Acute Pancreatitis Mortality Trends in the United States, 1999-2020: An Analysis of the CDC WONDER Database

Acute Pancreatitis Mortality Trends in the United States, 1999-2020: An Analysis of the CDC WONDER Database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Acute Pancreatitis Mortality Trends in the United States, 1999-2020: An Analysis of the CDC WONDER Database Maha Sajjad, Hassan Ijaz, Sajjad Ul Hasan, Jibran Ikram, Muhammad Fateh Alam Bhatty, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6750378/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 Background: Acute pancreatitis (AP), a leading cause of U.S. gastrointestinal hospitalizations, involves pancreatic autodigestion. Prior studies, limited to inpatient data, overlooked disparities; this study analyzes nationwide AP-related mortality trends from 1999–2020 across demographic and regional subgroups. Methods: Mortality data were extracted from CDC-WONDER (ICD-10 code K85). Age-adjusted mortality rates (AAMR) and crude mortality rates (CMR) per 1,000,000 people were calculated. Trends were analyzed using Joinpoint regression to compute annual percent change (APC) and average APC (AAPC), stratified by gender, age, race, ethnicity, census region, state, and urbanization. Results: Among 128,051 deaths, AAMR declined from 21.85 in 1999 to 14.65 in 2018, but rose sharply to 18.04 in 2020, with an AAPC of -1.23 (95% CI, -2.21 to -0.25, p = 0.014). Males had a persistently higher AAMR (21.86) than females (13.77). Black individuals exhibited the highest AAMR (35.01 in 1999; 20.90 in 2020), surpassing White populations (20.32 to 18.23). The South had the highest regional mortality rate, while the Northeast had the lowest. Mortality declined in individuals aged 85 + with an APC of -3.61 (95% CI, -3.99 to -3.23, p < 0.001), but younger age groups (15–74 years) exhibited stable CMR from 1999 to 2018, followed by sharp increases during 2018–2020. Conclusion: AP-related mortality declined initially but surged from 2018–2020, particularly among younger populations. Persistent higher mortality rates in males, Black individuals, the younger population, and the Southern region underscore the need for targeted interventions addressing risk factors and healthcare access. Investigating drivers of recent mortality spikes is critical. acute pancreatitis mortality temporal trends United States CDC Wonder Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Acute pancreatitis (AP), characterized by the acute inflammation of the pancreas, has seen a rising global incidence and remains a leading cause of gastrointestinal-related hospital admissions in the United States​, accounting for approximately 275,000 hospital admissions each year and $ 2.5 billion in annual healthcare expenses 1 , 2 . Its pathophysiology involves premature activation of pancreatic enzymes, leading to autodigestion of the pancreas and surrounding tissues ​ 3 ​​. Etiologies include gallstones, alcohol use, hypertriglyceridemia, smoking, genetic mutations (e.g., PRSS1, SPINK1, CFTR) ​, and anatomical and obstructive abnormalities 4 , 5 ​. According to the revised Atlanta classification (2012), AP diagnosis requires ≥ 2 of the following criteria: (i) epigastric pain radiating to the back, (ii) serum lipase or amylase ≥ 3 times the upper limit of normal, (iii) imaging (CECT or MRI) showing pancreatic inflammation, necrosis, or fluid collections 6 . Severity is stratified as mild (no organ failure or complications), moderately severe (local complications with or without transient organ failure 48 hours involving ≥ 1 organ) 7 . Globally, 21% of AP patients develop recurrent episodes, and 36% progress to chronic pancreatitis ​ 8 . Post-pancreatitis diabetes, the most common complication, is linked to around 80% of AP cases 9 . Late complications like walled-off pancreatic necrosis (WOPN) significantly impair quality of life 10 . Organ failure, occurring in 20% of cases, remains the strongest predictor of mortality 11 . The global incidence of AP is 33.74 cases, and mortality is 1.60 deaths per 100,000 person-years 12 . AP hospitalization rates have risen in the US, yet mortality has declined due to advances in critical care and step-up approaches for necrosis management 13 – 15 . Prior US studies on AP mortality, limited by reliance on inpatient and hospital-based databases (e.g., National Inpatient Sample and HCUP) or regional data, lack generalizability and mask demographic and geographic disparities 3 , 13 , 14 . To address this gap, we analyzed nationwide AP-related mortality trends from 1999 to 2020, stratified by demographic (gender, age, race, ethnicity) and regional subgroups (census region, state, urbanization), to identify high-risk populations and inform targeted interventions. Methods Study design: Mortality data were extracted from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC-WONDER) Database ​ 16 , analyzing AP-related deaths among individuals aged 15 to 85 + years from 1999 to 2020 in the US using ICD-10 code K85. The Multiple Cause-of-Death data were examined to identify AP as an underlying or contributing cause of death on death certificates. Institutional review board approval was waived as the dataset is publicly available and de-identified. Data extraction: Demographic variables included gender, race, ethnicity, and age groups, and regional variables included census region, state, urbanization, and place of death. Race was classified as White, Black or African American, Asian or Pacific Islander, and American Indian or Alaska Native. Ethnicity was categorized as Hispanic or Latino and not Hispanic or Latino. Age groups were defined by ten-year intervals: 15–24 years, 25–34 years, 35–44 years, 45–54 years, 55–64 years, 65–74 years, 75–84 years, and 85 + years. Census regions were categorized into Northeast, Midwest, South, and West. According to the 2013 US census classification, the population was split into large metropolitan areas (population ≥ 1 million), medium/small metropolitan areas (population = 50,000 to 999,999), and micropolitan counties (population < 50,000) using the National Center for Health Statistics Urban-Rural Classification Scheme 17 . Place of death included medical facilities (inpatient, outpatient, or ER), home, nursing home or long-term care facility, hospice facility, and others. Statistical analysis: Crude mortality rate (CMR) per 1,000,000 people was calculated by dividing the number of AP-related deaths by the population of that specific year. CMR was used to analyze age groups. Age-adjusted mortality rate (AAMR) was determined by standardizing the AP-related deaths to the corresponding year 2000 US population ​ 18 ​. Using AAMRs, we investigated deaths categorized by gender, race, ethnicity, census region, state, and urbanization. The Joinpoint Regression Program (version 5.4.0.0; National Cancer Institute) 19 was used to calculate the Annual Percent Changes (APC) and Average Annual Percent Changes (AAPC) in AAMR, with 95% confidence intervals (95% CI), identifying trends via Monte Carlo Permutation Tests ​ 20 ​. Using a two-tailed t-test, APCs were categorized as ascending or descending based on whether the slope representing the change in mortality significantly differed from zero. A test of parallelism was conducted using pairwise analysis to establish whether the mortality trends within subgroups were parallel or non-parallel to each other. Mann-Whitney U, Kruskal-Wallis, and Cuzick tests were applied to find significant differences among subgroups of each demographic variable using STATA version 14.2. A p-value < 0.05 was deemed statistically significant. Results Overall Trend: From 1999 to 2020, 128,051 AP-related deaths occurred. AAMR decreased from 21.85 per million in 1999 to 14.65 in 2018, with an APC of -2.51 (95% CI, -2.83 to -2.19, p = 0.000), followed by a significant rise to 18.04 in 2020, with an APC of 11.84 (95% CI, 0.42 to 24.57, p = 0.042) [AAPC of -1.23 (95% CI, -2.21 to -0.25, p = 0.014)]. The sharpest increase was from 14.72 to 18.04 between 2019–2020. Using the Cuzick test, a z value of -4.02 (Prob > |z| = 0.000) was calculated across the overall population (Table 1 , 2 , Fig. 1 ). Table 1 Demographic Characteristics of Acute Pancreatitis-related Deaths in the US from 1999–2020. Variable Acute Pancreatitis Deaths (n) Age-Adjusted Mortality Rate (AAMR) per 1,000,000 Overall Population 128,051 (100%) 17.647 (17.55 to 17.74) Sex Male 71,361 (55.7%) 21.86 (21.698 to 22.023) Female 56,690 (44.3%) 13.766 (13.651 to 13.881) US Census Region Northeast 20,562 (16.05%) 14.665 (14.463 to 14.868) Midwest 29,062 (22.69%) 17.953 (17.745 to 18.161) South 51,648 (40.33%) 19.42 (19.251 to 19.589) West 26,779 (20.91%) 16.849 (16.646 to 17.053) Race American Indian or Alaska Native 1,264 (0.98%) 19.585 (18.426 to 20.744) Asian or Pacific Islander 2,934 (2.29%) 9.855 (9.489 to 10.222) Black or African American 17,447 (13.62%) 22.371 (22.031 to 22.711) White 106,406 (83.09%) 17.328 (17.223 to 17.433) Hispanic Origin Hispanic or Latino 9,721 (7.59%) 14.82 (14.505 to 15.135) Not Hispanic or Latino 118,024 (92.16%) 17.967 (17.863 to 18.07) Age Groups a 15–24 years 1,228 (0.96%) 1.312 (1.239 to 1.386) 25–34 years 4,556 (3.56%) 4.952 (4.808 to 5.095) 35–44 years 9,996 (7.80%) 10.734 (10.523 to 10.944) 45–54 years 17,505 (13.67%) 18.872 (18.592 to 19.151) 55–64 years 21,938 (17.13%) 28.624 (28.245 to 29.003) 65–74 years 24,085 (18.80%) 47.183 (46.587 to 47.779) 75–84 years 26,758 (20.90%) 89.64 (88.566 to 90.714) 85 + years 21,522 (16.80%) 180.079 (177.674 to 182.485) 2013 Urbanization Large Central Metro 33,333 (26.03%) 16.209 (16.034 to 16.384) Large Fringe Metro 26,426 (20.63%) 14.992 (14.809 to 15.174) Medium Metro 28,695 (22.40%) 18.859 (18.639 to 19.079) Small Metro 13,551 (10.58%) 19.539 (19.206 to 19.873) Micropolitan (Nonmetro) 14,515 (11.33%) 21.083 (20.735 to 21.431) NonCore (Nonmetro) 11,531 (9.00%) 21.72 (21.313 to 22.126) Place of Death b Medical Facility 99,232 (77.49%) - Decedent’s Home 14,852 (11.60%) - Hospice Facility 3,495 (2.73%) - Nursing Home / Long-Term Care 7,301 (5.70%) - Other 2,748 (2.15%) - a Crude mortality rate (CMR) is used for age-dependent analysis. b Age-adjusted mortality rate (AAMR) is not applicable to the Place of