Evolution of Glaucoma-Related Mortality among Older Adults in the United States: Insights from CDC WONDER (2000–2023)

Evolution of Glaucoma-Related Mortality among Older Adults in the United States: Insights from CDC WONDER (2000–2023) | 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 Article Evolution of Glaucoma-Related Mortality among Older Adults in the United States: Insights from CDC WONDER (2000–2023) Muhammad Ali, Noreen Haidar Khan, Ahmad Kamal, Saif ur Rahman, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7850550/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Glaucoma is a common optic neuropathy in older U.S. adults, yet its national temporal mortality trends have not been elucidated. This study examines glaucoma-related trends and disparities in mortality among older adults, promoting awareness of ophthalmic health inequities. Death certificates from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database were analyzed among adults aged ≥ 65 years with glaucoma-related deaths from 2000 to 2023. Crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) per 100,000 were calculated and stratified by demographics and geography. Trends in annual percent change (APC) and average APC were assessed using Jointpoint regression with 95% confidence intervals. A total of 21,805 glaucoma-related deaths occurred in older adults from 2000 to 2023. AAMRs declined initially from 2.98 in 2000 to 1.80 in 2009 (APC: -6.01; 95% CI: -10.46 to -4.53), followed by stable rates until 2023. Mortality rates were highest in adults aged ≥ 85 years, men, non-Hispanic (NH) Black/African Americans, residents of non-metropolitan areas, and Midwestern regions. Heart disease was the leading underlying cause of glaucoma-associated death, with COVID-19 playing a major role from 2000 to 2023. Glaucoma-related mortality in older adults rose with notable risks among adults aged ≥ 85 years, men, NH Black/African Americans, residents in non-metropolitan areas, and the Midwest. These findings call for targeted, informed public health interventions to ameliorate outcomes. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Glaucoma Mortality Disparities CDC WONDER Population Health Epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1.0 INTRODUCTION Glaucoma is a chronic, progressive optic neuropathy disorder characterized by irreversible damage to the optic nerve, which results in visual field loss and blindness if untreated [ 1 ]. It is among the leading causes of irreversible blindness worldwide, affecting nearly 76 million people in 2020, and the number is projected to rise to 111.8 million by 2040, with around two-thirds of all glaucoma cases above 70 years of age [ 2 , 3 ]. The disease burden grows exponentially with advancing age, and population aging has therefore become a major driver of global glaucoma prevalence and associated disability [ 4 ]. Rising research has highlighted the possibility of glaucoma having more systemic risks than just visual side effects [ 5 ]. While glaucoma is usually not a cause of death, it does have associations with age-related vascular, metabolic, and neurodegenerative conditions. Having visual impairment can cause more falls, cognitive decline, and reduced quality of life, which can affect long-term morbidity and mortality, especially in elderly subjects [ 6 ]. By examining patterns of glaucoma mortality, we could gain a better understanding of both ocular and other health inequalities in aging populations. In the United States, glaucoma and its impact are distributed unevenly across racial, demographic, and geographic sub-groups [ 7 ]. These inequities are also due to socioeconomic factors, unequal access to quality health care, or differing patterns of health-seeking behaviors. Still, there is a lack of national-level analysis of glaucoma-related deaths, as most studies look at the prevalence, disparities in treatment, or visual impairment only. There is limited available research that has examined temporal mortality trends, with stratifications by demographic or regional classifications, or the impact of recent system disruptions such as COVID-19. Population-based data is essential for tracking mortality trends. This information helps us understand the long-term burden of disease. We used the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database to examine glaucoma-specific mortality trends over several decades [ 8 ]. This study explores trends and differences in glaucoma mortality among U.S. adults aged 65 and older from 2000 to 2023. It includes estimates of age-adjusted mortality rates for both the overall population and specific subgroups. 2.0 METHODS 2.1 Study Design and Data Source In this population-based analysis, death certificate data were retrieved from the CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database. Death certificate data from 2000 to 2023 for glaucoma-related mortality in adults aged ≥ 65 years was examined using codes from the International Statistical Classification of Diseases and Related Health Problems-10th Revision (ICD-10) specified as H40. This dataset includes cause of death from death certificates for the 50 states and the District of Columbia and has been previously used in several studies to determine trends in mortality [ 9 ]. The Multiple Cause-of-Death Public Use record death certificates were studied to select Glaucoma-related deaths, which were identified as those with glaucoma reported anywhere on the death certificate, either as a contributing or underlying cause of death. Additionally, extraction for the leading causes of glaucoma-associated deaths using the top 15 underlying causes of death (UCD-15) list from CDC WONDER was divided into pre-pandemic (2000–2019) and pandemic (2020–2023) time periods, with their respective ICD-10 codes (Supplemental Table S1 ). Older adults were defined as adults aged ≥ 65 years. Age groups were stratified into three categories: adults aged 65–74 years, 75–84 years, and ≥ 85 years. Similar age group classifications have been used to define older adults in previous studies [ 10 , 11 ]. This study was exempt from local institutional review board approval as it utilized de-identified, government-issued public use records. We followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting [ 12 ]. 2.2 Variables and Measures Data for population size, year, location of death, demographics, urbanicity, U.S. census region, state, and leading underlying causes of glaucoma-associated deaths were extracted and analyzed. Place of death included medical facilities (inpatient, outpatient/emergency room, death on arrival, or status unknown), decedent’s home, hospices, nursing home/long-term care facility, other, and unknown locations. Demographic grouping included sex, age group, and race (non-Hispanic (NH) White, NH Black or African American, and Hispanic or Latino). The Urban-Rural Classification Scheme from the National Center for Health Statistics was used to evaluate the population by metropolitan (large metropolitan area [population ≥ 1 million], medium/small metropolitan area [population between 50,000 and 999,999]) and non-metropolitan (population under 50,000) counties based on the 2013 U.S. census classification [ 13 ]. U.S. census regions were classified into the Northeast, Midwest, South, and West in line with the U.S. Census Bureau definitions. 2.3 Statistical Analysis To examine national trends in glaucoma-related mortality, we calculated crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) per 100,000 persons by standardizing glaucoma-related deaths to the year 2000 U.S. population [ 14 ]. CMRs and AAMRs from death certificates were extracted from 2000 to 2023 and stratified by year, sex, race, state, and urban-rural status with corresponding 95% CIs. AAMRs were calculated by standardizing glaucoma-related deaths to the year 2000 U.S. population. To quantify national annual trends in glaucoma-related mortality, the Joinpoint Regression Program (National Cancer Institute, version 5.0) was used to determine the annual percent change (APC) and average annual percent change (AAPC) with 95% CI in AAMR [ 15 ]. This method identifies significant changes in AAMR over time by fitting log-linear regression models where temporal variation occurred. A value of p < 0.05 was considered statistically significant. 3.0 RESULTS A total of 21,805 glaucoma-related deaths occurred among adults aged ≥ 65 years from 2000 to 2023 in the United States. Most deaths occurred in nursing homes/long-term care centers (10,216; 46.85%), followed by the decedent’s home (4,865; 22.31%) and medical facilities (4,828; 22.14%). Smaller proportions of deaths occurred in hospices (699; 3.21%) and other/unknown locations (1,197; 5.49%) (Fig. 1 ; Supplemental Table S2). 3.1 Annual Trends Overall AAMRs declined from 2.98 (95% CI: 2.80–3.16) in 2000 to 2.29 (95% CI: 2.16–2.42) in 2023 (AAPC: -1.39; 95% CI: -1.88 to -0.92). AAMRs initially decreased from 2000 to 2009 (APC: -6.01; 95% CI: -10.46 to -4.53), followed by stable rates from 2009 to 2016. Mortality rates increased afterwards until 2023 (APC: 5.36; 95% CI: 2.86 to 10.91) (Fig. 2 ; Supplemental Tables S3 and S4). 3.2 Sex-Specific Trends Women accounted for 13,738 deaths (63%), while men accounted for 8,067 deaths (37%). The average AAMR was similar for women and men (average AAMR women: 2.08; average AAMR men: 2.09). AAMRs for women declined from 3.00 (95% CI: 2.78–3.23) in 2000 to 2.21 (95% CI: 2.05–2.38) in 2023 (AAPC: -1.57; 95% CI: -2.17 to -1.01). AAMRs initially decreased from 2000 to 2010 (APC: -5.84; 95% CI: -10.80 to -0.23), followed by stable rates until 2023. AAMRs for men declined from 2.97 (95% CI: 2.66–3.29) in 2000 to 2.37 (95% CI: 2.16–2.58) in 2023 (AAPC: -1.09; 95% CI: -1.59 to -0.53). AAMRs initially decreased from 2000 to 2009 (APC: -5.71; 95% CI: -11.25 to -2.68), followed by stable rates from 2009 to 2015. Mortality rates then increased afterwards until 2023 (APC: 5.01; 95% CI: 0.41 to 10.53). (Fig. 2 ; Supplemental Tables S3 and S4). 3.3 Race Specific Trends Non-Hispanic (NH) Whites had the greatest number of deaths, 16,945 (79.81%), followed by NH Black/African Americans 3,182 (14.98%) and Hispanic/Latinos 1,105 (5.20%). In terms of AAMR, NH Black/African Americans had the highest average AAMR (3.92), followed by NH Whites (1.99) and Hispanic/Latinos (1.61). NH Black/African Americans had their AAMRs decrease from 5.83 (95% CI: 4.90–6.75) in 2000 to 4.15 (95% CI: 3.54–4.75) in 2023 (AAPC: -1.17; 95% CI: -2.17 to -0.12). AAMRs initially decreased from 2000 to 2014 (APC: -5.55; 95% CI: -8.87 to -3.69), followed by an increase in rates until 2023 (APC: 6.05; 95% CI: 2.56 to 14.61). NH Whites had their AAMRs decrease from 2.87 (95% CI: 2.68–3.06) in 2000 to 2.17 (95% CI: 2.03–2.32) in 2023 (AAPC: -1.39; 95% CI: -1.74 to -1.05). AAMRs initially decreased from 2000 to 2010 (APC: -5.89; 95% CI: -8.03 to -5.07), followed by stable rates from 2010 to 2016. Mortality rates then increased afterwards until 2023 (APC: 5.15; 95% CI: 3.63 to 9.02). AAMRs for Hispanic/Latinos remained stable from 1.73 (95% CI: 1.10–2.59) in 2000 to 2.27 (95% CI: 1.83–2.71) in 2023, with no increases or decreases in mortality rates interspersed throughout the study duration. (Fig. 3 ; Supplemental Tables S4 and S5). 