ObjectivesThis is the first general population study to evaluate whether evening chronotypes (E) have poorer work ability (WA) and higher probability for early disability pensions (DPs) than morning types (M) in middle age.MethodsAmong non-retired individuals (n=5831; 2672 men, 3159 women) of the Northern Finland Birth Cohort 1966, chronotype was determined at the age of 46 years with shortened Morningness–Eveningness Questionnaires in 2012. The outcomes were poor WA in 2012, indicated by scores 0–7/10 of Work Ability Score, and registered emergence of DPs in 2013–2016. Multivariate logistic and Cox regression analyses were separately adjusted for factors related to sleep, health and behaviours, sociodemographic and economic factors, or working times.ResultsE-types represented 10% (n=264) of men and 12% (n=382) of women. Compared with M-types, the unadjusted ORs with 95% CIs of poor WA for E-type men and women were 2.24 (95% CI 1.62 to 3.08) and 2.33 (95% CI 1.74 to 3.10), respectively. The odds remained statistically significant and approximately twofold in all separate adjustment models tested. During 2013–2016, 8 (3.0%) E-type men and 10 (2.6%) E-type women were granted DP, which, compared with M-types, represented a higher HR that was statistically significant for men (HR 3.12, 95% CI 1.27 to 7.63) and remained significant except when multiple sleep variables or working times were adjusted for.ConclusionsEveningness appears a previously unrecognised risk factor for poor WA and early disability. We suggest that individual chronotype be considered in attempts to lengthen work careers.

Background Productivity costs result from loss of paid and unpaid work and replacements due to morbidity and mortality. They are usually assessed in health economic evaluations with human capital method (HCM) or friction cost method (FCM). The methodology for estimating lost productivity is an area of considerable debate. Objective To compare traditional and adjusted HCM and FCM productivity cost estimates among young stroke patients. Methods The Northern Finland Birth Cohort 1966 was followed until the age of 50 to identify all 339 stroke patients whose productivity costs were estimated with traditional, occupation-specific and adjusted HCM and FCM models by using detailed, national register-based data on care, disability, mortality, education, taxation and labour market. Results Compared to traditional HCM, taking into account occupational class, national unemployment rate, disability-free life expectancy and decline in work ability, the productivity cost estimate decreased by a third, from €255,960 to €166,050. When traditional FCM was adjusted for occupational class and national unemployment rate, the estimate more than doubled from €3,040 to €7,020. HCM was more sensitive to adjustments for discount rate and wage growth rate than FCM. Conclusions This study highlights the importance of adjustments of HCM and FCM. Routine register-based data can be used for accurate productivity cost estimates of health shocks.

Purpose: This study estimated the long-term individual-level productivity costs of physical inactivity. Methods: The data were drawn from the Northern Finland Birth Cohort 1966, to which the productivity cost variables (sick leaves and disability pensions) from Finnish registries were linked. Individuals (N = 6261) were categorized into physical activity groups based on their level of physical activity, which was measured in three ways: 1) self-reported leisure-time moderate-to vigorous-intensity physical activity (MVPA) at 46 yr old, 2) longitudinal self-reported leisure-time MVPA at 31-46 yr old, and 3) accelerometer-measured overall MVPA at 46 yr old. The human capital approach was applied to calculate the observed costs (years 2012-2020) and the expected costs (years 2012-2031). Results: The results showed that the average individual-level productivity costs were higher among physically inactive compared with the costs among physically active. The results were consistent regardless of the measurement type of physical activity or the period used. On average, the observed long-term productivity costs among physically inactive individuals were €1900 higher based on self-reported MVPA, €1800 higher based on longitudinal MVPA, and €4300 higher based on accelerometer-measured MVPA compared with the corresponding productivity costs among physically active individuals. The corresponding difference in the expected costs was €2800, €1200, and €8700, respectively. Conclusions: The results provide evidence that productivity costs differ according to an individual's level of physical activity. Therefore, investments in physical activity may decrease not only the direct healthcare costs but also the indirect productivity costs paid by the employee, the employer, and the government.

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Background Severe health events may lead to reduced income among survivors. Importantly, individuals’ risks for both severe health events and for lower income are shaped by early life course. Our aim was to consider early-life factors in determining lost individual income after stroke, heart attack and cancer between ages 18 and 50. Methods A population-based Northern Finland Birth Cohort 1966 (N = 12 058) was used. Early-life factors were collected since mid-pregnancy until age 16 years and used to match all persons with stroke, heart attack, or cancer (n = 995) with four controls. Registered annual individual income development 15 years before and after the event was compared between cases and propensity score matched controls using time-to-event mixed models, stratified for sex. Results Compared to controls, a new decreasing income trend emerged among women after stroke (logarithmic income per time −0.54; 95% CI −0.88 to −0.20), whereas men getting stroke showed declining earnings already by the time of the event, further declining after stroke (−1.00, −1.37 to −0.63). Getting heart attack was associated with a new declining trend both in women (−0.68; −1.28 to −0.09) and men (−0.69, −1.05 to −0.32). Income declined also among control men (−0.24, −0.34 to −0.14), who had higher income but were less educated than control women. Conclusions Stroke and heart attack but not cancer have exogenous deleterious effects on individual economy, independently of early-life factors. The effects accelerate by time. Negative income trend in control men shows that severe health events do not explain all decrease in income.