Wood heater smoke and mortality in the Australian Capital Territory: a rapid health impact assessment.

OBJECTIVES: To estimate the number of deaths and the cost of deaths attributable to wood heater smoke in the Australian Capital Territory. STUDY DESIGN: Rapid health impact assessment, based on fine particulate matter (PM2.5 ) data from three outdoor air pollution monitors and published exposure-response functions for natural cause mortality attributed to PM2.5 exposure. SETTING: Australian Capital Territory (population, 2021: 454 000), 2016-2018, 2021, and 2022 (2019 and 2020 excluded because of the impact of extreme bushfires on air quality). MAIN OUTCOME MEASURES: Proportion of PM2.5 exposure attributable to wood heaters; numbers of deaths and associated cost of deaths (based on the value of statistical life: $5.3 million) attributable to wood heater smoke. RESULTS: Wood heater emissions contributed an estimated 1.16-1.73 µg/m3 to the annual mean PM2.5 concentration during the three colder years (2017, 2018, 2021), or 17-25% of annual mean exposure, and 0.72 µg/m3 (15%) or 0.89 µg/m3 (13%) during the two milder years (2016, 2022). Using the most conservative exposure-response function, the estimated annual number of deaths attributable to wood heater smoke was 17-26 during the colder three years and 11-15 deaths during the milder two years. Using the least conservative exposure-response function, an estimated 43-63 deaths per year (colder years) and 26-36 deaths per year (milder years) were attributable to wood heater smoke. The estimated annual equivalent cost of deaths was $57-136 million (most conservative exposure-response function) and $140-333 million (least conservative exposure-response function). CONCLUSIONS: The estimated annual number of deaths in the ACT attributable to wood heater PM2.5 pollution is similar to that attributed to the extreme smoke of the 2019-20 Black Summer bushfires. The number of wood heaters should be reduced by banning new installations and phasing out existing units in urban and suburban areas.

Effect of ambient air pollution on hospital admission for respiratory diseases in Hanoi children during 2007-2019.

Air pollution poses a threat to children's respiratory health. This study aims to quantify the association between short-term air pollution exposure and respiratory hospital admissions among children in Hanoi, Vietnam, and estimate the population-attributable burden using local data. A case-crossover analysis was conducted based on the individual records where each case is their own control. The health data was obtained from 13 hospitals in Hanoi and air pollution data was collected from four monitoring stations from 2007 to 2019. We used conditional logistic regression to estimate Percentage Change (PC) and 95% Confidence Interval (CI) in odd of hospital admissions per 10 µg/m3 increase in daily average particulate matter (e.g. PM1, PM2.5, PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), 8-h maximum Ozone and per 1000 µg/m3 increase in daily mean of Carbon Monoxide (CO). We also calculated the number and fraction of admissions attributed to air pollution in Hanoi by using the coefficient at lag 0. A 10 µg/m3 increase in the concentration of PM10, PM2.5, PM1, SO2, NO2, O3 8-h maximum and 1000 µg/m3 increase in CO concentration was associated with 0.6%, 1.2%, 1.4%, 0.8%, 1.6%, 0.3%, and 1.7% increase in odd of admission for all respiratory diseases among children under 16 years at lag 0-2. All PM metrics and NO2 are associated with childhood admission for pneumonia and bronchitis. Admissions due to asthma and upper respiratory diseases are related to increments in NO2 and CO. For attributable cases, PM2.5 concentrations in Hanoi exceeding the World Health Organization Air Quality Guidelines accounted for 1619 respiratory hospital admissions in Hanoi children in 2019. Our findings show that air pollution has a detrimental impact on the respiratory health of Hanoi children and there will be important health benefits from improved air quality management planning to reduce air pollution in Vietnam.

The burden of occupational injury attributable to high temperatures in Australia, 2014-19: a retrospective observational study.

