Burden of cardiovascular diseases in the Eastern Mediterranean Region, 1990–2015: findings from the Global Burden of Disease 2015 study

Burden of cardiovascular diseases in the Eastern Mediterranean Region, 1990–2015: findings from... Int J Public Health (2018) 63 (Suppl 1):S137–S149 https://doi.org/10.1007/s00038-017-1012-3 O R I G IN AL ARTI CL E Burden of cardiovascular diseases in the Eastern Mediterranean Region, 1990–2015: findings from the Global Burden of Disease 2015 study GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Received: 1 May 2017 / Revised: 20 June 2017 / Accepted: 28 June 2017 / Published online: 3 August 2017 The Author(s) 2017. This article is an open access publication Abstract and high body mass index were the leading risk factors for Objectives To report the burden of cardiovascular diseases CVD. (CVD) in the Eastern Mediterranean Region (EMR) during Conclusions The age-standardized DALY rates in the 1990–2015. EMR are considerably higher than the global average. Methods We used the 2015 Global Burden of Disease study These findings call for a comprehensive approach to pre- for estimates of mortality and disability-adjusted life years vent and control the burden of CVD in the region. (DALYs) of different CVD in 22 countries of EMR. Results A total of 1.4 million CVD deaths (95% UI: Keywords Cardiovascular disease  Burden of disease 1.3–1.5) occurred in 2015 in the EMR, with the highest Eastern Mediterranean Region number of deaths in Pakistan (465,116) and the lowest number of deaths in Qatar (723). The age-standardized DALY rate per 100,000 decreased from 10,080 in Introduction 1990 to 8606 in 2015 (14.6% decrease). Afghanistan had the highest age-standardized DALY rate of CVD in both The Global Burden of Disease (GBD) study documented that 1990 and 2015. Kuwait and Qatar had the lowest age-s- cardiovascular diseases (CVD) have been the leading cause of tandardized DALY rates of CVD in 1990 and 2015, global mortality since 1980 (Institute for Health Metrics and respectively. High blood pressure, high total cholesterol, Evaluation 2017; Mortality and Causes of Death 2016). CVD accounted for nearly one-third of all deaths worldwide in 2015. Meanwhile, the principal components of CVD, namely stroke and ischemic heart disease, accounted for 85.1% (95% This article is part of the supplement ‘‘The state of health in the uncertainty interval (UI): 84.7–85.5) of all deaths in the CVD Eastern Mediterranean Region, 1990–2015’’. category in 2015 (Mortality and Causes of Death 2016). Although the age-standardized mortality rates of CVD The members of GBD (Global Burden of Disease) 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators are have fallen by 27.3% in the last 25 years, the absolute number listed at the end of the article. Ali H. Mokdad, on behalf of GBD 2015 of deaths due to CVD increased globally by 42.4% between Eastern Mediterranean Region Cardiovascular Disease Collaborators, 1990 and 2015 (2017). Most CVD deaths occur in low- and is the corresponding author. middle-income countries (Mensah et al. 2015). The decline in Electronic supplementary material The online version of this age-standardized rates is mainly due to preventive interven- article (doi:10.1007/s00038-017-1012-3) contains supplementary tions and better access to quality treatment for acute cardio- material, which is available to authorized users. vascular conditions such as myocardial infarction and stroke & GBD 2015 Eastern Mediterranean Region Cardiovascular (Smith 2011). CVD also impose a high economic burden on Disease Collaborators health systems and society. For instance, CVD personal mokdaa@uw.edu spending in the United States was estimated to be 231.1 billion USD in 2013 and was the largest disease category of personal Institute for Health Metrics and Evaluation, University of health care spending (Dieleman et al. 2016). Washington, Seattle, WA, USA 123 S138 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators The Eastern Mediterranean Region (EMR) comprises 22 life tables for all-cause mortality were used to calculate countries with a population of nearly 580 million people, years of life lost (YLLs) (GBD 2015 Morality and Causes with a diverse range in per capita gross national product of Death Collaborators 2016; Roth et al. 2015a, b). (maximum 83,990 USD for Qatar, minimum 610 USD for We updated our previous systematic reviews for the Afghanistan) (World Development Indicators database GBD study separately for each of the non-fatal sequelae of 2017). To the best of our knowledge, there is no compre- CVD. Data on epidemiologic measures (incidence, preva- hensive report on the burden and mortality of CVD in the lence, and case fatality) were extracted from 170 data EMR. sources. List of all sources (by cause and location) are This study aimed to report findings on cardiovascular available at the Institute for Health Metrics and Evalua- diseases between 1990 and 2015, from the Global Burden tion’s website (IHME 2016). of Diseases, Injuries and Risk Factors Study (GBD 2015) Bayesian meta-regression analysis through DisMod-MR in the 22 countries of the EMR. This would be help us 2.1 was used for disease modeling. Model-based preva- better understand the burden of CVD and interventions lence estimates, in combination with disability weights, needed to control these diseases. were used to calculate cause-specific years lived with dis- ability (YLDs) for each age, sex, location, and year. Dis- ability-adjusted life years (DALYs) were calculated Methods through summation of YLLs and YLDs (DALYs and Collaborators 2016; Disease et al. 2016). GBD 2015 covers 195 countries, 21 regions, and seven We report 95% uncertainty intervals (UI) for each super-regions from 1990 to 2015 for 315 diseases and estimate, including rates, numbers of deaths, and DALYs. injuries, 2619 unique sequelae, and 79 risk factors by age We estimated UIs by taking 1000 samples from the pos- and sex. Detailed descriptions of the general methodolog- terior distribution of each quantity and using the 25th- and ical approach of GBD 2015 and specific methodology used 975th-ordered draws of the uncertainty distribution. for CVD have been provided elsewhere (GBD 2015 DALYs and Collaborators 2016; GBD 2015 Disease and Injury Prevalence Collaborators 2016; GBD 2015 Mortal- Results ity and Causes of Death Collaborators 2016). We evaluated the burden of CVD in the Eastern Mortality Mediterranean Region (EMR), which contains 22 coun- tries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, The CVD death rate per 100,000 population in the EMR Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pak- decreased from 515.1 (95% UI: 491.7–541.5) in 1990 to istan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, 456.5 (95% UI: 431.5–484.2) in 2015 (Table 1). A total of Syria, Tunisia, the United Arab Emirates (UAE), and 1,373,329 CVD deaths (95% UI: 1,290,959–1,465,047) Yemen. occurred in 2015 in the EMR, 54.8% of which were among The category of CVD includes the ten most common males. These deaths accounted for 34.1% (95% UI: global causes of CVD-related death: rheumatic heart dis- 33.1–35.1) of all deaths in the region in 2015, compared to ease, ischemic heart disease, cerebrovascular disease (is- 30.2% (95% UI: 29.5–30.9) of all deaths in 1990. The chemic stroke and hemorrhagic stroke), hypertensive heart number of men dying from CVD was consistently higher disease, cardiomyopathy and myocarditis, atrial fibrillation than the number of women during 1990–2015 (Fig. 1). and flutter, aortic aneurysm, peripheral vascular disease, The total number of deaths from ischemic heart disease endocarditis, and ‘‘other cardiovascular and circulatory (IHD) was 802,078 in 2015, which accounted for 58.4% of diseases.’’ Electronic supplementary table S1 shows the the total number of deaths due to CVD in the EMR. There International Classification of Diseases (ICD-10) codes for were 637,640 additional deaths in 2015 compared to 1990, each of the cardiovascular causes. out of which 62.5% was contributed by IHD. To estimate the number of deaths due to CVD, we Table 2 provides the total number of deaths and the age- estimated all-cause mortality envelopes (total number of standardized death rates from CVD in 1990 and 2015 for deaths) for each country-year during 1990–2015; we used all EMR countries. In 2015, Afghanistan had the highest all accessible data such as vital registration systems, sam- age-standardized death rate from CVD, followed by Iraq ple registration data, and household recall of deaths. These and Yemen. In most of the EMR countries, age-standard- sources were used as inputs for cause of death models. We ized death rates for CVD decreased between 1990 and used cause of death ensemble modeling (CODEm) to 2015, with the highest decreases in Bahrain, Qatar, Leba- estimate the number of deaths for each CVD by age, sex, non, and Jordan. country, and year. The number of deaths for each cause and 123 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S139 Table 1 Total number of deaths and age-standardized mortality rates for cardiovascular diseases in 1990 and 2015, and percentage change, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 Cause Number of deaths Age-standardized death rate per 100,000 1990 2015 % Change 1990 2105 % Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI Cardiovascular diseases 735,689 700,875–773,593 1,373,329 1,290,959–1,465,047 86.7 515.1 491.7–541.5 456.5 431.5–484.2 -11.4 Rheumatic heart disease 18,350 16,029–21,037 27,046 22,945–31,078 47.4 9.1 7.8–10.7 6.8 5.7–7.8 -25.5 Ischemic heart disease 403,355 379,184–425,913 802,078 750,839–859,266 98.9 294.0 276.9–310.3 269.1 252.5–286.9 -8.5 Ischemic stroke 92,230 79,786–106,780 174,760 158,325–190,197 89.5 75.5 65.5–87.8 65.6 59.7–71.2 -13.1 Hemorrhagic stroke 117,813 105,731–133,751 200,113 182,283–230,479 69.9 71.5 61–82.5 60.6 