Among the OECD countries, Costa Rica had the highest share of children living in poverty, reaching 28.5 percent in 2022. Türkiye followed with a share of 22 percent of children living in poverty, while 20.5 percent of children in Spain, Chile, and the United States did the same. On the other hand, only three percent of children in Finland were living in poverty.

Graph and download economic data for Estimate of People of All Ages in Poverty in United States (PEAAUS00000A647NCEN) from 1989 to 2023 about child, poverty, persons, and USA.

Out of all OECD countries, Cost Rica had the highest poverty rate as of 2022, at over 20 percent. The country with the second highest poverty rate was the United States, with 18 percent. On the other end of the scale, Czechia had the lowest poverty rate at 6.4 percent, followed by Denmark.

The significance of the OECD

The OECD, or the Organisation for Economic Co-operation and Development, was founded in 1948 and is made up of 38 member countries. It seeks to improve the economic and social well-being of countries and their populations. The OECD looks at issues that impact people’s everyday lives and proposes policies that can help to improve the quality of life.

Poverty in the United States

In 2022, there were nearly 38 million people living below the poverty line in the U.S.. About one fourth of the Native American population lived in poverty in 2022, the most out of any ethnicity. In addition, the rate was higher among young women than young men. It is clear that poverty in the United States is a complex, multi-faceted issue that affects millions of people and is even more complex to solve.

In 2023, the child poverty rate in Israel was 27.9 percent. This marked a decrease from the two previous years, when the rate was 28.1 percent. After peaking at 30.5 percent in 2014, the child poverty rate rapidly declined. The overall poverty rate in the country was lower than the rate among children.

In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.

Will all children be able to read by 2030? The ability to read with comprehension is a foundational skill that every education system around the world strives to impart by late in primary school—generally by age 10. Moreover, attaining the ambitious Sustainable Development Goals (SDGs) in education requires first achieving this basic building block, and so does improving countries’ Human Capital Index scores. Yet past evidence from many low- and middle-income countries has shown that many children are not learning to read with comprehension in primary school. To understand the global picture better, we have worked with the UNESCO Institute for Statistics (UIS) to assemble a new dataset with the most comprehensive measures of this foundational skill yet developed, by linking together data from credible cross-national and national assessments of reading. This dataset covers 115 countries, accounting for 81% of children worldwide and 79% of children in low- and middle-income countries. The new data allow us to estimate the reading proficiency of late-primary-age children, and we also provide what are among the first estimates (and the most comprehensive, for low- and middle-income countries) of the historical rate of progress in improving reading proficiency globally (for the 2000-17 period). The results show that 53% of all children in low- and middle-income countries cannot read age-appropriate material by age 10, and that at current rates of improvement, this “learning poverty” rate will have fallen only to 43% by 2030. Indeed, we find that the goal of all children reading by 2030 will be attainable only with historically unprecedented progress. The high rate of “learning poverty” and slow progress in low- and middle-income countries is an early warning that all the ambitious SDG targets in education (and likely of social progress) are at risk. Based on this evidence, we suggest a new medium-term target to guide the World Bank’s work in low- and middle- income countries: cut learning poverty by at least half by 2030. This target, together with improved measurement of learning, can be as an evidence-based tool to accelerate progress to get all children reading by age 10.

For further details, please refer to https://thedocs.worldbank.org/en/doc/e52f55322528903b27f1b7e61238e416-0200022022/original/Learning-poverty-report-2022-06-21-final-V7-0-conferenceEdition.pdf

At-risk-of poverty rate for children by country of birth of their parents (population aged 0 to 17 years)

Abstract

Young Lives: An International Study of Childhood Poverty is a collaborative project investigating the changing nature of childhood poverty in selected developing countries. The UK’s Department for International Development (DFID) is funding the first three-year phase of the project.

Young Lives involves collaboration between Non Governmental Organisations (NGOs) and the academic sector. In the UK, the project is being run by Save the Children-UK together with an academic consortium that comprises the University of Reading, London School of Hygiene and Tropical Medicine, South Bank University, the Institute of Development Studies at Sussex University and the South African Medical Research Council.

