Welsh Index of Multiple Deprivation (WIMD) 2019: results report

Welsh Index of Multiple Deprivation

(WIMD) 2019

Results report

Contact

Nia Jones

Social Justice Statistics

Knowledge and Analytical Services

Welsh Government

Cathays Park

Cardiff CF10 3NQ

Tel: 0300 025 4088 Email: stats.inclusion@gov.wales

All content is available under the Open Government Licence v3.0, except where otherwise

stated.

Mae’r ddogfen yma hefyd ar gael yn Gymraeg / This document is also available in Welsh

Table of Contents

1. What is WIMD? ............................................................................................................. 2

2 WIMD 2019 Overall Index ............................................................................................. 7

3. Income Domain .......................................................................................................... 30

4. Employment Domain .................................................................................................. 39

5. Health Domain ............................................................................................................ 48

6. Education Domain ...................................................................................................... 57

7. Access to Services Domain ........................................................................................ 65

8. Housing Domain ......................................................................................................... 75

9. Community Safety Domain ......................................................................................... 84

10. Physical Environment Domain .................................................................................... 92

Annex A: Further background to WIMD ........................................................................... 101

Annex B: List of all indicators included in WIMD 2019...................................................... 103

We are grateful for the contributions of many people and organisations who have provided data and

advice for WIMD 2019.

1. What is WIMD?

The Welsh Index of Multiple Deprivation (WIMD) is the official measure of relative deprivation for

small areas in Wales. It is a National Statistic produced by statisticians at the Welsh Government.

WIMD identifies areas with the highest concentrations of several different types of deprivation. The

prime purpose of the Index is to provide the evidence needed about the most deprived areas of

Wales to inform a variety of decisions, such as funding or targeting of programmes and services for

local areas. WIMD ranks all small areas in Wales from 1 (most deprived) to 1,909 (least deprived).

1.1 What does WIMD measure?

WIMD is currently made up of eight separate domains (or types) of deprivation. Each domain is

compiled from a range of different indicators. The domains included in WIMD 2019 are:

 Income

 Employment

 Health

 Education

 Access to Services

 Housing

 Community Safety

 Physical Environment

WIMD is a measure of multiple deprivation that is both an area-based measure and a measure of

relative deprivation. Further explanation of these terms can be found in our WIMD 2019 Guidance,

but the key things to remember are, for WIMD:

 ‘Multiple’ refers to the multiple domains of the index, and also the way the indicators may

capture both material and social aspects of deprivation.

 ‘Deprivation’ does not just mean being poor. It refers to unmet need which is caused by a

lack of resources of other kinds, not just financial. It can mean having fewer resources and

opportunities than we might expect in our society, for example in terms of health or

education.

 The ranks are calculated for all Lower layer Super Output Areas (LSOAs) in Wales. There

are 1,909 LSOAs in Wales with an average population of 1,600 people each. Further

information on LSOAs is provided in the Technical Report.

 WIMD provides insight into area-based deprivation by measuring concentrations of

deprivation. However many non-deprived people live in deprived areas, and many deprived

people live in non-deprived areas.

 The Index provides a way of identifying areas in the order of most to least deprived. It does

not provide a measure of the level of deprivation in an area, but rather whether an area is

more or less deprived relative to all other areas in Wales.

 The Index methodology is designed to reliably distinguish between areas at the most

deprived end of the distribution, but not at the least deprived end. This means that

differences between the least deprived areas in Wales are less well defined than differences

between the more deprived areas.

1.2 How the Index is constructed

The Index has three main components:

 The 47 underlying indicator datasets

 Ranks for the eight separate domains (or types) of deprivation, created by combining

relevant indicators within each domain

 Overall WIMD ranks, created by combining the domain ranks

All of these components are calculated for each of the small areas (LSOAs) in Wales. The indicator

data, domain ranks, and overall ranks are published on StatsWales. A full list of the indicators

included in WIMD 2019 can be found in Annex B. Detailed technical information on the indicators

and WIMD methodology can be found in the Technical Report.

The methodology used within WIMD 2019 is broadly the same as for the last Index, produced in

2014, with the same eight domains of deprivation captured. However there have been some

changes to the Index, including:

 changes to individual indicators, or the inclusion of new indicators within the Health,

Education, Access to Services, Physical Environment and Housing domains

 small changes to the relative weights applied to the domains (or types) of deprivation.

WIMD is constructed from a weighted sum of the deprivation score for each domain. The weights

reflect the importance of the domain as an aspect of deprivation, and the quality of the indicators

available for that domain.

The domain weights for WIMD 2019 are shown below, alongside the weights used in 2014.

Improvements to data used for the Housing and Health domains led to a decision to make small

increases to their weights. To allow for this, weights for the Income and Employment domains were

reduced slightly. However those domains retain the highest relative weights, since they are strong

determinants of deprivation.

Spreading a small amount of the weight previously placed on Income and Employment into other

domains also reflects the wide range of well-being goals set out in the Well-being of Future

Generations Act (Wales) 2015.

WIMD 2019

domain weight

WIMD 2014

domain weight

Income

22%

23.5%

Employment

22%

23.5%

Health

15%

14%

Education

14%

Access to Services

10%

Housing

Community Safety

Physical Environment

1.3 What can WIMD be used for?

Knowing how deprivation is distributed across Wales is important for many organisations when

developing area-based policies, programmes and funding. WIMD can be used (often alongside

other information) to inform these decisions and give a greater understanding of deprivation

patterns within Wales. WIMD can be used for:

 Identifying the most deprived small areas

 Comparing relative deprivation of small areas

 Exploring the 8 domains (types) of deprivation for small areas

 Comparing the proportion of small areas within a larger area (e.g. local authority) that are

very deprived

 Using indicator data (but not the ranks) to compare absolute change over time

WIMD can also be used to look at the change in relative deprivation ranks between iterations, for

example which areas have left, joined or remained in the most deprived group. However care

should be taken in interpreting this for WIMD 2019. In order to produce the best possible snapshot

of relative deprivation, using the latest available data, we have changed some of the indicators,

domain weights, and the ONS have revised population estimates underlying some WIMD 2014

indicators. These refinements to the measurement of deprivation may have contributed to an area

becoming more (or less) deprived relative to others, rather than underlying shifts in relative

deprivation of areas since WIMD 2014.

Government programmes – national and local – aiming to tackle deprivation often use WIMD to

target activity on the most deprived areas. It is also used widely by local authorities, other public

bodies, the voluntary sector, academics and students, and the private sector. Examples of known

uses of the Index include:

 targeting policies, and locating services or pilot areas

 building area profiles

 making and assessing funding bids and grant applications

 measuring the effect of deprivation on outcomes like health inequalities

 linking indicators of area deprivation to surveys for use in analysis

 modelling likely demands e.g. on police forces and other emergency services

 informing widening access schemes

 evidencing local wellbeing and needs assessments

 designing sample surveys or other studies

The WIMD 2019 Guidance document provides further details on where to start if you want to use

WIMD to provide an area profile, or to target activity.

The Index is most useful when used with other information, either from the underlying indicators,

other published sources or local information. References to useful contextual information are

included at the end of each domain chapter. There are a number of sources of information on local

areas that may be useful to users. These include:

 Data on certain Welsh towns and communities made available through the Understanding

Welsh Places resource

 Data on local authorities made available through the Thriving Places Wales resource

 Labour Market and Census statistics for local areas made available through the Office for

National Statistics’ Nomis website

1.4 Limitations of WIMD

It is important to remember that WIMD is not the only way to measure deprivation. WIMD has been

developed for a particular purpose - to measure concentrations of deprivation at a small area level.

Below are some of the limitations of WIMD, and further details can be found in the WIMD 2019

Guidance. WIMD can’t be used for:

 Quantifying how deprived a small area is

 Saying how much more deprived one area is than another – the difference between two

ranks can be tiny or large

 Using ranks to infer absolute change over time (as they are relative measures)

 Identifying deprived people – not everyone who is deprived lives in a deprived area

 Comparing with other UK countries - each country measures deprivation slightly differently

 Measuring affluence (lack of deprivation is not the same as being affluent)

1.5 Further details

A package of products is available relating to WIMD 2019, including Guidance materials, a

Technical Report and an interactive website. Details of other current and planned publications are

available on the WIMD website. The WIMD 2019 overall ranks, domain ranks and underlying

indicator data are published on StatsWales.

For further information please contact stats.inclusi[email protected]ales.

1.6 Next update

WIMD is typically updated every 3 to 5 years, but the dates of publication for future Indices have not

yet been scheduled. Users can be kept informed of future developments by registering for e-mail

updates. To register, please e-mail stats.inclusion@gov.wales with ‘subscribe’ in the subject

heading.

2 WIMD 2019 Overall Index

2.1 Methodology: Overall Index

For a complete description of the construction of the Index, its domains, and the underlying

indicators, please see the WIMD 2019 Technical Report.

Domains

WIMD 2019 is made up of eight separate domains (or types) of deprivation. Each domain is

compiled from a range of different indicators. The weights for the eight domains are given below:

Methodological changes between WIMD 2014 and WIMD 2019

As explained in the introduction, the methodology used within WIMD 2019 is broadly the same as

for the last Index, produced in 2014, with the same eight domains of deprivation captured. However

there have been some changes to the Index, including:

 changes to individual indicators, and the inclusion of new indicators within the Health,

Education, Access to Services, Physical Environment and Housing domains

 small changes to the relative weights applied to the domains (or types) of deprivation.

These changes are described in more details in the relevant domain chapters, and in the WIMD

2019 Technical Report.

2.2 Overall Index key results

 In WIMD 2019, there were pockets of high relative deprivation in the South Wales cities and

valleys, and in some North Wales coastal and border towns. This is shown in the map that

follows.

 The overall picture is similar to that of WIMD 2014. Seven of the ten most deprived areas

from WIMD 2014 remained in the ten most deprived areas in WIMD 2019.

 The most deprived small area in Wales in WIMD 2019 was Rhyl West 2 (the area around

Rhyl High Street) in Denbighshire, which was ranked second most deprived in WIMD 2014.

The neighbouring area of Rhyl West 1 is now ranked second most deprived.

 The former most deprived area in WIMD 2014, St James 3 (which contains a large part of

the Lansbury Park estate in Caerphilly) is now ranked third most deprived.

 The local authority with the highest proportion of small areas in the most deprived 10% in

Wales in WIMD 2019 was Newport (24.2%). Blaenau Gwent had the highest percentage of

areas in the most deprived 50% in Wales (85.1%).

 Monmouthshire had no areas in the most deprived 10%, and Powys only 1.3% (or 1 area).

 Analysis of deep-rooted deprivation looks at areas that have remained in the top 50 most

deprived for all WIMD iterations in the past 15 years. There are 26 small areas in deep-

rooted deprivation, spread across ten Local Authorities.

2.3 Comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

WIMD cannot be used to compare deprivation for one area with its deprivation in a previous

iteration of the Index. However, the following analysis provides an illustration of how the deprivation

groups of WIMD 2019 compare with WIMD 2014. A similar approach has been used in the other

analysis sections.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The deprivation groups are used within the main WIMD analyses,

including maps. They are designed to have smaller groups at the more deprived end, where the

difference between areas is greater than at the less deprived end.

The diagonal, in bold, shows the number of areas which have remained in the same deprivation

group. Above the diagonal are numbers of areas which have moved from a more to a less deprived

group. Below the diagonal are the numbers of areas which have moved from a less to a more

deprived group.

Table 1: Deprivation group movements for the Overall Index, between WIMD 2014

and WIMD 2019

Most areas have remained in the same deprivation group between WIMD 2014 and WIMD 2019 (on

the diagonal). Only three areas have changed by more than one deprivation group. However the

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

165 25 1 0 0 191

10-20% most

deprived

(ranks 192-382)

25 130 35 1 0 191

20-30% most

deprived

(ranks 383-573)

1 36 112 42 0 191

30-50% most

deprived

(ranks 574-955)

0 0 43 284 55 382

50% least

deprived

(ranks 956-1909)

0 0 0 55 899 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

WIMD domain 2019

WIMD domain 2014

ranks are relative, and no conclusion about changes to the levels of deprivation can be drawn from

changes to the Index ranks. The underlying indicators, which measure various types of deprivation,

can be analysed in order to understand how levels of deprivation have changed in individual areas.

Of the three areas that have moved by two deprivation groups, one moved from the 20-30% most

deprived in WIMD 2014 to the top 10% most deprived in 2019. This area is Colwyn 2, which is

located around the Tan-y-Lan and Penmaen Head area of Old Colwyn in Conwy, and its overall

rank changed from 522 in 2014 to 190 in 2019. It became relatively more deprived in five domains,

in the following order of greatest to smallest change: Health, Income, Employment, Community

Safety and Education.

The other two areas that moved a notable amount became relatively less deprived.

 Blackmill 2, in the Ogmore Valley (Bridgend), moved from the top 10% most deprived group

in WIMD 2014 to the 20-30% most deprived group in WIMD 2019. Its overall Index rank

changed from 171 in 2014 to 392 in 2019. This area became relatively less deprived in

seven of the domains, in the following order of greatest to smallest change: Community

Safety, Education, Health, Access to Services, Employment, Physical Environment and

Income. However, it became relatively more deprived in Housing (note that the

measurement of housing deprivation has changed).

 Tonyrefail West 1 covers Edmondstown and part of Penrhiwfer, south of Tonypandy in

Rhondda Cynon Taf. It moved from the 10-20% most deprived group in WIMD 2014 to the

30-50% most deprived group in WIMD 2019, and its overall Index rank changed from 280 to

577. This area became relatively less deprived in seven domains, in the following order of

greatest to smallest change: Community Safety, Physical Environment, Education, Health,

Employment, Access to Services and Income.

2.4 Analysis of the most deprived areas in WIMD 2019

The table below lists the ten most deprived areas in Wales, as determined by WIMD 2019, together

with three areas that were ranked between 1 and 10 in WIMD 2014, but have moved out of that

group in WIMD 2019.

Note that WIMD does not measure the level of deprivation in a small area, but rather whether an

area is more or less deprived relative to all other small areas in Wales. It is not possible to

determine from a change in rank alone whether deprivation has improved or not in an area, but the

underlying indicators may be used for this.

For example, most areas have seen decreases in the rate of employment deprivation between

indices. Overall, the rate of employment deprivation

decreased from 13% in WIMD 2014 to 10% in

WIMD 2019. Areas that rank highly compared to other areas may have seen decreases in absolute

deprivation since WIMD 2014.

Table 2: WIMD 2019 most deprived areas

The employment deprivation indicator measures the rate of working age people in receipt of Jobseekers

Allowance, Employment Support Allowance, or on Universal Credit and not in work. Changes to the welfare

system since WIMD 2014 mean that eligibility thresholds and criteria for some benefits have changed.

LSOA Local authority LSOA name

WIMD 2014

Rank

WIMD 2019

Rank

W01000240 Denbighshire Rhyl West 2 2 1

W01000239 Denbighshire Rhyl West 1 11 2

W01001421 Caerphilly St. James 3 1 3

W01001274 Rhondda Cynon Taf Tylorstown 1 5 4

W01000991 Bridgend Caerau (Bridgend) 1 6 5

W01001209 Rhondda Cynon Taf Penrhiwceiber 1 15 6

W01001308 Merthyr Tydfil Penydarren 1 14 7

W01001428 Caerphilly Twyn Carno 1 7 8

W01000413 Wrexham Queensway 1 3 9

W01001662 Newport Pillgwenlly 4 10 10

W01001874 Cardiff Splott 6 4 12

W01001303 Merthyr Tydfil Merthyr Vale 2 8 34

W01001222 Rhondda Cynon Taf Pen-y-waun 2 9 15

 Rhyl West 2, Denbighshire was the most deprived small area in Wales (it was ranked 2 in

WIMD 2014).

 Seven of the ten most deprived areas in WIMD 2014 remained in the most deprived ten

areas in WIMD 2019.

 Three areas have moved out of the most deprived ten areas since WIMD 2014.

We look at the ten most deprived areas (and those that have left the top 10) in greater detail below,

providing additional context about the areas.

As part of these descriptions we make reference to “area classifications” published by the Office for

National Statistics (ONS), which use socio-economic and demographic data from each census to

identify areas of the country with similar characteristics, and place them into groups based on

statistical techniques. After the 2011 Census, super output areas were classified into supergroups,

and beneath them, groups. Some examples of supergroups are “hard-pressed communities” or

“countryside living”. Data on super output area cluster membership are published on the ONS

website, as well as pen portraits of the different groups.

We also make reference to the following sources:

 2017 LSOA Population estimates on StatsWales

 Key statistics from the 2011 Census

 WIMD 2019 indicator data on income deprivation

1. Rhyl West 2, Denbighshire

Rhyl West 2, around Rhyl High Street, is

the most deprived small area in Wales

according to WIMD 2019. Its WIMD 2019

deprivation profile shows that Rhyl West

2 lies within the 10 most deprived areas

for the Income, Employment, Health,

Education and Community Safety

domains. It also lies within the 10% most

deprived (the top 191 areas) in terms of

Housing. WIMD indicator data shows that

61% of people in Rhyl West 2 were in

income deprivation in 2016-17.

