Literature DB >> 32778880

Grain and dietary fiber intake and bladder cancer risk: a pooled analysis of prospective cohort studies.

Evan Y W Yu1, Anke Wesselius1, Siamak Mehrkanoon2, Maree Brinkman1,3,4, Piet van den Brandt5,6, Emily White7, Elisabete Weiderpass8, Florence Le Calvez-Kelm8, Marc Gunter8, Inge Huybrechts8, Fredrik Liedberg9,10, Guri Skeie11, Anne Tjonneland12,13, Elio Riboli14, Graham G Giles4,15,16, Roger L Milne4,15,16, Maurice P Zeegers1,17,18.   

Abstract

BACKGROUND: Higher intakes of whole grains and dietary fiber have been associated with lower risk of insulin resistance, hyperinsulinemia, and inflammation, which are known predisposing factors for cancer.
OBJECTIVES: Because the evidence of association with bladder cancer (BC) is limited, we aimed to assess associations with BC risk for intakes of whole grains, refined grains, and dietary fiber.
METHODS: We pooled individual data from 574,726 participants in 13 cohort studies, 3214 of whom developed incident BC. HRs, with corresponding 95% CIs, were estimated using Cox regression models stratified on cohort. Dose-response relations were examined using fractional polynomial regression models.
RESULTS: We found that higher intake of total whole grain was associated with lower risk of BC (comparing highest with lowest intake tertile: HR: 0.87; 95% CI: 0.77, 0.98; HR per 1-SD increment: 0.95; 95% CI: 0.91, 0.99; P for trend: 0.023). No association was observed for intake of total refined grain. Intake of total dietary fiber was also inversely associated with BC risk (comparing highest with lowest intake tertile: HR: 0.86; 95% CI: 0.76, 0.98; HR per 1-SD increment: 0.91; 95% CI: 0.82, 0.98; P for trend: 0.021). In addition, dose-response analyses gave estimated HRs of 0.97 (95% CI: 0.95, 0.99) for intake of total whole grain and 0.96 (95% CI: 0.94, 0.98) for intake of total dietary fiber per 5-g daily increment. When considered jointly, highest intake of whole grains with the highest intake of dietary fiber showed 28% reduced risk (95% CI: 0.54, 0.93; P for trend: 0.031) of BC compared with the lowest intakes, suggesting potential synergism.
CONCLUSIONS: Higher intakes of total whole grain and total dietary fiber are associated with reduced risk of BC individually and jointly. Further studies are needed to clarify the underlying mechanisms for these findings.
Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.

Entities:  

Keywords:  bladder cancer; cohort study; dietary fiber; dose-response analysis; grain

Mesh:

Substances:

Year:  2020        PMID: 32778880      PMCID: PMC7657329          DOI: 10.1093/ajcn/nqaa215

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


Introduction

Bladder cancer (BC) is the 10th most common malignancy worldwide, with an estimated 550,000 new cases and 200,000 deaths annually (1, 2). Incidence rates of BC are highest in Europe and North America, with a strong predominance in males and the elderly (3–8). BC is reported to be the most expensive of all cancers in terms of lifetime treatment owing to its high rate of recurrence (9). Diet has been suspected to be important, in addition to smoking and occupational exposure, but only arsenic-contaminated food is considered to be an established dietary risk factor for BC (10–14). Because grain intake is an important component of numerous dietary guidelines globally, interest in the health effects of grain intake is increasing (15, 16). Whole grains contain all components of the kernel, i.e., the bran, germ, and endosperm. Both the bran outer coating and the inner germ are major sources of dietary fiber, vitamins, minerals, phytonutrients, and numerous other nutrients which may be beneficial to health (17). However, during the refining process, the outer bran and inner germ are removed and only the endosperm is retained. This results in a substantial reduction in dietary fiber, vitamins, minerals, and other components. Although many vitamins and minerals are often added back to refined grains by subsequent processing, the fiber content remains greatly diminished (18, 19). An accumulation of evidence shows that intake of dietary fiber is associated with lower risk of insulin resistance, hyperinsulinemia (20), and inflammation (21), which are known predisposing factors for cancer (22); however, evidence of association with BC risk is sparse, with only 2 case-control studies reporting insufficient evidence of an inverse association for intake of whole grains (23, 24). In contrast to the beneficial health associations of whole grains containing rich fiber, studies of refined grains mainly show no association with health (25–29), or harmful associations (30, 31), and there is no strong evidence of association with BC risk. We therefore assessed associations with BC risk for intakes of whole grains and refined grains, using data from 13 prospective cohort studies pooled in the BLEND (BLadder cancer Epidemiology and Nutritional Determinants) international study. In addition, we also investigated the potential association of dietary fiber intake with BC risk by evaluating total and individual food sources (i.e., cereal, fruit, and vegetable fiber).

Methods

Study sample

Data were obtained from BLEND, an international nutritional consortium currently consisting of 19 case-control studies and 16 cohort studies. Thirteen cohort studies with a total of 574,726 participants, 3214 of whom developed incident BC, had sufficient information on grain intake to be eligible for inclusion in the present study (). These studies originated from 12 countries in 3 continents {i.e., Europe: EPIC [European Prospective Investigation into Cancer and Nutrition cohort study] (32) [Denmark (33), France (34), Germany (35), Greece (36), Italy (37), Spain (36), Sweden (38, 39), the Netherlands (40), the United Kingdom (41, 42), and Norway (43)] and NLCS (NetherLands Cohort Study) (44); North America: VITAL (VITamins And Lifestyle cohort study) in the United States (45); and Oceania: MCCS (Melbourne Collaborative Cohort Study) in Australia (46, 47)}. Person-years of follow-up for each participant were calculated from the date of study enrolment until the date of BC diagnosis or the date of last follow-up (e.g., date of death, lost to follow-up, or study exit), whichever came first. For the NLCS study, a nested case-cohort design was applied in order to increase the follow-up coverage and efficiency, in which the number of person-years at risk was estimated based on a subcohort that was randomly sampled (44). Each study was approved by their local ethical research committee (32, 44, 45, 47) (). Informed consent was obtained from all individual participants included in each study.

Data collection and coding

Details on the methodology of the BLEND consortium have been described elsewhere (48). In brief, all included studies used a self-administered or trained interviewer–administered FFQ that was validated on either food groups (45, 49–52) and/or energy intake (49, 52, 53). For each study, participants were asked to report on their usual intake during the year before study enrolment of individual types of whole grains [i.e., brown rice, wheat or oat, and basic products of other cereals (e.g., buckwheat, millet, sorghum, or spelt)] and of refined grains [i.e., white rice, pasta or noodles, leavened bread, unleavened bread, other bakery wares, savory cereal dishes (e.g., dumplings, couscous, risotto, pizza, pancake, or pie), and breakfast cereals]. These data were harmonized using the hierarchal Eurocode 2 food coding system developed by the European Union (54), with weekly, monthly, or yearly intake converted to grams per day. This resulted in an aggregated data set with unified dietary intakes across the different studies included. In order to extract dry weight (e.g., uncooked pasta or noodles, uncooked rice, uncooked wheat or oat) across all grains, the water content of grains was determined according to the composition database from the USDA and subtracted from the grain intake (55). Total intakes of dietary fiber and dietary fiber from cereal, fruit, and vegetables were calculated by multiplying the amount of each food consumed by the dietary fiber content per gram according to the USDA. Each study ascertained incident BC, defined to include all urinary bladder neoplasms according to the International Classification of Diseases for Oncology, third edition (code C67), using population-based cancer registries, health insurance records, or medical records. BCs were classified as nonmuscle invasive bladder cancer (NMIBC) or muscle invasive bladder cancer (MIBC). For the present study, the primary outcome was defined as BC cases or non-BC cases, and the secondary outcome was defined as NMIBC, MIBC, or non-BC cases. NMIBC included noninvasive papillary carcinomas confined to the urothelium (stage Ta) and carcinomas that invaded the lamina propria of the bladder wall (stage T1). High-grade flat noninvasive carcinomas confined to the urothelium (carcinoma in situ) without other concomitant tumor stages [i.e., T1/Ta (classified to nonmuscle invasive prior) or muscle invasive] were also classified as NMIBC. MIBC included carcinomas that invaded into the detrusor muscle (stage T2), carcinomas that invaded into the peri-vesical tissue (stage T3), and carcinomas that invaded adjacent tissues and organs (most often the prostate or uterus, stage T4). In addition to information on grain and other dietary intakes, the BLEND data set also included data on study characteristics (design, method of dietary assessment, geographical region), participant demographics (age, sex, and ethnicity), smoking status, and smoking pack-years (i.e., the number of cigarettes smoked per day multiplied by the years of smoking), which were measured at baseline.

