Demographic and Regional Trends in Nonmelanoma Skin Cancer Mortality in the United States, 1999-2020

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We aimed to characterize temporal trends and demographic and regional disparities in age-adjusted NMSC mortality in the U.S. from 1999 through 2020. Methods We conducted a retrospective analysis of CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database from 1999 to 2020 for NMSC. Age-adjusted mortality rates (AAMRs) per 100,000 persons and annual percent change (APC) were calculated and stratified by year, sex, race, age group, and geographic region. Results A total of 68,223 NMSC-related deaths occurred. Overall AAMR increased from 0.845 (95% CI 0.810–0.879) in 1999 to 1.002 (0.971–1.032) in 2020. Trends showed an initial decline (1999–2004 APC − 0.7%), followed by a rise (2004–2020 APC 1.6%). Men had higher mortality than women (1.55 vs 0.43 per 100,000), with significant increases in both sexes (men 1999–2016 APC 1.4%; women 2011–2020 APC 2.5%). NH White individuals exhibited the highest AAMR (1.03) and steepest rise (2005–2015 APC 2.8%), while NH Blacks declined (APC − 1.5%) and Hispanics increased modestly (APC 0.9%). Those ≥ 65 years had the highest AAMR (5.63). Regionally, the South (1.01) and rural areas (1.04) bore the greatest burden, with persistent increases (rural APC 1.7%; suburban APC 1.4%). Conclusions Despite diagnostic and therapeutic advances, U.S. NMSC mortality has risen, with marked demographic and geographic disparities. Enhanced mortality surveillance, targeted prevention efforts, and equitable access to dermatologic care are needed to mitigate this growing public health burden. Demographic trends Regional variation Nonmelanoma skin cancer Mortality United States Age-adjusted mortality Joinpoint regression Epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Nonmelanoma skin cancer (NMSC) poses a significant burden on global health and the economy, with its incidence rising in aging populations. 1 Representing nearly one-third of all cancers diagnosed annually, NMSC is the most prevalent malignancy worldwide. 2 Within NMSC, basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) account for 99% of tumors and over 5,400 global deaths each month. 3 Ferlay et al. report that estimated mortality rates for all types of NMSC exceed those for melanoma, mesothelioma, oropharyngeal cancer, and thyroid cancer globally. 4 Annual mortality due to NMSC is predicted to increase by at least 50% by 2044. 5 In Germany, SCC mortality increased fivefold between 2007 and 2016. 6 Over the past decade, novel systemic therapies and artificial intelligence–enabled approaches have transformed NMSC management, 7 , 8 yet global mortality continues to rise. 5 Australia’s comprehensive skin-cancer registry offers a model for surveillance-driven intervention; 9 by contrast, the United States lacks a dedicated NMSC registry and relies on mortality surveillance systems of limited granularity, impeding insight into demographic and regional disparities. 10 To address this gap, we leveraged the Centers for Disease Control and Prevention’s Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database to evaluate age-adjusted NMSC mortality trends in the U.S. from 1999 to 2020. We stratified these trends by sex, race, age group, urban–rural classification, and geographic region. To our knowledge, this is the first detailed analysis of NMSC mortality trends using the CDC WONDER database, offering granular insights into temporal dynamics and demographic disparities. Methods Database, Study Setting, and Population We extracted U.S. mortality data from the CDC WONDER database for 1999–2020, 11 identifying NMSC-related deaths using ICD‑10 code C44. This publicly available database includes cause-of-death information from death certificates for all 50 states and the District of Columbia and undergoes internal validation to limit misclassification. The CDC WONDER database has been widely used in studies assessing cancers and other causes of mortality. We selected records where NMSC was the underlying cause of death. Institutional review board approval was not required, as CDC WONDER is deidentified and publicly available, and the study adheres to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Data Extraction We extracted data on year of death, population size; place of residence (state and region), place of death (medical facilities [inpatient, outpatient, emergency room, death on arrival, status unknown], home, hospice facility, nursing home/ long-term care, other), urban-rural classification, age at death (< 25, 25–44, 45–64, and 65 + years), sex (male or female), and race/ethnicity (non-Hispanic [NH] White, NH Black, NH Asian, and Hispanic or Latino). To assess the population the National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme was used which classifies the population into urban (large metropolitan area [population ≥ 1 million]), suburban (medium/small metropolitan area [population 50,000–999,999]), and rural (nonmetropolitan [population < 50,000]) counties per the 2013 U.S. census classification. 12 Regions were defined per U.S. Census Bureau categories: Northeast, Midwest, South, and West. 13 To preserve privacy when death counts are low, the database suppresses data for ages < 25 years and most data for NH American Indians. AAMRs for NH Asians were unreliable in 1999, 2002–2004, and 2008; we estimated those values via linear interpolation and extrapolation. Statistical Analysis We calculated age-adjusted mortality rates (AAMRs) per 100,000 population annually and by subgroup, standardizing to the U.S. 2000 population. 12 Crude mortality rates for each year were derived by dividing the total number of NMSC-related deaths by the corresponding U.S. population size. To determine trends in the annual percent change (APC) of AAMRs, we utilized the Joinpoint Regression Program (Version 5.0.2, National Cancer Institute). 14 The 95% Confidence Intervals (CI) for AAMR were determined at the identified line segments that link join points, using the Monte Carlo permutation tests. This approach allowed us to identify significant changes in AAMR over the period by fitting log-linear regression models wherever temporal variation took place. APCs were treated as increasing or decreasing depending on the slope’s change in mortality was significantly different than zero using 2-tailed t-testing. A p-value < 0.05 was deemed statistically significant. Results A total of 68,223 NMSC-related deaths occurred in the U.S. between 1999 and 2020 (Additional file 1: Supplemental Table 1). Information on location of death was available for 66,119 of these deaths. Of these, 40.5% occurred at home, 22.9% within medical facilities, 21.4% in nursing homes/long-term care facilities, and 9.4% occurred in hospice facilities (Additional file 1: Supplemental Table 2). Annual Trends for NMSC-related AAMR. The AAMR for NMSC-related deaths was 0.845 per 100,000 (95% CI: 0.810–0.879) in 1999 and increased to 1.002 per 100,000 (95% CI: 0.971–1.032) in 2020. Overall, the AAMR showed an initial decline from 1999 to 2004 (APC: -0.7%; 95% CI: − 3.4 to 2.1), followed by a significant rise from 2004 to 2020 (APC: 1.6%; 95% CI: 1.2 to 2.0) (Fig. 1 , Additional file 1: Supplemental Table 3). NMSC-related AAMR Stratified by Sex. Men consistently had higher AAMRs than women throughout the study period. The overall AAMR for men was significantly higher at 1.55 per 100,000 compared with women at 0.43 per 100,000. In men, a significant increase from 1999 to 2016 (APC: 1.4%; 95% CI: 1.0 to 1.9) reversed into a declining trend from 2016 to 2020 (APC: -1.0%; 95% CI: − 3.9 to 2.1). Conversely, women exhibited relative stability from 1999 to 2011 (APC: -0.1%; 95% CI: -1.2 to 1.0), but demonstrated a significant increase from 2011 to 2020 (APC: 2.5%; 95% CI: 1.1 to 4.1) (Fig. 1 , Additional file 1: Supplemental Table 3). NMSC-related AAMR Stratified by Race. AAMRs were highest among NH White individuals, followed by NH Black, Hispanic, and NH Asian individuals (overall AAMR NH White: 1.03; 95% CI: 1.02–1.04; NH Black: 0.44; 95% CI: 0.43–0.46; Hispanic: 0.42; 95% CI: 0.41–0.44; NH Asian: 0.23; 95% CI: 0.22–0.25). NH White individuals showed an initial declining trend from 1999 to 2005 (APC: -0.3%; 95% CI: -1.8 to 1.2), followed by a marked increase from 2005 to 2015 (APC: 2.8%; 95% CI: 2.1 to 3.5), then a slight stabilization between 2015 and 2020 (APC: 0.3%; 95% CI: -1.3 to 1.9). NH Black individuals showed a consistent declining trend throughout the entire study period (APC: -1.5%; 95% CI: -2.2 to -0.8). Hispanic individuals demonstrated a significant increasing trend (APC: 0.9%; 95% CI: 0.1 to 1.6), while NH Asian individuals exhibited a stable to slightly decreasing trend (APC: -0.7%; 95% CI: -1.5 to 0.2) (Fig. 2 , Additional file 1: Supplemental Table 4). NMSC-related AAMR Stratified by Age Group. Individuals aged ≥ 65 years showed markedly higher AAMRs compared with younger age groups, with an overall AAMR of 5.63 per 100,000. This age group initially exhibited a decreasing trend from 1999 to 2004 (APC: -1.0%; 95% CI: -3.2 to 1.3), followed by a significant increase from 2004 to 2015 (APC: 2.5%; 95% CI: 1.8 to 3.2), and stabilization thereafter (2015–2020 APC: 0.3%; 95% CI: -1.4 to 2.0). Age groups 45–64 years and 25–44 years maintained relatively low and stable AAMRs across the entire period (Fig. 3 , Additional file 1: Supplemental Table 5). NMSC-related AAMR Stratified by Geographic Region. State-level AAMRs ranged from 0.65 (95% CI: 0.52–0.80) in the District of Columbia to 1.29 (95% CI: 1.14–1.44) in Delaware. The top 10th percentile (Delaware, Tennessee, Oklahoma, Idaho, Arizona, Kentucky) had roughly double the AAMR of the bottom 10th percentile (District of Columbia, North Dakota, Alaska, New York, Hawaii, Connecticut) (Fig. 4 ; Additional file 1: Supplemental Table 6). On average over the study period, mortality was highest in the South (AAMR: 1.01; 95% CI: 1.00–1.02), followed by the West (AAMR: 0.96; 95% CI: 0.95–0.98), Midwest (AAMR: 0.86; 95% CI: 0.85–0.87), and Northeast (AAMR: 0.77; 95% CI: 0.76–0.79) (Additional file 1: Supplemental Table 7). Rural areas had consistently higher AAMRs (overall AAMR: 1.04; 95% CI: 1.02–1.06), followed by suburban (overall AAMR: 0.97; 95% CI: 0.95–0.98) and urban areas (overall AAMR: 0.83; 95% CI: 0.82–0.84). A significant rising trend was observed in rural (APC: 1.7%; 95% CI: 1.4 to 2.1) and suburban areas (APC: 1.4%; 95% CI: 1.0 to 1.7) throughout the study period. Urban areas displayed initial stability (1999–2010 APC: 0.1%; 95% CI: -0.5 to 0.8), followed by a significant rise from 2010 to 2015 (APC: 3.5%; 95% CI: 0.8 to 6.2) and subsequent stability from 2015 to 2020 (APC: -0.7%; 95% CI: -2.4 to 1.0) (Fig. 5 , Additional file 1: Supplemental Table 8). Discussion This nationwide analysis reveals that, despite advances in detection and treatment, NMSC mortality in the U.S. increased overall over the last two decades. After an initial dip in the early 2000s, age‑adjusted mortality rose significantly from 2004 onward, reaching 1.00 per 100,000 in 2020. We identified pronounced demographic disparities: men consistently had nearly threefold higher mortality than women, although female rates have escalated in recent years. NH White individuals experienced the highest mortality and the steepest increase over time, whereas NH Black individuals saw a modest decline in NMSC death rates. Mortality was overwhelmingly concentrated among older adults: by 2020, those aged ≥ 65 years had NMSC mortality more than eightfold higher than middle‑aged adults. Geographic patterns were also evident, with the Southern United States carrying the highest mortality burden and rural counties suffering greater NMSC mortality than suburban or urban areas. Rising overall NMSC mortality, notably pronounced in those ≥ 65 years, likely reflects long‑latency effects of cumulative ultraviolet radiation over the life course and shifts in sun‑seeking behaviors (e.g., indoor tanning, intermittent intense sun exposure) that were prevalent in mid‑life decades ago. 15 – 17 Adoption of dermoscopy in the early 2000s substantially improved diagnostic accuracy of keratinocyte carcinomas, 18 potentially facilitating earlier tumor detection. However, high-risk cohorts exposed to intense UV radiation in prior decades have since aged into the most vulnerable group. 16 Indoor tanning and recreational sunbathing surged in popularity during the 1990s and early 2000s. 19 In 2009, the World Health Organization classified UV tanning devices as carcinogenic, 20 and indoor tanning rates subsequently declined. 21 Yet irreversible damage from past UV exposure, responsible for roughly 90% of NMSC cases, 22 likely contributed to the continued rise in mortality through the early 2010s. Our findings mirror trends in other high-UV settings: for example, in Australia NMSC deaths have continued to increase despite decades of sun-safety campaigns. 23 Notably, although overall NMSC mortality continued to rise modestly through 2020, the rate of increase appeared to slow after 2015, possibly reflecting benefits of new therapies. Vismodegib (approved 2012) improved survival in advanced basal cell carcinoma, 7 and PD-1 inhibitors for metastatic SCC became available by 2018. 24 These advances, focused on inoperable or aggressive NMSCs (the primary cause of NMSC-related death), could be slowing mortality growth. Sex disparities in NMSC outcomes were striking and consistent. We found male mortality rates nearly three times higher than female rates, in line with prior national estimates and global patterns. 25 Men bear a disproportionate burden: epidemiologic analyses confirm that men have higher NMSC incidence, prevalence, and mortality than women. 10 Biological factors may contribute, as men appear more susceptible to UV‑induced immune suppression, 26 , 27 which could heighten their skin cancer risk. Consistent with these factors, nearly one-third of NMSC deaths globally have been attributed to occupational UV exposure. 28 This disparity underscores the need for targeted prevention in high-risk male groups (e.g., outdoor workers) to reduce excess male mortality. Racial and ethnic patterns in NMSC mortality were also evident. NH White individuals accounted for the vast majority of NMSC death, with age-adjusted mortality more than double that of any other racial group. This aligns with the known epidemiology of skin cancer: NMSC is most common among fair‑skinned populations, and White individuals have far higher NMSC incidence than Black, Hispanic, or Asian individuals. 1 , 5 Black Americans experienced the lowest NMSC mortality and even saw a modest decline over the study period, reflecting their much lower underlying NMSC incidence. 5 By contrast, in melanoma White patients have the highest incidence while minority patients often present with more advanced disease and poorer survival. 29 The comparatively low NMSC mortality in minority groups may reflect protective melanin pigmentation and historically limited UV exposure. 30 , 31 However, important disparities persist: when skin cancers occur in patients of color, they tend to be diagnosed at later stages due to lower awareness, atypical presentations, and limited access to care. 30 , 31 Multiple factors such as insurance status, access to care, cultural beliefs, and educational gaps contribute to these disparities. 32 Our results underscore that NMSC mortality is not immune to health inequities; efforts to improve skin cancer awareness and access in communities of color remain important, even if absolute mortality rates in these groups are low. Geographic disparities likely reflect environmental and healthcare system influences on NMSC outcomes. We observed the highest mortality rates in Southern states and the lowest in the Northeast, a north–south gradient that broadly correlates with regional UV index and outdoor lifestyle patterns. 5 , 33 We also found a clear rural–urban divide: rural counties had significantly higher NMSC mortality than suburban or urban areas. Rural populations often have greater occupational sun exposure (e.g., in farming or construction) and may face difficulties accessing dermatologic care for early lesion removal. 