Associations of Symptoms of ADHD and Oppositional Defiant Disorder (ODD) in Adolescence With Occupational Outcomes and Incomes in Adulthood.

OBJECTIVE: The purpose of this study was to examine the associations of ADHD and ODD symptoms in adolescence with occupational outcomes and incomes in adulthood within the Northern Finland Birth Cohort 1986 (NFBC1986). METHOD: ADHD symptoms were evaluated at ages 15 to 16 years using the Strengths and Weaknesses of ADHD symptoms and Normal Behaviors (SWAN) scale. ODD symptoms were assessed using a 7-point scale, like the SWAN assessment. RESULTS: Symptoms of ADHD and ADHD + ODD were associated with elevated rates of unemployment, increased sick days, and lower annual incomes compared to controls for both sexes. Symptoms of ODD were associated with higher unemployment and more sick days for males, although these associations did not reach statistical significance in their association with annual incomes. CONCLUSION: Symptoms of ADHD were associated with adverse occupational outcomes and lower incomes. Furthermore, symptoms of ODD were associated with occupational outcomes but not with incomes.

Productivity costs of schizophrenia spectrum and other psychotic disorders by friction cost and human capital methods: The Northern Finland Birth Cohort 1966.

PURPOSE: Psychotic disorders are associated with substantial productivity costs; however no previous studies have compared these between schizophrenia spectrum (SSD) and other psychotic disorders (OP). The human capital method (HCM) and the friction cost method (FCM) are the two most common approaches to assess productivity costs. The HCM focuses on employees' perspectives on the costs, whereas the FCM demonstrates employers' perspectives. Studies comparing these methods when estimating the productivity costs of psychoses are lacking. METHODS: Utilizing the Northern Finland Birth Cohort 1966 with linkages to national registers, we compared the adjusted productivity costs of SSD (n = 216) and OP (n = 217). The productivity costs were estimated from ages 18 to 53 including projections to statutory retirement age using the FCM and HCM. RESULTS: When estimated via the HCM, productivity losses were higher for SSD (€193,940) than for OP (€163,080). However, when assessed using the FCM, costs were significantly lower for SSD (€2,720) than for OP (€4,430). Productivity costs varied by sex and various clinical and occupational factors. CONCLUSION: This study highlights how productivity costs vary by psychosis diagnosis. These differences should be noted when planning interventions. The low FCM estimates indicate the need of interventions before or during the early phases of psychoses. From a societal perspective, interventions are needed, particularly for those with highest HCM productivity losses, such as males with SSD. Besides psychiatric services, the roles of social services, employment agencies and occupational health care should be considered when helping individuals with psychoses to working life.

Productivity costs of lifelong smoking-the Northern Finland Birth Cohort 1966 study.

BACKGROUND: Smoking is one of the leading causes of impaired health and mortality. Loss of paid and unpaid work and replacements due to morbidity and mortality result in productivity costs. Our aim was to investigate the productivity costs of lifelong smoking trajectories and cumulative exposure using advanced human capital method (HCM) and friction cost method (FCM). METHODS: Within the Northern Finland Birth Cohort 1966 (NFBC1966), 10 650 persons were followed from antenatal period to age 55 years. The life course of smoking behaviour was assessed with trajectory modelling and cumulative exposure with pack-years. Productivity costs were estimated with advanced HCM and FCM models by using detailed, national register-based data on care, disability, mortality, education, taxation, occupation and labour market. A two-part regression model was used to predict productivity costs associated with lifelong smoking and cumulative exposure. RESULTS: Of the six distinct smoking trajectories, lifetime smokers had the highest productivity costs followed by late starters, late adult quitters, young adult quitters and youth smokers. Never-smokers had the lowest productivity costs. The higher the number of pack-years, the higher the productivity costs. Uniform patterns were found in both men and women and when estimated with HCM and FCM. The findings were independent of other health behaviours. CONCLUSIONS: Cumulative exposure to smoking is more crucial to productivity costs than starting or ending age of smoking. This suggests that the harmful effects of smoking depend on dose and duration of smoking and are irrespective of age when smoking occurred.

Association of accelerometer-measured physical activity and midlife income: A Northern Finland Birth Cohort 1966 Study.

