In 2024, Monaco was the country with the highest percentage of the total population that was over the age of 65, with ** percent. Japan had the second highest with ** percent, while Portugal and Bulgaria followed in third with ***percent.

The average for 2023 based on 196 countries was 10.17 percent. The highest value was in Monaco: 36.36 percent and the lowest value was in Qatar: 1.57 percent. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

In 2023, the share of the population of Japan above the age of 65 was projected to amount to around ** percent. In contrast, the share of the population older than 65 in Thailand was projected to be about *** percent that year.

In Japan, ** percent of the population was 65 years or older in 2025, underlining the aging population of the country. Among the G7, Japan and Italy had a higher share of people aged 65 years. The United States had the highest share of children and youth between zero and 19 years at nearly ** percent.

In 2040, the percentage of the population of Singapore above the age of 65 was forecasted to reach more than ** percent. Comparatively, the share of the population older than 65 in Laos was forecasted to reach about *** percent.

Taiwan, Japan, South Korea, the United States, the United Kingdom, Germany, France, Norway, Sweden, the Netherlands, Switzerland, Austria, Italy, and Spain, and other countries, the historical and future estimated values of the proportion of the population aged 65 and over.

In 2050, the three East Asian countries Hong Kong (SAR of China), South Korea, and Japan are forecasted to have the highest share of people aged 65 years or more. Except for Kuwait, all the countries on the list are either in Europe or East Asia. By 2050, 22 percent of the world's population is expected to be above 60 years.

In 2024, Italy and Portugal were the European countries with the largest share of elderly population, with ** percent of the total population aged 65 years and older. Bulgaria, Finland, and Greece were the countries with the next highest shares of elderly people in their population, while the European Union on average had **** percent of the population being elderly. Iceland, Ireland, and Luxembourg had around ** percent of their population being elderly, while Türkiye and Azerbaijan had around ** percent.

We assess the potential impact of international migration on population ageing in Asian countries by estimating replacement migration for the period 2022-2050.

This open data deposit contains the code (R-scripts) and the datasets (csv-files) for the replacement migration scenarios and a zero-migration scenario:

• Constant chronological old-age dependency ratio (Constant OADR scenario)
• Constant prospective old-age dependency ratio (Constant POADR scenario)
• Constant chronological working-age population (Constant WA scenario)
• Constant prospective working-age population (Constant PWA scenario)
• Zero-migration (ZM scenario)

Countries included in the analysis: Armenia, China, Georgia, Hong Kong, Japan, Macao, North Korea, Singapore, South Korea, Taiwan, Thailand.

Please note that for Armenia and Hong Kong (2023) and Georgia (2024) later baseline years are applied due to the UN country-specific assumptions on post-Covid-19 mortality.

For detailed information about the scenarios and parameters:

Dörflinger, M., Potancokova, M., Marois, G. (2024): The potential impact of international migration on prospective population ageing in Asian countries. Asian Population Studies. https://doi.org/10.1080/17441730.2024.2436201

All underlying data (UN World Population Prospects 2022) are openly available at:

https://population.un.org/wpp/Download/Archive

Code

1_Data.R:

• Load and merge data from UN World Population Prospects 2022
• Define sample
• Prepare data (prospective old-age thresholds, model sex and age pattern of migrants)

2_Scenarios.R:

• Replacement migration scenarios:
  • Constant chronological old-age dependency
  • Constant prospective old-age dependency
  • Constant chronological working-age population
  • Constant prospective working-age population
• Zero-migration scenario

3_Robustness_checks.R:

• Run replacement migrations scenarios with different model sex and age patterns for net migration

Program version used: RStudio "Chocolate Cosmos" (e4392fc9, 2024-06-05). Files may not be compatible with other versions.

Datasets

The datasets contain the key information on population size, the relevant indicators (OADR, POADR, WA, PWA) and replacement migration volumes and rates by country and year. Please see readme_datasets.txt for detailed information.

Acknowledgements

Part of the research was developed in the Young Scientists Summer Program at the International Institute for Applied Systems Analysis, Laxenburg (Austria) with financial support from the German National Member Organization.

The historical and future estimated values of the aging index for countries such as Taiwan, Japan, South Korea, the United States, the United Kingdom, Germany, France, Norway, Sweden, the Netherlands, Switzerland, Austria, Italy, and Spain.