The area was previously ranked 2

(second most deprived) in WIMD 2014. It

is one of the areas of “deep-rooted”

deprivation described in section 2.6,

which identifies areas that have

consistently been in the top 50 most deprived areas since WIMD 2005. Rhyl West 2 has been

ranked 1 or 2 (first or second most deprived area) in each iteration of the Index since WIMD 2005.

Population estimates for 2017 show that 20% of the area’s population are aged under 16, and a

further 67% aged 16-64 (higher than the Wales average of 18% and 62%, respectively). The 2011

Census showed:

 nearly 80% of housing was rented: 49% private rented and 30% social rented households

(compared to 14% and 16% for Wales, respectively)

 a higher than average proportion of one person households (60% compared to 31% for

Wales)

 77% of dwellings were flats, maisonettes or apartments (13% for Wales), as opposed to a

whole house

 a higher than average percentage of people from a non-white ethnic group (6.2% compared

to 4.4% across Wales)

 nearly 10% of residents were born outside the UK (5.5% across Wales)

 Census area classifications place Rhyl West 2 in the “hard-pressed communities” category

(and the “constrained renters” group), which has the highest rate of unemployment across

categories

2. Rhyl West 1, Denbighshire

Rhyl West 1, the central terraced

housing area which neighbours Rhyl

West 2 (above), is the second most

deprived small area in Wales

according to WIMD 2019. Its WIMD

2019 deprivation profile shows that

Rhyl West 1 lies within the 10 most

deprived areas for the Income,

Employment, and Health domains. It

also lies within the 10% most deprived

(the top 191 areas) in terms of

Education, Housing and Community

Safety. WIMD indicator data shows

that 50% of people in Rhyl West 1

were in income deprivation in 2016-17.

The area was previously ranked 11 in

WIMD 2014. It is one of the areas of

“deep-rooted” deprivation described in section 2.6, which identifies areas that have consistently

been in the top 50 most deprived areas since WIMD 2005. Rhyl West 1 has been ranked within the

12 most deprived areas for each iteration of the Index since WIMD 2005.

Population estimates for 2017 show that over 20% of the area’s population are aged under 16, and

a further 66% aged 16-64 (higher than the Wales average of 18% and 62%, respectively). The 2011

Census showed:

 70% of housing was rented: 44% private rented and 26% social rented households

(compared to 14% and 16% for Wales, respectively)

 a higher than average proportion of one person households (53% compared to 31% for

Wales)

 64% of dwellings were flats, maisonettes or apartments (13% for Wales), as opposed to a

whole house

 a higher than average percentage of people from a non-white ethnic group (8.6% compared

to 4.4% across Wales)

 nearly 11% of residents were born outside the UK (5.5% across Wales)

 Census area classifications place Rhyl West 1 in the “hard-pressed communities” category

(and the “constrained renters” group), which has the highest rate of unemployment across

categories.

3. St. James 3, Caerphilly

St James 3 in Caerphilly contains

a large part of the Lansbury Park

estate. Its WIMD 2019 deprivation

profile shows that St James 3 lies

within the 10 most deprived areas

for the Income, Employment and

Health domains. It also lies within

the 10% most deprived (the top

191 areas) in terms of Education,

Community Safety and Physical

Environment. WIMD indicator data

shows that 47% of people in St

James 3 were in income

deprivation in 2016-17.

The area was previously ranked 1

(most deprived) in WIMD 2014. It

is one of the areas of “deep-

rooted” deprivation described in section 2.6, which identifies areas that have been in the top 50

most deprived consistently since WIMD 2005. St James 3 has been in the top 9 most deprived

areas since WIMD 2008 (in WIMD 2005 it was ranked 18).

Population estimates for 2017 show that 24% of the area’s population are aged under 16, higher

than the Wales average of 18%. The 2011 Census showed:

 77% of housing was rented, mostly social rented which accounted for 70% of housing

(compared to 16% social rented across Wales)

 slightly higher than average proportions of one person households (38% compared to 31%

for Wales) and of households with dependent children (35% compared to 28% for Wales)

 34% of dwellings were flats, maisonettes or apartments (13% for Wales), as opposed to a

whole house

 Census area classifications place St James 3 in the “hard-pressed communities” category

(and “challenged white communities” group), which has the highest rate of unemployment

across categories

4. Tylorstown 1, Rhondda Cynon Taf

Tylorstown 1, is around the

Penrhys area of the Rhondda

valley. Its WIMD 2019 deprivation

profile shows that Tylorstown 1

lies within the 10 most deprived

areas for the Income and Health

domains. It also lies within the

10% most deprived (the top 191

areas) in terms of Employment,

Education and Community

Safety. WIMD indicator data

shows that 47% of people in

Tylorstown 1 were in income

deprivation in 2016-17.

The area was previously ranked

5 in WIMD 2014. It is one of the

areas of “deep-rooted”

deprivation described in section

2.6, which identifies areas that

have consistently been in the top 50 most deprived areas since WIMD 2005. Tylorstown 1 has

become relatively more deprived with each iteration of the Index since WIMD 2005.

Population estimates for 2017 show that 26% of the area’s population are aged under 16, higher

than the Wales average of 18%. The 2011 Census showed:

 57% of housing was rented, mostly social rented which accounted for 42% of housing

(compared to 16% social rented across Wales)

 slightly higher than average proportions of one person households (36% compared to 31%

for Wales) and of households with dependent children (34% compared to 28% for Wales)

 Census area classifications place Tylorstown 1 in the “hard-pressed communities” category

(and “challenged white communities” group), which has the highest rate of unemployment

across categories

5. Caerau (Bridgend) 1, Bridgend

Caerau (Bridgend) 1, covers

Caerau Park and the Tudor

Estate. Its WIMD 2019

deprivation profile shows that

the area lies within the 10 most

deprived areas for the

Employment and Health

domains, it is ranked 1 (most

deprived) on Health. It also lies

within the 10% most deprived

(the top 191 areas) in terms of

Income, Education and

Community Safety. WIMD

indicator data shows that 46% of

people in Caerau 1 were in

income deprivation in 2016-17.

The area was previously ranked

6 in WIMD 2014. It is one of the

areas of “deep-rooted”

deprivation described in section

2.6, which identifies areas that have consistently been in the top 50 most deprived areas since

WIMD 2005. Caerau 1 has become relatively more deprived with each iteration of the Index since

WIMD 2005.

Population estimates for 2017 show that 26% of the area’s population are aged under 16, higher

than the Wales average of 18%. The 2011 Census showed:

 49% of housing was rented, mostly social rented which accounted for 39% of housing

(compared to 16% social rented across Wales)

 a slightly higher than average proportion of households with dependent children (32%

compared to 28% for Wales)

 Census area classifications place Caerau (Bridgend) 1 in the “hard-pressed communities”

category (and “challenged white communities” group), which has the highest rate of

unemployment across categories

6. Penrhiwceiber 1, Rhondda Cynon Taf

Penrhiwceiber 1 spans the

village of Perthcelyn and part of

Penrhiwceiber. Its WIMD 2019

deprivation profile shows that

Penrhiwceiber 1 lies within the 10

most deprived areas for the

Health and Education domains. It

also lies within the 10% most

deprived (the top 191 areas) in

terms of Income and

Employment. WIMD indicator

data shows that 45% of people in

Penrhiwceiber 1 were in income

deprivation in 2016-17.

The area was previously ranked

15 in WIMD 2014. It is one of the

areas of “deep-rooted”

deprivation described in section

2.6, which identifies areas that

have consistently been in the top 50 most deprived areas since WIMD 2005. Penrhiwceiber 1 has

been ranked within the top 15 most deprived areas since WIMD 2005.

Population estimates for 2017 show that 24% of the area’s population are aged under 16, higher

than the Wales average of 18%. The 2011 Census showed:

 48% of housing was rented, mostly social rented which accounted for 35% of housing

(compared to 16% social rented across Wales)

 a higher than average proportion of households with dependent children (37% compared to

28% for Wales)

 Census area classifications place Penrhiwceiber 1 in the “hard-pressed communities”

category (and “challenged white communities” group), which has the highest rate of

unemployment across categories

7. Penydarren 1, Merthyr Tydfil

Penydarren 1 is the Galon Uchaf

area of Merthyr Tydfil. Its WIMD

2019 deprivation profile shows that

Penydarren 1 lies within the 10

most deprived areas for the

Income and Education domains. It

also lies within the 10% most

deprived (the top 191 areas) in

terms of Employment, Health and

Housing. WIMD indicator data

shows that 46% of people in

Penydarren 1 were in income

deprivation in 2016-17.

The area was previously ranked 14

in WIMD 2014. It is one of the

areas of “deep-rooted” deprivation

described in section 2.6, which

identifies areas that have

consistently been in the top 50

most deprived areas since WIMD 2005. Penydarren 1 has been ranked within the top 14 most

deprived areas since WIMD 2005.

Population estimates for 2017 show that 27% of the area’s population are aged under 16, higher

than the Wales average of 18%. The 2011 Census showed:

 57% of housing was rented, mostly social rented which accounted for 50% of housing

(compared to 16% social rented across Wales)

 a much higher than average proportion of households with dependent children (48%

compared to 28% for Wales)

 nearly all dwellings were whole houses (98%, mainly semi-detached) as opposed to flats etc,

a higher proportion than across Wales (87%)

 Census area classifications place Penydarren 1 in the “hard-pressed communities” category

(and “challenged white communities” group), which has the highest rate of unemployment

across categories

8. Twyn Carno 1, Caerphilly

Twyn Carno 1, is at the North end of

the town of Rhymney. Its WIMD 2019

deprivation profile shows that Twyn

Carno 1 lies within the 10 most

deprived areas for the Employment

and Education domains. It also lies

within the 10% most deprived (the top

191 areas) in terms of Income,

Health, and Community Safety.

WIMD indicator data shows that 43%

of people in Twyn Carno 1 were in

income deprivation in 2016-17.

The area was previously ranked 7 in

WIMD 2014. It is one of the areas of

“deep-rooted” deprivation described

in section 2.6, which identifies areas

that have consistently been in the top

50 most deprived areas since WIMD

2005. Twyn Carno 1 has been ranked within the top 8 most deprived areas since WIMD 2005.

Population estimates for 2017 show that 24% of the area’s population are aged under 16, higher

than the Wales average of 18%. The 2011 Census showed:

 61% of housing was rented, mostly social rented which accounted for 57% of housing

(compared to 16% social rented across Wales)

 a higher than average proportion of households with dependent children (38% compared to

28% for Wales)

 a slightly higher proportion of dwellings were flats, maisonettes or apartments, as opposed to

a whole house (18% compared to 13% for Wales)

 Census area classifications place Twyn Carno 1 in the “hard-pressed communities” category

(and “challenged white communities” group), which has the highest rate of unemployment

across categories

9. Queensway 1, Wrexham

Queensway 1 is an area of the Caia

Park Community in Wrexham. Its

WIMD 2019 deprivation profile shows

that Queensway 1 lies within the 10

most deprived areas for the Income,

Education and Community Safety

domains. It also lies within the 10%

most deprived (the top 191 areas) in

terms of Employment and Health.

WIMD indicator data shows that 47%

of people in Queensway 1 were in

income deprivation in 2016-17.

The area was previously ranked 3

(third most deprived) in WIMD 2014. It

is one of the areas of “deep-rooted”

deprivation described in section 2.6,

which identifies areas that have

consistently been in the top 50 most deprived areas since WIMD 2005. Queensway 1 has been

ranked within the top 9 most deprived areas since WIMD 2005.

Population estimates for 2017 show that 36% of the area’s population are aged under 16, much

higher than the Wales average of 18%. The 2011 Census showed:

 86% of housing was rented, mostly social rented which accounted for 85% of housing

(compared to 16% social rented across Wales)

 half of households had dependent children in them, which is much higher than average (28%

for Wales)

 24% of dwellings were flats, maisonettes or apartments (13% for Wales), as opposed to a

whole house

 a slightly higher than average percentage of residents were born outside the UK (6.7%

compared to 5.5% across Wales)

 Census area classifications place Queensway 1 in the “hard-pressed communities” category

(and “challenged white communities” group), which has the highest rate of unemployment

across categories

10. Pillgwenlly 4, Newport

Pillgwenlly 4 is a densely populated

area to the south of Cardiff Road in

the Pillgwenlly Community of Newport.

Its WIMD 2019 deprivation profile

shows that the area lies within the 10

most deprived areas for the

Community Safety domain. It also lies

within the 10% most deprived (the top

191 areas) in terms of Income,

Employment, and Health domains.

WIMD indicator data shows that 44%

of people in Pillgwenlly 4 were in

income deprivation in 2016-17.

The area was also ranked 10 in WIMD

2014. However, it is not one of the

areas of “deep-rooted” deprivation

described in section 2.6, which

identifies areas that have consistently been in the top 50 most deprived areas since WIMD 2005.

This is because its rank was 65 in WIMD 2005. Since WIMD 2008, it has ranked within the top 27

most deprived areas.

Population estimates for 2017 show that 24% of the area’s population are aged under 16, higher

than the Wales average of 18%. The 2011 Census showed:

 74% of housing was rented, mostly social rented which accounted for 60% of housing

(compared to 16% social rented across Wales)

 a higher than average proportion of one person households (50% compared to 31% for

Wales), and slightly higher proportion where all residents were aged 65+ (24% compared to

23% across Wales)

 53% of dwellings were flats, maisonettes or apartments (13% for Wales), as opposed to a

whole house

 a much higher than average percentage of people from a non-white ethnic group (46.9%

compared to 4.4% across Wales)

 27% of residents were born outside the UK (5.5% across Wales)

 Census area classifications place Pillgwenlly 4 in the “multicultural living” category (and the

“urban cultural mix” group)

Areas that have moved out of the 10 most deprived since WIMD 2014

Splott 6, Cardiff

Splott 6 covers the area around East Tyndall Street and Ocean Way in south-east Cardiff. The area

now ranks at 12, but was previously ranked 4 in WIMD 2014. This change was driven by a decrease

in relative deprivation on Income and Education, amongst other domains.

Its WIMD 2019 deprivation profile shows that Splott 6 still lies within the 10% most deprived areas

for all domains except Access to Services. Although it is not one of the areas of “deep-rooted”

deprivation described in section 2.6 (those areas consistently in the 50 most deprived), this is

because it ranked just outside the 50 most deprived areas in WIMD 2005 (at 54) and WIMD 2008

(at 51).

Merthyr Vale 2, Merthyr Tydfil

Merthyr Vale 2 covers the majority of the village of Merthyr Vale on the banks of the river Taff. The

area now ranks 34, but was previously ranked 8 in WIMD 2014. This change was driven by a

decrease in relative deprivation on all five of the highest weighted domains (Income, Employment,

Health, Education and Access to Services), as well as on Community safety.

Its WIMD 2019 deprivation profile shows that Merthyr Vale 2 still lies within the 10% most deprived

areas for all domains except Access to Services and Community Safety. It is one of the areas of

“deep-rooted” deprivation described in section 2.6, which identifies areas that have consistently

been in the top 50 most deprived areas since WIMD 2005. WIMD 2014 was the only instance where

the area fell within the 10 most deprived areas.

Pen-y-waun 2, Rhondda Cynon Taf

Pen-y-waun 2 is in the Pen-y-waun community at the top of the Cynon valley. The area now ranks

15, but was previously ranked 9 in WIMD 2014. This change was driven by a decrease in relative

deprivation on Income, Employment, and Health.

Its WIMD 2019 deprivation profile shows that Pen-y-waun 2 ranks third on the Education domain,

and also still within the 10% most deprived areas for the Income, Employment, and Health domains.

It is one of the areas of “deep-rooted” deprivation described in section 2.6, which identifies areas

that have consistently been in the top 50 most deprived areas since WIMD 2005. Pen-y-waun 2 has

been ranked within the top 19 most deprived areas since WIMD 2005.

2.5 WIMD 2019 local authority analysis

The chart below shows the spread of WIMD 2019 ranks for each local authority in Wales. The blue

boxes contain half the total number of small areas in each local authority, centred on the median

(middle) rank for each local authority and the ‘whiskers’ show the full range of ranks. Deprivation

increases with decreasing rank (that is, towards the bottom of the plot).

Chart 1: Box plot of WIMD 2019 Overall ranks, by local authority

The table below shows, for the WIMD 2019 overall Index, the percentage of small areas (LSOAs) in

each local authority which were in the most deprived 10%, 20%, 30% and 50% areas in Wales.

Table 3: Concentrations of WIMD 2019 deprived areas, by local authority

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc.) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

The local authority with the highest proportion of areas in the most deprived 10% in Wales in WIMD

2019 was Newport (24.2% or 23 areas).

