Impact of Air Pollution and Trans-Boundary Haze on Nation-Wide Emergency Department Visits and Hospital Admissions in Singapore

Introduction: Air pollution is associated with adverse health outcomes. However, its impact on emergency health services is less well understood. We investigated the impact of air pollution on nation-wide emergency department (ED) visits and hospital admissions to public hospitals in Singapore. Materials and Methods: Anonymised administrative and clinical data of all ED visits to public hospitals in Singapore from January 2010 to December 2015 were retrieved and analysed. Primary and secondary outcomes were defined as ED visits and hospital admissions, respectively. Conditional Poisson regression was used to model the effect of Pollutant Standards Index (PSI) on each outcome. Both outcomes were stratified according to subgroups defined a priori based on age, diagnosis, gender, patient acuity and time of day. Results: There were 5,791,945 ED visits, of which 1,552,187 resulted in hospital admissions. No significant association between PSI and total ED visits (Relative risk [RR], 1.002; 99.2% confidence interval [CI], 0.995–1.008; P = 0.509) or hospital admissions (RR, 1.005; 99.2% CI, 0.996–1.014; P = 0.112) was found. However, for every 30-unit increase in PSI, significant increases in ED visits (RR, 1.023; 99.2% CI, 1.011–1.036; P = 1.24 × 10˗6) and hospital admissions (RR, 1.027; 99.2% CI, 1.010–1.043; P = 2.02 × 10˗5) for respiratory conditions were found. Conclusion: Increased PSI was not associated with increase in total ED visits and hospital admissions, but was associated with increased ED visits and hospital admissions for respiratory conditions in Singapore. Key words: Epidemiology, Healthcare utilisation, PSI, Public health, Time series

Impact of Air Pollution and Trans-Boundary Haze on Nation-Wide Emergency Department Visits and Hospital Admissions in Singapore

INTRODUCTION

Air pollution is associated with adverse health outcomes. However, its impact on emergency health services is less well understood. We investigated the impact of air pollution on nation-wide emergency department (ED) visits and hospital admissions to public hospitals in Singapore.

MATERIALS AND METHODS

Anonymised administrative and clinical data of all ED visits to public hospitals in Singapore from January 2010 to December 2015 were retrieved and analysed. Primary and secondary outcomes were defined as ED visits and hospital admissions, respectively. Conditional Poisson regression was used to model the effect of Pollutant Standards Index (PSI) on each outcome. Both outcomes were stratified according to subgroups defined a priori based on age, diagnosis, gender, patient acuity and time of day.

RESULTS

There were 5,791,945 ED visits, of which 1,552,187 resulted in hospital admissions. No significant association between PSI and total ED visits (Relative risk [RR], 1.002; 99.2% confidence interval [CI], 0.995-1.008; P = 0.509) or hospital admissions (RR, 1.005; 99.2% CI, 0.996-1.014; P = 0.112) was found. However, for every 30-unit increase in PSI, significant increases in ED visits (RR, 1.023; 99.2% CI, 1.011-1.036; P = 1.24 × 10^-6 ) and hospital admissions (RR, 1.027; 99.2% CI, 1.010-1.043; P = 2.02 × 10^-5 ) for respiratory conditions were found.

CONCLUSION

Increased PSI was not associated with increase in total ED visits and hospital admissions, but was associated with increased ED visits and hospital admissions for respiratory conditions in Singapore.

Multi-city study on air pollution and hospital outpatient visits for asthma in China

BACKGROUND

The proportion of asthma patients with mild to moderate exacerbations is far greater than the number who experience episodes that are severe enough to require emergency room visits or hospital admission. However the routinely collected data from hospitals is absent in the past.

OBJECTIVE

To evaluate associations between short-term exposures to air pollutants and hospital outpatient visits for asthma in China.

