Via Research Recognition Day 2024 VCOM-Carolinas

Educational Reports

Comparing Obesity Screening Measures in an Active Pediatric Population in Spartanburg County Mariam Aamir OMS-II, Elias Bouyounes OMS-II, Nathan Eisel OMS-II, Maheen Farooq OMS-II, Dema Hamed OMS-II, Haylie Smith OMS-II, Kaleigh Wingler OMS-II, Jamie Brown MD, Alexis M. Stoner PhD, MPH, David Redden PhD Edward Via College of Osteopathic Medicine - Carolinas, Spartanburg, S.C.

Conclusions

Introduction

Results

Figure 1. BMI Classification categorized into underweight, healthy weight, overweight, and obese.

Figure 2.Waist circumference to height ratio categorized into Not Obese and Obese

Spartanburg County, SC has numerous health issues that can be easily prevented. Prior research on the illnesses prevalent in the Spartanburg community has shown that deaths can largely be contributed to heart disease and cancer, which are known to be associated with obesity. Research in the community has shown high rates of pediatric obesity as well. The current body of research has been focused on measuring obesity with BMI measurements. Waist circumference to height ratio is an under-researched alternative method that is considered a good parameter for visceral fat and a marker for conditions that come with central adiposity. Waist circumference to height ratio as a measure of pediatric obesity is not a standard clinical practice.As such, we sought to compare the categorization of obesity in a Spartanburg county pediatric population using BMI and waist circumference to height ratio (WCtHR). • Standardized sport physicals data was collected at two Spartanburg County back to school events and four health screening events at Meeting StreetAcademy. • Data analysis was focused on descriptive statistics using a convenience sample. Inclusion criteria comprised any child at the event that was willing to participate in the study and was currently living in Spartanburg, SC. • A total of 392 children (aged 3-19) were assessed in their weight, waist circumference, and height measurements. • The results were categorized through gender, age, height, weight, waist circumference, and physical activity status. • BMI and waist circumference-to-height ratio were calculated using RStudio, while BMI percentiles were determined using the R package "cdcanthro." • The physical activity levels were categorized into varying degrees of activity status, ranging from 0-3. • 0: no physical activity status. • 1: involvement in one sport or one activity at home. • 2: involvement in 2 sports. • 3: involvement in 3 or more sports. • BMI classification was based on calculated percentile scores for a participant's age and sex according to the CDC 4 and waist circumference to height ratio classification was based on a cutoff of 0.49 according to Eslami, et. Al 3 . • For data analysis, a statistician summarized general demographics data on the 392 subjects. • The sample mean and standard deviation were also calculated to analyze continuous measures including BMI and waist circumference to height ratio. • Cohen's kappa statistic was used to measure agreement in obesity classification based on BMI and waist circumference to height ratio. • Kappa results be interpreted as follows: values ≤ 0 as indicating no agreement and 0.01-0.20 as none to slight, 0.21-0.40 as fair, 0.41-0.60 as moderate, 0.61 0.80 as substantial, and 0.81-1.00 as almost perfect agreement 5 . • We calculated the kappa at each activity level to and conducted a formal hypothesis, and this process was repeated for age and gender. • Analyses were performed using SAS 9.4. Methods

Given the discrepancies, comparing categorization of children as obese or non-obese by both measurements is important to determine the best method of diagnosing childhood obesity. We found that there is moderate agreement in establishment of obesity using either of these measurement methods, which goes against our hypothesis that there would be perfect agreement between the two. However, the agreement varies depending on age and activity level. Due to this, both measurements used together could increase sensitivity in the measurement of obesity. • No significant evidence that agreement varies by gender was found • The activity level status of 3 or more sports having a high level of agreement indicates a strong association between the two measurement methods. • Age levels of 3-6 and 15-19 showed low levels of agreement, indicating that more than one measurement method for measuring obesity status may be needed. • In children with lower activity levels and a category discrepancy, WCtHR categorized more children as obese compared to BMI. In children with higher activity levels, BMI categorized more children as unhealthy weight. • Limitation: The BMI screening tool for obesity includes an overweight category that is not found in waist circumference to height ratio obesity screenings. • Further research includes expanding sample size, diversification of population for BMI and waist circumference comparison. Additionally, the investigation of age groups 3-6 and 15-19 for low agreement levels to see if growth spurts and other effects of puberty potentially affect agreement level. Longitudinal study can also be conducted on pediatric patients to correlate childhood obesity with adult health outcomes. Discrepancies between BMI and WCtHR in screening for obesity in pediatric populations should raise a concern for continuing the traditional use of only BMI. Harm can be done to a child if they are wrongfully categorized as obese and therefore more consideration should be given to possibly utilizing both screening tools to deliver proper counseling and care depending on age and activity level.

Among the 392 subjects, 52.81% are female and 47.19% are male. 34.95% of the participants are 3-6 years old, 42.86% are 7-10 years old, 17.60% are 11-14 years old, and 4.59% are 15-19 years old. According to the BMI classification, 73.98% of the participants are classified as not obese, and 26.02% of the participants are classified as obese. As for the waist circumference to height ratio classification, 58.16% are classified as not obese, and 41.84% are classified as obese.

Table 1. Agreement between Classification Methods Controlling for Activity Level

BMI and WCtHR have a statistically strong agreement about the classification of obesity when the children play more than 3 sports . They have a moderate agreement in all other classifications and overall. The overall difference in agreement between the two measurements was not found to be significant.

Table 2. Agreement between Classification Methods Controlling for Age

BMI and WCtHR have an almost perfect agreement about the classification of obesity when the age group is 11 – 14-year-old. They have substantial agreement from the age group 7-10 and have a low level of agreement for the other 2 groups. They have a moderate agreement in all other classifications and overall. The difference in agreement between the two measurements is significant.

References

Table 3. Obesity Discrepancy by Activity Level and Measurement Tool

Categorization of obesity status discrepancies was found in 116 participants. BMI categorized more participants as healthy weight with a low activity level, andWCtHRcategorized more participants as not obese with a high activity level.

Edward Via College of Osteopathic Medicine Institutional Review Board, Blacksburg, VA, Record # 2023-058, Approval Date 08/03/2023. We would like to acknowledge Dr. Hanna Sahhar, Dr. Lisa Carroll, and Dr. Ronald Januchowski for their guidance and assistance and Yasmine Sanhaji OMS-II.

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2024 Research Recognition Day