This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The data are not archived at ICPSR. Users should consult the data owners (via the Roper Center for Public Opinion Research) directly for details on obtaining the data. This collection includes variable-level metadata of the 2014 poll What Shapes Health, a survey from National Public Radio/Robert Wood Johnson Foundation/Harvard School of Public Health conducted by Social Science Research Solutions (SSRS). Topics covered in this survey include:Concerned about own healthMeaning of healthControl over own healthEffort into maintaining healthFrequency of healthy activities Description of personal healthTypes of healthy habitsOn diet to lose weightWays to improve healthThings that cause health problemsChildhood problems causing future health issuesParticipation in community organizationsVolunteering improving healthBeing told to improve healthFamily/friend behavior influencing healthHealth habits of family/friendsProblems experienced in adulthoodProblems experience in childhoodReceiving health careDifficulty accessing health careParents' healthRecent serious illnessesDiagnosed with health conditionsFrequency of exercisingPersonal weightSmoking habitsHealth insuranceThe data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31092363]. Frequencies and summary statistics for the 244 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

The Health Statistics and Health Research Database is Estonian largest set of health-related statistics and survey results administrated by National Institute for Health Development. Use of the database is free of charge.

The database consists of eight main areas divided into sub-areas. The data tables included in the sub-areas are assigned unique codes. The data tables presented in the database can be both viewed in the Internet environment, and downloaded using different file formats (.px, .xlsx, .csv, .json). You can download the detailed database user manual here (.pdf).

The database is constantly updated with new data. Dates of updating the existing data tables and adding new data are provided in the release calendar. The date of the last update to each table is provided after the title of the table in the list of data tables.

A contact person for each sub-area is provided under the "Definitions and Methodology" link of each sub-area, so you can ask additional information about the data published in the database. Contact this person for any further questions and data requests.

Read more about publication of health statistics by National Institute for Health Development in Health Statistics Dissemination Principles.

The NIHR is one of the main funders of public health research in the UK. Public health research falls within the remit of a range of NIHR Research Programmes, NIHR Centres of Excellence and Facilities, plus the NIHR Academy. NIHR awards from all NIHR Research Programmes and the NIHR Academy that were funded between January 2006 and the present extraction date are eligible for inclusion in this dataset. An agreed inclusion/exclusion criteria is used to categorise awards as public health awards (see below). Following inclusion in the dataset, public health awards are second level coded to one of the four Public Health Outcomes Framework domains. These domains are: (1) wider determinants (2) health improvement (3) health protection (4) healthcare and premature mortality.More information on the Public Health Outcomes Framework domains can be found here.This dataset is updated quarterly to include new NIHR awards categorised as public health awards. Please note that for those Public Health Research Programme projects showing an Award Budget of £0.00, the project is undertaken by an on-call team for example, PHIRST, Public Health Review Team, or Knowledge Mobilisation Team, as part of an ongoing programme of work.Inclusion criteriaThe NIHR Public Health Overview project team worked with colleagues across NIHR public health research to define the inclusion criteria for NIHR public health research awards. NIHR awards are categorised as public health awards if they are determined to be ‘investigations of interventions in, or studies of, populations that are anticipated to have an effect on health or on health inequity at a population level.’ This definition of public health is intentionally broad to capture the wide range of NIHR public health awards across prevention, health improvement, health protection, and healthcare services (both within and outside of NHS settings). This dataset does not reflect the NIHR’s total investment in public health research. The intention is to showcase a subset of the wider NIHR public health portfolio. This dataset includes NIHR awards categorised as public health awards from NIHR Research Programmes and the NIHR Academy. This dataset does not currently include public health awards or projects funded by any of the three NIHR Research Schools or any of the NIHR Centres of Excellence and Facilities. Therefore, awards from the NIHR Schools for Public Health, Primary Care and Social Care, NIHR Public Health Policy Research Unit and the NIHR Health Protection Research Units do not feature in this curated portfolio.DisclaimersUsers of this dataset should acknowledge the broad definition of public health that has been used to develop the inclusion criteria for this dataset. This caveat applies to all data within the dataset irrespective of the funding NIHR Research Programme or NIHR Academy award.Please note that this dataset is currently subject to a limited data quality review. We are working to improve our data collection methodologies. Please also note that some awards may also appear in other NIHR curated datasets. Further informationFurther information on the individual awards shown in the dataset can be found on the NIHR’s Funding & Awards website here. Further information on individual NIHR Research Programme’s decision making processes for funding health and social care research can be found here.Further information on NIHR’s investment in public health research can be found as follows: NIHR School for Public Health here. NIHR Public Health Policy Research Unit here. NIHR Health Protection Research Units here. NIHR Public Health Research Programme Health Determinants Research Collaborations (HDRC) here. NIHR Public Health Research Programme Public Health Intervention Responsive Studies Teams (PHIRST) here.

