An information system based on data from the healthcare sector and related areas. The online portal gives researchers the opportunity to research various health topics including population, socio-economic factors, health insurance, health laws.

• Laws

• Population

  • Births
  • Deaths
  • Population Numbers
  • other

• Pregnancy, Births

• Terminations of Pregnancy

• Households, Families, Living Communities

• Social Conditions

  • Education
  • Habitation
  • Employment
  • Unemployment
  • Poverty and Disparity
  • Single parent
  • Income
  • Social Welfare
  • other

• Training of the Health Personnel

• Economy

• Research

• Private Health Insurance

• Statutory Health Insurance

  • Statutory Health Insurance: Income, Expenditure
  • Statutory Health Insurance: Members, Insured Persons
  • Statutory Health Insurance: Services
  • Statutory Health Insurance: Services (Pharmaceuticals)
  • Statutory Health Insurance: other

• Nursing Care Insurance

• Pension Insurance

  • Insured Persons
  • Rehabilitation Services
  • Pensions because of old age
  • Ppensions because of diminution of ability to wrk
  • Pensions because of death (widow/widower pensions)
  • other

• Accident Insurance, employers' liability insurance association

The Stata data file "CAP_Demographics_Jumla_Kavre_recoded.dta” and equivalent excel file of the same name comprises data collected by adolescent secondary school students during a "Citizen Science" project in the district of Kavre in the central hills of Nepal during April 2022 and in the district of Jumla in the remote mountains of West Nepal during June 2022. The project was part of a CIFF-funded Children in All Policies 2030 (CAP2030) project.

The data were generated by the students using a mobile device data collection form developed using "Open Data Kit (ODK) Collect" electronic data collection platform by Kathmandu Living Labs (KLL) and University College London (UCL) for the purposes of this study. Researchers from KLL and UCL trained the adolescents to record basic socio-demographic information about themselves and their households including caste/ethnicity, religion, education, water sources, assets, household characteristics, and income sources. The form also asked about their access to mobile phones or other devices and internet and their concerns with respect to climate change. The resulting data describe the participants in the citizen science project, but their names and addresses have been removed. The app and the process of gathering the data are described in a paper entitled "Citizen science for climate change resilience: engaging adolescents to study climate hazards, biodiversity and nutrition in rural Nepal" submitted to Wellcome Open Research in Feb 2023. The data contributed to Tables 2 and 3 of this paper.

Affinity DATA

This data set corresponds to the analyses carried out in the following article:

Rodríguez, S., Valle, A., Piñeiro, I., Rodríguez-Llorente, C., Guerrero, E., & Martins, L. (2020). Sociodemographic characteristics and stress of people confined by COVID-19. Eur. J. Investig. Health Psychol. Educ. 2020, 10(4), 1095-1105.

https://doi.org/10.3390/ejihpe10040077

It studies the socio-demographic variables that might predict stress and stress poor management during the confinement situation resulting from the COVID-19 pandemic.

