How to create stock groups based on top 10% most deprived LSOAs

Within Community Insight it is really quick and easy to set up any custom geography you are interested in – whether that is a ward, a local authority, parish or GP locality.

Another type of area (or stock group in Community Insight) that may be of particular use to you, is a composite area of all the LSOAs in your service patch that fall within the top 10% or 20% most deprived nationally, according to the Index of Multiple Deprivation.

It is fairly straightforward to work out which LSOAs fall within these deciles in your area and then create a stock group based upon these LSOAs through selecting from the standard areas dropdown.

Step-by-step guide

Here is a step-by-step guide for identifying the LSOAs to include, with the help of a handy tool from Swirrl.

1. Open the IMD Explorer tool


2. Select the geography

Select the Local Authority or County that you are interested in from the list.

3. Select the index you are interested in:

Most organisations will likely be interested in the overall Index of Multiple Deprivation. However, if you are interested in a particular theme, such as health or employment, you can choose one of these domains instead.

4. Select the decile you are interested in:

If you are interested in the top 10% most deprived LSOAs, select decile 1 and download

If you are interested in the top 20% most deprived LSOAs, you will need to download the data for decile 1 and decile 2 separately

NB: If this produces an empty file, it means that there are no LSOAs within your service patch that fall within this decile.

The following steps assume you are looking at the top 10% most deprived (decile 1). You will need to repeat these steps for decile 2 if you are looking at the top 20% most deprived.

5. Remove duplicates

The file you have downloaded provides you with all of the postcodes that are in the top 10% most deprived alongside their corresponding LSOA codes. For this purpose, we are only interested in the LSOAs that are in the top 10% most deprived, so you need to remove the duplicates in the LSOA code column (column C). To do this:

  1. Click on the Data tab in the tool bar
  2. Select Remove Duplicates
  3. Select the ‘LSOA Code’ check box only
  4. This is now your list of individual LSOAs within your service patch that fall in the top 10% most deprived nationally.
remove duplicates

Click on image to see full size

6. Create your stock group in Community Insight

You can now create your stock group in Community Insight. Please note, you must be a Power User or Group Admin to be able to do this.

The easiest method to create the stock group in Community Insight is through the Create a stock group by selecting a standard area option. This guidance is for users looking at one local authority. If you are creating an area for a county, please see step 7.

  1. Provide a name and description for your area (Please note names cannot be longer than 255 characters)
  2. In the stock group type box, select create area based on standard area
  3. Select LSOA as the geography
  4. Select the local authority the LSOAs are in
  5. Select from the dropdown all the LSOA codes that correspond to those in your download (if you have a few LSOAs you can use Control+F, or Command+F on a Mac to find the codes you need)
  6. Save the stock group
create custom area

Click on image to see full size

7. Create a stock group that spans multiple local authorities

If you are creating a stock group that spans multiple local authorities (such as a county), please send the full list of LSOA codes you would like included in your area to and we can set this up for you.

8. Explore data for your custom area

Your stock group is now ready to use. You can now:

Office Christmas closure

We hope you have a lovely break over the festive period!

OCSI will be closed from Monday 23rd December to Friday 3rd January inclusive. We will not be able to respond to support requests during this time. We will answer any support requests when the office re-opens on Monday 6th January.

As another year draws to a close we are, as ever, appreciative of your continued support. Thank you to all our clients who have made 2019 a year to remember. Here’s to what 2020 will bring!

Community Needs Index indicators now in Community Insight


Community Insight is the first platform to publish the new Community Needs Index, which can be used to help policymakers target investment in social infrastructure.

Introducing our newest set of indicators in Community Insight: Community Needs Index (CNI). This suite of indicators has been produced by OCSI to measure social and cultural factors that can contribute to poorer life outcomes. OCSI was commissioned by Local Trust to develop a quantitative measure of ‘left-behind’ areas (you can read the full publication to find out more about the research). As part of this, we developed a Community Needs Index, the first composite indicator of its kind, looking at the social and cultural factors that can contribute to poorer life outcomes.

