Systematic analysis of non-melanoma skin cancer burden: a comparative study between China and the world from 1990 to 2021 and prediction to 2036

Systematic analysis of non-melanoma skin cancer burden: a comparative study between China and the world from 1990 to 2021 and prediction to 2036 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Systematic analysis of non-melanoma skin cancer burden: a comparative study between China and the world from 1990 to 2021 and prediction to 2036 Su Liang, Xue Wang, Juan Mei Cao, Xue Song Jia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4948431/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Comparative analysis of the characteristics and trends of the burden of non-melanoma skin cancer (NMSC) in China and globally will provide a basis for the development of effective prevention and control measures in China. Methods Data related to incidence, death and disability-adjusted life year (DALY) of NMSC in China and the world were obtained from the Global Burden of Disease (GBD) 2021 database. The average annual percentage of change (AAPC) was estimated by the Joinpoint regression model to reflect the time trend. Bayesian age-period-cohort model was constructed for prediction. Results From 1990 to 2021, the increase rates (707.31%, 16.00%, and 10.04%) and upward trends (AAPC = 6.71% (95%: 6.01%~7.18%), 0.46% (95%: 0.40%~0.52%), and 0.28% ( 95%: 0.22%~0.34%)) of the NMSC age standardized incidence, mortality, and DALY rate in China were higher than the global level. Both the incidence of NMSC and its rise were higher in men than in women, and the levels of death and DALY were higher in men but rose more rapidly in women. The high incidence, mortality, and DALY rate of NMSC all occurred in the higher age groups. The age-standardized incidence of NMSC in China and globally was predicted to continue to rise over the next 15 years, while the age-standardized mortality rate will decline. Conclusion The burden of NMSC in China remained serious, especially in the context of an increasingly aging population. Relevant authorities should continue to develop and optimize preventive and control measures, especially for men, and adopt targeted measures to significantly reduce the burden of NMSC. Non-melanoma skin cancer Joinpoint regression model Bayesian age-period-cohort model Burden of disease Comparative study Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Non-melanoma skin cancer (NMSC) was one of the most common cancers, divided into basal cell carcinoma and squamous cell carcinoma, and had become a prominent public health problem worldwide [ 1 ]. According to GLOBOCAN, there were 1,234,595 new cases and 69,481 deaths of NMSC globally in 2022, accounting for 8% of all cancer deaths [ 2 ]. The incidence of NMSC had been found to increase annually, especially in areas with high UV exposure, such as Oceania and parts of the United States where the incidence was highest [ 3 ], and was more common in white population [ 4 ]. The age-standardized incidence of NMSC in the United States had increased from 402 (/100,000) in 1990 to 784 (/100,000) in 2019 [ 5 ]. Moreover, the actual incidence of NMSC may be underestimated because many countries were not required to report NMSC information to national cancer registries, which explained the lack of priority given to NMSC in most countries [ 6 ]. At present, there were relatively few epidemiological studies on NMSC in China, which mainly focus on clinical treatment [ 7 , 8 ]. Epidemiological evidence was essential for effective disease prevention and control. Therefore, in order to better address the challenges posed by NMSC, this study compared the burden (incidence, mortality, and disability-adjusted life-years (DALY)) caused by NMSC in China and globally from 1990 to 2021 and predicted it by gender, based on the GBD 2021 database, using the Joinpoint regression model and the Bayesian age-period-cohort (BAPC) model, and to develop more effective prevention and treatment strategies and interventions. 2. Materials and methods 2.1 Data collection Data related to the burden of NMSC were obtained from the GBD 2021 database, which provided epidemiological data for 204 countries or regions, 371 diseases, and 88 risk factors, and provided a strong basis for detailed and extensive understanding of global health trends and emerging challenges [ 9 ]. In this study, we extracted the number of incidence, deaths and DALYs of NMSC and their corresponding crude rates from GBD 2021 for China and the world. 2.2 Data analysis The incidence, mortality and DALY rates of NMSC in China and the world were standardized using the world standard demographics, and the average annual percentage change (AAPC) of each indicator was calculated using Joinpoint 5.0.2 software. Finally, R 4.3.2 was used for prediction. 2.2.1 Joinpoint regression model The Joinpoint regression model was a log-linear model with time (year) as the independent variable and incidence or mortality as the dependent variable [ 10 ]. It described the trend of incidence or mortality by splicing the joinpoints of different logarithmic line segments [ 11 ]. The model was used to calculate the AAPC and its 95% confidence interval (CI) from 1990 to 2021. The model formula was as follows: When both AAPC and its 95% CI are > 0, it meant that the corresponding indicator was on the rise; both < 0 were on the decline; and containing 0 meant that the indicator remained stable. 2.2.2 Bayesian age-period-cohort model We used the BAPC model to predict the age-standardized incidence, mortality and DALY rates for NMSC by sex from 2022 to 2036 [ 12 ]. The model allowed for the inference of unknown parameters by combining the posterior information obtained from the sample information with the a priori information on the unknown parameters [ 13 ], a process implemented using the BAPC and INLA packages in R 4.3.2. 3. Results 3.1 Incidence of NMSC in China and the world Compared with 1990, the number of global NMSC cases in 2021 increased from 1,661,600 to 6,336,800, with an increased rate of 281.37% and an upward trend for AAPC=4.37% (95%CI: 4.29%~4.44%); the incidence rate and age-standardized incidence rate (ASIR) increased from 31.15/100,000 and 45.04/100,000 to 80.30/100,000 and 74.10/100,000, respectively, with an increased rate of 157.78% and 64.52%, showed an upward trend, and the AAPC was 3.06% (95%CI: 2.93%~3.15%) and 1.57% (95%CI: 1.49%~1.64%), respectively. (Table 1) The number of NMSC cases in China increased from 39,500 to 791,900, and the increased rate (1904.81%) and upward trend (AAPC=9.88% (95%CI: 9.16%~10.37%)) were higher than that of the global level; the incidence rate and ASIR increased from 3.36/100,000 and 4.65/100,000 in 1990 to 55.66/100,000 and 37.54/100,000 in 2021, respectively, and both were lower than the global level in the same period, but their increase rates (1556.55% and 707.31%) and AAPC (9.22% (95%CI: 8.51%~9.71%) and 6.71% (95%CI: 6.01%~7.18%)) were significantly higher than the global level. (Table 1) Table 1 The incidence of NMSC in China and global, 1990-2021 Sex Incidence (10,000 cases) Incidence rate (per 100,000) ASIR (per 100,000) China Global China Global China Global Both 1990 3.95 166.16 3.36 31.15 4.65 45.04 2021 79.19 633.68 55.66 80.30 37.54 74.10 Change (%) 1904.81 281.37 1556.55 157.78 707.31 64.52 AAPC (%) 9.88 a 4.37 a 9.22 a 3.06 a 6.71 a 1.57 a 95%CI 9.16~10.37 4.29~4.44 8.51~9.71 2.93~3.15 6.01~7.18 1.49~1.64 Male 1990 2.15 87.40 3.55 32.54 5.34 55.30 2021 44.37 369.63 60.94 93.36 43.66 95.82 Change (%) 1963.72 322.92 1616.62 186.91 717.60 73.27 AAPC (%) 9.99 a 4.72 a 9.36 a 3.44 a 6.77 a 1.79 95%CI 9.29~10.47 4.63~4.79 8.67~9.84 3.31~3.53 6.10~7.22 1.69~1.88 Female 1990 1.80 78.77 3.15 29.75 4.11 38.23 2021 34.82 264.05 50.12 67.16 32.57 57.33 Change (%) 1834.44 235.22 1491.11 125.75 692.46 49.96 AAPC (%) 9.75 a 3.87 a 9.06 a 2.63 a 6.62 a 1.20 a 95%CI 8.99~10.25 3.76~3.96 8.31~9.56 2.47~2.73 5.87~7.12 1.09~1.29 NMSC, Non-melanoma skin cancer; ASIR, Age-standardized incidence rate; AAPC, Average annual percentage of change; a P < 0.001. Both in China and the world, the incidence cases, incidence and ASIR and corresponding increase rates and AAPC were higher in men than in women. In China, the age group with the highest incidence cases was 65-74 years old and the lowest was 85+ years old. Globally, the age group with the highest incidence cases was 65-74 years, and the lowest was 55-59 years. The age group with the lowest incidence in China and the world was 20-54 years old, the age group with the highest incidence in China was 80-84 years old, and the age group with the highest incidence in the world was 85+ years old. (Table 1, Figure 1) In 2022-2036, the ASIR of the Chinese population showed an increasing trend, with the male and female ASIR increasing from 79.94/100,000 and 63.35/100,000 in 2022 to 984,734.59/100,000 and 1,007,157.09/100,000 in 2036, respectively; and the global ASIR showed an increasing trend, with the male and female ASIR increased from 97.89/100,000 and 59.13/100,000 in 2022 to 173.16/100,000 and 111.51/100,000 in 2036. (Figure 2) 3.2 Mortality of NMSC in China and the world Compared with 1990, the global deaths in 2021 increased from 22,700 to 56,900, with an increase of 150.66% and an upward trend for AAPC=3.03% (95%CI: 3.00%~3.05%); the mortality rate and the age-standardized mortality rate (ASMR) increased from 0.42/100,000 and 0.67/100,000 to 0.72/100,000 and 0.69/100,000, respectively, with an increased rate of 71.43% and 2.99%, and an AAPC of 1.74% (95%CI: 1.71%~1.76%) and 0.14% (95%CI: 0.12%~0.16%), respectively. (Table 2) The NMSC deaths in China increased from 5,200 to 16,600, and the increased rate (219.23%) and upward trend (AAPC=3.75% (95%CI: 