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American Journal of Epidemiology Advance Access published online on June 27, 2007
American Journal of Epidemiology, doi:10.1093/aje/kwm122
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American Journal of Epidemiology Published by the Johns Hopkins Bloomberg School of Public Health 2007.

Original Contribution

Alcohol, Smoking, and Body Size in Relation to Incident Hodgkin's and Non-Hodgkin's Lymphoma Risk

Unhee Lim1, Lindsay M. Morton1, Amy F. Subar2, Dalsu Baris1, Rachael Stolzenberg-Solomon1, Michael Leitzmann1, Victor Kipnis2, Traci Mouw1, Leslie Carroll3, Arthur Schatzkin1 and Patricia Hartge1

1 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Rockville, MD
2 Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Rockville, MD
3 Information Management Services, Inc., Silver Spring, MD

Correspondence to Unhee Lim, Nutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard, EPS 320, Rockville, MD 20852 (e-mail: limu{at}mail.nih.gov).

Received for publication October 17, 2006. Accepted for publication March 14, 2007.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Studies associate alcohol consumption, cigarette smoking, and body size with the risk of overall or subtype lymphoma. Current data come mostly from case-control studies or prospective studies with few cases. In the prospective National Institutes of Health-former American Association of Retired Persons (NIH-AARP) Diet and Health Study, the authors assessed the above lifestyle factors via baseline questionnaire among 285,079 men and 188,905 women aged 50–71 years and ascertained histologically confirmed Hodgkin's lymphoma (n = 58) and non-Hodgkin's lymphoma (n = 1,381) cases through linkage with cancer registries from 1995 to 2000. Compared with nondrinkers, alcohol consumers had a lower risk for non-Hodgkin's lymphoma overall (for >28 drinks/week: adjusted relative risk (RR) = 0.77, 95% confidence interval (CI): 0.59, 1.00; ptrend among drinkers = 0.02) and for its main subtypes. Compared with never smokers, current smokers and recent quitters (≤4 years ago) had higher risk of Hodgkin's lymphoma (RR = 2.25, 95% CI: 1.04, 4.89; RR = 4.20, 95% CI: 1.94, 9.09, respectively), whereas current or former smokers had lower risk of follicular non-Hodgkin's lymphoma (RR = 0.67, 95% CI: 0.52, 0.86). Severe obesity (body mass index of ≥35: RR = 1.29, 95% CI: 1.02, 1.64) and taller height (RR = 1.19, 95% CI: 1.03, 1.38) were associated moderately with non-Hodgkin's lymphoma. These findings add to the evidence that lifestyle factors and relevant anthropometric characteristics play a role in lymphoma etiology.

alcohol drinking; body height; Hodgkin disease; lymphoma, non-Hodgkin; motor activity; obesity; prospective studies; smoking

Abbreviations: AARP, former American Association of Retired Persons; CI, confidence interval; ICD-O-2, International Classification of Diseases for Oncology, Second Edition; NIH-AARP, National Institutes of Health-former American Association of Retired Persons; RR, relative risk; SEER, Surveillance, Epidemiology, and End Results


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Doll and Peto (1) estimated 26 years ago that modifiable lifestyle factors, including alcohol consumption, cigarette smoking, and Westernized diet, may account for two thirds of all nongenetic cancer causes. Subsequent studies have confirmed the estimate and added the contribution of obesity and physical inactivity (2, 3). Lifestyle factors may in part explain the dramatic increase in non-Hodgkin's lymphoma incidence in recent decades, which is mostly unexplained by known causes (4–6). Added complexity is the potentially heterogeneous etiology among non-Hodgkin's lymphoma subtypes (5, 7).

