Data Catalogue Information Packs - Print version

Information Pack 1 - Housing and Homelessness

Definition: How do we define housing/homelessness?

Homelessness is defined by the Housing Act (1996) as “someone is homeless if they have no accommodation available to them, along with their household which:

• They have a legal right to occupy, such as by ownership, tenancy agreement, or other permission to reside there
• They can access
• Would be reasonable for them to continue occupying, such as being affordable and being fit for human habitation”

An individual can be threatened with homelessness if they are likely to become homeless within 56-days (such as end of tenancy agreement, or landlord selling the property).

Key contact within Coventry City Council

If you are wanting to know more information about homelessness, have any specific questions about the accessible data, or are keen to research homelessness, please contact:

Sophie Hall, E: Sophie.Hall@coventry.gov.uk [mailto:Sophie.Hall@coventry.gov.uk]

Why is housing a wider determinant of health?

Housing is a wider determinant of health because it directly and indirectly influences physical, mental, and social well-being through complex interactions of its quality, affordability, stability, and neighbourhood context. The conditions in which people live, work, and age significantly shape health outcomes and health inequalities across the lifespan.

Physical health impacts

Poor quality housing conditions can directly cause or exacerbate physical health problems due to:

• Damp and mould – exposure to dampness and mould is strongly associated with respiratory conditions, asthma, and other infections, particularly in children.
• Cold homes (fuel poverty) – inadequate heating and insulation can lead to excess winter deaths and exacerbate cardiovascular disease, respiratory illness, hypothermia and musculoskeletal conditions.
• Safety hazards – structural defects, a lack of safety devices (smoke alarms, carbon monoxide alarms), and poor design can increase the risk of accidents, injuries and fires.
• Overcrowding – inadequate living space increases the risk of infectious disease transmission and can affect physical development in children.

Mental and Psychosocial impacts

Housing conditions profoundly can affect mental health and overall wellbeing such as:

• Stress and anxiety – high housing costs (affordability issues) and the threat of eviction or homelessness create significant financial stress and anxiety.
• Security and control – a secure and stable home provides a sense of control and a “secure base” essential for mental well-being and a positive social identity. Housing insecurity, common in the private rental sector, can lead to frequent moves that undermine engagement with local services and support networks.
• Overcrowding and lack of privacy – living in non-decent or overcrowded housing is associated with increased stress, depression, and behavioural problems, particularly among children.

Wider social and economic impacts

Housing connects to broader social and economic determinants of health such as:

• Affordability – when a high proportion of income is spent on housing, less money is available for other health-promoting necessities like quality food, proper clothing, and recreation which can worsen health outcomes.
• Neighbourhood context – the surrounding neighbourhood environment impacts health through factors such as access to green spaces, air quality, community safety and proximity to services like healthcare and transportation.
• Health inequalities – poor housing conditions disproportionately affect low-income households, minority groups, and younger people, thereby entrenching existing health inequalities.

Key literature signposting

Gibson et al. (2011). Housing and health inequalities: A synthesis of systematic reviews of interventions aimed at different pathways linking housing and health [https://pmc.ncbi.nlm.nih.gov/articles/PMC3098470/#:~:text=Abstract,and%20potentially%20new%20evidence%20syntheses.].

House of Commons Library (2022). The link between housing and health [https://commonslibrary.parliament.uk/research-briefings/cbp-9414/#:~:text=The%20causal%20link%20between%20poor,on%20mental%20and%20physical%20health.].

House of Commons Library (2023). Health inequalities: Cold or damp homes [https://commonslibrary.parliament.uk/research-briefings/cbp-9696/#:~:text=Housing%20quality%20has%20a%20significant,wheezing%20and%20shortness%20of%20breath.].

National Library of Medicine (2009). The connection between health and homes [https://www.ncbi.nlm.nih.gov/books/NBK44199/#:~:text=Poor%20indoor%20air%20quality%20contributes,including%20neurological%20effects%20and%20cancer.].

Rolfe et al. (2020). Housing as a social determinant of health and wellbeing: Developing an empirically-informed realist theoretical framework [https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-09224-0#:~:text=The%20role%20of%20housing%20as,sectors%20in%20west%20central%20Scotland.].

Rana (2025). Sustainable housing as a social determinant of health and wellbeing [https://www.mdpi.com/2071-1050/17/16/7519#:~:text=Abstract,coherence%20can%20limit%20their%20reach.].

The Health Foundation (2020). Better housing is crucial for our health and the COVID-19 recovery [https://www.health.org.uk/reports-and-analysis/briefings/better-housing-is-crucial-for-our-health-and-the-covid-19-recovery].

The Health Foundation (2024). Relationship between living in overcrowded homes and mental health [https://www.health.org.uk/evidence-hub/housing/housing-stability-and-security/relationship-between-living-in-overcrowded#:~:text=Living%20in%20an%20overcrowded%20home,of%20conflict%20in%20their%20household.].

Publicly accessible data on housing/homelessness

1. LG Inform https://lginform.local.gov.uk/ [https://lginform.local.gov.uk/]

LG Inform (Local Government Inform), is an accessible platform which is funded by the UK government. The LG Inform platform was introduced as a practical solution to ensure that local governments and organisations could access data which will help influence decision making and policy, with the addition of being a free platform which members of the public can also use.

LG Inform has a range of publicly accessible data on housing. There are 2557 reports and/or datasets for individuals to access, which can be presented in a report, or access to the raw data is also accessible for individuals. Reports are themed into:

• Council and community housing (517 Reports)
• Homelessness and prevention (1583 reports)
• Improvements and repairs (81 reports)
• Multiple occupancy homes (12 reports)

For each specific data set, individuals can click on either ‘view report’ or ‘view data’ which provides specific data for specific locations (such as Coventry), providing direct comparison to other local authority locations or cities within the UK. Data can be presented as either a table, graph, or interactive map.

For individuals who are wanting to use housing/homelessness data for specific research, data available on LG Inform can be downloaded into an excel spreadsheet for each specific report. This will allow for data to be extracted more easily for research, comparison of statistics of differences over time with a comparison by year option also available.

1a) LG Inform Plus - https://home.esd.org.uk/ [https://home.esd.org.uk/]

Please note: LG Inform Plus requires a licence and is therefore only accessible for Coventry City Council Colleagues via registering for an account.

LG Inform Plus provides the same foundation content as LG Inform but allows for individuals to look at data through specific wards and transform data into charts, maps, and tables. For example, for housing and homelessness, data can be created into a detailed themed report, which is modifiable by:

• Data metric
• Date period
• Location
• Comparison group

The data is presented by tables, graphs, and interactive maps to allow individuals to get a clear insight into specific metrics surrounding housing/homelessness in Coventry.

2. Coventry City Council - Coventry Homelessness Review [https://www.coventry.gov.uk/homelessness-1/coventry-homelessness-review-2024/8]

Coventry City Council has a range of information and data surrounding housing and homelessness. The website includes a range of information including a review, data, and underlying reasons as to why homelessness occurs in Coventry.

Coventry data available on the Coventry City Council on this platform relating to housing/homelessness includes:

• Housing affordability
• Availability of affordable housing in Coventry

Housing affordability data is presented as either graphs or tables, with data being presented by year – allowing for direct comparison and trend analysis of housing affordability over the years. Each graph also includes a clear description for individuals to assist with interpretation, along with a comment of how Coventry’s statistics are in comparison to either England or the West Midlands.

Housing affordability data is also split into size of property to allow for comparison between one-bedroom to multiple bedroom home availability over the years in specific relation to the Local Housing Allowance rates (rent).

3. Department for Levelling Up, Housing & Communities - https://www.gov.uk/government/collections/homelessness-statistics [https://www.gov.uk/government/collections/homelessness-statistics]

The Government has a Department for Levelling Up, Housing & Communities which provides a range of statistics surrounding housing/homelessness for local authorities and cities across the UK – with the latest data being published in 2024.

