Incidence of autism in high risk neonatal follow up
===================================================

* Hussein S. Mohammed
* Saeed H. Wahass
* Adel A. Mahmoud

## Abstract

**Objective:** To detect autism spectrum disorder (ASD) cases within the High Risk Neonatal Follow up Program (HRNFP), as an indicator of the prevalence of ASD and associated risk factors in the Kingdom of Saudi Arabia (KSA).

**Methods:** We conducted this retrospective medical chart review in a tertiary care hospital in Riyadh, KSA. All patients admitted to the HRNFP were seen at 3 years corrected age between January 2012 and December 2013. Patients diagnosed with ASD from the HRNFP were referred to the King Fahad Medical City (KFMC) Autism Program for further assessment. The following potential risk factors for ASD were documented: low birth weight, gestational age less than 33 weeks, and male gender.

**Results:** In 2012, 59 patients were evaluated in the HRNFP. Three cases were diagnosed with ASD, with an ASD incidence rate of 5.1% (95% confidence interval [CI] calculated by adjusted Wald method: 1.2-14.5%). In 2013, 48 patients were evaluated and 2 cases were diagnosed with ASD, with an ASD incidence rate of 4.2% (95% CI: 0.4%-14.8%). The total ASD incidence rate during the 2-year study period was 4.7% (95% CI: 1.7%-10.8%). Factors associated with a higher likelihood of ASD were: male gender, low birth weight, and gestational age less than 33 weeks.

**Conclusion:** Compared with the community, the prevalence of ASD was higher in the HRNFP. Further investigation is required to evaluate risk factors.

The main characteristics of autism spectrum disorder (ASD) are persistent deficits in social interaction and social communication in multiple contexts, including nonverbal communicative behaviors and deficits in social reciprocity used for social interaction, and skills in developing, maintaining, and understanding relationships. The diagnosis of ASD, in addition to social communication deficits, requires the presence of restricted, repetitive, patterns of behavior and interests or activities.1 The High Risk Neonatal Follow up Program (HRNFP) is a program at King Fahad Medical City (KFMC), Riyadh, Kingdom of Saudi Arabia (KSA) involving a multi-disciplinary team of professionals who care for children with many risk factors for diseases and disabilities, such as low birth weight of 1250 grams or less, gestational age of 29 weeks or less, and grade III or IV intra ventricular hemorrhage. Autism spectrum disorder is increasingly being recognized as a public health problem of major importance.2 It is one of the leading disorders causing disabilities in the neonatal population.3 With current genetic testing, it is estimated that an etiology is identified in 15-20% of individuals with ASD; in others, the cause remains unknown.4 Advances in neonatal intensive care have dramatically increased survival in preterm infants, most strikingly among the sickest and most preterm.5 The contribution from the increasing number of survivors of extreme prematurity to this growing population of children with ASD has not been adequately evaluated.6 Prevalence studies for any disorder provide crucial information that may allow an estimation of the magnitude of the problem among the specified population; this in turn may assist policy makers in planning and decision making, as well as risk factor identification.7 Information on the prevalence of ASD in KSA is scarce and limited to small studies.8,9 In one study, it was found that the overall prevalence of autism in the primary school of Taif district whose age ranged from 7 to 12 years was 0.035%.8 According to a recent report from the Centers for Disease Control and Prevention (CDC),7 the rate of diagnosis has increased substantially, with one in 68 children identified with ASD; boys were almost 5 times more likely to be identified with ASD than girls. The average prevalence also varied by race and ethnicity.7 However, it is unclear whether this higher prevalence represents a true increase in disease burden or it could be attributed to changes in diagnostic practices and complex issues relating to service provision.7,13,14 The purpose of the present retrospective study was to estimate the incidence of ASD in the HRNFP at KFMC. We also sought to investigate the potential association of very low birth weight (VLBW) with ASD.

## Methods

We conducted this retrospective medical chart review in a tertiary care hospital in Riyadh, KSA. The Institutional Review Board (IRB) at KFMC approved the study. All patients in the HRNFP were screened for developmental disorders at the corrected age of 18 and 36 months. Evaluation was performed qualitatively and quantitatively. Patients who were diagnosed with ASD in the HRNFP were referred to the Comprehensive Autism Program (CAP), for further assessment and recommendation. The diagnosis of ASDs was based on DSM IV criteria.15

Using PubMed and Google, we carried out a manual search for previously published researchs. The results were documented and compared to our local results. Babies were evaluated and diagnosed with ASD in the CAP, which includes a multi-disciplinary team of psychologists, behavior specialized pediatricians, and speech therapists.

