Projecting Future Heat-Related Mortality under Climate Change Scenarios: A Systematic Review

Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality

Ambient Temperature and Morbidity: A Review of Epidemiological Evidence

Objective: In this paper, we review the epidemiological evidence on the relationship between ambient temperature and morbidity. We assessed the methodological issues in previous studies and proposed future research directions

Tobacco smoking changes during the first pre-vaccination phases of the COVID-19 pandemic: A systematic review and meta-analysis

Background: Globally, tobacco smoking remains the largest preventable cause of premature death. The COVID-19 pandemic has forced nations to take unprecedented measures, including ‘lockdowns’ that might impact tobacco smoking behaviour. We performed a systematic review and meta-analyses to assess smoking behaviour changes during the early pre-vaccination phases of the COVID-19 pandemic in 2020. Methods: We searched Medline/Embase/PsycINFO/BioRxiv/MedRxiv/SSRN databases (January–November 2020) for published and pre-print articles that reported specific smoking behaviour changes or intentions after the onset of the COVID-19 pandemic. We used random-effects models to pool prevalence ratios comparing the prevalence of smoking during and before the pandemic, and the prevalence of smoking behaviour changes during the pandemic. The PROSPERO registration number for this systematic review was CRD42020206383. Findings: 31 studies were included in meta-analyses, with smoking data for 269,164 participants across 24 countries. The proportion of people smoking during the pandemic was lower than that before, with a pooled prevalence ratio of 0·87 (95%CI:0·79–0·97). Among people who smoke, 21% (95%CI:14–30%) smoked less, 27% (95%CI:22–32%) smoked more, 50% (95%CI:41%-58%) had unchanged smoking and 4% (95%CI:1–9%) reported quitting smoking. Among people who did not smoke, 2% (95%CI:1–3%) started smoking during the pandemic. Heterogeneity was high in all meta-analyses and so the pooled estimates should be interpreted with caution (I2\u3e91% and p-heterogeneity\u3c0·001). Almost all studies were at high risk of bias due to use of non-representative samples, non-response bias, and utilisation of non-validated questions. Interpretation: Smoking behaviour changes during the first phases of the COVID-19 pandemic in 2020 were highly mixed. Meta-analyses indicated that there was a relative reduction in overall smoking prevalence during the pandemic, while similar proportions of people who smoke smoked more or smoked less, although heterogeneity was high. Implementation of evidence-based tobacco control policies and programs, including tobacco cessation services, have an important role in ensuring that the COVID-19 pandemic does not exacerbate the smoking pandemic and associated adverse health outcomes

Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure

Admission to hospital for effects of heat and light: NSW, 1993-94 to 2003-04

The study examined the hospital admission rates and characteristics of patients experiencing severe heat-related morbidity in NSW using data from the NSW Health Inpatient Statistics Collection. The study covered the 11-year period from July 1993 to June 2004. ICD-10-AM. codes examined included T67 (effects of heat and light). There was an average of 91 admissions for each year due to a principal diagnosis of the effects of heat and light, with consistently more males than females admitted (1.7 : 1). Many of the admissions (39%) were of people 65 years of age or older. Most admissions (49%) occurred in the summer months of December and January.6 page(s

Approaches to baseline studies of human health in relation to industries with potential environmental impact

A number of health concerns have been raised in relation to coal seam gas (CSG) mining in Australia. Very few studies have been conducted to investigate the potential health risks related to CSG industry internationally and in Australia. Health risks may be associated with all stages of CSG extraction (exploration, production and post-production), with possible exposures via water, soil and air pollution. The adverse health outcomes may include respiratory, cardiovascular, genitourinary and digestive diseases, skin problems, some types of cancer, injuries, hormonal disruption, fertility and reproductive effects. Concerns about poorer mental health associated with environmental, economic and social changes in the mining communities have also been raised. We discuss the potential health risks of the various types of exposures during each stage of CSG production. We then review epidemiological study designs aimed at identifying associations between environmental exposures (such as those that may occur during coal seam gas mining activity) and health outcomes, and we discuss the strengths and limitations of each study type. We identify four possible designs – and their key data sources– that could be used to examine potential health risks related to the mining of coal seam gas in New South Wales

