Poster Presentation ESA-SRB-ANZOS 2025 in conjunction with ENSA

Should we be worried about normal weight obesity in people with cystic fibrosis (129093)

Shanal Kumar 1 2 , Felicity Loel 1 , Angela Matson 1
  1. Adult Cystic Fibrosis Centre, The Prince Charles Hospital, Brisbane, QLD
  2. School of Medicine, University of Queensland, QLD

Aims
People with cystic fibrosis (pwCF) are increasingly at risk of overweight and obesity. The traditional measure of body mass index (BMI) used to commonly define overweight and obesity is crude and there is interest in more sensitive analytics comprising body composition. This study aimed to i) validate bioelectrical impedance assessment (BIA) against clinical standard dual X-ray absorptiometry (DXA) for body composition and ii) compare prevalence of obesity diagnosis based on body composition versus BMI cut-points in pwCF.

Methods
Our adult CF centre at The Prince Charles Hospital used a dual-frequency Tanita BIA machine for body composition in pwCF, with DXA performed contemporaneously for validation (HREC EX/2024/MNHB/110279). BIA validation was defined by a correlation coefficient >0.70. BIA was offered to pwCF attending routine face-to-face outpatient CF clinics across a calendar month where body composition parameters including weight, fat mass and percentage, lean mass, and bone mineral content were collected. General and age- and gender-specific cut-points for BIA-derived body fat percentage were then compared to BMI cut-points.

Results
Eight pwCF (3 females) underwent contemporaneous BIA and DXA analyses. Pearson correlation coefficients for weight (0.99), fat mass (0.94), and muscle mass (0.92) were very high, while bone mass showed moderate correlation (0.68).

Our cross-sectional analyses comprised 15 pwCF (5 females), of whom 80% were on Elexacaftor/Tezacaftor/Ivacaftor and 46% had CF-related diabetes with a mean BMI of 26.4 kg/m². The mean±SD body fat percentage was 33.2%±7.0 in females and 24.5%±6.9 in males. Age and gender-specific body composition cut-points for obesity were met by 73%, in contrast to only 26% using traditional BMI cut-points.

Conclusion
BIA showed strong correlation with DXA for body fat and lean mass in pwCF. Body composition analysis might be more sensitive than BMI for detection of ‘normal weight’ obesity, the prevalence of which might be high in pwCF.