gms | German Medical Science

Introduction: Age-related cognitive decline is an important topic due to aging populations in developed countries and the resulting burden of disease on these aging societies. Thus, it is important to identify persons at risk for cognitive decline to preserve cognitive functioning. A possibility to characterize early stages of cognitive decline in elderly populations is mild cognitive impairment (MCI) that describes the stage between normal cognitive changes in aging and early dementia [1]. Persons with MCI have a higher risk to develop dementia.

Recently, adverse effects of environmental exposures, such as air pollution (AP), on the central nervous system have been proposed [2]. Investigations of adverse effects of AP on cognitive functions are few and show inconsistent results [3], however, most studies generally support the hypothesis that ambient AP is associated with cognitive function [4]. On the other hand, the association of ambient noise with cognitive function has rarely been investigated. Only few long-term studies exist on the effect of traffic noise exposure on cognitive function, suggesting worse cognitive function in highly noise-exposed population [5]. To our knowledge, no studies have investigated the effect of simultaneous co-exposures of AP and traffic noise on cognitive function of adults, and potential modifying effects of one of these exposures on the other.

The aim of this study was to investigate whether long-term AP and noise have a synergistic adverse effect on cognitive function, using the following cognitive outcomes: MCI, five cognitive subtests, and a global cognitive score (GCS).

Methods: We used cross-sectional data from the second examination of the population-based Heinz Nixdorf Recall study (2006-2008), including cognitive performance completed in 4086 participants. We assessed long-term residential exposure to size-specific particulate matter (PM10, PM2.5, PM2.5 to 10 and PM2.5 absorbance), nitrogen oxides (NOx and NO2), and traffic noise (weighted 24-h (LDEN) and night-time (LNIGHT) means).

Cognitive performance was assessed using five subtests: verbal fluency, immediate and delayed verbal memory, labyrinth test, and the clock drawing test. The GCS was calculated additively using the five age- and education-specific z-scores of individual cognitive subtests. MCI was diagnosed according to the Petersen/International Working Group on MCI criteria [1].

Multiple linear and logistic regression models were calculated for the association of environmental exposures with the outcomes. The main model included age, sex, socio-economic status, alcohol consumption, smoking status, self-reported passive smoking, any regular physical activity, and body mass index. Models were run without (one-exposure model) and with (two-exposure model) adjustment for the other environmental exposure (both exposures used as continuous variables).

To investigate effect modification between environmental exposures, we dichotomized air pollution concentrations at the median value, and constructed product terms of air pollution (dichotomous)*noise (continuous). Noise variables were dichotomized at 60 dB(A) for LDEN and 55 dB(A) for LNIGHT for interaction analysis with continuous air pollution variables. We considered p for interaction < 0.1 as statistically significant.

Results: In fully adjusted one-exposure models, both PM and noise were associated with cognitive function. For example, an interquartile range increase in PM2.5 and a 10 dB(A) increase in LDEN were associated with MCI (odds ratio (95% confidence interval)=1.16 (1.05;1.27) and 1.40 (1.29;1.75), respectively). In two-exposure models, estimates attenuated slightly (i.e. for MCI: PM2.5 1.10 (0.99;1.24) and LDEN 1.34 (1.08;1.68). Results for subtests and GCS were generally similar.

Highly noise exposed participants displayed stronger associations between AP and all cognitive outcomes. For example, PM2.5 was associated with MCI with an OR of 1.30 (1.01;1.68) in participants with high LDEN exposure, and with an OR of 1.10 (0.94;1.29) in participants with low LDEN exposure (p for interaction 0.28). Similar tendencies were found for cognitive subtests and GCS. Similarly, highly AP exposed participants displayed stronger association between noise and cognitive outcomes. For example, the association between LDEN and MCI were OR=1.52 (1.04;2.21) for highly PM2.5 exposed participants, and OR=1.09 (0.62;1.91) for low PM2.5-exposed participants (p for interaction 0.33). Similar, partly significant tendencies of effect modification by AP were found for all associations of noise with cognitive outcomes.

Discussion: In our study we found first suggestive evidence for a modifying effect of long-term traffic noise exposure on the association between AP and cognitive outcomes, as well as for a modifying effect of long-term AP exposure on the association between noise and cognitive outcomes. The association of environmental exposures with cognition was stronger in those participants with high AP, or noise exposure, respectively. These results suggest that the two investigated environmental exposures may interact synergistically with each other. Longitudinal studies are necessary to corroborate our cross-sectional findings.