Abstract
Background
Obesity is an established risk factor for multiple myeloma (MM). Relatively few prior studies, however, have evaluated associations in Black populations.
Methods
Among 55,276 participants in the Black Women’s Health Study, a prospective U.S. cohort established in 1995, we confirmed 292 incident diagnoses of MM over 26 years of follow-up. Multivariable Cox proportional hazard models, adjusted for age and putative MM risk factors, were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations of usual body mass index (BMI), BMI at age 18, height, and waist-to-hip ratio with MM.
Results
Compared to women with a usual adult BMI < 25 kg/m2, the HR associated with a usual adult BMI ≥ 35 kg/m2 was 1.38 (95% CI: 0.96, 1.98). For early adult BMI, the HR comparing women with BMI ≥ 25 vs. <25 kg/m2 was 1.57 (95% CI: 1.08, 2.28). Women who were heavy in both early and later life had the highest risk compared to those who were lean at both time points (HR: 1.60; 95% CI: 1.02, 2.52). Height was also associated with the risk of MM; the HR per 10 cm was 1.21 (95% CI: 1.02, 1.43).
Conclusions
These results indicate that high early adult BMI is associated with a 57% increased risk of MM in Black women and potentially highlight the importance of weight control as a preventive measure.
Subject terms: Risk factors, Oncology
Introduction
Multiple myeloma (MM) is an incurable cancer of the plasma cells, with about 35,730 new cases expected to be diagnosed in the U.S. in 2023. Compared to non-Hispanic whites, Black men and women have a more than 2-fold higher incidence of MM [1]. Established risk factors for MM include age, male gender, African ancestry, and more recently obesity [2].
The obesity epidemic is a serious public health concern and has been linked to increased incidence of chronic diseases such as type 2 diabetes, cardiovascular disease, and certain cancers. Importantly, there are critical racial disparities in obesity rates. Across racial/ethnic groups, non-Hispanic Black women have the highest age-adjusted prevalence of obesity, reaching 56.9%, compared to 39.8% among non-Hispanic white women [3].
Precise mechanisms underlying the development of MM in the setting of obesity remain incompletely understood but various biological pathways have been implicated in its pathogenesis. These factors include dysregulation in insulin and IGF-1 axis [4], inflammation [5], oxidative stress, and adipokines such as adiponectin and leptin [6]. The IGF axis is involved in numerous stages of MM development including cell invasion, proliferation, and resistance to cell death [7].
In a meta-analysis of 23 prospective cohort studies (in largely white populations), the hazard ratio (HR) associated with a 5 kg/m2 increase in body mass index (BMI) was 1.06 [95% confidence interval (CI): 1.03, 1.10] [8]. Moreover, a pooled study incorporating repeated measures of adult BMI over time found a 10% increased risk per 5 kg/m2 of usual adult BMI, a time-varying cumulative average of BMI from baseline through follow-up [9]. Positive associations have also been reported for earlier life BMI (e.g., BMI at age 18) [10–12]. Thus, obesity, more prevalent among Black individuals compared to U.S. non-Hispanic whites (NHWs) [13], may play a role in observed disparities in incidence. Relatively few prior studies, however, have evaluated associations in Black populations [9, 14–16].
Obesity is the only established modifiable risk factor for MM and elucidating the relationship between obesity in high-risk populations might facilitate prevention strategies. We aimed to evaluate the relation of body size to the risk of MM in a large cohort of U.S. Black women.
Methods
Study population
The BWHS is a prospective cohort study that enrolled 59,000 self-identified Black women ages 21–69 in 1995 from across the US [17]. At baseline and biennially, participants provided information on their medical history as well as demographic, lifestyle, and early life factors via self-administered questionnaires. Notices of deaths were obtained from next-of-kin, the U.S. Postal Service, and annual searches of the National Death Index. For the current analyses, we excluded women with a history of cancer (other than non-melanoma skin cancer) at baseline. We also excluded women with missing data or implausible values for weight or height. In total, 55,276 BWHS participants were included in these analyses.
This study was approved by the Boston University Medical Campus Institutional Review Board (IRB) and by the IRBs of participating cancer registries. Informed consent was implied by the return of the baseline questionnaire.
