In 2021, Philadelphia, Pennsylvania was the city with the highest poverty rate of the United States' most populated cities. In this statistic, the cities are sorted by poverty rate, not population. The most populated city in 2021 according to the source was New York city - which had a poverty rate of 18 percent.

Two out of every three persons in Chiapas lived under the poverty line in 2022, making it the federal entity with the largest share of poor population in Mexico. On average, about 36 percent of the Mexican population was living in poverty that year.

The McAllen-Edinburg-Mission metropolitan area in Texas was ranked first with 27.2 percent of its population living below the poverty level in 2023. Eagle Pass, Texas had the second-highest poverty rate, at 24.4 percent.

In 2021, the city of Philadelphia in Pennsylvania had the highest family poverty rate of the 25 most populated cities in the United States. The city with the next highest poverty rate was Houston, Texas.

Abstract

The objective of the survey was to produce baselines for 15 large urban centers in Kenya. The urban centers covered Nairobi, Mombasa, Naivasha, Nakuru, Malindi, Eldoret, Garissa, Embu, Kitui, Kericho, Thika, Kakamega, Kisumu, Machakos, and Nyeri. The survey covered the following issues: (a) household characteristics; (b) household economic profile; (c) housing, tenure, and rents; and (d) infrastructure services. The survey was undertaken to deepen understanding of the cities’ growth dynamics, and to identify specific challenges to quality of life for residents. The survey pays special attention to living conditions for residents of formal versus informal settlements, poor versus non-poor, and male and female headed households.

Analysis unit

Household Urban center

Kind of data

Sample survey data [ssd]

Sampling procedure

The Kenya State of the Cities Baseline Survey is aimed to produce reliable estimates of key indicators related to demographic profile, infrastructure access and economic profile for each of the 15 towns and cities based on representative samples, including representative samples of households (HHs) residing in slum and non-slum areas. For this baseline household survey, NORC used a two- or three-stage stratified cluster sampling design within each of the 15 urban centers. Our first-stage sampling frame was based on the 2009 census frame of enumeration areas. For each of the 15 towns and cities, NORC received the sampling frame of EAs from the Kenya National Bureau of Statistics (KNBS). In the first stage, NORC selected a sample of enumeration areas (PSUs). The second stage involved a random selection of households (SSUs) from each selected EA. In order to manage the field interviewing efficiently, we drew a fixed number of HHs from each selected EA, irrespective of EA size. The third stage arose in instances of very large EAs (EAs containing more than 200 households) in which EAs were divided into 2, 3 or 4 segments, from which one segment was selected randomly for household selection.

Stratification of Enumeration Areas: A few stratification factors were available for stratifying the EAs to help to achieve the survey objectives. As mentioned earlier, for this baseline survey we wanted to draw representative samples from slum and non-slum areas and also to include poor/non-poor households (HHs). For the 2009 census, depending on the location, KNBS divided the EAs into three categories: rural, urban, and peri-urban.

Although there is a clear distinction of EAs into slum and non-slum areas, it is hard to classify EAs into poor and non-poor categories. To guarantee enough representation of HHs living in slum and non-slum areas (also referred to as formal and informal areas) as well as HHs living below and above the poverty line, NORC stratified the first-stage sampling units (EAs) into strata, based on EA type (3 types) and settlement type (2 types). Given the resources available, we believe this stratification would serve our purpose as HHs living in slum and in rural areas tend to be poor. Table 1 in Appendix C of final Overview Report (provided under the Related Materials tab) presents the allocation of sampled EAs across the strata for each of the 15 cities in the baseline survey.

Sampling households is not as straightforward as the first-stage sampling of EAs, since the 2009 census frame of HHs does not exist. In the absence of a household sampling frame, NORC carried out a listing of HHs within each EA selected in the first stage. Trained listers, accompanied by local cluster guides (local residents with some form of authority in the EA), systematically listed all households in each selected EA, gathering the address, names of head of household and spouse, household description, latitude and longitude. To ensure completeness of listing data, avoid duplication and improve ease of locating households that were eventually selected for interview, listers enumerated households by chalking household identification number above the household doorway (an accepted practice for national surveys). The sampling frame of HHs produced from the listing activity was, therefore, up-to-date and included new formal and informal settlements that appeared after the 2009 census.

