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334 results for “household”
SARS-CoV-2 Seroprevalence in a Rural and Urban Household Cohort, South Africa, July 2020–September 2021
<p>Early results of the PHIRST-C study seroprevalence results in South Africa</p>
South Sudan Household Unity study for COVID-19
<p>Results from the South Sudan Household Unity study for COVID-19</p>
Transmission Dynamics of COVID-19 Disease among household contacts in Delhi, India (SARS CoV-2 HT Study)
<p>Results from households in the MAMC Delhi FFX Unity study </p>
Finland Household Unity study for COVID-19
<p>Results from the Finland Household Unity study for COVID-19</p>
Replication package for "A Rise for Grandma: Pensions and Household Expenditure"
<p>Parraga Rodriguez, S. (2022). "A Rise for Grandma: Pensions and Household Expenditure", The Economic Journal.</p>
Socioeconomic impacts on Andean adolescents' growth: variation between households, between communities, and over time
<p>Background/Objectives</p> <p>We evaluated potential socioeconomic contributors to variation in Andean adolescents' growth between households within a peri-urban community undergoing rapid demographic and economic change, between different community types (rural, peri-urban, urban), and over time. Because growth monitoring is widely used for assessing community needs and progress, we compared the prevalences of stunting, underweight, and overweight estimated by three different growth references.</p> <p>Results</p> <p>Alteños' height averaged ∼0.8SD/∼0.6SD/∼2SDs greater than adolescents' height in urban and rural communities measured in 1983/1998/1977, respectively. Overweight prevalence was comparable to the WHO, and lower than MESA and Puno, references. Stunting was 8.5/2.5/0.5 times WHO/MESA/Puno samples, respectively. Female Alteños' growth was positively associated with household and maternal income indices.</p> <p>Conclusions/Implications</p> <p>Both peri-urban conditions and temporal trends contributed to gains in Alteños' growth. Rural out-migration can alleviate migrants' poverty, partly because of more diverse economic options in urbanized communities, especially for women. Nonetheless, Alteños averaged below WHO and MESA height and weight medians. Evolved biological adaptations to environmental challenges, and the consequent variability in growth trajectories, favors using multiple growth references. Growth monitoring should be informed by community- and household-level studies to detect and understand local factors causing or alleviating health disparities. Lay Summary Andean adolescents exhibited elevated rates of stunting; their height varied with socioeconomic status within and between high-altitude communities. Unlike some lowland populations, the prevalence of overweight/obesity was not elevated. Population-specific growth assessments and targeted interventions (e.g., maternal education and employment) are likely to help alleviate disparities in Andean children's growth.</p>
Perceived quality of care among households ever enrolled in a community-based health insurance scheme in two districts of northeast Ethiopia: A community-based, cross-sectional study
<p class="MsoNormal"><strong><span>Objectives: </span></strong><span>The purpose of this study was to examine how clients perceived the quality of health care they received and to identify associated factors both at the individual and facility levels.</span></p> <p class="MsoNormal"><strong><span>Design: </span></strong><span>A community-based, cross-sectional study.<span> </span></span></p> <p class="MsoNormal"><strong><span>Setting:</span></strong><span> Two rural districts of northeast Ethiopia</span><span>, Tehulederie and Kallu.</span></p> <p class="MsoNormal"><strong><span>Participants:</span></strong><span> 1081 rural households who had ever been enrolled in community-based health insurance and visited a health center at least once in the previous 12 months.<span> </span>Furthermore, 194 health care providers participated in the study to provide cluster-level data. <a name="_Hlk84940584"></a></span></p> <p class="MsoNormal"><span><strong><span>Outcome measures</span></strong></span><span><span>: The outcome variable of interest was the perceived quality of care, which was measured using a 17-item scale. </span></span><span>Respondents were asked to rate the degree to which they agreed on 5-point response items relating to their experiences with health care in the outpatient departments of nearby health centers. A multilevel linear regression analysis was used to identify predictors of perceived quality of care. </span></p> <p class="MsoNormal"><strong><span>Results:</span></strong><span> The mean perceived quality of care was 70.28 (SD=8.39). <a name="_Hlk85270466"></a>Five dimensions of perceived quality of care were extracted from the factor analysis, with the patient-provider communication dimension having the highest <span>mean score (M=77.84, SD=10.12), and information provision having the lowest (M=64.67, SD=13.87). Wealth status, current insurance status, perceived health status, presence of chronic illness, and time to a recent health center visit </span></span><span><span>were individual level variables that showed a significant association with the perceived quality of care. At the cluster level, the work experience of health care providers, patient volume, and an interaction term between patient volume and staff job satisfaction also showed a significant association</span><span>.</span></span><span><span> <span> </span></span></span></p> <p class="MsoNormal"><strong><span>Conclusions:</span></strong><span> Much work remains to improve the quality of care, especially on information provision and access to care quality dimensions. A range of individual and cluster-level characteristics influence the perceived quality of care. For a better quality of care, it is vital to optimize the patient-provider ratio and enhance staff job satisfaction.</span></p>
Replication package for: "The Short- and Long-Run Impacts of Free Education on Schooling: Direct Effects and Intra-household Spillovers"
