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Search Results: 1 - 10 of 6358 matches for " Shilu Tong "
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Health effects of ambient air pollution – recent research development and contemporary methodological challenges
Cizao Ren, Shilu Tong
Environmental Health , 2008, DOI: 10.1186/1476-069x-7-56
Abstract: It is well known that exposure to high levels of air pollution can adversely affect human health. A number of air pollution catastrophes occurred in industrial countries between 1950s and 1970s, such as the London smog of 1952 [1]. Air quality in western countries has significantly improved since the 1970s. However, adverse health effects of exposure to relatively low level of air pollution remain a public concern, motivated largely by a number of recent epidemiological studies that have shown the positive associations between air pollution and health outcomes using sophisticated time-series and other designs [2].This review highlights the key findings from major epidemiological study designs (including time-series, case-crossover, panel, cohort, and birth outcome studies) in estimating the associations of exposure to ambient air pollution with health outcomes over the last two decades, and identifies future research opportunities. We do not intend for this to be a formal systematic literature review or meta-analysis, but to discuss issues we feel are vitally important based on the recent literature and our own experience. This paper is divided into two parts: firstly to summarize recent findings from major epidemiological studies, and secondly to discuss key methodological challenges in this field and to identify research opportunities for future air pollution epidemiological studies.There are a large number of time-series studies on the short-term health effects of air pollution, with the emphasis on mortality and hospital admissions by means of fitting Poisson regression models at a community level or ecological level. This type of time-series design is a major approach to estimating short-term health effects of air pollution in epidemiological studies for the last two decades. Many studies have found associations between daily changes in ambient particulate air pollution and increased cardiorespiratory hospital admissions [3-6], along with cardiorespiratory mort
Assessing the Short-Term Effects of Heatwaves on Mortality and Morbidity in Brisbane, Australia: Comparison of Case-Crossover and Time Series Analyses
Shilu Tong, Xiao Yu Wang, Yuming Guo
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0037500
Abstract: Background Heat-related impacts may have greater public health implications as climate change continues. It is important to appropriately characterize the relationship between heatwave and health outcomes. However, it is unclear whether a case-crossover design can be effectively used to assess the event- or episode-related health effects. This study examined the association between exposure to heatwaves and mortality and emergency hospital admissions (EHAs) from non-external causes in Brisbane, Australia, using both case-crossover and time series analyses approaches. Methods Poisson generalised additive model (GAM) and time-stratified case-crossover analyses were used to assess the short-term impact of heatwaves on mortality and EHAs. Heatwaves exhibited a significant impact on mortality and EHAs after adjusting for air pollution, day of the week, and season. Results For time-stratified case-crossover analysis, odds ratios of mortality and EHAs during heatwaves were 1.62 (95% confidence interval (CI): 1.36–1.94) and 1.22 (95% CI: 1.14–1.30) at lag 1, respectively. Time series GAM models gave similar results. Relative risks of mortality and EHAs ranged from 1.72 (95% CI: 1.40–2.11) to 1.81 (95% CI: 1.56–2.10) and from 1.14 (95% CI: 1.06–1.23) to 1.28 (95% CI: 1.21–1.36) at lag 1, respectively. The risk estimates gradually attenuated after the lag of one day for both case-crossover and time series analyses. Conclusions The risk estimates from both case-crossover and time series models were consistent and comparable. This finding may have implications for future research on the assessment of event- or episode-related (e.g., heatwave) health effects.