55.4–69.6 -15.3 Hypertensive heart disease 36,179 30,771–46,101 62,663 55,680–71,029 73.2 27.0 22.7–35.2 21.4 19–24.1 -20.7 Cardiomyopathy and myocarditis 18,025 15,031–20,571 27,128 24,612–29,553 50.5 8.7 7.2–10 7.3 6.5–7.9 -16.6 Atrial fibrillation and flutter 3513 2654–4487 7535 5707–9666 114.5 3.9 2.9–5.1 3.5 2.6–4.5 -11.0 Aortic aneurysm 2694 2163–3414 6941 6291–7580 157.6 2.0 1.6–2.5 2.3 2.1–2.5 14.9 Peripheral artery disease 114 68–151 424 365–508 272.4 0.1 0.1–0.1 0.2 0.1–0.2 65.9 Endocarditis 5172 4167–7067 9016 7833–12,719 74.3 2.9 2.3–4.2 2.6 2.3–3.9 -8.3 Other cardiovascular and circulatory diseases 38,243 34,519–42,477 55,625 51,621–60,292 45.5 20.3 18.5–22.2 17.1 15.9–18.6 -15.7 S140 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Fig. 1 Trend of number of 800000 deaths and age-standardized mortality rate from cardiovascular diseases in males and females, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 300000 0 1990 1995 2000 2005 2010 2015 Male Female Male (rate) Female (rate) Electronic supplementary figure S1 shows the top- per 100,000 in 2015. Age-standardized YLD rates of CVD ranked death rates for different CVD in EMR countries. decreased between 1990 and 2015 in six countries of the Ischemic heart disease was the leading cause of CVD region: Iran, United Arab Emirates, Jordan, Djibouti, mortality in 20 countries of the EMR; the exceptions were Somalia, and Afghanistan. The biggest decline was seen in Djibouti and Somalia, where cerebrovascular disease (both Iran (4.6%), and the smallest reduction was in Afghanistan hemorrhagic and ischemic stroke) was the leading cause of (0.5%). Among the remaining 16 countries of the region cardiovascular-related death. that showed increases in age-standardized YLD rates of CVD, Syria’s was the greatest, at 9.1%. YLLs DALYs The age-standardized YLL rate decreased 15.3%, from 9618.7 (9148.6–10,141.7) per 100,000 in 1990–8145.0 The rate of DALYs from CVD per 100,000 population (7628.6–8744.3) per 100,000 in 2015 (Electronic supple- decreased from 5447.8 (95% UI: 5168.2–5739.0) in mentary table S2). In the region, Afghanistan had the 1990–5109.8 (95% UI: 4771.3–5511.1) in 2015, a 6.2% highest age-standardized YLL rate at 21,426.2 decrease—compared to an 8.4% reduction in the DALY (17,105.2–26,544.7), followed by Yemen and Iraq (Elec- rate for all other non-communicable diseases in the EMR. tronic supplementary table S2). In all countries of the EMR The age-standardized DALY rate also decreased 14.6% except Pakistan, age-standardized YLL rates decreased during 1990–2015 (Table 3). Table 3 reports numbers and from 1990 to 2015 (Electronic supplementary table S2). age-standardized rates of DALYs for different CVD in the EMR in 1990 and 2015. The age-standardized DALY rate YLDs of CVD for men and women in the EMR in 2015 was higher than in other WHO regions. It was 1.51 times the The years lived with disability caused by CVD in the EMR global rate for males and 1.86 times the global rate for increased from 1,058,839 (95% UI: 746,613–1409,913) in females. Electronic supplementary figure S2 shows the 1990 to 1,966,111 (95% UI: 1398,373–2597,819) in 2015. age-standardized rates of DALYs for different CVD in men The rate of YLD increased by 85.7% during 1990–2015 in and women. As shown, ischemic heart disease caused the the EMR. highest number of DALYs both in men (5771.9 per The age-standardized YLD rate in the EMR was 460.6 100,000) and women (3931.2 per 100,000), followed by (329.2–603.6) per 100,000 in 2015, which showed very hemorrhagic stroke and ischemic stroke. little decrease compared to 1990 (461.1 per 100,000) Electronic supplementary figure S3 shows DALY rates (Electronic supplementary table S2). Oman had the highest for each CVD in different age groups. As shown, the age-standardized YLD rate in the region in both 1990 and highest DALY rates for IHD, hemorrhagic stroke, ischemic 2015: it was 1261 (874.6–1722.1) per 100,000 in 2015, stroke, and hypertensive heart disease were observed in which was about 2.7 times higher than the regional aver- people aged 50–69 years. IHD, hemorrhagic stroke, and age. United Arab Emirates had the lowest age-standardized rheumatic heart disease showed the highest number of YLD rate in the EMR, 296.8 per 100,000 in 1990 and 285.8 DALYs in the 15–49 years age group. Number Rate per 100,000 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S141 Table 2 Total number of deaths and age-standardized mortality rates for cardiovascular disease causes of death in 1990 and 2015, and percent change, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 Country Number of deaths Age-standardized death rate per 100,000 1990 2015 % Change 1990 2015 % Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI EMR 735,689 700,875–773,593 1,373,329 1,290,959–1,465,047 86.7 515.1 491.7–541.5 456.5 431.5–484.2 -11.4 Afghanistan 34,755 27,217–42,776 10,1572 81,113–125,962 192.2 1048.1 860.6–1235.4 1042.5 865–1227.9 -0.5 Bahrain 614 547–681 792 671–933 29.0 414.1 371.4–456.9 186.1 162.1–210.2 -55.1 Djibouti 683 434–1025 1402 762–-2395 105.3 393.4 265.8–568.8 360.9 212.6–590.1 -8.3 Egypt 153,214 147,677–157,026 226,457 219,738–234,235 47.8 544.9 530.1–556.7 465.2 451.7–479.2 -14.6 Iran 96,775 86,347–107,587 176,299 148,576–203,480 82.2 499.2 451.4–547.5 402.2 344–456.9 -19.4 Iraq 44,476 38,326–51,342 75,604 61,673–91,552 70.0 657.6 569.1–755.1 604.4 503.7–715.3 -8.1 Jordan 4869 4319–5684 6788 6108–7611 39.4 416.0 370.2–481.4 236.9 214.1–264.4 -43.1 Kuwait 1262 1192–1324 2367 2040–2747 87.6 258.5 245–271.3 209.7 185–237 -18.9 Lebanon 7397 6206–8674 11,632 8967–14,195 57.3 464.2 391.3–540.9 252.1 196–305.1 -45.7 Libya 4864 4354–5397 9301 8130–10,535 91.2 310.3 276.6–344 299.7 263.3–339.3 -3.4 Morocco 36,293 32,487–40,581 59,824 47,641–75,972 64.8 362.1 327.5–400.4 268.3 216.5–336.6 -25.9 Oman 2108 1688–2552 4000 3336–4583 89.7 378.8 300.7–461.2 300.3 255.4–336.8 -20.7 Pakistan 216,936 191,002–247,476 465,116 407,279–528,666 114.4 513.1 454.9–578 530.9 469–599.1 3.5 Palestine 2333 1902–2925 5805 4683–6954 148.8 443.1 366.5–542 394.9 326.3–462.4 -10.9 Qatar 338 297–383 723 568–924 114.3 342.4 303.1–380.4 180.6 149.6–221.8 -47.3 Saudi Arabia 13,222 11,931–14,651 25,845 23,532–28,503 95.5 288.0 260.4–317.9 231.6 213.2–-253.4 -19.6 Somalia 11,706 3957–22,825 15,080 5270–31,505 28.8 508.9 192.7–890.2 439.7 172.6–813.3 -13.6 Sudan 42,922 35,852–51,825 74,648 56,697–97,015 73.9 611.3 512.7–738.5 501.9 388.7–634.1 -17.9 Syria 23,049 20,307–26,719 33,044 28,488–36,934 43.4 554.8 494.8–634.9 401.0 348.7–446.9 -27.7 Tunisia 10,747 9970–11,633 18,423 14,973–21,952 71.4 285.3 263.3–308.9 204.0 166.5–242.6 -28.5 UAE 1641 1260–2230 8563 6337–11,314 421.9 406.5 327.3–501.8 333.4 279.6–403.7 -18.0 Yemen 25,485 16,534–36,647 50,043 30,637–78,838 96.4 700.0 461.6–991.9 592.1 383–888.5 -15.4 S142 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Table 3 Total disability-adjusted life years (DALY) and age-standardized disability-adjusted life years rates for component cardiovascular causes of death in 1990 and 2015, and percent change, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 Cause Number of DALYs Age-standardized DALY rate per 100,000 1990 2015 % 1990 2015 % Change Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI Cardiovascular diseases 20,164,206 19,129,504–21,242,151 33,131,948 30,937,166–35,734,353 64.3 10,079.8 9594.7–10,603.6 8605.6 8074.6–9219.3 -14.6 Rheumatic heart disease 876,838 770,813–986,361 1153,351 993,217–1333,219 31.5 302.1 265.1–344.5 215.8 185.2–248.4 -28.5 Ischemic heart disease 9323,188 8770,306–9877,741 17,827,201 16,511,324–19,368,534 91.2 5370.1 5052.6–5672.7 4865.0 4533.1–5231.4 -9.4 Ischemic stroke 1879,679 1649,862–2128,711 3272,789 2963,211–3568,718 74.1 1183.5 1031.4–1361 997.6 903.8–1085.4 -15.7 Hemorrhagic stroke 3941,327 3658,523–4323,670 5565,221 5091,084–6337,446 41.2 1649.0 1485.2–1870.5 1303.2 1193.9–1493 -21.0 Hypertensive heart disease 822,728 711,712–1011,157 1366,662 1201,763–1571,258 66.1 479.4 411.3–603 371.0 328.2–422.5 -22.6 Cardiomyopathy and 833,292 693,153–982,453 1001,334 891,780–1097,777 20.2 247.2 206.1–281.7 188.0 170.3–204.4 -24.0 myocarditis Atrial fibrillation and flutter 77,777 61,867–94,926 161,328 129,867–199,493 107.4 63.3 51.4–77 58.2 47–71 -8.0 Aortic aneurysm 63,221 50,928–80,451 163,304 146,635–180,105 158.3 35.4 28.5–45 41.6 37.6–45.6 17.6 Peripheral artery disease 13,954 7359–24,367 32,852 18,777–56,064 135.4 10.1 5.3–17.9 11.2 6.4–19.3 11.3 Endocarditis 217,347 160,723–291,718 292,842 248,013–378,079 34.7 68.4 55–92.5 58.5 50.9–80.3 -14.4 Other CVD 2114,855 1844,679–2463,667 2295,064 2018,478–2613,017 8.5 671.3 599.3–755.3 495.4 440.4–555.8 -26.2 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S143 Table 4 Total number of disability-adjusted life years and age-standardized disability-adjusted life years rates for cardiovascular diseases in 1990 and 2015, and percent change, 1990–2015, in Eastern Mediterranean Region countries Country Number of DALYs Age-standardized DALY rate per 100,000 1990 2015 % Change 1990 2015 % Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI EMR 20,164,206 19,129,504–21,242,151 33,131,948 30,937,166–35,734,353 64.3 10,079.8 9594.7–10,603.6 8605.6 8074.6–9219.3 -14.6 Afghanistan 1,019,023 7,93,590–1,278,676 2,865,062 2,239,466–3,635,800 181.2 22,258.2 17,615.6–27,186.7 21,864.3 17,591.4–27,024.5 -1.8 Bahrain 18,578 16,524–20,639 23,376 19,748–27,808 25.8 8086.5 7206.4–8964 3281.4 2832.6–3769.2 -59.4 Djibouti 19,979 13,027–-29,586 35,930 19,430–64,153 79.8 7891.5 5171.4–11,605.5 7112.8 4021.2–12,056.6 -9.9 Egypt 4,373,017 4,109,349–4,595,897 5,436,416 5,216,937–5,700,475 24.3 11,230.6 10,762.9–11,583.1 8826.2 8508.6–9171.3 -21.4 Iran 2,941,466 2,601,284–3,291,417 3,875,985 3,249,465-4,577,119 31.8 9849.9 8776.8–10,950.2 7179.6 6090.9–8340.9 -27.1 Iraq 1,070,614 917,957–1248,583 1,875,448 1,489,313–2,315,419 75.2 12,513.4 