<p>The objective of this study is to examine the association between air pollution and health burden in Thailand, Malaysia, and Singapore from 2000 to 2021. PM<sub>2.5</sub> concentrations and life expectancy are measures of air pollution. Health outcomes include death, incidence, and prevalence of respiratory infections and tuberculosis. The data are obtained from the Global Burden of Disease and the Air Quality Life Index. A Generalized Additive Mixed Model is used to analyze spatial and temporal patterns in a panel dataset with repeated annual observations across countries. This method allows for the detection of nonlinear relationships and considers cross-country variation and time series. The results show that Thailand has a significantly lower death rate from respiratory infections and tuberculosis compared to Malaysia, while the difference for Singapore is not statistically significant. Incidence, prevalence, and time are significantly associated with the death rate. PM<sub>2.5</sub> concentrations and life expectancy do not show significant effects in the model. The study contributes to the understanding of how disease-specific indicators and time trends influence death. It provides cross-country evidence from Southeast Asia and supports the use of burden-specific indicators in public health planning and surveillance.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Air pollution and health burden: a generalized additive mixed model approach to PM2.5, life Expectancy, and respiratory infections and tuberculosis in Thailand, Malaysia, and Singapore

  • Wong Ming Wong,
  • Wunhong Su

摘要

The objective of this study is to examine the association between air pollution and health burden in Thailand, Malaysia, and Singapore from 2000 to 2021. PM2.5 concentrations and life expectancy are measures of air pollution. Health outcomes include death, incidence, and prevalence of respiratory infections and tuberculosis. The data are obtained from the Global Burden of Disease and the Air Quality Life Index. A Generalized Additive Mixed Model is used to analyze spatial and temporal patterns in a panel dataset with repeated annual observations across countries. This method allows for the detection of nonlinear relationships and considers cross-country variation and time series. The results show that Thailand has a significantly lower death rate from respiratory infections and tuberculosis compared to Malaysia, while the difference for Singapore is not statistically significant. Incidence, prevalence, and time are significantly associated with the death rate. PM2.5 concentrations and life expectancy do not show significant effects in the model. The study contributes to the understanding of how disease-specific indicators and time trends influence death. It provides cross-country evidence from Southeast Asia and supports the use of burden-specific indicators in public health planning and surveillance.