Using genetic and environmental risks to understand variation in social, emotional, and educational outcomes in individuals with language impairments.

语言障碍（LI）是儿童最常见的障碍之一。它的特点是在没有耳聋等明显原因的情况下，在使用和理解口语方面存在问题。这种疾病是“隐藏的”，因为受影响的个体没有任何明显的、与其他孩子区别开来的特征。在5岁的孩子中，大约7%的人患有LI，是自闭症的7倍。受LI影响的儿童经常经历社会、情感健康和教育问题。成年后，许多人很难找到稳定的工作，社交功能障碍和精神健康问题的风险也在增加。尽管这种情况对儿童及其家庭有严重的影响，但LI在普通社区中鲜为人知。LI是一种多样的障碍，不同的儿童表现出不同的相关困难。并不是所有的孩子都会有不好的结果。例如，有些人可能有行为困难，而另一些人则没有。确定是什么让不同的孩子易受伤害是一项挑战。该项目将利用遗传风险信息和儿童生命最初两年的数据（如家庭中的书籍数量、社会经济地位等），使用一种称为潜在类别分析的统计方法，将儿童划分为子群体。这将允许调查属于某些亚群体是否会影响儿童中期的结果。例如，可能具有高遗传风险和良好家庭环境的儿童与具有低遗传风险和良好家庭环境的儿童的结果相当。如果事实证明确实如此，那就表明有利的家庭环境可以减轻遗传风险。这将为针对最脆弱儿童的资源提供证据，以改善他们的生活质量。该项目还将查明在社会适应、受教育程度和心理健康功能方面导致不良结果的途径。例如，可能有高遗传风险和不利的家庭环境的儿童在童年中期有行为困难和情感问题。途径分析提供了对多因素和不同潜在途径的检查：儿童如何从A到b。它还提供了对不同途径强度的评估，以及评估不同功能领域的结果在多大程度上源于共同或独特的途径。这一建议的部分优势在于在同一模型中包含了多种因素：遗传、环境和心理。据估计，与语言障碍相关的经济成本占国民生产总值的2.5%。关于不良后果途径的证据将对公共卫生措施和服务提供产生广泛影响。这种类型的项目需要大量的参与者。已批准使用雅芳父母和儿童纵向研究（ALSPAC）。这是一个现有的流行病学数据库，有大约7000名儿童的记录，因此该项目不需要新的数据收集。

Language Impairment (LI) is one of the most common childhood disorders. It is characterized by problems with using and understanding spoken language, in the absence of obvious causes such as deafness. The disorder is 'hidden', in that affected individuals do not have any marked visible features distinguishing them from other children. Among 5-year-olds, approximately 7% have LI - seven times more prevalent than autism. Children affected by LI often experience social, emotional health, and educational problems. As adults, many will struggle to find stable employment and are at increased risk of social dysfunction and mental health difficulties. Despite the serious implications of the condition for children and their families, LI is little known among the general community. LI is a varied disorder, with different children manifesting different profiles of associated difficulties. Not all children go on to have poor outcomes. For example, some may have behavioural difficulties whilst others do not. Determining what makes different children vulnerable is challenging. The project will make use of genetic-risk information and data from the first 2 years of child's life (such as number of books in the household, socioeconomic status etc.) to classify children into sub-groups, using a statistical method known as latent class analysis. This will allow the investigation of whether belonging to certain sub-groups affects outcomes in middle childhood. For example, it may be that the children with a high genetic risk and a favourable home environment have comparable outcomes to those children with low genetic risk and a favourable home environment. If this does prove to be the case, it would suggest that genetic risk can be mitigated by a favourable home environment. This would provide evidence to target resources towards the most vulnerable children to improve their quality of life.The project will also identify the pathways to poor outcomes in social adjustment, educational attainment and mental health functioning. For example, it may be that children with high genetic risk and a unfavourable home environment have behavioural difficulties and emotional problems in middle childhood. Pathway analyses afford the examination of multiple factors and different potential routes: how children may get from A to B. It also affords the evaluation of the strength of different pathways and the assessment of the extent to which outcomes in different areas of functioning derive from common or distinctive routes. Part of the strength of this proposal is the inclusion of a variety of factors: genetic, environmental, and psychological in the same model. The economic cost associated with language impairment has been estimated at 2.5% of gross national product. Evidence on the pathways to adverse outcomes will have wide ranging implications for public health measures and service provision. This type of project requires large numbers of participants. Approval has been granted to use the Avon Longitudinal Study of Parents and Children (ALSPAC). This is an existing, epidemiological database that has records for ~7,000 children so no new data collection is needed for the project.