Epidemiologic evidence to date, principally from large pooled analyses of case-control studies (8) and a cohort study (9), suggests that current alcohol consumers have decreased risk of most types of non-Hodgkin's lymphoma, although such protection was limited to men and non-Mediterranean countries in another pooled analysis (10). Pooled case-control and cohort data indicate increased risk of follicular lymphoma among cigarette smokers (11, 12). More prospective data are needed to eliminate the possibility that these associations, mostly from case-control studies with retrospective data collection on lifestyle and with typically low response rates among eligible controls, were spurious because of differential recall between cases and controls and self-selection of healthier or otherwise systematically different controls. Information on risk of older adult onset Hodgkin's lymphoma is sparse, but recent evidence suggests reduced risk associated with alcohol drinking and increased risk with smoking (13, 14).

Evidence regarding body size or physical inactivity is less consistent. Some researchers report increased non-Hodgkin's lymphoma incidence or mortality with increasing body mass index (kg/m2) (15–23), height (19, 24–26), or physical inactivity (21), whereas others report null associations or mortality with increasing body mass index (25, 27–33), central obesity (29, 32), height (28, 29, 31, 32), or physical inactivity (19, 29, 34, 35). Limited data on Hodgkin's lymphoma indicate a positive association with height (36, 37) and physical inactivity (37) but conflicting results for body mass index (16, 20, 30, 31, 33, 37–39).

The few prospective studies on these topics lack sample size and sometimes the histology information needed to distinguish among lymphoma subtypes. Large cohorts with reliable subtypes are essential. To pursue the effect of lifestyle factors that are often intercorrelated for biologic and socioeconomic reasons, we investigated the associations simultaneously with incident lymphomas in a large prospective study of diet/lifestyle and cancer.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Study population
The National Institutes of Health-former American Association of Retired Persons (NIH-AARP) Diet and Health Study was conducted by the US National Cancer Institute to investigate the relation between diet and health. As described in detail (40), we mailed out baseline questionnaires in 1995–1996 to 3.5 million members of the former American Association of Retired Persons (AARP) who were aged 50–71 years and residing in California, Florida, Louisiana, New Jersey, North Carolina, Pennsylvania, or metropolitan Atlanta (Georgia) and Detroit (Michigan). Of the 617,119 persons who returned the questionnaire between October 1995 and February 1997, a total of 567,169 completed it satisfactorily. We excluded one withdrawal, 179 duplicates, 582 persons who had died or moved out of the study area before study entry, 51,219 persons with a history of cancer by self-report and registry data (to avoid spurious associations due to postdiagnostic lifestyle changes), 1,668 persons with a diagnosis at death without histology information, 15,760 proxy respondents, 4,399 persons with extreme calories, and 19,377 persons with body mass index values that were missing (n = 11, 825), outliers (n = 3, 887), or less than 18.5 (n = 3,665) to avoid spurious associations due to morbidity-driven underweight. As a result, we considered 473,984 baseline questionnaires (285,079 men, 188,905 women) for the study.

The NIH-AARP Study was approved by the National Cancer Institute Special Studies Institutional Review Board. All participants provided written informed consent.

Case ascertainment
Through the end of year 2000, we identified incident cancer cases through linkage of the cohort to the eight study area cancer registries and ascertained additional fatal cancer cases through the National Death Index, detecting about 90 percent of all incident cancers within the study population (41). We included observation time until participants' first cancer diagnosis regardless of the site; non-Hodgkin's lymphoma diagnoses preceded by other cancers were not considered. According to annual updates by use of the National Change of Address (US Postal Service), other address services, and self-reports, over 95 percent of the cohort members remained in the same address or relocated within the study area for active follow-up (41).

We used the histology (International Classification of Diseases for Oncology, Second Edition (ICD-O-2)) and immunophenotype information from the cancer registries to define lymphoid neoplasms according to the World Health Organization classification (42). We grouped the cases into Hodgkin's lymphoma (ICD-O-2 codes 9650, 9652–9655, 9657–9667) and non-Hodgkin's lymphoma (ICD-O-2 codes 9590–9595, 9670–9675, 9677, 9680–9688, 9690–9698, 9700–9709, 9710–9717, 9761, 9764, 9800–9801, 9820–9828, 9850, 9940–9941, 9970). Non-Hodgkin's lymphoma was further classified into the main subtypes of diffuse large B-cell lymphoma (ICD-O-2 codes 9680–9684, 9688, 9710–9712, 9715), follicular lymphoma (codes 9690–9693, 9695–9698), chronic lymphocytic leukemia (code 9823), and small lymphocytic lymphoma (code 9670) combined (chronic lymphocytic leukemia/small lymphocytic lymphoma), as well as T-cell lymphoma (codes 9700–9709, 9713–9714, 9716–9717, 9800–9801, 9827) (5).

