scholarly journals The Impact of Diabetes on Productivity in India

2021 ◽  
Author(s):  
Khyati K Banker ◽  
Danny Liew ◽  
Zanfina Ademi ◽  
Alice J Owen ◽  
Afsana Afroz ◽  
...  
Keyword(s):  
Labour Force ◽  
Productivity Loss ◽  
Work Productivity ◽  
Premature Mortality ◽  
Retirement Age ◽  
Years Of Life Lost ◽  
Life Years ◽  
Working Age ◽  
The Impact ◽  
Excess Deaths

<b>OBJECTIVE</b> Diabetes increases the risk of premature mortality and considerably impacts on work productivity. We sought to examine the impact of diabetes in India, in terms of excess premature mortality, years of life lost (YLL), productivity-adjusted life years (PALYs) lost and its associated economic impact. <p><b>RESEARCH DESIGN AND METHODS</b> A lifetable model was constructed to examine the productivity of the Indian working-age population currently aged 20–59 years with diabetes, until death or retirement age (60 years). The same cohort was re-simulated, hypothetically assuming that they did not have diabetes. The total difference between the two cohorts, in terms of excess deaths, YLL and PALYs lost reflected the impact of diabetes. Data regarding the prevalence of diabetes, mortality, labour force dropouts and productivity loss attributable to diabetes were derived from published sources. </p> <p><b>RESULTS</b> In 2017, an estimated 54.4 million (7.6%) people of working-age in India had diabetes. With simulated follow-up until death or retirement age, diabetes was predicted to cause 8.5 million excess deaths (62.7% of all deaths), 42.7 million YLL (7.4% of total estimated years of life lived) and 89.0 million PALYs lost (23.3% of total estimated PALYs), equating to an estimated INR 176.6 trillion (USD 2.6 trillion; PPP 9.8 trillion) in lost GDP<a>. </a></p> <p><b>CONCLUSIONS </b>Our study demonstrates the impact of diabetes on productivity loss and highlights the importance of health strategies aimed at the prevention of diabetes.</p>

scholarly journals The Impact of Diabetes on Productivity in India

2021 ◽  
Author(s):  
Khyati K Banker ◽  
Danny Liew ◽  
Zanfina Ademi ◽  
Alice J Owen ◽  
Afsana Afroz ◽  
...  
Keyword(s):  
Labour Force ◽  
Productivity Loss ◽  
Work Productivity ◽  
Premature Mortality ◽  
Retirement Age ◽  
Years Of Life Lost ◽  
Life Years ◽  
Working Age ◽  
The Impact ◽  
Excess Deaths

<b>OBJECTIVE</b> Diabetes increases the risk of premature mortality and considerably impacts on work productivity. We sought to examine the impact of diabetes in India, in terms of excess premature mortality, years of life lost (YLL), productivity-adjusted life years (PALYs) lost and its associated economic impact. <p><b>RESEARCH DESIGN AND METHODS</b> A lifetable model was constructed to examine the productivity of the Indian working-age population currently aged 20–59 years with diabetes, until death or retirement age (60 years). The same cohort was re-simulated, hypothetically assuming that they did not have diabetes. The total difference between the two cohorts, in terms of excess deaths, YLL and PALYs lost reflected the impact of diabetes. Data regarding the prevalence of diabetes, mortality, labour force dropouts and productivity loss attributable to diabetes were derived from published sources. </p> <p><b>RESULTS</b> In 2017, an estimated 54.4 million (7.6%) people of working-age in India had diabetes. With simulated follow-up until death or retirement age, diabetes was predicted to cause 8.5 million excess deaths (62.7% of all deaths), 42.7 million YLL (7.4% of total estimated years of life lived) and 89.0 million PALYs lost (23.3% of total estimated PALYs), equating to an estimated INR 176.6 trillion (USD 2.6 trillion; PPP 9.8 trillion) in lost GDP<a>. </a></p> <p><b>CONCLUSIONS </b>Our study demonstrates the impact of diabetes on productivity loss and highlights the importance of health strategies aimed at the prevention of diabetes.</p>

scholarly journals Assessing the impact of smoking on the health and productivity of the working-age Indonesian population using modelling