3.68%~3.80%)) were higher than that of the global level; the mortality rate and ASMR increased from 0.44/100,000 and 0.75/100,000 in 1990 to 1.17/100,000 and 0.87/100,000 in 2021, respectively, which were consistently higher than the global level during the same period, as were the increased rates (165.91% and 16.00%) and AAPC (3.17% (95%CI: 3.09%~3.22%) and 0.46% (95%CI: 0.40%~0.52%). (Table 2) Table 2 The mortality of NMSC in China and global, 1990-2021 Sex Mortality (10,000 cases) Mortality rate (per 100,000) ASMR (per 100,000) China Global China Global China Global Both 1990 0.52 2.27 0.44 0.42 0.75 0.67 2021 1.66 5.69 1.17 0.72 0.87 0.69 Change (%) 219.23 150.66 165.91 71.43 16.00 2.99 AAPC (%) 3.75 a 3.03 a 3.17 a 1.74 a 0.46 a 0.14 a 95%CI 3.68~3.80 3.00~3.05 3.09~3.22 1.71~1.76 0.40~0.52 0.12~0.16 Male 1990 0.28 1.28 0.46 0.48 0.93 0.88 2021 0.85 3.22 1.17 0.81 1.03 0.92 Change (%) 203.57 151.56 154.35 68.75 10.75 4.55 AAPC (%) 3.59 a 3.05 a 2.94 a 1.75 a 0.23 a 0.16 a 95%CI 3.51~3.67 3.03~3.07 2.86~3.01 1.73~1.77 0.09~0.33 0.14~0.17 Female 1990 0.24 0.99 0.42 0.37 0.64 0.52 2021 0.81 2.47 1.16 0.63 0.77 0.53 Change (%) 237.50 149.49 176.19 70.27 20.31 1.92 AAPC (%) 3.97 a 3.03 3.38 a 1.72 a 0.60 a 0.08 95%CI 3.91~4.02 2.98~3.07 3.30~3.46 1.68~1.75 0.53~0.67 0.04~0.11 NMSC, Non-melanoma skin cancer; ASMR, Age-standardized mortality rate; AAPC, Average annual percentage of change; a P < 0.001. Both in China and the world, the deaths, mortality rates and ASMR for NMSC were higher in men than in women, and the corresponding increase rates and AAPC were higher in men globally, but lower in men in China. The age group with the highest NMSC deaths in China was 65-74 years, and the lowest was 55-59 years; the age group with the highest deaths globally was 85+ years, and the lowest was 55-59 years. The lowest age group for mortality in both China and globally was 20-54 years, and the highest was 85+ years. (Table 2, Figure 3) Both the Chinese and global population-based ASMR were predicted to show a decreasing trend in 2022-2036, with the Chinese male and female ASMR decreased from 0.88/100,000 and 0.68/100,000 in 2022 to 0.82/100,000 and 0.56/100,000 in 2036, respectively, and the global male and female ASMR decreased from 0.78/100,000 and 0.45/100,000 in 2022 to 0.67/100,000 and 0.39/100,000 in 2036. (Figure 4) 3.3 DALY of NMSC in China and the world Compared to 1990, global DALY in 2021 increased from 545,600 to 1,122,900 person-years, the increased rate was 122.31%, and the AAPC was 2.61% (95%CI: 2.59% to 2.63%); the DALY rate and the age-standardized DALY rate (ASDR) increased from 10.23/100,000 and 14.02/100,000 to 15.37/100,000 and 14.33/100,000, respectively, the increased rate was 50.24% and 2.21%, respectively, and the AAPC was 1.31% (95%CI: 1.29%~1.33%) and 0.07% (95%CI: 0.04%~0.08%), respectively. (Table 3) Table 3 The burden of NMSC in China and global, 1990-2021 Sex DALY ( per 100,000 ) DALY rate (per 100,000) ASDR (per 100,000) China Global China Global China Global Both 1990 14.01 54.56 11.91 10.23 16.34 14.02 2021 36.08 121.29 25.36 15.37 17.98 14.33 Change (%) 151.53 122.31 112.93 50.24 10.04 2.21 AAPC (%) 3.07 a 2.61 a 2.45 a 1.31 a 0.28 a 0.07 a 95%CI 2.97~3.12 2.59~2.63 2.37~2.50 1.29~1.33 0.22~0.34 0.04~0.08 Male 1990 7.49 32.35 12.34 12.04 18.71 18.26 2021 18.85 71.78 25.88 18.13 20.23 18.61 Change (%) 151.67 121.89 109.72 49.75 8.12 1.92 AAPC (%) 3.01 a 2.61 a 2.36 a 1.33 a 0.18 0.04 95%CI 2.91~3.08 2.59~2.63 2.24~2.43 1.30~1.35 0.06~0.26 0.01~0.07 Female 1990 6.52 22.21 11.45 8.39 14.77 10.63 2021 17.23 49.51 24.82 12.59 16.34 10.82 Change (%) 164.26 122.92 116.77 50.06 10.63 1.79 AAPC (%) 3.16 a 2.63 a 2.56 a 1.31 a 0.35 a 0.07 a 95%CI 3.10~3.20 2.61~2.66 2.48~2.62 1.28~1.34 0.29~0.41 0.04~0.09 NMSC, Non-melanoma skin cancer; ASDR, Age-standardized disability-adjusted life years rate; AAPC, Average annual percentage of change; DALY, Disability-adjusted life years; a P < 0.001. DALY due to NMSC in China increased from 140,100 to 360,800 person-years, and the increased rate (151.53%) and AAPC (3.07% (95%CI: 2.97%~3.12%)) were higher than that of the global level; the DALY rate and ASDR increased from 11.91/100,000 and 16.34/100,000 in 1990 to 25.36/100,000 and 17.98/100,000 in 2021, respectively, both of which were higher than the global level in the same period, and their increased rates (112.93% and 10.04%) and AAPC (2.45% (95%CI: 2.37%~2.50%) and 0.28% (95%CI: 0.22%~0.34%)) were also higher than the global level. (Table 3) Both in China and globally, DALY, DALY rate and ASDR were higher in men than in women, and the corresponding increased rate and AAPC were lower in Chinese men than in women. DALY increased with age in both China and globally; the lowest DALY rate in China was in the 20-54 age group and the highest in the 85+ age group; the lowest DALY rate globally was in the 20-54 age group and the highest in the 85+ age group. (Table 3, Figure 5) In 2022-2036, it was predicted that the ASDR in Chinese males will increase from 19.22/100,000 in 2022 to 21.79/100,000 in 2036; the ASDR in Chinese females will decrease from 15.44/100,000 in 2022 to 13.98/100,000 in 2036. The global ASDR in males and females will decrease from 17.24/100,000 and 10.13/100,000 in 2022 to 15.40/100,000 and 8.95/100,000 in 2036, respectively. (Figure 6) 4. Discussion In this study, the GBD 2021 database was used to comprehensively compare and analyze the incidence, mortality and burden of NMSC in China and globally from 1990 to 2021, and to predict the trend in the next 15 years, providing strong evidence for the prevention and treatment of NMSC. Although the level of NMSC incidence in China was lower than the global level, it had relatively high levels of both death and DALY, and the increased rates of NMSC incidence, death and DLAY in China were faster than that of the world. There were significant gender differences in the burden of NMSC, with the incidence and rise of NMSC in men being higher than in women, but for mortality and DALY, although the levels were higher in men, the rise was faster in women. The high incidence, mortality and DALY rates of NMSC occurred in the higher age groups. It is predicted that the ASIR of China and global NMSC will continue to rise in the next 15 years, while the ASMR will decline. The burden of NMSC increased both in China and globally from 1990 to 2021, and the increase rate in China was higher than the global level. It was consistent with another study [ 14 ], indicating that NMSC remained a public health problem that cannot be ignored. This may be related to factors such as population aging, environmental pollution, and ozone layer depletion. The elderly were a high-risk group for NMSC, and the global population aging trend had an important impact on the incidence and mortality of NMSC [ 15 ]. In addition, UV radiation was a known risk factor for NMSC, which played a key role in the pathogenesis of skin cancer by causing DNA damage and immunosuppression [ 5 ]. Increased pollution due to urbanization and damage to the ozone layer had led to an increase in surface UV, thus raising the level of human UV exposure. In addition, with economic development and improved standards of living, people in today's society had more ability to engage in outdoor activities, including holidays, and these can increase the likelihood of tanning. It had been shown that tanning was significantly associated with an increased risk of developing NMSC, especially in women under the age of 25 [ 16 ]. As one of the fastest-aging countries in the world [ 17 ], China was faced with a particularly severe challenge. In addition, since the reform and opening up, China's economy had maintained high growth while facing enormous environmental cost pressures. The dependence of China's energy consumption structure on fossil energy sources, such as coal, had led to increasing problems with pollutants and carbon emissions [ 18 , 19 ]. These factors combined to increase the incidence of NMSC in China from 5th in 1990 to 4th today [ 20 ], a growth rate that exceeded the world average level. The higher mortality and burden of NMSC in China may be related to late diagnosis due to insufficient public awareness of the disease, unequal distribution of healthcare resources, and lack of systematic screening. NMSC, despite its high incidence, was generally curable by surgery. It had been reported that patients with NMSC in China were usually in the middle to late stages when diagnosed, missing the best treatment and having a shorter average survival [ 21 ]. Second, China's medical resources were unevenly distributed geographically, with high-quality medical resources more concentrated in large cities and developed coastal areas. This may make it difficult for residents in some areas to access timely and effective skin cancer screening and treatment. This study further found that the incidence of NMSC was higher in men than in women, both globally and in China. According to the American Cancer Society, NMSC was twice as common in men as in women, and squamous cell carcinoma was three times more common in men than women [ 22 ]. This difference may be related to the different work and lifestyle of men and women. Men worked outdoors more frequently and were therefore more exposed to UV light. In addition, men also used sunscreen, hats, and other protective gear less often than women [ 15 ]. This study also found that the burden of NMSC tended to increase with age, which was consistent with other studies [ 10 , 23 ]. Firstly, the skin was in contact with the natural environment for a long period and underwent exposure to wind and sun, which caused aging with age [ 2 ]. Secondly, the immune system was weaker in the elderly, and with reduced immune function after