METHODS

We obtained data for 143,057 asthma outpatient visits from the largest hospitals in 17 Chinese cities, between Jan 01 2013 and Dec 31 2015. We used daily concentrations of air pollutants measured by the China National Environmental Monitoring Centre. We used a time-stratified case-crossover design, and fitted conditional logistic regression models to determine the associations.

RESULTS

Particulate matter ≤10μm in diameter (PM10) and nitrogen dioxide (NO2) were associated with increased risks of hospital outpatient visits for asthma on the same day, while the effects were delayed for particulate matter ≤2.5μm in diameter (PM2.5) and sulphur dioxide (SO2). For the cumulative effect model at lag05 days, 10 μg/m3 increase in air pollutants concentrations were correlated with hospital outpatient visits for asthma with odds ratios (ORs) and 95% confidence intervals 1.004 (1.000-1.008) for PM2.5, 1.005 (1.002-1.008) for PM10, 1.030 (1.021-1.040) for NO2, and 1.015 (1.008-1.021) for SO2. Almost one in nine (10.9%; 7.7, 13.9%) hospital outpatient visits for asthma were attributable to NO2.

CONCLUSION

Short-term exposures to PM2.5, PM10, NO2 and SO2 were associated with hospital outpatient visits for asthma in China.

Differential Mental Health Impact Six Months After Extensive River Flooding in Rural Australia: A Cross-Sectional Analysis Through an Equity Lens

Background: Northern New South Wales in Australia is a “hotspot” for natural disaster declarations with recent extensive flooding in early 2017. With limited knowledge about how climate change affects mental health and resilience, robust local assessments are required to better understand long-term impact, particularly in communities prone to extreme weather events.

Methods: Six months post-flood, a cross-sectional survey of adults living in the region during the flood was conducted to quantify associations between flood impact and psychological morbidity (post-traumatic stress (PTSD), anxiety, depression, suicidal ideation) for different exposure scenarios, and respondent groups. We adopted a community-academic partnership approach and purposive recruitment to increase participation from marginalized groups.

Results: Of 2,180 respondents, almost all (91%) were affected by some degree of flood-related exposure at an individual and community level (ranging from suburb damage to home or business inundated). Socio-economically marginalized respondents were more likely to have their homes inundated and to be displaced. Mental health risk was significantly elevated for respondents: whose home/business/farm was inundated [e.g., home inundation: PTSD adjusted odds ratio (AOR) 13.72 (99% CI 4.53–41.56)]; who reported multiple exposures [e.g., three exposures: PTSD AOR 6.43 (99% CI 2.11–19.60)]; and who were still displaced after 6 months [e.g., PTSD AOR 24.43 (99% CI 7.05–84.69)].

Conclusion: The 2017 flood had profound impact, particularly for respondents still displaced and for socio-economically marginalized groups. Our community-academic partnership approach builds community cohesion, informs targeted mental health disaster preparedness and response policies for different sectors of the community and longer-term interventions aimed at improving community adaptability to climate change.

The 2019 report of the MJA-Lancet Countdown on health and climate change: a turbulent year with mixed progress

The MJA-Lancet Countdown on health and climate change was established in 2017 and produced its first Australian national assessment in 2018. It examined 41 indicators across five broad domains: climate change impacts, exposures and vulnerability; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. It found that, overall, Australia is vulnerable to the impacts of climate change on health, and that policy inaction in this regard threatens Australian lives. In this report we present the 2019 update. We track progress on health and climate change in Australia across the same five broad domains and many of the same indicators as in 2018. A number of new indicators are introduced this year, including one focused on wildfire exposure, and another on engagement in health and climate change in the corporate sector. Several of the previously reported indicators are not included this year, either due to their discontinuation by the parent project, the Lancet Countdown, or because insufficient new data were available for us to meaningfully provide an update to the indicator. In a year marked by an Australian federal election in which climate change featured prominently, we find mixed progress on health and climate change in this country. There has been progress in renewable energy generation, including substantial employment increases in this sector. There has also been some progress at state and local government level. However, there continues to be no engagement on health and climate change in the Australian federal Parliament, and Australia performs poorly across many of the indicators in comparison to other developed countries; for example, it is one of the world's largest net exporters of coal and its electricity generation from low carbon sources is low. We also find significantly increasing exposure of Australians to heatwaves and, in most states and territories, continuing elevated suicide rates at higher temperatures. We conclude that Australia remains at significant risk of declines in health due to climate change, and that substantial and sustained national action is urgently required in order to prevent this.

