Global, regional, and national burden of colorectal cancer attributable to modifiable risk factors, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Introduction

Colorectal cancer (CRC) continues to rank among the leading causes of cancer-related morbidity and mortality worldwide, with a considerable proportion of its incidence and mortality attributed to modifiable risk factors such as a high body mass index (BMI), insufficient physical activity, tobacco use, and dietary risks (1). Over the past three decades, demographic and lifestyle transitions including increasing urbanization, sedentary behaviors, and a shift toward highly processed dietary patterns, have intensified the contribution of these factors to CRC incidence and mortality. Although progress has been made in screening and therapeutic interventions, substantial regional disparities in disease burden remain, particularly in countries undergoing rapid socioeconomic changes such as Brazil, Russia, India, China, and South Africa (BRICS), where rising obesity prevalence and westernized diets intersect with persistent healthcare inequities (2,3).

The Global Burden of Disease (GBD) Study 2021 offers a comprehensive methodological framework to quantify the influence of these risk factors on CRC. Prior analyses from the GBD collaboration have underscored the increasing impact of metabolic and behavioral risks on non-communicable diseases (NCDs), with high BMI alone accounting for 5.7% of global disability-adjusted life years (DALYs) in 2021 (4). In the context of CRC, recent evidence indicates that risk-attributable burden is disproportionately concentrated in middle-income countries, where the implementation of preventive strategies has not kept pace with ongoing epidemiological transitions (5). In China, for example, a high BMI has emerged as a major contributor to the rising incidence of early-onset type 2 diabetes, a condition with overlapping risk factors for CRC (6). Similarly, dietary risks such as low fiber consumption and elevated intake of red meat have shown significant increases in regions including South Asia and Latin America, reflecting concurrent trends in CRC incidence (7).

Despite these developments, a comprehensive analysis of the spatiotemporal patterns of CRC burden attributable to these modifiable risks is still lacking, particularly within BRICS nations, which together account for approximately 40% of the global population and display considerable variation in healthcare infrastructure. Although high-income countries have reported declining CRC mortality, largely due to the widespread implementation of organized screening programs, BRICS countries continue to face a dual burden of rising incidence driven by lifestyle transitions and limited access to preventive healthcare services (8). In Brazil, for instance, urbanization has been linked to increased sedentary behavior, with physical inactivity contributing to 15% of DALYs related to NCDs (4). In India, dietary shifts toward processed foods have been associated with a 34% rise in diet-attributable CRC cases since 2000 (9).

Recent global evidence further indicates that a substantial proportion of cancer cases remains attributable to modifiable exposures, including tobacco use, alcohol consumption, high BMI, and insufficient physical activity, reinforcing the need for updated population-level assessments of preventable cancer burden (10). This study aimed to quantify the CRC burden attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks from 1990 to 2021, with an emphasis on regional variation and a specific evaluation of the BRICS countries, using data from the GBD 2021. The findings provide evidence to inform targeted risk-reduction strategies and align with the objectives of the United Nations Sustainable Development Goal 3.4, which aims to reduce premature mortality from NCDs by one-third by 2030 (11). We present this article in accordance with the GATHER reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-0335/rc).

Methods

Data sources and study design

Data from the GBD Study 2021, a collaborative initiative coordinated by the Institute for Health Metrics and Evaluation, were used to quantify the CRC burden attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks across 204 countries and territories from 1990 to 2021 (12). The GBD 2021 database incorporated population-level data obtained from sources such as censuses, vital registration systems, cancer registries, household surveys, and published cohort studies. These data were standardized using the Cause of Death Ensemble model and DisMod-MR 2.1 for the estimation of incidence and mortality (13). Exposures to risk factors were estimated based on meta-analyses of epidemiological studies, survey data, and biomarker measurements, with weighting applied according to geographic and socioeconomic covariates.

The attributable burden was estimated using the Comparative Risk Assessment framework, which associates levels of risk factor exposure with population-attributable fractions derived from relative risks reported in meta-analyses (14). For CRC, the following risk-outcome pairs were defined:

High BMI: BMI ≥25 kg/m² (15); low physical activity: less than 150 minutes of moderate-intensity or less than 75 minutes of vigorous-intensity activity per week (16); tobacco use: current or previous smoking, including use of smokeless tobacco (4); dietary risks: inadequate intake of fruits, vegetables, and whole grains; excessive consumption of red or processed meat and sodium (17). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Statistical analysis

Burden disaggregation

The disease burden of CRC attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks was stratified by sex, 5-year age groups (ranging from 0–4 to ≥95 years), Socio-demographic index (SDI) regions, GBD regions, individual countries, and BRICS nations in 2021. Age-standardized rates (ASRs) were calculated based on the GBD global reference population to facilitate cross-regional comparisons.