For adequate representativeness and to manage the interviewing task efficiently, NORC planned seven completed household interviews per EA. The final recommended sample size for the Kenya State of the Cities baseline survey is found in Table 2 in Appendix C of the final Overview Report.

Because the expected response rate was unknown prior to the start of the field period, the sampling team randomly selected ten households per enumeration area and distributed them to the interviewers working within the EA. Interviewing teams were instructed to complete at least seven interviews per EA from among the ten selected households. Interviewers were instructed to attempt at least three contacts with each selected household, approaching potential respondents on different days of the week and different times of day. Table 2 presents the final number of EAs listed per city and the final number of completed interviews per city. The table also presents the percent of planned EAs and interviews that were completed vs. planned. Please note that in several cities more interviews were completed than planned. As part of NORC's data quality plan, data collection teams were instructed to overshoot slightly the target of seven interviews per EA, if feasible, to mitigate any potential loss of cases due to poor quality or uncooperative respondents. Few cases were lost due to poor quality, therefore the target number of interviews remains over 100 percent in ten of the fifteen cities.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developed by World Bank staff with input from stakeholders in the Kenya Municipal Program and NORC researchers and survey methodologists. The base questionnaire for the project was a 2004 World Bank survey of Nairobi slums. However, an extended iterative review process led to many changes in the questionnaire. The final version that was used for programming provided under the Related Materials tab, and in Volume II of the Overview.

The questionnaire’s topical coverage is indicated by the titles of its nine modules: 1. Demographics and household composition 2. Security of housing, land and tenure 3. Housing and settlement profile 4. Economic profile 5. Infrastructure services 6. Health 7. Household enterprises7 8. Civil participation and respondent tracking

Response rate

The completion rate is reported as the number of households that successfully completed an interview over the total number of households selected for the EA. These are shown by city in Table 5 in Appendix C of the final Overview Report, and have an average rate of 68.66 percent, with variation from 66 to 74 percent (aside from Nairobi at 61.47 percent and Machakos at 56 percent). As described earlier, ten households were selected per EA if the EA contained more than 10 households. For EAs where fewer than ten households were selected for interviews, all households were selected. In some EAs, more than ten households were selected due to a central office error.

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2023, at 90,730 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 39,102 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 214,000 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.

The municipalities of Manapiare and Bolívar, located in the Venezuelan states of Amazonas and Falcón, respectively, registered the highest share of population living under the poverty line in the country in 2021. That year, almost the entire population of these municipalities was reported to be living in poverty. All the 25 Venezuelan cities listed in this statistic had at least 99.7 percent of their population living under the poverty line.

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.

Research background In his 1997 essay, 'The Ultimate Departure Lounge', the British writer J. G. Ballard wrote: 'Airports have become a new kind of discontinuous city... I suspect that the airport will be the true city of the 21st century. The great airports of the planet are already the suburbs of an invisible world capital, a virtual metropolis whose faubourgs are named Heathrow, Kennedy, Charles de Gaulle, Nagoya, a centripetal city whose population forever circles its notional centre, and will never need to gain access to its dark heart.' This series of works poses the question: do we pause to consider what effect generic urban environs, efficient and efficiently blank spaces, have on us? How are we shaped by these vast 'unnoticed' structures that play so large a role in our lives? Research contribution These paintings provide metaphorical readings of contemporary society, forming as representations of ciphers embodying change and entropy, poised between being and not being and functioning as signs evoking contemporaneity. This work forms as a fiction that 'allows us to imagine our world differently, and as such it offers escape routes... from our representational and often over stratified sense of self' (O'Sullivan, Art encounters Deleuze and Guattari : thought beyond representation. 2006, p. 29). The imagery in this work forms as a kind of symptom of disorganisation and resembles what Gilles Deleuze calls a 'zone of indeterminacy' (Deleuze, Francis Bacon : the logic of sensation. 2005, p.16) due to it existing as an in-between of states, a becoming that is not 'finished'. Research significance These paintings were a contribution to an exhibition selected by the curator, Anna-Louise Rolland, (Director of Leipzig International Artist Programme) investigating the current state of art in relation to spaces. Inclusion in this artist residency and exhibition was through an international peer selection process.

