Comparisons of self-reported and register data on sickness absence among public employees in Sweden.

Abstract

Self-reported assessments of sickness absence are often performed in epidemiological studies. The objective of this study was to compare the number of sick-leave days according to self-reported data over 12 months with data from the employer's register for the same period. An additional aim was to ascertain whether the self-reported information and the recorded data would show equivalent associations with self-reported general health.
The study was based on a cohort of 4869 municipal employees in Sweden, about 80% women, who answered a questionnaire in 2001-2. The responses provided by the employees included information on number of sick-leave days and self-rated health. Data on sick-leave days, occupation and age were derived from the employers' computerised registers. The questionnaire information on sick-leave days was compared with the corresponding information retrieved from the employer register by means of calculating sensitivity and specificity, using the employers' data as the "gold standard".
The annual number of sick-leave days was lower according to the self-reported information than to the register data. For women the agreement between the two sickness absence measures for no sick-leave days, 1-7 days and >/=28 days were 74%, 72% and 67%, respectively. The sensitivity of questionnaire versus register information regarding any self-reported sick-leave day was 91% and the specificity was 74%. Sensitivity and specificity for sickness absence >/=28 days were 67% and 98%, respectively. The results for men were similar to those for women. Self-reported and recorded sickness absence were both associated with self-rated health. The odds ratios were 7.27 and 8.25, for subjects with >/=28 recorded and self-reported number of sick-leave days respectively, compared to subjects with no sickness absence.
Good agreement was found between self-reported and register information on sickness absence. Self-reported data on sickness absence may be useful in common epidemiological applications.

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doi:10.1136/oem.2006.031427
2008;65;61-67; originally published online 17 Aug 2007; Occup. Environ. Med.

M Voss, S Stark, L Alfredsson, E Vingård and M Josephson


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Comparisons of self-reported and register data on
sickness absence among public employees in
Sweden
M Voss,1,2S Stark,2L Alfredsson,3,4E Vinga ˚rd,1,2M Josephson2
1Section of Personal Injury
Prevention, Department of
Clinical Neuroscience, Karolinska
Institutet, Stockholm, Sweden;
2Occupational and
Environmental Medicine,
Department of Medical
Sciences, Uppsala University,
Uppsala, Sweden;3Institute of
Environmental Medicine,
Karolinska Institutet, Stockholm,
Sweden;4Centre of Public
Health, Stockholm County
Council, Stockholm, Sweden
Correspondence to:
Dr M Voss, Section of Personal
Injury Prevention, Department of
Clinical Neuroscience, Karolinska
Institutet, SE-171 77 Stockholm,
Sweden; margaretha.voss@
ki.se
Accepted 11 July 2007
Published Online First
17 August 2007
ABSTRACT
Aim: Self-reported assessments of sickness absence are
often performed in epidemiological studies. The objective
of this study was to compare the number of sick-leave
days according to self-reported data over 12 months with
data from the employer’s register for the same period. An
additional aim was to ascertain whether the self-reported
information and the recorded data would show equivalent
associations with self-reported general health.
Methods: The study was based on a cohort of 4869
municipal employees in Sweden, about 80% women, who
answered a questionnaire in 2001–2. The responses
provided by the employees included information on
number of sick-leave days and self-rated health. Data on
sick-leave days, occupation and age were derived from
the employers’ computerised registers. The questionnaire
information on sick-leave days was compared with the
corresponding information retrieved from the employer
register by means of calculating sensitivity and specificity,
using the employers’ data as the ‘‘gold standard’’.
Results: The annual number of sick-leave days was lower
according to the self-reported information than to the
register data. For women the agreement between the
two sickness absence measures for no sick-leave days,
1–7 days and >28 days were 74%, 72% and 67%,
respectively. The sensitivity of questionnaire versus
register information regarding any self-reported sick-leave
day was 91% and the specificity was 74%. Sensitivity and
specificity for sickness absence >28 days were 67% and
98%, respectively. The results for men were similar to
those for women. Self-reported and recorded sickness
absence were both associated with self-rated health. The
odds ratios were 7.27 and 8.25, for subjects with >28
recorded and self-reported number of sick-leave days
respectively, compared to subjects with no sickness
absence.
Conclusions: Good agreement was found between self-
reported and register information on sickness absence.
