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45 results for “socioeconomic status”
Dataset for the manuscript Marmet, Wicki, Gmel, Gachoud, Daeppen, Bertholet, Studer (2021). The psychological impact of the COVID-19 crisis is higher among young Swiss men with a lower socioeconomic status: evidence from a cohort study. Plos One. DOI:10.1371/journal.pone.0255050
<p>Dataset for the manuscript Marmet, Wicki, Gmel, Gachoud, Daeppen, Bertholet, Studer (2021). The psychological impact of the COVID-19 crisis is higher among young Swiss men with a lower socioeconomic status: evidence from a cohort study. Plos One DOI:10.1371/journal.pone.0255050</p> <p>The dataset contains all data needed to reproduce the results in the above cited manuscript. Variable description and labels can be found in the codebook. For further information on the instruments used please refer to the manuscript.</p> <p> </p>
Socioeconomic status and adiposity in childhood cancer survivors: A cross-sectional retrospective study
<p>This dataset contains information on selected indicators of socioeconomic status and anthropometric indicators of adiposity in a population of childhood cancer survivors from the Late Effect Outpatient Clinic at St. Anne's Hospital in Brno, Czech Republic. </p>
Data for Age and socioeconomic status in relation to risk of maternal anemia among the Ariaal of northern Kenya
<p>Data used for a paper entitled, "Age and socioeconomic status in relation to risk of maternal anemia among the Ariaal agropastoralists of northern Kenya"</p>
Socioeconomic status affects the incidence of COVID-19 in Chilean multiple sclerosis patients
<p><span><b><span>Objective: </span></b>To investigate the frequency of coronavirus disease (COVID-19) in patients with multiple sclerosis (pwMSs) living in a high socioeconomic vulnerability area in Chile.<b> </b></span></p> <p><span><b><span>Methods:</span></b> In this prospective cohort study, we compared the frequency of COVID-19 in 52 Chilean pwMSs on disease-modifying treatments (DMTs), living in urban municipalities with low-income/high-poverty levels, with that previously reported in pwMSs living in municipalities with high-income/low-poverty rates in Santiago, Chile. Demographic and clinical features of the pwMSs were obtained from their last consultation between March 3, 2020, and August 29, 2020.<b> </b></span></p> <p><span><b><span>Results:</span></b> In the low-income pwMSs, the mean patient age was 34 years, 69% were women, mean disease duration was 3 years, and mean Expanded Disability Status Scale score was 1.6. Of these, 61.5% pwMSs (32/52) underwent quarantine during the study period. <span>COVID-19 diagnosis was confirmed by reverse transcriptase polymerase chain reaction in five patients (10%): two were on glatiramer acetate, one was on fingolimod, and two were on alemtuzumab. All pwMSs with COVID-19 recovered fully. </span>The previously reported frequency of confirmed COVID-19 in middle‒upper income pwMSs living in Santiago was 1%. The frequency of COVID-19 among pwMSs in the low- and middle‒high income inhabitants of Santiago differed significantly (z = -4.3235, p < 0.00001; one-tailed Fisher exact test, p < 0.01).</span></p> <p><span><b>Conclusion: </b>The frequency of COVID-19 in the low-income/high-poverty cohort in Santiago, Chile, was markedly high. Accordingly, high socioeconomic vulnerability should be considered as an important risk factor for COVID-19 in pwMSs.</span></p>
Reduced Nicotine Content Cigarettes in Smokers of Lower Socioeconomic Status
ClinicalTrials.gov study NCT01928719. IPD Sharing: NO. Countries: 1. Publications: 1.