10,678.3–14,669.9 11,244.0 9089.6–13,679.3 -10.1 Jordan 109,195 95,903–127,032 154,251 137,970–172,312 41.3 7692.8 6771.4–8983.8 4077.5 3666.1–4533 -47.0 Kuwait 40,918 38,315–43,123 75,385 65,509–87,507 84.2 4818.8 4558.7–5066.9 3884.1 3424.2–4417.1 -19.4 Lebanon 167,913 140,761–199,069 211,244 159,897–264,585 25.8 8792.7 7390.6–10,364.6 4213.8 3210.3–5249.2 -52.1 Libya 176,223 154,977–198,183 234,502 205,521–265,135 33.1 6384.4 5714.7–7050.6 5638.4 4957.2–6367.8 -11.7 Morocco 1,103,861 980,405–1,235,540 1,332,750 1,078,637–1,670,227 20.7 7222.4 6511.3–8059.2 4977.5 4039.5–6209.9 -31.1 Oman 93,965 76,349–115,695 135,300 114,087–155,337 44.0 8404.3 6832–10,016.2 5962.4 5071–6713.2 -29.1 Pakistan 5,069,303 4,422,395–5,880,731 10,719,663 9,250,078–12,360,492 111.5 9446.3 8281–10,798.4 9928.0 8664.3–11,288.5 5.1 Palestine 68,438 55,953–85,314 150,510 120,084–183,652 119.9 8263.4 6749.8–10,377.3 7280.6 5868.1–8727.7 -11.9 Qatar 10,556 9283–12,017 24,791 19,932–30,601 134.8 5873.6 5192.9–6542.3 3013.6 2466.4–3730 -48.7 Saudi Arabia 359,601 320,837–401,588 663,879 600,438–732,764 84.6 5285.0 4727.5–5861.6 4003.3 3650.2–4393.1 -24.3 Somalia 329,146 120,719–676,354 410,106 151,542–920,717 24.6 10,762.8 3851–21,078.4 9062.4 3379.7–18,999.5 -15.8 Sudan 1,359,599 1,129,865–1,596,275 2,047,475 1,542,545–2,657,659 50.6 12,814.4 10,687.4–15,522.9 9823.7 7427.1–12,742.4 -23.3 Syria 668,927 579,151–779,665 766,383 663,438–864,601 14.6 11,211.5 9876.4–13,008.3 7277.4 6299.5–8180.1 -35.1 Tunisia 282,490 259,822–306,247 371,042 306,673–438,530 31.3 5367.9 4992.8–5778.7 3694.6 3055.8–4362 -31.2 UAE 56,629 42,431–80,907 304,764 220,613–401,976 438.2 7978.3 6300–10,281.2 6184.6 4945.5–7774.5 -22.5 Yemen 824,766 550,243–1,143,803 1,417,685 876,250–2,252,582 71.9 14,715.3 9437–21,422.1 11,692.8 7228.8–18,372.2 -20.5 S144 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Fig. 2 Number of disability-adjusted life years for different cardiovascular diseases attributed to different risk factors, Global Burden of Disease study, Eastern Mediterranean Region, 2015 Table 4 summarizes age-standardized DALY rates for grains, low fruit, low vegetables, and high sodium intake CVD in the EMR countries in 1990 and 2015. As shown, were the most important dietary risk factors. DALY rates decreased in all EMR countries except Pak- istan from 1990 to 2015; the greatest reductions in DALY rates were seen in Bahrain (59.4%), Qatar (48.7%), and Discussion Jordan (47%). Afghanistan had the highest age-standard- ized CVD DALY rate in both 1990 and 2015. Kuwait had This study shows that CVD are the leading cause of disease the lowest age-standardized DALY rate of CVD in 1990, burden in the EMR as a whole and in most of the countries and Qatar had the lowest in 2015. of the region. Close to 33 million years of life were lost due Analyzing the components of DALYs, CVD had a to premature mortality or disability from CVD, and more higher YLL rate compared to YLD rate: on average, YLLs than 1.3 million people died in the EMR in 2015, were 17.7 times higher than YLDs in the EMR. The YLL/ accounting for around one-third of all deaths in the region. YLD ratio in the countries of the region showed a wide Previous studies have also reported CVD deaths as the range of variation, from 48.9 in Afghanistan to 3.7 in Oman main cause of death, for instance, 45% in the West Bank (Electronic supplementary table S2). (Palestine), 45% in Aleppo (Syria), 35% in Jordan, and 25% in UAE (Barakat et al. 2012; Loney et al. 2013; Shara Risk factors 2010). A study in Europe has reported CVD mortality as making up half of all deaths (Nichols et al. 2014). Figure 2 shows the contribution, in DALYs, of different CVD age-standardized mortality was considerably risk factors to different CVD. High blood pressure, high higher than the global average (456 compared to 286 per total cholesterol, and high body mass index were the 100,000); however it shows a declining trend over the past leading risk factors for CVD, accounting for 17,159,331 25 years in most of the EMR countries. Countries with DALYs, 9852,820 DALYs, and 8427,021 DALYs, higher declines (Bahrain, Qatar, Lebanon, and Jordan) respectively. were among the countries in the fourth Socio-demographic The cluster of all dietary risk factors accounts for Index quartile category. In another GBD study, we esti- 19,803,725 DALYs, making it the leading risk factor for mated an index for healthcare access and quality which is a CVD, higher than even high blood pressure. Low whole composite index based on estimates of mortality amenable 123 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S145 to personal health care and varies between 0 (worst) and A Cochrane systematic review showed that multiple risk 100 (best). The index showed substantial heterogeneity factor interventions may lower systolic and diastolic blood with a range between 32 (Afghanistan) and 85 (Qatar) in pressure, body mass index, and waist circumference in low- 2015 in the EMR. Linking these results to the findings of and middle-income countries (Uthman et al. 2015). our study showed that the countries with lower age-stan- Previous studies show a high percentage of undiagnosed dardized DALY rates due to CVD had a higher index for CVD risk factors, such as diabetes and hypertension, in the healthcare access and quality, and vice versa. This restates region (Abd El-Aty et al. 2015; El Bcheraoui et al. the importance of increasing access to and quality of health 2014a, b; Najafipour et al. 2014). The evidence shows that care to reduce CVD burden (Barber et al. 2017). delayed detection and undiagnosed risk factors, especially In the EMR, YLLs are the main component of CVD diabetes, are strong predictors of fatal CVDs (Nakagami burden. A global-level assessment showed that for overall et al. 2006). Based on reports from the region, required CVD, YLL rates were lowest in both the lowest and highest care and services (such as medications) are underutilized in socio-demographic groups, with an increase for those in the diagnosed cases, even in high-income countries like Saudi middle of the socio-demographic rankings. It has been Arabia (Moradi-Lakeh et al. 2016). Underutilization of suggested that medical care in countries with the highest medications is a function of availability, accessibility, Socio-demographic Index might have increased life affordability, acceptability, and quality of medicines (and expectancy to the point where CVD is most prevalent, care), as well as adherence to medical recommendations while people in the lowest socio-demographic group are (Behnood-Rod et al. 2016; Najafipour et al. 2014; van dying from other competing conditions before reaching the Mourik et al. 2010; Wirtz et al. 2016). The Prospective common age for developing ischemic heart disease and Urban Rural Epidemiology (PURE) study showed great stroke. Based on this hypothesis, people living in countries variation in availability, affordability, and use of medica- in the middle range of the socio-demographic rankings are tions for CVD, between and within countries. Countries surviving long enough to develop ischemic heart disease with less control over production, importation, distribution but do not have access to optimal medical or surgical chains, and retail outlets are specifically at risk of sub- treatment (GBD 2015 Mortality and Causes of Death standard quality and falsification of medicines (Khatib Collaborators 2016). et al. 2016). All these factors are important to achieve These findings call for a comprehensive approach to desired health outcomes in the field of CVD. CVD pre- prevent and control the burden of CVD in the region. This vention and control programs should improve the per- approach should include a road map for better monitoring ceived need and demand of the population for early of the burden in EMR countries, with a focus on potential detection and use of the prevention/control services. The study on CVD mortality forecast in 2015 has shown that variations in risk and care by regions within the countries. It should also include programs for increasing awareness the MENA region will not achieve the target of 25% among the general population of the importance of con- reduction of CVD mortality by 2025 without achieving all trolling CVD risk factors. major targets for risk factor reduction (i.e., reducing the The United Nations has set targets to decrease mortality prevalence of elevated systolic blood pressure by 25%, from non-communicable diseases (Sustainable Develop- reducing the prevalence of smoking by 30%, halting the ment Goals, target 3.4.1), and CVD is at the center of this rise in elevated body mass index, and halting the rise in target (GBD 2015 SDGs Collaborators 2016). The World fasting plasma glucose). Moreover, reports of health sys- Health Organization has suggested a package of essential tem challenges in controlling and managing CVD in some non-communicable disease interventions for primary health of the EMR countries reemphasize the need for significant care in low-resource settings (PEN). These interventions investment and improvement of access (Roth et al. include a mixture of cost-effective population-wide and 2015a, b; Romdhane et al. 2015; Ahmad et al. 2015). individual approaches to reduce the burden of major non- Our study has some limitations; accurate data on car- communicable diseases, such as methods for early detec- diovascular events (especially non-fatal outcomes) are tion and diagnosis using inexpensive technologies, non- limited in many countries, including the EMR countries. pharmacological and pharmacological approaches for We used the standard GBD methodology by using study- modification of risk factors, and affordable medications for and country-level covariates for adjustment and estimation prevention and treatment of heart attacks and strokes, of epidemiologic measures. Our study does not account for diabetes, cancer, and asthma (World-Health-Organization variation within countries. 