Cause-specific hospital admissions on hot days in Sydney, Australia

Background While morbidity outcomes for major disease categories during extreme heat have received increasing research attention, there has been very limited investigation at the level of specific disease subcategories. Methodology/Principal Findings We analyzed daily hospital admissions for cardiovascular (CVD), respiratory (RD), genitourinary (GU) and mental diseases (MD), diabetes (DIA), dehydration (DEH) and ‘the effects of heat and light’ (HEAT) in Sydney between 1991 and 2009. We further investigated the sensitivity to heat of subcategories within the major disease groups. We defined hot days as those with temperatures in the 95th and 99th percentiles within the study period. We applied time-stratified case-crossover analysis to compare the hospital admissions on hot days with those on non-hot days matched by day of the week. We calculated the odds ratios (OR) of admissions between the two types of days, accounting for other environmental variables (relative humidity, ozone and particulate matter) and non-environmental trends (public and school holidays). On hot days, hospital admissions increased for all major categories except GU. This increase was not shared homogeneously across all diseases within a major category: within RD, only ‘other diseases of the respiratory system’ (includes pleurisy or empyema) increased significantly, while admissions for asthma decreased. Within MD, hospital admissions increased only for psychoses. Admissions due to some major categories increased one to three days after a hot day (e.g., DIA, RD and CVD) and on two and three consecutive days (e.g., HEAT and RD). Conclusions/Significance High ambient temperatures were associated with increased hospital admissions for several disease categories, with some within-category variation. Future analyses should focus on subgroups within broad disease categories to pinpoint medical conditions most affected by ambient heat

Approaches to baseline studies of human health in relation to industries with potential environmental impact: Contribution to the independent review of coal seam gas activities in NSW

A number of health concerns have been raised in relation to coal seam gas (CSG) mining in Australia. Very few studies have been conducted to investigate the potential health risks related to CSG industry internationally and in Australia. Health risks may be associated with all stages of CSG extraction (exploration, production and post-production), with possible exposures via water, soil and air pollution. The adverse health outcomes may include respiratory, cardiovascular, genitourinary and digestive diseases, skin problems, some types of cancer, injuries, hormonal disruption, fertility and reproductive effects. Concerns about poorer mental health associated with environmental, economic and social changes in the mining communities have also been raised. We discuss the potential health risks of the various types of exposures during each stage of CSG production. We then review epidemiological study designs aimed at identifying associations between environmental exposures (such as those that may occur during coal seam gas mining activity) and health outcomes, and we discuss the strengths and limitations of each study type. We identify four possible designs – and their key data sources– that could be used to examine potential health risks related to the mining of coal seam gas in New South Wales

Location of the Sydney Statistical Division.

<p>Location of the Sydney Statistical Division.</p

Odds ratios (adjusted for relative humidity, O₃ and PM₁₀) comparing hospital admissions due to several specific diseases between extremely hot days and control days in the Sydney Statistical Division between July 1^st, 1991 and June 30^th, 2009; on a hot day and 1, 2, and 3 days after the hot day at the <i>99^th percentile</i> of average temperature (results shown after the FDR adjustment). Note: the x-axis scale for admissions on hot days is different.

<p>Odds ratios (adjusted for relative humidity, O₃ and PM₁₀) comparing hospital admissions due to several specific diseases between extremely hot days and control days in the Sydney Statistical Division between July 1^st, 1991 and June 30^th, 2009; on a hot day and 1, 2, and 3 days after the hot day at the <i>99^th percentile</i> of average temperature (results shown after the FDR adjustment). Note: the x-axis scale for admissions on hot days is different.</p