Luxembourg stands out as the European leader in quality of life for 2025, achieving a score of 220 on the Quality of Life Index. The Netherlands follows closely behind with 211 points, while Albania and Ukraine rank at the bottom with scores of 104 and 115 respectively. This index provides a thorough assessment of living conditions across Europe, reflecting various factors that shape the overall well-being of populations and extending beyond purely economic metrics. Understanding the quality of life index The quality of life index is a multifaceted measure that incorporates factors such as purchasing power, pollution levels, housing affordability, cost of living, safety, healthcare quality, traffic conditions, and climate, to measure the overall quality of life of a Country. Higher overall index scores indicate better living conditions. However, in subindexes such as pollution, cost of living, and traffic commute time, lower values correspond to improved quality of life. Challenges affecting life satisfaction Despite the fact that European countries register high levels of life quality by for example leading the ranking of happiest countries in the world, life satisfaction across the European Union has been on a downward trend since 2018. The EU's overall life satisfaction score dropped from 7.3 out of 10 in 2018 to 7.1 in 2022. This decline can be attributed to various factors, including the COVID-19 pandemic and economic challenges such as high inflation. Rising housing costs, in particular, have emerged as a critical concern, significantly affecting quality of life. This issue has played a central role in shaping voter priorities for the European Parliamentary Elections in 2024 and becoming one of the most pressing challenges for Europeans, profoundly influencing both daily experiences and long-term well-being.

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

In 2024, gross domestic product per capita in the United Kingdom was 40,172 British pounds, compared with 40,162 pounds in the previous year. In general, while GDP per capita has grown quite consistently throughout this period, there are noticeable declines, especially between 2007 and 2009, and between 2019 and 2020, due to the Global Financial Crisis, and COVID-19 pandemic, respectively. Why is GDP per capita stagnating when the economy is growing? During the last two years that GDP per capita fell and then stagnated in the UK, the overall economy grew by 0.4 percent in 2023 and 1.1 percent in 2024. While the overall UK economy is therefore larger than it was in 2022, the UK's population has grown at a faster rate, resulting in the lower GDP per capita figure. The long-term slump in the UK's productivity, as measured by output per hour worked, has meant that the gap between GDP growth and GDP per capita growth has been widening for some time. Economy remains the main concern of UK voters As of February 2025, the economy was seen as the main issue facing the UK, just ahead of immigration, health, and several other problems in the country. While Brexit was seen as the most important issue before COVID-19, and concerns about health were dominant throughout 2020 and 2021, the economy has generally been the primary facing voters issue since 2022. The surge in inflation throughout 2022 and 2023, and the impact this had on wages and living standards, resulted in a very tough period for UK households. As of January 2025, 57 percent of households were still noticing rising living costs, although this is down from a peak of 91 percent in August 2022.

A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

Context

Most countries of the world define poverty as a lack of money. Yet poor people themselves consider their experience of poverty much more broadly. A person who is poor can suffer from multiple disadvantages at the same time – for example they may have poor health or malnutrition, a lack of clean water or electricity, poor quality of work or little schooling. Focusing on one factor alone, such as income, is not enough to capture the true reality of poverty.

Multidimensional poverty measures can be used to create a more comprehensive picture. They reveal who is poor and how they are poor – the range of different disadvantages they experience. As well as providing a headline measure of poverty, multidimensional measures can be broken down to reveal the poverty level in different areas of a country, and among different sub-groups of people.

Content

OPHI researchers apply the AF method and related multidimensional measures to a range of different countries and contexts. Their analyses span a number of different topics, such as changes in multidimensional poverty over time, comparisons in rural and urban poverty, and inequality among the poor. For more information on OPHI’s research, see our working paper series and research briefings.

OPHI also calculates the Global Multidimensional Poverty Index MPI, which has been published since 2010 in the United Nations Development Programme’s Human Development Report. The Global MPI is an internationally-comparable measure of acute poverty covering more than 100 developing countries. It is updated by OPHI twice a year and constructed using the AF method.

The Alkire Foster (AF) method is a way of measuring multidimensional poverty developed by OPHI’s Sabina Alkire and James Foster. Building on the Foster-Greer-Thorbecke poverty measures, it involves counting the different types of deprivation that individuals experience at the same time, such as a lack of education or employment, or poor health or living standards. These deprivation profiles are analysed to identify who is poor, and then used to construct a multidimensional index of poverty (MPI). For free online video guides on how to use the AF method, see OPHI’s online training portal.

