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The physical status of children with autism in China
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Research in Developmental Disabilities 30 (2009) 70–76
The physical status of children with autism in China Nina Xiong a, Chengye Ji a,*, Yong Li a, Zhonghu He a, Hongli Bo b, Yufeng Zhao b a
Institute of Child and Adolescent Health, Peking University, Beijing, China b Beijing Stars Rain Education Institute for Autistic Children, China
Received 27 September 2007; received in revised form 25 October 2007; accepted 16 November 2007
Abstract The height, weight and BMI of children with autism was investigated and analyzed to find the physical status of children with autism in China. Three hundred and eighty boys and 49 girls diagnosed with autistic disorder participated. Their parents were interviewed with a questionnaire about general information, and children were evaluated with Childhood Autism Rating Scale, and height and weight were measured. Children with autism had high level height, weight and BMI; the rate of height P75 was less in 6–11 years old group than that in 2–5 years old group in boys and all children. The prevalence of at-risk-for or being overweight was 31.8% and 17.0% in 2–5 years old group, were 37.9% and 21.8% in 6–11 years old group. At-risk-for-overweight/overweight of children with autism had no relationship with their core symptoms, the older age was the only predictor for lower height and at-risk-for-overweight. Prevalence of at-risk-foroverweight and overweight in children with autism was high. Children’s height level decreased, and being at-risk-for-overweight increased with age. # 2007 Elsevier Ltd. All rights reserved. Keywords: Autism; Children; Height; Weight; BMI
1. Introduction Autism falls under the broad diagnostic category of Pervasive Developmental Disorders and is marked by impairments in communication, forming relationships/social interaction, and often behavioral control usually appears before the age of 3 years (American Psychiatric Association, 1994). To date, there is no cure for autism. However, there are a number of treatments that can * Corresponding author. Tel.: +86 10 82802344; fax: +86 10 82801178. E-mail addresses: [email protected] (N. Xiong), [email protected] (C. Ji), [email protected] (Y. Li), [email protected] (Z. He), [email protected] (H. Bo), [email protected] (Y. Zhao). 0891-4222/$ – see front matter # 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.ridd.2007.11.001
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help people with autism and their families lead more normal lives. Because of the clinic symptom characteristic of children with autism, most studies focused on language, psychology and behavior, and paid much less attention to their body growth and nutritional condition. Some studies reported underweight or propensity for underweight among autism population. Mouridsen, Rich, and Isager (2002), for example examined the height and weight status of 117 young Danish children with autism. They found body mass index (BMI) for males was significantly lower than the age matched reference population but not for females. Bo¨lte, Ozkara, and Poustka (2002) in a related study investigated and analyzed the BMI of 103 participants with autism or Asperger’s syndrome. Twenty-eight percent of the male individuals had a BMI in the fifth percentile or below. In a study conducted in Germany, a low BMI was reported in 13 children with Asperger’s syndrome (Hebebrand et al., 1997). Lesinskiene, Vilu¯naite, and Paskeviciu¯te (2002) found specific characteristics such as low appetite, narrow range of assortment of preferable dishes, and digestive autonomic nervous system reactions were significantly more common in the autistic group when compared to healthy controls. Physical growth of autistic children was delayed and was accompanied by other problematic behaviors. Other studies reported high epidemical level of at-risk-for-overweight and overweight among children with autism. A study of 140 Japanese children 7–18 years of age with autism for example revealed that 25% of the children were classified as obese (Sugiyama, 1991). Furthermore, a large study of 20,031 Japanese children and adolescents with mental retardation (6–17 years) that included 413 children with autism, the prevalence of obesity was reported to be 22% in boys and 11% in girls (Takeuchi, 1994); Curtin, Bandini, Perrin, Tybor, and Must (2005) found the overall prevalence of at-risk-for-overweight was 35.7% and prevalence of overweight was 19% among ASD children, when stratified by age, the prevalence of at-risk-for-overweight and overweight appears to be highest in the 12.0–17.9 years old group, differences by age category were not significant. Children with autism have different dietary pattern and life style from common children. These life style issues affect body growth and nutritional condition. The present study was aimed at extending further our knowledge of the physical status of children with autism with a group of Chinese children with autism. 2. Method 2.1. Participants We recruited children diagnosed and place in a school for autism (mainly provided Applied Behavior Analysis course) from 1999 to 2006. Excluded from the sample were children with Rett syndrome, Asperger syndrome or other autism spectrum disorders. A final cohort of 380 boys and 49 girls participated in our study. The ratio of males to females was 7.8:1, the children’s mean age was 5.1 years (S.D. = 1.7; range = 2–11 years). Table 1 summarizes some of the demographic detail of the children. All of the children had received a clinical diagnosis of autistic disorder from a pediatrician or psychiatrist using criteria established in the third edition of the Chinese Classification and diagnostic criteria of Mental Disorders (CCMD-3; Chinese Society of Psychiatry, 2001). To enroll in the school for autistic children they came to register they had to show the certificate of diagnosis or case history. The agreement for diagnosis of autism between CCMD-3 and ICD-10 was 100.0% (Kappa = 1.000, P = 0.000; Guo, Wan, & Shan, 2002), and the accordance of diagnosis of autism between CCMD-3 and DSM-IV was also well (96.08%; Liu, Yang, & Jia, 2006).
