Objective The incidence of oesophageal adenocarcinoma (EAC) has increased rapidly over the past 40 years and accumulating evidence suggests that obesity, as measured by body mass index (BMI), is a major risk factor. It remains unclear whether abdominal obesity is associated with EAC and gastric adenocarcinoma.
Design Cox proportional hazards regression was used to examine associations between overall and abdominal obesity with EAC and gastric adenocarcinoma among 218 854 participants in the prospective NIH–AARP cohort.
Results 253 incident EAC, 191 gastric cardia adenocarcinomas and 125 gastric non-cardia adenocarcinomas accrued to the cohort. Overall obesity (BMI) was positively associated with EAC and gastric cardia adenocarcinoma risk (highest (≥35 kg/m2) vs referent (18.5–<25 kg/m2); HR 2.11, 95% CI 1.09 to 4.09 and HR 3.67, 95% CI 2.00 to 6.71, respectively). Waist circumference was also positively associated with EAC and gastric cardia adenocarcinoma risk (highest vs referent; HR 2.01, 95% CI 1.35 to 3.00 and HR 2.22, 95% CI 1.43 to 3.47, respectively), whereas waist-to-hip ratio (WHR) was positively associated with EAC risk only (highest vs referent; HR 1.81, 95% CI 1.24 to 2.64) and persisted in patients with normal BMI (18.5–<25 kg/m2). Mutual adjustment of WHR and BMI attenuated both, but did not eliminate the positive associations for either with risk of EAC. In contrast, the majority of the anthropometric variables were not associated with adenocarcinomas of the gastric non-cardia.
Conclusion Overall obesity was associated with a higher risk of EAC and gastric cardia adenocarcinoma, whereas abdominal obesity was found to be associated with increased EAC risk; even in people with normal BMI.
- cancer epidemiology
- dietary factors
- gastric adenocarcinoma
- gastric cancer
- gastrointestinal cancer
- hepatocellular carcinoma
- molecular epidemiology
- oesophageal cancer
- tumour markers
Statistics from Altmetric.com
- cancer epidemiology
- dietary factors
- gastric adenocarcinoma
- gastric cancer
- gastrointestinal cancer
- hepatocellular carcinoma
- molecular epidemiology
- oesophageal cancer
- tumour markers
Significance of this study
What is already known about this subject?
The incidence of EAC has increased rapidly over the past 40 years, and is the most rapidly increasing cancer in the western world.
Epidemiological evidence suggests that obesity, as measured by BMI, may be a major risk factor. However, associations between body fat distribution, particularly abdominal obesity, have not been widely studied.
What are the new findings?
Overall obesity (BMI) was associated with a higher risk of EAC and gastric cardia adenocarcinoma, whereas abdominal obesity, as measured by waist circumference and WHR was associated with an increased EAC risk.
Waist circumference was also related to an increased risk of gastric cardia adenocarcinoma, but no association with WHR was observed.
The positive association between WHR and EAC risk persisted in patients with normal BMI (18.5–<25 kg/m2), and mutual adjustment of WHR and BMI attenuated both, but did not eliminate the positive associations for either with the risk of EAC.
How might it impact on clinical practice in the foreseeable future?
Associations between obesity and both EAC and gastric cardia adenocarcinoma suggest that interventions to reduce the prevalence of obesity may help to prevent adenocarcinomas of the oesophagus and gastric cardia.
The incidence of oesophageal adenocarcinoma (EAC) has dramatically increased in recent decades, and this cancer is the most rapidly increasing cancer in the western world.1–3 Despite improvements in surgery and chemotherapy, the outlook for patients diagnosed with EAC remains poor, with a 5-year survival rate of less than 20%.4 Several risk factors for EAC have been identified, including the presence of Barrett's oesophagus, gastro-oesophageal reﬂux disease (GERD), smoking, white race, male sex and obesity.5
Explanations for increasing rates of EAC remain unclear, although the concurrent increase in the prevalence of obesity may be a partial explanation. The most recent World Cancer Research Fund and American Institute for Cancer Research report rated the evidence for a higher risk of EAC due to greater body fatness as ‘convincing’.5 A study from 2008, using results from published meta-analyses and large cohort studies, reported a steadily increasing impact of obesity on trends in EAC incidence rates (from an attributable risk percentage of approximately 21% in 1976–80 to approximately 36% in 2001–4 to approximately 40% in 2007).6 Although overall obesity has emerged as a leading candidate risk factor for EAC,7–16 few studies have specifically examined body fat distribution, in particular measures of abdominal obesity.17 ,18
Therefore, we examined the relation between height, overall (weight and body mass index (BMI)) and abdominal (waist circumference, waist-to-hip ratio (WHR)) obesity with EAC using a large prospective cohort. We also assessed these associations with adjacent adenocarcinomas of the gastric cardia and gastric non-cardia.
