Academic literature on the topic 'Smoking Australia Mortality Statistics'

Abstract Frailty is gaining importance as a predictor of disability and mortality in older people, and becoming frail poses a challenge for healthy aging. We investigated the prevalence and factors associated with pre-frail and frail status in a large study cohort of community-dwelling healthy older adults from Australia and the United States. A total of 19,114 individuals (87% Australian and 56% women) aged 65 years or older enrolled in a primary prevention clinical trial were evaluated. Frailty status was classified using the modified Fried phenotype criteria comprising of exhaustion, body mass index, grip strength, gait speed and physical activity. Prevalence and factors associated with frailty status (e.g. demographic characteristics and lifestyle factors) were reported using descriptive statistics along with a logistic regression model. At baseline, 2.3 % (95% CI, 2.1-2.5) of older trial participants were frail and 39.2% (95% CI, 38.5-39.9) were pre-frail, respectively. Women were more likely to be frail (65.1% vs 36.9%) and prefrail (58.0% vs 42.0%) than men. Lower levels of education (<12 years), living alone, ethnic minorities, current smoking and past alcohol use were some of the factors which were common among frail or prefrail. Despite being a relatively healthy cohort, more than one-third of the older trial participants were pre-frail, which was more prevalent among specific subgroups of individuals. This study emphasizes the high burden of the prefrailty status even among an apparently healthy cohort of community-dwelling older people.

Ageing is associated with a decrease in odour identification. Additionally, deficits in olfaction have been linked to age-related disease and mortality. Heritability studies suggest genetic variation contributes to olfactory identification. The olfactory receptor (OR) gene family is the largest in the human genome and responsible for overall odour identification. In this study, we sought to find olfactory gene family variants associated with individual and overall odour identification and to examine the relationships between polygenic risk scores (PRS) for olfactory-related phenotypes and olfaction. Participants were Caucasian older adults from the Sydney Memory and Ageing Study and the Older Australian Twins Study with genome-wide genotyping data (n = 1395, mean age = 75.52 ± 6.45). The Brief-Smell Identification Test (BSIT) was administered in both cohorts. PRS were calculated from independent GWAS summary statistics for Alzheimer’s disease (AD), white matter hyperintensities (WMH), Parkinson’s disease (PD), hippocampal volume and smoking. Associations with olfactory receptor genes (n = 967), previously identified candidate olfaction-related SNPs (n = 36) and different PRS with BSIT scores (total and individual smells) were examined. All of the relationships were analysed using generalised linear mixed models (GLMM), adjusted for age and sex. Genes with suggestive evidence for odour identification were found for 8 of the 12 BSIT items. Thirteen out of 36 candidate SNPs previously identified from the literature were suggestively associated with several individual BSIT items but not total score. PRS for smoking, WMH and PD were negatively associated with chocolate identification. This is the first study to conduct genetic analyses with individual odorant identification, which found suggestive olfactory-related genes and genetic variants for multiple individual BSIT odours. Replication in independent and larger cohorts is needed.

The association between smoking and alcohol consumption and follicular lymphoma (FL) incidence and clinical outcome is uncertain. We conducted a population-based family case-control study (709 cases: 490 controls) in Australia. We assessed lifetime history of smoking and recent alcohol consumption and followed-up cases (median = 83 months). We examined associations with FL risk using unconditional logistic regression and with all-cause and FL-specific mortality of cases using Cox regression. FL risk was associated with ever smoking (OR = 1.38, 95%CI = 1.08–1.74), former smoking (OR = 1.36, 95%CI = 1.05–1.77), smoking initiation before age 17 (OR = 1.47, 95%CI = 1.06–2.05), the highest categories of cigarettes smoked per day (OR = 1.44, 95%CI = 1.04–2.01), smoking duration (OR = 1.53, 95%CI = 1.07–2.18) and pack-years (OR = 1.56, 95%CI = 1.10–2.22). For never smokers, FL risk increased for those exposed indoors to >2 smokers during childhood (OR = 1.84, 95%CI = 1.11–3.04). For cases, current smoking and the highest categories of smoking duration and lifetime cigarette exposure were associated with elevated all-cause mortality. The hazard ratio for current smoking and FL-specific mortality was 2.97 (95%CI = 0.91–9.72). We found no association between recent alcohol consumption and FL risk, all-cause or FL-specific mortality. Our study showed consistent evidence of an association between smoking and increased FL risk and possibly also FL-specific mortality. Strengthening anti-smoking policies and interventions may reduce the population burden of FL.