To identify the poor, the AF method counts the overlapping or simultaneous deprivations that a person or household experiences in different indicators of poverty. The indicators may be equally weighted or take different weights. People are identified as multidimensionally poor if the weighted sum of their deprivations is greater than or equal to a poverty cut off – such as 20%, 30% or 50% of all deprivations.

It is a flexible approach which can be tailored to a variety of situations by selecting different dimensions (e.g. education), indicators of poverty within each dimension (e.g. how many years schooling a person has) and poverty cut offs (e.g. a person with fewer than five years of education is considered deprived).

The most common way of measuring poverty is to calculate the percentage of the population who are poor, known as the headcount ratio (H). Having identified who is poor, the AF method generates a unique class of poverty measures (Mα) that goes beyond the simple headcount ratio. Three measures in this class are of high importance:

Adjusted headcount ratio (M0), otherwise known as the MPI: This measure reflects both the incidence of poverty (the percentage of the population who are poor) and the intensity of poverty (the percentage of deprivations suffered by each person or household on average). M0 is calculated by multiplying the incidence (H) by the intensity (A). M0 = H x A.

Find out about other ways the AF method is used in research and policy.

Additional data here.

Acknowledgements

Alkire, S. and Robles, G. (2017). “Multidimensional Poverty Index Summer 2017: Brief methodological note and results.” OPHI Methodological Note 44, University of Oxford.

Alkire, S. and Santos, M. E. (2010). “Acute multidimensional poverty: A new index for developing countries.” OPHI Working Papers 38, University of Oxford.

Alkire, S. Jindra, C. Robles, G. and Vaz, A. (2017). ‘Multidimensional Poverty Index – Summer 2017: brief methodological note and results’. OPHI MPI Methodological Notes No. 44, Oxford Poverty and Human Development Initiative, University of Oxford.

Inspiration

• Which countries exhibit the largest subnational disparities in MPI?
• Which countries have high per-capita incomes yet still rank highly in MPI?

The project, based at the University of Greenwich, UK and Stellenbosch University, South Africa, aimed to examine epidemiologic transitions by identifying and quantifying the drivers of change in CVD risk in the middle-income country of South Africa compared to the high-income nation of England. The project produced a harmonised dataset of national surveys measuring CVD risk factors in South Africa and England for others to use in future work. The harmonised dataset includes microdata from nationally-representative surveys in South Africa derived from the Demographic and Health Surveys, National Income Dynamics Study, South Africa National Health and Nutrition Examination Survey and Study on Global Ageing and Adult Health, covering 11 cross-sections and approximately 156,000 individuals aged 15+ years, representing South Africa’s adult population from 1998 to 2017.

Data for England come from 17 Health Surveys for England (HSE) over the same time period, covering over 168,000 individuals aged 16+ years, representing England’s adult population.

