Fifty-year forecasts of daily smoking prevalence: can Australia reach 5% by 2030?

OBJECTIVE: To compare 50-year forecasts of Australian tobacco smoking rates in relation to trends in smoking initiation and cessation and in relation to a national target of ≤5% adult daily prevalence by 2030. METHODS: A compartmental model of Australian population daily smoking, calibrated to the observed smoking status of 229 523 participants aged 20-99 years in 26 surveys (1962-2016) by age, sex and birth year (1910-1996), estimated smoking prevalence to 2066 using Australian Bureau of Statistics 50-year population predictions. Prevalence forecasts were compared across scenarios in which smoking initiation and cessation trends from 2017 were continued, kept constant or reversed. RESULTS: At the end of the observation period in 2016, model-estimated daily smoking prevalence was 13.7% (90% equal-tailed interval (EI) 13.4%-14.0%). When smoking initiation and cessation rates were held constant, daily smoking prevalence reached 5.2% (90% EI 4.9%-5.5%) after 50 years, in 2066. When initiation and cessation rates continued their trajectory downwards and upwards, respectively, daily smoking prevalence reached 5% by 2039 (90% EI 2037-2041). The greatest progress towards the 5% goal came from eliminating initiation among younger cohorts, with the target met by 2037 (90% EI 2036-2038) in the most optimistic scenario. Conversely, if initiation and cessation rates reversed to 2007 levels, estimated prevalence was 9.1% (90% EI 8.8%-9.4%) in 2066. CONCLUSION: A 5% adult daily smoking prevalence target cannot be achieved by the year 2030 based on current trends. Urgent investment in concerted strategies that prevent smoking initiation and facilitate cessation is necessary to achieve 5% prevalence by 2030.

Updated cost-effectiveness analysis of lung cancer screening for Australia, capturing differences in the health economic impact of NELSON and NLST outcomes.

BACKGROUND: A national, lung cancer screening programme is under consideration in Australia, and we assessed cost-effectiveness using updated data and assumptions. METHODS: We estimated the cost-effectiveness of lung screening by applying screening parameters and outcomes from either the National Lung Screening Trial (NLST) or the NEderlands-Leuvens Longkanker Screenings ONderzoek (NELSON) to Australian data on lung cancer risk, mortality, health-system costs, and smoking trends using a deterministic, multi-cohort model. Incremental cost-effectiveness ratios (ICERs) were calculated for a lifetime horizon. RESULTS: The ICER for lung screening compared to usual care in the NELSON-based scenario was AU$39,250 (95% CI $18,150-108,300) per quality-adjusted life year (QALY); lower than the NLST-based estimate (ICER = $76,300, 95% CI $41,750-236,500). In probabilistic sensitivity analyses, lung screening was cost-effective in 15%/60% of NELSON-like simulations, assuming a willingness-to-pay threshold of $30,000/$50,000 per QALY, respectively, compared to 0.5%/6.7% for the NLST. ICERs were most sensitive to assumptions regarding the screening-related lung cancer mortality benefit and duration of benefit over time. The cost of screening had a larger impact on ICERs than the cost of treatment, even after quadrupling the 2006-2016 healthcare costs of stage IV lung cancer. DISCUSSION: Lung screening could be cost-effective in Australia, contingent on translating trial-like lung cancer mortality benefits to the clinic.

Health utilities for participants in a population-based sample who meet eligibility criteria for lung cancer screening.