This study investigated the association between physical activity (PA) and midlife income. The population-based data comprised employed members of the Northern Finland Birth Cohort 1966 (N = 2797). Using binned scatterplots and polynomial regressions, we evaluated the association between accelerometer-measured moderate PA (MPA), vigorous PA (VPA), and moderate-to-vigorous PA (MVPA) at 46 years old and register-based income at 50 years old. The models were adjusted for sex, marital status, number of children, education, adolescent PA, occupational physical strenuousness, and time preference. We found MPA (p < 0.001), VPA (p < 0.05), and MVPA (p < 0.001) to associate curvilinearly with income. In subgroup analyses, a curvilinear association was found between MPA (p < 0.01) and MVPA (p < 0.01) among those with physically strenuous work, VPA among all females (p < 0.01) and females with physically light work (p < 0.01), and MPA and MVPA among all males and males with physically strenuous work (p < 0.05; p < 0.01; p < 0.05; p < 0.05, respectively) and income. The highest income benefits occurred at PA volumes higher than current PA guidelines. Linear associations between PA and income were found among females for MPA (p < 0.05) and MVPA (p < 0.05), among those with physically light work for MPA (p < 0.05), VPA (p < 0.05), and MVPA (p < 0.05), and among females with physically strenuous work for VPA (p < 0.05). We conclude that PA up to the current recommended level is associated with income, but MPA exceeding 505.4 min/week, VPA exceeding 216.4 min/week, and MVPA exceeding 555.0 min/week might have a negative association with income.

The Individual-Level Productivity Costs of Physical Inactivity.

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.

Did the Finnish depression of the early 1990s have a silver lining? The effect of unemployment on long-term physical activity.

This paper studies the impact of long-term unemployment on physical activity. We examined the effects 6 and 15 years following a severe business cycle downturn in Finland over the period 1991-1994. The study sample comprised residents of Northern Finland. The unemployed individuals were 23-26 years old during the downturn. Physical activity, measured by MET minutes and meeting WHO guidelines, was higher 15 years later among those people who experienced the longest periods of unemployment in 1991-1994. Physical activity was somewhat lower among people with relatively shorter periods of unemployment.

Leisure-time physical activity is associated with socio-economic status beyond income - Cross-sectional survey of the Northern Finland Birth Cohort 1966 study.

We apply neoclassical economic modelling augmented with behavioral aspects to provide a detailed empirical investigation into indicators of socio-economic status (SES) as determinants of leisure-time physical activity. We utilize the data from the Northern Finland Birth Cohort 1966 obtained at the most recent time point during 2012-2014 (response rate 67 %), at which time the participants were approximately 46 years old. Our final study sample consists of 3,335 employed participants (1520 men, 1815 women; 32.3 % of the target population). We apply logistic regression methods for estimating how the probability of being physically active is related to various indicators of socio-economic status, taking into account physical activity at work and individual lifestyle, family- and health-related factors. Overall, our findings show that belonging to a higher socio-economic group, whether defined by income level, educational attainment, or occupational status, is associated with higher leisure-time physical activity. However, when we analyze different socio-economic groups, defined in terms of education, income and occupation, separately, we find that income is not a significant determinant of leisure-time physical activity within any of the particular SES groups. Further, we find that leisure-time physical activity is negatively associated with higher screen time (i.e., watching TV and sitting at a computer), and other aspects of unhealthy lifestyle, and positively associated with self-assessed health. In addition, we note that proxies for individual motivational factors and childhood physical activity, such as the grade point average and the grade achieved in physical education when leaving basic education, are strongly correlated with leisure-time physical activity in middle age among men, but not among women. Our results are in line with behavioral economics reasoning that social comparisons and environments affect behaviors. We emphasize the importance of considering behavioral economic factors when designing policies to promote physical activity.

Economic crises and suicides between 1970 and 2011: time trend study in 21 developed countries.

BACKGROUND: Existing research on the relationship between economic recessions and suicides has almost completely concentrated on the most recent global financial crisis (2008). We provide the most comprehensive explanation to date of how different types of economic/financial crises since 1970 have affected suicides in developed countries. METHODS: Negative binomial regressions were used to estimate what the suicide rates would have been during and 1 year after each crisis began in 21 Organisation for Economic Co-operation and Development countries from 1970 to 2011 if the suicide rates had followed the pre-crisis trends. RESULTS: We found that every economic/financial crisis since 1970, except the European Exchange Rate Mechanism crisis in 1992, led to excess suicides in developed countries. Among males, the excess suicide rate (per 100 000 persons) varied from 1.1 (95% CI 0.7 to 1.5) to 9.5 (7.6 to 11.2) and, among females, from 0 to 2.4 (1.9 to 2.9). For both sexes, suicides increased mostly due to stock market crashes and banking crises. In terms of actual numbers, the post-1969 economic/financial crises caused >60 000 excess suicides in the 21 developed countries. The Asian financial crisis in 1997 was the most damaging crisis when assessed based on excess suicides. CONCLUSIONS: Evidence indicates that, when considered in terms of effects on suicide mortality, the most recent global financial crisis is not particularly severe compared with previous global economic/financial crises. The distinct types of crises (ie, banking, currency and inflation crises, and stock market crashes) have different effects on suicide.