Global, Regional, and National Burden of Gallbladder and Biliary Tract Cancer in Adults Aged 55 Years and Older: Analysis of the Global Burden of Disease 1990–2021

Global, Regional, and National Burden of Gallbladder and Biliary Tract Cancer in Adults Aged 55 Years and Older: Analysis of the Global Burden of Disease 1990–2021 | 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 Global, Regional, and National Burden of Gallbladder and Biliary Tract Cancer in Adults Aged 55 Years and Older: Analysis of the Global Burden of Disease 1990–2021 Qing-Kang Zheng, Ya-Nan Shi, Bo-Ying Zhu, Kai Sun, Bo-Yu Mei, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7839914/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective Gallbladder and biliary tract cancers (GBTC) are highly aggressive tumors that pose an increasing burden on global health. This study examined the temporal trends and global disease burden across 204 countries and territories from 1990 to 2021. Methods GBTC data from 1990 to 2021 were extracted from the Global Burden of Disease Study 2021, which included 204 countries and territories. Burden was assessed based on prevalence, incidence, and disability-adjusted life years (DALYs) stratified by age group and socio-demographic index (SDI). Temporal trends were analyzed using estimated annual percentage change (EAPC) and 95% confidence intervals (CIs). Results In 2021, gallbladder and biliary tract cancers (GBTC) accounted for 2.5 million prevalent cases, 2.0 million incident cases, and 3.1 million DALYs, reflecting increases of 58%, 51%, and 62% since 1990. Age-specific EAPCs were modest (prevalence, 0.32%; incidence, 0.05%; mortality,0.39%; and DALYs, 0.44%), indicating that demographic aging, rather than etiologic shifts drove the rising burden. Regionally, East Asia reported the highest DALY rates and fastest growth (EAPC ≈ 3.0), whereas Europe and North America showed either stable or declining trends. Older adults, particularly those aged ≥ 90 years, showed the steepest increase (> 160% DALY growth). Conclusions The global burden of GBTC has escalated in recent decades, reflecting the combined effects of demographic ageing and regionally heterogeneous risk factors. Targeted prevention strategies, enhanced early detection, and strengthened surveillance systems are essential to address disparities and mitigate the future impact of GBTC. Gallbladder and biliary tract cancers DALYs GBD 2021 SDI Aging Disease burden Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Gallbladder and biliary tract cancers (GBTC), originating from the epithelial lining of the gallbladder and bile ducts, are highly lethal malignancies within the hepatobiliary system[ 1 – 4 ]. Historically regarded as rare, the global incidence and mortality of GBTC have risen steadily over the past three decades, constituting a growing yet under-recognized public health challenge[ 5 , 6 ]. Typically, asymptomatic onset, anatomical complexity, and the absence of specific biomarkers often lead to late-stage diagnoses, resulting in poor prognosis, limited treatment options, and disproportionately high healthcare costs. GBTC encompasses several heterogeneous subtypes, such as gallbladder cancer, intrahepatic cholangiocarcinoma, and extrahepatic cholangiocarcinoma, each characterized by unique epidemiological patterns and etiological risk factors[ 7 , 8 ]. In high-income regions, risk factors such as primary sclerosing cholangitis (PSC) and metabolic syndrome are predominant, whereas in low- and middle-income countries, particularly in East and Southeast Asia, hepatitis B and C, liver fluke infection, and chronic inflammation are more prevalent[ 9 – 11 ]. These divergent etiological profiles, coupled with disparities in the diagnostic infrastructure, cancer registration, and access to treatment, contribute to significant geographical inequities in disease detection, management, and survival. In 2015, the United Nations launched Sustainable Development Goal 3 (SDG 3), which aims to "ensure healthy lives and promote well-being for all at all ages," including a specific target to reduce premature mortality from non-communicable diseases by one-third by 2030[ 12 ]. Given its rising burden and disproportionately high mortality, GBTC is a critical yet underrecognized component of the global NCD agenda[ 13 ]. Despite growing attention, there is a lack of comprehensive and globally stratified assessments of GBTC burden across demographic and socioeconomic dimensions. Moreover, limited research has tracked long-term trends at global, regional, and national scales within a standardized framework. This study systematically analyzed the prevalence, incidence, and DALYs of GBTC in 204 countries and territories between 1990 and 2021 using data from GBD2021[ 14 ]. Temporal trends, geographic disparities, and SDI-related patterns were further examined to provide evidence to support the development of prevention strategies and the refinement of screening policies. These findings aim to guide investments in diagnostic capacity, surveillance infrastructure, and risk factor control—key measures for advancing global equity in cancer control and accelerating progress towards SDG 3 targets. Methods Data Sources and Disease Definition This study employed data from GBD 2021, managed by the Institute for Health Metrics and Evaluation (IHME), offering systematic estimates for 371 diseases and injuries across 204 countries and territories between 1990 and 2021[ 14 , 15 ]. Data were synthesized from multiple sources, including vital registries, cancer registries, health surveys, and published studies, using standardized GBD modeling pipelines to ensure temporal and cross-country comparability. GBTC was identified using the International Classification of Diseases (ICD) codes: ICD-9 (156.0–156.9) for gallbladder and other/unspecified biliary tract, and ICD-10 (C23 for gallbladder, C24.0–C24.9 for other/unspecified biliary tract). Within the GBD 2021 cause hierarchy, GBTC are categorized as Level-4 neoplasms under cancers. Data were sourced from the Global Health Data Exchange (GHDx) utilizing case definitions, modeling frameworks, and metadata from previous GBD reports[ 16 – 19 ]. Socio-Demographic Index (SDI) SDI is an aggregate index comprising per capita income, average education levels for individuals aged 15 years and older, and fertility rates for those under 25years. The index, ranging from 0 to 100, categorizes countries into five developmental strata: low, low-middle, middle, high-middle, and high SDI quintiles, facilitating the contextualization of the disease burden concerning socioeconomic progress and healthcare resource availability[ 14 ]. DALYs (Disability-Adjusted Life Years) DALYs measure overall health loss by combining Years of Life Lost (YLLs) from early death and Years Lived with Disability (YLDs) from non-fatal conditions, expressed as DALYs = YLLs + YLDs. In the GBD 2021, Years of Life Lost (YLLs) were determined by multiplying the number of deaths from specific causes by the standard life expectancy at the age of death. Years Lived with Disability (YLDs) were calculated by multiplying the prevalence of specific conditions by their associated disability weights. In line with the GBD standards, each metric was derived from 500 Monte Carlo simulations, with outcomes presented as the mean and 95% uncertainty intervals (UIs) determined by the 2.5th – 97.5th percentiles of the simulations. All rates were calculated as age-specific rates in 5-year age groups for individuals aged 55 years and above, ensuring comparability across locations and times[ 20 ]. EAPC and Percentage Change EAPC was applied to quantify temporal trends in age-specific prevalence, incidence, and DALYs rates from 1990 to 2021. EAPC was derived by fitting the following log-linear regression model: log(y)=α + βx + ε ⇒ EAPC = 100×(e β −1) In this context, x denotes the calendar year, y signifies the age-specific rate, α is the intercept, β represents the slope, and ϵ accounts for the error term. In evaluating EAPC trends, 95% confidence intervals (CIs) derived from the regression coefficients were used for statistical inference. If the lower CI bound exceeded 0, the trend was classified as significantly increasing; if the upper CI bound was below 0, the trend was classified as significantly decreasing; and if the CI encompassed 0, the trend was interpreted as stable[ 20 , 21 ]. Additionally, the percentage change in absolute prevalence, incidence, and DALYs between 1990 and 2021 was calculated to capture shifts in the total burden attributable to demographic and epidemiological transitions. All analyses were conducted at global, regional (GBD 21 regions), national (204 countries), SDI-stratified, and age-stratified levels. Computational analysis was performed using R (version 4.2.1), and data visualization was performed using ggplot2. The final figures were edited using the Adobe Illustrator (version CS5). Results Global Level Between 1990 and 2021, the global burden of GBTC among individuals aged 55 years and above has markedly increased, as evidenced by the rising prevalence, incidence, and DALYs. Prevalent cases grew from 1.14 million in 1990 to 1.67 million in 2021, marking a 46.5% relative increase. Incident cases rose from 0.78 million to 1.19 million, a 52.6% increase, while DALYs expanded from 0.82 million to 1.20 million, reflecting a 46.3% increase over the same period. From 1990 to 2021, GBTC death rates among adults aged ≥ 55 years increased globally, with steeper slopes in middle and high middle SDI settings and near-stable or slightly declining trajectories in high-SDI settings (Fig. 1 A-B, Table 1 , Table S1 –S3). Adjusting for population age structure revealed more nuanced trends. From 1990 to 2021, both the global age-specific prevalence rate and DALYs rate showed modest increases, with an EAPC of 0.32 (95% CI: 0.30–0.34) and 0.31 (95% CI: 0.29–0.33), respectively. The incidence rate exhibited a modest rise with an EAPC of 0.28 (95% CI: 0.26–0.31) (Fig. 1 B–C, Figure S1 –S4). Table 1 The prevalence of GBTC cases and rates aged 55 years and above in 1990 and 2021, and the trends from 1990 to 2021 location Prevalent cases Prevalent rates 1990_number(95%UI) 2021_number(95%UI) Percentage change (100%) 1990_per 100000(95%UI) 2021_per 100000(95%UI) EAPC (95%CI) Andean Latin America 768.02 (585.98-908.81) 2083.67 (1585.74-2712.38) 1.71 22.89 (17.46–27.08) 21.03 (16.01–27.38) -0.47 (-0.64–0.3) Australasia 1412.16 (1330.18-1493.27) 4343.59 (3793.17-4725.24) 2.08 35.85 (33.77–37.9) 49.17 (42.94–53.49) 1 (0.67–1.34) Caribbean 346.64 (307.85-378.61) 494.19 (431.72–558.1) 0.43 8.04 (7.14–8.79) 5.34 (4.66–6.03) -1.54 (-1.66–1.42) Central Asia 395.18 (350.83-459.86) 557.78 (494.3-631.84) 0.41 4.94 (4.39–5.75) 3.83 (3.4–4.34) -1.3 (-1.67–0.92) Central Europe 5870.26 (5492.65-6134.77) 6949.12 (6265.27-7643.44) 0.18 22.13 (20.71–23.13) 18.77 (16.92–20.64) -0.76 (-0.85–0.68) Central Latin America 2674.01 (2580.55-2740.53) 4729.64 (4225.94-5252.39) 0.77 19.71 (19.02–20.2) 11.06 (9.88–12.28) -2.26 (-2.44–2.07) Central Sub-Saharan Africa 48.25 (33.49–69.9) 123.91 (83.68-175.18) 1.57 1.28 (0.89–1.86) 1.37 (0.93–1.94) 0.32 (0.24–0.39) East Asia 14267.77 (11181.9-18341.66) 67284.29 (46104.28-87117.93) 3.72 9.58 (7.51–12.31) 17.16 (11.76–22.22) 2.05 (1.95–2.15) Eastern Europe 4539.87 (4266.41-4868.25) 8718.76 (8055.2-9396.46) 0.92 9.29 (8.73–9.96) 14.04 (12.98–15.14) 1 (0.71–1.29) Eastern Sub-Saharan Africa 548.08 (375.46-741.01) 1119.1 (790.45-1478.89) 1.04 4.51 (3.09–6.09) 4.14 (2.92–5.47) -0.38 (-0.46–0.3) Global 108614.75 (99075.75-116782.93) 271324.43 (232609.19-304022.71) 1.5 16.18 (14.76–17.39) 18.26 (15.65–20.46) 0.38 (0.34–0.41) High-income Asia Pacific 20215.82 (18613.12-21288.44) 50619.94 (42563.16-56968.72) 1.5 57.81 (53.23–60.88) 71.8 (60.37–80.8) 0.79 (0.68–0.91) High-income North America 14946.74 (13849.43-15532.48) 29278.78 (26520.1-30813.3) 0.96 25.8 (23.91–26.81) 26.02 (23.57–27.38) -0.18 (-0.29–0.07) High-middle SDI 25750.55 (22817.27-27449.02) 68500.55 (52534.59-79534.39) 1.66 14.93 (13.23–15.91) 19.76 (15.15–22.94) 0.88 (0.83–0.93) High SDI 59059.87 (55510.54-61404.15) 123160.57 (109214.56-134051.48) 1.09 31.67 (29.77–32.93) 35.7 (31.66–38.85) 0.35 (0.3–0.41) Low-middle SDI 6644.45 (5685.37-9516.16) 20779.86 (16361.45-25872.28) 2.13 6.59 (5.64–9.44) 8.62 (6.79–10.73) 0.93 (0.88–0.97) Low SDI 1653.14 (1316.08-2294.21) 4742.9 (3260.24-5836.45) 1.87 4.43 (3.53–6.15) 5.78 (3.97–7.11) 0.96 (0.91–1.01) Middle SDI 15373.17 (13462.71-19744.55) 53962.26 (43414.81-71544.34) 2.51 8.86 (7.76–11.38) 11.48 (9.24–15.23) 0.78 (0.66–0.9) North Africa and Middle East 1701.04 (1381.69-2239.28) 5234.21 (3826.1-6493.05) 2.08 6.02 (4.89–7.92) 6.87 (5.02–8.52) 0.6 (0.49–0.7) Oceania 12.75 (7.81–16.65) 27.9 (19.06–35.7) 1.19 2.65 (1.62–3.46) 2.26 (1.54–2.89) -0.56 (-0.59–0.53) South Asia 6834 (5578.14-9830.78) 26642.51 (18586.17-31608.37) 2.9 7.2 (5.88–10.35) 10.73 (7.49–12.73) 1.31 (1.26–1.36) Southeast Asia 3178.93 (2327.45-4027.65) 11507.47 (8105.49-14737.47) 2.62 7.51 (5.5–9.51) 10.05 (7.08–12.87) 0.78 (0.72–0.84) Southern Latin America 3335.57 (3167.09-3481.85) 4620.96 (4231.79-4920.82) 0.39 42.11 (39.98–43.95) 31.4 (28.76–33.44) -1.07 (-1.15–0.99) Southern Sub-Saharan Africa 129.72 (93.67-174.83) 356.58 (248.78-420.74) 1.75 2.93 (2.12–3.95) 3.66 (2.56–4.32) 0.83 (0.68–0.97) Tropical Latin America 2141.2 (2018.14-2222.79) 5054.32 (4648.97-5298.67) 1.36 14.14 (13.33–14.68) 11.41 (10.49–11.96) -0.9 (-1.05–0.75) Western Europe 25220.36 (23618.75-26248.05) 41504.94 (36761.26-44580.69) 0.65 25.97 (24.32–27.03) 27.83 (24.65–29.89) 0.28 (0.18–0.37) Western Sub-Saharan Africa 28.38 (23.09–39.94) 72.78 (50.05–89.34) 1.56 0.2 (0.16–0.28) 0.23 (0.16–0.28) 1.06 (0.7–1.43) SDI regional level In 2021, individuals aged ≥ 55 years in the middle SDI region bore the greatest absolute GBTC burden, with 1.54 million prevalent cases (95% UI: 1.35–1.72 million), 0.64 million incident cases (95% UI: 0.55–0.76 million), and 0.86 million DALYs (95% UI: 0.78–0.95 million). These figures represent nearly one-third of the global burden across all metrics. Although regions with high SDI also carried a significant disease burden, their absolute and relative growth rates were slower. Between 1990 and 2021, the low SDI regions experience the largest relative increases of up to + 150% in prevalent cases, + 142% in incidence, and + 138% in DALYs, despite starting from a lower baseline. In contrast, high SDI regions exhibited only modest growth (< 10%) owing to stable or declining age-standardized rates (Table 1 , Tables S1–S2, Figs. 1 C–D, 2 A–B, and S1–S4). Trend analyses revealed that the middle SDI group had the highest increases in both prevalence rate (EAPC = 0.82; 95% CI: 0.78–0.86) and DALYs rate (EAPC = 0.91; 95% CI: 0.88–0.95), surpassing all other SDI categories. The middle SDI group also showed a consistent increase in the incidence rate (EAPC = 0.79; 95% CI: 0.76–0.83), whereas the high SDI group showed only minimal upward trends (EAPC < 0.2), and several low SDI countries displayed volatile trends, likely influenced by underreporting and disparities in diagnostic access (Fig. 2 B–C, Fig. 3 A-B, Figure S12–S15). From 1990 to 2021, global GBTC deaths among individuals aged 55 years and older have increased significantly, following the same pattern as the prevalence and DALYs. However, the death rate increased modestly (EAPC = 0.33; 95% CI: 0.30–0.36), suggesting that demographic ageing was the primary driver of the absolute increase. Moreover, the middle-SDI regions had the highest absolute mortality burden in 2021, whereas the low-SDI regions experienced the most significant relative increase (> 120%). High SDI regions exhibited stable or declining age-specific mortality rates among adults aged 55 and older, with several countries reporting negative EAPC for mortality (Fig. 4 C-D). Time-series plots (Fig. 1 B–C) underscore a steep, sustained increase in prevalence and incidence in middle and high-middle SDI regions between 1990 and 2021, in contrast to the plateauing trends in high SDI regions and variable patterns in low SDI areas. GBD regional level Between 1990 and 2021, the majority of GBD super-regions witnessed an upward trend in the total burden of GBTC prevalence, incidence, and DALYs among individuals aged 55 years. This upward trend was largely consistent across regions, with the exception of Central Europe, Eastern Europe, and the high-income Asia-Pacific region, where sustained decreases were observed. In East Asia, the prevalence rate rose sharply (EAPC = 2.6; 95% CI: 2.3–2.9), accompanied by a substantial escalation in the DALYs rate (EAPC = 3.1; 95% CI: 2.7–3.5). Andean Latin America showed similarly accelerated growth, with a prevalence EAPC of 1.9 (95% CI: 1.4–2.4) and a DALYs rate EAPC of 2.3 (95% CI: 1.8–2.9). In contrast, high-income North America and Southeast Asia experienced slight declines, with prevalence EAPC of − 0.04 (95% CI: −0.11 to 0.03) and − 0.05 (95% CI: −0.07 to − 0.03), and DALYs rate EAPC of − 0.07 (95% CI: −0.13 to 0.00) and − 0.03 (95% CI: −0.05 to − 0.01), indicating relatively stable or slightly improving disease control. Notably, incidence trends exhibited greater heterogeneity. Among the 21 GBD regions, 12 experienced reductions in age-specific incidence rates. Notably, the high-income Asia Pacific region demonstrated consistent declines across prevalence, incidence, and DALYs (Table 1 , S1–S3; Fig. 2 A–D, S1–S4). Countries level From 1990 to 2021, approximately 74% of countries experienced an upward trajectory in at least one major indicator of GBTC burden: prevalence, incidence, or DALYs. The most notable increases were observed in Persian Gulf nations, such as Qatar and the United Arab Emirates, both of which are high SDI countries, where the prevalence and mortality more than doubled (more than 2.1 times). These growth patterns contrast with the stable or declining trajectories observed in several other high-SDI countries, such as Norway, Germany, and France, reflecting heterogeneous epidemiological transitions even within economically advanced regions. In contrast, Northern European countries, including Sweden, Denmark, and the Netherlands, showed stable or negative EAPC, particularly for mortality. High-income Asia-Pacific countries, such as Japan and Australia, exhibited stable mortality and DALYs trends, with minimal changes in EAPC estimates throughout the study period. This relative stability differs from the significant increases seen in East Asia and the Persian Gulf, and the decreases noted in various Central and Eastern European nations. Singapore presented an interesting divergence from the typical high SDI pattern. Although its incidence rate remained relatively stable or showed a slight decline, both prevalence and DALYs demonstrated sustained upward trends, with EAPCs of 0.53 (95% CI: 0.40–0.67) and 0.50 (95% CI: 0.38–0.62), respectively. Peru also recorded one of the largest increases in incidence (EAPC, 0.35; 95% CI: 0.26–0.45). In contrast, countries such as South Korea and Thailand exhibited consistent decreases in incidence, with EAPC of − 0.39 (95% CI: −0.44 to − 0.34) and − 0.37 (95% CI: −0.42 to − 0.33), respectively. (Tables S4–S7, Figs. 3 A–D, and S5–S8). Age patterns From 1990 to 2021, global and SDI-stratified age-specific trends in GBTC burden showed marked increases with advancing age, particularly among populations aged 55 years and above (Fig. 4 A-B). The 55–59 age group experienced the smallest global percentage increases in prevalence, incidence, and DALYs at 48.3%, 52.1%, and 58.4%, respectively, with significant increases observed in older age groups. The ≥ 90 years age group showed the most substantial increase, with the prevalence, incidence, and DALYs growing by 150.6%, 160.8%, and 165.2%, respectively, approximately three times the increase observed in the youngest older-age cohort. In regions with low SDI, all older age groups consistently experienced high percentage changes, ranging from 160% to 182%. The burden displayed a pronounced age gradient in the low-middle and middle SDI regions. For example, in middle SDI settings, the prevalence increased from 72.4% in the 60–64 years age group to 138.2% in the 75–79 years age group, whereas DALYs in the latter reached 151.3%. In contrast, high-SDI regions exhibited more tempered increases. Although the prevalence and DALYs rates still increased with age, the percentage change in the 75–79 years age group was limited to 45.6%, which is far below the corresponding value in the middle SDI regions. Additionally, in the younger older-age cohorts (e.g., 55–59 years), the EAPC was negligible or negative (− 0.03; 95% CI: −0.06 to − 0.01). In comparison, EAPC increased steadily with age, peaking at 1.60 (95% CI: 1.30-2.00) in the ≥ 90 years age group, reflecting both a higher current burden and an accelerated long-term growth trend. Mortality exhibited a strong age-dependent pattern: death counts increased monotonically with age across all SDI groups, with the oldest age group (≥ 75 years) accounting for the highest absolute number of deaths by 2021. Furthermore, the age-specific percentage change in mortality increased with advancing age, and the proportion of deaths attributable to older age groups increased between 1990 and 2021 in most regions (Table 2 , Tables S8–S10; Fig. 4 C-D, S9-S18). Table 2 The prevalence of GBTC cases and rates aged 55 years and above in 1990 and 2021, and the trends in age patterns from 1990 to 2021 Location Age (years) Prevalent cases Prevalent rates 1990_number(95%UI) 2021_number(95%UI) Percentage_change(100%) 1990_per 100000(95%UI) 2021_per 100000(95%UI) EAPC (95%CI) Global 55+ 108614.75 (99075.75-116782.93) 271324.43 (232609.19-304022.71) 1.5 (1.35–1.6) 16.18 (14.76–17.39) 18.26 (15.65–20.46) 0.38 (0.34–0.41) 55–59 13427.3 (11843.47-14887.55) 29377.71 (23480.89-33978.73) 1.19 (0.98–1.28) 7.25 (6.39–8.04) 7.42 (5.93–8.59) 0.07 (0.01–0.13) 60–64 17378.14 (15689.32-19049.51) 34572.28 (28586.28-39141.68) 0.99 (0.82–1.05) 10.82 (9.77–11.86) 10.8 (8.93–12.23) 0.04 (-0.02-0.11) 65–69 20003.79 (18351.51-21713.36) 44921.98 (36705.99-51244.98) 1.25 (1-1.36) 16.18 (14.85–17.57) 16.29 (13.31–18.58) 0.05 (-0.04-0.13) 70–74 18428.25 (16920.94-19910.77) 47441.94 (39976.74-53255.5) 1.57 (1.36–1.67) 21.77 (19.99–23.52) 23.05 (19.42–25.87) 0.07 (0.01–0.13) 75–79 18398.96 (16938.47-19451.45) 41764.52 (36061.13-46540.27) 1.27 (1.13–1.39) 29.89 (27.52–31.6) 31.67 (27.34–35.29) 0.22 (0.17–0.28) 80–84 13121.34 (11619.07-14040.34) 37151.42 (31354.87-41329.94) 1.83 (1.7–1.94) 37.09 (32.84–39.69) 42.42 (35.8-47.19) 0.44 (0.36–0.53) 85–89 5971.3 (5078.86-6500.01) 23317.55 (18550.98-26590.4) 2.9 (2.65–3.09) 39.52 (33.61–43.01) 51 (40.57–58.16) 0.78 (0.66–0.89) 90–94 1660.13 (1342.82-1834.16) 10602.5 (7906-12369.42) 5.39 (4.89–5.74) 38.74 (31.34–42.8) 59.27 (44.19–69.14) 1.43 (1.36–1.49) 95+ 225.54 (170.42-256.42) 2174.53 (1458.39-2635.14) 8.64 (7.56–9.28) 22.15 (16.74–25.19) 39.9 (26.76–48.35) 1.94 (1.84–2.03) Low SDI 55+ 1653.14 (1316.08-2294.21) 4742.9 (3260.24-5836.45) 1.87 (1.48–1.54) 4.43 (3.53–6.15) 5.78 (3.97–7.11) 0.96 (0.91–1.01) 55–59 334.99 (248.31-465.14) 804.48 (541.09-1031.98) 1.4 (1.18–1.22) 2.87 (2.12–3.98) 3.18 (2.14–4.07) 0.19 (0.08–0.3) 60–64 398.31 (309.38-554.96) 960.42 (660.8-1221.67) 1.41 (1.14–1.2) 4.27 (3.31–5.95) 4.87 (3.35–6.2) 0.45 (0.35–0.55) 65–69 363.66 (279.25-502.17) 998.8 (661.14-1243.33) 1.75 (1.37–1.48) 5.23 (4.02–7.22) 6.62 (4.39–8.25) 0.91 (0.83–0.99) 70–74 280.35 (228.23-389.92) 924.13 (635.97-1163.56) 2.3 (1.79–1.98) 5.93 (4.83–8.25) 8.91 (6.13–11.22) 1.53 (1.43–1.62) 75–79 163.74 (129.04-228.31) 556.98 (382.98-689.15) 2.4 (1.97–2.02) 6.04 (4.76–8.42) 8.67 (5.96–10.73) 1.43 (1.33–1.53) 80–84 79.86 (63.65-114.09) 337.32 (230.49–414.3) 3.22 (2.62–2.63) 6.15 (4.9–8.78) 10 (6.83–12.28) 1.87 (1.62–2.11) 85–89 26.35 (20.13–37.72) 129.46 (86.08-163.07) 3.91 (3.28–3.32) 5.78 (4.42–8.28) 9.7 (6.45–12.22) 1.85 (1.54–2.15) 90–94 5.23 (3.77–7.8) 28.29 (19.27–37.15) 4.41 (4.11–3.76) 4.63 (3.33–6.9) 7.89 (5.37–10.36) 2.07 (1.74–2.4) 95+ 0.65 (0.45–1.02) 3.03 (1.91–4.16) 3.66 (3.24–3.08) 2.71 (1.87–4.25) 3.98 (2.51–5.47) 2.1 (1.72–2.48) Low-middle SDI 55+ 6644.45 (5685.37-9516.16) 20779.86 (16361.45-25872.28) 2.13 (1.88–1.72) 6.59 (5.64–9.44) 8.62 (6.79–10.73) 0.93 (0.88–0.97) 55–59 1291.6 (1064.96-1853.15) 3614.43 (2718.4-4539.14) 1.8 (1.55–1.45) 4.15 (3.42–5.96) 5.2 (3.91–6.53) 0.7 (0.63–0.78) 60–64 1558.29 (1303.76-2191.22) 4150.42 (3207.54-5027.28) 1.66 (1.46–1.29) 6.16 (5.15–8.66) 7.26 (5.61–8.79) 0.64 (0.57–0.7) 65–69 1366.25 (1146.35-1932.28) 4226.48 (3309.89-5338.17) 2.09 (1.89–1.76) 7.52 (6.31–10.63) 9.53 (7.46–12.03) 0.86 (0.79–0.92) 70–74 1091.61 (902.08-1584.64) 3766.4 (2961.06-4673.96) 2.45 (2.28–1.95) 8.88 (7.34–12.9) 11.98 (9.42–14.86) 0.95 (0.86–1.04) 75–79 714.79 (608.67-999.97) 2451.23 (1994.32–3165) 2.43 (2.28–2.17) 9.43 (8.03–13.19) 12.21 (9.93–15.76) 0.91 (0.85–0.97) 80–84 410.54 (340.51-569.77) 1628.49 (1284.51-2054.17) 2.97 (2.77–2.61) 9.86 (8.18–13.69) 