Data on this platform includes a ‘Detailed Local Authority Level Tables’ dataset. Once clicked on, this opens an excel file with a range of tabs for individuals to explore with data. The first tab ‘LA-dropdown’ permits for individuals to choose their specific location of interest (such as Coventry), with all other local authority areas included in the dropdown option – allowing for direct location comparison.

Other tabs within the excel spreadsheet are slightly less interactive but presents data in a table form on a range of different topics by local authority area. Topics presented include:

• Number of households by initial assessment of homelessness circumstances and needs
• Number of households owed a prevention duty by reason for loss, or threat of loss, of last settled home
• Number of households owed relief duty by reason for loss, or threat of loss, of last settled home.
• Ethnicity of main applicants assessed as owed a prevention or relief duty by local authority.
• Employment status of main applicants assessed as owed prevention or relief duty by local authority.

Many more topics are presented on the excel spreadsheet, allowing individuals to gain an in-depth understanding of housing/homelessness for a specific location, and for direct comparison of local authority areas. The overall department website also includes the in-depth data going back to 2010, also allowing for time comparison.

Additional Information

Please note: Coventry City Council also holds in-depth data on housing/homelessness. However, due to the sensitivity and confidentiality of this data, data can only be accessed by Coventry City Council colleagues if they use the Coventry City Council’s Data Protection Impact Assessment Process.

Information Pack 2 - Digital Inclusion

Definition: How do we define Digital Inclusion?

Digital inclusion can be defined as “ensuring that everyone has the access, skills, support and confidence to participate in and benefit from our modern digital society, whatever their circumstances” (Gov UK, 2025 [https://www.gov.uk/government/publications/digital-inclusion-action-plan-first-steps/digital-inclusion-action-plan-first-steps#chapter-3---defining-and-measuring-digital-inclusion]). The UK Government are currently focussing on digital inclusion, exploring four main priorities:

• Opening up opportunities through skills,
• Tackling data and device poverty,
• Breaking down barriers to digital services, and
• Building confidence and supporting local delivery.

Key contact within Coventry City Council

If you are wanting to know more information about homelessness, have any specific questions about the accessible data, or are keen to research digital inclusion, please contact: #Cov Connects Team: coventryconnectdigital@coventry.gov.uk [mailto:coventryconnectdigital@coventry.gov.uk] 

Why is digital inclusion a wider determinant of health?

Digital inclusion is considered a wider determinant of health (a "super social determinant of health") because it significantly influences the broad range of social and economic factors that shape an individual's health outcomes and life chances. Digital access, skills, and confidence are now essential for navigating modern life, impacting the five domains of wider health determinants:

1. Economic stability and employment: Most jobs now require digital skills. Digital inclusion improves job prospects, earning potential, and the ability to apply for jobs and benefits online. Without it, individuals are more likely to face economic hardship, which is a major driver of poor health outcomes.
2. Education and lifelong learning: Online access is critical for education at all levels. Digital exclusion can lead to an achievement gap for children and adults, limiting future opportunities and perpetuating cycles of poor health associated with lower educational attainment.
3. Social participation and community life: Internet access is essential for social connection, communication with loved ones, and participating in community activities and support groups. Digital exclusion can exacerbate social isolation and loneliness, which have significant negative impacts on mental and physical health.
4. Housing and built environment: Access to digital tools is often necessary for managing housing, reporting repairs, and applying for social housing. It is also used to access information about local resources and amenities.
5. Access to health and healthcare services: Digital platforms are increasingly the primary way to access healthcare, including booking appointments, ordering prescriptions, accessing medical records, and engaging in remote monitoring or telehealth consultations. Digital exclusion directly creates barriers to receiving timely and appropriate care, potentially leading to delayed diagnoses and worse health outcomes.

Beyond these indirect effects, digital inclusion also has a direct impact on health including:

• Health information and self-management: The internet provides a wealth of health information, enabling individuals with sufficient digital and health literacy to better manage chronic conditions and engage in preventative health measures.
• Mental wellbeing: the ability to stay connected and engaged online can improve mental health and a sense of belonging, while digital exclusion can lead to feelings of disempowerment, frustration, and stigma.

By influence so many aspects of life that affect health, digital inclusion is now recognised as a fundamental determinant of health, and a crucial factor in addressing health inequalities.

Key literature signposting

Good Things Foundation (2024). Digital inclusion and health – summary of key statistics [https://www.goodthingsfoundation.org/discover/digital-inclusion-insights/digital-inclusion-insights-2024/digital-inclusion-and-health#:~:text=The%20impact%20of%20digital%20integration,health%20and%20digital%20inclusion/exclusion.].

Good Things Foundation (2025). From analogue to digital: Tackling inequality and digital exclusion in the future NHS [https://www.goodthingsfoundation.org/discover/digital-inclusion-insights/digital-inclusion-insights-2025/tackling-digital-exclusion-in-the-future-nhs#:~:text=The%20digital%20divide%20in%20UK,accessible%20for%20everyone%20going%20forwards?].

Middle & Welch (2022). Experiences of digital exclusion and the impact on health in people living with severe mental illness [https://pmc.ncbi.nlm.nih.gov/articles/PMC9722951/#:~:text=Conclusion,priority%20for%20mental%20health%20services.].

NHS England (2023). Inclusive digital healthcare: A framework for NHS action on digital inclusion [https://www.england.nhs.uk/long-read/inclusive-digital-healthcare-a-framework-for-nhs-action-on-digital-inclusion/#:~:text=Digital%20exclusion%20can%20compound%20health,groups%20of%20people%20may%20face.].

López et al (2023). Digital literacy as a new determinant of health: A scoping review [https://pmc.ncbi.nlm.nih.gov/articles/PMC10569540/#:~:text=In%20any%20of%20these%20cases,the%20digital%20health%20literacy%20gap.].

Kessel et al (2022). Digital health literacy as a super determinant of health: More than simply the sum of its parts .

Sieck et al (2021). Digital inclusion as a social determinant of health [https://pmc.ncbi.nlm.nih.gov/articles/PMC7969595/#:~:text=Digital%20literacies%20and%20Internet%20connectivity,and%20sometimes%20exclusively%2C%20accessible%20online.].

Fee et al (2023). Strategies and solutions to address digital determinants of health (DDOH) across underinvested communities [https://pmc.ncbi.nlm.nih.gov/articles/PMC10569606/#:~:text=While%20acknowledged%20and%20highlighted%20broadly,the%20series%20on%20DDOH%20solutions.].

Publicly accessible data on Digital Inclusion

1. LG Inform - https://lginform.local.gov.uk/ [https://lginform.local.gov.uk/]

LG Inform (Local Government Inform), is an accessible platform which is funded by the UK government. The LG Inform platform was introduced as a practical solution to ensure that local governments and organisations could access data which will help influence decision making and policy, with the addition of being a free platform which members of the public can also use.

LG Inform provides an in-depth themed report surrounding digital inclusion for Coventry. This report includes:

• Key statistics
• Graphs
• Comparisons of topics to other Local Authority areas
• Mapping of data.

All maps and graphs provided within the report are interactive, allowing for live comparisons of digital inclusion between Coventry and other areas.

The themed report is divided into chapters including:

1. Availability
2. Digital usage
3. Tech skills and qualifications
4. Local context and digital engagement

As well as having themed reports available, LG Inform also has datasets available for digital inclusion, using the search function.  Please note: access for the datasets requires individuals to register for a free account.

For digital inclusion, there are 409 reports and/or datasets for individuals to access, which can be presented in a report, or access to the raw data is also accessible for individuals. This level of reporting for digital inclusion means that there is a wide range of data available to use for background information, reports, and building the need (rationale) for future research and/or funding applications.

2. Acorn - https://acorn.caci.co.uk [https://acorn.caci.co.uk]

Acorn provides a detailed understanding of the various types of people who make up a city’s customer base and catchment areas. Acorn analyses data from hundreds of different sources, and segments UK postcodes by common characteristics. Acorn can be accessed through a free trial (only for a limited time). Coventry City Council has a licence for Acorn, meaning that colleagues can access this platform simply by registering for an account.