Please note: This is a Synthetic data file, also known as a Dummy file - it is not real data. This synthetic file should not be used for purposes other than to develop an test computer programs that are to be submitted by remote access. Each record in the synthetic file matches the format and content parameters of the real Statistics Canada Master File with which it is associated, but the data themselves have been 'made up'. They do NOT represent responses from real individuals and should NOT be used for actual analysis. These data are provided solely for the purpose of testing statistical package 'code' (e.g. SPSS syntax, SAS programs, etc.) in preperation for analysis using the associated Master File in a Research Data Centre, by Remote Job Submission, or by some other means of secure access. If statistical analysis 'code' works with the synthetic data, researchers can have some confidence that the same code will run successfully against the Master File data in the Resource Data Centres. In the fall of 1991, the National Health Information Council recommended that an ongoing national survey of population health be conducted. This recommendation was based on consideration of the economic and fiscal pressures on the health care systems and the requirement for information with which to improve the health status of the population in Canada. Commencing in April 1992, Statistics Canada received funding for development of a National Population Health Survey (NPHS). The NPHS collects information related to the health of the Canadian population and related socio-demographic information to: aid in the development of public policy by providing measures of the level, trend and distribution of the health status of the population, provide data for analytic studies that will assist in understanding the determinants of health, and collect data on the economic, social, demographic, occupational and environmental correlates of health. In addition the NPHS seeks to increase the understanding of the relationship between health status and health care utilization, including alternative as well as traditional services, and also to allow the possibility of linking survey data to routinely collected administrative data such as vital statistics, environmental measures, community variables, and health services utilization. The NPHS collects information related to the health of the Canadian population and related socio-demographic information. It is composed of three components: the Households, the Health Institutions, and the North components. The Household component started in 1994/1995 and is conducted every two years. The first two cycles (1994/1995, 1996/1997) were both cross-sectional and longitudinal. The NPHS longitudinal sample includes 17,276 persons from all ages in 1994/1995 and these same persons are to be interviewed every two years. Each cycle, a common set of health questions is asked to the respondents. This allows for the analysis of changes in the health of the respondents over time. In addition to the common set of questions, the questionnaire does include focus content and supplements that change from cycle to cycle. Health Canada, Public Health Agency of Canada and provincial ministries of health use NPHS longitudinal data to plan, implement and evaluate programs and health policies to improve health and the efficiency of health services. Non-profit health organizations and researchers in the academic fields use the information to move research ahead and to improve health.

Sociodemographic characteristics by BMI subgroups in n (% cumulated).

The dataset presented provides the compilation of extensive socio-demographic profile variables as age, gender, family income measurements and so on. The purpose of this data is to analyze if the panelists of Ortiz, et al. participatory Delphi methodology correctly represents the diverse community of USFQ. This data supports the variables taken into consideration in the research design, process, and analysis.

1Only analysed among individuals who had had sexual intercourse.

Agreement rates between ethnicity data recorded in health-related administrative data sources with Census 2021 by sociodemographic characteristics, where population was restricted to those with data for all socio-demographic characteristics.

Statistics Norway carried out health surveys in 1968, 1975, 1985 and 1995. The Health survey in 1975 was more extensive than the survey in 1968, and conducted more in collaboration with the health authorities. The purpose of the study was like in 1968 to obtain a better overview of diseases and injuries among the population outside the health facility, and to examine the extent to which illness or injury leads to bed rest and decreased activity. One would also map out contact with health care and health care utilization. In 1975 there was also a desire to examine the consequences of illness and injury, for the sick themselves and for their families. Therefore, it is recorded data on absence from work, extra chores and any need for outside help. There were also questions about dental health, drug use and mental health. In this study, there was also greater emphasis on watching the health conditions in the context of socio-demographic factors, leisure activities and smoking and drinking habits. Data for 1975 are divided across two types of devices: personal and sick case.

BackgroundSuboptimal quality of care and disparities in services by healthcare providers are often reported in Nepal. Experience and perceptions about quality of care may differ according to women’s socio-cultural background, individual characteristics, their exposure and expectations. This study aimed to compare perceptions of the quality of maternal healthcare services between two groups that are consistently considered vulnerable, women with disabilities from both the non-Dalit population and Dalit population and their peers without disabilities from both non-Dalit and Dalit communities.MethodsA cross-sectional survey was conducted among 343 total women that included women with disabilities, Dalits and non-Dalits. Women were recruited for interview, who were aged 15–49 years, had been pregnant within the last five years and who had used maternal care services in one of the public health facilities of Rupandehi district. A 20-item, Likert-type scale with four sub-scales or dimensions: ‘Health Facility’, ‘Healthcare Delivery’, ‘Inter-personal’ and ‘Access to Care’ was used to measure women’s perceptions of quality of care. Chi-square test and t test were used to compare groups and to assess differences in perceptions; and linear regression was applied to assess confounding effects of socio-demographic factors. The mean score was compared for each item and separately for each dimension.ResultsAll groups, women with disabilities and women without disabilities, Dalit and non-Dalit rated their perceptions and experiences of quality of care lowly in a number of items. While perceived quality of care between women with disabilities and without disabilities in the ‘Health Facility’ dimension and associated items, was found to differ (p

This research allows us to evaluate the level of knowledge of the university population from I and II semester of the faculty of Basic and Health Sciences of the Simón Bolívar University in Barranquilla, about the different risk factors associated with cancer. Socio-demographic variables such as sex and age will be taken into account and knowledge of the factors associated with the appearance of cancer and knowledge of cancer prevention methods will be evaluated.

