Temporal Trends, Projections, and Risk Attribution of Colorectal Cancer in Australia, China, Japan, and Korea: GBD 2021 Analysis (1990–2041)

Temporal Trends, Projections, and Risk Attribution of Colorectal Cancer in Australia, China, Japan, and Korea: GBD 2021 Analysis (1990–2041) | 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 Temporal Trends, Projections, and Risk Attribution of Colorectal Cancer in Australia, China, Japan, and Korea: GBD 2021 Analysis (1990–2041) Guodong Yang, Yujiao Zhang, Gang Zhou, Zhiyong Yang, Yaqi Zhang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7388179/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose To generate implementation-ready evidence on colorectal cancer (CRC) burden and prevention priorities across four Asia–Pacific countries. Patients and Methods We analyzed Global Burden of Disease 2021 (GBD 2021) estimates for Australia, China, Japan, and the Republic of Korea (Korea) for 1990–2021. Outcomes included prevalence, incidence, mortality, and disability-adjusted life years (DALYs) as counts and age-standardized rates (ASRs) with 95% uncertainty intervals (UIs). For clarity, ASR components were the age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized disability-adjusted life-year rate (ASDR). Temporal trends used log-linear models to derive average annual percent change (AAPC) and Joinpoint regression; future trajectories (2022–2041) applied autoregressive integrated moving average (ARIMA) models. We performed Das Gupta decomposition (population growth, population aging, and epidemiologic change), assessed correlations with the Socio-demographic Index (SDI), and summarized sex-stratified population-attributable fractions (PAFs) for six modifiable risks (dietary risks, high body mass index (BMI), high fasting plasma glucose, low physical activity, alcohol use, and tobacco use). Results China had the largest counts in 2021; Japan had the highest ASPR. Men bore higher incidence, mortality, and DALY rates, with widening male disadvantages in China and Korea. From 1990–2021, ASPR/ASIR rose in China and Korea, while Australia’s ASPR was stable and ASIR declined; ASMR/ASDR fell in all countries, greatest in Australia. Decomposition attributed rising counts primarily to aging (notably China/Japan) with epidemiologic change contributing in China/Korea. SDI correlated inversely with ASMR/ASDR. Dietary risks were the leading contributors to deaths and DALYs, followed by high BMI and high fasting plasma glucose; PAFs were consistently higher in men. Forecasts suggest continued increases in prevalence/incidence in China/Korea, sustained declines in severity endpoints in Australia, and stability or gradual improvement in Japan through 2041. Conclusion Priorities include scaling high-quality screening and integrated risk-factor control—especially for men—in China and Korea, and sustaining early detection and survivorship gains in Japan and Australia. Findings support resource-appropriate implementation strategies in diverse health-system contexts. colorectal cancer global oncology screening risk factors ARIMA Joinpoint SDI Asia–Pacific Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related death globally, with more than 1.9 million incident cases and 935,000 deaths in 2020[1]. Over recent decades, the global burden of CRC has shift Here’s the same abstract with every abbreviation defined at first mention (JCO GO format preserved): Purpose To generate implementation-ready evidence on colorectal cancer (CRC) burden and prevention priorities across four Asia–Pacific countries. Patients and Methods We analyzed Global Burden of Disease 2021 (GBD 2021) estimates for Australia, China, Japan, and the Republic of Korea (Korea) for 1990–2021. Outcomes included prevalence, incidence, mortality, and disability-adjusted life years (DALYs) as counts and age-standardized rates (ASRs) with 95% uncertainty intervals (UIs) . For clarity, ASR components were the age-standardized prevalence rate (ASPR) , age-standardized incidence rate (ASIR) , age-standardized mortality rate (ASMR) , and age-standardized disability-adjusted life-year rate (ASDR) . Temporal trends used log-linear models to derive average annual percent change (AAPC) and Joinpoint regression; future trajectories (2022–2041) applied autoregressive integrated moving average (ARIMA) models. We performed Das Gupta decomposition (population growth, population aging, and epidemiologic change), assessed correlations with the Socio-demographic Index (SDI) , and summarized sex-stratified population-attributable fractions (PAFs) for six modifiable risks (dietary risks, high body mass index (BMI) , high fasting plasma glucose, low physical activity, alcohol use, and tobacco use). Results China had the largest counts in 2021; Japan had the highest ASPR. Men bore higher incidence, mortality, and DALY rates, with widening male disadvantages in China and Korea. From 1990–2021, ASPR/ASIR rose in China and Korea, while Australia’s ASPR was stable and ASIR declined; ASMR/ASDR fell in all countries, greatest in Australia. Decomposition attributed rising counts primarily to aging (notably China/Japan) with epidemiologic change contributing in China/Korea. SDI correlated inversely with ASMR/ASDR. Dietary risks were the leading contributors to deaths and DALYs, followed by high BMI and high fasting plasma glucose; PAFs were consistently higher in men. Forecasts suggest continued increases in prevalence/incidence in China/Korea, sustained declines in severity endpoints in Australia, and stability or gradual improvement in Japan through 2041. Conclusion Priorities include scaling high-quality screening and integrated risk-factor control—especially for men—in China and Korea, and sustaining early detection and survivorship gains in Japan and Australia. Findings support resource-appropriate implementation strategies in diverse health-system contexts. development and demographic transitions, presents a unique setting for understanding CRC epidemiology. Nations such as China and Korea are experiencing surges in CRC burden, whereas countries like Japan and Australia have seen stabilization or declines in age-standardized mortality rates (ASMR) due to effective screening and prevention programs[2-4]. CRC burden is modulated not only by demographic changes but also by modifiable lifestyle-related exposures, including dietary risks (e.g., low fiber intake, high red and processed meat consumption), obesity, alcohol consumption, tobacco use, physical inactivity, and elevated fasting plasma glucose[5, 6]. While these risk factors have been individually studied, comparative estimates of their attributable burden across countries remain limited. The Global Burden of Disease (GBD) 2021 study enables standardized estimation of population-attributable fractions (PAFs), facilitating inter-country comparison of preventable CRC burden. Understanding these differences is essential for informing tailored public health interventions, particularly in settings undergoing rapid epidemiological transitions. Moreover, substantial variation exists in CRC burden by sex and age. Males consistently experience higher CRC incidence and mortality than females, likely due to behavioral and biological factors[6]. Aging remains a key determinant of CRC risk, with individuals aged ≥50 years accounting for over 80% of cases in most countries[7]. However, trends in younger adults are also emerging, prompting interest in early-onset CRC and the influence of societal shifts such as sedentary behavior and processed food consumption. In parallel, sociodemographic indices (SDI) —a composite of fertility, education, and income—have shown strong associations with CRC burden trajectories, highlighting the intersection of development and disease risk[8, 9]. Despite these known drivers, few studies have comprehensively assessed and compared the full scope of CRC burden, temporal trends, future forecasts, and risk factor attribution across countries with distinct demographic and health system profiles. To address this gap, we conducted a comparative analysis of CRC burden in Australia, China, Japan, and the Republic of Korea using GBD 2021 data. We quantified CRC incidence, prevalence, mortality, and DALYs from 1990 to 2021, examined temporal trends via Joinpoint and log-linear regression, forecasted future burden to 2041 using autoregressive integrated moving average （ ARIMA ） models, and explored associations with SDI. Furthermore, we performed decomposition analyses to disentangle the effects of population growth, aging, and epidemiological change, and estimated the burden attributable to six key modifiable risk factors. These findings aim to inform region-specific prevention strategies and support evidence-based policymaking in the Asia–Pacific region. Materials and Methods Data sources This study utilized publicly available data from the Global Burden of Disease Study 2021 (GBD 2021) , coordinated by the Institute for Health Metrics and Evaluation (IHME) . All data were accessed via the Global Health Data Exchange (GHDx) and GBD Results Tool (https://vizhub.healthdata.org/gbd-results/). We extracted annual estimates of four key epidemiological indicators for CRC—prevalence, incidence, mortality, and disability-adjusted life years (DALYs)—from 1990 to 2021 for Australia, China, Japan, and the Republic of Korea. Data included both absolute numbers and age-standardized rates (ASRs), disaggregated by sex and 5-year age groups. The GBD framework defines CRC according to the International Classification of Diseases (ICD) codes: ICD-10: C18–C20 and ICD-9: 153–154 , ensuring consistency across countries and over time. DALYs were calculated as the sum of years of life lost (YLLs) due to premature mortality and years lived with disability (YLDs), using standardized methods and disability weights defined by the GBD protocol[10] Statistical analysis Descriptive burden assessment We first described the epidemiological burden in 2021 , reporting the number and age-standardized rates of CRC prevalence, incidence, deaths, and DALYs across the four countries, along with corresponding 95% uncertainty intervals (UIs). Age-standardization was performed using the GBD global reference population , enabling meaningful inter-country comparisons. Sex-specific and age-specific distributions were visualized to highlight demographic variations. Temporal trends (1990–2021) To assess temporal trends in colorectal cancer burden from 1990 to 2021, we calculated the percentage change (PC) and average annual percent change (AAPC) for each indicator (incidence, prevalence, mortality, DALYs), stratified by location, sex, and metric type. PC was defined as the relative change between 1990 and 2021: PC = ((Value_2021 - Value_1990) / Value_1990) × 100 AAPC was estimated by fitting a log-linear regression model: log(y) = β0 + β1 × year, AAPC = (e^β1 - 1) × 100 Here, y represents the annual burden estimates. 