The health care and societal costs of inherited retinal diseases in Australia: a microsimulation modelling study.

OBJECTIVES: To estimate the health care and societal costs of inherited retinal diseases (IRDs) in Australia. DESIGN, SETTING, PARTICIPANTS: Microsimulation modelling study based on primary data - collected in interviews of people with IRDs who had ophthalmic or genetic consultations at the Children's Hospital at Westmead or the Save Sight Institute (both Sydney) during 1 January 2019 - 31 December 2020, and of their carers and spouses - and linked Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Schedule (PBS) data. MAIN OUTCOME MEASURES: Annual and lifetime costs for people with IRDs and for their carers and spouses, grouped by payer (Australian government, state governments, individuals, private health insurance) and type (health care costs; societal costs: social support, National Disability Insurance Scheme (NDIS), income and taxation, costs associated with caring for family members with IRDs); estimated annual national cost of IRDs. RESULTS: Ninety-four people (74 adults, 20 people under 18 years; 55 girls and women [59%]) and 30 carers completed study surveys (participation rate: adults, 66%; children, 66%; carers, 63%). Total estimated lifetime cost was $5.2 million per person with an IRD, of which 87% were societal and 13% health care costs. The three highest cost items were lost income for people with IRDs ($1.4 million), lost income for their carers and spouses ($1.1 million), and social spending by the Australian government (excluding NDIS expenses: $1.0 million). Annual costs were twice as high for people who were legally blind as for those with less impaired vision ($83 910 v $41 357 per person). The estimated total annual cost of IRDs in Australia was $781 million to $1.56 billion. CONCLUSION: As the societal costs associated with IRDs are much larger than the health care costs, both contributors should be considered when assessing the cost-effectiveness of interventions for people with IRDs. The increasing loss of income across life reflects the impact of IRDs on employment and career opportunities.

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

BACKGROUND: Mental illness has a significant impact not only on patients, but also on their carers' 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 AU$451 million (£219.6 million) in 2015 to AU$645 million (£314 million) in 2030 in real terms. For the government, the total annual lost tax revenue was projected to rise from AU$121 million (£58.9 million) in 2015 to AU$170 million (£82.8 million) in 2030 and welfare payments to increase from AU$170 million (£82.8 million) to AU$220 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.

Informal caring for back pain: overlooked costs of back pain and projections to 2030.

This study models the economic costs of informal caring for people with back pain, using a microsimulation model, Care&WorkMOD, from 2015 to 2030. Care&WorkMOD was based on 3 national Australian Surveys of Disability, Ageing and Carers (2003, 2009, 2012) data sets for individuals aged 15 to 64 years. Estimated national income loss due to caring for people with back pain was AU$258 million in 2015, increasing to $398 million in 2030 (54% increase). Lost income tax revenue to the Australian government due to informal care of people with back pain was estimated to be AU$78 million in 2015, increasing to AU$118 million in 2030 (50% increase), and additional welfare payments were estimated to rise from $132 million in 2015 to AU$180 in 2030 (36% increase). Larger growth in lost income, compared with the increase in welfare payments, means that there would be an increasing income gap between those out of the labour force providing informal care and noncarers who are in the labour force, leading to increased inequality. Informal carers are defined as providers of informal, unpaid assistance to someone with a health condition, for at least 6 months. Informal carers of people with back pain who are out of the labour force incur substantial economic costs. Furthermore, back pain is a large economic burden on national governments. Policies addressing back pain prevention and treatment, and supporting carers, may offset government welfare expenditure, while improving the socioeconomic well-being of carers and patients.

Intellectual disability and autism: socioeconomic impacts of informal caring, projected to 2030.

