Abstract
Background
Red and processed meats could increase cancer risk via several potential mechanisms involving iron, heterocyclic amines, polycyclic aromatic hydrocarbons and N-nitroso compounds. Although there have been multiple studies of meat and colorectal cancer, other gastrointestinal malignancies are understudied.
Methods
We estimated hazards ratios (HR) and 95% confidence intervals (CI) for the association between meat, meat components, and meat cooking by-products and risk of esophageal or gastric cancer in a large cohort study. During approximately 10 years of follow-up, we accrued 215 esophageal squamous cell carcinomas, 630 esophageal adenocarcinomas, 454 gastric cardia adenocarcinomas and 501 gastric non-cardia adenocarcinomas.
Results
Red meat intake was positively associated with esophageal squamous cell carcinoma (HR for the top versus bottom quintile = 1.79, 95% CI: 1.07–3.01, P for trend = 0.019). Individuals in the highest intake quintile of 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (DiMeIQx) had an increased risk for gastric cardia cancer (HR = 1.44, 95% CI: 1.01–2.07, P for trend = 0.104). Furthermore, those in the highest quintile of 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx), 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) or heme iron intake had a suggestive increased risk for esophageal adenocarcinoma (HR = 1.35, 95% CI: 0.97–1.89, P for trend = 0.022; HR = 1.45, 95% CI: 0.99–2.12, P for trend = 0.463; HR = 1.47, 95% CI: 0.99-2.20, P for trend = 0.063, respectively). Benzo[a]pyrene, nitrate and nitrite were not associated with esophageal or gastric cancer.
Conclusions
We found positive associations between red meat intake and esophageal squamous cell carcinoma, and between DiMeIQx intake and gastric cardia cancer.
Keywords: meat, heterocyclic amines, iron, nitrate, nitrite, esophageal cancer, gastric cancer
Introduction
The positive association between both red and processed meat intake and colorectal cancer was deemed ‘convincing’ in a 2007 review of the large amount of epidemiologic data1; however, the prospective data for other gastrointestinal malignancies is limited. Based on data primarily from case-control studies, which can be subject to recall bias, the consensus for red and processed meat was that these foods were associated with a ‘limited-suggestive increased risk’ for esophageal cancer; although the same level of evidence was reported for the association between processed meat and gastric cancer, there was insufficient data for red meat intake and this malignancy1. There are multiple mechanisms through which meat could increase cancer risk. Meat cooked at high temperature results in the formation of the mutagens heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs)2. Furthermore, meat is a source of iron, and processed meat is also a source of nitrate, and nitrite; all of which have been associated with the formation of N-nitroso compounds (NOCs), which are known to cause cancer at a variety of anatomic sites in animals2.
Esophageal cancer is the sixth leading cause of cancer mortality worldwide, and gastric cancer is the second3. Esophageal cancer is comprised of squamous cell carcinomas and adenocarcinomas, and although approximately 90% of gastric cancers are adenocarcinomas, these are typically subdivided according to anatomic location: cardia or non-cardia cancers. There are etiologic differences for both esophageal and gastric cancers by cell type or subsite4, 5, although many previous dietary analyses have not addressed this.
Investigating a complex dietary exposure in relation to cancers that have important and under-studied subgroups requires a large prospective study with detailed data. Using the National Institutes of Health (NIH)-AARP Diet and Health study, a cohort of approximately half a million men and women who had completed a detailed meat intake questionnaire, we investigated meat and meat-related variables in relation to esophageal and gastric cancer.
Materials and Methods
Study population
The NIH-AARP Diet and Health study recruited men and women, aged 50–71 years, from six states throughout the U.S. (California, Florida, Louisiana, New Jersey, North Carolina, Pennsylvania) and two metropolitan areas (Atlanta, Georgia and Detroit, Michigan); further study details have been reported previously6. This cohort study was designed to investigate a variety of hypotheses for the role of diet in cancer etiology. The study was approved by the institutional review board of the U.S. National Cancer Institute.
Dietary assessment
At baseline (1995–96), participants completed self-administered demographic and lifestyle questionnaires, including a 124-item food frequency questionnaire (FFQ). Approximately six months later, cancer-free participants were mailed a risk factor questionnaire, which elicited detailed information on meat intake and cooking preferences. The FFQ assessed the usual frequency of consumption and portion size information of foods and drinks over the previous twelve months. Portion sizes and daily nutrient intakes were calculated from the 1994–96 U.S. Department of Agriculture’s Continuing Survey of Food Intakes by Individuals6. The FFQ compared favorably to other FFQs6, and was calibrated within this study population against two nonconsecutive 24-hour dietary recalls.
All types of beef, pork, and lamb were considered red meat, including bacon, beef, cold cuts, ham, hamburger, hotdogs, liver, pork, sausage, and steak. White meat included chicken and turkey (poultry cold cuts, chicken mixtures, low-fat sausages and low-fat hotdogs made from poultry), and fish. Processed meat included bacon, red meat sausage, poultry sausage, luncheon meats (red and white meat), cold cuts (red and white meat), ham, regular hotdogs and low-fat hotdogs made from poultry. Meats added to complex food mixtures, such as pizza, chili, lasagna, and stew, contributed to the relevant meat type. Total iron was the sum of dietary iron (from all sources including cereals, vegetables, and meat) plus supplementary iron. Heme iron levels in meat may vary according to cooking method7–11; therefore, we estimated heme iron intake using the detailed meat questionnaire in conjunction with a database of measured values from meats cooked by different methods and to varying degrees of doneness12. Furthermore, we estimated nitrate and nitrite intake from processed meats using a database of measured values from ten types of processed meats, which represent 90% of processed meats consumed in the U.S12; these meats were also measured for NOCs, but they were all below the detectable limit. Using the information collected on meat cooking methods (grilled/barbecued, pan-fried, microwaved, and broiled) and doneness levels (well-done and medium/rare) with the CHARRED database (http://charred.cancer.gov), we estimated intake of several HCAs, including 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), as well as benzo[a]pyrene (B[a]P) as a marker of PAH intake, and mutagenic activity (a measure of total mutagenic potential incorporating all meat-related mutagens)12.
