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

Tobacco smoke is a known carcinogen, but the magnitude of smoking‐related cancer risk depends on country‐specific, generational smoking patterns. We quantified cancer risk in relation to smoking in a population‐based cohort, the 45 and Up Study (2006‐2009) in New South Wales, Australia. Cox proportional hazards regressions estimated adjusted hazard ratios (HR) by self‐reported smoking history at baseline (2006‐2009) for incident, primary cancers via linkage to cancer registry data to 2013 and cancer death data to 2015. Among 229 028 participants aged ≥45 years, 18 475 cancers and 5382 cancer deaths occurred. Current‐smokers had increased risks of all cancers combined (HR = 1.42, 95% confidence interval [CI], 1.34‐1.51), cancers of the lung (HR = 17.66, 95%CI, 14.65‐21.29), larynx (HR = 11.29, 95%CI, 5.49‐23.20), head‐and‐neck (HR = 2.53, 95%CI, 1.87‐3.41), oesophagus (HR = 3.84, 95%CI, 2.33‐6.35), liver (HR = 4.07, 95%CI, 2.55‐6.51), bladder (HR = 3.08, 95%CI, 2.00‐4.73), pancreas (HR = 2.68, 95%CI, 1.93‐3.71), colorectum (HR = 1.31, 95%CI, 1.09‐1.57) and unknown primary site (HR = 3.26, 95%CI, 2.19‐4.84) versus never‐smokers. Hazards increased with increasing smoking intensity; compared to never‐smokers, lung cancer HR = 9.22 (95%CI, 5.14‐16.55) for 1‐5 cigarettes/day and 38.61 (95%CI, 25.65‐58.13) for >35 cigarettes/day. Lung cancer risk was lower with quitting at any age but remained higher than never‐smokers for quitters aged >25y. By age 80y, an estimated 48.3% of current‐smokers (41.1% never‐smokers) will develop cancer, and 14% will develop lung cancer, including 7.7% currently smoking 1‐5 cigarettes/day and 26.4% for >35 cigarettes/day (1.0% never‐smokers). Cancer risk for Australian smokers is significant, even for 'light' smokers. These contemporary estimates underpin the need for continued investment in strategies to prevent smoking uptake and facilitate cessation, which remain key to reducing cancer morbidity and mortality worldwide. [ABSTRACT FROM AUTHOR]

The aim of our study was to quantify sex-specific patterns of smoking prevalence and initiation in 10-year birth cohorts from 1910 to 1989 in Australia. We combined individual data of 385,810 participants from 33 cross-sectional surveys conducted between 1962 and 2018. We found that age-specific smoking prevalence varied considerably between men and women within birth cohorts born before 1960. The largest difference was observed in the earliest cohort (1910–1919), with up to 37.7% point greater proportion of current smokers in men than in women. In subsequent cohorts, the proportion decreased among men, but increased among women, until there was no more than 7.4% point difference in the 1960–69 birth cohort. In the 1970–79 and 1980–89 cohorts, smoking among men marginally increased, but the proportion was at most ~11.0% points higher than women. Our analysis of initiation indicated that many women born before the 1930s who smoked commenced smoking after age 25 years (e.g., ~27% born in 1910–19); compared to at most 8% of men in any birth cohort. The earliest birth cohort (1910–1919) had the greatest difference in age at initiation between sexes; 26.6 years in women versus 19.0 in men. In later cohorts, male and female smokers initiated increasingly earlier, converging in the 1960–69 cohort (17.6 and 17.8 years, respectively). While 22.9% of men and 8.4% of women initiated smoking aged < = 15 in the 1910–1919 cohort, in the latest cohort (1980–89) the reverse was true (21.4% and 28.8% for men and women, respectively). Marked differences in smoking prevalence and age at initiation existed between birth cohorts of Australian men and women born before 1960; after this, sex-specific trends in prevalence and initiation were similar. Understanding these patterns may inform the evaluation of tobacco control policies and the targeting of potential interventions for exposed populations such as lung cancer screening. [ABSTRACT FROM AUTHOR]

