Latent Growth Curve Paths to Longevity: The Terman Study

描述(由申请人提供)：从儿童早期开始的发育生物心理社会轨迹的差异可能会将那些到了特别健康的高龄的人与那些过早死亡或患有慢性病的人区分开来。来自特曼生命周期研究(Terman Life Cycle Study)的1528名个体将使用潜在增长曲线方法来检查纵向轨迹的变化，这是一份为期8年的综合档案。虽然研究中的人是因为童年时的智力和希望而被挑选出来的，但在后来的成功、寿命和疾病方面有很大的差异，包括痴呆症。在现有的丰富的心理社会、健康和死亡信息的80年中，生命轨迹尚未得到考虑。这个项目将使用动态建模方法来检查个人特征的稳定性和变化模式，包括体力活动水平、社会支持和个性，以及作为特定原因死亡率的函数的增长曲线的变化(病理学家编码)。儿童时期的数据将被用来预测成长轨迹的变化，例如出生体重、哺乳、儿童疾病、发育里程碑、性别、社会经济地位和参与者出生时的父母年龄。成年期发生的生活事件也将被视为健康和心理社会轨迹的潜在转折点，例如离婚或配偶死亡。样本和家庭因素，如智力和父母的寿命，将在分析中统计考虑在内。根据该请求(RFA)，目的是利用新的建模技术扩大对现有研究的使用和合作，以评估健康和心理社会轨迹的模式及其随时间的动态相互关系，以便区分那些达到老年以及他们是否健康达到老年的人。

DESCRIPTION (provided by applicant): Disparities in developmental biopsychosocial trajectories beginning in early childhood may distinguish those who reach advanced age exceptionally healthy from those who suffer an early death or chronic disease. Variations in longitudinal trajectories will be examined using a latent growth curve approach on 1,528 individuals from the Terman Life Cycle Study, a comprehensive 8-decade archive. Whilst individuals in the study were selected for childhood intelligence and promise, there was substantial variation in later success, longevity, and disease, including dementing illnesses. Life course trajectories have yet to be considered across the 8-decades of rich psychosocial, health and mortality information available. This project will use dynamical modeling approaches to examine patterns of stability and change for individual characteristics, including physical activity level, social support, and personality, and variations in growth curves as a function of cause-specific mortality (nosologist coded). Childhood data will be used as predictors of variations in growth trajectories, for example, birth weight, nursing, childhood illnesses, developmental milestones, gender, socioeconomic status, and parental age at participant's birth. Life events occurring in adulthood will also be examined as potential sources of turning points in health and psychosocial trajectories, for example, divorce or death of spouse. Sample and familial factors such as intelligence and parental longevity will be statistically accounted for in analyses. Consistent with the Request (RFA), the aim is to use new modeling techniques to expand use of and collaboration on an existing study to assess patterns of health and psychosocial trajectories as well as their dynamic interrelations across time in order to differentiate among those who reach old age and whether they reach it in good health.