In August 2025, approximately 14 percent of workers in Great Britain worked from home exclusively, with a further 22 percent working from home and travelling to work, while 41 percent only travelled to work. During this time period, the share of people only travelling to work was highest in March 2022, at 60 percent of respondents, with the peak for only working from home occurring in June 2020. In general, hybrid working has become steadily more popular than fully remote working, with the highest share of people hybrid working in November 2023, when 31 percent of people advising they were hybrid working. What type of workers are most likely to work from home? In 2020, over half of people working in the agriculture sector mainly worked from home, which was the highest share among UK industry sectors at that time. While this industry was one of the most accessible for mainly working at home, just six percent of workers in the accommodation and food services sector mainly did this, the lowest of any sector. In the same year, men were slightly more likely to mainly work from home than women, while the most common age group for mainly working from home was those aged 75 and over, at 45.4 percent. Over a long-term period, the share of people primarily home working has grown from 11.1 percent in 1998, to approximately 17.4 percent in 2020. Growth of Flexible working in the UK According to a survey conducted in 2023, working from home either on a regular, or ad hoc basis was the most common type of flexible working arrangement offered by organizations in the UK, at 62 percent of respondents. Other popular flexible working arrangements include the ability to work flexible hours, work part-time, or take career breaks. Since 2013, for example, the number of employees in the UK that can work flextime has increased from 3.2 million, to around 4.2 million by 2024. When asked why flexible work was important to them, most UK workers said that it supported a better work-life balance, with 41 percent expressing that it made their commute to work more manageable.

Experimental estimates from the Annual Population Survey for homeworking in the UK, including breakdowns by sex, full-time or part-time, ethnicity, occupation, industry, qualifications, hours worked, pay and sickness absence among others. Includes regression outputs on the different outcomes for homeworkers.

The percentage of people who mainly work from home in the United Kingdom reached **** percent in 2020, compared with **** percent in the previous year. Since 1998 the number of people that regularly work from home in the UK has increased by **** million after the number of remote workers reached *** million in 2020.

These figures are experimental estimates of online job adverts provided by Adzuna, an online job search engine. The number of job adverts over time is an indicator of the demand for labour. To identify these adverts we have applied text-matching to find job adverts which contain key phrases associated with homeworking such as “remote working”, “work from home”, “home-based” and “telework”. The data do not separately identify job adverts which exclusively offer homeworking from those which offer flexible homeworking, such as one day a week from home.

Data on working patterns and location of work of adults in Great Britain, including costs and benefits of homeworking and future expectations. Survey data from the Opinions and Lifestyle Survey (OPN).

In 2020, *** thousand people working in the professional, scientific, and technical industries in the United Kingdom worked mainly from home, the highest number of any sector. The industry sector with the highest percentage of homeworkers was agriculture, forestry, and fishing, with over half of that industry's workforce working from home.

Analysis of how working from home has affected individuals’ spending and how this differs by characteristics, Great Britain.

Data on working population's location of work patterns, well-being and attitudes to future working from home plans broken down by age, sex, income and region. Data are based on the COVID-19 module of the Opinions and Lifestyle Survey, collected between 21 April and 16 May 2021.

In 2021, approximately 37 percent of workers in Great Britain wished to work from home some of the time after the Coronavirus pandemic is over, with one in five wanted to work from home all the time. Despite this, 37 percent of British workers advised they never want to work from home, with seven percent not sure.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by method used to travel to work (2001 specification) and by distance travelled to work. The estimates are as at Census Day, 21 March 2021.

_As Census 2021 was during a unique period of rapid change, take care when using this data for planning purposes. Due to methodological changes the ‘mainly work at or from home: any workplace type’ category has a population of zero. Please use the transport_to_workplace_12a classification instead. Read more about this quality notice._

As Census 2021 was during a unique period of rapid change, take care when using this data for planning purposes. Read more about this quality notice.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Lower tier local authorities

Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.

Coverage

Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Method used to travel to workplace

A person's place of work and their method of travel to work. This is the 2001 method of producing travel to work variables.

"Work mainly from home" applies to someone who indicated their place of work as their home address and travelled to work by driving a car or van, for example visiting clients.

Distance travelled to work

The distance, in kilometres, between a person's residential postcode and their workplace postcode measured in a straight line. A distance travelled of 0.1km indicates that the workplace postcode is the same as the residential postcode. Distances over 1200km are treated as invalid, and an imputed or estimated value is added.

“Work mainly at or from home” is made up of those that ticked either the "Mainly work at or from home" box for the address of workplace question, or the “Work mainly at or from home” box for the method of travel to work question.

Distance is calculated as the straight line distance between the enumeration postcode and the workplace postcode.

Combine this variable with “Economic activity status” to identify those in employment at the time of the census.

