Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Dec 23;24(1):3564.
doi: 10.1186/s12889-024-21107-2.

Interaction effects of exposure to air pollution and social activities on cognitive function in middle-aged and older Chinese adults based on a nationwide cohort study

Affiliations

Interaction effects of exposure to air pollution and social activities on cognitive function in middle-aged and older Chinese adults based on a nationwide cohort study

Shijia Yuan et al. BMC Public Health. .

Abstract

Background: Although there have been many studies on the relationship between ambient air pollution and cognitive functioning in developed countries, there are no studies focusing on the interaction between ambient air pollution and social activities. This study aims to examine interactive effects of ambient air pollution and social activities on cognitive function in Chinese middle-aged and older.

Methods: This study used nationally representative longitudinal survey data of China Health and Retirement Longitudinal Study (CHARLS) 2013, 2015 and 2018. The study explored the additive interaction effects of air pollutants and social activities on cognitive function in middle-aged and older adults by constructing mixed linear regression analyses containing interaction terms, as well as constructing additive interaction analyses with dummy variables containing four unordered categories that were partitioned according to median. In addition, the study further explored the interaction between air pollution and different types of social activities through an interaction term between air pollution and different types of social activities.

Results: In the model fully adjusted for covariates such as age, sex, region, we found significant coefficients on the interaction term between PM2.5, O3 and social activities on cognitive function (PM2.5, β = -0.018, 95%CI: -0.029, -0.006; O3, β = 0.017, 95%CI: 0.007, 0.027). In the interaction analysis by constructing dummy variables, we found a significant antagonistic effect between PM2.5 and social activities (SI = 0.730, 95%CI: 0.674, 0.785), a possible antagonistic effect between NO2 and social activities (SI = 0.697, 95%CI: 0.648, 0.747), and a possible synergistic effect between O3 and social activities (SI = 1.769, 95%CI: 0.648, 0.747). In addition, the study found significant interactions between simple interaction, leisure and recreational, and intellectual participation social activities and air pollution.

Conclusion: Our study demonstrated an antagonistic effect of PM2.5 and social activities on cognitive function in middle-aged and older Chinese adults.

Keywords: Air pollution; CHARLS; China; Cognitive function; Cohort study; Interactive analysis.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: Ethical approval for all the CHARLS waves was granted from the Biomedical Ethics Review Committee of Peking University, and all participants were required to provide written informed consent. The ethical approval number was IRB00001052-11015. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Spatial distribution of average cognitive function scores and average annual air pollutant levels in 2013, 2015 and 2018. Notes: White portion represents no data
Fig. 2
Fig. 2
Model estimates of the relationship between PM2.5, NO2, O3 and social activities and their interaction term and participants' cognitive function scores. Notes: Model 1, 3, 5, crude model; Model 2, 4, 6, adjusted for sex, age, marital status, educational level, region, living area, individual health behavior variables (smoking status and drinking status) and chronic disease conditions based on crude models; β, Beta; CI, confidence interval
Fig. 3
Fig. 3
Interaction effect plot. Notes: PM2.5, annual mean PM2.5 concentration; Level of social activities social activeness scores; cognition, cognitive function scores

Similar articles

Cited by

References

    1. Miller BL, Clare L, Wu Y-T, Teale JC, MacLeod C, Matthews F, et al. Potentially modifiable lifestyle factors, cognitive reserve, and cognitive function in later life: a cross-sectional study. PLoS Med. 2017;14(3):e1002259. - PMC - PubMed
    1. Han X, Shi D, Zhou X, Yang Y, Zhu Z. The training and transfer effect of cognitive training in old adults. Adv Psycholog Sci. 2016;24(6):909.
    1. Jia Y. Research progress on cognitive function and intervention of the elderly. Adv Psychol. 2022;12(5):1827–32.
    1. Fang EF, Xie C, Schenkel JA, Wu C, Long Q, Cui H, et al. A research agenda for ageing in China in the 21st century (2nd edition): Focusing on basic and translational research, long-term care, policy and social networks. Ageing Res Rev. 2020;64:101174. - PMC - PubMed
    1. Man W, Wang S, Yang H. Exploring the spatial-temporal distribution and evolution of population aging and social-economic indicators in China. BMC Public Health. 2021;21(1):966. - PMC - PubMed

LinkOut - more resources