BackgroundAn increasing number of countries are implementing taxes on unhealthy foods and drinks to address the growing burden of dietary-related disease, but the cost-effectiveness of combining taxes on unhealthy foods and subsidies on healthy foods is not well understood.Methods and FindingsUsing a population model of dietary-related diseases and health care costs and food price elasticities, we simulated the effect of taxes on saturated fat, salt, sugar, and sugar-sweetened beverages and a subsidy on fruits and vegetables, over the lifetime of the Australian population. The sizes of the taxes and subsidy were set such that, when combined as a package, there would be a negligible effect on average weekly expenditure on food (<1% change). We evaluated the cost-effectiveness of the interventions individually, then determined the optimal combination based on maximising net monetary benefit at a threshold of AU$50,000 per disability-adjusted life year (DALY). The simulations suggested that the combination of taxes and subsidy might avert as many as 470,000 DALYs (95% uncertainty interval [UI]: 420,000 to 510,000) in the Australian population of 22 million, with a net cost-saving of AU$3.4 billion (95% UI: AU$2.4 billion to AU$4.6 billion; US$2.3 billion) to the health sector. Of the taxes evaluated, the sugar tax produced the biggest estimates of health gain (270,000 [95% UI: 250,000 to 290,000] DALYs averted), followed by the salt tax (130,000 [95% UI: 120,000 to 140,000] DALYs), the saturated fat tax (97,000 [95% UI: 77,000 to 120,000] DALYs), and the sugar-sweetened beverage tax (12,000 [95% UI: 2,100 to 21,000] DALYs). The fruit and vegetable subsidy (−13,000 [95% UI: −44,000 to 18,000] DALYs) was a cost-effective addition to the package of taxes. However, it did not necessarily lead to a net health benefit for the population when modelled as an intervention on its own, because of the possible adverse cross-price elasticity effects on consumption of other foods (e.g., foods high in saturated fat and salt). The study suggests that taxes and subsidies on foods and beverages can potentially be combined to achieve substantial improvements in population health and cost-savings to the health sector. However, the magnitude of health benefits is sensitive to measures of price elasticity, and further work is needed to incorporate potential benefits or harms associated with changes in other foods and nutrients that are not currently modelled, such as red and processed meats and fibre.ConclusionsWith potentially large health benefits for the Australian population and large benefits in reducing health sector spending on the treatment of non-communicable diseases, the formulation of a tax and subsidy package should be given a more prominent role in Australia’s public health nutrition strategy.
Aim Misreporting of energy intake is a common source of measurement error found in dietary surveys, resulting in biased estimates and a reduction in statistical power. The present study aims to refine the conventional cut‐off methods and to examine the extent to which Australian adults misreport their energy intake, and the characteristics of under‐reporters between two time points. Methods A revised Goldberg cut‐off approach was used to identify those who reported implausible intake amounts in a secondary analysis of two large cross‐sectional surveys. Identified low energy reporters were then used as the outcome variable in Poisson regressions to examine association with sex, age, body mass index (BMI), weight perceptions, education, relative household income, geographic remoteness and relative socioeconomic disadvantage. Results The prevalence of under‐reporting increased from 32% in 1995 to 41% in 2012, most of which can be attributed to an increase in men. Under‐reporting has a positive association with BMI and relative socioeconomic disadvantage, but an inverse association with age, education, relative household income and residence in inner regional areas. Conclusions Under‐reporting of energy intake is high in Australian adults, and appears have worsened over time in men, which could be partly explained by the upward trend in obesity. The use of conventional Goldberg method to identify under‐reporters can greatly underestimate the prevalence of under‐reporting, future studies should consider selecting a lower critical value to improve accuracy.