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e041832
Author(s):  
Regina P U Satyana ◽  
Regina E Uli ◽  
Dianna Magliano ◽  
Ella Zomer ◽  
Danny Liew ◽  
...  
Keyword(s):  
Control Strategies ◽  
Productivity Loss ◽  
Life Quality ◽  
Years Of Life Lost ◽  
Full Time ◽  
Indonesian Population ◽  
Annual Discount Rate ◽  
Life Years ◽  
Working Age ◽  
The Impact

ObjectivesTo estimate the impact of smoking in the working-age Indonesian population in terms of costs, years of life, quality-adjusted life years (QALYs) and productivity-adjusted life years (PALYs) lost.MethodsLife table modelling of Indonesian smokers aged 15–54 years, followed up until 55 years (retirement age). Contemporary data on demographics, all-cause mortality, population attributable fractions and prevalence of smoking were derived from the Institute for Health Metrics and Evaluation. The quality of life and reduction in productivity due to smoking were derived from published sources. The analysis was repeated but with the assumption that the cohorts were non-smokers. The differences in results represented the losses incurred due to smoking. Gross domestic product (GDP) per equivalent full-time worker (US$11 765) was used for estimation of the cost of each PALY, and an annual discount rate of 3.0% was applied to all costs and outcomes.ResultsThe prevalences of smoking among Indonesian working-age men and women were 67.2% and 2.16%, respectively. This study estimated that smoking caused 846 123 excess deaths, 2.9 million years of life lost (0.40%), 41.6 million QALYs lost (5.9%) and 15.6 million PALYs lost (2.3%). The total cost of productivity loss due to smoking amounted to US$183.7 billion among the working-age population followed up until retirement. Healthcare cost was predicted to be US$1.8 trillion. Over a 1-year time horizon, US$10.2 billion was lost in GDP and 117 billion was lost in healthcare costs.ConclusionSmoking imposes significant health and economic burden in Indonesia. The findings stress the importance of developing effective tobacco control strategies at the macro and micro levels, which would benefit the country both in terms of health and wealth.

scholarly journals Burden of disease and productivity impact of Streptococcus suis infection in Thailand

2021 ◽  
Vol 15 (1) ◽  
pp. e0008985
Author(s):  
Ajaree Rayanakorn ◽  
Zanfina Ademi ◽  
Danny Liew ◽  
Learn-Han Lee
Keyword(s):  
Public Health ◽  
Economic Burden ◽  
Transition Probabilities ◽  
Productivity Loss ◽  
Sensitivity Analyses ◽  
Years Of Life Lost ◽  
Uncertainty Interval ◽  
Life Years ◽  
Working Age ◽  
The Impact

Background Streptoccocus suis (S.suis) infection is a neglected zoonosis disease in humans mainly affects men of working age. We estimated the health and economic burden of S.suis infection in Thailand in terms of years of life lost, quality-adjusted life years (QALYs) lost, and productivity-adjusted life years (PALYs) lost which is a novel measure that adjusts years of life lived for productivity loss attributable to disease. Methods A decision-analytic Markov model was developed to simulate the impact of S. suis infection and its major complications: death, meningitis and infective endocarditis among Thai people in 2019 with starting age of 51 years. Transition probabilities, and inputs pertaining to costs, utilities and productivity impairment associated with long-term complications were derived from published sources. A lifetime time horizon with follow-up until death or age 100 years was adopted. The simulation was repeated assuming that the cohort had not been infected with S.suis. The differences between the two set of model outputs in years of life, QALYs, and PALYs lived reflected the impact of S.suis infection. An annual discount rate of 3% was applied to both costs and outcomes. One-way sensitivity analyses and Monte Carlo simulation modeling technique using 10,000 iterations were performed to assess the impact of uncertainty in the model. Key results This cohort incurred 769 (95% uncertainty interval [UI]: 695 to 841) years of life lost (14% of predicted years of life lived if infection had not occurred), 826 (95% UI: 588 to 1,098) QALYs lost (21%) and 793 (95%UI: 717 to 867) PALYs (15%) lost. These equated to an average of 2.46 years of life, 2.64 QALYs and 2.54 PALYs lost per person. The loss in PALYs was associated with a loss of 346 (95% UI: 240 to 461) million Thai baht (US$11.3 million) in GDP, which equated to 1.1 million Thai baht (US$ 36,033) lost per person. Conclusions S.suis infection imposes a significant economic burden both in terms of health and productivity. Further research to investigate the effectiveness of public health awareness programs and disease control interventions should be mandated to provide a clearer picture for decision making in public health strategies and resource allocations.

