In Sweden, the share of elderly of the total population has increased since 1970. Whereas people aged 65 years or more made up below 14 percent of the population in 1970, they made up over 20 percent of the population in 2023. In total, the population in Sweden increased steadily over the past decade and amounted to 10.55 million in 2023.

Aging population

As the average life expectancy at birth in Sweden increased over the past decade, meaning that people live longer, and the birth rate decreased during the same period, the average age of Swedes reached almost 42 years in 2022.

Aging population means smaller labor force

The aging population brings future challenges for the Swedish society. The increasing number of elderly needs care, but simultaneously, there will be fewer people at working age to take care of the elderly. At the same time, there will be fewer people available for other jobs as more people retire. By 2030, it is estimated that the share of the labor force aged 64 years or more will increase by two percent.

The elderly population (ageing 60 above) in India is increasing and is projected to climb by 11% point between 2010 to 2050 (UNPD, 2011). Due to better living condition and improved well-being, better health care system, availability of medicines, awareness among the people the mortality rate has reduced substantially. This demography brings a new economic and social concerns afront. The present work tries to investigate the health perception, nature and status of ailment and treatment availed by this part of population in India along with their demographic profile. The database used in the study is the 71st round dataset of National Sample Survey Organisation (NSSO). The work gives a brief review of the recent policies and initiatives taken to end the health challenges faced by the ageing population. Probable policy recommendations have been made that can potentially address the health concerns of the elderly in the country.

As of 2022, Indonesia’s senior population amounted to nearly ** million. The number of elderly citizens has gradually increased over the past decade. As Indonesia is entering a demographic dividend period where a working-age population dominates the country, it is expected that by the end of this phase, Indonesia will see a surge in the share of its old-age population.

Indonesia’s demographic shift Contrary to some Asian countries that are trying to accelerate their population growth, the Indonesian government has been trying to persuade its citizens to have fewer children. Many initiatives in promoting family planning and later marriages have led to a more controlled population growth. However, the country is expected to face a demographic shift in the upcoming years, with projections indicating that the elderly population will make up ** percent of the country’s population in 2045. Considering this, the Indonesian government has been reassessing its family planning initiatives to better prepare for the risks of an aging population.

Retirement readiness among the society  Indonesia still has a relatively low literacy rate for pension funds and a significantly lower inclusion rate of only slightly over five percent. In conjunction with this, only roughly ** percent of the elderly households in Indonesia were part of social security programs, and a large share of the country’s senior citizens live in three-generation households. These concerns tend to expose Indonesia to higher dependency risks among its aging population. Indeed, it is crucial to address the need to increase awareness of and enhance accessibility to pension funds or social security programs for adequate retirement planning in Indonesian society.

In 2024, there were around 754,000 residents aged 65 years and above in Singapore. Singapore is currently one of the most rapidly aging societies in Asia, along with Japan.

Author: Michael Robinson, educatorGrade/Audience: high school, ap human geography, professional developmentResource type: lessonSubject topic(s): population, human geographyRegion: asiaStandards: AP Human Geography Connection 2.9 Aging Populations - Explain the causes and consequences of an aging population. An aging population has political, social, and economic consequences, including the dependency ratio. Objectives: The student will identify the leading causes of death in South Korea. The student will describe the growing aging population in South Korea. The student will explain how South Korea is dealing with the aging population. The student will describe and explain possible ways of supporting the growing elderly population in South Korea. Summary: South Korea has one of the highest life expectancies in the world, which has led to a growing aged population. The number of persons over 65 is projected to continue to rise, and with the increase there are social issues the government must address. The lesson has students analyzing graphs and maps from The Atlas of Korea to identity, describe, and explain aging of the population of South Korea. Students will listen to a news report and read an editorial to help them determine solutions to this growing problem in South Korea.