14.16 (11.17–17.86) 1.31 (1.21–1.42) 85–89 165.33 (135.67-231.67) 702.67 (548.71-903.89) 3.25 (3.04–2.9) 10 (8.2-14.01) 14.06 (10.98–18.09) 1.26 (1.15–1.38) 90–94 39.95 (31.6-55.96) 205.4 (159.67–272.5) 4.14 (4.05–3.87) 9.05 (7.16–12.68) 12.69 (9.87–16.84) 1.29 (1.14–1.43) 95+ 6.07 (4.54–8.43) 34.32 (24.77–43.83) 4.65 (4.46–4.2) 6.01 (4.5–8.35) 7.57 (5.46–9.67) 1.04 (0.87–1.21) Middle SDI 55+ 15373.17 (13462.71-19744.55) 53962.26 (43414.81-71544.34) 2.51 (2.22–2.62) 8.86 (7.76–11.38) 11.48 (9.24–15.23) 0.78 (0.66–0.9) 55–59 2815.93 (2367.29-3560.91) 8524.36 (6771.2-11141.25) 2.03 (1.86–2.13) 5.3 (4.45–6.7) 6.18 (4.91–8.08) 0.38 (0.22–0.55) 60–64 3220.03 (2741.27-4035.91) 8877.86 (7124.09-11072.71) 1.76 (1.6–1.74) 7.52 (6.4–9.42) 8.72 (7-10.88) 0.5 (0.37–0.63) 65–69 3072.95 (2658.38-4016.32) 10850.08 (8548.71-14437.66) 2.53 (2.22–2.59) 9.64 (8.34–12.6) 12.17 (9.59–16.2) 0.69 (0.57–0.8) 70–74 2674.55 (2309.33-3496.57) 9900.48 (7985.01-13124.76) 2.7 (2.46–2.75) 12.24 (10.57-16) 16.06 (12.96–21.3) 0.85 (0.72–0.98) 75–79 1931.55 (1681.03-2511.71) 7549.74 (6157.07-10184.25) 2.91 (2.66–3.05) 14.45 (12.57–18.78) 19.27 (15.71–25.99) 0.95 (0.79–1.11) 80–84 1086.83 (919.27-1378.63) 5052.42 (4044.94-6364.02) 3.65 (3.4–3.62) 15.68 (13.26–19.89) 21.21 (16.98–26.72) 0.9 (0.74–1.06) 85–89 460.36 (389.76-561.88) 2404.26 (1891.13-3116.57) 4.22 (3.85–4.55) 16.87 (14.29–20.59) 20.97 (16.49–27.18) 0.61 (0.46–0.75) 90–94 97.25 (79.07-118.81) 688.76 (530.37–874.2) 6.08 (5.71–6.36) 14.69 (11.94–17.95) 17.86 (13.76–22.67) 0.49 (0.38–0.6) 95+ 13.72 (10.36–17.64) 114.3 (81.9-145.45) 7.33 (6.91–7.25) 9.34 (7.06–12.01) 10.99 (7.87–13.98) 0.4 (0.27–0.52) High-middle SDI 55+ 25750.55 (22817.27-27449.02) 68500.55 (52534.59-79534.39) 1.66 (1.3–1.9) 14.93 (13.23–15.91) 19.76 (15.15–22.94) 0.88 (0.83–0.93) 55–59 3474.07 (2954.06-3792.15) 8319.12 (6013.56-10146.03) 1.39 (1.04–1.68) 7.47 (6.35–8.16) 9.25 (6.69–11.28) 0.67 (0.56–0.78) 60–64 4685.95 (4096.15-5052.58) 9332.91 (6916.21-11109.5) 0.99 (0.69–1.2) 10.89 (9.52–11.74) 12.8 (9.48–15.23) 0.55 (0.44–0.66) 65–69 4954.81 (4346.65-5317.13) 12527.49 (9262.19-15156.22) 1.53 (1.13–1.85) 15.72 (13.79–16.87) 18.87 (13.95–22.82) 0.64 (0.5–0.78) 70–74 4298.22 (3819.33-4624.02) 12588.47 (9490.28-14793.23) 1.93 (1.48–2.2) 20.81 (18.49–22.39) 25.77 (19.43–30.28) 0.67 (0.55–0.79) 75–79 4330.11 (3891.73-4613.23) 10381.14 (7972.6-12190.48) 1.4 (1.05–1.64) 26.01 (23.38–27.72) 34.76 (26.69–40.81) 0.82 (0.71–0.94) 80–84 2686 (2392.55-2900.67) 8749.04 (6939.46-10049.89) 2.26 (1.9–2.46) 28.86 (25.71–31.16) 40.07 (31.79–46.03) 1.06 (0.96–1.16) 85–89 1024.92 (878-1121.69) 4710.41 (3785.79-5490.16) 3.6 (3.31–3.89) 27.41 (23.48–29.99) 41.4 (33.28–48.26) 1.22 (1.07–1.37) 90–94 259.97 (219.86-286.49) 1661.59 (1288.48-1931.22) 5.39 (4.86–5.74) 27.95 (23.64–30.8) 38.01 (29.47–44.17) 1.04 (0.85–1.23) 95+ 36.5 (28.64–41.26) 230.38 (169.64-270.63) 5.31 (4.92–5.56) 19.35 (15.19–21.88) 20.87 (15.37–24.52) 0.17 (-0.02-0.35) High SDI 55+ 59059.87 (55510.54-61404.15) 123160.57 (109214.56-134051.48) 1.09 (0.97–1.18) 31.67 (29.77–32.93) 35.7 (31.66–38.85) 0.35 (0.3–0.41) 55–59 5494.48 (5168.23-5780.07) 8098.25 (7381.77-8628.93) 0.47 (0.43–0.49) 12.91 (12.15–13.58) 11.13 (10.15–11.86) -0.44 (-0.52–0.35) 60–64 7492.83 (7129.72-7781.21) 11226.88 (10163.91-12064.61) 0.5 (0.43–0.55) 18.78 (17.87–19.5) 16.47 (14.91–17.7) -0.44 (-0.51–0.38) 65–69 10218.78 (9695.31-10635.5) 16287.32 (14664.39-17660.9) 0.59 (0.51–0.66) 29.24 (27.74–30.43) 26.87 (24.19–29.13) -0.31 (-0.39–0.22) 70–74 10063.89 (9438-10474.83) 20229.09 (18301.73-21816.73) 1.01 (0.94–1.08) 40.18 (37.68–41.82) 37.91 (34.3-40.89) -0.17 (-0.27–0.06) 75–79 11235.08 (10344.84-11815.5) 20796.52 (18435.98-22847.69) 0.85 (0.78–0.93) 53.07 (48.86–55.81) 57.43 (50.91–63.09) 0.33 (0.27–0.4) 80–84 8842.14 (7690.32-9473.45) 21360.1 (17616.16-23975.71) 1.42 (1.29–1.53) 64.87 (56.42–69.5) 79.19 (65.31–88.89) 0.72 (0.61–0.83) 85–89 4288.1 (3559.56-4716.13) 15357.31 (11802.66-17864.21) 2.58 (2.32–2.79) 65.83 (54.64–72.4) 93.09 (71.54-108.28) 1.07 (0.96–1.18) 90–94 1256.15 (990.76-1401.11) 8013.5 (5815.13-9501.61) 5.38 (4.87–5.78) 58.88 (46.44–65.67) 104.52 (75.85-123.93) 1.87 (1.8–1.94) 95+ 168.42 (124.88-193.28) 1791.61 (1186.63-2206.47) 9.64 (8.5-10.42) 30.26 (22.44–34.73) 64.67 (42.83–79.65) 2.62 (2.49–2.75) The association between GBTC burden and SDI In 2021, the prevalence, incidence, and DALYs rates of GBTC were positively and significantly associated with the SDI across all major epidemiological indicators. The correlation coefficients were R = 0.701 (95% CI: 0.663–0.735) for prevalence, R = 0.583 (95% CI: 0.534–0.628) for incidence, R = 0.424 (95% CI: 0.364–0.480) for mortality, and R = 0.361 (95% CI: 0.298–0.421) for DALYs rates. At the global level, the observed GBTC burden was moderately higher than that predicted using the SDI-based regression model. Across the 21 GBD regions, the association between the SDI and GBTC burden remained relatively stable when the SDI values ranged between 0.50 and 0.70. However, as the SDI approached approximately 0.80, the regression curve showed a pronounced upward deviation, indicating that countries with higher SDI levels tend to have disproportionately greater GBTC burdens. Notably, regions such as Eastern Europe, East Asia, and high-income North America clustered above the predicted line, whereas sub-Saharan Africa, Andean Latin America, and parts of Southeast Asia remained below expectations (Fig. 5 , Figure S19-S21). Discussion This analysis of global, regional, and national GBTC trends from 1990 to 2021 revealed a substantial yet unevenly distributed escalation in disease burden, shaped by demographic aging, evolving risk factor profiles, socioeconomic transitions, and disparities in healthcare capacity. Steep increases in middle SDI countries, persistently high burdens in East Asia, and emerging increases in select high-income and low SDI settings underscore the complex interplay of epidemiological transition, environmental exposure, and health system responsiveness. Globally, the prevalence of GBTC among individuals aged ≥ 55 years has increased from approximately 30 per 100,000 in 1990 to nearly 50 per 100,000 in 2021. This increase was largely attributable to population aging (≈ 45%) and improved diagnostic capacity, particularly the wider application of advanced imaging modalities (MRI, MRCP, and CT) and histopathologic confirmation, which enabled the recognition of previously undiagnosed cases[ 22 – 24 ]. Nonetheless, age-specific EAPC remained modest at 0.32% for prevalence and 0.31% for DALYs, indicating that demographic dynamics, rather than major etiologic shifts, primarily drove the increasing burden[ 25 ]. Age proved to be the strongest determinant of the disease burden. Individuals aged ≥ 55 years accounted for the majority of cases, with the 75–79 age group contributing the highest absolute prevalence and DALYs counts. The most rapid escalation occurred in the ≥ 90 years age group, where DALYs increased by 165% across the study period. This pattern reflects biological vulnerability—reduced hepatic reserve, increased comorbidity load, and limited tolerance for radical surgical or chemotherapeutic interventions—combined with cumulative lifetime exposure to carcinogens[ 26 – 29 ]. Additional drivers include chronic conditions such as HBV/HCV infection, diabetes, and gallstone disease, together with improved case detection through widespread imaging use. These factors, compounded by reduced treatment tolerance in the elderly, have produced a disproportionately higher DALYs burden in older populations[ 30 , 31 ]. Collectively, these findings underscore the urgent need for age-tailored screening strategies, evidence-based early detection protocols, and geriatric-focused oncology care frameworks, particularly for older adults, who remain underrepresented in cancer prevention and control policies. At the national level, 74% of countries showed upward trajectories for at least one GBTC burden indicator. These increases were shaped not only by population aging and improved diagnostic capacity but also by region-specific risk factors, lifestyle transitions, and uneven healthcare system development[ 32 ]. In East and Southeast Asia, liver fluke infections (Opisthorchis viverrini, Clonorchis sinensis) remain predominant, whereas in Western countries, conditions such as PSC, congenital biliary cysts, Caroli disease, and choledocholithiasis are more frequent[ 30 , 33 , 34 ]. Among the high SDI countries, our GBD-based analysis indicated that the steepest increases in DALYs (~ 90–102%) occurred in Qatar and the United Arab Emirates, in contrast to France, South Korea, and Norway, which demonstrated stable or declining trends consistent with effective prevention, early detection, and integrated care. Singapore exhibited moderate but steady increases (EAPC ≈ 0.5%), whereas Peru recorded a notable increase in incidence (EAPC ≈ 0.35%), reflecting demographic aging and expanded diagnostic access[ 35 ]. Between 1990 and 2021, the DALYs in the middle SDI regions increase by 34% (EAPC: +0.91%), which was more than threefold the increase observed in the high SDI regions. This acceleration is plausibly driven by rapid urbanization, higher exposure to chronic viral hepatitis, metabolic comorbidities, and delayed health system development[ 36 ]. Numerous studies indicate aa increasing incidence of inflammatory bowel disease (IBD), type 2 diabetes mellitus (T2DM), liver cirrhosis, alcohol-related liver disease, and cholelithiasis in the United States and Europe[ 11 , 37 ]. In contrast, countries with a low SDI reported the lowest measured burden, but this is likely a substantial underestimation owing to incomplete cancer registration systems, limited access to diagnostic technologies, and underreporting[ 38 ]. Regionally, East Asia has emerged as the global epicenter of the GBTC. In 2021, it reported the highest mortality and DALYs rates, along with the fastest increase in the disease burden (EAPC: 3.1). These trends are likely driven by the high prevalence of hepatitis B/C, liver fluke infections, rapid industrialization, and population aging[ 39 , 40 ]. In contrast, regions such as Australasia and the Caribbean demonstrated near-zero or negative EAPC, suggesting effective disease control, improved prevention strategies, or more efficient resource allocation. Although sub-Saharan Africa reported the lowest absolute burden, this likely reflects underdiagnosis, limited surveillance, and incomplete data systems, rather than a truly lower disease incidence[ 41 , 42 ]. To address the global GBTC burden, screening and surveillance should prioritize elderly populations with the highest disease risk, while middle SDI countries need accelerated investments in diagnostics, healthcare workforce, and prevention programs, including hygiene education, safe food handling, and large-scale deworming[ 43 ]. Proven strategies from countries like South Korea, Thailand, and Nordic nations—combining vaccination, early detection, and integrated care—should be adapted to similar contexts[ 44 , 45 ]. In low-SDI regions, urgent efforts are required to establish or strengthen cancer registries and surveillance systems to improve data accuracy and healthcare access[ 46 , 47 ]. These coordinated efforts will promote global equity in cancer control and align with the objectives of SDG-3, which seeks to reduce premature mortality and enhance health and well-being across all age groups by 2030. This study had several limitations. First, the estimates, sourced from the GBD database, may underestimate figures in low SDI regions owing to the integration of heterogeneous data sources of varying quality, incomplete cancer registries, limited diagnostic capacity, and underreporting. Second, variations in diagnostic access over time and between countries may exaggerate trends in regions with high SDI and mask the actual burden in resource-constrained settings. Third, the attribution of risk factors relies on ecological associations rather than individual-level data, which limits the causal inference. Fourth, the lack of granular clinical information such as tumor stage, histological subtype, and treatment data restricts the evaluation of survival patterns and healthcare effectiveness. Finally, SDI-based analyses may mask within-country inequalities, and the ecological nature of the findings precludes direct translation to individual-level risk. Conclusion In conclusion, the global burden of GBTC has increased substantially over the past three