Adolescent health in the Eastern Mediterranean Region: findings from the global burden of disease 2015 study

Adolescent health in the Eastern Mediterranean Region: findings from the global burden of disease... Int J Public Health (2018) 63 (Suppl 1):S79–S96 https://doi.org/10.1007/s00038-017-1003-4 O R I G IN AL ARTI CL E Adolescent health in the Eastern Mediterranean Region: findings from the global burden of disease 2015 study GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Received: 1 May 2017 / Revised: 15 June 2017 / Accepted: 21 June 2017 / Published online: 3 August 2017 The Author(s) 2017. This article is an open access publication Abstract amongst adolescents. Additionally, many EMR countries Objectives The 22 countries of the East Mediterranean had high rates of adolescent pregnancy and unmet need for Region (EMR) have large populations of adolescents aged contraception. 10–24 years. These adolescents are central to assuring the Conclusions Even with the return of peace and security, health, development, and peace of this region. We descri- adolescents will have a persisting poor health profile that bed their health needs. will pose a barrier to socioeconomic growth and develop- Methods Using data from the Global Burden of Disease ment of the EMR. Study 2015 (GBD 2015), we report the leading causes of mortality and morbidity for adolescents in the EMR from Keywords Adolescent health  Burden of disease  Eastern 1990 to 2015. We also report the prevalence of key health Mediterranean Region risk behaviors and determinants. Results Communicable diseases and the health conse- quences of natural disasters reduced substantially between Introduction 1990 and 2015. However, these gains have largely been offset by the health impacts of war and the emergence of The World Health Organization’s Eastern Mediterranean non-communicable diseases (including mental health dis- Region (EMR) is an administrative region of 22 countries orders), unintentional injury, and self-harm. Tobacco (Table 1) that while rich in natural resources, has marked smoking and high body mass were common health risks country-level variation in socioeconomic wealth (ranging from $US 549.3 per capita in Somalia to $US 73,653.4 per capita in Qatar), health system capacities and health cov- This article is part of the supplement ‘‘The state of health in the erage (Blair et al. 2014; Mandil et al. 2013; WHO 2017b). Eastern Mediterranean Region, 1990–2015’’. Many countries in the EMR have recently experienced social and political instabilities, civil unrest, war, and mass The members of GBD (Global Burden of Disease) 2015 Eastern Mediterranean Region Adolescent Health Collaborators are listed at displacement of people (Mokdad et al. 2016a). As a result, the end of the article. Ali H. Mokdad, on behalf of GBD 2015 Eastern health in many EMR countries has failed to improve in Mediterranean Region Adolescent Health Collaborators, is the recent years (Mokdad et al. 2016a, 2014). As other papers corresponding author. in this series highlight, there is now an increasing burden of Electronic supplementary material The online version of this many preventable health problems including HIV, mental article (doi:10.1007/s00038-017-1003-4) contains supplementary health disorders, and intentional injury (GBD 2015 Eastern material, which is available to authorized users. Mediterranean Region HIV/AIDS Collaborators and & GBD 2015 Eastern Mediterranean Region Adolescent Mokdad 2017; GBD 2015 Eastern Mediterranean Region Health Collaborators Intentional Injuries Collaborators and Mokdad 2017; GBD mokdaa@uw.edu 2015 Eastern Mediterranean Region Mental Health Col- laborators and Mokdad 2017). There is a risk that without Institute for Health Metrics and Evaluation, University of urgent action, the health status of this region will only Washington, Seattle, WA, USA 123 S80 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 1 Eastern Mediterranean region: Countries, adolescent population and socioeconomic development, 1990–2015 (World Bank, Global Burden of Disease Study 2015, Eastern Mediterranean Countries, 1990–2015) Country Proportion of country population aged Proportion of the GDP per capita Socio-demographic index (SDI) 10–24 year in % (n, number of EMR adolescent ($US) 1990 2015 SDI level adolescents in each country) population (%) Afghanistan 34.8% (11,356,556) 6.2 594.3 0.1440 0.2888 Low Bahrain 21.7% (296,971) 0.2 22,600.2 0.5969 0.7764 High-middle Djibouti 30.5% (271,064) 0.1 1945.1 0.3228 0.4615 Low-middle Egypt 26.9% (24,492,800) 13.3 3614.7 0.4409 0.6191 Middle Iran 22.8% (17,992,150) 9.8 – 0.4600 0.7154 High-middle Iraq 31.2% (11,348,292) 6.2 4943.8 0.3997 0.5756 Middle Jordan 29.9% (2,263,213) 1.2 4940.0 0.4967 0.6949 High-middle Kuwait 19.1% (745,077) 0.4 29,300.6 0.6911 0.8624 High Lebanon 28.5% (1,643,663) 0.9 8047.6 0.5698 0.7547 High-middle Libya 25.0% (1,574,514) 0.9 – 0.4747 0.6430 Middle Morocco 26.0% (8,932,361) 4.8 2878.2 0.3347 0.4959 Low-middle Oman 21.4% (960,174) 0.5 15,550.7 0.4089 0.7301 High-middle Pakistan 30.2% (57,088,761) 31 1434.7 0.2786 0.4676 Low-middle Palestine 33.6% (1,569,806) 0.9 – 0.4229 0.5670 Middle Qatar 19.3% (429,261) 0.2 73,653.4 0.6162 0.8045 High-middle Saudi Arabia 24.4% (7,683,094) 4.2 20,481.7 0.5245 0.7593 High-middle Somalia 32.7% (3,545,571) 1.9 549.3 0.1158 0.1506 Low Sudan 32.1% (12,950,382) 7.0 2414.7 0.2667 0.4282 Low-middle Syria 32.4% (6,032,616) 3.3 – 0.3881 0.5790 Middle Tunisia 22.6% (2,546,994) 1.4 3872.5 0.4503 0.6515 Middle United Arab Emirates 16.6% (1,516,072) 0.8 40,438.8 0.6324 0.8747 High Yemen 34.2% (9,191,689) 5.0 1406.3 0.1329 0.4080 Low-middle Total 28.4% (184,431,081) 100 – – – – This table details the 22 countries in the East Mediterranean region. It provides the population of adolescents and contribution of each country to the total adolescent population in the Eastern Mediterranean Region. It also provides the overall country-level GDP in 2015 and SDI in 1990 and 2015. Dashes indicate data are unavailable deteriorate further, with both regional and global conse- adolescents are critical to driving socioeconomic devel- quences for health, social stability, and economic opment (The World Bank 2006). Poor physical health and development. mental health are barriers to participation in education and Adolescence is increasingly understood as a key devel- employment, as are policies and systems that do not enable opmental stage for assuring health across the course of equitable access. Finally, in their role as current and future one’s life, and as such, provides significant opportunities to parents, the health of adolescents has significant implica- improve population health in the EMR (Patton et al. 2016; tions for the next generation (Patton et al. 2016). The World Bank 2006). Firstly, adolescents represent more To date, the health problems and health risks of ado- than a quarter of the population in the EMR, and their lescents in the EMR have been inadequately described health needs are likely to be distinct from children and (Alaovie et al. 2017). This is a significant barrier to adults. Conflict and civil unrest (which have been a feature developing comprehensive policies that address adolescent of many countries in the EMR) have a large impact on the health and to measuring the impact of any investments health of young people, both acutely (through high rates of made. This paper aims to report the health profile for mortality and morbidity due to violence) but also in the adolescents living in the EMR. longer term (including mental health disorder and poor sexual and reproductive health) (Viner et al. 2012). Sec- ondly, many health risks typically emerge during adoles- cence including those for non-communicable diseases Methods (NCDs) such as substance use, overweight, and physical inactivity. Given that NCDs are now the leading cause of We framed our study around the conceptual framework poor health in the EMR, there is a potential to intervene defined by the Lancet Commission of Adolescent Health before harms arise (Mokdad et al. 2016b). Thirdly, and Wellbeing (hereafter referred to as the Commission) 123 Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S81 (Patton et al. 2016). Health needs included: health out- In addition to region-level estimates, we also report comes (mortality, non-fatal diseases, and injuries); health country-specific DALY estimates and the prevalence of risks (behaviors and states that carry risk for poor health in three key health risks and four determinants (aligned with and beyond adolescence); and determinants of health (such the conceptual framework from the Commission and data as education and employment). Adolescence was defined availability) to help prioritize country-specific actions as 10–24 years, as these years encompass the important (Patton et al. 2016). Data for health risks were sourced biological, neurocognitive, and social role transitions that from GBD 2015. Tobacco smoking was defined as current typically define adolescence (Mokdad et al. 2016b; Patton daily smoked tobacco use (GBD Tobacco Collaborators et al. 2016; Sawyer et al. 2012). Where possible, we report 2017). Overweight was defined using the International age-disaggregated data for young adolescents Obesity Task Force age and gender specific cut-offs, (10–14 years), older adolescents (15–19 years), and young equivalent to BMI C25 kg/m at age 18 (Cole and Lobstein adults (20–24 years) (Patton et al. 2016). 2012). This definition includes those who are obese. Binge Data are drawn from the Global Burden of Disease drinking was defined as having consumed 60 grams of Study 2015 (GBD 2015) as this provides a complete set of alcohol on a single occasion for males and 48 grams of comparable health estimates for 195 countries, including alcohol on a single occasion for females in the last all those in the EMR. Methods are described in detail 12 months. With respect to determinants, adolescent fer- elsewhere (GBD DALYs Hale Collaborators 2016; GBD tility rate (live births per 1000 15- to 19-year-old females) Disease Injury Incidence and Prevalence Collaborators and mean years of educational attainment for 15- to 2016; GBD Mortality and Causes of Death Collaborators 24-year olds were sourced from GBD 2015 (GBD SDG 2016; GBD SDG Collaborators 2016), but briefly, GBD Collaborators 2016). Unmet need for contraception (15- to 2015 includes a comprehensive and systematic analysis of 24-year-old females currently married or in union and not 249 causes of death, 310 causes of disease and injury, and wanting to become pregnant within the next two years, who 79 behavioral and environmental health risks. GBD 2015 report not using any method of contraception) was sourced has four levels of causes that are mutually exclusive. Level from a review DHS and MICS surveys available in the one has three causes: type I conditions (communicable, EMR (data were collected from 2009 to 2014) (Patton et al. maternal, neonatal, and nutritional disorders); non-com- 2016). Youth unemployment data, defined as the percent- municable diseases; and injuries. Level two has 21 causes, age of 15- to 24-year olds without work but available for while levels three and four consist of all disaggregated and seeking employment, were obtained from the Inter- causes. For this analysis we report causes at level four. national Labor Organization modeled estimates for 2013 GBD is based on the best available primary data and (Patton et al. 2016). employs a series of disease models to harmonize health We reported observed estimates for the region. We estimates and fill data gaps. Each step of the estimation additionally report expected DALYs for each country process of GBD 2015 has been documented, as well as data based on the level of socioeconomic development. sources, in accordance with Guidelines for Accurate and Expected DALYs were estimated using the Socio-demo- Transparent Health Estimates Reporting (GATHER). For graphic Index (SDI) which is based on income per capita, this analysis, we accessed data in 5-year age bands, for average educational attainment for ages 15 or older, and males and females, from 1990 to 2015 in 5-year time slices. the total fertility rate (GBD SDG Collaborators 2016). SDI Mortality is reported as all-cause and cause-specific is reported as a continuous variable from 0 (lowest) to 1 rates per 100,000 (GBD Mortality and Causes of Death (highest), and as quintiles, as shown in Table 1. GBD 2015 Collaborators 2016). Non-fatal diseases and injuries are has estimated the relationship between SDI and each cause reported as years lived with disability (YLDs), a metric of DALYs using spline regressions, with these regressions which incorporates prevalence of disease, duration, and its then used to estimate expected DALYs at each level of SDI severity (using disease weights) (GBD Disease Injury (GBD DALYs Hale Collaborators 2016). Incidence and Prevalence Collaborators 2016). As a sum- mary measure of population health, we also report dis- ability-adjusted life-years (DALYs), the sum of years of Results healthy life lost due to premature mortality (YLLs), and years of life lived with disability (YLDs) (GBD DALYs Mortality Hale Collaborators 2016). For these estimates, we report 95% uncertainty estimates, which are distinct from confi- All-cause mortality rates for adolescents in the EMR dence intervals in that they represent uncertainty derived ranged from 63.3 per 100,000 for females aged from sampling, model estimation, and model specification 10–14 years to 253.2 per 100,000 for males aged (GBD DALYs Hale Collaborators 2016). 20–24 years in 2015 (e-Figure 1, panel A). Males had a 123 S82 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators higher overall mortality rate than females. The risk of and nutritional diseases. DALY rates have increased for mortality for males aged 15–24 years had increased males aged 15–19 and 20–24 since 1990, largely due to an over recent years compared to what was otherwise an increased burden of injury. The leading causes of DALYs by overall trend of reduction in mortality. Table 2 details age and sex are provided in Table 4. For females, type 1 the leading causes of mortality by sex. The most conditions (nutritional disorders, communicable disease, striking transition in mortality cause over time was the and maternal disorders) remain important causes of DALYs. reductionindeaths duetonatural disaster and com- However, non-communicable diseases (mental health dis- municable diseases, and the emergence of mortality due orders, migraine, skin conditions, and musculoskeletal dis- to injuries (especially in the context of war) and NCDs. orders) account for more than half of the total disease burden. In 1990 and 2005 natural disaster ranked as a leading For males, injuries due to conflict, transport, and other cause of mortality for adolescents, whereas in 2015 it unintentional injuries are the leading causes of DALYs, was no longer a leading cause of death for adolescents. particularly amongst 15- to 24-year olds. In 2015, war and legal interventions (law enforcement) There was considerable variation in all-cause and was the leading cause of death for adolescents of both cause-specific DALY rates across countries in the region sexes, representing 27.7% (14.2–38.4) of deaths (e-Figure 2, panels A–C). In all countries in the region, amongst male 20- to 24-year olds and 7.2% (3.1–10.9) DALY rates are highest among males, and higher among amongst female 20- to 24-year olds. For males, injuries 20- to 24-year olds than other ages in males and females. (unintentional injuries, self-harm and violence) were the The highest DALY rates were in countries most affected predominant causes of mortality across adolescence, by recent conflict or insecurity and/or those with the and communicable diseases an important cause for 10- lowest SDI, such as Pakistan (17,483 per 100,000 to 14-year olds. The leading cause of mortality for 10–24 years in 2015), Somalia (27,716 DALYs per females included injuries; however, communicable and 100,000 10- to 24-year olds in 2015), Afghanistan (32,068 maternal conditions were also leading causes, with per 100,000 10- to 24-year olds in 2015) and Syria NCDs emerging as an important cause amongst older (33,452 per 100,000 10- to 24-year olds in 2015), with female adolescents. 