Sickness absence, self- and doctor-certified
06.02 - Working conditions, sickness absenteeism
The statistics are published quarterly and annually.
National, county, and municipality level.
260 - Division for Labour Market Statistics
Statistics Act §3-2 (administrative registers)
Statistics Act §2-2 (obligation to provide information)
Statistics Act §2-3 (compulsory fines)
Not relevant.
Not relevant.
The statistics are intended to shed light on sickness absence trends in the aggregate and distributed by industry, occupation, hours worked and various personal variables connected with those on sick leave. These are intended to form the basis for developing and evaluating measures aimed at sickness absence. Publication began in 2001 and replaced the partially abridged statistics that had covered the central government and municipal sectors and parts of the private sector
Major users of the statistics are the authorities, employers' and employees' organisations, individual companies and researchers.
Aims that have governed the planning of the statistics are:
1. The possibility for employers and funds-appropriating authorities to make reliable estimates of expenses.
2. The possibility for employers' and employees' organisations to evaluate the efficiency of various measures implemented to reduce sickness absence.
3. The possibility of identifying risk groups in order to implement preventive measures.
4. The possibility of comparison over time as the basis for research in the area.
Central statistics on sickness absence consist of two parts:
- self-certified sickness absence
- doctor-certified sickness absence
The population is all employees aged 16-69 residing in Norway and registered in the Employee Register as employed during the reference period. The population is limited to employees having a job relation scheduled to more than four hours a week and lasting more than six days. Self-employed are not included in the statistics.
Doctor-certified sickness absence
The Sick Leave Register and the Employee Register are the main sources of information for doctor-certified sickness absence. The Norwegian Labour and Welfare Administration (NAV) is responsible for both registers.
The Sick Leave Register is based on the local NAV offices registrations of medical certificates ("Sykmeldingsattest IA") as part of its sickness benefits routine. These registrations are to cover all doctor-certified absences due to a person's own illness.
The Employee register contains all employees between 16 and 69 having a job relation scheduled to more than four hours a week and lasting more than six days. The date for start and stop of the job relation and position percentage are the most important variables for the sickness statistics.
Different registers are used to add variables to the job relations found in the Employee register, e.g. education and industry.
Self-certified sickness absence
The statistics on self-certified sickness absence are based on data reported by a sample of establishments.
A random sample of nearly 10 000 establishment is drawn from The Central Register of Establishments and Enterprises. The establishments are stratified by industry and size, and are divided into five strata by number of employees in the establishment. This ensures a wide range of industries and sizes of establishment. Systematic sampling ensures a relatively wide range of geographic diversity.
All establishments in the same strata of industry and size have the same probability to be drawn. The probability to be drawn increases by size. None of the small establishments (four or less employees) are drawn, while all big establishments (more than about 150 employees) are included. This ensures that the survey covers about 36 per cent of all employees while only 5.5 per cent of all establishments are surveyed.
While the biggest establishments are always surveyed, most others participate for four years at a time. Parts of the sample are rotated once a year. If an establishment has a small probability of being drawn into the sample, and it has been in the sample recently, then this establishment will be removed from the sampling population for some time to decrease the response burden.
The questionnaires are sent out the last week of each quarter to the enterprises having establishment(s) in the sample. The personnel office of the enterprise fills in the questionnaire or forwards it to the personnel office of their establishment. The deadline for delivery is about four weeks after receiving the questionnaire. An establishment may contact the Division for Data collection at Statistics Norway if it is impossible to separate the sickness absence figures for the chosen establishment. In this case the enterprise may give figures for the enterprise as a whole.
Doctor-certified sickness absence
The Norwegian Labour and Welfare Administration performs a number of controls and corrections on the doctor's certificates especially related to overlapping/inconsistencies in the dates. Statistics Norway checks both the Sick Leave Register and Employee Register against the register of unemployed persons as well as persons in labour market schemes registered at the municipal employment offices. Each year the Norwegian Labour and Welfare Administration performs an "annual check" of the Employee Register. Employers who report manually are sent lists of all persons reported as actively employed by them.
Self-certified sickness absence
Absolute checks: verification controls in the last stage of the optical data registration to reveal obvious errors from the optical reading, misunderstandings or inaccuracy in the reporting. An example would be wrong totals compared to the partial figures.
Evaluation checks: these checks aim to reveal errors due to extreme values reported or due to incorrect number of employees reported. For this purpose a check variable is being used, sickness absence cases per 100 employees. Large establishments that report extreme values on this variable will be more closely examined. Data from whole enterprises will also be adjusted in proportion to the portion of employees the sampled establishments represent in the enterprise as a whole. Before the final estimation, we also check that the net samples in each industry and size strata are large enough. If the net samples are too small for some strata, they will be added to the "neighbouring" strata in the same industry.
