Abstract
Background
Certain hazardous air pollutants (HAPs) are known or suspected to pose immunological or cancer risk to humans, but evidence is limited from the general population.
Methods
We assessed associations between residential exposure to HAPs at the Census tract level and incident non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) in the Nurses’ Health Study (NHS, 1986–2012) and NHSII (1989–2019). We used covariate-adjusted proportional hazards models to estimate hazard ratios (HRs) of NHL, major NHL subtypes, and MM per interquartile range increase in exposure to a given HAP and pooled the cohort-specific estimates using fixed-effects meta-analyses.
Results
There were 810 NHL and 158 MM cases in NHS (1,700,707 person-years), and 379 NHL and 59 MM cases in NHSII (2,820,772 person-years). Most HRs approximated unity. Meta-analyses did not show consistent evidence of associations between any HAP exposure and risk of NHL or MM.
Conclusions
Exposure to HAPs was not consistently associated with risks of NHL or MM in these nationwide prospective cohorts of women.
Impact
This is the first nationwide study assessing associations between residential HAP exposures and risk of lymphoid malignances in prospective cohorts and focuses on women, who have frequently been underrepresented in (primarily occupational) studies of exposure to HAPs.
Introduction
Non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) account for about 6% of all cancers in the United States (US), while known risk factors only explain a small proportion of disease occurrence.1 Hazardous air pollutants (HAPs) are compounds that are known or suspected to have adverse effects on health. Some of these compounds have been identified as lymphohematopoietic carcinogens, with likely mechanisms involving gene or chromosomal mutation and/or immune suppression,2 mostly based on evidence from animal studies or from occupational settings, which include relatively high-dose exposures. Studies conducted in the general population have been limited and largely ecological.3 We aimed to assess the associations between residential (comparatively lower-dose) exposure to HAPs and incident NHL and MM in two US nationwide prospective cohorts: the Nurses’ Health Study (NHS) and NHSII.
Materials and Methods
NHS and NHSII participants were female registered nurses recruited in 1976 and 1989, respectively. Participants completed the enrollment questionnaire and biennial follow-up questionnaires to update information on lifestyle and disease.4 In the present study, participants without cancer at baseline (NHS: 1986, NHSII: 1989) were followed until 2012 (NHS) or 2019 (NHSII). Censoring occurred at the earliest among first occurrence of any cancer other than the outcome of interest (except non-melanoma skin cancer), death, loss to follow-up, or end of follow-up. Incident NHL (ICD-8 or −9 codes 200, 202 and 204.1) and MM (ICD-8 or −9 code 203) were primarily identified via self-report and confirmed by review of medical records and pathology reports. Confirmed NHL cases were further assigned a histologic subtype: diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL).5 Estimated concentrations of selected HAPs at the Census tract level were obtained from the US Environmental Protection Agency’s 2002 National Air Toxics Assessment (NATA; available from: http://www.epa.gov/nata/) and assigned to participants’ residential address histories throughout follow-up.6 We chose the 2002 NATA estimates near the follow-up midpoint,6 considering the noncomparability of estimates across NATA years. HAPs identified as lymphohematopoietic carcinogens,2 having immunological risks, or suggested to be positively associated with lymphohematopoietic cancers7 were included: 1,3-butadiene, benzene, cadmium, ethylene oxide, formaldehyde, lead, nickel, and trichloroethylene. The estimated metal concentrations include the emissions of the metals and their compounds. We applied Cox proportional hazards models to assess cohort-specific hazard ratios (HRs) and 95% confidence intervals (CIs) associated with outcome risk per interquartile range (IQR) increase in HAP exposures after observing no deviations from linearity using cubic splines. Models were stratified by age and questionnaire cycle and adjusted for race, body mass index (BMI), behavioral factors, and individual- and neighborhood-level socioeconomic status (SES).8 Cohort-specific HRs were pooled using fixed-effects meta-analyses; a Cochran’s Q test with a P-value <0.1 indicated heterogeneity. The study protocol was approved by the institutional review boards of the Brigham and Women’s Hospital and Harvard T.H. Chan School of Public Health, and those of participating registries as required.
Data Availability
Because of participant confidentiality and privacy concerns, data are available upon request via standard controlled access procedures. Further information including the procedures to obtain and access data from the Nurses’ Health Studies is described at https://www.nurseshealthstudy.org/researchers.
