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Special Communication |

Global and National Burden of Diseases and Injuries Among Children and Adolescents Between 1990 and 2013 Findings From the Global Burden of Disease 2013 Study FREE

JAMA Pediatr. 2016;170(3):267-287. doi:10.1001/jamapediatrics.2015.4276.
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Importance  The literature focuses on mortality among children younger than 5 years. Comparable information on nonfatal health outcomes among these children and the fatal and nonfatal burden of diseases and injuries among older children and adolescents is scarce.

Objective  To determine levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged <5 years), older children (aged 5-9 years), and adolescents (aged 10-19 years) between 1990 and 2013 in 188 countries from the Global Burden of Disease (GBD) 2013 study.

Evidence Review  Data from vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14 244 site-years (ie, years of cause of death data by geography) from 1980 through 2013 were used to estimate cause-specific mortality. Data from 35 620 epidemiological sources were used to estimate the prevalence of the diseases and sequelae in the GBD 2013 study. Cause-specific mortality for most causes was estimated using the Cause of Death Ensemble Model strategy. For some infectious diseases (eg, HIV infection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models. For most nonfatal health outcomes, DisMod-MR 2.0, a Bayesian metaregression tool, was used to meta-analyze the epidemiological data to generate prevalence estimates.

Findings  Of the 7.7 (95% uncertainty interval [UI], 7.4-8.1) million deaths among children and adolescents globally in 2013, 6.28 million occurred among younger children, 0.48 million among older children, and 0.97 million among adolescents. In 2013, the leading causes of death were lower respiratory tract infections among younger children (905 059 deaths; 95% UI, 810 304-998 125), diarrheal diseases among older children (38 325 deaths; 95% UI, 30 365-47 678), and road injuries among adolescents (115 186 deaths; 95% UI, 105 185-124 870). Iron deficiency anemia was the leading cause of years lived with disability among children and adolescents, affecting 619 (95% UI, 618-621) million in 2013. Large between-country variations exist in mortality from leading causes among children and adolescents. Countries with rapid declines in all-cause mortality between 1990 and 2013 also experienced large declines in most leading causes of death, whereas countries with the slowest declines had stagnant or increasing trends in the leading causes of death. In 2013, Nigeria had a 12% global share of deaths from lower respiratory tract infections and a 38% global share of deaths from malaria. India had 33% of the world’s deaths from neonatal encephalopathy. Half of the world’s diarrheal deaths among children and adolescents occurred in just 5 countries: India, Democratic Republic of the Congo, Pakistan, Nigeria, and Ethiopia.

Conclusions and Relevance  Understanding the levels and trends of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies. Monitoring these trends over time is also key to understanding where interventions are having an impact. Proven interventions exist to prevent or treat the leading causes of unnecessary death and disability among children and adolescents. The findings presented here show that these are underused and give guidance to policy makers in countries where more attention is needed.

Figures in this Article

The current literature focuses on mortality rates and time trends among children younger than 5 years. There is little comparable information on the fatal and nonfatal burden of diseases and injuries among older children and adolescents. Children and adolescents constitute about a third of the world’s population and their health status is important for every country and society.

Global mortality rates among younger children (aged <5 years) have been declining since 1990, but striking variations in both the levels and trends exist across countries.1,2 For example, the number of deaths in children younger than 5 years per 1000 live births varied from 2.3 (95% uncertainty interval [UI], 1.8-2.9) in Singapore to 152.5 (95% UI, 130.6-177.4) in Guinea-Bissau in 2013.2 The annualized rates of change in mortality of younger children for 1990 through 2013 varied from −6.8% in Oman to 0.1% in Zimbabwe, and only 27 of 138 developing countries are estimated to have achieved the target of Millennium Development Goal 4, a two-thirds reduction of 1990 mortality levels by 2015 (equivalent to an annualized rate of change of −4.4%).2 Although between-country variations in mortality among younger children have been reported, information on nonfatal health outcomes among these children is scarce. Moreover, there has been little systematic data collection and reporting on the fatal and nonfatal burden of diseases and injuries among older children and adolescents. Knowing the current burden and trends of the leading causes of death and disability in these age groups is critically important to shed light on areas that need more attention. In this study, we identified levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged <5 years), older children (aged 5-9 years), and adolescents (defined by the United Nations as those aged 10-19 years3) from 1990 through 2013 in 188 countries based on the results from the Global Burden of Disease (GBD) 2013 study.