Digital health has become increasingly vital for managing the needs of rapidly aging populations. This study reviews and maps research on digital health and aging in Asian countries from 2000 to 2024, identifying key opportunities, challenges, and emerging themes. Using a systematic and bibliometric approach, we screened 3,236 studies from Scopus and Web of Science and analyzed 753 eligible articles. Bibliometric techniques—including co-word, co-citation, and co-author analyses—were applied using the Bibliometrix R-package and its Biblioshiny interface to uncover the intellectual and thematic structure of the field. Our findings reveal a significant increase in research since 2018, driven by researchers based in China, Japan, South Korea, and Singapore, with a strong emphasis on telemedicine, mHealth, AI- and IoT-based systems, wearable devices, and smart home technologies. These digital health innovations enhance the quality of life, reduce fall risks, and improve care for frail older adults with chronic conditions in both clinical and community settings. However, significant gaps remain in Southeast and South Asia, and most studies are small-scale or pilot-based, which limits their generalizability. This review highlights the potential of digital health interventions to transform aging care in Asia and underscores the need for context-specific studies, multicounty collaborations, and supportive policy frameworks.

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development.

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).

Articulated processes of demographic and epidemiological transition in progress in recent decades in the country are followed by the growth of the elderly population, particularly the number of oldest old, aged over 80 years. This population aging requires reorganization of the state and society, especially in relation to health and pension systems. OBJECTIVE: To analyze the socio-epidemiological profile and degree of autonomy and independence of the oldest old in the city of Recife, state of Pernambuco, Brazil. METHOD: This was a descriptive epidemiological study, of cross-sectional type, with random sample composed of 227 seniors. They answered the questionnaire Brazil Old Age Schedule (BOAS) Modified on household interviews in the six districts of the city. RESULTS: In most elderly there are feminization, low level of education, marital status as widowhood and retirement as main source of income. Older people commonly lived with daughters and grandchildren, and major health problems were hypertension, column disease, vision problems, incontinence and osteoporosis. The degree of autonomy and independence of the oldest old was considered good, since there were no reports of impairments in performing activities of daily living (ADLs) for most seniors. CONCLUSIONS: With the trend towards increasing the number of oldest old in the coming years, it is necessary to implement specific policies, adapting programs and actions that contribute effectively to the achievement of quality of life in advanced old age.

The Aging Population Services market has emerged as a critical sector in response to the growing global demographic shift towards an older population. As life expectancy increases and birth rates decline, an estimated 1.4 billion people worldwide will be aged 60 and over by 2030. This demographic change is exerting

PurposeTo comprehensively identify the determinants of quality of life (QoL) in a population study sample of persons aged 18–50 and 50+.MethodsIn this observational, cross-sectional study, QoL was measured with the WHOQOL-AGE, a brief instrument designed to measure QoL in older adults. Eight hierarchical regression models were performed to identify determinants of QoL. Variables were entered in the following order: Sociodemographic; Health Habits; Chronic Conditions; Health State description; Vision and Hearing; Social Networks; Built Environment. In the final model, significant variables were retained. The final model was re-run using data from the three countries separately.ResultsComplete data were available for 5639 participants, mean age 46.3 (SD 18.4). The final model accounted for 45% of QoL variation and the most relevant contribution was given by sociodemographic data (particularly age, education level and living in Finland: 17.9% explained QoL variation), chronic conditions (particularly depression: 4.6%) and a wide and rich social network (4.6%). Other determinants were presence of disabling pain, learning difficulties and visual problems, and living in usable house that is perceived as non-risky. Some variables were specifically associated to QoL in single countries: age in Poland, alcohol consumption in Spain, angina in Finland, depression in Spain, and self-reported sadness both in Finland and Poland, but not in Spain. Other were commonly associated to QoL: smoking status, bodily aches, being emotionally affected by health problems, good social network and home characteristics.ConclusionsOur results highlight the importance of modifiable determinants of QoL, and provide public health indications that could support concrete actions at country level. In particular, smoking cessation, increasing the level of physical activity, improving social network ties and applying universal design approach to houses and environmental infrastructures could potentially increase QoL of ageing population.

Overview

This is a subset of the NPHA dataset filtered down to develop and validate machine learning algorithms for predicting the number of doctors a survey respondent sees in a year. This dataset’s records represent seniors who responded to the NPHA survey.

