The dynamics of transgenerational obesity: simulating systems solutions

 描述(由申请人提供)：建议的NIDDK K01奖项的目标是开发一个独立的研究计划，调查环境和行为方法，以减轻母体肥胖的多代影响。候选人是一位肥胖流行病学家，在环境和行为对青少年和成年人肥胖的影响方面拥有丰富的专业知识，并拥有广泛的量化方法。应聘者最近在围产期的生命过程和肥胖的胎儿规划方面拥有专业知识。候选人的长期目标是帮助理解在生命早期编程的生物易感性如何通过生命过程和多代人与复杂的行为和环境系统相互作用。拟议的职业发展目标包括获得(1)胎盘生物学及其与胎儿编程的联系和(2)系统科学方面的专业知识。这种专业知识对于整合生物学和流行病学知识以调查多代肥胖过程的创新跨学科研究是必要的。这项培训将由一个由慢性病流行病学(Fortmann；初级导师)、胎儿编程和胎盘学(Thornburg)、母胎医学(Caueh)和系统科学(Wakland)专家组成的跨学科导师小组提供支持。这项拟议的研究将开发一种新的方法来研究母体肥胖对多代人的影响。它克服了胎儿编程本质上是一种多代现象的挑战，但用传统方法在人类群体中进行多代研究是不可行的。它使用一种复杂的系统建模技术-基于代理的模型-来整合关于胎儿编程过程的可靠经验数据，以及在合成种群中对人类行为的多层次影响。该模型将考虑母亲肥胖对后代肥胖易感性的生物学影响，童年行为对产前行为和健康的累积影响，以及其他复杂性。我们将(1)开发和验证基于代理的模型，然后使用它来(2)确定胎儿编程对四代人的人群范围和亚组特定肥胖率的影响，以及(3)确定模拟饮食和体力活动变化对四代人人群肥胖率的影响。这项研究将量化母亲肥胖如何引发肥胖加剧的正反馈循环，并首次评估在复杂系统中产生最佳长期肥胖率降低的最佳策略。研究和培训活动将最终提交R01申请，以调查胎儿编程如何传播肥胖相关健康中的多代种族/民族差异(基于代理的模型)，并将胎盘指标整合到补救胎儿编程改变的行为因素的流行病学研究中。

 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.