Materials and methods
The establishment and recruitment procedures of the National Institutes of Health–American Association of Retired Persons (NIH–AARP) Diet and Health Study have been described.19 Between 1995 and 1996, a baseline questionnaire was mailed to 3.5 million AARP (formerly known as the American Association of Retired Persons) members aged 50–71 years eliciting information on demographic characteristics, dietary intake and health-related behaviours. Members resided in six US states (California, Florida, Louisiana, New Jersey, North Carolina and Pennsylvania) and two metropolitan areas (Atlanta, Georgia and Detroit, Michigan). Of 617 119 questionnaires returned (17.6% of the 3.5 million mailed), a total of 566 401 respondents completed the survey in satisfactory detail and consented to participate in the study. A follow-up risk factor questionnaire was sent 6 months afterwards, which included information on waist and hip measurements. A total of 334 907 respondents completed and returned this survey. Of these respondents, we excluded subjects with a cancer diagnosis before returning the risk factor questionnaire (4552), proxy respondents (10 383), and those missing data for BMI (6608), or coded as missing/error for waist or hip measurements (88 255). Subjects who reported extreme (more than two times the IQR of sex-specific Box–Cox log-transformed values) total energy intake (1672), BMI (2191), waist (578) and hip (1813) measurements were also excluded. Those subjects who died or were diagnosed with cancer on the first day of follow-up were excluded (one). The resulting cohort included 218 854 participants: 132 288 men and 86 566 women.
Within the NIH–AARP Study, addresses for members of the cohort were updated annually through the USA Postal Service national change of address database and also linkage to commercial address databases, such as those used by banks and credit card companies, and take into account response to mailings; all told these resources provide nearly complete coverage. This method proved to be very robust as during 9 years of follow-up in a pilot study, only 2.5% (288/11 404) of surviving pilot study participants moved out of the cohort regions.20 Overall, our study has had limited loss to follow-up, with less than 5% of participants moving out of the cancer catchment area. Vital status was ascertained by linkage to the Social Security Administration Death Master File in the USA (all legal USA citizens are allocated a social security number), follow-up searches of the National Death Index (central computerised index of death record information), cancer registries (the NIH–AARP cohort was designed to include only individuals living in cancer registry states/metropolitan areas), questionnaire responses and responses to other mailings. Follow-up time extended from the study baseline (between 1995 and 1996) to 31 December 2006.
Identification of cancer cases
Incident cancer cases were identified by linkage between the NIH–AARP cohort membership and 10 state cancer registry databases, including the eight original states/metropolitan areas plus those of Texas and Arizona to capture subjects who moved to these states. A validation study showed that approximately 90% of all incident cancer cases in the NIH–AARP cohort were identified by using this approach.20 Cancer sites were identified by anatomical site and histological code of the International Classification of Disease for Oncology (ICD-O, 3rd edition).21 Tumours with ICD-O codes 15.0–15.9 were classified as oesophageal cancers; only oesophageal tumours that could be classified histologically as EAC were included in this analysis. Tumours histologically confirmed as adenocarcinomas and with an ICD-O site code of 16.0 were classified as gastric cardia adenocarcinomas; those with codes 16.1–16.7 were classified as gastric non-cardia adenocarcinomas; C16.8 (overlapping tumours) and C16.9 (not otherwise specified) were excluded in this analysis. The NIH–AARP Diet and Health Study was approved by the Special Studies Institutional Review Board of the US National Cancer Institute.
The anthropometric variables height, weight and BMI were derived from information provided in the baseline questionnaire. WHR was calculated from the risk factor questionnaire; participants recorded waist and hip measurements, to the nearest 0.25 inch, in response to detailed instructions. Due to differing fat distribution between men and women, sex-specific quartiles were used for height, weight, waist circumference, hip circumference and WHR. For BMI, we used predefined WHO standard categories: underweight, less than 18.5 kg/m2; normal, 18.5 to less than 25; overweight, 25 to less than 30; obese, 30 to less than 35; and morbidly obese 35 or greater.
