Establishing quality management system for biomonitoring laboratory network: based on element internal exposures in
Haocan Song1, Tian Qiu1, Yuebin Lv1
1China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Objective:
To build a multi-center laboratory network in the China National Human Biomonitoring (CNHBM) program and deliver high-quality datasets supporting national human biomonitoring exposure assessment and public health policy-making.
Methods:
A systematic Quality Management System (QMS) framework was established, encompassing laboratory network building, standardized policies, resource allocation, and a rigorous Quality Evaluation System (QES). Applicant laboratories underwent interlaboratory comparison investigations (ICI) using identical test samples. Certified network laboratories implemented strict standard operating procedures, analyzed reference materials and program-specific blinded Quality Control (QC) pools, and performed incurred sample reanalysis throughout the analytical process.
Results:
Through ICI, four laboratories were certified for heavy metals and metalloids (HMMs) analysis. Throughout the measurement of 21,701 blood and 21,704 urine samples, internal quality control (IQC) demonstrated high precision (CV% generally <15%, >80% within the reference range), and the median relative percentage difference (RPD) in sample reanalysis was below 5%. External quality control (EQC) using CNHBM-specific QC pools confirmed excellent inter-laboratory comparability, with overall coefficients of variation for key HMMs maintained below 15%.
Conclusion:
This study presents the first successful implementation of an integrated QMS framework for a national biomonitoring program in China. The framework effectively harmonized multi-laboratory data production, yielding a high-quality, unified national dataset for exposure assessment and public health policy-making, and provides a replicable model for large-scale environmental health surveillance initiatives.
