Burdens of liver cancer in young adults worldwide from 1990 to 2019, and predictions from 2020 to 2030

Burdens of liver cancer in young adults worldwide from 1990 to 2019, and predictions from 2020 to 2030 | 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 Burdens of liver cancer in young adults worldwide from 1990 to 2019, and predictions from 2020 to 2030 Chenlu Fan, Xin Zhang, Meichen Zhang, Yanmei Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3899212/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 Background This study was to investigate the prevalence of liver cancer among individuals aged 15–49 globally and predict future trends in its burden until 2030. Methods The age-standardized indicators and their estimated annual percentage changes (EAPCs) were calculated in this study. Generalized additive models (GAMs) were employed to predict the burdens for the period of 2020–2030. Results From 1990 to 2019, the burden of liver cancer increased significantly among individuals aged 35–49, with the highest peak observed among those aged 45–49. The burden was higher in men compared to women. During the same period, the age-standardized incidence rate (ASIR) and age-standardized death rate of liver cancer in young adults showed the greatest increase in Central Asia, while the age-standardized disability-adjusted life year rate increased the most in Eastern Europe. Among the 204 countries examined, Uzbekistan had the highest increase in ASIR of liver cancer in young adults. Furthermore, using GAMs, we predicted that from 2020 to 2030, the burden of liver cancer will continue to rise among individuals aged 30–34 and 35–39. Notably, the burden of liver cancer attributed to alcohol use is projected to increase significantly between 2020 and 2030. Conclusions The burden of liver cancer among young adults has shown an age-dependent increase in 2019, with men experiencing a greater burden compared to women. The projected estimates indicate a rise in the burden of liver cancer attributed to alcohol consumption among young adults, specifically from 2020 to 2030. Young adults Liver cancer Age-standardized DALY rate Age-standardized death rate Age-standardized incidence rate Figures Figure 1 Figure 2 Figure 3 1. Background Hepatocellular carcinoma, also known as liver cancer, poses a significant challenge in the field of global health. It is not only one of the most common types of cancer worldwide, but it also has wide-ranging impacts beyond the realm of health, affecting the socio-economic well-being of nations. For instance, in 2018, liver cancer caused the death of 781,631 individuals and was diagnosed in approximately 841,080 people, with its incidence continuing to rise steadily [ 1 ]. These statistics highlight the significant economic and health burden associated with liver cancer, emphasizing the urgent need for comprehensive research on its underlying causes, risk factors, and, most importantly, prevention and treatment strategies. The onset of liver cancer can be attributed to various factors, but excessive alcohol consumption and viral infections are identified as the main controllable causes. In recent studies, a strong association has been established between alcohol intake, diseases like hepatitis B and C, and the development of liver cancer [ 2 , 3 ]. These findings indicate that long-term alcohol abuse and viral infections significantly increase the risk of liver cancer. Young adults play a critical role in the workforce and are vital to a nation's economic health. Their own health serves as a reflection of the nation's present and future well-being. The habits they adopt, such as their diet, exercise, medication usage, and mental well-being, often have long-lasting effects on their health outcomes [ 4 ]. Given the significant impact of their well-being on global productivity, it is imperative that disease prevention and treatment for this demographic are prioritized. However, there is a concerning lack of research investigating the burden of liver cancer specifically in young adults, both on a global and national scale [ 4 ]. In response to this gap, this study aims to shed light on the burden and evolving trends of liver cancer among young adults worldwide. The findings from this study will provide valuable insights for stakeholders in order to develop effective prevention strategies [ 5 ]. Drawing on the Global Burden of Disease Study (GBD) 2019, this investigation examines various metrics related to liver cancer in young adults over a period of three decades (1990–2019). These metrics include the global age-standardized incidence rate (ASIR), death rate, disability-adjusted life years (DALY) rate, and their estimated annual percentage changes (EAPCs). The analysis also explores the burdens associated with alcohol use, hepatitis B, and hepatitis C, tracking their trajectories over time. Additionally, using generalized additive models (GAMs), we forecast the future global trends in liver cancer burdens until 2030, providing a forward-looking perspective. 2. Methods 2.1 Research data The GBD 2019 synthesized and examined data sourced from literature, surveys, and epidemiological studies. This comprehensive research was conducted by a team of over 3600 researchers from more than 145 countries. The study encompasses a wide range of information, including incidence, mortality, DALY, and other relevant metrics for more than 350 diseases in 204 global regions and countries. The foundation of this study is the publicly accessible database of GBD 2019, which is a secondary data source and, thus, did not require ethical approval [ 6 , 7 ]. The Socio-demographic Index (SDI) is a comprehensive indicator that captures various factors including per capita income, educational attainment, and fertility rates. It categorizes 204 countries worldwide into five distinct groups based on their SDI levels: low, low-middle, middle, high-middle, or high. Liver cancer classification is defined by the International Statistical Classification of Diseases and Related Health Problems (ICD-10 and ICD-9) utilizing specific codes (C22–C22.8 and D13.4 for ICD-10, and 155–155.1, 155.3, 155.9, and 211.5 for ICD-9). Notable risk factors for liver cancer consist of alcohol consumption and viral infections. The excessive and prolonged consumption of alcohol as well as specific viral infections, such as hepatitis B and C, significantly increase the likelihood of developing liver cancer. Understanding these risk factors is vital as they have a substantial impact on the incidence and mortality rates of liver cancer, particularly among young adults all over the world [ 8 , 9 ]. 2.2 Statistical analysis In this analysis, we employed age-standardized metrics to evaluate the impact of liver cancer on the global young adult population. We calculated ASIRs, age-standardized death rates (ASDRs), and age-standardized DALY rates. To assess trends in liver cancer within this demographic, we used EAPCs [ 10 , 11 ]. For quantifying the liver cancer burden, we derived age-standardized rates and their confidence intervals (CIs) using the World Health Organization's global standards spanning from 2000 to 2025: $$\frac{{\sum }_{i=1}^{A}{a}_{iwi}}{{\sum }_{i=1}^{A}{W}^{i}}$$ The variable "a i " represents the rate specific to the i th age group, while the variable "w i " represents the weight assigned to the i th age group in the chosen reference standard population. Age standardization is a critical technique used to mitigate the impact of differing age distributions in various populations, ultimately improving the comparability of research metrics. This method entails the computation of standardized or age-adjusted rates, which essentially function as weighted averages of age-specific rates across the populations being investigated. The weights, also known as standards, correspond to the relative age distribution of a reference population, allowing for the generation of a summarized rate for each group being compared. These standardized rates depict the anticipated number of events (e.g., incidence or mortality) that would occur if the populations being compared possessed identical age distributions. The average annual percentage change (AAPC) is an essential quantitative measure used to evaluate the average annual variation in age-standardized rates during a specific period. The calculation of AAPCs involves fitting the natural logarithm of time variables against their corresponding values, ensuring equal contribution from each data point in the analysis. AAPC is particularly effective in determining long-term trends in essential disease burden metrics such as incidence and mortality rates. In our analytical model, we established a relationship between the natural logarithm (ln) of the age-standardized rate (ASIR) and time using the formula: y = b0 + βx + c. In this formula, y represents ln (ASIR), x represents the calendar year, b0 is a constant, c is the error term, and β indicates the direction (negative or positive) of the trend in the chosen age-standardized rate. To calculate the annual percent change (EAPC), we used the formula: EAPC = 100 × (exp[β] − 1). We also derived the 95% confidence interval (CI) for the EAPC from the linear regression model. The interpretation of the estimated annual percent change (EAPC) and its 95% confidence interval (CI) adheres to specific criteria. A positive EAPC, demonstrated by a lower limit above 0 in the 95% CI, suggests an increasing trend. Conversely, a negative EAPC, indicated by an upper limit below 0 in the 95% CI, indicates a decreasing trend. In cases where these criteria are not met, the rate is considered stable, implying no significant change over the specified period [ 12 , 13 ]. 3. Results 3.1 Trends in the burdens of liver cancer in young adults worldwide from 1990 to 2019 From 1990 to 2019, there was an overall decrease in the burden of liver cancer among young adults worldwide. Specifically, the ASIR of liver cancer decreased from 3.73 in 1990 to 1.92 in 2019, the ASDR decreased from 3.34 in 1990 to 1.48 in 2019, and the age-standardized DALY rate decreased from 160.70 in 1990 to 71.10 in 2019. Therefore, throughout this period, the overall burden of liver cancer in young adults worldwide gradually decreased (Tables 1 – 3 , Fig. 1 ). Furthermore, the largest decreases in the ASIR, ASDR, and age-standardized DALY rate among young adults worldwide were observed for liver cancer caused by hepatitis B, with an estimated annual percent change (EAPC) of -3.82 (95% CI: -4.47, -3.17) in the ASIR, -4.37 (95% CI: -5.04, -3.69) in the ASDR, and − 4.37 (95% CI: -5.03, -3.71) in the age-standardized DALY rate (Tables 1 – 3 , Fig. 1 ). Table 1 The age-standardized incidence rate of global liver cancer burden of young adults due to alcohol use, hepatitis B and hepatitis C from 1990 to 2019 in different regions. 1990 2019 1990–2019 age-standardized incidence rate(per 100000) age-standardized incidence rate(per 100000) EAPC location No.(95%UI) Male/Female No.(95%UI) Male/Female No.