Box Section Ref ID

Key Points
  • Question: What are the levels and trends of fatal and nonfatal global burden of diseases and injuries among children and adolescents during the last 2 decades?

  • Findings: Of the 7.7 million deaths among children and adolescents globally in 2013, more than 80% occurred among younger children and, of the 135.6 million years lived with disability, nearly 60% were contributed by adolescents. Developing countries with rapid declines in all-cause mortality between 1990 and 2013 also experienced large declines in mortality for most leading causes of death during the same period, whereas for countries with the slowest declines in all-cause mortality there was either a stagnant or increasing trend in most of the leading causes of death.

  • Meaning: Detailed information on causes of death and nonfatal health outcomes in children and adolescents by age, sex, and country over time is an essential input into policy decision making on resource allocation to disease prevention and treatment programs.

Detailed methods of the GBD study have been published elsewhere1,46 and we provide only a brief description here. The study components relevant to the current article are shown in eFigure 1 in the Supplement.

Cause-specific mortality was estimated using a database of vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14 244 site-years (the number of years for which cause of death data were available for a particular geographic area such as a country or demographic surveillance site) from 1980 to 2013.1 Of the 14 244 site-years, 5039 were from vital registration systems, 3860 from cancer registry, 1798 from sibling history, 1433 from police records, 1430 from surveillance, 538 from verbal autopsy studies, and 146 from other sources including surveys, census, hospital, and burial or mortuary. The quality and comparability of the cause of death data were assessed and enhanced through multiple steps that have been reported in detail previously.1 Sample key steps include developing more than 100 maps to convert causes of death observed in the raw data to the GBD 2013 cause list and identifying deaths being assigned to ill-defined or intermediate causes rather than underlying causes of death, which were redistributed to more specific underlying causes.1,7 Moreover, data that were reported in aggregated categories were split into estimates of age- and sex-specific deaths using the observed global pattern of relative risks of death for a cause by age and sex and the local age and sex distribution of the population.7 Country-specific data sources and citations for each cause and data before and after redistribution are shown in the online data visualization of the cause of death database at http://vizhub.healthdata.org/cod/.8

For most causes, we used the Cause of Death Ensemble Model (CODEm) strategy,1,7,9,10 which has been widely used for generating global health estimates. The CODEm strategy evaluates a large number of potential models that apply different functional forms (mixed-effects models and space-time gaussian process regression models) to mortality rates or cause fractions with varying combinations of predictive covariates. An ensemble of models that performs best on out-of-sample predictive validity tests is selected for each cause of death. For some infectious diseases (eg, human immunodeficiency virus [HIV] infection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models (ie, models developed based on the natural history of diseases). For example, the natural history model for HIV/AIDS took into consideration the nature of HIV epidemics in particular countries as well as HIV mortality rates among those receiving and not receiving antiretroviral therapy, which were not captured in the cause of death data.11 Years of life lost due to premature mortality were calculated by multiplying the number of deaths at each age by a standard life expectancy at that age.1,7

The prevalence of diseases and their disabling consequences, called sequelae in the GBD, were estimated using an epidemiological database compiling data from systematic reviews on prevalence, incidence, remission, mortality risk, and severity distributions of the diseases and injuries included in the GBD. There were 35 620 data sources (mainly covered from 1990-2013) that include studies published in the scientific literature, nationally representative household surveys, antenatal clinic surveillance data, disease notifications, disease registries, hospital admissions data, outpatient visit data, population-based cancer registries, and other administrative data. Household surveys including the Demographic and Health Surveys, Multiple Indicator Cluster Surveys, Living Standards Measurement Studies, Reproductive Health Surveys, and other national health surveys included in the Global Health Data Exchange were systematically screened for relevant data. For some diseases (eg, measles and pertussis), case notifications reported to the World Health Organization up to 2013 were used as input data. A full list of citations for sources organized by country is available in the appendix of a previous GBD article (pages 97-653).5 Epidemiological data for most causes were meta-analyzed with DisMod-MR 2.0,5 a Bayesian metaregression tool that adjusts for variations in study methods between data sources and enforces consistency between data for different parameters such as incidence and prevalence. The tool evaluates all the data through a geographical cascade of 4 levels (global, superregion, region, and country). First, all data in the world are evaluated to estimate the fixed effects on age, sex, study-level, and country-level covariates and the random effects for countries, regions, and superregions (we grouped regions into 7 superregions for analytical purposes4). The outputs of the global level are then used as prior information for the next superregion level of the cascade. After fitting the model to each superregion’s data, the results are fed as priors to the region-specific fits, and finally region fits are used as a prior when modeling a country’s results for a particular period. For countries and periods for which little or no data are available, the estimation is facilitated by country characteristics and random effects on superregion, region, and country. For this purpose, a database of country covariates for 93 topic areas and 242 variants was created using data from household surveys, censuses, official reports, administrative data, and systematic reviews.1,5 The sources and imputation methods used to generate time series for the covariates have been reported previously.1 DisMod-MR 2.0 also allows the user to add strong prior knowledge on the age pattern and/or epidemiological parameters including incidence, remission, and excess mortality rate. For example, major depressive disorder cannot be detected at very young ages, and we set a prior of 0 incidences in children younger than 4 years. The assumptions and priors by individual condition have been reported in the appendix of a previous GBD article (pages 654-684).5 Years lived with disability (YLDs) were computed by multiplying the prevalence of each sequela by a disability weight.5 Because we applied disability weights to prevalence in calculating YLDs, the most prevalent cause of disability (defined as any departure from full health) is not necessarily the leading cause of YLDs. For instance, mild vision impairment and caries are very common but cause relatively little disability.