We have included four new datasets in Community Insight; the scores for each individual domain and the overall CNI. In each case, a higher score indicates higher levels of community need.

  • Community Needs Index: Civic Assets score
  • Community Needs Index: Connectedness score
  • Community Needs Index: Active and Engaged Community score
  • Community Needs Index: Community Needs Score

This blog will provide more information on the data and how you can explore it in Community Insight.

About the data 

The CNI is particularly exciting as it gives a different perspective to more economically based measures of local need and is a useful measure in and of itself to help policymakers target investment in social infrastructure. 

The index has been developed at ward level after significant consultation and debate. The principal reason for selecting wards as the units of analysis as opposed to Lower Super Output Areas (LSOAs) was that wards align more closely with community boundaries and are of a sufficient size to cover locally recognised neighbourhoods. There is, of course, a potential risk that this can mask variations in community need at a very local level. We have run the same analysis at LSOA level and the results are broadly consistent with the ward level data. 

The index covers 19 indicators, across three domains;

  • Civic Assets: Measures the presence of key community, civic, educational and cultural assets in close proximity of the area. These include pubs, libraries, green space, community centres, swimming pools – facilities that provide things to do often, at no or little cost, which are important to how positive a community feels about its area.
  • Connectedness: Measures the connectivity to key services, digital infrastructure, isolation and strength of the local jobs market. It looks at whether residents have access to key services, such as health services, within a reasonable travel distance. It considers how good public transport and digital infrastructure are and how strong the local job market is.
  • Active and Engaged Community: Measures the levels of third sector civic and community activity and barriers to participation and engagement. It shows whether charities are active in the area and whether people appear to be engaged in the broader civic life of their community.

For a more detailed look at the indicators included within the CNI, please have a flick through the slides below.

Using the data in Community Insight 

This figure shows the Community Needs score in the East of England where the need is particularly high, especially around the agricultural Fen areas near the Wash.

This figure shows the Community Needs score in the East of England where the need is particularly high, especially around the agricultural Fen areas near the Wash

Technical information

Please note, the Community Needs Index indicators are only in Community Insight England. There is no data available for Community Insight Wales or Scotland.

As the data was developed at Ward level, we have apportioned the data in order to be able to include it within Community Insight at standard geographies. The ward score was copied down to Output Area level (every OA in the ward got the same score) and then aggregated to all higher geographies using population-weighted aggregation.

Where an LSOA fits exactly in a ward it will also have the same score as the ward it fits in. Where an LSOA cuts across wards e.g. 60% of people in the LSOA lived in ward A and 40% in Ward B it would get 60% of ward A’s score and 40% of ward B’s score.


Across all four indicators, a higher score indicates higher levels of community need. These new indicators will not be shown on the Map by default, the Group Admin users can add these datasets to the maps using the Manage Indicators functionality. To do so, search the Unassigned theme for the indicator names, drag and drop them into a theme and then tick to show on the map.


All users can use the build a custom dashboard functionality to build dashboards that explore how different areas compare on these indicators. When building a custom dashboard, use the search bar to find the Community Needs Index indicators.


This new suite of indicators will be in any newly requested reports and can be found on page 70.

All Data Download

These indicators will also be added to the All Data Download in the next update which is due to take place at the end of November 2019.


If you have any questions on these datasets, or suggestions for new ones to add, please get in touch on


Access to Healthy Assets and Hazards

Introducing our newest set of indicators in Community Insight: Access to Healthy Assets and Hazards (AHAH). This suite of indicators from the University of Liverpool and CDRC includes 21 indicators (including a multi-dimensional index), that looks at how accessible certain health-related environmental features are to individuals. This covers, for example, proximity to GPs (an asset) to access to fast food outlets (a hazard).

This is the first time that a comprehensive small-scale set of indicators like these have been made available as open data with national coverage and there are exciting implications for supporting and informing decision making. The indicators included are from the recently updated version of AHAH (which includes an additional indicator).

