Physical Activity, Obesity, Energy Intake, and the Risk of Non-Hodgkin's Lymphoma: A Population-based Case-Control Study

Sai Yi Pan1, Yang Mao1, Anne-Marie Ugnat1 and the Canadian Cancer Registries Epidemiology Research Group

1 Surveillance and Risk Assessment Division, Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, Ottawa, Ontario, Canada

Correspondence to Dr. Yang Mao, Surveillance and Risk Assessment Division, Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, 120 Colonnade Road, Locator 6702A, Ottawa, Ontario, Canada K1A 0K9 (e-mail: Yang_Mao{at}phac-aspc.gc.ca).

Received for publication February 24, 2005. Accepted for publication August 1, 2005.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
The authors conducted a population-based case-control study of 1,030 cases with histologically confirmed, incident non-Hodgkin's lymphoma (NHL) and 3,106 controls to assess the impact of recreational physical activity, obesity, and energy intake on NHL risk in Canada from 1994 to 1997. Compared with those for subjects in the lowest quartiles of total recreational physical activity, multivariable-adjusted odds ratios for subjects in the highest quartile were 0.79 (95% confidence interval (CI): 0.59, 1.05) for men and 0.59 (95% CI: 0.42, 0.81) for women. Obesity (body mass index ≥30 kg/m2) was associated with odds ratios of 1.59 (95% CI: 1.18, 2.12) for men and 1.36 (95% CI: 1.00, 1.84) for women. For men and women with a lifetime maximum body mass index of ≥30 kg/m2, respective odds ratios were 1.55 (95% CI: 1.16, 2.06) and 1.10 (95% CI: 0.83, 1.46). For men and women in the highest quartiles of calorie intake, respective odds ratios were 1.95 (95% CI: 1.45, 2.62) and 1.13 (95% CI: 0.84, 1.52). Some differences were found between histologic subtypes of NHL for these associations. This study suggests that recreational physical activity decreases NHL risk, while obesity and excess calorie intake increase it. More studies are needed to confirm these results, especially the differences between histologic subtypes.

case-control studies; energy intake; exercise; lymphoma, non-Hodgkin; obesity; recreation


Abbreviations: BMI, body mass index; CI, confidence interval; MET, metabolic equivalent task; NHL, non-Hodgkin's lymphoma


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
The incidence and mortality of non-Hodgkin's lymphoma (NHL) have steadily increased in Canada (1Go) and in the United States since the 1970s but have stabilized in recent years in the United States (2Go). Over the last 30 years, the number of new cases of NHL has more than tripled among both men and women while the rates have doubled; and the number of annual deaths from NHL also has almost tripled, although the mortality rate has increased more modestly (1Go). This trend of increase appears worldwide (3Go), and the incidence rates in Canada and the United States are among the highest in the world (2Go). However, the reason for the increase is largely unknown.

The etiology of NHL is poorly understood. Suspected risk factors include immunodeficiency; infections of human T-cell lymphotrophic virus (types I and II), Epstein-Barr virus, and Helicobacter pylori; family history; and agricultural and pesticide exposure (3Go). Immunodeficiency is the strongest risk factor known to increase NHL risk (4Go), supported by evidence of substantially increased risk of NHL for patients treated with immunosuppressive drugs (5Go), people infected with human immunodeficiency virus (6Go), and young people with ataxia-telangiectasia or the Wiskott-Aldrich syndrome as well as children with X-linked lymphoproliferative syndrome or combined immunodeficiency (7Go).

Physical activity has been associated with reduced risks of some types of cancer (8Go–10Go), and improving immune function has been hypothesized to be one of the underlying mechanisms (10Go, 11Go); thus, it may decrease the risk of NHL. Obesity has been associated with significant metabolic abnormalities, including insulin resistance, glucose intolerance, and diabetes mellitus (12Go) as well as impaired immune function (13Go). Excess energy intake is also related to obesity. However, limited data are available, and the findings from previous epidemiologic research on the association of physical activity and obesity with NHL risk have been conflicting (14Go–23Go). Since there are very few known risk factors for NHL, and physical activity and obesity are modifiable lifestyle factors, if proven to be related to the risk of NHL, adoption of a healthy lifestyle would be a meaningful strategy for combating this tumor. Therefore, we conducted this study to examine the impact of recreational physical activity, obesity, and energy intake on the risk of NHL, using data from a large, population-based case-control study in Canada.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Study population
This study was part of the National Enhanced Cancer Surveillance System, a multicomponent, collaborative project of Health Canada and the provincial cancer registries. The case-control component included individual data from 21,020 Canadians with one of 19 types of cancers and 5,039 population controls aged 20–76 years; these data were collected between 1994 and 1997 in eight of the 10 Canadian provinces (Alberta, British Columbia, Manitoba, Newfoundland, Nova Scotia, Ontario, Prince Edward Island, and Saskatchewan). The respective ethics review boards of each province reviewed and approved the study proposal. The current analysis was based on 1,030 incident cases of NHL and 3,106 controls from all eight provinces except Ontario.

