Childhood asthma management has long focused on triggers like allergens and air quality, but the metabolic architecture of the body itself may be an underappreciated driver — one that a simple geometric ratio could help quantify at scale. Understanding which adiposity measures best predict asthma risk in children has real implications for early screening and preventive care strategies.
Drawing on nearly 29,000 participants from the long-running NHANES dataset spanning 1999 to 2020 and aged 6 to 20 years, this analysis examined the Body Roundness Index (BRI) — a composite derived from waist circumference and standing height — as a predictor of current asthma status. After multivariable adjustment, each unit increase in BRI was associated with 23.3% higher odds of asthma (OR = 1.233, 95% CI: 1.158–1.313). Restricted cubic spline modeling further revealed that this relationship is nonlinear, suggesting the risk accelerates at higher BRI values rather than increasing uniformly. ROC comparisons found BRI and BMI z-score performed similarly in discriminating asthma cases.
BRI is gaining traction as an accessible proxy for central adiposity — visceral fat distribution — which is mechanistically more relevant to systemic inflammation than overall body size. Adipose tissue, particularly abdominal fat, secretes pro-inflammatory cytokines including IL-6 and TNF-α that can heighten airway hyperresponsiveness. BMI, the traditional gold standard, conflates lean mass with fat mass and ignores fat distribution entirely. That BRI performed comparably to BMI z-score here is a meaningful finding: it validates BRI as a feasible alternative but stops short of demonstrating superiority.
The study's strengths include its large, nationally representative sample and two decades of data. Key limitations include reliance on questionnaire-based asthma diagnosis, cross-sectional design precluding causal inference, and the inability to distinguish asthma phenotypes. This is largely confirmatory work within an active research area, but the nonlinear dose-response curve is a clinically noteworthy detail deserving prospective follow-up.