Association between fire smoke fine particulate matter and asthma-related outcomes: Systematic review and meta-analysis

BACKGROUND

Asthma-related outcomes are regularly used by studies to investigate the association between human exposure to landscape fire smoke and health. Robust summary effect estimates are required to inform health protection policy for fire smoke exposure.

OBJECTIVE

To conduct a systematic review and meta-analysis to estimate the association between short-term exposure to landscape fire smoke (LFS) fine particulate matter (PM_2.5) and asthma-related outcomes.

METHODS

We conducted a systematic review and meta-analysis following PRISMA guidelines. Four databases (PubMed, Medline, EMBASE and Scopus) and reference lists of recent fire smoke and health reviews were searched. The Newcastle-Ottawa Scale was used to evaluate the quality of case-crossover studies, and a previously validated quality assessment framework was used for observational studies lacking control groups. Publication bias was assessed using funnel plots and Egger's Test. The trim and fill method was used when there was evidence of publication bias. Sensitivity and influence analyses were conducted on all endpoints to test the robustness of estimates. Summary estimates were obtained for hospitalisations and emergency department (ED) visits. A descriptive analysis was conducted for physician visits, medication use, and salbutamol dispensations.

RESULTS

From an initial 181 articles (after duplicate removal), 20 studies were included for quantitative assessment and descriptive synthesis. LFS PM_2.5 levels were positively associated with asthma hospitalisations (RR = 1.06, 95% CI: 1.02-1.09) and emergency department visits (RR = 1.07, 95% CI: 1.04-1.09). Subgroup analyses found that females were more susceptible than males for ED visits, and that there was an increasing association by age groups for hospital admissions and ED visits. High heterogeneity between studies was observed, but results were robust to sensitivity analysis.

CONCLUSIONS

Females and all adults aged over 65 years appear to be the population groups most sensitive to asthma-related outcomes when exposed to LFS PM_2.5. Overall, results were higher than those obtained for a typical PM_2.5 mixture.

Rationale and methods for a cross-sectional study of mental health and wellbeing following river flooding in rural Australia, using a community-academic partnership approach

BACKGROUND

Climate change is associated with greater frequency, duration, intensity and unpredictability of certain weather-related events, including floods. Floods harm mental health. There is limited understanding of the mental health and well-being effects from river flooding, particularly over the longer term and in rural contexts. This paper describes the rationale, aims, objectives, study design and socio-demographic characteristics of the sample for a study measuring associations between flood experience and mental health and wellbeing of residents (particularly those most likely to be negatively impacted and hard to reach) in rural NSW Australia 6 months following a devastating flood in 2017. To our knowledge, the study is the first of its kind within Australia in a rural community and is an important initiative given the likelihood of an increasing frequency of severe flooding in Australia given climate change.

METHODS

A conceptual framework (The Flood Impact Framework) drawing on social ecological approaches was developed by the research team. It was based on the literature and feedback from the community. The Framework describes putative relationships between flood exposure and mental health and wellbeing outcomes. Within a community-academic partnership approach, a cross-sectional survey was then undertaken to quantify and further explore these relationships.

RESULTS

The cross-sectional survey was conducted online (including on mobile phone) and on paper between September and November 2017 and recruited 2530 respondents. Of those, 2180 provided complete demographic data, among whom 69% were women, 91% were aged 25-74, 4% identified as Aboriginal and/or Torres Strait Islander, 9% were farmers and 33% were business owners.