Amazonas, a sparsely populated state located in the southern part of Venezuela, is the region with the highest poverty rate in Venezuela. In 2021, 99 percent of the population in Amazonas state was considered to live below the poverty line. Yaracuy and Sucre were other Venezuelan states that registered the highest poverty rates that year, both above 97 percent. More than half of households in Venezuela are estimated to be under extreme poverty.

Abstract

The Ugandan Government in 1997 introduced the Universal Primary Education (UPE) policy. The policy allowed the abolishment of tuition fees to increase access to education for the most marginalized. Other national programs and interventions exist to ensure that all children access quality education without any form of discrimination. Additionally, the Government of Uganda is also a signatory to international and local treaties that protect the right to education for all. Despite the UPE policy and other programs supporting access to quality education, children from marginalized communities still face exclusion from education opportunities. Gender, regional disparities, socio-economic status and disabilities are some of the key forms of exclusion that children face. To understand access to quality education in urban informal settlements in Uganda, the African Population and Health Research Center in 2018 brought together state and non-state actors of education working in the urban informal settlements through the urban education project. Through this project, the state and non-state actors of education formed a Uganda Urban Education Group (UEG). Stakeholders in this group engaged in different activities, such as forming and strengthening the UEG group for a collective voice in advocating for access to quality education for children living in urban informal settlements. Through this engagement and review of existing literature, the stakeholders identified a gap. The gap in the evidence was in relation to how children in urban informal areas in Uganda access education and where the children access education. It was after several consultations with the UEG members that the team sought to carry out a research study in selected urban informal settlements in Uganda. The study titled ‘The Urban Education Agenda in Uganda: A Call for Targeted Attention on Education for the Urban Poor’ sought to answer the following objectives. 1. What are the schooling patterns among children living in urban poor households in Uganda – including those with Special needs? 2. What explains the observed schooling patterns in small and large urban centers? 3. How do poor urban communities perceive and understand education as a right in the context of urbanization in Uganda? 4. What available education opportunities exist for children with special needs and living in poor households in Uganda? 5. What survival and educational mechanisms/initiatives did people in urban poor settlements adopt during the COVID-19 pandemic? 7 Urban Education Research Report - Uganda Data collection was carried out in two phases. The main data collection took place in October 2020, while the school survey and the rapid household survey both took place in March 2021. The study was conducted in 42 villages selected in seven parishes in Kampala and Mukono. Five of these parishes were from Kampala, and two from Mukono Municipality. In selecting the study site, the research team ensured that each of the study sites was classified as an urban informal settlement by the Uganda Bureau of Statistics (UBOS). Additionally, the Urban Education steering committee from the Ministry of Education and Sports (MoES) and Kampala Capital City Authority (KCCA) were also consulted in deciding on the areas of study. A total of five quantitative instruments were used. These included household amenities and schedule, individual schooling history, parental and perception, rapid household and institutional tools, and 1,102 households with 2,581 children aged 3-19 years were interviewed. Descriptive and inferential statistics were used to conduct the analysis. Tables and graphs have been used to present the findings. Qualitative tools were also used for this study. The following methods were used: Key Informant Interviews (KIIs) with national policy actors, In-depth Interviews (IDIs) with local administration and Focus Group Discussions (FGD) with parents. In analyzing the qualitative data, codes were developed and the deductive method was mainly used. 8 Urban Education Research Report - Uganda Key Findings Household Characteristics 1. 65.3 % of households in Uganda’s urban informal settlements have more than five members who live in the poorest wealth quintile. 2. More than half (53.9%) of the female-headed households were in the poorest wealth quintile compared to their male counterparts. 3. Across the three wealth index levels (poorest, middle, wealthiest),more than half of the household heads had attained a lower secondary or above in regard to education. 4. There were more girls (54%) in the selected households compared to boys (46%) that had school going children aged 3-19 years. 5. Across the three wealth index levels more children were attending the primary level (67%), followed by the secondary level (19%) and lastly, the pre-primary level 14%. School Attendance 1. Before the closure of schools due to COVID-19, 99.6% of the children aged 4 to 17 years had ever been to school. 