Cognitive Impacts of Ambient Air Pollution in the National Social Health and Aging Project (NSHAP) Cohort Lindsay A. Tallon MSPH1, Vivian C. Pun PhD1, Justin Manjourides PhD1, Helen Suh ScD1 1 Department of Health Sciences, Northeastern University, Boston, MA 02115 ABSTRACT RESULTS Background: Pathways through which air pollution may impact cognitive function are poorly understood, particularly with regard to whether and how air pollution interacts with social and emotional factors to influence cognitive health. To examine this issue, we examined the association between air pollutant exposures and cognitive outcomes among older adults participating in the National Social Life, Health, and Aging Project (NSHAP) cohort study. Methods: Measures of cognitive function, social connectedness, and emotional and physical health were obtained for each NSHAP participant between 2010-2011. Cognitive function was assessed using the well-validated Chicago Cognitive Function Measure (CCFM). Exposures to fine particles (PM2.5) were estimated for each participant using GIS-based spatio-temporal models, while exposures to ozone (O3) and nitrogen dioxide (NO2) were obtained from the nearest EPA monitors. Results: In adjusted linear regression models, IQR increases in 1 to 7 year PM2.5 exposures were associated with a 0.22 (95% CI: -0.44, -0.01) to a 0.25 (95% CI: -0.43, -0.06) point decrease in CCFM scores equivalent to aging 1.6 years. Similar decreases were associated with 1 to 7 year NO2 exposures. In contrast, 2 to 7 year exposures to O3 were associated with increased cognitive test scores. The impacts of PM2.5 on cognition were greater in individuals without stroke and with elevated anxiety, and were mediated by depression and elevated CRP levels. Conclusions: Exposures to long-term PM2.5 and NO2 were associated with decreased cognitive function in our cohort of older Americans. NSHAP participants who did not have a stroke or who had elevated anxiety were more susceptible to the effects of PM2.5 on cognition. The impacts of PM2.5 on cognition were mediated by depression, suggesting that PM2.5 may impact cognition through pathways related to mood disorders. Table 1. Participant Characteristics Table 4. CCFM Score per IQR Increment in 1yr PM2.5: Effect Modification In Wave 2 3,377 participants were administered the CCFM. The mean score was 13.45 Associations were modified by stroke and anxiety, but not significantly modified by obesity, elevated CRP, diabetes, hypertension, exercise, or current smoking Characteristic Wave 2 (Aug 2010-Jun 2011) Number of Participants 3377 Age, years (SD) 72.38 (8.10) Gender, n (%) Women Men   1839 (54.46%) 1538 (45.54%) Race, n (%) Non-Hispanic white Non-Hispanic black Hispanic non-black Other 2403 (70.71%) 517 (16.08%) 367 (10.51%) 78 (2.70%) Education Level, n (%) Less than High School H.S. or vocational school College degree or greater 645 (19.10%) 1905 (56.41%) 827 (24.49%) Median Household Income, mean (SD) 54.7 (26.4) CCFM score, mean (SD) 13.45 (4.05) Diabetes, n (%) 800 (23.67%) Stroke, n (%) 315 (9.36%) Hypertension (>90 diastolic, >140 systolic), n (%) 1603 (47.47%) CRP High CRP (>1) 4.48 (10.34) 2226 (65.92%) BMI (kg/m2) Obesity (>30 BMI), n (%) 29.36 (6.33) 1241 (38.87%) Exercise (weekly or more), n (%) 1902 (56.32%) Current smoker, n (%) 450 (13.33%) Elevated depression, n (%) 703 (20.82%) Elevated anxiety, n (%) 605 (21.31%) Pollutants, mean (SD) PM2.5 (µg/m3) NO2 (ppb) 10.23 (2.50) 10.13 (6.28) Effect modifier Effect Estimates Physical Health Measures BMI   <30 -0.15 (-0.38, 0.07) ≥30 -0.15 (-0.63, 0.34) CRP Low (<1) -0.23 (-0.71, 0.29) Elevated (>1) -0.21 (-0.46, -0.00) Diabetes No -0.16 (-0.41, 0.09) Yes -0.41 (-0.97, 0.16) Hypertension -0.23 (-0.45, -0.01) -0.30 (-0.16, 0.77) Stroke* -0.48 (-0.82, -0.13) -0.03 (-0.82, 0.77) Mental Health Measures Elevated Depression -0.19 (-0.44, 0.07) -0.90 (-1.49, -0.32) Elevated Anxiety* -0.16 (-0.75, 0.44) -0.39 (-0.65, -0.12) Health Behaviors Current Smoker -0.04 (-0.34, 0.26) -0.86 (-1.55, -0.17) Exercise None -0.21 (-0.43, 0.01) 1 or more times/week -0.20 (-0.67, 0.27) BACKGROUND Cognitive disorders