Effect of long-term exposure to PM2.5 on years of life lost in a populated Middle Eastern city.
Maryam MoradiMostafa HadeiMohsen YazdaniMohammad GoudarziZeynab BaboliYaser Tahmasebi BirganiAbdolkazem NeisiGholamreza GoudarziPublished in: Environmental geochemistry and health (2021)
From a public health point of view, years of life lost (YLL) is a more important index than the number of deaths to evaluate the effect of risk factors. The objective of the present study was to estimate the burden of disease including years of life lost (YLL) and expected life remaining (ELR) attributed to long-term exposure to PM2.5 in Ahvaz, one of the most polluted cities of the world, during March 2014 through March 2017. AirQ + software was used for the estimation of YLL and ELR due to all natural causes of death. Hourly concentrations of PM2.5 were acquired from the Department of Environment (DoE) of Ahvaz. Several steps were performed to validate the raw air quality data. Only the monitors were included that had minimum data completeness of 75%. Two age groups were selected for this study, including 0-64 and 65 < years. The life table approach was used to estimate YLL and ELR. Annual averages of PM2.5 were 5.2-8 times higher than the air quality guideline (10 μg/m3) set by WHO for long-term exposure to PM2.5. In total, PM2.5 has caused 234,041 years of life lost due to mortality. About 84% of YLLs were attributed to people older than 65 years old. The YLLs of men were higher than those for women. The YLLs in the third year were greater than the first two years. PM2.5 has caused the average age of total population, people aged 0-64 years old, and people > 65 years old decreased by 2.5, 3, and 1.6 years, respectively. These studies indicated that people in a city that the air quality is highly affected by dust storms, industrial emissions, and urban air pollution are significantly at risk. Air pollution control strategies and actions should be designed and executed to improve the quality of ambient air.
Keyphrases
- air pollution
- particulate matter
- heavy metals
- polycyclic aromatic hydrocarbons
- public health
- lung function
- risk factors
- water soluble
- electronic health record
- physical activity
- chronic obstructive pulmonary disease
- machine learning
- skeletal muscle
- risk assessment
- polycystic ovary syndrome
- climate change
- deep learning
- sewage sludge