Disability weight measurement for the severity of different diseases in Wuhan, China
Xiaoxue LiuYan GuoFang WangYong YuYaqiong YanHaoyu WenFang ShiYafeng WangXuyan WangHui ShenShiyang LiYanyun GongSisi KeWei ZhangQiman JinGang ZhangYu WuMaigeng ZhouChuanhua Yu
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Abstract Background Measurement of the Chinese burden of disease with disability-adjusted life-years (DALYs) requires disability weight (DW) that quantify health losses for all non-fatal consequences of disease and injury. The Global Burden of Disease (GBD) 2013 DW study indicates that it is limited by lack of geographic variation in DW data and by the current measurement methodology. We aim to estimate DW for a set of health states from major diseases in the Wuhan population. Methods We conducted the DW measurement study for 206 health states through a household survey with computer-assisted face-to-face interviews and a web-based survey. Based on GBD 2013 DW study, paired comparison (PC) and Population health equivalence (PHE) method was used and different PC/PHE questions were randomly assigned to each respondent. In statistical analysis, the PC data was analyzed by probit regression. The probit regression results will be anchored by results from the PHE data analyzed by interval regression on the DW scale units between 0 (no loss of health) and 1 (loss equivalent to death). Results A total of 2610 and 3140 individuals were included in the household and web-based survey, respectively. The results from the total pooled data showed health state “mild anemia” (DW = 0.005, 95% UI 0.000–0.027) or “allergic rhinitis (hay fever)” (0.005, 95% UI 0.000–0.029) had the lowest DW and “heroin and other opioid dependence, severe” had the highest DW (0.699, 95% UI 0.579–0.827). A high correlation coefficient (Pearson’s r = 0.876; P < 0.001) for DWs of same health states was observed between Wuhan’s survey and GBD 2013 DW survey. Health states referred to mental symptom, fatigue, and the residual category of other physical symptoms were statistically significantly associated with a lower Wuhan’s DWs than the GBD’s DWs. Health states with disfigurement and substance use symptom had a higher DW in Wuhan population than the GBD 2013 study. Conclusions This set of DWs could be used to calculate local diseases burden for health policy-decision in Wuhan population. The DW differences between the GBD’s survey and Wuhan’s survey suggest that there might be some contextual or culture factors influencing assessment on the severity of diseases.Keywords:
Disability-adjusted life year
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Campylobacteriosis
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This is an overview of the first burden of disease and injury studies carried out in Australia. Methods developed for the World Bank and World Health Organization Global Burden of Disease Study were adapted and applied to Australian population health data. Depression was found to be the top-ranking cause of non-fatal disease burden in Australia, causing 8% of the total years lost due to disability in 1996. Mental disorders overall were responsible for nearly 30% of the non-fatal disease burden. The leading causes of total disease burden (disability-adjusted life years [DALYs]) were ischaemic heart disease and stroke, together causing nearly 18% of the total disease burden. Depression was the fourth leading cause of disease burden, accounting for 3.7% of the total burden. Of the 10 major risk factors to which the disease burden can be attributed, tobacco smoking causes an estimated 10% of the total disease burden in Australia, followed by physical inactivity (7%).
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Disease burden indicators assess the impact of disease on a population. They integrate mortality and disability in a single indicator. This allows setting priorities for health services and focusing resources.To analyze the burden of neurological diseases in Peru from 1990-2015.A descriptive study that used the epidemiological data published by the Institute for Health Metrics and Evaluation of Global Burden of Diseases from 1990 to 2015. Disease burden was measured using disability-adjusted life years (DALY) and their corresponding 95% uncertainty intervals (UIs), which results from the addition of the years of life lost (YLL) and years lived with disability (YLD).The burden of neurological diseases in Peru were 9.06 and 10.65%, in 1990 and 2015, respectively. In 2015, the main causes were migraine, cerebrovascular disease (CVD), neonatal encephalopathy (NE), and Alzheimer's disease and other dementias (ADD). This last group and nervous system cancer (NSC) increased 157 and 183% of DALY compared to 1990, respectively. Young population (25 to 44 years old) and older (>85 years old) were the age groups with the highest DALY. The neurological diseases produced 11.06 and 10.02% of the national YLL (CVD as the leading cause) and YLD (migraine as the main cause), respectively.The burden of disease (BD) increased by 1.6% from 1990 to 2015. The main causes were migraine, CVD, and NE. ADD and NSC doubled the DALY in this period. These diseases represent a significant cause of disability attributable to the increase in the life expectancy of our population among other factors. Priority actions should be taken to prevent and treat these causes.