aging, abnormal cells cannot be completely removed and will gradually proliferate, thus increased the chance of developing cancer. This emphasized the importance of attention and preventive measures for the elderly [ 24 , 25 ]. The incidence of NMSC will continue to increase in China and globally from 2022 to 2036, whereas the mortality and DALY were predicted to gradually decrease. The main reasons for this increase were likely to be population aging and high-risk behaviors (e.g. increased outdoor recreational activities). China had implemented the "Healthy China Action: Cancer Prevention and Control Implementation Plan (2019–2030)", and the mortality rate of NMSC had been effectively controlled, but there was still a gap compared with European and American countries [ 14 ]. Between 2013 and 2017, with the introduction of new therapies such as immune checkpoint inhibitors and targeted therapies for metastatic melanoma, the melanoma mortality rate in the United States decreased significantly by 6.4% per year. This reflected the progress made in recent years in the early diagnosis and treatment of skin cancer. Effective prevention and treatment of skin cancer played an important role in reducing the morbidity and mortality of this disease, especially NMSC. The sustainability of this positive trend needed to be supported by further surveillance and public health interventions. This study had some limitations. The GBD database was a global endeavor to describe the epidemiology of diseases around the world using existing data and sophisticated analytical frameworks but may lack data from vital registries, verbal autopsies, and other sources. In addition, the quantity, quality and calibration methods of the model data also had an impact on the estimated information. This study compared the burden of NMSC in China with that of the world, analyzed differences in age and sex, but did not consider other risk factors, and the study was cross-sectional and could not suggest a causal relationship between relevant risk factors. 5. Conclusion The findings of this study provide valuable information for public health policymakers. In order to address the burden of NMSC, it was recommended that sunscreen education and public awareness of skin cancer risk factors should be strengthened, especially prevention and screening strategies targeting men and older populations. Future studies should focus on the specific causes of NMSC and how to reduce its burden through effective preventive measures. In addition, studies should consider multiple risk factors, including genetic, environmental, and socioeconomic factors, to gain a more comprehensive understanding of the prevalence of NMSC. In conclusion, this study highlighted the importance of NMSC as a global public health problem and provided a scientific basis for future prevention and intervention measures. Declarations Authors’ contributions Su Liang : Conceptualization, Methodology, Software, Formal analysis, Writing -original draft, Writing-review & editing. Juan Mei Cao and Xue Song Jia : Methodology, Software, Formal analysis. Xue Wang : Conceptualization, Methodology, Software, Formal analysis, Writing-original draft, Writing-review & editing, Supervision, Project administration, Funding acquisition. Funding This study was supported by National Natural Science Foundation of China Youth Project. (Project No:82203956). Availability of data and materials All data can be publicly obtained from link https://www.healthdata.org/Data-tools-practices/data-practices/ihme-free-charge-non-commercial-user-agreement. Acknowledgments We thank all related works from The First Affiliated Hospital of Shihezi University Who devoted their time and energy to preparing these publicly available data. C ompeting interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. References Gordon R. Skin cancer: an overview of epidemiology and risk factors. SEMIN ONCOL NURS 2013, 29(3):160-169. Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024, 74(3): 229-263. van Bodegraven B, Vernon S, Eversfield C, Board R, Craig P, Gran S, et al. 'Get Data Out' Skin: national cancer registry incidence and survival rates for all registered skin tumour groups for 2013-2019 in England. Br J Dermatol 2023, 188(6):777-784. Leigh IM. Progress in skin cancer: the U.K. experience. Br J Dermatol 2014, 171(3):443-445. Aggarwal P, Knabel P, Fleischer AJ. United States burden of melanoma and non-melanoma skin cancer from 1990 to 2019. J AM ACAD DERMATOL 2021, 85(2):388-395. Lomas A, Leonardi-Bee J, Bath-Hextall F. A systematic review of worldwide incidence of nonmelanoma skin cancer. Br J Dermatol 2012, 166(5):1069-1080. Kansara S, Bell D, Weber R. Surgical management of non melanoma skin cancer of the head and neck. ORAL ONCOL 2020, 100:104485. Tanese K, Nakamura Y, Hirai I, Funakoshi T. Updates on the Systemic Treatment of Advanced Non-melanoma Skin Cancer. Front Med (Lausanne) 2019, 6:160. Jorge R Ledesma, Jianing Ma, Meixin Zhang, Ann V L Basting, Huong Thi Chu, Avina Vongpradith, et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. LANCET 2024, 403(10440):2162-2203. Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. STAT MED 2000, 19(3):335-351. Quante AS, Ming C, Rottmann M, Engel J, Boeck S, Heinemann V, et al. Projections of cancer incidence and cancer-related deaths in Germany by 2020 and 2030. Cancer Med 2016, 5(9):2649-2656. Vollset SE, Goren E, Yuan CW, Cao J, Smith AE, Hsiao T, et al. Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study. LANCET 2020, 396(10258):1285-1306. Wu X, Du J, Li L, Cao W, Sun S. Bayesian Age-Period-Cohort Prediction of Mortality of Type 2 Diabetic Kidney Disease in China: A Modeling Study. Front Endocrinol (Lausanne) 2021, 12:767263. Yan Wu, Yu Wang, Lijun Wang, Peng Yin, Yun Lin, Maigeng Zhou. Burden of melanoma in China, 1990–2017: Findings from the 2017 global burden of disease study. INT J CANCER 2020, 147(3). Hu W, Fang L, Ni R, Zhang H, Pan G. Changing trends in the disease burden of non-melanoma skin cancer globally from 1990 to 2019 and its predicted level in 25 years. BMC CANCER 2022, 22(1):836. Apalla Z, Nashan D, Weller RB, Castellsague X. Skin Cancer: Epidemiology, Disease Burden, Pathophysiology, Diagnosis, and Therapeutic Approaches. Dermatol Ther (Heidelb) 2017, 7(Suppl 1):5-19. Man W, Wang S, Yang H. Exploring the spatial-temporal distribution and evolution of population aging and social-economic indicators in China. BMC PUBLIC HEALTH 2021, 21(1):966. World Energy Outlook 2020. Zhang S, Chen W. Assessing the energy transition in China towards carbon neutrality with a probabilistic framework. NAT COMMUN 2022. Cao W, Chen H-D, Yu Y-W. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chinese Medical Journal 2021, 134(7):9. Hao M, Zhao G, Du X, Yang Y, Yang J. Clinical characteristics and prognostic indicators for metastatic melanoma: data from 446 patients in north China. Tumour Biol 2016, 37(8):10339-10348. Artosi F, Costanza G, Di Prete M, Garofalo V, Lozzi F, Dika E, et al. Epidemiological and clinical analysis of exposure-related factors in non- melanoma skin cancer: A retrospective cohort study. ENVIRON RES 2024, 247:118117. Oh CM, Cho H, Won YJ, Kong HJ, Roh YH, Jeong KH, et al. Nationwide Trends in the Incidence of Melanoma and Non-melanoma Skin Cancers from 1999 to 2014 in South Korea. CANCER RES TREAT 2018, 50(3):729-737. Cives M, Mannavola F, Lospalluti L, Sergi MC, Cazzato G, Filoni E, et al. Non-Melanoma Skin Cancers: Biological and Clinical Features. INT J MOL SCI 2020, 21(15). Sol S, Boncimino F, Todorova K, Waszyn SE, Mandinova A. Therapeutic Approaches for Non-Melanoma Skin Cancer: Standard of Care and Emerging Modalities. INT J MOL SCI 2024, 25(13). Molassiotis A, Kwok S, Leung A, Tyrovolas S. Associations between sociodemographic factors, health spending, disease burden, and life expectancy of older adults (70 + years old) in 22 countries in the Western Pacific Region, 1995-2019: estimates from the Global Burden of Disease (GBD) Study 2019. GEROSCIENCE 2022, 44(2):925-951. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-4948431","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":355318887,"identity":"4d7bceff-0691-44f9-a6f2-bc0696a2bbb8","order_by":0,"name":"Su Liang","email":"","orcid":"","institution":"the First Affiliated Hospital of Shihezi University","correspondingAuthor":false,"prefix":"","firstName":"Su","middleName":"","lastName":"Liang","suffix":""},{"id":355318888,"identity":"29fd16de-ea97-4db4-988c-2027d91ed139","order_by":1,"name":"Xue Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYBACNvb+hw8kftjIsTEzHyBOCx/PGWYDy540Yz72tgTitMhJ+LBJVLAdSpzHc8aASIdJ8B42uMFzwJhNIufjjTcMdnK6DYS0SPclPpxhcUeOTSJ3s+UchmRjswOEtMgcMDaW4HkGtCV3mzQPw4HEbQS1SCSYSf9hO5zYJpHzjFgtOWYSEiAtPGfYiNTCcyzZQBIYyGzsbcaWcwyI8It8e/NBcFTKNzM/vPGmwk6OoBYUIMFDZNQgayFVxygYBaNgFIwIAAAmPT6nyKZ/kgAAAABJRU5ErkJggg==","orcid":"","institution":"the First Affiliated Hospital of Shihezi University","correspondingAuthor":true,"prefix":"","firstName":"Xue","middleName":"","lastName":"Wang","suffix":""},{"id":355318889,"identity":"5cb5cec6-f458-4625-a576-7fb0716053e2","order_by":2,"name":"Juan Mei Cao","email":"","orcid":"","institution":"the First Affiliated Hospital of Shihezi University","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"Mei","lastName":"Cao","suffix":""},{"id":355318890,"identity":"429c1d17-98cd-47ad-9334-3b1b42cf5ae4","order_by":3,"name":"Xue Song Jia","email":"","orcid":"","institution":"the First Affiliated Hospital of Shihezi University","correspondingAuthor":false,"prefix":"","firstName":"Xue","middleName":"Song","lastName":"Jia","suffix":""}],"badges":[],"createdAt":"2024-08-21 03:58:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4948431/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4948431/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64912668,"identity":"4c0b2116-2a43-4a42-9afc-6df885591951","added_by":"auto","created_at":"2024-09-20 10:05:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36612,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIncidence changes of NMSC in China and global from 1990 to 2021.