Statistical analyses

To assess the influence of intake of grains and fiber on BC risk, Cox regression analyses with a stratification approach to adjust for cross-cohort heterogeneity (56) were used to estimate the pooled HRs and 95% CIs. The proportional hazard assumption was examined for each analysis and no evidence of violation was found. In addition, the appropriateness of the use of the log-normal distribution was tested using a Wald test, and again no evidence of violation was found. Grain intake (i.e., total grain, total whole grain, total refined grain, brown rice, wheat or oat, basic products of other cereals, white rice, pasta or noodles, leavened bread, unleavened bread, bakery wares, savory cereals, and breakfast cereals) and dietary fiber intake (i.e., total dietary fiber from all food sources, cereal fiber, fruit fiber, and vegetable fiber) were divided into 3 groups defined by tertile based on the pooled data: low intake (tertile 1), medium intake (tertile 2), and high intake (tertile 3). Low intake was used as the reference group and associations were assessed applying 2 models: model 1 adjusted for age (y), sex (male/female), smoking, and total energy intake [kcal/d; continuous; using a residual model to remove extraneous variation (57)] and included cohort as a stratification variable ( provide results) and model 2 in addition adjusted for ethnicity (Caucasian/non-Caucasian) and for potential dietary factors that affect the development of BC (10), including alcohol intake (mL/d; continuous), sugar intake (g/d; continuous), meat intake (g/d; continuous), vegetable intake (g/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), and total fluid intake (mL/d; continuous). Smoking was defined as a dummy variable as follows: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; and 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]. The main interaction terms (between grain/dietary fiber and age, sex, and smoking; between total whole grain and total dietary fiber) were added to model 1 (P-interaction < 0.05 was considered statistically significant). Stratified analyses were performed by BC subtype (i.e., NMIBC and MIBC), sex, and smoking status. In addition, the HRs and 95% CIs of BC per 1-SD increase in grain and dietary fiber intakes were also estimated using the same models. Furthermore, a potential joint association of total whole grain and total dietary fiber intakes with BC risk was assessed using the lowest intakes of both total whole grain and total dietary fiber as the reference. To test for linearity or nonlinearity, we included both linear and quadratic terms (i.e., the absolute intake and intake squared) in the models, then a likelihood ratio test was used to assess the difference between the nonlinear and linear models (58). Because results showed no evidence of a nonlinear association, linear models were applied in the present study. A P for trend test was conducted by assigning medians to per 1 SD as a continuous variable in the models. The variables of BC status (i.e., cases or noncases), follow-up time, age, sex, smoking, ethnicity, and total energy intake were complete without missing values. Missing variables (e.g., alcohol intake, sugar intake, meat intake, vegetable intake, fruit intake, fat intake, and total fluid intake; missing proportions were all <5%) were imputed separately in each participating cohort by the multiple imputation method. Only participants with complete information on BC status, age, sex, smoking, ethnicity, and total energy intake were included when building the imputation models. Linear regression models were then fitted for those variables with missing data separately. In our secondary analyses, potential dose–response relations of grain/dietary fiber with BC risk were assessed by using fractional polynomial regression from the ln of the HRs across categories of intake, in which the best-fitting second-order fractional polynomial regression model was defined as the model with the lowest deviance (59, 60). For this, we categorized each source of grain (e.g., total whole grain or total refined grain) and dietary fiber (e.g., total dietary fiber, cereal fiber, fruit fiber, and vegetable fiber) into 10 doses according to the range of intake of each grain or dietary fiber, by which the intervals of each intake were different. P values for trend were estimated by assigning medians to each category of intake as a continuous variable. A likelihood ratio test was used to assess the difference between the nonlinear (i.e., the absolute dose and dose squared) and linear (i.e., the absolute dose) models to test for linearity or nonlinearity (58). Model 2 was applied in dose–response analyses. Sensitivity analyses were performed by 1) removing cases diagnosed within the first 2 y after recruitment to each study and 2) only including the complete data set, thereby excluding the participants with missing data on variables included in model 2. An extra sensitivity analysis for total refined grain was assessed by excluding pasta source in order to test whether the possible misclassification of pasta would influence the result. Furthermore, the role of smoking was tested by replacing the smoking dummy variable by both smoking status (never, former, and current) and smoking pack-years (continuous). In addition, a quintile-based analysis was performed in order to test whether the differently categorized intakes would affect the results. As a last step, the associations between intake of grains/dietary fiber and BC risk were assessed in each participating cohort separately and combined in a meta-analysis using a random-effect model; subsequently, we conducted a sensitivity analysis by excluding the study that mostly likely dominated the analysis for each dietary factor examined in the present study. All statistical analyses were performed using STATA version 14 SE (Stata Corporation). A 2-tailed P value < 0.05 was considered statistically significant.

Results

Baseline characteristics

shows the baseline characteristics of the study sample. In total, 574,726 study participants contributed 6,335,667 person-years of follow-up over a median of 11 y, with 3214 incident BC cases (2416 males, 798 females) diagnosed. Of these, 2041 (63%) cases had available diagnosis records of NMIBC (39%) or MIBC (24%). The median age at baseline was 53 y. The majority (99.3%) of participants were Caucasian. No statistical interaction with age, sex, and smoking was found for total whole grain and total dietary fiber. Total refined grain intake showed a significant interaction with sex (P-interaction = 0.048).
TABLE 1

Characteristics of the study population (3214 cases and 571,512 noncases) according to tertiles of grain and dietary fiber intakes[1]

