Activity

1. The author is interested in studying the suicide problem in Thailand due to the increasing trend of suicide, the high suicide rate of more than 6 people per 100,000 population, and the lack of quantitative research at the macro-level.

2. Population over 60 years of age (AGE60) is one of the risk factors that significantly increases the suicide rate (p < 0.01 for both models). Many older adults in Thailand lack effective financial and social support. Many live without family support, without regular income or adequate living allowances, which may lead to depression and suicidal ideation.

3. Statistical modeling helps in studying the epidemiological and spatial studies of suicide problems in Thailand in the following ways:

– Identifying risk factors that influence suicide. For example, using multiple regression models allows for the identification of the level of the relationship between factors and the ability to distinguish which factors have a positive or negative relationship with suicide rates. This helps to decide which factor should be controlled first if we want to reduce suicide rates.

– Interpreting spatial data. For example, a model using data by province can compare differences between regions and show which regions have higher suicide rates. It can also help find local causes, such as being an agricultural or industrial area, which may relate to income and cost of living.

– Statistical models help control confounders and check if the model fits the data. This makes the results more reliable.