153 research outputs found

    Estimated health benefits, costs, and cost-effectiveness of eliminating industrial transfatty acids in Australia: A modelling study

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    Background: trans-fatty acids (TFAs) are a well-known risk factor of ischemic heart disease (IHD). In Australia, the highest TFA intake is concentrated to the most socioeconomically disadvantaged groups. Elimination of industrial TFA (iTFA) from the Australian food supply could result in reduced IHD mortality and morbidity while improving health equity. However, such legislation could lead to additional costs for both government and food industry. Thus, we assessed the potential cost-effectiveness, health gains, and effects on health equality of an iTFA ban from the Australian food supply. Methods and findings: Markov cohort models were used to estimate the impact on IHD burden and health equity, as well as the cost-effectiveness of a national ban of iTFA in Australia. Intake of TFA was assessed using the 2011–2012 Australian National Nutrition and Physical Activity Survey. The IHD burden attributable to TFA was calculated by comparing the current level of TFA intake to a counterfactual setting where consumption was lowered to a theoretical minimum distribution with a mean of 0.5% energy per day (corresponding to TFA intake only from nonindustrial sources, e.g., dairy foods). Policy costs, avoided IHD events and deaths, health-adjusted life years (HALYs) gained, and changes in IHD-related healthcare costs saved were estimated over 10 years and lifetime of the adult Australian population. Cost-effectiveness was assessed by calculation of incremental cost-effectiveness ratios (ICERs) using net policy cost and HALYs gained. Health benefits and healthcare cost changes were also assessed in subgroups based on socioeconomic status, defined by Socio-Economic Indexes for Areas (SEIFA) quintile, and remoteness. Compared to a base case of no ban and current TFA intakes, elimination of iTFA was estimated to prevent 2,294 (95% uncertainty interval [UI]: 1,765; 2,851) IHD deaths and 9,931 (95% UI: 8,429; 11,532) IHD events over the first 10 years. The greatest health benefits were accrued to the most socioeconomically disadvantaged quintiles and among Australians living outside of major cities. The intervention was estimated to be cost saving (net cost <0 AUD) or cost-effective (i.e., ICER < AUD 169,361/HALY) regardless of the time horizon, with ICERs of 1,073 (95% UI: dominant; 3,503) and 1,956 (95% UI: 1,010; 2,750) AUD/HALY over 10 years and lifetime, respectively. Findings were robust across several sensitivity analyses. Key limitations of the study include the lack of recent data of TFA intake and the small sample sizes used to estimate intakes in subgroups. As with all simulation models, our study does not prove that a ban of iTFA will prevent IHD, rather, it provides the best quantitative estimates and corresponding uncertainty of a potential effect in the absence of stronger direct evidence. Conclusions: Our model estimates that a ban of iTFAs could avert substantial numbers of IHD events and deaths in Australia and would likely be a highly cost-effective strategy to reduce social–economic and urban–rural inequalities in health. These findings suggest that elimination of iTFA can cost-effectively improve health and health equality even in countries with low iTFA intake

    Cost-Effectiveness of Pharmacotherapy to Reduce Obesity

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    Aims: Obesity causes a high disease burden in Australia and across the world. We aimed to analyse the cost-effectiveness of weight reduction with pharmacotherapy in Australia, and to assess its potential to reduce the disease burden due to excess body weight

    Primary and secondary prevention interventions for cardiovascular disease in low-income and middle-income countries: a systematic review of economic evaluations.

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    BACKGROUND: Cardiovascular disease (CVD) is the leading cause of deaths globally, with greatest premature mortality in the low- and middle-income countries (LMIC). Many of these countries, especially in sub-Saharan Africa, have significant budget constraints. The need for current evidence on which interventions offer good value for money to stem this CVD epidemic motivates this study. METHODS: In this systematic review, we included studies reporting full economic evaluations of individual and population-based interventions (pharmacologic and non-pharmacologic), for primary and secondary prevention of CVD among adults in LMIC. Several medical (PubMed, EMBASE, SCOPUS, Web of Science) and economic (EconLit, NHS EED) databases and grey literature were searched. Screening of studies and data extraction was done independently by two reviewers. Drummond's checklist and the National Institute for Health and Care Excellence quality rating scale were used in the quality appraisal for all studies used to inform this evidence synthesis. RESULTS: From a pool of 4059 records, 94 full texts were read and 50 studies, which met our inclusion criteria, were retained for our narrative synthesis. Most of the studies were from middle-income countries and predominantly of high quality. The majority were modelled evaluations, and there was significant heterogeneity in methods. Primary prevention studies dominated secondary prevention. Most of the economic evaluations were performed for pharmacological interventions focusing on blood pressure, cholesterol lowering and antiplatelet aggregants. The greatest majority were cost-effective. Compared to individual-based interventions, population-based interventions were few and mostly targeted reduction in sodium intake and tobacco control strategies. These were very cost-effective with many being cost-saving. CONCLUSIONS: This evidence synthesis provides a contemporary update on interventions that offer good value for money in LMICs. Population-based interventions especially those targeting reduction in salt intake and tobacco control are very cost-effective in LMICs with potential to generate economic gains that can be reinvested to improve health and/or other sectors. While this evidence is relevant for policy across these regions, decision makers should additionally take into account other multi-sectoral perspectives, including considerations in budget impact, fairness, affordability and implementation while setting priorities for resource allocation