BackgroundPrimary care patients, especially those with an older age, are one of the most vulnerable populations for post-COVID-19 symptoms. Identifying predictors of post-COVID symptoms can help identify high-risk individuals for preventive care.MethodsOut of 977 primary care patients aged 55 years or above with comorbid physical and psychosocial conditions in a prospective cohort in Hong Kong, 207 patients infected in the previous 5–24 weeks were included. The three most common post-COVID-19 symptoms (breathlessness, fatigue, cognitive difficulty), which lasted beyond the 4-week acute infection period, were assessed using items from the COVID-19 Yorkshire Rehabilitation Scale (C19-YRS), together with other self-reported symptoms. Multivariable analyses were conducted to identify predictors of post-acute and long COVID-19 symptoms (5–24 weeks after infection).ResultsThe 207 participants had a mean age of 70.8 ± 5.7 years, 76.3% were female, and 78.7% had ≥2 chronic conditions. In total, 81.2% reported at least one post-COVID symptom (mean: 1.9 ± 1.3); 60.9, 56.5 and 30.0% reported fatigue, cognitive difficulty, and breathlessness respectively; 46.1% reported at least one other new symptom (such as other respiratory-related symptoms (14.0%), insomnia or poor sleep quality (14.0%), and ear/nose/throat symptoms (e.g., sore throat) (10.1%), etc.). Depression predicted post-COVID-19 fatigue. The female sex predicted cognitive difficulty. Receiving fewer vaccine doses (2 doses vs. 3 doses) was associated with breathlessness. Anxiety predicted a higher overall symptom severity level of the three common symptoms.ConclusionDepression, the female sex, and fewer vaccine doses predicted post-COVID symptoms. Promoting vaccination and providing intervention to those at high-risk for post-COVID symptoms are warranted.
We investigate the causal effect of English proficiency on labour, social and health outcomes of immigrants in Australia. We use age at arrival combined with country of origin to form an instrument of English proficiency. We find that immigrants in Australia with better language proficiency are able to earn higher income, attain higher level of education, have higher probability of complete tertiary studies, and get more hours of work per week. Language proficiency also improves social integration, leading to higher probability of marriage to a native and higher probability of obtaining citizenship. We find only limited evidence with respect to the hypothesised causal relationship between language and health for immigrants. This last result may be due to small sample sizes. Effects of language proficiency on labour, social and health outcomes of Australian immigrants AbstractWe investigate the causal effect of English proficiency on labour, social and health outcomes of immigrants in Australia. Age at arrival combined with country of origin is used to form an instrument for English proficiency. We find that Australian immigrants with better language proficiency are able to earn higher incomes, attain higher levels of education, have a higher probability of completing tertiary studies, and are able to work more hours per week.Language proficiency is also shown to improve social integration, leading to higher probability of marriage to an Australian born resident (native)and higher probability of obtaining citizenship. We find only limited evidence with respect to the hypothesised causal relationship between language and health for immigrants. This last result may be due to the smallness of the surveys' sample size.
BackgroundLow health literacy (HL) is negatively associated with mammography screening uptake. However, evidence of the links between poor HL and low mammography screening participation is scarce.MethodsWe conducted a cross-sectional questionnaire survey among participants of a cancer screening program. We measured HL using a validated Chinese instrument. We assessed breast cancer screening-related beliefs using the Health Belief Model and the accuracy of risk perception. We used multivariable regression models to estimate the relationship between HL and the outcomes.ResultsA total of 821 females were included. 264 (32.2%) had excellent or sufficient, 353 (43.0%) had problematic, and 204 (24.8%) had inadequate health literacy (IHL). Women with IHL were more likely to agree that high price (β = -0.211, 95% CI -0.354 to -0.069), lack of time (β = -0.219, 95% CI -0.351 to -0.088), inconvenient service time (β = -0.291, 95% CI -0.421 to -0.160), long waiting time (β = -0.305, 95% CI -0.447 to -0.164), fear of positive results (β = -0.200, 95% CI -0.342 to -0.058), embarrassment (β = -0.225, 95% CI -0.364 to -0.086), fear of pain (β = -0.154, 95% CI -0.298 to -0.010), fear of radiation (β = -0.177, 95% CI -0.298 to -0.056), lack of knowledge on service location (β = -0.475, 95% CI -0.615 to -0.335), and lack of knowledge on mammography (β = -0.360, 95% CI -0.492 to -0.228) were barriers. They were also less likely to have an accurate breast cancer risk perception (aOR 0.572, 95% CI 0.341 to 0.956).ConclusionWomen with lower HL could have stronger perceived barriers to BC screening and an over-estimation of their breast cancer risk. Tackling emotional and knowledge barriers, financial and logistical assistance, and guidance on risk perception are needed to increase their breast cancer screening uptake.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.