Census 2021 data on religion by economic activity status, by sex, by age, and religion by occupation, by sex, by age, England and Wales combined. This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

This dataset shows population counts for usual residents aged between 16 to 64 years old only. This is to focus on religious affiliation differences among the working age. Population counts in these tables may be different from other publications which use different age breakdowns.

Quality notes can be found here

Quality information about Labour Market can be found here

The Standard Occupation Classification 2020 code used can be found here

Religion

The 8 ‘tickbox’ religious groups are as follows:

• Buddhist
• Christian
• Hindu
• Jewish
• Muslim
• No religion
• Sikh
• Other religion

Census 2021 data on religion by highest qualification level, by sex, by age, England and Wales combined. This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

This dataset shows population counts for usual residents aged 16 years and over. Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

Quality notes can be found here

Quality information about Education can be found here

Religion

The 8 ‘tickbox’ religious groups are as follows:

• Buddhist
• Christian
• Hindu
• Jewish
• Muslim
• No religion
• Sikh
• Other religion

No qualifications

No qualifications

Level 1

Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

Level 2

5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

Apprenticeship

Apprenticeship

Level 3

2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

Level 4 +

Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

Other

Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)

MP Religion & Assisted Dying Dashboard

This data powers a dashboard presenting insights into the religious affiliations and Assisted Dying voting patterns of UK Members of Parliament (MPs). It can be found here:

👉 https://davidjeffery.shinyapps.io/mp-religion/.

Please cite all uses of the data.

📊 What is this dashboard?

This dashboard presents insights into the religious affiliations and Assisted Dying voting patterns of UK Members of Parliament. It combines publicly available data to support transparency and understanding of Parliament’s composition.

📂 Where does the data come from?

The data is compiled from publicly available parliamentary records and voting data. You can download it directly from the link in the header or view it in the Raw Data tab of the dashboard.

🙏 How is religion determined?

There are three steps to determining religion. An MP is classified as having a religion based on the following criteria:

1. If the MP is a member of a religiously based group, they are classified as a member of that religion.

2. If a member has publicly spoken about their religion, they are classified as a member of that religion.

3. Finally, the text an MP swore in on is used to help infer their religion.

These sources are used in order of priority. For example, Tim Farron is a member of Christians in Parliament and has spoken about his religious views. However, he did not take the oath on the Bible, but made a solemn affirmation on no text. Regardless, he is still classed as Christian.

🧾 Variable Reference

What do those variable names mean?

• Member ID – member_id – A unique numeric identifier for each MP provided by Parliament.

• Name – display_as – The full display name of the MP.

• Gender – gender – The MP’s gender.

• Party – party – The full political party name.

• Party (Simplified) – party_simple – A shortened or cleaned version of the party name.

• Religion – mp_final_relig – The MP’s classified religion based on multiple criteria outlined above.

• AD: 2nd Reading Vote – ass_suicide_2nd – The MP’s vote (Yes, No, Abstain) on the Assisted Dying Bill 2nd Reading.

• AD: 3rd Reading Vote – ass_suicide_3rd – The MP’s vote (Yes, No, Abstain) on the Assisted Dying Bill 3rd Reading.

• LGBT Status – lgbt – Whether the MP is publicly identified as LGBT (LGBT.MP).

• Ethnic Minority – ethnic_mp – Whether the MP identifies as an ethnic minority.

• Religious Group: Christian – relig_christian – MP belongs to a Christian group (1 = Yes).

• Religious Group: Muslim – relig_muslim – MP belongs to a Muslim group (1 = Yes).

• Religious Group: Jewish – relig_jewish – MP belongs to a Jewish group (1 = Yes).

• Religious Group: Sikh – relig_sikh – MP belongs to a Sikh group (1 = Yes).

• Oath Taken – mp_swear – Whether the MP took the Oath or made an Affirmation.

• Oath Book – mp_swear_book – The specific religious text (e.g., Bible, Quran) used when swearing in.

• Inferred Religion – mp_inferred_relig – The religion inferred from the swearing-in text.

• Election Outcome – elected – Whether the MP was re-elected in the most recent election.

• Majority – majority – The MP’s vote share margin.

• Constituency Type – constituency_type – Type: Borough or County.

• Claimant Rate – cen_claimant – % of constituents claiming unemployment benefits.

• % White (Census) – cen_eth_white – Proportion of white ethnicity in the constituency.

• % Christian – cen_rel_christian – Constituency Christian population from the Census.

• % Buddhist – cen_rel_buddhist – Constituency Buddhist population.

• % Hindu – cen_rel_hindu – Constituency Hindu population.

• % Jewish – cen_rel_jewish – Constituency Jewish population.

• % Muslim – cen_rel_muslim – Constituency Muslim population.

• % Sikh – cen_rel_sikh – Constituency Sikh population.

• % No Religion – cen_rel_no religion – Constituents identifying as non-religious.

• % No Qualifications – cen_qual_none – Constituents with no formal qualifications.

• % Graduates – cen_qual_grad – Constituents with degree-level education.

• % Some Disability – cen_disab_some – Constituents reporting a form of disability.

✝️ Why are Catholics separate from Christians?

Don’t worry, I’m not suggesting we bring back the Test Acts. The logic here is that more granular data is better.

When swearing in, there are versions of the Bible specific to Catholics — typically the New Jerusalem Bible or the Douay–Rheims Bible — whereas if someone just asks for “the Bible”, they are given the King James Version and could be from any Christian denomination.

It would be a shame to lose that detail, so I provide the option to break out Catholic MPs separately.

📚 Where can I find more information about swearing in and the parliamentary oath?

The Parliament website has a great guide:

👉 https://www.parliament.uk/about/how/elections-and-voting/swearingin/

👤 Who created this dashboard?

This dashboard was created by Dr David Jeffery, University of Liverpool.

Follow me on Twitter/X or Bluesky.

❓ Why did you create this dashboard?

I needed to know MPs’ religion, and the text MPs used to swear in seemed like a valid proxy. This information was held by Humanists UK and when I asked for it, they said no.

So I did what any time-starved academic would do: I collected the data myself, by hand, and decided to make it public.

Table showing the numbers and percentage of resident population (all ages) broken down into six faiths, plus no religion and any other religion. Data is taken from the Annual Population Survey (ONS).

The data covers: Christian, Buddhist, Hindu, Jewish, Muslim, Sikh, any other religion and no religion at all.

95% Confidence Intervals are shown.

Or alternatively, faith data from the 2011 Census is able to show numbers for each of the main religions.

Comprehensive socio-economic dataset for British Indian Ocean Territory including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

Mosaiced 100m resolution global datasets. The methodology used to estimate the annual subnational census-based figures can be found in LLoyd et al (https://www. tandfonline.com/doi/full/10.1080/20964471.2019.1625151). The mapping approach is Random Forest-based dasymetric redistribution. More info at: www.worldpop.org.