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Institute of Clinical Medicine, Psychiatry, University of Eastern Finland, FinlandInstitute of Clinical Medicine, Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, Finland
Institute of Clinical Medicine, Psychiatry, University of Eastern Finland, FinlandInstitute of Clinical Medicine, Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, FinlandDepartment of Psychiatry, Kuopio University Hospital, FinlandDepartments of Psychiatry: South-Savonia Hospital District, Mikkeli, North Karelia Central Hospital, Joensuu, SOTE, Iisalmi, Finland
Institute of Clinical Medicine, Psychiatry, University of Eastern Finland, FinlandInstitute of Clinical Medicine, Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, Finland
Institute of Clinical Medicine, Psychiatry, University of Eastern Finland, FinlandInstitute of Clinical Medicine, Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, FinlandSchool of Medicine, Deakin University, Australia
Institute of Clinical Medicine, Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, FinlandDepartment of Psychiatry, Kuopio University Hospital, FinlandDepartment of Psychiatry, Oulu University Hospital, Oulu, Finland
The study investigated the extent of comorbidity between mental disorders and musculoskeletal disorders in ageing women using national registries on prescription medications and work disability pensions.
•
There was strong evidence for comorbidity between mental disorders and musculoskeletal disorders in ageing women.
•
Further research concerning their longitudinal relationships is warranted.
Abstract
Background
Mental disorders (MDs) and musculoskeletal disorders (MSDs) are the main causes of disability. Yet, their comorbidity has not received the deserved attention.
Objective
To investigate the extent of the comorbidity between MDs and MSDs in ageing women using national registries on prescription medications and work disability pensions (DPs).
Methods
The study included 7,809 Finnish women, born during 1932–41, from the population-based Kuopio Osteoporosis Risk Factor and Prevention Study (OSTPRE) cohort, established in 1989. Lifetime permanent DPs due to: 1) ‘MDs only’ (n = 359), 2) ‘MSDs only’ (n = 954), 3) ‘MDs + MSDs’ (n = 227), were recorded till 2003. The reference group was ‘no DP’ (n = 6,269). Data from the OSTPRE questionnaires was obtained in 1994. Use of medications was recorded in 1995 and 2003. The use of musculoskeletal or psychotropic medications by women having a DP or medication due to MD, or MSD diagnoses, respectively, was considered as an indicator of comorbidity.
Results
In 1995, all DP groups had used psychotropic and musculoskeletal medications more often than the referents. Use of musculoskeletal medications was associated with a higher use of psychotropic medications, and vice versa (OR=2.45; 95% CI 2.17–2.77), compared with non-use. The ‘MSDs only’ group was more likely to use psychotropic (OR=1.79; 95% CI 1.50–2.12), and the ‘MDs only’ group musculoskeletal medications (OR=1.38; 95% CI 1.09–1.74), compared with those without DPs. The proportions of medication users were similar in 1995 and 2003; however, the amounts used increased.
Conclusions
There was strong evidence for comorbidity between MDs and MSDs in ageing women. Further research concerning their longitudinal relationships is warranted.
North Staffordshire GP Consortium Clinical multimorbidity and physical function in older adults: a record and health status linkage study in general practice.
World Health Organization (WHO). Global strategy and action plan on ageing and health. Geneva: World Health Organization; 2017. Licence: CC BY-NC-SA 3.0 IGO.
] emphasizes the need for a broader, rather than, a single-disease approach in research, medical education, health promotion, disease prevention and healthcare [
Work outcome in persons with musculoskeletal diseases: comparison with other chronic diseases & the role of musculoskeletal diseases in multimorbidity.
]. At working age, premature retirement due to permanent disability represents a severe form of disease, often preceded by a long sickness absence regardless of occupational class [
Sickness absence as a predictor of disability retirement in different occupational classes: a register-based study of a working-age cohort in Finland in 2007-2014.
]. Despite these increases, the extent to which people with MDs use musculoskeletal medications and people with MSDs use psychotropic medications (indicating comorbidity), have not been thoroughly explored.
In general, MDs could be either a precursor to, or a consequence of MSDs and other chronic conditions [
World Health Organization (WHO). Regional Office for Europe Addressing comorbidity between mental disorders and major noncommunicable diseases.
in: Background technical report to support implementation of the WHO European Mental Health Action Plan 2013-2020 and the WHO European Action Plan for the Prevention and Control of Noncommunicable Diseases 2016-2025, Copenhagen2017
]. Furthermore, comorbid MDs are associated with decreased physical functioning, lower quality of life and other adversities such as mortality and high health care use [
Work outcome in persons with musculoskeletal diseases: comparison with other chronic diseases & the role of musculoskeletal diseases in multimorbidity.
