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Medical History, Lifestyle, Family History, and Occupational Risk Factors for Follicular Lymphoma: The InterLymph Non-Hodgkin Lymphoma Subtypes Project

Medical History, Lifestyle, Family History, and Occupational Risk Factors for Follicular... Abstract Background Follicular lymphoma (FL) has been linked with cigarette smoking and, inconsistently, with other risk factors. Methods We assessed associations of medical, hormonal, family history, lifestyle, and occupational factors with FL risk in 3530 cases and 22639 controls from 19 case–control studies in the InterLymph consortium. Age-, race/ethnicity-, sex- and study-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression. Results Most risk factors that were evaluated showed no association, except for a few modest or sex-specific relationships. FL risk was increased in persons: with a first-degree relative with non-Hodgkin lymphoma (OR = 1.99; 95% CI = 1.55 to 2.54); with greater body mass index as a young adult (OR = 1.15; 95% CI = 1.04 to 1.27 per 5kg/m2 increase); who worked as spray painters (OR = 2.66; 95% CI = 1.36 to 5.24); and among women with Sjögren syndrome (OR = 3.37; 95% CI = 1.23 to 9.19). Lower FL risks were observed in persons: with asthma, hay fever, and food allergy (ORs = 0.79–0.85); blood transfusions (OR = 0.78; 95% CI = 0.68 to 0.89); high recreational sun exposure (OR = 0.74; 95% CI = 0.65 to 0.86, fourth vs first quartile); who worked as bakers or millers (OR = 0.51; 95% CI = 0.28 to 0.93) or university/higher education teachers (OR = 0.58; 95% CI = 0.41 to 0.83). Elevated risks specific to women included current and longer duration of cigarette use, whereas reduced risks included current alcohol use, hay fever, and food allergies. Other factors, including other autoimmune diseases, eczema, hepatitis C virus seropositivity, hormonal drugs, hair dye use, sun exposure, and farming, were not associated with FL risk. Conclusions The few relationships observed provide clues suggesting a multifactorial etiology of FL but are limited in the extent to which they explain FL occurrence. Follicular lymphoma (FL), the second most common form of lymphoma in the United States and western Europe, is a lymphoproliferative disorder of germinal center B cells (1). The US age-adjusted incidence rate for FL during 1992–2001 was 3.18 per 100000, with a 3.6-fold variation between the highest and lowest rates (in white males and American Indian/Alaska Native males, respectively) (2) and a 2.8-fold variation in rates among Asian Americans of different origins (3). Age-adjusted FL rates are slightly higher in males than in females. Most patients present with indolent disease, although 2%–3% of FL cases transform annually to diffuse large B-cell lymphoma (4). Few epidemiologic studies published before 2004 evaluated risk factors separately for subtypes of non-Hodgkin lymphoma (NHL) based on the Revised European-American Lymphoma (REAL)/ World Health Organization (WHO) classification (5–10). Subsequently, an expanding literature has examined risk factors for the common NHL subtypes, although most of these studies have assessed specific or related categories of exposure but did not evaluate risks across a broad range of exposures. Cigarette smoking has repeatedly been associated with a higher risk of FL (11–13), and some reports, including previous InterLymph pooled analyses, have linked excess risk of FL with Sjögren syndrome (14), blood transfusions (15), family history of hematopoietic malignancies (16,17), hair dyes (18,19), and greater height (20). A few reports have linked occupational exposure to benzene, oils/greases, and other solvents such as styrene and trichloroethylene with increased risks of FL (9,21–23). Reduced risks of FL have been linked with atopic disorders (24), oral contraceptive use (25), alcohol consumption (26,27), and sun exposure (28–30). We have pooled data from 19 case–control studies conducted in Europe, North America, and Australia to examine associations between medical and family history, lifestyle, hormonal drugs, and occupation. The broad range of risk factors available provided an opportunity to assess multivariate associations, and the large study size, 3530 FL cases and 22639 controls, provided an opportunity to examine relatively rare exposures and weak associations overall and in subgroups defined by sex, race/ethnicity, region, and source of controls. Methods Study Population Detailed methodology for the InterLymph NHL Subtypes Project is provided elsewhere in this issue. Studies eligible for inclusion in this pooled analysis were case–control studies, with incident, histologically confirmed cases of FL defined according to the WHO classification (31,32); each study collected individual-level data for at least several risk factors of interest and these were submitted to the pooling project by December 31, 2011. Most studies excluded individuals with a known history of solid organ transplantation or HIV/AIDS. Contributing studies were approved by local ethics review committees, and all participants provided written, informed consent prior to participation. Risk Factors and NHL Subtype Ascertainment and Harmonization Each study collected data on potential NHL risk factors in a standardized, structured format by in-person or telephone interviews, and/or self-administered questionnaires. Risk factors included were those where data were available from at least four studies. Each variable was harmonized individually, then related exposure variables were reviewed for consistency as detailed elsewhere (33). Cases were classified according to the WHO classification (31,32) using guidelines from the InterLymph Pathology Working Group (34,35). Statistical Analysis Risk of FL associated with each exposure variable was evaluated using logistic regression models, adjusting for age, race/ethnicity, sex, and study in a basic adjusted model. The significance of each association was evaluated by a likelihood ratio test, comparing models with and without the exposure variable of interest, with P values less than 0.05 identifying putatively influential factors. To quantify the magnitude of the association, we estimated the relative risk using odds ratios (ORs) and 95% confidence intervals (CIs) derived from the logistic regression models. Individuals with missing data for a variable of interest were excluded. To evaluate effect heterogeneity among the studies, we performed a separate logistic regression within each study and then quantified the variability of the coefficients by the H statistic, adapting the definition by Higgins and Thompson to categorical variables (36). To consider possible effect modification, we repeated the above logistic regression analyses but stratified individuals by age, sex, race/ethnicity, region (ie, North America vs Europe vs Australia), study design (ie, population-based vs hospital-based), or other putative risk factors identified in the analysis. To assess confounding, we first evaluated the risk estimate for each putative risk factor in a series of models that adjusted for one other putative risk factor individually in addition to the basic adjusted model. Next, we conducted a single logistic regression model including all putative risk factors, this time including a separate missing category for each variable to ensure that the entire study population was included in the analysis. Finally, we conducted a forward step-wise logistic regression with all putative risk factors, adjusting for age, sex, race/ethnicity, and study. Results from this series of multivariate adjusted logistic regression models showed little difference from the findings based on the basic adjusted models (ie, adjusted for age, sex, race/ethnicity, and study). We therefore report the results for the basic adjusted models only. Because controls for most original studies were frequency matched by age and sex to all cases, we conducted sensitivity analyses using a subset of controls individually matched by age and sex to the FL cases. The results were similar to those using the full set of controls and, thus, we retained all controls for the main analyses to increase statistical power. Results The median age was similar for FL cases at diagnosis (median: 58 years, range: 18–91 years) and controls at the time of interview (median: 59 years, range: 16–98 years). FL cases were more likely to be female, but FL cases and controls were similar by race/ethnicity (with >90% non-Hispanic whites) and socioeconomic status (Table 1). Most cases and controls were from North America or northern Europe and from population-based studies. Table 1. Descriptive characteristics of follicular lymphoma cases and controls     Controls  Cases      No. (%)  No. (%)  Total  22639 (86.5)  3530 (13.5)  Age at diagnosis/interview, y   <30  1356 (6.0)  38 (1.1)   30–39  2143 (9.5)  253 (7.2)   40–49  3090 (13.6)  655 (18.6)   50–59  4870 (21.5)  1003 (28.4)   60–69  6277 (27.7)  1011 (28.6)   70–79  4048 (17.9)  508 (14.4)   ≥80  839 (3.7)  58 (1.6)   Missing  16 (0.1)  4 (0.1)  Sex   Male  13228 (58.4)  1785 (50.6)   Female  9411 (41.6)  1745 (49.4)  Race   White non-Hispanic  21145 (93.4)  3231 (91.5)   Black  351 (1.6)  37 (1.0)   Asian  321 (1.4)  70 (2.0)   Hispanic  334 (1.5)  59 (1.7)   Other/unknown/missing  488 (2.2)  133 (3.8)  Socioeconomic status   Low  9266 (40.9)  1384 (39.2)   Medium  6577 (29.1)  1061 (30.1)   High  6386 (28.2)  1019 (28.9)   Other/missing  410 (1.8)  66 (1.9)  Region   North America  11005 (48.6)  1854 (52.5)   Northern Europe  6542 (28.9)  1100 (31.2)   Southern Europe  4398 (19.4)  324 (9.2)   Australia  694 (3.1)  252 (7.1)  Study design   Population-based  17389 (76.8)  2908 (82.4)   Hospital-based  5250 (23.2)  622 (17.6)      Controls  Cases      No. (%)  No. (%)  Total  22639 (86.5)  3530 (13.5)  Age at diagnosis/interview, y   <30  1356 (6.0)  38 (1.1)   30–39  2143 (9.5)  253 (7.2)   40–49  3090 (13.6)  655 (18.6)   50–59  4870 (21.5)  1003 (28.4)   60–69  6277 (27.7)  1011 (28.6)   70–79  4048 (17.9)  508 (14.4)   ≥80  839 (3.7)  58 (1.6)   Missing  16 (0.1)  4 (0.1)  Sex   Male  13228 (58.4)  1785 (50.6)   Female  9411 (41.6)  1745 (49.4)  Race   White non-Hispanic  21145 (93.4)  3231 (91.5)   Black  351 (1.6)  37 (1.0)   Asian  321 (1.4)  70 (2.0)   Hispanic  334 (1.5)  59 (1.7)   Other/unknown/missing  488 (2.2)  133 (3.8)  Socioeconomic status   Low  9266 (40.9)  1384 (39.2)   Medium  6577 (29.1)  1061 (30.1)   High  6386 (28.2)  1019 (28.9)   Other/missing  410 (1.8)  66 (1.9)  Region   North America  11005 (48.6)  1854 (52.5)   Northern Europe  6542 (28.9)  1100 (31.2)   Southern Europe  4398 (19.4)  324 (9.2)   Australia  694 (3.1)  252 (7.1)  Study design   Population-based  17389 (76.8)  2908 (82.4)   Hospital-based  5250 (23.2)  622 (17.6)  View Large Medical Conditions and Treatments Overall, participants with a history of autoimmune diseases involving B-cell or T-cell activation were not at an increased risk of FL, except for those with Sjögren syndrome (Table 2). History of any atopic condition (OR = 0.87; 95% CI = 0.80 to 0.94) or any specific allergies (ORs ranged from 0.82 to 0.88), but not eczema, was associated with a reduced risk of FL (Table 2). Hay fever and food allergy were associated with significantly reduced FL risk in females but not males (P heterogeneity = .01 and .04, respectively; Table 3). Table 2. Autoimmune and allergic disorders and risk of follicular lymphoma*   Controls†  Cases†      No. (%)  No. (%)  OR (95% CI)‡  P  History of autoimmune conditions   History of autoimmune disease   No autoimmune disease  19423 (95.9)  3242 (95.8)  1.00 (referent)  .358   B-cell activation  157 (0.8)  39 (1.2)  1.26 (0.88 to 1.81)     T-cell activation  664 (3.3)  100 (3.0)  0.88 (0.71 to 1.10)     Both  15 (0.1)  4 (0.1)  1.40 (0.45 to 4.32)     Sjögren syndrome   No  6917 (97.2)  1487 (96.6)  1.00 (referent)  .024   Yes  9 (0.1)  7 (0.5)  3.37 (1.23 to 9.19)     Systematic lupus erythematosus   No  15987 (98.6)  2807 (98.0)  1.00 (referent)  .104   Yes  33 (0.2)  12 (0.4)  1.81 (0.91 to 3.60)     Inflammatory bowel disorder   No  16231 (97.6)  2620 (97.2)  1.00 (referent)  .349   Yes  199 (1.2)  29 (1.1)  0.83 (0.56 to 1.24)     Celiac disease   No  8907 (99.4)  1459 (98.8)  1.00 (referent)  .632   Yes  25 (0.3)  7 (0.5)  1.24 (0.52 to 2.96)     Type I diabetes   No  13185 (95.9)  1861 (92.0)  1.00 (referent)  .982   Yes  84 (0.6)  14 (0.7)  0.99 (0.55 to 1.80)    Atopic disorders   Any atopic disorder§   No  15601 (68.9)  2345 (66.4)  1.00 (referent)  <.001   Yes  6442 (28.5)  1107 (31.4)  0.87 (0.80 to 0.94)     Allergy∥   No  10790 (72.1)  1903 (70.0)  1.00 (referent)  .018   Yes  3309 (22.1)  590 (21.7)  0.88 (0.79 to 0.98)     Food allergy   No  12757 (85.2)  2180 (80.1)  1.00 (referent)  .007   Yes  988 (6.6)  171 (6.3)  0.79 (0.67 to 0.94)     Asthma   No  18448 (85.6)  2894 (83.9)  1.00 (referent)  .018   Yes  1698 (7.9)  260 (7.5)  0.85 (0.74 to 0.97)     Hay fever   No  12467 (71.3)  2086 (69.3)  1.00 (referent)  <.001   Yes  2958 (16.9)  521 (17.3)  0.82 (0.73 to 0.91)     Eczema   No  14766 (86.1)  2452 (82.4)  1.00 (referent)  .283   Yes  1605 (9.4)  318 (10.7)  1.08 (0.94 to 1.23)      Controls†  Cases†      No. (%)  No. (%)  OR (95% CI)‡  P  History of autoimmune conditions   History of autoimmune disease   No autoimmune disease  19423 (95.9)  3242 (95.8)  1.00 (referent)  .358   B-cell activation  157 (0.8)  39 (1.2)  1.26 (0.88 to 1.81)     T-cell activation  664 (3.3)  100 (3.0)  0.88 (0.71 to 1.10)     Both  15 (0.1)  4 (0.1)  1.40 (0.45 to 4.32)     Sjögren syndrome   No  6917 (97.2)  1487 (96.6)  1.00 (referent)  .024   Yes  9 (0.1)  7 (0.5)  3.37 (1.23 to 9.19)     Systematic lupus erythematosus   No  15987 (98.6)  2807 (98.0)  1.00 (referent)  .104   Yes  33 (0.2)  12 (0.4)  1.81 (0.91 to 3.60)     Inflammatory bowel disorder   No  16231 (97.6)  2620 (97.2)  1.00 (referent)  .349   Yes  199 (1.2)  29 (1.1)  0.83 (0.56 to 1.24)     Celiac disease   No  8907 (99.4)  1459 (98.8)  1.00 (referent)  .632   Yes  25 (0.3)  7 (0.5)  1.24 (0.52 to 2.96)     Type I diabetes   No  13185 (95.9)  1861 (92.0)  1.00 (referent)  .982   Yes  84 (0.6)  14 (0.7)  0.99 (0.55 to 1.80)    Atopic disorders   Any atopic disorder§   No  15601 (68.9)  2345 (66.4)  1.00 (referent)  <.001   Yes  6442 (28.5)  1107 (31.4)  0.87 (0.80 to 0.94)     Allergy∥   No  10790 (72.1)  1903 (70.0)  1.00 (referent)  .018   Yes  3309 (22.1)  590 (21.7)  0.88 (0.79 to 0.98)     Food allergy   No  12757 (85.2)  2180 (80.1)  1.00 (referent)  .007   Yes  988 (6.6)  171 (6.3)  0.79 (0.67 to 0.94)     Asthma   No  18448 (85.6)  2894 (83.9)  1.00 (referent)  .018   Yes  1698 (7.9)  260 (7.5)  0.85 (0.74 to 0.97)     Hay fever   No  12467 (71.3)  2086 (69.3)  1.00 (referent)  <.001   Yes  2958 (16.9)  521 (17.3)  0.82 (0.73 to 0.91)     Eczema   No  14766 (86.1)  2452 (82.4)  1.00 (referent)  .283   Yes  1605 (9.4)  318 (10.7)  1.08 (0.94 to 1.23)    * CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. § Atopic disorders include asthma, eczema, hay fever, or other allergies, excluding drug allergies. ∥ History of allergy excludes drug allergies, asthma, eczema, and hay fever. View Large Table 3. Sex-specific medical, lifestyle, family history, and occupational exposures and follicular lymphoma*   Male  Female      Controls†  Cases†      Controls†  Cases†          No. (%)  No. (%)  OR (95% CI)‡  P  No. (%)  No. (%)  OR (95% CI)‡  P  P heterogeneity  Medical conditions   Sjögren’s syndrome   No  —  —  —  —  3555 (97.5)  829 (96.4)  1.00 (referent)  .028  .0030   Yes  0  0  —  —  9 (0.2)  7 (0.8)  3.24 (1.19 to 8.80)  —  —   Any atopic disorder§   No  9660 (73.0)  1247 (69.9)  1.00 (referent)  .180  5941 (63.1)  1098 (62.9)  1.00 (referent)  <.001  .0587   Yes  3187 (24.1)  497 (27.8)  0.92 (0.82 to 1.04)    3255 (34.6)  610 (35.0)  0.82 (0.73 to 0.92)  —  —   Allergy||   No  6682 (76.8)  1049 (73.9)  1.00 (referent)  .596  4108 (65.5)  854 (65.7)  1.00 (referent)  .006  .0947   Yes  1556 (17.9)  255 (18.0)  0.96 (0.82 to 1.12)  —  1753 (28.0)  335 (25.8)  0.82 (0.70 to 0.94)  —  —   Food allergy   No  6704 (86.1)  1078 (79.7)  1.00 (referent)  .744  5141 (82.0)  1034 (79.5)  1.00 (referent)  .002  .0409   Yes  405 (5.2)  71 (5.3)  0.96 (0.73 to 1.25)  —  583 (9.3)  100 (7.7)  0.70 (0.56 to 0.88)  —  —   Asthma   No  10548 (86.3)  1468 (85.1)  1.00 (referent)  .112  7900 (84.6)  1426 (82.7)  1.00 (referent)  .079  .8354   Yes  909 (7.4)  120 (7.0)  0.85 (0.69 to 1.04)  —  789 (8.5)  140 (8.1)  0.84 (0.69 to 1.02)  —  —   Hay fever   No  7000 (72.9)  1031 (69.1)  1.00 (referent)  .256  5467 (69.3)  1055 (69.6)  1.00 (referent)  <.001  .0124   Yes  1475 (15.4)  249 (16.7)  0.91 (0.78 to 1.07)  —  1483 (18.8)  272 (18.0)  0.74 (0.63 to 0.86)  —  —   Eczema   No  8722 (88.2)  1272 (85.0)  1.00 (referent)  .583  6044 (83.3)  1180 (79.7)  1.00 (referent)  .321  .8818   Yes  737 (7.5)  125 (8.4)  1.06 (0.86 to 1.30)  —  868 (12.0)  193 (13.0)  1.09 (0.92 to 1.30)  —  —   Blood transfusion     No  6085 (75.1)  996 (77.3)  1.00 (referent)  .005  4657 (78.9)  1020 (81.5)  1.00 (referent)  .011  .4838   Yes  878 (10.8)  101 (7.8)  0.74 (0.59 to 0.92)  —  1088 (18.4)  196 (15.7)  0.80 (0.68 to 0.95)  —  —  Family history     NHL     No  8544 (86.2)  1095 (85.5)  1.00 (referent)  <.001  5572 (80.0)  1050 (83.6)  1.00 (referent)  .022  .385   Yes  132 (1.3)  52 (4.1)  2.54 (1.81 to 3.58)  —  146 (2.1)  44 (3.5)  1.54 (1.08 to 2.20)  —  —   NHL in male relatives     No  7003 (84.5)  923 (85.8)  1.00 (referent)  <.001  4756 (78.5)  889 (83.6)  1.00 (referent)  .777  .0263   Yes  54 (0.7)  23 (1.9)  2.73 (1.63 to 4.60)  —  59 (1.0)  12 (1.1)  1.10 (0.58 to 2.08)  —  —   NHL in female relatives     No  6661 (83.9)  906 (85.8)  1.00 (referent)  .008  4744 (78.3)  877 (82.5)  1.00 (referent)  .043  .5794   Yes  55 (0.7)  20 (1.9)  2.14 (1.26 to 3.65)  —  71 (1.2)  24 (2.3)  1.69 (1.04 to 2.75)  —  —  Lifestyle factors     BMI as a young adult (kg/m2)     Continuous  13228 (100.0)  1785 (100.0)  1.09 (0.94 to 1.27)  .275  9411 (100.0)  1745 (100.0)  1.25 (1.09 to 1.44)  .948  .0606   Physical activity     None  319 (9.5)  41 (6.8)  1.00 (referent)  .153  397 (10.7)  57 (7.4)  1.00 (referent)  .190  .7835   Mild  210 (6.2)  52 (8.6)  1.30 (0.81 to 2.07)  —  264 (7.1)  82 (10.7)  1.53 (1.02 to 2.30)  —  —   Moderate  424 (12.6)  84 (13.9)  1.06 (0.69 to 1.62)  —  510 (13.8)  125 (16.3)  1.16 (0.79 to 1.69)  —  —   Vigorous  1380 (41.0)  255 (42.1)  1.37 (0.95 to 1.98)  —  1657 (44.8)  330 (43.0)  1.19 (0.86 to 1.66)  —  —   History of cigarette smoking¶   No  3934 (30.8)  520 (31.0)  1.00 (referent)  .695  4945 (54.9)  744 (45.8)  1.00 (referent)  <.001  .0038   Yes  8047 (63.0)  987 (58.8)  0.98 (0.87 to 1.10)  —  3643 (40.4)  762 (46.9)  1.22 (1.09 to 1.37)  —  —   History of alcohol consumption   Nondrinker  1995 (17.1)  239 (16.1)  1.00 (referent)  .551  2282 (28.5)  404 (27.7)  1.00 (referent)  .002  .1969   Drinker (at least 1 drink per month)  7245 (62.2)  833 (56.3)  0.95 (0.80 to 1.12)  —  3749 (46.8)  630 (43.2)  0.79 (0.68 to 0.91)  —  —   Recreational sun exposure (h/wk)   Quartile 1 (low)  1003 (18.1)  195 (20.4)  1.00 (referent)  .034  1231 (23.3)  327 (28.4)  1.00 (referent)  .002  .8752   Quartile 2  1112 (20.1)  176 (18.4)  0.77 (0.61 to 0.96)  —  1220 (23.1)  245 (21.3)  0.77 (0.64 to 0.93)  —  —   Quartile 3  1121 (20.2)  177 (18.5)  0.74 (0.58 to 0.93)  —  1038 (19.7)  216 (18.8)  0.78 (0.64 to 0.95)  —  —   Quartile 4 (high)  1745 (31.5)  277 (29.0)  0.77 (0.62 to 0.95)  —  1238 (23.5)  228 (19.8)  0.70 (0.58 to 0.85)  —  —  Occupational exposures   Bakers and millers   No  6124 (93.7)  970 (98.1)  1.00 (referent)  .143  5222 (98.7)  1001 (99.5)  1.00 (referent)  .040  .6802   Yes  97 (1.5)  7 (0.7)  0.58 (0.27 to 1.27)  —  61 (1.2)  5 (0.5)  0.42 (0.17 to 1.06)  —  —   Chemists and chemical workers   No  5804 (92.8)  884 (95.7)  1.00 (referent)  .090  5090 (99.3)  989 (99.4)  1.00 (referent)  .968  .5551   Yes  136 (2.2)  28 (3.0)  1.46 (0.96 to 2.23)  —  31 (0.6)  6 (0.6)  1.02 (0.42 to 2.49)  —  —   Medical worker   No  5996 (91.7)  934 (94.4)  1.00 (referent)  .489  5124 (88.3)  1023 (87.7)  1.00 (referent)  .489  .3100   Yes  225 (3.4)  43 (4.3)  1.13 (0.80 to 1.59)  —  670 (11.6)  144 (12.3)  0.93 (0.77 to 1.14)  —  —   Medical doctor   No  5709 (93.7)  912 (97.1)  1.00 (referent)  .480  5515 (99.4)  1103 (99.5)  1.00 (referent)  .765  .9556   Yes  63 (1.0)  13 (1.4)  1.25 (0.68 to 2.32)  —  19 (0.3)  5 (0.5)  1.17 (0.42 to 3.24)  —  —   Spray-painter (except construction)   No  5465 (94.1)  790 (96.7)  1.00 (referent)  <.001   4854 (99.6)  936 (99.9)  1.00 (referent)  .111  .8588   Yes  22 (0.4)  13 (1.6)  3.83 (1.87 to 7.84)  —  7 (0.1)  0 (0.0)  —    —   University and higher education teachers     No  6063 (92.7)  959 (97.0)  1.00 (referent)  .011  5666 (97.7)  1145 (98.1)  1.00 (referent)  .066  .6104   Yes  154 (2.4)  16 (1.6)  0.53 (0.31 to 0.90)  —  120 (2.1)  21 (1.8)  0.65 (0.40 to 1.05)  —  —    Male  Female      Controls†  Cases†      Controls†  Cases†          No. (%)  No. (%)  OR (95% CI)‡  P  No. (%)  No. (%)  OR (95% CI)‡  P  P heterogeneity  Medical conditions   Sjögren’s syndrome   No  —  —  —  —  3555 (97.5)  829 (96.4)  1.00 (referent)  .028  .0030   Yes  0  0  —  —  9 (0.2)  7 (0.8)  3.24 (1.19 to 8.80)  —  —   Any atopic disorder§   No  9660 (73.0)  1247 (69.9)  1.00 (referent)  .180  5941 (63.1)  1098 (62.9)  1.00 (referent)  <.001  .0587   Yes  3187 (24.1)  497 (27.8)  0.92 (0.82 to 1.04)    3255 (34.6)  610 (35.0)  0.82 (0.73 to 0.92)  —  —   Allergy||   No  6682 (76.8)  1049 (73.9)  1.00 (referent)  .596  4108 (65.5)  854 (65.7)  1.00 (referent)  .006  .0947   Yes  1556 (17.9)  255 (18.0)  0.96 (0.82 to 1.12)  —  1753 (28.0)  335 (25.8)  0.82 (0.70 to 0.94)  —  —   Food allergy   No  6704 (86.1)  1078 (79.7)  1.00 (referent)  .744  5141 (82.0)  1034 (79.5)  1.00 (referent)  .002  .0409   Yes  405 (5.2)  71 (5.3)  0.96 (0.73 to 1.25)  —  583 (9.3)  100 (7.7)  0.70 (0.56 to 0.88)  —  —   Asthma   No  10548 (86.3)  1468 (85.1)  1.00 (referent)  .112  7900 (84.6)  1426 (82.7)  1.00 (referent)  .079  .8354   Yes  909 (7.4)  120 (7.0)  0.85 (0.69 to 1.04)  —  789 (8.5)  140 (8.1)  0.84 (0.69 to 1.02)  —  —   Hay fever   No  7000 (72.9)  1031 (69.1)  1.00 (referent)  .256  5467 (69.3)  1055 (69.6)  1.00 (referent)  <.001  .0124   Yes  1475 (15.4)  249 (16.7)  0.91 (0.78 to 1.07)  —  1483 (18.8)  272 (18.0)  0.74 (0.63 to 0.86)  —  —   Eczema   No  8722 (88.2)  1272 (85.0)  1.00 (referent)  .583  6044 (83.3)  1180 (79.7)  1.00 (referent)  .321  .8818   Yes  737 (7.5)  125 (8.4)  1.06 (0.86 to 1.30)  —  868 (12.0)  193 (13.0)  1.09 (0.92 to 1.30)  —  —   Blood transfusion     No  6085 (75.1)  996 (77.3)  1.00 (referent)  .005  4657 (78.9)  1020 (81.5)  1.00 (referent)  .011  .4838   Yes  878 (10.8)  101 (7.8)  0.74 (0.59 to 0.92)  —  1088 (18.4)  196 (15.7)  0.80 (0.68 to 0.95)  —  —  Family history     NHL     No  8544 (86.2)  1095 (85.5)  1.00 (referent)  <.001  5572 (80.0)  1050 (83.6)  1.00 (referent)  .022  .385   Yes  132 (1.3)  52 (4.1)  2.54 (1.81 to 3.58)  —  146 (2.1)  44 (3.5)  1.54 (1.08 to 2.20)  —  —   NHL in male relatives     No  7003 (84.5)  923 (85.8)  1.00 (referent)  <.001  4756 (78.5)  889 (83.6)  1.00 (referent)  .777  .0263   Yes  54 (0.7)  23 (1.9)  2.73 (1.63 to 4.60)  —  59 (1.0)  12 (1.1)  1.10 (0.58 to 2.08)  —  —   NHL in female relatives     No  6661 (83.9)  906 (85.8)  1.00 (referent)  .008  4744 (78.3)  877 (82.5)  1.00 (referent)  .043  .5794   Yes  55 (0.7)  20 (1.9)  2.14 (1.26 to 3.65)  —  71 (1.2)  24 (2.3)  1.69 (1.04 to 2.75)  —  —  Lifestyle factors     BMI as a young adult (kg/m2)     Continuous  13228 (100.0)  1785 (100.0)  1.09 (0.94 to 1.27)  .275  9411 (100.0)  1745 (100.0)  1.25 (1.09 to 1.44)  .948  .0606   Physical activity     None  319 (9.5)  41 (6.8)  1.00 (referent)  .153  397 (10.7)  57 (7.4)  1.00 (referent)  .190  .7835   Mild  210 (6.2)  52 (8.6)  1.30 (0.81 to 2.07)  —  264 (7.1)  82 (10.7)  1.53 (1.02 to 2.30)  —  —   Moderate  424 (12.6)  84 (13.9)  1.06 (0.69 to 1.62)  —  510 (13.8)  125 (16.3)  1.16 (0.79 to 1.69)  —  —   Vigorous  1380 (41.0)  255 (42.1)  1.37 (0.95 to 1.98)  —  1657 (44.8)  330 (43.0)  1.19 (0.86 to 1.66)  —  —   History of cigarette smoking¶   No  3934 (30.8)  520 (31.0)  1.00 (referent)  .695  4945 (54.9)  744 (45.8)  1.00 (referent)  <.001  .0038   Yes  8047 (63.0)  987 (58.8)  0.98 (0.87 to 1.10)  —  3643 (40.4)  762 (46.9)  1.22 (1.09 to 1.37)  —  —   History of alcohol consumption   Nondrinker  1995 (17.1)  239 (16.1)  1.00 (referent)  .551  2282 (28.5)  404 (27.7)  1.00 (referent)  .002  .1969   Drinker (at least 1 drink per month)  7245 (62.2)  833 (56.3)  0.95 (0.80 to 1.12)  —  3749 (46.8)  630 (43.2)  0.79 (0.68 to 0.91)  —  —   Recreational sun exposure (h/wk)   Quartile 1 (low)  1003 (18.1)  195 (20.4)  1.00 (referent)  .034  1231 (23.3)  327 (28.4)  1.00 (referent)  .002  .8752   Quartile 2  1112 (20.1)  176 (18.4)  0.77 (0.61 to 0.96)  —  1220 (23.1)  245 (21.3)  0.77 (0.64 to 0.93)  —  —   Quartile 3  1121 (20.2)  177 (18.5)  0.74 (0.58 to 0.93)  —  1038 (19.7)  216 (18.8)  0.78 (0.64 to 0.95)  —  —   Quartile 4 (high)  1745 (31.5)  277 (29.0)  0.77 (0.62 to 0.95)  —  1238 (23.5)  228 (19.8)  0.70 (0.58 to 0.85)  —  —  Occupational exposures   Bakers and millers   No  6124 (93.7)  970 (98.1)  1.00 (referent)  .143  5222 (98.7)  1001 (99.5)  1.00 (referent)  .040  .6802   Yes  97 (1.5)  7 (0.7)  0.58 (0.27 to 1.27)  —  61 (1.2)  5 (0.5)  0.42 (0.17 to 1.06)  —  —   Chemists and chemical workers   No  5804 (92.8)  884 (95.7)  1.00 (referent)  .090  5090 (99.3)  989 (99.4)  1.00 (referent)  .968  .5551   Yes  136 (2.2)  28 (3.0)  1.46 (0.96 to 2.23)  —  31 (0.6)  6 (0.6)  1.02 (0.42 to 2.49)  —  —   Medical worker   No  5996 (91.7)  934 (94.4)  1.00 (referent)  .489  5124 (88.3)  1023 (87.7)  1.00 (referent)  .489  .3100   Yes  225 (3.4)  43 (4.3)  1.13 (0.80 to 1.59)  —  670 (11.6)  144 (12.3)  0.93 (0.77 to 1.14)  —  —   Medical doctor   No  5709 (93.7)  912 (97.1)  1.00 (referent)  .480  5515 (99.4)  1103 (99.5)  1.00 (referent)  .765  .9556   Yes  63 (1.0)  13 (1.4)  1.25 (0.68 to 2.32)  —  19 (0.3)  5 (0.5)  1.17 (0.42 to 3.24)  —  —   Spray-painter (except construction)   No  5465 (94.1)  790 (96.7)  1.00 (referent)  <.001   4854 (99.6)  936 (99.9)  1.00 (referent)  .111  .8588   Yes  22 (0.4)  13 (1.6)  3.83 (1.87 to 7.84)  —  7 (0.1)  0 (0.0)  —    —   University and higher education teachers     No  6063 (92.7)  959 (97.0)  1.00 (referent)  .011  5666 (97.7)  1145 (98.1)  1.00 (referent)  .066  .6104   Yes  154 (2.4)  16 (1.6)  0.53 (0.31 to 0.90)  —  120 (2.1)  21 (1.8)  0.65 (0.40 to 1.05)  —  —  * BMI = body mass index; CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. § Atopic disorders include asthma, eczema, hay fever, or other allergies, excluding drug allergies. || History of allergy excludes drug allergies, asthma, eczema, and hay fever. ¶ Smoked longer than 6 months or more than 100 cigarettes in lifetime. View Large History of a blood transfusion was associated with a 22% lower risk of FL (Table 4). Reductions in FL risk were most notable for those who received a transfusion after age 55 years and within 40 years before the diagnosis of FL/interview. Positive hepatitis C virus serology was not linked with FL risk (OR = 1.28; 95% CI = 0.64 to 2.57, based on 11 exposed cases and 34 exposed controls). Neither use of oral contraceptives nor use of hormonal replacement therapy was linked with FL risk (data not shown). Table 4. History of blood transfusions and risk of follicular lymphoma*   Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Blood transfusion   No  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Yes  1966 (14.0)  297 (11.7)  0.78 (0.68 to 0.89)    Age at first transfusion   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <25 y  483 (3.4)  82 (3.2)  0.83 (0.65 to 1.06)     25–39 y  579 (4.1)  99 (3.9)  0.80 (0.64 to 1.00)     40–54 y  449 (3.2)  71 (2.8)  0.82 (0.63 to 1.06)     55 or older  455 (3.2)  45 (1.8)  0.62 (0.45 to 0.85)    Total number of blood transfusions   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   1 transfusion  1306 (9.3)  202 (8.0)  0.83 (0.71 to 0.97)     2 transfusions  361 (2.6)  47 (1.9)  0.63 (0.46 to 0.86)     3 or more transfusions  229 (1.6)  35 (1.4)  0.73 (0.50 to 1.05)     Transfusion, but number unknown  70 (0.5)  13 (0.5)  0.88 (0.48 to 1.62)    Number of years from 1st transfusion to date of diagnosis/interview     No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <20 y  878 (6.3)  121 (4.8)  0.77 (0.63 to 0.94)     20–39 y  748 (5.3)  118 (4.6)  0.76 (0.62 to 0.93)     ≥40 y  340 (2.4)  58 (2.3)  0.86 (0.64 to 1.14)    Blood transfusion before 1990   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Before 1990  1457 (10.4)  235 (9.3)  0.83 (0.71 to 0.96)     After 1990  404 (2.9)  44 (1.7)  0.62 (0.45 to 0.86)     Transfusion year unknown  105 (0.7)  18 (0.7)  0.68 (0.39 to 1.17)      Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Blood transfusion   No  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Yes  1966 (14.0)  297 (11.7)  0.78 (0.68 to 0.89)    Age at first transfusion   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <25 y  483 (3.4)  82 (3.2)  0.83 (0.65 to 1.06)     25–39 y  579 (4.1)  99 (3.9)  0.80 (0.64 to 1.00)     40–54 y  449 (3.2)  71 (2.8)  0.82 (0.63 to 1.06)     55 or older  455 (3.2)  45 (1.8)  0.62 (0.45 to 0.85)    Total number of blood transfusions   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   1 transfusion  1306 (9.3)  202 (8.0)  0.83 (0.71 to 0.97)     2 transfusions  361 (2.6)  47 (1.9)  0.63 (0.46 to 0.86)     3 or more transfusions  229 (1.6)  35 (1.4)  0.73 (0.50 to 1.05)     Transfusion, but number unknown  70 (0.5)  13 (0.5)  0.88 (0.48 to 1.62)    Number of years from 1st transfusion to date of diagnosis/interview     No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <20 y  878 (6.3)  121 (4.8)  0.77 (0.63 to 0.94)     20–39 y  748 (5.3)  118 (4.6)  0.76 (0.62 to 0.93)     ≥40 y  340 (2.4)  58 (2.3)  0.86 (0.64 to 1.14)    Blood transfusion before 1990   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Before 1990  1457 (10.4)  235 (9.3)  0.83 (0.71 to 0.96)     After 1990  404 (2.9)  44 (1.7)  0.62 (0.45 to 0.86)     Transfusion year unknown  105 (0.7)  18 (0.7)  0.68 (0.39 to 1.17)    * CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. View Large Family History of Hematopoietic Malignancies Participants with a first-degree relative with a history of NHL experienced approximately a twofold greater risk of FL than participants without such a history (Table 5), and risks were elevated in both male and female participants except females with affected male relatives (Table 3). Male and female participants with first-degree male, but not female, relatives with multiple myeloma had an increased risk of FL (Table 5). FL was not increased in participants with first-degree relatives with leukemia or Hodgkin lymphoma (Table 5). Table 5. Family history of hematopoietic malignancies and risk of follicular lymphoma*   Controls†  Cases†      First-degree family history  No. (%)  No. (%)  OR (95% CI)‡  P   Any hematologic malignancy   No  14346 (81.5)  2144 (81.3)  1.00 (referent)  <.001   Yes  769 (4.4)  198 (7.5)  1.48 (1.25 to 1.75)     Any hematologic malignancy in male relatives   No  11543 (80.5)  1759 (82.2)  1.00 (referent)  <.001   Yes  329 (2.3)  88 (4.1)  1.56 (1.22 to 2.00)     Any hematologic malignancy in female relatives     No  11560 (80.6)  1764 (82.5)  1.00 (referent)  .011   Yes  312 (2.2)  83 (3.9)  1.41 (1.09 to 1.82)     NHL   No  14116 (83.6)  2145 (84.6)  1.00 (referent)  <.001   Yes  278 (1.6)  96 (3.8)  1.99 (1.55 to 2.54)     NHL in male relatives   No  11759 (82.0)  1812 (84.7)  1.00 (referent)  .004   Yes  113 (0.8)  35 (1.6)  1.84 (1.24 to 2.73)     NHL in female relatives   No  11746 (81.9)  1803 (84.3)  1.00 (referent)  <.001   Yes  126 (0.9)  44 (2.1)  1.93 (1.35 to 2.75)     Multiple myeloma   No  11327 (81.9)  1795 (85.4)  1.00 (referent)  .040   Yes  41 (0.3)  16 (0.8)  1.93 (1.06 to 3.51)     Multiple myeloma in male relatives   No  8048 (76.6)  1338 (81.7)  1.00 (referent)  .003   Yes  16 (0.2)  11 (0.7)  3.64 (1.65 to 8.05)     Multiple myeloma in female relatives   No  8842 (92.1)  1550 (91.6)  1.00 (referent)  .870   Yes  25 (0.3)  5 (0.3)  0.92 (0.35 to 2.46)     Leukemia   No  13831 (92.4)  2129 (91.3)  1.00 (referent)  .853   Yes  402 (2.7)  65 (2.8)  0.98 (0.74 to 1.28)     Leukemia in male relatives   No  11634 (92.6)  1811 (91.5)  1.00 (referent)  .873   Yes  197 (1.6)  31 (1.6)  0.97 (0.66 to 1.43)     Leukemia in female relatives   No  11680 (92.9)  1815 (91.7)  1.00 (referent)  .933   Yes  151 (1.2)  27 (1.4)  1.02 (0.67 to 1.55)     HL   No  14149 (94.5)  2173 (93.2)  1.00 (referent)  .133   Yes  84 (0.6)  21 (0.9)  1.47 (0.90 to 2.40)     HL in male relatives   No  11288 (93.6)  1795 (92.3)  1.00 (referent)  .239   Yes  39 (0.3)  11 (0.6)  1.53 (0.77 to 3.04)     HL in female relatives   No  10316 (94.6)  1694 (93.6)  1.00 (referent)  .456   Yes  29 (0.3)  7 (0.4)  1.39 (0.60 to 3.23)      Controls†  Cases†      First-degree family history  No. (%)  No. (%)  OR (95% CI)‡  P   Any hematologic malignancy   No  14346 (81.5)  2144 (81.3)  1.00 (referent)  <.001   Yes  769 (4.4)  198 (7.5)  1.48 (1.25 to 1.75)     Any hematologic malignancy in male relatives   No  11543 (80.5)  1759 (82.2)  1.00 (referent)  <.001   Yes  329 (2.3)  88 (4.1)  1.56 (1.22 to 2.00)     Any hematologic malignancy in female relatives     No  11560 (80.6)  1764 (82.5)  1.00 (referent)  .011   Yes  312 (2.2)  83 (3.9)  1.41 (1.09 to 1.82)     NHL   No  14116 (83.6)  2145 (84.6)  1.00 (referent)  <.001   Yes  278 (1.6)  96 (3.8)  1.99 (1.55 to 2.54)     NHL in male relatives   No  11759 (82.0)  1812 (84.7)  1.00 (referent)  .004   Yes  113 (0.8)  35 (1.6)  1.84 (1.24 to 2.73)     NHL in female relatives   No  11746 (81.9)  1803 (84.3)  1.00 (referent)  <.001   Yes  126 (0.9)  44 (2.1)  1.93 (1.35 to 2.75)     Multiple myeloma   No  11327 (81.9)  1795 (85.4)  1.00 (referent)  .040   Yes  41 (0.3)  16 (0.8)  1.93 (1.06 to 3.51)     Multiple myeloma in male relatives   No  8048 (76.6)  1338 (81.7)  1.00 (referent)  .003   Yes  16 (0.2)  11 (0.7)  3.64 (1.65 to 8.05)     Multiple myeloma in female relatives   No  8842 (92.1)  1550 (91.6)  1.00 (referent)  .870   Yes  25 (0.3)  5 (0.3)  0.92 (0.35 to 2.46)     Leukemia   No  13831 (92.4)  2129 (91.3)  1.00 (referent)  .853   Yes  402 (2.7)  65 (2.8)  0.98 (0.74 to 1.28)     Leukemia in male relatives   No  11634 (92.6)  1811 (91.5)  1.00 (referent)  .873   Yes  197 (1.6)  31 (1.6)  0.97 (0.66 to 1.43)     Leukemia in female relatives   No  11680 (92.9)  1815 (91.7)  1.00 (referent)  .933   Yes  151 (1.2)  27 (1.4)  1.02 (0.67 to 1.55)     HL   No  14149 (94.5)  2173 (93.2)  1.00 (referent)  .133   Yes  84 (0.6)  21 (0.9)  1.47 (0.90 to 2.40)     HL in male relatives   No  11288 (93.6)  1795 (92.3)  1.00 (referent)  .239   Yes  39 (0.3)  11 (0.6)  1.53 (0.77 to 3.04)     HL in female relatives   No  10316 (94.6)  1694 (93.6)  1.00 (referent)  .456   Yes  29 (0.3)  7 (0.4)  1.39 (0.60 to 3.23)    * CI = confidence interval; HL = Hodgkin lymphoma; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. View Large Lifestyle Factors Risks for FL were increased in those who were overweight (OR = 1.49; 95% CI = 1.21 to 1.83) or obese (OR = 1.46; 95% CI = 0.98 to 2.17) as young adults and rose 15% with each five kg/m2 increase in young adult body mass index (BMI) (Table 6). No significant relationship was observed for usual adult BMI or weight. Greater adult height in males, but not females, was associated with increased risk of FL (data not shown). Table 6. Lifestyle factors and risk of follicular lymphoma*   Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  BMI, weight, and height   BMI as a young adult, kg/m2   15–<18.5  382 (2.5)  66 (2.5)  0.90 (0.67 to 1.19)     18.5–<22.5  2800 (18.1)  464 (17.8)  1.00 (referent)  .001   22.5–<25  1391 (9.0)  201 (7.7)  1.03 (0.85 to 1.24)     25–<30  838 (5.4)  164 (6.3)  1.49 (1.21 to 1.83)     30–50  172 (1.1)  34 (1.3)  1.46 (0.98 to 2.17)     Continuous (5kg/m2 increase in BMI)  5583  929  1.21 (1.09 to 1.35)  <.001   Usual adult BMI, kg/m2   15–<18.5  267 (1.6)  25 (0.9)  0.67 (0.44 to 1.03)     18.5–<22.5  3481 (20.3)  538 (19.4)  1.00 (referent)  .143   22.5–<25  4276 (25.0)  706 (25.5)  1.09 (0.96 to 1.23)     25–<30  6112 (35.7)  959 (34.6)  1.01 (0.89 to 1.14)     30–<35  1760 (10.3)  325 (11.7)  1.07 (0.91 to 1.25)     35–50  608 (3.6)  109 (3.9)  0.93 (0.73 to 1.17)     Continuous (5kg/m2 increase in BMI)  16504  2662  0.99 (0.95 to 1.04)  .735   Usual adult height   Quartile 1 (low)  4131 (24.1)  584 (21.1)  1.00 (referent)  .124   Quartile 2  3852 (22.5)  603 (21.8)  1.04 (0.92 to 1.18)     Quartile 3  4169 (24.3)  695 (25.1)  1.05 (0.93 to 1.19)     Quartile 4 (high)  4352 (25.4)  780 (28.1)  1.15 (1.02 to 1.30)     Usual adult weight   Quartile 1 (low)  4115 (24.0)  583 (21.0)  1.00 (referent)  .263   Quartile 2  3953 (23.1)  627 (22.6)  1.01 (0.89 to 1.14)     Quartile 3  4335 (25.3)  680 (24.5)  0.94 (0.83 to 1.07)     Quartile 4 (high)  4101 (24.0)  772 (27.8)  1.06 (0.94 to 1.20)     Physical activity   No  716 (10.1)  98 (7.1)  1.00 (referent)  . 