Cohort follow-up and case ascertainment
We ascertained vital status through annual linkage of the cohort to the U.S. Social Security Administration Death Master File, follow-up searches of the National Death Index Plus, cancer registry linkage, questionnaire responses, and responses to other mailings. Follow-up for these analyses began on the date the questionnaire was received until censoring at the end of 2006, or when the participant moved out of one of the state cancer registry areas (which included the eight original states plus two additional states where participants commonly move to: Texas and Arizona), had a cancer diagnosis, or died, whichever came first.
We identified cancer cases through probabilistic linkage with state cancer registries. Cancer cases were first primary cancers of the upper gastrointestinal tract. The cancer endpoints were defined by anatomic site and histologic code of the International Classification of Diseases for Oncology (ICD-O-3)13; esophageal cancer included topography codes: C15.0–C15.9, gastric cardia cancer included code: C16.0, and gastric non-cardia cancer included codes: C16.1–C16.7, as well as C16.8 (overlapping tumors) and C16.9 (not otherwise specified). Esophageal cancers were categorized as squamous cell carcinomas, which included histology codes: 8050–8076; and adenocarcinomas, which included: 8140, 8141, 8190–8231, 8260–8263, 8310, 8430, 8480–8490, 8560, 8570–8572. Gastric cancers were restricted to adenocarcinomas.
Statistical analysis
After excluding duplicates and participants who died or moved before the questionnaire was received or withdrew from the study, a total of 566,402 participants returned the baseline questionnaire and 337,074 of these also returned the risk factor questionnaire. For the analyses of baseline data, we excluded individuals whose questionnaire was filled in by someone else on their behalf (n = 15,760), who had prevalent cancer according to the cancer registry or self-report (n = 51,234), and those with extreme daily total energy intake (n = 4,417), defined as more than two inter-quartile ranges above the 75th or below the 25th percentile on the logarithmic scale. For the analyses of data from the risk factor questionnaire, we excluded individuals whose questionnaire was filled in by someone else on their behalf (n = 10,383), who had prevalent cancer (identified by cancer registry or self-report) at the time they completed the risk factor questionnaire (n = 18,862), and those with extreme daily total energy intake (n = 2,503). After all exclusions, our baseline analytic cohort consisted of 494,979 persons (295,305 men and 199,674 women) and the risk factor questionnaire cohort consisted of 303,156 persons (176,842 men and 126,314 women).
Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression with person years as the underlying time metric; analyses using age as the underlying time metric yielded almost identical HRs. The proportional hazards assumption was verified using a time interaction model. The models were constructed as addition models – where the model summed to total meat; for example, red and white meat were in the same model, as were processed and non-processed meat. A full range of potential confounders were investigated, the final multivariate models contained known and suspected confounders and included: age, sex, body mass index (BMI), education, ethnicity, tobacco smoking, alcohol drinking, usual physical activity at work, vigorous physical activity, and intake of fruit, vegetables, saturated fat and calories. Inclusion of a comprehensive (31-level) smoking variable did not alter our findings.
Dietary variables were adjusted for energy by the multivariate nutrient density method14. Multivariate HRs are reported within quintiles, using the lowest quintile as the referent category. Tests for linear trend were calculated using the median value of each quintile. Interactions were evaluated by including cross product terms in multivariate models. Furthermore, we conducted a lag-analysis by excluding the first two years of follow up. All reported P values are two-sided and all statistical analyses were carried out using Statistical Analysis Systems (SAS) software (SAS Institute Inc, Cary, NC).
Results
During a median follow-up time of 10 years (interquartile range: 10.5 – 10.8 years), we accrued 215 esophageal squamous cell carcinomas, 630 esophageal adenocarcinomas, 454 gastric cardia cancers and 501 gastric non-cardia cancers with data from baseline. Within the subcohort of participants who completed the risk factor questionnaire, there were 128 incident esophageal squamous cell carcinomas, 377 esophageal adenocarcinomas, 255 gastric cardia cancers and 277 gastric non-cardia cancers.
Individuals in the highest, compared to the lowest, quintile of red meat intake were more likely to be male, a current smoker, Caucasian, in a physically demanding job, have a higher BMI, and to consume more calories and alcohol; furthermore, they tended to be younger, less educated and less likely to be physically active outside of work, and consumed fewer fruits and vegetables (Table 1). Although the intake of white meat was independent of red meat (r = −0.049), the majority of the baseline characteristics for those in the highest quintile of white meat were opposed to the highest quintile of red meat; for example, while red meat consumption was associated with a higher propensity to be a current smoker and less educated, those in the highest quintile of white meat were less likely to be current smoker and tended to be more educated.
Table 1.
