Abstract
Background
Ultraviolet radiation (UVR) exposure is the primary risk factor for melanoma, although the relationship is complex. Compared with radiation from UVB wavelengths, UVA makes up a majority of the surface solar UVR, penetrates the skin more deeply, is the principal range emitted by tanning beds, and is less filtered by sunscreens and window glass. Few studies have examined the relationship between ambient UVA and UVB and melanoma risk.
Methods
Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were estimated for the association between satellite-based ambient (based on residential history) UVA, UVB, and melanoma in non-Hispanic White participants using data from the United States Radiologic Technologists study, a large, nationwide prospective cohort. Associations of UVA and UVB quartile (Q) were examined in mutually adjusted and stratified models, additionally adjusted for demographic and sun sensitivity characteristics.
Results
There were 837 incident melanoma cases among 62 785 participants. Incidence of melanoma was statistically significantly increased for the highest quartile of childhood UVA exposure after adjustment for UVB (IRR = 2.82; 95% CI = 1.46 to 5.44) but not for higher childhood UVB after adjustment for UVA. Childhood UVA was associated with increased melanoma risk within strata of UVB. Childhood UVB was not associated with melanoma after adjustment for UVA, but there was some evidence of lower risk with increased lifetime ambient UVB after UVA adjustment.
Conclusions
Melanoma risk was elevated among participants living in locations with high annual childhood and lifetime UVA after controlling for UVB. With confirmation, these findings support increased protection from solar UVA for melanoma prevention.
Melanoma of the skin is the fifth most common cancer in the United States, with an estimated 97 610 new cases in 2023 (1). Melanoma incidence is increasing in the United States, particularly among women, with an average annual percent change of 1.8 from 2014 to 2018 (2). Similar increases in melanoma incidence are reported in Australia and northern Europe (3). Established risk factors for melanoma include increased number of nevi, light pigmentary traits, family history of melanoma, personal history of previous skin cancer, chronic immunosuppression, and exposure to ultraviolet radiation (UVR) (4,5).
Although UVR exposure, particularly during childhood (6), is widely considered to be the main preventable cause of melanoma, the health effects of the specific wavelengths of UV light are poorly understood. UVA (320-400 nm) exposure results in deeper skin penetration (dermis), skin aging, and indirect DNA damage through oxidative stress, and it breaks down vitamin D bound to the vitamin D receptor. UVA is also responsible for 3 times greater immune-suppressive effects in the skin compared with UVB (280-319 nm) for moderate daily sun exposure (7). In contrast, UVB penetrates only the surface of skin (epidermis), causes sunburn and direct DNA damage, and stimulates the production of vitamin D (8-10).
Epidemiological evidence for a role of UVA in melanoma risk is based largely on studies of indoor tanning devices, which primarily emit UVA and are associated with increased melanoma risk (11,12). Use of sunscreens, which historically reduced primarily UVB-associated sunburn (13), have also been hypothesized to increase overall duration of sun exposure and total UVA exposure (12), as noted by IARC’s evaluation of epidemiological studies from earlier time periods (14). An ecological study in Scandinavia found that the incidence of melanoma is more closely related to changes in UVA (based on latitude), whereas squamous cell carcinoma is more closely related to UVB (15). To our knowledge, ambient UVA and UVB have not been previously examined in relation to melanoma incidence in a large prospective cohort with substantial heterogeneity in ambient solar ultraviolet radiation due to wide residential latitude and altitude differences and with detailed skin cancer risk factors.
We sought to assess the relationship between UVA, UVB, and incidence of melanoma using data from the United States Radiologic Technologists (USRT) study. This is a large nationwide cohort, which has collected geocoded information on residence over the lifetime linked to satellite-based estimates of UVR, personal sun sensitivity characteristics, and lifestyle factors, in a population exposed to a wide range of ambient UVR.
