SlideShare une entreprise Scribd logo
1  sur  3
Télécharger pour lire hors ligne
Relative income poverty
ethnicity and disability
Relative income poverty
Ethnicity and disability
Financial year ending 2019
Non-white ethnicity is linked with a greater
likelihood of relative income poverty
• In the latest period (2014-15 to 2018-19, an average of 5 financial
years) people who were living in households where the head of the
household was from a non-white ethnic group were more likely to be
in relative income poverty compared with those where the head of the
household was from a white ethnic group.
• There was a 25 per cent likelihood of people from a non-white ethnic
group living in relative income poverty compared to a 23 per cent
likelihood for those from a white ethnic group in 2014-15 to 2018-19.
• However, because the vast majority of households in Wales have a
head who is from a white ethnic group, most people (98 per cent)
who were living in relative income poverty were from such
households.
We were not able to produce robust figures for children or pensioners by ethnic group of head of
household due to low sample sizes. For UK breakdowns by ethnic group please see the HBAI tables
produced by the Department for Work and Pensions.
Living with a person who has a disability makes
relative income poverty more likely for children and
working age people
• In the survey data, disabled people are identified as those who report any
physical or mental health condition or illness that are expected to last 12 months
or more, and which limit their ability to carry out day-to-day activities a little, or a
lot. This is in line with the Equality Act definition.
• In the latest period (2016-17 to 2018-19), 37 per cent of children who lived in a
household where there was someone with a disability were in relative income
poverty compared with 24 per cent in households where no-one was disabled.
• 31 per cent of working-age adults who lived in a household where there was
someone with a disability were in relative income poverty compared with 18 per
cent of those who lived in a household where no-one was disabled.

Contenu connexe

Plus de Statistics for Wales @ Welsh Government

Plus de Statistics for Wales @ Welsh Government (20)

NHS activity and performance summary: January and February 2020
NHS activity and performance summary: January and February 2020NHS activity and performance summary: January and February 2020
NHS activity and performance summary: January and February 2020
 
NHS activity and performance summary: December 2019 and January 2020
NHS activity and performance summary: December 2019 and January 2020NHS activity and performance summary: December 2019 and January 2020
NHS activity and performance summary: December 2019 and January 2020
 
NHS activity and performance summary: November and December 2019
NHS activity and performance summary: November and December 2019NHS activity and performance summary: November and December 2019
NHS activity and performance summary: November and December 2019
 
NHS activity and performance summary: October and November 2019
NHS activity and performance summary: October and November 2019NHS activity and performance summary: October and November 2019
NHS activity and performance summary: October and November 2019
 
Well-being of Wales, 2019
Well-being of Wales, 2019Well-being of Wales, 2019
Well-being of Wales, 2019
 
NHS activity and performance summary: September and October 2019
NHS activity and performance summary: September and October 2019NHS activity and performance summary: September and October 2019
NHS activity and performance summary: September and October 2019
 
NHS activity and performance summary: August and September 2019
NHS activity and performance summary: August and September 2019NHS activity and performance summary: August and September 2019
NHS activity and performance summary: August and September 2019
 
NHS activity and performance summary: July and August 2019
NHS activity and performance summary: July and August 2019NHS activity and performance summary: July and August 2019
NHS activity and performance summary: July and August 2019
 
NHS activity and performance summary: June and July 2019
NHS activity and performance summary: June and July 2019NHS activity and performance summary: June and July 2019
NHS activity and performance summary: June and July 2019
 
Well-being of Wales, 2018: what do we know about children's well-being?
Well-being of Wales, 2018: what do we know about children's well-being?Well-being of Wales, 2018: what do we know about children's well-being?
Well-being of Wales, 2018: what do we know about children's well-being?
 
Well-being of Wales, 2018
Well-being of Wales, 2018Well-being of Wales, 2018
Well-being of Wales, 2018
 
NHS activity and performance summary: May and June 2019
NHS activity and performance summary: May and June 2019NHS activity and performance summary: May and June 2019
NHS activity and performance summary: May and June 2019
 
NHS activity and performance summary: April and May 2019
NHS activity and performance summary: April and May 2019NHS activity and performance summary: April and May 2019
NHS activity and performance summary: April and May 2019
 
New house building, April 2018 to March 2019
New house building, April 2018 to March 2019New house building, April 2018 to March 2019
New house building, April 2018 to March 2019
 
NHS activity and performance summary: March and April 2019
NHS activity and performance summary: March and April 2019NHS activity and performance summary: March and April 2019
NHS activity and performance summary: March and April 2019
 
Welsh Government Future Trends 2017: society and culture
Welsh Government Future Trends 2017: society and cultureWelsh Government Future Trends 2017: society and culture
Welsh Government Future Trends 2017: society and culture
 
