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自闭症诊断年龄的城乡差异:多模型分析

Rural-Urban Differences in Age at Autism Diagnosis: A Multiple Model Analysis.

作者信息

Ghahari Nima, Yousefian Fatemeh, Behzadi Saeed, Jalilzadeh Amin

机构信息

Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.

Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

出版信息

Iran J Psychiatry. 2022 Jul;17(3):294-303. doi: 10.18502/ijps.v17i3.9729.

Abstract

Early recognition of autism is important, but diagnosis age varies among children. Recent studies have aimed to identify factors affecting age of diagnosis and several studies have attempted to explore geographic variation in age at diagnosis of autism. However, there is a lack of research examining geographic variations with multiple models to find whether geographic differences can be explained by risk factors such as socioeconomic status and differences in child characteristics. This study aimed to address this gap of knowledge by comparing age at diagnosis of autism between the group of people living in the center of the province and the group of people living in the rest of the province, considering potential medical and socioeconomic confounders. The study population consisted of 50 autistic children born in East Azerbaijan Province between 2004 and 2016. Initially, univariate testing by ANOVA was performed to identify family and individual factors contributing to differences in age at autism diagnosis. Following this, the association between living in the center of the province and age at diagnosis in univariate and multivariate analyses was examined. Results from the initial univariate analysis indicate a significant association between living in the center of province and early diagnosis. However, inclusion of possible confounders in multiple model illustrates that these geographical disparities in age at diagnosis can be explained by differences in socioeconomic and medical status. Although geographic variation in age at diagnosis of autism was observed, analyses show that differences in individual and family-level factors may contribute to geographic differences. In this study, most of the observed variation was accounted for by family-level factors rather than geographic policies. Findings prove that multiple strategies are required to identify targeted interventions and strategies.

摘要

早期识别自闭症很重要,但儿童的诊断年龄各不相同。最近的研究旨在确定影响诊断年龄的因素,一些研究试图探讨自闭症诊断年龄的地理差异。然而,缺乏使用多种模型来研究地理差异的研究,以确定地理差异是否可以由社会经济地位和儿童特征差异等风险因素来解释。本研究旨在通过比较该省中心地区居民组和该省其他地区居民组的自闭症诊断年龄,同时考虑潜在的医学和社会经济混杂因素,来填补这一知识空白。 研究人群包括2004年至2016年在东阿塞拜疆省出生的50名自闭症儿童。最初,通过方差分析进行单变量测试,以确定导致自闭症诊断年龄差异的家庭和个体因素。在此之后,在单变量和多变量分析中研究了居住在该省中心地区与诊断年龄之间的关联。 最初的单变量分析结果表明,居住在该省中心地区与早期诊断之间存在显著关联。然而,在多模型中纳入可能的混杂因素表明,这些诊断年龄的地理差异可以由社会经济和医学状况差异来解释。 虽然观察到自闭症诊断年龄存在地理差异,但分析表明,个体和家庭层面因素的差异可能导致地理差异。在本研究中,观察到的大多数差异是由家庭层面因素而非地理政策造成的。研究结果证明,需要多种策略来确定有针对性的干预措施和策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b6/9699809/8ab04635e55f/IJPS-17-294-g001.jpg

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