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 2.3 13.6 18.2 38.6

Gwynedd 73 2.7 5.5 8.2 34.2

Conwy 71 5.6 12.7 19.7 40.8

Denbighshire 58 12.1 15.5 22.4 46.6

Flintshire 92 3.3 10.9 19.6 31.5

Wrexham 85 7.1 11.8 28.2 41.2

Powys 79 1.3 6.3 11.4 24.1

Ceredigion 46 2.2 4.3 6.5 45.7

Pembrokeshire 71 5.6 11.3 15.5 42.3

Carmarthenshire 112 4.5 10.7 26.8 54.5

Swansea 148 11.5 23.6 31.1 45.9

Neath Port Talbot 91 15.4 33.0 45.1 69.2

Bridgend 88 6.8 20.5 39.8 55.7

Vale of Glamorgan 79 3.8 12.7 19.0 35.4

Rhondda Cynon Taf 154 17.5 28.6 45.5 71.4

Merthyr Tydfil 36 22.2 30.6 50.0 77.8

Caerphilly 110 10.0 23.6 38.2 62.7

Blaenau Gwent 47 12.8 44.7 63.8 85.1

Torfaen 60 5.0 31.7 41.7 56.7

Monmouthshire 56 0.0 1.8 5.4 19.6

Newport 95 24.2 34.7 40.0 60.0

Cardiff 214 18.2 27.6 34.6 49.1

Wales 1909 10 20 30 50

Monmouthshire had none of its areas in the most deprived 10% and only 19.6% (or 11 areas) in the

most deprived 50% in Wales.

Blaenau Gwent had the highest percentage of areas in the most deprived 50% in Wales (85.1% or

40 areas). The next highest was Merthyr Tydfil, with 77.8% (or 28) of its areas in the most deprived

half of Wales.

In general, the valleys and urban local authorities have higher concentrations of multiple

deprivation. This is discussed further in the WIMD 2014 article on analysing deprivation in rural

areas, due to be updated with WIMD 2019 analysis in early 2020.

2.6 Deep-Rooted Deprivation

Small areas (lower layer super output areas or LSOAs) of ‘deep-rooted’ deprivation are those that

have remained within the top 50 most deprived, roughly equal to the top 2.6% of small areas in

Wales for the last five publications of WIMD rankings (WIMD 2005, 2008, 2011, 2014 and 2019).

This means that across a period of 15 years, the small areas that fall into this category are

considered the most deprived, as they have consistently ranked in the top 50 out of 1,909 small

areas in Wales. The analysis only looks at rankings as far back as WIMD 2005 as this was the first

Index based on the current geography of LSOAs.

Since WIMD is a measure of relative deprivation, it doesn’t give an indication of the level of

deprivation in these small areas. The small areas that fall into the deep-rooted deprivation category

may have seen a decrease in levels of deprivation since WIMD 2005, but are still some of the most

deprived when compared against other small areas in Wales.

In total, there are 26 small areas that are in deep-rooted deprivation, representing roughly 1.4% of

all small areas in Wales. These are listed in the table below, ordered by their WIMD 2019 Overall

rank, and also shown in the map below.

Of the small areas listed, three have been ranked within the top 10 most deprived since WIMD 2005

(Rhyl West 2, Twyn Carno 1, Queensway 1). In addition to these three small areas, a further five

(Rhyl West 1, St. James 3, Penrhiwceiber 1, Penydarren 1, Pen-y-waun 2) make up the eight small

areas that have consistently been ranked within the top 20 most deprived.

The 26 small areas of deep-rooted deprivation are spread across ten Local Authorities; the highest

number of which are found in Swansea. These eight small areas located in Swansea account for

almost a third (31%) of those consistently ranking within the top 50 most deprived, twice as many as

the Local Authorities with the next highest number (Rhondda Cynon Taf and Caerphilly, with four

small areas each).

Table 4: Small areas of Deep-Rooted Deprivation

There are 12 Local Authorities with no small areas of deep-rooted deprivation (Isle of Anglesey,

Gwynedd, Conwy, Flintshire, Powys, Ceredigion, Pembrokeshire, Carmarthenshire, Vale of

Glamorgan, Torfaen, Newport, and Monmouthshire). This does not mean that there aren’t currently

any very deprived areas in these Local Authorities.

Twenty-two of the small areas identified as being in deep-rooted deprivation are classed as being in

Urban (City and Town) areas, representing 85% of the total. The remaining 4 (15%) are classed as

Rural (Town and Fringe) areas.

All but one of the 26 are located within a named Built Up Area, with the most being found in

Swansea (8) followed by Rhyl (3) and Caerphilly (2). Other Built Up Areas with one small area of

deep-rooted deprivation each are Abercynon, Aberfan, Bargoed, Cardiff, Hirwaun, Maesteg, Merthyr

Tydfil, Mountain Ash, Rhymney, Tredegar, Tylorstown and Wrexham. The area in deep-rooted

deprivation but not in a Built Up Area is Cymmer 2 in Neath Port Talbot, centred around the village

of Croeserw.

LSOA Local Authority LSOA Name WIMD 2019 Rank

W01000240 Denbighshire Rhyl West 2 1

W01000239 Denbighshire Rhyl West 1 2

W01001421 Caerphilly St. James 3 3

W01001274 Rhondda Cynon Taf Tylorstown 1 4

W01000991 Bridgend Caerau (Bridgend) 1 5

W01001209 Rhondda Cynon Taf Penrhiwceiber 1 6

W01001308 Merthyr Tydfil Penydarren 1 7

W01001428 Caerphilly Twyn Carno 1 8

W01000413 Wrexham Queensway 1 9

W01001222 Rhondda Cynon Taf Pen-y-waun 2 15

W01000863 Swansea Townhill 2 16

W01000862 Swansea Townhill 1 18

W01000237 Denbighshire Rhyl South West 2 19

W01000832 Swansea Penderry 3 22

W01000742 Swansea Castle 1 23

W01001739 Cardiff Ely 3 24

W01001339 Caerphilly Bargoed 4 29

W01000830 Swansea Penderry 1 31

W01000864 Swansea Townhill 3 32

W01001144 Rhondda Cynon Taf Abercynon 2 33

W01001303 Merthyr Tydfil Merthyr Vale 2 34

W01001479 Blaenau Gwent Tredegar Central and West 2 35

W01000817 Swansea Mynyddbach 1 37

W01000921 Neath Port Talbot Cymmer (Neath Port Talbot) 2 38

W01001345 Caerphilly Bedwas Trethomas and Machen 6 43

W01000833 Swansea Penderry 4 48

3. Income domain

3.1. Introduction

The purpose of this domain is to measure the proportion of people with income below a defined

level. The domain has a relative weight of 22% in the overall index. For a complete description of

the construction of the domain, please see the WIMD 2019 Technical Report.

3.2. Indicator

The domain contains a single composite indicator, income deprivation, made up of four elements:

 Income related benefit claimants; this includes Income Support claimants, Jobseeker's

Allowance claimants, Pension Credit claimants, and Income Based Employment and

Support Allowance claimants; and their dependent children. Sourced from the Department

for Work and Pensions (DWP). The data are based on an average of the individuals who

were in receipt of these benefits during the financial year 2016-17. Individuals who are in

receipt of multiple benefits are only counted once within this element.

 The number of children and adults within families that are in receipt of Working Tax Credits

and Child Tax Credits with an income which is less than 60% of the median income for

Wales (Before Housing Costs). Sourced from Her Majesty’s Revenue & Customs (HMRC),

using 2015/16 tax credits data as at 31

August 2015.

 Supported Asylum Seekers i.e. those who were supported under Section 95 of the

Immigration and Asylum Act, and their dependent children. Sourced from the Home Office,

as at 30

June 2017.

 People on Universal Credit and their dependent children. We exclude those who are

"working with no requirements" according to the dataset's "conditionality" marker. Sourced

from DWP, as at 2016-17.

The indicators are summed and expressed as a percentage of the residential population of the area.

The residential population estimates are sourced from the Mid-2016 Small Area Population

Estimates, published by the Office for National Statistics. We subtract the prison population as at

mid-2016 (sourced from Ministry of Justice) from the population estimates, for the four areas

containing prisons.

The resulting composite indicator is a cross-sectional snapshot of people in income deprivation,

measured by receipt of certain income-related benefits or tax credits.

The weight of the domain has reduced from 23.5% to 22% for WIMD 2019. This reflects the

increased lag in the currency of the data we are able to use (due to the impact of introducing

Universal Credit on a staggered basis), and a desire to slightly increase weights of other key

domains now with improved data (health and housing).

Full technical information on the indicator is available in the WIMD 2019 Technical Report.

3.3. Income domain key results

 In the WIMD 2019 income domain, there were pockets of high income deprivation in the

South Wales valleys and large cities, and in some North Wales coastal towns. This is shown

in the map below.

 All local authorities except Monmouthshire had at least some areas with over 30% of people

in income deprivation (equivalent to being in the most deprived 10% of areas).

 The local authorities with the highest proportion of areas in the most deprived 10% were

Newport, Merthyr Tydfil and Cardiff, all at around 20%. Monmouthshire had no areas in the

most deprived 10%.

 For the income domain, the most deprived area in Wales was Rhyl West 2, Denbighshire

(around Rhyl High Street), the same as for WIMD 2014. Eight of the 10 most deprived areas

in WIMD 2019 were also in the 10 most deprived areas in WIMD 2014.

 The overall patterns of income deprivation in WIMD 2019 are similar to those for WIMD

2014.

 21.6% of people who are income deprived are in the most deprived 10% of small areas for

the income domain (the areas ranked 1-191).

 Just over half of those who are income deprived are in the most deprived 28.6% of areas for

the income domain.

 Overall, the rate of income deprivation for WIMD 2019 was slightly lower than for WIMD

2014 (16 compared to 17%). Although the majority of small areas saw a decrease in the rate

of income deprivation, many saw stagnation or small increases.

3.4. Income domain comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved from a more to a less deprived group. Below the diagonal are the numbers of areas which

have moved from a less to a more deprived group.

Table 5: Movement between income deprivation group between WIMD 2014 and 2019

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

166 23 1 1 0 191

10-20% most

deprived

(ranks 192-382)

24 135 30 2 0 191

20-30% most

deprived

(ranks 383-573)

1 33 109 48 0 191

30-50% most

deprived

(ranks 574-955)

0 0 51 281 50 382

50% least

deprived

(ranks 956-1909)

0 0 0 50 904 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Income domain 2019

Income domain 2014

Relatively more deprived: One area has moved from the 20-30% most deprived group to the 10%

most deprived group in WIMD 2019. This was Colwyn 2 in Old Colwyn (Conwy), where 35% of

people were in income deprivation in the latest figures (for 2016-17).

Relatively less deprived: Four areas have become relatively less deprived by more than one

deprivation group, between WIMD 2014 and WIMD 2019. Two of these were in Llanrumney

(Cardiff), one in Barry and one in Mold.

Distribution of the Income deprived population in WIMD 2019

The chart below shows the ranks and indicator values for the income domain in WIMD 2019.

Chart 2: WIMD 2019 Income domain distribution

The plot shows that, at the most deprived end of the distribution, there is a steep increase in the

percentage of people that are income deprived. There is a wide range in the percentage of people

who are income deprived within the most deprived 10% of areas. The percentages range from 61%

for Rhyl West 2, Denbighshire (the area ranked 1), to 30% for Sandfields West 4, Port Talbot (the

area ranked 191).

The table below puts these numbers into context. The most deprived 10% of areas contains 21.6%

of people who are income deprived within Wales. Just over half of people who are income deprived

can be found in the most deprived 28.6% of areas for the income domain.

Table 6: Distribution of the Income deprived population, WIMD 2019

3.5. Income domain local authority analysis

The chart below shows the spread of income domain ranks for each local authority in Wales. The

blue boxes contain half the total number of areas in each local authority, centred on the median

(middle) rank for each local authority and the ‘whiskers’ show the full range of ranks. Deprivation

increases with decreasing rank (that is, towards the bottom of the plot).

Chart 3: Box plot of WIMD 2019 income domain ranks, by local authority

Percentage of all

income deprived people

Percentage of

Welsh LSOAs

Income

domain ranks

21.6 most-deprived 10% 1 - 191

38.2 most-deprived 20% 1 - 382

50.0 most-deprived 28.6% 1 - 546

6.7 least-deprived 20% 1529 - 1909

The table below shows, for the income domain of WIMD 2019, the percentage of small areas

(LSOAs) in each local authority which were in the most deprived 10%, 20%, 30% and 50% areas in

Wales.

Table 7: Concentrations of WIMD 2019 income deprived areas, by local authority

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 4.5 15.9 18.2 45.5

Gwynedd 73 4.1 5.5 5.5 34.2

Conwy 71 7.0 11.3 26.8 47.9

Denbighshire 58 12.1 17.2 31.0 56.9

Flintshire 92 2.2 12.0 18.5 34.8

Wrexham 85 5.9 16.5 24.7 47.1

Powys 79 1.3 5.1 11.4 20.3

Ceredigion 46 2.2 4.3 8.7 32.6

Pembrokeshire 71 5.6 12.7 16.9 38.0

Carmarthenshire 112 3.6 13.4 24.1 49.1

Swansea 148 12.8 25.0 33.1 50.0

Neath Port Talbot 91 15.4 28.6 45.1 67.0

Bridgend 88 6.8 19.3 39.8 56.8

Vale of Glamorgan 79 6.3 16.5 21.5 38.0

Rhondda Cynon Taf 154 16.2 29.9 44.8 69.5

Merthyr Tydfil 36 19.4 25.0 36.1 72.2

Caerphilly 110 10.0 24.5 37.3 64.5

Blaenau Gwent 47 10.6 36.2 57.4 80.9

Torfaen 60 8.3 23.3 40.0 60.0

Monmouthshire 56 0.0 3.6 5.4 26.8

Newport 95 20.0 32.6 41.1 57.9

Cardiff 214 19.2 27.6 35.5 44.4

Wales 1909 10 20 30 50

The local authority with the highest proportion of areas in the most deprived 10% in Wales was

Newport (20%, or 19 areas), followed by Merthyr Tydfil and Cardiff (19.4% and 19.2% respectively).

Monmouthshire had no small areas in the most deprived 10% in Wales, followed by Powys with only

1.3% of its areas in that group. These were also the local authorities with the lowest concentrations

of areas in the most deprived half of Wales, at 20.3% for Powys and 26.8% for Monmouthshire.

Blaenau Gwent had the highest percentage of areas in the most deprived 50% in Wales, at 80.9%.

3.6. Income domain methodological changes between WIMD 2014 and WIMD 2019

The introduction of Universal Credit has had a significant impact on the measurement of the income

domain of WIMD. Universal Credit is replacing most benefits and tax credits inputting to this domain.

Once fully rolled out in all areas, those areas become directly comparable and can be ranked

against one another even if eligibility conditions and levels of benefit differ from those relating to

benefits currently within WIMD.

However, given the geographical nature and lengthy timescale of implementation, differences

between Universal Credit and legacy benefits means we may not be comparing like with like at a

given point during the rollout.

Although rollout of Universal Credit full service did not begin in Wales until April 2017, there had

previously been implementation of Universal Credit for (mainly) single, new claimants of Job-

Seekers Allowance.

To ensure consistency of data across areas, for WIMD 2019 we have used data at a point in time

before the start of rollout of Universal Credit full service in Wales, which is the 2016-17 financial

year. This does not impact much on the currency of the data compared to previous indices. Early,

straightforward cases of Universal Credit claimants have been included.

Since WIMD 2014, other changes to the welfare system may mean that eligibility thresholds and

criteria for some benefits have changed.

We will continue to work with the Department for Work and Pensions (DWP) on options for a

suitable indicator using data on Universal Credit claimants in future indices.

3.7. Income domain background information

DWP benefit statistics

The Department for Work and Pensions (DWP) publish a range of tools to allow you to download

and customise benefit statistics, including local area data and time series.

Data for England and Wales

We will continue to work with the Ministry of Housing, Communities and Local Government

(MHCLG) to publish a consistent set of income deprivation data for areas across England and

Wales during 2020.

Modelled Income estimates

The ONS currently produces small area model-based income estimates, modelled down to Middle-

layer Super Output Area (MSOA) level from survey estimates.

Households Below Average Income data

The Department for Work and Pensions (DWP) publish a dataset on Households Below Average

Income (HBAI). Based on that data, the Welsh Government publish analysis of poverty in Wales,

with various breakdowns. The data cannot be broken down below Wales level due to limitations in

sample size.

Experimental Statistics on Income

The Office for National Statistics have published new experimental statistics on income, which are

based on linked administrative data, as part of work on the Administrative Data Census. They bring

together data from the Pay As You Earn and benefits systems (but not yet including income from

self-employment) to derive experimental estimates of gross and net income. The outputs include

small area level data on proportion of people and households in certain income bands for the tax

year 2015/16.

We will review this data source’s quality and coverage ahead of autumn 2020, for the possible

publication of contextual information alongside our first set of WIMD 2019 indicator updates.

