Comparative Analysis of Suicide Rate between Malaysia and Other Asian Countries

Tay, Jes Mie (2025) Comparative Analysis of Suicide Rate between Malaysia and Other Asian Countries. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

This study analyses the differences in suicide rates between Malaysia and other Asian countries, focusing on socio-economic and demographic that influence these trends. Malaysia reports lower suicide rates compared to countries like Japan and South Korea, but concerns about underreporting persist due to legal and social barriers. The study employs statistical methods, including t-tests, ANOVA, chi-square tests, Pearson correlation, multiple linear regression, quantile regression, and ARIMA time-series forecasting, to examine patterns in suicide rates. K-Means clustering is also applied to classify countries into different suicide risk levels, allowing for a deeper understanding of regional trends. Data is sourced from the World Health Organization (WHO) and the World Bank, covering the years 2000 to 2019. Findings indicate that GDP and unemployment rates have weak but statistically significant correlations with suicide rates. Clustering results show that countries can be categorized into Low, Moderate, High, and Very High suicide rate levels with Malaysia grouped in the Moderate category. ARIMA forecasting suggests different future trends across countries, highlighting the need for targeted interventions. The study also finds that suicide rates are higher among males across all regions, consistent with global trends. This research provides valuable insights for policymakers and mental health professionals, emphasizing the need for improved suicide prevention policies, better data collection methods, and targeted mental health support systems. The findings can contribute to regional efforts in understanding and addressing suicide trends more effectively. Keywords: Suicide Rate, Malaysia, Asia, Statistical Analysis, ARIMA, K-Means Clustering, Quantile Regression