Are self-report of disability pension and long-term sickness absence accurate? Comparisons of self-reported interview data with national register data in a Swedish twin cohort

Aim: This case study aimed to investigate the process of integrating resources of multiple biobanks and health-care registers, especially addressing data permit application, time schedules, co-operation of stakeholders, data exchange and data quality. Methods: We investigated the process in the context of a retrospective study: Pharmacogenomics of antithrombotic drugs (PreMed study). The study involved linking the genotype data of three Finnish biobanks (Auria Biobank, Helsinki Biobank and THL Biobank) with register data on medicine dispensations, health-care encounters and laboratory results. Results: We managed to collect a cohort of 7005 genotyped individuals, thereby achieving the statistical power requirements of the study. The data collection process took 16 months, exceeding our original estimate by seven months. The main delays were caused by the congested data permit approval service to access national register data on health-care encounters. Comparison of hospital data lakes and national registers revealed differences, especially concerning medication data. Genetic variant frequencies were in line with earlier data reported for the European population. The yearly number of international normalised ratio (INR) tests showed stable behaviour over time. Conclusions: A large cohort, consisting of versatile individual-level phenotype and genotype data, can be constructed by integrating data from several biobanks and health data registers in Finland. Co-operation with biobanks is straightforward. However, long time periods need to be reserved when biobank resources are linked with national register data. There is a need for efforts to define general, harmonised co-operation practices and data exchange methods for enabling efficient collection of data from multiple sources.

Download Full-text

Work ability score and future work ability as predictors of register-based disability pension and long-term sickness absence: A three-year follow-up study

Scandinavian Journal of Public Health ◽

10.1177/1403494817745190 ◽

2017 ◽

Vol 46 (3) ◽

pp. 321-330 ◽

Cited By ~ 20

Author(s):

Ulla Kinnunen ◽

Jouko Nätti

Keyword(s):

Sickness Absence ◽

Work Ability ◽

Disability Pension ◽

Negative Binomial ◽

Work Ability Index ◽

Rate Ratios ◽

Future Work ◽

Work Ability Score

Aims: We investigated two single items of the Work Ability Index – work ability score, and future work ability – as predictors of register-based disability pension and long-term sickness absence over a three-year follow-up. Methods: Survey responses of 11,131 Finnish employees were linked to pension and long-term (more than 10 days) sickness absence register data by Statistics Finland. Work ability score was divided into poor (0–5), moderate (6–7) and good/excellent (8–10) and future work ability into poor (1–2) and good (3) work ability at baseline. Cox proportional hazard regressions were used in the analysis of disability pension, and a negative binomial model in the analysis of long-term sickness absence. The results were adjusted for several background, work- and health-related covariates. Results: Compared with those with good/excellent work ability scores, the hazard ratios of disability pension after adjusting for all covariates were 9.84 (95% CI 6.68–14.49) for poor and 2.25 (CI 95% 1.51–3.35) for moderate work ability score. For future work ability, the hazard ratio was 8.19 (95% CI 4.71–14.23) among those with poor future work ability. The incidence rate ratios of accumulated long-term sickness absence days were 3.08 (95% CI 2.19–4.32) and 1.59 (95% CI 1.32–1.92) for poor and moderate work ability scores, and 1.51 (95% CI 0.97–2.36) for poor future work ability. Conclusions: The single items of work ability score and future work ability predicted register-based disability pension equally well, but work ability score was a better predictor of register-based long-term sickness absence days than future work ability in a three-year follow-up. Both items seem to be of use especially when examining the risk of poor work ability for disability but also for long sick leave.

Download Full-text

Sleep disturbance and work-related mental strain: A national prospective cohort study of the prediction of subsequent long-term sickness absence, disability pension and mortality

Scandinavian Journal of Public Health ◽

10.1177/1403494820911813 ◽

2020 ◽

Vol 48 (8) ◽

pp. 888-895

Author(s):

Torbjörn Åkerstedt ◽

Ellenor Mittendorfer-Rutz ◽

Syed Rahman

Keyword(s):

Sleep Disturbance ◽

Sickness Absence ◽

Work Disability ◽

Disability Pension ◽

Sleep Disturbances ◽

Workplace Stress ◽

Mental Strain ◽

Work Related ◽

Synergy Effects

Aims: Sleep disturbances and work-related mental strain are linked to increased sickness absence and disability pension (DP), but we have no information on synergy effects. The aim of this study was to examine the combined (and separate) association of the two predictors with subsequent long-term work disability and mortality. Methods: A total of 45,498 participants aged 16–64 years were interviewed in the Swedish Surveys of Living Conditions between 1997 and 2013, and were followed up on long-term sickness absence (LTSA; >90 days/year), DP and mortality via national registers until 2016. Crude and multivariable Cox analyses were used to estimate hazard ratios (HR) and 95% confidence intervals (CI). Results: For LTSA, the HRs for sleep disturbances and work-related mental strain were 1.6 (95% CI 1.5–1.7) and 1.3 (95% CI 1.2–1.4), respectively. For DP, the HRs were 2.0 (95% CI 1.8–2.2) and 1.4 (95% CI 1.2–1.5). Mortality was only predicted by sleep disturbances (HR=1.2, 95% CI 1.1–1.4). No synergy effect was seen. Conclusions: Work-related mental strain and, in particular, sleep disturbances were associated with a higher risk of subsequent LTSA and DP, but without synergy effects. Sleep disturbances were also associated with mortality. Exposure to interventions tackling sleep disturbance and prevention of workplace stress may reduce work disability.

Download Full-text