CONCLUSIONS

The study recruited a wide range of respondents and the partnership facilitated the community's engagement with the design and implementation of the study. The study will provide a basis for a follow-up study, that will aim to improve the understanding of mental health and wellbeing effects over the longer term. It will provide an important and original contribution to understanding river flooding and mental health in rural Australia, a topic that will grow in importance in the context of human-induced climate change, and identify critical opportunities to strengthen services, emergency planning and resilience to future flooding.

Acute Health Impacts of the Southeast Asian Transboundary Haze Problem-A Review

Air pollution has emerged as one of the world’s largest environmental health threats, with various studies demonstrating associations between exposure to air pollution and respiratory and cardiovascular diseases. Regional air quality in Southeast Asia has been seasonally affected by the transboundary haze problem, which has often been the result of forest fires from “slash-and-burn” farming methods. In light of growing public health concerns, recent studies have begun to examine the health effects of this seasonal haze problem in Southeast Asia. This review paper aims to synthesize current research efforts on the impact of the Southeast Asian transboundary haze on acute aspects of public health. Existing studies conducted in countries affected by transboundary haze indicate consistent links between haze exposure and acute psychological, respiratory, cardiovascular, and neurological morbidity and mortality. Future prospective and longitudinal studies are warranted to quantify the long-term health effects of recurrent, but intermittent, exposure to high levels of seasonal haze. The mechanism, toxicology and pathophysiology by which these toxic particles contribute to disease and mortality should be further investigated. Epidemiological studies on the disease burden and socioeconomic cost of haze exposure would also be useful to guide policy-making and international strategy in minimizing the impact of seasonal haze in Southeast Asia.

Acute Health Impacts of the Southeast Asian Transboundary Haze Problem-A Review

Air pollution has emerged as one of the world's largest environmental health threats, with various studies demonstrating associations between exposure to air pollution and respiratory and cardiovascular diseases. Regional air quality in Southeast Asia has been seasonally affected by the transboundary haze problem, which has often been the result of forest fires from "slash-and-burn" farming methods. In light of growing public health concerns, recent studies have begun to examine the health effects of this seasonal haze problem in Southeast Asia. This review paper aims to synthesize current research efforts on the impact of the Southeast Asian transboundary haze on acute aspects of public health. Existing studies conducted in countries affected by transboundary haze indicate consistent links between haze exposure and acute psychological, respiratory, cardiovascular, and neurological morbidity and mortality. Future prospective and longitudinal studies are warranted to quantify the long-term health effects of recurrent, but intermittent, exposure to high levels of seasonal haze. The mechanism, toxicology and pathophysiology by which these toxic particles contribute to disease and mortality should be further investigated. Epidemiological studies on the disease burden and socioeconomic cost of haze exposure would also be useful to guide policy-making and international strategy in minimizing the impact of seasonal haze in Southeast Asia.

A statistical downscaling approach for generating high spatial resolution health risk maps: a case study of road noise and ischemic heart disease mortality in Melbourne, Australia

Introduction

Road traffic noise increases the risk of mortality from ischemic heart disease (IHD). Because noise is highly localized, high resolution maps of exposures and health outcomes are key to urban planning interventions that are informed by health risks. In Australia, publicly accessible IHD deaths data are only available at the coarse spatial aggregation level of local government area (LGA), in which about 130,000 people reside. Herein, we addressed this limitation of health data using statistical downscaling and generated environmental health risk maps for noise at the meshblock level (MB; ~ 90 people).

Methods

We estimated noise exposures at the MB level using a model of road traffic noise in Melbourne, Australia, from 2011. As recommended by the World Health Organization, a non-linear exposure–response function for traffic noise and IHD was used to calculate odds ratios for noise related IHD in all MBs. Noise attributable risks of IHD death were then estimated by statistically downscaling LGA-level IHD rates to the MB level.