055   Mild  474 (6.7)  134 (9.8)  1.41 (1.04 to 1.91)     Moderate  934 (13.2)  209 (15.2)  1.09 (0.83 to 1.45)     Vigorous  3037 (43.0)  585 (42.6)  1.26 (0.99 to 1.60)    Cigarette smoking   History of cigarette smoking§   No  8879 (40.7)  1264 (38.3)  1.00 (referent)  .046   Yes  11690 (53.6)  1749 (53.0)  1.09 (1.00 to 1.18)     Smoking status   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .009   Former smoker  6327 (29.0)  956 (29.0)  1.02 (0.93 to 1.12)     Current smoker  4829 (22.2)  743 (22.5)  1.19 (1.07 to 1.32)     Smoker, status unknown  534 (2.5)  50 (1.5)  1.05 (0.76 to 1.45)     Age started smoking cigarettes regularly   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .051   <14 y  1068 (4.9)  125 (3.8)  0.88 (0.72 to 1.07)     14–17 y  4348 (20.0)  710 (21.5)  1.12 (1.01 to 1.25)     18–19 y  2352 (10.8)  384 (11.6)  1.11 (0.97 to 1.26)     ≥20 y  3251 (14.9)  475 (14.4)  1.11 (0.99 to 1.25)     Smoker, age start unknown  671 (3.1)  55 (1.7)  0.94 (0.69 to 1.27)     Frequency of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .088   Smoker, 1–10 cigarettes/d  3910 (17.9)  603 (18.3)  1.09 (0.98 to 1.21)     Smoker, 11–20 cigarettes/d  4766 (21.9)  731 (22.1)  1.13 (1.02 to 1.25)     Smoker, 21–30 cigarettes/d  1248 (5.7)  189 (5.7)  1.09 (0.92 to 1.29)     Smoker, >30 cigarettes/d  1339 (6.1)  155 (4.7)  0.90 (0.75 to 1.09)     Smoker, cigarettes/day unknown  427 (2.0)  71 (2.2)  1.11 (0.84 to 1.45)     Continuous  20173  2946  1.00 (1.00 to 1.00)  .948   Duration of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .013   1–20 y  3917 (18.0)  534 (16.2)  1.02 (0.91 to 1.14)     21–30 y  2341 (10.7)  388 (11.8)  1.10 (0.97 to 1.25)     30–39 y  2392 (11.0)  417 (12.6)  1.13 (1.00 to 1.28)     ≥40 y  2749 (12.6)  391 (11.8)  1.18 (1.04 to 1.35)     Smoker, duration unknown  291 (1.3)  19 (0.6)  0.63 (0.39 to 1.01)     Continuous  20278  2994  1.00 (1.00 to 1.01)  .006   Lifetime cigarette exposure   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .150   1–10 pack-years  3473 (15.9)  501 (15.2)  1.06 (0.95 to 1.19)     11–20 pack-years  2272 (10.4)  341 (10.3)  1.06 (0.93 to 1.21)     21–35 pack-years  2369 (10.9)  409 (12.4)  1.18 (1.04 to 1.34)     ≥36 pack-years  3038 (13.9)  425 (12.9)  1.10 (0.97 to 1.25)     Smoker, pack-years unknown  538 (2.5)  73 (2.2)  0.93 (0.72 to 1.22)  Alcohol consumption   History of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .009   Drinker (at least 1 drink per month)  10994 (55.9)  1463 (49.8)  0.86 (0.77 to 0.96)     Alcohol consumption status   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .003   Former drinker  609 (3.1)  125 (4.3)  1.16 (0.91 to 1.49)     Current drinker  5010 (25.5)  723 (24.6)  0.88 (0.76 to 1.03)     Drinker, status unknown  5375 (27.3)  615 (20.9)  0.81 (0.69 to 0.95)     Age at first alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .023   <20 y  2281 (11.6)  316 (10.8)  0.92 (0.76 to 1.12)     20–29 y  2908 (14.8)  349 (11.9)  0.88 (0.74 to 1.05)     ≥30 y  768 (3.9)  117 (4.0)  1.07 (0.85 to 1.35)     Drinker, age start unknown  5037 (25.6)  681 (23.2)  0.80 (0.68 to 0.93)     Duration of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .078   1–20 y  1307 (6.6)  128 (4.4)  0.87 (0.69 to 1.11)     21–30 y  1085 (5.5)  164 (5.6)  0.90 (0.72 to 1.13)     30–39 y  1247 (6.3)  182 (6.2)  0.95 (0.76 to 1.17)     ≥40 y  1900 (9.7)  243 (8.3)  1.00 (0.81 to 1.22)     Drinker, duration unknown  5455 (27.7)  746 (25.4)  0.80 (0.69 to 0.93)     Servings of alcohol per week as an adult   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .017   <1 drink/wk  955 (4.9)  182 (6.2)  0.89 (0.74 to 1.08)     1–6 drinks/wk  3738 (19.0)  571 (19.4)  0.85 (0.75 to 0.97)     7–13 drinks/wk  2216 (11.3)  288 (9.8)  0.84 (0.72 to 0.99)     14–27 drinks/wk  2137 (10.9)  258 (8.8)  0.91 (0.77 to 1.08)     ≥28 drinks/wk or binge drinkers  1918 (9.8)  157 (5.3)  0.78 (0.64 to 0.96)     Drinker, drinks/week unknown  30 (0.2)  7 (0.2)  3.00 (1.25 to 7.23)     Grams of ethanol per week as an adult, consumed from any type of alcoholic beverage     Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .005   Quartile 1 (low)  2421 (12.3)  347 (11.8)  0.79 (0.68 to 0.92)     Quartile 2  2471 (12.6)  325 (11.1)  0.83 (0.71 to 0.97)     Quartile 3  2488 (12.6)  315 (10.7)  0.87 (0.75 to 1.02)     Quartile 4 (high)  2534 (12.9)  230 (7.8)  0.79 (0.66 to 0.94)     Drinker, grams consumed unknown  1080 (5.5)  246 (8.4)  1.33 (0.97 to 1.83)     Lifetime alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .007   1–100 kg  1444 (7.3)  182 (6.2)  0.75 (0.60 to 0.93)     101–200 kg  641 (3.3)  67 (2.3)  0.68 (0.51 to 0.91)     201–400 kg  651 (3.3)  96 (3.3)  1.05 (0.81 to 1.37)     >400 kg  759 (3.9)  75 (2.6)  0.85 (0.64 to 1.14)     Drinker, lifetime consumption unknown  7499 (38.1)  1043 (35.5)  0.90 (0.79 to 1.03)     Continuous  7886  1106  1.00 (1.00 to 1.00)  .893  Sun exposure   Total sun exposure (h/wk)   Quartile 1 (low)  1508 (18.7)  337 (20.6)  1.00 (referent)  .116   Quartile 2  1594 (19.8)  293 (18.0)  0.83 (0.69 to 0.99)     Quartile 3  1633 (20.3)  307 (18.8)  0.88 (0.73 to 1.05)     Quartile 4 (high)  1714 (21.3)  299 (18.3)  0.82 (0.69 to 0.99)     Recreational sun exposure (h/wk)   Quartile 1 (low)  2234 (20.6)  522 (24.8)  1.00 (referent)  <.001   Quartile 2  2332 (21.6)  421 (20.0)  0.77 (0.67 to 0.90)     Quartile 3  2159 (20.0)  393 (18.6)  0.77 (0.66 to 0.89)     Quartile 4 (high)  2983 (27.6)  505 (24.0)  0.74 (0.65 to 0.86)      Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  BMI, weight, and height   BMI as a young adult, kg/m2   15–<18.5  382 (2.5)  66 (2.5)  0.90 (0.67 to 1.19)     18.5–<22.5  2800 (18.1)  464 (17.8)  1.00 (referent)  .001   22.5–<25  1391 (9.0)  201 (7.7)  1.03 (0.85 to 1.24)     25–<30  838 (5.4)  164 (6.3)  1.49 (1.21 to 1.83)     30–50  172 (1.1)  34 (1.3)  1.46 (0.98 to 2.17)     Continuous (5kg/m2 increase in BMI)  5583  929  1.21 (1.09 to 1.35)  <.001   Usual adult BMI, kg/m2   15–<18.5  267 (1.6)  25 (0.9)  0.67 (0.44 to 1.03)     18.5–<22.5  3481 (20.3)  538 (19.4)  1.00 (referent)  .143   22.5–<25  4276 (25.0)  706 (25.5)  1.09 (0.96 to 1.23)     25–<30  6112 (35.7)  959 (34.6)  1.01 (0.89 to 1.14)     30–<35  1760 (10.3)  325 (11.7)  1.07 (0.91 to 1.25)     35–50  608 (3.6)  109 (3.9)  0.93 (0.73 to 1.17)     Continuous (5kg/m2 increase in BMI)  16504  2662  0.99 (0.95 to 1.04)  .735   Usual adult height   Quartile 1 (low)  4131 (24.1)  584 (21.1)  1.00 (referent)  .124   Quartile 2  3852 (22.5)  603 (21.8)  1.04 (0.92 to 1.18)     Quartile 3  4169 (24.3)  695 (25.1)  1.05 (0.93 to 1.19)     Quartile 4 (high)  4352 (25.4)  780 (28.1)  1.15 (1.02 to 1.30)     Usual adult weight   Quartile 1 (low)  4115 (24.0)  583 (21.0)  1.00 (referent)  .263   Quartile 2  3953 (23.1)  627 (22.6)  1.01 (0.89 to 1.14)     Quartile 3  4335 (25.3)  680 (24.5)  0.94 (0.83 to 1.07)     Quartile 4 (high)  4101 (24.0)  772 (27.8)  1.06 (0.94 to 1.20)     Physical activity   No  716 (10.1)  98 (7.1)  1.00 (referent)  . 055   Mild  474 (6.7)  134 (9.8)  1.41 (1.04 to 1.91)     Moderate  934 (13.2)  209 (15.2)  1.09 (0.83 to 1.45)     Vigorous  3037 (43.0)  585 (42.6)  1.26 (0.99 to 1.60)    Cigarette smoking   History of cigarette smoking§   No  8879 (40.7)  1264 (38.3)  1.00 (referent)  .046   Yes  11690 (53.6)  1749 (53.0)  1.09 (1.00 to 1.18)     Smoking status   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .009   Former smoker  6327 (29.0)  956 (29.0)  1.02 (0.93 to 1.12)     Current smoker  4829 (22.2)  743 (22.5)  1.19 (1.07 to 1.32)     Smoker, status unknown  534 (2.5)  50 (1.5)  1.05 (0.76 to 1.45)     Age started smoking cigarettes regularly   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .051   <14 y  1068 (4.9)  125 (3.8)  0.88 (0.72 to 1.07)     14–17 y  4348 (20.0)  710 (21.5)  1.12 (1.01 to 1.25)     18–19 y  2352 (10.8)  384 (11.6)  1.11 (0.97 to 1.26)     ≥20 y  3251 (14.9)  475 (14.4)  1.11 (0.99 to 1.25)     Smoker, age start unknown  671 (3.1)  55 (1.7)  0.94 (0.69 to 1.27)     Frequency of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .088   Smoker, 1–10 cigarettes/d  3910 (17.9)  603 (18.3)  1.09 (0.98 to 1.21)     Smoker, 11–20 cigarettes/d  4766 (21.9)  731 (22.1)  1.13 (1.02 to 1.25)     Smoker, 21–30 cigarettes/d  1248 (5.7)  189 (5.7)  1.09 (0.92 to 1.29)     Smoker, >30 cigarettes/d  1339 (6.1)  155 (4.7)  0.90 (0.75 to 1.09)     Smoker, cigarettes/day unknown  427 (2.0)  71 (2.2)  1.11 (0.84 to 1.45)     Continuous  20173  2946  1.00 (1.00 to 1.00)  .948   Duration of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .013   1–20 y  3917 (18.0)  534 (16.2)  1.02 (0.91 to 1.14)     21–30 y  2341 (10.7)  388 (11.8)  1.10 (0.97 to 1.25)     30–39 y  2392 (11.0)  417 (12.6)  1.13 (1.00 to 1.28)     ≥40 y  2749 (12.6)  391 (11.8)  1.18 (1.04 to 1.35)     Smoker, duration unknown  291 (1.3)  19 (0.6)  0.63 (0.39 to 1.01)     Continuous  20278  2994  1.00 (1.00 to 1.01)  .006   Lifetime cigarette exposure   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .150   1–10 pack-years  3473 (15.9)  501 (15.2)  1.06 (0.95 to 1.19)     11–20 pack-years  2272 (10.4)  341 (10.3)  1.06 (0.93 to 1.21)     21–35 pack-years  2369 (10.9)  409 (12.4)  1.18 (1.04 to 1.34)     ≥36 pack-years  3038 (13.9)  425 (12.9)  1.10 (0.97 to 1.25)     Smoker, pack-years unknown  538 (2.5)  73 (2.2)  0.93 (0.72 to 1.22)  Alcohol consumption   History of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .009   Drinker (at least 1 drink per month)  10994 (55.9)  1463 (49.8)  0.86 (0.77 to 0.96)     Alcohol consumption status   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .003   Former drinker  609 (3.1)  125 (4.3)  1.16 (0.91 to 1.49)     Current drinker  5010 (25.5)  723 (24.6)  0.88 (0.76 to 1.03)     Drinker, status unknown  5375 (27.3)  615 (20.9)  0.81 (0.69 to 0.95)     Age at first alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .023   <20 y  2281 (11.6)  316 (10.8)  0.92 (0.76 to 1.12)     20–29 y  2908 (14.8)  349 (11.9)  0.88 (0.74 to 1.05)     ≥30 y  768 (3.9)  117 (4.0)  1.07 (0.85 to 1.35)     Drinker, age start unknown  5037 (25.6)  681 (23.2)  0.80 (0.68 to 0.93)     Duration of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .078   1–20 y  1307 (6.6)  128 (4.4)  0.87 (0.69 to 1.11)     21–30 y  1085 (5.5)  164 (5.6)  0.90 (0.72 to 1.13)     30–39 y  1247 (6.3)  182 (6.2)  0.95 (0.76 to 1.17)     ≥40 y  1900 (9.7)  243 (8.3)  1.00 (0.81 to 1.22)     Drinker, duration unknown  5455 (27.7)  746 (25.4)  0.80 (0.69 to 0.93)     Servings of alcohol per week as an adult   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .017   <1 drink/wk  955 (4.9)  182 (6.2)  0.89 (0.74 to 1.08)     1–6 drinks/wk  3738 (19.0)  571 (19.4)  0.85 (0.75 to 0.97)     7–13 drinks/wk  2216 (11.3)  288 (9.8)  0.84 (0.72 to 0.99)     14–27 drinks/wk  2137 (10.9)  258 (8.8)  0.91 (0.77 to 1.08)     ≥28 drinks/wk or binge drinkers  1918 (9.8)  157 (5.3)  0.78 (0.64 to 0.96)     Drinker, drinks/week unknown  30 (0.2)  7 (0.2)  3.00 (1.25 to 7.23)     Grams of ethanol per week as an adult, consumed from any type of alcoholic beverage     Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .005   Quartile 1 (low)  2421 (12.3)  347 (11.8)  0.79 (0.68 to 0.92)     Quartile 2  2471 (12.6)  325 (11.1)  0.83 (0.71 to 0.97)     Quartile 3  2488 (12.6)  315 (10.7)  0.87 (0.75 to 1.02)     Quartile 4 (high)  2534 (12.9)  230 (7.8)  0.79 (0.66 to 0.94)     Drinker, grams consumed unknown  1080 (5.5)  246 (8.4)  1.33 (0.97 to 1.83)     Lifetime alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .007   1–100 kg  1444 (7.3)  182 (6.2)  0.75 (0.60 to 0.93)     101–200 kg  641 (3.3)  67 (2.3)  0.68 (0.51 to 0.91)     201–400 kg  651 (3.3)  96 (3.3)  1.05 (0.81 to 1.37)     >400 kg  759 (3.9)  75 (2.6)  0.85 (0.64 to 1.14)     Drinker, lifetime consumption unknown  7499 (38.1)  1043 (35.5)  0.90 (0.79 to 1.03)     Continuous  7886  1106  1.00 (1.00 to 1.00)  .893  Sun exposure   Total sun exposure (h/wk)   Quartile 1 (low)  1508 (18.7)  337 (20.6)  1.00 (referent)  .116   Quartile 2  1594 (19.8)  293 (18.0)  0.83 (0.69 to 0.99)     Quartile 3  1633 (20.3)  307 (18.8)  0.88 (0.73 to 1.05)     Quartile 4 (high)  1714 (21.3)  299 (18.3)  0.82 (0.69 to 0.99)     Recreational sun exposure (h/wk)   Quartile 1 (low)  2234 (20.6)  522 (24.8)  1.00 (referent)  <.001   Quartile 2  2332 (21.6)  421 (20.0)  0.77 (0.67 to 0.90)     Quartile 3  2159 (20.0)  393 (18.6)  0.77 (0.66 to 0.89)     Quartile 4 (high)  2983 (27.6)  505 (24.0)  0.74 (0.65 to 0.86)    * BMI = body mass index; CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. § Smoked longer than 6 months or more than 100 cigarettes in lifetime. View Large History of cigarette smoking was positively associated with FL risk in females but not males (P heterogeneity = .004; Table 3). Among women, a modest increase in risk of FL in those who ever smoked cigarettes was limited to current smokers, along with a significant positive trend for duration of smoking (data not shown). The trend in pack-years of smoking in women was more clearly related to duration than frequency of cigarettes smoked (data not shown). FL risks were reduced modestly in women, but not men, who ever drank alcohol, particularly current drinkers (Table 3), but there was no clear pattern with duration, number of drinks per week, or cumulative alcohol consumption (data not shown); we note, however, that many studies did not collect these data. A lower risk of FL was associated with increasing number of hours per week of recreational sun exposure for both men and women (Table 3) but was attenuated for total sun exposure hours (Table 6). FL risk, examined in females only, was not linked with hair dye use overall or by type, duration, or frequency (data not shown), except for a modest increase in those who used hair dyes before 1980 (OR = 1.40, 95% CI = 1.10 to 1.78). Occupational Factors Working or living on a farm was not associated with risk of FL (Table 7). Bakers and millers, and those working as university or higher education teachers, experienced reduced risks, whereas spray painters had increased risks of FL. A modest, nonsignificant increase in risk of FL was seen for those ever working as medical doctors, but those working more than 10 years in this occupation had a significantly elevated risk (OR = 2.06, 95% CI = 1.08 to 3.92, based on 38 cases vs 13 controls). Employment in other occupations was not associated with risk of FL (Table 7). Table 7. Occupational factors and risk of follicular lymphoma*   Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Farm residence and/or farming & related occupation   Ever lived on a farm   No  4779 (56.3)  822 (58.1)  1.00 (referent)  .592   Yes  3470 (40.9)  554 (39.1)  0.97 (0.85 to 1.09)     Ever worked on a farm   No  11675 (80.0)  1978 (83.0)  1.00 (referent)  .177   Yes  2717 (18.6)  371 (15.6)  0.92 (0.81 to 1.04)     Animal farm workers   No  11699 (94.8)  2092 (97.0)  1.00 (referent)  .985   Yes  316 (2.6)  52 (2.4)  1.00 (0.73 to 1.36)     Crop farm workers   No  11442 (92.7)  2069 (96.0)  1.00 (referent)  .994   Yes  573 (4.6)  75 (3.5)  1.00 (0.78 to 1.29)     Farm workers, any type   No  10583 (85.8)  1935 (89.7)  1.00 (referent)  .839   Yes  1432 (11.6)  209 (9.7)  0.98 (0.84 to 1.16)     Forestry worker   No  11227 (96.6)  2001 (99.1)  1.00 (referent)  .580   Yes  71 (0.6)  7 (0.3)  0.81 (0.37 to 1.77)     Meat worker   No  11907 (96.5)  2121 (98.4)  1.00 (referent)  .491   Yes  108 (0.9)  23 (1.1)  1.18 (0.74 to 1.88)    Other selected occupations   Bakers and millers   No/never  11857 (96.1)  2132 (98.9)  1.00 (referent)  .017   Yes  158 (1.3)  12 (0.6)  0.51 (0.28 to 0.93)     Chemists and chemical workers   No/never  11848 (96.0)  2110 (97.9)  1.00 (referent)  .156   Yes  167 (1.4)  34 (1.6)  1.33 (0.91 to 1.94)     Petroleum worker   No/never  10558 (96.9)  1905 (99.3)  1.00 (referent)  .518   Yes  18 (0.2)  2 (0.1)  0.63 (0.14 to 2.78)     Medical worker   No/never  11120 (90.1)  1957 (90.8)  1.00 (referent)  .752   Yes  895 (7.3)  187 (8.7)  0.97 (0.82 to 1.16)     Medical doctor   No/never  11921 (96.6)  2123 (98.5)  1.00 (referent)  .425   Yes  82 (0.7)  18 (0.8)  1.24 (0.74 to 2.10)     Spray-painter (except construction)   No/never  10596 (96.7)  1777 (98.4)  1.00 (referent)  .008   Yes  29 (0.3)  13 (0.7)  2.66 (1.36 to 5.24)     University and higher education teachers     No/never  11729 (95.1)  2104 (97.6)  1.00 (referent)  .001   Yes  274 (2.2)  37 (1.7)  0.58 (0.41 to 0.83)      Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Farm residence and/or farming & related occupation   Ever lived on a farm   No  4779 (56.3)  822 (58.1)  1.00 (referent)  .592   Yes  3470 (40.9)  554 (39.1)  0.97 (0.85 to 1.09)     Ever worked on a farm   No  11675 (80.0)  1978 (83.0)  1.00 (referent)  .177   Yes  2717 (18.6)  371 (15.6)  0.92 (0.81 to 1.04)     Animal farm workers   No  11699 (94.8)  2092 (97.0)  1.00 (referent)  .985   Yes  316 (2.6)  52 (2.4)  1.00 (0.73 to 1.36)     Crop farm workers   No  11442 (92.7)  2069 (96.0)  1.00 (referent)  .994   Yes  573 (4.6)  75 (3.5)  1.00 (0.78 to 1.29)     Farm workers, any type   No  10583 (85.8)  1935 (89.7)  1.00 (referent)  .839   Yes  1432 (11.6)  209 (9.7)  0.98 (0.84 to 1.16)     Forestry worker   No  11227 (96.6)  2001 (99.1)  1.00 (referent)  .580   Yes  71 (0.6)  7 (0.3)  0.81 (0.37 to 1.77)     Meat worker   No  11907 (96.5)  2121 (98.4)  1.00 (referent)  .491   Yes  108 (0.9)  23 (1.1)  1.18 (0.74 to 1.88)    Other selected occupations   Bakers and millers   No/never  11857 (96.1)  2132 (98.9)  1.00 (referent)  .017   Yes  158 (1.3)  12 (0.6)  0.51 (0.28 to 0.93)     Chemists and chemical workers   No/never  11848 (96.0)  2110 (97.9)  1.00 (referent)  .156   Yes  167 (1.4)  34 (1.6)  1.33 (0.91 to 1.94)     Petroleum worker   No/never  10558 (96.9)  1905 (99.3)  1.00 (referent)  .518   Yes  18 (0.2)  2 (0.1)  0.63 (0.14 to 2.78)     Medical worker   No/never  11120 (90.1)  1957 (90.8)  1.00 (referent)  .752   Yes  895 (7.3)  187 (8.7)  0.97 (0.82 to 1.16)     Medical doctor   No/never  11921 (96.6)  2123 (98.5)  1.00 (referent)  .425   Yes  82 (0.7)  18 (0.8)  1.24 (0.74 to 2.10)     Spray-painter (except construction)   No/never  10596 (96.7)  1777 (98.4)  1.00 (referent)  .008   Yes  29 (0.3)  13 (0.7)  2.66 (1.36 to 5.24)     University and higher education teachers     No/never  11729 (95.1)  2104 (97.6)  1.00 (referent)  .001   Yes  274 (2.2)  37 (1.7)  0.58 (0.41 to 0.83)    * CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. View Large Risks According to Race/Ethnicity, Source of Population, and Region For the associations observed in all FL patients, patterns were generally similar by race/ethnicity, except for increased risks for any atopic disorder and hay fever, and a trend in recreational sun exposure in Asians (Supplementary Table 1, available online). Comparison of FL risks in population-based versus hospital-based studies revealed that the findings were mainly driven by the former (Supplementary Table 2, available online). Risks according to region were mostly consistent, although risks for combined and individual atopic allergic disorders showed greater reductions in risk in Australia than in Europe or North America (Supplementary Table 3, available online). Discussion In the largest pooled analysis of case–control studies focused on FL and the first to assess a broad range of exposures simultaneously, most risk factors examined were not associated with risk of FL specifically, except for a few mostly modest or sex-specific relationships. We found novel associations with FL risk for certain occupations, including reduced risk in bakers/millers, and university/higher education teachers, and increased risk in spray painters. With our larger number of studies and strong evidence for independence in multivariate models, this analysis extends earlier InterLymph observations of an increased risk of FL for those with Sjögren syndrome (37), a first-degree relative with a history of NHL (17), and reduced risks among those with allergic diseases (24) and greater recreational hours spent per week in the sun (30). Increased FL risks among current cigarette smokers, in conjunction with a positive trend with duration of smoking, were restricted to women, as were the significantly reduced risks of FL in those with a history of hay fever or food allergy. We also found a reduced risk of FL with a history of blood transfusion. Although meta-analyses of all NHL (5,38,39) found a modest up to 10% increase in risk among those who had worked in farming, few studies have evaluated occupational risks for FL specifically. A pooled analysis of studies in Kansas and Nebraska found increases in FL risk in association with employment in agriculture or farming that were not statistically significant (40). Two studies with stratification of cases by chromosomal translocation in t(14;18) found associations with certain agricultural pesticides (but not farming per se) for t(14;18)-positive NHL, but not for t(14;18)-negative cases (41,42). Although t(14;18) is not specific to FL, this molecular feature occurs in 70%–90% of FL cases compared with 20%–30% of diffuse large B-cell lymphoma cases and 5%–10% of other NHL subtypes (31). It is possible that FL may be associated with specific exposures in farming, such as poultry (43), which were not characterized in our assessment of farming as an occupation. Unfortunately, molecular characterization according to t(14;18) status was not available for the majority of the FL cases in this pooled study. Our finding of an increased risk of FL in spray painters is consistent with previous reports finding that NHL risk is elevated among those working in the occupation of painter and those working with solvents used in paint product formulations (44,45). The decreased risk of FL in university/higher education teachers is not consistent with the results from a meta-analysis showing increased risk among teachers (38), but the meta-analysis included teachers at all levels, whereas our finding was restricted to university/higher education teachers. The meta-analysis did not provide separate estimates of risk for university/higher education teachers. This, and our findings for medical doctors and for bakers/millers, should be further investigated in occupational epidemiologic studies to evaluate specific exposures. Reasons for the female-specific modest increase in FL risk associated with cigarette smoking are not clear, but these results are consistent with those of a recent meta-analysis of 24 studies which reported a 43% increased risk of FL in female smokers compared with nonsmokers, but no association of smoking status, duration, or intensity in males (46). Findings from cohort studies (11,27,47) also provide some support for this association. An association of cigarette smoking with FL is biologically plausible in that increased rates of t(14;18) translocations have been observed in heavy smokers (48). The current analysis, with more than twice as many studies and threefold more FL cases than our earlier InterLymph consortium analysis (13), provides more precise estimates of FL risk (20% increase in our analysis of “current” smokers vs 31% in our earlier assessment), and identified a similar significant relationship with increasing duration of smoking, establishing that this association is not likely to be confounded by alcohol, BMI, or a variety of other risk factors evaluated here. Our finding of an excess risk of FL associated with Sjögren’s syndrome is consistent with our earlier InterLymph pooled analysis (12 studies, 12982 NHL cases (14)) in which Sjögren’s syndrome was the only autoimmune disease associated with FL. We found reductions in risk of FL in relation to history of allergic conditions except for eczema. These findings are consistent with our earlier pooled analysis (2842 FL) (24). However, this first sex-specific assessment revealed that the significant reductions in risks for any allergy, hay fever, and food allergy were restricted to females. Our findings of increased risks for atopic disorders and hay fever in Asian participants require further evaluation. Our results also mirror those from our previous pooled InterLymph analysis (1703 FL) (17) that found a twofold increased FL risk among participants with a first-degree relative with a history of NHL, with risks elevated in both male and female participants, except females with affected male relatives (17). Our data also support findings from other studies of a stronger familial association of NHL risk in male relatives, which is consistent for FL and other lymphoma subtypes (49–51). The present study reveals a reduced risk of FL only in current drinkers who were female, but not related to the frequency or duration of their alcohol consumption. In our earlier InterLymph pooled evaluation based on nine studies (1307 FL) (26), we observed a reduced risk of FL associated with alcohol consumption, particularly in current drinkers, but with no evidence of dose–response relationships with frequency or duration of alcohol use. Prospective studies have shown mixed results with moderate (52–56) and heavy (27) alcohol intake associated with reductions in FL risk ranging from 23% to 41% in some studies, but not in others (57–59). One cohort study found an elevated risk of FL among women who were former alcohol drinkers (60). It has been postulated that these findings may be due to effects of alcohol in modulating immune function (61) but because immune deficiency has not been shown to be important for FL risk, chronic inflammation may be a potential biologic mechanism, although alcohol has many other biologic effects. An alternative explanation is that the association is not causal but may reflect differences in other characteristics between alcohol drinkers and nondrinkers. In our previous InterLymph evaluation of sun exposure (1642 FL) (30), we found a downward trend in risk with increasing total recreational sun exposure, particularly for exposures at 18–40 years of age and in the 10 years before diagnosis for all B-cell lymphomas and for FL, but no association with occupational sun exposure. This inverse association may be due partly to effects on the immune function from sun exposure (62), vitamin D production (63), or chance. A cohort study examining ambient residential ultraviolet radiation among California teachers showed null findings for FL (28). To our knowledge, the current study is the first to find that persons with a history of blood transfusion experienced a modestly reduced risk of FL. Blood transfusion (which suppresses cellular immunity, includes transfer of allogeneic cells, and may transmit infectious and chemical agents) has been associated with increased risk of all NHL in some (15,64–66), but not all studies (67–72). Limited data on the role of transfusions in FL suggest no risk (73–76) or a modest increase in risk (8,15). Cerhan and colleagues (15) have suggested that transfusions may be a marker for underlying medical conditions rather than directly associated with NHL or its subtypes. The association of overweight and obesity in early adulthood with FL risk is strengthened by the significant positive dose–response trend of early adult BMI with FL risk. However, most cohort studies (7,56,58,77–82), with one exception (83), found no relationship of early adult weight or BMI with FL, although many of these studies included relatively small numbers of FL cases. Our finding of a relationship between greater adult height in males, but not females, in relation to FL is likely a chance finding since most cohort studies (56,58,78–82) reported no relationship of height in men or women with FL except for three (20,77,83) that found a positive relationship in women. This pooled analysis is the first and largest multivariate assessment of a broad range of putative risk factors for FL. Other strengths include assessment of effect modification (particularly gender) and confounding. The systematic nature of the subtype evaluation using the WHO classification, exposure assessment by standardized questionnaires, population-based design for most of the studies, along with careful efforts to harmonize the variables included in the pooled analyses, represent additional strengths. Limitations include the self-reported nature of the data collected, the difficulty of using retrospectively collected information, reliance on job titles instead of specific occupational exposures, the limited types of exposures evaluated, and lack of comprehensive assessment of many of the individual putative risk factors, multiple comparisons, and absence of assessment of some variables for all studies. Sex-specific associations could be due to chance or unexplained bias, although it is possible that such associations may reflect genetic variation, hormonal exposure, or occupational exposures. Other limitations include lack of independent evaluation of exposures and the potential for recall bias. Some findings (eg, female-specific associations with alcohol consumption, the inverse association with history of blood transfusions or the relationship with BMI in early adulthood) may be due to chance. In conclusion, the majority of the factors evaluated were not associated with risk of FL. As noted above, associations with blood transfusion and BMI in early adulthood are inconsistent with prior studies. The sex-specific findings for cigarette smoking and allergic disorders, as well as the associations with some occupations, deserve further evaluation. Although this study does not identify risk factors that explain much of FL occurrence, the few relationships observed do provide clues suggesting a complex multifactorial etiology. Funding This pooled analysis was supported by the Intramural Research Program of the National Cancer Institute/National Institutes of Health and National Cancer Institute/National Institutes of Health (R01 CA14690, U01 CA118444, and R01 CA92153-S1). InterLymph annual meetings during 2010–2013 were supported by the Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute/National Institutes of Health (2010–2013); Lymphoma Coalition (2010–2013); National Institutes of Health Office of Rare Diseases Research (2010); National Cancer Institute/National Institutes of Health (R13 CA159842 01) (2011); University of Cagliari, Provincial Administration of Cagliari, Banca di Credito Sardo, and Consorzio Industriale Sardo, Italy (2011); Intramural Research Program of the National Cancer Institute/National Institutes of Health (2012); and Faculté de Médecine de Dijon, Institut de Veille Sanitaire, Registre des hémopathies malignes de Côte d’Or, INSERM, Institut National du Cancer, Université de Bourgogne, Groupe Ouest Est d’Etude des Leucémies et Autres Maladies du Sang (GOELAMS), l’Institut Bergonié, The Lymphoma Study Association (LYSA), Registre Régional des Hémopathies de Basse Normandie, and the City of Dijon, France (2013). Meeting space at the 2013 Annual Meeting of the American Association for Cancer Research (AACR) was provided by the Molecular Epidemiology Group (MEG) of the AACR. Individual studies were supported by: the Canadian Institutes for Health Research (CIHR), Canadian Cancer Society, and Michael Smith Foundation for Health Research (British Columbia); Intramural Research Program of the National Cancer Institute/National Institutes of Health (Iowa/Minnesota); National Cancer Institute/National Institutes of Health (N01-CP-ES-11027) (Kansas); National Cancer Institute/National Institutes of Health (R01 CA50850) (Los Angeles); National Cancer Institute/National Institutes of Health (R01 CA92153 and P50 CA97274), Lymphoma Research Foundation (164738), and the Henry J. Predolin Foundation (Mayo Clinic); Intramural Research Program of the National Cancer Institute/National Institutes of Health and Public Health Service (contracts N01-PC-65064, N01-PC-67008, N01-PC-67009, N01-PC-67010, and N02-PC-71105) (NCI-SEER); National Cancer Institute/National Institutes of Health (R01CA100555 and R03CA132153) and American Institute for Cancer Research (99B083) (Nebraska [newer]); National Cancer Institute/National Institutes of Health (N01-CP-95618) and State of Nebraska Department of Health (LB-506) (Nebraska [older]); National Cancer Institute/National Institutes of Health (R01CA45614, RO1CA154643-01A1, and R01CA104682) (UCSF1); National Cancer Institute/National Institutes of Health (CA143947, CA150037, R01CA087014, R01CA104682, RO1CA122663, and RO1CA154643-01A1) (UCSF2); National Heart Lung and Blood Institute/National Institutes of Health (hematology training grant award T32 HL007152), National Center for Research Resources/National Institutes of Health (UL 1 RR024160), and National Cancer Institute/National Institutes of Health (K23 CA102216 and P50 CA130805) (University of Rochester); National Cancer Institute/National Institutes of Health (CA62006 and CA165923) (Yale); Association pour la Recherche contre le Cancer, Fondation de France, AFSSET, and a donation from Faberge employees (Engela); European Commission (QLK4-CT-2000-00422 and FOOD-CT-2006-023103), Spanish Ministry of Health (CIBERESP, PI11/01810, RCESP C03/09, RTICESP C03/10, and RTIC RD06/0020/0095), Rio Hortega (CM13/00232), Agència de Gestió d’Ajuts Universitaris i de Recerca–Generalitat de Catalunya (Catalonian Government, 2009SGR1026), National Institutes of Health (contract NO1-CO-12400), Italian Ministry of Education, University and Research (PRIN 2007 prot. 2007WEJLZB, PRIN 2009 prot. 20092ZELR2), Italian Association for Cancer Research (IG grant 11855/2011); Federal Office for Radiation Protection (StSch4261 and StSch4420), José Carreras Leukemia Foundation (DJCLS-R04/08), German Federal Ministry for Education and Research (BMBF-01-EO-1303), Health Research Board, Ireland and Cancer Research Ireland, and Czech Republic MH CZ – DRO (MMCI, 00209805) (EpiLymph); National Cancer Institute/National Institutes of Health (CA51086), European Community (Europe Against Cancer Programme), and Italian Alliance Against Cancer (Lega Italiana per la Lotta contro i Tumori) (Italy, multicenter); Italian Association for Cancer Research (Italy, Aviano-Milan); Italian Association for Cancer Research (Italy, Aviano-Naples); Swedish Cancer Society (2009/659), Stockholm County Council (20110209), Strategic Research Program in Epidemiology at Karolinska Institut, Swedish Cancer Society (02 6661), Danish Cancer Research Foundation, Lundbeck Foundation (R19-A2364), Danish Cancer Society (DP 08-155), National Cancer Institute/National Institutes of Health (5R01 CA69669-02), and Plan Denmark (SCALE); Leukaemia & Lymphoma Research, UK; and Australian National Health and Medical Research Council (ID990920), Cancer Council NSW, and University of Sydney Faculty of Medicine (New South Wales). 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Oxford University Press
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Published by Oxford University Press 2014.