OBJECTIVES: To assess the population health impact of high temperatures on workplace health and safety by estimating the burden of heat-attributable occupational injury in Australia. STUDY DESIGN, SETTING: Retrospective observational study; estimation of burden of occupational injury in Australia attributable to high temperatures during 2014-19, based on Safe Work Australia (work-related traumatic injury fatalities and workers' compensation databases) and Australian Institute of Health and Welfare data (Australian Burden of Disease Study and National Hospital Morbidity databases), and a meta-analysis of climate zone-specific risk data. MAIN OUTCOME MEASURE: Burden of heat-attributable occupational injuries as disability-adjusted life years (DALYs), comprising the numbers of years of life lived with disability (YLDs) and years of life lost (YLLs), nationally, by Köppen-Geiger climate zone, and by state and territory. RESULTS: During 2014-19, an estimated 42 884 years of healthy life were lost to occupational injury, comprising 39 485 YLLs (92.1%) and 3399 YLDs (7.9%), at a rate of 0.80 DALYs per 1000 workers per year. A total of 967 occupational injury-related DALYs were attributable to heat (2.3% of occupational injury-related DALYs), comprising 890 YLLs (92%) and 77 YLDs (8%). By climate zone, the heat-attributable proportion was largest in the tropical Am (12 DALYs; 3.5%) and Aw zones (34 DALYs; 3.5%); by state and territory, the proportion was largest in New South Wales and Queensland (each 2.9%), which also included the largest numbers of heat-attributable occupational injury-related DALYs (NSW: 379 DALYs, 39% of national total; Queensland: 308 DALYs; 32%). CONCLUSION: An estimated 2.3% of the occupational injury burden in Australia is attributable to high ambient temperatures. To prevent this burden increasing with global warming, adaptive measures and industry-based policies are needed to safeguard workplace health and safety, particularly in heat-exposed industries, such as agriculture, transport, and construction.

Maternal factors and risk of spontaneous preterm birth due to high ambient temperatures in New South Wales, Australia.

BACKGROUND: Exposure to high ambient temperatures has been shown to increase the risk of spontaneous preterm birth. Determining which maternal factors increase or decrease this risk will inform climate adaptation strategies. OBJECTIVES: This study aims to assess the risk of spontaneous preterm birth associated with exposure to ambient temperature and differences in this relationship between mothers with different health and demographic characteristics. METHODS: We used quasi-Poisson distributed lag non-linear models to estimate the effect of high temperature-measured as the 95th percentile of daily minimum, mean and maximum compared with the median-on risk of spontaneous preterm birth (23-36 weeks of gestation) in pregnant women in New South Wales, Australia. We estimated the cumulative lagged effects of daily temperature and analyses on population subgroups to assess increased or decreased vulnerability to this effect. RESULTS: Pregnant women (n = 916,678) exposed at the 95th percentile of daily mean temperatures (25ºC) had an increased risk of preterm birth (relative risk 1.14, 95% confidence interval 1.07, 1.21) compared with the median daily mean temperature (17℃). Similar effect sizes were seen for the 95th percentile of minimum and maximum daily temperatures compared with the median. This risk was slightly higher among women with diabetes, hypertension, chronic illness and women who smoked during pregnancy. CONCLUSIONS: Higher temperatures increase the risk of preterm birth and women with pre-existing health conditions and who smoke during pregnancy are potentially more vulnerable to these effects.

The impact of prolonged landscape fire smoke exposure on women with asthma in Australia.