2010). Our study showed that increased blood pressure is the most important risk factor for CVD in the EMR, followed by high total cholesterol and high body mass index. 123 S146 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Epidemiology Unit, Lund University, Lund, Sweden. Muktar Beshir Conclusion Ahmed, MPH, College of Health Sciences, Department of Epidemi- ology, ICT and e-Learning Coordinator, Jimma University, Jimma, Most of the EMR countries have launched programs to Ethiopia. Baran Aksut, MD, Cleveland Clinic, Cleveland, United reduce the burden of non-communicable disease, but they States. Khurshid Alam, PhD, Murdoch Childrens Research Institute, The University of Melbourne, Parkville, Victoria, Australia. The generally do not have widespread programs to combat University of Melbourne, Melbourne, VIC, Australia, The University CVD. This study calls for strengthening efforts to design of Sydney, Sydney, NSW, Australia. Deena Alasfoor, MSc, Ministry and launch comprehensive programs to cover all aspects of of Health, Al Khuwair, Muscat, Oman. Raghib Ali, MSc, University prevention and control of CVDs through evidence-in- of Oxford, Oxford, UK. Reza Alizadeh-Navaei, PhD, Gastrointestinal Cancer Research Center, Mazandaran University of Medical Sci- formed, efficient interventions. The countries should ences, Sari, Iran. Rajaa Al-Raddadi, PhD, Joint Program of Family establish or improve information systems such as surveil- and Community Medicine, Jeddah, Saudi Arabia. Ubai Alsharif, lance sy stems to provide valid and accurate information MPH, Charite ´ Universita ¨tsmedizin, Berlin, Germany. Khalid A. for policymaking and monitoring of the situation. Altirkawi, MD, King Saud University, Riyadh, Saudi Arabia. Nelson Alvis-Guzman, PhD, Universidad de Cartagena, Colombia. Nahla Anber, PhD, Mansoura University, Mansoura, Egypt. Palwasha GBD 2015 Eastern Mediterranean Region Cardiovascular Dis- Anwari, MD, Self-employed, Kabul, Afghanistan. Johan Arnlo ¨ v, ease Collaborators: Ali H. Mokdad, PhD (corresponding author), PhD, Department of Neurobiology, Care Sciences and Society, Institute for Health Metrics and Evaluation, University of Washing- Division of Family Medicine and Primary Care, Karolinska Institutet, ton, Seattle, Washington, United States. Arash Tehrani-Banihashemi, Stockholm, Sweden, School of Health and Social Studies, Dalarna PhD, Preventive Medicine and Public Health Research Center, Iran University, Falun, Sweden. Solomon Weldegebreal Asgedom, PhD, University of Medical Sciences, Tehran, Iran. Maziar Moradi-Lakeh, Mekelle University, Mekelle, Ethiopia. Tesfay Mehari Atey, MS, MD, Department of Community Medicine, Preventive Medicine Mekelle University, Mekelle, Ethiopia. Ashish Awasthi, PhD, Sanjay Public Health Research Center, Gastrointestinal and Liver Disease Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India. Research Center (GILDRC), Iran University of Medical Sciences, Till Barnighausen, MD, Department of Global Health and Population, Tehran, Iran. Charbel El Bcheraoui, PhD, Institute for Health Metrics Harvard T. H. Chan School of Public Health, Harvard University, and Evaluation, University of Washington. Raghid Charara, MD, Boston, MA, United States; Africa Health Research Institute, Mtu- American University of Beirut, Beirut, Lebanon. Ibrahim Khalil, MD, batuba, South Africa; Institute of Public Health, Heidelberg Univer- Institute for Health Metrics and Evaluation, University of Washing- sity, Heidelberg, Germany. Umar Bacha, PhD, School of Health ton. Ashkan Afshin, MD, Institute for Health Metrics and Evaluation, Sciences, University of Management and Technology, Lahore, Pak- University of Washington, Seattle, Washington, United States. istan. Aleksandra Barac, PhD, Faculty of Medicine, University of Michael Collison, BS, Institute for Health Metrics and Evaluation, Belgrade, Belgrade, Serbia. Suzanne L. Barker-Collo, PhD, School of University of Washington, Seattle, Washington, United States. Farah Psychology, University of Auckland, Auckland, New Zealand. Neeraj Daoud, BA/BS, Institute for Health Metrics and Evaluation, Univer- Bedi, MD, College of Public Health and Tropical Medicine, Jazan, sity of Washington. Kristopher J. Krohn, BA, Institute for Health Saudi Arabia. Derrick A. Bennett, PhD, Nuffield Department of Metrics and Evaluation, University of Washington, Seattle, Wash- Population Health, University of Oxford, Oxford, UK. Derbew Fikadu ington, United States. 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Tommi Vasankari, PhD, UKK Institute for Health Promotion Research, Conflict of interest The authors declare that they have no conflicts of Tampere, Finland. Vasiliy Victorovich Vlassov, MD, National interest at this time. Research University Higher School of Economics, Moscow, Russia. Stein Emil Vollset, DrPH, Center for Disease Burden, Norwegian Open Access This article is distributed under the terms of the Institute of Public Health, Bergen, Norway; Department of Global Creative Commons Attribution 4.0 International License (http://crea Public Health and Primary Care, University of Bergen, Bergen, tivecommons.org/licenses/by/4.0/), which permits unrestricted use, Norway; Institute for Health Metrics and Evaluation, University of distribution, and reproduction in any medium, provided you give Washington, Seattle, WA, United States. Tolassa Wakayo, MS, appropriate credit to the original author(s) and the source, provide a Jimma University, Jimma, Ethiopia. Robert G. 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Burden of cardiovascular diseases in the Eastern Mediterranean Region, 1990–2015: findings from the Global Burden of Disease 2015 study

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Abstract

Int J Public Health (2018) 63 (Suppl 1):S137–S149 https://doi.org/10.1007/s00038-017-1012-3 O R I G IN AL ARTI CL E Burden of cardiovascular diseases in the Eastern Mediterranean Region, 1990–2015: findings from the Global Burden of Disease 2015 study GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Received: 1 May 2017 / Revised: 20 June 2017 / Accepted: 28 June 2017 / Published online: 3 August 2017 The Author(s) 2017. This article is an open access publication Abstract and high body mass index were the leading risk factors for Objectives To report the burden of cardiovascular diseases CVD. (CVD) in the Eastern Mediterranean Region (EMR) during Conclusions The age-standardized DALY rates in the 1990–2015. EMR are considerably higher than the global average. Methods We used the 2015 Global Burden of Disease study These findings call for a comprehensive approach to pre- for estimates of mortality and disability-adjusted life years vent and control the burden of CVD in the region. (DALYs) of different CVD in 22 countries of EMR. Results A total of 1.4 million CVD deaths (95% UI: Keywords Cardiovascular disease  Burden of disease 1.3–1.5) occurred in 2015 in the EMR, with the highest Eastern Mediterranean Region number of deaths in Pakistan (465,116) and the lowest number of deaths in Qatar (723). The age-standardized DALY rate per 100,000 decreased from 10,080 in Introduction 1990 to 8606 in 2015 (14.6% decrease). Afghanistan had the highest age-standardized DALY rate of CVD in both The Global Burden of Disease (GBD) study documented that 1990 and 2015. Kuwait and Qatar had the lowest age-s- cardiovascular diseases (CVD) have been the leading cause of tandardized DALY rates of CVD in 1990 and 2015, global mortality since 1980 (Institute for Health Metrics and respectively. High blood pressure, high total cholesterol, Evaluation 2017; Mortality and Causes of Death 2016). CVD accounted for nearly one-third of all deaths worldwide in 2015. Meanwhile, the principal components of CVD, namely stroke and ischemic heart disease, accounted for 85.1% (95% This article is part of the supplement ‘‘The state of health in the uncertainty interval (UI): 84.7–85.5) of all deaths in the CVD Eastern Mediterranean Region, 1990–2015’’. category in 2015 (Mortality and Causes of Death 2016). Although the age-standardized mortality rates of CVD The members of GBD (Global Burden of Disease) 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators are have fallen by 27.3% in the last 25 years, the absolute number listed at the end of the article. Ali H. Mokdad, on behalf of GBD 2015 of deaths due to CVD increased globally by 42.4% between Eastern Mediterranean Region Cardiovascular Disease Collaborators, 1990 and 2015 (2017). Most CVD deaths occur in low- and is the corresponding author. middle-income countries (Mensah et al. 2015). The decline in Electronic supplementary material The online version of this age-standardized rates is mainly due to preventive interven- article (doi:10.1007/s00038-017-1012-3) contains supplementary tions and better access to quality treatment for acute cardio- material, which is available to authorized users. vascular conditions such as myocardial infarction and stroke & GBD 2015 Eastern Mediterranean Region Cardiovascular (Smith 2011). CVD also impose a high economic burden on Disease Collaborators health systems and society. For instance, CVD personal mokdaa@uw.edu spending in the United States was estimated to be 231.1 billion USD in 2013 and was the largest disease category of personal Institute for Health Metrics and Evaluation, University of health care spending (Dieleman et al. 2016). Washington, Seattle, WA, USA 123 S138 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators The Eastern Mediterranean Region (EMR) comprises 22 life tables for all-cause mortality were used to calculate countries with a population of nearly 580 million people, years of life lost (YLLs) (GBD 2015 Morality and Causes with a diverse range in per capita gross national product of Death Collaborators 2016; Roth et al. 