scholarly journals Health and productivity burden of coronary heart disease in the working Indonesian population using life-table modelling

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e039221 ◽  
Author(s):  
Regina E Uli ◽  
Regina P U Satyana ◽  
Ella Zomer ◽  
Dianna Magliano ◽  
Danny Liew ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Life Table ◽  
Secondary Outcome ◽  
Mortality Data ◽  
Retirement Age ◽  
Years Of Life Lost ◽  
Life Years ◽  
Working Age ◽  
The Impact

ObjectivesThe impact of coronary heart disease (CHD) and its effect on work productivity at a population level remains unknown in Indonesia. This study estimates the health and productivity lost to CHD in terms of years of life, quality-adjusted life years (QALYs) and productivity-adjusted life years (PALYs).Setting and participantsA life-table model was constructed to simulate the experiences of Indonesians currently aged 15–54 years (working age) with CHD, followed-up to 55 years (retirement age). The life-table analysis was then repeated assuming that the cohort did not have CHD. Differences in the results reflected the impact of CHD. Demographical, prevalence and mortality data were based on the 2017 Global Burden of Disease study and 2018 Indonesian National Health Survey. Costs, productivity indices and utilities were derived from published sources. The cost of each PALY was assumed to be equivalent to gross domestic product per equivalent full-time worker (US$11 765). Future costs and outcomes were discounted by 3% annually.Primary and secondary outcome measuresDifferences in total deaths, years of life and PALYs represented the impact of CHD.ResultsAt present, 1 954 543 (1.45%) Indonesians of working-age have CHD. By retirement age, it was estimated that CHD resulted in 32 492 (36.6%) excess deaths, 128 132 (0.5%) years of life lost, 2 331 495 (10.5%) QALYs lost and 1 589 490 (6.9%) PALYs lost. The economic impact of lost productivity amounted to US$33.3 billion, and healthcare costs to US$139 billion.ConclusionThe health and economic burden of CHD in Indonesia looms large. This highlights the importance of its prevention and control, strategies for which, if effective, will deliver financial return.

scholarly journals Impact of the Burden of COVID-19 in Italy: Results of Disability-Adjusted Life Years (DALYs) and Productivity Loss

2020 ◽  
Vol 17 (12) ◽  
pp. 4233 ◽  
Author(s):  
Mario Cesare Nurchis ◽  
Domenico Pascucci ◽  
Martina Sapienza ◽  
Leonardo Villani ◽  
Floriana D’Ambrosio ◽  
...  
Keyword(s):  
Productivity Loss ◽  
Premature Mortality ◽  
Direct Costs ◽  
Years Of Life Lost ◽  
The Novel ◽  
Disability Adjusted Life Years ◽  
Disability Adjusted Life ◽  
Life Years ◽  
The Government ◽  
Novel Coronavirus

