Mauritania MR: Current Health Expenditure: % of GDP data was reported at 4.640 % in 2015. This records an increase from the previous number of 4.204 % for 2014. Mauritania MR: Current Health Expenditure: % of GDP data is updated yearly, averaging 4.055 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 5.187 % in 2002 and a record low of 3.166 % in 2011. Mauritania MR: Current Health Expenditure: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mauritania – Table MR.World Bank.WDI: Health Statistics. Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted average;

This dataset contains 6500 physiological measurements collected from wearable health monitoring devices designed to track important vital parameters related to human health. The dataset focuses on key physiological indicators such as heart activity, oxygen saturation, temperature variation, respiration behavior, and blood pressure levels. These parameters provide valuable insights into an individual's current health condition and can help identify possible physiological irregularities. The records represent health observations gathered across individuals with varying age groups, gender categories, and physical activity levels. Each entry includes a collection of vital measurements along with an associated health status label indicating whether the recorded physiological state is within normal conditions or indicates a potential abnormality. Wearable health monitoring technologies have become increasingly important in modern healthcare systems. Continuous measurement of vital signs enables timely medical attention, remote patient monitoring, and improved healthcare accessibility. The dataset supports research related to physiological signal analysis, wearable healthcare technologies, remote patient observation, and intelligent health monitoring systems. The dataset structure includes demographic attributes, physiological vital signs, and contextual activity information that together describe the overall physiological condition of individuals at the time of observation. These variables help represent variations in vital signs that may occur due to health conditions, physical exertion, or other physiological changes.

Column Description

Patient_ID – Unique identifier assigned to each patient record in the dataset.

Age – Age of the individual measured in years.

Gender – Biological gender of the individual recorded as Male or Female.

Heart_Rate_bpm – Number of heartbeats per minute recorded during observation.

SpO2_percent – Percentage of oxygen saturation in the blood indicating oxygen levels in circulation.

Body_Temperature_C – Measured body temperature of the individual expressed in degrees Celsius.

ECG_RR_Interval_ms – Time interval between two consecutive R-peaks in the electrocardiogram signal measured in milliseconds.

Respiration_Rate_bpm – Number of breathing cycles per minute indicating respiratory activity.

Systolic_BP_mmHg – Systolic blood pressure level representing the pressure in arteries during heart contraction.

Diastolic_BP_mmHg – Diastolic blood pressure level representing the pressure in arteries during heart relaxation.

Activity_Level – Physical activity state of the individual during measurement such as Resting, Walking, Moderate Activity, or High Activity.

Health_Status – Categorical indicator describing whether the physiological condition is Normal or Abnormal.

Data is most valuable when it can be compared to other datasets. Standardization ensures that data can be interpreted consistently across time and context. Clearly defining and communicating aspects of standardization—such as release levels—is essential to interpreting data accurately and supporting agency-wide consistency. A Release Level is a designation indicating the maturity and finality of a dataset at the time of release. Release levels are a type of metadata assigned to all data assets managed by the Department of Health. All release levels may refer to either aggregate or record-level datasets and datasets shared internal to the government agency or external (i.e., to the public). All reports or data products, other than live data feeds, produced by the Department of Health are a static snapshot of the data at a specific date and time when produced. It is recommended to always reference the “last updated” date. Showing when data were “last updated” helps people know how recent the information is, whether it reflects current conditions, and how things may have changed when comparing different data releases.