10- to 24-year olds globally having a DALY rate of 14,557 per 100,000 in 2015. In these countries, injury, YLDs particularly due to war and legal intervention was a major contributor to DALYs, particularly amongst males. For All-cause YLD rates are similar for males and females in the example, in Syria over 70% of DALYs to 10–24 year region, and have seen little improvement since 1990 (e- olds were due to injury, with males aged 20–24 experi- encing the largest burden. A number of these countries Figure 1 panel B). The leading causes of YLDs are detailed in Table 3. While the burden of some communicable, also experience a high burden of nutritional disorders and maternal, and nutritional disorders has declined, this has communicable disease among younger adolescents, in largely been offset by an increase in disability due to injury addition to a substantial burden of maternal health prob- among males and lack of reduction in YLDs from non- lems. Countries with a higher SDI and those less affected communicable disease. From 1990 to 2015, iron deficiency by conflict experienced a lower burden of poor health. In anemia was the leading cause of disability for females aged these settings DALYs were mostly due to NCDs includ- 10–14 and 15–19 years, and for males aged 10–14 years. ing mental health disorders, skin conditions, asthma, NCDs, particularly mental health disorders, migraine, migraine, and musculoskeletal disorders. asthma, skin conditions, and musculoskeletal disorders, The three countries that had the largest populations of were major contributors to YLDs for both sexes in 2015. adolescents in the EMR (Pakistan, Iran, and Egypt) had very Major depression emerged as the leading cause of morbidity different disease burdens. Egypt (12,418 DALYs per 100,000 amongst males aged 15–19 (7.0%, uncertainty 4.6–9.9) and 10- to 24-year olds in 2015) and Iran (12,624 DALYs per 20–24 years (8.0%, uncertainty 5.1–11.7) and for females 100,000 10- to 24-year olds in 2015) has similar low rates of aged 20–24 years (9.1%, uncertainty 6.2–12.4) in 2015. DALYs; however, Iran had a higher burden due to injury Among older males, opioid use disorders and war were also (3361 per 100,000 in Iran compared to 1938 per 100,000 in important causes of disability. Egypt). Pakistan had a high burden of injury (3367 per 100,000) but more so type I conditions (5252 per 100,000). DALYs e-Figure 2, panels D–F shows the expected DALYs in each country based on the SDI. The most striking finding All-cause DALY rates have declined for females of all ages is that with the reduction of DALYs due to war (which is and 10- to 14-year-old males in the region (e-Figure 1, panel not expected based on development), there remains a very c), largely due to a reduction of communicable, maternal, large burden of poor health for adolescents in the EMR. 123 Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S83 Table 2 Leading contributors to poor health (mortality) for adolescents in the Eastern Mediterranean Region, in 1990, 2005, 2015 Top ten causes of mortality in females and males Females 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Natural disaster 8.0% (3.2–12.6) Natural disaster 12.8% (7.4–18) War and legal intervention 9.5% (4.2–14.2) 2 Diarrheal diseases 5.8% (4.1–7.8) Typhoid fever 5.3% (2.9–8.9) Lower respiratory infect. 5.6% (3.6–7.3) 3 Lower respiratory infect. 5.7% (3.5–7.4) Lower respiratory infect. 4.7% (3.2–6.1) Typhoid fever 5.2% (2.9–8.7) 4 Measles 5.3% (1.5–12.7) Diarrheal diseases 4.6% (3.2–6.7) Congenital heart 4.8% (3.3–6.5) 5 Tuberculosis 4.5% (2.2–67) Tuberculosis 4.4% (2.5–6.4) Drowning 4.3% (2.7–5.9) 6 Drowning 4.3% (2.5–6.4) Drowning 4.1% (2.6–5.8) Tuberculosis 4.0% (2.3–6) 7 Typhoid fever 4.3% (2 3–7.5) Congenital heart 3.9% (2.6–5.8) Diarrheal diseases 3.9% (2.6–5.9) 8 Motor vehicle road inj. 3.2% (2.4–4.2) Motor vehicle road inj. 3.5% (2.8–4.2) Motor vehicle road inj. 3.6% (2.9–4.5) 9 Hemorrhagic stroke 3.1% (2.5–3.9) Malaria 2.8% (0.9–7.2) Other unintentional 2.7% (1.7–4.1) 10 Congenital heart 3.1% (2–5.2) Measles 2.4% (0.6–6.7) Malaria 2.6% (0.7–7.6) 15–19 years 1 Natural disaster 5.8% (2.2–9.3) Natural disaster 8.1% (4.4–11.5 War and legal intervention 10.1% (4.4–15.5) 2 Tuberculosis 5.8% (3.3–8.7) Maternal hemorrhage 5.4% (3.7–7.2) Tuberculosis 4.7% (2.8–6.7) 3 Maternal hemorrhage 5.5% (3.8–7.7) Tuberculosis 5.2% (3.2–7.2) Maternal hemorrhage 3.8% (2.3–5.6) 4 Diarrheal diseases 4.2% (3–5.7) Maternal hypertension 3.6% (2.4–5) Motor vehicle road inj. 3.5% (2.8–4.4) 5 Maternal hypertension 3.8% (2.4–5.7) Motor vehicle road inj. 3.6% (2.9–4.4) Maternal hypertension 3.4% (2–5.3) 6 Drowning 3.4% (2–5.2) Diarrheal diseases 3.5% (2.4–4.9) Drowning 3.4% (2–4.8) 7 Ischemic heart disease 3.0% (2.5–3.6) Drowning 3.4% (2–4.7) Malaria 3.3% (1.5–6.3) 8 Motor vehicle road inj. 2.9% (2.3–3.7) Self-harm 3.4% (2.5–6.3) Self-harm 2.9% (2.1–6.3) 9 Self-harm 2.9% (1.9–5.3) Ischemic heart disease 2.9% (2.4–3.5) Diarrheal diseases 2.9% (1.9–4.2) 10 Hemorrhagic stroke 2.8% (2.3–3.4) Malaria 2.9% (1.5–5.1) Ischemic heart disease 2.8% (2.3–3.5) 20–24 years 1 Maternal hemorrhage 8.2% (5.8–11) Maternal hemorrhage 7.7% (5.7–10.2) War and legal intervention 7.2% (3.1–10.9) 2 Tuberculosis 7.1% (4.4–10.7) Tuberculosis 6.2% (4–8.5) Tuberculosis 5.9% (3.7–8.1) 3 Maternal hypertension 5.6% (3.7––8.2) Natural disaster 5.9% (3.2–8.5) Maternal hemorrhage 5.6% (3.7–8.1) 4 Natural disaster 4.1% (1.5–6.6) Maternal hypertension 5.4% (3.8–7.4) Maternal hypertension 5.0% (3.1–7.6) 5 Other maternal disorders 3.9% (2.4–5.8) Motor vehicle road inj. 3.6% (2.9–4.4) Ischemic heart disease 3.6% (3–4.4) 6 Ischemic heart disease 3.6% (3–4.3) Ischemic heart disease 3.5% (2.9–4.3) Motor vehicle road inj. 3.5% (2.9–4.3) 7 Hemorrhagic stroke 2.9% (2.4–3.5) Self-harm 3.3% (2.4–6.2) Self-harm 3.1% (2.3–6.5) 8 Motor vehicle road inj. 2.8% (2.2–3.7) Hemorrhagic stroke 2.6% (2.2–3.2) Other maternal disorders 2.9% (1.7–4.5) 9 Diarrheal diseases 2.8% (2–3.9) Abortion, miscarriage, ectopic 2.3% (1.5–3.3) Hemorrhagic stroke 2.6% (2.1–3.3) 10 Abortion, miscarriage, ectopic 2.8% (1.7–4.4) Other maternal disorders 2.2% (1.6–3.1) Cirrhosis other 2.2% (1.5–3) S84 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 2 continued Top ten causes of mortality in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Natural disaster 9.8% (15.1–3.9) Natural disaster 16.1% (9.4–22.1) War and legal intervention 12.2% (5.5–18.1) 2 Drowning 8.6% (10.9–6.5) Drowning 6.4% (5.2–7.7) Other unintentional 6.9% (4.6–10.1) 3 Lower respiratory infect. 5.4% (7.1–3.4) Motor vehicle road inj. 5.7% (4.8–7) Drowning 6.4% (5.2–7.9) 4 Motor vehicle road inj. 5.3% (6.3–4.2) Other unintentional 5.6% (3.6–8.2) Motor vehicle road inj. 6.0% (4.8–7.5) 5 Pedestrian road inj. 5.3% (6.6–4) Pedestrian road inj. 5.0% (3.9–6.2) Lower respiratory infect. 4.8% (3.5–6.3) 6 Diarrheal diseases 4.1% (6–2.7) Lower respiratory infect. 4.2% (3.2–5.5) Pedestrian road inj. 4.7% (3.6–5.9) 7 Measles 3.7% (9.2–1) Typhoid fever 4.0% (2.2–6.8) Typhoid fever 4.0% (2.1–7) 8 Other unintentional 3.7% (5.4–2.5) Diarrheal diseases 3.1% (1.9–4.7) Diarrheal diseases 2.9% (1.8–4.6) 9 Typhoid fever 3.6% (6.1–1.9) Hemorrhagic stroke 2.3% (1.9–2.6) Congenital heart 2.6% (1.8–3.4) 10 Hemorrhagic stroke 3.3% (4.1–2.7) Congenital heart 2.2% (1.4–2.9) Hemorrhagic stroke 2.2% (1.9–2.6) 15–19 years 1 Natural disaster 9.6%(3.8–14.8) Natural disaster 12.5% (7.2–17.5) War and legal intervention 27.2% (13.2–37.9) 2 Motor vehicle road inj. 8.9% (6.8–11.8) Motor vehicle road inj. 9.8% (8.1–12.1) Other unintentional 8.4% (5–12.5) 3 Drowning 6.7% (4.8–8.9) Other unintentional 7.9% (5.2–11.3) Motor vehicle road inj. 8.4% (6.5–10.8) 4 Other unintentional 5.3% (3.5–7.5) Pedestrian road inj. 5.4% (4.1–6.8) Drowning 4.0% (3.1–5.2) 5 Pedestrian road inj. 4.7% (2.9–6.2) Drowning 5.1% (4.3–6.2) Pedestrian road inj. 4.0% (2.9–5.3) 6 War and legal intervention 4.3% (1.5–9.3) Motorcyclist road inj. 4.0% (2.9–5.4) Self-harm 2.9% (2.2–3.7) 7 Self-harm 3.1% (2.4–4) Self-harm 3.5% (2.8–4.2) Motorcyclist road inj. 2.8% (1.8–3.9) 8 Motorcyclist road inj. 3.0% (1.8–4.5) War and legal intervention 3.4% (1.7–5) Lower respiratory infect. 2.3% (1.6–3.1) 9 Lower respiratory infect. 3.0% (2–3.8) Lower respiratory infect. 2.4% (1.8–3.1) Physical violence by firearm 2.2% (1.2–3.3) 10 Hemorrhagic stroke 2.8% (2.2–3.4) Hemorrhagic stroke 2.2% (1.8–2.5) Other physical violence 1.8% (0.8–2.9) 20–24 years 1 Motor vehicle road inj. 9.9% (7.7–12.9) Motor vehicle road inj. 11.1% (9.4–13.4) War and legal intervention 27.7% (14.2–38.4) 2 Natural disaster 6.8% (2.7–10.8) Natural disaster 8.9% (5–12.8) Motor vehicle road inj. 8.9% (7–11.3) 3 War and legal intervention 5.3% (1.8–11.5) Other unintentional 6.8% (4.4–10.1) Other unintentional 6.8% (4–10.3) 4 Pedestrian road inj. 5.0% (3.1–6.5) Pedestrian road inj. 5.7% (4.4–7) Pedestrian road inj. 4.2% (3.1–5.4) 5 Other unintentional 5.0% (3.3–7.1) Self-harm 4.6% (3.8–5.5) Self-harm 3.8% (3–5) 6 Drowning 5.0% (3.4–6.7) War and legal intervention 4.3% (2.2–6.4) Motorcyclist road inj. 2.8% (2–4) 7 Self-harm 4.2% (3.3–5.4) Motorcyclist road inj. 4.1% (3–5.6) Drowning 2.8% (2.2–3.6) 8 Tuberculosis 3.7% (2.4–5.9) Drowning 3.7% (3.1–4.4) Other physical violence 2.6% (1–4) Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S85 Health risks and determinants The prevalence of selected health risks is provided in e-Figure 3. The prevalence of overweight and obesity was highest among countries with a higher SDI in the region, and was generally similar for males and females. Rates of daily tobacco smoking among males aged 10–24 years ranged from 1.9% in Sudan to 18% in Kuwait, but were less than 5% for females in the region. Similarly, the prevalence of binge drinking was higher among males than females at all ages, but was less than 10% for both sexes in most EMR countries. Unmet need for contraception was high among the 11 countries for which data are available (e-Figure 4). More than one third of females who are married or in union have unmet need for contraception in Pakistan, Djibouti, Somalia, Sudan, and Yemen. These countries also have among the highest rates of adolescent birth rates in the region, adolescent fertility the greatest in Somalia (114.7 live births per 1000 females aged 15–19 in 2015). There was also great variation in educational attainment in the EMR region. Low-SDI countries affected by protracted insecurity and conflict have the lowest mean number of years of completed education, most notably for females. Rates of unemployment among 15- to 24-year olds also vary considerably, and were generally higher for females than males. Discussion This study is the first systematic analysis of adolescent health in the EMR. The findings suggest dramatic shifts in the health of adolescents living in the EMR over the past 25 years. Communicable diseases and the health conse- quences of natural disasters have reduced substantially, but these gains have largely been offset by war and the emergence of NCDs including mental health disorders, unintentional injury, and self-harm. Indeed, adolescents living in Syria, Afghanistan, and Somalia experience amongst the largest burdens of disease and injury of all adolescents globally (Patton et al. 2016). Even with the return of peace and security to this region, adolescents will have a persisting poor health profile that will pose a barrier to socioeconomic growth and development of the EMR (The World Bank 2006). The substantial reductions in mortality and morbidity due to communicable disease, maternal disorders, and natural disasters in the EMR are likely the result of socioeconomic growth and development, educational par- ticipation, and interventions through the health system. Recent wars and civil conflict, however, threaten the foundations on which these gains were made, with the risk of resurgence of many of these conditions. This is in Table 2 continued Top ten causes of mortality in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 9 Motorcyclist road inj. 3.1% (1.8–4.7) Other physical violence 3.0% (1.3–4.1) Physical violence by firearm 2.4% (1.3–3.6) 10 Ischemic heart disease 3.0% (2.5–3.6) Ischemic heart disease 2.7% (2.3–3.2) Ischemic heart disease 2.3% (1.8–2.9) Global burden of disease study 2015, Eastern Mediterranean Region, 1990–2015 Italic defines communicable, maternal, neonatal and nutritional diseases Bold defines non-communicable diseases Bold, italic defines injuries S86 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 3 Leading contributors to poor health (YLDs) for adolescents in the Eastern Mediterranean Region, in 1990, 2005, 2015 Top ten causes of years lived with a disability (YLDs) in females and males Females 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 15.7% (13.5–17.6) Iron-deficiency anemia 16.4% (13.9–18.6) Iron-deficiency anemia 16.7% (14.3–18.9) 2 Migraine 7.0% (4.4–9.9) Migraine 7.5% (4.7–10.7) Migraine 7.6% (4.8–10.8) 3 Anxiety disorders 6.4% (4.6–8.8) Anxiety disorders 6.8% (4.9–9.3) Anxiety disorders 7.0% (5–9.5) 4 Asthma 5.6% (4.2–7.4) Conduct disorder 5.8% (3.3–8.6) Conduct disorder 5.9% (3.4–8.8) 5 Conduct disorder 5.5% (3.1–8.4) Asthma 5.3% (3.9–6.9) Asthma 5.7% (4.1–7.6) 6 Major depressive disorder 4.1% (2.6–6) Major depressive disorder 4.3% (2.7–6.2) Major depressive disorder 4.4% (2.8–6.3) 7 Low back pain 3.0% (2.3–3.9) Acne vulgaris 3.1% (1.7–5.3) Acne vulgaris 3.2% (1.7–5.5) 3 Epilepsy 2.9% (1.9–3.9) Low back pain 3.0% (2.3–4) Low hack pain 3.0% (2.3–4) 9 Acne vulgaris 2.8% (1.5–4.8) Epilepsy 2.8% (2–3.8) Dermatitis 2.8% (2.1–3.6) 10 Dermatitis 2.5% (1.9–3.3) Dermatitis 2.7% (2–3.6) Epilepsy 2.6% (1.8–3.7) 15–19 years 1 Iron-deficiency anemia 10.3% (8.2–12.3) Iron-deficiency anemia 10.1% (8.3–12) Iron-deficiency anemia 10.0% (8.1–11.9) 2 Major depressive disorder 8.0% (5.6–10.9) Major depressive disorder 8.1% (5.7–11) Migraine 8.3% (5.3–11.9) 3 Migraine 7.9% (4.9–11.3) Migraine 8.1% (5.1– 11.4) Major depressive disorder 8.3% (5.9–11.2) 4 Anxiety disorders 6.8% (5–9.2) Anxiety disorders 7.0% (5.2–9.4) Anxiety disorders 7.2% (5.3–9.7) 5 Low back pain 5.0% (3.8–6.4) Low back pain 5.1% (3.9–6.6) Low hack pain 5.0% (3.8–6.5) 6 Acne vulgaris 3.5% (1.8–5.9) Acne vulgaris 3.7% (2–6.3) Acne vulgaris 3.9% (2–6.6) 7 Asthma 3.4% (2.4–4.4) Other musculoskeletal 3.7% (2.6–5.1) Other musculoskeletal 3.9% (2.7–5.5) 8 Conduct disorder 3.1% (1.8–4.9) Conduct disorder 3.2% (1.9–5) Conduct disorder 3.3% (1.9–5.1) 9 Other musculoskeletal 3.0% (2.1–4.2) Asthma 3.2% (2.3–4.2) Asthma 3.3% (2.3–4.3) 10 Epilepsy 2.2% (1.5–3) Epilepsy 2.1% (1.5–2.8) Epilepsy 2.0% (1.4–2.8) 20–24 years 1 Iron-deficiency anemia 10.2% (8.1–12.3) Iron-deficiency anemia 9.0% (7.1–11) Major depressive disorder 9.1% (6.2–12.4) 2 Major depressive disorder 8.7% (5.9–11.8) Major depressive disorder 8.8% (6–12.1) Iron-deficiency anemia 8.9% (7–10.8) 3 Migraine 7.8% (4.9–11.4) Migraine 8.0% (5–11.6) Migraine 8.3% (5.3–12) 4 Anxiety disorders 6.0% (4.4–8.2) Anxiety disorders 6.2% (4.5–8.5) Anxiety disorders 6.4% (4.7–8.6) 