Spatial distribution of suicide in Queensland, Australia
Xin Qi, Shilu Tong, Wenbiao Hu
BMC Psychiatry , 2010, DOI: 10.1186/1471-244x-10-106
Abstract: Data on suicide and demographic variables in each LGA between 1999 and 2003 were acquired from the Australian Bureau of Statistics. An age standardised mortality (ASM) rate for suicide was calculated at the LGA level. GIS techniques were used to examine the geographical difference of suicide across different areas.Far north and north-eastern Queensland (i.e., Cook and Mornington Shires) had the highest suicide incidence in both genders, while the south-western areas (i.e., Barcoo and Bauhinia Shires) had the lowest incidence in both genders. In different age groups (≤24 years, 25 to 44 years, 45 to 64 years, and ≥65 years), ASM rates of suicide varied with gender at the LGA level. Mornington and six other LGAs with low socioeconomic status in the upper Southeast had significant spatial clusters of high suicide risk.There was a notable difference in ASM rates of suicide at the LGA level in Queensland. Some LGAs had significant spatial clusters of high suicide risk. The determinants of the geographical difference of suicide should be addressed in future research.Suicide is a major cause of death around the world with about 877,000 suicide deaths each year globally [1]. The World Health Organization has predicted that the suicide rate will steadily increase into the future [2].In Australia, the trend of suicide has fluctuated over the 20th Century and early 21st Century [3,4]. In recent years, there have been over 2000 suicide cases recorded annually in Australia (ABS 2003, 2004) [4], with males accounting for the majority of these suicides. A number of studies have explored the distribution of suicide in different states in Australia [5-9].Some Australian and international studies have applied spatial analysis to assess the geographical difference in suicide incidence [10-15]. Our previous study analysed the spatiotemporal association between socio-environmental factors (climate, socioeconomic and demographic factors) and suicide in Queensland, Australia [13]. Some ot
Effects of temperature on mortality in Chiang Mai city, Thailand: a time series study
Yuming Guo, Kornwipa Punnasiri, Shilu Tong
Environmental Health , 2012, DOI: 10.1186/1476-069x-11-36
Abstract: A time series model was used to examine the effects of temperature on cause-specific mortality (non-external, cardiopulmonary, cardiovascular, and respiratory) and age-specific non-external mortality (<=64, 65–74, 75–84, and?>?=85?years), while controlling for relative humidity, air pollution, day of the week, season and long-term trend. We used a distributed lag non-linear model to examine the delayed effects of temperature on mortality up to 21?days.We found non-linear effects of temperature on all mortality types and age groups. Both hot and cold temperatures resulted in immediate increase in all mortality types and age groups. Generally, the hot effects on all mortality types and age groups were short-term, while the cold effects lasted longer. The relative risk of non-external mortality associated with cold temperature (19.35°C, 1st percentile of temperature) relative to 24.7°C (25th percentile of temperature) was 1.29 (95% confidence interval (CI): 1.16, 1.44) for lags 0–21. The relative risk of non-external mortality associated with high temperature (31.7°C, 99th percentile of temperature) relative to 28°C (75th percentile of temperature) was 1.11 (95% CI: 1.00, 1.24) for lags 0–21.This study indicates that exposure to both hot and cold temperatures were related to increased mortality. Both cold and hot effects occurred immediately but cold effects lasted longer than hot effects. This study provides useful data for policy makers to better prepare local responses to manage the impact of hot and cold temperatures on population health.Many studies have demonstrated that both hot and cold temperatures had adverse effects on mortality. For example, elevated ambient temperature and heat-waves were associated with excess deaths in 86 US cities [1]. High temperatures had significant impacts on deaths from all causes, chronic bronchitis, pneumonia, ischemic heart disease, and cerebrovascular disease in England and Wales [2]. McMichael et al. found a U-shaped temperatu
Preliminary spatiotemporal analysis of the association between socio-environmental factors and suicide
Xin Qi, Shilu Tong, Wenbiao Hu
Environmental Health , 2009, DOI: 10.1186/1476-069x-8-46
Abstract: Seasonal data on suicide, demographic variables and socioeconomic indexes for areas in each Local Government Area (LGA) between 1999 and 2003 were acquired from the Australian Bureau of Statistics. Climate data were supplied by the Australian Bureau of Meteorology. A multivariable generalized estimating equation model was used to examine the impact of socio-environmental factors on suicide.The preliminary data analyses show that far north Queensland had the highest suicide incidence (e.g., Cook and Mornington Shires), while the south-western areas had the lowest incidence (e.g., Barcoo and Bauhinia Shires) in all the seasons. Maximum temperature, unemployment rate, the proportion of Indigenous population and the proportion of population with low individual income were statistically significantly and positively associated with suicide. There were weaker but not significant associations for other variables.Maximum temperature, the proportion of Indigenous population and unemployment rate appeared to be major determinants of suicide at a LGA level in Queensland.Suicide is one of the major causes of mortality around the world with about 877,000 suicide deaths each year globally [1]. Socio-environmental impacts on mental health, including suicide, have drawn increasing research attention, especially in recent years as global socio-environmental conditions change rapidly [2,3].A number of studies have examined the impact of meteorological factors on suicide and found that lower suicide rates were associated with increased rainfall [4], decreased temperature [5], decreased humidity [6], and increased sunshine [7]. Additionally, some studies indicated that suicide rates varied with season [8,9]. Socioeconomic status [10,11], unemployment rate [12-14], country of birth [15,16], governmental policy [17,18] and intervention [19,20] were also associated with suicide in different countries and areas.Most of the previous suicide studies have focused on either meteorological or so
Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia
Wenbiao Hu, Kerrie Mengersen, Shilu Tong
BMC Infectious Diseases , 2010, DOI: 10.1186/1471-2334-10-311
Abstract: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models.The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.Cryptosporidiosis is a diarrhoeal disease caused by microscopic parasites of the Cryptosporidium parvum [1]. The parasite is one of the most common causes of waterborne disease in Australia and globally and is found in drinking water and recreational water [2]. Cryptosporidiosis can also be transmitted via contaminated food, contact between people, or contact between people and animals.