Results

Noise levels of 80 dB were recorded in some MBs. From the given noise maps, approximately 5% of the population was exposed to traffic noise above the risk threshold of 55 dB. Maps of excess risk at the MB level identified areas in which noise levels and exposed populations are large. Attributable rates of IHD deaths due to noise were generally very low, but some were as high as 5–10 per 100,000, and in extremely noisy and populated MBs represented more than 8% excess risk of IHD death. We presented results as interactive maps of excess risk due to noise at the small neighbourhood scale.

Conclusion

Our method accommodates low-resolution health data and could be used to inform urban planning and public health decision making for various environmental health concerns. Estimated noise related IHD deaths were relatively few in Melbourne in 2011, likely because road traffic is one of many noise sources and the current noise model underestimates exposures. Nonetheless, this novel computational framework could be used globally to generate maps of noise related health risks using scant health outcomes data.

The MJA-Lancet Countdown on health and climate change: Australian policy inaction threatens lives

Climate plays an important role in human health and it is well established that climate change can have very significant impacts in this regard. In partnership with The Lancet and the MJA, we present the inaugural Australian Countdown assessment of progress on climate change and health. This comprehensive assessment examines 41 indicators across five broad sections: climate change impacts, exposures and vulnerability; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. These indicators and the methods used for each are largely consistent with those of the Lancet Countdown global assessment published in October 2017, but with an Australian focus. Significant developments include the addition of a new indicator on mental health. Overall, we find that Australia is vulnerable to the impacts of climate change on health, and that policy inaction in this regard threatens Australian lives. In a number of respects, Australia has gone backwards and now lags behind other high income countries such as Germany and the United Kingdom. Examples include the persistence of a very high carbon-intensive energy system in Australia, and its slow transition to renewables and low carbon electricity generation. However, we also find some examples of good progress, such as heatwave response planning. Given the overall poor state of progress on climate change and health in Australia, this country now has an enormous opportunity to take action and protect human health and lives. Australia has the technical knowhow and intellect to do this, and our annual updates of this assessment will track Australia's engagement with and progress on this vitally important issue.

All-cause mortality and long-term exposure to low level air pollution in the '45 and up study' cohort, Sydney, Australia, 2006-2015

BACKGROUND

Epidemiological studies show that long-term exposure to ambient air pollution reduces life expectancy. Most studies have been in environments with relatively high concentrations such as North America, Europe and Asia. Associations at the lower end of the concentration-response function are not well defined.

OBJECTIVES

We assessed associations between all-cause mortality and exposure to annual average particulate matter <2.5 μm (PM_2.5) and nitrogen dioxide (NO₂) in Sydney, Australia, where concentrations are relatively low.

METHODS

The '45 and Up Study' comprises a prospective longitudinal cohort from the state of New South Wales, Australia with 266,969 participants linked to death registry data. We analyzed data for the participants who resided in Sydney at baseline questionnaire (n = 75,268). Exposures to long-term pollution were estimated using annual averages from a chemical transport model (PM_2.5), and a satellite-based land-use regression model (NO₂). Socio-demographic information was extracted from the baseline questionnaire. Cox proportional hazard models were applied to estimate associations, while adjusting for covariates.

RESULTS

In our cohort mean annual PM_2.5 was 4.5 μg/m³ and mean NO₂ was 17.8 μg/m³. The mortality rate was 4.4% over the 7 years of follow up. Models that adjusted for individual-level and area-level risk factors resulted in a detrimental non statistically significant hazard ratio (HR) of 1.05 (95% CI: 0.98-1.12) per 1 μg/m³ increase in PM_2.5, and 1.03 (95% CI: 0.98-1.07) per 5 μg/m³ increase in NO₂.

CONCLUSIONS

We found evidence that low-level air pollution exposure was associated with increased risk of mortality in this cohort of adults aged 45 years and over, even at the relatively low concentrations seen in Sydney. However, a clear determination of the association with mortality is difficult because the results were sensitive to some covariates. Our findings are supportive of emerging evidence that exposure to low levels of air pollution reduces life expectancy.