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1052-6773
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1745-6614
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10.1093/jncimonographs/lgu006
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25174024
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Abstract

Abstract Background Follicular lymphoma (FL) has been linked with cigarette smoking and, inconsistently, with other risk factors. Methods We assessed associations of medical, hormonal, family history, lifestyle, and occupational factors with FL risk in 3530 cases and 22639 controls from 19 case–control studies in the InterLymph consortium. Age-, race/ethnicity-, sex- and study-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression. Results Most risk factors that were evaluated showed no association, except for a few modest or sex-specific relationships. FL risk was increased in persons: with a first-degree relative with non-Hodgkin lymphoma (OR = 1.99; 95% CI = 1.55 to 2.54); with greater body mass index as a young adult (OR = 1.15; 95% CI = 1.04 to 1.27 per 5kg/m2 increase); who worked as spray painters (OR = 2.66; 95% CI = 1.36 to 5.24); and among women with Sjögren syndrome (OR = 3.37; 95% CI = 1.23 to 9.19). Lower FL risks were observed in persons: with asthma, hay fever, and food allergy (ORs = 0.79–0.85); blood transfusions (OR = 0.78; 95% CI = 0.68 to 0.89); high recreational sun exposure (OR = 0.74; 95% CI = 0.65 to 0.86, fourth vs first quartile); who worked as bakers or millers (OR = 0.51; 95% CI = 0.28 to 0.93) or university/higher education teachers (OR = 0.58; 95% CI = 0.41 to 0.83). Elevated risks specific to women included current and longer duration of cigarette use, whereas reduced risks included current alcohol use, hay fever, and food allergies. Other factors, including other autoimmune diseases, eczema, hepatitis C virus seropositivity, hormonal drugs, hair dye use, sun exposure, and farming, were not associated with FL risk. Conclusions The few relationships observed provide clues suggesting a multifactorial etiology of FL but are limited in the extent to which they explain FL occurrence. Follicular lymphoma (FL), the second most common form of lymphoma in the United States and western Europe, is a lymphoproliferative disorder of germinal center B cells (1). The US age-adjusted incidence rate for FL during 1992–2001 was 3.18 per 100000, with a 3.6-fold variation between the highest and lowest rates (in white males and American Indian/Alaska Native males, respectively) (2) and a 2.8-fold variation in rates among Asian Americans of different origins (3). Age-adjusted FL rates are slightly higher in males than in females. Most patients present with indolent disease, although 2%–3% of FL cases transform annually to diffuse large B-cell lymphoma (4). Few epidemiologic studies published before 2004 evaluated risk factors separately for subtypes of non-Hodgkin lymphoma (NHL) based on the Revised European-American Lymphoma (REAL)/ World Health Organization (WHO) classification (5–10). Subsequently, an expanding literature has examined risk factors for the common NHL subtypes, although most of these studies have assessed specific or related categories of exposure but did not evaluate risks across a broad range of exposures. Cigarette smoking has repeatedly been associated with a higher risk of FL (11–13), and some reports, including previous InterLymph pooled analyses, have linked excess risk of FL with Sjögren syndrome (14), blood transfusions (15), family history of hematopoietic malignancies (16,17), hair dyes (18,19), and greater height (20). A few reports have linked occupational exposure to benzene, oils/greases, and other solvents such as styrene and trichloroethylene with increased risks of FL (9,21–23). Reduced risks of FL have been linked with atopic disorders (24), oral contraceptive use (25), alcohol consumption (26,27), and sun exposure (28–30). We have pooled data from 19 case–control studies conducted in Europe, North America, and Australia to examine associations between medical and family history, lifestyle, hormonal drugs, and occupation. The broad range of risk factors available provided an opportunity to assess multivariate associations, and the large study size, 3530 FL cases and 22639 controls, provided an opportunity to examine relatively rare exposures and weak associations overall and in subgroups defined by sex, race/ethnicity, region, and source of controls. Methods Study Population Detailed methodology for the InterLymph NHL Subtypes Project is provided elsewhere in this issue. Studies eligible for inclusion in this pooled analysis were case–control studies, with incident, histologically confirmed cases of FL defined according to the WHO classification (31,32); each study collected individual-level data for at least several risk factors of interest and these were submitted to the pooling project by December 31, 2011. Most studies excluded individuals with a known history of solid organ transplantation or HIV/AIDS. Contributing studies were approved by local ethics review committees, and all participants provided written, informed consent prior to participation. Risk Factors and NHL Subtype Ascertainment and Harmonization Each study collected data on potential NHL risk factors in a standardized, structured format by in-person or telephone interviews, and/or self-administered questionnaires. Risk factors included were those where data were available from at least four studies. Each variable was harmonized individually, then related exposure variables were reviewed for consistency as detailed elsewhere (33). Cases were classified according to the WHO classification (31,32) using guidelines from the InterLymph Pathology Working Group (34,35). Statistical Analysis Risk of FL associated with each exposure variable was evaluated using logistic regression models, adjusting for age, race/ethnicity, sex, and study in a basic adjusted model. The significance of each association was evaluated by a likelihood ratio test, comparing models with and without the exposure variable of interest, with P values less than 0.05 identifying putatively influential factors. To quantify the magnitude of the association, we estimated the relative risk using odds ratios (ORs) and 95% confidence intervals (CIs) derived from the logistic regression models. Individuals with missing data for a variable of interest were excluded. To evaluate effect heterogeneity among the studies, we performed a separate logistic regression within each study and then quantified the variability of the coefficients by the H statistic, adapting the definition by Higgins and Thompson to categorical variables (36). To consider possible effect modification, we repeated the above logistic regression analyses but stratified individuals by age, sex, race/ethnicity, region (ie, North America vs Europe vs Australia), study design (ie, population-based vs hospital-based), or other putative risk factors identified in the analysis. To assess confounding, we first evaluated the risk estimate for each putative risk factor in a series of models that adjusted for one other putative risk factor individually in addition to the basic adjusted model. Next, we conducted a single logistic regression model including all putative risk factors, this time including a separate missing category for each variable to ensure that the entire study population was included in the analysis. Finally, we conducted a forward step-wise logistic regression with all putative risk factors, adjusting for age, sex, race/ethnicity, and study. Results from this series of multivariate adjusted logistic regression models showed little difference from the findings based on the basic adjusted models (ie, adjusted for age, sex, race/ethnicity, and study). We therefore report the results for the basic adjusted models only. Because controls for most original studies were frequency matched by age and sex to all cases, we conducted sensitivity analyses using a subset of controls individually matched by age and sex to the FL cases. The results were similar to those using the full set of controls and, thus, we retained all controls for the main analyses to increase statistical power. Results The median age was similar for FL cases at diagnosis (median: 58 years, range: 18–91 years) and controls at the time of interview (median: 59 years, range: 16–98 years). FL cases were more likely to be female, but FL cases and controls were similar by race/ethnicity (with >90% non-Hispanic whites) and socioeconomic status (Table 1). Most cases and controls were from North America or northern Europe and from population-based studies. Table 1. Descriptive characteristics of follicular lymphoma cases and controls     Controls  Cases      No. (%)  No. (%)  Total  22639 (86.5)  3530 (13.5)  Age at diagnosis/interview, y   <30  1356 (6.0)  38 (1.1)   30–39  2143 (9.5)  253 (7.2)   40–49  3090 (13.6)  655 (18.6)   50–59  4870 (21.5)  1003 (28.4)   60–69  6277 (27.7)  1011 (28.6)   70–79  4048 (17.9)  508 (14.4)   ≥80  839 (3.7)  58 (1.6)   Missing  16 (0.1)  4 (0.1)  Sex   Male  13228 (58.4)  1785 (50.6)   Female  9411 (41.6)  1745 (49.4)  Race   White non-Hispanic  21145 (93.4)  3231 (91.5)   Black  351 (1.6)  37 (1.0)   Asian  321 (1.4)  70 (2.0)   Hispanic  334 (1.5)  59 (1.7)   Other/unknown/missing  488 (2.2)  133 (3.8)  Socioeconomic status   Low  9266 (40.9)  1384 (39.2)   Medium  6577 (29.1)  1061 (30.1)   High  6386 (28.2)  1019 (28.9)   Other/missing  410 (1.8)  66 (1.9)  Region   North America  11005 (48.6)  1854 (52.5)   Northern Europe  6542 (28.9)  1100 (31.2)   Southern Europe  4398 (19.4)  324 (9.2)   Australia  694 (3.1)  252 (7.1)  Study design   Population-based  17389 (76.8)  2908 (82.4)   Hospital-based  5250 (23.2)  622 (17.6)      Controls  Cases      No. (%)  No. (%)  Total  22639 (86.5)  3530 (13.5)  Age at diagnosis/interview, y   <30  1356 (6.0)  38 (1.1)   30–39  2143 (9.5)  253 (7.2)   40–49  3090 (13.6)  655 (18.6)   50–59  4870 (21.5)  1003 (28.4)   60–69  6277 (27.7)  1011 (28.6)   70–79  4048 (17.9)  508 (14.4)   ≥80  839 (3.7)  58 (1.6)   Missing  16 (0.1)  4 (0.1)  Sex   Male  13228 (58.4)  1785 (50.6)   Female  9411 (41.6)  1745 (49.4)  Race   White non-Hispanic  21145 (93.4)  3231 (91.5)   Black  351 (1.6)  37 (1.0)   Asian  321 (1.4)  70 (2.0)   Hispanic  334 (1.5)  59 (1.7)   Other/unknown/missing  488 (2.2)  133 (3.8)  Socioeconomic status   Low  9266 (40.9)  1384 (39.2)   Medium  6577 (29.1)  1061 (30.1)   High  6386 (28.2)  1019 (28.9)   Other/missing  410 (1.8)  66 (1.9)  Region   North America  11005 (48.6)  1854 (52.5)   Northern Europe  6542 (28.9)  1100 (31.2)   Southern Europe  4398 (19.4)  324 (9.2)   Australia  694 (3.1)  252 (7.1)  Study design   Population-based  17389 (76.8)  2908 (82.4)   Hospital-based  5250 (23.2)  622 (17.6)  View Large Medical Conditions and Treatments Overall, participants with a history of autoimmune diseases involving B-cell or T-cell activation were not at an increased risk of FL, except for those with Sjögren syndrome (Table 2). History of any atopic condition (OR = 0.87; 95% CI = 0.80 to 0.94) or any specific allergies (ORs ranged from 0.82 to 0.88), but not eczema, was associated with a reduced risk of FL (Table 2). Hay fever and food allergy were associated with significantly reduced FL risk in females but not males (P heterogeneity = .01 and .04, respectively; Table 3). Table 2. Autoimmune and allergic disorders and risk of follicular lymphoma*   Controls†  Cases†      No. (%)  No. (%)  OR (95% CI)‡  P  History of autoimmune conditions   History of autoimmune disease   No autoimmune disease  19423 (95.9)  3242 (95.8)  1.00 (referent)  .358   B-cell activation  157 (0.8)  39 (1.2)  1.26 (0.88 to 1.81)     T-cell activation  664 (3.3)  100 (3.0)  0.88 (0.71 to 1.10)     Both  15 (0.1)  4 (0.1)  1.40 (0.45 to 4.32)     Sjögren syndrome   No  6917 (97.2)  1487 (96.6)  1.00 (referent)  .024   Yes  9 (0.1)  7 (0.5)  3.37 (1.23 to 9.19)     Systematic lupus erythematosus   No  15987 (98.6)  2807 (98.0)  1.00 (referent)  .104   Yes  33 (0.2)  12 (0.4)  1.81 (0.91 to 3.60)     Inflammatory bowel disorder   No  16231 (97.6)  2620 (97.2)  1.00 (referent)  .349   Yes  199 (1.2)  29 (1.1)  0.83 (0.56 to 1.24)     Celiac disease   No  8907 (99.4)  1459 (98.8)  1.00 (referent)  .632   Yes  25 (0.3)  7 (0.5)  1.24 (0.52 to 2.96)     Type I diabetes   No  13185 (95.9)  1861 (92.0)  1.00 (referent)  .982   Yes  84 (0.6)  14 (0.7)  0.99 (0.55 to 1.80)    Atopic disorders   Any atopic disorder§   No  15601 (68.9)  2345 (66.4)  1.00 (referent)  <.001   Yes  6442 (28.5)  1107 (31.4)  0.87 (0.80 to 0.94)     Allergy∥   No  10790 (72.1)  1903 (70.0)  1.00 (referent)  .018   Yes  3309 (22.1)  590 (21.7)  0.88 (0.79 to 0.98)     Food allergy   No  12757 (85.2)  2180 (80.1)  1.00 (referent)  .007   Yes  988 (6.6)  171 (6.3)  0.79 (0.67 to 0.94)     Asthma   No  18448 (85.6)  2894 (83.9)  1.00 (referent)  .018   Yes  1698 (7.9)  260 (7.5)  0.85 (0.74 to 0.97)     Hay fever   No  12467 (71.3)  2086 (69.3)  1.00 (referent)  <.001   Yes  2958 (16.9)  521 (17.3)  0.82 (0.73 to 0.91)     Eczema   No  14766 (86.1)  2452 (82.4)  1.00 (referent)  .283   Yes  1605 (9.4)  318 (10.7)  1.08 (0.94 to 1.23)      Controls†  Cases†      No. (%)  No. (%)  OR (95% CI)‡  P  History of autoimmune conditions   History of autoimmune disease   No autoimmune disease  19423 (95.9)  3242 (95.8)  1.00 (referent)  .358   B-cell activation  157 (0.8)  39 (1.2)  1.26 (0.88 to 1.81)     T-cell activation  664 (3.3)  100 (3.0)  0.88 (0.71 to 1.10)     Both  15 (0.1)  4 (0.1)  1.40 (0.45 to 4.32)     Sjögren syndrome   No  6917 (97.2)  1487 (96.6)  1.00 (referent)  .024   Yes  9 (0.1)  7 (0.5)  3.37 (1.23 to 9.19)     Systematic lupus erythematosus   No  15987 (98.6)  2807 (98.0)  1.00 (referent)  .104   Yes  33 (0.2)  12 (0.4)  1.81 (0.91 to 3.60)     Inflammatory bowel disorder   No  16231 (97.6)  2620 (97.2)  1.00 (referent)  .349   Yes  199 (1.2)  29 (1.1)  0.83 (0.56 to 1.24)     Celiac disease   No  8907 (99.4)  1459 (98.8)  1.00 (referent)  .632   Yes  25 (0.3)  7 (0.5)  1.24 (0.52 to 2.96)     Type I diabetes   No  13185 (95.9)  1861 (92.0)  1.00 (referent)  .982   Yes  84 (0.6)  14 (0.7)  0.99 (0.55 to 1.80)    Atopic disorders   Any atopic disorder§   No  15601 (68.9)  2345 (66.4)  1.00 (referent)  <.001   Yes  6442 (28.5)  1107 (31.4)  0.87 (0.80 to 0.94)     Allergy∥   No  10790 (72.1)  1903 (70.0)  1.00 (referent)  .018   Yes  3309 (22.1)  590 (21.7)  0.88 (0.79 to 0.98)     Food allergy   No  12757 (85.2)  2180 (80.1)  1.00 (referent)  .007   Yes  988 (6.6)  171 (6.3)  0.79 (0.67 to 0.94)     Asthma   No  18448 (85.6)  2894 (83.9)  1.00 (referent)  .018   Yes  1698 (7.9)  260 (7.5)  0.85 (0.74 to 0.97)     Hay fever   No  12467 (71.3)  2086 (69.3)  1.00 (referent)  <.001   Yes  2958 (16.9)  521 (17.3)  0.82 (0.73 to 0.91)     Eczema   No  14766 (86.1)  2452 (82.4)  1.00 (referent)  .283   Yes  1605 (9.4)  318 (10.7)  1.08 (0.94 to 1.23)    * CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. § Atopic disorders include asthma, eczema, hay fever, or other allergies, excluding drug allergies. ∥ History of allergy excludes drug allergies, asthma, eczema, and hay fever. View Large Table 3. Sex-specific medical, lifestyle, family history, and occupational exposures and follicular lymphoma*   Male  Female      Controls†  Cases†      Controls†  Cases†          No. (%)  No. (%)  OR (95% CI)‡  P  No. (%)  No. (%)  OR (95% CI)‡  P  P heterogeneity  Medical conditions   Sjögren’s syndrome   No  —  —  —  —  3555 (97.5)  829 (96.4)  1.00 (referent)  .028  .0030   Yes  0  0  —  —  9 (0.2)  7 (0.8)  3.24 (1.19 to 8.80)  —  —   Any atopic disorder§   No  9660 (73.0)  1247 (69.9)  1.00 (referent)  .180  5941 (63.1)  1098 (62.9)  1.00 (referent)  <.001  .0587   Yes  3187 (24.1)  497 (27.8)  0.92 (0.82 to 1.04)    3255 (34.6)  610 (35.0)  0.82 (0.73 to 0.92)  —  —   Allergy||   No  6682 (76.8)  1049 (73.9)  1.00 (referent)  .596  4108 (65.5)  854 (65.7)  1.00 (referent)  .006  .0947   Yes  1556 (17.9)  255 (18.0)  0.96 (0.82 to 1.12)  —  1753 (28.0)  335 (25.8)  0.82 (0.70 to 0.94)  —  —   Food allergy   No  6704 (86.1)  1078 (79.7)  1.00 (referent)  .744  5141 (82.0)  1034 (79.5)  1.00 (referent)  .002  .0409   Yes  405 (5.2)  71 (5.3)  0.96 (0.73 to 1.25)  —  583 (9.3)  100 (7.7)  0.70 (0.56 to 0.88)  —  —   Asthma   No  10548 (86.3)  1468 (85.1)  1.00 (referent)  .112  7900 (84.6)  1426 (82.7)  1.00 (referent)  .079  .8354   Yes  909 (7.4)  120 (7.0)  0.85 (0.69 to 1.04)  —  789 (8.5)  140 (8.1)  0.84 (0.69 to 1.02)  —  —   Hay fever   No  7000 (72.9)  1031 (69.1)  1.00 (referent)  .256  5467 (69.3)  1055 (69.6)  1.00 (referent)  <.001  .0124   Yes  1475 (15.4)  249 (16.7)  0.91 (0.78 to 1.07)  —  1483 (18.8)  272 (18.0)  0.74 (0.63 to 0.86)  —  —   Eczema   No  8722 (88.2)  1272 (85.0)  1.00 (referent)  .583  6044 (83.3)  1180 (79.7)  1.00 (referent)  .321  .8818   Yes  737 (7.5)  125 (8.4)  1.06 (0.86 to 1.30)  —  868 (12.0)  193 (13.0)  1.09 (0.92 to 1.30)  —  —   Blood transfusion     No  6085 (75.1)  996 (77.3)  1.00 (referent)  .005  4657 (78.9)  1020 (81.5)  1.00 (referent)  .011  .4838   Yes  878 (10.8)  101 (7.8)  0.74 (0.59 to 0.92)  —  1088 (18.4)  196 (15.7)  0.80 (0.68 to 0.95)  —  —  Family history     NHL     No  8544 (86.2)  1095 (85.5)  1.00 (referent)  <.001  5572 (80.0)  1050 (83.6)  1.00 (referent)  .022  .385   Yes  132 (1.3)  52 (4.1)  2.54 (1.81 to 3.58)  —  146 (2.1)  44 (3.5)  1.54 (1.08 to 2.20)  —  —   NHL in male relatives     No  7003 (84.5)  923 (85.8)  1.00 (referent)  <.001  4756 (78.5)  889 (83.6)  1.00 (referent)  .777  .0263   Yes  54 (0.7)  23 (1.9)  2.73 (1.63 to 4.60)  —  59 (1.0)  12 (1.1)  1.10 (0.58 to 2.08)  —  —   NHL in female relatives     No  6661 (83.9)  906 (85.8)  1.00 (referent)  .008  4744 (78.3)  877 (82.5)  1.00 (referent)  .043  .5794   Yes  55 (0.7)  20 (1.9)  2.14 (1.26 to 3.65)  —  71 (1.2)  24 (2.3)  1.69 (1.04 to 2.75)  —  —  Lifestyle factors     BMI as a young adult (kg/m2)     Continuous  13228 (100.0)  1785 (100.0)  1.09 (0.94 to 1.27)  .275  9411 (100.0)  1745 (100.0)  1.25 (1.09 to 1.44)  .948  .0606   Physical activity     None  319 (9.5)  41 (6.8)  1.00 (referent)  .153  397 (10.7)  57 (7.4)  1.00 (referent)  .190  .7835   Mild  210 (6.2)  52 (8.6)  1.30 (0.81 to 2.07)  —  264 (7.1)  82 (10.7)  1.53 (1.02 to 2.30)  —  —   Moderate  424 (12.6)  84 (13.9)  1.06 (0.69 to 1.62)  —  510 (13.8)  125 (16.3)  1.16 (0.79 to 1.69)  —  —   Vigorous  1380 (41.0)  255 (42.1)  1.37 (0.95 to 1.98)  —  1657 (44.8)  330 (43.0)  1.19 (0.86 to 1.66)  —  —   History of cigarette smoking¶   No  3934 (30.8)  520 (31.0)  1.00 (referent)  .695  4945 (54.9)  744 (45.8)  1.00 (referent)  <.001  .0038   Yes  8047 (63.0)  987 (58.8)  0.98 (0.87 to 1.10)  —  3643 (40.4)  762 (46.9)  1.22 (1.09 to 1.37)  —  —   History of alcohol consumption   Nondrinker  1995 (17.1)  239 (16.1)  1.00 (referent)  .551  2282 (28.5)  404 (27.7)  1.00 (referent)  .002  .1969   Drinker (at least 1 drink per month)  7245 (62.2)  833 (56.3)  0.95 (0.80 to 1.12)  —  3749 (46.8)  630 (43.2)  0.79 (0.68 to 0.91)  —  —   Recreational sun exposure (h/wk)   Quartile 1 (low)  1003 (18.1)  195 (20.4)  1.00 (referent)  .034  1231 (23.3)  327 (28.4)  1.00 (referent)  .002  .8752   Quartile 2  1112 (20.1)  176 (18.4)  0.77 (0.61 to 0.96)  —  1220 (23.1)  245 (21.3)  0.77 (0.64 to 0.93)  —  —   Quartile 3  1121 (20.2)  177 (18.5)  0.74 (0.58 to 0.93)  —  1038 (19.7)  216 (18.8)  0.78 (0.64 to 0.95)  —  —   Quartile 4 (high)  1745 (31.5)  277 (29.0)  0.77 (0.62 to 0.95)  —  1238 (23.5)  228 (19.8)  0.70 (0.58 to 0.85)  —  —  Occupational exposures   Bakers and millers   No  6124 (93.7)  970 (98.1)  1.00 (referent)  .143  5222 (98.7)  1001 (99.5)  1.00 (referent)  .040  .6802   Yes  97 (1.5)  7 (0.7)  0.58 (0.27 to 1.27)  —  61 (1.2)  5 (0.5)  0.42 (0.17 to 1.06)  —  —   Chemists and chemical workers   No  5804 (92.8)  884 (95.7)  1.00 (referent)  .090  5090 (99.3)  989 (99.4)  1.00 (referent)  .968  .5551   Yes  136 (2.2)  28 (3.0)  1.46 (0.96 to 2.23)  —  31 (0.6)  6 (0.6)  1.02 (0.42 to 2.49)  —  —   Medical worker   No  5996 (91.7)  934 (94.4)  1.00 (referent)  .489  5124 (88.3)  1023 (87.7)  1.00 (referent)  .489  .3100   Yes  225 (3.4)  43 (4.3)  1.13 (0.80 to 1.59)  —  670 (11.6)  144 (12.3)  0.93 (0.77 to 1.14)  —  —   Medical doctor   No  5709 (93.7)  912 (97.1)  1.00 (referent)  .480  5515 (99.4)  1103 (99.5)  1.00 (referent)  .765  .9556   Yes  63 (1.0)  13 (1.4)  1.25 (0.68 to 2.32)  —  19 (0.3)  5 (0.5)  1.17 (0.42 to 3.24)  —  —   Spray-painter (except construction)   No  5465 (94.1)  790 (96.7)  1.00 (referent)  <.001   4854 (99.6)  936 (99.9)  1.00 (referent)  .111  .8588   Yes  22 (0.4)  13 (1.6)  3.83 (1.87 to 7.84)  —  7 (0.1)  0 (0.0)  —    —   University and higher education teachers     No  6063 (92.7)  959 (97.0)  1.00 (referent)  .011  5666 (97.7)  1145 (98.1)  1.00 (referent)  .066  .6104   Yes  154 (2.4)  16 (1.6)  0.53 (0.31 to 0.90)  —  120 (2.1)  21 (1.8)  0.65 (0.40 to 1.05)  —  —    Male  Female      Controls†  Cases†      Controls†  Cases†          No. (%)  No. (%)  OR (95% CI)‡  P  No. (%)  No. (%)  OR (95% CI)‡  P  P heterogeneity  Medical conditions   Sjögren’s syndrome   No  —  —  —  —  3555 (97.5)  829 (96.4)  1.00 (referent)  .028  .0030   Yes  0  0  —  —  9 (0.2)  7 (0.8)  3.24 (1.19 to 8.80)  —  —   Any atopic disorder§   No  9660 (73.0)  1247 (69.9)  1.00 (referent)  .180  5941 (63.1)  1098 (62.9)  1.00 (referent)  <.001  .0587   Yes  3187 (24.1)  497 (27.8)  0.92 (0.82 to 1.04)    3255 (34.6)  610 (35.0)  0.82 (0.73 to 0.92)  —  —   Allergy||   No  6682 (76.8)  1049 (73.9)  1.00 (referent)  .596  4108 (65.5)  854 (65.7)  1.00 (referent)  .006  .0947   Yes  1556 (17.9)  255 (18.0)  0.96 (0.82 to 1.12)  —  1753 (28.0)  335 (25.8)  0.82 (0.70 to 0.94)  —  —   Food allergy   No  6704 (86.1)  1078 (79.7)  1.00 (referent)  .744  5141 (82.0)  1034 (79.5)  1.00 (referent)  .002  .0409   Yes  405 (5.2)  71 (5.3)  0.96 (0.73 to 1.25)  —  583 (9.3)  100 (7.7)  0.70 (0.56 to 0.88)  —  —   Asthma   No  10548 (86.3)  1468 (85.1)  1.00 (referent)  .112  7900 (84.6)  1426 (82.7)  1.00 (referent)  .079  .8354   Yes  909 (7.4)  120 (7.0)  0.85 (0.69 to 1.04)  —  789 (8.5)  140 (8.1)  0.84 (0.69 to 1.02)  —  —   Hay fever   No  7000 (72.9)  1031 (69.1)  1.00 (referent)  .256  5467 (69.3)  1055 (69.6)  1.00 (referent)  <.001  .0124   Yes  1475 (15.4)  249 (16.7)  0.91 (0.78 to 1.07)  —  1483 (18.8)  272 (18.0)  0.74 (0.63 to 0.86)  —  —   Eczema   No  8722 (88.2)  1272 (85.0)  1.00 (referent)  .583  6044 (83.3)  1180 (79.7)  1.00 (referent)  .321  .8818   Yes  737 (7.5)  125 (8.4)  1.06 (0.86 to 1.30)  —  868 (12.0)  193 (13.0)  1.09 (0.92 to 1.30)  —  —   Blood transfusion     No  6085 (75.1)  996 (77.3)  1.00 (referent)  .005  4657 (78.9)  1020 (81.5)  1.00 (referent)  .011  .4838   Yes  878 (10.8)  101 (7.8)  0.74 (0.59 to 0.92)  —  1088 (18.4)  196 (15.7)  0.80 (0.68 to 0.95)  —  —  Family history     NHL     No  8544 (86.2)  1095 (85.5)  1.00 (referent)  <.001  5572 (80.0)  1050 (83.6)  1.00 (referent)  .022  .385   Yes  132 (1.3)  52 (4.1)  2.54 (1.81 to 3.58)  —  146 (2.1)  44 (3.5)  1.54 (1.08 to 2.20)  —  —   NHL in male relatives     No  7003 (84.5)  923 (85.8)  1.00 (referent)  <.001  4756 (78.5)  889 (83.6)  1.00 (referent)  .777  .0263   Yes  54 (0.7)  23 (1.9)  2.73 (1.63 to 4.60)  —  59 (1.0)  12 (1.1)  1.10 (0.58 to 2.08)  —  —   NHL in female relatives     No  6661 (83.9)  906 (85.8)  1.00 (referent)  .008  4744 (78.3)  877 (82.5)  1.00 (referent)  .043  .5794   Yes  55 (0.7)  20 (1.9)  2.14 (1.26 to 3.65)  —  71 (1.2)  24 (2.3)  1.69 (1.04 to 2.75)  —  —  Lifestyle factors     BMI as a young adult (kg/m2)     Continuous  13228 (100.0)  1785 (100.0)  1.09 (0.94 to 1.27)  .275  9411 (100.0)  1745 (100.0)  1.25 (1.09 to 1.44)  .948  .0606   Physical activity     None  319 (9.5)  41 (6.8)  1.00 (referent)  .153  397 (10.7)  57 (7.4)  1.00 (referent)  .190  .7835   Mild  210 (6.2)  52 (8.6)  1.30 (0.81 to 2.07)  —  264 (7.1)  82 (10.7)  1.53 (1.02 to 2.30)  —  —   Moderate  424 (12.6)  84 (13.9)  1.06 (0.69 to 1.62)  —  510 (13.8)  125 (16.3)  1.16 (0.79 to 1.69)  —  —   Vigorous  1380 (41.0)  255 (42.1)  1.37 (0.95 to 1.98)  —  1657 (44.8)  330 (43.0)  1.19 (0.86 to 1.66)  —  —   History of cigarette smoking¶   No  3934 (30.8)  520 (31.0)  1.00 (referent)  .695  4945 (54.9)  744 (45.8)  1.00 (referent)  <.001  .0038   Yes  8047 (63.0)  987 (58.8)  0.98 (0.87 to 1.10)  —  3643 (40.4)  762 (46.9)  1.22 (1.09 to 1.37)  —  —   History of alcohol consumption   Nondrinker  1995 (17.1)  239 (16.1)  1.00 (referent)  .551  2282 (28.5)  404 (27.7)  1.00 (referent)  .002  .1969   Drinker (at least 1 drink per month)  7245 (62.2)  833 (56.3)  0.95 (0.80 to 1.12)  —  3749 (46.8)  630 (43.2)  0.79 (0.68 to 0.91)  —  —   Recreational sun exposure (h/wk)   Quartile 1 (low)  1003 (18.1)  195 (20.4)  1.00 (referent)  .034  1231 (23.3)  327 (28.4)  1.00 (referent)  .002  .8752   Quartile 2  1112 (20.1)  176 (18.4)  0.77 (0.61 to 0.96)  —  1220 (23.1)  245 (21.3)  0.77 (0.64 to 0.93)  —  —   Quartile 3  1121 (20.2)  177 (18.5)  0.74 (0.58 to 0.93)  —  1038 (19.7)  216 (18.8)  0.78 (0.64 to 0.95)  —  —   Quartile 4 (high)  1745 (31.5)  277 (29.0)  0.77 (0.62 to 0.95)  —  1238 (23.5)  228 (19.8)  0.70 (0.58 to 0.85)  —  —  Occupational exposures   Bakers and millers   No  6124 (93.7)  970 (98.1)  1.00 (referent)  .143  5222 (98.7)  1001 (99.5)  1.00 (referent)  .040  .6802   Yes  97 (1.5)  7 (0.7)  0.58 (0.27 to 1.27)  —  61 (1.2)  5 (0.5)  0.42 (0.17 to 1.06)  —  —   Chemists and chemical workers   No  5804 (92.8)  884 (95.7)  1.00 (referent)  .090  5090 (99.3)  989 (99.4)  1.00 (referent)  .968  .5551   Yes  136 (2.2)  28 (3.0)  1.46 (0.96 to 2.23)  —  31 (0.6)  6 (0.6)  1.02 (0.42 to 2.49)  —  —   Medical worker   No  5996 (91.7)  934 (94.4)  1.00 (referent)  .489  5124 (88.3)  1023 (87.7)  1.00 (referent)  .489  .3100   Yes  225 (3.4)  43 (4.3)  1.13 (0.80 to 1.59)  —  670 (11.6)  144 (12.3)  0.93 (0.77 to 1.14)  —  —   Medical doctor   No  5709 (93.7)  912 (97.1)  1.00 (referent)  .480  5515 (99.4)  1103 (99.5)  1.00 (referent)  .765  .9556   Yes  63 (1.0)  13 (1.4)  1.25 (0.68 to 2.32)  —  19 (0.3)  5 (0.5)  1.17 (0.42 to 3.24)  —  —   Spray-painter (except construction)   No  5465 (94.1)  790 (96.7)  1.00 (referent)  <.001   4854 (99.6)  936 (99.9)  1.00 (referent)  .111  .8588   Yes  22 (0.4)  13 (1.6)  3.83 (1.87 to 7.84)  —  7 (0.1)  0 (0.0)  —    —   University and higher education teachers     No  6063 (92.7)  959 (97.0)  1.00 (referent)  .011  5666 (97.7)  1145 (98.1)  1.00 (referent)  .066  .6104   Yes  154 (2.4)  16 (1.6)  0.53 (0.31 to 0.90)  —  120 (2.1)  21 (1.8)  0.65 (0.40 to 1.05)  —  —  * BMI = body mass index; CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. § Atopic disorders include asthma, eczema, hay fever, or other allergies, excluding drug allergies. || History of allergy excludes drug allergies, asthma, eczema, and hay fever. ¶ Smoked longer than 6 months or more than 100 cigarettes in lifetime. View Large History of a blood transfusion was associated with a 22% lower risk of FL (Table 4). Reductions in FL risk were most notable for those who received a transfusion after age 55 years and within 40 years before the diagnosis of FL/interview. Positive hepatitis C virus serology was not linked with FL risk (OR = 1.28; 95% CI = 0.64 to 2.57, based on 11 exposed cases and 34 exposed controls). Neither use of oral contraceptives nor use of hormonal replacement therapy was linked with FL risk (data not shown). Table 4. History of blood transfusions and risk of follicular lymphoma*   Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Blood transfusion   No  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Yes  1966 (14.0)  297 (11.7)  0.78 (0.68 to 0.89)    Age at first transfusion   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <25 y  483 (3.4)  82 (3.2)  0.83 (0.65 to 1.06)     25–39 y  579 (4.1)  99 (3.9)  0.80 (0.64 to 1.00)     40–54 y  449 (3.2)  71 (2.8)  0.82 (0.63 to 1.06)     55 or older  455 (3.2)  45 (1.8)  0.62 (0.45 to 0.85)    Total number of blood transfusions   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   1 transfusion  1306 (9.3)  202 (8.0)  0.83 (0.71 to 0.97)     2 transfusions  361 (2.6)  47 (1.9)  0.63 (0.46 to 0.86)     3 or more transfusions  229 (1.6)  35 (1.4)  0.73 (0.50 to 1.05)     Transfusion, but number unknown  70 (0.5)  13 (0.5)  0.88 (0.48 to 1.62)    Number of years from 1st transfusion to date of diagnosis/interview     No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <20 y  878 (6.3)  121 (4.8)  0.77 (0.63 to 0.94)     20–39 y  748 (5.3)  118 (4.6)  0.76 (0.62 to 0.93)     ≥40 y  340 (2.4)  58 (2.3)  0.86 (0.64 to 1.14)    Blood transfusion before 1990   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Before 1990  1457 (10.4)  235 (9.3)  0.83 (0.71 to 0.96)     After 1990  404 (2.9)  44 (1.7)  0.62 (0.45 to 0.86)     Transfusion year unknown  105 (0.7)  18 (0.7)  0.68 (0.39 to 1.17)      Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Blood transfusion   No  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Yes  1966 (14.0)  297 (11.7)  0.78 (0.68 to 0.89)    Age at first transfusion   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <25 y  483 (3.4)  82 (3.2)  0.83 (0.65 to 1.06)     25–39 y  579 (4.1)  99 (3.9)  0.80 (0.64 to 1.00)     40–54 y  449 (3.2)  71 (2.8)  0.82 (0.63 to 1.06)     55 or older  455 (3.2)  45 (1.8)  0.62 (0.45 to 0.85)    Total number of blood transfusions   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   1 transfusion  1306 (9.3)  202 (8.0)  0.83 (0.71 to 0.97)     2 transfusions  361 (2.6)  47 (1.9)  0.63 (0.46 to 0.86)     3 or more transfusions  229 (1.6)  35 (1.4)  0.73 (0.50 to 1.05)     Transfusion, but number unknown  70 (0.5)  13 (0.5)  0.88 (0.48 to 1.62)    Number of years from 1st transfusion to date of diagnosis/interview     No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  .003   <20 y  878 (6.3)  121 (4.8)  0.77 (0.63 to 0.94)     20–39 y  748 (5.3)  118 (4.6)  0.76 (0.62 to 0.93)     ≥40 y  340 (2.4)  58 (2.3)  0.86 (0.64 to 1.14)    Blood transfusion before 1990   No transfusion  10742 (76.7)  2016 (79.4)  1.00 (referent)  <.001   Before 1990  1457 (10.4)  235 (9.3)  0.83 (0.71 to 0.96)     After 1990  404 (2.9)  44 (1.7)  0.62 (0.45 to 0.86)     Transfusion year unknown  105 (0.7)  18 (0.7)  0.68 (0.39 to 1.17)    * CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. View Large Family History of Hematopoietic Malignancies Participants with a first-degree relative with a history of NHL experienced approximately a twofold greater risk of FL than participants without such a history (Table 5), and risks were elevated in both male and female participants except females with affected male relatives (Table 3). Male and female participants with first-degree male, but not female, relatives with multiple myeloma had an increased risk of FL (Table 5). FL was not increased in participants with first-degree relatives with leukemia or Hodgkin lymphoma (Table 5). Table 5. Family history of hematopoietic malignancies and risk of follicular lymphoma*   Controls†  Cases†      First-degree family history  No. (%)  No. (%)  OR (95% CI)‡  P   Any hematologic malignancy   No  14346 (81.5)  2144 (81.3)  1.00 (referent)  <.001   Yes  769 (4.4)  198 (7.5)  1.48 (1.25 to 1.75)     Any hematologic malignancy in male relatives   No  11543 (80.5)  1759 (82.2)  1.00 (referent)  <.001   Yes  329 (2.3)  88 (4.1)  1.56 (1.22 to 2.00)     Any hematologic malignancy in female relatives     No  11560 (80.6)  1764 (82.5)  1.00 (referent)  .011   Yes  312 (2.2)  83 (3.9)  1.41 (1.09 to 1.82)     NHL   No  14116 (83.6)  2145 (84.6)  1.00 (referent)  <.001   Yes  278 (1.6)  96 (3.8)  1.99 (1.55 to 2.54)     NHL in male relatives   No  11759 (82.0)  1812 (84.7)  1.00 (referent)  .004   Yes  113 (0.8)  35 (1.6)  1.84 (1.24 to 2.73)     NHL in female relatives   No  11746 (81.9)  1803 (84.3)  1.00 (referent)  <.001   Yes  126 (0.9)  44 (2.1)  1.93 (1.35 to 2.75)     Multiple myeloma   No  11327 (81.9)  1795 (85.4)  1.00 (referent)  .040   Yes  41 (0.3)  16 (0.8)  1.93 (1.06 to 3.51)     Multiple myeloma in male relatives   No  8048 (76.6)  1338 (81.7)  1.00 (referent)  .003   Yes  16 (0.2)  11 (0.7)  3.64 (1.65 to 8.05)     Multiple myeloma in female relatives   No  8842 (92.1)  1550 (91.6)  1.00 (referent)  .870   Yes  25 (0.3)  5 (0.3)  0.92 (0.35 to 2.46)     Leukemia   No  13831 (92.4)  2129 (91.3)  1.00 (referent)  .853   Yes  402 (2.7)  65 (2.8)  0.98 (0.74 to 1.28)     Leukemia in male relatives   No  11634 (92.6)  1811 (91.5)  1.00 (referent)  .873   Yes  197 (1.6)  31 (1.6)  0.97 (0.66 to 1.43)     Leukemia in female relatives   No  11680 (92.9)  1815 (91.7)  1.00 (referent)  .933   Yes  151 (1.2)  27 (1.4)  1.02 (0.67 to 1.55)     HL   No  14149 (94.5)  2173 (93.2)  1.00 (referent)  .133   Yes  84 (0.6)  21 (0.9)  1.47 (0.90 to 2.40)     HL in male relatives   No  11288 (93.6)  1795 (92.3)  1.00 (referent)  .239   Yes  39 (0.3)  11 (0.6)  1.53 (0.77 to 3.04)     HL in female relatives   No  10316 (94.6)  1694 (93.6)  1.00 (referent)  .456   Yes  29 (0.3)  7 (0.4)  1.39 (0.60 to 3.23)      Controls†  Cases†      First-degree family history  No. (%)  No. (%)  OR (95% CI)‡  P   Any hematologic malignancy   No  14346 (81.5)  2144 (81.3)  1.00 (referent)  <.001   Yes  769 (4.4)  198 (7.5)  1.48 (1.25 to 1.75)     Any hematologic malignancy in male relatives   No  11543 (80.5)  1759 (82.2)  1.00 (referent)  <.001   Yes  329 (2.3)  88 (4.1)  1.56 (1.22 to 2.00)     Any hematologic malignancy in female relatives     No  11560 (80.6)  1764 (82.5)  1.00 (referent)  .011   Yes  312 (2.2)  83 (3.9)  1.41 (1.09 to 1.82)     NHL   No  14116 (83.6)  2145 (84.6)  1.00 (referent)  <.001   Yes  278 (1.6)  96 (3.8)  1.99 (1.55 to 2.54)     NHL in male relatives   No  11759 (82.0)  1812 (84.7)  1.00 (referent)  .004   Yes  113 (0.8)  35 (1.6)  1.84 (1.24 to 2.73)     NHL in female relatives   No  11746 (81.9)  1803 (84.3)  1.00 (referent)  <.001   Yes  126 (0.9)  44 (2.1)  1.93 (1.35 to 2.75)     Multiple myeloma   No  11327 (81.9)  1795 (85.4)  1.00 (referent)  .040   Yes  41 (0.3)  16 (0.8)  1.93 (1.06 to 3.51)     Multiple myeloma in male relatives   No  8048 (76.6)  1338 (81.7)  1.00 (referent)  .003   Yes  16 (0.2)  11 (0.7)  3.64 (1.65 to 8.05)     Multiple myeloma in female relatives   No  8842 (92.1)  1550 (91.6)  1.00 (referent)  .870   Yes  25 (0.3)  5 (0.3)  0.92 (0.35 to 2.46)     Leukemia   No  13831 (92.4)  2129 (91.3)  1.00 (referent)  .853   Yes  402 (2.7)  65 (2.8)  0.98 (0.74 to 1.28)     Leukemia in male relatives   No  11634 (92.6)  1811 (91.5)  1.00 (referent)  .873   Yes  197 (1.6)  31 (1.6)  0.97 (0.66 to 1.43)     Leukemia in female relatives   No  11680 (92.9)  1815 (91.7)  1.00 (referent)  .933   Yes  151 (1.2)  27 (1.4)  1.02 (0.67 to 1.55)     HL   No  14149 (94.5)  2173 (93.2)  1.00 (referent)  .133   Yes  84 (0.6)  21 (0.9)  1.47 (0.90 to 2.40)     HL in male relatives   No  11288 (93.6)  1795 (92.3)  1.00 (referent)  .239   Yes  39 (0.3)  11 (0.6)  1.53 (0.77 to 3.04)     HL in female relatives   No  10316 (94.6)  1694 (93.6)  1.00 (referent)  .456   Yes  29 (0.3)  7 (0.4)  1.39 (0.60 to 3.23)    * CI = confidence interval; HL = Hodgkin lymphoma; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. View Large Lifestyle Factors Risks for FL were increased in those who were overweight (OR = 1.49; 95% CI = 1.21 to 1.83) or obese (OR = 1.46; 95% CI = 0.98 to 2.17) as young adults and rose 15% with each five kg/m2 increase in young adult body mass index (BMI) (Table 6). No significant relationship was observed for usual adult BMI or weight. Greater adult height in males, but not females, was associated with increased risk of FL (data not shown). Table 6. Lifestyle factors and risk of follicular lymphoma*   Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  BMI, weight, and height   BMI as a young adult, kg/m2   15–<18.5  382 (2.5)  66 (2.5)  0.90 (0.67 to 1.19)     18.5–<22.5  2800 (18.1)  464 (17.8)  1.00 (referent)  .001   22.5–<25  1391 (9.0)  201 (7.7)  1.03 (0.85 to 1.24)     25–<30  838 (5.4)  164 (6.3)  1.49 (1.21 to 1.83)     30–50  172 (1.1)  34 (1.3)  1.46 (0.98 to 2.17)     Continuous (5kg/m2 increase in BMI)  5583  929  1.21 (1.09 to 1.35)  <.001   Usual adult BMI, kg/m2   15–<18.5  267 (1.6)  25 (0.9)  0.67 (0.44 to 1.03)     18.5–<22.5  3481 (20.3)  538 (19.4)  1.00 (referent)  .143   22.5–<25  4276 (25.0)  706 (25.5)  1.09 (0.96 to 1.23)     25–<30  6112 (35.7)  959 (34.6)  1.01 (0.89 to 1.14)     30–<35  1760 (10.3)  325 (11.7)  1.07 (0.91 to 1.25)     35–50  608 (3.6)  109 (3.9)  0.93 (0.73 to 1.17)     Continuous (5kg/m2 increase in BMI)  16504  2662  0.99 (0.95 to 1.04)  .735   Usual adult height   Quartile 1 (low)  4131 (24.1)  584 (21.1)  1.00 (referent)  .124   Quartile 2  3852 (22.5)  603 (21.8)  1.04 (0.92 to 1.18)     Quartile 3  4169 (24.3)  695 (25.1)  1.05 (0.93 to 1.19)     Quartile 4 (high)  4352 (25.4)  780 (28.1)  1.15 (1.02 to 1.30)     Usual adult weight   Quartile 1 (low)  4115 (24.0)  583 (21.0)  1.00 (referent)  .263   Quartile 2  3953 (23.1)  627 (22.6)  1.01 (0.89 to 1.14)     Quartile 3  4335 (25.3)  680 (24.5)  0.94 (0.83 to 1.07)     Quartile 4 (high)  4101 (24.0)  772 (27.8)  1.06 (0.94 to 1.20)     Physical activity   No  716 (10.1)  98 (7.1)  1.00 (referent)  . 