Burden and Disparities of Digestive Diseases in Sub-Saharan Africa

Burden and Disparities of Digestive Diseases in Sub-Saharan Africa | 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 Burden and Disparities of Digestive Diseases in Sub-Saharan Africa Omar Al Ta’ani, Yazan Al-Ajlouni, Mohammad Tanashat, Basile Njei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4401782/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 Introduction Digestive diseases (DD), such as cirrhosis, upper digestive diseases, inflammatory bowel disease, and pancreatitis, present a significant public health challenge in Sub-Saharan Africa (SSA). The prevalence and impact of these conditions vary widely, highlighting the challenges in managing DD within diverse health systems and sociocultural contexts. Despite their severe impact on morbidity and mortality, they have not garnered as much attention as diseases like HIV/AIDS or malaria. This study utilizes the Global Burden of Disease (GBD) dataset to provide a comprehensive epidemiological overview of DD in SSA, aiming to address gaps in current research and inform effective health policies and interventions. Methods Our study utilized data from the GBD dataset spanning 1990 to 2019, which offers extensive data on mortality, incidence, and disability-adjusted life years (DALYs) across 204 countries. We analyzed trends in the prevalence, deaths, and DALYs of DD, calculating percentage changes and estimated annual percentage changes (EAPCs) in age-standardized rates. Linear regression was employed to compute EAPCs, while Pearson correlation analyses were used to assess the relationships between EAPCs and socio-demographic indices. Results Our study documented a marked increase in total cases of digestive diseases from 1990 to 2019, with prevalence rising by 95.7% for males and 103.5% for females. However, age-standardized prevalence rates per 100,000 individuals declined by 6.9% for males and 7.2% for females. Age-standardized DALY rates for all digestive diseases decreased by 23.7%, and age-standardized death rates reduced by 20.6% for males and 22.1% for females. Specific conditions, such as cirrhosis, experienced significant declines in both DALY and death rates, with reductions of 25.9% and 30.7% for DALYs and 25.6% and 27.6% for death rates in males and females, respectively. The analysis revealed a significant correlation between the EAPCs of DALYs and the Universal Health Coverage (UHC) effective coverage index, with Pearson's r of -0.38 (p-value: 0.008). Conclusion Our study identified significant shifts in the prevalence of digestive diseases in Sub-Saharan Africa, with declines in conditions like cirrhosis and rises in inflammatory bowel disease, influenced by risk factors such as high BMI and drug use. These insights underscore the urgent need for tailored health policies and interventions that address both decreasing and newly emerging health challenges, enhancing public health strategies and ultimately improving health outcomes in the region. Digestive diseases Sub-saharan Africa Cirrhosis DALYs Healthcare Disparities Risk Factors Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Digestive diseases (DD), encompassing cirrhosis, upper digestive diseases, inflammatory bowel disease, and pancreatitis, among others, represent a significant and evolving public health challenge in Sub-Saharan Africa (SSA). The prevalence and impact of these conditions vary markedly across different regions. For example, while community-based studies report a cirrhosis prevalence of 2.8% in the Gambia, a figure that escalates to 17.3% among individuals with chronic HBV infection in Ethiopia, 1 the broader spectrum of DD similarly demonstrates substantial disparities. 2 These discrepancies emphasize the challenges of managing such diseases within diverse health systems and sociocultural contexts. Moreover, the global impact of hepatitis B and C suggests that targeted interventions could significantly mitigate the disease's burden. 3 The socioeconomic impacts, such as potentially underestimated mortality rates, emphasize the need for tailored educational, preventative, and diagnostic measures to effectively manage and reduce digestive diseases-related morbidity and mortality. 4 Further research elucidates the critical nature of DD as a public health issue in SSA, associated with significant morbidity and mortality. 5–8 The global impact of risk factors such as viral hepatitis, alcohol consumption, unhealthy diets, and limited healthcare access suggests that targeted interventions could significantly mitigate the burden of these diseases. 9, 10 The World Health Organization (WHO) has identified SSA as the region with the highest prevalence, morbidity and mortality from cirrhosis. 11 Between 1980 and 2010, cirrhosis-related deaths doubled in SSA. 12 Moreover, SSA is experiencing a rapid epidemiological transition, characterized by a shift from communicable diseases to an increasing predominance of chronic, non-communicable diseases (NCDs). The region is expected to see one of the largest increases in mortality due to NCDs globally, NCD risk factor surveillance indicates that most adults in SSA are exposed to at least one risk factor for NCDs, including harmful alcohol use, unhealthy diets, and obesity, which are significant contributors to gastric diseases. Despite the severity of these health issues, gastric diseases have not received the same level of attention as other prevalent diseases like HIV/AIDS or malaria. This oversight has led to critical gaps in health policy and resource allocation. Moreover, the lack of comprehensive surveillance and systematic data collection further hampers effective response and intervention strategies. 13 The existing research, often limited by narrow regional focuses and confined to hospital-based studies or specific communities, may not accurately reflect broader regional realities. 1 These studies often face methodological limitations, such as small sample sizes and retrospective designs that fail to capture the full spectrum of health outcomes related to gastric diseases. Consequently, there is a pressing need for a more detailed, systematically collected, and up-to-date dataset that can provide a clearer picture of the burden of gastric diseases across diverse settings within the region. The Global Burden of Disease (GBD) dataset presents a unique and robust tool that has not yet been fully utilized to quantify the burden of DD in SSA, where detailed health data are often scarce. 14 Consequently, the primary aim of this study is to leverage the comprehensive capabilities of the GBD dataset to fill the critical gaps identified in the existing literature. By doing so, we aim to provide a more precise and comprehensive epidemiological overview of digestive diseases in SSA. This approach will enhance our understanding of the prevalence and distribution of DD, facilitate the analysis of key risk factors, and assess the potential impacts of targeted health interventions over the past decades. The insights gained from this study are expected to inform effective and sustainable health policies, offering valuable guidance for healthcare providers, policymakers, and other stakeholders in the region. Methods Data source The study utilized the GBD dataset, an expansive collaborative research project designed to quantify health challenges. This dataset provides detailed estimates of mortality, incidence, prevalence, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) associated with 369 diseases and injuries as well as 87 unique risk factors for both genders in 204 countries and territories. The records extend from 1990 to 2019 and are updated on an annual basis. 15 For the assessment of disease burden, the GBD study integrates data from diverse sources, including vital statistics registries, demographic surveys, health facilities, and death certificates. The study that developed this extensive database was carried out by the Institute for Health Metrics and Evaluation, with financial support from several entities, among them the World Bank, the National Institutes of Health, and the Bill & Melinda Gates Foundation. Measures This GBD study utilizes three key measures of disease burden: prevalence, deaths, and DALYs. Prevalence refers to the total number of cases of a disease that exist in a population at a specific point in time. Deaths represent the number of mortalities attributable to a particular disease or condition. DALYs combine the impacts of premature death and disability on an individual’s quality of life and are calculated by summing the years of life lost due to premature death and the years of healthy life lost due to disability. One DALY equates to the loss of one year of full health. Using DALYs allows for comparisons between diseases that may cause premature death but little disability and those that do not lead to death but cause significant disability, thereby providing a more comprehensive view of the overall disease burden on a population. The digestive diseases included in the GBD 2019 encompassed cirrhosis and other chronic liver diseases (from causes such as hepatitis B, hepatitis C, alcohol-related liver disease, non-alcoholic steatohepatitis, and other causes); upper digestive system diseases (including peptic ulcer disease, gastritis and duodenitis, and gastroesophageal reflux disease); appendicitis; paralytic ileus and intestinal obstruction; inguinal, femoral, and abdominal hernia; inflammatory bowel disease; vascular intestinal disorders; gallbladder and biliary diseases; pancreatitis; and other digestive diseases (an aggregate of other conditions of the digestive system). For consistency in measurement, case definitions largely conformed to the 10th revision of the International Classification of Diseases (ICD-10), as detailed in Supplemental Table 1. Sub-Saharan Africa Region According to the classification provided by the Global Burden of Disease study, Sub-Saharan Africa is divided into four regions. Central Sub-Saharan Africa includes Angola, the Central African Republic, Republic of Congo, Democratic Republic of the Congo, Equatorial Guinea, and Gabon. Eastern Sub-Saharan Africa encompasses Burundi, Comoros, Djibouti, Eritrea, Ethiopia, Kenya, Madagascar, Malawi, Mozambique, Rwanda, Somalia, South Sudan, Uganda, the United Republic of Tanzania, and Zambia. The Southern region comprises Botswana, Eswatini, Lesotho, Namibia, South Africa, and Zimbabwe. Lastly, the Western region consists of Benin, Burkina Faso, Cabo Verde, Cameroon, Chad, Côte d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Sao Tome and Principe, Senegal, Sierra Leone, and Togo. Risk Factors Our analysis centered on the age-standardized DALYs attributable to specific risk factors for digestive diseases, as identified by the GBD study. 16 These risk factors comprised alcohol consumption, tobacco smoking, high body mass index (BMI), and drug use. We explored the temporal trends of these risk factors to evaluate their changing impact on health outcomes over time. SDI The Socio-Demographic Index (SDI) serves as an indicator of a country's developmental status, with a demonstrable correlation to healthcare outcomes. It is scaled from 0 to 1 and is derived from three components: the total fertility rate among women under 25 years of age, the average years of education for individuals aged 15 and older, and the lag-distributed income per capita. 15 UHC Universal Health Coverage (UHC) effective coverage index The Universal Health Coverage (UHC) effective coverage index quantitatively assesses the extent of a population's access to essential health services, with a scale ranging from 0 (no coverage) to 100 (full coverage by high-quality health services). This index evaluates service provision across five categories—promotion, prevention, treatment, rehabilitation, and palliation—categorized further for various age groups from newborns to older adults. 17, 18 Statistical analysis The GBD study aggregates data from a variety of sources and the data is meticulously processed and adjusted for covariates. Standardized modeling tools such as the Cause of Death Ensemble model (CODEm), spatiotemporal Gaussian process regression (ST-GPR), and DisMod-MR are employed to ensure accurate representation of health data. The GBD Compare website facilitates the downloading and interactive visualization of these results. To handle missing data, the GBD study team employs multiple imputation techniques for data considered missing at random, and inverse probability weighting or similar methods for data not missing at random. This rigorous approach helps maintain the quality and consistency of the data, with thorough documentation of the methods used to ensure transparency in data handling. Data on prevalence, deaths, and DALYs for digestive diseases, along with their 95% uncertainty intervals (UIs), were obtained from the GBD study. Both raw numbers and age-standardized rates per 100,000 people were obtained for these measures. We analyzed the distribution of prevalence, DALYS, and deaths by cause, location, and year, and calculated the percentage changes between 1990 and 2019 using the formula: $$Percent change=\frac{measures in 2019-measures in 1990}{measures in 1990}x 100\%$$ Additionally, we evaluated the Estimated Annual Percentage Changes (EAPCs) in age standardized DALYs by fitting a regression line to the natural logarithm of the rates over time, expressed as y = α + βx + ε, where y is the natural log of the rate, and x is the calendar year. The EAPC is calculated as 100×(exp(β) − 1). Pearson correlation analyses were conducted to investigate the relationships between the EAPCs in ASDR with both the Socio-demographic Index (SDI) and the UHC effective coverage index for 2019. All statistical analyses and graphical representations were performed using R version 4.3.3, with a significance level set at a p-value of less than 0.05. Results Trends in prevalence From 1990 to 2019, the total number of cases for all digestive diseases increased significantly as shown in Table 1 . For males, the raw prevalence count rose from approximately 66,462,980 (62,493,145 − 70,508,314) to 130,060,299 (122,479,265 − 137,392,648), showing a 95.7% increase. For females, the count escalated from about 58,327,017 (54,815,114 − 61,990,604) to 118,687,212 (111,282,639 − 125,905,960), reflecting a 103.5% increase. Despite these increases in raw prevalence, the age-standardized prevalence rate per 100,000 individuals for these diseases decreased for both genders; males saw a reduction from 35,492.6 (33,744.9–37,211.4) to 33,046 (31,408.2–34,636.2) reflecting a -6.9% change, and females from 30,944.2 (29,264.5–32,605.2) to 28,710.3 (27,171.3–30,346.4), a -7.2% change. Table 1 Comparative Analysis of Raw prevalence count and Age-Standardized Prevalence Rates by Cause Between 1990 and 2019 Diseases Gender Raw Prevalence count in 1990 Raw Prevalence count in 2019 Percentage Change Age-standardized Prevalence Rate per 100,000 individuals in 1990 Age-standardized Prevalence Rate per 100,000 individuals in 2019 Percentage Change Digestive diseases Male 66462980 (62493145–70508314) 130060299 (122479265–137392648) 95.7% 35492.6 (33744.9–37211.4) 33046 (31408.2–34636.2) -6.9% Female 58327017 (54815114–61990604) 118687212 (111282639–125905960) 103.5% 30944.2 (29264.5–32605.2) 28710.3 (27171.3–30346.4) -7.2% Both 124789997 (117287349–132625322) 248747511 (233819408–263441009) 99.3% 33186.6 (31471–34859.3) 30799.6 (29254.1–32405) -7.2% Cirrhosis and other chronic liver diseases Male 59153833 (54721751–63853325) 111237049 (102704642–120128711) 88.0% 31501.2 (29310–33858.5) 28515.2 (26564.7–30662.9) -9.5% Female 47246412 (43599642–51350843) 90720228 (83291585–98305656) 92.0% 24662.3 (22818.2–26596.9) 22048.4 (20327.2–23821.9) -10.6% Both 106400245 (98347910–115137528) 201957277 (185642055–218897497) 89.8% 28029.7 (26021.1–30128.6) 25151.6 (23357.5–27100.6) -10.3% Upper digestive system diseases Male 16908371 (14697155–19009360) 38694457 (33668313–43433067) 128.8% 10741.5 (9484.3–11984.7) 10779.3 (9531.3–12013.1) 0.4% Female 18580942 (16227709–20850367) 44478693 (38897220–49912550) 139.4% 11433.3 (10120.1–12713.2) 11501.7 (10217.9–12768.2) 0.6% Both 35489312 (30898246–39702407) 83173150 (72429981–93104973) 134.4% 11095.6 (9838.1–12340.2) 11158.5 (9909.3–12402.3) 0.6% Peptic ulcer disease Male 208041 (174753–245487) 405087 (339460–484246) 94.7% 124.8 (106.9–146.1) 106.9 (91.9–125.2) -14.3% Female 225506 (187635–268700) 509009 (420734–611005) 125.7% 124.1 (105.9–144.1) 122.2 (103.6–142.7) -1.5% Both 433547 (363910–512370) 914097 (760724–1086367) 110.8% 125.2 (107.5–145.5) 115.2 (98.9–134.2) -8.0% Gastritis and duodenitis Male 900240 (742729–1092157) 2242010 (1839827–2735914) 149.0% 550 (448.1–670.2) 625.4 (508.1–766) 13.7% Female 886918 (725156–1077859) 2289168 (1855546–2791811) 158.1% 572.7 (468.2–692.9) 658.6 (534.2–800.6) 15.0% Both 1787158 (1475370–2155987) 4531178 (3705560–5505999) 153.5% 563.2 (460.2–684.3) 645.4 (526.2–784.1) 14.6% Gastroesophageal reflux disease Male 16907111 (14447788–19279463) 38544124 (32868460–43948861) 128.0% 10822.7 (9407.5–12275.1) 10810.1 (9400.5–12258.5) -0.1% Female 18727174 (16092624–21251693) 44707764 (38398765–50882942) 138.7% 11586.6 (10122.4–13021) 11588.5 (10128.6–13029.7) 0.0% Both 35634285 (30584669–40327777) 83251888 (71370051–94360134) 133.6% 11211.4 (9768.4–12598.4) 11216.4 (9767.8–12591.5) 0.0% Appendicitis Male 9791 (7366–12830) 31325 (23425–41525) 219.9% 3.7 (2.9–4.9) 5.3 (4.1–6.9) 43.2% Female 11218 (8313–14852) 35095 (25743–47297) 212.8% 4.1 (3.2–5.4) 5.7 (4.4–7.6) 39.0% Both 21009 (15710–27719) 66420 (49074–88488) 216.2% 3.9 (3–5.1) 5.5 (4.2–7.2) 41.0% Paralytic ileus and intestinal obstruction Male 19745 (18409–21057) 44403 (41509–47061) 124.9% 6.9 (6.6–7.2) 8.4 (8–8.7) 21.7% Female 16834 (15559–18111) 37904 (35346–40466) 125.2% 5.3 (5–5.6) 6.4 (6.1–6.7) 20.8% Both 36579 (33976–39129) 82307 (76873–87475) 125.0% 6.1 (5.8–6.4) 7.3 (7–7.7) 19.7% Inguinal, femoral, and abdominal hernia Male 1782031 (1492320–2124544) 3883462 (3304836–4608609) 117.9% 908.1 (782.2–1042.8) 982.9 (848.4–1127.3) 8.2% Female 392574 (302833–496992) 839614 (658903–1041656) 113.9% 164.9 (135.5–198.1) 164.8 (136.3–196.1) -0.1% Both 2174605 (1808347–2609627) 4723076 (3972468–5616761) 117.2% 534 (459.6–615.2) 557.5 (478.2–642.7) 4.4% Inflammatory bowel disease Male 10976 (9030–13425) 28048 (23015–34315) 155.5% 7.5 (6.2–9.2) 8.5 (7.1–10.5) 13.3% Female 12854 (10596–15509) 34903 (28726–42214) 171.5% 8.4 (7–10.1) 9.5 (7.9–11.5) 13.1% Both 23830 (19646–28849) 62951 (51710–76247) 164.2% 7.9 (6.6–9.6) 9 (7.5–11) 13.9% Vascular intestinal disorders Male 2090 (1568–2808) 5041 (3845–6649) 141.2% 1 (0.8–1.2) 1.2 (1–1.5) 20.0% Female 1245 (956–1668) 3385 (2649–4465) 171.9% 0.6 (0.5–0.8) 0.8 (0.7–1) 33.3% Both 3335 (2532–4436) 8425 (6508–11135) 152.6% 0.8 (0.7–1) 1 (0.8–1.2) 25.0% Gallbladder and biliary diseases Male 414266 (341700–503137) 866630 (716551–1051831) 109.2% 240.7 (203.7–285.4) 225.4 (193.1–270.4) -6.4% Female 1001637 (839993–1180407) 2005036 (1686092–2398035) 100.2% 577.3 (494.2–681.2) 496.8 (427.1–587.3) -13.9% Both 1415903 (1180582–1664140) 2871665 (2404941–3424194) 102.8% 411.8 (352.1–486.3) 367.3 (316.2–434.9) -10.8% Pancreatitis Male 30567 (27561–33676) 79735 (72216–87457) 160.9% 20.7 (18.8–22.7) 24.6 (22.3–26.8) 18.8% Female 18619 (16435–21078) 48783 (42957–55134) 162.0% 12.7 (11.3–14.3) 14.6 (12.9–16.4) 15.0% Both 49186 (44130–54860) 128518 (115569–142469) 161.3% 16.7 (15–18.4) 19.4 (17.4–21.4) 16.2% For cirrhosis and other chronic liver diseases specifically, the age-standardized rate per 100,000 individuals saw a decline for both genders. Males experienced a decrease from 31,501.2 (29,310 − 33,858.5) to 28,515.2 (26,564.7–30,662.9), a -9.5% change. Females saw a larger reduction