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      Risk factors for ASD : Risk Factors for Autism Spectrum Disorder in Shanghai, China: A Population-based Case-control Study

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          Abstract

          Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder that brings heavy burdens to families and the society. This case-control study explored risk factors for ASD based on 74,252 children aged 3-12 years who were recruited from general education kindergartens, primary schools, and special education schools in Shanghai, China. One hundred ninety-two children were identified with ASD according to the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition. Male sex, the presence of anoxia or asphyxia at birth, artificial feeding, adverse maternal psychological status, complications during pregnancy and higher paternal education were associated with ASD even after controlling for age, residential district, family history of mental disorders, parental personality, and amount of daily TV viewing.

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          Most cited references57

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          Diagnostic and Statistical Manual of Mental Disorders

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            Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016

            Problem/Condition Autism spectrum disorder (ASD). Period Covered 2016. Description of System The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Results For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (40% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively). Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months). Interpretation The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children. Public Health Action These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.
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              Autism spectrum disorder

              Autism spectrum disorder is a term used to describe a constellation of early-appearing social communication deficits and repetitive sensory–motor behaviours associated with a strong genetic component as well as other causes. The outlook for many individuals with autism spectrum disorder today is brighter than it was 50 years ago; more people with the condition are able to speak, read, and live in the community rather than in institutions, and some will be largely free from symptoms of the disorder by adulthood. Nevertheless, most individuals will not work full-time or live independently. Genetics and neuroscience have identified intriguing patterns of risk, but without much practical benefit yet. Considerable work is still needed to understand how and when behavioural and medical treatments can be effective, and for which children, including those with substantial comorbidities. It is also important to implement what we already know and develop services for adults with autism spectrum disorder. Clinicians can make a difference by providing timely and individualised help to families navigating referrals and access to community support systems, by providing accurate information despite often unfiltered media input, and by anticipating transitions such as family changes and school entry and leaving.
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                Author and article information

                Contributors
                Journal
                Journal of Autism and Developmental Disorders
                J Autism Dev Disord
                Springer Science and Business Media LLC
                0162-3257
                1573-3432
                August 2023
                May 20 2022
                August 2023
                : 53
                : 8
                : 2954-2963
                Article
                10.1007/s10803-022-05603-1
                35596026
                3b40604d-82e4-4023-9254-323c95f48d2c
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

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