Self-reported data on sickness absence may be useful in
common epidemiological applications.
There are an increasing number of studies using
self-reported sickness absence as an outcome. The
value of such retrospective self-reported informa-
tion depends on the quality of the data. Poor
quality may lead to biased results of the studied
associations due to differential or non-differential
misclassification. Studies of the quality of different
types of sickness absence data are, however, scarce
and there is a need for more knowledge on this
matter.1
Sickness absence has a multifactorial background
that comprises risk factors at different structural
levels (for example, societal, demographic, work-
related and individual factors),2and it has been
described as a global measure of health in a
working population.3 4
employer-registered sickness absence have been
found to be associated with self-reported general
health5–7and mortality,4 5 8and poor self-reported
health is also a predictor of subsequent mortal-
ity.4 9 10
Earlier studies that have validated self-reported
information of sickness absence with register data
have mostly been based on small populations,
between 150 and 600 employees within different
occupations (coal miners, office and production
work).11–15Several of these studies have focused on
sickness absence due to back pain.11–13One recently
published larger study with focus on sickness
absence irrespective of diagnoses was based on
the Whitehall cohort of about 8000 civil servants in
London.7
In some investigations, the sensitivity of apply-
ing self-reported sick-leave data to detect the
occurrence of sickness absence, using register
information as the standard, has varied between
55% and 88% during follow-up periods of one
month to four years.11–13 15These studies reported
specificities ranging from 83% to 98%. In a Dutch
study of five recall periods (2 and 4 weeks, and 2, 6
and 12 months), the cumulative proportions dis-
playing a maximum difference of two days
between self-reported
absence were 95%, 95%, 87%, 57% and 51%,
respectively—that is, a decrease with increased
length of the recall periods.14Moreover, the larger
Whitehall study compared number of self-reported
sick-leave days over the last 12 months with data
from the employers’ registers, and a maximum
discrepancy of two sick-leave days (adjusted for
employment grade and number of sickness absence
days) was found for 60% of the women and 73% of
the men.7Analyses also revealed that both self-
reported and recorded sickness absence showed a
similar association with self-reported health.
The target group of the present study is employ-
ees in the public sector in Sweden, about one
million people, of whom about 80% are women.
Almost half of the female work force is employed
in this female-dominated public sector and about
50% are over 45 years of age. This heterogeneous
group of various types of occupations involves
both physically and mentally demanding work
mainly within the areas of health care, social
welfare, and education—so-called ‘‘human service’’
occupations. Swedish national data on sickness
Both self-reported and
andrecordedsickness
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absence show that public sector employees, specifically those
working in the municipalities, are over-represented among those
on sick leave for 60 days or more per annum.16The intention
with the current study was partly to replicate the Whitehall
study,7but on a different population—mainly women in
human service occupations, with a different age distribution,
and with higher levels of sickness absence.
The aim of the present study was to compare self-reported
information on sick-leave days in the last 12 months with
sickness absence data from employers’ registers, irrespective of
diagnoses. Furthermore, as in the Whitehall II study, another
goal was to ascertain whether the self-reported sickness
absences and the register data from the employers show the
same degree of association with self-reported general health.
METHODS
Study population
The investigation was conducted within the framework of the
Swedish study entitled ‘‘Work and Health in the Public Sector’’
(denoted HAKuL).17The data used covered a cohort of employ-
ees at local authorities in five municipalities and three county
councils in different parts of Sweden. A questionnaire was
administered in 2001–2 to 7229 employees who were deemed
eligible because they had permanent employment and were not
on long-term sick leave (.90 days) at the time the information
was collected. The response rate was 75% (n=5411). For 90%
(n=4869) of those employees, we had access to complete
register data on employment status and absence from work
during the 12-month study period. Self-reported sickness
absences were missing for 122 individuals, and the final study
population consisted of 4747 employees (84% women) aged 19–
65 years, with mean ages of 45 and 46 for women and men,
respectively.
Considering occupations, most of the women were teachers,
preschool teachers, child care centre staff, nurses, assistant
nurses, home care workers in elderly care, cleaners and kitchen
staff, and carers of mentally retarded persons. Most of the men
were teachers or various types of production and maintenance
workers, including operating personnel, construction workers,
and park wardens. Information on occupation and age was
derived from employers’ registers.
