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Epidemiology

Anthropometric traits and risk of multiple myeloma: a pooled prospective analysis

British Journal of Cancer volume 127, pages 1296–1303 (2022)Cite this article

Subjects

Abstract

Background

Obesity is a risk factor for multiple myeloma (MM), yet results of prior studies have been mixed regarding the importance of early and/or later adult obesity; other measures of body composition have been less well studied.

Methods

We evaluated associations of early adult (ages 18–21) and usual adult body mass index (BMI), waist circumference, and predicted fat mass with MM by pooling data from six U.S. prospective cohort studies comprising 544,016 individuals and 2756 incident diagnoses over 20–37 years of follow-up. We used Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations, adjusted for age and other risk factors.

Results

Each 5 kg/m2 increase in usual adult BMI was associated with a 10% increased risk of MM (HR: 1.10; 95% CI: 1.05–1.15). Positive associations were also noted for early adult BMI (HR per 5 kg/m2: 1.14; 95% CI: 1.04–1.25), height (HR per 10 cm: 1.28; 95% CI: 1.20–1.37), waist circumference (HR per 15 cm: 1.09; 95% CI: 1.00–1.19), and predicted fat mass (HR per 5 kg: 1.06; 95% CI: 1.01–1.11).

Conclusions

These findings highlight the importance of avoidance of overweight/obesity and excess adiposity throughout adulthood as a potential MM risk-reduction strategy.

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Data availability

Data will be made available upon reasonable request to the senior author.

References

  1. Lauby-Secretan B, Scoccianti C, Loomis D, Grosse Y, Bianchini F, Straif K, et al. Body fatness and cance—viewpoint of the IARC Working Group. N Engl J Med. 2016;375:794–8.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Noone AM, Howlader N, Krapcho M, Miller D, Brest A, Yu M, et al. SEER cancer statistics review, 1975-2015. Bethesda, MD: National Cancer Institute. Bethesda, MD; 2018.

  3. SEER*Explorer: an interactive website for SEER cancer statistics [Internet]. Surveillance Research Program, National Cancer Institute. [Cited 2021 April 15]. https://seer.cancer.gov/explorer/.

  4. Fryar CD, Carroll MD, Ogden C. Prevalence of overweight, obesity, and extreme obesity among adults: United States, trends 1960–1962 through 2009–2010. Hyattsville, MD: National Center for Health Statistics; 2012.

  5. Abar L, Sobiecki JG, Cariolou M, Nanu N, Vieira AR, Stevens C, et al. Body size and obesity during adulthood, and risk of lympho-haematopoietic cancers: an update of the WCRF-AICR systematic review of published prospective studies. Ann Oncol. 2019;30:528–41.

    Article  CAS  PubMed  Google Scholar 

  6. Pylypchuk RD, Schouten LJ, Goldbohm RA, Schouten HC, van den Brandt PA. Body mass index, height, and risk of lymphatic malignancies: a prospective cohort study. Am J Epidemiol. 2009;170:297–307.

    Article  PubMed  Google Scholar 

  7. Birmann BM, Andreotti G, De Roos AJ, Camp NJ, Chiu BCH, Spinelli JJ, et al. Young adult and usual adult body mass index and multiple myeloma risk: a pooled analysis in the International Multiple Myeloma Consortium (IMMC). Cancer Epidemiol Biomark Prev. 2017;26:876–85.

    Article  Google Scholar 

  8. Marinac CR, Birmann BM, Lee IM, Rosner BA, Townsend MK, Giovannucci E, et al. Body mass index throughout adulthood, physical activity, and risk of multiple myeloma: a prospective analysis in three large cohorts. Br J Cancer. 2018;118:1013–9.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hofmann JN, Moore SC, Lim U, Park Y, Baris D, Hollenbeck AR, et al. Body mass index and physical activity at different ages and risk of multiple myeloma in the NIH-AARP diet and health study. Am J Epidemiol. 2013;177:776–86.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Blair CK, Cerhan JR, Folsom AR, Ross JA. Anthropometric characteristics and risk of multiple myeloma. Epidemiology. 2005;16:691–4.

    Article  PubMed  Google Scholar 

  11. Britton JA, Khan AE, Rohrmann S, Becker N, Linseisen J, Nieters A, et al. Anthropometric characteristics and non-Hodgkin’s lymphoma and multiple myeloma risk in the European Prospective Investigation into Cancer and Nutrition (EPIC). Haematologica. 2008;93:1666–77.