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.

Objectives of the study The Young Lives study has three broad objectives: • producing good quality panel data about the changing nature of the lives of children in poverty. • trace linkages between key policy changes and child poverty • informing and responding to the needs of policy makers, planners and other stakeholders There will also be a strong education and media element, both in the countries where the project takes place, and in the UK.

The study takes a broad approach to child poverty, exploring not only household economic indicators such as assets and wealth, but also child centred poverty measures such as the child’s physical and mental health, growth, development and education. These child centred measures are age specific so the information collected by the study will change as the children get older.

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

Geographic coverage

Young Lives is an international study of childhood poverty, involving 12,000 children in 4 countries. - Ethiopia (20 communities in Addis Ababa, Amhara, Oromia, and Southern National, Nationalities and People's Regions) - India (20 sites across Andhra Pradesh and Telangana) - Peru (74 communities across Peru) - Vietnam (20 communities in the communes of Lao Cai in the north-west, Hung Yen province in the Red River Delta, the city of Danang on the coast, Phu Yen province from the South Central Coast and Ben Tre province on the Mekong River Delta)

Analysis unit

Individuals; Families/households

Universe

Location of Units of Observation: Cross-national; Subnational Population: Children aged approximately 1 year old and their households, and children aged 8 years old and their households, in Ethiopia, India (Andhra Pradesh), Peru and Vietnam, in 2002. See documentation for details of the exact regions covered in each country.

Kind of data

Sample survey data [ssd]

Sampling procedure

Purposive selection/case studies

A key need for the study's objectives was to obtain data at different levels - the children, their households, the community in which they resided, as well as at regional and national levels. This need thus determined that children should be selected in geographic clusters rather than randomly selected across the country. There was, however, a much more important reason for recruiting children in clusters - the sites are also intended to provide suitable settings for a range of complementary thematic studies. For example, one or a few sites may be used for a qualitative study designed to achieve a deeper level of understanding of some social issues, either because they are important in that particular place, or because the sites are appropriate locales to investigate a more general concern. The quantitative panel study is seen as the foundation upon which a coherent and interesting range of linked studies can be set up.

Thus the design was decided, in each country, comprising 20 geographic clusters with 100 children sampled in each cluster.

For details on sample design, see the methodological document which is available in the documentation.

Sampling deviation

Ethiopia: 1,999 (1-year-olds), 1,000 (8-year-olds); India: 2,011 (1-year-olds), 1,008 (8-year-olds); Peru: 2,052 (1-year-olds), 714 (8-year-olds); Vietnam: 2,000 (1-year-olds), 1,000 (8-year-olds).

Mode of data collection

Face-to-face interview

Research instrument

Every questionnaire used in the study consists of a 'core' element and a country-specific element, which focuses on issues important for that country.

The core element of the questionnaires consists of the following sections: Core 6-17.9 month old household questionnaire • Section 1: Locating information • Section 2: Household composition • Section 3: Pregnancy, delivery and breastfeeding • Section 4: Child care • Section 5: Child health • Section 6: Caregiver background • Section 7: Livelihoods and time allocation • Section 8: Economic changes • Section 9: Socio-economic status • Section 10: Caregiver psychosocial well-being • Section 11: Social capital • Section 12: Tracking details • Section 13: Anthropometry

Core 7.5-8.5 year old household questionnaire • Section 1: Locating information • Section 2: Household composition • Section 3: Births and deaths • Section 4: Child school • Section 5: Child health • Section 6: Caregiver background • Section 7: Livelihoods and time allocation • Section 8: Economic changes • Section 9: Socio-economic status • Section 10: Child mental health • Section 11: Social capital • Section 12: Tracking details • Section 13: Anthropometry

The communnity questionnaire consists of the following sections: • Section 1: Physical environment • Section 2: Social environment • Section 3: Infrastructure and access • Section 4: Economy • Section 5: Health and education

Abstract

Young Lives: An International Study of Childhood Poverty is a collaborative project investigating the changing nature of childhood poverty in selected developing countries. The UK’s Department for International Development (DFID) is funding the first three-year phase of the project.