Case ascertainment
Incident cases of MM (ICD-8 203; ICD-O-3 9732, 9733) were ascertained through self-report on biennial follow-up questionnaires or identified through death records and linkage to 24 cancer registries in states covering 95% of participants. Diagnoses were confirmed by review of medical records, pathology reports, and cancer registry records. Through 2021, 292 incident MM cases were diagnosed over 1,373,581 person-years of follow-up.
Exposure and covariate assessment
Exposures of interest included usual adult BMI, BMI at age 18, and waist-to-hip ratio. Women reported adult height and their current weight at the baseline questionnaire in 1995; weight was updated on each biennial follow-up questionnaire. Weight at age 18 was reported at baseline questionnaire. BMI was calculated as weight in kilograms divided by the square of height in metres at each follow-up cycle. Usual adult BMI was calculated as the time-varying cumulative average of BMI from baseline through each follow-up cycle. For example, usual adult BMI in 1997 was the average of BMI assessed in 1995 and 1997; usual adult BMI in 1999 was the average of BMI assessed in 1995, 1997, and 1999; etc. Waist and hip circumference were assessed at the baseline questionnaire. Self-reports of weight, height, waist circumference, and hip circumference were highly correlated with technician measurements in a validation study [18]. Covariates of interest were putative risk factors for MM including alcohol consumption, smoking history, physical activity, and educational attainment. Covariates were updated on follow-up questionnaires and treated as time-varying in analyses.
Statistical methods
Person-time was calculated from 1995 to diagnosis of MM, death, or the end of follow-up (2021), whichever came first. Cox proportional hazard models, stratified by age and follow-up period, were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the risk of MM associated with each category of exposure variables. A priori, usual adult BMI was categorised as <25.0 (reference), 25.0-29.9, 30.0-34.9, and ≥35.0 kg/m2; early adult BMI (i.e., BMI at age 18) was categorised as <20 (reference), 20-24.9, and ≥25.0 kg/m2. Waist-to-hip ratio was categorised as <0.80 (reference), 0.80-0.85, and ≥0.86. Tests for linear trends considered BMI and other anthropometric factors as continuous variables. We also examined the potential non-linear relation between BMI and MM non-parametrically with restricted cubic splines [19]. Tests for non-linearity used the likelihood ratio test comparing the model with only the linear term to the model with the linear term and the cubic spline terms.
Multivariable models included adjustment for potential confounders: smoking history (never, past, current), current alcohol consumption ( <1, 1–6, ≥7 drinks/week), physical activity (none, <5, ≥5 h/week), and educational attainment ( ≤12, 13–15, ≥16 years). We also considered adjustment for history of type 2 diabetes. Missing indicator categories were used to account for missing information in covariates (generally 2–4%).
In mutually adjusted models, we evaluated potential confounding by other anthropometric factors (e.g., models for BMI considered adjustment for height and vice versa). Similarly, to determine the impact of exposure to overweight/obesity across the life course, we cross-classified women according to young adult and usual adult BMI.
All analyses were performed using SAS 9.4 (Cary, North Carolina).
Results
At baseline in 1995, the median BMI was 26.6 kg/m2. Women with BMI < 25 kg/m2 tended to have higher educational attainment and higher levels of physical activity compared to women with BMI ≥ 30 kg/m2. As expected, women with BMI < 25 kg/m2 also had lower waist-to-hip ratio and lower prevalence of type 2 diabetes. There were no apparent differences in smoking history or alcohol consumption by BMI (Table 1).
Table 1.
Baseline characteristics of the study population by body mass index (BMI).