Death. Table 2 Annual Percentage Change (APC) and Average Annual Percentage Change (AAPC) values in Acute Pancreatitis Mortality Rates in the US from 1999 to 2020. Variable Trend Segment Year APC (95% CI) AAPC (95% CI) Overall Population 1 1999–2018 -2.5161* (-2.8323 to -2.1989) -1.2321* (-2.2068 to -0.2476) 2 2018–2020 11.8424* (0.4160 to 24.5690) Sex Male 1 1999–2018 -2.2878* (-2.5887 to -1.9861) -0.8731 (-1.7586 to 0.0203) 2 2018–2020 13.6311* (3.1166 to 25.2178) Female 1 1999–2018 -2.9251* (-3.3111 to -2.5375) -1.8567* (-3.1088 to -0.5884) 2 2018–2020 8.8983 (-5.3382 to 25.2759) US Census Region Northeast 1 1999–2018 -3.1925* (-35346 to -2.8491) -1.6894* (-2.8180 to -0.5477) 2 2018–2020 13.8066* (0.3240 to 29.1010) Midwest 1 1999–2018 -2.1829* (-2.5849 to -1.7793) -0.9275 (-2.1912 to 0.3525) 2 2018–2020 11.8321 (-2.7508 to 28.6016) South 1 1999–2001 4.8400 (-3.3295 to 13.6998) -1.2785 (-2.6782 to 0.1414) 2 2001–2004 -6.9577 (-14.0766 to 0.7510) 3 2004–2018 -2.3710* (-2.8023 to -1.9378) 4 2018–2020 9.8310* (1.2895 to 19.0928) West 1 1999–2018 -2.0323* (-2.4433 to -1.6195) -0.7691 (-1.9580 to 0.4342) 2 2018–2020 12.0738 (-1.6137 to 27.6656) Race Asian or Pacific Islander 1 1999–2020 -4.2700* (-5.0383 to -3.4954) -4.2700* (-5.0380 to -3.4954) Black or African American 1 1999–2017 -5.1159* (-5.7261 to -4.5018) -2.9723* (-4.3393 to -1.5858) 2 2017–2020 10.9453* (0.4215 to 22.5719) American Indian or Alaskan Native 1 1999–2011 -4.9396* (-8.0637 to -1.7093) -0.7926 (-3.1361 to 1.6075) 2 2011–2020 5.0193* (0.8764 to 9.3325) White 1 1999–2018 -2.0169* (-2.3348 to -1.6980) -0.8691 (-1.8539 to 0.1256) 2 2018–2020 10.7283 (-0.6609 to 23.4232) Hispanic Origin Hispanic or Latino 1 1999–2018 -3.6728* (-4.1763 to -3.1667) -2.2483* (-3.5752 to -0.9032) 2 2018–2020 12.3801 (-2.9079 to 30.0754) Not Hispanic or Latino 1 1999–2018 -2.3559* (-2.6742 to -2.0366) -1.0551* (-2.0547 to -0.0453) 2 2018–2020 12.2000* (0.4623 to 25.3092) Age Groups a 15–24 years 1 1999–2018 -2.0058* (-3.1615 to -0.8363) 1.7377 (-1.4649 to 5.0443) 2 2018–2020 45.2633* (3.0331 to 104.8025) 25–34 years 1 1999–2005 -4.7305 (-9.3726 to 0.1494) 2.0501 (-0.5032 to 4.6691) 2 2005–2018 1.3214 (-0.3835 to 3.0555) 3 2018–2020 31.4088* (5.0445 to 64.3900) 35–44 years 1 1999–2006 -4.7305* (-6.8990 to -2.5114) 0.6361 (-1.1174 to 2.4208) 2 2006–2018 -0.4562 (-1.7642 to 0.8691) 3 2018–2020 30.1645* (10.1079 to 53.8745) 45–54 years 1 1999–2018 -1.1432* (-1.6293 to -0.6546) 0.0623 (-1.4646 to 1.6128) 2 2018–2020 12.2728 (-5.0299 to 32.7279) 55–64 years 1 1999–2001 5.1439 (-4.6281 to 15.9171) 0.0443 (-1.5480 to 1.6625) 2 2001–2004 -7.9298 (-16.0825 to 1.0149) 3 2004–2018 -0.6327* (-1.0891 to -0.1743) 4 2018–2020 13.0724* (4.7154 to 22.0962) 65–74 years 1 1999–2001 3.9526 (-3.7702 to 12.2951) -1.5648* (-2.5870 to -0.5318) 2 2001–2007 -4.8963* (-6.5827 to -3.1795) 3 2007–2018 -2.4761* (-3.0841 to -1.8643) 4 2018–2020 8.7785* (1.2614 to 16.8535) 75–84 years 1 1999–2002 2.1545 (-2.7091 to 7.2612) -2.9251* (-3.6046 to -2.2408) 2 2002–2020 -3.7468* (-4.0757 to -3.4167) 85 + years 1 1999–2020 -3.6122* (-3.9930 to -3.2298) -3.6122* (-3.9930 to -3.2298) 2013 Urbanization Large Central Metro 1 1999–2018 -3.3637* (-3.7424 to -2.9835) -2.0377* (-3.2452 to -0.8152) 2 2018–2020 11.5026 (-2.5911 to 27.6354) Micropolitan (Nonmetro) 1 1999–2018 -1.5559* (-1.9978 to -1.1120) -0.5069 (-1.8936 to 0.8993) 2 2018–2020 10.0326 (-5.5562 to 28.1944) a Crude mortality rate (CMR) is used for age-dependent analysis. *Indicates that annual percentage change (APC) and average annual percent change (AAPC) values are significantly different from zero at the alpha = 0.05 level. Trends by Gender: Males had higher mortality than females. In males, AAMR dropped from 26.89 (1999) to 18.66 (2018) [APC: -2.29 (95% CI, -2.59 to -1.99, p = 0.000)], then rose to 23.57 (2020) [APC: 13.63 (95% CI, 3.12 to 25.22, p = 0.012)]. In females, AAMR dropped from 17.49 (1999) to 11.03 (2018) [APC: -2.92 (95% CI, -3.31 to -2.53, p = 0.000)], followed by an increase to 12.87 (2020) [APC: 8.90 (95% CI, -5.34 to 25.28, p = 0.214)]. Pairwise analysis revealed non-parallel trends. Mann-Whitney U test showed a significant difference between the mortality trends in both sexes (p |z| = 0.000) was calculated across genders (Table 1 , 2 , Fig. 2 ). Trends by Race: Blacks or African Americans had the highest AAMR from 1999–2012 and the second highest from 2013–2020 (American Indians or Alaska Natives had the highest during this period). AAMR for Blacks was 35.01 in 1999, declining until 2017 [APC: -5.11 (95% CI, -5.73 to -4.50, p = 0.000)], and then rose to 20.90 in 2020 [APC: 10.94 (95% CI, 0.42 to 22.57, p = 0.042)]. Whites exhibited a declining trend in AAMR from 20.32 (1999) to 14.85 (2018) [APC: -2.01 (95% CI, -2.33 to -1.69, p = 0.000)], followed by an increase to 18.23 (2020) [APC: 10.72 (95% CI, -0.66 to 23.42, p = 0.064)]. Pairwise analysis showed non-parallel trends between Whites and Blacks. AAMR for American Indians or Alaska Natives declined from 29.15 (1999) to 15.72 (2011) [APC: -4.94 (95% CI, -8.06 to -1.70, p = 0.005)], and then increased to 26.85 (2020) [APC: 5.02 (95% CI, 0.88 to 9.33, p = 0.019)]. A pairwise comparison of American Indians with Blacks and Asians showed non-parallel trends, however, the trends were parallel with Whites. The AAMR for Asians or Pacific Islanders showed a consistent trend in AAMR from 17.64 (1999) to 7.65 (2020) [APC: -4.27 (95% CI, -5.03 to -3.49, p = 0.000)] (Table 1 , 2 , Fig. 3 ). Trends by Ethnicity: The AAMR of Hispanics or Latinos declined from 21.12 (1999) to 10.97 (2018) [APC: -3.67 (95% CI, -4.17 to -3.16, p = 0.000)], and then increased to 14.48 (2020) [APC: 12.38 (95% CI, -2.90 to 30.07, p = 0.110)]. In Not Hispanics or Latinos, the AAMR dropped from 21.83 (1999) to 15.19 (2018) [APC: -2.35 (95% CI, -2.67 to -2.03, p = 0.000)]. It then increased to 18.67 (2020) [APC: 12.2 (95% CI, 0.46 to 25.30, p = 0.042)]. Pairwise analysis showed non-parallel trends between Hispanics and non-Hispanics. Applying the Mann-Whitney U test, we obtained a significant difference in mortality rates of Hispanics and non-Hispanics (p = 0.012). Using the Cuzick test, a z value of 2.51 (Prob > |z| = 0.012) was calculated across Hispanic origin (Table 1 , 2 , Supplementary Fig. 1). Trends by Age Groups: Individuals aged 85 + years exhibited a steady decline in CMR from 241.69 (1999) to 128.71 (2020) [AAPC: -3.61 (95% CI, -3.99 to -3.23, p = 0.000)]. Individuals aged 75–84 years showed an increase in CMR from 112.14 (1999) to 122.13 (2002) [APC: 2.15 (95% CI, -2.71 to 7.26, p = 0.369)], followed by a decline to 64.37 (2020) [APC: -3.74 (95% CI, -4.07 to -3.41, p = 0.000)]. All age groups between 15–74 years exhibited similar trends, with the CMR remaining relatively stable from 1999 to 2018, followed by a sharp increase during 2018–2020 [65–74 years: APC 8.77 (95% CI, 1.26 to 16.85, p = 0.025), 55–64 years: APC 13.07 (95% CI, 4.71 to 22.09, p = 0.004), 45–54 years: APC 12.27 (95% CI, -5.02 to 32.72, p = 0.162), 35–44 years: APC 30.16 (95% CI, 10.11 to 53.87, p = 0.004), 25–34 years: APC 31.40 (95% CI, 5.04 to 64.39, p = 0.020) and 15–24 years: APC 45.26 (95% CI, 3.03 to 104.80, p = 0.034)]. The Kruskal-Wallis test showed a significant difference among mortality rates in different age groups (p |z| = 0.000) was calculated across age groups (Table 1 , 2 , Fig. 4 ). Trends by Census Region and State: South displayed the highest AAMR throughout the study period, i.e., 24.94 in 1999 and 19.26 in 2020, followed by the Midwest, which showed an AAMR of 21.06 in 1999 and 18.86 in 2020. West was in third place with an AAMR of 19.82 in 1999 and 18.21 in 2020. Northeast showed the lowest AAMR of 19.38 in 1999 and 14.38 in 2020. The Kruskal-Wallis test revealed a significant difference between the mortality trends in different census regions (p |z| = 0.008) across census regions (Table 1 , 2 , Supplementary Fig. 2). States showed considerable differences in the AAMR. The states with the highest AAMR include South Carolina (AAMR = 25.90; 95% CI = 24.93 to 26.86), Kentucky (AAMR = 25.62; 95% CI = 24.62 to 26.61), Oklahoma (AAMR = 25.59; 95% CI = 24.52 to 26.66), West Virginia (AAMR = 25.50; 95% CI = 24.07 to 26.93) and Mississippi (AAMR = 24.44; 95% CI = 23.25 to 25.63). The AAMRs of these states were almost twice as compared to those at the lower end of the spectrum, i.e., New York (AAMR = 13.12; 95% CI = 12.79 to 13.45), Hawaii (AAMR = 13.32; 95% CI = 12.09 to 14.55), New Jersey (AAMR = 14.28; 95% CI = 13.77 to 14.79), Arizona (AAMR = 14.62; 95% CI = 13.99 to 15.24) and Massachusetts (AAMR = 14.66; 95% CI = 14.07 to 15.24). The state of California had the highest number of deaths (13,574) from 1999 to 2020 (Table 1 , 2 , Supplementary Fig. 3). Trends by Urbanization and Place of Death: Micropolitan (non-metro) areas displayed a higher AAMR (21.08) than large central metropolitan areas (16.21) across the study period. Micropolitan (non-metro) areas showed a decrease in AAMR from 1999–2018 [APC: -1.55 (95% CI, 1.99 to -1.11, p = 0.000)] and an increase from 2018–2020 [APC: 10.03 (95% CI, -5.56 to 28.19, p = 0.204)]. Large central metropolitan areas exhibited a decrease in AAMR from 1999–2018 [APC: -3.36 (95% CI, -3.74 to -2.98, p = 0.000], followed by an increase from 2018–2020 [APC: 11.50 (95% CI, -2.59 to 27.64, p = 0.107)]. Applying the Mann-Whitney U test, we found a significant difference between mortalities based on urbanization (p |z| = 0.000) was calculated across urbanization (Table 1 , 2 , Supplementary Fig. 4). Out of 127,628 deaths with the place of death known, 73.3% occurred in an inpatient medical facility, 3.98% occurred in outpatient and ER, 0.33% were dead on arrival, 11.63% occurred at the decedent’s home, 2.73% in hospice care and 5.72% in nursing or long-term care facilities (Table 1 , 2 ). Discussion In this nationwide study, we present several significant findings on AP-related mortality trends in the US from 1999 to 2020. First, AP-related mortality declined steadily from 1999–2018 but significantly increased between 2018–2020. While prior studies have reported overall AP-related mortality declines 3 , 13 , 14 , our study highlights a recent significant increase. Second, males consistently had higher