Probabilistic dietary exposure modeling and health risk assessment of heavy metals via the fodder-cattle-human continuum in Bangladesh

Dietary exposure to heavy metals (HMs) via animal-source foods is a critical environmental health pathway. In rapidly industrializing Bangladesh, contamination of the bovine food chain from agricultural feeds and industrial emissions poses an unquantified public health burden. This study evaluated exposure pathways, spatial distribution, mass-transfer dynamics, and health risks of six HMs (Cr, Cu, Cd, Pb, As, and Hg) across the fodder-cattle-human continuum. Samples of beef (n = 76), raw milk (n = 76), commercial cattle feed (n = 40), and fodder (n = 88) were collected from eight sites across industrial and non-industrial zones in Bangladesh and analysed by atomic absorption spectroscopy. Probabilistic Monte Carlo simulations (10,000 iterations) quantified estimated daily intake, target hazard quotients (THQ), cumulative hazard index (HI), and lifetime carcinogenic risk (CR) for adult and pediatric receptors. Copper (Cu) was the dominant contaminant across all matrices, peaking in beef (103.89 {+/-} 15.87 mg/kg) and milk (13.67 {+/-} 1.53 mg/L). Spatial analysis revealed distinct contamination profiles: Pb burden peaked in industrial zones while Cr was elevated in non-industrial sectors. Monte Carlo modelling identified commercial feed as the most efficient transfer vector into beef. Pediatric THQ for Cu significantly exceeded the safety threshold (THQ > 1), and upper-bound lifetime carcinogenic risk from As approached the critical USEPA 10-4 regulatory ceiling. These findings demonstrate that industrial and agricultural externalities efficiently contaminate the bovine food supply chain in Bangladesh, with copper and arsenic representing the most critical non-carcinogenic and carcinogenic dietary hazards, respectively. Children are disproportionately vulnerable due to lower body weight. The results underscore the need for targeted upstream interventions in commercial feed production and provide evidence to support feed-quality regulation and environmental monitoring in rapidly industrializing settings.