decades, primarily because of demographic aging and disparities in health-system capacity. The disproportionate impact on older adults and countries with a middle SDI score highlights the urgent need for age-specific screening programs, risk-based preventive measures, and equitable access to diagnostic and treatment services. Region-specific interventions are critical: East Asia requires enhanced control of hepatitis and liver fluke infections; middle-SDI regions should prioritize investment in cancer care infrastructure; and low-SDI countries must strengthen cancer registries and surveillance systems. By aligning these findings with Sustainable Development Goal 3, this study provides essential evidence to inform policies aimed at reducing premature mortality, advancing equity in cancer care, and promoting healthy ageing. Abbreviations GBTC: Gallbladder and Biliary Tract Cancer; DALY: disability-adjusted life years; SDI: socio-demographic index; EAPC: estimated annual percentage change; CI: confidence intervals; GBD: Global Burden of Disease; ICD: International Classification of Diseases; YLL: Years of Life Lost; YLD: Years Lived with Disability; UI: uncertainty intervals; T2DM: type 2 diabetes mellitus. Declarations Funding This work was supported by The Henan Medical Science and Technology Research Key Project Co-Sponsored by the Province and Ministry in China (grant no. SBGJ202302094). The funders had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation. Conflicts of interest All authors declare no conflict of interest. Availability of data and material All data and material during this research are included in the published article. Authors' contributions Huan-Zhang Niu designed the study. Qing-Kang Zheng wrote the manuscript. Ya-Nan Shi ang Kai Sun prepared the figures and tables. Bo-Ying Zhu and Bo-Yu Mei drafted and revised the manuscript. All authors contributed to manuscript revision, and read and approved the submitted version. Acknowledgements None. Ethics approval Not applicable. 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Supplementary Files Tables.docx GBTCAdditionalfile1FigureS1S21.docx GBTCAdditionalfile2TableS1S10.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 11 Nov, 2025 Editor invited by journal 16 Oct, 2025 Editor assigned by journal 14 Oct, 2025 Submission checks completed at journal 14 Oct, 2025 First submitted to journal 12 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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. 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09:59:24","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":228918,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/c1953ffab687ef33ed0d36ad.html"},{"id":96400319,"identity":"0084fcc2-b5cd-4541-987a-ea350a4b000e","added_by":"auto","created_at":"2025-11-20 16:04:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":110213,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trend of GBTC aged 55 years and above in global and 5 territories. A Percentage change in cases of DALY, deaths, incidence, and prevalence in 1990 and 2021. B The EAPC of DALY, deaths, incidence, and prevalence rates from 1990 to 2021. C The incidence rate per 100,000 population from 1990 to 2021. D The prevalence rate per 100,000 population s from 1990 to 2021.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/92e8a9a73476f277bbc50be4.png"},{"id":96400322,"identity":"374f6595-3213-4fd9-811a-4877fb3a769e","added_by":"auto","created_at":"2025-11-20 16:04:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153071,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trend of GBTC aged 55 years and above in regions. A Prevalence rate per 100,000 population in 1990 and 2021. B Incidence rate per 100,000 population in 1990 and 2021.C EAPC of rates of DALY, deaths, incidence, and prevalence from 1990 to 2021. D Percentage change of DALY, deaths, incidence, and prevalence from 1990 to 2021.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/8ae3070eb8c5298a6c2b8417.png"},{"id":96453912,"identity":"a2c43da1-214a-498d-b1ad-8ee7a2429167","added_by":"auto","created_at":"2025-11-21 10:02:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":529236,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trend of GBTC aged 55 years and above globally. A Percentage change in incidence cases across 204 countries in 1990 and 2021. B EAPC in incidence rates across 204 countries from 1990 to 2021. C Percentage change in prevalent cases across 204 countries in 1990 and 2021. D EAPC in prevalent rates across 204 countries from 1990 to 2021.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/4ebd715ba1d0b98af6936064.png"},{"id":96400327,"identity":"4c5f30c5-aa04-42f8-ad20-64efe579b628","added_by":"auto","created_at":"2025-11-20 16:04:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":287463,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trend of GBTC aged 55 years and above by age pattern in different regions. A Prevalent cases of 9 age groups(55–95+ years, 5-year intervals) from 1990 to 2021 globally and in 5 territories (low to high SDIs). B The distribution of prevalent cases across 9 age groups as percentages globally, in 5 territories, and 21 GBD regions in 1990 and 2021. C EAPC of prevalent rates of 9 age groups globally and in 5 territories from 1990 to 2021. D Percentage change in prevalent cases of 9 age groups globally and in 5 territories in 1990 and 2021.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/dc03986344996bd0dbb5c901.png"},{"id":96453709,"identity":"48136ad0-f333-43d8-9817-6a7b43af60e9","added_by":"auto","created_at":"2025-11-21 10:01:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":218162,"visible":true,"origin":"","legend":"\u003cp\u003eThe associations between the SDI and prevalent rates per 100,000 population of GBTC aged 55 years and above across 21 GBD regions.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/58f0838f51f28454e3cb7cb6.png"},{"id":96456864,"identity":"7aa6ccab-7758-4c8d-90eb-c2be9be0c6d6","added_by":"auto","created_at":"2025-11-21 10:08:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2461574,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/250e189d-9c82-41be-b277-8906dc544a69.pdf"},{"id":96400320,"identity":"e45197fb-2b28-469c-acc4-d3a888bc791d","added_by":"auto","created_at":"2025-11-20 16:04:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":34106,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/3e742639e39f71d789f13b42.docx"},{"id":96400346,"identity":"11bf6c4e-9f89-4df2-ab7e-496b88f7ece7","added_by":"auto","created_at":"2025-11-20 16:04:41","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":7614883,"visible":true,"origin":"","legend":"","description":"","filename":"GBTCAdditionalfile1FigureS1S21.docx","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/0c9b357d01d1c04e9d0f4b6e.docx"},{"id":96400324,"identity":"0d6e6cf7-0d24-47b9-b1a5-3178239b424b","added_by":"auto","created_at":"2025-11-20 16:04:40","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":132390,"visible":true,"origin":"","legend":"","description":"","filename":"GBTCAdditionalfile2TableS1S10.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7839914/v1/ee6b6257b32d5b74fd2eb08d.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global, Regional, and National Burden of Gallbladder and Biliary Tract Cancer in Adults Aged 55 Years and Older: Analysis of the Global Burden of Disease 1990–2021","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGallbladder and biliary tract cancers (GBTC), originating from the epithelial lining of the gallbladder and bile ducts, are highly lethal malignancies within the hepatobiliary system[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Historically regarded as rare, the global incidence and mortality of GBTC have risen steadily over the past three decades, constituting a growing yet under-recognized public health challenge[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Typically, asymptomatic onset, anatomical complexity, and the absence of specific biomarkers often lead to late-stage diagnoses, resulting in poor prognosis, limited treatment options, and disproportionately high healthcare costs. GBTC encompasses several heterogeneous subtypes, such as gallbladder cancer, intrahepatic cholangiocarcinoma, and extrahepatic cholangiocarcinoma, each characterized by unique epidemiological patterns and etiological risk factors[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In high-income regions, risk factors such as primary sclerosing cholangitis (PSC) and metabolic syndrome are predominant, whereas in low- and middle-income countries, particularly in East and Southeast Asia, hepatitis B and C, liver fluke infection, and chronic inflammation are more prevalent[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These divergent etiological profiles, coupled with disparities in the diagnostic infrastructure, cancer registration, and access to treatment, contribute to significant geographical inequities in disease detection, management, and survival.\u003c/p\u003e\u003cp\u003eIn 2015, the United Nations launched Sustainable Development Goal 3 (SDG 3), which aims to \"ensure healthy lives and promote well-being for all at all ages,\" including a specific target to reduce premature mortality from non-communicable diseases by one-third by 2030[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Given its rising burden and disproportionately high mortality, GBTC is a critical yet underrecognized component of the global NCD agenda[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite growing attention, there is a lack of comprehensive and globally stratified assessments of GBTC burden across demographic and socioeconomic dimensions. Moreover, limited research has tracked long-term trends at global, regional, and national scales within a standardized framework.\u003c/p\u003e\u003cp\u003eThis study systematically analyzed the prevalence, incidence, and DALYs of GBTC in 204 countries and territories between 1990 and 2021 using data from GBD2021[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Temporal trends, geographic disparities, and SDI-related patterns were further examined to provide evidence to support the development of prevention strategies and the refinement of screening policies. These findings aim to guide investments in diagnostic capacity, surveillance infrastructure, and risk factor control\u0026mdash;key measures for advancing global equity in cancer control and accelerating progress towards SDG 3 targets.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Sources and Disease Definition\u003c/h2\u003e\u003cp\u003eThis study employed data from GBD 2021, managed by the Institute for Health Metrics and Evaluation (IHME), offering systematic estimates for 371 diseases and injuries across 204 countries and territories between 1990 and 2021[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Data were synthesized from multiple sources, including vital registries, cancer registries, health surveys, and published studies, using standardized GBD modeling pipelines to ensure temporal and cross-country comparability. GBTC was identified using the International Classification of Diseases (ICD) codes: ICD-9 (156.0\u0026ndash;156.9) for gallbladder and other/unspecified biliary tract, and ICD-10 (C23 for gallbladder, C24.0\u0026ndash;C24.9 for other/unspecified biliary tract). Within the GBD 2021 cause hierarchy, GBTC are categorized as Level-4 neoplasms under cancers. Data were sourced from the Global Health Data Exchange (GHDx) utilizing case definitions, modeling frameworks, and metadata from previous GBD reports[\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSocio-Demographic Index (SDI)\u003c/h3\u003e\n\u003cp\u003eSDI is an aggregate index comprising per capita income, average education levels for individuals aged 15 years and older, and fertility rates for those under 25years. The index, ranging from 0 to 100, categorizes countries into five developmental strata: low, low-middle, middle, high-middle, and high SDI quintiles, facilitating the contextualization of the disease burden concerning socioeconomic progress and healthcare resource availability[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eDALYs (Disability-Adjusted Life Years)\u003c/h3\u003e\n\u003cp\u003eDALYs measure overall health loss by combining Years of Life Lost (YLLs) from early death and Years Lived with Disability (YLDs) from non-fatal conditions, expressed as