{"paper_id":"4e64f5ec-aea3-4919-b197-648aad4fbbc1","body_text":"Colorectal Cancer Screening Over 25 Years: Evaluating Mortality Declines and Ongoing Disparities | 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 Colorectal Cancer Screening Over 25 Years: Evaluating Mortality Declines and Ongoing Disparities Mohamed Eldesouki, Mohammed Y. Youssef, Mohamed Ali, Muhammed Umer, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7015087/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2025 Read the published version in Digestive Diseases and Sciences → Version 1 posted 7 You are reading this latest preprint version Abstract Introduction: Colorectal cancer (CRC) is the fourth most common cancer in the U.S and second leading cause of cancer deaths. While screening rates have increased and mortality rates have declined, disparities persist. This study investigates the screening rates and mortality correlation over 25 years. Methods: We analyzed trends in age-adjusted CRC screening and mortality rates (AAMRs) for adults aged ≥50 using BRFSS and CDC WONDER databases respectively. Correlation analysis between CRC screening rates and AAMRs, and projected AAMRs at 100% screening rates were calculated using Jamovi and R software. Results : CRC screening rates increased from 41.5% in 1999 to 76.3% in 2023. Non-Hispanic Whites recorded the highest rates (80.1%) while, American Indians or Alaskan Natives (AI/AN) had a low screening rate of 48.65% in 2023. Non-insured individuals had a screening rate of 33.02%, while insured recorded 78.13% in 2023. AAMRs of CRC declined significantly over time, from 69.3% to 40.7% per 100,000 (1999–2024). AAMRs demonstrated a strong inverse correlation (–0.885) with screening rates. Correlation analysis revealed stronger associations between screening and mortality for NH Whites and African Americans (AA) populations (–0.824 and –1.19, respectively). The projected AAMR at 100% screening was 18.91 (95% CI: 17.92–19.91), versus 40.4 at 76.3% in 2023. Conclusion: CRC screening increased over the past 25 years, achieving 76.3% in 2023, correlating with decrease in AAMRs. Disparities persist across races, and different socioeconomic groups. At 100% screening rates, projected AAMR is 18.919. Equity-focused interventions are needed to further increase CRC screening rates. Colorectal cancer CRC screening CRC mortality health disparities epidemiology public health. Figures Figure 1 Figure 2 Figure 3 Article Highlights - Trend of CRC rate from 1999-2023 - Impact of CRC screening on CRC mortality - Disparities between races over the same period Introduction Colorectal (CRC) cancer is the fourth most common cancer in the US, representing the second cause of cancer-related deaths (1,2). CRC represents a significant public health problem; it is projected to increase by 60% with more than 2.2 million new cases and 1.1 million deaths expected by 2030 (3). A recent report by the National Colorectal Cancer Roundtable (NCCRT) estimated that there would be 107,320 cases of colon cancer in the US, and a mortality of 52,900 (4). Incidence and mortality rates of CRC decreased significantly over the past two decades, with a decline of 34% in the overall cancer mortality rate from 1991 to 2022 in the United States (4). This decline is largely attributed to advancements in screening measures and intervention modalities; however, screening tests remain underutilized (5). Notably, CRC incidence has been rising among younger adults; therefore, the U.S. Preventive Services Task Force (USPSTF) recommended initiating CRC screening at age 45 years old, lowering the previous starting age from 50 in 2021 (12,13). Multiple factors contribute to the increase in CRC screening rates such as heightened national awareness of screening and prevention, changes in healthcare policies, and sincere efforts to increase screening access across the nation and in minorities specifically (8). We aim to investigate CRC screening trends, their correlation with CRC mortality, and disparities across gender, race, and other demographics, using two large national databases: the Behavioral Risk Factor Surveillance System (BRFSS) and the Centers for Disease Control and Prevention Wide-Ranging ONline Data for Epidemiologic Research database (CDC WONDER), spanning the years 1999 to 2024. Methods Data source: BRFSS database Data on CRC screening was obtained from BRFSS, spanning the years 1999 to 2023. BRFSS is a large, annual cross-sectional survey that collects data from more than 400,000 U.S. adults aged 18 years and older. The survey focuses on health-related risk behaviors and the use of preventive services (9). We analyzed responses from individuals aged ≥ 50 who were asked whether they had received a colonoscopy or sigmoidoscopy as a CRC screening method. Age-adjusted annual screening rates per 1,000 were calculated using analytic codes provided by BRFSS. Sociodemographic variables, including race, sex, income, education, and insurance, were obtained. Data for Hispanic individuals before 2001 were unavailable. CDC WONDER database CRC-related deaths were obtained from the CDC WONDER database for the years 1999 to 2024. This database is based on death certificates across all 50 states and the District of Columbia, it includes information on underlying and contributing causes of death, as well as demographic details (e.g., sex, race/ethnicity, and age) and geographic data (e.g., urban-rural classification, county, state, and census region). Deaths attributed to CRC were identified using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: malignant neoplasm of colon (C18), rectosigmoid junction (C19), and rectum (C20). The analysis included individuals aged 45 and older. Age-adjusted mortality rates (AAMRs) were calculated by multiplying age-specific death rates for each age group by the respective weight from a standard population and multiplying by 100,000. For urban-rural classifications, counties were categorized using the 2013 National Center for Health Statistics Urban-Rural Classification Scheme, dividing them into urban areas (large metropolitan areas with populations ≥1 million) and rural areas (populations <50,000). Since both BRFSS and CDC WONDER provide publicly available, de-identified data, this study did not require institutional review board approval. Statistical Analysis: Age-adjusted annual CRC screening rates were calculated using a post-stratification weighting method employed by BRFSS. Analysis was performed using SPSS (Version 29.0.2.0, IBM Corp., Armonk, NY) to generate annual rates per 1,000 individuals aged ≥50. In addition, Joinpoint Regression Program (Version 5.2.0.0, National Cancer Institute) was utilized to identify trends and significant temporal changes in annual screening rates and AAMRs, by applying log-linear regression and the Monte Carlo permutation test to calculate annual percent changes (APC) with 95% confidence intervals (CI). Statistical significance was set at P < 0.05. Correlation between screening rates and AAMRs was analyzed using Jamovi (Version 2.0, The Jamovi Project, 2022) and R (Version 4.1, R Core Team, 2021) to get the coefficient correlation between the screening rates and AAMR (10,11). Last, we used the linear regression analysis model to get the projected CRC-related AAMR at screening rates of 100%, assuming no other confounding factors. Results Time trends in CRC screening rates in 1999–2023 among individuals ≥50 years old CRC screening rates increased from 41.53% (CI: 40.93–42.12) in 1999 to 76.30% (CI: 75.44–77.16) in 2023 (Table 1, Figure 1.a, S3). The screening Average Annual Percent Change (AAPC) showed a significant increase from 1999 to 2013 of 3.31 (95% CI: 2.76–4.36; p < .01), then followed by a milder non-significant rise of 0.25 (95% CI: –0.34–0.72; p = .31) until 2023 (Table 2, Figure S1). CRC Screening rate by gender Both genders demonstrated comparable CRC screening rates. In 1999, the screening rate for men was 43.73% (95% CI: 42.79–44.68), increasing to 75.55% (95% CI: 74.27–76.83) in 2023. The screening rate for women was 40.15% (95% CI: 39.38–40.38) in 1999, rising to 76.93% (95% CI: 75.77–78.09) in 2023 (Table 1, Figure 1.a). CRC Screening rate by race The Non-Hispanic (NH) White population had the highest CRC screening rates, increasing from 42.14% (95% CI: 41.52–42.77) in 1999 to 80.09% (95% CI: 79.12–81.06) in 2023. Similarly, AI/AN had the lowest screening rate of 34.25% (95% CI: 29.17–39.33) in 1999, which increased to 48.65% (95% CI: 32.54–64.75) in 2023 (Table 1, Figure 1.b). CRC Screening rate according to different education and income levels Individuals who never attended school had screening rates of 28.02% (95% CI: 17.10–38.93%) in 1999, which increased to 38.46% (95% CI: 23.22–63.74%) in 2023. College graduates had the highest screening rates, starting at 47.62% (95% CI: 46.45–48.78%) in 1999 and increasing to 81.19% (95% CI: 80.04–82.33%) in 2023 (Table 1, Table 2, Figures 2.a). Individuals with an income of $100,000 or more had a higher CRC screening rate of 47.53% (95% CI: 45.69–49.38%) in 1999, which increased to 80.97% (95% CI: 78.66–82.27%) in 2023. In contrast, individuals with an income of $10,000 or less had a lower screening rate of 36.56% (95% CI: 34.39–38.73%) in 1999, and 46.20% (95% CI: 38.73–53.67%) in 2023 (Table 1, Table 2, Figure S2). CRC Screening rate across insurance coverage Insured individuals had a rising screening rate from 42.83% (95% CI: 42.22–43.44%) in 1999 to 78.13% (95% CI: 77.26–78.99%) in 2023. However, uninsured had lower screening rates of 24.49% (95% CI: 21.69–26.81%) in 1999 and 33.02% (95% CI: 27.85–38.19%) in 2023. (Table 1, Figure 2.b, S4) Time trends in CRC age-adjusted mortality rates in individuals 45 and older (1990–2024) Overall CRC Mortality The age-adjusted mortality rate (AAMR) related to CRC declined significantly in individuals >45, from 69.3 (95% CI: 68.7–69.8) in 1999 to 40.7 (95% CI: 40.3–41.0) in 2024. The AAPC showed a decline of –2.41 (95% CI: –2.72 to –2.13, p < 0.01) (Tables S3, S4, Figure 2.a). CRC Mortality rates by gender AAMR was higher in males compared with females. In males, the AAMR was 86.3 (95% CI: 85.3–87.2) in 1999, decreasing to 48.8 (95% CI: 48.3–49.4) in 2024. In females, the AAMR was 57.7 (95% CI: 57.1–58.4) in 1999, decreasing to 33.8 (95% CI: 33.4–34.2) in 2024. (Table 4; Figure 3.a) CRC Mortality by race AA recorded the highest AAMR between races with an AAMR of 91 (88.9–93.1) in 1999, then it decreased to 48.8 (47.7–49.9) in 2024. Asians recorded the lowest AAMR of 39.1 (26.3–28.7) in 1999, and 26.7 (25.6–27.8) in 2024. (Table 4; Tables S4; Figures 3b) CRC Mortality in rural and urban areas CRC-related AAMR was higher in rural areas compared with urban areas. In rural (non-metro) areas, the AAMR was 71.7 (95% CI: 69.9–73.5) in 1999 and 50.8 (95% CI: 49.4–52.2) in 2020. In urban (large central metro) areas, the AAMR was 69.0 (95% CI: 68.0–70.0) in 1999, and 38.2 (95% CI: 37.6–38.8) in 2020. (Table S3) Correlation between CRC screening rates and AAMRs Mortality data from CRC was compared to screening rates, which demonstrated a strong inverse correlation of –0.885 (95% CI: –0.958 to –0.813, p < 0.01) between CRC screening rates and AAMR in the general population. Among racial