Who smokes in Australia? Cross-sectional analysis of Australian Bureau of Statistics survey data, 2017-19.

OBJECTIVES: To assess the socio-demographic and health-related characteristics of people who smoke daily, people who formerly smoked, and people who have never smoked in Australia. STUDY DESIGN: Cross-sectional analysis of Australian Bureau of Statistics (ABS) survey data. SETTING, PARTICIPANTS: Adult participants (16 370 people aged 18 years or older) in the ABS 2017-18 National Health Survey (NHS); adult participants in the ABS 2018-19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS) (6423 people aged 18 years or older). MAIN OUTCOME MEASURES: Socio-demographic and health-related characteristics of people who smoke daily, people who formerly smoked, and people who have never smoked, expressed as population-weighted proportions, overall and by Indigeneity. RESULTS: Among adult NHS respondents, an estimated 58.8% of people who smoked daily (95% confidence interval [CI], 56.2-61.4%) were men, 61.3% (95% CI, 58.7-63.9%) were 25-54 years old, 72.5% (95% CI, 70.0-74.8%) were born in Australia, and 65.4% (95% CI, 62.8-67.8%) lived in major cities and 54.3% (95% CI, 51.6-57.0%) in areas in the two socio-economically most disadvantaged quintiles; 75.9% (95% CI, 73.5-78.1%) reported good to excellent health, 73.0% (95% CI, 70.5-75.4%) reported low to moderate psychological distress, 69.0% of those aged 25-64 years (ie, of working age) had completed year 12 (high school), and 68.5% were currently employed. An estimated 2.57 million people smoke daily in Australia: 2.37 million non-Indigenous people (92%) and 195 700 Aboriginal or Torres Strait Islander people (8%). CONCLUSIONS: While smoking is more frequent among people living in socio-economically disadvantaged areas and in certain population sub-groups, this first quantitative national profile indicates that most people who smoke daily are in paid employment, are non-Indigenous, are in good physical and mental health, and have completed year 12. Improved comprehensive structural supply- and demand-based tobacco control, informed by the needs of priority groups and the overall profile of people who smoke, is needed to reduce daily smoking prevalence among adults to the 2030 targets of 5% or less for all Australians and 27% or less for Aboriginal and Torres Strait Islander people.

Inequalities in Mortality in the Asia-Pacific: A Cross-National Comparison of Socioeconomic Gradients.

OBJECTIVES: Social inequalities in mortality are poorly studied in much of the Asia-Pacific. Using data from harmonized nationally representative longitudinal health and aging surveys our study systematically assesses mortality disparities across 3 standardized measures of socioeconomic status in 7 Asia-Pacific countries. METHODS: We used data from multiple waves of 7 representative sample surveys: the Health, Income and Labour Dynamics in Australia survey, China Health and Retirement Longitudinal Study, the Indonesian Family Life Survey, the New Zealand Health, Work and Retirement survey, the Korean Longitudinal Study on Ageing and the Health, Aging and Retirement in Thailand survey, and the Japanese Study of Aging and Retirement. We use Cox proportional hazards modeling to examine how the hazard of mortality differs across domains of social stratification including educational attainment, wealth, and occupational status across countries. RESULTS: We found consistent and pervasive gradients in mortality risk in the high-income countries by all available measures of social stratification. In contrast, patterns of inequality in adult mortality in middle-income and recently transitioned high-income countries investigated varied depending on the measure of social stratification, with strong gradients by wealth but mixed gradients by education. DISCUSSION: Analyzing social gradients in mortality in the Asia-Pacific shows that inequalities, especially wealth-based inequalities, in later-life health are present across the region, and that the magnitude of social gradients in mortality is overall larger in high-income countries as compared to middle-income countries.

A G358S mutation in the Plasmodium falciparum Na+ pump PfATP4 confers clinically-relevant resistance to cipargamin.

Diverse compounds target the Plasmodium falciparum Na+ pump PfATP4, with cipargamin and (+)-SJ733 the most clinically-advanced. In a recent clinical trial for cipargamin, recrudescent parasites emerged, with most having a G358S mutation in PfATP4. Here, we show that PfATP4G358S parasites can withstand micromolar concentrations of cipargamin and (+)-SJ733, while remaining susceptible to antimalarials that do not target PfATP4. The G358S mutation in PfATP4, and the equivalent mutation in Toxoplasma gondii ATP4, decrease the sensitivity of ATP4 to inhibition by cipargamin and (+)-SJ733, thereby protecting parasites from disruption of Na+ regulation. The G358S mutation reduces the affinity of PfATP4 for Na+ and is associated with an increase in the parasite's resting cytosolic [Na+]. However, no defect in parasite growth or transmissibility is observed. Our findings suggest that PfATP4 inhibitors in clinical development should be tested against PfATP4G358S parasites, and that their combination with unrelated antimalarials may mitigate against resistance development.