    The effects of built environment attributes on physical activity-related health and health care costs outcomes in Australia

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    Attributes of the built environment can positively influence physical activity of urban populations, which results in health and economic benefits. In this study, we derived scenarios from the literature for the association built environment-physical activity and used a mathematical model to translate improvements in physical activity to health-adjusted life years and health care costs. We modelled 28 scenarios representing a diverse range of built environment attributes including density, diversity of land use, availability of destinations, distance to transit, design and neighbourhood walkability. Our results indicated potential health gains in 24 of the 28 modelled built environment attributes. Health care cost savings due to prevented physical activity-related diseases ranged between A1300toA1300 to A105,355 per 100,000 adults per year. On the other hand, additional health care costs of prolonged life years attributable to improvements in physical activity were nearly 50% higher than the estimated health care costs savings. Our results give an indication of the potential health benefits of investing in physical activity-friendly built environments

    The economic impact of diabetes through lost labour force participation on individuals and government: evidence from a microsimulation model

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    Background\ud \ud Diabetes is a costly and debilitating disease. The aim of the study is to quantify the individual and national costs of diabetes resulting from people retiring early because of this disease, including lost income; lost income taxation, increased government welfare payments; and reductions in GDP.\ud \ud Methods\ud \ud A purpose-built microsimulation model, Health&WealthMOD2030, was used to estimate the economic costs of early retirement due to diabetes. The study included all Australians aged 45–64 years in 2010 based on Australian Bureau of Statistics' Surveys of Disability, Ageing and Carers. A multiple regression model was used to identify significant differences in income, government welfare payments and taxation liabilities between people out of the labour force because of their diabetes and those employed full time with no chronic health condition.\ud \ud Results\ud \ud The median annual income of people who retired early because of their diabetes was significantly lower (AU11784)comparedtothoseemployedfulltimewithoutachronichealthconditionwhoreceivedalmostfivetimesmoreincome.Atthenationallevel,therewasalossofAU11 784) compared to those employed full time without a chronic health condition who received almost five times more income. At the national level, there was a loss of AU384 million in individual earnings by those with diabetes, an extra AU4millionspentingovernmentwelfarepayments,alossofAU4 million spent in government welfare payments, a loss of AU56 million in taxation revenue, and a loss of AU$1 324 million in GDP in 2010: all attributable to diabetes through its impact on labour force participation. Sensitivity analysis was used to assess the impact of different diabetes prevalence rates on estimates of lost income, lost income taxation, increased government welfare payments, and reduced GDP.\ud \ud Conclusions\ud \ud Individuals bear the cost of lost income in addition to the burden of the disease. The Government endures the impacts of lost productivity and income taxation revenue, as well as spending more in welfare payments. These national costs are in addition to the Government's direct healthcare costs

    Population awareness of cardiovascular disease and its risk factors in Buea, Cameroon

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    Abstract Background Adequate awareness of cardiovascular diseases (CVD) and their risk factors may help reduce the population’s exposure to modifiable risk factors and thereby contribute to prevention and control strategies. There is limited data on knowledge among the general population in sub-Saharan Africa regarding CVD and risk factors. We aimed to assess the population awareness (and associated factors) of CVD types and risk factors in Buea, Cameroon. Methods This was a community-based cross-sectional study conducted in 2016 among randomly selected adults (>18 years). Data on socio-demographic characteristics, knowledge about CVD types, their risk factors and warning signs for CVD events (stroke and heart attack) were acquired using a self-administered questionnaire. Logistic regression analysis was used to investigate factors associated with moderate-to-good knowledge. Results Of the 1162 participants (61.7% women, mean age 32 years), 52.5% had overall poor knowledge (mean score 12.1 on total of 25) on CVD with only about a quarter correctly identifying types of CVD. Overall, 36, 63 and 45% were unaware of CVD risk factors, warning signs of heart attack and stroke respectively. In multivariable analysis; high level of education (aOR = 2.26 (1.69–3.02), p < 0.0001), high monthly income (aOR = 1.64 (1.07–2.51), p = 0.023), having a family history of CVD (aOR = 1.59 (1.21–2.09), p = 0.001) and being a former smoker (aOR = 1.11 (1.02–1.95), p = 0.043) were associated with moderate-to-good knowledge. Conclusions There exists a significant gap in population awareness about CVDs in Cameroon and this is similar to previous reports. Cost-effective community health education interventions taking into account socioeconomic status may be beneficial in this setting