Download the full indicator list for Access to Healthy Assets and Hazards in Insight

This blog will provide more information on the data (although for a much more detailed explanation, please read the technical report) as well as looking at how organisations may want to use this in practice and the ways Community Insight can support this work. 

About the data 

This is a vastly simplified summary of the datasets, so for the #dataheroes among us, please read the technical report, which goes into a lot more detail on the methodological choices made when constructing the datasets.

The individual indicators are based upon four domains of accessibility;

  • Retail environment (access to fast food outlets, pubs, off-licences, tobacconists, gambling outlets)
  • Health services (access to GPs, hospitals, pharmacies, dentists, leisure services)
  • Physical environment (Blue Space, Green Space – Active, Green Space – Passive)
  • Air quality (Nitrogen Dioxide, Particulate Matter 10, Sulphur Dioxide).

The individual indicators are combined to create the overall index, using an adapted version of the methodology for the Index of Multiple Deprivation. All data is published at LSOA level (or the equivalent Data Zones for Scotland) with larger scores depicting poorer health-related environments.

The datasets can be accessed via CRDC.


As with all datasets, there are some limitations in using these indicators. The academic paper from the first version of the index has more detail on each of the points below:

  • The suite of indicators do not include all features of the environment that may influence health
  • It is simplistic to assume that we can separate environments to be ‘positive’ or ‘negative’ – that is to say different combinations of different features may produce different outcomes
  • The suite of indicators do not incorporate features of the social environment (which was a conscious decision so as not to replicate existing deprivation measures)
  • Each measure and overall domain scores are weighted equally, however they may not contribute equally towards influencing health.

Use cases

Map from Local Insight shows hotspot areas for poor access to GPs

Map from Community Insight shows hotspot areas for poor access to GPs

Some of the use cases below are sourced from the previously mentioned academic paper.

Service provision and use

The datasets can provide insight into whether services are provided in areas that are most in need. The dataset itself could help to flag up hotspot areas that have the poorest access to services. Using Community Insight, you can identify these areas quickly and easily using hotspots and then overlay this data with your locally held data on individual local assets (such as GP practices & pharmacies), in order to start conversations and inform commissioning decisions.

In addition, you could also compare the data with socio-economic indicators on the dashboard to quickly and easily identify areas with poor access to health services that have high health needs. 

Retail outlets and shaping behaviour

There is an argument that the sources of services and goods we have access to may shape our behaviours. For example, some research has shown that individuals who have a greater number of fast food outlets within their vicinity can be associated with risk of obesity and the proximity to gambling outlets may affect the risk of problem gambling behaviours.

With this in mind, being able to identify areas with a particularly large score in relation to hazards could be useful in targeting public health communications and resources to these areas. Furthermore, it could have implications for planning and licensing teams and the public health implications for any new premises. 

The Index of AHAH could also be useful to compare with locally held data to test underlying assumptions about which areas have most or least access to these services.

National level decision-making

Finally, as this data has been made available as open data on a national scale, there are lots of opportunities for better partnership working both across institutions and local authority boundaries, through removing some of the barriers associated with sharing data. For organisations that have a public-facing Community Insight site, this means that stakeholders from across local authorities, CCGs and the local community and voluntary sector can all find and use consistent, up-to-date and robust data around local assets and hazards. 

Equally, as the methodology has been applied consistently across all areas, it is possible to make comparisons across different local authorities with less risk of local bias. In practice, this means local authorities can compare their own areas to other authorities that are experiencing broadly similar socio-economic challenges, but with a substantially different outlook when it comes to AHAH. This could lead to better sharing of resources & knowledge around policy-making and initiatives that are most likely to have a positive impact. 


How to access the data in Community Insight 


Group Admin users can add these datasets to the maps using the Manage Indicators functionality. To do so, search the Unassigned theme for the indicator names, drag and drop them into a theme and then tick to show on the map.