Employee earnings estimates

The Office for National Statistics publishes estimates of employee earnings based on data from the

Annual Survey of Hours and Earnings (ASHE). These are the most robust and comprehensive

source of earnings data for the UK, however estimates are not available below local authority level,

the data are only a subset of all sources of income and they do not cover the self-employed.

4. Employment domain

4.1. Introduction

The purpose of this domain is to capture lack of employment. This covers involuntary exclusion of

the working-age population from work, including those who cannot work due to ill-health or who are

unemployed but are actively seeking work.

The domain has a relative weight of 22% in the overall Index. For a complete description of the

construction of the domain, please see the WIMD 2019 Technical Report.

4.2. Indicator

The employment domain contains one single composite indicator, employment related benefits,

made up of four elements:

• Jobseeker's Allowance (JSA) claimants

• Employment and Support Allowance (ESA) claimants

• Incapacity Benefit (and Severe Disablement Allowance) claimants

• Universal Credit (UC) claimants who are not in employment

The data are based on an average of the individuals who were in receipt of these benefits during

the financial year 2016-17, sourced from the Department for Work and Pensions. Individuals who

claim multiple benefits are only counted once. Each element of this indicator is summed together,

and then divided by the working-age (aged 16-64) population of the area, to form a single indicator.

The population estimates are sourced from the Mid-2016 Small Area Population Estimates,

published by the Office for National Statistics. We subtract the prison population as at mid-2016

(sourced from Ministry of Justice) from the population estimates, for the four areas containing

prisons.

The resulting composite indicator is a cross-sectional snapshot of people in employment

deprivation, measured by receipt of unemployment-related benefits.

The weight of the domain has reduced from 23.5 to 22% for WIMD 2019. This reflects the increased

lag in the currency of the data we are able to use (due to the impact of introducing Universal Credit

on a staggered basis), and a desire to slightly increase weights of other key domains now with

improved data (health and housing).

Full technical information on the indicator is available in the WIMD 2019 Technical Report.

4.3. Employment domain key results

 In the WIMD 2019 employment domain, there were pockets of high employment deprivation

in the South Wales valleys and large cities, and in some North Wales coastal towns. This is

shown in the map below.

 All local authorities except Monmouthshire had at least some areas with over 19% of people

in employment deprivation (equivalent to being in the most deprived 10% of areas).The local

authority with the highest proportion of areas in the most deprived 10% in Wales for the

employment domain was Blaenau Gwent (23.4%), followed by Merthyr Tydfil (22.2%).

Monmouthshire had no areas in the most deprived 10%.

 For the employment domain, the most deprived area in Wales was Rhyl West 2,

Denbighshire (around Rhyl High Street), the same as for WIMD 2014. Seven of the 10 most

deprived areas in WIMD 2019 were also in the 10 most deprived areas in WIMD 2014.

 The overall patterns of employment deprivation in WIMD 2019 are similar to those for WIMD

2014.

 20.8% of people who are employment deprived are in the most deprived 10% of small areas

for the employment domain (the areas ranked 1-191).

 Just over half of those who are employment deprived are in the most deprived 29.6% of

areas for the employment domain.

 Overall, the rate of employment deprivation for WIMD 2019 was lower than for WIMD 2014

(10% compared to 13%). Although the vast majority of small areas saw a decrease in the

rate of employment deprivation, some saw stagnation or small increases.

4.4. Employment domain comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved to a less deprived group. Below the diagonal are the numbers of areas which have moved to

a more deprived group.

Table 8: Movement between employment deprivation group between WIMD 2014 and

2019

Relatively more deprived: Six areas have become relatively more deprived in WIMD 2019 compared

to WIMD 2014, by more than one deprivation group. Three of these areas (in Port Talbot, Cardigan

and Milford Haven) moved from the 20-30% most deprived group into the 10% most deprived, and

the other 3 areas (in Colwyn Bay, Caerleon and Swansea) moved from the 30-50% most deprived

group into the 10-20% most deprived.

Relatively less deprived: Five areas have become relatively less deprived between WIMD 2014 and

WIMD 2019, by more than one deprivation group. Two of these areas were in Cardiff, two in

Treharris, and one in Bridgend, with all moving from the 10-20% most deprived group into the 30-

50% most deprived grouping.

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

165 26 0 0 0 191

10-20% most

deprived

(ranks 192-382)

23 124 39 5 0 191

20-30% most

deprived

(ranks 383-573)

3 38 109 41 0 191

30-50% most

deprived

(ranks 574-955)

0 3 43 282 54 382

50% least

deprived

(ranks 956-1909)

0 0 0 54 900 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Employment domain 2019

Employment domain 2014

Distribution of the Employment deprived population in WIMD 2019

The chart below shows the ranks and indicator values for the employment domain in WIMD 2019.

Chart 4: WIMD 2019 Employment domain distribution

The plot shows that, at the most deprived end of the distribution, there is a steep increase in the

percentage of working-age people that are employment deprived. There is a wide range in the rate

of employment deprivation within the most deprived 10% of areas. The percentages range from

43% for Rhyl West 2, Denbighshire (the area ranked 1), to 19% for Gurnos 3, Merthyr Tydfil (the

area ranked 191).

The table below puts these numbers into context. The most deprived 10% of areas contains 20.8%

of people that are employment deprived within Wales. Just over half of the people who are

employment deprived can be found in the most deprived 29.6% of areas for the employment

domain.

Table 9: Distribution of the Employment deprived population, WIMD 2019

Percentage of all employment

deprived people

Percentage of

Welsh LSOAs

Employment

domain ranks

20.8 most-deprived 10% 1 - 191

36.7 most-deprived 20% 1 - 382

50.0 most-deprived 29.6% 1 - 565

7.5 least-deprived 20% 1529 - 1909

4.5. Employment domain local authority analysis

The chart below shows the spread of employment domain ranks for each local authority in Wales.

The blue boxes contain half the total number of areas in each local authority, centred on the median

(middle) rank for each local authority and the ‘whiskers’ show the full range of ranks. Deprivation

increases with decreasing rank (that is, towards the bottom of the plot).

Chart 5: Box plot of WIMD 2019 Employment domain ranks, by local authority

The table below shows, for the employment domain of WIMD 2019, the percentage of small areas

(LSOAs) in each local authority which were in the most deprived 10% of Wales, 20%, 30% and 50%

areas in Wales.

Table 10: Concentrations of WIMD 2019 employment deprived areas, by local

authority

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc.) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 4.5 13.6 18.2 43.2

Gwynedd 73 2.7 4.1 4.1 26.0

Conwy 71 7.0 14.1 28.2 43.7

Denbighshire 58 12.1 19.0 25.9 51.7

Flintshire 92 1.1 7.6 15.2 27.2

Wrexham 85 3.5 9.4 18.8 44.7

Powys 79 2.5 3.8 11.4 22.8

Ceredigion 46 4.3 6.5 6.5 23.9

Pembrokeshire 71 7.0 11.3 14.1 38.0

Carmarthenshire 112 6.3 16.1 27.7 56.3

Swansea 148 14.9 23.0 30.4 52.0

Neath Port Talbot 91 18.7 36.3 53.8 74.7

Bridgend 88 6.8 29.5 39.8 61.4

Vale of Glamorgan 79 5.1 13.9 17.7 35.4

Rhondda Cynon Taf 154 19.5 36.4 50.6 73.4

Merthyr Tydfil 36 22.2 33.3 55.6 88.9

Caerphilly 110 11.8 29.1 42.7 68.2

Blaenau Gwent 47 23.4 48.9 72.3 91.5

Torfaen 60 5.0 21.7 43.3 58.3

Monmouthshire 56 0.0 1.8 8.9 23.2

Newport 95 11.6 25.3 34.7 53.7

Cardiff 214 14.0 18.7 27.1 39.7

Wales 1909 10 20 30 50

The local authority with the highest proportion of areas in the most deprived 10% in Wales was

Blaenau Gwent (23.4%, or 11 areas). Merthyr Tydfil has the second highest proportion of areas in

the most deprived 10% (22.2%, or 8 areas).

Monmouthshire had no areas in the most deprived 10%. Flintshire had only 1.1% of its areas in the

10% most deprived group. Only 22.8% of the areas in Powys were in the most deprived 50% in

Wales, closely followed by Ceredigion with 23.9%.

Blaenau Gwent had the highest percentage of areas in the most deprived 50% in Wales (91.5%).

The next highest was Merthyr Tydfil, with 88.9% of its areas in the most deprived half of Wales.

4.6. Employment domain methodological changes between WIMD 2014 and WIMD

2019

The introduction of Universal Credit has had a significant impact on the measurement of the

employment domain of WIMD. Universal Credit is replacing most benefits and tax credits inputting

to this domain. Once fully rolled out in all areas, those areas become directly comparable and can

be ranked against one another even if eligibility conditions and levels of benefit differ from those

relating to benefits currently within WIMD.

However, given the geographical nature and lengthy timescale of implementation, differences

between Universal Credit and legacy benefits means we may not be comparing like with like at a

given point during the rollout.

Although rollout of Universal Credit full service did not begin in Wales until April 2017, there had

previously been implementation of Universal Credit for (mainly) single, new claimants of Job-

Seekers Allowance.

To ensure consistency of data across areas, for WIMD 2019 we have used data at a point in time

before the start of rollout of Universal Credit full service in Wales, which is the 2016-17 financial

year. This does not impact much on the currency of the data compared to previous indices. Early,

straightforward cases of Universal Credit claimants have been included.

Since WIMD 2014, other changes to the welfare system may mean that eligibility thresholds and

criteria for some benefits have changed.

We will continue to work with the Department for Work and Pensions (DWP) on options for a

suitable indicator using data on Universal Credit claimants in future indices.

4.7. Employment domain background information

DWP benefit statistics

The Department for Work and Pensions (DWP) publish a range of tools to allow you to download

and customise benefit statistics, including local area data and time series.

Data for England and Wales

We will continue to work with the Ministry of Housing, Communities and Local Government

(MHCLG) to publish a consistent set of employment deprivation data for areas across England and

Wales during 2020.

Workless households

Workless household are those where none of the adults aged 16 to 64 are in employment. The data

are sourced from the Annual Population Survey (APS) and Labour Force Survey (LFS). These data

enable household analyses to be carried out at a local authority level, including details of people in

workless households, children in workless households, lone parents and housing tenure. Key

results for Wales can be found in the Welsh Government’s Labour Market Statistics for

Households analysis.

Labour Market research outputs

The ONS have produced new labour market research outputs as part of work on the Administrative

Data Census. The aim is to produce small area, multivariate statistics, and they have published data

on labour market status by local authority for tax year 2011/12.

Labour market status estimates

The Welsh Government publishes estimates of employment, unemployment and economic inactivity

based on data from the Annual Population Survey (APS). These estimates are updated on a

quarterly basis but are available down to local authority level only.

5. Health domain

5.1. Introduction

The purpose of this domain is to measure lack of good health. This domain does not contain any

sub-domains. Some indicators in this domain are age-sex standardised to account for population

differences across small areas.

The domain has a relative weight of 15% in the overall index. This has increased from 14% in the

2014 index, due to the addition of three new indicators; diagnosed chronic conditions, diagnosed

mental health conditions, and children aged 4-5 who are obese. The 2019 health domain indicators

are weighted as shown below. For a complete description of the construction of the domain, please

see the WIMD 2019 Technical Report.

5.2. Health Domain Indicators

The domain contains seven indicators, weighted as shown below:

 The indicator on GP-recorded chronic conditions measures the number of people per 100

with a current diagnosis of one or more of the conditions listed below:

o Coronary Heart Disease

o Chronic Obstructive Pulmonary Disease

o Stroke and Transient Ischaemic Attack

o Peripheral Arterial Disease

o Chronic Kidney Disease

o Diabetes Mellitus (type 1 all ages, type 2/other for aged 17 plus)

o Epilepsy

 The indicator on GP-recorded mental health conditions measures the number of people per

100 with a current diagnosis of one or more of the conditions listed below:

o Depression

o Low mood (patients with record of low mood and an active repeat prescription for an

anti-depressant)

o Anxiety disorder (including panic disorders)

o Dementia

o Severe mental illnesses (schizophrenia, bipolar affective disorder and other

psychoses)

The numerator for the two new indicators on diagnosed chronic and mental health conditions was

based on counts of diagnoses from the above defined lists of disease registers and sub-indicators

obtained from GP practices in Wales. These counts were de-duplicated so that patients with more

than one condition were not counted twice. Patient level data was aggregated to small areas

(LSOAs), according to patient addresses, so that prevalence is based on where people live rather

than where they are registered with a GP.

 The indicator on Limiting long-term illness measures the number of people with a limiting

long-term illness per 100 people, and is based on 2011 Census data (Office for National

Statistics).

 The indicator on premature deaths measures the number of deaths of those under the age

of 75 per 100,000 people and is based on the 2009-2018 average (Office for National

Statistics).

 The indicator on Cancer Incidence measures the number of incidences of cancer per

100,000 people, and was based on the 2007-2016 average (Welsh Cancer Intelligence and

Surveillance Unit, Velindre NHS Trust).

All the above indicators are age-sex standardised to adjust for the expected prevalence of disease

within the underlying population. This allows the Index to identify areas where health deprivations

exists beyond the effect of age and sex.

 The indicator on Low Birth Weight measures the percentage of live single births less than

2.5 kg (5.5lb), and was based on the 2009-2018 average (Office for National Statistics).

 The indicator on children who are obese measures the proportion of reception aged children

(those aged 4 and 5) who are obese and is based on the 2012-13 to 2017-18 average, child

measurement programme.

For a full explanation of how these indicators are calculated and combined together, please see the

WIMD 2019 Technical Report.

5.3. Health domain key results

 In the WIMD 2019 health domain, there were pockets of high deprivation in the South Wales

valleys and large cities, and in some North Wales coastal and border towns. This is shown in

the map below.

 The local authorities with the highest concentration of areas in the most deprived 10% were

Merthyr Tydfil, followed by Blaenau Gwent. Isle of Anglesey, Ceredigion, and

Monmouthshire had no small areas in the most deprived 10%.

 For the health domain, the most deprived small area in Wales was Caerau 1 (which covers

Caerau Park and the Tudor Estate) in Bridgend (ranked 6 in the WIMD 2014 health domain),

followed by Rhyl West 2 in Denbighshire (ranked 1 in the WIMD 2014 health domain).

 The overall patterns of health deprivation in WIMD 2019 are fairly similar to those for WIMD

2014, with only 75 areas moving by more than one health deprivation group in either

direction.

5.4. Health domain comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved from a more to a less deprived group. Below the diagonal are the numbers of areas which

have moved from a less to a more deprived group.

Table 11: Movement between health deprivation group between WIMD 2014 and 2019

Relatively more deprived: Seven areas have moved from outside the 20% most deprived group into

the 10% most deprived group for this domain in WIMD 2019. These areas lie in six different local

authorities, with two in Cardiff. The only area to move from outside the 30% most deprived into the

10% most deprived group was Flint Coleshill 2 in Flintshire.

Relatively less deprived: Twelve areas have moved from the 10% most deprived group to outside

the 20% most deprived group for this domain in WIMD 2019. Nine of these were either in Rhondda

Cynon Taf (5 of them) or Caerphilly (4 of them).

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

143 36 10 1 1 191

10-20% most

deprived

(ranks 192-382)

41 84 50 16 0 191

20-30% most

deprived

(ranks 383-573)

6 46 71 60 8 191

30-50% most

deprived

(ranks 574-955)

1 22 53 222 84 382

50% least

deprived

(ranks 956-1909)

0 3 7 83 861 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Health domain 2019

Health domain 2014

5.5. Health domain local authority analysis

The chart below shows the spread of health domain ranks for each local authority in Wales. The

blue boxes contain half the total number of areas in each local authority, centred on the median

(middle) rank for each local authority and the ‘whiskers’ show the full range of ranks. Deprivation

increases with decreasing rank (that is, towards the bottom of the plot).

Chart 6: Box plot of WIMD 2019 health domain ranks, by local authority

The table below shows, for the health domain of WIMD 2019, the percentage of small areas

(LSOAs) in each local authority which were in the most deprived 10%, 20%, 30% and 50% areas in

Wales.

Table 12: Concentrations of WIMD 2019 health deprived areas, by local authority

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 0.0 6.8 11.4 27.3

Gwynedd 73 1.4 4.1 6.8 20.5

Conwy 71 4.2 11.3 16.9 36.6

Denbighshire 58 17.2 17.2 29.3 53.4

Flintshire 92 5.4 12.0 18.5 34.8

Wrexham 85 7.1 17.6 28.2 52.9

Powys 79 1.3 3.8 8.9 21.5

Ceredigion 46 0.0 0.0 4.3 8.7

Pembrokeshire 71 1.4 5.6 12.7 32.4

Carmarthenshire 112 3.6 9.8 21.4 48.2

Swansea 148 12.2 25.0 30.4 52.0

Neath Port Talbot 91 16.5 33.0 46.2 74.7

Bridgend 88 15.9 33.0 47.7 63.6

Vale of Glamorgan 79 5.1 10.1 17.7 36.7

Rhondda Cynon Taf 154 16.9 34.4 53.2 78.6

Merthyr Tydfil 36 25.0 33.3 52.8 88.9

Caerphilly 110 10.9 24.5 42.7 70.0

Blaenau Gwent 47 19.1 36.2 61.7 87.2

Torfaen 60 8.3 30.0 41.7 66.7

Monmouthshire 56 0.0 3.6 7.1 19.6

Newport 95 14.7 26.3 34.7 54.7

Cardiff 214 15.9 26.2 32.2 43.0

Wales 1909 10 20 30 50

 The local authority with the highest concentration of areas in the most deprived 10% in

Wales was Merthyr Tydfil (25%, or 9 areas), followed by Blaenau Gwent (19%, also 9

areas). For Merthyr, 8 of the areas are in or near the town of Merthyr Tydfil itself, and one is

in Merthyr Vale.

