Authors: Daniele Piovani, Gisella Figlioli, Georgios K. Nikolopoulos, Konstantinos K. Tsilidis, Alessio Aghemo, Cesare Hassan, Alessandro Repici, Michael Bretthauer, Stefanos Bonovas
Categories: Research, Neoplasms, Epidemiology, Global health, Risk factors, Abdominal fat, Intestinal neoplasms
Source: BMC Medicine
Authors: Daniele Piovani, Gisella Figlioli, Georgios K. Nikolopoulos, Konstantinos K. Tsilidis, Alessio Aghemo, Cesare Hassan, Alessandro Repici, Michael Bretthauer, Stefanos Bonovas
Central obesity is a major risk factor for colorectal cancer (CRC) and may better reflect obesity-related risk than body mass index (BMI). Its global burden, however, remains poorly quantified. We aimed to estimate the number and proportion of CRC cases attributable to central obesity in 2022 across global, regional, and national levels.
We estimated population attributable fractions (PAFs) by combining sex-specific prevalence of central obesity from national surveys with pooled relative risks from meta-analysis. Central obesity was defined as elevated waist circumference using standardised sex- and ethnicity-specific thresholds, accounting for variation in definitions via probabilistic modelling. We addressed missing data through multiple imputation. CRC incidence estimates for 2022 were obtained from GLOBOCAN for 185 countries. Monte Carlo simulations propagated uncertainty in exposure prevalence and risk estimates.
In 2022, an estimated 311 418 (95% uncertainty interval 242 603–378 880) CRC cases were attributable to central obesity, corresponding to a global PAF of 16.2% (12.6–19.7). PAFs were higher in females (18.2%, 13.0–23.3) than in males (14.5%, 9.6–19.3), though age-standardised rates (ASRs) were slightly higher in males. The highest PAF was in North America, and the highest ASRs in Australia–New Zealand and northern Europe. PAFs and ASRs declined with decreasing income levels among males but not females. Regional variation in sex differences was substantial, with higher female PAFs in parts of Africa and Asia, and smaller or reversed gaps in high-income settings. In high-income countries, the estimated 10-year CRC risk at screening age (55–69 years) was 1.32% in males with central obesity versus 0.90% in those without, and 0.92% versus 0.64% in females, corresponding to one excess CRC case per 236 (180–353) men and 357 (279–502) women.
Central obesity accounts for a substantial share of the global CRC burden, with large geographical variability. Applying established waist circumference thresholds in surveillance and incorporating central obesity into individual risk stratification may inform more effective CRC screening and prevention strategies.
The online version contains supplementary material available at 10.1186/s12916-026-04858-0.
Globally, colorectal cancer (CRC) ranks as the third most commonly diagnosed cancer and the second leading cause of cancer death, accounting for nearly 2 million new cases and 900 000 deaths annually [1]. Incidence varies geographically, with the highest rates in high-income regions and the lowest in parts of Africa and southcentral Asia [2]. In countries undergoing socioeconomic transition, CRC rates are rising, likely reflecting increasing prevalence of Western dietary patterns, physical inactivity, and obesity [1–3]. Obesity is a modifiable risk factor for CRC, with approximately 10% of cases attributable to raised body-mass index (BMI) [4, 5]. However, BMI alone does not fully capture the complexity of excess adiposity. Waist circumference (WC) is a more reliable proxy for visceral fat and may better reflect obesity-related metabolic dysfunction [6]. Central obesity is mechanistically linked to colorectal carcinogenesis [7], and recent epidemiological evidence suggests it may be a stronger predictor of CRC risk than BMI-defined obesity, with one in six cases in the UK attributable to high WC [8]. Despite this, global burden estimates of CRC have so far relied on BMI-based exposure definitions [4], and the burden attributable to central obesity has not been quantified at the global level.
In line with this evidence, the Lancet Diabetes & Endocrinology Commission redefined obesity not simply as elevated BMI, but as a chronic, systemic disease caused by the pathological effects of excess adiposity on organ function. It advocates complementing BMI with central obesity measures, such as waist circumference, using sex- and ethnicity-specific thresholds [9].
The International Agency for Research on Cancer (IARC) has concluded that avoiding weight gain has a cancer-preventive effect against CRC [10]. As central obesity continues to rise globally [11], estimating the burden of CRC attributable to high WC is essential for quantifying its preventable share, guiding targeted prevention efforts and complementing clinical strategies for risk stratification. However, population-based data on central obesity remain sparse, particularly in low-income and middle-income countries, and are often subject to methodological inconsistencies, with heterogeneous thresholds and sampling strategies. These limitations have precluded robust global estimates of the CRC burden attributable to central obesity.