Total whole grainTotal refined grainTotal dietary fiber
Low (tertile 1)Medium (tertile 2)High (tertile 3)Mean ± SD, g/d P-interactionLow (tertile 1)Medium (tertile 2)High (tertile 3)Mean ± SD, g/d P-interactionLow (tertile 1)Medium (tertile 2)High (tertile 3)Mean ± SD, g/d P-interaction
Overall population, n (%)72,821 (33.5)74,285 (34.1)70,450 (32.4)9.82 ± 12.69191,576 (33.4)191,575 (33.3)191,575 (33.3)156.37 ± 102.19191,576 (33.4)191,575 (33.3)191,575 (33.3)23.37 ± 12.38
 Noncases, n (%)71,830 (33.3)73,932 (34.3)70,061 (32.4)10.79 ± 14.19190,572 (33.4)190,337 (33.3)190,603 (33.4)156.39 ± 102.24190,402 (33.3)190,371 (33.3)190,739 (33.4)23.38 ± 12.40
 Cases, n (%)991 (57.2)353 (20.4)389 (22.4)9.81 ± 12.681004 (31.3)1238 (38.5)972 (30.2)153.34 ± 93.321174 (36.5)1204 (37.5)836 (26.0)21.04 ± 9.07
TNM stage
 MIBC, n (%)360 (63.7)92 (16.3)113 (20.0)5.73 ± 11.50267 (34.5)356 (46.1)150 (19.4)135.49 ± 75.98273 (35.3)323 (41.8)177 (22.9)20.68 ± 8.56
 NMIBC, n (%)424 (59.5)133 (18.7)156 (21.8)6.78 ± 13.65422 (33.3)491 (38.7)355 (28.0)149.82 ± 97.02472 (37.2)467 (36.8)329 (26.0)20.84 ± 9.13
Person-years1,016,724870,317855,8599.82 ± 12.691,929,4662,262,4172,143,784156.38 ± 102.232,001,7902,187,8602,146,05823.37 ± 12.38
Sex0.9060.0480.336
 Male, n (%)22,476 (36.1)18,167 (29.2)21,659 (34.7)10.98 ± 14.5257,331 (30.4)51,474 (27.3)80,057 (42.4)177.41 ± 118.6467,336 (35.7)59,435 (31.5)62,091 (32.8)22.02 ± 10.68
 Female, n (%)50,345 (32.4)56,118 (36.2)48,791 (31.4)9.40 ± 11.93134,245 (34.8)140,101 (36.3)111,518 (28.9)146.08 ± 91.34124,240 (32.2)132,140 (34.3)129,484 (33.6)24.03 ± 13.09
Age,[2] y52.9849.7548.519.82 ± 12.690.72454.9652.0750.90156.37 ± 102.190.40654.9351.8651.1423.37 ± 12.380.431
 ≤55, n (%)40,336 (28.4)50,475 (35.6)50,994 (36.0)10.22 ± 12.6697,204 (28.6)117,384 (34.5)125,269 (36.9)166.82 ± 104.1997,474 (28.7)117,242 (34.5)125,141 (36.8)24.52 ± 12.49
 55–60, n (%)12,111 (37.8)10,592 (33.1)9300 (29.1)9.04 ± 11.6133,855 (34.5)31,659 (32.3)32,527 (33.2)154.42 ± 102.1433,998 (34.7)32,299 (32.9)31,744 (32.4)23.03 ± 12.43
 60–65, n (%)10,241 (41.8)7687 (31.4)6557 (26.8)9.13 ± 12.4728,094 (35.4)26,446 (33.3)24,846 (31.3)149.48 ± 96.9729,037 (36.6)26,494 (33.4)23,855 (30.0)22.34 ± 11.85
 65–70, n (%)6919 (52.1)3653 (27.5)2709 (20.4)8.92 ± 13.9518,125 (50.6)11,241 (31.4)6464 (18.0)116.61 ± 83.2017,708 (49.4)10,284 (28.7)7838 (21.9)19.74 ± 11.78
 70–75, n (%)2311 (54.7)1305 (30.9)610 (14.4)8.08 ± 12.6012,691 (68.5)3917 (22.2)1909 (10.3)88.89 ± 68.9812,691 (68.5)3917 (22.2)1909 (10.3)15.85 ± 8.61
 >75, n (%)903 (51.4)573 (32.6)280 (16.0)8.15 ± 13.101607 (51.9)928 (30.0)560 (18.1)111.71 ± 76.901331 (43.0)897 (29.0)867 (28.0)21.23 ± 11.68
Smoking status
 Never, n (%)38,321 (32.0)42,404 (35.4)39,024 (32.6)9.91 ± 12.9197,586 (34.1)98,375 (34.4)90,409 (31.6)152.51 ± 98.3689,338 (31.2)94,872 (33.1)102,160 (35.7)24.37 ± 13.21
 Former, n (%)21,503 (36.3)19,219 (32.4)18,553 (31.3)9.43 ± 12.9762,296 (36.8)52,397 (31.0)54,517 (32.2)151.42 ± 103.6062,807 (37.1)54,623 (32.3)51,780 (30.6)22.25 ± 11.83
 Current, n (%)12,997 (33.7)12,662 (32.9)12,873 (33.4)9.36 ± 11.5231,694 (26.6)40,803 (34.3)46,649 (39.2)172.70 ± 107.4339,431 (33.1)42,080 (35.3)37,635 (31.6)22.56 ± 10.79
Smoking pack-years[3]22.9919.2219.729.65 ± 12.3024.5022.6623.08150.29 ± 102.0324.8422.7222.3623.03 ± 12.67
Smoking[4]0.8780.9840.970
 0, n (%)38,321 (32.0)42,404 (35.4)39,024 (32.6)9.91 ± 12.9197,586 (34.1)98,375 (34.4)90,409 (31.6)152.51 ± 98.3689,338 (31.2)94,872 (33.1)102,160 (35.7)24.37 ± 13.21
 1, n (%)5526 (29.8)6513 (35.2)6489 (35.0)9.55 ± 11.8516,366 (28.9)19,438 (34.3)20,834 (36.8)166.01 ± 104.2418,745 (33.1)20,112 (35.5)17,781 (31.4)22.49 ± 10.71
 2, n (%)5930 (39.7)4418 (29.6)4594 (30.8)8.95 ± 11.1012,788 (24.8)18,134 (35.1)20,703 (40.1)176.88 ± 109.3117,486 (33.9)18,410 (35.7)15,729 (30.4)22.31 ± 10.46
 3, n (%)3555 (66.6)693 (13.0)1087 (20.4)11.99 ± 16.2222,466 (81.6)4201 (15.3)869 (3.2)67.58 ± 46.9219,501 (70.8)5459 (19.8)2576 (9.4)14.31 ± 8.10
 4, n (%)2505 (72.0)368 (10.6)606 (17.4)12.53 ± 16.888996 (74.8)2450 (20.4)582 (4.8)76.84 ± 52.018111 (67.4)2612 (21.7)1305 (10.9)14.93 ± 8.31
 5, n (%)1541 (30.4)1731 (34.2)1790 (35.4)9.82 ± 11.332540 (23.3)3231 (29.7)5112 (47.0)187.69 ± 112.193200 (29.4)3558 (32.7)4125 (37.9)24.15 ± 12.48
 6, n (%)15,443 (30.6)18,158 (36.0)16,860 (33.4)9.73 ± 12.5830,834 (23.8)45,746 (35.3)53,066 (40.9)176.15 ± 103.3035,195 (27.1)46,552 (35.9)47,899 (37.0)24.61 ± 11.77
Ethnicity
 Non-Caucasian,n (%)3772 (94.0)228 (5.7)15 (0.3)49.05 (31.28)3302 (82.2)514 (12.8)199 (5.0)11.88 (7.26)
 Caucasian,[5]n (%)72,821 (33.5)74,285 (34.1)70,450 (32.4)9.82 ± 12.69187,804 (32.9)191,347 (33.5)191,560 (33.6)157.13 ± 102.12188,274 (33.0)191,061 (33.5)191,376 (33.5)23.45 ± 12.37
Energy intake, kcal/d2055.902074.742251.099.82 ± 12.691731.562002.272455.98156.37 ± 102.191726.742016.212446.8623.37 ± 12.38
Alcohol intake, mL/d9.179.7911.099.69 ± 12.437.209.5712.44157.61 ± 103.548.179.7711.2623.61 ± 12.39
Fat intake, g/d24.2122.7724.559.80 ± 12.6916.8825.3031.74156.57 ± 101.9818.5525.7829.5923.44 ± 12.52
Fruit intake, g/d154.49147.67160.539.83 ± 12.87101.98132.83134.84156.71 ± 101.4872.61118.01179.0223.37 ± 12.39
Meat intake, g/d85.9382.2488.929.80 ± 12.6354.4875.4591.59160.86 ± 101.7954.5073.9493.0923.75 ± 12.38
Sugar intake, g/d22.1023.9723.529.96 ± 13.0620.7323.3227.37155.95 ± 102.8018.6920.7731.9622.99 ± 11.97
Vegetable intake, g/d222.97239.05263.399.82 ± 12.69181.77212.32204.19156.68 ± 102.06130.47189.46278.3523.38 ± 12.38
Total fluid intake, mL/d1189.351264.411153.819.82 ± 12.691368.741337.531444.93156.64 ± 102.071420.231397.251333.7223.37 ± 12.38

The intervals of tertiles were defined as follows: total whole grain: 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; total refined grain: 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; total dietary fiber: 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d. P-interaction < 0.05 was considered statistically significant. MIBC, muscle invasive bladder cancer; NMIBC, nonmuscle invasive bladder cancer; TNM, tumor, nodes, and metastasis classification.

Age at the time of recruitment.

Pack-years was defined as the number of cigarettes smoked per day multiplied by the years of smoking.

Smoking was defined as a dummy variable: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)].

All of the included participants for whole grain intake were Caucasian.

Characteristics of the study population (3214 cases and 571,512 noncases) according to tertiles of grain and dietary fiber intakes[1] The intervals of tertiles were defined as follows: total whole grain: 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; total refined grain: 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; total dietary fiber: 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d. P-interaction < 0.05 was considered statistically significant. MIBC, muscle invasive bladder cancer; NMIBC, nonmuscle invasive bladder cancer; TNM, tumor, nodes, and metastasis classification. Age at the time of recruitment. Pack-years was defined as the number of cigarettes smoked per day multiplied by the years of smoking. Smoking was defined as a dummy variable: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]. All of the included participants for whole grain intake were Caucasian.

Associations of grain and dietary fiber intakes with BC risk

Total grain intake and BC risk

For the different categories of intake of “total grains,” no evidence of association for tertile of intake was observed overall, by cancer subtype, by sex, or by smoking status (). However, the HR per 1-SD increment showed a decreased risk (model 2: 0.91; 95% CI: 0.85, 0.98; P for trend = 0.011) of BC among males.
TABLE 2

Risk of bladder cancer according to intakes of total grains, total whole grains, and total refined grains[1]

