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Войти в исследования International journal of women's health · 2026
Spatiotemporal Analysis of Hospitalisations and Mortality From Gynaecological Cancers in Ecuador, 2015-2024.
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Lalangui-Vivanco Karina, Jaramillo-Feijoo Leyda Elizabeth, Real-Cotto Jhony Joe, Quentin Emmanuelle
Аннотация
PURPOSE: To analyse the spatiotemporal patterns of hospitalisations and mortality due to gynaecological cancers in Ecuador (2015-2024), identify provincial geographic disparities, and examine the association between healthcare infrastructure and clustering patterns.
METHODS: This population-based ecological study used INEC hospital discharge and general death records for women with gynaecological cancers (ICD-10: C51-C57) in Ecuador from 2015 to 2024. Age-standardised rates per 100,000 women were calculated by year, cause, age group, and province of residence. K-means clustering was applied separately to hospitalisation and mortality rates to identify provinces with similar temporal trajectories. Global and local Moran's I assessed spatial autocorrelation, and Spearman correlations and Kruskal-Wallis tests examined associations with healthcare infrastructure.
RESULTS: Between 2015 and 2024, 39,492 hospitalisations and 11,410 deaths were recorded. Cervical cancer accounted for 45.4% of hospitalisations and 42.2% of deaths, followed by ovarian cancer (32.6% and 22.0%). Hospitalisations declined markedly in 2020 during the COVID-19 pandemic. Trajectory-based k-means identified three clusters for each outcome. The highest hospitalisation rates were concentrated in the southern provinces, with significant global spatial autocorrelation (Moran's I = 0.48-0.64, all p ≤ 0.002) and a persistent High-High spatial cluster, while the highest mortality occurred in the northern and central Sierra and the Amazon, without consistent spatial autocorrelation. Nine provinces had high mortality, low hospitalisation, and lower bed density (224.9 vs 260.1 per 100,000 women). Bed density was not significantly correlated with hospitalisation (rho = 0.35, p = 0.097) or mortality (rho = -0.27, p = 0.205); bed density did not differ across mortality clusters (p = 0.52).
CONCLUSION: The mismatch between hospitalisation and mortality clustering patterns, together with lower healthcare infrastructure in high-mortality provinces, suggests that unequal access to timely care may contribute to excess mortality, although these associations were not statistically significant.
METHODS: This population-based ecological study used INEC hospital discharge and general death records for women with gynaecological cancers (ICD-10: C51-C57) in Ecuador from 2015 to 2024. Age-standardised rates per 100,000 women were calculated by year, cause, age group, and province of residence. K-means clustering was applied separately to hospitalisation and mortality rates to identify provinces with similar temporal trajectories. Global and local Moran's I assessed spatial autocorrelation, and Spearman correlations and Kruskal-Wallis tests examined associations with healthcare infrastructure.
RESULTS: Between 2015 and 2024, 39,492 hospitalisations and 11,410 deaths were recorded. Cervical cancer accounted for 45.4% of hospitalisations and 42.2% of deaths, followed by ovarian cancer (32.6% and 22.0%). Hospitalisations declined markedly in 2020 during the COVID-19 pandemic. Trajectory-based k-means identified three clusters for each outcome. The highest hospitalisation rates were concentrated in the southern provinces, with significant global spatial autocorrelation (Moran's I = 0.48-0.64, all p ≤ 0.002) and a persistent High-High spatial cluster, while the highest mortality occurred in the northern and central Sierra and the Amazon, without consistent spatial autocorrelation. Nine provinces had high mortality, low hospitalisation, and lower bed density (224.9 vs 260.1 per 100,000 women). Bed density was not significantly correlated with hospitalisation (rho = 0.35, p = 0.097) or mortality (rho = -0.27, p = 0.205); bed density did not differ across mortality clusters (p = 0.52).
CONCLUSION: The mismatch between hospitalisation and mortality clustering patterns, together with lower healthcare infrastructure in high-mortality provinces, suggests that unequal access to timely care may contribute to excess mortality, although these associations were not statistically significant.