In an earlier paper (Benjamin, 1981) on the subject of cigarette smoking and mortality, statistics from a number of national prospective studies were brought together. These studies agreed in the general finding that the smoking of cigarettes doubled the risk of dying before the age of 65; that diseases most likely to intervene to produce this excess mortality were lung cancer, bronchitis, and emphysema, ischaemic heart disease, certain other cancers (notably of buccal cavity, oesophagus, bladder) and cirrhosis of the liver. It was emphasized that the excess mortality from heart and circulatory disease was not restricted to coronary heart disease, though this latter cause provided the most important element. There was for cigarette smokers a 70% higher risk of dying from myocardial infarction (for the same level of smoking that risk was not less for women than for men). A restricted number of international comparisons of mortality were provided. In almost all countries in Europe, ischaemic heart disease mortality was rising. Outside Europe there was a contrast between the less developed countries where the amount of tobacco consumed was low and those developed countries where consumption was higher. Death-rates were much higher in the latter group. The most pronounced association between smoking and disease was that of lung cancer. The recent experience of lung cancer mortality in a number of countries was recorded. In all countries where there was substantial participation in smoking, death-rates had been rising for men. In most countries where a high proportion of women had been smoking for many years the death-rate for cancer of the lung was rising and in most cases quite rapidly. A reminder was given that heart disease and cancer were not the only penalties of smoking. Emphysema, bronchitis, asthma, influenza, pneumonia and respiratory tuberculosis were diseases for which the risk of dying was increased in cigarette smokers.

Many articles by foreign authors, published in scientific journals with a stable international reputation, contain claims that smoking tobacco reduces the likelihood of infection with SARS-CoV-2. To study this issue, a correlation analysis was carried out to assess the dependence between the proportion of women and men who smoke in 94 countries located in Eurasia, North and South America, Australia, where more than 64 % of the world’s population lives, and the incidence and mortality of the population from COVID-19 during the period from February 1 to November 21, 2021. The results showed that an increase in the proportion of the population who smokes is always accompanied by an increase in morbidity and mortality among the world’s population. This tendency is especially pronounced in Europe, the USA and Canada, with the most detrimental effect of smoking on the growth of mortality. The results obtained allow us to reject with a high degree of confidence the conclusions about the protective effect of smoking from infection with SARS-CoV-2 and provide the media, medical, educational and educational institutions with additional arguments for informing the population about the negative consequences of smoking, especially during the COVID-19 pandemic.

The aim of this paper was to estimate the number of premature deaths, years of potential productive life lost (YPPLL) and labour losses attributable to tobacco smoking due to premature death by gender for the Spanish population. The human capital approach was applied. Employment, gross wage and death data were obtained from the Spanish National Institute of Statistics. Relative risks of death due to cigarette smoking and former smoking were applied. The base case used an annual discount rate of 3% and an annual labour productivity growth rate of 1%. Univariate deterministic sensitivity analysis was performed on discount rates and labour productivity growth rates. Between 2002 and 2016, smoking was estimated to cause around 13,171–13,781 annual deaths in the population under 65 years of age (legal retirement age) in Spain. This increase was mostly due to female deaths. YPPLLs for females have increased over the years, while for males they have fallen markedly. Labour losses associated with smoking mortality ranged from €2269 million in 2002 to €1541 in 2016 (base year 2016). In fact, labour productivity losses have decreased over the years for men (−39.8%) but increased sharply for women (101.6%). The evolution of monetary value of lost productivity due to smoking mortality shows clearly differentiated trends by gender.