All users can use the build a custom dashboard functionality to build dashboards that explore how different areas compare on these indicators.


This new suite of indicators will be in any newly requested reports and can be found on page 45.

If you have any questions on these datasets, or suggestions for new ones to add, please get in touch on

New dashboard upgrades for a more intuitive and tailored experience

We have been working on some big improvements to the dashboard and we are so excited that they are now live for you to use.

The developments focus on:

  • making the dashboard more interactive and tailored to individual users
  • making it easier to understand and interpret the data

This blog is here to give you a rundown of all the changes including:

  • Creating your own custom dashboards
  • How the colour scales work
  • Using the national comparator
  • Improved metadata
  • Tailored data exports

For step-by-step guidance, please read through the Dashboard section on the Knowledge Base.

Creating your own custom dashboards

Build custom dashboards on a per user basis

Using the Areas and Data buttons (see below) you can now edit which indicators and areas populate the dashboard from within the dashboard page. This enables any user to create multiple dashboards that explore different themes for different areas, rather than using a dashboard preset by the Group Admin.

Dashboard buttons


Choose a preset theme and build a dashboard in seconds

Community Insight has preset themes (the themes that are shown on your Maps page). These have been set by the Group Admin in your organisation. You can now select to view all indicators in one particular theme on the dashboard.

Select a theme


Build your own custom dashboard from all the indicators in Community Insight

Community Insight has over 900 indicators. Use the custom dashboard builder to search through those indicators and find the ones that are most important to you. This enables you to create dashboards which reflect your strategic priorities or the priorities of individual projects. This is made much easier through the new search bar.

custom theme


Choose which areas to compare data for

The core functionality of the dashboard allows you to see how your areas compare to multiple indicators. However, we know that you may not always want to compare all of your areas at the same time. You can still select which areas you wish to display on the dashboard. However, now when you select areas, the dashboard will recalculate the colour bands so it is comparing only those areas you have selected to view.

areas button

How the colour scale works

We have simplified the colour scale on the dashboard so that it is easier to see patterns and identify issues across your areas. The areas are now shaded in three colours which represent high, medium or low values. The methodology used to distribute the areas into the colour bands takes the highest and lowest value across your custom areas and then create 3 bands which equally span that range.

Take the example below, looking at Cancer prevalence. The highest value in the table is 3.3 and the lowest is 1.5.

dashboard colours example


Therefore the value bands are as follows:colour bands

Note that these are equally sized bands so the difference between the lower and upper threshold of each band is 0.6 in this case.

As mentioned in the previous section, when you change which areas are displayed, the colours will also update to reflect how the selected areas compare against each other. The figure for the national average is not included in the creation of the value bands.

Please note: in cases where there are decimal figures involved, the figures in the dashboard are rounded to 1 decimal point.


Using the national comparator

The colours on the dashboard allow you to see how your areas compare against each other. However, you can now look at the national average along the top of the dashboard as a benchmark for how your areas fare compared to the national picture.

national comparator


Improved metadata

The dashboard is designed to show lots of data at once in a clear and concise manner. We also want to ensure that it is quick and easy for you to understand what the numbers show. Introducing:

  • Metadata on indicator headers
  • More info on what the data represents when you hover over a data value

Click on the indiactor headers

metadata popup

Hover interaction

Tailored data exports

The Export button allows you to export your dashboard to Excel, so that you can do further analysis or share with colleagues. We have made the export functionality more intuitive, so now when you export – the file will include the areas and the data you are currently viewing on the dashboard. The export also contains the data at a more granular level with the full decimal figure.

Please note:

  • As part of our work to make the dashboard simpler and more intuitive to use, we’ve decided to remove the charts tab. Our research tells us that the charts were not widely used and charts are accessible within the reports for those people who do want to see them


We are always looking for more feedback so whether you love the dashboard or if there are a few tweaks and tidies that you’d like to see, please let us know on

Download all the data in Community Insight at LSOA level

You can now download all the data (more than 900 datasets) in Community Insight for every Lower Layer Super Output Area (LSOA) in the country. In addition to being able to explore data within Community Insight, we hope that access to all the raw data in one place will make further analysis even easier.

