Nationwide trends in hospital admissions and mortality for cardiovascular and renal diseases in Suriname from 2013 to 2022 a retrospective observational study

Nationwide trends in hospital admissions and mortality for cardiovascular and renal diseases in Suriname from 2013 to 2022 a retrospective observational study | 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 Nationwide trends in hospital admissions and mortality for cardiovascular and renal diseases in Suriname from 2013 to 2022 a retrospective observational study Ritesh Dhanpat, Rakesh Gajadhar Sukul, Jerry R. Toelsie, Angele Mendeszoon, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9271418/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Cardiovascular disorders are the leading global cause of death, with more premature mortality in middle-income countries (MICs) than in high-income countries (HICs), challenging health systems. However, data on cardiovascular-related hospital admissions in MICs remain limited. This study assessed such admissions in Suriname, a MIC in South America with high cardiovascular mortality. Methods We conducted a retrospective, hospital-based repeated cross-sectional study using discharge records from Suriname’s three largest public hospitals (71.8% of national admissions). Diagnoses were classified using ICD-10 codes for Cancer, Diabetes (DM), Ischemic Heart Disease (IHD), Stroke, Heart Failure (HF), Renal Disease (RD), and Other Cardiac Diseases (OCD). Age-standardized rates (ASR) were calculated using the WHO standard population. Trends were analyzed using log-linear regression to estimate Annual Percentage Change (APC) with 95% confidence intervals. Results Total age-standardized admissions increased by 6.6% annually (APC 6.6, 95% CI 4.2–9.1). The largest rise occurred in renal disease admissions (APC 14.6) and mortality (APC 11.4). IHD and HF admissions increased steadily, while OCD mortality rose most sharply (APC 19.2). Overall mortality increased (APC 8.2), more in males (10.2%) than females (6.3%), widening the sex gap by 29%. Cancer and diabetes admissions remained stable. Conclusion Suriname faces a rapidly increasing hospital burden and mortality driven by cardiovascular and renal diseases. The sharp rise in renal disease and widening male mortality gap highlight the need for sex-specific prevention and improved hypertension and diabetes management, alongside expanded nephrology and cardiac care capacity. Suriname Cardiovascular Disease Renal Disease Mortality Hospital Admissions Epidemiological Transition Male Disadvantage Introduction Between 2006 and 2016, 71% of global deaths were due to non-communicable disorders (NCDs). Annually, NCDs kill nearly 41 million people, with 77% of these deaths occurring in low- and middle-income countries (1). In 2019, four major NCDs caused about 33.3 million deaths, a 28% increase from 2000. These include cardiovascular disease (17.9 million), cancer (9.3 million), chronic respiratory disease (4.1 million), and diabetes (2.0 million) (WHO, 2024). Countries differ significantly in their progress towards the Sustainable Development Goal (SDG) 3.4(2). Between 2000 and 2019, the number of people who died from chronic respiratory disease fell by 37%, from cardiovascular disease by 27%, and from cancer by 16%. However, diabetes deaths increased by 3%. This overall decline represents a 22.2% global reduction, with regional declines ranging from 13% in Southeast Asia and the Eastern Mediterranean to over 25% in the Western Pacific (26.8%) and Europe (31.2%)(3). Each year, more than 15 million people aged 30 to 69 die from NCDs, with 85% of these premature deaths occurring in low- and middle-income countries(4). Cardiovascular diseases (CVDs) are the leading cause of death worldwide and claim approximately 17.9 million deaths each year. More than 20% of the CVD deaths are due to ischemic heart disease and stroke, and one-third of these deaths occur prematurely. Unfortunately, the age-standardized mortality rate of premature CVD mortality in middle -income countries is more than 4 times higher than in high -income countries, which results in a higher burden expressed as potential life lost (YPLL) and standard expected years of life lost (SEYLL) in these countries (5,6). Additionally, the YLL rate has remained constant over the last thirty years in the MIC, which puts a strain on the health care systems (7). Limited data is available on hospital admissions. A UK study (1999–2011) showed a significant decline in hospital admissions for acute cardiovascular disease and stroke, along with reduced mortality and readmission rates(8). On the other hand, a study in Ghana found that more people were being admitted to the hospital for heart problems and that more were dying from these issues, with heart failure being the main reason and an increase in cases of ischemic heart disease (9). These contrasting trends call for further investigation into cardiovascular disorders' hospital admissions. In Suriname, a middle-income country (MIC), non-communicable diseases (NCDs) are the leading cause of mortality, representing a significant portion of healthcare demands and imposing considerable pressure on the healthcare system (10,11). In 2009, NCDs, including cardiovascular diseases, diabetes, and cancers, accounted for 60% of deaths in Suriname, highlighting a substantial healthcare challenge with increased hospitalizations and outpatient visits since 2005 (12,13). Cardiovascular diseases primarily affect men in Suriname, while diabetes and cancer impact both sexes more equally. The average age for hospitalization due to cardiovascular diseases is around 60 years, whereas diabetes and cancer typically occur around 40 years of age (13). In low- and middle-income countries (LMICs), comprehensive data to monitor progress towards Sustainable Development Goal 3.4 (SDG3.4) are often limited or lacking. Hospitalization data can help evaluate the burden of these conditions in a similar way to other disorders (14). Suriname has a notable prevalence of deaths from cardiovascular diseases (CVDs), constituting 60% of all mortalities(12). However, there is limited data on the trend over the past decade or its projected trajectory in the next decade. This study aims to provide insights into these data trends, to enhance understanding of the predominant health landscape in Suriname. For this reason, we assessed the admission rate as well as the evolution of age at admission and length of stay in hospital due to major cardiovascular disorders. Methods Study design and setting We conducted a retrospective, cross-sectional study of hospital admissions for major cardiovascular and selected non-communicable diseases in Suriname between 1 January 2013 and 31 December 2022. Data was provided by the Ministry pf Health Wellness and Labor and were obtained from the three largest public hospitals (Academic Hospital Paramaribo, ‘s Lands Hospital and Mungra Medical Centre) in the country, which collectively account for approximately 71.8% of all national hospital admissions. This study is not a clinical trial. It is a retrospective observational study based on routinely collected hospital admission and mortality data, and does not involve any intervention or prospective assignment of participants. Clinical trial number: not applicable. Data sources and study population Hospital discharge records were extracted from electronic administrative databases. All admissions with a primary discharge diagnosis corresponding to predefined ICD-10 categories were included. Admissions were considered independent events. Patients with missing discharge status (n = 28) were excluded from mortality analyses. Diagnostic classification Discharge diagnoses were classified according to the International Classification of Diseases, Tenth Revision coding system and grouped into major disease categories relevant to the burden of non-communicable diseases. Cancer diagnoses included codes C00–D49, while diabetes mellitus was defined using codes E10–E14. Cardiovascular conditions were subdivided into several categories: ischemic heart disease was identified using codes I20–I25, stroke using codes I60–I69, and heart failure using code I50. Renal disease was classified using codes N17–N19, capturing both acute and chronic renal failure presentations. In addition, other cardiac diseases were grouped under codes I30–I49 and I51–I52, encompassing a range of non-ischemic cardiac conditions including arrhythmias, inflammatory heart diseases, and other structural cardiac disorders. The primary outcome was annual hospital admission rate per 10,000 population. Secondary outcomes included in-hospital mortality (case-fatality proportion), mean age at admission, and mean length of hospital stay. Rate calculations Population denominators were obtained from the General Bureau of Statistics of Suriname (ABS) for each study year. Mid-year population estimates stratified by age and sex were used to calculate annual admission and mortality rates. Five-year age bands were used to ensure compatibility between hospital data and population denominators. Annual crude admission rates were calculated as: admission rate per 100.000 = \(\:\frac{Number\:of\:admission\:in\:year}{Mid-year\:population\:}\times\:100.000\) In-hospital mortality was defined as the proportion of admissions resulting in death during hospitalization. Age-standardized admission rates (ASR) per 100,000 population were calculated using the direct standardization method. The WHO world standard population was applied as the reference population. Rates were calculated overall and stratified by sex. All analyses were performed separately for men, women, and the total population. Statistical analysis Descriptive statistics were used to summarize admissions, mortality, age, and length of stay. Temporal trends were evaluated using log-linear regression models of the form: $$\:log\left(rate\right)={\beta\:}_{0}+{\beta\:}_{1}\left(year\right)\:$$ All analyses were performed using SPSS, JASP and MedCalc. Statistical significance was defined as p < 0.05 (two-sided). Temporal trends in ASR between 2013 and 2022 were assessed using log-linear regression models. Annual Percentage Change (APC) and corresponding 95% confidence intervals (CI) were derived from the log-linear regression coefficients; APC = \(\:\left({e}^{{\beta\:}_{1}}-1\right)\times\:100\) . Trends were considered statistically significant when the 95% CI did not include zero. A factorial analysis of variance was conducted to examine the effects of condition, sex, and year on patient age and length of hospital stay (LOS). The results are summarized in Table 5 . The study was conducted in accordance with the Declaration of Helsinki and approved by the national ethics committee of the Ministry of Health, Wellness and Labor. Study funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The study was conducted as part of routine institutional and public health collaboration. Results This study included 152,210 hospital admissions between 2013 and 2022 from three major hospitals, representing 71.8% of all national admissions. Of these, 5,832 cases (5.15%) resulted in in-hospital death due to cardiovascular-related conditions. A total of 144,350 patients were discharged alive. Discharge status was unknown for 28 patients, who were excluded from further analysis. In-hospital mortality Between 2013 and 2022, in hospital age-standardized mortality rates demonstrated marked heterogeneity across conditions (Table 1). The most pronounced and statistically significant increases were observed for other cardiac diseases (male APC 21.5%, 95% CI 12.0–31.7; female APC 16.3%, 95% CI 6.5–26.7; total APC 19.2%, 95% CI 11.0–28.0) and renal disease (male APC 12.8%, 95% CI 6.1–19.8; female APC 9.9%, 95% CI 3.0–17.2; total APC 11.4%, 95% CI 6.0–17.1). Overall mortality across all conditions increased significantly (total APC 8.2%, 95% CI 4.1–12.5), with a steeper rise among males (10.2%) compared to females (6.3%), resulting in a persistent male excess mortality (male-to-female ratio in 2022: 1.60). Mortality from ischemic heart disease increased modestly but significantly at the population level (total APC 4.1%, 95% CI 0.2–8.0), whereas trends for cerebrovascular disease and heart failure were not statistically significant. Notably, sex disparities were most evident for cancer and other cardiac diseases, where male mortality rates in 2022 were more than twice those of females, indicating widening gender inequalities in cause-specific