The authors have declared that no competing interests exist.
Conceived and designed the experiments: MW CB KA BR PT EM. Performed the experiments: MW CB KA BR PT EM. Analyzed the data: MW CB KA BR PT EM. Contributed reagents/materials/analysis tools: MW CB KA BR PT EM. Wrote the paper: MW CB KA BR PT EM.
Work-related functional impairment in terms of sickness absence and disability pension (SA/DP) has been reported to be associated with subsequent suicide. However, there is only limited knowledge on SA/DP patterns prior to suicide. The aim was to identify trajectories of work-related functional impairment prior to suicide and to describe associations of socio-demographic and medical factors with such trajectories.
This is a population-based retrospective cohort study of the 4 209 individuals aged 22–65 years who committed suicide during 2007–2010 in Sweden. Work-related functional impairment was measured as mean annual number of months of SA/DP. We analyzed trajectories of SA/DP during five years prior to suicide (i.e., 2002–2009) by a group-based trajectory method. Associations between socio-demographic and medical factors with different groups of trajectories were estimated by chi2-test and multinomial logistic regression.
Five different functional impairment trajectory groups were identified prior to suicide. One group had constant low levels of SA/DP (46%), while 30% had constant high levels of SA/DP. Two groups (16%) showed increasing number of SA/DP months. The remaining 7% showed decreasing number of SA/DP months before the suicide. Sex, age, educational level, family situation, and diagnosis-specific healthcare were significantly associated with different trajectory groups (Likelihood ratio X2 tests <0.05). A larger proportion of higher educated and younger men with a lower proportion of previous suicide attempts were found in the group with constant low levels. Opposite characteristics were displayed in the group with constant high levels.
This study identified five different groups of work-related functional impairment trajectories before suicide. These differences might be partly explained by the variations in socio-demographic profiles and health care consumptions five years before suicide.
Suicide is a major public health issue, also globally with nearly one million annual suicide deaths [
People of working ages are frequently recommended sickness absence (SA) in healthcare, that is, given a sick note or granted disability pension (DP) according to reduced work capacity caused by injuries or diseases [
Moreover, socio-demographic and health care related factors have been identified to be associated with SA and DP [
The aim of this study was to identify trajectories of work-related functional impairment in terms of SA/DP prior to suicide. Another aim was to describe associations of socio-demographic and medical factors in the different trajectory groups of work-related functional impairment before suicide in order to gain a better understanding of these trajectories.
We conducted a population-based retrospective cohort study by means of merging different Swedish nationwide registers. We selected all the 4 209 individuals who committed suicide during 2007–2010 when aged 22–65 years, from the Swedish Cause of Death Register. Suicide is often underreported or reported as undetermined intent [
The individuals’ unique personal identity number was used to link de-identified annual data from nationwide registers from Statistics Sweden and the National Board of Health and Welfare for the five years preceding the year of suicide. We used an annual time-scale where T–5 represents 5 years prior to suicide (i.e., 2002–2005). The time during T–5 to T–1 (i.e., 2002–2009) was applied to explore how trajectories of SA/DP developed over time before suicide.
