Abstract:
BACKGROUND: Screening for traditional risk factors of cardiovascular disease is well known
in primary healthcare (PHC) settings. However, other risk factors through newer tools
(such as bioelectrical impedance analysis [BIA]) could also be predictors of increased
cardiovascular risk (CVR). Body composition estimates (body fat percentage, body water
percentage, body lean mass) by BIA and its association to CVR have been studied with
variable results.
AIM: This study assesses the body composition estimates and their association with CVR
in the South African PHC setting.
METHODS: A retrospective record analysis was conducted on a cohort of de-identified
patients utilising the ABBY® Health Check Machine at a PHC facility in South Africa between
May 2020 and August 2022. The ABBY Machine estimates body fat percentage (BF%) and
body water percentage (BW%) estimates from BIA. Cardiovascular risk based on the
Framingham-risk-score was stratified into high, medium and low CVR. An analysis of
variance was used to determine mean differences of BF% and BW% among these groups.
RESULTS: A total of 4008 records (n = 4008) were used in the final analysis. The majority of
patients were female (70.1%) with a mean age of 33.6 years. Higher mean BF% (35.75% vs.
31.10% vs. 27.73%; p < 0.0001) and lower mean BW% (49.46% vs. 53.15% vs. 56.18%; p = 0000)
were found to be significantly associated with high CVR.
LESSONS LEARNT: This study demonstrated the use of newer technologies that could assist
in the identification of CVR in low resource PHC settings.