28 , 34 Higher poverty rates and lower insurance coverage in rural communities could further delay diagnosis and treatment. This rural excess emphasizes the need to bridge the care gap outside metropolitan centers through measures such as teledermatology outreach or mobile screening programs. 35 , 36 Clinical and public health implications: Our findings reinforce the importance of strengthening both prevention and early detection of NMSC, especially in high-risk groups. 37 From a prevention standpoint, reducing UV exposure remains paramount. Preventive efforts should continue to focus on reducing UV exposure through policy measures (e.g., indoor tanning restrictions, particularly for minors) and environmental interventions such as sun‑safe school and workplace policies. 38 , 39 Mass-media campaigns have shown a high return on investment, for example, an Australian program yielded $ 3.85 for every $ 1 spent. 40 Similar efforts in the U.S. could help instill lifelong sun protection habits. 41 Early detection strategies must also adapt to evolving epidemiology: for older adults, especially sun‑damaged men, regular total‑body skin examinations can facilitate prompt treatment of aggressive lesions. 42 Expanding opportunistic skin checks in primary care and community settings could improve early detection in regions lacking specialists. 43 Teledermatology and smartphone applications are promising adjuncts for triaging lesions in remote areas; some mobile apps show approximately 90% sensitivity for detecting malignancies. 35 Moreover, integrating artificial intelligence tools into screening may further enhance diagnostic accuracy and referral decisions. 8 By leveraging such technologies and targeted outreach (e.g., mobile skin clinics in high-mortality rural areas or subsidized screenings for high-risk seniors), resources can be allocated more equitably. A combined approach of public education, UV policy measures, and expanded screening could help reduce NMSC mortality and narrow the demographic gaps identified in this study. Several limitations should be considered. First, our reliance on death‑certificate coding for cause of death may introduce misclassification bias, some fatalities coded as NMSC could represent metastatic disease from other primaries, while true NMSC deaths may go unrecorded. Second, CDC WONDER lacks tumor‑level detail (histologic subtype, stage at diagnosis, treatment), preventing us from distinguishing trends in SCC versus BCC or assessing the impact of therapeutic advances. Third, our ecological, population‑level design precludes individual‑level inference and, combined with the suppression of low death counts for privacy, limited certain subgroup analyses (for example, state‑level trends among minority groups) and may obscure local hotspots. Fourth, to estimate suppressed age‑adjusted rates for NH Asian individuals, we used linear interpolation and extrapolation, an approach that may introduce estimation error. Finally, key individual‑level risk factors (socioeconomic status, occupational UV exposure, insurance coverage) are not captured in CDC WONDER, preventing adjustment for potential confounders in the observed mortality patterns. Future research should focus on: (1) establishing a dedicated national NMSC registry to improve epidemiologic tracking and guide targeted interventions; (2) evaluating the effectiveness of artificial intelligence-driven screening tools, particularly in rural and underserved populations; and (3) developing and implementing tailored sun-safety education and policy measures aimed specifically at high-risk populations, such as older adults, outdoor workers, and residents of regions with high UV exposure. Conclusion Our analysis revealed a significant increase in U.S. NMSC mortality from 2004 to 2020, with marked disparities evident among older adults, men, NH White populations, rural counties, and Southern states. These findings reflect the cumulative impact of historical ultraviolet exposure and highlight gaps in skin cancer surveillance and healthcare accessibility. Our results underscore the need to prioritize targeted prevention strategies, regular screening, and resource allocation toward these high-risk groups to mitigate NMSC mortality. Abbreviations NMSC Nonmelanoma Skin Cancer BCC Basal Cell Carcinoma SCC Squamous Cell Carcinoma CDC WONDER Centers for Disease Control and Prevention’s Wide‑ranging Online Data for Epidemiologic Research CDC Centers for Disease Control and Prevention ICD‑10 International Classification of Diseases, Tenth Revision STROBE Strengthening the Reporting of Observational Studies in Epidemiology NH Non‑Hispanic NCHS National Center for Health Statistics U.S. United States AAMR Age‑Adjusted Mortality Rate(s) APC Annual Percent Change CI Confidence Interval(s) PD‑1 Programmed Cell Death Protein 1 p‑value Probability Value Declarations Ethics approval and consent to participate: Not applicable. This study did not involve any human participants, human data, or human tissue, but rather utilized publicly available, deidentified data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database, which is in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Consent for publication: Not applicable. This manuscript does not contain any individual person's data. Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. The data that support the findings of this study are derived from public domains including the CDC WONDER database. Specific data extraction details are disclosed in the manuscript, ensuring transparency and reproducibility. Competing interests: The authors declare that they have no competing interests. Funding: No funding was received to assist with the preparation of this manuscript. Authors' contributions: AS and ARR conceived the study, designed the project. ARR performed data analysis and prepared figures. ARR and ZZF drafted the manuscript. All authors read, revised critically for important intellectual content, and approved the final manuscript. Acknowledgements: Not applicable Authors' information: A.S. is a board-certified dermatologist with extensive expertise in global dermatology, currently an Adjunct Associate Professor at Yale University and Director of the Yale Dermatology Global Health Program. A.S.'s experience includes over a decade of work at the University of Chicago, where she led high-risk skin cancer clinics and contributed to dermatologic care initiatives worldwide. A.S.'s research and clinical focus on addressing global health disparities, particularly in skin cancer, aligns directly with this manuscript’s exploration of non-melanoma skin cancer mortality. 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The ongoing racial disparities in melanoma: An analysis of the Surveillance, Epidemiology, and End Results database (1975–2016). J Am Acad Dermatol [Internet]. 2021 Jun 1 [cited 2025 Jul 4];84(6):1585–93. Available from: https://pubmed.ncbi.nlm.nih.gov/32861710/ Shao K, Feng H. Racial and Ethnic Healthcare Disparities in Skin Cancer in the United States: A Review of Existing Inequities, Contributing Factors, and Potential Solutions. J Clin Aesthet Dermatol [Internet]. 2022 Jul 1 [cited 2025 Jul 15];15(7):16. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9345197/ Agbai ON, Buster K, Sanchez M, Hernandez C, Kundu RV, Chiu M et al. Skin cancer and photoprotection in people of color: A review and recommendations for physicians and the public. J Am Acad Dermatol [Internet]. 2014 [cited 2025 Jul 15];70(4):748–62. Available from: https://pubmed.ncbi.nlm.nih.gov/24485530/ Shao K, Feng H. Racial and Ethnic Healthcare Disparities in Skin Cancer in the United States: A Review of Existing Inequities, Contributing Factors, and Potential Solutions. J Clin Aesthet Dermatol [Internet]. 2022 Jul 1 [cited 2025 Jul 4];15(7):16. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9345197/ The UV Index | US EPA [Internet]. [cited 2025 Jul 16]. Available from: https://www.epa.gov/sunsafety/uv-index-1 Association between occupational exposure to solar ultraviolet radiation and skin cancers. The WHO systematic review and meta-analysis | ARPANSA [Internet]. [cited 2025 Jul 16]. Available from: https://www.arpansa.gov.au/association-between-occupational-exposure-solar-ultraviolet-radiation-and-skin-cancers-who Chuchu N, Dinnes J, Takwoingi Y, Matin RN, Bayliss SE, Davenport C et al. Teledermatology for diagnosing skin cancer in adults. Cochrane Database of Systematic Reviews [Internet]. 2018 Dec 3 [cited 2025 Jul 16];2018(12). Available from: https://www.cochranelibrary.com/cdsr/doi/ 10.1002/14651858.CD013193/full Nikolakis G, Vaiopoulos AG, Georgopoulos I, Papakonstantinou E, Gaitanis G, Zouboulis CC. Insights, Advantages, and Barriers of Teledermatology vs. Face-to-Face Dermatology for the Diagnosis and Follow-Up of Non-Melanoma Skin Cancer: A Systematic Review. Cancers (Basel) [Internet]. 2024 Feb 1 [cited 2025 Jul 16];16(3):578. Available from: https://www.mdpi.com/ 2072-6694/16/3/578/htm. Conte S, Aldien AS, Jetté S, LeBeau J, Alli S, Netchiporouk E et al. Skin Cancer Prevention across the G7, Australia and New Zealand: A Review of Legislation and Guidelines. Current Oncology [Internet]. 2023 Jul 1 [cited 2025 Jul 16];30(7):6019–40. Available from: https://pubmed.ncbi.nlm.nih.gov/37489567/ Sun Safety Facts. | Skin Cancer | CDC [Internet]. [cited 2025 Jul 16]. Available from: https://www.cdc.gov/skin-cancer/sun-safety/index.html Indoor Tanning Legislation. 2023 - AIM at Melanoma Foundation [Internet]. [cited 2025 Jul 16]. Available from: https://www.aimatmelanoma.org/legislation-policy-advocacy/indoor-tanning/ Doran CM, Ling R, Byrnes J, Crane M, Shakeshaft AP, Searles A et al. Benefit cost analysis of three skin cancer public education mass-media campaigns implemented in New South Wales, Australia. PLoS One [Internet]. 2016 Jan 1 [cited 2025 Jul 15];11(1). Available from: https://pubmed.ncbi.nlm.nih.gov/26824695/ Glanz K, Schoenfeld ER, Steffen A. A randomized trial of tailored skin cancer prevention messages for adults: Project SCAPE. Am J Public Health [Internet]. 2010 Apr 1 [cited 2025 Jul 16];100(4):735–41. Available from: https://pubmed.ncbi.nlm.nih.gov/20167900/ Mangione CM, Barry MJ, Nicholson WK, Chelmow D, Coker TR, Davis EM et al. Screening for Skin Cancer: US Preventive Services Task Force Recommendation Statement. JAMA [Internet]. 2023 Apr 18 [cited 2025 Jul 16];329(15):1290–5. Available from: https://pubmed.ncbi.nlm.nih.gov/37071089/ Mauad EC, Silva TB, Latorre MRDO, Vieira RAC, Haikel RL, Vazquez VL et al. Opportunistic screening for skin cancer using a mobile unit in Brazil. BMC Dermatol [Internet]. 2011 Jun 6 [cited 2025 Jul 16];11(1):1–6. Available from: https://bmcdermatol.biomedcentral.com/articles/ 10.1186/1471-5945-11-12 Sendín-Martín M, Bueno-Molina RC, Hernández-Rodríguez JC, Cayuela L, Cayuela A, Pereyra-Rodríguez JJ. Incidence and mortality of nonmelanoma skin cancer in Europe: current trends and challenges. Clin Transl Oncol [Internet]. 2025 Jul 11 [cited 2025 Jul 15]; Available from: https://pubmed.ncbi.nlm.nih.gov/40643870/ Additional Declarations No competing interests reported. Supplementary Files Additionalfile1SupplementalTables.docx Cite Share Download PDF Status: Published Journal Publication published 31 Mar, 2026 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 27 Feb, 2026 Reviews received at journal 25 Feb, 2026 Reviews received at journal 05 Feb, 2026 Reviewers agreed at journal 31 Jan, 2026 Reviews received at journal 26 Jan, 2026 Reviewers agreed at journal 26 Jan, 2026 Reviewers agreed at journal 23 Jan, 2026 Reviewers agreed at journal 26 Dec, 2025 Reviews received at journal 14 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviewers invited by journal 25 Aug, 2025 Editor invited by journal 24 Jul, 2025 Editor assigned by journal 21 Jul, 2025 Submission checks completed at journal 21 Jul, 2025 First submitted to journal 20 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7169797","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":508491236,"identity":"aad36a0d-2853-47b1-83b6-03817a1a4d81","order_by":0,"name":"Ahsan Raza Raja","email":"data:image/png;base64,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","orcid":"","institution":"Aga Khan University","correspondingAuthor":true,"prefix":"","firstName":"Ahsan","middleName":"Raza","lastName":"Raja","suffix":""},{"id":508491237,"identity":"c94e6611-a460-4180-b1d0-c3a80d39c6fd","order_by":1,"name":"Zoha Zahid Fazal","email":"","orcid":"","institution":"Stanford University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zoha","middleName":"Zahid","lastName":"Fazal","suffix":""},{"id":508491238,"identity":"ce1c1408-9c22-4ec9-b5ed-25de90d30943","order_by":2,"name":"Aisha Sethi","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Aisha","middleName":"","lastName":"Sethi","suffix":""}],"badges":[],"createdAt":"2025-07-20 13:08:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7169797/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7169797/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-026-15953-z","type":"published","date":"2026-03-31T16:00:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90527295,"identity":"7d780a61-2ce5-4542-a39b-c22d01d629d1","added_by":"auto","created_at":"2025-09-03 17:18:30","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":148185,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Nonmelanoma skin cancer-related age-adjusted mortality rate, overall and stratified by sex in the United States, 1999-2020\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e*Indicates that the annual percentage change (APC) is significantly different from zero at α = 0.05.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7169797/v1/ad745436fb751ee3299a7537.jpeg"},{"id":90526716,"identity":"905b72c4-905b-4f69-8332-4249819cfd09","added_by":"auto","created_at":"2025-09-03 17:10:30","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":167464,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Nonmelanoma skin cancer-related age-adjusted mortality rate stratified by race in the United States, 1999-2020\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e*Indicates that the annual percentage change (APC) is significantly different from zero at α = 0.05. NH = non-Hispanic\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7169797/v1/182f108a4c435a67ef188491.jpeg"},{"id":90526713,"identity":"5f0e2215-5ef8-4c66-849f-47527ba14698","added_by":"auto","created_at":"2025-09-03 17:10:30","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":134776,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Nonmelanoma skin cancer-related age-adjusted mortality rate stratified by age in the United States, 1999-2020\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e*Indicates that the annual percentage change (APC) is significantly different from zero at α = 0.05.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7169797/v1/44ef6562eb3ce0851445f63e.jpeg"},{"id":90527883,"identity":"90700603-0b8a-4c06-aadd-93fc9e00765d","added_by":"auto","created_at":"2025-09-03 17:26:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":263775,"visible":true,"origin":"","legend":"\u003cp\u003eNonmelanoma skin cancer-related age-adjusted mortality rate stratified by\u003cstrong\u003e \u003c/strong\u003estate in the United States, 1999-2020\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7169797/v1/adb57955a66fa138dbe54151.png"},{"id":90526724,"identity":"4bafd901-c591-43f4-89f6-6710a8c54455","added_by":"auto","created_at":"2025-09-03 17:10:31","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":143170,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Nonmelanoma skin cancer-related age-adjusted mortality rate stratified by Urban-Rural Classification in the United States, 1999-2020\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e*Indicates that the annual percentage change (APC) is significantly different from zero at α = 0.05.