Materials and methods
Overview
The USRT is an occupational cohort of 146 022 radiologic technologists who were certified by the American Registry of Radiological Technologists for at least 2 years from 1926 through 1982. Detailed descriptions of the cohort and methods have been previously published (16,17). Self-administered questionnaires were mailed to cohort members during 4 time periods: 1) 1983-1989, 2) 1994-1998, 3) 2003-2005, and 4) 2012-2013. The third questionnaire (2003-2005), which collected information on residential location over the lifetime, was completed by 73 838 (73%) of 101 694 technologists who were located, living, and answered either the first or second questionnaires. The fourth questionnaire (2012-2013) was completed by 58 587 (62%) of 93 787 technologists who were located, living, and responded to either the first or second questionnaires. Informed consent was obtained to collect medical records to confirm self-reports of melanoma and certain types of other cancers. The USRT study has been annually approved by human subjects’ review boards at the University of Minnesota and the National Cancer Institute.
Study population and cancer ascertainment
Our study population included participants who reported being cancer-free (except for keratinocyte carcinomas and basal and squamous cell carcinoma) at start of follow-up (earliest of first or second questionnaire) and who completed the third questionnaire, which collected information on lifetime residence (73 492) (Supplementary Figure 1, available online). We excluded those who had zero or less follow-up time (excluded, n = 1865) because of later reported cancer diagnosis. Because of a small number of cases who reported a race or ethnicity other than non-Hispanic White (4849 participants, 12 melanoma cases), we included only non-Hispanic White participants. We also excluded participants who did not report their childhood residential history (excluded, n = 3933), resulting in a total study population of 62 785 participants. Follow-up continued from the earliest of first or second questionnaire until the earlier of a first primary cancer diagnosis (excluding keratinocyte carcinoma) or completion of the latest (third or fourth) questionnaire.
Melanoma was ascertained from questionnaires through self-report (cases, n = 837). Confirmatory medical records and pathology reports were requested for all self-reported cases. Confirmation of invasive melanoma diagnoses were successfully obtained for 464 of 837 (55%) cases, with 397 confirmed through medical records and 67 confirmed with cancer registry linkage only (18). A positive predictive value for melanomas self-reported from the fourth questionnaire has been found to be 82.9%. Because our results did not substantially differ after restricting to confirmed cases, we included the remaining 373 cases for whom medical records were not received.
Exposure assessment
Information on residential location over the lifetime (sought for main residence at ages 0-12, 13-19, 20-39, 40-64, and ≥65 years) was ascertained in the third questionnaire. Average annual lifetime ambient UVR exposure was derived by linking the geocoded residential history to the Total Ozone Mapping Spectrometer database maintained by the National Aeronautics and Space Administration (19). Cloud-adjusted daily ambient ultraviolet irradiance 305 nm (UVB) and 380 nm (UVA) are provided on a 1° latitude by 1° longitude grid. UVR estimates have had little variation since the 1970s, when measurements were initiated (20); thus, daily noontime estimates were averaged annually and for summer months (June, July, and August). These UVR estimates account for the number of years a participant is in each age period over the follow-up. UVA, UVB, and melanoma risk was assessed for annual and summer levels across various life periods (0-12 [“childhood”], 13-19 [“adolescent”], 20-39, 40-64, and ≥65 years [adult], and lifetime). If an age period is missing location, the UVR for the locations in other periods are used in the calculation of adult and lifetime average (number of participants with missing locations by period: 981 [13-19 years], 1799 [20-39 years], 1859 [40-64 years], and 523 [≥65 years]). Hereafter, we refer to these measures as “ambient UVA” and “ambient UVB.”
Statistical analysis
To evaluate the relationship between ambient UVA, UVB, and first primary melanoma, Poisson regression was used to compute incidence rate ratios (IRRs) and 95% confidence intervals (CIs) using a table of person-years and melanoma cases stratified on exposure variables and potential confounding factors. The 3 main models considered were a model with 1) ambient UVA or UVB quartile, 2) ambient UVA and UVB quartile, and 3) ambient UVA or UVB quartile stratified on ambient UVB or UVA quartile, respectively. Strata with fewer than 5 cases were combined with the nearest populated quartile for stratified analyses. The following variables were considered to be potential confounders because they were statistically significantly associated with both ambient UVR and melanoma incidence but were not believed to be on the causal pathway: attained age, calendar year, birth cohort, education, marital status, body mass index, smoking history, alcohol consumption, physical activity, occupational ionizing radiation dose to the skin, eye iris color, skin complexion, hair color, Celtic/Gaelic ancestry, and self-reported time outdoors over the lifetime. We used multiple imputation with chained equations as implemented in IVEware to impute missing values (21). We created 5 imputed datasets and combined the estimates using PROC MIANALYSIS in SAS 9.4 with Rubins’ formula for the variance. Birth cohort (5-year groups), sex, and eye iris color were included in all UVR models for a priori reasons because they were considered in previous publications and are known to be risk factors for melanoma in this cohort (22,23). Other considered potential confounders were not associated with melanoma risk or did not influence UVA/UVB effect estimates. We examined whether the childhood and lifetime annual UVA/UVB relationship with melanoma changes by year of follow-up by testing the significance of an interaction term for calendar year of follow-up based on a likelihood ratio test.
