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BackgroundSeveral studies have reported weak associations between religious or spiritual belief and psychological health. However, most have been cross-sectional surveys in the USA, limiting inference about generalizability. An international longitudinal study of incidence of major depression gave us the opportunity to investigate this relationship further.MethodData were collected in a prospective cohort study of adult general practice attendees across seven countries. Participants were followed at 6 and 12 months. Spiritual and religious beliefs were assessed using a standardized questionnaire, and DSM-IV diagnosis of major depression was made using the Composite International Diagnostic Interview (CIDI). Logistic regression was used to estimate incidence rates and odds ratios (ORs), after multiple imputation of missing data.ResultsThe analyses included 8318 attendees. Of participants reporting a spiritual understanding of life at baseline, 10.5% had an episode of depression in the following year compared to 10.3% of religious participants and 7.0% of the secular group (p < 0.001). However, the findings varied significantly across countries, with the difference being significant only in the UK, where spiritual participants were nearly three times more likely to experience an episode of depression than the secular group [OR 2.73, 95% confidence interval (CI) 1.59–4.68]. The strength of belief also had an effect, with participants with strong belief having twice the risk of participants with weak belief. There was no evidence of religion acting as a buffer to prevent depression after a serious life event.ConclusionsThese results do not support the notion that religious and spiritual life views enhance psychological well-being. [ABSTRACT FROM PUBLISHER]

BackgroundThere are no risk models for the prediction of anxiety that may help in prevention. We aimed to develop a risk algorithm for the onset of generalized anxiety and panic syndromes.MethodFamily practice attendees were recruited between April 2003 and February 2005 and followed over 24 months in the UK, Spain, Portugal and Slovenia (Europe4 countries) and over 6 months in The Netherlands, Estonia and Chile. Our main outcome was generalized anxiety and panic syndromes as measured by the Patient Health Questionnaire. We entered 38 variables into a risk model using stepwise logistic regression in Europe4 data, corrected for over-fitting and tested it in The Netherlands, Estonia and Chile.ResultsThere were 4905 attendees in Europe4, 1094 in Estonia, 1221 in The Netherlands and 2825 in Chile. In the algorithm four variables were fixed characteristics (sex, age, lifetime depression screen, family history of psychological difficulties); three current status (Short Form 12 physical health subscale and mental health subscale scores, and unsupported difficulties in paid and/or unpaid work); one concerned country; and one time of follow-up. The overall C-index in Europe4 was 0.752 [95% confidence interval (CI) 0.724–0.780]. The effect size for difference in predicted log odds between developing and not developing anxiety was 0.972 (95% CI 0.837–1.107). The validation of predictA resulted in C-indices of 0.731 (95% CI 0.654–0.809) in Estonia, 0.811 (95% CI 0.736–0.886) in The Netherlands and 0.707 (95% CI 0.671–0.742) in Chile.ConclusionsPredictA accurately predicts the risk of anxiety syndromes. The algorithm is strikingly similar to the predictD algorithm for major depression, suggesting considerable overlap in the concepts of anxiety and depression. [ABSTRACT FROM PUBLISHER]

Background: The reduction of major depression incidence is a public health challenge., Aim: To develop an algorithm to estimate the risk of occurrence of major depression in patients attending primary health centers (PHC)., Material and Methods: Prospective cohort study of a random sample of 2832 patients attending PHC centers in Concepción, Chile, with evaluations at baseline, six and twelve months. Thirty nine known risk factors for depression were measured to build a model, using a logistic regression. The algorithm was developed in 2,133 patients not depressed at baseline and compared with risk algorithms developed in a sample of 5,216 European primary care attenders. The main outcome was the incidence of major depression in the follow-up period., Results: The cumulative incidence of depression during the 12 months follow up in Chile was 12%. Eight variables were identified. Four corresponded to the patient (gender, age, depression background and educational level) and four to patients' current situation (physical and mental health, satisfaction with their situation at home and satisfaction with the relationship with their partner). The C-Index, used to assess the discriminating power of the final model, was 0.746 (95% confidence intervals (CI = 0,707-0,785), slightly lower than the equation obtained in European (0.790 95% CI = 0.767-0.813) and Spanish attenders (0.82; 95% CI = 0.79-0.84)., Conclusions: Four of the factors identified in the risk algorithm are not modifiable. The other two factors are directly associated with the primary support network (family and partner). This risk algorithm for the incidence of major depression provides a tool that can guide efforts towards design, implementation and evaluation of effectiveness of interventions to prevent major depression.