2. Before the closure of schools due to COVID-19, 2.1 % of children were out of school, but after full school re-opening, this increased to 9 %. 3. By gender, before school closure, more boys (2.4%) were out of school compared to girls (2.1%), but after full re-opening, more female learners (9.2%) were not enrolled compared to (8.6%) boys. 4. At all the primary and secondary levels, there were more learners enrolled in private schools compared to government schools during school closures due to COVID-19 and after full school re-opening. At the primary level before COVID-19, enrollment stood at 68.1%, but after full re-opening, this went down to 63.8 %. At the secondary level, it was 71.7% before the school’s closure, and surprisingly, this remained the same after full school re-opening. 5. After full school re-opening, the findings show an increase in the learners from the poorest wealth index level at the primary level moving to government schools from 33.9% to 43.9%. 6. About 42.3% of parents transferred their children after full school reopening due to the affordability of school fees. 7. More children from the urban informal settlements for the period 2015-2022 have predominantly utilized private schools compared to government schools. 8. Overall, 8.2% of children had repeated a grade, with more boys (9.3%) repeating than girls (7.3%). 9. About 28.4 % of learners did not progress to the next grade after full school re-opening. Pupil-Teacher Ratio 1. The PTR at the primary school level was high (1:55) in government schools compared to 1:19 in private schools. 9 Urban Education Research Report - Uganda Perceptions on Quality of Education 1. Slightly more than half (51.9%) of parents from the urban informal settlements felt that the quality of education had improved since the introduction of the Universal Free Primary Education policy. Stakeholders’ Understanding of the Right to Education 1. Notably, the concept of the Right to Education was well understood by all the stakeholders, including the parents. The parents highlighted several ways in which they uphold the right to education, which included providing uniforms and food for their children while going to school. Additionally, they encouraged each other to enroll their children in schools while acknowledging the role the community plays. 2. The mechanisms used to report violations of the Right to Education were better understood by the policy actors and local administration as compared to the parents. Parents indicated using more community-level-based methods, such as the village local council meetings compared to the structures set up by the Ministry of Education and Sports and others. Opportunities for Continued Learning During COVID-19 1. Overall, the poorest households (15%) accessed the least and paid (54%) more for these opportunities compared to those households that were in the middle and wealthiest wealth index levels. 2. The main challenges in accessing learning opportunities included a lack of resources to purchase learning materials, competing responsibilities at home that limited the time available for study and a lack of study spaces at home. 10 Urban Education Research Report - Uganda Conclusion The urban informal areas in our towns and cities continue growing rapidly. This trend comes with an increase in the population and, consequently, a growing demand for public services such as education. In Uganda’s urban informal settlements, more children are utilizing private schools than government public schools to access education. This pattern is associated with distance to school and hence the reason for parents choosing private schools over government schools, which are already crowded. Despite the UPE policy, there was an indication that children from urban poor informal settlements largely do not benefit from the UPE policy, enhancing education inequalities and continuously denying opportunities to the most marginalized children. It was also evident that children from urban poor informal settlements were more likely to not access learning opportunities during school disruptions such as that of COVID-19. Therefore, calling on the government to develop measures and programs to cushion learners from such settings when such instances occur. Moreover, girls are more likely to be affected by disruptions such as COVID-19 in different ways. This includes being prone to teenage pregnancies and taking up responsibilities to take care of younger siblings compared to boys. The community plays a critical role in upholding the right to education and the community members including parents trust the structures that are at the community level in addressing some of the challenges they face in ensuring children from the urban informal communities access quality education. Recommendations 1. The government should strengthen the Public-Private Partnership (PPP) mechanism that already exists, despite

In 2021, New York city had the highest number of families living below the poverty line, at an estimated 272,461 families. New York city is also the most heavily populated city in the United States.

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.