Results
We observed 810 NHL and 158 MM cases in NHS (1,700,707 person-years), and 379 NHL and 59 MM cases in NHSII (2,820,772 person-years) (Table 1). The cohorts included mostly (self-identified) White, married, and/or non-smoking females whose ages averaged 62 years in NHS and 47 years in NHSII over follow-up. HAPs showed right-skewed distributions with concentrations below 1 μg/m3, except for benzene and formaldehyde. Correlations between HAPs were mostly modest (Spearman r<0.7), except for high correlations between 1,3-butadiene and benzene (r’s=0.87 and 0.88), and 1,3-butadiene and formaldehyde (r’s=0.76 and 0.80). No proportional hazards assumption violation was detected through the test of effect modification by time. In meta-analyses, most HRs approximated unity (Table 2). Non-significantly elevated MM risk was suggested for 1,3-butadiene and benzene exposures. Between-cohort heterogeneity was generally small to moderate. We observed a statistically significant positive association between exposure to cadmium and DLBCL incidence (HR=1.04, 95% CI: 1.00, 1.08 per 0.08 ng/m3 increase), with heterogeneous cohort-specific findings (Q-test p-value=0.08). We observed positive associations of trichloroethylene exposure with FL risk in NHS and of exposure to cadmium with NHL risk overall in NHSII, the latter primarily driven by an association with DLBCL risk. We also observed statistically significant inverse associations of exposure to cadmium and lead with FL incidence in NHSII.
Table 1.
Age-adjusted Cohort Characteristics over Follow-up in the Nurses’ Health Study (NHS) and Nurses’ Health Study II (NHSII)
| NHS | NHSII | |
|---|---|---|
| N = 90,886 | N = 113,902 | |
| PY = 1,700,707 | PY = 2,820,772 | |
|
| ||
| Follow-up period | 1986 − 2012 | 1989 − 2019 |
| Number of cases | ||
| NHL | 810 | 379 |
| DLBCL | 132 | 82 |
| FL | 146 | 98 |
| CLL | 199 | 63 |
| MM | 158 | 59 |
| Population characteristics | ||
| Age (years)a, Mean ± SD | 61.9 ± 9.6 | 47.3 ± 9.6 |
| White, % | 94 | 96 |
| BMI (kg/m2) at age 18, Mean ± SD | 21.4 ± 2.7 | 21.2 ± 3.1 |
| Current BMI (kg/m2), Mean ± SD | 25.9 ± 4.6 | 25.6 ± 4.9 |
| Smoking status | ||
| Never smoked, % | 45 | 65 |
| Past smoker, % | 41 | 26 |
| Current smoker, % | 13 | 9 |
| AHEI diet score, Mean ± SD | 53.4 ± 11.2 | 53.9 ± 12.8 |
| Daily energy intake (kcal), Mean ± SD | 1,675 ± 413 | 1,808 ± 476 |
| Alcohol consumption (grams/day), Mean ± SD | 5.8 ± 8.5 | 3.6 ± 5.9 |
| Physical activity (MET-hrs/week), Mean ± SD | 17.2 ± 22.1 | 22.7 ± 29.2 |
| Married - ever, % | 92 | 94 |
| Live alone, % | 13 | 8 |
| Husband's highest education level in 1992 (NHS) or 1999 (NHSII) | ||
| High school, % | 33 | 15 |
| College, % | 21 | 42 |
| Graduate school, % | 18 | 24 |
| Mother’s occupation housewife when participant was 16 years old, % | 64 | NA |
| Father’s occupation professional/manager when participant was 16 years old, % | 25 | NA |
| Registered nurse with a degree in 1972, % | 80 | NA |
| Retired, % | 36 | NA |
| Household income >=100k in 2001, % | NA | 23 |
| Region | ||
| Northeast, % | 53 | 33 |
| Midwest, % | 19 | 33 |
| West, % | 12 | 15 |
| South, % | 16 | 19 |
| Neighborhood SES scoreb, Mean ± SD | −0.08 ± 3.70 | −0.03 ± 3.67 |
| Rural area (<500 people/mile2), % | 26 | 29 |
| Concentration of HAPs (ng/m3), median (25th − 75th percentile) | ||
| 1,3-Butadiene | 80 (50 − 110) | 70 (50 − 100) |
| Benzene | 1,300 (970 − 1,650) | 1,240 (880 − 1,610) |
| Cadmium | 0.10 (0.06 − 0.14) | 0.09 (0.06 − 0.14) |
| Ethylene oxide | 4.70 (2.59 − 8.10) | 5.13 (2.87 − 7.98) |
| Formaldehyde | 1,680 (1,360 − 2,080) | 1,660 (1,280 − 2,120) |
| Lead | 2.23 (1.43 − 3.45) | 2.10 (1.29 − 3.41) |
| Nickel | 0.89 (0.44 − 1.53) | 0.77 (0.33 − 1.45) |
| Trichloroethylene | 70 (50 − 110) | 70 (40 − 110) |
Value not age-adjusted
Neighborhood SES score is the sum of nine z-standardized variables from the US Census: median household income, median home value, percent with a college degree, percent non-Hispanic White, percent non-Hispanic Black, percent of foreign-born residents, percent of families receiving interest or dividends, percent of occupied housing units, and percent unemployed.
