Sickness absence in the UK labour market: 2018

• An estimated 141.4 million working days were lost because of sickness or injury in the UK in 2018, the equivalent to 4.4 days per worker.

• The sickness absence rate was relatively flat between 2010 and 2018 and stood at 2.0% in 2018.

• The groups with the highest rates of sickness absence in 2018 were women, older workers, those with long-term health conditions, people working part-time, and those working in organisations with 500 or more employees.

• The groups with the greatest reduction in sickness absence rates between 1997 and 2018 are workers with long-term health conditions, workers aged 50 to 64 years, and those in the public sector.

• The four most common reasons for sickness absence in 2018 were minor illnesses (including coughs and colds), musculoskeletal problems (including back pain and neck and upper limb problems), “other” conditions (including accidents, poisonings and diabetes), and mental health conditions (including stress, depression and anxiety).

We estimate that 141.4 million working days were lost because of sickness or injury in the UK in 2018. This is equivalent to 4.4 days per worker.

The number of working days lost due because of sickness or injury generally declined through the 2000s. In 2017, this reached the lowest level since records began in 1997 , when 131.5 million working days were lost (equivalent to 4.1 days per worker). Despite the increase between 2017 and 2018, the total number of days lost remained relatively flat between 2010 and 2018.

Minor illnesses were the most common reason for sickness absence in 2018, accounting for 27.2% (38.5 million days) of the total days lost to sickness. This was followed by musculoskeletal problems, at 19.7% (27.8 million days). After “other” conditions, mental health conditions were the next most common reason, accounting for 12.4% (17.5 million days).

Although the sickness absence rate for women is higher, the four main reasons given for sickness absence (in terms of the percentage of its occurrence) are fairly consistent for both sexes in 2018:

• minor illnesses (36.5% for men; 33.3% for women)
• musculoskeletal problems (18.5% for men; 14.2% for women)
• other conditions (13.3% for men; 12.6% for women)
• mental health conditions (8.5% for men; 8.8% for women)

Demographics and geography

The sickness absence rates have been consistently lower for men than women since 1995, although rates for both sexes generally fell between 1995 and 2018. Women lost 2.5% of their working hours in 2018 as a result of sickness or injury, a fall of 1.3 percentage points since 1995. In contrast, men lost 1.6% of their working hours, which represents a fall of 1.0 percentage points since 1995. The rate has increased 0.1 percentage points on the year for both groups.

Sickness absence rates are higher among older workers than younger workers as they are more likely to develop health problems. The sickness absence rates for all age groups fell in 2018 compared with 1995. In 2018, the rate was highest for those aged 50 to 64 years, at 2.6%. This figure is equivalent to the lowest absence rates in 1995 (for those aged 16 to 24 years and 25 to 34 years).

Even though the employment rate of those aged 65 years and over has increased since 1995, the sickness absence rate has decreased and stood at 1.9% in 2018.

Workers living in Wales and Scotland had the highest sickness absence rates in 2018, at 2.4%. Northern Ireland had a sickness absence rate of 1.5%. In England, workers living in Yorkshire and The Humber had the highest rate, at 2.3%, while those in London had the lowest rate, at 1.4%. These figures can be largely explained by the differing age profiles and occupations for workers in different parts of the UK.

Health status

Workers who report having a long-term health condition (that is, those that last 12 months or more) have a higher sickness absence rate than those who do not report having such a condition. The sickness absence rate for those with a long-term health condition was 4.4% in 2018, compared with 1.1% for those without such a condition. The latter was the lowest rate since records began in 1997. However, the sickness absence rate for people who suffer from a long-term health condition increased by 0.5 percentage points in 2018 from the record low of 3.9% in 2017.

Workers with long-term health conditions have experienced a notable reduction in their sickness absence rate between 1997 and 2018. Since the series began, the rate has fallen by 2.6 percentage points, from 7.0% in 1997 to 4.4% in 2018.

Note: The long-term health condition is not necessarily the reason for the sickness absence experienced.

Employment type

Sickness absence rates for workers within the public and private sector stood at 2.7% and 1.8% respectively in 2018. The sickness absence rate for public sector employees has been consistently higher than the rate for private sector employees since 1995, although both sectors have seen an overall decrease.

When comparing the reasons given for sickness absence in the public and private sector, mental health conditions are given as the reason more frequently in the public sector. They accounted for 10.2% of absences in the public sector and 8.1% in the private sector in 2018. The gap between the public and private sector has narrowed from 7.7 percentage points in 2015 (14.9% and 7.2% respectively), when it was highest, to 2.1 percentage points in 2018 (10.2% and 8.1% respectively).

There are a number of factors to consider when examining the differences between the public and private sectors, including:

• there are differences in the types of jobs between the sectors, and some jobs have higher likelihoods of sickness than others
• workers in the private sector are more likely not to be paid sickness absence than those in the public sector
• the analysis only counts someone as sick if they work fewer hours than they are contracted for and would exclude someone who makes up lost hours at a later point in the week; individuals in smaller workforces, which are more prominent in the private sector, may be under more pressure to make up any lost hours, but no data is collected on hours made up following sick absence

In terms of workforce size, workers in large organisations employing 500 people or more report the highest rate of sickness absence. This stood at 2.5% in 2018 compared with a rate of 1.7% for workers in organisations that employ fewer than 25 people.