WHO Health Indicators in Turkey

Health Status, Infrastructure, and Financing

By Humanitarian Data Exchange [source]

About this dataset

This dataset from the World Health Organization's data portal features a wide range of important health and socioeconomic indicators for Turkey. Included in the dataset are categories such as Mortality, Global Health Estimates, Sustainable Development Goals, Millennium Development Goals (MDGs), Public Health and Environment, Noncommunicable Diseases CCS, Neglected Tropical Diseases, Immunization and more. Through exploring this dataset you can gain valuable insights into health issues ranging from child health to infectious diseases to substance use and mental health for Turkey. Additionally this dataset is ideal for craft detailed socio-economic profiles regarding specific diseases or health-related topics. With access to information concerning essential health technologies, medical equipment, human resources availability and more; public policy research can benefit greatly from examining this data. Organizations or researchers concerned with inequalities in healthcare systems can also utilize this wealth of data to track key performance indicators or discover areas needing improved services. By leveraging these powerful aspects of the WHO Data Portal not only will decision-makers have a better understanding of effective policies but potentially lives can be saved through informed strategies that arise through analysis of these kinds of datasets

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How to use the dataset

This dataset contains health indicators for Turkey from the World Health Organization's data portal. It is an excellent resource for anyone researching the current state of Turkey’s health indicators and it has a wide variety of topics covered such as mortality and global health estimates, sustainable development goals, infectious diseases, mental health, nutrition, urban health and more.

In order to effectively use this dataset for your research you should have a basic understanding of what data is included in each field provided. For example there are fields that identify which Global Health Observatory (GHO) indicator is being measured (GHO Code), what type of indicator it is (Display Value), which region within Turkey the data applies to (Region Code), or the start year of an indicator(StartYear). Additionally there are fields that provide extra details such as definitions (Comments) or URLs to access more information about specific indicators(GHO URL).

Using this information you can easily create queries to retrieve relevant results. For example if you are looking for urban health indicators in 2019 released by WHO then you would run a query with selections based on “Urban Health” under GHO Display , “Turkey” under Country Display , “2019” Start Year . You can also use comparison operators such as less than/greater than (<=/>=) or exact match (= ) when selecting criteria values.

Lastly certain columns contain numeric values so they will require mathematical operations such as averages or percentages when calculating summary stats. Numeric fields include Low , High , StdErr , StdDev and Numeric . If an exact value associated with your query remains unknown due to missing information those field can be left blank without causing any errors.

By following these general tips this dataset will provide useful insights into the current state of turkey's healthcare system- no matter what questions arise during your research journey!

Research Ideas

• Analyzing overall health trends in Turkish region over time by investigating changes in outcomes of various health indicators across years.
• Understanding socioeconomic and demographic disparities in access to healthcare resources and services by comparing data between different regions, age groups, genders and countries.
• Comparing the levels of access to healthcare resources between Turkey and other countries by analyzing the global burden of disease child causes for each nation

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: icd-indicators-for-turkey-28.csv | Column name | Description | |:---------------------------|:---------------------------------------------------------------| | GHO (CODE) | The Global Health Observatory code for the indicator. (Strin...

Jordan JO: Domestic Private Health Expenditure: % of Current Health Expenditure data was reported at 36.141 % in 2015. This records an increase from the previous number of 29.639 % for 2014. Jordan JO: Domestic Private Health Expenditure: % of Current Health Expenditure data is updated yearly, averaging 39.058 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 52.422 % in 2000 and a record low of 28.780 % in 2010. Jordan JO: Domestic Private Health Expenditure: % of Current Health Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank: Health Statistics. Share of current health expenditures funded from domestic private sources. Domestic private sources include funds from households, corporations and non-profit organizations. Such expenditures can be either prepaid to voluntary health insurance or paid directly to healthcare providers.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;

This CD-ROM is the eighth annual compilation of Health, United States. The series presents national trends in health statistics. Major findings are presented in the highlights section. The report includes a chartbook, trend tables, extensive appendixes, and an index. The Chartbook assesses the Nation's health by presenting trends and current information on selected determinants and measures of health status. Determinants of health considered in the chartbook include demographic factors, healt h insurance coverage, health behaviors and risk factors, and preventive health care. Measures of health status include mortality and limitations of activity due to chronic health conditions. Many measures are shown separately for persons of different ages because of the strong effect of age on health, as well as differences in causes of morbidity and mortality across the age span. Selected figures also highlight differences in determinants and measures of health status by such characteristics as sex, race, and Hispanic origin. The chartbook section is followed by 147 trend tables organized around four major subject areas: health status and determinants, health care utilization, health care resources, and health care expenditures. A major criterion used in selecting the trend tables is availability of comparable national data over a period of several years. The tables report data for selected years to highlight major trends in health statistics. Many tables present data according to race and Hispanic origin. Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

In 2021, domestic general government health expenditure accounted for **** percent of current health expenditure in Vietnam. In that year, the current health expenditure accounted for **** percent of the GDP in the country.