Working from home has seen a rise in prevalence, particularly in the wake of the covid-19 pandemic. Although it is widely believed that wfh enables employees to better combine paid work with domestic duties, potentially enhancing work-life balance, emerging evidence suggests that it may also hinder career advancement and adversely affect mental health, with notable impacts on women. We employ longitudinal data from three British Cohort Studies, collected one year into the covid-19 pandemic, to investigate the characteristics of those who report working from home and the relationship with gender disparities in hourly wages, mental health, and well-being. Using longitudinal data also allows us to control for cohort members’ labour market situation prior to the pandemic, thereby helping to isolate the pandemic’s effects. Our findings indicate that individuals who work from home typically receive higher wages compared to those who work from employers’ premises, but the gender wage gap is most pronounced among those who work from home. Furthermore, consistent with the flexibility paradox, our analysis reveals that women who work from home - particularly those who work hybrid - experience the most detrimental mental health outcomes.

People that worked from home in the United Kingdom in September 2020 started their working day slightly later than their counterparts that worked away from home according to a survey on how workers spent their workdays, and using 1200hrs (midday) as a baseline. Due to starting later in the day, people working from home were also working later in the day than people working in other locations. The peak for working at home was 1100hrs, at *****, while for working away from home the peak time was 1130hrs, at *****.

An analysis of home working across the UK. Who these home workers are, where they are found, what they do and how this has changed over time. Some comparison at Local Authority and regional level and across the European Union.

Source agency: Office for National Statistics

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: Characteristics of Home Workers in the UK

Background: The Coronavirus disease (COVID-19) has emphasised the critical need to investigate the mental well-being of healthcare professionals working during the pandemic. It has been highlighted that healthcare professionals display a higher prevalence of mental distress and research has largely focused on frontline professions. Social restrictions were enforced during the pandemic that caused rapid changes to the working environment (both clinically and remotely). The present study aims to examine the mental health of a variety of healthcare professionals, comparing overall mental wellbeing in both frontline and non-frontline professionals and the effect of the working environment on mental health outcomes.

Method: A cross-sectional mixed methods design, conducted through an online questionnaire. Demographic information was optional but participants were required to complete: (a) Patient Health Questionnaire, (b) Generalised Anxiety Disorder, (c) Perceived Stress Scale, and (d) Copenhagen Burnout Inventory. The questionnaire included one open-ended question regarding challenges experienced working during the pandemic.

Procedure:
Upon ethical approval the online questionnaire was advertised for six weeks from 1st May 2021 to 12th June 2021 to maximise the total number of respondents able to partake. The survey was hosted on the survey platform “Online Surveys”. It was not possible to determine a response rate because identifying how many people had received the link was unattainable information. The advert for the study was placed on social media platforms (WhatsApp, Instagram, Facebook and Twitter) and shared through emails.

Participants were recruited through the researchers’ existing professional networks and they shared the advertisement and link to questionnaire with colleagues. The information page explained the purpose of the study, eligibility criteria, procedure, costs and benefits of partaking and data storage. Participants were made aware on the information page that completing and submitting the questionnaire indicated their informed consent. It was not possible to submit complete questionnaires unless blank responses were optional demographic data. Participants were informed that completed questionnaires could not be withdrawn due to anonymity.

The questionnaire consisted of four sections: demographic data, mental health information and the four psychometric tools, PHQ-9, GAD-7, PSS-10 and CBI. Due to the sensitive nature of this research, only the psychometric measures required an answer for each question, thus all demographic information was optional to encourage participant contentment. Once participants had completed the questionnaire and submitted, they were automatically taken to a debrief page. This revealed the hypothesis of the questionnaire and rationalised why it was necessary to conceal this prior to completion. Participants were signposted to mental health charities and a self-referral form for psychological support. Participants could contact the researcher via email to express an interest in the results. It was explained that findings would be analysed using descriptive statistics to investigate any correlations or patterns in the responses. Data collected was stored electronically, on a password protected laptop. It will be kept for three years and then destroyed.

Instruments: PHQ-9, GAD-7, PSS-10 and CBI.

Other questions included:

Thank you for considering taking part in the questionnaire! Please remember by completing and submitting the questionnaire you are giving your informed consent to participate in this study.

Demographic:

Gender: please select one of the following:

Male Female Non-binary Prefer not to answer

Age: what is your age?

Open question: Prefer not to answer

What is your current region in the UK?

South West, East of England, South East, East Midlands, Yorkshire and the Humber, North West, West Midlands, North East, London, Scotland, Wales, Northern Ireland Prefer not to answer

Ethnicity: please select one of the following:

White English, Welsh, Scottish, Northern Irish or British Irish Gypsy or Irish Traveller Any other White background Mixed or Multiple ethnic groups White and Black Caribbean White and Black African White and Asian Any other Mixed or Multiple ethnic background Asian or Asian British Indian Pakistani Bangladeshi Chinese Any other Asian background Black, African, Caribbean or Black British African Caribbean Any other Black, African or Caribbean background Other ethnic group Arab Option for other please specify Prefer not to answer

Employment/environment:

What was your employment status in 2020 prior to COVID-19 pandemic?

Please select the option that best applies. Employed Self-employed Unpaid work (homemaker/carer) Out of work and looking for work Out of work but not currently looking for work Student Volunteer Retired Unable to work Prefer not to answer Option for other please specify

What is your current employment status?

Please tick the option that best applies. Employed Self-employed Unpaid work (homemaker/carer) Out of work and looking for work Out of work but not currently looking for work Student Volunteer Retired Unable to work Prefer not to answer Option for other please specify

What is your healthcare profession/helping profession?

