Understanding towns in England and Wales, investigating socioeconomic trends: May 2026

• Population in towns with lower income deprivation grew faster on average than those with higher income deprivation between 2001 and 2021, mainly caused by an increase in people in the age group 65 years and over.

• Across all types of towns, retirement was the main reason people were not working; overall, less deprived residential towns had on average the largest share of residents who were retired.

• Towns within 30 minutes' drive of other large urban areas, with lower deprivation and a high ratio of jobs to residents were most likely to have employment growth above the England and Wales average between 2015 and 2024.

• House prices were highest in less deprived towns, but have risen fastest in more deprived towns since 2001.

• Just over half of less deprived towns fell into the "more visited" visitor category, meaning many areas within them regularly drew in a high proportion of visitors compared with their resident population.

This article analyses data for 1,395 towns and cities in England and Wales with a population greater than 5,000 people, using the built-up areas (BUAs) 2024 geography. It develops on our previous Understanding towns articles.

To help understand the data, three classifications have been calculated for each town to enable us to group together towns that share some similar characteristics. Two of these classifications were used in previous Understanding towns articles, namely job density class (working or residential) and income deprivation measures (higher or lower deprivation). Having developed this two-part categorisation, we now include a "nearer" or "further" categorisation based on relative access derived from the 2021 Rural Urban Classification (RUC) methodology. This represents whether a town is within 30 minutes' drive of a town of at least 75,000 people (nearer) or not (further). This is a proxy for access to the wider goods, services and employment opportunities offered by major towns and cities.

All BUAs (except those in London) are classified using this framework and included in the reference dataset. However, the figures in this article concentrate on comparing those towns with higher or lower values for income deprivation, and job density. A high value gives a "working" categorisation and a low value a "residential" categorisation. For example, Leeds is classified as "nearer, higher deprivation working", while Porthcawl is classified as "further, lower deprivation residential".

Together, these form an eight-way combined categorisation:

• further, higher deprivation, residential

• further, higher deprivation, working

• further, lower deprivation, residential

• further, lower deprivation, working

• nearer, higher deprivation, residential

• nearer, higher deprivation, working

• nearer, lower deprivation, residential

• nearer, lower deprivation, working

This structure provides a basis for analysing socioeconomic differences and their access to major urban centres. When combined with indicators such as population growth, house prices and demographic change, it offers context for geographic patterns of change since 2001.

Between the 2001 Census and Census 2021, the population of England and Wales increased by 14.6%, rising from 52.0 million to 59.6 million people. However, this growth has not been uniform, it has varied across individual towns and cities.

Figure 1 shows how populations have changed across different categories of town. The largest growth was in the nearer, lower deprivation, residential category in which towns had an average population increase of 25.6%. Other lower deprivation categories had smaller, but still substantial, growth (between 16.4% and 16.8%).

More generally, average population growth was higher in working higher deprivation towns, while lower average growth occurred across residential higher deprivation towns. For further details of these categories, please see Section 9: Glossary.

Many towns in this latter group are coastal communities. Coastal towns had a lower average growth (7.5%) compared with the average growth across non‑coastal towns (17.4%). A full list of coastal towns can be found in our Understanding towns in England and Wales, investigating socioeconomic trends dataset.

Demographic change

Figure 2 shows the population change by town category from 2001 to 2021 by age group. Clear patterns emerge across age ranges.

The fastest growing demographic in all categories was people aged 65 years and over. Average growth in this group was highest in lower deprivation towns, where the population growth in those aged 65 years and over was often double that in higher deprivation equivalents. Examples include Sandhurst (96.9% growth) and Portishead (92.2% growth).

The previous section showed that the population aged 65 years and over had grown faster than other age groups in most towns across England and Wales. This affects how many people are economically active. Figure 3 shows the share of population aged 16 years and over in each town who were economically inactive because of retirement in 2021.