BACKGROUND: Intellectual disability and autism spectrum disorder (ASD) influence the interactions of a person with their environment and generate economic and socioeconomic costs for the person, their family and society. AIMS: To estimate costs of lost workforce participation due to informal caring for people with intellectual disability or autism spectrum disorders by estimating lost income to individuals, lost taxation payments to federal government and increased welfare payments. METHOD: We used a microsimulation model based on the Australian Bureau of Statistics' Surveys of Disability, Ageing and Carers (population surveys of people aged 15-64), and projected costs of caring from 2015 in 5-year intervals to 2030. RESULTS: The model estimated that informal carers of people with intellectual disability and/or ASD in Australia had aggregated lost income of AU$310 million, lost taxation of AU$100 million and increased welfare payments of AU$204 million in 2015. These are projected to increase to AU$432 million, AU$129 million and AU$254 million for income, taxation, and welfare respectively by 2030. The income gap of carers for people with intellectual disability and/or ASD is estimated to increase by 2030, meaning more financial stress for carers. CONCLUSIONS: Informal carers of people with intellectual disability and/or ASD experience significant loss of income, leading to increased welfare payments and reduced taxation revenue for governments; these are all projected to increase. Strategic policies supporting informal carers wishing to return to work could improve the financial and psychological impact of having a family member with intellectual disability and/or ASD. DECLARATION OF INTEREST: None.

Economic costs of informal care for people with chronic diseases in the community: Lost income, extra welfare payments, and reduced taxes in Australia in 2015-2030.

We estimated the economic costs of informal care in the community from 2015 to 2030, using an Australian microsimulation model, Care&WorkMOD. The model was based on data from three Surveys of Disability, Ageing, and Carers (SDACs) for the Australian population aged 15-64 years old. Estimated national income lost was AU$3.58 billion in 2015, increasing to $5.33 billion in 2030 (49% increase). Lost tax payments were estimated at AU$0.99 billion in 2015, increasing to AU$1.44 billion in 2030 (45% increase), and additional welfare payments were expected to rise from $1.45 billion in 2015 to AU$1.94 in 2030 (34% increase). There are substantial economic costs both to informal carers and the government due to carers being out of the labour-force to provide informal care for people with chronic diseases. Health and social policies supporting carers to remain in the labour force may allow governments to make substantial savings, while improving the economic situation of carers.

The long-term economic impacts of arthritis through lost productive life years: results from an Australian microsimulation model.

BACKGROUND: While the direct (medical) costs of arthritis are regularly reported in cost of illness studies, the 'true' cost to indivdiuals and goverment requires the calculation of the indirect costs as well including lost productivity due to ill-health. METHODS: Respondents aged 45-64 in the ABS Survey of Disability, Ageing and Carers 2003, 2009 formed the base population. We projected the indirect costs of arthritis using Health&WealthMOD2030 - Australia's first microsimulation model on the long-term impacts of ill-health in older workers - which incorporated outputs from established microsimulation models (STINMOD and APPSIM), population and labour force projections from Treasury, and chronic conditions trends for Australia. All costs of arthritis were expressed in real 2013 Australian dollars, adjusted for inflation over time. RESULTS: We estimated there are 54,000 people aged 45-64 with lost PLYs due to arthritis in 2015, increasing to 61,000 in 2030 (13% increase). In 2015, people with lost PLYs are estimated to receive AU$706.12 less in total income and AU$311.67 more in welfare payments per week than full-time workers without arthritis, and pay no income tax on average. National costs include an estimated loss of AU$1.5 billion in annual income in 2015, increasing to AU$2.4 billion in 2030 (59% increase). Lost annual taxation revenue was projected to increase from AU$0.4 billion in 2015 to $0.5 billion in 2030 (56% increase). We projected a loss in GDP of AU$6.2 billion in 2015, increasing to AU$8.2 billion in 2030. CONCLUSIONS: Significant costs of arthritis through lost PLYs are incurred by individuals and government. The effectiveness of arthritis interventions should be judged not only on healthcare use but quality of life and economic wellbeing.

The costs of diabetes among Australians aged 45-64†years from 2015 to 2030: projections of lost productive life years (PLYs), lost personal income, lost taxation revenue, extra welfare payments and lost gross domestic product from Health&WealthMOD2030.

