Nutrients, Vol. 18, Pages 1410: Optimizing Public Health Screening: Population-Specific BMI Thresholds for Targeted Body Composition Assessment in Hungary
Nutrients doi: 10.3390/nu18091410
Authors:
Tamas Jarecsny
Nadim Al-Muhanna
Dora Rebeka Fabian
Roland Kosik
Richard Schwab
Gergo Jozsef Szollosi
Laszlo Schandl
Gyula Tomasics
Eszter Melinda Pazmandi
Andras Folyovich
Ferenc Fazekas
Monika Fekete
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.
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. Read More