groups, the correlation analysis revealed stronger associations for NH Whites and AA, with correlations of –0.824 (95% CI: –0.871 to –0.762, p < 0.01) and –1.19 (95% CI: –1.06 to –0.871, p < 0.01). Asians showed the weakest correlation, with a value of –0.389 (95% CI: –0.532 to –0.251, p < 0.01) (Table S5). Projected CRC-AAMR at a screening rate of 100% The projected overall CRC-AAMR at a 100% screening rate was 18.919, compared to 40.4 at a screening rate of 76.3% in 2023. For females, the projected AAMR was 16.92 at 100% screening, while it was 33.5 at a screening rate of 76.93% in 2023. Males had a higher predicted AAMR of 18.89, compared to females, and their AAMR was 48.5 at a screening rate of 75.55%. Among racial groups, Whites had an estimated AAMR of 19.29 at 100% screening, compared to 40.6 at a screening rate of 80.09% in 2023. AA had a projected AAMR of 21.39 at 100% screening but recorded an AAMR of 48.7 at a screening rate of 70.14% in 2023. Hispanics had a projected AAMR of 16.08 at 100% screening, but their AAMR was 32.4 at a screening rate of 64.86% in 2023. Asians had the lowest estimated AAMR of 14.99 at 100% screening rates (Table S6). Discussion CRC screening is a grade A recommendation from the U.S. Preventive Task Force; this means that with high certainty, screening for CRC in adults between 45 and 75 years has substantial net benefit ( 12 , 13 ). The most recent data as of 2021 showed the screening rate among adults between 50–75 is 69.9%, which represents an increase from 47.7 in 2005 ( 15 ). While this demonstrates substantial progress over the past two decades, the rate remains below the national target of 80% ( 16 ). In this study, we shed light on the CRC screening rate, mortality, and the projected AAMR at 100% screening rates. The data showed increased CRC screening rates from 41.53–76.3% between 1999 and 2023 but the disparities in screening rates persisted ( 17 , 18 ). These disparities can be explained by barriers such as socioeconomic status, lack of insurance, and limited education. The increase was most significant between the years 1999 and 2013. The observed increased rates of screening are related to the observed decline in CRC mortality rates. AI/PI, despite their lower screening rates, recorded the lowest overall AAMR. This finding does not align with the traditional models associating lower screening rates with higher mortality. Potential protective factors, such as cultural attitudes toward health and family support systems, may contribute to this discrepancy ( 19 , 20 ). When projected at 100% screening rates, the estimated AAMR falls to 18.92 compared to 40.4 per 100,000 in 2023 at a screening rate of 76.30%. However, there is still disparity persisted across races and genders ( 21 ). Also, at 100% screening rates, AA would still show higher mortality rates. This indicates the potential existence of other factors that affect the outcomes. The disparity could be attributed to the fact that they are more likely to present late with advanced disease, increasing mortality even with high screening rates, in addition to the systemic healthcare inequities including delays in diagnosis and treatment as highlighted by other studies ( 23 – 25 ). It is well established that disparities exist between races and different socioeconomic backgrounds ( 26 , 27 ), similar results were observed, where lower income, lack of insurance, and limited education affected screening rates. These factors were compounded by geographic disparities, with rural populations representing additional challenges to healthcare access. These barriers will require comprehensive strategies, including community-based programs that provide culturally relevant education and navigation services ( 28 ). Several solutions have been suggested to tackle these barriers, with patient education remaining the cornerstone in CRC screening. Integrating culturally tailored education and outreach activities recommended by the National Cancer Institute remains a top priority ( 29 ). Furthermore, structured community-based strategies aiming to address barriers faced by minorities and underserved populations, as they are the most vulnerable group, would be beneficial in achieving equity as highlighted by previous research ( 30 , 31 ). Implementing electronic physician reminders showed that it’s beneficial to increase rates of CRC screening referrals during office visits ( 32 ). Also, involving nonphysician team members has been shown to increase referral rates as it addresses the issue of physicians’ lack of time ( 33 ). Colorectal cancer screening rates showed upward trends until the 2020 COVID pandemic. Then, all cancer screening rates dramatically declined ( 34 ). An international study estimated a global decline of 90%, leading to a 32% reduction in new CRC diagnoses and hence a 53% decline in CRC-related surgeries ( 35 ). Similarly, the study observed a noticeable decline in CRC screening rates in 2020, followed by a gradual increase in subsequent years. Interestingly, the study showed that the disparities in CRC screening increased even more during COVID. The decline in cancer screening rates could be attributed to several reasons, one of them being the temporary closure of screening facilities, with staff shortages and resource relocation toward COVID management ( 38 ). Other population-related causes include patient hesitancy due to fear of contracting the virus, along with the socioeconomic challenges of losing jobs and health insurance ( 39 ). Although COVID is no longer a pandemic, the screening rates did not return to pre-COVID levels. Also, a microsimulation study projected that the pandemic could lead to long-term negative outcomes in CRC indices and mortality ( 40 ). This is a high alarm that we should relocate more resources toward CRC screening advocacy among the population. The study offered several notable strengths, as it is the first study of its type to involve 25 years, providing a robust longitudinal perspective on CRC screening and mortality rates, taking into consideration the differences among races, genders, socioeconomic standards, and education levels, allowing for comparison and revealing disparities in screening rates and the outcomes. Moreover, this study is unique in the use of projection models in estimating the AAMR at 100% screening rates among the entire population and providing the estimate among minorities and different groups. There are several limitations that affected the study. The use of the BRFSS database comes with the downside that most of the data is self-reported, relying on the accuracy of respondents’ recall ability and truthfulness regarding the screening test and its timing, which can lead to recall bias or reporting bias when individuals do not respond to the survey. Another limitation is that the National Health Interview Survey (NHIS) data does not differentiate between screening and diagnostic colonoscopy or sigmoidoscopy, which, in theory, could create discrepancies between the reported data and real-life data. However, studies have found moderate to good agreement between self-reported data and information from medical records ( 40 , 41 ). Additionally, the nature of the CDC WONDER database, which relies on death certificates, may be subject to human error, misidentification of the cause of death, or data loss during file compilation, potentially resulting in underreporting of CRC-related mortality. The database may also lack important individual variables that could influence outcomes, such as healthcare access, comorbidity burden, or medical treatment. Another limitation of this approach is that CDC WONDER reports AAMR only for each ten-year age group (45–55), requiring us to estimate the AAMR for individuals aged 45 while using screening rates for those aged 50. Conclusion This study highlights significant progress in CRC screening over the last 25 years, achieving 76.30% in 2023. The increase in CRC screening rates correlates with the decrease in CRC AAMR. However, disparities persist across races, genders, and different socioeconomic groups. Even at the projected 100% colonoscopy rates, these disparities would remain, emphasizing that although universal screening and timely intervention could reduce mortality, equity must be prioritized to further reduce CRC mortality. Continued research is pivotal in identifying effective interventions to address the gaps in CRC screening. Abbreviations AAMR Age-Adjusted Mortality Rate AA African American AI/AN American Indian or Alaskan Native APC Annual Percent Change BRFSS Behavioral Risk Factor Surveillance System CDC Centers for Disease Control and Prevention CMS Centers for Medicare & Medicaid Services CRC Colorectal Cancer ICD-10-CM International Classification of Diseases, 10th Revision, Clinical Modification NCCRT National Colorectal Cancer Roundtable NCHS National Center for Health Statistics NH Non-Hispanic NH/PI Native Hawaiian or Other Pacific Islander NCI National Cancer Institute NHIS National Health Interview Survey SPSS Statistical Package for the Social Sciences USPSTF U.S. Preventive Services Task Force Declarations Conflict of Interest The authors declare no conflicts of interest. Funding The authors received no financial support or funding for the research, authorship, and/or publication of this article. Author Contribution M.E., M.Y., and M.A.A. conceived the study concept and design. M.E. and M.U. performed data analysis. M.Y. and A.A.A. contributed to data interpretation. K.E. and M.Y. drafted the initial manuscript. A.S. critically revised the manuscript for important intellectual content and provided senior supervision. All authors reviewed and approved the final version of the manuscript. Data Availability The data used in this study were obtained from publicly available databases: the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) and the Behavioral Risk Factor Surveillance System (BRFSS). Both sources provide de-identified, aggregate data that are freely accessible to the public. No individual-level or identifiable information was used. References Gupta S. Screening for colorectal cancer. Hematol Oncol Clin North Am. 2022;36(3):393–414. Siegel RL, Wagle NS, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2023. CA Cancer J Clin. 2023;73(3):233–254. 