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7169797/v1/41d23e15c269db4ee0c73b0f.jpeg"},{"id":106344502,"identity":"2b50f48e-975f-4abc-a0c5-f2fc51862c5d","added_by":"auto","created_at":"2026-04-07 16:15:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1447815,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7169797/v1/29f8f659-cd76-4492-986e-f51e9894a11b.pdf"},{"id":90527882,"identity":"c61ebeb9-266f-4485-bb18-334283ff6150","added_by":"auto","created_at":"2025-09-03 17:26:31","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":53553,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1SupplementalTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7169797/v1/11b125b6e13c738d878a5058.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Demographic and Regional Trends in Nonmelanoma Skin Cancer Mortality in the United States, 1999-2020","fulltext":[{"header":"Background","content":"\u003cp\u003eNonmelanoma skin cancer (NMSC) poses a significant burden on global health and the economy, with its incidence rising in aging populations.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Representing nearly one-third of all cancers diagnosed annually, NMSC is the most prevalent malignancy worldwide.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Within NMSC, basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) account for 99% of tumors and over 5,400 global deaths each month.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Ferlay et al. report that estimated mortality rates for all types of NMSC exceed those for melanoma, mesothelioma, oropharyngeal cancer, and thyroid cancer globally.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Annual mortality due to NMSC is predicted to increase by at least 50% by 2044.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e In Germany, SCC mortality increased fivefold between 2007 and 2016.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eOver the past decade, novel systemic therapies and artificial intelligence\u0026ndash;enabled approaches have transformed NMSC management,\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e yet global mortality continues to rise.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Australia\u0026rsquo;s comprehensive skin-cancer registry offers a model for surveillance-driven intervention;\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e by contrast, the United States lacks a dedicated NMSC registry and relies on mortality surveillance systems of limited granularity, impeding insight into demographic and regional disparities.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e To address this gap, we leveraged the Centers for Disease Control and Prevention\u0026rsquo;s Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database to evaluate age-adjusted NMSC mortality trends in the U.S. from 1999 to 2020. We stratified these trends by sex, race, age group, urban\u0026ndash;rural classification, and geographic region. To our knowledge, this is the first detailed analysis of NMSC mortality trends using the CDC WONDER database, offering granular insights into temporal dynamics and demographic disparities.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eDatabase, Study Setting, and Population\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe extracted U.S. mortality data from the CDC WONDER database for 1999\u0026ndash;2020,\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e identifying NMSC-related deaths using ICD‑10 code C44. This publicly available database includes cause-of-death information from death certificates for all 50 states and the District of Columbia and undergoes internal validation to limit misclassification. The CDC WONDER database has been widely used in studies assessing cancers and other causes of mortality. We selected records where NMSC was the underlying cause of death. Institutional review board approval was not required, as CDC WONDER is deidentified and publicly available, and the study adheres to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Extraction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe extracted data on year of death, population size; place of residence (state and region), place of death (medical facilities [inpatient, outpatient, emergency room, death on arrival, status unknown], home, hospice facility, nursing home/ long-term care, other), urban-rural classification, age at death (\u0026lt;\u0026thinsp;25, 25\u0026ndash;44, 45\u0026ndash;64, and 65\u0026thinsp;+\u0026thinsp;years), sex (male or female), and race/ethnicity (non-Hispanic [NH] White, NH Black, NH Asian, and Hispanic or Latino). To assess the population the National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme was used which classifies the population into urban (large metropolitan area [population\u0026thinsp;\u0026ge;\u0026thinsp;1 million]), suburban (medium/small metropolitan area [population 50,000\u0026ndash;999,999]), and rural (nonmetropolitan [population\u0026thinsp;\u0026lt;\u0026thinsp;50,000]) counties per the 2013 U.S. census classification.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Regions were defined per U.S. Census Bureau categories: Northeast, Midwest, South, and West.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e To preserve privacy when death counts are low, the database suppresses data for ages\u0026thinsp;\u0026lt;\u0026thinsp;25 years and most data for NH American Indians. AAMRs for NH Asians were unreliable in 1999, 2002\u0026ndash;2004, and 2008; we estimated those values via linear interpolation and extrapolation.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eWe calculated age-adjusted mortality rates (AAMRs) per 100,000 population annually and by subgroup, standardizing to the U.S. 2000 population.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Crude mortality rates for each year were derived by dividing the total number of NMSC-related deaths by the corresponding U.S. population size. To determine trends in the annual percent change (APC) of AAMRs, we utilized the Joinpoint Regression Program (Version 5.0.2, National Cancer Institute).\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The 95% Confidence Intervals (CI) for AAMR were determined at the identified line segments that link join points, using the Monte Carlo permutation tests. This approach allowed us to identify significant changes in AAMR over the period by fitting log-linear regression models wherever temporal variation took place. APCs were treated as increasing or decreasing depending on the slope\u0026rsquo;s change in mortality was significantly different than zero using 2-tailed t-testing. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 68,223 NMSC-related deaths occurred in the U.S. between 1999 and 2020 (Additional file 1: Supplemental Table\u0026nbsp;1). Information on location of death was available for 66,119 of these deaths. Of these, 40.5% occurred at home, 22.9% within medical facilities, 21.4% in nursing homes/long-term care facilities, and 9.4% occurred in hospice facilities (Additional file 1: Supplemental Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnnual Trends for NMSC-related AAMR.\u003c/b\u003e The AAMR for NMSC-related deaths was 0.845 per 100,000 (95% CI: 0.810\u0026ndash;0.879) in 1999 and increased to 1.002 per 100,000 (95% CI: 0.971\u0026ndash;1.032) in 2020. Overall, the AAMR showed an initial decline from 1999 to 2004 (APC: -0.7%; 95% CI: \u0026minus;\u0026thinsp;3.4 to 2.1), followed by a significant rise from 2004 to 2020 (APC: 1.6%; 95% CI: 1.2 to 2.0) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Additional file 1: Supplemental Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNMSC-related AAMR Stratified by Sex.\u003c/b\u003e Men consistently had higher AAMRs than women throughout the study period. The overall AAMR for men was significantly higher at 1.55 per 100,000 compared with women at 0.43 per 100,000. In men, a significant increase from 1999 to 2016 (APC: 1.4%; 95% CI: 1.0 to 1.9) reversed into a declining trend from 2016 to 2020 (APC: -1.0%; 95% CI: \u0026minus;\u0026thinsp;3.9 to 2.1). Conversely, women exhibited relative stability from 1999 to 2011 (APC: -0.1%; 95% CI: -1.2 to 1.0), but demonstrated a significant increase from 2011 to 2020 (APC: 2.5%; 95% CI: 1.1 to 4.