Young Lives involves collaboration between Non Governmental Organisations (NGOs) and the academic sector. In the UK, the project is being run by Save the Children-UK together with an academic consortium that comprises the University of Reading, London School of Hygiene and Tropical Medicine, South Bank University, the Institute of Development Studies at Sussex University and the South African Medical Research Council.

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.

Objectives of the study The Young Lives study has three broad objectives: • producing good quality panel data about the changing nature of the lives of children in poverty. • trace linkages between key policy changes and child poverty • informing and responding to the needs of policy makers, planners and other stakeholders There will also be a strong education and media element, both in the countries where the project takes place, and in the UK.

The study takes a broad approach to child poverty, exploring not only household economic indicators such as assets and wealth, but also child centred poverty measures such as the child’s physical and mental health, growth, development and education. These child centred measures are age specific so the information collected by the study will change as the children get older.

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

Constructed Files: The Rounds 1-3 Constructed Files, 2002-2009 are combined sub-sets of selected variables from Round 1, 2 and 3 of the Young Lives survey. One main constructed data file is available for each of the four countries. These are presented in a panel format and contain approximately 200 original and constructed variables, with the majority comparable across all three rounds.

Geographic coverage

Young Lives is an international study of childhood poverty, involving 12,000 children in 4 countries. - Ethiopia (20 communities in Addis Ababa, Amhara, Oromia, and Southern National, Nationalities and People's Regions) - India (20 sites across Andhra Pradesh and Telangana) - Peru (74 communities across Peru) - Vietnam (20 communities in the communes of Lao Cai in the north-west, Hung Yen province in the Red River Delta, the city of Danang on the coast, Phu Yen province from the South Central Coast and Ben Tre province on the Mekong River Delta)

Analysis unit

Individuals; Families/households

Universe

Location of Units of Observation: Cross-national; Subnational Population: Young Lives children and their households, in Ethiopia, India (Andhra Pradesh), Peru and Vietnam, in 2002-2009.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Procedures: Purposive selection/case studies Number of Units: Ethiopia: 8,997 children; India: 9,057 children; Peru: 8,298 children; Vietnam: 9,000 children

Mode of data collection

Face-to-face interview

Cleaning operations

The constructed files are combined sub-sets of selected variables from Round 1, 2 and 3 of the Young Lives survey. The files contain about 200 original and constructed variables, most of them comparable across the three rounds, presented in a panel format and classified in four broad groups: panel information, general characteristics, household characteristics, and child characteristics.

Abstract copyright UK Data Service and data collection copyright owner.

The Young Lives survey is an innovative long-term project investigating the changing nature of childhood poverty in four developing countries. The study is being conducted in Ethiopia, India, Peru and Vietnam and has tracked the lives of 12,000 children over a 20-year period, through 5 (in-person) survey rounds (Round 1-5) and, with the latest survey round (Round 6) conducted over the phone in 2020 and 2021 as part of the Listening to Young Lives at Work: COVID-19 Phone Survey.
Round 1 of Young Lives surveyed two groups of children in each country, at 1 year old and 5 years old. Round 2 returned to the same children who were then aged 5 and 12 years old. Round 3 surveyed the same children again at aged 7-8 years and 14-15 years, Round 4 surveyed them at 12 and 19 years old, and Round 5 surveyed them at 15 and 22 years old. Thus the younger children are being tracked from infancy to their mid-teens and the older children through into adulthood, when some will become parents themselves.

The 2020 phone survey consists of three phone calls (Call 1 administered in June-July 2020; Call 2 in August-October 2020 and Call 3 in November-December 2020) and the 2021 phone survey consists of two additional phone calls (Call 4 in August 2021 and Call 5 in October-December 2021) The calls took place with each Young Lives respondent, across both the younger and older cohort, and in all four study countries (reaching an estimated total of around 11,000 young people).
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.

This study includes data and documentation for Round 3 only. Round 1 is available under SN 5307, Round 2 under SN 6852, Round 4 under SN 7931 and Round 5 under SN 8357.