This study uses existing data to identify drivers of recent health transitions in South Africa compared to England. The global burden of non-communicable diseases (NCDs) on health is increasing. Cardiovascular diseases (CVD) in particular are the leading causes of death globally and often share characteristics with many major NCDs. Namely, they tend to increase with age and are influenced by behavioural factors such as diet, exercise and smoking. Risk factors for CVD are routinely measured in population surveys and thus provide an opportunity to study health transitions. Understanding the drivers of health transitions in countries that have not followed expected paths (eg, South Africa) compared to those that exemplified models of 'epidemiologic transition' (eg, England) can generate knowledge on where resources may best be directed to reduce the burden of disease. In the middle-income country of South Africa, CVD is the second leading cause of death after HIV/AIDS and tuberculosis (TB). Moreover, many of the known risk factors for NCDs like CVD are highly prevalent. Rates of hypertension are high, with recent estimates suggesting that over 40% of adults have high blood pressure. Around 60% of women and 30% of men over 15 are overweight in South Africa. In addition, excessive alcohol consumption, a risk factor for many chronic diseases, is high, with over 30% of men aged 15 and older having engaged in heavy episodic drinking within a 30-day period. Nevertheless, infectious diseases such as HIV/AIDS remain the leading cause of death, though many with HIV/AIDS and TB also have NCDs. In high-income countries like England, by contrast, NCDs such as CVD have been the leading causes of death since the mid-1900s. However, CVD and risk factors such as hypertension have been declining in recent decades due to increased prevention and treatment. The major drivers of change in disease burden have been attributed to factors including ageing, improved living standards, urbanisation, lifestyle change, and reduced infectious disease. Together, these changes are often referred to as the epidemiologic transition. However, recent research has questioned whether epidemiologic transition theory accurately describes the experience of many low- and middle-income countries or, in fact, of high-income nations such as England. Furthermore, few studies have empirically tested the relative contributions of demographic, behavioural, health and economic factors to trends in disease burden and risk, particularly on the African continent. In addition, many social and environmental factors are overlooked in this research. To address these gaps, our study will use population measurements of CVD risk derived from surveys in South Africa over nearly 20 years in order to examine whether and to what extent demographic, behavioural, environmental, medical, social and other factors contribute to recent health trends and transitions. We will compare these trends to those occurring in England over the same time period. Thus, this analysis seeks to illuminate the drivers of health transitions in a country which is assumed to still be 'transitioning' to a chronic disease profile but which continues to have a high infectious disease burden (South Africa) as compared to a country which is assumed to have already transitioned following epidemiological transition theory (England). The analysis will employ modelling techniques on pooled cross-sectional data to examine how various factors explain the variation in CVD risk over time in representative population samples from South Africa and England. The results of this analysis may help to identify some of the main contributors to recent changes in CVD risk in South Africa and England. Such information can be used to pinpoint potential areas for intervention, such as social policy and services, thereby helping to set priorities for governmental and nongovernmental action to control the CVD epidemic and improve health.

Abstract

The Young Lives survey is an innovative long-term project investigating the changing nature of childhood poverty in four developing countries. The purpose of the project is to improve understanding of the causes and consequences of childhood poverty and examine how policies affect children's well-being, in order to inform the development of future policy and to target child welfare interventions more effectively. The study is being conducted in Ethiopia, India (in Andhra Pradesh), Peru and Vietnam. These countries were selected because they reflect a range of cultural, geographical and social contexts and experience differing issues facing the developing world; high debt burden, emergence from conflict, and vulnerability to environmental conditions such as drought and flood.

The survey consists of three main elements: a child questionnaire, a household questionnaire and a community questionnaire. The household data gathered is similar to other cross-sectional datasets (such as the World Bank's Living Standards Measurement Study). It covers a range of topics such as household composition, livelihood and assets, household expenditure, child health and access to basic services, and education. This is supplemented with additional questions that cover caregiver perceptions, attitudes, and aspirations for their child and the family. Young Lives also collects detailed time-use data for all family members, information about the child's weight and height (and that of caregivers), and tests the children for school outcomes (language comprehension and mathematics). An important element of the survey asks the children about their daily activities, their experiences and attitudes to work and school, their likes and dislikes, how they feel they are treated by other people, and their hopes and aspirations for the future. The community questionnaire provides background information about the social, economic and environmental context of each community. It covers topics such as ethnicity, religion, economic activity and employment, infrastructure and services, political representation and community networks, crime and environmental changes. The Young Lives survey is carried out by teams of local researchers, supported by the Principal Investigator and Data Manager in each country.

Further information about the survey, including publications, can be downloaded from the Young Lives website.

Geographic coverage

Ethiopia - National Coverage India - Andhra Pradesh only Peru - National Coverage Vietnam - National Coverage

Analysis unit

Individuals Families/households Data are also gathered at Community and Mini-Community level.

Universe

Cross-national; Subnational Children aged 12 years old, children aged 19 years old, and the households of both sets, in Ethiopia, India (Andhra Pradesh), Peru and Vietnam. These children were originally interviewed in Rounds 1-3 of the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Number of units: Ethiopia: 1,875 (12-year-olds), 908 (19-year-olds); India: 1,915 (12-year-olds), 952 (19-year-olds); Peru: 1,902 (12-year-olds), 635 (19-year-olds); Vietnam: 1,932 (12-year-olds), 887 (19-year-olds) More detailed information on survey design and sampling is available at http://www.younglives.org.uk/content/our-research-methods

Mode of data collection

Face-to-face interview; Self-completion

Research instrument

The Older Cohort Household Questionnaire (age 19) includes sections on: - Parental background; Household and child education - Livelihoods and asset framework - Household food and non-food consumption and expenditure - Social capital; Economic changes and recent life history - Socio-economic status

