RESUMO
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.
Assuntos
Algoritmos , Transtorno Depressivo Maior/epidemiologia , Atenção Primária à Saúde/estatística & dados numéricos , Adolescente , Adulto , Idoso , Chile/epidemiologia , Transtorno Depressivo Maior/diagnóstico , Métodos Epidemiológicos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Fatores Socioeconômicos , Adulto JovemRESUMO
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.
Assuntos
Adolescente , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Adulto Jovem , Algoritmos , Transtorno Depressivo Maior/epidemiologia , Atenção Primária à Saúde/estatística & dados numéricos , Chile/epidemiologia , Transtorno Depressivo Maior/diagnóstico , Métodos Epidemiológicos , Fatores SocioeconômicosRESUMO
Unemployment is known to be associated with poor mental health, but it is not clear how strongly unemployment leads to onset of diagnosed clinical depression (causation), or if depression raises the risks of becoming unemployed (health selection), or indeed if both pathways operate. We therefore investigate the direction of associations between clinical depression and unemployment in a cross-cultural prospective cohort study. 10,059 consecutive general practice attendees (18-75 years) were recruited from six European countries and Chile between 2003 and 2004 and followed up at six, 12 and (in a subset) 24 months. The analysis sample was restricted to 3969 men and women who were employed or unemployed and seeking employment and had data on depression measures. The outcomes were depressive episodes, assessed using the Depression Section of the Composite International Diagnostic Interview (CIDI) and self-reported employment status. Among 3969 men and women with complete data on depression and unemployment, 10% (n = 393) had depression symptoms and a further 6% (n = 221) had major depression at 12 months. 11% (n = 423) of the sample were unemployed by 6 months. Participants who became unemployed between baseline and 6 months compared to those employed at both times had an adjusted relative risk ratio for 12-month depression of 1.58 (95% Confidence Interval 0.76, 3.27). Participants with depression at baseline and 6 months compared to neither time had an odds ratio for 6-month unemployment of 1.58 (95% Confidence Interval 0.97, 2.58). We found evidence that causation and (to a lesser extent) health selection raise the prevalence of depression in the unemployed. Unemployed adults are at particular risk for onset of major clinical depression and should be offered extra services or screened. Given the trend for adults with depression to perhaps be at greater risk of subsequent unemployment, employees with depressive symptoms should also be supported at work as a precautionary principle.
Assuntos
Transtorno Depressivo Maior/epidemiologia , Desemprego/psicologia , Adolescente , Adulto , Fatores Etários , Idoso , Chile/epidemiologia , Comparação Transcultural , Europa (Continente)/epidemiologia , Feminino , Medicina Geral/estatística & dados numéricos , Humanos , Entrevistas como Assunto , Masculino , Pessoa de Meia-Idade , Prevalência , Estudos Prospectivos , Fatores de Risco , Fatores Sexuais , Desemprego/estatística & dados numéricos , Adulto JovemRESUMO
BACKGROUND: Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. METHODS: A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. RESULTS: 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). CONCLUSIONS: The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.