Dataset Context: This dataset was created from the "Health Bulletin 2019" report, which provides a comprehensive overview of the health status and trends in Bangladesh for the year 2019. It includes various health indicators, disease statistics, healthcare infrastructure, workforce, financing, policies, and health education and training information. The dataset was extracted and cleaned to facilitate further research on public health, disease prevention, healthcare systems, and policy analysis in Bangladesh. This dataset will be valuable for exploring health trends, disparities, and the impact of health programs, as well as for informing the development of new healthcare policies.

Sources: The dataset is sourced from the Health Bulletin 2019, a government publication by the Ministry of Health and Family Welfare, Bangladesh. The report presents a detailed analysis of various aspects of the country's healthcare system, including:

Demographics and Health Indicators Disease Statistics Healthcare Financing and Policy Health Services Utilization Health Workforce Health Education and Training Healthcare Infrastructure The data was extracted from the 263 pages of the Health Bulletin, covering the state of healthcare in Bangladesh, and subsequently cleaned and structured for analysis.

Inspiration Behind the Dataset: The primary motivation behind creating this dataset was to enable in-depth research on several key public health challenges facing Bangladesh. The health indicators and statistics from the bulletin provide crucial insights into the population's health status, the effectiveness of health programs, and the accessibility of healthcare services across different regions.

This dataset serves as a foundation for:

Assessing the health status of the Bangladeshi population: Understanding the current health conditions and disease prevalence in different demographics. Evaluating the effectiveness of health programs: Analyzing the impact of health interventions and public health policies in Bangladesh. Identifying health disparities: Investigating inequalities in healthcare access and outcomes across various regions and population groups. Developing new health policies and programs: Using data-driven insights to inform future healthcare policies, ensuring better health outcomes for the population. The dataset is also intended for use in academic research, policy development, and the creation of evidence-based recommendations for improving healthcare in Bangladesh.

2011 to present. BRFSS combined land line and cell phone prevalence data. BRFSS is a continuous, state-based surveillance system that collects information about modifiable risk factors for chronic diseases and other leading causes of death. Data will be updated annually as it becomes available. Detailed information on sampling methodology and quality assurance can be found on the BRFSS website (http://www.cdc.gov/brfss). Methodology: http://www.cdc.gov/brfss/factsheets/pdf/DBS_BRFSS_survey.pdf Glossary: https://chronicdata.cdc.gov/Behavioral-Risk-Factors/Behavioral-Risk-Factor-Surveillance-System-BRFSS-H/iuq5-y9ct/data

New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data tables are provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State.

A cross sectional study that enrolled youth, ages 12 through 24, who received care for HIV infection at sites participating in the ATN during the study period. The study was conducted in one visit and examined a broad spectrum of youth engaged in care at ATN sites including those newly enrolled in care. Information was collected on rates of adherence to medical regimens, sexual risk behaviors, substance use and mental health concerns, and basic demographic and biomedical data to understand risk behaviors, risk and protective factors, and relationships between factors in adolescents and young adults with HIV infection.

This statistic represents the distribution of the value of current health expenditure in France in 2018, in billions of euros. Long-term care accounts for almost ** billion euros in spending.

