2017 Study Abstract
Exposure to air pollution is associated with cardiovascular mortality and pulmonary morbidity, including asthma, COPD, lower respiratory infections, and possibly sleep apnea. Although air pollution also may influence sleep quality through alterations in inflammatory or autonomic nervous system pathways, the relationship between air pollution and sleep has not been well studied. We evaluated the relationship between participant-level estimates of long-term ambient-derived traffic-related air pollution exposure with objective sleep fragmentation.
We analyzed data from a subpopulation of the Multi-Ethnic Study of Atherosclerosis (MESA) who participated in both MESA Sleep and AIR studies. Exposure to traffic related air pollutants (oxides of nitrogen) were estimated at participants’ homes using spatio-temporal models based on cohort-specific monitoring averaged for one and five years prior to sleep assessment. Objective sleep fragmentation was evaluated with wrist actigraphy recorded over seven 24 hour periods. We used multivariate logistic regression models to evaluate for an association of traffic related air pollution with low sleep efficiency (<88%) and increased wake after sleep onset (WASO; > 60 mins). We adjusted for socio-demographics, sleep apnea (AHI>15), short sleep duration (< 6 hrs) and residential socio-economic status (SES).
MESA participants (n=1863) were an average age 68 (+/- 9) years, 46% male, 36% white, 24% Hispanic, 29% black and 12% Asian. A quarter of the sample had < 88% sleep efficiency and 11% had WASO > 60 mins. The highest quartile NO2 exposure level (> 23.7 ppb) over 5 years compared to the lowest (< 10 ppb) was associated with a 57% greater odds of low sleep efficiency in fully adjusted models with a significant test for trend (table 1). The highest quartile compared to the lowest quartile NO2/x average 1 and 5-years exposure levels were also associated with 71-91% greater odds of > 60min WASO.
Higher levels of traffic-related air pollution are associated with greater odds of objectively measured sleep disruption after adjusting for individual and residential socio-demographics. Further research is needed to identify the mechanisms and whether associations are attributable to oxides of nitrogen, traffic noise, other pollutants or environmental exposures that co-vary with traffic.