Digital inclusion is explored in ACORN in three main ways:

1. Digital
2. Devices
3. Internet

When exploring digital inclusion, data can be explored in many ways including:

• Category segments
• Group segments
• Type segments (as shown in the image below).

When searching specific data, individuals have the option to choose by generic postcode such as CV (for Coventry) or can break data down further by choosing specific postcodes such as CV1 which will be displayed on the map on the righthand side of data.

3. Coventry City Council - https://coventry-city-council.github.io/connected-nations/ [https://coventry-city-council.github.io/connected-nations/]

Within this platform, Coventry City council provide local digital exclusion insights for Coventry specifically. This data can be explored at both a city-wide and local level, and crossmatches multiple data sources which individuals can explore and filter.

When exploring each data set, data is presented in a concise manner, using graphs, tables, and interactive mapping for individuals to explore.

Statistics can be presented by ward or LSOA if individuals require in-depth data on a specific location. This allows for identification of digital exclusion, internet access, broadband, and internet user statistics for each area and direct comparison – helping to identify areas where work is needed to support residents, as well as being useful for backgrounds to reports or rationales for research.

Information pack 3 - Children Early Years

The table is also available for individuals to download, allowing individuals to use the data in their work, reports, and for any presentations surrounding this topic. Please note: when interpreting this data, the ONS provides some information as to why 2019/20 and 2020/21 is not available (due to the COVID-19 pandemic). Data from before 2018 is also not available for this topic due to changes in the ‘Writing Teacher Assessment Frameworks’ which makes data not comparable.

ONS also provides the direct link to the original dataset for this topic, via the Department of Education where a direct hyperlink is provided.

Communication and language skills by end of early year foundation age

Within this section, ONS provides data on the percentage of 5-year-olds at ‘expected level’ across all communication and language early learning goals. The data is provided over 3 academic years, ranging from 2021/22-2023/24, allowing for individuals to examine differences over time for the local area or comparison across the UK.

Data is presented through a range of different formats including an interactive map. The interactive map allows for individuals to change options on geography type (ranging from country and regions to lower-tier/unitary authorities) to examine data on percentage of 5-year-olds at ‘expected level’ across all communication and language early learning goals.

Data for this topic is also presented in the following formats, allowing for individuals to explore and present data in the most accessible way:

• Line chart (interactive across local authorities)
• Bar chart (interactive across local authorities)
• Table.

The table provides area codes and names for all authorities, allowing for individuals again to choose an option of geography type (the same as the interactive map). The table of data provides data for all three academic years (from 2021/22 to 2023/24), allowing for a clear comparison across academic years for this data.

The table is also available for individuals to download, allowing individuals to use the data in their work, reports, and for any presentations surrounding this topic.

Please note: when exploring data on this topic, the only years available are from the academic year 2021/22. The ONS highlights that this is due to the Early Years Foundation stage profile changed significantly in September 2021 which means that any data prior to this is not comparable with current data presented. ONS also provides the direct link to the original dataset for this topic, via the Department of Education where a direct hyperlink is provided.

Literacy skills and maths skills by end of early years foundation age

Within this section, ONS provides data on the percentage of 5-year-olds at ‘expected level’ across all literacy early learning goals. The data is provided over 3 academic years, ranging from 2021/22-2023/24, allowing for individuals to examine differences over time for the local area or comparison across the UK.

Data is presented through a range of different formats including an interactive map. The interactive map allows for individuals to change options on geography type (ranging from country and regions to lower-tier/unitary authorities) to examine data on percentage of 5-year-olds at ‘expected level’ across all literacy early learning goals.

Data for this topic is also presented in the following formats, allowing for individuals to explore and present data in the most accessible way:

• Line chart (interactive across local authorities)
• Bar chart (interactive across local authorities)
• Table.

The table provides area codes and names for all authorities, allowing for individuals again to choose an option of geography type (the same as the interactive map). The table of data provides data for all three academic years (from 2021/22 to 2023/24), allowing for a clear comparison across academic years for this data.

The table is also available for individuals to download, allowing individuals to use the data in their work, reports, and for any presentations surrounding this topic.

Please note: when exploring data on this topic, the only years available are from the academic year 2021/22. The ONS highlights that this is due to the Early Years Foundation stage profile changed significantly in September 2021 which means that it is not possible to compare assessment outcomes with data before the 2021/22 academic year. Also, for this topic, ONS highlights that some of the data has been aggregated, which needs to be noted when individuals are accessing and using the data. ONS also provides the direct link to the original dataset for this topic, via the Department of Education where a direct hyperlink is provided.

2. LG Inform (and LG Inform Plus) https://lginform.local.gov.uk/ [https://lginform.local.gov.uk/]

LG Inform (Local Government Inform), is an accessible platform which is funded by the UK government. The LG Inform platform was introduced as a practical solution to ensure that local governments and organisations could access data which will help influence decision making and policy, with the addition of being a free platform which members of the public can also use.

LG Inform Plus provides the same foundation content as LG Inform but allows for individuals to look at data through specific wards and transform data into charts, maps, and tables. Please note: LG Inform Plus requires a licence and is therefore only accessible for Coventry City Council Colleagues via registering for an account.

Due to children (early years) not being a defined topic on LG Inform (or LG Inform Plus), individuals will need to use the following search terms to look for data on this topic:

• ‘Childhood’
• ‘Infants’
• ‘Children’

To access the search option, individuals need to click on ‘search data and reports’ followed by ‘search’ instead of ‘explorer’.

When using the above search terms, LG Inform contains a range of data, but the following are the most in depth and offer the options to view both the report and data:

• Childhood obesity (from 3 years old to year 6 age)
• Vaccination coverage (from 1-5 years).

Childhood Overweight and Obesity statistics (from reception age to year 6 age)

For childhood obesity and overweight statistics, LG Inform and LG Inform Plus breaks these down into reception age and year 6 age.

Overweight and obesity statistics are provided as either a 3-year total (from the academic year 2021/22 to 2023/24), or as a percentage. The ‘overweight children in reception year (3-year total)’, allows for individuals to view the data which is provided either in:

• Table format
• Bar graph format
• Interactive map format.

These formats allow for individuals to view Coventry’s overall total across the 3-years and compare with other local authority areas.

Within the table format and interactive map, individuals are able to select how they would like to view data and are able to select to view the local authority and compare by wards. For Coventry, all wards are presented in the table format, allowing for comparison across the wards and identification of which area/s are higher in terms of overweight levels in childhood (of reception age).

When using LG Inform Plus, individuals can ‘view report’ for number of children in reception classified as overweight, including obesity (3-year total) for Coventry broken down by ward.

Within this 6-page report, individuals have access to data on this topic in a range of formats including:

• Tables
• Bar graphs and
• Maps

with all data being broken down by ward to allow individuals to compare statistics across Coventry. The report within LG Inform Plus can be downloaded into a PDF, allowing for individuals to share the report and use key statistics within work and to help inform policy and evidence-based decision making for this topic. All data within this report is originated from the Office for Health Improvement and Disparities (OHID), with acknowledgment of the name of the collection where the data sits in OHID and how to interpret the data.

Please note: statistics around childhood overweight levels and childhood obesity levels for reception and year 6 age children are presented separately but are presented in the same format.

Vaccination Coverage (from 1-5 years)

For vaccination coverage statistics, LG Inform and LG Inform Plus breaks these down into age and vaccination type including:

• Population vaccination coverage – MenB (1 years old)
• Population vaccination coverage – DtaP IPV Hib, HepB (2 years old)
• Population vaccination coverage – DtaP/IPV booster (5 years old)
• Population vaccination coverage – DtaP IPV Hib HepB (1 years old)
• Population vaccination coverage – MenB booster (2 years old)
• Population vaccination coverage – Rotavirus (1 years old).

Please note: for all vaccinations and ages included in LG Inform and LG Inform Plus, data is presented in the same format, allowing individuals to compare Coventry statistics to other local authorities. The data for this topic is not broken down into ward, meaning comparison of areas within Coventry is not possible.