| BMI (kg/m2) | ||||
|---|---|---|---|---|
| Characteristic | <25 (n = 21,310) | 25–29.9 (n = 17,358) | 30-34.9 (n = 9076) | ≥35 (n = 7532) |
| Age in years, mean (SD)a | 36.1 (10.0) | 40.4 (10.8) | 41.0 (10.7) | 40.0 (10.2) |
| Height in cm, mean (SD) | 165 (7.1) | 165 (7.1) | 164 (7.0) | 165 (7.3) |
| Type 2 diabetes, % | 2 | 3 | 6 | 9 |
| Waist-to-hip ratio, % | ||||
| <0.8 | 60 | 45 | 35 | 34 |
| 0.8–0.85 | 15 | 20 | 21 | 19 |
| ≥0.86 | 12 | 19 | 26 | 27 |
| Missing | 13 | 16 | 18 | 19 |
| Smoking history, % | ||||
| Current | 16 | 16 | 16 | 14 |
| Past | 17 | 20 | 21 | 23 |
| Never | 66 | 64 | 63 | 64 |
| Alcohol consumption in drinks/week, % | ||||
| <1 | 70 | 68 | 69 | 73 |
| 1–6 | 22 | 24 | 23 | 20 |
| ≥7 | 7 | 7 | 7 | 7 |
| Missing | 1 | 1 | 1 | 1 |
| Educational attainment in years, % | ||||
| <12 | 14 | 18 | 20 | 22 |
| 13–15 | 34 | 37 | 39 | 40 |
| ≥16 | 52 | 44 | 40 | 37 |
| Missing | 1 | 1 | 1 | 1 |
| Physical activity in hours/week, % | ||||
| None | 34 | 38 | 45 | 54 |
| <5 | 56 | 54 | 50 | 42 |
| ≥5 h per week | 10 | 8 | 6 | 4 |
Values are means (SD) or percentages and are standardised to the age distribution of the study
population. Percentages may not sum to the total due to rounding.
BMI body mass index.
aValue is not age-adjusted.
As shown in Table 2, in multivariable models, higher usual and early adult BMI were positively associated with risk of MM. Compared to women with a usual adult BMI < 25 kg/m2, the HR associated with a usual adult BMI ≥ 35 kg/m2 was 1.38 (95% CI: 0.96, 1.98); the HR per 5 kg/m2 was 1.09 (1.00, 1.20). Associations for early adult BMI were somewhat stronger: compared to women with early adult BMI < 20 kg/m2, the HR for early adult BMI ≥ 25 kg/m2 was 1.57 (95% CI: 1.08, 2.28) and each 5-unit increase was associated with 19% increased risk of MM (HR: 1.19; 95% CI: 1.03, 1.38). Results from age-adjusted models were similar to those from multivariable-adjusted models, suggesting little evidence of confounding by the covariates considered, including height (Table 2). Further adjustment for type 2 diabetes did not materially impact effect estimates (data not shown). There was no evidence of non-linearity of associations (data not shown).
Table 2.
Hazard ratios (95% confidence intervals) for multiple myeloma in relation to usual adult BMI and early adult BMI, 1995–2021.
| Usual adult BMI | Early adult BMI | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| BMI category, kg/m2 | Person-years | N cases | Age-adjusted HR (95% CI) | Multivariable HRa (95% CI) | BMI category, kg/m2 | Person-years | N cases | Age-adjusted HR (95% CI) | Multivariable HRa (95% CI) |
| <25 | 403,308 | 61 | 1.00 (ref) | 1.00 (ref) | < 20 | 556,892 | 113 | 1.00 (ref) | 1.00 (ref) |
| 25–<30 | 466,737 | 96 | 0.94 (0.68, 1.30) | 0.93 (0.67, 1.29) | 20–<25 | 613,159 | 138 | 1.33 (1.03, 1.71) | 1.38 (1.07, 1.78) |
| 30–<35 | 274,992 | 70 | 1.11 (0.79, 1.58) | 1.09 (0.77, 1.55) | ≥25 | 192,226 | 39 | 1.56 (1.07, 2.27) | 1.57 (1.08, 2.28) |
| ≥35 | 228,544 | 65 | 1.44 (1.01, 2.05) | 1.38 (0.96, 1.98) | |||||
| HR per 5 kg/m2 | 1,373,581 | 292 | 1.11 (1.01, 1.21) | 1.09 (1.00, 1.20) | HR per 5 kg/m2 | 1,362,277 | 290 | 1.18 (1.02, 1.37) | 1.19 (1.03, 1.38) |
BMI body mass index, HR hazard ratio, CI confidence interval.
aHRs adjusted for age, period, height, alcohol consumption, physical activity, smoking history, and educational attainment.
In mutually adjusted models, HRs for usual adult and early adult BMI were each attenuated and became similar in magnitude. Specifically, the age-adjusted HR for usual adult BMI ≥ 35 vs. <25 kg/m2 was 1.25 (95% CI: 0.84, 1.87) and the age-adjusted HR for early adult BMI ≥ 25 vs. <20 kg/m2 was 1.34 (95% CI: 0.87, 2.04) when both were included in the same model.