Disability weights for a set of 235 health states were estimated by pairwise comparison methods presenting pairs of lay health state descriptions to respondents in surveys conducted among the general population in 9 countries and an open web-based survey.12 Each of the 2337 sequelae defined for 301 diseases and injuries mapped to 1 or a combination of the 235 health states. Sequelae are the direct consequences of disease or injury.4 Sequelae that are common across different diseases or injuries are called health states.4 For example, severe anemia due to malaria is a sequela that shares the health state of severe anemia with a number of other diseases such as hookworm disease and maternal hemorrhage. Disability-adjusted life-years (DALYs) were computed as the sum of years of life lost due to premature mortality and YLDs for each country, age, sex, and year. A full list of causes of death and disability and the corresponding International Classification of Diseases, Ninth Revision (ICD-9) and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes have been reported in previous GBD articles.1,5

The GBD classifies countries into developed (Australasia, North America, all of Europe, Brunei, Japan, Singapore, and South Korea) and developing (all other countries) rather than using the World Bank income classification of low-, middle-, and high-income countries. As the income status of a country may change over time, it makes reporting on time series for country groupings with a varying composition more difficult. Although we realize that the inclusion of some countries in either the developed or developing category is controversial, we have opted to use the GBD classification in this article as it illustrates important differences in the levels and trends of mortality and DALY rates between the 2 sets of countries.

Global Mortality and Leading Causes of Death in 2013

In 2013, there were 7.7 (95% UI, 7.4-8.1) million deaths among children and adolescents globally, of which 6.28 million occurred among younger children, 0.48 million among older children, and 0.97 million among adolescents (Table 1, Table 2, and eTables 1-4 in the Supplement).

Table Graphic Jump LocationTable 1.  Number of Deaths and Age-Standardized Rates per 100 000 Children and Adolescents for the Top 10 Global Causes of Death in the 50 Most Populous Countries by Child and Adolescent Population, Aged 0 to 19 Years, Both Sexes, 2013
Table Graphic Jump LocationTable 2.  Number of Deaths and Rates per 100 000 Children and Adolescents for the Top 10 Global Causes of Death in the 50 Most Populous Countries by Child and Adolescent Population, Younger Than 5 Years, Both Sexes, 2013

Among all children and adolescents, the leading causes of death were predominantly those common in younger children (Figure 1, Figure 2, and Figure 3) because of the large share of deaths in children younger than 5 years. The leading causes of death among younger children (aged <5 years) globally in 2013 were lower respiratory tract infections (905 059 deaths; 95% UI, 810 304-998 125), preterm birth complications (742 381 deaths; 95% UI, 591 348-910 767), neonatal encephalopathy following birth trauma and asphyxia (643 765 deaths; 95% UI, 515 010-760 486), malaria (586 844 deaths; 95% UI, 451 969-756 864), and diarrheal diseases (519 666 deaths; 95% UI, 438 795-593 675) (Table 2, Figure 2, and eTable 1 in the Supplement). These 5 causes accounted for 3.4 million deaths or 54% of all deaths among children younger than 5 years. Five other causes accounted for an additional 24% of deaths: congenital anomalies (495 319 deaths; 95% UI, 424 788-590 319), neonatal sepsis (366 041 deaths; 95% UI, 233 155-510 770), other neonatal disorders (276 231 deaths; 95% UI, 219 603-350 681), protein-energy malnutrition (225 906 deaths; 95% UI, 168 497-280 129), and meningitis (141 952 deaths; 95% UI, 105 060-182 518) (Table 2 and eTable 1 in the Supplement). The leading cause of death among younger children in each country in 2013 is shown in a map (eFigure 2 in the Supplement). Lower respiratory tract infections, malaria, and diarrheal diseases were the prevailing leading causes of death in sub-Saharan African countries. Lower respiratory tract infections were also the leading cause for some countries in Asia. Neonatal encephalopathy was the most common cause of death in some South Asian countries. Preterm birth complications and congenital anomalies were the leading causes of death among countries in North America, Australasia, Europe, East Asia, and most countries in Latin America and the Caribbean.