Background Globally, tobacco smoking remains the largest 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 phases of the COVID-19 pandemic. 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 smokers during and before the pandemic, and the prevalence of smoking behaviour changes. Results 33 studies were included in meta-analyses, with smoking data for ∼230,000 participants across 24 countries. The proportions of smokers during and before the pandemic were similar, with a pooled prevalence ratio 0.85 (95%CI:0.76-0.95). In studies limited to smokers, 27% (95%CI:21-32%) smoked more, 17% (95%CI:13-21%) smoked less, 54% (95%CI:47-61%) smoked the same and 5% (95%CI:2-9%) reported quitting smoking. Among all participants, 1% (95%CI:0-2%) started smoking during the pandemic. All studies were at high risk of bias due to use of non-representative samples, likely non-response bias, and utilisation of non-validated questions. Conclusions Smoking behaviour changes during the early phases of the COVID-19 pandemic were highly mixed. Meta-analyses indicated slightly lower overall smoking prevalence during the pandemic, but higher intensity among smokers. Key messages More recent and higher quality studies of smoking behaviour changes are required to measure the longer term impact of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Simulation models of smoking behaviour provide vital forecasts of exposure to inform policy targets, estimates of the burden of disease, and impacts of tobacco control interventions. A key element of useful model-based forecasts is a clear picture of uncertainty due to the data used to inform the model, however, assessment of this parameter uncertainty is incomplete in almost all tobacco control models. As a remedy, we demonstrate a Bayesian approach to model calibration that quantifies parameter uncertainty. With a model calibrated to Australian data, we observed that the smoking cessation rate in Australia has increased with calendar year since the late 20th century, and in 2016 people who smoked would quit at a rate of 4.7 quit-events per 100 person-years (90% equal-tailed interval (ETI): 4.5–4.9). We found that those who quit smoking before age 30 years switched to reporting that they never smoked at a rate of approximately 2% annually (90% ETI: 1.9–2.2%). The Bayesian approach demonstrated here can be used as a blueprint to model other population behaviours that are challenging to measure directly, and to provide a clearer picture of uncertainty to decision-makers. [ABSTRACT FROM AUTHOR]

Background Tobacco smoke is a known carcinogen and the magnitude of smoking-related cancer risk varies according to time and population. Local, contemporary evidence can drive appropriate tobacco control. We provide comprehensive cancer risk estimates related to smoking in the population-based, New South Wales (NSW) 45 and Up Study. Methods We estimated smoking-related hazard ratios (HR) for cancer using Cox proportional hazards regression using linked questionnaire (2006-2009) and incident cancer data (n ≥ 50 cases per cancer type), from the NSW Cancer Registry (to December 2013) (via CHeReL). Results Of 18,475 cancers among 229,028 participants aged ≥45 years, current smokers had significantly increased risks of cancers of the lung, larynx, head and neck, oesophagus, liver, bladder, pancreas, stomach, colorectum, and cancers with unknown primary site, compared to never-smokers; lung cancer risk was markedly elevated, including for current-smokers of 1-5 cigarettes/day (HR = 9.25, 95%CI=5.2-16.6), increasing to 38.39 (26.2-56.2) for current-smokers of > 30 cigarettes/day. Quitting substantively decreased cancer risk compared to continued smoking, with lung cancer risk decreasing with decreasing age at quitting (p(trend)<0.05), however risks remained elevated for those quitting aged >25 compared to never-smokers (1.73, 1.1-2.6 for age 26-30 years). An estimated 20% of current-smokers in Australia will get lung cancer during their lifetime versus 1.6% of never-smokers. Conclusions Smoking-attributable cancer risks in Australia are significant, comparable to contemporary risks from other developed nations. Key messages Smokers – including "light" smokers – are at high cancer risk, with ∼one-fifth of Australian lifetime smokers developing lung cancer. Quitting is beneficial. Continued investment in tobacco control is essential. [ABSTRACT FROM AUTHOR]

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.