In analyses of joint categories of usual and early adult BMI, the strongest association was apparent for women who were heavy in both early and later adulthood. Compared to women who were lean in both time periods, the HR for those with early adult BMI ≥ 25 kg/m2 and usual adult BMI ≥ 35 kg/m2 was 1.60 (95% CI: 1.02, 2.52) (Table 3).
Table 3.
Hazard ratios (95% confidence intervals) for multiple myeloma in relation to joint categories of usual adult BMI and early adult BMI.
| Usual adult BMI | ||||||
|---|---|---|---|---|---|---|
| <25 kg/m2 | 25- <30 kg/m2 | ≥30 kg/m2 | ||||
| Early adult BMI | N | HRa (95% CI) | N | HRa (95% CI) | N | HRa (95% CI) |
| <20 kg/m2 | 42 | 1.00 (reference) | 43 | 0.78 (0.50, 1.21) | 28 | 0.91 (0.55, 1.50) |
| 20– <25 kg/m2 | 18 | 1.15 (0.66, 2.00) | 50 | 1.18 (0.78, 1.79) | 70 | 1.28 (0.86, 1.89) |
| ≥25 kg/m2 | 0 | - | 2 | ∞ | 37 | 1.60 (1.02, 2.52) |
aHRs adjusted for age, period, height, alcohol, physical activity, smoking status, and education.
∞HRs not shown when n < 5.
Regarding other measures of body size, height was strongly and statistically significantly associated with risk of MM. In a multivariable-adjusted model, the HR per 10 cm was 1.21 (95% CI: 1.02, 1.43) (Table 4). This result was virtually unchanged when BMI was included in the model (data not shown). There was no apparent association between waist-to-hip ratio and risk of MM (Table 4).
Table 4.
Hazard ratios (95% confidence intervals) for multiple myeloma in relation to height and waist-to-hip ratio.
| Person-years | N | HRa (95% CI) | HRb (95% CI) | |
|---|---|---|---|---|
| Height (per 10 cm) | 1,373,581 | 292 | 1.21 (1.02, 1.42) | 1.21 (1.02, 1.43) |
| Waist-to-hip ratio | ||||
| <0.80 | 600,717 | 126 | 1.00 (ref) | 1.00 (ref) |
| 0.80–<0.86 | 282,283 | 62 | 0.98 (0.72, 1.33) | 0.96 (0.71, 1.31) |
| ≥0.86 | 324,684 | 70 | 0.95 (0.71, 1.28) | 0.92 (0.68, 1.24) |
HR hazard ratio, CI confidence interval, cm centimetre.
aHRs adjusted for age, period.
bHRs adjusted for age, period, alcohol consumption, physical activity, smoking history, and educational attainment.
Discussion
Consistent with prior studies in predominantly white populations [9–12], we found that both usual adult and early adult BMI are positively associated with MM in this large, prospective study of Black women. Findings for early adult BMI were somewhat stronger than those for usual adult BMI: each 5 kg/m2 increase in early adult BMI was associated with a statistically significant 19% increased risk of MM vs. 9% for usual adult BMI. Overall, these results support the important role obesity in early and later stages of life plays in increased risk of MM among Black women. Our findings suggest that maintenance of a healthy weight throughout an individual’s life may be a tenable prevention strategy.
While it is well recognised that obesity is a risk factor for MM [8], published literature assessing this association among Black populations is limited. In an early cohort study based on only 34 cases, a positive but non-significant association between BMI and MM risk was observed among Black men; there was no association among Black women (n = 12) [15]. In a US population-based case-control study, Black individuals with obesity had a 50% higher risk of MM compared to those with a BMI between 18.5-24.9 kg/m2 (193 cases, 903 controls) [14]. Risk of MM was also increased for obese vs. non-obese (age-adjusted RR: 1.26; 95% CI: 1.02, 1.56) in a cohort of US Black male veterans (89 obese cases, 1509 non-obese cases) [16]. More recently, in a pooled analysis of prospective cohort studies, each 5-unit increase in usual BMI was associated with a 24% increased risk of MM in Black individuals (HR: 1.24; 95% CI: 0.97, 1.57; n = 357 cases) [9].
Of interest, the strongest relationship was observed for women who were heavy in both early and later adulthood. Similar findings have been reported in predominantly white populations in pooled analyses of case-control and cohort studies [9, 10, 12]. Taken together, these data suggest that earlier adult BMI and weight maintenance throughout adulthood play a role in MM risk.