The STAMINA study examined the nutritional risks of low-income peri-urban mothers, infants and young children (IYC), and households in Peru during the COVID-19 pandemic. The study was designed to capture information through three, repeated cross-sectional surveys at approximately 6 month intervals over an 18 month period, starting in December 2020. The surveys were carried out by telephone in November-December 2020, July-August 2021 and in February-April 2022. The third survey took place over a longer period to allow for a household visit after the telephone interview.The study areas were Manchay (Lima) and Huánuco district in the Andean highlands (~ 1900m above sea level).In each study area, we purposively selected the principal health centre and one subsidiary health centre. Peri-urban communities under the jurisdiction of these health centres were then selected to participate. Systematic random sampling was employed with quotas for IYC age (6-11, 12-17 and 18-23 months) to recruit a target sample size of 250 mother-infant pairs for each survey.Data collected included: household socio-demographic characteristics; infant and young child feeding practices (IYCF), child and maternal qualitative 24-hour dietary recalls/7 day food frequency questionnaires, household food insecurity experience measured using the validated Food Insecurity Experience Scale (FIES) survey module (Cafiero, Viviani, & Nord, 2018), and maternal mental health.In addition, questions that assessed the impact of COVID-19 on households including changes in employment status, adaptations to finance, sources of financial support, household food insecurity experience as well as access to, and uptake of, well-child clinics and vaccination health services were included.This folder includes the dataset and dictionary of variables for survey 3 (English only).The survey questionnaire for survey 3 is available at 10.17028/rd.lboro.21740921.

Cardiovascular Disease Prevalence in Travis County (2014-2018)

Assessing Risk Factors in an Urban Community

By City of Austin [source]

About this dataset

This dataset provides invaluable insight into the prevalence of cardiovascular disease in Travis County, Texas between 2014 and 2018. By utilizing data from the Behavioral Risk Factor Surveillance System (BRFSS), this dataset offers a comprehensive look at the health of the adult population in Travis County. Are your heart health concerns growing or declining? This dataset has the answer. Through its detailed analysis, you can quickly identify any changes in cardiovascular disease over time as well as understand how disability and other factors such as age may be connected to heart-related diagnosis rates. Investigate how diabetes, lifestyle habits and other factors are affecting residents of Travis County with this insightful strategic measure!

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How to use the dataset

This dataset provides valuable insight into the prevalence of cardiovascular disease among adults in Travis County from 2014 to 2018. The data includes a Date_Time variable, which is the date and time of the survey, as well as a Year variable and Percent variable detailing prevalence within that year. This data can be used for further research into cardiovascular health outcomes in Travis County over time.

The first step in using this dataset is understanding its contents. This data contains information on each year’s percent of residents with cardiovascular disease and was collected during annual surveys by Behavioral Risk Factor Surveillance System (BRFSS). With this information, users can compare yearly changes in cardiovascular health across different cohorts. They can also use it to identify particular areas with higher or lower prevalence of cardiovascular disease throughout Travis County.

Now that you understand what’s included and what it describes, you can start exploring deeper insights within your analysis. Try examining demographic factors such as age group or sex to uncover potential trends underlying the increase or decrease in overall percentage over time . Additionally, look for other data sources relevant to your research topic and explore how prevalence differs across different factors within Travis County like specific counties or cities within it or types of geographies like rural versus urban settings . By overlaying additional datasets such as these , you will learn more about any correlations between them and this BRFSS-surveyed measure overtime .

Finally remember that any findings related to this dataset should always be interpreted carefully given their scale relative to our broader population . Yet by digging deep into the changes taking place , we are able to answer important questions about howCV risk factors might vary from county-to-county across Texas while also providing insight on where public health funding should be directed towards next !