Global Burden of Diseases (GBD) Collaborators Global, regional and national incidence, prevalence and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.
The World Health Organization (WHO) provides recommendations for treating patients with severe MDs suffering from major non-communicable diseases, but MSDs are yet to be considered [
]. Burgeoning evidence suggests that diagnosed MDs are linked with certain common MSDs, such as chronic back pain and low bone mineral density, but what is known regarding the overall comorbidity between MDs and MSDs is still emerging [
]. Thus, further research is needed to garner an appropriate public health response. The aim of the present study was to investigate the extent of the comorbidity between MDs and MSDs by using comprehensive registry-based data on DPs and prescribed medications in a large population-based sample of ageing women.
2. Methods
2.1 Study design and participants
The Kuopio Osteoporosis Risk Factor and Prevention Study (OSTPRE) is a population-based cohort study, which was launched in 1989, capturing all (n = 14,220) women born during 1932–41, who were residing in Kuopio Province, Eastern Finland. Data has been collected by postal enquiries at 5-year intervals and through linkage with several national health registries.
Our study sample included a total of 7809 women (aged 52–61 years) from the OSTPRE cohort, who responded (response rate: 88%) to the postal enquiry in 1994, were alive until 2003 and had relevant linked national register data recorded (see Section 2.3). Specifically, the present study used questionnaire data from 1994 (TQ) and registry data on prescriptions from 1995 (TR1) (the first year of its complete data) and 2003 (TR2), when even the youngest participants had reached the age entitling an old-age pension in Finland, which supersedes eligibility to receive a new DP. Over 80% of the participants, who had become recipients of a premature DP, had received it by the end of 1995 (TR1) (Fig. 1).
Fig. 1Cumulative percent distribution of received lifetime disability pensions (DPs) by DP status in 1964–2003.
All participants provided a written informed consent, and the study was approved by the Ethics Committee of Kuopio University Hospital.
2.2 Questionnaire data
In 1994 (TQ), participants completed a self-reported questionnaire including information on the presence and number of lifetime chronic physician-diagnosed health disorders and currently used prescribed medications. Self-rated health was recorded as: 1) very good; 2) good; 3) fair; 4) rather poor; and 5) poor. Body mass index (BMI) was determined as kg/m2. Current smoking status was used as a two categorical variable (yes/no), and total alcohol consumption (drinks/month, one drink corresponding to 12 gs of ethanol) was treated either as a continuous or a three categorical variable: 1) no alcohol use (i.e. 0 drinks per month); 2) moderate use (i.e. 1–27 drinks per month); and 3) high use (i.e. 28 or more drinks per month).
2.3 Register data
Using personal identification numbers, the OSTPRE questionnaire data was linked with data from two national registries: the National Register for Pensions [
All pensions due to disability (DPs) administered since the 1950′s (i.e. since the early adulthood of the participants) have been classified according to the International Statistical Classification of Diseases (ICD) 8–10. ICD codes 290–319 (ICD 8–9) and F00–F99 (ICD–10) correspond to DPs relating to MDs and codes 710–739 and M00–M99 to MSDs, respectively. For this study, DPs from 1964 till the end of 2003 were used and categorized into: 1) ‘MDs only’; 2) ‘MSDs only’; 3) ‘MDs + MSDs’; and 4) ‘no DP’ (the reference group). Women with DPs due to other health disorders (n = 3529) were excluded.
2.3.2 Finnish Prescription Register (FPR)
The FPR contains data from all reimbursed prescription medications purchased in any pharmacy in Finland since 1995. Medications were classified according to the Anatomical Therapeutic Chemical (ATC) codes. In the present study we used ATC codes N05/N06 (“psycholeptics/psychoanaleptics”) and N05C (“hypnotics and sedatives”) for psychotropic medications, and M (“musculoskeletal medicines”) and M01 (“anti-inflammatory and anti-rheumatic medicines”) for musculoskeletal medications [
]. Participants were considered as medication users if they made a purchase of and received reimbursement for the medications (as above) in 1995 (TR1) or 2003 (TR2). Medication use was treated both as a dichotomous (yes/no) and a continuous variable [i.e. as defined daily doses (DDDs)], with 1 DDD corresponding to an average of one-day use.