Socioeconomic status affects the incidence of COVID-19 in Chilean multiple sclerosis patients
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Dateset The "blue eyed" in our school – overcoming stereotypes as the pathway to creating better conditions for pupil development in the school class - control group and equal socioeconomic status groups
<p>Dateset The “blue eyed” in our school – overcoming stereotypes as the pathway to creating better conditions for pupil development in the school class - control group and equal socioeconomic status groups</p>
Data from: Relationship between socioeconomic status and HIV infection: findings from a survey in the Free State and Western Cape Provinces of South Africa
Background Studies have shown a mixed association between socioeconomic status [SES] and prevalent HIV infection across and within settings in sub-Saharan Africa. In general, the relationship between years of formal education and HIV infection changed from a positive to a negative association with maturity of the HIV epidemic. Our objective was to determine the association between SES and HIV in women of reproductive age in the Free State [FSP] and Western Cape Provinces [WCP] of South Africa [SA]. Study design Cross sectional Setting South Africa Methods We conducted secondary analysis on 1906 women of reproductive age from a 2007-2008 survey that evaluated effectiveness of Prevention of Mother-to-Child HIV Transmission programs. SES was measured by household wealth quintiles, years of formal education and employment status. Our analysis principally utilized logistic regression for survey data. Results There was a significant negative trend between prevalent HIV infection and wealth quintile in WCP [p-value<0.001] and FSP [p-value=0.025]. In adjusted analysis, every additional year of formal education was associated with a 10% [adjusted Odds Ratio [aOR] 0.90 [95% Confidence Interval [CI]: 0.85-0.96] significant reduction in risk of prevalent HIV infection in WCP but no significant association was observed in FSP [aOR 0.99 CI: 0.89-1.11]. There was no significant association between employment and prevalent HIV in each province: [aOR 1.54 CI: 0.84-2.84] in WCP and [aOR 0.96 CI: 0.71-1.30] in FSP. Conclusion The association between HIV infection and SES differed by province and by measure of SES and underscores the disproportionately higher burden of prevalent HIV infection among poorer and lowly educated women. Our findings suggest the need for re-evaluation of whether current HIV prevention efforts meet needs of the least educated [in WCP] and the poorest women [both WCP and FSP], and point to the need to investigate additional or tailored strategies for these women.
Socioeconomic Status, Psychosocial Factors, and CVD Risk in Mexican-American Women
ClinicalTrials.gov study NCT00387166. IPD Sharing: Not stated. Countries: 1. Publications: 8.
The Burden of Childhood Anemia in Bangladesh: Does Socioeconomic Status Matter?
ClinicalTrials.gov study NCT03126253. IPD Sharing: NO. Countries: 1. Publications: 1.
The Socioeconomic Status and Child Characteristics on the Physical Therapy Outcome in Children With Spastic Cerebral Palsy
ClinicalTrials.gov study NCT04160403. IPD Sharing: YES. Countries: 1. Publications: 0.
Individualized Dietetic Intervention-eating Habits in Obese Hispanic Children of Low Socioeconomic Status
ClinicalTrials.gov study NCT01925976. IPD Sharing: Not stated. Countries: 1. Publications: 27.
Impact of Cataract Surgery to Socioeconomic Status in Rural Area
ClinicalTrials.gov study NCT03020056. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Data from: Relationship between socioeconomic status and HIV infection: findings from a survey in the Free State and Western Cape Provinces of South Africa
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Data from: Hospital distance, socioeconomic status, and timely treatment of ischemic stroke
Objective: To determine whether lower socioeconomic status (SES) and longer home-hospital driving time are associated with reductions in tPA administration and timeliness of the treatment. Methods: We conducted a retrospective observational study using data from the Get With The Guidelines-Stroke Registry (GWTG-Stroke) between January 2015 to March 2017. The study included 118,683 ischemic stroke patients age ≥18 who were transported by EMS to one of 1,489 US hospitals. We defined each patient's SES based on their zip code median household income. We calculated the driving time between each patient's home zip code and the hospital where they were treated, using the Google Maps Directions Application Programing Interface. The primary outcomes were tPA administration and onset-to-arrival time (OTA). Outcomes were analyzed using hierarchical multivariable logistic regression models. Results: SES was not associated with OTA (p=0.31) or tPA administration (p=0.47), but was associated with the secondary outcomes of onset-to-treatment time (p=0.0160) and in-hospital mortality (p=0.0037), with higher SES associated with shorter OTT and lower in-hospital mortality. Driving time was associated with tPA administration (p <0.001) and OTA (p <0.0001), with lower odds of tPA (0.83, 0.79-0.88) and longer OTA (1.30, 1.24-1.35) in patients with the longest versus shortest driving time quartiles. Lower SES quintiles were associated with slightly longer driving time quartiles (p=0.0029), but there was no interaction between the SES and driving time for either OTA (p=0.1145) or tPA (p=0.6103). Conclusions: Longer driving times were associated with lower odds of tPA administration and longer OTA, however SES did not modify these associations.