DALYs\u0026thinsp;=\u0026thinsp;YLLs\u0026thinsp;+\u0026thinsp;YLDs. In the GBD 2021, Years of Life Lost (YLLs) were determined by multiplying the number of deaths from specific causes by the standard life expectancy at the age of death. Years Lived with Disability (YLDs) were calculated by multiplying the prevalence of specific conditions by their associated disability weights. In line with the GBD standards, each metric was derived from 500 Monte Carlo simulations, with outcomes presented as the mean and 95% uncertainty intervals (UIs) determined by the 2.5th \u0026ndash; 97.5th percentiles of the simulations. All rates were calculated as age-specific rates in 5-year age groups for individuals aged 55 years and above, ensuring comparability across locations and times[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eEAPC and Percentage Change\u003c/h3\u003e\n\u003cp\u003eEAPC was applied to quantify temporal trends in age-specific prevalence, incidence, and DALYs rates from 1990 to 2021. EAPC was derived by fitting the following log-linear regression model:\u003c/p\u003e\u003cp\u003elog(y)=α\u0026thinsp;+\u0026thinsp;βx\u0026thinsp;+\u0026thinsp;ε \u0026rArr; EAPC\u0026thinsp;=\u0026thinsp;100\u0026times;(e\u003csup\u003eβ\u003c/sup\u003e\u0026minus;1)\u003c/p\u003e\u003cp\u003eIn this context, x denotes the calendar year, y signifies the age-specific rate, α is the intercept, β represents the slope, and ϵ accounts for the error term. In evaluating EAPC trends, 95% confidence intervals (CIs) derived from the regression coefficients were used for statistical inference. If the lower CI bound exceeded 0, the trend was classified as significantly increasing; if the upper CI bound was below 0, the trend was classified as significantly decreasing; and if the CI encompassed 0, the trend was interpreted as stable[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, the percentage change in absolute prevalence, incidence, and DALYs between 1990 and 2021 was calculated to capture shifts in the total burden attributable to demographic and epidemiological transitions.\u003c/p\u003e\u003cp\u003eAll analyses were conducted at global, regional (GBD 21 regions), national (204 countries), SDI-stratified, and age-stratified levels. Computational analysis was performed using R (version 4.2.1), and data visualization was performed using ggplot2. The final figures were edited using the Adobe Illustrator (version CS5).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eGlobal Level\u003c/h2\u003e\u003cp\u003eBetween 1990 and 2021, the global burden of GBTC among individuals aged 55 years and above has markedly increased, as evidenced by the rising prevalence, incidence, and DALYs. Prevalent cases grew from 1.14\u0026nbsp;million in 1990 to 1.67\u0026nbsp;million in 2021, marking a 46.5% relative increase. Incident cases rose from 0.78\u0026nbsp;million to 1.19\u0026nbsp;million, a 52.6% increase, while DALYs expanded from 0.82\u0026nbsp;million to 1.20\u0026nbsp;million, reflecting a 46.3% increase over the same period. From 1990 to 2021, GBTC death rates among adults aged\u0026thinsp;\u0026ge;\u0026thinsp;55 years increased globally, with steeper slopes in middle and high middle SDI settings and near-stable or slightly declining trajectories in high-SDI settings (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S3). Adjusting for population age structure revealed more nuanced trends. From 1990 to 2021, both the global age-specific prevalence rate and DALYs rate showed modest increases, with an EAPC of 0.32 (95% CI: 0.30\u0026ndash;0.34) and 0.31 (95% CI: 0.29\u0026ndash;0.33), respectively. The incidence rate exhibited a modest rise with an EAPC of 0.28 (95% CI: 0.26\u0026ndash;0.31) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u0026ndash;C, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S4).\u003c/p\u003e\u003cp\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 prevalence of GBTC cases and rates aged 55 years and above in 1990 and 2021, and the trends from 1990 to 2021\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003elocation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePrevalent cases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003ePrevalent rates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1990_number(95%UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2021_number(95%UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage change (100%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1990_per 100000(95%UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2021_per 100000(95%UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eEAPC (95%CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\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\u003e768.02 (585.98-908.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2083.67 (1585.74-2712.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e22.89 (17.46\u0026ndash;27.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e21.03 (16.01\u0026ndash;27.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.47 (-0.64\u0026ndash;0.3)\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\u003e1412.16 (1330.18-1493.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4343.59 (3793.17-4725.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e35.85 (33.77\u0026ndash;37.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e49.17 (42.94\u0026ndash;53.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1 (0.67\u0026ndash;1.34)\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\u003e346.64 (307.85-378.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e494.19 (431.72\u0026ndash;558.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.04 (7.14\u0026ndash;8.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.34 (4.66\u0026ndash;6.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-1.54 (-1.66\u0026ndash;1.42)\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\u003e395.18 (350.83-459.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e557.78 (494.3-631.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.94 (4.39\u0026ndash;5.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.83 (3.4\u0026ndash;4.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-1.3 (-1.67\u0026ndash;0.92)\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\u003e5870.26 (5492.65-6134.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6949.12 (6265.27-7643.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e22.13 (20.71\u0026ndash;23.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e18.77 (16.92\u0026ndash;20.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.76 (-0.85\u0026ndash;0.68)\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\u003e2674.01 (2580.55-2740.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4729.64 (4225.94-5252.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e19.71 (19.02\u0026ndash;20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11.06 (9.88\u0026ndash;12.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-2.26 (-2.44\u0026ndash;2.07)\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\u003e48.25 (33.49\u0026ndash;69.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e123.91 (83.68-175.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.28 (0.89\u0026ndash;1.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.37 (0.93\u0026ndash;1.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.32 (0.24\u0026ndash;0.39)\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\u003e14267.77 (11181.9-18341.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67284.29 (46104.28-87117.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.58 (7.51\u0026ndash;12.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17.16 (11.76\u0026ndash;22.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.05 (1.95\u0026ndash;2.15)\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\u003e4539.87 (4266.41-4868.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8718.76 (8055.2-9396.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.29 (8.73\u0026ndash;9.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e14.04 (12.98\u0026ndash;15.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1 (0.71\u0026ndash;1.29)\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\u003e548.08 (375.46-741.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1119.1 (790.45-1478.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.51 (3.09\u0026ndash;6.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.14 (2.92\u0026ndash;5.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.38 (-0.46\u0026ndash;0.3)\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\u003cp\u003e108614.75 (99075.75-116782.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e271324.43 (232609.19-304022.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16.18 (14.76\u0026ndash;17.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e18.26 (15.65\u0026ndash;20.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.38 (0.34\u0026ndash;0.41)\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\u003e20215.82 (18613.12-21288.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50619.94 (42563.16-56968.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e57.81 (53.23\u0026ndash;60.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e71.8 (60.37\u0026ndash;80.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.79 (0.68\u0026ndash;0.91)\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\u003e14946.74 (13849.43-15532.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29278.78 (26520.1-30813.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e25.8 (23.91\u0026ndash;26.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e26.02 (23.57\u0026ndash;27.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.18 (-0.29\u0026ndash;0.07)\u003c/p\u003e\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\u003cp\u003e25750.55 (22817.27-27449.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68500.55 (52534.59-79534.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.93 (13.23\u0026ndash;15.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e19.76 (15.15\u0026ndash;22.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.88 (0.83\u0026ndash;0.93)\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\u003cp\u003e59059.87 (55510.54-61404.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e123160.57 (109214.56-134051.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e31.67 (29.77\u0026ndash;32.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e35.7 (31.66\u0026ndash;38.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.35 (0.3\u0026ndash;0.41)\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\u003cp\u003e6644.45 (5685.37-9516.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20779.86 (16361.45-25872.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.59 (5.64\u0026ndash;9.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e8.62 (6.79\u0026ndash;10.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.93 (0.88\u0026ndash;0.97)\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\u003cp\u003e1653.14 (1316.08-2294.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4742.9 (3260.24-5836.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.43 (3.53\u0026ndash;6.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.78 (3.97\u0026ndash;7.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.96 (0.91\u0026ndash;1.01)\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\u003cp\u003e15373.17 (13462.71-19744.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53962.26 (43414.81-71544.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.86 (7.76\u0026ndash;11.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11.48 (9.24\u0026ndash;15.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.78 (0.66\u0026ndash;0.9)\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\u003e1701.04 (1381.69-2239.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5234.21 (3826.1-6493.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.02 (4.89\u0026ndash;7.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.87 (5.02\u0026ndash;8.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.6 (0.49\u0026ndash;0.7)\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\u003e12.75 (7.81\u0026ndash;16.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.9 (19.06\u0026ndash;35.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.65 (1.62\u0026ndash;3.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.26 (1.54\u0026ndash;2.