The Older Cohort Child Questionnaire (age 19) includes sections on: - Parents and Caregiver update; Mobility - Subjective well-being - Education - Employment, earnings, and time-use - Feelings and attitudes - Household decision-making - Marital and living arrangements - Fertility; Anthropometry - Health and nutrition

The Older Cohort Cognitive Tests (age 19) includes - Mathematics test - Reading comprehension test

The Older Cohort Self-Administered Questionnaire (age 19) includes sections on: - Relationship with parents - Smoking, Violence, Alcohol, Sexual behaviour (administered in Peru only)

The Younger Cohort Household Questionnaire (age 12) includes sections on:
- Parental background - Household and child education - Livelihoods and asset framework - Household food and non-food consumption and expenditure - Social capital - Economic changes and recent life history - Socio-economic status - Health - Anthropometry (for the study child and a sibling) - Caregiver perceptions and attitudes

The Younger Cohort Child Questionnaire (age 12) includes sections on: - Schooling - Time-us - Health - Social networks - Feelings and attitudes

The Younger Cohort Cognitive Tests (age 12) include: - Peabody Picture Vocabulary Test (administered to the study child and a sibling) - Mathematics test - Reading comprehension test. In Ethiopia and Peru only: a computerised cognitive skill (Executive Functioning) test administered on touch-screen tablet computers for the study child and a younger sibling. In Ethiopia only an additional English and Amharic reading test.

The Community Questionnaire (administered in the main communities where Young Lives children live) includes sections on: - General characteristics of the locality - Social environment - Access to services; Economy - Local prices - Social protection - Educational services - Health services; Migration

The Mini-community questionnaire (administered in communities into which one or study children moved) includes sections on: - General characteristics of the locality - Social environment - Access to Services - Economy - Local prices

The qualitative research was conducted in order to illuminate older people’s quality of life from the perspective of older people themselves. The aim was to paint a picture of the lives of older people and to gain insight into how older people in the region have been affected by the massive societal changes of the last 15 years and how they are coping with the impacts of these changes.

The project involves a mixed method design, combining quantitative analysis of the living standards of older people of recently available household survey data, with qualitative research providing deep insight into the reality of life for older people today. Obtaining greater insight into how the lives of older people have been affected by the socio-economic transformations of the last 15 years, and relative role of the state and family in both providing support to and benefiting from the contribution of, older people will aid the formulation of poverty alleviation programmes. Tajikistan, Kyrgyzstan and Moldova were chosen as countries for qualitative research as these three countries are the poorest of the former Soviet states. In each country, data collection sites were selected to represent different geographical and social conditions. Data collection commenced in each country with the capital city. Data were also collected in a smaller town and a rural location as it was seen as important to investigate any differences in older people’s experiences which might be related to the places in which they live. With consideration for the above criteria, sites were then selected according to safety and accessibility issues and the availability of local contacts.

This project examines the living conditions and sources of finance and social support (both state and family) amongst older people living in the seven poorest countries of the former Soviet Union. The break-up of the Soviet Union and the subsequent transition to market-led economies has been accompanied by a decade of economic and social upheaval on an unprecedented scale. Older people face particular challenges. Having lived their entire working lives under a paternal and relatively generous welfare system, they now find themselves in later life facing a new world – politically, economically, socially, psychologically and physically.

Carried out every four years, the European Quality of Life Survey (EQLS) examines both the objective circumstances of European citizens' lives and how they feel about those circumstances and their lives in general. It collects data on a range of issues, such as employment, income, education, housing, family, health and work-life balance. It also looks at subjective topics, such as people's levels of happiness, life satisfaction, and perceived quality of society. By running the survey regularly, it has also become possible to track key trends in the quality of people's lives over time. Previous surveys have shown, for instance, that people are having greater difficulty making ends meet since the economic crisis began. In many countries, they also feel that there is now more tension between people from different ethnic groups. And across Europe, people now trust their governments less than they did before. However, people still continue to get the greatest satisfaction from their family life and personal relationships.

Over the years, the EQLS has developed into a valuable set of indicators which complements traditional indicators of economic growth and living standard such as GDP or income. The EQLS indicators are more inclusive of environmental and social aspects of progress and therefore are easily integrated into the decision-making process and taken up by public debate at EU and national levels in the European Union.

In each wave a sample of adult population has been selected randomly for a face to face interview. In view of the prospective European enlargements the geographical coverage of the survey has expanded over time from 28 countries in 2003 to 34 countries in 2011-12.