from 24,662.3 (22,818.2–26,596.9) to 22,048.4 (20,327.2–23,821.9), a -10.6% change. As shown in Fig. 1 , the top three causes of age-standardized prevalence rates for cirrhosis and other chronic liver diseases were MASLD, hepatitis C, and hepatitis B. During the period from 1990 to 2019, MASLD saw an increase in prevalence. In contrast, both hepatitis B and hepatitis C experienced decreases in their age-standardized prevalence rates. Meanwhile, the prevalence of alcohol-related liver disease and other chronic liver diseases remained relatively stable. Upper digestive system diseases, which include conditions like peptic ulcer disease and gastritis and duodenitis, also saw significant changes. The total prevalence more than doubled for both genders, with minor adjustments in age-standardized rates. For males, the rate slightly increased from 10,741.5 (9,484.3–11,984.7) to 10,779.3 (9,531.3–12,013.1), a 0.4% change, and for females, it went from 11,433.3 (10,120.1–12,713.2) to 11,501.7 (10,217.9–12,768.2), a 0.6% change. Lastly, other conditions such as appendicitis, paralytic ileus, and various types of hernias also saw increases in age-standardized rates. Specifically, appendicitis rates increased by 43.2% for males and 39.0% for females, paralytic ileus by 21.7% for males and 20.8% for females, and hernias by 8.2% for males and a slight decrease of -0.1% for females. Trends in DALYs From 1990 to 2019, the total number of disability-adjusted life years (DALYs) for all digestive diseases increased significantly from approximately 8,127,236 (7,087,624–9,210,919) to 13,278,484 (11,044,907–15,915,542), showing a 63.4% increase. However, the age-standardized DALY rate per 100,000 individuals for these diseases decreased from 2,524.8 (2,225.2–2,869.4) to 1,925.6 (1,639.9–2,252.9), reflecting a -23.7% change as shown in Table 2 . Table 2 Comparative Analysis of Raw DALY count and Age-Standardized DALY Rates by Cause Between 1990 and 2019 Diseases Gender Raw DALY count in 1990 Raw DALY count in 2019 Percentage Change Age-standardized DALY Rate per 100,000 individuals in 1990 Age-standardized DALYs Rate per 100,000 individuals in 2019 Percentage Change Digestive diseases Male 5216032 (4508051–6013101) 8647797 (7156940–10461767) 65.8% 3334.4 (2876.8–3950.9) 2617.8 (2208.2–3111.5) -21.5% Female 2911203 (2396479–3413357) 4630687 (3812822–5569544) 59.1% 1721.1 (1469.3–1956.1) 1293.5 (1097.5–1514.4) -24.8% Both 8127236 (7087624–9210919) 13278484 (11044907–15915542) 63.4% 2524.8 (2225.2–2869.4) 1925.6 (1639.9–2252.9) -23.7% Cirrhosis and other chronic liver diseases Male 2762262 (2337721–3315642) 4481721 (3613857–5508896) 62.2% 1967.6 (1663.7–2388.8) 1457.3 (1193–1761.3) -25.9% Female 1378858 (1116574–1653059) 2142593 (1727089–2642294) 55.4% 935.7 (776.4–1098) 648 (533.4–782.8) -30.7% Both 4141120 (3592417–4817954) 6624313 (5462975–8037298) 60.0% 1450.2 (1254.5–1682) 1033.9 (876–1235.1) -28.7% Upper digestive system diseases Male 730838 (588064–925249) 1131218 (901122–1427775) 54.8% 466.4 (377.4–586.9) 328.2 (264.6–411.7) -29.6% Female 505463 (387239–649104) 923559 (693365–1255825) 82.7% 310.8 (242.5–391.7) 257 (199.8–341.9) -17.3% Both 1236301 (1008224–1529649) 2054778 (1605408–2689991) 66.2% 389.3 (320.8–475.4) 291.9 (234.5–374.6) -25.0% Peptic ulcer disease Male 419957 (316563–552889) 550478 (441923–666105) 31.1% 280.5 (213.2–374.9) 169 (138.9–201) -39.8% Female 259235 (195182–338955) 388303 (311170–481908) 49.8% 157 (124–192.4) 112.6 (93.2–133.4) -28.3% Both 679192 (554588–832926) 938781 (777532–1127559) 38.2% 219.1 (183–267.2) 140 (120.1–161.4) -36.1% Gastritis and duodenitis Male 179739 (117026–247051) 280584 (198138–368993) 56.1% 102.6 (64.5–144.3) 75.8 (52.9–99.7) -26.1% Female 102268 (74078–135934) 190582 (137908–254402) 86.4% 65.4 (46.8–85.3) 55.8 (40.8–74) -14.7% Both 282007 (202411–359973) 471166 (347774–611127) 67.1% 84.3 (59–108.8) 65.7 (49.1–84.6) -22.1% Gastroesophageal reflux disease Male 131142 (67360–230256) 300156 (155286–527280) 128.9% 83.3 (42.5–148.4) 83.4 (42.5–149.2) 0.1% Female 143961 (75267–254950) 344674 (180957–612008) 139.4% 88.4 (46–158.6) 88.6 (46.1–159.4) 0.2% Both 275103 (143637–485821) 644831 (337420–1136189) 134.4% 85.9 (44.5–153.3) 86.1 (44.7–154.3) 0.2% Appendicitis Male 153317 (48664–258595) 145509 (82355–227633) -5.1% 59.3 (26.2–97.2) 31 (18.2–49.7) -47.7% Female 118826 (41531–217973) 120841 (71216–184521) 1.7% 43.6 (19.9–79.7) 22.7 (14.4–35.4) -47.9% Both 272143 (107665–467393) 266350 (171347–369648) -2.1% 51.4 (26.6–85.1) 26.7 (18.4–38.5) -48.1% Paralytic ileus and intestinal obstruction Male 690150 (502042–874495) 1341699 (915084–1856079) 94.4% 333.8 (239.9–441.7) 332.6 (230.6–438.6) -0.4% Female 380734 (308761–469130) 600485 (435628–829996) 57.7% 133.2 (109.2–163.3) 119.9 (89.6–155.6) -10.0% Both 1070884 (866511–1297226) 1942184 (1390130–2664654) 81.4% 231.5 (185.4–288.9) 220.7 (163.4–285.7) -4.7% Inguinal, femoral, and abdominal hernia Male 303715 (189253–410174) 487130 (364104–645213) 60.4% 137.7 (97.2–175.1) 126 (94.6–172.6) -8.5% Female 79732 (36523–124462) 115800 (67335–172580) 45.2% 30.8 (16.4–42.6) 26.5 (14.9–42.8) -14.0% Both 383447 (248613–503128) 602929 (452855–787932) 57.2% 83.4 (60.5–105.1) 73.9 (55.5–99.5) -11.4% Inflammatory bowel disease Male 39580 (19569–74376) 69062 (49913–87806) 74.5% 22.4 (14.2–31.9) 20.7 (15.9–26.3) -7.6% Female 43202 (16129–67315) 64697 (38965–99935) 49.8% 18.6 (10–26.9) 14.8 (10.4–20.4) -20.4% Both 82782 (42029–136040) 133759 (97840–178122) 61.6% 20.4 (14.1–27.8) 17.5 (13.8–22.1) -14.2% Vascular intestinal disorders Male 56466 (34982–81122) 94653 (74749–122926) 67.6% 34.5 (26.8–43.5) 33.8 (25.8–41.7) -2.0% Female 21198 (14479–30103) 50392 (39736–60621) 137.7% 17.9 (12.7–22.7) 20.1 (16.1–24) 12.3% Both 77664 (52976–108283) 145045 (116789–177670) 86.8% 26.2 (21.1–31.9) 26.6 (21–31.3) 1.5% Gallbladder and biliary diseases Male 92188 (69313–120870) 202099 (131784–273031) 119.2% 73.3 (55–102.3) 78.9 (52.1–110.8) 7.6% Female 144682 (103275–187239) 257812 (185465–320609) 78.2% 90.9 (70.1–114.5) 79.7 (57.4–103.1) -12.3% Both 236870 (184712–290659) 459911 (331744–580737) 94.2% 82.1 (66.2–105) 79 (57.4–104.9) -3.8% Pancreatitis Male 169007 (114307–257654) 372800 (261940–551834) 120.6% 118.1 (79.5–182.7) 114.2 (80.9–168.7) -3.3% Female 56476 (35392–85859) 107522 (69940–152554) 90.4% 38 (26.8–56) 33 (23–46.3) -13.2% Both 225483 (163301–314823) 480321 (359618–657521) 113.0% 77.9 (55.6–113.4) 71.8 (53.9–99.5) -7.8% Other digestive diseases Male 218509 (141351–308190) 321906 (232164–413472) 47.3% 121.4 (81.3–164.5) 95.2 (66.4–129.9) -21.6% Female 182032 (70505–354649) 246987 (150105–333495) 35.7% 101.7 (48.7–146.7) 71.9 (43.2–101.2) -29.3% Both 400541 (218966–658315) 568893 (394504–710262) 42.0% 112.3 (62.6–141.6) 83.5 (57.8–105.6) -25.6% For cirrhosis and other chronic liver diseases, the age-standardized DALY rate per 100,000 individuals saw a decline for both genders. Males experienced a decrease from 1,967.6 (1,663.7–2,388.8) in 1990 to 1,457.3 (1,193–1,761.3) by 2019, marking a -25.9% change. Females saw a more significant reduction from 935.7 (776.4–1,098) to 648 (533.4–782.8), a -30.7% change. Upper digestive system diseases, which include conditions like peptic ulcer disease and gastritis and duodenitis, also observed significant changes in age-standardized DALY rates. For males, the rate decreased from 46.4 (377.4–586.9) to 328.2 (264.6–411.7), a -29.6% change. For females, the rate dropped from 310.8 (242.5–391.7) to 257 (199.8–341.9), a -17.3% change. Other conditions such as appendicitis, paralytic ileus, and various types of hernias showed changes in their age-standardized DALY rates as well, with appendicitis in males decreasing by 47.7% and in females by 47.9%. Paralytic ileus experienced a slight decrease in the male rate by -0.4% and a more noticeable reduction in females by -10.0%. Hernias decreased by -8.5% in males and − 14.0% in females. Trends in Deaths From 1990 to 2019, the total number of deaths attributed to all digestive diseases rose significantly as shown in Table 3 . For males, the raw death count increased from 127,904 (109,839 − 152,830) to 209,458 (175,720 − 251,923), marking a 63.8% increase. For females, the count increased from 68,936 (58,646 − 78,852) to 114,239 (97,095–134,786), reflecting a 65.7% increase. Despite the rise in raw death counts, the age-standardized death rate per 100,000 individuals for these diseases decreased for both genders; males saw a reduction from 109.7 (93.2–132.5) to 87.1 (74.5–102.3), a -20.6% change, and females from 58.5 (49.8–67.5) to 45.6 (39.7–52.6), a -22.1% change. Table 3 Comparative Analysis of Raw Death count and Age-Standardized Death Rates by Cause Between 1990 and 2019 Diseases Gender Raw Death count in 1990 Raw Death counts in 2019 Percentage Change Age-standardized Death Rate per 100,000 individuals in 1990 Age-standardized Death Rate per 100,000 individuals in 2019 Percentage Change Digestive diseases Male 127904 (109839–152830) 209458 (175720–251923) 63.8% 109.7 (93.2–132.5) 87.1 (74.5–102.3) -20.6% Female 68936 (58646–78852) 114239 (97095–134786) 65.7% 58.5 (49.8–67.5) 45.6 (39.7–52.6) -22.1% Both 196840 (172532–224386) 323697 (275509–380783) 64.4% 83.6 (72.9–97.2) 65 (56.3–74.9) -22.2% Cirrhosis and other chronic liver diseases Male 78800 (66487–95410) 124274 (101827–150290) 57.7% 68.7 (57.8–82.9) 51.1 (42.8–60.5) -25.6% Female 39477 (32926–46533) 63431 (52053–76060) 60.7% 34.1 (28.7–41.1) 24.7 (20.3–29.2) -27.6% Both 118277 (102235–137488) 187705 (159804–223646) 58.7% 51.1 (44.2–59.5) 37.1 (32.1–43.1) -27.4% Upper digestive system diseases Male 14032 (11182–18016) 18499 (14978–22060) 31.8% 12.1 (9.7–15.8) 7.6 (6.4–8.9) -37.2% Female 8463 (6752–10300) 13461 (11161–16034) 59.1% 7.8 (6.2–9.4) 5.9 ( 5 – 7 ) -24.4% Both 22495 (19089–26889) 31960 (26970–36903) 42.1% 10.0 (8.5–12.1) 6.8 (5.9–7.7) -32.0% Peptic ulcer disease Male 10945 (8310–14628) 14296 (11678–17109) 30.6% 9.8 (7.5–13.1) 6.1 (5.1–7.2) -37.8% Female 6955 (5451–8616) 11211 (9294–13306) 61.2% 6.4 (5–7.9) 4.9 (4.1–5.7) -23.4% Both 17900 (14874–21753) 25507 (21908–29473) 42.5% 8.1 (6.8–10) 5.5 (4.8–6.2) -32.1% Gastritis and duodenitis Male 3087 (1655–4623) 4203 (2395–5874) 36.2% 2.3 (1.2–3.6) 1.5 (0.8–2.1) -34.8% Female 1508 (854–2151) 2250 (1349–2997) 49.2% 1.4 (0.8–1.9) 1 (0.6–1.4) -28.6% Both 4595 (2791–6214) 6453 (3900–8515) 40.4% 1.9 (1.1–2.6) 1.3 (0.8–1.7) -31.6% Appendicitis Male 2541 (1031–4219) 2654 (1514–4356) 4.4% 1.4 (0.7–2.4) 0.9 (0.5–1.4) -35.7% Female 1935 (830–3585) 2073 (1274–3282) 7.1% 1 (0.6–2.2) 0.6 (0.4–1) -40.0% Both 4476 (2198–7520) 4727 (3152–6875) 5.6% 1.2 (0.7–2) 0.7 (0.5–1.1) -41.7% Paralytic ileus and intestinal obstruction Male 14286 (10243–18552) 29442 (20378–38846) 106.1% 11.3 (8–15.2) 11.5 (8.3–14.8) 1.8% Female 6615 (5456–8103) 12038 (9033–15528) 82.0% 4.3 (3.3–5.3) 4.1 (3.1–5) -4.7% Both 20901 (16794–25671) 41480 (30755–53581) 98.5% 7.6 (5.9–9.6) 7.4 (5.7–9.2) -2.6% Inguinal, femoral, and abdominal hernia Male 3576 (1728–4717) 5475 (3733–8722) 53.1% 2.8 (1.7–4.6) 2.5 (1.7–4.2) -10.7% Female 997 (290–1534) 1650 (528–3339) 65.5% 0.7 (0.3–1.3) 0.7 (0.2–1.5) 0.0% Both 4573 (2438–5917) 7125 (5005–11041) 55.8% 1.7 (1.1–2.7) 1.5 (1.1–2.5) -11.8% Inflammatory bowel disease Male 904 (548–1308) 1726 (1299–2204) 90.9% 0.8 (0.5–1.2) 0.7 (0.5–1) -12.5% Female 758 (371–1130) 1300 (903–1837) 71.5% 0.5 (0.3–0.7) 0.4 (0.3–0.5) -20.0% Both 1662 (1097–2308) 3026 (2377–3901) 82.1% 0.6 (0.4–0.9) 0.6 (0.5–0.7) 0.0% Vascular intestinal disorders Male 1505 (1151–1904) 3031 (2309–3744) 101.4% 9.8 (7.5–13.1) 1.5 (1.2–1.8) 1.6 (1.2–2) Female 860 (609–1073) 2243 (1787–2696) 160.8% 6.4 (5–7.9) 1 (0.7–1.2) 1.2 (0.9–1.4) Both 2365 (1908–2887) 5275 (4191–6180) 123.0% 8.1 (6.8–10) 1.2 (1–1.4) 1.4 (1.1–1.6) Gallbladder and biliary diseases Male 2906 (2161–4154) 6751 (4267–9709) 132.3% 3.4 (2.5–4.9) 3.9 (2.5–5.8) 14.7% Female 3663 (2728–4656) 7505 (5274–10098) 104.9% 3.5 (2.7–4.5) 3.5 (2.5–4.8) 0.0% Both 6569 (5170–8542) 14256 (9930–19359) 117.0% 3.4 (2.8–4.6) 3.7 (2.6–5.1) 8.8% Pancreatitis Male 4381 (2928–6839) 9484 (6655–14050) 116.5% 3.6 (2.4–5.6) 3.6 (2.5–5.2) 0.0% Female 1576 (1099–2331) 3081 (2161–4356) 95.5% 1.4 (0.9–1.9) 1.2 (0.9–1.7) -14.3% Both 5957 (4210–8614) 12565 (9420–17371) 110.9% 2.5 (1.7–3.6) 2.3 (1.7–3.1) -8.0% Other digestive diseases Male 4973 (3234–6683) 8122 (5604–11119) 63.3% 4.2 (2.9–6.5) 3.6 (2.4–5.2) -14.3% Female 4592 (2143–6681) 7458 (4394–10472) 62.4% 4.2 (2.1–5.6) 3.4 (1.9–4.8) -19.0% Both 9565 (5295–12316) 15580 (10658–19829) 62.9% 4.3 (2.6–5.6) 3.5 (2.3–4.5) -18.6% For cirrhosis and other chronic liver diseases, the age-standardized death rate per 100,000 individuals declined for both genders. Males experienced a decrease from 68.7 (57.8–82.9) to 51.1 (42.8–60.5), a -25.6% change. Females saw an even more significant reduction from 34.1 (28.7–41.1) to 24.7 (20.3–29.2), a -27.6% change. Upper digestive system diseases, which include conditions like peptic ulcer disease and gastritis and duodenitis, also observed significant changes in age-standardized death rates. For males, the rate decreased from 12.1 (9.7–15.8) to 7.6 (6.4–8.9), a -37.2% change, and for females, it went from 7.8 (6.2–9.4) to 5.9 ( 5 – 7 ), a -24.4% change. Other conditions such as appendicitis, paralytic ileus, and various types of hernias also showed changes in their age-standardized death rates. Specifically, appendicitis in males saw a decrease by 35.7%, and in females by 40.0%. Paralytic ileus experienced a slight increase in the male rate by 1.8% and a reduction in females by -4.7%. Hernias decreased by -10.7% in males and remained stable in females at 0.0%. Risk Factors In 1990, smoking was responsible for 27.31 age-standardized DALYs per 100,000 population (CI: 20.50–36.63), alcohol use for 660.08 (CI: 498.00–843.91), drug use for 28.21 (CI: 17.43–45.67), and high body-mass index for 12.13 (CI: 5.84–21.53). By 2019, these figures had changed: smoking decreased to 14.78 DALYs (CI: 11.20–18.69), alcohol use decreased to 515.85 (CI: 382.60–668.17), drug use increased to 36.63 (CI: 23.24–55.38), and high body-mass index increased to 19.21 (CI: 10.65–31.38). Throughout the years, alcohol remained the leading risk factor despite a decrease in its associated DALYs. Drug use consistently occupied the second spot, with its impact slightly increasing. High body-mass index, which was the lowest in 1990, surpassed smoking by 2019 due to the latter's significant decrease and the former's steady increase. Smoking showed the largest reduction over the 29 years, more than halving its DALYs, reflecting successful public health interventions, as shown in Fig. 3 . Estimated Annual Percentage Change in ASDR by Country, and Relationship with the SDI and UHC effective coverage index. As shown in Fig. 3 , within the Central Sub-Saharan Africa region, Angola had the highest age-standardized DALY rate in 1990 at 3037.56 (CI: 3956.72–2235.31) per 100,000 population, while the Central African Republic reported a rate of 3346.52 (CI: 4237.03–2485.49). By 2019, Gabon, also in the Central region, had the highest rate at 1664.11 (CI: 2085.89–1277.41), followed by Mozambique in the Eastern region with a rate of 1740.44 (CI: 2172.28–1386.69). The lowest rates in 1990 were noted in Eritrea at 2584.49 (CI: 3426.00–1841.94) and Eswatini at 1933.64 (CI: 2614.91–1549.30) from the Eastern and Southern regions, respectively. In 2019, Eswatini recorded a decreased rate of 1786.09 (CI: 2393.63–1319.66), and Eritrea reported a rate of 2519.10 (CI: 3276.83–1942.26). SSA experienced a notable decline in age standardized DALYs with an EAPC of -0.94 (-1.00 to -0.88). Among the countries in the region, Mauritania had the highest decrease in DALYs, with an EAPC of -2.31 (-2.38 to -2.23). Conversely, Lesotho displayed an upward trend with an EAPC of 0.42 (0.23 to 0.61), indicating an increase in the burden of disease. Equatorial Guinea also saw a substantial decrease with an EAPC of -2.77 (-2.99 to -2.56), and Ethiopia reflected a significant reduction with an EAPC of -1.94 (-2.05 to -1.83). In examining the correlations, EAPC versus the Socio-demographic Index (SDI) for 2019 had a Pearson's r of -0.26 (p-value: 0.080) as shown in Fig. 4 , and EAPC against the Universal Health Coverage (UHC) Effective Coverage Index in 2019 had a Pearson's r of -0.38 (p-value: 0.008) as shown in Fig. 5 . Discussion The primary objective of this study was to employ the GBD dataset to provide a comprehensive epidemiological analysis of the burden of digestive diseases in SSA, a region often underrepresented in global health research. This study is notably the first in the region to utilize the GBD dataset specifically for digestive diseases, offering the most up-to-date and comprehensive data available. Furthermore, our analysis also reveals significant correlations between the Estimated Annual Percentage Changes in DALYs and the UHC effective coverage index, underscoring the impact of healthcare access and socio-economic development on health outcomes. By focusing on an understudied region, this research fills significant gaps in our understanding of the epidemiological profile and health impacts associated with these conditions. Overall, our findings reveal notable changes in the prevalence, DALYs, and mortality rates associated with digestive diseases over the past decades. There has been a significant decrease in the age-standardized prevalence and DALY rates for cirrhosis, peptic ulcer disease, and appendicitis, reflecting improvements in public health interventions and healthcare delivery. Conversely, the study identified an increase in the rates of inflammatory bowel disease and vascular intestinal disorders, indicating emerging public health challenges that require urgent attention. These trends underscore the dynamic nature of disease burden in the region and highlight the critical need for targeted health policies to address both declining and emerging health threats. The analysis of prevalence data from the GBD dataset reveals significant trends in digestive diseases in Sub-Saharan Africa from 1990 to 2019. Cirrhosis and other chronic liver diseases displayed the most substantial declines in age-standardized prevalence rates, decreasing by 10.6% in females and 9.5% in males. This marked reduction suggests that, despite the near doubling of raw prevalence counts, the standardized risk of digestive diseases may have decreased when accounting for demographic changes. On the other hand, inflammatory bowel disease experienced the most significant increase in age-standardized rates, with a rise of 13.9% for both genders combined. The overall rising prevalence of digestive diseases in the region can be attributed to several interconnected factors. As Sub-Saharan Africa undergoes a demographic transition with increasing life expectancy, there is an anticipated growth in the burden of NCDs, including those affecting the digestive system. 2 Improved access to treatments such as antiretroviral therapy contributes to longer life expectancies and, consequently, an increased prevalence of NCDs, including many digestive diseases linked to chronic viruses. 2 Additionally, the increasing incidence of diabetes—a metabolic disorder linked to various digestive complications—is further exacerbating the burden of digestive diseases. 19 Challenges related to healthcare access and service delivery, coupled with adverse biological factors, also contribute significantly to the rising disease burden. 20 Moreover, lifestyle changes linked to urbanization and the epidemiological transition, such as unhealthy diets and sedentary lifestyles, are driving the increase in NCDs, including digestive disorders. 21 Environmental and social determinants, such as poverty and limited healthcare access, also play a crucial role in shaping the epidemiology of these diseases in the region. 