All vaccination coverage data is available in the following formats for individuals to access and view data:

• Table format
• Bar graph format and
• Interactive map format.

When using LG Inform Plus, individuals can ‘view report’ for vaccination coverage for all topics and ages available in LG Inform. Within this 6-page report, individuals have access to data on this topic in a range of formats including:

• Tables
• Bar graphs and
• Maps

with all data being available by local authority across England. The report within LG Inform Plus can be downloaded into a PDF, allowing for individuals to share the report and use key statistics within work and to help inform policy and evidence-based decision making for this topic. All data within this report is originated from the Public Health Outcomes Framework which sits within the Office for Health Improvement and Disparities.

3. Fingertips https://fingertips.phe.org.uk/ [https://fingertips.phe.org.uk/]

Fingertips is a large public health data collection maintained by Public Health England. Data within Fingertips is organised into themed profiles. When using the Fingertips platform, there is an option to view ‘Public Health Profiles’ for a specific area. There are 29 Public Health Profiles on the platform, including ‘Child and Maternal Health’. When clicking on each profile, individuals can select a specific local authority to get location specific data.

When selecting a specific area, individuals can select either ‘view data’ or ‘view reports’ for each specific profile.

‘View Data’

When selecting ‘view data’ individuals can view the statistics for a range of topics and view the trend of the data signifying whether the statistic from the previous time period is increasing or decreasing. When viewing Coventry data, Fingertips also provides comparisons for the West Midlands and overall England statistics, allowing for individuals to examine the local area data and make comparisons.

Please note: Some data provided by Fingertips is not up to date. For example, the ‘Health Behaviours in young people’ report is from 2016, meaning that data may not be providing a ‘true’ reflection of the current picture in the specific local area.

Individuals can view three distinct timepoints allowing for a time-trend analysis between 2020/21 to 2023. Please note: Data from 2024 is currently not available on this platform.

‘View Reports’

When selecting ‘view reports’, individuals can view a range of reports on the topic for the chosen area.  For ‘Child and Maternal Health’, the following reports are available on Fingertips:

• Child Health Profile
• Child Health Profile – Historical Reports (date range from 2011-2021)
• Health behaviours in young people
• Oral Health Profile of 5-year-olds.

Each report provides key statistics in a variety of formats including tables, maps, bar graphs, and for some figures provides statistical comparison of the local area to the England average and ‘worst’ statistic.

The reports also include written summaries of the findings, including a ‘key findings' section for individuals to see the most important statistics for the local area selected. Reports are printable and available to download, allowing for reports to be shared within teams and key findings to be disseminated to encourage the use of data within practice, and evidence and policy decision making.

Information pack 4 - Employment and Skills

Definition: How do we define Employment and Skills?

Employment

Employment is defined as “working for at least one hour a week for some payment, either for a wage or for profit, or commission, or without pay in a family business” (Gov UK, 2025 [https://www.gov.uk/employment-status/employee]). The employment rate is defined as the rate which “measures the proportion of the working-age population in employment. A rising employment rate indicates economic growth.

Skills

Employability skills are defined as “the foundational skills, personal qualities, and attitudes which enable individuals to succeed in the workplace and advance in their careers” (Institute for Employment Studies, 2025 [https://www.employment-studies.co.uk/report-summaries/report-summary-employability-developing-framework-policy-analysis]). Education and skills are often interlinked and include factors such as apprenticeships, GCSE’s and further education, providing individuals with the ‘hard skills’ which are often recorded in the data, whereas soft skills (such as personality) are often not recorded in datasets.

Key contact within Coventry City Council

If you are wanting to know more information about employment and skills, have any specific questions about the accessible data, or are keen to research employment and skills, please contact:

Glen Smailes. E: glen.smailes@coventry.gov.uk [mailto:glen.smailes@coventry.gov.uk]

Alex Dickson. E: alex.dickson@coventry.gov.uk [mailto:alex.dickson@coventry.gov.uk]

Why is ‘Employment and Skills’ a wider determinant of health?

Employment and skills are wider determinants of health because good jobs provide income, security, purpose, and social connection, while poor work or unemployment leads to stress, poverty, and unhealthy coping, directly impacting mental and physical health. Skills influence job quality, and overall work conditions shape well-being, creating a cycle where good work improves health and good health enables work.

They are key drivers of health inequalities, as variations in these factors determine an individual's access to the "building blocks" of a healthy life.

How employment affects health

• Income & Resources: Employment provides money for better nutrition, housing, and healthcare, improving living standards and reducing material deprivation.
• Purpose & Social Connection: Work offers a sense of identity, purpose, routine, and social interaction, boosting mental health and reducing isolation.
• Stress & Mental Health: Unemployment is a major stressor, linked to anxiety, depression, and lower self-esteem, while stressful, demanding jobs also harm mental health.
• Physical Health: Good jobs offer protection from hazards, while job insecurity and poverty can lead to unhealthy behaviours (smoking, poor diet) and increased risk of chronic conditions.

How skills influence health

• Job Quality: Higher skills often lead to better-paying jobs with more control, job security, and better working conditions, promoting better health.
• Labour Market Position: Education and skills determine one's place in the labour market, influencing income, housing, and overall health outcomes (the "social gradient").
• Resilience: Higher qualifications can make it easier to stay employed or find new work if health declines, buffering against negative health impacts.

The Bidirectional “Virtuous Circle”

• Two-Way Relationship: Good health is necessary to gain and retain employment, while stable employment actively supports health.
• Economic Impact: Research continues to emphasise that failing health in the working-age population reduces productivity and increases welfare costs, while inclusive recruitment can help "level up" deprived communities.

Key literature signposting

Belloni, M., Carrino, L., & Meschi, E. (2022). The impact of working conditions on mental health: Novel evidence from the UK [https://www.sciencedirect.com/science/article/pii/S0927537122000677]. Labour Economics, 76.

Burgard, S. A., & Lin, K. Y. (2014). Bad jobs, bad health? How work and working conditions contribute to health disparities [https://pmc.ncbi.nlm.nih.gov/articles/PMC3813007/#:~:text=While%20material%20benefits%20are%20obviously,leading%20to%20risky%20health%20behaviors.]. American Journal of Health Science, 57.

City of Hackney Council. (2026). Wider Determinants of Health: Employment and Income [https://cityhackneyhealth.org.uk/wider-determinants-of-health/employment-and-income/#:~:text=Employment%20and%20income%20%2D%20City%20and,end%20of%20the%20social%20gradient.].

Creative Health Toolkit (2026). Wider Determinants of Health: Employment [https://creativehealthtoolkit.org.uk/creative-health-in-context/wider-determinants-of-health#:~:text=Conversely%2C%20health%20conditions%20can%20also,improve%20health%20in%20the%20workplace.].

Hergenrather, K. C., Zeglin, R. J., McGuire-Kuletz, M., & Rhodes, S. D. (2015). Employment as a social determinants of health: A systematic review of longitudinal studies exploring the relationship between employment status and physical health [https://www.researchgate.net/publication/273333771_Employment_as_a_Social_Determinant_of_Health_A_Systematic_Review_of_Longitudinal_Studies_Exploring_the_Relationship_Between_Employment_Status_and_Physical_Health]. Rehabilitation Research Policy and Education, 29.

Lai, H., Due, C., & Ziersch, A. (2022). The relationship between employment and health for people from refugee and asylum-seeking backgrounds: A systematic review of quantitative studies . SSM – Population Health, 18, e101075.

NHS Employers. (2022). Tackling Health Inequalities through Inclusive Recruitment [https://www.nhsemployers.org/publications/tackling-health-inequalities-through-inclusive-recruitment#:~:text=19%20workforce%20practices-,Introduction,have%20recently%20been%20made%20unemployed.].

