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Exposure to ambient PM2.5 concentrations and cognitive function among older Mexican adults

  • Aarón Salinas-Rodríguez
  • , Julián Alfredo Fernández-Niño
  • , Betty Manrique-Espinoza
  • , Grea Litai Moreno-Banda
  • , Ana Luisa Sosa-Ortiz
  • , Zhengmin (Min) Qian
  • , Hualiang Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Recent epidemiological research has shown that exposure to fine particulate pollution (PM2.5) is associated with a reduction in cognitive function in older adults. However, primary evidence comes from high-income countries, and no specific studies have been conducted in low and middle-income countries where higher air pollution levels exist. Objectives: To estimate the association between the exposure to PM2.5 and cognitive function in a nationally representative sample of older Mexican adults and the associated effect modifiers. Methods: Data for this study were taken from the National Survey of Health and Nutrition in Mexico carried out in 2012. A total of 7986 older adults composed the analytical sample. Cognitive function was assessed using two tests: semantic verbal fluency and three-word memory. The annual concentration of PM2.5 was calculated using satellite data. Association between exposure to PM2.5 and cognitive function was estimated using two-level logistic and linear regression models. Results: In adjusted multilevel regression models, each 10 μg/m3 increase in ambient PM2.5 raised the odds of a poorer cognitive function using the three-word memory test (OR = 1.37, 95% CI: 1.08, 1.74), and reduced the number of valid animal named in the verbal fluency test (β = −0.72, 95% CI: −1.05, −0.40). Stratified analyses did not yield any significant modification effects of age, sex, indoor pollution, urban/rural dwelling, education, smoking and other factors. Conclusions: This study supports an association between exposure to PM2.5 concentrations and cognitive function in older adults. This is particularly relevant to low- and middle-income countries, which are marked by a rapid growth of their aging population and high levels of air pollution.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalEnvironment international
Volume117
DOIs
StatePublished - Aug 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

All Science Journal Classification (ASJC) codes

  • General Environmental Science

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