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 Estimated Percent of People of All Ages in Poverty for United States (PPAAUS00000A156NCEN) from 1989 to 2023 about percent, child, poverty, 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 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.

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.

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.

In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.

According to a study from 2020, over 70 percent of the poorest children living in Mali, Niger, Nigeria, and Guinea dis not attend school. Overall, Sub-Saharan Africa has the highest illiteracy rate in the world. Countries in East and West Africa suffer from high levels of poverty, including health, malnutrition, lack of clean water and electricity, poor education, and other similar aspects.

In 2023, Wildwood-The Villages metropolitan area in Florida was ranked first, with 39.3 percent of its population aged under 18 years living below the poverty level. McAllen-Edinburg-Mission metro area in Texas had the second-highest rate of child poverty in the nation.

From 2017 to 2021, the share of households living under the poverty line in Venezuela has been surpassing 90 percent. In addition, more than six out of every ten households (67.97 percent) lived in extreme poverty in 2021. The overall household poverty rate in Venezuela has registered a steady growth from 2014 to 2019, after having remained relatively stable, below 40 percent, since 2005. Although poverty is widespread among the population as a whole, some groups are more vulnerable than others. That is the case of younger generations and particularly children: 98.03 percent of Venezuelans aged 15 or younger lived in poverty in 2021. An economy in disarray Venezuela, the country with the largest oil reserves in the world and whose economy has been largely dependent on oil revenues for decades, was once one of the most prosperous countries in Latin America. Today, hyperinflation and an astronomic public debt are only some of the many pressing concerns that affect the domestic economy. The socio-economic consequences of the crisis As a result of the economic recession, more than half of the population in every state in Venezuela lives in extreme poverty. This issue is particularly noteworthy in the states of Amazonas, Monagas, and Falcón, where the extreme poverty rate hovers over 80 percent. Such alarming levels of poverty, together with persistent food shortages, provoked a rapid increase in undernourishment, which was estimated at 17.9 percent between 2020 and 2022. The combination of humanitarian crisis, political turmoil and economic havoc led to the Venezuelan refugee and migrant crisis. As of 2020, more than five million Venezuelans had fled their home country, with neighboring Colombia being the main country of destination.

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.

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, and to improve our understanding of:

• the relationships between learning outcomes, and children's home backgrounds, gender, work, schools, teachers and class and school peer-groups
• school effectiveness, by analysing factors explaining the development of cognitive and non-cognitive skills in school, including value-added analysis of schooling and comparative analysis of school-systems
• equity issues (including gender) in relation to learning outcomes and the evolution of inequalities within education

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. It 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 Young Lives.

A further round of school surveys took place during the 2016-2017 school year. The key focus areas for these were:

• benchmarking levels of student attainment and progress in key learning domains
• effects of school and teacher quality, and school effectiveness
• educational transitions at age 15

The 2016-2017 school surveys focused on the level of schooling accessed by 15-year-olds in each country, so including Grade 7 and 8 students in Ethiopia (upper primary level), Grade 9 students in India (lower secondary level), and Grade 10 students in Vietnam (upper secondary level).

The School Survey data are held separately for each country. The Ethiopia data are available from the UK Data Archive under SN 7823 and SN 8359, the India data are available from SN 7478 and SN 8359, and the Peru data have been archived under SN 7479 (no 2016-2017 survey).

Further information is available from the Young Lives School Survey webpages.


Main Topics:

The Vietnam survey included data collection at the school, class and pupil level, and involved the Principal / Head teacher, the Maths and English teachers, and the Young Lives child. The instruments included in the survey were:

• Principal questionnaire - collected background data on the principal and the school (including school management practices)
• Teacher questionnaire - collected background data on Grade 10 Maths and English teachers (including teacher motivation, and class-level information)
• Student questionnaire - collected background data on Grade 10 students (including academic support within and beyond school, and psychosocial measures)
• Maths test - repeated measures, administered at the beginning and end of Grade 10. Assessing students’ curriculum knowledge, and ability...

