Recreational physical activity, leisure sitting time and risk of non-Hodgkin lymphoid neoplasms in the American Cancer Society Cancer Prevention Study II Cohort



Results of studies that examined the relationship between physical activity and non-Hodgkin lymphoid neoplasms (NHL) are inconsistent, and only one study to date examined time spent sitting in relation to NHL. We examined recreational physical activity and leisure-time sitting in relation to risk of NHL in the American Cancer Society Cancer Prevention Study II Nutrition Cohort. Between 1992 and 2007, 2,002 incident cases were identified among 146,850 participants who were cancer-free at enrollment. Cox proportional hazards regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) while adjusting for potential confounders. Women who sat for at least 6 hr/day were at 28% higher risk of NHL compared to women who sat for fewer than 3 hr/day. In analyses of specific subtypes, sitting time was associated with risk of multiple myeloma only (6+ vs. 3 hr/day sitting: HR = 2.40, 95% CI: 1.45–3.97). Women who engaged in any recreational physical activity had a nonsignificant 20%–30% lower risk of NHL (p-trend = 0.05) compared to women who reported no recreational physical activity. Neither leisure-time sitting nor recreational physical activity was associated with risk of NHL or major NHL subtype in men. There was no evidence of statistical interaction between physical activity and sitting time, or between body mass index and physical activity or sitting time. Further research is needed to confirm an association between sitting time and multiple myeloma and explore a possible association between physical activity and NHL.

Non-Hodgkin lymphoid neoplasms (NHL), including multiple myeloma and chronic lymphocytic leukemia, account for > 6% of new cancer diagnoses1 and include heterogeneous subtypes that may have varied etiologies.2 Risk factors for NHL vary by subtype, but the strongest known risk factors for several types of NHL involve altered immune function or infection.3

Physical activity is associated with risk of several cancers4 and modulation of immune function is one hypothesized mechanism underlying these associations.5, 6 However, results of studies that examined the relationship between physical activity and NHL are inconsistent7, 8 Sedentary behavior, a distinct class of behavior imparting independent effects on disease risk,9 has been associated with several cancers independent of physical activity.10 To our knowledge, only one study (case–control design) examined time spent sitting in relation to NHL.11 That study was limited to the use of a job title rather than a specific measure of time spent sitting and did not report associations for specific histologic subtypes of NHL.

In the American Cancer Society Cancer Prevention Study II (CPS-II) Nutrition Cohort—a large, prospective study with more than 2,000 cases of NHL—we examined both reported recreational physical activity and reported hours of leisure-time sitting in relation to risk of NHL in aggregate and common individual subtypes.

Material and Methods

Study population

Men and women in this analysis were drawn from the 184,190 participants in the CPS-II Nutrition Cohort, a prospective study of cancer incidence and mortality established by the American Cancer Society in 1992 as a subgroup of the larger 1982 CPS-II mortality cohort.12 Most participants were aged 50–74 years at enrollment in 1992. At baseline, they completed a ten-page self-administered questionnaire that included questions on demographic, medical, behavioral, environmental and dietary factors. Beginning in 1997, follow-up questionnaires were sent to cohort members every 2 years to update exposure information and ascertain newly diagnosed cancers. All follow-up questionnaire response rates (after multiple mailings) among living cohort members are at least 88%. End of follow-up for our analysis was June 30, 2007.

We excluded 6,261 men and women who were lost to follow-up (i.e., alive at the first follow-up questionnaire in 1997 but did not return the 1997 or any subsequent follow-up questionnaire), who reported prevalent cancer (except nonmelanoma skin cancer) at baseline (n = 22,863), or whose self-reported lymphoid cancer on the first (1997) follow-up questionnaire could not be verified through medical or cancer registry records or had an unknown diagnosis date (n = 49). Finally, we excluded individuals with missing (n = 2,305) or extreme (top or bottom 0.1%) body mass index (BMI) (n = 282) or missing sitting time (n = 3,339) or physical activity information (n = 2,241). After all exclusions, the final analytic cohort consisted of 146,850 men and women who were aged 62.9 years on average ( equation image 6.4 SD) when enrolled in the study. Men and women who self-reported a lymphoid cancer in 1999 or later that could not be verified were censored at the date of their last cancer-free survey.

