The Office of National Statistics (ONS) has recently released multivariate data from the 2021 Census, and we have started to add key indicators to Local Insight. Multivariate data is important because it allows us to combine indicators to gain a deeper understanding of our communities. With a vast number of possible combinations, we would like to know what you are most interested in seeing in the tool.

The ONS has released the data in the form of an online build a custom dataset tool. This means you can choose which indicators you would like to combine, and which geographic level you’d like to see the data for.

However, this should be used with caution as there are gaps in the data for some indicator combinations at small area level. This may be due to data suppression, to avoid the risk of identifying individuals from the data. For instance, multivariate indicators related to sexuality and gender identity are not available below LA level. 

Multivariate data has relatively low numbers when compared to indicators with a single variant. This can lead to inaccuracies when apportioning and aggregating data for use with custom areas. Therefore, to make sure that the data we’re using is useful, we will only add multivariate indicators to Local Insight when they are available nationally at Output Area (OA) level. This allows for accurate aggregation for larger custom areas.

There is some multivariate data available at OA level for the following themes:

• Economic activity status
• Overcrowded housing
• General health
• Highest level of qualification
• Occupation
• Tenure
• Unpaid care

For each of these themes, we will provide data for a range of groups including ethnicity, age, gender, household composition, disability and carers. For example, highest level of qualification by different age groups. We will also provide data for where those themes intersect with each other. For example, overcrowded housing by general health. As above, this is subject to the data being available at OA level.

Our research team is currently prioritising key combinations. We want to know which themes you are most interested in seeing so that we can add them to the tool more quickly. We are running a webinar on May 3rd at 11am focusing on the Census multivariate data, which you can sign up for here. Please let us know which themes are most important to you via this form.

Some Multivariate census data is now live in Local Insight. You can start using and analysing this data for all your custom areas.

For guidance on using Census 2021 data in Local Insight please see “How to explore Census 2021 data in Local Insight”.

Summary of published data

We have added nine multivariate Census 2021 indicators to Local Insight. Indicators for the following datasets can now be seen live in Local Insight:

• Children providing unpaid care
• Employment rate by ethnicity (5 indicators)
• People aged over 65 with not good health
• People travelling more than 10km to work by public transport and by driving (2 indicators)

Click here to download a list of all updated Census indicators.

Reports

We have updated Children Providing Unpaid Care in the Local Insight reports (see Vulnerable Groups: page 23). You will need to update your reports in order to see Census 2021 data here.

Local Insight contains a number of indicators from the Department for Work and Pensions (DWP). These indicators are useful for understanding labour market activity and vulnerable groups in your areas.

This blog will inform you of the changing landscape, such as the move to Universal Credit, so that you can use these datasets with confidence. We also provide recommendations for which indicators to use in Local Insight for different topics.

Read on to find out about:

• The rollout of Universal Credit
• Recommended indicators to use
• The advantages of these indicators 
• Viewing change over time for unemployment

The rollout of Universal Credit

In the early 2010s, the DWP began a major reform of the benefits system, moving away from multiple benefits payable to people with different needs towards a single benefit – Universal Credit (UC). 

The full-service rollout was completed in 2018. However, the managed migration of existing benefit claimants was delayed by the pandemic and is incomplete. As a result, some people are still receiving the benefits that preceded UC, sometimes referred to as ‘legacy benefits’. This includes Jobseekers Allowance (JSA). As this affects those that have been claiming Job Seekers Allowance on a long-term basis, using UC alone may exclude many long-term unemployed from the figures. Migration is uneven across different parts of the country. The House of Commons Library regularly releases data on how far the rollout has progressed. 

As a result of the ongoing migration to UC, it can be difficult to know which DWP indicators to use. For example, looking solely at people in receipt of UC may miss groups of people who are still on the legacy benefits. To mitigate this, Local Insight includes a number of indicators that contain benefit combinations to cover people on legacy benefits as well as those receiving UC. This includes the below indicators: 

• Unemployment Benefit (JSA and Universal Credit)
• Working Age Benefit Claimants (Benefit Combinations)
• Claiming out of Work Benefits (Benefits Combination)
• People receiving Disability Benefits [This is a derived indicator created by OCSI]
• People of Pensionable Age Claiming DWP Benefits (Benefits Combinations)

Recommended indicators to use

Unemployment Benefit (JSA and Universal Credit)

This indicator gives the most comprehensive figures at a local level of those that are currently unemployed. You may also see this referred to simply as the ‘claimant count’.  This figure is a combination of JSA claimants and a subset of Universal Credit claimants, which covers those that are required to seek work and be available for work.