(95%CI) global liver cancer 3.73(3.71,3.76) 3.44 1.92(1.90,1.93) 3.75 -3.47(-4.06,-2.87) Liver cancer due to alcohol use 0.27(0.26,0.27) 3.31 0.20(0.20,0.21) 4.26 -1.69(-2.00,-1.37) Liver cancer due to hepatitis B 2.78(2.76,2.80) 5.22 1.31(1.30,1.32) 6.08 -3.82(-4.47,-3.17) Liver cancer due to hepatitis C 0.28(0.27,0.29) 1.16 0.17(0.17,0.17) 1.31 -2.61(-3.02,-2.20) Sociodemographic index High-middle SDI liver cancer 4.45(4.39,4.51) 4.32 2.04(2.01,2.08) 4.93 -4.17(-4.90,-3.44) Liver cancer due to alcohol use 0.29(0.27,0.30) 3.47 0.18(0.18,0.19) 4.35 -2.46(-2.93,-1.98) Liver cancer due to hepatitis B 3.42(3.37,3.47) 6.88 1.49(1.47,1.52) 8.25 -4.43(-5.20,-3.65) Liver cancer due to hepatitis C 0.29(0.28,0.31) 1.12 0.15(0.14,0.16) 1.48 -3.44(-4.02,-2.86) High SDI liver cancer 1.21(1.18,1.25) 3.77 1.37(1.34,1.40) 3.02 0.07(-0.49,0.62) Liver cancer due to alcohol use 0.22(0.20,0.23) 6.43 0.28(0.27,0.30) 5.70 0.63(0.15,1.12) Liver cancer due to hepatitis B 0.62(0.59,0.64) 5.36 0.69(0.67,0.71) 4.61 0.04(-0.67,0.75) Liver cancer due to hepatitis C 0.24(0.22,0.25) 2.57 0.21(0.19,0.22) 1.49 -0.97(-1.27,-0.68) Low-middle SDI liver cancer 1.94(1.90,1.98) 2.40 1.14(1.12,1.17) 2.22 -2.74(-3.18,-2.29) Liver cancer due to alcohol use 0.17(0.15,0.18) 2.58 0.15(0.14,0.16) 3.04 -0.90(-1.17,-0.63) Liver cancer due to hepatitis B 1.39(1.36,1.43) 3.66 0.72(0.70,0.74) 3.55 -3.29(-3.79,-2.80) Liver cancer due to hepatitis C 0.14(0.13,0.16) 0.62 0.11(0.11,0.12) 0.64 -1.31(-1.56,-1.07) Low SDI liver cancer 1.05(1.00,1.10) 1.45 1.01(0.98,1.04) 1.53 -0.25(-0.31,-0.20) Liver cancer due to alcohol use 0.14(0.12,0.16) 2.79 0.14(0.13,0.15) 2.99 -0.05(-0.13,0.02) Liver cancer due to hepatitis B 0.61(0.58,0.65) 1.96 0.57(0.54,0.59) 2.10 -0.39(-0.45,-0.32) Liver cancer due to hepatitis C 0.14(0.12,0.16) 0.64 0.14(0.12,0.15) 0.71 -0.22(-0.26,-0.18) Middle SDI liver cancer 6.51(6.45,6.57) 3.37 2.82(2.79,2.85) 4.72 -4.13(-4.88,-3.37) Liver cancer due to alcohol use 0.38(0.36,0.39) 2.84 0.23(0.22,0.24) 4.59 -2.62(-3.15,-2.08) Liver cancer due to hepatitis B 5.01(4.96,5.06) 5.03 2.07(2.04,2.09) 7.51 -4.34(-5.13,-3.55) Liver cancer due to hepatitis C 0.42(0.40,0.43) 1.06 0.21(0.20,0.22) 1.67 -3.37(-3.95,-2.79) Region (overall liver cancer) Andean Latin America 1.15(0.99,1.34) 1.16 0.62(0.54,0.71) 1.23 -2.73(-3.10,-2.36) Australasia 0.50(0.38,0.65) 2.75 0.99(0.84,1.17) 2.58 2.69(2.32,3.06) Caribbean 1.31(1.13,1.50) 1.43 0.76(0.65,0.88) 1.66 -2.09(-2.90,-1.27) Central Asia 0.68(0.57,0.79) 2.40 1.83(1.71,1.96) 2.03 2.58(2.03,3.13) Central Europe 0.98(0.90,1.06) 1.75 0.56(0.50,0.62) 2.02 -1.87(-2.13,-1.60) Central Latin America 0.67(0.61,0.74) 1.08 0.53(0.49,0.57) 1.28 -0.82(-1.26,-0.38) Central sub-Saharan Africa 0.67(0.55,0.80) 0.97 0.59(0.53,0.67) 0.98 -0.53(-0.58,-0.48) East Asia 12.16(12.07,12.25) 3.71 4.96(4.91,5.00) 6.06 -4.76(-5.67,-3.83) Eastern Europe 0.36(0.33,0.40) 1.86 0.78(0.73,0.84) 2.48 2.95(2.57,3.33) Eastern Sub-Saharan Africa 0.74(0.67,0.81) 0.97 0.74(0.70,0.79) 1.23 -0.26(-0.40,-0.13) High-income Asia Pacific 2.62(2.52,2.72) 5.19 2.81(2.71,2.91) 4.25 0.04(-0.81,0.88) High-income North America 0.57(0.53,0.61) 2.46 1.00(0.96,1.05) 2.70 1.43(0.96,1.91) North Africa and Middle East 1.33(1.27,1.40) 1.92 1.25(1.21,1.28) 1.64 -0.13(-0.23,-0.04) Oceania 1.01(0.65,1.50) 1.76 0.77(0.56,1.03) 2.20 -0.73(-0.80,-0.66) South Asia 0.71(0.68,0.73) 1.80 0.70(0.68,0.72) 1.61 -0.12(-0.20,-0.05) Southeast Asia 2.03(1.97,2.10) 2.91 1.67(1.63,1.71) 3.36 -1.00(-1.13,-0.88) Southern Latin America 0.27(0.20,0.34) 1.51 0.32(0.26,0.38) 1.69 1.04(0.87,1.21) Southern sub-Saharan Africa 2.66(2.44,2.90) 1.79 2.65(2.50,2.82) 2.89 -0.77(-1.36,-0.17) Tropical Latin America 0.47(0.41,0.52) 1.48 0.43(0.39,0.46) 1.70 -0.13(-0.26,0.00) Western Europe 0.60(0.56,0.63) 2.22 0.97(0.93,1.01) 2.39 1.73(1.40,2.06) Western sub-Saharan Africa 1.43(1.34,1.53) 2.19 1.21(1.15,1.26) 2.55 -0.87(-1.02,-0.73) Table 2 The age-standardized death rate of global liver cancer burden of young adults due to alcohol use, hepatitis B and hepatitis C from 1990 to 2019 in different regions. 1990 2019 1990–2019 age-standardized death rate(per 100000) age-standardized death rate(per 100000) EAPC location No.(95%UI) Male/Female No.(95%UI) Male/Female No.(95%CI) global liver cancer 3.34(3.32,3.37) 3.49 1.48(1.47,1.49) 3.74 -3.99(-4.62,-3.36) Liver cancer due to alcohol use 0.24(0.23,0.24) 3.26 0.16(0.15,0.16) 4.15 -2.15(-2.52,-1.79) Liver cancer due to hepatitis B 2.50(2.48,2.52) 5.30 1.01(1.00,1.02) 6.06 -4.37(-5.04,-3.69) Liver cancer due to hepatitis C 0.25(0.24,0.25) 1.13 0.13(0.13,0.14) 1.28 -3.05(-3.52,-2.58) Sociodemographic index High-middle SDI liver cancer 3.99(3.94,4.05) 4.39 1.46(1.44,1.49) 4.92 -4.99(-5.74,-4.24) Liver cancer due to alcohol use 0.26(0.24,0.27) 3.46 0.14(0.13,0.15) 4.21 -3.15(-3.66,-2.63) Liver cancer due to hepatitis B 3.07(3.03,3.12) 7.00 1.07(1.04,1.09) 8.29 -5.26(-6.03,-4.48) Liver cancer due to hepatitis C 0.26(0.25,0.28) 1.12 0.11(0.10,0.12) 1.41 -4.31(-4.94,-3.66) High SDI liver cancer 0.93(0.90,0.95) 3.95 0.77(0.74,0.79) 3.12 -1.16(-1.72,-0.59) Liver cancer due to alcohol use 0.16(0.15,0.17) 6.43 0.16(0.15,0.17) 5.55 -0.47(-0.93,0.00) Liver cancer due to hepatitis B 0.49(0.47,0.51) 5.72 0.39(0.37,0.40) 5.00 -1.32(-2.04,-0.60) Liver cancer due to hepatitis C 0.17(0.16,0.19) 2.58 0.12(0.11,0.13) 1.45 -1.99(-2.31,-1.66) Low-middle SDI liver cancer 1.76(1.72,1.80) 2.43 1.01(0.99,1.03) 2.24 -2.80(-3.26,-2.34) Liver cancer due to alcohol use 0.15(0.14,0.17) 2.59 0.14(0.13,0.14) 3.06 -0.94(-1.22,-0.65) Liver cancer due to hepatitis B 1.26(1.23,1.30) 3.71 0.63(0.62,0.65) 3.58 -3.37(-3.88,-2.86) Liver cancer due to hepatitis C 0.13(0.12,0.14) 0.62 0.10(0.10,0.11) 0.65 -1.33(-1.59,-1.08) Low SDI liver cancer 0.94(0.90,0.99) 1.44 0.91(0.88,0.93) 1.53 -0.24(-0.30,-0.19) Liver cancer due to alcohol use 0.13(0.11,0.14) 2.77 0.13(0.12,0.14) 2.98 -0.04(-0.12,0.03) Liver cancer due to hepatitis B 0.55(0.51,0.58) 1.94 0.51(0.49,0.53) 2.09 -0.38(-0.44,-0.31) Liver cancer due to hepatitis C 0.13(0.11,0.15) 0.64 0.13(0.11,0.14) 0.71 -0.22(-0.26,-0.17) Middle SDI liver cancer 5.92(5.86,5.98) 3.41 2.25(2.23,2.28) 4.85 -4.55(-5.30,-3.79) Liver cancer due to alcohol use 0.35(0.33,0.36) 2.85 0.19(0.19,0.20) 4.73 -2.92(-3.45,-2.38) Liver cancer due to hepatitis B 4.56(4.51,4.61) 5.09 1.64(1.61,1.66) 7.68 -4.79(-5.58,-4.00) Liver cancer due to hepatitis C 0.39(0.37,0.40) 1.06 0.18(0.17,0.18) 1.76 -3.66(-4.24,-3.07) Region(overall liver cancer) Andean Latin America 1.02(0.87,1.20) 1.15 0.53(0.45,0.61) 1.22 -2.89(-3.29,-2.49) Australasia 0.39(0.28,0.53) 2.75 0.64(0.52,0.78) 2.30 2.00(1.73,2.28) Caribbean 1.16(1.00,1.35) 1.45 0.66(0.56,0.77) 1.69 -2.20(-3.05,-1.34) Central Asia 0.62(0.52,0.73) 2.43 1.65(1.54,1.77) 2.05 2.63(2.07,3.19) Central Europe 0.87(0.80,0.95) 1.76 0.47(0.42,0.53) 2.01 -2.11(-2.40,-1.82) Central Latin America 0.60(0.54,0.66) 1.08 0.45(0.42,0.49) 1.30 -1.07(-1.52,-0.61) Central sub-Saharan Africa 0.59(0.48,0.72) 0.93 0.53(0.46,0.60) 0.95 -0.52(-0.58,-0.47) East Asia 11.03(10.95,11.12) 3.75 3.74(3.70,3.78) 6.16 -5.38(-6.30,-4.45) Eastern Europe 0.32(0.29,0.36) 1.89 0.67(0.62,0.72) 2.52 2.93(2.50,3.36) Eastern Sub-Saharan Africa 0.66(0.59,0.73) 0.95 0.67(0.63,0.72) 1.21 -0.14(-0.27,-0.01) High-income Asia Pacific 1.95(1.87,2.04) 5.70 1.43(1.36,1.51) 4.85 -1.46(-2.41,-0.50) High-income North America 0.40(0.37,0.44) 2.35 0.58(0.54,0.61) 2.42 0.72(0.29,1.16) North Africa and Middle East 1.21(1.15,1.27) 1.99 1.03(1.00,1.07) 2.04 -0.45(-0.52,-0.39) Oceania 0.91(0.57,1.38) 1.79 0.68(0.49,0.93) 2.27 -0.76(-0.84,-0.69) South Asia 0.64(0.61,0.66) 1.83 0.62(0.60,0.64) 1.64 -0.15(-0.24,-0.06) Southeast Asia 1.84(1.78,1.91) 2.96 1.43(1.39,1.47) 3.53 -1.18(-1.31,-1.04) Southern Latin America 0.23(0.18,0.31) 1.53 0.25(0.20,0.31) 1.75 0.75(0.58,0.92) Southern sub-Saharan Africa 2.39(2.18,2.61) 1.83 2.36(2.21,2.51) 2.94 -0.76(-1.33,-0.18) Tropical Latin America 0.42(0.37,0.47) 1.49 0.37(0.33,0.40) 1.74 -0.25(-0.38,-0.11) Western Europe 0.43(0.41,0.46) 2.25 0.51(0.48,0.54) 2.32 0.48(0.23,0.73) Western sub-Saharan Africa 1.28(1.19,1.37) 2.15 1.09(1.04,1.14) 2.53 -0.86(-1.03,-0.70) Table 3 The age-standardized DALY rate of global liver cancer burden of young adults due to alcohol use, hepatitis B and hepatitis C from 1990 to 2019 in different regions. 1990 2019 1990–2019 age-standardized DALY rate (per 100000) age-standardized DALY rate (per 100000) EAPC location No.(95%UI) Male/Female No.(95%UI) Male/Female No.(95%CI) global liver cancer 160.70(160.54,160.86) 3.44 71.10(71.02,71.19) 3.65 -4.00(-4.61,-3.38) Liver cancer due to alcohol use 10.90(10.85,10.94) 3.26 7.32(7.30,7.35) 4.10 -2.14(-2.50,-1.78) Liver cancer due to hepatitis B 120.64(120.50,120.78) 5.21 48.93(48.86,49.00) 5.88 -4.37(-5.03,-3.71) Liver cancer due to hepatitis C 11.35(11.31,11.40) 1.13 6.12(6.10,6.14) 1.27 -3.04(-3.51,-2.58) Sociodemographic index High-middle SDI liver cancer 191.21(190.84,191.58) 4.35 70.64(70.46,70.82) 4.84 -4.97(-5.71,-4.23) Liver cancer due to alcohol use 11.82(11.72,11.91) 3.49 6.39(6.34,6.44) 4.17 -3.13(-3.64,-2.61) Liver cancer due to hepatitis B 147.58(147.26,147.90) 6.89 51.75(51.60,51.91) 8.10 -5.23(-5.99,-4.46) Liver cancer due to hepatitis C 11.99(11.89,12.08) 1.12 4.96(4.91,5.00) 1.40 -4.31(-4.95,-3.67) High SDI liver cancer 43.89(43.70,44.09) 3.86 36.50(36.34,36.66) 3.01 -1.14(-1.68,-0.59) Liver cancer due to alcohol use 7.47(7.39,7.55) 6.51 7.39(7.32,7.46) 5.46 -0.44(-0.89,0.01) Liver cancer due to hepatitis B 23.45(23.31,23.59) 5.58 18.50(18.39,18.62) 4.76 -1.35(-2.05,-0.65) Liver cancer due to hepatitis C 7.79(7.71,7.87) 2.58 5.30(5.24,5.36) 1.43 -1.93(-2.24,-1.61) Low-middle SDI liver cancer 84.77(84.49,85.04) 2.41 48.85(48.70,48.99) 2.18 -2.81(-3.26,-2.35) Liver cancer due to alcohol use 7.15(7.06,7.23) 2.62 6.32(6.27,6.38) 3.01 -0.93(-1.21,-0.65) Liver cancer due to hepatitis B 61.14(60.91,61.37) 3.67 30.74(30.62,30.85) 3.47 -3.38(-3.88,-2.88) Liver cancer due to hepatitis C 6.08(6.01,6.16) 0.63 4.78(4.74,4.83) 0.64 -1.33(-1.58,-1.07) Low SDI liver cancer 45.59(45.28,45.90) 1.43 44.03(43.83,44.23) 1.50 -0.24(-0.30,-0.18) Liver cancer due to alcohol use 5.80(5.69,5.92) 2.82 5.96(5.88,6.03) 2.93 -0.03(-0.11,0.05) Liver cancer due to hepatitis B 26.70(26.46,26.93) 1.94 24.92(24.77,25.07) 2.06 -0.37(-0.43,-0.30) Liver cancer due to hepatitis C 6.03(5.92,6.15) 0.64 5.76(5.68,5.83) 0.70 -0.21(-0.26,-0.17) Middle SDI liver cancer 283.73(283.34,284.12) 3.38 107.82(107.64,107.99) 4.77 -4.55(-5.29,-3.81) Liver cancer due to alcohol use 15.97(15.87,16.06) 2.88 8.90(8.85,8.95) 4.72 -2.91(-3.43,-2.38) Liver cancer due to hepatitis B 219.20(218.86,219.54) 5.03 78.62(78.47,78.77) 7.53 -4.80(-5.57,-4.02) Liver cancer due to hepatitis C 17.64(17.54,17.74) 1.07 8.10(8.05,8.15) 1.75 -3.66(-4.24,-3.07) Region(overall liver cancer) Andean Latin America 50.77(49.65,51.92) 1.17 26.54(25.98,27.10) 1.26 -2.84(-3.23,-2.45) Australasia 18.88(18.08,19.72) 2.68 30.65(29.78,31.54) 2.25 1.94(1.68,2.21) Caribbean 56.15(54.97,57.35) 1.44 32.37(31.65,33.09) 1.67 -2.13(-2.97,-1.28) Central Asia 28.76(28.07,29.46) 2.34 78.63(77.83,79.42) 1.99 2.75(2.19,3.32) Central Europe 41.82(41.31,42.33) 1.73 22.50(22.13,22.87) 1.97 -2.11(-2.40,-1.83) Central Latin America 29.18(28.76,29.60) 1.10 22.14(21.89,22.40) 1.31 -1.05(-1.51,-0.59) Central sub-Saharan Africa 28.88(28.10,29.67) 0.95 25.96(25.51,26.41) 0.97 -0.50(-0.55,-0.45) East Asia 527.44(526.85,528.04) 3.71 180.62(180.34,180.90) 6.09 -5.35(-6.26,-4.42) Eastern Europe 15.64(15.40,15.87) 1.83 32.60(32.27,32.94) 2.45 2.88(2.47,3.30) Eastern Sub-Saharan Africa 31.78(31.33,32.23) 0.94 32.83(32.54,33.12) 1.20 -0.12(-0.25,0.01) High-income Asia Pacific 91.06(90.47,91.65) 5.46 67.05(66.56,67.54) 4.61 -1.47(-2.41,-0.51) High-income North America 19.49(19.27,19.71) 2.29 27.66(27.42,27.90) 2.35 0.73(0.33,1.13) North Africa and Middle East 57.14(56.72,57.56) 1.93 49.07(48.83,49.31) 1.98 -0.44(-0.51,-0.37) Oceania 43.71(41.15,46.40) 1.73 33.06(31.63,34.54) 2.18 -0.77(-0.84,-0.70) South Asia 31.20(31.04,31.36) 1.77 30.40(30.29,30.52) 1.58 -0.16(-0.25,-0.07) Southeast Asia 88.98(88.56,89.41) 2.92 68.96(68.69,69.22) 3.46 -1.21(-1.35,-1.07) Southern Latin America 11.20(10.78,11.64) 1.50 12.18(11.82,12.55) 1.74 0.75(0.58,0.91) Southern sub-Saharan Africa 118.75(117.26,120.25) 1.78 116.86(115.80,117.92) 2.93 -0.77(-1.36,-0.18) Tropical Latin America 20.24(19.90,20.59) 1.49 17.88(17.65,18.12) 1.72 -0.22(-0.35,-0.10) Western Europe 20.89(20.70,21.09) 2.19 24.54(24.33,24.74) 2.26 0.48(0.24,0.71) Western sub-Saharan Africa 62.31(61.71,62.92) 2.13 52.70(52.36,53.05) 2.48 -0.88(-1.04,-0.71) 3.2 Age distribution of liver cancer in young adults worldwide in 2019 In 2019, the global disease burden of liver cancer in young adults exhibited an increase with age. We classified 204 countries into four categories according to age-standardized rates, ranging from low to high, and subsequently generated a heatmap based on age groups. Our analysis revealed that the overall burden of liver cancer remained relatively stable among individuals aged 15–34, experienced a significant increase in those aged 35–49, and reached its highest point among individuals aged 45–49 (Tables S4-6, Fig. 2 ). In 2019, a comprehensive analysis indicated that the burden of liver cancer varied across different age groups and countries (Tables S4–6, Fig. 3 ). Specifically, the youngest age group in nearly all countries exhibited a lower burden of this disease, while the burden increased with age. In Mongolia, individuals aged 45–49 accounted for the highest proportion of ASIR, ASDR, and age-standardized DALY rate. Conversely, in Cambodia, this age group represented the lowest proportion of these indicators. Remarkably, the average values of these three indicators among individuals aged 45–49 were found to constitute at least 50% of the corresponding values across all age groups globally (Tables S4–6, Figure S1 ). 3.3 Gender distribution of burdens of liver cancer in young adults worldwide from 1990 to 2019 From 1990 to 2019, there was a decrease in the overall burden of liver cancer in young adults globally. However, during the same period, it was observed that the growth trend in the ASIRs, ASDRs, and age-standardized DALY rates of liver cancer in young adults indicated a higher burden in men compared to women. In 2019, the male-to-female ratios for ASIR, ASDR, and age-standardized DALY rates of liver cancer in young adults were 3.75, 3.74, and 3.65, respectively, as presented in Tables 1 – 3 and Figure S2. 