ESPE Abstracts (2018) 89 P-P3-166

Assessment of Obesity in Children with Achondroplasia and Hypochondroplasia

Yukako Nakanoa, Taichi Kitaokaa, Shinji Takeyaria, Yasuhisa Ohataa,b, Takuo Kubotaa & Keiichi Ozonoa


aDepartment of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan; bThe 1st. Department of Oral and Maxillofacial Surgery, Osaka University Graduate School of Dentistry, Suita, Japan


Introduction: Obesity is one of common complications in achondroplasia (ACH) and hypochondroplasia (HCH). Obesity can be a risk factor for excessive load on joints or lower spines in aged, worsen sleep apnea and develop a metabolic syndrome. Thus, it is critical to maintain their proper weight from early childhood. ACH specific growth charts and BMI has been used to evaluate their overweight and obesity. Due to disproportional short stature, the assessment by BMI could lead an overestimation of body fat. Dual X-ray absorptiometry has been known to be a powerful tool to assess body compositions accurately. In this study, DXA as well as anthropometric measurement were performed to evaluate the degree of obesity in our cohort.

Objective: Our objective is to assess their obesity using % body fat by DXA and body index obtained from anthropometric measurement and to find a useful parameter which reflects an adiposity.

Subjective and Methods: Thirty-one participants of our University Hospital were recruited in this retrospective study. Their anthropometric measurements (height, weight, hip circumference and waist circumference) were extracted from the medical records. Then, we calculated BMI, waist height ratio and waist hip ratio. Whole body DXA scans were performed on a Hologic Discovery A DXA scanner (Hologic Inc., Waltham, MA). % body fat was also measured by Tanita DC320 dual frequency body composition analyzer (Tania Corp. Tokyo, Japan) using bioelectrical impedance analysis (BIA). All statistical analyses were performed using IBM SPSS Statistics software. The definition of obesity was made the following conditions; boys with more than 25% body fat, girls under 10 years of age with more than 30% body fat and girls over 11 years old with more than 35% body fat.

Results: It was 25.8% that met the criteria of obesity (27.8% in boy and 23.1% in girl). Whereas, subjects with BMI over 85% accounted for 83.9%. (83.3% in boy, 84.6% in girl). Moreover, as much as 45.2% of all was above 95% BMI (50% in boy, 38.5% in girl). Our data showed no age dependency to fulfill obesity criteria from the point of %BF.

Discussion: There was a discrepancy between BMI percentile and %BF (DXA) in number of patients satisfied obesity criteria. It seems to be unreliable to predict a quantity of adiposity from BMI. The relationship between obesity and insulin resistance is the next issue to be examined.

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