The scope of this paper was to assess the health level in Brazilian states using the Health Development Index (HDI). The HDI consisted of the following dimensions: (1) Health resources: Availability and quality of health resources; (2) Primary Healthcare coverage and sanitation; (3) Effectiveness of health policies. Each dimension was composed of a set of indicators obtained from national databases. In 2005, Brazil had an intermediate level of development of health, having progressed from a low level in 1999. Most states had medium and low development, with deficits in resources and coverage. The dimension of effectiveness was highly developed nationwide. With the construction of a synthetic indicator (HDI) it was possible to detect that in most of the country there are severe deficiencies in the availability and quality of health resources. These results can help health managers to tackle the challenge of making public health universal.
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http://dx.doi.org/10.1590/s1413-81232012000900027 | DOI Listing |
Sci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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December 2024
School of Biotechnology, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand.
Effector proteins secreted via the type III secretion system (T3SS) of nitrogen-fixing rhizobia are key determinants of symbiotic compatibility in legumes. Previous report revealed that the T3SS of Bradyrhizobium sp. DOA9 plays negative effects on Arachis hypogaea symbiosis.
View Article and Find Full Text PDFNat Commun
December 2024
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Sand and dust storms (SDS) can cause adverse health effects, with the oxidative potential (OP) and environmentally persistent free radicals (EPFRs) inducing oxidative stress. We mapped the OP and EPFRs concentrations at 1735 sites in China during SDS periods using experimental data for 2021-2023 and a random forest model. We examined 855,869 hospitalizations during SDS events for 2015-2022 in Beijing, China.
View Article and Find Full Text PDFEcol Lett
January 2025
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
Theory suggests that animals make hierarchical, multiscale resource selection decisions to address the hierarchy of factors limiting their fitness. Ecologists have developed tools to link population-level resource selection across scales; yet, theoretical expectations about the relationship between coarse- and fine-scale selection decisions at the individual level remain elusive despite their importance to fitness. With GPS-telemetry data collected across California, USA, we evaluated resource selection of mountain lions (Puma concolor; n = 244) relative to spatial variation in human-caused mortality risk.
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January 2025
Department of Cellular and Molecular Biology, Harvard University, Cambridge, Massachusetts, USA.
Climate change is intensifying extreme weather events, with severe implications for ecosystem dynamics. A key behavioural mechanism whereby animals may cope with such events is by altering their social structure, which in turn could influence epidemic risk. However, how and to what extent natural disasters affect disease risk via changes in sociality remains unexplored in animal populations.
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