Basal cell carcinoma (BCC) incidence for men (A) and women (B). Squamous cell carcinoma incidence for men (C) and women (D).
Basal cell carcinoma incidence for men (A) and women (B). Squamous cell carcinoma incidence for men (C) and women (D). The shaded line is the exponential trend line.
eAppendix. Search Strategy
eTable 1. Quality Assessment Checklist for Included Studies
eTable 2. Study Inclusion Criteria
eTable 3. Summary of Studies Satisfying the Inclusion Criteria and Included in the Analyses
Xiang F, Lucas R, Hales S, Neale R. Incidence of Nonmelanoma Skin Cancer in Relation to Ambient UV Radiation in White Populations, 1978-2012Empirical Relationships. JAMA Dermatol. 2014;150(10):1063-1071. doi:10.1001/jamadermatol.2014.762
Copyright 2014 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
Nonmelanoma skin cancers (NMSCs) are the most common cancers in fair-skinned populations. Their incidence continues to increase in many countries. Exposure to UV radiation (UVR) is the primary cause of NMSC, although the pattern of exposure that gives rise to different types of NMSC appears to vary.
To examine dose-response relationships between ambient UVR levels and NMSC incidence at the population level.
Design, Setting, and Participants
Peer-reviewed literature published from January 1, 1978, through December 31, 2012, that provided age- and sex-specific incidence of NMSC in white populations worldwide was systematically reviewed.
Mean erythemally weighted daily ambient UVR levels for each study location were derived from satellite data.
Main Outcomes and Measures
The incidence of NMSC in white populations worldwide as reported in population-based studies.
Forty eligible publications were included in the analysis. Analysis models that contained age group, sex, study year, mean daily UVR, and day-to-day variability of UVR explained most of the variability in NMSC incidence: 82% for basal cell carcinoma (BCC) and 85% for squamous cell carcinoma (SCC). Exclusion of studies in which imputation of age-specific incidence data from standardized rates was required improved the model fit to 85% for BCC and 88% for SCC. Higher mean daily UVR was associated with higher NMSC incidence rates; this was greater in men than women for BCC (70% vs 60%) but greater in women for SCC (99% vs 92%). Incidence rates for BCC and SCC were higher among those older than 60 years, but the increase with age was steeper for those younger than 60 years.
Conclusions and Relevance
Our models highlight the etiologic differences between BCC and SCC and allow prediction of NMSC incidence for data-poor regions and under changing demographic and environmental conditions.
Nonmelanoma skin cancers (NMSCs), predominantly squamous cell carcinoma (SCC) and basal cell carcinoma (BCC), are the most common cancers in fair-skinned populations throughout the world.1 Their incidence has been increasing during the last 40 years. In Australia, NMSCs comprise 75% of all cancers and are the most costly cancers, accounting for A$511 million in 2010.2 In the United States, the estimated total annual expenditure for NMSC care is $650 million.3
Exposure to UV radiation (UVR) is the primary cause of NMSC, although the pattern of exposure that gives rise to different types of NMSC appears to vary. Squamous cell carcinoma is predominantly caused by long-term sun exposure.4,5 The association between sun exposure and BCC appears to be more complex. A relatively high proportion of BCCs occur on body sites that are not routinely exposed to the sun,6,7 and exposure early in life or an intermittent exposure pattern may be more important than simple cumulative exposure.8
There is considerable variability in NMSC incidence according to geographic location, with approximately a 10-fold difference between Australia and Scotland.9,10 Epidemiologic studies11,12 performed in a single location that examined the role of sun exposure have mainly generated odds ratios or relative risks that are less than 2. Although this may be due to the inherent challenges in measuring individual sun exposure, it may also indicate that individual variability in behavior is far less important than the ambient UVR to which a population is exposed.
Establishing public health policy that balances the risks and benefits of sun exposure requires a comprehensive understanding of the association between UVR dose and NMSC risk, with population-level analyses being arguably more important. We conducted an ecologic study to examine dose-response relationships between ambient UVR levels and NMSC incidence at the population level (separately for BCC and SCC). The analysis models estimate the proportion of variability in population-based NMSC incidence that can be explained by differences in ambient UVR without taking account of individual-level sun exposure behavior. This information has the added advantage of permitting estimation of risk under changing UVR conditions and in regions without population-based data on NMSC incidence.