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N. Xiong et al. / Research in Developmental Disabilities 30 (2009) 70–76
Table 1 Sample characteristics Age (years old)
Boys
Girls
Total
n
%
n
%
n
%
2 3 4 5 6 7 8 9 10 11
13 62 108 89 58 22 14 4 7 3
3.4 16.3 28.4 23.4 15.3 5.8 3.7 1.1 1.8 0.8
2 7 16 8 8 2 3 0 2 1
4.1 14.3 32.7 16.3 16.3 4.1 6.1 0.0 4.1 2.0
15 69 124 97 66 24 17 4 9 4
3.5 16.1 28.9 22.6 15.4 5.6 4.0 0.9 2.1 0.9
Total
380
88.6
49
11.4
429
100.0
2.2. Procedure This study employed a general information interview (including the height and weight measuring) and a clinical symptom evaluation, by one researcher and two psychology teachers from the autism school. All clinical trials were approved by the Peking University ethics committee. The researcher interviewed parents with a questionnaire mainly about the child’s gender, date of birth, parent’s education level etc. and measured the height and weight of each children. BMI was calculated from the height and weight. Percentiles were calculated according to age-adapted reference values of the 2000 CDC growth charts for the United States (Department of Health and Human Services CCDC-P-NCHS, 2002). We chose the cut-point of P5, P75 and P95 for height and weight, P5, P85 (at-risk-for-overweight) and P95 (overweight) for BMI (Barlow & Dietz, 1998). The psychology teachers evaluated children with the Childhood Autism Rating Scale (CARS; Schopler, Reichler, Devellis, & Daly, 1980). The CARS was originally developed to identify children with autism according to commonly employed diagnostic criteria. The CARS consists of 15 items: (1) relating to people; (2) imitation; (3) emotional response; (4) body use; (5) object use; (6) adaptation to change; (7) visual response; (8) listening response; (9) taste, smell, and touch response and use; 10) anxiety; (11) verbal communication; (12) nonverbal communication; (13) activity level; (14) level and consistency of intellectual response; (15) general impressions. Each scale is rated with a score of 1 (with normal for child’s age), 2 (mildly abnormal), 3 (moderately abnormal), or 4 (severely abnormal). Additionally, Tobing and Glenwick (2002) have reported on the CARS-P (Childhood Autism Rating Scale-Parent version, the categories of the CARS-P are the same as those of the CARS, with the exception of the deletion of one item, general impressions). Advantages of the CARS over other diagnostic systems include fewer items and a shorter administration time. Liu, Yang, Shu, and Su (2004) had found the alpha reliability for CARS was 0.735 for the Chinese version. 2.3. Data analysis Chi-square was used to compare the percentiles of height, weight and BMI between different gender groups and different age groups, Binary logistic regression was performed using a enter
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Table 2 The physical status of children with autism in different groups Groups
Height, cm (%)
Weight, kg (%)
BMI (%)
P5
P75
P95
P5
P75
P95
P5
P85
P95
2–5-year-old boys (n = 272) 6–11 year old boys (n = 108)
1.5 3.7
49.6 28.7##
14.0 12.0
1.8 3.7
46.7 53.7
19.1 16.7
8.1 2.8
32.7 38.9
18.0 20.4
2–5-year-old girls (n = 33) 6–11-year-old girls (n = 16)
6.1 6.3
45.5 43.8
12.1 0.0
0.0 6.3
39.4 31.3
18.2 25.0
3.0 18.8
24.2 31.3
9.1 31.3
2–5-year-old children (n = 305) 6–11-year-old children (n = 124)
2.0 4.0
49.2 30.6##
13.8 10.5
1.6 4.0
45.9 50.8
19.0 17.7
7.5 4.8
31.8 37.9
17.0 21.8
2–11-year-old boys (n = 380) 2–11-year-old girls (n = 49)
2.1 6.1
43.7 44.9
13.4 8.2
2.4 2.0
48.7 36.7
18.4 20.4
6.6 8.2
34.5 26.5
18.7 16.3
2–11-year-old children (n = 429)
2.6
43.8
12.8
2.3
47.3
18.6
6.8
33.6
18.4
2
(##) x tests, P < 0.01.