In "nearer" towns, those located within 30 minutes' drive of major towns and cities, lower deprivation towns had a higher share of retirees than higher deprivation towns. In "further" towns, however, retirement rates were high across all groups, regardless of deprivation. Some coastal towns in these further locations, such as Walton-on-the-Naze, had particularly large, retired populations - over 40% of adults aged 16 years and over.

Figure 3: On average, nearer, lower deprivation towns had the highest proportions of retired people, while further higher deprivation coastal towns had some of the highest shares of retired people across any combined category

"Economically inactive- retired" proportions among towns, by combined category, England and Wales, 2021, % of usual residents aged 16 years and over

Notes:

1. All economic inactivity categories are based on the Census 2021 population aged 16 years and over.

While Figure 3 displays the retired population as a proportion of the whole population aged 16 years and over, Figure 4 focuses only on people who are aged 16 years and over and economically inactive - those not working or actively seeking work. It breaks down the economically inactive population by reason for inactivity.  

Alongside retirement, Figure 4 highlights other patterns. For example, student numbers were particularly high in nearer working locations, which includes many of the largest urban areas in England and Wales. It also shows long-term sickness and disability was a more common reason for economic inactivity in higher deprivation towns.

Figure 5 shows the changes in employment levels across towns between 2015 and 2024 based on the Business Register Employment Survey (BRES). Over this period, employment in England and Wales (including London) grew by 10.4%. To show how towns in each combined category compared with this national benchmark, Figure 5 groups towns according to whether their employment:

• declined

• increased at a rate below the England and Wales average

• increased at a rate above the England and Wales average but less than double that average

• increased at more than twice the England and Wales average

Across all towns within the eight combined categories, 37.4% experienced a decline in employment. At least half of further, higher deprivation residential and further, lower deprivation working towns recorded a fall in employment. In contrast, nearer, working towns (regardless of their deprivation level) had the smallest proportion of employment declines, with 25.6% to 30.7% of towns in these categories reporting decreases. Towns with the highest above average employment growth - combining categories that are above or twice the England and Wales average - are in the nearer, lower deprivation working category.

Broadly, the results show an interaction between relative access and job density. Further categories generally have greater numbers of towns with declining job growth, while working locations that are nearer to other population centres perform better. There was also a clear effect of job density, with working categories less likely to experience declining employment.

A further notable finding is that in most categories fewer than one in three towns achieved employment growth above the England and Wales average. The strongest performing category was nearer, lower deprivation working (45.4%), representing towns with strong employment and wealthier populations in the vicinity of major urban centres.

Median house price

Figure 6 shows the median house price (MHP) in 2023 by combined categories. The data show that house prices were significantly higher in lower deprivation towns, particularly those in the nearer category, and were lowest in higher deprivation towns. Working categories had a higher MHP than their equivalent residential category.

Uniquely, within the further higher deprivation residential category, coastal towns had most of the highest MHPs. This suggests that although house prices were lowest in this category, coastal locations still command a premium. This was not reflected in other combined categories.

Figure 6: Highest median house prices were in nearer, lower deprivation categories, with working categories having higher median prices than their residential equivalents

Median house price among towns, by combined category, England and Wales, 2023, %

Notes:

1. Median house prices are an average across all sales, and do not control for different accommodation types.

Median house price growth

When assessing patterns of growth in MHP since 2001, we see a different trend (Figure 7). Overall, higher deprivation towns had the fastest average growth, regardless of their relative access category. High growth areas included Grimethorpe (550.0%), Rhondda (468.2%) and Salford (427.5%).

The faster average growth among higher deprivation towns compared with lower deprivation towns is most observable within the "nearer" towns, likely reflecting lower starting prices combined with proximity to major urban centres.