Area-Level Walkability and the Geographic Distribution of High Body Mass in Sydney, Australia: A Spatial Analysis Using the 45 and Up Study

Improving the walkability of built environments to promote healthy lifestyles and reduce high body mass is increasingly considered in regional development plans. Walkability indexes have the potential to inform, benchmark and monitor these plans if they are associated with variation in body mass outcomes at spatial scales used for health and urban planning. We assessed relationships between area-level walkability and prevalence and geographic variation in overweight and obesity using an Australian population-based cohort comprising 92,157 Sydney respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. Individual-level data on overweight and obesity were aggregated to 2006 Australian postal areas and analysed as a function of area-level Sydney Walkability Index quartiles using conditional auto regression spatial models adjusted for demographic, social, economic, health and socioeconomic factors. Both overweight and obesity were highly clustered with higher-than-expected prevalence concentrated in the urban sprawl region of western Sydney, and lower-than-expected prevalence in central and eastern Sydney. In fully adjusted spatial models, prevalence of overweight and obesity was 6% and 11% lower in medium-high versus low, and 10% and 15% lower in high versus low walkability postcodes, respectively. Postal area walkability explained approximately 20% and 9% of the excess spatial variation in overweight and obesity that remained after accounting for other individual- and area-level factors. These findings provide support for the potential of area-level walkability indexes to inform, benchmark and monitor regional plans aimed at targeted approaches to reducing population-levels of high body mass through environmental interventions. Future research should consider potential confounding due to neighbourhood self-selection on area-level walkability relations.

Satellite-Based Land-Use Regression for Continental-Scale Long-Term Ambient PM2.5 Exposure Assessment in Australia

Australia has relatively diverse sources and low concentrations of ambient fine particulate matter (<2.5 μm, PM_2.5). Few comparable regions are available to evaluate the utility of continental-scale land-use regression (LUR) models including global geophysical estimates of PM_2.5, derived by relating satellite-observed aerosol optical depth to ground-level PM_2.5 ("SAT-PM_2.5"). We aimed to determine the validity of such satellite-based LUR models for PM_2.5 in Australia. We used global SAT-PM_2.5 estimates (∼10 km grid) and local land-use predictors to develop four LUR models for year-2015 (two satellite-based, two nonsatellite-based). We evaluated model performance at 51 independent monitoring sites not used for model development. An LUR model that included the SAT-PM_2.5 predictor variable (and six others) explained the most spatial variability in PM_2.5 (adjusted R² = 0.63, RMSE (μg/m³ [%]): 0.96 [14%]). Performance decreased modestly when evaluated (evaluation R² = 0.52, RMSE: 1.15 [16%]). The evaluation R² of the SAT-PM_2.5 estimate alone was 0.26 (RMSE: 3.97 [56%]). SAT-PM_2.5 estimates improved LUR model performance, while local land-use predictors increased the utility of global SAT-PM_2.5 estimates, including enhanced characterization of within-city gradients. Our findings support the validity of continental-scale satellite-based LUR modeling for PM_2.5 exposure assessment in Australia.

Traffic related air pollution and development and persistence of asthma and low lung function

BACKGROUND AND AIMS

Traffic Related Air Pollution (TRAP) exposure is known to exacerbate existing respiratory diseases. We investigated longer term effects of TRAP exposure for individuals with or without existing asthma, and with or without lower lung function.

METHODS

Associations between TRAP exposure and asthma (n = 689) and lung function (n = 599) were investigated in the prospective Tasmanian Longitudinal Health Study (TAHS). TRAP exposure at age 45 years was measured using two methods based on residential address: mean annual NO₂ exposure; and distance to nearest major road. Adjusted multinomial logistic regression was used to model the association between exposure to TRAP at 45 years and changes in asthma and lung function, using three follow ups of TAHS (45, 50 and 53 years).