5 Low back pain 6.0% (4.6–7.7) Low back pain 6.1%(4.7–7.9) Low back pain 6.1% (4.7–7.9) 6 Other musculoskeletal 4.2% (3–5.6) Other musculoskeletal 4.9% (3.5–6.6) Other musculoskeletal 5.4% (3.9–7.3) 7 Bipolar disorder 2.4% (1.6–3.5) Neck pain 2.5% (1.7–3.4) Bipolar disorder 2.5% (1.7–3.7) 8 Neck pain 2.3% (1.5–3.2) Bipolar disorder 2.4% (1.6–3.5) Neck pain 2.4% (1.6–3.3) 9 Other mental and substance 2.2% (1.7–2.8) Other mental and substance 2.3% (1.8–2.9) Other mental and substance 2.4% (1.9–3.1) 10 Premenstrual syndrome 1.9% (1.4–2.6) Premenstrual syndrome 1.9% (1.4–2.6) Medication overuse 1.9% (1.2–3) Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S87 Table 3 continued Top ten causes of years lived with a disability (YLDs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 18.9% (16.6–20.9) Iron-deficiency anemia 19.4% (17–21.5) Iron-deficiency anemia 19.5% (17–21.6) 2 Conduct disorder 7.5% (4.7–10.7) Conduct disorder 7.9% (5–11.3) Conduct disorder 8.1% (5.1–11.5) 3 Asthma 5.3% (3.9–6.9) Asthma 5.2% (3.8–6.8) Asthma 5.1% (3.7–6.8) 4 Anxiety disorders 4.0% (2.8–5.5) Anxiety disorders 4.2% (3–5.9) Anxiety disorders 4.3% (3.1–6.1) 5 Migraine 3.3% (2–4.8) Migraine 3.5% (2.2–5.2) Migraine 3.6% (2.2–5.3) 6 Low back pain 2.9% (2.2–3.9) Low back pain 3.1% (2.3–4) Low back pain 3.0% (23–4.1) 7 Epilepsy 2.9% (2–3.9) Major depressive disorder 2.9% (1.7–4.5) Major depressive disorder 3.0% (1.8–4.6) 8 Major depressive disorder 2.7% (1.6–4.3) Acne vulgaris 2.8% (1.5–4.7) Acne vulgaris 2.9% (1.5–4.9) 9 Acne vulgaris 2.5% (1.3–4.2) Epilepsy 2.6% (1.8–3.4) Epilepsy 2.5% (1.7–3.5) 10 Thalassemias trait 2.2% (1.9–2.4) Thalassemias trait 2.4% (2.1–2.6) Thalassemias trait 2.4% (2.1–2.7) 15–19 years 1 Iron-deficiency anemia 7.7% (6.2–9.6) Major depressive disorder 6.9% (4.5–9.9) Major depressive disorder 7.0% (4.6–9.9) 2 Major depressive disorder 6.6% (4.3–9.6) Iron-deficiency anemia 6.8% (5.2–8.6) Iron-deficiency anemia 6.5% (5–8.3) 3 Low back pain 6.3% (4.9–8.1) Low back pain 6.5% (4.9–8.3) Low back pain 6.4% (4.8–8.3) 4 Conduct disorder 5.7% (3.5–8.3) Conduct disorder 6.0% (3.8–8.7) Conduct disorder 6.0% (3.7–8.8) 5 Migraine 4.9% (3–7.1) Migraine 5.2% (3.2–7.5) Migraine 5.3% (3.3–7.7) 6 Anxiety disorders 4.6% (3.3–6.3) Anxiety disorders 4.9% (3.5–6.6) Anxiety disorders 4.9% (3.6–6.7) 7 Acne vulgaris 3.7% (1.9–6.4) Acne vulgaris 4.1% (2.1–6.8) Acne vulgaris 4.2% (2.2–7.1) 8 Asthma 3.5% (2.6–4.6) Other musculoskeletal 3.8% (2.7–5.3) Other musculoskeletal 4.0% (2.7–5.6) 9 Other musculoskeletal 3.0% (2–4.3) Asthma 3.5% (2.5–4.6) Asthma 3.3% (2.4–4.5) 10 Epilepsy 2.6% (1.9–3.5) Epilepsy 2.5% (1.8–3.3) War and legal intervention 2.7% (1.2–5) 20–24 years 1 Major depressive disorder 7.7% (4.9–11.4) Major depressive disorder 7.9% (5–11.8) Major depressive disorder 8.0% (5.1–11.7) 2 Low back pain 7.3% (5.7–9.4) Low back pain 7.4% (5.7–9.4) Low back pain 7.4% (5.7–9.4) 3 Migraine 5.7% (3.7–8.1) Migraine 5.8% (3.8–8.3) Migraine 5.9% (3.8–8.5) 4 Other mental and substance 4.2% (3.4–5.3) Opioid use disorders 5.1% (3.6–6.8) Other musculoskeletal 4.9% (3.5–6.6) 5 Iron-deficiency anemia 4.2% (3–5.5) Other musculoskeletal 4.6% (3.3–6.1) Opioid use disorders 4.9% (3.5–6.6) 6 Opioid use disorders 4.2% (2.9–5.6) Other mental and substance 4.4% (3.6–5.5) Other mental and substance 4.5% (3.5–5.5) 7 Anxiety disorders 3.9% (2.7–5.5) Anxiety disorders 4.0% (2.8–5.5) Anxiety disorders 4.0% (2.8–5.7) 8 War and legal intervention 3.8% (2–6.1) Iron-deficiency anemia 3.6% (2.6–4.8) War and legal intervention 3.6% (1.6–6.3) S88 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators addition to the growing burden of NCDs and injuries. Renewed efforts to consolidate gains made in communi- cable disease and maternal health will be required. The Lancet Commission described the benefits that can accrue from investments in adolescence. Without these invest- ments, the EMR region risks poor health across adoles- cence, adulthood, and in the next generation (Patton et al. 2016). War and legal interventions (deaths due to law enforcement, regardless of their legality) were the leading causes of mortality for adolescents aged 10–24 years of both genders in the EMR. While not all countries in the EMR are affected by conflict, the magnitude of mortality in those countries that are affected signifies this as a priority for the region. It should also be noted, however, that at a population level (all ages combined), war and legal inter- vention is only the fifth leading cause of mortality in the EMR (GBD 2015 Eastern Mediterranean Region Collab- orators and Mokdad 2017). This may reflect competing causes of mortality at other ages, or it may signify that war and legal interventions disproportionately affect adoles- cents, particularly 20- to 24-year-old males. In addition to the physical injuries and disability that accompany conflict, violence and trauma at this critical developmental stage carry a risk of persisting effects on future mental health and well-being. War and conflict are also likely to result in disruption to quality education, social infrastructure, and community development, which have profound implica- tions for health and well-being across the course of one’s life. This may explain why expected DALYs in countries which have experienced large burdens of conflict remain high. In addition to the health status of adolescents, we explored the burden of risk behavior for future health. Tobacco smoking and high body mass were common risks where interventions during adolescence have the potential to avert later ischemic heart disease, the leading cause of poor health in the region. Of note, estimates of tobacco smoking reported here do not include Sisha smoking which is prevalent in some countries of the EMR and harmful (Maziak et al. 2004). Low rates of education completion in many countries including Afghanistan, Somalia, and Yemen are a major obstacle to growth and future prosperity of this region. High rates of adolescent pregnancy represent an important target for action to improve health and life opportunities for girls and young women. Unmet need for contraception is very high, and is likely to also signify high rates of unmet need for other essential health interventions, particularly for culturally sensitive needs such as sexually transmitted infections and mental health. Given adolescents face barriers in accessing health facilities, there is a need to explore other approaches such as community-based deliv- ery or school health services (Tylee et al. 2007). There is Table 3 continued Top ten causes of years lived with a disability (YLDs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 9 Other musculoskeletal 3.5% (2.5–4.8) Neck pain 2.5% (1.7–3.5) Iron-deficiency anemia 3.1% (2.2–4.1) 10 Other unintentional inj. 2.3% (2–2.7) Bipolar disorder 2.4% (1.6–3.5) Bipolar disorder 2.4% (1.6–3.5) Global burden of disease study 2015, Eastern Mediterranean Region, 1990–2015 Italic defines communicable, maternal, neonatal and nutritional diseases Bold defines non-communicable diseases Bold, italic defines injuries YLDs years of life with disability Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S89 Table 4 Leading contributors to poor health (DALYs) for adolescents in the Eastern Mediterranean Region, in 1990, 2005, 2015 Top ten causes of disability- adjusted life years (DALYs) in females and males Females 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 7.8% (6.1–9.8) Iron-deficiency anemia 8.8% (6.9–11) Iron-deficiency anemia 9.9% (7.9–12.1) 2 Natural disaster 4.5% (2–6.9) Natural disaster 7.0% (4–9.8) War and legal intervention 4.5% (2.3–6.9) 3 Diarrheal diseases 3.4% (2.5–4.6) Migraine 4.0% (2.5–5.7) Migraine 4.5% (2.8–6.4) 4 Migraine 3.4% (2.1–5) Anxiety disorders 3.6% (2.5–4.9) Anxiety disorders 4.1% (2.9–5.6) 5 Asthma 3.3% (2.4–4.3) Asthma 3.3% (2.5–4.3) Asthma 3.8% (2.7–5) 6 Anxiety disorders 3.2% (2.2–4.3) Conduct disorder 3.1% (1.8–4.7) Conduct disorder 3.5% (2–5.3) 7 Lower respiratory infect. 3.0% (1.8–4) Diarrheal diseases 2.7% 12–3 .8) Major depressive disorder 2.6 % (1.6–3.7) 8 Measles 2.7% (0.8–6.5) Typhoid fever 2.5% (1.4–4.2) Lower respiratory infect. 2.3% (1.5–3.2) 9 Conduct disorder 2.7% (1.5–4.2) Major depressive disorder 2.3% (1.4–3.3) Epilepsy 2.2% (1.6–2.9) 10 Tuberculosis 2.4% (1.3–3.7) Lower respiratory infect. 2.2% (1.5–3) Diarrheal diseases 2.2% (1.6–3.1) 15–19 years 1 Iron-deficiency anemia 5.3% (3.9–6.8) Iron-deficiency anemia 5.4% (4.1–6.8) Iron-deficiency anemia 5.5% (4.2–7.1) 2 Major depressive disorder 4.0% (2.7–5.6) Natural disaster 4.6% (2.7–6.4) War and legal intervention 5.3% (2.6–8.1) 3 Migraine 4.0% (2.4–5.7) Major depressive disorder 4.2% (2.9–5.9) Migraine 4.6% (2.8–6.6) 4 Anxiety disorders 3.4% (2.4–4.7) Migraine 4.2% (2.6–6.1) Major depressive disorder 4.5% (3.1–6.3) 5 Natural disaster 3.2% (1.4–5.1) Anxiety disorders 3.7% (2.6–4.9) Anxiety disorders 3.9% (2.8–5.3) 6 Tuberculosis 3.1% (1.9–4.7) Low back pain 2.6% (2–3.5) Low back pain 2.7% (2–3.6) 7 Maternal hemorrhage 2.7% (1.9–3.9) Tuberculosis 2.6% (1.6–3.7) Tuberculosis 2.3% (1.4–3.3) 8 Low back pain 2.5% (1.9–3.3) Maternal hemorrhage 2.6% (1.8–3.7) Other musculoskeletal 2.3% (1.6–3.1) 9 Diarrheal diseases 2.4% (1.8–3.3) Asthma 2.1% (1.5–2.7) Asthma 2.2% (1.6–2.9) 10 Asthma 2.2% (1.7–2.8) Other musculoskeletal 2.0% (1.4–2.8) Acne vulgaris 2.2% (1.1–3.8) 20–24 years 1 Iron-deficiency anemia 5.0% (3.7–6.6) Iron-deficiency anemia 4.7% (3.5–6.2) Major depressive disorder 5.0% (3.3–7) 2 Maternal hemorrhage 4.2% (3–5.8) Major depressive disorder 4.6% (3–6.5) Iron-deficiency anemia 4.9% (3.6–6.3) 3 Major depressive disorder 4.2% (2.8–6) Migraine 4.1% (2.6–6.1) Migraine 4.5% (2.9–6.7) 4 Tuberculosis 3.9% (2.5–5.6) Maternal hemorrhage 3.7% (2.6–5.1) War and legal intervention 3.7% (1.8–5.6) 5 Migraine 3.8% (2.4–5.6) Natural disaster 3.5% (2.1–5) Anxiety disorders 3.5% (2.4–4.8) 6 Maternal hypertension 3.1% (2–4.4) Anxiety disorders 3.2% (2.3–4.4) Low back pain 3.3% (2.4–4.5) 7 Anxiety disorders 2.9% (2–4) Tuberculosis 3.2% (2.1–4.5) Other musculoskeletal 3.1% (2.2–4.2) 8 Low back pain 2.9% (2.1–3.8) Low back pain 3.2% (2.3–4.2) Tuberculosis 2.9% (1.9–4) 9 Natural disaster 2.3% (0.9–3.7) Maternal hypertension 2.7% (1.9–3.8) Maternal hemorrhage 2.6% (1.6–3.8) 10 Other maternal disorders 2.1% (1.3–3.1) Other musculoskeletal 2.7% (1.9–3.6) Maternal hypertension 2.4% (1.5–3.7) S90 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 4 continued Top ten causes of disability- adjusted life years (DALYs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 8.4% (6.5–10.6) Iron-deficiency anemia 9.5% (7.4–11.8) Iron-deficiency anemia 10.6% (8.4–13) 2 Natural disaster 5.8% (2.4–9.1) Natural disaster 8.9% (5–12.7) War and legal intervention 6.2% (2.9–9.5) 3 Drowning 4.9% (3.4–6.3) Conduct disorder 3.9% (2.4–5.8) Conduct disorder 4.4% (2.7–6.5) 4 Conduct disorder 3.3% (2–5) Other unintentional 3.6% (2.6–5) Other unintentional 4.0% (2.8–5.6) 5 Motor vehicle road inj. 3.0% (2.3–4) Drowning 3.3% (2.6–4.1) Asthma 3.3% (2.5–4.4) 6 Lower respiratory infect. 3.0% (2–4.1) Asthma 3.2% (2.4–4.1) Drowning 2.9% (2.3–3.8) 7 Asthma 3.0% (2.3–3.9) Motor vehicle road inj. 3.0% (2.4–3.7) Motor vehicle road inj. 2.8% (2.2–3.5) 8 Pedestrian road inj. 3.0% (2.2–3.9) Pedestrian road inj. 2.6% (2–3.2) Anxiety disorders 2.3% (1.6–3 2) 9 Other unintentional 2.8% (2.2–3.8) Lower respiratory infect. 2.2% (1.6–3) Lower respiratory infect. 2.3% (1.6–3.1) 10 Diarrheal diseases 2.6% (1.8–3.7) Typhoid fever 2.1% (1.1–3.6) Pedestrian road inj. 2.1% (1.6–2.8) 15–19 years 1 Natural disaster 6.0 % (2.5–9.3) Natural disaster 7.9% (4.4–11.3) War and legal intervention 17.9% (8.9–25.7) 2 Motor vehicle road inj. 5.3% (4–7.1) Motor vehicle road inj. 5.9% (4.8–7.5) Other unintentional 5.9% (3.9–8.3) 3 Other unintentional 4.0% (3–5.4) Other unintentional 5.6% (3.9–7.7) Motor vehicle road inj. 5.2% (4.1–6.6) 4 Drowning 4.0% (2.8–5.4) Pedestrian road inj. 3.2% (2.4–4.1) Major depressive disorder 2.7% (1.7–4.1) 5 Iron-deficiency anemia 3.3% (2.4–4.4) Drowning 3.1% (2.5–3.8) Iron-deficiency anemia 2.5% (1.7–3.5) 6 War and legal intervention 3.2% (1.5–6.2) Iron-deficiency anemia 2.8% (2–3.8) Drowning 2.5% (1.9–3.2) 7 Pedestrian road inj. 2.8% (1.7–3.7) Major depressive disorder 2.8% (1.7–4.2) Pedestrian road inj. 2.5% (1.8–3.3) 8 Major depressive disorder 2.7% (1.7–4.1) Low back pain 2.6% (1.9–3.5) Low back pain 2.4% (1.7–3.3) 9 Low back pain 2.6% (1.9–3.5) Motorcyclist road inj. 2.4% (1.7–3.3) Conduct disorder 2.3% (1.4–3.6) 10 Conduct disorder 2.3% (1.4–3.6) Conduct disorder 2.4% (1.4–3.7) Migraine 2.0% (1.2–3) 20–24 years 1 Moter vehicle road inj. 6.2% (4.9–8.1) Motor vehicle road inj. 7.1% (5.8–8.7) War and legal intervention 19.5% (10–27.7) 2 War and legal intervention 4.7% (2.3–8.7) Natural disaster 5.9% (3.3–8.5) Motor vehicle road inj. 5.9% (4.7–7.4) 3 Natural disaster 4.4% (1.8–7) Other unintentional 5.2% (3.7–7.3) Other unintentional 5.2% (3.4–7.4) 4 Other unintentional 4.0% (2.9–5.4) Pedestrian road inj. 3.6% (2.7–4.5) Pedestrian road inj. 2.8% (2.1–3.5) 5 Pedestrian road inj. 3.1% (1.9–4.2) War and legal intervention 3.4% (2–4.8) Major depressive disorder 2.7% (1.7–4.3) 6 Drowning 3.1% (2.1–4.2) Major depressive disorder 2.9% (1.8–4.7) Low back pain 2.5% (1.8–3.5) 7 Major depressive disorder 2.9% (1.8–4.5) Self-harm 2.9% (2.4–3.5) Self-harm 2.5% (2–3.2) Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S91 also the need for community-based interventions to address some of the sociocultural barriers that contribute to high unmet need for interventions relating to sexual and repro- ductive health (Patton et al. 2016). As over half of the region’s adolescents live in Pakistan, Iran, and Egypt (Table 1), a regional response must pri- oritize these three countries. This is challenging, however, given the different stages of development and the very different needs of adolescents across these countries. For example, the burden of disease experienced by adolescents in Egypt is predominantly caused by NCDs, which require interventions to address the burden of chronic illness and health risks such as tobacco smoking and obesity (Patton et al. 2016). In addition to NCDs, adolescents living in Iran are burdened by injury (particularly relating to transport injury) which requires a suite of inter-sectoral actions (WHO 2017a). Adolescents living in Pakistan experience a ’’multi-burden’’ profile of disease, with a large burden of communicable, nutritional, and reproductive poor health in addition to NCDs and injury. However, in countries such as Afghanistan, Somalia, and Sudan, adolescents represent almost a third of the country-level population and experi- ence a particularly large and complex burden of disease. It is, therefore, important not to neglect their health needs (or indeed other countries in the EMR). What this analysis highlights is that unintentional injury, mental health, sexual health, substance use, and self-harm are increasingly important health issues for adolescents in the EMR. While these are health issues common to adolescents globally (Patton et al. 2016), they have typically sat at the margins (if at all) of policy, program, and data collection in EMR, given religious and cultural sensitivities. These findings highlight the need to better align health actions, including data monitoring of sensitive health outcomes, including risks, in this region to these needs. Our analysis has important limitations. Firstly, there is considerable variation in the availability and quality of primary data for adolescent health. This includes paucity of data for some age groups (particularly 10- to 14-year olds), and for many health outcomes and risks of importance