This dataset was created to support the 2016 DIA (Related publication only available in Spanish). The accelerated aging process that countries in Latin America and the Caribbean are undergoing imposes unprecedented pressures on the long-term care sector. In this context, the growing demand for care from the elderly population occurs alongside a reduction in the availability of informal care. Governments in the region must prepare to address these pressures by supporting the provision of care services to alleviate social exclusion in old age. The Inter-American Development Bank has created an Observatory on Aging and Care — the focus of this policy brief — aimed at providing decision-makers with information to design policies based on available empirical evidence. In this initial phase, the Observatory seeks to document the demographic situation of countries in the region, the health of their elderly population, their limitations and dependency status, as well as their main socioeconomic characteristics. The goal is to estimate the care needs countries in the region will face. This brief summarizes the key findings from an initial analysis of the data. The results highlight the scale of the problem. The figures speak for themselves: in the region, 11% of the population aged 60 and older is dependent. Both the magnitude and intensity of dependency increase with age. Women are the most affected across all age groups. This policy brief is part of a series of studies on dependency care, including works by Caruso, Galiani, and Ibarrarán (2017); Medellín et al. (2018); López-Ortega (2018); and Aranco and Sorio (2018).

The G7 countries are facing aging populations in the coming decades. This is especially the case in Italy and Japan, where over ** percent of the population is forecast to be 65 years or older by 2050. By 2050, all G7 countries are predicted to have a higher share of people above 65 years than people between 0 and 19 years. Japan, Italy, as well as Germany already had a higher share of older population than children and youth in 2024.

This map shows where senior populations are found throughout the world. Areas with more than 10% seniors are highlighted with a dark red shading while a dot representation reveals the number of seniors and their distribution in bright red.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics

BackgroundLow-and middle-income countries mostly have ageing populations with many unmet economic, social, or health-related needs, Vietnam being an example. Community-based support in Vietnam, organized as Intergenerational Self-Help Clubs (ISHCs) based on the Older People Associations (OPA) model, can help to meet these needs by the provision of services for various aspects of life. This study aims to assess the implementation of the ISHCs and whether successful implementation is associated with more member-reported positive health.MethodsWe used the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework to evaluate the implementation using multiple data sources: ISHC board surveys (n = 97), ISHC member surveys (n = 5,080 in 2019 and n = 5,555 in 2020), focus group discussions (6; n = 44), and interviews with members and board leaders (n = 4).ResultsReach ranged between 46 and 83% of ISHCs reaching target groups, with a majority of women and older people participating. Regarding Effectiveness, members indicated high satisfaction with the ISHCs. Adoption scores were high, with 74%–99% for healthcare and community support activities, and in 2019, higher adoption scores were associated with more members reporting good positive health. In 2020, reported positive health slightly decreased, probably due to the influence of the COVID-19 pandemic. A total of 61 ISHCs had consistent or improving Implementation from 2019 to 2020, and confidence in Maintenance was high.ConclusionThe implementation of the OPA model in Vietnam is promising regarding its promotion of health and may help to tackle the needs of an ageing population. This study further shows that the RE-AIM framework helps to assess community health promotion approaches.

Opinion on the needs, objectives, expenditures and outcomes of national family policies. Expectations for the future. Role of EU. #####The results by volumes are distributed as follows: * Volume A: Countries * Volume AA: Groups of countries * Volume A' (AP): Trends * Volume AA' (AAP): Trends of groups of countries * Volume B: EU/socio-demographics * Volume C: Country/socio-demographics ---- Researchers may also contact GESIS - Leibniz Institute for the Social Sciences: http://www.gesis.org/en/home/

Abstract

Purpose: The multi-country Study on Global Ageing and Adult Health (SAGE) is run by the World Health Organization's Multi-Country Studies unit in the Innovation, Information, Evidence and Research Cluster. SAGE is part of the unit's Longitudinal Study Programme which is compiling longitudinal data on the health and well-being of adult populations, and the ageing process, through primary data collection and secondary data analysis. INDEPTH SAGE Wave 1 (2006/7) provides data on the health and well-being of adults in: Ghana, India and South Africa.