3.4 Distribution of the disease burden of liver cancer in different regions and countries worldwide from 1990 to 2019 In 2019, the highest ASIR for overall liver cancer among young adults in 21 geographical regions worldwide was observed in Southern sub-Saharan Africa (2.65), followed by High-income Asia Pacific (2.81) and East Asia (4.96). Conversely, the lowest ASIR was found in Southern Latin America (0.32), followed by Tropical Latin America (0.43) and Central Latin America (0.53). Between 1990 and 2019, the ASIR for overall liver cancer in young adults experienced the greatest increase in Eastern sub-Saharan Africa (EAPC:2.52), Australasia (EAPC:2.84), and Central Asia (EAPC:5.44). On the other hand, the least increase was observed in Central Europe (EAPC:0.60), East Asia (EAPC:0.65), and the Caribbean (EAPC:0.91) (Table S8). In 2019, the regions with the highest ASDR for overall liver cancer in young adults were Central Asia (ASDR: 1.65), followed by Southern sub-Saharan Africa (ASDR: 2.36) and East Asia (ASDR: 3.74). On the other hand, the regions with the lowest ASDR were Southern Latin America (ASDR: 0.25), Tropical Latin America (ASDR: 0.37), and Central Latin America (ASDR: 0.45). From 1990 to 2019, the regions that experienced the greatest increase in ASDR for overall liver cancer in young adults were Central sub-Saharan Africa (EAPC: 2.41), Eastern sub-Saharan Africa (EAPC: 2.57), and Central Asia (EAPC: 5.40). In contrast, the regions with the smallest increase in ASDR were East Asia (EAPC: 0.55), Central Europe (EAPC: 0.57), and High-income Asia Pacific (EAPC: 0.83) (Table A8). In 2019, the highest age-standardized DALY rate for overall liver cancer among young adults in 21 geographical regions worldwide was observed in East Asia (180.62), followed by Central Asia (78.63) and Southern sub-Saharan Africa (116.86). Conversely, the lowest age-standardized DALY rate was reported in Southern Latin America (12.18), followed by Tropical Latin America (17.88) and Central Latin America (22.14). Between 1990 and 2019, the age-standardized DALY rate for overall liver cancer in young adults showed the most significant increase in Australasia (EAPC: 1.94), Central Asia (EAPC: 2.75), and Eastern Europe (EAPC: 2.88). On the other hand, the rate decreased the most in East Asia (EAPC: -5.35), Andean Latin America (EAPC: -2.84), and Caribbean (EAPC: -2.13) based on Tables 1 – 3 and Table S8. From 1990 to 2019, there were notable variations in the age-standardized DALY rate for liver cancer among young adults across different regions of the world, as reported by the EAPC. The regions with the largest increases in this rate were Eastern Europe (EAPC: 2.14), Australia (EAPC: 2.50), and Central Asia (EAPC: 3.49). However, when looking specifically at men, the largest increases were observed in Australasia (EAPC: 1.77), Central Asia (EAPC: 2.39), and Eastern Europe (EAPC: 3.26). Moreover, the burden of disease from liver cancer in Eastern Europe varied between men and women, as detailed in Table S8. Between 1990 and 2019, the ASIR for liver cancer in young adults showed a significant increase in various countries across the globe. The countries with the highest increase in ASIR for overall liver cancer were Turkmenistan (EAPC: 9.59), Armenia (EAPC: 9.84), and Uzbekistan (EAPC: 10.80). On the other hand, Saint Kitts and Nevis (EAPC: -6.20), Cuba (EAPC: -5.81), and China (EAPC: -4.81) demonstrated the most substantial decrease in ASIR for overall liver cancer during the same time period (Table S7, Figure S3). 3.5 Relationship between the disease burden and SDI of liver cancer in young adults worldwide from 1990 to 2019 The burden of liver cancer among young adults worldwide in 2019 varied based on the SDI of the regions. Specifically, the ASIR was highest (2.82) in middle-SDI regions and lowest (1.01) in low-SDI regions. Similarly, the ASDR and age-standardized DALY rates were highest in middle-SDI regions (ASDR: 2.25; DALY: 107.82) and lowest in high-SDI regions (ASDR: 0.77; DALY: 36.50). From 1990 to 2019, the burden of overall liver cancer in young adults worldwide, as measured by ASIR, ASDR, and age-standardized DALY rate, exhibited varying trends based on the countries' SDIs. Analysis of the burden trends for each country using regression revealed a consistent pattern. As the SDIs changed from 0 to 1, the burden generally decreased from large to small and then stabilized. Notably, low-SDI countries had the highest burden, surpassing the global average disease burden, albeit being few in number. Additionally, with an increase in SDI from 0 to approximately 0.25, the burden experienced a decreasing trend. Between an SDI of 0.25 and 0.75, the burden remained relatively stable. However, for an SDI above 0.75, the burden initially decreased and then reversed, showing an upward trajectory. Consequently, countries with SDIs around 0.80 exhibited lower burdens compared to those with SDIs below 0.80. Conversely, countries with SDIs exceeding 0.80 experienced higher burdens. These findings are summarized in Tables 1 – 3 , Tables S1-S3, and Figure S4. 3.6 Prediction of burdens of liver cancer in young adults worldwide from 2020 to 2030 Data from the years 1990 to 2019 were utilized for fitting a Generalized Additive Model (GAM), allowing us to project changes in the global burden of liver cancer in young adults from 2020 to 2030. Specifically, we initially fitted trends in various measures including the incidence number, incidence rate, death number, death rate, DALY number, and DALY rate for different age groups during the aforementioned time period. This analysis revealed a notable pattern: the overall burden for each age group initially increased between 1990 and 2000, reached a peak between 1995 and 2000, followed by a decrease, another peak between 2005 and 2010, and finally an increase thereafter (Tables 1 – 3 , Tables S1–3, Figure S5). We conducted predictions on burdens for each age group from 2020 to 2030, and observed a consistent pattern in the overall indicators. Specifically, between the years 2020 and 2030, an increase in burden is projected for individuals aged 30–34 and 35–39, while a decrease is anticipated for other age groups, with the exception of those aged 20–24 where it is expected to remain relatively stable. Consequently, it is imperative for public health efforts to concentrate on addressing the disease burden specifically among individuals aged 30–40 (Figure S5). We utilized GAMs to generate predictions regarding the future burden of liver cancer in young men and women between 2020 and 2030. Our findings indicate a decrease in the overall burden of liver cancer during this period. Nevertheless, it is important to note that the age-standardized DALY rate of liver cancer attributed to alcohol use is projected to experience a substantial increase in both young men and women. Specifically, both the ASIR and ASDR are predicted to rise significantly. In the absence of an effective intervention, our predictions suggest that by 2030, the ASIR of liver cancer caused by alcohol use will be 1.1 times higher than the rate observed in 2005. This highlights the urgent need to prioritize prevention and treatment efforts targeted at this particular type of liver cancer among young adults worldwide (Figure S6). 4. Discussion In this comprehensive analysis of the global burden of liver cancer from 1990 to 2019, with a particular focus on young adults, the GBD 2019 data revealed a significant decrease in liver cancer cases in this demographic over the study period. This decline can be primarily attributed to the successful implementation of hepatitis B vaccines [ 14 ] and increased public health awareness, particularly regarding the associated risks of alcohol consumption [ 15 , 16 ]. Moreover, demographic changes, such as those observed in China, have also contributed to this trend, as younger cohorts exhibit a reduced risk of liver cancer, likely due to vaccination efforts [ 17 ]. However, it is important to note that concerns still persist in regions like Latin America, where lifestyle factors continue to heighten the risks of liver cancer [ 18 ]. The study reveals that the liver cancer burden has variations, not only with age but also geographically. Specifically, individuals aged 35–49 are particularly vulnerable due to factors such as prolonged alcohol use and viral infections. Moreover, there are disparities in liver cancer burden in countries like Mongolia and Cambodia, which can possibly be attributed to genetic, environmental, and lifestyle differences [ 19 ]. In a global context, men are more affected by liver cancer than women, possibly because of higher exposure to risk factors such as excessive alcohol use and occupational hazards, as well as less frequent health screenings [ 20 , 21 ]. This disparity emphasizes the importance of implementing gender-specific and culturally sensitive prevention and screening strategies [ 22 ]. The study uncovers notable variances in liver cancer burdens among different regions and genders. These disparities are shaped by factors such as environmental influences, advancements in medical technology, the adoption of screening programs, and cultural practices including alcohol consumption and smoking [ 23 , 24 ]. Regions classified as high-SDI typically demonstrate stronger capabilities in prevention, screening, and treatment, which ultimately contribute to lower liver cancer incidence rates. In contrast, low-SDI regions often lack accessible medical resources and advanced treatment technologies [ 25 , 26 ]. Using GAMs to project future trends based on data spanning from 1990 to 2019, our analysis suggests a potential increase in the burden of liver cancer, particularly among individuals aged 30–40. We identified lifestyle factors, such as dietary habits and work-life stress, as key contributors to this trend, as they are known to lead to unhealthy choices and excessive alcohol consumption. Although advancements in early cancer diagnosis have been significant, the effectiveness of treatments for advanced stages remains challenging. Additionally, our study predicts a surge in liver cancer incidence rates among young adults, which may be attributed to the growing prevalence of non-alcoholic steatohepatitis and the aging global population [ 27 ]. This study represents a pioneering effort in conducting a comprehensive examination of the global burden of liver cancer in young adults over a period of three decades. Although the findings provide valuable strategic information for various regions, certain limitations need to be acknowledged. Despite the high quality of the data from the Global Burden of Disease 2019 study, potential biases or inaccuracies cannot be disregarded. In addition, the study focuses extensively on factors such as hepatitis B infections and access to healthcare technologies, while other significant risk factors may not have received sufficient attention. 5. Conclusions In conclusion, our findings highlight a reduction in the burden of liver cancer among young adults, specifically cases related to hepatitis B. However, there is a growing burden as individuals age, particularly in the 35–49 age group, along with noticeable gender discrepancies and regional disparities. These findings underscore the need for intensified and targeted efforts aimed at specific risk groups. Abbreviations EAPCs Estimated annual percentage changes GAMs Generalized additive models ASIR Age-standardized incidence rate GBD Global Burden of Disease Study DALY Disability-adjusted life years SDI Socio-demographic Index ASDRs Age-standardized death rates CIs Confidence intervals AAPC Average annual percentage change Declarations Ethics approval and consent to participate The GBD study is based entirely on publicly available databases and does not require clinical ethics approval. Consent for publication Not applicable. Availability of data and materials All data generated or analysed during this study are included in this published article [and its supplementary information files]. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions Chenlu Fan contributed to the conceptualization and methodology of the study. Xin Zhang and Meichen Zhang was responsible for data curation, as well as the initial preparation of the original draft. Yanmei Yang contributed to the reviewing and editing of the manuscript. All authors have reviewed and approved the final version of the manuscript. Acknowledgements We thank all authors for their contributions to the article and the GBD collaborators. References Amini M, Looha MA, Zarean E, Pourhoseingholi MA. Global pattern of trends in incidence, mortality, and mortality-to-incidence ratio rates related to liver cancer, 1990–2019: a longitudinal analysis based on the global burden of disease study. BMC Public Health. 