Baseline characteristics of the cohort according to quintile of red meat and white meat intake (n=494,979)
| Red meat | White meat | |||||
|---|---|---|---|---|---|---|
| Quintile 1 | Quintile 3 | Quintile 5 | Quintile 1 | Quintile 3 | Quintile 5 | |
| Red meat, g/1000kcals‡ | 10.0 (5.7–13.4) | 32.2 (29.6–34.9) | 64.8 (57.6–76.9) | 28.6 (15.9–45.0) | 35.0 (22.3–50.0) | 28.6 (15.8–45.1) |
| White meat, g/1000kcals‡ | 28.6 (14.0–51.2) | 27.5 (17.2–42.9) | 28.6 (17.9–43.0) | 9.7 (6.6–12.3) | 28.0 (25.6–30.7) | 65.8 (56.4–82.6) |
| Male† | 44,470 (15) | 58,667 (20) | 74,655 (25) | 61,032 (21) | 60,334 (20) | 54,049 (18) |
| Age, years‡ | 63.0 (58.0–67.0) | 62.8 (57.9–66.7) | 61.7 (57.0–65.9) | 63.2 (58.2–67.0) | 62.7 (57.8–66.6) | 61.8 (57.1–66.1) |
| BMI, kg/m2‡ | 25.1 (22.8–27.9) | 26.5 (24.1–29.4) | 27.5 (25.0–30.7) | 26.0 (23.6–29.2) | 26.5 (24.0–29.6) | 26.6 (24.1–29.7) |
| Calories, kcal/day‡ | 1,542 (1,180–2,009) | 1,654 (1,260–2,159) | 1,789 (1,347–2,348) | 1,725 (1,286–2,297) | 1,660 (1,261–2,168) | 1,571 (1,205–2,044) |
| Vegetable, servings/1000kcals‡ | 2.4 (1.6–3.4) | 2.0 (1.5–2.7) | 1.9 (1.4–2.5) | 1.7 (1.2–2.5) | 2.0 (1.5–2.7) | 2.4 (1.7–3.1) |
| Fruit, servings/1000kcals‡ | 2.2 (1.4–3.2) | 1.5 (0.9–2.2) | 1.0 (0.6–1.5) | 1.4 (0.8–2.4) | 1.5 (0.9–2.3) | 1.5 (1.0–2.3) |
| Education, completed graduate school§ | 24,517 (26) | 18,818 (20) | 16,467 (17) | 15,109 (16) | 19,989 (21) | 23,147 (24) |
| Current smoker, >1 pack/day§ | 1,877 (2) | 4,402 (5) | 8,485 (9) | 7,007 (7) | 4,597 (5) | 3,081 (3) |
| Ethnicity | ||||||
| Non-Hispanic white§ | 85,863 (88) | 91,215 (93) | 92,497 (95) | 90,121 (93) | 90,900 (93) | 88,979 (91) |
| Non-Hispanic black§ | 6,200 (6) | 3,465 (4) | 2,324 (2) | 2,986 (3) | 3,666 (4) | 5,052 (5) |
| Hispanic§ | 2,427 (3) | 1,733 (2) | 1,824 (2) | 2,263 (2) | 1,631 (2) | 1,982 (2) |
| Other§ | 2,707 (3) | 1,429 (1) | 1,120 (1) | 1,918 (2) | 1,602 (2) | 1,663 (2) |
| Physical activity at work, heavy work/carry loads§ | 2,251 (2) | 2,744 (3) | 3,619 (4) | 3,972 (4) | 2,736 (3) | 1,990 (2) |
| Vigorous physical activity, ≥5 times/week§ | 26,119 (27) | 17,753 (18) | 14,821 (15) | 18,966 (19) | 18,570 (19) | 20,422 (21) |
| Alcoholic drinks, >3/day§ | 3,185 (3) | 6,954 (7) | 12,503 (13) | 7,643 (8) | 7,582 (8) | 6,767 (7) |
Number, percent among the row
Median, inter-quartile range
Number, percent among the category
Red meat intake was positively associated with esophageal squamous cell carcinoma (HR for the top versus bottom quintile = 1.79, 95% CI: 1.07–3.01, P for trend = 0.019; HR = 1.06, 95% CI: 1.00–1.13 for each 10g/1000kcal increase), but not with adenocarcinoma of the esophagus or gastric (cardia or non-cardia) cancer (Table 2). Neither white meat nor processed meat was associated with any of the malignancies investigated in this study. None of the meat-related variables we investigated proved to be statistically significantly associated with esophageal squamous cell carcinoma (Table 3). However, we found positive associations for HCA intake and the other malignancies investigated; specifically, individuals in the highest quintile, compared to the lowest, of DiMeIQx intake had an elevated risk for gastric cardia cancer (HR = 1.44, 95% CI: 1.01–2.07); risks were elevated across quintiles two through five. Furthermore, we observed borderline statistically significant increased risks for adenocarcinoma of the esophagus for those in the highest intake quintile of MeIQx and PhIP (HR = 1.35, 95% CI: 0.97–1.89, P for trend = 0.022; HR = 1.45, 95% CI: 0.99–2.12, P for trend = 0.463, respectively). In addition to HCAs, we found a suggestive positive association for heme iron intake and esophageal adenocarcinoma (HR for the top versus bottom quintile = 1.47, 95% CI: 0.99–2.20, P for trend = 0.063), but no associations between other meat-related variables, including B[a]P, nitrate, or nitrite, and esophageal or gastric cancers. Examining the overall index of mutagenicity of the meats consumed did not reveal any further associations.
Table 2.
