Author Affiliations: Department of Research on Children with Special Needs, National Research Centre (NRC), Cairo, Egypt (Meguid NA); Department of Biological Anthropology, NRC, Cairo, Egypt (Kandeel WA, Wakeel KE, El-Nofely AA)

 

Corresponding Author:Nagwa A Meguid, MD, Human Genetics, Research on Children with Special Needs Department, National Research Centre, Tahrir street, Cairo, Egypt (Tel: 0201223316372; Fax: 202 37601877; Email: meguidna@yahoo.com)

 

doi: 10.1007/s12519-014-0510-0

 

 

 

 

 

 

 

 

Autism is the fastest rising developmental disorder in the world today. The centers for disease control released that the incidence of autism is rising at about 12% each year.^[1] The lack of successful therapy, etiological heterogeneity, and the increasing incidence make autism one of the most challenging neuro-developmental disorders. It presents a burden upon both the family and the society as a whole. The rising rates of autism and the fact that the concordance of identical twins can not completely support the theory that autism results from a combination of genetic and environmental factors.^[2]

Research into this disorder is increasingly focused on both genetic causes and neuroanatomical bases for the heterogeneous behavioral and clinical phenotypes.^[3] Thus attempts to discover major autism susceptibility genes have been largely unsuccessful, with only 15% to 20% of cases of autism link to specific genes.^[4] Gene expression pattern differs geographically between populations and within population and indicates regional specificity in gene/environment interactions.^[5] There is increasing evidence that it is a highly diverse disease affecting multiple systems of the body.^[6]

A primary reason for the lack of progress in understanding the etiology and genetic underpinnings of autism spectrum disorder (ASD) is undoubtedly the significant heterogeneity within both behavioral and clinical phenotypes. Anthropometric measurements, as basic physical growth criteria, are valuable tools for assessment of the clinical phenotype and reflect the impact of the genetic background as well as environmental setup, particularly nutritional and health factors. In the last decades, one could observe increasing interest in monitoring the physical growth parameters in patients with psychiatric disorders in general and autism in particular.^[7-12] The study of head circumference and other anthropometric variables, and morphological characteristics has begun to merge into autism research. To stratify ASDs into more homogenous subgroups, recent studies^[10,13,14] have found an unexpectedly large proportion of autistic children with large heads, and reported that macrocephaly is a consistent and replicated biological finding in autism. However, some scholars^[15] reported no macrocephaly in their autistic children. Even, microcephaly was reported in autistic children with a rate varying from 2.2% to 15%.^[16]

Similar differences could be seen in reports on the general body growth in weight and height of children with autism.^[17-19] Therefore, the present study aims to explore any differences in some important anthropometric measurements between a group of Egyptian children with autism and the pertinent healthy normal population.

 

 

One hundred children with autism who have received care at the Outpatient Clinic for "Autistic Children" at the Medical Research Center of Excellence of the National Research Centre in Cairo, Egypt, were recruited. They were from different socioeconomic strata and their age ranged from 3 to 10 years. The sex and age of these children are shown in Table 1.

 

Diagnosis

All patients met the following conditions: 1) Detailed case history, including three generation pedigree analysis, pregnancy history, peri-natal history, developmental history, similarly affected family members, and age of presenting manifestations; 2) Application of the criteria for autism defined in the DSM-IV-TR;^[20] 3) Autism Diagnostic Interview Revised;^[21] 4) Diagnostic interviews using Childhood Autism Rating Scale.^[22]

 

Exclusion criteria

Exclusion criteria for participation in the study included: severe sensory problems (e.g., visual impairment or hearing loss), significant motor impairments (e.g., failure to sit by 12 months, or walk by 24 months), or identified metabolic, genetic, or progressive neurological disorders, based on screening by clinical staff.

Written informed consent from the parent or caregiver was obtained for all participants. The study was approved by the Ethics Review Committee of the National Research Centre.

