Evidence map›Paper›PMID 42326920›Full record

ArticleFrontiers in public health2026

Spatio-temporal patterns of neurodegenerative disease hospitalizations in mainland Portugal.

Mariana Oliveira, Alberto Freitas, Ana Cláudia Teodoro, Hernâni Gonçalves

Abstract read
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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mariana Oliveira *RISE-Health, Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, Porto, Portugal.
Alberto Freitas *RISE-Health, Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, Porto, Portugal.
Ana Cláudia Teodoro *Department of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto, Porto, Portugal.
Hernâni Gonçalves *RISE-Health, Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, Porto, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neurodegenerative diseases are an increasing concern for the aging population worldwide. In Portugal, as in many other developed countries, the population is aging rapidly. Understanding temporal and spatial patterns is of utmost relevance to help manage the burden these diseases place on the healthcare system. Methods: In this retrospective study, we analyzed over 500,000 hospitalizations discharged between 2000 and 2016. We used the empirical Bayes method to compute the smoothed age-standardized hospitalization rates for each neurodegenerative disease, for all hospitalizations per year, and across administrative divisions (districts and municipalities). We then searched for data clusters using both global and local spatial autocorrelation methods based on the Moran index. Results: A steady increase in age-standardized hospitalization rates was observed throughout the study period. Statistically significant global spatial autocorrelation was found when considering all diseases per municipality (Moran's Conclusion: Temporal analysis showed increasing age-standardized hospitalization rates over time, likely reflecting the aging population in Portugal. The spatial analysis showed significant clustering, which may reflect geographic differences in hospitalization practices, access to care, population structure, or other contextual factors. Through this study, we hope to enlighten future research by providing insights into the anticipated spatio-temporal patterns.

Indexed as

HospitalizationNeurodegenerative DiseasesAgedBayes TheoremFemaleHumansMalePortugalRetrospective StudiesSpatio-Temporal Analysisenvironmental healthhospitalization ratesneurodegenerative diseasesspatial epidemiologyspatio-temporal analysis

Identifiers

PMID42326920
PMCPMC13277314

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