Survey data on household spatial quality and experiences of stress.
Ontology highlight
ABSTRACT:
SUBMITTER: Campagna G
PROVIDER: S-EPMC4796714 | biostudies-literature | 2016 Jun
REPOSITORIES: biostudies-literature
Publications
Survey data on household spatial quality and experiences of stress.
Data in brief 20160309
This data article describes a dataset of 1,668 cases representing self-reported assessments of housing inadequacy and perceived housing stress. The dataset also contains person-level and household-level demographic data to contextualize the above measures. A second supplemental file contains the text of the survey instrument. Discussion of theoretical background and measures development as well as a more detailed socioeconomic profile of the sample is available in the associated research article ...[more]
Similar Datasets
Project description:The data presented in this article are related to the research paper titled, "The impact of a household biogas programme on energy use and expenditure in East Java" (A.S. Bedi, R. Sparrow, L. Tasciotti, 2017) [1]. This Data in Brief article presents two rounds of survey data conducted in 2011 and 2012 for a panel of 677 dairy farm households in the province of East Java, Indonesia. The survey relied on structured questionnaires to collect data on the production and use of biogas, the use of other non-renewable energy sources, farm characteristics, and socioeconomic and demographic characteristics of households. The panel data set in STATA format and do files are made publicly available to promote replicability and extended analyses of a sustainable energy initiative.
| S-EPMC5854924 | biostudies-literature
Project description:OBJECTIVES:Air pollution causes various disease in exposed populations, and can lead to premorbid health effects manifested as both physical and psychological functional impairment. The present study investigated the subjective stress level in daily life in relation to the level of air pollution. METHODS:Data from the Community Health Survey (2013), comprising 99,162 men, and 121,273 women residing in 253 healthcare administrative districts, were combined with air pollutant concentration modelling data from the Korean Air Quality Forecasting System, and were stratified by subjective stress levels into five strata for multiple logistic regression. Levels of exposure were divided into five quintiles according to the annual concentration of nitrogen dioxide (NO2), and were analyzed using a single-pollutant model using NO2 concentration only, and a multi-pollutant model adjusted for the concentration of particulate matter <10 ?m in diameter. RESULTS:Analysis of men and women in various age groups showed the highest odds ratio (OR) for subjective stress level at the highest NO2 concentration quintile in men and women aged 30-64 years (men: 2.91; 95% confidence interval [CI], 2.12 to 4.01; women: 1.82; 95% CI, 1.32 to 2.51). As the NO2 concentration quintile increased, the OR increased. Men showed higher ORs than women in all strata. CONCLUSIONS:In the present study, annual NO2 concentrations were found to be associated with subjective stress levels. This association was especially clear among socioeconomically active men and women aged 30-64 years.
| S-EPMC6178364 | biostudies-other
Project description:The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R2 value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses.
| S-EPMC8921279 | biostudies-literature
Project description:Based on 1128 survey questionnaires, main information on urban and rural household electricity consumption was obtained. Original data included household income, the price of electricity, all kinds of electrical appliances, purchase price of main appliances, household size, electricity consumption, as well as power, daily use time of electrical appliances in this data article. These data fully reflected behavior, preferences and living pattern of sample households in electricity use and provided the basis for analyzing the relationship between household electricity consumption and the quality of life ("Does electricity consumption improve residential living status in less developed regions? An empirical analysis using the quantile regression approach" [1]).
| S-EPMC4833132 | biostudies-literature
Project description:SummaryThe advent of spatial transcriptomics has revolutionized our understanding of the spatial heterogeneity in tissues, providing unprecedented insights into the cellular and molecular mechanisms underlying biological processes. Although quality control (QC) critical for downstream data analyses, there is currently a lack of specialized tools for one-stop spatial transcriptome QC. Here, we introduce SpatialQC, a one-stop QC pipeline, which generates comprehensive QC reports and produces clean data in an interactive fashion. SpatialQC is widely applicable to spatial transcriptomic techniques.Availability and implementationsource code and user manuals are available via https://github.com/mgy520/spatialQC, and deposited on Zenodo (https://doi.org/10.5281/zenodo.12634669).