Lifestyle and anthropometric data
The baseline questionnaire included a food frequency questionnaire validated against two 24-hour recalls (40). The food frequency questionnaire asked about consumption frequency in the past year of 124 food items, including three alcoholic beverages: beer in summer and for the rest of the year, wine or wine coolers, and liquor or mixed drinks. Participants selected the frequency (10 response categories ranging from never to ≥2 times/day for foods or ≥6 times/day for beverages) and portion size (small, medium, large): The medium portion was defined as 1–2 cans (12 ounces (354.88 ml)) for beer, 4–8 ounces (118.29–236.58 ml) for wine, and 1–2 shots for liquor.

The questionnaire asked about other lifestyle characteristics, that is, if the respondent had smoked 100 or more cigarettes during his/her lifetime, smoking status (currently smoking; quit <1, 1–4, 5–9, or ≥10 years ago), and usual dose (1–10, 11–20, 21–40, 41–60, or ≥61 cigarettes/day). Participants were also asked to report their current height (feet and inches) and weight (pounds), from which body mass index was calculated and categorized as normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), or obese (≥30 kg/m2) (World Health Organization (43)); additionally, we examined body mass index of 35 kg/m2 or more as "severely obese." We removed extreme calories and body mass index values outside the two interquartiles from their sex-specific transformed means, analyzing men with 415–6,143 kcal and body mass index of 18.5–42.6 and women with 322–4,823 kcal and body mass index of 18.5–49.3. Current physical activity at work or home was assessed by frequency (never; rarely; 1–3 times/month; 1–2, 3–4, or ≥5 times/week) of activities that lasted at least 20 minutes and caused breathing or heart rate increase or sweating. Queries were also made on activity levels at work and at the ages of 15–18 years.

We sought information on past body weight and self-measured waist and hip circumferences through a second questionnaire, with 60 percent response (n = 334,910) among the baseline participants. After application of the exclusion criteria, 287,091 participants were analyzed for past weight or body mass index (using weight at ages 18, 35, and 50 years and minimum and maximum adult weight), and 207,072 participants were analyzed for waist and hip circumferences.

Statistical analyses
We computed age- and sex-standardized incidence ratios to compare the incidence rates of Hodgkin's lymphoma and non-Hodgkin's lymphoma in our data with the rates in the US Surveillance, Epidemiology, and End Results (SEER) data (44), using SEER*Stat software, version 6.2.3. To ensure comparability of the AARP and SEER data for the standardized incidence ratio estimation, we included, for this and not other analyses, all individuals regardless of history of other cancers in the AARP data and combined chronic lymphocytic leukemia, which is considered the same disease as small lymphocytic lymphoma, with the other non-Hodgkin's lymphoma subtypes in the SEER data.

We examined baseline characteristics by lifestyle and by case status to identify potential confounders. Age- and sex-adjusted means of characteristics were estimated for each category of alcohol, smoking, body mass index, and height (sex-specific quartiles) using general linear models, while cases were compared with others by Wilcoxon's rank sum tests (continuous) and chi-squared tests (categorical) for unadjusted characteristics.