Panama PA: Current Health Expenditure: % of GDP data was reported at 7.009 % in 2015. This records an increase from the previous number of 6.843 % for 2014. Panama PA: Current Health Expenditure: % of GDP data is updated yearly, averaging 6.740 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 7.525 % in 2004 and a record low of 6.025 % in 2011. Panama PA: Current Health Expenditure: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank: Health Statistics. Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted average;

This statistic depicts the percentage of U.S. suicides with known or unknown mental health conditions as of 2015, by crises within the past or upcoming two weeks. According to the data, 13.4 percent of all suicide victims in that year had a physical health problem within the past two weeks prior to death. Furthermore, 12.9 percent of suicides among those with a known mental health condition had a recent physical health problem.

Laos LA: Current Health Expenditure: % of GDP data was reported at 2.806 % in 2015. This records an increase from the previous number of 2.573 % for 2014. Laos LA: Current Health Expenditure: % of GDP data is updated yearly, averaging 3.771 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 4.965 % in 2003 and a record low of 2.162 % in 2011. Laos LA: Current Health Expenditure: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank: Health Statistics. Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;

There are two datasets related to the State Level Prevention Agenda Tracking Indicators posted on this site. Each dataset consists of 99 state-level health tracking indicators and sub-indicators for the Prevention Agenda 2019-2024: New York State’s Health Improvement Plan. A health tracking indicator is a metric through which progress on a certain area of health improvement can be assessed. The indicators are organized by the Priority Area of the Prevention Agenda as well as the Focus Area under each Priority Area. Priority areas include Prevent Chronic Disease; Promote a Healthy and Safe Environment; Promote Healthy Women, Infants and Children; Promote Well-Being and Prevent Mental and Substance Use Disorders; and Communicable Diseases. The data sets also include indicators about major cross-cutting health outcomes and indicators of health disparities, organized into Health Status and Reduce Health Disparities. The most recent year dataset includes the most recent state level data for all indicators. The trend dataset includes the most recent state level data and historical data, where available. Each dataset also includes the Prevention Agenda 2024 state objectives for the indicators. Sub-indicators are included in these datasets to measure health disparities among racial, ethnic, and socioeconomic groups and persons with disabilities.

The 2004 National Nursing Home Survey (NNHS), conducted between August and December of 2004, was reintroduced into the field after a five-year break, during which time the survey was redesigned and expanded to collect many new data items. All nursing homes that participated in the NNHS had at least three beds and were either certified (by Medicare or Medicaid) or had a state license to operate as a nursing home. The redesigned survey was administered using a computer-assisted personal interviewing (CAPI) system. The National Nursing Home Survey provides information on nursing homes from two perspectives-that of the provider of services and that of the recipient of care. Data about the facilities include characteristics such as size, ownership, Medicare/Medicaid certification, services provided and specialty programs offered, and charges. For recipients, data were obtained on demographic characteristics, health status and medications taken, services received, and sources of payment.

Data for the survey were obtained through personal interviews with facility administrators and designated staff who used administrative records to answer questions about the facilities, staff, services and programs, and medical records to answer questions about the residents.

The total number of nursing home facilities that participated in NNHS is 1,174.

NUMBER OF MEASURES FOR WHICH GROUP FARED WORSE, THE SAME, OR BETTER COMPARED TO WHITE PEOPLE:. Notes: Measures are for the most recent year for which data are available. "Better" or "Worse" indicates a statistically significant difference from White people at the p<0.05 level. No difference indicates no statistically significant difference. "Data limitation" indicates no separate data for a racial/ethnic group, insufficient data for a reliable estimate, or comparisons not possible due to overlapping samples. AIAN refers to American Indian or Alaska Native. NHPI refers to Native Hawaiian and Pacific Islander. Persons of Hispanic origin may be of any race but are categorized as Hispanic for this analysis; other groups are non-Hispanic.

A survey from January 2019 found that 83 percent of U.S. adults stated their current health-related priority was their oral health. Oral health was rated higher than mental health, exercise, and diet as a health-related priority.

As of 2022, Tunisia's health expenditure accounted for nearly seven percent of its GDP, the highest in North Africa. Morocco followed, with the second-largest share at 5.68 percent. On the other hand, Algeria had the lowest health spending as a share of GDP in the region.