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.56 (-0.59\u0026ndash;0.53)\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\u003e6834 (5578.14-9830.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26642.51 (18586.17-31608.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.2 (5.88\u0026ndash;10.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10.73 (7.49\u0026ndash;12.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.31 (1.26\u0026ndash;1.36)\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\u003e3178.93 (2327.45-4027.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11507.47 (8105.49-14737.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.51 (5.5\u0026ndash;9.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10.05 (7.08\u0026ndash;12.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.78 (0.72\u0026ndash;0.84)\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\u003e3335.57 (3167.09-3481.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4620.96 (4231.79-4920.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.11 (39.98\u0026ndash;43.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e31.4 (28.76\u0026ndash;33.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-1.07 (-1.15\u0026ndash;0.99)\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\u003e129.72 (93.67-174.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e356.58 (248.78-420.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.93 (2.12\u0026ndash;3.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.66 (2.56\u0026ndash;4.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.83 (0.68\u0026ndash;0.97)\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\u003e2141.2 (2018.14-2222.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5054.32 (4648.97-5298.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.14 (13.33\u0026ndash;14.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11.41 (10.49\u0026ndash;11.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.9 (-1.05\u0026ndash;0.75)\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\u003e25220.36 (23618.75-26248.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41504.94 (36761.26-44580.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e25.97 (24.32\u0026ndash;27.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e27.83 (24.65\u0026ndash;29.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.28 (0.18\u0026ndash;0.37)\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\u003e28.38 (23.09\u0026ndash;39.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72.78 (50.05\u0026ndash;89.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.2 (0.16\u0026ndash;0.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.23 (0.16\u0026ndash;0.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.06 (0.7\u0026ndash;1.43)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSDI regional level\u003c/h3\u003e\n\u003cp\u003eIn 2021, individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;55 years in the middle SDI region bore the greatest absolute GBTC burden, with 1.54\u0026nbsp;million prevalent cases (95% UI: 1.35\u0026ndash;1.72\u0026nbsp;million), 0.64\u0026nbsp;million incident cases (95% UI: 0.55\u0026ndash;0.76\u0026nbsp;million), and 0.86\u0026nbsp;million DALYs (95% UI: 0.78\u0026ndash;0.95\u0026nbsp;million). These figures represent nearly one-third of the global burden across all metrics. Although regions with high SDI also carried a significant disease burden, their absolute and relative growth rates were slower. Between 1990 and 2021, the low SDI regions experience the largest relative increases of up to +\u0026thinsp;150% in prevalent cases, +\u0026thinsp;142% in incidence, and +\u0026thinsp;138% in DALYs, despite starting from a lower baseline. In contrast, high SDI regions exhibited only modest growth (\u0026lt;\u0026thinsp;10%) owing to stable or declining age-standardized rates (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Tables S1\u0026ndash;S2, Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u0026ndash;D, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;B, and S1\u0026ndash;S4). Trend analyses revealed that the middle SDI group had the highest increases in both prevalence rate (EAPC\u0026thinsp;=\u0026thinsp;0.82; 95% CI: 0.78\u0026ndash;0.86) and DALYs rate (EAPC\u0026thinsp;=\u0026thinsp;0.91; 95% CI: 0.88\u0026ndash;0.95), surpassing all other SDI categories. The middle SDI group also showed a consistent increase in the incidence rate (EAPC\u0026thinsp;=\u0026thinsp;0.79; 95% CI: 0.76\u0026ndash;0.83), whereas the high SDI group showed only minimal upward trends (EAPC\u0026thinsp;\u0026lt;\u0026thinsp;0.2), and several low SDI countries displayed volatile trends, likely influenced by underreporting and disparities in diagnostic access (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u0026ndash;C, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B, Figure S12\u0026ndash;S15). From 1990 to 2021, global GBTC deaths among individuals aged 55 years and older have increased significantly, following the same pattern as the prevalence and DALYs. However, the death rate increased modestly (EAPC\u0026thinsp;=\u0026thinsp;0.33; 95% CI: 0.30\u0026ndash;0.36), suggesting that demographic ageing was the primary driver of the absolute increase. Moreover, the middle-SDI regions had the highest absolute mortality burden in 2021, whereas the low-SDI regions experienced the most significant relative increase (\u0026gt;\u0026thinsp;120%). High SDI regions exhibited stable or declining age-specific mortality rates among adults aged 55 and older, with several countries reporting negative EAPC for mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D). Time-series plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u0026ndash;C) underscore a steep, sustained increase in prevalence and incidence in middle and high-middle SDI regions between 1990 and 2021, in contrast to the plateauing trends in high SDI regions and variable patterns in low SDI areas.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eGBD regional level\u003c/h3\u003e\n\u003cp\u003eBetween 1990 and 2021, the majority of GBD super-regions witnessed an upward trend in the total burden of GBTC prevalence, incidence, and DALYs among individuals aged 55 years. This upward trend was largely consistent across regions, with the exception of Central Europe, Eastern Europe, and the high-income Asia-Pacific region, where sustained decreases were observed. In East Asia, the prevalence rate rose sharply (EAPC\u0026thinsp;=\u0026thinsp;2.6; 95% CI: 2.3\u0026ndash;2.9), accompanied by a substantial escalation in the DALYs rate (EAPC\u0026thinsp;=\u0026thinsp;3.1; 95% CI: 2.7\u0026ndash;3.5). Andean Latin America showed similarly accelerated growth, with a prevalence EAPC of 1.9 (95% CI: 1.4\u0026ndash;2.4) and a DALYs rate EAPC of 2.3 (95% CI: 1.8\u0026ndash;2.9). In contrast, high-income North America and Southeast Asia experienced slight declines, with prevalence EAPC of \u0026minus;\u0026thinsp;0.04 (95% CI: \u0026minus;0.11 to 0.03) and \u0026minus;\u0026thinsp;0.05 (95% CI: \u0026minus;0.07 to \u0026minus;\u0026thinsp;0.03), and DALYs rate EAPC of \u0026minus;\u0026thinsp;0.07 (95% CI: \u0026minus;0.13 to 0.00) and \u0026minus;\u0026thinsp;0.03 (95% CI: \u0026minus;0.05 to \u0026minus;\u0026thinsp;0.01), indicating relatively stable or slightly improving disease control. Notably, incidence trends exhibited greater heterogeneity. Among the 21 GBD regions, 12 experienced reductions in age-specific incidence rates. Notably, the high-income Asia Pacific region demonstrated consistent declines across prevalence, incidence, and DALYs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, S1\u0026ndash;S3; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;D, S1\u0026ndash;S4).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eCountries level\u003c/h2\u003e\u003cp\u003eFrom 1990 to 2021, approximately 74% of countries experienced an upward trajectory in at least one major indicator of GBTC burden: prevalence, incidence, or DALYs. The most notable increases were observed in Persian Gulf nations, such as Qatar and the United Arab Emirates, both of which are high SDI countries, where the prevalence and mortality more than doubled (more than 2.1 times). These growth patterns contrast with the stable or declining trajectories observed in several other high-SDI countries, such as Norway, Germany, and France, reflecting heterogeneous epidemiological transitions even within economically advanced regions.\u003c/p\u003e\u003cp\u003eIn contrast, Northern European countries, including Sweden, Denmark, and the Netherlands, showed stable or negative EAPC, particularly for mortality. High-income Asia-Pacific countries, such as Japan and Australia, exhibited stable mortality and DALYs trends, with minimal changes in EAPC estimates throughout the study period. This relative stability differs from the significant increases seen in East Asia and the Persian Gulf, and the decreases noted in various Central and Eastern European nations. Singapore presented an interesting divergence from the typical high SDI pattern. Although its incidence rate remained relatively stable or showed a slight decline, both prevalence and DALYs demonstrated sustained upward trends, with EAPCs of 0.53 (95% CI: 0.40\u0026ndash;0.67) and 0.50 (95% CI: 0.38\u0026ndash;0.62), respectively. Peru also recorded one of the largest increases in incidence (EAPC, 0.35; 95% CI: 0.26\u0026ndash;0.45). In contrast, countries such as South Korea and Thailand exhibited consistent decreases in incidence, with EAPC of \u0026minus;\u0026thinsp;0.39 (95% CI: \u0026minus;0.44 to \u0026minus;\u0026thinsp;0.34) and \u0026minus;\u0026thinsp;0.37 (95% CI: \u0026minus;0.42 to \u0026minus;\u0026thinsp;0.33), respectively. (Tables S4\u0026ndash;S7, Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026ndash;D, and S5\u0026ndash;S8).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAge patterns\u003c/h2\u003e\u003cp\u003eFrom 1990 to 2021, global and SDI-stratified age-specific trends in GBTC burden showed marked increases with advancing age, particularly among populations aged 55 years and above (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). The 55\u0026ndash;59 age group experienced the smallest global percentage increases in prevalence, incidence, and DALYs at 48.3%, 52.1%, and 58.4%, respectively, with significant increases observed in older age groups. The \u0026ge;\u0026thinsp;90 years age group showed the most substantial increase, with the prevalence, incidence, and DALYs growing by 150.6%, 160.8%, and 165.2%, respectively, approximately three times the increase observed in the youngest older-age cohort. In regions with low SDI, all older age groups consistently experienced high percentage changes, ranging from 160% to 182%. The burden displayed a pronounced age gradient in the low-middle and middle SDI regions. For example, in middle SDI settings, the prevalence increased from 72.4% in the 60\u0026ndash;64 years age group to 138.2% in the 75\u0026ndash;79 years age group, whereas DALYs in the latter reached 151.3%.\u003c/p\u003e\u003cp\u003eIn contrast, high-SDI regions exhibited more tempered increases. Although the prevalence and DALYs rates still increased with age, the percentage change in the 75\u0026ndash;79 years age group was limited to 45.6%, which is far below the corresponding value in the middle SDI regions. Additionally, in the younger older-age cohorts (e.g., 55\u0026ndash;59 years), the EAPC was negligible or negative (\u0026minus;\u0026thinsp;0.03; 95% CI: \u0026minus;0.06 to \u0026minus;\u0026thinsp;0.01). In comparison, EAPC increased steadily with age, peaking at 1.60 (95% CI: 1.30-2.00) in the \u0026ge;\u0026thinsp;90 years age group, reflecting both a higher current burden and an accelerated long-term growth trend. Mortality exhibited a strong age-dependent pattern: death counts increased monotonically with age across all SDI groups, with the oldest age group (\u0026ge;\u0026thinsp;75 years) accounting for the highest absolute number of deaths by 2021. Furthermore, the age-specific percentage change in mortality increased with advancing age, and the proportion of deaths attributable to older age groups increased between 1990 and 2021 in most regions (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Tables S8\u0026ndash;S10; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D, S9-S18).