In this population attributable fraction (PAF) study, we estimated the global, regional, and national burden of CRC attributable to central obesity, defined as high WC, using consistent and standardized methods. We quantified the PAF and age-standardized incidence rate of CRC attributable to central obesity in 2022 across 185 countries and territories, stratified by sex, geographic region, and income level, incorporating modelling techniques to account for uncertainty in exposure and risk estimates.
This study was conducted in accordance with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) [12].
We obtained country- and sex-specific data on prevalence of central obesity among adults from nationally representative surveys such as the World Health Organization (WHO) STEPwise approach to non-communicable disease risk factor surveillance (STEPs) surveys, and national health or nutrition surveys led by ministries of health, national institutes of statistics, public health agencies, or other scientific societies (Additional file Appendix Table S1 [13–174]). When multiple data sources were available, we prioritized surveys using probabilistic cluster sampling and applying sample weights to account for sampling design and non-response. If multiple time points were available, we selected the data closest to 2008–2012 to allow a latency period between central adiposity and the development of CRC in 2022, consistent with established models of colorectal carcinogenesis that suggest an average 10–15-year adenoma–carcinoma sequence [175, 176].
Central obesity was defined as elevated WC, using sex- and ethnicity-specific thresholds based on the Joint Interim Statement of major scientific societies (Additional file Appendix Table S2) [177]. When prevalence estimates were not reported directly, or thresholds differed from those recommended, we estimated prevalence from available summary statistics (e.g. mean and standard deviation) under the assumption of a normal distribution. We modelled uncertainty using binomial or uniform distributions, depending on the data source. In countries with heterogeneous ethnic populations and multiple applicable WC thresholds, we applied a probabilistic approach using a uniform distribution bounded by the most and least conservative sex-specific thresholds, selected by expert consensus in accordance with the Joint Interim Statement (Additional file Supplementary Methods S1 [177–181], and Appendix Table S3).
In countries lacking representative WC data, we applied multiple imputation by chained equations (MICE), stratified by sex and waist circumference threshold group. The imputation model included covariates associated with central country-level obesity prevalence (BMI ≥ 30 kg/m^2^), underweight (BMI < 18.5 kg/m^2^), diabetes, and insufficient physical activity in 2010 by sex (from WHO Global Health Observatory), as well as World Bank income group and United Nations (UN) geographic region. Imputed prevalence estimates, along with their uncertainty distributions, were carried forward into the analysis (Additional file Appendix Table S4).
We extracted the number of CRC cases (International Classification of Diseases, 10th edition, C18–21) and corresponding crude and age-standardized incidence rates for 2022 by sex from the Global Cancer Observatory’s Cancer Today (GLOBOCAN) database in 185 countries.
We estimated the PAF of CRC due to central obesity in 2022 by sex and country using a counterfactual framework, assuming a causal association, and defining the theoretical minimum risk exposure level as the absence of elevated central obesity (i.e. waist circumference below sex- and ethnicity-specific thresholds). PAFs were computed using Levin’s \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ PAF=\frac{P(RR-1)}{1+P(RR-1)}
To account for uncertainty in both prevalence and the RR estimates, we implemented a Monte Carlo simulation with 10 000 iterations. At each iteration, we performed multiple imputation for missing prevalence data and then randomly sampled from the resulting distribution of central obesity prevalence, as well as from the sex-specific log-normal distribution of RRs. This process yielded 10 000 country- and sex-specific estimates for all outcomes of interest. We report 95% uncertainty intervals (UIs) as the 2.5th to 97.5th percentiles of the simulated distributions, reflecting simulation-based uncertainty in model inputs and parameters (Additional file Supplementary Methods S1). The primary analysis included 122 countries with nationally representative