Case ascertainment

This analysis included 2,002 verified incident cases of NHL diagnosed between the date of enrollment and June 30, 2007. Of these, 1,622 NHL cases were identified initially by self-report on a follow-up questionnaire and subsequently verified from medical records (n = 1,227) or linkage with state cancer registries (n = 395). A previous study linking cohort participants with state cancer registries has shown that the Nutrition Cohort participants are highly accurate (93% sensitivity) in reporting cancer diagnoses.13 An additional 47 cases were reported by participants as another type of cancer but were found to be NHL on examination of medical or registry records. Finally, 333 incident cases were identified as interval deaths through biennial automated linkage of the entire cohort with the National Death Index and subsequently verified through linkage with state cancer registries.

NHL subtypes were defined using the classification guidelines created by the International Lymphoma Epidemiology Consortium (InterLymph) Pathology Working Group.14 These guidelines were based on the 2008-revised WHO classification of tumors of hematopoietic and lymphoid tissues15 and were designed to facilitate epidemiologic studies that include cases diagnosed in different years and, therefore, using different coding guidelines. In addition, the InterLymph classifications were put forth to provide guidance in grouping hematologic malignancies when sample size does not allow individual analyses of the over 40 lymphoma subtypes defined by WHO. Based on these recommendations, we used histology codes from the International Classification of Disease for Oncology, Second and Third Editions to group NHL into the following subtypes: diffuse large B-cell lymphoma (DLBCL; n = 435), follicular lymphoma (N = 280), chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL; n = 482), multiple myeloma (n = 343), other B-cell lymphoid neoplasms (B-NHL; n = 326), T-cell lymphoid neoplasms (T-NHL; n = 110) and NHL not otherwise specified (n = 26).

Measures of physical activity and sitting time

Baseline information on recreational physical activity was collected using the question “During the past year, what was the average time/week you spent at the following kinds of activities: walking, jogging/running, lap swimming, tennis or racquetball, bicycling or stationary biking, aerobics/calisthenics, and dancing?” Response to each activity included “none,” “1–3 hr/week,” “4–6 hr/week” or “7+ hr/week.” Summary MET-hr/week were calculated for each participant. A MET, or metabolic equivalent, is the ratio of the metabolic rate during a specific activity to resting metabolic rate.16 Due to the older age of this population, the summary MET score for each participant was calculated by multiplying the lowest number of hours within each category times the moderate intensity MET score for each activity according to the Compendium of Physical Activities16 to provide conservatively estimated summary measures. The MET scores for various activities were as follows: 3.5 for walking, 7.0 for jogging/running, 7.0 for lap swimming, 6.0 for tennis or racquetball, 4.0 for bicycling/stationary biking, 4.5 for aerobics/calisthenics and 3.5 for dancing. Recreational physical activity at baseline was categorized in MET-hr/week as none, >0–<7, 7–<17.5 or ≥17.5. For reference, 17.5 MET-hr/week corresponds to ∼1 hr of moderate-paced walking (3.0 mph) 5 days/week. In addition to recreational leisure activity at baseline, nonrecreational leisure activity was also examined based on information collected from the question: “During the past year, what was the average time/week you spent at the following kinds of activities: gardening/mowing/planting, heavy housework/vacuuming, heavy home repair/painting, and shopping?” The above algorithm was used to calculate MET-hr/week using the following values for each activity16: 3.0 for gardening/mowing/planting, 2.5 for heavy housework/vacuuming, 3.0 for heavy home repair/painting and 2.5 for shopping. Although physical activity information was reported on follow-up questionnaires, response categories were different from those on the baseline questionnaire. Thus, we only present physical activity at baseline in our analysis. However, a qualitative comparison of the baseline and follow-up physical activity information showed that most study participants remained in the same relative quartile of physical activity across follow-up cycles (data not shown).