mortality. Table 1: Annual Percent Change (APC) in Age-Standardized Mortality Rates (2013–2022) by Sex Condition Male APC % (95% CI) Female APC % (95% CI) Total APC % (95% CI) M/F Ratio (2022) IHD 5.0 (0.5–9.7) 3.2 (−1.0–7.5) 4.1 (0.2–8.0) 1.31 Renal Disease 12.8 (6.1–19.8) 9.9 (3.0–17.2) 11.4 (6.0–17.1) 1.37 Cerebrovascular Disease 2.1 (−1.8–6.1) −0.3 (−4.1–3.5) 0.9 (−2.1–4.0) 1.66 Heart Failure 0.3 (−3.5–4.2) −0.6 (−4.5–3.4) −0.1 (−3.2–3.0) 0.76 Other Cardiac Diseases 21.5 (12.0–31.7) 16.3 (6.5–26.7) 19.2 (11.0–28.0) 2.04 Cancer 6.9 (−1.5–15.6) 2.5 (−5.8–11.2) 4.7 (−0.8–10.5) 2.29 Diabetes Mellitus 3.8 (−2.0–9.8) 4.5 (−1.4–10.7) 4.2 (−0.5–9.1) 1.04 All Conditions 10.2 (5.1–15.5) 6.3 (1.2–11.7) 8.2 (4.1–12.5) 1.60 Within the study period, sex disparities in hospital age-standardized mortality evolved substantially across conditions (Table 2). For all conditions combined, the male-to-female mortality ratio increased from 1.24 to 1.60 (+29%), indicating a widening male excess. The most pronounced shift was observed for renal disease, where the ratio increased from 0.72 to 1.37 (+90%), reflecting a transition from female to male predominance. Cancer mortality demonstrated the largest relative change, reversing from female predominance (0.44) in 2013 to marked male excess (2.29) in 2022. Cerebrovascular mortality showed a moderate widening of male excess (+27%). In contrast, ischemic heart disease and other cardiac diseases, while remaining male-predominant, demonstrated partial narrowing of the sex gap. Diabetes-related mortality showed a substantial reduction in male excess over time (−66%). Overall, these findings indicate dynamic and condition-specific shifts in sex disparities, with a general trend toward increasing male disadvantage in several major categories. Table 2: Evolution of Male-to-Female Mortality Rate Ratios (MRR) by Condition, 2013–2022 Condition 2013 2016 2019 2020 2021 2022 Overall Trend 2013–2022 All Conditions 1.24 1.30 1.37 1.32 1.58 1.60 ↑ Increasing male excess IHD 1.42 0.87 1.91 2.37 4.18 1.31 Fluctuating, overall male predominance Renal Disease 0.72 1.32 1.28 0.96 0.73 1.37 Variable, ending with male excess Cerebrovascular Disease 1.31 1.53 1.34 1.03 1.22 1.66 Progressive male predominance Heart Failure 0.54 0.79 1.47 0.41 1.63 0.76 Highly variable, no clear direction Other Cardiac Diseases 2.64 1.89 1.44 1.55 1.38 2.04 Persistently high male excess Cancer 0.44 0.28 0.77 1.25 3.08 2.29 Shift from female to strong male excess Diabetes Mellitus 3.06 1.67 1.40 1.46 2.62 1.04 Male excess narrowing over time Age-Standardized Admission Rates Between 2013 and 2022, age-standardized hospital admission rates increased significantly for most cardiovascular and renal conditions in Suriname (Table 3). For all conditions combined, the annual increase was substantial and statistically significant in men (APC 7.2%, 95% CI 5.5–9.0), women (APC 6.1%, 95% CI 4.5–7.8), and in the total population (APC 6.6%, 95% CI 5.3–8.0). These findings indicate a sustained rise in overall hospital burden across the study period. Among cardiovascular conditions, ischemic heart disease (IHD) demonstrated a marked and consistent upward trend (Table 3). The APC was 7.6% (95% CI 5.2–10.1) in men and 5.0% (95% CI 3.0–7.1) in women, corresponding to an overall annual increase of 6.3%. Absolute age-standardized rates increased from 1,067.3 per 100,000 population in 2013 to 1,874.5 per 100,000 in 2022, representing one of the largest absolute increases observed. Cerebrovascular disease admissions also increased significantly (Table 3), with APCs of 5.3% (95% CI 2.4–8.3) in men and 4.2% (95% CI 1.5–7.0) in women. The overall APC was 5.0% (95% CI 2.8–7.2), indicating a steady rise in stroke-related hospitalizations throughout the study period. Similarly, heart failure admissions rose significantly in both sexes (Table 3). The APC was 6.2% (95% CI 1.8–10.8) in men and 5.6% (95% CI 2.1–9.3) in women, yielding an overall APC of 6.0% (95% CI 2.8–9.4). Other cardiac diseases exhibited a significant increase in men (APC 8.7%, 95% CI 2.0–15.8) and in the total population (APC 6.6%, 95% CI 1.5–12.0), whereas the increase in women did not reach statistical significance. Renal disease showed the steepest rise among all examined conditions (Table 3). Age-standardized rates more than tripled during the study period, increasing from 128.3 per 100,000 in 2013 to 421.9 per 100,000 in 2022. The APC was 12.5% (95% CI 7.8–17.4) in men and 16.2% (95% CI 8.4–24.6) in women, with an overall annual increase of 14.6% (95% CI 9.6–19.9). This represents the most rapidly expanding contributor to hospital burden over the decade. In contrast, cancer and diabetes mellitus admissions did not demonstrate statistically significant trends over time (Table 3). For cancer, a downward trend was observed in men (APC −4.5%, 95% CI −9.2 to 0.4), although this did not reach statistical significance, while rates in women remained stable. Diabetes mellitus admissions also showed no significant changes, with APC estimates of 1.9% (95% CI −2.6–6.6) in men and −0.8% (95% CI −5.6–4.2) in women, indicating overall stability. Table 3: Annual Percent Change (APC) in Age-Standardized Admission Rates, 2013–2022 Condition Male APC % (95% CI) Female APC % (95% CI) Total APC % (95% CI) Ischemic Heart Disease 7.6 (5.2–10.1) 5.0 (3.0–7.1) 6.3 (4.6–8.0) Renal Disease 12.5 (7.8–17.4) 16.2 (8.4–24.6) 14.6 (9.6–19.9) Cerebrovascular Disease 5.3 (2.4–8.3) 4.2 (1.5–7.0) 5.0 (2.8–7.2) Heart Failure 6.2 (1.8–10.8) 5.6 (2.1–9.3) 6.0 (2.8–9.4) Other Cardiac Diseases 8.7 (2.0–15.8) 4.9 (−0.8–10.9) 6.6 (1.5–12.0) Cancer −4.5 (−9.2–0.4) −0.6 (−5.0–4.1) −2.0 (−5.9–2.0) Diabetes Mellitus 1.9 (−2.6–6.6) −0.8 (−5.6–4.2) 0.5 (−3.6–4.8) All Conditions 7.2 (5.5–9.0) 6.1 (4.5–7.8) 6.6 (5.3–8.0) Sex Differences Over Time Table 4 depicts the sex disparities in age-standardized hospital admission rates evolving heterogeneously across conditions during 2013–2022. For ischemic heart disease, the male-to-female rate ratio increased from 1.27 in 2013 to 1.60 in 2022, indicating a widening male predominance over time. A similar pattern was observed for cerebrovascular disease, where the rate ratio rose from 1.24 to 1.38. In contrast, heart failure demonstrated persistent female predominance throughout the study period, with male-to-female rate ratios remaining below unity (0.79 in 2013 and 0.81 in 2022). Cancer admissions showed a stable female predominance, with the rate ratio declining slightly from 0.37 to 0.26 over time. Renal disease displayed substantial temporal variability, with early male predominance (2.26 in 2013), a mid-period reversal favoring females, and renewed male excess by 2022 (1.44), suggesting dynamic shifts in sex-specific burden or healthcare utilization. For all conditions combined, overall admissions shifted from near parity at baseline (rate ratio 0.99 in 2013) to modest male predominance by 2022 (1.10). Collectively, these findings indicate that while overall hospital burden increased in both sexes, the magnitude and direction of sex disparities varied considerably by diagnostic category, with widening male excess particularly evident for ischemic and cerebrovascular disease. Table 4: Evolution of Male-to-Female Admission Rate Ratios (ASR), 2013–2022 Condition 2013 2016 2019 2020 2021 2022 Overall Trend 2013–2022 Ischemic Heart Disease 1.27 1.27 1.67 1.51 1.54 1.60 Increasing male predominance Renal Disease 2.26 0.84 0.96 1.37 1.77 1.44 Fluctuating, overall male predominance Cerebrovascular Disease 1.24 1.30 1.65 1.28 1.28 1.38 Slight increase in male predominance Heart Failure 0.79 0.77 0.72 0.89 0.87 0.81 Persistent female predominance Other Cardiac Diseases 0.82 0.97 1.00 1.01 1.15 1.17 Shift toward male predominance Cancer 0.37 0.27 0.26 0.34 0.26 0.26 Persistent strong female predominance Diabetes Mellitus 1.02 0.83 1.02 1.16 1.06 1.17 Slight increase in male predominance All Conditions 0.99 0.94 1.13 1.10 1.08 1.10 Gradual shift toward male predominance Healthcare outcome Table 5 presents trends in mean age at admission. Across all conditions combined, the mean age of hospitalized patients increased modestly between 2013 and 2022. In both years, male patients were slightly older than female patients, and the difference between sexes remained statistically significant. Pronounced sex differences in age were observed for several disease categories. In neoplasms, female patients were admitted at a substantially younger age than males in both study years. Although the mean age increased for both sexes over time, this gender difference remained significant in 2022. For diabetes mellitus, the age pattern differed by sex. The mean age of male patients remained relatively stable over the study period, whereas female patients showed a significant increase in mean age, resulting in women presenting slightly older than men by 2022. Cardiovascular conditions showed a clear aging pattern. In ischemic heart disease and other cardiac diseases, the mean age of admission increased over time for both sexes, with female patients consistently presenting at older ages than males in 2022. A similar pattern was observed in cerebrovascular disease, where women were older than men at admission in both study years. Table 5 also presents trends in mean length of hospital stay. The average length of hospital stay across all conditions decreased significantly between 2013 and 2022 for both sexes, suggesting improvements in hospital throughput or clinical management. This decline was particularly evident in acute cardiovascular conditions such as heart failure and cerebrovascular disease, where LOS decreased for both men and women. Table 5: Mean age and mean length of hospital stay (LOS) by condition, sex, and year. * indicate a statistically significant change between 2013 and 2022 within the same sex (p < 0.05). ! indicates a statistically significant difference between male and female Age Length of hospital stay Male Female Male Female Condition 2013 2022 2013 2022 2013 2022 2013 2022 All conditions 59.05 60.12* ! 56.89 ! 58.39* ! 10.14 8.24* ! 9.60 8.35* ! Cancer 55.90 61.08* ! 47.65 ! 53.17 *! 94.32 8.38 61.81 55.47 ! Cerebrovascular Diseases 61.10 62.27 64.10 ! 65.13 ! 12.58 10.06* ! 13.07 11.85 Diabetes Mellitus 59.04 58.56 57.27 59.31* ! 14.17 11.44* ! 12.20 110.36* ! Heart Failure 64.39 63.17 66.88 67.84 ! 9.04 6.44* ! 8.87 6.81* ! Ischemic Heart Disease 57.13 58.08 59.84 ! 61.60* ! 49.27 48.30 5.10 ! 44.52* ! Other Cardiac Diseases 58.72 65.99* ! 63.94 ! 70.64* ! 64.43 42.89 9.65 ! 48.23* ! Renal Diseases 61.02 59.57 56.91 ! 61.26* ! 16.77 161.66* ! 142.84 ! 147.29 However, several conditions deviated markedly from this general pattern. In the diabetes mellitus cohort, LOS decreased for male patients but increased dramatically among female patients. By 2022, the mean LOS for females reached 110.36 days, representing both a substantial temporal increase and a pronounced gender disparity compared with male patients. Renal diseases also showed a striking change in hospital resource use. While LOS was relatively moderate for men in 2013, it increased sharply by 2022, reaching a mean of 161.66 days. Female patients already exhibited long hospital stays in 2013, and LOS remained similarly elevated in 2022, effectively narrowing the initial gender difference. Other cardiac diseases demonstrated a mixed pattern. Although male LOS decreased over time, female LOS increased substantially, producing a pronounced divergence between sexes in 2022. Taken together, the findings suggest divergent patterns across disease categories. Acute cardiovascular conditions, such as heart failure and ischemic heart disease, showed shorter hospital stays over time and relatively converging outcomes between sexes. In contrast, chronic metabolic and organ-failure conditions—including diabetes mellitus, renal disease, and certain oncological conditions—were characterized by increasing complexity, older patient populations, and widening gender differences in hospital resource utilization. Discussion This nationwide analysis of hospital data in Suriname from 2013 to 2022 reveals a dual escalation in age-standardized hospital admissions and mortality for major non-communicable diseases (NCDs). With a sustained 6.6% annual increase in total admissions and a significant 8.2% rise in overall mortality , these findings indicate a rapidly intensifying cardiometabolic burden that is currently outpacing the capacity of the national healthcare system. The study highlights a critical shift in