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

美国西班牙裔/拉丁裔晚期青少年/年轻人的睡眠和心脏代谢健康

基本信息

批准号：
10636884
负责人：
Bing Si
金额：
$ 7.56万
依托单位：
STATE UNIVERSITY OF NY,BINGHAMTON
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-06-06 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10636884
关键词：
Accelerometer Acculturation Adolescence Adolescent Adult Affect Age Years Algorithms Atherosclerosis Attenuated Beds Blood Tests Cardiometabolic Disease Cardiovascular Diseases Cardiovascular system Cessation of life Characteristics Classification Clinical Communities Data Data Science Data Set Development Diabetes Mellitus Diet Dimensions Early Intervention Elderly Equation Etiology Fasting Funding Goals Health Health Care Costs Health Sciences Healthcare Heterogeneity Hispanic Hispanic Community Health Study Hispanic Populations Home Hour Hypertension Industrialization Inflammation Insulin Resistance Intervention Knowledge Latino Latino Population Life Style Link Measures Metabolic Metabolic Diseases Metabolic syndrome Minority Groups Modeling Myocardial Infarction Obesity Outcome Oxidative Stress Pathway interactions Physical activity Population Prevalence Psyche structure Quality of life Reproducibility Research Risk Risk Factors Scientist Sleep Sleep Apnea Syndromes Sleep Deprivation Sleep Disorders Sleep disturbances Sleeplessness Stress Stroke Structure Subgroup Therapeutic Intervention United States United States National Institutes of Health adverse outcome cardiometabolic risk cardiometabolism cardiovascular risk factor comorbidity cost effective intervention diabetes risk disorder subtype early onset epidemiology study ethnic discrimination evidence based guidelines health disparity high risk improved knowledge base lifestyle intervention middle age mortality multi-component intervention multidisciplinary multimodality novel nutrition personalized intervention physical inactivity prevent preventable death secondary analysis sleep health young adult

项目摘要

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.

项目摘要/摘要心脏代谢（CM）疾病伴随着心血管（CV）风险的增加。治疗和生活方式干预措施可以针对和减少一个或多个CM风险因素，从而防止或延迟不良CM 结果并降低简历死亡率。然而，在过去的十年中，简历死亡率的下降趋势，可能是由于高血压，肥胖，糖尿病和其他新出现的CM风险因素的流行率的增长所致（包括，尤其是睡眠障碍）。因此，至关重要的是：1）描述多模式互连CM风险因素，2）制定CM风险亚组的新分类标准发现，实现了新颖的目标多模式干预，以降低高风险亚组的CM风险并改善 CM健康。但是，现有关于CM风险亚组发现的研究具有三个关键的知识差距。 GAP I：先前的研究重点是中年和老年人，对年轻人口的早期CM风险因素。 GAP II：与传统的CM风险因素不同，睡眠不足精神压力是新兴的CM风险因素。但是，他们对他们的理解很少，尤其是在美国西班牙裔/拉丁裔。 GAP III：新的西班牙裔社区健康研究（HCHS）调查了西班牙裔/拉丁美洲人的CM疾病和危险因素的患病率，并提供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疾病高风险的亚组，但那里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连CM风险因素。这个丰富而全面的数据集未充分利用。我们提出了二级分析：1）开发一种新型的稀疏多模式结构方程模型（多SEM）到集群多模式混合型风险因素； 2）应用开发算法识别和根据多种多样的亚组特异性概况，表征高风险与低风险CM疾病亚组模态睡眠中断，精神和适应压力，代谢失调，肥胖，身体不活动和 HCHS数据集的晚期青少年/年轻人的营养不佳。具体目的是： AIM 1：开发一种新型的稀疏多SEM，用于CM风险亚组识别和表征多数模态混合风险因素。 AIM 2：将稀疏的多SEM应用于HCHS数据集中：（1）识别，表征和验证CM风险来自多模式CM风险因素的亚组；（2）总结可再现的CM风险亚组西班牙裔/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基于证据的指南和干预措施具有成本效益和早期干预措施，针对以早发风险不良CM结局的亚组西班牙裔/拉丁裔晚期青少年/年轻人，最终改善了从青少年到成人健康的过渡美国西班牙裔/拉丁美洲人的护理和降低CM健康差异和医疗保健费用。