95% confidence intervals (CIs) were derived from the model. To avoid undefined log values, zero or negative data were replaced with the smallest positive non-zero value. Models with insufficient data were excluded. All analyses were conducted using R (v4.2.2) with the dplyr, tidyr, and base stats packages. Joinpoint regression We applied Joinpoint regression analysis to identify inflection points and characterize the evolution of CRC burden across time. Using the Joinpoint Regression Program (version 4.9.1.0, National Cancer Institute, USA), we modeled the annual ASRs and estimated annual percent changes (APCs) and average annual percent change (AAPC) with Monte Carlo permutation tests to identify significant joinpoints (p < 0.05) [11]. Forecasting future burden (2022–2041) To project the CRC burden from 2022 to 2041, we applied ARIMA models to the ASRs of each indicator and country. Model selection was based on Akaike information criterion (AIC) and Bayesian information criterion (BIC) , and model adequacy was assessed using Ljung-Box tests and residual diagnostics. Forecasting was performed using the forecast and tseries packages in R software (version 4.2.2) [12]. Socio-demographic association We evaluated the relationship between CRC burden and SDI using Pearson correlation coefficients between annual SDI values and ASRs from 1990 to 2020 for each country. SDI is a composite indicator ranging from 0 to 1, incorporating measures of fertility, education, and income per capita [13]. Trends were visualized to assess the dynamic relationship between CRC burden and socioeconomic development. Decomposition analysis To disentangle the drivers of changes in absolute burden over time, we performed a contribution decomposition analysis that attributed the net change in CRC cases, deaths, and DALYs between 1990 and 2021 to three factors: population growth , population aging , and epidemiological change (change in age-specific rates). This was conducted using Das Gupta’s method , a validated demographic decomposition technique [14]. Risk factor attribution To quantify the burden of CRC attributable to modifiable risk factors, we extracted GBD 2021 estimates of population attributable fractions (PAFs) for six Level 2 risks from the GBD Comparative Risk Assessment framework : dietary risks, high body-mass index, high fasting plasma glucose, alcohol use, tobacco use, and low physical activity. Sex-specific proportions of CRC deaths and DALYs attributable to each risk were summarized for each country in 2021 [15]. All statistical analyses and graphical visualizations were conducted using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was assessed using two-sided tests, with P-values < 0.05 considered indicative of a statistically significant Results Epidemiological burden of CRC among Australia, China, Japan, and Korea in 2021 In 2021, CRC posed a substantial but heterogeneous burden across the four Asia–Pacific countries (Table 1). China reported the highest absolute burden, with 3.61 million prevalent cases (95% UI 2.91–4.35 million; age-standardized prevalence rate [ASPR] 168.6 per 100,000 [95% UI 136.6–203.1]), 658,321 incident cases (95% UI 532.0–798.1 thousand; age-standardized incidence rate [ASIR] 31.4 per 100,000 [95% UI 25.5–38.0]), 287,000 deaths (95% UI 221.4–361.7 thousand; age-standardized mortality rate [ASMR] 21.9 per 100,000 [95% UI 16.9–28.1]), and 2.28 million disability-adjusted life years (DALYs; 95% UI 1.75–2.95 million; age-standardized DALY rate [ASDR] 219.3 per 100,000 [95% UI 169.6–281.0]). Japan ranked second in prevalence with 1.00 million cases (95% UI 0.90–1.07 million; ASPR 310.3 per 100,000 [95% UI 285.2–326.6]) and reported 417,000 incident cases (95% UI 382.7–457.1 thousand; ASIR 28.5 per 100,000 [95% UI 26.2–31.1]), 60,300 deaths (95% UI 55.2–65.5 thousand; ASMR 16.7 per 100,000 [95% UI 15.3–18.2]), and 3.64 million DALYs (95% UI 3.35–3.94 million; ASDR 202.4 per 100,000 [95% UI 186.7–219.1]). Republic of Korea had 200,854 prevalent cases (95% UI 168.3–232.9 thousand; ASPR 214.8 per 100,000 [95% UI 180.1–249.2]), 52,700 incident cases (95% UI 45.0–60.6 thousand; ASIR 25.6 per 100,000 [95% UI 21.9–29.5]), 15,800 deaths (95% UI 13.5–18.1 thousand; ASMR 18.1 per 100,000 [95% UI 15.6–20.8]), and 1.05 million DALYs (95% UI 0.87–1.23 million; ASDR 198.5 per 100,000 [95% UI 165.7–234.4]). Australia , despite its smaller population, exhibited the highest ASPR (270.9 per 100,000 [95% UI 241.2–305.4]), with 116,744 prevalent cases (95% UI 103.3–132.1 thousand), 20,900 incident cases (95% UI 18.6–23.5 thousand; ASIR 26.3 per 100,000 [95% UI 23.4–29.5]), 5,800 deaths (95% UI 5.1–6.6 thousand; ASMR 13.5 per 100,000 [95% UI 11.8–15.4]), and 328,000 DALYs (95% UI 286.0–374.5 thousand; ASDR 152.7 per 100,000 [95% UI 133.1–174.5]). Age- and sex-specific analysis revealed notable heterogeneity across the four countries (Table S1, Figure 1). CRC burden increased sharply with age, peaking between 70–84 years for incidence, mortality, and DALYs in all countries. Males consistently exhibited higher incidence, mortality, and DALY rates than females, with male-to-female mortality ratios exceeding 1.3 in China and Korea. The proportion of CRC cases among individuals aged ≥50 years exceeded 80% in all countries, underscoring the dominant contribution of aging populations. Notably, Australia and Japan showed a greater share of CRC burden in those aged ≥75 years compared to China and Korea, reflecting their more advanced population aging. These findings highlight substantial demographic and sex-related differences in CRC epidemiology across the Asia–Pacific region. Temporal trends of colorectal cancer burden from 1990 to 2021 From 1990 to 2021, the four Asia–Pacific countries showed heterogeneous temporal trends in CRC burden (Table 1, Figure 2). China experienced the most remarkable growth across all indicators: prevalence increased from 635,609 (95% UI 548,090–729,557) to 3.61 million (95% UI 2.91–4.35 million), with a PC of +467.3% and an AAPC of +6.08% (95% UI 5.91–6.25); the ASPR rose from 69.9 to 168.6 per 100,000 (PC +141.2%, AAPC +3.17%, 95% UI 3.03–3.31). Incidence more than quadrupled (from 158,389 to 658,321; PC +315.6%, AAPC +4.87%, 95% UI 4.70–5.05), with the ASIR increasing from 19.0 to 31.4 per 100,000 (PC +65.1%, AAPC +1.75%, 95% UI 1.64–1.87). Mortality and disability-adjusted life years (DALYs) also climbed substantially, with deaths rising from 119,303 to 275,129 (PC +130.6%, AAPC +2.69%, 95% UI 2.58–2.79), while ASMR declining from 15.49 to 13.64 per 100,000 (PC −11.9%, AAPC −0.49%, 95% UI −0.55– −0.43), and ASDR from 390.63 to 331.73 per 100,000 (PC −15.10%, AAPC −0.62%, 95% UI −0.71– −0.54). Korea displayed similar upward trends, particularly for prevalence (ASPR increased from 82.6 to 214.8 per 100,000; PC +160.1%, AAPC +3.44%, 95% UI 2.90–3.99). By contrast, Japan and Australia demonstrated relatively stable or slightly declining age-standardized rates, with Japan maintaining moderate increases in prevalence (ASPR 250.6 to 310.3 per 100,000; PC +23.8%, AAPC +0.60%, 95% UI 0.51–0.69) but limited changes in incidence and mortality, while Australia exhibited minimal variation in prevalence (ASPR 260.6 to 270.9 per 100,000; PC +3.9%, AAPC +0.07%, 95% UI −0.14–0.29) and a modest decline in mortality (ASMR from 23.8 to 13.98 per 100,000; PC −41.3%, AAPC −1.95%, 95% UI −2.05– −1.85). Across all four countries, males consistently exhibited higher CRC burden than females for prevalence, incidence, mortality, and DALYs (Figure 2; Table 1). The sex gap was most evident in China and the Republic of Korea: male incidence rates increased faster than female rates (China ASIR AAPC: males 2.32% vs. females 0.86%; Korea: 2.35% vs. 1.47%), while declines in ASMR and ASDR were steeper in women, indicating a gradually widening male disadvantage (Figure 2E–H, M–P; Table 1). In Australia and Japan, men also had higher rates, but the trajectories between sexes were largely parallel—incidence was flat to modestly changing and mortality/DALY rates declined in both sexes—so the sex gap remained comparatively stable (Figure 2A–D, I–L; Table 1). Taken together, absolute numbers rose in all four countries, but age-standardized patterns diverged. China and Korea showed clear increases in ASPR and ASIR (e.g., China ASPR 69.9→168.6 per 100,000; ASIR 19.0→31.4; Korea ASPR 82.6→214.8; ASIR 19.3→35.5), while ASMR and ASDR declined in every country (China ASMR 15.49→13.64; ASDR 390.6→331.7; Korea ASMR 14.12→12.56; ASDR 336.1→267.4). Japan had moderate rises in prevalence and a small increase in incidence (ASPR 250.6→310.3; ASIR 43.2→48.7) alongside decreases in mortality and DALYs (ASMR 19.0→15.9; ASDR 445.6→358.4). Australia showed minimal change in prevalence (ASPR 260.6→270.9) but declines in incidence, mortality, and DALYs (ASIR 48.5→42.7; ASMR 23.8→14.0; ASDR 552.3→315.5). These patterns indicate that improvements in survival and disease management (reflected by falling ASMR/ASDR) co-occurred with rising detection/underlying risk (rising ASIR/ASPR) in China and Korea, whereas Japan—and especially Australia—achieved broader reductions across severity endpoints (Figure 2; Table 1). Joinpoint Regression Analysis of Colorectal Cancer Trends (1990–2021) Joinpoint regression analysis was conducted to characterize the temporal trends of CRC burden from 1990 to 2021 in Australia, China, Japan, and the Republic of Korea. We report the AAPC with corresponding 95% UIs, along with significant joinpoints and segment-specific APCs, based on the ASRs of prevalence, incidence, mortality, and DALYs (Table S3, S4; Figure 3). Australia: Prevalence : The overall trend was slightly decreasing (AAPC: –0.27% , 95% UI: –0.46 to –0.07), with joinpoints in 1996 and 2008. The trend rose during 1990–1996 (APC: +1.81% ) but declined steadily afterward. Incidence : A decreasing trend was observed (AAPC: –0.42% , 95% UI: –0.60 to –0.24), with a turning point in 2000, after which the decline accelerated (APC: –1.26%). Mortality : A sustained and substantial decrease was seen (AAPC: –1.71% , 95% UI: –2.01 to –1.40), with a rapid decline from 1996 onwards. DALYs : The greatest reduction among all countries was found in DALYs (AAPC: –1.80% , 95% UI: –2.00 to –1.60), indicating continuous improvements in CRC outcomes over three decades. China: Prevalence : A steep increase was observed (AAPC: +2.95% , 95% UI: 2.80 to 3.11), with major accelerations post-1997 and 2008 (APCs: +3.82% and +2.63%, respectively). Incidence : The rate rose significantly (AAPC: +1.66% , 95% UI: 1.39 to 1.94), reflecting increasing CRC detection and possibly changing risk exposures. Mortality : A modest upward trend was noted (AAPC: +0.42% , 95% UI: 0.25 to 0.59), with joinpoints in 1996 and 2015 suggesting a partial stabilization in recent years. DALYs : Despite lower mortality gains, DALYs continued to increase (AAPC: +1.29% , 95% UI: 1.12 to 1.46), likely due to a higher disease burden in younger populations and growing prevalence. Japan: Prevalence : AAPC of +0.67% (95% UI: 0.50 to 0.84) indicated a mild upward trend, with leveling-off seen after the early 2000s. Incidence : The trajectory remained largely stable (AAPC: +0.36% , 95% UI: 0.09 to 0.64); after peaking in 2002–2016 (APC: –0.84%), incidence began to decline. Mortality : A consistent decline was detected (AAPC: –0.59% , 95% UI: –0.77 to –0.41), with the fastest drop occurring between 2012–2021. DALYs : A downward trend was also observed (AAPC: –0.72% , 95% UI: –0.88 to –0.56), consistent with improved screening and survival. Republic of Korea: Prevalence : The most pronounced increase among the four countries (AAPC: +3.08% , 95% UI: 2.88 to 3.28), with APCs exceeding +4% during 1990–2002. Incidence : AAPC of +1.97% (95% UI: 1.71 to 2.22), reflecting rising case numbers, but a noticeable slowdown was observed after 2010. Mortality : Although initially increasing, mortality rates plateaued post-2010. Overall, AAPC was –0.48% (95% UI: –0.60 to –0.37), suggesting improved CRC management. DALYs : AAPC was –0.50% (95% UI: –0.66 to –0.33), marking a transition from growth to decline around 2010–2016. This analysis reveals divergent epidemiologic trajectories of CRC across Asia–Pacific countries. China and Korea exhibited rising trends in most indicators, especially prevalence and incidence, while Japan and Australia showed declines in mortality and DALYs. These trends likely reflect differences in screening implementation, healthcare access, and risk factor transitions. The identified joinpoints align with periods of public health intervention and policy changes (e.g., national screening rollout in Korea and Japan). Forecasted Trends in Colorectal Cancer Burden (2022–2041) Based on ARIMA modeling, the future burden ofCRC shows heterogeneous trajectories across the four Asia–Pacific countries between 2022 and 2041 (Table S5, Figure 4). In Australia , the ASPR is projected to remain stable, rising only slightly from 271.2 to 274.8 per 100,000, while ASIR is expected to plateau. In contrast, both ASMR and ASDR are anticipated to continue their steady declines, reaching 7.6 and 162.7 per 100,000 respectively by 2041, reflecting sustained advancements in screening and clinical management. In China , CRC burden is forecasted to increase moderately, with ASPR rising from 171.0 to 186.1 and ASIR increasing from 38.2 to 41.0 per 100,000. Mortality rates are projected to stabilize, while ASDR is expected to show a slight upward trend, indicating the growing impact of CRC despite recent public health efforts. In Japan , prevalence is predicted to increase minimally, while incidence is expected to remain flat. Both mortality and DALY rates will likely decline further, maintaining Japan’s favorable trajectory in CRC control. In the Republic of Korea , prevalence is forecasted to increase from 318.3 to 342.9 per 100,000, while incidence is expected to remain steady. Meanwhile, ASMR and ASDR are projected to decline progressively, indicating improved disease outcomes in recent years. Overall, Australia and Japan are expected to