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

项目总结/摘要 心脏代谢（CM）疾病伴有心血管（CV）风险增加。治疗和 生活方式干预可以针对和减少一个或多个CM风险因素，从而预防或延迟不良CM 降低CV死亡率。然而，CV死亡率的下降在过去十年中已经趋于平缓， 这可能是由于高血压、肥胖、糖尿病和其他新兴CM风险因素的患病率不断增加 （包括尤其是睡眠障碍）。因此，至关重要的是：1）描述 多模态相互关联的CM风险因素，以及2）开发CM风险亚组的新分类标准 发现，使新的有针对性的多模式干预，以减少CM风险的高风险亚组，并提高 CM健康然而，现有的研究CM风险亚组发现有三个关键的知识差距。 GAP I：之前的研究主要集中在中年和老年人群体，对以下方面的研究有限： 年轻人群中早发性CM的危险因素。GAP II：与传统的CM风险因素不同，睡眠剥夺 和精神压力是新出现的CM危险因素。然而，人们对它们的了解非常少，特别是在美国。 西班牙裔/拉丁裔。GAP III：新推出的西班牙裔社区健康研究（HCHS）调查了 西班牙裔/拉丁裔中CM疾病的患病率和风险因素，并提供了前所未有的机会， 在西班牙裔/拉丁裔晚期青少年/年轻人中确定CM疾病的高风险亚组，但 缺乏结构化的多维分析方法，无法直接分析和聚类 多模式互联CM风险因素。这个丰富而全面的数据集未得到充分利用。 我们提出了一个二次分析：1）开发一个新的稀疏多模态结构方程模型 （多SEM）聚类多模态混合类型的风险因素; 2）应用开发的算法来识别和 基于多个亚组的亚组特异性特征，表征高风险与低风险CM疾病亚组， 模态睡眠中断，精神和文化适应压力，代谢失调，肥胖，身体活动不足， 来自HCHS数据集的晚期青少年/年轻人营养不良。具体目标是： 目的1：开发一种新的稀疏多SEM，用于CM风险亚组识别和表征， 典型混合型危险因素。 目的2：将稀疏多SEM应用于HCHS数据集，以：（1）识别，表征和验证CM风险 多模态CM风险因素的亚组;（2）总结 西班牙裔/拉丁裔晚期青少年/年轻人。 影响：这项研究将有助于为综合多模式提供循证指南和干预措施。 具有成本效益的早期干预措施，针对具有CM不良结局早发风险的亚组， 西班牙裔/拉丁裔晚期青少年/年轻人，最终改善从青少年到成人健康的过渡 护理和减少CM健康差距和医疗保健费用在美国西班牙裔/拉丁裔人口。

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.