IQ and mental health are vital predictors of work drop out and early mortality. Multi-state analyses of Norwegian male conscripts

Lie, Stein Atle; Tveito, Torill H.; Rème, Silje Endresen; Eriksen, Hege R.

doi:10.1371/journal.pone.0180737

Cited by 14 publications

(17 citation statements)

References 39 publications

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“…The ELMA method uses all information of time duration and transitions between labor market states based on the multi-state model for the entire follow-up period. Analyses with multi-state modeling of three or more states are typically characterized by a large number of transitions, and may lead to very large tables for displaying the results [ 11 , 27 ]. The ELMA method is able to sum up numerous results from multi-state models without compromising details on transitions, the number of states, confounders, or proportionality assumptions concerning the survival analysis part.…”

Section: Discussionmentioning

confidence: 99%

“…Typical studies related to this type of analysis use age as the underlying time axis, and an entire life-course until retirement age in terms of analyzing the working life expectation [ 2 , 3 , 6 , 7 , 8 ]. In comparison, Lie et al (2017) used a high-dimensional multi-state model and a simple time axis in a restricted sixteen-year follow-up period from age 20 until age 55 years and showed that low IQ and mental health problems were associated with an increased risk of receiving a disability benefit [ 11 ]. Based on earlier research, showing that sex, age, socioeconomic factors, and health behaviors are associated with labor market outcomes, we included ‘educational level’, ‘smoking habits’, ‘body mass index’, and ‘working time arrangement’ [ 28 , 29 , 30 ].…”

Section: Discussionmentioning

confidence: 99%

“…In addition, these methods are used for investigating factors such as education level that will remain the same throughout the working life. No similar conceptual method has yet been developed to examine only a restricted follow-up period of labor market affiliation, using, e.g., dates or time since a major event as the underlying time axis, and for investigating factors of a temporary nature; though the idea of summing up the results of a multi-state model for restricted periods is not new [ 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies on perceived stress and labor market outcomes have investigated the association with single labor market outcomes, such as sickness absence, disability pension, or return to work [ 16 , 17 ]. However, in a highly flexible and dynamic labor market such as the Danish labor market, individuals are likely to experience recurrent periods of sickness absence and unemployment in between periods of work, making analysis of single outcomes an oversimplification of the complex work participation patterns [ 3 , 11 , 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

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Expected Labor Market Affiliation: A New Method Illustrated by Estimating the Impact of Perceived Stress on Time in Work, Sickness Absence and Unemployment of 37,605 Danish Employees

Pedersen

Solovieva

Thorsen

et al. 2021

IJERPH

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As detailed data on labor market affiliation become more accessible, new approaches are needed to address the complex patterns of labor market affiliation. We introduce the expected labor market affiliation (ELMA) method by estimating the time-restricted impact of perceived stress on labor market affiliation in a large sample of Danish employees. Data from two national surveys were linked with a national register. A multi-state proportional hazards model was used to calculate ELMA estimates, i.e., the number of days in work, sickness absence, and unemployment during a 4-year follow-up period, stratified by gender and age. Among employees reporting frequent work-related stress, the expected number of working days decreased with age, ranging from 103 days lost among older women to 37 days lost among younger and middle-aged men. Young and middle-aged women reporting frequent work- and personal life-related stress lost 62 and 81 working days, respectively, and had more days of sickness absence (34 days and 42 days). In conclusion, we showed that perceived stress affects the labor market affiliation. The ELMA estimates provide a detailed understanding of the impact of perceived stress on labor market affiliation over time, and may inform policy and practice towards a more healthy and sustainable working life.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Expected Labor Market Affiliation: A New Method Illustrated by Estimating the Impact of Perceived Stress on Time in Work, Sickness Absence and Unemployment of 37,605 Danish Employees

