamin E, folic acid, beta carotene, anthocyanidins, flavan3ols, flavonols, flavanones, flavones, isoflavones, caffeine, and tea | DII (OR Continuous = 1.11, 95% CI = 1.03, 1.20)/ (OR Quartile4vs1 = 1.97, 95% CI = 1.28, 3.03) |
| Author | Year | Events followed | Diagnostic criteria | MD/WD compliance assessment method | Variables for adjustment | ||||||
| Schulpen, et al | 2019 | Bladder Cancer Risk |
record linkage with the Netherlands cancer Registry and the nationwide Dutch Pathology Registry |
FFQ | age, sex | ||||||
| Witlox, et al | 2020 | Bladder Cancer Risk | pathology confirmed cases | FFQ | sex, age, smoking, total energy intake | ||||||
| Bravi, et al | 2018 | Bladder Cancer Risk | incident diagnosis of urothelial carcinoma of the bladder (93%histologically confirmed) | FFQ | Age, sex, BMI, study center, year of interview, Education, Smoking, non-alcohol energy intake, History of Diabetes, History of Cystitis, Family history of bladder cancer | ||||||
| Buckland, et al | 2014 | Bladder Cancer Risk | All newly diagnosed by pathology reports | dietary questionnaires | smoking, dietary energy | ||||||
| Brinkman, et al | 2011 | Bladder Cancer Risk | histologically confirmed with transitional cell carcinoma | FFQ | age, sex, smoking characteristics, occupational exposures, calorie intake | ||||||
| Dugué, et al | 2016 | Bladder Cancer Risk | identified from Victorian cancer registry and the Australian Cancer Database | FFQ | sex, country of birth, smoking, alcohol consumption, body mass index physical activity, education, and socioeconomic status | ||||||
| Dianatinasab, et al | 2020 | Bladder Cancer Risk | the International Classification of Diseases for Oncology (ICD-O-3 code C67) using population-based cancer registries, health insurance records or medical records | FFQ | total energy intake in kilocalories, sex, smoking status (never, former or current smoker) and smoking intensity, fluid, vegetables and fruits intake | ||||||
| Westhoff, et al | 2018 | risk of recurrence and progression in non- muscle-invasive bladder cancer | newly histologically confirmed NMIBC | FFQ | age, sex, education, income, body mass index, smoking status and intensity, total energy intake, grade, tumor multiplicity, concomi- tant carcinoma in situ, and treatment | ||||||
| Stefani, et al | 2008 | Bladder Cancer Risk | newly diagnosed and micro- scopically confirmed cases of transitional cell carcinoma of the bladder with hospitalized controls | FFQ | age, sex, residence, urban/rural status, education, family history of bladder cancer, high-risk occupation, body mass index, years smoked, and total energy intake | ||||||
| Shivappa, et al | 2019 | Bladder Cancer Risk | histologically confirmed cases | FFQ | age, sex, body mass index (BMI), physical activity, smoking status, alcohol use and family history of cancer | ||||||
| Abufaraj, et al | 2019 | Bladder Cancer Risk | confirmed by retrieving relevant medical records | FFQ | age, energy intake, smoking status, fluid intake, nonsteroidal anti- inflammatory drug use, pregnancy, menopausal status, age at menopause | ||||||
| Shivappa, et al | 2017 | Bladder Cancer Risk | histologically confirmed cases of BC | FFQ | age, sex, year of interview, study center, and total energy intake, education, smoking | ||||||