3.4 Age Group Specific Trends Adults aged ≥ 85 years contributed the greatest number of deaths (14,389) and the highest average CMR (10.98), followed by adults aged 75–84 years (5,503 deaths; average CMR: 1.64) and 65–74 years (1,913 deaths; average CMR: 0.33). CMRs for adults aged 65–74 years remained stable from 0.53 (95% CI: 0.43–0.65) in 2000 to 0.37 (95% CI: 0.31–0.43) in 2023. CMRs initially decreased from 2000 to 2015 (APC: -5.19; 95% CI: -7.33 to -3.67), followed by an increase in rates until 2023 (APC: 8.15; 95% CI: 4.62 to 14.45). CMRs for adults aged 75–84 years decreased from 2.54 (95% CI: 2.26–2.82) in 2000 to 1.64 (95% CI: 1.45–1.82) in 2023 (AAPC: -1.83; 95% CI: -2.26 to -1.37). CMRs initially decreased from 2000 to 2014 (APC: -5.10; 95% CI: -6.09 to -4.31), followed by an increase in rates until 2023 (APC: 3.49; 95% CI: 1.90 to 5.84). CMRs for adults aged ≥ 85 years declined from 14.91 (95% CI: 13.74–16.07) in 2000 to 12.33 (95% CI: 11.46–13.21) in 2023 (AAPC: -1.30; 95% CI: -1.82 to -0.79). CMRs initially decreased from 2000 to 2010 (APC: -5.78; 95% CI: -10.09 to -1.95), followed by stable rates from 2010 to 2016. Mortality rates then increased afterwards until 2023 (APC: 4.80; 95% CI: 1.85 to 11.07) (Fig. 4 ; Supplemental Tables S4 and S6). 3.5 Urbanization-Specific Trends (2000–2020) Although metropolitan areas accounted for most of the deaths (14,698), average AAMRs were higher in non-metropolitan (2.39) compared with metropolitan (2.02) areas. AAMRs for non-metropolitan areas declined from 3.45 (95% CI: 3.01–3.89) in 2000 to 2.33 (95% CI: 2.01–2.65) in 2020 (AAPC: -2.74; 95% CI: -3.84 to -1.96). AAMRs initially decreased from 2000 to 2015 (APC: -5.27; 95% CI: -7.53 to -4.32), followed by stable rates until 2020. Metropolitan areas had their AAMRs decline from 2.89 (95% CI: 2.69–3.09) in 2000 to 2.16 (95% CI: 2.03–2.30) in 2020 (AAPC: -2.09; 95% CI: -2.69 to -1.59). AAMRs initially decreased from 2000 to 2009 (APC: -6.35; 95% CI: -10.16 to -4.81), followed by stable rates from 2009 to 2016. Mortality rates then increased afterwards until 2020 (APC: 6.34; 95% CI: 2.15 to 14.07) (Fig. 5 ; Supplemental Tables S4 and S7). 3.6 Region-Specific Trends The Midwest had the highest number of deaths (5,562) and the greatest average AAMR (2.36), followed by the Northeast (4,864 deaths; average AAMR: 2.22), West (4,661 deaths; average AAMR: 2.09), and South (6,718 deaths; average AAMR: 1.84). In the Northeast, AAMRs remained stable over the study period, from 2.88 (95% CI: 2.50–3.26) in 2000 to 3.19 (95% CI: 2.84–3.54) in 2023. AAMRs initially decreased from 2000 to 2008 (APC: -7.19; 95% CI: -10.4361 to -4.9079), followed by increasing rates from 2008 to 2013 (APC: 6.41; 95% CI: 0.87 to 15.96). Mortality rates then decreased again from 2013 to 2016 (APC: -10.11; 95% CI: -15.35 to -1.17), followed by another increase in rates from 2016 to 2020 (APC: 16.03; 95% CI: 10.96 to 25.42) and lastly stable rates until 2023. In the Midwest, AAMRs declined from 3.79 (95% CI: 3.38–4.20) in 2000 to 1.37 (95% CI: 1.15–1.59) in 2023 (AAPC: -4.33; 95% CI: -5.15 to -3.61). AAMRs initially decreased from 2000 to 2014 (APC: -6.32; 95% CI: -8.99 to -5.30), followed by stable rates until 2023. In the South, AAMRs declined from 2.77 (95% CI: 2.47–3.07) in 2000 to 2.21 (95% CI: 2.00–2.42) in 2023 (AAPC: -1.33; 95% CI: -2.08 to -0.62). AAMRs initially decreased from 2000 to 2010 (APC: -6.69; 95% CI: -13.48 to -3.78), followed by stable rates from 2010 to 2018, and lastly increasing rates thereafter until 2023 (APC: 8.75; 95% CI: 3.44 to 19.97). In the West, AAMRs remained stable, from 2.55 (95% CI: 2.17–2.93) in 2000 to 2.48 (95% CI: 2.19–2.76). AAMRs were initially stable from 2000 to 2010, followed by increasing mortality rates thereafter until 2023 (APC: 3.79; 95% CI: 2.69 to 5.01) (Fig. 6 ; Supplemental Tables S4 and S8). 3.7 Leading Underlying Causes of Death (2000–2019) From 2000 to 2019, the top 5 leading underlying causes of glaucoma-associated deaths were heart disease, malignant neoplasms, Alzheimer’s disease, cerebrovascular diseases, and chronic lower respiratory diseases. Heart disease resulted in 4,000 deaths with an AAMR of 0.44 (95% CI: 0.42–0.45), followed by malignant neoplasms with 2,730 deaths and an AAMR of 0.33 (95% CI: 0.32–0.34). Alzheimer’s disease accounted for 1,702 deaths (AAMR: 0.18; 95% CI: 0.17–0.19), and cerebrovascular diseases caused 1,413 deaths (AAMR: 0.15; 95% CI: 0.14–0.15). Chronic lower respiratory diseases and diabetes mellitus each contributed 808 and 796 deaths, respectively, both with an AAMR of 0.08. Other notable causes included essential hypertension and hypertensive renal disease (687 deaths; AAMR: 0.06), unintentional injuries (348 deaths; AAMR: 0.02), Parkinson’s disease (345 deaths; AAMR: 0.06), influenza and pneumonia (196 deaths; AAMR: 0.01), pneumonitis due to solids and liquids (105 deaths; AAMR: 0.01), in situ/benign/uncertain or unknown behavior neoplasms (103 deaths; AAMR: 0.01), sepsis (85 deaths; AAMR: 0.01), nephritis/nephrotic syndrome/nephrosis (82 deaths; AAMR: 0.01), and anemias (61 deaths; AAMR: 0.00) (Fig. 7 ; Supplemental Tables S9 and S10). 3.8 Leading Underlying Causes of Death (2020–2023) From 2020 to 2023, the top 5 leading underlying causes of glaucoma-associated deaths included heart disease, malignant neoplasms, Alzheimer’s disease, cerebrovascular diseases, and COVID-19. Heart disease accounted for 793 deaths with an AAMR of 0.34 (95% CI: 0.32–0.37), followed by malignant neoplasms with 643 deaths and an AAMR of 0.31 (95% CI: 0.28–0.33). Alzheimer’s disease resulted in 398 deaths (AAMR: 0.18; 95% CI: 0.16–0.20), while cerebrovascular diseases caused 282 deaths (AAMR: 0.13; 95% CI: 0.12–0.15). COVID-19 contributed to 276 deaths with an AAMR of 0.12 (95% CI: 0.11–0.14). Other notable causes included diabetes mellitus (199 deaths; AAMR: 0.07; 95% CI: 0.06–0.08), chronic lower respiratory diseases (172 deaths; AAMR: 0.08; 95% CI: 0.07–0.10), and essential hypertension and hypertensive renal disease (162 deaths; AAMR: 0.06; 95% CI: 0.05–0.07). Remaining causes, such as unintentional injuries, Parkinson’s disease, nutritional deficiencies, influenza and pneumonia, septicemia, chronic liver disease, and in situ/benign/uncertain or unknown behavior neoplasms, accounted for fewer deaths with corresponding lower AAMRs (Fig. 8 ; Supplemental Tables S9 and S10). 4.0 DISCUSSION Glaucoma mortality among older US adults spanning more than two decades was dynamic, with a decrease in the early 2000s, relative stabilization over the next decade, and a foreboding spike after 2016. These trends are also reflected in worldwide reports of initial progress through mass screening, new pharmacologic therapy, and improved surgical technique, followed by plateauing of these advances in high-resource nations. The later rebound is concurrent with aging populations, increasing systemic comorbidities like diabetes and vascular disease, and persisting disparities in access to specialty care [ 16 , 17 ]. By examining the CDC WONDER national mortality data and Joinpoint regression, it is revealed that while earlier there was improvement, sex, race, age, urbanization, and geographic disparities still characterize the burden of glaucoma mortality in the United States. The broad trend of early declines ultimately reversed to increases, capturing the interplay between medical innovation and population health forces. Death decreased with improvements in cataract and glaucoma surgery, the introduction of prostaglandin analogues, and access to eye exams due to factors related to Medicare. As treatment becomes commonplace, innovation stalls, and population condition and demographic pressures once more catch up with deaths. Post-2016 increase in later rise also aligns with wider literature that indicates multimorbidity, frailty, and demographically driven aging are transforming ophthalmic results as a systemic disease concern rather than as an isolated ocular disease. [ 18 ]. In the post-2020 period, an additional finding was the emergence of COVID-19 as a significant co-occurring and contributing cause of glaucoma-associated deaths, reflecting the systemic vulnerability of elderly adults with ocular and vascular comorbidities. Sex trends were also noticed to be relatively evenly balanced during the study duration, where men and women both declined and then rose, and had similar average AAMRs. This concordance agrees with other US and European studies that found there were few sex-specific differences in glaucoma progression after controlling for age and comorbidity [ 19 , 20 ]. Underneath this, there are differences in behavior and care-seeking. Preventive eye care in the past has been accessed more by women, allowing earlier detection, while more surgical intervention was performed in men, including for more advanced disease. With increasing access to health care becoming increasingly equal between the two sexes with the passage of time, mortality convergence occurred. Late acceleration in both sexes follows evidence where enhanced improvement in longevity and increasing multimorbidity have similar effects on men and women, plugging earlier gaps in use of care and results [ 21 ]. There were significant racial and ethnic disparities during the study duration. Non-Hispanic Black adults in all regions consistently reported higher glaucoma mortality compared to Whites and Hispanics. This is consistent with much of decades of epidemiologic evidence for a more rapid onset, faster rate of progression, and greater glaucoma severity in Blacks [ 22 , 23 ]. Biologic susceptibility in the form of thinner corneal thickness and increased burden of more advanced open-angle glaucoma subtypes is augmented by social determinants such as decreased access to subspecialty services, decreased rates of surgical follow-up, and system-level healthcare inequities in infrastructure [ 24 ]. The rising mortality trend for Black adults is concerning and in line with evidence that specialist disparities in the availability of healthcare have increased since 2015 [ 25 ]. Hispanic adults, on the other hand, had lower mortality as seen in prevalence studies earlier, although rising diabetes and hypertension burden within the cohort perhaps to redirect future trends [ 26 ]. All these differences prove that global, behavioral, and biological determinants converge to create a mortality gradient by race. The most dramatic gradient was demonstrated in age-stratified analysis and is described in older persons with the highest burden of mortality associated with glaucoma. All global cohort studies identify increasing age as the most significant disease course and risk factor for visual impairment. Late-life survival gains once depended on successful surgery, new classes of drugs, and increasing Medicare-sponsored screening of the eyes. The resulting increase is nonetheless in line with the demographic increase of the oldest-old population and increasing frailty, multimorbidity, and polypharmacy to exert risk [ 27 , 28 ]. Adults aged 65–74 years evidenced more gradual and slower rising rates, as would be predicted by the hypothesis that disease states at earlier stages in the course of the disease are best treated by longer duration therapy and fewer systemic comorbidities [ 29 ]. The age disparity serves to highlight the fact that glaucoma mortality is no less an index of systemic susceptibility than of ocular disease. Urbanizing trends were imposed upon rural disadvantage. Non-metropolitan residents have always had higher glaucoma mortality compared with metropolitan residents. These results are consistent with those of rural ophthalmologist shortages, greater travel distances to special care services, and greater continuity-of-care issues. Rural-urban disparities during previous years presumably resulted from national expansions of Medicare coverage and eye care utilization [ 30 , 31 ]. Yet rural disadvantage remerges more recently with clinic closures, transportation issues, and reduced availability of subspecialists. Urban populations also evidenced lagging growth, that is, even the wealthiest environments are not exempt from the cumulative effects of aging and systemic disease [ 32 ]. Geographic variation also evidenced convergence of trends in demographics and health system capacity. The Midwest experienced record-high rates but achieved long-term decreases, and these most likely resulted from an initial high burden combined with judicious utilization of surgical and community-based eye care programs. Northeast experienced unstable trends, which is typical of its very heterogeneous population and mixed health infrastructure. South had lower mean rates but with a high total number of deaths, in accordance with its race and size, and long-standing differences in provision. West fluctuated up and down until late on, in accordance with demographic change, rising migration, and skewed distribution of healthcare facilities. These trends emphasize the necessity for region-level interventions that take into consideration both sociodemographic conditions and health system capability [ 33 , 34 ]. Death trends of nursing homes contributed additional information about populations most impacted. The prevalence of glaucoma death among nursing homes and long-term care facilities highlights the susceptibility of frail, dependent elderly persons. Such groups are at higher risk for severe comorbidity and lower accessibility to specialty ophthalmologic treatment, raising the risk of death. Hospital mortality relative to other chronic illnesses is consistent with the literature describing glaucoma as more disabling and causative than acute terminal in nature [ 35 , 36 ]. Home death frequency is consistent with end-of-life care unmet needs and visually impaired older person support, described consistently throughout geriatric care literature as being a chronic shortcoming. 