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Unequal recovery in colorectal cancer screening following the COVID-19 pandemic: A comparative microsimulation analysis. medRxiv. Preprint posted online December 26, 2022. doi:10.1101/2022.12.23.22283887 Tables Table 1. CRC screening by colonoscopy or sigmoidoscopy percentages over the study period 1999 - 2023 CRC screening by Coloscopy (%) 1999 2004 2009 2014 2019 2023 Overall 41.5 53.1 67.6 70.1 75.1 76.3 Gender Female 40.15 52.94 67.33 72.07 75.51 76.93 Male 43.73 53.28 67.98 70.60 74.49 75.55 Race White 42.14 54.20 67.67 72.53 76.44 80.09 African Americans 37.10 47.17 59.89 69.35 71.67 70.14 Hispanics 33.75 * 41.76 50.44 56.59 67.99 64.86 American Indians or Alaskan Native 34.25 40.34 60.29 56.96 70.0 48.65 Asian 37.07 38.64 56.83 56.35 58.45 64.35 Native Hawaiian or Other Pacific Islander 36.54 38.51 49.33 60.69 54.72 60 Educational level Never attended school or only kindergarten 28.02 42.45 42.15 46.28 43.48 38.46 Elementary school (Grade 1-8) 35.25 48.54 56.25 53.93 64.77 55.74 Some high school (Grade 9 – 11) 37.73 48.46 54.63 58.41 62.35 58.61 High school graduates (Grade 12 or GED) 39.47 50.96 63.86 66.91 69.34 68.97 Some college or technical school (college 1-3) 43.11 53.04 67.12 72.34 74.77 77.81 College Graduate (4 years or more) 47.62 54.42 74.50 78.23 80.61 81.19 Income level < $ 10,000 36.56 42.45 59.71 52.71 63.47 46.20 $ 10,000 - $15,000 39.95 48.54 66.40 61.75 68.87 64.90 $ 15,000 – 20,000 41.06 48.46 56.42 63.28 66.35 65.73 $ 20,000 - 25,000 41.27 50.96 62.96 67.34 59.51 67.44 $ 25,000 - 35,000 43.12 53.04 66.99 69.90 70.56 70.18 $ 35,000 -50,000 54.42 70.14 73.73 73.73 73.56 78.92 $ 50,000 -75,000 42.50 54.69 72.52 76.15 81.12 78.05 $ 75,000 - 100,000 47.62 54.42 74.50 78.23 80.61 80.97 Insurance level Insured 42.83 55.11 69.64 73.23 76.55 78.13 Non-Insured 24.25 29.06 40.54 36.26 45.60 33.02 Table 2. Trend analysis of the annual percentage changes in screening rates 1999 – 2023 Variables Years APC 95% CI P-Value Overall 1999 - 2013 3.31 2.76 – 4.36 < 0.01 2013 - 2023 0.25 -0.34 – 0.72 0.31 Gender Female 1999 - 2013 3.49 2.98 – 4.55 < 0.01 2013 -2023 0.11 -0.47 – 0.58 0.6 Male 1999 - 2013 3.18 2.62 – 4.11 < 0.01 2013 - 2023 0.06 -0.51 – 0.49 0.7 Race White 1999 - 2011 4.06 3.35 – 5.24 < 0.01 2011 - 2023 0.49 0.10 – 0.86 0.02 Black or African American 1999 - 2013 4.23 3.77 – 4.85 < 0.01 2013 -2023 0.14 - 0.19 – 0.51 0.33 Hispanic 2001 - 2015 3.05 2.01 – 5.97 < 0.01 2015 - 2023 -0.91 -3.04 – 0.31 0.11 Asian 1999 - 2009 4.67 2.80 – 9.16 < 0.01 2009 - 2023 -0.11 - 0.75 – 0.41 0.65 Native Hawaiian or other Pacific Islander 1999 - 2015 4.51 3.32 – 7.38 < 0.01 2015 - 2023 -2.11 - 3.69 – - 0.87 < 0.01 American Indian or Alaskan Native 1999 - 2013 3.07 2.47 – 4.17 < 0.01 2013 - 2023 0.01 -1.05 – 0.73 0.95 Level of education Never attended school or only kindergarten 1999 - 2004 8.71 1.04 – 9.22 0.01 2004 - 2023 0.51 -0.31 – 0.88 0.14 Elementary School 1999 - 2013 2.61 1.89 – 4.18 < 0.01 2013 - 2023 -0.14 -1.83 – 0.81 0.72 High school graduate 1999 - 2011 3.95 3.33 – 4.82 < 0.01 2011 - 2023 0.48 0.15 – 0.81 < 0.01 College graduate 1999 - 2013 3.28 2.64 – 4.63 < 0.01 2013 - 2023 -0.41 -1.06 – 0.12 0.13 Level of income $10 K 1999 - 2009 3.45 2.49 – 5.9 < 0.01 2009 -2023 0.88 0.33 – 1.28 0.016 $ 20 k 1999 - 2011 3.37 2.82 – 4.57 < 0.01 2011 -2023 0.71 0.21 – 1.09 0.013 $ 50 K 1999 - 2011 4.47 3.76 – 5.38 < 0.01 2011 -2023 0.33 -0.2 – 0.67 0.05 $ 75 K 1999 - 2015 2.52 1.94 – 3.68 < 0.01 2015 - 2023 -1.43 -2.77 – - 0.49 < 0.01 $100 K 1999 - 2009 3.45 2.49 – 5.9 < 0.01 2009 -2023 0.88 0.33 – 1.28 0.016 Insurance status Insured 1999 - 2011 4.11 3.41 – 5.06 < 0.01 2011 -2023 0.31 -0.03 – 0.63 0.07 Non-Insured 1999 - 2018 2.29 1.91 – 2.91 < 0.01 2018 - 2023 -6.84 -12.36 – - 4.33 < 0.01 Additional Declarations No competing interests reported. Supplementary Files suppdata.docx Cite Share Download PDF Status: Published Journal Publication published 13 Nov, 2025 Read the published version in Digestive Diseases and Sciences → Version 1 posted Editorial decision: Revision requested 15 Sep, 2025 Reviews received at journal 13 Sep, 2025 Reviewers agreed at journal 22 Aug, 2025 Reviewers invited by journal 07 Jul, 2025 Editor assigned by journal 01 Jul, 2025 Submission checks completed at journal 01 Jul, 2025 First submitted to journal 30 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7015087\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":481984673,\"identity\":\"5c67305f-d2b1-40ab-9ba9-6ffbc1536c6c\",\"order_by\":0,\"name\":\"Mohamed Eldesouki\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"New York Medical College at Saint Michael’s Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohamed\",\"middleName\":\"\",\"lastName\":\"Eldesouki\",\"suffix\":\"\"},{\"id\":481984674,\"identity\":\"9a26c810-0a85-4418-8c76-bd50866800a3\",\"order_by\":1,\"name\":\"Mohammed Y. Youssef\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYFACHjDJ2ADhycnxszcwMJOixdhYsucAiVoSN8xIwK9Ft7334KebOTayG473GH/8UWGQuEHyjeHnggobBv727gRsWszOnEuWzt2WZrzhzBkzaZ4zBsbbpXOMpWecSWOQOHN2A1YtN3IMgFoOJ264kWPGzNj2R3bnbKAIb9thBgOJXFxajH/nbvsP0mL88ec/A8YNN88Y/yagxQxoywGQFgMJ3gYDxQ03eMzw2wL0gnXutmTjmWeOlUnzHDMABnJamTXPmTQenH4BBtTt3G12sn3Hmzd//FFjAIzKw5tv81TYyPG392LVAgcKB+BMDgMQyYNXOQjIN8CZ7A8Iqh4Fo2AUjIIRBQB9bWrNHYNv2AAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Hunt Regional Medical Center\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Mohammed\",\"middleName\":\"Y.\",\"lastName\":\"Youssef\",\"suffix\":\"\"},{\"id\":481984675,\"identity\":\"5542e3a9-eaac-440d-bcb6-5df670ec2529\",\"order_by\":2,\"name\":\"Mohamed Ali\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"South Valley University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohamed\",\"middleName\":\"\",\"lastName\":\"Ali\",\"suffix\":\"\"},{\"id\":481984676,\"identity\":\"4ac4686a-ec6b-4cd6-af9f-0fff901421a4\",\"order_by\":3,\"name\":\"Muhammed Umer\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"New York Medical College at Saint Michael’s Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Muhammed\",\"middleName\":\"\",\"lastName\":\"Umer\",\"suffix\":\"\"},{\"id\":481984677,\"identity\":\"0d06ef7e-86cf-4c8b-bec6-c4b6b4c2ff31\",\"order_by\":4,\"name\":\"Abdelaziz Awad\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Al-Azhar University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Abdelaziz\",\"middleName\":\"\",\"lastName\":\"Awad\",\"suffix\":\"\"},{\"id\":481984678,\"identity\":\"fb89e492-8be0-47a7-a4bd-75ac56e47bac\",\"order_by\":5,\"name\":\"Khaled Elfert\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"West Virginia University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Khaled\",\"middleName\":\"\",\"lastName\":\"Elfert\",\"suffix\":\"\"},{\"id\":481984680,\"identity\":\"97582b94-c3d0-4b66-be1e-3b8b0da16b18\",\"order_by\":6,\"name\":\"Aasma Shawkat\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"NYU Grossman School of Medicine, NYU Langone Health\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Aasma\",\"middleName\":\"\",\"lastName\":\"Shawkat\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-07-01 02:23:06\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-7015087/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-7015087/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1007/s10620-025-09472-3\",\"type\":\"published\",\"date\":\"2025-11-13T15:57:20+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":86514741,\"identity\":\"8de03734-2e7a-48c2-ad93-076388e95b4f\",\"added_by\":\"auto\",\"created_at\":\"2025-07-11 13:53:32\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":104309,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003e(a)\\u003c/strong\\u003e Screening rates across gender from 1999 to 2023, showing an overall upward trend in CRC screening for both males and females. \\u003cstrong\\u003e(b)\\u003c/strong\\u003eScreening rates across racial groups from 1999 to 2023, demonstrating an overall increase in CRC screening but persistent disparities.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7015087/v1/2c218fc0f220e848fe87328a.png\"},{\"id\":86514102,\"identity\":\"8bf8924a-49e1-42c6-a39b-096538096a21\",\"added_by\":\"auto\",\"created_at\":\"2025-07-11 13:45:32\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":109248,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003e(a)\\u003c/strong\\u003e CRC screening rates by education level (1999–2023), showing higher rates among college graduates and lower uptake among those with no formal education. \\u003cstrong\\u003e(b)\\u003c/strong\\u003e Screening rates by insurance status (1999–2023), with insured individuals consistently having higher rates than uninsured.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7015087/v1/d1c395656d83bd7a7569630b.png\"},{\"id\":86514747,\"identity\":\"8a2d0892-f155-4ffb-918b-b9e0e40a580d\",\"added_by\":\"auto\",\"created_at\":\"2025-07-11 13:53:32\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":306234,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e(a) CRC age-adjusted mortality rate (AAMR) by gender (1999–2024), showing a consistent decline over time, with males having higher mortality rates than females. (b) CRC age-adjusted mortality rates (AAMR) race from 1999 to 2020. While AAMR declined across all racial groups, Black or African American individuals consistently had the highest mortality rates, whereas Asian or Pacific Islander populations had the lowest.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7015087/v1/c554279409b98f7eaa00c3a2.png\"},{\"id\":96104986,\"identity\":\"e15c95dd-d67e-4493-bb13-1356f891100f\",\"added_by\":\"auto\",\"created_at\":\"2025-11-17 16:06:24\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1439379,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7015087/v1/f27b0975-613a-4d16-879f-f28c505dad22.pdf\"},{\"id\":86514100,\"identity\":\"0da8e6ed-444d-4a4d-8fa8-8e5f23ce5c7c\",\"added_by\":\"auto\",\"created_at\":\"2025-07-11 13:45:32\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1040099,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"suppdata.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7015087/v1/f2dea91c221f9c0528c9e8f8.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Colorectal Cancer Screening Over 25 Years: Evaluating Mortality Declines and Ongoing Disparities\",\"fulltext\":[{\"header\":\"Article Highlights\",\"content\":\"\\u003cp\\u003e- Trend of CRC rate from 1999-2023\\u003c/p\\u003e\\n\\u003cp\\u003e- Impact of CRC screening on CRC mortality\\u003c/p\\u003e\\n\\u003cp\\u003e- Disparities between races over the same period\\u003c/p\\u003e\"},{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eColorectal (CRC) cancer is the fourth most common cancer in the US, representing the second cause of cancer-related deaths (1,2). CRC represents a significant public health problem; it is projected to increase by 60% with more than 2.2 million new cases and 1.1 million deaths expected by 2030 (3). A recent report by the National Colorectal Cancer Roundtable (NCCRT) estimated that there would be 107,320 cases of colon cancer in the US, and a mortality of 52,900 (4).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;Incidence and mortality rates of CRC decreased significantly over the past two decades, with a decline of 34% in the overall cancer mortality rate from 1991 to 2022 in the United States (4). This decline is largely attributed to advancements in screening measures and intervention modalities; however, screening tests remain underutilized (5). Notably, CRC incidence has been rising among younger adults; therefore, the U.S. Preventive Services Task Force (USPSTF) recommended initiating CRC screening at age 45 years old, lowering the previous starting age from 50 in 2021 (12,13). Multiple factors contribute to the increase in CRC screening rates such as heightened national awareness of screening and prevention, changes in healthcare policies, and sincere efforts to increase screening access across the nation and in minorities specifically (8).