\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 prevalence of GBTC cases and rates aged 55 years and above in 1990 and 2021, and the trends in age patterns from 1990 to 2021\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003cp\u003e(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003ePrevalent cases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"61\" rowspan=\"62\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003ePrevalent rates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1990_number(95%UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2021_number(95%UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePercentage_change(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1990_per 100000(95%UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2021_per 100000(95%UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eEAPC (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\u003cp\u003e55+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108614.75 (99075.75-116782.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e271324.43 (232609.19-304022.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5 (1.35\u0026ndash;1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.18 (14.76\u0026ndash;17.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e18.26 (15.65\u0026ndash;20.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.38 (0.34\u0026ndash;0.41)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55\u0026ndash;59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13427.3 (11843.47-14887.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29377.71 (23480.89-33978.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.19 (0.98\u0026ndash;1.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.25 (6.39\u0026ndash;8.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.42 (5.93\u0026ndash;8.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.07 (0.01\u0026ndash;0.13)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17378.14 (15689.32-19049.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34572.28 (28586.28-39141.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.99 (0.82\u0026ndash;1.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.82 (9.77\u0026ndash;11.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e10.8 (8.93\u0026ndash;12.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.04 (-0.02-0.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20003.79 (18351.51-21713.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44921.98 (36705.99-51244.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.25 (1-1.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.18 (14.85\u0026ndash;17.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e16.29 (13.31\u0026ndash;18.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.05 (-0.04-0.13)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u0026ndash;74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18428.25 (16920.94-19910.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47441.94 (39976.74-53255.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.57 (1.36\u0026ndash;1.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e21.77 (19.99\u0026ndash;23.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e23.05 (19.42\u0026ndash;25.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.07 (0.01\u0026ndash;0.13)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75\u0026ndash;79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18398.96 (16938.47-19451.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41764.52 (36061.13-46540.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.27 (1.13\u0026ndash;1.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.89 (27.52\u0026ndash;31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e31.67 (27.34\u0026ndash;35.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.22 (0.17\u0026ndash;0.28)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80\u0026ndash;84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13121.34 (11619.07-14040.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37151.42 (31354.87-41329.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.83 (1.7\u0026ndash;1.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37.09 (32.84\u0026ndash;39.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e42.42 (35.8-47.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.44 (0.36\u0026ndash;0.53)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85\u0026ndash;89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5971.3 (5078.86-6500.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23317.55 (18550.98-26590.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.9 (2.65\u0026ndash;3.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e39.52 (33.61\u0026ndash;43.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e51 (40.57\u0026ndash;58.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.78 (0.66\u0026ndash;0.89)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u0026ndash;94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1660.13 (1342.82-1834.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10602.5 (7906-12369.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.39 (4.89\u0026ndash;5.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e38.74 (31.34\u0026ndash;42.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e59.27 (44.19\u0026ndash;69.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.43 (1.36\u0026ndash;1.49)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e225.54 (170.42-256.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2174.53 (1458.39-2635.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.64 (7.56\u0026ndash;9.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22.15 (16.74\u0026ndash;25.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e39.9 (26.76\u0026ndash;48.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.94 (1.84\u0026ndash;2.03)\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\u003cp\u003e55+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1653.14 (1316.08-2294.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4742.9 (3260.24-5836.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.87 (1.48\u0026ndash;1.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.43 (3.53\u0026ndash;6.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.78 (3.97\u0026ndash;7.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.96 (0.91\u0026ndash;1.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55\u0026ndash;59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e334.99 (248.31-465.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e804.48 (541.09-1031.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.4 (1.18\u0026ndash;1.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.87 (2.12\u0026ndash;3.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.18 (2.14\u0026ndash;4.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.19 (0.08\u0026ndash;0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd 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colname=\"c2\"\u003e\u003cp\u003e65\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10218.78 (9695.31-10635.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16287.32 (14664.39-17660.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.59 (0.51\u0026ndash;0.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.24 (27.74\u0026ndash;30.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e26.87 (24.19\u0026ndash;29.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.31 (-0.39\u0026ndash;0.22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u0026ndash;74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" 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colname=\"c5\"\u003e\u003cp\u003e1.42 (1.29\u0026ndash;1.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e64.87 (56.42\u0026ndash;69.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e79.19 (65.31\u0026ndash;88.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.72 (0.61\u0026ndash;0.83)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85\u0026ndash;89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4288.1 (3559.56-4716.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15357.31 (11802.66-17864.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.58 (2.32\u0026ndash;2.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e65.83 (54.64\u0026ndash;72.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e93.09 (71.54-108.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.07 (0.96\u0026ndash;1.18)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u0026ndash;94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1256.15 (990.76-1401.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8013.5 (5815.13-9501.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.38 (4.87\u0026ndash;5.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e58.88 (46.44\u0026ndash;65.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e104.52 (75.85-123.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.87 (1.8\u0026ndash;1.94)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168.42 (124.88-193.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1791.61 (1186.63-2206.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.64 (8.5-10.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e30.26 (22.44\u0026ndash;34.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e64.67 (42.83\u0026ndash;79.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.62 (2.49\u0026ndash;2.75)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eThe association between GBTC burden and SDI\u003c/h2\u003e\u003cp\u003eIn 2021, the prevalence, incidence, and DALYs rates of GBTC were positively and significantly associated with the SDI across all major epidemiological indicators. The correlation coefficients were R\u0026thinsp;=\u0026thinsp;0.701 (95% CI: 0.663\u0026ndash;0.735) for prevalence, R\u0026thinsp;=\u0026thinsp;0.583 (95% CI: 0.534\u0026ndash;0.628) for incidence, R\u0026thinsp;=\u0026thinsp;0.424 (95% CI: 0.364\u0026ndash;0.480) for mortality, and R\u0026thinsp;=\u0026thinsp;0.361 (95% CI: 0.298\u0026ndash;0.421) for DALYs rates. At the global level, the observed GBTC burden was moderately higher than that predicted using the SDI-based regression model. Across the 21 GBD regions, the association between the SDI and GBTC burden remained relatively stable when the SDI values ranged between 0.50 and 0.70. However, as the SDI approached approximately 0.80, the regression curve showed a pronounced upward deviation, indicating that countries with higher SDI levels tend to have disproportionately greater GBTC burdens. Notably, regions such as Eastern Europe, East Asia, and high-income North America clustered above the predicted line, whereas sub-Saharan Africa, Andean Latin America, and parts of Southeast Asia remained below expectations (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Figure S19-S21).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis analysis of global, regional, and national GBTC trends from 1990 to 2021 revealed a substantial yet unevenly distributed escalation in disease burden, shaped by demographic aging, evolving risk factor profiles, socioeconomic transitions, and disparities in healthcare capacity. Steep increases in middle SDI countries, persistently high burdens in East Asia, and emerging increases in select high-income and low SDI settings underscore the complex interplay of epidemiological transition, environmental exposure, and health system responsiveness.