Research Ideas

• Evaluating the correlation between cardiovascular disease prevalence and socio-economic factors such as income, education, and occupation in Travis County over time.
• Building an interactive data visualization tool to help healthcare practitioners easily understand the current trends in cardiovascular disease prevalence for adults in Travis County.
• Developing a predictive model to forecast the future prevalence of cardiovascular disease for adults in Travis County over time given relevant socio-economic factors

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: strategic-measure-percentage-of-residents-with-cardiovascular-disease-1.csv | Column name | Description | |:--------------|:---------------------------------------------------------------------------| | Date_Time | Date and time of the survey. (DateTime) | | Year | Year of the survey. (Integer) | | Percent | Percentage of adults in Travis County with cardiovascular disease. (Float) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit City of Austin.

Association (OR, 95% CI) between socio–demographic factors, self–rated health, and high number of lifetime sexual partners.

The purpose of our dataset is to measure how the Covid-19 pandemic, along health, financial, professional and socio-demographic factors, have affected the behavior of individuals. We are also estimated on repeated measures (life before COVID-19, life now with COVID-19, and life after the COVID-19 pandemic, in terms of future expectation) for a large sample (1746 respondents) from 43 worldwide countries during the period of May 2020 and October 2022. These datasets contain useful information for policymakers to improve the conditions of living in the areas of health and welfare. Is also unique, because: is first survey to investigate the wellbeing in three measurement moments: pre-, during- and post- Covid- 19 pandemic. Second, we discovered a great diversity of factors that influence the behavior of individuals in pandemic context. Third, this dataset permits exploration of levels of happiness and carrying out comparative studies with other countries, because our database contains information about the well-known Subjective Happiness Scale (Lyubomirsky & Lepper, 1999).

The epidemiological surveillance of HIV in Belgium is based on several data collections carried out by Sciensano. National data are collected from the HIV reference centres (HRCs) and AIDS reference laboratories (ARLs): a) National data collection of all HIV diagnosed patients in Belgium; b) National data collection of all HIV patients in care, through an exhaustive data collection of all viral load measures performed in Belgium and a data collection of demographic, biological, immunological, treatment and death data of patients in care in the HRCs (around 80 % of all patients in care in Belgium); c) A laboratory data collection on viro-immunological follow-up of all new-borns from HIV positive mothers; d) A national data collection of post-exposure prophylaxis episodes. Since the beginning of the HIV epidemic, this surveillance enables the monitoring of the trends in number of people diagnosed with HIV and number of patients in medical follow-up, as well as to identify certain socio-demographic factors associated with the risk of HIV infection or of a pejorative clinical outcome. This information supports health authorities and HIV stakeholders to decide on evidence-based HIV prevention and care strategies and define target groups for tailored interventions. Statbel, the Belgian statistical office collects, produces and disseminates reliable and relevant figures on the Belgian economy, society and territory. The collection is based on administrative data sources and surveys. This project aims to link the HIV surveillance data with selected Statbel information. This will permit to greatly improve the quality of the HIV surveillance data by completing the data already collected by Sciensano with additional socio-economic and socio-demographic information on patients profiles, filling in missing data in the Sciensano database with demographics from Statbel, ascertaining vital status of lost-to-follow-up patients and completing the information on causes of death. Additionally, a linkage with the new-born registry would permit to have more demographic and clinical information on children born from HIV-positive women.

a)Separate multivariate models indicated for perceived health and disease indicatorsb)Statistically significant COR values in boldc)Variable not included in the model, because it was not statistically significant when assessed with other variablesd)The categories having COR values close to each other were combined in all analyses

file_adolescents_dryad_V2data used study adolescents

Percentage of persons for selected health indicators, by visible minority and selected sociodemographic characteristics (age group, gender or immigrant status) for the population aged 18 and older in the ten provinces. Data is available for Canada (excluding territories). A similar table with a geographical breakdown by region is available in table 13-10-0880.