Kudos to Kirsten Corazzini and her entire team for the submission of her NIH R03 application entitled “Social Networks, Chronic Illness, and Risk for Dementia in Older Health Disparity Populations.” This proposal requests funding for a two-year period with a start date of Sept. 1, 2018.

Alzheimer’s Disease and related dementias (ADRD) are incurable, neurodegenerative disorders affecting more than five million older adults in the United States and 47 million globally; the average person lives with ADRD for 10 years, and suffers unrelenting functional losses, requiring care that is challenging for the person with dementia and his or her family. As such, ADRD affects not just the person living with dementia, but also his or her social network of family and community. Extensive research has established the relationships between characteristics of social networks of older adults and neurocognitive disorders, generating recent efforts to target these social networks as potential levers for intervention development.  However, these early efforts lack a robust accounting for the multimorbid chronic illness burden experienced by persons with dementia, as fundamentally embedded in a person’s network.  Therefore, the purpose of this study is to integrate our knowledge of the effects of social network structure on ADRD with our knowledge of chronic illness symptoms and self-management, to empirically derive a typology of structure and symptoms in community-residing older adults, and relate this typology to risk for ADRD.  This purpose aligns with the National Institute on Aging’s Strategic Goal to understand the effects of personal, interpersonal, and societal factors on aging, including the mechanisms through which these factors exert their effects.  Using data from waves two and three of the National Social Life, Health and Aging Project (NSHAP), this quantitative, descriptive, secondary data analysis study aims to: (1) Based on the concepts of the Adaptive Leadership Framework for Chronic Illness, use latent class analysis to identify different patterns of social network structure (size, density) and chronic illness symptoms (pain, fatigue, sleep disturbance, mood, anxiety, well-being) in the NSHAP wave two nationally-representative sample of community-residing older adults and determine associated socio-demographic and clinical factors;  (2) Describe the relationship between different patterns and risk for mild cognitive impairment and dementia; and  (3) Use latent transition analysis to explore the potential relationships between an individual’s pattern of social network structure and chronic illness symptoms at wave two with pattern at wave three, five years later. Findings from this study will inform the next steps study that will integrate longitudinal data of networks and symptoms with health services utilization data to understand the impact of patterns of social networks and symptoms on trajectories of health, to inform intervention development.