Further information about the survey can be found on the European Foundation for the Improvement of Living and Working Conditions (Eurofound) EQLS web pages.

For the second edition (January 2014) the data file has been updated with a new total weighting variable. See documentation for further details and see also the updated version of the EQLS integrated file, held under SN 7348).

In the build up to the Second World War, the United States was the major power with the highest gross domestic product (GDP) per capita in the world. In 1938, the United States also had the highest overall GDP in the world, and by a significant margin, however differences in GDP per person were much smaller. Switzerland In terms of countries that played a notable economic role in the war, the neutral country of Switzerland had the highest GDP per capita in the world. A large part of this was due to the strength of Switzerland's financial system. Most major currencies abandoned the gold standard early in the Great Depression, however the Swiss Franc remained tied to it until late 1936. This meant that it was the most stable, freely convertible currency available as the world recovered from the Depression, and other major powers of the time sold large amounts of gold to Swiss banks in order to trade internationally. Switzerland was eventually surrounded on all sides by Axis territories and lived under the constant threat of invasion in the war's early years, however Swiss strategic military planning and economic leverage made an invasion potentially more expensive than it was worth. Switzerland maintained its neutrality throughout the war, trading with both sides, although its financial involvement in the Holocaust remains a point of controversy. Why look at GDP per capita? While overall GDP is a stronger indicator of a state's ability to fund its war effort, GDP per capita is more useful in giving context to a country's economic power in relation to its size and providing an insight into living standards and wealth distribution across societies. For example, Germany and the USSR had fairly similar GDPs in 1938, whereas Germany's per capita GDP was more than double that of the Soviet Union. Germany was much more industrialized and technologically advanced than the USSR, and its citizens generally had a greater quality of life. However these factors did not guarantee victory - the fact that the Soviet Union could better withstand the war of attrition and call upon its larger population to replenish its forces greatly contributed to its eventual victory over Germany in 1945.

This dataset contains detailed Global Multidimensional Poverty Index (MPI) data for 110 countries.The Global MPI reflects the combined simultaneous disadvantages poor people experience across different areas of their lives, including education, health and living standards. If people are deprived in at least one-third of ten weighted indicators, they are identified as multi-dimensionally poor. For further information on the MPI visit: http://www.ophi.org.uk/multidimensional-poverty-index/

The dataset includes main MPI results for each country, the proportion of people who are MPI poor and experience deprivations in each indicator of poverty, the percentage contribution of deprivations to the MPI for each country, and other measures of poverty and wellbeing at the national level. It is an appendix to OPHI's Methodological Note – Winter 2014/2015 (http://www.ophi.org.uk/multidimensional-poverty-index/mpi-2014-2015/mpi-methodology/)

Please cite the data as: Alkire, S., Conconi, A., Robles, G. and Seth, S. (2015). “Multidimensional Poverty Index, Winter 2014/2015: Brief Methodological Note and Results.” OPHI Briefing 27, University of Oxford, January.

The global Multidimensional Poverty Index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the acute deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. Critically, the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS), the Multi-Indicator Cluster Surveys (MICS) and in some cases, national surveys.

The subnational multidimensional poverty data from the data tables are published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. For the details of the global MPI methodology, please see the latest Methodological Notes found here.

The global Multidimensional Poverty Index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the acute deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. Critically, the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS), the Multi-Indicator Cluster Surveys (MICS) and in some cases, national surveys.

The subnational multidimensional poverty data from the data tables are published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. For the details of the global MPI methodology, please see the latest Methodological Notes found here.

Home Burglar Alarm System Market Outlook

The global Home Burglar Alarm System market size was valued at approximately USD 4.5 billion in 2023 and is projected to reach around USD 7.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5% over the forecast period. This growth can be attributed to the increasing need for home security solutions, driven by rising crime rates and the growing awareness among consumers about the importance of personal safety.

One of the primary growth factors for the market is the advancements in technology that have enabled more intelligent and connected home security systems. The integration of Internet of Things (IoT) technologies and smart home devices has made it possible to monitor and control alarm systems remotely through smartphones and other devices. This has considerably enhanced user convenience and the effectiveness of these systems, thereby driving their adoption. Additionally, the increasing penetration of high-speed internet and improved connectivity in both urban and rural areas has further accelerated the growth of smart home burglar alarm systems.