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This paper uses the Disability Adjusted Life Year (DALY) to estimate disease burden at a local level and relates this to programme budget (PB) data.We estimated DALY using the global burden of disease (GBD) template. For years of life lost, local mortality data were used and for years of life with disability, the GBD estimates from World Health Organization EURO A region (including the UK) were used. We used PB data to analyse how healthcare expenditure matched disease burden.In 2005 the burden of disease in Lambeth was estimated at 36,368 DALYs (13,515 DALYs lost per 100,000) and in Southwark was 34,196 DALYs (13,244 DALYs lost per 100,000). There were gender and area differences. The ranking is different when mortality and morbidity are combined compared with mortality alone. We estimated that the average spend per DALY lost in 2005 was 11,066 pounds in Lambeth and 9390 pounds in Southwark.We used a pragmatic approach to estimate overall disease burden providing a local, more comprehensive picture with important differences in spend by disease and health authority area. However, a more detailed approach to support decisions about prioritization based on modelling interventions that impact on avoidable burden of disease is recommended.
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To support public health policy, information on the burden of disease is essential. In recent years, the Disability-Adjusted Life Year (DALY) has emerged as the most important summary measure of public health. DALYs quantify the number of healthy life years lost due to morbidity and mortality, and thereby facilitate the comparison of the relative impact of diseases and risk factors and the monitoring of public health over time. Evidence on the disease burden in Belgium, expressed as DALYs, is available from international and national efforts. Non-communicable diseases and injuries dominate the overall disease burden, while dietary risks, tobacco smoking, and high body-mass index are the major risk factors for ill health. Notwithstanding these efforts, if DALYs were to be used for guiding health policy, a more systematic approach is required. By integrating DALYs in the current data generating systems, comparable estimates, rooted in recent local data, can be produced. This might however be hampered by several restrictions, such as limited harmonization, timeliness, inclusiveness and accessibility of current databases. Routine quantification of disease burden in terms of DALYs would provide a significant added value to evidence-based public health policy in Belgium, although some hurdles need to be cleared.
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The disability adjusted life year (DALY), a single indicator of the burden of disease, is widely used to measure the burden of diseases, injuries, and risk factors. In this study, we review the relative sizes of the burden of disease worldwide and the characteristics of the burden of disease of the Korean population. Future research directions for study of the burden of disease in Korea are also suggested. In the Korean population, diabetes mellitus was the leading cause of the burden of disease (970 DALYs per 100,000 population) in 2002, followed by cerebrovascular disease (937 DALYs per 100,000 population) and asthma (709 DALYs per 100,000 population), which differed with the leading causes of the burden of disease globally: unipolar depressive disorder, ischemic heart disease, and cerebrovascular disease. In 2007, cirrhosis of the liver in males and cerebrovascular disease in females became the leading causes of the burden of disease of the Korean population with the epidemiologic transition. Despite the methodological difference with global burden of disease study, these findings represent the characteristics of the burden of disease in Korea. Though many studies have been conducted to measure the burden of disease in Korea, there is a need to go beyond these to combine policymaking for resource allocation, such as cost effectiveness analysis, with burden of disease studies.
