Spatial and temporal analysis of breast cancer mortality in a state in northeastern Brazil
Breast cancer (BC) is the most common neoplasm, and its global burden has become one of the most important factors jeopardizing the health of the world population, especially women. The aim of this study was to analyze mortality trends and the spatial distribution of BC in women in the capital and s...
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Veröffentlicht in: | Cancer epidemiology 2024-12, Vol.93, p.102661, Article 102661 |
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Sprache: | eng |
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Zusammenfassung: | Breast cancer (BC) is the most common neoplasm, and its global burden has become one of the most important factors jeopardizing the health of the world population, especially women. The aim of this study was to analyze mortality trends and the spatial distribution of BC in women in the capital and state of Sergipe, aiming to contribute to the implementation and improvement of strategies for the prevention and health promotion of women with BC. Trends were calculated using the Joinpoint Regression Program 5.0.2. Spatial analyses were performed using the empirical Bayesian model, thematic maps were created using QGIS 3.10.7 and Moran's I indices were calculated using TerraView 4.2.2. Between 1996 and 2022, 1384 and 3128 BC deaths were recorded in the capital and state of Sergipe, respectively. The mortality trend increased in the age groups of 45–75+ for the state of Sergipe, while in the capital, we observed stability in all age groups. The highest AAPC was 4.6213, with a 95 % confidence interval (2.16; 7.14). Univariate global Moran's I analysis indicated spatial autocorrelation during the study period. A direct relationship was found between mortality rates and the more economically developed regions.
•Breast cancer mortality rates rose among women of all ages in Sergipe State.•Breast cancer mortality trends remained stable across all age groups in Aracaju.•Higher mortality rates were linked to economically developed regions.•High breast cancer mortality rates were found in Sergipe's southeastern region.•Spatial analysis showed clustering of high mortality rates in specific areas. |
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ISSN: | 1877-7821 1877-783X 1877-783X |
DOI: | 10.1016/j.canep.2024.102661 |