Influence of Socioeconomic Status on Functional Outcomes After Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND: This review aimed to quantify the impact of socioeconomic status on functional outcomes from stroke and identify the socioeconomic status indicators that exhibit the highest magnitude of association. METHODS AND RESULTS: We performed a systematic literature search across Medline and Embase from inception to May 2022, to identify observational studies (n≥100, and in English). Risk of bias was assessed using the modified Newcastle Ottawa Scale. Random effects meta-analysis was used to pool data. We included 19 studies (157 715 patients, 47.7% women) reporting functional outcomes measured with modified Rankin Scale or Barthel index, with 10 assessed as low risk of bias. Measures of socioeconomic status reported were education (11 studies), income (8), occupation (4), health insurance status (3), and neighborhood socioeconomic deprivation (3). Pooled data suggested that low socioeconomic status was significantly associated with poor functional outcomes, including incomplete education or below high school level versus high school attainment and above (odds ratio [OR], 1.66 [95% CI, 1.40-1.95]), lowest income versus highest income (OR, 1.36 [95% CI, 1.02-1.83]), a manual job/being unemployed versus a nonmanual job/working (OR, 1.62 [95% CI, 1.29-2.02]), and living in the most disadvantaged socioeconomic neighborhood versus the least disadvantaged (OR, 1.55 [95% CI, 1.25-1.92]). Low health insurance status was also associated with an increased risk of poor functional outcomes (OR, 1.32 [95% CI, 0.95-1.84]), although this was association was not statistically significant. CONCLUSIONS: Despite great strides in stroke treatment in the past decades, social disadvantage remains a risk factor for poor functional outcome after an acute stroke. Further research is needed to better understand causal mechanisms and disparities.

Electronic cigarette social norms among adolescents in New South Wales, Australia.

The use of electronic cigarettes (e-cigarettes) is common and increasing, especially among youth. In 2022/2023, 30% of 12- to 17-year-olds reported ever using e-cigarettes in Australia-a >50% increase from 2017 (14%). Several adverse e-cigarette health effects have been identified and most effects remain unknown. Social norms, rules that govern social behaviours, are associated with current and future adolescent e-cigarette use. Understanding social norms in Australian adolescents is critical to the development of targeted and effective e-cigarette prevention activities. This study aims to explore e-cigarette social norms among adolescents living in New South Wales, Australia. A total of 32 online single or paired semi-structured qualitative interviews were conducted involving 46 participants aged 14-17 years, as part of the Generation Vape project. Reflexive thematic analysis was applied within a constructivist perceptive. Adolescents perceived e-cigarettes use as prolific among their peers, with use considered common, acceptable and normal. Fuelled by social exposure to e-cigarettes, 'everyone' was generally thought to be using them (descriptive norms). E-cigarette use was considered so entrenched that it was part of adolescent identity, with abstinence regarded as atypical. Use was driven by an internalised desire to fit it (injunctive norm), rather than being attributed to overt/external 'peer-pressure'. Positive e-cigarette norms exist among Australian adolescents with norm formation strongly influenced by social exposure, including e-cigarette promotion. Prevention efforts should include limiting adolescent exposure to e-cigarette marketing to help redefine existing pro-e-cigarette social norms and protect health.

Electronic cigarettes and health outcomes: umbrella and systematic review of the global evidence.