Socio-demographic characteristics included sex, age, educational level, type of place of residence, country of birth, and family situation and were obtained from Statistics Sweden. The variables were measured at T–5 and categorized as indicated in
All | Women | Men | ||||
---|---|---|---|---|---|---|
n | % | n | % | n | % | |
Age |
||||||
17–27 | 786 | 18.7 | 176 | 14.9 | 610 | 20.1 |
28–38 | 873 | 20.7 | 257 | 21.8 | 616 | 20.3 |
39–49 | 1 276 | 30.3 | 368 | 31.2 | 908 | 30.0 |
50–61 | 1 274 | 30.3 | 380 | 32.2 | 894 | 29.5 |
Education (years) |
||||||
Compulsory (≤9) | 1 290 | 30.6 | 321 | 27.2 | 969 | 32.0 |
High school (10–12) | 2 105 | 50.0 | 570 | 48.3 | 1 535 | 50.7 |
University (>12) | 778 | 18.5 | 278 | 23.5 | 500 | 16.5 |
Missing | 36 | 0.9 | 12 | 1.0 | 24 | 0.8 |
Country of birth |
||||||
Sweden | 3 635 | 86.4 | 1 011 | 85.6 | 2 624 | 86.7 |
Other Nordic countries | 209 | 5.0 | 61 | 5.2 | 148 | 4.9 |
EU25 without Northern European countries | 97 | 2.3 | 37 | 3.1 | 60 | 2.0 |
Rest of the world | 268 | 6.4 | 72 | 6.1 | 196 | 6.5 |
Type of place of residence |
||||||
Big cities | 1 459 | 34.7 | 453 | 38.4 | 1 006 | 33.2 |
Medium sized cities | 1 477 | 35.1 | 417 | 35.3 | 1 060 | 35.0 |
Small towns/villages | 1 237 | 29.4 | 299 | 25.3 | 938 | 31.0 |
Missing | 36 | 0.9 | 12 | 1.0 | 24 | 0.8 |
Family situation |
||||||
Married |
367 | 8.7 | 128 | 10.8 | 239 | 7.9 |
Married |
877 | 20.8 | 233 | 19.7 | 644 | 21.3 |
Single |
2 452 | 58.3 | 578 | 48.9 | 1 874 | 61.9 |
Single |
258 | 6.1 | 185 | 15.7 | 73 | 2.4 |
Adolescents living with parents, 16–20 years | 219 | 5.2 | 45 | 3.8 | 174 | 5.7 |
Missing | 36 | 0.9 | 12 | 1.0 | 24 | 0.8 |
Hospital stay due to mental disorders (days) |
||||||
No hospital stay | 3 784 | 89.9 | 1 009 | 85.4 | 2 775 | 91.6 |
1 to 11 | 226 | 5.4 | 87 | 7.4 | 139 | 4.6 |
>11 | 199 | 4.7 | 85 | 7.2 | 114 | 3.8 |
Hospital stay due to somatic disorders (days) |
||||||
No hospital stay | 3 663 | 87.0 | 970 | 82.1 | 2 693 | 88.9 |
1 to 3 | 308 | 7.3 | 110 | 9.3 | 198 | 6.5 |
>3 | 238 | 5.7 | 101 | 8.6 | 137 | 4.5 |
Outpatient care visits due to mental disorders (visits) |
||||||
No visits | 3 722 | 88.4 | 994 | 84.2 | 2 728 | 90.1 |
1 to 2 | 305 | 7.2 | 111 | 9.4 | 194 | 6.4 |
>2 | 182 | 4.3 | 76 | 6.4 | 106 | 3.5 |
Outpatient care visits due to somatic disorders (visits) |
||||||
No visits | 2 243 | 53.3 | 499 | 42.3 | 1 744 | 57.6 |
1 to 2 | 1 010 | 24.0 | 297 | 25.1 | 713 | 23.5 |
>2 | 956 | 22.7 | 385 | 32.6 | 571 | 18.9 |
Suicide attempt (inpatient care) |
||||||
No suicide attempt | 4 109 | 97.6 | 1 127 | 95.4 | 2 982 | 98.5 |
Suicide attempt | 100 | 2.4 | 54 | 4.6 | 46 | 1.5 |
* Significant sex differences.
a Measured at T–5.
b Place of residence: big cities: Stockholm, Gothenburg and Malmö; medium sized cities: cities with more than 90 000 inhabitants within 30 km distance from the centre of the city; small cities/villages.
c Married includes all living with partner; cohabitant.
d Single includes divorced, separated or widowed
e Hospital stay due to mental/somatic disorders (days): categorized based on median length among those hospitalized.
f Outpatient specialized health care visits due to mental/somatic disorders: categorized based on median visits among those with such visits.