2.3.3 Comorbidity indicators
Register data was used to examine specific indicators of the extent of comorbidity between MDs and MSDs. The indicators were:
1)
concurrent use of musculoskeletal and psychotropic medications;
2)
belonging to ‘MDs only’ group and using musculoskeletal medications;
3)
belonging to ‘MSDs only’ group and using psychotropic medications; and
4)
belonging to ‘MDs + MSDs’ group, regardless of medication use
2.4 Statistical analyses
The SPSS statistical package 25.0 for Macintosh (SPSS Inc., Chicago, IL, USA) was used for all statistical analyses.
Descriptive statistics were used to calculate the proportion of participants by DP status and the cumulative percent distribution of received DPs by year (Fig. 1). Chi-squared test or Fisher's exact test for categorical, and Mann-Whitney U test for continuous variables were used to examine differences by DP status, according to study characteristics derived from the questionnaire data. (Table 1).
Table 1Study characteristics according to the questionnaire data (TQ) by lifetime disability pension (DP) status.
DISABILITY PENSION STATUS
CHARACTERISTICS (TQ)
‘no DP’(n = 6269)
‘MDs only’(n = 359) p1, p2
‘MSDs only’(n = 954)p1
‘MDs + MSDs’(n = 227)p1
Age, mean (SD)
57.0 (2.9)
57.1 (2.8)ns, *
57.5 (2.9)***
56.6 (2.8)ns
BMI, mean (SD)
26.6 (4.0)
28.5 (5.6)***, ns
27.7 (4.3)***
28.1 (4.8)***
Current smoker, n (%)
551 (13.9%)
56 (23.3%)***, ***
90 (14.2%)ns
33 (21.0%)*
Alcohol consumption (drinks/month), mean (SD)
5.0 (9.6)
6.4 (16.1)***, ns
3.9 (7.3)***
4.7 (7.7)ns
Alcohol consumption (drinks/month), excluding non-users, mean (SD)
10.8 (13.7)
20.4 (29.5)ns, ns
9.9 (10.3)ns
11.7 (11.4)ns
No. of diseases, mean (SD)
1.3 (0.9)
2.1 (1.5)***, ns
2.1 (1.3)***
2.7 (1.6)***
No. of currently used prescribed medications, mean (SD)
0.9 (1.2)
2.2 (1.7)***, ***
1.8 (1.6)***
2.2 (1.7)***
Self-rated health, mean (SD)
2.3a), (0.8)
3.1b) (0.9)***, **
3.3b) (0.9)***
3.3b) (0.8)***
Abbreviations: DP = permanent work disability pension (lifetime since 1964 to 2003); TQ = Questionnaire-based data in 1994; MDs = mental disorders, MSDs = musculoskeletal diseases.
BMI = body mass index (kg/m2); IQR = interquartile range; no. = number.
p1 = p-value with reference group ‘no DP’; p2 = p-value for the difference between the groups ‘MSDs only’ and ‘MDs only’.
ns = non-significant i.e. p>0.05; * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001.
a)corresponding ’good’ self-rated health.
b)corresponding ‘fair’ self-rated health.
Tests: Mann-Whitney U test for continuous variables, chi-square for categorical variables.
Chi-squared and Mann-Whitney U tests were used to examine medication use (Y/N) and DDDs by DP status, respectively (Table 2). In DDD analyses, those with no medication purchases were excluded.
Table 2.Number of medication users (Y/N) and mean defined daily doses (DDDs) (TR1) by lifetime disability pension (DP) status.