Abstract

Multiple causes for displacement, all too often underpinned by violence and persecution, has led to over 800,000 Central Americans fleeing their homes, beginning in 2013. Year after year, there has been an increase in individuals fleeing. This was marked initially by especially large numbers of unaccompanied children, then joined in around 2018 with dramatic increases in families units fleeing Central America. Families are forced to flee together as violent threats and persecution by criminal groups in communities extend beyond individuals to entire family units.

Given these shifting dynamics in human mobility in these countries, UNHCR and UNICEF, through the Interdisciplinary Development Consultants, CID Gallup, decided to undertake this study with the aim of understanding and giving visibility to the forced displacement of families that flee northern Central America. In addition, the study also seeks to shed light on the current trends, protection risks and factors associated to the forced displacement and migration of unaccompanied and separated children.

For this purpose, Gallup conducted 3,104 surveys, complemented by focus group sessions segmented according to the geography of displacement in the region: country of origin, of transit and of asylum. Additionally, interviews were undertaken with families who were part of large mixed movement "caravans" that left Honduras at the beginning of 2020.

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

A significant sample was taken of each profile interviewed for a total of 3,104 surveys conducted in Honduras, El Salvador, Guatemala and Mexico. The content of each survey was focused on the following profiles:

Families and children and adolescents at risk of displacement in countries of origin: a total of 789 surveys were carried out with families identified from a non-probabilistic sampling. The surveys were taken in areas with the highest criminality and violence rates in countries of origin (El Salvador, Honduras and Guatemala), which were also areas with a prior history of forced displacement identified through previous studies. The survey questions focused on risks faced by families in their places of origin, including those that would compel them to flee, particularly those related to violence and poverty.

Families and children and adolescents in transit: a total of 836 surveys were carried out with families identified from a non-probabilistic sampling. The surveys were taken at locations where persons in transit were typically found in Guatemala and Mexico, such as Casas de Migrantes. For the quantitative component, data of unaccompanied children and adolescents was gatheredin Casa Nuestras Raices in Guatemala City and Quetzaltenango. This segment of the population was surveyed on the risks they faced during transit as well as the causes of displacement from their countries of origin.

Families and children and adolescents in country of destination: through non-probabilistic sampling methods, 453 people were surveyed, the majority of whom were recognized as refugees or asylum seekers in Mexico. Several interviews were facilitated by the UNHCR Office in Mexico in areas with this population profile: Casa del Migrante Monsenor-Oluta Veracruz, Scalabrinianas Mision con Migrantes y Refugiados, State DIF, Municipal DIF, among others. The survey questions for this population focused on the asylum procedure and their living conditions in the country.

Deported families and children and adolescents: non-probability cluster sampling. Interviews were conducted with 1,026 families that had been detained and deported during the 12 months prior to the survey. Locations included the Guatemalan Air Force base, outside of the Center for the Comprehensive Assistance to Migrants (CAIM for its acronym in Spanish) and outside of the following locations in Honduras: Center for the Assistance of Migrant Children and Families in Belen, and Center for the Assistance to the Returned Migrant (CAMR) and CAMR-OMOA.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire contains the following sections: household characteristics, individual characteristics, details on deportation, risks, transit, settled households.

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.

Young Lives research has expanded to explore linking geographical data collected during the rounds to external datasets. Matching Young Lives data with administrative and geographic datasets significantly increases the scope for research in several areas, and may allow researchers to identify sources of exogenous variation for more convincing causal analysis on policy and/or early life circumstances.

Young Lives: Data Matching Series, 1900-2021 includes the following linked datasets:

1. Climate Matched Datasets (four YL study countries): Community-level GPS data has been matched with temperature and precipitation data from the University of Delaware. Climate variables are offered at the community level, with a panel data structure spanning across years and months. Hence, each community has a unique value of precipitation (variable PRCP) and temperature (variable TEMP), for each year and month pairing for the period 1900-2017.

2. COVID-19 Matched Dataset (Peru only): The YL Phone Survey Calls data has been matched with external data sources (The Peruvian Ministry of Health and the National Information System of Deaths in Peru). The matched dataset includes the total number of COVID cases per 1,000 inhabitants, the total number of COVID deaths by district and per 1,000 inhabitants; the total number of excess deaths per 1,000 inhabitants and the number of lockdown days in each Young Lives district in Peru during August 2020 to December 2021.