AHEI = Alternative Healthy Eating Index, BMI = body mass index, CLL/SLL = chronic lymphocytic leukemia/small lymphocytic lymphoma, DLBCL = diffuse large B-cell lymphoma, FL = follicular lymphoma, HAPs = hazardous air pollutants, MET = metabolic equivalent of task, MM = multiple myeloma, NHL = non-Hodgkin lymphoma, PY = person-years, SD = standard deviation, SES = socioeconomic status
Table 2.
Hazard ratios and corresponding 95% confidence intervals for non-Hodgkin lymphoma (N case = 1,189) and multiple myeloma (N case = 217) associated with an interquartile rangea increase in hazardous air pollutant exposure in the Nurses’ Health Study (NHS, follow-up 1986–2012, person-years = 1,700,707) and Nurses’ Health Study II (NHSII, follow-up 1989–2019, person-years = 2,820,772)
| Hazardous air pollutant | Outcome | HRs (95% CIs) from meta-analysisb | P-value for heterogeneityc | NHSd | NHSIId |
|---|---|---|---|---|---|
|
| |||||
| 1,3-Butadiene | NHL overall | 0.97 (0.91, 1.04) | 0.58 | 0.96 (0.87, 1.04) | 0.99 (0.90, 1.10) |
| DLBCL | 0.96 (0.80, 1.15) | 0.82 | 0.94 (0.73, 1.20) | 0.98 (0.75, 1.27) | |
| FL | 0.97 (0.91, 1.04) | 0.58 | 0.92 (0.74, 1.14) | 0.92 (0.71, 1.19) | |
| CLL/SLL | 1.01 (0.93, 1.09) | 0.80 | 0.99 (0.83, 1.17) | 1.01 (0.93, 1.11) | |
| MM | 1.04 (0.90, 1.20) | 0.25 | 0.96 (0.78, 1.17) | 1.14 (0.92, 1.40) | |
| Benzene | NHL overall | 0.97 (0.90, 1.04) | 0.21 | 0.93 (0.84, 1.03) | 1.02 (0.92, 1.13) |
| DLBCL | 0.90 (0.74, 1.10) | 0.32 | 0.81 (0.61, 1.08) | 1.00 (0.75, 1.31) | |
| FL | 0.97 (0.90, 1.04) | 0.21 | 0.86 (0.67, 1.10) | 0.87 (0.66, 1.15) | |
| CLL/SLL | 1.04 (0.94, 1.15) | 0.97 | 1.04 (0.88, 1.21) | 1.04 (0.91, 1.19) | |
| MM | 1.07 (0.92, 1.25) | 0.31 | 1.00 (0.81, 1.23) | 1.17 (0.93, 1.47) | |
| Cadmium | NHL overall | 1.01 (0.99, 1.03) | 0.24 | 1.00 (0.96, 1.03) | 1.02 (1.00, 1.05) |
| DLBCL | 1.04 (1.00, 1.08) | 0.08 | 0.84 (0.66, 1.07) | 1.05 (1.01, 1.09) | |
| FL | 1.01 (0.99, 1.03) | 0.24 | 0.98 (0.88, 1.09) | 0.73 (0.55, 0.96) | |
| CLL/SLL | 1.02 (0.99, 1.06) | 0.66 | 1.02 (0.99, 1.06) | 1.00 (0.90, 1.11) | |
| MM | 0.95 (0.83, 1.07) | 0.72 | 0.96 (0.83, 1.10) | 0.91 (0.69, 1.19) | |
| Ethylene oxide | NHL overall | 1.00 (0.97, 1.03) | 0.98 | 1.00 (0.97, 1.03) | 1.00 (0.92, 1.08) |
| DLBCL | 1.00 (0.89, 1.11) | 0.85 | 0.98 (0.81, 1.19) | 1.01 (0.88, 1.15) | |
| FL | 1.00 (0.97, 1.03) | 0.98 | 1.00 (0.96, 1.05) | 0.96 (0.77, 1.19) | |
| CLL/SLL | 0.98 (0.87, 1.11) | 0.94 | 0.99 (0.86, 1.12) | 0.97 (0.73, 1.30) | |
| MM | 0.98 (0.88, 1.09) | 0.31 | 1.00 (0.89, 1.11) | 0.84 (0.61, 1.16) | |
| Formaldehyde | NHL overall | 0.96 (0.89, 1.04) | 0.63 | 0.95 (0.86, 1.05) | 0.99 (0.86, 1.13) |
| DLBCL | 0.92 (0.75, 1.13) | 0.49 | 0.86 (0.65, 1.14) | 0.99 (0.74, 1.33) | |
| FL | 0.96 (0.89, 1.04) | 0.63 | 1.03 (0.81, 1.31) | 0.97 (0.74, 1.27) | |