Figure 7: The fastest growth in median house prices was in towns in the nearer, higher deprivation categories

Growth in median house prices among towns, by combined category, England and Wales, 2001 to 2023, % change since 2001

Notes:

1. Median house prices are an average across all sales and do not control for different accommodation types.

In this section, anonymised and aggregated O2 Motion mobility data from 2024 to 2025 are used to provide experimental analysis of trends in visitor numbers across towns in England and Wales. The data and insights are based on O2 Motion mobile phone data, anonymised and aggregated by O2 and expanded to represent the UK population. This analysis was conducted using data made available on the Integrated Data Platform hosted by the Office for National Statistics (ONS). These are not official statistics. We are publishing them as research into a new method for producing subnational visitor statistics. Please do not use them for policy or decision making.

O2 Motion data defines a "visit" as a mobile device dwelling in a Lower layer Super Output Area (LSOA) for more than 30 minutes, excluding the device's usual nighttime (home) and typical daytime (work) locations. Counts are aggregated to LSOA level and expanded to represent the UK population before being supplied to the ONS. We then use these data to calculate a visitor to resident ratio, helping identify LSOAs with substantially higher visitor numbers and strong local pull factors.

A single town level total cannot be produced from LSOA level data, because of the inclusion populations travelling across a town throughout the day. Creating sum totals in this way would lead to double counting, and inflation of the estimates. For town level analysis, we therefore use the median visitor to resident ratio (representing the typical LSOA within a town) and the maximum ratio (showing the most extreme case). We also produce a visitor to resident profile for each town, summarising the number of LSOAs falling into each quintile, where the highest quintile (5) represents the 20% of LSOAs in England and Wales with the highest visitor to resident ratios.

Exploration of the data shows that the highest ratios occurred in Central London, often around major transport hubs and visitor attractions. These areas are excluded from further analysis, as the focus of this report is towns and cities outside the capital.

Figure 8: Many towns with the highest maximum visitor to resident ratio were urban centres or contained major transport hubs such as railway stations or airports

Maximum and median visitor to resident ratios in the eight combined categories for towns in England and Wales, 2024 to 2025

Notes:

1. These are not official statistics. We are publishing them as research into a new method for producing subnational visitor statistics. Please do not use them for policy or decision making.

Figure 8 shows visitor to resident ratios for towns and cities in the eight combined categories. Towns with the highest maximum visitor to resident ratios typically contained LSOAs with major transport infrastructure, such as airports or rail stations, or large visitor destinations like shopping centres and leisure complexes. Examples include Crawley, which contains Gatwick Airport, and Takeley and Little Canfield, home to Stansted Airport.

Working towns consistently recorded higher maximum visitor ratios than residential areas, reflecting their concentration of jobs, services and amenities. The highest ratios occurred in nearer higher deprivation working BUAs such as the cities of Newcastle-upon-Tyne and Nottingham, because the largest urban centres fall into this category. In contrast, residential towns showed the lowest maximum ratios across all classifications, likely because of less visitor demand or visitors associated with work-based activities.

To avoid overemphasising single outlier LSOAs, we also examined the median visitor to resident ratio, which better represents typical visitation within a town. The most notable example of consistently high median visitor to resident ratios were the resort towns of Ingoldmells and Chapel St Leonards, where a small resident population is outweighed by a substantial tourism offer.

Working towns broadly showed higher median ratios than residential areas. In further locations, coastal towns stood out with higher median visitor to resident ratios than non-coastal counterparts, reflecting a strong tourism influence.

To better understand visitor patterns, towns have been grouped into six visitor to resident ratio profiles as shown in Figure 9. These are:

• more visited

• less visited

• mixed

• flat

• n-shaped

• u-shaped

These groups can help inform how visitor patterns can vary in different places, both in terms of levels of visitation to a town and the spatial distribution of visitors within a town.

Figure 9: Examples showing how visitor levels and distributions can vary by town

Proportion of LSOAs within each quintile, England and Wales, 2024 to 2025, %

Notes:

1. These are not official statistics. We are publishing them as research into a new method for producing subnational visitor statistics. Please do not use them for policy or decision making.