22 "In addition to reinforcing trends observed in prevalence, the detailed analysis of DALYs provides crucial insights into the differential impacts of various digestive diseases in Sub-Saharan Africa. For instance, cirrhosis and other chronic liver diseases have shown significant improvements, with age-standardized DALY rates decreasing by 25.9% for males and an even more notable 30.7% for females. Similarly, overall digestive diseases have observed substantial reductions in DALYs, with a 21.5% decrease for males and 24.8% for females, culminating in a combined decrease of 23.7%. Notably, acute appendicitis, despite being the leading cause of abdominal surgical emergencies in the region, 23 has seen some of the largest declines in DALY rates at 48.1%. This significant reduction reflects advancements in surgical management and treatment strategies, contributing positively at the population health level. However, not all trends point towards improvement. Vascular intestinal disorders, for instance, saw an increase in age-standardized DALY rates for females by 12.3%, indicating a worsening disease impact. Such disparities in disease outcomes highlight the critical need for epidemiological analysis to inform health policy and direct resource allocation effectively. The varied responses across different digestive diseases suggest that while some public health strategies have yielded substantial benefits, others need urgent reevaluation to address the increasing burden and complexity of disease patterns, especially in diseases that are on the rise. The study highlights significant shifts in the epidemiology of cirrhosis and other chronic liver diseases in Sub-Saharan Africa from 1990 to 2019. The rates of cirrhosis due to Hepatitis B and C have significantly decreased, suggesting successful impacts of improved treatment approaches and vaccination programs. Such findings align with global health initiatives, like the WHO's strategy aiming for a 90% reduction in new cases of chronic hepatitis by 2030, reflecting the potential of targeted healthcare interventions. 24 Despite these advances, the prevalence of metabolic-associated steatohepatitis (MASLD) has notably increased, pointing to the rising impact of metabolic factors on liver health. This uptick contrasts with the declining trend of viral hepatitis-related cirrhosis and underscores the complex and evolving burden of liver diseases. The prevalence of hepatitis B remains high, reported at about 6% in the region, with significant co-infection rates among HIV patients, highlighting the ongoing challenge of managing liver health amid the HIV epidemic. 12, 25 Moreover, with hepatitis B as a leading cause of hepatocellular carcinoma, 26 these findings emphasize the critical need for continuous epidemiological surveillance and adaptive health policies to address both infectious and non-infectious contributors to liver disease in Sub-Saharan Africa. Furthermore, our findings on regional differences highlight significant variability in disease burden across Sub-Saharan Africa. In 2019, the Republic of Mozambique reported the highest age-standardized DALY rate for digestive diseases among the sampled African countries, with a rate of 1740.44 per 100,000 individuals. This starkly contrasts with the Republic of South Africa, which had the lowest rate at 976.49 per 100,000 individuals the same year. Looking back to 1990, the Federal Democratic Republic of Ethiopia exhibited a particularly high burden with a rate of 3604.30, exemplifying the severe impact of digestive diseases at the time. Over the decades, there has been a general downward trend in these rates across the region. The pronounced regional differences in the burden of digestive diseases underscore the critical need for tailored public health interventions and policies. Such variability demands that health strategies be customized to the specific challenges and resources of each country to effectively address the unique aspects of their healthcare landscapes. This approach is essential for continuing the progress observed in reducing the burden of digestive diseases and for targeting emerging health threats more effectively. In addition to quantifying the burden of gastric diseases in SSA, our analysis of GBD data revealed unique insights about risk factors that interplay to influence gastric diseases outcomes. In addition to quantifying the burden of gastric diseases in SSA, our analysis of GBD data revealed a significant trend: a consistent decline in age standardized DALYs attributable to alcohol use from 1990 to 2019. This suggests a positive shift in health outcomes related to alcohol consumption over three decades. Despite this general trend, literature highlights important demographic nuances. For instance, problematic drinking patterns are more prevalent among men, particularly those who are divorced or widowed and current smokers. 27 Moreover, alcohol consumption rates vary significantly by gender and region, being higher in men (60.3% vs. 29.3% in women), with the highest rates in men from Soweto (70.8%) and women from Nanoro (59.8%). 27 These findings indicate that while overall alcohol-related health outcomes have improved, regional and demographic disparities persist. Crucially, the literature also identifies external factors exacerbating these trends, such as aggressive marketing by alcohol companies and low regulatory oversight, which enhance alcohol availability and distribution, negatively impacting national alcohol policies. 28–31 This constitutes a potential area of intervention that could continue to improve trends in alcohol consumption within SSA region. Transitioning from the impact of alcohol, another critical risk factor for gastric diseases in SSA is the marked increase in high BMI observed between 1990 and 2019. This rising trend in BMI, linked to many complex health outcomes, must be a subject of focused attention due to its substantial contribution to the burden of gastric diseases across the region. The significance of high BMI and its varying impact across SSA is exemplified by data from the Demographic and Health Survey (DHS). Neupane et al. 32 reported significant regional differences in the prevalence of overweight and obesity within SSA countries. For instance, the pooled prevalence of overweight was lowest in Madagascar (5.6%) and highest in Swaziland (27.7%). Furthermore, the wealth index emerged as the strongest predictor of overweight status in most countries, indicating that socio-economic factors play a crucial role in the spread of obesity and must be considered when directing intervention measures. Of note, our findings reveal a significant correlation between the UHC effective coverage index and health outcomes, with better health coverage associated with faster reductions in DALYs. This accentuates the critical role of access to quality healthcare in mitigating health risks, including those associated with high BMI. Although the correlation between health outcomes and the SDI was not statistically significant, the trend suggests that socio-economic development may also influence health outcomes. Therefore, comprehensive policies that address both healthcare access and socio-economic disparities are essential for improving health across SSA. Further supporting concerns regarding obesity as a risk factor, additional literature points to the increasing burden of childhood obesity in the region. Danquah et al. 33 highlight that the health risks associated with obesity and overweight are particularly problematic in children, given the potential for long-term health implications. This trend underscores the urgency of addressing high BMI from a young age to mitigate its extensive health impacts. Compounding these issues is the ongoing nutrition and physical activity transition within SSA, characterized by increased reliance on energy-saving devices, the availability of inexpensive, high-calorie dense foods, and a general decline in physical activity. 34, 35 Furthermore, sociocultural beliefs that revere and associate obesity with prestige, a good life, and economic value exacerbate the situation. 34, 36–38 These factors collectively contribute to the normalization of high BMI, challenging public health efforts to combat its rise. Building upon the trends observed in alcohol and high BMI, another evolving challenge in SSA is the moderate increase in drug use. This rise has raised significant public health concerns. Varshney et al. conducted a systematic review which highlights the grave health consequences of nyaope usage, particularly its association with increased HIV infections and the misuse of HIV antiretrovirals. 39 To mitigate these issues, it is crucial that drug prevention and treatment programs in SSA are robust and evidence-based. Strategies such as harm reduction, access to substance abuse treatment, and community-based prevention programs must be intensified. Additionally, targeted educational and rehabilitation interventions are vital for specifically addressing the health risks posed by nyaope and other drugs. 39 The literature indicates that while studies on substance use in SSA do exist, they often focus on specific demographics such as people living with HIV, the homeless, or university students, and may not be nationally representative. 40–46 This highlights a need for broader and more inclusive research to fully understand and address the drug use landscape across different societal segments. Smoking Transitioning to the risk factor of smoking, our findings show a notable decrease in smoking-related health issues, suggesting some success in public health measures to reduce tobacco use. However, despite these gains, the literature reveals a significant gap in tobacco control efforts within the region. Peer et al. and Mamudu et al. have both pointed out that smoking cessation campaigns and tobacco control interventions are scant in SSA. 47, 48 The region has been described as a "research desert" concerning tobacco control, with a clear need for increased investment in both research and training over the past 50 years. 48 The lack of comprehensive tobacco cessation interventions highlights an urgent need for SSA to prioritize and invest in effective tobacco control strategies. Developing targeted campaigns, enhancing public health messaging, and investing in cessation programs are essential steps towards addressing the smoking-related health burden more effectively. Limitations While this study provides valuable insights into the burden of digestive diseases in SSA and utilizes the comprehensive GBD dataset, several limitations must be acknowledged. Firstly, the reliance on secondary data may introduce inherent biases associated with data collection and reporting standards, which can vary significantly across different SSA countries. This could affect the accuracy and comparability of the data on regional and national levels. Additionally, the GBD approach primarily focuses on quantifiable health outcomes, potentially overlooking socio-cultural factors and individual behaviors that significantly influence health. This might lead to an underestimation of the impact of such factors on the prevalence and severity of digestive diseases. Another limitation is the broad geographic and demographic categorization used, which might mask nuanced intra-regional variations and specific population dynamics. Lastly, while this study marks significant progress in highlighting trends and risk factors for digestive diseases in SSA, the findings might not fully represent all sub-populations or the latest shifts in health trends due to the lag in data compilation and publication. Future Research Future research on the burden of digestive diseases in Sub-Saharan Africa should aim to address the limitations of current studies by incorporating more real-time, primary data collection and by expanding the scope to include qualitative assessments that capture socio-cultural dynamics and individual behaviors affecting health outcomes. There is also a need for studies to focus on more granular, locally relevant data that can uncover intra-regional variations and allow for targeted interventions. Additionally, longitudinal studies would provide a deeper understanding of the temporal relationships and causative factors behind the observed trends in digestive disease prevalence and outcomes. This approach could facilitate the development of more effective, tailored public health strategies and interventions. Furthermore, integrating genetic, environmental, and lifestyle factors into research models could enhance our understanding of the complex interplay of factors influencing digestive health in this diverse region. Expanding research to include these dimensions will provide a more comprehensive and nuanced understanding of the health challenges and needs in Sub-Saharan Africa. Conclusions This study leverages the GBD dataset to illuminate the shifting landscape of digestive diseases in Sub-Saharan Africa, revealing marked improvements and emerging health challenges over the last three decades. While declines in diseases like cirrhosis indicate progress due to enhanced healthcare interventions, the rise in conditions such as inflammatory bowel disease and the complex influence of risk factors like high BMI and drug use highlight ongoing public health challenges. These findings represent a call for region-specific health policies and interventions that address both existing and emerging health threats. Continued research is essential to refine our understanding of these diseases and to guide effective public health strategies, ultimately improving health outcomes across the region. Declarations Ethics approval and consent to participate. Given that we utilized publicly accessible data, no IRB or individual consent was needed. Consent for publication. Given that we utilize publicly accessible data, individual consent for publication is not required. Data Availability Statement The data supporting this study's findings come from the GBD study, available on the Institute for Health Metrics and Evaluation website. The GBD offers comprehensive health data worldwide, including mortality, morbidity, and risk factor estimates for various diseases and conditions. The dataset can be accessed by visiting the IHME GBD Data Tool at https://vizhub.healthdata.org/gbd-compare/#. This interactive tool allows for the exploration of health trends at global, regional, and country levels. The dataset is openly accessible under IHME's terms, supporting its use for research and policy analysis. Competing interest The authors have no competing interests to declare. Funding No funding was obtained for this manuscript. Authors' contributions (A=Study Design, B=Data collection, C=Statistical analysis, D=Data interpretation, E=Manuscript preparation, F=Literature search, G=Manuscript review) Omar Al Ta’ani: ABCDEFG Yazan Al-Ajlouni: ADEFG Mohammad Tanashat: ADEFG Basile Njei: ADEFG Acknowledgements We thank the GBD collaborators for the data used in this study. References Surial B, Wyser D, Béguelin C, Ramírez-Mena A, Rauch A, Wandeler G. 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Boua PR, Soo CC, Debpuur C, Maposa I, Nkoana S, Mohamed SF, et al. Prevalence and socio-demographic correlates of tobacco and alcohol use in four sub-Saharan African countries: a cross-sectional study of middle-aged adults. BMC Public Health. 2021;21(1):1126. Da Pilma Lekettey J, Dako-Gyeke P, Agyemang SA, Aikins M. Alcohol consumption among pregnant women in James Town Community, Accra, Ghana. Reprod Health. 2017;14(1):120-. Martinez P, Røislien J, Naidoo N, Clausen T. Alcohol abstinence and drinking among African women: data from the World Health Surveys. BMC public health. 2011;11:160-. Ferreira-Borges C, Parry CDH, Babor TF. Harmful Use of Alcohol: A Shadow over Sub-Saharan Africa in Need of Workable Solutions. International journal of environmental research and public health. 2017;14(4):346. Morojele NK, Dumbili EW, Obot IS, Parry CDH. Alcohol consumption, harms and policy developments in sub‐Saharan Africa: The case for stronger national and regional responses. Drug and Alcohol Review. 2021;40(3):402-19. Neupane S, KC P, Doku DT. Overweight and obesity among women: analysis of demographic and health survey data from 32 Sub-Saharan African Countries. BMC public health. 2015;16:1-9. Danquah FI, Ansu-Mensah M, Bawontuo V, Yeboah M, Kuupiel D. Prevalence, incidence, and trends of childhood overweight/obesity in Sub-Saharan Africa: a systematic scoping review. Archives of Public Health. 2020;78:1-20. Onywera VO. Childhood obesity and physical inactivity threat in Africa: strategies for a healthy future. Global health promotion. 2010;17(2_suppl):45-6. Mozaffari H, Nabaei B. Obesity and related risk factors. The Indian Journal of Pediatrics. 2007;74:265-7. Pangani IN, Kiplamai FK, Kamau JW, Onywera VO. Prevalence of overweight and obesity among primary school children aged 8–13 Years in Dar es Salaam city, Tanzania. Advances in preventive medicine. 2016;2016. Kanter R, Caballero B. Global gender disparities in obesity: a review. Advances in nutrition. 2012;3(4):491-8. Gellner R, Domschke W. Epidemiology of obesity. Der Chirurg. 2008;79:807-18. Varshney K, Browning SD, Debnath SK, Shet P, Shet D. A systematic review of risk factors and consequences of Nyaope usage: The illicit street drug containing HIV antiretrovirals. AIDS and Behavior. 2023;27(2):558-77. Ayano G, Assefa D, Haile K, Chaka A, Solomon H, Hagos P, et al. Mental, neurologic, and substance use (MNS) disorders among street homeless people in Ethiopia. Ann Gen Psychiatry. 2017;16:40-. Elf JL, Variava E, Chon S, Lebina L, Motlhaoleng K, Gupte N, et al. Prevalence and Correlates of Smoking Among People Living With HIV in South Africa. Nicotine Tob Res. 2018;20(9):1124-31. Gebremariam TB, Mruts KB, Neway TK. Substance use and associated factors among Debre Berhan University students, Central Ethiopia. Subst Abuse Treat Prev Policy. 2018;13(1):13-. Kassa A, Wakgari N, Taddesse F. Determinants of alcohol use and khat chewing among Hawassa University students, Ethiopia: a cross sectional study. Afr Health Sci. 2016;16(3):822-30. Mdege ND, Shah S, Ayo-Yusuf OA, Hakim J, Siddiqi K. Tobacco use among people living with HIV: analysis of data from Demographic and Health Surveys from 28 low-income and middle-income countries. Lancet Glob Health. 2017;5(6):e578-e92. Molla Z, Dube L, Krahl W, Soboka M. Tobacco dependence among people with mental illness: a facility-based cross sectional study from Southwest Ethiopia. BMC Res Notes. 2017;10(1):289-. Nkoana S, Sodi T, Darikwa TB. Heavy episodic alcohol drinking among students from a rural South African university: Correlates with personal-social variables. Journal of Psychology in Africa. 2016;26(4):368-72. Peer N, Naicker A, Khan M, Kengne A-P. A narrative systematic review of tobacco cessation interventions in Sub-Saharan Africa. SAGE Open Medicine. 2020;8:2050312120936907. Mamudu HM, Subedi P, Alamin AE, Veeranki SP, Owusu D, Poole A, et al. The progress of tobacco control research in sub-Saharan Africa in the past 50 years: a systematic review of the design and methods of the studies. International Journal of Environmental Research and Public Health. 2018;15(12):2732. Additional Declarations No competing interests reported. Supplementary Files Supplementary.