All analyses were carried out using SAS V.9.1. We interpreted p<0.05 and/or 95% CI that excluded 1 as statistically significant. We used two-sided tests exclusively. Follow-up time extended from the day of study entry to the date of death, date of diagnosis of first upper gastrointestinal cancer or head and neck cancer, participant relocation out of the registry ascertainment area, or 31 December 2006, whichever date was earliest. We used multivariate Cox proportional hazards regression to estimate HR and 95% CI.
We fitted age and sex-adjusted models (data not shown) for comparison to fully adjusted models that included total energy intake (daily kilocalories), antacid, aspirin and non-steroidal anti-inflammatory drug use (yes/no during the past 12 months), marital status (yes/no), diabetes (yes/no), ethnicity (non-Hispanic white, non-Hispanic black, Hispanic and Asian/Pacific Islander/Native American), cigarette smoking (never smokers, former smokers who smoked ≤20 cigarettes/day, former smokers who smoked >20 cigarettes/day, current smokers who smoke ≤20 cigarettes/day and current smokers who smoke >20 cigarettes/day), education (high school graduate or less, post high school training or some college training, college graduate and postgraduate education), vigorous physical activity (never, rarely, 1–3 times/month, 1–2 times/week, 3–4 times/week, 5 or more times per week), usual activity throughout the day (sit all day, sit much of the day/walk some times, stand/walk often/no lifting, lift/carry light loads and carry heavy loads), alcohol consumption (none, >0–0.5, >0.5–1, >1–2, >2–4, >4 drinks per day), red and white meat intake (grams per day) and fruit and vegetable intakes (both pyramid servings per day). For the less than 4% of the cohort who had missing data for a particular covariate, a separate indicator variable for missing was included in the models. As a sensitivity analysis, we also created parsimonious regression models by adding potential confounding variables and retaining those that changed the β coefficients for the anthropometric variables by 10% or greater. Risk estimates were similar for both fully adjusted and parsimonious models, and therefore only results from the fully adjusted models are referenced.
We evaluated interactions with smoking (ever/never) and between WHR and BMI (normal 18.5–<25 kg/m2 or overweight ≥25 kg/m2) by performing stratified analysis and evaluating interaction terms.
In secondary analysis, we estimated whether abdominal obesity was associated with cancer risk statistically independently of the association with general obesity by mutually adjusting BMI and WHR for each other. In separate analyses, waist circumference and hip circumference were also mutually adjusted for each other.
Tests for trend across the categories of anthropometric variables were evaluated by assigning each participant the median category value and modelling this value as a continuous variable.
Table 1 presents the cohort characteristics by sex-specific quartiles of WHR. A similar table by BMI was published previously.16 During follow-up, we documented 253 cases of EAC (239 men and 14 women), 191 cases of gastric cardia adenocarcinoma (161 men and 30 women) and 125 cases of gastric non-cardia adenocarcinoma (89 men and 36 women). Men and women with higher WHR had fewer years of education, smoked more, reported less vigorous physical activity, consumed more calories and red meat per day, and were more likely to report diabetes.
Correlations between anthropometric variables are shown in table 2. Briefly, the correlations of BMI with waist circumference, hip circumference and WHR were 0.72, 0.72 and 0.35, respectively, and the correlation of waist circumference to hip circumference was 0.65. The correlations of WHR with waist circumference and hip circumference were 0.76 and 0.01, respectively.
Table 3 presents full multivariate adjusted HR (95% CI) for associations between anthropometric variables and the risk of EAC, gastric cardia adenocarcinoma and gastric non-cardia adenocarcinoma.
For EAC, weight, BMI, waist circumference, hip circumference and WHR were positively associated with EAC risk (highest vs referent category; HR 2.66, 95% CI 1.76 to 4.02, p for trend <0.01; HR 2.11, 95% CI 1.09 to 4.09, p for trend <0.01; HR 2.01, 95% CI 1.35 to 3.00, p for trend <0.01; HR 1.65, 95% CI 1.15 to 2.36, p for trend 0.01; and HR 1.81, 95% CI 1.24 to 2.64, p for trend <0.01, respectively). Multivariate adjustment had only a minor influence on the observed risk estimates from the age and sex-adjusted models (data not shown). For height, no association for those in the fourth quartile versus the referent was seen in the age and sex-adjusted model (HR 1.06, 95% CI 0.75 to 1.50, p for trend 0.92), but a borderline significant inverse association was observed in the multivariate adjusted model (HR 0.69, 95% CI 0.47 to 1.01, p for trend 0.09).