The population-based provincial cancer registries identified NHL cases through a review of pathology reports. All cases were patients with histologically confirmed incident NHL, newly diagnosed between 1994 and 1997 in the seven participating provinces. The cancer registries tried to identify cases as soon as possible after diagnosis to reduce the loss of subjects caused by severe illness and death. The registries identified 1,678 NHL cases. Physicians refused consent to contact 109 cases (6.5 percent), and 147 cases (8.8 percent) died before they could be sent questionnaires. Questionnaires were mailed to 1,422 cases; 1,030 cases completed and returned the questionnaires, representing 72.4 percent of cases who were sent questionnaires and 61.4 percent of ascertained cases.

The morphologic data were derived from pathology reports and were coded by using the International Classification of Diseases for Oncology, Second Edition. The histologic subtypes of NHL were grouped on the basis of this coding by using the method developed by Groves et al. (24Go). However, because of the small number of cases for the categories of high-grade and peripheral T cell, the histologic subtypes were grouped into the following four broader categories: diffuse, follicular, small lymphocytic, and others.

In the National Enhanced Cancer Surveillance System, frequency matching to the overall case group (19 types of cancers) was used to select population controls with a similar age and sex distribution so there would be at least one control for every case within each sex and 5-year age group for any specific cancer site in each province. The sampling strategy for control selection varied by province, depending on data availability, data quality (completeness and timeliness), and the confidentiality restrictions of provincial databases.

Prince Edward Island, Nova Scotia, Manitoba, Saskatchewan, and British Columbia used provincial health insurance plans to obtain a random sample of the provincial population stratified by age group and sex. More than 95 percent of Canadians are covered by these public plans, and individuals are excluded only if they are covered through other federal plans. Newfoundland and Alberta used similar random digit dialing protocols to obtain population samples. In Alberta, the University of Alberta's Population Research Laboratory generated a random sample of provincial telephone numbers, including unlisted numbers. Of the numbers called, 4 percent were not in service or were assigned to businesses, 3.6 percent involved a communication barrier, and, for 11.5 percent, there was no answer after attempting to call eight times. Of those households contacted, 91.3 percent agreed to a census of residents, and 90.1 percent of the eligible individuals agreed to have a questionnaire sent. Ninety-nine percent of Albertan households have telephones, and the Population Research Laboratory estimates that 92–97 percent of people in the province are reachable. Newfoundland Telephone Company provided the local cancer registry with a random sample of Newfoundland phone numbers, including unlisted numbers. Exact contact and eligibility rates are unavailable; however, study personnel estimated that 85 percent of the phone numbers were reached. Cooperation levels were similar to those in Alberta. Of the controls who were sent questionnaires, 83 percent and 75 percent completed and returned them in Alberta and Newfoundland, respectively.

The provincial cancer registries recruited 5,107 subjects without cancer in the seven participating provinces studied and mailed these subjects the same questionnaires as those sent to cases. Questionnaires were returned for 81 controls (1.6 percent) because of a wrong or old address, and no updated address could be found. A total of 3,106 controls completed and returned questionnaires, representing 60.8 percent of the ascertained controls.

Data collection
The provincial registries collected data by self-administered questionnaires, with telephone follow-up when necessary for clarification and completeness. The registries used the same protocol to collect data for both cases and controls.

The questionnaires were designed to obtain detailed data on risk factors for cancers. Information was collected on education, average family income over the last 5 years, marital status, ethnic group, height, weight, physical activity, alcohol consumption, diet (69-item food frequency questions), and vitamin and mineral supplement use 2 years before interview. Questionnaires also gathered information about smoking history, menstrual and reproductive history, employment history, residential history, and history of occupational exposure to some specific chemicals.

Assessment of physical activity
The questionnaire elicited information on recreational physical activity 2 years before interview. Respondents were asked in which seasons, how often, and how long per session, on average, they participated in each of the 12 most common types of leisure-time physical activity in Canada. Individual activities included walking for exercise, jogging or running, gardening or yard work, home exercise or exercise class, golf, racquet sports, bowling or curling, swimming or water exercise, skiing or skating, bicycling, social dancing, and other strenuous exercise. Respondents indicated their usual frequency of participating in each of these activities by choosing one of the following categories: never, less than once per month, 1–3 times per month, 1–2 times per week, 3–6 times per week, or every day. Time per session was recorded as less than 15 minutes, 15–30 minutes, 31–60 minutes, and more than 60 minutes. We estimated the intensity of each activity by assigning a specific metabolic equivalent task (MET) value to each reported activity. The MET values used here were abstracted from the Compendium of Physical Activities (25Go, 26Go). A MET is defined as the ratio of the associated metabolic rate for a specific activity compared with the resting metabolic rate (27Go). One MET is the average seated resting energy cost for an adult and is set at 3.5 ml/kg of body weight per minute of oxygen.

