The dynamics of transgenerational obesity: simulating systems solutions

 拟议的NIDDK K 01奖的目的是开发一个独立的研究计划，调查环境和行为方法，以减轻多代影响产妇肥胖。候选人是一名肥胖流行病学家，在青少年和成人肥胖的环境和行为影响方面具有丰富的专业知识，以及广泛的定量方法。候选人最近在围产期的生命过程和肥胖的胎儿编程的专业知识。候选人的长期目标是帮助理解早期生命中编程的生物相容性如何通过生命过程和多代人与行为和环境的复杂系统相互作用。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）系统科学的专业知识。这种专业知识对于创新的跨学科研究是必要的，该研究整合了生物学和流行病学知识，以调查多代肥胖过程。这项培训将由一个跨学科的导师团队提供支持，该团队由慢性病流行病学（Fortmann;主要导师），胎儿编程和胎盘学（Thornburg），母胎医学（Caughey）和系统科学（Wakeland）的专家组成。这项拟议的研究将开发一种新的方法来调查母亲肥胖对多代人的影响。它克服了胎儿编程是一个固有的多代现象的挑战，但在人类群体中的多代研究是不可行的传统方法。它使用了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强大经验数据和对合成人群中人类行为的多层次影响。该模型将解释母亲肥胖对后代肥胖易感性的生物学影响，儿童期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群和亚组特定肥胖患病率的影响，以及（3）确定模拟饮食和身体活动变化对四代人群肥胖患病率的影响。这项研究将量化母亲肥胖如何引起肥胖升级的正反馈循环，并提供对复杂系统中产生最佳长期肥胖患病率降低的最佳策略的首次评估。研究和培训活动将在提交R 01申请时达到高潮，以调查胎儿编程如何传播肥胖相关健康（基于代理的模型）中的多代种族/种族差异，以及在补救胎儿编程改变的行为因素的流行病学研究中整合胎盘指标。

 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.