\u003c/strong\u003eIncidence cases in China (A) and Global (B), incidence in China (C) and Global (D).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4948431/v1/618d73552b0cfeddbe2e2358.png"},{"id":64912671,"identity":"002eb837-f0cd-4919-8158-285151283475","added_by":"auto","created_at":"2024-09-20 10:05:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":201433,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe ASIR prediction of NMSC in China and global from 2022 to 2036.\u003c/strong\u003e ASIR prediction in China male (A), China female (B), Global male (C), Global female (D). Observed (dashed lines) and predicted rates (solid lines). The blue region shows the upper and lower limits of the 95% uncertainty intervals (95% UI). ASIR, Age-standardized incidence rate. NMSC, Non-melanoma skin cancer.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4948431/v1/1c0ac5120c4bc4bf8f7db8f8.png"},{"id":64912670,"identity":"437d4479-5a6c-4227-9cc0-5df6c6abe91a","added_by":"auto","created_at":"2024-09-20 10:05:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":34259,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMortality changes of NMSC in China and global from 1990 to 2021.\u003c/strong\u003e Deaths in China (A) and Global (B), mortality rate in China (C) and Global (D).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4948431/v1/65a74dde6c8b1b469783e9a2.png"},{"id":64912664,"identity":"b89e6b1b-eaa4-4127-978f-3e7d24ce1f32","added_by":"auto","created_at":"2024-09-20 10:05:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":239735,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe ASMR prediction of NMSC in China and global from 2022 to 2036.\u003c/strong\u003e ASMR prediction in China male (A), China female (B), Global male (C), Global female (D). Observed (dashed lines) and predicted rates (solid lines). The blue region shows the upper and lower limits of the 95% uncertainty intervals (95% UI). ASMR, Age-standardized mortality rate. NMSC, Non-melanoma skin cancer.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4948431/v1/7bb17d465222cfb159bf088c.png"},{"id":64912669,"identity":"7ca31d4d-4bca-4b12-9949-9e767a721b49","added_by":"auto","created_at":"2024-09-20 10:05:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":36823,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDALY changes of NMSC in China and global from 1990 to 2021.\u003c/strong\u003e DALY in China (A) and Global (B), DALY rate in China (C) and Global (D). DALY, Disability-adjusted life years.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4948431/v1/f3c1a2bd7f95a0de99a565a0.png"},{"id":64912667,"identity":"69499b10-605e-4401-8f52-4d1578d094e2","added_by":"auto","created_at":"2024-09-20 10:05:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":227597,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe ASDR prediction of NMSC in China and global from 2022 to 2036.\u003c/strong\u003e ASDR prediction in China male (A), China female (B), Global male (C), Global female (D). Observed (dashed lines) and predicted rates (solid lines). The blue region shows the upper and lower limits of the 95% uncertainty intervals (95% UI). ASDR, Age-standardized disability-adjusted life years rate. NMSC, Non-melanoma skin cancer.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4948431/v1/4adb810b944a7f92f8740c01.png"},{"id":69865943,"identity":"e98bcdab-464b-4a5f-bbfb-993bd34c6c75","added_by":"auto","created_at":"2024-11-26 06:54:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1714644,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4948431/v1/79805589-4f63-406e-aea5-44f76e7214de.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Systematic analysis of non-melanoma skin cancer burden: a comparative study between China and the world from 1990 to 2021 and prediction to 2036","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNon-melanoma skin cancer (NMSC) was one of the most common cancers, divided into basal cell carcinoma and squamous cell carcinoma, and had become a prominent public health problem worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to GLOBOCAN, there were 1,234,595 new cases and 69,481 deaths of NMSC globally in 2022, accounting for 8% of all cancer deaths [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The incidence of NMSC had been found to increase annually, especially in areas with high UV exposure, such as Oceania and parts of the United States where the incidence was highest [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and was more common in white population [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The age-standardized incidence of NMSC in the United States had increased from 402 (/100,000) in 1990 to 784 (/100,000) in 2019 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, the actual incidence of NMSC may be underestimated because many countries were not required to report NMSC information to national cancer registries, which explained the lack of priority given to NMSC in most countries [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt present, there were relatively few epidemiological studies on NMSC in China, which mainly focus on clinical treatment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Epidemiological evidence was essential for effective disease prevention and control. Therefore, in order to better address the challenges posed by NMSC, this study compared the burden (incidence, mortality, and disability-adjusted life-years (DALY)) caused by NMSC in China and globally from 1990 to 2021 and predicted it by gender, based on the GBD 2021 database, using the Joinpoint regression model and the Bayesian age-period-cohort (BAPC) model, and to develop more effective prevention and treatment strategies and interventions.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Data collection\u003c/h2\u003e\n \u003cp\u003eData related to the burden of NMSC were obtained from the GBD 2021 database, which provided epidemiological data for 204 countries or regions, 371 diseases, and 88 risk factors, and provided a strong basis for detailed and extensive understanding of global health trends and emerging challenges [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]. In this study, we extracted the number of incidence, deaths and DALYs of NMSC and their corresponding crude rates from GBD 2021 for China and the world.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Data analysis\u003c/h2\u003e\n \u003cp\u003eThe incidence, mortality and DALY rates of NMSC in China and the world were standardized using the world standard demographics, and the average annual percentage change (AAPC) of each indicator was calculated using Joinpoint 5.0.2 software. Finally, R 4.3.2 was used for prediction.\u003c/p\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 Joinpoint regression model\u003c/h2\u003e\n \u003cp\u003eThe Joinpoint regression model was a log-linear model with time (year) as the independent variable and incidence or mortality as the dependent variable [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]. It described the trend of incidence or mortality by splicing the joinpoints of different logarithmic line segments [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. The model was used to calculate the AAPC and its 95% confidence interval (CI) from 1990 to 2021. The model formula was as follows:\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cimg src=\"data:image/png;base64,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\" style=\"width: 470px; height: 62.1071px;\" width=\"470\" height=\"62.1071\"\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eWhen both AAPC and its 95% CI are \u0026gt;\u0026thinsp;0, it meant that the corresponding indicator was on the rise; both \u0026lt;\u0026thinsp;0 were on the decline; and containing 0 meant that the indicator remained stable.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Bayesian age-period-cohort model\u003c/h2\u003e\n \u003cp\u003eWe used the BAPC model to predict the age-standardized incidence, mortality and DALY rates for NMSC by sex from 2022 to 2036 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. The model allowed for the inference of unknown parameters by combining the posterior information obtained from the sample information with the a priori information on the unknown parameters [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e], a process implemented using the BAPC and INLA packages in R 4.3.2.