are a leading cause of death and disability and are a growing problem in an aging population A growing body of literature has shown a relationship between air pollution and cognitive function While existing studies provide important evidence, unanswered questions remain regarding pathways through which air pollution may impact cognition To investigate collective impacts of air pollution exposures and physical and emotional health on cognition, we used data obtained from older adults participating in the National Social Life, Health, and Aging Project (NSHAP) Table 2. Change in CCFM Score per IQR Change in Air Pollution: 1-5 year moving average exposures PM2.5 and NO2 exposures were associated with lower cognitive function, while O3 exposures (not shown) were positively associated with cognitive function.   PM2.5 (n=3374)1 NO2 (n=2106)2 Base Adjusted 1 year -0.27 (-0.47, -0.07)* -0.22 (-0.44, -0.01)* -0.06 (-0.24, 0.12) -0.13 (-0.34, 0.08) 2 years -0.23 (-0.43,-0.04)* (-0.42, -0.01)* (-0.29, 0.04) -0.26 (-0.45, -0.06)* 3 years -0.21 (-0.40, -0.03)* (-0.40, -0.02)* (-0.30, 0.03) (-0.46, -0.07)* 4 years (-0.41, -0.05)* (-0.40, -0.04)* -0.14 (-0.31, 0.02) -0.29 (-0.48, -0.09)* 5 years -0.25 (-0.43, -0.07)* (-0.42, -0.05)* -0.17 (-0.34, -0.01)* -0.32 (-0.52, -0.12)* 1 PM2.5 1yr IQR=4.25, 2yr IQR=4.03, 3 yr IQR=3.93, 4 yr IQR=3.99, 5yr IQR=4.10, 6 yr IQR=4.18, 7 yr IQR=4.33 2 NO2 1yr IQR=8.37, 2yr IQR =6.66, 3 yr IQR=6.68, 4 yr IQR=6.90, 5 yr IQR=6.99, 6 yr IQR=7.28, 7yr IQR=7.42 * p<0.05 DISCUSSION METHODS Increased PM2.5 and NO2 exposures are associated with significant decreases in cognitive function, equivalent to aging 1.6 and 1.9 years, respectively Our findings of mediation of the air pollution-cognitive function association by elevated depression suggest that air pollution may harm cognition through pathways related to emotional health Mediation by CRP did not follow expected biological pathways, as increased PM2.5 led to decreased CRP (Step 2) and increased CRP improved cognition (Step 3), suggesting invalid mediation findings for CRP. Limitations Exposure error resulting from (1) NO2 (and O3) exposures estimated using nearest ambient monitor concentrations and (2) absence of information on activity patterns and home characteristics Analyses based on one data collection wave Strengths A nationally representative study of older adults Understanding of effect modification leads to knowledge about modifiable exposures Robust findings of our analysis Study Design Nationally representative, participants aged 57 to 85 Used Wave 2 of data: 2010-2011 with 3,377 participants Health measures Cognitive function measured by 20 point modified version of Montreal Cognitive Assessment known as the Chicago Cognitive Function Measure (CCFM) Measured BMI and CRP levels Self-reported medical conditions, smoking status, emotional health Air pollution exposures Assessed using PM2.5 from spatio-temporal models Ozone (summer) and NO2 measured at nearest ambient EPA AQS monitor (< 60 km) 1-5 yr moving average exposures from interview date for each participant Statistical analysis Cross-sectional analysis with CCFM score as outcome Models controlled for race/ethnicity, gender, education, age, season, current smoking status, geographic region, and median household income of census tract Examined effect modification by obesity, hypertension, stroke, diabetes, CRP, depression, anxiety, exercise, and current smoking status. Assessed mediation by CRP, depression, and anxiety Table 3. Mediation Analysis1 Depression fully mediated the 1-yr PM2.5 –CCFM relationship; anxiety was not a statistically significant mediator. While significant, mediation by CRP did not follow hypothesized biological pathways.   Depression6 Anxiety7 CRP9 Step 1: PM2.5CCFM2 -0.24 (-0.42, -0.06)* Step 2: PM2.5 M3 0.34 (0.14, 0.54)* -0.08 (-0.23, 0.07) -0.07 (-0.12, -0.02)* Step 3: PM2.5 CCFM -0.18 (-0.40, 0.03) -0.26 (-0.49, -0.03)* -0.20 (-0.43, 0.03) M  CCFM (-0.11, -0.06)* (-0.11, -0.05)* 0.18 (0.06, 0.30)* ACKNOWLEDGEMENTS This work was funded by NIEHS grant 1R01ES022657-01A1. All authors declare no competing financial interest.