Andrew J Petkus1, Diana Younan2, Keith Widaman3, Margaret Gatz4, JoAnn E Manson5, Xinhui Wang6, Marc Serre7, William Vizuete8, Helena Chui9, Mark A Espeland10, Susan Resnick11, Jiu-Chiuan Chen12. 1. University of Southern California, Department of Neurology, 1520 San Pablo St. Suite 3000, Los Angeles, CA 90033, United States. Electronic address: petkus@usc.edu. 2. University of Southern California, Department of Preventive Medicine, 2001 North Soto Street, Los Angeles, CA 90033, United States. Electronic address: dyounan@usc.edu. 3. University of California at Riverside, Graduate School of Education, 900 University Ave., 1207 Sproul Hall, Riverside, CA 92521, United States. Electronic address: keith.widaman@ucr.edu. 4. University of Southern California, Center for Economics and Social Research, 635 Downey Way, Los Angeles, CA 90089-3332, United States. Electronic address: gatz@usc.edu. 5. Harvard Medical School, Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, United States. Electronic address: jmanson@rics.bwh.harvard.edu. 6. University of Southern California, Department of Neurology, 1520 San Pablo St. Suite 3000, Los Angeles, CA 90033, United States. Electronic address: xinhuiwa@usc.edu. 7. University of North Carolina, Department of Environmental Sciences and Engineering, 1303 Michael Hooker Research Center, CB#7431, Chapel Hill, NC 27599, United States. Electronic address: marc_serre@unc.edu. 8. University of North Carolina, Department of Environmental Sciences and Engineering, 1303 Michael Hooker Research Center, CB#7431, Chapel Hill, NC 27599, United States. Electronic address: airquality@unc.edu. 9. University of Southern California, Department of Neurology, 1520 San Pablo St. Suite 3000, Los Angeles, CA 90033, United States. Electronic address: chui@usc.edu. 10. Wake Forest School of Medicine, Department of Biostatistics and Data Science, 475 Vine Street, Winston-Salem, NC 27101, United States. Electronic address: mespeland@wakehealth.edu. 11. National Institute on Aging, Laboratory of Behavioral Neuroscience, 251 Bayview Boulevard, Suite 100, Baltimore, MD 21224, United States. Electronic address: resnicks@grc.nia.nih.gov. 12. University of Southern California, Department of Neurology, 1520 San Pablo St. Suite 3000, Los Angeles, CA 90033, United States; University of Southern California, Department of Preventive Medicine, 2001 North Soto Street, Los Angeles, CA 90033, United States. Electronic address: jcchen@usc.edu.
Abstract
BACKGROUND: Emerging data suggests PM2.5 (particulate matter with aerodynamic diameter <2.5 μm) may be associated with both earlier declines in episodic memory (EM) and increased depressive symptoms in older adults. Although late-life depressive symptoms are associated with EM, no longitudinal studies have examined the inter-relationship among PM2.5, depressive symptoms and EM. METHODS: Older women (n = 2,202; aged 67-83 in 1999) enrolled in the Women's Health Initiative Study of Cognitive Aging completed up to eight annual assessments of depressive symptoms (15-item Geriatric Depression Scale) and EM (California Verbal Learning Test). A nationwide spatiotemporal model (1999-2010) was used to estimate ambient PM2.5 exposure at residential locations. Univariate and bivariate structural equation models (SEMs) for latent-change scores were used to examine how 3-year average PM2.5 preceding each assessment affects the temporal dynamics and bidirectional relations of annual changes in depressive symptoms and EM. RESULTS: In univariate SEMs, one inter-quartile (4.04 μg/m3) increment of 3-year PM2.5 was significantly (p < 0.05) associated with accelerated declines in verbal learning (List A trials 1-3: β = -1.48) and free-recall memory (short-delay: β = -1.43; long-delay: β = -1.11), but not with change in depressive symptoms (β = 0.12; p = 0.71). In bivariate SEMs, significant associations were observed between PM2.5 and accelerated declines in EM measures (β = -1.44 to -0.99; p < 0.05) and between EM performance and changes in depressive symptoms (β = -0.08 to -0.05; p < 0.05), with significant indirect PM2.5 effects on changes in depressive symptoms (β = 0.08-0.10; p < 0.05). These findings were robust with adjustment for multiple demographic, lifestyle, and clinical factors, and remained after excluding subjects with dementia or mild cognitive impairment. No associations were found between PM2.5 and change in depressive symptoms or depressive symptoms and subsequent EM decline. CONCLUSIONS: Findings suggest that PM2.5 neurotoxicity may damage brain areas implicated in EM, followed by manifestation of depressive symptoms. Our data did not support depressive symptoms as the neuropsychological mediator of accelerated brain aging associated with PM2.5 exposure.
BACKGROUND: Emerging data suggests PM2.5 (particulate matter with aerodynamic diameter <2.5 μm) may be associated with both earlier declines in episodic memory (EM) and increased depressive symptoms in older adults. Although late-life depressive symptoms are associated with EM, no longitudinal studies have examined the inter-relationship among PM2.5, depressive symptoms and EM. METHODS: Older women (n = 2,202; aged 67-83 in 1999) enrolled in the Women's Health Initiative Study of Cognitive Aging completed up to eight annual assessments of depressive symptoms (15-item Geriatric Depression Scale) and EM (California Verbal Learning Test). A nationwide spatiotemporal model (1999-2010) was used to estimate ambient PM2.5 exposure at residential locations. Univariate and bivariate structural equation models (SEMs) for latent-change scores were used to examine how 3-year average PM2.5 preceding each assessment affects the temporal dynamics and bidirectional relations of annual changes in depressive symptoms and EM. RESULTS: In univariate SEMs, one inter-quartile (4.04 μg/m3) increment of 3-year PM2.5 was significantly (p < 0.05) associated with accelerated declines in verbal learning (List A trials 1-3: β = -1.48) and free-recall memory (short-delay: β = -1.43; long-delay: β = -1.11), but not with change in depressive symptoms (β = 0.12; p = 0.71). In bivariate SEMs, significant associations were observed between PM2.5 and accelerated declines in EM measures (β = -1.44 to -0.99; p < 0.05) and between EM performance and changes in depressive symptoms (β = -0.08 to -0.05; p < 0.05), with significant indirect PM2.5 effects on changes in depressive symptoms (β = 0.08-0.10; p < 0.05). These findings were robust with adjustment for multiple demographic, lifestyle, and clinical factors, and remained after excluding subjects with dementia or mild cognitive impairment. No associations were found between PM2.5 and change in depressive symptoms or depressive symptoms and subsequent EM decline. CONCLUSIONS: Findings suggest that PM2.5 neurotoxicity may damage brain areas implicated in EM, followed by manifestation of depressive symptoms. Our data did not support depressive symptoms as the neuropsychological mediator of accelerated brain aging associated with PM2.5 exposure.
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