Suriname’s cardiovascular landscape. While ischemic heart disease (IHD) saw moderate growth in both admissions (6.3% APC) and mortality (4.1% APC), the most dramatic shifts occurred in heart failure and non-ischemic conditions (15). Mortality from "other cardiac diseases"—a category including arrhythmias and cardiomyopathies—exhibited the steepest increase of all categories ( 19.2% APC ). Unlike many high-income nations that have achieved declines in IHD mortality through aggressive primary prevention and lipid-lowering therapies, Suriname’s upward trend suggests the country is in an earlier, more volatile phase of the cardiovascular transition. Here, the rising prevalence of metabolic risk factors is expanding faster than the implementation of preventive infrastructure (5,16,17). Renal disease emerged as the most consistent and concerning healthcare challenge identified in this study. Admissions for renal conditions more than tripled ( 14.6% APC ), mirrored by an 11.4% annual increase in mortality . The simultaneous rise in both utilization and death suggests a genuine increase in disease severity and late-stage presentations rather than improved detection alone. Given the well-established links between diabetes, hypertension, and chronic kidney disease (CKD) in the Surinamese population, this trajectory forecasts an unsustainable demand for renal replacement therapy (RRT) (18). From a health systems perspective, renal disease represents a high-cost, high-mortality pathway that threatens to exhaust tertiary care resources if upstream management is not radically strengthened. A defining feature of the study period was the widening "male disadvantage." While hospital admissions were near parity in 2013, a clear male predominance emerged by 2022, particularly in IHD and cerebrovascular disease. More strikingly, the male-to-female mortality ratio increased by 29% across all conditions. This pattern suggests that improvements in prevention and early detection have not occurred uniformly across sexes. Men in Suriname may be disproportionately affected by delayed healthcare utilization, higher behavioral risk profiles (such as smoking), and poorer adherence to long-term management for hypertension (19). This widening gap aligns with regional trends in the Americas, where traditional barriers to primary care engagement often result in higher premature NCD mortality among men (20). Renal disease represents a particularly concerning finding. While admissions for renal disease increased dramatically, mortality remained relatively stable. This divergence suggests either improved survival among hospitalized renal patients or increasing admission of less severe cases. Nonetheless, the rapid growth in renal admissions highlights the expanding burden of chronic kidney disease and its cardiovascular implications, emphasizing the need for strengthened early detection and outpatient management strategies. In contrast to the sharp rises in cardiovascular and renal categories, cancer and diabetes admissions remained relatively stable. For diabetes, this apparent stability—despite its role as a primary driver of heart and kidney failure—likely reflects a shift in clinical coding or hospital utilization. Patients may increasingly be admitted for the consequences of diabetes (e.g., CKD or heart failure) rather than for primary glycemic control. This pattern underscores the importance of effective primary care systems capable of preventing progression to acute hospitalization (21). The stability in cancer admissions, coupled with a persistent female predominance, likely reflects established sex-specific screening programs and healthcare-seeking behaviors already integrated into the system. The progressive increase in mean age across most major cardiovascular categories reflects population ageing and possibly improved survival from chronic conditions. At the same time, the significant reduction in length of hospital stay across most conditions suggests improvements in efficiency, clinical pathways, or discharge planning. The most pronounced reductions were observed in other cardiac diseases and stroke, which may indicate advances in standardized acute care management. Nevertheless, shortening hospital stays must be carefully monitored to ensure that reductions do not compromise post-discharge outcomes. Overall, the findings suggest a healthcare system adapting to rising cardiovascular demand and increasing mortality in several major categories. However, the rapid growth in admissions—particularly for renal and ischemic heart disease—and the widening gender mortality gap indicate areas requiring targeted intervention. Strengths and Limitations Strengths Longitudinal Scope : This study utilizes a robust, 10-year dataset (2013–2022), providing a comprehensive view of long-term epidemiological shifts rather than a cross-sectional "snapshot." Nationwide Representation : By incorporating nationally aggregated hospital data, the findings reflect the actual clinical burden on the Surinamese health system rather than localized or single-center trends. Methodological Rigor : The use of age-standardized rates allows for meaningful comparisons over time by removing the confounding effect of Suriname’s aging population. Formal Trend Estimation : The application of the Average Annual Percent Change (APC) provides a statistically sound measure of the magnitude and direction of trends, allowing for the identification of significant disparities between sexes and disease categories. Limitations Inpatient Bias : The analysis is based exclusively on hospital admissions and mortality. Consequently, it does not capture the significant "silent" burden of NCDs managed in outpatient primary care or undiagnosed cases in the community. Data Quality and Coding : Trends may be influenced by evolving clinical coding practices (ICD-10 transitions), changes in hospital reporting accuracy, or improvements in diagnostic technology over the decade. Ecological Design : As an ecological study, these findings describe population-level trends; they cannot be used to establish direct causal links between specific individual risk factors (e.g., smoking or diet) and the observed outcomes. External Shocks : The log-linear APC model assumes a constant rate of change. It may not fully account for non-linear "shocks" to the healthcare system, most notably the COVID-19 pandemic , which may have temporarily suppressed admission rates or skewed mortality data between 2020 and 2022. Secondary Prevention Gap : The data does not distinguish between first-time admissions and readmissions, which limits our ability to evaluate the specific effectiveness of secondary prevention programs. Conclusion Over the past decade, Suriname has transitioned into a period of intensifying cardiometabolic morbidity and mortality. The concurrent rise in hospitalizations and deaths related to cardiovascular and renal diseases signals an urgent public health crisis. The most alarming trend is the tripling of the renal disease burden, which represents a high-cost trajectory that threatens health system sustainability. Policy implication The widening sex disparity—specifically the increasing mortality risk among men—highlights a critical need for gender-sensitive healthcare delivery. To achieve Sustainable Development Goal (SDG) 3.4, which aims to reduce premature mortality from non-communicable diseases (NCDs), Suriname must adopt a comprehensive and strategic approach to strengthening its health system. A central priority should be the reinforcement of integrated primary care services, particularly in the management of hypertension and diabetes. Effective detection, monitoring, and long-term management of these conditions are essential to prevent progression to severe complications such as end-stage renal disease and advanced cardiac failure. In addition, public health strategies should place greater emphasis on engaging men in preventive healthcare. Evidence consistently shows that men are less likely to seek early screening or adhere to long-term treatment, which contributes to higher rates of advanced disease and mortality. Developing targeted interventions that promote early health-seeking behavior and sustained treatment adherence among men is therefore critical. Finally, given the growing burden of complex NCD cases, Suriname must expand its specialized care capacity, particularly in nephrology and advanced cardiac services. Strengthening these services will be necessary to effectively manage the increasing number of patients presenting with high-acuity conditions requiring specialized and resource-intensive care. Declarations Author Contribution R.D. (Ritesh Dhanpat) performed the statistical analyses, interpreted the data, and drafted the manuscript.R.B. (Robbert Bipat) and J.T. (Jerry Toelsie) supervised the study, contributed to the methodological structure of the manuscript, and provided critical revisions with respect to content, organization, and scientific presentation.V.J. (Vanita Jairam) and A.M. (Angelle Mendeszoon) contributed to data acquisition and supported the data collection process within their respective hospitals, and reviewed the manuscript with relevant feedback.R.G.S. (Rakesh Gajadhar Sukul) facilitated access to the national dataset through the Ministry of Health, Wellness and Labor and contributed to data acquisition.All authors approved the final manuscript and agree to be accountable for the work. Acknowledgement The authors gratefully acknowledge the Ministry of Health, Wellness and Labor of Suriname for granting access to the national hospital admission data used in this study. The use of these data was made possible through their support and approval. The authors further recognize the contribution of the national medical registration system in enabling this research. Data Availability The data that support the findings of this study are not publicly available due to restrictions related to patient confidentiality and institutional data protection policies. The dataset consists of routinely collected hospital admission data obtained through national medical registration systems and the Ministry of Health of Suriname.Access to these data is subject to approval by the relevant institutional authorities and the Ministry of Health, Wellness and Labor of Suriname. Researchers who meet the criteria for access to confidential data may submit a reasonable request to the corresponding author, subject to institutional permission and applicable data protection regulations. References Di M, Di Cesare CM. Global trends of chronic non-communicable diseases risk factors [Internet]. 2019. Available from: https://academic.oup.com/eurpub/article/29/Supplement_4/ckz185.196/5624434 Martinez R, Soliz P, Mujica OJ, Reveiz L, Campbell NRC, Ordunez P. The slowdown in the reduction rate of premature mortality from cardiovascular diseases puts the Americas at risk of achieving SDG 3.4: A population trend analysis of 37 countries from 1990 to 2017. J Clin Hypertens. 2020 Aug 1;22(8):1296–309. doi:10.1111/JCH.13922 PubMed PMID: 33289261. World Health Statistics. SDGs Sustainable Development Goals. 2023. WHO. WHO newsroom NCD factsheet. 2024. Kyu HH, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet. 2018 Nov;392(10159):1859–922. doi:10.1016/S0140-6736(18)32335-3 Hay SI, Ong KL, Santomauro DF, Bhoomadevi A, Aalipour MA, Aalruz H, et al. Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2…. Lancet. 2025 Oct 18;406(10513):1873. doi:10.1016/S0140-6736(25)01637-X PubMed PMID: 41092926. Martinez R, Lloyd-Sherlock P, Soliz P, Ebrahim S, Vega E, Ordunez P, et al. Trends in premature avertable mortality from non-communicable diseases for 195 countries and territories, 1990–2017: a population-based study. Lancet Glob Health. 2020 Apr 1;8(4):e511–23. doi:10.1016/S2214-109X(20)30035-8 PubMed PMID: 32199120. Krumholz HM, Normand SLT, Wang Y. Trends in hospitalizations and outcomes for acute cardiovascular disease and stroke, 1999-2011. Circulation. Lippincott Williams and Wilkins; 2014. p. 966–75. doi:10.1161/CIRCULATIONAHA.113.007787 PubMed PMID: 25135276. Appiah LT, Sarfo FS, Agyemang C, Tweneboah HO, Appiah NABA, Bedu-Addo G, et al. Current trends in admissions and outcomes of cardiac diseases in Ghana. Clin Cardiol. 2017 Oct 1;40(10):783–8. doi:10.1002/clc.22753 PubMed PMID: 28692760. Prevention and control of noncommunicable diseases and mental disorders in Suriname: Investment case [Internet]. doi:10.37774/9789275130278 Punwasi W B. Doodsoorzaken_in_Suriname. Doodsoorzaken in Suriname: 2010-2011. 