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;We aim to investigate CRC screening trends, their correlation with CRC mortality, and disparities across gender, race, and other demographics, using two large national databases: the Behavioral Risk Factor Surveillance System (BRFSS) and the Centers for Disease Control and Prevention Wide-Ranging ONline Data for Epidemiologic Research database (CDC WONDER), spanning the years 1999 to 2024.\\u003c/p\\u003e\"},{\"header\":\" Methods\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eData source:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBRFSS database\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eData on CRC screening was obtained from BRFSS, spanning the years 1999 to 2023. BRFSS is a large, annual cross-sectional survey that collects data from more than 400,000 U.S. adults aged 18 years and older. The survey focuses on health-related risk behaviors and the use of preventive services (9). We analyzed responses from individuals aged \\u0026ge; 50 who were asked whether they had received a colonoscopy or sigmoidoscopy as a CRC screening method. Age-adjusted annual screening rates per 1,000 were calculated using analytic codes provided by BRFSS. Sociodemographic variables, including race, sex, income, education, and insurance, were obtained. Data for Hispanic individuals before 2001 were unavailable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCDC WONDER database\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eCRC-related deaths were obtained from the CDC WONDER database for the years 1999 to 2024. This database is based on death certificates across all 50 states and the District of Columbia, it includes information on underlying and contributing causes of death, as well as demographic details (e.g., sex, race/ethnicity, and age) and geographic data (e.g., urban-rural classification, county, state, and census region). Deaths attributed to CRC were identified using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: malignant neoplasm of colon (C18), rectosigmoid junction (C19), and rectum (C20). The analysis included individuals aged 45 and older. Age-adjusted mortality rates (AAMRs) were calculated by multiplying age-specific death rates for each age group by the respective weight from a standard population and multiplying by 100,000. For urban-rural classifications, counties were categorized using the 2013 National Center for Health Statistics Urban-Rural Classification Scheme, dividing them into urban areas (large metropolitan areas with populations \\u0026ge;1 million) and rural areas (populations \\u0026lt;50,000). Since both BRFSS and CDC WONDER provide publicly available, de-identified data, this study did not require institutional review board approval.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStatistical Analysis:\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAge-adjusted annual CRC screening rates were calculated using a post-stratification weighting method employed by BRFSS. Analysis was performed using SPSS (Version 29.0.2.0, IBM Corp., Armonk, NY) to generate annual rates per 1,000 individuals aged \\u0026ge;50. In addition, Joinpoint Regression Program (Version 5.2.0.0, National Cancer Institute) was utilized to identify trends and significant temporal changes in annual screening rates and AAMRs, by applying log-linear regression and the Monte Carlo permutation test to calculate annual percent changes (APC) with 95% confidence intervals (CI). Statistical significance was set at P \\u0026lt; 0.05. Correlation between screening rates and AAMRs was analyzed using Jamovi (Version 2.0, The Jamovi Project, 2022) and R (Version 4.1, R Core Team, 2021) to get the coefficient correlation between the screening rates and AAMR (10,11). Last, we used the linear regression analysis model to get the projected CRC-related AAMR at screening rates of 100%, assuming no other confounding factors.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eTime trends in CRC screening rates in 1999–2023 among individuals ≥50 years old\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;CRC screening rates increased from 41.53% (CI: 40.93–42.12) in 1999 to 76.30% (CI: 75.44–77.16) in 2023 (Table 1, Figure 1.a, S3). The screening Average Annual Percent Change (AAPC) showed a significant increase from 1999 to 2013 of 3.31 (95% CI: 2.76–4.36; p \\u0026lt; .01), then followed by a milder non-significant rise of 0.25 (95% CI: –0.34–0.72; p = .31) until 2023 (Table 2, Figure S1).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCRC Screening rate by gender\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;Both genders demonstrated comparable CRC screening rates. In 1999, the screening rate for men was 43.73% (95% CI: 42.79–44.68), increasing to 75.55% (95% CI: 74.27–76.83) in 2023. The screening rate for women was 40.15% (95% CI: 39.38–40.38) in 1999, rising to 76.93% (95% CI: 75.77–78.09) in 2023 (Table 1, Figure 1.a).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCRC Screening rate by race\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;The Non-Hispanic (NH) White population had the highest CRC screening rates, increasing from 42.14% (95% CI: 41.52–42.77) in 1999 to 80.09% (95% CI: 79.12–81.06) in 2023. \\u0026nbsp;Similarly, AI/AN had the lowest screening rate of 34.25% (95% CI: 29.17–39.33) in 1999, which increased to 48.65% (95% CI: 32.54–64.75) in 2023 (Table 1, Figure 1.b).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCRC Screening rate according to different education and income levels\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;Individuals who never attended school had screening rates of 28.02% (95% CI: 17.10–38.93%) in 1999, which increased to 38.46% (95% CI: 23.22–63.74%) in 2023. College graduates had the highest screening rates, starting at 47.62% (95% CI: 46.45–48.78%) in 1999 and increasing to 81.19% (95% CI: 80.04–82.33%) in 2023 (Table 1, Table 2, Figures 2.a).\\u003cbr\\u003e\\u0026nbsp;Individuals with an income of $100,000 or more had a higher CRC screening rate of 47.53% (95% CI: 45.69–49.38%) in 1999, which increased to 80.97% (95% CI: 78.66–82.27%) in 2023. In contrast, individuals with an income of $10,000 or less had a lower screening rate of 36.56% (95% CI: 34.39–38.73%) in 1999, and 46.20% (95% CI: 38.73–53.67%) in 2023 (Table 1, Table 2, Figure S2).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCRC Screening rate across insurance coverage\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;Insured individuals had a rising screening rate from 42.83% (95% CI: 42.22–43.44%) in 1999 to 78.13% (95% CI: 77.26–78.99%) in 2023. However, uninsured had lower screening rates of 24.49% (95% CI: 21.69–26.81%) in 1999 and 33.02% (95% CI: 27.85–38.19%) in 2023. (Table 1, Figure 2.b, S4)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTime trends in CRC age-adjusted mortality rates in individuals 45 and older (1990–2024)\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eOverall CRC Mortality\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;The age-adjusted mortality rate (AAMR) related to CRC declined significantly in individuals \\u0026gt;45, from 69.3 (95% CI: 68.7–69.8) in 1999 to 40.7 (95% CI: 40.3–41.0) in 2024. The AAPC showed a decline of –2.41 (95% CI: –2.72 to –2.13, p \\u0026lt; 0.01) (Tables S3, S4, Figure 2.a).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCRC Mortality rates by gender\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;AAMR was higher in males compared with females. In males, the AAMR was 86.3 (95% CI: 85.3–87.2) in 1999, decreasing to 48.8 (95% CI: 48.3–49.4) in 2024. In females, the AAMR was 57.7 (95% CI: 57.1–58.4) in 1999, decreasing to 33.8 (95% CI: 33.4–34.2) in 2024. (Table 4; Figure 3.a)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCRC Mortality by race\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;AA recorded the highest AAMR between races with an AAMR of 91 (88.9–93.1) in 1999, then it decreased to 48.8 (47.7–49.9) in 2024. Asians recorded the lowest AAMR of 39.1 (26.3–28.7) in 1999, and 26.7 (25.6–27.8) in 2024. (Table 4; Tables S4; Figures 3b)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCRC Mortality in rural and urban areas\\u003c/strong\\u003e\\u003cbr\\u003eCRC-related AAMR was higher in rural areas compared with urban areas. In rural (non-metro) areas, the AAMR was 71.7 (95% CI: 69.9–73.5) in 1999 and 50.8 (95% CI: 49.4–52.2) in 2020. In urban (large central metro) areas, the AAMR was 69.0 (95% CI: 68.0–70.0) in 1999, and 38.2 (95% CI: 37.6–38.8) in 2020. (Table S3)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCorrelation between CRC screening rates and AAMRs\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;Mortality data from CRC was compared to screening rates, which demonstrated a strong inverse correlation of –0.885 (95% CI: –0.958 to –0.813, p \\u0026lt; 0.01) between CRC screening rates and AAMR in the general population. Among racial groups, the correlation analysis revealed stronger associations for NH Whites and AA, with correlations of –0.824 (95% CI: –0.871 to –0.762, p \\u0026lt; 0.01) and –1.19 (95% CI: –1.06 to –0.871, p \\u0026lt; 0.01). Asians showed the weakest correlation, with a value of –0.389 (95% CI: –0.532 to –0.251, p \\u0026lt; 0.01) (Table S5).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eProjected CRC-AAMR at a screening rate of 100%\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;The projected overall CRC-AAMR at a 100% screening rate was 18.919, compared to 40.4 at a screening rate of 76.3% in 2023. For females, the projected AAMR was 16.92 at 100% screening, while it was 33.5 at a screening rate of 76.93% in 2023. Males had a higher predicted AAMR of 18.89, compared to females, and their AAMR was 48.5 at a screening rate of 75.55%. Among racial groups, Whites had an estimated AAMR of 19.29 at 100% screening, compared to 40.6 at a screening rate of 80.09% in 2023. AA had a projected AAMR of 21.39 at 100% screening but recorded an AAMR of 48.7 at a screening rate of 70.14% in 2023. Hispanics had a projected AAMR of 16.08 at 100% screening, but their AAMR was 32.4 at a screening rate of 64.86% in 2023. Asians had the lowest estimated AAMR of 14.99 at 100% screening rates (Table S6).\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eCRC screening is a grade A recommendation from the U.S. Preventive Task Force; this means that with high certainty, screening for CRC in adults between 45 and 75 years has substantial net benefit (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). The most recent data as of 2021 showed the screening rate among adults between 50\\u0026ndash;75 is 69.9%, which represents an increase from 47.7 in 2005 (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e). While this demonstrates substantial progress over the past two decades, the rate remains below the national target of 80% (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e). In this study, we shed light on the CRC screening rate, mortality, and the projected AAMR at 100% screening rates.\\u003c/p\\u003e\\u003cp\\u003eThe data showed increased CRC screening rates from 41.53\\u0026ndash;76.3% between 1999 and 2023 but the disparities in screening rates persisted (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e). These disparities can be explained by barriers such as socioeconomic status, lack of insurance, and limited education. The increase was most significant between the years 1999 and 2013.