Effects of Coarse Particulate Matter on Emergency Hospital Admissions for Respiratory Diseases: A Time-Series Analysis in Hong Kong

No studies have evaluated the influence of pharmaceutical copayment on hospital admission rates using time series analysis. Therefore, we aimed to analyze the relationship between hospital admission rates and the influence of the introduction of a pharmaceutical copayment system (PCS). In July 2012, a PCS was implemented in Spain, and we designed a time series analysis (1978–2018) to assess its impact on emergency hospital admissions. Hospital admission rates were estimated between 1978 and 2018 each month using the Hospital Morbidity Survey in Spain (the number of urgent hospital admissions per 100,000 inhabitants). This was conducted for men, women and both and for all-cause, cardiovascular and respiratory hospital discharges. Life expectancy was obtained from the National Institute of Statistics. The copayment variable took a value of 0 before its implementation (pre-PCS: January 1978–June 2012) and 1 after that (post-PCS: July 2012–December 2018). ARIMA (Autoregressive Integrated Moving Average) (2,0,0)(1,0,0) models were estimated with two predictors (life expectancy and copayment implementation). Pharmaceutical copayment did not influence hospital admission rates (with p-values between 0.448 and 0.925) and there was even a reduction in the rates for most of the analyses performed. In conclusion, the PCS did not influence hospital admission rates. More studies are needed to design health policies that strike a balance between the amount contributed by the taxpayer and hospital admission rates.

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Health Effects of Coarse Particulate Matter: A Time-series Analysis in Hong Kong

Epidemiology ◽

10.1097/01.ede.0000392069.31581.fc ◽

2011 ◽

Vol 22 ◽

pp. S130-S131

Author(s):

Hong Qiu ◽

Linwei Tian ◽

Tze Wai Wong ◽

Ignatius T. S. Yu

Keyword(s):

Time Series ◽

Hong Kong ◽

Particulate Matter ◽

Time Series Analysis ◽

Health Effects ◽

Series Analysis ◽

Coarse Particulate Matter

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Influence of coarse particulate matter on chickenpox in Jiading District, Shanghai, 2009–2018: A distributed lag non-linear time series analysis

Environmental Research ◽

10.1016/j.envres.2020.110039 ◽

2020 ◽

Vol 190 ◽

pp. 110039

Author(s):

Hongjie Yu ◽

Yingjian Wang ◽

Qian Peng ◽

Yueqin Shao ◽

Chunmei Duan ◽

...

Keyword(s):

Time Series ◽

Particulate Matter ◽

Time Series Analysis ◽

Linear Time ◽

Series Analysis ◽

Distributed Lag ◽

Non Linear ◽

Coarse Particulate Matter

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Relationship between respiratory diseases and environmental conditions: a time-series analysis in Eastern Amazon

Revista Brasileira de Ciências Ambientais (Online) ◽

10.5327/z217694781020 ◽

2021 ◽

Vol 56 (3) ◽

pp. 398-412

Author(s):

Mauricio Do Nascimento Moura ◽

Maria Isabel Vitorino ◽

Glauber Guimarães Cirino da Silva ◽

Valdir Soares de Andrade Filho

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Rainy Season ◽

Respiratory Diseases ◽

Hospital Admissions ◽

Dry Season ◽

Climate Indices ◽

Series Analysis ◽

Decadal Scale ◽

The City

This study examines the relationship between the time-series analysis of climate, deforestation, wildfire, Aerosol Optical Depth (AOD), and hospital admissions for respiratory diseases in the Eastern Amazon. Through a descriptive study with an ecological approach of an 18-year time-series analysis, we made a statistical analysis of two pre-established periods, namely, the rainy season and the dry season. On a decadal scale, analyzing the signals of climate indices [i.e., the Southern Oscillation Index (SOI) and the Atlantic Meridional Mode (AMM)], the city of Marabá presents correlations between hospital admissions, wildfire, and AOD. This is not observed with the same accuracy in Santarém. On a seasonal scale, our analysis demonstrated how both cities in this research presented an increase in the number of hospital admissions during the dry season: Marabá, 3%; Santarém, 5%. The same season also presented a higher number of fire outbreaks, AOD, and higher temperatures. The AOD monthly analysis showed that the atmosphere of Marabá may be under the influence of other types of aerosols, such as those from mining activities. There is a time lag of approximately 2 months in the records of wildfire in the city. Such lag is not found in Santarém. The linear regression analysis shows that there is a correlation above 64% (Marabá) and 50% (Santarém), which is statistically significant because it proves that the number of hospital admissions for respiratory diseases is dependable on the AOD value. From the cities in the study, Marabá presents the highest incidence of wildfire, with an average of 188.5— the average in Santarém is 68.7—, and therefore the highest AOD value, with an average of 0.66 (Santarém, 0.47), both during the dry season. It is evident that the climate component has a relevant contribution to the increase in the number of hospital admissions, especially during the rainy season, where there are few or no records of wildfires.

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