Meat intake in relation to esophageal and gastric cancer using baseline data (n=494,979)†
| Q1 | Q2 | Q3 | Q4 | Q5 | P for trend§ | Continuous scale (per 10g/1000kcal) | |
|---|---|---|---|---|---|---|---|
| Red meat | |||||||
| Quintile median (g/1000kcals) | 10.0 | 21.9 | 32.2 | 44.1 | 64.8 | ||
| ESCC‡ | |||||||
| Cases | 28 | 35 | 42 | 41 | 69 | ||
| HR (95%CI) | 1.00 | 1.18 (0.71–1.96) | 1.34 (0.80–2.22) | 1.19 (0.70–2.01) | 1.79 (1.07–3.01) | 0.019 | 1.06 (1.00–1.13) |
| EADC‡ | |||||||
| Cases | 74 | 112 | 113 | 154 | 177 | ||
| HR (95%CI) | 1.00 | 1.18 (0.87–1.59) | 1.00 (0.74–1.37) | 1.17 (0.87–1.59) | 1.15 (0.84–1.57) | 0.492 | 1.01 (0.98–1.06) |
| Gastric Cardia | |||||||
| Cases | 57 | 90 | 90 | 104 | 113 | ||
| HR (95%CI) | 1.00 | 1.29 (0.92–1.81) | 1.12 (0.79–1.59) | 1.13 (0.79–1.61) | 1.04 (0.72–1.51) | 0.589 | 1.00 (0.95–1.04) |
| Gastric Noncardia | |||||||
| Cases | 110 | 95 | 88 | 105 | 103 | ||
| HR (95%CI) | 1.00 | 0.81 (0.61–1.08) | 0.72 (0.53–0.97) | 0.83 (0.61–1.11) | 0.77 (0.56–1.06) | 0.261 | 0.99 (0.94–1.04) |
| White meat | |||||||
| Quintile median (g/1000kcals) | 9.7 | 18.9 | 28.0 | 40.3 | 65.8 | ||
| ESCC‡ | |||||||
| Cases | 55 | 44 | 47 | 36 | 33 | ||
| HR (95%CI) | 1.00 | 0.84 (0.56–1.25) | 0.92 (0.62–1.37) | 0.73 (0.47–1.12) | 0.69 (0.44–1.08) | 0.089 | 0.96 (0.90–1.02) |
| EADC‡ | |||||||
| Cases | 151 | 138 | 118 | 120 | 103 | ||
| HR (95%CI) | 1.00 | 0.92 (0.73–1.16) | 0.82 (0.64–1.05) | 0.88 (0.69–1.13) | 0.84 (0.65–1.09) | 0.239 | 0.98 (0.95–1.02) |
| Gastric Cardia | |||||||
| Cases | 94 | 92 | 85 | 97 | 86 | ||
| HR (95%CI) | 1.00 | 1.02 (0.76–1.36) | 1.00 (0.74–1.35) | 1.22 (0.91–1.63) | 1.18 (0.87–1.60) | 0.154 | 1.03 (1.00–1.07) |
| Gastric Noncardia | |||||||
| Cases | 113 | 101 | 103 | 102 | 82 | ||
| HR (95%CI) | 1.00 | 0.98 (0.75–1.29) | 1.05 (0.80–1.38) | 1.09 (0.83–1.44) | 0.90 (0.67–1.20) | 0.578 | 0.99 (0.95–1.03) |
| Processed meat | |||||||
| Quintile median (g/1000kcals) | 1.7 | 4.5 | 7.8 | 12.6 | 23.2 | ||
| ESCC‡ | |||||||
| Cases | 34 | 38 | 34 | 49 | 60 | ||
| HR (95%CI) | 1.00 | 1.03 (0.64–1.66) | 0.86 (0.52–1.42) | 1.15 (0.72–1.86) | 1.32 (0.83–2.10) | 0.085 | 1.08 (0.96–1.21) |
| EADC‡ | |||||||
| Cases | 83 | 101 | 128 | 137 | 181 | ||
| HR (95%CI) | 1.00 | 0.92 (0.68–1.24) | 0.98 (0.74–1.32) | 0.91 (0.68–1.22) | 1.08 (0.81–1.43) | 0.262 | 1.03 (0.96–1.11) |
| Gastric Cardia | |||||||
| Cases | 68 | 78 | 93 | 108 | 107 | ||
| HR (95%CI) | 1.00 | 0.89 (0.64–1.24) | 0.91 (0.66–1.26) | 0.92 (0.67–1.28) | 0.82 (0.59–1.14) | 0.285 | 1.00 (0.92–1.09) |
| Gastric Noncardia | |||||||
| Cases | 93 | 81 | 105 | 105 | 117 | ||
| HR (95%CI) | 1.00 | 0.87 (0.64–1.18) | 1.10 (0.82–1.47) | 1.04 (0.77–1.41) | 1.09 (0.81–1.48) | 0.329 | 1.02 (0.94–1.11) |
age (continuous), sex, BMI (<18.5, ≥ 18.5 to <25, ≥ 25 to <30, ≥ 30 to <35, 35 kg/m2, unknown), education (≤ 11years school, 12 years or completed high school, post-high school/some college, college graduate, postgraduate, unknown), ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, other, unknown), tobacco smoking (never, quit smoking ≥20 cigarettes/day, quit smoking >20 cigarettes/day, current smoker of ≥20 cigarettes/day, current smoker of >20 cigarettes/day, unknown), alcohol drinking (none, >0 to 1, >1 to 3, >3 drinks per day, unknown), usual physical activity at work (all day sitting, mostly sitting, walking around a lot, lifting/carrying light loads/climbing stairs or hills often, heavy work/carrying heavy loads, unknown), vigorous physical activity (never, rarely, 1–3 times/month, 1–2 times/week, 3–4 times/week, ≥5 times/week, unknown), and the daily intake of fruit (continuous/1000kcals), vegetables (continuous/1000kcals), saturated fat (continuous/1000kcals), and calories (kcals/day)
ESCC = Esophageal squamous cell carcinoma, EADC = Esophageal adenocarcinoma
P values for trend were calculated by representing intake as an ordinal variable for each category in the adjusted models described above.
Table 3.