Temporal trend analysis

Linear regression analysis was used to assess temporal trends in age-standardized rates of deaths, DALYs, years lived with disability, and years of life lost from 1990 to 2021. Estimated annual percentage changes (EAPCs) and corresponding 95% confidence intervals were computed for each trend segment. The EAPCs were calculated using the regression coefficient (β) from the natural log-transformed rates plotted against calendar year, using the formula: EAPC = 100 × (e^β − 1). Trends were classified as increasing (EAPC >0), decreasing (EAPC <0), or stable (EAPC =0).

Forecasting to 2050

The burden of CRC attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks was projected through the year 2050 using Autoregressive Integrated Moving Average (ARIMA) models and the Exponential Smoothing (ES) model.

Health inequality assessment

Health inequalities across SDI quintiles and countries were assessed using the Slope Index of Inequality (SII) and the Concentration Index (CI). The SII quantified absolute differences in ASRs between the highest and lowest SDI groups, whereas the CI measured relative inequality across the full SDI distribution.

Software and validation

All statistical analyses were conducted using R software (version 4.2.2; R Foundation for Statistical Computing).

Results

Disease burden in 2021

In 2021, males in BRICS countries exhibited a significantly higher burden of CRC attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks across most indicators when compared with females (Tables S1-S16). Analysis by age distribution indicated distinct patterns, with the number of cases and corresponding ASRs initially increasing with age before declining in the older age groups within the BRICS countries (Figures S1-S8). Geographically, regions with higher SDI levels reported the greatest absolute number of cases and ASRs for CRC attributable to the specified risk factors, whereas regions with lower SDI levels demonstrated the smallest burden (Figures S9-S12). Substantial variation in disease burden was observed across 54 GBD regions and 204 countries (Figures S13-S20). To make the key quantitative findings more accessible in the main text, we added a concise summary table presenting selected estimates for BRICS countries and major SDI regions. Table 1 summarizes attributable DALYs, DALY age-standardized rates, and EAPCs from 1990 to 2021 for the four modifiable risk factors.

Temporal trend from 1990 to 2021

From 1990 to 2021, an upward trend in the number of CRC cases attributable to high BMI was consistently observed in all five BRICS countries among both sexes. Regarding ASRs, increasing trends were identified in Brazil, Russia, China, and South Africa, whereas a declining trend was observed in India.

For CRC attributable to insufficient physical activity, tobacco use, and dietary risks, the number of cases increased across all five BRICS countries. However, the ASR trends varied, with either stable or decreasing trajectories observed for both sexes (Figures S21-S40). When stratified by age group, the trends in CRC attributable to all four risk factors mirrored those observed in BRICS countries, with nearly all indicators demonstrating an increasing pattern over time (Figures S41-S60).

At the global level, the number of CRC cases attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks increased across all five SDI regions. ASR trends diverged, with decreases observed in higher SDI regions and increases in lower SDI regions (Figures S61-S64, Tables S1-S16).

Notable regional differences in burden trends were identified across GBD regions. To classify regions with similar patterns, hierarchical clustering analysis was conducted. For CRC attributable to high BMI, significant increases in ASRs were found in the Region of the Americas, America, Central Asia, North America, High-income North America, Commonwealth High Income, Australasia, and Western Europe. In contrast, significant declines were recorded in the High-income Asia Pacific, Europe & Central Asia, WB, European Region, Europe, Advanced Health System, Oceania, Eastern Europe, Central Europe, and Southern Latin America (Figure S65).

For CRC attributable to insufficient physical activity, substantial increases in ASRs were observed in the Region of the Americas, America, Oceania, European Region, Europe & Central Asia, WB, Europe, Advanced Health System, High-income Asia Pacific, Commonwealth High Income, Australasia, Western Europe, North America, and High-income North America. Decreases were observed in the Middle East & North Africa-WB, Latin America & Caribbean-WB, Andean Latin America, Tropical Latin America, Southeast Asia, Eastern Mediterranean Region, Western Sub-Saharan Africa, Western Africa, Africa, Southern Sub-Saharan Africa, Southern Africa, Northern Africa, and Central Latin America (Figure S66).