Peckham, T., Fujishiro, K., Hajat, A., Flaherty, B. P., & Seixas, N. (2019). Evaluating employment quality as a determinant of health in a changing labour market [https://www.jstor.org/stable/10.7758/rsf.2019.5.4.09?seq=1]. The Russell Safe Foundation Journal of the Social Sciences, 5, 258-281.

Public Health England. (2018). Chapter 6: Wider Determinants of Health [https://www.gov.uk/government/publications/health-profile-for-england-2018/chapter-6-wider-determinants-of-health#work-and-the-labour-market].

The Health Foundation (2024). Relationship between Employment and Health .

The Health Foundation (2026). Wider Determinants of Health: Work [https://www.health.org.uk/evidence-hub/work].

Woodall, J., Coan, S., & Stanley, M. (2023). Reducing health inequalities through skills training, support, and removing barriers to employment [https://journals.sagepub.com/doi/10.1177/00178969231175991#:~:text=Meaningful%20employment%20is%20an%20important%20constituent%20of%20individual%20and%20community,et%20al.%2C%202022).]. Health Education Journal, 82.

Publicly accessible data on 

Employment and Skills

1. Office for National Statistics (ONS) https://www.ons.gov.uk/explore-local-statistics/ [https://www.ons.gov.uk/explore-local-statistics/]

Office for National Statistics (ONS) is an accessible platform which is funded by the UK government through the Open Government Licence. Within this platform, individuals are able to explore local statistics, exploring how a local area compares to the Great Britain average. Data is presented in graphs which are interactive, allowing for individuals to examine how their local area (Coventry) compares to the GB average, and other local authorities. The ONS platform provides data for a wide range of topics including economy (includes employment) and education and skills.                  

Economy (Employment)
For all graphs available, individuals can see the local area, as it currently stands (with data being up to date for each year), as well as a time-trend analysis on the right-hand side of the graphs for each section. This allows for identification of how the local area has changed over the past 20-years on each topic. When selecting the ‘chart options’, individuals are able to alter the year range which they would like to focus upon.

This allows for more focussed time trend analysis to examine how a particular factor has changed within a local area. For employment, the ONS platform has the following factors available for the economy:

• Employment
  • Economic inactivity rate
  • Employment rate
  • Modelled unemployment rate
  • Claimant count
• Pay and income
  • Gross disposable household income
  • Gross median weekly pay
• Productivity
  • Gross value added per hour worked
  • Gross domestic product per head at current market prices
  • Gross domestic product per head in chained volume measures
• Business
  • Active businesses
  • Business births
  • Business deaths
  • High growth businesses.

This wide range of data available for local areas and the inclusion of GB averages allows for the employment and economic status of an area to be examined.

Education and Skills

As with employment, for education and skills, within the ONS platform all graphs which are available individuals can see the local area, as it currently stands (with data being up to date for each year), as well as a time-trend analysis on the right-hand side of the graphs for each section. This allows for identification of how the local area has changed over the past 20-years on each topic. When selecting the ‘chart options’, individuals are able to alter the year range which they would like to focus upon.

For education and skills, the ONS platform has the following factors available for the economy:

• Attainment and participation
  • Further education and skills participation
  • GCSE’s in English and maths
  • Level 3 or above qualifications
  • Pupils meeting the expected standard in reading, writing and maths at the end of key stage 2
  • No qualifications
• Apprenticeships
  • Apprenticeship achievements
  • Apprenticeship starts

2. LG Inform  https://lginform.local.gov.uk/ [https://lginform.local.gov.uk/]

LG Inform (Local Government Inform), is an accessible platform which is funded by the UK government. The LG Inform platform was introduced as a practical solution to ensure that local governments and organisations could access data which will help influence decision making and policy, with the addition of being a free platform which members of the public can also use.

LG Inform has a range of accessible data on business and employment. There are 1256 reports and/or datasets for individuals to access, which can be presented in a report, or access to the raw data is also accessible for individuals. Reports are themed into:

• Business grants (32 reports)
• Business rates (57 reports)
• Careers and employment (825 reports)
• Health and safety at work (8 reports)
• Trading standards (8 reports)

For each specific data set, individuals can click on either ‘view report’ or ‘view data’ which provides specific data for specific locations (such as Coventry), providing direct comparison to other local authority locations or cities within the UK. Data can be presented as either a table, graph, or interactive map.

2a. LG Inform Plus - https://home.esd.org.uk/ [https://home.esd.org.uk/]

Please note: LG Inform Plus requires a licence and is therefore only accessible for Coventry City Council Colleagues via registering for an account.

LG Inform Plus provides the same foundation content as LG Inform but allows for individuals to look at data through specific wards and transform data into charts, maps, and tables. For example, for employment, data can be created into a detailed themed report, which is modifiable by:

• Data metric
• Date period
• Location
• Comparison group

Whilst using LG Inform Plus, individuals are able to search for data on employment specifically. This provides 2097 results including information on topics such as:

• Number of economically inactive
• Employment status
• Employment indicator
• Female employment
• Male employment and many more!

Whilst using LG Inform Plus, individuals can generate reports which are only visible to them on a particular topic. For example, for Employment and Skills, a report can be generated adding in a map of the local area, bar graphs of data on employment, and break data down by ward. Once an individual has added all in data relevant to their chosen topic, the personalised report can be downloaded as PDF and shared. The report function allows for specific data to be shared in an accessible way on a particular topic, with graphs generated in the report being interactive for the reader to highlight any key areas of interest or statistics.

3. NOMIS https://www.nomisweb.co.uk [https://www.nomisweb.co.uk]

NOMIS is an accessible online platform which is developed by the Office for National Statistics. NOMIS does not require individuals to have a licence, meaning that all data is accessible. When using NOMIS, individuals are able to explore area profiles, and explore a specific location in relation to a range of factors including:

• Resident population
• Employment and unemployment
• Economic activity
• Workless households
• Employment by occupation
• Qualifications
• Earnings by place of residence
• Out of work benefits
• Jobs (total jobs / employee jobs)
• Businesses

All data is provided in tables and includes the specific number along with the percentage for the area chosen. If selecting Coventry, within the table there is comparison to the West Midlands (comparison of percentages) and Great Britain. 

When exploring the data, individuals are able to select ‘compare other areas’ allowing for comparison of number and percentage data to be compared for a specific topic. This is particularly useful if individuals are wanting to work with individuals from another local authority area or collaborate on research to demonstrate the need for research or work on the topics in those areas.

Individuals are also able to view a time-series of the data. The data in NOMIS goes back to 2004, allowing for individuals to explore how the data on employment has changed in the area over the past 21 years. Data going back to 2004 is presented both within an interactive graph (time-trend analysis) and as a table which provides numerical and percentage data.

4. Coventry City Council https://www.coventry.gov.uk/facts-coventry/economy-business [https://www.coventry.gov.uk/facts-coventry/economy-business]

Coventry City Council also have their own accessible data platform on ‘Economy and Employment’ in Coventry. The platform includes information on Coventry Labour market profile, skills which employers are seeking in the local are (ward) for residents in Coventry.

The PowerBI dashboard also includes data on:

• Employment rate
• Enterprises in Coventry
• Percentage of individuals claiming unemployment benefits
• Percentage of 16+ year olds employed claimants
• Median gross annual pay of employees by residence
• Number of workless households with dependent children

Data presented within the PowerBI graphs is presented over a range of years, with some datasets going back to 2005. This allows for individuals to explore the changes in employment over the years in Coventry.

5. Plumplot https://www.plumplot.co.uk/Coventry-salary-and-unemployment.html [https://www.plumplot.co.uk/Coventry-salary-and-unemployment.html]

Plumplot is an open accessible platform which provides information on a range of topics such as area insights, population, income/unemployment, home features, crimes and many more. Data is presented in a range of manners including interactive mapping, graphs and tables, allowing individuals to explore numerical data as well as see the data presented in graphs which is effective for presentations.

Individuals are able to explore specific areas using the ‘area insights’ option. For employment in Coventry, Plumplot provides information on 5 topic areas relating to employment.