We conducted analyses to determine if risk estimates differed for the subset of confirmed cases (n = 464). We conducted additional analyses using UVA = Q1, UVB = Q1 as a reference group to enable comparisons of adjusted IRRs in various strata with a single reference group. We conducted further analysis to understand whether survival of individuals diagnosed with melanoma to time of self-reported melanoma diagnosis affected incidence rate ratios by using a nested case-control sample (1:4 matched on sex, age, birth cohort, and follow-up time) (24). Statistical tests were 2-sided, and P values were considered statistically significant at the 0.05 α level. Analyses were conducted using Epicure (Hirosoft) and SAS 9.4 software (SAS Institute, Cary, NC).
Results
The study population included 62 785 non-Hispanic White participants residing throughout the United States, with 1 423 421 person-years of follow-up and 837 melanoma cases. The study population was 80% female and had a mean age of 39 years at entry. IRRs for melanoma were significantly increased for older age at entry, more recent birth cohort, male individuals, and among participants with fair complexion, light eye and hair color, and Celtic/Gaelic ancestry after adjustment for age (Table 1). The distribution of study participants, melanoma cases, and person-years at risk across quartiles of childhood and lifetime UVA and UVB is shown in Supplementary Table 1 (available online). Most study participants and cases were in the same quartiles of UVA and UVB for both childhood and lifetime. However, 179 of 837 (21.4%) and 173 of 837 (20.7%) of melanoma cases were in different UVA and UVB quartiles for childhood and lifetime average UVR, respectively.
Table 1.
Selected characteristics of 62 785 non-Hispanic White participants in the US Radiologic Technologists studya
| Characteristics | Person-years | No. participants | No. melanoma | IRR (95% CI)a |
|---|---|---|---|---|
| Total | 1 423 421 | 62 785 | 837 | |
| Age at entry,b years | ||||
| 20-29 | 280 003 | 10 999 | 122 | Referent |
| 30-39 | 664 134 | 27 600 | 376 | 1.30 (1.06 to 1.59) |
| 40-49 | 337 023 | 16 117 | 213 | 1.45 (1.16 to 1.81) |
| 50-85 | 142 296 | 8069 | 126 | 2.03 (1.58 to 2.61) |
| Year of birth | ||||
| 1905-1940 | 243 798 | 11 645 | 188 | Referent |
| 1941-1945 | 200 906 | 8893 | 126 | 1.15 (0.90 to 1.46) |
| 1946-1950 | 325 480 | 14 116 | 200 | 1.35 (1.07 to 1.71) |
| 1951-1955 | 411 648 | 17 770 | 205 | 1.31 (1.02 to 1.70) |
| 1956-1966 | 241 624 | 10 361 | 118 | 1.51 (1.11 to 2.05) |
| Sexc | ||||
| Female | 1 151 090 | 50 202 | 598 | Referent |
| Male | 272 366 | 12 583 | 239 | 1.59 (1.36 to 1.84) |
| Eye color | ||||
| Brown | 329 625 | 14 568 | 141 | Referent |
| Light brown/hazel | 326 834 | 14 438 | 189 | 1.35 (1.08 to 1.67) |
| Blue/green/gray | 721 917 | 31 738 | 478 | 1.54 (1.28 to 1.86) |
| Unknown/missing | 45 080 | 2041 | 29 | 1.62 (1.08 to 2.41) |
| Natural hair color at younger than age 20 years | ||||
| Dark brown/black | 351 696 | 15 582 | 147 | Referent |
| Medium brown | 429 353 | 18 758 | 220 | 1.27 (1.04 to 1.57) |
| Reddish-brown/light brown | 372 284 | 16 435 | 227 | 1.52 (1.23 to 1.87) |
| Red/blonde | 268 496 | 11 940 | 243 | 2.22 (1.81 to 2.73) |
| Unknown/missing | 1626 | 70 | 0 | NE |
| Skin complexion | ||||
| Medium/Dark | 667 541 | 33 575 | 322 | Referent |