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Additional file 1: Supplemental Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003e\u003cb\u003eNMSC-related AAMR Stratified by Race.\u003c/b\u003e AAMRs were highest among NH White individuals, followed by NH Black, Hispanic, and NH Asian individuals (overall AAMR NH White: 1.03; 95% CI: 1.02\u0026ndash;1.04; NH Black: 0.44; 95% CI: 0.43\u0026ndash;0.46; Hispanic: 0.42; 95% CI: 0.41\u0026ndash;0.44; NH Asian: 0.23; 95% CI: 0.22\u0026ndash;0.25). NH White individuals showed an initial declining trend from 1999 to 2005 (APC: -0.3%; 95% CI: -1.8 to 1.2), followed by a marked increase from 2005 to 2015 (APC: 2.8%; 95% CI: 2.1 to 3.5), then a slight stabilization between 2015 and 2020 (APC: 0.3%; 95% CI: -1.3 to 1.9). NH Black individuals showed a consistent declining trend throughout the entire study period (APC: -1.5%; 95% CI: -2.2 to -0.8). Hispanic individuals demonstrated a significant increasing trend (APC: 0.9%; 95% CI: 0.1 to 1.6), while NH Asian individuals exhibited a stable to slightly decreasing trend (APC: -0.7%; 95% CI: -1.5 to 0.2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Additional file 1: Supplemental Table\u0026nbsp;4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNMSC-related AAMR Stratified by Age Group.\u003c/b\u003e Individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years showed markedly higher AAMRs compared with younger age groups, with an overall AAMR of 5.63 per 100,000. This age group initially exhibited a decreasing trend from 1999 to 2004 (APC: -1.0%; 95% CI: -3.2 to 1.3), followed by a significant increase from 2004 to 2015 (APC: 2.5%; 95% CI: 1.8 to 3.2), and stabilization thereafter (2015\u0026ndash;2020 APC: 0.3%; 95% CI: -1.4 to 2.0). Age groups 45\u0026ndash;64 years and 25\u0026ndash;44 years maintained relatively low and stable AAMRs across the entire period (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Additional file 1: Supplemental Table\u0026nbsp;5).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNMSC-related AAMR Stratified by Geographic Region.\u003c/b\u003e State-level AAMRs ranged from 0.65 (95% CI: 0.52\u0026ndash;0.80) in the District of Columbia to 1.29 (95% CI: 1.14\u0026ndash;1.44) in Delaware. The top 10th percentile (Delaware, Tennessee, Oklahoma, Idaho, Arizona, Kentucky) had roughly double the AAMR of the bottom 10th percentile (District of Columbia, North Dakota, Alaska, New York, Hawaii, Connecticut) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; Additional file 1: Supplemental Table\u0026nbsp;6). On average over the study period, mortality was highest in the South (AAMR: 1.01; 95% CI: 1.00\u0026ndash;1.02), followed by the West (AAMR: 0.96; 95% CI: 0.95\u0026ndash;0.98), Midwest (AAMR: 0.86; 95% CI: 0.85\u0026ndash;0.87), and Northeast (AAMR: 0.77; 95% CI: 0.76\u0026ndash;0.79) (Additional file 1: Supplemental Table\u0026nbsp;7). Rural areas had consistently higher AAMRs (overall AAMR: 1.04; 95% CI: 1.02\u0026ndash;1.06), followed by suburban (overall AAMR: 0.97; 95% CI: 0.95\u0026ndash;0.98) and urban areas (overall AAMR: 0.83; 95% CI: 0.82\u0026ndash;0.84). A significant rising trend was observed in rural (APC: 1.7%; 95% CI: 1.4 to 2.1) and suburban areas (APC: 1.4%; 95% CI: 1.0 to 1.7) throughout the study period. Urban areas displayed initial stability (1999\u0026ndash;2010 APC: 0.1%; 95% CI: -0.5 to 0.8), followed by a significant rise from 2010 to 2015 (APC: 3.5%; 95% CI: 0.8 to 6.2) and subsequent stability from 2015 to 2020 (APC: -0.7%; 95% CI: -2.4 to 1.0) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Additional file 1: Supplemental Table\u0026nbsp;8).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis nationwide analysis reveals that, despite advances in detection and treatment, NMSC mortality in the U.S. increased overall over the last two decades. After an initial dip in the early 2000s, age‑adjusted mortality rose significantly from 2004 onward, reaching 1.00 per 100,000 in 2020. We identified pronounced demographic disparities: men consistently had nearly threefold higher mortality than women, although female rates have escalated in recent years. NH White individuals experienced the highest mortality and the steepest increase over time, whereas NH Black individuals saw a modest decline in NMSC death rates. Mortality was overwhelmingly concentrated among older adults: by 2020, those aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years had NMSC mortality more than eightfold higher than middle‑aged adults. Geographic patterns were also evident, with the Southern United States carrying the highest mortality burden and rural counties suffering greater NMSC mortality than suburban or urban areas.\u003c/p\u003e\u003cp\u003eRising overall NMSC mortality, notably pronounced in those\u0026thinsp;\u0026ge;\u0026thinsp;65 years, likely reflects long‑latency effects of cumulative ultraviolet radiation over the life course and shifts in sun‑seeking behaviors (e.g., indoor tanning, intermittent intense sun exposure) that were prevalent in mid‑life decades ago.\u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Adoption of dermoscopy in the early 2000s substantially improved diagnostic accuracy of keratinocyte carcinomas,\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e potentially facilitating earlier tumor detection. However, high-risk cohorts exposed to intense UV radiation in prior decades have since aged into the most vulnerable group.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Indoor tanning and recreational sunbathing surged in popularity during the 1990s and early 2000s.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e In 2009, the World Health Organization classified UV tanning devices as carcinogenic,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and indoor tanning rates subsequently declined.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Yet irreversible damage from past UV exposure, responsible for roughly 90% of NMSC cases,\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e likely contributed to the continued rise in mortality through the early 2010s. Our findings mirror trends in other high-UV settings: for example, in Australia NMSC deaths have continued to increase despite decades of sun-safety campaigns.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Notably, although overall NMSC mortality continued to rise modestly through 2020, the rate of increase appeared to slow after 2015, possibly reflecting benefits of new therapies. Vismodegib (approved 2012) improved survival in advanced basal cell carcinoma,\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and PD-1 inhibitors for metastatic SCC became available by 2018.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e These advances, focused on inoperable or aggressive NMSCs (the primary cause of NMSC-related death), could be slowing mortality growth.\u003c/p\u003e\u003cp\u003eSex disparities in NMSC outcomes were striking and consistent. We found male mortality rates nearly three times higher than female rates, in line with prior national estimates and global patterns.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Men bear a disproportionate burden: epidemiologic analyses confirm that men have higher NMSC incidence, prevalence, and mortality than women.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Biological factors may contribute, as men appear more susceptible to UV‑induced immune suppression,\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e which could heighten their skin cancer risk. Consistent with these factors, nearly one-third of NMSC deaths globally have been attributed to occupational UV exposure.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e This disparity underscores the need for targeted prevention in high-risk male groups (e.g., outdoor workers) to reduce excess male mortality.