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Figure 1.
Top 25 Global Causes of Death for the 50 Most Populous Countries by Child and Adolescent Population, Both Sexes, Ages 0 to 19 Years, 2013

Colors correspond to the ranking of the leading causes of death, with dark red as the most common cause and dark green as the least common cause for the location indicated. The numbers inside each box indicate the ranking. HIV indicates human immunodeficiency virus infection.

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Figure 2.
Top 25 Global Causes of Death for the 50 Most Populous Countries by Child and Adolescent Population, Both Sexes, Younger Than 5 Years, 2013

Colors correspond to the ranking of the leading causes of death, with dark red as the most common cause and dark green as the least common cause for the location indicated. The numbers inside each box indicate the ranking. HIV indicates human immunodeficiency virus infection.

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Figure 3.
Top Cause of Death by Country for Children and Adolescents Aged 0 to 19 Years, Both Sexes, 2013

Foreign body indicates foreign body in lung and pulmonary aspiration; HIV, human immunodeficiency virus infection; and neonatal encephalopathy, neonatal encephalopathy following birth trauma and asphyxia. ATG indicates Antigua and Barbuda; BRB, Barbados; COM, Comoros; DMA, Dominica; E Med, Eastern Mediterranean; FJI, Fiji; FSM, Federated States of Micronesia; GRD, Grenada; KIR, Kiribati; LCA, Saint Lucia; MDV, Maldives; MHL, Marshall Islands; MLT, Malta; MUS, Mauritius; SGP, Singapore; SLB, Solomon Islands; SYC, Seychelles; TLS, Timor-Leste; TON, Tonga; TTO, Trinidad and Tobago; VCT, Saint Vincent and the Grenadines; VUT, Vanuatu; W Africa, West Africa; and WSM, Samoa.

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Among older children (aged 5-9 years), the most common cause of death in 2013 was diarrheal disease (38 325 deaths; 95% UI, 30 365-47 678), followed by lower respiratory tract infections (37 431 deaths; 95% UI, 30 713-44 837), road injuries (36 577 deaths; 95% UI, 31 097-41 896), intestinal infectious diseases (mainly typhoid and paratyphoid) (36 110 deaths; 95% UI, 20 561-57 277), and malaria (35 212 deaths; 95% UI, 26 187-46 691) (eTable 2 and eFigure 3 in the Supplement). These 5 causes accounted for 181 000 deaths or 39% of deaths among 5- to 9-year-old children. Five other causes accounted for an additional 23% of deaths: drowning (31 500 deaths; 95% UI, 25 452-42 630), HIV/AIDS (28 211 deaths; 95% UI, 26 407-30 307), hemoglobinopathies (20 229 deaths; 95% UI, 6077-42 394), congenital anomalies (17 508 deaths; 95% UI, 14 677-20 722), and meningitis (13 577 deaths; 95% UI, 10 777-16 863) (eTable 2 in the Supplement). Country-specific leading causes of death among children aged 5 to 9 years are shown in eFigure 4 in the Supplement. Road injuries were the leading cause of death for countries in North America, Latin America and the Caribbean, and Australasia, while drowning was the most common cause of death in most countries in Eastern Europe, East Asia, and Southeast Asia. Intestinal infectious diseases and lower respiratory tract infections were the leading causes for countries in South Asia, while diarrheal diseases, HIV/AIDS, and malaria were the leading causes for countries in sub-Saharan Africa.