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-4401782","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304066539,"identity":"40ff7c46-5796-4596-899c-d7777508bda9","order_by":0,"name":"Omar Al Ta’ani","email":"","orcid":"","institution":"Allegheny Health Network","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"Al","lastName":"Ta’ani","suffix":""},{"id":304066541,"identity":"133b34ef-2df8-4091-b831-6b9b3b39aa9d","order_by":1,"name":"Yazan Al-Ajlouni","email":"","orcid":"","institution":"Montefiore Medical 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16:06:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4401782/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4401782/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57036566,"identity":"2884546f-ac31-42df-97e8-a84c53660cba","added_by":"auto","created_at":"2024-05-23 18:40:12","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77396,"visible":true,"origin":"","legend":"\u003cp\u003eTrend of Cirrhosis and Other Chronic Liver Disease Prevalence by Cause from 1990 to 2019\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4401782/v1/80686ea7125f2bb879188ff7.jpg"},{"id":57036565,"identity":"2903ad59-767c-4377-bb93-34494b7e5531","added_by":"auto","created_at":"2024-05-23 18:40:12","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38792,"visible":true,"origin":"","legend":"\u003cp\u003ea: Age-standardized DALYs Attributable to Alcohol Use, b: Age-standardized DALYs Attributable to Other Risk Factors\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4401782/v1/97fba7056ae0b97f2258b8ef.jpg"},{"id":57037389,"identity":"560202e6-0d97-4a3d-b2ef-b6cbdcfea21f","added_by":"auto","created_at":"2024-05-23 18:48:12","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":72678,"visible":true,"origin":"","legend":"\u003cp\u003eAge-standardized DALYs Rate by Country, 1990 vs 2019\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4401782/v1/06be27b1c289098281909dca.jpg"},{"id":57036568,"identity":"522c8ced-7b68-4234-8f67-594eeec3df39","added_by":"auto","created_at":"2024-05-23 18:40:12","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":46571,"visible":true,"origin":"","legend":"\u003cp\u003eAge-standardized DALYs Estimated Annual Percentage Change against countries’ SDI in 2019\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4401782/v1/4de0aa1b9c58dfa18bca7808.jpg"},{"id":57037390,"identity":"0080687a-1ea8-4421-9ee7-97bbe4f449fd","added_by":"auto","created_at":"2024-05-23 18:48:12","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":50337,"visible":true,"origin":"","legend":"\u003cp\u003eAge-standardized DALYs Estimated Annual Percentage Change against countries’ UHC Effective Coverage Index in 2019\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4401782/v1/5a067fe7c8d04e66239994ac.jpg"},{"id":61189440,"identity":"41bba8ff-24f3-442f-8875-d1df6470d515","added_by":"auto","created_at":"2024-07-26 19:11:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1808552,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4401782/v1/33cef92b-03a3-4c44-8717-4f67dcb87bfd.pdf"},{"id":57036569,"identity":"38aae9b0-f1fd-46d6-9040-344e1f6e3b41","added_by":"auto","created_at":"2024-05-23 18:40:12","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15111,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-4401782/v1/8b7767bf45e139e2caef2b76.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Burden and Disparities of Digestive Diseases in Sub-Saharan Africa","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDigestive diseases (DD), encompassing cirrhosis, upper digestive diseases, inflammatory bowel disease, and pancreatitis, among others, represent a significant and evolving public health challenge in Sub-Saharan Africa (SSA). The prevalence and impact of these conditions vary markedly across different regions. For example, while community-based studies report a cirrhosis prevalence of 2.8% in the Gambia, a figure that escalates to 17.3% among individuals with chronic HBV infection in Ethiopia,\u003csup\u003e1\u003c/sup\u003e the broader spectrum of DD similarly demonstrates substantial disparities.\u003csup\u003e2\u003c/sup\u003e These discrepancies emphasize the challenges of managing such diseases within diverse health systems and sociocultural contexts. Moreover, the global impact of hepatitis B and C suggests that targeted interventions could significantly mitigate the disease's burden.\u003csup\u003e3\u003c/sup\u003e The socioeconomic impacts, such as potentially underestimated mortality rates, emphasize the need for tailored educational, preventative, and diagnostic measures to effectively manage and reduce digestive diseases-related morbidity and mortality.\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurther research elucidates the critical nature of DD as a public health issue in SSA, associated with significant morbidity and mortality.\u003csup\u003e5\u0026ndash;8\u003c/sup\u003e The global impact of risk factors such as viral hepatitis, alcohol consumption, unhealthy diets, and limited healthcare access suggests that targeted interventions could significantly mitigate the burden of these diseases.\u003csup\u003e9, 10\u003c/sup\u003e The World Health Organization (WHO) has identified SSA as the region with the highest prevalence, morbidity and mortality from cirrhosis.\u003csup\u003e11\u003c/sup\u003e Between 1980 and 2010, cirrhosis-related deaths doubled in SSA.\u003csup\u003e12\u003c/sup\u003e Moreover, SSA is experiencing a rapid epidemiological transition, characterized by a shift from communicable diseases to an increasing predominance of chronic, non-communicable diseases (NCDs). The region is expected to see one of the largest increases in mortality due to NCDs globally, NCD risk factor surveillance indicates that most adults in SSA are exposed to at least one risk factor for NCDs, including harmful alcohol use, unhealthy diets, and obesity, which are significant contributors to gastric diseases.\u003c/p\u003e \u003cp\u003eDespite the severity of these health issues, gastric diseases have not received the same level of attention as other prevalent diseases like HIV/AIDS or malaria. This oversight has led to critical gaps in health policy and resource allocation. Moreover, the lack of comprehensive surveillance and systematic data collection further hampers effective response and intervention strategies.\u003csup\u003e13\u003c/sup\u003e The existing research, often limited by narrow regional focuses and confined to hospital-based studies or specific communities, may not accurately reflect broader regional realities.\u003csup\u003e1\u003c/sup\u003e These studies often face methodological limitations, such as small sample sizes and retrospective designs that fail to capture the full spectrum of health outcomes related to gastric diseases. Consequently, there is a pressing need for a more detailed, systematically collected, and up-to-date dataset that can provide a clearer picture of the burden of gastric diseases across diverse settings within the region.\u003c/p\u003e \u003cp\u003eThe Global Burden of Disease (GBD) dataset presents a unique and robust tool that has not yet been fully utilized to quantify the burden of DD in SSA, where detailed health data are often scarce.\u003csup\u003e14\u003c/sup\u003e Consequently, the primary aim of this study is to leverage the comprehensive capabilities of the GBD dataset to fill the critical gaps identified in the existing literature. By doing so, we aim to provide a more precise and comprehensive epidemiological overview of digestive diseases in SSA. This approach will enhance our understanding of the prevalence and distribution of DD, facilitate the analysis of key risk factors, and assess the potential impacts of targeted health interventions over the past decades. The insights gained from this study are expected to inform effective and sustainable health policies, offering valuable guidance for healthcare providers, policymakers, and other stakeholders in the region.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThe study utilized the GBD dataset, an expansive collaborative research project designed to quantify health challenges. This dataset provides detailed estimates of mortality, incidence, prevalence, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) associated with 369 diseases and injuries as well as 87 unique risk factors for both genders in 204 countries and territories. The records extend from 1990 to 2019 and are updated on an annual basis.\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor the assessment of disease burden, the GBD study integrates data from diverse sources, including vital statistics registries, demographic surveys, health facilities, and death certificates. The study that developed this extensive database was carried out by the Institute for Health Metrics and Evaluation, with financial support from several entities, among them the World Bank, the National Institutes of Health, and the Bill \u0026amp; Melinda Gates Foundation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003eThis GBD study utilizes three key measures of disease burden: prevalence, deaths, and DALYs. Prevalence refers to the total number of cases of a disease that exist in a population at a specific point in time. Deaths represent the number of mortalities attributable to a particular disease or condition. DALYs combine the impacts of premature death and disability on an individual\u0026rsquo;s quality of life and are calculated by summing the years of life lost due to premature death and the years of healthy life lost due to disability. One DALY equates to the loss of one year of full health. Using DALYs allows for comparisons between diseases that may cause premature death but little disability and those that do not lead to death but cause significant disability, thereby providing a more comprehensive view of the overall disease burden on a population.\u003c/p\u003e \u003cp\u003eThe digestive diseases included in the GBD 2019 encompassed cirrhosis and other chronic liver diseases (from causes such as hepatitis B, hepatitis C, alcohol-related liver disease, non-alcoholic steatohepatitis, and other causes); upper digestive system diseases (including peptic ulcer disease, gastritis and duodenitis, and gastroesophageal reflux disease); appendicitis; paralytic ileus and intestinal obstruction; inguinal, femoral, and abdominal hernia; inflammatory bowel disease; vascular intestinal disorders; gallbladder and biliary diseases; pancreatitis; and other digestive diseases (an aggregate of other conditions of the digestive system). For consistency in measurement, case definitions largely conformed to the 10th revision of the International Classification of Diseases (ICD-10), as detailed in \u003cb\u003eSupplemental Table\u0026nbsp;1.\u003c/b\u003e\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eSub-Saharan Africa Region\u003c/h2\u003e \u003cp\u003eAccording to the classification provided by the Global Burden of Disease study, Sub-Saharan Africa is divided into four regions. Central Sub-Saharan Africa includes Angola, the Central African Republic, Republic of Congo, Democratic Republic of the Congo, Equatorial Guinea, and Gabon. Eastern Sub-Saharan Africa encompasses Burundi, Comoros, Djibouti, Eritrea, Ethiopia, Kenya, Madagascar, Malawi, Mozambique, Rwanda, Somalia, South Sudan, Uganda, the United Republic of Tanzania, and Zambia. The Southern region comprises Botswana, Eswatini, Lesotho, Namibia, South Africa, and Zimbabwe. Lastly, the Western region consists of Benin, Burkina Faso, Cabo Verde, Cameroon, Chad, C\u0026ocirc;te d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Sao Tome and Principe, Senegal, Sierra Leone, and Togo.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eRisk Factors\u003c/h2\u003e \u003cp\u003eOur analysis centered on the age-standardized DALYs attributable to specific risk factors for digestive diseases, as identified by the GBD study.\u003csup\u003e16\u003c/sup\u003e These risk factors comprised alcohol consumption, tobacco smoking, high body mass index (BMI), and drug use. We explored the temporal trends of these risk factors to evaluate their changing impact on health outcomes over time.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSDI\u003c/h2\u003e \u003cp\u003eThe Socio-Demographic Index (SDI) serves as an indicator of a country's developmental status, with a demonstrable correlation to healthcare outcomes. It is scaled from 0 to 1 and is derived from three components: the total fertility rate among women under 25 years of age, the average years of education for individuals aged 15 and older, and the lag-distributed income per capita.\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eUHC Universal Health Coverage (UHC) effective coverage index\u003c/h2\u003e \u003cp\u003eThe Universal Health Coverage (UHC) effective coverage index quantitatively assesses the extent of a population's access to essential health services, with a scale ranging from 0 (no coverage) to 100 (full coverage by high-quality health services). This index evaluates service provision across five categories\u0026mdash;promotion, prevention, treatment, rehabilitation, and palliation\u0026mdash;categorized further for various age groups from newborns to older adults.\u003csup\u003e17, 18\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe GBD study aggregates data from a variety of sources and the data is meticulously processed and adjusted for covariates. Standardized modeling tools such as the Cause of Death Ensemble model (CODEm), spatiotemporal Gaussian process regression (ST-GPR), and DisMod-MR are employed to ensure accurate representation of health data. The GBD Compare website facilitates the downloading and interactive visualization of these results.\u003c/p\u003e \u003cp\u003eTo handle missing data, the GBD study team employs multiple imputation techniques for data considered missing at random, and inverse probability weighting or similar methods for data not missing at random. This rigorous approach helps maintain the quality and consistency of the data, with thorough documentation of the methods used to ensure transparency in data handling.\u003c/p\u003e \u003cp\u003eData on prevalence, deaths, and DALYs for digestive diseases, along with their 95% uncertainty intervals (UIs), were obtained from the GBD study. Both raw numbers and age-standardized rates per 100,000 people were obtained for these measures. We analyzed the distribution of prevalence, DALYS, and deaths by cause, location, and year, and calculated the percentage changes between 1990 and 2019 using the formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$Percent change=\\frac{measures in 2019-measures in 1990}{measures in 1990}x 100\\%$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAdditionally, we evaluated the Estimated Annual Percentage Changes (EAPCs) in age standardized DALYs by fitting a regression line to the natural logarithm of the rates over time, expressed as y\u0026thinsp;=\u0026thinsp;α\u0026thinsp;+\u0026thinsp;βx\u0026thinsp;+\u0026thinsp;ε, where y is the natural log of the rate, and x is the calendar year. The EAPC is calculated as 100\u0026times;(exp(β)\u0026thinsp;\u0026minus;\u0026thinsp;1).\u003c/p\u003e \u003cp\u003ePearson correlation analyses were conducted to investigate the relationships between the EAPCs in ASDR with both the Socio-demographic Index (SDI) and the UHC effective coverage index for 2019. All statistical analyses and graphical representations were performed using R version 4.3.3, with a significance level set at a p-value of less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTrends in prevalence\u003c/h2\u003e \u003cp\u003eFrom 1990 to 2019, the total number of cases for all digestive diseases increased significantly as shown \u003cb\u003ein\u003c/b\u003e Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For males, the raw prevalence count rose from approximately 66,462,980 (62,493,145\u0026thinsp;\u0026minus;\u0026thinsp;70,508,314) to 130,060,299 (122,479,265\u0026thinsp;\u0026minus;\u0026thinsp;137,392,648), showing a 95.7% increase. For females, the count escalated from about 58,327,017 (54,815,114\u0026thinsp;\u0026minus;\u0026thinsp;61,990,604) to 118,687,212 (111,282,639\u0026thinsp;\u0026minus;\u0026thinsp;125,905,960), reflecting a 103.5% increase. Despite these increases in raw prevalence, the age-standardized prevalence rate per 100,000 individuals for these diseases decreased for both genders; males saw a reduction from 35,492.6 (33,744.9\u0026ndash;37,211.4) to 33,046 (31,408.2\u0026ndash;34,636.2) reflecting a -6.9% change, and females from 30,944.2 (29,264.5\u0026ndash;32,605.2) to 28,710.3 (27,171.3\u0026ndash;30,346.4), a -7.2% change.\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\u003eComparative Analysis of Raw prevalence count and Age-Standardized Prevalence Rates by Cause Between 1990 and 2019\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRaw Prevalence count in 1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw Prevalence count in 2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAge-standardized Prevalence Rate per 100,000 individuals in 1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAge-standardized Prevalence Rate per 100,000 individuals in 2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePercentage Change\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDigestive diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66462980 (62493145\u0026ndash;70508314)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130060299 (122479265\u0026ndash;137392648)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35492.6 (33744.9\u0026ndash;37211.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33046 (31408.2\u0026ndash;34636.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-6.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58327017 (54815114\u0026ndash;61990604)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e118687212 (111282639\u0026ndash;125905960)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30944.2 (29264.5\u0026ndash;32605.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28710.3 (27171.3\u0026ndash;30346.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-7.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124789997 (117287349\u0026ndash;132625322)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248747511 (233819408\u0026ndash;263441009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33186.6 (31471\u0026ndash;34859.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30799.6 (29254.1\u0026ndash;32405)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-7.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCirrhosis and other chronic liver diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59153833 (54721751\u0026ndash;63853325)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111237049 (102704642\u0026ndash;120128711)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31501.2 (29310\u0026ndash;33858.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28515.2 (26564.7\u0026ndash;30662.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-9.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47246412 (43599642\u0026ndash;51350843)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90720228 (83291585\u0026ndash;98305656)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24662.3 (22818.2\u0026ndash;26596.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22048.4 (20327.2\u0026ndash;23821.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106400245 (98347910\u0026ndash;115137528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e201957277 (185642055\u0026ndash;218897497)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28029.7 (26021.1\u0026ndash;30128.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25151.6 (23357.5\u0026ndash;27100.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eUpper digestive system diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16908371 (14697155\u0026ndash;19009360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38694457 (33668313\u0026ndash;43433067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e128.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10741.5 (9484.3\u0026ndash;11984.