RESULTS

For those who never had asthma by 45, living <200 m from a major road was associated with increased odds of new asthma that persisted from 50 to 53 years (adjusted Odds Ratio [aOR] 5.20; 95% CI 1.07, 25.4). Asthmatic participants at 45 had an increased risk of persistent asthma up to 53 years if they were living <200 m from a major road, compared with asthmatic participants living >200 m from a major road (aOR = 5.21; 95% CI 1.54, 17.6).

CONCLUSION

For middle aged adults, living <200 m for a major road (a marker of TRAP exposure) influences both the development and persistence of asthma. These findings have public health implications for asthma prevention strategies in primary and secondary settings.

Air Pollution and Otitis Media in Children: A Systematic Review of Literature

Young children are particularly vulnerable to otitis media (OM) which globally affects over 80% of children below the age of 3 years. Although there is convincing evidence for an association between environmental tobacco smoke exposure and OM in children, the relationship with ambient air pollution is not clear. We aimed to systematically review the literature on the relationship between ambient air pollution exposure and OM in children. A systematic search was performed in PubMed and EMBASE databases. Of 934 references identified, 24 articles were included. There is an increasing body of evidence supporting an association between higher ambient air pollution exposure and a higher risk of OM in children. While NO₂ showed the most consistent association with OM, other specific pollutants showed inconsistent associations. Studies were mainly conducted in high/middle income countries with limited evidence from low-income countries. Although there was a general consensus that higher air pollution exposure is associated with a greater prevalence of OM, the evidence for associations with specific pollutants is inconsistent. More well-designed studies on associations between specific air pollutants as risk factors for OM are warranted, especially in low income countries with high air pollution levels.

Blending Multiple Nitrogen Dioxide Data Sources for Neighborhood Estimates of Long-Term Exposure for Health Research

Exposure to traffic related nitrogen dioxide (NO₂) air pollution is associated with adverse health outcomes. Average pollutant concentrations for fixed monitoring sites are often used to estimate exposures for health studies, however these can be imprecise due to difficulty and cost of spatial modeling at the resolution of neighborhoods (e.g., a scale of tens of meters) rather than at a coarse scale (around several kilometers). The objective of this study was to derive improved estimates of neighborhood NO₂ concentrations by blending measurements with modeled predictions in Sydney, Australia (a low pollution environment). We implemented the Bayesian maximum entropy approach to blend data with uncertainty defined using informative priors. We compiled NO₂ data from fixed-site monitors, chemical transport models, and satellite-based land use regression models to estimate neighborhood annual average NO₂. The spatial model produced a posterior probability density function of estimated annual average concentrations that spanned an order of magnitude from 3 to 35 ppb. Validation using independent data showed improvement, with root mean squared error improvement of 6% compared with the land use regression model and 16% over the chemical transport model. These estimates will be used in studies of health effects and should minimize misclassification bias.

The contribution of area-level walkability to geographic variation in physical activity: a spatial analysis of 95,837 participants from the 45 and Up Study living in Sydney, Australia

BACKGROUND

Individual-level studies support a positive relation between walkable built environments and participation in moderate-intensity walking. However, the utility of this evidence for population-level planning is less clear as it is derived at much finer spatial scales than those used for regional programming. The aims of this study were to: evaluate if individual-level relations between walkability and walking to improve health manifest at population-level spatial scales; assess the specificity of area-level walkability for walking relative to other moderate and vigorous physical activity (MVPA); describe geographic variation in walking and other MVPA; and quantify the contribution of walkability to this variation.

METHODS

Data on sufficient walking, sufficient MVPA, and high MVPA to improve health were analyzed for 95,837 Sydney respondents to the baseline survey of the 45 and Up Study between January 2006 and April 2010. We used conditional autoregressive models to create smoothed MVPA "disease maps" and assess relations between sufficient MVPA to improve health and area-level walkability adjusted for individual-level demographic, socioeconomic, and health factors, and area-level relative socioeconomic disadvantage.