Novel statistical approaches to identify risk factors for soil-transmitted helminth infection in Timor-Leste.

Soil-transmitted helminths (STHs) are parasitic intestinal worms that infect almost a fifth of the global population. Sustainable control of STHs requires understanding the complex interaction of factors contributing to transmission. Identifying risk factors has mainly relied on logistic regression models where the underlying assumption of independence between variables is not always satisfied. Previously demonstrated risk factors including water, sanitation and hygiene (WASH) access and behaviours, and socioeconomic status are intrinsically linked. Similarly, environmental factors including climate, soil and land attributes are often strongly correlated. Alternative methods such as recursive partitioning and Bayesian networks can handle correlated variables, but there are no published studies comparing these methods with logistic regression in the context of STH risk factor analysis. Baseline cross-sectional data from school-aged children in the (S)WASH-D for Worms study were used to compare risk factors identified from modelling the same data using three different statistical techniques. Outcomes of interest were infection with Ascaris spp. and any hookworm species (Necator americanus, Ancylostoma duodenale, and Ancylostoma ceylanicum). Mixed-effects logistic regression identified the fewest risk factors. Recursive partitioning identified the most WASH and demographic risk factors, while Bayesian networks identified the most environmental risk factors. Recursive partitioning produced classification trees that visualised potentially at-risk population sub-groups. Bayesian networks helped visualise relationships between variables and enabled interactive modelling of outcomes based on different scenarios for the predictor variables of interest. Model performance was similar across all techniques. Risk factors identified across all techniques were vegetation for Ascaris spp., and cleaning oneself with water after defecating for hookworm. This study adds to the limited body of evidence exploring alternative data modelling approaches in identifying risk factors for STH infections. Our findings suggest these approaches can provide novel insights for more robust interpretation.

Investigating spatial convergence of diagnosed dementia, depression and type 2 diabetes prevalence in West Adelaide, Australia.

BACKGROUND: Comorbid depression and type 2 diabetes (T2D) is an important risk factor for dementia. This study investigates the factors associated with, the spatial variation and spatial convergence of diagnosed cases of these conditions. This approach may identify areas with unmet needs. METHODS: We used cross-sectional data (2010 to 2014) from 16 general practices in west Adelaide, Australia. Multi-level modelling accounting for individual-level characteristics nested within statistical area level 1 (SA1) determined covariate associations with these three diseases. Getis-Ord Gi method was used to investigate spatial variation, hot spots and cold spots of these conditions. RESULTS: 1.4% of active patients in west Adelaide aged 45 and above were diagnosed with dementia, 9.6% with depression and 13.3% with T2D. Comorbidity was significant across all three diseases. Elderly age (65+ years) was significantly associated with diagnosed dementia and T2D. Hyperlipidemia or hypertension diagnosis and belonging to lower socioeconomic status were significantly associated with diagnosed T2D and depression. The spatial distribution of each disease varied across west Adelaide. Spatial convergence of the three diseases was observed in two large hot spot clusters and one main cluster of cold spots. LIMITATIONS: Due to underreporting, potentially significant covariates like alcohol intake were unable to be assessed. There may be a bias towards health-conscious individuals or patients managing diagnosed diseases that actively visit their general practice. CONCLUSIONS: Patterns of spatial convergence and the shared associations in dementia, depression and diabetes enable policymakers to tailor interventions to the areas where risk of these conditions are greater.

Utilization of Traditional Chinese Medicine Practitioners in Later Life in Mainland China.

Mainland China is one of the world's most rapidly aging countries, and yet there is very limited literature on traditional Chinese medicine (TCM) use in older individuals. This study aimed to determine the national and provincial prevalence of TCM practitioner utilization in later life and associated factors. We used World Health Organization China Study on Global Aging and Adult Health Wave 1 data to determine descriptive statistics of the study population of participants aged 50 years and over. Multivariate logistic regression was conducted controlling for sociodemographic and health factors. A total of 14% of participants utilized a TCM practitioner, and the prevalence of utilization varied significantly by locality. Utilization was more likely in participants living in rural areas [adjusted odds ratio (OR) = 12.96; p < 0.001], Hubei (OR = 7.17; p < 0.001), or Shandong provinces (OR = 4.21; p < 0.001) and being diagnosed with chronic lung disease (OR = 1.97; p = 0.005). Hence, rurality, provincial influence, and chronic lung diseases are significant factors associated with TCM practitioner utilization among older individuals in China. These findings may inform policy for preservation and development of TCM nationally as well as its sustainability in an increasingly aging society.