method to find the predictors of height P5, P75, P95, and the predictors of BMI P5, P85 and P95. SPSS 11.5 was employed for all the statistical analysis. 3. Result The following data from our total sample was obtained; 2.6% height P5, 43.8% height P75, 12.8% height P95; 2.3% weight P5, 47.3% weight P75, 18.6% weight P95; 6.8% BMI P5, 33.6% BMI P85, 18.4% BMI P95. There was no difference on height between boys and girls compared to their norm groups, but rate of height P75 was less in 6–11 years old group than that in 2–5 years old group in boys and all children. As to the weight and BMI of autistic children, no difference between gender and age were noted (Table 2). We employed binary logistic regression to find the predictors of children’s height. Children’ height level was entered as a dependent variables, children’s gender (1, male; 2, female), children’s age (2–11 years), father’s education level (1, college or above; 2, high middle school; 3, low middle school or below), mother’s education level, and CARS (18–56) scores were entered as independent variables. When children’s height P5 (1, P5; 0, >P5), children’s height P95 (1, P95; 0,
Gender Age Father education Mother education CARS score Constant
Height P75
Height P5
Height P95
OR
95% CI
P
OR
95% CI
P
OR
95% CI
P
2.778 1.296 0.785 1.436 1.021 0.001
0.692–11.152 0.967–1.737 0.247–2.493 0.481–4.288 0.927–1.124
0.150 0.083 0.681 0.517 0.680 0.004
1.061 0.794 1.204 0.973 0.989 2.345
0.571–1.971 0.700–0.900 0.816–1.777 0.666–1.421 0.957–1.022
0.851 0.000 0.349 0.886 0.500 0.296
0.610 0.832 1.421 0.716 0.994 0.760
0.209–1.780 0.684–1.011 0.798–2.530 0.404–1.268 0.947–1.043
0.365 0.064 0.232 0.252 0.817 0.823
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N. Xiong et al. / Research in Developmental Disabilities 30 (2009) 70–76
Table 4 Binary regression predicting BMI of children with autism Variables
Gender Age Father education Mother education CARS score Constant
BMI P85
BMI P5
BMI P95
OR
95% CI
P
OR
95% CI
P
OR
95% CI
P
1.381 0.915 1.256 0.929 0.997 0.059
0.456–4.182 0.717–1.168 0.588–2.686 0.440–1.963 0.935–1.063
0.568 0.477 0.556 0.847 0.920 0.075
0.617 1.126 1.079 1.018 0.986 0.600
0.308–1.236 1.000–1.267 0.722–1.614 0.687–1.509 0.953–1.020
0.173 0.049 0.709 0.927 0.404 0.551
0.853 1.120 1.023 1.064 0.989 0.177
0.380–1.916 0.976–1.285 0.629–1.665 0.661–1.712 0.949–1.030
0.700 0.107 0.926 0.799 0.583 0.095
We also employed binary logistic regression to establish predictors of children’s BMI. Children’ BMI level entered as dependent variables, Children’s gender (1, male; 2, female), children’s age (2–11 years), father’s education level (1, college or above; 2, high middle school; 3, low middle school or below), mother’s education level, score of CARS (18–56) entered as independent variables. When children’s BMI P5 (1, P5; 0, >P5), BMI P95 (1, P95; 0,
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problems in childhood may be a more proximal indicator of overweight risk in childhood. Autistic children had so many behavior problems that the serious prevalence of at-risk-foroverweight and overweight may be partly attributed to their behavior problems. This hypothesis requires further study. The analysis of logistic regression showed the score of CARS or CARS-P was not a predictor for height or for at-risk-for-overweight/overweight. Overweight had no relationship with core clinical symptom of children with autism. We did find that older age was the only predictor of lower height and at-risk-for-overweight (BMI P85). Rosser and Frey (2003) reported less time spent in moderate activity in children with ASD compared to children without ASD. Opportunities to engage in structured activities may be limited for these children and may further decline with age for children with ASD (Curtin et al., 2005). These factors may explain the decreasing height and increasing at-risk-for-overweight with age in children with autism. The factors that contribute to overweight or its development in autistic children may different from normal children. Therefore, this field still needs further exploration. Furthermore, the burden of managing potential co-morbidities associated with obesity may be particularly problematic for children with developmental disorders and their families. As a result, this area need more focus, including the involvement of parents of children with autism. References Aman, M. G., Arnold, L. E., McDougle, C. J., Vitiello, B., Scahill, L., Davies, M., et al. (2005). Acute and long-term safety and tolerability of Risperidone in children with autism. Journal of Child and Adolescent Psychopharmacology, 15, 869–884. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th edition). Washington, DC: American Psychiatric Association. Barlow, S. E., & Dietz, W. H. (1998). Obesity evaluation and treatment: Expert committee recommendations. The Maternal and Child Health Bureau, Health Resources and Services Administration and the Department of Health and Human Services. Pediatrics, 102, E29. Bo¨lte, S., Ozkara, N., & Poustka, F. (2002). Autism spectrum disorders and low body weight: Is there really a systematic association? International Journal of Eating Disorders, 31, 349–351. Chinese Society of Psychiatry. (2001). The third edition of the Chinese classification and diagnostic criteria of mental disorders. Jinan: Shandong Science and Technology Press. (in Chinese). Curtin, C., Bandini, L. G., Perrin, E. C., Tybor, D. J., & Must, A. (2005). Prevalence of overweight in children and adolescents with attention deficit hyperactivity disorder and autism spectrum disorders: A chart review. BMC Pediatrics, 5, 48. Department of Health and Human Services CCDC-P-NCHS. (2002). Vital and health statistics, 2000. CDC growth chart for the United States: Methods and development, data from the National Health and Nutrition Examination Surveys (NHANES). Guo, L.-T., Wan, Y., & Shan, Y.-H. (2002). A clinical study of the third edition of the Chinese classification and diagnostic criteria of mental disorders for childhood autism. Chinese Journal of Psychiatry, 35, 162–165 (in Chinese). Hebebrand, J., Hennighausen, K., Nau, S., Himmelmann, G. W., Schulz, E., Schafer, H., et al. (1997). Low body weight in male children and adolescents with schizoid personality disorder or Asperger’s disorder. Acta Psychiatric Scandivania, 96, 64–67. Lesinskiene, S., Vilu¯naite, E., & Paskeviciu¯te, B. (2002). Aspects of the development of autistic children. Medicina (Kaunas), 38, 405–411. Liu, J.-P., Yang, Z.-W., Shu, M.-Y., & Su, L.-Y. (2004). Reliability, validity analysis of the childhood autism rating scale. China Journal of Modern Medicine, 14, 119–123 (in Chinese). Liu, J., Yang, X.-L., & Jia, M.-X. (2006). A comparative study of diagnostic criteria of CCMD-3 and DSM-IV on childhood autism. Chinese Mental Health Journal, 20, 568–585 (in Chinese). Lumeng, J. C., Gannon, K., Cabral, H. J., Frank, D. A., & Zuckerman, B. (2003). Association between clinically meaningful behavior problems and overweight in children. Pediatrics, 112, 1138–1145.
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Mouridsen, S. E., Rich, B., & Isager, T. (2002). Body mass index in male and female children with infantile autism. Autism, 6, 197–205. Must, A., & Srauss, R. S. (1999). Risks and consequences of childhood and adolescent obesity. International Journal of Obesity, 23(Suppl 2), S2–S11. Rosser, D. D., & Frey, G. C. (2003). Comparison on physical activity levels between children with and without autistic spectrum disorders. Medicine & Science in Sports & Exercise 35 S1. S76. Schopler, E., Reichler, R. J., Devellis, R. F., & Daly, K. (1980). Toward objective classification of childhood autism: Childhood autism rating scale (CARS). Journal of Autism and Developmental Disorders, 10, 91–103. Sugiyama, T. (1991). A research of obesity in autism. Japanese Journal on Developmental Disabilities, 13, 53–58. Takeuchi, E. (1994). Incidence of obesity among school children with mental retardation in Japan. American Journal of Mental Retardation, 99, 283–288. Tobing, L. E., & Glenwick, D. S. (2002). Relation of the childhood autism rating scale—Parent version to diagnosis, stress, and age. Research in Developmental Disabilities, 23, 211–223. Valicenti-McDermott, M. R., & Demb, H. (2006). Clinical effects and adverse reactions of off-label use of Aripiprazole in children and adolescents with developmental disabilities. Journal of Child and Adolescent Psychopharmacology, 16, 549–560.