| S-EPMC11333854 | biostudies-literature
Project description:BackgroundMost injury care research in low-income contexts such as Malawi is facility centric. Community-derived data is needed to better understand actual injury incidence, health system utilisation and barriers to seeking care following injury.MethodsWe administered a household survey to 2200 households in Karonga, Malawi. The primary outcome was injury incidence, with non-fatal injuries classified as major or minor (> 30 or 1-29 disability days respectively). Those seeking medical treatment were asked about time delays to seeking, reaching and receiving care at a facility, where they sought care, and whether they attended a second facility. We performed analysis for associations between injury severity and whether the patient sought care, stayed overnight in a facility, attended a second facility, or received care within 1 or 2 h. The reason for those not seeking care was asked.ResultsMost households (82.7%) completed the survey, with 29.2% reporting an injury. Overall, 611 non-fatal and four fatal injuries were reported from 531 households: an incidence of 6900 per 100,000. Major injuries accounted for 26.6%. Three quarters, 76.1% (465/611), sought medical attention. Almost all, 96.3% (448/465), seeking care attended a primary facility first. Only 29.7% (138/465), attended a second place of care. Only 32.0% (142/444), received care within one hour. A further 19.1% (85/444) received care within 2 h. Major injury was associated with being more likely to have; sought care (94.4% vs 69.8% p < 0.001), stayed overnight at a facility (22.9% vs 15.4% P = 0.047), attended a second place of care (50.3% vs 19.9%, P < 0.001). For those not seeking care the most important reason was the injury not being serious enough for 52.1% (74/142), followed by transport difficulties 13.4% (19/142) and financial costs 5.6% (8/142).ConclusionInjuries in Northern Malawi are substantial. Community-derived details are necessary to fully understand injury burden and barriers to seeking and reaching care.
| S-EPMC10809521 | biostudies-literature
Project description:To target food security interventions for smallholder households, decision makers need large-scale information, such as maps on poverty, food security and key livelihood activities. Such information is often based on expert knowledge or aggregated data, despite the fact that food security and poverty are driven largely by processes at the household level. At present, it is unclear if and how household level information can contribute to the spatial prediction of such welfare indicators or to what extent local variability is ignored by current mapping efforts. A combination of geo-referenced household level information with spatially continuous information is an underused approach to quantify local and large-scale variation, while it can provide a direct estimate of the variability of welfare indicators at the most relevant scale. We applied a stepwise regression kriging procedure to translate point information to spatially explicit patterns and create country-wide predictions with associated uncertainty estimates for indicators on food availability and related livelihood activities using household survey data from Uganda. With few exceptions, predictions of the indicators were weak, highlighting the difficulty in capturing variability at larger scale. Household explanatory variables identified little additional variation compared to environmental explanatory variables alone. Spatial predictability was strongest for indicators whose distribution was determined by environmental gradients. In contrast, indicators of crops that were more ubiquitously present across agroecological zones showed large local variation, which often overruled large-scale patterns. Our procedure adds to existing approaches that often only show large-scale patterns by revealing that local variation in welfare is large. Interventions that aim to target the poor must recognise that diversity in livelihood activities for income generation within any given area often overrides the variability of livelihood activities between distant regions in the country.
| S-EPMC6292625 | biostudies-literature
Project description:Earth observation (EO) is the use of remote sensing and in situ observations to gather data on the environment. It finds increasing application in the study of environmentally modulated neglected tropical diseases (NTDs). Obtaining and assuring the quality of the relevant spatially and temporally indexed EO data remain challenges. Our objective was to review the Earth observation products currently used in studies of NTD epidemiology and to discuss fundamental issues relating to spatial data quality (SDQ), which limit the utilization of EO and pose challenges for its more effective use. We searched Web of Science and PubMed for studies related to EO and echinococossis, leptospirosis, schistosomiasis, and soil-transmitted helminth infections. Relevant literature was also identified from the bibliographies of those papers. We found that extensive use is made of EO products in the study of NTD epidemiology; however, the quality of these products is usually given little explicit attention. We review key issues in SDQ concerning spatial and temporal scale, uncertainty, and the documentation and use of quality information. We give examples of how these issues may interact with uncertainty in NTD data to affect the output of an epidemiological analysis. We conclude that researchers should give careful attention to SDQ when designing NTD spatial-epidemiological studies. This should be used to inform uncertainty analysis in the epidemiological study. SDQ should be documented and made available to other researchers.