INTRODUCTION: Trial-based, risk-targeted lung cancer screening with low-dose computed tomography has been shown to reduce lung cancer mortality but implementation may depend on favourable cost-effectiveness evaluations where quality-adjusted life-years are a key metric. Baseline health utility values for a screening population at high risk of lung cancer are not likely to match age-specific population norms, and utilities derived from screening trials may not be representative of real-world screening populations. We estimated utility values for screening-eligible individuals in a population-based cohort study in Australia. METHODS: Cancer-free participants aged 50-80 years in the New South Wales 45 and Up Study completed the 12-Item Short Form Survey (2010-2011). Mean SF-6D utility values were calculated for 19,991 participants and compared across screening criteria defined by the US Preventive Services Task Force (USPSTF-2021/2013), NELSON trial eligibility, and the PLCOm2012 risk tool. RESULTS: Mean SF-6D utility values were comparable across screening criteria: USPSTF-2021, 0.772 (95%CI, 0.768-0.776); USPSTF-2013, 0.764 (95%CI, 0.759-0.770); NELSON, 0.768 (95%CI, 0.763-0.774), and were each lower than among ineligible participants (0.810-0.814). While there was a decline in utilities with increasing risk of lung cancer as measured with the PLCOm2012 risk tool, mean utility values for those with ≥ 1.51% 6-year risk did not differ to other criteria (0.772, 95%CI, 0.767-0.776). CONCLUSION: Risk criteria are necessary for the efficiency of lung cancer screening programs, but they select populations with lower mean health utilities than population norms. We provide baseline values that can be used in cost-effectiveness evaluations of risk-targeted lung cancer screening.

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 >91% and p-heterogeneity<0·001). 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. Funding: No specific funding was received for this study.

Evaluating Prognostic Factors for Sex Differences in Lung Cancer Survival: Findings From a Large Australian Cohort.

INTRODUCTION: Women tend to survive a lung cancer diagnosis longer than men; however potential drivers of this sex-related disparity remain largely elusive. We quantified factors related to sex differences in lung cancer survival in a large prospective cohort in Australia. METHODS: Participants in the 45 and Up Study (recruited 2006-2009) diagnosed with incident lung cancer were followed up to December 2015. Prognostic factors were identified from questionnaire data linked with cancer registrations, hospital inpatient records, emergency department records, and reimbursement records for government-subsidized medical services and prescription medicines. Hazard ratios (HRs) and 95% confidence intervals (CIs) for lung cancer death for men versus women were estimated using Cox proportional hazard regression in relation to key prognostic factors alone and jointly. RESULTS: A total of 488 women and 642 men were diagnosed with having lung cancer. Women survived significantly longer (median 1.28 versus 0.77 y; HR for men = 1.43, 95% CI: 1.25-1.64, p < 0.0001). The survival disparity remained when each subgroup of major prognostic factors was evaluated separately, including histologic subtype, stage at diagnosis, treatment received, and smoking status. Multivariable analyses revealed that treatment-related factors explained half of the survival difference, followed by lifestyle and tumor characteristics (explaining 28%, 26%, respectively). After adjusting for all major known prognostic factors, the excess risk for men was reduced by more than 80% (HR = 1.06, 95% CI: 0.96-1.18, p = 0.26). CONCLUSIONS: The sex-related lung cancer survival disparity in this Australian cohort was largely accounted for by known prognostic factors, indicating an opportunity to explore sex differences in treatment preferences, options, and access.

Cancer incidence and cancer death in relation to tobacco smoking in a population-based Australian cohort study.

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.

Birth-cohort estimates of smoking initiation and prevalence in 20th century Australia: Synthesis of data from 33 surveys and 385,810 participants.

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.

Association between density and proximity of tobacco retail outlets with smoking: A systematic review of youth studies.

BACKGROUND: Reducing the retail availability of tobacco has been proposed as a component of tobacco endgame, yet it is not known whether retail availability has a direct impact on smoking behaviours. A narrative review and a meta-analysis have been undertaken to examine the density and proximity of tobacco retail outlets, but were limited in scope, exposure and outcome variables. The aim of this current study was to undertake a systematic review of the international literature on the density and proximity of tobacco retail outlets to homes, schools and communities and their association with smoking behaviours among youth. METHODS: We reviewed and critically appraised the evidence documenting the association between density or proximity of tobacco retail outlets and smoking behaviours among school-age youth (18 and under), between 1 January 1990 and 21 October 2019. We reviewed original quantitative research that examined the associations of tobacco retail outlet density and proximity with individual smoking status or population-level smoking prevalence; initiation of smoking; frequency of tobacco use; sales to minors; purchasing by minors; susceptibility to smoking among non-smokers; perceived prevalence of smoking, and quitting behaviours. FINDINGS: Thirty-five peer-reviewed papers met the inclusion criteria. This review provided evidence of a relationship between density of tobacco retail outlets and smoking behaviours, particularly for the density near youths' home. A study using activity spaces also found a significant positive association between exposure to tobacco retail outlets and daily tobacco use. The review did not provide evidence of an association between the proximity of tobacco retail outlets to homes or schools and smoking behaviours among youth. CONCLUSIONS: The existing evidence supports a positive association between tobacco retail outlet density and smoking behaviours among youth, particularly for the density near youths' home. This review provides evidence for the development and implementation of policies to reduce the density of tobacco retail outlets to reduce smoking prevalence among youth.