4.1 Limitations Dependence on death certificate data has the potential for misclassification of risk because glaucoma is an uncommon main cause of death, but instead often occurs episodically as a contributing cause. Inter-state and inter-temporal variation in rules for certification and coding may alter observed mortality patterns. Second, small numbers culling in CDC WONDER limited the capacity to estimate less prevalent racial and geographic subgroups reasonably, which may suppress inequities. Third, ecological design will not allow adjustment for variables at the individual level, such as socioeconomic status, treatment adherence, or disease comorbid burden, all of which have been shown to affect outcomes. Fourth, changes in diagnostic methods, improvement in treatment, and usage of healthcare during the observation interval cannot be completely divorced from underlying trends in epidemiology. Beyond such limitations, the article presents a broad nationwide image of long-term demographic and geographical trends in glaucoma fatalities. 5.0 CONCLUSION Taken together, these data place glaucoma not just as an ocular disease, but as an expression of systemic susceptibility and imbalance. This pattern of escalating early losses with subsequent gains both reflects poor people's victory over disease and the limitation of poor people's asymmetric access and population pressure. Stratified sex, race, age, urbanization, and geographic estimates affirm glaucoma mortality burden remains disproportionately skewed, based on a sophisticated interplay of biological risk, health system, and structural disadvantage. Abbreviations AAMR Age–adjusted Mortality Rate CMR Crude Mortality Rate AAPC Average Annual Percent Change APC Annual Percent Change CDC WONDER Centers for Disease Control and Prevention Wide–Ranging Online Data for Epidemiologic Research ICD 10–International Statistical Classification of Disease and Related Health Problems, 10th Revision NH non–Hispanic U.S United States UCD Underlying Cause of Death Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Data availability The datasets generated and/or analysed during the current study are publicly available, de-identified data from the CDC WONDER Multiple Cause-of-Death database. Available at: https://wonder.cdc.gov/mcd.html Competing interests The authors declare that they have no competing interests. Funding Not applicable. Authors' contributions MA: conceptualization, project administration, supervision, validation, investigation, methodology, writing, writing – original draft, writing – review and editing; NHK: investigation, methodology, writing – original draft, writing – review and editing; AK: investigation, methodology, writing – original draft, writing – review and editing; SUR: investigation, methodology, writing – original draft, writing – review and editing; NZ: investigation, methodology, writing – original draft, writing – review and editing; RF: investigation, methodology, writing – original draft; MSA: graph and figure curation; MM: figure curation; IA: investigation, methodology, writing – original draft, writing – review and editing; AR: methodology– original draft, writing – review and editing; KAK: writing – review and editing; HS: writing – review and editing; MAS: writing – review and editing. All authors read and approved the final manuscript. Acknowledgements Fig. 7 and Fig. 8 were created using Datawrapper. Available at: https://www.datawrapper.de/ References Weinreb RN, Aung T, Medeiros FA. The pathophysiology and treatment of glaucoma: a review. JAMA. 2014 May 14;311(18):1901-11. doi: 10.1001/jama.2014.3192. PMID: 24825645; PMCID: PMC4523637. Tham YC, Li X, Wong TY, Quigley HA, Aung T, Cheng CY. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology. 2014 Nov;121(11):2081-90. doi: 10.1016/j.ophtha.2014.05.013. Epub 2014 Jun 26. PMID: 24974815. Wolfram C. The Epidemiology of Glaucoma - an Age-Related Disease. Klin Monbl Augenheilkd. 2024 Feb;241(2):154-161. English, German. doi: 10.1055/a-2257-6940. Epub 2024 Feb 27. PMID: 38412979. Leske MC. Open-angle glaucoma -- an epidemiologic overview. Ophthalmic Epidemiol. 2007 Jul-Aug;14(4):166-72. doi: 10.1080/09286580701501931. PMID: 17896292. Wey S, Amanullah S, Spaeth GL, Ustaoglu M, Rahmatnejad K, Katz LJ. Is primary open-angle glaucoma an ocular manifestation of systemic disease? Graefes Arch Clin Exp Ophthalmol. 2019 Apr;257(4):665-673. doi: 10.1007/s00417-019-04239-9. Epub 2019 Jan 15. PMID: 30643967. Ehrlich JR, Ramke J, Macleod D, Burn H, Lee CN, Zhang JH, Waldock W, Swenor BK, Gordon I, Congdon N, Burton M, Evans JR. Association between vision impairment and mortality: a systematic review and meta-analysis. Lancet Glob Health. 2021 Apr;9(4):e418-e430. doi: 10.1016/S2214-109X(20)30549-0. Epub 2021 Feb 16. PMID: 33607015; PMCID: PMC7966688. Khachatryan N, Pistilli M, Maguire MG, Chang AY, Samuels MR, Mulvihill K, Salowe RJ, O'Brien JM. A Review of Studies of the Association of Vision-Related Quality of Life with Measures of Visual Function and Structure in Patients with Glaucoma in the United States. Ophthalmic Epidemiol. 2021 Jun;28(3):265-276. doi: 10.1080/09286586.2020.1863992. Epub 2021 Feb 3. PMID: 33530788; PMCID: PMC8261792. CDC. CDC Wide-Ranging Online Data for Epidemiologic Research (WONDER). Available online: https://wonder.cdc.gov. Rani, S., Kumar, L., Ali, S.M.E. et al. Trends in United States mortality among patients with atrial fibrillation/flutter related heart failure (1999–2024): disparities by gender, race/ethnicity and region. BMC Cardiovasc Disord 25, 558 (2025). https://doi.org/10.1186/s12872-025-05036-5 Rath, S., Hameed, H., Rahman, S.U. et al. Disparities in hernia-related mortality among older adults in the U.S.: A 21-year analysis of the CDC-WONDER database. Hernia 29, 285 (2025). https://doi.org/10.1007/s10029-025-03464-y Shree Rath, Amar Lal, Ahmed Hasan, Muhammad Ali, Laiba Sultan, Mishaim Khan, Umama Alam, Long-Term Mortality Trends From Prostate Cancer and Associated Second Malignancies in the U.S., 1999 to 2023: Implications for Survivorship Care, Clinical Genitourinary Cancer, 2025, 102428, ISSN 1558-7673, https://doi.org/10.1016/j.clgc.2025.102428. Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Ann Intern Med. 2007 Oct 16;147(8):W163-94. doi:10.7326/0003-4819-147-8-200710160-00010-w1. Ingram D.D., Franco S.J. 2013 NCHS Urban-Rural Classification Scheme for Counties. US Department of Health and Human Services, Centers for Disease Control and Prevention, 2014. Anderson R.N., Rosenberg H.M. Age Standardization of death rates: implementation of the year 2000 standard. Natl Vital Stat Rep 1998;47:1-17 National Cancer Institute, Surveillance Research Program. Joinpoint Trend Analysis Software Internet. Bethesda (MD): National Cancer Institute; cited 2025 Oct 8. Available from: https://surveillance.cancer.gov/joinpoint/ Kühn T, Rohrmann S, Karavasiloglou N, Friedman DS, Cassidy A, Bärnighausen T, et al. Glaucoma and mortality risk: findings from a prospective population-based study. Sci Rep. 2021 June 3;11:11771. Huang X, Xu M, Zhou M, Liu W, Zhao X, Sun X. The association between glaucoma and all-cause mortality in middle-aged and elderly Chinese people: results from the China Health and Retirement Longitudinal Study. Epidemiol Health. 2023 July 21;45:e2023066. Frailty and Glaucoma Have Links, Potential Casual Relationship - Ophthalmology Advisor [Internet]. [cited 2025 Oct 2]. Available from: https://www.ophthalmologyadvisor.com/news/frailty-and-glaucoma-associated-and-patients-face-increased-health-disparities/ Sato M, Yasuda M, Takahashi N, Hashimoto K, Himori N, Nakazawa T. Sex differences in the association between systemic oxidative stress status and optic nerve head blood flow in normal-tension glaucoma. PLOS ONE. 2023 Feb 24;18(2):e0282047. Banik S, Ghosh A, Debi H. The Prevalence Trend of Glaucoma by Age and Sex Difference in South Asia: A Systematic Review and Meta‐Analysis of Population‐Based Studies. Health Sci Rep. 2025 Mar 18;8(3):e70542. Vajaranant TS, Nayak S, Wilensky JT, Joslin CE. Gender and glaucoma: what we know and what we need to know. Curr Opin Ophthalmol. 2010 Mar;21(2):91–9. Bennion JR, Wise ME, Carver JA, Sorvillo F. Analysis of glaucoma-related mortality in the United States using death certificate data. J Glaucoma. 2008 Sept;17(6):474–9. Racial Disparities in Glaucoma: From Epidemiology to Pathophysiology - PMC [Internet]. [cited 2025 Oct 2]. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9312450/ Racial Differences in Corneal Thickness in Glaucomatous and Non-glaucomatous Populations | IOVS | ARVO Journals [Internet]. [cited 2025 Oct 2]. Available from: https://iovs.arvojournals.org/article.aspx?articleid=2418000 THE AFRICAN DESCENT AND GLAUCOMA EVALUATION STUDY (ADAGES): PREDICTORS OF VISUAL FIELD DAMAGE IN GLAUCOMA SUSPECTS - PMC [Internet]. [cited 2025 Oct 2]. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4361282/ U.S. Latinos Have High Rates of Eye Disease and Visual Impairment | National Eye Institute [Internet]. [cited 2025 Oct 2]. Available from: https://www.nei.nih.gov/about/news-and-events/news/us-latinos-have-high-rates-eye-disease-and-visual-impairment Ehrlich JR, Ramke J, Macleod D, Burn H, Lee CN, Zhang JH, et al. Association between vision impairment and mortality: a systematic review and meta-analysis. Lancet Glob Health. 2021 Feb 16;9(4):e418–30. Al-Namaeh M. Common causes of visual impairment in the elderly. Med Hypothesis Discov Innov Ophthalmol. 2022 Feb 24;10(4):191–200. Killeen OJ, De Lott LB, Zhou Y, Hu M, Rein D, Reed N, et al. Population Prevalence of Vision Impairment in US Adults 71 Years and Older. JAMA Ophthalmol. 2023 Feb;141(2):197–204. Swaminathan SS, Medeiros FA. Socioeconomic Disparities in Glaucoma Severity at Initial Diagnosis: A Nationwide EHR Cohort Analysis. Am J Ophthalmol. 2024 July;263:50–60. Davuluru SS, Jess AT, Kim JSB, Yoo K, Nguyen V, Xu BY. Identifying, Understanding, and Addressing Disparities in Glaucoma Care in the United States. Transl Vis Sci Technol. 