The more visited profile represents 40.6% of all 1,395 towns and features a high proportion of LSOAs with elevated visitor to resident ratios. It is common in small (51.7%), coastal (43.6%), and further towns (45.6%), reflecting tourism and lower population density. Examples include Cromer and Whitby. It also includes 51.8% of lower deprivation and 46.5% of working towns, such as Sevenoaks and Durham.

The less visited profile represents 30.6% of towns, characterised by consistently low LSOA visitor to resident ratios because of limited or more dispersed attractions. It includes 30.3% of nearer and 31.7% of further, along with 40.4% of higher deprivation and 36.7% of residential towns. Examples include Darlington, Grimsby, and Yeovil.

An n‑shaped visitor to resident profile has most LSOAs in the middle quintiles, with fewer very high or very low ratios. 11.7% of towns fall into this group. All are small or medium in size, typically with a mix of moderately visited areas and a few LSOAs that are either very quiet or relatively busy, such as towns with a single central shopping area and several dispersed smaller attractions. 19.7% of residential towns have this profile, including Crosby (Sefton) and Gravesend.

A mixed profile applies to 7.8% of towns, including Penarth, Fareham, Peterborough, and York, reflecting varied visitor behaviour.

The flat profile, found in 6.0% of towns, is most common among major BUAs (54.2%) such as Sheffield, Derby, and Bristol, where large numbers of LSOAs produce a balanced distribution of visitor to resident ratios.

The rare u‑shaped profile appears in 3.2% of areas, including one major city (Portsmouth) and 4.7% of coastal and 5.2% of further towns. Examples include Ramsgate, Scarborough and Morecambe, where a few highly visited areas sit alongside largely residential LSOAs with low visitor levels.

Overall, these profiles help distinguish towns and cities that attract visitors across most LSOAs from those with more localised visitor hotspots, offering useful insight into how visitor patterns relate to wider socioeconomic differences. This analysis is experimental and we would be happy to hear feedback on its usefulness or ideas for further development. One potential extension for further work is to extend the method to detect seasonal shifts in visitor activity and identify locations that are more dependent on seasonal visits.

Towns and cities

This article is part of our series which provides new data and analysis on towns in England and Wales. In our initial publications, the town definition focused on built-up areas (BUAs) with a population between 5,000 and 225,000. The vast majority of these BUAs held town status, some villages and smaller cities were also captured within the definition given it is a population size-based definition. More recent articles have also included larger cities in the analysis for comparison, and this is also the case in this article - no upper population threshold has been used.

Overall, this article includes 1,395 BUAs in England and Wales, based on the BUA 2024 geography, which have a population above 5,000 as measured by Census 2021. Please note that London is not included. This is because in Greater London, the method to identify BUAs does not recognise individual settlements in the same way. Instead, it provides data by London borough boundaries. 

Coastal and non-coastal BUAs

In this article, we used the same definition and classification of coastal BUAs used in our Coastal communities, characteristics of built-up areas, England and Wales: Census 2021 article. As such, this article captures 211 coastal towns and cities across England and Wales.

Working, mixed and residential towns

Using a framework we have proposed previously, the towns in England and Wales have been grouped according to their workplace characteristics.

Towns have been grouped into three categories depending on their level of job density:

• working towns, with higher job density - the highest 4 deciles

• residential towns, with lower job density - the lowest 4 deciles

• mixed, with medium-level job density - the central 2 deciles

For the purpose of the analysis in this article, mixed towns have been excluded, but they are included in our accompanying dataset.

Income deprivation

Measures of income deprivation follow both the English Index of Multiple Deprivation 2025 (IMD 2025) for English towns and the Welsh index of Multiple Deprivation 2025 (WIMD 2025) for Welsh towns. For each country, the towns have been ranked based on the income deprivation score and placed into deciles, with the towns with the highest average score of income deprivation in decile 1 and the towns with the lowest average score of income deprivation in decile 10. English towns are ranked relative to the English IMD income domain and Welsh towns ranked relative to the WIMD income domain, which measure income deprivation in a similar but not identical way. This means that English and Welsh scores are not directly comparable.

