In the Western Pacific, 81 percent of nurses were female and 19 percent were male. In comparison, 35 percent of nurses in the African region were male. The statistic illustrates the gender distribution of nurses worldwide in 2019, by region.

In the United States, the large majority of registered nurses are *****. From 2014 to 2017, only *** out of ten registered nurses were men. Although nursing remains predominately a female profession, the share of male registered nurses has slightly increased over the years.

As of 2023, nearly one in ten registered nurses in Canada is male. The percentage of male nurses has been slowly increasing since 2006, where just *** percent of registered nurses were men. Still, nursing is a female-dominated profession. Nurses in Canada As of 2023, while there were nearly ******* registered nurses (RN) in Canada. The average age of a registered nurse in Canada has been decreasing in recent years. Besides registered nurses, three other nurse professionals are regulated in Canada, nurse practitioners (NP), registered psychiatric nurses (RPN), and licensed practical nurses (LPN). LPNs need less education, while NPs require higher education than RNs. Nurses by province The province with the highest number of registered nurses in Canada is Ontario, followed by Quebec, British Columbia, and Alberta. Yukon has the smallest number of registered nurses, with just over ***. The average age of a registered nurse can also differ by a few years depending on the province, ranging from 40 to 46 years

This statistic depicts the number of registered nurses in Canada, sorted by gender, from 2014 to 2023. In 2023, approximately ***** thousand registered nurses in Canada identified as women, while **** thousand nurses identified as men.

According to 2023 data, almost one in ten nursing assistants in nursing homes were men in the United States. Meanwhile, men accounted for 16 percent of residential care aids in the same year.

In 2022, women accounted for over ** percent of the nursing personnel in Costa Rica, while less than *** in every ten people working in the sector were men. In that year, there was an average ratio of *** nurses per doctor in the country.

In 2023, the majority of the nursing personnel in Brazil was composed of women, who represented more than **** percent of the workforce in the sector. In 2021, the density of nursery and midwifery personnel in the country amounted to ***** professionals per 10,000 people.

Totals and percentages of nursing and residential care facility residents by age group and gender, by 2017 NAICS (North American Industry Classification System), for Canada, provinces and territories, annual.

In 2023, women accounted for nearly ** percent of the nursing personnel in Argentina, while over ** percent of people working in the sector were men. In 2022, there was an average ratio of *** nurses per doctor in the South American country.

In 2023, women accounted for over ** percent of the nursing personnel in Uruguay, while less than ** in every ten people working in the sector were men. In 2022, there was an average ratio of *** nurses per doctor in the South American country.

The Organisation for Economic Co-operation and Development (OECD) Health Statistics offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems. Within UKDS.Stat the data are presented in the following databases:

Health status

This datasets presents internationally comparable statistics on morbidity and mortality with variables such as life expectancy, causes of mortality, maternal and infant mortality, potential years of life lost, perceived health status, infant health, dental health, communicable diseases, cancer, injuries, absence from work due to illness. The annual data begins in 2000.

Non-medical determinants of health

This dataset examines the non-medical determinants of health by comparing food, alcohol, tobacco consumption and body weight amongst countries. The data are expressed in different measures such as calories, grammes, kilo, gender, population. The data begins in 1960.

Healthcare resources

This dataset includes comparative tables analyzing various health care resources such as total health and social employment, physicians by age, gender, categories, midwives, nurses, caring personnel, personal care workers, dentists, pharmacists, physiotherapists, hospital employment, graduates, remuneration of health professionals, hospitals, hospital beds, medical technology with their respective subsets. The statistics are expressed in different units of measure such as number of persons, salaried, self-employed, per population. The annual data begins in 1960.

Healthcare utilisation

This dataset includes statistics comparing different countries’ level of health care utilisation in terms of prevention, immunisation, screening, diagnostics exams, consultations, in-patient utilisation, average length of stay, diagnostic categories, acute care, in-patient care, discharge rates, transplants, dialyses, ICD-9-CM. The data is comparable with respect to units of measures such as days, percentages, population, number per capita, procedures, and available beds.