Information on both mental and somatic diagnoses as well as suicide attempts was obtained from the National Patient Register. In-patient care was categorized according to the median length of inpatient care among those hospitalized (no inpatient care; ≤median length; >median length). A similar approach was used for outpatient specialized health care visits (no visits; ≤median visits; >median visits). Health care information was measured at T–5, as indicated in
During the study period, all people in Sweden above the age of 16 who had reduced work capacity due to disease or injury were eligible for sickness benefits if having an income from work or unemployment or parental benefits. Sickness benefit amounts to 80% of the lost income up to a certain level. Employers provided sick pay for the first 2 weeks of a sick-leave spell, thereafter employees received sickness benefits from the Social Insurance Agency (SIA). Unemployed individuals could be granted benefits from SIA from the second day of a sick-leave spell (the first day being a qualifying day for both employed and unemployed individuals) whereas self-employed individuals received sick pay from SIA according to which insurance coverage they had chosen. DP could be granted all individuals living in Sweden whose work capacity had been reduced permanently due to disease or injury. People below the age of 30 could be granted temporary disability pension if their work capacity (including capacity to study) was reduced due to disease or injury for at least one year [
Group-based trajectory modelling was used to estimate trajectories of SA/DP from T–5 to T–1 before suicide. This procedure is based on a mixture model that provides the capacity to identify subgroups of individuals who followed distinct trajectories during the time of observation and estimates a regression model for each discrete group [
Second, we estimated associations of socio-demographic and medical characteristics in each SA/DP trajectory group by chi2-test and multinomial logistic regression. Possible sex differences in the proportion of characteristics in relation to different socio-demographic and medical characteristics were tested by chi2-test. For the chi2-test in relation to SA/DP trajectory groups we excluded missing values (n = 36) on “education”, “type of place of residence” and “family situation”. For the multinomial logistic regression, individuals (n = 36) with missing values were excluded from the study population. The likelihood ratio chi2-tests were used to evaluate whether socio-demographic and medical factors were associated with type of trajectory in the full model and Nagelkerke R2 were used to evaluate the strength of these associations. By consecutively excluding each factor from the full model, we calculated differences in R2 for each factor in order to examine the contribution of a given factor to the full model. Data processing was performed using statistical software SAS for Windows version 9.4 (SAS-based procedure “Traj”) and SPSS for Windows version 22.0 (chi2-test and multinomial logistic regression).
The study population was based on linkage of several public national registers. Ethical vetting is always required when using register data in Sweden. The ethical vetting is performed by regional ethical review boards and the risk appraisal associated with the Law on Public Disclosure and Secrecy is done by data owners. The ethical review boards can however waive the requirement to consult the data subjects (or in case of minors/children the next of kin, careers or guardians) directly to obtain their informed consent, and will often do so if the research is supported by the ethical review board and the data has already been collected in some other context. Also, the institutional review board/ethics committee waived the need for written informed consent from the participants. Patient records/information was anonymized and de-identified prior to analysis by the authority, Statistics Sweden, which was responsible for data linkage. Researchers received de-identified data. According to these standards in Sweden this project has been evaluated and approved by the Regional Ethical Review Board of Karolinska Institutet, Stockholm, Sweden.
In
Among those who had had inpatient care, more women than men had inpatient mental health care (14.6% vs. 8.4%) and inpatient somatic health care (17.9% compared to 11.0% among men), respectively. Also, a higher rate of the women than men had outpatient mental health care (15.8% vs. 9.9%) and outpatient somatic health care (57.7% vs. 42.4%). Moreover, at T–5 a higher rate of the women (4.6%) than men (1.5%) had had inpatient care due to attempted suicide (
In the trajectory analyses, the BIC-based procedure identified five groups of different trajectories of SA/DP months as the best fitting model (
The figure displayed five different trajectories of sickness absence and disability pension (SA/DP) five years before suicide. The “Constant Low” group (red line) included individuals (46.4%) who had few month of SA/DP over the year before suicide. The “Constant high” group (yellow line) included 30.4% of the individuals with high level of SA/DP over the years. There were 9.2% of individuals belonged to the “Increasing Low” group (blue line) and 6.9% of individuals belonged to the “Increasing High” group (black line). This two groups revealed increasing of SA/DP with different speeds. The “Decreasing” group (green line) contained 7.1% of the individuals with a decrease in SA/DP over time.
