Dataset Information

Post-traumatic stress disorder and major depression in conflict-affected populations: an epidemiological model and predictor analysis.

ABSTRACT:

Background

Despite significant research examining mental health in conflict-affected populations we do not yet have a comprehensive epidemiological model of how mental disorders are distributed, or which factors influence the epidemiology in these populations. We aim to derive prevalence estimates specific for region, age and sex of major depression, and PTSD in the general populations of areas exposed to conflict, whilst controlling for an extensive range of covariates.

Methods

A systematic review was conducted to identify epidemiological estimates of depression and PTSD in conflict-affected populations and potential predictors. We analyse data using Bayesian meta-regression techniques.

Results

We identified 83 studies and a list of 34 potential predictors. The age-standardised pooled prevalence of PTSD was 12.9% (95% UI 6.9-22.9), and major depression 7.6% (95% UI 5.1-10.9) - markedly lower than estimated in previous research but over two-times higher than the mean prevalence estimated by the Global Burden of Disease Study [3.7% (95% UI 3.0-4.5) and 3.5% (95% UI 2.9-4.2) for anxiety disorders and MDD, respectively]. The age-patterns reveal sharp prevalence inclines in the childhood years. A number of ecological variables demonstrated associations with prevalence of both disorders. Symptom scales were shown to significantly overestimate prevalence of both disorders. Finding suggests higher prevalence of both disorders in females.

Conclusion

This study provides, for the first time, age-specific estimates of PTSD and depression prevalence adjusted for an extensive range of covariates and is a significant advancement on our current understanding of the epidemiology in conflict-affected populations.

SUBMITTER: Charlson FJ

PROVIDER: S-EPMC5314754 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Post-traumatic stress disorder and major depression in conflict-affected populations: an epidemiological model and predictor analysis.

Charlson F J FJ Flaxman A A Ferrari A J AJ Vos T T Steel Z Z Whiteford H A HA

Global mental health (Cambridge, England) 20160210

<h4>Background</h4>Despite significant research examining mental health in conflict-affected populations we do not yet have a comprehensive epidemiological model of how mental disorders are distributed, or which factors influence the epidemiology in these populations. We aim to derive prevalence estimates specific for region, age and sex of major depression, and PTSD in the general populations of areas exposed to conflict, whilst controlling for an extensive range of covariates.<h4>Methods</h4>A ...[more]

PMID: 28596873

Similar Datasets

Project description:BackgroundFrom 1986 to 2006, Northern Uganda experienced an atrocious civil war between the Lord's Resistance Army (LRA) and the Ugandan government. Acholi people living in the region continue to be impacted by trauma sequelae of the war and a wide range of daily stressors including poverty, hunger, and high rates of HIV infection. To date, there is a dearth of gender-differentiated mental health research in this post-conflict setting. The current study aimed to estimate the prevalence of probable post-traumatic stress disorder (PTSD) and depression in three districts most affected by the Northern Ugandan conflict and examine socio-structural, war-related, and sexual vulnerability factors associated with mental health.MethodsCango Lyec (Healing the Elephant) is an open cohort study involving participants from eight randomly selected communities in Amuru, Gulu, and Nwoya districts of Northern Uganda. Between November 2011 and July 2012, the baseline cohort (N = 2,458) completed the Harvard Trauma Questionnaire (HTQ) and Hopkins Symptom Checklist-25 (HSCL-25) for screening PTSD and depression, in addition to a detailed questionnaire assessing socio-demographic-behavioral characteristics. Baseline categorical variables were compared between males and females using Fisher's exact test. Multivariate logistic regression was used to model correlates of probable PTSD and depression. All analyses were stratified by gender.ResultsThe overall prevalence of probable PTSD and depression was 11.7% and 15.2% respectively. Among former abductees, the prevalence was 23.2% for probable PTSD and 26.6% for probable depression. Women were significantly more likely to experience mental distress than men. Factors associated with mental distress included wartime trauma (adjusted odds ratios ranging from 2.80 to 7.19), experiences of abduction (adjusted odds ratios ranging from 1.97 to 3.03), and lack of housing stability and safety (adjusted odds ratios ranging from 1.95 to 4.59). Additional risk factors for women included HIV infection (AOR=1.90; 95% CI: 1.29-2.80), sexual abuse in the context of war (AOR=1.58; 95% CI: 1.02-2.45), and intimate partner violence (AOR=2.45; 95% CI: 1.07-5.63).ConclusionCango Lyec participants displayed lower than previously reported yet significant levels of probable PTSD and depression. Based on findings from this study, providing trauma-informed care, ensuring food and housing security, eliminating gender-based violence, and reintegrating former abductees remain important tasks to facilitate post-conflict rehabilitation in Northern Uganda.

Project description:BackgroundWith the rise of fragility, conflict and violence (FCV), understanding the prevalence and risk factors associated with mental disorders is beneficial to direct aid to vulnerable groups. To better understand mental disorders depending on the population and the timeframe, we performed a systematic review to investigate the aggregate prevalence of depression, anxiety and post-traumatic stress symptoms among both civilian and military population exposed to war.MethodsWe used MEDLINE (PubMed), Web of Science, PsycINFO, and Embase to identify studies published from inception or 1-Jan, 1945 (whichever earlier), to 31-May, 2022, to reporting on the prevalence of depression, anxiety and post-traumatic stress symptoms using structured clinical interviews and validated questionnaires as well as variables known to be associated with prevalence to perform meta-regression. We then used random-effects bivariate meta-analysis models to estimate the aggregate prevalence rate.ResultsThe aggregate prevalence of depression, anxiety and post-traumatic stress during times of conflict or war were 28.9, 30.7, and 23.5%, respectively. Our results indicate a significant difference in the levels of depression and anxiety, but not post-traumatic stress, between the civilian group and the military group respectively (depression 34.7 vs 21.1%, p < 0.001; anxiety 38.6 vs 16.2%, p < 0.001; post-traumatic stress: 25.7 vs 21.3%, p = 0.256). The aggregate prevalence of depression during the wars was 38.7% (95% CI: 30.0-48.3, I 2 = 98.1%), while the aggregate prevalence of depression post-wars was 29.1% (95% CI: 24.7-33.9, I 2 = 99.2%). The aggregate prevalence of anxiety during the wars was 43.4% (95% CI: 27.5-60.7, I 2 = 98.6%), while the aggregate prevalence of anxiety post-wars was 30.3% (95% CI: 24.5-36.9, I 2 = 99.2%). The subgroup analysis showed significant difference in prevalence of depression, and anxiety between the civilians and military group (p < 0.001).ConclusionThe aggregate prevalence of depression, anxiety and post-traumatic stress in populations experiencing FCV are 28.9, 30.7, and 23.5%, respectively. There is a significant difference in prevalence of depression and anxiety between civilians and the military personnels. Our results show that there is a significant difference in the prevalence of depression and anxiety among individuals in areas affected by FCV during the wars compared to after the wars. Overall, these results highlight that mental health in times of conflict is a public health issue that cannot be ignored, and that appropriate aid made available to at risk populations can reduce the prevalence of psychiatric symptoms during time of FCV.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=337486, Identifier 337486.

Dataset Information

Post-traumatic stress disorder and major depression in conflict-affected populations: an epidemiological model and predictor analysis.

Background

Methods

Results

Conclusion

Publications

Post-traumatic stress disorder and major depression in conflict-affected populations: an epidemiological model and predictor analysis.

Similar Datasets

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