The relationship between air pollutants and preterm birth and blood routine changes in typical river valley city.

OBJECTIVE: To collect maternal maternity information on preterm births in two tertiary hospitals in the urban area of Baota District, Yan'an City, from January 2018 to December 2020, to explore the long-term and short-term effects of air pollutants (PM2.5, PM10, SO2, NO2, CO and O3) and preterm births, and to explore changes in blood cell counts due to air pollutants. METHODS: Daily average mass concentration data of six air pollutants in the urban area of Yan'an City from January 1, 2017 to December 31, 2020 were collected from the monitoring station in Baota District, Yan'an City. Meteorological information was obtained from the Meteorological Bureau of Yan'an City, including temperature,relative humidity and wind speed for the time period. The mass concentration of air pollutants in each exposure window of pregnant women was assessed by the nearest monitoring station method, and conditional logistic regression was used to analyze the relationship between air pollutants and preterm births, as well as the lagged and cumulative effects of air pollutants. Multiple linear regression was used to explore the relationship between air pollutants and blood tests after stepwise linear regression was used to determine confounders for each blood test. RESULTS: The long-term effects of pollutants showed that PM2.5, PM10, SO2, NO2and CO were risk factors for preterm birth. In the two-pollutant model, PM2.5, PM10, SO2 and NO2 mixed with other pollutants were associated with preterm birth. The lagged effect showed that PM2.5, PM10, SO2, NO, and CO were associated with preterm birth; the cumulative effect showed that other air pollutants except O3 were associated with preterm birth. The correlation study between air pollutants and blood indicators showed that air pollutants were correlated with leukocytes, monocytes, basophils, erythrocytes, hs-CRPand not with CRP. CONCLUSION: Exposure to air pollutants is a risk factor for preterm birth. Exposure to air pollutants was associated with changes in leukocytes, monocytes, basophils and erythrocytes and hs-CRP.

Relationship between air pollutants and spontaneous abortion in a coal resource valley city: a retrospective cohort study.

OBJECTIVE: Pollutants in the atmosphere have been linked to poor pregnancy outcomes in women. However, such investigations are scarce in metropolitan northern China. The major exposure window of air pollution affecting pregnant women is also unknown. METHODS: For the analysis, this retrospective cohort study enrolled 6960 pregnant women recorded at Tongchuan People's Hospital from January 2018 to December 2019. Pollutant concentration values from the nearest monitoring station to the pregnant women were used to estimate exposure doses for each exposure window. Logistic regression models were created to investigate the connection between pollutants and spontaneous abortion while controlling for confounding factors. RESULTS: PM2.5 was a risk factor for spontaneous abortion in T3 (30-60 days before the first day of the last menstrual period [LMP]), (OR: 1.305, 95% CI: 1.143-1.490) and T4 (60-90 days before the first day of the LMP),(OR: 1.450, 95% CI: 1.239-1.696) after controlling for covariates. In the same window, PM10 was a risk factor (OR: 1.308, 95% CI: 1.140-1.500), (OR: 1.386, 95% CI: 1.184-1.621). In T2 (30 days before the first day of the LMP), T3, and T4, SO2 was a risk factor for spontaneous abortion (OR: 1.185, 95% CI: 1.025-1.371), (OR: 1.219, 95% CI: 1.071-1.396), (OR: 1.202, 95% CI: 1.040-1.389). In T3 and T4, NO2 was a risk factor (OR: 1.171, 95% CI: 1.019- 1.346), (OR: 1.443, 95% CI: 1.259-1.655). In T1 (from the first day of the LMP to the date of abortion), O3 was found to be a risk factor (OR: 1.366, 95% CI: 1.226-1.521). CONCLUSION: Exposure to high levels of air pollutants before and during pregnancy may be a risk factor for spontaneous abortion in pregnant women. This study further illustrates the importance of reducing air pollution emissions.

Relationship of Red Cell Index with the Severity of Chronic Obstructive Pulmonary Disease.

BACKGROUND: We aimed to investigate the association between red cell index (RCI) and the severity of Chronic Obstructive Pulmonary Disease (COPD), and compare predictive value of RCI, neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) for the severity of COPD. METHODS: A total of 207 participants were recruited (100 COPD patients and 107 healthy controls). COPD patients were divided into two groups according to the optimal cut-off value of RCI determined by the receiver operating characteristic (ROC) curve. Pearson's correlation test, logistic regression analysis and other tests were performed. RESULTS: Compared with low RCI group, the forced expiration volume in 1 second (FEV1) and FEV1 in percent of the predicted value (FEV1%) in high RCI group were lower (p = 0.016, p = 0.001). There was a negative correlation between RCI and FEV1% (r = -0.302, p = 0.004), while no correlation between FEV1% and NLR as well as PLR were found. RCI showed higher predictive value than NLR and PLR for predicting Global Initiative for Chronic Obstructive Lung Disease classification (GOLD), with a cut-off value of 1.75 and area under the curve (AUC) of 0.729 (p = 0.001). Multivariate logistic regression analysis proved that RCI was an independent factor for lung function in COPD patients (odds ratio [OR] = 4.27, 95% CI: 1.57-11.63, p = 0.004). CONCLUSION: RCI is a novel biomarker that can better assess pulmonary function and severity of COPD than NLR and PLR. Higher RCI is related to deterioration of pulmonary function.