BACKGROUND: Little is known about the physical and mental health impact of exposure to landscape fire smoke in women with asthma. This study examined the health impacts and information-seeking behaviours of women with asthma exposed to the 2019/2020 Australian fires, including women who were pregnant. METHODS: Women with asthma were recruited from the Breathing for Life Trial in Australia. Following the landscape fire exposure period, self-reported data were collected regarding symptoms (respiratory and non-respiratory), asthma exacerbations, wellbeing, quality of life, information seeking, and landscape fire smoke exposure mitigation strategies. Participants' primary residential location and fixed site monitoring was used to geolocate and estimate exposure to landscape fire-related fine Particulate Matter (PM2.5). RESULTS: The survey was completed by 81 pregnant, 70 breastfeeding and 232 non-pregnant and non-breastfeeding women with asthma. Participants had a median daily average of 17 µg/m3 PM2.5 and 105 µg/m3 peak PM2.5 exposure over the fire period (October 2019 to February 2020). Over 80% of participants reported non-respiratory and respiratory symptoms during the fire period and 41% reported persistent symptoms. Over 82% reported asthma symptoms and exacerbations of asthma during the fire period. Half the participants sought advice from a health professional for their symptoms. Most (97%) kept windows/doors shut when inside and 94% stayed indoors to minimise exposure to landscape fire smoke. Over two in five (43%) participants reported that their capacity to participate in usual activities was reduced due to prolonged smoke exposure during the fire period. Participants reported greater anxiety during the fire period than after the fire period (mean (SD) = 53(13) versus 39 (13); p < 0.001). Two in five (38%) pregnant participants reported having concerns about the effect of fire events on their pregnancy. CONCLUSION: Prolonged landscape fire smoke exposure during the 2019/2020 Australian fire period had a significant impact on the health and wellbeing of women with asthma, including pregnant women with asthma. This was despite most women taking actions to minimise exposure to landscape fire smoke. Effective and consistent public health messaging is needed during landscape fire events to guard the health of women with asthma.

The effects on mortality and the associated financial costs of wood heater pollution in a regional Australian city.

OBJECTIVES: To estimate the annual burden of mortality and the associated health costs attributable to air pollution from wood heaters in Armidale. DESIGN: Health impact assessment (excess annual mortality and financial costs) based upon atmospheric PM2.5 measurements. SETTING: Armidale, a regional Australian city (population, 24 504) with high levels of air pollution in winter caused by domestic wood heaters, 1 May 2018 - 30 April 2019. MAIN OUTCOME MEASURES: Estimated population exposure to PM2.5 from wood heaters; estimated numbers of premature deaths and years of life lost. RESULTS: Fourteen premature deaths (95% CI, 12-17 deaths) per year, corresponding to 210 (95% CI, 172-249) years of life lost, are attributable to long term exposure to wood heater PM2.5 pollution in Armidale. The estimated financial cost is $32.8 million (95% CI, $27.0-38.5 million), or $10 930 (95% CI, $9004-12 822) per wood heater per year. CONCLUSIONS: The substantial mortality and financial cost attributable to wood heating in Armidale indicates that effective policies are needed to reduce wood heater pollution, including public education about the effects of wood smoke on health, subsidies that encourage residents to switch to less polluting home heating (perhaps as part of an economic recovery package), assistance for those affected by wood smoke from other people, and regulations that reduce wood heater use (eg, by not permitting new wood heaters and requiring existing units to be removed when houses are sold).

The 2021 report of the MJA-Lancet Countdown on health and climate change: Australia increasingly out on a limb.

The MJA-Lancet Countdown on health and climate change in Australia was established in 2017, and produced its first national assessment in 2018, its first annual update in 2019, and its second annual update in 2020. It examines 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. Our special report in 2020 focused on the unprecedented and catastrophic 2019-20 Australian bushfire season, highlighting indicators that explore the relationships between health, climate change and bushfires. For 2021, we return to reporting on the full suite of indicators across each of the five domains and have added some new indicators. We find that Australians are increasingly exposed to and vulnerable to excess heat and that this is already limiting our way of life, increasing the risk of heat stress during outdoor sports, and decreasing work productivity across a range of sectors. Other weather extremes are also on the rise, resulting in escalating social, economic and health impacts. Climate change disproportionately threatens Indigenous Australians' wellbeing in multiple and complex ways. In response to these threats, we find positive action at the individual, local, state and territory levels, with growing uptake of rooftop solar and electric vehicles, and the beginnings of appropriate adaptation planning. However, this is severely undermined by national policies and actions that are contrary and increasingly place Australia out on a limb. Australia has responded well to the COVID-19 public health crisis (while still emerging from the bushfire crisis that preceded it) and it now needs to respond to and prepare for the health crises resulting from climate change.

The 2020 special report of the MJA-Lancet Countdown on health and climate change: lessons learnt from Australia's "Black Summer".