 Merthyr Tydfil and Blaenau Gwent also had the highest percentage of areas in the most

deprived 50% in Wales (both with almost 90%).

 Isle of Anglesey, Ceredigion, and Monmouthshire had no small areas in the most deprived

10%. Only 8.7% of the areas in Ceredigion were in the most deprived 50% in Wales.

5.6. Health domain methodological changes between WIMD 2014 and WIMD 2019

There have been considerable developments in the health domain since WIMD 2014 with the health

status of communities now being captured through a wider range of data sources. To help illustrate

this, we have grouped our indicators into the three categories below:

Indicators that relate to children

As well as updating the measure on low birth weight, we have also included a new measure on

children aged 4 and 5 who are obese according to the Child Measurement Programme. We chose

to include this measure given the links between being an unhealthy weight in childhood and long

term health problems in adulthood.

Indicators that capture specific diagnosed conditions

In WIMD 2019, we have expanded the range of indicators from cancer incidence alone, to include

measures on the prevalence of GP-recorded chronic conditions and mental health conditions (see

section 5.2).

Indicators that capture the status of the population’s health more broadly

The indicator on limiting long term illness has not changed since 2014, since it is census-based.

The all-cause death rate, was included in WIMD 2011 and WIMD 2014 as a proxy for morbidity. We

are now including an indicator on the all-cause rate of deaths for those that are under the age of 75,

the premature death rate, instead of the previous indicator. The premature mortality measure is

more sensitive to poor health that is manifest through lower life expectancy and so is more relevant

to health deprivation in a population.

For a more detail on these indicators, see the WIMD 2019 Technical Report.

Weighting

In recognition that a greater number of health conditions are now being captured in the health

domain, its weighting in the overall index has increased slightly from 14% to 15%.

5.7. Health domain background information

The information below provides a list of sources of health statistics for Wales.

Welsh Government Health and Social Care Statistics

The Welsh Government publishes a comprehensive set of information on health, health services

and social services in Wales. These statistics cover a wide range of topics including NHS primary

and community activity, waiting times and NHS staff.

National Survey for Wales

The National Survey for Wales asks questions about health and use of health services. This covers

a wide range of topics which vary by survey year, and results can be found on the Survey topic

pages for Population Health and NHS & Social Care.

Public Health Wales

The Public Health Wales Observatory provides public health intelligence for decision makers and

the public. As part of this, the Public Health Outcomes Framework compiles information on health

outcomes for the people of Wales.

Welsh Cancer Intelligence & Surveillance Unit

The Welsh Cancer Intelligence & Surveillance Unit is the National Cancer Registry for Wales and its

primary role is to record, store and report on all incidence of cancer for the resident population of

Wales wherever they are treated.

Health Maps Wales

Health Maps Wales contains a wide range of health data about Welsh residents, including hospital

admissions, mortality and child health.

Office for National Statistics

The Office for National Statistics also publishes statistics on health and social care, including life

expectancy, and mortality data, collected from registrations and surveys.

Secure Anonymised Information Linkage (SAIL) databank

For future WIMD iterations, we will continue to explore the possibility of deriving health indicators

through accessing linked data available in the SAIL databank (which is supported by Swansea

University). This could include data on chronic disease, emergency stays in hospital, childhood

obesity and mental health.

6. Education domain

6.1. Introduction

The purpose of this domain is to capture the extent of deprivation relating to education, training and

skills. It is designed to reflect educational disadvantage within an area in terms of lack of

qualifications and skills.

The domain has a relative weight of 14% in the overall index. The indicators are weighted as shown

below. For a complete description of the construction of the domain, please see the WIMD 2019

Technical Report.

6.2. Indicators

The domain contains 6 indicators, weighted as shown below:

Four of these indicators focus on capturing low attainment among children and young people:

 The Foundation Phase Average Point Score indicator measures the average point scores of

pupils as assessed by teachers in Year 2 (final year of the Foundation Phase), and is based on

a three-year average (academic years 2015/16 – 2017/18). The data are derived from the

National Data Collection Database (NDC) and the Pupil Level Annual Schools Census

(PLASC), Welsh Government.

 The Key Stage 2 (KS2) Average Point Score indicator measures the average point scores of

pupils as assessed by teachers in Year 6 (final year of primary school), and is based on a

three-year average (academic years 2015/16 – 2017/18). The data are derived from the

National Data Collection Database (NDC) and the Pupil Level Annual Schools Census

(PLASC), Welsh Government.

 The Key Stage 4 (KS4) Average Point Score in Core Subjects indicator measures the average

point scores of year 11 pupils calculated from the grades achieved in the core subjects of

GCSE English or Welsh, GCSE Mathematics and GCSE Science (or equivalent qualifications).

It is based on a three-year average (academic years 2015/16 – 2017/18) and the data are

derived from the National Pupil Database (NPD), the Welsh Examinations Database (WED) and

PLASC, Welsh Government.

 The Repeat Absenteeism indicator measures the percentage of primary and secondary pupils

missing more than 15% of school sessions, and is based on a three-year average (academic

years 2015/16 – 2017/18). The data are derived from NPD and PLASC, Welsh Government.

The other two indicators focus on capturing the lack of qualifications and skills in adults:

 The KS4 Leavers Entering Higher Education indicator measures the proportion of KS4 pupils

who, at some point in the subsequent three years after leaving year 11, enter Higher Education

(defined as any programme of learning above level 3), and is based on a 4 year average

(academic years 2011/12 to 2014/15). The data is derived from the Higher Education Statistics

Agency (HESA) record, PLASC and the Lifelong Learning Wales Record (LLWR), Welsh

Government.

 The No Qualifications indicator measures the numbers of adults aged 25-64 with no

qualification, and is based on 2011 Census data.

For a full explanation of how these indicators are calculated and combined together, please see the

WIMD 2019 Technical Report.

6.3. Education domain key results

 The overall patterns of educational deprivation in WIMD 2019 are similar to those for WIMD

2014. This is shown in the map below.

 The local authorities with the highest concentration of areas in the most deprived 10% were

Newport, Neath Port Talbot, Blaenau Gwent and Rhondda Cynon Taf.

 Ceredigion, Isle of Anglesey and Monmouthshire had no areas in the most deprived 10%.

 The most educationally deprived small area in Wales was Queensway 1, an area of the Caia

Park Community in Wrexham.

6.4. Education domain comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved from a more to a less deprived group. Below the diagonal are the numbers of areas which

have moved from a less to a more deprived group.

Table 13: Movement between Education deprivation groups between WIMD 2014 and

2019

Relatively more deprived: 50 areas have moved into the 10% most deprived group for this domain

in WIMD 2019. These are spread across 14 local authorities and the majority were in the 10 to 30%

most deprived areas for the domain in WIMD 2014. One area moved substantially from the least

deprived 50% in WIMD 2014.

Relatively less deprived: 50 areas have moved from the 10% most deprived group in WIMD 2019.

These are spread across 13 local authorities and the majority moved to the 10 to 20% most

deprived group. No areas moved substantially into the 50% least deprived group.

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

141 39 10 1 0 191

10-20% most

deprived

(ranks 192-382)

36 76 52 24 3 191

20-30% most

deprived

(ranks 383-573)

10 54 60 60 7 191

30-50% most

deprived

(ranks 574-955)

3 21 62 195 101 382

50% least

deprived

(ranks 956-1909)

1 1 7 102 843 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Education domain 2019

Education domain 2014

6.5. Education domain local authority analysis

The chart below shows the spread of education domain ranks for each local authority in Wales. The

blue boxes contain half the total number of areas in each local authority, centred on the median

(middle) rank for each local authority and the ‘whiskers’ show the full range of ranks. Deprivation

increases with decreasing rank (that is, towards the bottom of the plot).

Chart 7: Box plot of WIMD 2019 Education domain ranks, by local authority

The table below shows, for the education domain of WIMD 2019, the percentage of small areas

(LSOAs) in each local authority which were in the most deprived 10%, 20%, 30% and 50% areas in

Wales.

Table 14: Concentrations of WIMD 2019 Education domain deprived areas, by local

authority

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

Local Authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 0.0 15.9 18.2 47.7

Gwynedd 73 1.4 4.1 6.8 26.0

Conwy 71 1.4 8.5 19.7 38.0

Denbighshire 58 8.6 15.5 29.3 51.7

Flintshire 92 9.8 18.5 30.4 47.8

Wrexham 85 11.8 24.7 35.3 54.1

Powys 79 1.3 7.6 11.4 22.8

Ceredigion 46 0.0 0.0 2.2 21.7

Pembrokeshire 71 8.5 19.7 26.8 49.3

Carmarthenshire 112 7.1 12.5 21.4 48.2

Swansea 148 11.5 18.9 30.4 45.3

Neath Port Talbot 91 19.8 31.9 45.1 74.7

Bridgend 88 6.8 17.0 27.3 50.0

Vale of Glamorgan 79 3.8 10.1 15.2 32.9

Rhondda Cynon Taf 154 14.3 31.8 46.8 69.5

Merthyr Tydfil 36 11.1 25.0 41.7 77.8

Caerphilly 110 12.7 28.2 38.2 65.5

Blaenau Gwent 47 17.0 38.3 59.6 85.1

Torfaen 60 13.3 28.3 41.7 60.0

Monmouthshire 56 0.0 1.8 7.1 21.4

Newport 95 21.1 29.5 44.2 52.6

Cardiff 214 14.0 24.3 31.8 47.2

Wales 1909 10 20 30 50

 The local authority with the highest concentration of areas in the most deprived 10% in

Wales was Newport (21.1%, or 20 areas).

 The local authorities with the lowest proportion of areas in the most deprived 10% in Wales

were Ceredigion, Isle of Anglesey and Monmouthshire with 0% of their areas in the most

deprived 10%. Only 21.4% of the areas in Monmouthshire and 21.7% of the areas in

Ceredigion were in the most deprived 50% in Wales.

 Blaenau Gwent had the highest percentage of areas in the most deprived 50% in Wales

(85.1%). The next highest was Merthyr Tydfil, with 77.8% of its areas in the most deprived

half of Wales.

6.6. Education domain methodological changes between WIMD 2014 and WIMD 2019

Three of the six indicators in the WIMD 2019 education domain were present in WIMD 2014:

 Key Stage 2 Average Point Score

 Repeat Absenteeism Rate

 Number of Adults aged 25-64 with No Qualifications

A Foundation Phase Average Point Score indicator based upon the results of teacher assessments

for pupils taught in National Curriculum Year Group 2 has been included in WIMD 2019. It is

intended to complement the Key Stage 2 Average Point Score indicator to measure education

deprivation at primary school level.

The two Key Stage 4 indicators included in WIMD 2014 have been replaced with a single indicator.

This indicator has been constructed using a new methodology and is, therefore, not comparable

with the previous indicators used in WIMD 2014.

The Proportion of People aged 18-19 not entering Higher Education indicator has been replaced

with an indicator measuring the Proportion of Key Stage 4 Leavers entering Higher Education.

Whilst these indicators measure similar things, they are not directly comparable.

6.7. Education domain background information

Welsh Government Education Statistics

The Welsh Government publishes a comprehensive set of information on education and skills in

Wales. These statistics cover a wide range of topics relating to Education including schools, further

and higher education and work-based learning.

Key Stage 4

In September 2019, the Welsh Government moved to an updated ‘capped 9’ points score to

measure achievement at KS4. However, changes to KS4 measures have been implemented

gradually since 2015/16 and it was not possible to produce three comparable years of ‘capped 9’

points score data for WIMD 2019. Therefore the KS4 Average Point Score in Core Subjects

indicator was developed as an interim indicator but it is anticipated that the KS4 ‘capped 9’ point

score will be adopted for future iterations of WIMD.

Young people not in education, employment or Training / learner destinations

Conceptually, a measure of those not in education, employment or training (NEET) would be a

suitable measure of educational deprivation.

Headline estimates of young people who are NEET can be found in the statistical release

'Participation of young people in education and the labour market'. However, the estimates are

available at Wales level only and, as the number of those who are NEET is relatively low and this

data is collected using a sample survey, it is not possible to derive an indicator at a small area level.

Hence this indicator was not included in WIMD 2019.

There is a Welsh Government programme of work currently looking at the development of KS4 /

KS5 destinations datasets. These datasets are derived by the linking of education data-sources

alongside engagement with DfE’s Longitudinal Educational Outcomes Study (which aims to link

education datasets to employment/earning data from DWP/HMRC) and provide data on where

pupils go once they leave compulsory education. Experimental statistics produced from these

datasets can be found in the statistical release 'Consistent performance measures for post-16

learning (learner destinations): August 2015 to July 2016'.

Whilst it was not possible to use these datasets to produce a NEETs indicator for WIMD 2019, they

were used to produce the KS4 leavers entering Higher Education indicator. The ongoing

development of these datasets will be monitored and their potential for inclusion in future WIMD

releases considered.

7. Access to Services domain

7.1. Introduction

The purpose of this domain is to capture deprivation as a result of a household’s inability to access

a range of services considered necessary for day-to-day living, both physically and online. This

covers both material deprivation (for example, not being able to get food) and social aspects of

deprivation (for example, not being able to attend after school activities). Poor access to services is

a factor which can compound other types of deprivation that exist in an area.

The access to services domain measures travel times to a range of services as a proxy for wider

physical access to services. For WIMD 2019, the domain also considers access to digital services,

through an indicator on the availability of superfast broadband.

In terms of the travel times, measurements do not take into account the availability of the services to

the individual once they get there (e.g. availability of GP appointments), nor does it take into

account an individual’s personal choice in accessing certain services (e.g. if someone would prefer

to be educated at a faith school).

In terms of digital services, measurement takes into account reported operator data on availability of

fixed line broadband services, but does not take into account take-up.

The domain has a relative weight of 10% in the overall index. The indicators are weighted as shown

below. For a complete description of the construction of the access to services domain, please see

the WIMD 2019 Technical Report.

7.2. Access to Services domain indicators

The access to services domain contains 10 indicators.

Of these, 9 are physical access indicators, each relating to a type of service such as food shop or

school. Each indicator measures an average return travel time (in minutes) from residential

dwellings to the nearest service, by public and private transport. Public transport includes travel by:

public bus, public train, foot, and national coach. Private transport is considered to be transport by

private car. The weights to combine the public and private transport times together are calculated

for each area using data from the 2011 Census on car ownership and the number of adults aged 17

and over.

The domain also includes a new indicator, measuring access to digital services. This is calculated

as the proportion of homes and small businesses unable to receive fixed line broadband at a

download speed of at least 30Mb/s (superfast broadband). This includes properties with no

broadband coverage. The source is Ofcom’s Connected Nations update, Spring 2019. Ofcom

collects and analyses data from the main fixed broadband internet service providers on addresses

covered by their service.

The physical and digital aspects are treated as two sub-domains, with the 9 travel time indicators

weighted together using factor analysis (see resultant weights below), then combined with the single

access to digital services indicator, which is given a weight of 10%.

*The average travel time to a Petrol Station indicator only considers private transport.

For a full explanation of how these indicators are calculated and combined together, please see the

WIMD 2019 Technical Report.

7.3. Access to Services domain key results

 In the WIMD 2019 access to services domain, high deprivation was widespread across rural

areas of Wales. There were also some deprived pockets near large urban areas. This is

shown in the map below.

 The local authorities with the highest proportion of small areas in the most deprived 10% in

Wales for access to services were Powys (50.6%) and Ceredigion (50.0%).

 Cardiff, Neath Port Talbot, Bridgend, Rhondda Cynon Taf, Blaenau Gwent and Torfaen local

authorities had no areas in the most deprived 10%.

 For the access to services domain, the most deprived small area in Wales was Cynwyl

Gaeo, Carmarthenshire, the same as for WIMD 2014. Six of the 10 most deprived areas in

WIMD 2019 were also in the 10 most deprived areas in WIMD 2014.

 The overall patterns of access to services deprivation in WIMD 2019 are similar to those for

WIMD 2014.

 However, there have been notable changes to relative ranks at the least deprived end. This

reflects the significant improvements in the travel time calculations (see section 7.6), as well

as possible changes to service locations, public transport and road networks since 2014,

and the inclusion of the new access to digital services indicator.