2012. World Health Organization 2026 data.who.int, Suriname [Country overview]. (Accessed on 16 March 2026). Ministry of Health Suriname SURINAME National Action Plan for the Prevention and Control of Noncommunicable Diseases. 2012. Kashyap S, Gombar S, Yadlowsky S, Callahan A, Fries J, Pinsky BA, et al. Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening. Journal of the American Medical Informatics Association. 2020 Jul 1;27(7):1026–131. doi:10.1093/jamia/ocaa076 PubMed PMID: 32548636. Sairras S, Baldew SS, van der Hilst K, Shankar A, Zijlmans W, Lichtveld M, et al. Heart Failure Hospitalizations and Risk Factors among the Multi-Ethnic Population from a Middle Income Country: The Suriname Heart Failure Studies. J Natl Med Assoc. 2021 Apr 1;113(2):177–86. doi:10.1016/j.jnma.2020.08.010 PubMed PMID: 32928542. da Silva RA, de Araújo Fonseca LG, de Santana Silva JP, Lima NMFV, Gualdi LP, Lima INDF. The impact of the strategic action plan to combat chronic non-communicable diseases on hospital admissions and deaths from cardiovascular diseases in Brazil. PLoS One. 2022 Jun 1;17(6 June). doi:10.1371/journal.pone.0269583 PubMed PMID: 35675279. Forouzanfar MH, Afshin A, Alexander LT, Biryukov S, Brauer M, Cercy K, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016 Oct 10;388(10053):1659. doi:10.1016/S0140-6736(16)31679-8 PubMed PMID: 27733284. Nannan Panday R, Haan Y, Diemer F, Punwasi A, Rommy C, Heerenveen I, et al. Chronic kidney disease and kidney health care status: the healthy life in Suriname (HeliSur) study. Intern Emerg Med. 2019 Mar 11;14(2):249–58. doi:10.1007/s11739-018-1962-3 PubMed PMID: 30361850. K D Bertakis, R Azari, L J Helms, E J Callahan, J A Robbins. Gender differences in the utilization of health care services. The Journal of family practice . 2000;49.2:147–52. Ali Ch I, Health St Anthony Hospital Oklahoma City SO, Ali Qasim S, Zafar H, Maryam S, Qasim Shaheed Mohtarma Benazir Bhutto Medical College M, et al. Premature Coronary Artery Disease Related Mortality in the United States: Regional, Gender, and Racial Disparities – Insights from the CDC WONDER Database (1999–2023). medRxiv. 2025 Dec 18;2025.12.16.25342435. doi:10.64898/2025.12.16.25342435 Shih-Chuan Chou, Jeremiah D. Schuur, Olesya Baker. Changes in Emergency Department Care Intensity from 2007-16: Analysis of the National Hospital Ambulatory Medical Care Survey. Western Journal of Emergency Medicine. 2020;21(2):209–2016. doi:10.5811/westjem.2019.10.43497 PubMed PMID: 32191176. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 16 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers agreed at journal 10 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers invited by journal 04 May, 2026 Editor invited by journal 13 Apr, 2026 Editor assigned by journal 11 Apr, 2026 Submission checks completed at journal 08 Apr, 2026 First submitted to journal 08 Apr, 2026 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. 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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-9271418","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623991825,"identity":"efc6b246-b54a-4000-afb6-3c9c08a31962","order_by":0,"name":"Ritesh Dhanpat","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYDCCG1CaDYiZGSpAJHMDMVoMGNjYQFrOgLQwEqkFZA0zYxuIQ0AL3+3mZ48Lav7k88k3H/5cOK82mr8dqOVHxTacWiTvHDM3nnHMwLKNjS1Neua247kzDjM2MPacuY1Ti8GNBDNpHjYDAzY2HjNm3m3HchuAWoAuxKcl/Zs0zz+QFv7Pn3nnHMudT1hLjpk0bxvYFgZp3oaa3A2EtEjeyCmTntlnDNSSBnThsQO5G4FaDuLzC9+N9G3SBd/kDIAB9vgzT01d7rzzhw8++FGBWwsIMCOxD4PJA3jVo2mpI6R4FIyCUTAKRiAAAAV+VTKTCI3kAAAAAElFTkSuQmCC","orcid":"","institution":"Ministry of Health of the Government of Suriname","correspondingAuthor":true,"prefix":"","firstName":"Ritesh","middleName":"","lastName":"Dhanpat","suffix":""},{"id":623991827,"identity":"c4748ed4-3ca0-486c-85f2-484561850d04","order_by":1,"name":"Rakesh Gajadhar Sukul","email":"","orcid":"","institution":"Ministry of Health of the Government of Suriname","correspondingAuthor":false,"prefix":"","firstName":"Rakesh","middleName":"Gajadhar","lastName":"Sukul","suffix":""},{"id":623991828,"identity":"60c2a331-20cf-482d-9d0e-1ac638480746","order_by":2,"name":"Jerry R. Toelsie","email":"","orcid":"","institution":"Anton de Kom University of Suriname","correspondingAuthor":false,"prefix":"","firstName":"Jerry","middleName":"R.","lastName":"Toelsie","suffix":""},{"id":623991829,"identity":"39df4eb5-205c-4a9d-b76f-40313715b6f5","order_by":3,"name":"Angele Mendeszoon","email":"","orcid":"","institution":"’s Lands Hospitaal","correspondingAuthor":false,"prefix":"","firstName":"Angele","middleName":"","lastName":"Mendeszoon","suffix":""},{"id":623991831,"identity":"163d9034-8eb3-4e86-85c6-89199802b2ff","order_by":4,"name":"Vanita Jairam","email":"","orcid":"","institution":"Academic Hospital Paramaribo","correspondingAuthor":false,"prefix":"","firstName":"Vanita","middleName":"","lastName":"Jairam","suffix":""},{"id":623991832,"identity":"5cfb8cd7-598c-4f43-9390-93d7db04c622","order_by":5,"name":"Robbert Bipat","email":"","orcid":"","institution":"Anton de Kom University of Suriname","correspondingAuthor":false,"prefix":"","firstName":"Robbert","middleName":"","lastName":"Bipat","suffix":""}],"badges":[],"createdAt":"2026-03-30 19:08:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9271418/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9271418/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107705950,"identity":"f4a0cfb4-8a07-45ef-ad2d-96f251415193","added_by":"auto","created_at":"2026-04-24 09:15:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":423849,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9271418/v1/0a76296b-217f-4b3d-b5f8-e220212792d5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Nationwide trends in hospital admissions and mortality for cardiovascular and renal diseases in Suriname from 2013 to 2022 a retrospective observational study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBetween 2006 and 2016, 71% of global deaths were due to non-communicable disorders (NCDs). Annually, NCDs kill nearly 41\u0026nbsp;million people, with 77% of these deaths occurring in low- and middle-income countries (1). In 2019, four major NCDs caused about 33.3\u0026nbsp;million deaths, a 28% increase from 2000. These include cardiovascular disease (17.9\u0026nbsp;million), cancer (9.3\u0026nbsp;million), chronic respiratory disease (4.1\u0026nbsp;million), and diabetes (2.0\u0026nbsp;million) (WHO, 2024). Countries differ significantly in their progress towards the Sustainable Development Goal (SDG) 3.4(2).\u003c/p\u003e \u003cp\u003eBetween 2000 and 2019, the number of people who died from chronic respiratory disease fell by 37%, from cardiovascular disease by 27%, and from cancer by 16%. However, diabetes deaths increased by 3%. This overall decline represents a 22.2% global reduction, with regional declines ranging from 13% in Southeast Asia and the Eastern Mediterranean to over 25% in the Western Pacific (26.8%) and Europe (31.2%)(3). Each year, more than 15\u0026nbsp;million people aged 30 to 69 die from NCDs, with 85% of these premature deaths occurring in low- and middle-income countries(4).\u003c/p\u003e \u003cp\u003eCardiovascular diseases (CVDs) are the leading cause of death worldwide and claim approximately 17.9\u0026nbsp;million deaths each year. More than 20% of the CVD deaths are due to ischemic heart disease and stroke, and one-third of these deaths occur prematurely. Unfortunately, the age-standardized mortality rate of premature CVD mortality in middle -income countries is more than 4 times higher than in high -income countries, which results in a higher burden expressed as potential life lost (YPLL) and standard expected years of life lost (SEYLL) in these countries (5,6). Additionally, the YLL rate has remained constant over the last thirty years in the MIC, which puts a strain on the health care systems (7).\u003c/p\u003e \u003cp\u003eLimited data is available on hospital admissions. A UK study (1999\u0026ndash;2011) showed a significant decline in hospital admissions for acute cardiovascular disease and stroke, along with reduced mortality and readmission rates(8). On the other hand, a study in Ghana found that more people were being admitted to the hospital for heart problems and that more were dying from these issues, with heart failure being the main reason and an increase in cases of ischemic heart disease (9). These contrasting trends call for further investigation into cardiovascular disorders' hospital admissions.\u003c/p\u003e \u003cp\u003eIn Suriname, a middle-income country (MIC), non-communicable diseases (NCDs) are the leading cause of mortality, representing a significant portion of healthcare demands and imposing considerable pressure on the healthcare system (10,11). In 2009, NCDs, including cardiovascular diseases, diabetes, and cancers, accounted for 60% of deaths in Suriname, highlighting a substantial healthcare challenge with increased hospitalizations and outpatient visits since 2005 (12,13). Cardiovascular diseases primarily affect men in Suriname, while diabetes and cancer impact both sexes more equally. The average age for hospitalization due to cardiovascular diseases is around 60 years, whereas diabetes and cancer typically occur around 40 years of age (13). In low- and middle-income countries (LMICs), comprehensive data to monitor progress towards Sustainable Development Goal 3.4 (SDG3.4) are often limited or lacking.\u003c/p\u003e \u003cp\u003eHospitalization data can help evaluate the burden of these conditions in a similar way to other disorders (14). Suriname has a notable prevalence of deaths from cardiovascular diseases (CVDs), constituting 60% of all mortalities(12). However, there is limited data on the trend over the past decade or its projected trajectory in the next decade. This study aims to provide insights into these data trends, to enhance understanding of the predominant health landscape in Suriname. For this reason, we assessed the admission rate as well as the evolution of age at admission and length of stay in hospital due to major cardiovascular disorders.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective, cross-sectional study of hospital admissions for major cardiovascular and selected non-communicable diseases in Suriname between 1 January 2013 and 31 December 2022. Data was provided by the Ministry pf Health Wellness and Labor and were obtained from the three largest public hospitals (Academic Hospital Paramaribo, \u0026lsquo;s Lands Hospital and Mungra Medical Centre) in the country, which collectively account for approximately 71.8% of all national hospital admissions.\u003c/p\u003e \u003cp\u003eThis study is not a clinical trial. It is a retrospective observational study based on routinely collected hospital admission and mortality data, and does not involve any intervention or prospective assignment of participants.\u003c/p\u003e \u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData sources and study population\u003c/h3\u003e\n\u003cp\u003eHospital discharge records were extracted from electronic administrative databases. All admissions with a primary discharge diagnosis corresponding to predefined ICD-10 categories were included. Admissions were considered independent events. Patients with missing discharge status (n\u0026thinsp;=\u0026thinsp;28) were excluded from mortality analyses.\u003c/p\u003e\n\u003ch3\u003eDiagnostic classification\u003c/h3\u003e\n\u003cp\u003eDischarge diagnoses were classified according to the \u003cb\u003eInternational Classification of Diseases, Tenth Revision\u003c/b\u003e coding system and grouped into major disease categories relevant to the burden of non-communicable diseases. Cancer diagnoses included codes C00\u0026ndash;D49, while diabetes mellitus was defined using codes E10\u0026ndash;E14. Cardiovascular conditions were subdivided into several categories: ischemic heart disease was identified using codes I20\u0026ndash;I25, stroke using codes I60\u0026ndash;I69, and heart failure using code I50. Renal disease was classified using codes N17\u0026ndash;N19, capturing both acute and chronic renal failure presentations. In addition, other cardiac diseases were grouped under codes I30\u0026ndash;I49 and I51\u0026ndash;I52, encompassing a range of non-ischemic cardiac conditions including arrhythmias, inflammatory heart diseases, and other structural cardiac disorders.