2022;22(1):604. Cao G, Liu J, Liu M, Global. Regional, and National Trends in Incidence and Mortality of Primary Liver Cancer and Its Underlying Etiologies from 1990 to 2019: Results from the Global Burden of Disease Study 2019. 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Int J Epidemiol. 2021;50(1):128–42. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3899212","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":270971123,"identity":"09f3d70e-d241-4b0b-aaeb-d9b4fc311763","order_by":0,"name":"Chenlu Fan","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chenlu","middleName":"","lastName":"Fan","suffix":""},{"id":270971124,"identity":"32159695-aa9c-442b-b069-6744b3af32c6","order_by":1,"name":"Xin Zhang","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Zhang","suffix":""},{"id":270971125,"identity":"c33ce6e6-3a62-4f19-a311-004a60679454","order_by":2,"name":"Meichen Zhang","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Meichen","middleName":"","lastName":"Zhang","suffix":""},{"id":270971126,"identity":"56c6eba3-ad60-47eb-946e-3552bb74727e","order_by":3,"name":"Yanmei Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYFADZuZjDIwNYKYBsVrY0kjVwsBjRpwWg+NnD7/mqbkTzc/O8+1x5Y5tiQ3szdskGGru4NZyJi/NmufYs9yZzbzbDc+euZ3YwHOsTILh2DPcWg7kmBnzsB3O3XCYd5tkYxtQi0SOmQRjw2HcWs6/AWr5dzh3/2GeZxAt8m8IaLmRY/yYtw1oCzMPG9QWHvxaJG+8MWOc23c4d8ZhNjPJxjO3jdt40ootEo7h1sJ3Psf4w5tvh3P7+w8DHbbjtmw/++GNNz7U4NaicICBTYoHWYQNRCTg1MDAIN/AwPzxBx4Fo2AUjIJRMAoYAJKkXMg2kiUOAAAAAElFTkSuQmCC","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yanmei","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2024-01-26 06:44:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3899212/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3899212/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50671553,"identity":"2e50dcd4-6f4b-4728-bc95-f53fee79632d","added_by":"auto","created_at":"2024-02-05 14:42:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":677871,"visible":true,"origin":"","legend":"\u003cp\u003eThe age standard rates of global liver cancer burden of young adults due to alcohol use, hepatitis B and hepatitis C, by Sex and Location. (A) ASDR in 1990 (B) ASDR in 2019 (C) age-standardized DALY rate in 1990 (D) age-standardized DALY rate in 2019 (E) ASIR in 1990 (F) ASIR in 2019. The left column is male group, the right column is female group. ASIR = age standardized incidence rate. ASDR = age standardized death rate.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3899212/v1/bf9dc0ea708d58dc600c9ab0.png"},{"id":50672489,"identity":"e918ad8e-3ccb-45d9-ae82-8737ec15e473","added_by":"auto","created_at":"2024-02-05 14:50:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":602585,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of rate for global liver cancer burden of young adults in 2019, by country and age group. (A) Incidence rate (B) DALY rate (C) death rate.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3899212/v1/a845f96ed32d2d288aa2c9e0.png"},{"id":50671555,"identity":"bbca5f5a-fee4-4d35-b878-9ff1da91044e","added_by":"auto","created_at":"2024-02-05 14:42:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":217328,"visible":true,"origin":"","legend":"\u003cp\u003eThe rate for global liver cancer burden of young adults in 2019, by top 30 country and age group. (A) Incidence rate (B) DALY rate (C) death rate.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3899212/v1/a76f84ff697b866e47c20d47.png"},{"id":67780947,"identity":"c91f5e2b-9e92-4e5f-946b-102b57c3d90b","added_by":"auto","created_at":"2024-10-29 15:54:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2864189,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3899212/v1/49499d99-df35-41ef-99db-6d8ac584e55a.pdf"},{"id":50671565,"identity":"f0dee64b-0c86-497b-b4ba-ff5e39a1a3cf","added_by":"auto","created_at":"2024-02-05 14:42:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5843085,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3899212/v1/d907a536eaeea23d2d036489.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Burdens of liver cancer in young adults worldwide from 1990 to 2019, and predictions from 2020 to 2030","fulltext":[{"header":"1. Background","content":"\u003cp\u003eHepatocellular carcinoma, also known as liver cancer, poses a significant challenge in the field of global health. It is not only one of the most common types of cancer worldwide, but it also has wide-ranging impacts beyond the realm of health, affecting the socio-economic well-being of nations. For instance, in 2018, liver cancer caused the death of 781,631 individuals and was diagnosed in approximately 841,080 people, with its incidence continuing to rise steadily [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These statistics highlight the significant economic and health burden associated with liver cancer, emphasizing the urgent need for comprehensive research on its underlying causes, risk factors, and, most importantly, prevention and treatment strategies.\u003c/p\u003e \u003cp\u003eThe onset of liver cancer can be attributed to various factors, but excessive alcohol consumption and viral infections are identified as the main controllable causes. In recent studies, a strong association has been established between alcohol intake, diseases like hepatitis B and C, and the development of liver cancer [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These findings indicate that long-term alcohol abuse and viral infections significantly increase the risk of liver cancer.\u003c/p\u003e \u003cp\u003eYoung adults play a critical role in the workforce and are vital to a nation's economic health. Their own health serves as a reflection of the nation's present and future well-being. The habits they adopt, such as their diet, exercise, medication usage, and mental well-being, often have long-lasting effects on their health outcomes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Given the significant impact of their well-being on global productivity, it is imperative that disease prevention and treatment for this demographic are prioritized. However, there is a concerning lack of research investigating the burden of liver cancer specifically in young adults, both on a global and national scale [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In response to this gap, this study aims to shed light on the burden and evolving trends of liver cancer among young adults worldwide. The findings from this study will provide valuable insights for stakeholders in order to develop effective prevention strategies [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDrawing on the Global Burden of Disease Study (GBD) 2019, this investigation examines various metrics related to liver cancer in young adults over a period of three decades (1990\u0026ndash;2019). These metrics include the global age-standardized incidence rate (ASIR), death rate, disability-adjusted life years (DALY) rate, and their estimated annual percentage changes (EAPCs). The analysis also explores the burdens associated with alcohol use, hepatitis B, and hepatitis C, tracking their trajectories over time. Additionally, using generalized additive models (GAMs), we forecast the future global trends in liver cancer burdens until 2030, providing a forward-looking perspective.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Research data\u003c/h2\u003e \u003cp\u003eThe GBD 2019 synthesized and examined data sourced from literature, surveys, and epidemiological studies. This comprehensive research was conducted by a team of over 3600 researchers from more than 145 countries. The study encompasses a wide range of information, including incidence, mortality, DALY, and other relevant metrics for more than 350 diseases in 204 global regions and countries. The foundation of this study is the publicly accessible database of GBD 2019, which is a secondary data source and, thus, did not require ethical approval [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Socio-demographic Index (SDI) is a comprehensive indicator that captures various factors including per capita income, educational attainment, and fertility rates. It categorizes 204 countries worldwide into five distinct groups based on their SDI levels: low, low-middle, middle, high-middle, or high.\u003c/p\u003e \u003cp\u003eLiver cancer classification is defined by the International Statistical Classification of Diseases and Related Health Problems (ICD-10 and ICD-9) utilizing specific codes (C22\u0026ndash;C22.8 and D13.4 for ICD-10, and 155\u0026ndash;155.1, 155.3, 155.9, and 211.5 for ICD-9). Notable risk factors for liver cancer consist of alcohol consumption and viral infections. The excessive and prolonged consumption of alcohol as well as specific viral infections, such as hepatitis B and C, significantly increase the likelihood of developing liver cancer. Understanding these risk factors is vital as they have a substantial impact on the incidence and mortality rates of liver cancer, particularly among young adults all over the world [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Statistical analysis\u003c/h2\u003e \u003cp\u003eIn this analysis, we employed age-standardized metrics to evaluate the impact of liver cancer on the global young adult population. We calculated ASIRs, age-standardized death rates (ASDRs), and age-standardized DALY rates. To assess trends in liver cancer within this demographic, we used EAPCs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor quantifying the liver cancer burden, we derived age-standardized rates and their confidence intervals (CIs) using the World Health Organization's global standards spanning from 2000 to 2025:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\frac{{\\sum }_{i=1}^{A}{a}_{iwi}}{{\\sum }_{i=1}^{A}{W}^{i}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe variable \"a\u003csub\u003ei\u003c/sub\u003e\" represents the rate specific to the i\u003csup\u003eth\u003c/sup\u003e age group, while the variable \"w\u003csub\u003ei\u003c/sub\u003e\" represents the weight assigned to the i\u003csup\u003eth\u003c/sup\u003e age group in the chosen reference standard population.\u003c/p\u003e \u003cp\u003eAge standardization is a critical technique used to mitigate the impact of differing age distributions in various populations, ultimately improving the comparability of research metrics. This method entails the computation of standardized or age-adjusted rates, which essentially function as weighted averages of age-specific rates across the populations being investigated. The weights, also known as standards, correspond to the relative age distribution of a reference population, allowing for the generation of a summarized rate for each group being compared. These standardized rates depict the anticipated number of events (e.g., incidence or mortality) that would occur if the populations being compared possessed identical age distributions.\u003c/p\u003e \u003cp\u003eThe average annual percentage change (AAPC) is an essential quantitative measure used to evaluate the average annual variation in age-standardized rates during a specific period. The calculation of AAPCs involves fitting the natural logarithm of time variables against their corresponding values, ensuring equal contribution from each data point in the analysis. AAPC is particularly effective in determining long-term trends in essential disease burden metrics such as incidence and mortality rates.\u003c/p\u003e \u003cp\u003eIn our analytical model, we established a relationship between the natural logarithm (ln) of the age-standardized rate (ASIR) and time using the formula: y\u0026thinsp;=\u0026thinsp;b0\u0026thinsp;+\u0026thinsp;βx\u0026thinsp;+\u0026thinsp;c. In this formula, y represents ln (ASIR), x represents the calendar year, b0 is a constant, c is the error term, and β indicates the direction (negative or positive) of the trend in the chosen age-standardized rate. To calculate the annual percent change (EAPC), we used the formula: EAPC\u0026thinsp;=\u0026thinsp;100 \u0026times; (exp[β]\u0026thinsp;\u0026minus;\u0026thinsp;1). We also derived the 95% confidence interval (CI) for the EAPC from the linear regression model.