Research in Developmental Disabilities 30 (2009) 70–76
The physical status of children with autism in China Nina Xiong a, Chengye Ji a,*, Yong Li a, Zhonghu He a, Hongli Bo b, Yufeng Zhao b a
Institute of Child and Adolescent Health, Peking University, Beijing, China b Beijing Stars Rain Education Institute for Autistic Children, China
Received 27 September 2007; received in revised form 25 October 2007; accepted 16 November 2007
Abstract The height, weight and BMI of children with autism was investigated and analyzed to find the physical status of children with autism in China. Three hundred and eighty boys and 49 girls diagnosed with autistic disorder participated. Their parents were interviewed with a questionnaire about general information, and children were evaluated with Childhood Autism Rating Scale, and height and weight were measured. Children with autism had high level height, weight and BMI; the rate of height P75 was less in 6–11 years old group than that in 2–5 years old group in boys and all children. The prevalence of at-risk-for or being overweight was 31.8% and 17.0% in 2–5 years old group, were 37.9% and 21.8% in 6–11 years old group. At-risk-for-overweight/overweight of children with autism had no relationship with their core symptoms, the older age was the only predictor for lower height and at-risk-for-overweight. Prevalence of at-risk-foroverweight and overweight in children with autism was high. Children’s height level decreased, and being at-risk-for-overweight increased with age. # 2007 Elsevier Ltd. All rights reserved. Keywords: Autism; Children; Height; Weight; BMI
1. Introduction Autism falls under the broad diagnostic category of Pervasive Developmental Disorders and is marked by impairments in communication, forming relationships/social interaction, and often behavioral control usually appears before the age of 3 years (American Psychiatric Association, 1994). To date, there is no cure for autism. However, there are a number of treatments that can * Corresponding author. Tel.: +86 10 82802344; fax: +86 10 82801178. E-mail addresses: [email protected] (N. Xiong), [email protected] (C. Ji), [email protected] (Y. Li), [email protected] (Z. He), [email protected] (H. Bo), [email protected] (Y. Zhao). 0891-4222/$ – see front matter # 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.ridd.2007.11.001
N. Xiong et al. / Research in Developmental Disabilities 30 (2009) 70–76
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help people with autism and their families lead more normal lives. Because of the clinic symptom characteristic of children with autism, most studies focused on language, psychology and behavior, and paid much less attention to their body growth and nutritional condition. Some studies reported underweight or propensity for underweight among autism population. Mouridsen, Rich, and Isager (2002), for example examined the height and weight status of 117 young Danish children with autism. They found body mass index (BMI) for males was significantly lower than the age matched reference population but not for females. Bo¨lte, Ozkara, and Poustka (2002) in a related study investigated and analyzed the BMI of 103 participants with autism or Asperger’s syndrome. Twenty-eight percent of the male individuals had a BMI in the fifth percentile or below. In a study conducted in Germany, a low BMI was reported in 13 children with Asperger’s syndrome (Hebebrand et al., 1997). Lesinskiene, Vilu¯naite, and Paskeviciu¯te (2002) found specific characteristics such as low appetite, narrow range of assortment of preferable dishes, and digestive autonomic nervous system reactions were significantly more common in the autistic group when compared to healthy controls. Physical growth of autistic children was delayed and was accompanied by other problematic behaviors. Other studies reported high epidemical level of at-risk-for-overweight and overweight among children with autism. A study of 140 Japanese children 7–18 years of age with autism for example revealed that 25% of the children were classified as obese (Sugiyama, 1991). Furthermore, a large study of 20,031 Japanese children and adolescents with mental retardation (6–17 years) that included 413 children with autism, the prevalence of obesity was reported to be 22% in boys and 11% in girls (Takeuchi, 1994); Curtin, Bandini, Perrin, Tybor, and Must (2005) found the overall prevalence of at-risk-for-overweight was 35.7% and prevalence of overweight was 19% among ASD children, when stratified by age, the prevalence of at-risk-for-overweight and overweight appears to be highest in the 12.0–17.9 years old group, differences by age category were not significant. Children with autism have different dietary pattern and life style from common children. These life style issues affect body growth and nutritional condition. The present study was aimed at extending further our knowledge of the physical status of children with autism with a group of Chinese children with autism. 2. Method 2.1. Participants We recruited children diagnosed and place in a school for autism (mainly provided Applied Behavior Analysis course) from 1999 to 2006. Excluded from the sample were children with Rett syndrome, Asperger syndrome or other autism spectrum disorders. A final cohort of 380 boys and 49 girls participated in our study. The ratio of males to females was 7.8:1, the children’s mean age was 5.1 years (S.D. = 1.7; range = 2–11 years). Table 1 summarizes some of the demographic detail of the children. All of the children had received a clinical diagnosis of autistic disorder from a pediatrician or psychiatrist using criteria established in the third edition of the Chinese Classification and diagnostic criteria of Mental Disorders (CCMD-3; Chinese Society of Psychiatry, 2001). To enroll in the school for autistic children they came to register they had to show the certificate of diagnosis or case history. The agreement for diagnosis of autism between CCMD-3 and ICD-10 was 100.0% (Kappa = 1.000, P = 0.000; Guo, Wan, & Shan, 2002), and the accordance of diagnosis of autism between CCMD-3 and DSM-IV was also well (96.08%; Liu, Yang, & Jia, 2006).