The income deprivation measure is based on the proportion of the residential population in a town experiencing deprivation relating to low income. Towns are allocated into:

• lower deprivation if they are in the lowest 4 deciles for deprivation

• higher deprivation if they are in the highest 4 deciles for deprivation

• middle deprivation if they are in the central 2 deciles

Middle deprivation towns are excluded from the analysis but are available in our accompanying dataset.

This is calculated independently for England and Wales and then combined. For more information on our methods see our Understanding towns in England and Wales: spatial analysis article. For more detailed information please see the English indices of deprivation 2025 research report and the Welsh Index of Multiple Deprivation (WIMD) 2025 technical report.

Relative access

This analysis is based on the 2021 Rural Urban Classification (RUC) relative access methodology which identifies whether a town is "nearer" or "further" from BUAs with populations over 75,000. The article applies the 2021 RUC methodology to each 2024 BUA. 

It is possible to run alternative population thresholds which may better represent very rural places where smaller towns may provide more amenities. For example, in Wales, Welsh Government use a 25,000 person threshold alongside the main definition. This could be a potential avenue for further analysis. Details on relative access measures can be found in the Rural-Urban Classification Methodology (2021).  

Towns combined categories

Combinations of relative access, income deprivation and job density categories result in the eight-way category used in the analysis of towns in this article. These combined categories are:

• further, higher deprivation, residential - 54 BUAs, including towns which have higher income deprivation alongside a lower job density (residential), being further than a 30 minutes' drive to a BUA with a population of at least 75,000 people; examples include Margate, Aylesham and Aberdare

• further, higher deprivation, working - 66 BUAs, including towns which have higher income deprivation alongside a higher job density (working), being further than a 30 minutes' drive to a BUA with a population of at least 75,000 people; examples include Scarborough, Kettering and St Austell

• further, lower deprivation, residential - 24 BUAs, including towns which have lower income deprivation alongside a lower job density (residential), being further than a 30 minutes' drive to a BUA with a population of at least 75,000 people; examples include Glossop, Wantage and Porthcawl

• further, lower deprivation, working - 32 BUAs, including towns which have lower income deprivation alongside a higher job density (working), being further than a 30 minutes' drive to a BUA with a population of at least 75,000 people; examples include Brackley, Ilkley and Rhoose

• nearer, higher deprivation, residential - 160 BUAs, including towns which have higher income deprivation alongside a lower job density (residential), while being within 30 minutes' drive of a BUA with a population of at least 75,000 people; examples include South Shields, Gosport and Blaenavon

• nearer, higher deprivation, working - 168 BUAs, including towns which have higher income deprivation alongside a higher job density (working), while being within 30 minutes' drive of a BUA with a population of at least 75,000 people; examples include Newcastle-upon-Tyne, Blackburn (Blackburn with Darwen) and Portsmouth

• nearer, lower deprivation, residential - 221 BUAs, including towns which have lower income deprivation alongside a lower job density ratio (residential), while being within 30 minutes' drive of a BUA with a population of at least 75,000 people; examples include Kenilworth, Sandhurst (Bracknell Forest) and Lee-on-the-Solent

• nearer, lower deprivation, working - 176 BUAs, including towns which have lower income deprivation alongside a higher job density (working), while being within 30 minutes' drive of a BUA with a population of at least 75,000 people; examples include Durham, Sevenoaks and Penarth

Please note that towns with either a mid-level of income deprivation or a mid-level job density are not included in the eight combined categories. However, data for these towns can be found in the Understanding towns in England and Wales, investigating socioeconomic trends dataset.

Visitor to resident quintile profiles

These are not official statistics. We are publishing them as research into a new method for producing subnational visitor statistics. Please do not use them for policy or decision making.