AP-related mortality rates than females. Third, Blacks or African Americans showed the highest AAMR from 1999 to 2012 and the second highest AAMR from 2013 to 2020 (American Indians or Alaska Natives ranked highest then). Fourth, AP-related mortality was highest in the 85 + age group but steadily declined from 1999 to 2020. All 15-74-year age groups showed stable mortality from 1999 to 2018, but sharp increases during 2018–2020, particularly among younger age groups. The sudden increment in AAMR from 2018 to 2020 may stem from increasing obesity ​ 21 , 22 ​, diabetes ​ 23 ​, alcohol ​ 24 , and smoking ​ 24 risks. Abdominal obesity independently increases AP risk​ 25 ​. CDC data shows that the prevalence of obesity in the US rose from 30.5% in 1999–2000 to 41.9% in 2017–2020, especially among non-Hispanic Blacks. Obesity also raises gallstone risk, potentially triggering AP 21 , 26 . US gallstone prevalence doubled from 1988 to 2020 ​ 27 . A Swedish study from 1985 to 1999 found a positive correlation between gallstone-related AP incidence and overall gallstone rates​ 28 . Comorbid diabetes mellitus is linked to a 31% higher risk of AP-related death during hospitalization 23 . US diabetes prevalence rose from 0.82% in 1999–2002 to 1.14% in 2015–2020 ​ 29 ​. Furthermore, alcohol abuse sensitizes the pancreas to damage from genetic and environmental factors, thus increasing the risk of AP 30 . The US alcohol-induced mortality rate increased by 14.1% per year from 1999 to 2020 ​ 31 , possibly increasing the mortality rate of alcohol-induced AP. Smoking independently increases AP risk, especially among males, who exhibit higher smoking rates 32 – 34 . The AP-related mortality rate in the US decreased from 1999 to 2020, aligning with the global trends ​ 35 ​. Declines reflect improvements in the diagnosis and management of AP. Validated methods for predicting the severity of AP assess early physiological responses, including cardiopulmonary and renal function, laboratory studies indicating extrapancreatic organ injury (such as liver enzymes), and pancreatic imaging 32 . Early aggressive fluid resuscitation and early enteral feeding lower the risk of infectious complications and mortality ​ 36 ​. A "step-up approach" is currently advised for acute necrotizing pancreatitis, which involves endoscopic or percutaneous drainage of the peripancreatic fluid collection. Surgical drainage is usually considered if the step-up approach fails or expertise is lacking ​ 15 ​. Men consistently showed higher AP-related mortality, in congruence with prior studies ​ 3 , 14 , 23 . Higher male alcohol use contributes to AP risk ​ 30 . Greater smoking rates also increase male susceptibility ​ 33 , 34 . Men are also more prone to comorbid conditions such as heart, renal, and cerebrovascular diseases, which are useful in predicting mortality rates in AP ​ 37 . Men with AP with concomitant diabetes, obesity, and/or hypertension have worse outcomes and higher death rates than women ​ 27 ​. This may explain our study's lower mortality rate in females than males. However, female mortality recently rose, likely from gallstone susceptibility ​ 27 despite lower rates of alcohol consumption and smoking ​ 38 , 39 . Blacks or African Americans had the highest AAMR from 1999 to 2012 and the second highest AAMR from 2013 to 2020, with American Indians or Alaska Natives exhibiting the highest rate during this period. Previous studies have shown a 2 to 3-fold higher risk of AP in Blacks as compared to Whites ​ 38 , 39 ​. This high mortality rate among Blacks may be attributed to socioeconomic disparities, poverty, inadequate resources, and various lifestyle factors affecting this population ​ 35 ​. American Indians exhibited the highest mortality trend from 2011 to 2020, which could result from a higher incidence of diabetes, alcoholism, smoking, and socioeconomic factors ​ 40 ​. Asians or Pacific Islanders showed a consistent decline in AAMR, with the lowest mortality rate, possibly due to lower obesity and smoking ​rates 41 . Non-Hispanics had a persistently higher mortality rate than Hispanics, which aligns with prior literature ​ 13 ​. The mortality trend declined for the 85 + and 75–84 age groups, likely due to improved healthcare strategies, timely treatments, advanced surgical approaches, and smart management 42 ​. However, younger age groups (15–74 years) faced rising mortality between 2018 and 2020, possibly from delayed care and increasing substance use, which raises the chances of undiagnosed comorbidities ​ 37 . The Southern region consistently recorded the highest AAMR during the study period, potentially attributed to a greater burden of chronic diseases and socioeconomic barriers 43 – 45 . Significant regional differences in AAMR were noted at the state level, with the South and Appalachian states (i.e., South Carolina, Kentucky, Oklahoma, West Virginia, and Mississippi) exhibiting mortality rates double those of Northeastern states (i.e., New York, Hawaii, New Jersey, Arizona, and Massachusetts). A higher mortality rate in the South and Appalachian states may be due to increased comorbidities, such as cardiovascular diseases ​ 46 . Micropolitan (non-metro) areas reported higher mortality than large central metropolitan areas, emphasizing the lack of medical services in remote areas ​ 47 . A majority of AP-related deaths occurred in hospital settings, with 73.3% occurring in inpatient medical facilities and 3.98% in emergency or outpatient settings. Previous studies have also reported high in-hospital death rates related to AP ​ 48 . Limitations: Mortality data from the CDC WONDER database, derived from death certificates, may be subject to misclassification due to incomplete diagnoses or non-registration bias, as it excludes individuals without documented death certificates. The reliance on death certificates limits clinical details, potentially obscuring a comprehensive assessment of disease burden. Furthermore, focusing solely on AAMR may overlook key confounders, such as underlying comorbidities and socioeconomic factors. Geographic attribution also poses a challenge, as deaths are recorded based on residence rather than the location at the time of death. Conclusion AP-related mortality declined overall from 1999 to 2020, but surged from 2018 to 2020. The highest rates occurred in males, Blacks, the 85+ age group, and Southern residents. Rising mortality in the younger age groups in recent years warrants investigation. Additional research should address the underlying causes of these disparities and evaluate interventions to mitigate AP-related mortality. Declarations Ethical Declarations; This study was performed on deidentified data using a publicly available Dataset (CDC WONDER), therefore, it was exempted from needing an IRB approval. Funding Declaration; No Funding received. Author Contributions; M.S.; Study Conceptualization, Data analysis, Final Approval H.I.; Study Conceptualization, Data analysis S.H.; Manuscript writing J.I.; Manuscript writing M.B.; Data Collection and compiling I.Q.; Figures and tables A.I.; Manuscript writing L.M.; Drafting M.R.; Drafting M.Q.; critical appraisal M.S.; critical appraisal M.A.; Interpretation of data, Manuscript revision A.H.; Interpretation of data, Manuscript revision Data Availability The data used in this study is publicly availaible fron the CDC WONDER database;https://wonder.cdc.gov/mcd.html Conflict of Interest: None to declare References Lee PJ, Papachristou GIJNrG, hepatology. New insights into acute pancreatitis. 2019;16(8):479–496. Forsmark CE, Swaroop VS, Wilcox CMJNEJoM. Supplement to: Acute pancreatitis. 2016;375(20) Ingraham NE, King S, Proper J, et al. Morbidity and mortality trends of pancreatitis: an observational study. 2021;22(10):1021–1030. Lew D, Afghani E, Pandol SJDd, sciences. Chronic pancreatitis: current status and challenges for prevention and treatment. 2017;62:1702–1712. Mandalia A, Wamsteker E-J, DiMagno MJJF. Recent advances in understanding and managing acute pancreatitis. 2019;7:F1000 Faculty Rev-959. Banks PA, Bollen TL, Dervenis C, et al. Classification of acute pancreatitis—2012: revision of the Atlanta classification and definitions by international consensus. 2013;62(1):102–111. Gapp J, Tariq A, Chandra SJSP. Acute Pancreatitis. StatPearls. 2023;1:2023. Sankaran SJ, Xiao AY, Wu LM, Windsor JA, Forsmark CE, Petrov MSJG. Frequency of progression from acute to chronic pancreatitis and risk factors: a meta-analysis. 2015;149(6):1490–1500. e1. Petrov MS, Yadav DJNrG, hepatology. Global epidemiology and holistic prevention of pancreatitis. 2019;16(3):175–184. Boškoski I, Costamagna GJAogqpotHSoG. Walled-off pancreatic necrosis: where are we? 2014;27(2):93. Garg PK, Singh VPJG. Organ failure due to systemic injury in acute pancreatitis. 2019;156(7):2008–2023. Xiao AY, Tan ML, Wu LM, et al. Global incidence and mortality of pancreatic diseases: a systematic review, meta-analysis, and meta-regression of population-based cohort studies. 2016;1(1):45–55. Gapp J, Hall AG, Walters RW, Jahann D, Kassim T, Reddymasu SJP. Trends and outcomes of hospitalizations related to acute pancreatitis: epidemiology from 2001 to 2014 in the United States. 2019;48(4):548–554. Brindise E, Elkhatib I, Kuruvilla A, Silva RJP. Temporal trends in incidence and outcomes of acute pancreatitis in hospitalized patients in the United States from 2002 to 2013. 2019;48(2):169–175. Dudekula A, Munigala S, Zureikat AH, Yadav DJJoGS. Operative trends for pancreatic diseases in the USA: analysis of the nationwide inpatient sample from 1998–2011. 2016;20(4):803–811. Centers for Disease Control and Prevention NCfHS. National Vital Statistics System, Mortality 1999–2020 on CDC WONDER Online Database. Accessed June 10, 2024, http://wonder.cdc.gov/mcd-icd10.html Ingram DD, Franco SJJNCfHS. NCHS urban-rural classification scheme for counties. US Department of Health and Human Services, Centers for Disease Control and Prevention. 2014; Anderson RN, Rosenberg HM. Age standardization of death rates; implementation of the year 2000 standard. 1998; Institute NC. Joinpoint Regression Program (Version 5.4.0.0) [Computer software]. Bethesda, MD: National Cancer Institute; 2024. Kim HJ, Fay MP, Feuer EJ, Midthune DNJSim. Permutation tests for joinpoint regression with applications to cancer rates. 