Grain source, subgroup, intake tertilesModel 2[2]
Cases/participants, nHR (95% CI)HR per 1-SD increase (95% CI) P-trend
Total grains, g/d
 Overall
  Tertile 11005/191,576Ref.0.97 (0.92, 1.02)0.240
  Tertile 21227/191,5750.93 (0.84, 1.02)
  Tertile 3982/191,5750.94 (0.83, 1.05)
 MIBC
  Tertile 1263/190,834Ref.0.90 (0.78, 1.02)0.119
  Tertile 2350/190,6980.89 (0.74, 1.08)
  Tertile 3160/190,7530.79 (0.61, 1.02)
 NMIBC
  Tertile 1425/190,996Ref.0.99 (0.91, 1.07)0.750
  Tertile 2481/190,8290.96 (0.82, 1.13)
  Tertile 3352/190,9550.93 (0.77, 1.14)
 Male
  Tertile 1793/62,954Ref.0.91 (0.85, 0.98)0.011
  Tertile 21049/62,9540.89 (0.80, 1.00)
  Tertile 3574/62,9540.88 (0.77, 1.02)
 Female
  Tertile 1287/128,622Ref.1.07 (0.97, 1.19)0.174
  Tertile 2291/128,6210.97 (0.81, 1.17)
  Tertile 3220/128,6211.10 (0.88, 1.37)
 Never smoker
  Tertile 1212/95,457Ref.1.00 (0.90, 1.13)0.801
  Tertile 2244/95,4571.02 (0.79, 1.32)
  Tertile 3201/95,4560.94 (0.75, 1.17)
 Current smoker
  Tertile 1403/39,716Ref.0.97 (0.89, 1.06)0.488
  Tertile 2456/39,7151.04 (0.90, 1.20)
  Tertile 3339/39,7150.99 (0.82, 1.19)
 Former smoker
  Tertile 1416/56,404Ref.0.90 (0.82, 1.01)0.517
  Tertile 2543/56,4030.85 (0.72, 1.00)
  Tertile 3400/56,4030.85 (0.69, 1.02)
Total whole grains, g/d
 Overall
  Tertile 1991/72,821Ref.0.95 (0.91, 0.99)0.023
  Tertile 2353/74,2851.01 (0.89, 1.15)
  Tertile 3389/70,4500.87 (0.77, 0.98)
 MIBC
  Tertile 1360/72,190Ref.0.92 (0.85, 1.00)0.038
  Tertile 292/74,0241.21 (0.95, 1.53)
  Tertile 3113/70,1740.86 (0.70, 1.07)
 NMIBC
  Tertile 1424/72,254Ref.0.96 (0.90, 1.03)0.281
  Tertile 2133/72,0651.07 (0.87, 1.32)
  Tertile 3156/70,2170.85 (0.70, 1.03)
 Male
  Tertile 1787/22,476Ref.0.93 (0.83, 1.02)0.059
  Tertile 2259/19,1490.98 (0.84, 1.14)
  Tertile 3295/20,6770.85 (0.74, 0.98)
 Female
  Tertile 1204/51,754Ref.0.93 (0.85, 1.01)0.053
  Tertile 2104/51,8300.98 (0.83, 1.15)
  Tertile 384/51,6700.83 (0.71, 0.96)
 Never smoker
  Tertile 1188/39,917Ref.0.96 (0.87, 1.06)0.434
  Tertile 293/40,8081.04 (0.86, 1.45)
  Tertile 377/39,0240.83 (0.63, 1.10)
 Current smoker
  Tertile 1362/12,997Ref.0.96 (0.90, 1.02)0.167
  Tertile 2117/12,6991.00 (0.80, 1.25)
  Tertile 3151/12,8360.87 (0.71, 1.08)
 Former smoker
  Tertile 1425/19,760Ref.0.94 (0.87, 1.02)0.125
  Tertile 2152/19,9700.98 (0.80, 1.19)
  Tertile 3168/19,5450.90 (0.75, 1.09)
Total refined grains, g/d
 Overall
  Tertile 11004/191,576Ref.0.97 (0.92, 1.02)0.242
  Tertile 21238/191,5750.93 (0.85, 1.03)
  Tertile 3972/191,5750.95 (0.84, 1.07)
 MIBC
  Tertile 1267/190,839Ref.0.93 (0.81, 1.07)0.327
  Tertile 2356/190,6930.90 (0.74, 1.08)
  Tertile 3150/190,7530.80 (0.61, 1.04)
 NMIBC
  Tertile 1422/190,994Ref.0.99 (0.91, 1.08)0.906
  Tertile 2491/190,8281.00 (0.85, 1.18)
  Tertile 3355/190,9580.98 (0.80, 1.20)
 Male
  Tertile 1808/62,954Ref.0.92 (0.86, 1.00)0.040
  Tertile 21048/62,9540.89 (0.80, 1.00)
  Tertile 3560/62,9540.87 (0.75, 1.01)
 Female
  Tertile 1283/128,623Ref.1.08 (0.98, 1.20)0.135
  Tertile 2295/128,6201.00 (0.83, 1.20)
  Tertile 3220/128,6211.11 (0.89, 1.40)
 Never smoker
  Tertile 1217/95,457Ref.0.99 (0.91, 1.10)0.720
  Tertile 2232/95,4570.92 (0.70, 1.08)
  Tertile 3208/95,4560.99 (0.81, 1.24)
 Current smoker
  Tertile 1404/39,716Ref.0.98 (0.90, 1.07)0.679
  Tertile 2464/39,7151.07 (0.92, 1.24)
  Tertile 3330/39,7151.00 (0.83, 1.21)
 Former smoker
  Tertile 1414/56,404Ref.0.91 (0.84, 1.00)0.054
  Tertile 2552/56,4030.89 (0.73, 1.07)
  Tertile 3393/56,4030.88 (0.75, 1.02)

The intervals of tertiles were defined as follows: total grains: 1) overall, 0 ≤ tertile 1 ≤ 105 g/d, 105 < tertile 2 ≤ 186 g/d, tertile 3 > 186 g/d; 2) MIBC, 0 ≤ tertile 1 ≤ 105 g/d, 105 < tertile 2 ≤ 186 g/d, tertile 3 > 186 g/d; 3) NMIBC, 0 ≤ tertile 1 ≤ 105 g/d, 105 < tertile 2 ≤ 186 g/d, tertile 3 > 186 g/d; 4) male, 0 ≤ tertile 1 ≤ 113 g/d, 113 < tertile 2 ≤ 215 g/d, tertile 3 > 215 g/d; 5) female, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 173 g/d, tertile 3 > 173 g/d; 6) never smoker, 0 ≤ tertile 1 ≤ 104 g/d, 104 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 7) current smoker, 0 ≤ tertile 1 ≤ 121 g/d, 121 < tertile 2 ≤ 204 g/d, tertile 3 > 204 g/d; 8) former smoker, 0 ≤ tertile 1 ≤ 96 g/d, 96 < tertile 2 ≤ 182 g/d, tertile 3 > 182 g/d; total whole grains: 1) overall, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 2) MIBC, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 3) NMIBC, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 4) male, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 5) female, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 6) never smoker, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 7) current smoker, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 8) former smoker, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; total refined grains: 1) overall, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 2) MIBC, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 3) NMIBC, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 4) male, 0 ≤ tertile 1 ≤ 111 g/d, 111 < tertile 2 ≤ 211 g/d, tertile 3 > 211 g/d; 5) female, 0 ≤ tertile 1 ≤ 99 g/d, 99 < tertile 2 ≤ 169 g/d, tertile 3 > 169 g/d; 6) never smoker, 0 ≤ tertile 1 ≤ 100 g/d, 100 < tertile 2 ≤ 176 g/d, tertile 3 > 176 g/d; 7) current smoker, 0 ≤ tertile 1 ≤ 119 g/d, 119 < tertile 2 ≤ 201 g/d, tertile 3 > 201 g/d; 8) former smoker, 0 ≤ tertile 1 ≤ 93 g/d, 93 < tertile 2 ≤ 178 g/d, tertile 3 > 178 g/d. Reference group was lowest intake (tertile 1). P-trend < 0.05 was considered statistically significant. MIBC, muscle invasive bladder cancer; NMIBC, nonmuscle invasive bladder cancer.

Model 2 of Cox regression: adjusted for age (y; continuous), sex (male or female, if applicable), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous).

Risk of bladder cancer according to intakes of total grains, total whole grains, and total refined grains[1] The intervals of tertiles were defined as follows: total grains: 1) overall, 0 ≤ tertile 1 ≤ 105 g/d, 105 < tertile 2 ≤ 186 g/d, tertile 3 > 186 g/d; 2) MIBC, 0 ≤ tertile 1 ≤ 105 g/d, 105 < tertile 2 ≤ 186 g/d, tertile 3 > 186 g/d; 3) NMIBC, 0 ≤ tertile 1 ≤ 105 g/d, 105 < tertile 2 ≤ 186 g/d, tertile 3 > 186 g/d; 4) male, 0 ≤ tertile 1 ≤ 113 g/d, 113 < tertile 2 ≤ 215 g/d, tertile 3 > 215 g/d; 5) female, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 173 g/d, tertile 3 > 173 g/d; 6) never smoker, 0 ≤ tertile 1 ≤ 104 g/d, 104 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 7) current smoker, 0 ≤ tertile 1 ≤ 121 g/d, 121 < tertile 2 ≤ 204 g/d, tertile 3 > 204 g/d; 8) former smoker, 0 ≤ tertile 1 ≤ 96 g/d, 96 < tertile 2 ≤ 182 g/d, tertile 3 > 182 g/d; total whole grains: 1) overall, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 2) MIBC, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 3) NMIBC, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 4) male, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 5) female, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 6) never smoker, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 7) current smoker, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 8) former smoker, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; total refined grains: 1) overall, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 2) MIBC, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 3) NMIBC, 0 ≤ tertile 1 ≤ 102 g/d, 102 < tertile 2 ≤ 181 g/d, tertile 3 > 181 g/d; 4) male, 0 ≤ tertile 1 ≤ 111 g/d, 111 < tertile 2 ≤ 211 g/d, tertile 3 > 211 g/d; 5) female, 0 ≤ tertile 1 ≤ 99 g/d, 99 < tertile 2 ≤ 169 g/d, tertile 3 > 169 g/d; 6) never smoker, 0 ≤ tertile 1 ≤ 100 g/d, 100 < tertile 2 ≤ 176 g/d, tertile 3 > 176 g/d; 7) current smoker, 0 ≤ tertile 1 ≤ 119 g/d, 119 < tertile 2 ≤ 201 g/d, tertile 3 > 201 g/d; 8) former smoker, 0 ≤ tertile 1 ≤ 93 g/d, 93 < tertile 2 ≤ 178 g/d, tertile 3 > 178 g/d. Reference group was lowest intake (tertile 1). P-trend < 0.05 was considered statistically significant. MIBC, muscle invasive bladder cancer; NMIBC, nonmuscle invasive bladder cancer. Model 2 of Cox regression: adjusted for age (y; continuous), sex (male or female, if applicable), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous).

