Developmental origins of BMI trajectory among adolescents

描述（由申请人提供）：肥胖有望超过烟草，成为美国可预防死亡的最大贡献者。超重儿童成年后超重的风险增加，并且与许多负面健康结果相关的高发病率风险增加（例如，心血管疾病、糖尿病、某些癌症和中风）。超重和肥胖的危险因素在生命早期就开始了，甚至在产前就开始了，尽管研究生命早期因素和肥胖之间纵向关系的研究很少。由于大多数现有研究缺乏重复的拟人化测量，我们对早期生活因素对跨越儿童期、青春期和成年早期的个体超重和肥胖轨迹的影响的理解特别有限。我们建议研究产前和产后因素对从儿童晚期和青春期过渡到成年早期的青少年BMI轨迹的影响。鉴于儿童和青少年时期的肥胖会增加成年后肥胖的风险，因此旨在提高我们对BMI升高轨迹的潜在可改变风险因素的理解的研究非常重要。迄今为止，大多数肥胖研究未能探索解释BMI轨迹模式的风险因素。使用的统计分析技术，能够表征群体的青年，表达随着时间的推移，一般生长混合模型的BMI差异模式，该项目将评估的影响，关键时期的暴露对肥胖的风险。这些目标将通过“今日成长研究”（GUTS）进行调查，这是一项正在进行的纵向队列研究，研究对象是参加“护士健康研究II”（NHS II）的母亲所生的9 039名少女和7 843名男孩（1996年基线年龄为9-14岁）。因此，这些数据集也提供了一个独特的机会来探索肥胖的代际预测因素以及产前和产后因素的交叉点，以及儿童健康行为，以解释从童年到青年期过渡期间BMI不同轨迹的预测因素。 公共卫生相关性：这项拟议的研究将使用纵向队列数据（今天成长研究）来调查产前和产后因素对从儿童晚期和青春期过渡到成年早期的青少年BMI轨迹的影响。所选择的结果在生命早期发生率很高，并影响许多负面的健康结果（例如，心血管疾病、糖尿病、某些癌症、中风）。核心假设是，早期生活中的不利因素对后来的体重轨迹有独立和累积的影响，但可能会被生活方式和行为所改变。我们将使用生长混合模型来估计从儿童晚期到成年早期的BMI变化模式，以及产前和产后因素和儿童行为对BMI轨迹的相对影响。这种新的分析技术有望识别出不同的肥胖风险人群，并针对每个亚组可能独特的长期肥胖预防的关键时间段。

DESCRIPTION (provided by applicant): Obesity is poised to overtake tobacco as the greatest contributor to preventable death in the United States. Overweight children are at increased risk of being overweight as adults and are at increased risk of high morbidity related to a number of negative health outcomes (e.g., cardiovascular disease, diabetes, some cancers, and stroke). Risk factors for overweight and obesity start in early life, even prenatally although research that examines the longitudinal relationship between early life factors and obesity are sparse. We are particularly limited in our understanding of the influence of early life factors on individual overweight and obesity trajectories spanning over childhood, adolescence and early adulthood given the lack of repeated anthropomorphic measurements in most existing studies. We propose to examine the influence of prenatal and postnatal factors on BMI trajectory among youth transitioning from late childhood and adolescence into early adulthood. Given that obesity in childhood and adolescence increases risk for obesity in adulthood, research aimed at enhancing our understanding of potentially modifiable risk factors for an elevated BMI trajectory is important. To date most obesity research has failed to explore risk factors that explain patterns of BMI trajectory. Using a statistical analysis technique that is able to characterize groups of youth that express differential patterns of BMI over time-General Growth Mixture Modeling-this project will assess the impact of critical periods of exposure on obesity risk. These aims will be investigated using the Growing Up Today Study (GUTS), an ongoing longitudinal cohort study of 9,039 adolescent girls and 7,843 boys (aged 9-14 at baseline in 1996) who are offspring of mothers participating in the Nurses' Health Study II (NHS II). As a result, these datasets also allow for a unique opportunity to explore intergenerational predictors of obesity as well as the intersection of prenatal and postnatal factors, and childhood health behavior in explaining predictors of distinct trajectories of BMI during the transition from childhood to young adulthood. PUBLIC HEALTH RELEVANCE: The proposed study will use longitudinal cohort data (Growing Up Today Study) to investigate the influence of prenatal and postnatal factors on BMI trajectory among youth transitioning from late childhood and adolescence into early adulthood. The chosen outcome occurs with high prevalence in early life and influences a number of negative health outcomes (e.g., cardiovascular disease, diabetes, some cancers, stroke) throughout the life cycle. The central hypothesis is that adverse early life factors have both an independent and a cumulative impact on later weight trajectory but may be modified by lifestyles and behaviors. We will use growth mixture modeling to estimate the pattern of change in BMI across age beginning in late childhood to early adulthood and the relative influence of the pre- and post-natal factors and childhood behavior on the BMI trajectories. This novel analytic technique holds the promise of identifying distinct populations at risk for obesity and targeting critical time periods for long-term obesity prevention that may be unique to each subgroup.