Chronic respiratory disease mortality and its associated factors in selected Asian countries: evidence from panel error correction model.

backgroundChronic Respiratory Diseases (CRDs) in Asian countries are a growing concern in terms of morbidity and mortality. However, a systematic understanding of the increasing age-adjusted mortality rate of chronic respiratory disease (CRD) and its associated factors is not readily available for many Asian countries. We aimed to determine country-level factors affecting CRD mortality using a panel error correction model.

methodsBased on data from the Global Burden of Disease Study 2017, we estimated the trends and distribution of CRD mortality for selected Asian countries from 2010 to 2017. Furthermore, we evaluated the relationship between CRD mortality and Gross Domestic Product (GDP) per capita, average years of schooling, urbanization, and pollutant emission (PM2.5 concentration) using a fixed-effect model. We corrected the estimates for heteroscedasticity and autocorrelation through Prais-Winsten adjustment along with robust standard error.

resultsBetween 2010 and 2017, approximately 21.4 million people died from chronic respiratory diseases in the countries studied. Age-standardized crude mortality rate from CRDs in the period had minimum and maximum values of 8.19 (Singapore in 2016) and 155.42 (North Korea in 2010) per 100,000 population, respectively. The coefficients corrected for autocorrelation and heteroskedasticity based on the final model of our study (Prais-Winsten), showed that all explanatory variables were statistically significant (p < 0.001). The model shows that the 1% increase in GDP per capita results in a 20% increase (0.203) in the CRD mortality rate and that a higher concentration of air pollution is also positively associated with the CRD deaths (0.00869). However, an extra year of schooling reduces the mortality rate by 4.79% (- 0.0479). Further, rate of urbanization is negatively associated with the CRD death rate (- 0.0252).

conclusionsOur results indicate that both socioeconomic and environmental factors impact CRD mortality rates. Mortality due to CRD increases with rising GDP per capita and decreases with the percentage of the total population residing in urban areas. Further, mortality increases with greater exposure to PM2.5. Also, higher years of schooling mitigate rising CRD mortality rates, showing that education can act as a safety net against CRD mortality. These results are an outcome of sequential adjustments in the final model specification to correct for heteroscedasticity and autocorrelation.