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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The association between air pollutants and mild cognitive impairment in Taiwanese elderly
Sui-Lung Su1, Yue-Ting Lin1, Chih-Hong Pan1,2
1Graduate Institute of Public Health, College of Public Health, National Defense Medical University, Taipei, Taiwan.
Background:
Mild cognitive impairment (MCI) is considered a prodromal stage of dementia, and cognitive decline is generally challenging to reverse. Recently, air pollution has been identified as a risk factor for cognitive impairment, making the exploration of this association an essential research topic. However, nationwide studies investigating the relationship between air pollution and MCI are still lacking.
Objective:
This study aimed to investigate the association between air pollution and MCI in Taiwan.
Methods:
This cross-sectional study utilized data from the Taiwan Biobank, retrieved elderly participants aged above 60, between 2008 and 2021. The study collected demographic data and cognitive function assessments using the Mini-Mental State Examination (MMSE) scale. MCI was defined by cut-off scores of 18, 21, and 25 according to educational levels. Google Map was used to locate the nearest air quality monitoring station from the residential address of participants. Individual daily average exposure concentrations of PM2.5, PM10, SO2, O3, CO, and NO2 were sourced from the air quality monitoring station of Environmental Protection Administration (EPA) between 1993 and 2021. Regression models were employed to identify factors associated with MCI in Taiwan.
Results:
This study contains 4,173 cases with MCI and 31,022 controls, representing an MCI prevalence of 11.9%. The individual daily average exposure concentrations of PM2.5, PM10, O3, CO, SO2 and NO2 are 30.70±8.38 μg/m3, 59.25±15.81 μg/m3, 25.96±3.08 ppb, 0.65±0.42 ppm, 4.97±2.59 ppb and 20.22±5.09 ppb, respectively. Tertiles of pollution exposure in regression models show that higher exposure to PM2.5 and SO2 are associated with a higher risk of MCI compared to that of lower exposure levels (OR = 1.23, 95% CI: 1.11-1.37; OR = 1.20, 95% CI: 1.07-1.34). Furthermore, concurrent exposure to the highest tertiles (T3) of both PM2.5 and SO2 increased the risk of MCI to 2.33 (95% CI: 1.56-3.48).
Conclusions:
We found evidence of the effect of PM2.5 and SO2 on MCI among elderly individuals in Taiwan. Moreover, the association between PM2.5 and MCI risk escalated with higher SO2 concentrations, demonstrating a synergistic interaction between the two pollutants. This discovery may provide evidence for policy of MCI prevention.
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