Measures of sickness absence
The number of self-reported sick-leave days in the last
12 months was derived from the following question: ‘‘How
many days, approximately, have you been off work for health
reasons the last 12 months?’’
Register data on all spells of sickness absence were obtained
from the employers’ computerised personnel records for the
12 months prior to the questionnaire survey. The date of the
first and the last day of each spell of absence was available for
individual employees.
Overlapping, consecutive, or duplicate sick-leave spells were
merged into a single spell. All calendar days registered as a sick-
leave day were counted, regardless of whether they were work
days, and sickness absence part of the day was defined as a sick-
leave day. For each employee, the numbers of sick-leave days in
the 12 months before the questionnaire were computed by
considering the date on which the questionnaire was returned
as the starting date for calculating sick-leave days.
All subjects in this study were covered by the Swedish
national health insurance, which provides sickness benefits to
those who fulfil the requirement of being unable to work due to
disease or injury. At the time of this study, compensation for
the first 14 days of a sick-leave spell was paid by the employer,
with the exception of the first qualifying (‘‘waiting’’) day, for
which no benefit was paid. The first seven days of absence in a
sick-leave spell could be self-certified; thereafter a medical
certificate was required. All sickness absence, both self-certified
and certified by a physician, was included in the present study.
Self-reported general health
Self-reported general health was measured by a single item on
the questionnaire: ‘‘In general, how would you describe your
health?’’ The response options were excellent, very good, good,
fair, or poor, and the answers fair and poor were considered to
indicate ‘‘poor general health’’.
Statistical analyses
Mean annual self-reported and recorded sick-leave days strati-
fied by sex, age and occupational skill level were calculated, and
the differences between the two absence measures are presented
with 95% confidence intervals. Analysis of variance was carried
out to determine whether the differences between the mean
number of self-reported and recorded sick-leave days per year for
women and men were associated with age, occupational skill
level, and number of recorded sick-leave days. In addition, the
proportions of women and men with a maximum discrepancy
of two days between the two absence measures were calculated.
The total numbers of self-reported and employer-registered
sick-leave days were stratified into the five categories: 0, 1–7, 8–
14, 15–27 and >28 days, which are presented in cross tables
showing the proportion of complete agreement for each
category (tables 2 and 3). Estimates of the sensitivity and
specificity of the self-reported sick-leave days over the last
12 months were calculated on the assumption that the register
information from the employers was correct.
Logistic regression analyses were performed to study the
associations between self-reported general health and the five
categories of self-reported and recorded sick-leave days. The
odds ratios were adjusted for age, sex and occupational skill
level. Occupational skill level was classified according to the
International Standard Classification of Occupations (ISCO-
88), and the occupations were stratified into four skill levels:
managers and university or postgraduate university degree,
occupations that require 1–3 years of education after high
school, skilled workers with vocational training and unskilled
workers.
RESULTS
The numbers of self-reported sick-leave days was lower than the
corresponding employer recorded numbers for both women and
men, among different age groups, and in the four groups of
occupational skill level (table 1). No discrepancies in the
difference between recorded and self-reported mean annual
number of sick-leave days were found in the four groups of
occupational skill level among women. However, among men in
occupations requiring 1–3 years of education after high school
the difference between recorded and self-reported mean annual
number of sick-leave days was lower (one day) compared with
the difference for skilled workers with vocational training
(5.8 days). The sex differences in mean annual number of sick-
leave days according to the two different methods of recording
remained significant after adjustment for age and level of
occupational skills (results not shown). Additional adjustment
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for recorded number of sick-leave days reduced this difference
somewhat (p=0.099).
Table 2 presents the total numbers of self-reported and
recorded sick-leave days for women divided into five categories.
The greatest overall agreement between the two sickness
absence measures for women was found for no sick-leave days,
1–7 days and >28 days, as indicated by 74%, 72% and 67%
agreement, respectively. In all, 91% (2335) of the 2566 female
employees who had any sickness absence according to the
register data also reported at least one sick-leave day on the
questionnaire (sensitivity). Among women with no recorded
sick-leave days (n=1402), 74% reported that they had not been
on sick leave (specificity). The sensitivity of >28 recorded sick-
leave days was 67% with a specificity of 98%.
