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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Cancer. Author manuscript; available in PMC 2011 September 15.
Published in final edited form as:
PMCID: PMC2936663
NIHMSID: NIHMS208022

Meat and components of meat and the risk of bladder cancer in the NIH-AARP Diet and Health Study

Abstract

Background

Meat could be involved in bladder carcinogenesis via multiple potentially carcinogenic meat-related compounds related to cooking and processing, including nitrate, nitrite, heterocyclic amines (HCAs), and polycyclic aromatic hydrocarbons. We comprehensively investigated the association between meat and meat components and bladder cancer.

Methods

During 7 years of follow-up, 854 transitional cell bladder cancer cases were identified among 300,933 men and women who completed a validated food frequency questionnaire in the large prospective NIH-AARP Diet and Health Study. We estimated intake of nitrate and nitrite from processed meat and HCAs and PAHs from cooked meat using quantitative databases of measured values. We calculated total dietary nitrate and nitrite based on literature values.

Results

The hazard ratios (HR) and 95% confidence intervals (CI) for red meat (HR for fifth compared to first quintile=1.22, 95% CI=0.96–1.54, p-trend=0.07) and the HCA 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) (HR=1.19, 95% CI=0.95–1.48, p-trend=0.06) conferred a borderline statistically significant increased risk of bladder cancer. We observed positive associations in the top quintile for total dietary nitrite (HR=1.28, 95% CI=1.02–1.61, p-trend= 0.06) and nitrate plus nitrite intake from processed meat (HR=1.29 95% CI=1.00–1.67, p-trend= 0.11).

Conclusions

These findings provide modest support for a role for total dietary nitrite and nitrate plus nitrite from processed meat in bladder cancer. Our results also suggest a positive association between red meat and PhIP and bladder carcinogenesis.

Keywords: Diet, bladder cancer, meat, nitrate, nitrite

Introduction

Recognized risk factors for bladder cancer include smoking, as well as occupational or environmental exposure to aromatic amines, polycyclic aromatic hydrocarbons (PAHs), and arsenic.13 However, these exposures only partly explain the etiology of bladder cancer. Since nutrients or their metabolites are excreted through the urinary tract, some dietary factors could be involved in carcinogenesis via contact with the bladder epithelium2, 4, 5 or through systemic exposure.

Meat is an important dietary component to consider in relation to bladder cancer, as it is a source of multiple potentially carcinogenic compounds resulting from cooking or processing. Evidence from prospective epidemiologic studies of meat is inconsistent, with some positive associations between certain meat types and bladder cancer6, 7 and other studies observing no association.812 Comprehensive epidemiologic data on meat-related exposures potentially mechanistically involved in bladder carcinogenesis are lacking.

A key hypothesis for bladder carcinogenesis involves nitrate and nitrite, compounds added to processed meat for preservation and enhance color and flavor. Nitrate and nitrite are precursors to N-nitroso compounds (NOCs), which induce tumors in many organs, including the bladder, in multiple animal species.1316 In healthy individuals, NOCs can form endogenously from nitrite in the presence of amines, amides, and bacteria, and may be excreted in the urine.1719 Additional NOC formation can also occur directly in the bladder when bacterial infection occurs. The source of nitrate and nitrite is important because the primary sources of nitrate can be fruits and vegetables, which contain inhibitors of endogenous nitrosation.20, 21 There are few epidemiologic studies of dietary nitrate19, 22, 23 and nitrite23, 24 and bladder cancer.

Given the role of aromatic amines and PAHs from occupational exposures in bladder cancer and the presence of these compounds in cigarette smoke, another important risk factor, heterocyclic amines (HCAs) and PAHs formed in meats prepared by high temperature cooking methods2528 could be implicated in this malignancy. HCAs and PAHs are mutagenic and carcinogenic in animal studies,29, 30 and some HCAs induce bladder tumors specifically.3133 Two case-control studies of HCAs from meat in relation to bladder cancer have been null.34, 35

We evaluated the role of meat, nitrate, nitrite, and meat mutagens in relation to transitional cell bladder cancer in a large prospective cohort study by utilizing a detailed meat questionnaire linked to a database of published values from the literature and quantitative databases of laboratory measures of meat samples.