Welsh Government Future Trends 2017: health
Welsh Government Future Trends 2017: healthWelsh Government Future Trends 2017: health
Welsh Government Future Trends 2017: health
 
Welsh Government Future Trends 2017: economy and infrastructure
Welsh Government Future Trends 2017:  economy and infrastructureWelsh Government Future Trends 2017:  economy and infrastructure
Welsh Government Future Trends 2017: economy and infrastructure
 
Welsh Government Future Trends 2017: population
Welsh Government Future Trends 2017: populationWelsh Government Future Trends 2017: population
Welsh Government Future Trends 2017: population
 
NHS activity and performance summary: February and March 2019
NHS activity and performance summary: February and March 2019NHS activity and performance summary: February and March 2019
NHS activity and performance summary: February and March 2019
 

Dernier

RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝DelhiRS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhijennyeacort
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsVICTOR MAESTRE RAMIREZ
 
RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.natarajan8993
 
Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)Cathrine Wilhelmsen
 
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degreeyuu sss
 
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一F sss
 
Call Girls In Dwarka 9654467111 Escorts Service
Call Girls In Dwarka 9654467111 Escorts ServiceCall Girls In Dwarka 9654467111 Escorts Service
Call Girls In Dwarka 9654467111 Escorts ServiceSapana Sha
 
Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Colleen Farrelly
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...Boston Institute of Analytics
 
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档208367051
 
INTERNSHIP ON PURBASHA COMPOSITE TEX LTD
INTERNSHIP ON PURBASHA COMPOSITE TEX LTDINTERNSHIP ON PURBASHA COMPOSITE TEX LTD
INTERNSHIP ON PURBASHA COMPOSITE TEX LTDRafezzaman
 
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样vhwb25kk
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectBoston Institute of Analytics
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfchwongval
 
Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Seán Kennedy
 
How we prevented account sharing with MFA
How we prevented account sharing with MFAHow we prevented account sharing with MFA
How we prevented account sharing with MFAAndrei Kaleshka
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanMYRABACSAFRA2
 
DBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdfDBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdfJohn Sterrett
 
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfPredicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfBoston Institute of Analytics
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPTBoston Institute of Analytics
 

Dernier (20)

RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝DelhiRS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business Professionals
 
RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.
 
Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)
 
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
 
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
 
Call Girls In Dwarka 9654467111 Escorts Service
Call Girls In Dwarka 9654467111 Escorts ServiceCall Girls In Dwarka 9654467111 Escorts Service
Call Girls In Dwarka 9654467111 Escorts Service
 
Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
 
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
 
INTERNSHIP ON PURBASHA COMPOSITE TEX LTD
INTERNSHIP ON PURBASHA COMPOSITE TEX LTDINTERNSHIP ON PURBASHA COMPOSITE TEX LTD
INTERNSHIP ON PURBASHA COMPOSITE TEX LTD
 
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis Project
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdf
 
Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...
 
How we prevented account sharing with MFA
How we prevented account sharing with MFAHow we prevented account sharing with MFA
How we prevented account sharing with MFA
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population Mean
 
DBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdfDBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdf
 
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfPredicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
 

Relative income poverty: Ethnicity and disability, financial year ending 2019

  • 1. Relative income poverty ethnicity and disability Relative income poverty Ethnicity and disability Financial year ending 2019
  • 2. Non-white ethnicity is linked with a greater likelihood of relative income poverty • In the latest period (2014-15 to 2018-19, an average of 5 financial years) people who were living in households where the head of the household was from a non-white ethnic group were more likely to be in relative income poverty compared with those where the head of the household was from a white ethnic group. • There was a 25 per cent likelihood of people from a non-white ethnic group living in relative income poverty compared to a 23 per cent likelihood for those from a white ethnic group in 2014-15 to 2018-19. • However, because the vast majority of households in Wales have a head who is from a white ethnic group, most people (98 per cent) who were living in relative income poverty were from such households. We were not able to produce robust figures for children or pensioners by ethnic group of head of household due to low sample sizes. For UK breakdowns by ethnic group please see the HBAI tables produced by the Department for Work and Pensions.
  • 3. Living with a person who has a disability makes relative income poverty more likely for children and working age people • In the survey data, disabled people are identified as those who report any physical or mental health condition or illness that are expected to last 12 months or more, and which limit their ability to carry out day-to-day activities a little, or a lot. This is in line with the Equality Act definition. • In the latest period (2016-17 to 2018-19), 37 per cent of children who lived in a household where there was someone with a disability were in relative income poverty compared with 24 per cent in households where no-one was disabled. • 31 per cent of working-age adults who lived in a household where there was someone with a disability were in relative income poverty compared with 18 per cent of those who lived in a household where no-one was disabled.