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

Martha S. Linet; Claire M. Vajdic; Lindsay M. Morton; Anneclaire J. de Roos; Christine F. Skibola; Paolo Boffetta; James R. Cerhan; Christopher R. Flowers; Silvia de Sanjosé; Alain Monnereau; Pierluigi Cocco; Jennifer L. Kelly; Alexandra G. Smith; Dennis D. Weisenburger; Christina A. Clarke; Aaron Blair; Leslie Bernstein; Tongzhang Zheng; Lucia Miligi; Jacqueline Clavel; Yolanda Benavente; Brian C. H. Chiu

doi:10.1093/jncimonographs/lgu006

Linet, Martha S.;Vajdic, Claire M.;Morton, Lindsay M.;de Roos, Anneclaire J.;Skibola, Christine F.;Boffetta, Paolo;Cerhan, James R.;Flowers, Christopher R.;de Sanjosé, Silvia;Monnereau, Alain;Cocco, Pierluigi;Kelly, Jennifer L.;Smith, Alexandra G.;Weisenburger, Dennis D.;Clarke, Christina A.;Blair, Aaron;Bernstein, Leslie;Zheng, Tongzhang;Miligi, Lucia;Clavel, Jacqueline;Benavente, Yolanda;Chiu, Brian C. H.

2014-08-30 00:00:00

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

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Publisher: Oxford University Press
Copyright: Published by Oxford University Press 2014.
ISSN: 1052-6773
eISSN: 1745-6614
DOI: 10.1093/jncimonographs/lgu006
pmid: 25174024
Publisher site: See Article on Publisher Site

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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 Lymphoma: The InterLymph Non-Hodgkin Lymphoma Subtypes Project