maintain favorable trends with reduced CRC burden, while China and Korea face ongoing challenges, particularly in prevalence and early detection. Association Between CRC Burden and SDI To explore the relationship between SDI and CRC burden, we analyzed the correlation between the SDI and ASPR, ASIR, ASMR, and ASDR from 1990 to 2020 across the four countries (Figure 5). Across all indicators, China and the Republic of Korea demonstrated strong positive correlations between SDI and both ASPR and ASIR (R = 1.0, p < 0.001), indicating that CRC prevalence and incidence increased consistently with rising socioeconomic levels. In Australia and Japan , however, these relationships were non-linear or even inverse. In Australia, ASPR remained relatively stable as SDI increased (R = 0.19), while in Japan, ASPR showed a slight negative association with SDI (R = –0.34, p < 0.05). Regarding mortality (ASMR), all four countries exhibited negative correlations with SDI, suggesting that improvements in health systems and socioeconomic conditions have contributed to reduced mortality. This trend was particularly pronounced in Australia (R = –0.95) and Japan (R = –0.83) , followed by the Republic of Korea (R = –0.68) and China (R = –0.93) . For DALY rates (ASDR), a similar inverse pattern was observed, with stronger correlations in Australia (R = –0.93) and Republic of Korea (R = –0.89) , reflecting their effective disease management strategies. Japan and China also showed significant negative correlations (R = –0.80 and –0.91, respectively), though the reduction in disease burden occurred at a slower pace compared to Australia. Decomposition analysis of changes in CRC burden (1990–2021) To elucidate the driving forces behind the changes in CRC burden over the past three decades, we decomposed the total change in four key indicators—prevalence, incidence, deaths, and DALYs—into contributions from population aging, population growth, and epidemiological change across the four countries (Figure 6, Table 2). In China , the total increases were substantial for all burden metrics, with prevalence rising by 2,352,628 cases, incidence by 499,932 cases, deaths by 377,740, and DALYs by 3,283,194. Aging emerged as the dominant contributor across all indicators, accounting for 39.9% to 60.3% of the total change, followed by epidemiological changes (ranging from 35.8% to 46.3%), and a relatively minor contribution from population growth in deaths and DALYs. In Japan , CRC burden also increased but to a lesser extent. The increases in prevalence (285,067), incidence (55,491), deaths (64,948), and DALYs (729,152) were primarily driven by aging, which contributed more than 70% in all indicators. Epidemiological change played a minor or even negative role, particularly in DALYs (−8.1%), indicating progress in treatment or early detection. In the Republic of Korea , the total burden increased modestly, with prevalence, incidence, deaths, and DALYs rising by 51,501, 20,173, 17,100, and 202,278, respectively. Here again, aging was the predominant contributor to the increases (67.3%–85.6%), while epidemiological change had a minimal or negative impact, especially in deaths (−3.5%) and DALYs (−1.6%). Conversely, Australia exhibited a different pattern. While prevalence (105,957) and incidence (9,474) rose over the period, both deaths (6,753) and DALYs (52,601) showed relatively stable or declining trends. Notably, the increase in DALYs was largely attributed to population aging (53,749), with epidemiological improvements leading to a substantial reduction (−116,205 DALYs, accounting for −220.9% of the change), offsetting the effects of population growth and aging. These findings highlight the dominant role of population aging in driving the CRC burden in the Asia–Pacific region, particularly in China, Japan, and Korea, while underscoring the mitigating effect of improved healthcare and prevention in Australia. Risk factor attribution analysis for CRC burden in 2021 To better understand the underlying contributors to CRC burden, we analyzed the proportion of CRC deaths and DALYs attributable to six modifiable risk factors—dietary risks, high alcohol use, high body mass index (BMI), high fasting plasma glucose, low physical activity, and tobacco use—in Australia, China, Japan, and the Republic of Korea, stratified by sex (Figure 7). Among all four countries, dietary risks consistently accounted for the largest proportion of attributable burden in both deaths and DALYs, ranging from 35.9% to 41.4% . In 2021, Australia had the highest proportion of CRC deaths attributable to dietary risks (41.2%), followed closely by Japan (40.3%), the Republic of Korea (39.8%), and China (37.3%). A similar pattern was observed for DALYs, with Japan (41.1%) and Australia (41.4%) topping the list. Males exhibited slightly higher attributable fractions than females in most countries. High BMI was the second most important contributor, particularly in Australia, where it accounted for 13.9% of CRC deaths and 14.4% of DALYs . By contrast, the proportions in China (8.2% deaths, 8.6% DALYs) and Japan (5.3% deaths, 5.5% DALYs) were notably lower, although sex differences persisted across all nations. High fasting plasma glucose also contributed significantly, with proportions ranging from 6.3% to 10.1% for deaths and 6.3% to 8.7% for DALYs. China, Japan, and Korea showed relatively similar burdens, while Australia had a marginally higher fraction. Low physical activity showed a particularly strong impact in Australia, where it accounted for 12.6% of deaths and 11.8% of DALYs , whereas in China and Korea, the impact was generally lower (≤8.7%). High alcohol use and tobacco use played lesser but still notable roles. Australia exhibited the highest proportion of CRC deaths and DALYs attributable to alcohol consumption ( 11.4% and 12.3% , respectively), followed by Korea and Japan. China’s alcohol-related burden remained the lowest among the four countries (0.8–0.9%). Overall, these results emphasize that dietary modification, obesity control, and increased physical activity represent key intervention targets for CRC prevention in the Asia–Pacific region, particularly for males. The relatively high burden attributable to modifiable lifestyle risks in Australia suggests both an opportunity and a need for intensified public health interventions. Discussion This study offers a comprehensive comparative analysis of the CRC burden in Australia, China, Japan, and the Republic of Korea, providing critical insight into the temporal evolution, underlying drivers, and potential future trajectories across the Asia–Pacific region[ 16 ]. Our findings confirm pronounced heterogeneity in CRC epidemiology across the four countries. From 1990 to 2021, China and the Republic of Korea showed clear increases in age-standardized prevalence (ASPR) and incidence (ASIR) alongside rising absolute numbers, whereas age-standardized mortality (ASMR) and DALY rates (ASDR) declined in all four countries. Japan exhibited a moderate rise in ASPR and a small increase in ASIR, with concurrent declines in ASMR/ASDR; Australia showed minimal change in ASPR, a decline in ASIR, and marked reductions in ASMR/ASDR. These divergent trajectories likely reflect differences in screening uptake and quality of care, the pace of population aging, and transitions in lifestyle-related risks across settings[ 17 ]. In 2021, China carried the highest absolute counts, consistent with its population size and ongoing demographic aging, whereas Japan recorded the highest ASPR among the four countries—compatible with higher detection and longer post-diagnosis survival. Australia’s relatively low and falling ASMR/ASDR align with sustained improvements in screening pathways, early treatment, and survivorship care. The male disadvantage was evident in all countries and widened in China and Korea, driven by faster increases in male ASIR and relatively slower declines in male ASMR/ASDR, in line with higher exposure to tobacco, alcohol, and metabolic risks among men[ 18 ]. Joinpoint and decomposition analyses indicate that population aging remains the dominant driver of growth in absolute burden—particularly in China and Japan—but epidemiological change (incidence dynamics linked to modifiable risks and health-system responses) contributed substantially in China and Korea. These results echo prior evidence that aging alone cannot explain the rising case load in rapidly developing contexts and underscore the role of dietary westernization, adiposity, hyperglycemia, and evolving screening practices[ 19 ]. Looking forward, our ARIMA projections suggest that China and Korea are likely to experience continued increases in prevalence and incidence, whereas Australia is projected to maintain broad declines across severity endpoints, and Japan to see stability or gradual decline in mortality and DALYs with modest changes in incidence. These patterns mirror global observations of improving survival but persistent or rising incidence where unfavorable risk profiles and incomplete screening coverage remain[ 20 ]. Importantly, our risk attribution analysis showed that dietary risks were the leading contributor to CRC deaths and DALYs across all four countries, followed by high BMI, high fasting plasma glucose, and low physical activity. These findings echo the Global Cancer Observatory’s assessment that unhealthy diets and obesity account for over one-third of CRC-related mortality worldwide (GLOBOCAN). Moreover, the higher attributable burden among men further emphasizes the need for sex-specific prevention strategies[ 21 ]. The findings also underscore the urgency of strengthening national policies around food environment regulation, physical activity promotion, and diabetes control—particularly in China and Korea, where trends remain adverse. This study has several strengths. It leverages high-quality GBD 2021 data, incorporates advanced statistical modeling (joinpoint, ARIMA, decomposition), and provides cross-national comparisons over a 30-year period. However, limitations include the reliance on secondary data, which may be subject to underreporting or misclassification, particularly in low-resource settings. Additionally, the forecasts may not fully capture disruptive events such as COVID-19 or future screening policy changes. Conclusion CRC burden across the Asia–Pacific is heterogeneous. China and Korea show rising ASPR/ASIR with declining—but still substantial—ASMR/ASDR; Japan shows moderate increases in ASPR and slight increases in ASIR with declining severity endpoints; and Australia demonstrates stable ASPR, falling ASIR, and the largest declines in ASMR/ASDR. Men consistently bear higher burden, with an expanding sex gap in China and Korea. Population aging is the principal driver of increasing counts, but modifiable risks—especially diet, adiposity, hyperglycemia, and inactivity—remain critical levers. To curb future burden, China and Korea should prioritize expanding high-quality screening and risk-factor control with male-focused strategies, while Japan and Australia should sustain early detection and survivorship optimization. Region-specific policies that integrate risk reduction, equitable screening coverage, and high-value treatment pathways will be essential to bending both incidence and severity curves over the coming decades. Abbreviations AAPC average annual percent change AIC Akaike information criterion APC annual percent change ARIMA autoregressive integrated moving average ASDR age-standardized disability-adjusted life-year rate ASIR age-standardized incidence rate ASMR age-standardized mortality rate ASPR age-standardized prevalence rate ASR(s) age-standardized rate(s) BIC Bayesian information criterion BMI body mass index CI(s) confidence interval(s) CRC colorectal cancer DALY(s) disability-adjusted life year(s) GBD Global Burden of Disease GHDx Global Health Data Exchange GLOBOCAN Global Cancer Observatory cancer database (IARC) ICD-9/ICD-10 International Classification of Diseases, Ninth/Tenth Revision IHME Institute for Health Metrics and Evaluation PAF(s) population-attributable fraction(s) PC percentage change SDI Socio-demographic Index UI(s) uncertainty interval(s) Declarations AUTHOR CONTRIBUTIONS Guodong Yang and Yujiao Zhang contributed equally to this work. [Guodong Yang]: Conceptualization, data acquisition, statistical analysis, manuscript drafting, and critical revision. [Yujiao Zhang and Gang Zhou]: Data interpretation, literature review, and manuscript drafting. [Yaqi Zhang and Jiping Wang]: Statistical modeling (Joinpoint, ARIMA), figure preparation, and critical review. [Qibin Wu]: Methodology supervision, interpretation of results, and critical manuscript revision. All authors: Approved the final version of the manuscript and agree to be accountable for all aspects of the work. ACKNOWLEDGMENTS The authors thank the Institute for Health Metrics and Evaluation (IHME) for providing access to the Global Burden of Disease database. CONFLICT OF INTEREST STATEMENT The authors have no conflict of interest. DATA AVAILABILITY STATEMENT The datasets used and/or analyzed in this study are publicly available from the Global Burden of Disease database: https://vizhub.healthdata.org/gbd-results/ . FUNDING INFORMATION This work was supported by the Special Scientific Research Fund for Medical Consortium of Hunan Provincial People's Hospital (Grant No. 2022YLT005) and 2025 Natural Science Foundation of Hubei Province(Grant No.JCZRLH20250859). ETHICS STATEMENT This study used publicly available, de-identified data from the Global Burden of Disease 2021 database. Ethical approval and consent to participate were not required. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F: Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries . CA Cancer J Clin 2021, 71 (3):209-249. Ma R, Jing C, Zhang Y, Cao H, Liu S, Wang Z, Chen D, Zhang J, Wu Y, Wu J et al : The somatic mutation landscape of Chinese Colorectal Cancer . J Cancer 2020, 11 (5):1038-1046. Nam S, Choi YJ, Kim DW, Park EC, Kang JG: Risk Factors for Colorectal Cancer in Korea: A Population-Based Retrospective Cohort Study . Annals of coloproctology 2019, 35 (6):347-356. Worthington J, Lew JB, Feletto E, Holden CA, Worthley DL, Miller C, Canfell K: Improving Australian National Bowel Cancer Screening Program outcomes through increased participation and cost-effective investment . PLoS One 2020, 15 (2):e0227899. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019 . Lancet (London, England) 2020, 396 (10258):1223-1249. Augustus GJ, Ellis NA: Colorectal Cancer Disparity in African Americans: Risk Factors and Carcinogenic Mechanisms . The American journal of pathology 2018, 188 (2):291-303. Sung JJY, Chiu HM, Jung KW, Jun JK, Sekiguchi M, Matsuda T, Kyaw MH: Increasing Trend in Young-Onset Colorectal Cancer in Asia: More Cancers in Men and More Rectal Cancers . The American journal of gastroenterology 2019, 114 (2):322-329. 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Luo T, Zhou J, Yang J, Xie Y, Wei Y, Mai H, Lu D, Yang Y, Cui P, Ye LJJoMIR: Early warning and prediction of scarlet fever in China using the Baidu search index and autoregressive integrated moving average with explanatory variable (ARIMAX) model: time series analysis . 2023, 25 :e49400. Naghavi M, Ong KL, Aali A, Ababneh HS, Abate YH, Abbafati C, Abbasgholizadeh R, Abbasian M, Abbasi-Kangevari M, Abbastabar HJTL: Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021 . 2024, 403 (10440):2100-2132. Beltrán-Sánchez H, Preston SH, Canudas-Romo V: An integrated approach to cause-of-death analysis: cause-deleted life tables and decompositions of life expectancy . Demographic research 2008, 19 :1323. Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015 . Lancet (London, England) 2016, 388 (10053):1813-1850. Zhang T, Guo Y, Qiu B, Dai X, Wang Y, Cao X: Global, regional, and national trends in colorectal cancer burden from 1990 to 2021 and projections to 2040 . Front Oncol 2024, 14 :1466159. Mousavi SE, Ilaghi M, Hamidi Rad R, Nejadghaderi SA: Epidemiology and socioeconomic correlates of colorectal cancer in Asia in 2020 and its projection to 2040 . Scientific Reports 2025, 15 (1):26639. Yin Y, Zhang X: Analysis of trends in the burden of colorectal cancer in China and globally from 1990 to 2021 with projections for the next 15 years: a cross-sectional study based on the GBD database . Frontiers in public health 2025, 13 :1518536. Tian H, Xie X, Li X, Pang Y, Xie J: Global burden and projection of colorectal cancer attributable to low whole-grain diets: an analysis of GBD 2021 data with Bayesian age-period-cohort modeling . Front Oncol 2025, 15 :1572053. Wang D, Tan M, Nov P: Southeast Asia burden and trend of Gastrointestinal tract cancers from 1990 to 2021 and its prediction to 2050: findings from the Global Burden of Disease Study 2021 . International journal of colorectal disease 2025, 40 (1):60. Su J, Liang Y, He X: The global burden and trends analysis of early-onset colorectal cancer attributable to dietary risk factors in 204 countries and territories, 1990-2019: a secondary analysis for the global burden of disease study 2019 . Frontiers in nutrition 2024, 11 :1384352. Tables Tables 1 and 2 are available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files Table1.xlsx Table2.xlsx TableS1.xlsx TableS2.xlsx TableS3.xlsx TableS4.xlsx TableS5.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":75322198,"visible":true,"origin":"","legend":"\u003cp\u003eAge- and sex-specific burden of colorectal cancer in Australia (A–D), China (E–H), Japan (I–L), and Republic of Korea (M–P) in 2021. Red bars represent female counts, blue bars represent male counts. Solid lines represent age-standardized rates for females (red) and males (blue).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/f6bbbdcf822adbd5aa1d24ef.png"},{"id":91843188,"identity":"dcd98ce4-85a7-47a1-a372-dd59903d5830","added_by":"auto","created_at":"2025-09-22 10:05:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27700557,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends in prevalence (A, E, I, M), incidence (B, F, J, N), deaths (C, G, K, O), and DALYs (D, H, L, P) of colorectal cancer in Australia (A–D), China (E–H), Japan (I–L), and Republic of Korea (M–P) from 1990 to 2021. Bars represent annual case numbers for males (blue) and females (red), while solid lines represent age-standardized rates (ASRs) for males (blue) and females (red), with shaded areas indicating 95% uncertainty intervals (UI).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/bc3d4451dc29113a73cfc2a9.png"},{"id":91843177,"identity":"51a09c6a-5fb8-40c8-aa84-44c513792978","added_by":"auto","created_at":"2025-09-22 10:05:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22199842,"visible":true,"origin":"","legend":"\u003cp\u003eJoinpoint regression analysis of age-standardized prevalence (A), incidence (B), mortality (C), and disability-adjusted life years (DALYs) (D) of colorectal cancer in Australia, China, Japan, and Republic of Korea from 1990 to 2021.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/f388c48e01b4f5edf62cd587.png"},{"id":91843170,"identity":"bc2c1808-2d05-4386-95b8-9a8802097db9","added_by":"auto","created_at":"2025-09-22 10:05:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2785560,"visible":true,"origin":"","legend":"\u003cp\u003eForecasted trends of age-standardized rates for colorectal cancer in Australia, China, Japan, and the Republic of Korea from 1990 to 2041 using ARIMA models. (A) ASPR; (B) ASIR; (C) ASMR; (D) ASDR.\u003cbr\u003e\nSolid lines represent historical trends from 1990 to 2021, and dashed lines represent ARIMA-based predictions from 2022 to 2041. Shaded areas indicate 95% UI\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/650be8b6d76ea9d411a4a384.png"},{"id":91843173,"identity":"fcf83ecd-c4ed-4a7b-957e-91b2db3104f4","added_by":"auto","created_at":"2025-09-22 10:05:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":10130387,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between ASRs of CRC and theSDI in Australia, China, Japan, and the Republic of Korea from 1990 to 2020.\u003cbr\u003e\n(A) ASPR vs. SDI; (B) ASIR vs. SDI; (C) ASMR vs. SDI; (D) ASDR vs. SDI. Pearson’s correlation coefficient (R) and \u003cem\u003ep\u003c/em\u003e-value are shown for each country.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/9773dd799e8e4b152e29df19.png"},{"id":91845551,"identity":"62d4d808-9411-4872-8250-49cea9fe3bd7","added_by":"auto","created_at":"2025-09-22 10:13:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":905597,"visible":true,"origin":"","legend":"\u003cp\u003eDecomposition of changes in CRC burden from 1990 to 2021 in Australia, China, Japan, and the Republic of Korea. (A) Prevalence; (B) Incidence; (C) Deaths; (D) DALYs. Each bar represents the absolute change in case numbers attributable to three components: population aging (orange), population growth (cyan), and epidemiological change (yellow). Black diamonds indicate the net total burden change.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/e8416117d442cc84e63d3abb.png"},{"id":91845554,"identity":"2e6c9ddc-9619-4c65-a149-492bc935e008","added_by":"auto","created_at":"2025-09-22 10:13:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1415998,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of CRC deaths (A) and disability-adjusted life years (DALYs) (B) attributable to six modifiable risk factors—dietary risks, high alcohol use, high body-mass index, high fasting plasma glucose, low physical activity, and tobacco use—in Australia, China, Japan, and the Republic of Korea in 2021, stratified by sex (both sexes, male, female). Bars represent the proportion of total CRC burden attributable to each risk factor.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/d5fa8d50a7f530d68dc923f3.png"},{"id":91843166,"identity":"cb852d7f-9a4a-4861-a8be-ac494e065bf1","added_by":"auto","created_at":"2025-09-22 10:05:14","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18241,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/737d5056e0c3d7f31b9726ec.xlsx"},{"id":91843167,"identity":"0f849def-fa33-4834-8e38-4a168e73ba57","added_by":"auto","created_at":"2025-09-22 10:05:14","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13018,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/7828f04a485867d04a8fe109.xlsx"},{"id":91847121,"identity":"55775ec7-f182-46e6-a188-fe2700f3f84b","added_by":"auto","created_at":"2025-09-22 10:21:14","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":161080,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/09a7f3dac361544644ec26c9.xlsx"},{"id":91843174,"identity":"5056686b-5876-44b8-b263-537f17244ba3","added_by":"auto","created_at":"2025-09-22 10:05:15","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":585947,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/384934bdc587f09fcb225b09.xlsx"},{"id":91845552,"identity":"413439b4-2ffc-41d3-81c3-2183bf7cc921","added_by":"auto","created_at":"2025-09-22 10:13:14","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":12218,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/21b6e81c22d83e578e36f42e.xlsx"},{"id":91845557,"identity":"d083f9c0-d094-4e77-93d5-1cc895e091dc","added_by":"auto","created_at":"2025-09-22 10:13:15","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":17395,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/fc6ffc965a546c5a7fd90d57.xlsx"},{"id":91843179,"identity":"15c86fb5-8ef0-488a-b53c-6d1d0def210d","added_by":"auto","created_at":"2025-09-22 10:05:15","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":28982,"visible":true,"origin":"","legend":"","description":"","filename":"TableS5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7388179/v1/52c7ce5e3a0f76bd6f8ffd36.