Is body mass index related to function in individuals with cerebral palsy?

Is body mass index related to function in individuals with cerebral palsy?
DJ OEFFINGER PHD1, MJ GURKA PHD2, RD STEVENSON MD2, CM TYLKOWSKI MD1
1 Shriners Hospitals for Children, Lexington, Lexington, KY;
2 School of Medicine, University of Virginia, Charlottesville, VA, USA

Background/Objectives: How body composition affects functional abilities of individuals with cerebral palsy (CP) has not been thoroughly investigated. Body Mass Index (BMI) is a commonly used method for estimating body composition. Our objectives were to establish the relationship between BMI and function in ambulatory children with CP and to determine if the relationships between BMI and function vary by GMFCS level.
Design: Multi-center, prospective cohorts study.
Participants and Setting: 557 (336 males, 221 females) ambulatory children with CP (N=230 GMFCS Level I, 182 level II, 119 level III); Diplegia (366), Hemiplegia (162), Quadriplegia (29); participated from 7 pediatric orthopedic facilities. Mean age was 11.1 ± 3.5 years (range 4-18 years).
Materials/Methods: BMI values were calculated from height and weight measurements and converted to z-scores (CDC normal reference) and evaluated by GMFCS level, CP type and gender. Linear regression was utilized to assess the relationship between BMI z-score and each of the outcome measures: GMFM, PODCI, PedsQL, WeeFIM, and temporal-spatial gait data. Linear, quadratic, and cubic relationships were assessed for those with significant findings. To examine if the relationships were different based on GMFCS level, interactions between BMI z-score and GMFCS were assessed for each linear model of all outcome measures. R2 values are reported and are the proportion of the variability of the outcome score that can be explained by BMI z-score.
Results: GMFCS level and CP type were not significantly associated with BMI z-score. There were no significant relationships between BMI z-score and GMFM-66 (Figure GIA), GMFM E; WeeFMI Mobility; PedsQL Social, School; PODCI Transfers & Mobility, Physical Function, Expectations or velocity and stride length. Statistically significant (P<0.05) relationships were found for BMI z-score and GMFM D (R2=0.0008), WeeFIM Self-care (R2=0.012), Cognition (R2=0.030); PedsQL Physical (R2=0.011); PODCI Global Functioning (R2=0.012) (Figure G1B), Upper extremity (R2=0.014), Comfort/Pain (R2=0.010), and Happiness (R2=0.010). There were no significant interactions between BMI z-score and GMFCS for any linear model of any of the study outcome tools.
Conclusions/Significance: BMI is not related to function as measured by the studied outcome tools. Due to the large sample size, statistical significance was found for some tools; however, the relationships were very weak with no more than 3% of the variance explained by BMI. While BMI alone is not related to function, changes in BMI may be more strongly related to changes in function. This relationship is currently being investigated.

 
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