The COVID-19 pandemic has affected college students, leading to increased anxiety and emotional distress. This study investigated how perceived public health crises relate to anxiety levels in college students, and how social support and gender influence this relationship. Data from 3,165 college students from six universities in Shaanxi Province, China, were collected and analyzed by using AMOS and SPSS PROCESS 4.0. Results showed that perceived COVID-19 risk significantly impacted anxiety levels, and social support moderated this relationship. Gender also had multiple interaction effects with social support and perceived pandemic risk on anxiety. Overall, the study confirms that COVID-19 quarantine and perceived risk increase stress and anxiety in college students, with social support playing a buffering role, albeit with variations based on gender.

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

This formatted dataset (AnalysisDatabaseGBD) originates from raw data files from the Institute of Health Metrics and Evaluation (IHME) Global Burden of Disease Study (GBD2017) affiliated with the University of Washington. We are volunteer collaborators with IHME and not employed by IHME or the University of Washington.

The population weighted GBD2017 data are on male and female cohorts ages 15-69 years including noncommunicable diseases (NCDs), body mass index (BMI), cardiovascular disease (CVD), and other health outcomes and associated dietary, metabolic, and other risk factors. The purpose of creating this population-weighted, formatted database is to explore the univariate and multiple regression correlations of health outcomes with risk factors. Our research hypothesis is that we can successfully model NCDs, BMI, CVD, and other health outcomes with their attributable risks.

These Global Burden of disease data relate to the preprint: The EAT-Lancet Commission Planetary Health Diet compared with Institute of Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis. The data include the following: 1. Analysis database of population weighted GBD2017 data that includes over 40 health risk factors, noncommunicable disease deaths/100k/year of male and female cohorts ages 15-69 years from 195 countries (the primary outcome variable that includes over 100 types of noncommunicable diseases) and over 20 individual noncommunicable diseases (e.g., ischemic heart disease, colon cancer, etc). 2. A text file to import the analysis database into SAS 3. The SAS code to format the analysis database to be used for analytics 4. SAS code for deriving Tables 1, 2, 3 and Supplementary Tables 5 and 6 5. SAS code for deriving the multiple regression formula in Table 4. 6. SAS code for deriving the multiple regression formula in Table 5 7. SAS code for deriving the multiple regression formula in Supplementary Table 7
8. SAS code for deriving the multiple regression formula in Supplementary Table 8 9. The Excel files that accompanied the above SAS code to produce the tables

For questions, please email davidkcundiff@gmail.com. Thanks.

Financial overview and grant giving statistics of Illinois Public Health Institute

The Institute for Health Metrics and Evaluation (IHME) is an independent population health research center at UW Medicine, part of the University of Washington, that provides rigorous and comparable measurement of the world's most important health problems and evaluates the strategies used to address them. IHME makes this information freely available so that policymakers have the evidence they need to make informed decisions about how to allocate resources to best improve population health.

The Norwegian Institute of Public Health has two statistical banks with data on health status, disease, treatment, risk factors, birth and abortion, health services and social inequalities in health. Norgeshelsa Statbank has data that is adapted for the country, health regions and counties. Kommunehelsa Statbank has data that is adapted for municipalities. Data are distributed by gender, age groups, years and geographical areas. Norgeshelsa Statbank offers a total of 80 topics, about 20 topics is about social inequality in health. Data is obtained from central health registries, health surveys, Statistics Norway and several other sources, including the Directorate of Health, the University of Bergen and the Norwegian Labour and Welfare Administration (NAV). In the statistics bank, data is facilitated with age standardisation so that comparisons can be made between years and geographical areas. Data can be downloaded as excel tables, and in new versions will also be able to be downloaded in other formats. Norgeshelsa Statbank is updated continuously. Kommunehelsa Statbank has fewer topics and is updated in January each year. The StatBank is linked to the preparation of public health profiles. You can find the full indicator list and metadata in the statistics banks.

(B). Summary of sources of information regarding public health topics.

Graph and download economic data for Expenditures: Healthcare by Education: High School Graduate with Some College (CXUHEALTHLB1305M) from 1995 to 2012 about no college, secondary schooling, healthcare, secondary, health, education, expenditures, and USA.

Graph and download economic data for Expenditures: Healthcare by Highest Education: Less Than College Graduate: High School Graduate (CXUHEALTHLB1404M) from 2012 to 2023 about no college, healthcare, secondary schooling, secondary, health, expenditures, education, and USA.

The "https://addhealth.cpc.unc.edu/" Target="_blank">National Longitudinal Study of Adolescent to Adult Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32*. Add Health combines longitudinal survey data on respondents' social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The fifth wave of data collection is planned to begin in 2016.

Initiated in 1994 and supported by three program project grants from the "https://www.nichd.nih.gov/" Target="_blank">Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) with co-funding from 23 other federal agencies and foundations, Add Health is the largest, most comprehensive longitudinal survey of adolescents ever undertaken. Beginning with an in-school questionnaire administered to a nationally representative sample of students in grades 7-12, the study followed up with a series of in-home interviews conducted in 1995, 1996, 2001-02, and 2008. Other sources of data include questionnaires for parents, siblings, fellow students, and school administrators and interviews with romantic partners. Preexisting databases provide information about neighborhoods and communities.

Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health, and Waves I and II focus on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants have aged into adulthood, however, the scientific goals of the study have expanded and evolved. Wave III, conducted when respondents were between 18 and 26** years old, focuses on how adolescent experiences and behaviors are related to decisions, behavior, and health outcomes in the transition to adulthood. At Wave IV, respondents were ages 24-32* and assuming adult roles and responsibilities. Follow up at Wave IV has enabled researchers to study developmental and health trajectories across the life course of adolescence into adulthood using an integrative approach that combines the social, behavioral, and biomedical sciences in its research objectives, design, data collection, and analysis.

* 52 respondents were 33-34 years old at the time of the Wave IV interview.
** 24 respondents were 27-28 years old at the time of the Wave III interview.

The Wave III public-use data are helpful in analyzing the transition between adolescence and young adulthood. Included in this dataset are data on pregnancy.

This dataset provides the following measures related to COVID-19 in CT public and private PK-12 schools for the latest week-long reporting period:

Number of staff cases and change from the previous reporting period Number of student cases and change from the previous reporting period Number of student cases by learning model (fully in-person, hybrid, fully remote, or unknown) and change from the previous reporting period

As of 6/24/2021, COVID-19 school-based surveillance activities for the 2020 – 2021 academic year has ended. The Connecticut Department of Public Health along with the Connecticut State Department of Education are planning to resume these activities at the start of the 2021 – 2022 academic year.

Data for the 2021-2022 school year is available here: https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-in-CT-Schools-State-Summary-2021-20/r6vy-dvtz

Three level of (A) students’ reported public health knowledge and (B) self-assessment.

Analysis of ‘Performance Metrics - Public Health - School-Based Oral Health Programming’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/add2c1ff-656d-48ec-bad2-e1698718a93f on 26 January 2022.

--- Dataset description provided by original source is as follows ---

The Chicago Department of Public Health contracts with licensed dentists to provide and the Chicago Public Schools' students a dental exam/screening, a dental cleaning, a fluoride varnish treatment and apply dental sealant(s) as needed at no cost to students or their families in school. This metric tracks the number of students served by the program per month during the school year. The annual performance goal is to serve 96,000 students per school year.

--- Original source retains full ownership of the source dataset ---

Financial overview and grant giving statistics of Zumwalt Institute for Public Health and Environmental Medicine Inc.

Financial overview and grant giving statistics of Institute for Public Health and Education Research Inc.

Financial overview and grant giving statistics of Institute for Public Health Innovation

Purpose: Develop an easy-to-use data product to facilitate comparative effectiveness research involving complex patients. Scope: Claims data can be difficult to use, requiring experience to most appropriately aggregate to the patient level and to create meaningful variables such as treatments, covariates, and endpoints. Easy to use data products will accelerate meaningful comparative effectiveness research (CER). Methods: This project used data from the Medicare Chronic Condition Data Warehouse for patients hospitalized with acute myocardial infarction (AMI) or stroke in 2007 with two-year follow-up and one-year pre-admission baseline. The project joined over 100 raw data files per condition to create research-ready person- and service-level analytic files, code templates, and macros while at the same time adding uniformity in measures of comorbid conditions and other covariates. The data product was tested in a project on statin effectiveness in older patients with multiple comorbidities. Results: A programmer/analyst with no administrative claims data experience was able to use the data product to create an analytic dataset with minimal support aside from the documentation provided. Analytic dataset creation used the conditions, procedures, and timeline macros provided. The data structure created for AMI adapted successfully for stroke. Complexity increased and statin treatment decreased with age. The two-year survival benefit of statins post-AMI increased with age. Conclusion: Claims data can be made more user-friendly for CER research on complex conditions. The data product should be expanded by refreshing the cohort and increasing follow-up. Action is warranted to increase the rate of statin use among the oldest patients. Data Access: These data are not available from ICPSR. The data cannot be made publicly available. Data are stored on University of Iowa College of Public Health secure servers, and may be used only for projects covered within the aims of the original research protocol and Centers for Medicare and Medicaid Services (CMS)-approved data use agreement. Data sharing is allowed only for research protocols approved under data re-use requests by the CMS privacy board. The CMS process for data re-use requests is described at Research Data Assistance Center (ResDac) . Please note that as of May 2013, the DUA covering this work is set to expire February 1, 2014. Thereafter, per the terms of the DUA, datasets created for this project may not be available. User guides are available from ICPSR for detailed descriptions of the data products, including a user guide for Acute Myocardial Infarction (AMI) Analytic Files and a user guide for Stroke and Transient Ischemic Attack (TIA) Analytic Files. Data dictionaries are available upon request. Please contact Nick Rudzianski (nicholas-rudzianski@uiowa.edu or 319-335-9783) for more information.