Whole grain intake and BC risk

Table 2 shows the results of the Cox regression analyses for the associations between total whole grains and BC risk. In multivariable-adjusted analyses (model 2), higher total whole grain intake was significantly associated with lower BC risk (comparing the highest with the lowest tertile of intake: HR: 0.87; 95% CI: 0.77, 0.98; HR per 1-SD increment: 0.95; 95% CI: 0.91, 0.99; P for trend = 0.023). No evidence of association for tertile of intake was observed in the stratified analyses by cancer subtype, whereas the HR per 1-SD increment showed a borderline decreased risk (HRmodel2: 0.92; 95% CI: 0.85, 1.00; P for trend = 0.038) of MIBC. Results were consistent for both males (comparing the highest with the lowest intake tertile: HRmodel2: 0.85; 95% CI: 0.74, 0.98; HR per 1-SD increment: 0.93; 95% CI: 0.83, 1.02; P for trend = 0.059) and females (comparing the highest with the lowest intake tertile: HRmodel2: 0.83; 95% CI: 0.71, 0.96; HR per 1-SD increment: 0.93; 95% CI: 0.85, 1.01; P for trend = 0.053). No evidence of association was observed in the smoking-stratified analyses. Of the individual whole grains assessed, only higher intake of brown rice was significantly associated with a decreased BC risk (comparing the highest with the lowest intake tertile: HRmodel2: 0.78; 95% CI: 0.67, 0.92; HR per 1-SD increment: 0.89; 95% CI: 0.82, 0.95; P for trend = 0.001) (). All other whole grains showed a null-association.
TABLE 3

Risk of bladder cancer according to individual intakes of whole grains and refined grains[1]

Grain source, subgroup, intake tertilesModel 2[2]
Cases/participants, nHR (95% CI)HR per 1-SD increase (95% CI) P-trend
Whole grains, g/d
 Brown rice
  Tertile 1910/64,959Ref.0.89 (0.82, 0.95)0.001
  Tertile 2262/64,6850.97 (0.83, 1.13)
  Tertile 3270/64,8220.78 (0.67, 0.92)
 Wheat or oat
  Tertile 1877/15,715Ref.0.99 (0.92, 1.06)0.747
  Tertile 281/35901.20 (0.95, 1.52)
  Tertile 3210/90320.93 (0.80, 1.09)
 Basic products of other cereals[3]
  Tertile 1820/4802Ref.0.98 (0.91, 1.06)0.637
  Tertile 225/2330.78 (0.52, 1.16)
  Tertile 332/2121.03 (0.72, 1.47)
Refined grains, g/d
 White rice
  Tertile 1976/44,980Ref.0.96 (0.88, 1.04)0.344
  Tertile 2288/44,9511.09 (0.93, 1.28)
  Tertile 3221/44,9541.05 (0.92, 1.21)
 Pasta or noodles
  Tertile 1806/193,351Ref.0.99 (0.94, 1.04)0.697
  Tertile 2787/188,3770.90 (0.81, 0.99)
  Tertile 3744/187,7510.90 (0.80, 1.01)
 Leavened bread
  Tertile 11057/191,576Ref.0.99 (0.94, 1.05)0.746
  Tertile 21260/191,5941.01 (0.91, 1.11)
  Tertile 3897/191,5561.01 (0.89, 1.15)
 Unleavened bread
  Tertile 1775/119,122Ref.0.95 (0.89, 1.00)0.070
  Tertile 2939/181,1240.95 (0.85, 1.06)
  Tertile 3863/181,1240.97 (0.87, 1.09)
 Bakery wares
  Tertile 11732/477,213Ref.0.99 (0.96, 1.01)0.307
  Tertile 2688/14,0111.08 (0.76, 1.54)
  Tertile 3448/14,0111.00 (0.70, 1.44)
 Savory cereals dishes[4]
  Tertile 1161/28,872Ref.0.95 (0.83, 1.08)0.423
  Tertile 296/18,9960.96 (0.74, 1.24)
  Tertile 389/21,6230.89 (0.67, 1.17)
 Breakfast cereals
  Tertile 11013/33,151Ref.0.97 (0.90, 1.04)0.422
  Tertile 2251/32,9491.01 (0.86, 1.20)
  Tertile 3250/31,7280.97 (0.81, 1.16)

The intervals of tertiles were defined as follows: total whole grains: 1) brown rice, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 2) wheat or oat, tertile 1 = 0 g/d, 0 < tertile 2 ≤ 2 g/d, tertile 3 > 2 g/d; 3) basic products of other cereals: tertile 1 = 0 g/d, 0 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; total refined grains: 1) white rice, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; 2) pasta or noodles, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 3) leavened bread, 0 ≤ tertile 1 ≤ 73 g/d, 73 < tertile 2 ≤ 160 g/d, tertile 3 > 160 g/d; 4) unleavened bread, tertile 1 = 0 g/d, 0 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 5) bakery wares, tertile 1 = 0 g/d, 0 < tertile 2 ≤ 27 g/d, tertile 3 > 27 g/d; 6) savory cereals dishes, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 7 g/d, tertile 3 > 7 g/d; 7) breakfast cereals, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 27 g/d, tertile 3 > 27 g/d. Reference group was lowest intake (tertile 1). P-trend < 0.05 was considered statistically significant.

Model 2 of Cox regression: adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous).

“Basic products of other cereals”: buckwheat, millet, sorghum, or spelt.

“Savory cereals dishes”: dumplings, couscous, risotto, pizza, pancake, or pie.

Risk of bladder cancer according to individual intakes of whole grains and refined grains[1] The intervals of tertiles were defined as follows: total whole grains: 1) brown rice, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 2) wheat or oat, tertile 1 = 0 g/d, 0 < tertile 2 ≤ 2 g/d, tertile 3 > 2 g/d; 3) basic products of other cereals: tertile 1 = 0 g/d, 0 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; total refined grains: 1) white rice, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; 2) pasta or noodles, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 3) leavened bread, 0 ≤ tertile 1 ≤ 73 g/d, 73 < tertile 2 ≤ 160 g/d, tertile 3 > 160 g/d; 4) unleavened bread, tertile 1 = 0 g/d, 0 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 5) bakery wares, tertile 1 = 0 g/d, 0 < tertile 2 ≤ 27 g/d, tertile 3 > 27 g/d; 6) savory cereals dishes, 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 7 g/d, tertile 3 > 7 g/d; 7) breakfast cereals, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 27 g/d, tertile 3 > 27 g/d. Reference group was lowest intake (tertile 1). P-trend < 0.05 was considered statistically significant. Model 2 of Cox regression: adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous). “Basic products of other cereals”: buckwheat, millet, sorghum, or spelt. “Savory cereals dishes”: dumplings, couscous, risotto, pizza, pancake, or pie.

Refined grain intake and BC risk

Overall, no evidence of association between different categories of total refined grain intake and BC risk was observed. However, males showed a borderline decreased BC risk per 1-SD increment (HRmodel 2: 0.92; 95% CI: 0.86, 1.00; P for trend = 0.040) (Table 2). Looking at the individual refined grain sources, similar null-associations were found, except for the intake of “pasta or noodles,” which was inversely associated with BC risk when comparing medium intake with low intake (HRmodel2: 0.90; 95% CI: 0.81, 0.99; HR per 1-SD increment: 0.99; 95% CI: 0.94, 1.04; P for trend = 0.697) (Table 3).

