Association between environmental factors and cognitive function among older adults : evidence from China health and retirement longitudinal study

Abstract

Globally, dementia is the main cause of disability and dependency among older adults. Dementia prevention requires identifying modifiable risk factors of dementia. However, evidence from longitudinal studies covering a comprehensive set of modifiable risk factors was lacking globally and even scarcer in China. Emerging evidence suggested that physical environmental factors, such as air pollution and land use/land cover (LULC), might be associated with dementia/cognition. However, most robust evidence was limited to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and green space. The impact of other components of air pollution and LULC remains unclear. In this thesis, four interconnected studies comprehensively examined cognitive function associated with both individual-level and environmental risk factors in China. Study one reviewed evidence on the association between air pollution and cognitive decline and dementia. While PM2.5 and NO2 were identified as the most significant risk factors, good-quality evidence from China remained highly homogeneous. Covariates were usually not comprehensively considered in previous studies. Hence, this study highlighted the need to examine the longitudinal association between air pollution and cognition with a nationally representative dataset and fully controlled covariates among older Chinese adults. Study two systematically summarized findings regarding the association between LULC and cognitive decline and dementia. Green space was most widely examined and presented a protective effect on cognitive function. However, the impact of diverse vegetation structures and other LULC features on cognitive function remained ambiguous for lack of standardized measurement. Findings accentuated the importance of assessing the association between LULC features and cognitive decline with standardized measurements. Study three applied multilevel models (MLM) to analyze the associations between modifiable risk factors and cognition. Findings suggested that education showed a protective effect on cognitive function, whereas hearing loss, depressive symptoms, social isolation, and polluting cooking fuel was negatively associated with all cognitive measures. PM2.5 was only associated with worse episodic memory. Smoking was associated with a faster cognitive decline. This study suggested that tailored interventions should be conducted to reduce air pollution, screen depressive symptoms and hearing loss, encourage smoking cessation and social participation, and promote education equality in China. Study four applied latent profile analysis (LPA) to cluster the candidate cities based on their distribution of local climate zone (LCZ). The results showed five distinct LULC profiles. MLM models assessed the impact of LULC profiles on three measures of cognition. The models found that dense trees and water bodies had protective effects on mental status, whereas other vegetation types, might have no effect or negative effect on mental status. Urbanization had dual effects on mental status. These findings suggest that policy makers should attend to the construction of dense trees and water bodies in urban planning for older adults.

This thesis describes the cognitive trajectories among a representative Chinese population sample, examines the personal risk factors, and identifies physical environmental factors. These findings enable individual-level and population-level understanding of cognitive decline to promote effective clinical practice and tailored urban planning strategies to slow cognitive decline and prevent dementia, thus reducing the healthcare burden. (498 words)