Predictors of new-onset depressive disorders - Results from the longitudinal Finnish Health 2011 Study.

BACKGROUND: Identifying risk factors for depression is important for understanding etiological mechanisms and targeting preventive efforts. No prior studies have compared risk factors of dysthymia and major depressive disorder (MDD) in a longitudinal setting. METHODS: Predictors of new-onset MDD and dysthymia were examined in a longitudinal general population study (Health 2000 and 2011 Surveys, BRIF8901). 4057 persons free of depressive disorders at baseline were followed up for 11 years. DSM-IV MDD and dysthymia were diagnosed with the Composite International Diagnostic Interview. RESULTS: 126 persons (4.4%, 95%CI 3.6-5.2) were diagnosed with MDD or dysthymia at follow-up. Predictors of new-onset depressive disorders were younger age (adjusted OR 0.97, 95%CI 0.95-0.99 per year), female gender (aOR 1.46, 95%CI 1.01-2.12), multiple childhood adversities (aOR 1.76, 95%CI 1.10-2.83), low trust dimension of social capital (aOR 0.58, 95%CI 0.36-0.96 for high trust), baseline anxiety disorder (aOR 2.75, 95%CI 1.36-5.56), and baseline depressive symptoms (aOR 1.65, 95%CI 1.04-2.61 for moderate and aOR 2.49, 95%CI 1.20-5.17 for severe symptoms). Risk factors for MDD were younger age, female gender, anxiety disorder and depressive symptoms, whereas younger age, multiple childhood adversities, low trust, and having 1-2 somatic diseases predicted dysthymia. LIMITATIONS: We only had one follow-up point at eleven years, and did not collect information on the subjects' health during the follow-up period. CONCLUSIONS: Persons with subclinical depressive symptoms, anxiety disorders, low trust, and multiple childhood adversities have a higher risk of depressive disorders. Predictors of MDD and dysthymia appear to differ. This information can be used to target preventive efforts and guide social policies.

Prognosis of depressive disorders in the general population- results from the longitudinal Finnish Health 2011 Study.

BACKGROUND: Depressive disorders are among the most pressing public health challenges worldwide. Yet, not enough is known about their long-term outcomes. This study examines the course and predictors of different outcomes of depressive disorders in an eleven-year follow-up of a general population sample. METHODS: In a nationally representative sample of Finns aged 30 and over (BRIF8901), major depressive disorder (MDD) and dysthymia were diagnosed with the Composite International Diagnostic Interview (M-CIDI) in 2000. The participants were followed up in 2011 (n=5733). Outcome measures were diagnostic status, mortality, depressive symptoms and health-related quality of life. Multiple imputation (MI) was used to account for nonresponse. RESULTS: At follow-up, 33.8% of persons with baseline MDD and 42.6% with baseline dysthymia received a diagnosis of depressive, anxiety or alcohol use disorder. Baseline severity of disorder, measured by the Beck Depression Inventory, predicted both persistence of depressive disorder and increased mortality risk. In addition, being never-married, separated or widowed predicted persistence of depressive disorders, whereas somatic and psychiatric comorbidity, childhood adversities and lower social capital did not. Those who received no psychiatric diagnosis at follow-up still had residual symptoms and lower quality of life. LIMITATIONS: We only had one follow-up point at eleven years, and did not collect information on the subjects' health during the follow-up period. CONCLUSIONS: Depressive disorders in the general population are associated with multiple negative outcomes. Severity of index episode is the strongest predictor of negative outcomes. More emphasis should be placed on addressing the long-term consequences of depression.

Social capital and all-cause mortality among Finnish men and women aged 30-79.

BACKGROUND: More knowledge is needed about how various dimensions of social capital associate with mortality either independently or mediated by other factors. In this cohort study, individual-level social capital was assessed as a possible predictor of all-cause mortality. METHODS: A 9-year mortality follow-up was conducted for participants of a nationally representative Health 2000 Survey carried out in 2000-01. The survey included a personal interview, self-administered questionnaires and a health examination. Response rates to different items varied between 80 and 88%. Due to the item non-response, missing values were replaced by using multiple imputation. Participants (N = 6377) were 30-79 years old at the baseline. During the follow-up period, 245 women and 340 men died. Cox regression models were used to assess the association between social capital and mortality. We analysed three dimensions of social capital: social support, social participation and trust. Their association with the risk of death was adjusted for several socio-demographic factors, health behaviours, health and biological risk factors. RESULTS: Unactive social participation was associated with higher mortality risk even when adjusting for the other factors. The association was stronger among men [hazard ratio (HR) = 1.56] than women (HR = 1.42). The other two dimensions of social capital were associated with mortality when only age was adjusted for, but this association disappeared when social participation was included in the explanatory model. CONCLUSIONS: Active social participation protects against early death. This association is partly mediated through health behaviour and to a minor extent also through health.

Social capital, health behaviours and health: a population-based associational study.

BACKGROUND: Social capital is associated with health behaviours and health. Our objective was to explore how different dimensions of social capital and health-related behaviours are associated, and whether health behaviours mediate this association between social capital and self-rated health and psychological well-being. METHODS: We used data from the Health 2000 Survey (n=8028) of the adult population in Finland. The response rate varied between 87% (interview) and 77% (the last self-administered questionnaire). Due to item non-response, missing values were replaced using multiple imputation. The associations between three dimensions of social capital (social support, social participation and networks, trust and reciprocity) and five health behaviours (smoking, alcohol use, physical activity, vegetable consumption, sleep) were examined by using logistic regression and controlling for age, gender, education, income and living arrangements. The possible mediating role of health behaviours in the association between social capital and self-rated health and psychological well-being was also analysed with a logistic regression model. RESULTS: Social participation and networks were associated with all of the health behaviours. High levels of trust and reciprocity were associated with non-smoking and adequate duration of sleep, and high levels of social support with adequate duration of sleep and daily consumption of vegetables. Social support and trust and reciprocity were independently associated with self-rated health and psychological well-being. Part of the association between social participation and networks and health was explained by physical activity. CONCLUSIONS: Irrespective of their social status, people with higher levels of social capital - especially in terms of social participation and networks - engage in healthier behaviours and feel healthier both physically and psychologically.

Social capital as a determinant of self-rated health and psychological well-being.

OBJECTIVE: To examine whether specific dimensions of social capital are related to self-rated health and psychological well-being. METHODS: Cross-sectional data from a health survey representing the adult Finnish population (N = 8,028) were used. Logistic regression analysis was used to reveal and quantify the possible associations between three dimensions of social capital (social support; social participation and networks; trust and reciprocity) and two general health indicators (self-rated health and psychological well-being). The roles of age, gender, education, living arrangements, income, type of region, functional capacity, and long-standing illness were also assessed. RESULTS: Good self-rated health was associated with high levels of social participation and networks and trust and reciprocity, but social support did not remain statistically significant after adjustment for socio-demographic factors, long-standing illness, and functional capacity. The association between social support and psychological well-being was explained by the other two dimensions of social capital. The strong positive association between trust and psychological well-being persisted after controlling for all the other factors in our model. CONCLUSIONS: Our findings suggest that trust and reciprocity and social participation and networks contribute to good self-rated health and psychological well-being.