Dietary fiber intake and BC risk

shows the associations of the intakes of total dietary fiber and dietary fiber from different food sources with BC risk. The intake of total dietary fiber was inversely associated with BC risk (comparing the highest with the lowest intake tertile: HRmodel2: 0.86; 95% CI: 0.76, 0.98; HR per 1-SD increment: 0.91; 95% CI: 0.82, 0.98; P for trend = 0.021). Consistent results were observed for both males (comparing the highest with the lowest intake tertile: HRmodel2: 0.89; 95% CI: 0.79, 0.98; HR per 1-SD increment: 0.90; 95% CI: 0.83, 0.97; P for trend = 0.007) and females (comparing the highest with the lowest intake tertile: HRmodel2: 0.79; 95% CI: 0.66, 0.97; HR per 1-SD increment: 0.89; 95% CI: 0.79, 1.00; P for trend = 0.049); however, no association was observed in the smoking-stratified analyses. For the individual dietary fiber food sources, only vegetable fiber showed a borderline decreased BC risk per 1-SD increment (HRmodel2: 0.93; 95% CI: 0.86, 1.00; P for trend = 0.046).
TABLE 4

Risk of bladder cancer according to intakes of total dietary fiber and individual sources of dietary fiber[1]

Grain source, subgroup, intake tertilesModel 2[2]
Cases/participants, nHR (95% CI)HR per 1-SD increase (95% CI) P-trend
Total dietary fiber, g/d
 Overall
  Tertile 11015/191,576Ref.0.91 (0.82, 0.98)0.021
  Tertile 21097/191,5750.92 (0.83, 1.02)
  Tertile 31102/191,5750.86 (0.76, 0.98)
 Male
  Tertile 1775/62,954Ref.0.90 (0.83, 0.97)0.007
  Tertile 2971/62,9540.94 (0.85, 1.03)
  Tertile 3670/62,9540.89 (0.79, 0.98)
 Female
  Tertile 1322/128,622Ref.0.89 (0.79, 1.00)0.049
  Tertile 2272/128,6210.81 (0.68, 0.96)
  Tertile 3204/128,6210.79 (0.66, 0.97)
 Never smoker
  Tertile 1242/95,457Ref.0.95 (0.80, 1.12)0.523
  Tertile 2272/95,4570.91 (0.69, 1.20)
  Tertile 3170/95,4560.84 (0.67, 1.04)
 Current smoker
  Tertile 1436/39,716Ref.0.94 (0.85, 1.03)0.287
  Tertile 2438/39,7150.92 (0.78, 1.09)
  Tertile 3324/39,7150.82 (0.67, 1.00)
 Former smoker
  Tertile 1473/56,404Ref.0.89 (0.80, 1.00)0.059
  Tertile 2492/56,4030.97 (0.82, 1.14)
  Tertile 3394/56,4030.85 (0.70, 1.05)
Cereal fiber, g/d
 Overall
  Tertile 11111/191,576Ref.0.96 (0.91, 1.01)0.124
  Tertile 21203/191,5760.95 (0.86, 1.04)
  Tertile 3900/191,5740.95 (0.85, 1.07)
 Male
  Tertile 1869/62,954Ref.0.91 (0.86, 1.01)0.058
  Tertile 21017/62,9540.95 (0.85, 1.05)
  Tertile 3530/62,9540.89 (0.77, 1.03)
 Female
  Tertile 1300/128,622Ref.0.97 (0.91, 1.07)0.329
  Tertile 2293/128,6211.07 (0.85, 1.34)
  Tertile 3205/128,6211.03 (0.86, 1.23)
 Never smoker
  Tertile 1227/95,457Ref.0.98 (0.91, 1.04)0.435
  Tertile 2245/95,4571.01 (0.80, 1.34)
  Tertile 3185/95,4560.99 (0.81, 1.23)
 Current smoker
  Tertile 1462/39,723Ref.0.97 (0.89, 1.06)0.525
  Tertile 2416/39,7181.00 (0.87, 1.16)
  Tertile 3320/39,7050.96 (0.79, 1.15)
 Former smoker
  Tertile 1450/56,404Ref.0.90 (0.86, 1.01)0.275
  Tertile 2557/56,4030.88 (0.76, 1.02)
  Tertile 3352/56,4030.82 (0.69, 1.00)
Fruit fiber, g/d
 Overall
  Tertile 11059/191,576Ref.0.98 (0.90, 1.06)0.573
  Tertile 2950/191,6130.98 (0.87, 1.11)
  Tertile 31205/191,5370.97 (0.89, 1.07)
 Male
  Tertile 1688/62,954Ref.1.01 (0.92, 1.11)0.792
  Tertile 2689/62,9540.98 (0.88, 1.10)
  Tertile 31039/62,9541.02 (0.89, 1.17)
 Female
  Tertile 1250/128,628Ref.0.87 (0.73, 1.03)0.119
  Tertile 2264/128,6150.94 (0.78, 1.13)
  Tertile 3284/128,3370.76 (0.58, 1.02)
 Never smoker
  Tertile 1170/95,459Ref.0.94 (0.78, 1.13)0.517
  Tertile 2231/95,4551.02 (0.88, 1.19)
  Tertile 3256/95,4560.89 (0.73, 1.09)
 Current smoker
  Tertile 1380/39,716Ref.0.99 (0.88, 1.18)0.574
  Tertile 2376/39,7151.17 (0.95, 1.43)
  Tertile 3442/39,7151.11 (0.83, 1.49)
 Former smoker
  Tertile 1396/56,413Ref.0.97 (0.86, 1.10)0.639
  Tertile 2384/56,3940.93 (0.81, 1.08)
  Tertile 3579/56,4031.03 (0.86, 1.24)
Vegetable fiber, g/d
 Overall
  Tertile 11185/191,576Ref.0.93 (0.86, 1.00)0.046
  Tertile 21223/191,5750.98 (0.89, 1.08)
  Tertile 3806/191,5750.91 (0.79, 1.05)
 Male
  Tertile 1718/62,954Ref.0.95 (0.88, 1.02)0.176
  Tertile 2810/62,9541.02 (0.91, 1.15)
  Tertile 3888/62,9540.90 (0.78, 1.05)
 Female
  Tertile 1359/128,622Ref.0.88 (0.74, 1.05)0.151
  Tertile 2295/128,6210.90 (0.75, 1.08)
  Tertile 3144/128,6210.77 (0.59, 1.01)
 Never smoker
  Tertile 1282/95,457Ref.0.92 (0.76, 1.12)0.400
  Tertile 2237/95,4570.93 (0.76, 1.13)
  Tertile 3138/95,4570.93 (0.70, 1.24)
 Current smoker
  Tertile 1403/39,716Ref.0.87 (0.76, 1.01)0.171
  Tertile 2453/39,7150.95 (0.81, 1.12)
  Tertile 3342/39,7150.84 (0.67, 1.04)
 Former smoker
  Tertile 1488/56,404Ref.0.94 (0.82, 1.07)0.328
  Tertile 2497/56,4031.01 (0.87, 1.17)
  Tertile 3374/56,4030.89 (0.72, 1.09)

The intervals of tertiles were defined as follows: total dietary fiber: 1) overall, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d; 2) male, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 26 g/d, tertile 3 > 26 g/d; 3) female, 0 ≤ tertile 1 ≤ 18 g/d, 18 < tertile 2 ≤ 26 g/d, tertile 3 > 26 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 18 g/d, 18 < tertile 2 ≤ 26 g/d, tertile 3 > 26 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d; cereal fiber: 1) overall, 0 ≤ tertile 1 ≤ 7 g/d, 7 < tertile 2 ≤ 12 g/d, tertile 3 > 12 g/d; 2) male, 0 ≤ tertile 1 ≤ 7 g/d, 7 < tertile 2 ≤ 13 g/d, tertile 3 > 13 g/d; 3) female, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 8 g/d, 8 < tertile 2 ≤ 13 g/d, tertile 3 > 13 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; fruit fiber: 1) overall, 0 ≤ tertile 1 ≤ 2 g/d, 2 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 2) male, 0 ≤ tertile 1 ≤ 1 g/d, 1 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; 3) female, 0 ≤ tertile 1 ≤ 2 g/d, 2 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 2 g/d, 2 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 1 g/d, 1 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 1 g/d, 1 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; vegetable fiber: 1) overall, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 2) male, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 7 g/d, tertile 3 > 7 g/d; 3) female, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d. Reference group was lowest intake (tertile 1). P-trend < 0.05 was considered statistically significant.

Model 2 of Cox regression: adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous).

Risk of bladder cancer according to intakes of total dietary fiber and individual sources of dietary fiber[1] The intervals of tertiles were defined as follows: total dietary fiber: 1) overall, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d; 2) male, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 26 g/d, tertile 3 > 26 g/d; 3) female, 0 ≤ tertile 1 ≤ 18 g/d, 18 < tertile 2 ≤ 26 g/d, tertile 3 > 26 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 18 g/d, 18 < tertile 2 ≤ 26 g/d, tertile 3 > 26 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d; cereal fiber: 1) overall, 0 ≤ tertile 1 ≤ 7 g/d, 7 < tertile 2 ≤ 12 g/d, tertile 3 > 12 g/d; 2) male, 0 ≤ tertile 1 ≤ 7 g/d, 7 < tertile 2 ≤ 13 g/d, tertile 3 > 13 g/d; 3) female, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 8 g/d, 8 < tertile 2 ≤ 13 g/d, tertile 3 > 13 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 6 g/d, 6 < tertile 2 ≤ 11 g/d, tertile 3 > 11 g/d; fruit fiber: 1) overall, 0 ≤ tertile 1 ≤ 2 g/d, 2 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 2) male, 0 ≤ tertile 1 ≤ 1 g/d, 1 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; 3) female, 0 ≤ tertile 1 ≤ 2 g/d, 2 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 2 g/d, 2 < tertile 2 ≤ 4 g/d, tertile 3 > 4 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 1 g/d, 1 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 1 g/d, 1 < tertile 2 ≤ 3 g/d, tertile 3 > 3 g/d; vegetable fiber: 1) overall, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 2) male, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 7 g/d, tertile 3 > 7 g/d; 3) female, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 4) never smoker, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 9 g/d, tertile 3 > 9 g/d; 5) current smoker, 0 ≤ tertile 1 ≤ 5 g/d, 5 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; 6) former smoker, 0 ≤ tertile 1 ≤ 4 g/d, 4 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d. Reference group was lowest intake (tertile 1). P-trend < 0.05 was considered statistically significant. Model 2 of Cox regression: adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous).