OBJECTIVE: To review and synthesise the global evidence regarding the health effects of electronic cigarettes (e-cigarettes, vapes). STUDY DESIGN: Umbrella review (based on major independent reviews, including the 2018 United States National Academies of Sciences, Engineering, and Medicine [NASEM] report) and top-up systematic review of published, peer-reviewed studies in humans examining the relationship of e-cigarette use to health outcomes published since the NASEM report. DATA SOURCES: Umbrella review: eight major independent reviews published 2017-2021. Systematic review: PubMed, MEDLINE, Scopus, Web of Science, the Cochrane Library, and PsycINFO (articles published July 2017 - July 2020 and not included in NASEM review). DATA SYNTHESIS: Four hundred eligible publications were included in our synthesis: 112 from the NASEM review, 189 from our top-up review search, and 99 further publications cited by other reviews. There is conclusive evidence linking e-cigarette use with poisoning, immediate inhalation toxicity (including seizures), and e-cigarette or vaping product use-associated lung injury (EVALI; largely but not exclusively for e-liquids containing tetrahydrocannabinol and vitamin E acetate), as well as for malfunctioning devices causing injuries and burns. Environmental effects include waste, fires, and generation of indoor airborne particulate matter (substantial to conclusive evidence). There is substantial evidence that nicotine e-cigarettes can cause dependence or addiction in non-smokers, and strong evidence that young non-smokers who use e-cigarettes are more likely than non-users to initiate smoking and to become regular smokers. There is limited evidence that freebase nicotine e-cigarettes used with clinical support are efficacious aids for smoking cessation. Evidence regarding effects on other clinical outcomes, including cardiovascular disease, cancer, development, and mental and reproductive health, is insufficient or unavailable. CONCLUSION: E-cigarettes can be harmful to health, particularly for non-smokers and children, adolescents, and young adults. Their effects on many important health outcomes are uncertain. E-cigarettes may be beneficial for smokers who use them to completely and promptly quit smoking, but they are not currently approved smoking cessation aids. Better quality evidence is needed regarding the health impact of e-cigarette use, their safety and efficacy for smoking cessation, and effective regulation. REGISTRATION: Systematic review: PROSPERO, CRD42020200673 (prospective).

Workforce participation, health and wealth inequality among older Australians between 2001 and 2015.

BACKGROUND: Australians born in 2012 can expect to live about 33 years longer than those born 100 years earlier. However, only seven of these additional years are spent in the workforce. Longer life expectancy has driven policies to extend working life and increase retirement age; the current Australian policy, which has increased the eligibility for the pension from 65 to 67 by 2023, assumes that an improvement in longevity corresponds with an improvement in healthy life expectancy. However, there is mixed evidence of health trends in Australia over the past two decades. Although some health outcomes are improving among older age groups, many are either stable or deteriorating. This raises a question of how health trends intersect with policy for older Australians aged from 50 to 70. This paper considers the interplay between older workers' health and workforce participation rates over the past 15 years when extended workforce participation has been actively encouraged. METHODS: We compared health and economic outcomes of the older people in following years with the base year (start of the study period), adjusting for some key socio-economic characteristics such as age, sex, ethnicity, education and equivalized household income by applying the Random effects estimator with maximum likelihood estimation technique. RESULTS: We find that regardless of increasing longevity, the health of older adults aged between 50 and 70 has slightly deteriorated. In addition, health gaps between those who were working into their older age and those who were not have widened over the 15-year period. Finally, we find that widening health gaps linked to workforce participation are also accompanied by rising economic inequality in incomes, financial assets and superannuation. With the exception of a small group of healthy and very wealthy retirees, the majority of the older Australians who were not working had low incomes, assets, superannuation, and poor health. CONCLUSIONS: The widening economic and health gap within older population over time indicates a clear and urgent need to add policy actions on income and health, to those that seek to increase workforce participation among older adults.

Smokers Increasingly Motivated and Able to Quit as Smoking Prevalence Falls: Umbrella and Systematic Review of Evidence Relevant to the "Hardening Hypothesis," Considering Transcendence of Manufactured Doubt.

