Shannon Rutherford

Associations between outdoor air pollution and hospital admissions in Brisbane, Australia

Abstract The authors investigated the effects of ambient air pollution on hospital admissions in Brisbane, Australia. The authors used the Air Pollution on Health: European Approach protocol to examine the effects of particles, ozone, sulfur dioxide, and nitrogen dioxide on daily hospital admissions for asthma and respiratory, cardiovascular, and digestive disorders (control diagnosis) that occurred during the period 1987-1994. Ozone was consistently associated with admissions for asthma and respiratory disease—with little evidence of a threshold. In two-pollutant models, the ozone effect was relatively unaffected by the control for high levels of other pollutants. Particulate pollution (measured by nephelometry) was associated positively with admissions for respiratory disease and admissions for asthma in summer, whereas a negative association was observed for cardiovascular admissions. Although sulfur dioxide was associated significantly with admissions for respiratory and cardiovascular disease, a significant association was also found for the control diagnosis of digestive disorders. No significant associations were found for nitrogen dioxide over the study period, although significantly positive seasonal interactions were found for asthma and respiratory disease in autumn, winter, and spring. It was concluded that current levels of ambient air pollution in Brisbane make a significant contribution to the variation in daily hospital admissions for asthma and respiratory disease.

Gastroenteritis Outbreaks Caused by Norovirus GII.17, Guangdong Province, China, 2014-2015.

In the past decade, the most prevalent norovirus genotype causing viral gastroenteritis outbreaks worldwide, including China, has been GII.4. In winter 2014–15, norovirus outbreaks in Guangdong, China, increased. Sequence analysis indicated that 82% of the outbreaks were caused by a norovirus GII.17 variant.

Associations between Outdoor Air Pollution and Daily Mortality in Brisbane, Australia

The results of several studies have indicated significant associations between daily mortality and air pollution, with little evidence of a threshold. In the current study, the authors examined daily mortality during the period 1987-1993 for the Brisbane region, which is the fastest-growing urban region in Australia (annual average concentration of particulate matter less than 10 microm in diameter = 27 microg/m3, maximum hourly sulfur dioxide level = 60 ppb, and maximum daily ozone hourly level = 118 ppb). The authors conducted a general estimating equation analysis, and they used autoregressive Poisson models for daily mortality to examine associations with air pollution variables. The authors used research methods developed in the Air Pollution on Health, European Approach (APHEA), project to control confounding effects of weather and temporal trends. The air pollutants examined included particulate pollution (measured by nephelometry [bsp data]), sulfur dioxide, ozone, and nitrogen dioxide. The results indicated that the associations between total daily mortality and particulate levels found in studies in the United States and other countries may be applicable in Brisbane, Australia. Ozone levels were also associated significantly with total daily mortality. There was little evidence of interaction between the ozone effects (mainly in summer) and particulates or with sulfur dioxide and nitrogen dioxide. The associations between pollutants (ozone, bsp) and daily mortality were significant only for individuals who were older than 65 y of age; positive associations were also found with cardiovascular disease categories, and the regression coefficients--when significant--were higher than those for total mortality. The results indicated a possible threshold for ozone levels, but a similar result for particulate levels was not apparent.

Using Google Trends for Influenza Surveillance in South China

Background Google Flu Trends was developed to estimate influenza activity in many countries; however there is currently no Google Flu Trends or other Internet search data used for influenza surveillance in China. Methods and Findings Influenza surveillance data from 2008 through 2011 were obtained from provincial CDC influenza-like illness and virological surveillance systems of Guangdong, a province in south China. Internet search data were downloaded from the website of Google Trends. Pearsons correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data and internet search trends. The correlation between CDC ILI surveillance and CDC virus surveillance was 0.56 (95% CI: 0.43, 0.66). The strongest correlation was between the Google Trends term of Fever and ILI surveillance with a correlation coefficient of 0.73 (95% CI: 0.66, 0.79). When compared with influenza virological surveillance, the Google Trends term of Influenza A had the strongest correlation with a correlation coefficient of 0.64 (95% CI: 0.43, 0.79) in the 2009 H1N1 influenza pandemic period. Conclusions This study shows that Google Trends in Chinese can be used as a complementary source of data for influenza surveillance in south China. More research in the future should develop new models using search trends in Chinese language to estimate local disease activity and detect early signals of outbreaks.