Joint association of total whole grain and total dietary fiber with BC risk

shows the results of the Cox regression analyses for the potential joint effect of total whole grain and total dietary fiber on BC. Individuals with the highest intake of both total whole grain and total dietary fiber showed a 28% reduced BC risk (95% CI: 0.54, 0.93; P for trend = 0.031) compared with individuals with the lowest intakes of both total whole grain and total dietary fiber.
TABLE 5

Joint association of intake of total whole grain and total dietary fiber with bladder cancer risk[1]

Total whole grain and total dietary fiber, g/d
Model 2[2]
Total dietary fiber, g/dTertile 1Tertile 2Tertile 3 P-trend P-interaction
Tertile 1
 Cases, n3484212220.0310.027
 HR (95% CI)Ref.0.91 (0.79, 1.06)0.89 (0.70, 1.14)
Tertile 2
 Cases, n93157103
 HR (95% CI)0.94 (0.74, 1.21)0.86 (0.69, 1.08)0.82 (0.63, 1.09)
Tertile 3
 Cases, n84152153
 HR (95% CI)0.79 (0.60, 1.03)0.71 (0.57, 0.88)0.72 (0.54, 0.93)

The intervals of tertiles were defined as follows: total whole grain: 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; total dietary fiber: 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d. P-trend < 0.05 was considered statistically significant. Reference group was lowest intake of both total whole grain and total dietary fiber.

Model 2 of Cox regression: adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous).

Joint association of intake of total whole grain and total dietary fiber with bladder cancer risk[1] The intervals of tertiles were defined as follows: total whole grain: 0 ≤ tertile 1 ≤ 3 g/d, 3 < tertile 2 ≤ 8 g/d, tertile 3 > 8 g/d; total dietary fiber: 0 ≤ tertile 1 ≤ 17 g/d, 17 < tertile 2 ≤ 25 g/d, tertile 3 > 25 g/d. P-trend < 0.05 was considered statistically significant. Reference group was lowest intake of both total whole grain and total dietary fiber. Model 2 of Cox regression: adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior and no information on pack-years)]}, total energy intake (kcal/d; continuous), ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous).

Dose-response analyses

, , and show dose–response relations between grain/dietary fiber intake and the risk of BC. There were inverse associations of intakes of total whole grain and total dietary fiber with BC risk, but no association was observed of intakes of total refined grain, cereal fiber, fruit fiber, and vegetable fiber with BC risk. A significant reduction of risk was shown at >15 g/d intake of total whole grain and >25 g/d intake of total dietary fiber; the estimated HRs were 0.97 (0.95, 0.99) and 0.96 (0.94, 0.98) per 5-g daily increment, respectively.
FIGURE 1

Dose–response relations between grain/dietary fiber intake and the risk of bladder cancer among total whole grain (A), total refined grain (B), total dietary fiber (C), and cereal fiber (D). The solid lines represent the HRs; the dashed lines represent the 95% CIs for the trend. The HRs were adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior, and no information on pack-years)]}, ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous) (model 2). Reference group was nonintake. P values < 0.05 were considered statistically significant for nonlinearity. P-increments < 0.05 were considered statistically significant.

Dose–response relations between grain/dietary fiber intake and the risk of bladder cancer among total whole grain (A), total refined grain (B), total dietary fiber (C), and cereal fiber (D). The solid lines represent the HRs; the dashed lines represent the 95% CIs for the trend. The HRs were adjusted for age (y; continuous), sex (male/female), smoking {smoking was defined as: 0 (never smokers); 1 [current light smokers (i.e., smoking <20 pack-years)]; 2 [current heavy smokers (i.e., smoking >20 pack-years)]; 3 [current smokers (no information on pack-years)]; 4 [former light smokers (i.e., smokers who ceased smoking >1 y prior and smoked <20 pack-years)]; 5 [former heavy smokers (i.e., smokers who ceased smoking >1 y prior and smoked >20 pack-years)]; or 6 [former smokers (smokers who ceased smoking >1 y prior, and no information on pack-years)]}, ethnicity (Caucasian or non-Caucasian, if applicable), alcohol intake (mL/d; continuous), fruit intake (g/d; continuous), fat intake (g/d; continuous), meat intake (g/d; continuous), sugar intake (g/d; continuous), vegetable intake (g/d; continuous), and total fluid intake (mL/d; continuous) (model 2). Reference group was nonintake. P values < 0.05 were considered statistically significant for nonlinearity. P-increments < 0.05 were considered statistically significant.

Sensitivity analyses

Removing BC cases diagnosed within the first 2 y after enrolling into each individual study gave similar results, in which a decreased BC risk was observed for total whole grain (comparing the highest with the lowest intake tertile: HRmodel2: 0.81; 95% CI: 0.67, 0.97; HR per 1-SD increment: 0.95; 95% CI: 0.91, 1.00; P for trend = 0.040) and for total dietary fiber (comparing the highest with the lowest intake tertile: HRmodel2: 0.85; 95% CI: 0.76, 0.96; HR per 1-SD increment: 0.86; 95% CI: 0.78, 0.94; P for trend = 0.002) (). The analysis excluding missing data (model 2) showed similar results to the analysis with multiple imputation (). Results of the quintile-based analyses showed inverse associations between total whole grain and total dietary fiber intakes and BC risk (comparing the highest with the lowest intake quintile: HRmodel2: 0.86; 95% CI: 0.75, 0.98; P for trend = 0.032; and HRmodel2: 0.84; 95% CI: 0.72, 0.98; P for trend = 0.022, respectively) (). In addition, excluding pasta as a source of total refined grain showed the same results as when pasta intake was included (). The analysis adjusting for both smoking status and smoking pack-years showed similar results with the adjustment of the smoking dummy variable (). The meta-analysis approach showed similar results, that is, a significantly reduced BC risk with total whole grain intake (HR: 0.89; 95% CI: 0.81, 0.98) and total dietary fiber intake (HR: 0.89; 95% CI: 0.80, 0.98), whereas there was no evidence of association for intakes of total refined grain and individual sources of dietary fiber with BC risk (); in addition, after removing the study that most likely dominated the analysis for each dietary factor, results remained the same ().