Further information is available in the PDF reports included in the study documentation.

Main Topics:

Climate Matched Datasets: 5 variables including anonymised community identifier, monthly average temperature, monthly total precipitation, and year and month of climate data.

COVID-19 Matched Dataset (Peru): 29 variables to covering anonymised respondent identifier, cumulative number of COVID-19 cases per 1,000 inhabitants, fatalities, migration, vaccine distribution, and lockdown conditions implemented by the Peruvian government in areas where YL participants were living at the time of the Phone Survey Calls.

This app is published as Open Data, is the most recent, and replaces any previously published dataset.Scottish Index of Multiple Deprivation (2020), Small Area Population Estimates (2021), and Child Poverty (2022/23)The Scottish Index of Multiple Deprivation 2020 is the Scottish Government’s official tool for identifying those places in Scotland suffering from deprivation. It incorporates several different aspects of deprivation (employment, income, health, education, skills and training, geographic access, crime and housing), combining them into a single index.The 2020 Index provides a relative ranking for small areas in Scotland, defined by the Scottish Neighbourhood Statistics (SNS) Data Zone 2011 geography, from 1 (most deprived) to 6,976 (least deprived). By identifying small areas where there are concentrations of multiple deprivation, the SIMD can be used to target policies and resources at the places with greatest need. The SIMD also provides a rank for each data zone within each of the seven domains, and therefore it is possible to look at individual aspects of deprivation for each area, as well as the overall level of deprivation.Child Poverty by Datazone (2022/23)This app uses the following published resources:mapdataset

In 2023, the number of child workers in Indonesia amounted to around 1.01 million people. This indicated a decrease of approximately 40 thousand people compared to 2021. Child labor in Indonesia is still an ongoing issue due to poverty and a lack of access to education in some parts of the country. The pandemic notably affected the problem, as the number of child workers increased in 2020. Although the numbers have decreased since then, they remain higher than the pre-pandemic level. The challenges of child labor in Indonesia The persisting issue of child labor in Indonesia stems from different factors such as economics, social norms, and education. Poverty acts as a crucial driving factor in the case of child labor practices. Many children are pushed to stop attending school and get to work to help the family’s income, as over nine percent of the Indonesian population still lives below the poverty line. The islands in the eastern part of the archipelago, such as Maluku and Papua, had the highest poverty rates of over 20 percent in 2022. It was also found that Papua had the highest share of students who had to attend school and work simultaneously. Moreover, in certain areas of the archipelago, cultural beliefs are linked to entering the labor force at an early age, with some believing this to help shape children to have better life opportunities in the future. The lack of awareness about the effects of child labor and some companies not complying with the laws against child labor further exacerbate the issue. Child labor in the Indonesian agricultural sector Child labor in Indonesia is more prevalent in rural areas. As of 2022, there has been an increase in the child labor rate in Indonesia’s rural areas in the agricultural sector, which most commonly offers informal employment with minimal employment protections. Child workers in this sector face higher risks of being exposed to harmful chemicals used in pesticides and fertilizers, causing raised concerns about their safety. Despite the efforts to overcome this issue, such as child protection laws, government allocations for infrastructure, and government allocations for education to improve living conditions and educational access, the need for strategic initiatives to combat child labor in Indonesia remains.

This dataset is published as Open Data, is the most recent, and replaces any previously published dataset.The Scottish Index of Multiple Deprivation 2020 is the Scottish Government’s official tool for identifying those places in Scotland suffering from deprivation. It incorporates several different aspects of deprivation (employment, income, health, education, skills and training, geographic access, crime and housing), combining them into a single index.The 2020 Index provides a relative ranking for small areas in Scotland, defined by the Scottish Neighbourhood Statistics (SNS) Data Zone 2011 geography, from 1 (most deprived) to 6,976 (least deprived). By identifying small areas where there are concentrations of multiple deprivation, the SIMD can be used to target policies and resources at the places with greatest need. The SIMD also provides a rank for each data zone within each of the seven domains, and therefore it is possible to look at individual aspects of deprivation for each area, as well as the overall level of deprivation.The dataset can be viewed by Ward, Intermediate Zone (IZ) and Scottish Parliamentary Constituency (SPC).Details of the methodology used to determine the income, employment, education, health, access (to services), crime and housing domains can be opened from this link. Depending on the browser used to access this dataset, view the document from the options appearing on the screen.The SIMD dataset has been sourced from: SpatialData.gov.scotThis dataset is also used in the associated SIMD and Child Poverty map and application.