The WHO declared the novel coronavirus disease a pandemic, with severe consequences for health and global economic activity and Italy is one of the hardest hit countries. This study aims to assess the socio-economic burden of COVID-19 pandemic in Italy through the estimation of Disability-Adjusted Life Years (DALYs) and productivity loss. The observational study was based on data from official governmental sources collected since the inception of epidemic until 28 April 2020. DALYs for a disease combines the years of life lost due to premature mortality in the population and the years lost due to disability of the disease. In addition to DALYs, temporary productivity loss due to absenteeism from work and permanent productivity loss due to premature mortality were estimated using the Human Capital Approach. The total DALYs amount to 2.01 per 1000 persons. The total permanent productivity loss was around EUR 300 million while the temporary productivity loss was around EUR 100 million. This evaluation does not consider other economic aspects related to lockdown, quarantine of contacts, healthcare direct costs etc. The burden of disease methodology is functional metric for steering choices of health policy and allowing the government to be accountable for the utilization of resources.

scholarly journals Impact of COVID-19 infection on life expectancy, premature mortality, and DALY in Maharashtra, India

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guru Vasishtha ◽  
Sanjay K. Mohanty ◽  
Udaya S. Mishra ◽  
Manisha Dubey ◽  
Umakanta Sahoo
Keyword(s):  
Life Expectancy ◽  
Premature Mortality ◽  
The State ◽  
Multiple Sources ◽  
Life Expectancy At Birth ◽  
Disability Adjusted Life ◽  
Life Years ◽  
Working Age ◽  
Using Data ◽  
The Impact

Abstract Background The COVID-19 infections and deaths have largely been uneven within and between countries. With 17% of the world’s population, India has so far had 13% of global COVID-19 infections and 8.5% of deaths. Maharashtra accounting for 9% of India’s population, is the worst affected state, with 19% of infections and 33% of total deaths in the country until 23rd December 2020. Though a number of studies have examined the vulnerability to and spread of COVID-19 and its effect on mortality, no attempt has been made to understand its impact on mortality in the states of India. Method Using data from multiple sources and under the assumption that COVID-19 deaths are additional deaths in the population, this paper examined the impact of the disease on premature mortality, loss of life expectancy, years of potential life lost (YPLL), and disability-adjusted life years (DALY) in Maharashtra. Descriptive statistics, a set of abridged life tables, YPLL, and DALY were used in the analysis. Estimates of mortality indices were compared pre- and during COVID-19. Result COVID-19 attributable deaths account for 5.3% of total deaths in the state and have reduced the life expectancy at birth by 0.8 years, from 73.2 years in the pre-COVID-19 period to 72.4 years by the end of 2020. If COVID-19 attributable deaths increase to 10% of total deaths, life expectancy at birth will likely reduce by 1.4 years. The probability of death in 20–64 years of age (the prime working-age group) has increased from 0.15 to 0.16 due to COVID-19. There has been 1.06 million additional loss of years (YPLL) in the state, and DALY due to COVID-19 has been estimated to be 6 per thousand. Conclusion COVID-19 has increased premature mortality, YPLL, and DALY and has reduced life expectancy at every age in Maharashtra.

scholarly journals Estimating the return on investment of the Bureau of Tobacco Free Florida tobacco control programme from 1999 to 2015

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e040012
Author(s):  
James Nonnemaker ◽  
Anna J MacMonegle ◽  
Nathan Mann ◽  
Robyn Woodlea ◽  
Jennifer Duke ◽  
...  
Keyword(s):  
Tobacco Control ◽  
Return On Investment ◽  
Premature Mortality ◽  
Control Programme ◽  
Attributable Mortality ◽  
Years Of Life Lost ◽  
Synthetic Control ◽  
Healthcare Expenditures ◽  
Life Years ◽  
The Impact