\\u003c/p\\u003e\\u003cp\\u003eThe observed increased rates of screening are related to the observed decline in CRC mortality rates. AI/PI, despite their lower screening rates, recorded the lowest overall AAMR. This finding does not align with the traditional models associating lower screening rates with higher mortality. Potential protective factors, such as cultural attitudes toward health and family support systems, may contribute to this discrepancy (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eWhen projected at 100% screening rates, the estimated AAMR falls to 18.92 compared to 40.4 per 100,000 in 2023 at a screening rate of 76.30%. However, there is still disparity persisted across races and genders (\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e). Also, at 100% screening rates, AA would still show higher mortality rates. This indicates the potential existence of other factors that affect the outcomes. The disparity could be attributed to the fact that they are more likely to present late with advanced disease, increasing mortality even with high screening rates, in addition to the systemic healthcare inequities including delays in diagnosis and treatment as highlighted by other studies (\\u003cspan additionalcitationids=\\\"CR24\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eIt is well established that disparities exist between races and different socioeconomic backgrounds (\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e), similar results were observed, where lower income, lack of insurance, and limited education affected screening rates. These factors were compounded by geographic disparities, with rural populations representing additional challenges to healthcare access. These barriers will require comprehensive strategies, including community-based programs that provide culturally relevant education and navigation services (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eSeveral solutions have been suggested to tackle these barriers, with patient education remaining the cornerstone in CRC screening. Integrating culturally tailored education and outreach activities recommended by the National Cancer Institute remains a top priority (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e). Furthermore, structured community-based strategies aiming to address barriers faced by minorities and underserved populations, as they are the most vulnerable group, would be beneficial in achieving equity as highlighted by previous research (\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e). Implementing electronic physician reminders showed that it\\u0026rsquo;s beneficial to increase rates of CRC screening referrals during office visits (\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e). Also, involving nonphysician team members has been shown to increase referral rates as it addresses the issue of physicians\\u0026rsquo; lack of time (\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eColorectal cancer screening rates showed upward trends until the 2020 COVID pandemic. Then, all cancer screening rates dramatically declined (\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e). An international study estimated a global decline of 90%, leading to a 32% reduction in new CRC diagnoses and hence a 53% decline in CRC-related surgeries (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e). Similarly, the study observed a noticeable decline in CRC screening rates in 2020, followed by a gradual increase in subsequent years. Interestingly, the study showed that the disparities in CRC screening increased even more during COVID. The decline in cancer screening rates could be attributed to several reasons, one of them being the temporary closure of screening facilities, with staff shortages and resource relocation toward COVID management (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e). Other population-related causes include patient hesitancy due to fear of contracting the virus, along with the socioeconomic challenges of losing jobs and health insurance (\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e). Although COVID is no longer a pandemic, the screening rates did not return to pre-COVID levels. Also, a microsimulation study projected that the pandemic could lead to long-term negative outcomes in CRC indices and mortality (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e). This is a high alarm that we should relocate more resources toward CRC screening advocacy among the population.\\u003c/p\\u003e\\u003cp\\u003eThe study offered several notable strengths, as it is the first study of its type to involve 25 years, providing a robust longitudinal perspective on CRC screening and mortality rates, taking into consideration the differences among races, genders, socioeconomic standards, and education levels, allowing for comparison and revealing disparities in screening rates and the outcomes. Moreover, this study is unique in the use of projection models in estimating the AAMR at 100% screening rates among the entire population and providing the estimate among minorities and different groups. There are several limitations that affected the study. The use of the BRFSS database comes with the downside that most of the data is self-reported, relying on the accuracy of respondents\\u0026rsquo; recall ability and truthfulness regarding the screening test and its timing, which can lead to recall bias or reporting bias when individuals do not respond to the survey. Another limitation is that the National Health Interview Survey (NHIS) data does not differentiate between screening and diagnostic colonoscopy or sigmoidoscopy, which, in theory, could create discrepancies between the reported data and real-life data. However, studies have found moderate to good agreement between self-reported data and information from medical records (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e). Additionally, the nature of the CDC WONDER database, which relies on death certificates, may be subject to human error, misidentification of the cause of death, or data loss during file compilation, potentially resulting in underreporting of CRC-related mortality. The database may also lack important individual variables that could influence outcomes, such as healthcare access, comorbidity burden, or medical treatment. Another limitation of this approach is that CDC WONDER reports AAMR only for each ten-year age group (45\\u0026ndash;55), requiring us to estimate the AAMR for individuals aged 45 while using screening rates for those aged 50.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThis study highlights significant progress in CRC screening over the last 25 years, achieving 76.30% in 2023. The increase in CRC screening rates correlates with the decrease in CRC AAMR. However, disparities persist across races, genders, and different socioeconomic groups. Even at the projected 100% colonoscopy rates, these disparities would remain, emphasizing that although universal screening and timely intervention could reduce mortality, equity must be prioritized to further reduce CRC mortality. Continued research is pivotal in identifying effective interventions to address the gaps in CRC screening.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"524\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAAMR\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAge-Adjusted Mortality Rate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAA\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAfrican American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAI/AN\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAmerican Indian or Alaskan Native\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAPC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAnnual Percent Change\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eBRFSS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eBehavioral Risk Factor Surveillance System\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCDC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eCenters for Disease Control and Prevention\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCMS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eCenters for Medicare \\u0026amp; Medicaid Services\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCRC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eColorectal Cancer\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eICD-10-CM\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eInternational Classification of Diseases, 10th Revision, Clinical Modification\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNCCRT\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eNational Colorectal Cancer Roundtable\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNCHS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eNational Center for Health Statistics\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eNon-Hispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNH/PI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eNative Hawaiian or Other Pacific Islander\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNCI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eNational Cancer Institute\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNHIS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eNational Health Interview Survey\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSPSS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eStatistical Package for the Social Sciences\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eUSPSTF\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eU.S. Preventive Services Task Force\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003ch2\\u003eConflict of Interest\\u003c/h2\\u003e\\u003cp\\u003eThe authors declare no conflicts of interest.\\u003c/p\\u003e\\u003c/p\\u003e\\u003ch2\\u003eFunding\\u003c/h2\\u003e\\u003cp\\u003eThe authors received no financial support or funding for the research, authorship, and/or publication of this article.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eM.E., M.Y., and M.A.A. conceived the study concept and design. M.E. and M.U. performed data analysis. M.Y. and A.A.A. contributed to data interpretation. K.E. and M.Y. drafted the initial manuscript. A.S. critically revised the manuscript for important intellectual content and provided senior supervision. All authors reviewed and approved the final version of the manuscript.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eThe data used in this study were obtained from publicly available databases: the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) and the Behavioral Risk Factor Surveillance System (BRFSS). Both sources provide de-identified, aggregate data that are freely accessible to the public. No individual-level or identifiable information was used.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eGupta S. Screening for colorectal cancer. Hematol Oncol Clin North Am. 2022;36(3):393\\u0026ndash;414.