2015a, b). (maximum 83,990 USD for Qatar, minimum 610 USD for We updated our previous systematic reviews for the Afghanistan) (World Development Indicators database GBD study separately for each of the non-fatal sequelae of 2017). To the best of our knowledge, there is no compre- CVD. Data on epidemiologic measures (incidence, preva- hensive report on the burden and mortality of CVD in the lence, and case fatality) were extracted from 170 data EMR. sources. List of all sources (by cause and location) are This study aimed to report findings on cardiovascular available at the Institute for Health Metrics and Evalua- diseases between 1990 and 2015, from the Global Burden tion’s website (IHME 2016). of Diseases, Injuries and Risk Factors Study (GBD 2015) Bayesian meta-regression analysis through DisMod-MR in the 22 countries of the EMR. This would be help us 2.1 was used for disease modeling. Model-based preva- better understand the burden of CVD and interventions lence estimates, in combination with disability weights, needed to control these diseases. were used to calculate cause-specific years lived with dis- ability (YLDs) for each age, sex, location, and year. Dis- ability-adjusted life years (DALYs) were calculated Methods through summation of YLLs and YLDs (DALYs and Collaborators 2016; Disease et al. 2016). GBD 2015 covers 195 countries, 21 regions, and seven We report 95% uncertainty intervals (UI) for each super-regions from 1990 to 2015 for 315 diseases and estimate, including rates, numbers of deaths, and DALYs. injuries, 2619 unique sequelae, and 79 risk factors by age We estimated UIs by taking 1000 samples from the pos- and sex. Detailed descriptions of the general methodolog- terior distribution of each quantity and using the 25th- and ical approach of GBD 2015 and specific methodology used 975th-ordered draws of the uncertainty distribution. for CVD have been provided elsewhere (GBD 2015 DALYs and Collaborators 2016; GBD 2015 Disease and Injury Prevalence Collaborators 2016; GBD 2015 Mortal- Results ity and Causes of Death Collaborators 2016). We evaluated the burden of CVD in the Eastern Mortality Mediterranean Region (EMR), which contains 22 coun- tries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, The CVD death rate per 100,000 population in the EMR Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pak- decreased from 515.1 (95% UI: 491.7–541.5) in 1990 to istan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, 456.5 (95% UI: 431.5–484.2) in 2015 (Table 1). A total of Syria, Tunisia, the United Arab Emirates (UAE), and 1,373,329 CVD deaths (95% UI: 1,290,959–1,465,047) Yemen. occurred in 2015 in the EMR, 54.8% of which were among The category of CVD includes the ten most common males. These deaths accounted for 34.1% (95% UI: global causes of CVD-related death: rheumatic heart dis- 33.1–35.1) of all deaths in the region in 2015, compared to ease, ischemic heart disease, cerebrovascular disease (is- 30.2% (95% UI: 29.5–30.9) of all deaths in 1990. The chemic stroke and hemorrhagic stroke), hypertensive heart number of men dying from CVD was consistently higher disease, cardiomyopathy and myocarditis, atrial fibrillation than the number of women during 1990–2015 (Fig. 1). and flutter, aortic aneurysm, peripheral vascular disease, The total number of deaths from ischemic heart disease endocarditis, and ‘‘other cardiovascular and circulatory (IHD) was 802,078 in 2015, which accounted for 58.4% of diseases.’’ Electronic supplementary table S1 shows the the total number of deaths due to CVD in the EMR. There International Classification of Diseases (ICD-10) codes for were 637,640 additional deaths in 2015 compared to 1990, each of the cardiovascular causes. out of which 62.5% was contributed by IHD. To estimate the number of deaths due to CVD, we Table 2 provides the total number of deaths and the age- estimated all-cause mortality envelopes (total number of standardized death rates from CVD in 1990 and 2015 for deaths) for each country-year during 1990–2015; we used all EMR countries. In 2015, Afghanistan had the highest all accessible data such as vital registration systems, sam- age-standardized death rate from CVD, followed by Iraq ple registration data, and household recall of deaths. These and Yemen. In most of the EMR countries, age-standard- sources were used as inputs for cause of death models. We ized death rates for CVD decreased between 1990 and used cause of death ensemble modeling (CODEm) to 2015, with the highest decreases in Bahrain, Qatar, Leba- estimate the number of deaths for each CVD by age, sex, non, and Jordan. country, and year. The number of deaths for each cause and 123 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S139 Table 1 Total number of deaths and age-standardized mortality rates for cardiovascular diseases in 1990 and 2015, and percentage change, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 Cause Number of deaths Age-standardized death rate per 100,000 1990 2015 % Change 1990 2105 % Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI Cardiovascular diseases 735,689 700,875–773,593 1,373,329 1,290,959–1,465,047 86.7 515.1 491.7–541.5 456.5 431.5–484.2 -11.4 Rheumatic heart disease 18,350 16,029–21,037 27,046 22,945–31,078 47.4 9.1 7.8–10.7 6.8 5.7–7.8 -25.5 Ischemic heart disease 403,355 379,184–425,913 802,078 750,839–859,266 98.9 294.0 276.9–310.3 269.1 252.5–286.9 -8.5 Ischemic stroke 92,230 79,786–106,780 174,760 158,325–190,197 89.5 75.5 65.5–87.8 65.6 59.7–71.2 -13.1 Hemorrhagic stroke 117,813 105,731–133,751 200,113 182,283–230,479 69.9 71.5 61–82.5 60.6 55.4–69.6 -15.3 Hypertensive heart disease 36,179 30,771–46,101 62,663 55,680–71,029 73.2 27.0 22.7–35.2 21.4 19–24.1 -20.7 Cardiomyopathy and myocarditis 18,025 15,031–20,571 27,128 24,612–29,553 50.5 8.7 7.2–10 7.3 6.5–7.9 -16.6 Atrial fibrillation and flutter 3513 2654–4487 7535 5707–9666 114.5 3.9 2.9–5.1 3.5 2.6–4.5 -11.0 Aortic aneurysm 2694 2163–3414 6941 6291–7580 157.6 2.0 1.6–2.5 2.3 2.1–2.5 14.9 Peripheral artery disease 114 68–151 424 365–508 272.4 0.1 0.1–0.1 0.2 0.1–0.2 65.9 Endocarditis 5172 4167–7067 9016 7833–12,719 74.3 2.9 2.3–4.2 2.6 2.3–3.9 -8.3 Other cardiovascular and circulatory diseases 38,243 34,519–42,477 55,625 51,621–60,292 45.5 20.3 18.5–22.2 17.1 15.9–18.6 -15.7 S140 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Fig. 1 Trend of number of 800000 deaths and age-standardized mortality rate from cardiovascular diseases in males and females, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 300000 0 1990 1995 2000 2005 2010 2015 Male Female Male (rate) Female (rate) Electronic supplementary figure S1 shows the top- per 100,000 in 2015. Age-standardized YLD rates of CVD ranked death rates for different CVD in EMR countries. decreased between 1990 and 2015 in six countries of the Ischemic heart disease was the leading cause of CVD region: Iran, United Arab Emirates, Jordan, Djibouti, mortality in 20 countries of the EMR; the exceptions were Somalia, and Afghanistan. The biggest decline was seen in Djibouti and Somalia, where cerebrovascular disease (both Iran (4.6%), and the smallest reduction was in Afghanistan hemorrhagic and ischemic stroke) was the leading cause of (0.5%). Among the remaining 16 countries of the region cardiovascular-related death. that showed increases in age-standardized YLD rates of CVD, Syria’s was the greatest, at 9.1%. YLLs DALYs The age-standardized YLL rate decreased 15.3%, from 9618.7 (9148.6–10,141.7) per 100,000 in 1990–8145.0 The rate of DALYs from CVD per 100,000 population (7628.6–8744.3) per 100,000 in 2015 (Electronic supple- decreased from 5447.8 (95% UI: 5168.2–5739.0) in mentary table S2). In the region, Afghanistan had the 1990–5109.8 (95% UI: 4771.3–5511.1) in 2015, a 6.2% highest age-standardized YLL rate at 21,426.2 decrease—compared to an 8.4% reduction in the DALY (17,105.2–26,544.7), followed by Yemen and Iraq (Elec- rate for all other non-communicable diseases in the EMR. tronic supplementary table S2). In all countries of the EMR The age-standardized DALY rate also decreased 14.6% except Pakistan, age-standardized YLL rates decreased during 1990–2015 (Table 3). Table 3 reports numbers and from 1990 to 2015 (Electronic supplementary table S2). age-standardized rates of DALYs for different CVD in the EMR in 1990 and 2015. The age-standardized DALY rate YLDs of CVD for men and women in the EMR in 2015 was higher than in other WHO regions. It was 1.51 times the The years lived with disability caused by CVD in the EMR global rate for males and 1.86 times the global rate for increased from 1,058,839 (95% UI: 746,613–1409,913) in females. Electronic supplementary figure S2 shows the 1990 to 1,966,111 (95% UI: 1398,373–2597,819) in 2015. age-standardized rates of DALYs for different CVD in men The rate of YLD increased by 85.7% during 1990–2015 in and women. As shown, ischemic heart disease caused the the EMR. highest number of DALYs both in men (5771.9 per The age-standardized YLD rate in the EMR was 460.6 100,000) and women (3931.2 per 100,000), followed by (329.2–603.6) per 100,000 in 2015, which showed very hemorrhagic stroke and ischemic stroke. little decrease compared to 1990 (461.1 per 100,000) Electronic supplementary figure S3 shows DALY rates (Electronic supplementary table S2). Oman had the highest for each CVD in different age groups. As shown, the age-standardized YLD rate in the region in both 1990 and highest DALY rates for IHD, hemorrhagic stroke, ischemic 2015: it was 1261 (874.6–1722.1) per 100,000 in 2015, stroke, and hypertensive heart disease were observed in which was about 2.7 times higher than the regional aver- people aged 50–69 years. IHD, hemorrhagic stroke, and age. United Arab Emirates had the lowest age-standardized rheumatic heart disease showed the highest number of YLD rate in the EMR, 296.8 per 100,000 in 1990 and 285.8 DALYs in the 15–49 years age