ObjectiveTo assess the return on investment (ROI) of the Florida tobacco control programme, the Bureau of Tobacco Free Florida (BTFF), in terms of healthcare expenditure savings and mortality cost saved as a result of reduced mortality due to the programme from 1999 to 2015.MethodsWe use a synthetic control method to estimate the impact of the BTFF on smoking-attributable mortality, years of life lost (YLL), healthcare expenditures, and the economic value of premature mortality due to smoking in Florida from 1999 through 2015. We calculated an ROI for healthcare expenditures and for the value of life years saved.ResultsFrom 1999 to 2015, adult smoking prevalence in Florida averaged 0.98 percentage points lower than prevalence in the synthetic control states (19.6% vs 20.6%). The ROI over the period from 1999 to 2015 was 9.61 for healthcare expenditures and 112.44 for premature mortality. These ROIs suggest that for every US$1 of expenditure by BTFF, smoking-attributable healthcare expenditures decreased by almost US$11 and reductions in the economic costs associated with YLL due to smoking-attributable mortality totaled approximately US$113.ConclusionsOur results suggest the BTFF resulted in fewer YLL, substantial healthcare cost savings and substantial savings in terms of mortality costs. The positive ROIs for healthcare expenditures and premature mortality suggest that the BTFF is a good investment of public funds.

scholarly journals Estimation of the economic burden of COVID-19 using disability-adjusted life years (DALYs) and productivity losses in Kerala, India: a model-based analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e049619
Author(s):  
Denny John ◽  
M S Narassima ◽  
Jaideep Menon ◽  
Jammy Guru Rajesh ◽  
Amitava Banerjee
Keyword(s):  
Economic Burden ◽  
Premature Mortality ◽  
Secondary Outcome ◽  
Years Of Life Lost ◽  
Disability Adjusted Life Years ◽  
Model Based ◽  
Disability Adjusted Life ◽  
Life Years ◽  
The Impact ◽  
Model Based Analysis

ObjectivesFrom the beginning of the COVID-19 pandemic, clinical practice and research globally have centred on the prevention of transmission and treatment of the disease. The pandemic has had a huge impact on the economy and stressed healthcare systems worldwide. The present study estimates disability-adjusted life years (DALYs), years of potential productive life lost (YPPLL) and cost of productivity lost (CPL) due to premature mortality and absenteeism secondary to COVID-19 in the state of Kerala, India.SettingDetails on sociodemographics, incidence, death, quarantine, recovery time, etc were derived from public sources and the Collective for Open Data Distribution-Keralam. The working proportion for 5-year age–gender cohorts and the corresponding life expectancy were obtained from the 2011 Census of India.Primary and secondary outcome measuresThe impact of the disease was computed through model-based analysis on various age–gender cohorts. Sensitivity analysis was conducted by adjusting six variables across 21 scenarios. We present two estimates, one until 15 November 2020 and later updated to 10 June 2021.ResultsSeverity of infection and mortality were higher among the older cohorts, with men being more susceptible than women in most subgroups. DALYs for males and females were 15 954.5 and 8638.4 until 15 November 2020, and 83 853.0 and 56 628.3 until 10 June 2021. The corresponding YPPLL were 1323.57 and 612.31 until 15 November 2020, and 6993.04 and 3811.57 until 10 June 2021, and the CPL (premature mortality) were 263 780 579.94 and 41 836 001.82 until 15 November 2020, and 1 419 557 903.76 and 278 275 495.29 until 10 June 2021.ConclusionsMost of the COVID-19 burden was contributed by years of life lost. Losses due to YPPLL were reduced as the impact of COVID-19 infection was lesser among the productive cohorts. The CPL values for individuals aged 40–49 years old were the highest. These estimates provide the data necessary for policymakers to work on reducing the economic burden of COVID-19 in Kerala.

scholarly journals The impact of diabetes on the productivity and economy of Bangladesh

2020 ◽  
Vol 5 (6) ◽  
pp. e002420 ◽  
Author(s):  
Afsana Afroz ◽  
Thomas R Hird ◽  
Ella Zomer ◽  
Alice Owen ◽  
Lei Chen ◽  
...  
Keyword(s):  
Life Table ◽  
Productivity Loss ◽  
Mortality Data ◽  
Years Of Life Lost ◽  
Full Time ◽  
Life Years ◽  
Bangladeshi Population ◽  
Disease Study ◽  
The Impact