A large proportion of the individuals (46.4%) belonged to the “Constant Low” group. They constantly had few months of SA/DP over the years prior to suicide. The “Constant High” group included 30.4% of the individuals. On average, they had more than 10 months of SA/DP/year annually. There were 9.2% and 6.9% of the individuals in the “Increasing Low” and the “Increasing High” groups, respectively. Both of the groups mainly had increasing SA/DP months during the time prior to suicide with different increasing patterns. The “Increasing Low” group had less SA/DP months at T–5 and increased only marginally up until T–2, when the increase was sharp. On the other hand, the “Increasing High” group started with a strong increase of SA/DP months and continued with the strong increasing until T–2. The “Decreasing” group contained 7.1% of the individuals and showed a decrease in SA/DP over time (
Constant Low | Decreasing | Increasing Low | Increasing High | Constant High | X2 (p-value) | Log-likelihood testX2(p-value) | Diff. in R2 |
|
---|---|---|---|---|---|---|---|---|
n (%) | n (%) | n (%) | n (%) | n (%) | ||||
Sex |
||||||||
Women | 356 (30.1) | 101 (8.6) | 117 (9.9) | 94 (8.0) | 513 (43.4) | 195.8 (<0.01) | 118.4 (<0.01) | 0.02 |
Men | 1 605 (53.0) | 200 (6.6) | 261 (8.6) | 195 (6.4) | 767 (25.3) | |||
Age |
||||||||
17–27 | 532 (67.7) | 37 (4.7) | 101 (12.8) | 53 (6.7) | 63 (8.0) | 399.3 (<0.01) | 394.6 (<0.01) | 0.07 |
28–38 | 455 (52.1) | 73 (8.4) | 79 (9.9) | 56 (6.4) | 210 (24.1) | |||
39–49 | 527 (41.3) | 117 (9.2) | 100 (7.8) | 99 (7.8) | 433 (33.9) | |||
50–61 | 447 (35.1) | 74 (5.8) | 98 (7.7) | 81 (6.4) | 574 (45.1) | |||
Education (years) |
||||||||
Compulsory (≤9) | 587 (45.5) | 80 (6.2) | 103 (8.0) | 91 (7.1) | 429 (33.3) | 25.6 (<0.01) | 40.2 (<0.01) | 0.01 |
High school (10–12) | 936 (44.5) | 172 (8.2) | 198 (9.4) | 145 (6.9) | 654 (31.1) | |||
University (>12) | 407 (52.3) | 49 (6.3) | 74 (9.5) | 51(6.6) | 197 (25.3) | |||
Country of birth |
||||||||
Sweden | 1 685 (46.4) | 264 (7.3) | 335 (9.2) | 247 (6.8) | 1 104 (30.4) | 14.2 (0.29) | 4.7 (0.97) | <0.01 |
Other Nordic countries | 90 (43.1) | 13 (6.2) | 12 (5.7) | 14 (6.7) | 80 (38.3) | |||
EU25 without Northern European countries | 46 (47.4) | 7 (7.2) | 6 (6.2) | 8 (8.2) | 30 (30.9) | |||
Rest of the world | 140 (52.2) | 17 (6.3) | 25 (9.3) | 20 (7.5) | 66 (24.6) | |||
Type of place of residence |
||||||||
Big cities | 659 (45.2) | 108 (7.4) | 141 (9.7) | 102 (7.0) | 449 (30.8) | 5.3 (0.72) | 11.9 (0.16) | <0.01 |
Medium sized cities | 680 (46.0) | 103 (7.0) | 139 (9.4) | 106 (7.2) | 449 (30.4) | |||
Small towns/villages | 591 (47.8) | 90 (7.3) | 95 (7.7) | 79 (6.4) | 382 (30.9) | |||
Family situation |