Latest edition:
For the fourth edition (August 2022), the Peruvian household level data files (pe_oc_householdlevel and pe_yc_householdlevel) have been updated to include the mother's health variables.

Main Topics:

This dataset comprises the data from the 8-year-olds' and 15-year-olds' household surveys and child questionnaires carried out in 2009. For each of the four countries the dataset contains files at the community, household and child level for both ages. In addition there are several files at lower levels (i.e. where there are several records per household). These include the household roster and activity schedules for livelihoods, etc. The Peru community level data includes an additional file with community data covering new communities for children who have migrated.

Topics covered in the dataset include: community characteristics (environmental, social and economic); 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; child care, education and activities; child health; anthropometry; caregivers perceptions and attitudes; school and activities, child time use; social networks, social skills and social support; feelings and attitudes; parents and household issues; child development; perception of the future, environment and household wealth.

Also included are calculated indices such as a wealth index, various social capital scores, and mental health scores, which are all detailed in the documentation. The SPSS syntax code and/or Stata 'do' files that show methods of calculation for the composite indices are also included in the dataset.

BackgroundEducation and health are both constituents of human capital that enable people to earn higher wages and enhance people’s capabilities. Human capabilities may lead to fulfilling lives by enabling people to achieve a valuable combination of human functionings—i.e., what people are able to do or be as a result of their capabilities. A better understanding of how these different human capabilities are produced together could point to opportunities to help jointly reduce the wide disparities in health and education across populations.Methods and findingsWe use nationally and regionally representative individual-level data from Demographic and Health Surveys (DHS) for 55 low- and middle-income countries (LMICs) to examine patterns in human capabilities at the national and regional levels, between 2000 and 2017 (N = 1,657,194 children under age 5). We graphically analyze human capabilities, separately for each country, and propose a novel child-based Human Development Index (HDI) based on under-five survival, maternal educational attainment, and measures of a child’s household wealth. We normalize the range of each component using data on the minimum and maximum values across countries (for national comparisons) or first-level administrative units within countries (for subnational comparisons). The scores that can be generated by the child-based HDI range from 0 to 1.We find considerable heterogeneity in child health across countries as well as within countries. At the national level, the child-based HDI ranged from 0.140 in Niger (with mean across first-level administrative units = 0.277 and standard deviation [SD] 0.114) to 0.755 in Albania (with mean across first-level administrative units = 0.603 and SD 0.089). There are improvements over time overall between the 2000s and 2010s, although this is not the case for all countries included in our study. In Cambodia, Malawi, and Nigeria, for instance, under-five survival improved over time at most levels of maternal education and wealth. In contrast, in the Philippines, we found relatively few changes in under-five survival across the development spectrum and over time. In these countries, the persistent location of geographical areas of poor child health across both the development spectrum and time may indicate within-country poverty traps.Limitations of our study include its descriptive nature, lack of information beyond first- and second-level administrative units, and limited generalizability beyond the countries analyzed.ConclusionsThis study maps patterns and trends in human capabilities and is among the first, to our knowledge, to introduce a child-based HDI at the national and subnational level. Areas of chronic deprivation may indicate within-country poverty traps and require alternative policy approaches to improving child health in low-resource settings.

Abstract

Young Lives: An International Study of Childhood Poverty is a collaborative project investigating the changing nature of childhood poverty in selected developing countries. The UK’s Department for International Development (DFID) is funding the first three-year phase of the project.

Young Lives involves collaboration between Non Governmental Organisations (NGOs) and the academic sector. In the UK, the project is being run by Save the Children-UK together with an academic consortium that comprises the University of Reading, London School of Hygiene and Tropical Medicine, South Bank University, the Institute of Development Studies at Sussex University and the South African Medical Research Council.

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.

Objectives of the study The Young Lives study has three broad objectives: • producing good quality panel data about the changing nature of the lives of children in poverty. • trace linkages between key policy changes and child poverty • informing and responding to the needs of policy makers, planners and other stakeholders There will also be a strong education and media element, both in the countries where the project takes place, and in the UK.