Anthropometric measurements

According to the recommendations of the International Biological Program,^[23] some anthropometric measurements were made. Bilateral measures were taken on the left side of the body. The following measures were attempted by well trained anthropologists: 1) The body height (HT) was measured to the nearest 0.1 cm by a Holtain portable anthropometer; 2) The body weight (WT) was determined to the nearest 0.01 kg on a Seca scale balance with the subject wearing minimal clothing and no shoes; 3) Circumferences were obtained with a flexible non-stretchable measuring tape: Head circumference (HC) was measured (cm) around the child's head. It is the maximum circumference passing around the glabella and occiput; mid upper arm circumference (MUAC, cm) was measured at a point mid-way between the tip of the shoulder and the tip of the elbow; 4) The skin fold thickness (SF) approximated to the nearest 0.1 mm was determined using a Harpenden skin fold caliper over triceps muscle parallel to the long axis of the arm, oblique at subscapular regions, and transverse at supra-iliac regions; 5) Body mass index (BMI) was calculated as body weight (in kilograms) divided by body height (in meters) squared.

 

Statistical analysis

As there is age and sex variation among the sample members, and we need to compare the growth of the study sample as a whole with normal population, we calculated Z scores for the different anthropometrical measurements for each patient. The standard tables of "Anthropometry of Egyptians from Birth till Senility" (which fairly represent Egyptian children from the Big Cairo area and of different socio-economic strata) published by the National Research Centre, Egypt^[24] were used as the most precise and suitable reference data for the normal Egyptian population. The data of the normal population were recorded yearly and tabulated as age categories (e.g. the 5-year group include subjects of 4.50-5.49 years old). The interpolation technique was used to calculate the most suitable reference value.^[25] For example, if a patient was 5 years and 3 months old, and we have normal tabulated values for age 5 and 6 years. Hence, the following formula was used to calculate the interpolated reference value. P=P₁+ΔP/ΔAge(Age–Age₁), where P is the estimated parameter (mean, or standard deviation); P₁, P₂ are parameters at Age₁, and Age₂; ΔP=P₂–P₁; ΔAge=Age₂–Age₁; Age is the patient age. To implement the interpolation technique we have developed a software using Visual Studio. Net running under the Windows operating system. Then the Z score is calculated as follows: Z=X-Mean/SD, where X represents the anthropometric measure; Mean is the estimated reference mean for age and sex; SD is the estimated standard deviation for age and sex. To assess whether the anthropometric sample means is different from normal, we used the mean Z of the sample as a sample statistic. One sample t test (t=X– -μ / SD √–n) is used assuming population mean (µ) that is equal to 0, and sample standard deviation (SD) as an estimator for population variance, and  X–   is the sample mean.

 

 

The mean Z score analyses of the 8 parameters and their standard deviations are statistically significant with the exception of mid upper arm circumference (Table 2). Table 3 demonstrates the mean Z scores which were distributed by gender and arranged in three groups of relevant characteristics. The first group included weight, body mass index, and mid upper arm circumference which reflects body mass. The second group represented skeletal and neural growth, whereas the third group of measurements represented the distribution of skin fold sickness. Table 4 shows the distribution of the mean Z scores, standard deviation, and range of the measurements according to age, i.e. a younger group aged up to 50 months, and an older group aged more than 50 months. We calculated the inter-correlations between the 8 parameters. Positive correlation was significant between all variables except ZHT, ZBMI; ZHT, ZTSF; and ZHC, Z Suprailiac SF (ZSISF) (Table 5).

In addition, ZHC was regressed on ZHT and the results were: ZHC=0.378 (ZHT)+0.298.

Both of the slop and intercept were significant (P=0.001 for the slop and P=0.04 for the intercept). This shows that children with autistic manifestations have a larger head of nearly 0.3 than normal children.

On the other hand, the regression of ZHT on ZHC is shown in the equation: ZHT=0.308 (ZHC)+0.082. Here the slop is the only significant parameter (P=0.001).

A software module was developed to generate the data for the normal distribution based on the mean and standard deviation. The module was developed using Visual Studio 2008 (Visual Basic) running on the Windows 8 operating system.