| CLL/SLL | 1.06 (0.95, 1.18) | 0.73 | 1.07 (0.95, 1.20) | 1.02 (0.80, 1.30) | |
| MM | 1.00 (0.82, 1.21) | 0.55 | 0.95 (0.75, 1.22) | 1.09 (0.77, 1.54) | |
| Lead | NHL overall | 1.01 (0.98, 1.04) | 0.61 | 1.01 (0.98, 1.04) | 0.99 (0.92, 1.06) |
| DLBCL | 1.00 (0.95, 1.05) | 0.70 | 0.97 (0.82, 1.15) | 1.00 (0.95, 1.06) | |
| FL | 1.01 (0.98, 1.04) | 0.61 | 1.03 (0.97, 1.09) | 0.65 (0.47, 0.90) | |
| CLL/SLL | 1.02 (0.99, 1.06) | 0.17 | 1.02 (0.99, 1.06) | 0.81 (0.58, 1.13) | |
| MM | 0.99 (0.88, 1.11) | 0.75 | 1.00 (0.88, 1.13) | 0.95 (0.72, 1.26) | |
| Nickel | NHL overall | 1.01 (0.98, 1.03) | 0.43 | 0.99 (0.95, 1.03) | 1.01 (0.98, 1.04) |
| DLBCL | 1.02 (0.98, 1.05) | 0.39 | 0.94 (0.79, 1.13) | 1.02 (0.98, 1.06) | |
| FL | 1.01 (0.98, 1.03) | 0.43 | 1.01 (0.94, 1.07) | 0.96 (0.81, 1.12) | |
| CLL/SLL | 1.01 (0.98, 1.05) | 0.56 | 1.00 (0.93, 1.07) | 1.02 (0.98, 1.05) | |
| MM | 1.00 (0.95, 1.06) | 0.55 | 1.01 (0.95, 1.06) | 0.95 (0.80, 1.13) | |
| Trichloroethylene | NHL overall | 1.02 (0.99, 1.05) | 0.39 | 1.02 (0.99, 1.05) | 0.98 (0.88, 1.08) |
| DLBCL | 0.96 (0.82, 1.13) | 0.80 | 0.98 (0.80, 1.19) | 0.94 (0.71, 1.23) | |
| FL | 1.02 (0.99, 1.05) | 0.39 | 1.06 (1.03, 1.10) | 0.85 (0.64, 1.14) | |
| CLL/SLL | 1.02 (0.95, 1.09) | 0.79 | 1.02 (0.95, 1.09) | 0.99 (0.79, 1.23) | |
| MM | 0.96 (0.82, 1.11) | 0.79 | 0.94 (0.77, 1.15) | 0.98 (0.78, 1.23) | |
Effect estimates were associated with a 55 ng/m3 increase in 1,3-butadiene exposure; a 710 ng/m3 increase in benzene exposure; an 0.08 ng/m3 increase in exposure to cadmium; a 5.3 ng/m3 increase in ethylene oxide exposure; a 785 ng/m3 increase in formaldehyde exposure; a 2.06 ng/m3 increase in exposure to lead; a 1.1 ng/m3 increase in exposure to nickel; and, a 65 ng/m3 increase in trichloroethylene exposure.
Hazard ratios (HRs) and 95% confidence intervals (CIs) from a fixed-effects meta-analysis of cohort-specific associations.
From Cochran’s Q test to assess heterogeneity by cohort, from fixed-effects meta-analyses.
Models were stratified on age in months and follow-up cycle and further adjusted for race, BMI at age 18, current BMI, current smoking status, current AHEI diet score, current daily energy intake in tertiles, current alcohol consumption in tertiles, current physical activity in quintiles, marital status (ever married/ not married), current living arrangement, husband's highest educational level (1992 in NHS or 1999 in NHSII), mother’s occupation as a housewife when participant was 16 years old (only in NHS), father’s occupation as a professional/manager when participant was 16 years old (only in NHS), registered nursing degree in 1972 (only in NHS), current retirement status (only in NHS), household income in 2001 (only in NHSII), current region of residence, current neighborhood SES score, current neighborhood population density.