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Temporal Trends, Projections, and Risk Attribution of Colorectal Cancer in Australia, China, Japan, and Korea: GBD 2021 Analysis (1990–2041)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related death globally, with more than 1.9 million incident cases and 935,000 deaths in 2020[1]. Over recent decades, the global burden of CRC has shift\u0026nbsp;Here’s the same abstract with every abbreviation defined at first mention (JCO GO format preserved):\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003cbr\u003eTo generate implementation-ready evidence on \u003cstrong\u003ecolorectal cancer (CRC)\u003c/strong\u003e burden and prevention priorities across four Asia–Pacific countries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients and Methods\u003c/strong\u003e\u003cbr\u003eWe analyzed \u003cstrong\u003eGlobal Burden of Disease 2021 (GBD 2021)\u003c/strong\u003e estimates for Australia, China, Japan, and the \u003cstrong\u003eRepublic of Korea (Korea)\u003c/strong\u003e for 1990–2021. Outcomes included prevalence, incidence, mortality, and \u003cstrong\u003edisability-adjusted life years (DALYs)\u003c/strong\u003e as counts and \u003cstrong\u003eage-standardized rates (ASRs)\u003c/strong\u003e with 95% \u003cstrong\u003euncertainty intervals (UIs)\u003c/strong\u003e. For clarity, ASR components were the \u003cstrong\u003eage-standardized prevalence rate (ASPR)\u003c/strong\u003e, \u003cstrong\u003eage-standardized incidence rate (ASIR)\u003c/strong\u003e, \u003cstrong\u003eage-standardized mortality rate (ASMR)\u003c/strong\u003e, and \u003cstrong\u003eage-standardized disability-adjusted life-year rate (ASDR)\u003c/strong\u003e. Temporal trends used log-linear models to derive \u003cstrong\u003eaverage annual percent change (AAPC)\u003c/strong\u003e and Joinpoint regression; future trajectories (2022–2041) applied \u003cstrong\u003eautoregressive integrated moving average (ARIMA)\u003c/strong\u003e models. We performed Das Gupta decomposition (population growth, population aging, and epidemiologic change), assessed correlations with the \u003cstrong\u003eSocio-demographic Index (SDI)\u003c/strong\u003e, and summarized sex-stratified \u003cstrong\u003epopulation-attributable fractions (PAFs)\u003c/strong\u003e for six modifiable risks (dietary risks, high \u003cstrong\u003ebody mass index (BMI)\u003c/strong\u003e, high fasting plasma glucose, low physical activity, alcohol use, and tobacco use).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;China had the largest counts in 2021; Japan had the highest ASPR. Men bore higher incidence, mortality, and DALY rates, with widening male disadvantages in China and Korea. From 1990–2021, ASPR/ASIR rose in China and Korea, while Australia’s ASPR was stable and ASIR declined; ASMR/ASDR fell in all countries, greatest in Australia. Decomposition attributed rising counts primarily to aging (notably China/Japan) with epidemiologic change contributing in China/Korea. SDI correlated inversely with ASMR/ASDR. Dietary risks were the leading contributors to deaths and DALYs, followed by high BMI and high fasting plasma glucose; PAFs were consistently higher in men. Forecasts suggest continued increases in prevalence/incidence in China/Korea, sustained declines in severity endpoints in Australia, and stability or gradual improvement in Japan through 2041.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Priorities include scaling high-quality screening and integrated risk-factor control—especially for men—in China and Korea, and sustaining early detection and survivorship gains in Japan and Australia. Findings support resource-appropriate implementation strategies in diverse health-system contexts.\u003c/p\u003e\n\u003cp\u003edevelopment and demographic transitions, presents a unique setting for understanding CRC epidemiology. Nations such as China and Korea are experiencing surges in CRC burden, whereas countries like Japan and Australia have seen stabilization or declines in age-standardized mortality rates \u003cstrong\u003e(ASMR)\u0026nbsp;\u003c/strong\u003edue to effective screening and prevention programs[2-4].\u003c/p\u003e\n\u003cp\u003eCRC burden is modulated not only by demographic changes but also by modifiable lifestyle-related exposures, including dietary risks (e.g., low fiber intake, high red and processed meat consumption), obesity, alcohol consumption, tobacco use, physical inactivity, and elevated fasting plasma glucose[5, 6]. While these risk factors have been individually studied, comparative estimates of their attributable burden across countries remain limited. The \u003cstrong\u003eGlobal Burden of Disease (GBD)\u003c/strong\u003e 2021 study enables standardized estimation of population-attributable fractions (PAFs), facilitating inter-country comparison of preventable CRC burden. Understanding these differences is essential for informing tailored public health interventions, particularly in settings undergoing rapid epidemiological transitions.\u003c/p\u003e\n\u003cp\u003eMoreover, substantial variation exists in CRC burden by sex and age. Males consistently experience higher CRC incidence and mortality than females, likely due to behavioral and biological factors[6]. Aging remains a key determinant of CRC risk, with individuals aged ≥50 years accounting for over 80% of cases in most countries[7]. However, trends in younger adults are also emerging, prompting interest in early-onset CRC and the influence of societal shifts such as sedentary behavior and processed food consumption. In parallel, \u003cstrong\u003esociodemographic indices (SDI)\u003c/strong\u003e—a composite of fertility, education, and income—have shown strong associations with CRC burden trajectories, highlighting the intersection of development and disease risk[8, 9].\u003c/p\u003e\n\u003cp\u003eDespite these known drivers, few studies have comprehensively assessed and compared the full scope of CRC burden, temporal trends, future forecasts, and risk factor attribution across countries with distinct demographic and health system profiles. To address this gap, we conducted a comparative analysis of CRC burden in Australia, China, Japan, and the Republic of Korea using GBD 2021 data. We quantified CRC incidence, prevalence, mortality, and DALYs from 1990 to 2021, examined temporal trends via Joinpoint and log-linear regression, forecasted future burden to 2041 using autoregressive integrated moving average\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eARIMA\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003cstrong\u003emodels,\u003c/strong\u003e and explored associations with SDI. Furthermore, we performed decomposition analyses to disentangle the effects of population growth, aging, and epidemiological change, and estimated the burden attributable to six key modifiable risk factors. These findings aim to inform region-specific prevention strategies and support evidence-based policymaking in the Asia–Pacific region.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch2\u003eData sources\u003c/h2\u003e\n\u003cp\u003eThis study utilized publicly available data from the \u003cstrong\u003eGlobal Burden of Disease Study 2021 (GBD 2021)\u003c/strong\u003e, coordinated by the \u003cstrong\u003eInstitute for Health Metrics and Evaluation (IHME)\u003c/strong\u003e. All data were accessed via the Global Health Data Exchange (GHDx) and GBD Results Tool (https://vizhub.healthdata.org/gbd-results/). We extracted annual estimates of four key epidemiological indicators for CRC\u0026mdash;prevalence, incidence, mortality, and disability-adjusted life years (DALYs)\u0026mdash;from 1990 to 2021 for Australia, China, Japan, and the Republic of Korea. Data included both absolute numbers and age-standardized rates (ASRs), disaggregated by sex and 5-year age groups.\u003c/p\u003e\n\u003cp\u003eThe GBD framework defines CRC according to the International Classification of Diseases (ICD) codes: \u003cstrong\u003eICD-10: C18\u0026ndash;C20\u003c/strong\u003e and \u003cstrong\u003eICD-9: 153\u0026ndash;154\u003c/strong\u003e, ensuring consistency across countries and over time. DALYs were calculated as the sum of years of life lost (YLLs) due to premature mortality and years lived with disability (YLDs), using standardized methods and disability weights defined by the GBD protocol[10]\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003ch4\u003eDescriptive burden assessment\u003c/h4\u003e\n\u003cp\u003eWe first described the \u003cstrong\u003eepidemiological burden in 2021\u003c/strong\u003e, reporting the number and age-standardized rates of CRC prevalence, incidence, deaths, and DALYs across the four countries, along with corresponding 95% uncertainty intervals (UIs). Age-standardization was performed using the \u003cstrong\u003eGBD global reference population\u003c/strong\u003e, enabling meaningful inter-country comparisons. Sex-specific and age-specific distributions were visualized to highlight demographic variations.\u003c/p\u003e\n\u003ch4\u003eTemporal trends (1990\u0026ndash;2021)\u003c/h4\u003e\n\u003ch4\u003eTo assess temporal trends in colorectal cancer burden from 1990 to 2021, we calculated the percentage change (PC) and average annual percent change (AAPC) for each indicator (incidence, prevalence, mortality, DALYs), stratified by location, sex, and metric type.\u003cbr\u003e\u0026nbsp;PC was defined as the relative change between 1990 and 2021:\u003cbr\u003e\u0026nbsp;PC = ((Value_2021 - Value_1990) / Value_1990) \u0026times; 100\u003cbr\u003e\u0026nbsp;AAPC was estimated by fitting a log-linear regression model:\u003cbr\u003e\u0026nbsp;log(y) = \u0026beta;0 + \u0026beta;1 \u0026times; year, \u0026nbsp; \u0026nbsp; AAPC = (e^\u0026beta;1 - 1) \u0026times; 100\u003cbr\u003e\u0026nbsp;Here, y represents the annual burden estimates. 95% confidence intervals (CIs) were derived from the model. To avoid undefined log values, zero or negative data were replaced with the smallest positive non-zero value. Models with insufficient data were excluded. All analyses were conducted using R (v4.2.2) with the dplyr, tidyr, and base stats packages.\u003c/h4\u003e\n\u003ch4\u003eJoinpoint regression\u003c/h4\u003e\n\u003cp\u003eWe applied \u003cstrong\u003eJoinpoint regression analysis\u003c/strong\u003e to identify inflection points and characterize the evolution of CRC burden across time. Using the Joinpoint Regression Program (version 4.9.1.0, National Cancer Institute, USA), we modeled the annual ASRs and estimated \u003cstrong\u003eannual percent changes (APCs)\u003c/strong\u003e and \u003cstrong\u003eaverage annual percent change (AAPC)\u003c/strong\u003e with \u003cstrong\u003eMonte Carlo permutation tests\u003c/strong\u003e to identify significant joinpoints (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) [11].\u003c/p\u003e\n\u003ch4\u003eForecasting future burden (2022\u0026ndash;2041)\u003c/h4\u003e\n\u003cp\u003eTo project the CRC burden from 2022 to 2041, we applied \u003cstrong\u003eARIMA\u0026nbsp;\u003c/strong\u003emodels to the ASRs of each indicator and country. Model selection was based on \u003cstrong\u003eAkaike information criterion (AIC)\u003c/strong\u003e and \u003cstrong\u003eBayesian information criterion (BIC)\u003c/strong\u003e, and model adequacy was assessed using \u003cstrong\u003eLjung-Box tests\u003c/strong\u003e and residual diagnostics. Forecasting was performed using the\u0026nbsp;\u003ccode\u003eforecast\u003c/code\u003e and\u0026nbsp;\u003ccode\u003etseries\u003c/code\u003e packages in \u003cstrong\u003eR software (version 4.2.2)\u003c/strong\u003e [12].\u003c/p\u003e\n\u003ch4\u003eSocio-demographic association\u003c/h4\u003e\n\u003cp\u003eWe evaluated the relationship between CRC burden and \u003cstrong\u003eSDI\u003c/strong\u003e using \u003cstrong\u003ePearson correlation coefficients\u003c/strong\u003e between annual SDI values and ASRs from 1990 to 2020 for each country. SDI is a composite indicator ranging from 0 to 1, incorporating measures of fertility, education, and income per capita [13]. Trends were visualized to assess the dynamic relationship between CRC burden and socioeconomic development.\u003c/p\u003e\n\u003ch4\u003eDecomposition analysis\u003c/h4\u003e\n\u003cp\u003eTo disentangle the drivers of changes in absolute burden over time, we performed a \u003cstrong\u003econtribution decomposition analysis\u003c/strong\u003e that attributed the net change in CRC cases, deaths, and DALYs between 1990 and 2021 to three factors: \u003cstrong\u003epopulation growth\u003c/strong\u003e, \u003cstrong\u003epopulation aging\u003c/strong\u003e, and \u003cstrong\u003eepidemiological change\u003c/strong\u003e (change in age-specific rates). This was conducted using \u003cstrong\u003eDas Gupta\u0026rsquo;s method\u003c/strong\u003e, a validated demographic decomposition technique [14].\u003c/p\u003e\n\u003ch4\u003eRisk factor attribution\u003c/h4\u003e\n\u003cp\u003eTo quantify the burden of CRC attributable to modifiable risk factors, we extracted GBD 2021 estimates of \u003cstrong\u003epopulation attributable fractions (PAFs)\u003c/strong\u003e for six Level 2 risks from the \u003cstrong\u003eGBD Comparative Risk Assessment framework\u003c/strong\u003e: dietary risks, high body-mass index, high fasting plasma glucose, alcohol use, tobacco use, and low physical activity. Sex-specific proportions of CRC deaths and DALYs attributable to each risk were summarized for each country in 2021 [15].