Among adolescents (aged 10-19 years), the leading cause of death in 2013 was road injuries (115 186 deaths; 95% UI, 105 185-124 870), followed by HIV/AIDS (75 564 deaths; 95% UI, 69 254-82 629), self-harm (59 114 deaths; 95% UI, 47 914-70 864), drowning (51 013 deaths; 95% UI, 43 533-68 179), and intestinal infectious diseases (44 171 deaths; 95% UI, 24 318-72 643) (eTable 3 and eFigure 5 in the Supplement). These 5 leading causes accounted for 34% of all deaths in this age group. Another 5 causes contributed an additional 17% of all deaths: interpersonal violence (38 300 deaths; 95% UI, 27 452-45 009), lower respiratory tract infections (36 190 deaths; 95% UI, 31 124-42 361), diarrheal diseases (32 616 deaths; 95% UI, 26 725-38 766), malaria (30 764 deaths; 95% UI, 25 003-38 940), and tuberculosis (29 257 deaths; 95% UI, 23 880-34 091) (eTable 3 in the Supplement). Country-specific leading causes of death among adolescents in 2013 are shown in eFigure 6 in the Supplement. Injury-related deaths were the leading causes in most countries except for those in sub-Saharan Africa, where HIV/AIDS was the dominant leading cause of death. Self-harm was the most common cause of death for some parts of Asia and Eastern Europe.

Contributions to Global Child and Adolescent Deaths According to Population Proportion

Table 1 shows the number of deaths and age-standardized mortality rates for the 10 leading causes among children and adolescents at the global level and in the 50 countries with the largest child and adolescent populations. In 2013, there were 2.5 billion children and adolescents in the world, and the 50 countries represented 73% of this population (eTable 5 in the Supplement). In 2013, Nigeria had about 4% of the world’s children and adolescents (eTable 5 in the Supplement) but a 12% global share of deaths from lower respiratory tract infections and a 38% global share of deaths from malaria (Table 1). India had nearly 20% of the world’s child and adolescent population but 33% of the world’s deaths from neonatal encephalopathy. Half of the world’s deaths from diarrheal diseases among children and adolescents occurred in just 5 countries: India, Democratic Republic of the Congo, Pakistan, Nigeria, and Ethiopia, which together represented 30% of the world’s pediatric population in 2013 (Table 1 and eTable 5 in the Supplement).

Mortality Time Trends

The global decline in mortality between 1990 and 2013 was faster among younger children (annual percentage change [APC], −3.0%) and older children (APC, −2.9%) than adolescents (APC, −1.6%) (eTables 6-8 in the Supplement). The corresponding APC figures in developing countries were −3.1%, −3.0%, and −1.7%, respectively, and those in developed countries were −3.5%, −3.9%, and −2.5%, respectively (eTables 6-8 in the Supplement).

Among children younger than 5 years, countries in which all-cause mortality declined rapidly experienced these large declines in most of the leading causes of death (eTable 6 in the Supplement). For example, Oman, China, and Maldives, the 3 countries with the fastest declining mortality rates for children younger than 5 years, showed an annual reduction of 5.6% or greater in mortality from at least 6 of the 10 leading causes of death (eTable 6 in the Supplement). Countries with the slowest declines (Vanuatu, Fiji, Swaziland, Lesotho, and Zimbabwe) showed either a stagnant or increasing trend in most of the 10 leading causes (eTable 6 in the Supplement). Similarly, among older children and adolescents, countries with a rapid decline in all-cause mortality experienced greater declines for most of the leading causes of death in these age groups (eTables 7-9 in the Supplement).

Global YLDs and Prevalence of the Leading Causes of Disability

In 2013, disability caused 135.6 million YLDs among children and adolescents, of which 26.4 million affected children younger than 5 years, 29.6 million affected older children, and 79.6 million affected adolescents (data not shown).

Leading causes of YLDs largely overlapped among the 3 age groups. Iron deficiency anemia was the most common cause of YLDs in younger children, older children, and adolescents in 2013 (Table 3 and eTables 10-13 in the Supplement), affecting 619 (95% UI, 618-621) million prevalent cases in 2013. The 50 countries with the largest child and adolescent population contributed to 86% of global iron deficiency anemia cases in this population (Table 3). India contributed the largest number of cases (147.9 million), followed by China (75.8 million) and Nigeria (24.7 million). The prevalence of children and adolescents with iron deficiency anemia was highest in Afghanistan (41.0%), followed by Yemen (39.8%) and Senegal (38.5%) (Table 3 and eTable 13 in the Supplement).