2023 Oct 27;12(10):18. Rural Health Disparities Overview - Rural Health Information Hub [Internet]. [cited 2025 Oct 2]. Available from: https://www.ruralhealthinfo.org/topics/rural-health-disparities Ye L, Huang X, Xu Y. Global trends and disparities in burden of blindness and vision loss caused by non-communicable diseases from 1990 to 2021, and forecasts to 2045: a systematic analysis for the global burden of disease study 2021. Front Med [Internet]. 2025 June 19 [cited 2025 Oct 2];12. Available from: https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1561568/full New “Prevalence of glaucoma in the US in 2022” study finds higher prevalence of the eye disease than previously estimated | Institute for Health Metrics and Evaluation [Internet]. [cited 2025 Oct 2]. Available from: https://www.healthdata.org/news-events/newsroom/news-releases/new-prevalence-glaucoma-us-2022-study-finds-higher-prevalence The association between glaucoma and all-cause mortality in middle-aged and elderly Chinese people: results from the China Health and Retirement Longitudinal Study [Internet]. [cited 2025 Oct 2]. Available from: https://www.e-epih.org/journal/view.php?doi=10.4178%2Fepih.e2023066 Quaranta L, Galbussera AA, Tettamanti M, Novella A, Pasina L, Fortino I, et al. Relationships Among Glaucoma, Cardiovascular Diseases, and Mortality. Adv Ther. 2025 Sept;42(9):4403–17. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile1.docx Supplementary File 1. Docx Supplementary Materials Contains supplemental tables referenced in the manuscript as an additional file Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7850550","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":543047406,"identity":"90013160-c1af-4d6f-bf64-d8fc57756684","order_by":0,"name":"Muhammad Ali","email":"","orcid":"","institution":"Dow International Medical College","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Ali","suffix":""},{"id":543047407,"identity":"28c945be-09c6-4052-9a42-4cb0da47a2e9","order_by":1,"name":"Noreen Haidar Khan","email":"","orcid":"","institution":"College of Medicine and Public Health, Flinders University","correspondingAuthor":false,"prefix":"","firstName":"Noreen","middleName":"Haidar","lastName":"Khan","suffix":""},{"id":543047408,"identity":"ba75cbe6-e257-4a6e-8b25-3ae1a8cdbb47","order_by":2,"name":"Ahmad Kamal","email":"","orcid":"","institution":"Bannu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Kamal","suffix":""},{"id":543047411,"identity":"e66b4f77-ce79-4103-82f2-5fecab49fbb7","order_by":3,"name":"Saif ur Rahman","email":"","orcid":"","institution":"Bacha Khan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Saif","middleName":"ur","lastName":"Rahman","suffix":""},{"id":543047412,"identity":"1db493b4-fa5b-499b-956f-510e215a813c","order_by":4,"name":"Nafila Zeeshan","email":"","orcid":"","institution":"Dow University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Nafila","middleName":"","lastName":"Zeeshan","suffix":""},{"id":543047413,"identity":"7663a61b-4f04-4a72-821e-1040bdd49213","order_by":5,"name":"Rahul Falodia","email":"","orcid":"","institution":"All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Rahul","middleName":"","lastName":"Falodia","suffix":""},{"id":543047415,"identity":"43d52996-1710-4a95-80ce-2f6e0311cbfb","order_by":6,"name":"Muhammad Seerat Ali","email":"","orcid":"","institution":"Quaid-e-Azam Medical College","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Seerat","lastName":"Ali","suffix":""},{"id":543047416,"identity":"73aa3b11-a4d9-4b20-90d9-e5a8816f73a5","order_by":7,"name":"Muhammad Mukhlis","email":"","orcid":"","institution":"Ayub Medical College","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Mukhlis","suffix":""},{"id":543047421,"identity":"e4432e7a-7b17-4f0a-ab72-30ae9403a8c8","order_by":8,"name":"Irtiza Ali","email":"","orcid":"","institution":"Texas A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"Irtiza","middleName":"","lastName":"Ali","suffix":""},{"id":543047422,"identity":"481aeeb0-a0b7-47d0-8e27-9e86a8c4d7bd","order_by":9,"name":"Ali Rizvi","email":"","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Rizvi","suffix":""},{"id":543047424,"identity":"213f14ab-2ed6-4ec6-b3bb-90673a0bb08e","order_by":10,"name":"Kamil Ahmad Kamil","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYDCCA2xAwsCCwQBISSRUAElm5gZitEhAtDw4A9LCSIwWBogWyYdtIA4BLXy3jyV+ulEgIW8udvjhjcR5tdH87UAtPyq24dQieS7tsHSOgYThztlpxhaJ247nzjjM2MDYc+Y2Ti0GZ9gbQFoYN9xOMJNI3HYstwGohZmxDa+W5t9ALfYbbqd/k0iccyx3PmEtbMdAtiRuuJ0DtKWhJncDIS2SZ9jSrIFakoFaii0Sjh3I3QjUchCfX/jOsBnfzvljYwt02MabP2rqcuedP3zwwY8K3FrQwWEweYBo9UBQR4riUTAKRsEoGCEAAPfEX+tks3SwAAAAAElFTkSuQmCC","orcid":"","institution":"Mirwais Regional Hospital","correspondingAuthor":true,"prefix":"","firstName":"Kamil","middleName":"Ahmad","lastName":"Kamil","suffix":""},{"id":543047425,"identity":"564361be-6ec6-4bd2-8958-04b277d68664","order_by":11,"name":"Hamza Shakil","email":"","orcid":"","institution":"Dow International Medical College","correspondingAuthor":false,"prefix":"","firstName":"Hamza","middleName":"","lastName":"Shakil","suffix":""},{"id":543047426,"identity":"4a532592-7cda-4a98-bc50-41ed2030807c","order_by":12,"name":"Muhammad Anas","email":"","orcid":"","institution":"Dow International Medical College","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Anas","suffix":""}],"badges":[],"createdAt":"2025-10-13 15:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7850550/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7850550/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95800447,"identity":"c718ad2f-e7fc-4bd5-8a14-bb8a22381d3d","added_by":"auto","created_at":"2025-11-13 08:22:40","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1889243,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/1d62b97e685ced6a22147a7f.docx"},{"id":95715660,"identity":"88f41dbb-fcbb-4e20-9015-c07eb0956430","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13608,"visible":true,"origin":"","legend":"","description":"","filename":"1574d08005fb481aa3b67b06206e9cba.json","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/80bdbc31e39a5d13c33db07e.json"},{"id":95715671,"identity":"574f4761-65a9-491e-9561-e86f8bb8f325","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5233565,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/4f64f9dfadeed94961aa738c.docx"},{"id":95800318,"identity":"bc0f6d34-85ef-46ef-bf31-259cb205dc69","added_by":"auto","created_at":"2025-11-13 08:22:12","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":93735,"visible":true,"origin":"","legend":"","description":"","filename":"1574d08005fb481aa3b67b06206e9cba1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/fd98b4654f4bed9b04619dc7.xml"},{"id":95715664,"identity":"6c98ba71-0f63-497c-8193-4af5539b7a61","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":583594,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/818ca83dfad57d95f903ee54.jpeg"},{"id":95800063,"identity":"52acce17-8cd2-43d0-823a-8ba9153d4e52","added_by":"auto","created_at":"2025-11-13 08:21:30","extension":"emf","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4303496,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.emf","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/d1c04911f3a9e17159e9950a.emf"},{"id":95715677,"identity":"5bd3b501-44b1-48c7-95c7-81743e58354f","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"emf","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3935408,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.emf","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/dd57e4cf296f72d8ca815d34.emf"},{"id":95715669,"identity":"014ff9c8-c1af-48d9-a2be-fbf4968c52a1","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"emf","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4398792,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.emf","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/b4130007f47d01e9b005a89c.emf"},{"id":95800397,"identity":"8c460347-1520-4f97-9885-007dd6152e48","added_by":"auto","created_at":"2025-11-13 08:22:35","extension":"emf","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4450924,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.emf","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/e894dc2336c71b4693700ec0.emf"},{"id":95715678,"identity":"01b20c00-75d5-4d35-bcc7-ca07b4974190","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"emf","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4456896,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.emf","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/3e68217a224e748eda27d7d8.emf"},{"id":95799900,"identity":"6bf782d6-5b0f-4e15-9173-a274d26ab1fd","added_by":"auto","created_at":"2025-11-13 08:21:04","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":299790,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/c225707c7dce1dd526e456f1.png"},{"id":95715685,"identity":"57a61a6d-dac2-477e-aa2b-8b360acd4c6e","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":293404,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/30f939eaf7e740f5470848bf.png"},{"id":95715667,"identity":"17a9eeac-cac2-43a5-87e0-48bef0d3d1be","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":94481,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/8b3f6430302e2bd1d1c46519.png"},{"id":95800481,"identity":"577f1a55-fa0a-46e6-b872-ed9d8fd0d94a","added_by":"auto","created_at":"2025-11-13 08:22:43","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":25974,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/89257e9ebba543d1d8064ef1.png"},{"id":95715674,"identity":"0e92d561-44e9-40e4-b961-4af96fb1dce5","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":27572,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/7d6d93d0613ed26268dfed1d.png"},{"id":95801132,"identity":"9b394726-c97f-488c-b709-75507f999b24","added_by":"auto","created_at":"2025-11-13 08:24:31","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":25531,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/a5c84092db9f7cf557571810.png"},{"id":95715683,"identity":"7ed4f349-6ca4-4f1b-b56d-c98197141ef3","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":22734,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/45e263ef0e76d18b6ccad847.png"},{"id":95715681,"identity":"7584d2f0-cac5-487e-9cf3-2e925a977d4b","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38701,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/42c8bbce492347d0ce476eb0.png"},{"id":95800102,"identity":"44bc4e61-8aab-4724-b39a-46b49368c5ae","added_by":"auto","created_at":"2025-11-13 08:21:35","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":67336,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/ec6ee48fe486a8559252180c.png"},{"id":95715680,"identity":"199c0b47-1ec8-4fbf-9bc8-c5244d9cecfd","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66391,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/1caaf91c56276919d6508aeb.png"},{"id":95715673,"identity":"e8581232-2da6-4215-a406-f4c0e705baf1","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"xml","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":91139,"visible":true,"origin":"","legend":"","description":"","filename":"1574d08005fb481aa3b67b06206e9cba1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/c1782f7972d4d57a906cfb2e.xml"},{"id":95715687,"identity":"e86d75cf-fabb-47f3-a2aa-e6fbc3e3bc94","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"html","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":106566,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/c2937ef8001b65e540782c4c.html"},{"id":95715656,"identity":"df122d11-81b6-4a04-9ec9-612197cb59aa","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":248915,"visible":true,"origin":"","legend":"\u003cp\u003eCentral Illustration.