MEDICATION CLASS (ATC code) (TR1)
DISBILITY PENSION STATUS
‘no DP’(n = 6269)
‘MDs only’(n = 359)p1, p2
‘MSDs only’(n = 954)p1
‘MDs + MSDs’(n = 227)p1
Psycholeptics/psychoanaleptics (N05/N06)
no. (% within DP group) of medication users
811 (13.0%)
238 (66.3%)***,***
200 (21.0%)***
104 (45.8%)***
mean DDDs (SD)
126 (176.6)
428 (466.7)***,***
154 (225.0)ns
278 (368.2)***
Hypnotics and sedatives (N05C)
no. (% within DP group) of medication users
424 (6.8%)
89 (24.8%)***,***
110 (11.5%)***
55 (24.2%)***
mean DDDs (SD)
114 (134.5)
244 (288.3)***,***
137 (172.4)ns
161 (225.3)*
Musculoskeletal medicines (M)
no. (% within DP group) of medication users
1538 (24.6%)
111 (30.9%)***,***
456 (47.8%)***
102 (44.9%)***
mean DDDs (SD)
60 (80.2)
91 (122.2)***,***
137 (163.1)***
101 (125.5)***
Anti-inflammatory/antirheumatic medicines (M01)
no. (% within DP group) of medication users
1430 (22.8%)
104 (29.0%)**,***
436 (45.7%)***
93 (41.0%)***
mean DDDs (SD)
59 (78.6)
83 (111.8)*,***
135 (157.9)***
99 (124.6)***
Abbreviations: DP = permanent work disability pension (lifetime since 1964 to 2003); MDs = mental disorders, MSDs=musculoskeletal diseases; TR1 = Registry-based data in 1995; ATC = anatomical therapeutic chemical; BMI = body mass index (kg/m2); no.=number; IQR = interquartile range.
p1 = p-value with reference group ‘no DP’; p2 = p-value for the difference between the groups ‘MSDs only’ and ‘MDs only’.ns = non-significant i.e. p>0.05; * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001.
Tests: independent-samples Mann-Whitney U test for continuous variables, chi-square for categorical variables.
Crude and adjusted risk estimates were computed with logistic regression models [odds ratios (ORs)] with 95% confidence intervals (95% CIs) to examine factors related to medication use (Tables 3 and 4). Logistic regression models (ORs; 95% CIs) were also performed to investigate specific indicators of comorbidity between MDs and MSDs (Tables 3 and 4). Adjusted models were used to control for possible confounding of age and BMI.
Table 3Unadjusted Odds Ratios (ORs; 95% CI) for medication use (Y/N) (TR1) by study characteristics and lifetime work disability pension (DP) status.
CHARACTERISTICS
USE OF MEDICATIONS (ATC code) (TR1)
Psycholeptics/-analeptics (N05/06)
Hypnotics/sedatives (N05C)
Musculoskeletal (M)
Anti-inflammatory/-rheumatic (M01)
(n = 1353)
(n = 678)
(n = 2207)
(n = 2.063)
OR (95% CI)p-value
OR (95% CI)p-value
OR (95% CI)p-value
OR (95% CI)p-value
Age (n = 7797), (TQ) BMI (n = 7367), (TQ) Current smoker (n = 4987), (TQ) no (4257) yes (730) Alcohol consumption (n = 5154), (TQ) no (2846) moderate (2157) high (151) No. of diseases (n = 7809), (TQ)
Self-rated health (n = 7560), (TQ) very good (n = 894) good (2870) fair (3137) rather poor (n = 458) poor (n = 201) Lifetime DP status (n = 7809) ‘no DP’ (6269) ‘MDs only’ (359) ‘MSDs only’ (954) ‘MDs + MSDs’ (227) Being a user of M (n = 7809), (TR1) no (5602) yes (2207) Being a user of N05/N06 (n = 7809), (TR1) no (6456) yes (1353)
Abbreviations: DP = permanent work disability pension (lifetime since 1964 to 2003); MDs = mental disorders, MSDs = musculoskeletal diseases.
TQ = Questionnaire-based data in 1994; TR1 = registry-based data in 1995; ATC = anatomical therapeutic chemical; BMI = body mass index (kg/m2); OR = odds ratio; 95%CI = 95% confidence interval; ns = non-significant i.e. p>0.05; * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001.
3.1 Study population characteristics by disability pension status
A total of 80.3% (6269/7809) of the participants had no lifetime DP, while 12.2% (954/7809) had a permanent DP due to ‘MSDs only’, 4.6% (359/7809) due to ‘MDs only’ and 2.9% (227/7809) due to ‘MDs + MSDs’.
Participants with DPs had higher BMI, poorer self-rated health and reported more physician-diagnosed diseases and currently used prescription medications than participants without DPs in 1994 (Table 1; all p ≤ 0.001). Participants in the ‘MDs only’ group were more often current smokers and consumed more alcohol than those with no DPs, whereas the ‘MSDs only’ group consumed less alcohol (all p ≤ 0.001) but had similar smoking status as the reference group (Table 1).