Table Graphic Jump LocationTable 3.  Number of Prevalent Cases and Age-Standardized Rate for the Top 10 Global Causes of Years Lived With Disability in Children and Adolescents in the 50 Most Populous Countries by Child and Adolescent Population, Aged 0 to 19, Both Sexes, 2013

Skin diseases were the second leading cause of YLDs among children and adolescents in 2013 (Table 3). Younger and older children were most commonly affected by viral skin diseases and dermatitis, whereas adolescents were mainly affected by acne vulgaris (data not shown). Depressive disorders were the third most common cause of YLDs among children and adolescents, with the prevalence in adolescents being 4 times as high as that in older children (2.8% vs 0.7%, respectively) (Table 3 and eTables 11 and 12 in the Supplement).

Among other leading causes of YLDs among children and adolescents, conduct disorder, anxiety disorders, low back and neck pain, and migraine mainly affected older children and adolescents, whereas sense organ diseases and hemoglobinopathies affected all 3 age groups (Table 3 and eTables 10-12 in the Supplement). Among sense organ diseases, uncorrected refractive error and hearing loss were the most frequently occurring causes in all 3 age groups (data not shown). The country-, year-, age-, and sex-specific distributions of YLDs for each cause and their subcategories are viewable in an interactive online visualization tool at http://vizhub.healthdata.org/gbd-compare.13

DALYs Among Children and Adolescents

Figure 4 shows DALY rates for leading causes among boys and girls aged 0 to 19 years at the global level and in the 50 countries with the largest child and adolescent populations. Age group–specific leading causes of DALYs are shown in eFigures 7, 8, and 9 in the Supplement. The rankings of leading causes of deaths and DALYs are similar if the percentage of contribution to the disease burden by mortality is high, which is especially the case for the main conditions affecting younger children (Figure 2 and eFigure 7 in the Supplement). Sex differences were small in younger children but larger in some of the causes among adolescents. For instance, transport injuries, drowning, and interpersonal violence among adolescent boys were much higher than among adolescent girls (eFigure 9 in the Supplement). The most striking sex differences were observed in Venezuela, Colombia, and Brazil for interpersonal violence (eFigure 9 in the Supplement). Maternal disorders were common causes of DALYs among adolescent girls in sub-Saharan African and South Asian countries (eFigure 9 in the Supplement).

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Figure 4.
Age-Standardized Rates of Disability-Adjusted Life-Years (DALYs) per 100 000 Children and Adolescents Aged 0 to 19 Years, 2013

Causes are listed in order starting from 0 on the horizontal axes. Developed indicates the rates for developed countries; global, the global rates; and developing, the rates for developing countries. DRC indicates Democratic Republic of the Congo; HIV, human immunodeficiency virus infection; and LRTIs, lower respiratory tract infections.

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Time Trends in DALYs

Among all children and adolescents, the leading causes of DALYs were dominated by those common in children younger than 5 years (Figure 5 and Figure 6), who had the greatest share of deaths. Lower respiratory tract infections remained the leading cause of DALYs among children younger than 5 years in both 1990 and 2013, but the number and rate of DALYs declined during the 23 years by 58% and 59%, respectively (Figure 6). Preterm birth complications and neonatal encephalopathy rose in rank (from third and fourth to second and third, respectively) because of their relatively slower rates of decline than diarrheal diseases, which dropped from second to fifth with a 67% decrease in DALY rates (Figure 6). The rate for measles also notably declined (from 8th to 14th), with an 84% decrease in DALY rates between 1990 and 2013 (Figure 6).

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Figure 5.
Top 25 Global Causes of Disability-Adjusted Life-Years (DALYs) in Children and Adolescents Aged 0 to 19 Years, Both Sexes, 1990 and 2013

Solid lines connecting the 1990 and 2013 charts indicate increased or unchanged rank; dotted lines, decreased rank; COPD, chronic obstructive pulmonary disease; and HIV, human immunodeficiency virus infection.

aCalculated at the 1000 draw level.

bChanges that are statistically significant (P < .05).

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Figure 6.
Top 25 Global Causes of Disability-Adjusted Life-Years (DALYs) in Children Younger Than 5 Years, Both Sexes, 1990 and 2013

Solid lines connecting the 1990 and 2013 charts indicate increased or unchanged rank; dotted lines, decreased rank; COPD, chronic obstructive pulmonary disease; and HIV, human immunodeficiency virus infection.

aCalculated at the 1000 draw level.

bChanges that are statistically significant (P < .05).