7.4. Access to Services domain comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved to a less deprived group. Below the diagonal are the numbers of areas which have moved to

a more deprived group.

Table 15: Movement between Access to Services deprivation group between WIMD

2014 and WIMD 2019

Caution should be used in interpreting the table above. Significant changes to the methodology

mean that it is difficult to interpret changes between WIMD 2014 and WIMD 2019. See section 7.6

for further details.

Relatively more deprived: Twenty-two areas have moved into the 10% most deprived group in

WIMD 2019, spread across 10 of the 22 local authorities in Wales. They were all within the 30%

most deprived areas for the domain in WIMD 2014.

Relatively less deprived: Twenty-two areas have moved from the 10% most deprived group for this

domain in WIMD 2014, one of which moved into the least deprived half, and a further 2 into the

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

169 19 0 2 1 191

10-20% most

deprived

(ranks 192-382)

20 89 41 31 10 191

20-30% most

deprived

(ranks 383-573)

2 29 43 72 45 191

30-50% most

deprived

(ranks 574-955)

0 30 54 110 188 382

50% least

deprived

(ranks 956-1909)

0 24 53 167 710 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Access to services domain 2019

Access to services domain 2014

least deprived 70% of areas in WIMD 2019. All three areas moving furthest out of the most deprived

decile were near Glynneath in Neath Port Talbot local authority.

7.5. Access to Services domain local authority analysis

The chart below shows the spread of access to services domain ranks for each local authority in

Wales. The blue boxes contain half the total number of areas in each local authority, centred on the

median (middle) rank for each local authority and the lines show the full range of ranks. Deprivation

increases with decreasing rank (that is, towards the bottom of the plot).

Chart 8: Box plot of WIMD 2019 Access to Services domain ranks, by local authority

The table below shows, for the access to services domain of WIMD 2019, the percentage of small

areas (LSOAs) in each local authority which were in the most deprived 10%, 20%, 30% and 50%

areas in Wales.

Table 16: Concentration of WIMD 2019 Access to Services deprived areas, by local

authority

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc.) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 15.9 45.5 50.0 65.9

Gwynedd 73 27.4 50.7 63.0 74.0

Conwy 71 12.7 16.9 28.2 54.9

Denbighshire 58 13.8 31.0 32.8 46.6

Flintshire 92 3.3 15.2 19.6 41.3

Wrexham 85 7.1 16.5 24.7 47.1

Powys 79 50.6 68.4 74.7 87.3

Ceredigion 46 50.0 63.0 80.4 87.0

Pembrokeshire 71 38.0 56.3 64.8 74.6

Carmarthenshire 112 21.4 38.4 46.4 69.6

Swansea 148 1.4 5.4 17.6 39.9

Neath Port Talbot 91 0.0 8.8 23.1 53.8

Bridgend 88 0.0 5.7 13.6 42.0

Vale of Glamorgan 79 3.8 7.6 11.4 32.9

Rhondda Cynon Taf 154 0.0 7.8 18.8 40.9

Merthyr Tydfil 36 2.8 19.4 36.1 63.9

Caerphilly 110 0.9 4.5 14.5 26.4

Blaenau Gwent 47 0.0 17.0 38.3 51.1

Torfaen 60 0.0 5.0 11.7 38.3

Monmouthshire 56 26.8 39.3 51.8 66.1

Newport 95 2.1 8.4 23.2 43.2

Cardiff 214 0.0 4.2 14.5 36.0

Wales 1909 10 20 30 50

The local authority with the highest proportion of small areas in the most deprived 10% in Wales for

access to services was Powys (50.6%, or 40 areas). Ceredigion was the next highest, with 50% (or

23) of its areas in the most deprived 10%. This is because these local authorities are large and

sparsely populated, with many small rural settlements.

Neath Port Talbot, Bridgend, Rhondda Cynon Taf, Blaenau Gwent, Torfaen, and Cardiff local

authorities had no small areas in the most deprived 10%. However the local authority with the

fewest areas that were among the most deprived 50% in Wales was Caerphilly (26.4% or 29 areas).

Powys and Ceredigion had just under 90% of their small areas in the most deprived 50% in Wales,

followed by Gwynedd and Pembrokeshire, with around three-quarters of their areas in the most

deprived half of Wales.

7.6. Access to Services domain methodological changes between WIMD 2014 and

WIMD 2019

As well as updating the WIMD 2014 suite of indicators measuring travel times to key services, we

have introduced a new indicator on access to digital services, weighted as 10% within the domain.

This indicator is calculated as the proportion of homes and small businesses unable to receive fixed

line broadband at a download sync speed of at least 30Mb/s (superfast broadband). This includes

properties with no broadband coverage.

Concerning calculation of updated travel times to key services, whilst the principles of methodology

have not changed between WIMD 2014 and WIMD 2019 – the technical toolkits used have

undergone rigorous change to seek to increase the accuracy, robustness and repeatability of the

data. These changes included:

 Improvements to granularity of private routing, providing mapping to the doorstep of every

residential address.

 Improvements to granularity of public transport routing, changing from a gridded catchment

approach in WIMD 2014 to that of an isochrone approach in WIMD 2019.

 Improvements to the definition of residential dwelling to be as encompassing to the

population of Wales as possible, by using domestic council tax records.

Types of services modelled remain unchanged from WIMD 2014, and as such, data sources, the

number of sites and the definitions adhered to are mostly comparable. However, the Food shops

indicator has been enhanced to include certain chains of Frozen Food retailers who adhere to our

basic provisions definition. Leisure Centres have been renamed to Sports Facilities to encompass

the wider service offering now modelled.

Due to the above, care should be taken in interpreting changes in the travel time indicator values,

which are not strictly comparable to older data. The main effect of the update is to raise the lower

travel times, leading to notable movements between relative ranks at the least deprived end. More

generally, reasons for changes include:

 changes to the methodology used to calculate the travel times by both private and public

transport (see above)

 the opening and closure of services since 2014

 changes in public transport and road networks since 2014

 changes to location of residential dwellings in an area (e.g. new housing) since 2014

For a more detail, see the WIMD 2019 Technical Report.

7.7. Access to Services background information

Further related WIMD analysis

Following on from publication of WIMD 2019, related statistical articles produced following WIMD

2014 will be updated with the new data, and published in due course on our website. Links to the

WIMD 2014 versions are provided below:

 A guide to analysing deprivation in rural areas

 Analysis of the Access to Services Domain by type of settlement

Data Science Campus – multi-modal transport journey analysis

To improve our measurement of access to services, we have used the Data Science Campus at

ONS’s new tool to analyse multi-modal transport journeys. The tool, called “propeR” and written for

the R programming language, will improve the granularity and ease of performing public transport

travel time analysis across Wales, and beyond.

Alternative approach - floating catchment areas

The WISERD team at the University of South Wales have been undertaking research

into a

refinement of the approach for assessing service accessibility, called the enhanced two-step floating

catchment area (E2SFCA) method, a derivative of gravity model techniques.

Their work aims to calculate, for each location of interest, a service access figure that takes into

consideration the geographical distribution of all supply sites found within a reasonable travel

time/distance. Both the proximity and capacity of such sites are evaluated in relation to the potential

service demand placed upon each by their own local populations.

For example the recent articles: Measuring Spatial Accessibility to Services within Indices of

Multiple Deprivation and Investigating spatial variations in access to childcare provision using

network‐based Geographic Information System models

Where possible, we will continue to share inputs and methods for this domain with the WISERD

team. This will enable the production of a parallel set of outputs using the FCA method, allowing us

to assess the implications of adopting an FCA approach on future Access to Services domain data.

National Survey for Wales – access to services

In 2017-18, the National Survey for Wales asked questions about whether people are satisfied with

their ability to access the services and facilities they need. Results are summarised in a statistical

bulletin.

8. Housing domain

8.1. Introduction

Conceptually, the purpose of the housing domain is to identify inadequate housing, in terms of

physical and living conditions and availability. Here, living condition means the suitability of the

housing for its inhabitant(s), for example in terms of health and safety, and necessary adaptations.

Housing as a component of multiple deprivation is somewhat different to most other domains.

Generally, housing tenure, age and type tend to influence measures of housing deprivation, as

defined above. For example, different tenures of housing have varying regulations or standards

applicable to them, which can influence housing quality. Therefore we would not always expect

measures of housing deprivation to correlate strongly with overall deprivation. However, as with

poor access to services, the compounding effect of poor housing along with other components of

deprivation, such as health can be significant, and is important to capture.

The domain has a relative weight of 7% in the overall index. This has increased from 5% in the

2014 index, due to the addition of a new modelled indicator on the likelihood of poor quality housing.

For a complete description of the construction of the domain, please see the WIMD 2019 Technical

Report.

8.2. Indicators

The domain contains two indicators, weighted as shown below:

 The indicator on overcrowding measures the percentage of people living in overcrowded

households (2011 Census-based bedroom measure)

 The indicator on poor quality housing is a modelled indicator. It measures the likelihood of

housing being in disrepair or containing serious hazards (for example, risk of falls or cold

housing).

For further description of these indicators, and explanation of how they are calculated and combined

together, please see section 8.6, and the WIMD 2019 Technical Report.

8.3. Housing domain key results

 In the WIMD 2019 housing domain, there were pockets of high housing deprivation in the

South Wales cities and valleys, as well as in West and North Wales. This is shown in the

map below.

 The local authority with the highest concentration of areas in the most deprived 10% was

Ceredigion (28.3%). Merthyr Tydfil had the highest percentage of areas in the most deprived

50% in Wales (86.1%).

 Torfaen had no areas in the most deprived 10% in Wales and in Monmouthshire only 1.8%

of small areas (or 1 LSOA) fell in this group.

 For the housing domain, the most deprived area in Wales was Grangetown 9 in Cardiff,

around the North end of Corporation Road. In fact, the top four most housing deprived areas

in Wales were adjacent areas in Grangetown.

 When looking at the top 10 most housing deprived areas in Wales, 8 were in Cardiff (in

Grangetown and Riverside) with the other two in Swansea and Newport (Castle 6 and

Victoria 3, respectively). Previously, all were ranked within the top 31 most deprived areas in

the WIMD 2014 housing domain.

 There have been changes in the patterns of housing deprivation seen in WIMD 2019

compared to those seen in WIMD 2014. This is to be expected given the inclusion of the new

indicator on poor quality housing alongside the overcrowding measure (also used in WIMD

2014). An indicator on lack of central heating has been removed from the index, as

explained in the WIMD 2019 consultation summary.

8.4. Housing domain comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved from a more to a less deprived group. Below the diagonal are the numbers of areas which

have moved from a less to a more deprived group.

Table 17: Deprivation group movements for the Housing domain between WIMD 2014

and 2019

Relatively more deprived: Four areas have moved from the least deprived 50% group in WIMD 2014

to the 10% most deprived group in WIMD 2019. Three of these areas are in rural villages in

Flintshire, Monmouthshire and Denbighshire, with one area on the outskirts of a town in Bridgend

(Maesteg). These changes are driven by relatively high rates in the new poor quality housing

indicator.

Relatively less deprived: Twelve areas have moved from the 10% most deprived group in WIMD

2014 to the 50% least deprived group in WIMD 2019. All of these areas were in relatively urban

areas spread across Wales, with half (six) in Cardiff. Despite having relatively high rates of

overcrowding, these areas have low likelihood of poor quality housing

The two indicators are now weighted equally in the domain, whereas in WIMD 2014, the overcrowding

indicator was weighted higher (67%) than the (previous) other indicator on lack of central heating (33%).

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

105 32 15 27 12 191

10-20% most

deprived

(ranks 192-382)

46 46 35 43 21 191

20-30% most

deprived

(ranks 383-573)

19 46 26 53 47 191

30-50% most

deprived

(ranks 574-955)

17 46 63 130 126 382

50% least

deprived

(ranks 956-1909)

4 21 52 129 748 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Housing domain 2019

Housing domain 2014

8.5. Housing domain local authority analysis

The chart below shows the spread of housing domain ranks for each local authority in Wales. The

blue boxes contain half the total number of small areas in each local authority, centred on the

median (middle) rank for each local authority and the ‘whiskers’ show the full range of ranks.

Deprivation increases with decreasing rank (that is, towards the bottom of the plot).

Chart 9: Box plot of WIMD 2019 housing domain ranks, by local authority

The table below shows, for the housing domain of WIMD 2019, the percentage of small areas

(LSOAs) in each local authority which were in the most deprived 10%, 20%, 30% and 50% areas in

Wales.

Table 18: Concentrations of WIMD 2019 Housing deprived areas, by local authority

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc.) of all small areas in Wales.

This method can be seen as identifying the concentration of the most deprived areas in a local

authority, rather than an average level of deprivation.

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 2.3 20.5 27.3 47.7

Gwynedd 73 21.9 39.7 49.3 75.3

Conwy 71 8.5 18.3 28.2 46.5

Denbighshire 58 15.5 27.6 32.8 60.3

Flintshire 92 2.2 12.0 20.7 42.4

Wrexham 85 5.9 11.8 22.4 47.1

Powys 79 2.5 12.7 30.4 54.4

Ceredigion 46 28.3 47.8 58.7 78.3

Pembrokeshire 71 7.0 9.9 19.7 47.9

Carmarthenshire 112 11.6 20.5 33.9 53.6

Swansea 148 7.4 15.5 23.6 41.2

Neath Port Talbot 91 2.2 11.0 24.2 46.2

Bridgend 88 4.5 11.4 17.0 35.2

Vale of Glamorgan 79 6.3 12.7 16.5 26.6

Rhondda Cynon Taf 154 7.8 21.4 39.0 60.4

Merthyr Tydfil 36 22.2 36.1 52.8 86.1

Caerphilly 110 3.6 12.7 24.5 55.5

Blaenau Gwent 47 10.6 27.7 40.4 61.7

Torfaen 60 0.0 13.3 23.3 38.3

Monmouthshire 56 1.8 10.7 17.9 35.7

Newport 95 12.6 25.3 27.4 37.9

Cardiff 214 25.7 31.8 39.7 51.9

Wales 1909 10 20 30 50

The local authority with the highest proportion of areas in the most deprived 10% in Wales was

Ceredigion (28.3%, or 13 areas). These are mainly areas in sparse villages with relatively high

likelihood of poor quality housing, but also a few areas in towns (Aberystwyth, Cardigan and

Lampeter) with relatively high overcrowding rates.

Torfaen had no small areas in the most deprived 10% in Wales and in Monmouthshire only 1.8% of

areas (1 LSOA) fell in this group. Only 26.6% of the small areas in the Vale of Glamorgan were in

the most deprived 50% in Wales.

Merthyr Tydfil had the highest percentage of areas in the most deprived 50% in Wales (86.1%). The

next highest was Ceredigion, with 78.3% of its areas in the most deprived half of Wales.

8.6. Housing domain methodological changes between WIMD 2014 and WIMD 2019

In WIMD 2014 there was a lack of appropriate data available and it was not possible to measure

fully housing deprivation according to our definition. The housing domain previously included two

2011 Census indicators:

 The percentage of the population living in overcrowded households (weighted 66.6%)

 The percentage of people living in a household with no central heating (weighted 33.3%)

In WIMD 2019, the housing domain continues to include the indicator on overcrowding (to capture

availability and to some extent living condition), and also consists of a modelled indicator on poor

quality housing. This indicator helps to capture both physical and living conditions.

The new indicator is calculated using a model built from survey data, which makes probabilistic

predictions about individual level dwellings in Wales, using a range of administrative datasets as

inputs. This allows us to estimate the likelihood that dwellings in a given area:

 contain a Category 1 hazard for excess cold, falls or other hazards under the Housing Health

and Safety Rating System (HHSRS)

 or are in a state of disrepair

A dwelling is determined to have a category 1 hazard as a result of excess cold if there is a severe

threat from sub-optimal indoor temperatures. A dwelling is assessed as having a category 1 hazard

in terms of falls if there is determined to be a serious risk of falling on stairs, between levels, level

surfaces or falling associated with a bath, shower or similar facility.

A dwelling is said to be in disrepair if at least one of the key building components is old and needs

replacing or major repair due to its condition; or more than one of the other building components are

old and need replacing or major repair.

Note that there is a requirement for social housing to maintain the Welsh Housing Quality Standard

(WHQS), and therefore in areas where there is a high proportion of social housing, the modelled

data tends to show a lower likelihood of poor quality housing.

This is the first instance of using modelled data in any domain of WIMD. This exercise has improved

the range of information on housing available at the local area, using indicators which align closely

with our definition of housing deprivation. Our quality assurance process, which involved local

authority officials, suggests that the model is reasonably accurate. One drawback of using this

approach on an ongoing basis would be possible limitations in reflecting the impact of recent

housing interventions or other changes. If informing decisions, modelled data should be used

alongside robust, up-to-date local data or intelligence wherever possible. We will seek to explore

alternative (non-modelled) sources for future indices, as outlined in our consultation summary.

