Sleep and Cardiometabolic Health in United States Hispanic/Latino Late Adolescents/Young Adults

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Project Summary/Abstract Cardiometabolic (CM) disease is accompanied by increased cardiovascular (CV) risk. Therapeutic and lifestyle interventions can target and reduce one or more CM risk factors, and thus prevent or delay adverse CM outcomes and reduce CV mortality. However, the decline in CV mortality has flattened over the past decade, likely due to the growing prevalence of hypertension, obesity, diabetes, and other emerging CM risk factors (including and especially sleep disorders). Therefore, it is critical to: 1) delineate the substantial heterogeneity in multi-modal interconnected CM risk factors, and 2) develop new classification criteria for CM risk subgroup discovery, enabling novel targeted multi-modal intervention to reduce CM risk in high-risk subgroups and improve CM health. However, existing research on CM risk subgroup discovery has three critical knowledge gaps. GAP I: Prior research has focused on the middle-aged and older adult population, with limited research on early-onset CM risk factors in the younger population. GAP II: Unlike traditional CM risk factors, sleep deprivation and mental stress are emerging CM risk factors. However, they are very poorly understood, particularly in U.S. Hispanics/Latinos. GAP III: The newly available Hispanic Community Health Study (HCHS) investigates the prevalence of CM diseases and risk factors among Hispanics/Latinos and offers unprecedented opportunity to identify subgroups at high-risk for CM diseases among Hispanic/Latino late adolescents/young adults, but there is a lack of structured multi-dimensional analytical approaches with direct capacity to analyze and cluster the multi-modal interconnected CM risk factors. This rich and comprehensive dataset is under-utilized. We propose a secondary analysis to: 1) develop a novel sparse multi-modal Structural Equation Model (multi-SEM) to cluster multi-modal mixed-typed risk factors; 2) apply the developed algorithm to identify and characterize high-risk vs low-risk CM disease subgroups based upon subgroup-specific profiles across multi- modal sleep disruption, mental and acculturation stress, metabolic dysregulation, obesity, physical inactivity, and poor nutrition among late adolescents/young adults from the HCHS dataset. Specific Aims are: Aim 1: Develop a novel sparse multi-SEM for CM risk subgroup identification and characterization from multi- modal mixed-typed risk factors. Aim 2: Apply the sparse multi-SEM to the HCHS dataset to: (1) identify, characterize, and validate CM risk subgroups from multi-modal CM risk factors; (2) summarize reproducible CM risk subgroups among the Hispanic/Latino late adolescents/young adults. Impact: This study will help provide evidence-based guidelines and interventions for integrated multi-modal cost-effective and early interventions targeting subgroups with early-onset risk for adverse CM outcomes among Hispanic/Latino late adolescents/young adults, eventually improving the transition from adolescent to adult health care and reducing CM health disparities and health care costs in the U.S. Hispanic/Latino population.