scholarly journals Physical comorbidities in men with mood and anxiety disorders: a population-based study

BMC Medicine ◽  
2013 ◽  
Vol 11 (1) ◽  
Author(s):  
Livia Sanna ◽  
Amanda L Stuart ◽  
Julie A Pasco ◽  
Mark A Kotowicz ◽  
Michael Berk ◽  
...  
2014 ◽  
Vol 30 (11) ◽  
pp. 2413-2422 ◽  
Author(s):  
Mariane Ricardo Acosta Lopez Molina ◽  
Bárbara Spessato ◽  
Karen Jansen ◽  
Ricardo Pinheiro ◽  
Ricardo Silva ◽  
...  

This research aims to evaluate factors associated with the presence of comorbidities between mood and anxiety disorders in young adults aged 18 to 24 years, from Pelotas, Rio Grande do Sul State, Brazil. This was a cross-sectional, population-based study with a probabilistic sample by conglomerates. The Mini International Neuropsychiatric Interview (MINI) was used to assess mood and anxiety disorders. The prevalence of mental disorders in the sample (n = 1,561) was of 26.8% of which 9.7% had comorbidities between mood and anxiety disorders. The prevalence of comorbidities on mood and anxiety disorders is almost three times higher among women than men (p < 0.001). Lower education levels, socioeconomic status (p < 0.001) and a history of divorced parents (p < 0.050) was associated with comorbidities between mood and anxiety disorders. The main conclusion is that social factors are highly associated with comorbidities between mood and anxiety disorders. Prevention strategies on mental health should focus particularly on women in vulnerable social conditions.


2016 ◽  
Vol 12 ◽  
pp. P298-P298
Author(s):  
I. Fan Kuo ◽  
C. Andrew Basham ◽  
Heather Prior ◽  
Silvia Alessi-Severini ◽  
James Bolton ◽  
...  

2016 ◽  
Vol 12 ◽  
pp. P603-P603
Author(s):  
I fan Kuo ◽  
C. Andrew Basham ◽  
Heather Prior ◽  
Silvia Alessi-Severini ◽  
James Bolton ◽  
...  

2021 ◽  
Vol 30 ◽  
Author(s):  
Jordan Edwards ◽  
A. Demetri Pananos ◽  
Amardeep Thind ◽  
Saverio Stranges ◽  
Maria Chiu ◽  
...  

Abstract Aims There is currently no universally accepted measure for population-based surveillance of mood and anxiety disorders. As such, the use of multiple linked measures could provide a more accurate estimate of population prevalence. Our primary objective was to apply Bayesian methods to two commonly employed population measures of mood and anxiety disorders to make inferences regarding the population prevalence and measurement properties of a combined measure. Methods We used data from the 2012 Canadian Community Health Survey – Mental Health linked to health administrative databases in Ontario, Canada. Structured interview diagnoses were obtained from the survey, and health administrative diagnoses were identified using a standardised algorithm. These two prevalence estimates, in addition to data on the concordance between these measures and prior estimates of their psychometric properties, were used to inform our combined estimate. The marginal posterior densities of all parameters were estimated using Hamiltonian Monte Carlo (HMC), a Markov Chain Monte Carlo technique. Summaries of posterior distributions, including the means and 95% equally tailed posterior credible intervals, were used for interpretation of the results. Results The combined prevalence mean was 8.6%, with a credible interval of 6.8–10.6%. This combined estimate sits between Bayesian-derived prevalence estimates from administrative data-derived diagnoses (mean = 7.4%) and the survey-derived diagnoses (mean = 13.9%). The results of our sensitivity analysis suggest that varying the specificity of the survey-derived measure has an appreciable impact on the combined posterior prevalence estimate. Our combined posterior prevalence estimate remained stable when varying other prior information. We detected no problematic HMC behaviour, and our posterior predictive checks suggest that our model can reliably recreate our data. Conclusions Accurate population-based estimates of disease are the cornerstone of health service planning and resource allocation. As a greater number of linked population data sources become available, so too does the opportunity for researchers to fully capitalise on the data. The true population prevalence of mood and anxiety disorders may reside between estimates obtained from survey data and health administrative data. We have demonstrated how the use of Bayesian approaches may provide a more informed and accurate estimate of mood and anxiety disorders in the population. This work provides a blueprint for future population-based estimates of disease using linked health data.


2014 ◽  
Vol 46 (1) ◽  
pp. 150-157 ◽  
Author(s):  
Frank W. Paulus ◽  
Aline Backes ◽  
Charlotte S. Sander ◽  
Monika Weber ◽  
Alexander von Gontard

2013 ◽  
Vol 35 (4) ◽  
pp. 347-352 ◽  
Author(s):  
Thaíse Campos Mondin ◽  
Caroline Elizabeth Konradt ◽  
Taiane de Azevedo Cardoso ◽  
Luciana de Avila Quevedo ◽  
Karen Jansen ◽  
...  

2012 ◽  
Vol 43 (1) ◽  
pp. 73-84 ◽  
Author(s):  
J. Sareen ◽  
C. A. Henriksen ◽  
S.-L. Bolton ◽  
T. O. Afifi ◽  
M. B. Stein ◽  
...  

BackgroundAlthough it has been posited that exposure to adverse childhood experiences (ACEs) increases vulnerability to deployment stress, previous literature in this area has demonstrated conflicting results. Using a cross-sectional population-based sample of active military personnel, the present study examined the relationship between ACEs, deployment related stressors and mood and anxiety disorders.MethodData were analyzed from the 2002 Canadian Community Health Survey – Canadian Forces Supplement (CCHS-CFS; n = 8340, age 18–54 years, response rate 81%). The following ACEs were self-reported retrospectively: childhood physical abuse, childhood sexual abuse, economic deprivation, exposure to domestic violence, parental divorce/separation, parental substance abuse problems, hospitalization as a child, and apprehension by a child protection service. DSM-IV mood and anxiety disorders [major depressive disorder, post-traumatic stress disorder (PTSD), generalized anxiety disorder (GAD), panic attacks/disorder and social phobia] were assessed using the Composite International Diagnostic Interview (CIDI).ResultsEven after adjusting for the effects of deployment-related traumatic exposures (DRTEs), exposure to ACEs was significantly associated with past-year mood or anxiety disorder among men [adjusted odds ratio (aOR) 1.34, 99% confidence interval (CI) 1.03–1.73, p < 0.01] and women [aOR 1.37, 99% CI 1.00–1.89, p = 0.01]. Participants exposed to both ACEs and DRTEs had the highest prevalence of past-year mood or anxiety disorder in comparison to those who were exposed to either ACEs alone, DRTEs alone, or no exposure.ConclusionsACEs are associated with several mood and anxiety disorders among active military personnel. Intervention strategies to prevent mental health problems should consider the utility of targeting soldiers with exposure to ACEs.


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