The dynamics of transgenerational obesity: simulating systems solutions

跨代肥胖的动态：模拟系统解决方案

• 批准号: 9032966
• 负责人: Janne Boone-Heinonen
• 金额: $ 14.51万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2018-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9032966
• 关键词: Accounting; Adolescence; Adolescent; Adult; Affect; Age; Animals; Behavior; Behavioral; Biological; Biological Models; Biology; Child; Childhood; Chronic Disease; Clinical; Complex; Computer Simulation; Coronary artery; Data; Desire for food; Development; Diet; Diet Modification; Environment; Epidemic; Epidemiologic Studies; Epidemiologist; Epidemiology; Ethnic Origin; Ethnic group; Fatty acid glycerol esters; Feedback; Female; Fetal Development; Functional disorder; Future; Future Generations; Generations; Goals; Health; Health Planning; Health behavior; High Prevalence; Human; International; Investigation; Knowledge; Life; Life Cycle Stages; Longitudinal Studies; Mentored Research Scientist Development Award; Mentors; Mentorship; Metabolic; Methodology; Methods; Modeling; National Health and Nutrition Examination Survey; National Institute of Diabetes and Digestive and Kidney Diseases; Obesity; Perinatal; Physical activity; Physiological; Population; Population Characteristics; Predisposition; Pregnancy; Prevalence; Prevention strategy; Process; Public Health; Publishing; Race; Research; Research Activity; Research Infrastructure; Risk; Science; Solutions; Study models; Subgroup; System; Techniques; Time; Training; Training Activity; Variant; Vital Statistics; Weight; age group; base; behavior influence; career development; cohort; fetal medicine; fetal programming; follow-up; health disparity; innovation; models and simulation; novel; obesity in children; obesity risk; offspring; population health; prenatal; programs; public health relevance; skills; trend; young adult

 DESCRIPTION (provided by applicant): The objective of the proposed NIDDK K01 award is to develop an independent research program that investigates environmental and behavioral approaches to mitigating multigenerational effects maternal obesity. The candidate is an obesity epidemiologist with strong expertise in environmental and behavioral influences on obesity in adolescents and adults, and a wide range of quantitative methods. The candidate has recent expertise in the perinatal period of the life course and fetal programming of obesity. The candidate's long-term goal is to contribute understanding of how biological susceptibilities programmed in early life interact with a complex system of behaviors and environments through the life course and through multiple generations. The proposed career development goals include gaining expertise in (1) placental biology and its linkages to fetal programming and (2) systems science. This expertise is necessary for innovative transdisciplinary research that integrates biological and epidemiological knowledge to investigate multigenerational obesity processes. This training will be supported by an interdisciplinary mentorship team composed of experts in chronic disease epidemiology (Fortmann; primary mentor), fetal programming and placentology (Thornburg), maternal-fetal medicine (Caughey), and systems science (Wakeland). The proposed research will develop a novel methodology for investigating the effects of maternal obesity over multiple generations. It overcomes the challenge that fetal programming is an inherently multigenerational phenomenon, yet multigenerational research in human populations is not feasible with traditional methods. It uses a complex system modeling technique - agent-based models - to integrate robust empirical data on fetal programming processes and multi-level influences on human behavior in a synthetic population. The model will account for the biological effects of maternal obesity on offspring obesity susceptibility, cumulative impacts of childhood behaviors on prenatal behaviors and health, and other complexities. We will (1) develop and validate the agent-based model, then use it to (2) determine the effects of fetal programming on population-wide and subgroup-specific obesity prevalence over four generations and (3) determine the effects of simulated diet and physical activity changes on population-wide obesity prevalence over four generations. This research will quantify how maternal obesity can induce a positive feedback loop of escalating obesity and provide the first assessment of optimal strategies that yield optimal long-term reductions in obesity prevalence within a complex system. Research and training activities will culminate in submission of R01 applications to investigate how fetal programming propagates multigenerational race/ethnic disparities in obesity-related health (agent-based model), and integration of placental metrics in an epidemiologic study of behavioral factors that remediate fetal programming alterations.