The study takes a broad approach to child poverty, exploring not only household economic indicators such as assets and wealth, but also child centred poverty measures such as the child’s physical and mental health, growth, development and education. These child centred measures are age specific so the information collected by the study will change as the children get older.

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

Geographic coverage

Young Lives is an international study of childhood poverty, involving 12,000 children in 4 countries. - Ethiopia (20 communities in Addis Ababa, Amhara, Oromia, and Southern National, Nationalities and People's Regions) - India (20 sites across Andhra Pradesh and Telangana) - Peru (74 communities across Peru) - Vietnam (20 communities in the communes of Lao Cai in the north-west, Hung Yen province in the Red River Delta, the city of Danang on the coast, Phu Yen province from the South Central Coast and Ben Tre province on the Mekong River Delta)

Analysis unit

Individuals; Families/households

Universe

Cross-national; Subnational

Children aged approximately 5 years old and their households, and children aged 12 years old and their households, in Ethiopia, India (Andhra Pradesh), Peru and Vietnam, in 2006-2007. These children were originally interviewed in Round 1 of the study. See documentation for details of the exact regions covered in each country.

Kind of data

Sample survey data [ssd]

Sampling procedure

Purposive selection/case studies

Sampling deviation

Ethiopia: 1,886 (8-year-olds), 974 (15-year-olds); India: 1,930 (8-year-olds), 977 (15-year-olds); Peru: 1,946 (8-year-olds), 678 (15-year-olds); Vietnam: 1,963 (8-year-olds), 972 (15-year-olds)

Mode of data collection

Face-to-face interview; Self-completion

Research instrument

Every questionnaire used in the study consists of a 'core' element and a country-specific element, which focuses on issues important for that country.

The core element of the questionnaires consists of the following sections: Core 5 & 12 year old household questionnaire • Section 1: Parental background • Section 2: Household education • Section 3: Livelihoods and asset framework • Section 3a: Land & crops • Section 3b: Time allocation • Section 3c: Productive assets • Section 3d: Non-agricultural earnings • Section 3e: Transfers • Section 4: Consumption/Expenditure • Section 4a: Food consumption/expenditure • Section 4b: Non-food consumption/expenditure • Section 5: Social capital • Section 5a: Support networks • Section 5b: Family, group and political capital • Section 5c: Collective action and exclusion • Section 5d: Information networks • Section 6: Economic changes and recent life history • Section 7: Socio-economic status • Section 8: Child care, education & activities (blank in 12yr old household) • Section 9: Child health • Section 10: Child development (blank in 12yr old household) • Section 11: Anthropometry • Section 12: Caregiver perceptions & attitudes

Core 12 year old child questionnaire • Section 1: School and activities • Section 2: Child health • Section 3: Social networks, social skills and social support • Section 4: Feelings and attitudes • Section 5: Parents and household issues • Section 6: Perceptions of household wealth and future • Section 7: Child Development

The community questionnaire used in Ethiopia consists of the following sections: - MODULE 1 General Module • Section 1 General Community Characteristics • Section 2 Social Environment • Section 3 Access to Services • Section 4 Economy • Section 5 Local Prices - MODULE 2 Child-Specific Modules • Section 1 Educational Service (General) • Section 2 NOT INCLUDED IN ETHIOPIA CONTEXT INSTRUMENT • Section 3 Educational Services (Preschool, Primary, Secondary) • Section 4 Health Services • Section 5 Child Protection Services - MODULE 3 Country specific community level questions • Section 1 Conversion factors • Section 2 Migration • Section 3 Social protection program • Section 4 Equity and budget management in education and health

The community questionnaire used in India consists of the following sections: - MODULE 1 General Module • Section 1: General Community Characteristics • Section 2: Social Environment • Section 3: Access to Services • Section 4: Economy • Section 5; Local Prices - MODULE 2 Child-Specific Modules • Section 1: Educational Services (General) • Section 2: Child day care Services • Section 3: Educational Services (Preschool, Primary, Secondary) • Section 4: Health Services • Section 5: Child Protection Services