Local Insight also contains a subset of this indicator that shows Youth unemployment (18-24 receiving JSA or Universal Credit).

How often it’s updated: Monthly 

Working Age Benefit Claimants (Benefit Combinations)

This indicator shows the proportion of people of working age receiving DWP benefits. In this dataset, the working age is defined as people aged 16-64 (this is the denominator that the DWP uses).

Working age DWP Benefits are benefits payable to all people of working age (16-64) who need additional financial support due to low income, worklessness, poor health, caring responsibilities, bereavement or disability. 

How often it’s updated: Quarterly

Claiming out of work benefits (Benefit Combinations)

This shows the total benefit combinations for individuals that claim Out of Work benefits. Out of work benefits are defined as being on at least one of the following benefits: Jobseekers Allowance (JSA), Employment and Support Allowance (ESA), Incapacity Benefit (IB), Severe Disablement Allowance (SDA), Income Support (IS) where Carers Allowance (CA) not also in payment, Pension Credit (PC) where Carers Allowance (CA) and Universal Credit (UC) conditionality regime is one of Searching for Work, Preparing for Work or Planning for Work. 

How often it’s updated: Quarterly

People of Pensionable Age Claiming DWP Benefits (Benefit Combinations)

Shows the total benefit combinations for State Pension Age individuals. The benefit combinations shown in these statistics do not cover every possible combination. This does not include those that claim State Pension Only. Currently, this indicator uses 65 as the State Pension Age, this is set by the DWP. 

How often it’s updated: Quarterly

People receiving Disability Benefits 

The previous indicators are all published directly by DWP. The People receiving Disability Benefits indicator is a derived indicator created by our Research Team at OCSI.  It combines people receiving the legacy Disability Living Allowance benefit with the new style Personal Independence Payment (PIP).  

How often it’s updated: Annually

The advantages of these indicators 

This suite of benefit combination indicators is useful for a number of reasons:

• They are published at a small area level (LSOA) so you can see how your local areas fare on these indicators.
• They are updated frequently by DWP and in turn by us in Local Insight so you know you are looking at relevant data.
• They are from a robust data sample. 

Viewing change over time for unemployment

In Local Insight, you can explore how the proportion of those in receipt of unemployment benefits has changed over the past few years. This is only possible for the two below indicators:

• Unemployment Benefit (JSA and Universal Credit)
• Youth unemployment (18-24 receiving JSA or Universal Credit)

This is part of an experiment to improve how you can access trend data in Local Insight. We are continuing to look at ways of improving this and are always keen to hear feedback on support@ocsi.co.uk. 

Viewing the unemployment  trend data on the map

• Click on the Data button
• Search Unemployment using the search bar
• You will see the most recent Unemployment benefit (JSA and Universal Credit) indicator and the historic time points listed beneath going back to March 2020

Use the dashboard to download the unemployment trend data for your custom areas

Follow these steps to build a dashboard displaying the individual unemployment claimant count datasets for each month for your areas. 

1. Open the Dashboard tab 
2. Use the Areas button to select the areas you would like to display
3. Click on the Data button and select build a custom dashboard 
4. In the search bar type Unemployment benefit (JSA and Universal Credit) or Youth unemployment (18-24 receiving JSA or Universal Credit)
5. On the right-hand side it will now display all the different timepoints
6. Select the time points in the order you want them to display 
7. Click Done
8. Once you have created your dashboard, you can either view it on Local Insight or export it to Excel to create your own visualisations 
9. You can also copy and paste the dashboard into Excel and keep the colour scale

Reports

In the reports, you can see how the data has changed over a much longer time period between 2004 and 2023 (page 10).

Introduction

Poverty is a complex issue affecting individuals and communities across the UK, including in rural areas. Some methods that are used to identify poverty can lead to pockets of deprivation in rural areas being overlooked or hidden.

The Index of Multiple Deprivation (IMD), for example, is published at the Lower Layer Super Output Area (LSOA) level. LSOAs have an average population of 1,500; in an urban area with higher population density this would equate to a much smaller physical geography than it would in a rural area. Therefore, while an urban LSOA is likely to have a much more consistent socioeconomic demographic, a rural LSOA may contain multiple villages where some are much more deprived than others. Here, the IMD score would be unlikely to identify the rural LSOA as being one of the more deprived areas, so the more deprived village/s within it may be overlooked.

So how can we overcome this? When considering rural poverty, some indicators will be more useful than others. The Office for National Statistics (ONS) Rural Urban Classification can also be a useful tool. Used in combination with custom areas in Local Insight, we can find more meaningful ways to use data to help us identify rural poverty.