Components of meat in relation to esophageal and gastric cancer using data from the risk factor questionnaire (n=303,156)
| Q1 | Q2 | Q3 | Q4 | Q5 | P for trend§ | Continuous data | |
|---|---|---|---|---|---|---|---|
| DiMeIQx | per 0.5 ng increase | ||||||
| Quintile median (ng/1000kcals) | 0.0 | 0.1 | 0.4 | 0.8 | 2.1 | ||
| ESCC‡ | |||||||
| Cases | 44 | 23 | 24 | 18 | 19 | ||
| HR (95%CI) | 1.00 | 1.21 (0.73–2.02) | 1.31 (0.79–2.16) | 0.97 (0.56–1.69) | 1.00 (0.58–1.73) | 0.747 | 1.02 (1.00–1.03) |
| EADC‡ | |||||||
| Cases | 130 | 49 | 47 | 77 | 74 | ||
| HR (95%CI) | 1.00 | 0.93 (0.67–1.30) | 0.81 (0.58–1.13) | 1.20 (0.90–1.59) | 1.11 (0.83–1.48) | 0.237 | 1.01 (1.00–1.02) |
| Gastric Cardia | |||||||
| Cases | 72 | 37 | 48 | 46 | 52 | ||
| HR (95%CI) | 1.00 | 1.24 (0.83–1.85) | 1.49 (1.04–2.16) | 1.34 (0.92–1.94) | 1.44 (1.01–2.07) | 0.104 | 1.01 (1.00–1.02) |
| Gastric Noncardia | |||||||
| Cases | 95 | 45 | 42 | 49 | 46 | ||
| HR (95%CI) | 1.00 | 1.01 (0.71–1.45) | 0.93 (0.64–1.33) | 1.07 (0.75–1.51) | 0.97 (0.68–1.39) | 0.934 | 1.00 (0.97–1.03) |
| MeIQx | per 5 ng increase | ||||||
| Quintile median (ng/1000kcals) | 0.5 | 2.5 | 5.5 | 10.6 | 25.0 | ||
| ESCC‡ | |||||||
| Cases | 22 | 28 | 28 | 25 | 25 | ||
| HR (95%CI) | 1.00 | 1.21 (0.69–2.13) | 1.18 (0.67–2.09) | 1.03 (0.57–1.86) | 0.96 (0.53–1.75) | 0.527 | 1.02 (1.00–1.05) |
| EADC‡ | |||||||
| Cases | 56 | 72 | 65 | 69 | 115 | ||
| HR (95%CI) | 1.00 | 1.13 (0.79–1.60) | 0.91 (0.64–1.31) | 0.89 (0.62–1.27) | 1.35 (0.97–1.89) | 0.022 | 1.01 (0.99–1.03) |
| Gastric Cardia | |||||||
| Cases | 41 | 38 | 55 | 55 | 66 | ||
| HR (95%CI) | 1.00 | 0.85 (0.55–1.32) | 1.14 (0.75–1.71) | 1.06 (0.70–1.60) | 1.16 (0.77–1.75) | 0.295 | 1.01 (0.99–1.03) |
| Gastric Noncardia | |||||||
| Cases | 58 | 49 | 48 | 62 | 60 | ||
| HR (95%CI) | 1.00 | 0.82 (0.56–1.21) | 0.76 (0.52–1.12) | 0.93 (0.65–1.35) | 0.83 (0.57–1.22) | 0.739 | 0.98 (0.94–1.02) |
| PhIP | per 25 ng increase | ||||||
| Quintile median (ng/1000kcals) | 2.1 | 11.2 | 25.4 | 51.0 | 127.3 | ||
| ESCC‡ | |||||||
| Cases | 21 | 32 | 25 | 24 | 26 | ||
| HR (95%CI) | 1.00 | 1.44 (0.83–2.52) | 1.08 (0.59–1.95) | 1.00 (0.54–1.82) | 1.09 (0.60–1.97) | 0.702 | 1.00 (0.95–1.05) |
| EADC‡ | |||||||
| Cases | 39 | 76 | 91 | 78 | 93 | ||
| HR (95%CI) | 1.00 | 1.45 (0.98–2.14) | 1.50 (1.02–2.19) | 1.20 (0.81–1.78) | 1.45 (0.99–2.12) | 0.463 | 1.01 (0.98–1.03) |
| Gastric Cardia | |||||||
| Cases | 42 | 35 | 65 | 53 | 60 | ||
| HR (95%CI) | 1.00 | 0.67 (0.43–1.06) | 1.11 (0.75–1.66) | 0.87 (0.57–1.31) | 0.97 (0.64–1.46) | 0.695 | 1.01 (0.98–1.04) |
| Gastric Noncardia | |||||||
| Cases | 45 | 60 | 58 | 54 | 60 | ||
| HR (95%CI) | 1.00 | 1.25 (0.84–1.84) | 1.17 (0.79–1.74) | 1.09 (0.73–1.64) | 1.22 (0.82–1.83) | 0.620 | 1.01 (0.98–1.04) |
| B[a]P | per 10 ng increase | ||||||
| Quintile median (ng/1000kcals) | 0.2 | 1.5 | 6.3 | 17.3 | 45.8 | ||
| ESCC‡ | |||||||
| Cases | 27 | 28 | 23 | 30 | 20 | ||
| HR (95%CI) | 1.00 | 1.06 (0.62–1.80) | 0.98 (0.56–1.72) | 1.23 (0.72–2.08) | 0.70 (0.39–1.26) | 0.179 | 0.99 (0.93–1.05) |
| EADC‡ | |||||||
| Cases | 59 | 80 | 75 | 84 | 79 | ||
| HR (95%CI) | 1.00 | 1.19 (0.85–1.67) | 1.18 (0.84–1.66) | 1.11 (0.79–1.55) | 0.86 (0.61–1.22) | 0.062 | 0.99 (0.96–1.02) |
| Gastric Cardia | |||||||
| Cases | 44 | 42 | 52 | 53 | 64 | ||
| HR (95%CI) | 1.00 | 0.88 (0.58–1.34) | 1.14 (0.76–1.71) | 1.04 (0.70–1.56) | 1.09 (0.73–1.61) | 0.547 | 1.00 (0.97–1.04) |
| Gastric Noncardia | |||||||
| Cases | 55 | 56 | 54 | 58 | 54 | ||
| HR (95%CI) | 1.00 | 0.95 (0.65–1.38) | 1.01 (0.69–1.48) | 1.08 (0.74–1.56) | 0.99 (0.67–1.46) | 0.925 | 0.99 (0.94–1.03) |
| Mutagenic activity | per 1000 revertant colonies increase | ||||||
| Quintile median (revertant colonies/1000kcals) | 168 | 617 | 1186 | 2097 | 4468 | ||
| ESCC‡ | |||||||
| Cases | 25 | 29 | 27 | 21 | 26 | ||
| HR (95%CI) | 1.00 | 1.08 (0.62–1.85) | 0.98 (0.56–1.72) | 0.74 (0.41–1.36) | 0.93 (0.53–1.66) | 0.609 | 1.01 (1.00–1.02) |
| EADC‡ | |||||||