This study used only previously published data. Human ethics approval was provided as applicable for the individual studies as described in the original publications and was not required for this additional analysis. We used estimates of erythemally weighted ambient UVR derived from satellite measurements of column ozone and incidence data from epidemiologic studies to develop empirical dose-response relationships for BCC and SCC.
For purposes of our search, we defined NMSC as BCC or SCC. We searched the PubMed database for articles published from January 1, 1978, through December 31, 2012, using the keywords nonmelanoma skin cancer AND incidence (68 articles), keratinocyte cancer AND incidence (2 articles), basal cell carcinoma AND incidence (201 articles), and squamous cell carcinoma AND incidence (208 articles) (for specific search strategies, see the eAppendix in the Supplement).
All titles, abstracts, or text, as necessary, were reviewed in detail by 2 of us (R.L. and F.X.), and only studies conducted in white populations and with full texts published in English were retained. To assess the quality of included studies, we used a checklist that considered 5 aspects of the study methods, including NMSC diagnostic criteria, study sample, study location, study year, and data-reporting method (eTable 1 in the Supplement). Using these criteria, we categorized articles as class I to III (eTable 2 in the Supplement). Articles categorized as class III were excluded from the current analysis (79 articles).
For each eligible article, the following information was extracted and recorded on a spreadsheet: type of NMSC (BCC or SCC), study year(s), study location(s), and incidence rates (age- and sex-specific incidence rates or standardized incidence rates, depending on availability). For studies in which incidence rates were reported using graphs, ImageJ software13 was used to derive the relevant data. Latitude and longitude coordinates for each study location were assigned in a geographic information system (Quantum GIS, version 1.7.4; QGIS Development Team).
Mean daily ambient UVR levels weighted to the action spectrum for sunburn14 were estimated for each study location(s) and study year(s) with the geographic information system using 2 databases: the International Research Institute web-based data library (1979-2004)15 and the National Aeronautics and Space Administration Ozone Monitoring Instrument (2005-2012).16 The R statistical software package (R Project for Statistical Computing) was used to extract data from the geographic information system. The resolution (1 grid cell) of the satellite data was 1° latitude and 1.25° longitude. For studies conducted in large geographic regions that consisted of more than one grid cell, the ambient UVR was calculated as the mean ambient UVR for all grid cells (eg, national data from a country with a wide latitude range, such as Australia9,17,18). We did not use population-weighted ambient UVR for Australia-wide studies because the population is concentrated in the South, whereas the highest NMSC incidence is in the North. Use of population-weighted UVR would introduce a false magnitude of any association. For studies conducted during several years, the ambient UVR was calculated as the mean ambient UVR for all calendar years. For studies conducted before 1979 or for which the study median year was before 1979, ambient UVR data in 1979 were used as a substitute for the mean ambient UVR of the whole study period.
Incidence data were converted to World Health Organization age groups (0-4, 5-14, 15-29, 30-44, 45-59, 60-69, 70-79, and ≥80 years) using DISMOD II.19 For studies that did not include all age groups, we estimated missing data as follows: for age groups younger than the youngest reported age group, incidence rates were assumed to be zero, and for age groups older than the oldest reported age group, incidence rates were extrapolated using the incidence pattern from another study with similar latitude and study year(s) that had data available for these groups.
For studies that reported only age-standardized incidence rates (the target study), the age-specific incidence rate for each age group was imputed using another study with similar latitude and study year(s) that had data available for all age groups (the reference study). That is, we used the pattern of age-specific incidence from the reference study to impute the age-specific incidence that would provide us the summary age-standardized incidence rate from the target study.
We used Poisson distribution regression analysis to model the association between BCC or SCC incidence rates and the explanatory variables. Given that NMSCs rarely occur in children, all regression analyses were restricted to age groups of 15 years and older. For each model, robust SEs were obtained to control for mild violation of the distribution assumption that the variance equals the mean.20 Poisson regression models included a trend variable (study year; if the incidence rate was reported for several years, the median calendar year was chosen to represent the study year); dummy variables for age group, sex, and mean daily UVR in the study year(s); and a variable that indicated the mean day-to-day variability of surface UVR (root mean square anomaly). Analyses stratified by study location, sex, and age group were also undertaken. Other models (ie, negative binomial and ordinary least squares regression with log transformation) were explored, with regression diagnostics revealing Poisson regression to be the best option. P ≤ .05 was considered statistically significant. Statistical analysis was performed using STATA software, version 12.0 (StataCorp LP).