    Article  PubMed  Google Scholar 

  12. Lu Y, Sullivan-Halley J, Henderson KD, Ma H, Horn-Ross PL, Reynolds P, et al. Anthropometric characteristics and multiple myeloma risk. Epidemiology. 2010;21:272–3.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Hagstrom H, Andreasson A, Carlsson AC, Jerkeman M, Carlsten M. Body composition measurements and risk of hematological malignancies: a population-based cohort study during 20 years of follow-up. PLoS ONE. 2018;13:e0202651.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Marinac CR, Suppan CA, Giovannucci E, Song M, Kvaerner AS, Townsend MK, et al. Elucidating under-studied aspects of the link between obesity and multiple myeloma: weight pattern, body shape trajectory, and body fat distribution. JNCI cancer Spectr. 2019;3:pkz044.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Wang SS, Voutsinas J, Chang ET, Clarke CA, Lu Y, Ma H, et al. Anthropometric, behavioral, and female reproductive factors and risk of multiple myeloma: a pooled analysis. Cancer Causes Control. 2013;24:1279–89.

    Article  PubMed  PubMed Central  Google Scholar 

  16. U.S. Department of Health and Human Services, Plan and Operation of the Third National Health and Nutrition Examination Survey, 1988-94. Hyattsville, MD National Center for Health Statistics 1994;Vital and Health Statistics Series 1, No. 32. DHHS Publication PHS 94-1308.

  17. Lee DH, Keum N, Hu FB, Orav EJ, Rimm EB, Sun Q, et al. Development and validation of anthropometric prediction equations for lean body mass, fat mass and percent fat in adults using the National Health and Nutrition Examination Survey (NHANES) 1999–2006. Br J Nutr. 2017;118:858–66.

  18. Smith-Warner SA, Spiegelman D, Ritz J, Albanes D, Beeson WL, Bernstein L, et al. Methods for pooling results of epidemiologic studies: the Pooling Project of Prospective Studies of Diet and Cancer. Am J Epidemiol. 2006;163:1053–64.

    Article  PubMed  Google Scholar 

  19. Samuelsen SO. A pseudolikelihood approach to analysis of nested case-control studies. Biometrika. 1997;84:379–94.

    Article  Google Scholar 

  20. Stoer NC, Samuelsen SO. Inverse probability weighting in nested case-control studies with additional matching-a simulation study. Stat Med. 2013;32:5328–39.

    Article  PubMed  Google Scholar 

  21. Birmann BM, Giovannucci E, Rosner B, Anderson KC, Colditz GA. Body mass index, physical activity, and risk of multiple myeloma. Cancer Epidemiol Biomark Prev. 2007;16:1474–8.

    Article  Google Scholar 

  22. Teras LR, Kitahara CM, Birmann BM, Hartge PA, Wang SS, Robien K, et al. Body size and multiple myeloma mortality: a pooled analysis of 20 prospective studies. Br J Haematol. 2014;166:667–76.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Psaltopoulou T, Sergentanis TN, Ntanasis-Stathopoulos I, Tzanninis IG, Riza E, Dimopoulos MA. Anthropometric characteristics, physical activity and risk of hematological malignancies: a systematic review and meta-analysis of cohort studies. Int J Cancer. 2019;145:347–59.

    Article  CAS  PubMed  Google Scholar 

  24. Wallin A, Larsson SC. Body mass index and risk of multiple myeloma: a meta-analysis of prospective studies. Eur J Cancer. 2011;47:1606–15.

    Article  PubMed  Google Scholar 

  25. Avgerinos KI, Spyrou N, Mantzoros CS, Dalamaga M. Obesity and cancer risk: emerging biological mechanisms and perspectives. Metabolism. 2019;92:121–35.

    Article  CAS  PubMed  Google Scholar 

  26. Hosgood HD, Gunter MJ, Murphy N, Rohan TE, Strickler HD. The relation of obesity-related hormonal and cytokine levels with multiple myeloma and non-Hodgkin lymphoma. Front Oncol. 2018;8:103.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Costas L, Lambert BH, Birmann BM, Moysich KB, De Roos AJ, Hofmann JN, et al. A pooled analysis of reproductive factors, exogenous hormone use, and risk of multiple myeloma among women in the International Multiple Myeloma Consortium. Cancer Epidemiol Biomark Prev. 2016;25:217–21.

    Article  CAS  Google Scholar 

  28. Kanda J, Matsuo K, Inoue M, Iwasaki M, Sawada N, Shimazu T, et al. Association of anthropometric characteristics with the risk of malignant lymphoma and plasma cell myeloma in a Japanese population: a population-based cohort study. Cancer Epidemiol Biomark Prev. 2010;19:1623–31.

    Article  CAS  Google Scholar 

  29. Ugai T, Ito H, Oze I, Saito E, Rahman MS, Boffetta P, et al. Association of BMI, smoking, and alcohol with multiple myeloma mortality in Asians: a pooled analysis of more than 800,000 participants in the Asia Cohort Consortium. Cancer Epidemiol Biomark Prev. 2019;28:1861–7.