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Incidence of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eNMSC\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;in China and the world\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared with 1990, the number of global NMSC cases in 2021 increased from 1,661,600 to 6,336,800, with an increased rate of 281.37% and an upward trend for AAPC=4.37% (95%CI: 4.29%~4.44%); the incidence rate and age-standardized incidence rate (ASIR) increased from 31.15/100,000 and 45.04/100,000 to 80.30/100,000 and 74.10/100,000, respectively, with an increased rate of 157.78% and 64.52%, showed an upward trend, and the AAPC was 3.06% (95%CI: 2.93%~3.15%) and 1.57% (95%CI: 1.49%~1.64%), respectively. (Table 1)\u003c/p\u003e\n\u003cp\u003eThe number of NMSC cases in China increased from 39,500 to 791,900, and the increased rate (1904.81%) and upward trend (AAPC=9.88% (95%CI: 9.16%~10.37%)) were higher than that of the global level; the incidence rate and ASIR increased from 3.36/100,000 and 4.65/100,000 in 1990 to 55.66/100,000 and 37.54/100,000 in 2021, respectively, and both were lower than the global level in the same period, but their increase rates (1556.55% and 707.31%) and AAPC (9.22% (95%CI: 8.51%~9.71%) and 6.71% (95%CI: 6.01%~7.18%)) were significantly higher than the global level. (Table 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 The incidence of NMSC in China and global, 1990-2021\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.010544815465728%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncidence\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(10,000 cases)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.71353251318102%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncidence rate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(per 100,000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.71353251318102%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eASIR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(per 100,000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.735537190082646%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84297520661157%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.3057851239669422%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.702479338842975%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.702479338842975%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.3057851239669422%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.702479338842975%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.702479338842975%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e3.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e166.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e31.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e45.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e79.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e633.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e55.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e80.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e37.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e74.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e1904.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e281.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1556.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e157.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e707.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e64.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e9.88\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e4.37\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e9.22\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e3.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e6.71\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1.57\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e9.16~10.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e4.29~4.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e8.51~9.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e2.93~3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e6.01~7.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1.49~1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e87.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e32.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e55.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e44.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e369.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e60.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e93.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e43.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e95.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e1963.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e322.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1616.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e186.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e717.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e73.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e9.99\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e4.72\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e9.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e3.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e6.77\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e9.29~10.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e4.63~4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e8.67~9.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e3.31~3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e6.10~7.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1.69~1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e78.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e29.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e38.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e34.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e264.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e50.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e67.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e32.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e57.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e1834.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e235.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1491.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e125.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e692.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e49.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e9.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e3.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e9.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e2.63\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e6.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.235500878734623%\"\u003e\n \u003cp\u003e8.99~10.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.775043936731107%\"\u003e\n \u003cp\u003e3.76~3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e8.31~9.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e2.47~2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e5.87~7.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.35676625659051%\"\u003e\n \u003cp\u003e1.09~1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNMSC, Non-melanoma skin cancer; ASIR, Age-standardized incidence rate; AAPC, Average annual percentage of change; \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e\n\u003cp\u003eBoth in China and the world, the incidence cases, incidence and ASIR and corresponding increase rates and AAPC were higher in men than in women. In China, the age group with the highest incidence cases was 65-74 years old and the lowest was 85+ years old. Globally, the age group with the highest incidence cases was 65-74 years, and the lowest was 55-59 years. The age group with the lowest incidence in China and the world was 20-54 years old, the age group with the highest incidence in China was 80-84 years old, and the age group with the highest incidence in the world was 85+ years old. (Table 1, Figure 1)\u003c/p\u003e\n\u003cp\u003eIn 2022-2036, the ASIR of the Chinese population showed an increasing trend, with the male and female ASIR increasing from 79.94/100,000 and 63.35/100,000 in 2022 to 984,734.59/100,000 and 1,007,157.09/100,000 in 2036, respectively; and the global ASIR showed an increasing trend, with the male and female ASIR increased from 97.89/100,000 and 59.13/100,000 in 2022 to 173.16/100,000 and 111.51/100,000 in 2036. (Figure 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Mortality of NMSC in China and the world\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared with 1990, the global deaths in 2021 increased from 22,700 to 56,900, with an increase of 150.66% and an upward trend for AAPC=3.03% (95%CI: 3.00%~3.05%); the mortality rate and the age-standardized mortality rate (ASMR) increased from 0.42/100,000 and 0.67/100,000 to 0.72/100,000 and 0.69/100,000, respectively, with an increased rate of 71.43% and 2.99%, and an AAPC of 1.74% (95%CI: 1.71%~1.76%) and 0.14% (95%CI: 0.12%~0.16%), respectively. (Table 2)\u003c/p\u003e\n\u003cp\u003eThe NMSC deaths in China increased from 5,200 to 16,600, and the increased rate (219.23%) and upward trend (AAPC=3.75% (95%CI: 3.68%~3.80%)) were higher than that of the global level; the mortality rate and ASMR increased from 0.44/100,000 and 0.75/100,000 in 1990 to 1.17/100,000 and 0.87/100,000 in 2021, respectively, which were consistently higher than the global level during the same period, as were the increased rates (165.91% and 16.00%) and AAPC (3.17% (95%CI: 3.09%~3.22%) and 0.46% (95%CI: 0.40%~0.52%). (Table 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 The mortality of NMSC in China and global, 1990-2021\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.017667844522968%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.558303886925795%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(10,000 cases)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.8268551236749118%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.385159010600706%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality rate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(per 100,000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.8268551236749118%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.385159010600706%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eASMR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(per 100,000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.462809917355372%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462809917355372%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.3057851239669422%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.3057851239669422%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e5.