AimsTo estimate the impact of type 2 diabetes in terms of mortality, years of life lost (YLL) and productivity-adjusted life years (PALY) lost in Bangladesh.MethodsA life table model was constructed to estimate the productivity of the Bangladeshi population of current working age (20–59 years) with diabetes. Follow-up to 60 years (retirement age) was simulated. The life table analysis was then repeated assuming that the cohort did not have diabetes, with subsequent improvement in productivity. Differences in the results of the two analyses reflected the impact of diabetes on health and productivity. Demographic and the prevalence of diabetes data were sourced from the International Diabetes Foundation estimates for 2017 and mortality data were based on the 2017 Global Burden of Disease study. Relative risk and productivity indices were based on an Indian and Bangladeshi study, respectively. The cost of each PALY was assumed to be equivalent to gross domestic product (GDP) per equivalent full-time worker (US$8763). Future costs and years of life, and PALYs lived were discounted at an annual rate of 3%.ResultsAssuming a follow-up of this population (aged 20–59 years) until age 60 years or death, an estimated 813 807 excess deaths, loss of 4.0 million life years (5.5%) and 9.2 million PALYs (20.4%) were attributable to having diabetes. This was equivalent to 0.7 YLL, and 1.6 PALYs lost per person. The loss in PALYs equated to a total of US$97.4 billion lost (US$16 987 per person) in GDP. The results of the scenario analysis showed that the estimation was robust.ConclusionIn Bangladesh, the impact of diabetes on productivity loss and the broader economy looms large, and poses a substantial risk to the country’s future prosperity. This highlights the critical importance of health strategies aimed at the control of diabetes.

Estimating the Productivity Impact of Acute Myeloid Leukemia in Australia Between 2020 and 2029, Using a Novel Work Utility Measure: The Productivity-Adjusted Life Year (PALY)

2021 ◽  
pp. OP.20.00904
Author(s):  
Catriona Parker ◽  
Danny Liew ◽  
Zanfina Ademi ◽  
Alice J. Owen ◽  
Darshini Ayton ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
High Mortality ◽  
Myeloid Leukemia ◽  
Productivity Loss ◽  
Years Of Life Lost ◽  
Mortality And Morbidity ◽  
Life Years ◽  
Secondary Analyses ◽  
The Impact ◽  
Acute Myeloid

PURPOSE: Acute myeloid leukemia (AML) is a rare hematologic malignancy accounting for 0.8% of new cancer diagnoses in Australia. High mortality and morbidity affect work productivity through workforce dropout and premature death. This study sought to estimate the productivity loss attributable to AML in the Australian population over 10 years and to estimate the costs of this productivity loss. Productivity was measured using productivity-adjusted life years (PALYs), a similar concept to quality-adjusted life years, but adjusts for the productivity loss attributable to disease, rather than impaired health. MATERIALS AND METHODS: Dynamic life tables modeled the Australian working population (age 15-65 years) between 2020 and 2029. The model population had two cohorts: those with and without AML. Differences in life years, PALYs, and costs represented the health and productivity impact of AML. Secondary analyses evaluated the impact of different scenarios. RESULTS: Over the next 10 years, there will be 7,600 years of life lost and 7,337 PALYs lost because of AML, amounting to Australian dollars (AU$) 1.43 billion in lost gross domestic product ($971 million in US dollars). Secondary analyses highlight potential savings of approximately AU$52 million if survival rates were improved by 20% and almost AU$118 million in savings if the return-to-work rates increased by 20% on the current estimates. CONCLUSION: Our study demonstrates that even in low-incidence cancer, high mortality and morbidity translate to profound impacts on years of life, productivity, and the broader economy. Better treatment strategies are likely to result in significant economic gains. This highlights the value of investing in research for improved therapies.

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