Data presented compares Coventry to the closest local areas as well as the United Kingdom statistic. This allows for direct comparison, potentially allowing for individuals to highlight any successes or challenges for employment in Coventry. Data also goes back to 1999 for all line graphs, allowing for a time-trend analysis and identification of whether employment in Coventry (and any comparator areas) has improved or decreased.

Information pack 5 - Air Quality

Definition: How do we define Air Quality?

Air quality refers to the concentration of pollutants in the air at a specific location. Air quality is a measure of how clean or polluted the air is and can be impacted by factors such as human activity, weather, geography, transport. Poor air quality can be harmful to human physical health, including links to respiratory and cardiovascular conditions (GOV UK, 2019; NASA, 2024).

An Air Quality Management Area (AQMA) for Coventry was declared in 2009 because of high levels of nitrogen dioxide (NO2).

Key contact within Coventry City Council

If you are wanting to know more information about air quality, have any specific questions about the accessible data, or are keen to research air quality, please contact:

• Steve Dewar. E: steve.dewar@coventry.gov.uk

Why is Air Quality a wider determinant of health?

Air quality is considered a wider determinant of health because it is an environmental factor that shapes health outcomes beyond and individuals’ biology or personal choices. It is the largest environmental risk to public health in the United Kingdom, affecting people across their entire life course.

Key reasons why air quality is considered a wider determinant of health include:

• Environmental inequity: exposure is often beyond an individual’s control. Low-income and marginalised communities frequently live in highly polluted areas, such as near busy roads or industrial zones, leading to significant health inequalities.
• Lifelong impact: it affects health from the womb to old age. Exposure can lead to low birth weight, stunted lung development in children, and chronic conditions like Cardiovascular Disease, Dementia and Cancer in later life.
• Economic burden: poor air quality imposes massive costs on society. In the UK, health impacts are estimated to cost the economy between £8 billion and £20 billion annually due to healthcare needs and lost productivity.
• Co-benefits of improvement: addressing air quality often requires changes to other wider determinants, such as transport and urban planning. Initiatives like promoting active travel (walking/cycling) improve air quality whilst also increasing physical activity and mental wellbeing.
• Intersection with climate: pollutants that harm health often drive climate change. Strategies to reduce emissions simultaneously address environmental sustainability and immediate public health.

Unlike some pollutants that act slowly, Nitrogen Dioxide (NO2) has both immediate (acute) and long-term (chronic) effects on the human body including inflammation of the airways, reduced lung function, and increased vulnerability (weakening of immune system).

Key literature signposting

Air Quality Consultants. (2008). Review of bus fleet compositions and implications for emissions reduction strategies [https://uk-air.defra.gov.uk/reports/cat05/0906110919_Bus_Emissions_Report_Final_220409.pdf#:~:text=1.4%20The%20report%20focuses%20on%20areas%20where,contribute%20to%20exceedences%20across%20wider%20urban%20areas.].

Canaday, F. T., Georas, S. N., Croft, D. P. (2024). Examining the impact of air pollution, climate change, and social determinants of health on asthma and environmental justice [https://journals.lww.com/co-pulmonarymedicine/abstract/2024/05000/examining_the_impact_of_air_pollution,_climate.13.aspx]. Current Opinion in Pulmonary Medicine, 30, 276-280.

Gov UK. (2018). Health Matters: Air Pollution [https://assets.publishing.service.gov.uk/media/660182eaf1d3a0666832ac78/CD7.3.G_Guidance_Health_Matters_Air_Pollution.pdf].

Hoffmann, B., Boogaard, H., de Nazelle, A., Andersen, Z. J., Abramson, M., Brauer, M., Brunekreef, B., Forastiere, F., & Thurston, G. (2021). WHO air quality guidelines 2021 – aiming for healthier air for all: A joint statement by medical, public health, scientific societies, and patient representative organisations [https://www.ssph-journal.org/journals/international-journal-of-public-health/articles/10.3389/ijph.2021.1604465/full]. International Journal of Public Health, 66.

Leicester City Council. (2025). Air Quality Action Plan 2025-2030 [https://www.leicester.gov.uk/media/cb4m4m2b/air-quality-action-plan-leicester-2025-2030.pdf].

Monteiro, A., Figueiredo, E., Rodrigues, V., Cardoso, C., Lopes, M., Roebeling, P., Relvas, H., Seixas, P., Gouveia, S., Gomes, A., Martins, A., Gama, C., Aragao, A., Miranda, A. I., & Hayes, E. (2026). Air pollution and environmental justice: A systematic literature review on methodological approaches [https://www.sciencedirect.com/science/article/pii/S2405844025026933#:~:text=These%20wider%20determinants%20of%20health,health%20care%20services%20%5B19%5D.]. Heliyon, 12, e44289.

Patel, L., Friedman, E., Johannes, S. A., Lee, S. S., O’Brien, H. G., & Schear, S. E. (2021). Air pollution as a social and structural determinant of health [https://www.sciencedirect.com/science/article/pii/S2667278221000328#:~:text=The%20quality%20of%20a%20person's,them%20to%20these%20toxic%20pollutants.]. The Journal of Climate Change and Health, e100035.

Public Health England. (2019). Review of interventions to improve outdoor air quality and public health [https://assets.publishing.service.gov.uk/media/5fbf93258fa8f559dbb1add9/Review_of_interventions_to_improve_air_quality_March-2019-2018572.pdf].

Royal College of Physicians. (2016). Every breath we take: The lifelong impact of air pollution [https://rcp.ac.uk/media/jzul5jgn/every-breath-we-take-the-lifelong-impact-of-air-pollution-full-report.pdf].

Royal College of Physicians. (2025). A breath of fresh air: Responding to the health challenges of modern air quality [https://www.rcp.ac.uk/media/hvbeolvx/21072025-update-rcp-full-report-a-breath-of-fresh-air.pdf].

UK Health Security Agency. (2023). Health Effects of Climate Change (HECC) in the UK: 2023 Report [https://assets.publishing.service.gov.uk/media/6570a68b7469300012488948/HECC-report-2023-chapter-4-outdoor-air-quality.pdf].

Publicly accessible data on Air Quality

1. Fingertips: https://fingertips.phe.org.uk/ [https://fingertips.phe.org.uk/]

Fingertips is a large public health data collection maintained by Public Health England. Data within Fingertips is organised into themed profiles. When searching for air quality data, you can select from ICB’s, NHS Regions, Districts and counties.

Fingertips provides data on:

• Fraction of mortality attributable to particulate air pollution (presented in percentages)
• Air pollution: fine particulate matter (using concentrations of PM2.5)

This data source allows for comparison between specific locations, all districts within the West Midlands, and England.

Please note: data from air quality sources may have limitations when interpreting and transferring data to explore air quality in the wider area. For example, air quality measurement requires specific tools and technology which may be localised to the place where it is installed. Results can also be hindered by factors such as humidity, dust, seasons (time of year) and the overall sensitivity of the sensors. Therefore, it is best to ensure that data is examined carefully and only assumptions are made surrounding air quality and the correlation with mortality.

2. Department for Environment Food & Rural Affairs (DEFRA): https://uk-air.defra.gov.uk/networks/network-info?view=aurn [https://uk-air.defra.gov.uk/networks/network-info?view=aurn]

The Automatic Urban and Rural Network (AURN) is the UK's largest automatic monitoring network and is the main network used for compliance reporting against the Ambient Air Quality Directives. It includes automatic air quality monitoring stations measuring oxides of nitrogen (NOx), sulphur dioxide (SO2), ozone (O3), carbon monoxide (CO) and particles (PM10, PM2.5). The AURN currently uses 193 sites and has 305 approved sites in total. For Coventry, there are two sites:

• Coventry Allesley
• Coventry Binley Road

Information about these locations can be found on the main page, under the AURN monitoring dropdown tab.

The interactive monitoring networks map option also allows for you to see measurements across multiple locations. You are also able to view a variety of data for each site (as seen in image).