during these important developmental years (Mokdad et al. 2016b; Patton et al. 2012; The Global Burden of Disease Child and Adoelscent Health Collaboration 2017). Avail- ability of timely, quality data is likely to be particularly poor in settings of conflict and insecurity, which affects many countries in this region. The poor quality of primary data necessitated the use of modeled estimates, and some of these modeled estimates may have over- or under-esti- mated the true burden. For example, ischemic heart disease was found to be a leading cause of mortality amongst males aged 20–24 years, a cause of death more commonly asso- ciated with adulthood. Premature death due to Table 4 continued Top ten causes of disability- adjusted life years (DALYs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 8 Low back pain 2.8% (2–3.8) Opioid use disorders 2.8% (2.2–3.4) Opioid use disorders 2.5% (1.9–3.2) 9 Self-harm 2.6% (2.1–3.4) Low back pain 2.7% (1.9–3.7) Migraine 2.0% (1.3–3.1) 10 Tuberculosis 2.5% (1.6–3.9) Motorcyclist road inj. 2.6% (1.9–3.6) Motorcyclist road inj. 1.9% (1.3-2.6) Global burden of disease study 2015, Eastern Mediterranean Region, 1990–2015 Italic defines communicable, maternal, neonatal and nutritional diseases Bold defines non-communicable diseases Bold, italic defines injuries DALYs disability-adjusted life-years S92 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Sawyer, MD, Murdoch Childrens Research Institute, The University cardiovascular disease is possible during adolescence, of Melbourne, Parkville, Victoria, Australia. Charbel El Bcheraoui, particularly in the context of adolescent obesity which is PhD, Institute for Health Metrics and Evaluation, University of prevalent in EMR (Franks et al. 2010). This finding may Washington, Seattle, Washington, United States. Raghid Charara, also be an artifact of disease modeling, as ischemic heart MD, American University of Beirut, Beirut, Lebanon. Ibrahim Khalil, MD, Institute for Health Metrics and Evaluation, University of disease is the leading cause of mortality in the EMR, and Washington, Seattle, Washington, United States. Maziar Moradi- these deaths are modeled to have their onset after 0.1 years Lakeh, MD, Department of Community Medicine, Preventive Medi- of age (GBD 2015 Eastern Mediterranean Region Cardio- cine and Public Health Research Center, Gastrointestinal and Liver vascular Disease Collaborators and Mokda 2017; GBD Disease Research Center (GILDRC), Iran University of Medical Sciences, Tehran, Iran. Michael Collison, BS, Institute for Health 2015 Eastern Mediterranean Region Collaborators and Metrics and Evaluation, University of Washington, Seattle, Wash- Mokdad 2017; GBD Mortality and Causes of Death Col- ington, United States. Rima A. Afifi, PhD, American University of laborators 2016). The findings of this study should there- Beirut, Beirut, Lebanon. Jamela Al-Raiby, MD, World Health fore be interpreted as not only indicating priority areas to Organization. Kristopher J. Krohn, BA, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, address adolescent health in the EMR, but also where data United States. Farah Daoud, BA/BS, Institute for Health Metrics and collection efforts should focus. A further limitation is that Evaluation, University of Washington. Adrienne Chew, ND, Institute the broader impacts of armed conflict on adolescent health for Health Metrics and Evaluation, University of Washington, Seattle, and well-being, beyond mortality, are not captured by the Washington, United States. Ashkan Afshin, MD, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Wash- 2015 GBD study. These include participation in education ington, United States. Kyle J. Foreman, PhD, Institute for Health and employment, as well as the impacts of trauma on Metrics and Evaluation, University of Washington, Seattle, Wash- adolescent development and wellbeing. Additionally, some ington, United States; Imperial College London, London, United important health issues such as female genital cut- Kingdom. Nicholas J. Kassebaum, MD, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, ting/mutilation (common in countries such as Somalia) are United States; Department of Anesthesiology & Pain Medicine, not included in GBD 2015 (UNICEF 2016a). Seattle Children’s Hospital, Seattle, Washington, United States. There are several regional efforts that may facilitate Michael Kutz, BS, Institute for Health Metrics and Evaluation, addressing the needs of adolescents in the EMR. For University of Washington, Seattle, Washington, United States. Hmwe H. Kyu, PhD, Institute for Health Metrics and Evaluation, University example, a coalition of youth advocates for health in the of Washington, Seattle, Washington, United States. Patrick Liu, BA, EMR has been established (Alaovie et al. 2017). There is a Institute for Health Metrics and Evaluation, University of Washing- joint UN strategy for youth in the region (IATTTYP 2015). ton, Seattle, Washington, United States. Helen E. Olsen, MA, Institute UNICEF has also published guidance around good practice for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States. Alison Smith, BA, Institute for Health with adolescent and youth programming (UNICEF 2016b). Metrics and Evaluation, University of Washington, Seattle, Wash- This study compliments these efforts, and helps to inform ington, United States. Jeffrey D. Stanaway, PhD, Institute for Health some priority areas for health. For conflict-affected coun- Metrics and Evaluation, University of Washington, Seattle, Wash- tries, the focus must clearly be on the return of peace and ington, United States. Haidong Wang, PhD, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Wash- stability and the rebuilding of health, education, and social ington, United States. Johan Arnlo ¨ v, PhD, Department of Neurobi- systems. In doing so, it is important to design services that ology, Care Sciences and Society, Division of Family Medicine and meet the needs of adolescents. For countries not affected Primary Care, Karolinska Institutet, Stockholm, Sweden; School of by conflict, health actions include the need to re-orientate Health and Social Studies, Dalarna University, Falun, Sweden. Aliasghar Ahmad Kiadaliri, PhD, Department of Clinical Sciences health systems to focus on prevention and the growing Lund, Orthopedics, Clinical Epidemiology Unit, Lund University, burden of NCDs. This needs to extend to inter-sectoral Lund, Sweden. Khurshid Alam, PhD, Murdoch Childrens Research actions to address the broader determinants of NCDs and Institute, The University of Melbourne, Parkville, Victoria, Australia; injuries. Without urgent action, there is a risk that profiles The University of Melbourne, Melbourne, VIC, Australia; The University of Sydney, Sydney, NSW, Australia. Deena Alasfoor, of adolescent health will continue to deteriorate with MSc, Ministry of Health, Al Khuwair, Muscat, Oman. Raghib Ali consequences for future population health and wellbeing, MSc, University of Oxford, Oxford, United Kingdom. Reza Alizadeh- productivity, and ultimately the stability of civil society. Navaei, PhD, Gastrointestinal Cancer Research Center, Mazandaran University of Medical Sciences, Sari, Mazandaran, Iran. Rajaa Al- GBD 2015 Eastern Mediterranean Region Adolescent Health Raddadi, PhD, Joint Program of Family and Community Medicine, Collaborators: Ali H. Mokdad, PhD (corresponding author), Insti- Jeddah, Makkah, Saudi Arabia. Khalid A. Altirkawi, MD, King Saud tute for Health Metrics and Evaluation, University of Washington, University, Riyadh, Saudi Arabia. Nelson Alvis-Guzman, PhD, Seattle, Washington, United States. Peter Azzopardi, PhD, Burnet Universidad de Cartagena, Cartagena de Indias, Colombia. 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Compliance with ethical standards 1016/S0140-6736(16)31467-2 GBD Tobacco Collaborators (2017) Smoking prevalence and This manuscript reflects original work that has not previously been attributable disease burden in 195 countries and territories, published in whole or in part and is not under consideration else- 1990–2015: a systematic analysis from the global burden of disease study 2015. Lancet. doi:10.1016/S0140-6736(17)30819-X where. All authors have read the manuscript and have agreed that the GBD 2015 Eastern Mediterranean Region Cardiovascular Disease work is ready for submission and accept responsibility for its con- Collaborators, Mokdad AH (2017) Burden of cardiovascular tents. The authors of this paper have complied with all ethical stan- diseases in the Eastern Mediterranean Region, 1990–2015: dards and do not have any conflicts of interest to disclose at the time findings from the global burden of disease 2015 study. Int J of submission. The funding source played no role in the design of the Public Health. doi:10.1007/s00038-017-1012-3 study, the analysis and interpretation of data, and the writing of the GBD 2015 Eastern Mediterranean Region Collaborators, Mokdad AH paper. The study did not involve human participants and/or animals; (2017) Danger ahead: the burden of diseases, injuries, and risk therefore, no informed consent was needed. factors in the Eastern Mediterranean Region, 1990–2015. Int J Conflict of interest The authors declare that they have no conflicts of Public Health. doi:10.1007/s00038-017-1017-y interest at this time. GBD 2015 Eastern Mediterranean Region HIV/AIDS Collaborators, Mokdad AH (2017) Trends in HIV/AIDS morbidity and mortality in Eastern Mediterranean countries, 1990–2015: find- Funding statement GBD 2015 is funded by Bill & Melinda Gates Foundation. ings from the global burden of disease 2015 study. Int J Public Health. doi:10.1007/s00038-017-1023-0 GBD 2015 Eastern Mediterranean Region Intentional Injuries Open Access This article is distributed under the terms of the Collaborators, Mokdad AH (2017) Intentional injuries in the Creative Commons Attribution 4.0 International License (http://crea Eastern Mediterranean Region, 1990–2015: findings from the tivecommons.org/licenses/by/4.0/), which permits unrestricted use, global burden of disease 2015 study. Int J Public Health. doi:10. distribution, and reproduction in any medium, provided you give 1007/s00038-017-1005-2 appropriate credit to the original author(s) and the source, provide a GBD 2015 Eastern Mediterranean Region Mental Health Collabora- link to the Creative Commons license, and indicate if changes were tors, Mokdad AH (2017) The burden of mental disorders in the made. Eastern Mediterranean Region, 1990–2015: findings from the global burden of disease study 2015. 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Accessed 12 Jul 387:2423–2478. doi:10.1016/S0140-6736(16)00579-1 2017 Sawyer SM, Afifi RA, Bearinger LH, Blakemore SJ, Dick B, Ezeh Viner RM, Ozer EM, Denny S, Marmot M, Resnick M, Fatusi A, AC, Patton GC (2012) Adolescence: a foundation for future Currie C (2012) Adolescence and the social determinants of health. Lancet 379:1630–1640. doi:10.1016/S0140-6736(12)60 health. Lancet 379:1641–1652. doi:10.1016/S0140-6736(12)60 072-5 149-4 The Global Burden of Disease Child and Adoelscent Health WHO (2017a) Global accelerated action for the health of adolescents Collaboration (2017) Child and adolescent health from 1990 to (AA-HA!): guidance to support country implementation. http:// 2015: findings from the global burden of diseases, injuries, and apps.who.int/iris/bitstream/10665/255415/1/9789241512343- risk factors 2015 study. JAMA Pediatr. doi:10.1001/jamapedia eng.pdf?ua=1. Accessed 12 Jul 2017 trics.2017.0250 WHO (2017b) WHO regional office for the Eastern Mediterranean. The World Bank (2006) Development and the next generation. http:// http://www.emro.who.int/entity/about-us/index.html. Accessed documents.worldbank.org/curated/en/556251468128407787/pdf/ 12 Jul 2017 359990WDR0complete.pdf. Accessed 12 Jul 2017 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Public Health Springer Journals

Adolescent health in the Eastern Mediterranean Region: findings from the global burden of disease 2015 study

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Abstract

Int J Public Health (2018) 63 (Suppl 1):S79–S96 https://doi.org/10.1007/s00038-017-1003-4 O R I G IN AL ARTI CL E Adolescent health in the Eastern Mediterranean Region: findings from the global burden of disease 2015 study GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Received: 1 May 2017 / Revised: 15 June 2017 / Accepted: 21 June 2017 / Published online: 3 August 2017 The Author(s) 2017. This article is an open access publication Abstract amongst adolescents. Additionally, many EMR countries Objectives The 22 countries of the East Mediterranean had high rates of adolescent pregnancy and unmet need for Region (EMR) have large populations of adolescents aged contraception. 10–24 years. These adolescents are central to assuring the Conclusions Even with the return of peace and security, health, development, and peace of this region. We descri- adolescents will have a persisting poor health profile that bed their health needs. will pose a barrier to socioeconomic growth and develop- Methods Using data from the Global Burden of Disease ment of the EMR. Study 2015 (GBD 2015), we report the leading causes of mortality and morbidity for adolescents in the EMR from Keywords Adolescent health  Burden of disease  Eastern 1990 to 2015. We also report the prevalence of key health Mediterranean Region risk behaviors and determinants. Results Communicable diseases and the health conse- quences of natural disasters reduced substantially between Introduction 1990 and 2015. However, these gains have largely been offset by the health impacts of war and the emergence of The World Health Organization’s Eastern Mediterranean non-communicable diseases (including mental health dis- Region (EMR) is an administrative region of 22 countries orders), unintentional injury, and self-harm. Tobacco (Table 1) that while rich in natural resources, has marked smoking and high body mass were common health risks country-level variation in socioeconomic wealth (ranging from $US 549.3 per capita in Somalia to $US 73,653.4 per capita in Qatar), health system capacities and health cov- This article is part of the supplement ‘‘The state of health in the erage (Blair et al. 2014; Mandil et al. 2013; WHO 2017b). Eastern Mediterranean Region, 1990–2015’’. Many countries in the EMR have recently experienced social and political instabilities, civil unrest, war, and mass The members of GBD (Global Burden of Disease) 2015 Eastern Mediterranean Region Adolescent Health Collaborators are listed at displacement of people (Mokdad et al. 2016a). As a result, the end of the article. Ali H. Mokdad, on behalf of GBD 2015 Eastern health in many EMR countries has failed to improve in Mediterranean Region Adolescent Health Collaborators, is the recent years (Mokdad et al. 2016a, 2014). As other papers corresponding author. in this series highlight, there is now an increasing burden of Electronic supplementary material The online version of this many preventable health problems including HIV, mental article (doi:10.1007/s00038-017-1003-4) contains supplementary health disorders, and intentional injury (GBD 2015 Eastern material, which is available to authorized users. Mediterranean Region HIV/AIDS Collaborators and & GBD 2015 Eastern Mediterranean Region Adolescent Mokdad 2017; GBD 2015 Eastern Mediterranean Region Health Collaborators Intentional Injuries Collaborators and Mokdad 2017; GBD mokdaa@uw.edu 2015 Eastern Mediterranean Region Mental Health Col- laborators and Mokdad 2017). There is a risk that without Institute for Health Metrics and Evaluation, University of urgent