Regarding CRC attributable to tobacco use, ASRs increased significantly in the Commonwealth High Income and Australasia regions. In contrast, decreases were observed in North America, High-income North America I, High-income Asia Pacific, the Region of the Americas, America, Western Europe, and the Advanced Health System group (Figure S67).

For CRC attributable to dietary risks, significant increases in ASRs were found in Tropical Latin America, Northern Africa, Central Latin America, Southern Sub-Saharan Africa, Southern Africa, North Africa and Middle East, Central Europe, Andean Latin America, Southern Latin America, Middle East & North Africa-WB, Caribbean, Latin America & Caribbean-WB, Southeast Asia, and Eastern Mediterranean Region. Significant declines were observed in Western Europe, Commonwealth High Income, North America, High-income North America, and Australasia (Figure S68).

Variations in trends were noted across individual countries and territories, including BRICS nations, for all four risk factors (Figures S69-S76, Tables S1-S16). The main quantitative estimates underlying these temporal patterns are summarized in Table 1, which highlights the changes in DALYs, DALY ASRs, and EAPCs across BRICS countries and representative SDI regions.

Predicted results from 2022 to 2050

From the projections generated using the ARIMA model for the period 2022 to 2050, a consistent increase in the number of CRC cases attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks was observed among both sexes in BRICS countries. However, ASRs exhibited a decreasing trend in certain instances. The ES model projected a slight upward trend in the number of cases, yielding results generally consistent with those of the ARIMA model. In contrast, ASRs estimated by the ES model remained relatively stable over the projection period (Figures S77-S116).

Health inequality analysis

Globally, the burden of CRC attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks, as measured by ASRs was predominantly concentrated in countries with lower SDI levels. Between 1990 and 2021, the SII indicated an improvement in inequality among lower-SDI countries. In contrast, the Concentration Index for ASRs remained relatively stable, suggesting a persistent concentration of burden in lower-SDI settings throughout the study period (Figures 1-4).

Figure 1 Results of health inequality analysis for CRC attributable to high BMI. BMI, body mass index; CRC, colorectal cancer; SDI, Socio-demographic index.

Figure 2 Results of health inequality analysis for CRC attributable to insufficient physical activity. CRC, colorectal cancer; SDI, Socio-demographic index.

Figure 3 Results of health inequality analysis for CRC attributable to tobacco use. CRC, colorectal cancer; SDI, Socio-demographic index.

Figure 4 Results of health inequality analysis for CRC attributable to dietary risks. CRC, colorectal cancer; SDI, Socio-demographic index.

Discussion

This study comprehensively assessed the global, regional, and national burden of CRC attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks from 1990 to 2021, with particular attention to BRICS countries. The analysis identified significant disparities in disease burden. In 2021, males in BRICS countries exhibited higher CRC burdens associated with these risk factors. Age-specific patterns indicated peak burden among older adults, with a notable increase observed in younger populations in certain countries. Regions with higher SDI levels reported the greatest absolute number of cases, whereas regions with lower SDI levels exhibited increasing trends in ASRs. Temporal trends differed across BRICS countries: although CRC burden is attributable to high BMI increased in all five nations, the direction of ASR trends varied. Projections to 2050 suggested continued growth in absolute case numbers across BRICS countries, underscoring the need for timely and effective intervention strategies.

The concentration of CRC burden in lower-SDI regions and low- and middle-income countries (LMICs) remains a significant public health concern. High BMI, a major contributing factor, has increased markedly in rapidly urbanizing regions such as South Asia and Southeast Asia. A 2020 study published in The Lancet associated a 10% rise in mean national BMI with a 12% increase in CRC incidence, with the most pronounced effects observed in LMICs (18). In China, the prevalence of overweight and obesity doubled between 1990 and 2020, paralleling a 37% increase in CRC DALYs attributable to high BMI (19). Similarly, in Brazil, the ongoing “nutrition transition” characterized by decreased physical activity and increased consumption of processed foods, was linked to a 25% rise in CRC cases attributable to low physical activity since 2000 (20).

CRC burden related to tobacco use demonstrated divergent regional trends. Declines in ASRs were observed in high-income regions such as Australia and Western Europe, likely reflecting the implementation of comprehensive tobacco control policies, including taxation and smoke-free legislation. In contrast, increases were documented in Commonwealth High Income countries and several LMICs, where persistent tobacco use and limited cessation support continue to pose challenges (21).