group. Number Rate per 100,000 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S141 Table 2 Total number of deaths and age-standardized mortality rates for cardiovascular disease causes of death in 1990 and 2015, and percent change, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 Country Number of deaths Age-standardized death rate per 100,000 1990 2015 % Change 1990 2015 % Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI EMR 735,689 700,875–773,593 1,373,329 1,290,959–1,465,047 86.7 515.1 491.7–541.5 456.5 431.5–484.2 -11.4 Afghanistan 34,755 27,217–42,776 10,1572 81,113–125,962 192.2 1048.1 860.6–1235.4 1042.5 865–1227.9 -0.5 Bahrain 614 547–681 792 671–933 29.0 414.1 371.4–456.9 186.1 162.1–210.2 -55.1 Djibouti 683 434–1025 1402 762–-2395 105.3 393.4 265.8–568.8 360.9 212.6–590.1 -8.3 Egypt 153,214 147,677–157,026 226,457 219,738–234,235 47.8 544.9 530.1–556.7 465.2 451.7–479.2 -14.6 Iran 96,775 86,347–107,587 176,299 148,576–203,480 82.2 499.2 451.4–547.5 402.2 344–456.9 -19.4 Iraq 44,476 38,326–51,342 75,604 61,673–91,552 70.0 657.6 569.1–755.1 604.4 503.7–715.3 -8.1 Jordan 4869 4319–5684 6788 6108–7611 39.4 416.0 370.2–481.4 236.9 214.1–264.4 -43.1 Kuwait 1262 1192–1324 2367 2040–2747 87.6 258.5 245–271.3 209.7 185–237 -18.9 Lebanon 7397 6206–8674 11,632 8967–14,195 57.3 464.2 391.3–540.9 252.1 196–305.1 -45.7 Libya 4864 4354–5397 9301 8130–10,535 91.2 310.3 276.6–344 299.7 263.3–339.3 -3.4 Morocco 36,293 32,487–40,581 59,824 47,641–75,972 64.8 362.1 327.5–400.4 268.3 216.5–336.6 -25.9 Oman 2108 1688–2552 4000 3336–4583 89.7 378.8 300.7–461.2 300.3 255.4–336.8 -20.7 Pakistan 216,936 191,002–247,476 465,116 407,279–528,666 114.4 513.1 454.9–578 530.9 469–599.1 3.5 Palestine 2333 1902–2925 5805 4683–6954 148.8 443.1 366.5–542 394.9 326.3–462.4 -10.9 Qatar 338 297–383 723 568–924 114.3 342.4 303.1–380.4 180.6 149.6–221.8 -47.3 Saudi Arabia 13,222 11,931–14,651 25,845 23,532–28,503 95.5 288.0 260.4–317.9 231.6 213.2–-253.4 -19.6 Somalia 11,706 3957–22,825 15,080 5270–31,505 28.8 508.9 192.7–890.2 439.7 172.6–813.3 -13.6 Sudan 42,922 35,852–51,825 74,648 56,697–97,015 73.9 611.3 512.7–738.5 501.9 388.7–634.1 -17.9 Syria 23,049 20,307–26,719 33,044 28,488–36,934 43.4 554.8 494.8–634.9 401.0 348.7–446.9 -27.7 Tunisia 10,747 9970–11,633 18,423 14,973–21,952 71.4 285.3 263.3–308.9 204.0 166.5–242.6 -28.5 UAE 1641 1260–2230 8563 6337–11,314 421.9 406.5 327.3–501.8 333.4 279.6–403.7 -18.0 Yemen 25,485 16,534–36,647 50,043 30,637–78,838 96.4 700.0 461.6–991.9 592.1 383–888.5 -15.4 S142 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Table 3 Total disability-adjusted life years (DALY) and age-standardized disability-adjusted life years rates for component cardiovascular causes of death in 1990 and 2015, and percent change, Global Burden of Disease study, Eastern Mediterranean Region, 1990–2015 Cause Number of DALYs Age-standardized DALY rate per 100,000 1990 2015 % 1990 2015 % Change Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI Cardiovascular diseases 20,164,206 19,129,504–21,242,151 33,131,948 30,937,166–35,734,353 64.3 10,079.8 9594.7–10,603.6 8605.6 8074.6–9219.3 -14.6 Rheumatic heart disease 876,838 770,813–986,361 1153,351 993,217–1333,219 31.5 302.1 265.1–344.5 215.8 185.2–248.4 -28.5 Ischemic heart disease 9323,188 8770,306–9877,741 17,827,201 16,511,324–19,368,534 91.2 5370.1 5052.6–5672.7 4865.0 4533.1–5231.4 -9.4 Ischemic stroke 1879,679 1649,862–2128,711 3272,789 2963,211–3568,718 74.1 1183.5 1031.4–1361 997.6 903.8–1085.4 -15.7 Hemorrhagic stroke 3941,327 3658,523–4323,670 5565,221 5091,084–6337,446 41.2 1649.0 1485.2–1870.5 1303.2 1193.9–1493 -21.0 Hypertensive heart disease 822,728 711,712–1011,157 1366,662 1201,763–1571,258 66.1 479.4 411.3–603 371.0 328.2–422.5 -22.6 Cardiomyopathy and 833,292 693,153–982,453 1001,334 891,780–1097,777 20.2 247.2 206.1–281.7 188.0 170.3–204.4 -24.0 myocarditis Atrial fibrillation and flutter 77,777 61,867–94,926 161,328 129,867–199,493 107.4 63.3 51.4–77 58.2 47–71 -8.0 Aortic aneurysm 63,221 50,928–80,451 163,304 146,635–180,105 158.3 35.4 28.5–45 41.6 37.6–45.6 17.6 Peripheral artery disease 13,954 7359–24,367 32,852 18,777–56,064 135.4 10.1 5.3–17.9 11.2 6.4–19.3 11.3 Endocarditis 217,347 160,723–291,718 292,842 248,013–378,079 34.7 68.4 55–92.5 58.5 50.9–80.3 -14.4 Other CVD 2114,855 1844,679–2463,667 2295,064 2018,478–2613,017 8.5 671.3 599.3–755.3 495.4 440.4–555.8 -26.2 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S143 Table 4 Total number of disability-adjusted life years and age-standardized disability-adjusted life years rates for cardiovascular diseases in 1990 and 2015, and percent change, 1990–2015, in Eastern Mediterranean Region countries Country Number of DALYs Age-standardized DALY rate per 100,000 1990 2015 % Change 1990 2015 % Change Number 95% UI Number 95% UI Rate 95% UI Rate 95% UI EMR 20,164,206 19,129,504–21,242,151 33,131,948 30,937,166–35,734,353 64.3 10,079.8 9594.7–10,603.6 8605.6 8074.6–9219.3 -14.6 Afghanistan 1,019,023 7,93,590–1,278,676 2,865,062 2,239,466–3,635,800 181.2 22,258.2 17,615.6–27,186.7 21,864.3 17,591.4–27,024.5 -1.8 Bahrain 18,578 16,524–20,639 23,376 19,748–27,808 25.8 8086.5 7206.4–8964 3281.4 2832.6–3769.2 -59.4 Djibouti 19,979 13,027–-29,586 35,930 19,430–64,153 79.8 7891.5 5171.4–11,605.5 7112.8 4021.2–12,056.6 -9.9 Egypt 4,373,017 4,109,349–4,595,897 5,436,416 5,216,937–5,700,475 24.3 11,230.6 10,762.9–11,583.1 8826.2 8508.6–9171.3 -21.4 Iran 2,941,466 2,601,284–3,291,417 3,875,985 3,249,465-4,577,119 31.8 9849.9 8776.8–10,950.2 7179.6 6090.9–8340.9 -27.1 Iraq 1,070,614 917,957–1248,583 1,875,448 1,489,313–2,315,419 75.2 12,513.4 10,678.3–14,669.9 11,244.0 9089.6–13,679.3 -10.1 Jordan 109,195 95,903–127,032 154,251 137,970–172,312 41.3 7692.8 6771.4–8983.8 4077.5 3666.1–4533 -47.0 Kuwait 40,918 38,315–43,123 75,385 65,509–87,507 84.2 4818.8 4558.7–5066.9 3884.1 3424.2–4417.1 -19.4 Lebanon 167,913 140,761–199,069 211,244 159,897–264,585 25.8 8792.7 7390.6–10,364.6 4213.8 3210.3–5249.2 -52.1 Libya 176,223 154,977–198,183 234,502 205,521–265,135 33.1 6384.4 5714.7–7050.6 5638.4 4957.2–6367.8 -11.7 Morocco 1,103,861 980,405–1,235,540 1,332,750 1,078,637–1,670,227 20.7 7222.4 6511.3–8059.2 4977.5 4039.5–6209.9 -31.1 Oman 93,965 76,349–115,695 135,300 114,087–155,337 44.0 8404.3 6832–10,016.2 5962.4 5071–6713.2 -29.1 Pakistan 5,069,303 4,422,395–5,880,731 10,719,663 9,250,078–12,360,492 111.5 9446.3 8281–10,798.4 9928.0 8664.3–11,288.5 5.1 Palestine 68,438 55,953–85,314 150,510 120,084–183,652 119.9 8263.4 6749.8–10,377.3 7280.6 5868.1–8727.7 -11.9 Qatar 10,556 9283–12,017 24,791 19,932–30,601 134.8 5873.6 5192.9–6542.3 3013.6 2466.4–3730 -48.7 Saudi Arabia 359,601 320,837–401,588 663,879 600,438–732,764 84.6 5285.0 4727.5–5861.6 4003.3 3650.2–4393.1 -24.3 Somalia 329,146 120,719–676,354 410,106 151,542–920,717 24.6 10,762.8 3851–21,078.4 9062.4 3379.7–18,999.5 -15.8 Sudan 1,359,599 1,129,865–1,596,275 2,047,475 1,542,545–2,657,659 50.6 12,814.4 10,687.4–15,522.9 9823.7 7427.1–12,742.4 -23.3 Syria 668,927 579,151–779,665 766,383 663,438–864,601 14.6 11,211.5 9876.4–13,008.3 7277.4 6299.5–8180.1 -35.1 Tunisia 282,490 259,822–306,247 371,042 306,673–438,530 31.3 5367.9 4992.8–5778.7 3694.6 3055.8–4362 -31.2 UAE 56,629 42,431–80,907 304,764 220,613–401,976 438.2 7978.3 6300–10,281.2 6184.6 4945.5–7774.5 -22.5 Yemen 824,766 550,243–1,143,803 1,417,685 876,250–2,252,582 71.9 14,715.3 9437–21,422.1 11,692.8 7228.8–18,372.2 -20.5 S144 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Fig. 2 Number of disability-adjusted life years for different cardiovascular diseases attributed to different risk factors, Global Burden of Disease study, Eastern Mediterranean Region, 2015 Table 4 summarizes age-standardized DALY rates for grains, low fruit, low vegetables, and high sodium intake CVD in the EMR countries in 1990 and 2015. As shown, were the most important dietary risk factors. DALY rates decreased in all EMR countries except Pak- istan from 1990 to 2015; the greatest reductions in DALY rates were seen in Bahrain (59.4%), Qatar (48.7%), and Discussion Jordan (47%). Afghanistan had the highest age-standard- ized CVD DALY rate in both 1990 and 2015. Kuwait had This study shows that CVD are the leading cause of disease the lowest age-standardized DALY rate of CVD in 1990, burden in the EMR as a whole and in most of the countries and Qatar had the lowest in 2015. of the region. Close to 33 million years of life were lost due Analyzing the components of DALYs, CVD had a to premature mortality or disability from CVD, and more higher YLL rate compared to YLD rate: on average, YLLs than 1.3 million people died in the EMR in 2015, were 17.7 times higher than YLDs in the EMR. The YLL/ accounting for around one-third of all deaths in the region. YLD ratio in the countries of the region showed a wide Previous studies have also reported CVD deaths as the range of variation, from 48.9 in Afghanistan to 3.7 in Oman main cause of death, for instance, 45% in the West Bank (Electronic supplementary table S2). (Palestine), 45% in Aleppo (Syria), 35% in Jordan, and 25% in UAE (Barakat et al. 2012; Loney et al. 2013; Shara Risk factors 2010). A study in Europe has reported CVD mortality as making up half of all deaths (Nichols et al. 2014). Figure 2 shows the contribution, in DALYs, of different CVD age-standardized mortality was considerably risk factors to different CVD. High blood pressure, high higher than the global average (456 compared to 286 per total cholesterol, and high body mass index were the 100,000); however it shows a declining trend over the past leading risk factors for CVD, accounting for 17,159,331 25 years in most of the EMR countries. Countries with DALYs, 9852,820 DALYs, and 8427,021 DALYs, higher declines (Bahrain, Qatar, Lebanon, and Jordan) respectively. were among the countries in the fourth Socio-demographic The cluster of all dietary risk factors accounts for