\u003c/p\u003e \u003cp\u003eThe primary outcome was annual hospital admission rate per 10,000 population. Secondary outcomes included in-hospital mortality (case-fatality proportion), mean age at admission, and mean length of hospital stay.\u003c/p\u003e\n\u003ch3\u003eRate calculations\u003c/h3\u003e\n\u003cp\u003ePopulation denominators were obtained from the General Bureau of Statistics of Suriname (ABS) for each study year. Mid-year population estimates stratified by age and sex were used to calculate annual admission and mortality rates. Five-year age bands were used to ensure compatibility between hospital data and population denominators.\u003c/p\u003e \u003cp\u003eAnnual crude admission rates were calculated as:\u003c/p\u003e \u003cp\u003eadmission rate per 100.000 = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{Number\\:of\\:admission\\:in\\:year}{Mid-year\\:population\\:}\\times\\:100.000\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eIn-hospital mortality was defined as the proportion of admissions resulting in death during hospitalization.\u003c/p\u003e \u003cp\u003eAge-standardized admission rates (ASR) per 100,000 population were calculated using the direct standardization method. The WHO world standard population was applied as the reference population. Rates were calculated overall and stratified by sex. All analyses were performed separately for men, women, and the total population.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize admissions, mortality, age, and length of stay.\u003c/p\u003e \u003cp\u003eTemporal trends were evaluated using log-linear regression models of the form:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:log\\left(rate\\right)={\\beta\\:}_{0}+{\\beta\\:}_{1}\\left(year\\right)\\:$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAll analyses were performed using SPSS, JASP and MedCalc. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-sided).\u003c/p\u003e \u003cp\u003eTemporal trends in ASR between 2013 and 2022 were assessed using log-linear regression models. Annual Percentage Change (APC) and corresponding 95% confidence intervals (CI) were derived from the log-linear regression coefficients; APC = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left({e}^{{\\beta\\:}_{1}}-1\\right)\\times\\:100\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eTrends were considered statistically significant when the 95% CI did not include zero.\u003c/p\u003e \u003cp\u003eA factorial analysis of variance was conducted to examine the effects of condition, sex, and year on patient age and length of hospital stay (LOS). The results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e The study was conducted in accordance with the Declaration of Helsinki and approved by the national ethics committee of the Ministry of Health, Wellness and Labor.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy funding\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The study was conducted as part of routine institutional and public health collaboration.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThis study included 152,210 hospital admissions between 2013 and 2022 from three major hospitals, representing 71.8% of all national admissions. Of these, 5,832 cases (5.15%) resulted in in-hospital death due to cardiovascular-related conditions. A total of 144,350 patients were discharged alive. Discharge status was unknown for 28 patients, who were excluded from further analysis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn-hospital mortality\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBetween 2013 and 2022, in hospital age-standardized mortality rates demonstrated marked heterogeneity across conditions (Table 1). The most pronounced and statistically significant increases were observed for \u003cstrong\u003eother cardiac diseases\u003c/strong\u003e (male APC 21.5%, 95% CI 12.0\u0026ndash;31.7; female APC 16.3%, 95% CI 6.5\u0026ndash;26.7; total APC 19.2%, 95% CI 11.0\u0026ndash;28.0) and \u003cstrong\u003erenal disease\u003c/strong\u003e (male APC 12.8%, 95% CI 6.1\u0026ndash;19.8; female APC 9.9%, 95% CI 3.0\u0026ndash;17.2; total APC 11.4%, 95% CI 6.0\u0026ndash;17.1). Overall mortality across all conditions increased significantly (total APC 8.2%, 95% CI 4.1\u0026ndash;12.5), with a steeper rise among males (10.2%) compared to females (6.3%), resulting in a persistent male excess mortality (male-to-female ratio in 2022: 1.60). Mortality from ischemic heart disease increased modestly but significantly at the population level (total APC 4.1%, 95% CI 0.2\u0026ndash;8.0), whereas trends for cerebrovascular disease and heart failure were not statistically significant. Notably, sex disparities were most evident for cancer and other cardiac diseases, where male mortality rates in 2022 were more than twice those of females, indicating widening gender inequalities in cause-specific mortality.\u003c/p\u003e\n\u003cp\u003eTable 1: Annual Percent Change (APC) in Age-Standardized Mortality Rates (2013\u0026ndash;2022) by Sex\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCondition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale APC % (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale APC % (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal APC % (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM/F Ratio (2022)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e5.0 (0.5\u0026ndash;9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e3.2 (\u0026minus;1.0\u0026ndash;7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e4.1 (0.2\u0026ndash;8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRenal Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e12.8 (6.1\u0026ndash;19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e9.9 (3.0\u0026ndash;17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e11.4 (6.0\u0026ndash;17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebrovascular Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e2.1 (\u0026minus;1.8\u0026ndash;6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026minus;0.3 (\u0026minus;4.1\u0026ndash;3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e0.9 (\u0026minus;2.1\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart Failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e0.3 (\u0026minus;3.5\u0026ndash;4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026minus;0.6 (\u0026minus;4.5\u0026ndash;3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026minus;0.1 (\u0026minus;3.2\u0026ndash;3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Cardiac Diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e21.5 (12.0\u0026ndash;31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e16.3 (6.5\u0026ndash;26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e19.2 (11.0\u0026ndash;28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e6.9 (\u0026minus;1.5\u0026ndash;15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e2.5 (\u0026minus;5.8\u0026ndash;11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e4.7 (\u0026minus;0.8\u0026ndash;10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes Mellitus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e3.8 (\u0026minus;2.0\u0026ndash;9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e4.5 (\u0026minus;1.4\u0026ndash;10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e4.2 (\u0026minus;0.5\u0026ndash;9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll Conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e10.2 (5.1\u0026ndash;15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e6.3 (1.2\u0026ndash;11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e8.2 (4.1\u0026ndash;12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWithin the study period, sex disparities in hospital age-standardized mortality evolved substantially across conditions (Table 2). For all conditions combined, the male-to-female mortality ratio increased from 1.24 to 1.60 (+29%), indicating a widening male excess. The most pronounced shift was observed for renal disease, where the ratio increased from 0.72 to 1.37 (+90%), reflecting a transition from female to male predominance. Cancer mortality demonstrated the largest relative change, reversing from female predominance (0.44) in 2013 to marked male excess (2.29) in 2022. Cerebrovascular mortality showed a moderate widening of male excess (+27%). In contrast, ischemic heart disease and other cardiac diseases, while remaining male-predominant, demonstrated partial narrowing of the sex gap. Diabetes-related mortality showed a substantial reduction in male excess over time (\u0026minus;66%). Overall, these findings indicate dynamic and condition-specific shifts in sex disparities, with a general trend toward increasing male disadvantage in several major categories.\u003c/p\u003e\n\u003cp\u003eTable 2: Evolution of Male-to-Female Mortality Rate Ratios (MRR) by Condition, 2013\u0026ndash;2022\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCondition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Trend 2013\u0026ndash;2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll Conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026uarr; Increasing male excess\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eFluctuating, overall male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRenal Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eVariable, ending with male excess\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebrovascular Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eProgressive male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart Failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eHighly variable, no clear direction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Cardiac Diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003ePersistently high male excess\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eShift from female to strong male excess\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes Mellitus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eMale excess narrowing over time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAge-Standardized Admission Rates\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBetween 2013 and 2022, age-standardized hospital admission rates increased significantly for most cardiovascular and renal conditions in Suriname (Table 3). For all conditions combined, the annual increase was substantial and statistically significant in men (APC 7.2%, 95% CI 5.5\u0026ndash;9.0), women (APC 6.1%, 95% CI 4.5\u0026ndash;7.8), and in the total population (APC 6.6%, 95% CI 5.3\u0026ndash;8.0). These findings indicate a sustained rise in overall hospital burden across the study period.\u003c/p\u003e\n\u003cp\u003eAmong cardiovascular conditions, ischemic heart disease (IHD) demonstrated a marked and consistent upward trend (Table 3). The APC was 7.6% (95% CI 5.2\u0026ndash;10.1) in men and 5.0% (95% CI 3.0\u0026ndash;7.1) in women, corresponding to an overall annual increase of 6.3%. Absolute age-standardized rates increased from 1,067.3 per 100,000 population in 2013 to 1,874.5 per 100,000 in 2022, representing one of the largest absolute increases observed.\u003c/p\u003e\n\u003cp\u003eCerebrovascular disease admissions also increased significantly (Table 3), with APCs of 5.3% (95% CI 2.4\u0026ndash;8.3) in men and 4.2% (95% CI 1.5\u0026ndash;7.0) in women. The overall APC was 5.0% (95% CI 2.8\u0026ndash;7.2), indicating a steady rise in stroke-related hospitalizations throughout the study period.\u003c/p\u003e\n\u003cp\u003eSimilarly, heart failure admissions rose significantly in both sexes (Table 3). The APC was 6.2% (95% CI 1.8\u0026ndash;10.8) in men and 5.6% (95% CI 2.1\u0026ndash;9.3) in women, yielding an overall APC of 6.0% (95% CI 2.8\u0026ndash;9.4). Other cardiac diseases exhibited a significant increase in men (APC 8.7%, 95% CI 2.0\u0026ndash;15.8) and in the total population (APC 6.6%, 95% CI 1.5\u0026ndash;12.0), whereas the increase in women did not reach statistical significance.\u003c/p\u003e\n\u003cp\u003eRenal disease showed the steepest rise among all examined conditions (Table 3). Age-standardized rates more than tripled during the study period, increasing from 128.3 per 100,000 in 2013 to 421.9 per 100,000 in 2022. The APC was 12.5% (95% CI 7.8\u0026ndash;17.4) in men and 16.2% (95% CI 8.4\u0026ndash;24.6) in women, with an overall annual increase of 14.6% (95% CI 9.6\u0026ndash;19.9). This represents the most rapidly expanding contributor to hospital burden over the decade.