\u003c/p\u003e\n\u003cp\u003eAll statistical analyses and graphical visualizations were conducted using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was assessed using two-sided tests, with P-values \u0026lt; 0.05 considered indicative of a statistically significant\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003eEpidemiological burden of CRC among Australia, China, Japan, and Korea in 2021\u003c/h3\u003e\n\u003cp\u003eIn 2021, CRC posed a substantial but heterogeneous burden across the four Asia–Pacific countries (Table 1). \u003cstrong\u003eChina\u003c/strong\u003e reported the highest absolute burden, with 3.61 million prevalent cases (95% UI 2.91–4.35 million; age-standardized prevalence rate [ASPR] 168.6 per 100,000 [95% UI 136.6–203.1]), 658,321 incident cases (95% UI 532.0–798.1 thousand; age-standardized incidence rate [ASIR] 31.4 per 100,000 [95% UI 25.5–38.0]), 287,000 deaths (95% UI 221.4–361.7 thousand; age-standardized mortality rate [ASMR] 21.9 per 100,000 [95% UI 16.9–28.1]), and 2.28 million disability-adjusted life years (DALYs; 95% UI 1.75–2.95 million; age-standardized DALY rate [ASDR] 219.3 per 100,000 [95% UI 169.6–281.0]). \u003cstrong\u003eJapan\u003c/strong\u003e ranked second in prevalence with 1.00 million cases (95% UI 0.90–1.07 million; ASPR 310.3 per 100,000 [95% UI 285.2–326.6]) and reported 417,000 incident cases (95% UI 382.7–457.1 thousand; ASIR 28.5 per 100,000 [95% UI 26.2–31.1]), 60,300 deaths (95% UI 55.2–65.5 thousand; ASMR 16.7 per 100,000 [95% UI 15.3–18.2]), and 3.64 million DALYs (95% UI 3.35–3.94 million; ASDR 202.4 per 100,000 [95% UI 186.7–219.1]). \u003cstrong\u003eRepublic of Korea\u003c/strong\u003e had 200,854 prevalent cases (95% UI 168.3–232.9 thousand; ASPR 214.8 per 100,000 [95% UI 180.1–249.2]), 52,700 incident cases (95% UI 45.0–60.6 thousand; ASIR 25.6 per 100,000 [95% UI 21.9–29.5]), 15,800 deaths (95% UI 13.5–18.1 thousand; ASMR 18.1 per 100,000 [95% UI 15.6–20.8]), and 1.05 million DALYs (95% UI 0.87–1.23 million; ASDR 198.5 per 100,000 [95% UI 165.7–234.4]). \u003cstrong\u003eAustralia\u003c/strong\u003e, despite its smaller population, exhibited the highest ASPR (270.9 per 100,000 [95% UI 241.2–305.4]), with 116,744 prevalent cases (95% UI 103.3–132.1\u0026nbsp;thousand), 20,900 incident cases (95% UI 18.6–23.5\u0026nbsp;thousand; ASIR 26.3 per 100,000 [95% UI 23.4–29.5]), 5,800 deaths (95% UI 5.1–6.6\u0026nbsp;thousand; ASMR 13.5 per 100,000 [95% UI 11.8–15.4]), and 328,000 DALYs (95% UI 286.0–374.5\u0026nbsp;thousand; ASDR 152.7 per 100,000 [95% UI 133.1–174.5]).\u003c/p\u003e\n\u003cp\u003eAge- and sex-specific analysis revealed notable heterogeneity across the four countries (Table\u0026nbsp;S1, Figure\u0026nbsp;1). CRC burden increased sharply with age, peaking between 70–84\u0026nbsp;years for incidence, mortality, and DALYs in all countries. Males consistently exhibited higher incidence, mortality, and DALY rates than females, with male-to-female mortality ratios exceeding 1.3 in China and Korea. The proportion of CRC cases among individuals aged ≥50\u0026nbsp;years exceeded 80% in all countries, underscoring the dominant contribution of aging populations. Notably, Australia and Japan showed a greater share of CRC burden in those aged ≥75\u0026nbsp;years compared to China and Korea, reflecting their more advanced population aging. These findings highlight substantial demographic and sex-related differences in CRC epidemiology across the Asia–Pacific region.\u003c/p\u003e\n\u003ch3\u003eTemporal trends of colorectal cancer burden from 1990 to 2021\u003c/h3\u003e\n\u003cp\u003eFrom 1990 to 2021, the four Asia–Pacific countries showed heterogeneous temporal trends in CRC burden (Table 1, Figure 2). China experienced the most remarkable growth across all indicators: prevalence increased from 635,609 (95% UI 548,090–729,557) to 3.61 million (95% UI 2.91–4.35 million), with a PC of +467.3% and an AAPC of +6.08% (95% UI 5.91–6.25); the ASPR rose from 69.9 to 168.6 per 100,000 (PC +141.2%, AAPC +3.17%, 95% UI 3.03–3.31). Incidence more than quadrupled (from 158,389 to 658,321; PC +315.6%, AAPC +4.87%, 95% UI 4.70–5.05), with the ASIR increasing from 19.0 to 31.4 per 100,000 (PC +65.1%, AAPC +1.75%, 95% UI 1.64–1.87). Mortality and disability-adjusted life years (DALYs) also climbed substantially, with deaths rising from 119,303 to 275,129 (PC +130.6%, AAPC +2.69%, 95% UI 2.58–2.79), while ASMR declining from 15.49 to 13.64 per 100,000 (PC −11.9%, AAPC −0.49%, 95% UI −0.55– −0.43), and ASDR from 390.63 to 331.73 per 100,000 (PC −15.10%, AAPC −0.62%, 95% UI −0.71– −0.54). Korea displayed similar upward trends, particularly for prevalence (ASPR increased from 82.6 to 214.8 per 100,000; PC +160.1%, AAPC +3.44%, 95% UI 2.90–3.99). By contrast, Japan and Australia demonstrated relatively stable or slightly declining age-standardized rates, with Japan maintaining moderate increases in prevalence (ASPR 250.6 to 310.3 per 100,000; PC +23.8%, AAPC +0.60%, 95% UI 0.51–0.69) but limited changes in incidence and mortality, while Australia exhibited minimal variation in prevalence (ASPR 260.6 to 270.9 per 100,000; PC +3.9%, AAPC +0.07%, 95% UI −0.14–0.29) and a modest decline in mortality (ASMR from 23.8 to 13.98 per 100,000; PC −41.3%, AAPC −1.95%, 95% UI −2.05– −1.85).\u003c/p\u003e\n\u003cp\u003eAcross all four countries, males consistently exhibited higher CRC burden than females for prevalence, incidence, mortality, and DALYs (Figure 2; Table 1). The sex gap was most evident in China and the Republic of Korea: male incidence rates increased faster than female rates (China ASIR AAPC: males 2.32% vs. females 0.86%; Korea: 2.35% vs. 1.47%), while declines in ASMR and ASDR were steeper in women, indicating a gradually widening male disadvantage (Figure 2E–H, M–P; Table 1). In Australia and Japan, men also had higher rates, but the trajectories between sexes were largely parallel—incidence was flat to modestly changing and mortality/DALY rates declined in both sexes—so the sex gap remained comparatively stable (Figure 2A–D, I–L; Table 1).\u003c/p\u003e\n\u003cp\u003eTaken together, absolute numbers rose in all four countries, but age-standardized patterns diverged. China and Korea showed clear increases in ASPR and ASIR (e.g., China ASPR 69.9→168.6 per 100,000; ASIR 19.0→31.4; Korea ASPR 82.6→214.8; ASIR 19.3→35.5), while ASMR and ASDR declined in every country (China ASMR 15.49→13.64; ASDR 390.6→331.7; Korea ASMR 14.12→12.56; ASDR 336.1→267.4). Japan had moderate rises in prevalence and a small increase in incidence (ASPR 250.6→310.3; ASIR 43.2→48.7) alongside decreases in mortality and DALYs (ASMR 19.0→15.9; ASDR 445.6→358.4). Australia showed minimal change in prevalence (ASPR 260.6→270.9) but declines in incidence, mortality, and DALYs (ASIR 48.5→42.7; ASMR 23.8→14.0; ASDR 552.3→315.5). These patterns indicate that improvements in survival and disease management (reflected by falling ASMR/ASDR) co-occurred with rising detection/underlying risk (rising ASIR/ASPR) in China and Korea, whereas Japan—and especially Australia—achieved broader reductions across severity endpoints (Figure 2; Table 1).\u003c/p\u003e\n\u003ch3\u003eJoinpoint Regression Analysis of Colorectal Cancer Trends (1990–2021)\u003c/h3\u003e\n\u003cp\u003eJoinpoint regression analysis was conducted to characterize the temporal trends of CRC burden from 1990 to 2021 in Australia, China, Japan, and the Republic of Korea. We report the AAPC with corresponding 95% UIs, along with significant joinpoints and segment-specific APCs, based on the ASRs of prevalence, incidence, mortality, and DALYs (Table S3, S4; Figure 3).\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eAustralia:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePrevalence\u003c/strong\u003e: The overall trend was slightly decreasing (AAPC:\u0026nbsp;\u003cstrong\u003e–0.27%\u003c/strong\u003e, 95% UI: –0.46 to –0.07), with joinpoints in 1996 and 2008. The trend rose during 1990–1996 (APC:\u0026nbsp;\u003cstrong\u003e+1.81%\u003c/strong\u003e) but declined steadily afterward.\u0026nbsp;\u003cstrong\u003eIncidence\u003c/strong\u003e: A decreasing trend was observed (AAPC:\u0026nbsp;\u003cstrong\u003e–0.42%\u003c/strong\u003e, 95% UI: –0.60 to –0.24), with a turning point in 2000, after which the decline accelerated (APC: –1.26%).\u0026nbsp;\u003cstrong\u003eMortality\u003c/strong\u003e: A sustained and substantial decrease was seen (AAPC:\u0026nbsp;\u003cstrong\u003e–1.71%\u003c/strong\u003e, 95% UI: –2.01 to –1.40), with a rapid decline from 1996 onwards.\u0026nbsp;\u003cstrong\u003eDALYs\u003c/strong\u003e: The greatest reduction among all countries was found in DALYs (AAPC:\u0026nbsp;\u003cstrong\u003e–1.80%\u003c/strong\u003e, 95% UI: –2.00 to –1.60), indicating continuous improvements in CRC outcomes over three decades.\u003c/h4\u003e\n\u003ch4\u003e\u003cstrong\u003eChina: Prevalence\u003c/strong\u003e: A steep increase was observed (AAPC:\u0026nbsp;\u003cstrong\u003e+2.95%\u003c/strong\u003e, 95% UI: 2.80 to 3.11), with major accelerations post-1997 and 2008 (APCs: +3.82% and +2.63%, respectively).\u0026nbsp;\u003cstrong\u003eIncidence\u003c/strong\u003e: The rate rose significantly (AAPC:\u0026nbsp;\u003cstrong\u003e+1.66%\u003c/strong\u003e, 95% UI: 1.39 to 1.94), reflecting increasing CRC detection and possibly changing risk exposures.\u0026nbsp;\u003cstrong\u003eMortality\u003c/strong\u003e: A modest upward trend was noted (AAPC:\u0026nbsp;\u003cstrong\u003e+0.42%\u003c/strong\u003e, 95% UI: 0.25 to 0.59), with joinpoints in 1996 and 2015 suggesting a partial stabilization in recent years.\u0026nbsp;\u003cstrong\u003eDALYs\u003c/strong\u003e: Despite lower mortality gains, DALYs continued to increase (AAPC:\u0026nbsp;\u003cstrong\u003e+1.29%\u003c/strong\u003e, 95% UI: 1.12 to 1.46), likely due to a higher disease burden in younger populations and growing prevalence.\u003c/h4\u003e\n\u003ch4\u003e\u003cstrong\u003eJapan: Prevalence\u003c/strong\u003e: AAPC of\u0026nbsp;\u003cstrong\u003e+0.67%\u003c/strong\u003e (95% UI: 0.50 to 0.84) indicated a mild upward trend, with leveling-off seen after the early 2000s.\u003cstrong\u003eIncidence\u003c/strong\u003e: The trajectory remained largely stable (AAPC:\u0026nbsp;\u003cstrong\u003e+0.36%\u003c/strong\u003e, 95% UI: 0.09 to 0.64); after peaking in 2002–2016 (APC: –0.84%), incidence began to decline.\u0026nbsp;\u003cstrong\u003eMortality\u003c/strong\u003e: A consistent decline was detected (AAPC:\u0026nbsp;\u003cstrong\u003e–0.59%\u003c/strong\u003e, 95% UI: –0.77 to –0.41), with the fastest drop occurring between 2012–2021.\u003cstrong\u003eDALYs\u003c/strong\u003e: A downward trend was also observed (AAPC:\u0026nbsp;\u003cstrong\u003e–0.72%\u003c/strong\u003e, 95% UI: –0.88 to –0.56), consistent with improved screening and survival.\u003c/h4\u003e\n\u003ch4\u003e\u003cstrong\u003eRepublic of Korea: Prevalence\u003c/strong\u003e: The most pronounced increase among the four countries (AAPC:\u0026nbsp;\u003cstrong\u003e+3.08%\u003c/strong\u003e, 95% UI: 2.88 to 3.28), with APCs exceeding +4% during 1990–2002.\u003cstrong\u003eIncidence\u003c/strong\u003e: AAPC of\u0026nbsp;\u003cstrong\u003e+1.97%\u003c/strong\u003e (95% UI: 1.71 to 2.22), reflecting rising case numbers, but a noticeable slowdown was observed after 2010.\u003cstrong\u003eMortality\u003c/strong\u003e: Although initially increasing, mortality rates plateaued post-2010. Overall, AAPC was\u0026nbsp;\u003cstrong\u003e–0.48%\u003c/strong\u003e (95% UI: –0.60 to –0.37), suggesting improved CRC management.\u0026nbsp;\u003cstrong\u003eDALYs\u003c/strong\u003e: AAPC was\u0026nbsp;\u003cstrong\u003e–0.50%\u003c/strong\u003e (95% UI: –0.66 to –0.33), marking a transition from growth to decline around 2010–2016.\u003c/h4\u003e\n\u003ch3\u003eThis analysis reveals divergent epidemiologic trajectories of CRC across Asia–Pacific countries.\u0026nbsp;China and Korea\u0026nbsp;exhibited rising trends in most indicators, especially prevalence and incidence, while\u0026nbsp;Japan and Australia\u0026nbsp;showed declines in mortality and DALYs. These trends likely reflect differences in screening implementation, healthcare access, and risk factor transitions. The identified joinpoints align with periods of public health intervention and policy changes (e.g., national screening rollout in Korea and Japan).