RESULTS

Within-cohort prevalence of meeting recommendations for sufficient walking, sufficient MVPA, and high MVPA were 31.7 (95% CI 31.4-32.0), 69.4 (95% CI 69.1-69.7), and 56.1 (95% CI 55.8-56.4) percent. Prevalence of sufficient walking was increased by 1.20 (95% CrI 1.12-1.29) and 1.07 (95% CrI 1.01-1.13) for high and medium-high versus low walkability postal areas, and for sufficient MVPA by 1.05 (95% CrI 1.01-1.08) for high versus low walkability postal areas. Walkability was not related to high MVPA. Postal area walkability explained 65.8 and 47.4 percent of residual geographic variation in sufficient walking and sufficient MVPA not attributable to individual-level factors.

CONCLUSIONS

Walkability is associated with area-level prevalence and geographic variation in sufficient walking and sufficient MVPA to improve health in Sydney, Australia. Our study supports the use of walkability indexes at multiple spatial scales for informing population-level action to increase physical activity and the utility of spatial analysis for walkability research and planning.

Joint modelling of potentially avoidable hospitalisation for five diseases accounting for spatiotemporal effects: A case study in New South Wales, Australia

Background

Three variant formulations of a spatiotemporal shared component model are proposed that allow examination of changes in shared underlying factors over time.

Methods

Models are evaluated within the context of a case study examining hospitalisation rates for five chronic diseases for residents of a regional area in New South Wales: type II diabetes mellitus (DMII), chronic obstructive pulmonary disease (COPD), coronary arterial disease (CAD), hypertension (HT) and congestive heart failure (CHF) between 2001–2006. These represent ambulatory care sensitive (ACS) conditions, often used as a proxy for avoidable hospitalisations. Using a selected model, the effects of socio-economic status (SES) as a shared component are estimated and temporal patterns in the influence of the residual shared spatial component are examined.

Results

Choice of model depends upon the application. In the featured application, a model allowing for changing influence of the shared spatial component over time was found to have the best fit and was selected for further analyses. Hospitalisation rates were found to be increasing for COPD and DMII, decreasing for CHF and stable for CAD and HT. SES was substantively associated with hospitalisation rates, with differing degrees of influence for each disease. In general, most of the spatial variation in hospitalisation rates was explained by disease-specific spatial components, followed by the residual shared spatial component.

Conclusion

Appropriate selection of a joint disease model allows for the examination of temporal patterns of disease outcomes and shared underlying spatial factors, and distinction between different shared spatial factors.

Is short-term exposure to ambient fine particles associated with measles incidence in China? A multi-city study

BACKGROUND

China's rapid economic development has resulted in severe particulate matter (PM) air pollution and the control and prevention of infectious disease is an ongoing priority. This study examined the relationships between short-term exposure to ambient particles with aerodynamic diameter ≤2.5µm (PM_2.5) and measles incidence in China.

METHODS

Data on daily numbers of new measles cases and concentrations of ambient PM_2.5 were collected from 21 cities in China during Oct 2013 and Dec 2014. Poisson regression was used to examine city-specific associations of PM_2.5 and measles, with a constrained distributed lag model, after adjusting for seasonality, day of the week, and weather conditions. Then, the effects at the national scale were pooled with a random-effect meta-analysis.

RESULTS

A 10µg/m³ increase in PM_2.5 at lag 1day, lag 2day and lag 3day was significantly associated with increased measles incidence [relative risk (RR) and 95% confidence interval (CI) were 1.010 (1.003, 1.018), 1.010 (1.003, 1.016) and 1.006 (1.000, 1.012), respectively]. The cumulative relative risk of measles associated with PM_2.5 at lag 1-3 days was 1.029 (95% CI: 1.010, 1.048). Stratified analyses by meteorological factors showed that the PM_2.5 and measles associations were stronger on days with high temperature, low humidity, and high wind speed.

CONCLUSIONS

We provide new evidence that measles incidence is associated with exposure to ambient PM_2.5 in China. Effective policies to reduce air pollution may also reduce measles incidence.