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10779.3 (9531.3\u0026ndash;12013.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18580942 (16227709\u0026ndash;20850367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44478693 (38897220\u0026ndash;49912550)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e139.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11433.3 (10120.1\u0026ndash;12713.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11501.7 (10217.9\u0026ndash;12768.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35489312 (30898246\u0026ndash;39702407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83173150 (72429981\u0026ndash;93104973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e134.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11095.6 (9838.1\u0026ndash;12340.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11158.5 (9909.3\u0026ndash;12402.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePeptic ulcer disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208041 (174753\u0026ndash;245487)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e405087 (339460\u0026ndash;484246)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e124.8 (106.9\u0026ndash;146.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e106.9 (91.9\u0026ndash;125.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-14.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225506 (187635\u0026ndash;268700)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e509009 (420734\u0026ndash;611005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e124.1 (105.9\u0026ndash;144.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e122.2 (103.6\u0026ndash;142.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-1.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e433547 (363910\u0026ndash;512370)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e914097 (760724\u0026ndash;1086367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e110.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e125.2 (107.5\u0026ndash;145.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e115.2 (98.9\u0026ndash;134.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-8.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGastritis and duodenitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e900240 (742729\u0026ndash;1092157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2242010 (1839827\u0026ndash;2735914)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e149.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e550 (448.1\u0026ndash;670.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e625.4 (508.1\u0026ndash;766)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e886918 (725156\u0026ndash;1077859)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2289168 (1855546\u0026ndash;2791811)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e158.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e572.7 (468.2\u0026ndash;692.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e658.6 (534.2\u0026ndash;800.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1787158 (1475370\u0026ndash;2155987)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4531178 (3705560\u0026ndash;5505999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e153.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e563.2 (460.2\u0026ndash;684.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e645.4 (526.2\u0026ndash;784.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGastroesophageal reflux disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16907111 (14447788\u0026ndash;19279463)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38544124 (32868460\u0026ndash;43948861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e128.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10822.7 (9407.5\u0026ndash;12275.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10810.1 (9400.5\u0026ndash;12258.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18727174 (16092624\u0026ndash;21251693)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44707764 (38398765\u0026ndash;50882942)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e138.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11586.6 (10122.4\u0026ndash;13021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11588.5 (10128.6\u0026ndash;13029.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35634285 (30584669\u0026ndash;40327777)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83251888 (71370051\u0026ndash;94360134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e133.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11211.4 (9768.4\u0026ndash;12598.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11216.4 (9767.8\u0026ndash;12591.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAppendicitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9791 (7366\u0026ndash;12830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31325 (23425\u0026ndash;41525)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e219.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.7 (2.9\u0026ndash;4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.3 (4.1\u0026ndash;6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e43.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11218 (8313\u0026ndash;14852)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35095 (25743\u0026ndash;47297)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e212.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.1 (3.2\u0026ndash;5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.7 (4.4\u0026ndash;7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e39.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21009 (15710\u0026ndash;27719)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66420 (49074\u0026ndash;88488)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e216.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.9 (3\u0026ndash;5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.5 (4.2\u0026ndash;7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e41.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParalytic ileus and intestinal obstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19745 (18409\u0026ndash;21057)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44403 (41509\u0026ndash;47061)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e124.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.9 (6.6\u0026ndash;7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.4 (8\u0026ndash;8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e21.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16834 (15559\u0026ndash;18111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37904 (35346\u0026ndash;40466)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.3 (5\u0026ndash;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.4 (6.1\u0026ndash;6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36579 (33976\u0026ndash;39129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82307 (76873\u0026ndash;87475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.1 (5.8\u0026ndash;6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.3 (7\u0026ndash;7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInguinal, femoral, and abdominal hernia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1782031 (1492320\u0026ndash;2124544)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3883462 (3304836\u0026ndash;4608609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e908.1 (782.2\u0026ndash;1042.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e982.9 (848.4\u0026ndash;1127.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e392574 (302833\u0026ndash;496992)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e839614 (658903\u0026ndash;1041656)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e113.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e164.9 (135.5\u0026ndash;198.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e164.8 (136.3\u0026ndash;196.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2174605 (1808347\u0026ndash;2609627)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4723076 (3972468\u0026ndash;5616761)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e534 (459.6\u0026ndash;615.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e557.5 (478.2\u0026ndash;642.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInflammatory bowel disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10976 (9030\u0026ndash;13425)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28048 (23015\u0026ndash;34315)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e155.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.5 (6.2\u0026ndash;9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.5 (7.1\u0026ndash;10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12854 (10596\u0026ndash;15509)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34903 (28726\u0026ndash;42214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e171.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.4 (7\u0026ndash;10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.5 (7.9\u0026ndash;11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23830 (19646\u0026ndash;28849)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62951 (51710\u0026ndash;76247)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e164.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.9 (6.6\u0026ndash;9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9 (7.5\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVascular intestinal disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2090 (1568\u0026ndash;2808)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5041 (3845\u0026ndash;6649)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e141.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1 (0.8\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.2 (1\u0026ndash;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1245 (956\u0026ndash;1668)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3385 (2649\u0026ndash;4465)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e171.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6 (0.5\u0026ndash;0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.8 (0.7\u0026ndash;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3335 (2532\u0026ndash;4436)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8425 (6508\u0026ndash;11135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e152.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8 (0.7\u0026ndash;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1 (0.8\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e25.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGallbladder and biliary diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e414266 (341700\u0026ndash;503137)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e866630 (716551\u0026ndash;1051831)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e109.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e240.7 (203.7\u0026ndash;285.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e225.4 (193.1\u0026ndash;270.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-6.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1001637 (839993\u0026ndash;1180407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2005036 (1686092\u0026ndash;2398035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e577.3 (494.2\u0026ndash;681.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e496.8 (427.1\u0026ndash;587.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-13.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1415903 (1180582\u0026ndash;1664140)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2871665 (2404941\u0026ndash;3424194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e411.8 (352.1\u0026ndash;486.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e367.3 (316.2\u0026ndash;434.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30567 (27561\u0026ndash;33676)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79735 (72216\u0026ndash;87457)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e160.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.7 (18.8\u0026ndash;22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e24.6 (22.3\u0026ndash;26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e18.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18619 (16435\u0026ndash;21078)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48783 (42957\u0026ndash;55134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e162.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.7 (11.3\u0026ndash;14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.6 (12.9\u0026ndash;16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49186 (44130\u0026ndash;54860)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128518 (115569\u0026ndash;142469)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.7 (15\u0026ndash;18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.4 (17.4\u0026ndash;21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor cirrhosis and other chronic liver diseases specifically, the age-standardized rate per 100,000 individuals saw a decline for both genders. Males experienced a decrease from 31,501.2 (29,310\u0026thinsp;\u0026minus;\u0026thinsp;33,858.5) to 28,515.2 (26,564.7\u0026ndash;30,662.9), a -9.5% change. Females saw a larger reduction from 24,662.3 (22,818.2\u0026ndash;26,596.9) to 22,048.4 (20,327.2\u0026ndash;23,821.9), a -10.6% change. As shown \u003cb\u003ein\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the top three causes of age-standardized prevalence rates for cirrhosis and other chronic liver diseases were MASLD, hepatitis C, and hepatitis B. During the period from 1990 to 2019, MASLD saw an increase in prevalence. In contrast, both hepatitis B and hepatitis C experienced decreases in their age-standardized prevalence rates. Meanwhile, the prevalence of alcohol-related liver disease and other chronic liver diseases remained relatively stable.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUpper digestive system diseases, which include conditions like peptic ulcer disease and gastritis and duodenitis, also saw significant changes. The total prevalence more than doubled for both genders, with minor adjustments in age-standardized rates. For males, the rate slightly increased from 10,741.5 (9,484.3\u0026ndash;11,984.7) to 10,779.3 (9,531.3\u0026ndash;12,013.1), a 0.4% change, and for females, it went from 11,433.3 (10,120.1\u0026ndash;12,713.2) to 11,501.7 (10,217.9\u0026ndash;12,768.2), a 0.6% change.\u003c/p\u003e \u003cp\u003eLastly, other conditions such as appendicitis, paralytic ileus, and various types of hernias also saw increases in age-standardized rates. Specifically, appendicitis rates increased by 43.2% for males and 39.0% for females, paralytic ileus by 21.7% for males and 20.8% for females, and hernias by 8.2% for males and a slight decrease of -0.1% for females.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTrends in DALYs\u003c/h2\u003e \u003cp\u003eFrom 1990 to 2019, the total number of disability-adjusted life years (DALYs) for all digestive diseases increased significantly from approximately 8,127,236 (7,087,624\u0026ndash;9,210,919) to 13,278,484 (11,044,907\u0026ndash;15,915,542), showing a 63.4% increase. However, the age-standardized DALY rate per 100,000 individuals for these diseases decreased from 2,524.8 (2,225.2\u0026ndash;2,869.4) to 1,925.6 (1,639.9\u0026ndash;2,252.9), reflecting a -23.7% change as shown \u003cb\u003ein\u003c/b\u003e Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eComparative Analysis of Raw DALY count and Age-Standardized DALY Rates by Cause Between 1990 and 2019\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRaw DALY count in 1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw DALY count in 2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAge-standardized DALY Rate per 100,000 individuals in 1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAge-standardized DALYs Rate per 100,000 individuals in 2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePercentage Change\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDigestive diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5216032 (4508051\u0026ndash;6013101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8647797 (7156940\u0026ndash;10461767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3334.4 (2876.8\u0026ndash;3950.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2617.8 (2208.2\u0026ndash;3111.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-21.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2911203 (2396479\u0026ndash;3413357)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4630687 (3812822\u0026ndash;5569544)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1721.1 (1469.3\u0026ndash;1956.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1293.5 (1097.5\u0026ndash;1514.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-24.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8127236 (7087624\u0026ndash;9210919)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13278484 (11044907\u0026ndash;15915542)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2524.8 (2225.2\u0026ndash;2869.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1925.6 (1639.9\u0026ndash;2252.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-23.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCirrhosis and other chronic liver diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2762262 (2337721\u0026ndash;3315642)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4481721 (3613857\u0026ndash;5508896)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1967.6 (1663.7\u0026ndash;2388.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1457.3 (1193\u0026ndash;1761.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-25.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1378858 (1116574\u0026ndash;1653059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2142593 (1727089\u0026ndash;2642294)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e935.7 (776.4\u0026ndash;1098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e648 (533.4\u0026ndash;782.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-30.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4141120 (3592417\u0026ndash;4817954)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6624313 (5462975\u0026ndash;8037298)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1450.2 (1254.5\u0026ndash;1682)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1033.9 (876\u0026ndash;1235.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-28.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eUpper digestive system diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e730838 (588064\u0026ndash;925249)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1131218 (901122\u0026ndash;1427775)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e466.4 (377.4\u0026ndash;586.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e328.2 (264.6\u0026ndash;411.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-29.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e505463 (387239\u0026ndash;649104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e923559 (693365\u0026ndash;1255825)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e310.8 (242.5\u0026ndash;391.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e257 (199.8\u0026ndash;341.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-17.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1236301 (1008224\u0026ndash;1529649)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2054778 (1605408\u0026ndash;2689991)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e389.3 (320.8\u0026ndash;475.