\u003c/p\u003e \u003cp\u003eThe interpretation of the estimated annual percent change (EAPC) and its 95% confidence interval (CI) adheres to specific criteria. A positive EAPC, demonstrated by a lower limit above 0 in the 95% CI, suggests an increasing trend. Conversely, a negative EAPC, indicated by an upper limit below 0 in the 95% CI, indicates a decreasing trend. In cases where these criteria are not met, the rate is considered stable, implying no significant change over the specified period [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Trends in the burdens of liver cancer in young adults worldwide from 1990 to 2019\u003c/h2\u003e \u003cp\u003eFrom 1990 to 2019, there was an overall decrease in the burden of liver cancer among young adults worldwide. Specifically, the ASIR of liver cancer decreased from 3.73 in 1990 to 1.92 in 2019, the ASDR decreased from 3.34 in 1990 to 1.48 in 2019, and the age-standardized DALY rate decreased from 160.70 in 1990 to 71.10 in 2019. Therefore, throughout this period, the overall burden of liver cancer in young adults worldwide gradually decreased (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, the largest decreases in the ASIR, ASDR, and age-standardized DALY rate among young adults worldwide were observed for liver cancer caused by hepatitis B, with an estimated annual percent change (EAPC) of -3.82 (95% CI: -4.47, -3.17) in the ASIR, -4.37 (95% CI: -5.04, -3.69) in the ASDR, and \u0026minus;\u0026thinsp;4.37 (95% CI: -5.03, -3.71) in the age-standardized DALY rate (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe age-standardized incidence rate of global liver cancer burden of young adults due to alcohol use, hepatitis B and hepatitis C from 1990 to 2019 in different regions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1990\u0026ndash;2019\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-standardized incidence rate(per 100000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eage-standardized incidence rate(per 100000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEAPC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.(95%UI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale/Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.(95%UI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale/Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.(95%CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglobal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.73(3.71,3.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.92(1.90,1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.47(-4.06,-2.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.27(0.26,0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20(0.20,0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.69(-2.00,-1.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.78(2.76,2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.31(1.30,1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.82(-4.47,-3.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28(0.27,0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17(0.17,0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.61(-3.02,-2.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.45(4.39,4.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.04(2.01,2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.17(-4.90,-3.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29(0.27,0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18(0.18,0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.46(-2.93,-1.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.42(3.37,3.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.49(1.47,1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.43(-5.20,-3.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29(0.28,0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15(0.14,0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.44(-4.02,-2.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.21(1.18,1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.37(1.34,1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07(-0.49,0.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22(0.20,0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28(0.27,0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.63(0.15,1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.62(0.59,0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69(0.67,0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04(-0.67,0.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24(0.22,0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21(0.19,0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.97(-1.27,-0.68)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.94(1.90,1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14(1.12,1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.74(-3.18,-2.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.17(0.15,0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15(0.14,0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.90(-1.17,-0.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39(1.36,1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72(0.70,0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.29(-3.79,-2.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14(0.13,0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11(0.11,0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.31(-1.56,-1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05(1.00,1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01(0.98,1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.25(-0.31,-0.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14(0.12,0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14(0.13,0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.05(-0.13,0.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.61(0.58,0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57(0.54,0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.39(-0.45,-0.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14(0.12,0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14(0.12,0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.22(-0.26,-0.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.51(6.45,6.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.82(2.79,2.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.13(-4.88,-3.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.38(0.36,0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23(0.22,0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.62(-3.15,-2.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.01(4.96,5.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.07(2.04,2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.34(-5.13,-3.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.42(0.40,0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21(0.20,0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.37(-3.95,-2.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion (overall liver cancer)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndean Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15(0.99,1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62(0.54,0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.73(-3.10,-2.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAustralasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50(0.38,0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99(0.84,1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.69(2.32,3.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaribbean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31(1.13,1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76(0.65,0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.09(-2.90,-1.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.68(0.57,0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.83(1.71,1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.58(2.03,3.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98(0.90,1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56(0.50,0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.87(-2.13,-1.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67(0.61,0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53(0.49,0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.82(-1.26,-0.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67(0.55,0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59(0.53,0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.53(-0.58,-0.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.16(12.07,12.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.96(4.91,5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.76(-5.67,-3.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.36(0.33,0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78(0.73,0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.95(2.57,3.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.74(0.67,0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74(0.70,0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.26(-0.40,-0.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income Asia Pacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.62(2.52,2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.81(2.71,2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04(-0.81,0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income North America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.57(0.53,0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.96,1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.43(0.96,1.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Africa and Middle East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.33(1.27,1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.25(1.21,1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.13(-0.23,-0.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOceania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01(0.65,1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77(0.56,1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.73(-0.80,-0.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.71(0.68,0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70(0.68,0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.12(-0.20,-0.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoutheast Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.03(1.97,2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.67(1.63,1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.00(-1.13,-0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.27(0.20,0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32(0.26,0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.04(0.87,1.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.66(2.44,2.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.65(2.50,2.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.77(-1.36,-0.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTropical Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.47(0.41,0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43(0.39,0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.13(-0.26,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60(0.56,0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97(0.93,1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.73(1.40,2.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.43(1.34,1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.21(1.15,1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.87(-1.02,-0.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe age-standardized death rate of global liver cancer burden of young adults due to alcohol use, hepatitis B and hepatitis C from 1990 to 2019 in different regions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1990\u0026ndash;2019\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-standardized death rate(per 100000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eage-standardized death rate(per 100000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEAPC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.(95%UI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale/Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.(95%UI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale/Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.(95%CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglobal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.34(3.32,3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48(1.47,1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.99(-4.62,-3.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24(0.23,0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16(0.15,0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.15(-2.52,-1.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.50(2.48,2.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01(1.00,1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.37(-5.04,-3.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25(0.24,0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13(0.13,0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.05(-3.52,-2.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.99(3.94,4.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.46(1.44,1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.99(-5.74,-4.