A weekly number of MET-hours was derived for each activity by combining the frequency, duration, and MET value (intensity) of each activity. We categorized levels of recreational activity as moderate (MET ≥3–≤6), vigorous (MET >6), and total (moderate plus vigorous) (28Go). The variable used in the analysis was the sum of each category of moderate, vigorous, and total physical activity.

Assessment of obesity and energy intake
Participants in the study reported their adult height and weight 2 years before interview as well as their lifetime maximum weight (except during pregnancy). As a measure of overweight and obesity, body mass index (BMI) was calculated as the reference weight in kilograms divided by height in meters squared. On the basis of World Health Organization standards, obesity was defined as a BMI of 30 kg/m2 or more, and overweight was defined as a BMI of between 25 and less than 30 kg/m2 for both sexes (29Go).

The questionnaire asked subjects the usual frequency and portion size for each of the 69 food items consumed 2 years before interview. We calculated weekly intake of calories for each item by multiplying the quantity of each item per week by the associated calorie value, which is determined from food composition data by using the Canadian Nutrient Guide (30Go). We summed the weekly calorie intake for all 69 items to obtain total calorie intake.

Statistical analysis
We estimated the risk of NHL associated with recreational physical activity and obesity based on odds ratios and corresponding 95 percent confidence intervals, using unconditional logistic regression with the software package SAS (version 8; SAS Institute, Inc., Cary, North Carolina). Variables were categorized into quartiles based on the distribution of the variables in the control population.

Because cases and controls were not directly matched, the methods for identifying cases and controls varied by province; and, because age is associated with NHL risk, all logistic regression analyses were controlled for province of residence and age to remove the impact of any uneven distribution of these factors between cases and controls. We used the change-in-point-estimate approach to assess the potential confounding effect of a wide range of factors, including age, educational level, family income adequacy, marital status, alcohol consumption, smoking, BMI, total calorie intake, menopausal status, and number of livebirths. We retained variables in the final models that are considered biologically important if their inclusion changed the odds ratio estimate appreciably, regardless of the statistical significance. We adjusted the final multivariate models for age (years, continuous), province of residence, education (years completed: <10, 10–12, >12), alcohol consumption (servings per week, continuous), pack-years of smoking (continuous), total calorie intake (kilocalories per week, continuous), self-reported exposure to some chemicals, and ever employment in some occupations. We conducted tests for trends for all models of categorized data by treating the different categories as a single ordinal variable.

The literature suggests that risk factors for NHL may differ by histologic subtype; therefore, we performed stratified analysis by histologic subtype of NHL. Because BMI is related to levels of insulin and insulin-like growth factors, which may also be affected by physical activity (10Go–12Go), we assessed possible effect modification by BMI.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Data from 1,030 NHL cases and 3,106 controls were available for analysis. Diffuse NHL was the most common histologic subtype among cases (n = 419, 40.7 percent of all cases), followed by follicular (n = 242, 23.5 percent) and small lymphocytic (n = 100, 9.7 percent). All other types accounted for 26.1 percent (n = 269) of all cases of NHL.

Table 1 shows the distribution of some selected characteristics of NHL cases and controls. For both sexes combined, compared with controls, cases tended to have higher total calorie intake and were more likely to be obese and to be exposed to several chemicals (pesticides, herbicides, vinyl chloride, benzidine, benzene, mineral or cutting oil, and dyestuffs). There were no clear differences between cases and controls regarding other variables. For men and women separately, the distribution of these variables among cases and controls was similar to that for both sexes combined, except that female cases drank less alcohol than did female controls.


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TABLE 1. Selected characteristics of non-Hodgkin's lymphoma cases and controls, National Enhanced Cancer Surveillance System, Canada, 1994–1997*

 
Table 2 presents the NHL risks associated with different levels of recreational physical activity (moderate, vigorous, and total), BMI, and calorie intake, by sex. Compared with those for subjects in the lowest quartiles of total activity, multivariable-adjusted odds ratios for those in the highest quartiles were 0.79 (95 percent confidence interval (CI): 0.59, 1.05) for men and 0.59 (95 percent CI: 0.42, 0.81) for women. The risk reduction was attributed to both moderate and vigorous physical activity but was more profound for women than for men. For obese (BMI ≥30 kg/m2) men and women compared with those whose BMI was 18.5–<25 kg/m2, the respective multivariable-adjusted odds ratios were 1.59 (95 percent CI: 1.18, 2.12) and 1.36 (95 percent CI: 1.00, 1.84). For subjects with a lifetime maximum BMI of ≥30 kg/m2, the odds ratios were 1.55 (95 percent CI: 1.16, 2.06) for men and 1.10 (95 percent CI: 0.83, 1.46) for women. We found an increased odds ratio of 1.95 for men in the highest quartile of calorie intake, but not for women (odds ratio = 1.13).