Forty articles were identified and met the inclusion criteria; 36 articles documented BCC incidence rates and 32 documented SCC incidence rates ( eTable 3 in the Supplement). The NMSC incidence rates varied substantially across different geographic locations. For example, for studies conducted in the 1990s, the BCC incidence rates (per 100 000 person-years) for men 80 years and older ranged from 475 in Trento, Italy21 (46°N and 11°E; annual mean ambient UVR, 0.8 kJ/m2) to 14 173 in Townsville, Australia (19°S and 147°E; annual mean ambient UVR, 1.8 kJ/m2).22 The corresponding SCC incidence rates ranged from 79 in New Hampshire23 (44°N and 11°W; annual mean ambient UVR, 0.7 kJ/m2) to 12 149 in Townsville, Australia.22
Figure 1 illustrates the association between ambient UVR and NMSC according to age group and sex. The dose-response curves revealed an exponential increase in NMSC incidence with increasing ambient UVR.
Age group, sex, and study year explained 37%, 3%, and 3% of the variability in BCC incidence rates, respectively. The corresponding proportions for SCC were 34%, 3%, and 6%. Ambient UVR alone explained 37% of the variability in BCC incidence rates and 40% of the variability in SCC incidence rates.
A model that contained study year, age group, sex, mean daily UVR, and day-to-day variability of UVR (root mean square anomaly) explained 82% of the variability in the incidence rates of BCC and 85% for SCC (full model). Restriction of the analysis to studies that reported age-specific incidence data, without data imputed from the summary age-standardized rate (restricted models), improved the variability explained by the models to 85% for BCC and 88% for SCC (Table 1).
All the explanatory variables were significantly associated with NMSC in the fully adjusted models (Table 1). The NMSC incidence rates were significantly higher in men than in women and increased with age. Higher mean daily UVR was associated with higher NMSC incidence rates, with the effect greater for SCC than for BCC (P < .001). The BCC and SCC incidence rates increased with calendar year (Figure 2). Greater day-to-day variability in ambient UVR levels was associated with lower incidence of BCC and SCC. In the restricted models, this effect was reduced and no longer statistically significant (P = .53 for BCC and P = .37 for SCC). Analyses stratified by latitude (Table 2) revealed that the increase in NMSC incidence for a 1-kJ/m2 increase in daily UVR was greater at lower latitudes (≤40°N or ≤40°S) than at higher latitudes (exponentiated coefficients of 40% vs 25% for BCC and 68% vs 11% for SCC). At higher latitudes, there was a slight, but statistically significant, decrease in SCC incidence rates with calendar year (P = .001).
Table 3 provides the results of the full models stratified by sex. The increase in incidence with a 1-kJ/m2 increase in daily UVR was greater in men than in women for BCC (70% vs 60%) but greater in women for SCC (99% vs 92%).
Finally, the analyses were stratified by age group (Table 4). For populations older than 60 years, men were 1.6 times more likely to develop BCC than women compared with 1.4 times for populations younger than 60 years (P = .001). Although the incidence rates were significantly higher in older age groups for both strata, the increase with age was steeper for people younger than 60 years. In people younger than 60 years, the BCC incidence in the oldest age group (45-59 years) was 24 times that in the youngest age group (15-29 years) when holding other factors constant. However, in people older than 60 years, the BCC incidence in the oldest age group (≥80 years) was about twice that in the youngest group (60-69 years). The pattern was similar for SCC incidence.
Our results reveal that more than 80% of the variation in NMSC incidence rates can be predicted by models that include ambient UVR, day-to-day variability of UVR, age group, sex, and study year. These factors explained less of the variability in BCC than in SCC incidence rates, irrespective of study location, age group, or sex. Overall, a 1-kJ/m2 increase in ambient UVR was associated with a 67% increase in BCC incidence and a 95% increase in SCC incidence, with a stronger effect across lower-latitude locations compared with higher-latitude locations. The NMSC incidence was higher in men than in women and associated with increasing age. To put the unit increase of ambient UVR into perspective, a 1-kJ/m2 increase in mean daily ambient UVR (averaged for a calendar year) is equivalent to the difference between Barcelona, Spain (41.4°N and 2.2°E) and Copenhagen, Denmark (55.7°N and 12.6°E).