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e291.9 (234.5\u0026ndash;374.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-25.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePeptic ulcer disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e419957 (316563\u0026ndash;552889)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e550478 (441923\u0026ndash;666105)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e280.5 (213.2\u0026ndash;374.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e169 (138.9\u0026ndash;201)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-39.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e259235 (195182\u0026ndash;338955)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e388303 (311170\u0026ndash;481908)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e157 (124\u0026ndash;192.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e112.6 (93.2\u0026ndash;133.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-28.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e679192 (554588\u0026ndash;832926)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e938781 (777532\u0026ndash;1127559)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e219.1 (183\u0026ndash;267.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e140 (120.1\u0026ndash;161.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-36.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGastritis and duodenitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179739 (117026\u0026ndash;247051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e280584 (198138\u0026ndash;368993)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e102.6 (64.5\u0026ndash;144.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e75.8 (52.9\u0026ndash;99.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-26.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102268 (74078\u0026ndash;135934)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190582 (137908\u0026ndash;254402)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e65.4 (46.8\u0026ndash;85.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e55.8 (40.8\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-14.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282007 (202411\u0026ndash;359973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e471166 (347774\u0026ndash;611127)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e84.3 (59\u0026ndash;108.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e65.7 (49.1\u0026ndash;84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-22.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGastroesophageal reflux disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131142 (67360\u0026ndash;230256)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e300156 (155286\u0026ndash;527280)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e128.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83.3 (42.5\u0026ndash;148.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e83.4 (42.5\u0026ndash;149.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143961 (75267\u0026ndash;254950)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e344674 (180957\u0026ndash;612008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e139.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e88.4 (46\u0026ndash;158.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88.6 (46.1\u0026ndash;159.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e275103 (143637\u0026ndash;485821)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e644831 (337420\u0026ndash;1136189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e134.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e85.9 (44.5\u0026ndash;153.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e86.1 (44.7\u0026ndash;154.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAppendicitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153317 (48664\u0026ndash;258595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145509 (82355\u0026ndash;227633)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-5.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.3 (26.2\u0026ndash;97.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31 (18.2\u0026ndash;49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-47.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118826 (41531\u0026ndash;217973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120841 (71216\u0026ndash;184521)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43.6 (19.9\u0026ndash;79.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.7 (14.4\u0026ndash;35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-47.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e272143 (107665\u0026ndash;467393)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e266350 (171347\u0026ndash;369648)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.4 (26.6\u0026ndash;85.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.7 (18.4\u0026ndash;38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-48.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParalytic ileus and intestinal obstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e690150 (502042\u0026ndash;874495)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1341699 (915084\u0026ndash;1856079)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e333.8 (239.9\u0026ndash;441.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e332.6 (230.6\u0026ndash;438.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e380734 (308761\u0026ndash;469130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e600485 (435628\u0026ndash;829996)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e133.2 (109.2\u0026ndash;163.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e119.9 (89.6\u0026ndash;155.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1070884 (866511\u0026ndash;1297226)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1942184 (1390130\u0026ndash;2664654)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e231.5 (185.4\u0026ndash;288.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e220.7 (163.4\u0026ndash;285.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-4.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInguinal, femoral, and abdominal hernia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e303715 (189253\u0026ndash;410174)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e487130 (364104\u0026ndash;645213)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e137.7 (97.2\u0026ndash;175.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e126 (94.6\u0026ndash;172.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-8.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79732 (36523\u0026ndash;124462)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115800 (67335\u0026ndash;172580)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30.8 (16.4\u0026ndash;42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.5 (14.9\u0026ndash;42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-14.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e383447 (248613\u0026ndash;503128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e602929 (452855\u0026ndash;787932)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83.4 (60.5\u0026ndash;105.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e73.9 (55.5\u0026ndash;99.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-11.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInflammatory bowel disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39580 (19569\u0026ndash;74376)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69062 (49913\u0026ndash;87806)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22.4 (14.2\u0026ndash;31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.7 (15.9\u0026ndash;26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-7.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43202 (16129\u0026ndash;67315)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64697 (38965\u0026ndash;99935)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.6 (10\u0026ndash;26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.8 (10.4\u0026ndash;20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-20.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82782 (42029\u0026ndash;136040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133759 (97840\u0026ndash;178122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.4 (14.1\u0026ndash;27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17.5 (13.8\u0026ndash;22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-14.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVascular intestinal disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56466 (34982\u0026ndash;81122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94653 (74749\u0026ndash;122926)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.5 (26.8\u0026ndash;43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33.8 (25.8\u0026ndash;41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-2.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21198 (14479\u0026ndash;30103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50392 (39736\u0026ndash;60621)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e137.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.9 (12.7\u0026ndash;22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.1 (16.1\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e12.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77664 (52976\u0026ndash;108283)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145045 (116789\u0026ndash;177670)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.2 (21.1\u0026ndash;31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.6 (21\u0026ndash;31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGallbladder and biliary diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92188 (69313\u0026ndash;120870)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202099 (131784\u0026ndash;273031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e119.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e73.3 (55\u0026ndash;102.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e78.9 (52.1\u0026ndash;110.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144682 (103275\u0026ndash;187239)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e257812 (185465\u0026ndash;320609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e90.9 (70.1\u0026ndash;114.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e79.7 (57.4\u0026ndash;103.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-12.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e236870 (184712\u0026ndash;290659)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e459911 (331744\u0026ndash;580737)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e82.1 (66.2\u0026ndash;105)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e79 (57.4\u0026ndash;104.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-3.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169007 (114307\u0026ndash;257654)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e372800 (261940\u0026ndash;551834)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e118.1 (79.5\u0026ndash;182.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e114.2 (80.9\u0026ndash;168.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-3.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56476 (35392\u0026ndash;85859)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107522 (69940\u0026ndash;152554)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38 (26.8\u0026ndash;56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33 (23\u0026ndash;46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-13.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225483 (163301\u0026ndash;314823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e480321 (359618\u0026ndash;657521)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e113.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77.9 (55.6\u0026ndash;113.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e71.8 (53.9\u0026ndash;99.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-7.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eOther digestive diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218509 (141351\u0026ndash;308190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e321906 (232164\u0026ndash;413472)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e121.4 (81.3\u0026ndash;164.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e95.2 (66.4\u0026ndash;129.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-21.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182032 (70505\u0026ndash;354649)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e246987 (150105\u0026ndash;333495)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e101.7 (48.7\u0026ndash;146.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e71.9 (43.2\u0026ndash;101.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-29.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400541 (218966\u0026ndash;658315)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e568893 (394504\u0026ndash;710262)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e112.3 (62.6\u0026ndash;141.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e83.5 (57.8\u0026ndash;105.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-25.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor cirrhosis and other chronic liver diseases, the age-standardized DALY rate per 100,000 individuals saw a decline for both genders. Males experienced a decrease from 1,967.6 (1,663.7\u0026ndash;2,388.8) in 1990 to 1,457.3 (1,193\u0026ndash;1,761.3) by 2019, marking a -25.9% change. Females saw a more significant reduction from 935.7 (776.4\u0026ndash;1,098) to 648 (533.4\u0026ndash;782.8), a -30.7% change.\u003c/p\u003e \u003cp\u003eUpper digestive system diseases, which include conditions like peptic ulcer disease and gastritis and duodenitis, also observed significant changes in age-standardized DALY rates. For males, the rate decreased from 46.4 (377.4\u0026ndash;586.9) to 328.2 (264.6\u0026ndash;411.7), a -29.6% change. For females, the rate dropped from 310.8 (242.5\u0026ndash;391.7) to 257 (199.8\u0026ndash;341.9), a -17.3% change.\u003c/p\u003e \u003cp\u003eOther conditions such as appendicitis, paralytic ileus, and various types of hernias showed changes in their age-standardized DALY rates as well, with appendicitis in males decreasing by 47.7% and in females by 47.9%. Paralytic ileus experienced a slight decrease in the male rate by -0.4% and a more noticeable reduction in females by -10.0%. Hernias decreased by -8.5% in males and \u0026minus;\u0026thinsp;14.0% in females.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTrends in Deaths\u003c/h2\u003e \u003cp\u003eFrom 1990 to 2019, the total number of deaths attributed to all digestive diseases rose significantly as shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. For males, the raw death count increased from 127,904 (109,839\u0026thinsp;\u0026minus;\u0026thinsp;152,830) to 209,458 (175,720\u0026thinsp;\u0026minus;\u0026thinsp;251,923), marking a 63.8% increase. For females, the count increased from 68,936 (58,646\u0026thinsp;\u0026minus;\u0026thinsp;78,852) to 114,239 (97,095\u0026ndash;134,786), reflecting a 65.7% increase. Despite the rise in raw death counts, the age-standardized death rate per 100,000 individuals for these diseases decreased for both genders; males saw a reduction from 109.7 (93.2\u0026ndash;132.5) to 87.1 (74.5\u0026ndash;102.3), a -20.6% change, and females from 58.5 (49.8\u0026ndash;67.5) to 45.6 (39.7\u0026ndash;52.6), a -22.1% change.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Analysis of Raw Death count and Age-Standardized Death Rates by Cause Between 1990 and 2019\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRaw Death count in 1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw Death counts in 2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAge-standardized Death Rate per 100,000 individuals in 1990\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAge-standardized Death Rate per 100,000 individuals in 2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePercentage Change\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDigestive diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127904 (109839\u0026ndash;152830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e209458 (175720\u0026ndash;251923)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e109.7 (93.2\u0026ndash;132.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87.1 (74.5\u0026ndash;102.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-20.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68936 (58646\u0026ndash;78852)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114239 (97095\u0026ndash;134786)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.5 (49.8\u0026ndash;67.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.6 (39.7\u0026ndash;52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-22.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196840 (172532\u0026ndash;224386)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e323697 (275509\u0026ndash;380783)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83.6 (72.9\u0026ndash;97.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65 (56.3\u0026ndash;74.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-22.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCirrhosis and other chronic liver diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78800 (66487\u0026ndash;95410)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124274 (101827\u0026ndash;150290)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e68.7 (57.8\u0026ndash;82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51.1 (42.8\u0026ndash;60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-25.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39477 (32926\u0026ndash;46533)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63431 (52053\u0026ndash;76060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.1 (28.7\u0026ndash;41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.7 (20.3\u0026ndash;29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-27.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118277 (102235\u0026ndash;137488)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187705 (159804\u0026ndash;223646)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.1 (44.2\u0026ndash;59.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.1 (32.1\u0026ndash;43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-27.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eUpper digestive system diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14032 (11182\u0026ndash;18016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18499 (14978\u0026ndash;22060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.1 (9.7\u0026ndash;15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.6 (6.4\u0026ndash;8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-37.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8463 (6752\u0026ndash;10300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13461 (11161\u0026ndash;16034)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.8 (6.2\u0026ndash;9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.9 (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-24.