Pedersen

Solovieva

Thorsen

et al. 2021

IJERPH

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show abstract

“…22 Multistate event histories model complex time-to-event data as a sequence of transitions (the events) between different states (the event types). Applications in medical research include oncology, [23][24][25] cardiology, 26 gastroenterology, 27 orthopaedics, 28 psychology, 29 prenatal studies, 30 or hospital epidemiology. 31,32 This paper considers simulation-or resampling-of multistate trajectories from an empirical multivariate hazard measure as, eg, given by the (nonparametric) multistate Nelson-Aalen estimator of cumulative transition hazards.…”

mentioning

confidence: 99%

Bootstrapping complex time‐to‐event data without individual patient data, with a view toward time‐dependent exposures

Bluhmki¹,

Putter

Allignol

et al. 2019

Statistics in Medicine

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We consider nonparametric and semiparametric resampling of multistate event histories by simulating multistate trajectories from an empirical multivariate hazard measure. One advantage of our approach is that it does not necessarily require individual patient data, but may be based on published information. This is also attractive for both study planning and simulating realistic real‐world event history data in general. The concept extends to left‐truncation and right‐censoring mechanisms, nondegenerate initial distributions, and nonproportional as well as non‐Markov settings. A special focus is on its connection to simulating survival data with time‐dependent covariates. For the case of qualitative time‐dependent exposures, we demonstrate that our proposal gives a more natural interpretation of how such data evolve over the course of time than many of the competing approaches. The multistate perspective avoids any latent failure time structure and sampling spaces impossible in real life, whereas its parsimony follows the principle of Occam's razor. We also suggest empirical simulation as a novel bootstrap procedure to assess estimation uncertainty in the absence of individual patient data. This is not possible for established procedures such as Efron's bootstrap. A simulation study investigating the effect of liver functionality on survival in patients with liver cirrhosis serves as a proof of concept. Example code is provided.

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The linkage of depressive and anxiety disorders with the expected labor market affiliation (ELMA): a longitudinal multi-state study of Danish employees

Pedersen

Framke

Thorsen

et al. 2022

Int Arch Occup Environ Health

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Objective Depressive and anxiety disorders are prevalent among employees in general. Still, knowledge regarding the contribution of these disorders to the dynamics of the labor market in terms of working time, sickness absence, and unemployment is scarce. We aim to quantify the linkage of depressive and anxiety disorders with labor market participation using the expected labor market affiliation method (ELMA), in a large sample of Danish employees. Methods We combined three survey waves on occupational health with six high-quality national registers in N = 43,148 Danish employees, of which the 2012 survey contributed 29,665 person years, the 2014 survey 33,043 person years, and the 2016 survey 35,375 person years. We used the new ELMA method to estimate the multi-state transition probabilities and 2-year expected time in work, sickness absence, and unemployment. Depressive and anxiety disorders were assessed by the Major Depression Inventory and the SCL-ANX4 scales, respectively. We adjusted for multiple variables by applying inverse probability weighting in groups of gender and age. Results Depressive and anxiety disorders among employees link to reduced labor market affiliation by significantly changed transitions probabilities between the labor markets states, viewed as reduced working time by 4–51 days (in two years), increased time in sickness absence by 6–44 days (in two years), and unemployment by 6–12 days (in two years) when compared to employees without depression or anxiety disorders. The results were most pronounced for women employees and for employees with both depression and anxiety disorders. Conclusions The study reveals detailed insight into what extent depression and anxiety disorders influence the labor market affiliation, in terms of the complex interrelation between working time, sickness absence, and unemployment. The study emphasizes the importance of preventing and handling depressive and anxiety disorders among employees for strengthening work participation.

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IQ and mental health are vital predictors of work drop out and early mortality. Multi-state analyses of Norwegian male conscripts

Cited by 14 publications

References 39 publications

Expected Labor Market Affiliation: A New Method Illustrated by Estimating the Impact of Perceived Stress on Time in Work, Sickness Absence and Unemployment of 37,605 Danish Employees

Expected Labor Market Affiliation: A New Method Illustrated by Estimating the Impact of Perceived Stress on Time in Work, Sickness Absence and Unemployment of 37,605 Danish Employees

Bootstrapping complex time‐to‐event data without individual patient data, with a view toward time‐dependent exposures

The linkage of depressive and anxiety disorders with the expected labor market affiliation (ELMA): a longitudinal multi-state study of Danish employees

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