For the associations between lifestyle and lymphoma, we obtained relative risks and 95 percent confidence intervals using Cox's proportional hazards regression that adjusted for age at study entry, sex, ethnicity, alcohol consumption (0, 0.1–2, 2.1–7, or >7 drinks/week), and smoking history (never, former, or current smoker) among 465,858 persons (57 Hodgkin's lymphoma and 1,350 non-Hodgkin's lymphoma cases) with the covariate information. In addition, body mass index, height, and physical activity were mutually adjusted for in estimating their individual main effects. We evaluated other lifestyle and dietary characteristics and retained them in the model for confounding if their addition changed the relative risk of the main association by 10 percent or more. Risk estimates were virtually unchanged when age, rather than follow-up time (adjusted for baseline age), was the underlying time metric. A linear trend (dose response) between a categorical factor and cancer was determined by use of the Wald test of a score variable that contained median values of the categories. Effect modification of each main association by other factors was evaluated using cross-product terms (p < 0.10 considered significant). All other p values were two sided, with an {alpha} of 0.05 (SAS, version 8, software; SAS Institute, Inc., Cary, North Carolina).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
During up to 5.2 years of follow-up (mean: 4.3 years; 2,060,611 person-years), 43 men and 15 women were diagnosed with Hodgkin's lymphoma, and 958 men and 423 women were diagnosed with non-Hodgkin's lymphoma. The age- and sex-standardized incidence rates among Whites in the NIH-AARP Study (3/100,000 person-years for Hodgkin's lymphoma, 73/100,000 person-years for non-Hodgkin's lymphoma) were largely comparable with the SEER rates for Hodgkin's lymphoma (standardized incidence ratio = 0.79, 95 percent confidence interval (CI): 0.60, 1.02) and non-Hodgkin's lymphoma (standardized incidence ratio = 0.98, 95 percent CI: 0.94, 1.03). The standardized incidence ratios were similarly null in men and women and in other races (data not shown).

As expected, alcohol intake and cigarette smoking were related to each other and to body mass index (table 1). Drinkers were more likely to smoke and vice versa. Drinkers were also leaner and physically more active. Current smokers (12 percent) tended to have lower body mass indexes and to be less active than former or never smokers. Compared with normal-weight participants, overweight (43 percent) and obese (22 percent) individuals tended to drink less and were likely to be former smokers and less active. More taller individuals (quartiles 2–4) consumed alcohol and were former smokers, lighter, and active. Unadjusted or age- and sex-adjusted correlations among the four lifestyle factors were all significant (p < 0.0001), but only the coefficient of –0.16 between body mass index and physical activity was above 0.1. In a comparison by case status, both Hodgkin's lymphoma cases and non-Hodgkin's lymphoma cases were more likely to be older and male than the others. Hodgkin's lymphoma cases tended to be less educated, and non-Hodgkin's lymphoma cases tended to be White (data not shown).


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  		TABLE 1. Baseline characteristics (age- and sex-adjusted means or proportions)* by categories of alcohol intake, smoking status, body mass index, and height at baseline, NIH-AARP{dagger} Diet and Health Study, 1995–2000 (n = 473,984)

 
Compared with nondrinkers, people who consumed an increasing amount of alcohol had lower risk of non-Hodgkin's lymphoma (table 2). Risk estimates were similar without adjustment for smoking (relative risks (RRs) = 0.97, 0.81, 0.70, 0.75, and 0.75; 95 percent CI: 0.58, 0.98) and for the small number of Hodgkin's lymphoma cases. When adjusted additionally for body mass index and physical activity, the association changed little (for non-Hodgkin's lymphoma: RRs = 0.98, 0.83, 0.72, 0.78, and 0.79; 95 percent CI: 0.60, 1.03). The inverse alcohol-lymphoma association remained for the main B-cell subtypes (diffuse large B-cell lymphoma, follicular lymphoma, and chronic lymphocytic leukemia/small lymphocytic lymphoma) and did not vary by age, sex, race, smoking status, or body mass index (data not shown). We also observed similar inverse associations for individual beverage types. In a mutually adjusted model including all three types, the association remained for beer but was attenuated for liquor and wine (data not shown). However, the inverse alcohol–non-Hodgkin's lymphoma association persisted among non-beer drinkers.