Another significant growth driver is the rising disposable income and improving living standards across various regions. As consumers become more financially capable, they are increasingly investing in advanced security systems to protect their homes and families. Moreover, the increasing trend of urbanization and the proliferation of smart city initiatives are boosting the demand for home burglar alarm systems. Governments and municipalities are also playing a crucial role by promoting the use of security systems through various awareness programs and incentives, further propelling the market growth.

Furthermore, the growing concerns about child safety and the need to monitor elderly family members have led to an increased adoption of home security systems equipped with advanced features like video surveillance and emergency alerts. The COVID-19 pandemic has also had a positive impact on the market, as the prolonged periods of lockdowns and increased home stay have heightened the focus on home security. As people spend more time at home, the need for robust security systems to protect against potential burglaries has become even more critical.

Regionally, North America dominates the home burglar alarm system market, driven by high consumer awareness, advanced technological infrastructure, and significant investments in home security solutions. Europe follows closely, with substantial demand stemming from countries like Germany, the UK, and France. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, owing to rapid urbanization, increasing disposable incomes, and growing adoption of smart home technologies in countries like China, India, and Japan. Meanwhile, Latin America and the Middle East & Africa are emerging markets with significant growth potential, driven by improving economic conditions and rising security concerns.

Component Analysis

The home burglar alarm system market can be segmented into hardware, software, and services. Each of these components plays a crucial role in the overall functionality and effectiveness of the system. The hardware segment includes various devices such as sensors, alarms, cameras, and control panels. These components are essential for detecting intrusions and alerting homeowners or security personnel. The continuous advancements in hardware technology, such as the development of more sensitive sensors and high-definition cameras, have significantly enhanced the reliability and performance of home burglar alarm systems.

Software is another critical component of the home burglar alarm system market. The software segment includes the applications and platforms that enable users to monitor and control their security systems remotely. These software solutions often come with features such as real-time alerts, video streaming, and integration with other smart home devices. The increasing demand for user-friendly and intuitive software interfaces has driven the development of more sophisticated and feature-rich applications. Moreover, the growing trend of cloud-based software solutions has made it easier for users to access and manage their security systems from anywhere in the world.

The services segment encompasses the various installation, maintenance, and monitoring services offered by security solution providers. Professional installation services ensure that the alarm systems are set up correctly and function optimally. Maintenan

The European residential construction market, valued at €1.08 billion in 2025, is projected to experience robust growth, driven by several key factors. A rising population, particularly in urban centers across major European economies like the UK, Germany, and France, fuels the demand for new housing. Furthermore, government initiatives aimed at stimulating affordable housing and addressing housing shortages, coupled with improving economic conditions in several regions, contribute to market expansion. The market is segmented by property type (single-family and multi-family) and construction type (new construction and renovation), with new construction currently dominating due to higher profitability and demand for modern housing amenities. Growth in the multi-family segment is expected to accelerate due to increasing urbanization and changing lifestyle preferences. While challenges remain, such as fluctuating material costs, skilled labor shortages, and stringent building regulations, these are likely to be mitigated by technological advancements in construction and sustainable building practices. Key players like Bellway plc, Skanska AB, and Persimmon plc are actively shaping the market landscape through strategic acquisitions, technological integration, and expansion into new regions. The projected CAGR of 5.67% suggests a consistently growing market over the forecast period (2025-2033), indicating significant investment opportunities. The renovation segment is expected to witness steady growth, driven by the increasing need to upgrade existing properties to meet modern standards of energy efficiency and sustainability. Government incentives and regulations promoting green building practices are further bolstering this segment. Competition within the market is intense, with established players focusing on innovation, diversification, and efficient project management to maintain their market share. The regional performance will vary depending on economic conditions and governmental policies within each nation. The UK, Germany, and France are anticipated to be the largest markets, driven by stronger economies and higher population density. However, other countries within the specified region (including Italy, Spain, Netherlands, Belgium, Sweden, Norway, Poland, and Denmark) will contribute significantly to the overall market growth, particularly as housing shortages are addressed through public and private sector investments. Recent developments include: April 2023: Apollo Global Management Inc. agreed to buy part of a portfolio of apartments from Vonovia SEfor €1 billion ($1.1 billion), with the largest German residential deal in months suggesting confidence is returning to the under-pressure sector. The private equity firm will acquire a minority stake in 21,000 homes in the German state of Baden-Wuerttemberg at a discount of about 5% to the portfolio’s year-end valuation., October 2023: The new housing association, Sovereign Network Group (SNG), announced its formation yesterday following a tie-up between 61,000-home Sovereign and Network Homes, which managed 21,000 properties. The new organisation will be a member of the G15 group of London’s largest landlords, and will manage more than 82,000 homes with 210,000 customers across London, Hertfordshire and the South of England.. Notable trends are: Increasing in Investments in Multifamily Residential Construction.