INTRODUCTION: The "hardening hypothesis" proposes that as the prevalence of smoking in a population declines, there will be a "hardening" of the remaining smoker population. This review examines the evidence regarding smokers' motivation, dependence, and quitting behavior as smoking prevalence declines, to assess whether population "hardening" (decreasing propensity to quit) or "softening" (the converse) is occurring. METHODS: MEDLINE, PsychINFO, Scopus, Web of Science, and Cochrane Library were searched to July 2019, using terms related to smoking and hardening, for reviews and large, population-based repeat cross-sectional studies. There were additional searches of reference lists and citations of key research articles. Two reviewers screened half the titles and abstracts each, and two reviewers screened full texts independently using tested criteria. Four reviewers independently and systematically extracted data from eligible publications, with one reviewer per study, checked by another reviewer. RESULTS: Of 265 titles identified, three reviews and ten repeat cross-sectional studies were included. Reviews concluded that hardening has not occurred among the general smoking population over time. Among repeated cross-sectional studies, five examined motivation, nine examined dependence, five examined hardcore smoking, and two examined quit outcomes. All but one study found a lack of hardening. Most found softening within the smoking population, consistent across hardening indicators, definitions, countries (and tobacco control environments), and time periods examined. CONCLUSIONS: Tobacco control reduces smoking prevalence and fosters a smoking population more amenable to evidence-based interventions. Based on the weight of the available evidence, the "hardening hypothesis" should be rejected and the reality of softening accepted. IMPLICATIONS: This umbrella review and systematic review provides a critical consideration of evidence from epidemiology and psychology and other fields regarding the "hardening hypothesis"-a persistent myth undermining tobacco control. It reaches the conclusion that the sum-total of the worldwide evidence indicates either "softening" of the smoking population, or a lack of hardening. Hence, tobacco control reduces smoking prevalence and fosters a smoking population more amenable to evidence-based interventions. The review indicates that the time has come to take active steps to combat the myth of hardening and to replace it with the reality of "softening."

Workforce participation in relation to cancer diagnosis, type and stage: Australian population-based study of 163,556 middle-aged people.

PURPOSE: To quantify the relationship of cancer diagnosis to workforce participation in Australia, according to cancer type, clinical features and personal characteristics. METHODS: Questionnaire data (2006-2009) from participants aged 45-64 years (n=163,556) from the population-based 45 and Up Study (n=267,153) in New South Wales, Australia, were linked to cancer registrations to ascertain cancer diagnoses up to enrolment. Modified Poisson regression estimated age- and sex-adjusted prevalence ratios (PRs) for non-participation in the paid workforce-in participants with cancer (n=8,333) versus without (n=155,223), for 13 cancer types. RESULTS: Overall, 42% of cancer survivors and 29% of people without cancer were out of the workforce (PR=1.18; 95%CI=1.15-1.21). Workforce non-participation varied substantively by cancer type, being greatest for multiple myeloma (1.83; 1.53-2.18), oesophageal (1.70; 1.13-2.58) and lung cancer (1.68; 1.45-1.93) and moderate for colorectal (1.23; 1.15-1.33), breast (1.11; 1.06-1.16) and prostate cancer (1.06; 0.99-1.13). Long-term survivors, 5 or more years post-diagnosis, had 12% (7-16%) greater non-participation than people without cancer, and non-participation was greater with recent diagnosis, treatment or advanced stage. Physical disability contributed substantively to reduced workforce participation, regardless of cancer diagnosis. CONCLUSIONS: Cancer survivors aged 45-64 continue to participate in the workforce. However, participation is lower than in people without cancer, varying by cancer type, and is reduced particularly around the time of diagnosis and treatment and with advanced disease. IMPLICATIONS FOR CANCER SURVIVORS: While many cancer survivors continue with paid work, participation is reduced. Workforce retention support should be tailored to survivor preferences, cancer type and cancer journey stage.

E-cigarette use and combustible tobacco cigarette smoking uptake among non-smokers, including relapse in former smokers: umbrella review, systematic review and meta-analysis.

OBJECTIVE: To review and summarise the current evidence on the uptake of combustible cigarette smoking following e-cigarette use in non-smokers-including never-smokers, people not currently smoking and past smokers-through an umbrella review, systematic review and meta-analysis. DESIGN: Umbrella review, systematic review and meta-analysis. DATA SOURCES: PubMed, Scopus, Web of Science, PsychINFO (Ovid), Medline (Ovid) and Wiley Cochrane Library up to April 2020. RESULTS: Of 6225 results, 25 studies of non-smokers-never, not current and former smokers-with a baseline measure of e-cigarette use and an outcome measure of combustible smoking uptake were included. All 25 studies found increased risk of smoking uptake with e-cigarette exposure, although magnitude varied substantially. Using a random-effects model, comparing e-cigarette users versus non-e-cigarette users, among never-smokers at baseline the OR for smoking initiation was 3.25 (95% CI 2.61 to 4.05, I2 85.7%) and among non-smokers at baseline the OR for current smoking was 2.87 (95% CI 1.97 to 4.19, I2 90.1%). Among former smokers, smoking relapse was higher in e-cigarette users versus non-users (OR=2.40, 95% CI 1.50 to 3.83, I2 12.3%). CONCLUSIONS: Across multiple settings, non-smokers who use e-cigarettes are consistently more likely than those avoiding e-cigarettes to initiate combustible cigarette smoking and become current smokers. The magnitude of this risk varied, with an average of around three times the odds. Former smokers using e-cigarettes have over twice the odds of relapse as non-e-cigarettes users. This study is the first to our knowledge to review and pool data on the latter topic. PROSPERO REGISTRATION NUMBER: CRD42020168596.