2000;19(3):335–351. Hong S, Qiwen B, Ying J, Wei A, Chaoyang TJEjog, hepatology. Body mass index and the risk and prognosis of acute pancreatitis: a meta-analysis. 2011;23(12):1136–1143. Martinez J, Johnson C, Sanchez-Paya J, De Madaria E, Robles-Díaz G, Pérez-Mateo MJP. Obesity is a definitive risk factor of severity and mortality in acute pancreatitis: an updated meta-analysis. 2006;6(3):206–209. Weissman S, Pandol SJ, Ghaffar U, et al. Impact of sex and comorbid diabetes on hospitalization outcomes in acute pancreatitis: A large United States population-based study. 2023;10(1):105. Yadav D, Whitcomb DCJNrG, hepatology. The role of alcohol and smoking in pancreatitis. 2010;7(3):131–145. Sadr-Azodi O, Orsini N, Andrén-Sandberg Å, Wolk AJOjotACoG, ACG. Abdominal and total adiposity and the risk of acute pancreatitis: a population-based prospective cohort study. 2013;108(1):133–139. Yadav D, Lowenfels ABJP. Trends in the epidemiology of the first attack of acute pancreatitis: a systematic review. 2006;33(4):323–330. Unalp-Arida A, Ruhl CEJH. Increasing gallstone disease prevalence and associations with gallbladder and biliary tract mortality in the US. 2023;77(6):1882–1895. Lindkvist B, Appelros S, Manjer J, Borgström AJCG, Hepatology. Trends in incidence of acute pancreatitis in a Swedish population: is there really an increase? 2004;2(9):831–837. Ouyang A, Hu K, Chen LJDr, practice c. Trends and risk factors of diabetes and prediabetes in US adolescents, 1999–2020. 2024;207:111022. Pandol SJ, Lugea A, Mareninova OA, et al. Investigating the pathobiology of alcoholic pancreatitis. 2011;35(5):830–837. Maleki N, Yunusa I, Karaye IMJIJoMH, Addiction. Alcohol-induced mortality in the USA: trends from 1999 to 2020. 2024;22(6):3805–3817. Hines OJ, Pandol SJJB. Management of severe acute pancreatitis. 2019;367 Sadr-Azodi O, Andrén-Sandberg Å, Orsini N, Wolk AJG. Cigarette smoking, smoking cessation and acute pancreatitis: a prospective population-based study. 2012;61(2):262–267. Lindkvist B, Appelros S, Manjer J, Berglund G, Borgström AJP. A prospective cohort study of smoking in acute pancreatitis. 2008;8(1):63–70. Li C-l, Jiang M, Pan C-q, Li J, Xu L-gJBg. The global, regional, and national burden of acute pancreatitis in 204 countries and territories, 1990–2019. 2021;21:1–12. Mederos MA, Reber HA, Girgis MDJJ. Acute pancreatitis: a review. 2021;325(4):382–390. Hidalgo NJ, Pando E, Mata R, et al. Impact of comorbidities on hospital mortality in patients with acute pancreatitis: a population-based study of 110,021 patients. 2023;23(1):81. Yadav D, Lowenfels ABJG. The epidemiology of pancreatitis and pancreatic cancer. 2013;144(6):1252–1261. Yang AL, Vadhavkar S, Singh G, Omary MBJAoim. Epidemiology of alcohol-related liver and pancreatic disease in the United States. 2008;168(6):649–656. Espey DK, Jim MA, Cobb N, et al. Leading causes of death and all-cause mortality in American Indians and Alaska Natives. 2014;104(S3):S303-S311. Gad MM, Găman M-A, Saad AM, et al. Temporal trends of incidence and mortality in Asian-Americans with pancreatic adenocarcinoma: an epidemiological study. 2020;33(2):210. Şahiner ES, Acehan F, Inan O, Aslan M, Altiparmak E, Ateş IJEGM. Characteristics and clinical outcomes of patients over 80 years of age with acute pancreatitis. 2022;13(4):1013–1022. Song S, Trisolini MG, LaBresh KA, Smith SC, Jin Y, Zheng Z-JJJno. Factors associated with county-level variation in premature mortality due to noncommunicable chronic disease in the United States, 1999–2017. 2020;3(2):e200241-e200241. Benavidez GA, Zahnd WE, Hung P, Eberth JMJPcd. Chronic disease prevalence in the US: sociodemographic and geographic variations by zip code tabulation area. 2024;21:E14. Hunyadi JV, Zhang K, Xiao Q, Strong LL, Bauer CJAJoPM. Spatial and Temporal Patterns of Chronic Disease Burden in the US, 2018–2021. 2025;68(1):107–115. Dwyer-Lindgren L, Bertozzi-Villa A, Stubbs RW, et al. US county-level trends in mortality rates for major causes of death, 1980–2014. 2016;316(22):2385–2401. Harrington RA, Califf RM, Balamurugan A, et al. Call to action: rural health: a presidential advisory from the American Heart Association and American Stroke Association. 2020;141(10):e615-e644. McNabb-Baltar J, Ravi P, Isabwe GA, et al. A population-based assessment of the burden of acute pancreatitis in the United States. 2014;43(5):687–691. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile.docx 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6750378","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":465624906,"identity":"964dddb5-ec41-4bb8-b4d0-b6dec5547529","order_by":0,"name":"Maha Sajjad","email":"","orcid":"","institution":"King Edward Medical University","correspondingAuthor":false,"prefix":"","firstName":"Maha","middleName":"","lastName":"Sajjad","suffix":""},{"id":465624908,"identity":"37c2cf43-637c-4ba2-9d4a-27898d49ce04","order_by":1,"name":"Hassan Ijaz","email":"","orcid":"","institution":"King Edward Medical 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Consortium","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Haq","suffix":""}],"badges":[],"createdAt":"2025-05-26 11:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6750378/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6750378/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83920334,"identity":"21c99ed1-d246-4298-a45a-3bbf327f8f25","added_by":"auto","created_at":"2025-06-04 13:36:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19521,"visible":true,"origin":"","legend":"\u003cp\u003eOverall acute pancreatitis-related age-adjusted mortality rates (AAMRs) per 1,000,000 in the United States, 1999 to 2020.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6750378/v1/a92b1bcbe8d475d530e64de4.png"},{"id":83921201,"identity":"999da756-1dc8-4dda-9f73-ff008bbf85e3","added_by":"auto","created_at":"2025-06-04 13:44:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23143,"visible":true,"origin":"","legend":"\u003cp\u003eSex-stratified acute pancreatitis-related age-adjusted mortality rates (AAMRs) per 1,000,000 in the United States, 1999 to 2020.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6750378/v1/3aed240134627985e1c1e278.png"},{"id":83921530,"identity":"82013ed0-474d-4265-a7ac-5256365ede5e","added_by":"auto","created_at":"2025-06-04 13:52:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48675,"visible":true,"origin":"","legend":"\u003cp\u003eAcute pancreatitis-related age-adjusted mortality rates (AAMRs) per 1,000,000 stratified by race in the United States, 1999 to 2020.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6750378/v1/5d694e13b1dabc9ef47c6263.png"},{"id":83921203,"identity":"7a22e7c7-1223-4130-9704-129300226652","added_by":"auto","created_at":"2025-06-04 13:44:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48930,"visible":true,"origin":"","legend":"\u003cp\u003eAcute pancreatitis-related crude mortality rates (AAMRs) per 1,000,000 stratified by age groups in the United States, 1999 to 2020.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6750378/v1/af01e94a816f254e49191dfc.png"},{"id":89451387,"identity":"5b4c4ccb-a8d3-4da2-8244-7df985eef861","added_by":"auto","created_at":"2025-08-20 06:16:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1187350,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6750378/v1/db7938bb-6f41-4e8f-ac97-270ec9c76e57.pdf"},{"id":83920339,"identity":"5de96cde-137b-4a1e-b9b7-b805e3fee7fe","added_by":"auto","created_at":"2025-06-04 13:36:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":197731,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-6750378/v1/ce26c8f1efb68d89e84caf47.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Acute Pancreatitis Mortality Trends in the United States, 1999-2020: An Analysis of the CDC WONDER Database","fulltext":[{"header":"Introduction","content":"\u003cp\u003e Acute pancreatitis (AP), characterized by the acute inflammation of the pancreas, has seen a rising global incidence and remains a leading cause of gastrointestinal-related hospital admissions in the United States​, accounting for approximately 275,000 hospital admissions each year and \u003cspan\u003e$\u003c/span\u003e2.5\u0026nbsp;billion in annual healthcare expenses \u003csup\u003e \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e \u003c/sup\u003e. Its pathophysiology involves premature activation of pancreatic enzymes, leading to autodigestion of the pancreas and surrounding tissues ​\u003csup\u003e \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e \u003c/sup\u003e​​. Etiologies include gallstones, alcohol use, hypertriglyceridemia, smoking, genetic mutations (e.g., PRSS1, SPINK1, CFTR) ​, and anatomical and obstructive abnormalities \u003csup\u003e \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e \u003c/sup\u003e​.