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Association between fine particle exposure and common test items in clinical laboratory: A time-series analysis in
Zhonghua Deng1, Chaochao Tan2, Yangen Xiang3
1Department of Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha 410013, PR China; Department of Laboratory Medicine, Xiangya School of Medicine, Central South University, Changsha 410013, PR China; Department of Medical Laboratory, Hunan Provincial People's Hospital, Changsha 410005, PR China; Department of Medical Laboratory, The First Affiliated Hospital of Hunan Normal University, Changsha 410005, PR China.
Abstract:
Most studies on the health effects of PM2.5 (fine particulate matter with diameter smaller than 2.5 μm) use indirect indicators, such as mortality and number of hospital visits. Recent research shows that biomarkers can also be used to evaluate the health effects of PM2.5; however, these biomarkers are not very common. Clinical laboratories can provide a significant amount of test data that have been proven to have important diagnostic value. Therefore, we use big data analysis methods to find the associations between clinical laboratory common test items and PM2.5 exposure. Data related to air pollution and meteorological information between 2014 and 2016 were obtained from the China National Environmental Monitoring Centre and the China National Meteorological Information Center. Additionally, data of 27 common test items from the same period were collected from Changsha Central Hospital. Primary analyses included a generalized additive model to analyze the associations between PM2.5 concentration and common test items; the model was adjusted for time trends, weather conditions (temperature and humidity), and days of the week. Furthermore, we adjusted the effects of other air pollutants, such as PM10, SO2, NO2, CO, and O3. 17 items such as TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, LDL, WBC, K, Cl, Ca, TT, and FIB were significantly positively associated with PM2.5 concentration (P< 0.05) and have concentration-response relationship. After adjusting the effect of PM10+SO2+NO2+CO+O3, TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, WBC, Cl, and Ca were still significantly associated with PM2.5 concentration (P< 0.05). This current study suggested that clinical laboratory common test items may be used to assess and predict the health effects of PM2.5 on the population.
Insights
Clinical lab tests can help assess health effects from fine particulate matter (PM2.5) exposure. This study found significant associations between common blood test results and PM2.5 levels.
Area of Science:
- Environmental Health Science
- Clinical Biochemistry
- Big Data Analytics in Public Health
Background:
- Traditional health effect assessments for fine particulate matter (PM2.5) rely on indirect indicators like mortality and hospital visits.
- Biomarkers offer a more direct method for evaluating PM2.5 health impacts, but common biomarkers are not widely utilized.
- Clinical laboratory tests generate extensive data with significant diagnostic value, presenting an opportunity for novel health effect assessments.
Purpose of the Study:
- To investigate the associations between common clinical laboratory test items and exposure to fine particulate matter (PM2.5) using big data analysis.
- To explore the potential of routine clinical laboratory data for assessing and predicting population health effects related to PM2.5.
Main Methods:
- Utilized big data analysis on air pollution, meteorological data (2014-2016, China), and 27 common clinical laboratory test results from Changsha Central Hospital.
- Employed a generalized additive model to analyze PM2.5 concentration associations with test items, adjusting for time trends, weather, day of the week, and other air pollutants (PM10, SO2, NO2, CO, O3).
- Assessed concentration-response relationships for significant associations.
Main Results:
- 17 common clinical test items showed significant positive associations with PM2.5 concentration, including TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, LDL, WBC, K, Cl, Ca, TT, and FIB (P < 0.05).
- Even after adjusting for other major air pollutants, 14 items (TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, WBC, Cl, Ca) remained significantly associated with PM2.5 (P < 0.05).
- Demonstrated concentration-response relationships between PM2.5 levels and these clinical laboratory markers.
Conclusions:
- Commonly measured clinical laboratory test items can serve as valuable indicators for assessing the health effects of PM2.5 exposure.
- These laboratory test results may be utilized to predict population-level health impacts associated with fine particulate matter pollution.
- Highlights the potential of integrating clinical laboratory data with environmental monitoring for enhanced public health surveillance.