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26(0.24,0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14(0.13,0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.15(-3.66,-2.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.07(3.03,3.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07(1.04,1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.26(-6.03,-4.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26(0.25,0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11(0.10,0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.31(-4.94,-3.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93(0.90,0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77(0.74,0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.16(-1.72,-0.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.16(0.15,0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16(0.15,0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.47(-0.93,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.49(0.47,0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39(0.37,0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.32(-2.04,-0.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.17(0.16,0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12(0.11,0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.99(-2.31,-1.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.76(1.72,1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01(0.99,1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.80(-3.26,-2.34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15(0.14,0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14(0.13,0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.94(-1.22,-0.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26(1.23,1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63(0.62,0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.37(-3.88,-2.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13(0.12,0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10(0.10,0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.33(-1.59,-1.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94(0.90,0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91(0.88,0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.24(-0.30,-0.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13(0.11,0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13(0.12,0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.04(-0.12,0.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.55(0.51,0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51(0.49,0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.38(-0.44,-0.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13(0.11,0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13(0.11,0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.22(-0.26,-0.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.92(5.86,5.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.25(2.23,2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.55(-5.30,-3.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.35(0.33,0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19(0.19,0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.92(-3.45,-2.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.56(4.51,4.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.64(1.61,1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.79(-5.58,-4.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.39(0.37,0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18(0.17,0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.66(-4.24,-3.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion(overall liver cancer)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndean Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02(0.87,1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53(0.45,0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.89(-3.29,-2.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAustralasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.39(0.28,0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64(0.52,0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.00(1.73,2.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaribbean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.16(1.00,1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66(0.56,0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.20(-3.05,-1.34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.62(0.52,0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.65(1.54,1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.63(2.07,3.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.87(0.80,0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47(0.42,0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.11(-2.40,-1.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60(0.54,0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45(0.42,0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.07(-1.52,-0.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59(0.48,0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53(0.46,0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.52(-0.58,-0.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.03(10.95,11.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.74(3.70,3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.38(-6.30,-4.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32(0.29,0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67(0.62,0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.93(2.50,3.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.66(0.59,0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67(0.63,0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.14(-0.27,-0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income Asia Pacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.95(1.87,2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43(1.36,1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.46(-2.41,-0.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income North America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.40(0.37,0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58(0.54,0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72(0.29,1.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Africa and Middle East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.21(1.15,1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03(1.00,1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.45(-0.52,-0.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOceania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91(0.57,1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68(0.49,0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.76(-0.84,-0.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.64(0.61,0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62(0.60,0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.15(-0.24,-0.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoutheast Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.84(1.78,1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43(1.39,1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.18(-1.31,-1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23(0.18,0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25(0.20,0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75(0.58,0.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.39(2.18,2.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.36(2.21,2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.76(-1.33,-0.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTropical Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.42(0.37,0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37(0.33,0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.25(-0.38,-0.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.43(0.41,0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51(0.48,0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48(0.23,0.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.28(1.19,1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09(1.04,1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.86(-1.03,-0.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe age-standardized DALY rate of global liver cancer burden of young adults due to alcohol use, hepatitis B and hepatitis C from 1990 to 2019 in different regions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1990\u0026ndash;2019\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-standardized DALY rate (per 100000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eage-standardized DALY rate (per 100000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEAPC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.(95%UI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale/Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.(95%UI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale/Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.(95%CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglobal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160.70(160.54,160.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.10(71.02,71.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.00(-4.61,-3.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.90(10.85,10.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.32(7.30,7.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.14(-2.50,-1.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120.64(120.50,120.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.93(48.86,49.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.37(-5.03,-3.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.35(11.31,11.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.12(6.10,6.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.04(-3.51,-2.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e191.21(190.84,191.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.64(70.46,70.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.97(-5.71,-4.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.82(11.72,11.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.39(6.34,6.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.13(-3.64,-2.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147.58(147.26,147.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.75(51.60,51.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.23(-5.99,-4.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.99(11.89,12.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.96(4.91,5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.31(-4.95,-3.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.89(43.70,44.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.50(36.34,36.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.14(-1.68,-0.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.47(7.39,7.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.39(7.32,7.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.44(-0.89,0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.45(23.31,23.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.50(18.39,18.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.35(-2.05,-0.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.79(7.71,7.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.30(5.24,5.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.93(-2.24,-1.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.77(84.49,85.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.85(48.70,48.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.81(-3.26,-2.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.15(7.06,7.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.32(6.27,6.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.93(-1.21,-0.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.14(60.91,61.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.74(30.62,30.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.38(-3.88,-2.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.08(6.01,6.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.78(4.74,4.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.33(-1.58,-1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.59(45.28,45.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.03(43.83,44.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.24(-0.30,-0.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.80(5.69,5.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.96(5.88,6.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.03(-0.11,0.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.70(26.46,26.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.92(24.77,25.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.37(-0.43,-0.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.03(5.92,6.