action, the health status of this region will only Washington, Seattle, WA, USA 123 S80 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 1 Eastern Mediterranean region: Countries, adolescent population and socioeconomic development, 1990–2015 (World Bank, Global Burden of Disease Study 2015, Eastern Mediterranean Countries, 1990–2015) Country Proportion of country population aged Proportion of the GDP per capita Socio-demographic index (SDI) 10–24 year in % (n, number of EMR adolescent ($US) 1990 2015 SDI level adolescents in each country) population (%) Afghanistan 34.8% (11,356,556) 6.2 594.3 0.1440 0.2888 Low Bahrain 21.7% (296,971) 0.2 22,600.2 0.5969 0.7764 High-middle Djibouti 30.5% (271,064) 0.1 1945.1 0.3228 0.4615 Low-middle Egypt 26.9% (24,492,800) 13.3 3614.7 0.4409 0.6191 Middle Iran 22.8% (17,992,150) 9.8 – 0.4600 0.7154 High-middle Iraq 31.2% (11,348,292) 6.2 4943.8 0.3997 0.5756 Middle Jordan 29.9% (2,263,213) 1.2 4940.0 0.4967 0.6949 High-middle Kuwait 19.1% (745,077) 0.4 29,300.6 0.6911 0.8624 High Lebanon 28.5% (1,643,663) 0.9 8047.6 0.5698 0.7547 High-middle Libya 25.0% (1,574,514) 0.9 – 0.4747 0.6430 Middle Morocco 26.0% (8,932,361) 4.8 2878.2 0.3347 0.4959 Low-middle Oman 21.4% (960,174) 0.5 15,550.7 0.4089 0.7301 High-middle Pakistan 30.2% (57,088,761) 31 1434.7 0.2786 0.4676 Low-middle Palestine 33.6% (1,569,806) 0.9 – 0.4229 0.5670 Middle Qatar 19.3% (429,261) 0.2 73,653.4 0.6162 0.8045 High-middle Saudi Arabia 24.4% (7,683,094) 4.2 20,481.7 0.5245 0.7593 High-middle Somalia 32.7% (3,545,571) 1.9 549.3 0.1158 0.1506 Low Sudan 32.1% (12,950,382) 7.0 2414.7 0.2667 0.4282 Low-middle Syria 32.4% (6,032,616) 3.3 – 0.3881 0.5790 Middle Tunisia 22.6% (2,546,994) 1.4 3872.5 0.4503 0.6515 Middle United Arab Emirates 16.6% (1,516,072) 0.8 40,438.8 0.6324 0.8747 High Yemen 34.2% (9,191,689) 5.0 1406.3 0.1329 0.4080 Low-middle Total 28.4% (184,431,081) 100 – – – – This table details the 22 countries in the East Mediterranean region. It provides the population of adolescents and contribution of each country to the total adolescent population in the Eastern Mediterranean Region. It also provides the overall country-level GDP in 2015 and SDI in 1990 and 2015. Dashes indicate data are unavailable deteriorate further, with both regional and global conse- adolescents are critical to driving socioeconomic devel- quences for health, social stability, and economic opment (The World Bank 2006). Poor physical health and development. mental health are barriers to participation in education and Adolescence is increasingly understood as a key devel- employment, as are policies and systems that do not enable opmental stage for assuring health across the course of equitable access. Finally, in their role as current and future one’s life, and as such, provides significant opportunities to parents, the health of adolescents has significant implica- improve population health in the EMR (Patton et al. 2016; tions for the next generation (Patton et al. 2016). The World Bank 2006). Firstly, adolescents represent more To date, the health problems and health risks of ado- than a quarter of the population in the EMR, and their lescents in the EMR have been inadequately described health needs are likely to be distinct from children and (Alaovie et al. 2017). This is a significant barrier to adults. Conflict and civil unrest (which have been a feature developing comprehensive policies that address adolescent of many countries in the EMR) have a large impact on the health and to measuring the impact of any investments health of young people, both acutely (through high rates of made. This paper aims to report the health profile for mortality and morbidity due to violence) but also in the adolescents living in the EMR. longer term (including mental health disorder and poor sexual and reproductive health) (Viner et al. 2012). Sec- ondly, many health risks typically emerge during adoles- cence including those for non-communicable diseases Methods (NCDs) such as substance use, overweight, and physical inactivity. Given that NCDs are now the leading cause of We framed our study around the conceptual framework poor health in the EMR, there is a potential to intervene defined by the Lancet Commission of Adolescent Health before harms arise (Mokdad et al. 2016b). Thirdly, and Wellbeing (hereafter referred to as the Commission) 123 Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S81 (Patton et al. 2016). Health needs included: health out- In addition to region-level estimates, we also report comes (mortality, non-fatal diseases, and injuries); health country-specific DALY estimates and the prevalence of risks (behaviors and states that carry risk for poor health in three key health risks and four determinants (aligned with and beyond adolescence); and determinants of health (such the conceptual framework from the Commission and data as education and employment). Adolescence was defined availability) to help prioritize country-specific actions as 10–24 years, as these years encompass the important (Patton et al. 2016). Data for health risks were sourced biological, neurocognitive, and social role transitions that from GBD 2015. Tobacco smoking was defined as current typically define adolescence (Mokdad et al. 2016b; Patton daily smoked tobacco use (GBD Tobacco Collaborators et al. 2016; Sawyer et al. 2012). Where possible, we report 2017). Overweight was defined using the International age-disaggregated data for young adolescents Obesity Task Force age and gender specific cut-offs, (10–14 years), older adolescents (15–19 years), and young equivalent to BMI C25 kg/m at age 18 (Cole and Lobstein adults (20–24 years) (Patton et al. 2016). 2012). This definition includes those who are obese. Binge Data are drawn from the Global Burden of Disease drinking was defined as having consumed 60 grams of Study 2015 (GBD 2015) as this provides a complete set of alcohol on a single occasion for males and 48 grams of comparable health estimates for 195 countries, including alcohol on a single occasion for females in the last all those in the EMR. Methods are described in detail 12 months. With respect to determinants, adolescent fer- elsewhere (GBD DALYs Hale Collaborators 2016; GBD tility rate (live births per 1000 15- to 19-year-old females) Disease Injury Incidence and Prevalence Collaborators and mean years of educational attainment for 15- to 2016; GBD Mortality and Causes of Death Collaborators 24-year olds were sourced from GBD 2015 (GBD SDG 2016; GBD SDG Collaborators 2016), but briefly, GBD Collaborators 2016). Unmet need for contraception (15- to 2015 includes a comprehensive and systematic analysis of 24-year-old females currently married or in union and not 249 causes of death, 310 causes of disease and injury, and wanting to become pregnant within the next two years, who 79 behavioral and environmental health risks. GBD 2015 report not using any method of contraception) was sourced has four levels of causes that are mutually exclusive. Level from a review DHS and MICS surveys available in the one has three causes: type I conditions (communicable, EMR (data were collected from 2009 to 2014) (Patton et al. maternal, neonatal, and nutritional disorders); non-com- 2016). Youth unemployment data, defined as the percent- municable diseases; and injuries. Level two has 21 causes, age of 15- to 24-year olds without work but available for while levels three and four consist of all disaggregated and seeking employment, were obtained from the Inter- causes. For this analysis we report causes at level four. national Labor Organization modeled estimates for 2013 GBD is based on the best available primary data and (Patton et al. 2016). employs a series of disease models to harmonize health We reported observed estimates for the region. We estimates and fill data gaps. Each step of the estimation additionally report expected DALYs for each country process of GBD 2015 has been documented, as well as data based on the level of socioeconomic development. sources, in accordance with Guidelines for Accurate and Expected DALYs were estimated using the Socio-demo- Transparent Health Estimates Reporting (GATHER). For graphic Index (SDI) which is based on income per capita, this analysis, we accessed data in 5-year age bands, for average educational attainment for ages 15 or older, and males and females, from 1990 to 2015 in 5-year time slices. the total fertility rate (GBD SDG Collaborators 2016). SDI Mortality is reported as all-cause and cause-specific is reported as a continuous variable from 0 (lowest) to 1 rates per 100,000 (GBD Mortality and Causes of Death (highest), and as quintiles, as shown in Table 1. GBD 2015 Collaborators 2016). Non-fatal diseases and injuries are has estimated the relationship between SDI and each cause reported as years lived with disability (YLDs), a metric of DALYs using spline regressions, with these regressions which incorporates prevalence of disease, duration, and its then used to estimate expected DALYs at each level of SDI severity (using disease weights) (GBD Disease Injury (GBD DALYs Hale Collaborators 2016). Incidence and Prevalence Collaborators 2016). As a sum- mary measure of population health, we also report dis- ability-adjusted life-years (DALYs), the sum of years of Results healthy life lost due to premature mortality (YLLs), and years of life lived with disability (YLDs) (GBD DALYs Mortality Hale Collaborators 2016). For these estimates, we report 95% uncertainty estimates, which are distinct from confi- All-cause mortality rates for adolescents in the EMR dence intervals in that they represent uncertainty derived ranged from 63.3 per 100,000 for females aged from sampling, model estimation, and model specification 10–14 years to 253.2 per 100,000 for males aged (GBD DALYs Hale Collaborators 2016). 20–24 years in 2015 (e-Figure 1, panel A). Males had a 123 S82 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators higher overall mortality rate than females. The risk of and nutritional diseases. DALY rates have increased for mortality for males aged 15–24 years had increased males aged 15–19 and 20–24 since 1990, largely due to an over recent years compared to what was otherwise an increased burden of injury. The leading causes of DALYs by overall trend of reduction in mortality. Table 2 details age and sex are provided in Table 4. For females, type 1 the leading causes of mortality by sex. The most conditions (nutritional disorders, communicable disease, striking transition in mortality cause over time was the and maternal disorders) remain important causes of DALYs. reductionindeaths duetonatural disaster and com- However, non-communicable diseases (mental health dis- municable diseases, and the emergence of mortality due orders, migraine, skin conditions, and musculoskeletal dis- to injuries (especially in the context of war) and NCDs. orders) account for more than half of the total disease burden. In 1990 and 2005 natural disaster ranked as a leading For males, injuries due to conflict, transport, and other cause of mortality for adolescents, whereas in 2015 it unintentional injuries are the leading causes of DALYs, was no longer a leading cause of death for adolescents. particularly amongst 15- to 24-year olds. In 2015, war and legal interventions (law enforcement) There was considerable variation in all-cause and was the leading cause of death for adolescents of both cause-specific DALY rates across countries in the region sexes, representing 27.7% (14.2–38.4) of deaths (e-Figure 2, panels A–C). In all countries in the region, amongst male 20- to 24-year olds and 7.2% (3.1–10.9) DALY rates are highest among males, and higher among amongst female 20- to 24-year olds. For males, injuries 20- to 24-year olds than other ages in males and females. (unintentional injuries, self-harm and violence) were the The highest DALY rates were in countries most affected predominant causes of mortality across adolescence, by recent conflict or insecurity and/or those with the and communicable diseases an important cause for 10- lowest SDI, such as Pakistan (17,483 per 100,000 to 14-year olds. The leading cause of mortality for 10–24 years in 2015), Somalia (27,716 DALYs per females included injuries; however, communicable and 100,000 10- to 24-year olds in 2015), Afghanistan (32,068 maternal conditions were also leading causes, with per 100,000 10- to 24-year olds in 2015) and Syria NCDs emerging as an important cause amongst older (33,452 per 100,000 10- to 24-year olds in 2015), with female adolescents. 10- to 24-year olds globally having a DALY rate of 14,557 per 100,000 in 2015. In these countries, injury, YLDs particularly due to war and legal intervention was a major contributor to DALYs, particularly amongst males. For All-cause YLD rates are similar for males and females in the example, in Syria over 70% of DALYs to 10–24 year region, and have seen little improvement since 1990 (e- olds were due to injury, with males aged 20–24 experi- encing the largest burden. A number of these countries Figure 1 panel B). The leading causes of YLDs are detailed in Table 3. While the burden of some communicable, also experience a high burden of nutritional disorders and maternal, and nutritional disorders has declined, this has communicable disease among younger adolescents, in largely been offset by an increase in disability due to injury addition to a substantial burden of maternal health prob- among males and lack of reduction in YLDs from non- lems. Countries with a higher SDI and those less affected communicable disease. From 1990 to 2015, iron deficiency by conflict experienced a lower burden of poor health. In anemia was the leading cause of disability for females aged these settings DALYs were mostly due to NCDs includ- 10–14 and 15–19 years, and for males aged 10–14 years. ing mental health disorders, skin conditions, asthma, NCDs, particularly mental health disorders, migraine, migraine, and musculoskeletal disorders. asthma, skin conditions, and musculoskeletal disorders, The three countries that had the largest populations of were major contributors to YLDs for both sexes in 2015. adolescents in the EMR (Pakistan, Iran, and Egypt) had very Major depression emerged as the leading cause of morbidity different disease burdens. Egypt (12,418 DALYs per 100,000 amongst males aged 15–19 (7.0%, uncertainty 4.6–9.9) and 10- to 24-year olds in 2015) and Iran (12,624 DALYs per 20–24 years (8.0%, uncertainty 5.1–11.7) and for females 100,000 10- to 24-year olds in 2015) has similar low rates of aged 20–24 years (9.1%, uncertainty 6.2–12.4) in 2015. DALYs; however, Iran had a higher burden due to injury Among older males, opioid use disorders and war were also (3361 per 100,000 in Iran compared to 1938 per 100,000 in important causes of disability. Egypt). Pakistan had a high burden of injury (3367 per 100,000) but more so type I conditions (5252 per 100,000). DALYs e-Figure 2, panels D–F shows the expected DALYs in each country based on the SDI. The most striking finding All-cause DALY rates have declined for females of all ages is that with the reduction of DALYs due to war (which is and 10- to 14-year-old males in the region (e-Figure 1, panel not expected based on development), there remains a very c), largely due to a reduction of communicable, maternal, large burden of poor health for adolescents in the EMR. 123 Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S83 Table 2 Leading contributors to poor health (mortality) for adolescents in the Eastern Mediterranean Region, in 1990, 2005, 2015 Top ten causes of mortality in females and males Females 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Natural disaster 8.0% (3.2–12.6) Natural disaster 12.8% (7.4–18) War and legal intervention 9.5% (4.2–14.2) 2 Diarrheal diseases 5.8% (4.1–7.8) Typhoid fever 5.3% (2.9–8.9) Lower respiratory infect. 