\u003c/p\u003e\u003cp\u003eRacial and ethnic patterns in NMSC mortality were also evident. NH White individuals accounted for the vast majority of NMSC death, with age-adjusted mortality more than double that of any other racial group. This aligns with the known epidemiology of skin cancer: NMSC is most common among fair‑skinned populations, and White individuals have far higher NMSC incidence than Black, Hispanic, or Asian individuals.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Black Americans experienced the lowest NMSC mortality and even saw a modest decline over the study period, reflecting their much lower underlying NMSC incidence.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e By contrast, in melanoma White patients have the highest incidence while minority patients often present with more advanced disease and poorer survival.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e The comparatively low NMSC mortality in minority groups may reflect protective melanin pigmentation and historically limited UV exposure.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e However, important disparities persist: when skin cancers occur in patients of color, they tend to be diagnosed at later stages due to lower awareness, atypical presentations, and limited access to care.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Multiple factors such as insurance status, access to care, cultural beliefs, and educational gaps contribute to these disparities.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Our results underscore that NMSC mortality is not immune to health inequities; efforts to improve skin cancer awareness and access in communities of color remain important, even if absolute mortality rates in these groups are low.\u003c/p\u003e\u003cp\u003eGeographic disparities likely reflect environmental and healthcare system influences on NMSC outcomes. We observed the highest mortality rates in Southern states and the lowest in the Northeast, a north\u0026ndash;south gradient that broadly correlates with regional UV index and outdoor lifestyle patterns.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e We also found a clear rural\u0026ndash;urban divide: rural counties had significantly higher NMSC mortality than suburban or urban areas. Rural populations often have greater occupational sun exposure (e.g., in farming or construction) and may face difficulties accessing dermatologic care for early lesion removal.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Higher poverty rates and lower insurance coverage in rural communities could further delay diagnosis and treatment. This rural excess emphasizes the need to bridge the care gap outside metropolitan centers through measures such as teledermatology outreach or mobile screening programs.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eClinical and public health implications: Our findings reinforce the importance of strengthening both prevention and early detection of NMSC, especially in high-risk groups.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e From a prevention standpoint, reducing UV exposure remains paramount. Preventive efforts should continue to focus on reducing UV exposure through policy measures (e.g., indoor tanning restrictions, particularly for minors) and environmental interventions such as sun‑safe school and workplace policies.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Mass-media campaigns have shown a high return on investment, for example, an Australian program yielded \u003cspan\u003e$\u003c/span\u003e3.85 for every \u003cspan\u003e$\u003c/span\u003e1 spent.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e Similar efforts in the U.S. could help instill lifelong sun protection habits.\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Early detection strategies must also adapt to evolving epidemiology: for older adults, especially sun‑damaged men, regular total‑body skin examinations can facilitate prompt treatment of aggressive lesions.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Expanding opportunistic skin checks in primary care and community settings could improve early detection in regions lacking specialists.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Teledermatology and smartphone applications are promising adjuncts for triaging lesions in remote areas; some mobile apps show approximately 90% sensitivity for detecting malignancies.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Moreover, integrating artificial intelligence tools into screening may further enhance diagnostic accuracy and referral decisions.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e By leveraging such technologies and targeted outreach (e.g., mobile skin clinics in high-mortality rural areas or subsidized screenings for high-risk seniors), resources can be allocated more equitably. A combined approach of public education, UV policy measures, and expanded screening could help reduce NMSC mortality and narrow the demographic gaps identified in this study.\u003c/p\u003e\u003cp\u003eSeveral limitations should be considered. First, our reliance on death‑certificate coding for cause of death may introduce misclassification bias, some fatalities coded as NMSC could represent metastatic disease from other primaries, while true NMSC deaths may go unrecorded. Second, CDC WONDER lacks tumor‑level detail (histologic subtype, stage at diagnosis, treatment), preventing us from distinguishing trends in SCC versus BCC or assessing the impact of therapeutic advances. Third, our ecological, population‑level design precludes individual‑level inference and, combined with the suppression of low death counts for privacy, limited certain subgroup analyses (for example, state‑level trends among minority groups) and may obscure local hotspots. Fourth, to estimate suppressed age‑adjusted rates for NH Asian individuals, we used linear interpolation and extrapolation, an approach that may introduce estimation error. Finally, key individual‑level risk factors (socioeconomic status, occupational UV exposure, insurance coverage) are not captured in CDC WONDER, preventing adjustment for potential confounders in the observed mortality patterns.\u003c/p\u003e\u003cp\u003eFuture research should focus on: (1) establishing a dedicated national NMSC registry to improve epidemiologic tracking and guide targeted interventions; (2) evaluating the effectiveness of artificial intelligence-driven screening tools, particularly in rural and underserved populations; and (3) developing and implementing tailored sun-safety education and policy measures aimed specifically at high-risk populations, such as older adults, outdoor workers, and residents of regions with high UV exposure.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur analysis revealed a significant increase in U.S. NMSC mortality from 2004 to 2020, with marked disparities evident among older adults, men, NH White populations, rural counties, and Southern states. These findings reflect the cumulative impact of historical ultraviolet exposure and highlight gaps in skin cancer surveillance and healthcare accessibility. Our results underscore the need to prioritize targeted prevention strategies, regular screening, and resource allocation toward these high-risk groups to mitigate NMSC mortality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNMSC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNonmelanoma Skin Cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBCC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBasal Cell Carcinoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSCC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSquamous Cell Carcinoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCDC WONDER\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCenters for Disease Control and Prevention\u0026rsquo;s Wide‑ranging Online Data for Epidemiologic Research\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCDC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCenters for Disease Control and Prevention\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICD‑10\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInternational Classification of Diseases, Tenth Revision\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSTROBE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStrengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNon‑Hispanic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNCHS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNational Center for Health Statistics\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eU.S.