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.

The School Survey data are held separately for each country. The India data are available from the UK Data Archive under SN 7478, the Vietnam data have been archived under SN 7663, and the Ethiopia data are available from SN 7823.

A further round of school surveys took place during the 2016-2017 school year. The Ethiopia survey is available under SN 8358, the India survey under SN 8359 and the Vietnam survey under SN 8360.

Further information is available from the Young Lives https://www.younglives.org.uk/content/school-survey" title="School Survey">School Survey webpages.

In 2021, Niger was the African country with the highest fertility rate. There, each woman had an average of 6.82 children in her reproductive years. Somalia and Chad followed, with a fertility rate of around 6.31 and 6.26 children per woman, respectively. Fertility levels in Africa remain high despite a steady decline The fertility rate in Africa has gradually decreased since 2000 and is projected to decline further in the coming years. Factors including improved socio-economic conditions and educational opportunities, lower infant mortality, and decreasing poverty levels have driven the declining birth rate on the continent. Nevertheless, Africa remains the continent with the highest fertility rate worldwide. Between 2015 and 2021, women in Africa had an average of 4.47 children in their reproductive years. Africa was the only continent registering a fertility rate higher than the global average, which was set at 2.32 children per woman. Worldwide, the continent also had the highest adolescent fertility rate as of 2021, with West and Central Africa leading with 107 births per 1,000 girls aged 15 to 19 years. Africa’s population keeps growing According to projections, over 46 million births will be registered in Africa in 2023. Contrary to the declining fertility rate, the absolute number of births on the continent will continue to grow in the coming years to reach around 50.1 million by 2026. In general, Africa’s population – amounting to over 1.39 billion inhabitants as of 2021 – is forecast to increase considerably and achieve almost 2.5 billion in 2050. Countries such as Niger, Angola, and Equatorial Guinea are key drivers of population growth in Africa, registering the highest average population growth rate on the continent between 2020 and 2025. For instance, in that period, Niger’s population was forecast to expand by 3.7 percent each year.

In 2025, *** percent of Kenya’s population live below **** U.S. dollars per day. This meant that over 8.9 million Kenyans were in extreme poverty, most of whom were in rural areas. Over *** million Kenyans in rural communities lived on less than **** U.S. dollars daily, an amount *** times higher than that recorded in urban regions. Nevertheless, the poverty incidence has declined compared to 2020. That year, businesses closed, unemployment increased, and food prices soared due to the coronavirus (COVID-19) pandemic. Consequently, the country witnessed higher levels of impoverishment, although improvements were already visible in 2021. Overall, the poverty rate in Kenya is expected to decline to ** percent by 2025. Poverty triggers food insecurity Reducing poverty in Kenya puts the country on the way to enhancing food security. As of November 2021, *** million Kenyans lacked sufficient food for consumption. That corresponded to **** percent of the country's population. Also, in 2021, over one-quarter of Kenyan children under five years suffered from chronic malnutrition, a growth failure resulting from a lack of adequate nutrients over a long period. Another *** percent of the children were affected by acute malnutrition, which concerns a rapid deterioration in the nutritional status over a short period. A country where prosperity and poverty walk side by side The poverty incidence in Kenya contrasts with the country's economic development. In 2021, Kenya ranked among the ten highest GDPs in Africa, at almost *** billion U.S. dollars. Moreover, its gross national income per capita has increased to ***** U.S. dollars over the last 10 years, a growth of above**** percent. Generally, while poverty decreased in the country during the same period, Kenya still seems to be far from reaching the United Nation's Sustainable Development Goals (SDGs) to eliminate extreme poverty by 2030.