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Work disability patterns before and after incident acute myocardial infarction and subsequent risk of common mental disorders: A Swedish cohort study.

ABSTRACT: This study investigated the extent to which work disability patterns including sickness absence and disability pension (SA/DP) before and after acute myocardial infarction (AMI) were associated with subsequent common mental disorders (CMDs) such as depression and anxiety in AMI patients without previous CMD. Total 11,493 patients 26-64 years with incident AMI during 2008-10 were followed up for CMD (measured as antidepressant prescription) through 2013. Four SA/DP trajectory groups during the 3-years pre-AMI and 1-year post-AMI were identified. Hazard ratios (HRs) with 95% confidence intervals for subsequent CMD were estimated in Cox models. Higher pre-AMI SA/DP annual levels (>1-12 months/year) were associated with 40-60% increased CMD rate than the majority (78%) with low increasing levels (increasing up to 1 month/year). Regarding post-AMI findings, constant high (~25-30 days/month) SA/DP levels within the first 3 months was associated with a 76% higher CMD rate, compared to constant low (0 days/month). A gradually decreasing post-AMI SA/DP pattern over a 12-month period suggested protective influences for CMD (HR?=?0.80). This is the first study to demonstrate that pre- and post-AMI work disability patterns are associated with subsequent CMD risk in AMI patients. Work disability patterns should be considered as an indicator of AMI prognosis in terms of CMD risk.

SUBMITTER: Bokenberger K

PROVIDER: S-EPMC6834568 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Work disability patterns before and after incident acute myocardial infarction and subsequent risk of common mental disorders: A Swedish cohort study.

Bokenberger K K Rahman S S Wang M M Vaez M M Dorner T E TE Helgesson M M Ivert T T Mittendorfer-Rutz E E

Scientific reports 20191106 1

This study investigated the extent to which work disability patterns including sickness absence and disability pension (SA/DP) before and after acute myocardial infarction (AMI) were associated with subsequent common mental disorders (CMDs) such as depression and anxiety in AMI patients without previous CMD. Total 11,493 patients 26-64 years with incident AMI during 2008-10 were followed up for CMD (measured as antidepressant prescription) through 2013. Four SA/DP trajectory groups during the 3- ...[more]

PMID: 31695106

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Project description:BackgroundLabour-market marginalisation (LMM) and common mental disorders (CMDs) are serious societal problems. The aims were to describe trajectories of LMM (both work disability and unemployment) among young adults with and without CMDs, and to elucidate the characteristics associated with these trajectories.MethodsThe study was based on Swedish registers and consisted of all individuals 19-30 years with an incident diagnosis of a CMD in year 2007 (n = 7245), and a matched comparison group of individuals without mental disorders during the years 2004-07 (n = 7245). Group-based trajectory models were used to describe patterns of LMM both before, and after the incident diagnosis of a CMD. Multinomial logistic regressions investigated the associations between sociodemographic and medical covariates and the identified trajectories.ResultsTwenty-six percent (n = 1859) of young adults with CMDs followed trajectories of increasing or constant high levels of work disability, and 32 % (n = 2302) followed trajectories of increasing or constant high unemployment. In the comparison group, just 9 % (n = 665) followed increasing or constant high levels of work disability and 21 % (n = 1528) followed trajectories of increasing or constant high levels of unemployment. A lower share of young adults with CMDs followed trajectories of constant low levels of work disability (n = 4546, 63%) or unemployment (n = 2745, 38%), compared to the level of constant low work disability (n = 6158, 85%) and unemployment (n = 3385, 50%) in the comparison group. Remaining trajectories were fluctuating or decreasing. Around 50% of young adults with CMDs had persistent levels of LMM at the end of follow-up. The multinomial logistic regression revealed that educational level and comorbid mental disorders discriminated trajectories of work disability, while educational level, living area and age determined differences in trajectories of unemployment (R2difference = 0.02-0.05, p < 0.001).ConclusionsA large share, nearly 50%, of young adults with CMDs, substantially higher than in the comparison group of individuals without mental disorders, display increasing or high persistent levels of either work disability or unemployment throughout the follow-up period. Low educational level, comorbidity with other mental disorders and living in rural areas were factors that increased the probability for LMM.

Project description:BackgroundWith the spread of COVID-19 pandemic, there have been reports on its impact on incident myocardial infarction (MI) emanating from studies with small to modest sample sizes. We therefore examined the incidence of MI in a very large population health cohort with COVID-19 using a methodology which integrates the dynamicity of prior comorbid history. We used two approaches, i.e. main effect modelling and a machine learning (ML) methodology, accounting for the complex dynamic relationships among comorbidity and other variables.MethodsWe studied a very large prospective 18-90-year US population, including 4,289,481 patients from medical databases in a 12-month investigation of those with/without newly incident COVID-19 cases together with a 2-year comorbid profile in the baseline period. Incident MI outcomes were examined in relationship to diverse multimorbid conditions, COVID-19 status and demographic variables-with ML accounting for the dynamic nature of changing multimorbidity risk factors.ResultsMultimorbidity, defined as a composite of cardiometabolic/noncardiometabolic comorbid profile, significantly contributed to the onset of confirmed COVID-19 cases. Furthermore, a main effect model (C-index value 0.932; 95%CI 0.930-0.934) had medium to large effect sizes with incident MI outcomes in a COVID-19 cohort for the classic multimorbid conditions in medical history profile which includes prior coronary artery disease (OR 4.61 95%CI 4.49-4.73); hypertension (OR 3.55 95%CI 3.55-3.83); congestive heart failure (2.31 95%CI 2.24-2.37); valvular disease (1.43 95%CI 1.39-1.47); stroke (1.30 95%CI 1.26-1.34); and diabetes (1.26 95%CI 1.23-1.34). COVID-19 status (1.86 95%CI 1.79-1.93) contributed an independent large size risk effect for incident MI. The ML algorithm demonstrated better discriminatory validity than the main effect model (training: C-index 0.949, 95%CI 0.948-0.95; validation: C-index 0.949, 95%CI 0.948-0.95). Calibration of the ML-based formulation was satisfactory and better than the main effect model. Decision curve analysis demonstrated that the ML clinical utility was better than the 'treat all' strategy and the main effect model. The ML logistic regression model was better than the neural network algorithm.ConclusionThe very large investigation conducted herein confirmed the importance of cardiometabolic and noncardiometabolic multimorbidity in increasing vulnerabilities to a higher risk of COVID-19 infections. Furthermore, the presence of COVID-19 infections increased incident MI complications both in terms of independent effects and interactions with the multimorbid profile and age.

Dataset Information

Work disability patterns before and after incident acute myocardial infarction and subsequent risk of common mental disorders: A Swedish cohort study.

Publications

Work disability patterns before and after incident acute myocardial infarction and subsequent risk of common mental disorders: A Swedish cohort study.

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