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUnited States\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAAMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAge‑Adjusted Mortality Rate(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAnnual Percent Change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePD‑1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProgrammed Cell Death Protein 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ep‑value\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProbability Value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study did not involve any human participants, human data, or human tissue, but rather utilized publicly available, deidentified data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database, which is in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This manuscript does not contain any individual person\u0026apos;s data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. The data that support the findings of this study are derived from public domains including the CDC WONDER database. Specific data extraction details are disclosed in the manuscript, ensuring transparency and reproducibility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received to assist with the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAS and ARR conceived the study, designed the project. ARR performed data analysis and prepared figures. ARR and ZZF drafted the manuscript. All authors read, revised critically for important intellectual content, and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA.S.\u003c/strong\u003e is a board-certified dermatologist with extensive expertise in global dermatology, currently an Adjunct Associate Professor at Yale University and Director of the Yale Dermatology Global Health Program. A.S.\u0026apos;s experience includes over a decade of work at the University of Chicago, where she led high-risk skin cancer clinics and contributed to dermatologic care initiatives worldwide. A.S.\u0026apos;s research and clinical focus on addressing global health disparities, particularly in skin cancer, aligns directly with this manuscript\u0026rsquo;s exploration of non-melanoma skin cancer mortality.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCiążyńska M, Kamińska-Winciorek G, Lange D, Lewandowski B, Reich A, Sławińska M et al. The incidence and clinical analysis of non-melanoma skin cancer. Sci Rep [Internet]. 2021 Dec 1 [cited 2025 Jul 4];11(1). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/33619293/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/33619293/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCiuciulete AR, Stepan AE, Andreiana BC, Simionescu CE. 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Clin Transl Oncol [Internet]. 2025 Jul 11 [cited 2025 Jul 15]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/40643870/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/40643870/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Demographic trends, Regional variation, Nonmelanoma skin cancer, Mortality, United States, Age-adjusted mortality, Joinpoint regression, Epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-7169797/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7169797/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eNonmelanoma skin cancer (NMSC) is the most common malignancy worldwide, yet the United States lacks a dedicated registry to monitor its mortality. We aimed to characterize temporal trends and demographic and regional disparities in age-adjusted NMSC mortality in the U.S. from 1999 through 2020.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a retrospective analysis of CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database from 1999 to 2020 for NMSC. Age-adjusted mortality rates (AAMRs) per 100,000 persons and annual percent change (APC) were calculated and stratified by year, sex, race, age group, and geographic region.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 68,223 NMSC-related deaths occurred. Overall AAMR increased from 0.845 (95% CI 0.810\u0026ndash;0.879) in 1999 to 1.002 (0.971\u0026ndash;1.032) in 2020. Trends showed an initial decline (1999\u0026ndash;2004 APC \u0026minus;\u0026thinsp;0.7%), followed by a rise (2004\u0026ndash;2020 APC 1.6%). Men had higher mortality than women (1.55 vs 0.43 per 100,000), with significant increases in both sexes (men 1999\u0026ndash;2016 APC 1.4%; women 2011\u0026ndash;2020 APC 2.5%). NH White individuals exhibited the highest AAMR (1.03) and steepest rise (2005\u0026ndash;2015 APC 2.8%), while NH Blacks declined (APC \u0026minus;\u0026thinsp;1.5%) and Hispanics increased modestly (APC 0.9%). Those\u0026thinsp;\u0026ge;\u0026thinsp;65 years had the highest AAMR (5.63). Regionally, the South (1.01) and rural areas (1.04) bore the greatest burden, with persistent increases (rural APC 1.7%; suburban APC 1.4%).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eDespite diagnostic and therapeutic advances, U.S. NMSC mortality has risen, with marked demographic and geographic disparities. Enhanced mortality surveillance, targeted prevention efforts, and equitable access to dermatologic care are needed to mitigate this growing public health burden.\u003c/p\u003e","manuscriptTitle":"Demographic and Regional Trends in Nonmelanoma Skin Cancer Mortality in the United States, 1999-2020","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 17:10:26","doi":"10.21203/rs.3.rs-7169797/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-27T06:15:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T21:13:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-05T10:54:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20311878544658821150267897808116145551","date":"2026-01-31T19:47:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-26T06:25:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235099050762609677032457044089442983753","date":"2026-01-26T06:15:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80260999833810753038269439324639008389","date":"2026-01-23T13:32:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180587170332839588641944006782516036976","date":"2025-12-26T08:59:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-14T14:59:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46774071731361933107759353744736485845","date":"2025-09-04T05:53:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-25T07:46:39+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-24T09:11:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-21T13:12:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-21T13:11:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-07-20T12:52:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4d2d202f-2d25-4e38-a89d-e4b0a3cbbd25","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-07T16:12:04+00:00","versionOfRecord":{"articleIdentity":"rs-7169797","link":"https://doi.org/10.1186/s12885-026-15953-z","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2026-03-31 16:00:08","publishedOnDateReadable":"March 31st, 2026"},"versionCreatedAt":"2025-09-03 17:10:26","video":"","vorDoi":"10.1186/s12885-026-15953-z","vorDoiUrl":"https://doi.org/10.1186/s12885-026-15953-z","workflowStages":[]},"version":"v1","identity":"rs-7169797","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7169797","identity":"rs-7169797","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}