%0 Journal Article %J International Journal of Geriatric Psychiatry %D 2022 %T The intersectionality of life course socioeconomic status, race, and cognitive decline: An 18-year follow-up %A Zeng, Yue %A Sang Lum, Terry Yat %A Chen, Yu-Chih %K Cognitive decline %K race %K socioeconomic status %K trajectory %X Objectives Studies have documented the impact of childhood socioeconomic status (SES) on cognition. However, research that simultaneously considers SES in varied life stages, the multidimensional mechanisms, and racial differences is relatively understudied. This study examines the intersectionality across age, SES, and race and its impact on cognitive trajectories. Methods Using 8,376 respondents aged 65+ from the 1998-2016 Health and Retirement Study, we used latent growth curve modeling to examine the effects of four life course models (latency, pathway, accumulation, and mobility) on 18-year trajectories of mental status and episodic memory. We further tested for differences in the links between SES and cognitive trajectories between black and white respondents. Results Cognitive function declines with age and is interrelated with SES and race. Adulthood has a stronger effect on cognitive performance than childhood. However, linked positive childhood and adulthood SES contributes to positive cognition. Accumulated SES disadvantages were associated with lower cognition. Older adults with downward mobility and low SES throughout their lifespans had the lowest cognition scores. Life course models operated differently on trajectories of cognitive decline, yet these effects were particularly evident among older black respondents. Overall, those with socioeconomic advantages tended to have a slower decline in cognition, while a faster decline occurred for those with accrued disadvantages. Conclusions Cognitive performance is a complex, longitudinal process intertwined with socioeconomic conditions and population heterogeneity shaped by life course contexts. Policies that facilitate healthy cognitive performance and address SES inequality could equalize health opportunities and address racial cognitive disparities later in life. %B International Journal of Geriatric Psychiatry %V 37 %G eng %N 8 %R 10.1002/gps.5774 %0 Journal Article %J Innovation in Aging %D 2019 %T PATTERNS OF WEALTH TRAJECTORY IN LATER LIFE: CRITICAL PERIOD, ACCUMULATION, AND SOCIAL MOBILITY MODELS %A Chen, Yu-Chih %A So Jung Park %A Morrow-Howell, Nancy %K modeling %K social mobility %K Wealth %K wealth trajectory %X Wealth, an important financial cushion for older adults to buffer economic stress, requires a longer time to accumulate and develop in one’s course of life. However, little is known about the trajectories of wealth in later life, and how the life course socioeconomic status (SES) may contribute to the development of wealth at old-age. This study investigated longitudinal patterns of wealth trajectory and whether SES across the life course affects these trajectories using critical period, accumulation, and social mobility models. Using data from 16,189 adults aged 51 and older from the 2004-2014 Health and Retirement Study, a growth mixture model was used to explore distinct wealth trajectories. Impacts of life course models were studied using multinomial logistic regression. Results showed that four heterogeneous latent classes of wealth were identified: Stable high (reference group), Low and increasing, Stable low, and High but decline. Disadvantaged adulthood SES, accumulated exposure to socioeconomic risks, and downward or persistent socioeconomic disadvantage over the life course were associated with Stable low, Low and increasing, and High but decline, supporting all three life course mechanisms on wealth development in later life. Evidence suggests that wealth development is heterogeneous across individuals, and a strong gradient effect of life-course SES on wealth trajectories are clearly observed. Programs and policies should address the effects of life course on wealth development to strengthen the economic well-being in later life. %B Innovation in Aging %V 3 %P S382 - S382 %8 2019/11/08 %@ 2399-5300 %G eng %U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6840301/ %N Suppl 1 %! Innov Aging %0 Journal Article %J The Gerontologist %D 2018 %T Activity Patterns and Health Outcomes in Later Life: The Role of Nature of Engagement %A Chen, Yu-Chih %A Putnam, Michelle %A Lee, Yung Soo %A Morrow-Howell, Nancy %K Activity engagement %K Cognition %K depression %K Self-rated health %X The health benefit of activity participation at older ages is documented in the current literature. Many studies, however, only explored the health benefits of engaging in a few activities and did not examine mechanisms connecting activity participation to health. We investigated the pathway between activity and health by testing the mediation role of the nature of engagement (physical, cognitive, and social) on physical, mental, and cognitive health of older adults.We analyzed data of 6,044 older adults from the 2010 and 2012 Health and Retirement Study linked with 2011 Consumption and Activity Mail Survey. We used latent class analysis to identify the patterns of participating in 33 activities as well as patterns of nature of engagement, and examined how these patterns were associated with cognition, depressive symptoms, and self-rated health in later life.Meaningful patterns of activity (high, medium, low, passive leisure, and working) and the nature of activity engagement (full, partial, and minimal) were identified. High and working groups, compared to the passive leisure group, showed better health and cognition outcomes. The nature of engagement mediated the relationship between activity patterns and health, especially for older adults who were either full or partially engaged.The nature of engagement may play a more important role than the activity itself in relation to health. Identifying the heterogeneity in activity engagement in later life is critical for tailoring interventions and designing programs that can improve the health of older adults. %B The Gerontologist %V 59 %P 698-708 %8 04 %G eng %U https://www.ncbi.nlm.nih.gov/pubmed/29659800 %R 10.1093/geront/gny023