\u003c/p\u003e \u003cp\u003eAccording to the revised Atlanta classification (2012), AP diagnosis requires\u0026thinsp;\u0026ge;\u0026thinsp;2 of the following criteria: (i) epigastric pain radiating to the back, (ii) serum lipase or amylase\u0026thinsp;\u0026ge;\u0026thinsp;3 times the upper limit of normal, (iii) imaging (CECT or MRI) showing pancreatic inflammation, necrosis, or fluid collections \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Severity is stratified as mild (no organ failure or complications), moderately severe (local complications with or without transient organ failure\u0026thinsp;\u0026lt;\u0026thinsp;48 hours), and severe (persistent organ failure\u0026thinsp;\u0026gt;\u0026thinsp;48 hours involving\u0026thinsp;\u0026ge;\u0026thinsp;1 organ) \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Globally, 21% of AP patients develop recurrent episodes, and 36% progress to chronic pancreatitis ​\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Post-pancreatitis diabetes, the most common complication, is linked to around 80% of AP cases \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Late complications like walled-off pancreatic necrosis (WOPN) significantly impair quality of life \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Organ failure, occurring in 20% of cases, remains the strongest predictor of mortality \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe global incidence of AP is 33.74 cases, and mortality is 1.60 deaths per 100,000 person-years \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. AP hospitalization rates have risen in the US, yet mortality has declined due to advances in critical care and step-up approaches for necrosis management \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Prior US studies on AP mortality, limited by reliance on inpatient and hospital-based databases (e.g., National Inpatient Sample and HCUP) or regional data, lack generalizability and mask demographic and geographic disparities \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. To address this gap, we analyzed nationwide AP-related mortality trends from 1999 to 2020, stratified by demographic (gender, age, race, ethnicity) and regional subgroups (census region, state, urbanization), to identify high-risk populations and inform targeted interventions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design:\u003c/h2\u003e \u003cp\u003eMortality data were extracted from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC-WONDER) Database ​\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, analyzing AP-related deaths among individuals aged 15 to 85\u0026thinsp;+\u0026thinsp;years from 1999 to 2020 in the US using ICD-10 code K85. The Multiple Cause-of-Death data were examined to identify AP as an underlying or contributing cause of death on death certificates. Institutional review board approval was waived as the dataset is publicly available and de-identified.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData extraction:\u003c/h3\u003e\n\u003cp\u003eDemographic variables included gender, race, ethnicity, and age groups, and regional variables included census region, state, urbanization, and place of death. Race was classified as White, Black or African American, Asian or Pacific Islander, and American Indian or Alaska Native. Ethnicity was categorized as Hispanic or Latino and not Hispanic or Latino. Age groups were defined by ten-year intervals: 15\u0026ndash;24 years, 25\u0026ndash;34 years, 35\u0026ndash;44 years, 45\u0026ndash;54 years, 55\u0026ndash;64 years, 65\u0026ndash;74 years, 75\u0026ndash;84 years, and 85\u0026thinsp;+\u0026thinsp;years. Census regions were categorized into Northeast, Midwest, South, and West. According to the 2013 US census classification, the population was split into large metropolitan areas (population\u0026thinsp;\u0026ge;\u0026thinsp;1\u0026nbsp;million), medium/small metropolitan areas (population\u0026thinsp;=\u0026thinsp;50,000 to 999,999), and micropolitan counties (population\u0026thinsp;\u0026lt;\u0026thinsp;50,000) using the National Center for Health Statistics Urban-Rural Classification Scheme \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Place of death included medical facilities (inpatient, outpatient, or ER), home, nursing home or long-term care facility, hospice facility, and others.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eCrude mortality rate (CMR) per 1,000,000 people was calculated by dividing the number of AP-related deaths by the population of that specific year. CMR was used to analyze age groups. Age-adjusted mortality rate (AAMR) was determined by standardizing the AP-related deaths to the corresponding year 2000 US population ​\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e​. Using AAMRs, we investigated deaths categorized by gender, race, ethnicity, census region, state, and urbanization. The Joinpoint Regression Program (version 5.4.0.0; National Cancer Institute) \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e was used to calculate the Annual Percent Changes (APC) and Average Annual Percent Changes (AAPC) in AAMR, with 95% confidence intervals (95% CI), identifying trends via Monte Carlo Permutation Tests ​\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e​. Using a two-tailed t-test, APCs were categorized as ascending or descending based on whether the slope representing the change in mortality significantly differed from zero. A test of parallelism was conducted using pairwise analysis to establish whether the mortality trends within subgroups were parallel or non-parallel to each other. Mann-Whitney U, Kruskal-Wallis, and Cuzick tests were applied to find significant differences among subgroups of each demographic variable using STATA version 14.2. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOverall Trend:\u003c/h2\u003e \u003cp\u003eFrom 1999 to 2020, 128,051 AP-related deaths occurred. AAMR decreased from 21.85 per million in 1999 to 14.65 in 2018, with an APC of -2.51 (95% CI, -2.83 to -2.19, p\u0026thinsp;=\u0026thinsp;0.000), followed by a significant rise to 18.04 in 2020, with an APC of 11.84 (95% CI, 0.42 to 24.57, p\u0026thinsp;=\u0026thinsp;0.042) [AAPC of -1.23 (95% CI, -2.21 to -0.25, p\u0026thinsp;=\u0026thinsp;0.014)]. The sharpest increase was from 14.72 to 18.04 between 2019\u0026ndash;2020. Using the Cuzick test, a z value of -4.02 (Prob \u0026gt; |z| = 0.000) was calculated across the overall population (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of Acute Pancreatitis-related Deaths in the US from 1999\u0026ndash;2020.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcute Pancreatitis Deaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge-Adjusted Mortality Rate (AAMR) per 1,000,000\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128,051 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.647 (17.55 to 17.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71,361 (55.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.86 (21.698 to 22.023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56,690 (44.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.766 (13.651 to 13.881)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUS Census Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,562 (16.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.665 (14.463 to 14.868)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29,062 (22.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.953 (17.745 to 18.161)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51,648 (40.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.42 (19.251 to 19.589)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,779 (20.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.849 (16.646 to 17.053)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,264 (0.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.585 (18.426 to 20.744)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,934 (2.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.855 (9.489 to 10.222)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,447 (13.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.371 (22.031 to 22.711)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106,406 (83.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.328 (17.223 to 17.433)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHispanic Origin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,721 (7.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.82 (14.505 to 15.135)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118,024 (92.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.967 (17.863 to 18.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge Groups\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,228 (0.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.312 (1.239 to 1.386)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,556 (3.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.952 (4.808 to 5.095)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,996 (7.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.734 (10.523 to 10.944)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,505 (13.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.872 (18.592 to 19.151)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026ndash;64 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21,938 (17.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.624 (28.245 to 29.003)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;74 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24,085 (18.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.183 (46.587 to 47.779)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u0026ndash;84 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,758 (20.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.64 (88.566 to 90.714)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e85\u003csup\u003e+\u003c/sup\u003e years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21,522 (16.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180.079 (177.674 to 182.485)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2013 Urbanization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge Central Metro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33,333 (26.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.209 (16.034 to 16.384)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge Fringe Metro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,426 (20.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.992 (14.809 to 15.174)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium Metro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28,695 (22.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.859 (18.639 to 19.079)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall Metro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,551 (10.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.539 (19.206 to 19.873)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicropolitan (Nonmetro)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,515 (11.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.083 (20.735 to 21.431)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNonCore (Nonmetro)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,531 (9.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.72 (21.313 to 22.126)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of Death\u003c/b\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99,232 (77.