    Article  Google Scholar 

  30. Greenberg AS, Obin MS. Obesity and the role of adipose tissue in inflammation and metabolism. Am J Clin Nutr. 2006;83:461S–5S.

    Article  CAS  PubMed  Google Scholar 

  31. Recalde M, Davila-Batista V, Diaz Y, Leitzmann M, Romieu I, Freisling H, et al. Body mass index and waist circumference in relation to the risk of 26 types of cancer: a prospective cohort study of 3.5 million adults in Spain. BMC Med. 2021;19:10.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Albanes D, Jones DY, Schatzkin A, Micozzi MS, Taylor PR. Adult stature and risk of cancer. Cancer Res. 1988;48:1658–62.

    CAS  PubMed  Google Scholar 

  33. Green J, Cairns BJ, Casabonne D, Wright FL, Reeves G, Beral V, et al. Height and cancer incidence in the Million Women Study: prospective cohort, and meta-analysis of prospective studies of height and total cancer risk. Lancet Oncol. 2011;12:785–94.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Engeland A, Tretli S, Hansen S, Bjorge T. Height and body mass index and risk of lymphohematopoietic malignancies in two million Norwegian men and women. Am J Epidemiol. 2007;165:44–52.

    Article  PubMed  Google Scholar 

  35. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42:565–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Silventoinen K. Determinants of variation in adult body height. J Biosoc Sci. 2003;35:263–85.

    Article  PubMed  Google Scholar 

  37. Albanes D, Winick M. Are cell number and cell proliferation risk factors for cancer? J Natl Cancer Inst. 1988;80:772–4.

    Article  CAS  PubMed  Google Scholar 

  38. Nunney L. Size matters: height, cell number and a person’s risk of cancer. Proc Biol Sci. 2018;285:20181743.

  39. Clayton PE, Banerjee I, Murray PG, Renehan AG. Growth hormone, the insulin-like growth factor axis, insulin and cancer risk. Nat Rev Endocrinol. 2011;7:11–24.

    Article  CAS  PubMed  Google Scholar 

  40. Giovannucci E. Nutrition, insulin, insulin-like growth factors and cancer. Horm Metab Res. 2003;35:694–704.

    Article  CAS  PubMed  Google Scholar 

  41. Teras LR, Bertrand KA, Deubler EL, Chao CR, Lacey JV, Jr, Patel AV, et al. Body size and risk of non-Hodgkin lymphoma by subtype: a pooled analysis from six prospective cohorts in the United States. Br J Haematol. 2022;197:714–27.

  42. Cozen W, Gebregziabher M, Conti DV, Van Den Berg DJ, Coetzee GA, Wang SS, et al. Interleukin-6-related genotypes, body mass index, and risk of multiple myeloma and plasmacytoma. Cancer Epidemiol Biomark Prev. 2006;15:2285–91.

    Article  CAS  Google Scholar 

  43. Birmann BM, Neuhouser ML, Rosner B, Albanes D, Buring JE, Giles GG, et al. Prediagnosis biomarkers of insulin-like growth factor-1, insulin, and interleukin-6 dysregulation and multiple myeloma risk in the Multiple Myeloma Cohort Consortium. Blood. 2012;120:4929–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Dalamaga M, Christodoulatos GS. Adiponectin as a biomarker linking obesity and adiposopathy to hematologic malignancies. Horm Mol Biol Clin Investig. 2015;23:5–20.

    CAS  PubMed  Google Scholar 

  45. Hofmann JN, Birmann BM, Teras LR, Pfeiffer RM, Wang Y, Albanes D, et al. Low levels of circulating adiponectin are associated with multiple myeloma risk in overweight and obese individuals. Cancer Res. 2016;76:1935–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Morris EV, Edwards CM. Adipokines, adiposity, and bone marrow adipocytes: dangerous accomplices in multiple myeloma. J Cell Physiol. 2018;233:9159–66.

  47. Renehan AG, Zwahlen M, Egger M. Adiposity and cancer risk: new mechanistic insights from epidemiology. Nat Rev Cancer. 2015;15:484–98.

    Article  CAS  PubMed  Google Scholar 

  48. Klein B, Tarte K, Jourdan M, Mathouk K, Moreaux J, Jourdan E, et al. Survival and proliferation factors of normal and malignant plasma cells. Int J Hematol. 2003;78:106–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Howlader N, Noone AM, Krapcho M, Miller D, Brest A, Yu M, et al., editors. SEER Cancer Statistics Review, 1975-2017. Bethesda, MD: National Cancer Institute; 2020.

  50. Rimm EB, Stampfer MJ, Colditz GA, Chute CG, Litin LB, Willett WC. Validity of self-reported waist and hip circumferences in men and women. Epidemiology. 1990;1:466–73.

