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Background The eastern Mediterranean region is comprised of 22 countries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the United Arab Emirates, and Yemen. Since our Global Burden of Disease Study 2010 (GBD 2010), the region has faced unrest as a result of revolutions, wars, and the so-called Arab uprisings. The objective of this study was to present the burden of diseases, injuries, and risk factors in the eastern Mediterranean region as of 2013. Methods GBD 2013 includes an annual assessment covering 188 countries from 1990 to 2013. The study covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Our GBD 2013 analyses included the addition of new data through updated systematic reviews and through the contribution of unpublished data sources from collaborators, an updated version of modelling software, and several improvements in our methods. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically. Findings The leading cause of death in the region in 2013 was ischaemic heart disease (90·3 deaths per 100 000 people), which increased by 17·2% since 1990. However, diarrhoeal diseases were the leading cause of death in Somalia (186·7 deaths per 100 000 people) in 2013, which decreased by 26·9% since 1990. The leading cause of disability-adjusted life-years (DALYs) was ischaemic heart disease for males and lower respiratory infection for females. High blood pressure was the leading risk factor for DALYs in 2013, with an increase of 83·3% since 1990. Risk factors for DALYs varied by country. In low-income countries, childhood wasting was the leading cause of DALYs in Afghanistan, Somalia, and Yemen, whereas unsafe sex was the leading cause in Djibouti. Non-communicable risk factors were the leading cause of DALYs in high-income and middle-income countries in the region. DALY risk factors varied by age, with child and maternal malnutrition affecting the younger age groups (aged 28 days to 4 years), whereas high bodyweight and systolic blood pressure affected older people (aged 60–80 years). The proportion of DALYs attributed to high body-mass index increased from 3·7% to 7·5% between 1990 and 2013. Burden of mental health problems and drug use increased. Most increases in DALYs, especially from non-communicable diseases, were due to population growth. The crises in Egypt, Yemen, Libya, and Syria have resulted in a reduction in life expectancy; life expectancy in Syria would have been 5 years higher than that recorded for females and 6 years higher for males had the crisis not occurred. Interpretation Our study shows that the eastern Mediterranean region is going through a crucial health phase. The Arab uprisings and the wars that followed, coupled with ageing and population growth, will have a major impact on the region’s health and resources. The region has historically seen improvements in life expectancy and other health indicators, even under stress. However, the current situation will cause deteriorating health conditions for many countries and for many years and will have an impact on the region and the rest of the world. Based on our findings, we call for increased investment in health in the region in addition to reducing the conflicts. Funding Bill & Melinda Gates Foundation.
The Global Burden of Disease Study 2013 (GBD 2013) includes an annual assessment covering 188 countries from 1990 to 2013. It covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Detailed descriptions of the method and approach of GBD 2013 have been published elsewhere.4, 5, 6, 7 Key changes in the methods from GBD 2010 are the inclusion of new data through updated systematic reviews and the contribution of unpublished data sources from various collaborators; the use of a counterfactual approach for estimating causes of diarrhoea and pneumonia; elaboration of the sequelae list to include asymptomatic states; use of more detailed nature of injury codes (N-codes); improvements to the Bayesian meta-regression method; increased simulation size for comorbidity; estimation of the prevalence of injuries by cohort; and use of a new method to estimate the distribution of mild, moderate, and severe anaemia by cause. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically. We report 95% uncertainty intervals for each value in our analysis. Evidence before this study The Global Burden of Disease Study 2010 (GBD 2010) became available in 2012. GBD 2010 reported on disability-adjusted life-years (DALYs), health-adjusted life expectancy, and 67 risks and risk clusters by 21 world regions and 188 countries. GBD 2010 covered 20 age and sex groups. Added value of this study GBD 2013 includes an annual assessment covering 188 countries, from 1990 to 2013. It covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. GBD 2013 included key methodological differences from GBD 2010, which were inclusion of new data through updated systematic reviews and through the contribution of unpublished data sources from many collaborators; use of a counterfactual approach for estimating diarrhoea and pneumonia causes; elaboration of the sequelae list to include asymptomatic states; use of more detailed nature of injury codes (N-codes); improvements to the Bayesian meta-regression method; increased simulation size for comorbidity; estimation of the prevalence of injuries by cohort; and use of a new method to estimate the distribution of mild, moderate, and severe anaemia by cause. This study provides an overview of the comprehensive burden of diseases and risk factors for the eastern Mediterranean region. Implications of all the available evidence The eastern Mediterranean region is facing numerous health challenges, as a result of previous wars, revolutions, the wars that followed, and ageing and population growth. These challenges will have a major impact on health outcomes and available resources. The region has historically seen improvements in life expectancy and other health indicators even under stress. However, according to our study, the current situation has resulted in deteriorating health conditions for many countries that are threatening these gains and will have an impact on the region and the rest of the world. On the basis of our data, we call for increased investment in health in the region and the end of ongoing conflicts. We generated child mortality rates and adult mortality rates under the influence of natural disasters and armed conflicts as previously described.7 Because of ongoing unrest and war, some datapoints needed for our analyses were not available. A list of all datapoints used in this study are available on our Global Health Data Exchange web page. When data were unavailable, we relied on our ensemble modelling techniques to generate the estimates using other available variables and the information for neighbouring countries or countries with a similar health profile in the region. We used six different modelling strategies for the 240 causes of death using our cause-of-death ensemble model for causes with sufficient information. We estimated national time series from 1950 to 2013 for gross domestic product, educational attainment, tobacco prevalence, and obesity. For mortality rates of children younger than 5 years, we analysed all survey, census, sample registration, and vital registration sources. Wherever possible, we analysed microdata from surveys and censuses with updated methods for child mortality. We corrected for bias in different sources in specific countries. For adult mortality, we identified all available vital registration data, sibling history survey data, sample registration data, and household recall of deaths. We assessed vital registration data for completeness and analysed sibling history data to account for survivor bias, zero-surviving sibships, and recall bias. We used spatiotemporal regression and Gaussian process regression to synthesise all measurements of mortality. We used UN population estimates that account for migration in our analyses. Moreover, we applied mortality shocks based on multiple reports to our analyses. We used the comparative risk assessment approach to evaluate how much of the burden of disease observed in a given year can be attributed to past exposure to a risk factor.7 We estimated attributable burden by comparing observed health outcomes with outcomes that would have been observed if an alternative or counterfactual level of exposure had taken place in the past. We used the exposure level that minimises risk for the population, termed the theoretical minimum risk exposure level. We avoided double counting in the presentation of overall results by computing the overlap for joint risk distributions: behavioural risks alone; environmental or occupational risks alone; metabolic risks alone; behavioural and environmental or occupational risks together; behavioural and metabolic risks together; environmental or occupational and metabolic risks together; and behavioural, environmental or occupational, and metabolic risks together. We cross-tabulated the quantiles of disability-adjusted life-years (DALYs) by quintiles of annual DALY increase from 1990 to 2013 to show rates of DALY increase by burden. We divided the region into three categories according to the gross national income (GNI) per capita. The first category represents the low-income countries with an average GNI per capita of US$523·3 On the opposite end of the spectrum are oil-rich, high-income countries with an average GNI per capita of $39 688. The nations that lie in between are the middle-income countries with an average GNI per capita of $3251, which can be further subdivided into lower-middle-income and upper-middle-income countries. Low-income countries were Afghanistan, Djibouti, Somalia, and Yemen. Middle-income countries were Egypt, Iran, Iraq, Jordan, Lebanon, Libya, Morocco, Pakistan, Palestine, Sudan, Syria, and Tunisia. High-income countries were Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility to submit the paper.