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecedent\u0026rsquo;s Home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,852 (11.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospice Facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,495 (2.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNursing Home / Long-Term Care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,301 (5.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,748 (2.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003ea\u003c/b\u003e Crude mortality rate (CMR) is used for age-dependent analysis.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eb\u003c/b\u003e Age-adjusted mortality rate (AAMR) is not applicable to the Place of Death.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual Percentage Change (APC) and Average Annual Percentage Change (AAPC) values in Acute Pancreatitis Mortality Rates in the US from 1999 to 2020.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrend Segment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAAPC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall Population\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.5161* (-2.8323 to -2.1989)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-1.2321* (-2.2068 to -0.2476)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8424* (0.4160 to 24.5690)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.2878* (-2.5887 to -1.9861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.8731 (-1.7586 to 0.0203)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.6311* (3.1166 to 25.2178)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.9251* (-3.3111 to -2.5375)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-1.8567* (-3.1088 to -0.5884)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.8983 (-5.3382 to 25.2759)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUS Census Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.1925* (-35346 to -2.8491)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-1.6894* (-2.8180 to -0.5477)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.8066* (0.3240 to 29.1010)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.1829* (-2.5849 to -1.7793)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.9275 (-2.1912 to 0.3525)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8321 (-2.7508 to 28.6016)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8400 (-3.3295 to 13.6998)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e-1.2785 (-2.6782 to 0.1414)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2001\u0026ndash;2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6.9577 (-14.0766 to 0.7510)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2004\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.3710* (-2.8023 to -1.9378)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.8310* (1.2895 to 19.0928)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.0323* (-2.4433 to -1.6195)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.7691 (-1.9580 to 0.4342)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.0738 (-1.6137 to 27.6656)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.2700* (-5.0383 to -3.4954)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.2700* (-5.0380 to -3.4954)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.1159* (-5.7261 to -4.5018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-2.9723* (-4.3393 to -1.5858)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2017\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.9453* (0.4215 to 22.5719)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmerican Indian or Alaskan Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.9396* (-8.0637 to -1.7093)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.7926 (-3.1361 to 1.6075)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2011\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0193* (0.8764 to 9.3325)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.0169* (-2.3348 to -1.6980)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.8691 (-1.8539 to 0.1256)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.7283 (-0.6609 to 23.4232)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHispanic Origin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.6728* (-4.1763 to -3.1667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-2.2483* (-3.5752 to -0.9032)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.3801 (-2.9079 to 30.0754)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.3559* (-2.6742 to -2.0366)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-1.0551* (-2.0547 to -0.0453)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.2000* (0.4623 to 25.3092)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge Groups\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.0058* (-3.1615 to -0.8363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.7377 (-1.4649 to 5.0443)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.2633* (3.0331 to 104.8025)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.7305 (-9.3726 to 0.1494)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.0501 (-0.5032 to 4.6691)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2005\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3214 (-0.3835 to 3.0555)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.4088* (5.0445 to 64.3900)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.7305* (-6.8990 to -2.5114)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.6361 (-1.1174 to 2.4208)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2006\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.4562 (-1.7642 to 0.8691)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.1645* (10.1079 to 53.8745)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.1432* (-1.6293 to -0.6546)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.0623 (-1.4646 to 1.6128)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.2728 (-5.0299 to 32.7279)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026ndash;64 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1439 (-4.6281 to 15.9171)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.0443 (-1.5480 to 1.6625)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2001\u0026ndash;2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7.9298 (-16.0825 to 1.0149)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2004\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.6327* (-1.0891 to -0.1743)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.0724* (4.7154 to 22.0962)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;74 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.9526 (-3.7702 to 12.2951)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e-1.5648* (-2.5870 to -0.5318)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2001\u0026ndash;2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.8963* (-6.5827 to -3.1795)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2007\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.4761* (-3.0841 to -1.8643)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.7785* (1.2614 to 16.8535)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u0026ndash;84 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1545 (-2.7091 to 7.2612)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-2.9251* (-3.6046 to -2.2408)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2002\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.7468* (-4.0757 to -3.4167)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e85\u003csup\u003e+\u003c/sup\u003e years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.6122* (-3.9930 to -3.2298)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.6122* (-3.9930 to -3.2298)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2013 Urbanization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge Central Metro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.3637* (-3.7424 to -2.9835)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-2.0377* (-3.2452 to -0.8152)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5026 (-2.5911 to 27.6354)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicropolitan (Nonmetro)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.5559* (-1.9978 to -1.1120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.5069 (-1.8936 to 0.8993)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.0326 (-5.5562 to 28.1944)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003ea\u003c/b\u003e Crude mortality rate (CMR) is used for age-dependent analysis.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Indicates that annual percentage change (APC) and average annual percent change (AAPC) values are significantly different from zero at the alpha\u0026thinsp;=\u0026thinsp;0.05 level.