The MJA-Lancet Countdown on health and climate change was established in 2017, and produced its first Australian national assessment in 2018 and its first annual update in 2019. It examines 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. In the wake of the unprecedented and catastrophic 2019-20 Australian bushfire season, in this special report we present the 2020 update, with a focus on the relationship between health, climate change and bushfires, highlighting indicators that explore these linkages. In an environment of continuing increases in summer maximum temperatures and heatwave intensity, substantial increases in both fire risk and population exposure to bushfires are having an impact on Australia's health and economy. As a result of the "Black Summer" bushfires, the monthly airborne particulate matter less than 2.5 µm in diameter (PM2.5 ) concentrations in New South Wales and the Australian Capital Territory in December 2019 were the highest of any month in any state or territory over the period 2000-2019 at 26.0 µg/m3 and 71.6 µg/m3 respectively, and insured economic losses were $2.2 billion. We also found growing awareness of and engagement with the links between health and climate change, with a 50% increase in scientific publications and a doubling of newspaper articles on the topic in Australia in 2019 compared with 2018. However, despite clear and present need, Australia still lacks a nationwide adaptation plan for health. As Australia recovers from the compounded effects of the bushfires and the coronavirus disease 2019 (COVID-19) pandemic, the health profession has a pivotal role to play. It is uniquely suited to integrate the response to these short term threats with the longer term public health implications of climate change, and to argue for the economic recovery from COVID-19 to align with and strengthen Australia's commitments under the Paris Agreement.

Ambient air pollution exposure association with diabetes prevalence and glycosylated hemoglobin (HbA1c) levels in China. Cross-sectional analysis from the WHO study of AGEing and adult health wave 1.

Over the past decades, air pollution has become one of the critical environmental health issues in China. The present study aimed to evaluate links between ambient air pollution and the prevalence of type 2 diabetes mellitus (T2DM) and the levels of glycosylated hemoglobin (HbA1c). A multilevel linear and logistic regression was used to assess these associations among 7,770 participants aged ≥50 years from the WHO Study on global AGEing and adult health (SAGE) in China in 2007-2010. The average exposure to each of pollutants (particulate matter with an aerodynamic diameter of ≤10 µm/≤2.5 µm/≤1 µm [PM10/PM2.5/PM1] and nitrogen dioxide [NO2]) was estimated using a satellite-based spatial statistical model. In logistic models, a 10 µg/m3 increase in PM10 and PM2.5 was associated with increased T2DM prevalence (Prevalence Odds Ratio, POR: 1.27; 95% CI: 1.11, 1.45 and POR: 1.23; 95% CI: 1.03, 1.46). Similar increments in PM10, PM2.5, PM1 and NO2 were associated with increase in HbA1c levels of 1.8% (95% CI: 1.3, 2.3), 1.3% (95% CI: 1.1, 1.5), 0.7% (95% CI: 0.1, 1.3), and 0.8% (95% CI: 0.4, 1.2), respectively. In a large cohort of older Chinese adults, air pollution was liked to both higher T2DM prevalence and elevated HbA1c levels.

Ambient Particulate Matter and Paramedic Assessments of Acute Diabetic, Cardiovascular, and Respiratory Conditions.

BACKGROUND: Ambulance data provide a useful source of population-based and spatiotemporally resolved information for assessing health impacts of air pollution in nonhospital settings. We used the clinical records of paramedics to quantify associations between particulate matter (PM2.5) and diabetic, cardiovascular, and respiratory conditions commonly managed by those responding to calls for emergency ambulance services. METHODS: We evaluated 394,217 paramedic assessments from three states in Southeastern Australia (population 13.2 million) and daily PM2.5 concentrations modeled at 5 km resolution from 2009 to 2014. We used a time-stratified, case-crossover analysis adjusted for daily meteorology to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for each clinical outcome per 10 µg/m increase in daily PM2.5 at lags from 0 to 2 days. RESULTS: Increased PM2.5 was associated with increased odds of paramedic assessments of hypoglycemia (OR = 1.07; 95% CI = 1.02, 1.12, lag 0), arrhythmia (OR = 1.05; 95% CI = 1.02, 1.09, lag 0), heart failure (OR = 1.07; 95% CI = 1.02, 1.12, lag 1), faint (OR = 1.09; 95% CI = 1.04-1.13, lag 0), asthma (OR = 1.06; 95% CI = 1.01, 1.11, lag 1), chronic obstructive pulmonary disease (OR = 1.07; 95% CI = 1.01, 1.13, lag 1), and croup (OR = 1.09; 95% CI = 1.02, 1.17). We did not identify associations with cerebrovascular outcomes. CONCLUSIONS: Ambulance data enable the evaluation of important clinical syndromes that are often initially managed in nonhospital settings. Daily PM2.5 was associated with hypoglycemia, faint, and croup in addition to the respiratory and cardiovascular outcomes that are better established.