Dataset Information

For what purpose was the dataset created? The National Poll on Healthy Aging dataset was created to gather insights on the health, healthcare, and health policy issues affecting Americans aged 50 and older. By focusing on the perspectives of older adults and their caregivers, the University of Michigan aimed to inform the public, healthcare providers, policymakers, and advocates about the various aspects of aging. This includes topics like health insurance, household composition, sleep issues, dental care, prescription medications, and caregiving, thereby providing a comprehensive understanding of the health-related needs and concerns of the older population.

Who funded the creation of the dataset? The dataset was funded by AARP and Michigan Medicine, the University of Michigan's academic medical centre.

What do the instances in this dataset represent? Each row represents a survey respondent.

Does the dataset contain data that might be considered sensitive in any way? Yes. There is information about race/ethnicity, gender, age.

Was there any data preprocessing performed? For this subset of the original NPHA dataset we chose 14 features related to health and sleep to use for the prediction task. We then removed all survey respondents with missing responses for any of the chosen features.

Has Missing Values? No

Introductory Paper National Poll on Healthy Aging (NPHA) By Malani, Preeti N., Kullgren, Jeffrey, and Solway, Erica. 2017 Published in Inter-university Consortium for Political and Social Research

Additional Variable Information

Class Labels

Number of Doctors Visited: The total count of different doctors the patient has seen = { 1: 0-1 doctors 2: 2-3 doctors 3: 4 or more doctors }

Age: The patient's age group = { 1: 50-64 2: 65-80 }

Physical Health: A self-assessment of the patient's physical well-being = { -1: Refused 1: Excellent 2: Very Good 3: Good 4: Fair 5: Poor }

Mental Health: A self-evaluation of the patient's mental or psychological health = { -1: Refused 1: Excellent 2: Very Good 3: Good 4: Fair 5: Poor }

Dental Health: A self-assessment of the patient's oral or dental health= { -1: Refused 1: Excellent 2: Very Good 3: Good 4: Fair 5: Poor }

Employment: The patient's employment status or work-related information = { -1: Refused 6 1: Working full-time 2: Working part-time 3: Retired 4: Not working at this time }

Stress Keeps Patient from Sleeping: Whether stress affects the patient's ability to sleep = { 0: No 1: Yes }

Medication Keeps Patient from Sleeping: Whether medication impacts the patient's sleep = { 0: No 1: Yes }

Pain Keeps Patient from Sleeping: Whether physical pain disturbs the patient's sleep = { 0: No 1: Yes }

Bathroom Needs Keeps Patient from Sleeping: Whether the need to use the bathroom affects the patient's sleep = { 0: No 1: Yes }

Unknown Keeps Patient from Sleeping: Unidentified factors affecting the patient's sleep = { 0: No 1: Yes }

Trouble Sleeping: General issues or difficulties the patient faces with sleeping = { 0: No 1: Yes }

Prescription Sleep Medication: Information about any sleep medication prescribed to the patient = { -1: Refused 1: Use regularly 2: Use occasionally 3: Do not use }

Race: The patient's racial or ethnic background = { -2: Not asked -1: REFUSED 1: White, Non-Hispanic 2: Black, Non-Hispanic 3: Other, Non-Hispanic 4: Hispanic 5: 2+ Races, Non-Hispanic } Gender: The gender identity of the patient = { -2: Not asked -1: REFUSED 1: Male 2: Female }

