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There is increasing evidence that domestic violence (DV) is an important risk factor for suicidal behaviour. The level of risk and its contribution to the overall burden of suicidal behaviour among men and women has not been quantified in South Asia. We carried out a large case-control study to examine the association between DV and self-poisoning in Sri Lanka.
Cases (N = 291) were patients aged ⩾18 years, admitted to a tertiary hospital in Kandy Sri Lanka for self-poisoning. Sex and age frequency matched controls were recruited from the hospital's outpatient department (N = 490) and local population (N = 450). Exposure to DV was collected through the Humiliation, Afraid, Rape, Kick questionnaire. Multivariable logistic regression models were conducted to estimate the association between DV and self-poisoning, and population attributable fractions were calculated.
Exposure to at least one type of DV within the previous 12 months was strongly associated with self-poisoning for women [adjusted OR (AOR) 4.08, 95% CI 1.60–4.78] and men (AOR 2.52, 95% CI 1.51–4.21), compared to those reporting no abuse. Among women, the association was strongest for physical violence (AOR 14.07, 95% CI 5.87–33.72), whereas among men, emotional abuse showed the highest risk (AOR 2.75, 95% CI 1.57–4.82). PAF% for exposure to at least one type of DV was 38% (95% CI 32–43) in women and 22% (95% CI 14–29) in men.
Multi-sectoral interventions to address DV including enhanced identification in health care settings, community-based strategies, and integration of DV support and psychological services may substantially reduce suicidal behaviour in Sri Lanka.
Self-harm is a significant public health issue, and both our understanding and ability to predict adverse outcomes are currently inadequate. The current study explores how preventative efforts could be aided through short-term prediction and modelling of risk factors for self-harm.
Patients (72% female, Mage = 40.3 years) within an inpatient psychiatric facility self-reported their psychological distress, interpersonal circumstances, and wish to live and die on a daily basis during 3690 unique admissions. Hierarchical logistic regressions assessed whether daily changes in self-report and history of self-harm could predict self-harm, with machine learning used to train and test the model. To assess interrelationships between predictors, network and cross-lagged panel models were performed.
Increases in a wish to die (β = 1.34) and psychological distress (β = 1.07) on a daily basis were associated with increased rates of self-harm, while a wish to die on the day prior [odds ratio (OR) 3.02] and a history of self-harm (OR 3.02) was also associated with self-harm. The model detected 77.7% of self-harm incidents (positive predictive value = 26.6%, specificity = 79.1%). Psychological distress, wish to live and die, and interpersonal factors were reciprocally related over the prior day.
Short-term fluctuations in self-reported mental health may provide an indication of when an individual is at-risk of self-harm. Routine monitoring may provide useful feedback to clinical staff to reduce risk of self-harm. Modifiable risk factors identified in the current study may be targeted during interventions to minimise risk of self-harm.
Now in its fourth edition, Essential Epidemiology is an engaging and accessible introduction to the foundations of epidemiology. It addresses the study of infectious and chronic diseases, public health and clinical epidemiology, and the role of epidemiology in a range of health monitoring and research activities. Contemporary, historical and hypothetical examples enable students to engage with content, while mathematics is kept understandable with complex mathematics housed in optional material so the book remains accessible. With over ninety questions and answers to work through, this book is an essential resource for students, practitioners and anyone else who needs to interpret health data in their studies or work. Epidemiology's most important goal is to bring rigour to the collection, analysis and interpretation of health data to improve health on a global scale; Essential Epidemiology provides readers the tools to achieve that goal.