Is memory in older adulthood influenced by changes in air pollution over the previous decade?: Examining concurrent trajectories in ambient PM2.5 and NO2 using sequence analysis

The temporal pattern of air pollution exposure may affect cognitive aging. We characterized 10-year trajectories of particulate matter (PM<sub>2.5</sub>) and nitrogen dioxide (NO<sub>2</sub>) exposure at the United States census tract level using sequence and cluster analysis and evaluated their association with memory among 6750 National Health and Aging Trends Study (NHATS) participants aged 65 or older. For each year between 2000 and 2010, we trichotomized PM<sub>2.5</sub> and NO<sub>2</sub> concentrations in each census tract using the national 2010 25th and 75th percentiles of PM<sub>2.5</sub> (7.9 and 10.8 µg/m<sup>3</sup>) and NO<sub>2</sub> (4.8 and 10.8 ppb), creating nine mutually exclusive air pollution categories for each census tract each year (e.g., high PM<sub>2.5</sub> and high NO<sub>2</sub>, high PM<sub>2.5</sub> and medium NO<sub>2</sub>, etc.). We quantified the dissimilarity between each census tract's 10-year PM<sub>2.5</sub> and NO<sub>2</sub> trajectory and all other trajectories in NHATS using sequence analysis, and combined similar air pollution trajectories using hierarchical clustering. We assigned a 10-year air pollution trajectory cluster to each participant based on their residential census tract location in 2011. Episodic memory score in 2011 was the mean of immediate and delayed word recall scores. We estimated the association of air pollution trajectory with this episodic memory score using linear models adjusted for age, gender, education level, race/ethnicity, neighborhood socioeconomic status, census region, and urbanicity. We clustered 1080 unique air pollution trajectories from 2000 to 2010 into nine distinct groups. In general, participants belonging to clusters with higher pollutant concentrations in 2000 had lower memory scores in 2011, even when pollutant concentrations in the cluster later declined. For example, those exposed to high PM<sub>2.5</sub> and high NO<sub>2</sub> concentrations in 2000, with decreasing NO<sub>2</sub> concentration (and consistently high PM<sub>2.5</sub>) starting in 2006, had an adjusted mean memory score that was 0.20 units lower (95% confidence interval: -0.35, -0.046) than those in clusters with consistently low concentrations of both pollutants. This application of sequence analysis offers a new approach for characterizing temporal patterns of PM<sub>2.5</sub> and NO<sub>2</sub> exposure, simultaneously incorporating pollutant type, timing, duration, and concentration.

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Journal
Environmental Epidemiology
Published
2026-01-21
DOI
https://doi.org/10.1097/ee9.0000000000000448
Primary Topic
Air Quality and Health Impacts
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article
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article

Is memory in older adulthood influenced by changes in air pollution over the previous decade?: Examining concurrent trajectories in ambient PM2.5 and NO2 using sequence analysis

Kevin James Lane, Anusha M. Vable, Kristina Dang, IE Allen et al.
Environmental Epidemiology
Air Quality and Health Impacts
article

Is memory in older adulthood influenced by changes in air pollution over the previous decade?: Examining concurrent trajectories in ambient PM2.5 and NO2 using sequence analysis

Kevin James Lane, Anusha M. Vable, Kristina Dang, IE Allen, Jennifer Weuve, Lucia Pacca, Michael Brauer, M. Maria Glymour
article en

Abstract

The temporal pattern of air pollution exposure may affect cognitive aging. We characterized 10-year trajectories of particulate matter (PM<sub>2.5</sub>) and nitrogen dioxide (NO<sub>2</sub>) exposure at the United States census tract level using sequence and cluster analysis and evaluated their association with memory among 6750 National Health and Aging Trends Study (NHATS) participants aged 65 or older. For each year between 2000 and 2010, we trichotomized PM<sub>2.5</sub> and NO<sub>2</sub> concentrations in each census tract using the national 2010 25th and 75th percentiles of PM<sub>2.5</sub> (7.9 and 10.8 µg/m<sup>3</sup>) and NO<sub>2</sub> (4.8 and 10.8 ppb), creating nine mutually exclusive air pollution categories for each census tract each year (e.g., high PM<sub>2.5</sub> and high NO<sub>2</sub>, high PM<sub>2.5</sub> and medium NO<sub>2</sub>, etc.). We quantified the dissimilarity between each census tract's 10-year PM<sub>2.5</sub> and NO<sub>2</sub> trajectory and all other trajectories in NHATS using sequence analysis, and combined similar air pollution trajectories using hierarchical clustering. We assigned a 10-year air pollution trajectory cluster to each participant based on their residential census tract location in 2011. Episodic memory score in 2011 was the mean of immediate and delayed word recall scores. We estimated the association of air pollution trajectory with this episodic memory score using linear models adjusted for age, gender, education level, race/ethnicity, neighborhood socioeconomic status, census region, and urbanicity. We clustered 1080 unique air pollution trajectories from 2000 to 2010 into nine distinct groups. In general, participants belonging to clusters with higher pollutant concentrations in 2000 had lower memory scores in 2011, even when pollutant concentrations in the cluster later declined. For example, those exposed to high PM<sub>2.5</sub> and high NO<sub>2</sub> concentrations in 2000, with decreasing NO<sub>2</sub> concentration (and consistently high PM<sub>2.5</sub>) starting in 2006, had an adjusted mean memory score that was 0.20 units lower (95% confidence interval: -0.35, -0.046) than those in clusters with consistently low concentrations of both pollutants. This application of sequence analysis offers a new approach for characterizing temporal patterns of PM<sub>2.5</sub> and NO<sub>2</sub> exposure, simultaneously incorporating pollutant type, timing, duration, and concentration.

Environmental EpidemiologyVol. 10(1)
Boston University (US), University of Southern California (US), San Francisco General Hospital (US), University of British Columbia (CA), University of California, San Francisco (US), Washington University in St. Louis (US)
Openalex Percentile: Top 83%
Air Quality and Health Impacts
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