This study assessed the reciprocal predictive relation between multiple domains of health and academic performance (AP) in elementary schoolchildren through autoregressive models. A school-based longitudinal observational study was carried out, with a baseline measurement in 2014 and a follow-up at 12 and 24 months, in an Argentine sample of 533 children aged 9-13 years. Health was measured by self-administration of the KIDSCREEN-52 child version in the classroom, which evaluates 10 dimensions of health. AP was established with the final grades in language and mathematics obtained from the school records. Other variables collected were sex, mother's educational level, socioeconomic status, and intellectual capability. To examine the interdependencies between different health domains and AP, autoregressive and cross-lag coefficients between adjacent time points were calculated with structural equation modeling. A substantial portion of AP individual differences was explained by AP in the previous wave (β above .790). Conversely, health measures were not as stable between different waves (β around .400). Cross-lag path coefficients showed a significant dependence on health of previous-year AP, as can be seen in the physical well-being, psychological well-being, school environment, and social acceptance dimensions of health. AP also was influenced by previous-year health, as occurs with the self-perception, mood and emotions, and school environment health dimensions that significantly predict the next AP. These results are consistent with a positive two-way association between health and AP in childhood. This analysis is important to identify priority areas of intervention that could to improve both children's AP and well-being. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译：

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通过自回归模型，儿童健康与学业表现之间的相互关系。

这项研究通过自回归模型评估了小学生健康状况和学业成绩（AP）的多个领域之间的相互预测关系。进行了一项基于学校的纵向观察性研究，该研究于2014年进行了基线测量，并在12个月和24个月时对533名9-13岁的阿根廷儿童进行了随访。健康状况是通过在教室自行管理KIDSCREEN-52儿童版本来衡量的，该版本评估了10个方面的健康状况。AP的建立是根据学校记录获得的语言和数学的最终成绩。收集的其他变量包括性别，母亲的教育程度，社会经济地位和智力水平。要检查不同健康域和AP之间的相互依赖性，利用结构方程模型计算了相邻时间点之间的自回归系数和交叉滞后系数。AP个体差异的很大一部分由上一波的AP解释（β大于.790）。相反，不同波浪之间的健康指标不稳定（β约为0.400）。跨时滞路径系数显示出对上一年AP的健康的显着依赖性，可以从身体健康，心理健康，学校环境和健康的社会接受维度中看出。AP也受到前一年健康状况的影响，自我感知，情绪和情感以及学校环境健康维度也可以显着预测下一次AP。这些结果与儿童期健康与AP之间的正向双向关联一致。这项分析对于确定可以改善儿童的AP和幸福感的优先干预领域很重要。（PsycInfo数据库记录（c）2020 APA，保留所有权利）。