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TABLE 2. Risk of non-Hodgkin's lymphoma associated with recreational physical activity, body mass index, and energy intake, by sex, National Enhanced Cancer Surveillance System, Canada, 1994–1997

 
We also examined the risks of NHL associated with recreational physical activity (moderate, vigorous, and total), BMI, and calorie intake by NHL histologic subtype (table 3). We observed various degrees of reduction in NHL risk related to total activity for all four subtypes, with a larger effect for follicular, small lymphocytic, and others than for the diffuse type. The obesity-related increase in NHL risk was more profound for diffuse and others types than for follicular and small lymphocytic type. The risk increase associated with excess calorie intake was observed for follicular, small lymphocytic, and others types, with no apparent effect for diffuse type.


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TABLE 3. Risk of non-Hodgkin's lymphoma associated with recreational physical activity, body mass index, and energy intake, by histologic subtype, National Enhanced Cancer Surveillance System, Canada, 1994–1997

 
We then assessed the effect of total recreational physical activity on NHL risk stratified by BMI, by sex (table 4). A decreased NHL risk associated with total activity was restricted to women whose BMI was 18.5–<25 and 25–<30 kg/m2 and to men whose BMI was 18.5–<25 and BMI ≥30 kg/m2.


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TABLE 4. Risk of non-Hodgkin's lymphoma associated with total recreational physical activity, by body mass index and sex, National Enhanced Cancer Surveillance System, Canada, 1994–1997

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Our results indicated that higher levels of recreational physical activity were associated with a reduced risk of NHL for both sexes, with a larger effect for women. This activity-related decrease in risk was attributed to both moderate and vigorous activity. We observed greater reductions in NHL risk associated with recreational physical activity for follicular, small lymphocytic, and others subtypes of NHL tumors. This study also suggested that obese men and women had a significantly increased risk of NHL, and the magnitude of the obesity-related risk increase was greater for diffuse and others subtypes. We also found that excess energy intake increased the risk of NHL for men, and this increase was observed for all four subtypes except diffuse.

Only a few studies have been published on the association between physical activity and NHL risk. To our knowledge, our study is the second that has assessed the relation of physical activity with NHL risk by histologic subtype. The prospective study of Iowa women (14Go) found no age-adjusted association between level of recreational physical activity and NHL risk, overall and by subtype, but a suggestive (nonsignificant) inverse association for follicular subtypes. However, the Iowa study did not assess duration of physical activity. In another cohort study on college alumni (15Go), those who played sports at least 5 hours per week at their colleges had a (nonsignificant) relative risk of 0.67 of developing NHL compared with those who played less or not at all. Two other studies (16Go, 17Go) found no evidence of an association between occupational physical activity and NHL risk; however, as the authors of one of the studies pointed out, the occupation-based measures of physical activity might have introduced nondifferential misclassification, which tends to bias the risk estimates toward unity. The discrepancy between our study and others could be due to the different parameters (e.g., duration, frequency, intensity, and type) of physical activity assessed by different studies, different profiles of the populations, different strategies of adjustment for confounders, or different proportions of histologic subtypes.

Research on the relation of obesity to NHL risk is also scarce, and the results are conflicting. The increased risk of NHL associated with obesity observed in our study is consistent with findings from four other studies (18Go–21Go). A population-based case-control study with 725 cases and 1,566 controls showed elevated risks associated with obesity for NHL and the two major subtypes, diffuse large cell and follicular lymphoma (18Go). In a Swedish hospital-based cohort study of 29,129 persons, women (but not men) with a hospital diagnosis of obesity had an excess risk of NHL when compared with the incidence in the general population (19Go). An elevated risk of NHL associated with a higher ponderal index was also reported in an early cohort study (20Go). Furthermore, in the largest cohort study (404,576 men and 495,477 women), BMI was significantly associated with higher rates of death due to NHL among both men and women (21Go). However, three studies found no association between obesity and NHL risk. The cohort study of Iowa women reported no relation, either overall or by subtype (14Go), and neither did an Italian case-control study (22Go) nor a Danish record-linkage study (23Go).