The results for men were similar to those for women,
showing substantial total agreement of 78%, 71% and 74% with
the categories no sick-leave days, 1–7 days and >28 days,
respectively (table 3). Moreover, the sensitivity for any number
of sick-leave days was the same as for women, 91%, with a
specificity of 78%. For >28 recorded sick-leave days, the
sensitivity was 73% and the specificity 99%.
Crude and adjusted analyses of the associations between poor
self-rated health and self-reported and recorded number of sick-
leave days are presented in table 4. The point estimates of the
Table 1
leave days
Mean annual recorded and self-reported sick-leave days and differences in mean number of sick
n
Mean annual
sick-leave days
RecordedSelf-reported Difference (95% CI)
Sex
Women
Men
Women
Age group (years)
(29
30–39
40–49
50–59
>60
Occupational skill levels
Managers/university
1–3 years’ education after high school
Skilled workers with vocational training
Unskilled workers
Men
Age group (years)
(29
30–39
40–49
50–59
>60
Occupational skill levels
Managers/university
1–3 years’ education after high school
Skilled workers with vocational training
Unskilled workers
3968
779
28.9
16.3
17.7
10.5
11.1 (9.5 to 12.7)
5.7 (3.1 to 8.3)
352
823
1341
1260
192
17.6
18.8
29.6
36.6
36.6
14.0
13.2
18.0
22.0
14.7
3.5 (0.9 to 6.1)
5.6 (3.4 to 7.9)
11.7 (8.7 to 14.6)
14.6 (11.3 to 17.9)
21.9 (11.8 to 32.0)
752
996
2086
134
25.2
28.2
30.5
28.2
13.6
15.5
20.3
18.0
11.6 (7.7 to 15.3)
12.7 (9.2 to 16.3)
10.2 (8.1 to 12.4)
10.2 (3.6 to 16.8)
52
146
245
287
49
5.2
13.5
14.2
20.6
20.8
4.6
8.8
8.6
13.2
16.0
0.6 (–1.1 to 2.3)
4.7 (–1.5 to 10.8)
5.6 (1.2 to 10.0)
7.4 (2.4 to 12.5)
4.9 (–0.9 to 10.6)
279
118
361
20
13.5
7.1
18.4
67.1
8.3
6.1
12.6
28.9
5.2 (0.8 to 9.6)
1.0 (0.1 to 2.0)
5.8 (2.0 to 9.7)
38.2 (-5.8 to 82.0)
Table 2
and the sensitivity and specificity of any sick-leave day and >28 days
Self-reported and recorded sick-leave days for female public employees in Sweden over 12 months
Self-reported days
Recorded days
0 days1–7 days8–14 days 15–27 days
>28 days
n%n%n%n%n%
0 days
1–7 days
8–14 days
15–27 days
>28 days
1039
307
74.1
21.9
2.1
0.7
1.1
143
803
128
22
15
12.9
72.3
11.5
2.0
1.4
16
155
159
41
14
4.2
40.3
41.3
10.6
3.6
14
34
107
119
26
4.7
11.3
35.7
39.7
8.7
48
58
48
99
6.2
7.5
6.2
12.9
67.1
30
10
16 517
1402
Any sick leave
91%*
74%
1111385 300770
>28 days
67%
98%{
Sensitivity
Specificity
Figures in bold denote complete agreement between recorded and self-reported days.
*(11112143)+(385216)+(300214)+(770248)/1111+385+300+770=0.91.
{(1402216)+(1111215)+(385214)+(300226)/1402+1111+385+300=0.98.
Original article
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associations with poor self-rated health were slightly higher for
self-reported days than for recorded days but there was no real
difference in the strength of the associations. The strongest
associations were found among those with >28 self-reported
days (adjusted OR 8.25, 95% CI 6.62 to 10.29) and >28 recorded
days (adjusted OR 7.27, 95% CI 5.93 to 8.91).
DISCUSSION
In this study self-reported sickness absence collected using a
questionnaire was compared with sickness absence data
compiled by employers. The results show that the number of
self-reported sick-leave days was lower than the recorded
number of sick-leave days over a period of 12 months.