In terms of occupation, workers in caring, leisure and other service occupations have the highest sickness absence rate. This stood at 2.9% in 2018. In contrast, those working in managerial and senior roles (for example, chief executives and financial managers) have the lowest sickness absence rate, at 1.3%.

The sickness absence rate for part-time workers has been consistently higher than the rate for full-time workers. This can be explained in part by higher numbers of women working part-time, as they also tend to have higher rates of sickness absence. The sickness absence rates of both part-time and full-time workers declined between 1995 to 2018. The sickness absence rate for part-time workers in 2018 was 2.4% compared with 1.9% for full-time workers.

The sickness absence rate for part-time workers reached a record low of 2.4% in 2018, the lowest since 1995. This suggests that despite the overall rise in the sickness absence rate in 2018, this was not driven by part-time workers as their rate fell.

The likelihood of an individual being absent from work as a result of sickness or injury varies according to different factors. We have reported on each factor separately, but we have not considered the collinearity that may exist between factors. For example, the difference between part-time and full-time workers could be driven by the proportion of women in part-time jobs and not by the fact that someone works part-time.

Logistic regression is a statistical technique that can consider factors individually. It can be used to examine how each independent variable (whether factor or demographic) impacts on the dependent variable (that is, the likelihood of sickness absence) given that all other factors remain equal. This technique then calculates the likelihood of a worker in a particular group reporting sickness absence relative to a reference group (for example, the likelihood of women doing so relative to men).

From January 2018 to December 2018, the likelihood of reporting sickness absence (when controlling for different factors that may influence sickness) for different groups were:

• by sex, 39% higher for women relative to men
• by age, 41% lower for workers aged 16 to 24 years, 24% lower for workers aged 25 to 34 years and 21% lower for workers aged 35 to 49 years, all relative to those aged 50 years to State Pension age
• by sector, 8% higher for workers in the public sector relative to workers in the private sector
• by size of organisation, 40% higher for workers in organisations with 500 and over employees relative to workers in organisations with fewer than 25 employees
• by occupation group, 12% lower for managers and senior officials relative to those working in professional roles, but 52% higher for workers in the caring, leisure and other service occupations sector

Further results can be found in Table 20 of the dataset that accompanies this release.

The estimates included in this release have been produced using the Labour Force Survey (LFS) and Annual Population Survey (APS). They relate to people aged 16 years and over in employment and are for the whole of the UK. Estimates are available from 1995 onwards for most breakdowns. Estimates calculated using the LFS are based on annual averages across quarters for each calendar year: taking an average of the January to March, April to June, July to September and October to December datasets within a calendar year. Estimates calculated using the APS are based on the annual January to December datasets.

Definitions

Important information for interpreting these statistics:

• a working day is defined as 7 hours and 30 minutes
• the total number of days lost is presented in millions, unless otherwise stated
• the sickness absence rate is defined as the proportion of total hours lost as a result of sickness or injury to total hours worked (see the formula in the following)
• the sickness absence rate is presented as a percentage throughout these analyses
• the number of days lost per worker is defined as the proportion of days lost to number of persons in employment (see the formula in the following)

Important information on the definitions of reason for sickness absence used in these analyses:

• “musculoskeletal problems” includes back pain, neck and upper limb problems, and other musculoskeletal problems
• “other” includes the total number of days lost to accidents, poisonings, infectious diseases, skin disorders, diabetes and anything else not covered
• “mental health conditions” include stress, depression, anxiety and serious mental health problems
• “minor illnesses” includes coughs, colds, flu, sickness, nausea and diarrhoea
• “disability status” is defined as whether a person meets the legal definition of being disabled according to the Equality Act 2010

Formulae

Quality and Methodology Information reports

The Labour Force Survey (LFS) and Annual Population Survey (APS) Quality and Methodology Information (QMI) reports contain important information on:

• the strengths and limitations of the data and how it compares with released data
• the uses and users of the data
• how the output was created
• the quality of the output including the accuracy of the data

More information on the quality, methodology and history of the LFS can be found in the Labour Force Survey – user guidance.

Accuracy in estimates

Estimates of sickness absence at the UK level in 2018 were based on a sample size of approximately 1,070 averaged across the year. There is therefore a limit to how many breakdowns can be made of the data without significantly reducing quality or requiring an element of disclosure control.

The numbers quoted throughout this release are based on sample sizes of three or higher. Within the main tables, any estimate based on fewer than three people has been suppressed (denoted by an asterisk). In instances where secondary disclosure was present, the “Prefers not to say” category has also been suppressed. Any estimate based on a sample size of between 3 and 25 has been highlighted (with grey shading), to emphasise the potential quality limitation of the estimate. These have been applied as per Measuring and reporting reliability of Labour Force Survey and Annual Population Survey Estimates.