\u003c/p\u003e\u003cp\u003eGlobally, the prevalence of GBTC among individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;55 years has increased from approximately 30 per 100,000 in 1990 to nearly 50 per 100,000 in 2021. This increase was largely attributable to population aging (\u0026asymp;\u0026thinsp;45%) and improved diagnostic capacity, particularly the wider application of advanced imaging modalities (MRI, MRCP, and CT) and histopathologic confirmation, which enabled the recognition of previously undiagnosed cases[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Nonetheless, age-specific EAPC remained modest at 0.32% for prevalence and 0.31% for DALYs, indicating that demographic dynamics, rather than major etiologic shifts, primarily drove the increasing burden[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAge proved to be the strongest determinant of the disease burden. Individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;55 years accounted for the majority of cases, with the 75\u0026ndash;79 age group contributing the highest absolute prevalence and DALYs counts. The most rapid escalation occurred in the \u0026ge;\u0026thinsp;90 years age group, where DALYs increased by 165% across the study period. This pattern reflects biological vulnerability\u0026mdash;reduced hepatic reserve, increased comorbidity load, and limited tolerance for radical surgical or chemotherapeutic interventions\u0026mdash;combined with cumulative lifetime exposure to carcinogens[\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additional drivers include chronic conditions such as HBV/HCV infection, diabetes, and gallstone disease, together with improved case detection through widespread imaging use. These factors, compounded by reduced treatment tolerance in the elderly, have produced a disproportionately higher DALYs burden in older populations[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Collectively, these findings underscore the urgent need for age-tailored screening strategies, evidence-based early detection protocols, and geriatric-focused oncology care frameworks, particularly for older adults, who remain underrepresented in cancer prevention and control policies.\u003c/p\u003e\u003cp\u003eAt the national level, 74% of countries showed upward trajectories for at least one GBTC burden indicator. These increases were shaped not only by population aging and improved diagnostic capacity but also by region-specific risk factors, lifestyle transitions, and uneven healthcare system development[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In East and Southeast Asia, liver fluke infections (Opisthorchis viverrini, Clonorchis sinensis) remain predominant, whereas in Western countries, conditions such as PSC, congenital biliary cysts, Caroli disease, and choledocholithiasis are more frequent[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Among the high SDI countries, our GBD-based analysis indicated that the steepest increases in DALYs (~\u0026thinsp;90\u0026ndash;102%) occurred in Qatar and the United Arab Emirates, in contrast to France, South Korea, and Norway, which demonstrated stable or declining trends consistent with effective prevention, early detection, and integrated care. Singapore exhibited moderate but steady increases (EAPC\u0026thinsp;\u0026asymp;\u0026thinsp;0.5%), whereas Peru recorded a notable increase in incidence (EAPC\u0026thinsp;\u0026asymp;\u0026thinsp;0.35%), reflecting demographic aging and expanded diagnostic access[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBetween 1990 and 2021, the DALYs in the middle SDI regions increase by 34% (EAPC: +0.91%), which was more than threefold the increase observed in the high SDI regions. This acceleration is plausibly driven by rapid urbanization, higher exposure to chronic viral hepatitis, metabolic comorbidities, and delayed health system development[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Numerous studies indicate aa increasing incidence of inflammatory bowel disease (IBD), type 2 diabetes mellitus (T2DM), liver cirrhosis, alcohol-related liver disease, and cholelithiasis in the United States and Europe[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In contrast, countries with a low SDI reported the lowest measured burden, but this is likely a substantial underestimation owing to incomplete cancer registration systems, limited access to diagnostic technologies, and underreporting[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Regionally, East Asia has emerged as the global epicenter of the GBTC. In 2021, it reported the highest mortality and DALYs rates, along with the fastest increase in the disease burden (EAPC: 3.1). These trends are likely driven by the high prevalence of hepatitis B/C, liver fluke infections, rapid industrialization, and population aging[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In contrast, regions such as Australasia and the Caribbean demonstrated near-zero or negative EAPC, suggesting effective disease control, improved prevention strategies, or more efficient resource allocation. Although sub-Saharan Africa reported the lowest absolute burden, this likely reflects underdiagnosis, limited surveillance, and incomplete data systems, rather than a truly lower disease incidence[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo address the global GBTC burden, screening and surveillance should prioritize elderly populations with the highest disease risk, while middle SDI countries need accelerated investments in diagnostics, healthcare workforce, and prevention programs, including hygiene education, safe food handling, and large-scale deworming[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Proven strategies from countries like South Korea, Thailand, and Nordic nations\u0026mdash;combining vaccination, early detection, and integrated care\u0026mdash;should be adapted to similar contexts[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In low-SDI regions, urgent efforts are required to establish or strengthen cancer registries and surveillance systems to improve data accuracy and healthcare access[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. These coordinated efforts will promote global equity in cancer control and align with the objectives of SDG-3, which seeks to reduce premature mortality and enhance health and well-being across all age groups by 2030.\u003c/p\u003e\u003cp\u003eThis study had several limitations. First, the estimates, sourced from the GBD database, may underestimate figures in low SDI regions owing to the integration of heterogeneous data sources of varying quality, incomplete cancer registries, limited diagnostic capacity, and underreporting. Second, variations in diagnostic access over time and between countries may exaggerate trends in regions with high SDI and mask the actual burden in resource-constrained settings. Third, the attribution of risk factors relies on ecological associations rather than individual-level data, which limits the causal inference. Fourth, the lack of granular clinical information such as tumor stage, histological subtype, and treatment data restricts the evaluation of survival patterns and healthcare effectiveness. Finally, SDI-based analyses may mask within-country inequalities, and the ecological nature of the findings precludes direct translation to individual-level risk.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the global burden of GBTC has increased substantially over the past three decades, primarily because of demographic aging and disparities in health-system capacity. The disproportionate impact on older adults and countries with a middle SDI score highlights the urgent need for age-specific screening programs, risk-based preventive measures, and equitable access to diagnostic and treatment services. Region-specific interventions are critical: East Asia requires enhanced control of hepatitis and liver fluke infections; middle-SDI regions should prioritize investment in cancer care infrastructure; and low-SDI countries must strengthen cancer registries and surveillance systems. By aligning these findings with Sustainable Development Goal 3, this study provides essential evidence to inform policies aimed at reducing premature mortality, advancing equity in cancer care, and promoting healthy ageing.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGBTC: Gallbladder and Biliary Tract Cancer; DALY: disability-adjusted life years; SDI: socio-demographic index; EAPC: estimated annual percentage change; CI: confidence intervals; GBD: Global Burden of Disease; ICD: International Classification of Diseases; YLL: Years of Life Lost; YLD: Years Lived with Disability; UI: uncertainty intervals; T2DM: type 2 diabetes mellitus.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by The Henan Medical Science and Technology Research Key Project Co-Sponsored by the Province and Ministry in China (grant no. SBGJ202302094). The funders had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll data and material during this research are included in the published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHuan-Zhang Niu designed the study. Qing-Kang Zheng wrote the manuscript. Ya-Nan Shi ang Kai Sun prepared the figures and tables. Bo-Ying Zhu and Bo-Yu Mei drafted and revised the manuscript. All authors contributed to manuscript revision, and read and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRoth, G.S., et al., \u003cem\u003eBiliary tract cancers: French national clinical practice guidelines for diagnosis, treatments and follow-up (TNCD, SNFGE, FFCD, UNICANCER, GERCOR, SFCD, SFED, AFEF, SFRO, SFP, SFR, ACABi, ACHBPT).\u003c/em\u003e European Journal of Cancer, 2024. \u003cstrong\u003e202\u003c/strong\u003e: p. 114000.\u003c/li\u003e\n\u003cli\u003eDutta, P., et al., \u003cem\u003eSex disparities in global burden of gallbladder and biliary tract cancer: analysis of Global Burden of Disease study from 2010 to 2019.\u003c/em\u003e J Gastroenterol Hepatol, 2024. \u003cstrong\u003e39\u003c/strong\u003e(12): p. 2863-2871.\u003c/li\u003e\n\u003cli\u003eSharma, A., et al., \u003cem\u003eGallbladder cancer epidemiology, pathogenesis and molecular genetics: Recent update.\u003c/em\u003e World J Gastroenterol, 2017. \u003cstrong\u003e23\u003c/strong\u003e(22): p. 3978-3998.\u003c/li\u003e\n\u003cli\u003eMiranda-Filho, A., et al., \u003cem\u003eGallbladder and extrahepatic bile duct cancers in the Americas: Incidence and mortality patterns and trends.\u003c/em\u003e Int J Cancer, 2020. \u003cstrong\u003e147\u003c/strong\u003e(4): p. 978-989.\u003c/li\u003e\n\u003cli\u003eVithayathil, M. and S.A. 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This study examined the temporal trends and global disease burden across 204 countries and territories from 1990 to 2021.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eGBTC data from 1990 to 2021 were extracted from the Global Burden of Disease Study 2021, which included 204 countries and territories. Burden was assessed based on prevalence, incidence, and disability-adjusted life years (DALYs) stratified by age group and socio-demographic index (SDI). Temporal trends were analyzed using estimated annual percentage change (EAPC) and 95% confidence intervals (CIs).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eIn 2021, gallbladder and biliary tract cancers (GBTC) accounted for 2.5\u0026nbsp;million prevalent cases, 2.0\u0026nbsp;million incident cases, and 3.1\u0026nbsp;million DALYs, reflecting increases of 58%, 51%, and 62% since 1990. Age-specific EAPCs were modest (prevalence, 0.32%; incidence, 0.05%; mortality,0.39%; and DALYs, 0.44%), indicating that demographic aging, rather than etiologic shifts drove the rising burden. Regionally, East Asia reported the highest DALY rates and fastest growth (EAPC\u0026thinsp;\u0026asymp;\u0026thinsp;3.0), whereas Europe and North America showed either stable or declining trends. Older adults, particularly those aged\u0026thinsp;\u0026ge;\u0026thinsp;90 years, showed the steepest increase (\u0026gt;\u0026thinsp;160% DALY growth).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe global burden of GBTC has escalated in recent decades, reflecting the combined effects of demographic ageing and regionally heterogeneous risk factors. Targeted prevention strategies, enhanced early detection, and strengthened surveillance systems are essential to address disparities and mitigate the future impact of GBTC.\u003c/p\u003e","manuscriptTitle":"Global, Regional, and National Burden of Gallbladder and Biliary Tract Cancer in Adults Aged 55 Years and Older: Analysis of the Global Burden of Disease 1990–2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 16:04:36","doi":"10.21203/rs.3.rs-7839914/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-11-11T06:36:03+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-16T07:16:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T05:53:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-14T05:50:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-10-12T09:55:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"95ba80a7-46bf-4306-827d-a90325da7b39","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-20T16:04:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 16:04:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7839914","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7839914","identity":"rs-7839914","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}