| Cases | 41 | 66 | 94 | 83 | 93 | ||
| HR (95%CI) | 1.00 | 1.20 (0.81–1.78) | 1.51 (1.04–2.20) | 1.26 (0.86–1.85) | 1.37 (0.94–2.01) | 0.347 | 1.00 (0.99–1.02) |
| Gastric Cardia | |||||||
| Cases | 38 | 51 | 49 | 60 | 57 | ||
| HR (95%CI) | 1.00 | 1.08 (0.70–1.65) | 0.94 (0.61–1.45) | 1.09 (0.72–1.67) | 1.00 (0.65–1.54) | 0.955 | 1.00 (0.99–1.02) |
| Gastric Noncardia | |||||||
| Cases | 53 | 54 | 60 | 51 | 59 | ||
| HR (95%CI) | 1.00 | 0.91 (0.62–1.34) | 0.97 (0.67–1.43) | 0.82 (0.55–1.22) | 0.94 (0.64–1.39) | 0.807 | 0.99 (0.95–1.03) |
| Heme Iron | per 100 μg increase | ||||||
| Quintile median (μg/1000kcals) | 48.8 | 102.9 | 154.2 | 218.7 | 347.7 | ||
| ESCC‡ | |||||||
| Cases | 17 | 25 | 31 | 27 | 28 | ||
| HR (95%CI) | 1.00 | 1.38 (0.74–2.58) | 1.60 (0.87–2.96) | 1.33 (0.70–2.53) | 1.25 (0.64–2.42) | 0.944 | 1.02 (0.89–1.17) |
| EADC‡ | |||||||
| Cases | 39 | 55 | 81 | 88 | 114 | ||
| HR (95%CI) | 1.00 | 1.12 (0.74–1.70) | 1.40 (0.94–2.07) | 1.32 (0.89–1.97) | 1.47 (0.99–2.20) | 0.063 | 1.04 (0.96–1.12) |
| Gastric Cardia | |||||||
| Cases | 38 | 45 | 58 | 56 | 58 | ||
| HR (95%CI) | 1.00 | 0.98 (0.63–1.52) | 1.10 (0.72–1.68) | 0.94 (0.60–1.45) | 0.83 (0.53–1.30) | 0.256 | 0.95 (0.86–1.05) |
| Gastric Noncardia | |||||||
| Cases | 63 | 49 | 39 | 69 | 57 | ||
| HR (95%CI) | 1.00 | 0.71 (0.49–1.04) | 0.54 (0.36–0.82) | 0.92 (0.64–1.33) | 0.72 (0.48–1.08) | 0.531 | 0.96 (0.87–1.06) |
| Nitrate | per 100 μg increase | ||||||
| Quintile median | 24.2 | 66.9 | 112.7 | 174.5 | 298.0 | ||
| (μg/1000kcals) | |||||||
| ESCC‡ | |||||||
| Cases | 22 | 25 | 15 | 25 | 41 | ||
| HR (95%CI) | 1.00 | 1.06 (0.59–1.91) | 0.60 (0.30–1.18) | 0.90 (0.49–1.67) | 1.30 (0.72–2.35) | 0.153 | 1.08 (0.96–1.23) |
| EADC‡ | |||||||
| Cases | 47 | 61 | 68 | 89 | 112 | ||
| HR (95%CI) | 1.00 | 0.97 (0.66–1.43) | 0.91 (0.62–1.35) | 1.01 (0.70–1.47) | 1.10 (0.75–1.60) | 0.350 | 1.04 (0.96–1.12) |
| Gastric Cardia | |||||||
| Cases | 39 | 57 | 36 | 61 | 62 | ||
| HR (95%CI) | 1.00 | 1.17 (0.77–1.77) | 0.64 (0.40–1.02) | 0.94 (0.61–1.45) | 0.81 (0.52–1.25) | 0.259 | 0.99 (0.90–1.09) |
| Gastric Noncardia | |||||||
| Cases | 50 | 48 | 50 | 56 | 73 | ||
| HR (95%CI) | 1.00 | 0.90 (0.60–1.35) | 0.89 (0.59–1.33) | 0.91 (0.61–1.37) | 1.04 (0.69–1.55) | 0.578 | 1.01 (0.92–1.10) |
| Nitrite | per 100 μg increase | ||||||
| Quintile median | 12.1 | 34.6 | 61.4 | 102.9 | 199.2 | ||
| (μg/1000kcals) | |||||||
| ESCC‡ | |||||||
| Cases | 20 | 30 | 19 | 28 | 31 | ||
| HR (95%CI) | 1.00 | 1.36 (0.76–2.43) | 0.82 (0.43–1.57) | 1.15 (0.63–2.11) | 1.21 (0.67–2.20) | 0.651 | 1.00 (0.83–1.21) |
| EADC‡ | |||||||
| Cases | 50 | 60 | 66 | 81 | 120 | ||
| HR (95%CI) | 1.00 | 0.89 (0.61–1.30) | 0.82 (0.56–1.20) | 0.88 (0.61–1.27) | 1.19 (0.84–1.68) | 0.029 | 1.05 (0.95–1.15) |
| Gastric Cardia | |||||||
| Cases | 44 | 40 | 55 | 61 | 55 | ||
| HR (95%CI) | 1.00 | 0.72 (0.47–1.11) | 0.88 (0.58–1.32) | 0.87 (0.58–1.31) | 0.71 (0.47–1.08) | 0.250 | 0.89 (0.77–1.03) |
| Gastric Noncardia | |||||||
| Cases | 54 | 44 | 48 | 67 | 64 | ||
| HR (95%CI) | 1.00 | 0.77 (0.51–1.15) | 0.79 (0.53–1.18) | 1.04 (0.71–1.52) | 0.93 (0.63–1.37) | 0.615 | 1.02 (0.91–1.15) |
age (continuous), sex, BMI (<18.5, ≥ 18.5 to <25, ≥25 to <30, ≥30 to <35, ≥35 kg/m2, unknown), education (≤11years school, 12 years or completed high school, post-high school/some college, college graduate, postgraduate, unknown), ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, other, unknown), tobacco smoking (never, quit smoking ≤ 20 cigarettes/day, quit smoking >20 cigarettes/day, current smoker of ≤ 20 cigarettes/day, current smoker of >20 cigarettes/day, unknown), alcohol drinking (none, >0 to 1, >1 to 3, >3 drinks per day, unknown), usual physical activity at work (all day sitting, mostly sitting, walking around a lot, lifting/carrying light loads/climbing stairs or hills often, heavy work/carrying heavy loads, unknown), vigorous physical activity (never, rarely, 1–3 times/month, 1–2 times/week, 3–4 times/week, ≥5 times/week, unknown), and the daily intake of fruit (continuous/1000kcals), vegetables (continuous/1000kcals), saturated fat (continuous/1000kcals), and calories (kcals/day)