The strengths of this analysis are that all included studies are population based with histologically confirmed NMSC cases, and the locations of the studies cover a broad range of latitudes and ambient UVR levels, which has allowed development of precise estimates from the regression models. The quality of the included studies has been reviewed and assessed according to strict criteria. We use an ecologic study design, which is ideal for the examination of these population-level associations. Indeed, although individual-level observational studies11,12 reveal modest increases in NMSC risk in association with (usually self-reported) higher past sun exposure, the ecologic design allows us to quantify the large increase in risk at the population level that is associated with living in a location with higher ambient UVR, taking into account the differences in age, sex, and study year.
This study has some limitations. Most studies included in the current analysis were based on cancer registry data. Incidence data from cancer registries depends on clinical notifications or is based on treatments and is likely to underestimate the true incidence in the population.23,24 In addition, in many countries, NMSCs are still removed by destructive therapies and are not recorded on cancer registries, necessitating epidemiologic studies, often of limited size, in selected geographic areas or specific populations. The derivation of the early satellite UVR data (1979-2004) used a different algorithm than that for the later data (2005-2012), although the differences that result from use of these different algorithms are minor, particularly for the mean data used in this study.25 We have limited the analysis to white populations because of the paucity of information in nonwhite populations. Finally, no measure of individual-level sun exposure behavior was available in the included studies, so we are unable to evaluate the possible additional contribution of this factor to the models.
Our analysis explained most of the variability in NMSC incidence rates because, although there is considerable variability in sun exposure behavior within populations, the mean UVR exposure across many different populations is fairly constant at approximately 3% of the ambient UVR, with a range of 2% to 4%.26,27 Thus, the inclusion of age group, sex, study year, ambient UVR, and daily variability in UVR reflects population-level means in sun exposure behavior.
The results indicate that higher ambient daily UVR is associated with higher NMSC incidence rates in white populations, with a greater magnitude of effect for SCC. A latitude gradient of NMSC incidence rates has been reported previously,17,18,24,28,29 although most analyses have focused on a single country. In the Nurses’ Health Study there were significantly increased risks of SCC and BCC for women living in medium (mean UVR index in August, 6) and high (mean UVR index in August, ≥7) compared with low (mean UVR index in August, ≤5) UVR index locations,30 with a stronger effect for SCC than BCC, consistent with our results. In an older analysis of NMSC incidence in various locations in the United States, UV-B dose explained more than 90% of the variation in incidence rates.31 The analyses used combined BCC and SCC incidence despite the likely different associations with UVR, and data were from a single country and covered a narrow time span (1977-1978). Nevertheless, the value of such modeling was later demonstrated by Stern and colleagues,32 who used the estimated parameters to infer a model of multistage carcinogenesis with 2 UVR dose-dependent stages, which was then used to estimate the risk reduction for NMSC that might be achieved with childhood sunscreen use.
The magnitude of the increase in NMSC incidence for a 1-kJ/m2 increase in mean daily ambient UVR was greatest at low latitudes. At higher latitudes, this small increase in ambient UVR is from a low baseline, in absolute terms, and may be insufficient to initiate carcinogenesis. The weakest model (lowest proportion of variance explained) was for BCC incidence at high latitude locations (R2 = 0.73). This finding is consistent with one study33 from Finland (60°-70°N), which found no north-south gradient for the BCC incidence. This finding may have occurred because the differences in absolute UVR dose were too small in this high-latitude location with low ambient UVR to substantially alter the NMSC risk, or it may also reflect the more complex association between the BCC risk and patterns and level of sun exposure. Alternatively, the increasing trend of spending holidays in sunny locations that is reported for people living in high-latitude locations34 may result in a weakening of the effect of local variation in ambient UVR.
Several previous studies18,35- 37 have found that NMSC incidence has increased over time. Our analyses also indicate this increase, which persists after adjustment for age group, sex, and ambient UVR. In our study, the annual increase in incidence rate was greater for SCC (4%) than for BCC (1%). Previous studies have reported estimates for increasing incidence ranging from 3% to 9% for SCC18,23,37 and 3% to 6% for BCC.18,35- 38 Our slightly lower estimates may be because our results account for age group, sex, and ambient UVR. Temporal trends in NMSC may, at least in part, be due to increased ascertainment through screening, changes in management so that a greater proportion are histologically confirmed, or better improvements in registration. Other explanations include higher levels of exposure to UVR over time, for example, due to lower levels of sun protection by clothing,39 travel to sunny destinations, or use of sunbeds40; exposure to other factors that increase risk, such as specific carcinogens (eg, arsenic)41; or immunosuppression (eg, human immunodeficiency virus or organ transplantation).42 Alternatively, other unknown factors may contribute to the patterns observed in this study. No significant increase in BCC incidence over time was found in the younger group (<60 years). This finding could be interpreted as an early effect of sun protection programs, leading to a beneficial reduction in intermittent UVR exposure, although SCC incidence increased in this age group. Although BCC incidence did not increase significantly over time in high-latitude areas (>40°N or >40°S) across all studies, subregional analyses revealed a significant trend (regression coefficient, 0.05; P < .001) in studies from Europe.