In 2024, the share of the Malaysian population aged over 65 years was at *** percent, an increase compared to *** percent in the previous year. Malaysia is currently facing the prospect of an aging population, and the latest statistical data predicted this to be happening as soon as in 2030. Aging population by 2030? An aging population is defined as one in which those aged 65 years and above make up at least 15 percent of the total population. According to a statement by Malaysia’s Chief Statistician in July 2019, the 15 percent threshold would be crossed in 2030. The past ten years have seen a change in Malaysia’s age structure. The share of the population between 0 and 14 years had been decreasing steadily, while the inverse was true for those aged 65 and above. The average age of the Malaysian population reflected this trend, and was expected to reach **** years in 2030, up from **** years in 2015. Is Malaysia ready for an aging society? Academics fear that Malaysian society would not be ready to meet the needs of a rapidly aging society. In a survey on aging, more than ** percent of Malaysian respondents felt that it was the duty of the young to take care of the elderly. This mindset places the burden of care on a shrinking base of young people. Not only that, it could contribute to the underdevelopment of social services for the elderly. Already, more Malaysians seemed pessimistic about aging. Existing problems such as a lack of professional caregivers, affordable care, and elderly-friendly housing, especially in rural areas, need to be quickly addressed before the silver tsunami overwhelms the country.

The global market for digital smart elderly care solutions is experiencing robust growth, driven by an aging global population and increasing demand for convenient, effective, and remote monitoring capabilities. The market, estimated at $15 billion in 2025, is projected to experience a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors, including technological advancements in sensor technology, AI-powered analytics, and telehealth platforms. Governments worldwide are also increasingly investing in supportive infrastructure and policies encouraging the adoption of these solutions, further bolstering market growth. The cloud-based segment currently dominates the market due to its scalability, cost-effectiveness, and accessibility, while the North American market holds a significant share, driven by high technological adoption rates and a sizeable elderly population. However, challenges remain, including data privacy concerns, the digital literacy gap among older adults, and the high initial investment costs associated with implementing comprehensive smart elderly care systems.
The market segmentation reveals strong performance across various application areas, with family-based solutions leading the way, followed by nursing homes and other institutional settings. The technology is evolving rapidly, creating opportunities for companies like Philips, IBM, Siemens, GE Healthcare, and others to innovate and develop advanced solutions incorporating features such as fall detection, medication reminders, and remote health monitoring. While the market is witnessing substantial growth, competition among established players and emerging startups is likely to intensify in the coming years. Future success will depend on developing user-friendly interfaces, addressing data security and privacy issues effectively, and offering affordable solutions accessible across various socioeconomic backgrounds. Geographical expansion into developing economies with rapidly aging populations represents significant untapped potential for growth and market penetration.

The global market for smart elderly care solutions is experiencing robust growth, driven by an aging global population and increasing demand for independent living solutions. Technological advancements, such as AI-powered monitoring systems, wearable sensors, and smart home automation, are transforming how elderly individuals receive care. The market is segmented by solution type (e.g., remote monitoring, telehealth, assistive robotics), deployment model (cloud-based, on-premise), and end-user (home, assisted living facilities). While the market faces challenges like high initial investment costs and data privacy concerns, the long-term benefits of improved health outcomes and reduced healthcare burdens are driving widespread adoption. Key players like Emoha Elder Care, MariCare, and others are leveraging technological innovations and strategic partnerships to gain market share. The market's growth trajectory is expected to remain strong throughout the forecast period (2025-2033), fueled by rising disposable incomes, increased awareness of smart elderly care benefits, and supportive government initiatives promoting aging-in-place solutions. We project a steady CAGR, even accounting for potential market fluctuations. Specific regional growth rates will vary based on factors like healthcare infrastructure, technological adoption rates, and government policies. The market's competitive landscape is characterized by both established players and emerging startups, leading to increased innovation and competition. The success of smart elderly care solutions hinges on addressing the specific needs and concerns of the elderly population and their caregivers. This includes ensuring user-friendliness, data security, and seamless integration with existing healthcare systems. Further growth will depend on overcoming hurdles like technological literacy gaps among older adults and ensuring affordability for a wide range of users. The development of advanced analytics capabilities that can predict health risks and facilitate proactive interventions will further contribute to market expansion. The focus will be on creating personalized and adaptable solutions that cater to individual needs and preferences, optimizing both the quality of life and the efficiency of care delivery. This includes a growing trend toward integrated solutions that combine various aspects of smart elderly care, such as medication reminders, fall detection, and remote health monitoring into a single, unified platform.