The underlying mechanisms operative in the association between physical activity and NHL have not been established. One of the plausible mechanisms hypothesized is the exercise-induced increase in antitumor immune defenses (10Go, 11Go). Moderate habitual physical activity may enhance immune function by increasing the number and activity of macrophages, natural killer cells, lymphokine-activated killer cells, and regulating cytokines (31Go–33Go). Experimental studies have demonstrated greater activity of natural killer cells and of lymphokine-activated killer cells in trained or physically active mice, resulting in greater clearance of tumor cells and incidence of tumors (34Go–36Go). Studies in humans have suggested that moderate exercise training has been associated with increases in natural killer cell activity or cell count (37Go–40Go), alterations in lymphocyte subpopulations (41Go, 42Go), changes in interleukin-2 production and interleukin-2 receptor expression (38Go, 39Go), and elevation in immunoglobulin levels (43Go). Because immunodeficiency is a strong risk factor for NHL, physical-activity-related improvement in immune function may play a role in the protective effect of physical activity against developing NHL. Immunotherapy with high-dose interleukin-2 has been shown to successfully treat tumors in animal models (44Go) and cause dramatic tumor regressions in some patients with metastatic melanoma, renal cell carcinoma, and NHL (45Go–47Go). Other hypothesized mechanisms include improving antioxidant defense systems, increasing insulin sensitivity, and decreasing levels of insulin and insulin-like growth factors (10Go, 11Go). Physical activity may also decrease NHL risk through its influence on obesity. The greater risk reduction associated with physical activity among obese men (but not women) observed in our study supports a possible role of physical activity in affecting NHL risk for men through its influence on obesity, and it also suggests that different mechanisms might be involved for men and women regarding the association of recreational physical activity with NHL risk.

The mechanism for the link between NHL risk and obesity is not clear. One proposed hypothesis is the decreased immune response associated with obesity. Studies of immunologic function in obese humans and experimental animals indicate that the excess adiposity is associated with impairments in host defense mechanisms (13Go, 48Go–51Go). Different animal models of obesity have shown a decrease in all T-lymphocyte subsets and the B-cell population as well as lower lymphocyte responsiveness to different mitogens in obese animals compared with lean ones (52Go–55Go). Investigations in humans also suggested a reduced number of subsets of T cells and their functions in obese humans (56Go) or a lower capacity of lymphocytes to proliferate in response to mitogen activation (57Go). Research showed that energy restriction or adequate weight reduction could restore the impaired immune response in overweight rats (58Go) or obese humans (56Go).

One recent population-based case-control study suggested that the involvement of leptin and its receptor in the regulation of immune function might be one of the mechanisms underlying the association between obesity and NHL (18Go). Leptin is a hormone primarily derived from adipocytes that plays an important role in the regulation of food intake, energy expenditure, and the control of body weight (59Go). Leptin's weight-regulating effects are mediated through the binding and activation of its receptor (60Go). The case-control study by Skibola et al. (18Go) found that genetic polymorphisms in the leptin and its receptor genes associated with an obese phenotype were associated with increased risks of NHL, and the authors suggested that genetic interactions between leptin and its receptor might promote the immune dysfunction associated with the pathogenesis of lymphoma.

Another possible mechanism explaining the relation of obesity with NHL risk is the hypothesis that obesity can cause changes in the metabolism of endogenous hormones, including sex steroids, insulin, and insulin-like growth factors, which could distort the normal balance between cell proliferation, differentiation, and apoptosis (61Go).

The stratified analyses by NHL subtype were exploratory, and we cannot explain the difference in association with physical activity, obesity, and energy intake between subtypes. It could be due to subtype misclassification since subtyping was based on cancer registry pathology report rather than review by a panel of pathologists.

Our study used the Working Formulation classification system with a modification for NHL subtyping. In our study, the provincial cancer registry coded NHL by using International Classification of Diseases for Oncology, Second Edition, morphologic classification. We did not use the revised European-American Lymphoma classification because it was proposed in 1994, and cases of NHL in this study were not coded according to this system. We grouped the subtypes into four broader categories because of small numbers of some subtypes.

Some potential limitations of this study deserve consideration. Recall bias is possible among cases regarding their responses to questions on physical activity a few months after their cancer diagnoses. The possibility that such a bias was introduced into this study was reduced by including many questions on other exposures, such as diet, employment history, and residential history, and by not placing any particular emphasis on physical activity in the questionnaire. In our study, the loss of eligible cases because of death, physician's refusal, and nonresponse was probably due to severe illness and could affect the generalization of our results, that is, our results might be generalizable to only less aggressive tumors or healthier subjects.

Histologic subtypes of NHL were diagnosed by pathologists in the respective provinces rather than by a single expert pathologist; therefore, errors regarding histologic subtypes were possible. Several studies assessed the reliability of the Working Formulation classification and found that, although there was a good agreement between reported diagnoses and expert diagnoses (90–98 percent) (62Go–65Go), only 59 percent and 55 percent agreement with subtypes were observed between reported diagnoses from the cancer registry and from expert pathologists, respectively (64Go, 65Go), with a better agreement when grouped into broader categories (e.g., agreement improved to 73 percent for diffuse, 83 percent for follicular, and 74 percent for high-grade type) (65Go). Another limitation is that we could not assess the effect of total physical activity because we did not collect information on occupational physical activity; however, recreational physical activity might be more relevant in Western societies. Self-reported weight could introduce misclassification in exposure of BMI, but the tendency of underreporting of weight by obese people would be nondifferential and tends to attenuate the estimates.

