We recruited 15,417 participants aged 18 to 36 months in central China using a stratified, multi-stage random sampling method. For children with a positive result in Toddlers screening test, further diagnostic assessment of autism spectrum disorders (ASD) was performed using the childhood autism rating scale and the Diagnostic and Statistical Manual of Mental Disorders. ASD prevalence among these children was 0.58% in Hubei province. Multivariate-adjusted logistic regression models were then used to explore potential ASD risk factors. One parent aged 35 or older, preterm birth, and birth weight < 2.0 kg remained significantly associated with elevated ASD risk (P < 0.05). These findings indicated that management of adverse perinatal factors may prevent the occurrence of ASD.
Published in | Journal of Family Medicine and Health Care (Volume 5, Issue 4) |
DOI | 10.11648/j.jfmhc.20190504.15 |
Page(s) | 64-69 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2019. Published by Science Publishing Group |
Autism Spectrum Disorders, Prevalence, Risk Factors
[1] | Coo H, Ouellette-Kuntz H, Lloyd JE, Kasmara L, Holden JJ, et al. Trends in autism prevalence: diagnostic substitution revisited. J Autism Dev Disord. 2008; 38 (6): 1036-1046. |
[2] | Wingate M, Kirby RS, Pettygrove S, Cunniff C, Schulz E, et al. Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveill Summ. 2014; 63 (2): 1-21. |
[3] | Baird G, Simonoff E, Pickles A, Chandler S, Loucas T, et al. Prevalence of disorders of the autism spectrum in a population cohort of children in South Thames: the Special Needs and Autism Project (SNAP). Lancet. 2006; 368 (9531): 210-215. |
[4] | Mulvihill B, Wingate M, Kirby RS, Pettygrove S, Cunniff C, et al. Prevalence of Autism Spectrum Disorders - Autism and Developmental Disabilities Monitoring Network, United States, 2006. MMWR Surveill Summ. 2009; 58 (10): 1-20. |
[5] | Skonieczna-Zydecka K, Gorzkowska I, Pierzak-Sominka J, Adler G. The Prevalence of Autism Spectrum Disorders in West Pomeranian and Pomeranian Regions of Poland. J Appl Res Intellect Disabil. 2016; 30 (2): 283-289. |
[6] | Zachor D, Yang JW, Itzchak EB, Furniss F, Pegg E, et al. Cross-cultural differences in comorbid symptoms of children with autism spectrum disorders: an international examination between Israel, South Korea, the United Kingdom and the United States of America.. Dev Neurorehabil. 2011; 14 (4): 215-220. |
[7] | Dobson S, Upadhyaya S, McNeil J, Venkateswaran S, Gilderdale D. Developing an information pack for the Asian carers of people with autism spectrum disorders. Int J Lang Commun Disord. 2001; 36 Suppl: 216-221. |
[8] | Elsabbagh M, Divan G, Koh YJ, Kim YS, Kauchali S, et al. Global prevalence of autism and other pervasive developmental disorders. Autism Res. 2012; 5 (3): 160-179. |
[9] | Risi S, Lord C, Gotham K, Corsello C, Chrysler C, et al. Combining information from multiple sources in the diagnosis of autism spectrum disorders. J Am Acad Child Adolesc Psychiatry. 2006; 45 (9): 1094-1103. |
[10] | Larsson HJ, Eaton WW, Madsen KM, Vestergaard M, Olesen AV, et al. Risk factors for autism: perinatal factors, parental psychiatric history, and socioeconomic status. Am J Epidemiol. 2005; 161 (10): 916-925. |
[11] | Yassin W, Kojima M, Owada K, Kuwabara H, Gonoi W, et al. Paternal age contribution to brain white matter aberrations in autism spectrum disorder. Psychiatry Clin Neurosci. 2019; 73 (10): 649-659. |
[12] | Taylor LJ, Eapen V, Maybery MT, Midford S, Paynter J, et al. Diagnostic evaluation for autism spectrum disorder: a survey of health professionals in Australia. BMJ Open. 2016; 6 (9): e012517. |
[13] | Dai Q, Xu HQ. Analysis of Bibliometric Papers on the epidemiology of Children with Autism Spectrum Disorders in China form 2000-2016 years. Chinese Journal of Child Health Care.2017; (25): 271-274. |
[14] | Lyall K, Croen L, Daniels J, Fallin MD, Ladd-Acosta C, et al. The Changing Epidemiology of Autism Spectrum Disorders. Annu Rev Public Health. 2017; 38: 81-102. |
[15] | Mintz, ME. A parent-centered approach to autism diagnosis in early childhood. World J Pediatr. 2018; 14 (3): 212-214. |
[16] | Carter AS, Black DO, Tewani S, Connolly CE, Kadlec MB, et al. Sex differences in toddlers with autism spectrum disorders. J Autism Dev Disord. 2007; 37 (1): 86-97. |
[17] | Rai D, Lee BK, Dalman C, Golding J, Lewis G, et al. Parental depression, maternal antidepressant use during pregnancy, and risk of autism spectrum disorders: population based case-control study. BMJ. 2013; 346: f2059. |
[18] | Leblond CS, Nava C, Polge A, Gauthier J, Huguet G, et al. Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: a gradient of severity in cognitive impairments. PLoS Genet. 2014; 10 (9): e1004580. |
[19] | Gong X, Wang H. SHANK1 and autism spectrum disorders. Sci China Life Sci. 2015; 58 (10): 985-990. |
[20] | Sato D, Lionel AC, Leblond CS, Prasad A, Pinto D, et al. SHANK1 Deletions in Males with Autism Spectrum Disorder. Am J Hum Genet. 2012; 90 (5): 879-887. |