Please state your job title. Open question

How often did you work from home before the COVID-19 pandemic?

Not at all, rarely, some, most, everyday Option for N/A

How often did you work from home during the first UK national lockdown for COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often did you work from home during the second UK national lockdown during COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often have you worked from home during the third UK national lockdown during COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often are you currently working from home during the COVID-19 pandemic?

Not at all, rarely, some, most, everyday Option for N/A

Mental health:

How would you describe your mental health leading up to the COVID-19 pandemic?

Excellent, Very good, Good, Fair, Poor

How would you describe your mental health during the COVID-19 pandemic?

Excellent, Very good, Good, Fair, Poor

What have been the main challenges working as a healthcare professional/helping profession during COVID-19 pandemic? Open question

Data analysis: Firstly, any missing data was checked by the researcher and noted in the results section. The data was then analysed using a statistical software package called Statistical Package for the Social Sciences version 28 (SPSS-28). Descriptive statistics were collected to organise and summarise the data, and a correlation coefficient describes the strength and direction of the relationship between two variables. Inferential statistics were used to determine whether the effects were statistically significant. Responses to the open-ended question were coded and examined for key themes and patterns utilising the Braun and Clarke (2006) thematic analysis approach.

Ethical considerations: The study was approved by the Health Science, Engineering and Technology Ethical Committee with Delegated Authority at the University of Hertfordshire.

The potential benefits and risks of partaking in the research were contemplated and presented on the information page to promote informed consent. Precautions to prevent harm to participants included eligibility criteria, excluding those under eighteen years older or experiencing mental health distress. As the questionnaire was based around employment and the working environment, another exclusion involved experiencing a recent job change which caused upset.

An anonymous questionnaire and optional input of demographic data fostered the participants’ right to autonomy, privacy and respect. Specific employment and organisation or company information were not collected to protect confidentiality. Although participants were initially deceived regarding the hypotheses, they were provided with accurate information about the purpose of the study. Deceit was appropriate to collect unbiased information and participants were subsequently informed of the hypotheses on the debrief page.

As the UK went into the first lockdown of the COVID-19 pandemic, the team behind the biggest social survey in the UK, Understanding Society (UKHLS), developed a way to capture these experiences. From April 2020, participants from this Study were asked to take part in the Understanding Society COVID-19 survey, henceforth referred to as the COVID-19 survey or the COVID-19 study.The COVID-19 survey regularly asked people about their situation and experiences. The resulting data gives a unique insight into the impact of the pandemic on individuals, families, and communities. The COVID-19 Teaching Dataset contains data from the main COVID-19 survey in a simplified form. It covers topics such as Socio-demographics Whether working at home and home-schooling COVID symptoms Health and well-being Social contact and neighbourhood cohesion Volunteering The resource contains two data files: Cross-sectional: contains data collected in Wave 4 in July 2020 (with some additional variables from other waves); Longitudinal: Contains mainly data from Waves 1, 4 and 9 with key variables measured at three time points. Key features of the dataset Missing values: in the web survey, participants clicking "Next" but not answering a question were given further options such as "Don't know" and "Prefer not to say". Missing observations like these are recorded using negative values such as -1 for "Don't know". In many instances, users of the data will need to set these values as missing. The User Guide includes Stata and SPSS code for setting negative missing values to system missing.

The Longitudinal file is a balanced panel and is in wide format. A balanced panel means it only includes participants that took part in every wave. In wide format, each participant has one row of information, and each measurement of the same variable is a different variable.

Weights: both the cross-sectional and longitudinal files include survey weights that adjust the sample to represent the UK adult population. The cross-sectional weight (betaindin_xw) adjusts for unequal selection probabilities in the sample design and for non-response. The longitudinal weight (ci_betaindin_lw) adjusts for the sample design and also for the fact that not all those invited to participate in the survey, do participate in all waves.

Both the cross-sectional and longitudinal datasets include the survey design variables (psu and strata). A full list of variables in both files can be found in the User Guide appendix.Who is in the sample?All adults (16 years old and over as of April 2020), in households who had participated in at least one of the last two waves of the main study Understanding Society, were invited to participate in this survey. From the September 2020 (Wave 5) survey onwards, only sample members who had completed at least one partial interview in any of the first four web surveys were invited to participate. From the November 2020 (Wave 6) survey onwards, those who had only completed the initial survey in April 2020 and none since, were no longer invited to participate The User guide accompanying the data adds to the information here and includes a full variable list with details of measurement levels and links to the relevant questionnaire.

Socio-demographics; Whether working at home and home-schooling; COVID symptoms; Health and well-being; Social contact and neighbourhood cohesion; Volunteering.

National and regional breakdowns of night-time workers by industry groupings, gender, working patterns, age groups, time of day usually worked, place of birth (UK or outside the UK), and whether or not they work from home.

Analysis of the relationships between COVID-19 restrictions, homeworking and spending, comparison of these variables: percentage of homeworkers, Google Workplace Mobility Index, Oxford Stringency Index and CHAPS spending.