\u003c/p\u003e\n\u003cp\u003eIn contrast, cancer and diabetes mellitus admissions did not demonstrate statistically significant trends over time (Table 3). For cancer, a downward trend was observed in men (APC \u0026minus;4.5%, 95% CI \u0026minus;9.2 to 0.4), although this did not reach statistical significance, while rates in women remained stable. Diabetes mellitus admissions also showed no significant changes, with APC estimates of 1.9% (95% CI \u0026minus;2.6\u0026ndash;6.6) in men and \u0026minus;0.8% (95% CI \u0026minus;5.6\u0026ndash;4.2) in women, indicating overall stability.\u003c/p\u003e\n\u003cp\u003eTable 3: Annual Percent Change (APC) in Age-Standardized Admission Rates, 2013\u0026ndash;2022\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCondition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale APC % (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale APC % (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal APC % (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIschemic Heart Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.6\u003c/strong\u003e (5.2\u0026ndash;10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.0\u003c/strong\u003e (3.0\u0026ndash;7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.3\u003c/strong\u003e (4.6\u0026ndash;8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRenal Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.5\u003c/strong\u003e (7.8\u0026ndash;17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16.2\u003c/strong\u003e (8.4\u0026ndash;24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.6\u003c/strong\u003e (9.6\u0026ndash;19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebrovascular Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.3\u003c/strong\u003e (2.4\u0026ndash;8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.2\u003c/strong\u003e (1.5\u0026ndash;7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.0\u003c/strong\u003e (2.8\u0026ndash;7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart Failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.2\u003c/strong\u003e (1.8\u0026ndash;10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.6\u003c/strong\u003e (2.1\u0026ndash;9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.0\u003c/strong\u003e (2.8\u0026ndash;9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Cardiac Diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.7\u003c/strong\u003e (2.0\u0026ndash;15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e4.9 (\u0026minus;0.8\u0026ndash;10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.6\u003c/strong\u003e (1.5\u0026ndash;12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026minus;4.5 (\u0026minus;9.2\u0026ndash;0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026minus;0.6 (\u0026minus;5.0\u0026ndash;4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026minus;2.0 (\u0026minus;5.9\u0026ndash;2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes Mellitus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e1.9 (\u0026minus;2.6\u0026ndash;6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026minus;0.8 (\u0026minus;5.6\u0026ndash;4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e0.5 (\u0026minus;3.6\u0026ndash;4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll Conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.2\u003c/strong\u003e (5.5\u0026ndash;9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.1\u003c/strong\u003e (4.5\u0026ndash;7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.6\u003c/strong\u003e (5.3\u0026ndash;8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSex Differences Over Time\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 depicts the sex disparities in age-standardized hospital admission rates evolving heterogeneously across conditions during 2013\u0026ndash;2022. For ischemic heart disease, the male-to-female rate ratio increased from 1.27 in 2013 to 1.60 in 2022, indicating a widening male predominance over time. A similar pattern was observed for cerebrovascular disease, where the rate ratio rose from 1.24 to 1.38. In contrast, heart failure demonstrated persistent female predominance throughout the study period, with male-to-female rate ratios remaining below unity (0.79 in 2013 and 0.81 in 2022). Cancer admissions showed a stable female predominance, with the rate ratio declining slightly from 0.37 to 0.26 over time. Renal disease displayed substantial temporal variability, with early male predominance (2.26 in 2013), a mid-period reversal favoring females, and renewed male excess by 2022 (1.44), suggesting dynamic shifts in sex-specific burden or healthcare utilization. For all conditions combined, overall admissions shifted from near parity at baseline (rate ratio 0.99 in 2013) to modest male predominance by 2022 (1.10).\u003c/p\u003e\n\u003cp\u003eCollectively, these findings indicate that while overall hospital burden increased in both sexes, the magnitude and direction of sex disparities varied considerably by diagnostic category, with widening male excess particularly evident for ischemic and cerebrovascular disease.\u003c/p\u003e\n\u003cp\u003eTable 4: Evolution of Male-to-Female Admission Rate Ratios (ASR), 2013\u0026ndash;2022\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCondition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Trend 2013\u0026ndash;2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eIschemic Heart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eIncreasing male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eRenal Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eFluctuating, overall male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eCerebrovascular Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eSlight increase in male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eHeart Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003ePersistent female predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eOther Cardiac Diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eShift toward male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eCancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003ePersistent strong female predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eSlight increase in male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eAll Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eGradual shift toward male predominance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealthcare outcome\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 presents trends in mean age at admission. Across all conditions combined, the mean age of hospitalized patients increased modestly between 2013 and 2022. In both years, male patients were slightly older than female patients, and the difference between sexes remained statistically significant.\u003c/p\u003e\n\u003cp\u003ePronounced sex differences in age were observed for several disease categories. In neoplasms, female patients were admitted at a substantially younger age than males in both study years. Although the mean age increased for both sexes over time, this gender difference remained significant in 2022.\u003c/p\u003e\n\u003cp\u003eFor diabetes mellitus, the age pattern differed by sex. The mean age of male patients remained relatively stable over the study period, whereas female patients showed a significant increase in mean age, resulting in women presenting slightly older than men by 2022.\u003c/p\u003e\n\u003cp\u003eCardiovascular conditions showed a clear aging pattern. In ischemic heart disease and other cardiac diseases, the mean age of admission increased over time for both sexes, with female patients consistently presenting at older ages than males in 2022. A similar pattern was observed in cerebrovascular disease, where women were older than men at admission in both study years.\u003c/p\u003e\n\u003cp\u003eTable 5 also presents trends in mean length of hospital stay. The average length of hospital stay across all conditions decreased significantly between 2013 and 2022 for both sexes, suggesting improvements in hospital throughput or clinical management. This decline was particularly evident in acute cardiovascular conditions such as heart failure and cerebrovascular disease, where LOS decreased for both men and women.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5: Mean age and mean length of hospital stay (LOS) by condition, sex, and year. * indicate a statistically significant change between 2013 and 2022 within the same sex (p \u0026lt; 0.05). ! indicates a statistically significant difference between male and female\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 35px;\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 39px;\"\u003e\n \u003cp\u003eLength of hospital stay \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 17px;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 17px;\"\u003e\n \u003cp\u003eFemale \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 19px;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 20px;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eCondition\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eAll conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e59.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e60.12* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e56.89 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e58.39* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e10.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e8.24* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e9.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e8.35* !\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eCancer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e55.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e61.08* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e47.65 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e53.17 *!\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e94.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e8.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e61.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e55.47 !\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eCerebrovascular Diseases \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e61.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e62.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e64.10 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e65.13 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e12.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e10.06* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e13.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e11.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eDiabetes Mellitus \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e59.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e58.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e57.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e59.31* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e11.44* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e12.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e110.36* !\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eHeart Failure \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e64.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e63.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e66.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e67.84 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e9.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6.44* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e8.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6.81* !\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eIschemic Heart Disease \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e57.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e58.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e59.84 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e61.60* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e49.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e48.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e5.10 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e44.52* !\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eOther Cardiac Diseases \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e58.