Index quartile category. In another GBD study, we esti- 19,803,725 DALYs, making it the leading risk factor for mated an index for healthcare access and quality which is a CVD, higher than even high blood pressure. Low whole composite index based on estimates of mortality amenable 123 Burden of cardiovascular diseases in the Eastern Mediterranean Region… S145 to personal health care and varies between 0 (worst) and A Cochrane systematic review showed that multiple risk 100 (best). The index showed substantial heterogeneity factor interventions may lower systolic and diastolic blood with a range between 32 (Afghanistan) and 85 (Qatar) in pressure, body mass index, and waist circumference in low- 2015 in the EMR. Linking these results to the findings of and middle-income countries (Uthman et al. 2015). our study showed that the countries with lower age-stan- Previous studies show a high percentage of undiagnosed dardized DALY rates due to CVD had a higher index for CVD risk factors, such as diabetes and hypertension, in the healthcare access and quality, and vice versa. This restates region (Abd El-Aty et al. 2015; El Bcheraoui et al. the importance of increasing access to and quality of health 2014a, b; Najafipour et al. 2014). The evidence shows that care to reduce CVD burden (Barber et al. 2017). delayed detection and undiagnosed risk factors, especially In the EMR, YLLs are the main component of CVD diabetes, are strong predictors of fatal CVDs (Nakagami burden. A global-level assessment showed that for overall et al. 2006). Based on reports from the region, required CVD, YLL rates were lowest in both the lowest and highest care and services (such as medications) are underutilized in socio-demographic groups, with an increase for those in the diagnosed cases, even in high-income countries like Saudi middle of the socio-demographic rankings. It has been Arabia (Moradi-Lakeh et al. 2016). Underutilization of suggested that medical care in countries with the highest medications is a function of availability, accessibility, Socio-demographic Index might have increased life affordability, acceptability, and quality of medicines (and expectancy to the point where CVD is most prevalent, care), as well as adherence to medical recommendations while people in the lowest socio-demographic group are (Behnood-Rod et al. 2016; Najafipour et al. 2014; van dying from other competing conditions before reaching the Mourik et al. 2010; Wirtz et al. 2016). The Prospective common age for developing ischemic heart disease and Urban Rural Epidemiology (PURE) study showed great stroke. Based on this hypothesis, people living in countries variation in availability, affordability, and use of medica- in the middle range of the socio-demographic rankings are tions for CVD, between and within countries. Countries surviving long enough to develop ischemic heart disease with less control over production, importation, distribution but do not have access to optimal medical or surgical chains, and retail outlets are specifically at risk of sub- treatment (GBD 2015 Mortality and Causes of Death standard quality and falsification of medicines (Khatib Collaborators 2016). et al. 2016). All these factors are important to achieve These findings call for a comprehensive approach to desired health outcomes in the field of CVD. CVD pre- prevent and control the burden of CVD in the region. This vention and control programs should improve the per- approach should include a road map for better monitoring ceived need and demand of the population for early of the burden in EMR countries, with a focus on potential detection and use of the prevention/control services. The study on CVD mortality forecast in 2015 has shown that variations in risk and care by regions within the countries. It should also include programs for increasing awareness the MENA region will not achieve the target of 25% among the general population of the importance of con- reduction of CVD mortality by 2025 without achieving all trolling CVD risk factors. major targets for risk factor reduction (i.e., reducing the The United Nations has set targets to decrease mortality prevalence of elevated systolic blood pressure by 25%, from non-communicable diseases (Sustainable Develop- reducing the prevalence of smoking by 30%, halting the ment Goals, target 3.4.1), and CVD is at the center of this rise in elevated body mass index, and halting the rise in target (GBD 2015 SDGs Collaborators 2016). The World fasting plasma glucose). Moreover, reports of health sys- Health Organization has suggested a package of essential tem challenges in controlling and managing CVD in some non-communicable disease interventions for primary health of the EMR countries reemphasize the need for significant care in low-resource settings (PEN). These interventions investment and improvement of access (Roth et al. include a mixture of cost-effective population-wide and 2015a, b; Romdhane et al. 2015; Ahmad et al. 2015). individual approaches to reduce the burden of major non- Our study has some limitations; accurate data on car- communicable diseases, such as methods for early detec- diovascular events (especially non-fatal outcomes) are tion and diagnosis using inexpensive technologies, non- limited in many countries, including the EMR countries. pharmacological and pharmacological approaches for We used the standard GBD methodology by using study- modification of risk factors, and affordable medications for and country-level covariates for adjustment and estimation prevention and treatment of heart attacks and strokes, of epidemiologic measures. Our study does not account for diabetes, cancer, and asthma (World-Health-Organization variation within countries. 2010). Our study showed that increased blood pressure is the most important risk factor for CVD in the EMR, followed by high total cholesterol and high body mass index. 123 S146 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators Epidemiology Unit, Lund University, Lund, Sweden. Muktar Beshir Conclusion Ahmed, MPH, College of Health Sciences, Department of Epidemi- ology, ICT and e-Learning Coordinator, Jimma University, Jimma, Most of the EMR countries have launched programs to Ethiopia. Baran Aksut, MD, Cleveland Clinic, Cleveland, United reduce the burden of non-communicable disease, but they States. Khurshid Alam, PhD, Murdoch Childrens Research Institute, The University of Melbourne, Parkville, Victoria, Australia. The generally do not have widespread programs to combat University of Melbourne, Melbourne, VIC, Australia, The University CVD. This study calls for strengthening efforts to design of Sydney, Sydney, NSW, Australia. Deena Alasfoor, MSc, Ministry and launch comprehensive programs to cover all aspects of of Health, Al Khuwair, Muscat, Oman. Raghib Ali, MSc, University prevention and control of CVDs through evidence-in- of Oxford, Oxford, UK. Reza Alizadeh-Navaei, PhD, Gastrointestinal Cancer Research Center, Mazandaran University of Medical Sci- formed, efficient interventions. The countries should ences, Sari, Iran. Rajaa Al-Raddadi, PhD, Joint Program of Family establish or improve information systems such as surveil- and Community Medicine, Jeddah, Saudi Arabia. Ubai Alsharif, lance sy stems to provide valid and accurate information MPH, Charite ´ Universita ¨tsmedizin, Berlin, Germany. Khalid A. for policymaking and monitoring of the situation. Altirkawi, MD, King Saud University, Riyadh, Saudi Arabia. Nelson Alvis-Guzman, PhD, Universidad de Cartagena, Colombia. Nahla Anber, PhD, Mansoura University, Mansoura, Egypt. Palwasha GBD 2015 Eastern Mediterranean Region Cardiovascular Dis- Anwari, MD, Self-employed, Kabul, Afghanistan. Johan Arnlo ¨ v, ease Collaborators: Ali H. Mokdad, PhD (corresponding author), PhD, Department of Neurobiology, Care Sciences and Society, Institute for Health Metrics and Evaluation, University of Washing- Division of Family Medicine and Primary Care, Karolinska Institutet, ton, Seattle, Washington, United States. Arash Tehrani-Banihashemi, Stockholm, Sweden, School of Health and Social Studies, Dalarna PhD, Preventive Medicine and Public Health Research Center, Iran University, Falun, Sweden. Solomon Weldegebreal Asgedom, PhD, University of Medical Sciences, Tehran, Iran. Maziar Moradi-Lakeh, Mekelle University, Mekelle, Ethiopia. Tesfay Mehari Atey, MS, MD, Department of Community Medicine, Preventive Medicine Mekelle University, Mekelle, Ethiopia. Ashish Awasthi, PhD, Sanjay Public Health Research Center, Gastrointestinal and Liver Disease Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India. Research Center (GILDRC), Iran University of Medical Sciences, Till Barnighausen, MD, Department of Global Health and Population, Tehran, Iran. Charbel El Bcheraoui, PhD, Institute for Health Metrics Harvard T. H. Chan School of Public Health, Harvard University, and Evaluation, University of Washington. Raghid Charara, MD, Boston, MA, United States; Africa Health Research Institute, Mtu- American University of Beirut, Beirut, Lebanon. Ibrahim Khalil, MD, batuba, South Africa; Institute of Public Health, Heidelberg Univer- Institute for Health Metrics and Evaluation, University of Washing- sity, Heidelberg, Germany. Umar Bacha, PhD, School of Health ton. Ashkan Afshin, MD, Institute for Health Metrics and Evaluation, Sciences, University of Management and Technology, Lahore, Pak- University of Washington, Seattle, Washington, United States. istan. Aleksandra Barac, PhD, Faculty of Medicine, University of Michael Collison, BS, Institute for Health Metrics and Evaluation, Belgrade, Belgrade, Serbia. Suzanne L. Barker-Collo, PhD, School of University of Washington, Seattle, Washington, United States. Farah Psychology, University of Auckland, Auckland, New Zealand. Neeraj Daoud, BA/BS, Institute for Health Metrics and Evaluation, Univer- Bedi, MD, College of Public Health and Tropical