ESCC = Esophageal squamous cell carcinoma, EADC = Esophageal adenocarcinoma
P values for trend were calculated by representing intake as an ordinal variable for each category in the adjusted models described above.
We conducted several sensitivity and stratified analyses, which revealed consistency in our findings. A lag analysis, excluding the first two years of follow-up did not affect our results. Upon stratification by gender, alcohol, smoking, BMI, and vitamin C, we did not find any consistent modification of our findings. For example, the association between red meat intake and esophageal squamous cell carcinoma was evident in never smokers (HR for the top versus bottom quintile = 1.50, 95% CI: 0.40–5.51) and in those who do not drink alcohol (HR for the top versus bottom quintile = 2.18, 95% CI: 0.77–6.13), although the risks were not statistically significant due to limited power within this subgroup.
Discussion
Individuals in the highest category of red meat intake had an elevated risk for esophageal squamous cell carcinoma and those in the highest category of DiMeIQx intake had an increased risk for gastric cardia cancer. Furthermore, we observed a suggestive increased risk for esophageal adenocarcinoma for those in the highest intake category of MeIQx, PhIP or heme iron.
The World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) consensus report concluded that the evidence to date for red meat and processed meat as risk factors for esophageal cancer was ‘limited suggestive increased risk’; although there was no consideration for histologic subtype, largely because of a lack of data1. There are very few cohort studies investigating meat intake and esophageal cancer; one Norwegian study with no data on histology and only 22 cases15, one study of adenocarcinoma (n=65) from Europe16, and one study of squamous cell cancer (n=1,958) from China that only gave risk estimates for total meat and not red and processed meat separately17. The European study reported a strong positive association for those in the highest tertile of processed meat intake and adenocarcinoma of the esophagus (HR=3.54, 95% CI: 1.57–7.99), but no association for red meat16. In addition, data from our cohort was presented as part of a multi-site cancer analysis with follow-up through 2003 that combined all esophageal cancer cases and used a standard set of covariates for all sites; this analysis reported elevated risks for those in the highest quintile of red meat (HR=1.51, 95%: 1.09–2.08), but no association for processed meat intake (HR=0.94, 95% CI: 0.70–1.25)18. Data from the present study, however, highlight the importance of analyzing squamous cell and adenocarcinoma of the esophagus separately. There are more case-control studies than cohort studies even though this is not an ideal study design for dietary analyses or for digestive tract cancers; in these studies, red meat intake has been positively associated with both adenocarcinoma19, 20 and squamous cell cancer20–23 of the esophagus.
Although there are many more studies of meat intake, particularly processed meat, and gastric cancer, the data remains inconsistent. The WCRF/AICR 2007 report concludes that there is ‘limited suggestive’ evidence for a positive association between processed meat intake and gastric cancer1, and insufficient data for red meat. The vast majority of studies conducted thus far have not differentiated between cardia and non-cardia gastric cancer. The cohort studies mainly reported data on processed meat, and while two studies reported statistically significant elevated risks16, 24, which appeared to be confined to non-cardia in the one study with data by subsite16, others found elevated risks that did not reach statistical significance25, 26, and others were null27, 28.