Dietary risk-related CRC burden indicated regional heterogeneity: ASRs increased in areas with dietary patterns characterized by high intake of red and processed meat and low fiber consumption, such as Latin America and the Middle East, whereas stabilization was noted in high-income regions with established dietary guidelines, such as Southern Europe (22). These findings are consistent with a 2019 meta-analysis published in Gut, which reported that each additional 50 g/day of processed meat consumption was associated with an 18% increase in CRC risk (23).

The heterogeneity observed among BRICS countries highlights the necessity for context-specific public health interventions. These recommendations should be interpreted as broad policy directions rather than prescriptive national programs. For China and Russia, where high BMI and tobacco-related burden appear to be important priorities in the present analysis, integrated strategies linking obesity prevention, smoking cessation, and age-appropriate CRC screening may be particularly relevant. For India, where dietary risks and rising BMI are prominent concerns, prevention efforts may need to place greater emphasis on improving dietary quality, reducing excess intake of energy-dense and ultra-processed foods, and strengthening early-life and community-based obesity prevention. For Brazil and South Africa, where physical inactivity and tobacco use are important contributors, policies that promote active transport, community-level physical activity, and sustained tobacco-control implementation may be useful. However, the design and implementation of these strategies should be adapted to each country’s health-system capacity, socioeconomic context, and existing national prevention programs. In China and Russia, where high BMI and tobacco use represent major risk factors, integrating obesity management into primary care settings and the expanding tobacco cessation programs may offer significant benefits. In India, where dietary risks and rising BMI are prevalent, policy measures such as food fortification, taxation of salt and sugar, and agricultural subsidies for fruit and vegetable production—approaches that have proven effective in Thailand and Chile—are warranted (24,25). In Brazil and South Africa, where physical inactivity and tobacco use are prominent contributors, urban infrastructure promoting active transport (e.g., pedestrian zones and bicycle lanes) and strengthened tobacco control policies should be prioritized, drawing from successful interventions implemented in Uruguay (26).

The ongoing “risk transition” in BRICS nations, wherein infectious disease burdens coexist with rising NCD risks, presents complex challenges. These countries account for approximately 40% of the global population yet contribute to 55% of global CRC-attributable DALYs from modifiable risk factors (27). Addressing this dual burden requires coordinated, multisectoral engagement. Policy alignment among health, education, and urban development sectors is essential to foster healthier environments, while healthcare systems must be equipped with robust CRC screening programs such as fecal occult blood testing and colonoscopy to support timely diagnosis and improved clinical outcomes. Such approaches have been associated with reduced CRC mortality in settings such as the United States (28).

The findings of this study align with previous GBD analyses, which have demonstrated that metabolic and behavioral risk factors now account for over 40% of the global CRC burden, surpassing the contributions of genetic and infectious etiologies (29). A 2022 review published in CA: A Cancer Journal for Clinicians highlighted that although high-income countries have achieved reductions in CRC mortality through widespread screening and effective risk factor management, LMICs continue to face challenges due to limited access to preventive and therapeutic services (30). The regional clustering analysis conducted in this study provides further insight, identifying geographic “hotspots” of increasing risk such as tropical Latin America for dietary risks and Central Asia for high BMI and “cold spots” of declining burden, particularly in high-income Asia Pacific for tobacco-related CRC. These patterns reflect underlying differences in socioeconomic development and the implementation of public health policies (31).

The observed rise in CRC burden among younger age groups in BRICS countries is consistent with emerging literature on the increasing incidence of early-onset CRC in the United States and Europe. These trends have been associated with childhood obesity, increased sedentary behavior, and the adoption of Westernized dietary patterns during adolescence (32,33). Such findings underscore the importance of implementing life-course interventions, including school-based nutrition and physical activity programs, to address risk factors at an early stage.