How will the All Data Download work?

You can now download a CSV file which contains all the data in Community Insight for all LSOAs in the country. This file will be updated on a quarterly basis, so that you always have the latest data at your fingertips. We will send a mailout to all users every time the file is updated to keep you in the loop.

The CSV file (roughly 300 MB in size) can be found on the Reports tab

All Data download on Community Insight

What does the file contain?

The file contains data for all the indicators in Community Insight at LSOA level, as well as the associated metadata (e.g. name, description, date, source).

How to find the LSOAs  you care about

In Column B, we have included the local authority names. Filter this column to search only for the local authorities you are interested in, in order to make the file more manageable.

If you need a reminder of how LSOAs are defined and how they are created check out this handy geographies guide 


Further analysis

The All Data Download makes further analysis easier outside of Community Insight. For example anybody within your organisation could very quickly and easily:

  • Use Excel or other visualisation tools to produce your own charts and tables for use in your analysis
  • Identify which (if any) of your LSOAs are in the 10% most deprived nationally for the index of multiple deprivation.

And of course the analysts among us could delve a lot further into the data, using the Rank command in Excel for benchmarking or using conditional formatting to see whether the areas you care about score relatively high or low compared to other areas, as a couple of examples.

We would love to know how you are using the All Data Download and if you have any ideas and tips to share with the rest of Community Insight user base, please tell us on


Download data for all your stock groups

If you want to download data for all your existing stock groups in Community Insight, you can use the dashboard export feature.

Learn how to export data from the dashboard

Full guidance & feedback

For more information on using the All Data Download, please read through the Knowledge Base.

If you have any thoughts & feedback on this new functionality then do get in touch. We’d love to hear how you are going to use the All Data Download and if there is anything we can do to make the process of accessing and analysing the data any easier.

You can get in touch with the Support Team on or on 01273 810270.


Better communication around report generation

We have made some improvements to the way that Community Insight manages and communicates the status of report generation. Previously, when you requested a report for a stock group, it would show as report pending. However, if the stock group area was not valid (e.g. because it was too small) and unable to create a report, then the report would remain pending indefinitely.  This was understandably frustrating and to remedy this, we have improved the status messages so that if a stock group is not valid, this is now highlighted, so that you can edit the stock group and generate a new report.

Why do reports get stuck pending?

Generating a report should take roughly 10 -15 minutes. If the report has been pending for a lot longer than this, there may be a problem with the way the stock group was created or there may be a backlog of reports waiting to be generated.

Stock group too small to produce data

When you create a stock group by drawing on the map, you can draw an area as large or small as you like. However, in order to generate a report, the area must be large enough to produce data. For this,  the area must cover at least 50% of the residential postcodes in at least one output area. On average an output area has an average population of about 310 residents. If you are not familiar with output areas or statistical geographies then check out this handy beginners guide to statistical geographies.


An output area in Teeside

An output area in Teeside

A lot of reports have been requested at once

Sometimes your reports will show as pending for a long time if a large number of reports have been generated at once, in which case your reports will be added to a queue. While we cannot prevent this from happening, we have improved the way we monitor this to ensure that we can step in and speed up the process if necessary.

New status Updates

You will see the following changes when generating reports in Community Insight.

Immediately after creating a stock group, the Report button will read as Report Unavailable and not be clickable until the area has been successfully created (this should take a couple of minutes).

report unavailable

If the area you have created is too small, the Report button will read as Area failed. You will not be able to generate a report for that area. You then need to edit the area so that it is large enough to generate a report.

Area failed

If the area has been successfully created, you will see the Request  Report button.

Request report

Once clicked, it will read Report Pending until the report is generated and published in the Reports tab

How to fix a stock group that is too small

If you do create an area which is too small and you see the Area Failed text, then you can just edit the area and expand it until it is large enough to create data.

