Name
Title | ||
|---|---|---|
Identifying and characterizing the effects of calendar and environmental conditions on pediatric admissions in Shanghai. |
Abstract | ||
|---|---|---|
Global environmental pollution caused by human activities has become a threat to public health. Children are especially susceptible to adverse environmental conditions owing to their unique physiological and behavioral characteristics. A number of studies have demonstrated associations between the incidence of some childhood diseases and adverse environmental conditions. Shanghai is the largest and most important economic center in China. After rapid population expansion in recent decades, the shortage of pediatric medical resources is becoming a serious public health problem. This study aimed to identify and characterize the social and environmental effect of adverse environmental conditions on overall pediatric admissions at hospitals in Shanghai, China. This was a multi-center study spanning from January, 2013 to November, 2014. Daily pediatric admission data (~ 12,000 overall pediatric admissions/day) of three tertiary pediatric hospitals were collected from the large-scale health information exchange network of Shanghai. We linked the admission data with local environmental data. A seasonal decomposition method was applied to a time-trend analysis of the admission data; a generalized additive model was applied to model the association between environmental measurements and admissions data. Admissions to outpatient and emergency departments were highly influenced by calendar factors; however, these same factors showed opposite effects on different clinical departments. The effect of nitrogen dioxide was a 0.27% increase (95% confidence interval (CI) 0.23% to 0.32%) in outpatient admissions and 0.78% (95% CI 0.68% to 0.88%) increase in emergency admissions. Concentrations of fine particles ≤ 2.5 micrometers in diameter (PM2.5) and carbon monoxide (CO) showed multi-faceted effects on pediatric admissions. PM2.5 and CO concentrations were significantly associated with decreased current-day outpatient admissions but also significantly associated with increased current-day emergency admissions at all three hospitals. Based on the health information exchange network of Shanghai, we conducted a large-scale, multi-center retrospective study of the association between adverse environmental conditions and pediatric admissions. Our study contributes to environmental health research in children and may guide decision-making regarding pediatric resource planning and policies. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1186/s40537-019-0171-x | Journal of Big Data |
Keywords | Field | DocType |
Pediatric care, Retrospective analysis, Hospital admissions, Generalized additive model, Environment, Shanghai, China | Data science,Public health,Population,Computational Science and Engineering,Environmental pollution,Computer science,China,Environmental health,Environmental effect,Economic shortage | Journal |
Volume | Issue | ISSN |
6 | 1 | 2196-1115 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guang-Jun Yu | 1 | 1 | 1.03 |
| JianLei Gu | 2 | 22 | 1.84 |
| Wenbin Cui | 3 | 0 | 0.68 |
| j jiang | 4 | 0 | 1.01 |
| Yang Wang | 5 | 0 | 1.01 |
| Georgi Z. Genchev | 6 | 0 | 0.34 |
| Ting Lu | 7 | 87 | 10.95 |
| Hui Lu | 8 | 49 | 6.27 |