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/0bc95b9254621ad2f4d4a0b2.png"},{"id":95799323,"identity":"a80d11a6-0f25-4d19-817b-6283baa62f74","added_by":"auto","created_at":"2025-11-13 08:19:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46675,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Glaucoma-Related Age-Adjusted Mortality Rate by Sex, 2000 to 2023.\u003c/p\u003e\n\u003cp\u003e*Indicates APC is significantly different from 0\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/f02aed1aabc563766914f8c3.png"},{"id":95715657,"identity":"b87aaee6-adb6-43a7-85ee-d12a39b58853","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54722,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Glaucoma-Related Age-Adjusted Mortality Rate by Race, 2000 to 2023.\u003c/p\u003e\n\u003cp\u003eNH = non-Hispanic\u003c/p\u003e\n\u003cp\u003e*Indicates APC is significantly different from 0\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/ca792cca3c7364b75565e7fb.png"},{"id":95715659,"identity":"f045d79c-75c0-4b35-91c6-7dfef95c67c8","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":43075,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Glaucoma-Related Crude Mortality Rate by Age Group, 2000 to 2023.\u003c/p\u003e\n\u003cp\u003e*Indicates APC is significantly different from 0\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/86c33df68be2fd47a92b1899.png"},{"id":95715663,"identity":"01619a5f-7474-49c2-80bd-f3f4e57a6140","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":37725,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Glaucoma-Related Age-Adjusted Mortality Rate by Urbanization, 2000 to 2020.\u003c/p\u003e\n\u003cp\u003e*Indicates APC is significantly different from 0\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/8cb0f3cbf8f9d4e2c0ae1492.png"},{"id":95800678,"identity":"42edf8fb-5172-45ba-a989-ab7ffb718bb7","added_by":"auto","created_at":"2025-11-13 08:23:10","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":66110,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Glaucoma-Related Age-Adjusted Mortality Rate by Census Region, 2000 to 2023.\u003c/p\u003e\n\u003cp\u003e*Indicates APC is significantly different from 0\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/ce4edf657e9924cb9e058f38.png"},{"id":95715676,"identity":"1dc74cff-c5f5-4f78-a78f-72a1550f8ae5","added_by":"auto","created_at":"2025-11-12 08:42:26","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":104171,"visible":true,"origin":"","legend":"\u003cp\u003eLeading Underlying Causes of Glaucoma-Associated Death by % of Deaths, 2000 to 2019.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/72d41de7e8f1b475bf0e4c2f.png"},{"id":95800306,"identity":"3d741c8f-cfc8-4373-996e-597798c88cf7","added_by":"auto","created_at":"2025-11-13 08:22:07","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":103731,"visible":true,"origin":"","legend":"\u003cp\u003eLeading Underlying Causes of Glaucoma-Associated Death by % of Deaths, 2020 to 2023.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/044cd665c7fc98e004d36ea7.png"},{"id":99316119,"identity":"5454d4e7-2805-4a9e-84e6-135bd7d1cebc","added_by":"auto","created_at":"2025-12-31 16:27:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1273864,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/add4006e-f0ed-48cb-8976-eb14aa827b67.pdf"},{"id":95715666,"identity":"19a2167d-ed72-4505-ad8d-9cff58e18a17","added_by":"auto","created_at":"2025-11-12 08:42:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5233565,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary File 1. Docx\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Materials\u003c/p\u003e\n\u003cp\u003eContains supplemental tables referenced in the manuscript as an additional file\u003c/p\u003e","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7850550/v1/f07c8a22ec0aba65ca4fccf0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evolution of Glaucoma-Related Mortality among Older Adults in the United States: Insights from CDC WONDER (2000–2023)","fulltext":[{"header":"1.0 INTRODUCTION","content":"\u003cp\u003eGlaucoma is a chronic, progressive optic neuropathy disorder characterized by irreversible damage to the optic nerve, which results in visual field loss and blindness if untreated [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is among the leading causes of irreversible blindness worldwide, affecting nearly 76\u0026nbsp;million people in 2020, and the number is projected to rise to 111.8\u0026nbsp;million by 2040, with around two-thirds of all glaucoma cases above 70 years of age [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The disease burden grows exponentially with advancing age, and population aging has therefore become a major driver of global glaucoma prevalence and associated disability [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRising research has highlighted the possibility of glaucoma having more systemic risks than just visual side effects [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. While glaucoma is usually not a cause of death, it does have associations with age-related vascular, metabolic, and neurodegenerative conditions. Having visual impairment can cause more falls, cognitive decline, and reduced quality of life, which can affect long-term morbidity and mortality, especially in elderly subjects [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. By examining patterns of glaucoma mortality, we could gain a better understanding of both ocular and other health inequalities in aging populations.\u003c/p\u003e\u003cp\u003eIn the United States, glaucoma and its impact are distributed unevenly across racial, demographic, and geographic sub-groups [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These inequities are also due to socioeconomic factors, unequal access to quality health care, or differing patterns of health-seeking behaviors. Still, there is a lack of national-level analysis of glaucoma-related deaths, as most studies look at the prevalence, disparities in treatment, or visual impairment only. There is limited available research that has examined temporal mortality trends, with stratifications by demographic or regional classifications, or the impact of recent system disruptions such as COVID-19.\u003c/p\u003e\u003cp\u003ePopulation-based data is essential for tracking mortality trends. This information helps us understand the long-term burden of disease. We used the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database to examine glaucoma-specific mortality trends over several decades [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study explores trends and differences in glaucoma mortality among U.S. adults aged 65 and older from 2000 to 2023. It includes estimates of age-adjusted mortality rates for both the overall population and specific subgroups.\u003c/p\u003e"},{"header":"2.0 METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design and Data Source\u003c/h2\u003e\u003cp\u003eIn this population-based analysis, death certificate data were retrieved from the CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database. Death certificate data from 2000 to 2023 for glaucoma-related mortality in adults aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years was examined using codes from the International Statistical Classification of Diseases and Related Health Problems-10th Revision (ICD-10) specified as H40. This dataset includes cause of death from death certificates for the 50 states and the District of Columbia and has been previously used in several studies to determine trends in mortality [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The Multiple Cause-of-Death Public Use record death certificates were studied to select Glaucoma-related deaths, which were identified as those with glaucoma reported anywhere on the death certificate, either as a contributing or underlying cause of death. Additionally, extraction for the leading causes of glaucoma-associated deaths using the top 15 underlying causes of death (UCD-15) list from CDC WONDER was divided into pre-pandemic (2000\u0026ndash;2019) and pandemic (2020\u0026ndash;2023) time periods, with their respective ICD-10 codes (Supplemental Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Older adults were defined as adults aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years. Age groups were stratified into three categories: adults aged 65\u0026ndash;74 years, 75\u0026ndash;84 years, and \u0026ge;\u0026thinsp;85 years. Similar age group classifications have been used to define older adults in previous studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This study was exempt from local institutional review board approval as it utilized de-identified, government-issued public use records. We followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Variables and Measures\u003c/h2\u003e\u003cp\u003eData for population size, year, location of death, demographics, urbanicity, U.S. census region, state, and leading underlying causes of glaucoma-associated deaths were extracted and analyzed. Place of death included medical facilities (inpatient, outpatient/emergency room, death on arrival, or status unknown), decedent\u0026rsquo;s home, hospices, nursing home/long-term care facility, other, and unknown locations. Demographic grouping included sex, age group, and race (non-Hispanic (NH) White, NH Black or African American, and Hispanic or Latino). The Urban-Rural Classification Scheme from the National Center for Health Statistics was used to evaluate the population by metropolitan (large metropolitan area [population\u0026thinsp;\u0026ge;\u0026thinsp;1 million], medium/small metropolitan area [population between 50,000 and 999,999]) and non-metropolitan (population under 50,000) counties based on the 2013 U.S. census classification [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. U.S. census regions were classified into the Northeast, Midwest, South, and West in line with the U.S. Census Bureau definitions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Statistical Analysis\u003c/h2\u003e\u003cp\u003eTo examine national trends in glaucoma-related mortality, we calculated crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) per 100,000 persons by standardizing glaucoma-related deaths to the year 2000 U.S. population [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. CMRs and AAMRs from death certificates were extracted from 2000 to 2023 and stratified by year, sex, race, state, and urban-rural status with corresponding 95% CIs. AAMRs were calculated by standardizing glaucoma-related deaths to the year 2000 U.S. population. To quantify national annual trends in glaucoma-related mortality, the Joinpoint Regression Program (National Cancer Institute, version 5.0) was used to determine the annual percent change (APC) and average annual percent change (AAPC) with 95% CI in AAMR [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This method identifies significant changes in AAMR over time by fitting log-linear regression models where temporal variation occurred. A value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3.0 RESULTS","content":"\u003cp\u003eA total of 21,805 glaucoma-related deaths occurred among adults aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years from 2000 to 2023 in the United States. Most deaths occurred in nursing homes/long-term care centers (10,216; 46.85%), followed by the decedent\u0026rsquo;s home (4,865; 22.31%) and medical facilities (4,828; 22.14%). Smaller proportions of deaths occurred in hospices (699; 3.21%) and other/unknown locations (1,197; 5.49%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Supplemental Table S2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Annual Trends\u003c/h2\u003e\u003cp\u003eOverall AAMRs declined from 2.98 (95% CI: 2.80\u0026ndash;3.16) in 2000 to 2.29 (95% CI: 2.16\u0026ndash;2.42) in 2023 (AAPC: -1.39; 95% CI: -1.88 to -0.92). AAMRs initially decreased from 2000 to 2009 (APC: -6.01; 95% CI: -10.46 to -4.53), followed by stable rates from 2009 to 2016. Mortality rates increased afterwards until 2023 (APC: 5.36; 95% CI: 2.86 to 10.91) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Supplemental Tables S3 and S4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Sex-Specific Trends\u003c/h2\u003e\u003cp\u003eWomen accounted for 13,738 deaths (63%), while men accounted for 8,067 deaths (37%). The average AAMR was similar for women and men (average AAMR women: 2.08; average AAMR men: 2.09).