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Among older children and adolescents, iron deficiency anemia remained the leading cause of DALYs in both 1990 and 2013, with a modest decrease in the number and rate of DALYs during the 23 years (eFigures 10 and 11 in the Supplement). The rank of HIV/AIDS increased from 101st to 6th among adolescents, 78th to 10th among older children, and 33rd to 17th among younger children between 1990 and 2013, with a statistically significant increase in both DALY counts and rates (Figure 6 and eFigures 10 and 11 in the Supplement). Full details of the results by age, sex, geography, and period can be viewed in the online interactive visualization tool (http://vizhub.healthdata.org/gbd-compare).13

This is the first of a series of annual updates to identify levels and trends in the fatal and nonfatal burden of diseases and injuries among children and adolescents at the country level. Of the 7.7 million deaths among children and adolescents globally in 2013, more than 80% occurred among younger children. Of the 135.6 million YLDs among children and adolescents in 2013, nearly 60% of the YLDs were contributed by adolescents. Leading causes of death among children and adolescents in 2013 fell into 4 main categories: neonatal, congenital, infectious diseases, and injuries. Developing and developed countries had both similarities and differences in the leading causes of death. In both sets of countries, preterm birth complications and congenital anomalies were common causes of death among children younger than 5 years, whereas injuries were major causes of death in adolescents. Infectious diseases including lower respiratory tract infections, neonatal sepsis, malaria, diarrheal diseases, HIV/AIDS, typhoid, and tuberculosis remained major challenges in developing nations. In several countries, vaccine-preventable diseases such as measles and pertussis were still among the 10 leading causes of death, indicating a need to strengthen immunization programs in those countries. Leading causes of YLDs largely overlapped among the 3 age groups, with iron deficiency anemia and skin diseases being the first and second most common causes of YLDs among children and adolescents.

Trends from the leading causes of death in younger children varied widely across countries. Countries with greater declines in all-cause child mortality tended to have a rapid decline in mortality rates for most of the main causes of death, suggesting that general improvements in health services and public health interventions for a wide range of health problems (eg, improved management of childhood illnesses, immunization, mass distribution of insecticide-treated bed nets, and improved access to prenatal, obstetric, and postnatal care) rather than single disease programs determine success. The declines in poverty levels and improvements in living conditions over time might have also contributed to the declines in mortality. Countries with slowly declining or stagnant trends in all-cause mortality in children younger than 5 years generally showed similar trends in mortality rates for the leading causes. Most of these deaths, especially in developing countries, could be prevented by a concerted response from health systems and public health interventions.

The typical leading causes of death in younger children such as lower respiratory tract infections and diarrheal diseases were also common causes of death for older children in many developing countries, indicating that interventions targeting the former should extend to cover the latter. Mortality and DALY rates for lower respiratory tract infections and diarrheal diseases declined during the past 23 years, but they were still among the top 5 causes for both younger and older children in 2013. In fact, lower respiratory tract infections were the first leading cause of death among younger children, whereas diarrheal diseases were the most common cause of death among older children. These deaths are largely avoidable through case identification and proper management and prevention of risk factors. Unsafe water, sanitation, and hand-washing practices are largely responsible for diarrheal disease–related deaths, whereas household air pollution and ambient air pollution are important risk factors for deaths from lower respiratory tract infections in both younger and older children, with undernutrition being an additional key risk factor for both lower respiratory tract infections and diarrheal diseases among younger children.14 Proven interventions1517 exist to reduce exposures to these risk factors but uptake is insufficient.

The decline in all-cause mortality rates among adolescents between 1990 and 2013 was slower than that among younger and older children. Road injuries were the leading cause of death among adolescents globally, with a stagnant or increasing trend in most developing countries. Many countries inadequately implement proven road safety practices (eg, safety measures for road users and vehicles, road infrastructure, and postcrash care).18 With increasing motorization, these trends are likely to worsen unless decisive action is taken.