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  		TABLE 2. Adjusted relative risks and 95% confidence intervals of incident Hodgkin's lymphoma, non-Hodgkin's lymphoma, and non-Hodgkin's lymphoma subtypes according to levels of alcohol intake, the NIH-AARP* Diet and Health Study, 1995–2000 (n = 465,858){dagger}

 
Hodgkin's lymphoma risk was doubled among current smokers and even greater among former smokers who had quit recently (table 3). The association was slightly strengthened when adjusted for body mass index and physical activity (for current smokers: RR = 2.43, 95 percent CI: 1.11, 5.32). On the other hand, the risk for non-Hodgkin's lymphoma overall and subtypes (including non-major B-cell subtypes combined) was not associated with smoking, except for follicular lymphoma. We observed lower risk of follicular lymphoma associated with both current and former smokers, but without a dose-response relation among smokers. The protective effect was substantial and significant for former smokers who had quit 10 or more years prior to baseline but not among more recent quitters. The association was not affected by adjustment for other lifestyle factors and was consistent across categories of age, sex, ethnicity, alcohol consumption, and body mass index (data not shown).


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  		TABLE 3. Adjusted relative risks and 95% confidence intervals of incident Hodgkin's lymphoma and non-Hodgkin's lymphoma overall and for the main subtypes according to levels of cigarette smoking, the NIH-AARP* Diet and Health Study, 1995–2000 (n = 465,858){dagger}

 
Severe obesity (body mass index of ≥35 kg/m2) at baseline was associated with elevated risk of Hodgkin's lymphoma and non-Hodgkin's lymphoma (table 4). The body mass index–non-Hodgkin's lymphoma association did not vary by age, sex, ethnicity, activity, smoking status, or alcohol intake (data not shown). When lower body mass index (18.5–22.4 kg/m2) was set as the referent, risk estimates became strengthened for diffuse large B-cell lymphoma (for body mass index ranges 22.5–24.9, 25–29.9, 30–34.9, and ≥35 kg/m2: RRs = 1.48, 1.22, 1.46, and 1.53; 95 percent CI: 0.88, 2.69). However, we found no relation to lymphoma risk with central obesity (waist/hip ratio) (table 4), body mass index at ages 18, 35, and 50 years, or maximum weight gain during adulthood (data not shown), data for which were available in a subgroup that completed the second questionnaire. People who completed the second questionnaire were similar to those who did not, with a slightly lower mean body mass index (26.9 vs. 27.3 kg/m2), and showed a weaker association between severe obesity and non-Hodgkin's lymphoma (RR = 1.15, 95 percent CI: 0.84, 1.57) than the baseline cohort. Average to taller height was associated with increased risk for non-Hodgkin's lymphoma (for quartiles 2–4 combined: RR = 1.19, 95 percent CI: 1.05, 1.35) and similarly for the subgroup (data not shown). Current overall activity (table 4), as well as activity at work or at ages 15–18 years (data not shown), was not associated with lymphoma risk.


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  		TABLE 4. Adjusted relative risks and 95% confidence intervals of incident non-Hodgkin's lymphoma overall and the main subtypes according to levels of body size indicators, the NIH-AARP* Diet and Health Study, 1995–2000 (n = 465,858){dagger}

