Systematic review of the health risks of waste related heavy metals and toxic chemicals among vulnerable populations in low- and middle-income countries
In developing countries, poor waste management causes widespread heavy metal and toxic chemical contamination, threatening vulnerable populations. This systematic review of the health risks of waste-related heavy metals and toxic chemicals among vulnerable populations in low- and middle-income (LMICs) countries synthesizes multifaceted exposure pathways, clinical biomarker data, and localized risk thresholds. PubMed, Scopus, ScienceDirect, and ProQuest databases were searched for peer-reviewed studies published in English between 2012 and 2025. Out of the 731 records identified, two independent reviewers extracted data and appraised the quality of 21 eligible studies using Joanna Briggs Institute (JBI) Critical Appraisal Checklist, with initial variances successfully resolved via a formal consensus protocol. Primary contaminants identified were Pb, Cd, Cr, As, Hg, and Ni. Exposure pathways included soil and dust ingestion, inhalation of contaminated emissions, dermal absorption, occupational contact. Pediatric cohorts face extreme risks through ingestion and inhalation; mean blood lead reached 60.43 µg/L, breaching the World Health Organization 50 µg/L threshold, and correlated with a Full-Scale IQ decline (β= − 18.42, p < 0.05). Risk modeling showed pediatric non-carcinogenic vulnerabilities exceeded the US EPA Hazard Index baseline of 1.0 (e.g., Mn HI = 1.69), while total carcinogenic risk reached concerning level (10–5). Occupational biomarkers tracked hair mercury up to 10.8 mg/kg in miners and mean blood cyanide at 400 µg/L. Toxic waste exposures drive severe, unequal neurological, renal, hepatic, and carcinogenic burdens across LMICs. Mitigating these risks requires operationalized policies including enforcement of the Basel convention, mandatory provision of N95/P100 respirators and nitrile gloves, annual blood lead screenings, and formalizing labor contracts via Extended Producer Responsibility models.