During 2020 and 2021, Australia implemented relatively stringent government restrictions yet had few COVID-19 deaths. This provides an opportunity to understand the effects of lockdowns and quarantining restrictions on short-term mortality and to help provide evidence in understanding how such public health policies can impact on health. Our analysis is based on preliminary mortality data collected by the Australian Bureau of Statistics. Rates were estimated by disease and over time and compared with mortality statistics in the period 2015–2019. Comparing deaths in 2020-2021 with 2015–2019 show the annual mortality rate (per 100 000 people) fell by 5.9% from 528.4 in 2015–2019 to 497.0 in 2020–2021. Declines in mortality are across many disease categories including respiratory diseases (down 9.4 deaths per 100 000), cancer (down 7.5 deaths per 100 000) and heart disease (down 8.4 deaths per 100 000). During 2020 and 2021, Australian age-standardised mortality rates fell by 6%. This drop was similar for men and women, and was driven by a reduction in both communicable and non-communicable causes of death. Such evidence can help inform public health policies designed to both control COVID-19 and other infectious diseases.

[Truncated abstract. Please see pdf format for complete text.] Background : The excess burden of mortality born by young Indigenous Australians and the disparity in infant and childhood mortality between Indigenous and non-Indigenous Australians have been well documented. The accuracy and completeness of national data describing the health of Indigenous Australians is inconsistent. The Western Australia (WA) Maternal and Child Health Research Database (MCHRDB), is a linked total population database that includes perinatal maternal and infant data, and infant and childhood morbidity and mortality data. Overall, these data are more than 99% complete, with a similar high level of completeness and validity for Indigenous Western Australians. Aim : The aim of this thesis is to measure Indigenous infant (0 to <1 year) and childhood (>=1 to <19 years) mortality and the disparity between Indigenous and non-Indigenous infants and children in WA for birth cohorts from 1980 to 1997 inclusive. To achieve this aim a number of secondary aims were identified, including the measurement of certain maternal and infant variables, and the age-specific, all-cause and cause-specific mortality for WA infants and children. Method : The study comprises a longitudinal birth cohort study, the primary data source being the MCHRDB. Data included on the MCHRDB are complete for all births in WA from 1980 onwards, with new birth cohorts linked on an annual basis. Maternal and infant variables and the geographical location of the residence and the time of birth and death were included in the descriptive and multivariate analyses. Each infant and childhood death was coded using a three-digit code developed primarily for research purposes. The descriptive analyses of mortality referred to the probability of dying in infancy and in childhood as the cumulative mortality risk (CMR), for various diseases and various population subgroups. Age-specific childhood rates were also calculated. The results of multivariate analyses included the fitting of Cox and Poisson regression models, and estimates of effect were represented as hazard ratios (Cox regression) and relative rates (Poisson regression). Results : Between 1980 and 1997, births to Indigenous mothers accounted for 6% of total WA births. Approximately 46% of Indigenous births were to mothers living in a remote location compared to 9% of non-Indigenous births. Indigenous mothers gave birth at an earlier age (30% of births were to teenage mothers compared to 6% of non-Indigenous births), and were more likely to be single than non-Indigenous mothers (40% Indigenous, 9% non-Indigenous). Indigenous infants had more siblings, were born at an earlier gestation and with a lower birth weight and percentage of expected birth weight. The CMR for Indigenous infants was 22 per 1000 live births compared with 6.7 for non- Indigenous infants, a relative risk (RR) of 3.3 (95%CI 3.0, 3.6). While there was a decrease in the CMR over the birth year groups for both populations, the disparity between the rate of Indigenous and non-Indigenous infant mortality increased. The Indigenous postneonatal (>28 to 365 days) mortality rate (11.7 per 1,000 neonatal survivors) was higher than the neonatal (0 to 28 days) mortality rate (10.3 per 1,000 live births). This profile differed from that for non-Indigenous infants, where the neonatal mortality rate (4.3 per 1,000 live births) was nearly twice that of the postneonatal mortality rate (2.4 per 1,000 neonatal survivors). The main causes of infant mortality among Indigenous infants were potentially preventable. These causes were infection followed by Sudden Infant Death Syndrome (SIDS), which differed from the main causes for non-Indigenous infants, sequelae of prematurity and birth defects. The CMR attributable to SIDS increased over the years amongst Indigenous infants and decreased significantly over the years in the non-Indigenous population. Furthermore, the disparity in mortality between the two populations increased and, in 1995 to 1997, was over seven times higher amongst Indigenous infants. The CMR was highest amongst infants living in remote locations for all causes of death except for Indigenous deaths attributable to SIDS, where the risk of death was highest amongst infants living in metropolitan locations. With the exception of infection, there was no difference in cause-specific mortality amongst Indigenous infants according to geographical location. Indigenous infants living in a remote location were at a significantly increased risk of death due to infection compared with their peers living in a rural or metropolitan location. The risk of death for Indigenous children was more than three times higher than for non-Indigenous children. This risk was significantly increased when most of the perinatal maternal and infant variables were considered.