As a result of the indicator changes that better capture housing deprivation, the housing domain has

been given an increased weight in the overall index in WIMD 2019. The domain now has a relative

weight of 7% in the overall index, increasing from 5% in the 2014 index.

Full technical information on the domain is available in the Technical Report.

8.7. Housing domain background information

Homelessness

Homelessness can be considered to be the most extreme form of deprivation in relation to access

to housing. Data relating to statutory homelessness are available at Local Authority level. Rough

Sleeper data are also available at Local Authority level.

Housing Conditions Evidence Programme

Established in 2016, the Housing Conditions Evidence Programme (HCEP) is a strategic

programme of investment in evidence about the condition and energy efficiency/ performance of

housing in Wales. It encompasses:

 the Welsh Housing Conditions Survey, which collects information about the condition and

energy efficiency of all types and tenures of housing in Wales, and was last conducted in

2017-18.

 the Housing Stock Analytical Resource for Wales, which aims to bring together a range of

data on the characteristics, fabric, condition and energy efficiency of the housing stock in

Wales. This resource is still at an early stage of development, but will be considered in future

index iterations, subject to the continuation of the HCEP.

Fuel Poverty

As defined in the Welsh Government’s Fuel Poverty Strategy, a household in Wales is in fuel

poverty if they spend 10% or more of their income (including Housing Benefit, Income Support for

Mortgage Interest or council tax benefits) on energy costs in order to adequately heat their homes.

Fuel poverty has a significant impact on the health, social and economic well-being of

householders. Fuel Poverty estimates for Wales for 2018 have been published and modelled Local

Authority analysis will be published in due course. However data are not currently available at small

area level.

Energy Efficiency

Information on Standard Assessment Procedure (SAP) ratings could be regarded as a broad proxy

for Housing quality. Homes with poor energy efficiency performance are more difficult/expensive to

heat. An Energy Performance Certificate (EPC) is required for properties when constructed, sold or

let. The EPC provides details on the energy performance of the property and what can be done to

improve it. EPC data has been published by the Ministry for Housing, Communities and Local

Government. Although coverage of EPC records across LSOAs was quite good, it is not complete

and poses risk of bias. Many records are several years out of date.

9. Community Safety domain

9.1. Introduction

This domain is intended to consider deprivation relating to living in a safe community. It covers

actual experience of crime and fire, as well as perceptions of safety whilst out and about in the local

area. The domain has a relative weight of 5% in the overall index. The indicators are weighted as

shown below. For a complete description of the construction of the domain, please see the WIMD

2019 Technical Report.

9.2. Indicators

The domain contains 6 indicators, weighted as shown below:

Five of these indicators are derived from Police Recorded Crime data:

 The indicator on Police Recorded Criminal Damage measures the number of reported incidents

of criminal damage as a percentage of the resident population, excluding the prison population,

and is based on a two-year (2017-18 and 2018-19) average.

 The indicator on Police Recorded Violent Crime measures the number of reported incidents of

violent crime as a percentage of the resident population, excluding the prison population, and is

based on a two-year (2017-18 and 2018-19) average.

 The indicator on Police Recorded Theft measures the number of reported incidents of theft as a

percentage of the resident population, excluding the prison population, and is based on a two-

year (2017-18 and 2018-19) average.

 The indicator on Police Recorded Burglary measures the number of reported incidents of

burglary as a percentage of the number of dwellings and business addresses, and is based on a

two-year (2017-18 and 2018-19) average.

 The indicator on Anti-Social Behaviour incidences measures the number of reported incidents of

anti-social behaviour as a percentage of the resident population, excluding the prison population,

and is based on a two-year (2017-18 and 2018-19) average.

The sixth indicator uses fire incidence data.

 The indicator on Fire Incidences measures the number of fire incidents attended as a percentage

of the resident population, and is based on a two-year (2017-18 and 2018-19) average. The data

are derived from the Fire and Rescue Services (FRS) reporting, compiled by Welsh Government.

For a full explanation of how these indicators are calculated and combined together, please see the

WIMD 2019 Technical Report.

9.3. Community Safety domain key results

 In the WIMD 2019 community safety domain, there were pockets of high deprivation in the

South Wales valleys, the large cities in South Wales, and the coastal and border towns in

North Wales. This is shown in the map below.

 The local authorities with the highest concentration of areas in the most deprived 10% were

Newport (35.8%) followed by Blaenau Gwent (27.7%). Monmouthshire had the lowest

proportion of areas in the most deprived 10% (1.8%, or 1 LSOA).

 For the community safety domain, the most deprived small area in Wales was Cathays 10, in

Cardiff city centre, which includes Cathays Park and Bute Park.

 The overall patterns of community safety deprivation in WIMD 2019 are similar to those for

WIMD 2014.

 At a Wales level, there was a notable increase in the violent crime indicator and smaller

increases in the criminal damage and fire incidences indicators. Whereas decreases were

observed in the burglary, theft and anti-social behaviour indicators.

9.4. Community safety domain comparison between WIMD 2014 and WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved from a more to a less deprived group. Below the diagonal are the numbers of areas which

have moved from a less to a more deprived group.

Table 19: Movement between Community Safety deprivation groups between WIMD

2014 and 2019

Relatively more deprived: 65 areas have moved into the 10% most deprived group for this domain

in WIMD 2019. These are mostly in urban city and town areas, with Newport and Caerphilly having

the largest share. One area in Neath Port Talbot moved from the 50% least deprived group due to

notable increases in all crime types.

Relatively less deprived: 65 areas have moved out of the 10% most deprived group for this domain

in WIMD 2019. These are spread across most local authorities with Cardiff comprising the majority.

One area, in the Vale of Glamorgan, moved from the 10% most deprived group in WIMD 2014 to

the 50% least deprived group in WIMD 2019. This was driven primarily by decreases in the criminal

damage, anti-social behaviour and theft indicators.

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

126 40 15 9 1 191

10-20% most

deprived

(ranks 192-382)

38 62 50 34 7 191

20-30% most

deprived

(ranks 383-573)

18 46 50 61 16 191

30-50% most

deprived

(ranks 574-955)

8 33 62 166 113 382

50% least

deprived

(ranks 956-1909)

1 10 14 112 817 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Community safety domain 2019

Community safety domain 2014

9.5. Community safety domain local authority analysis

The chart below shows the spread of community safety domain ranks for each local authority in

Wales. The blue boxes contain half the total number of areas in each local authority, centred on the

median (middle) rank for each local authority and the ‘whiskers’ show the full range of ranks.

Deprivation increases with decreasing rank (that is, towards the bottom of the plot).

Chart 10: Box plot of WIMD 2019 Community Safety domain ranks, by local authority

The table below shows, for the community safety domain of WIMD 2019, the percentage of small

areas (LSOAs) in each local authority which were in the most deprived 10%, 20%, 30% and 50%

areas in Wales.

Table 20: Concentrations of WIMD 2019 Community Safety deprived areas, by local

authority

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 6.8 15.9 22.7 40.9

Gwynedd 73 6.8 12.3 27.4 41.1

Conwy 71 8.5 16.9 28.2 50.7

Denbighshire 58 10.3 22.4 29.3 39.7

Flintshire 92 8.7 13.0 25.0 39.1

Wrexham 85 18.8 31.8 47.1 68.2

Powys 79 5.1 7.6 11.4 20.3

Ceredigion 46 6.5 13.0 15.2 26.1

Pembrokeshire 71 8.5 16.9 21.1 31.0

Carmarthenshire 112 5.4 12.5 17.0 33.9

Swansea 148 10.1 21.6 27.7 47.3

Neath Port Talbot 91 5.5 11.0 18.7 37.4

Bridgend 88 2.3 10.2 12.5 40.9

Vale of Glamorgan 79 2.5 12.7 20.3 34.2

Rhondda Cynon Taf 154 3.2 9.7 23.4 58.4

Merthyr Tydfil 36 5.6 27.8 38.9 75.0

Caerphilly 110 14.5 30.0 46.4 77.3

Blaenau Gwent 47 27.7 53.2 78.7 97.9

Torfaen 60 15.0 38.3 58.3 71.7

Monmouthshire 56 1.8 5.4 7.1 23.2

Newport 95 35.8 47.4 54.7 75.8

Cardiff 214 11.2 22.9 36.9 57.5

Wales 1909 10 20 30 50

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

 The local authority with the highest concentration of areas in the most deprived 10% in

Wales was Newport (35.8%, or 34 areas).

 The local authority with the lowest proportion of areas in the most deprived 10% in Wales

was Monmouthshire (1.8%, or 1 LSOA). Only 20.3% of the areas in Powys were in the most

deprived 50% in Wales.

 Blaenau Gwent had the highest percentage of areas in the most deprived 50% in Wales

(97.9%). The next highest was Caerphilly, with 77.3% of its areas in the most deprived half

of Wales.

9.6. Community Safety domain methodological changes between WIMD 2014 and

WIMD 2019

Minor changes have been made to the methodology for constructing the crime and incident

numerators. These changes include the adoption of the same geographical aggregation technique

and constraining technique as used in the Crime Domain of the English Indices of Deprivation 2019.

The two-stage quality assurance process with the police forces also mirrors that adopted in the

Crime Domain of the English Indices of Deprivation 2019. For further details, please see the WIMD

2019 Technical Report.

In addition, small changes to the detailed categories composing each of the recorded crime

indicators were necessitated due to changes to the Home Office Counting Rules since the

publication of WIMD 2014.

9.7. Community Safety domain background information

Police Recorded Crime

Since the publication of WIMD 2014, there has been a renewed focus on the quality of crime

recording by the police. This follows the inspections of forces by Her Majesty’s Inspectorate of

Constabulary (HMIC), the Public Administration Select Committee (PASC) inquiry into crime

statistics and the UK Statistics Authority’s decision to remove the National Statistics designation

from police recorded crime statistics in January 2014.

This renewed focus is thought to have led to improved compliance with the National Crime

Recording Standard (NCRS), leading to the recording of a greater proportion of crimes coming to

the attention of the police. It was considered and agreed by the community safety domain group that

police recorded crime data remained the best source of crime data available for WIMD 2019 at the

small area level.

Police.UK

The Police.UK website allows users to explore and compare crime and outcomes of crime in local

areas.

Additional Crime Data: The Crime Survey for England and Wales

The Crime Survey for England and Wales measures the extent of crime in England and Wales by

asking people whether they have experienced any crime in the past year. The Crime Survey

records crimes that may not have been reported to the police and it is therefore used alongside the

police recorded crime figures to show a more accurate picture of the level of crime in the country.

An additional element that the Crime Survey provides is information on perceptions of crime and

anti-social behaviour. This is a key element of community safety deprivation, in terms of feeling safe

whilst out and about in your local area. Data and further information on the Crime Survey for

England and Wales can be found on the Office for National Statistics' website. These data are not

included in WIMD 2019, as the data are not statistically robust below a Wales level.

Feeling unsafe – National Survey for Wales

The National Survey for Wales asks about feeling unsafe after dark in your local area. Perceptions

of safety are included in the definition of community safety deprivation. Further information and data

can be found on the Welsh Government website.

Violence Against Women, Domestic Abuse and Sexual Violence.

Earlier this year the Welsh Government consulted on a range of indicators to underpin its Violence

Against Women, Domestic Abuse and Sexual Violence (VAWDASV) strategy. The responses to this

consultation have been reviewed and ongoing stakeholder engagement is currently being

undertaken to further inform indicator development.

10. Physical Environment Domain

10.1. Introduction

The purpose of this domain is to measure factors in the local area that may impact on the wellbeing

or quality of life of those living in an area. The domain has a relative weight of 5% in the overall

index. The sub domains and indicators are weighted as shown below. For a complete description of

the construction of the domain, please see the WIMD 2019 Technical Report.

10.2. Indicators

The domain contains three sub domains, weighted as shown below:

The air quality sub-domain comprises three indicators which measure the population weighted

average concentration values of the key pollutants Nitrogen dioxide (NO

), Particulates < 10 µm

(PM

) and Particulates < 2.5 µm (PM

2.5

) respectively. The indicator values are based on pollutant

levels from 2017 DEFRA air concentration grids and are population-weighted then combined to form

an air quality sub domain score.

The flood risk sub domain score is based on the proportion of households at risk of flooding from

rivers, the sea or surface flooding and is sourced from Natural Resources Wales’ Flood Risk

Assessment Wales (FRAW) dataset.

The green space sub domain is comprised of two equally weighted indicators:

 Proximity to accessible natural green space indicator which measures the proportion of

households in each area that are within a 5 minute walk / 300 metres of an accessible,

natural green space, and

 Ambient green space score which measures the ambient greenness of an area using the

mean household Normalised Difference Vegetation Index (NDVI) score within a 300 metre

buffer around each residential dwelling.

Further guidance to help interpretation and understanding of the green space sub-domain indicator

data can be found in section 10.6. A full explanation of how these indicators are calculated and

combined together can be found in the WIMD 2019 Technical Report.

10.3. Physical Environment domain key results

 In the WIMD 2019 physical environment domain, there were pockets of high deprivation in

and around the large cities in South East Wales and, to a lesser extent, the South Wales

valleys. On the whole, deprivation levels were lower in the North Wales local authorities.

This is shown in the map below.

 The local authorities with the highest concentration of areas in the most deprived 10% were

Newport (43.2%) and Cardiff (43.0%). Whereas Blaenau Gwent, Conwy, Isle of Anglesey,

Pembrokeshire and Wrexham had no areas in the most deprived 10%.

 In the physical environment domain, the most deprived small area in Wales was Penylan 5

in Cardiff, the area around Waterloo Gardens and part of Newport Road.

 The overall patterns of physical environment deprivation in WIMD 2019 are notably different

to those for WIMD 2014. However, this is partly due to a number of methodological changes

between WIMD 2014 and WIMD 2019. These changes have been designed and

implemented to better reflect deprivation in terms of physical environment and how it impacts

on peoples’ wellbeing or quality of life. Further information can be found in section 10.6.

10.4. Physical Environment domain comparison between WIMD 2014 and

WIMD 2019

The full set of domain ranks from WIMD 2019 and the underlying indicators can be downloaded

from the Welsh Government’s StatsWales web pages.

The table below shows the number of small areas (LSOAs) in each of the WIMD deprivation groups

for WIMD 2014 and WIMD 2019. The diagonal, in bold, shows the number of areas which have

remained in the same deprivation group. Above the diagonal are numbers of areas which have

moved from a more to a less deprived group. Below the diagonal are the numbers of areas which

have moved from a less to a more deprived group.

Table 21: Movement between Physical Environment deprivation group between

WIMD 2014 and 2019

Caution should be used in interpreting the table above. A number of methodological changes to the

domain mean that it is difficult to interpret changes between WIMD 2014 and WIMD 2019. See

section 10.6 for further details.

Relatively more deprived: 99 areas have moved into the 10% most deprived group for this domain

in WIMD 2019. Over half of these areas were in Cardiff or Newport with the remainder spread

across 13 other local authorities. The movements were driven by changes in all of the sub domains.

However, the 13 areas moving from the least deprived 50% into the 10% most deprived were

10% most

deprived

(ranks

1-191)

10-20%

most

deprived

(ranks

192-382)

20-30%

most

deprived

(ranks

383-573)

30-50%

most

deprived

(ranks

574-955)

50% least

deprived

(ranks

956-1909)

Total

(ranks

1-1909)

10% most

deprived

(ranks 1-191)

92 29 18 26 26 191

10-20% most

deprived

(ranks 192-382)

47 37 26 31 50 191

20-30% most

deprived

(ranks 383-573)

22 38 27 42 62 191

30-50% most

deprived

(ranks 574-955)

17 51 58 96 160 382

50% least

deprived

(ranks 956-1909)

13 36 62 187 656 954

Total

(ranks 1-1909)

191 191 191 382 954 1909

Physical Environment domain 2019

Physical Environment domain 2014

primarily attributable to a combination of the inclusion of surface flooding in the flood risk sub

domain and/or the introduction of the green space sub domain.

Relatively less deprived: 99 areas have moved out of the 10% most deprived group for this domain

in WIMD 2019. These areas were spread across 17 local authorities. However, nearly a third of

these areas (31) were in Flintshire which was notably affected by the methodological changes to the

sub-domains (in particular, the inclusion of the green space sub-domain and the exclusion of the

proximity to waste disposal and industrial site sub-domain). Twenty-six areas moved 5 or more

deciles and these movements were primarily due to the introduction of the green space sub-domain.

Changes to the air quality sub-domain were also a contributory factor.

10.5. Physical environment domain local authority analysis

The chart below shows the spread of physical environment domain ranks for each local authority in

Wales. The blue boxes contain half the total number of areas in each local authority, centred on the

median (middle) rank for each local authority and the ‘whiskers’ show the full range of ranks.

Deprivation increases with decreasing rank (that is, towards the bottom of the plot).

Chart 11: Box plot of WIMD 2019 physical environment domain ranks, by local

authority

The table below shows, for the physical environment domain of WIMD 2019, the percentage of

small areas (LSOAs) in each local authority which were in the most deprived 10%, 20%, 30% and

50% areas in Wales.