Fig. 1 demonstrates the distribution of the measurements representing body mass, i.e. body weight and BMI, with a significant shift to the right (the more shift the more increased value), but mid upper arm circumference almost similar to the normal. In Fig. 2, the distribution of body height and head circumference is significantly shifted to the right but more evidently for HC. It is realized that the distribution of skin fold thicknesses is normally skewed to the right; however Fig. 3 demonstrates quite evidently the higher values for the three folds in the autistic patients with a wide range for the supra iliac (or abdominal) fold. Fig. 4 shows the sex difference in the distribution of HC, which is significantly higher in males, whereas the curve in females almost coincides with the normal distribution.

 

 

The need is obvious for early clinical signs specific to autism. Anthropometric assessment might be an additional research helpful to early diagnosis. Autism as a complex developmental neuropsychiatric disorder characterized by impairment of social and communicational interactions seems to affect the life style mobility and feeding behavior as well. Studies^[17,26,27] have focused on aberrations in conduct during meals, selectivity of food as well as problems in timing of meals.

Our results show a tendency towards the increase of Z body weight and Z body mass index, indicating an increase in total body mass as well as weight per height. Searching for the body components that share in this tendency, one could observe that the Z upper mid arm circumference is almost similar to the reference norm. Likely this means that taking the circumference of bone, muscle and subcutaneous fat layer together, it is similar in autistic children to normal healthy children.

However, the skin-fold thicknesses on the triceps as well as the sub-scapular and supra-iliac skin-folds are significantly thicker in autistic children than in normal children. This agrees with the statement of Berry et al^[26] that typically children with autism spectrum disorders have strong preference for carbohydrates and rejection to fruits, vegetables, and diary products. Probably, our findings indicate that the increase of fat component is the factor responsible for the increase of body mass index in the sample, due to increased carbohydrate and fat intake as well as sedentary life style. Comparing males with females (regardless of the difference in numbers) shows that the same tendency is repeated in both genders though it is more evident in males. Comparing the Z scores of measurements in the younger group to those in the older group shows a similar tendency though it is more evident in the older group, particularly the Z scores for upper mid-arm circumference, body mass index, and triceps skin-fold thickness.

These findings have immediate and important implications for raising autistic children and suggesting a feeding program to control the relevant physical consequences of the disease. Meanwhile, scholars^[28] assume some type of deviant overgrowth in the cerebral, cerebellum and limbic structures that underlie AS disorder and predispose to language dysfunction among others. This overgrowth results in increased brain size which could be measured directly by MRI in postmortem studies or indirectly by head circumference. Generally, head circumference correlates perfectly with brain size till the age of 12 years with a coefficient of correlation that is equal to 0.88.^[10] Later, the coefficient of correlation decreases due to continuation of cranial growth, thickening of bone, and increased size of air sinuses, whereas the neural pattern of growth practically stops at that age.

However, macrocephaly may not be specific to autism, and in the present it may index the presence of additional symptoms^[29] or superimposition of other pathologies, or constitute a distinct subgroups of the spectrum.^[30] Normal or small head circumference was also observed in children with autism.^[15] Miles et al^[16] reported microcephaly in autistic children with a rate varying from 2.2% to 15%. In our study, 14% of the patients were macrocephalic with a Z score >1.96, 2% microcephalic, and 84% normocephalic. Our study showed an increased Z score of head circumference, also with a wide range of distribution (between 7 to 3.36 SDs of the normal healthy children).

In contrast to normal female children, ZHC score increased in males. This finding agrees with those reported elsewhere.^[10,31] Besides, the ZHC score also increased in the older group than in the younger group. As a matter of fact, the proper assessment of increased head circumference in autistic children necessitates a study of head circumference in the family^[12] and at birth^[32] and exclusion of superimposed pathology.^[14]

It is worthy to mention that the absolute brain size in general is significantly larger in males than in females, but not equal in all parts.^[33] It may be part of excessive body growth. If ZHC score in autistic patients is high but equal to the Z score of body height, this excludes overgrowth of the brain alone. In our patients, ZHC was higher than height Z score although both tended to be higher than in normal children. This tendency is underscored in males. But in our female patients, height Z score is insignificantly negative and ZHC is almost nil, indicating no differences from normal children.