We also explored the association between waist-to-hip ratio as a marker of central or abdominal adiposity with respect to MM risk. In relatively few prior studies, WHR or waist circumference have been weakly and inconsistently associated with MM [12, 20–23]. In the current analysis, we found no association between WHR and MM risk, whereas a recent pooled prospective analysis in a predominantly white population demonstrated a small but significant association between waist circumference and MM risk with an HR of 1.09 per 15 cm (95% CI: 1.00–1.19) [9]. The inconsistency in research to date may reflect in part the imprecision of WHR as an instrument. To our knowledge, no prior studies reported associations of measures of central adiposity with MM risk specifically in Black individuals.
We report a 21% increase in the risk of MM per 10 cm increase in height. Height has been identified as a potential risk factor for several types of cancer, including MM [9, 23, 24]. Our present findings further support this prior evidence. While it is not entirely clear why height may increase the risk of MM, taller individuals have more cells at risk of malignant transformation and higher levels of growth factors such as IGF-1 [25], which could increase the risk of abnormal plasma cell growth and the development of MM.
Several complex physiological mechanisms linking obesity and MM have been described. Obesity is a state of chronic inflammation and insulin resistance causing disturbances in signalling pathways that may promote myelomagenesis. Inflammatory markers and growth factors such as IL-6, C-reactive protein, IGF-1, and TNF-alpha are elevated in adipose tissue [26]. High serum IL-6 levels, which promote plasma cell proliferation, have been associated with MM.[27] Deregulation in adipokines such as adiponectin, an anti-inflammatory, and insulin sensitising marker, is also associated with a higher risk of MM among obese individuals [28, 29]. Collectively, the evidence suggests that there is a strong biological plausibility for the association between obesity and the risk of MM.
A potential limitation of this study is that height and weight and other measures of body size were self-reported; however, a validation study within the BWHS showed good agreement with objective measures [18]. Because a tape measure was necessary for participants to report their waist and hip circumference, we lacked data on this variable for nearly 20% of the population; the results of these analyses may be underpowered. Given higher educational attainment in the BWHS compared to the general U.S. Black population, results may not be generalisable to all Black women. Strengths of this study include the large sample size, the prospective study design, and the repeated measures of BMI over up to 26 years of follow-up. Assessment of BMI at age 18 enabled us to evaluate the impact of weight earlier in life and is a unique contribution of this study.
To date, obesity remains the only known modifiable risk factor for MM. The results of the present study extend the prior literature by showing an association in Black women, who have both a higher risk of MM and a greater prevalence of obesity compared to NHWs. Further studies investigating weight management throughout life in this high-risk population can help inform prevention strategies and potentially help close the gap in racial disparities.
Acknowledgements
The authors would like to acknowledge the contribution to this study from central cancer registries supported through the Centres for Disease Control and Prevention’s National Programme of Cancer Registries (NPCR) and/or the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Programme. Central registries may also be supported by state agencies, universities, and cancer centres. Participating central cancer registries include the following: AL, AR, AZ, CA, CO, CT, DE, DC, FL, GA, HI, IA, IL, IN, KY, LA, MD, MA, MI, MO, MS, NE, NJ, NM, NY, NC, OH, OK, OR, PA, SC, TN, TX, VA, WA, WI. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, the National Institutes of Health, or the state cancer registries. We thank the participants and staff of the BWHS for their contributions.
Author contributions
YK, JRP, and KAB contributed to the study conception and design. Data collection was performed by JRP and KAB. Statistical analyses were performed by BNP and KAB. The first draft of the manuscript was written by YK and KAB; all authors provided critical feedback on the draft and read and approved the final manuscript.
Funding
This work was supported by the National Institutes of Health (CA058420 and CA164974). Julie R. Palmer received support from the Karin Grunebaum Cancer Research Foundation.
Data availability
The data underlying this article cannot be shared publicly to protect the confidentiality of individuals who participated in the study. The data will be shared on reasonable request to the corresponding author.
Competing interests
The authors declare no competing interests.
Ethics approval and consent to participate
The BWHS study protocol was approved by the Boston University Medical Campus Institutional Review Board (IRB) and by the IRBs of participating cancer registries as required. Informed consent was implied by the return of the baseline questionnaire.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
The data underlying this article cannot be shared publicly to protect the confidentiality of individuals who participated in the study. The data will be shared on reasonable request to the corresponding author.