Department of Health Care Organization and Policy, UAB School of Public Health, 1720 2nd Avenue S. RPHB 330, Birmingham, AL, 35294-0022, USA.
Department of Psychology, University of Alabama At Birmingham, 1720 2nd Avenue S. CH19 307U, Birmingham, AL, 35294-2041, USA.
Matern Child Health J. 2021 Jun;25(6):956-966. doi: 10.1007/s10995-020-03064-5. Epub 2021 Jan 4.
To propose a tailored social ecological model for Autism Spectrum Disorders and explore relationships between variables in a large nationally-representative dataset.
A tailored social-ecological model was developed and examined across variables in the 2016/2017 National Survey of Children's Health. A series of iterative multivariable logistic regressions were performed including individual, family, and community/neighborhood variables. A multivariable logistic regression using state-level fixed effects was performed to understand dynamics related to macro-level policies.
In the full model, gender, disability severity, certain types of insurance coverage and household income were significantly related to ASD diagnosis. Females had lower odds of a diagnosis compared to males (aOR: 0.27; CI:0.18-0.41). Children with at least one other moderate/severe disability had odds 7.61 higher (CI:5.36-10.82) of a diagnosis than children without moderate/severe disabilities. Children with public insurance only (aOR:1.66; CI:1.14-2.41) or both private and public insurance coverage (aOR: 2.62; CI:1.6-4.16) had higher odds of a diagnosis compared to children with private insurance only. For those who reported it was "somewhat" or "very often" hard to cover basics with their income, odds of a diagnosis were higher compared to those who reported it was "never" or "hardly ever" hard to cover basics (aOR: 1.676; CI:0.21-2.56).
Patterns of ASD diagnosis are related to individual and family characteristics. There is some evidence that a child's environment has some relationship to reported ASD diagnosis. Professionals should be aware of an individual's environmental factors or context when assessing for ASD.
提出一个定制的自闭症谱系障碍社会生态模型，并在一个大型全国代表性数据集中探索变量之间的关系。
在 2016/2017 年全国儿童健康调查中，开发并检验了一个定制的社会生态模型，其中包括个体、家庭和社区/邻里变量。进行了一系列迭代多变量逻辑回归，包括个体、家庭和社区/邻里变量。使用州级固定效应进行多变量逻辑回归，以了解与宏观政策相关的动态。
在全模型中，性别、残疾严重程度、某些类型的保险覆盖和家庭收入与 ASD 诊断显著相关。与男性相比，女性诊断的可能性较低（aOR：0.27；CI：0.18-0.41）。至少有一种其他中度/重度残疾的儿童比没有中度/重度残疾的儿童诊断的可能性高 7.61 倍（CI：5.36-10.82）。只有公共保险（aOR：1.66；CI：1.14-2.41）或同时拥有私人和公共保险（aOR：2.62；CI：1.6-4.16）的儿童比只有私人保险的儿童诊断的可能性更高。对于那些报告收入“有些”或“经常”难以支付基本费用的人，与那些报告“从不”或“几乎从不”难以支付基本费用的人相比，诊断的可能性更高（aOR：1.676；CI：0.21-2.56）。
ASD 诊断模式与个体和家庭特征有关。有一些证据表明，儿童的环境与报告的 ASD 诊断有一定的关系。专业人员在评估 ASD 时应注意个体的环境因素或背景。