<p>The replication package contains the following folders: (1) The "do" folder, which contains all ".do" and ".R" files used to reproduce all figures and tables in the paper and the appendix; (2) The "outputs" folder, which stores all figures and tables; and (3) The "add-ons" folder, which includes all necessary Stata or R add-on packages. Additionally, the replication package contains a README PDF file to illustrate the result replication procedure.</p>
Economic and Nutritional Losses Result from Household Food Waste Behavior in the Special Region of Yogyakarta
<p>This material has presented on 2nd International Conference on Advance Research in Agriculture and Food 2023 in October 25, 2023.</p>
Multi-survey data collection on Finnish household waste sorting and recycling
<p>This dataset consists of surveys that have been marked with letters from A to L.</p> <ul> <li>Surveys A, B, D, E, F, G, H, I, K and L have at least one questionnaire. Each questionnaire, presented with questions in both Finnish and English, has its results displayed in the dataset table. Dataset tables haven't been translated, they are in Finnish.</li> <li>Survey C is an interview based study. Questions have been translated into English, but the interview data is in Finnish only.</li> <li>Survey J is an experiment on how to target communication in social media. The dataset shows how many times each post has been watched, which hastags were used etc.</li> </ul> <p>The work was carried out by groups of students as part of the Sustainable Product Development Project course in November-December 2023. All the surveys are interconnected in one way or another with the promotion of household waste sorting and recycling, as the topic of the assignment came from HAMK Smart research group's KOTILO project (Participatory Design of Source Separation in Recycling). For more information, go to hamk.fi/kotilo</p> <p>Each survey is licensed under CC BY 4.0 Attribution 4.0 International for the respective group of students, the names of the students are at the beginning of each dataset.</p>
The CORESIDENCE Database: National and Subnational Data on Household and Living Arrangements Around the World, 1964-2021
<p>Households are the fundamental units of co-residence and play a crucial role in social and economic reproduction worldwide. They are also widely used as units of enumeration for data collection purposes, with substantive implications for research on poverty, living conditions, family structure, and gender dynamics. However, reliable comparative data on households and changes and living arrangements around the world is still under development. The CORESIDENCE database (CoDB) aims to bridge the existing data gap by offering valuable insights not only into the documented disparities <em>between</em> countries but also into the often-elusive regional differences <em>within</em> countries. By providing comprehensive data, it facilitates a deeper understanding of the complex dynamics of co-residence around the world. This database is a significant contribution to research, as it sheds light on both macro-level variations across nations and micro-level variations within specific regions, facilitating more nuanced analyses and evidence-based policymaking.</p> <p>The CoDB is composed of three datasets covering 155 countries (National Dataset), 3563 regions (Subnational Dataset), and 1511 harmonized regions (Subnational-Harmonized Dataset) for the period 1960 to 2021, and it provides 146 indicators on household composition and family arrangements across the world. </p> <p>This repository is composed of the following elements: a RData file named CORESIDENDE_DATABASE containing the CoDB in the form of a List. </p> <p>The CORESIDENDE_DB list object is composed of six elements:</p> <ol> <li>NATIONAL: a data frame with the household composition and living arrangements indicators at the national level.</li> <li>SUBNATIONAL: a data frame with the household composition and living arrangements indicators at the subnational level computed over the original subnational division provided in each sample and data source.</li> <li>SUBNATIONAL_HARMONIZED: a data frame with the household composition and living arrangements indicators computed over the harmonized subnational regions.</li> <li>SUBNATIONAL_BOUNDARIES_CORESIDENCE: a spatial data frame (a sf object) with the boundary’s delimitation of the subnational harmonized regions created for this project.</li> <li>CODEBOOK: a data frame with the complete list of indicators, their code names and description.</li> <li>HARMONIZATION_TABLE: a data frame with the full list of individual country-year samples employed in this project and their state of inclusion in the 3 datasets composing the CoDB.</li> </ol> <p>Elements 1, 2, 3, 5 and 6 of the R list are also provided as <em>csv</em> files under the same names. Element 4, the harmonized boundaries, is at disposal as <em>gpkg</em> (Geopackage) file.</p> <p><strong>Articles published by the CORESIDENCE team</strong></p> <p><a href="https://www.nature.com/articles/s41597-024-02964-3" rel="nofollow">2024, Scientific Data, <strong>CORESIDENCE: National and subnational data on household size and composition around the world, 1964–2021</strong></a></p> <p><a href="https://genus.springeropen.com/articles/10.1186/s41118-024-00211-6" rel="nofollow">2024, Genus, <strong>A global perspective on household size and composition, 1970–2020</strong></a></p> <p><a href="https://onlinelibrary.wiley.com/doi/10.1111/padr.12603" rel="nofollow">2024, Population and Development Review, <strong>Trends in Living Arrangements Around the World</strong></a></p>
Household Fuel Holder Use
<p>Household fuel holder use - not using, and using correctly </p>
Socio-Economic Factors Influencing Biogas Technology Uptake among Rural Households in Kuresoi South Sub-County, Nakuru County