The visitor to resident profile for each town (BUA) summarises the proportion of Lower layer Super Output Areas (LSOAs) falling into each quintile. The highest quintile (5) represents the 20% of LSOAs in the 1,395 towns in England and Wales included in this article with the highest visitor to resident ratios. Each quintile profile was defined as:

• more visited - if 50% or more LSOAs fell into either quintile 4, quintile 5 or a combination of quintile 4 and quintile 5

• less visited - if 50% or more LSOAs fell into either quintile 1, quintile 2 or a combination of quintile 1 and quintile 2

• n-shaped - if 75% or more LSOAs fell into either a combination of quintile 2 and quintile 3, a combination of quintile 2 and quintile 4, a combination of quintile 3 and quintile 4, or a combination of quintile 2, quintile 3 and quintile 4

• u-shaped - if 50% or more LSOAs fell into a combination of quintile 1 and quintile 5 (but not separately)

• flat - if between 10% and 30% of LSOAs fell into each quintile

• mixed - if the town didn't fall into any of the other quintile profiles

This article provides data and analysis on 1,395 built-up areas (BUAs) in England and Wales with a focus on population, employment and house price data.

The population data are sourced from the Office for National Statistics (ONS) 2001 Census and Census 2021. Economic inactivity data are from the Census 2021 and employment data are derived from Business Register Employment Survey (BRES) covering the years 2015 to 2024.

House price data are based on aggregated ONS housing data, derived from HM Land Registry sources, which is calculated from the average across all accommodation types.

Visitor to resident ratio data are for the period November 2024 to November 2025 and derived from O2 Motion People Counts - mobile phone data anonymised and aggregated by O2 and expanded to represent the UK population. These are not official statistics. We are publishing them as research into a new method for producing subnational visitor statistics. Please do not use them for policy or decision making.

The relative access measures are derived from the ESRI ArcGIS Pro "Generate Service Areas" tool, using a dataset that incorporates network analysis of historical, live, predicted and modelled drive times.

Job density data are based on total employment, which includes employees and working proprietors, from the BRES. Note that the BRES does not include all self-employed.

This article uses data from Census 2021, England and Wales. Details of the strengths, limitations, uses, users and methods used are provided in our Quality and methodology information (QMI) for Census 2021. Information on the quality and limitations of Census 2001 data can be found in the Census 2001 Quality report for England and Wales (PDF, 993 KB).

You can also read about topic specific quality considerations in our:

• Demography and migration quality information for Census 2021 methodology

• Labour market quality information for Census 2021 methodology

• Business Register Employment Survey (BRES) QMI

• House price statistics for small areas QMI

• O2 Motion People Counts

• Rural-Urban Classification methodology (2021)

• English indices of deprivation 2025 research report

• Welsh Index of Multiple Deprivation (WIMD) 2025 technical report

Built-up area (BUA) geography

Data in this article are reported at BUA level. Information on the use of BUAs can be found in our Towns and cities, characteristics of built-up areas, England and Wales: Census 2021 article. BUAs are updated by Ordnance Survey every two years. The BUA boundaries used in this article are the Built Up Areas (December 2024) Boundaries EW BGG (V2).

Each dataset (apart from the O2 Motion People Counts data) has been aggregated to 2024 BUAs using a best fit method based on population weighted centroids. More information on best fit methods can be found in An overview of best-fitting: Building 2021 Census estimates from output areas (OAs).

London's BUAs have been excluded from the analysis because the BUA methodology is unable to identify separate settlements within London and therefore follows a local authority boundary approach instead. Because that differs from the approach used in the rest of the country, London is excluded.

Data are provided for towns to give local areas as much information as possible on the places where most people live. However, compared with data for local authorities or regions, sample sizes for town data are significantly smaller. As such, users should be aware that there will inherently be more volatility within data at this geographic level and caution should be used in interpreting the data.