Analyses of five categories of sick-leave days using sickness
absence data from employers’ registers as the standard indicated
good agreement between self-reported and recorded informa-
tion for any self-reported sick-leave day, 1–7 sick-leave days and
sickness absence of 28 days or more. Both measures of sickness
absence were associated with self-rated health, and this
association was strengthened with increasing number of sick-
leave days.
Methodological considerations
Since the study population originated from the longitudinal
HAKuL study, which included interventions at the workplaces,
the selection of participating county councils and municipalities
was not random. However, the cohort represented all kinds of
activities performed by county councils and municipalities in
different parts of Sweden, including both rural and urban areas,
although there was some predominance of home care and
healthcare workers.17Excluding employees on long-term sick
leave when the study started implies a relatively healthy study
population and a lower proportion of employees in the category
>28 sick-leave days. However, we do not think that this has
affected the agreement between self-reported and registered
number of sick-leave days or the association between sickness
absence and self-reported general health.
An advantage of our study was the high questionnaire
response rate of 75%. High validity of the employers’ registers of
sickness absence could be assumed, because these records are the
basis for calculating salaries. The mean number of recorded sick-
leave days was greater for employees who had information on
self-reported sick-leave days (16.9 days) than for those for
whom such information was missing (12.6 days). The starting
point for calculating the number of recorded sick-leave days was
the date when the completed questionnaire was returned. This
dislocation of the follow-up periods might have led to a few
days of discrepancy between the two sickness absence
measures, but that would have had only a minor effect on the
results.
Several different measures of sickness absence can be used,
and they may provide dissimilar results.1Therefore, the
definition of a measure of sickness absence is of importance.
In Sweden it is possible to be on part-time sick leave for 25%,
50% or 75% of working hours. The proportion of part-time sick
leave was 26% of all sick-leave days in 2001 and this was more
common among women than among men.18However, part-
time sick leave is rare during the first 14 days of sick leave—
about 5% of these days are part-time sick-leave days compared
to more than 35% of the sick-leave days in spells of more than
180 days.18
In the present study all sick-leave days recorded by employers
were regarded as full days, and, if part-time sick-leave days were
added together by the respondent to yield full days, this may
Table 3
and the sensitivity and specificity of any sick-leave day and >28 days
Self-reported and recorded sick-leave days for male public employees in Sweden over 12 months
Self-reported days
Recorded days
0 days1–7 days8–14 days15–27 days
>28 days
n%n%n%n%n%
0 days
1–7 days
8–14 days
15–27 days
>28 days
322
83
78.3
20.2
1.5
0.0
0.0
2312.6
70.9
15.4
0.5
0.5
58.2
36.1
37.7
16.4
1.6
24.8
23.8
23.8
40.5
7.1
4
6
6
6
4.8
7.2
7.2
7.2
73.5
129
28
22
23
10
1
61
10
10
17
3
42
6
0
0
1
161
83411182
Any sick leave
91%*
78%
>28 days
73%
99%{
Sensitivity
Specificity
Figures in bold denote complete agreement between recorded and self-reported days.
*(182223)+(6125)+(4222)+(8324)/182+61+42+83=0.91.
{411+(18221)+(6121)+(4223)/411+182+61+42=0.99.
Table 4
days
Associations between poor self-rated health and number of self-reported and recorded sick-leave
Sick-leave
daysn*
Crude OR (95% CI)Adjusted OR (95% CI){
Recorded Self-reported RecordedSelf-reported
0
1–7
8–14
15–27
>28
1813
1293
446
342
853
1.00
1.44 (1.16 to 1.77)
2.17 (1.66 to 2.85)
3.70 (2.82 to 4.85)
7.79 (6.38 to 9.50)
1.00
1.18 (0.97 to 1.45)
2.13 (1.66 to 2.73)
4.21 (3.21 to 5.52)
8.42 (6.79 to 10.43)
1.00
1.51 (1.22 to 1.87)
2.17 (1.65 to 2.85)
3.81 (2.89 to 5.03)
7.27 (5.93 to 8.91)
1.00
1.30 (1.06 to 1.60)
2.32 (1.80 to 2.99)
4.40 (3.34 to 5.80)
8.25 (6.62 to 10.29)
*Register data from employers’ personnel records.
{Adjusted for sex, age, and level of occupational skills.
Original article
64 Occup Environ Med 2008;65:61–67. doi:10.1136/oem.2006.031427
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