<p>Biogas technology presents an alternative sustainable energy source that offers an opportunity to transform energy security, environmental sustainability, and reduction in greenhouse gas emissions. The research study explores the socioeconomic factors affecting biogas technology uptake among rural households in Kuresoi South Sub-County, Nakuru County. This is a descriptive study design based on the use of both primary and secondary data sources. The data collection covered 155 respondents through the use of questionnaires, focus group discussions, key informant interviews and observations. Selection of the respondents was done by using systematic random sampling, while data analysis was done using descriptive statistics, chi-square tests, and cross-tabulation supported by SPSS version 26. Results indicated that despite high levels of awareness, the adoption of biogas technology was low, with firewood remaining the primary source of energy in 68% of the households. Fixed dome and tubular were the biogas digester types in use, since they are relatively cheaper and more durable; however, economic factors, mainly household income, were the main determinant of uptake. The chi-square results indicated that there was a significant relationship between household income and uptake of biogas, χ² = 9.531, p = 0.048, implying that the poorer a household is, the greater the financial barrier to the technology. Level of education, too had a say in energy adoption; education and energy choice had a strong association-since χ² = 12.814, p = 0.002-which depicted that more educated households were more likely to adopt the technology. The gender factor is insignificant in influencing energy choices, underlining a proof from the fact that χ² = 2.119, p = 0.346, where broader socio-economic factors played a much greater role in decisions. This study also revealed out that radio was the effective channel for knowledge sharing and information dissemination related to biogas technology. On the other hand, partial understanding of the technical aspects has acted as a big barrier to the better diffusion of this technology. In conclusion, income levels and education are two main factors affecting the uptake of biogas technology. Enhanced education, targeted financial support and better outreach strategies go toward increasing adoption rates and supporting transitions to sustainable energy in rural areas.</p>
Interaction of household air pollution and healthy lifestyle on the risk of sarcopenia: China Health and Retirement Longitudinal Study
Open the record for dataset details and reuse information.
Paradoxical risk mitigation behavior in private households
<p>Abstract</p> <p>More than 40% of registered foodborne outbreaks can be attributed to unsafe food handling practices in private households (World Health Organization (WHO), 2016). Although households represent the final stage of the food chain (where mitigation of food safety risks would be vital), consumers generally do not consider themselves to be a responsible actor in this respect (Taché & Carpentier, 2014). Poor hygiene and food handling practices are among the major risk factors for household-related <a href="https://www.sciencedirect.com/topics/food-science/food-borne-disease">foodborne illnesses</a>, specifically cross-contamination and inefficient handwashing. In this work, we present two studies in which we analyzed hygiene and safety aspects of the poultry handling habits of consumers. Study 1 was an in-home behavior observation study involving 15 households. Besides inefficient handwashing, washing of poultry meat in the sink was the most problematic behavior. <em>Salmonella</em> and/or <em>Campylobacter</em> spp. were detected in 47% of meat samples taken during the home visits. Study 2 was a nationally representative household survey (<em>N</em> = 1007). 83% of the respondents reported that they washed poultry meat before food preparation. Based on patterns of poultry washing practices, knowledge about and interest in food safety, and worries about the safety of homemade dishes, five clusters of consumers were identified. Only one of these clusters had a significantly reduced tendency to wash poultry before preparation. The results indicate that, paradoxically, the more the conscious consumers are of microbiological hazards, the more likely they are to wash their poultry: most consumers believe that washing poultry before preparation is good hygiene practice and are not aware of cross-contamination risk.</p>
Micro data from the Greek Household Budget Survey on energy consumption
<p>The dataset is the end product of compiling a number of datasets from the Greek Household Budget Survey, covering 13 years between 2004 and 2020. The variables included are basic socio-economic, demographic and housing characteristics, along with quantity and cost data of household energy sources.</p>
Data and Code for "Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica"
<p>Data and Code for "Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica"</p>
Household survey on water-related ecosystem services in the South West Mau, Kenya
<p>This household survey was conducted to investigate the perceived importance and socio-cultural value of the South West Mau forest for the provisioning of water-related ecosystem services for communities living adjacent to and further away from the forest. The dataset contains the questions from the household survey and the corresponding survey results (i.e. responses from participants). The respondents are classified according to their geographical location in the Chemosit catchment (upper, middle and lower catchment). The numbers in the column headings correspond to the question number in the household survey.</p>
Does educating children improve household wealth in the developing world? More evidence from the Young Lives dataset
<p>This dataset is the source data for which the above paper derives its results. Current working paper version</p>
Replication package for "How Consumption Carbon Emission Intensity Varies Across Spanish Households"
<p>This package replicated the empirical analysis of the paper "How Consumption Carbon Emission Intensity Varies Across Spanish Households".</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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