Burden of fine air pollution on mortality in the desert climate of Kuwait

Author:

Alahmad BarrakORCID,Li Jing,Achilleos Souzana,Al-Mulla Fahd,Al-Hemoud Ali,Koutrakis Petros

Abstract

Abstract Background Middle Eastern desert countries like Kuwait are known for intense dust storms and enormous petrochemical industries affecting ambient air pollution. However, local health authorities have not been able to assess the health impacts of air pollution due to limited monitoring networks and a lack of historical exposure data. Objective To assess the burden of PM2.5 on mortality in the understudied dusty environment of Kuwait. Methods We analyzed the acute impact of fine particulate matter (PM2.5) on daily mortality in Kuwait between 2001 and 2016. To do so, we used spatiotemporally resolved estimates of PM2.5 in the region. Our analysis explored factors such as cause of death, sex, age, and nationality. We fitted quasi-Poisson time-series regression for lagged PM2.5 adjusted for time trend, seasonality, day of the week, temperature, and relative humidity. Results There was a total of 70,321 deaths during the study period of 16 years. The average urban PM2.5 was estimated to be 46.2 ± 19.8 µg/m3. A 10 µg/m3 increase in a 3-day moving average of urban PM2.5 was associated with 1.19% (95% CI: 0.59, 1.80%) increase in all-cause mortality. For a 10 µg/m3 reduction in annual PM2.5 concentrations, a total of 52.3 (95% CI: 25.7, 79.1) deaths each year could be averted in Kuwait. That is, 28.6 (95% CI: 10.3, 47.0) Kuwaitis, 23.9 (95% CI: 6.4, 41.5) non-Kuwaitis, 9.4 (95% CI: 1.2, 17.8) children, and 20.9 (95% CI: 4.3, 37.6) elderly deaths each year. Impact Statement The overwhelming prevalence of devastating dust storms and enormous petrochemical industries in the Gulf and the Middle East has intensified the urgency to address air pollution and its detrimental health effects. Alarmingly, the region’s epidemiological research lags behind, hindered by a paucity of ground monitoring networks and historical exposure data. In response, we are harnessing the power of big data to generate predictive models of air pollution across time and space, providing crucial insights into the mortality burden associated with air pollution in this under-researched yet critically impacted area.

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health,Pollution,Toxicology,Epidemiology

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