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTrends by Gender:\u003c/h2\u003e \u003cp\u003eMales had higher mortality than females. In males, AAMR dropped from 26.89 (1999) to 18.66 (2018) [APC: -2.29 (95% CI, -2.59 to -1.99, p\u0026thinsp;=\u0026thinsp;0.000)], then rose to 23.57 (2020) [APC: 13.63 (95% CI, 3.12 to 25.22, p\u0026thinsp;=\u0026thinsp;0.012)]. In females, AAMR dropped from 17.49 (1999) to 11.03 (2018) [APC: -2.92 (95% CI, -3.31 to -2.53, p\u0026thinsp;=\u0026thinsp;0.000)], followed by an increase to 12.87 (2020) [APC: 8.90 (95% CI, -5.34 to 25.28, p\u0026thinsp;=\u0026thinsp;0.214)]. Pairwise analysis revealed non-parallel trends. Mann-Whitney U test showed a significant difference between the mortality trends in both sexes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Using the Cuzick test, a z value of 5.59 (Prob \u0026gt; |z| = 0.000) was calculated across genders (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTrends by Race:\u003c/h3\u003e\n\u003cp\u003eBlacks or African Americans had the highest AAMR from 1999\u0026ndash;2012 and the second highest from 2013\u0026ndash;2020 (American Indians or Alaska Natives had the highest during this period). AAMR for Blacks was 35.01 in 1999, declining until 2017 [APC: -5.11 (95% CI, -5.73 to -4.50, p\u0026thinsp;=\u0026thinsp;0.000)], and then rose to 20.90 in 2020 [APC: 10.94 (95% CI, 0.42 to 22.57, p\u0026thinsp;=\u0026thinsp;0.042)]. Whites exhibited a declining trend in AAMR from 20.32 (1999) to 14.85 (2018) [APC: -2.01 (95% CI, -2.33 to -1.69, p\u0026thinsp;=\u0026thinsp;0.000)], followed by an increase to 18.23 (2020) [APC: 10.72 (95% CI, -0.66 to 23.42, p\u0026thinsp;=\u0026thinsp;0.064)]. Pairwise analysis showed non-parallel trends between Whites and Blacks. AAMR for American Indians or Alaska Natives declined from 29.15 (1999) to 15.72 (2011) [APC: -4.94 (95% CI, -8.06 to -1.70, p\u0026thinsp;=\u0026thinsp;0.005)], and then increased to 26.85 (2020) [APC: 5.02 (95% CI, 0.88 to 9.33, p\u0026thinsp;=\u0026thinsp;0.019)]. A pairwise comparison of American Indians with Blacks and Asians showed non-parallel trends, however, the trends were parallel with Whites. The AAMR for Asians or Pacific Islanders showed a consistent trend in AAMR from 17.64 (1999) to 7.65 (2020) [APC: -4.27 (95% CI, -5.03 to -3.49, p\u0026thinsp;=\u0026thinsp;0.000)] (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTrends by Ethnicity:\u003c/h3\u003e\n\u003cp\u003eThe AAMR of Hispanics or Latinos declined from 21.12 (1999) to 10.97 (2018) [APC: -3.67 (95% CI, -4.17 to -3.16, p\u0026thinsp;=\u0026thinsp;0.000)], and then increased to 14.48 (2020) [APC: 12.38 (95% CI, -2.90 to 30.07, p\u0026thinsp;=\u0026thinsp;0.110)]. In Not Hispanics or Latinos, the AAMR dropped from 21.83 (1999) to 15.19 (2018) [APC: -2.35 (95% CI, -2.67 to -2.03, p\u0026thinsp;=\u0026thinsp;0.000)]. It then increased to 18.67 (2020) [APC: 12.2 (95% CI, 0.46 to 25.30, p\u0026thinsp;=\u0026thinsp;0.042)]. Pairwise analysis showed non-parallel trends between Hispanics and non-Hispanics. Applying the Mann-Whitney U test, we obtained a significant difference in mortality rates of Hispanics and non-Hispanics (p\u0026thinsp;=\u0026thinsp;0.012). Using the Cuzick test, a z value of 2.51 (Prob \u0026gt; |z| = 0.012) was calculated across Hispanic origin (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTrends by Age Groups:\u003c/h2\u003e \u003cp\u003eIndividuals aged 85\u0026thinsp;+\u0026thinsp;years exhibited a steady decline in CMR from 241.69 (1999) to 128.71 (2020) [AAPC: -3.61 (95% CI, -3.99 to -3.23, p\u0026thinsp;=\u0026thinsp;0.000)]. Individuals aged 75\u0026ndash;84 years showed an increase in CMR from 112.14 (1999) to 122.13 (2002) [APC: 2.15 (95% CI, -2.71 to 7.26, p\u0026thinsp;=\u0026thinsp;0.369)], followed by a decline to 64.37 (2020) [APC: -3.74 (95% CI, -4.07 to -3.41, p\u0026thinsp;=\u0026thinsp;0.000)]. All age groups between 15\u0026ndash;74 years exhibited similar trends, with the CMR remaining relatively stable from 1999 to 2018, followed by a sharp increase during 2018\u0026ndash;2020 [65\u0026ndash;74 years: APC 8.77 (95% CI, 1.26 to 16.85, p\u0026thinsp;=\u0026thinsp;0.025), 55\u0026ndash;64 years: APC 13.07 (95% CI, 4.71 to 22.09, p\u0026thinsp;=\u0026thinsp;0.004), 45\u0026ndash;54 years: APC 12.27 (95% CI, -5.02 to 32.72, p\u0026thinsp;=\u0026thinsp;0.162), 35\u0026ndash;44 years: APC 30.16 (95% CI, 10.11 to 53.87, p\u0026thinsp;=\u0026thinsp;0.004), 25\u0026ndash;34 years: APC 31.40 (95% CI, 5.04 to 64.39, p\u0026thinsp;=\u0026thinsp;0.020) and 15\u0026ndash;24 years: APC 45.26 (95% CI, 3.03 to 104.80, p\u0026thinsp;=\u0026thinsp;0.034)]. The Kruskal-Wallis test showed a significant difference among mortality rates in different age groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Using the Cuzick test, a z value of 13.12 (Prob \u0026gt; |z| = 0.000) was calculated across age groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTrends by Census Region and State:\u003c/h2\u003e \u003cp\u003eSouth displayed the highest AAMR throughout the study period, i.e., 24.94 in 1999 and 19.26 in 2020, followed by the Midwest, which showed an AAMR of 21.06 in 1999 and 18.86 in 2020. West was in third place with an AAMR of 19.82 in 1999 and 18.21 in 2020. Northeast showed the lowest AAMR of 19.38 in 1999 and 14.38 in 2020. The Kruskal-Wallis test revealed a significant difference between the mortality trends in different census regions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The Cuzick test revealed a z value of 2.65 (Prob \u0026gt; |z| = 0.008) across census regions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eStates showed considerable differences in the AAMR. The states with the highest AAMR include South Carolina (AAMR\u0026thinsp;=\u0026thinsp;25.90; 95% CI\u0026thinsp;=\u0026thinsp;24.93 to 26.86), Kentucky (AAMR\u0026thinsp;=\u0026thinsp;25.62; 95% CI\u0026thinsp;=\u0026thinsp;24.62 to 26.61), Oklahoma (AAMR\u0026thinsp;=\u0026thinsp;25.59; 95% CI\u0026thinsp;=\u0026thinsp;24.52 to 26.66), West Virginia (AAMR\u0026thinsp;=\u0026thinsp;25.50; 95% CI\u0026thinsp;=\u0026thinsp;24.07 to 26.93) and Mississippi (AAMR\u0026thinsp;=\u0026thinsp;24.44; 95% CI\u0026thinsp;=\u0026thinsp;23.25 to 25.63). The AAMRs of these states were almost twice as compared to those at the lower end of the spectrum, i.e., New York (AAMR\u0026thinsp;=\u0026thinsp;13.12; 95% CI\u0026thinsp;=\u0026thinsp;12.79 to 13.45), Hawaii (AAMR\u0026thinsp;=\u0026thinsp;13.32; 95% CI\u0026thinsp;=\u0026thinsp;12.09 to 14.55), New Jersey (AAMR\u0026thinsp;=\u0026thinsp;14.28; 95% CI\u0026thinsp;=\u0026thinsp;13.77 to 14.79), Arizona (AAMR\u0026thinsp;=\u0026thinsp;14.62; 95% CI\u0026thinsp;=\u0026thinsp;13.99 to 15.24) and Massachusetts (AAMR\u0026thinsp;=\u0026thinsp;14.66; 95% CI\u0026thinsp;=\u0026thinsp;14.07 to 15.24). The state of California had the highest number of deaths (13,574) from 1999 to 2020 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTrends by Urbanization and Place of Death:\u003c/h2\u003e \u003cp\u003eMicropolitan (non-metro) areas displayed a higher AAMR (21.08) than large central metropolitan areas (16.21) across the study period. Micropolitan (non-metro) areas showed a decrease in AAMR from 1999\u0026ndash;2018 [APC: -1.55 (95% CI, 1.99 to -1.11, p\u0026thinsp;=\u0026thinsp;0.000)] and an increase from 2018\u0026ndash;2020 [APC: 10.03 (95% CI, -5.56 to 28.19, p\u0026thinsp;=\u0026thinsp;0.204)]. Large central metropolitan areas exhibited a decrease in AAMR from 1999\u0026ndash;2018 [APC: -3.36 (95% CI, -3.74 to -2.98, p\u0026thinsp;=\u0026thinsp;0.000], followed by an increase from 2018\u0026ndash;2020 [APC: 11.50 (95% CI, -2.59 to 27.64, p\u0026thinsp;=\u0026thinsp;0.107)]. Applying the Mann-Whitney U test, we found a significant difference between mortalities based on urbanization (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Using the Cuzick test, a z value of 6.32 (Prob \u0026gt; |z| = 0.000) was calculated across urbanization (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eOut of 127,628 deaths with the place of death known, 73.3% occurred in an inpatient medical facility, 3.98% occurred in outpatient and ER, 0.33% were dead on arrival, 11.63% occurred at the decedent\u0026rsquo;s home, 2.73% in hospice care and 5.72% in nursing or long-term care facilities (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this nationwide study, we present several significant findings on AP-related mortality trends in the US from 1999 to 2020. First, AP-related mortality declined steadily from 1999\u0026ndash;2018 but significantly increased between 2018\u0026ndash;2020. While prior studies have reported overall AP-related mortality declines \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, our study highlights a recent significant increase. Second, males consistently had higher AP-related mortality rates than females. Third, Blacks or African Americans showed the highest AAMR from 1999 to 2012 and the second highest AAMR from 2013 to 2020 (American Indians or Alaska Natives ranked highest then). Fourth, AP-related mortality was highest in the 85\u0026thinsp;+\u0026thinsp;age group but steadily declined from 1999 to 2020. All 15-74-year age groups showed stable mortality from 1999 to 2018, but sharp increases during 2018\u0026ndash;2020, particularly among younger age groups.\u003c/p\u003e \u003cp\u003eThe sudden increment in AAMR from 2018 to 2020 may stem from increasing obesity ​\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e​, diabetes ​\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e​, alcohol ​\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, and smoking ​\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e risks. Abdominal obesity independently increases AP risk​\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e​. CDC data shows that the prevalence of obesity in the US rose from 30.5% in 1999\u0026ndash;2000 to 41.9% in 2017\u0026ndash;2020, especially among non-Hispanic Blacks. Obesity also raises gallstone risk, potentially triggering AP \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. US gallstone prevalence doubled from 1988 to 2020 ​\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. A Swedish study from 1985 to 1999 found a positive correlation between gallstone-related AP incidence and overall gallstone rates​\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Comorbid diabetes mellitus is linked to a 31% higher risk of AP-related death during hospitalization \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. US diabetes prevalence rose from 0.82% in 1999\u0026ndash;2002 to 1.14% in 2015\u0026ndash;2020 ​\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e​. Furthermore, alcohol abuse sensitizes the pancreas to damage from genetic and environmental factors, thus increasing the risk of AP \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The US alcohol-induced mortality rate increased by 14.1% per year from 1999 to 2020 ​\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, possibly increasing the mortality rate of alcohol-induced AP. Smoking independently increases AP risk, especially among males, who exhibit higher smoking rates \u003csup\u003e\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe AP-related mortality rate in the US decreased from 1999 to 2020, aligning with the global trends ​\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e​. Declines reflect improvements in the diagnosis and management of AP. Validated methods for predicting the severity of AP assess early physiological responses, including cardiopulmonary and renal function, laboratory studies indicating extrapancreatic organ injury (such as liver enzymes), and pancreatic imaging \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Early aggressive fluid resuscitation and early enteral feeding lower the risk of infectious complications and mortality ​\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e​. A \"step-up approach\" is currently advised for acute necrotizing pancreatitis, which involves endoscopic or percutaneous drainage of the peripancreatic fluid collection. Surgical drainage is usually considered if the step-up approach fails or expertise is lacking ​\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e​.