OBJECTIVES: To project the number of people aged 45-64 years with lost productive life years (PLYs) due to diabetes and related costs (lost income, extra welfare payments, lost taxation revenue); and lost gross domestic product (GDP) attributable to diabetes in Australia from 2015 to 2030. DESIGN: A simulation study of how the number of people aged 45-64 years with diabetes increases over time (based on population growth and disease trend data) and the economic losses incurred by individuals and the government. Cross-sectional outputs of a microsimulation model (Health&WealthMOD2030) which used the Australian Bureau of Statistics' Survey of Disability, Ageing and Carers 2003 and 2009 as a base population and integrated outputs from two microsimulation models (Static Incomes Model and Australian Population and Policy Simulation Model), Treasury's population and labour force projections, and chronic disease trends data. SETTING: Australian population aged 45-64 years in 2015, 2020, 2025 and 2030. OUTCOME MEASURES: Lost PLYs, lost income, extra welfare payments, lost taxation revenue, lost GDP. RESULTS: 18 100 people are out of the labour force due to diabetes in 2015, increasing to 21 400 in 2030 (18% increase). National costs consisted of a loss of $A467 million in annual income in 2015, increasing to $A807 million in 2030 (73% increase). For the government, extra annual welfare payments increased from $A311 million in 2015 to $A350 million in 2030 (13% increase); and lost annual taxation revenue increased from $A102 million in 2015 to $A166 million in 2030 (63% increase). A loss of $A2.1 billion in GDP was projected for 2015, increasing to $A2.9 billion in 2030 attributable to diabetes through its impact on PLYs. CONCLUSIONS: Individuals incur significant costs of diabetes through lost PLYs and lost income in addition to disease burden through human suffering and healthcare costs. The government incurs extra welfare payments, lost taxation revenue and lost GDP, along with direct healthcare costs.

Working Beyond the Traditional Retirement Age: The Influence of Health on Australia's Older Workers.

This article examines the relationship between health and workforce participation beyond the age of 65 years in Australia. This study found that people with a chronic health condition were less likely to be employed than those without a health condition (OR, 0.59; 95% CI [0.38, 0.92]). Among those with a chronic health condition, those in income quartile 2 (OR, 0.27; 95% CI [0.11, 0.67]) and 3 (OR, 0.38; 95% CI, [0.15-0.93]) were significantly less likely to be employed relative to those in income quartile 4. Older workers with a chronic health condition were less likely to work beyond the age of 65; however, among those with a chronic health condition, those with very high income and those with very low income were the most likely to keep working.

The indirect costs of back problems (dorsopathies) in Australians aged 45 to 64 years from 2015 to 2030: results from a microsimulation model, Health&WealthMOD2030.

This study projected the indirect costs of back problems through lost productive life years (PLYs) from the individual's perspective (lost disposable income), the governmental perspective (reduced taxation revenue, greater welfare spending), and the societal perspective (lost gross domestic product, GDP) from 2015 to 2030, using Health&WealthMOD2030-Australia's first microsimulation model on the long-term impacts of ill-health. Quantile regression analysis was used to examine differences in median weekly income, welfare payments, and taxes of people unable to work due to back problems with working full-time without back problems as comparator. National costs and lost GDP resulting from missing workers due to back problems were also projected. We projected that 90,000 people have lost PLYs due to back problems in 2015, increasing to 104,600 in 2030 (16.2% increase). People with lost PLYs due to back problems are projected to receive AU$340.91 less in total income and AU$339.77 more in welfare payments per week than full-time workers without back problems in 2030 and pay no income tax on average. National costs consisted of a loss of AU$2931 million in annual income in 2015, increasing to AU$4660 million in 2030 (60% increase). For government, extra annual welfare payments are projected to increase from AU$1462 million in 2015 to AU$1709 million in 2030 (16.9% increase), and lost annual taxation revenue to increase from AU$671 million in 2015 to $961 million in 2030 (43.2% increase). We projected losses in GDP of AU$10,543 million in 2015, increasing to AU$14,522 million in 2030 due to back problems.

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.

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 $A12.6 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 $A6.2 billion in 2015, increasing to $A7.3 billion in 2030-a 17.7% increase; and a loss of $A3.1 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.

Lost productive life years caused by chronic conditions in Australians aged 45-64 years, 2010-2030.