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.76(5.68,5.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.21(-0.26,-0.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e283.73(283.34,284.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107.82(107.64,107.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.55(-5.29,-3.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to alcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.97(15.87,16.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.90(8.85,8.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.91(-3.43,-2.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e219.20(218.86,219.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.62(78.47,78.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.80(-5.57,-4.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer due to hepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.64(17.54,17.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.10(8.05,8.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.66(-4.24,-3.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion(overall liver cancer)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndean Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.77(49.65,51.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.54(25.98,27.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.84(-3.23,-2.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAustralasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.88(18.08,19.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.65(29.78,31.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.94(1.68,2.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaribbean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.15(54.97,57.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.37(31.65,33.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.13(-2.97,-1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.76(28.07,29.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.63(77.83,79.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.75(2.19,3.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.82(41.31,42.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.50(22.13,22.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.11(-2.40,-1.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.18(28.76,29.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.14(21.89,22.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.05(-1.51,-0.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.88(28.10,29.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.96(25.51,26.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.50(-0.55,-0.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e527.44(526.85,528.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e180.62(180.34,180.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.35(-6.26,-4.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.64(15.40,15.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.60(32.27,32.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.88(2.47,3.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.78(31.33,32.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.83(32.54,33.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.12(-0.25,0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income Asia Pacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.06(90.47,91.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.05(66.56,67.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.47(-2.41,-0.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income North America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.49(19.27,19.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.66(27.42,27.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.73(0.33,1.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Africa and Middle East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.14(56.72,57.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.07(48.83,49.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.44(-0.51,-0.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOceania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.71(41.15,46.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.06(31.63,34.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.77(-0.84,-0.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.20(31.04,31.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.40(30.29,30.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.16(-0.25,-0.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoutheast Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.98(88.56,89.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.96(68.69,69.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.21(-1.35,-1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.20(10.78,11.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.18(11.82,12.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75(0.58,0.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118.75(117.26,120.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116.86(115.80,117.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.77(-1.36,-0.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTropical Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.24(19.90,20.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.88(17.65,18.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.22(-0.35,-0.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.89(20.70,21.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.54(24.33,24.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48(0.24,0.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.31(61.71,62.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.70(52.36,53.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.88(-1.04,-0.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Age distribution of liver cancer in young adults worldwide in 2019\u003c/h2\u003e \u003cp\u003eIn 2019, the global disease burden of liver cancer in young adults exhibited an increase with age. We classified 204 countries into four categories according to age-standardized rates, ranging from low to high, and subsequently generated a heatmap based on age groups. Our analysis revealed that the overall burden of liver cancer remained relatively stable among individuals aged 15\u0026ndash;34, experienced a significant increase in those aged 35\u0026ndash;49, and reached its highest point among individuals aged 45\u0026ndash;49 (Tables S4-6, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn 2019, a comprehensive analysis indicated that the burden of liver cancer varied across different age groups and countries (Tables S4\u0026ndash;6, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Specifically, the youngest age group in nearly all countries exhibited a lower burden of this disease, while the burden increased with age. In Mongolia, individuals aged 45\u0026ndash;49 accounted for the highest proportion of ASIR, ASDR, and age-standardized DALY rate. Conversely, in Cambodia, this age group represented the lowest proportion of these indicators. Remarkably, the average values of these three indicators among individuals aged 45\u0026ndash;49 were found to constitute at least 50% of the corresponding values across all age groups globally (Tables S4\u0026ndash;6, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Gender distribution of burdens of liver cancer in young adults worldwide from 1990 to 2019\u003c/h2\u003e \u003cp\u003eFrom 1990 to 2019, there was a decrease in the overall burden of liver cancer in young adults globally. However, during the same period, it was observed that the growth trend in the ASIRs, ASDRs, and age-standardized DALY rates of liver cancer in young adults indicated a higher burden in men compared to women. In 2019, the male-to-female ratios for ASIR, ASDR, and age-standardized DALY rates of liver cancer in young adults were 3.75, 3.74, and 3.65, respectively, as presented in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Figure S2.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.4 Distribution of the disease burden of liver cancer in different regions and countries worldwide from 1990 to 2019\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn 2019, the highest ASIR for overall liver cancer among young adults in 21 geographical regions worldwide was observed in Southern sub-Saharan Africa (2.65), followed by High-income Asia Pacific (2.81) and East Asia (4.96). Conversely, the lowest ASIR was found in Southern Latin America (0.32), followed by Tropical Latin America (0.43) and Central Latin America (0.53). Between 1990 and 2019, the ASIR for overall liver cancer in young adults experienced the greatest increase in Eastern sub-Saharan Africa (EAPC:2.52), Australasia (EAPC:2.84), and Central Asia (EAPC:5.44). On the other hand, the least increase was observed in Central Europe (EAPC:0.60), East Asia (EAPC:0.65), and the Caribbean (EAPC:0.91) (Table S8).\u003c/p\u003e \u003cp\u003eIn 2019, the regions with the highest ASDR for overall liver cancer in young adults were Central Asia (ASDR: 1.65), followed by Southern sub-Saharan Africa (ASDR: 2.36) and East Asia (ASDR: 3.74). On the other hand, the regions with the lowest ASDR were Southern Latin America (ASDR: 0.25), Tropical Latin America (ASDR: 0.37), and Central Latin America (ASDR: 0.45). From 1990 to 2019, the regions that experienced the greatest increase in ASDR for overall liver cancer in young adults were Central sub-Saharan Africa (EAPC: 2.41), Eastern sub-Saharan Africa (EAPC: 2.57), and Central Asia (EAPC: 5.40). In contrast, the regions with the smallest increase in ASDR were East Asia (EAPC: 0.55), Central Europe (EAPC: 0.57), and High-income Asia Pacific (EAPC: 0.83) (Table A8).\u003c/p\u003e \u003cp\u003eIn 2019, the highest age-standardized DALY rate for overall liver cancer among young adults in 21 geographical regions worldwide was observed in East Asia (180.62), followed by Central Asia (78.63) and Southern sub-Saharan Africa (116.86). Conversely, the lowest age-standardized DALY rate was reported in Southern Latin America (12.18), followed by Tropical Latin America (17.88) and Central Latin America (22.14). Between 1990 and 2019, the age-standardized DALY rate for overall liver cancer in young adults showed the most significant increase in Australasia (EAPC: 1.94), Central Asia (EAPC: 2.75), and Eastern Europe (EAPC: 2.88). On the other hand, the rate decreased the most in East Asia (EAPC: -5.35), Andean Latin America (EAPC: -2.84), and Caribbean (EAPC: -2.13) based on Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table S8.\u003c/p\u003e \u003cp\u003eFrom 1990 to 2019, there were notable variations in the age-standardized DALY rate for liver cancer among young adults across different regions of the world, as reported by the EAPC. The regions with the largest increases in this rate were Eastern Europe (EAPC: 2.14), Australia (EAPC: 2.50), and Central Asia (EAPC: 3.49). However, when looking specifically at men, the largest increases were observed in Australasia (EAPC: 1.77), Central Asia (EAPC: 2.39), and Eastern Europe (EAPC: 3.26). Moreover, the burden of disease from liver cancer in Eastern Europe varied between men and women, as detailed in Table S8.\u003c/p\u003e \u003cp\u003eBetween 1990 and 2019, the ASIR for liver cancer in young adults showed a significant increase in various countries across the globe. The countries with the highest increase in ASIR for overall liver cancer were Turkmenistan (EAPC: 9.59), Armenia (EAPC: 9.84), and Uzbekistan (EAPC: 10.80). On the other hand, Saint Kitts and Nevis (EAPC: -6.20), Cuba (EAPC: -5.81), and China (EAPC: -4.81) demonstrated the most substantial decrease in ASIR for overall liver cancer during the same time period (Table S7, Figure S3).\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.5 Relationship between the disease burden and SDI of liver cancer in young adults worldwide from 1990 to 2019\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe burden of liver cancer among young adults worldwide in 2019 varied based on the SDI of the regions. Specifically, the ASIR was highest (2.82) in middle-SDI regions and lowest (1.01) in low-SDI regions. Similarly, the ASDR and age-standardized DALY rates were highest in middle-SDI regions (ASDR: 2.25; DALY: 107.82) and lowest in high-SDI regions (ASDR: 0.77; DALY: 36.50).