Exposure to indoor air pollution is known to affect respiratory and cardiovascular health, but little is known about its effects on cognitive function. We measured the concentrations and magnetite content of airborne particulate matter (PM) in the indoor environment arising from burning peat, wood or coal in residential open fires. Highest indoor PM2.5 concentrations (60 µg/m3, i.e. 2.4 times the WHO-recommended 24-hour mean) occurred when peat was burned, followed by burning of coal (30 µg/m3) and wood (17 µg/m3). Conversely, highest concentrations of coarser PM (PM10-2.5) were associated with coal burning (20 µg/m3), with lower concentrations emitted during burning of wood (10 µg/m3) and peat (8 µg/m3). The magnetic content of the emitted PM, greatest (for both PM size fractions) when coal was burned, is similar to that of roadside airborne PM. Exposure to PM, and to strongly magnetic airborne PM, can be greater for individuals spending ~5 hours/day indoors with a coal-burning open fire for 6 months/year compared to those commuting via heavily-trafficked roads for 1 hour/day for 12 months/year. Given these high indoor PM and magnetite concentrations, and the reported associations between (outdoor) PM and impaired neurological health, we used individual-level data from The Irish Longitudinal Study on Ageing (TILDA) to examine the association between the usage of open fires and the cognitive function of older people. Using a sample of nearly seven thousand older people, we estimated multi-variate models of the association between cognitive function and open fire usage, in order to account for relevant confounders such as socio-economic status. We found a negative association between open fire usage and cognitive function as measured by widely-used cognitive tests such as word recall and verbal fluency tests. The negative association was largest and statistically strongest among women, a finding explained by the greater exposure of women to open fires in the home because they spent more time at home than men. Our findings were also robust to stratifying the sample between old and young, rich and poor, and urban and rural.
This is the author’s version of a work that was accepted for publication in Environmental Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Research, 373, 110298, 2020 DOI: 10.1016/j.envres.2020.110298