||||||||
Married |
148 (40.3) | 19 (5.2) | 29 (7.9) | 22 (6.0) | 149 (40.6) | 240.5 (<0.01) | 116.8 (<0.01) | 0.02 |
Married |
482 (55.0) | 78 (8.9) | 94 (10.7) | 66 (7.5) | 157 (17.9) | |||
Single |
1 050 (42.8) | 172 (7.0) | 200 (8.2) | 169 (6.9) | 861 (35.1) | |||
Single |
83 (32.2) | 28 (10.9) | 25 (9.7) | 176 (6.6) | 105 (40.7) | |||
Adolescents living with parents, 16–20 years | 167 (76.3) | 4 (1.8) | 27 (12.3) | 13 (5.9) | 8 (3.7) | |||
Hospital stay due to mental disorders (days) |
||||||||
No hospital stay | 1 899 (50.2) | 252 (6.7) | 353 (9.3) | 261 (6.9) | 1 019 (26.9) | 277.1 (<0.01) | 47.7 (<0.01) | 0.01 |
1 to 11 | 38 (16.8) | 22 (9.7) | 18 (8.0) | 15 (6.6) | 133 (58.8) | |||
>11 | 24 (12.1) | 27 (13.6) | 7 (3.5) | 13 (6.5) | 128 (64.3) | |||
Hospital stay due to somatic disorders (days) |
||||||||
No hospital stay | 1 835 (50.1) | 246 (6.7) | 345 (9.4) | 247 (6.7) | 990 (27.0) | 215.2 (<0.01) | 17.3 (<0.05) | <0.01 |
1 to 3 | 89 (28.9) | 29 (9.4) | 23 (7.5) | 26 (8.4) | 141 (45.8) | |||
> 3 | 37 (15.5) | 26 (10.9) | 10 (4.2) | 16 (6.7) | 149 (62.6) | |||
Outpatient care visits due to mental disorders (visits) |
||||||||
No visits | 1 875 (50.4) | 256 (6.9) | 346 (9.3) | 247 (6.6) | 998 (26.8) | 257.5 (<0.01) | 115.7 (<0.01) | 0.02 |
1 to 2 | 69 (22.6) | 22 (7.2) | 22 (7.2) | 25 (8.2) | 167 (54.8) | |||
>2 | 17 (9.3) | 23 (12.6) | 10 (5.5) | 17 (9.3) | 115 (63.2) | |||
Outpatient care visits due to somatic disorders (visits) |
||||||||
No visits | 1 319 (58.8) | 124 (5.5) | 217 (9.7) | 142 (6.3) | 441 (19.7) | 538.5 (<0.01) | 229.2 (<0.01) | 0.04 |
1 to 2 | 442 (43.8) | 76 (7.5) | 109 (10.8) | 76 (7.5) | 307 (30.4) | |||
> 2 | 200 (20.9) | 101 (10.6) | 52 (5.4) | 71 (7.4) | 532 (55.6) | |||
Suicide attempt (inpatient care) |
||||||||
No suicide attempt | 1 954 (47.6) | 290 (7.1) | 370 (9.0) | 282 (6.9) | 1 213 (29.5) | 81.8 (<0.01) | 12.8 (<0.05) | <0.01 |
Suicide attempt | 7 (7.0) | 11 (11.0) | 8 (8.0) | 7 (7.0) | 67 (67.0) |
* Difference in Nagelkerke R2 between model including tested variable and model without tested variable. Nagelkerke R2 for full model is 0.34.
a Measured at T–5.
b Type of place of residence: big cities: Stockholm, Gothenburg and Malmö; medium sized cities: cities with more than 90 000 inhabitants within 30 km distance from the centre of the city; small cities/villages.
c Married includes all living with partner; cohabitant.
d Single includes divorced, separated or widowed
e Hospital stay due to mental/somatic disorders (days): categorized based on median length among those hospitalized.
f Outpatient specialized health care visits due to mental/somatic disorders: categorized based on median visits among those with such visits.
