Determining the dynamic influence of social networks on development and health trajectories

确定社交网络对发展和健康轨迹的动态影响

• 批准号: 9300952
• 负责人: Brenda McCowan
• 金额: $ 60.83万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9300952
• 关键词: Adolescence; Adopted; Asthma; Biological; Biological Markers; Birth; Chronic Obstructive Airway Disease; Communities; Complex; Coupled; Development; Disease; Disease Outcome; Effectiveness; Family Characteristics; Glucocorticoids; Health; Human; Immune system; Individual; Infant; Infant Development; Intervention; Joints; Lead; Life; Methods; Modeling; Neurosecretory Systems; Outcome; Parents; Pathway Analysis; Physiological; Play; Process; Public Health; Regulation; Research; Resistance; Risk; Role; Science; Shapes; Social Development; Social Environment; Social Network; Societies; Socioeconomic Status; Statistical Methods; Structure; System; Systems Development; Techniques; Testing; Time; Tissues; Vacuum; Variant; Work; biological systems; disease diagnosis; experimental study; hormone regulation; immune function; improved; insight; member; multilevel analysis; nonhuman primate; peer; predictive marker; prevent; psychologic; public health relevance; social; social group

 DESCRIPTION (provided by applicant): The ability to treat and prevent illness and improve human health requires not only a detailed understanding of the complex interplay of biological systems contributing to disease processes but also the mechanisms underlying the influence of social complexity on biological systems. A developmental systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health by investigating their effects on modulating the interplay among biological systems during development. The proposed research adopts this approach by modeling multi-level networked systems over time in a well-established nonhuman primate model. We predict that the coordination and regulation of biological systems within individuals are critical to shaping health trajectories and are dynamically modulated by the complex network structure of individuals' social relationships.