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e219.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e150.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e165.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e71.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e16.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e3.17\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.14\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.68~3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.00~3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e3.09~3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.71~1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.40~0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.12~0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e203.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e151.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e154.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e68.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e10.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e2.94\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.51~3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.03~3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e2.86~3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.73~1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.09~0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.14~0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e237.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e149.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e176.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e70.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e20.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e3.38\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.72\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.60\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.938488576449911%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e3.91~4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.302284710017574%\"\u003e\n \u003cp\u003e2.98~3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e3.30~3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e1.68~1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.81195079086116%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.53~0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.708260105448154%\"\u003e\n \u003cp\u003e0.04~0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNMSC, Non-melanoma skin cancer; ASMR, Age-standardized mortality rate; AAPC, Average annual percentage of change; \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e\n\u003cp\u003eBoth in China and the world, the deaths, mortality rates and ASMR for NMSC were higher in men than in women, and the corresponding increase rates and AAPC were higher in men globally, but lower in men in China. The age group with the highest NMSC deaths in China was 65-74 years, and the lowest was 55-59 years; the age group with the highest deaths globally was 85+ years, and the lowest was 55-59 years. The lowest age group for mortality in both China and globally was 20-54 years, and the highest was 85+ years. (Table 2, Figure 3)\u003c/p\u003e\n\u003cp\u003eBoth the Chinese and global population-based ASMR were predicted to show a decreasing trend in 2022-2036, with the Chinese male and female ASMR decreased from 0.88/100,000 and 0.68/100,000 in 2022 to 0.82/100,000 and 0.56/100,000 in 2036, respectively, and the global male and female ASMR decreased from 0.78/100,000 and 0.45/100,000 in 2022 to 0.67/100,000 and 0.39/100,000 in 2036. (Figure 4)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 DALY of NMSC in China and the world\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared to 1990, global DALY in 2021 increased from 545,600 to 1,122,900 person-years, the increased rate was 122.31%, and the AAPC was 2.61% (95%CI: 2.59% to 2.63%); the DALY rate and the age-standardized DALY rate (ASDR) increased from 10.23/100,000 and 14.02/100,000 to 15.37/100,000 and 14.33/100,000, respectively, the increased rate was 50.24% and 2.21%, respectively, and the AAPC was 1.31% (95%CI: 1.29%~1.33%) and 0.07% (95%CI: 0.04%~0.08%), respectively. (Table 3)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 The burden of NMSC in China and global, 1990-2021\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.964912280701753%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eDALY\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003e\u003cstrong\u003eper 100,000\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.964912280701753%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eDALY\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;rate\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(per 100,000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.964912280701753%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eASDR\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(per 100,000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.416666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.416666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.416666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.416666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.416666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.416666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e14.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e54.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e11.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e10.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e16.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e14.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e36.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e121.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e25.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e15.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e17.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e14.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e151.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e122.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e112.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e50.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e10.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e3.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.61\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.28\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.97~3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.59~2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.37~2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.29~1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.22~0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.04~0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e7.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e32.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e12.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e12.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e18.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e18.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e18.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e71.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e25.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e18.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e20.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e18.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e151.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e121.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e109.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e49.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e8.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e3.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.61\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.33\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.91~3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.59~2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.24~2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.30~1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.06~0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.01~0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e6.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e22.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e11.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e8.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e14.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e10.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e17.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e49.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e24.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e12.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e16.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e10.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eChange (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e164.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e122.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e116.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e50.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e10.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003eAAPC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e3.