055   Mild  474 (6.7)  134 (9.8)  1.41 (1.04 to 1.91)     Moderate  934 (13.2)  209 (15.2)  1.09 (0.83 to 1.45)     Vigorous  3037 (43.0)  585 (42.6)  1.26 (0.99 to 1.60)    Cigarette smoking   History of cigarette smoking§   No  8879 (40.7)  1264 (38.3)  1.00 (referent)  .046   Yes  11690 (53.6)  1749 (53.0)  1.09 (1.00 to 1.18)     Smoking status   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .009   Former smoker  6327 (29.0)  956 (29.0)  1.02 (0.93 to 1.12)     Current smoker  4829 (22.2)  743 (22.5)  1.19 (1.07 to 1.32)     Smoker, status unknown  534 (2.5)  50 (1.5)  1.05 (0.76 to 1.45)     Age started smoking cigarettes regularly   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .051   <14 y  1068 (4.9)  125 (3.8)  0.88 (0.72 to 1.07)     14–17 y  4348 (20.0)  710 (21.5)  1.12 (1.01 to 1.25)     18–19 y  2352 (10.8)  384 (11.6)  1.11 (0.97 to 1.26)     ≥20 y  3251 (14.9)  475 (14.4)  1.11 (0.99 to 1.25)     Smoker, age start unknown  671 (3.1)  55 (1.7)  0.94 (0.69 to 1.27)     Frequency of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .088   Smoker, 1–10 cigarettes/d  3910 (17.9)  603 (18.3)  1.09 (0.98 to 1.21)     Smoker, 11–20 cigarettes/d  4766 (21.9)  731 (22.1)  1.13 (1.02 to 1.25)     Smoker, 21–30 cigarettes/d  1248 (5.7)  189 (5.7)  1.09 (0.92 to 1.29)     Smoker, >30 cigarettes/d  1339 (6.1)  155 (4.7)  0.90 (0.75 to 1.09)     Smoker, cigarettes/day unknown  427 (2.0)  71 (2.2)  1.11 (0.84 to 1.45)     Continuous  20173  2946  1.00 (1.00 to 1.00)  .948   Duration of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .013   1–20 y  3917 (18.0)  534 (16.2)  1.02 (0.91 to 1.14)     21–30 y  2341 (10.7)  388 (11.8)  1.10 (0.97 to 1.25)     30–39 y  2392 (11.0)  417 (12.6)  1.13 (1.00 to 1.28)     ≥40 y  2749 (12.6)  391 (11.8)  1.18 (1.04 to 1.35)     Smoker, duration unknown  291 (1.3)  19 (0.6)  0.63 (0.39 to 1.01)     Continuous  20278  2994  1.00 (1.00 to 1.01)  .006   Lifetime cigarette exposure   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .150   1–10 pack-years  3473 (15.9)  501 (15.2)  1.06 (0.95 to 1.19)     11–20 pack-years  2272 (10.4)  341 (10.3)  1.06 (0.93 to 1.21)     21–35 pack-years  2369 (10.9)  409 (12.4)  1.18 (1.04 to 1.34)     ≥36 pack-years  3038 (13.9)  425 (12.9)  1.10 (0.97 to 1.25)     Smoker, pack-years unknown  538 (2.5)  73 (2.2)  0.93 (0.72 to 1.22)  Alcohol consumption   History of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .009   Drinker (at least 1 drink per month)  10994 (55.9)  1463 (49.8)  0.86 (0.77 to 0.96)     Alcohol consumption status   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .003   Former drinker  609 (3.1)  125 (4.3)  1.16 (0.91 to 1.49)     Current drinker  5010 (25.5)  723 (24.6)  0.88 (0.76 to 1.03)     Drinker, status unknown  5375 (27.3)  615 (20.9)  0.81 (0.69 to 0.95)     Age at first alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .023   <20 y  2281 (11.6)  316 (10.8)  0.92 (0.76 to 1.12)     20–29 y  2908 (14.8)  349 (11.9)  0.88 (0.74 to 1.05)     ≥30 y  768 (3.9)  117 (4.0)  1.07 (0.85 to 1.35)     Drinker, age start unknown  5037 (25.6)  681 (23.2)  0.80 (0.68 to 0.93)     Duration of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .078   1–20 y  1307 (6.6)  128 (4.4)  0.87 (0.69 to 1.11)     21–30 y  1085 (5.5)  164 (5.6)  0.90 (0.72 to 1.13)     30–39 y  1247 (6.3)  182 (6.2)  0.95 (0.76 to 1.17)     ≥40 y  1900 (9.7)  243 (8.3)  1.00 (0.81 to 1.22)     Drinker, duration unknown  5455 (27.7)  746 (25.4)  0.80 (0.69 to 0.93)     Servings of alcohol per week as an adult   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .017   <1 drink/wk  955 (4.9)  182 (6.2)  0.89 (0.74 to 1.08)     1–6 drinks/wk  3738 (19.0)  571 (19.4)  0.85 (0.75 to 0.97)     7–13 drinks/wk  2216 (11.3)  288 (9.8)  0.84 (0.72 to 0.99)     14–27 drinks/wk  2137 (10.9)  258 (8.8)  0.91 (0.77 to 1.08)     ≥28 drinks/wk or binge drinkers  1918 (9.8)  157 (5.3)  0.78 (0.64 to 0.96)     Drinker, drinks/week unknown  30 (0.2)  7 (0.2)  3.00 (1.25 to 7.23)     Grams of ethanol per week as an adult, consumed from any type of alcoholic beverage     Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .005   Quartile 1 (low)  2421 (12.3)  347 (11.8)  0.79 (0.68 to 0.92)     Quartile 2  2471 (12.6)  325 (11.1)  0.83 (0.71 to 0.97)     Quartile 3  2488 (12.6)  315 (10.7)  0.87 (0.75 to 1.02)     Quartile 4 (high)  2534 (12.9)  230 (7.8)  0.79 (0.66 to 0.94)     Drinker, grams consumed unknown  1080 (5.5)  246 (8.4)  1.33 (0.97 to 1.83)     Lifetime alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .007   1–100 kg  1444 (7.3)  182 (6.2)  0.75 (0.60 to 0.93)     101–200 kg  641 (3.3)  67 (2.3)  0.68 (0.51 to 0.91)     201–400 kg  651 (3.3)  96 (3.3)  1.05 (0.81 to 1.37)     >400 kg  759 (3.9)  75 (2.6)  0.85 (0.64 to 1.14)     Drinker, lifetime consumption unknown  7499 (38.1)  1043 (35.5)  0.90 (0.79 to 1.03)     Continuous  7886  1106  1.00 (1.00 to 1.00)  .893  Sun exposure   Total sun exposure (h/wk)   Quartile 1 (low)  1508 (18.7)  337 (20.6)  1.00 (referent)  .116   Quartile 2  1594 (19.8)  293 (18.0)  0.83 (0.69 to 0.99)     Quartile 3  1633 (20.3)  307 (18.8)  0.88 (0.73 to 1.05)     Quartile 4 (high)  1714 (21.3)  299 (18.3)  0.82 (0.69 to 0.99)     Recreational sun exposure (h/wk)   Quartile 1 (low)  2234 (20.6)  522 (24.8)  1.00 (referent)  <.001   Quartile 2  2332 (21.6)  421 (20.0)  0.77 (0.67 to 0.90)     Quartile 3  2159 (20.0)  393 (18.6)  0.77 (0.66 to 0.89)     Quartile 4 (high)  2983 (27.6)  505 (24.0)  0.74 (0.65 to 0.86)      Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  BMI, weight, and height   BMI as a young adult, kg/m2   15–<18.5  382 (2.5)  66 (2.5)  0.90 (0.67 to 1.19)     18.5–<22.5  2800 (18.1)  464 (17.8)  1.00 (referent)  .001   22.5–<25  1391 (9.0)  201 (7.7)  1.03 (0.85 to 1.24)     25–<30  838 (5.4)  164 (6.3)  1.49 (1.21 to 1.83)     30–50  172 (1.1)  34 (1.3)  1.46 (0.98 to 2.17)     Continuous (5kg/m2 increase in BMI)  5583  929  1.21 (1.09 to 1.35)  <.001   Usual adult BMI, kg/m2   15–<18.5  267 (1.6)  25 (0.9)  0.67 (0.44 to 1.03)     18.5–<22.5  3481 (20.3)  538 (19.4)  1.00 (referent)  .143   22.5–<25  4276 (25.0)  706 (25.5)  1.09 (0.96 to 1.23)     25–<30  6112 (35.7)  959 (34.6)  1.01 (0.89 to 1.14)     30–<35  1760 (10.3)  325 (11.7)  1.07 (0.91 to 1.25)     35–50  608 (3.6)  109 (3.9)  0.93 (0.73 to 1.17)     Continuous (5kg/m2 increase in BMI)  16504  2662  0.99 (0.95 to 1.04)  .735   Usual adult height   Quartile 1 (low)  4131 (24.1)  584 (21.1)  1.00 (referent)  .124   Quartile 2  3852 (22.5)  603 (21.8)  1.04 (0.92 to 1.18)     Quartile 3  4169 (24.3)  695 (25.1)  1.05 (0.93 to 1.19)     Quartile 4 (high)  4352 (25.4)  780 (28.1)  1.15 (1.02 to 1.30)     Usual adult weight   Quartile 1 (low)  4115 (24.0)  583 (21.0)  1.00 (referent)  .263   Quartile 2  3953 (23.1)  627 (22.6)  1.01 (0.89 to 1.14)     Quartile 3  4335 (25.3)  680 (24.5)  0.94 (0.83 to 1.07)     Quartile 4 (high)  4101 (24.0)  772 (27.8)  1.06 (0.94 to 1.20)     Physical activity   No  716 (10.1)  98 (7.1)  1.00 (referent)  . 055   Mild  474 (6.7)  134 (9.8)  1.41 (1.04 to 1.91)     Moderate  934 (13.2)  209 (15.2)  1.09 (0.83 to 1.45)     Vigorous  3037 (43.0)  585 (42.6)  1.26 (0.99 to 1.60)    Cigarette smoking   History of cigarette smoking§   No  8879 (40.7)  1264 (38.3)  1.00 (referent)  .046   Yes  11690 (53.6)  1749 (53.0)  1.09 (1.00 to 1.18)     Smoking status   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .009   Former smoker  6327 (29.0)  956 (29.0)  1.02 (0.93 to 1.12)     Current smoker  4829 (22.2)  743 (22.5)  1.19 (1.07 to 1.32)     Smoker, status unknown  534 (2.5)  50 (1.5)  1.05 (0.76 to 1.45)     Age started smoking cigarettes regularly   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .051   <14 y  1068 (4.9)  125 (3.8)  0.88 (0.72 to 1.07)     14–17 y  4348 (20.0)  710 (21.5)  1.12 (1.01 to 1.25)     18–19 y  2352 (10.8)  384 (11.6)  1.11 (0.97 to 1.26)     ≥20 y  3251 (14.9)  475 (14.4)  1.11 (0.99 to 1.25)     Smoker, age start unknown  671 (3.1)  55 (1.7)  0.94 (0.69 to 1.27)     Frequency of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .088   Smoker, 1–10 cigarettes/d  3910 (17.9)  603 (18.3)  1.09 (0.98 to 1.21)     Smoker, 11–20 cigarettes/d  4766 (21.9)  731 (22.1)  1.13 (1.02 to 1.25)     Smoker, 21–30 cigarettes/d  1248 (5.7)  189 (5.7)  1.09 (0.92 to 1.29)     Smoker, >30 cigarettes/d  1339 (6.1)  155 (4.7)  0.90 (0.75 to 1.09)     Smoker, cigarettes/day unknown  427 (2.0)  71 (2.2)  1.11 (0.84 to 1.45)     Continuous  20173  2946  1.00 (1.00 to 1.00)  .948   Duration of cigarette smoking   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .013   1–20 y  3917 (18.0)  534 (16.2)  1.02 (0.91 to 1.14)     21–30 y  2341 (10.7)  388 (11.8)  1.10 (0.97 to 1.25)     30–39 y  2392 (11.0)  417 (12.6)  1.13 (1.00 to 1.28)     ≥40 y  2749 (12.6)  391 (11.8)  1.18 (1.04 to 1.35)     Smoker, duration unknown  291 (1.3)  19 (0.6)  0.63 (0.39 to 1.01)     Continuous  20278  2994  1.00 (1.00 to 1.01)  .006   Lifetime cigarette exposure   Nonsmoker  8879 (40.7)  1264 (38.3)  1.00 (referent)  .150   1–10 pack-years  3473 (15.9)  501 (15.2)  1.06 (0.95 to 1.19)     11–20 pack-years  2272 (10.4)  341 (10.3)  1.06 (0.93 to 1.21)     21–35 pack-years  2369 (10.9)  409 (12.4)  1.18 (1.04 to 1.34)     ≥36 pack-years  3038 (13.9)  425 (12.9)  1.10 (0.97 to 1.25)     Smoker, pack-years unknown  538 (2.5)  73 (2.2)  0.93 (0.72 to 1.22)  Alcohol consumption   History of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .009   Drinker (at least 1 drink per month)  10994 (55.9)  1463 (49.8)  0.86 (0.77 to 0.96)     Alcohol consumption status   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .003   Former drinker  609 (3.1)  125 (4.3)  1.16 (0.91 to 1.49)     Current drinker  5010 (25.5)  723 (24.6)  0.88 (0.76 to 1.03)     Drinker, status unknown  5375 (27.3)  615 (20.9)  0.81 (0.69 to 0.95)     Age at first alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .023   <20 y  2281 (11.6)  316 (10.8)  0.92 (0.76 to 1.12)     20–29 y  2908 (14.8)  349 (11.9)  0.88 (0.74 to 1.05)     ≥30 y  768 (3.9)  117 (4.0)  1.07 (0.85 to 1.35)     Drinker, age start unknown  5037 (25.6)  681 (23.2)  0.80 (0.68 to 0.93)     Duration of alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .078   1–20 y  1307 (6.6)  128 (4.4)  0.87 (0.69 to 1.11)     21–30 y  1085 (5.5)  164 (5.6)  0.90 (0.72 to 1.13)     30–39 y  1247 (6.3)  182 (6.2)  0.95 (0.76 to 1.17)     ≥40 y  1900 (9.7)  243 (8.3)  1.00 (0.81 to 1.22)     Drinker, duration unknown  5455 (27.7)  746 (25.4)  0.80 (0.69 to 0.93)     Servings of alcohol per week as an adult   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .017   <1 drink/wk  955 (4.9)  182 (6.2)  0.89 (0.74 to 1.08)     1–6 drinks/wk  3738 (19.0)  571 (19.4)  0.85 (0.75 to 0.97)     7–13 drinks/wk  2216 (11.3)  288 (9.8)  0.84 (0.72 to 0.99)     14–27 drinks/wk  2137 (10.9)  258 (8.8)  0.91 (0.77 to 1.08)     ≥28 drinks/wk or binge drinkers  1918 (9.8)  157 (5.3)  0.78 (0.64 to 0.96)     Drinker, drinks/week unknown  30 (0.2)  7 (0.2)  3.00 (1.25 to 7.23)     Grams of ethanol per week as an adult, consumed from any type of alcoholic beverage     Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .005   Quartile 1 (low)  2421 (12.3)  347 (11.8)  0.79 (0.68 to 0.92)     Quartile 2  2471 (12.6)  325 (11.1)  0.83 (0.71 to 0.97)     Quartile 3  2488 (12.6)  315 (10.7)  0.87 (0.75 to 1.02)     Quartile 4 (high)  2534 (12.9)  230 (7.8)  0.79 (0.66 to 0.94)     Drinker, grams consumed unknown  1080 (5.5)  246 (8.4)  1.33 (0.97 to 1.83)     Lifetime alcohol consumption   Nondrinker  4277 (21.7)  643 (21.9)  1.00 (referent)  .007   1–100 kg  1444 (7.3)  182 (6.2)  0.75 (0.60 to 0.93)     101–200 kg  641 (3.3)  67 (2.3)  0.68 (0.51 to 0.91)     201–400 kg  651 (3.3)  96 (3.3)  1.05 (0.81 to 1.37)     >400 kg  759 (3.9)  75 (2.6)  0.85 (0.64 to 1.14)     Drinker, lifetime consumption unknown  7499 (38.1)  1043 (35.5)  0.90 (0.79 to 1.03)     Continuous  7886  1106  1.00 (1.00 to 1.00)  .893  Sun exposure   Total sun exposure (h/wk)   Quartile 1 (low)  1508 (18.7)  337 (20.6)  1.00 (referent)  .116   Quartile 2  1594 (19.8)  293 (18.0)  0.83 (0.69 to 0.99)     Quartile 3  1633 (20.3)  307 (18.8)  0.88 (0.73 to 1.05)     Quartile 4 (high)  1714 (21.3)  299 (18.3)  0.82 (0.69 to 0.99)     Recreational sun exposure (h/wk)   Quartile 1 (low)  2234 (20.6)  522 (24.8)  1.00 (referent)  <.001   Quartile 2  2332 (21.6)  421 (20.0)  0.77 (0.67 to 0.90)     Quartile 3  2159 (20.0)  393 (18.6)  0.77 (0.66 to 0.89)     Quartile 4 (high)  2983 (27.6)  505 (24.0)  0.74 (0.65 to 0.86)    * BMI = body mass index; CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. § Smoked longer than 6 months or more than 100 cigarettes in lifetime. View Large History of cigarette smoking was positively associated with FL risk in females but not males (P heterogeneity = .004; Table 3). Among women, a modest increase in risk of FL in those who ever smoked cigarettes was limited to current smokers, along with a significant positive trend for duration of smoking (data not shown). The trend in pack-years of smoking in women was more clearly related to duration than frequency of cigarettes smoked (data not shown). FL risks were reduced modestly in women, but not men, who ever drank alcohol, particularly current drinkers (Table 3), but there was no clear pattern with duration, number of drinks per week, or cumulative alcohol consumption (data not shown); we note, however, that many studies did not collect these data. A lower risk of FL was associated with increasing number of hours per week of recreational sun exposure for both men and women (Table 3) but was attenuated for total sun exposure hours (Table 6). FL risk, examined in females only, was not linked with hair dye use overall or by type, duration, or frequency (data not shown), except for a modest increase in those who used hair dyes before 1980 (OR = 1.40, 95% CI = 1.10 to 1.78). Occupational Factors Working or living on a farm was not associated with risk of FL (Table 7). Bakers and millers, and those working as university or higher education teachers, experienced reduced risks, whereas spray painters had increased risks of FL. A modest, nonsignificant increase in risk of FL was seen for those ever working as medical doctors, but those working more than 10 years in this occupation had a significantly elevated risk (OR = 2.06, 95% CI = 1.08 to 3.92, based on 38 cases vs 13 controls). Employment in other occupations was not associated with risk of FL (Table 7). Table 7. Occupational factors and risk of follicular lymphoma*   Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Farm residence and/or farming & related occupation   Ever lived on a farm   No  4779 (56.3)  822 (58.1)  1.00 (referent)  .592   Yes  3470 (40.9)  554 (39.1)  0.97 (0.85 to 1.09)     Ever worked on a farm   No  11675 (80.0)  1978 (83.0)  1.00 (referent)  .177   Yes  2717 (18.6)  371 (15.6)  0.92 (0.81 to 1.04)     Animal farm workers   No  11699 (94.8)  2092 (97.0)  1.00 (referent)  .985   Yes  316 (2.6)  52 (2.4)  1.00 (0.73 to 1.36)     Crop farm workers   No  11442 (92.7)  2069 (96.0)  1.00 (referent)  .994   Yes  573 (4.6)  75 (3.5)  1.00 (0.78 to 1.29)     Farm workers, any type   No  10583 (85.8)  1935 (89.7)  1.00 (referent)  .839   Yes  1432 (11.6)  209 (9.7)  0.98 (0.84 to 1.16)     Forestry worker   No  11227 (96.6)  2001 (99.1)  1.00 (referent)  .580   Yes  71 (0.6)  7 (0.3)  0.81 (0.37 to 1.77)     Meat worker   No  11907 (96.5)  2121 (98.4)  1.00 (referent)  .491   Yes  108 (0.9)  23 (1.1)  1.18 (0.74 to 1.88)    Other selected occupations   Bakers and millers   No/never  11857 (96.1)  2132 (98.9)  1.00 (referent)  .017   Yes  158 (1.3)  12 (0.6)  0.51 (0.28 to 0.93)     Chemists and chemical workers   No/never  11848 (96.0)  2110 (97.9)  1.00 (referent)  .156   Yes  167 (1.4)  34 (1.6)  1.33 (0.91 to 1.94)     Petroleum worker   No/never  10558 (96.9)  1905 (99.3)  1.00 (referent)  .518   Yes  18 (0.2)  2 (0.1)  0.63 (0.14 to 2.78)     Medical worker   No/never  11120 (90.1)  1957 (90.8)  1.00 (referent)  .752   Yes  895 (7.3)  187 (8.7)  0.97 (0.82 to 1.16)     Medical doctor   No/never  11921 (96.6)  2123 (98.5)  1.00 (referent)  .425   Yes  82 (0.7)  18 (0.8)  1.24 (0.74 to 2.10)     Spray-painter (except construction)   No/never  10596 (96.7)  1777 (98.4)  1.00 (referent)  .008   Yes  29 (0.3)  13 (0.7)  2.66 (1.36 to 5.24)     University and higher education teachers     No/never  11729 (95.1)  2104 (97.6)  1.00 (referent)  .001   Yes  274 (2.2)  37 (1.7)  0.58 (0.41 to 0.83)      Controls†  Cases†        No. (%)  No. (%)  OR (95% CI)‡  P  Farm residence and/or farming & related occupation   Ever lived on a farm   No  4779 (56.3)  822 (58.1)  1.00 (referent)  .592   Yes  3470 (40.9)  554 (39.1)  0.97 (0.85 to 1.09)     Ever worked on a farm   No  11675 (80.0)  1978 (83.0)  1.00 (referent)  .177   Yes  2717 (18.6)  371 (15.6)  0.92 (0.81 to 1.04)     Animal farm workers   No  11699 (94.8)  2092 (97.0)  1.00 (referent)  .985   Yes  316 (2.6)  52 (2.4)  1.00 (0.73 