Health Care Quality Indicators

This dataset includes comparative tables analyzing various health care quality indicators such as cancer care, care for acute exacerbation of chronic conditions, care for chronic conditions and care for mental disorders. The annual data begins in 1995.

Pharmaceutical market

This dataset focuses on the pharmaceutical market comparing countries in terms of pharmaceutical consumption, drugs, pharmaceutical sales, pharmaceutical market, revenues, statistics. The annual data begins in 1960.

Long-term care resources and utilisation

This dataset provides statistics comparing long-term care resources and utilisation by country in terms of workers, beds in nursing and residential care facilities and care recipients. In this table data is expressed in different measures such as gender, age and population. The annual data begins in 1960.

Health expenditure and financing

This dataset compares countries in terms of their current and total expenditures on health by comparing how they allocate their budget with respect to different health care functions while looking at different financing agents and providers. The data covers the years starting from 1960 extending until 2010. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, and United States.

Social protection

This dataset introduces the different health care coverage systems such as the government/social health insurance and private health insurance. The statistics are expressed in percentage of the population covered or number of persons. The annual data begins in 1960.

Demographic references

This dataset provides statistics regarding general demographic references in terms of population, age structure, gender, but also in term of labour force. The annual data begins in 1960.

Economic references

This dataset presents main economic indicators such as GDP and Purchasing power parities (PPP) and compares countries in terms of those macroeconomic references as well as currency rates, average annual wages. The annual data begins in 1960.

These data were first provided by the UK Data Service in November 2014.

People who need personal care or nursing due to an illness, disorder or disability can make use of district nursing under the Healthcare Insurance Act (Zvw). It is possible to purchase this care in kind and/or via a personal budget (pgb). This table provides information about the use during a year (reporting year), the use on a certain reference date and the scope of care and average expenditure per care user of district nursing. The figures are broken down by gender, age on 31 December of the year under review, care type district nursing, type of care delivery and region. Data available from: 2015 Status of the figures: The figures for the last year are provisional, the figures for previous years are final. Changes as of 25 January 2022: Provisional figures for 2020 have been added. The volume figures for 2019 have been adjusted and then made final. In the case of declarations for services that fall under 'comprehensive district nursing services', the volume was previously estimated on the basis of the invoiced amount and the average rate of a similar service, if any, and otherwise on the basis of the average rate of total district nursing. From 2019, the volume of services that fall under 'comprehensive district nursing services' is estimated on the basis of the average rate for total district nursing and the amount claimed. This change of method results in a difference in total volume for 2019 of less than 1% with the provisional figures. When will new numbers come out? The provisional figures will be published no later than 18 months after the end of the year under review. When new annual figures are published, the figures for the previous year become final.

In 2023, women accounted for almost ** percent of the nursing personnel in Peru, while only *** in every ten people working in the sector were men. In that year, there was an average ratio of *** nurses per doctor in the South American country.

This dataset has been meticulously compiled and exported directly from the World Bank's official World Development Indicators (WDI) database, covering an extensive period from 2011 to 2021. It provides detailed socioeconomic indicators for 19 advanced economies: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Italy, Japan, Republic of Korea, Netherlands, Norway, Spain, Sweden, Switzerland, United Arab Emirates, United Kingdom, and the United States.

The dataset encompasses comprehensive indicators capturing detailed aspects such as: - Education Expenditure: Financial allocation towards primary, secondary, tertiary, and overall public education institutions. - Educational Attainment: Proportion of the adult population achieving various education levels, from primary education through doctoral degrees, distinguished by gender. - Health Expenditure: Overall and government-specific health expenditure as a percentage of GDP. - Healthcare Infrastructure: Availability of physicians, nurses, midwives, and hospital beds per capita. - Labor Market Dynamics: Employment indicators across agriculture, industry, and services sectors, employment-to-population ratios, and part-time employment statistics segmented by gender and age groups. - Labor Market Vulnerability: Data on vulnerable employment, self-employment, wage and salaried employment, and employer statistics by gender. - Youth Engagement: Rates of youth neither in education, employment nor training (NEET). - Migration Patterns: International migrant stock and net migration flows. - Healthcare Resources: Availability of healthcare professionals including physicians, nurses, midwives, and hospital beds per capita. - Health Expenditure: Overall healthcare spending as a percentage of GDP, including general government health expenditure. - Population Dynamics & Structure: Annual growth rates, total population figures, and gender-specific population distribution. - Research & Technological Infrastructure: Investment in research and development, density of researchers, and scientific publications. - Mortality and Survival: Survival rates to age 65, differentiated by gender. - Unemployment: Comprehensive unemployment data segmented by gender, education level (basic, intermediate, advanced), and youth-specific unemployment rates.