Microscopic and submicron components of atmospheric particulate matter during high asthma periods in Brisbane, Queensland, Australia

The study identifies the various components contributing to atmospheric particulate matter in Brisbane, Queensland, Australia, during the period from the end of April and the months of July–August in 1992, covering the autumn period which is typically the period of high asthma incidence in Brisbane. Most particulate matter is < 2 μm and submicronic. Electron microscopy revealed that the submicron material is composed mainly of combusted (“soot”) and incompletely burned hydrocarbons arising from motor vehicle exhaust emissions, crustal matter in the form of quartz microconcretions and other silicates, quiescent spores of Mucorales, and soil bacteria. The contribution from pollen and fungal spores has been evaluated and quantified. Fungal spores counts dominate the bioaerosol counts in the 2–10 μm range and are very high in Brisbane from the end of April through May to mid-June. However even at peak periods the total bioaerosol count only contributes of the order of 5–10% of the total particulate mass. The results show that Pm10 (particulate matter less than 10 μm in diameter) and nephelometer readings do not indicate peak periods of allergenic bioaerosol readings (in fact there is a negative correlation) due to the low contribution of the bioaerosol count to the total and the different influences of wind speed. However the electron microscopy results show that this does not mean there are no synergies between aerosols from anthropogenic sources and bioaerosols. The cytoplasmic content of spores and pollen was often found to be adhered to motor vehicle emission material and crustal matter. The latter may therefore act as carriers for dispersed cytoplasmic allergenic material released from pollen and fungal spores.

The short-term effect of heat waves on mortality and its modifiers in China: An analysis from 66 communities

BACKGROUND Many studies have reported increased mortality risk associated with heat waves. However, few have assessed the health impacts at a nation scale in a developing country. This study examines the mortality effects of heat waves in China and explores whether the effects are modified by individual-level and community-level characteristics. METHODS Daily mortality and meteorological variables from 66 Chinese communities were collected for the period 2006-2011. Heat waves were defined as ≥2 consecutive days with mean temperature ≥95th percentile of the year-round community-specific distribution. The community-specific mortality effects of heat waves were first estimated using a Distributed Lag Non-linear Model (DLNM), adjusting for potential confounders. To investigate effect modification by individual characteristics (age, gender, cause of death, education level or place of death), separate DLNM models were further fitted. Potential effect modification by community characteristics was examined using a meta-regression analysis. RESULTS A total of 5.0% (95% confidence intervals (CI): 2.9%-7.2%) excess deaths were associated with heat waves in 66 Chinese communities, with the highest excess deaths in north China (6.0%, 95% CI: 1%-11.3%), followed by east China (5.2%, 95% CI: 0.4%-10.2%) and south China (4.5%, 95% CI: 1.4%-7.6%). Our results indicate that individual characteristics significantly modified heat waves effects in China, with greater effects on cardiovascular mortality, cerebrovascular mortality, respiratory mortality, the elderly, females, the population dying outside of a hospital and those with a higher education attainment. Heat wave mortality effects were also more pronounced for those living in urban cities or densely populated communities. CONCLUSION Heat waves significantly increased mortality risk in China with apparent spatial heterogeneity, which was modified by some individual-level and community-level factors. Our findings suggest adaptation plans that target vulnerable populations in susceptible communities during heat wave events should be developed to reduce health risks.

Short-term effects of the 2008 cold spell on mortality in three subtropical cities in Guangdong Province, China.

Background: Few studies have been conducted to investigate the impact of extreme cold events on mortality in subtropical regions. Objective: In the present study we aimed to investigate the effects of the 2008 cold spell on mortality and the possibility of mortality displacement in three subtropical cities in China. Methods: Daily mortality, air pollution, and weather data were collected from 2006 to 2009 in Guangzhou, Nanxiong (no air pollutants), and Taishan. We used a polynomial distributed lag model (DLM) to analyze the relationship between the 2008 cold spell and mortality. To observe the mortality displacement of the cold spell, we estimated the cumulative effects at lag0, lag0–6, lag0–13, lag0–20, and lag0–27 separately. Results: During the 2008 cold spell, the cumulative risk of nonaccidental mortality increased significantly in Guangzhou [relative risk (RR) = 1.60; 95% CI: 1.19, 2.14] and Taishan (RR = 1.60; 95% CI: 1.06, 2.40) when lagged up to 4 weeks after the cold spell ended. Estimated effects at lag0–27 were more pronounced for males than for females, for respiratory mortality than for cardiovascular mortality, and for the elderly (≥ 75 years of age) than for those 0–64 years of age. Most of the cumulative RRs increased with longer lag times in Guangzhou and Taishan. However, in Nanxiong, the trend with cumulative RRs was less consistent, and we observed no statistically significant associations at lag0–27. Conclusion: We found associations between the 2008 cold spell and increased mortality in the three subtropical cities of China. The lag effect structure of the cold spell varied with location and the type of mortality, and evidence of short-term mortality displacement was inconsistent. These findings suggest that extreme cold is an important public health problem in subtropical regions.

