In 2023/24, **** percent of children in the United Kingdom were estimated to be living in relative poverty after housing costs were considered, compared with **** percent of working age adults, **** percent of pensioners, and **** percent of families where someone is disabled

Rates of poverty and persistent poverty in 2017 are included for the UK and EU, including characteristics, measures of material deprivation and well-being.

Historical chart and dataset showing U.K. poverty rate by year from 1968 to 2021.

As of 2023/24 approximately 11.6 million people were living in relative poverty in the United Kingdom, with that number increasing to over 14.2 million when housing costs are considered.

Model-based estimates of the proportion of households with mean weekly income lower than 60% of the national median weekly income, by middle layer super output area, England and Wales.

Between 2018 and 2022, people in households in the ‘other’, Asian and black ethnic groups were the most likely to be in persistent low income, both before and after housing costs, out of all ethnic groups.

United Kingdom UK: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 0.700 % in 2015. This records an increase from the previous number of 0.500 % for 2014. United Kingdom UK: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 0.700 % from Dec 2004 (Median) to 2015, with 12 observations. The data reached an all-time high of 1.200 % in 2004 and a record low of 0.400 % in 2012. United Kingdom UK: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Population 25 years and over Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in New Britain, Connecticut by age, education, race, gender, work experience and more.

The Children in low-income families' local area statistics (CiLIF), provides information on the number and proportion of children living in Absolute low income by local area across the United Kingdom.The summary Statistical Release and tables which also show the proportions of children living in low income families are available here: Children in low income families: local area statistics - GOV.UK (www.gov.uk)Statistics on the number of children in low income families by financial year are published on Stat-Xplore. Figures are calibrated to the Households Below Average Income (HBAI) survey regional estimates of children in low income but provide more granular local area information not available from the HBAI, for example by Local Authority, Westminster Parliamentary Constituency and Ward.Absolute low-income is defined as a family in low income Before Housing Costs (BHC) in the reference year in comparison with incomes in 2010/11. A family must have claimed Child Benefit and at least one other household benefit (Universal Credit, tax credits, or Housing Benefit) at any point in the year to be classed as low income in these statistics. Gross income measure is Before Housing Costs (BHC) and includes contributions from earnings, state support and pensions.

Statistical disclosure control has been applied with Stat-Xplore, which guards against the identification of an individual claimant.

5 to 17 years Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in New Britain, Connecticut by age, education, race, gender, work experience and more.

Indicators from the Opinions and Lifestyle Survey (OPN) related to household income changes and subjective poverty.

United Kingdom UK: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 18.600 % in 2017. This records an increase from the previous number of 17.000 % for 2016. United Kingdom UK: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 17.800 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 18.600 % in 2017 and a record low of 17.000 % in 2016. United Kingdom UK: Poverty Headcount Ratio at National Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Social: Poverty and Inequality. National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.;World Bank, Poverty and Inequality Platform. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.;;This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Compares the at-risk-of-poverty rates for the UK and EU between 2005 and 2010.

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: Comparison of UK and EU at-risk-of-poverty rates

Employed Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in New Britain, Connecticut by age, education, race, gender, work experience and more.

Focus group interviews were conducted between November and December 2010 in five different locations, including in each of the four territories comprising the UK: Bristol, Cardiff, London, Glasgow and Belfast. Separate group interviews were conducted amongst low income samples (5 groups), non-low income samples (5 groups), and mixed income samples (4 groups). These groups were also stratified by household type (11 groups) and minority ethnic status (3 groups)

Pan London financial capability data to support Local Authorities Child Poverty Needs Assessments, updated in April 2011 with 2010 data.

This data is designed to help local authorities improve their understanding of the areas within their borough where low financial capability is most likely to exist. This could be useful to child poverty needs assessments, and subsequent work to develop and target support services for residents within their borough.

Supporting Documents

Technical information about the datasets is available in the readme.txt file.

A support note prepared by MAS and CPU is available to advise local authorities on using the data in Child Poverty Needs Assessments.

Profiles of the data categories are available in the Pen Portraits report and details of the underlying model used by Experian are available in Technical Model report.

Further Information

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For more information on the Money Advice Service (formerly the Consumer Financial Education Body): http://www.moneyadviceservice.org.uk

For more information on Child Poverty Unit: http://www.education.gov.uk/childrenandyoungpeople/
families/childpoverty

For details of the Experian model:
http://webarchive.nationalarchives.gov.uk/
http://www.hm-treasury.gov.uk/thoresen_review_index.htm

BackgroundThe ageing population poses a tremendous challenge in understanding the sources of inequalities in health. Though they appear to be far removed, childhood conditions are known to be inextricably linked with adult health, and in turn on health in later life. The long arm of childhood conditions hypothesis is often tested using recollection of childhood circumstances, but such subjective recall can yield potentially inaccurate or possibly biased inferences. We tested the long arm hypothesis on three outcomes in later life, arrayed from objective to subjective health, namely: gait speed, episodic memory and mental health.Methods and FindingsWe used the English Longitudinal Study of Ageing 2006 enriched with retrospective life history (N = 5,913). To deal with recall problems two solutions, covariate measurement and endogenous treatment models, were applied. Retrospective childhood material lack includes growing up without running hot or cold water, fixed bath, indoor lavatory and central heating. Adjustment is made for an extensive set of confounders including sex, age, adult health, wealth, education, occupation, social support, social connections, chronic conditions, smoking, drinking, and physical exercise. It is found that material poverty when growing up shows no association with health when growing old, assuming accurate recall. Once recall problems are controlled, we found that childhood material poverty changes inversely with later life health.ConclusionA poorer childhood goes with slower gait, poorer memory and more depression in later life. This result provides a further impetus to eliminate child poverty.