Weight, BMI, waist circumference and hip circumference all displayed an increasing risk of gastric cardia adenocarcinoma across their quartiles/categories (highest vs referent category; HR 2.52, 95% CI 1.55 to 4.11, p for trend <0.01; HR 3.67, 95% CI 2.00 to 6.71, p for trend <0.01; HR 2.22, 95% CI 1.43 to 3.47, p for trend <0.01; HR 1.71, 95% CI 1.14 to 2.58, p for trend 0.01, respectively). WHR was associated with gastric cardia adenocarcinoma in the age and sex-adjusted model (fourth quartile vs the referent; HR 1.57, 95% CI 1.08 to 2.28, p for trend 0.01), but was attenuated after multivariate adjustment (HR 1.37, 95% CI 0.92 to 2.05, p for trend 0.08). For height, no association for those in the fourth quartile versus the referent was seen in the age and sex-adjusted model (HR 1.10, 95% CI 0.76 to 1.61, p for trend 0.97), but a suggested inverse association was found in the multivariate adjusted model (HR 0.70, 95% CI 0.46 to 1.07, p for trend 0.09).
No consistent associations were seen for gastric non-cardia adenocarcinoma with the majority of the anthropometric variables in the multivariate adjusted models. However, weight appeared to be positively associated with gastric non-cardia adenocarcinoma risk; fourth quartile versus the referent; HR 1.93, 95% CI 1.05 to 3.54, and the p for trend approached significance 0.07. WHR was also associated with gastric non-cardia adenocarcinoma in the age and sex-adjusted model (fourth quartile vs the referent; HR 1.58, 95% CI 1.05 to 2.37, p for trend 0.02), and was marginally attenuated after multivariate adjustment (HR 1.56, 95% CI 0.94 to 2.59, p for trend 0.05).
We further evaluated whether smoking modified the relation of BMI and WHR with cancer risk using stratified models based on smoking status (smokers/non-smokers). This was evaluated because smoking can potentially be a strong confounder or effect modifier of the obesity–cancer association. In general, the pattern of risks was similar to that for the overall population, non-smokers and smokers. Formal tests for interaction failed to reach statistical significance in any of the investigations (all p for interaction >0.05) (see supplementary table, available online only).
The association of WHR with cancer risk was also assessed using dichotomous stratification of BMI as normal 18.5 to less than 25 kg/m2 or overweight 25 kg/m2 or greater (data not shown). When looking at WHR continuously, per 0.1 unit increment, the positive association seen between WHR and the risk of EAC in unstratified analysis (HR 1.27, 95% CI 1.05 to 1.53) remained evident in patients with normal BMI (HR 1.33, 95% CI 0.85 to 2.07), and overweight patients (HR 1.23, 95% CI 0.99 to 1.53). A positive association for WHR was also seen for the risk of gastric cardia adenocarcinoma in patients with normal BMI (HR 1.64, 95% CI 1.06 to 2.53), yet it was not present in overweight patients (HR 1.04, 95% CI 0.80 to 1.34), or in unstratified analysis (HR 1.16, 95% CI 0.93 to 1.44). However, formal tests for interaction failed to reach statistical significance in any of these investigations (all p for interaction >0.05).
In secondary analyses that further mutually adjusted BMI and WHR (table 4), the positive associations reported for the risk of EAC were both attenuated but not eliminated (BMI highest vs referent category; HR 1.77, 95% CI 0.90 to 3.49, p for trend <0.01; WHR highest versus referent category; HR 1.47, 95% CI 0.99 to 2.18, p for trend 0.02). For gastric cardia adenocarcinoma, adjustment of BMI for WHR had only a minor influence on the BMI risk estimate (highest vs referent category; HR 3.28, 95% CI 1.76 to 6.11, p for trend <0.01). WHR risk estimates remained non-significant, and were attenuated further after mutual adjustment for BMI. Adjustment of waist circumference for hip circumference had a minor effect on the risk estimates for either EAC or gastric cardia adenocarcinoma, whereas mutual adjustment of hip circumference for waist circumference resulted in null risk estimates for both EAC and gastric cardia adenocarcinoma. No consistent changes in associations were seen for gastric non-cardia adenocarcinoma after mutual adjustments.