Discussion

This large, multicenter, prospective cohort study indicates a potential beneficial effect of total whole grain (particularly brown rice) and total dietary fiber intake for the prevention of BC, whereas intakes of total refined grain and individual fiber sources (i.e., cereal, fruit, and vegetable) did not show any significant association with BC risk. To our knowledge, this is the first prospective study to investigate the association between whole grain intake and BC risk; in line with this result a previously conducted case-control study reported a nonsignificant protective effect of higher intake of total whole grains on BC risk (23), and another case-control study conducted in the 1980s reported a modest inverse association (24). Because it was reported that an increased BC risk was associated with a high dietary glycemic load (23), which has been reported to be reduced by the postprandial glucose and insulin responses to whole grain intake (61), the authors suggested that any potential benefit of whole grain intake to BC risk may act by mitigating the carcinogenic effects of hyperglycemia and hyperinsulinemia (62–64). In addition, our findings are strengthened by experimental studies which show that whole grains may exert their potential antitumor activity through the reduction of inflammation (65), which is thought to be related to a decreased BC risk (66). One plausible reason total refined grain was not found to be protective for BC is that refined grains lack a high amount of dietary fiber and other bioactive compounds which are rich in whole grains (67, 68). The lack of dietary fiber could especially be emphasized because the present study shows that high intake both of total whole grain and of total dietary fiber was associated with a decreased BC risk. Epidemiological studies have shown that the intakes of whole grains and of dietary fiber were associated with a lower risk of chronic diseases (69–73), including various cancer types (74–76). In addition, experimental studies have reported that dietary fiber may protect cancer by improving insulin sensitivity and metabolic regulation, reducing inflammation, modulating the gut microbiota, removal of damaged cells, diluting carcinogens, and decreasing transit time (65, 77–81). Although most standard pastas are made with refined wheat flour, several whole-wheat pastas are available and worldwide consumed in nontrivial amounts (68, 82). Considering that several cohorts have been conducted after the 2000s, the pasta intake could be a mixture of pasta made of refined and whole grains. Unfortunately, we were unable to distinguish between these types of pasta intake. Nevertheless, we only found a borderline-decreased BC risk for medium intake of “pasta or noodles.” In addition, the results of total refined grains were unchanged after excluding pasta intake. Because the lack of information on pasta types might have led to inaccurate estimates, results from the present study on the influence of pasta could be due to chance, therefore, they must be interpreted with caution. Further investigation of the influence of specific pasta types on BC risk may be warranted. Half of the world's population relies on rice as a daily staple food and it is considered one of the most important crops globally. The association of this specific grain with BC risk might differ from any other grains, because rice has been reported to contain considerable amounts of inorganic arsenic (83), which has been acknowledged to be a human carcinogen for bladder (84). A previous prospective study in the United States found no association for BC risk with either brown rice or white rice (85). In our study we showed that both brown and white rice do not cause an increased BC risk; in addition, it has been reported that the washing and cooking procedure reduces the arsenic content of rice (83, 86), therefore, the potential influence of arsenic on the findings of the present study is minimal. In the present study we found that high intake of total dietary fiber was significantly associated with a lower BC risk. However, none of the dietary fiber sources were associated with BC risk individually. One possible explanation is that individual dietary fiber intakes failed to reach the threshold at which a protective effect is manifested. In addition, some residual confounding such as “cooking methods” might mask the potential beneficial effect of cereal-, fruit-, or vegetable-fiber intake. The joint effect of both whole grains and dietary fiber showed a stronger inverse association with BC risk than did the intakes individually. This finding confirmed the assumption that potential benefits of fiber may be derived from its combination with nutrients of whole grains working together, which suggests the simultaneous intake of both as part of a healthy, nutritious diet. Although current dietary guidelines recommend that individuals derive at least half of their grain intake from whole grains, no quantifications are given for the amount of total whole grains to be consumed (87). The present study shows that a daily intake of ≥15 g (uncooked) should be consumed in order to reduce the BC risk. For dietary fiber, the European Commission's strategy recommends a daily dietary fiber intake of 25–38 g in order to prevent noncommunicable diseases (88). This is in accordance with our observation of 25 g/d total dietary intake for reducing BC. The present study pooled data from 13 prospective cohorts, enabling detailed analyses with good precision and statistical power. However, this study also includes some limitations: 1) other than the included adjustments, limited information was available on other possible risk factors [e.g., BMI (89) and diabetes (90)] or dietary additives (e.g., dip or sauce); 2) some tumor subtype information was missing, which hampered the statistical power required for stratified subgroup analyses; 3) although status as well as duration and intensity of smoking were taken into account, residual confounding by smoking is difficult to rule out completely—however, because never smokers showed similar results to the overall analysis adjusted for smoking, the effect of residual confounding is likely to be minimal; 4) people with a high intake of whole grains might have generally healthier lifestyles and diets than those with a low intake (91, 92), thus we could not rule out the possibility that some of the associations could be more likely due to a healthy lifestyle than to whole grain intake per se; 5) the sample size for whole grains was significantly smaller than for refined grains and dietary fiber, which may have led to less statistical power; 6) data were not available on dietary fiber types (e.g., soluble compared with insoluble), thus we were unable to investigate the association by dietary fiber subtypes; 7) for most cohorts, the exposure variable was assessed by FFQs—therefore, measurement error and misclassification of study participants in terms of the exposure and outcome are unavoidable; and 8) the present study sample consisted mostly of Caucasians, and this may limit the generalizability of our results to other racial/ethnic populations or geographic regions. In summary, our study, of >3200 cases of incident BC occurring in almost 0.6 million participants, indicates a decreased BC risk with higher intakes of total whole grain (>8 g/d) and total dietary fiber (>23 g/d) individually and jointly. This, in turn, supports recommendations to increase the intakes of whole grains and dietary fiber to improve public health. Click here for additional data file.
  81 in total

1.  Whole grain intake is associated with lower body mass and greater insulin sensitivity among adolescents.

Authors:  Lyn M Steffen; David R Jacobs; Maureen A Murtaugh; Antoinette Moran; Julia Steinberger; Ching-Ping Hong; Alan R Sinaiko
Journal:  Am J Epidemiol       Date:  2003-08-01       Impact factor: 4.897

2.  Flexible meta-regression functions for modeling aggregate dose-response data, with an application to alcohol and mortality.

Authors:  Vincenzo Bagnardi; Antonella Zambon; Piero Quatto; Giovanni Corrao
Journal:  Am J Epidemiol       Date:  2004-06-01       Impact factor: 4.897

3.  High dose human insulin and insulin glargine promote T24 bladder cancer cell proliferation via PI3K-independent activation of Akt.

Authors:  S Liu; Y Li; T Lin; X Fan; Y Liang; U Heemann
Journal:  Diabetes Res Clin Pract       Date:  2010-12-03       Impact factor: 5.602

4.  Intake of whole grains in Scandinavia is associated with healthy lifestyle, socio-economic and dietary factors.

Authors:  Cecilie Kyrø; Guri Skeie; Lars O Dragsted; Jane Christensen; Kim Overvad; Göran Hallmans; Ingegerd Johansson; Eiliv Lund; Nadia Slimani; Nina F Johnsen; Jytte Halkjær; Anne Tjønneland; Anja Olsen
Journal:  Public Health Nutr       Date:  2011-02-22       Impact factor: 4.022

5.  Fasting serum glucose level and cancer risk in Korean men and women.

Authors:  Sun Ha Jee; Heechoul Ohrr; Jae Woong Sull; Ji Eun Yun; Min Ji; Jonathan M Samet
Journal:  JAMA       Date:  2005-01-12       Impact factor: 56.272

Review 6.  The role of inflammation in bladder cancer.

Authors:  Georgios Gakis
Journal:  Adv Exp Med Biol       Date:  2014       Impact factor: 2.622

7.  The present and future burden of urinary bladder cancer in the world.

Authors:  Martine Ploeg; Katja K H Aben; Lambertus A Kiemeney
Journal:  World J Urol       Date:  2009-02-15       Impact factor: 4.226

Review 8.  Modifiable risk factors for the prevention of bladder cancer: a systematic review of meta-analyses.

Authors:  Abdulmohsen H Al-Zalabani; Kelly F J Stewart; Anke Wesselius; Annemie M W J Schols; Maurice P Zeegers
Journal:  Eur J Epidemiol       Date:  2016-03-21       Impact factor: 8.082

9.  International pooled study on diet and bladder cancer: the bladder cancer, epidemiology and nutritional determinants (BLEND) study: design and baseline characteristics.

Authors:  Maria E Goossens; Fatima Isa; Maree Brinkman; David Mak; Raoul Reulen; Anke Wesselius; Simone Benhamou; Cristina Bosetti; Bas Bueno-de-Mesquita; Angela Carta; Md Farouk Allam; Klaus Golka; Eric J Grant; Xuejuan Jiang; Kenneth C Johnson; Margaret R Karagas; Eliane Kellen; Carlo La Vecchia; Chih-Ming Lu; James Marshall; Kirsten Moysich; Hermann Pohlabeln; Stefano Porru; Gunnar Steineck; Marianne C Stern; Li Tang; Jack A Taylor; Piet van den Brandt; Paul J Villeneuve; Kenji Wakai; Elisabete Weiderpass; Emily White; Alicja Wolk; Zuo-Feng Zhang; Frank Buntinx; Maurice P Zeegers
Journal:  Arch Public Health       Date:  2016-07-06

Review 10.  Inflammation and cancer.

Authors:  Mariko Murata
Journal:  Environ Health Prev Med       Date:  2018-10-20       Impact factor: 3.674

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  4 in total

1.  Relationship Between Dietary Fiber and Vitamin C Intake and Oral Cancer.

Authors:  Jing Wang; Yi Fan; Jiawen Qian; Sijie Wang; Yanni Li; Mingming Xu; Fa Chen; Jing Wang; Yu Qiu; Lisong Lin; Baochang He; Fengqiong Liu
Journal:  Front Public Health       Date:  2022-05-12

Review 2.  Insulin and cancer: a tangled web.

Authors:  Brooks P Leitner; Stephan Siebel; Ngozi D Akingbesote; Xinyi Zhang; Rachel J Perry
Journal:  Biochem J       Date:  2022-03-18       Impact factor: 3.766

3.  Dietary B group vitamin intake and the bladder cancer risk: a pooled analysis of prospective cohort studies.

Authors:  Iris W A Boot; Anke Wesselius; Evan Y W Yu; Maree Brinkman; Piet van den Brandt; Eric J Grant; Emily White; Elisabete Weiderpass; Pietro Ferrari; Matthias B Schulze; Bas Bueno-de-Mesquita; Maria Jose-Sanchez; Bjorn Gylling; Maurice P Zeegers
Journal:  Eur J Nutr       Date:  2022-02-07       Impact factor: 4.865

Review 4.  Let food be thy medicine: the role of diet in colorectal cancer: a narrative review.

Authors:  Ying Zheng; Lingnan Meng; Hao Liu; Lijuan Sun; Yongzhan Nie; Qiong Wu; Daiming Fan; Mengbin Li
Journal:  J Gastrointest Oncol       Date:  2022-08
  4 in total

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