In our younger group, height Z score was higher than ZHC score, but there were no differences in height in the older group except for increased head circumference, indicating that the relative overgrowth of head circumference is evidenced by age.

Moreover, head circumference is correlated with discrepancies between verbal and nonverbal IQ scores independent of the absolute level of verbal ability.^[34,35] In autistic children with higher head circumference, there are higher nonverbal abilities but problems in verbal abilities and differences in neuro-cognitive profile.^[30] This implies that overgrowth in the brain areas responsible for language generation in autistic children is associated with the decrease of verbal abilities and increase of head size.^[36] The overgrowth in certain areas of the brain might lead to alteration of connectivity between neurons.^[37] Peculiar brain disconnection is hypothesized to be the neural substrata of autism core symptoms as confirmed by some diffuse tensor imaging studies on altered structural connectivity in individuals with ASD.^[37]

 

 

Funding: Funding was from the National Research Centre.

Ethical approval: This work was ethically approved by the ethical committee of National Research Centre.

Competing interest: The author(s) declare that they have no competing interests.

Contributors: MNA and EAA wrote the first draft of this paper. All authors contributed to the intellectual and statistical content and approved the final version. EAA is the guarantor.

 

 

1   Hertz-Picciotto I, Delwiche L. The rise in autism and the role of age at diagnosis. Epidemiology 2009;20:84-90.

2   Gohlke JM, Thomas R, Zhang Y, Rosenstein MC, Davis AP, Murphy C, et al. Genetic and environmental pathways to complex diseases. BMC SystBiol 2009;3:46.

3   O'Roak BJ, State MW. Autism genetics: strategies, challenges, and opportunities. Autism Res 2008;1:4-17.

4   Novarino G, El-Fishawy P, Kayserili H, Meguid NA, Scott EM, Schroth J, et al. Mutations in BCKD-kinase lead to a potentially treatable form of autism with epilepsy. Science 2012;338:394-397.

5   Dufault R, Lukiw WJ, Crider R, Schnoll R, Wallinga D, Deth R. A macroepigenetic approach to identify factors responsible for the autism epidemic in the United States.Clin Epigenetics 2012;4:6.

6   Randolph-Gips M, Srinivasan P. Modeling autism: a systems biology approach. J ClinBioinforma 2012;2:17.

7   Campbell M, Petti TA, Green WH, Cohen IL, Genieser NB, David R. Some physical parameters of young autistic children. J Am Acad Child Psychiatry 1980;19:193-212.

8   Davidovitch M, Patterson B, Gartside P. Head circumference measurements in children with autism. J Child Neurol 1996;11:389-393.

9   Fidler DJ, Baily JN, Smally SL. Macrocephaly in autism and other peava size developmental disorders. Dev Med child neurol 2000;42:737-740.

10 Lainhart JE, Bigler ED, Bocian M, Coon H, Dinh E, Dawson G, et al. Head circumference and height in autism: a study by the Collaborative Program of Excellence in Autism. Am J Med Genet A 2006;140:2257-2274.

11 Rommelse NN, Peters CT, Oosterling IJ, Visser JC, Bons D, van Steijn DJ, et al. A pilot study of abnormal growth in autism spectrum disorders and other childhood psychiatric disorders. J Autism Dev Disord 2011;41:44-54.

12 Froehlich W, Cleveland S, Torres A, Phillips J, Cohen B, Torigoe T, et al. Head circumferences in twins with and without Autism Spectrum Disorders. J Autism Dev Disord 2013;43:2026-2037.

13 Sacco R, Militerni R, Frolli A, Bravaccio C, Gritti A, Elia M, et al. Clinical, morphological, and biochemical correlates of head circumference in autism. Biol Psychiatry 2007;62:1038-1047.

14 Ververi A, Vargiami E, Papadopoulou V, Tryfonas D, Zafeiriou DI. Clinical and laboratory data in a sample of Greek children with autism spectrum disorders. J Autism Dev Disord 2012;42:1470-1476.