There are very few studies that have investigated components of meat or compounds formed during cooking or processing of meat in relation to esophageal or gastric cancer. Only one other study investigated HCA intake and esophageal cancer by subtype and this was a case-control study that reported an increased risk of squamous cell carcinoma for those in the highest quartile of MeIQx and DiMeIQx, but no association for adenocarcinoma of the esophagus29. Similarly, there are no cohort studies and very few case-control studies of HCAs in relation to gastric cancer; although a positive association was observed in one study30, two other studies did not find statistically significant associations29, 31, and a study that investigated well-done meat intake as a proxy for HCA exposure reported an increased risk19. We were not able to speculate about the potential mechanism relating red meat intake to esophageal squamous cell carcinoma since none of the meat-related variables we investigated proved to be statistically significantly associated with this cancer. Our observation that DiMeIQx was positively associated with gastric cardia cancer is supported by animal studies showing a diet high in HCAs results in increased stomach tumors32. Since HCAs are multisite carcinogens in animal models, their detrimental effects are possible at many anatomical subsites.
Meat is a source of iron and although high iron levels in toenails were indicative of an elevated risk of esophageal cancer in a case-control study33, there was no association between iron levels in esophageal biopsy specimens in a prospective study of squamous cell carcinoma of the esophagus34. With regard to gastric cancer, a recent case-control study did not find an association for iron intake35. Heme iron specifically may contribute to carcinogenesis via increasing oxidative stress36 or by catalyzing the endogenous formation of NOCs37, which are known carcinogens. A large multi-center European cohort created an index for the propensity for endogenous NOC formation by estimating iron intake using standard food databases in relation to fecal NOC levels from published literature; individuals in the highest category of this index had an elevated risk for non-cardia gastric cancer38. Ours is the first study to estimate heme intake using a database of measured values from specific meats in relation to cancers of the esophagus and stomach; and we revealed a suggestive positive association between heme iron intake and esophageal adenocarcinoma, but not squamous cell carcinoma or gastric cancer.
In agreement with our data, two case-control studies reported null findings for high nitrite meat intake in relation to adenocarcinoma and squamous cell carcinoma of the esophagus20, 39. Furthermore, a case-control31 and a cohort study28 reported no association between nitrate or nitrite intake and gastric cancer; however, analyses by subsite found that a high nitrite diet39 or meats high in nitrite20 increased the risk of non-cardia gastric cancer, a finding not replicated in our study. There is very little data on NOC intake specifically; two cohort studies estimated intake of one NOC – N-nitrosodimethylamine (NDMA) using tables containing values for foods and beverages, one of the studies found an elevated risk for gastric cancer for those in the highest category of NDMA intake24, but the other found no association for cardia or non-cardia gastric cancer38.
There were many notable strengths of our study, several relating to the dietary questionnaire, which not only contained detailed questions pertaining to meat-cooking preferences and components of meat, but it was also completed prior to diagnoses, which limited recall bias and reverse causation. This cohort was also very large, which enabled us to investigate esophageal and gastric cancer by their important subtypes, and produced a wide range of meat intake, increasing the ability to detect associations. However, some of the categories had a small number of cases in; power calculations revealed approximately 80% power to detect a risk of 1.4 for all subgroups, except for esophageal squamous cell carcinoma for which we had approximately 80% power to detect an association of 1.6. Other limitations of our study included the possibility of measurement error in general, and underestimation of both nitrate and heme iron, since we lacked data on nitrate intake from drinking water, and because the iron database was limited by the number of meats included. It is also possible that our risk estimates were confounded by other lifestyle factors and possibly by gastroesophageal reflux or Helicobacter pylori, for which we do not have information on in our cohort. Although there is no evidence that H. pylori is related to meat intake, they do both tend to be associated with socioeconomic status, which we attempted to control for in the form of years of education. A previous study, with limited statistical power, found stronger associations between meat intake and non-cardia gastric cancer in H. pylori antibody-positive individuals16; however, the findings from our study were limited to DiMeIQx intake from meat and cardia cancers. Lastly, adenocarcinoma of the esophagus and gastric cardia cancers both tend to arise near the esophageal-gastric junction40, leading to difficulties in determining the subsite of origin; therefore, there may have been some misclassification in tumor site.
In conclusion, we found a positive association between red meat intake and squamous cell carcinoma of the esophagus, and between DiMeIQx intake and gastric cardia cancer. Processed meat intake was not associated with either esophageal or gastric cancer.
Study Highlights.
What is current knowledge
Red and processed meat are known sources of potential mutagens
Red and processed meat are positively associated with colorectal cancer, but the effect on other gastrointestinal malignancies is unclear
The majority of the literature on meat intake and the risk of esophageal and gastric cancers is from case-control studies, which are subject to biases, and do not differentiate between important subtypes of these cancers
What is new here
We observed a positive association between red meat intake and squamous cell carcinoma of the esophagus, but no association for adenocarcinoma – suggesting differences in their etiology
Heterocyclic amines formed in high temperature cooked meat were positively associated with gastric cardia cancer, and there was a suggestive positive association for esophageal adenocarcinoma
Heme iron intake may be associated with esophageal adenocarcinoma risk
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 (FCDC) under contract with the Florida Department of Health (FDOH). The views expressed herein are solely those of the authors and do not necessarily reflect those of the FCDC or FDOH. 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. 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 Services
Abbreviations
- B[a]P
benzo[a]pyrene
- BMI
body mass index
- CI
confidence interval
- DiMeIQx
2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline
- FFQ
food frequency questionnaire
- HR
hazard ratio
- HCA
heterocyclic amine
- MeIQx
2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline
- NOC
N-nitroso compound
- PAH
polycyclic aromatic hydrocarbon
- PhIP
2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine
Footnotes
Competing Interest
None to declare.
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