Medicine, Jazan, sity of Washington. Kristopher J. Krohn, BA, Institute for Health Saudi Arabia. Derrick A. Bennett, PhD, Nuffield Department of Metrics and Evaluation, University of Washington, Seattle, Wash- Population Health, University of Oxford, Oxford, UK. Derbew Fikadu ington, United States. Adrienne Chew, ND, Institute for Health Berhe, MS, School of Pharmacy, Mekelle University, Mekelle, Metrics and Evaluation, University of Washington. Leslie Cornaby, Ethiopia. Sibhatu Biadgilign, MPH, Independent Public Health BS, Institute for Health Metrics and Evaluation, University of Consultants, Addis Ababa, Ethiopia. Zahid A. Butt, PhD, Al Shifa Washington, Seattle, Washington, United States. Kyle J. Foreman, Trust Eye Hospital, Rawalpindi, Pakistan. Jonathan R. Carapetis, PhD, Institute for Health Metrics and Evaluation, University of PhD, Telethon Kids Institute, Princess Margaret Hospital for Chil- Washington, Seattle, Washington, United States. Imperial College dren, The University of Western Australia, Subiaco, Western Aus- London, London, UK. Joseph Frostad, Institute for Health Metrics tralia, Australia. Ruben Estanislao Castro, PhD, Universidad Diego and Evaluation, University of Washington. Nicholas J. Kassebaum, Portales, Santiago, Region Metropolitana, Chile. Abdulaal A. Chith- MD, Institute for Health Metrics and Evaluation, University of eer, MD, Ministry of Health, Baghdad, Iraq. Kairat Davletov, PhD, Washington, Seattle, Washington, United States; Department of Republican Institute of Cardiology and Internal Diseases, Almaty, Anesthesiology and Pain Medicine, Seattle Children’s Hospital, Kazakhstan, School of Public Health, Kazakh National Medical Seattle, Washington, United States. Laura Kemmer, PhD, Institute for University, Almaty, Kazakhstan. Samath D. Dharmaratne, MD, Health Metrics and Evaluation, University of Washington. Michael Department of Community Medicine, Faculty of Medicine, Univer- Kutz, BS, Institute for Health Metrics and Evaluation, University of sity of Peradeniya, Peradeniya, Sri Lanka. Shirin Djalalinia, PhD, Washington. Patrick Liu, BA, Institute for Health Metrics and Eval- Undersecretary for Research and Technology, Ministry of Health and uation, University of Washington. Mojde Mirarefin, MPH, Institute Medical Education, Tehran, Iran. Huyen Phuc Do, MSc, Institute for for Health Metrics and Evaluation, University of Washington, Seattle, Global Health Innovations, Duy Tan University, Da Nang, Vietnam. Washington, United States; Hunger Action Los Angeles, Los Ange- Manisha Dubey, MPhil, International Institute for Population Sci- les, CA, United States. Grant Nguyen, MPH, Institute for Health ences, Mumbai, India. Hedyeh Ebrahimi, MD, Non-communicable Metrics and Evaluation, University of Washington, Seattle, Wash- Diseases Research Center, Tehran University of Medical Sciences, ington, United States. Haidong Wang, PhD, Institute for Health Tehran, Iran; Liver and Pancreaticobiliary Diseases Research Center, Metrics and Evaluation, University of Washington, Seattle, Wash- Digestive Disease Research Institute, Shariati Hospital, Tehran ington, United States. Ben Zipkin, BS, Institute for Health Metrics University of Medical Sciences, Tehran, Tehran, Iran. Babak Eshrati, and Evaluation, University of Washington, Seattle, Washington, PhD, Ministry of Health and Medical Education, Tehran, Iran, Arak United States. Amanuel Alemu Abajobir, MPH, School of Public University of Medical Sciences, Arak, Iran. Alireza Esteghamati, Health, University of Queensland, Brisbane, QLD, Australia. Marian MD, Endocrinology and Metabolism Research Center, Tehran Abouzeid, DPH, Telethon Kids Institute, Perth, Australia. Niveen University of Medical Sciences, Tehran, Iran. Maryam S. Farvid, M.E. Abu-Rmeileh, PhD, Institute of Community and Public Health, PhD, Department of Nutrition, Harvard T. H. Chan School of Public Birzeit University, Ramallah, Palestine. 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Vuong Minh Nong, rian Fischer, PhD, School of Public Health, Bielefeld University, MSc, Institute for Global Health Innovations, Duy Tan University, Da Bielefeld, Germany. Solomon Weldemariam Gebrehiwot, MS, Col- Nang, Vietnam. Jonathan Pearson-Stuttard, MD, Imperial College lege of Health Sciences, Mekelle University, Mekelle, Ethiopia. London, London, UK. Farhad Pishgar, MD, Non-communicable Tsegaye Tewelde Gebrehiwot, MPH, Jimma University, Jimma, Diseases Research Center, Tehran University of Medical Sciences, Ethiopia. Richard F. Gillum, MD, Howard University, Washington, Tehran, Iran; Uro-Oncology Research Center, Tehran University of DC, United States. Philimon N. Gona, PhD, University of Mas- Medical Sciences, Tehran, Iran. Farshad Pourmalek, PhD, University sachusetts Boston, Boston, Massachusetts, United States. Rajeev of British Columbia, Vancouver, British Columbia, Canada. Mostafa Gupta, PhD, Eternal Heart Care Centre and Research Institute, Jaipur, Qorbani, PhD, Non-communicable Diseases Research Center, Alborz India. Nima Hafezi-Nejad, MD, Endocrinology and Metabolism University of Medical Sciences, Karaj, Iran. Amir Radfar, MD, A T Research Center, Tehran University of Medical Sciences, Tehran, Still University, Kirksville, MO, United States. Anwar Rafay, MS, Iran. Randah Ribhi Hamadeh, DPhil, Arabian Gulf University, Contech International Health Consultants, Lahore, Pakistan; Contech Manama, Bahrain. Samer Hamidi, DrPH, Hamdan Bin Mohammed School of Public Health, Lahore, Pakistan. Vafa Rahimi-Movaghar, Smart University, Dubai, United Arab Emirates. Mohamed Hsairi, MD, Sina Trauma and Surgery Research Center, Tehran University of MD, Department of Epidemiology, Salah Azaiz Institute, Tunis, Medical Sciences, Tehran, Iran. Rajesh Kumar Rai, MPH, Society for Tunisia. Sun Ha Jee, PhD, Graduate School of Public Health, Yonsei Health and Demographic Surveillance, Suri, India. Saleem M. Rana, University, Seoul, South Korea. Jost B. Jonas, MD, Department of PhD, Contech School of Public Health, Lahore, Pakistan, Contech Ophthalmology, Medical Faculty Mannheim, Ruprecht-Karls- International Health Consultants, Lahore, Pakistan. David Laith University Heidelberg, Mannheim, Germany. Chante Karimkhani, Rawaf, MD, WHO Collaborating Centre, Imperial College London, MD, Case Western University Hospitals, Cleveland, Ohio, United London, UK, North Hampshire Hospitals, Basingstroke, UK; States. Amir Kasaeian, PhD, Hematology-Oncology and Stem Cell University College London Hospitals, London, UK. Salman Rawaf, Transplantation Research Center, Tehran University of Medical Sci- MD, Imperial College London, London, UK. Andre M. N. Renzaho, ences, Tehran, Iran; Endocrinology and Metabolism Population Sci- PhD, Western Sydney University, Penrith, NSW, Australia. 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Mensah, MD, Center for Translation Research and Implementation nopolis, Brazil. Jasvinder A. Singh, MD, University of Alabama at Science, National Heart, Lung, and Blood Institute, National Insti- Birmingham and Birmingham Veterans Affairs Medical Center, tutes of Health, Bethesda, MD, United States. Atte Meretoja, PhD, Birmingham, Alabama, United States. Badr H. A Sobaih, MD, King Department of Medicine, The University of Melbourne, Melbourne, Saud University, Riyadh, Saudi Arabia. Konstantinos Stroumpoulis, Victoria, Australia, Department of Neurology, Helsinki University PhD, Alexandra General Hospital of Athens, Athens, Greece; Centre Hospital, Helsinki, Finland. Ted R. Miller, PhD, Pacific Institute for Hospitalier Public du Cotentin, Cherbourg, France. Rizwan Sulian- Research and Evaluation, Calverton, MD, United States; Centre for katchi Abdulkader, MD, Ministry of Health, Kingdom of Saudi Population Health, Curtin University, Perth, WA, Australia. Erkin M. Arabia, Riyadh, Saudi Arabia. Cassandra E. I. Szoeke, PhD, Institute Mirrakhimov, PhD, Kyrgyz State Medical Academy, Bishkek, Kyr- of Health and Ageing, The University of Melbourne, Melbourne, gyzstan; National Center of Cardiology and Internal Disease, Victoria, Australia. Mohamad-Hani Temsah, MD, King Saud 123 S148 GBD 2015 Eastern Mediterranean Region Cardiovascular Disease Collaborators University, Riyadh, Saudi Arabia. Bach Xuan Tran, PhD, Johns writing of the paper. The study did not involve human participants Hopkins University, Baltimore, Maryland, United States; Hanoi and/or animals; therefore, no informed consent was needed. Medical University, Hanoi, Vietnam. Kingsley Nnanna Ukwaja, MD, Department of Internal Medicine, Federal Teaching Hospital, Funding This research was funded by the Bill & Melinda Gates Abakaliki, Ebonyi State, Nigeria. Olalekan A. Uthman, PhD, War- Foundation. wick Medical School, University of Warwick, Coventry, UK. Tommi Vasankari, PhD, UKK Institute for Health Promotion Research, Conflict of interest The authors declare that they have no conflicts of Tampere, Finland. Vasiliy Victorovich Vlassov, MD, National interest at this time. Research University Higher School of Economics, Moscow, Russia. Stein Emil Vollset, DrPH, Center for Disease Burden, Norwegian Open Access This article is distributed under the terms of the Institute of Public Health, Bergen, Norway; Department of Global Creative Commons Attribution 4.0 International License (http://crea Public Health and Primary Care, University of Bergen, Bergen, tivecommons.org/licenses/by/4.0/), which permits unrestricted use, Norway; Institute for Health Metrics and Evaluation, University of distribution, and reproduction in any medium, provided you give Washington, Seattle, WA, United States. Tolassa Wakayo, MS, appropriate credit to the original author(s) and the source, provide a Jimma University, Jimma, Ethiopia. Robert G. 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International Journal of Public HealthSpringer Journals

Published: Aug 3, 2017

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