15 Davidovitch M, Golan D, Vardi O, Lev D, Lerman-Sagie T. Israeli children with autism spectrum disorder are not macrocephalic. J Child Neurol 2011;26:580-585.

16 Miles JH, Hadden LL, Takahashi TN, Hillman RE. Head circumference is an independent clinical finding associated with autism. Am J Med Genet 2000;95:339-350.

17 Chapman SC, Lucas MJ, McCamman S. Nutritional assessment of children with autism. J Am Diet Assoc 1989;98:86-90.

18 Adams JB, Audhya T, McDonough-Means S, Rubin RA, Quig D, Geis E, et al. Nutritional and metabolic status of children with autism vs. neurotypical children, and the association with autism severity. NutrMetab (Lond) 2011;8:34.

19 Bauset SM, Zazpe I, Sanchis AM, González AL, Suárez-Varela MM. Are there anthropometric differences between autistic and healthy children? J Child Neurol 2013;28:1226-1232.

20 American Psychiatric Association. Diagnostic and statistical manual of mental disorders,4th ed. Washington, DC: American Psychiatric Association, 1994.

21 Lord C, Rutter M, Le Couteur A. Autism Diagnostic Interview-Revised: a revised version of diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord 1994;24:659-685.

22 Schopler E, Reichler RJ, Renner BR. Childhood Autism Rating Scale. Los Angeles, CA: Western Psychological Services, 1993.

23 Hiernaux J, Tanner JM, Growth and physical studies. In: Weiner JS, Lourie SA, eds. Human biology: a guide to field methods. London: Blackwell Scientific Publications Oxford UK, 1969: 315-340.

24 El-Nofely AA. Anthropometry of Egyptians from birth till senility. Cairo: Sociology Research Centre-Cairo University Press, 2012: 53-85.

25 Morhardt DR, Barrow W, Jaworski M, Accardo PJ. Head circumference in young children with autism: the impact of different head circumference charts. J Child Neurol 2014;29:412-414.

26 Berry R, Sharp WG, Jaquess DL, Hartwig S. Food selectivity and autism: a retrospective chart review regarding the anthropometric status, nutritional intake and dietary variety among children with and without ASD. Pub.Marcus Autism Center, Atlanta, GA, USA, 2012.

27 Marcus Autism Centre-Atlanta, GA, USA, 2012. http://www.marcus.org/Clinical-Services/Feeding (accessed February 1, 2013).

28 Courchesne E. Brain development in autism: early overgrowth followed by premature arrest of growth. Ment Retard Dev Disabil Res Rev 2004;10:106-111.

29 Ghaziuddin M, Zaccagnini J, Tsai L, Elardo S. Is megalencephaly specific to autism? J Intellect Disabil Res 1999;43:279-282.

30 Tager-Flusberg H, Joseph RM. Identifying neurocognitive phnotypes in autism. Philos Trans R SocLond B BiolSci 2003;358:303-314.

31 Fukumoto A, Hashimoto T, Mori K, Tsuda Y, Arisawa K, Kagami S. Head circumference and body growth in autism spectrum disorders. Brain Dev 2011;33:569-575.

32 Grandgeorge M, Lemonnier E, Jallot N. Autism spectrum disorders: Head circumference and body length at birth are both relative. ActaPaediatr 2013;102:901-907.

33 Allen JS, Damasio H, Grabowski TJ. Normal neuroanatomical variation in the human brain: an MRI-Volumetric study. Am J PhysAnthropol 2002;118:341-358.

34 Deutsch CK, Joseph RM. Brief report: cognitive correlates of enlarged head circumference in children with autism. J Autism Dev Disord 2003;33:209-215.

35 Herbert MR. Large brains in autism: the challenge of pervasive abnormality. Neuroscientist 2005;11:417-440.

36 Hyde JS, Linn MC. Gender differences in verbal ability: A meta-analysis. Psych Bul 1988;104:53-69.

37 Sundaram SR, Kumar A, Marri MI, Rehan ME, Chugani HT, Chugani DC. Diffusion tensor imaging of frontal bone in autism spectrum disorder.Cereb Cortex 2008;18:2659-2665.

 

                                                           Received August 27, 2013