Is body Mass Index as a Marker of Obesity Predicting Motor Development of Obese Children?

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Article Type:
Editorial (دارای رتبه معتبر)
Abstract:

The issue of obesity in childhood will be associated with deficits in rudimentary, basic, and specialized skills, as well as a drop in physical literacy. This problem can be the beginning of delay in other motor skills in later ages, so that it strengthens the negative cycle of obesity-inactivity-poor motor development, which reciprocally causes obesity to decrease in motor development and decrease in motor development causes obesity. Regardless of the physical effects, obesity and poor motor development cause the decline of psychological functions of obese children such as self-confidence and self-esteem. The issue that is the basis of the trainers' action for the diagnosis of obesity is the the body mass index, which cannot seem logical due to the importance of body composition. Therefore, it is essential that teachers and trainers do not have classifications based on the child's weight and body mass index calculation, because the state of muscles, body water and fat percentage are important in calculating this overall weight value. In response to the main question why the body mass index as an accepted measure of obesity cannot predict the motor development of obese children, it can be stated that absolute body weight index is a combination of muscles, fat percentage, body water and skeletal system. For instance, a child who has a body mass index between 20 and 25 has a good physical condition according to diagnostic criteria, but there are cases where the same body mass index can be misleading and the child is obese. For example, a child has sarcopenic obesity and has lost part of his muscles and replaced it with fat, so when we want to check the condition of children's obesity, the best ideal is to check their body composition in order to have a more accurate measure for predicting the motor development process of children.

Language:
English
Published:
Journal of Motor Control and Learning, Volume:5 Issue: 2, Spring 2023
Pages:
19 to 20
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