| Fair | 533 933 | 27 263 | 488 | 1.89 (1.65 to 2.18) |
| Unknown/missing | 221 946 | 1947 | 27 | 1.62 (1.09 to 2.40) |
| Celtic or Gaelic ancestry | ||||
| No | 716 402 | 31 318 | 382 | Referent |
| Yes | 287 720 | 12 782 | 207 | 1.26 (1.06 to 1.49) |
| Unknown | 267 963 | 11 937 | 147 | 1.01 (0.84 to 1.22) |
| Missing | 151 334 | 6748 | 101 | 1.25 (1.00 to 1.55) |
Adjusted for age except age at entry. IRR = incidence rate ratio; CI = confidence interval; Ref = reference; NE = not estimated.
Mean age at entry of 38.8 years.
Female individuals comprised 80% of the study population.
Iris color, hair color at age 20 or younger, and skin complexion collected from second and third questionnaires.
Results for ambient childhood and lifetime annual UVA analyses are shown in Table 2. The IRRs for melanoma for all categories of childhood ambient UVA and virtually all categories of lifetime average ambient UVA were greater than 1 before and after adjustment for UVB quartile. Incidence of melanoma was significantly increased for the highest quartile of childhood UVA exposure after adjustment for UVB (IRR = 2.82; 95% CI = 1.46 to 5.44). We observed a monotonic increasing trend with increasing childhood and lifetime ambient UVA quartile before and after UVB adjustment (childhood Ptrend = .001; lifetime average Ptrend < .001). Melanoma risk was significantly elevated with increasing childhood UVA within strata of UVB Q2 and Q3. Results were similar for lifetime average UVA. These patterns of increased risk were also observed for annual UVA in adolescence, adulthood (Supplementary Table 2, available online), and summer UVA exposure (Supplementary Table 3, available online), although summer UVA was not significantly associated with melanoma after adjustment for UVB.
Table 2.
Incidence rate ratios and 95% confidence intervals for childhood ambient UVA quartile and melanoma among non-Hispanic White participants in the US Radiologic Technologists study
| UVA Quartile | N Cases | Model 1a | Model 2: adjusted for UVB quartile | Model 3: stratified by UVB |
|||
|---|---|---|---|---|---|---|---|
| UVB Q1 | UVB Q2 | UVB Q3 | UVB Q4 | ||||
| IRR (95% CI) for childhood UVAb | |||||||
| Q1 | 175 | Referent | Referent | Referent | Referent | ||
| Q2 | 188 | 1.06 (0.86 to 1.30) | 1.10 (0.84 to 1.43) | 1.07 (0.76 to 1.52) | 1.10 (0.72 to 1.67) | Referent | |
| Q3 | 235 | 1.36 (1.12 to 1.65) | 1.53 (1.10 to 2.14) | 1.69 (1.07 to 2.67) | 1.24 (0.89 to 1.74) | Referent | |
| Q4 | 239 | 1.37 (1.13 to 1.66) | 2.82 (1.46 to 5.44) | 2.34 (1.14 to 4.81) | 1.82 (0.58 to 5.69) | ||
| P trend | <.001 | .001 | |||||
| IRR (95% CI) for lifetime average UVAc | |||||||
| Q1 | 159 | Referent | Referent | Referent | Referent | ||
| Q2 | 225 | 1.41 (1.15 to 1.73) | 1.73 (1.31 to 2.27) | 1.79 (1.28 to 2.50) | 1.62 (1.01 to 2.62) | Referent | |
| Q3 | 192 | 1.21 (0.98 to 1.49) | 1.90 (1.30 to 2.78) | 2.31 (1.34 to 3.99) | 0.83 (0.57 to 1.21) | Referent | |
| Q4 | 261 | 1.62 (1.33 to 1.97) | 3.39 (2.08 to 5.52) | 1.38 (0.82 to 2.30) | 2.36 (1.21 to 4.58) | ||
| P trend | <.001 | <.001 | |||||
All models adjusted for attained age, birth cohort (<1941, 1941-1945, 1946-1950, 1951-1955, 1956+), sex, and eye color. IRRs not shown for fewer than 5 cases. IRR = incidence rate ratio; CI = confidence interval; Q = quartile; Ref = reference.