The community questionnaire used in Peru consists of the following sections: - MODULE 1 General Module • Section 1: General Community Characteristics • Section 2: Social Environment • Section 3: Access to Services • Section 4: Economy • Section 5: Local Prices - MODULE 2 Child-Specific Modules • Section 1: Educational Services (General) • Section 2: Child day care Services • Section 3: Educational Services (Preschool, Primary, Secondary) • Section 4: Health Services • Section 5: Child Protection Services

The community questionnaire used in Vietnam consists of the following sections: - MODULE 1 General Module • Section 1: General Community Characteristics • Section 2: Social Environment • Section 3: Access to Services • Section 4: Economy • Section 5: Local Prices • Section 6: Poverty Alleviation and Infrastructure Initiatives - MODULE 2 Child-Specific Module • Section 1: Educational Services (General and Country Specific) • Section 2: Child day care Services • Section 3: Educational Services (Preschool, Primary, Secondary) • Section 4: Health Services • Section 5: Child Protection Services

Goal 1End poverty in all its forms everywhereTarget 1.1: By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a dayIndicator 1.1.1: Proportion of the population living below the international poverty line by sex, age, employment status and geographic location (urban/rural)SI_POV_DAY1: Proportion of population below international poverty line (%)SI_POV_EMP1: Employed population below international poverty line, by sex and age (%)Target 1.2: By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitionsIndicator 1.2.1: Proportion of population living below the national poverty line, by sex and ageSI_POV_NAHC: Proportion of population living below the national poverty line (%)Indicator 1.2.2: Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitionsSD_MDP_MUHC: Proportion of population living in multidimensional poverty (%)SD_MDP_ANDI: Average proportion of deprivations for people multidimensionally poor (%)SD_MDP_MUHHC: Proportion of households living in multidimensional poverty (%)SD_MDP_CSMP: Proportion of children living in child-specific multidimensional poverty (%)Target 1.3: Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerableIndicator 1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns, work-injury victims and the poor and the vulnerableSI_COV_MATNL: [ILO] Proportion of mothers with newborns receiving maternity cash benefit (%)SI_COV_POOR: [ILO] Proportion of poor population receiving social assistance cash benefit, by sex (%)SI_COV_SOCAST: [World Bank] Proportion of population covered by social assistance programs (%)SI_COV_SOCINS: [World Bank] Proportion of population covered by social insurance programs (%)SI_COV_CHLD: [ILO] Proportion of children/households receiving child/family cash benefit, by sex (%)SI_COV_UEMP: [ILO] Proportion of unemployed persons receiving unemployment cash benefit, by sex (%)SI_COV_VULN: [ILO] Proportion of vulnerable population receiving social assistance cash benefit, by sex (%)SI_COV_WKINJRY: [ILO] Proportion of employed population covered in the event of work injury, by sex (%)SI_COV_BENFTS: [ILO] Proportion of population covered by at least one social protection benefit, by sex (%)SI_COV_DISAB: [ILO] Proportion of population with severe disabilities receiving disability cash benefit, by sex (%)SI_COV_LMKT: [World Bank] Proportion of population covered by labour market programs (%)SI_COV_PENSN: [ILO] Proportion of population above statutory pensionable age receiving a pension, by sex (%)Target 1.4: By 2030, ensure that all men and women, in particular the poor and the vulnerable, have equal rights to economic resources, as well as access to basic services, ownership and control over land and other forms of property, inheritance, natural resources, appropriate new technology and financial services, including microfinanceIndicator 1.4.1: Proportion of population living in households with access to basic servicesSP_ACS_BSRVH2O: Proportion of population using basic drinking water services, by location (%)SP_ACS_BSRVSAN: Proportion of population using basic sanitation services, by location (%)Indicator 1.4.2: Proportion of total adult population with secure tenure rights to land, (a) with legally recognized documentation, and (b) who perceive their rights to land as secure, by sex and type of tenureSP_LGL_LNDDOC: Proportion of people with legally recognized documentation of their rights