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.63\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.35\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.789473684210526%\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e3.10~3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.61~2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e2.48~2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e1.28~1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.29~0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.982456140350877%\"\u003e\n \u003cp\u003e0.04~0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNMSC, Non-melanoma skin cancer; ASDR, Age-standardized disability-adjusted life years rate; AAPC, Average annual percentage of change; DALY, Disability-adjusted life years; \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e\n\u003cp\u003eDALY due to NMSC in China increased from 140,100 to 360,800 person-years, and the increased rate (151.53%) and AAPC (3.07% (95%CI: 2.97%~3.12%)) were higher than that of the global level; the DALY rate and ASDR increased from 11.91/100,000 and 16.34/100,000 in 1990 to 25.36/100,000 and 17.98/100,000 in 2021, respectively, both of which were higher than the global level in the same period, and their increased rates (112.93% and 10.04%) and AAPC (2.45% (95%CI: 2.37%~2.50%) and 0.28% (95%CI: 0.22%~0.34%)) were also higher than the global level. (Table 3)\u003c/p\u003e\n\u003cp\u003eBoth in China and globally, DALY, DALY rate and ASDR were higher in men than in women, and the corresponding increased rate and AAPC were lower in Chinese men than in women. DALY increased with age in both China and globally; the lowest DALY rate in China was in the 20-54 age group and the highest in the 85+ age group; the lowest DALY rate globally was in the 20-54 age group and the highest in the 85+ age group. (Table 3, Figure 5)\u003c/p\u003e\n\u003cp\u003eIn 2022-2036, it was predicted that the ASDR in Chinese males will increase from 19.22/100,000 in 2022 to 21.79/100,000 in 2036; the ASDR in Chinese females will decrease from 15.44/100,000 in 2022 to 13.98/100,000 in 2036. The global ASDR in males and females will decrease from 17.24/100,000 and 10.13/100,000 in 2022 to 15.40/100,000 and 8.95/100,000 in 2036, respectively. (Figure 6)\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, the GBD 2021 database was used to comprehensively compare and analyze the incidence, mortality and burden of NMSC in China and globally from 1990 to 2021, and to predict the trend in the next 15 years, providing strong evidence for the prevention and treatment of NMSC. Although the level of NMSC incidence in China was lower than the global level, it had relatively high levels of both death and DALY, and the increased rates of NMSC incidence, death and DLAY in China were faster than that of the world. There were significant gender differences in the burden of NMSC, with the incidence and rise of NMSC in men being higher than in women, but for mortality and DALY, although the levels were higher in men, the rise was faster in women. The high incidence, mortality and DALY rates of NMSC occurred in the higher age groups. It is predicted that the ASIR of China and global NMSC will continue to rise in the next 15 years, while the ASMR will decline.\u003c/p\u003e \u003cp\u003eThe burden of NMSC increased both in China and globally from 1990 to 2021, and the increase rate in China was higher than the global level. It was consistent with another study [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], indicating that NMSC remained a public health problem that cannot be ignored. This may be related to factors such as population aging, environmental pollution, and ozone layer depletion. The elderly were a high-risk group for NMSC, and the global population aging trend had an important impact on the incidence and mortality of NMSC [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In addition, UV radiation was a known risk factor for NMSC, which played a key role in the pathogenesis of skin cancer by causing DNA damage and immunosuppression [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Increased pollution due to urbanization and damage to the ozone layer had led to an increase in surface UV, thus raising the level of human UV exposure. In addition, with economic development and improved standards of living, people in today's society had more ability to engage in outdoor activities, including holidays, and these can increase the likelihood of tanning. It had been shown that tanning was significantly associated with an increased risk of developing NMSC, especially in women under the age of 25 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs one of the fastest-aging countries in the world [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], China was faced with a particularly severe challenge. In addition, since the reform and opening up, China's economy had maintained high growth while facing enormous environmental cost pressures. The dependence of China's energy consumption structure on fossil energy sources, such as coal, had led to increasing problems with pollutants and carbon emissions [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These factors combined to increase the incidence of NMSC in China from 5th in 1990 to 4th today [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], a growth rate that exceeded the world average level. The higher mortality and burden of NMSC in China may be related to late diagnosis due to insufficient public awareness of the disease, unequal distribution of healthcare resources, and lack of systematic screening. NMSC, despite its high incidence, was generally curable by surgery. It had been reported that patients with NMSC in China were usually in the middle to late stages when diagnosed, missing the best treatment and having a shorter average survival [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Second, China's medical resources were unevenly distributed geographically, with high-quality medical resources more concentrated in large cities and developed coastal areas. This may make it difficult for residents in some areas to access timely and effective skin cancer screening and treatment.\u003c/p\u003e \u003cp\u003eThis study further found that the incidence of NMSC was higher in men than in women, both globally and in China. According to the American Cancer Society, NMSC was twice as common in men as in women, and squamous cell carcinoma was three times more common in men than women [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This difference may be related to the different work and lifestyle of men and women. Men worked outdoors more frequently and were therefore more exposed to UV light. In addition, men also used sunscreen, hats, and other protective gear less often than women [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This study also found that the burden of NMSC tended to increase with age, which was consistent with other studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Firstly, the skin was in contact with the natural environment for a long period and underwent exposure to wind and sun, which caused aging with age [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Secondly, the immune system was weaker in the elderly, and with reduced immune function after aging, abnormal cells cannot be completely removed and will gradually proliferate, thus increased the chance of developing cancer. This emphasized the importance of attention and preventive measures for the elderly [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe incidence of NMSC will continue to increase in China and globally from 2022 to 2036, whereas the mortality and DALY were predicted to gradually decrease. The main reasons for this increase were likely to be population aging and high-risk behaviors (e.g. increased outdoor recreational activities). China had implemented the \"Healthy China Action: Cancer Prevention and Control Implementation Plan (2019\u0026ndash;2030)\", and the mortality rate of NMSC had been effectively controlled, but there was still a gap compared with European and American countries [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Between 2013 and 2017, with the introduction of new therapies such as immune checkpoint inhibitors and targeted therapies for metastatic melanoma, the melanoma mortality rate in the United States decreased significantly by 6.4% per year. This reflected the progress made in recent years in the early diagnosis and treatment of skin cancer. Effective prevention and treatment of skin cancer played an important role in reducing the morbidity and mortality of this disease, especially NMSC. The sustainability of this positive trend needed to be supported by further surveillance and public health interventions.\u003c/p\u003e \u003cp\u003eThis study had some limitations. The GBD database was a global endeavor to describe the epidemiology of diseases around the world using existing data and sophisticated analytical frameworks but may lack data from vital registries, verbal autopsies, and other sources. In addition, the quantity, quality and calibration methods of the model data also had an impact on the estimated information. This study compared the burden of NMSC in China with that of the world, analyzed differences in age and sex, but did not consider other risk factors, and the study was cross-sectional and could not suggest a causal relationship between relevant risk factors.