\u003c/h3\u003e\n\u003ch3\u003eForecasted Trends in Colorectal Cancer Burden (2022–2041)\u003c/h3\u003e\n\u003cp\u003eBased on ARIMA modeling, the future burden ofCRC shows heterogeneous trajectories across the four Asia–Pacific countries between 2022 and 2041 (Table S5, Figure 4). In \u003cstrong\u003eAustralia\u003c/strong\u003e, the ASPR is projected to remain stable, rising only slightly from 271.2 to 274.8 per 100,000, while ASIR is expected to plateau. In contrast, both ASMR and ASDR are anticipated to continue their steady declines, reaching 7.6 and 162.7 per 100,000 respectively by 2041, reflecting sustained advancements in screening and clinical management. In \u003cstrong\u003eChina\u003c/strong\u003e, CRC burden is forecasted to increase moderately, with ASPR rising from 171.0 to 186.1 and ASIR increasing from 38.2 to 41.0 per 100,000. Mortality rates are projected to stabilize, while ASDR is expected to show a slight upward trend, indicating the growing impact of CRC despite recent public health efforts. In \u003cstrong\u003eJapan\u003c/strong\u003e, prevalence is predicted to increase minimally, while incidence is expected to remain flat. Both mortality and DALY rates will likely decline further, maintaining Japan’s favorable trajectory in CRC control. In the \u003cstrong\u003eRepublic of Korea\u003c/strong\u003e, prevalence is forecasted to increase from 318.3 to 342.9 per 100,000, while incidence is expected to remain steady. Meanwhile, ASMR and ASDR are projected to decline progressively, indicating improved disease outcomes in recent years. Overall, Australia and Japan are expected to maintain favorable trends with reduced CRC burden, while China and Korea face ongoing challenges, particularly in prevalence and early detection.\u003c/p\u003e\n\u003ch3\u003eAssociation Between CRC Burden and SDI\u003c/h3\u003e\n\u003cp\u003eTo explore the relationship between SDI and CRC burden, we analyzed the correlation between the SDI and ASPR, ASIR, ASMR, and ASDR from 1990 to 2020 across the four countries (Figure 5).\u003c/p\u003e\n\u003cp\u003eAcross all indicators, \u003cstrong\u003eChina\u003c/strong\u003e and the \u003cstrong\u003eRepublic of Korea\u003c/strong\u003e demonstrated strong positive correlations between SDI and both ASPR and ASIR (R = 1.0, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), indicating that CRC prevalence and incidence increased consistently with rising socioeconomic levels. In \u003cstrong\u003eAustralia\u003c/strong\u003e and \u003cstrong\u003eJapan\u003c/strong\u003e, however, these relationships were non-linear or even inverse. In Australia, ASPR remained relatively stable as SDI increased (R = 0.19), while in Japan, ASPR showed a slight negative association with SDI (R = –0.34, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eRegarding mortality (ASMR), all four countries exhibited \u003cstrong\u003enegative correlations\u003c/strong\u003e with SDI, suggesting that improvements in health systems and socioeconomic conditions have contributed to reduced mortality. This trend was particularly pronounced in \u003cstrong\u003eAustralia (R = –0.95)\u003c/strong\u003e and \u003cstrong\u003eJapan (R = –0.83)\u003c/strong\u003e, followed by the \u003cstrong\u003eRepublic of Korea (R = –0.68)\u003c/strong\u003e and \u003cstrong\u003eChina (R = –0.93)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eFor DALY rates (ASDR), a similar inverse pattern was observed, with stronger correlations in \u003cstrong\u003eAustralia (R = –0.93)\u003c/strong\u003e and \u003cstrong\u003eRepublic of Korea (R = –0.89)\u003c/strong\u003e, reflecting their effective disease management strategies. \u003cstrong\u003eJapan\u003c/strong\u003e and \u003cstrong\u003eChina\u003c/strong\u003e also showed significant negative correlations (R = –0.80 and –0.91, respectively), though the reduction in disease burden occurred at a slower pace compared to Australia.\u003c/p\u003e\n\u003ch3\u003eDecomposition analysis of changes in CRC burden (1990–2021)\u003c/h3\u003e\n\u003cp\u003eTo elucidate the driving forces behind the changes in CRC burden over the past three decades, we decomposed the total change in four key indicators—prevalence, incidence, deaths, and DALYs—into contributions from population aging, population growth, and epidemiological change across the four countries (Figure 6, Table 2).\u003c/p\u003e\n\u003cp\u003eIn \u003cstrong\u003eChina\u003c/strong\u003e, the total increases were substantial for all burden metrics, with prevalence rising by 2,352,628 cases, incidence by 499,932 cases, deaths by 377,740, and DALYs by 3,283,194. Aging emerged as the dominant contributor across all indicators, accounting for 39.9% to 60.3% of the total change, followed by epidemiological changes (ranging from 35.8% to 46.3%), and a relatively minor contribution from population growth in deaths and DALYs.\u003c/p\u003e\n\u003cp\u003eIn \u003cstrong\u003eJapan\u003c/strong\u003e, CRC burden also increased but to a lesser extent. The increases in prevalence (285,067), incidence (55,491), deaths (64,948), and DALYs (729,152) were primarily driven by aging, which contributed more than 70% in all indicators. Epidemiological change played a minor or even negative role, particularly in DALYs (−8.1%), indicating progress in treatment or early detection.\u003c/p\u003e\n\u003cp\u003eIn \u003cstrong\u003ethe Republic of Korea\u003c/strong\u003e, the total burden increased modestly, with prevalence, incidence, deaths, and DALYs rising by 51,501, 20,173, 17,100, and 202,278, respectively. Here again, aging was the predominant contributor to the increases (67.3%–85.6%), while epidemiological change had a minimal or negative impact, especially in deaths (−3.5%) and DALYs (−1.6%).\u003c/p\u003e\n\u003cp\u003eConversely, \u003cstrong\u003eAustralia\u003c/strong\u003e exhibited a different pattern. While prevalence (105,957) and incidence (9,474) rose over the period, both deaths (6,753) and DALYs (52,601) showed relatively stable or declining trends. Notably, the increase in DALYs was largely attributed to population aging (53,749), with epidemiological improvements leading to a substantial reduction (−116,205 DALYs, accounting for −220.9% of the change), offsetting the effects of population growth and aging.\u003c/p\u003e\n\u003cp\u003eThese findings highlight the dominant role of population aging in driving the CRC burden in the Asia–Pacific region, particularly in China, Japan, and Korea, while underscoring the mitigating effect of improved healthcare and prevention in Australia.\u003c/p\u003e\n\u003ch3\u003eRisk factor attribution analysis for CRC burden in 2021\u003c/h3\u003e\n\u003cp\u003eTo better understand the underlying contributors to CRC burden, we analyzed the proportion of CRC deaths and DALYs attributable to six modifiable risk factors—dietary risks, high alcohol use, high body mass index (BMI), high fasting plasma glucose, low physical activity, and tobacco use—in Australia, China, Japan, and the Republic of Korea, stratified by sex (Figure 7).\u003c/p\u003e\n\u003cp\u003eAmong all four countries, \u003cstrong\u003edietary risks\u003c/strong\u003e consistently accounted for the largest proportion of attributable burden in both deaths and DALYs, ranging from \u003cstrong\u003e35.9% to 41.4%\u003c/strong\u003e. In 2021, Australia had the highest proportion of CRC deaths attributable to dietary risks (41.2%), followed closely by Japan (40.3%), the Republic of Korea (39.8%), and China (37.3%). A similar pattern was observed for DALYs, with Japan (41.1%) and Australia (41.4%) topping the list. Males exhibited slightly higher attributable fractions than females in most countries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHigh BMI\u003c/strong\u003e was the second most important contributor, particularly in Australia, where it accounted for \u003cstrong\u003e13.9% of CRC deaths\u003c/strong\u003e and \u003cstrong\u003e14.4% of DALYs\u003c/strong\u003e. By contrast, the proportions in China (8.2% deaths, 8.6% DALYs) and Japan (5.3% deaths, 5.5% DALYs) were notably lower, although sex differences persisted across all nations. \u003cstrong\u003eHigh fasting plasma glucose\u003c/strong\u003e also contributed significantly, with proportions ranging from \u003cstrong\u003e6.3% to 10.1%\u003c/strong\u003e for deaths and \u003cstrong\u003e6.3% to 8.7%\u003c/strong\u003e for DALYs. China, Japan, and Korea showed relatively similar burdens, while Australia had a marginally higher fraction. \u003cstrong\u003eLow physical activity\u003c/strong\u003e showed a particularly strong impact in Australia, where it accounted for \u003cstrong\u003e12.6% of deaths\u003c/strong\u003e and \u003cstrong\u003e11.8% of DALYs\u003c/strong\u003e, whereas in China and Korea, the impact was generally lower (≤8.7%). \u003cstrong\u003eHigh alcohol use\u003c/strong\u003e and \u003cstrong\u003etobacco use\u003c/strong\u003e played lesser but still notable roles. Australia exhibited the highest proportion of CRC deaths and DALYs attributable to alcohol consumption (\u003cstrong\u003e11.4% and 12.3%\u003c/strong\u003e, respectively), followed by Korea and Japan. China’s alcohol-related burden remained the lowest among the four countries (0.8–0.9%).\u003c/p\u003e\n\u003cp\u003eOverall, these results emphasize that \u003cstrong\u003edietary modification, obesity control, and increased physical activity\u003c/strong\u003e represent key intervention targets for CRC prevention in the Asia–Pacific region, particularly for males. The relatively high burden attributable to modifiable lifestyle risks in Australia suggests both an opportunity and a need for intensified public health interventions.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study offers a comprehensive comparative analysis of the CRC burden in Australia, China, Japan, and the Republic of Korea, providing critical insight into the temporal evolution, underlying drivers, and potential future trajectories across the Asia\u0026ndash;Pacific region[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur findings confirm pronounced heterogeneity in CRC epidemiology across the four countries. From 1990 to 2021, China and the Republic of Korea showed clear increases in age-standardized prevalence (ASPR) and incidence (ASIR) alongside rising absolute numbers, whereas age-standardized mortality (ASMR) and DALY rates (ASDR) declined in all four countries. Japan exhibited a moderate rise in ASPR and a small increase in ASIR, with concurrent declines in ASMR/ASDR; Australia showed minimal change in ASPR, a decline in ASIR, and marked reductions in ASMR/ASDR. These divergent trajectories likely reflect differences in screening uptake and quality of care, the pace of population aging, and transitions in lifestyle-related risks across settings[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn 2021, China carried the highest absolute counts, consistent with its population size and ongoing demographic aging, whereas Japan recorded the highest ASPR among the four countries\u0026mdash;compatible with higher detection and longer post-diagnosis survival. Australia\u0026rsquo;s relatively low and falling ASMR/ASDR align with sustained improvements in screening pathways, early treatment, and survivorship care. The male disadvantage was evident in all countries and widened in China and Korea, driven by faster increases in male ASIR and relatively slower declines in male ASMR/ASDR, in line with higher exposure to tobacco, alcohol, and metabolic risks among men[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eJoinpoint and decomposition analyses indicate that population aging remains the dominant driver of growth in absolute burden\u0026mdash;particularly in China and Japan\u0026mdash;but epidemiological change (incidence dynamics linked to modifiable risks and health-system responses) contributed substantially in China and Korea. These results echo prior evidence that aging alone cannot explain the rising case load in rapidly developing contexts and underscore the role of dietary westernization, adiposity, hyperglycemia, and evolving screening practices[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLooking forward, our ARIMA projections suggest that China and Korea are likely to experience continued increases in prevalence and incidence, whereas Australia is projected to maintain broad declines across severity endpoints, and Japan to see stability or gradual decline in mortality and DALYs with modest changes in incidence. These patterns mirror global observations of improving survival but persistent or rising incidence where unfavorable risk profiles and incomplete screening coverage remain[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImportantly, our risk attribution analysis showed that dietary risks were the leading contributor to CRC deaths and DALYs across all four countries, followed by high BMI, high fasting plasma glucose, and low physical activity. These findings echo the Global Cancer Observatory\u0026rsquo;s assessment that unhealthy diets and obesity account for over one-third of CRC-related mortality worldwide (GLOBOCAN). Moreover, the higher attributable burden among men further emphasizes the need for sex-specific prevention strategies[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The findings also underscore the urgency of strengthening national policies around food environment regulation, physical activity promotion, and diabetes control\u0026mdash;particularly in China and Korea, where trends remain adverse.