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21
datasets available to search
ShareScore release 0.9.0
Dataset results
21 results for “socioeconomic factors”
Dataset of Proportion of non-native plants in urban parks correlates with climate, socioeconomic factors and plant traits
<p>Full datasets for the research entitled 'Proportion of non-native plants in urban parks correlates with climate, socioeconomic factors and plant traits'.</p>
Dataset of "Social Robots and Sensors for Enhanced Ageing at Home: A Focus on Mobility and Socioeconomic Factors."
<p>This dataset supports the article:</p> <p>"Social Robots and Sensors for Enhanced Aging at Home: A Focus on Mobility and Socioeconomic Factors."</p> <p>For further details see the Readme.txt file.</p>
SOCIOECONOMIC, DEMOGRAPHIC AND ENVIRONMENTAL FACTORS AND COVID - 19 VACCINATION: INTERACTIONS AFFECTING EFFECTIVENESS
<p>This study analyses the relation between people fully vaccinated and mortality to assess the effectiveness of this health policy to cope with COVID-19 pandemic between a sample of 150 countries. Statistical analyses show a positive correlation between share of people fully vaccinated and total COVID-19 mortality in early 2022 (r= 0.65, p-value <.01). These results suggest that COVID-19 vaccinations cannot be a sufficient policy response to eradicate the overall negative impact of the new infectious disease in society. Although high levels of vaccinations in some countries, many demographic (density of population), environmental (air pollution), technological (equipment of non-invasive ventilators), biological (new variants), socioeconomic (health expenditures) factors, etc., influence the diffusion and negative effects of COVID-19 pandemic society. This study can provide new knowledge to improve crisis management and the preparedness of countries to cope with or prevent future pandemic crisis and negative effects in socioeconomic systems.</p>
Global analysis of environmental and socioeconomic factors associated with human burden of environmentally mediated pathogens
<p>This repository contains four datasets that support repeatability of the analyses in the Sokolow et al. paper published in <em>Lancet Planetary Health</em>. Descriptions of the four datasets are included in the metadata document. This study found that 80% of pathogen species known to infect humans are environmentally mediated, causing about 40% of contemporary infectious-disease burden (global loss of 130 million years of healthy life annually). More than 91% of this environmentally-mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. There were weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden there. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections."</p>
Ecological and socioeconomic factors associated with reported tick-borne viruses
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Data from: How Hurricanes Irma and Maria affected population dynamics and nutrient content of <em>Aedes aegypti</em> in San Juan, PR, USA: socioeconomic and temporal factors
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Global analysis of environmental and socioeconomic factors associated with human burden of environmentally mediated pathogens
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Temperature impacts on dengue incidence are nonlinear and mediated by climatic and socioeconomic factors
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Data from: Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery
Fine-scale information about urban vegetation and social-ecological relationships is crucial to inform both urban planning and ecological research, and high spatial resolution imagery is a valuable tool for assessing urban areas. However, urban ecology and remote sensing have largely focused on cities in temperate zones. Our goal was to characterize urban vegetation cover with sub-meter resolution aerial imagery, and identify social-ecological relationships of urban vegetation patterns in a tropical city, the San Juan Metropolitan Area, Puerto Rico. Our specific objectives were to: i) map vegetation cover using sub-meter spatial resolution (0.3 m) imagery; ii) quantify the amount of residential and non-residential vegetation; and iii) investigate the relationship between patterns of urban vegetation versus socioeconomic and environmental factors. We found that 61% of the San Juan Metropolitan Area was green, and that our combination of high spatial resolution imagery and object-based classification was highly successful for extracting vegetation cover in a moist tropical city (97% accuracy). In addition, simple spatial pattern analysis allowed us to separate residential from non-residential vegetation with 76% accuracy, and patterns of residential and non-residential vegetation varied greatly across the city. Both socioeconomic (e.g., population density, building age, detached homes) and environmental variables (e.g., topography) were important in explaining variations in vegetation cover in our spatial regression models. However, important socioeconomic drivers found in cities in temperate zones, such as income and home value, were not important in San Juan. Climatic and cultural differences between tropical and temperate cities may result in different social-ecological relationships. Our study provides novel information for local land use planners, highlights the value of high spatial resolution remote sensing data to advance ecological research and urban planning in tropical cities, and emphasizes the need for more studies in tropical cities.
Linking socioeconomic inequalities and type 2 diabetes through obesity and lifestyle factors among Mexican adults: a structural equations modeling approach
<p><strong>Objective. </strong>To assess the association between type 2 diabetes (DM2) and socioeconomic inequalities, mediated by the contribution of body mass index (BMI), physical activity (PA), and diet (diet-DII). <strong>Materials and methods</strong>. We conducted a cross-sectional analysis using data of adults participating in the Diabetes Mellitus Survey of Mexico City. Socioeconomic and demographic characteristics as well as height and weight, dietary intake, leisure time activity and the presence of DM2 were measured. We fitted a structural equation model (SEM) with DM2 as the main outcome, and BMI, diet-DII and PA served as mediator variables between socioeconomic inequalities index (SII) and DM2. <strong>Results. </strong>The prevalence of DM2 was 13.6%. From the fitted SEM, each standard deviation increases in the SII was associated with increased scores of DM2 (β=0.174, <em>P</em><0.001). <strong>Conclusion. </strong>The results in the present study show how high scores in the index of SII may influence the presence of DM2.</p>
Socioeconomic Status, Psychosocial Factors, and CVD Risk in Mexican-American Women
ClinicalTrials.gov study NCT00387166. IPD Sharing: Not stated. Countries: 1. Publications: 8.
Observing 3-5 Year Old Children's Use of Interactive Electronic Devices (IED) in the Family Home to Understand the Context These Devices Are Being Used in, Exploring Whether Socioeconomic Factors or P
ClinicalTrials.gov study NCT07373483. IPD Sharing: YES. Countries: 1. Publications: 0.
An Observational Study of Environmental and SocioEconomic Factors in Opioid Recovery
ClinicalTrials.gov study NCT03604861. IPD Sharing: NO. Countries: 1. Publications: 2.
Influence of Socioeconomic and Environmental Factors on the Natural History of Idiopathic Pulmonary Fibrosis
ClinicalTrials.gov study NCT04619199. IPD Sharing: NO. Countries: 1. Publications: 12.
An Observational Study of Environmental and Socioeconomic Factors in Opioid Recovery - Long Term
ClinicalTrials.gov study NCT04577144. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Linking socioeconomic inequalities and type 2 diabetes through obesity and lifestyle factors among Mexican adults: a structural equations modeling approach
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Data from: Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery
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Bangkok Noi District Electronic Health Database With Socioeconomic Factors From Bangkok Noi Model Project (BANMOP)
ClinicalTrials.gov study NCT06583694. IPD Sharing: YES. Countries: 0. Publications: 2.
Evaluation of the Nutritional Status of Omega-3 Fatty Acids and the Possible Influences of Dietary Patterns and Different Socioeconomic Factors, in a Spanish Population Over 60 Years of Age
ClinicalTrials.gov study NCT06916455. IPD Sharing: YES. Countries: 1. Publications: 0.
The Impact Of Media, Socioeconomic And Psychological Factors, Adoption Of Aesthetic Technology & CS
ClinicalTrials.gov study NCT07049354. IPD Sharing: NO. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.