In the statistics there are two measures of sickness absence:
Proportion of man-days lost: proportion of scheduled man-days lost during the statistics period due to absences caused by an employee's own illness
Proportion of persons on sick leave: persons on sick leave at a given reference date at the end of the statistics period.
The emphasis is on the proportion of man-days lost due to own sickness, which is also the measure referred to as the sickness absence rate. The formulas are presented in connection to the definitions of concepts and variables in Section 4.
The sickness absence does do not cover absence due to a child's illness or family and maternity leave.
Doctor-certified absence
Persons with a so-called active self-certificate are included in the statistics as ordinary doctor-certified sickness absence.
Self-certified absence
Sheltered workshops and establishments in the following industries are not a part of the sample: Animal husbandry service activities (except veterinary activities), extraction of crude petroleum and natural gas, water transport, private households with employed persons and extra territorial organizations. In the estimation, employees from these groups are represented by employees from other industries.
Estimation at national level
A model-based ratio estimator is used to inflate sample data of self-certified sickness absence to population level. The ratio model corresponds to a linear regression model without a constant term and with the disturbance term that are proportional with the number of male (female) employees. Auxiliary variables about total number of male (female) employees in each establishment in the population are used. The figures are taken from the Register of Employees. The dependent variable is the number of self-certified sickness absence man-days for male (female). A weighted least square method is used to fit the regression models. The population totals for each group are predicted by using the groups model estimates and the population sums of the number of employees in each group.
Because the smallest establishments are not sampled, a "Cut-off"-estimator is being used for these strata. This means that the number of male (female) employees in the population of the smallest strata is being multiplied by the ratios for the second smallest strata. This method is being done separately for each industry strata. This method assumes that the ratios in the strata with the smallest establishments are similar to the corresponding ratios in the strata with the second smallest establishments. If the ratios are very different we introduce a bias.
Estimation at county level and institutional sector level
Self-certified sickness absence by county of work and institutional sector is estimated with a different method than the national level estimates, because the sample is not stratified on these variables. For the figures by county and sector, we use model based ratio estimators for different groups.
The estimations of sickness absence by county are done separately for two industry groups, sex and the 19 counties of work. One industry group consists of agriculture, forestry and fishing, and industrial activities; the other group is service activities.
In the estimation of figures by institutional sector, each of the tree sectors 1) central government, 2) counties and municipalities, and 3) private sector and government enterprises are estimated separately for male and for female for groups of industry. Depending on what the sample sizes allow, different groups of industry are used for each of the tree sectors.
The different model-based ratio estimators can add up to figures of totals that are a little different from the official national totals from the design-based ratio estimator. Due to that, we use the county and sector divided figures to make percentage distributions, which the official national totals are broken down with, so that the totals also are right.
Not relevant.
Sickness absence
Absence from work due to one's own illness.
Sickness absence rate
The sickness absence rate measures man-days lost due to own sickness as a percentage of contractual man-days.
Sickness absence rate = {sickness absence man-days*100} / contractual man-days
Case of sickness absence: a case of sickness absence is defined by a common personal identification number, a common start date for the medical certificate date, and a common organisation number for the company. A case of sickness absence will consist of the initial medical certificate and also medical certificates being extensions of the initial one. If an employee on sick leave has more than one job relation, we assume that the person has sick leave from all job relations. For example, a person having two job relations being active during two medical certificates, and these medical certificates are separated by some time where the person is not on sick leave, the person will have four cases of sickness absence.
Working day: a day during which one normally is supposed to be at work.
Contractual working hours: all the job relations in the population are divided into six groups formed by sex and the interval values of scheduled working hours from the Employee Register (4-19 hours per week, 20-29 hours per week, and 30 hours per week and above). For each job relation in a group, the scheduled working hours is estimated as the average scheduled working hours in this group according to the Labour Force Survey (LFS).
Position percentage: position percentage is set equal to contractual working hours, divided by 37.5. Hence, we assume 37.5 to be working hours of a full-time position, which is a simplification.
Degree of disability: whether the person in question is on full or partial sick leave, and to what degree, is indicated by the degree of disability. The degree of disability is between 20 percent and 100 percent, where 100 means full sick leave. If a sickness absence case consists of more than one medical certificate, we use the average of the degrees of disability for the medical certificates in question.
Man-day: one man-day corresponds to the length in time of one working day for a person in a full-time position (100% position).
