Melissa Chambers1, Stephanie K Tanamas2, Elena J Clark2, Diana L Dunnigan3, Chirag R Kapadia1, Robert L Hanson2, Robert G Nelson2, William C Knowler2, Madhumita Sinha4. 1. Division of Endocrinology and Diabetes, Phoenix Children's Hospital, Phoenix, Arizona. 2. Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona; and. 3. Phoenix Indian Medical Center, Phoenix, Arizona. 4. Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona; and madhumita.sinha@nih.gov.
Abstract
OBJECTIVES: To illustrate the difficulties in optimal growth monitoring of children with severe obesity or underweight by using the Centers for Disease Control and Prevention (CDC) 2000 age- and sex-specific BMI percentile growth charts. We also aimed to examine the utility of a new modified CDC BMI z score chart to monitor growth in children with normal and extreme BMI percentiles by using real-life clinical scenarios. METHODS: Modified BMI z score charts were created by using the 2000 CDC algorithm. Three cases of children with extreme BMI values and abnormal growth patterns were plotted by using the standard CDC 2000 clinical growth chart, the modified BMI z score chart, and the CDC BMI percentile chart, modified to include the percentage of the 95th percentile (%BMIp95) curves. RESULTS: Children with severe obesity could not be plotted on the standard CDC BMI percentile chart because their BMI points lay above the chart cutoff. Children with a low BMI (<3%) were also difficult to track on the standard BMI percentile chart. The addition of the %BMIp95 scale to the standard BMI percentile chart allowed tracking of severely obese children; however, it did not address severely underweight children and required a change of units within the chart when transitioning from normal to obese BMIs. The modified BMI z score chart allowed uniform tracking. CONCLUSIONS: The modified CDC z score chart is suitable for growth tracking of children with normal and extreme growth patterns; the measures correlate well with the %BMIp95, and the chart can be incorporated easily into existing electronic health record systems for clinical use.
OBJECTIVES: To illustrate the difficulties in optimal growth monitoring of children with severe obesity or underweight by using the Centers for Disease Control and Prevention (CDC) 2000 age- and sex-specific BMI percentile growth charts. We also aimed to examine the utility of a new modified CDC BMI z score chart to monitor growth in children with normal and extreme BMI percentiles by using real-life clinical scenarios. METHODS: Modified BMI z score charts were created by using the 2000 CDC algorithm. Three cases of children with extreme BMI values and abnormal growth patterns were plotted by using the standard CDC 2000 clinical growth chart, the modified BMI z score chart, and the CDC BMI percentile chart, modified to include the percentage of the 95th percentile (%BMIp95) curves. RESULTS:Children with severe obesity could not be plotted on the standard CDC BMI percentile chart because their BMI points lay above the chart cutoff. Children with a low BMI (<3%) were also difficult to track on the standard BMI percentile chart. The addition of the %BMIp95 scale to the standard BMI percentile chart allowed tracking of severely obesechildren; however, it did not address severely underweight children and required a change of units within the chart when transitioning from normal to obese BMIs. The modified BMI z score chart allowed uniform tracking. CONCLUSIONS: The modified CDC z score chart is suitable for growth tracking of children with normal and extreme growth patterns; the measures correlate well with the %BMIp95, and the chart can be incorporated easily into existing electronic health record systems for clinical use.
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