Methods

Study population

From 1995 to 1996, the NIH-AARP Diet and Health Study enrolled men and women, ages 50 to 71 years, from six U.S. states (California, Florida, Louisiana, New Jersey, North Carolina, Pennsylvania) and two metropolitan areas (Atlanta, Georgia; Detroit, Michigan). At baseline, participants completed a mailed self-administered questionnaire on demographic, lifestyle, and medical characteristics. Details of the study design have been described elsewhere.36 The study was approved by the Special Studies Institutional Review Board of the U.S. National Cancer Institute.

Dietary variables

At baseline, participants completed a 124-item food frequency questionnaire (FFQ), based on the National Cancer Institute’s Diet History Questionnaire (http://riskfactor.cancer.gov/DHQ/forms/files/shared/dhq1.2002.sample.pdf). Portion sizes and daily nutrient intakes were calculated with the 1994–1996 U.S. Department of Agriculture’s Continuing Survey of Food Intake by Individuals.37 The FFQ compared favorably to other FFQs,38 and was validated in a sub-set of this cohort against two nonconsecutive 24-hour dietary recalls.36 Energy-adjusted correlation coefficients for red meat were 0.62 and 0.70 for men and women, respectively.39 Approximately six months after baseline, participants completed a mailed risk factor questionnaire (RFQ) with questions on meat cooking methods and doneness levels. The FFQ meat-cooking module has been compared to using multiple food diaries, and its ability to rank individuals according to HCA intake was acceptable.40 Red meat included bacon, beef, cold cuts, ham, hamburger, hot dogs, liver, pork, sausage, and steak. White meat included all chicken and turkey meat products and fish. Processed meat included bacon, sausage, luncheon meats, ham, and hotdogs. Meat products from mixed dishes were included in the relevant meat groups.

Nitrate and nitrite intake from processed meats was calculated with a database of laboratory measured values of these compounds in 10 types of processed meats representing 90% of processed meats consumed by the U.S. population.41 For total dietary exposure the published literature for nitrate and nitrite measurement data was reviewed and a mean of the published values for individual foods was calculated and weighted by the sample size of the study. Food-specific nitrate and nitrite values were combined using the same methodology applied to other nutrients.38

With meat cooking method (grilled/BBQ, pan-fried, microwaved, and broiled) and doneness level (well-done/very well-done and medium/rare) data and the Computerized Heterocyclic Amines Resource for Research in Epidemiology of Disease (CHARRED) (http://charred.cancer.gov),41 we estimated three HCAs: 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (DiMeIQx), 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx), and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP). With CHARRED, we also estimated benzo[a]pyrene (B[a]P), a marker of overall PAH exposure from meat, and total mutagenic activity, a measure incorporating mutagenicity of all meat-related mutagens.

Identification of cases and cohort follow-up

We identified incident transitional cell bladder cancers through probabilistic linkage with state cancer registries; eight original states plus three additional states where participants commonly move (Texas, Arizona, Nevada). Cancer endpoints were defined by anatomic site and histologic code of the International Classification of Diseases for Oncology.42 Cases included transitional cell bladder cancer with codes C67.0–C67.9, encompassing morphologies 8050, 8120–8122, and 8130.

Cohort members were followed for change of address using the U.S. Postal Service. Vital status was ascertained by annual linkage of the cohort to the U.S. Social Security Administration Death Master File, follow-up searches of the National Death Index Plus for participants who matched to the Social Security Administration Death Master File, cancer registry linkage, questionnaire responses, and responses to other mailings. Follow-up for this analysis was from the date the RFQ was received until December 31, 2003, or when the participant moved out of one of the state cancer registry areas, had a cancer diagnosis, or died, whichever came first. Overall, only 4% of participants were lost to follow-up as a result of moving and these individuals were similar in regards to baseline characteristics as those for which follow-up information was available.

Statistical analysis

A total of 566,402 persons returned the baseline questionnaire (after excluding duplicates and subjects who died, moved before entry, or withdrew from the study) and of these, 337,074 returned the RFQ. We further excluded individuals who: died before the RFQ was received (n=1,619); moved out of the eight study areas before returning the RFQ (n=547); had a proxy complete either questionnaire (n=10,383); had prevalent cancer (based on cancer registry or self-report) at RFQ entry (n=18,844); had a death only report for any cancer (n=2,246); or reported extreme total energy intake (n=2,483), defined as more than two inter-quartile ranges above the 75th or below the 25th percentile on the logarithmic scale. Our analytic cohort consisted of 300,933 persons; 125,574 women and 175,359 men.

Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression with age as the underlying time metric. Diagnostic testing, using a time interaction model, for proportional hazards indicated assumptions were not violated. Dietary variables were energy adjusted using the multivariate nutrient density method; residual energy adjustment resulted in similar risk estimates.43 Quantile cut-points were based on intake in the analytic cohort; the lowest quantile served as the referent; although quintiles were used for most variables, tertiles were used for cooking methods and doneness levels due to a lower range of intake. All models summed to total meat; for example, red meat and white meat were included in the same model, as were meats cooked rare, medium, well-done plus those with no doneness information. Multivariate models were adjusted for the following characteristics which altered the risk estimates by 10% or greater: age (continuous, years), gender, smoking (never, quit ≥ 10 years ago, quit 5–9 years ago, quit 1–4 years ago, quit <1 year ago or ≤ 20 cigarettes/day, 20–40 cigarettes/day, >40 cigarettes/day), and intakes of fruit (continuous, cup equivalents/1,000 kcal), vegetables (continuous, cup equivalents/1,000 kcal), beverages (continuous, mL/day; sum of beer, coffee, juice, liquor, milk, soda, tea and wine), and total energy (continuous, kcal). Adjustment for other possible confounders, including aspirin use, body mass index (BMI), dairy, ethnicity, history of diabetes, physical activity, and intakes of dairy and vitamins C and E did not alter risk estimates. Tests for linear trend were based on quintile median values. P-values are two-sided and analyses were conducted using SAS (SAS Institute, Cary, NC, Version 9).

We assessed effect modification by gender, smoking, beverage intake, and vitamin C (dietary, supplemental, total) with cross product terms in the multivariate models. To account for potential exposure to nitrate from drinking water, in sensitivity analyses we excluded individuals whose enrollment address was in a census tract area in which 50% of the area of the tract was estimated to have groundwater nitrate levels ≥10 mg/L nitrate-nitrogen (U.S. Environmental Protection Agency Maximum Contaminant Level) as determined by a nationwide model incorporating information on land use, soil type, and other factors.44

Results

During 1,922,817 person-years of follow-up, we identified 854 transitional cell bladder cancers (720 men, 134 women). Individuals consuming the most red meat were younger, less educated and physically active, and had lower intakes of fruits, vegetable, and vitamins C and E than those consuming the least (Table 1). Those in the highest quintile of red meat compared to those in the lowest were more likely to be non-Hispanic white, current smokers, to have a higher BMI, and to have higher intakes of beverages and total energy.

Table 1
Means and proportions of baseline characteristics by red meat quintiles (g/1000kcal) (n=300,933).

We observed a borderline statistically significant increased risk of bladder cancer for those in the highest versus the lowest quintile of red meat (HR=1.22, 95% CI=0.96–1.54, p-trend= 0.07), but no association with white meat or processed meat (Table 2). The red meat association was driven by processed red meats (HR for fifth compared to first quintile=1.30, 95% CI=1.00–1.69, p-trend=0.17), rather than non-processed red meats (HR=1.08, 95% CI=0.84–1.38, p-trend=0.22) (data not shown). There were no associations with beef, bacon, hamburger, sausage, or steak; however, we did observe a positive non-linear association for red meat cold cuts (HR for fifth compared to first quintile=1.42, 95% CI=1.10–1.84, p-trend=0.18) (data not shown). Analyses using residual energy adjustment (g/day) resulted in a similar association for red meat (HR=1.17, 95% CI=0.93–1.47, p-trend=0.10) and a slightly stronger association for processed meat (HR=1.14, 95% CI=0.91–1.43, p-trend= 0.06). Including squamous cell carcinomas, adenocarcinomas, and not otherwise specified carcinomas of the bladder (an additional 113 cases) did not alter risk estimates. There was also no evidence of effect modification for the meat exposures by gender, smoking, or beverage intake (data not shown).

Table 2
Distribution and HRs with 95% CIs for bladder cancer risk within quintiles of meat (g/1000 kcal).