AHEI = Alternative Healthy Eating Index, BMI = body mass index, CLL/SLL = chronic lymphocytic leukemia/small lymphocytic lymphoma, DLBCL = diffuse large B-cell lymphoma, FL = follicular lymphoma, MET = metabolic equivalent of task, MM = multiple myeloma, NHL = non-Hodgkin lymphoma, SES = socioeconomic status
Conclusions
We did not find consistent evidence of associations between HAP exposures and NHL/MM risk. Limitations included the use of HAP exposures from a single year, though we observed similar patterns using 1996 NATA. The linkage of HAPs at the Census tract level may underestimate the spatial variability of exposures, potentially introducing bias towards null associations. Further, we could not examine many individual NHL subtypes, and our findings may not be generalizable to all US women or to men. Study strengths include the nationwide coverage of the cohorts with variability in HAP exposures at levels lower than typically studied in occupational settings, extensive covariate information, and a large combined cohort size with almost 30 years of follow-up, which increased statistical power. Although some literature suggested that certain HAPs may be associated with increased lymphohematopoietic cancer incidence, we did not observe clear associations with NHL or MM risk in our general population cohorts.
Acknowledgements
This study was supported in part by a pilot grant from the Harvard Chan-National Institute of Environmental Health Sciences (NIEHS) Center (P30 ES000002) to B. M. Birmann and in part by the National Cancer Institute (UM1 CA186107 [to B.M. Birmann, J.E. Hart, F. Laden], P01 CA87969 [to B.M.Birmann, J.E.Hart, F. Laden], U01 HL145386 [to J.E. Hart and F. Laden], R01 CA149445 [to B.M. Birmann], R01 CA09812 [to F. Laden], and U01 CA176726 [to B.M. Birmann, J.E. Hart, F. Laden]). 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 centers. Participating central cancer registries include the following: Alabama, Alaska, Arizona, Arkansas, California, Delaware, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kentucky, Louisiana, Maine, Maryland, Massachusetts, 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. We would also like to thank the participants and staff of the Nurses’ Health Study (NHS) and the NHSII for their valuable contributions. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Footnotes
Conflicts of Interest
The authors have no conflict of interest to declare
References
- 1.Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA: A Cancer Journal for Clinicians. 2023;73(1):17–48. [DOI] [PubMed] [Google Scholar]
- 2.Eastmond DA, Keshava N, Sonawane B. Lymphohematopoietic cancers induced by chemicals and other agents and their implications for risk evaluation: An overview. Mutat Res Rev Mutat Res. 2014;761:40–64. [DOI] [PubMed] [Google Scholar]
- 3.Whitworth KW, Symanski E, Coker AL. Childhood lymphohematopoietic cancer incidence and hazardous air pollutants in southeast Texas, 1995–2004. Environ Health Perspect. 2008;116(11):1576–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Bao Y, Bertoia ML, Lenart EB, Stampfer MJ, Willett WC, Speizer FE, et al. Origin, Methods, and Evolution of the Three Nurses’ Health Studies. Am J Public Health. 2016;106(9):1573–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Swerdlow S, Campo E, Harris N, Jaffe E, Pileri S, Stein H, et al. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues: WHO Classification of Tumours, Revised 4th Edition, Volume 2; 2017. [Google Scholar]
- 6.Hart JE, Bertrand KA, DuPre N, James P, Vieira VM, VoPham T, et al. Exposure to hazardous air pollutants and risk of incident breast cancer in the nurses’ health study II. Environ Health. 2018;17(1):28. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Deubler EL, Gapstur SM, Diver WR, Gaudet MM, Hodge JM, Stevens VL, et al. Erythrocyte levels of cadmium and lead and risk of B-cell non-Hodgkin lymphoma and multiple myeloma. Int J Cancer. 2020;147(11):3110–8. [DOI] [PubMed] [Google Scholar]
- 8.DeVille NV, Iyer HS, Holland I, Bhupathiraju SN, Chai B, James P, et al. Neighborhood socioeconomic status and mortality in the nurses’ health study (NHS) and the nurses’ health study II (NHSII). Environmental Epidemiology. 2023;7(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Because of participant confidentiality and privacy concerns, data are available upon request via standard controlled access procedures. Further information including the procedures to obtain and access data from the Nurses’ Health Studies is described at https://www.nurseshealthstudy.org/researchers.