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 95(th) and 99(th) 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.

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. DATA SOURCES AND DATA EXTRACTION: We searched the PubMed database for epidemiological studies on ambient temperature and morbidity of noncommunicable diseases published in refereed English journals before 30 June 2010. Forty relevant studies were identified. Of these, 24 examined the relationship between ambient temperature and morbidity, 15 investigated the short-term effects of heat wave on morbidity, and 1 assessed both temperature and heat wave effects. DATA SYNTHESIS: Descriptive and time-series studies were the two main research designs used to investigate the temperature-morbidity relationship. Measurements of temperature exposure and health outcomes used in these studies differed widely. The majority of studies reported a significant relationship between ambient temperature and total or cause-specific morbidities. However, there were some inconsistencies in the direction and magnitude of nonlinear lag effects. The lag effect of hot temperature on morbidity was shorter (several days) compared with that of cold temperature (up to a few weeks). The temperature-morbidity relationship may be confounded or modified by sociodemographic factors and air pollution. CONCLUSIONS: There is a significant short-term effect of ambient temperature on total and cause-specific morbidities. However, further research is needed to determine an appropriate temperature measure, consider a diverse range of morbidities, and to use consistent methodology to make different studies more comparable.

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. OBJECTIVES: We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios. DATA SOURCES AND EXTRACTION: A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 through July 2010. DATA SYNTHESIS: Fourteen studies fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding historical temperature-mortality relationships and considering the future changes in climate, population, and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution, and mortality displacement. CONCLUSIONS: Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality.

Constraints and barriers to public health adaptation to climate change: a review of the literature.

Public health adaptation to climate change is an important issue and inevitably is needed to address the adverse health impacts of climate change over the next few decades. This paper provides an overview of the constraints and barriers to public health adaptation and explores future research directions in this emerging field. An extensive literature review was conducted in 2010 and published literature from 2000 to 2010 was retrieved. This review shows that public health adaptation essentially can operate at two levels, namely, adaptive-capacity building and implementation of adaptation actions. However, there are constraints and barriers to public health adaptation arising from uncertainties of future climate and socioeconomic conditions, as well as financial, technologic, institutional, social capital, and individual cognitive limits. The opportunities for planning and implementing public health adaptation are reliant on effective strategies to overcome these constraints and barriers. It is proposed here that high research priority should be given to multidisciplinary research on the assessment of potential health impacts of climate change, projections of health impacts under different climate and socioeconomic scenarios, identification of health co-benefits of mitigation strategies, and evaluation of cost-effective public health adaptation options.

Is the association between temperature and mortality modified by age, gender and socio-economic status?

BACKGROUND: A number of studies have examined the relationship between high ambient temperature and mortality. Recently, concern has arisen about whether this relationship is modified by socio-demographic factors. However, data for this type of study is relatively scarce in subtropical/tropical regions where people are well accustomed to warm temperatures. OBJECTIVE: To investigate whether the relationship between daily mean temperature and daily all-cause mortality is modified by age, gender and socio-economic status (SES) in Brisbane, Australia. METHODS: We obtained daily mean temperature and all-cause mortality data for Brisbane, Australia during 1996-2004. A generalised additive model was fitted to assess the percentage increase in all deaths with every one degree increment above the threshold temperature. Different age, gender and SES groups were included in the model as categorical variables and their modification effects were estimated separately. RESULTS: A total of 53,316 non-external deaths were included during the study period. There was a clear increasing trend in the harmful effect of high temperature on mortality with age. The effect estimate among women was more than 20 times that among men. We did not find an SES effect on the percent increase associated with temperature. CONCLUSIONS: The effects of high temperature on all deaths were modified by age and gender but not by SES in Brisbane, Australia.