3.2 Medication use
In 1995 (TR1), 17.3% (1353/7809, c.f. Table 2) of all the participants had used psycholeptics/psychoanaleptics (ATC codes: N05/N06) and 8.7% hypnotics and sedatives (N05C), whereas 28.3% of all the participants had used musculoskeletal medications (M), and 26.4% anti-inflammatory and anti-rheumatic medications (M01).
The proportions of medication users differed significantly between the ‘MDs only’ (range: 25–66%) and ‘MSDs only’ (range: 12–48%) groups (all p ≤ 0.001) (Table 2). These proportions were higher in all the DP groups than in the reference group (range: 7–25%) (p ≤ 0.001, except for M01 in ‘MDs only’ p ≤ 0.01) (Table 2).
The medication users in the ‘MDs only’ group had higher mean DDDs across all the examined medication classes than users with no DPs (p ≤ 0.001, except for M01 in ‘MDs only’ p ≤ 0.05). In the ‘MSDs only’ group, only the DDDs of musculoskeletal medication users were significantly higher (p ≤ 0.001) than those of the users in the reference group (Table 2).
The number of medication users remained similar at TR1 and TR2, but the mean DDDs increased, regardless of medications class or DP status (Fig. 2).
Fig. 2Mean defined daily doses (DDDs) of psychotropic and musculoskeletal medications in 1995 (TR1) and in 2003 (TR2) by lifetime disability pension (DP) status.
In crude logistic regression analyses on medication use at TR1, the use of musculoskeletal medications (M) was associated with a higher use of psychotropic medications, and vice versa (OR=2.45; 95%CI 2.17–2.77), when compared with non-use (Table 3).
Having a DP due to ‘MDs only’ was related to a higher use of any of the included medication classes. The ORs were 13.2 (95% CI 10.5–16.7) for using psychotropic medications (N05/N06) and 1.38 (1.09–1.74) for using musculoskeletal medications, compared to ‘no DP’. In the ‘MSDs only’ group, the respective ORs were 1.79 (1.50–2.12) and 2.82 (2.45–3.45), and in the ‘MDs + MSDs’ group, 5.69 (4.34–7.46) and 2.51 (1.92–3.28), respectively (Table 3).
Higher age was marginally associated with higher use of hypnotics and sedatives (N05C) but lower use of musculoskeletal medications (M). Number of diseases, low self-rated health and higher BMI were related to the use of all the included medication classes (Table 3), except for BMI in respect of hypnotics and sedatives (N05C). High alcohol use and current smoking were strongly related to the use of psychotropic (N05/N06), but not musculoskeletal medications (M, M01) (Table 3). In multivariable analyses, adjusting for age and BMI did not substantially change the associations between DP status and use of medications (Table 4). These relationships with respect to the use of medications and other factors remained similar at TR2.
4. Discussion
In the present study, the comorbidity between MDs and MSDs was studied in their severe forms using data from Finnish national registries on prescription medications and disability pensions. The comorbidity between the two leading causes of disability was evident. Compared to non-use, the use of either musculoskeletal or psychotropic medications substantially increased (+145%) the likelihood of the use of the other. Further, both the use of psychotropic medications in women granted a DP due to MSDs (+79%), and the use of musculoskeletal medications in women granted a DP due to MDs (+37%), were higher than expected. Even if in the ‘MDs + MSDs’ group neither of these causes of DP separately is usually severe enough for a disability pension, the co-occurrence of MDs and MSDs in the retirees per se indicates highly disabling comorbidity. During the 9-year interval (1995–2003), the observed pattern overall did not change greatly, but the mean amounts of purchased medications increased, regardless of medication class or DP status. All the DPs and prescription medications were related to an increased morbidity (e.g. diseases, use of medications, poor self-rated health and life style).
Previously, specific MDs, including mood and anxiety disorders, have been shown to be associated with MSDs such as chronic back pain, cervical or lumbar disc herniation and low bone mineral density [
]. The increased concurrent use of psychotropic and musculoskeletal medications in the studied group of ageing women emphasizes the significance of the overall comorbidity between MDs and MSDs. Thus, further research investigating the relationships between MDs and MSDs could hold major potential for supporting functional ability and overall well-being amongst the ageing.
The increasing use of prescription medications (incl. psychotropics) over time has been previously reported [
]. The progressive increase in the use of antidepressants, in particular, has been argued to be partly driven by an increase in their long-term use, based on follow-up data from the UK for the period between 1995 and 2011 [
]. Indeed, in the present study, the number of psychotropic medication users did not change greatly across the time period (1995–2003), but the use in DDDs did increase, regardless of whether the disability was present or not. In addition to long-term use, the increased use of medications could also be due to reasons such as disease progression or intensified treatment needs.
