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Real-time monitoring of formaldehyde exposure and acute health symptoms in healthcare workers in Morocco: a cross-sectional study

Aug 2026 · Cadernos de Saúde Pública · Vol 42 · 0 citations · 34 references
Medicine

TL;DR

Despite the cross-sectional design, formaldehyde exposure was strongly associated with acute symptoms even at sub-threshold concentrations, suggesting current limits may not fully protect workers.

Abstract

Abstract: Formaldehyde remains widely used in clinical and dental procedures, particularly in low- and middle-income countries with limited regulatory oversight, where occupational exposure data remain scarce. This cross-sectional study evaluated real-time formaldehyde exposure and its association with acute health symptoms among 180 healthcare workers in Morocco. Airborne formaldehyde was measured across 12 hospital departments during eight-hour shifts using a calibrated semiconductor dosimeter, alongside a structured symptom questionnaire. Associations were assessed using multivariate logistic regression and Spearman’s correlation. All mean concentrations remained below the Moroccan occupational limit of 0.25mg/m3 (range: 0.048-0.196mg/m3; 19-78% of the limit). Nevertheless, highly exposed workers reported significantly more symptoms, including eye irritation (72.5%), headaches (63%), and respiratory discomfort (56.5%). Prolonged exposure (≥ 8 hours/day, ≥ 3 days/week) independently predicted multiple symptoms (AOR = 3.2; 95%CI: 1.7-5.9), as did inadequate ventilation (AOR = 2.4) and inconsistent PPE use (AOR = 1.9). Years of exposure correlated moderately with symptom count (ρ = 0.41; p < 0.01). Despite the cross-sectional design, formaldehyde exposure was strongly associated with acute symptoms even at sub-threshold concentrations, suggesting current limits may not fully protect workers. Strengthening preventive measures is essential in resource-limited settings. These findings support integrated exposure-surveillance approaches in low- and middle-income countries. Longitudinal studies with biomarkers are needed to refine causal inference and inform policy.

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