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N. Xiong et al. / Research in Developmental Disabilities 30 (2009) 70–76
Table 1 Sample characteristics Age (years old)
Boys
Girls
Total
n
%
n
%
n
%
2 3 4 5 6 7 8 9 10 11
13 62 108 89 58 22 14 4 7 3
3.4 16.3 28.4 23.4 15.3 5.8 3.7 1.1 1.8 0.8
2 7 16 8 8 2 3 0 2 1
4.1 14.3 32.7 16.3 16.3 4.1 6.1 0.0 4.1 2.0
15 69 124 97 66 24 17 4 9 4
3.5 16.1 28.9 22.6 15.4 5.6 4.0 0.9 2.1 0.9
Total
380
88.6
49
11.4
429
100.0
2.2. Procedure This study employed a general information interview (including the height and weight measuring) and a clinical symptom evaluation, by one researcher and two psychology teachers from the autism school. All clinical trials were approved by the Peking University ethics committee. The researcher interviewed parents with a questionnaire mainly about the child’s gender, date of birth, parent’s education level etc. and measured the height and weight of each children. BMI was calculated from the height and weight. Percentiles were calculated according to age-adapted reference values of the 2000 CDC growth charts for the United States (Department of Health and Human Services CCDC-P-NCHS, 2002). We chose the cut-point of P5, P75 and P95 for height and weight, P5, P85 (at-risk-for-overweight) and P95 (overweight) for BMI (Barlow & Dietz, 1998). The psychology teachers evaluated children with the Childhood Autism Rating Scale (CARS; Schopler, Reichler, Devellis, & Daly, 1980). The CARS was originally developed to identify children with autism according to commonly employed diagnostic criteria. The CARS consists of 15 items: (1) relating to people; (2) imitation; (3) emotional response; (4) body use; (5) object use; (6) adaptation to change; (7) visual response; (8) listening response; (9) taste, smell, and touch response and use; 10) anxiety; (11) verbal communication; (12) nonverbal communication; (13) activity level; (14) level and consistency of intellectual response; (15) general impressions. Each scale is rated with a score of 1 (with normal for child’s age), 2 (mildly abnormal), 3 (moderately abnormal), or 4 (severely abnormal). Additionally, Tobing and Glenwick (2002) have reported on the CARS-P (Childhood Autism Rating Scale-Parent version, the categories of the CARS-P are the same as those of the CARS, with the exception of the deletion of one item, general impressions). Advantages of the CARS over other diagnostic systems include fewer items and a shorter administration time. Liu, Yang, Shu, and Su (2004) had found the alpha reliability for CARS was 0.735 for the Chinese version. 2.3. Data analysis Chi-square was used to compare the percentiles of height, weight and BMI between different gender groups and different age groups, Binary logistic regression was performed using a enter
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Table 2 The physical status of children with autism in different groups Groups
Height, cm (%)
Weight, kg (%)
BMI (%)
P5
P75
P95
P5
P75
P95
P5
P85
P95
2–5-year-old boys (n = 272) 6–11 year old boys (n = 108)
1.5 3.7
49.6 28.7##
14.0 12.0
1.8 3.7
46.7 53.7
19.1 16.7
8.1 2.8
32.7 38.9
18.0 20.4
2–5-year-old girls (n = 33) 6–11-year-old girls (n = 16)
6.1 6.3
45.5 43.8
12.1 0.0
0.0 6.3
39.4 31.3
18.2 25.0
3.0 18.8
24.2 31.3
9.1 31.3
2–5-year-old children (n = 305) 6–11-year-old children (n = 124)
2.0 4.0
49.2 30.6##
13.8 10.5
1.6 4.0
45.9 50.8
19.0 17.7
7.5 4.8
31.8 37.9
17.0 21.8
2–11-year-old boys (n = 380) 2–11-year-old girls (n = 49)
2.1 6.1
43.7 44.9
13.4 8.2
2.4 2.0
48.7 36.7
18.4 20.4
6.6 8.2
34.5 26.5
18.7 16.3
2–11-year-old children (n = 429)
2.6
43.8
12.8
2.3
47.3
18.6
6.8
33.6
18.4
2
(##) x tests, P < 0.01.