Get in touch!

If you have any questions, please do not hesitate to get in touch with us on or give us a call on 01273 810270

Local differences in internet engagement

What are the local differences in how people engage with the internet?

Digital Exclusion is not a new topic. We know that even today, when people in the UK check their smartphones, on average, every 12 minutes of the waking day, there is still a proportion of the population that lack access to the internet and the skills to be able to use it (as well as those people who actively choose to disengage with the internet).

We also know that many of those that are digitally excluded are already likely to experience other challenges, such as the elderly, unemployed, people with disabilities and those in social housing. However, there is a lack of data available at a local level on those groups that are digitally excluded and where they are.

Beyond the issue of digital exclusion, greater insight into how different people are using the internet can only be a good thing, and another tool that communications team can use to ensure that their messages are being delivered in the right way to the right people. This information could be used across the public and third sector to identify the most appropriate channels to communicate through, measure uptake of digital services and target digital literacy programmes.

The ESRC Consumer Data research Centre (CDRC) at UCL has developed a Classification of Internet Use – how people living in different parts of the country interact with the internet. Although this dataset alone doesn’t fill the data gap and can’t answer all questions relating to digital skills, it is great to see datasets that tackle this issue at small area level. It is equally great that the data is updated regularly, providing an up-to-date picture of internet use, as well as insights into how areas are changing over time.

These datasets are now available for you to use in Community Insight.

About the data

The classification uses data from the British Population Survey (BPS), which provides information on the behavioural characteristics of the population regarding various aspects of internet use. These are linked with demographic data from the Census and supplemented with data from online retailers and infrastructure data from Ofcom on download speed.

Every LSOA in England has been classified into 10 groups, detailed below.

IUC (1)

CDRC have also produced a pen portrait for each of these groups, providing a profile of how each group interacts with the internet in regards to e.g typical hardware owned, how often they use the internet and the extent to which they use the internet for communication and entertainment.

Of course, some caution should be taken when using this data in isolation to target services, as whole LSOAs are being assigned single classification types and there will likely be notable differences in internet behaviours within an LSOA.

How to access the data

You can download the raw data at LSOA level and Pen Portraits directly from the CDRC website once you have registered for an account. You can also explore the data in interactive maps from CDRC too without registering for an account.

We have also added each of these classifications into Community Insight. As we have mentioned previously, these datasets give a really important insight into how people engage with the internet – but they are not the whole story.

Ewithdrawn (1)

To add these datasets to your maps and dashboard, use the Manage Indicators functionality. Search the Unassigned theme for ‘Internet User Classification’. You will be able to add each of the 10 groups to your maps and dashboards as individual indicators.

If you have any questions on these datasets, or suggestions for new ones to add, please get in touch on

New Local Health data in Community Insight England

The latest additions to Community Insight are an interesting bunch. Not least because they are local health datasets and also because they are so relevant to a number of different sectors, job roles and priorities.

The 21 new indicators added look at estimated prevalence of a number of health conditions including Asthma, Dementia, Depression, Diabetes, Epilepsy, Serious Mental Illness & Learning Disabilities. Download this Excel file to see a List of all new Local Health data in Community Insight:  List-of-all-new-Local-Health-data-in-Community-Insight

Please note, these indicators are only available in Community England. They are not available in Community Insight Scotland or Wales.

Read on for more information on the datasets, a closer look at the prevalence of dementia and how you can explore the data for yourself.

Explore in Community Insight:

You can now view these datasets in Community Insight on the maps, dashboard and in the reports.

View on the maps and on the dashboard

To add these new datasets to the Community Insight maps and dashboard, head to ‘Group Admin’, ‘Manage Indicators’ and then ‘Unassigned’ to drag and drop the indicator into a theme. When searching for the new indicators in the unassigned theme you can search for the word “prevalence “. (If you have not customised your themes yet, click ‘Start managing your indicators’, then head to unassigned). For more detail, see our knowledge base article on how to do this.