\\u003c/li\\u003e\\n\\u003cli\\u003eSiegel RL, Wagle NS, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2023. CA Cancer J Clin. 2023;73(3):233\\u0026ndash;254.\\u003c/li\\u003e\\n\\u003cli\\u003eIlyas F, Ahmed E, Ali H, Ilyas M, Sarfraz S, Khalid M, et al. Temporal trends in colorectal cancer mortality rates (1999\\u0026ndash;2022) in the United States. Cancer Rep. 2024;7(3):e2012.\\u003c/li\\u003e\\n\\u003cli\\u003eThelen A. American Cancer Society National Colorectal Cancer Roundtable. CRC News: January 16, 2025. Published 2025. Accessed January 22, 2025. https://nccrt.org/crc-news-january-16-2025/\\u003c/li\\u003e\\n\\u003cli\\u003eNawras Y, Merza N, Beier K, Dakroub A, Al-Obaidi H, Al-Obaidi AD, et al. Temporal trends in racial and gender disparities of early onset colorectal cancer in the United States: An analysis of the CDC WONDER database. 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Public Opin Q. 2006;70(5):646\\u0026ndash;675. doi:10.1093/poq/nfl033\\u003c/li\\u003e\\n\\u003cli\\u003ejamovi project. jamovi (Version 2.0) [Computer Software]. Published 2022. Accessed January 22, 2025. https://www.jamovi.org/\\u003c/li\\u003e\\n\\u003cli\\u003eR Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Published 2021. Accessed January 22, 2025. https://cran.r-project.org/\\u003c/li\\u003e\\n\\u003cli\\u003eUS Preventive Services Task Force. Screening for colorectal cancer: US Preventive Services Task Force recommendation statement. JAMA. 2021;325(19):1965\\u0026ndash;1977.\\u003c/li\\u003e\\n\\u003cli\\u003eKnudsen AB, Zauber AG, Rutter CM, Naber SK, Doria-Rose VP, Pabiniak C, et al. Estimation of benefits, burden, and harms of colorectal cancer screening strategies: Modeling study for the US Preventive Services Task Force. JAMA. 2016;315(23):2595\\u0026ndash;2609.\\u003c/li\\u003e\\n\\u003cli\\u003eZhang J, Chen G, Li Z, Zhang P, Li X, Gan D, et al. Colonoscopic screening is associated with reduced colorectal cancer incidence and mortality: a systematic review and meta-analysis. J Cancer. 2020;11(20):5953\\u0026ndash;5970.\\u003c/li\\u003e\\n\\u003cli\\u003eEbner DW, Finney Rutten LJ, Miller-Wilson LA, Markwat N, Vahdat V, Ozbay AB, et al. Trends in colorectal cancer screening from the National Health Interview Survey: Analysis of the impact of different modalities on overall screening rates. Cancer Prev Res. 2024;17(6):275\\u0026ndash;280.\\u003c/li\\u003e\\n\\u003cli\\u003eAmerican Cancer Society. 80% in Every Community. Accessed January 22, 2025. https://nccrt.org/our-impact/80-in-every-community/\\u003c/li\\u003e\\n\\u003cli\\u003eHollis RH, Chu DI. Healthcare disparities and colorectal cancer. Surg Oncol Clin N Am. 2022;31(2):157\\u0026ndash;169.\\u003c/li\\u003e\\n\\u003cli\\u003eBarnholtz-Sloan JS, Guan X, Zeigler-Johnson C, Meropol NJ, Rebbeck TR. Decision tree\\u0026ndash;based modeling of androgen pathway genes and prostate cancer risk. Cancer Epidemiol Biomarkers Prev. 2011;20(6):1146\\u0026ndash;1155.\\u003c/li\\u003e\\n\\u003cli\\u003eGonzales M, Nelson H, Rhyne RL, Stone SN, Hoffman RM. Surveillance of colorectal cancer screening in New Mexico Hispanics and non-Hispanic whites. J Community Health. 2012;37(6):1279\\u0026ndash;1288.\\u003c/li\\u003e\\n\\u003cli\\u003eHenriques A, Silva S, Severo M, Fraga S, Barros H. Socioeconomic position and quality of life among older people: The mediating role of social support. Prev Med. 2020;135:106073.\\u003c/li\\u003e\\n\\u003cli\\u003eMayo Clinic. Comprehensive colorectal screening for closing the gap in racial disparities. Accessed January 22, 2025. https://www.mayoclinic.org/medical-professionals/cancer/news/comprehensive-colorectal-screening-for-closing-the-gap-in-racial-disparities/mac-20531415\\u003c/li\\u003e\\n\\u003cli\\u003eBurnett-Hartman AN, Mehta SJ, Zheng Y, Ghai NR, McLerran DF, Chubak J, et al. Racial/ethnic disparities in colorectal cancer screening across healthcare systems. Am J Prev Med. 2016;51(4):e107\\u0026ndash;e115.\\u003c/li\\u003e\\n\\u003cli\\u003eAtkin WS, Edwards R, Kralj-Hans I, Wooldrage K, Hart AR, Northover JM, et al. Once-only flexible sigmoidoscopy screening in prevention of colorectal cancer: a multicentre randomised controlled trial. Lancet. 2010;375(9726):1624\\u0026ndash;1633.\\u003c/li\\u003e\\n\\u003cli\\u003eKuczewski MG. Addressing systemic health inequities involving undocumented youth in the United States. AMA J Ethics. 2021;23(2):146\\u0026ndash;155.\\u003c/li\\u003e\\n\\u003cli\\u003ePruitt SL, Davidson NO, Gupta S, Yan Y, Schootman M. Missed opportunities: racial and neighborhood socioeconomic disparities in emergency colorectal cancer diagnosis and surgery. BMC Cancer. 2014;14:927.\\u003c/li\\u003e\\n\\u003cli\\u003eThe Promise and Challenge of Adolescent Immunization. Am J Prev Med. 2008;35(2):152\\u0026ndash;157.\\u003c/li\\u003e\\n\\u003cli\\u003eWilkins T, Gillies RA, Harbuck S, Garren J, Looney SW, Schade RR. Racial disparities and barriers to colorectal cancer screening in rural areas. J Am Board Fam Med. 2012;25(3):308\\u0026ndash;317.\\u003c/li\\u003e\\n\\u003cli\\u003eFedewa SA, Flanders WD, Ward KC, Lin CC, Jemal A, Goding Sauer A, et al. Racial and ethnic disparities in interval colorectal cancer incidence. Ann Intern Med. 2017;166(12):857\\u0026ndash;866.\\u003c/li\\u003e\\n\\u003cli\\u003eNational Cancer Institute. Screen to Save - Colorectal Cancer Screening. Published 2017. Accessed January 23, 2025. https://www.cancer.gov/about-nci/organization/crchd/community-outreach/screen-to-save\\u003c/li\\u003e\\n\\u003cli\\u003eSepassi A, Li M, Zell JA, Chan A, Saunders IM, Mukamel DB. Rural-urban disparities in colorectal cancer screening, diagnosis, treatment, and survivorship care: A systematic review and meta-analysis. Oncologist. 2024;29(4):e431\\u0026ndash;e446.\\u003c/li\\u003e\\n\\u003cli\\u003eTorabi M, Green C, Nugent Z, Mahmud SM, Demers AA, Griffith J, et al. Geographical variation and factors associated with colorectal cancer mortality in a universal health care system. Can J Gastroenterol Hepatol. 2014;28(4):707420.\\u003c/li\\u003e\\n\\u003cli\\u003eSequist TD, Zaslavsky AM, Marshall R, Fletcher RH, Ayanian JZ. Patient and physician reminders to promote colorectal cancer screening: a randomized controlled trial. Arch Intern Med. 2009;169(4):364\\u0026ndash;371.\\u003c/li\\u003e\\n\\u003cli\\u003eHudson SV, Ohman-Strickland P, Cunningham R, Ferrante JM, Hahn K, Crabtree BF. The effects of teamwork and system support on colorectal cancer screening in primary care practices. Cancer Detect Prev. 2007;31(5):417\\u0026ndash;423.\\u003c/li\\u003e\\n\\u003cli\\u003eD\\u0026eacute;siron HAM, Donceel P, Godderis L, Van Hoof E, de Rijk A. What is the value of occupational therapy in return to work for breast cancer patients? A qualitative inquiry among experts. Eur J Cancer Care. 2015;24(2):267\\u0026ndash;280.\\u003c/li\\u003e\\n\\u003cli\\u003eKhoja S, McGregor SE, Hilsden RJ. Validation of self-reported history of colorectal cancer screening. Can Fam Physician. 2007;53(7):1192\\u0026ndash;1197.\\u003c/li\\u003e\\n\\u003cli\\u003eAlkatout I, Biebl M, Momenimovahed Z, Giovannucci E, Hadavandsiri F, Salehiniya H, et al. Has COVID-19 affected cancer screening programs? A systematic review. Front Oncol. 2021;11:675038. doi:10.3389/fonc.2021.675038\\u003c/li\\u003e\\n\\u003cli\\u003eKopel J, Ristic B, Brower GL, Goyal H. Global impact of COVID-19 on colorectal cancer screening: Current insights and future directions. Medicina. 2022;58(1):100. doi:10.3390/medicina58010100\\u003c/li\\u003e\\n\\u003cli\\u003eNational Cancer Institute. COVID-19 pandemic\\u0026rsquo;s impact on cancer screening and efforts to increase screening rates. Published 2022. Accessed January 22, 2025. https://www.cancer.gov/news-events/cancer-currents-blog/2022/covid-increasing-cancer-screening\\u003c/li\\u003e\\n\\u003cli\\u003eLofters AK, Wu F, Frymire E, et al. Cancer screening disparities before and after the COVID-19 pandemic. JAMA Netw Open. 2023;6(11):e2343796. doi:10.1001/jamanetworkopen.2023.43796\\u003c/li\\u003e\\n\\u003cli\\u003eNational Cancer Institute. COVID-19 pandemic\\u0026rsquo;s impact on cancer screening and efforts to increase screening rates. Published 2022. Accessed January 22, 2025. https://www.cancer.gov/news-events/cancer-currents-blog/2022/covid-increasing-cancer-screening\\u003c/li\\u003e\\n\\u003cli\\u003eLofters AK, Wu F, Frymire E, et al. Cancer screening disparities before and after the COVID-19 pandemic. JAMA Netw Open. 2023;6(11):e2343796. doi:10.1001/jamanetworkopen.2023.43796\\u003c/li\\u003e\\n\\u003cli\\u003ede Lima PN, van den Puttelaar R, Hahn AI, et al. Unequal recovery in colorectal cancer screening following the COVID-19 pandemic: A comparative microsimulation analysis. medRxiv. Preprint posted online December 26, 2022. doi:10.1101/2022.12.23.22283887\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003eTable 1. CRC screening by colonoscopy or sigmoidoscopy percentages over the study period 1999 - 2023\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"666\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCRC screening by Coloscopy (%)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e1999\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2004\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2009\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2014\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2019\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2023\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eOverall\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e41.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e53.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e67.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e70.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e75.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e76.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"7\\\" valign=\\\"bottom\\\" style=\\\"width: 666px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eGender\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e40.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e52.94\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e67.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e72.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e75.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e76.93\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eMale\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e43.73\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e53.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e67.98\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e70.60\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e74.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e75.55\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"7\\\" valign=\\\"bottom\\\" style=\\\"width: 666px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eRace\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eWhite\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e42.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e54.20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e67.