Contractual days og work: the number of working days that a person has agreed on with his or her employer to work in a period. We define possible working days as the number of calendar days that the employee relationship is lasting minus weekends and general holidays. For many employees such a generalisation will not be correct. At the aggregate level, and when looking at a given period, we believe nonetheless that this approach works reasonably well. For reasons of quality, in the statistics we established a ceiling for how many employee relationships a person may have simultaneously.
Contractual man-days in a period = {contractual working days in the period} x {position percentage} x {vacation correction factor}
Sickness absence day: a day during which one normally is supposed to be at work but is not because of one's own illness. The number of sickness absence days in a case of sickness absence is equal to the number of calendar days within the statistics period to which the case of sickness absence pertains minus any weekends and holidays.
Sickness absence man-day: a sickness absence man-day corresponds to one sickness absence day for a person in a full-time position (100%) and who is on full sick leave (100% degree of disability).
Sickness absence man-days in the period = {sickness absence days in the period} x {position percentage} x {degree of disability}.
Counting employee relationship: in some instances, it is necessary to select one employee relationship as counting for persons who are registered with more than one employee relationships simultaneously at a given reference point or in a given period. For instance we have to do this if we wish to divide employees by industry and municipality of the workplace.
The counting employee relationship is selected according to the following criteria, which are the same criteria used by Statistics Norway in its Register statistics of employees:
The employee relationship having the longest contracted working hours per week is the counting employee relationship of a person. In the case of equal working hours, the one with the latest start date is chosen.
Age: age is defined as the age at the end of the statistics period.
Duration: Duration is measured among ongoing sickness absences at the reference point, which causes the duration to be shorter than if we were looking at terminated sickness absences.
Industry is coded according to the Standard Industrial Classification, SIC2007.
Education is coded according to the Norwegian Standard Classification of Education, NUS (NOS C 751).
Occupation is coded according to the Norwegian Standard Classification of Occupations (NOS C 521)
Sector: The classification is based on institutional sector codes from the Central Coordinating Register for Legal Entities. The following classification is used in the tables:
Central government administration
County administration
Municipal administration
Private sector (incl. public enterprises)
Collection and processing errors (self-certified sickness absence)
Errors may occur in many parts of the data collection process. They may for instance occur when filling in the questionnaire, registration of the data or through incorrect optical reading or revision of data. Different interpretations of the questionnaires' notions may also cause faulty data. Many faults are however revealed and corrected by means of an elaborate process of checks and revision. The questionnaire was revised the 4th quarter 2001. Before the revision we asked for the total sickness absence of 1 - 3 days (both self- and doctor-certified) while we after the revision ask for all the self-certified sickness absence only (independent of duration). This may cause faults if some establishments do not change their reporting routines.
Sampling errors (self-certified sickness absence)
All surveys are bound to have a certain level of sample uncertainty. The uncertainty generally increases with a declining numbers of observations used in the survey. We get a measure of the variance by calculating the standard deviation in per cent of the estimate. The calculation based on the figures from the 4th quarter 2004 reveals a relative standard deviation of 0.8 per cent in the total number of man-days lost because of sickness absence. The relative standard deviation for each of the 12 groups of industry used in our survey varies and has an average of 3.2 per cent.
The population of establishments constantly changes because of new establishments, bankruptcies, fusions and changes in kind of industry (SIC 94). The original sample of 1997 was not changed before the 1st quarter 2002. If new establishments within the same group of industry and size during that period have other averages of sickness absence per employee than the 1997 population, a bias in the estimates will arise. From 2002 the sample is upgraded annually. Since the smallest establishments are held outside the sample, particular uncertainty is attached to the calculated numbers within this group.
In all voluntary questionnaires there will be a certain degree of non-response. With the new sample from the 1st quarter 2002 we reached a 65 per cent response rate after reminders. At the start of the survey we had almost the same level of response, but it decreased gradually to 55 per cent towards 2001. This may cause biased estimates, even though the method of estimation is reliable in relation to changes in the structure of industry group and size. An analysis of the non-response establishments revealed the same level of doctor-certified sickness absence as in the establishments that responded.
Because of the low response rate, the questionnaire became a mandatory survey from the 2nd quarter of 2003. This effort raised the response rate to a much higher level, at about 90 percent in the following quarters.
Self-Certified sickness absence
The number of employed men and women in the establishments found in the Register of employees is used as factor of estimation. Some establishments report the numbers of sickness absence based on a larger or smaller group of employees than recorded in the register. This might cause a disproportion between the number of sickness absence reported and the corresponding number of employees. This phenomenon represents a potential source of bias, but occurrences of larger disproportion are revealed and corrected by means of our quality checks. A delay in the reporting of employees to the Register of employees causes some bias in the number of days used in the denominator of our calculated per cent of sickness absence.