5.6% (3.6–7.3) 3 Lower respiratory infect. 5.7% (3.5–7.4) Lower respiratory infect. 4.7% (3.2–6.1) Typhoid fever 5.2% (2.9–8.7) 4 Measles 5.3% (1.5–12.7) Diarrheal diseases 4.6% (3.2–6.7) Congenital heart 4.8% (3.3–6.5) 5 Tuberculosis 4.5% (2.2–67) Tuberculosis 4.4% (2.5–6.4) Drowning 4.3% (2.7–5.9) 6 Drowning 4.3% (2.5–6.4) Drowning 4.1% (2.6–5.8) Tuberculosis 4.0% (2.3–6) 7 Typhoid fever 4.3% (2 3–7.5) Congenital heart 3.9% (2.6–5.8) Diarrheal diseases 3.9% (2.6–5.9) 8 Motor vehicle road inj. 3.2% (2.4–4.2) Motor vehicle road inj. 3.5% (2.8–4.2) Motor vehicle road inj. 3.6% (2.9–4.5) 9 Hemorrhagic stroke 3.1% (2.5–3.9) Malaria 2.8% (0.9–7.2) Other unintentional 2.7% (1.7–4.1) 10 Congenital heart 3.1% (2–5.2) Measles 2.4% (0.6–6.7) Malaria 2.6% (0.7–7.6) 15–19 years 1 Natural disaster 5.8% (2.2–9.3) Natural disaster 8.1% (4.4–11.5 War and legal intervention 10.1% (4.4–15.5) 2 Tuberculosis 5.8% (3.3–8.7) Maternal hemorrhage 5.4% (3.7–7.2) Tuberculosis 4.7% (2.8–6.7) 3 Maternal hemorrhage 5.5% (3.8–7.7) Tuberculosis 5.2% (3.2–7.2) Maternal hemorrhage 3.8% (2.3–5.6) 4 Diarrheal diseases 4.2% (3–5.7) Maternal hypertension 3.6% (2.4–5) Motor vehicle road inj. 3.5% (2.8–4.4) 5 Maternal hypertension 3.8% (2.4–5.7) Motor vehicle road inj. 3.6% (2.9–4.4) Maternal hypertension 3.4% (2–5.3) 6 Drowning 3.4% (2–5.2) Diarrheal diseases 3.5% (2.4–4.9) Drowning 3.4% (2–4.8) 7 Ischemic heart disease 3.0% (2.5–3.6) Drowning 3.4% (2–4.7) Malaria 3.3% (1.5–6.3) 8 Motor vehicle road inj. 2.9% (2.3–3.7) Self-harm 3.4% (2.5–6.3) Self-harm 2.9% (2.1–6.3) 9 Self-harm 2.9% (1.9–5.3) Ischemic heart disease 2.9% (2.4–3.5) Diarrheal diseases 2.9% (1.9–4.2) 10 Hemorrhagic stroke 2.8% (2.3–3.4) Malaria 2.9% (1.5–5.1) Ischemic heart disease 2.8% (2.3–3.5) 20–24 years 1 Maternal hemorrhage 8.2% (5.8–11) Maternal hemorrhage 7.7% (5.7–10.2) War and legal intervention 7.2% (3.1–10.9) 2 Tuberculosis 7.1% (4.4–10.7) Tuberculosis 6.2% (4–8.5) Tuberculosis 5.9% (3.7–8.1) 3 Maternal hypertension 5.6% (3.7––8.2) Natural disaster 5.9% (3.2–8.5) Maternal hemorrhage 5.6% (3.7–8.1) 4 Natural disaster 4.1% (1.5–6.6) Maternal hypertension 5.4% (3.8–7.4) Maternal hypertension 5.0% (3.1–7.6) 5 Other maternal disorders 3.9% (2.4–5.8) Motor vehicle road inj. 3.6% (2.9–4.4) Ischemic heart disease 3.6% (3–4.4) 6 Ischemic heart disease 3.6% (3–4.3) Ischemic heart disease 3.5% (2.9–4.3) Motor vehicle road inj. 3.5% (2.9–4.3) 7 Hemorrhagic stroke 2.9% (2.4–3.5) Self-harm 3.3% (2.4–6.2) Self-harm 3.1% (2.3–6.5) 8 Motor vehicle road inj. 2.8% (2.2–3.7) Hemorrhagic stroke 2.6% (2.2–3.2) Other maternal disorders 2.9% (1.7–4.5) 9 Diarrheal diseases 2.8% (2–3.9) Abortion, miscarriage, ectopic 2.3% (1.5–3.3) Hemorrhagic stroke 2.6% (2.1–3.3) 10 Abortion, miscarriage, ectopic 2.8% (1.7–4.4) Other maternal disorders 2.2% (1.6–3.1) Cirrhosis other 2.2% (1.5–3) S84 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 2 continued Top ten causes of mortality in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Natural disaster 9.8% (15.1–3.9) Natural disaster 16.1% (9.4–22.1) War and legal intervention 12.2% (5.5–18.1) 2 Drowning 8.6% (10.9–6.5) Drowning 6.4% (5.2–7.7) Other unintentional 6.9% (4.6–10.1) 3 Lower respiratory infect. 5.4% (7.1–3.4) Motor vehicle road inj. 5.7% (4.8–7) Drowning 6.4% (5.2–7.9) 4 Motor vehicle road inj. 5.3% (6.3–4.2) Other unintentional 5.6% (3.6–8.2) Motor vehicle road inj. 6.0% (4.8–7.5) 5 Pedestrian road inj. 5.3% (6.6–4) Pedestrian road inj. 5.0% (3.9–6.2) Lower respiratory infect. 4.8% (3.5–6.3) 6 Diarrheal diseases 4.1% (6–2.7) Lower respiratory infect. 4.2% (3.2–5.5) Pedestrian road inj. 4.7% (3.6–5.9) 7 Measles 3.7% (9.2–1) Typhoid fever 4.0% (2.2–6.8) Typhoid fever 4.0% (2.1–7) 8 Other unintentional 3.7% (5.4–2.5) Diarrheal diseases 3.1% (1.9–4.7) Diarrheal diseases 2.9% (1.8–4.6) 9 Typhoid fever 3.6% (6.1–1.9) Hemorrhagic stroke 2.3% (1.9–2.6) Congenital heart 2.6% (1.8–3.4) 10 Hemorrhagic stroke 3.3% (4.1–2.7) Congenital heart 2.2% (1.4–2.9) Hemorrhagic stroke 2.2% (1.9–2.6) 15–19 years 1 Natural disaster 9.6%(3.8–14.8) Natural disaster 12.5% (7.2–17.5) War and legal intervention 27.2% (13.2–37.9) 2 Motor vehicle road inj. 8.9% (6.8–11.8) Motor vehicle road inj. 9.8% (8.1–12.1) Other unintentional 8.4% (5–12.5) 3 Drowning 6.7% (4.8–8.9) Other unintentional 7.9% (5.2–11.3) Motor vehicle road inj. 8.4% (6.5–10.8) 4 Other unintentional 5.3% (3.5–7.5) Pedestrian road inj. 5.4% (4.1–6.8) Drowning 4.0% (3.1–5.2) 5 Pedestrian road inj. 4.7% (2.9–6.2) Drowning 5.1% (4.3–6.2) Pedestrian road inj. 4.0% (2.9–5.3) 6 War and legal intervention 4.3% (1.5–9.3) Motorcyclist road inj. 4.0% (2.9–5.4) Self-harm 2.9% (2.2–3.7) 7 Self-harm 3.1% (2.4–4) Self-harm 3.5% (2.8–4.2) Motorcyclist road inj. 2.8% (1.8–3.9) 8 Motorcyclist road inj. 3.0% (1.8–4.5) War and legal intervention 3.4% (1.7–5) Lower respiratory infect. 2.3% (1.6–3.1) 9 Lower respiratory infect. 3.0% (2–3.8) Lower respiratory infect. 2.4% (1.8–3.1) Physical violence by firearm 2.2% (1.2–3.3) 10 Hemorrhagic stroke 2.8% (2.2–3.4) Hemorrhagic stroke 2.2% (1.8–2.5) Other physical violence 1.8% (0.8–2.9) 20–24 years 1 Motor vehicle road inj. 9.9% (7.7–12.9) Motor vehicle road inj. 11.1% (9.4–13.4) War and legal intervention 27.7% (14.2–38.4) 2 Natural disaster 6.8% (2.7–10.8) Natural disaster 8.9% (5–12.8) Motor vehicle road inj. 8.9% (7–11.3) 3 War and legal intervention 5.3% (1.8–11.5) Other unintentional 6.8% (4.4–10.1) Other unintentional 6.8% (4–10.3) 4 Pedestrian road inj. 5.0% (3.1–6.5) Pedestrian road inj. 5.7% (4.4–7) Pedestrian road inj. 4.2% (3.1–5.4) 5 Other unintentional 5.0% (3.3–7.1) Self-harm 4.6% (3.8–5.5) Self-harm 3.8% (3–5) 6 Drowning 5.0% (3.4–6.7) War and legal intervention 4.3% (2.2–6.4) Motorcyclist road inj. 2.8% (2–4) 7 Self-harm 4.2% (3.3–5.4) Motorcyclist road inj. 4.1% (3–5.6) Drowning 2.8% (2.2–3.6) 8 Tuberculosis 3.7% (2.4–5.9) Drowning 3.7% (3.1–4.4) Other physical violence 2.6% (1–4) Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S85 Health risks and determinants The prevalence of selected health risks is provided in e-Figure 3. The prevalence of overweight and obesity was highest among countries with a higher SDI in the region, and was generally similar for males and females. Rates of daily tobacco smoking among males aged 10–24 years ranged from 1.9% in Sudan to 18% in Kuwait, but were less than 5% for females in the region. Similarly, the prevalence of binge drinking was higher among males than females at all ages, but was less than 10% for both sexes in most EMR countries. Unmet need for contraception was high among the 11 countries for which data are available (e-Figure 4). More than one third of females who are married or in union have unmet need for contraception in Pakistan, Djibouti, Somalia, Sudan, and Yemen. These countries also have among the highest rates of adolescent birth rates in the region, adolescent fertility the greatest in Somalia (114.7 live births per 1000 females aged 15–19 in 2015). There was also great variation in educational attainment in the EMR region. Low-SDI countries affected by protracted insecurity and conflict have the lowest mean number of years of completed education, most notably for females. Rates of unemployment among 15- to 24-year olds also vary considerably, and were generally higher for females than males. Discussion This study is the first systematic analysis of adolescent health in the EMR. The findings suggest dramatic shifts in the health of adolescents living in the EMR over the past 25 years. Communicable diseases and the health conse- quences of natural disasters have reduced substantially, but these gains have largely been offset by war and the emergence of NCDs including mental health disorders, unintentional injury, and self-harm. Indeed, adolescents living in Syria, Afghanistan, and Somalia experience amongst the largest burdens of disease and injury of all adolescents globally (Patton et al. 2016). Even with the return of peace and security to this region, adolescents will have a persisting poor health profile that will pose a barrier to socioeconomic growth and development of the EMR (The World Bank 2006). The substantial reductions in mortality and morbidity due to communicable disease, maternal disorders, and natural disasters in the EMR are likely the result of socioeconomic growth and development, educational par- ticipation, and interventions through the health system. Recent wars and civil conflict, however, threaten the foundations on which these gains were made, with the risk of resurgence of many of these conditions. This is in Table 2 continued Top ten causes of mortality in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 9 Motorcyclist road inj. 3.1% (1.8–4.7) Other physical violence 3.0% (1.3–4.1) Physical violence by firearm 2.4% (1.3–3.6) 10 Ischemic heart disease 3.0% (2.5–3.6) Ischemic heart disease 2.7% (2.3–3.2) Ischemic heart disease 2.3% (1.8–2.9) Global burden of disease study 2015, Eastern Mediterranean Region, 1990–2015 Italic defines communicable, maternal, neonatal and nutritional diseases Bold defines non-communicable diseases Bold, italic defines injuries S86 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 3 Leading contributors to poor health (YLDs) for adolescents in the Eastern Mediterranean Region, in 1990, 2005, 2015 Top ten causes of years lived with a disability (YLDs) in females and males Females 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 15.7% (13.5–17.6) Iron-deficiency anemia 16.4% (13.9–18.6) Iron-deficiency anemia 16.7% (14.3–18.9) 2 Migraine 7.0% (4.4–9.9) Migraine 7.5% (4.7–10.7) Migraine 7.6% (4.8–10.8) 3 Anxiety disorders 6.4% (4.6–8.8) Anxiety disorders 6.8% (4.9–9.3) Anxiety disorders 7.0% (5–9.5) 4 Asthma 5.6% (4.2–7.4) Conduct disorder 5.8% (3.3–8.6) Conduct disorder 5.9% (3.4–8.8) 5 Conduct disorder 5.5% (3.1–8.4) Asthma 5.3% (3.9–6.9) Asthma 5.7% (4.1–7.6) 6 Major depressive disorder 4.1% (2.6–6) Major depressive disorder 4.3% (2.7–6.2) Major depressive disorder 4.4% (2.8–6.3) 7 Low back pain 3.0% (2.3–3.9) Acne vulgaris 3.1% (1.7–5.3) Acne vulgaris 3.2% (1.7–5.5) 3 Epilepsy 2.9% (1.9–3.9) Low back pain 3.0% (2.3–4) Low hack pain 3.0% (2.3–4) 9 Acne vulgaris 2.8% (1.5–4.8) Epilepsy 2.8% (2–3.8) Dermatitis 2.8% (2.1–3.6) 10 Dermatitis 2.5% (1.9–3.3) Dermatitis 2.7% (2–3.6) Epilepsy 2.6% (1.8–3.7) 15–19 years 1 Iron-deficiency anemia 10.3% (8.2–12.3) Iron-deficiency anemia 10.1% (8.3–12) Iron-deficiency anemia 10.0% (8.1–11.9) 2 Major depressive disorder 8.0% (5.6–10.9) Major depressive disorder 8.1% (5.7–11) Migraine 8.3% (5.3–11.9) 3 Migraine 7.9% (4.9–11.3) Migraine 8.1% (5.1– 11.4) Major depressive disorder 8.3% (5.9–11.2) 4 Anxiety disorders 6.8% (5–9.2) Anxiety disorders 7.0% (5.2–9.4) Anxiety disorders 7.2% (5.3–9.7) 5 Low back pain 5.0% (3.8–6.4) Low back pain 5.1% (3.9–6.6) Low hack pain 5.0% (3.8–6.5) 6 Acne vulgaris 3.5% (1.8–5.9) Acne vulgaris 3.7% (2–6.3) Acne vulgaris 3.9% (2–6.6) 7 Asthma 3.4% (2.4–4.4) Other musculoskeletal 3.7% (2.6–5.1) Other musculoskeletal 3.9% (2.7–5.5) 8 Conduct disorder 3.1% (1.8–4.9) Conduct disorder 3.2% (1.9–5) Conduct disorder 3.3% (1.9–5.1) 9 Other musculoskeletal 3.0% (2.1–4.2) Asthma 3.2% (2.3–4.2) Asthma 3.3% (2.3–4.3) 10 Epilepsy 2.2% (1.5–3) Epilepsy 2.1% (1.5–2.8) Epilepsy 2.0% (1.4–2.8) 20–24 years 1 Iron-deficiency anemia 10.2% (8.1–12.3) Iron-deficiency anemia 9.0% (7.1–11) Major depressive disorder 9.1% (6.2–12.4) 2 Major depressive disorder 8.7% (5.9–11.8) Major depressive disorder 8.8% (6–12.1) Iron-deficiency anemia 8.9% (7–10.8) 3 Migraine 7.8% (4.9–11.4) Migraine 8.0% (5–11.6) Migraine 8.3% (5.3–12) 4 Anxiety disorders 6.0% (4.4–8.2) Anxiety disorders 6.2% (4.5–8.5) Anxiety disorders 6.4% (4.7–8.6) 5 Low back pain 6.0% (4.6–7.7) Low back pain 6.1%(4.7–7.9) Low back pain 6.1% (4.7–7.9) 6 Other musculoskeletal 4.2% (3–5.6) Other musculoskeletal 4.9% (3.5–6.6) Other musculoskeletal 5.4% (3.9–7.3) 7 Bipolar disorder 2.4% (1.6–3.5) Neck pain 2.5% (1.7–3.4) Bipolar disorder 2.5% (1.7–3.7) 8 Neck pain 2.3% (1.5–3.2) Bipolar disorder 2.4% (1.6–3.5) Neck pain 2.4% (1.6–3.3) 9 Other mental and substance 2.2% (1.7–2.8) Other mental and substance 2.3% (1.8–2.9) Other mental and substance 2.4% (1.9–3.1) 10 Premenstrual syndrome 1.9% (1.4–2.6) Premenstrual syndrome 1.9% (1.4–2.6) Medication overuse 1.9% (1.2–3) Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S87 Table 3 continued Top ten causes of years lived with a disability (YLDs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 18.9% (16.6–20.9) Iron-deficiency anemia 19.4% (17–21.5) Iron-deficiency anemia 19.5% (17–21.6) 2 Conduct disorder 7.5% (4.7–10.7) Conduct disorder 7.9% (5–11.3) Conduct disorder 8.1% (5.1–11.5) 3 Asthma 5.3% (3.9–6.9) Asthma 5.2% (3.8–6.8) Asthma 5.1% (3.7–6.8) 4 Anxiety disorders 4.0% (2.8–5.5) Anxiety disorders 4.2% (3–5.9) Anxiety disorders 4.3% (3.1–6.1) 5 Migraine 3.3% (2–4.8) Migraine 3.5% (2.2–5.2) Migraine 3.6% (2.2–5.3) 6 Low back pain 2.9% (2.2–3.9) Low back pain 3.1% (2.3–4) Low back pain 3.0% (23–4.1) 7 Epilepsy 2.9% (2–3.9) Major depressive disorder 2.9% (1.7–4.5) Major depressive disorder 3.0% (1.8–4.6) 8 Major depressive disorder 2.7% (1.6–4.3) Acne vulgaris 2.8% (1.5–4.7) Acne vulgaris 2.9% (1.5–4.9) 9 Acne vulgaris 2.5% (1.3–4.2) Epilepsy 2.6% (1.8–3.4) Epilepsy 2.5% (1.7–3.5) 10 Thalassemias trait 2.2% (1.9–2.4) Thalassemias trait 2.4% (2.1–2.6) Thalassemias trait 2.4% (2.1–2.7) 15–19 years 1 Iron-deficiency anemia 7.7% (6.2–9.6) Major depressive disorder 6.9% (4.5–9.9) Major depressive disorder 7.0% (4.6–9.9) 2 Major depressive disorder 6.6% (4.3–9.6) Iron-deficiency anemia 6.8% (5.2–8.6) Iron-deficiency anemia 6.5% (5–8.3) 3 Low back pain 6.3% (4.9–8.1) Low back pain 6.5% (4.9–8.3) Low back pain 6.4% (4.8–8.3) 4 Conduct disorder 5.7% (3.5–8.3) Conduct disorder 6.0% (3.8–8.7) Conduct disorder 6.0% (3.7–8.8) 5 Migraine 4.9% (3–7.1) Migraine 5.2% (3.2–7.5) Migraine 5.3% (3.3–7.7) 6 Anxiety disorders 4.6% (3.3–6.3) Anxiety disorders 4.9% (3.5–6.6) Anxiety disorders 4.9% (3.6–6.7) 7 Acne vulgaris 3.7% (1.9–6.4) Acne vulgaris 4.1% (2.1–6.8) Acne vulgaris 4.2% (2.2–7.1) 8 Asthma 3.5% (2.6–4.6) Other musculoskeletal 3.8% (2.7–5.3) Other musculoskeletal 4.0% (2.7–5.6) 9 Other musculoskeletal 3.0% (2–4.3) Asthma 3.5% (2.5–4.6) Asthma 3.3% (2.4–4.5) 10 Epilepsy 2.6% (1.9–3.5) Epilepsy 2.5% (1.8–3.3) War and legal intervention 2.7% (1.2–5) 20–24 years 1 Major depressive disorder 7.7% (4.9–11.4) Major depressive disorder 7.9% (5–11.8) Major depressive disorder 8.0% (5.1–11.7) 2 Low back pain 7.3% (5.7–9.4) Low back pain 7.4% (5.7–9.4) Low back pain 7.4% (5.7–9.4) 3 Migraine 5.7% (3.7–8.1) Migraine 5.8% (3.8–8.3) Migraine 5.9% (3.8–8.5) 4 Other mental and substance 4.2% (3.4–5.3) Opioid use disorders 5.1% (3.6–6.8) Other musculoskeletal 4.9% (3.5–6.6) 5 Iron-deficiency anemia 4.2% (3–5.5) Other musculoskeletal 4.6% (3.3–6.1) Opioid use disorders 4.9% (3.5–6.6) 6 Opioid use disorders 4.2% (2.9–5.6) Other mental and substance 4.4% (3.6–5.5) Other mental and substance 4.5% (3.5–5.5) 7 Anxiety disorders 3.9% (2.7–5.5) Anxiety disorders 4.0% (2.8–5.5) Anxiety disorders 4.0% (2.8–5.7) 8 War and legal intervention 3.8% (2–6.1) Iron-deficiency anemia 3.6% (2.6–4.8) War and legal intervention 3.6% (1.6–6.3) S88 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators addition to the growing burden of NCDs and injuries. Renewed efforts to consolidate gains made in communi- cable disease and maternal health will be required. The Lancet Commission described