The estimated per capita income across Sikkim was the highest among Indian states at around *** thousand Indian rupees in the financial year 2024. Meanwhile, it was the lowest in the northern state of Bihar at over ** thousand rupees. India’s youngest state, Telangana stood in the fifth place. The country's average per capita income that year was an estimated *** thousand rupees. What is per capita income? Per capita income is a measure of the average income earned per person in a given area in a certain period. It is calculated by dividing the area's total income by its total population. If absolute numbers are noted, India’s per capita income doubled from the financial year 2015 to 2023. Wealth inequality However, as per economists, the increase in the per capita income of a country does not always reflect an increase in the income of the entire population. Wealth distribution in India remains highly skewed. The average income hides the disbursal and inequality in a society. Especially in a society like India where the top one percent owned over ** percent of the total wealth in 2022.

The Nigerian states of Sokoto and Taraba had the largest percentage of people living below the poverty line as of 2019. The lowest poverty rates were recorded in the South and South-Western states. In Lagos, this figure equaled 4.5 percent, the lowest rate in Nigeria.

A large population in poverty

In Nigeria, an individual is considered poor when they have an availability of less than 137.4 thousand Nigerian Naira (roughly 334 U.S. dollars) per year. Similarly, a person having under 87.8 thousand Naira (about 213 U.S. dollars) in a year available for food was living below the poverty line according to Nigerian national standards. In total, 40.1 percent of the population in Nigeria lived in poverty.

Food insecurity on the rise

On average, 21.4 percent of the population in Nigeria experienced hunger between 2018 and 2020. People in severe food insecurity would go for entire days without food due to lack of money or other resources. Over the last years, the prevalence with severe food among Nigerians has been increasing, as the demand for food is rising together with a fast-growing population.

The gross domestic product (GDP) of California was about 3.23 trillion U.S. dollars in 2023, meaning that it contributed the most out of any state to the country’s GDP in that year. In contrast, Vermont had the lowest GDP in the United States, with 35.07 billion U.S. dollars. What is GDP? Gross domestic product, or GDP, is the total monetary value of all goods and services produced by an economy within a certain time period. GDP is used by economists to determine the economic health of an area, as well as to determine the size of the economy. GDP can be determined for countries, states and provinces, and metropolitan areas. While GDP is a good measure of the absolute size of a country's economy and economic activity, it does account for many other factors, making it a poor indicator for measuring the cost or standard of living in a country, or for making cross-country comparisons. GDP of the United States The United States has the largest gross domestic product in the world as of 2023, with China, Japan, Germany, and India rounding out the top five. The GDP of the United States has almost quadrupled since 1990, when it was about 5.9 trillion U.S. dollars, to about 25.46 trillion U.S. dollars in 2022.

In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

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.

This graph shows the Percentage of households led by a female householder with no spouse present with own children under 18 years living in the household in the U.S. in 2021, by state. In 2021, about 4.24 percent of Californian households were single mother households with at least one child.

Additional information on single mother households and poverty in the United States

For most single mothers a constant battle persists between finding the time and energy to raise their children and the demands of working to supply an income to house and feed their families. The pressures of a single income and the high costs of childcare mean that the risk of poverty for these families is a tragic reality. Comparison of the overall United States poverty rate since 1990 with that of the poverty rate for families with a female householder shows that poverty is much more prevalent in the latter. In 2021, while the overall rate was at 11.6 percent, the rate of poverty for single mother families was 23 percent. Moreover, the degree of fluctuation tends to be lower for single female household families, suggesting the rate of poverty for these groups is less affected by economic conditions.

The sharp rise in the number of children living with a single mother or single father in the United States from 1970 to 2022 suggests more must be done to ensure that families in such situations are able to avoid poverty. Moreover, attention should also be placed on overall racial income inequality given the higher rate of poverty for Hispanic single mother families than their white or Asian counterparts.

In Italy, the largest part of population who live below the poverty line is located in the South. As of 2021, in three Southern regions, Apulia, Campania, and Calabria over 20 percent of the population was living below the poverty line. An Italian household with four members is considered poor when it has an availability of less than about 1.7 thousand euros a month.