\u003c/p\u003e\u003cp\u003eAAMRs for women declined from 3.00 (95% CI: 2.78\u0026ndash;3.23) in 2000 to 2.21 (95% CI: 2.05\u0026ndash;2.38) in 2023 (AAPC: -1.57; 95% CI: -2.17 to -1.01). AAMRs initially decreased from 2000 to 2010 (APC: -5.84; 95% CI: -10.80 to -0.23), followed by stable rates until 2023.\u003c/p\u003e\u003cp\u003eAAMRs for men declined from 2.97 (95% CI: 2.66\u0026ndash;3.29) in 2000 to 2.37 (95% CI: 2.16\u0026ndash;2.58) in 2023 (AAPC: -1.09; 95% CI: -1.59 to -0.53). AAMRs initially decreased from 2000 to 2009 (APC: -5.71; 95% CI: -11.25 to -2.68), followed by stable rates from 2009 to 2015. Mortality rates then increased afterwards until 2023 (APC: 5.01; 95% CI: 0.41 to 10.53). (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Supplemental Tables S3 and S4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Race Specific Trends\u003c/h2\u003e\u003cp\u003eNon-Hispanic (NH) Whites had the greatest number of deaths, 16,945 (79.81%), followed by NH Black/African Americans 3,182 (14.98%) and Hispanic/Latinos 1,105 (5.20%). In terms of AAMR, NH Black/African Americans had the highest average AAMR (3.92), followed by NH Whites (1.99) and Hispanic/Latinos (1.61).\u003c/p\u003e\u003cp\u003eNH Black/African Americans had their AAMRs decrease from 5.83 (95% CI: 4.90\u0026ndash;6.75) in 2000 to 4.15 (95% CI: 3.54\u0026ndash;4.75) in 2023 (AAPC: -1.17; 95% CI: -2.17 to -0.12). AAMRs initially decreased from 2000 to 2014 (APC: -5.55; 95% CI: -8.87 to -3.69), followed by an increase in rates until 2023 (APC: 6.05; 95% CI: 2.56 to 14.61).\u003c/p\u003e\u003cp\u003eNH Whites had their AAMRs decrease from 2.87 (95% CI: 2.68\u0026ndash;3.06) in 2000 to 2.17 (95% CI: 2.03\u0026ndash;2.32) in 2023 (AAPC: -1.39; 95% CI: -1.74 to -1.05). AAMRs initially decreased from 2000 to 2010 (APC: -5.89; 95% CI: -8.03 to -5.07), followed by stable rates from 2010 to 2016. Mortality rates then increased afterwards until 2023 (APC: 5.15; 95% CI: 3.63 to 9.02).\u003c/p\u003e\u003cp\u003eAAMRs for Hispanic/Latinos remained stable from 1.73 (95% CI: 1.10\u0026ndash;2.59) in 2000 to 2.27 (95% CI: 1.83\u0026ndash;2.71) in 2023, with no increases or decreases in mortality rates interspersed throughout the study duration. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Supplemental Tables S4 and S5).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Age Group Specific Trends\u003c/h2\u003e\u003cp\u003eAdults aged\u0026thinsp;\u0026ge;\u0026thinsp;85 years contributed the greatest number of deaths (14,389) and the highest average CMR (10.98), followed by adults aged 75\u0026ndash;84 years (5,503 deaths; average CMR: 1.64) and 65\u0026ndash;74 years (1,913 deaths; average CMR: 0.33).\u003c/p\u003e\u003cp\u003eCMRs for adults aged 65\u0026ndash;74 years remained stable from 0.53 (95% CI: 0.43\u0026ndash;0.65) in 2000 to 0.37 (95% CI: 0.31\u0026ndash;0.43) in 2023. CMRs initially decreased from 2000 to 2015 (APC: -5.19; 95% CI: -7.33 to -3.67), followed by an increase in rates until 2023 (APC: 8.15; 95% CI: 4.62 to 14.45).\u003c/p\u003e\u003cp\u003eCMRs for adults aged 75\u0026ndash;84 years decreased from 2.54 (95% CI: 2.26\u0026ndash;2.82) in 2000 to 1.64 (95% CI: 1.45\u0026ndash;1.82) in 2023 (AAPC: -1.83; 95% CI: -2.26 to -1.37). CMRs initially decreased from 2000 to 2014 (APC: -5.10; 95% CI: -6.09 to -4.31), followed by an increase in rates until 2023 (APC: 3.49; 95% CI: 1.90 to 5.84).\u003c/p\u003e\u003cp\u003eCMRs for adults aged\u0026thinsp;\u0026ge;\u0026thinsp;85 years declined from 14.91 (95% CI: 13.74\u0026ndash;16.07) in 2000 to 12.33 (95% CI: 11.46\u0026ndash;13.21) in 2023 (AAPC: -1.30; 95% CI: -1.82 to -0.79). CMRs initially decreased from 2000 to 2010 (APC: -5.78; 95% CI: -10.09 to -1.95), followed by stable rates from 2010 to 2016. Mortality rates then increased afterwards until 2023 (APC: 4.80; 95% CI: 1.85 to 11.07) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; Supplemental Tables S4 and S6).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Urbanization-Specific Trends (2000\u0026ndash;2020)\u003c/h2\u003e\u003cp\u003eAlthough metropolitan areas accounted for most of the deaths (14,698), average AAMRs were higher in non-metropolitan (2.39) compared with metropolitan (2.02) areas.\u003c/p\u003e\u003cp\u003eAAMRs for non-metropolitan areas declined from 3.45 (95% CI: 3.01\u0026ndash;3.89) in 2000 to 2.33 (95% CI: 2.01\u0026ndash;2.65) in 2020 (AAPC: -2.74; 95% CI: -3.84 to -1.96). AAMRs initially decreased from 2000 to 2015 (APC: -5.27; 95% CI: -7.53 to -4.32), followed by stable rates until 2020.\u003c/p\u003e\u003cp\u003eMetropolitan areas had their AAMRs decline from 2.89 (95% CI: 2.69\u0026ndash;3.09) in 2000 to 2.16 (95% CI: 2.03\u0026ndash;2.30) in 2020 (AAPC: -2.09; 95% CI: -2.69 to -1.59). AAMRs initially decreased from 2000 to 2009 (APC: -6.35; 95% CI: -10.16 to -4.81), followed by stable rates from 2009 to 2016. Mortality rates then increased afterwards until 2020 (APC: 6.34; 95% CI: 2.15 to 14.07) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; Supplemental Tables S4 and S7).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Region-Specific Trends\u003c/h2\u003e\u003cp\u003eThe Midwest had the highest number of deaths (5,562) and the greatest average AAMR (2.36), followed by the Northeast (4,864 deaths; average AAMR: 2.22), West (4,661 deaths; average AAMR: 2.09), and South (6,718 deaths; average AAMR: 1.84).\u003c/p\u003e\u003cp\u003eIn the Northeast, AAMRs remained stable over the study period, from 2.88 (95% CI: 2.50\u0026ndash;3.26) in 2000 to 3.19 (95% CI: 2.84\u0026ndash;3.54) in 2023. AAMRs initially decreased from 2000 to 2008 (APC: -7.19; 95% CI: -10.4361 to -4.9079), followed by increasing rates from 2008 to 2013 (APC: 6.41; 95% CI: 0.87 to 15.96). Mortality rates then decreased again from 2013 to 2016 (APC: -10.11; 95% CI: -15.35 to -1.17), followed by another increase in rates from 2016 to 2020 (APC: 16.03; 95% CI: 10.96 to 25.42) and lastly stable rates until 2023.\u003c/p\u003e\u003cp\u003eIn the Midwest, AAMRs declined from 3.79 (95% CI: 3.38\u0026ndash;4.20) in 2000 to 1.37 (95% CI: 1.15\u0026ndash;1.59) in 2023 (AAPC: -4.33; 95% CI: -5.15 to -3.61). AAMRs initially decreased from 2000 to 2014 (APC: -6.32; 95% CI: -8.99 to -5.30), followed by stable rates until 2023.\u003c/p\u003e\u003cp\u003eIn the South, AAMRs declined from 2.77 (95% CI: 2.47\u0026ndash;3.07) in 2000 to 2.21 (95% CI: 2.00\u0026ndash;2.42) in 2023 (AAPC: -1.33; 95% CI: -2.08 to -0.62). AAMRs initially decreased from 2000 to 2010 (APC: -6.69; 95% CI: -13.48 to -3.78), followed by stable rates from 2010 to 2018, and lastly increasing rates thereafter until 2023 (APC: 8.75; 95% CI: 3.44 to 19.97).\u003c/p\u003e\u003cp\u003eIn the West, AAMRs remained stable, from 2.55 (95% CI: 2.17\u0026ndash;2.93) in 2000 to 2.48 (95% CI: 2.19\u0026ndash;2.76). AAMRs were initially stable from 2000 to 2010, followed by increasing mortality rates thereafter until 2023 (APC: 3.79; 95% CI: 2.69 to 5.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e; Supplemental Tables S4 and S8).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.7 Leading Underlying Causes of Death (2000\u0026ndash;2019)\u003c/h2\u003e\u003cp\u003eFrom 2000 to 2019, the top 5 leading underlying causes of glaucoma-associated deaths were heart disease, malignant neoplasms, Alzheimer\u0026rsquo;s disease, cerebrovascular diseases, and chronic lower respiratory diseases. Heart disease resulted in 4,000 deaths with an AAMR of 0.44 (95% CI: 0.42\u0026ndash;0.45), followed by malignant neoplasms with 2,730 deaths and an AAMR of 0.33 (95% CI: 0.32\u0026ndash;0.34). Alzheimer\u0026rsquo;s disease accounted for 1,702 deaths (AAMR: 0.18; 95% CI: 0.17\u0026ndash;0.19), and cerebrovascular diseases caused 1,413 deaths (AAMR: 0.15; 95% CI: 0.14\u0026ndash;0.15). Chronic lower respiratory diseases and diabetes mellitus each contributed 808 and 796 deaths, respectively, both with an AAMR of 0.08. Other notable causes included essential hypertension and hypertensive renal disease (687 deaths; AAMR: 0.06), unintentional injuries (348 deaths; AAMR: 0.02), Parkinson\u0026rsquo;s disease (345 deaths; AAMR: 0.06), influenza and pneumonia (196 deaths; AAMR: 0.01), pneumonitis due to solids and liquids (105 deaths; AAMR: 0.01), in situ/benign/uncertain or unknown behavior neoplasms (103 deaths; AAMR: 0.01), sepsis (85 deaths; AAMR: 0.01), nephritis/nephrotic syndrome/nephrosis (82 deaths; AAMR: 0.01), and anemias (61 deaths; AAMR: 0.00) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e7\u003c/span\u003e; Supplemental Tables S9 and S10).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.8 Leading Underlying Causes of Death (2020\u0026ndash;2023)\u003c/h2\u003e\u003cp\u003eFrom 2020 to 2023, the top 5 leading underlying causes of glaucoma-associated deaths included heart disease, malignant neoplasms, Alzheimer\u0026rsquo;s disease, cerebrovascular diseases, and COVID-19. Heart disease accounted for 793 deaths with an AAMR of 0.34 (95% CI: 0.32\u0026ndash;0.37), followed by malignant neoplasms with 643 deaths and an AAMR of 0.31 (95% CI: 0.28\u0026ndash;0.33). Alzheimer\u0026rsquo;s disease resulted in 398 deaths (AAMR: 0.18; 95% CI: 0.16\u0026ndash;0.20), while cerebrovascular diseases caused 282 deaths (AAMR: 0.13; 95% CI: 0.12\u0026ndash;0.15). COVID-19 contributed to 276 deaths with an AAMR of 0.12 (95% CI: 0.11\u0026ndash;0.14). Other notable causes included diabetes mellitus (199 deaths; AAMR: 0.07; 95% CI: 0.06\u0026ndash;0.08), chronic lower respiratory diseases (172 deaths; AAMR: 0.08; 95% CI: 0.07\u0026ndash;0.10), and essential hypertension and hypertensive renal disease (162 deaths; AAMR: 0.06; 95% CI: 0.05\u0026ndash;0.07). Remaining causes, such as unintentional injuries, Parkinson\u0026rsquo;s disease, nutritional deficiencies, influenza and pneumonia, septicemia, chronic liver disease, and in situ/benign/uncertain or unknown behavior neoplasms, accounted for fewer deaths with corresponding lower AAMRs (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e; Supplemental Tables S9 and S10).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4.0 DISCUSSION","content":"\u003cp\u003eGlaucoma mortality among older US adults spanning more than two decades was dynamic, with a decrease in the early 2000s, relative stabilization over the next decade, and a foreboding spike after 2016. These trends are also reflected in worldwide reports of initial progress through mass screening, new pharmacologic therapy, and improved surgical technique, followed by plateauing of these advances in high-resource nations. The later rebound is concurrent with aging populations, increasing systemic comorbidities like diabetes and vascular disease, and persisting disparities in access to specialty care [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. By examining the CDC WONDER national mortality data and Joinpoint regression, it is revealed that while earlier there was improvement, sex, race, age, urbanization, and geographic disparities still characterize the burden of glaucoma mortality in the United States.