the benefits that can accrue from investments in adolescence. Without these invest- ments, the EMR region risks poor health across adoles- cence, adulthood, and in the next generation (Patton et al. 2016). War and legal interventions (deaths due to law enforcement, regardless of their legality) were the leading causes of mortality for adolescents aged 10–24 years of both genders in the EMR. While not all countries in the EMR are affected by conflict, the magnitude of mortality in those countries that are affected signifies this as a priority for the region. It should also be noted, however, that at a population level (all ages combined), war and legal inter- vention is only the fifth leading cause of mortality in the EMR (GBD 2015 Eastern Mediterranean Region Collab- orators and Mokdad 2017). This may reflect competing causes of mortality at other ages, or it may signify that war and legal interventions disproportionately affect adoles- cents, particularly 20- to 24-year-old males. In addition to the physical injuries and disability that accompany conflict, violence and trauma at this critical developmental stage carry a risk of persisting effects on future mental health and well-being. War and conflict are also likely to result in disruption to quality education, social infrastructure, and community development, which have profound implica- tions for health and well-being across the course of one’s life. This may explain why expected DALYs in countries which have experienced large burdens of conflict remain high. In addition to the health status of adolescents, we explored the burden of risk behavior for future health. Tobacco smoking and high body mass were common risks where interventions during adolescence have the potential to avert later ischemic heart disease, the leading cause of poor health in the region. Of note, estimates of tobacco smoking reported here do not include Sisha smoking which is prevalent in some countries of the EMR and harmful (Maziak et al. 2004). Low rates of education completion in many countries including Afghanistan, Somalia, and Yemen are a major obstacle to growth and future prosperity of this region. High rates of adolescent pregnancy represent an important target for action to improve health and life opportunities for girls and young women. Unmet need for contraception is very high, and is likely to also signify high rates of unmet need for other essential health interventions, particularly for culturally sensitive needs such as sexually transmitted infections and mental health. Given adolescents face barriers in accessing health facilities, there is a need to explore other approaches such as community-based deliv- ery or school health services (Tylee et al. 2007). There is Table 3 continued Top ten causes of years lived with a disability (YLDs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 9 Other musculoskeletal 3.5% (2.5–4.8) Neck pain 2.5% (1.7–3.5) Iron-deficiency anemia 3.1% (2.2–4.1) 10 Other unintentional inj. 2.3% (2–2.7) Bipolar disorder 2.4% (1.6–3.5) Bipolar disorder 2.4% (1.6–3.5) Global burden of disease study 2015, Eastern Mediterranean Region, 1990–2015 Italic defines communicable, maternal, neonatal and nutritional diseases Bold defines non-communicable diseases Bold, italic defines injuries YLDs years of life with disability Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S89 Table 4 Leading contributors to poor health (DALYs) for adolescents in the Eastern Mediterranean Region, in 1990, 2005, 2015 Top ten causes of disability- adjusted life years (DALYs) in females and males Females 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 7.8% (6.1–9.8) Iron-deficiency anemia 8.8% (6.9–11) Iron-deficiency anemia 9.9% (7.9–12.1) 2 Natural disaster 4.5% (2–6.9) Natural disaster 7.0% (4–9.8) War and legal intervention 4.5% (2.3–6.9) 3 Diarrheal diseases 3.4% (2.5–4.6) Migraine 4.0% (2.5–5.7) Migraine 4.5% (2.8–6.4) 4 Migraine 3.4% (2.1–5) Anxiety disorders 3.6% (2.5–4.9) Anxiety disorders 4.1% (2.9–5.6) 5 Asthma 3.3% (2.4–4.3) Asthma 3.3% (2.5–4.3) Asthma 3.8% (2.7–5) 6 Anxiety disorders 3.2% (2.2–4.3) Conduct disorder 3.1% (1.8–4.7) Conduct disorder 3.5% (2–5.3) 7 Lower respiratory infect. 3.0% (1.8–4) Diarrheal diseases 2.7% 12–3 .8) Major depressive disorder 2.6 % (1.6–3.7) 8 Measles 2.7% (0.8–6.5) Typhoid fever 2.5% (1.4–4.2) Lower respiratory infect. 2.3% (1.5–3.2) 9 Conduct disorder 2.7% (1.5–4.2) Major depressive disorder 2.3% (1.4–3.3) Epilepsy 2.2% (1.6–2.9) 10 Tuberculosis 2.4% (1.3–3.7) Lower respiratory infect. 2.2% (1.5–3) Diarrheal diseases 2.2% (1.6–3.1) 15–19 years 1 Iron-deficiency anemia 5.3% (3.9–6.8) Iron-deficiency anemia 5.4% (4.1–6.8) Iron-deficiency anemia 5.5% (4.2–7.1) 2 Major depressive disorder 4.0% (2.7–5.6) Natural disaster 4.6% (2.7–6.4) War and legal intervention 5.3% (2.6–8.1) 3 Migraine 4.0% (2.4–5.7) Major depressive disorder 4.2% (2.9–5.9) Migraine 4.6% (2.8–6.6) 4 Anxiety disorders 3.4% (2.4–4.7) Migraine 4.2% (2.6–6.1) Major depressive disorder 4.5% (3.1–6.3) 5 Natural disaster 3.2% (1.4–5.1) Anxiety disorders 3.7% (2.6–4.9) Anxiety disorders 3.9% (2.8–5.3) 6 Tuberculosis 3.1% (1.9–4.7) Low back pain 2.6% (2–3.5) Low back pain 2.7% (2–3.6) 7 Maternal hemorrhage 2.7% (1.9–3.9) Tuberculosis 2.6% (1.6–3.7) Tuberculosis 2.3% (1.4–3.3) 8 Low back pain 2.5% (1.9–3.3) Maternal hemorrhage 2.6% (1.8–3.7) Other musculoskeletal 2.3% (1.6–3.1) 9 Diarrheal diseases 2.4% (1.8–3.3) Asthma 2.1% (1.5–2.7) Asthma 2.2% (1.6–2.9) 10 Asthma 2.2% (1.7–2.8) Other musculoskeletal 2.0% (1.4–2.8) Acne vulgaris 2.2% (1.1–3.8) 20–24 years 1 Iron-deficiency anemia 5.0% (3.7–6.6) Iron-deficiency anemia 4.7% (3.5–6.2) Major depressive disorder 5.0% (3.3–7) 2 Maternal hemorrhage 4.2% (3–5.8) Major depressive disorder 4.6% (3–6.5) Iron-deficiency anemia 4.9% (3.6–6.3) 3 Major depressive disorder 4.2% (2.8–6) Migraine 4.1% (2.6–6.1) Migraine 4.5% (2.9–6.7) 4 Tuberculosis 3.9% (2.5–5.6) Maternal hemorrhage 3.7% (2.6–5.1) War and legal intervention 3.7% (1.8–5.6) 5 Migraine 3.8% (2.4–5.6) Natural disaster 3.5% (2.1–5) Anxiety disorders 3.5% (2.4–4.8) 6 Maternal hypertension 3.1% (2–4.4) Anxiety disorders 3.2% (2.3–4.4) Low back pain 3.3% (2.4–4.5) 7 Anxiety disorders 2.9% (2–4) Tuberculosis 3.2% (2.1–4.5) Other musculoskeletal 3.1% (2.2–4.2) 8 Low back pain 2.9% (2.1–3.8) Low back pain 3.2% (2.3–4.2) Tuberculosis 2.9% (1.9–4) 9 Natural disaster 2.3% (0.9–3.7) Maternal hypertension 2.7% (1.9–3.8) Maternal hemorrhage 2.6% (1.6–3.8) 10 Other maternal disorders 2.1% (1.3–3.1) Other musculoskeletal 2.7% (1.9–3.6) Maternal hypertension 2.4% (1.5–3.7) S90 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Table 4 continued Top ten causes of disability- adjusted life years (DALYs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 10–14 years 1 Iron-deficiency anemia 8.4% (6.5–10.6) Iron-deficiency anemia 9.5% (7.4–11.8) Iron-deficiency anemia 10.6% (8.4–13) 2 Natural disaster 5.8% (2.4–9.1) Natural disaster 8.9% (5–12.7) War and legal intervention 6.2% (2.9–9.5) 3 Drowning 4.9% (3.4–6.3) Conduct disorder 3.9% (2.4–5.8) Conduct disorder 4.4% (2.7–6.5) 4 Conduct disorder 3.3% (2–5) Other unintentional 3.6% (2.6–5) Other unintentional 4.0% (2.8–5.6) 5 Motor vehicle road inj. 3.0% (2.3–4) Drowning 3.3% (2.6–4.1) Asthma 3.3% (2.5–4.4) 6 Lower respiratory infect. 3.0% (2–4.1) Asthma 3.2% (2.4–4.1) Drowning 2.9% (2.3–3.8) 7 Asthma 3.0% (2.3–3.9) Motor vehicle road inj. 3.0% (2.4–3.7) Motor vehicle road inj. 2.8% (2.2–3.5) 8 Pedestrian road inj. 3.0% (2.2–3.9) Pedestrian road inj. 2.6% (2–3.2) Anxiety disorders 2.3% (1.6–3 2) 9 Other unintentional 2.8% (2.2–3.8) Lower respiratory infect. 2.2% (1.6–3) Lower respiratory infect. 2.3% (1.6–3.1) 10 Diarrheal diseases 2.6% (1.8–3.7) Typhoid fever 2.1% (1.1–3.6) Pedestrian road inj. 2.1% (1.6–2.8) 15–19 years 1 Natural disaster 6.0 % (2.5–9.3) Natural disaster 7.9% (4.4–11.3) War and legal intervention 17.9% (8.9–25.7) 2 Motor vehicle road inj. 5.3% (4–7.1) Motor vehicle road inj. 5.9% (4.8–7.5) Other unintentional 5.9% (3.9–8.3) 3 Other unintentional 4.0% (3–5.4) Other unintentional 5.6% (3.9–7.7) Motor vehicle road inj. 5.2% (4.1–6.6) 4 Drowning 4.0% (2.8–5.4) Pedestrian road inj. 3.2% (2.4–4.1) Major depressive disorder 2.7% (1.7–4.1) 5 Iron-deficiency anemia 3.3% (2.4–4.4) Drowning 3.1% (2.5–3.8) Iron-deficiency anemia 2.5% (1.7–3.5) 6 War and legal intervention 3.2% (1.5–6.2) Iron-deficiency anemia 2.8% (2–3.8) Drowning 2.5% (1.9–3.2) 7 Pedestrian road inj. 2.8% (1.7–3.7) Major depressive disorder 2.8% (1.7–4.2) Pedestrian road inj. 2.5% (1.8–3.3) 8 Major depressive disorder 2.7% (1.7–4.1) Low back pain 2.6% (1.9–3.5) Low back pain 2.4% (1.7–3.3) 9 Low back pain 2.6% (1.9–3.5) Motorcyclist road inj. 2.4% (1.7–3.3) Conduct disorder 2.3% (1.4–3.6) 10 Conduct disorder 2.3% (1.4–3.6) Conduct disorder 2.4% (1.4–3.7) Migraine 2.0% (1.2–3) 20–24 years 1 Moter vehicle road inj. 6.2% (4.9–8.1) Motor vehicle road inj. 7.1% (5.8–8.7) War and legal intervention 19.5% (10–27.7) 2 War and legal intervention 4.7% (2.3–8.7) Natural disaster 5.9% (3.3–8.5) Motor vehicle road inj. 5.9% (4.7–7.4) 3 Natural disaster 4.4% (1.8–7) Other unintentional 5.2% (3.7–7.3) Other unintentional 5.2% (3.4–7.4) 4 Other unintentional 4.0% (2.9–5.4) Pedestrian road inj. 3.6% (2.7–4.5) Pedestrian road inj. 2.8% (2.1–3.5) 5 Pedestrian road inj. 3.1% (1.9–4.2) War and legal intervention 3.4% (2–4.8) Major depressive disorder 2.7% (1.7–4.3) 6 Drowning 3.1% (2.1–4.2) Major depressive disorder 2.9% (1.8–4.7) Low back pain 2.5% (1.8–3.5) 7 Major depressive disorder 2.9% (1.8–4.5) Self-harm 2.9% (2.4–3.5) Self-harm 2.5% (2–3.2) Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S91 also the need for community-based interventions to address some of the sociocultural barriers that contribute to high unmet need for interventions relating to sexual and repro- ductive health (Patton et al. 2016). As over half of the region’s adolescents live in Pakistan, Iran, and Egypt (Table 1), a regional response must pri- oritize these three countries. This is challenging, however, given the different stages of development and the very different needs of adolescents across these countries. For example, the burden of disease experienced by adolescents in Egypt is predominantly caused by NCDs, which require interventions to address the burden of chronic illness and health risks such as tobacco smoking and obesity (Patton et al. 2016). In addition to NCDs, adolescents living in Iran are burdened by injury (particularly relating to transport injury) which requires a suite of inter-sectoral actions (WHO 2017a). Adolescents living in Pakistan experience a ’’multi-burden’’ profile of disease, with a large burden of communicable, nutritional, and reproductive poor health in addition to NCDs and injury. However, in countries such as Afghanistan, Somalia, and Sudan, adolescents represent almost a third of the country-level population and experi- ence a particularly large and complex burden of disease. It is, therefore, important not to neglect their health needs (or indeed other countries in the EMR). What this analysis highlights is that unintentional injury, mental health, sexual health, substance use, and self-harm are increasingly important health issues for adolescents in the EMR. While these are health issues common to adolescents globally (Patton et al. 2016), they have typically sat at the margins (if at all) of policy, program, and data collection in EMR, given religious and cultural sensitivities. These findings highlight the need to better align health actions, including data monitoring of sensitive health outcomes, including risks, in this region to these needs. Our analysis has important limitations. Firstly, there is considerable variation in the availability and quality of primary data for adolescent health. This includes paucity of data for some age groups (particularly 10- to 14-year olds), and for many health outcomes and risks of importance during these important developmental years (Mokdad et al. 2016b; Patton et al. 2012; The Global Burden of Disease Child and Adoelscent Health Collaboration 2017). Avail- ability of timely, quality data is likely to be particularly poor in settings of conflict and insecurity, which affects many countries in this region. The poor quality of primary data necessitated the use of modeled estimates, and some of these modeled estimates may have over- or under-esti- mated the true burden. For example, ischemic heart disease was found to be a leading cause of mortality amongst males aged 20–24 years, a cause of death more commonly asso- ciated with adulthood. Premature death due to Table 4 continued Top ten causes of disability- adjusted life years (DALYs) in females and males Males 1990 2005 2015 Rank Cause Proportion Cause Proportion Cause Proportion 8 Low back pain 2.8% (2–3.8) Opioid use disorders 2.8% (2.2–3.4) Opioid use disorders 2.5% (1.9–3.2) 9 Self-harm 2.6% (2.1–3.4) Low back pain 2.7% (1.9–3.7) Migraine 2.0% (1.3–3.1) 10 Tuberculosis 2.5% (1.6–3.9) Motorcyclist road inj. 2.6% (1.9–3.6) Motorcyclist road inj. 1.9% (1.3-2.6) Global burden of disease study 2015, Eastern Mediterranean Region, 1990–2015 Italic defines communicable, maternal, neonatal and nutritional diseases Bold defines non-communicable diseases Bold, italic defines injuries DALYs disability-adjusted life-years S92 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Sawyer, MD, Murdoch Childrens Research Institute, The University cardiovascular disease is possible during adolescence, of Melbourne, Parkville, Victoria, Australia. Charbel El Bcheraoui, particularly in the context of adolescent obesity which is PhD, Institute for Health Metrics and Evaluation, University of prevalent in EMR (Franks et al. 2010). This finding may Washington, Seattle, Washington, United States. Raghid Charara, also be an artifact of disease modeling, as ischemic heart MD, American University of Beirut, Beirut, Lebanon. Ibrahim Khalil, MD, Institute for Health Metrics and Evaluation, University of disease is the leading cause of mortality in the EMR, and Washington, Seattle, Washington, United States. Maziar Moradi- these deaths are modeled to have their onset after 0.1 years Lakeh, MD, Department of Community Medicine, Preventive Medi- of age (GBD 2015 Eastern Mediterranean Region Cardio- cine and Public Health Research Center, Gastrointestinal and Liver vascular Disease Collaborators and Mokda 2017; GBD Disease Research Center (GILDRC), Iran University of Medical Sciences, Tehran, Iran. Michael Collison, BS, Institute for Health 2015 Eastern Mediterranean Region Collaborators and Metrics and Evaluation, University of Washington, Seattle, Wash- Mokdad 2017; GBD Mortality and Causes of Death Col- ington, United States. Rima A. Afifi, PhD, American University of laborators 2016). The findings of this study should there- Beirut, Beirut, Lebanon. Jamela Al-Raiby, MD, World Health fore be interpreted as not only indicating priority areas to Organization. Kristopher J. Krohn, BA, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, address adolescent health in the EMR, but also where data United States. Farah Daoud, BA/BS, Institute for Health Metrics and collection efforts should focus. A further limitation is that Evaluation, University of Washington. Adrienne Chew, ND, Institute the broader impacts of armed conflict on adolescent health for Health Metrics and Evaluation, University of Washington, Seattle, and well-being, beyond mortality, are not captured by the Washington, United States. Ashkan Afshin, MD, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Wash- 2015 GBD study. These include participation in education ington, United States. Kyle