OBJECTIVES: To estimate (1) productive life years (PLYs) lost because of chronic conditions in Australians aged 45-64 years from 2010 to 2030, and (2) the impact of this loss on gross domestic product (GDP) over the same period. DESIGN, SETTING AND PARTICIPANTS: A microsimulation model, Health&WealthMOD2030, was used to project lost PLYs caused by chronic conditions from 2010 to 2030. The base population consisted of respondents aged 45-64 years to the Australian Bureau of Statistics Survey of Disability, Ageing and Carers 2003 and 2009. The national impact of lost PLYs was assessed with Treasury's GDP equation. MAIN OUTCOME MEASURES: Lost PLYs due to chronic disease at 2010, 2015, 2020, 2025 and 2030 (ie, whole life years lost because of chronic disease); the national impact of lost PLYs at the same time points (GDP loss caused by PLYs); the effects of population growth, labour force trends and chronic disease trends on lost PLYs and GDP at each time point. RESULTS: Using Health&WealthMOD2030, we estimated a loss of 347,000 PLYs in 2010; this was projected to increase to 459,000 in 2030 (32.28% increase over 20 years). The leading chronic conditions associated with premature exits from the labour force were back problems, arthritis and mental and behavioural problems. The percentage increase in the number of PLYs lost by those aged 45-64 years was greater than that of population growth for this age group (32.28% v 27.80%). The strongest driver of the increase in lost PLYs was population growth (accounting for 89.18% of the increase), followed by chronic condition trends (8.28%). CONCLUSION: Our study estimates an increase of 112 000 lost PLYs caused by chronic illness in older workers in Australia between 2010 and 2030, with the most rapid growth projected to occur in men aged 55-59 years and in women aged 60-64 years. The national impact of this lost labour force participation on GDP was estimated to be $37.79 billion in 2010, increasing to $63.73 billion in 2030.

Labour force participation and the influence of having arthritis on financial status.

The objective of this study was to quantify the impact that having arthritis has on income poverty status and accumulated wealth in Australia. Cross-sectional analysis of Health&WealthMOD, a microsimulation model built on data from the Australian Bureau of Statistics' Survey of Disability, Ageing and Carers and STINMOD, an income and savings microsimulation model. Across all categories of labour force participation status (employed full time, part time or not in the labour force at all), those with arthritis were significantly more likely to be in poverty. Those employed full time with no health condition had 0.82 times the odds of being in income poverty (95 % CI 0.80-0.84) compared with those employed full time with arthritis. Those not in the labour force with no chronic health conditions had 0.36 times the odds of being in income poverty compared with those not in the labour force due to arthritis (95 % CI 0.36-0.37). For people not in the labour force with no long-term health condition, the total value of their wealth was 211 % higher (95 % CI 38-618 %) than the amount of wealth accumulated by those not in the labour force due to arthritis. Similarly, those employed part time with no chronic health condition had 50 % more wealth than those employed part time with arthritis (95 % CI 3-116 %). Arthritis has a profound impact upon the economic circumstances of individuals, which adds a further dimension to the detrimental living standards of older individuals suffering from the condition.

Depression prevention, labour force participation and income of older working aged Australians: A microsimulation economic analysis.

OBJECTIVE: Depression has economic consequences not only for the health system, but also for individuals and society. This study aims to quantify the potential economic impact of five-yearly screening for sub-syndromal depression in general practice among Australians aged 45-64 years, followed by a group-based psychological intervention to prevent progression to depression. METHOD: We used an epidemiological simulation model to estimate reductions in prevalence of depression, and a microsimulation model, Health&WealthMOD2030, to estimate the impact on labour force participation, personal income, savings, taxation revenue and welfare expenditure. RESULTS: Group therapy is estimated to prevent around 5,200 prevalent cases of depression (2.2%) and add about 520 people to the labour force. Private incomes are projected to increase by $19 million per year, tax revenues by $2.4 million, and transfer payments are reduced by $2.6 million. CONCLUSION: Group-based psychological intervention to prevent depression could result in considerable economic benefits in addition to its clinical effects.