Choosing the most helpful indicators

Lifestyle can vary significantly between rural and urban areas, so certain things might be a sign of deprivation in one but not necessarily in the other. A good example of this is car ownership, which is more of a necessity in rural areas since public transport tends to be a lot less available and efficient there. While car ownership in general would tend to be higher in rural than urban areas, if you can look at just the rural areas, comparatively lower levels of car ownership may signify deprivation. If you identify rural areas with low levels of car ownership you may wish to combine this with indicators like public transport and access to services. You can build a custom dashboard in Local Insight to look at these indicators together for your areas.

The indicators that tend to be most useful when looking at rural poverty can be loosely categorised as being related to connectivity (both physical and digital), employment or living costs. Due to the nature of rural areas, access to services can be more limited. People might need to travel longer distances, so increased fuel or transportation costs may have a greater impact. Houses tend to be older on average and have lower EPC ratings, so fuel poverty might be more commonplace. 

Below are some indicators that our Research team here at OCSI suggest for looking at rural poverty, and an example of a custom dashboard set up in Local Insight using some of these indicators:

How to find indicators in Local Insight

There are over 1500 indicators in Local Insight that you can view on the map and dashboard. You can find detailed instructions on how to do this in these sections of our help centre:

• Dashboard
• Customise Themes and Indicators

Custom Areas

As we’ve seen, looking at data at LSOA level can lead to rural areas being overlooked in some contexts. One way of overcoming this is to look below LSOA level, allowing smaller areas of deprivation to be picked up. Rural parishes tend to be very small, and more reflective of the actual communities on the ground than LSOAs. This means a Parish is likely to contain households of a more similar socioeconomic demographic than a rural LSOA would, so setting up parishes as custom areas in Local Insight may be useful.

When data is released at Output Area (OA) level, it is stored in Local Insight at that level and the tool will use the OA level data to aggregate for larger areas. When data is released at LSOA level the tool will apportion this down to OA level and aggregate for larger areas. Therefore, if you’re looking at parishes which are smaller than LSOAs but larger than OAs, and you are looking at indicators that have been released at OA level, then you will be looking at accurate data for your parishes. At the time of writing, there are 640 indicators in Local Insight at OA level – you can find a full list of these by downloading our list of all indicators and filtering by ‘lowest published geography’.

Below is an example of this. The Parish, Egmanton, sits within the LSOA Newark and Sherwood 003B in Nottinghamshire. The screenshots below show this on the map, and in the ‘data for your areas’ popups for two indicators. The IMD rank is released at LSOA level and therefore shows the same value for the parish as for the LSOA. In contrast, the ‘households with no car’ indicator is released at OA level and aggregated for the parish.

How to set up parishes as Custom Areas in Local Insight

The best way to do this would be to use the shapefile importer, which is explained in this section of our Help Centre: Import Shapefiles.

You can download shapefiles for parishes from the ONS Open Geography portal – go to ‘boundaries’ > ‘administrative boundaries’ > ‘parishes’ > ‘2022 boundaries’. The file you want is called ‘Parishes (December 2022) EW BGC’ – in the description you will see ‘generalised (20m) – clipped to the coastline’. You can filter by the parishes that you want, making sure you toggle filters when downloading the file. This process is shown in the video below.

The ONS file doesn’t allow you to filter parishes by ward or local authority. If you would like all parishes in a Local Authority, and want to avoid the need to filter for them all individually, it is necessary to download all parishes and then filter the shapefile by the ones you want using a lookup table. This can be done using GIS software. If you’re not able to do this, get in touch at support@ocsi.co.uk and we can help.

ONS Rural Urban Classification

The ONS have analysed every settlement in the country. Settlements of more than 10,000 people are classified as Urban, and settlements of below 10,000 people are classified as rural. Each OA in the country has been assigned a settlement type. This leaflet goes into more detail about the methodology and definitions used.

In Local Insight, we can add the rural and urban classifications as custom areas. The below example shows how each of these look for Essex. We have also added a group boundary. 

The areas are made up from their constituent OAs and provide full coverage of Essex.  You can see all of the individual OAs outlined on the map. This makes it a bit difficult to see which areas are and aren’t included when you’re looking at the rural classification area. There are ways to make this easier to view.

You can:

• select the urban area and look at the areas that are outside it. 
• zoom in on the map to see the area boundaries more clearly. 

If you think these areas would be helpful for your organisation, get in touch at support@ocsi.co.uk.

Essex Urban Areas

Essex Rural Areas