In conclusion, our population-based study showed a reduced NHL risk for men and women engaged in higher levels of recreational physical activity. This activity-related risk decrease was attributed to both moderate and vigorous activity. This study also suggested that obesity and excess energy intake were associated with a significantly increased risk of NHL. Further investigations are warranted to confirm our results, especially the differences between histologic subtypes. Because physical inactivity, obesity, and energy intake are modifiable lifestyle factors, the findings from our study (if confirmed by other studies) may provide a strategy to prevent NHL.


    ACKNOWLEDGMENTS
 
The authors are grateful to Robert Semenciw for his advice on statistical analysis and his insightful comments on the revision of this manuscript.

The Canadian Cancer Registries Epidemiology Research Group comprises a principal investigator from each of the provincial cancer registries involved in the National Enhanced Cancer Surveillance System: Bertha Paulse, Newfoundland Cancer Foundation; Ron Dewar, Nova Scotia Cancer Registry; Dagny Dryer, Prince Edward Island Cancer Registry; Nancy Kreiger, Cancer Care Ontario; Erich Kliewer, CancerCare Manitoba; Diane Robson, Saskatchewan Cancer Foundation; Shirley Fincham, Division of Epidemiology, Prevention and Screening, Alberta Cancer Board; and Nhu Le, British Columbia Cancer Agency.

Conflict of interest: none declared.