Objectives: To obtain reliable, valid and comparable health, health-related and well-being data over a range of key domains for adult and older adult populations in nationally representative samples To examine patterns and dynamics of age-related changes in health and well-being using longitudinal follow-up of a cohort as they age, and to investigate socio-economic consequences of these health changes To supplement and cross-validate self-reported measures of health and the anchoring vignette approach to improving comparability of self-reported measures, through measured performance tests for selected health domains To collect health examination and biomarker data that improves reliability of morbidity and risk factor data and to objectively monitor the effect of interventions

Additional Objectives: To generate large cohorts of older adult populations and comparison cohorts of younger populations for following-up intermediate outcomes, monitoring trends, examining transitions and life events, and addressing relationships between determinants and health, well-being and health-related outcomes To develop a mechanism to link survey data to demographic surveillance site data To build linkages with other national and multi-country ageing studies To improve the methodologies to enhance the reliability and validity of health outcomes and determinants data To provide a public-access information base to engage all stakeholders, including national policy makers and health systems planners, in planning and decision-making processes about the health and well-being of older adults

Methods: INDEPTH SAGE's first full round of data collection included persons aged 50 years and older in the health and demographic surveillance sites. All persons aged 50+ years (for example, spouses and siblings) were invited to participate. Standardized SAGE survey instruments were used in all countries consisting of two main parts: 1) household questionnaire; 2) individual questionnaire. The procedures for including country-specific adaptations to the standardized questionnaire and translations into local languages from English follow those developed by and used for the World Health Survey.

Content - Household questionnaire 0000 Coversheet 0100 Sampling Information 0200 Geocoding and GPS Information 0300 Recontact Information 0350 Contact Record 0400 Household Roster 0450 Kish Tables and Household Consent 0500 Housing 0600 Household and Family Support Networks and Transfers 0700 Assets and Household Income 0800 Household Expenditures 0900 Interviewer Observations

• Individual questionnaire 1000 Socio-Demographic Characteristics 1500 Work History and Benefits 2000 Health State Descriptions and Vignettes 2500 Anthropometrics, Performance Tests and Biomarkers 3000 Risk Factors and Preventive Health Behaviours 4000 Chronic Conditions and Health Services Coverage 5000 Health Care Utilization 6000 Social Cohesion 7000 Subjective Well-Being and Quality of Life (WHOQoL-8 and Day Reconstruction Method) 8000 Impact of Caregiving 9000 Interviewer Assessment

Geographic coverage

Rural subdistrict Mpumalanga Province

Analysis unit

household and individuals

Universe

Agincourt Health and Demographic Surveillance Site fifty plus population

Kind of data

Sample survey data [ssd]

Sampling procedure

Simple random sample of 575 persons 50 years and older with an oversample of women from the 2005 HDSS census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were based on the WHS Model Questionnaire with some modification and many new additions. A household questionnaire was administered to all households eligible for the study. An Individual questionnaire was administered to eligible respondents identified from the household roster. The questionnaires were developed in English and were piloted as part of the SAGE pretest. All documents were translated into Shangaan.

Cleaning operations

Data editing took place at a number of stages including: (1) office editing and coding (2) during data entry (3) structural checking of the CSPro files (4) range and consistency secondary edits in Stata

Response rate

86% of participants accepted to participate, 10% were not found and 4% refused to participate.

The unprecedented demographic shifts toward an aging population pose significant challenges to global healthcare systems. Understanding the heterogeneity in disease prevalence among the elderly is crucial for effective public health strategies. Using prevalence data of 85 types of age-related diseases, we calculated the global heterogeneity of disease distribution by the Shannon Diversity Index (SHDI). We observed significant geographic variations in disease heterogeneity, with higher SHDI values in high-income Western countries such as the United States of America and Sweden and lower in South Asia and Oceania (p < 0.05). In 2021, SHDI values in elderly populations (age ≥ 60 years) for Europe and North America countries were an average of 1.12 times higher than in Oceania. While SHDI increases toward higher ages (for instance, in 2021, SHDI for adults above 95 years is 1.06 times higher than for ages between 60 and 64 years), the global SHDI tends to decrease nonlinearly over time. From 1990 to 2021, global age-standardized SHDI (age ≥ 60 years) averagely decreased by 1.2% for both men and women. Our analysis further revealed that socio-economic factors (e.g., socio-demographic indices, governance) strongly impacted global SHDI changes, while climatic and environmental factors (e.g., extreme climate and air pollution) showed significant differences across genders. Our study highlights the need for implementing comprehensive healthcare strategies, focusing on reducing health disparities and addressing environmental and socio-economic determinants to address inequalities in age-related diseases effectively.