Methodological challenges when estimating the effects of season and seasonal exposures on birth outcomes
Linn Strand, Adrian G Barnett, Shilu Tong
BMC Medical Research Methodology , 2011, DOI: 10.1186/1471-2288-11-49
Abstract: To demonstrate the bias we simulated a retrospective birth cohort with no seasonal pattern in gestation and used a range of cohort end dates. As a real example, we used a cohort of 114,063 singleton births in Brisbane between 1 July 2005 and 30 June 2009 and examined the bias when estimating changes in gestation length associated with season (using month of conception) and a seasonal exposure (temperature). We used survival analyses with temperature as a time-dependent variable.We found strong artificial seasonal patterns in gestation length by month of conception, which depended on the end date of the study. The bias was avoided when the day and month of the start date was just before the day and month of the end date (regardless of year), so that the longer gestations at the start of the study were balanced by the shorter gestations at the end. After removing the fixed cohort bias there was a noticeable change in the effect of temperature on gestation length. The adjusted hazard ratios were flatter at the extremes of temperature but steeper between 15 and 25°C.Studies using retrospective birth cohorts should account for the fixed cohort bias by removing selected births to get unbiased estimates of seasonal health effects.Worldwide, it is estimated that 2.2% of all babies are stillborn [1] and 9.6% of all births are preterm (less than 37 completed weeks of gestation) [2]. Preterm babies are at greater risk of poor health and early death, require longer periods of hospitalisation after birth, and are more likely to develop disabilities [3-5].Environmental and meteorological factors may be a cause of adverse birth outcomes [6]. Increases in air pollution [7] and temperature [8] have been associated with adverse birth outcomes. Air pollution and temperature usually have a strong seasonal pattern, meaning that one method of examining environmental factors is to explore seasonal patterns. Research has shown that the risk of preterm birth varies by season of birth [9,10]
Surveillance of Dengue Fever Virus: A Review of Epidemiological Models and Early Warning Systems
Vanessa Racloz ,Rebecca Ramsey,Shilu Tong,Wenbiao Hu
PLOS Neglected Tropical Diseases , 2012, DOI: 10.1371/journal.pntd.0001648
Abstract: Dengue fever affects over a 100 million people annually hence is one of the world's most important vector-borne diseases. The transmission area of this disease continues to expand due to many direct and indirect factors linked to urban sprawl, increased travel and global warming. Current preventative measures include mosquito control programs, yet due to the complex nature of the disease and the increased importation risk along with the lack of efficient prophylactic measures, successful disease control and elimination is not realistic in the foreseeable future. Epidemiological models attempt to predict future outbreaks using information on the risk factors of the disease. Through a systematic literature review, this paper aims at analyzing the different modeling methods and their outputs in terms of acting as an early warning system. We found that many previous studies have not sufficiently accounted for the spatio-temporal features of the disease in the modeling process. Yet with advances in technology, the ability to incorporate such information as well as the socio-environmental aspect allowed for its use as an early warning system, albeit limited geographically to a local scale.
Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia
Suchithra Naish, Wenbiao Hu, Kerrie Mengersen, Shilu Tong
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0025688
Abstract: Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.
Assessment of Heat-Related Health Impacts in Brisbane, Australia: Comparison of Different Heatwave Definitions
Shilu Tong,Xiao Yu Wang,Adrian Gerard Barnett
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0012155
Abstract: There is no global definition of a heatwave because local acclimatisation and adaptation influence the impact of extreme heat. Even at a local level there can be multiple heatwave definitions, based on varying temperature levels or time periods. We investigated the relationship between heatwaves and health outcomes using ten different heatwave definitions in Brisbane, Australia.
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