In the prospective NIH–AARP cohort, we found that overall obesity, as measured by BMI, was related to a higher risk of EAC and gastric cardia adenocarcinoma. We also observed an increased risk of EAC with increasing abdominal obesity, as measured by waist circumference and WHR. Although waist circumference was also related to an increased risk of gastric cardia adenocarcinoma, no association with WHR was observed. The positive association between WHR and EAC risk persisted in patients with normal BMI, and mutual adjustment of WHR and BMI attenuated both, but did not eliminate the positive associations for either with the risk of EAC. No consistent associations were seen for gastric non-cardia adenocarcinoma with the majority of the anthropometric variables.
The use of BMI as a marker of obesity has been widely used, with the observation of this current study that BMI is positively associated with the risk of EAC being supported by case–control and cohort studies.8–14 16–18 22–24 Because EAC and gastric cardia adenocarcinoma are adjacent tumours that are difficult to separate clinically, they potentially share many of the same risk factors. Therefore, it was unsurprising to find a strong positive association between BMI and gastric cardia adenocarcinoma. Although the pooled results from a meta-analysis of case–control studies found only a weak association between increased BMI and gastric cardia adenocarcinoma in studies from the USA and Europe and no clear association in studies from China,8 results reported in previous cohort studies, which tend to be more robust, have shown similar results to our study.11 ,12 ,16 ,17 ,22 ,24 The lack of an association between BMI and gastric non-cardia adenocarcinoma observed in this current study is also in agreement with several previous studies11; 15 ,22 ,24 although a reduced risk with increasing BMI was demonstrated in a cohort study from Linxian, China25 in a population considerably leaner than that of the current study.
Even though similar results were found for the risk of EAC and gastric cardia adenocarcinoma with BMI, our models suggested that abdominal obesity (as measured by WHR) is associated only with EAC risk and not gastric cardia adenocarcinoma risk. This finding was somewhat surprising and unexpected, particularly due to their adjacent anatomical location and similar risk factors, as demonstrated within this current study. Nonetheless, we cannot rule out chance as the causal factor for this difference. Further studies are needed to address this potential discrepancy.
Our findings that abdominal obesity was also directly associated with the risk of EAC helps further extend those observations reported for BMI. To our knowledge, only three other studies have prospectively examined abdominal obesity in relation to EAC.15 ,17 ,18 Consistent with our study, a significant positive association was reported with waist circumference in all three,15 ,17 ,18 although only two of the studies further adjusted abdominal obesity for BMI.17 ,18 In our study, associations of WHR with EAC risk were attenuated, but not eliminated by adjustment for BMI.
Higher WHR can be the result of a larger waist as well as a smaller hip, either of which could affect disease risk.26 For example, studies of cardiovascular disease have noted that both large waist circumference and small hip circumference were related to disease risk in a mutually adjusted model.26–29 In the current study, the positive associations between waist circumference and EAC and gastric cardia adenocarcinoma risk remained after mutual adjustment for hip circumference; whereas associations between hip circumference and EAC and gastric cardia adenocarcinoma became non-significant after mutual adjustment for waist circumference. These results suggest that the positive association between WHR and EAC risk may be due to increasing waist circumference and perhaps visceral fat,17 ,18 rather than hip circumference, which may be a marker of lean muscle mass. As waist circumference and WHR are crude measures of intra-abdominal fat, we cannot draw definite conclusions. Future studies with more accurate measures of visceral fat and fat distribution are needed to confirm and extend these findings. Nevertheless, it would appear from our results that both overall and abdominal obesity may be positively associated with EAC risk.
One potential mechanism linking obesity to EAC is mechanical. Obese individuals are thought to have a higher prevalence of GERD due to increased intra-abdominal pressure on the lower oesophageal sphincter.30–32 Patients with GERD are commonly treated with medications to suppress the production of or neutralise gastric acid, for example antacids. If repeated exposure of oesophageal epithelium to gastric acid is the underlying cause of EAC, then it might be predicted that among patients with GERD, those taking acid suppressant medications would have lower risks of EAC than those not taking such medications. However, previous studies do not appear to support these hypotheses, instead suggesting that obesity and GERD are independent risk factors,10 ,33 and reporting a lack of association between acid suppressant medications and EAC associated with GERD.34 ,35 Also, in a recent study and editorial,36 ,37 it was suggested that intra-abdominal fat is associated with an increased risk of erosive oesophagitis in both men and women, independent of GERD. Unfortunately, our study lacked information on GERD and thus we could not explore this potential mechanism. However, we did carefully adjust our risk estimates for antacid use, although such adjustment had little effect.