Doctor-certified sickness absence
A good deal of sick leave is registered that cannot be linked to employee relationships. Compared with all sick leaves, this corresponds to approximately seven percent. Analyses indicate that most by far are sick leaves that do not pertain to employee relationships subject to notification, and they are therefore kept out of the data basis. However, keeping them all outside gives us a certain level of under coverage in the statistics.
The transitions from sickness absence days to man-days and from possible working days to possible man-days go via the calculated variable "position percentage". On the person level we only have information on whether the employment is full-time or short or long part-time. By comparing 37.5 hours per week with what part-time or short or long part-time employees divided by sex responded in the LFS that they had as fixed/contracted working hours per week, we get the "position percentages". This generalisation produces errors for many individuals, but produces fewer errors on the aggregate level.
Not relevant.
In the autumn of 2001 the authorities and the organisations of employers and employees signed an agreement aiming at reducing the level of sickness absence. One of the means was to offer the employees an expanded period of self-certified sickness absence beyond three days combined with dialogues with the employer. This effort might turn some of the sickness absence from the doctor- to the self - certified kind. Due to this - the survey has to capture a greater part of the sickness absence than earlier, and our questionnaire for the 4th quarter of 2001 was changed accordingly. This change implies more questionnaire-based reporting from the establishments at the expense of register data based on the doctors' reports.
New industry classification
A new industry classification (SIC2007) was introduced from the publication of the first quarter of 2009. Compared with earlier published figures classified by the previous industry standard (SIC2002) there will be a break in the time series. Here is an article presenting general information about the new Norwegian industry classification.
It is not a one to one link between all the detailed codes of SIC2002 and SIC2007. However 1st quarter 2009 all active establishments in the Central Register of Establishments and Enterprises are coded both after SIC2002 and SIC2007. This information, linked to the Sick Leave Register and the Employee Register, is utilized to construct conversion matrixes. These conversion matrixes are used to calculate aggregated SIC2007 divided historical figures from aggregated SIC2002 divided figures.
For the variable doctor-certified sickness absence man-days and for contractual man-days the conversion calculation are made separately for males and females in 4 age groups (16 – 24, 25 – 39, 40 – 54 and 55 – 69 years) for the most detailed industry code as possible. For the conversion of the variable doctor-certified sickness absence man-days the conversion percentage distribution are calculated from doctor-certified sickness absence man-days 1st quarter 2009. For the conversion of the variable contractual man-days the conversion percentage distribution are calculated from contractual man-days 1st quarter 2009.
Self-certified sickness absence man-days figures are converted from SIC2002 to SIC2007 within the industry stratums used in the sampline and estimation before and after the change. This is done separately for males and females based on conversion percentage distributions made from the variable contractual man-days 1st quarter 2009. Industry conversion of the denominator used in the self-certified sickness absence rate are done separately for males and females within the industry stratums in the same way as the self-certified sickness absence man-days figures are converted.
Gender and SIC2007 divided figures are converted quarterly for the period 2000 – 2007 under the assumption that the different detailed conversion percentage distributions are constant and equal to the once in 1st quarter 2009.
Many different bodies produce or have produced sickness absence statistics that each covers various sectors of business and industry. The Confederation of Norwegian Business and Industry (NHO) compiled earlier sickness absence statistics covering blue-collar and white-collar workers in mining, manufacturing and general contracting activities. Now NHO has stopped their data collection and receives data from Statistics Norway in stead.
The Norwegian Association of Local and Regional Authorities (KS) compiles sickness absence statistics for permanent employees in nearly all municipalities and county authorities as well as for employees of companies that are associate members of KS. The Ministry of Labour and Government Administration compiles sickness absence statistics for all employees for whom the central government is the employer. A more detailed comparison of the various measurement figures for sickness absence has been made in the report from the Central Statistics on Sickness Absence pilot project. Other absence statistics are also available. For the retail and financial intermediation industries, the Federation of Norwegian Commercial and Service Enterprises and the Norwegian Financial Services Association (FNH) compile statistics respectively.
The Labour Force Survey, which Statistics Norway publishes quarterly, also contains some information about sickness absence. The target figure used in this survey is the number of employees who have been absent during the whole registration week in per cent of employees in total. The figure is given by gender and group of industry. This target-figure is less comparable with those in the other Norwegian statistics. The Central statistics of sickness absence for instance, include persons on partial sick leave and also cases of sickness absence shorter than one week. In addition these statistics also take into account both the working time and the duration of the sickness absence when the portion of sickness absence is calculated.
http://www.ssb.no/sykefratot_en/ .
More detailed statistics on sickness absence certified by a doctor, produced in cooperation with the Norwegian Labour and Welfare Administration, are to be found at:
http://www.ssb.no/sykefra_en/ .
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