\u003c/p\u003e \u003cp\u003eFrom 1990 to 2019, the burden of overall liver cancer in young adults worldwide, as measured by ASIR, ASDR, and age-standardized DALY rate, exhibited varying trends based on the countries' SDIs. Analysis of the burden trends for each country using regression revealed a consistent pattern. As the SDIs changed from 0 to 1, the burden generally decreased from large to small and then stabilized. Notably, low-SDI countries had the highest burden, surpassing the global average disease burden, albeit being few in number. Additionally, with an increase in SDI from 0 to approximately 0.25, the burden experienced a decreasing trend. Between an SDI of 0.25 and 0.75, the burden remained relatively stable. However, for an SDI above 0.75, the burden initially decreased and then reversed, showing an upward trajectory. Consequently, countries with SDIs around 0.80 exhibited lower burdens compared to those with SDIs below 0.80. Conversely, countries with SDIs exceeding 0.80 experienced higher burdens. These findings are summarized in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Tables S1-S3, and Figure S4.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Prediction of burdens of liver cancer in young adults worldwide from 2020 to 2030\u003c/h2\u003e \u003cp\u003eData from the years 1990 to 2019 were utilized for fitting a Generalized Additive Model (GAM), allowing us to project changes in the global burden of liver cancer in young adults from 2020 to 2030. Specifically, we initially fitted trends in various measures including the incidence number, incidence rate, death number, death rate, DALY number, and DALY rate for different age groups during the aforementioned time period. This analysis revealed a notable pattern: the overall burden for each age group initially increased between 1990 and 2000, reached a peak between 1995 and 2000, followed by a decrease, another peak between 2005 and 2010, and finally an increase thereafter (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Tables S1\u0026ndash;3, Figure S5).\u003c/p\u003e \u003cp\u003eWe conducted predictions on burdens for each age group from 2020 to 2030, and observed a consistent pattern in the overall indicators. Specifically, between the years 2020 and 2030, an increase in burden is projected for individuals aged 30\u0026ndash;34 and 35\u0026ndash;39, while a decrease is anticipated for other age groups, with the exception of those aged 20\u0026ndash;24 where it is expected to remain relatively stable. Consequently, it is imperative for public health efforts to concentrate on addressing the disease burden specifically among individuals aged 30\u0026ndash;40 (Figure S5).\u003c/p\u003e \u003cp\u003eWe utilized GAMs to generate predictions regarding the future burden of liver cancer in young men and women between 2020 and 2030. Our findings indicate a decrease in the overall burden of liver cancer during this period. Nevertheless, it is important to note that the age-standardized DALY rate of liver cancer attributed to alcohol use is projected to experience a substantial increase in both young men and women. Specifically, both the ASIR and ASDR are predicted to rise significantly. In the absence of an effective intervention, our predictions suggest that by 2030, the ASIR of liver cancer caused by alcohol use will be 1.1 times higher than the rate observed in 2005. This highlights the urgent need to prioritize prevention and treatment efforts targeted at this particular type of liver cancer among young adults worldwide (Figure S6).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this comprehensive analysis of the global burden of liver cancer from 1990 to 2019, with a particular focus on young adults, the GBD 2019 data revealed a significant decrease in liver cancer cases in this demographic over the study period. This decline can be primarily attributed to the successful implementation of hepatitis B vaccines [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and increased public health awareness, particularly regarding the associated risks of alcohol consumption [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Moreover, demographic changes, such as those observed in China, have also contributed to this trend, as younger cohorts exhibit a reduced risk of liver cancer, likely due to vaccination efforts [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, it is important to note that concerns still persist in regions like Latin America, where lifestyle factors continue to heighten the risks of liver cancer [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study reveals that the liver cancer burden has variations, not only with age but also geographically. Specifically, individuals aged 35\u0026ndash;49 are particularly vulnerable due to factors such as prolonged alcohol use and viral infections. Moreover, there are disparities in liver cancer burden in countries like Mongolia and Cambodia, which can possibly be attributed to genetic, environmental, and lifestyle differences [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In a global context, men are more affected by liver cancer than women, possibly because of higher exposure to risk factors such as excessive alcohol use and occupational hazards, as well as less frequent health screenings [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This disparity emphasizes the importance of implementing gender-specific and culturally sensitive prevention and screening strategies [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study uncovers notable variances in liver cancer burdens among different regions and genders. These disparities are shaped by factors such as environmental influences, advancements in medical technology, the adoption of screening programs, and cultural practices including alcohol consumption and smoking [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Regions classified as high-SDI typically demonstrate stronger capabilities in prevention, screening, and treatment, which ultimately contribute to lower liver cancer incidence rates. In contrast, low-SDI regions often lack accessible medical resources and advanced treatment technologies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUsing GAMs to project future trends based on data spanning from 1990 to 2019, our analysis suggests a potential increase in the burden of liver cancer, particularly among individuals aged 30\u0026ndash;40. We identified lifestyle factors, such as dietary habits and work-life stress, as key contributors to this trend, as they are known to lead to unhealthy choices and excessive alcohol consumption. Although advancements in early cancer diagnosis have been significant, the effectiveness of treatments for advanced stages remains challenging. Additionally, our study predicts a surge in liver cancer incidence rates among young adults, which may be attributed to the growing prevalence of non-alcoholic steatohepatitis and the aging global population [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study represents a pioneering effort in conducting a comprehensive examination of the global burden of liver cancer in young adults over a period of three decades. Although the findings provide valuable strategic information for various regions, certain limitations need to be acknowledged. Despite the high quality of the data from the Global Burden of Disease 2019 study, potential biases or inaccuracies cannot be disregarded. In addition, the study focuses extensively on factors such as hepatitis B infections and access to healthcare technologies, while other significant risk factors may not have received sufficient attention.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn conclusion, our findings highlight a reduction in the burden of liver cancer among young adults, specifically cases related to hepatitis B. However, there is a growing burden as individuals age, particularly in the 35\u0026ndash;49 age group, along with noticeable gender discrepancies and regional disparities. These findings underscore the need for intensified and targeted efforts aimed at specific risk groups.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEAPCs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstimated annual percentage changes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGAMs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeneralized additive models\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASIR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAge-standardized incidence rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlobal Burden of Disease Study\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDALY\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDisability-adjusted life years\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSDI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSocio-demographic Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASDRs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAge-standardized death rates\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAAPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAverage annual percentage change\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe GBD study is based entirely on publicly available databases and does not require clinical ethics approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChenlu Fan contributed to the conceptualization and methodology of the study. Xin Zhang and Meichen Zhang was responsible for data curation, as well as the initial preparation of the original draft. Yanmei Yang contributed to the reviewing and editing of the manuscript. All authors have reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all authors for their contributions to the article and the GBD collaborators.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmini M, Looha MA, Zarean E, Pourhoseingholi MA. Global pattern of trends in incidence, mortality, and mortality-to-incidence ratio rates related to liver cancer, 1990\u0026ndash;2019: a longitudinal analysis based on the global burden of disease study. BMC Public Health. 2022;22(1):604.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao G, Liu J, Liu M, Global. 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Int J Epidemiol. 2021;50(1):128\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\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":"Young adults, Liver cancer, Age-standardized DALY rate, Age-standardized death rate, Age-standardized incidence rate","lastPublishedDoi":"10.21203/rs.3.rs-3899212/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3899212/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study was to investigate the prevalence of liver cancer among individuals aged 15\u0026ndash;49 globally and predict future trends in its burden until 2030.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe age-standardized indicators and their estimated annual percentage changes (EAPCs) were calculated in this study. Generalized additive models (GAMs) were employed to predict the burdens for the period of 2020\u0026ndash;2030.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFrom 1990 to 2019, the burden of liver cancer increased significantly among individuals aged 35\u0026ndash;49, with the highest peak observed among those aged 45\u0026ndash;49. The burden was higher in men compared to women. During the same period, the age-standardized incidence rate (ASIR) and age-standardized death rate of liver cancer in young adults showed the greatest increase in Central Asia, while the age-standardized disability-adjusted life year rate increased the most in Eastern Europe. Among the 204 countries examined, Uzbekistan had the highest increase in ASIR of liver cancer in young adults. Furthermore, using GAMs, we predicted that from 2020 to 2030, the burden of liver cancer will continue to rise among individuals aged 30\u0026ndash;34 and 35\u0026ndash;39. Notably, the burden of liver cancer attributed to alcohol use is projected to increase significantly between 2020 and 2030.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe burden of liver cancer among young adults has shown an age-dependent increase in 2019, with men experiencing a greater burden compared to women. The projected estimates indicate a rise in the burden of liver cancer attributed to alcohol consumption among young adults, specifically from 2020 to 2030.\u003c/p\u003e","manuscriptTitle":"Burdens of liver cancer in young adults worldwide from 1990 to 2019, and predictions from 2020 to 2030","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-05 14:42:43","doi":"10.21203/rs.3.rs-3899212/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":"01dfa247-63de-40ef-a3ad-10e2a487929a","owner":[],"postedDate":"February 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-29T15:53:53+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-05 14:42:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3899212","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3899212","identity":"rs-3899212","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}