Particle size and chemical constituents of ambient particulate pollution associated with cardiovascular mortality in Guangzhou, China.

Though significant associations between particulate matter (PM) air pollution and cardiovascular diseases have been widely reported, it remains unclear what characteristics, such as particle size and chemical constituents, may be responsible for the effects. A time-series model was applied to examine the cardiovascular effects of particle size (for the period of 2009-2011) and chemical constituents (2007-2010) in Guangzhou, we controlled for potential confounders in the model, such as time trends, day of the week, public holidays, meteorological factors and influenza epidemic. We found significant associations of cardiovascular mortality with PM10, PM2.5 and PM1; the excess risk (ER) was 6.10% (95% CI: 1.76%, 10.64%), 6.11% (95% CI: 1.76%, 10.64%) and 6.48% (95% CI: 2.10%, 11.06%) for per IQR increase in PM10, PM2.5 and PM1 at moving averages for the current day and the previous 3 days (lag03), respectively. We did not find significant effects of PM2.5-10 and PM1-2.5. For PM2.5 constituents, we found that organic carbon, elemental carbon, sulfate, nitrate and ammonium were significantly associated with cardiovascular mortality, the corresponding ER for an IQR concentration increase at lag03 was 1.13% (95% CI: 0.10%, 2.17%), 2.77% (95% CI: 0.72%, 4.86%), 2.21% (95% CI: 1.05%, 3.38%), 1.98% (95% CI: 0.54%, 3.44%), and 3.38% (95% CI: 1.56%, 5.23%), respectively. These results were robust to adjustment of other air pollutants and they remained consistent in various sensitivity analyses by changing model parameters. Our study suggests that PM1 and constituents from combustion and secondary aerosols might be important characteristics of PM pollution associated with cardiovascular mortality in Guangzhou.

The effect of heat waves on mortality and effect modifiers in four communities of Guangdong Province, China

BACKGROUND Heat waves have been reported to be associated with increased mortality; however, fewer studies have examined the effect modification by heat wave characteristics, individual characteristics and community characteristics. METHODS This study investigated the effect of extreme heat on mortality in 2 urban and 2 rural communities in Guangdong Province, China during 2006-2010. The effect of extreme heat was divided into two parts: main effect due to high temperature and added effect due to prolonged heat for several consecutive days. A distributed lag non-linear model was used to calculate the relative risk with consideration of lag days and potential confounding factors. Separate models were further fit by individual characteristics (cause of death, age and gender) and heat wave characteristics (intensity, duration and timing), and potential effect modification of community characteristics was examined using a meta-regression, such as educational levels, percentage of the elderly, Gross Regional Domestic Product (GDP). RESULTS The overall main effects (ER=8.2%, 95% CI: 3.4%, 13.2%) were greater than the added effects (ER=0.0%, 95% CI: -3.8%, 4.0%) on the current day. The main effect peaked at lag0-2, and was higher for the two rural areas compared to the two cities, for respiratory compared to cardiovascular mortality, for those ≥75 years old and for females. The modifying effects of heat wave characteristics and community characteristics on mortality were not statistically significant. CONCLUSION This study suggests the effects of extreme heat were mainly driven by high temperature, which can be modified by some individual characteristics.

The temperature–mortality relationship in China: An analysis from 66 Chinese communities

BACKGROUND Previous studies examining temperature-mortality associations in China focused on a single city or a small number of cities. A multi-city study covering different climatic zones is necessary to better understand regional differences in temperature risk on mortality in China. METHODS Sixty-six communities from 7 regions across China were included in this study. We first used a Distributed Lag Non-linear Model (DLNM) to estimate community-specific effects of temperature on non-accidental mortality during 2006-2011. A multivariate meta-analysis was then applied to pool the estimates of community-specific effects. RESULTS A U-shaped curve was observed between temperature and mortality at the national level in China, indicating both low and high temperatures were associated with increased mortality risk. The overall threshold was at about the 75th percentile of the pooled temperature distribution. The relative risk was 1.61 (95% CI: 1.48-1.74) for extremely cold temperature (1st percentile of temperature), and 1.21 (95% CI: 1.10-1.34) for extreme hot temperature (99th percentile of temperature) at lag0-21 days. The temperature-mortality relationship is different for different regions. Compared with north China, south China had a higher minimum mortality temperature (MMT), and there was a larger cold effect in the more southern parts of China and a more pronounced hot effect in more northern parts. CONCLUSIONS Both cold and hot temperatures increase mortality risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.