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e72.53\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e76.44\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e80.09\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eAfrican Americans\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e37.10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e47.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e59.89\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e69.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e71.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e70.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eHispanics\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e33.75\\u003csup\\u003e*\\u0026nbsp;\\u003c/sup\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e41.76\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e50.44\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e56.59\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e67.99\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e64.86\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eAmerican Indians or Alaskan Native\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e34.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e40.34\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e60.29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e56.96\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e70.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e48.65\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eAsian\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e37.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e38.64\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e56.83\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e56.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e58.45\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e64.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eNative Hawaiian or Other Pacific Islander\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e36.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e38.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e49.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e60.69\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e54.72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e60\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"7\\\" valign=\\\"bottom\\\" style=\\\"width: 666px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eEducational level\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eNever attended school or only kindergarten\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e28.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e42.45\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e42.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e46.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e43.48\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e38.46\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eElementary school (Grade 1-8)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e35.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e48.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e56.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e53.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e64.77\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e55.74\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eSome high school (Grade 9 \\u0026ndash; 11)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e37.73\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e48.46\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e54.63\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e58.41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e62.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e58.61\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eHigh school graduates (Grade 12 or GED)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e39.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e50.96\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e63.86\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e66.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e69.34\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e68.97\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eSome college or technical school (college 1-3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e43.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e53.04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e67.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e72.34\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e74.77\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e77.81\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eCollege Graduate (4 years or more)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e47.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e54.42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e74.50\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e78.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e80.61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e81.19\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"7\\\" valign=\\\"bottom\\\" style=\\\"width: 666px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIncome level\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; $ 10,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e36.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e42.45\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e59.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e52.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e63.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e46.20\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e$ 10,000 - $15,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e39.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e48.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e66.40\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e61.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e68.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e64.90\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e$ 15,000 \\u0026ndash; 20,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e41.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e48.46\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e56.42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e63.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e66.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e65.73\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e$ 20,000 - 25,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e41.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e50.96\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e62.96\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e67.34\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e59.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e67.44\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e$ 25,000 - 35,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e43.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e53.04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e66.99\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e69.90\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e70.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e70.18\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e$ 35,000 -50,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e54.42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e70.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e73.73\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e73.73\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e73.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e78.92\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e$ 50,000 -75,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e42.50\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e54.69\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e72.52\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e76.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e81.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e78.05\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003e$ 75,000 - 100,000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e47.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e54.42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e74.50\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e78.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e80.61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e80.97\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"7\\\" valign=\\\"bottom\\\" style=\\\"width: 666px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eInsurance level\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eInsured\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e42.83\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e55.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e69.64\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e73.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e76.55\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e78.13\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 270px;\\\"\\u003e\\n \\u003cp\\u003eNon-Insured\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003e24.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 76px;\\\"\\u003e\\n \\u003cp\\u003e29.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 64px;\\\"\\u003e\\n \\u003cp\\u003e40.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 9.6095%;\\\"\\u003e\\n \\u003cp\\u003e36.26\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 8.859%;\\\"\\u003e\\n \\u003cp\\u003e45.60\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 52px;\\\"\\u003e\\n \\u003cp\\u003e33.02\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eTable 2. Trend analysis of the annual percentage changes in screening rates 1999 \\u0026ndash; 2023\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"660\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariables\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eYears\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAPC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e95% CI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eP-Value\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eOverall\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.31\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.76 \\u0026ndash; 4.36\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2013 - 2023\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; -0.34 \\u0026ndash; 0.72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.31\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"5\\\" style=\\\"width: 660px;\\\"\\u003e\\n \\u003cp\\u003eGender\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eFemale \\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.98 \\u0026ndash; 4.55\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2013 -2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;-0.47 \\u0026ndash; 0.58\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eMale \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.62 \\u0026ndash; 4.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2013 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;-0.51 \\u0026ndash; 0.