data. National representativeness was defined as probability-based surveys designed to reflect the adult population at the national level, whereas partially representative data referred to probability-based surveys with limited geographic coverage or incomplete population representativeness. For all included countries, survey characteristics and primary data sources are detailed in Additional file Appendix Table S1. For the remaining 63 countries (37 with partially representative data and 26 with no data), imputed values were used (Additional file Appendix Table S4). We performed two sensitivity analyses to assess the robustness of our findings. First, we retained observed values for the 37 countries with partially representative data, imputing only the 26 countries without population-based data. In the second sensitivity analysis, we used a simpler, widely adopted approach, assigning to each of the 63 countries the sex-specific regional mean from countries using the same WC thresholds. We mapped country-level PAFs and ASRs using choropleth maps, stratified by sex. To support clinical and public health interpretation, we estimated the 10-year absolute risk of CRC in adults aged 55–69 years—a key screening population in many countries—stratified by sex and central obesity status. We applied a cause-specific hazards framework to account for competing mortality from other causes, using sex-specific CRC incidence rates derived from GLOBOCAN 2022 and all-cause mortality data from the Global Burden of Disease 2021 study. CRC incidence among individuals with and without central obesity was partitioned using pooled RRs and modelled exposure prevalence (fully detailed in the Additional file Supplementary Methods S1). All statistical analyses and visualizations were performed in R (version 4.4.2). ## Results We estimated that 311 418 (95% UI 242 603–378 880) cases of CRC worldwide in 2022 were attributable to central obesity (Table 1), corresponding to a global PAF of 16.2% (95% UI 12.6–19.7). Attributable cases were evenly distributed by sex (155 964 females, 95% UI 111 336–199 959; 155 455 males, 102 102–206 861). Although the PAF was numerically higher among females (18.2%; 95% UI 13.0–23.3) than in males (14.5%; 95% UI 9.5–19.3), age-standardized rates of CRC attributable to central obesity were 3.2 per 100 000 among males (95% UI 2.1–4.2) and 2.8 among females (95% UI 2.0–3.5). Table 1Colorectal cancer cases in 2022 attributable to central obesity, by sex and UN region. Data in parentheses are 95% uncertainty intervalsAreaMalesFemalesTotalAttributable casesPAF (%)ASRAttributable casesPAF (%)ASRAttributable casesPAF (%)ASR**Africa** Eastern Africa421 (264–581)4.4 (2.8–6.1)0.4 (0.2–0.5)1631 (1151–2101)16.7 (11.8–21.5)1.2 (0.8–1.6)2052 (1550–2541)10.6 (8.0–13.1)0.8 (0.6–1.0) Middle Africa154 (88–234)5.6 (3.2–8.5)0.3 (0.2–0.5)452 (311–598)17.2 (11.8–22.8)0.9 (0.6–1.2)606 (448–774)11.2 (8.3–14.3)0.6 (0.5–0.8) Northern Africa1762 (1138–2397)14.7 (9.5–20.0)1.6 (1.0–2.2)2812 (2046–3551)24.4 (17.8–30.9)2.3 (1.7–3.0)4574 (3578–5538)19.5 (15.2–23.6)2.0 (1.6–2.4) Southern Africa343 (218–469)8.5 (5.4–11.6)1.4 (0.9–1.9)807 (582–1022)22.1 (15.9–28.0)2.4 (1.7–3.0)1150 (891–1397)14.9 (11.6–18.1)1.9 (1.5–2.3) Western Africa726 (391–1087)9.4 (5.1–14.1)0.7 (0.4–1.0)1244 (874–1611)18.6 (13.1–24.2)1.1 (0.8–1.4)1970 (1469–2481)13.7 (10.2–17.2)0.9 (0.7–1.1) Total (Africa)3406 (2177–4641)9.4 (6.0–12.8)0.9 (0.5–1.2)6947 (4979–8839)20.3 (14.6–25.8)1.5 (1.1–1.9)10,353 (8029–12581)14.7 (11.4–17.9)1.2 (0.9–1.5)**Americas** North America18,766 (12,406–24,919)19.3 (12.8–25.6)5.9 (3.9–7.8)19,770 (14,225–25,094)22.8 (16.4–29.0)5.5 (4.0–7.0)38,536 (30,111–46,666)21.0 (16.4–25.4)5.7 (4.5–6.9) Caribbean and central America2471 (1582–3415)15.4 (9.9–21.3)1.9 (1.2–2.7)3573 (2566–4552)21.8 (15.6–27.7)2.3 (1.7–2.9)6044 (4698–7387)18.6 (14.5–22.8)2.1 (1.7–2.6) South America8841 (5660–12,160)15.6 (10.0–21.4)3.3 (2.1–4.6)11,978 (8579–15,310)21.5 (15.4–27.5)3.6 (2.6–4.6)20,820 (16,153–25,470)18.5 (14.4–22.7)3.5 (2.7–4.3) Total (Americas)30,078 (19,864–39,914)17.7 (11.7–23.5)4.2 (2.8–5.5)35,322 (25,476–44,844)22.3 (16.1–28.3)4.2 (3.0–5.3)65,400 (51,293–79,093)19.9 (15.6–24.1)4.2 (3.3–5.1)**Asia** Eastern Asia55,750 (36,391–74,401)13.6 (8.9–18.2)3.7 (2.4–5.0)44,708 (31,496–57,740)15.4 (10.8–19.9)2.7 (1.9–3.5)100,458 (77,506–123,427)14.4 (11.1–17.6)3.2 (2.5–3.9) Southcentral Asia7922 (5130–10,667)12.0 (7.8–16.2)0.8 (0.5–1.1)8490 (6049–10,852)19.0 (13.6–24.3)0.8 (0.6–1.1)16,412 (12,768–20,067)14.9 (11.6–18.2)0.8 (0.6–1.0) Southeastern Asia5049 (3215–6899)8.0 (5.1–10.9)1.4 (0.9–1.9)7539 (5299–9759)15.2 (10.7–19.7)1.8 (1.3–2.3)12,589 (9662–15,453)11.2 (8.6–13.7)1.6 (1.3–2.0) Western Asia3667 (2406–4924)15.5 (10.1–20.8)2.8 (1.8–3.8)4225 (3031–5367)21.5 (15.4–27.3)3.0 (2.1–3.8)7892 (6146–9584)18.2 (14.2–22.1)2.9 (2.3–3.5) Total (Asia)72,388 (47,144–96,735)12.9 (8.4–17.2)2.4 (1.6–3.3)64,963 (45,882–83,690)16.1 (11.3–20.7)2.0 (1.4–2.6)137,351 (106,303–168,317)14.2 (11.0–17.4)2.2 (1.7–2.7)**Europe** Eastern Europe14,910 (9622–20,230)16.0 (10.4–21.8)6.2 (4.0–8.5)17,569 (12,425–22,635)20.3 (14.4–26.1)4.8 (3.4–6.2)32,479 (25,047–39,701)18.1 (14.0–22.1)5.4 (4.2–6.6) Northern Europe7447 (4866–10,000)17.3 (11.3–23.2)6.3 (4.1–8.5)7306 (5167–9392)19.4 (13.7–25.0)5.5 (3.9–7.0)14,753 (11,387–18,074)18.3 (14.1–22.4)5.9 (4.5–7.2) Southern Europe12,008 (7796–16,189)16.5 (10.7–22.3)6.5 (4.2–8.8)9820 (6879–12,859)17.8 (12.5–23.3)4.4 (3.1–5.7)21,828 (16,668–27,055)17.1 (13.0–21.2)5.4 (4.1–6.7) Western Europe12,900 (8436–17,375)16.1 (10.5–21.7)5.6 (3.7–7.5)11,984 (8412–15,603)17.2 (12.0–22.3)4.2 (2.9–5.5)24,884 (19,211–30,486)16.6 (12.8–20.3)4.9 (3.8–6.0) Total (Europe)47,266 (31,022–63,115)16.4 (10.7–21.8)6.2 (4.0–8.2)46,679 (33,227–59,948)18.7 (13.3–24.1)4.6 (3.3–6.0)93,945 (73,098–114,355)17.5 (13.6–21.3)5.3 (4.1–6.5)**Oceania** Australia and New Zealand2271 (1509–3028)20.3 (13.5–27.0)7.9 (5.3–10.6)1977 (1412–2532)19.9 (14.2–25.4)6.3 (4.5–8.1)4248 (3304–5189)20.1 (15.6–24.5)7.1 (5.5–8.7) Melanesia, Micronesia, and Polynesia46 (27–68)7.9 (4.6–11.6)1.2 (0.7–1.7)76 (54–98)18.5 (13.1–23.7)1.7 (1.2–2.1)122 (93–153)12.3 (9.3–15.3)1.5 (1.1–1.8) Total (Oceania)2317 (1540–3084)19.7 (13.1–26.2)6.9 (4.6–9.1)2053 (1465–2628)19.8 (14.1–25.3)5.5 (3.9–7.0)4370 (3396–5336)19.7 (15.3–24.1)6.1 (4.8–7.5)**World**155,455 (10,2102–206,861)14.5 (9.5–19.3)3.2 (2.1–4.2)155,964 (111,336–199,959)18.2 (13.0–23.3)2.8 (2.0–3.5)311,418 (242,603–378,880)16.2 (12.6–19.7)3.0 (2.3–3.6)*Abbreviations:** ASR* age-standardized rates per 100,000, *PAF* population attributable fraction, *UN* United Nations The total attributable burden was highest in North America (PAF 21.0%; 95% UI 16.4–25.4), followed by Australia and New Zealand, and northern Africa, and lowest in eastern and middle Africa and southeastern Asia (Figs. 1 and 2). Eastern Asia accounted for the largest share of total attributable CRC cases (32.2%; 100 458; 95% UI 77 506–123 427) followed by North America and eastern Europe (Table 1). By contrast, the largest ASRs were estimated in Australia and New Zealand (7.1 per 100 000; 95% UI 5.5–8.7) followed by northern Europe and North America (Figs. 2 and 3).Fig. 1Population attributable fraction of colorectal cancer in 2022 attributable to central obesity by country and sex. **A** Males. **B** FemalesFig. 2Population attributable fraction and age-standardized incidence rates (per 100 000) of colorectal cancer in 2022 attributable to central obesity, by UN region. Error bars indicate 95% uncertainty intervals. Abbreviation: UN, United NationsFig. 3Age-standardized rates of colorectal cancer per 100 000 in 2022 attributable to central obesity by country and sex. **A** Males. **B** Females Regional variation in PAFs was markedly greater among males than females, ranging from 4.4% (95% UI 2.8–6.1) in eastern Africa to 20.3% (13.5–27.0) in Australia and New Zealand. Among females, estimates ranged from 15.2% (10.7–19.7) in southeastern Asia to 24.4% (17.8–30.9) in northern Africa. Overall, PAFs attributable to central obesity were consistently higher in females than in males, except in Australia and New Zealand, southern and western Europe, and North America, where sex-specific estimates were broadly similar or slightly higher in males. The largest relative sex differences in PAFs were estimated in countries in the Middle East, southcentral Asia, and southern Africa, where PAFs among females were two to three times higher than those in males (Table 1). Among females, the highest PAFs were estimated in Morocco (28.2%, 95% UI 20.8–35.0), Afghanistan (25.8%, 18.8–32.2), and Iran (25.5%, 18.6–32.0; Fig. 1; Additional file Appendix Table S5). A total of 88 countries had estimated PAFs of 20% or higher, with elevated proportions observed in several countries across all continents. The highest ASRs in females were estimated in Norway (8.1 per 100 000, 95% UI 5.4–10.9); Denmark (7.1, 4.8–9.5); and New Zealand (6.6, 4.6–8.4). In 19 countries, the ASR was 5 per 100 000 or higher, the majority of which were in Europe, with the exception of New Zealand, Australia, the USA, Uruguay, and Brunei Darussalam (Fig. 3). Among males, the highest PAFs were estimated in the Bahamas (24.5%, 95% UI 16.6–31.9); Trinidad and Tobago (22.7%, 15.3–29.8); and Qatar (21.9%, 14.8–28.6, Fig. 1; Additional file Appendix Table S5). Eleven countries had estimated PAFs of 20% or higher, primarily in the Middle East, southern and eastern Europe, Australia, and the USA. The highest ASRs in males were estimated in Hungary (11.1, 95% UI 7.2–15.2); Croatia (10.0, 6.5–13.6); and Romania (9.5, 6.4–12.6). In 44 countries, ASRs were 5 per 100 000 or higher. In addition to North America, Australia, New Zealand, and most European countries, high ASRs were also observed in Japan, Brunei Darussalam, Puerto Rico, Israel, Singapore, the Bahamas, Uruguay, Barbados, Samoa, and Argentina (Fig. 3). High-income countries had the highest PAF for central obesity (17.7%, 95% UI 13.7–21.5) and the highest ASR (5.3 per 100 000, 4.1–6.4), accounting for 46.4% of the global number of attributable CRC cases (144 456, 95% UI 112 281–175 845). Progressively lower PAFs and ASRs were observed across groups of countries with decreasing income levels (Fig. 4). Low-income countries accounted for only 1.2% of the total attributable cases, and ASRs were approximately five times lower than those in high-income countries.Fig. 4Population attributable fraction, age-standardized incidence rate, and share of world total colorectal cancer cases in 2022 attributable to central obesity, by sex and World Bank income categorization. Error bars indicate 95% uncertainty intervals The distribution of PAFs across income groups varied by sex. Among males, PAFs increased with income, ranging from 6.6% (95% UI 4.1–9.4) in low-income to 17.8% (11.9–23.5) in high-income countries. Among females, however, PAFs were more consistent across income groups, ranging from 17.0% (12.1–22.0) in low-income to 18.9% (13.5–24.2) in upper-middle-income countries, with no clear gradient by income level. Among females, the largest share of CRC cases attributable to central obesity was estimated in upper-middle-income countries (45.3%), whereas among males, it was observed in high-income areas (51.3%, Fig. 4). ### Sensitivity analyses The results from both sensitivity analyses were consistent with the main findings (Additional file Appendix Table S6–S7). When observed values were retained for the 37 countries with partially representative data, global attributable cases (311 994 [95% UI 244 290–381 105]) and PAF (16.2% [12.7–19.8]) remained virtually unchanged. In males, estimated attributable cases declined modestly in middle Africa (106 [68–147] vs 154 [88–234]) and western Africa (492 [314–681] vs 726 [391–1087]), offset by marginal increases in northern Africa and southeastern Europe. In females, estimates slightly increased in western Africa (1443 [1045–1825] vs 1244 [874–1611]), with minor variations in eastern and southern Europe (Additional file Appendix Table S6). The largest shift was observed in Chad, where attributable cases increased by 56%, with a more pronounced difference in males (data not shown), reflecting the overrepresentation of urban populations in the available data. Using a simpler imputation method based on regional means from countries applying the same waist circumference thresholds yielded global estimates closely aligned with the primary analysis (Additional file Appendix Table S7). However, the PAF among males in low-income settings was modestly overestimated (8.4% [5.5–11.3] vs 6.6% [4.1–9.4] in the primary analysis). Given the relatively small proportion of global CRC cases arising from these countries, this had minimal influence on overall burden estimates. ### Absolute risk estimates in screening-age adults Among adults aged 55–69 years, the global estimated 10-year CRC risk was 0.76% (95% UI 0.71–0.81) in males and 0.52% (0.50–0.54) in females with central obesity, compared with 0.52% (0.48–0.55) and 0.36% (0.34–0.39), respectively, in those without—absolute differences of 0.24% (one excess case per 410 males [308–621]) and 0.16% (per 628 females [492–882]). The highest absolute risks were observed in high-income 1.32% (1.25–1.39) vs 0.90% (0.83–0.96) in males and 0.92% (0.88–0.95) vs 0.64% (0.59–0.68) in females, corresponding to one excess case per 236 men (180–353) and 357 women (279–502). Country-level results are provided in the Additional file Appendix Table S8. ## Discussion In 2022, over 300 000 CRC cases worldwide were attributable to central obesity, a modifiable but under-recognized contributor to the global cancer burden. This is the first