We saw no clear association for total dietary nitrate (HR=0.80, 95% CI=0.58–1.10, p-trend=0.28). However, total dietary nitrite was positively associated with bladder cancer in the top quintile (HR=1.28, 95% CI=1.02–1.61), although the p for linear trend was only borderline statistically significant (p-trend=0.06) (Table 3). We observed a suggestive positive association with measured values of nitrate from processed meat, but this association failed to reach statistical significance in the highest quintile (HR=1.20, 95% CI=0.95–1.51, p-trend=0.06). There was no clear association with measured values nitrite from processed meat and bladder cancer (HR=1.07, 95% CI=0.85–1.36, p-trend=0.79). However, we observed a borderline statistically significant association for combined nitrate and nitrite from processed meat among those in the top quintile (HR=1.29, 95% CI=1.00–1.67, p-trend=0.11).

Table 3
Distribution and HRs with 95% CIs for bladder cancer risk within quintiles of nitrate and nitrite (mg/1000 kcal).

There was no evidence of effect modification for the nitrate and nitrite exposures by gender, beverage intake, smoking, or vitamin C intake (data not shown). In addition, excluding individuals who may have had substantial exposure to nitrate from drinking water (n=7,085) due to residence in an area with high nitrate ground water levels did not alter our risk estimates (data not shown).

DiMeIQx, MeIQx, B[a]P, and mutagenic activity were not associated with bladder cancer, but there was suggestive increased risk with PhIP (HR=1.19, 95% CI=0.95–1.48, p-trend= 0.06) (Table 4). There was no association between grilled (top vs. bottom tertile HR=0.97, 95% CI=0.82–1.15, p-trend=0.50), pan-fried (HR=1.02, 95% CI=0.86–1.22, p-trend=0.79) or well/very-well done (HR=1.03, 95% CI=0.86–1.23. p-trend=0.33) meat and bladder cancer (data not shown).

Table 4
Distribution and HRs with 95% CIs for bladder cancer risk within quintiles of meat mutagens.

Discussion

In this large prospective cohort, we found an increased risk of bladder cancer among those in the top quintile of total dietary nitrite and nitrate plus nitrite from processed meat. There were also suggestive positive associations for this malignancy with increasing intake of red meat and the HCA PhIP.

Few prospective studies have found a positive association between meat and bladder cancer. One cohort found an increased risk with beef and pork6 and another analysis of two cohorts observed a positive association with bacon.7 A recent study also observed reduced risk of bladder cancer for vegetarians compared to those who ate meat.45 However, several other prospective investigations of meat and bladder cancer,8, 1012 including an analysis of baseline dietary data in the full NIH-AARP cohort,9 were null. Additionally, a nested-case control study in the European Prospective Investigation into Cancer and Nutrition cohort found positive association with meat and bladder cancer limited only to individuals with a rapid N-acetyltransferase 2 genotype.12 Data from case-control studies are similarly inconsistent, with some positive associations for red meat or individual meat items,24, 4651 and several null findings.35, 5256

We saw no clear association with total processed meat, yet by separating red meat into processed and non-processed and examining individual processed meat items, we observed positive associations with red processed meat and red meat cold-cuts and bladder cancer. Other evidence for a positive association between processed meats and bladder cancer come from a Hawaiian case-control study for bacon, ham, and sausage (limited to Japanese men, not Caucasians or Japanese women)24 and a case-control study in Uruguay for salted meats.49 Bacon has also been associated with an increased risk in two cohort studies.7

Although we saw no association with intake of processed meat, there was evidence of an elevated risk of bladder cancer with nitrate plus nitrite from processed meats. In addition, by estimating total dietary exposure to nitrate and nitrite from values in the literature, we observed a statistically significant increased risk with dietary nitrite. Our positive findings for nitrate plus nitrite from processed meat support the hypothesis of NOCs involvement in bladder carcinogenesis, as processed meat also provides amines and amides necessary for the endogenous formation of NOCs. Our laboratory measured values of nitrate and nitrite from processed meat represent more recent levels of these additives,41 as the amount of added nitrate and nitrite was reduced in recent decades. When we estimated nitrate and nitrite from processed meat based on literature values from the 1970s, we observed similar associations, with a stronger positive association for nitrite (data not shown).