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e65.99* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e63.94 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e70.64* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e64.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e42.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e9.65 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e48.23* !\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eRenal Diseases\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e61.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e59.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e56.91 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e61.26* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e16.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e161.66* !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e142.84 !\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e147.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eHowever, several conditions deviated markedly from this general pattern. In the diabetes mellitus cohort, LOS decreased for male patients but increased dramatically among female patients. By 2022, the mean LOS for females reached 110.36 days, representing both a substantial temporal increase and a pronounced gender disparity compared with male patients.\u003c/p\u003e\n\u003cp\u003eRenal diseases also showed a striking change in hospital resource use. While LOS was relatively moderate for men in 2013, it increased sharply by 2022, reaching a mean of 161.66 days. Female patients already exhibited long hospital stays in 2013, and LOS remained similarly elevated in 2022, effectively narrowing the initial gender difference.\u003c/p\u003e\n\u003cp\u003eOther cardiac diseases demonstrated a mixed pattern. Although male LOS decreased over time, female LOS increased substantially, producing a pronounced divergence between sexes in 2022.\u003c/p\u003e\n\u003cp\u003eTaken together, the findings suggest divergent patterns across disease categories. Acute cardiovascular conditions, such as heart failure and ischemic heart disease, showed shorter hospital stays over time and relatively converging outcomes between sexes. In contrast, chronic metabolic and organ-failure conditions\u0026mdash;including diabetes mellitus, renal disease, and certain oncological conditions\u0026mdash;were characterized by increasing complexity, older patient populations, and widening gender differences in hospital resource utilization.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis nationwide analysis of hospital data in Suriname from 2013 to 2022 reveals a dual escalation in age-standardized hospital admissions and mortality for major non-communicable diseases (NCDs). With a sustained \u003cb\u003e6.6% annual increase in total admissions\u003c/b\u003e and a \u003cb\u003esignificant 8.2% rise in overall mortality\u003c/b\u003e, these findings indicate a rapidly intensifying cardiometabolic burden that is currently outpacing the capacity of the national healthcare system.\u003c/p\u003e \u003cp\u003eThe study highlights a critical shift in Suriname\u0026rsquo;s cardiovascular landscape. While \u003cb\u003eischemic heart disease (IHD)\u003c/b\u003e saw moderate growth in both admissions (6.3% APC) and mortality (4.1% APC), the most dramatic shifts occurred in heart failure and non-ischemic conditions (15). Mortality from \"other cardiac diseases\"\u0026mdash;a category including arrhythmias and cardiomyopathies\u0026mdash;exhibited the steepest increase of all categories (\u003cb\u003e19.2% APC\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eUnlike many high-income nations that have achieved declines in IHD mortality through aggressive primary prevention and lipid-lowering therapies, Suriname\u0026rsquo;s upward trend suggests the country is in an earlier, more volatile phase of the cardiovascular transition. Here, the rising prevalence of metabolic risk factors is expanding faster than the implementation of preventive infrastructure (5,16,17).\u003c/p\u003e \u003cp\u003eRenal disease emerged as the most consistent and concerning healthcare challenge identified in this study. Admissions for renal conditions more than tripled (\u003cb\u003e14.6% APC\u003c/b\u003e), mirrored by an \u003cb\u003e11.4% annual increase in mortality\u003c/b\u003e. The simultaneous rise in both utilization and death suggests a genuine increase in disease severity and late-stage presentations rather than improved detection alone.\u003c/p\u003e \u003cp\u003eGiven the well-established links between diabetes, hypertension, and chronic kidney disease (CKD) in the Surinamese population, this trajectory forecasts an unsustainable demand for renal replacement therapy (RRT) (18). From a health systems perspective, renal disease represents a high-cost, high-mortality pathway that threatens to exhaust tertiary care resources if upstream management is not radically strengthened.\u003c/p\u003e \u003cp\u003eA defining feature of the study period was the widening \"male disadvantage.\" While hospital admissions were near parity in 2013, a clear male predominance emerged by 2022, particularly in IHD and cerebrovascular disease. More strikingly, the \u003cb\u003emale-to-female mortality ratio increased by 29%\u003c/b\u003e across all conditions.\u003c/p\u003e \u003cp\u003eThis pattern suggests that improvements in prevention and early detection have not occurred uniformly across sexes. Men in Suriname may be disproportionately affected by delayed healthcare utilization, higher behavioral risk profiles (such as smoking), and poorer adherence to long-term management for hypertension (19). This widening gap aligns with regional trends in the Americas, where traditional barriers to primary care engagement often result in higher premature NCD mortality among men (20).\u003c/p\u003e \u003cp\u003eRenal disease represents a particularly concerning finding. While admissions for renal disease increased dramatically, mortality remained relatively stable. This divergence suggests either improved survival among hospitalized renal patients or increasing admission of less severe cases. Nonetheless, the rapid growth in renal admissions highlights the expanding burden of chronic kidney disease and its cardiovascular implications, emphasizing the need for strengthened early detection and outpatient management strategies.\u003c/p\u003e \u003cp\u003eIn contrast to the sharp rises in cardiovascular and renal categories, cancer and diabetes admissions remained relatively stable. For diabetes, this apparent stability\u0026mdash;despite its role as a primary driver of heart and kidney failure\u0026mdash;likely reflects a shift in clinical coding or hospital utilization. Patients may increasingly be admitted for the \u003cem\u003econsequences\u003c/em\u003e of diabetes (e.g., CKD or heart failure) rather than for primary glycemic control. This pattern underscores the importance of effective primary care systems capable of preventing progression to acute hospitalization (21). The stability in cancer admissions, coupled with a persistent female predominance, likely reflects established sex-specific screening programs and healthcare-seeking behaviors already integrated into the system.\u003c/p\u003e \u003cp\u003eThe progressive increase in mean age across most major cardiovascular categories reflects population ageing and possibly improved survival from chronic conditions. At the same time, the significant reduction in length of hospital stay across most conditions suggests improvements in efficiency, clinical pathways, or discharge planning. The most pronounced reductions were observed in other cardiac diseases and stroke, which may indicate advances in standardized acute care management. Nevertheless, shortening hospital stays must be carefully monitored to ensure that reductions do not compromise post-discharge outcomes.\u003c/p\u003e \u003cp\u003eOverall, the findings suggest a healthcare system adapting to rising cardiovascular demand and increasing mortality in several major categories. However, the rapid growth in admissions\u0026mdash;particularly for renal and ischemic heart disease\u0026mdash;and the widening gender mortality gap indicate areas requiring targeted intervention.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003eStrengths\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLongitudinal Scope\u003c/b\u003e: This study utilizes a robust, 10-year dataset (2013\u0026ndash;2022), providing a comprehensive view of long-term epidemiological shifts rather than a cross-sectional \"snapshot.\"\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eNationwide Representation\u003c/b\u003e: By incorporating nationally aggregated hospital data, the findings reflect the actual clinical burden on the Surinamese health system rather than localized or single-center trends.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eMethodological Rigor\u003c/b\u003e: The use of \u003cb\u003eage-standardized rates\u003c/b\u003e allows for meaningful comparisons over time by removing the confounding effect of Suriname\u0026rsquo;s aging population.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFormal Trend Estimation\u003c/b\u003e: The application of the \u003cb\u003eAverage Annual Percent Change (APC)\u003c/b\u003e provides a statistically sound measure of the magnitude and direction of trends, allowing for the identification of significant disparities between sexes and disease categories.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eInpatient Bias\u003c/b\u003e: The analysis is based exclusively on hospital admissions and mortality. Consequently, it does not capture the significant \"silent\" burden of NCDs managed in outpatient primary care or undiagnosed cases in the community.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eData Quality and Coding\u003c/b\u003e: Trends may be influenced by evolving clinical coding practices (ICD-10 transitions), changes in hospital reporting accuracy, or improvements in diagnostic technology over the decade.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEcological Design\u003c/b\u003e: As an ecological study, these findings describe population-level trends; they cannot be used to establish direct causal links between specific individual risk factors (e.g., smoking or diet) and the observed outcomes.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eExternal Shocks\u003c/b\u003e: The log-linear APC model assumes a constant rate of change. It may not fully account for non-linear \"shocks\" to the healthcare system, most notably the \u003cb\u003eCOVID-19 pandemic\u003c/b\u003e, which may have temporarily suppressed admission rates or skewed mortality data between 2020 and 2022.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSecondary Prevention Gap\u003c/b\u003e: The data does not distinguish between first-time admissions and readmissions, which limits our ability to evaluate the specific effectiveness of secondary prevention programs.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOver the past decade, Suriname has transitioned into a period of intensifying cardiometabolic morbidity and mortality. The concurrent rise in hospitalizations and deaths related to cardiovascular and renal diseases signals an urgent public health crisis. The most alarming trend is the tripling of the renal disease burden, which represents a high-cost trajectory that threatens health system sustainability.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePolicy implication\u003c/h2\u003e \u003cp\u003eThe widening sex disparity\u0026mdash;specifically the increasing mortality risk among men\u0026mdash;highlights a critical need for gender-sensitive healthcare delivery. To achieve Sustainable Development Goal (SDG) 3.4, which aims to reduce premature mortality from non-communicable diseases (NCDs), Suriname must adopt a comprehensive and strategic approach to strengthening its health system. A central priority should be the reinforcement of integrated primary care services, particularly in the management of hypertension and diabetes. Effective detection, monitoring, and long-term management of these conditions are essential to prevent progression to severe complications such as end-stage renal disease and advanced cardiac failure. In addition, public health strategies should place greater emphasis on engaging men in preventive healthcare. Evidence consistently shows that men are less likely to seek early screening or adhere to long-term treatment, which contributes to higher rates of advanced disease and mortality. Developing targeted interventions that promote early health-seeking behavior and sustained treatment adherence among men is therefore critical. Finally, given the growing burden of complex NCD cases, Suriname must expand its specialized care capacity, particularly in nephrology and advanced cardiac services. Strengthening these services will be necessary to effectively manage the increasing number of patients presenting with high-acuity conditions requiring specialized and resource-intensive care.