[21] | Chakrabarti S, Fombonne E. Pervasive developmental disorders in preschool children: confirmation of high prevalence. Am J Psychiatry. 2005; 162 (6): 1133-1141. |
[22] | Manzouri L, Yousefian S, Keshtkari A, Hashemi N. Advanced Parental Age and Risk of Positive Autism Spectrum Disorders Screening. Int J Prev Med. 2019; 10: 135. |
[23] | Shelton JF, Hertz-Picciotto I, Pessah IN. Tipping the balance of autism risk: potential mechanisms linking pesticides and autism. Environ Health Perspect. 2012; 120 (7): 944-951. |
[24] | Tran PL, Lehti V, Lampi KM, Helenius H, Suominen A, et al., Smoking during pregnancy and risk of autism spectrum disorder in a Finnish National Birth Cohort. Paediatr Perinat Epidemiol. 2013; 27 (3): 266-274. |
[25] | Smith SE, Li J, Garbett K, Mirnics K, Patterson PH. Maternal immune activation alters fetal brain development through interleukin-6. J Neurosci. 2007; 27 (40): 10695-10702. |
[26] | Pinto D, Delaby E, Merico D, Barbosa M, Merikangas A, et al. Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders. Am J Hum Genet. 2014; 94 (5): 677-694. |
[27] | Diehl JJ, Schmitt LM, Villano M, Crowell CR. The clinical use of robots for individuals with Autism Spectrum Disorders: A critical review. Res Autism Spectr Disord. 2012; 6 (1): 249-262. |
[28] | Padilla N, Eklöf E, Mårtensson GE, Bölte S, Lagercrantz H, et al. Poor Brain Growth in Extremely Preterm Neonates Long Before the Onset of Autism Spectrum Disorder Symptoms. Cereb Cortex. 2017; 27 (2): 1245-1252. |
APA Style
Qiong Dai, Xuejun Kong, Yiqing Song, Aiqin Zhou, Xuan Zhang, et al. (2019). Prevalence and Risk Factors of Autism Spectrum Disorders in Children Aged 18-36 Months in Hubei Province, China. Journal of Family Medicine and Health Care, 5(4), 64-69. https://doi.org/10.11648/j.jfmhc.20190504.15
ACS Style
Qiong Dai; Xuejun Kong; Yiqing Song; Aiqin Zhou; Xuan Zhang, et al. Prevalence and Risk Factors of Autism Spectrum Disorders in Children Aged 18-36 Months in Hubei Province, China. J. Fam. Med. Health Care 2019, 5(4), 64-69. doi: 10.11648/j.jfmhc.20190504.15
AMA Style
Qiong Dai, Xuejun Kong, Yiqing Song, Aiqin Zhou, Xuan Zhang, et al. Prevalence and Risk Factors of Autism Spectrum Disorders in Children Aged 18-36 Months in Hubei Province, China. J Fam Med Health Care. 2019;5(4):64-69. doi: 10.11648/j.jfmhc.20190504.15
@article{10.11648/j.jfmhc.20190504.15, author = {Qiong Dai and Xuejun Kong and Yiqing Song and Aiqin Zhou and Xuan Zhang and Ping Zhang and Minghui Li and Xinglian Liu and Jun Wang and Haiqing Xu}, title = {Prevalence and Risk Factors of Autism Spectrum Disorders in Children Aged 18-36 Months in Hubei Province, China}, journal = {Journal of Family Medicine and Health Care}, volume = {5}, number = {4}, pages = {64-69}, doi = {10.11648/j.jfmhc.20190504.15}, url = {https://doi.org/10.11648/j.jfmhc.20190504.15}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jfmhc.20190504.15}, abstract = {We recruited 15,417 participants aged 18 to 36 months in central China using a stratified, multi-stage random sampling method. For children with a positive result in Toddlers screening test, further diagnostic assessment of autism spectrum disorders (ASD) was performed using the childhood autism rating scale and the Diagnostic and Statistical Manual of Mental Disorders. ASD prevalence among these children was 0.58% in Hubei province. Multivariate-adjusted logistic regression models were then used to explore potential ASD risk factors. One parent aged 35 or older, preterm birth, and birth weight P < 0.05). These findings indicated that management of adverse perinatal factors may prevent the occurrence of ASD.}, year = {2019} }
TY - JOUR T1 - Prevalence and Risk Factors of Autism Spectrum Disorders in Children Aged 18-36 Months in Hubei Province, China AU - Qiong Dai AU - Xuejun Kong AU - Yiqing Song AU - Aiqin Zhou AU - Xuan Zhang AU - Ping Zhang AU - Minghui Li AU - Xinglian Liu AU - Jun Wang AU - Haiqing Xu Y1 - 2019/12/06 PY - 2019 N1 - https://doi.org/10.11648/j.jfmhc.20190504.15 DO - 10.11648/j.jfmhc.20190504.15 T2 - Journal of Family Medicine and Health Care JF - Journal of Family Medicine and Health Care JO - Journal of Family Medicine and Health Care SP - 64 EP - 69 PB - Science Publishing Group SN - 2469-8342 UR - https://doi.org/10.11648/j.jfmhc.20190504.15 AB - We recruited 15,417 participants aged 18 to 36 months in central China using a stratified, multi-stage random sampling method. For children with a positive result in Toddlers screening test, further diagnostic assessment of autism spectrum disorders (ASD) was performed using the childhood autism rating scale and the Diagnostic and Statistical Manual of Mental Disorders. ASD prevalence among these children was 0.58% in Hubei province. Multivariate-adjusted logistic regression models were then used to explore potential ASD risk factors. One parent aged 35 or older, preterm birth, and birth weight P < 0.05). These findings indicated that management of adverse perinatal factors may prevent the occurrence of ASD. VL - 5 IS - 4 ER -