The statistic shows the total population in Canada from 2020 to 2024, with projections up until 2030. In 2024, the total population in Canada amounted to about 41.14 million inhabitants. Population of Canada Canada ranks second among the largest countries in the world in terms of area size, right behind Russia, despite having a relatively low total population. The reason for this is that most of Canada remains uninhabited due to inhospitable conditions. Approximately 90 percent of all Canadians live within about 160 km of the U.S. border because of better living conditions and larger cities. On a year to year basis, Canada’s total population has continued to increase, although not dramatically. Population growth as of 2012 has amounted to its highest values in the past decade, reaching a peak in 2009, but was unstable and constantly fluctuating. Simultaneously, Canada’s fertility rate dropped slightly between 2009 and 2011, after experiencing a decade high birth rate in 2008. Standard of living in Canada has remained stable and has kept the country as one of the top 20 countries with the highest Human Development Index rating. The Human Development Index (HDI) measures quality of life based on several indicators, such as life expectancy at birth, literacy rate, education levels and gross national income per capita. Canada has a relatively high life expectancy compared to many other international countries, earning a spot in the top 20 countries and beating out countries such as the United States and the UK. From an economic standpoint, Canada has been slowly recovering from the 2008 financial crisis. Unemployment has gradually decreased, after reaching a decade high in 2009. Additionally, GDP has dramatically increased since 2009 and is expected to continue to increase for the next several years.

The New Europe Barometer (NEB) series, originally known as the New Democracies Barometer (NDB), has been conducted annually across Central and Eastern Europe since autumn 1991. The same questions are asked in each country and repeated from year to year, so trends can be analysed across a wide variety of post-Communist societies. Approximately 1,000 respondents in each country are interviewed face-to-face each year about their economic, political and social attitudes and behaviour. Data are available for separate years and also as a trend dataset (SN 5241). Further information on the NEB is available on the CSPP Barometer Surveys web site, along with details of other survey series.
Since the collapse of the Berlin Wall in 1989, post-communist regimes have followed radically different paths: ten are now new member states of the European Union, while others remain partners in the post-Soviet Commonwealth of Independent States. This project draws on a unique database of more than 100 New Europe Barometer (NEB) surveys undertaken in post-communist countries since 1991. Funding from the Economic and Social Research Council (ESRC) supported a fresh multinational survey in autumn/winter 2004-5 in Belarus, Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Russia, Slovakia, Slovenia and Ukraine.

The seventh NEB survey (2004-2005) focuses on topics such as whether respondents evaluate their new regime and compare it to the past, and how committed are they to the rejection of undemocratic alternatives; what accounts for differences in evaluations of post-communist regimes; and how important the costs of economic transformation and/or the opportunities of movement to the market have been.

The NEB surveys are comparative; the same questions are asked in all countries covered. For 2004, the results were merged into a single multinational data file, with each country's responses weighted equally at 1,000. The multinational data file encourages research that considers the extent to which causes of division within society, for example education, age or economic status, operate transnationally. It is possible to assess to what extent and under what circumstances national context is an important influence on behaviour and attitudes (net of individual attributes), and to test the importance of absolute standards of living, which are measured cross-nationally by a household's material possessions, as against relative income advantage or disadvantage.

In addition to this, separate data files for all 13 countries are included in the dataset. The majority of questions asked in the 2004-2005 survey had been asked in previous surveys.

The responses from Estonia, Latvia and Lithuania are comparable with the New Baltic Barometer survey series (available from the UK Data Archive under GN 33416).

In 2024 there were approximately 41 million households in Germany, 32 million households in France, and 26.3 million households in Italy, with these three countries having the highest number of households among EU countries.