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"5\\\" style=\\\"width: 660px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eRace\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eWhite\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e4.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e3.35 \\u0026ndash; 5.24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2011 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e0.10 \\u0026ndash; 0.86\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eBlack or African American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e4.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e3.77 \\u0026ndash; 4.85\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2013 -2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;- 0.19 \\u0026ndash; 0.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eHispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2001 - 2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.01 \\u0026ndash; 5.97\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2015 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e-0.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;-3.04 \\u0026ndash; 0.31\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eAsian \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e4.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.80 \\u0026ndash; 9.16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2009 - 2023\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e-0.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;- 0.75 \\u0026ndash; 0.41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.65\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eNative Hawaiian or other Pacific Islander \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e4.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e3.32 \\u0026ndash; 7.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2015 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e-2.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;- 3.69 \\u0026ndash; - 0.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eAmerican Indian or Alaskan Native \\u0026nbsp; \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.47 \\u0026ndash; 4.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2013 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; -1.05 \\u0026ndash; 0.73\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"5\\\" style=\\\"width: 660px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eLevel of education\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eNever attended school or only kindergarten \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2004\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e8.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e1.04 \\u0026ndash; 9.22\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2004 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; -0.31 \\u0026ndash; 0.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eElementary School\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e2.61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e1.89 \\u0026ndash; 4.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2013 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e-0.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;-1.83 \\u0026ndash; 0.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eHigh school graduate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e3.33 \\u0026ndash; 4.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2011 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.48\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e0.15 \\u0026ndash; 0.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"bottom\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003eCollege graduate\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.64 \\u0026ndash; 4.63\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2013 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e-0.41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; -1.06 \\u0026ndash; 0.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"5\\\" style=\\\"width: 660px;\\\"\\u003e\\n \\u003cp\\u003eLevel of income\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003e$10 K\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.45\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.49 \\u0026ndash; 5.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2009 -2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e0.33 \\u0026ndash; 1.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003e$ 20 k\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.37\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.82 \\u0026ndash; 4.57\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2011 -2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e0.21 \\u0026ndash; 1.09\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003e$ 50 K\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e4.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e3.76 \\u0026ndash; 5.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2011 -2023\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e0.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;-0.2 \\u0026ndash; 0.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e0.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003e$ 75 K\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2015\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e2.52\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e1.94 \\u0026ndash; 3.68\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2015 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e-1.43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; -2.77 \\u0026ndash; - 0.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 168px;\\\"\\u003e\\n \\u003cp\\u003e$100 K\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1999 - 2009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e3.45\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e2.49 \\u0026ndash; 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2.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e2018 - 2023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e-6.84\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 203px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; -12.36 \\u0026ndash; - 4.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 84px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"digestive-diseases-and-sciences\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ddsj\",\"sideBox\":\"Learn more about [Digestive Diseases and Sciences](http://link.springer.com/journal/10620)\",\"snPcode\":\"10620\",\"submissionUrl\":\"https://submission.nature.com/new-submission/10620/3\",\"title\":\"Digestive Diseases and Sciences\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"Colorectal cancer, CRC screening, CRC mortality, health disparities, epidemiology, public health. \",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7015087/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7015087/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eIntroduction:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eColorectal cancer (CRC) is the fourth most common cancer in the U.S and second leading cause of cancer deaths. While screening rates have increased and mortality rates have declined, disparities persist. This study investigates the screening rates and mortality correlation over 25 years.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe analyzed trends in age-adjusted CRC screening and mortality rates (AAMRs) for adults aged ≥50 using BRFSS and CDC WONDER databases respectively. Correlation analysis between CRC screening rates and AAMRs, and projected AAMRs at 100% screening rates were calculated using Jamovi and R software.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults\\u003c/strong\\u003e:\\u003c/p\\u003e\\n\\u003cp\\u003eCRC screening rates increased from 41.5% in 1999 to 76.3% in 2023. Non-Hispanic Whites recorded the highest rates (80.1%) while, American Indians or Alaskan Natives (AI/AN) had a low screening rate of 48.65% in 2023. Non-insured individuals had a screening rate of 33.02%, while insured recorded 78.13% in 2023. AAMRs of CRC declined significantly over time, from 69.3% to 40.7% per 100,000 (1999–2024). AAMRs demonstrated a strong inverse correlation (–0.885) with screening rates. Correlation analysis revealed stronger associations between screening and mortality for NH Whites and African Americans (AA) populations (–0.824 and –1.19, respectively). The projected AAMR at 100% screening was 18.91 (95% CI: 17.92–19.91), versus 40.4 at 76.3% in 2023.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eCRC screening increased over the past 25 years, achieving 76.3% in 2023, correlating with decrease in AAMRs. Disparities persist across races, and different socioeconomic groups. At 100% screening rates, projected AAMR is 18.919. Equity-focused interventions are needed to further increase CRC screening rates.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Colorectal Cancer Screening Over 25 Years: Evaluating Mortality Declines and Ongoing Disparities\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-07-11 13:45:27\",\"doi\":\"10.21203/rs.3.rs-7015087/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-09-15T17:28:50+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-09-14T02:11:15+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"164002605128940060453360206973123700607\",\"date\":\"2025-08-22T23:20:42+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-07-07T20:00:18+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-07-01T23:19:58+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-07-01T13:17:46+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Digestive Diseases and Sciences\",\"date\":\"2025-07-01T02:09:10+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"digestive-diseases-and-sciences\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ddsj\",\"sideBox\":\"Learn more about [Digestive Diseases and Sciences](http://link.springer.com/journal/10620)\",\"snPcode\":\"10620\",\"submissionUrl\":\"https://submission.nature.com/new-submission/10620/3\",\"title\":\"Digestive Diseases and Sciences\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"702c4ad4-30cd-4d27-871b-5a3b05a8dc5f\",\"owner\":[],\"postedDate\":\"July 11th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-11-17T16:00:21+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-7015087\",\"link\":\"https://doi.org/10.1007/s10620-025-09472-3\",\"journal\":{\"identity\":\"digestive-diseases-and-sciences\",\"isVorOnly\":false,\"title\":\"Digestive Diseases and Sciences\"},\"publishedOn\":\"2025-11-13 15:57:20\",\"publishedOnDateReadable\":\"November 13th, 2025\"},\"versionCreatedAt\":\"2025-07-11 13:45:27\",\"video\":\"\",\"vorDoi\":\"10.1007/s10620-025-09472-3\",\"vorDoiUrl\":\"https://doi.org/10.1007/s10620-025-09472-3\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7015087\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7015087\",\"identity\":\"rs-7015087\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}