Please note only Group Admin users can select to show these new indicators on the maps and dashboard if you are not a Group Admin and are unsure who to ask within your organisation please get in touch with us on


All reports generated from this time point onward (February 2019) will have data for the new indicators on page 46. See below, a graph from one of the Community Insight reports showing how areas fare of the disease prevalence indicators.

disease prev

More on the data:

The new indicators were originally collected and published at GP practice level by NHS Digital. Data collected at GP level can be very valuable for identifying the health challenges experienced by individual GP practices and their patients. However, for the purpose of analysis, it can present some challenges as it is not straightforward to link practice data to standard statistical geographies – patients living in the same neighbourhoods can attend different GP practices, and patients are not necessarily registered with their local GP, so it is difficult to straightforwardly attribute GP data to the neighbourhood in which the GP is located in.

The Commons Library have recently taken these indicators and aggregated them to MSOA level in order to estimate disease prevalence, so that the insights from the data can be used in a more place-based way.

For more detail on the methodology used to aggregate GP level data to MSOA, take a look at The Commons Library’s documentation.

These datasets have also been used in their interactive tool, which provides health related information for each parliamentary constituency.

Health Warnings:

As with any dataset, these indicators come with their own challenges and caveats. These datasets are estimates­ and based upon what has been reported to GPs. The following guidance on using the datasets has been taken from The Commons Library:

  • These figures are only estimates and some divergence between separate areas served by an individual GP practices is bound to be lost.
  • In attributing GP practice-level data to different areas, weighting adjustments have been made in respect of the relevant age category (e.g. diabetes prevalence is measured for age 17+ only), based on the varying age profiles of different small areas.
  • For some conditions, the proportion of people on GP registers is less than the proportion of the people living with the disease. For example: only 67.5% of cases of dementia are estimated to have been diagnosed, and 29% of adults are obese compared with 10% identified on GP registers. The prevalence estimates here represent only those cases diagnosed by a GP.
  • These estimates are sensitive to the quality and consistency of data reporting by GPs. People who are not registered at GP practices are not included in the estimates – either in the numerator or the denominator.
  • Some GP practices did not submit data in 2017/18. In these areas, data for 2016/17 was used.
  • Comparable figures can’t be calculated on the same basis for Scotland, Wales or Northern Ireland.

A Closer Look at Dementia

Using Community Insight, we have taken a look at one of the indicators in more detail – the estimated prevalence of dementia across Bracknell Forest. The estimate is calculated as a percentage and is based on the number of people listed on GP registers in 2017/18, and the number of people recorded as having dementia.

The estimated prevalence of dementia at a national level is 0.8%. Bracknell Forest has a slightly lower estimated prevalence at 0.6%. This is equal to the average prevalence across the whole of Berkshire (defined as Bracknell Forest, Reading, Slough, West Berkshire, Windsor and Maidenhead, Wokingham). Of the local authorities in Berkshire, Windsor and Maidenhead has the highest estimated prevalence of dementia (0.9%) and Slough the lowest (0.4%).

When looking at the estimated prevalence of dementia across wards in Bracknell Forest, Crown Wood ward has the lowest estimated prevalence of dementia (0.3%) and and Winkfield and Cranbourne ward has the highest (1.2%).

Data updates


Community Insight is updated every month with new data. To see a list of all the datasets in Community Insight check out this article on our Help Centre

Here you can find archived links to previous data updates:

Community Insight England Community Insight Scotland
Community Insight Wales
2021-Oct 2021-Oct 2021-Oct
2021-Sep 2021-Sep 2021-Sep
2021-August 2021-August 2021-August
2021-July 2021-July 2021-July
2021-June 2021-June 2021-June
2020-May 2020-May 2020-May
2021-Apr 2021-Apr 2021-Apr
2021-Mar 2021-Mar 2021-Mar
2021-Feb 2021-Feb 2021-Feb
2021-Jan 2021-Jan 2021-Jan
2020-Nov 2020-Nov 2020-Nov