    Economic costs of chronic disease through lost productive life years (PLYs) among Australians aged 45–64 years from 2015 to 2030:Results from a microsimulation model

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    Objectives: To project the number of older workers with lost productive life years (PLYs) due to chronic disease and resultant lost income; and lost taxes and increased welfare payments from 2015 to 2030. Design, setting and participants: Using a microsimulation model, Health&WealthMOD2030, the costs of chronic disease in Australians aged 45–64 were projected to 2030. The model integrates household survey data from the Australian Bureau of Statistics Surveys of Disability, Ageing and Carers (SDACs) 2003 and 2009, output from long-standing microsimulation models (STINMOD (Static Incomes Model) and APPSIM (Australian Population and Policy Simulation Model)) used by various government departments, population and labour force growth data from Treasury, and disease trends data from the Australian Burden of Disease and Injury Study (2003). Respondents aged 45–64 years in the SDACs 2003 and 2009 formed the base population. Main outcome measures: Lost PLYs due to chronic disease; resultant lost income, lost taxes and increased welfare payments in 2015, 2020, 2025 and 2030. Results: We projected 380 000 (6.4%) people aged 45–64 years with lost PLYs in 2015, increasing to 462 000 (6.5%) in 2030—a 22% increase in absolute numbers. Those with lost PLYs experience the largest reduction in income than any other group in each year compared to those employed full time without a chronic disease, and this income gap widens over time. The total economic loss due to lost PLYs consisted of lost income modelled at A12.6billionin2015,increasingtoA12.6 billion in 2015, increasing to A20.5 billion in 2030—a 62.7% increase. Additional costs to the government consisted of increased welfare payments at A6.2billionin2015,increasingtoA6.2 billion in 2015, increasing to A7.3 billion in 2030—a 17.7% increase; and a loss of A3.1billionintaxesin2015,increasingtoA3.1 billion in taxes in 2015, increasing to A4.7 billion in 2030—a growth of 51.6%. Conclusions: There is a need for greater investment in effective preventive health interventions which improve workers’ health and work capacity.Full Tex

    Individual and national financial impacts of informal caring for people with mental illness in Australia, projected to 2030

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    Background Mental illness has a significant impact not only on patients, but also on their carers\u27 capacity to work. Aims To estimate the costs associated with lost labour force participation due to the provision of informal care for people with mental illness in Australia, such as income loss for carers and lost tax revenue and increased welfare payments for government, from 2015 to 2030. Method The output data of a microsimulation model Care&WorkMOD were analysed to project the financial costs of informal care for people with mental illness, from 2015 to 2030. Care&WorkMOD is a population-representative microsimulation model of the Australian population aged between 15 and 64 years, built using the Australian Bureau of Statistics Surveys of Disability, Ageing and Carers data and the data from other population-representative microsimulation models. Results The total annual national loss of income for all carers due to caring for someone with mental illness was projected to rise from AU451million(£219.6million)in2015toAU451 million (£219.6 million) in 2015 to AU645 million (£314 million) in 2030 in real terms. For the government, the total annual lost tax revenue was projected to rise from AU121million(£58.9million)in2015toAU121 million (£58.9 million) in 2015 to AU170 million (£82.8 million) in 2030 and welfare payments to increase from AU170million(£82.8million)toAU170 million (£82.8 million) to AU220 million (£107 million) in 2030. Conclusions The costs associated with lost labour force participation due to the provision of informal care for people with mental illness are projected to increase for both carers and government, with a widening income gap between informal carers and employed non-carers, putting carers at risk of increased inequality

    Physical Activity and Risk of Breast Cancer, Colon Cancer, Diabetes, Ischemic Heart Disease, and Ischemic Stroke Events: Systematic Review and Dose-Response Meta-Analysis for the Global Burden of Disease Study 2013

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    Objective: To quantify the dose-response associations between total physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events
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