Socioeconomic factors affecting suicides in Sri Lanka

Abstract

Suicide is a serious public health problem in Sri Lanka with strong emotional repercussions for its survivors and for the families of its victims. More than 4000 people in Sri Lanka killed themselves in 2016 and were listed as having the third highest suicide rate. Hence, suicides have emphasized the importance of various factors in the prediction of suicide. Therefore, the main objectives of this study are to determine the major factors associated with suicide and predict the risk of suicide by age and gender separately. We analyzed data based on social and environmental surroundings from 2005 to 2011, obtained from the Sri Lanka Police. Additionally, the data from 2014 - 2016 were used for validation purposes. Factor analysis method was used to determine the variability among correlated variables. Moreover, LASSO regression model, Poisson regression model and Negative binomial regression model were used to predict the total suicides. AIC values were used to identify the best model in the Poisson regression and Negative binomial models. Besides, finest lambda value was used to identify the best LASSO regression model. All the predictions are made assuming that the prevailing conditions in the country affecting crime rates remain unchanged during the period. Further, the mean absolute percentage error (MAPE), is calculated, in order to find the prediction accuracy of the proposed model. Model accuracies for proposed LASSO regression model, Poisson regression model and Negative Binomial model are approximately 89.43%, 87.67% and 80.65% for males, and 76.22%, 92.81% and 90.58% for females respectively. Based on MAPE values, LASSO Regression model was selected as the best male model and the Poisson regression model was selected as the best female model.