Three studies of dietary nitrate in relation to bladder cancer have been null.19, 22, 23 One case-control study found a positive association for dietary nitrite and nitrosamines and bladder cancer for Japanese men only;24 however, another case-control in Iowa observed no association for dietary nitrite.23 The suggestive inverse association with dietary nitrate in our population supports the vast majority of this compound coming from fruits and vegetables, which are potential protective factors against bladder cancer5 and contain vitamins20, 21 and polyphenols57, 58 that can inhibit the formation of NOCs. We hypothesized that inhibitory action by vitamin C might modify risk, but we saw no evidence of an interaction, perhaps due to this population’s relatively high fruit and vegetable intake.

We observed a possible increased risk of bladder cancer with PhIP, the most abundant HCA in cooked meat, but no clear associations with other HCAs. Two case-control studies that have investigated HCAs from meat and bladder cancer were null.34, 35 It is possible that the positive association with PhIP was due to chance; however, it should be noted that the major sources of the three HCAs varied. Well-done barbecued hamburgers were largest source of MeIQx (36%) and DiMeIQx (50%), while the largests source of PhIP was medium-done barbecued steak (20%). Our results for B[a]P and total mutagenic activity were null, and we are not aware of other studies to which we can compare these findings. In addition, we saw no evidence of an association between meat cooking methods or doneness levels and bladder cancer.

Our study had several strengths including its large size, high follow-up rate, and detailed questionnaire on meat cooking and doneness to assess multiple components of meat. By utilizing a quantitative database for processed meat and values from the literature for all food items, we were able to examine different dietary sources of nitrate and nitrite. We were also able to assess a wide range of potential confounders, including fine control for smoking. However, we lacked information on urination frequency and bladder infections and had only limited data on beverage intake (no data on water intake), yet epidemiologic evidence on total fluid intake in relation to bladder cancer is inconsistent. In addition, despite no individual level data of nitrate exposure from drinking water, a sub-analysis excluding those with potential high exposure did not alter our risk estimates.

This study provides limited evidence for a role of total dietary nitrite and nitrate plus nitrite from processed meat in bladder carcinogenesis. To better understand these associations, future analyses should continue to focus on the different dietary sources of these compounds. Additional research is needed to confirm our findings of a possible increased risk of bladder cancer with intake of red meat and especially for the HCA PhIP, as prospective investigations of meat-related mutagens and this malignancy are lacking.

Acknowledgments

Cancer incidence data from the Atlanta metropolitan area were collected by the Georgia Center for Cancer Statistics, Department of Epidemiology, Rollins School of Public Health, Emory University. Cancer incidence data from California were collected by the California Department of Health Services, Cancer Surveillance Section. Cancer incidence data from the Detroit metropolitan area were collected by the Michigan Cancer Surveillance Program, Community Health Administration, State of Michigan. The Florida cancer incidence data used in this report were collected by the Florida Cancer Data System under contract to the Department of Health (DOH). The views expressed herein are solely those of the authors and do not necessarily reflect those of the contractor or DOH. Cancer incidence data from Louisiana were collected by the Louisiana Tumor Registry, Louisiana State University Medical Center in New Orleans. Cancer incidence data from New Jersey were collected by the New Jersey State Cancer Registry, Cancer Epidemiology Services, New Jersey State Department of Health and Senior Services. Cancer incidence data from North Carolina were collected by the North Carolina Central Cancer Registry. Cancer incidence data from Pennsylvania were supplied by the Division of Health Statistics and Research, Pennsylvania Department of Health, Harrisburg, Pennsylvania. The Pennsylvania Department of Health specifically disclaims responsibility for any analyses, interpretations or conclusions. Cancer incidence data from Arizona were collected by the Arizona Cancer Registry, Division of Public Health Services, Arizona Department of Health Services. Cancer incidence data from Texas were collected by the Texas Cancer Registry, Cancer Epidemiology and Surveillance Branch, Texas Department of State Health Services. Cancer incidence data from Nevada were collected by the Nevada Central Cancer Registry, Center for Health Data and Research, Bureau of Health Planning and Statistics, State Health Division, State of Nevada Department of Health and Human Services. We are indebted to the participants in the NIH-AARP Diet and Health Study for their outstanding cooperation. We also thank Sigurd Hermansen and Kerry Grace Morrissey from Westat for study outcomes ascertainment and management and Leslie Carroll at Information Management Services for data support and analysis.

Funding/Support: This research was supported (in part) by the Intramural Research Program of the National Cancer Institute, National Institutes of Health, Department of Health and Human Service

Footnotes

Financial Disclosure: Nothing to disclose.

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