Multiple chronic health conditions and their link with wealth assets.

BACKGROUND: There has been little research on the economic status of those with multiple health conditions, particularly on the relationship between multiple health conditions and wealth. This paper will assess the difference in the value and type of wealth assets held by Australians who have multiple chronic health conditions. METHODS: Using Health&WealthMOD, a microsimulation model of the 45-64-year-old Australian population in 2009, a counterfactual analysis was undertaken. The actual proportion of people with different numbers of chronic health conditions with any wealth, and the value of this wealth was estimated. This was compared with the counterfactual values had the individuals had no chronic health conditions. RESULTS: There was no change in the proportion of people with one health condition who actually had any wealth, compared to the counterfactual proportion had they had no chronic health conditions. Ninety-four percent of those with four or more health conditions had some accumulated wealth; however, under the counterfactual, 100% would have had some accumulated wealth. There was little change in the value of non-income-producing assets under the counterfactual, regardless of number of health conditions. Those with four or more chronic health conditions had a mean value of $17 000 in income-producing assets; under the counterfactual, the average would have been $78 000. CONCLUSION: This study has highlighted the variation in the value of wealth according to number of chronic health conditions, and hence the importance of considering multiple morbidities when discussing the relationship between health and wealth.

Back problems, comorbidities, and their association with wealth.

BACKGROUND CONTEXT: Studies assessing the economic burden of back problems have given little consideration to the presence of comorbidities. PURPOSE: To assess the difference in the value of wealth held by Australians who have back problems and varying numbers of chronic comorbidities. STUDY DESIGN: A cross-sectional study. PATIENT SAMPLE: Individuals aged 45 to 64 years in 2009: 4,388 with no chronic health conditions, 1,405 with back problems, and 3,018 with other health conditions. OUTCOME MEASURE: Total wealth (cash, shares, superannuation, investment property, and owner occupied home). METHODS: Using a microsimulation model (Health&WealthMOD), logistic regression models were used to assess the odds of having any wealth. Linear regression models were used to assess the difference in the value of this wealth. RESULTS: Those with back problems and two comorbidities had 0.16 (95% confidence interval [CI]: 0.06-0.42) times the odds and those with back problems and three or more comorbidities had 0.20 (95% CI: 0.11-0.38) times the odds of having accumulated some wealth than those with no chronic health conditions. Those with back problems and three or more comorbidities had a median value of total wealth of around $150,000, whereas those with back problems only and back problems and one comorbidity had a median value of total wealth of around $250,500. There was no significant difference in the amount of wealth accumulated by those with back problems and at least one comorbidity and those with other health conditions and the same number of comorbidities. However, those with only one health condition (excluding back problems) had 65% more wealth than those with back problems only (95% CI: 5.1-161.2). CONCLUSIONS: This study highlights the importance of considering multiple morbidities when discussing the relationship between back problems and economic circumstances.

The impact of diabetes on the labour force participation and income poverty of workers aged 45-64 years in Australia.

OBJECTIVE: To quantify the poverty status and level of disadvantage experienced by Australians aged 45-64 years who have left the labour force due to diabetes in 2010. RESEARCH DESIGN AND METHODS: A purpose-built microsimulation model, Health&WealthMOD2030, was used to estimate the poverty status and level of disadvantage of those aged 45-64 years who prematurely retire from the workforce due to diabetes. A multiple regression model was used to identify significant differences in rates of income poverty and the degree of disadvantage between those out of the labour force due to diabetes and those employed full- or part-time with no diabetes. RESULTS: 63.9% of people aged 45-64 years who were out of the labour force due to diabetes were in poverty in 2010. The odds of being in poverty for those with no diabetes and employed full-time (OR of being in poverty 0.02 95%CI: 0.01-0.04) or part-time (OR of being in poverty 0.10 95%CI: 0.05-0.23) are significantly lower than those for persons not in the labour force due to diabetes. Amongst those with diabetes, those who were able to stay in either full- or part-time employment were as much as 97% less likely to be in poverty than those who had to retire early because of the condition. Sensitivity analysis was used to assess impacts of different poverty line thresholds and key socioeconomic predictors of poverty. CONCLUSIONS: This study has shown that having diabetes and not being in the labour force because of this condition significantly increases the chances of living in poverty. Intervening to prevent or delay the onset of diabetes is likely to improve their living standards.