This thesis examines mortality rates among adults who experienced full-time imprisonment in New South Wales between January 1988 and December 2002, by record linkage to the Australian National Death Index. The cohort included 76383 men and 8820 women. Over a mean follow-up of 7.7 years, 5137 deaths (4724 men, 423 women) were identified. Three hundred and three deaths (295 men, eight women) occurred in custody. The median age at death was 36.6 years for men and 32.7 years for women. The prominent causes of death were drug overdose, suicide, accidental and cardiovascular disease. The crude mortality rate was 797 per 100000 person-years for men and 685 per 100000 person-years for women. Risk of mortality was 3.7 times greater in male and 7.8 times greater in female prisoners than the standard population. The excess mortality was substantially raised following release from prison in both men (standardised mortality ratio 4.0 vs 1.7) and women (standardised mortality ratio 8.2 vs 2.1). The period of highest risk of death was the first two weeks after release. Drug overdose was the main cause of death, responsible for 68% of the deaths in the first two weeks for men and for 90% of the deaths in this period for women. In men, there was also a clustering of suicide directly after release. Prisoners admitted to prison psychiatric hospital, repeat offenders and those in the early stage of followup were at increased risk of mortality. Violent offenders were overrepresented in suicide figures and property offenders in death from overdose. Minority groups, in particular men, had a lower risk of death than white people. The above findings reinforce how disadvantaged prisoners are, measured by mortality as the most fundamental scale of human wellbeing. Prison represents a potential opportunity for treatment and public health intervention to address some of the health problems underlying the high mortality found in this study. The key challenge is, however, to provide a continuum of care between the prison and community.

Accompanying CD-ROM is part of the appendix. It includes computer programs, data files and output tables. Bibliography: leaves 166-170. The average length of life from birth until death in a human population is a single statistic that is often used to characterise the prevailing health status of the population. It is one of many statistics calculated from an analysis that, for each age, combines the number of deaths with the size of the population in which these deaths occur. This analysis is generally known as life table analysis. Life tables have only occasionally been produced specifically for South Australia, although the necessary data has been routinely collected since 1842. In this thesis, the mortality pattern of South Australia over the period of 150 years of European settlement is quantified by using life table analyses and estimates of average length of life. System requirements for accompanying CD-ROM: IBM compatible computer. Other requirements: Winzip. Adobe Acrobat Reader is required to view or print the PDF files.

Many older people in Australia sell their family home to fund a long term residential arrangement with a “retirement village”. The contracts are complex. Consumers usually lack the capacity to compare various retirement village contracts with each other or with other arrangements. We have designed a methodology for comparing such contracts via a comparison rent and other metrics. We are working towards developing a free online publicly available calculator and relevant educational material to facilitate informed decision making by consumers. Our proposed calculator will utilise publicly available data on mortality and disability to model survival of resident status. It will compute various metrics that measure the costs, benefits and risks of these contracts. These metrics vary with age, gender, and health characteristics. These freely (soon) available resources are intended to educate both consumers and their advisors / families in statistical, health, and financial literacy when they need to make an important decision towards the end of their lives.

Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asymptomatic disease in current (13%) and former (24%) Australian smokers.(4) The purpose of this Evidence Check review is to identify and analyse existing and emerging evidence for LDCT lung cancer screening in high-risk individuals to guide future program and policy planning. Evidence Check questions This review aimed to address the following questions: 1. What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? 2. What is the evidence of potential harms from lung cancer screening for higher-risk individuals? 3. What are the main components of recent major lung cancer screening programs or trials? 4. What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Summary of methods The authors searched the peer-reviewed literature across three databases (MEDLINE, PsycINFO and Embase) for existing systematic reviews and original studies published between 1 January 2009 and 8 August 2019. Fifteen systematic reviews (of which 8 were contemporary) and 64 original publications met the inclusion criteria set across the four questions. Key findings Question 1: What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? There is sufficient evidence from systematic reviews and meta-analyses of combined (pooled) data from screening trials (of high-risk individuals) to indicate that LDCT examination is clinically effective in reducing lung cancer mortality. In 2011, the landmark National Lung Cancer Screening Trial (NLST, a large-scale randomised controlled trial [RCT] conducted in the US) reported a 20% (95% CI 6.8% – 26.7%; P=0.004) relative reduction in mortality among long-term heavy smokers over three rounds of annual screening. High-risk eligibility criteria was defined as people aged 55–74 years with a smoking history of ≥30 pack-years (years in which a smoker has consumed 20-plus cigarettes each day) and, for former smokers, ≥30 pack-years and have quit within the past 15 years.(5) All-cause mortality was reduced by 6.7% (95% CI, 1.2% – 13.6%; P=0.02). Initial data from the second landmark RCT, the NEderlands-Leuvens Longkanker Screenings ONderzoek (known as the NELSON trial), have found an even greater reduction of 26% (95% CI, 9% – 41%) in lung cancer mortality, with full trial results yet to be published.(6, 7) Pooled analyses, including several smaller-scale European LDCT screening trials insufficiently powered in their own right, collectively demonstrate a statistically significant reduction in lung cancer mortality (RR 0.82, 95% CI 0.73–0.91).(8) Despite the reduction in all-cause mortality found in the NLST, pooled analyses of seven trials found no statistically significant difference in all-cause mortality (RR 0.95, 95% CI 0.90–1.00).(8) However, cancer-specific mortality is currently the most relevant outcome in cancer screening trials. These seven trials demonstrated a significantly greater proportion of early stage cancers in LDCT groups compared with controls (RR 2.08, 95% CI 1.43–3.03). Thus, when considering results across mortality outcomes and early stage cancers diagnosed, LDCT screening is considered to be clinically effective. Question 2: What is the evidence of potential harms from lung cancer screening for higher-risk individuals? The harms of LDCT lung cancer screening include false positive tests and the consequences of unnecessary invasive follow-up procedures for conditions that are eventually diagnosed as benign. While LDCT screening leads to an increased frequency of invasive procedures, it does not result in greater mortality soon after an invasive procedure (in trial settings when compared with the control arm).(8) Overdiagnosis, exposure to radiation, psychological distress and an impact on quality of life are other known harms. Systematic review evidence indicates the benefits of LDCT screening are likely to outweigh the harms. The potential harms are likely to be reduced as refinements are made to LDCT screening protocols through: i) the application of risk predication models (e.g. the PLCOm2012), which enable a more accurate selection of the high-risk population through the use of specific criteria (beyond age and smoking history); ii) the use of nodule management algorithms (e.g. Lung-RADS, PanCan), which assist in the diagnostic evaluation of screen-detected nodules and cancers (e.g. more precise volumetric assessment of nodules); and, iii) more judicious selection of patients for invasive procedures. Recent evidence suggests a positive LDCT result may transiently increase psychological distress but does not have long-term adverse effects on psychological distress or health-related quality of life (HRQoL). With regards to smoking cessation, there is no evidence to suggest screening participation invokes a false sense of assurance in smokers, nor a reduction in motivation to quit. The NELSON and Danish trials found no difference in smoking cessation rates between LDCT screening and control groups. Higher net cessation rates, compared with general population, suggest those who participate in screening trials may already be motivated to quit. Question 3: What are the main components of recent major lung cancer screening programs or trials? There are no systematic reviews that capture the main components of recent major lung cancer screening trials and programs. We extracted evidence from original studies and clinical guidance documents and organised this into key groups to form a concise set of components for potential implementation of a national lung cancer screening program in Australia: 1. Identifying the high-risk population: recruitment, eligibility, selection and referral 2. Educating the public, people at high risk and healthcare providers; this includes creating awareness of lung cancer, the benefits and harms of LDCT screening, and shared decision-making 3. Components necessary for health services to deliver a screening program: a. Planning phase: e.g. human resources to coordinate the program, electronic data systems that integrate medical records information and link to an established national registry b. Implementation phase: e.g. human and technological resources required to conduct LDCT examinations, interpretation of reports and communication of results to participants c. Monitoring and evaluation phase: e.g. monitoring outcomes across patients, radiological reporting, compliance with established standards and a quality assurance program 4. Data reporting and research, e.g. audit and feedback to multidisciplinary teams, reporting outcomes to enhance international research into LDCT screening 5. Incorporation of smoking cessation interventions, e.g. specific programs designed for LDCT screening or referral to existing community or hospital-based services that deliver cessation interventions. Most original studies are single-institution evaluations that contain descriptive data about the processes required to establish and implement a high-risk population-based screening program. Across all studies there is a consistent message as to the challenges and complexities of establishing LDCT screening programs to attract people at high risk who will receive the greatest benefits from participation. With regards to smoking cessation, evidence from one systematic review indicates the optimal strategy for incorporating smoking cessation interventions into a LDCT screening program is unclear. There is widespread agreement that LDCT screening attendance presents a ‘teachable moment’ for cessation advice, especially among those people who receive a positive scan result. Smoking cessation is an area of significant research investment; for instance, eight US-based clinical trials are now underway that aim to address how best to design and deliver cessation programs within large-scale LDCT screening programs.(9) Question 4: What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Assessing the value or cost-effectiveness of LDCT screening involves a complex interplay of factors including data on effectiveness and costs, and institutional context. A key input is data about the effectiveness of potential and current screening programs with respect to case detection, and the likely outcomes of treating those cases sooner (in the presence of LDCT screening) as opposed to later (in the absence of LDCT screening). Evidence about the cost-effectiveness of LDCT screening programs has been summarised in two systematic reviews. We identified a further 13 studies—five modelling studies, one discrete choice experiment and seven articles—that used a variety of methods to assess cost-effectiveness. Three modelling studies indicated LDCT screening was cost-effective in the settings of the US and Europe. Two studies—one from Australia and one from New Zealand—reported LDCT screening would not be cost-effective using NLST-like protocols. We anticipate that, following the full publication of the NELSON trial, cost-effectiveness studies will likely be updated with new data that reduce uncertainty about factors that influence modelling outcomes, including the findings of indeterminate nodules. Gaps in the evidence There is a large and accessible body of evidence as to the effectiveness (Q1) and harms (Q2) of LDCT screening for lung cancer. Nevertheless, there are significant gaps in the evidence about the program components that are required to implement an effective LDCT screening program (Q3). Questions about LDCT screening acceptability and feasibility were not explicitly included in the scope. However, as the evidence is based primarily on US programs and UK pilot studies, the relevance to the local setting requires careful consideration. The Queensland Lung Cancer Screening Study provides feasibility data about clinical aspects of LDCT screening but little about program design. The International Lung Screening Trial is still in the recruitment phase and findings are not yet available for inclusion in this Evidence Check. The Australian Population Based Screening Framework was developed to “inform decision-makers on the key issues to be considered when assessing potential screening programs in Australia”.(10) As the Framework is specific to population-based, rather than high-risk, screening programs, there is a lack of clarity about transferability of criteria. However, the Framework criteria do stipulate that a screening program must be acceptable to “important subgroups such as target participants who are from culturally and linguistically diverse backgrounds, Aboriginal and Torres Strait Islander people, people from disadvantaged groups and people with a disability”.(10) An extensive search of the literature highlighted that there is very little information about the acceptability of LDCT screening to these population groups in Australia. Yet they are part of the high-risk population.(10) There are also considerable gaps in the evidence about the cost-effectiveness of LDCT screening in different settings, including Australia. The evidence base in this area is rapidly evolving and is likely to include new data from the NELSON trial and incorporate data about the costs of targeted- and immuno-therapies as these treatments become more widely available in Australia.