Leisure-time spent sitting was assessed with the baseline survey question: “During the past year, on an average day, (not counting time spent at your job) how many hours/day did you spend sitting (watching TV, reading, etc.)?” Responses included “none, less than 3, 3–5, 6–8, more than 8 hr/day.” Due to small numbers in some categories, these responses were collapsed into the following categories for analyses: zero to less than three, three to less than five and six or more hr/day of leisure-time sitting.

Statistical analysis

Cox proportional hazards regression17 was used to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the relationships of recreational physical activity and time spent sitting with risk of NHL and NHL subtypes (DLBCL, follicular lymphoma, CLL/SLL, multiple myeloma, other B-NHL and T-NHL). Statistical Analysis Software (SAS) version 9.2 was used for all analyses. For each exposure variable, risk was assessed in both an age-only adjusted model and a multivariable model. All Cox models were stratified on exact year of age at enrollment and follow-up time in days was used as the time-axis.

Potential confounders included in the multivariable models were selected because they were known or suspected to be associated with both lymphoid neoplasms and our exposure variables. These covariates included family history of hematopoietic cancers (yes/no), alcohol intake at baseline (nondrinker, <1 drink/day, 1–2 drinks/day, >2 drinks/day, missing), education (less than high school graduate, high school graduate, some college or technical school, college graduate or higher, missing), smoking status (never, current, former, ever unknown status, missing), BMI (<18.5, 18.5–<25, 25–<30, 30+ kg/m2) and height (quintiles).

Likelihood ratio tests were used to evaluate multiplicative statistical interaction between our exposures of interest (physical activity and sitting time), as well as the exposures and sex and the exposures and BMI. Models with multiplicative interaction terms for each of the potential effect modifiers were compared to models with no interaction terms and a p-value < 0.05 was considered statistically significant. In addition, interaction terms between the exposure variables and time were also created to test for any violation of the Cox proportional hazards assumption; no violations were observed. Finally, we conducted a sensitivity analysis to evaluate the role of reverse causation by excluding the first 3 years of follow-up.


Approximately 12% of men and 9% of women reported no recreational physical activity at baseline. Among men and women who reported any recreational physical activity at baseline, the median MET expenditure was 14.0 and 9.5 MET-hr/week, respectively. Compared to inactive participants, physically active participants were slightly older and less likely to be obese, more likely to have higher educational attainment and more likely to be nonsmokers (Table 1).

Table 1. Baseline characteristics of men and women in the CPS-II Nutrition Cohort by recreational physical activity and leisure sitting time
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Fourteen percent of men and 10% of women reported sitting at least 6 hr/day during their leisure time. On average, BMI was similar across different sitting time categories in men but slightly higher in women who sat the longest. Participants who reported the most sitting were more likely to be current smokers and drinkers compared to those who sat less. Although men and women who engaged in no recreational physical activity were the most likely to sit ≥ 6 hr/day (Table 1), there was no statistical correlation between leisure-time sitting and recreational physical activity (r = −0.03).

In women, those who reported even low levels of regular recreational physical activity at baseline seemed to have a modest 20%–30% reduction in risk of lymphoid neoplasms compared to women who reported no recreational physical activity, with a trend of borderline statistical significance (p-trend = 0.05; Table 2). This association remained virtually unchanged when plasma cell neoplasms were excluded from the analysis for better comparison to earlier NHL studies. However, in subtype analyses, the strongest association was observed for multiple myeloma. Women who reported ≥ 17.5 MET-hr/week of recreational physical activity had a 48% lower risk of multiple myeloma (95% CI: 0.27–1.00; p-trend = 0.08) compared to women who reported no recreational physical activity. Nonsignificant associations of a similar magnitude to those observed for all NHL were also suggested for DLBCL, CLL/SLL and follicular lymphoma in women (Table 2). Baseline recreational physical activity was not associated with risk of other B-NHLs or T-NHL in women (data not shown). In men, recreational physical activity did not seem to predict risk of NHL in aggregate or in any NHL subtype (Table 3). Although the associations of recreational physical activity with NHL seemed to differ in women and men, we did not observe a statistically significant interaction of physical activity with sex (p-value = 0.22). In addition, nonrecreational leisure activities (e.g., gardening, shopping or housework) were not associated with risk of NHL in women (p-trend = 0.95) or men (p-trend = 0.24). Furthermore, these activities did not confound or modify the associations between recreational physical activity and NHL (data not shown). Although these activities comprise a large part of the total activity among older men and women, they may not be vigorous enough to cause a physiologic response.