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

BACKGROUND: 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. METHODS: 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. RESULTS: The median annual income of people who retired early because of their diabetes was significantly lower (AU$11,784) 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 AU$384 million in individual earnings by those with diabetes, an extra AU$4 million spent in government welfare payments, a loss of AU$56 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. CONCLUSIONS: 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.

How co-morbidities magnify the effect of arthritis on labour force participation and economic status: a costs of illness study in Australia.

Few studies have assessed the impact of co-morbid conditions amongst patients with arthritis. This study will quantify the impact co-morbid health conditions have on the labour force status and economic circumstances of people with arthritis. This study uses a microsimulation model, Health&WealthMOD, to quantify the impact of co-morbidities on the labour force participation and economic circumstances of 45- to 64-year-old Australians with arthritis. The results show that the probability of being out of the labour force increases with increasing number of co-morbidities. However, there was no statistically significant difference in the amount of weekly private income received by people with arthritis and no co-morbidities, and people with arthritis and one or two co-morbidities. However, those with arthritis and three or more co-morbidities received a weekly private income 72 % lower than people with arthritis alone (95 % CI -82, -57). People with arthritis and co-morbidities paid less in tax and received more in government transfer payments. As such, it is important to consider the co-morbid conditions an individual has when assessing the impact of arthritis on labour force participation and economic circumstances. People with arthritis that have multiple co-morbid conditions are likely to have their labour force participation and economic circumstances interrupted much more than those with arthritis only.

Indirect economic impacts of comorbidities on people with heart disease.

BACKGROUND: Few studies have assessed the effect of multiple health conditions among patients with heart disease, particularly the economic implications of having multiple conditions. METHODS AND RESULTS: This study used a microsimulation model, Health&WealthMOD, to assess the effect of comorbidities on the labor force participation of 45-64-year-old Australians with heart disease, and the indirect economic costs to these individuals and government. For most comorbid conditions, there is a significant increase in the chance of an individual being out of the labor force, relative to those with heart disease alone. For example, individuals with heart disease and arthritis have more than 6-fold the odds of being out of the labor force relative to those with heart disease alone (OR 6.64, 95% CI: 2.46-17.95). People with heart disease and ≥1 comorbidities also receive a significantly lower income, pay less in taxation and receive more in government transfer payments than those with heart disease alone. CONCLUSIONS: It is important to consider whether an individual with heart disease also has other health conditions, as individuals with comorbidities have inferior financial situations and are a greater burden on government finances than those with only heart disease. (Circ J 2014; 78: 644-648).

Multiple chronic health conditions and their link with labour force participation and economic status.

AIMS: To assess the labour force participation and quantify the economic status of older Australian workers with multiple health conditions. BACKGROUND: Many older people suffer from multiple health conditions. While multiple morbidities have been highlighted as an important research topic, there has been limited research in this area to date, particularly on the economic status of those with multiple morbidities. METHODS: Cross sectional analysis of Health&WealthMOD, a microsimulation model of Australians aged 45 to 64 years. RESULTS: People with one chronic health condition had 0.59 times the odds of being employed compared to those with no condition (OR 0.59, 95% CI: 0.49, 0.71), and those with four or more conditions had 0.14 times the odds of being employed compared to those with no condition (OR 0.14, 95% CI: 0.11, 0.18). People with one condition received a weekly income 32% lower than those with no health condition, paid 49 % less tax, and received 37% more in government transfer payments; those with four or more conditions received a weekly income 94% lower, paid 97% less in tax and received over 2,000% more in government transfer payments per week than those with no condition. CONCLUSION: While having a chronic health condition is associated with lower labour force participation and poorer economic status, having multiple conditions compounds the affect - with these people being far less likely to be employed and having drastically lower incomes.