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Home > Online-first > Lim

Estimating Suicide Mortality in Thailand: A Comparison of Verbal Autopsy Data from 2005 and 2019

Apiradee Lim, Nuttapat Makka, Kanitta Bundhamcharoen, Narissara Salae, Surasak Sangkhathat

Abstract

Objective: An accurate cause of death is essential for establishing health planning and policies. Underreporting of suicide deaths has occurred, leading to the use of verbal autopsy to confirm the more accurate cause of death. This study estimated the number and rate of suicide deaths from two verbal autopsy (VA) data sources in 2005 and 2019.
Material and Methods: VA data were obtained from the International Health Policy Program (IHPP), Ministry of Public Health, Thailand, excluding deaths under 10 years, resulting in 9,452 deaths in VA 2005 and 8,848 deaths in VA 2019. A logistic regression was used to estimate the number of deaths. Linear regression was used to identify the patterns of death by age-gender and region.
Results: The suicide death rate among individuals aged 10 years and older increased significantly from 12.74 per 100,000 population in 2005 to 14.95 per 100,000 in 2019. Males, except 10 to 29, had higher rates than the average, with the highest in the 30 to 39 age group. The northern regions reported the highest rates in both 2005 and 2019.
Conclusion: The higher suicide rates observed in 2019 compared with 2005, especially among older individuals and populations in northern regions, highlight the importance of implementing targeted, culturally sensitive intervention strategies.

 Keywords

estimated death;, reported death, suicide death; triangulation method; verbal autopsy

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References

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DOI: http://dx.doi.org/10.31584/jhsmr.20261423

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About The Authors

Apiradee Lim
Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Mueang, Pattani Campus, Pattani 94000,
Thailand

Nuttapat Makka
International Health Policy Program, Ministry of Public Health, Mueang, Nonthaburi 11000,
Thailand

Kanitta Bundhamcharoen
International Health Policy Program, Ministry of Public Health, Mueang, Nonthaburi 11000,
Thailand

Narissara Salae
Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Mueang, Pattani Campus, Pattani 94000,
Thailand

Surasak Sangkhathat
Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok Noi, Bangkok 10700,
Thailand

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2023 (June)
Acceptance rate: 23.6%
2024 (June)
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2025 (June)
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