### Statistical analyses

Continuous variables are presented as mean±SD (normal distribution) and as median with interquartile range (skewed distribution). Categorical variables are presented as percentages with corresponding 95% confidence intervals (95% CI). The adjusted Wald method, which provides the best coverage for binomial CI when samples are less than 150,16 was used for computation of the 95% CI of reported prevalences. Pearson’s Chi-Square test was used to detect univariate associations between VLBW and ASD. The IBM SPSS Statistics for Windows (Version 22.0, IBM Corp., Armonk, NY, USA) was used for statistical analyses.17

## Results

A total of 5 patients were diagnosed with ASD during the study period. All the diagnosed patients had VLBW (100%). The gestational age was less or equal to 29 weeks in 80% (n=4) of ASD patients (**Table 1**). In 2012, 59 patients were evaluated by the HRNFP, and 3 cases were diagnosed with ASD (**Table 2**) giving an ASD incidence rate of 5.1% (95% CI calculated by the adjusted Wald method: 1.2-14.5%). In year 2013, 48 patients were evaluated by the HRNFP and 2 cases were diagnosed with ASD (**Table 2**), giving an ASD incidence rate of 4.2% (95% CI: 0.4-14.8%). The total rate of ASD during the 2-year study period was 4.7% (95% CI: 1.7-10.8%).

View this table:
[Table 1](http://nsj.org.sa/content/21/1/43/T1)

Table 1 
Birth weight and gestational period for diagnosed autism spectrum disorder patients.

View this table:
[Table 2](http://nsj.org.sa/content/21/1/43/T2)

Table 2 
Rate of ASD in HRNFP patients in 2012 and 2013 and total rate.

## Discussion

Low birth weight and gestational age have been identified in several studies as important perinatal risk factors for disturbances in social interaction, communication, and behavior,18,19 as well as later psycho affective disorders in adulthood.20,21 In a recent study,22,23 it was shown that preterm birth increased ASD risk.

There is a lack of published studies describing the prevalence of autism in high risk children in KSA. The current study documented a substantial prevalence rate of ASD among HRFP patients (1 in 21), which is higher in comparison with the prevalence of ASD in the general population that ranges from 1 in 88 to 1 in 150 births.24

Higher autism spectrum traits were associated with very low birth weight adults as compared to term-born controls.25 Low birth weight and preterm birth place these infants at higher risk for disturbances in social interaction, communication, and other psycho affective disorders in adulthood.26 An Indian study27 evaluating perinatal and neonatal risk factors showed labor complications, preterm birth, neonatal jaundice, delayed birth cry and birth asphyxia to be associated with ASD with an odds ratio greater than 1.5.

Certain limitations of the present study need to be acknowledged. First, our limited sample size does not allow us to accurately estimate ASD prevalence with a narrow 95% CI. Second, the retrospective nature of our study does not provide definitive evidence regarding the potential causality of VLBW and early gestational age with ASD. Third, selection bias cannot be excluded given that the chart review was conducted in a tertiary care center. Consequently, the actual prevalence in the general population may be substantially lower. Fourth, other potential risk factors that might have been associated with a higher ASD prevalence were not collected including: maternal age, family history of ASD and number of prior spontaneous abortions, abnormal presentation, umbilical-cord complications, fetal distress, birth injury, or trauma, multiple birth, maternal hemorrhage, summer birth, low birth weight, small for gestational age, congenital malformation, low 5-minute Apgar score, feeding difficulties, meconium aspiration, neonatal anemia, ABO, or Rh incompatibility, and hyperbilirubinemia. Finally, the limited sample of ASD cases (n=5) prevents the investigation of the potential relationships between specific HRNFP diagnoses with ASD.

In conclusion, our findings indicate that the prevalence of ASDs was high in HRNFP patients at KFMC. Further investigations are required to evaluate which potential risk factors may be associated with the higher ASD incidence documented in this specific population.

## Acknowledgment

*We acknowledge the contribution of Abeer Sobuh, Staff Nurse of the High Risk Program, KFMC. We also acknowledge the Secretarial support provided by Levina Tiongco, Pediatric Neurology Department, NNI, KFMC*.

## Footnotes

*   Disclosure
    
    Authors disclose no affiliation or financial involvement with organizations or entities with a direct financial interest in the subject matter or materials discussed in the manuscript. No funding was received for this work from any organization.

*   Received July 20, 2015.
*   Accepted December 2, 2015.


*   Copyright: © Neurosciences

Neurosciences is an Open Access journal and articles published are distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC). Readers may copy, distribute, and display the work for non-commercial purposes with the proper citation of the original work.

## References

1.  American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, Washington (DC)), 5th ed.
    
    

2.  Raz R, Roberts AL, Lyall K, Hart JE, Just AC, Laden F, et al. (2015) Autism spectrum disorder and particulate matter air pollution before, during, and after pregnancy:a nested case-control analysis within the Nurses’ Health Study II Cohort. Environ Health Perspect 123, 264–270.
    
    

3.  Dickerson AS, Rahbar MH, Han I, Bakian AV, Bilder DA, Harrington RA, et al. (2015) Autism spectrum disorder prevalence and proximity to industrial facilities releasing arsenic, lead or mercury. Sci Total Environ 536, 245–251.
    
    

4.  1.  Pagon RA, 
    2.  Bird TC, 
    3.  Dolan CR, 
    4.  Stephens K
    
    Miles JH, Mc Cathren RB, Stichter J, Shinawi M (1993-2003) Autism Spectrum Disorders. in Gene Reviews [Internet], eds Pagon RA, Bird TC, Dolan CR, Stephens K (University of Washington, Seattle, Seattle (WA)), updated 2010 Apr 13.
    