Childhood UVB quartiles are 5-23, 24-25, 26-32, and 33-97; childhood UVA quartiles are 174-420, 421-447, 448-492, and 493-840.
Lifetime UVB quartiles are 9-24, 25-27, 28-36, and 37-81; lifetime UVA quartiles are 260-428, 429-463, 464-522, and 523-720.
The IRRs for melanoma for all categories of childhood and lifetime average ambient UVB were greater than 1 before adjustment for UVA quartile with significantly increased trends (childhood Ptrend = .005; lifetime average Ptrend = .013) (Table 3). After adjustment for UVA quartile, there were no significant trends for childhood UVB (Ptrend = .143) and decreasing risk for increasing lifetime average UVB (Ptrend = .001). Incidence of melanoma was significantly decreased for the highest quartile of lifetime UVB exposure after adjustment for UVA (IRR = 0.45; 95% CI = 0.28 to 0.73). Melanoma risk was not significantly associated with childhood UVB within strata of UVA. Annual UVB in adolescence or adulthood was not associated with increased risk after adjustment for UVA (Supplementary Table 4, available online). Summer UVB was not significantly associated with melanoma after adjustment for UVA (Supplementary Table 5, available online).
Table 3.
Incidence rate ratios and 95% confidence intervals for ambient UVB quartile and melanoma among non-Hispanic White participants in the US Radiologic Technologists study
| UVB Quartile | N Cases | Model 1a | Model 2: adjusted for UVA quartile | Model 3: stratified by UVA |
|||
|---|---|---|---|---|---|---|---|
| UVA Q1 | UVA Q2 | UVA Q3 | UVA Q4 | ||||
| IRR (95% CI) for childhood UVBb | |||||||
| Q1 | 188 | Referent | Referent | Referent | Referent | ||
| Q2 | 191 | 1.14 (0.93 to 1.40) | 0.99 (0.76 to 1.29) | 0.96 (0.64 to 1.44) | 0.98 (0.68 to 1.41) | Referent | |
| Q3 | 225 | 1.24 (1.02 to 1.51) | 0.87 (0.62 to 1.21) | 0.97 (0.63 to 1.50) | 0.80 (0.59 to 1.08) | Referent | |
| Q4 | 233 | 1.30 (1.07 to 1.58) | 0.48 (0.25 to 0.92) | 0.45 (0.14 to 1.45) | 0.55 (0.28 to 1.06) | ||
| P trend | .005 | .143 | |||||
| IRR (95% CI) for lifetime average UVBc | |||||||
| Q1 | 185 | Referent | Referent | Referent | Referent | ||
| Q2 | 206 | 1.16 (0.95 to 1.42) | 0.79 (0.60 to 1.03) | 0.84 (0.53 to 1.35) | 0.73 (0.52 to 1.01) | Referent | |
| Q3 | 202 | 1.09 (0.89 to 1.33) | 0.61 (0.42 to 0.88) | 0.74 (0.47 to 1.16) | 0.61 (0.43 to 0.86) | Referent | |
| Q4 | 244 | 1.32 (1.09 to 1.59) | 0.45 (0.28 to 0.73) | 0.36 (0.17 to 0.73) | 0.83 (0.55 to 1.24) | ||
| P trend | .013 | .001 | |||||
All models adjusted for attained age, birth cohort (<1941, 1941-1945, 1946-1950, 1951-1955, 1956+), sex, and eye color. IRRs not shown for fewer than 5 cases. IRR = incidence rate ratio; CI = confidence interval; Q = quartile; Ref = reference.