to land out of total adult population, by sex (%)SP_LGL_LNDSEC: Proportion of people who perceive their rights to land as secure out of total adult population, by sex (%)SP_LGL_LNDSTR: Proportion of people with secure tenure rights to land out of total adult population, by sex (%)Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disastersIndicator 1.5.1: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 populationVC_DSR_MISS: Number of missing persons due to disaster (number)VC_DSR_AFFCT: Number of people affected by disaster (number)VC_DSR_MORT: Number of deaths due to disaster (number)VC_DSR_MTMP: Number of deaths and missing persons attributed to disasters per 100,000 population (number)VC_DSR_MMHN: Number of deaths and missing persons attributed to disasters (number)VC_DSR_DAFF: Number of directly affected persons attributed to disasters per 100,000 population (number)VC_DSR_IJILN: Number of injured or ill people attributed to disasters (number)VC_DSR_PDAN: Number of people whose damaged dwellings were attributed to disasters (number)VC_DSR_PDYN: Number of people whose destroyed dwellings were attributed to disasters (number)VC_DSR_PDLN: Number of people whose livelihoods were disrupted or destroyed, attributed to disasters (number)Indicator 1.5.2: Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)VC_DSR_GDPLS: Direct economic loss attributed to disasters (current United States dollars)VC_DSR_LSGP: Direct economic loss attributed to disasters relative to GDP (%)VC_DSR_AGLH: Direct agriculture loss attributed to disasters (current United States dollars)VC_DSR_HOLH: Direct economic loss in the housing sector attributed to disasters (current United States dollars)VC_DSR_CILN: Direct economic loss resulting from damaged or destroyed critical infrastructure attributed to disasters (current United States dollars)VC_DSR_CHLN: Direct economic loss to cultural heritage damaged or destroyed attributed to disasters (millions of current United States dollars)VC_DSR_DDPA: Direct economic loss to other damaged or destroyed productive assets attributed to disasters (current United States dollars)Indicator 1.5.3: Number of countries that adopt and implement national disaster risk reduction strategies in line with the Sendai Framework for Disaster Risk Reduction 2015–2030SG_DSR_LGRGSR: Score of adoption and implementation of national DRR strategies in line with the Sendai FrameworkSG_DSR_SFDRR: Number of countries that reported having a National DRR Strategy which is aligned to the Sendai FrameworkIndicator 1.5.4: Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national disaster risk reduction strategiesSG_DSR_SILS: Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national disaster risk reduction strategies (%)SG_DSR_SILN: Number of local governments that adopt and implement local DRR strategies in line with national strategies (number)SG_GOV_LOGV: Number of local governments (number)Target 1.a: Ensure significant mobilization of resources from a variety of sources, including through enhanced development cooperation, in order to provide adequate and predictable means for developing countries, in particular least developed countries, to implement programmes and policies to end poverty in all its dimensionsIndicator 1.a.1: Total official development assistance grants from all donors that focus on poverty reduction as a share of the recipient country’s gross national incomeDC_ODA_POVLG: Official development assistance grants for poverty reduction, by recipient countries (percentage of GNI)DC_ODA_POVDLG: Official development assistance grants for poverty reduction, by donor countries (percentage of GNI)DC_ODA_POVG: Official development assistance grants for poverty reduction (percentage of GNI)Indicator 1.a.2: Proportion of total government spending on essential services (education, health and social protection)SD_XPD_ESED: Proportion of total government spending on essential services, education (%)Target 1.b: Create sound policy frameworks at the national, regional and international levels, based on pro-poor and gender-sensitive development strategies, to support accelerated investment in poverty eradication actionsIndicator 1.b.1: Pro-poor public social spending

Countries ranked by child-based capability index.

In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

5 to 17 years Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Country Club, Florida by age, education, race, gender, work experience and more.