3. West Midlands Air Quality Data Platform: https://experience.arcgis.com/experience/41445259d79c4fb7aa95f98291fb9582 [https://experience.arcgis.com/experience/41445259d79c4fb7aa95f98291fb9582]

The WM Air Quality Data platform shows the air quality sensor measurements of several pollutants that can be harmful to health and air quality. Particulates (PM10, PM2.5 and PM1), Nitrogen Dioxide (NO2), and Ground level ozone (O3) are measured within this platform.

There are 10 sensor sites within Coventry:

• Eden Girls School
• King Henry VIII School
• Buckingham Rise
• University Hospital Coventry and Warwickshire
• Stoke Primary School
• The Xcel Leisure Centre
• Stoke Heath Primary School
• Henley Green Medical Centre
• Willenhall Community Primary School
• Families for All Hub

To search for these locations in the 7- or 10-day charts, you will need to use the location specific name.

The data platform is an interactive map which shows information from all sensors across the West Midlands for NO2, PM10 and PM 2.5 and is frequently updated – showing live figures. This allows for direct comparisons for all WM Air sensors across the West Midlands, with reliable and up-to-date information.

4. Coventry City Council – Air Quality: https://www.coventry.gov.uk/pollution-1/air-quality/3 [https://www.coventry.gov.uk/pollution-1/air-quality/3]

Coventry City Council has a range of information and resources for air quality monitoring including:

• Transport and air quality in Coventry
• Coventry local air quality action plan
• Monitoring air quality in Coventry

Monitoring air quality in Coventry

The monitoring air quality in Coventry page explores pollution monitoring, and how nitrogen dioxide is measured using Diffusion tubes. This includes an interactive map showing nitrogen dioxide level in Coventry which can be explored and compared by Ward and is updated once per year.

Air quality assessments and reports are available, which include raw data from monitoring results within the reports and analysed data presented in graphs comparing yearly figures. Reports start from 2006 (screening assessment) and available to download via PDF.

You can find air quality assessments and reports here: https://www.coventry.gov.uk/downloads/download/618/air_quality_in_coventry [https://www.coventry.gov.uk/downloads/download/618/air_quality_in_coventry]

5. West Midlands Combined Authority: Air Quality - https://www.wmca.org.uk/what-we-do/environment-energy/air-quality/ [https://www.wmca.org.uk/what-we-do/environment-energy/air-quality/]

The West Midlands Combined Authority (WMCA) have been working with local authorities within the West Midlands and key stakeholders to help design and deliver a clear plan for cleaner air within the West Midlands.

The Air Quality Framework Reference Document [https://www.wmca.org.uk/media/n5ppmbp2/wmca-air-quality-framework-reference-document.pdf] provides 145 options which can be implemented to help improve air quality. These options can be applied to any local (West Midlands location) to help improve air quality. 

Within the document, there are sources of accessible data for air quality and air pollution within the West Midlands. The accessible data includes:

• Identifying sources of air pollution by specific pollutant
• Mapping of air pollutants within the West Midlands
• Trends of air pollutants for the UK from 1970-2021.

Information pack 6 - Children Young People

Definition: How do we define Children (Young People) – best start in life?

Children (young people) is often referred to as adolescence, which is defined as the transitional stage of development between childhood and adulthood. While often associated with the “teenage” years, it is increasingly understood as a broader period which is driven by biological, cognitive and social milestones rather than a specific age range.

Key contact within Coventry City Council

If you are wanting to know more information about children (young people), have any specific questions about the accessible data, or are keen to research children (young people) / best start in life, please contact:Datateam.PD@coventry.gov.uk [mailto:Datateam.PD@coventry.gov.uk]

Why is Children (young people) – best start in life a wider determinant of health?

Adolescence is a critical wider determinant of health because it acts as a ‘second sensitive period’ of development. During this time, rapid biological changes intersect with shifting social environmental to entrain life-long health trajectories.

Rather than just being a life stage, it acts as a ‘gateway’ where external social factors (such as education, family, stability, and peer influence) intersect with rapid brain development to local in health trajectories.

Establishment of lifelong health behaviours

Adolescence is the primary window for adopting habits that account for a massive portion of the adult disease burden:

• Risk initiation: most smokers usually start during their teens; those who do not start by the age of 20 are highly unlikely to ever smoke.
• Habit formation: patterns of diet, physical activity and substance use established now often persist throughout adulthood.
• Long-term impact: behaviours adopted in this period are major drivers of non-communicable disease (i.e., heart disease and cancer) in later life.

Critical life transitions

Adolescence is defined by major social transitions that determine future “life changes” and socioeconomic status:

• Education to work: successful transitions from school to employment protect against the poverty and social exclusion that drive poor adult health.
• Autonomy: young people move from family-led care to taking responsibility for their own health, making their early interaction with health systems a determinant of future health-seeking behaviour.

Key literature signposting

Aagaard-Hansen, J., Hindhede, A. L., & Maindal, H. T. (2023). A conceptual framework for selecting appropriate populations for public health interventions [https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.1161034/full]. Frontiers, 11.

Lancet Series on Adolescent Health. (2014). Adolescence and the Social Determinants of Health [https://www.prb.org/wp-content/uploads/2014/07/lancet-youth-factsheet-2.pdf].

Likhar, A., Baghel, P., & Patil, M. (2022). Early childhood development and social determinants [https://www.cureus.com/articles/112074-early-childhood-development-and-social-determinants#!/]. Cureus, 14(9), e29500.

Mance, G. S., Grant, K. E., Roberts, D., Carter, J., Turek, C., Adam, E., Thorpe Jr, R. J. (2019). Environmental stress and socioeconomic status: Does parent and adolescent stress influence executive functioning in urban youth [https://www.tandfonline.com/doi/full/10.1080/10852352.2019.1617386]? Journal of Prevent & Intervention in the Community, 47(4), 279-294.

Nichols, M., Nemeth, L. S., Magwood, G., Odulana, A., Newman, S. (2016). Exploring the contextual factors of adolescent obesity in an underserved population through photovoice [https://journals.lww.com/familyandcommunityhealth/abstract/2016/10000/exploring_the_contextual_factors_of_adolescent.10.aspx#:~:text=This%20approach%20allowed%20consistent%20categorization%20of%20barriers,peer%20influence%2C%20social%20environment%2C%20physical%20environment%2C%20etc).]. Family and Community Health, 39(4), 301-309.

Ross, D. A., Friedman, H. S., Welch, D., Kaoma, N. S., Bhushan, R., & Rasmussen, B. (2022). Four powerful reasons for increasing investment in adolescents and their wellbeing [https://www.bmj.com/content/379/bmj.o2526]. The BMJ, 379.

Scales, P. C., Benson, P. L., Oesterle, S., Hill, K. G., Hawkins, D., & Pashak, T. J. (2015). The dimensions of successful young adult development: A conceptual and measurement framework [https://www.tandfonline.com/doi/full/10.1080/10888691.2015.1082429]. Applied Developmental Science, 20(3), 150-174.

Viner, R. M., Ozer, E. M., Denny, S., Marmot, M., Resnick, M., Fatusi, A., & Currie, C. (2012). Adolescence and the social determinants of health [https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(12)60149-4/abstract]. Adolescent Health, 379.

Yang, C. Y., Walsh, C. E., Johnson, M. P., Belsky, D. W., Reason, M., Curran, P., Aiello, A. E., Chanti-Ketterl, M., & Harris, K. M. (2021). Life-course trajectories of body mass index from adolescence to old age: Racial and educational disparities [https://www.pnas.org/doi/full/10.1073/pnas.2020167118]. PNAS Social Sciences, 118(17), e2020167118.

Publicly accessible data on Children (Young People) – best start in life

1. Office for National Statistics https://www.ons.gov.uk/explore-local-statistics/ [https://www.ons.gov.uk/explore-local-statistics/]

Office for National Statistics (ONS) is an accessible platform which is funded by the UK government through the Open Government Licence. Within this platform, individuals can explore local statistics, exploring how a local area compares to the Great Britain average. Data is presented in graphs which are interactive, allowing for individuals to examine how their local area (Coventry) compares to the GB average, and other local authorities.