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe findings of this study provide valuable information for public health policymakers. In order to address the burden of NMSC, it was recommended that sunscreen education and public awareness of skin cancer risk factors should be strengthened, especially prevention and screening strategies targeting men and older populations. Future studies should focus on the specific causes of NMSC and how to reduce its burden through effective preventive measures. In addition, studies should consider multiple risk factors, including genetic, environmental, and socioeconomic factors, to gain a more comprehensive understanding of the prevalence of NMSC. In conclusion, this study highlighted the importance of NMSC as a global public health problem and provided a scientific basis for future prevention and intervention measures.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSu Liang\u003c/strong\u003e:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Software, Formal analysis, Writing\u0026nbsp;-original draft, Writing-review\u0026nbsp;\u0026amp;\u0026nbsp;editing.\u0026nbsp;\u003cstrong\u003eJuan Mei Cao and Xue Song Jia\u003c/strong\u003e:\u0026nbsp;Methodology, Software, Formal analysis.\u0026nbsp;\u003cstrong\u003eXue Wang\u003c/strong\u003e:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Software, Formal analysis, Writing-original draft, Writing-review\u0026nbsp;\u0026amp;\u0026nbsp;editing, Supervision, Project administration, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by National Natural Science Foundation of China Youth Project. (Project No:82203956).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data can be publicly obtained from link https://www.healthdata.org/Data-tools-practices/data-practices/ihme-free-charge-non-commercial-user-agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all related works from The First Affiliated Hospital of Shihezi University Who devoted their time and energy to preparing these publicly available data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003eompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing\u0026nbsp;financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGordon R. Skin cancer: an overview of epidemiology and risk factors. SEMIN ONCOL NURS 2013, 29(3):160-169.\u003c/li\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024, 74(3): 229-263.\u003c/li\u003e\n\u003cli\u003evan Bodegraven B, Vernon S, Eversfield C, Board R, Craig P, Gran S, et al. \u0026apos;Get Data Out\u0026apos; Skin: national cancer registry incidence and survival rates for all registered skin tumour groups for 2013-2019 in England. Br J Dermatol 2023, 188(6):777-784.\u003c/li\u003e\n\u003cli\u003eLeigh IM. Progress in skin cancer: the U.K. experience. Br J Dermatol 2014, 171(3):443-445.\u003c/li\u003e\n\u003cli\u003eAggarwal P, Knabel P, Fleischer AJ. United States burden of melanoma and non-melanoma skin cancer from 1990 to 2019. J AM ACAD DERMATOL 2021, 85(2):388-395.\u003c/li\u003e\n\u003cli\u003eLomas A, Leonardi-Bee J, Bath-Hextall F. A systematic review of worldwide incidence of nonmelanoma skin cancer. Br J Dermatol 2012, 166(5):1069-1080.\u003c/li\u003e\n\u003cli\u003eKansara S, Bell D, Weber R. Surgical management of non melanoma skin cancer of the head and neck. ORAL ONCOL 2020, 100:104485.\u003c/li\u003e\n\u003cli\u003eTanese K, Nakamura Y, Hirai I, Funakoshi T. Updates on the Systemic Treatment of Advanced Non-melanoma Skin Cancer. Front Med (Lausanne) 2019, 6:160.\u003c/li\u003e\n\u003cli\u003eJorge R Ledesma, Jianing Ma, Meixin Zhang, Ann V L Basting, Huong Thi Chu, Avina Vongpradith, et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. LANCET 2024, 403(10440):2162-2203.\u003c/li\u003e\n\u003cli\u003eKim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. STAT MED 2000, 19(3):335-351.\u003c/li\u003e\n\u003cli\u003eQuante AS, Ming C, Rottmann M, Engel J, Boeck S, Heinemann V, et al. Projections of cancer incidence and cancer-related deaths in Germany by 2020 and 2030. Cancer Med 2016, 5(9):2649-2656.\u003c/li\u003e\n\u003cli\u003eVollset SE, Goren E, Yuan CW, Cao J, Smith AE, Hsiao T, et al. Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study. LANCET 2020, 396(10258):1285-1306.\u003c/li\u003e\n\u003cli\u003eWu X, Du J, Li L, Cao W, Sun S. Bayesian Age-Period-Cohort Prediction of Mortality of Type 2 Diabetic Kidney Disease in China: A Modeling Study. Front Endocrinol (Lausanne) 2021, 12:767263.\u003c/li\u003e\n\u003cli\u003eYan Wu, Yu Wang, Lijun Wang, Peng Yin, Yun Lin, Maigeng Zhou. Burden of melanoma in China, 1990\u0026ndash;2017: Findings from the 2017 global burden of disease study. INT J CANCER 2020, 147(3).\u003c/li\u003e\n\u003cli\u003eHu W, Fang L, Ni R, Zhang H, Pan G. Changing trends in the disease burden of non-melanoma skin cancer globally from 1990 to 2019 and its predicted level in 25 years. BMC CANCER 2022, 22(1):836.\u003c/li\u003e\n\u003cli\u003eApalla Z, Nashan D, Weller RB, Castellsague X. Skin Cancer: Epidemiology, Disease Burden, Pathophysiology, Diagnosis, and Therapeutic Approaches. Dermatol Ther (Heidelb) 2017, 7(Suppl 1):5-19.\u003c/li\u003e\n\u003cli\u003eMan W, Wang S, Yang H. Exploring the spatial-temporal distribution and evolution of population aging and social-economic indicators in China. BMC PUBLIC HEALTH 2021, 21(1):966.\u003c/li\u003e\n\u003cli\u003eWorld Energy Outlook 2020.\u003c/li\u003e\n\u003cli\u003eZhang S, Chen W. Assessing the energy transition in China towards carbon neutrality with a probabilistic framework. NAT COMMUN 2022.\u003c/li\u003e\n\u003cli\u003eCao W, Chen H-D, Yu Y-W. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chinese Medical Journal 2021, 134(7):9.\u003c/li\u003e\n\u003cli\u003eHao M, Zhao G, Du X, Yang Y, Yang J. Clinical characteristics and prognostic indicators for metastatic melanoma: data from 446 patients in north China. Tumour Biol 2016, 37(8):10339-10348.\u003c/li\u003e\n\u003cli\u003eArtosi F, Costanza G, Di Prete M, Garofalo V, Lozzi F, Dika E, et al. Epidemiological and clinical analysis of exposure-related factors in non- melanoma skin cancer: A retrospective cohort study. ENVIRON RES 2024, 247:118117.\u003c/li\u003e\n\u003cli\u003eOh CM, Cho H, Won YJ, Kong HJ, Roh YH, Jeong KH, et al. Nationwide Trends in the Incidence of Melanoma and Non-melanoma Skin Cancers from 1999 to 2014 in South Korea. CANCER RES TREAT 2018, 50(3):729-737.\u003c/li\u003e\n\u003cli\u003eCives M, Mannavola F, Lospalluti L, Sergi MC, Cazzato G, Filoni E, et al. Non-Melanoma Skin Cancers: Biological and Clinical Features. INT J MOL SCI 2020, 21(15).\u003c/li\u003e\n\u003cli\u003eSol S, Boncimino F, Todorova K, Waszyn SE, Mandinova A. Therapeutic Approaches for Non-Melanoma Skin Cancer: Standard of Care and Emerging Modalities. INT J MOL SCI 2024, 25(13).\u003c/li\u003e\n\u003cli\u003eMolassiotis A, Kwok S, Leung A, Tyrovolas S. Associations between sociodemographic factors, health spending, disease burden, and life expectancy of older adults (70 + years old) in 22 countries in the Western Pacific Region, 1995-2019: estimates from the Global Burden of Disease (GBD) Study 2019. GEROSCIENCE 2022, 44(2):925-951.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Non-melanoma skin cancer, Joinpoint regression model, Bayesian age-period-cohort model, Burden of disease, Comparative study","lastPublishedDoi":"10.21203/rs.3.rs-4948431/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4948431/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eComparative analysis of the characteristics and trends of the burden of non-melanoma skin cancer (NMSC) in China and globally will provide a basis for the development of effective prevention and control measures in China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData related to incidence, death and disability-adjusted life year (DALY) of NMSC in China and the world were obtained from the Global Burden of Disease (GBD) 2021 database. The average annual percentage of change (AAPC) was estimated by the Joinpoint regression model to reflect the time trend. Bayesian age-period-cohort model was constructed for prediction.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFrom 1990 to 2021, the increase rates (707.31%, 16.00%, and 10.04%) and upward trends (AAPC\u0026thinsp;=\u0026thinsp;6.71% (95%: 6.01%~7.18%), 0.46% (95%: 0.40%~0.52%), and 0.28% ( 95%: 0.22%~0.34%)) of the NMSC age standardized incidence, mortality, and DALY rate in China were higher than the global level. Both the incidence of NMSC and its rise were higher in men than in women, and the levels of death and DALY were higher in men but rose more rapidly in women. The high incidence, mortality, and DALY rate of NMSC all occurred in the higher age groups. The age-standardized incidence of NMSC in China and globally was predicted to continue to rise over the next 15 years, while the age-standardized mortality rate will decline.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe burden of NMSC in China remained serious, especially in the context of an increasingly aging population. Relevant authorities should continue to develop and optimize preventive and control measures, especially for men, and adopt targeted measures to significantly reduce the burden of NMSC.\u003c/p\u003e","manuscriptTitle":"Systematic analysis of non-melanoma skin cancer burden: a comparative study between China and the world from 1990 to 2021 and prediction to 2036","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-20 10:05:38","doi":"10.21203/rs.3.rs-4948431/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"523e91e3-be1d-42b1-bfcb-e053bd9e7fa8","owner":[],"postedDate":"September 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-26T06:54:24+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-20 10:05:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4948431","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4948431","identity":"rs-4948431","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}