Disability, psychological distress and quality of life in relation to cancer diagnosis and cancer type: population-based Australian study of 22,505 cancer survivors and 244,000 people without cancer.

BACKGROUND: Improved survival means that cancer is increasingly becoming a chronic disease. Understanding and improving functional outcomes are critical to optimising survivorship. We quantified physical and mental health-related outcomes in people with versus without cancer, according to cancer type. METHODS: Questionnaire data from an Australian population-based cohort study (45 and Up Study (n = 267,153)) were linked to cancer registration data to ascertain cancer diagnoses up to enrolment. Modified Poisson regression estimated age- and sex-adjusted prevalence ratios (PRs) for adverse person-centred outcomes-severe physical functional limitations (disability), moderate/high psychological distress and fair/poor quality of life (QoL)-in participants with versus without cancer, for 13 cancer types. RESULTS: Compared to participants without cancer (n = 244,000), cancer survivors (n = 22,505) had greater disability (20.6% versus 12.6%, respectively, PR = 1.28, 95%CI = (1.25-1.32)), psychological (22.2% versus 23.5%, 1.05 (1.02-1.08)) and poor/fair QoL (15.2% versus 10.2%; 1.28 (1.24-1.32)). The outcomes varied by cancer type, being worse for multiple myeloma (PRs versus participants without cancer for disability 3.10, 2.56-3.77; distress 1.53, 1.20-1.96; poor/fair QoL 2.40, 1.87-3.07), lung cancer (disability 2.81, 2.50-3.15; distress 1.67, 1.46-1.92; poor/fair QoL 2.53, 2.21-2.91) and non-Hodgkin's lymphoma (disability 1.56, 1.37-1.78; distress 1.20, 1.05-1.36; poor/fair QoL 1.66, 1.44-1.92) and closer to those in people without cancer for breast cancer (disability 1.23, 1.16-1.32; distress 0.95, 0.90-1.01; poor/fair QoL 1.15, 1.05-1.25), prostate cancer (disability 1.11, 1.04-1.19; distress 1.09, 1.02-1.15; poor/fair QoL 1.15, 1.08-1.23) and melanoma (disability 1.02, 0.94-1.10; distress 0.96, 0.89-1.03; poor/fair QoL 0.92, 0.83-1.01). Outcomes were worse with recent diagnosis and treatment and advanced stage. Physical disability in cancer survivors was greater in all population subgroups examined and was a major contributor to adverse distress and QoL outcomes. CONCLUSIONS: Physical disability, distress and reduced QoL are common after cancer and vary according to cancer type suggesting priority areas for research, and care and support.

Earning to learn: the time-health trade-offs of employed Australian undergraduate students.

Australian undergraduate students are facing difficult economic circumstances and rates of psychological distress are well above the general population. Many are combining their study with paid work to manage financially. There is, however, little to no research on the relationship between economic pressures, academic demands and health (mental and physical) among these young adults. This study used a mixed-methods approach, combining semi-structured interviews with health measures to investigate the interactions and interconnections between work, study and health among 22 Australian undergraduate students. Thematic data analysis concentrated on the effect of time constraints on health, due to the financial and academic demands of contemporary undergraduate life. We found that students felt time-pressured, and commonly sacrificed sleep, nutrition, exercise and lecture attendance as a way of managing employment demands. These strategies contributed to poor health; we observed very high rates of psychological distress, poor sleep, diet and exercise, peaking during exams. Our in-depth study illustrates the challenges facing the current generation of undergraduate students in Australia, raising their study-work conflict as a genuine public health and social equity issue.