Table 22: Concentrations of WIMD 2019 Physical Environment deprived areas, by

local authority

Local authority

Number of

LSOAs in

local

authority

% LSOAs in

most-

deprived

10%

ranks 1-191

% LSOAs in

most-

deprived

20%

ranks 1-382

% LSOAs in

most-

deprived

30%

ranks 1-573

% LSOAs in

most-

deprived

50%

ranks 1-955

Isle of Anglesey 44 0.0 0.0 0.0 2.3

Gwynedd 73 1.4 2.7 2.7 16.4

Conwy 71 0.0 2.8 12.7 21.1

Denbighshire 58 1.7 5.2 5.2 25.9

Flintshire 92 1.1 5.4 9.8 23.9

Wrexham 85 0.0 0.0 3.5 8.2

Powys 79 1.3 3.8 8.9 26.6

Ceredigion 46 2.2 2.2 6.5 23.9

Pembrokeshire 71 0.0 1.4 4.2 36.6

Carmarthenshire 112 3.6 21.4 32.1 47.3

Swansea 148 1.4 4.7 16.2 35.8

Neath Port Talbot 91 8.8 26.4 33.0 59.3

Bridgend 88 4.5 9.1 22.7 39.8

Vale of Glamorgan 79 6.3 10.1 24.1 59.5

Rhondda Cynon Taf 154 7.1 20.1 35.1 63.0

Merthyr Tydfil 36 13.9 22.2 33.3 52.8

Caerphilly 110 6.4 15.5 25.5 57.3

Blaenau Gwent 47 0.0 8.5 23.4 48.9

Torfaen 60 6.7 13.3 30.0 68.3

Monmouthshire 56 5.4 30.4 42.9 67.9

Newport 95 43.2 68.4 80.0 95.8

Cardiff 214 43.0 67.3 85.0 98.6

Wales 1909 10 20 30 50

One way of considering WIMD data at the local authority level is to look at the proportion of areas

within the local authority that are in the most deprived 10% (or 20% etc) of all areas in Wales. This

method can be seen as identifying the concentration of the most deprived areas in a local authority,

rather than an average level of deprivation.

 The local authority with the highest concentration of areas in the most deprived 10% in

Wales was Newport (43.2%, or 41 areas) closely followed by Cardiff (43.0%, or 92 areas).

This is primarily attributable to the impact of the air quality and green space sub-domains.

 The local authorities with the lowest proportion of areas in the most deprived 10% in Wales

were Blaenau Gwent, Conwy, Isle of Anglesey, Pembrokeshire and Wrexham who had none

of their areas in the most deprived 10%. Only 2.3% of the areas in Isle of Anglesey were in

the most deprived 50% in Wales.

 Cardiff had the highest percentage of areas in the most deprived 50% in Wales (98.6%). The

next highest was Newport, with 95.8% of its areas in the most deprived half of Wales.

10.6. Physical environment domain methodological changes between WIMD

2014 and WIMD 2019

Air Quality sub-domain

The indicators in the air quality sub domain were simplified to focus on the pollutants Nitrogen

dioxide (NO

), Particulates < 10 µm (PM

) and Particulates < 2.5 µm (PM

2.5

). This change was

intended to align the sub-domain more closely with the national well-being indicators and to reflect

that these three pollutants are of prime concern to health nationwide. However, the exclusion of

certain pollutants (for example, Sulphur Dioxide) may contribute to historically heavily industrial

areas seeming to be less deprived than in WIMD 2014.

Flood Risk sub-domain

The WIMD 2019 flood risk sub-domain was calculated using a beta version of the Flood Risk

Assessment Wales (FRAW) dataset as provided by Natural Resources Wales. This dataset differs

significantly in terms of modelling methodology and inputs from the National Flood Risk Assessment

(NaFRA) flood risk dataset used to inform WIMD 2014.

In particular, the FRAW dataset includes information on flood risk from rivers, the sea and surface

water flooding. However, this is a change from WIMD 2014 where the flood risk sub-domain data

did not consider surface water flooding.

The inclusion of risk arising from surface water flooding has resulted in higher levels of deprivation

due to flooding being observed in certain local authorities. In particular, a number of areas in

Merthyr Tydfil and Rhondda Cynon Taf become markedly more deprived when surface water

flooding is considered.

Green Space sub-domain

The green space sub-domain has been developed to replace the proximity to waste disposal and

industrial sites sub-domain that was previously included in WIMD 2014.

The proximity to waste disposal and industrial sites sub-domain was originally developed as a proxy

measure to capture the general quality of life arising from living in a particular area. However, it had

some known limitations as it estimated the impact of regulated waste disposal and industrial sites

but did not capture proximity to non-regulated sites (which arguably will have more impact on the

surrounding environment).

Natural green space is considered to have a positive impact on people’s well-being and the green

space sub-domain has been developed to capture deprivation arising from its absence. Given that

the green space sub domain and the proximity to waste disposal and industrial sites sub domain are

measuring conceptually distinct things, we would expect to see differences between them.

Note that both indicators in the green space sub domain focus on the area immediately surrounding

the residential dwellings within an area as opposed to the LSOA area in its entirety. This aligns with

the methodologies underpinning the air quality and flood risk sub-domains (which are population-

weighted and focussed on households in flood risk areas respectively).

Further to this, the green space sub-domain specifically looks at proximity to accessible, natural

green space – i.e. sites that could confidently be described as ‘natural feeling’ places to which the

public have right of access.

Therefore, some rural or semi-rural areas may have higher levels of green space deprivation than

expected due to the inaccessibility of green space in the area and/or the absence of green space in

close proximity to residential dwellings in the area.

We will continue to monitor ongoing developments in the measurement of green space and, where

appropriate, consider refinements to this sub domain for the next iteration of WIMD.

10.7. Physical Environment domain background information

Air quality

Further information on the UK Government’s Pollution Climate Mapping (PCM) model which

calculates average pollutant concentrations for each square kilometre of the UK can be found on

the DEFRA website. Information on national well-being indicator 5 (Levels of Nitrogen Dioxide

pollution in the air) can be found on the Welsh Government Well-being of Wales website.

Flood risk

A range of reports, evidence and data on flooding can be found on the Natural Resources Wales

website.

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Green space

Data on people’s perceptions of and satisfaction with local green space is collected as part of the

National Survey for Wales. Headline results can be found in the National Survey for Wales Results

Viewer.

A Green Space Index including data for Wales has been published by Fields in Trust.

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Annex A: Further background to WIMD

1. Development and User engagement

During 2018, statisticians at the Welsh Government worked with seven expert topic groups to

review indicators used in WIMD 2014 and to consider potential new indicators for WIMD 2019. Each

topic group included analytical experts from the Welsh Government, local authorities, other public

bodies (for example, Natural Resources Wales, Public Health Wales) and policy representatives

from the Welsh Government. An Advisory Group including key users of the Index from public bodies

and third sector organisations also helped shape the proposals.

A public consultation on proposed indicators for WIMD 2019 was held between October and

December in 2018. The purpose of this consultation was to expose proposals for the domains and

indicators for WIMD 2019 to critical review. Responses were received from a range of different

organisations and individuals. A summary of these responses, and changes made in light of

consultation responses, was published in April 2019.

We will continue to share information with users about WIMD 2019, and seek input to future

iterations through seminars, conferences and bespoke events. We welcome any feedback on any

aspect of these statistics which can be provided by email to stats.inclusion@gov.wales.

2. Key quality information

WIMD is a complex statistical product drawing on a range of data sources, some National or Official

Statistics themselves, others based on administrative datasets. A brief summary of quality

information is provided below along with links to further information. More detailed documentation of

WIMD 2019 quality information will be made available in future, based on the Office for Statistics

Regulation’s Administrative Data Quality Assurance Toolkit.

Relevance

Our Consultation documents outline the rationale behind the choice of indicators to reflect different

aspects of deprivation.

Accuracy

WIMD 2019 follows on from the previous iterations of the index and has been designed to ensure

the reliability of results. Our Consultation document includes details of the indicator criteria applied.

WIMD 2019 brings together 47 independent indicators from a wide range of data sources, which

ensures robustness of the overall results. Areas that are very deprived according to WIMD are likely

to be very deprived on a number of the domains. Due to the variety of data inputs, there is little

chance that an area is identified as very deprived due to a bias in any one of the underlying

indicators.

102

In terms of the accuracy of the processing of the underlying data, there was an agreed Quality

Assurance plan for WIMD 2019 which outlined several stages of data checks, including:

 Replicating results for any new or changed indicators with different analysis tools

 Sense-checking data with the expert topic groups, and local authority representatives

Timeliness and punctuality

We use the latest available information for all indicators. Our Technical Report described the time

period associated with each indicator, and this has also been brought together in a spreadsheet for

ease of reference.

Accessibility and clarity

In 2016 we surveyed users about our WIMD 2014 results package, and since users were broadly

content with the 2014 offering, we have continued to produce the same range of outputs, with

improvements where possible. We have published results in a range of formats to help different

types of users access and interpret WIMD results. Full details and signposting is available on the

WIMD webpages.

Comparability and coherence

Our Guidance provides further information about indices of deprivation for the other three countries

of the UK, and why results should not be compared across countries.

3. National Statistics status

The United Kingdom Statistics Authority has designated these statistics as National Statistics, in

accordance with the Statistics and Registration Service Act 2007 and signifying compliance with the

Code of Practice for Statistics.

National Statistics status means that official statistics meet the highest standards of trustworthiness,

quality and public value.

All official statistics should comply with all aspects of the Code of Practice for Statistics. They are

awarded National Statistics status following an assessment by the UK Statistics Authority’s

regulatory arm. The Authority considers whether the statistics meet the highest standards of Code

compliance, including the value they add to public decisions and debate.

It is Welsh Government’s responsibility to maintain compliance with the standards expected of

National Statistics. If we become concerned about whether these statistics are still meeting the

appropriate standards, we will discuss any concerns with the Authority promptly. National Statistics

status can be removed at any point when the highest standards are not maintained, and reinstated

when standards are restored.

These statistics last underwent a full assessment against the Code of Practice in 2010.

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Annex B: List of all indicators included in WIMD 2019

Additional information is available in the Technical Report.

Indicator

Units

Denominator

Indicator

Year(s)

Data Source

Income Domain

Percentage of population in receipt

of income-related benefits

Percentage

Small Area

Population

Estimates 2016

(minus 2016

prison

population),

ONS

Defined as those who are either:

(a) An adult, or dependent child of

an adult, in receipt of income

related benefits

2016/17

Department

for Work and

Pensions

(DWP)

(b) An adult, or dependent child of

an adult, in receipt of Working and

Child Tax Credits, with income less

than 60% of the Wales median

Aug-15

Her Majesty’s

Revenue and

Customs

(HMRC)

by Section 95)

Jun-17

Home Office

(HO)

(d) People on Universal Credit

(except those “working with no

requirements”)

2016/17

DWP

Employment Domain

Percentage of working-age

population in receipt of employment

related benefits (job-seekers

allowance, employment support

allowance, or Universal Credit and

not in employment)

Percentage

Small Area

Population

Estimates 2016

(minus 2016

prison

population),

ONS

2016/17

DWP

Health

People with a GP-recorded

diagnosis of a Chronic condition

(indirectly age-sex standardised)

[Coronary Heart Disease, Chronic

Obstructive Pulmonary Disease,

Stroke and Transient Ischaemic

Attack, Peripheral Arterial Disease,

Chronic Kidney Disease, Diabetes

Mellitus, or Epilepsy]

Rate per

100

Small Area

Population

Estimates 2018

(minus 2018

prison

population),

ONS

31st

March

2019

NHS Wales

Informatics

Service

Limiting Long-Term Illness

(indirectly age-sex standardised)

Rate per

100

LSOA

population,

Census

2011

2011 Census,

Office for

National

Statistics

(ONS)

104

Indicator

Units

Denominator

Indicator

Year(s)

Data Source

Health (continued)

Premature Death Rate (death of

those under the age of 75)

Rate per

100,000

Small Area

Population

Estimates, ONS

2009-18

(10 year

average)

Death

Registrations,

ONS

People with a GP-recorded diagnosis

of a mental health condition

[Depression, Low mood (with active

repeat prescription for an anti-

depressant), Anxiety disorder

(including panic disorders),

Dementia, Severe mental illnesses

(schizophrenia, bipolar affective

disorder and other psychoses)]

Rate per

100

Small Area

Population

Estimates 2018

(minus 2018

prison

population),

ONS

31st

March

2019

NHS Wales

Informatics

Service

Cancer Incidence (indirectly age-sex

standardised)

Rate per

100,000

Small Area

Population

Estimates, ONS

2007-16

(10 year

average)

Welsh Cancer

Intelligence and

Surveillance

Unit, Velindre

NHS Trust

Low Birth Weight, Single Births (live

births less than 2.5 Kg)

Percentage

Number of

singleton live

births

2009-18

(10 year

average)

Birth

Registrations,

ONS

Children aged 4-5 who are Obese

Percentage

Number of

children aged 4-

5, CMP

2012/13 -

2017/18

Child

Measurement

Programme

(CMP), Public

Health Wales

Indicator

Units

Denominator

Indicator

Year(s)

Data Source

Education

Foundation Phase Average Point

Score

Point score

Total number of

pupils in

National

Curriculum Year

Group 2

Academic

Years

2015/16 -

2017/18

Pupil Level

Annual School

Census

(PLASC), NDC

Key Stage 2 Average Point Score

Point score

Total number of

pupils in

National

Curriculum Year

Group 6

Academic

Years

2015/16 -

2017/18

PLASC, NDC

Key Stage 4 Average Point Score for

Core Subjects

Point score

Total number of

pupils in

National

Curriculum Year

Group 11

Academic

Years

2015/16 -

2017/18

PLASC, NPD,

WED

105

Indicator

Units

Denominator

Indicator

Year(s)

Data Source

Education (continued)

Repeat Absenteeism

Percentage

Total numbers of

Primary and

Secondary pupils

Academic

Years

2015/16 -

2017/18

PLASC, NPD

Proportion of Key Stage 4 leavers

entering Higher Education

Percentage

Proportion of Key

Stage 4 leavers

entering Higher

Education

Academic

Years

2011/12 -

2014/15

PLASC, HESA,

LLWR

Number of adults aged 25-64 with

No Qualifications

Percentage

Total population

aged 25-64,

Census

2011

2011 Census,

ONS

Access to Services Domain

Physical Access – average return

travel times to key services by

public and private transport: food

shops, GP surgeries, primary

schools, secondary schools, post

office, public library, pharmacy,

sports facility, petrol station (private

transport only)

Minutes

N/A

Mar-19

Welsh

Government

Digital Access - % Unavailability of

broadband at 30Mb/s

Percentage

Number of

premises

Jan-19

The Office of

Communications

(Ofcom)

Housing

Percentage of people living in

overcrowded households (bedroom

measure)

Percentage

Number of people

living in

households,

Census

2011

2011 Census,

ONS

Likelihood of poor quality housing

(being in disrepair or containing

serious hazards)

Percentage

(likelihood)

Number of

residential

dwellings

2017/18

Building

Research

Establishment

Two sub-indicators are also

published, the likelihood that

dwellings:

• contain a Category 1 hazard for

excess cold, falls or other hazards

under the Housing Health and

Safety Rating System (HHSRS)

• are in a state of disrepair (at least

one of the key building components

is old and needs replacing or major

repair due to its condition; or more

than one of the other building

components are old and need

replacing or major repair)

106

Indicator

Units

Denominator

Indicator

Year(s)

Data Source

Physical Environment

Population weighted average

concentration values of Nitrogen

dioxide (NO

)

Values

N/A

2017

DEFRA,

ONS

Population weighted average

concentration values of

Particulates < 10 µm (PM

)

Values

N/A

2017

DEFRA,

ONS

Population weighted average

concentration values of

Particulates < 2.5 µm (PM

2.5

)

Values

N/A

2017

DEFRA,

ONS

Proximity to Accessible, Natural

Green Space – measuring the

proportion of households within

300 metres of an accessible,

natural green space

Percentage

Number of

households in

LSOA

2017

MasterMap

Topography

Layer,

AddressBase

Plus

Ambient Green Space Score –

measuring the mean household

Normalised Difference Vegetation

Index (NDVI)

Score

N/A

n/a -

Aerial

Imagery

captured

over re-

visional

time

series

WISERD

Flood Risk

Score

(between 1

and 100)

N/A

2017

FRAW, NRW

Community Safety

Police Recorded Criminal

Damage

Rate (per

100)

Small Area

Population

Estimates

2017 (minus

2017 prison

population),

ONS

2017/18,

2018/19

Welsh Police

Forces

Police Recorded Violent Crime

Police Recorded Anti-Social

Behaviour

Police Recorded Burglary

Police Recorded Theft

Fire Incidents

Rate (per

100)

Small Area

Population

Estimates

2017 (minus

2017 prison

population),

ONS

2017/18,

2018/19

Incident

Recording

System

(IRS), Welsh

Government