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22495 (19089\u0026ndash;26889)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31960 (26970\u0026ndash;36903)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.0 (8.5\u0026ndash;12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.8 (5.9\u0026ndash;7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-32.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePeptic ulcer disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10945 (8310\u0026ndash;14628)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14296 (11678\u0026ndash;17109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.8 (7.5\u0026ndash;13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.1 (5.1\u0026ndash;7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-37.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6955 (5451\u0026ndash;8616)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11211 (9294\u0026ndash;13306)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.4 (5\u0026ndash;7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.9 (4.1\u0026ndash;5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-23.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17900 (14874\u0026ndash;21753)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25507 (21908\u0026ndash;29473)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.1 (6.8\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.5 (4.8\u0026ndash;6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-32.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGastritis and duodenitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3087 (1655\u0026ndash;4623)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4203 (2395\u0026ndash;5874)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.3 (1.2\u0026ndash;3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5 (0.8\u0026ndash;2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-34.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1508 (854\u0026ndash;2151)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2250 (1349\u0026ndash;2997)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4 (0.8\u0026ndash;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (0.6\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-28.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4595 (2791\u0026ndash;6214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6453 (3900\u0026ndash;8515)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.9 (1.1\u0026ndash;2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.3 (0.8\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-31.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAppendicitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2541 (1031\u0026ndash;4219)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2654 (1514\u0026ndash;4356)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4 (0.7\u0026ndash;2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.9 (0.5\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-35.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1935 (830\u0026ndash;3585)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2073 (1274\u0026ndash;3282)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1 (0.6\u0026ndash;2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6 (0.4\u0026ndash;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-40.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4476 (2198\u0026ndash;7520)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4727 (3152\u0026ndash;6875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2 (0.7\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7 (0.5\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-41.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParalytic ileus and intestinal obstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14286 (10243\u0026ndash;18552)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29442 (20378\u0026ndash;38846)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.3 (8\u0026ndash;15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.5 (8.3\u0026ndash;14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6615 (5456\u0026ndash;8103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12038 (9033\u0026ndash;15528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.3 (3.3\u0026ndash;5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.1 (3.1\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-4.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20901 (16794\u0026ndash;25671)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41480 (30755\u0026ndash;53581)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.6 (5.9\u0026ndash;9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.4 (5.7\u0026ndash;9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-2.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInguinal, femoral, and abdominal hernia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3576 (1728\u0026ndash;4717)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5475 (3733\u0026ndash;8722)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.8 (1.7\u0026ndash;4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5 (1.7\u0026ndash;4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e997 (290\u0026ndash;1534)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1650 (528\u0026ndash;3339)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7 (0.3\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7 (0.2\u0026ndash;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4573 (2438\u0026ndash;5917)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7125 (5005\u0026ndash;11041)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.7 (1.1\u0026ndash;2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5 (1.1\u0026ndash;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-11.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInflammatory bowel disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e904 (548\u0026ndash;1308)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1726 (1299\u0026ndash;2204)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8 (0.5\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7 (0.5\u0026ndash;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-12.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e758 (371\u0026ndash;1130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1300 (903\u0026ndash;1837)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5 (0.3\u0026ndash;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4 (0.3\u0026ndash;0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-20.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1662 (1097\u0026ndash;2308)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3026 (2377\u0026ndash;3901)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6 (0.4\u0026ndash;0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6 (0.5\u0026ndash;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVascular intestinal disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1505 (1151\u0026ndash;1904)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3031 (2309\u0026ndash;3744)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.8 (7.5\u0026ndash;13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5 (1.2\u0026ndash;1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.6 (1.2\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e860 (609\u0026ndash;1073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2243 (1787\u0026ndash;2696)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e160.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.4 (5\u0026ndash;7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (0.7\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.2 (0.9\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2365 (1908\u0026ndash;2887)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5275 (4191\u0026ndash;6180)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e123.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.1 (6.8\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.2 (1\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.4 (1.1\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGallbladder and biliary diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2906 (2161\u0026ndash;4154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6751 (4267\u0026ndash;9709)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e132.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.4 (2.5\u0026ndash;4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.9 (2.5\u0026ndash;5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3663 (2728\u0026ndash;4656)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7505 (5274\u0026ndash;10098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.5 (2.7\u0026ndash;4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.5 (2.5\u0026ndash;4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6569 (5170\u0026ndash;8542)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14256 (9930\u0026ndash;19359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.4 (2.8\u0026ndash;4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.7 (2.6\u0026ndash;5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4381 (2928\u0026ndash;6839)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9484 (6655\u0026ndash;14050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e116.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.6 (2.4\u0026ndash;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.6 (2.5\u0026ndash;5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1576 (1099\u0026ndash;2331)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3081 (2161\u0026ndash;4356)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4 (0.9\u0026ndash;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.2 (0.9\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-14.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5957 (4210\u0026ndash;8614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12565 (9420\u0026ndash;17371)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e110.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.5 (1.7\u0026ndash;3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.3 (1.7\u0026ndash;3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-8.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eOther digestive diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4973 (3234\u0026ndash;6683)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8122 (5604\u0026ndash;11119)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.2 (2.9\u0026ndash;6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.6 (2.4\u0026ndash;5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-14.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4592 (2143\u0026ndash;6681)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7458 (4394\u0026ndash;10472)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.2 (2.1\u0026ndash;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.4 (1.9\u0026ndash;4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-19.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9565 (5295\u0026ndash;12316)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15580 (10658\u0026ndash;19829)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.3 (2.6\u0026ndash;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.5 (2.3\u0026ndash;4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-18.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor cirrhosis and other chronic liver diseases, the age-standardized death rate per 100,000 individuals declined for both genders. Males experienced a decrease from 68.7 (57.8\u0026ndash;82.9) to 51.1 (42.8\u0026ndash;60.5), a -25.6% change. Females saw an even more significant reduction from 34.1 (28.7\u0026ndash;41.1) to 24.7 (20.3\u0026ndash;29.2), a -27.6% change.\u003c/p\u003e \u003cp\u003eUpper digestive system diseases, which include conditions like peptic ulcer disease and gastritis and duodenitis, also observed significant changes in age-standardized death rates. For males, the rate decreased from 12.1 (9.7\u0026ndash;15.8) to 7.6 (6.4\u0026ndash;8.9), a -37.2% change, and for females, it went from 7.8 (6.2\u0026ndash;9.4) to 5.9 (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), a -24.4% change.\u003c/p\u003e \u003cp\u003eOther conditions such as appendicitis, paralytic ileus, and various types of hernias also showed changes in their age-standardized death rates. Specifically, appendicitis in males saw a decrease by 35.7%, and in females by 40.0%. Paralytic ileus experienced a slight increase in the male rate by 1.8% and a reduction in females by -4.7%. Hernias decreased by -10.7% in males and remained stable in females at 0.0%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRisk Factors\u003c/h2\u003e \u003cp\u003eIn 1990, smoking was responsible for 27.31 age-standardized DALYs per 100,000 population (CI: 20.50\u0026ndash;36.63), alcohol use for 660.08 (CI: 498.00\u0026ndash;843.91), drug use for 28.21 (CI: 17.43\u0026ndash;45.67), and high body-mass index for 12.13 (CI: 5.84\u0026ndash;21.53). By 2019, these figures had changed: smoking decreased to 14.78 DALYs (CI: 11.20\u0026ndash;18.69), alcohol use decreased to 515.85 (CI: 382.60\u0026ndash;668.17), drug use increased to 36.63 (CI: 23.24\u0026ndash;55.38), and high body-mass index increased to 19.21 (CI: 10.65\u0026ndash;31.38).\u003c/p\u003e \u003cp\u003eThroughout the years, alcohol remained the leading risk factor despite a decrease in its associated DALYs. Drug use consistently occupied the second spot, with its impact slightly increasing. High body-mass index, which was the lowest in 1990, surpassed smoking by 2019 due to the latter's significant decrease and the former's steady increase. Smoking showed the largest reduction over the 29 years, more than halving its DALYs, reflecting successful public health interventions, as shown \u003cb\u003ein\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eEstimated Annual Percentage Change in ASDR by Country, and Relationship with the SDI and UHC effective coverage index.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAs shown \u003cb\u003ein\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, within the Central Sub-Saharan Africa region, Angola had the highest age-standardized DALY rate in 1990 at 3037.56 (CI: 3956.72\u0026ndash;2235.31) per 100,000 population, while the Central African Republic reported a rate of 3346.52 (CI: 4237.03\u0026ndash;2485.49). By 2019, Gabon, also in the Central region, had the highest rate at 1664.11 (CI: 2085.89\u0026ndash;1277.41), followed by Mozambique in the Eastern region with a rate of 1740.44 (CI: 2172.28\u0026ndash;1386.69). The lowest rates in 1990 were noted in Eritrea at 2584.49 (CI: 3426.00\u0026ndash;1841.94) and Eswatini at 1933.64 (CI: 2614.91\u0026ndash;1549.30) from the Eastern and Southern regions, respectively. In 2019, Eswatini recorded a decreased rate of 1786.09 (CI: 2393.63\u0026ndash;1319.66), and Eritrea reported a rate of 2519.10 (CI: 3276.83\u0026ndash;1942.26).\u003c/p\u003e \u003cp\u003eSSA experienced a notable decline in age standardized DALYs with an EAPC of -0.94 (-1.00 to -0.88). Among the countries in the region, Mauritania had the highest decrease in DALYs, with an EAPC of -2.31 (-2.38 to -2.23). Conversely, Lesotho displayed an upward trend with an EAPC of 0.42 (0.23 to 0.61), indicating an increase in the burden of disease. Equatorial Guinea also saw a substantial decrease with an EAPC of -2.77 (-2.99 to -2.56), and Ethiopia reflected a significant reduction with an EAPC of -1.94 (-2.05 to -1.83). In examining the correlations, EAPC versus the Socio-demographic Index (SDI) for 2019 had a Pearson's r of -0.26 (p-value: 0.080) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, and EAPC against the Universal Health Coverage (UHC) Effective Coverage Index in 2019 had a Pearson's r of -0.38 (p-value: 0.008) as shown \u003cb\u003ein\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary objective of this study was to employ the GBD dataset to provide a comprehensive epidemiological analysis of the burden of digestive diseases in SSA, a region often underrepresented in global health research. This study is notably the first in the region to utilize the GBD dataset specifically for digestive diseases, offering the most up-to-date and comprehensive data available. Furthermore, our analysis also reveals significant correlations between the Estimated Annual Percentage Changes in DALYs and the UHC effective coverage index, underscoring the impact of healthcare access and socio-economic development on health outcomes. By focusing on an understudied region, this research fills significant gaps in our understanding of the epidemiological profile and health impacts associated with these conditions. Overall, our findings reveal notable changes in the prevalence, DALYs, and mortality rates associated with digestive diseases over the past decades. There has been a significant decrease in the age-standardized prevalence and DALY rates for cirrhosis, peptic ulcer disease, and appendicitis, reflecting improvements in public health interventions and healthcare delivery. Conversely, the study identified an increase in the rates of inflammatory bowel disease and vascular intestinal disorders, indicating emerging public health challenges that require urgent attention. These trends underscore the dynamic nature of disease burden in the region and highlight the critical need for targeted health policies to address both declining and emerging health threats.\u003c/p\u003e \u003cp\u003eThe analysis of prevalence data from the GBD dataset reveals significant trends in digestive diseases in Sub-Saharan Africa from 1990 to 2019. Cirrhosis and other chronic liver diseases displayed the most substantial declines in age-standardized prevalence rates, decreasing by 10.6% in females and 9.5% in males. This marked reduction suggests that, despite the near doubling of raw prevalence counts, the standardized risk of digestive diseases may have decreased when accounting for demographic changes. On the other hand, inflammatory bowel disease experienced the most significant increase in age-standardized rates, with a rise of 13.9% for both genders combined.\u003c/p\u003e \u003cp\u003eThe overall rising prevalence of digestive diseases in the region can be attributed to several interconnected factors. As Sub-Saharan Africa undergoes a demographic transition with increasing life expectancy, there is an anticipated growth in the burden of NCDs, including those affecting the digestive system.\u003csup\u003e2\u003c/sup\u003e Improved access to treatments such as antiretroviral therapy contributes to longer life expectancies and, consequently, an increased prevalence of NCDs, including many digestive diseases linked to chronic viruses.\u003csup\u003e2\u003c/sup\u003e Additionally, the increasing incidence of diabetes\u0026mdash;a metabolic disorder linked to various digestive complications\u0026mdash;is further exacerbating the burden of digestive diseases.\u003csup\u003e19\u003c/sup\u003e Challenges related to healthcare access and service delivery, coupled with adverse biological factors, also contribute significantly to the rising disease burden.\u003csup\u003e20\u003c/sup\u003e Moreover, lifestyle changes linked to urbanization and the epidemiological transition, such as unhealthy diets and sedentary lifestyles, are driving the increase in NCDs, including digestive disorders.\u003csup\u003e21\u003c/sup\u003e Environmental and social determinants, such as poverty and limited healthcare access, also play a crucial role in shaping the epidemiology of these diseases in the region.