Table 2. Hazard ratios of non-Hodgkin lymphoid neoplasms according to leisure-time sitting and physical activity among women in the Cancer Prevention Study II Nutrition Cohort, 1992–2007
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Table 3. Hazard ratios of non-Hodgkin lymphoid neoplasms according to leisure-time sitting and physical activity among men in the Cancer Prevention Study II Nutrition Cohort, 1992–2007
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Leisure-time sitting was positively associated with risk of all NHL in women (p-trend = 0.008; Table 2), and risk was nearly 30% higher for those who reported sitting for ≥ 6 hr/day compared to those who sat for < 3 hr. However, in analyses that excluded plasma cell neoplasms, sitting time was no longer associated with NHL (6+ vs. <3 hr/day of sitting: HR = 1.12 (95% CI: 0.87–1.45)). Accordingly, in analyses of specific NHL subtypes, we observed a significant positive association of leisure-time sitting with multiple myeloma (p-trend = 0.0012), including a strong and statistically significant more than twofold increase in multiple myeloma risk among women who reported ≥ 6 hr/day of sitting (compared to <3 hr/day). HR for follicular lymphoma were modestly elevated but were not statistically significant (p-trend = 0.10); no other subtype-specific associations were apparent. We did not observe an association of leisure-time sitting with all NHL or any NHL subtype in men (Table 3), and the heterogeneity of the findings by sex was statistically significant (p-interaction = 0.02). Mutual adjustment for recreational physical activity and leisure-time sitting did not change the results.

Finally, there was no evidence of statistical interaction between physical activity and sitting time, or between BMI and physical activity or sitting time; nor was there evidence of reverse causation from our sensitivity analyses excluding the first 3 years of follow-up.


In this large, prospective cohort, time spent sitting was associated with an increased incidence of NHL, particularly multiple myeloma, in women. Women who sat for > 6 hr/day were more than twice as likely to develop multiple myeloma as those who sat for < 3 hr/day of leisure time. A nonsignificant increased risk was also observed for follicular lymphoma but not for the other NHL subtypes examined in our study. There was no association between sitting time and any lymphoid neoplasm that we examined in men. There was a nonsignificant inverse association between recreational physical activity and risk of all NHL and in multiple myeloma in women but no evidence of associations in men.

Most other published studies did not report an association of recreational physical activity with NHL.8, 11, 18–20 However, most NHL studies did not include multiple myeloma, the subgroup where we observed the strongest suggestion of an association with physical activity. Three population-based case-control studies found no association between either occupational8, 11, 18 or recreational8 physical activity and NHL or common NHL subtypes. Two additional case-control studies reported an inverse trend between physical activity and NHL,21, 22 but in one of the studies,22 the trend was no longer statistically significant after adjustment for BMI and height. Findings from case-control studies on this topic may be biased due to potential changes in physical activity before diagnosis and/or differential recall of activity between cases and controls. No associations were found in three prospective cohort studies19, 20, 23 (with 324, 574 and 778 cases, respectively) that assessed the association between recreational physical activity and risk of NHL and NHL subtypes. In contrast, although very little has been published on the independent association between physical activity and multiple myeloma, two cohort studies suggest an association. A Japanese cohort study found that people who walked < 30 min/day were twice as likely to die from multiple myeloma as those who walked > 1 hr/day.24 And participants in the Nurses' Health Study and Health Professionals Follow-up Study cohorts who reported more than minimal levels of regular physical activity had a nonsignificantly diminished risk of multiple myeloma that was comparable in magnitude to the suggestive associations observed in our study.25