Childhood UVB quartiles are 5-23, 24-25, 26-32, and 33-97; childhood UVA quartiles are 174-420, 421-447, 448-492, and 493-840.
Lifetime UVB quartiles are 9-24, 25-27, 28-36, and 37-81; lifetime UVA quartiles are 260-428, 429-463, 464-522, and 523-720.
Analyses restricted to confirmed melanoma cases revealed similar patterns in melanoma risks with childhood and lifetime UVA and UVB quartiles after mutual stratification (Supplementary Table 6, available online). Analyses using the reference group of UVA = Q1, UVB = Q1 also indicated similar patterns of risk within strata of childhood and lifetime UVA and UVB (Supplementary Table 7, available online). Restricting the study population to study participants with no history of keratinocyte carcinoma had little impact on the IRRs (data not shown). Analyses accounting for potential survival bias found adjusted effect estimates did not substantively differ from estimates not accounting for potential survival bias (data not shown). There was no evidence that calendar year of follow-up modified the relationship between UVA/UVB and melanoma (data not shown).
Discussion
In this nationwide United States cohort of indoor workers exposed to a wide range of ambient UVA and UVB, melanoma risk was elevated among non-Hispanic White participants living in locations with higher childhood and lifetime ambient UVA, for various strata of UVB. The overall pattern of IRRs suggests no increased risk of melanoma associated with childhood UVB after adjustment for UVA.
Our findings of increased melanoma risk associated with ambient UVA are supported by some epidemiological studies of artificial tanning devices and sunscreen use, which may result in increased exposure to UVA (12). Indoor tanning devices typically emit levels of UVA irradiance much higher than the sun, while emitting lower UVB than natural sunlight (11). A recent meta-analysis of 36 studies and 14 583 melanoma cases reported a summary relative risk of 1.27 (95% CI = 1.16 to 1.39) for ever vs never use of indoor tanning (25). Sunscreens block a greater proportion of UVB (to prevent sunburn) and, as a result, may extend time spent outside, thus increasing UVA exposure relative to the natural distribution received from sunlight, particularly for sunscreen formulations before FDA guidance in 2011 (9,13,14). Evidence of sunscreen use and melanoma risk has been inconsistent. A randomized trial set in Australia among adults 25-75 reported a reduced risk of melanoma associated with sunscreen use (26), but a meta-analysis of population-based observational studies of sunscreen use and risk of melanoma has reported summary relative risks greater than 1 for case-control and cohort studies (27). Because individuals who are sensitive to sun exposure may be more likely to use sunscreen and sunscreen is used by people who spend more time outdoors, confounding by indication may bias risk estimates toward a positive association between sunscreen use and skin cancer in observational studies (28).
We found little evidence that childhood ambient UVB was associated with risk of melanoma after adjustment for UVA, and for lifetime UVB, several effect estimates were significantly below the null value of 1. Although ultraviolet radiation from sun exposure has been classified as carcinogenic to humans by the International Agency for Research on Cancer, studies examining UVB after controlling for UVA are lacking. A recent study of ambient UVR weighted toward UVB found an increased risk of melanoma in the highest quintile (29). A meta-analysis of sun exposure and melanoma found a nonsignificant association for chronic sun exposure, but significant associations with sunburn, particularly in childhood (30). Although sunburn is caused primarily by UVB, it may also be a surrogate for increased overall sun exposure. It has been hypothesized that vitamin D generated from UVB exposure may be protective for some cancers. However, a recent meta-analysis of 6 studies found circulating levels of 25-hydroxyvitamin D to be associated with higher melanoma risk (summary relative risk per 30 nmol/L = 1.42; 95% CI = 1.17 to 1.72), although confounding by sun exposure was likely according to Mahamat-Saleh and colleagues (31).
