tetano
Editor, Senior Moderator
Sci Total Environ
. 2022 Feb 25;154135.
doi: 10.1016/j.scitotenv.2022.154135. Online ahead of print.
Community-level ambient fine particulate matter and seasonal influenza among children in Guangzhou, China: A Bayesian spatiotemporal analysis
Rong Zhang[SUP] 1 [/SUP], Ka Yan Lai[SUP] 1 [/SUP], Wenhui Liu[SUP] 2 [/SUP], Yanhui Liu[SUP] 2 [/SUP], Jianyun Lu[SUP] 2 [/SUP], Linwei Tian[SUP] 3 [/SUP], Chris Webster[SUP] 1 [/SUP], Lei Luo[SUP] 4 [/SUP], Chinmoy Sarkar[SUP] 5 [/SUP]
Affiliations
Abstract
Background: Influenza is a major preventable infectious respiratory disease. However, there is little detailed long-term evidence of its associations with PM[SUB]2.5[/SUB] among children. We examined the community-level associations between exposure to ambient PM[SUB]2.5[/SUB] and incident influenza in Guangzhou, China.
Methods: We used data from the city-wide influenza surveillance system collected by Guangzhou Centre for Disease Control and Prevention (GZCDC) over the period 2013 and 2019. Incident influenza was defined as daily new influenza (both clinically diagnosed and laboratory confirmed) cases as per standard diagnostic criteria. A 200-meter city-wide grid of daily ambient PM[SUB]2.5[/SUB] exposure was generated using a random forest model. We developed spatiotemporal Bayesian hierarchical models to examine the community-level associations between PM[SUB]2.5[/SUB] and the influenza adjusting for meteorological and socioeconomic variables and accounting for spatial autocorrelation. We also calculated community-wide influenza cases attributable to PM[SUB]2.5[/SUB] levels exceeding the China Grade 1 and World Health Organization (WHO) regulatory thresholds.
Results: Our study comprised N = 191,846 children from Guangzhou aged ≤19 years and diagnosed with influenza between January 1, 2013 and December 31, 2019. Each 10 μg/m[SUP]3[/SUP] increment in community-level PM[SUB]2.5[/SUB] measured on the day of case confirmation (lag 0) and over a 6-day moving average (lag 0-5 days) was associated with higher risks of influenza (RR = 1.05, 95% CI: 1.05-1.06 for lag 0 and RR = 1.15, 95% CI: 1.14-1.16 for lag 05). We estimated that 8.10% (95%CI: 7.23%-8.57%) and 20.11% (95%CI: 17.64%-21.48%) influenza cases respectively were attributable to daily PM[SUB]2.5[/SUB] exposure exceeding the China Grade I (35 μg/m[SUP]3[/SUP]) and the WHO limits (25 μg/m[SUP]3[/SUP]). The risks associated with PM[SUB]2.5[/SUB] exposures were more pronounced among children of the age-group 10-14 compared to other age groups.
Conclusions: More targeted non-pharmaceutical interventions aimed at reducing PM[SUB]2.5[/SUB] exposures at home, school and during commutes among children may constitute additional influenza prevention and control polices.
Keywords: Air pollution; Children; Community-level; Guangzhou; Influenza; PM(2.5); Spatiotemporal Bayesian hierarchical model.
. 2022 Feb 25;154135.
doi: 10.1016/j.scitotenv.2022.154135. Online ahead of print.
Community-level ambient fine particulate matter and seasonal influenza among children in Guangzhou, China: A Bayesian spatiotemporal analysis
Rong Zhang[SUP] 1 [/SUP], Ka Yan Lai[SUP] 1 [/SUP], Wenhui Liu[SUP] 2 [/SUP], Yanhui Liu[SUP] 2 [/SUP], Jianyun Lu[SUP] 2 [/SUP], Linwei Tian[SUP] 3 [/SUP], Chris Webster[SUP] 1 [/SUP], Lei Luo[SUP] 4 [/SUP], Chinmoy Sarkar[SUP] 5 [/SUP]
Affiliations
- PMID: 35227720
- DOI: 10.1016/j.scitotenv.2022.154135
Abstract
Background: Influenza is a major preventable infectious respiratory disease. However, there is little detailed long-term evidence of its associations with PM[SUB]2.5[/SUB] among children. We examined the community-level associations between exposure to ambient PM[SUB]2.5[/SUB] and incident influenza in Guangzhou, China.
Methods: We used data from the city-wide influenza surveillance system collected by Guangzhou Centre for Disease Control and Prevention (GZCDC) over the period 2013 and 2019. Incident influenza was defined as daily new influenza (both clinically diagnosed and laboratory confirmed) cases as per standard diagnostic criteria. A 200-meter city-wide grid of daily ambient PM[SUB]2.5[/SUB] exposure was generated using a random forest model. We developed spatiotemporal Bayesian hierarchical models to examine the community-level associations between PM[SUB]2.5[/SUB] and the influenza adjusting for meteorological and socioeconomic variables and accounting for spatial autocorrelation. We also calculated community-wide influenza cases attributable to PM[SUB]2.5[/SUB] levels exceeding the China Grade 1 and World Health Organization (WHO) regulatory thresholds.
Results: Our study comprised N = 191,846 children from Guangzhou aged ≤19 years and diagnosed with influenza between January 1, 2013 and December 31, 2019. Each 10 μg/m[SUP]3[/SUP] increment in community-level PM[SUB]2.5[/SUB] measured on the day of case confirmation (lag 0) and over a 6-day moving average (lag 0-5 days) was associated with higher risks of influenza (RR = 1.05, 95% CI: 1.05-1.06 for lag 0 and RR = 1.15, 95% CI: 1.14-1.16 for lag 05). We estimated that 8.10% (95%CI: 7.23%-8.57%) and 20.11% (95%CI: 17.64%-21.48%) influenza cases respectively were attributable to daily PM[SUB]2.5[/SUB] exposure exceeding the China Grade I (35 μg/m[SUP]3[/SUP]) and the WHO limits (25 μg/m[SUP]3[/SUP]). The risks associated with PM[SUB]2.5[/SUB] exposures were more pronounced among children of the age-group 10-14 compared to other age groups.
Conclusions: More targeted non-pharmaceutical interventions aimed at reducing PM[SUB]2.5[/SUB] exposures at home, school and during commutes among children may constitute additional influenza prevention and control polices.
Keywords: Air pollution; Children; Community-level; Guangzhou; Influenza; PM(2.5); Spatiotemporal Bayesian hierarchical model.