Three Exposure Metrics for Fine Particulate Matter Associated With Outpatient Visits for Acute Lower Respiratory Infection Among Children in Guangzhou, China.

Ambient fine particulate matter (PM2.5) is associated with an elevated risk of acute lower respiratory infections (ALRI). However, this association has not been examined using alternative exposure metrics. We collected outpatient data of patients with ALRI aged <14 years from the administrative database of a large tertiary hospital in Guangzhou, China, from 2013 to 2019. Ambient PM2.5 was measured using three metrics: (a) daily mean, (b) daily excessive concentration hours (DECH), and (c) hourly peak. Generalized additive models were fitted to estimate the excess risk (ER) associated with PM2.5. A total of 105,639 ALRI (35,310 pneumonia and 68,218 bronchiolitis) outpatient visits were identified during the study period. An interquartile range increment in PM2.5 DECH was consistently associated with the highest ER of ALRI-related outpatient visits: 12.30% (95% confidence interval [CI]: 9.49-15.18%), compared with 11.20% (95% CI: 8.34-14.13%) for daily mean and 9.73% (95% CI: 6.97-12.55%) for hourly peak. The associations between the three metrics of PM2.5 and ALRI-related outpatient visits were stronger in the cold season than in the warm season. Future studies should consider PM2.5 DECH as an alternative method of exposure measurement, in addition to daily mean and hourly peak concentrations of PM2.5.

Three exposure metrics of size-specific particulate matter associated with acute lower respiratory infection hospitalization in children: A multi-city time-series analysis in China.

BACKGROUND: The global burden of acute lower respiratory infection (ALRI) attributable to air pollution has increased in recent years, but the association between ALRI and exposure to size-specific particulate matter has not been investigated using different exposure metrics. METHODS: We obtained ALRI admission from seven cities from 2014 to 2016 in China. Different sized particles were measured using three metrics (a) daily mean, (b) hourly peak, and (c) daily excessive concentration hours (DECH). Generalized additive models were fitted for each of the seven cities, and the city-specific estimates were then pooled using random-effects meta-analysis models. Stratified analyses were conducted to examine the effect modifications of gender, age, and season. We also estimated the disease burden due to particulate matter exposures. RESULTS: There were 111,426 ALRI (79,803 pneumonia and 31,622 bronchiolitis) hospital admissions under the age of 15 between 2014 and 2016 in our study. Daily means were associated with the largest ALRI estimates (95% confidence interval [CI]): 2.43% (0.79%, 4.11%) for PM2.5, 2.25% (0.11%, 4.44%) for PMc, and 2.64% (0.73%, 4.58%) for PM10. The magnitude of effect sizes were followed by DECH: 1.94% (0.51%, 3.39%) for PM2.5, 0.88% (-0.14%, 1.92%) for PMc, 1.86% (0.50%, 2.01%) for PM10; and hourly peak: 0.70% (-0.60%, 2.01%) for PM2.5, 1.05% (-0.13%, 2.66%) for PMc, and 1.20% (-0.20%, 2.62%) for PM10 at lag03. We found significantly higher effects in cold seasons than that in warm seasons, while we did not find a significant different between gender and age groups. CONCLUSIONS: The adverse effects of exposure to particulate matter on ALRI hospitalizations are reconfirmed. DECH was a possible alternative exposure indicator for PM2.5 assessment, which may affect air quality standards in the future.

SAA and CRP are potential indicators in distinction and severity assessment for children with influenza.

PURPOSE: The clinical values of C-reactive protein (CRP) and serum amyloid A (SAA) to distinguish non-severe from severe influenza in children are rarely reported. METHODS: Baseline characteristics and laboratory results were collected and analyzed. Receiver operating characteristic (ROC) curve analysis was used for combined detection of indicators for children with influenza, and scatter-dot plots were used to compare the differences between non-severe and severe influenza. RESULTS: Children with influenza B had more bronchitis and pneumonia (P < 0.05) and children with influenza A had more other serious symptoms (P = 0.015). Lymphocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), CRP, and SAA performed differently among children with influenza A and B. Joint detection of SAA and other indicators could better separate healthy children from children with influenza than single indicator detection. The CRP and SAA levels of children with severe influenza B infection and SAA levels of children with severe influenza A infection were significantly elevated compared with children with non-severe influenza (P < 0.05). CONCLUSIONS: SAA and CRP could be potential indicators in distinction and severity assessment for children with influenza; however, age should be taken into account when using them in children with influenza B.