to 1.36)     Crop farm workers   No  11442 (92.7)  2069 (96.0)  1.00 (referent)  .994   Yes  573 (4.6)  75 (3.5)  1.00 (0.78 to 1.29)     Farm workers, any type   No  10583 (85.8)  1935 (89.7)  1.00 (referent)  .839   Yes  1432 (11.6)  209 (9.7)  0.98 (0.84 to 1.16)     Forestry worker   No  11227 (96.6)  2001 (99.1)  1.00 (referent)  .580   Yes  71 (0.6)  7 (0.3)  0.81 (0.37 to 1.77)     Meat worker   No  11907 (96.5)  2121 (98.4)  1.00 (referent)  .491   Yes  108 (0.9)  23 (1.1)  1.18 (0.74 to 1.88)    Other selected occupations   Bakers and millers   No/never  11857 (96.1)  2132 (98.9)  1.00 (referent)  .017   Yes  158 (1.3)  12 (0.6)  0.51 (0.28 to 0.93)     Chemists and chemical workers   No/never  11848 (96.0)  2110 (97.9)  1.00 (referent)  .156   Yes  167 (1.4)  34 (1.6)  1.33 (0.91 to 1.94)     Petroleum worker   No/never  10558 (96.9)  1905 (99.3)  1.00 (referent)  .518   Yes  18 (0.2)  2 (0.1)  0.63 (0.14 to 2.78)     Medical worker   No/never  11120 (90.1)  1957 (90.8)  1.00 (referent)  .752   Yes  895 (7.3)  187 (8.7)  0.97 (0.82 to 1.16)     Medical doctor   No/never  11921 (96.6)  2123 (98.5)  1.00 (referent)  .425   Yes  82 (0.7)  18 (0.8)  1.24 (0.74 to 2.10)     Spray-painter (except construction)   No/never  10596 (96.7)  1777 (98.4)  1.00 (referent)  .008   Yes  29 (0.3)  13 (0.7)  2.66 (1.36 to 5.24)     University and higher education teachers     No/never  11729 (95.1)  2104 (97.6)  1.00 (referent)  .001   Yes  274 (2.2)  37 (1.7)  0.58 (0.41 to 0.83)    * CI = confidence interval; OR = odds ratio. † The counts do not add up to the total # of cases/controls due to data missing by design or report. ‡ OR (95% CI) adjusted for age, sex, race/ethnicity, and study. View Large Risks According to Race/Ethnicity, Source of Population, and Region For the associations observed in all FL patients, patterns were generally similar by race/ethnicity, except for increased risks for any atopic disorder and hay fever, and a trend in recreational sun exposure in Asians (Supplementary Table 1, available online). Comparison of FL risks in population-based versus hospital-based studies revealed that the findings were mainly driven by the former (Supplementary Table 2, available online). Risks according to region were mostly consistent, although risks for combined and individual atopic allergic disorders showed greater reductions in risk in Australia than in Europe or North America (Supplementary Table 3, available online). Discussion In the largest pooled analysis of case–control studies focused on FL and the first to assess a broad range of exposures simultaneously, most risk factors examined were not associated with risk of FL specifically, except for a few mostly modest or sex-specific relationships. We found novel associations with FL risk for certain occupations, including reduced risk in bakers/millers, and university/higher education teachers, and increased risk in spray painters. With our larger number of studies and strong evidence for independence in multivariate models, this analysis extends earlier InterLymph observations of an increased risk of FL for those with Sjögren syndrome (37), a first-degree relative with a history of NHL (17), and reduced risks among those with allergic diseases (24) and greater recreational hours spent per week in the sun (30). Increased FL risks among current cigarette smokers, in conjunction with a positive trend with duration of smoking, were restricted to women, as were the significantly reduced risks of FL in those with a history of hay fever or food allergy. We also found a reduced risk of FL with a history of blood transfusion. Although meta-analyses of all NHL (5,38,39) found a modest up to 10% increase in risk among those who had worked in farming, few studies have evaluated occupational risks for FL specifically. A pooled analysis of studies in Kansas and Nebraska found increases in FL risk in association with employment in agriculture or farming that were not statistically significant (40). Two studies with stratification of cases by chromosomal translocation in t(14;18) found associations with certain agricultural pesticides (but not farming per se) for t(14;18)-positive NHL, but not for t(14;18)-negative cases (41,42). Although t(14;18) is not specific to FL, this molecular feature occurs in 70%–90% of FL cases compared with 20%–30% of diffuse large B-cell lymphoma cases and 5%–10% of other NHL subtypes (31). It is possible that FL may be associated with specific exposures in farming, such as poultry (43), which were not characterized in our assessment of farming as an occupation. Unfortunately, molecular characterization according to t(14;18) status was not available for the majority of the FL cases in this pooled study. Our finding of an increased risk of FL in spray painters is consistent with previous reports finding that NHL risk is elevated among those working in the occupation of painter and those working with solvents used in paint product formulations (44,45). The decreased risk of FL in university/higher education teachers is not consistent with the results from a meta-analysis showing increased risk among teachers (38), but the meta-analysis included teachers at all levels, whereas our finding was restricted to university/higher education teachers. The meta-analysis did not provide separate estimates of risk for university/higher education teachers. This, and our findings for medical doctors and for bakers/millers, should be further investigated in occupational epidemiologic studies to evaluate specific exposures. Reasons for the female-specific modest increase in FL risk associated with cigarette smoking are not clear, but these results are consistent with those of a recent meta-analysis of 24 studies which reported a 43% increased risk of FL in female smokers compared with nonsmokers, but no association of smoking status, duration, or intensity in males (46). Findings from cohort studies (11,27,47) also provide some support for this association. An association of cigarette smoking with FL is biologically plausible in that increased rates of t(14;18) translocations have been observed in heavy smokers (48). The current analysis, with more than twice as many studies and threefold more FL cases than our earlier InterLymph consortium analysis (13), provides more precise estimates of FL risk (20% increase in our analysis of “current” smokers vs 31% in our earlier assessment), and identified a similar significant relationship with increasing duration of smoking, establishing that this association is not likely to be confounded by alcohol, BMI, or a variety of other risk factors evaluated here. Our finding of an excess risk of FL associated with Sjögren’s syndrome is consistent with our earlier InterLymph pooled analysis (12 studies, 12982 NHL cases (14)) in which Sjögren’s syndrome was the only autoimmune disease associated with FL. We found reductions in risk of FL in relation to history of allergic conditions except for eczema. These findings are consistent with our earlier pooled analysis (2842 FL) (24). However, this first sex-specific assessment revealed that the significant reductions in risks for any allergy, hay fever, and food allergy were restricted to females. Our findings of increased risks for atopic disorders and hay fever in Asian participants require further evaluation. Our results also mirror those from our previous pooled InterLymph analysis (1703 FL) (17) that found a twofold increased FL risk among participants with a first-degree relative with a history of NHL, with risks elevated in both male and female participants, except females with affected male relatives (17). Our data also support findings from other studies of a stronger familial association of NHL risk in male relatives, which is consistent for FL and other lymphoma subtypes (49–51). The present study reveals a reduced risk of FL only in current drinkers who were female, but not related to the frequency or duration of their alcohol consumption. In our earlier InterLymph pooled evaluation based on nine studies (1307 FL) (26), we observed a reduced risk of FL associated with alcohol consumption, particularly in current drinkers, but with no evidence of dose–response relationships with frequency or duration of alcohol use. Prospective studies have shown mixed results with moderate (52–56) and heavy (27) alcohol intake associated with reductions in FL risk ranging from 23% to 41% in some studies, but not in others (57–59). One cohort study found an elevated risk of FL among women who were former alcohol drinkers (60). It has been postulated that these findings may be due to effects of alcohol in modulating immune function (61) but because immune deficiency has not been shown to be important for FL risk, chronic inflammation may be a potential biologic mechanism, although alcohol has many other biologic effects. An alternative explanation is that the association is not causal but may reflect differences in other characteristics between alcohol drinkers and nondrinkers. In our previous InterLymph evaluation of sun exposure (1642 FL) (30), we found a downward trend in risk with increasing total recreational sun exposure, particularly for exposures at 18–40 years of age and in the 10 years before diagnosis for all B-cell lymphomas and for FL, but no association with occupational sun exposure. This inverse association may be due partly to effects on the immune function from sun exposure (62), vitamin D production (63), or chance. A cohort study examining ambient residential ultraviolet radiation among California teachers showed null findings for FL (28). To our knowledge, the current study is the first to find that persons with a history of blood transfusion experienced a modestly reduced risk of FL. Blood transfusion (which suppresses cellular immunity, includes transfer of allogeneic cells, and may transmit infectious and chemical agents) has been associated with increased risk of all NHL in some (15,64–66), but not all studies (67–72). Limited data on the role of transfusions in FL suggest no risk (73–76) or a modest increase in risk (8,15). Cerhan and colleagues (15) have suggested that transfusions may be a marker for underlying medical conditions rather than directly associated with NHL or its subtypes. The association of overweight and obesity in early adulthood with FL risk is strengthened by the significant positive dose–response trend of early adult BMI with FL risk. However, most cohort studies (7,56,58,77–82), with one exception (83), found no relationship of early adult weight or BMI with FL, although many of these studies included relatively small numbers of FL cases. Our finding of a relationship between greater adult height in males, but not females, in relation to FL is likely a chance finding since most cohort studies (56,58,78–82) reported no relationship of height in men or women with FL except for three (20,77,83) that found a positive relationship in women. This pooled analysis is the first and largest multivariate assessment of a broad range of putative risk factors for FL. Other strengths include assessment of effect modification (particularly gender) and confounding. The systematic nature of the subtype evaluation using the WHO classification, exposure assessment by standardized questionnaires, population-based design for most of the studies, along with careful efforts to harmonize the variables included in the pooled analyses, represent additional strengths. Limitations include the self-reported nature of the data collected, the difficulty of using retrospectively collected information, reliance on job titles instead of specific occupational exposures, the limited types of exposures evaluated, and lack of comprehensive assessment of many of the individual putative risk factors, multiple comparisons, and absence of assessment of some variables for all studies. Sex-specific associations could be due to chance or unexplained bias, although it is possible that such associations may reflect genetic variation, hormonal exposure, or occupational exposures. Other limitations include lack of independent evaluation of exposures and the potential for recall bias. Some findings (eg, female-specific associations with alcohol consumption, the inverse association with history of blood transfusions or the relationship with BMI in early adulthood) may be due to chance. In conclusion, the majority of the factors evaluated were not associated with risk of FL. As noted above, associations with blood transfusion and BMI in early adulthood are inconsistent with prior studies. The sex-specific findings for cigarette smoking and allergic disorders, as well as the associations with some occupations, deserve further evaluation. Although this study does not identify risk factors that explain much of FL occurrence, the few relationships observed do provide clues suggesting a complex multifactorial etiology. Funding This pooled analysis was supported by the Intramural Research Program of the National Cancer Institute/National Institutes of Health and National Cancer Institute/National Institutes of Health (R01 CA14690, U01 CA118444, and R01 CA92153-S1). InterLymph annual meetings during 2010–2013 were supported by the Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute/National Institutes of Health (2010–2013); Lymphoma Coalition (2010–2013); National Institutes of Health Office of Rare Diseases Research (2010); National Cancer Institute/National Institutes of Health (R13 CA159842 01) (2011); University of Cagliari, Provincial Administration of Cagliari, Banca di Credito Sardo, and Consorzio Industriale Sardo, Italy (2011); Intramural Research Program of the National Cancer Institute/National Institutes of Health (2012); and Faculté de Médecine de Dijon, Institut de Veille Sanitaire, Registre des hémopathies malignes de Côte d’Or, INSERM, Institut National du Cancer, Université de Bourgogne, Groupe Ouest Est d’Etude des Leucémies et Autres Maladies du Sang (GOELAMS), l’Institut Bergonié, The Lymphoma Study Association (LYSA), Registre Régional des Hémopathies de Basse Normandie, and the City of Dijon, France (2013). Meeting space at the 2013 Annual Meeting of the American Association for Cancer Research (AACR) was provided by the Molecular Epidemiology Group (MEG) of the AACR. Individual studies were supported by: the Canadian Institutes for Health Research (CIHR), Canadian Cancer Society, and Michael Smith Foundation for Health Research (British Columbia); Intramural Research Program of the National Cancer Institute/National Institutes of Health (Iowa/Minnesota); National Cancer Institute/National Institutes of Health (N01-CP-ES-11027) (Kansas); National Cancer Institute/National Institutes of Health (R01 CA50850) (Los Angeles); National Cancer Institute/National Institutes of Health (R01 CA92153 and P50 CA97274), Lymphoma Research Foundation (164738), and the Henry J. Predolin Foundation (Mayo Clinic); Intramural Research Program of the National Cancer Institute/National Institutes of Health and Public Health Service (contracts N01-PC-65064, N01-PC-67008, N01-PC-67009, N01-PC-67010, and N02-PC-71105) (NCI-SEER); National Cancer Institute/National Institutes of Health (R01CA100555 and R03CA132153) and American Institute for Cancer Research (99B083) (Nebraska [newer]); National Cancer Institute/National Institutes of Health (N01-CP-95618) and State of Nebraska Department of Health (LB-506) (Nebraska [older]); National Cancer Institute/National Institutes of Health (R01CA45614, RO1CA154643-01A1, and R01CA104682) (UCSF1); National Cancer Institute/National Institutes of Health (CA143947, CA150037, R01CA087014, R01CA104682, RO1CA122663, and RO1CA154643-01A1) (UCSF2); National Heart Lung and Blood Institute/National Institutes of Health (hematology training grant award T32 HL007152), National Center for Research Resources/National Institutes of Health (UL 1 RR024160), and National Cancer Institute/National Institutes of Health (K23 CA102216 and P50 CA130805) (University of Rochester); National Cancer Institute/National Institutes of Health (CA62006 and CA165923) (Yale); Association pour la Recherche contre le Cancer, Fondation de France, AFSSET, and a donation from Faberge employees (Engela); European Commission (QLK4-CT-2000-00422 and FOOD-CT-2006-023103), Spanish Ministry of Health (CIBERESP, PI11/01810, RCESP C03/09, RTICESP C03/10, and RTIC RD06/0020/0095), Rio Hortega (CM13/00232), Agència de Gestió d’Ajuts Universitaris i de Recerca–Generalitat de Catalunya (Catalonian Government, 2009SGR1026), National Institutes of Health (contract NO1-CO-12400), Italian Ministry of Education, University and Research (PRIN 2007 prot. 2007WEJLZB, PRIN 2009 prot. 20092ZELR2), Italian Association for Cancer Research (IG grant 11855/2011); Federal Office for Radiation Protection (StSch4261 and StSch4420), José Carreras Leukemia Foundation (DJCLS-R04/08), German Federal Ministry for Education and Research (BMBF-01-EO-1303), Health Research Board, Ireland and Cancer Research Ireland, and Czech Republic MH CZ – DRO (MMCI, 00209805) (EpiLymph); National Cancer Institute/National Institutes of Health (CA51086), European Community (Europe Against Cancer Programme), and Italian Alliance Against Cancer (Lega Italiana per la Lotta contro i Tumori) (Italy, multicenter); Italian Association for Cancer Research (Italy, Aviano-Milan); Italian Association for Cancer Research (Italy, Aviano-Naples); Swedish Cancer Society (2009/659), Stockholm County Council (20110209), Strategic Research Program in Epidemiology at Karolinska Institut, Swedish Cancer Society (02 6661), Danish Cancer Research Foundation, Lundbeck Foundation (R19-A2364), Danish Cancer Society (DP 08-155), National Cancer Institute/National Institutes of Health (5R01 CA69669-02), and Plan Denmark (SCALE); Leukaemia & Lymphoma Research, UK; and Australian National Health and Medical Research Council (ID990920), Cancer Council NSW, and University of Sydney Faculty of Medicine (New South Wales). 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JNCI MonographsOxford University Press

Published: Aug 30, 2014

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