Recent research on early-onset CRC further suggests that the effects of modifiable risk factors should be interpreted from a life-course perspective (34). Genetic susceptibility, early-life environmental exposures, diet, obesity, physical inactivity, tobacco use, microbial factors, and other lifestyle-related exposures may accumulate over time and influence colorectal carcinogenesis through metabolic, inflammatory, immune, microbial, genetic, and epigenetic pathways (35,36). This concept is consistent with the framework of molecular pathological epidemiology, which links exposures to tumor molecular characteristics and disease mechanisms). Although the present GBD-based analysis could not evaluate individual exposure histories, tumor molecular subtypes, or gene-environment interactions, our findings highlight the need for future studies integrating population-level burden data with molecular, genetic, microbiome, and exposome information (36). Such approaches may support more precise risk stratification, prevention, and early detection strategies, particularly for early-onset CRC. Prospective cohort incident-tumor biobank method-based research may provide a promising direction for addressing these questions (37,38). By linking longitudinal cohort data on genetic variation, diet, lifestyle, environmental exposures, and other long-term risk factors with biospecimens from incident tumors, this approach can help evaluate how cumulative exposures are associated with tumor biomarkers, molecular phenotypes, tumor microenvironmental features, and clinical outcomes. Such studies may complement GBD-based population analyses by providing individual-level mechanistic evidence for early-onset cancer etiology and precision prevention.

The interpretation of these findings should also consider the possibility of risk-factor clustering. The four modifiable risks examined in this study were analyzed separately within the GBD comparative risk assessment framework, and our analysis did not directly estimate statistical interaction or multiplicative effects among them. Nevertheless, high BMI, unhealthy dietary patterns, insufficient physical activity, and tobacco use may co-occur within the same populations, particularly in settings undergoing rapid urbanization and lifestyle transition. Such clustering could increase overall CRC risk beyond what is suggested by any single exposure considered in isolation. In addition, other relevant exposures not included in the present analysis, such as alcohol consumption, may further contribute to CRC burden and may interact with the risk factors examined here. Future studies using individual-level or cohort-based data are needed to quantify joint exposure patterns and to determine whether additive or multiplicative interactions exist among these modifiable risks.

Despite the comprehensive nature of this analysis, several limitations must be acknowledged. The GBD methodology relies on modeled data, particularly in regions with limited cancer registry coverage, such as sub-Saharan Africa, which may introduce uncertainty into burden estimates (39). Additionally, the scope of this study was confined to four modifiable risk factors, excluding other relevant contributors such as alcohol consumption and genetic susceptibility, thereby limiting the ability to assess the cumulative effects of multiple risk exposures (40). Furthermore, the aggregate nature of GBD estimates precluded evaluation of individual-level exposure histories, tumor molecular phenotypes, molecular pathological epidemiology questions, gene-environment interactions, and PCIBM-based longitudinal tumor biomarker analyses. The projection models used in this analysis assumed constant trajectories of risk exposure and healthcare access, which may not fully capture the impact of future developments, such as global obesity reduction initiatives or pandemics influencing physical activity patterns (41). Furthermore, the grouping of Brazil, Russia, India, China, and South Africa as a single BRICS cohort may obscure important intra-country variations, as subnational disparities such as urban–rural divides in India and China may not be adequately reflected in aggregated national-level estimates (42). In addition, the ARIMA and Exponential Smoothing models used for projections to 2050 did not have detailed model parameters, selection criteria, out-of-sample validation metrics, or sensitivity analyses reported. This is a methodological limitation.

Conclusions

This study offers a detailed, time-resolved assessment of CRC burden attributable to high BMI, insufficient physical activity, tobacco use, and dietary risks, underscoring the critical need for targeted and equity-oriented public health interventions. The concurrent rise in risk exposure within LMICs and the persistence of health inequalities necessitate the implementation of a comprehensive global strategy. Such a strategy should integrate upstream policy measures such as regulation of the food environment and urban planning to promote physical activity with downstream healthcare services, including routine screening and personalized risk-factor counseling.

In BRICS countries, where demographic and lifestyle transitions are accelerating, the incorporation of both policy- and health system-level interventions into national NCD strategies may offer substantial impact. Alignment with the United Nations Sustainable Development Goal 3.4 which aims to reduce premature mortality from NCDs, has the potential to prevent millions of CRC cases by 2050. Continued investment in health data infrastructure, particularly in low-SDI settings, is essential to improve the precision and effectiveness of future interventions and to ensure that no population group is excluded from efforts to reduce preventable CRC burden.

Acknowledgments

We thank the staff for their dedicated work in implementing the study’s intervention and evaluation.

Footnote

Reporting Checklist: The authors have completed the GATHER reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-0335/rc

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-0335/prf

Funding: The work was supported by the Beijing Municipal Administration of Hospitals Clinical Medicine Development and Research Cultivation Project (No. PZ2022008).

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-0335/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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