\u003c/p\u003e\u003cp\u003eThe broad trend of early declines ultimately reversed to increases, capturing the interplay between medical innovation and population health forces. Death decreased with improvements in cataract and glaucoma surgery, the introduction of prostaglandin analogues, and access to eye exams due to factors related to Medicare. As treatment becomes commonplace, innovation stalls, and population condition and demographic pressures once more catch up with deaths. Post-2016 increase in later rise also aligns with wider literature that indicates multimorbidity, frailty, and demographically driven aging are transforming ophthalmic results as a systemic disease concern rather than as an isolated ocular disease. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the post-2020 period, an additional finding was the emergence of COVID-19 as a significant co-occurring and contributing cause of glaucoma-associated deaths, reflecting the systemic vulnerability of elderly adults with ocular and vascular comorbidities.\u003c/p\u003e\u003cp\u003eSex trends were also noticed to be relatively evenly balanced during the study duration, where men and women both declined and then rose, and had similar average AAMRs. This concordance agrees with other US and European studies that found there were few sex-specific differences in glaucoma progression after controlling for age and comorbidity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Underneath this, there are differences in behavior and care-seeking. Preventive eye care in the past has been accessed more by women, allowing earlier detection, while more surgical intervention was performed in men, including for more advanced disease. With increasing access to health care becoming increasingly equal between the two sexes with the passage of time, mortality convergence occurred. Late acceleration in both sexes follows evidence where enhanced improvement in longevity and increasing multimorbidity have similar effects on men and women, plugging earlier gaps in use of care and results [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThere were significant racial and ethnic disparities during the study duration. Non-Hispanic Black adults in all regions consistently reported higher glaucoma mortality compared to Whites and Hispanics. This is consistent with much of decades of epidemiologic evidence for a more rapid onset, faster rate of progression, and greater glaucoma severity in Blacks [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Biologic susceptibility in the form of thinner corneal thickness and increased burden of more advanced open-angle glaucoma subtypes is augmented by social determinants such as decreased access to subspecialty services, decreased rates of surgical follow-up, and system-level healthcare inequities in infrastructure [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The rising mortality trend for Black adults is concerning and in line with evidence that specialist disparities in the availability of healthcare have increased since 2015 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Hispanic adults, on the other hand, had lower mortality as seen in prevalence studies earlier, although rising diabetes and hypertension burden within the cohort perhaps to redirect future trends [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. All these differences prove that global, behavioral, and biological determinants converge to create a mortality gradient by race. The most dramatic gradient was demonstrated in age-stratified analysis and is described in older persons with the highest burden of mortality associated with glaucoma.\u003c/p\u003e\u003cp\u003eAll global cohort studies identify increasing age as the most significant disease course and risk factor for visual impairment. Late-life survival gains once depended on successful surgery, new classes of drugs, and increasing Medicare-sponsored screening of the eyes. The resulting increase is nonetheless in line with the demographic increase of the oldest-old population and increasing frailty, multimorbidity, and polypharmacy to exert risk [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Adults aged 65\u0026ndash;74 years evidenced more gradual and slower rising rates, as would be predicted by the hypothesis that disease states at earlier stages in the course of the disease are best treated by longer duration therapy and fewer systemic comorbidities [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The age disparity serves to highlight the fact that glaucoma mortality is no less an index of systemic susceptibility than of ocular disease. Urbanizing trends were imposed upon rural disadvantage.\u003c/p\u003e\u003cp\u003eNon-metropolitan residents have always had higher glaucoma mortality compared with metropolitan residents. These results are consistent with those of rural ophthalmologist shortages, greater travel distances to special care services, and greater continuity-of-care issues. Rural-urban disparities during previous years presumably resulted from national expansions of Medicare coverage and eye care utilization [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Yet rural disadvantage remerges more recently with clinic closures, transportation issues, and reduced availability of subspecialists. Urban populations also evidenced lagging growth, that is, even the wealthiest environments are not exempt from the cumulative effects of aging and systemic disease [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Geographic variation also evidenced convergence of trends in demographics and health system capacity.\u003c/p\u003e\u003cp\u003eThe Midwest experienced record-high rates but achieved long-term decreases, and these most likely resulted from an initial high burden combined with judicious utilization of surgical and community-based eye care programs. Northeast experienced unstable trends, which is typical of its very heterogeneous population and mixed health infrastructure. South had lower mean rates but with a high total number of deaths, in accordance with its race and size, and long-standing differences in provision. West fluctuated up and down until late on, in accordance with demographic change, rising migration, and skewed distribution of healthcare facilities. These trends emphasize the necessity for region-level interventions that take into consideration both sociodemographic conditions and health system capability [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Death trends of nursing homes contributed additional information about populations most impacted.\u003c/p\u003e\u003cp\u003eThe prevalence of glaucoma death among nursing homes and long-term care facilities highlights the susceptibility of frail, dependent elderly persons. Such groups are at higher risk for severe comorbidity and lower accessibility to specialty ophthalmologic treatment, raising the risk of death. Hospital mortality relative to other chronic illnesses is consistent with the literature describing glaucoma as more disabling and causative than acute terminal in nature [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Home death frequency is consistent with end-of-life care unmet needs and visually impaired older person support, described consistently throughout geriatric care literature as being a chronic shortcoming.\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Limitations\u003c/h2\u003e\u003cp\u003eDependence on death certificate data has the potential for misclassification of risk because glaucoma is an uncommon main cause of death, but instead often occurs episodically as a contributing cause. Inter-state and inter-temporal variation in rules for certification and coding may alter observed mortality patterns. Second, small numbers culling in CDC WONDER limited the capacity to estimate less prevalent racial and geographic subgroups reasonably, which may suppress inequities. Third, ecological design will not allow adjustment for variables at the individual level, such as socioeconomic status, treatment adherence, or disease comorbid burden, all of which have been shown to affect outcomes. Fourth, changes in diagnostic methods, improvement in treatment, and usage of healthcare during the observation interval cannot be completely divorced from underlying trends in epidemiology. Beyond such limitations, the article presents a broad nationwide image of long-term demographic and geographical trends in glaucoma fatalities.\u003c/p\u003e\u003c/div\u003e"},{"header":"5.0 CONCLUSION","content":"\u003cp\u003eTaken together, these data place glaucoma not just as an ocular disease, but as an expression of systemic susceptibility and imbalance. This pattern of escalating early losses with subsequent gains both reflects poor people's victory over disease and the limitation of poor people's asymmetric access and population pressure. Stratified sex, race, age, urbanization, and geographic estimates affirm glaucoma mortality burden remains disproportionately skewed, based on a sophisticated interplay of biological risk, health system, and structural disadvantage.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAAMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAge\u0026ndash;adjusted Mortality Rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCrude Mortality Rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAAPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAverage Annual Percent Change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAnnual Percent Change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCDC WONDER\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCenters for Disease Control and Prevention Wide\u0026ndash;Ranging Online Data for Epidemiologic Research\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e10\u0026ndash;International Statistical Classification of Disease and Related Health Problems, 10th Revision\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enon\u0026ndash;Hispanic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eU.S\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUnited States\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUCD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUnderlying Cause of Death\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are publicly available, de-identified data from the CDC WONDER Multiple Cause-of-Death database. Available at: https://wonder.cdc.gov/mcd.html\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMA: conceptualization, project administration, supervision, validation, investigation, methodology, writing, writing – original draft, writing – review and editing; NHK: investigation, methodology, writing – original draft, writing – review and editing; AK: investigation, methodology, writing – original draft, writing – review and editing; SUR: investigation, methodology, writing – original draft, writing – review and editing; NZ: investigation, methodology, writing – original draft, writing – review and editing; RF: investigation, methodology, writing – original draft; MSA: graph and figure curation; MM: figure curation; IA: investigation, methodology, writing – original draft, writing – review and editing; AR: methodology– original draft, writing – review and editing; KAK: writing – review and editing; HS: writing – review and editing; MAS: writing – review and editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFig. 7 and Fig. 8 were created using Datawrapper. Available at: https://www.datawrapper.de/\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWeinreb RN, Aung T, Medeiros FA. The pathophysiology and treatment of glaucoma: a review. JAMA. 2014 May 14;311(18):1901-11. doi: 10.1001/jama.2014.3192. PMID: 24825645; PMCID: PMC4523637.\u003c/li\u003e\n\u003cli\u003eTham YC, Li X, Wong TY, Quigley HA, Aung T, Cheng CY. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology. 2014 Nov;121(11):2081-90. doi: 10.1016/j.ophtha.2014.05.013. Epub 2014 Jun 26. PMID: 24974815.\u003c/li\u003e\n\u003cli\u003eWolfram C. The Epidemiology of Glaucoma - an Age-Related Disease. Klin Monbl Augenheilkd. 2024 Feb;241(2):154-161. English, German. doi: 10.1055/a-2257-6940. Epub 2024 Feb 27. PMID: 38412979.\u003c/li\u003e\n\u003cli\u003eLeske MC. Open-angle glaucoma -- an epidemiologic overview. Ophthalmic Epidemiol. 2007 Jul-Aug;14(4):166-72. doi: 10.1080/09286580701501931. PMID: 17896292.\u003c/li\u003e\n\u003cli\u003eWey S, Amanullah S, Spaeth GL, Ustaoglu M, Rahmatnejad K, Katz LJ. Is primary open-angle glaucoma an ocular manifestation of systemic disease? Graefes Arch Clin Exp Ophthalmol. 2019 Apr;257(4):665-673. doi: 10.1007/s00417-019-04239-9. Epub 2019 Jan 15. PMID: 30643967.\u003c/li\u003e\n\u003cli\u003eEhrlich JR, Ramke J, Macleod D, Burn H, Lee CN, Zhang JH, Waldock W, Swenor BK, Gordon I, Congdon N, Burton M, Evans JR. Association between vision impairment and mortality: a systematic review and meta-analysis. Lancet Glob Health. 2021 Apr;9(4):e418-e430. doi: 10.1016/S2214-109X(20)30549-0. Epub 2021 Feb 16. PMID: 33607015; PMCID: PMC7966688.\u003c/li\u003e\n\u003cli\u003eKhachatryan N, Pistilli M, Maguire MG, Chang AY, Samuels MR, Mulvihill K, Salowe RJ, O\u0026apos;Brien JM. A Review of Studies of the Association of Vision-Related Quality of Life with Measures of Visual Function and Structure in Patients with Glaucoma in the United States. Ophthalmic Epidemiol. 2021 Jun;28(3):265-276. doi: 10.1080/09286586.2020.1863992. Epub 2021 Feb 3. PMID: 33530788; PMCID: PMC8261792.\u003c/li\u003e\n\u003cli\u003eCDC. CDC Wide-Ranging Online Data for Epidemiologic Research (WONDER). Available online: https://wonder.cdc.gov.\u003c/li\u003e\n\u003cli\u003eRani, S., Kumar, L., Ali, S.M.E. et al. Trends in United States mortality among patients with atrial fibrillation/flutter related heart failure (1999\u0026ndash;2024): disparities by gender, race/ethnicity and region. BMC Cardiovasc Disord 25, 558 (2025). https://doi.org/10.1186/s12872-025-05036-5\u003c/li\u003e\n\u003cli\u003eRath, S., Hameed, H., Rahman, S.U. \u003cem\u003eet al.\u003c/em\u003e Disparities in hernia-related mortality among older adults in the U.S.: A 21-year analysis of the CDC-WONDER database. \u003cem\u003eHernia\u003c/em\u003e 29, 285 (2025). https://doi.org/10.1007/s10029-025-03464-y\u003c/li\u003e\n\u003cli\u003eShree Rath, Amar Lal, Ahmed Hasan, Muhammad Ali, Laiba Sultan, Mishaim Khan, Umama Alam, Long-Term Mortality Trends From Prostate Cancer and Associated Second Malignancies in the U.S., 1999 to 2023: Implications for Survivorship Care, Clinical Genitourinary Cancer, 2025, 102428, ISSN 1558-7673, https://doi.org/10.1016/j.clgc.2025.102428.\u003c/li\u003e\n\u003cli\u003eVandenbroucke JP, von Elm E, Altman DG, G\u0026oslash;tzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Ann Intern Med. 2007 Oct 16;147(8):W163-94. doi:10.7326/0003-4819-147-8-200710160-00010-w1.\u003c/li\u003e\n\u003cli\u003eIngram D.D., Franco S.J. 2013 NCHS Urban-Rural Classification Scheme for Counties. US Department of Health and Human Services, Centers for Disease Control and Prevention, 2014.\u003c/li\u003e\n\u003cli\u003eAnderson R.N., Rosenberg H.M. Age Standardization of death rates: implementation of the year 2000 standard. Natl Vital Stat Rep 1998;47:1-17\u003c/li\u003e\n\u003cli\u003eNational Cancer Institute, Surveillance Research Program. Joinpoint Trend Analysis Software Internet. Bethesda (MD): National Cancer Institute; cited 2025 Oct 8. Available from: https://surveillance.cancer.gov/joinpoint/\u003c/li\u003e\n\u003cli\u003eK\u0026uuml;hn T, Rohrmann S, Karavasiloglou N, Friedman DS, Cassidy A, B\u0026auml;rnighausen T, et al. Glaucoma and mortality risk: findings from a prospective population-based study. Sci Rep. 2021 June 3;11:11771. \u003c/li\u003e\n\u003cli\u003eHuang X, Xu M, Zhou M, Liu W, Zhao X, Sun X. The association between glaucoma and all-cause mortality in middle-aged and elderly Chinese people: results from the China Health and Retirement Longitudinal Study. Epidemiol Health. 2023 July 21;45:e2023066. \u003c/li\u003e\n\u003cli\u003eFrailty and Glaucoma Have Links, Potential Casual Relationship - Ophthalmology Advisor [Internet]. [cited 2025 Oct 2]. Available from: https://www.ophthalmologyadvisor.com/news/frailty-and-glaucoma-associated-and-patients-face-increased-health-disparities/\u003c/li\u003e\n\u003cli\u003eSato M, Yasuda M, Takahashi N, Hashimoto K, Himori N, Nakazawa T. Sex differences in the association between systemic oxidative stress status and optic nerve head blood flow in normal-tension glaucoma. PLOS ONE. 2023 Feb 24;18(2):e0282047. \u003c/li\u003e\n\u003cli\u003eBanik S, Ghosh A, Debi H. The Prevalence Trend of Glaucoma by Age and Sex Difference in South Asia: A Systematic Review and Meta‐Analysis of Population‐Based Studies. Health Sci Rep. 2025 Mar 18;8(3):e70542. \u003c/li\u003e\n\u003cli\u003eVajaranant TS, Nayak S, Wilensky JT, Joslin CE. Gender and glaucoma: what we know and what we need to know. Curr Opin Ophthalmol. 2010 Mar;21(2):91\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eBennion JR, Wise ME, Carver JA, Sorvillo F. Analysis of glaucoma-related mortality in the United States using death certificate data. J Glaucoma. 2008 Sept;17(6):474\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eRacial Disparities in Glaucoma: From Epidemiology to Pathophysiology - PMC [Internet]. [cited 2025 Oct 2]. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9312450/\u003c/li\u003e\n\u003cli\u003eRacial Differences in Corneal Thickness in Glaucomatous and Non-glaucomatous Populations | IOVS | ARVO Journals [Internet]. [cited 2025 Oct 2]. Available from: https://iovs.arvojournals.org/article.aspx?articleid=2418000\u003c/li\u003e\n\u003cli\u003eTHE AFRICAN DESCENT AND GLAUCOMA EVALUATION STUDY (ADAGES): PREDICTORS OF VISUAL FIELD DAMAGE IN GLAUCOMA SUSPECTS - PMC [Internet]. [cited 2025 Oct 2]. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4361282/\u003c/li\u003e\n\u003cli\u003eU.S. Latinos Have High Rates of Eye Disease and Visual Impairment | National Eye Institute [Internet]. [cited 2025 Oct 2]. Available from: https://www.nei.nih.gov/about/news-and-events/news/us-latinos-have-high-rates-eye-disease-and-visual-impairment\u003c/li\u003e\n\u003cli\u003eEhrlich JR, Ramke J, Macleod D, Burn H, Lee CN, Zhang JH, et al. Association between vision impairment and mortality: a systematic review and meta-analysis. Lancet Glob Health. 2021 Feb 16;9(4):e418\u0026ndash;30. \u003c/li\u003e\n\u003cli\u003eAl-Namaeh M. Common causes of visual impairment in the elderly. Med Hypothesis Discov Innov Ophthalmol. 2022 Feb 24;10(4):191\u0026ndash;200. \u003c/li\u003e\n\u003cli\u003eKilleen OJ, De Lott LB, Zhou Y, Hu M, Rein D, Reed N, et al. Population Prevalence of Vision Impairment in US Adults 71 Years and Older. JAMA Ophthalmol. 2023 Feb;141(2):197\u0026ndash;204. \u003c/li\u003e\n\u003cli\u003eSwaminathan SS, Medeiros FA. Socioeconomic Disparities in Glaucoma Severity at Initial Diagnosis: A Nationwide EHR Cohort Analysis. Am J Ophthalmol. 2024 July;263:50\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003eDavuluru SS, Jess AT, Kim JSB, Yoo K, Nguyen V, Xu BY. Identifying, Understanding, and Addressing Disparities in Glaucoma Care in the United States. Transl Vis Sci Technol. 2023 Oct 27;12(10):18. \u003c/li\u003e\n\u003cli\u003eRural Health Disparities Overview - Rural Health Information Hub [Internet]. [cited 2025 Oct 2]. Available from: https://www.ruralhealthinfo.org/topics/rural-health-disparities\u003c/li\u003e\n\u003cli\u003eYe L, Huang X, Xu Y. Global trends and disparities in burden of blindness and vision loss caused by non-communicable diseases from 1990 to 2021, and forecasts to 2045: a systematic analysis for the global burden of disease study 2021. Front Med [Internet]. 2025 June 19 [cited 2025 Oct 2];12. Available from: https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1561568/full\u003c/li\u003e\n\u003cli\u003eNew \u0026ldquo;Prevalence of glaucoma in the US in 2022\u0026rdquo; study finds higher prevalence of the eye disease than previously estimated | Institute for Health Metrics and Evaluation [Internet]. [cited 2025 Oct 2]. Available from: https://www.healthdata.org/news-events/newsroom/news-releases/new-prevalence-glaucoma-us-2022-study-finds-higher-prevalence\u003c/li\u003e\n\u003cli\u003eThe association between glaucoma and all-cause mortality in middle-aged and elderly Chinese people: results from the China Health and Retirement Longitudinal Study [Internet]. [cited 2025 Oct 2]. Available from: https://www.e-epih.org/journal/view.php?doi=10.4178%2Fepih.e2023066\u003c/li\u003e\n\u003cli\u003eQuaranta L, Galbussera AA, Tettamanti M, Novella A, Pasina L, Fortino I, et al. Relationships Among Glaucoma, Cardiovascular Diseases, and Mortality. Adv Ther. 2025 Sept;42(9):4403\u0026ndash;17. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Glaucoma, Mortality, Disparities, CDC WONDER, Population Health, Epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-7850550/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7850550/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlaucoma is a common optic neuropathy in older U.S. adults, yet its national temporal mortality trends have not been elucidated. This study examines glaucoma-related trends and disparities in mortality among older adults, promoting awareness of ophthalmic health inequities. Death certificates from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database were analyzed among adults aged ≥ 65 years with glaucoma-related deaths from 2000 to 2023. Crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) per 100,000 were calculated and stratified by demographics and geography. Trends in annual percent change (APC) and average APC were assessed using Jointpoint regression with 95% confidence intervals.\u003cstrong\u003e \u003c/strong\u003eA total of 21,805 glaucoma-related deaths occurred in older adults from 2000 to 2023. AAMRs declined initially from 2.98 in 2000 to 1.80 in 2009 (APC: -6.01; 95% CI: -10.46 to -4.53), followed by stable rates until 2023. Mortality rates were highest in adults aged ≥ 85 years, men, non-Hispanic (NH) Black/African Americans, residents of non-metropolitan areas, and Midwestern regions. Heart disease was the leading underlying cause of glaucoma-associated death, with COVID-19 playing a major role from 2000 to 2023.\u003cstrong\u003e \u003c/strong\u003eGlaucoma-related mortality in older adults rose with notable risks among adults aged ≥ 85 years, men, NH Black/African Americans, residents in non-metropolitan areas, and the Midwest. These findings call for targeted, informed public health interventions to ameliorate outcomes.\u003c/p\u003e","manuscriptTitle":"Evolution of Glaucoma-Related Mortality among Older Adults in the United States: Insights from CDC WONDER (2000–2023)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-12 08:42:20","doi":"10.21203/rs.3.rs-7850550/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"31daf749-6ac1-4097-93a8-387f3e585ed1","owner":[],"postedDate":"November 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57770202,"name":"Health sciences/Diseases"},{"id":57770203,"name":"Health sciences/Health care"},{"id":57770204,"name":"Health sciences/Medical research"},{"id":57770205,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-12-29T18:38:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-12 08:42:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7850550","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7850550","identity":"rs-7850550","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}