    Article  CAS  PubMed  Google Scholar 

  51. Troy LM, Hunter DJ, Manson JE, Colditz GA, Stampfer MJ, Willett WC. The validity of recalled weight among younger women. Int J Obes Relat Metab Disord. 1995;19:570–2.

    CAS  PubMed  Google Scholar 

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Acknowledgements

The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study-II cohort. The authors express sincere appreciation to all Cancer Prevention Study-II participants, and to the members of the study and biospecimen management group. The authors would also like to acknowledge the contribution from central cancer registries supported through the Centers for Disease Control and Prevention’s National Program of Cancer Registries and cancer registries supported by the National Cancer Institute’s Surveillance Epidemiology and End Results Program. The study protocol was approved by the institutional review boards of Emory University, and those of participating registries as required. The authors assume full responsibility for all analyses and interpretation of results. The views expressed here are those of the authors and do not necessarily represent the American Cancer Society or the American Cancer Society—Cancer Action Network. The collection of cancer incidence data used in the California Teachers Study was supported by the California Department of Public Health pursuant to California Health and Safety Code Section 103885; Centers for Disease Control and Prevention’s National Program of Cancer Registries, under cooperative agreement 5NU58DP006344; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201800032I awarded to the University of California, San Francisco, contract HHSN261201800015I awarded to the University of Southern California, and contract HHSN261201800009I awarded to the Public Health Institute. The opinions, findings, and conclusions expressed herein are those of the author(s) and do not necessarily reflect the official views of the State of California, Department of Public Health, the National Cancer Institute, the National Institutes of Health, the Centers for Disease Control and Prevention or their Contractors and Subcontractors, or the Regents of the University of California, or any of its programmes. The authors would like to thank the California Teachers Study Steering Committee that is responsible for the formation and maintenance of the Study within which this research was conducted. A full list of California Teachers Study team members is available at https://www.calteachersstudy.org/team. All of the data associated with this publication and in the California Teachers Study are available for research use. The California Teachers Study welcomes all such inquiries and encourages individuals to visit https://www.calteachersstudy.org/for-researchers. The authors would like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention’s National Program of Cancer Registries (NPCR) and/or the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program. Central registries may also be supported by state agencies, universities, and cancer centres. Participating central cancer registries include the following: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kentucky, Louisiana, Massachusetts, Maine, Maryland, Michigan, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, Seattle SEER Registry, South Carolina, Tennessee, Texas, Utah, Virginia, West Virginia, Wyoming. The authors assume full responsibility for the analyses and interpretation of these data. We would also like to thank the participants and staff of the Health Professionals Follow-up Study and Nurses’ Health Study for their valuable contributions. We thank the members of Kaiser Permanente for helping us improve care through the use of information collected through our electronic health record systems.

Funding

This work was supported by the National Institutes of Health (R01 CA202712, UM1 CA186107, P01 CA87969, U01 CA176726, U01 CA167552, U01 CA199277; P30 CA033572; P30 CA023100; UM1 CA164917; R01 CA077398; R01 CA207020). The Nurses’ Health Study II received additional funding from the Breast Cancer Research Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

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Authors and Affiliations

  1. Slone Epidemiology Center, Boston University, Boston, MA, USA

    Kimberly A. Bertrand

  2. American Cancer Society, Atlanta, GA, USA

    Lauren R. Teras & Emily L. Deubler

  3. Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA

    Chun R. Chao

  4. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

    Bernard A. Rosner, Ke Wang & Brenda M. Birmann

  5. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Bernard A. Rosner

  6. City of Hope, Duarte, CA, USA

    Charlie Zhong & Sophia S. Wang

  7. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

    Charlie Zhong

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Contributions

All authors contributed data from their respective cohort studies. KAB, LRT and BMB developed the analytic plan with significant contributions from SSW and CRC. ELD conducted the majority of the statistical analyses with contributions from KW and consultation from BAR. KAB drafted the manuscript with input and revisions from LRT, SSW and BMB. All other authors (ELD, CRC, BAR, KW and CZ) provided critical revisions to the writing and analyses. All authors approved the final version of this manuscript.

Corresponding author

Correspondence to Kimberly A. Bertrand.

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The authors declare no competing interests.

Ethics approval and consent to participate

This study was approved by the Institutional Review Boards of City of Hope, Brigham and Women’s Hospital, Harvard T.H. Chan School of Public Health, Kaiser Permanente Southern California, and those of participating cancer registries as required. Informed consent was implied by the return of the baseline questionnaire. The study was performed in accordance with the Declaration of Helsinki.

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Bertrand, K.A., Teras, L.R., Deubler, E.L. et al. Anthropometric traits and risk of multiple myeloma: a pooled prospective analysis. Br J Cancer 127, 1296–1303 (2022). https://doi.org/10.1038/s41416-022-01907-2

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