Spatial analysis of heat-related mortality among the elderly between 1993 and 2004 in Sydney, Australia.

This study analyzed the geographical patterns of heat-related mortality among the population aged 65 and over within the metropolitan area of Sydney, Australia between 1993 and 2004, and evaluated the role of some physical and socio-demographic risk factors associated with it. The effect of temperature on all-cause mortality during unusually hot days was investigated using spatial analytic techniques, such as cluster analysis and spatial regression analysis. Generalized Linear Models (GLMs) were used to investigate the role of daily average temperature, ozone (O(3)) and particulate matter of diameter less than 10 microm (PM(10)) at the regions that showed a significant increase in mortality on unusually hot days. Spatial variation in mortality on unusually hot days was observed among the population 65 and over. Elderly people living within 5-20 km south-west and west of the Sydney Central Business District (CBD) were found to be more vulnerable. However, analysis using GLMs showed temperature to be a significant modifier of daily mortality in the region to the south-west of the CBD only. O(3) and PM(10) were found to be non-significant factors in the regions where air pollutants were studied. Socio-economic status and the proportion of vegetation or developed land in each Statistical Local Area (SLA) were also not a significant factor explaining the increased mortality. A combination of social and environmental factors may be at play. Our results suggest an effect of temperature on mortality of the elderly population in Sydney Statistical Division at the SLA level. More spatially-based research would be beneficial once climate datasets with improved spatial coverage become available.

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.

Effect of temperature on mortality during the six warmer months in Sydney, Australia, between 1993 and 2004.

Studies of heat-related mortality have been predominantly based on analyses of underlying cause of death as the single indicator of a population's vulnerability to high temperatures. Examination of both underlying and associated causes of death could provide a more comprehensive understanding of the population at risk. This study analyzes the impact of high temperatures on mortality in Sydney, Australia, during the warmer six months (October-March) between 1993 and 2004, using the underlying and associated cause of death due to all-cause, circulatory, and respiratory disease. Some mortality datasets were also divided into two age groups, 0-64 and 65+. A generalized linear model assuming negative binomial distribution was constructed for the daily mortality counts using daily maximum temperature and hourly maximum concentrations of ozone (O3) and particulate matter (PM10) as covariates. With the air pollution terms in a model, the change in mortality was estimated to be between 4.5% and 12.1% for a 10 degrees C increase in maximum daily temperature, depending on mortality dataset. When air pollutants were removed from a model, the above mortality percentages changed by -1.1% to 0.9%. When both underlying and associated causes of death were considered, the effect remained the same or became lower. Maximum temperature has been found to have a significant effect on mortality in Sydney, with PM10 and O3 confounding the association.

Synoptic analysis of heat-related mortality in Sydney, Australia, 1993-2001.

Exposure to extremely hot weather has been associated with increased mortality. Temporal Synoptic Index is an effective method used to analyze the relationship between mortality and combined weather factors. The aim of this study is to examine the short-term effect of ambient heat on mortality in Sydney during the warmest 6-month period (October-March) for the years 1993-2001. Eleven synoptic categories were related to daily mortality rates in Sydney. Two distinctive warm categories were associated with significantly higher mortality rates. Hot, dry and relatively rare Synoptic Category 7 (SC7) days showed the highest daily mortality rates, followed by warm and humid SC3 days, which occurred more frequently. Increased mortality was more pronounced among the elderly population, and gender-stratified analysis showed women to be more vulnerable. Mortality on the day of the weather event was higher than 1 or 2 days after the adverse synoptic situation. Ozone and particulate matter smaller than 10 microm were found at high concentrations in SC3 and SC7, respectively, but their impact on mortality was not clear. The population of Sydney was found to be vulnerable to high temperatures, with a lower susceptibility than those of some cities in the USA and Europe.