    

5.  Saugstad OD (2010) [Better prognosis for the extremely premature infants]. Tidsskr Nor Laegeforen 130, 52–54, Norwegian.
    
    

6.  Raina SK, Kashyap V, Bhardwaj AK, Kumar D, Chander V (2015) Prevalence of autism spectrum disorders among children (1-10 years of age) - Findings of a mid-term report from Northwest India. J Postgrad Med 61, 243–246.
    
    

7.  Centers for Disease Control and Prevention (2014) Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years —Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2010. MMWR Morb Mortal Wkly Rep 63, 1–21.
    
    

8.  Al Zahrani AH (2013) Prevalence and clinical characteristics of autism spectrum disorders in school-age children in Taif- KSA. Int J Med Sci Public Health 2, 578–582.
    
    

9.  Al-Salehi SM, Al-Hifthy EH, Ghaziuddin M (2009) Autism in Saudi Arabia:presentation, clinical correlates and comorbidity. Transcult Psychiatry 46, 340–347.
    
    

10. Raz R, Weisskopf MG, Davidovitch M, Pinto O, Levine H (2015) Differences in autism spectrum disorders incidence by sub-populations in Israel 1992-2009: a total population study. J Autism Dev Disord 45, 1062–1069.
    
    

11. Lenoir P, Bodier C, Desombre H, Malvy J, Abert B, Ould Taleb M, et al. (2009) [Prevalence of pervasive developmental disorders. A review]. Encephale 35, 36–42, French.
    
    

12. Lian WB, Ho SK (2012) Profile of children diagnosed with autistic spectrum disorder managed at a tertiary child development unit. Singapore Med J 53, 794–800.
    
    

13. Aarnoudse-Moens CS, Weisglas-Kuperus N, van Goudoever JB, Oosterlaan J (2009) Meta-analysis of neurobehavioral outcomes in very preterm and/or very low birth weight children. Pediatrics 124, 717–728.
    
    

14. Limperopoulos C, Bassan H, Sullivan NR, Soul JS, Robertson RL Jr., Moore M, et al. (2008) Positive screening for autism in ex-preterm infants:prevalence and risk factors. Pediatrics 121, 758–765.
    
    

15. American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders: DSM-IV [Internet] (American Psychiatric Association, Washington (DC)), 4th ed, cited 2010 Mar 8, Available from: [http://www.psychiatryonline.com/DSMPDF/dsm-iv.pdf](http://www.psychiatryonline.com/DSMPDF/dsm-iv.pdf).
    
    

16. Lewis JR, Saur J (2006) When 100% really isn’t 100%:improving the accuracy of small-sample estimates of completion rates. Journal of Usability Studies 1, 136–150.
    
    

17. IBM SPSS Statistics For Windows. Version 22 (2013) (IBM Corp, Armonk (NY)).
    
    

18. Sigurdsson E, Van Os J, Fombonne E (2002) Are impaired childhood motor skills a risk factor for adolescent anxiety? Results from the 1958 U.K. birth cohort and the National Child Development Study. Am J Psychiatry 159, 1044–1046.
    
    

19. Pine D, Shaffer D, Schonfeld IS (1993) Persistent emotional disorder in children with neurological soft signs. J Am Acad Child Adolesc Psychiatry 32, 1229–1236.
    
    

20. Buka SL, Fan AP (1999) Association of prenatal and perinatal complications with subsequent bipolar disorder and schizophrenia. Schizophr Res 39, 113–119, discussion 160-1.
    
    

21. Wahlbeck K, Osmond C, Forsén T, Barker DJ, Eriksson JG (2001) Associations between childhood living circumstances and schizophrenia:a population-based cohort study. Acta Psychiatr Scand 104, 356–360.
    
    

22. Jones PB, Rantakallio P, Hartikainen AL, Isohanni M, Sipila P (1998) Schizophrenia as a long-term outcome of pregnancy, delivery, and perinatal complications:a 28-year follow-up of the 1966 north Finland general population birth cohort. Am J Psychiatry 155, 355–364.
    
    

23. Abel KM, Dalman C, Svensson AC, Susser E, Dal H, Idring S, et al. (2013) Deviance in fetal growth and risk of autism spectrum disorder. Am J Psychiatry 170, 391–398.
    
    

24. Kuehn BM (2007) CDC: autism spectrum disorders common. JAMA 297, 940.
    
    

25. Pyhälä R, Hovi P, Lahti M, Sammallahti S, Lahti J, Heinonen K, et al. (2014) Very low birth weight, infant growth, and autism-spectrum traits in adulthood. Pediatrics 134, 1075–1083.
    
    

26. Mahoney AD, Minter B, Burch K, Stapel-Wax J (2013) Autism spectrum disorders and prematurity:a review across gestational age subgroups. Adv Neonatal Care 13, 247–251.
    
    

27. Mamidala MP, Polinedi A, P T V PK, Rajesh N, Vallamkonda OR, Udani V, et al. (2013) Prenatal, perinatal and neonatal risk factors of Autism Spectrum Disorder:a comprehensive epidemiological assessment from India. Res Dev Disabil 34, 3004–1303.