\u003c/p\u003e \u003cp\u003eMen consistently showed higher AP-related mortality, in congruence with prior studies ​\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Higher male alcohol use contributes to AP risk ​\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Greater smoking rates also increase male susceptibility ​\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Men are also more prone to comorbid conditions such as heart, renal, and cerebrovascular diseases, which are useful in predicting mortality rates in AP ​\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Men with AP with concomitant diabetes, obesity, and/or hypertension have worse outcomes and higher death rates than women ​\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e​. This may explain our study's lower mortality rate in females than males. However, female mortality recently rose, likely from gallstone susceptibility ​\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e despite lower rates of alcohol consumption and smoking ​\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBlacks or African Americans had the highest AAMR from 1999 to 2012 and the second highest AAMR from 2013 to 2020, with American Indians or Alaska Natives exhibiting the highest rate during this period. Previous studies have shown a 2 to 3-fold higher risk of AP in Blacks as compared to Whites ​\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e​. This high mortality rate among Blacks may be attributed to socioeconomic disparities, poverty, inadequate resources, and various lifestyle factors affecting this population ​\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e​. American Indians exhibited the highest mortality trend from 2011 to 2020, which could result from a higher incidence of diabetes, alcoholism, smoking, and socioeconomic factors ​\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e​. Asians or Pacific Islanders showed a consistent decline in AAMR, with the lowest mortality rate, possibly due to lower obesity and smoking ​rates \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Non-Hispanics had a persistently higher mortality rate than Hispanics, which aligns with prior literature ​\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e​.\u003c/p\u003e \u003cp\u003eThe mortality trend declined for the 85\u0026thinsp;+\u0026thinsp;and 75\u0026ndash;84 age groups, likely due to improved healthcare strategies, timely treatments, advanced surgical approaches, and smart management \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e​. However, younger age groups (15\u0026ndash;74 years) faced rising mortality between 2018 and 2020, possibly from delayed care and increasing substance use, which raises the chances of undiagnosed comorbidities ​\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Southern region consistently recorded the highest AAMR during the study period, potentially attributed to a greater burden of chronic diseases and socioeconomic barriers \u003csup\u003e\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Significant regional differences in AAMR were noted at the state level, with the South and Appalachian states (i.e., South Carolina, Kentucky, Oklahoma, West Virginia, and Mississippi) exhibiting mortality rates double those of Northeastern states (i.e., New York, Hawaii, New Jersey, Arizona, and Massachusetts). A higher mortality rate in the South and Appalachian states may be due to increased comorbidities, such as cardiovascular diseases ​\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMicropolitan (non-metro) areas reported higher mortality than large central metropolitan areas, emphasizing the lack of medical services in remote areas ​\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. A majority of AP-related deaths occurred in hospital settings, with 73.3% occurring in inpatient medical facilities and 3.98% in emergency or outpatient settings. Previous studies have also reported high in-hospital death rates related to AP ​\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations:\u003c/h2\u003e \u003cp\u003eMortality data from the CDC WONDER database, derived from death certificates, may be subject to misclassification due to incomplete diagnoses or non-registration bias, as it excludes individuals without documented death certificates. The reliance on death certificates limits clinical details, potentially obscuring a comprehensive assessment of disease burden. Furthermore, focusing solely on AAMR may overlook key confounders, such as underlying comorbidities and socioeconomic factors. Geographic attribution also poses a challenge, as deaths are recorded based on residence rather than the location at the time of death.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAP-related mortality declined overall from 1999 to 2020, but surged from 2018 to 2020. \u0026nbsp;The highest rates occurred in males, Blacks, the 85+ age group, and Southern residents. Rising mortality in the younger age groups in recent years warrants investigation. Additional research should address the underlying causes of these disparities and evaluate interventions to mitigate AP-related mortality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Declarations;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed on deidentified data using a publicly available Dataset (CDC WONDER), therefore, it was exempted from needing an IRB approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo Funding received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.S.; Study Conceptualization, Data analysis, Final Approval\u003c/p\u003e\n\u003cp\u003eH.I.; Study Conceptualization, Data analysis\u003c/p\u003e\n\u003cp\u003eS.H.; Manuscript writing\u003c/p\u003e\n\u003cp\u003eJ.I.; Manuscript writing\u003c/p\u003e\n\u003cp\u003eM.B.; Data Collection and compiling\u003c/p\u003e\n\u003cp\u003eI.Q.; Figures and tables\u003c/p\u003e\n\u003cp\u003eA.I.; Manuscript writing\u003c/p\u003e\n\u003cp\u003eL.M.; Drafting \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eM.R.; Drafting\u003c/p\u003e\n\u003cp\u003eM.Q.; critical appraisal\u003c/p\u003e\n\u003cp\u003eM.S.; critical appraisal\u003c/p\u003e\n\u003cp\u003eM.A.; Interpretation of data, Manuscript revision\u003c/p\u003e\n\u003cp\u003eA.H.; Interpretation of data, Manuscript revision\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data used in this study is publicly availaible fron the CDC WONDER database;https://wonder.cdc.gov/mcd.html\u003c/p\u003e\u003cp\u003eConflict of Interest: None to declare\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLee PJ, Papachristou GIJNrG, hepatology. 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A population-based assessment of the burden of acute pancreatitis in the United States. 2014;43(5):687\u0026ndash;691.\u003c/span\u003e\u003c/li\u003e\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":"acute pancreatitis, mortality, temporal trends, United States, CDC Wonder","lastPublishedDoi":"10.21203/rs.3.rs-6750378/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6750378/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcute pancreatitis (AP), a leading cause of U.S. gastrointestinal hospitalizations, involves pancreatic autodigestion. Prior studies, limited to inpatient data, overlooked disparities; this study analyzes nationwide AP-related mortality trends from 1999–2020 across demographic and regional subgroups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMortality data were extracted from CDC-WONDER (ICD-10 code K85). Age-adjusted mortality rates (AAMR) and crude mortality rates (CMR) per 1,000,000 people were calculated. Trends were analyzed using Joinpoint regression to compute annual percent change (APC) and average APC (AAPC), stratified by gender, age, race, ethnicity, census region, state, and urbanization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 128,051 deaths, AAMR declined from 21.85 in 1999 to 14.65 in 2018, but rose sharply to 18.04 in 2020, with an AAPC of -1.23 (95% CI, -2.21 to -0.25, p = 0.014). Males had a persistently higher AAMR (21.86) than females (13.77). Black individuals exhibited the highest AAMR (35.01 in 1999; 20.90 in 2020), surpassing White populations (20.32 to 18.23). The South had the highest regional mortality rate, while the Northeast had the lowest. Mortality declined in individuals aged 85 + with an APC of -3.61 (95% CI, -3.99 to -3.23, p \u0026lt; 0.001), but younger age groups (15–74 years) exhibited stable CMR from 1999 to 2018, followed by sharp increases during 2018–2020.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAP-related mortality declined initially but surged from 2018–2020, particularly among younger populations. Persistent higher mortality rates in males, Black individuals, the younger population, and the Southern region underscore the need for targeted interventions addressing risk factors and healthcare access. Investigating drivers of recent mortality spikes is critical.\u003c/p\u003e","manuscriptTitle":"Acute Pancreatitis Mortality Trends in the United States, 1999-2020: An Analysis of the CDC WONDER Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-04 13:36:01","doi":"10.21203/rs.3.rs-6750378/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":"204352d2-5b73-4c91-9ef3-5459cc471b8d","owner":[],"postedDate":"June 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-20T06:08:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-04 13:36:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6750378","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6750378","identity":"rs-6750378","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}