An alternative hypothesis links obesity and cancer risk via the action of three hormonal systems; the insulin and insulin-like growth factor axis, sex steroids and adipokines.9 These metabolic products are all associated with increasing obesity, and help modulate cellular proliferation and apoptosis.38 In addition, the sex-steroid hypothesis may help explain higher incidence rates of these cancers in men, through the presence of oestrogen receptors in EAC.39 ,40 Limited evidence suggests that oestrogen receptors might mediate a protective effect on oestrogen in the development of oesophageal cancer.40 However, adipose tissue is one of the few in-vivo tissue depots that express oestrogen aromatase and is therefore a primary source of oestrogen in both men and postmenopausal women.41 Therefore, obesity seems unlikely to increase EAC risk through higher oestrogen levels in obese people, as women have substantially lower rates of EAC than men.
Another finding from our study is an apparent protective effect of increased height on EAC and gastric cardia adenocarcinoma risk; borderline significance comparing highest versus referent category for EAC; HR 0.69, 95% CI 0.47 to 1.01, p for trend 0.09); and a potential protective effect for gastric cardia adenocarcinoma (highest vs referent category; HR 0.70, 95% CI 0.46 to 1.07, p for trend 0.09). This result is somewhat consistent with the limited number of previous studies for EAC, but not gastric cardia adenocarcinoma.10 ,42 As attained adult height reflects the integration of many genetic, environmental, hormonal and also nutritional factors,5 it is not clear which aspect of height may contribute to the suggested association observed in our study. Future studies are needed to confirm these findings.
We noted an intriguing positive association between WHR and cigarette smoking (table 1), which is in contrast to the association of BMI in the same cohort.16 Similar findings have been reported in previous studies.43 ,44 It is possible that smoking habits may have an effect on fat distribution. Smoking could also affect the uptake and storage of triglyceride fatty acids, increasing fat mass. Differing associations between BMI and WHR with smoking require further study to help underpin a possible causal relationship.
As smoking is a risk factor for an increased risk of both EAC and gastric cardia adenocarcinoma,45–47 we carefully adjusted our risk estimates for cigarette smoking. Adjustment for smoking had a modest effect on risk estimates. Risk estimates for the anthropometric variables generally appeared similar across the stratum of cigarette smoking and tests for interaction were not significant. However, case numbers were limited in some joint categories of cigarette smoking and adiposity.
Our study had several strengths, including its prospective nature, large size and available data on a large number of adiposity measures and possible confounders. However, our study also had several limitations. As made evident from table 2, BMI was highly correlated with waist circumference and hip circumference, but not WHR. Therefore, interpretation of risk estimates from models containing multiple adiposity measures must be treated with caution. We lacked information on possibly important confounders, such as Helicobacter pylori infection, a cause of gastric non-cardia adenocarcinoma, which may protect against EAC,48 and may be associated with reduced obesity.49 Anthropometric variables in our study relied on self-reported data and therefore misclassification of exposure is a potential source of bias. Finally, we had limited ability to evaluate gender differences due to few case numbers in women. As men and women tend to have different fat distributions, future pooled studies are needed to assess possible differences by sex.
In summary, anthropometric indices of overall obesity were associated with a higher risk of EAC and gastric cardia adenocarcinoma. We also found an increased risk of EAC with increasing abdominal obesity, as measured by WHR, which persisted in patients with normal BMI. Finally, mutual adjustment of WHR and BMI attenuated both, but did not eliminate the positive associations for either with the risk of EAC. Associations between obesity and both cancer types suggest that interventions to reduce the prevalence of obesity may help to prevent adenocarcinomas of the oesophagus and gastric cardia.
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 Tumour 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.
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Files in this Data Supplement:
- Download Supplementary Data (PDF) - Manuscript file of format pdf
Funding This research was supported (in part) by the All-Ireland National Cancer Institute Cancer Consortium Joint Research Project in Cancer, supported by the Health and Social Care Research and Development Office (Belfast, Northern Ireland) and the Intramural Research Program of the National Institutes of Health, National Cancer Institute (Bethesda, Maryland, USA).
Competing interests None.
Ethics approval The NIH–AARP Diet and Health Study was approved by the Special Studies Institutional Review Board of the US National Cancer Institute.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement To gain access to the NIH–AARP data the correct procedures and proposal application should be followed. Instructions are accessible via the website: http://www.dietandhealth.cancer.gov.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.