comprehensive, global-level estimation of CRC cases attributable to central obesity using sex-specific and ethnicity-specific thresholds for waist circumference. Although the highest PAFs were seen in high-income regions such as Europe, Australia, North America, and Japan, considerable burdens were also present in parts of North Africa, Latin America, the Middle East, and Pacific island nations. These findings suggest a converging risk landscape in regions undergoing rapid nutritional and epidemiological transitions. The novelty of our study limits direct comparison with previous global estimates. In particular, Global Burden of Disease analyses have quantified CRC burden attributable to obesity using BMI-based exposure definitions [4], without considering measures of central adiposity. Our estimates therefore quantify for the first time a distinct and previously unmeasured component of the global obesity-related CRC burden, consistent with and directly aligned to the updated recommendations of the Lancet Diabetes & Endocrinology Commission to move beyond BMI-based definitions in the characterization of obesity [9]. A recent UK Biobank study estimated a PAF of 17.3% (95% confidence interval 12.3–22.1), closely aligning with our UK estimate of 18.8% (95% UI 14.4–23.3) [8]. However, the healthy volunteer bias inherent to the UK Biobank likely leads to underestimation of central obesity prevalence and, therefore, may yield a slightly conservative PAF. Our estimated global PAF of 16% based on waist circumference surpasses those derived from BMI-defined obesity (approximately 10%) [4, 5]. These estimates correspond to related exposures, and their combined interpretation should consider their partial overlap. Studies have shown that central obesity remains independently associated with CRC after adjusting for BMI, but not vice versa, suggesting that central adiposity is a stronger independent predictor of CRC risk [8, 184, 185]. This may reflect the metabolic activity of visceral adipose tissue, which promotes insulin resistance, chronic low-grade inflammation, and altered adipokine profiles [7]. Central obesity identifies a substantial number of individuals who would not be classified as overweight or obese based on BMI alone. A recent global analysis found that more than 20% of adults with a normal BMI had abdominal obesity, varying substantially across regions, and these individuals exhibited elevated cardiometabolic risk [186]. This supports the complementary value of assessing central adiposity alongside BMI in estimating obesity-related disease burden and reinforces the need to move beyond BMI in both surveillance and prevention strategies targeting obesity-related cancers. The higher global PAF in females reflects their greater prevalence of central and BMI-defined obesity [11, 187]. A pooled analysis of over 13 million individuals reported a global prevalence of central obesity of 47.6% in females and 30.4% in males [11]. This disparity reflects a combination of biological and sociocultural factors [188–191]. Women are more prone to subcutaneous fat accumulation, with adiposity often redistributing from the gluteofemoral to the abdominal region after menopause [188, 189]. Additionally, sociocultural norms, gender disparities in education, and limited access to physical activity may exacerbate central obesity in women, particularly in certain regions [190, 191]. These sex-specific patterns explain regional differences in attributable burden. The largest disparities were observed in parts of Africa and in southern and western Asia. Since RRs were similar across sexes, differences in exposure prevalence likely account for these gaps. Among males, PAFs peaked in high-income countries and declined with decreasing income, whereas in females they remained more stable across income levels. These findings align with the dynamics of the obesity transition model [192]. In the early stages of economic development, obesity disproportionately affects women and individuals with higher socioeconomic status. As societies develop, these disparities narrow or invert, with rising obesity among men and socioeconomically disadvantaged groups [192]. Central obesity appears to follow similar trajectories. As more countries progress through later stages of transition, male-attributable PAFs may rise, echoing patterns already observed in high-income settings. Despite the higher global PAF in females, attributable age-standardized CRC incidence rates remained slightly higher in males. This apparent paradox may reflect