\u003c/p\u003e\u003cp\u003eThis study has several strengths. It leverages high-quality GBD 2021 data, incorporates advanced statistical modeling (joinpoint, ARIMA, decomposition), and provides cross-national comparisons over a 30-year period. However, limitations include the reliance on secondary data, which may be subject to underreporting or misclassification, particularly in low-resource settings. Additionally, the forecasts may not fully capture disruptive events such as COVID-19 or future screening policy changes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCRC burden across the Asia\u0026ndash;Pacific is heterogeneous. China and Korea show rising ASPR/ASIR with declining\u0026mdash;but still substantial\u0026mdash;ASMR/ASDR; Japan shows moderate increases in ASPR and slight increases in ASIR with declining severity endpoints; and Australia demonstrates stable ASPR, falling ASIR, and the largest declines in ASMR/ASDR. Men consistently bear higher burden, with an expanding sex gap in China and Korea. Population aging is the principal driver of increasing counts, but modifiable risks\u0026mdash;especially diet, adiposity, hyperglycemia, and inactivity\u0026mdash;remain critical levers. To curb future burden, China and Korea should prioritize expanding high-quality screening and risk-factor control with male-focused strategies, while Japan and Australia should sustain early detection and survivorship optimization. Region-specific policies that integrate risk reduction, equitable screening coverage, and high-value treatment pathways will be essential to bending both incidence and severity curves over the coming decades.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAAPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eaverage annual percent change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAIC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAkaike information criterion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eannual percent change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eARIMA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eautoregressive integrated moving average\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eASDR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eage-standardized disability-adjusted life-year rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eASIR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eage-standardized incidence rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eASMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eage-standardized mortality rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eASPR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eage-standardized prevalence rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eASR(s)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eage-standardized rate(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBIC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBayesian information criterion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ebody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI(s)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003econfidence interval(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecolorectal cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDALY(s)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003edisability-adjusted life year(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGBD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlobal Burden of Disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGHDx\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlobal Health Data Exchange\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGLOBOCAN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlobal Cancer Observatory cancer database (IARC)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICD-9/ICD-10\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInternational Classification of Diseases, Ninth/Tenth Revision\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIHME\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInstitute for Health Metrics and Evaluation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePAF(s)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epopulation-attributable fraction(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epercentage change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSDI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSocio-demographic Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUI(s)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003euncertainty interval(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGuodong Yang and Yujiao Zhang contributed equally to this work.\u003cbr\u003e\u0026nbsp;[Guodong Yang]: Conceptualization, data acquisition, statistical analysis, manuscript drafting, and critical revision.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Yujiao Zhang and Gang Zhou]: Data interpretation, literature review, and manuscript drafting.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Yaqi Zhang and Jiping Wang]: Statistical modeling (Joinpoint, ARIMA), figure preparation, and critical review.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Qibin Wu]: Methodology supervision, interpretation of results, and critical manuscript revision.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAll authors: Approved the final version of the manuscript and agree to be accountable for all aspects of the work.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe authors thank the Institute for Health Metrics and Evaluation (IHME) for providing access to the Global Burden of Disease database.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe authors have no conflict of interest.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe datasets used and/or analyzed in this study are publicly available from the Global Burden of Disease database:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ehttps://vizhub.healthdata.org/gbd-results/\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING INFORMATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis work was supported by the Special Scientific Research Fund for Medical Consortium of Hunan Provincial People\u0026apos;s Hospital (Grant No. 2022YLT005) and 2025 Natural Science Foundation of Hubei Province(Grant No.JCZRLH20250859).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis study used publicly available, de-identified data from the Global Burden of Disease 2021 database. Ethical approval and consent to participate were not required.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F: \u003cstrong\u003eGlobal Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries\u003c/strong\u003e. \u003cem\u003eCA Cancer J Clin \u003c/em\u003e2021, \u003cstrong\u003e71\u003c/strong\u003e(3):209-249.\u003c/li\u003e\n\u003cli\u003eMa R, Jing C, Zhang Y, Cao H, Liu S, Wang Z, Chen D, Zhang J, Wu Y, Wu J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eThe somatic mutation landscape of Chinese Colorectal Cancer\u003c/strong\u003e. \u003cem\u003eJ Cancer \u003c/em\u003e2020, \u003cstrong\u003e11\u003c/strong\u003e(5):1038-1046.\u003c/li\u003e\n\u003cli\u003eNam S, Choi YJ, Kim DW, Park EC, Kang JG: \u003cstrong\u003eRisk Factors for Colorectal Cancer in Korea: A Population-Based 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\u003cstrong\u003e15\u003c/strong\u003e:1572053.\u003c/li\u003e\n\u003cli\u003eWang D, Tan M, Nov P: \u003cstrong\u003eSoutheast Asia burden and trend of Gastrointestinal tract cancers from 1990 to 2021 and its prediction to 2050: findings from the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eInternational journal of colorectal disease \u003c/em\u003e2025, \u003cstrong\u003e40\u003c/strong\u003e(1):60.\u003c/li\u003e\n\u003cli\u003eSu J, Liang Y, He X: \u003cstrong\u003eThe global burden and trends analysis of early-onset colorectal cancer attributable to dietary risk factors in 204 countries and territories, 1990-2019: a secondary analysis for the global burden of disease study 2019\u003c/strong\u003e. \u003cem\u003eFrontiers in nutrition \u003c/em\u003e2024, \u003cstrong\u003e11\u003c/strong\u003e:1384352.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 and 2 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"colorectal cancer, global oncology, screening, risk factors, ARIMA, Joinpoint, SDI, Asia–Pacific","lastPublishedDoi":"10.21203/rs.3.rs-7388179/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7388179/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eTo generate implementation-ready evidence on colorectal cancer (CRC) burden and prevention priorities across four Asia\u0026ndash;Pacific countries.\u003c/p\u003e\u003ch2\u003ePatients and Methods\u003c/h2\u003e\u003cp\u003eWe analyzed Global Burden of Disease 2021 (GBD 2021) estimates for Australia, China, Japan, and the Republic of Korea (Korea) for 1990\u0026ndash;2021. Outcomes included prevalence, incidence, mortality, and disability-adjusted life years (DALYs) as counts and age-standardized rates (ASRs) with 95% uncertainty intervals (UIs). For clarity, ASR components were the age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized disability-adjusted life-year rate (ASDR). Temporal trends used log-linear models to derive average annual percent change (AAPC) and Joinpoint regression; future trajectories (2022\u0026ndash;2041) applied autoregressive integrated moving average (ARIMA) models. We performed Das Gupta decomposition (population growth, population aging, and epidemiologic change), assessed correlations with the Socio-demographic Index (SDI), and summarized sex-stratified population-attributable fractions (PAFs) for six modifiable risks (dietary risks, high body mass index (BMI), high fasting plasma glucose, low physical activity, alcohol use, and tobacco use).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eChina had the largest counts in 2021; Japan had the highest ASPR. Men bore higher incidence, mortality, and DALY rates, with widening male disadvantages in China and Korea. From 1990\u0026ndash;2021, ASPR/ASIR rose in China and Korea, while Australia\u0026rsquo;s ASPR was stable and ASIR declined; ASMR/ASDR fell in all countries, greatest in Australia. Decomposition attributed rising counts primarily to aging (notably China/Japan) with epidemiologic change contributing in China/Korea. SDI correlated inversely with ASMR/ASDR. Dietary risks were the leading contributors to deaths and DALYs, followed by high BMI and high fasting plasma glucose; PAFs were consistently higher in men. Forecasts suggest continued increases in prevalence/incidence in China/Korea, sustained declines in severity endpoints in Australia, and stability or gradual improvement in Japan through 2041.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003ePriorities include scaling high-quality screening and integrated risk-factor control\u0026mdash;especially for men\u0026mdash;in China and Korea, and sustaining early detection and survivorship gains in Japan and Australia. Findings support resource-appropriate implementation strategies in diverse health-system contexts.\u003c/p\u003e","manuscriptTitle":"Temporal Trends, Projections, and Risk Attribution of Colorectal Cancer in Australia, China, Japan, and Korea: GBD 2021 Analysis (1990–2041)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 10:05:09","doi":"10.21203/rs.3.rs-7388179/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ab43202b-2a1c-4a4a-81d4-f62a476bb8de","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T15:23:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 10:05:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7388179","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7388179","identity":"rs-7388179","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}