Structure and Change: New Developments in Research on Cumulative Dis/Advantage

In a time of heightened social inequality and concern to reckon with its sources and consequences, the relevance of cumulative dis/advantage (CDA) to understanding patterns of aging has become even clearer, and CDA research has continued to expand in several fresh directions. Papers in this symposium will review the current state of knowledge regarding CDA and will present new analyses addressing key questions of its intersections with social change and its structural patterning. We will begin with a review of knowledge on comparative evidence regarding cumulative dis/advantage and its cross-national patterning. With regard to change, will examine the compare the effect of the 2008 recession and subsequent recovery across generational cohorts through a comparative examination of trajectories of income inequality. We will also present evidence on the impact of gender, focusing on women’s late-life health.

Sociodemographic, Health, and Caregiving Patterns of Aging Caregivers in Oregon: Gender Comparisons and the Role of Leisure Activities

Recent studies have projected an increase in aging informal caregivers who are often dealing with their frailty. However, little is known about their health, caregiving factors, or coping resources that promote health. Informed by lifespan perspective and health behavior models, this study examined the gender differences in health and caregiving profiles of aging informal caregivers and investigated the association between leisure activity and unhealthy days. A sample of 565 informal caregivers (>50 years) was drawn from the Oregon version of the 2017 Behavioral Risk Factor Surveillance System. Descriptive analyses revealed that the caregivers were mainly women between 60 and 69, White non-Hispanic, married, college graduates, retired and healthinsured. Negative binomial regression showed that leisure activities were related to fewer odds of reporting unhealthy days for most comparison scenarios. Findings emphasize the importance of accounting for group differences and similarities in understanding health and caregiving factors among informal caregivers.

A Panel of DNA Methylation and Proteomic Biomarkers for Specific Aging Pathways

Most aging biomarkers such as DNA methylation and proteomic clocks have focused on measuring overall “biological age,” a single number that predicts age-related morbidity and mortality better than absolute chronological age. While intuitive and interpretable, this single biological age number does not account for the possibility that different individuals may preferentially experience aging in different molecular and cellular pathways, and therefore does not suggest personalized aging interventions. We reasoned that a panel of biomarkers each capturing specific aging pathways, such as mitochondrial dysfunction or cellular senescence, may capture the heterogeneity of aging better than existing composite measures. To address this, we employed weighted gene co-expression network analysis to cluster tissue-specific transcriptomes and the serum proteome into specific modules with distinct biological functions and characterized how these modules change with age. We trained DNA methylation proxies of these functional modules that we then applied to independent validation data to identify associations with age-related morbidity and mortality. Clustering analysis using the DNA methylation biomarkers showed that different individuals show distinct patterns of aging. These pathway-specific biomarkers will elucidate how different aging mechanisms interact with each other to produce the larger phenomenon of aging, and for evaluating novel therapeutics targeting specific hallmarks of aging.

GENETIC INFLUENCES ON LUNG FUNCTION CONTRIBUTE TO SUBSEQUENT AGE CHANGES IN MOTOR FUNCTION

Researchers have striven to determine whether the age changes in physical and cognitive functioning are coincident, or does change in one domain precede functioning in the other. Dual change score models (DCSM) facilitate testing of hypotheses about temporal patterns of aging. Previous investigations in the Swedish Adoption/Twin Study of Aging (SATSA) indicate three directional effects: age changes in processing speed contribute to subsequent age changes in cognition, age changes in lung function contribute to subsequent age changes in processing speed, and age changes in motor function contribute to subsequent age changes in processing speed. In the current analysis we apply DCSM to twin data to examine the nature of the longitudinal relationship between motor functioning and lung function. Three motor functioning factors were created from 20 performance measures: balance, flexibility, and fine motor movement. Peak expiratory flow measured lung function. Participants were 829 adults aged 50-88 at the first of 9 waves of testing (mean = 4.4 waves) covering a 27-year follow-up period (mean = 13.1 years). Model comparisons indicated that genetic influences on decline in lung function contributed to subsequent decline in motor function. Combined with previous results, these results suggest a pathway that may start with age declines in lung function, which then contribute to declines in motor function, which in turn contribute to subsequent declines in processing speed and then cognitive decline. These data indicate that interventions focusing on improving or maintain lung function should have the added effect of maintaining motor and cognitive function.

LEVERAGING ANALYTIC METHODS TO EXPAND OPPORTUNITIES IN AGING-RELATED HEALTH DISPARITIES RESEARCH

The objective of the Symposium is to improve the understanding of how existing analytic methods and data can be leveraged to make progress in understanding the causes and mechanisms of health-related disparities in Alzheimer’s disease, related dementias and other prominent age-related diseases. Topics will cover a range of academic and administrative topics including: i) advanced analytic methods and modeling of health disparities with application to racial and geographic disparities in AD/ADRD; ii) the role of repeated anesthetic and surgical exposure in generation of disparities in AD/ADRD risk; iii) the nature of health disparities in cognitive aging as parallel to or distinct from health disparities in patterns of aging in other systems in the body; iv) recent advances in machine learning applied to large claims databases involving medical disparities; and v) geographic-related disparities in life expectancy across the U.S. A focus will be made on demonstrating how studies using established administrative data resources such as Medicare claims databases combined with innovative analytic approaches such as partitioning analyses, time-series based methods of projection and forecasting, and stochastic process models can be used to uncover previously overlooked or understudied aspects in this area of research. Analyses of such increasingly available large health datasets provides an opportunity to obtain nationally representative multiethnic results based on individual-level measures that reflect the real care-related and epidemiological processes ongoing in the U.S. healthcare system and allows the targetting of relatively rare diseases in relatively small population subgroups.

TESTING HEALTH DISPARITIES IN COGNITIVE AND BIOLOGICAL AGING IN OLDER ADULTS IN THE UNITED STATES

We conducted analysis to test if health disparities in cognitive aging were parallel to or different from health disparities in patterns of aging in other systems in the body, and if race/ethnicity-related disparities could be accounted for by differences in socioeconomic circumstances across the life-course. We analyzed data from more than 10,000 adults participating in the US NHANES and US Health and Retirement Study. We measured cognitive aging using neuropsychological tests of processing speed and memory. We measured aging in other systems using composite indices of biological aging based on organ-system function tests and blood chemistries. We conducted analysis to (i) quantify and compare health disparities in cognitive aging and biological aging; (ii) test if individuals exhibiting accelerated cognitive aging were also exhibiting accelerated biological aging; and (iii) test if race/ethnic disparities in cognitive and biological aging could be explained by measured socioeconomic resource differences in childhood and later life.