J. Foreman, PhD, Institute for Health and employment, as well as the impacts of trauma on Metrics and Evaluation, University of Washington, Seattle, Wash- adolescent development and wellbeing. Additionally, some ington, United States; Imperial College London, London, United important health issues such as female genital cut- Kingdom. Nicholas J. Kassebaum, MD, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, ting/mutilation (common in countries such as Somalia) are United States; Department of Anesthesiology & Pain Medicine, not included in GBD 2015 (UNICEF 2016a). Seattle Children’s Hospital, Seattle, Washington, United States. There are several regional efforts that may facilitate Michael Kutz, BS, Institute for Health Metrics and Evaluation, addressing the needs of adolescents in the EMR. For University of Washington, Seattle, Washington, United States. Hmwe H. Kyu, PhD, Institute for Health Metrics and Evaluation, University example, a coalition of youth advocates for health in the of Washington, Seattle, Washington, United States. Patrick Liu, BA, EMR has been established (Alaovie et al. 2017). There is a Institute for Health Metrics and Evaluation, University of Washing- joint UN strategy for youth in the region (IATTTYP 2015). ton, Seattle, Washington, United States. Helen E. Olsen, MA, Institute UNICEF has also published guidance around good practice for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States. Alison Smith, BA, Institute for Health with adolescent and youth programming (UNICEF 2016b). Metrics and Evaluation, University of Washington, Seattle, Wash- This study compliments these efforts, and helps to inform ington, United States. Jeffrey D. Stanaway, PhD, Institute for Health some priority areas for health. For conflict-affected coun- Metrics and Evaluation, University of Washington, Seattle, Wash- tries, the focus must clearly be on the return of peace and ington, United States. Haidong Wang, PhD, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Wash- stability and the rebuilding of health, education, and social ington, United States. Johan Arnlo ¨ v, PhD, Department of Neurobi- systems. In doing so, it is important to design services that ology, Care Sciences and Society, Division of Family Medicine and meet the needs of adolescents. For countries not affected Primary Care, Karolinska Institutet, Stockholm, Sweden; School of by conflict, health actions include the need to re-orientate Health and Social Studies, Dalarna University, Falun, Sweden. Aliasghar Ahmad Kiadaliri, PhD, Department of Clinical Sciences health systems to focus on prevention and the growing Lund, Orthopedics, Clinical Epidemiology Unit, Lund University, burden of NCDs. This needs to extend to inter-sectoral Lund, Sweden. Khurshid Alam, PhD, Murdoch Childrens Research actions to address the broader determinants of NCDs and Institute, The University of Melbourne, Parkville, Victoria, Australia; injuries. Without urgent action, there is a risk that profiles The University of Melbourne, Melbourne, VIC, Australia; The University of Sydney, Sydney, NSW, Australia. Deena Alasfoor, of adolescent health will continue to deteriorate with MSc, Ministry of Health, Al Khuwair, Muscat, Oman. Raghib Ali consequences for future population health and wellbeing, MSc, University of Oxford, Oxford, United Kingdom. Reza Alizadeh- productivity, and ultimately the stability of civil society. Navaei, PhD, Gastrointestinal Cancer Research Center, Mazandaran University of Medical Sciences, Sari, Mazandaran, Iran. Rajaa Al- GBD 2015 Eastern Mediterranean Region Adolescent Health Raddadi, PhD, Joint Program of Family and Community Medicine, Collaborators: Ali H. Mokdad, PhD (corresponding author), Insti- Jeddah, Makkah, Saudi Arabia. Khalid A. Altirkawi, MD, King Saud tute for Health Metrics and Evaluation, University of Washington, University, Riyadh, Saudi Arabia. Nelson Alvis-Guzman, PhD, Seattle, Washington, United States. Peter Azzopardi, PhD, Burnet Universidad de Cartagena, Cartagena de Indias, Colombia. Nahla Institute, Melbourne, VIC, Australia; Murdoch Children’s Research Anber, PhD, Mansoura University, Mansoura, Egypt. Carl Abelardo Institute, Melbourne, Victoria, Australia; Wardliparingga Aboriginal T. Antonio, MD, Department of Health Policy and Administration, Research Unit, South Australian Health and Medical Research Insti- College of Public Health, University of the Philippines Manila, tute (SAHMRI), Adelaide, South Australia, Australia. Karly Cini, Manila, Philippines. Palwasha Anwari, MD, Self-employed, Kabul, MClinEpi, Centre for Adolescent Health, Murdoch Childrens Afghanistan. Al Artaman, PhD, University of Manitoba, Winnipeg, Research Institute, Melbourne, Victoria, Australia. Elissa Kennedy, Manitoba, Canada. Hamid Asayesh, PhD, Department of Medical MBBS, MPH, Burnet Institute, Melbourne, VIC, Australia. Susan Emergency, School of Paramedic, Qom University of Medical 123 Adolescent health in the Eastern Mediterranean Region: findings from the global burden of… S93 Sciences, Qom, Iran. Suzanne L. Barker-Collo, PhD, School of Psy- DM, International Foundation for Dermatology, London, United chology, University of Auckland, Auckland, New Zealand. Neeraj Kingdom; King’s College London, London, United Kingdom. Ste- Bedi, MD, College of Public Health and Tropical Medicine, Jazan, phen J. C. Hearps, PGDipBiostat, Child Neuropsychology, Murdoch Saudi Arabia. Ettore Beghi, MD, IRCCS - Istituto di Ricerche Far- Childrens Research Hospital, Parkville, VIC, Australia. Delia Hen- macologiche Mario Negri, Milan, Italy. Derrick A. Bennett, PhD, drie, MA, Centre for Population Health Research, Curtin University, Nuffield Department of Population Health, University of Oxford, Bentley, WA, Australia. Peter J. Hotez, PhD, College of Medicine, Oxford, United Kingdom. Isabela M. Bensenor, PhD, University of Baylor University, Houston, Texas, United States. Guoqing Hu, PhD, Sa ˜o Paulo, Sa ˜o Paulo, Brazil. Zulfiqar A. Bhutta, PhD, Centre of Department of Epidemiology and Health Statistics, School of Public Excellence in Women and Child Health, Aga Khan University, Health, Central South University, Changsha, Hunan, China. Jost B. Karachi, Pakistan; Centre for Global Child Health, The Hospital for Jonas, MD, Department of Ophthalmology, Medical Faculty Man- Sick Children, Toronto, ON, Canada. Zahid A. Butt, PhD, Al Shifa nheim, Ruprecht-Karls-University Heidelberg, Mannheim, Germany. Trust Eye Hospital, Rawalpindi, Pakistan. Carlos A. Castan ˜ eda-Or- Andre ´ Karch, MD, Epidemiological and Statistical Methods Research juela, MSc, Colombian National Health Observatory, Instituto Group, Helmholtz Centre for Infection Research, Braunschweig, Nacional de Salud, Bogota, DC, Colombia; Epidemiology and Public Germany; Hannover-Braunschweig Site, German Center for Infection Health Evaluation Group, Public Health Department, Universidad Research, Braunschweig, Germany. Seyed M. Karimi, PhD, Univer- Nacional de Colombia, Bogota, Colombia. Ferra ´n Catala ´-Lo ´ pez, PhD, sity of Washington Tacoma, Tacoma, WA, United States. Amir Department of Medicine, University of Valencia/INCLIVA Health Kasaeian, PhD, Hematology-Oncology and Stem Cell Transplantation Research Institute and CIBERSAM, Valencia, Spain; Clinical Epi- Research Center, Tehran University of Medical Sciences, Tehran, demiology Program, Ottawa Hospital Research Institute, Ottawa, Iran; Endocrinology and Metabolism Population Sciences Institute, Canada. Fiona J. Charlson, PhD, School of Public Health, University Tehran University of Medical Sciences, Tehran, Iran. Seifu Kebede, of Queensland, Brisbane, Queensland, Australia; Institute for Health MS, Mekelle University, Mekele, Ethiopia. Andre Pascal Kengne, Metrics and Evaluation, University of Washington, Seattle, Wash- PhD, South African Medical Research Council, Cape Town, South ington, United States; Queensland Centre for Mental Health Research, Africa; University of Cape Town, Cape Town, South Africa. Ejaz Brisbane, Queensland, Australia. Hadi Danawi, PhD, Walden Ahmad Khan, MD, Health Services Academy, Islamabad, Pakistan. University, Minneapolis, Minnesota, United States. Diego De Leo, Ardeshir Khosravi, PhD, Iranian Ministry of Health and Medical DSc, Griffith University, Brisbane, Queensland, Australia. Louisa Education, Tehran, Iran; Non-communicable Diseases Research Degenhardt, PhD, National Drug and Alcohol Research Centre, Center, Tehran University of Medical Sciences, Tehran, Iran. Jagdish University of New South Wales, Sydney, Australia. Donna Denno, Khubchandani, PhD, Department of Nutrition and Health Science, MD, Department of Pediatrics, University of Washington, Seattle, Ball State University, Muncie, Indiana, United States. Yoshihiro Washington, United States; Department of Global Health, University Kokubo, PhD, Department of Preventive Cardiology, National of Washington, Seattle, Washington. Kebede Deribe, MPH, Brighton Cerebral and Cardiovascular Center, Suita, Japan. Jacek A. Kopec, and Sussex Medical School, Brighton, United Kingdom; School of PhD, University of British Columbia, Vancouver, BC, Canada. Soe- Public Health, Addis Ababa University, Addis Ababa, Ethiopia. Don warta Kosen, MD, Center for Community Empowerment, Health C. Des Jarlais, PhD, Mount Sinai Beth Israel, New York, New York, Policy and Humanities, National Institute of Health Research & United States; Icahn School of Medicine at Mount Sinai, New York Development, Jakarta, Daerah Khusus Ibukota (DKI) Jakarta, City, New York, United States. Subhojit Dey, PhD, Indian Institute of Indonesia. Heidi J. Larson, PhD, Department of Infectious Disease Public Health-Delhi, Public Health Foundation of India, Gurgaon, Epidemiology, London School of Hygiene & Tropical Medicine, India. Samath D. Dharmaratne, MD, Department of Community London, United Kingdom; Institute for Health Metrics and Evalua- Medicine, Faculty of Medicine, University of Peradeniya, Peradeniya, tion, University of Washington, Seattle, Washington, United States. Sri Lanka. Shirin Djalalinia, PhD, Undersecretary for Research & Anders Larsson, PhD, Department of Medical Sciences, Uppsala Technology, Ministry of Health & Medical Education, Tehran, Iran. University, Uppsala, Sweden. Janet L. Leasher, OD, College of Holly E. Erskine, PhD, Queensland Centre for Mental Health Optometry, Nova Southeastern University, Fort Lauderdale, Florida, Research, Brisbane, QLD, Australia; School of Public Health, United States. Janni Leung, PhD, School of Public Health, University University of Queensland, Brisbane, QLD, Australia; Institute for of Queensland, Brisbane, QLD, Australia; University of Washington, Health Metrics and Evaluation, University of Washington, Seattle, Seattle, Washington, United States. Yongmei Li, PhD, San Francisco Washington, United States. Seyed-Mohammad Fereshtehnejad, PhD, VA Medical Center, San Francisco, California, United States. Paulo Department of Neurobiology, Care Sciences and Society (NVS), A. Lotufo, DrPH, University of Sa ˜o Paulo, Sa ˜o Paulo, Brazil. Rai- Karolinska Institutet, Stockholm, Sweden. Alize J. Ferrari, PhD, mundas Lunevicius, PhD, Aintree University Hospital National School of Public Health, University of Queensland, Brisbane, Health Service Foundation Trust, Liverpool, United Kingdom; School Queensland, Australia; Queensland Centre for Mental Health of Medicine, University of Liverpool, Liverpool, United Kingdom. Research, Brisbane, Queensland, Australia; Institute for Health Met- Hassan Magdy Abd El Razek, MBBCH, Mansoura Faculty of Med- rics and Evaluation, University of Washington, Seattle, Washington, icine, Mansoura, Egypt. Reza Majdzadeh, PhD, Knowledge Utiliza- United States. Florian Fischer, PhD, School of Public Health, Biele- tion Research Center and Community Based Participatory Research feld University, Bielefeld, Germany. Tsegaye Tewelde Gebrehiwot, Center, Tehran University of Medical Sciences, Tehran, Iran. Azeem MPH, Jimma University, Jimma, Ethiopia. Johanna M. Geleijnse, Majeed, MD, Department of Primary Care & Public Health, Imperial PhD, Division of Human Nutrition, Wageningen University, College London, London, England, United Kingdom. Peter Memiah, Wageningen, Netherlands. Philimon N. Gona, PhD, University of PhD, University of West Florida, Pensacola, FL, United States. Ziad Massachusetts Boston, Boston, Massachusetts, United States. Harish A. Memish, MD, Saudi Ministry of Health, Riyadh, Saudi Arabia; Chander Gugnani, PhD, Departments of Microbiology and Epidemi- College of Medicine, Alfaisal University, Riyadh, Saudi Arabia. ology & Biostatistics, Saint James School of Medicine, The Quarter, Walter Mendoza, MD, United Nations Population Fund, Lima, Peru. Anguilla. Rajeev Gupta, PhD, Eternal Heart Care Centre and Francis Apolinary Mhimbira, MS, Ifakara Health Institute, Bag- Research Institute, Jaipur, Rajasthan, India. Randah Ribhi Hamadeh, amoyo, Tanzania. Ted R. Miller, PhD, Pacific Institute for Research DPhil, Arabian Gulf University, Manama, Bahrain. Samer Hamidi, & Evaluation, Calverton, MD, United States; Centre for Population DrPH, Hamdan Bin Mohammed Smart University, Dubai, United Health, Curtin University, Perth, WA, Australia. Philip B. Mitchell, Arab Emirates. Josep Maria Haro, MD, Parc Sanitari Sant Joan de MD, University of New South Wales, Kensington, New South Wales, De ´u - CIBERSAM, Sant Boi de Llobregat, Spain. Roderick J. Hay, Australia. Lorenzo Monasta, DSc, Institute for Maternal and Child 123 S94 GBD 2015 Eastern Mediterranean Region Adolescent Health Collaborators Health, IRCCS ‘‘Burlo Garofolo’’, Trieste, Italy. Carla Makhlouf of Nursing and Public Health, University of KwaZulu-Natal, Durban, Obermeyer, DSc, Center for Research on Population and Health, South Africa; UKZN Gastrointestinal Cancer Research Centre, South Faculty of Health Sciences, American University of Beirut, Beirut, African Medical Research Council (SAMRC), Durban, South Africa. Lebanon. In-Hwan Oh, PhD, Department of Preventive Medicine, David C. Schwebel, PhD, University of Alabama at Birmingham, School of Medicine, Kyung Hee University, Seoul, South Korea. Birmingham, Alabama, United States. Soraya Seedat, PhD, Stellen- Bolajoko Olubukunola Olusanya, PhD, Center for Healthy Start Ini- bosch University, Cape Town, South Africa. Sadaf G. Sepanlou, PhD, tiative, Lagos, Lagos, Nigeria. Alberto Ortiz PhD, IIS-Fundacion Digestive Diseases Research Institute, Tehran University of Medical Jimenez Diaz-UAM, Madrid, Spain. Eun-Kee Park, PhD, Department Sciences, Tehran, Iran. Tesfaye Setegn, MPH, Bahir Dar University, of Medical Humanities and Social Medicine, College of Medicine, Bahir Dar, Ethiopia. Amira Shaheen, PhD, Department of Public Kosin University, Busan, South Korea. Matti Parry, MD, Reproduc- Health, An-Najah University, Nablus, Palestine. Masood Ali Shaikh, tive Health and Reseearch/Adolescents and at-risk populations (RHR/ MD, Independent Consultant, Karachi, Pakistan. Rahman Shiri, PhD, AGH), World Health Organization, Geneva, Switzerland. David M. Finnish Institute of Occupational Health, Work Organizations, Work Pereira, PhD, REQUIMTE/LAQV, Laborato ´ rio de Farmacognosia, Disability Program, Department of Public Health, Faculty of Medi- Departamento de Quı ´mica, Faculdade de Farma ´cia, Universidade do cine, University of Helsinki, Helsinki, Finland. Inga Dora Sigfus- Porto, Porto, Portugal. Michael Robert Phillips, MD, Shanghai Jiao dottir, PhD, Reykjavik University, Reykjavik, Iceland. Jasvinder A. 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International Journal of Public HealthSpringer Journals

Published: Aug 3, 2017

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