We found that, in general, the incidence of BCC and SCC was higher in men than in women: 1.5 times greater for BCC and 1.9 times greater for SCC. This finding is comparable to findings from previous epidemiologic studies28 and probably reflects traditional role differences whereby men are more likely to have outdoor occupations and leisure activities and use less sunscreen than women,11 generally resulting in higher UVR exposure.27 Our stratified analyses that revealed a greater sex difference in older than in younger populations is consistent with this explanation, with social changes leading to less marked sex differences in occupation and behavior in younger populations.
The BCC and SCC incidence rates increase with age, reflecting the importance of cumulative sun damage. However, the SCC incidence was much more age dependent than the BCC incidence, again supporting previous findings that the development of SCC is more strongly linked to long-term and occupational UVR exposure.4
Although NMSCs seldom cause death, their extraordinarily high incidence combined with the functional and cosmetic morbidity that can result from treatment result in a heavy burden to health care systems.2,3 Our models, which are based on widely available data, could be used to provide estimates of likely NMSC incidence at different locations and among different population subgroups to inform health care policy.
Our results highlight the comparative disease burdens between young and old populations, male and female populations, and regions with high and low ambient UVR. For prevention, we are particularly interested in modifiable risk factors and the proportion of disease that could be prevented by decreasing exposure to a specific risk factor (the population-attributable risk). In our analyses, more than 80% of the variability in NMSC incidence is accounted for by a few variables, most of which are not amenable to change (age group, sex, and study year). Ambient UVR itself is similarly not alterable (except by migration), but it is the pattern of sun exposure in the population that translates ambient UVR into the biologically effective UV dose received. The NMSC risk in a particular region can be modified by shifting the whole population distribution of UVR exposure to lower levels.43 Concerted monitoring and sun safety education, including restrictions on the use of sunbeds,44 are required and have been implemented, particularly in environments with high ambient UVR and for fair-skinned populations. However, there remains a knowledge-behavior gap45 that continues to limit the effectiveness of sun protection programs.
We have modeled NMSC incidence in relation to widely available demographic and UVR data. The NMSC incidence rates were well predicted at the population level by a few key variables (age group, sex, study year, and ambient UVR), without a measure of individual sun exposure behavior. Our models highlight the etiologic differences between BCC and SCC, suggest that BCC incidence is no longer increasing in younger populations, and allow prediction of NMSC incidence for data-poor regions and under changing demographic and environmental conditions. This information can be used to predict future health care needs and to advocate for ongoing funding for sun protection programs.
Accepted for Publication: March 28, 2014.
Corresponding Author: Fan Xiang, PhD, National Centre for Epidemiology and Population Health, Australian National University, Bldg 62, Canberra ACT 0200, Australia (firstname.lastname@example.org).
Published Online: August 6, 2014. doi:10.1001/jamadermatol.2014.762.
Author Contributions: Drs Xiang and Lucas had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: All authors.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Xiang, Lucas, Hales.
Critical revision of the manuscript for important intellectual content: Lucas, Neale.
Statistical analysis: Xiang, Lucas, Hales.
Administrative, technical, or material support: Xiang.
Study supervision: Lucas, Neale.
Conflict of Interest Disclosures: Dr Xiang reported receiving support from a National Health and Medical Research Council Centre of Research Excellence in Sun and Health Postdoctoral Fellowship. Dr Lucas reported receiving support from a National Health and Medical Research Council Career Development Fellowship. Dr Neale reported receiving support from a National Health and Medical Research Council Research Fellowship. No other disclosures were reported.
Additional Contributions: Ivan Hanigan, BA, Fenner School of Environment and Society, Australian National University, Canberra, provided assistance with derivation of the ambient UVR according to location using a geographic information system.