The Life Opportunities Survey (LOS) was a large scale longitudinal survey of disability in Great Britain, which ran from 2009-2014. It was the first major ONS social survey to explore disability in terms of the social barriers to participation that people experience. The survey compared the experiences of disabled people with those of non-disabled people. Prior to the LOS, various surveys of disability had been carried out. The LOS aimed to meet the following long term information needs on experiences of disabled people living in Great Britain:

• dynamics of disability over time, including the factors associated with transitions and onsets of impairment
• social participation by disabled people
• up-to-date prevalence rates of impairments

The LOS was set up to track the experiences of disabled people over time to assess transitions through key life stages, such as moving from childhood to adulthood or in and out of work. The longitudinal design enabled three distinct groups to be followed over time:

• a disabled group
• a comparison group of non-disabled people
• a larger non-disabled group, monitored for the onset of impairment over time

Respondents were interviewed every 12 months, whether they were resident in the original household or had since moved. Following the baseline survey only the first two groups were interviewed face-to-face. The third group were monitored over time via a shorter telephone interview to check for the onset of an impairment. If any member of the household had experienced the onset of impairment, they were invited to take part in a face to face interview. Further information about the LOS series is available from the ONS Life Opportunities Survey webpage.

End User Licence and Special Licence LOS data:
Users should note that there are two versions of each LOS study. One is available under the standard End User Licence (EUL) agreement, and the other is a Special Licence (SL) version. The SL version contains geographic variables (Country, Government Office Region and Local Authority), deciles, age bands, a rural/urban indicator, and more information on household relationships, country of previous residence, medical conditions and occupations.

The EUL version contains less detailed variables. For example, there is no spatial unit and age is top-coded at 80. Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

The SL data have more restrictive access conditions than those made available under the standard EUL. Prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. Therefore, users are strongly advised to order the standard version of the data. In order to help users choose the correct dataset, 'Special Licence Access' has been added to the dataset titles for the SL versions of the data.
The Special Licence version of the Life Opportunities Survey is held under SN 6654.

For the fifth edition (March 2016), data and documentation from Wave 3 (the final wave) of the survey were added to the study.

In 1821, the population of the island of Ireland was just over 6.8 million people. During this time, the entire island was a part of the United Kingdom of Great Britain and Ireland, after both islands were united by the Act of Union in 1800. The population enjoyed steady growth between 1821 and 1841, and it rose by almost 1.4 million people in this time, however the Great Famine, which lasted from 1845 to 1849, had a devastating impact on the population, causing it to drop from 8.18 million in 1841 to 6.55 million in 1851. If applying modern-day borders, the population of Northern Ireland was not growing as fast as the population of the Republic of Ireland before 1841, however it was not as severely affected by the famine, which was hardest felt in the east and south. The Great Hunger The famine was caused by a Europe-wide potato blight that contributed to mass starvation and death throughout the continent, although it's impact on Ireland was much harsher than anywhere else. The potato blight affected Ireland so severely as the majority of potatoes in Ireland were of a single variety which allowed the disease to spread much faster than in other countries. As the potato blight spread, the population became increasingly dependent on dairy and grain products, however a lot of these resources were relocated by the British military to combat food shortages in Britain. Due to disproportional dependency on potatoes, and mismanagement by the British government, over one million people died and a further one million emigrated. The Great Famine lasted from just 1845 to 1849, but it's legacy caused almost a century of population decline, and to this day, the overall population of Ireland has never exceeded it's pre-famine levels. Decline continues through partition The population decline continued well into the twentieth century, during which time the Republic of Ireland achieved independence from the British Empire. After centuries of fighting and rebellion against British rule, Irish nationalists finally gained independence from Britain in 1921, although the six counties with the largest Protestant populations formed Northern Ireland, which is still a part of the United Kingdom today. Although there was much conflict in Ireland in the twentieth century which claimed the lives of thousands of people (particularly during the Northern Irish Troubles), and despite Ireland's high emigration rate, the overall population began growing again in the second half of the 1900s. Recovery The population of the Republic of Ireland was at it's lowest in 1961, with 2.8 million people, which is almost four million fewer people than before the famine. Since then it has grown consistently, reaching 4.6 million in 2011 and expected to reach 5 million people by 2020. In Northern Ireland, the population began growing again from the beginning of the 1900s, but growth has been very slow. The only time it fell was in the 1970s, at the peak of The Troubles, where high unemployment and violence contributed to a lower birth rate and an increase in emigration. From the 1980s onwards, living standards improved and the population began growing again, reaching 1.8 million people in 2011.