 
When the data in the first year of follow-up were disregarded to minimize the potential influence of latent diseases on behavior (current drinking or smoking) or anthropometry (current weight), associations were strengthened for alcohol and non-Hodgkin's lymphoma (for >28 drinks/week: RRs from 0.78 to 0.71, 95 percent CI: 0.52, 0.97; p = 0.009 among drinkers), smoking and Hodgkin's lymphoma (for current smoking: RRs from 2.25 to 2.67, 95 percent CI: 1.04, 6.82; p = 0.05), and severe obesity and non-Hodgkin's lymphoma (RRs from 1.29 to 1.44, 95 percent CI: 1.10, 1.88; p = 0.01), whereas the association between current smoking and follicular lymphoma was attenuated (RRs from 0.66 to 0.75, 95 percent CI: 0.47, 1.19). The association between former smoking and follicular lymphoma remained (RRs from 0.68 to 0.66, 95 percent CI: 0.49, 0.88). We also reexamined the anthropometric associations after including back the individuals with extreme calorie and body mass index values and found a slight attenuation (for severe obesity and non-Hodgkin's lymphoma: RR = 1.24, 95 percent CI: 0.98, 1.56; for the highest vs. the lowest height quartile: RR = 1.16, 95 percent CI: 1.00, 1.35). In addition, each main association was examined for potential confounding by dietary factors, including fat, protein, fiber, antioxidants, folate, fruits and vegetables, red meat, fish, and dairy intake. None of them meaningfully changed the associations, except attenuation of the smoking-Hodgkin's lymphoma relation by fruit intake (RRs from 2.25 to 1.78, 95 percent CI: 0.81, 3.94).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
In the large prospective data of older adults, we observed alcohol consumption associated with lower risk of non-Hodgkin's lymphoma, cigarette smoking with higher risk of Hodgkin's lymphoma but lower risk of follicular lymphoma, and severe obesity and taller height with moderately elevated risk of non-Hodgkin's lymphoma.

Our data support the majority of cohort (9) and case-control (8, 10, 13) study findings that moderate alcohol consumption is associated with lower risk of non-Hodgkin's lymphoma, similarly across the main B-cell subtypes (8, 13), beverage types (8, 9, 13), smoking status (8, 10), and demographic factors (8). However, while the inverse association was in a threshold pattern comparing drinkers and nondrinkers in the pooled data of the InterLymph (8), we observed a dose-response relation up to 14 drinks/week and a slight attenuation in higher doses, where dose categories were similar as in the pooled analyses. Our data were limited to determine whether a J-shaped association exists with heavy alcohol consumption above 28 drinks/week (about 50 g/day of alcohol). The protective pattern that we observed for Hodgkin's lymphoma is also inconclusive because of the small numbers, although such associations were reported previously (13, 14).

Moderate drinking may protect against lymphoma through modulating immunity (45, 46), insulin sensitivity (47–49), or inflammation (50–52). We observed the strongest effects with beer rather than wine or liquor intake, but the potential benefits specific to beer (53) did not explain the inverse alcohol–non-Hodgkin's lymphoma association among non-beer drinkers. An alternative explanation is confounding by socioeconomic status and behavior among mild to moderate drinkers. Although we did not find any strong confounding in our data, we cannot rule out residual confounding. Our investigation was limited to reports of recent alcohol consumption, which may reflect better health among drinkers versus nondrinkers who might have quit drinking because of health reasons. However, other studies with past drinking history found similar inverse associations with lifetime alcohol consumption (8, 15), with the protective effect largely limited to current or recent consumption (8).

The protective association between smoking and follicular lymphoma was an unexpected outcome. Previous studies have detected either null or positive associations (11, 12, 54), using self-reports that are considered reliable for assessing smoking (55). Some inconsistencies regarding our finding, such as no dose response among smokers and a stronger association among quitters of distant than recent past, imply not necessarily protection from smoking but potential confounding by other factors for this indolent disease that is largely diagnosed at later stages (56). We have detected positive associations of smoking with other tobacco-related cancers (57) and with Hodgkin's lymphoma in this cohort as reported previously (13, 14, 58, 59). If we exclude the first year of follow-up, to exclude lifestyle and anthropometry reports that might have reflected any prodromal illness in the year before lymphoma diagnosis, the association between current smoking in particular and follicular lymphoma is attenuated. We cannot infer with confidence whether there was a slight protective effect or no relation, but this further reduces the robustness of the protective association and implies a false positive finding.

