Background: Body mass index (BMI) is widely used as a proxy of nutritional status
and related lifestyle risk patterns in public health, yet it does not capture body
composition–related heterogeneity in cardiometabolic risk. Evidence on whether a more
detailed body composition assessment improves population-level screening efficiency
remains inconsistent, particularly in Central European populations. Methods: We conducted
a cross-sectional analysis of 868 Hungarian adults participating in a nationwide mobile
screening program. Locally weighted regression identified sex-specific BMI inflection
points for cardiometabolic risk. Stratified receiver operating characteristic (ROC)
analyses compared BMI with bioelectrical impedance-derived parameters across five
outcomes. Cost- and time-effectiveness of scalable screening strategies were modeled
at the population level. Results: Cardiometabolic risk increased at BMI levels below
current WHO thresholds (females: 21.8–22.3 kg/m2; males: 23.8–24.3 kg/m2). Overall,
body composition parameters did not outperform BMI in the full population. Subgroup-specific
differences were observed, particularly among men with BMI 24–36 kg/m2 for atherosclerosis
risk, suggesting limited and outcome-specific added value rather than broad superiority
over BMI. Together, non-linear risk patterns, stratified performance, and population-level
modeling converged on mid-range BMI intervals (females: 22–30 kg/m2; males: 24–30
kg/m2) as likely screening windows of phenotypic heterogeneity. Within these ranges,
targeted InBody assessment may help refine risk assessment for selected individuals.
A mixed screening strategy covering 52% of the population would cost 178.4% of BMI-only
screening, while reducing throughput by 24.3%. Conclusions: Population-specific BMI
thresholds may more accurately reflect early deviations in nutritional and cardiometabolic
risk than current universal cutoffs. BMI remains a useful first-line marker, and body
composition assessment may add complementary information in selected BMI ranges. Overall,
these findings support a potentially useful, subgroup-specific screening approach,
but the modeled cost and time trade-offs should be considered hypothesis-generating
and require further validation.