Files Descriptions:

This dataset includes a CSV file and a corresponding XLSX file: 1. Main Data CSV (WDI_MainData.csv): - Each row represents a specific country-year combination, structured as: - Time: Year (2011-2021) - Time Code: Numeric year code (integer) - Country Name: Name of the country - Country Code: ISO-3 country code - Columns for each indicator provided 2. Metadata XLSX (WDI_Metadata.xlsx): - Detailed descriptions for each indicator, including: - Code - License Type - Indicator Name - Short definition - Long definition - Source - Topic - Periodicity - Aggregation method - Statistical concept and methodology - Development relevance - Limitations and exceptions - General comments - Notes from original source - License URL

Aims of the Dataset:

This dataset provides insights into socioeconomic trends across 19 advanced economies from 2011 to 2021, enabling comparative analysis over time and between countries. It serves as a valuable resource for: - Comparing countries based on education, employment, healthcare, and demographics to identify trends and disparities. - Assisting students and professionals in selecting education and job destinations by analyzing relevant indicators. - Supporting policymakers in designing effective strategies by assessing labor markets, education systems, and healthcare investments. - Enabling researchers, analysts, and NGOs to evaluate public policies, workforce development, and socioeconomic conditions. - Facilitating data science and machine learning applications, including: - Data cleaning to prepare the dataset for further analysis. - Data visualization to explore trends and correlations across multiple indicators. - Feature engineering to extract meaningful patterns for predictive modeling. - Classification to categorize countries or time periods based on socioeconomic factors. - Trend analysis and forecasting to predict future changes in education, labor markets, and public health. - Anomaly detection to identify outliers and policy inefficiencies. - Automated dashboards to provide interactive and dynamic monitoring of key indicators. This dataset serves as a foundational tool for international benchmarking, decision-making, and AI-driven insights into socioeconomic dynamics.

Indicators (Sorted A-Z):

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Characteristics of included studies and quality assessment results.

In 2022, in the United States, the average age of a registered nurse was **** years old. The average age of male registered nurses was ****, lower compared to **** years for female registered nurses. With a total of ******* nurses, most registered nurses were part of the 30 to 34 years old age group in 2022.

Factors associated with aggression in the psychiatric department using a multiple logistic regression model.

AimIn the present study, we aimed to provide an epidemiological and descriptive overview of violence against healthcare workers in an Italian university hospital, presenting and characterizing the risk factors in the department where such events occur and to propose ways to prevent aggressive behaviors.MethodsWe retrospectively analyzed violence against healthcare workers by patients and attendants at an Italian university hospital from 2020 to 2022. Aggressions were documented in anonymous incident reports collected by the hospital’s Clinical Risk Unit. The frequencies and percentages were calculated via a descriptive analysis. Chi-square tests were used to compare the wards with the most aggressions to other wards.ResultsOf the 219 included cases, the aggressors were primarily male patients and the victims female nurses. Most of the aggressions occurred in the psychiatry and emergency department. Among the aggressors, 41.1%, had a psychiatric diagnosis or neurocognitive impairment. Over half the cases involved physical aggression. Compared to other wards, psychiatric wards showed an even distribution of aggressor gender, a higher proportion of male victims, fewer verbal aggressions, and less impact from environmental factors. Notably, female aggressor status (p 

In 2022, women accounted for nearly ** percent of the nursing personnel in El Salvador, while only one in every ten people working in the sector were men. In that year, there was an average ratio of *** nurses per doctor in the country.

ERI-effort and ERI-reward levels in dependence of gender (n = 6160) and profession (n = 6174).