Our results highlight that the burden of MDs and MSDs (both separate and comorbid) is not decreasing with increasing age, and a greater understanding about their mutual relationships – as well as preventive measures – is needed in order to decrease their subjective and objective disease burden. At present, patients with severe MDs have heavily decreased life expectancy [
Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy making and research agendas.
Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy making and research agendas.
] – as well as collaboration between medical specialties. It could give new opportunities for personal fulfilment and contribution to the community.
The strengths of the present study include the large population-based sample of ageing women and the use of two comprehensive and internationally comparable national registries [
], with DPs classified according to ICD and medications according to ATC. Even if the study participants were restricted by sex, age range and defined area of residence, the homogenous Finnish ageing population decrease confounding. Due to the original thematic scope of the OSTPRE (osteoporosis, falls, fractures etc.), the participants were likely to be active and interested in MSDs, but still, MSDs were also associated with higher than expected MD comorbidity. Our study does not allow causal conclusions, but it offers views for longitudinal research on the comorbidity between MDs and MSDs.
5. Conclusion
The comorbidity was evident between MDs and MSDs amongst ageing women, based on data from two comprehensive national registries, i.e. on disability pensions and on the use of medications. To disentangle the reciprocal causal relationships and to govern the disease burden due to these medical conditions, further research on their longitudinal relationships is needed.
Contributors
J Heikkinen contributed to conceptualization, data curation, formal analysis, methodology, validation, visualization, writing the original draft, and review and editing of the draft article.
H Koivumaa-Honkanen contributed to conceptualization, methodology, project administration, supervision, validation, visualization, writing the original draft, and review and editing of the draft article.
P Rauma contributed to conceptualization, data curation, formal analysis, methodology, and review and editing of the draft article.
LJ Williams contributed to review and editing of the draft article.
SE Quirk contributed to review and editing of the draft article.
J Leung contributed to review and editing of the draft article.
RJ Honkanen contributed to conceptualization, data curation, methodology, supervision, validation, and review and editing of the draft article.
Funding
Jeremi Heikkinen has been supported by the grant of the Päivikki and Sakari Sohlberg Foundation, received by Prof. Heli Koivumaa-Honkanen.
Shae Quirk has been supported by the grants of the Päivikki and Sakari Sohlberg Foundation and the Signe and Ane Gyllenberg Foundation, received by Prof. Heli Koivumaa-Honkanen.
Janni Leung is supported by a Development Fellowship at the University of Queensland.
Lana Williams is supported by a National Health and Medical Research Council (NHMRC) Emerging Research Fellowship (1174060).
Ethical approval
All participants provided a written informed consent, and the study was approved by the Ethics Committee of Kuopio University Hospital.
Provenance and peer review
This article was not commissioned and was externally peer reviewed.
Research data (data sharing and collaboration)
There are no linked research data sets for this paper. Data will be made available on request.
Declaration of competing interest
The authors declare that they have no competing interests.
References
Barnett K.
Mercer S.W.
Norbury M.
Watt G.
Wyke S.
Guthrie B.
Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.
World Health Organization (WHO). Global strategy and action plan on ageing and health. Geneva: World Health Organization; 2017. Licence: CC BY-NC-SA 3.0 IGO.
Institute for Health Metrics and Evaluation (IHME)
Global Burden of Disease (GBD) Results Tool [Internet].
Institute for Health Metrics and Evaluation (IHME),
Seattle, Washington2019 ([cited 2019 March]. Available from: https://vizhub.healthdata.org/gbd-compare/#)
Work outcome in persons with musculoskeletal diseases: comparison with other chronic diseases & the role of musculoskeletal diseases in multimorbidity.
Sickness absence as a predictor of disability retirement in different occupational classes: a register-based study of a working-age cohort in Finland in 2007-2014.
World Health Organization (WHO). Regional Office for Europe
Addressing comorbidity between mental disorders and major noncommunicable diseases.
in: Background technical report to support implementation of the WHO European Mental Health Action Plan 2013-2020 and the WHO European Action Plan for the Prevention and Control of Noncommunicable Diseases 2016-2025, Copenhagen2017
Global, regional and national incidence, prevalence and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.
Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy making and research agendas.
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