    References
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

  1. National Cancer Institute of Canada. Canadian cancer statistics 2003. Toronto, Canada: National Cancer Institute of Canada, 2003.
  2. Ries LA, Eisner MP, Kosary CL, et al, eds. SEER cancer statistics review, 1975–2002. Bethesda, MD: National Cancer Institute, 2002. (http://seer.cancer.gov/csr/1975_2002/).
  3. Vose JM, Chiu BC, Cheson BD, et al. Update on epidemiology and therapeutics for non-Hodgkin's lymphoma. Hematology (Am Soc Hematol Educ Program) 2002:241–62.
  4. Rabkin CS, Ward MH, Manns A, et al. Epidemiology of non-Hodgkin's lymphoma. In: Magrath IT, ed. The non-Hodgkin's lymphomas. 2nd ed. New York, NY: Oxford University Press, 1997:171–86.
  5. Hoover RN. Lymphoma risks in populations with altered immunity—a search for mechanism. Cancer Res 1992;52(suppl):5477S–5478S.
  6. Beral V, Peterman T, Berkelman R, et al. AIDS-associated non-Hodgkin lymphoma. Lancet 1991;337:805–9.[CrossRef][ISI][Medline]
  7. Filipovich AH, Mathur A, Kamat D, et al. Primary immunodeficiencies: genetic risk factors for lymphoma. Cancer Res 1992;52(suppl):5465S–5467S.
  8. Lee IM. Physical activity and cancer prevention—data from epidemiological studies. Med Sci Sports Exerc 2003;35:1823–7.[ISI][Medline]
  9. Weight control and physical activity. IARC handbooks of cancer prevention. Vol 6. Lyon, France: International Agency for Research on Cancer, 2002.
  10. Friedenreich CM, Orenstein MR. Physical activity and cancer prevention: etiologic evidence and biological mechanisms. J Nutr 2002;132:3456S–3464S.[Abstract/Free Full Text]
  11. Westerlind KC. Physical activity and cancer prevention—mechanisms. Med Sci Sports Exerc 2003;35:1834–40.[ISI][Medline]
  12. Kaaks R, Lukanova A. Effects on weight control and physical activity in cancer prevention. Ann N Y Acad Sci 2002;963:268–81.[Abstract/Free Full Text]
  13. Marti A, Marcos A, Martinez JA. Obesity and immune function relationships. Obes Rev 2001;2:131–40.[CrossRef][Medline]
  14. Cerhan JR, Janney CA, Vachon CM, et al. Anthropometric characteristics, physical activity, and risk of non-Hodgkin's lymphoma subtypes and B-cell chronic lymphocytic leukemia: a prospective study. Am J Epidemiol 2002;156:527–35.[Abstract/Free Full Text]
  15. Paffenbarger RS Jr, Lee IM, Wing AL. The influence of physical activity on the incidence of site-specific cancers in college alumni. Adv Exp Med Biol 1992;322:7–15.[Medline]
  16. Zahm SH, Hoffman-Goetz L, Dosemeci M, et al. Occupational physical activity and non-Hodgkin's lymphoma. Med Sci Sports Exerc 1999;31:566–71.[CrossRef][ISI][Medline]
  17. Brownson RC, Chang JC, Davis JR, et al. Physical activity on the job and cancer in Missouri. Am J Public Health 1991;81:639–42.[Abstract]
  18. Skibola CF, Holly EA, Forrest MS, et al. Body mass index, leptin and leptin receptor polymorphisms, and non-Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev 2004;13:779–86.[Abstract/Free Full Text]
  19. Wolk A, Gridley G, Sevensson M, et al. A prospective study of obesity and cancer risk (Sweden). Cancer Causes Control 2001;12:13–21.[CrossRef][ISI][Medline]
  20. Paffenbarger RS Jr, Wing AL, Hyde RT. Characteristics in youth predictive of adult-onset malignant lymphoma, melanomas, and leukemias: brief communication. J Natl Cancer Inst 1978;60:89–92.[ISI][Medline]
  21. Calle EE, Rodriguez C, Walker-Thurmond K, et al. Overweight, obesity, and mortality from cancer in a prospective studied cohort of U.S. adults. N Engl J Med 2003;348:1625–38.[Abstract/Free Full Text]
  22. Franceschi S, Serraino D, Carbone A, et al. Dietary factors and non-Hodgkin's lymphoma: a case-control study in the northeastern part of Italy. Nutr Cancer 1989;12:13–21.
  23. Moller H, Mellemgaard A, Lindvig K, et al. Obesity and cancer risk: a Danish record-linkage study. Eur J Cancer 1994;30A:344–50.[CrossRef]
  24. Groves FD, Linet MS, Travis LB, et al. Cancer surveillance series: non-Hodgkin's lymphoma incidence by histologic subtypes in the United States from 1978 through 1995. J Natl Cancer Inst 2000;92:1240–51.[Abstract/Free Full Text]
  25. Ainsworth BE, Haskell WL, Leon AS, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc 1993;25:71–80.[ISI][Medline]
  26. Ainsworth BE, Haskell WL, Whitt ML, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000;32(suppl):S498–504.[CrossRef][ISI][Medline]
  27. Anshel MH, Freedson P, Hamill J, et al. Dictionary of the sports and exercise sciences. Champaign, IL: Human Kinetics Publishers, 1991.
  28. Pate RR, Pratt M, Blair SN, et al. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995;273:402–7.[Abstract]
  29. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000;894:i–xii, 1–253.[Medline]
  30. Health Canada. Nutrient value of some common foods. Ottawa, Canada: Public Works and Government Services Canada, 1999. (Catalog no. H58-28/1999E).
  31. Shephard RJ, Shek PN. Cancer, immune function, and physical activity. Can J Appl Physiol 1995;20:1–25.[ISI][Medline]
  32. Newsholme EA, Parry-Billings M. Effects of exercise on the immune system. In: Bouchard C, Shephard RJ, Stephens T, eds. Physical activity, fitness, and health: international proceedings consensus statement. Champaign, IL: Human Kinetics, 1994:451.
  33. Woods JA, Davis JM, Smith JA, et al. Exercise and cellular innate immune function. Med Sci Sports Exerc 1999;31:57–66.[CrossRef][ISI][Medline]
  34. MacNeil B, Hoffman-Goetz L. Chronic exercise enhances in vivo and in vitro cytotoxic mechanisms of natural immunity in mice. J Appl Physiol 1993;74:388–95.[Abstract]
  35. Hoffman-Goetz L, May KM, Arumugam Y. Exercise training and mouse mammary tumor metastasis. Anticancer Res 1994;14:2627–32.[ISI][Medline]