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eR.D. (Ritesh Dhanpat) performed the statistical analyses, interpreted the data, and drafted the manuscript.R.B. (Robbert Bipat) and J.T. (Jerry Toelsie) supervised the study, contributed to the methodological structure of the manuscript, and provided critical revisions with respect to content, organization, and scientific presentation.V.J. (Vanita Jairam) and A.M. (Angelle Mendeszoon) contributed to data acquisition and supported the data collection process within their respective hospitals, and reviewed the manuscript with relevant feedback.R.G.S. (Rakesh Gajadhar Sukul) facilitated access to the national dataset through the Ministry of Health, Wellness and Labor and contributed to data acquisition.All authors approved the final manuscript and agree to be accountable for the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors gratefully acknowledge the Ministry of Health, Wellness and Labor of Suriname for granting access to the national hospital admission data used in this study. The use of these data was made possible through their support and approval. The authors further recognize the contribution of the national medical registration system in enabling this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are not publicly available due to restrictions related to patient confidentiality and institutional data protection policies. The dataset consists of routinely collected hospital admission data obtained through national medical registration systems and the Ministry of Health of Suriname.Access to these data is subject to approval by the relevant institutional authorities and the Ministry of Health, Wellness and Labor of Suriname. Researchers who meet the criteria for access to confidential data may submit a reasonable request to the corresponding author, subject to institutional permission and applicable data protection regulations.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDi M, Di Cesare CM. Global trends of chronic non-communicable diseases risk factors [Internet]. 2019. Available from: https://academic.oup.com/eurpub/article/29/Supplement_4/ckz185.196/5624434\u003c/li\u003e\n\u003cli\u003eMartinez R, Soliz P, Mujica OJ, Reveiz L, Campbell NRC, Ordunez P. The slowdown in the reduction rate of premature mortality from cardiovascular diseases puts the Americas at risk of achieving SDG 3.4: A population trend analysis of 37 countries from 1990 to 2017. J Clin Hypertens. 2020 Aug 1;22(8):1296\u0026ndash;309. doi:10.1111/JCH.13922 PubMed PMID: 33289261.\u003c/li\u003e\n\u003cli\u003eWorld Health Statistics. SDGs Sustainable Development Goals. 2023.\u003c/li\u003e\n\u003cli\u003eWHO. WHO newsroom NCD factsheet. 2024.\u003c/li\u003e\n\u003cli\u003eKyu HH, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet. 2018 Nov;392(10159):1859\u0026ndash;922. doi:10.1016/S0140-6736(18)32335-3\u003c/li\u003e\n\u003cli\u003eHay SI, Ong KL, Santomauro DF, Bhoomadevi A, Aalipour MA, Aalruz H, et al. Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990\u0026ndash;2023: a systematic analysis for the Global Burden of Disease Study 2\u0026hellip;. Lancet. 2025 Oct 18;406(10513):1873. doi:10.1016/S0140-6736(25)01637-X PubMed PMID: 41092926.\u003c/li\u003e\n\u003cli\u003eMartinez R, Lloyd-Sherlock P, Soliz P, Ebrahim S, Vega E, Ordunez P, et al. Trends in premature avertable mortality from non-communicable diseases for 195 countries and territories, 1990\u0026ndash;2017: a population-based study. Lancet Glob Health. 2020 Apr 1;8(4):e511\u0026ndash;23. doi:10.1016/S2214-109X(20)30035-8 PubMed PMID: 32199120.\u003c/li\u003e\n\u003cli\u003eKrumholz HM, Normand SLT, Wang Y. Trends in hospitalizations and outcomes for acute cardiovascular disease and stroke, 1999-2011. Circulation. Lippincott Williams and Wilkins; 2014. p. 966\u0026ndash;75. doi:10.1161/CIRCULATIONAHA.113.007787 PubMed PMID: 25135276.\u003c/li\u003e\n\u003cli\u003eAppiah LT, Sarfo FS, Agyemang C, Tweneboah HO, Appiah NABA, Bedu-Addo G, et al. Current trends in admissions and outcomes of cardiac diseases in Ghana. Clin Cardiol. 2017 Oct 1;40(10):783\u0026ndash;8. doi:10.1002/clc.22753 PubMed PMID: 28692760.\u003c/li\u003e\n\u003cli\u003ePrevention and control of noncommunicable diseases and mental disorders in Suriname: Investment case [Internet]. doi:10.37774/9789275130278\u003c/li\u003e\n\u003cli\u003ePunwasi W B. Doodsoorzaken_in_Suriname. Doodsoorzaken in Suriname: 2010-2011. 2012.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization 2026 data.who.int, Suriname [Country overview]. (Accessed on 16 March 2026).\u003c/li\u003e\n\u003cli\u003eMinistry of Health Suriname SURINAME National Action Plan for the Prevention and Control of Noncommunicable Diseases. 2012.\u003c/li\u003e\n\u003cli\u003eKashyap S, Gombar S, Yadlowsky S, Callahan A, Fries J, Pinsky BA, et al. Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening. Journal of the American Medical Informatics Association. 2020 Jul 1;27(7):1026\u0026ndash;131. doi:10.1093/jamia/ocaa076 PubMed PMID: 32548636.\u003c/li\u003e\n\u003cli\u003eSairras S, Baldew SS, van der Hilst K, Shankar A, Zijlmans W, Lichtveld M, et al. Heart Failure Hospitalizations and Risk Factors among the Multi-Ethnic Population from a Middle Income Country: The Suriname Heart Failure Studies. J Natl Med Assoc. 2021 Apr 1;113(2):177\u0026ndash;86. doi:10.1016/j.jnma.2020.08.010 PubMed PMID: 32928542.\u003c/li\u003e\n\u003cli\u003eda Silva RA, de Ara\u0026uacute;jo Fonseca LG, de Santana Silva JP, Lima NMFV, Gualdi LP, Lima INDF. The impact of the strategic action plan to combat chronic non-communicable diseases on hospital admissions and deaths from cardiovascular diseases in Brazil. PLoS One. 2022 Jun 1;17(6 June). doi:10.1371/journal.pone.0269583 PubMed PMID: 35675279.\u003c/li\u003e\n\u003cli\u003eForouzanfar MH, Afshin A, Alexander LT, Biryukov S, Brauer M, Cercy K, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990\u0026ndash;2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016 Oct 10;388(10053):1659. doi:10.1016/S0140-6736(16)31679-8 PubMed PMID: 27733284.\u003c/li\u003e\n\u003cli\u003eNannan Panday R, Haan Y, Diemer F, Punwasi A, Rommy C, Heerenveen I, et al. Chronic kidney disease and kidney health care status: the healthy life in Suriname (HeliSur) study. Intern Emerg Med. 2019 Mar 11;14(2):249\u0026ndash;58. doi:10.1007/s11739-018-1962-3 PubMed PMID: 30361850.\u003c/li\u003e\n\u003cli\u003eK D Bertakis, R Azari, L J Helms, E J Callahan, J A Robbins. Gender differences in the utilization of health care services. The Journal of family practice . 2000;49.2:147\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eAli Ch I, Health St Anthony Hospital Oklahoma City SO, Ali Qasim S, Zafar H, Maryam S, Qasim Shaheed Mohtarma Benazir Bhutto Medical College M, et al. Premature Coronary Artery Disease Related Mortality in the United States: Regional, Gender, and Racial Disparities \u0026ndash; Insights from the CDC WONDER Database (1999\u0026ndash;2023). medRxiv. 2025 Dec 18;2025.12.16.25342435. doi:10.64898/2025.12.16.25342435\u003c/li\u003e\n\u003cli\u003eShih-Chuan Chou, Jeremiah D. Schuur, Olesya Baker. Changes in Emergency Department Care Intensity from 2007-16: Analysis of the National Hospital Ambulatory Medical Care Survey. Western Journal of Emergency Medicine. 2020;21(2):209\u0026ndash;2016. doi:10.5811/westjem.2019.10.43497 PubMed PMID: 32191176.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"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":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Suriname, Cardiovascular Disease, Renal Disease, Mortality, Hospital Admissions, Epidemiological Transition, Male Disadvantage","lastPublishedDoi":"10.21203/rs.3.rs-9271418/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9271418/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCardiovascular disorders are the leading global cause of death, with more premature mortality in middle-income countries (MICs) than in high-income countries (HICs), challenging health systems. However, data on cardiovascular-related hospital admissions in MICs remain limited. This study assessed such admissions in Suriname, a MIC in South America with high cardiovascular mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective, hospital-based repeated cross-sectional study using discharge records from Suriname\u0026rsquo;s three largest public hospitals (71.8% of national admissions). Diagnoses were classified using ICD-10 codes for Cancer, Diabetes (DM), Ischemic Heart Disease (IHD), Stroke, Heart Failure (HF), Renal Disease (RD), and Other Cardiac Diseases (OCD). Age-standardized rates (ASR) were calculated using the WHO standard population. Trends were analyzed using log-linear regression to estimate Annual Percentage Change (APC) with 95% confidence intervals.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTotal age-standardized admissions increased by 6.6% annually (APC 6.6, 95% CI 4.2\u0026ndash;9.1). The largest rise occurred in renal disease admissions (APC 14.6) and mortality (APC 11.4). IHD and HF admissions increased steadily, while OCD mortality rose most sharply (APC 19.2). Overall mortality increased (APC 8.2), more in males (10.2%) than females (6.3%), widening the sex gap by 29%. Cancer and diabetes admissions remained stable.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSuriname faces a rapidly increasing hospital burden and mortality driven by cardiovascular and renal diseases. The sharp rise in renal disease and widening male mortality gap highlight the need for sex-specific prevention and improved hypertension and diabetes management, alongside expanded nephrology and cardiac care capacity.\u003c/p\u003e","manuscriptTitle":"Nationwide trends in hospital admissions and mortality for cardiovascular and renal diseases in Suriname from 2013 to 2022 a retrospective observational study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 05:03:11","doi":"10.21203/rs.3.rs-9271418/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-16T07:20:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300351501121596911650215926980588001594","date":"2026-05-13T02:30:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200310709790195829115067373430236955555","date":"2026-05-11T02:06:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76821054872333035046181761768648098072","date":"2026-05-08T00:40:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147968068489560806675643597767241067179","date":"2026-05-07T06:25:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-04T06:13:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-14T03:40:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-11T05:32:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-08T17:14:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-04-08T17:09:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2e268bc1-4fd2-4a58-9436-aba551d2d97c","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-16T07:20:26+00:00","index":72,"fulltext":""},{"type":"reviewerAgreed","content":"300351501121596911650215926980588001594","date":"2026-05-13T02:30:59+00:00","index":71,"fulltext":""},{"type":"reviewerAgreed","content":"200310709790195829115067373430236955555","date":"2026-05-11T02:06:54+00:00","index":68,"fulltext":""},{"type":"reviewerAgreed","content":"76821054872333035046181761768648098072","date":"2026-05-08T00:40:53+00:00","index":56,"fulltext":""},{"type":"reviewerAgreed","content":"147968068489560806675643597767241067179","date":"2026-05-07T06:25:41+00:00","index":54,"fulltext":""},{"type":"reviewersInvited","content":"40","date":"2026-05-04T06:13:09+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T06:24:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 05:03:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9271418","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9271418","identity":"rs-9271418","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}