Elder Care Robotics Market Outlook

The Elder Care Robotics market is experiencing robust growth, with a market size valued at approximately USD 1.5 billion in 2023 and projected to reach USD 9.2 billion by 2032, reflecting a remarkable compound annual growth rate (CAGR) of 22.4% over the forecast period. Key growth factors driving this market include the increasing aging population worldwide, advancements in robotics technology, and the growing need for efficient healthcare solutions to support elderly care. The convergence of technology and healthcare is enabling innovative solutions that are reshaping how elder care is delivered, making the market for elder care robotics expansive and dynamic.

One of the primary growth factors propelling the elder care robotics market is the demographic shift towards an aging population. With life expectancy rising globally, there is an increasing number of elderly individuals who require care and assistance. This demographic trend is particularly pronounced in countries like Japan, the United States, and several European nations. The demand for elder care solutions that can provide support while maintaining the dignity and independence of the elderly is consequently on the rise. Robotics offers an effective solution by providing assistive technologies that can help elderly individuals perform daily tasks, monitor their health, and ensure safety, reducing the burden on healthcare systems and caregivers.

The technological advancement in robotics and artificial intelligence (AI) is another significant growth catalyst in this market. The integration of AI and machine learning in robotic systems enhances their capability to perform complex tasks, learn from interactions, and adapt to the needs of elderly users. These technologies enable robots to offer personalized care, engage in social interactions, and provide critical health monitoring, making them indispensable tools in modern elder care. Continuous research and development in this sector are leading to the creation of more sophisticated, cost-effective, and user-friendly robotic solutions that cater specifically to the elderly, further fueling market growth.

Moreover, the societal trend towards independent living and in-home care is significantly influencing this market. Many elderly individuals prefer to stay in their homes rather than move to assisted living facilities, a preference that has been supported by advancements in elder care technologies. Elder care robots provide the necessary assistance that allows seniors to live independently with dignity and comfort. These robots can assist with routine activities, provide companionship, and perform health assessments, thereby enhancing the quality of life for seniors. This preference for in-home care is driving demand for elder care robotics, as families and care facilities look for innovative solutions to meet the needs of aging populations.

Regionally, the North American market is a leading adopter of elder care robotics, driven by high healthcare expenditure, technological innovation, and a supportive regulatory environment. The Asia Pacific region is also witnessing significant growth due to its large elderly population base, particularly in countries like China and Japan. Europe is steadily incorporating advanced elder care technologies as part of its healthcare strategy to address the increasing needs of its aging population. The Middle East & Africa and Latin America are emerging markets, gradually adopting elder care robotics as awareness and investment in this technology grow.

Product Type Analysis

The elder care robotics market is segmented by product type into assistive robots, monitoring robots, socially assistive robots, and others. Assistive robots are designed to aid elderly individuals in performing daily living activities such as dressing, bathing, and moving around. These robots are equipped with various features like mobility support, fall detection, and scheduling reminders, which not only enhance independence but also ensure the safety of seniors. With the integration of AI, these robots are becoming increasingly sophisticated, capable of recognizing voice commands and learning user preferences, making them more effective in providing personalized care.

Monitoring robots play a crucial role in elder care by ensuring the health and safety of elderly individuals. These robots are equipped with advanced sensors and cameras that monitor vital signs, detect falls, and alert caregivers in case of emergencies. The demand for monitoring robots is driven by the need for continuous health assessment and th

About this dataset

Context

The dataset tabulates the Country Life Acres population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Country Life Acres. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 38 (47.50% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Country Life Acres population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Country Life Acres is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Country Life Acres is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Country Life Acres Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Country Club Hills population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Country Club Hills. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 633 (62.24% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Country Club Hills population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Country Club Hills is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Country Club Hills is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Country Club Hills Population by Age. You can refer the same here