In
The “Decreasing” group consisted mainly of individuals of female sex, middle age (39–49 years), with high school education, and who were living single with children. Regarding medical characteristics, around 10–15% had attempted suicide or had mental or somatic in- or outpatient care exceeding the median number of days or visits.
The two groups with increasing SA/DP months showed slightly different distributions of socio-demographic and medical characteristics. The “Increasing Low” group tended to be younger, with higher education and with less somatic and mental inpatient and mental outpatient health care than the “Increasing High” group.
In this study of 4 209 people of working age in Sweden who committed suicide 2007–2010, we found five different groups of trajectories of work-related functional impairment, measured as previous number of sickness absence and disability pension (SA/DP) months over the five years preceding suicide. Nearly half of the suicide victims had few annual months of SA/DP while one third belonged to a group with more than 10 months yearly of SA/DP. There were also two smaller groups (16.1%) with increasing trends of SA/DP months preceding suicide, and one group with decreasing number of months (7% of the individuals). Sex, age, education, family situation, and diagnosis-specific health care were significantly associated with different trajectory groups.
To the best of our knowledge, this is the first study investigating trajectories of work-related functional impairment in terms of SA/DP prior to suicide. The population-based cohort design, including all individuals aged 22–65 years in the entire country of Sweden, offered satisfactory statistical power for the analyses of the trajectories of SA/DP months prior to suicide. Another strength is that we used data on suicide, SA/DP, socio-demographic, and medical factors from nationwide registers that are of good quality [
Some limitations of the study and considerations when interpreting our findings are important to mention. Information on sick-leave spells <14 days among employed individuals was not available. This means that for employed individuals the number of SA days contributing to the combined number of SA/DP days might be an underestimation. We only included suicide attempts that required inpatient care, that is, the medically most serious ones. This means that suicide attempters who had outpatient care or did not seek health care were not included. Further, there might be other socio-demographic or medical factors associated with trajectories of SA/DP than those we have studied.
Our findings with regard to five different trajectories of SA/DP prior to suicide reflect the general knowledge that suicide victims comprise a heterogeneous group with regard to etiology, health care seeking behaviour, the suicidal process, and underlying diseases [
Our results indicate that different SA/DP trajectories can be described by using information on socio-demographics and health care consumptions. Age showed the strongest associations in the full model. According to previous research, SA/DP rates increase with age [
Also, health care consumption was associated with how SA/DP developed over time prior to suicide. Long mental and somatic hospital stays and more frequent out-patient visits at T–5, as measures of type and severity of the underlying disorders, were found both in the “Constant High” and “Increasing High” group. The “Decreasing” group also had high level of health care consumptions at T–5. The decreasing SA/DP months might reflect improvement of their health conditions or inadequate treatment or rehabilitation.
On the other hand, the “Constant Low” and the “Increasing Low” groups included a larger proportion of individuals with less health care consumption at T–5. Regarding the “Increasing Low” group, the few months of SA/DP at T–5 could be interpreted by the better health condition in terms of less in- or outpatient health care. The increasing number of average months with SA/DP might reflect deterioration of somatic or mental health. One possible explanation of the lower health care consumption in the “Constant Low” group is that the group also comprised a larger proportion of young men. Young men are sometimes reported to have a higher threshold for reporting health complaints and are less help-seeking than their female counterparts [
This study showed different previous trajectories of work-related functional impairment among individuals with subsequent suicide. While nearly half of the suicide victims had low levels of work-related functional impairment in the five preceding years, around a quarter and a third had decreasing/increasing and constantly high levels, respectively. Socio-demographic and medical factors were associated with different SA/DP trajectories.