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 (PM2.5) 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 PM2.5 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 PM2.5. Overall, results were higher than those obtained for a typical PM2.5 mixture.

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.

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, PM2.5). Few comparable regions are available to evaluate the utility of continental-scale land-use regression (LUR) models including global geophysical estimates of PM2.5, derived by relating satellite-observed aerosol optical depth to ground-level PM2.5 ("SAT-PM2.5"). We aimed to determine the validity of such satellite-based LUR models for PM2.5 in Australia. We used global SAT-PM2.5 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-PM2.5 predictor variable (and six others) explained the most spatial variability in PM2.5 (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-PM2.5 estimate alone was 0.26 (RMSE: 3.97 [56%]). SAT-PM2.5 estimates improved LUR model performance, while local land-use predictors increased the utility of global SAT-PM2.5 estimates, including enhanced characterization of within-city gradients. Our findings support the validity of continental-scale satellite-based LUR modeling for PM2.5 exposure assessment in Australia.

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.

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.

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.

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 (PM2.5) and measles incidence in China. METHODS: Data on daily numbers of new measles cases and concentrations of ambient PM2.5 were collected from 21 cities in China during Oct 2013 and Dec 2014. Poisson regression was used to examine city-specific associations of PM2.5 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 PM2.5 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 PM2.5 at lag 1-3 days was 1.029 (95% CI: 1.010, 1.048). Stratified analyses by meteorological factors showed that the PM2.5 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 PM2.5 in China. Effective policies to reduce air pollution may also reduce measles incidence.

The distribution of maternity services across rural and remote Australia: does it reflect population need?

BACKGROUND: Australia has a universal health care system and a comprehensive safety net. Despite this, outcomes for Australians living in rural and remote areas are worse than those living in cities. This study will examine the current state of equity of access to birthing services for women living in small communities in rural and remote Australia from a population perspective and investigates whether services are distributed according to need. METHODS: Health facilities in Australia were identified and a service catchment was determined around each using a one-hour road travel time from that facility. Catchment exclusions: metropolitan areas, populations above 25,000 or below 1,000, and a non-birthing facility within the catchment of one with birthing. Catchments were attributed with population-based characteristics representing need: population size, births, demographic factors, socio-economic status, and a proxy for isolation - the time to the nearest facility providing a caesarean section (C-section). Facilities were dichotomised by service level - those providing birthing services (birthing) or not (no birthing). Birthing services were then divided by C-section provision (C-section vs no C-section birthing). Analysis used two-stage univariable and multivariable logistic regression. RESULTS: There were 259 health facilities identified after exclusions. Comparing services with birthing to no birthing, a population is more likely to have a birthing service if they have more births, (adjusted Odds Ratio (aOR): 1.50 for every 10 births, 95% Confidence Interval (CI) [1.33-1.69]), and a service offering C-sections 1 to 2 h drive away (aOR: 28.7, 95% CI [5.59-148]). Comparing the birthing services categorised by C-section vs no C-section, the likelihood of a facility having a C-section was again positively associated with increasing catchment births and with travel time to another service offering C-sections. Both models demonstrated significant associations with jurisdiction but not socio-economic status. CONCLUSIONS: Our investigation of current birthing services in rural and remote Australia identified disparities in their distribution. Population factors relating to vulnerability and isolation did not increase the likelihood of a local birthing facility, and very remote communities were less likely to have any service. In addition, services are influenced by jurisdictions.