Data provided surrounding children (young people) on the ONS sits within three key categories:

• Education and skills – attainment and participation
• Education and skills – school attendance
• Education and skills – apprenticeships

Education and skills – attainment and participation

In the section of attainment and participation, ONS provides data on GCSE in English and Maths among those by age 19.

GCSEs in English and Maths

Within GCSEs in English and Maths, users can access data on “the percentage of people achieving GCSEs in both subjects by age 19”. Data are available across different geography type, ranging from 2016/17-2023/24. There are four visualised formats for users to examine the data:

• interactive map,
• line chart,
• bar chart, and
• table.

This allows to examine performance differences within the local areas over time or compare those across the UK.

The interactive map allows individuals to change options on geography type and time to access the percentage of people achieving GCSEs in both subjects by age 19. Users can examine and compare performances of different local areas by referring to the colour chart attached to the bottom of the map. Users can view the exact percentage for an area by hovering the cursor over it on the map. Multiple geographic areas can be selected for comparison, and their values are highlighted on the colour chart. The selected areas are also displayed in the line chart and the bar chart, where they appear in coloured shades to distinguish them from other regions, enabling users to change over time (line chart) and compare across different regions (bar chart). 

The line chart, bar chart, and table all allow users to examine and compare the same indicator across geographic areas. The line chart shows how the selected areas have changed over time, rather than displaying data for a single point in time. Users can adjust the time period by clicking on Options above the chart. In contrast, the bar chart presents data across regions at a single time point. The table provides data for all available time periods, enabling both cross-sectional and time-series comparisons.

Please note: ONS acknowledges to users that, since the data are aggregated in this section, they may appear different from other published figures. The original data can be found on the Department for Education [https://explore-education-statistics.service.gov.uk/find-statistics/level-2-and-3-attainment-by-young-people-aged-19/2023-24] website.

Education and skills – school attendance

In the section of school attendance, ONS provides data on persistent absences for all pupils, persistent absences for pupils eligible for free school meals, persistent absences for pupils looked after by local authorities.

Persistent absences for all pupils

Within persistent absences for all pupils, users can access data on ‘the percentage of pupils in state-funded primary, state-funded secondary and special schools that were persistently absent (those absent for 10% of schooling sessions) during the academic year, in England’.

Data are available across different geography type, including countries and regions and upper-tier/unitary authorities, ranging from 2006/07-2023/24 (updated in September 2025).

There are four visualised formats for users to examine the data:

• interactive map,
• line chart,
• bar chart, and
• table.

This allows to examine performance differences within the local areas over time or compare those across the UK.

The interactive map allows individuals to change options on geography type and time period to access the percentage of pupils in state-funded schools that were absent for 10% of academic year. Users can examine and compare performances of different local areas by referring to the colour chart attached to the bottom of the map. Users can view the exact percentage for an area by hovering the cursor over it on the map. Multiple geographic areas can be selected for comparison, and their values are highlighted on the colour chart. The selected areas are also displayed in the line chart and the bar chart, where they appear in bold to distinguish them from other regions, enabling users to capture change over time (line chart) and compare across different regions (bar chart).

The line chart, bar chart, and table all allow users to examine and compare the same indicator across geographic areas. The line chart shows how the selected areas have changed over time, rather than displaying data for a single point in time. Users can adjust the time period by clicking on Options above the chart. In contrast, the bar chart presents data across regions at a single time point. The table provides data for all available time periods, enabling both cross-sectional and time-series comparisons.

Please note: ONS acknowledges to users that, data are not available for academic year 2019/20. The dataset covers state-funded primary and secondary schools as well as special schools, although data for special schools are only available from 2016/17 onwards. The original data can be found on the Department for Education [https://explore-education-statistics.service.gov.uk/find-statistics/level-2-and-3-attainment-by-young-people-aged-19/2023-24] website.

Persistent absences for pupils eligible for free school meals

Within persistent absences for pupils eligible for free school meals, users can access data on “the percentage of pupils in state-funded primary, secondary, and special schools who have been eligible for free school meals in the past 6 years that were persistently absent (those absent for 10% of schooling sessions) during the academic year, in England (state-funded schools), for academic years 2017/18-2023/24.

Data are available across different geography type, including countries and regions and upper-tier/unitary authorities, ranging from 2017/18-2023/24 (updated in September 2025). There are four visualised formats for users to examine the data:

• interactive map,
• line chart,
• bar chart, and
• table.

This allows to examine performance differences within the local areas over time or compare those across the UK.

The interactive map allows individuals to change options on geography type and time period to access the percentage of free school meal eligible pupils in state-funded schools that were absent for 10% of academic year. Users can examine and compare performances of different local areas by referring to the colour chart attached to the bottom of the map. Users can view the exact percentage for an area by hovering the cursor over it on the map. Multiple geographic areas can be selected for comparison, and their values are highlighted on the colour-shaded map. The selected areas are also displayed in the line chart and the bar chart, where they appear in coloured shades to distinguish them from other regions, enabling users to capture change over time (line chart) and compare across different regions (bar chart). 

The line chart, bar chart, and table all allow users to examine and compare the same indicator across geographic areas. The line chart shows how the selected areas have changed over time, rather than displaying data for a single point in time. Users can adjust the time period by clicking on Options above the chart. In contrast, the bar chart presents data across regions at a single time point. The table provides data for all available time periods, enabling both cross-sectional and time-series comparisons.

Please note: ONS acknowledges to users that, data are not available for academic year 2019/20. Sessions recorded as not attending due to COVID circumstances are included as possible sessions in 2020/21 and 2021/22 only, but not as an absence within absence rates. The original data can be found on the Department for Education [https://explore-education-statistics.service.gov.uk/find-statistics/level-2-and-3-attainment-by-young-people-aged-19/2023-24] website.

Persistent absences for pupils looked after by local authorities

Within persistent absences for pupils looked after by local authorities, users can access data on “the percentage of pupils in state-funded primary, secondary, special schools, and pupil referral units who have been looked after continuously for at least 12 months (as of 31 March of that year) by local authorities who were persistently absent (those absent for 10% of schooling sessions) during the academic year, in England, for financial years 2017/18-2023/24”.

Data are available across different geography type, ranging from 2017/18-2023/24 (updated in September 2025). There are four visualised formats for users to examine the data:

• interactive map,
• line chart,
• bar chart, and
• table.

This allows to examine performance differences within the local areas over time or compare those across the UK.

The interactive map allows individuals to change options on geography type and time period to access the percentage of pupils looked after continuously by local authorities for at least 12 months that were absent for 10% of academic year. Users can examine and compare performances of different local areas by referring to the colour chart attached to the bottom of the map. Users can view the exact percentage for an area by hovering the cursor over it on the map. Multiple geographic areas can be selected for comparison, and their values are highlighted on the colour-shaded map. The selected areas are also displayed in the line chart and the bar chart, where they appear in coloured shades to distinguish them from other regions, enabling users to capture change over time (line chart) and compare across different regions (bar chart). 

The line chart, bar chart, and table all allow users to examine and compare the same indicator across geographic areas. The line chart shows how the selected areas have changed over time, rather than displaying data for a single point in time. Users can adjust the time period by clicking on Options above the chart. In contrast, the bar chart presents data across regions at a single time point. The table provides data for all available time periods, enabling both cross-sectional and time-series comparisons.

Please note: ONS acknowledges to users that, the absence data in this section are matched to school census data for each school type. This means that pupils included in the dataset are those having absence data on the school census. Persistent absence figures for all pupils and those eligible for free school meals are taken from the national absence figures. They are produced and analysed in a different way from the data in this section, so it is not appropriate to compare these figures with those for looked after children. Additionally, data are not available for year 2019/20 due to COVID.  The original data can be found on the Department for Education [https://explore-education-statistics.service.gov.uk/find-statistics/level-2-and-3-attainment-by-young-people-aged-19/2023-24] website.