the overall higher CRC incidence among males, likely driven by a greater prevalence of other established risk factors such as tobacco use [193, 194], alcohol consumption [195, 196], intakes of red and processed meats [197, 198], and the protective role of oestrogens among females [199]. Nonetheless, central obesity remains a critical contributor to CRC risk in both sexes. In several high-income settings, male PAFs matched or exceeded those in females, highlighting the importance of sex-inclusive prevention strategies. This study has several strengths. It represents the first structured effort to estimate the global, regional, and national burden of CRC attributable to central obesity, stratified by sex and country. By using standardized waist circumference thresholds, our study provides a novel and complementary perspective on CRC burden, as compared with previous BMI-defined assessments [4]. We generated sex-stratified national estimates of this exposure among adults from representative health surveys in 122 countries, accounting for complex sampling and non-response adjustment. In data-scarce settings, we employed a robust multiple imputation strategy informed by relevant sociodemographic predictors, documented consistently with the GATHER guidelines. Sensitivity analysis using simpler imputation methods [200, 201] confirmed the plausibility of our estimates. To minimize bias, we excluded subnational or unrepresentative data, which were often skewed toward urban or older populations and likely to overestimate central obesity prevalence. A sensitivity analysis incorporating these data confirmed the direction of differences, supporting the conservative approach adopted in the main analysis and the robustness of our results. Nevertheless, several limitations merit consideration. Our estimates of attributable burden depend on the quality of GLOBOCAN data, which vary in completeness and accuracy—particularly in low-resource settings. In such regions, this may lead to underestimating CRC incidence and, consequently, the attributable cases. Differences in healthcare infrastructure, such as access to screening, surveillance, and diagnostic capacity, may further contribute to variability across countries. Additionally, the introduction of screening programs in certain countries over the past decade may have temporarily increased incidence due to lead-time bias, while reducing long-term risk through removal of precancerous lesions. These dynamics may affect absolute case estimates but are unlikely to affect PAFs. Central obesity prevalence was estimated from aggregated data using sex- and ethnicity-specific thresholds. In countries with multiple recommended definitions [6, 9, 177], we applied probabilistic strategies to capture this variability. As expected, this led to wider uncertainty intervals in specific settings, consistent with previous findings on the impact of alternative definitions [11, 26]. In the absence of prevalence data, we used standard methods based on reported waist circumference distributions, which assume normality. Validation against observed data showed good concordance, and available distributions indicated only modest deviations, with slight right skewness in higher-prevalence countries and slight left skewness in lower prevalence settings, supporting the pragmatic use of a normal approximation. Our analysis could not assess potential interactions between central obesity and other CRC risk factors, nor account for differences in fat composition (e.g. visceral versus subcutaneous) between sexes, or capture differences in anatomical CRC localization. These limitations, common to PAF modelling studies, underscore the need for prospective cohorts with individual-level data and more direct measures of visceral fat. We applied pooled RRs across sexes, derived from prospective cohort studies that adjusted for major confounders, assuming that ethnicity-specific waist circumference thresholds used to define exposure prevalence accurately capture differences in CRC risk. These RRs were applied globally under the assumption that the biological relationship between central obesity and CRC is broadly comparable across settings, with country-specific incidence and sex-specific exposure prevalence capturing much of the geographic variation. While this appears reasonable, it is primarily supported by data from Caucasian Europid populations [182], highlighting the need for studies in more diverse groups. In addition, our estimates are specific to CRC and should not be extrapolated to all