| S-EPMC4683053 | biostudies-literature
Project description:BackgroundEpidemiological and biomedical evidence link adverse childhood experiences (ACEs) with health-harming behaviors and the development of non-communicable disease in adults. Investment in interventions to improve early life experiences requires empirical evidence on levels of childhood adversity and the proportion of HHBs potentially avoided should such adversity be addressed.MethodsA nationally representative survey of English residents aged 18 to 69 (n = 3,885) was undertaken during the period April to July 2013. Individuals were categorized according to the number of ACEs experienced. Modeling identified the proportions of HHBs (early sexual initiation, unintended teenage pregnancy, smoking, binge drinking, drug use, violence victimization, violence perpetration, incarceration, poor diet, low levels of physical exercise) independently associated with ACEs at national population levels.ResultsAlmost half (47%) of individuals experienced at least one of the nine ACEs. Prevalence of childhood sexual, physical, and verbal abuse was 6.3%, 14.8%, and 18.2% respectively (population-adjusted). After correcting for sociodemographics, ACE counts predicted all HHBs, e.g. (0 versus 4+ ACEs, adjusted odds ratios (95% confidence intervals)): smoking 3.29 (2.54 to 4.27); violence perpetration 7.71 (4.90 to 12.14); unintended teenage pregnancy 5.86 (3.93 to 8.74). Modeling suggested that 11.9% of binge drinking, 13.6% of poor diet, 22.7% of smoking, 52.0% of violence perpetration, 58.7% of heroin/crack cocaine use, and 37.6% of unintended teenage pregnancy prevalence nationally could be attributed to ACEs.ConclusionsStable and protective childhoods are critical factors in the development of resilience to health-harming behaviors in England. Interventions to reduce ACEs are available and sustainable, with nurturing childhoods supporting the adoption of health-benefiting behaviors and ultimately the provision of positive childhood environments for future generations.
| S-EPMC4234527 | biostudies-literature
Project description:BACKGROUND:Iodine deficiency disorder is a significant public health problem, affecting both developed and developing nations worldwide. It is associated with poor body growth and irreversible mental retardation. However, little is known about the spatial distribution and determinants of household iodized salt utilization in Ethiopia. Therefore, this study aimed to explore the spatial distribution and determinants of iodized salt utilization at national level. METHODS:Ethiopian Demographic and Health Survey 2016 data was used to investigate the spatial distribution and determinants of household iodized salt utilization in Ethiopia. ArcGIS 10.6 and SaTScan™ version 9.6 software were used to explore the spatial distribution and detect significant clusters, respectively. The odds ratio with its 95% confidence interval (CI) was determined for potential determinants included in the multivariable multilevel logistic regression model. RESULTS:Household iodized salt utilization was spatially clustered in Ethiopia (Moran's Index?=?0.076, p-value?=?0.01). The significant hotspot areas with high iodized salt utilization were located in Benishangul, Amhara, Gambella, Tigray and Northwest Oromia regions. Significant cold spot areas (areas with low iodized salt utilization) were found in Somali, and East Afar regions. Those households with higher education level ((Adjusted Odds Ratio [AOR] =1.49, 95% CI =1.14-1.93), high community level education (AOR?=?1.51, 95% CI?=?1.03-2.20), middle wealth index (AOR?=?1.31, 95% CI?=?1.04-1.65) and high community media exposure (AOR?=?1.52, 95% CI?=?1.07-2.17) had higher odds of iodized salt utilization. CONCLUSIONS:Household iodized salt utilization had significant spatial variation across the country. Both household and community level variables were found to be associated with household iodized salt utilization in Ethiopia. Therefore, increasing the education level, wealth status and community media exposure is recommended to improve iodized salt utilization in a country. A targeted intervention is also needed for those regions with low household iodized salt utilization.
| S-EPMC7500019 | biostudies-literature