For sitting time, our results showed a statistically significant association with multiple myeloma but no other lymphoid neoplasms. In sensitivity analyses excluding plasma cell neoplasms, sitting time was no longer associated with NHL. Therefore, our results agree with the only other study on sitting time and NHL, which did not include multiple myelomas and found no association between sitting time and NHL.11

Our finding of an association between sitting time and NHL is supported by studies that reported independent health effects of sitting time.10, 26, 27 Even among highly physically active individuals, time spent sitting has been associated with cardiometabolic biomarker levels,26, 28 cancer10 and total mortality.27 However, the mechanisms by which longer time spent sitting increases risk of multiple myeloma are unclear. This relationship may be mediated through obesity, which has been associated with risk of NHL in several studies.21, 29–35 In our study, the association between longer sitting time and increased risk of multiple myeloma was independent of BMI. Sitting time has also been hypothesized to directly influence inflammation and sex hormones10 both of which have been shown to affect immune function and possibly lymphomagenesis.36–38 In support of a possible role of sex hormones, our finding of a statistically significant association between sitting time and multiple myeloma was limited to women. There was also a nonsignificant positive association with follicular lymphoma in women. Reasons for a possible sex difference are unclear and might be due to chance as there were only 24 female cases of multiple myeloma in the highest exposed group. However, it is interesting to note that studies of cardiometabolic biomarkers39–42 and mortality27 also show stronger associations of sitting time in women than in men.

Strengths of our study include the prospective design which eliminated the possibility of recall bias and minimized the likelihood that reverse causation played a role in the results. An additional strength is the ability to control for a variety of known or suspected NHL risk factors, and the relatively homogenous characteristics of individuals in our study reduced the likelihood of residual confounding by unknown factors. One limitation is that no information was collected on intensity for each type of physical activity, thus increasing the likelihood of misclassifying energy expenditure. Although the physical activity questions on our baseline questionnaire were not validated and are subject to misreporting, they are very similar to those used and validated in another prospective study.43 In that study, Wolf et al. found strong correlations between activity reported on past-week activity recalls or 7-day diaries and activity reported on the questionnaire (0.79 and 0.62, respectively). In addition, lower risks of breast and colon cancer were associated with high levels of activity in the CPS-II Nutrition Cohort.44, 45 Another possible limitation is that the sedentary activity questions are limited to time spent sitting outside of the workplace. However, as the majority of the participants in this analysis (65% in 1992) are retired or do no work outside the home, workplace sitting is an unlikely source of bias. However, to explore this potential source of bias further we conducted sensitivity analyses examining the associations between employment status (employed/not employed/unknown) and NHL as a main effect and as a potential confounder of our exposures. Being employed was only associated with DLBCL in men but neither sitting nor physical activity was associated with DLBCL in men (with or without employment status in the model). All our reported results remained unchanged. As the CPS-II population ages throughout follow-up, the percentage of participants that were not employed undoubtedly increased. And as unemployed persons have more opportunity for leisure-time sitting, our estimates of the proportion of the cohort that sat ≥ 6 hr/day for leisure is likely an increasingly large underestimate throughout follow-up. However, we expect this source of misclassification to bias toward the null, which would suggest that the true association may in fact be stronger than what we observed.

Finally, although the overall number of lymphoid neoplasms was large, statistical power was limited in the subtype-specific analyses, particularly for the less common subtypes. Because the etiologies of individual types of lymphoma are likely to include some common but also some distinct risk factors, further studies in pooled prospective cohorts are needed to properly evaluate the association of these potentially modifiable risk factors with specific histologic types of lymphoma.

As time spent watching television, playing video games and using computers increases, the public health relevance of the health consequences of inactive time (both sitting and lack of physical activity) becomes increasingly important. Further studies are needed to confirm our finding of an association between sitting time and NHL, particularly multiple myeloma, and to explore the possible association with recreational physical activity, the possible sex differences in these findings and the biologic pathways that underlie them.


The authors thank the American Cancer Society (ACS) Cancer Prevention Study II (CPS-II) participants and Study Management Group for their invaluable contributions to this research. ACS funds the creation, maintenance, and updating of the CPS-II cohort.