Obesity has been associated with higher non-Hodgkin's lymphoma mortality (17, 18), but prospective evidence for non-Hodgkin's lymphoma incidence has not been strong (25, 29, 33), with some positive findings based on direct measures of weight and height (16, 20). We observed moderately increased non-Hodgkin's lymphoma risk with severe obesity, especially for the clinically more aggressive diffuse large B-cell lymphoma (19, 23, 31). Within chronic lymphocytic leukemia/small lymphocytic lymphoma, the body mass index association was null for chronic lymphocytic leukemia and nonsignificantly inverse for small lymphocytic lymphoma, the latter of which is consistent with a previous observation that lymphadenopathy leading to small lymphocytic lymphoma diagnosis may be harder to detect among obese than normal-weight individuals (29, 60). The nonsignificant positive relation between obesity and Hodgkin's lymphoma is supported by two studies in men (16, 38) but not by others (16, 30, 31, 37). Despite the significant body mass index–non-Hodgkin's lymphoma finding, we detected a null association for central obesity that showed a positive pattern of association with non-Hodgkin's lymphoma in a cohort of women (29). However, we had data on central obesity and other anthropometric indicators only in a slightly leaner subgroup that showed an attenuated body mass index–non-Hodgkin's lymphoma association. Overall, our findings regarding body mass index suggest that the proposed carcinogenic mechanisms of excess adiposity (61) may be relevant to lymphomagenesis as well, possibly in different magnitudes in subtypes.

The association between physical activity and non-Hodgkin's lymphoma is not strong in this and other studies (19, 29, 34, 35), contradicting limited evidence for protection, especially regarding women or follicular lymphoma (21) and before adjustment for body mass index and alcohol intake (19). The null association in our data did not differ in subgroups or by covariate adjustments. It was suggested that the measurement error associated with physical activity assessment may be larger than measurement error in body mass index or dietary factors (19), which may be the case in our current or past activity data that included simple categories of frequency or intensity.

Our finding of a positive association between adult height and incident non-Hodgkin's lymphoma is in line with previous evidence (25). Adult height is determined by a combination of genetic and environmental factors during infancy, childhood, and puberty (62). Therefore, its positive association with non-Hodgkin's lymphoma and other cancers may be explained by socioeconomic confounding, physiologic factors that induce both growth and later susceptibility to carcinogenesis, or both. Mechanisms proposed for non-Hodgkin's lymphoma include more abundant growth factors and less frequent infection leading to taller stature, but also causing more unregulated somatic growth and less adaptive immunity (63).

Because of the large size of the cohort, we were able to estimate associations for the main subtypes of non-Hodgkin's lymphoma. The prospective follow-up reduced potential recall bias, and the comprehensive list of lifestyle factors allowed us to adjust for correlated lifestyle behaviors. Our study population had lymphoma incidence rates and lifestyle characteristics comparable with those of the US population of similar age, such as alcohol intake and beverage preferences (64), current smoking (65), and prevalence of obesity (66). Histology information from cancer registries minimized disease misclassification. We had a low loss to follow-up due to moving out of the study region (5 percent) and high completion of case ascertainment (90 percent). It is not likely that the loss to follow-up is associated with both exposure and risk, and thus not a source of bias, but it may have reduced the study power to detect a true association.

On the other hand, our data at this point in follow-up are still limited for detailed examination of non-Hodgkin's lymphoma subtypes. Our questionnaire-based estimation of alcohol intake and cigarette smoking did not incorporate cumulative exposure and likely involved measurement error stemming from general underreporting and misreporting (67). Similarly, measurement error in self-reported weight and height, together with bias from underreporting of weight among the heavy and overreporting of height among the short (68, 69), might have slightly attenuated the true underlying association of these factors or body mass index with lymphoma.

In summary, lifestyle was modestly associated with lymphoma risk. Our findings strengthen the existing evidence on alcohol, body mass index, and height and warrant further investigations of smoking and central and past obesity after a longer follow-up of this cohort and by other prospective studies.


   ACKNOWLEDGMENTS
 
This research was supported by the Intramural Research Program of the National Cancer Institute, National Institutes of Health.

The authors gratefully acknowledge the contributions of David Campbell, Eric Berger, and Joe Barker at Information Management Services, Inc., for programming support and Tawanda Roy at the Nutritional Epidemiology Branch for research assistance.

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; the views expressed herein are solely those of the authors and do not necessarily reflect those of the contractor or Department of Health. 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.

Conflict of interest: none declared.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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