To our knowledge, this is the first study to evaluate UVA and UVB in relation to risk of melanoma in a large nationwide US cohort with information on lifetime ambient UVR exposures on the basis of residential history geocoded and linked with NASA satellite data at different ages. Surface solar UVR is composed of approximately 5% UVB and 95% UVA, with much of UVB filtered by stratospheric ozone (32). Atmospheric changes in aerosols, cloud cover, and surface reflectivity (eg, snow cover) because of climate change are expected to disproportionately affect the levels of UVA and UVB that reach the Earth’s surface (33). The nationwide distribution of the cohort from all US states ensured a large range of microclimates that allowed for opportunities to examine participants living in locations with relatively high UVB (eg, at high altitudes) and relatively high UVA (eg, locations with high annual cloud cover and precipitation) (19). However, our study setting was still limited in that UVA and UVB were highly correlated. We did not have individual measures of personal UVA, UVB, or overall UVR exposure (eg, sun seeking or sun protective behaviors). However, detailed data on sun sensitivity and other characteristics were available in this cohort of indoor workers, and our results were not sensitive to inclusion of various potential confounders. Melanoma risks in the confirmed group were similar to those in the combined group of all cases, lending validity to the self-reported melanoma cases in this cohort of medical workers.
Our study has several additional limitations. The generalizability of our results may be limited because this is an occupational cohort of primarily female indoor workers. Although the study population was restricted to those who answered the third questionnaire, it was representative of the overall cohort with regard to age at entry, sex, and age- and sex-specific melanoma incidence (34). This study also lacks information on some important skin cancer risk factors, such as Fitzpatrick skin type or information on nevus density. Information on sun protection such as seeking shade, use of hats and clothing, artificial tanning, and sunscreen use was not available at the baseline of the study.
We found evidence for an increased risk of melanoma with UVA, but little evidence for an increased risk associated with ambient UVB after mutual adjustment. We cannot rule out the possibility of residual confounding from some unidentified factor, possibly related to geographical locations of residence or behavioral factors. Although it is challenging to isolate the effects of UVA and UVB, our findings support a role for solar ambient UVA on melanoma risk. With confirmation in other study populations, these findings support increased and effective protection from solar UVA for melanoma prevention.
Supplementary Material
Acknowledgments
We thank the study participants and Liana Watson of the American Registry of Radiologic Technologists for their continued support of this study, Diane Kampa and Allison Iwan of the University of Minnesota for study management and data collection, and Jeremy Miller of Information Management Systems for data preparation. This research was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services. The funder did not play a role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; or the decision to submit the manuscript for publication.
Contributor Information
Elizabeth K Cahoon, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA.
Soutrik Mandal, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA; Division of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Ruth M Pfeiffer, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA.
David C Wheeler, Department of Biostatistics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Michael R Sargen, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA.
Bruce H Alexander, Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Cari M Kitahara, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA.
Martha S Linet, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA.
Jim Z Mai, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA.
Data availability
Data are maintained by the National Cancer Institute, Division of Cancer Epidemiology and Genetics, and are available upon submission and approval of a research proposal and completion of a Data Transfer Agreement.
Author contributions
Elizabeth K. Cahoon, PhD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Writing—original draft; Writing—review & editing), Soutrik Mandal, PhD (Conceptualization; Data curation; Formal analysis; Methodology; Software; Writing—review & editing), Ruth M. Pfeiffer, PhD (Conceptualization; Formal analysis; Methodology; Software; Writing—review & editing), David C. Wheeler, PhD (Conceptualization; Data curation; Methodology; Writing—review & editing), Michael R. Sargen, MD (Investigation; Methodology; Writing—review & editing), Bruce H. Alexander, PhD (Conceptualization; Data curation; Investigation; Methodology; Project administration; Writing—review & editing), Cari M. Kitahara, PhD (Data curation; Investigation; Methodology; Project administration; Supervision; Writing—review & editing), Martha S. Linet, MD, MPH (Conceptualization; Data curation; Investigation; Methodology; Project administration; Supervision; Writing—original draft; Writing—review & editing), Jim Z. Mai, MD, PhD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Writing—original draft; Writing—review & editing).
Funding
This research was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services.
Conflict of interest
The authors declare no potential conflicts of interest.
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Data Availability Statement
Data are maintained by the National Cancer Institute, Division of Cancer Epidemiology and Genetics, and are available upon submission and approval of a research proposal and completion of a Data Transfer Agreement.