method to find the predictors of height P5, P75, P95, and the predictors of BMI P5, P85 and P95. SPSS 11.5 was employed for all the statistical analysis. 3. Result The following data from our total sample was obtained; 2.6% height P5, 43.8% height P75, 12.8% height P95; 2.3% weight P5, 47.3% weight P75, 18.6% weight P95; 6.8% BMI P5, 33.6% BMI P85, 18.4% BMI P95. There was no difference on height between boys and girls compared to their norm groups, but rate of height P75 was less in 6–11 years old group than that in 2–5 years old group in boys and all children. As to the weight and BMI of autistic children, no difference between gender and age were noted (Table 2). We employed binary logistic regression to find the predictors of children’s height. Children’ height level was entered as a dependent variables, children’s gender (1, male; 2, female), children’s age (2–11 years), father’s education level (1, college or above; 2, high middle school; 3, low middle school or below), mother’s education level, and CARS (18–56) scores were entered as independent variables. When children’s height P5 (1, P5; 0, >P5), children’s height P95 (1, P95; 0,
Gender Age Father education Mother education CARS score Constant
Height P75
Height P5
Height P95
OR
95% CI
P
OR
95% CI
P
OR
95% CI
P
2.778 1.296 0.785 1.436 1.021 0.001
0.692–11.152 0.967–1.737 0.247–2.493 0.481–4.288 0.927–1.124
0.150 0.083 0.681 0.517 0.680 0.004
1.061 0.794 1.204 0.973 0.989 2.345
0.571–1.971 0.700–0.900 0.816–1.777 0.666–1.421 0.957–1.022
0.851 0.000 0.349 0.886 0.500 0.296
0.610 0.832 1.421 0.716 0.994 0.760
0.209–1.780 0.684–1.011 0.798–2.530 0.404–1.268 0.947–1.043
0.365 0.064 0.232 0.252 0.817 0.823
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Table 4 Binary regression predicting BMI of children with autism Variables
Gender Age Father education Mother education CARS score Constant
BMI P85
BMI P5
BMI P95
OR
95% CI
P
OR
95% CI
P
OR
95% CI
P
1.381 0.915 1.256 0.929 0.997 0.059
0.456–4.182 0.717–1.168 0.588–2.686 0.440–1.963 0.935–1.063
0.568 0.477 0.556 0.847 0.920 0.075
0.617 1.126 1.079 1.018 0.986 0.600
0.308–1.236 1.000–1.267 0.722–1.614 0.687–1.509 0.953–1.020
0.173 0.049 0.709 0.927 0.404 0.551
0.853 1.120 1.023 1.064 0.989 0.177
0.380–1.916 0.976–1.285 0.629–1.665 0.661–1.712 0.949–1.030
0.700 0.107 0.926 0.799 0.583 0.095
We also employed binary logistic regression to establish predictors of children’s BMI. Children’ BMI level entered as dependent variables, Children’s gender (1, male; 2, female), children’s age (2–11 years), father’s education level (1, college or above; 2, high middle school; 3, low middle school or below), mother’s education level, score of CARS (18–56) entered as independent variables. When children’s BMI P5 (1, P5; 0, >P5), BMI P95 (1, P95; 0,
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problems in childhood may be a more proximal indicator of overweight risk in childhood. Autistic children had so many behavior problems that the serious prevalence of at-risk-foroverweight and overweight may be partly attributed to their behavior problems. This hypothesis requires further study. The analysis of logistic regression showed the score of CARS or CARS-P was not a predictor for height or for at-risk-for-overweight/overweight. Overweight had no relationship with core clinical symptom of children with autism. We did find that older age was the only predictor of lower height and at-risk-for-overweight (BMI P85). Rosser and Frey (2003) reported less time spent in moderate activity in children with ASD compared to children without ASD. Opportunities to engage in structured activities may be limited for these children and may further decline with age for children with ASD (Curtin et al., 2005). These factors may explain the decreasing height and increasing at-risk-for-overweight with age in children with autism. The factors that contribute to overweight or its development in autistic children may different from normal children. Therefore, this field still needs further exploration. Furthermore, the burden of managing potential co-morbidities associated with obesity may be particularly problematic for children with developmental disorders and their families. As a result, this area need more focus, including the involvement of parents of children with autism. References Aman, M. G., Arnold, L. E., McDougle, C. J., Vitiello, B., Scahill, L., Davies, M., et al. (2005). Acute and long-term safety and tolerability of Risperidone in children with autism. Journal of Child and Adolescent Psychopharmacology, 15, 869–884. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th edition). Washington, DC: American Psychiatric Association. Barlow, S. E., & Dietz, W. H. (1998). Obesity evaluation and treatment: Expert committee recommendations. The Maternal and Child Health Bureau, Health Resources and Services Administration and the Department of Health and Human Services. Pediatrics, 102, E29. Bo¨lte, S., Ozkara, N., & Poustka, F. (2002). Autism spectrum disorders and low body weight: Is there really a systematic association? International Journal of Eating Disorders, 31, 349–351. Chinese Society of Psychiatry. (2001). The third edition of the Chinese classification and diagnostic criteria of mental disorders. Jinan: Shandong Science and Technology Press. (in Chinese). Curtin, C., Bandini, L. G., Perrin, E. C., Tybor, D. J., & Must, A. (2005). Prevalence of overweight in children and adolescents with attention deficit hyperactivity disorder and autism spectrum disorders: A chart review. BMC Pediatrics, 5, 48. Department of Health and Human Services CCDC-P-NCHS. (2002). Vital and health statistics, 2000. CDC growth chart for the United States: Methods and development, data from the National Health and Nutrition Examination Surveys (NHANES). Guo, L.-T., Wan, Y., & Shan, Y.-H. (2002). A clinical study of the third edition of the Chinese classification and diagnostic criteria of mental disorders for childhood autism. Chinese Journal of Psychiatry, 35, 162–165 (in Chinese). Hebebrand, J., Hennighausen, K., Nau, S., Himmelmann, G. W., Schulz, E., Schafer, H., et al. (1997). Low body weight in male children and adolescents with schizoid personality disorder or Asperger’s disorder. Acta Psychiatric Scandivania, 96, 64–67. Lesinskiene, S., Vilu¯naite, E., & Paskeviciu¯te, B. (2002). Aspects of the development of autistic children. Medicina (Kaunas), 38, 405–411. Liu, J.-P., Yang, Z.-W., Shu, M.-Y., & Su, L.-Y. (2004). Reliability, validity analysis of the childhood autism rating scale. China Journal of Modern Medicine, 14, 119–123 (in Chinese). Liu, J., Yang, X.-L., & Jia, M.-X. (2006). A comparative study of diagnostic criteria of CCMD-3 and DSM-IV on childhood autism. Chinese Mental Health Journal, 20, 568–585 (in Chinese). Lumeng, J. C., Gannon, K., Cabral, H. J., Frank, D. A., & Zuckerman, B. (2003). Association between clinically meaningful behavior problems and overweight in children. Pediatrics, 112, 1138–1145.
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N. Xiong et al. / Research in Developmental Disabilities 30 (2009) 70–76
Mouridsen, S. E., Rich, B., & Isager, T. (2002). Body mass index in male and female children with infantile autism. Autism, 6, 197–205. Must, A., & Srauss, R. S. (1999). Risks and consequences of childhood and adolescent obesity. International Journal of Obesity, 23(Suppl 2), S2–S11. Rosser, D. D., & Frey, G. C. (2003). Comparison on physical activity levels between children with and without autistic spectrum disorders. Medicine & Science in Sports & Exercise 35 S1. S76. Schopler, E., Reichler, R. J., Devellis, R. F., & Daly, K. (1980). Toward objective classification of childhood autism: Childhood autism rating scale (CARS). Journal of Autism and Developmental Disorders, 10, 91–103. Sugiyama, T. (1991). A research of obesity in autism. Japanese Journal on Developmental Disabilities, 13, 53–58. Takeuchi, E. (1994). Incidence of obesity among school children with mental retardation in Japan. American Journal of Mental Retardation, 99, 283–288. Tobing, L. E., & Glenwick, D. S. (2002). Relation of the childhood autism rating scale—Parent version to diagnosis, stress, and age. Research in Developmental Disabilities, 23, 211–223. Valicenti-McDermott, M. R., & Demb, H. (2006). Clinical effects and adverse reactions of off-label use of Aripiprazole in children and adolescents with developmental disabilities. Journal of Child and Adolescent Psychopharmacology, 16, 549–560.