obesity-related cancers, because population-attributable fraction modelling requires a sufficiently robust causal exposure–disease relationship, and the degree of causal support for central obesity is not uniform across cancer sites. Presenting all obesity-related cancers within a single comparative framework would therefore risk conveying a similar level of epidemiological certainty across outcomes supported by more heterogeneous evidence. Central obesity was defined using waist circumference, which is the most widely standardised and globally available measure and corresponds to the exposure metric used in the underlying RR estimates [182]. Other pertinent anthropometric indicators, including waist-to-hip ratio, are not yet supported by sufficiently comparable and detailed global exposure data and risk estimates. As with other analyses based on international cancer surveillance data, our estimates are constrained by the temporal scope of the underlying GLOBOCAN dataset (2022). Finally, although colon and rectal cancers are reported separately in GLOBOCAN, subsite-specific burden estimates were not derived because the corresponding sex-specific risk estimates for central obesity remain less complete and less consistent than those for overall CRC, limiting the robustness and internal coherence of separate estimates. ## Conclusions In summary, more than 300 000 CRC cases globally in 2022 were attributable to central obesity. Our findings align with growing evidence that abdominal adiposity may be a stronger predictor of CRC risk than BMI-defined obesity [4, 5, 7, 8, 184, 185]. The estimated 10-year excess CRC risk from central obesity was of similar absolute magnitude to the benefit observed in screening trials [202], underscoring its clinical relevance. These results highlight the potential value of central obesity as a tool to refine screening programs, while emphasizing that the cornerstone of public health action remains population-level prevention of central obesity to reduce future CRC burden. Although the global burden was nearly evenly split between sexes, distinct regional and socioeconomic patterns emerged, consistent with the obesity transition model [192]. In males, lower burden in transitioning settings is expected to increase with ongoing socio-economic development. Simultaneously, CRC incidence is rising among younger adults, often presenting at advanced stages and with distal or rectal localization [203]. This shifting epidemiology is particularly relevant in light of evidence linking central obesity to early-onset CRC, especially of left-sided origin [204]. These patterns underscore the urgency of enhancing surveillance strategies and re-evaluating CRC screening protocols, including earlier initiation and the integration of sensitive biomarkers, particularly for individuals with abdominal obesity [205, 206]. Strengthening central obesity surveillance is essential. Routine, standardized measurement of waist circumference using sex- and ethnicity-specific thresholds for each individual should be incorporated into national health surveys. Uniform cut-offs risk misclassification and obscure ethnic differences in health risk. Transitioning to individualized classification would reduce uncertainty in future burden estimates and support more equitable and targeted prevention strategies. Multisectoral approaches to reduce abdominal obesity are urgently needed. Integrating measures of central adiposity into CRC screening and prevention may offer a timely opportunity to curb the global burden of this malignancy. ## Supplementary Information Additional file Appendix Table S1‒Sources of data. Appendix Table S2‒Waist circumference cut-offs for defining central obesity. Supplementary Methods S1. Appendix Table S3‒Waist circumference thresholds used for estimating the prevalence of central obesity. Appendix Table S4‒Age-standardized colorectal cancer incidence attributable to central obesity for countries with imputed prevalence data. Appendix Table S5‒Burden of colorectal cancer in 2022 attributable to central country-level estimates. Appendix Table S6‒Colorectal cancer cases attributable to central obesity by sex and UN sensitivity analysis 1. Appendix Table S7‒Colorectal cancer cases attributable to central obesity by sex and UN sensitivity analysis 2. Appendix Table S8‒Country-specific estimates of 10-year absolute risk difference (%) between individuals without and with central obesity, and number of excess colorectal cancer cases attributable to central obesity among adults aged 55–69 years.