Wall-Wieler Elizabeth, Roos Leslie L, Chateau Dan G, Rosella Laura C
Manitoba Centre for Health Policy, Department of Community Health Sciences, Faculty of Health Sciences, College of Medicine, University of Manitoba, 408-727 McDermot Avenue, Winnipeg, MB, R3E 3P5, Canada.
Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Can J Public Health. 2016 Jun 27;107(1):e16-e22. doi: 10.17269/cjph.107.5156.
A life course approach and linked Manitoba data from birth to age 18 were used to facilitate comparisons of two important outcomes: high school graduation and Attention-Deficit/Hyperactivity Disorder (ADHD). With a common set of variables, we sought to answer the following questions: Do the measures predicting high school graduation differ from those that predict ADHD? Which factors are most important? How well do the models fit each outcome?
Administrative data from the Population Health Research Data Repository at the Manitoba Centre for Health Policy were used to conduct one of the strongest observational designs: multilevel modelling of large population (n = 62,739) and sibling (n = 29,444) samples. Variables included are neighbourhood characteristics, measures of family stability, and mental and physical health conditions in childhood and adolescence.
The adverse childhood experiences important for each outcome differ. While family instability and economic adversity more strongly affect failing to graduate from high school, adverse health events in childhood and early adolescence have a greater effect on late adolescent ADHD. The variables included in the model provided excellent accuracy and discrimination.
These results offer insights on the role of several family and social variables and can serve as the basis for reliable, valid prediction tools that can identify high-risk individuals. Applying such a tool at the population level would provide insight into the future burden of these outcomes in an entire region or nation and further quantify the burden of risk in the population.
采用生命历程方法并利用曼尼托巴省从出生到18岁的关联数据,以促进对两个重要结果的比较:高中毕业和注意力缺陷多动障碍(ADHD)。通过一组共同的变量,我们试图回答以下问题:预测高中毕业的指标与预测ADHD的指标有何不同?哪些因素最为重要?模型对每个结果的拟合程度如何?
使用曼尼托巴省卫生政策中心人口健康研究数据存储库的行政数据进行最强有力的观察性设计之一:对大量人群(n = 62,739)和同胞(n = 29,444)样本进行多层次建模。纳入的变量包括邻里特征、家庭稳定性指标以及儿童期和青春期的心理和身体健康状况。
对每个结果重要的不良童年经历各不相同。虽然家庭不稳定和经济逆境对高中未毕业的影响更大,但儿童期和青春期早期的不良健康事件对青少年晚期的ADHD影响更大。模型中纳入的变量具有出色的准确性和区分能力。
这些结果提供了对若干家庭和社会变量作用的见解,并可作为可靠、有效的预测工具的基础,这些工具能够识别高危个体。在人群层面应用这样的工具将深入了解整个地区或国家这些结果未来的负担,并进一步量化人群中的风险负担。