Abstract: Understanding Environmental Effects on the Trajectories of Cognitive Functioning Among Older Adults in China (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

All live presentations are in Eastern time zone.

162P Understanding Environmental Effects on the Trajectories of Cognitive Functioning Among Older Adults in China

Schedule:
Tuesday, January 19, 2021
* noted as presenting author
Mingyang Zheng, MSW, Doctoral Student, University of Minnesota-Twin Cities, Saint Paul, MN
Background/Purpose: China is rapidly becoming an aging society. As people get older, they are more vulnerable to experiencing cognitive decline, which may lead to cognitive impairment or dementia. Experiencing cognitive decline can affect older adults’ quality of life as well as that of their family caregivers (Andersen et al., 2004; Hepburn et al., 2001). And yet, our current understanding regarding cognitive decline among older adults is limited as the findings are inconsistent and even contradictory. One of the reasons might be that most studies have tried to address the issue at the individual level, failing to examine the environmental effects on cognitive functioning. Thus, the current study investigated: (1) What is the trajectory of cognitive decline among older adults in China? and (2) What specific environmental factors, such as neighborhood SES, healthcare quality, and neighborhood physical environment, are associated with Chinese older adults’ trajectories of cognitive decline.

Methods: The current study employed a longitudinal design drawing data from three waves of the China Health and Retirement Longitudinal Study (CHRALS) to examine the trajectories of cognitive decline among middle and old age adults in China. CHRALS is a nationally representative longitudinal panel survey of 17,708 Chinese residents aged 45 and older since 2011(Zhao et al., 2014). The total sample in the study was 3,720 adults aged 45 and above from 418 communities, which consist of 11,160 observations. Multilevel growth curve models were used to explore the trajectories of cognitive change among respondents and the environmental impacts on the respondents’ cognitive functioning. Analyses were controlled for individual characteristics, such as gender, age, education, marital status, activities of daily livings, log personal consumption expenditures (PCE), health status, and level of depression.

Results: Our preliminary findings suggested that environmental factors can affect people’s cognitive functioning. Controlling for individual characteristics, respondents living in the community with better public infrastructure were associated with better cognitive functioning (ß = 0.22, p < .001); respondents living in the rural area were associated with lower cognitive functioning compared to people living in urban areas ( ß = 0.96, p < .001). Community socioeconomic status also affected individuals’ cognitive functioning. The higher log of community PCE was associated with better cognitive functioning (ß = 0.44, p < .001). Respondents living in a community that had easy access to outdoor activity facilities also had higher cognitive functioning (ß = 0.43, p < .05).

Conclusions and Implications: These findings demonstrate that the neighborhood environment can impact middle and older age adults’ cognitive functioning. Understanding the impact of neighborhood environments will help social workers to rethink their intervention strategies on improving cognitive functioning among older adults. Currently, social work interventions tend to focus on individuals. The study may help social workers understand the environmental impacts in depth and engage in building an age friendly community through policy practice.