The socioeconomic status of cities covaries with avian life-history strategies
<p>Cities are the planet's newest ecosystem and thus provide the opportunity to study community formation directly following major permanent environmental change. The human social and built components of environments can vary widely in different cities, yet it is largely unknown how features of cities covary with the traits of colonizing species despite humans being the ultimate cause of environments and disturbances in cities. We constructed a dataset from open-source data comprised of 13,502 breeding season observations of 213 Passerine species observed in 551 Census-defined urban areas across the United States. We found that as a city became more compact with less sprawl it tended to support more migratory species and species with lower body mass, shorter lifespans, and larger clutches. We also found that species had lower body mass in cities with higher median income, and higher body mass in highly populated cities. Our results highlight the complexity of human-dominated urban ecosystems, where human socioeconomic actions and everyday activities intermix leading to structurally heterogeneous environments that support the colonization of some species over others.</p>
Data from: Socioeconomic status effects on health vary between rural and urban Turkana
<p>Background and objectives: Understanding the social determinants of health is a major goal in evolutionary biology and human health research. Low socioeconomic status (often operationalized as absolute material wealth) is consistently associated with chronic stress, poor health, and premature death in high income countries. However, the degree to which wealth gradients in health are universal<span>—</span>or are instead made even steeper under contemporary, post-industrial conditions<span>—</span>remains poorly understood.</p> <p>Methodology: We quantified absolute material wealth and several health outcomes among a population of traditional pastoralists, the Turkana of northwest Kenya, who are currently transitioning toward a more urban, market-integrated lifestyle. We assessed whether wealth associations with health differed in subsistence-level versus urban contexts. We also explored the causes and consequences of wealth-health associations by measuring serum cortisol, potential sociobehavioral mediators in early life and adulthood, and adult reproductive success (number of surviving offspring).</p> <p>Results: Higher socioeconomic status and greater material wealth predicts better self-reported health and more offspring in traditional pastoralist Turkana, but worse cardiometabolic health and fewer offspring in urban Turkana. We do not find robust evidence for either direct biological mediators (i.e., cortisol) or indirect sociobehavioral mediators (e.g., adult diet or health behaviors, early life experiences) of wealth-health relationships in either context.</p> <p>Conclusions and implications: While social gradients in health are well-established across a variety of primate species, and in humans, across a variety of socioecological contexts, we show that the relationship between wealth and health can vary within a single population. Our findings emphasize that changes in economic and societal circumstances may directly alter how, why, and under what conditions socioeconomic status is predictive of health.</p>
Data and code for 'Baseline food insecurity moderates the acute effect of subjective socioeconomic status on food consumption'
<p>Data and R code underlying the paper 'Baseline food insecurity moderates the acute effect of subjective socioeconomic status on food consumption'</p> <p>This version uploaded in association with a new version of the paper and a different analysis strategy, May 2019</p>
Life Course Socioeconomic Status, Social Context and Cardiovascular Disease
ClinicalTrials.gov study NCT00014833. IPD Sharing: YES. Countries: 0. Publications: 1.
Study on the Relationship Between Chinese Women's Perinatal Mental Health and Socioeconomic Status
ClinicalTrials.gov study NCT04185207. IPD Sharing: NO. Countries: 0. Publications: 3.
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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.