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The Global Burden of Disease concept, first published in 1996, constitutes the most comprehensive and consistent set of estimates of mortality and morbidity yet (Murray & Lopez 1996), and WHO regularly develops burden of disease estimates at regional and global level (WHO 2008) for more than 135 causes of disease and injury. The Global Burden of Disease Study uses a summary measure of population health, the disability-adjusted life year (DALY). Despite the technical and ethical, but also political and economic debates they provoke (Nygaard 2000; Bonneux 2002), DALYs are used by the World Bank and, increasingly, by researchers to quantify the burden of disease in a given area. The DALY combines information about mortality and morbidity in a single number and thus allows for describing the losses caused by disability and the losses caused by premature death in a single unit. A DALY is a function of years of life lost and of years lived with disability. One DALY equals the loss of 1 year of healthy life (Spiegel et al. 2008). According to the latest data available on the Global Burden of Disease (WHO 2008), the estimated burden of infectious and parasitic diseases was 160 million DALYs11 Standard DALYs with 3% discounting and age weights. in Africa; the burden of non-communicable diseases was estimated at 79 million DALYs. When, in addition, low- and middle-income countries22 Defined as countries with a gross national income per capita less than 10 066 US$ in 2004. from the Americas, Africa, the Eastern Mediterranean Region, South-East Asia and the Western Pacific are considered, these figures rise to 436 million DALYs for infectious and parasitic diseases and to 1.2 billion for non-communicable diseases. In all low- and middle-income countries worldwide, 2.9 DALYs owing to non-communicable diseases correspond to 1 DALY owing to infectious and parasitic diseases. The most relevant of these are tuberculosis, HIV/AIDS, diarrhoeal diseases, childhood infections such as measles or pertussis and malaria. The compilation provided by WHO neither includes infectious respiratory diseases nor maternal and perinatal conditions. Conditions such as malignant neoplasms, diabetes mellitus, neuropsychiatric disorders, sense organ disorders such as cataracts, cardiovascular diseases, respiratory non-infectious conditions and digestive diseases (peptic ulcer and others) are classified as non-communicable diseases. In Africa, non-communicable diseases account for half as many DALYs as infectious and parasitic diseases, but in low- and middle-income countries from all WHO regions, non-communicable diseases cause nearly three times as many DALYs as infectious and parasitic diseases. These alarming figures warrant urgent attention. In low- and middle-income countries, under-reporting in some areas and over-reporting in others, mainly owing to inadequate diagnostic resources, notoriously results in imprecision and inaccurate DALY estimates. However, it is conceivable, if not likely, that non-communicable diseases are under-reported more frequently than infectious and parasitic diseases as has been shown for patients with kidney injuries, for example (Cerdáet al. 2008). Many African health systems are ill-prepared for patients suffering from chronic diseases or even for the current transition to ageing populations (Nordberg 1997). The reason may be that health systems in low- and middle-income countries focus on acute and infectious disorders because these conditions have long been the prime causes of morbidity and mortality. But patterns of disease are changing because of the epidemiologic transition, changes in lifestyle and nutrition, among other factors. Low- and middle-income countries now experience the double burden of endemic infectious and parasitic diseases and steadily growing incidences of non-communicable diseases (Amuna & Zotor 2008). Interestingly, structural interventions to diagnose and prevent non-communicable diseases may be cost-effective and successfully integrated into primary healthcare systems (Beaglehole et al. 2007; Gaziano et al. 2007). WHO forecasts that by 2020 non-communicable diseases will account for roughly 75% of fatalities in the developing world (Kelishadi 2007). Nevertheless, Tropical Medicine research obstinately concentrates on infectious and parasitic diseases. In view of Global Burden of Disease data, this emphasis does not appear to be entirely justified. The preamble of the constitution of the International Federation for Tropical Medicine states that ‘… within the past decade developing countries and international organizations have redefined the health problems and priorities much more broadly to address additional major causes of death, disability and diseases in vulnerable groups.’ The broad and multidisciplinary nature of Tropical Medicine calls for substantial action beyond clinical, experimental and theoretical infectology. Infectious and parasitic diseases, in particular HIV/AIDS, tuberculosis and malaria, are indubitably significant determinants of morbidity and mortality in many low- and middle-income countries, and certainly research must not abate or neglect them. But Tropical Medicine research should recognize the data and integrate studies of non-communicable diseases effectively. Funding bodies, non-governmental institutions and researchers from low-, middle- and high-income countries should reconsider research priorities. More effort and funding are needed to scale up fundamental and applied non-communicable disease research in low- and middle-income countries. These endeavours will have to precede due changes in health policies and should eventually result in necessary adaptations of health systems to the pandemic of non-communicable diseases. Thus, researchers in Tropical Medicine and policy makers could bring more people closer to health, expansively defined by the WHO as: ‘… a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.’
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