\u003csup\u003e22\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\"In addition to reinforcing trends observed in prevalence, the detailed analysis of DALYs provides crucial insights into the differential impacts of various digestive diseases in Sub-Saharan Africa. For instance, cirrhosis and other chronic liver diseases have shown significant improvements, with age-standardized DALY rates decreasing by 25.9% for males and an even more notable 30.7% for females. Similarly, overall digestive diseases have observed substantial reductions in DALYs, with a 21.5% decrease for males and 24.8% for females, culminating in a combined decrease of 23.7%. Notably, acute appendicitis, despite being the leading cause of abdominal surgical emergencies in the region,\u003csup\u003e23\u003c/sup\u003e has seen some of the largest declines in DALY rates at 48.1%. This significant reduction reflects advancements in surgical management and treatment strategies, contributing positively at the population health level. However, not all trends point towards improvement. Vascular intestinal disorders, for instance, saw an increase in age-standardized DALY rates for females by 12.3%, indicating a worsening disease impact. Such disparities in disease outcomes highlight the critical need for epidemiological analysis to inform health policy and direct resource allocation effectively. The varied responses across different digestive diseases suggest that while some public health strategies have yielded substantial benefits, others need urgent reevaluation to address the increasing burden and complexity of disease patterns, especially in diseases that are on the rise.\u003c/p\u003e \u003cp\u003eThe study highlights significant shifts in the epidemiology of cirrhosis and other chronic liver diseases in Sub-Saharan Africa from 1990 to 2019. The rates of cirrhosis due to Hepatitis B and C have significantly decreased, suggesting successful impacts of improved treatment approaches and vaccination programs. Such findings align with global health initiatives, like the WHO's strategy aiming for a 90% reduction in new cases of chronic hepatitis by 2030, reflecting the potential of targeted healthcare interventions.\u003csup\u003e24\u003c/sup\u003e Despite these advances, the prevalence of metabolic-associated steatohepatitis (MASLD) has notably increased, pointing to the rising impact of metabolic factors on liver health. This uptick contrasts with the declining trend of viral hepatitis-related cirrhosis and underscores the complex and evolving burden of liver diseases. The prevalence of hepatitis B remains high, reported at about 6% in the region, with significant co-infection rates among HIV patients, highlighting the ongoing challenge of managing liver health amid the HIV epidemic.\u003csup\u003e12, 25\u003c/sup\u003e Moreover, with hepatitis B as a leading cause of hepatocellular carcinoma,\u003csup\u003e26\u003c/sup\u003e these findings emphasize the critical need for continuous epidemiological surveillance and adaptive health policies to address both infectious and non-infectious contributors to liver disease in Sub-Saharan Africa.\u003c/p\u003e \u003cp\u003eFurthermore, our findings on regional differences highlight significant variability in disease burden across Sub-Saharan Africa. In 2019, the Republic of Mozambique reported the highest age-standardized DALY rate for digestive diseases among the sampled African countries, with a rate of 1740.44 per 100,000 individuals. This starkly contrasts with the Republic of South Africa, which had the lowest rate at 976.49 per 100,000 individuals the same year. Looking back to 1990, the Federal Democratic Republic of Ethiopia exhibited a particularly high burden with a rate of 3604.30, exemplifying the severe impact of digestive diseases at the time. Over the decades, there has been a general downward trend in these rates across the region. The pronounced regional differences in the burden of digestive diseases underscore the critical need for tailored public health interventions and policies. Such variability demands that health strategies be customized to the specific challenges and resources of each country to effectively address the unique aspects of their healthcare landscapes. This approach is essential for continuing the progress observed in reducing the burden of digestive diseases and for targeting emerging health threats more effectively.\u003c/p\u003e \u003cp\u003eIn addition to quantifying the burden of gastric diseases in SSA, our analysis of GBD data revealed unique insights about risk factors that interplay to influence gastric diseases outcomes. In addition to quantifying the burden of gastric diseases in SSA, our analysis of GBD data revealed a significant trend: a consistent decline in age standardized DALYs attributable to alcohol use from 1990 to 2019. This suggests a positive shift in health outcomes related to alcohol consumption over three decades. Despite this general trend, literature highlights important demographic nuances. For instance, problematic drinking patterns are more prevalent among men, particularly those who are divorced or widowed and current smokers.\u003csup\u003e27\u003c/sup\u003e Moreover, alcohol consumption rates vary significantly by gender and region, being higher in men (60.3% vs. 29.3% in women), with the highest rates in men from Soweto (70.8%) and women from Nanoro (59.8%).\u003csup\u003e27\u003c/sup\u003e These findings indicate that while overall alcohol-related health outcomes have improved, regional and demographic disparities persist. Crucially, the literature also identifies external factors exacerbating these trends, such as aggressive marketing by alcohol companies and low regulatory oversight, which enhance alcohol availability and distribution, negatively impacting national alcohol policies.\u003csup\u003e28\u0026ndash;31\u003c/sup\u003e This constitutes a potential area of intervention that could continue to improve trends in alcohol consumption within SSA region.\u003c/p\u003e \u003cp\u003eTransitioning from the impact of alcohol, another critical risk factor for gastric diseases in SSA is the marked increase in high BMI observed between 1990 and 2019. This rising trend in BMI, linked to many complex health outcomes, must be a subject of focused attention due to its substantial contribution to the burden of gastric diseases across the region. The significance of high BMI and its varying impact across SSA is exemplified by data from the Demographic and Health Survey (DHS). Neupane et al.\u003csup\u003e32\u003c/sup\u003e reported significant regional differences in the prevalence of overweight and obesity within SSA countries. For instance, the pooled prevalence of overweight was lowest in Madagascar (5.6%) and highest in Swaziland (27.7%). Furthermore, the wealth index emerged as the strongest predictor of overweight status in most countries, indicating that socio-economic factors play a crucial role in the spread of obesity and must be considered when directing intervention measures. Of note, our findings reveal a significant correlation between the UHC effective coverage index and health outcomes, with better health coverage associated with faster reductions in DALYs. This accentuates the critical role of access to quality healthcare in mitigating health risks, including those associated with high BMI. Although the correlation between health outcomes and the SDI was not statistically significant, the trend suggests that socio-economic development may also influence health outcomes. Therefore, comprehensive policies that address both healthcare access and socio-economic disparities are essential for improving health across SSA. Further supporting concerns regarding obesity as a risk factor, additional literature points to the increasing burden of childhood obesity in the region. Danquah et al.\u003csup\u003e33\u003c/sup\u003e highlight that the health risks associated with obesity and overweight are particularly problematic in children, given the potential for long-term health implications. This trend underscores the urgency of addressing high BMI from a young age to mitigate its extensive health impacts. Compounding these issues is the ongoing nutrition and physical activity transition within SSA, characterized by increased reliance on energy-saving devices, the availability of inexpensive, high-calorie dense foods, and a general decline in physical activity.\u003csup\u003e34, 35\u003c/sup\u003e Furthermore, sociocultural beliefs that revere and associate obesity with prestige, a good life, and economic value exacerbate the situation.\u003csup\u003e34, 36\u0026ndash;38\u003c/sup\u003e These factors collectively contribute to the normalization of high BMI, challenging public health efforts to combat its rise.\u003c/p\u003e \u003cp\u003eBuilding upon the trends observed in alcohol and high BMI, another evolving challenge in SSA is the moderate increase in drug use. This rise has raised significant public health concerns. Varshney et al. conducted a systematic review which highlights the grave health consequences of nyaope usage, particularly its association with increased HIV infections and the misuse of HIV antiretrovirals.\u003csup\u003e39\u003c/sup\u003e To mitigate these issues, it is crucial that drug prevention and treatment programs in SSA are robust and evidence-based. Strategies such as harm reduction, access to substance abuse treatment, and community-based prevention programs must be intensified. Additionally, targeted educational and rehabilitation interventions are vital for specifically addressing the health risks posed by nyaope and other drugs.\u003csup\u003e39\u003c/sup\u003e The literature indicates that while studies on substance use in SSA do exist, they often focus on specific demographics such as people living with HIV, the homeless, or university students, and may not be nationally representative.\u003csup\u003e40\u0026ndash;46\u003c/sup\u003e This highlights a need for broader and more inclusive research to fully understand and address the drug use landscape across different societal segments. Smoking Transitioning to the risk factor of smoking, our findings show a notable decrease in smoking-related health issues, suggesting some success in public health measures to reduce tobacco use. However, despite these gains, the literature reveals a significant gap in tobacco control efforts within the region. Peer et al. and Mamudu et al. have both pointed out that smoking cessation campaigns and tobacco control interventions are scant in SSA.\u003csup\u003e47, 48\u003c/sup\u003e The region has been described as a \"research desert\" concerning tobacco control, with a clear need for increased investment in both research and training over the past 50 years.\u003csup\u003e48\u003c/sup\u003e The lack of comprehensive tobacco cessation interventions highlights an urgent need for SSA to prioritize and invest in effective tobacco control strategies. Developing targeted campaigns, enhancing public health messaging, and investing in cessation programs are essential steps towards addressing the smoking-related health burden more effectively.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eWhile this study provides valuable insights into the burden of digestive diseases in SSA and utilizes the comprehensive GBD dataset, several limitations must be acknowledged. Firstly, the reliance on secondary data may introduce inherent biases associated with data collection and reporting standards, which can vary significantly across different SSA countries. This could affect the accuracy and comparability of the data on regional and national levels. Additionally, the GBD approach primarily focuses on quantifiable health outcomes, potentially overlooking socio-cultural factors and individual behaviors that significantly influence health. This might lead to an underestimation of the impact of such factors on the prevalence and severity of digestive diseases. Another limitation is the broad geographic and demographic categorization used, which might mask nuanced intra-regional variations and specific population dynamics. Lastly, while this study marks significant progress in highlighting trends and risk factors for digestive diseases in SSA, the findings might not fully represent all sub-populations or the latest shifts in health trends due to the lag in data compilation and publication.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFuture Research\u003c/h2\u003e \u003cp\u003eFuture research on the burden of digestive diseases in Sub-Saharan Africa should aim to address the limitations of current studies by incorporating more real-time, primary data collection and by expanding the scope to include qualitative assessments that capture socio-cultural dynamics and individual behaviors affecting health outcomes. There is also a need for studies to focus on more granular, locally relevant data that can uncover intra-regional variations and allow for targeted interventions. Additionally, longitudinal studies would provide a deeper understanding of the temporal relationships and causative factors behind the observed trends in digestive disease prevalence and outcomes. This approach could facilitate the development of more effective, tailored public health strategies and interventions. Furthermore, integrating genetic, environmental, and lifestyle factors into research models could enhance our understanding of the complex interplay of factors influencing digestive health in this diverse region. Expanding research to include these dimensions will provide a more comprehensive and nuanced understanding of the health challenges and needs in Sub-Saharan Africa.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study leverages the GBD dataset to illuminate the shifting landscape of digestive diseases in Sub-Saharan Africa, revealing marked improvements and emerging health challenges over the last three decades. While declines in diseases like cirrhosis indicate progress due to enhanced healthcare interventions, the rise in conditions such as inflammatory bowel disease and the complex influence of risk factors like high BMI and drug use highlight ongoing public health challenges. These findings represent a call for region-specific health policies and interventions that address both existing and emerging health threats. Continued research is essential to refine our understanding of these diseases and to guide effective public health strategies, ultimately improving health outcomes across the region.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven that we utilized publicly accessible data, no IRB or individual consent was needed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven that we utilize publicly accessible data, individual consent for publication is not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study\u0026apos;s findings come from the GBD study, available on the Institute for Health Metrics and Evaluation website. The GBD offers comprehensive health data worldwide, including mortality, morbidity, and risk factor estimates for various diseases and conditions.\u003c/p\u003e\n\u003cp\u003eThe dataset can be accessed by visiting the IHME GBD Data Tool at https://vizhub.healthdata.org/gbd-compare/#. This interactive tool allows for the exploration of health trends at global, regional, and country levels. The dataset is openly accessible under IHME\u0026apos;s terms, supporting its use for research and policy analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A=Study Design, B=Data collection, C=Statistical analysis, D=Data interpretation, E=Manuscript preparation, F=Literature search, G=Manuscript review)\u003c/p\u003e\n\u003cp\u003eOmar Al Ta\u0026rsquo;ani: ABCDEFG\u003c/p\u003e\n\u003cp\u003eYazan Al-Ajlouni: ADEFG\u003c/p\u003e\n\u003cp\u003eMohammad Tanashat: ADEFG\u003c/p\u003e\n\u003cp\u003eBasile Njei: ADEFG\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the GBD collaborators for the data used in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSurial B, Wyser D, B\u0026eacute;guelin C, Ram\u0026iacute;rez-Mena A, Rauch A, Wandeler G. 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International Journal of Environmental Research and Public Health. 2018;15(12):2732.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Digestive diseases, Sub-saharan Africa, Cirrhosis, DALYs, Healthcare Disparities, Risk Factors","lastPublishedDoi":"10.21203/rs.3.rs-4401782/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4401782/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eIntroduction\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDigestive diseases (DD), such as cirrhosis, upper digestive diseases, inflammatory bowel disease, and pancreatitis, present a significant public health challenge in Sub-Saharan Africa (SSA). The prevalence and impact of these conditions vary widely, highlighting the challenges in managing DD within diverse health systems and sociocultural contexts. Despite their severe impact on morbidity and mortality, they have not garnered as much attention as diseases like HIV/AIDS or malaria. This study utilizes the Global Burden of Disease (GBD) dataset to provide a comprehensive epidemiological overview of DD in SSA, aiming to address gaps in current research and inform effective health policies and interventions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur study utilized data from the GBD dataset spanning 1990 to 2019, which offers extensive data on mortality, incidence, and disability-adjusted life years (DALYs) across 204 countries. We analyzed trends in the prevalence, deaths, and DALYs of DD, calculating percentage changes and estimated annual percentage changes (EAPCs) in age-standardized rates. Linear regression was employed to compute EAPCs, while Pearson correlation analyses were used to assess the relationships between EAPCs and socio-demographic indices.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur study documented a marked increase in total cases of digestive diseases from 1990 to 2019, with prevalence rising by 95.7% for males and 103.5% for females. However, age-standardized prevalence rates per 100,000 individuals declined by 6.9% for males and 7.2% for females. Age-standardized DALY rates for all digestive diseases decreased by 23.7%, and age-standardized death rates reduced by 20.6% for males and 22.1% for females. Specific conditions, such as cirrhosis, experienced significant declines in both DALY and death rates, with reductions of 25.9% and 30.7% for DALYs and 25.6% and 27.6% for death rates in males and females, respectively. The analysis revealed a significant correlation between the EAPCs of DALYs and the Universal Health Coverage (UHC) effective coverage index, with Pearson's r of -0.38 (p-value: 0.008).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur study identified significant shifts in the prevalence of digestive diseases in Sub-Saharan Africa, with declines in conditions like cirrhosis and rises in inflammatory bowel disease, influenced by risk factors such as high BMI and drug use. These insights underscore the urgent need for tailored health policies and interventions that address both decreasing and newly emerging health challenges, enhancing public health strategies and ultimately improving health outcomes in the region.\u003c/p\u003e","manuscriptTitle":"Burden and Disparities of Digestive Diseases in Sub-Saharan Africa","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-23 18:40:07","doi":"10.21203/rs.3.rs-4401782/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":"91465e0a-2d76-41f3-add2-add5ff1182ed","owner":[],"postedDate":"May 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-26T19:03:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-23 18:40:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4401782","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4401782","identity":"rs-4401782","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}