  36. Woods JA, Davis JM, Mayer EP, et al. Effects of exercise on macrophage activation for antitumor cytotoxicity. J Appl Physiol 1994;76:2177–85.[Abstract/Free Full Text]
  37. Hoffman-Goetz L. Influence of physical activity and exercise on innate immunity. Nutr Rev 1998;56(1 pt 2):S126–30.[ISI][Medline]
  38. Rhind SG, Shek PN, Shinkai S, et al. Effects of moderate endurance exercise and training on in vitro lymphocyte proliferation, interleukin-2 (IL-2) production, and IL-2 receptor expression. Eur J Appl Physiol Occup Physiol 1996;74:348–60.[CrossRef][ISI][Medline]
  39. Rhind SG, Shek PN, Shinkai S, et al. Differential expression of interleukin-2 receptor alpha and beta chains in relation to natural killer cell subsets and aerobic fitness. Int J Sports Med 1994;15:311–18.[ISI][Medline]
  40. Nieman DC, Nehlsen-Cannarella SL, Markoff PA, et al. The effects of moderate exercise training on natural killer cells and acute upper respiratory tract infections. Int J Sports Med 1990;11:467–73.[ISI][Medline]
  41. Host CR, Norton KI, Olds TS, et al. The effects of altered exercise distribution on lymphocyte subpopulations. Eur J Appl Physiol Occup Physiol 1995;72:157–64.[CrossRef][ISI][Medline]
  42. LaPerriere A, Antoni MH, Ironson G, et al. Effects of aerobic exercise training on lymphocyte subpopulations. Int J Sports Med 1994;15(suppl 3):S127–30.[ISI][Medline]
  43. Nehlsen-Cannarella SL, Nieman DC, Balk-Lamberton AJ, et al. The effects of moderate exercise training on immune response. Med Sci Sports Exerc 1991;23:64–70.[ISI][Medline]
  44. Rosenberg SA, Mule JJ, Spiess PJ, et al. Regression of established pulmonary metastases and subcutaneous tumor mediated by the systemic administration of high-dose recombinant interleukin 2. J Exp Med 1985;161:1169–88.[Abstract/Free Full Text]
  45. Rosenberg SA. Progress in human tumour immunology and immunotherapy. Nature 2001;411:380–4.[CrossRef][ISI][Medline]
  46. Rosenberg SA, Yang JC, White DE, et al. Durability of complete response in patients with metastatic cancer treated with high-dose interleukin-2: identification of the antigens mediating response. Ann Surg 1998;228:307–19.[CrossRef][ISI][Medline]
  47. Rosenberg SA, Lotze MT, Muul LM, et al. Observations on the systemic administration of autologous lymphokine-activated killer cells and recombinant interleukin-2 to patients with metastatic cancer. N Engl J Med 1985;313:1485–92.[Abstract]
  48. Stallone DD. The influence of obesity and its treatment on the immune system. Nutr Rev 1994;52:37–50.[ISI][Medline]
  49. Tanaka S, Inoue S, Isoda F, et al. Impaired immunity in obesity: suppressed but reversible lymphocyte responsiveness. Int J Obes Relat Metab Disord 1993;17:631–6.[Medline]
  50. Weber DJ, Rutala WA, Samsa GP, et al. Impaired immunogenicity of hepatitis B vaccine in obese persons. (Letter). N Engl J Med 1986;314:1393.[ISI][Medline]
  51. Chandra RK, Kutty KM. Immunocompetence in obesity. Acta Paediatr Scand 1980;69:25–30.[ISI][Medline]
  52. Lamas O, Martinez JA, Marti A. T helper lymphopenia and decreased mitogenic response in cafeteria diet-induced obese rats. Nutr Res 2002;22:496–507.
  53. Tanaka S, Isoda F, Kiuchi Y, et al. T lymphopenia in genetically obese-diabetic Wistar fatty rats: effects of body weight reduction on T cells. Metabolism 2000;49:1261–6.[CrossRef][ISI][Medline]
  54. Tanaka S, Isoda F, Yamakawa T, et al. T lymphopenia in genetically obese rats. Clin Immunol Immunopathol 1998;96:219–25.[CrossRef]
  55. Kimura M, Tanaka S, Isoda F, et al. T lymphopenia in obese diabetic (db/db) mice is non-selective and thymus independent. Life Sci 1998;62:1243–50.[CrossRef][ISI][Medline]
  56. Marcos A, Nova E, Montero A. Changes in the immune system are conditioned by nutrition. Eur J Clin Nutr 2003;57(suppl 1):S66–9.[CrossRef][ISI][Medline]
  57. Tanaka S, Isoda F, Ishihara Y, et al. T lymphopaenia in relation to body mass index and TNF-alpha in human obesity: adequate weight reduction can be corrective. Clin Endocrinol 2001;54:347–54.[CrossRef][ISI][Medline]
  58. Lamas O, Martinez JA, Marti A. Energy restriction restores the impaired immune response in overweight (cafeteria) rats. J Nutr Biochem 2004;15:418–25.[CrossRef][ISI][Medline]
  59. Matarese G, Sanna V, Fontana S, et al. Leptin as a novel therapeutic target for immune intervention. Curr Drug Targets Inflamm Allergy 2002;1:13–22.[CrossRef][Medline]
  60. Yiannakouris N, Yannakoulia M, Melistas L, et al. The Q223R polymorphism of the leptin receptor gene is significantly associated with obesity and predicts a small percentage of body weight and body composition variability. J Clin Endocrinol Metab 2001;86:4434–9.[Abstract/Free Full Text]
  61. Bianchini F, Kaaks R, Vainio H. Overweight, obesity and cancer risk. Lancet Oncol 2002;3:565–74.[CrossRef][ISI][Medline]
  62. A clinical evaluation of the International Lymphoma Study Group classification of non-Hodgkin's lymphoma. The Non-Hodgkin's Lymphoma Classification Project. Blood 1997;89:3909–18.[Abstract/Free Full Text]
  63. Classification of non-Hodgkin's lymphomas. Reproducibility of major classification systems. NCI non-Hodgkin's Classification Project Writing Committee. Cancer 1985;55:91–5.[ISI][Medline]
  64. Dick F, VanLier S, Banks P, et al. Use of the working formulation for non-Hodgkin's lymphoma in epidemiologic studies: agreement between reported diagnoses and a panel of experienced pathologists. J Natl Cancer Inst 1987;78:1137–44.[ISI][Medline]
  65. Clarke CA, Glaser SL, Dorfman RF, et al. Expert review of non-Hodgkin's lymphomas in a population-based cancer registry: reliability of diagnosis and subtype classifications. Cancer Epidemiol Biomarkers Prev 2004;13:138–43.[Abstract/Free Full Text]




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