Users can obtain demographic, maternal and child health, and development information regarding countries with whom UNICEF works. BackgroundUNICEF (United Nations Children Fund) is a non-governmental agency that works with governments, national and international agencies and communities to reduce the cycle of poverty in more than 150 countries and territories. UNICEF’s programs address child health and nutrition, safe water and sanitation, gender-equitable quality basic education, and the protection of children from violence, exploitation and AIDS. Topics include: country demographics, basic health, HIV/AIDS , education, and economics, among others. User Functionality Users can obtain information regarding countries with whom UNICEF works. UNICEF provides a background of each country; indicators such as country demographics, basic health, HIV/AIDS, nutrition, education, economics, child protection, women’s health and status, and rate of progress; information regarding UNICEF initiatives in the country; and news regarding current events relevant to the well-being of its residents, the impact of UNICEF and similar programs, as well as the impact of epidemics, natural disaster and political conflicts on children. Users can obtain country summaries and health indicators for each country. Maps can be downloaded as PDF files. Data Notes Data are derived from multiple sources including: UNICEF, the United Nations Population Division, United Nations Statistics Division, Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Educational, Scientific and Cultural Organization (UNESCO), UNESCO Institute of Statistics (including Demographic Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), Education for All 2000 Assessment), World Health Organization (WHO), Report on the Global HIV/ AIDS Epidemic, US Census Bureau, HIV/AIDS Surveillance Database, Behavioral Surveillance Surveys (BSS), Reproductive Health Surveys (RHS), International Telecommunications Union, Yearbook of Statistics, Children on the Brink, World Bank, International Monetary Fund (IMF), Organization for Economic Co-operation and Development (OECD) and national household surveys and routine reporting systems. Years to which the data apply is noted with the relevant indicator. Data updates vary according to indicator, and can be found under the “Definitions and Data Source” tab. Information is available on the country level.

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 objectives of the study are to provide good quality long-term data about the lives of children living in poverty, trace linkages between key policy changes and child welfare, and inform and respond to the needs of policymakers, planners and other stakeholders. Research activities of the project include the collection of data on a set of child welfare outcomes and their determinants and the monitoring of changes in policy, in order to explore the links between the policy environment and outcomes for children. 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 Young Lives study aims to track the lives of 12,000 children over a 15-year period. This is the time-frame set by the UN to assess progress towards the Millennium Development Goals. Round 1 of the study followed 2,000 children (aged between 6 and 18 months in 2002) and their households, from both urban and rural communities, in each of the four countries (8,000 children in total). Data were also collected on an older cohort of 1,000 children aged 7 to 8 years in each country, in order to provide a basis for comparison with the younger children when they reach that age. Round 2 of the study returned to the same children who were aged 1-year-old in Round 1 when they were aged approximately 5-years-old, and to the children aged 8-years-old in Round 1 when they were approximately 12-years-old. Round 3 of the study returned to the same children again when they were aged 7 to 8 years (the same as the older cohort in Round 1) and 14 to 15 years. It is envisaged that subsequent survey waves will take place in 2013 and 2016. Thus the younger children are being tracked from infancy to their mid-teens and the older children through into adulthood, when some will become parents themselves. Further information about the survey, including publications, can be downloaded from the Young Lives website. School Survey: A school survey was introduced into Young Lives in 2010, following the third round of the household survey, in order to capture detailed information about children’s experiences of schooling. It addressed two main research questions: • how do the relationships between poverty and child development manifest themselves and impact upon children's educational experiences and outcomes? • to what extent does children’s experience of school reinforce or compensate for disadvantage in terms of child development and poverty? The survey allows researchers to link longitudinal information on household and child characteristics from the household survey with data on the schools attended by the Young Lives children and children's achievements inside and outside the school. A wide range of stakeholders, including government representatives at national and sub-national levels, NGOs and donor organisations were involved in the design of the school survey, so the researchers could be sure that the ‘right questions’ were being asked to address major policy concerns. This consultation process means that policymakers already understand the context and potential of the Young Lives research and are interested to utilise the data and analysis to inform their policy decisions. The survey provides policy-relevant information on the relationship between child development (and its determinants) and children’s experience of school, including access, quality and progression. This combination of household, child and school-level data over time constitutes the comparative advantage of the Young Lives study. School Survey data are currently only available for India and Peru. The Peru data are available from the UK Data Archive under SN 7479. Further information is available from the Young Lives School Survey webpages.

Under 5 years Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Town and Country, Missouri by age, education, race, gender, work experience and more.

Selected characteristics of study countries.