According to a survey carried out among the elderly in India in February 2023, 46 percent of respondents claimed that they were aware about dedicated healthcare facilities for elderly people in the country. About 19 percentage of respondents claimed they were unaware of such dedicated facilities.

Objective: This study investigated the prevalence of food security, and the association of food security with financial hardship and socio-demographic characteristics among the ageing population in Thailand.Methods: The study extracted data on 1,197 persons age 60 years or older from a nationally-representative sample survey of Thai households. The food security data were collected using the Food Insecurity Experience Scale (FIES), developed by the Food and Agriculture Organization. Multiple regression analysis was used to investigate the association between financial hardship, socio-demographic characteristics, and food security.Results: Of the total sample, 71% had food security. The least probability of having food security was observed in the respondents who sometimes and often had income problems (p < 0.001), and felt dissatisfied with their financial situation (p < 0.001). The respondents who were female, at oldest-old age, with lower than primary school education and in the Northeast were less likely to have food security.Conclusion: These findings suggest the need for government assistance for those who are experiencing financial hardship to help them manage their finances and food security more effectively, taking into account different socio-demographic characteristics.

As of 2023, more than ** percent of the elderly population in Indonesia had health complaints, showing a decrease from the previous years. In the same year, Indonesia's senior population had a morbidity rate of around **** percent.

The mental health of the elderly is a matter of increased concern in the context of an aging population since currently only a small fraction of this population is receiving adequate care. The provision of treatment in primary care by the General Practitioners (GPs) has been proposed for over a decade as a potential solution, as services offered by GPs are more accessible, less susceptible to stigma, and have a more comprehensive view of the other health care problems that the elderly might suffer from. In this study, we explored the perception of Romanian GPs regarding their practice and roles in caring for the mental health of the elderly as well as the willingness to increase their future involvement in the management of dementia and other mental health problems. Data was collected via an online questionnaire structured on four dimensions: (1) GPs' sociodemographic profile and practice characteristics, (2) GPs assessment of the services available for elderly with mental health problems, (3) GPs current involvement in mental health care for different categories of problems, and (4) factors that might influence the future involvement of GPs in providing care for elderly with mental health problems. The survey was sent via the member mailing lists of the National Society for Family Medicine. Results show that GPs are currently limited by prescribing possibilities, available resources and knowledge in the area, but they are willing to expand their role in the areas of early recognition and prevention of mental health problems as well as providing disease management and collaborative care. An improved communication with mental health care professionals, a better access to resources and having more financial incentives are the three most important categories for GPs to increase their involvement. In conclusion, increasing the access to personal and professional resources and setting up functional communication channels with specialized mental health care could motivate GPs to provide timely mental health support to elderly patients.

The Survey of Health, Ageing and Retirement in Europe (SHARE), is a longitudinal micro-data infrastructure created in response to a communication by the European Commission (2000) to the Council and the European Parliament, which identified population ageing and its social and economic challenges to growth and prosperity to be among the most pressing challenges of the 21st century in Europe. SHARE has also become one of the most prestigious social science infrastructures and was in 2011 the first to be appointed a European Research Infrastructure Consortium (ERIC) by the European Council.The overarching objective of SHARE is to better understand the interactions between bio-medical factors, the socio-economic environment and policy interventions in the ageing European populations. SHARE aims to achieve this objective by providing a research infrastructure for fundamental science as well as a tool for policy evaluation and design. Initiated in 2002, SHARE is scheduled to launch, all in all, 10 data collection waves. At present eight waves have been fulfilled and seven waves are available to the research community.

When using data from this dataset, please cite the dataset as follows:

Börsch-Supan, A. (2022). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 7. Release version: 8.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w7.800

Please also cite the following publications in addition to theSHARE acknowledgement: Bergmann, M., A. Scherpenzeel and A. Börsch-Supan (Eds.) (2019). SHARE Wave 7 Methodology: Panel Innovations and Life Histories. Munich: Munich Center for the Economics of Aging (MEA). Börsch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan, B., Stuck, S. and Zuber, S. (2013). Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE). International Journal of Epidemiology DOI: 10.1093/ije/dyt088.