Self-harm was the second most common cause of injury-related death among adolescents. While the most common suicidal methods differ across geography, restricting access to common lethal means has proven to be effective in reducing suicide rates.19,20 For example, pesticide ingestion is a commonly used method of suicide among young people in developing countries.21 Prohibition of toxic pesticides in Sri Lanka and South Korea has been shown to reduce both the overall and method-specific suicide rates.22,23 National suicide prevention strategies can play a role in preventing suicide, but such strategies are lacking in many countries worldwide.20 Mental and substance use disorders contributed to two-thirds of all suicide DALYs in the world, indicating the importance of early detection and effective management of these disorders as part of suicide prevention strategies.24

Drowning was among the 10 leading causes of death among older children and adolescents and the 14th leading cause of death among younger children in 2013. Lack of barriers to water sites and absence of close supervision are key risk factors for drowning among younger children in both developing and developed countries.25,26 Older children and adolescents usually drown during nonrecreational or daily activities in developing countries but during recreational activities in developed countries.27 Risk of death from drowning is especially high in rural areas in developing countries, where unfenced water sources are close to the homes, without any emergency medical care facilities or capacity to perform resuscitation for the drowning child.25,27 In developed countries, failure to wear life jackets during boating activities and alcohol use among adolescents during water-related recreation are among the risk factors for drowning.26,27

In addition to injuries, infectious diseases were important causes of death among adolescents in developing countries, especially HIV/AIDS, lower respiratory tract infections, intestinal infectious diseases, diarrheal diseases, malaria, and tuberculosis. The mortality rates for all these diseases except HIV/AIDS are decreasing. Deaths from HIV/AIDS among adolescents are concentrated in sub-Saharan Africa and have been increasing since 1990. This trend differs from that in all age groups, where it increased after 1990, peaked around 2005, and then declined steadily after antiretroviral treatment became more widely available.11 Low rates of HIV testing, an important step toward HIV treatment, and poor access to antiretroviral treatment among adolescents28 might explain some of the increases in HIV/AIDS mortality in this age group. Although much emphasis has been placed on prevention of HIV infection among adolescents, little attention has been given to the care of those who were infected during infancy.29 High rates of children orphaned by HIV/AIDS, the necessity of guardian consent to undergo HIV testing, and the lack of clear policies and guidance regarding consent and HIV testing among minors are some of the barriers to HIV testing and care for older children and adolescents.29,30

Leading causes of disability among all children and adolescents were dominated by causes common in adolescents because of a larger share of YLDs by this age group. However, iron deficiency anemia, the largest cause of disability, is common in both younger and older children and adolescents. The high demand of nutrients for growth, blood loss during menstruation in adolescent girls, and hookworm infections (especially in developing countries) put children and adolescents at risk for this deficiency. Although iron supplementation is effective, challenges exist in terms of distribution, cost, and compliance.31 Other cost-effective interventions exist, including food fortification and biofortification of crops, with the latter being a way of reaching rural populations with limited access to marketed fortified foods.31,32

Compared with changes in the causes of mortality that are generally showing decreasing rates in all age groups,1 there are smaller changes, if at all, in the prevalence of many causes of disability (data not shown). The slow decline in disabling conditions is not specific to children and adolescents but a more common feature across the age span.5 Major depressive disorder, conduct disorder, and anxiety disorders were major causes of disability among older children and adolescents in 2013. Whereas identification and treatment of these disorders are important, prevention of modifiable risk factors such as child abuse and neglect, bullying, and intimate partner violence should also be a priority.33 Other common causes of disability such as low back and neck pain, migraine, and skin disorders also showed little change. Musculoskeletal disorders have drawn more attention since the GBD 2010 study, but there is still limited policy discussion on the approaches to deal with and/or prevent the leading causes of low back and neck pain.5,34,35 Migraine and other headache disorders generally attract low health care priority despite the disability attributed to them.36

The general limitations of the GBD study also apply to this report. These limitations have been discussed widely and in detail in the published GBD 2013 articles and we summarize the relevant limitations here.1,2,5,6,11 First, there were variations in the instrument used for collection of verbal autopsy data, which might reduce the between-country comparability of cause of death data. Moreover, the quality of the medical certification of causes of death (eg, diagnostic accuracy) might have also influenced our estimates. Second, although redistribution of ill-defined or intermediate causes to specific underlying causes improved the comparability of cause of death data, it could yield results different from official statistics of countries. This could happen because the redistribution used global or regional algorithms, which did not pick up variations across countries in terms of certification practices or the timing of implementation of coding rules. We plan to use more country-specific redistribution algorithms in future rounds of the GBD study. Third, the fact that the sum of cause-specific mortality estimates must equal all-cause mortality for a particular country, age, sex, and year is a strength of the GBD study approach, but it also has a limitation. Causes of death with very wide UIs (eg, hemoglobinopathies) tend to be adjusted downward relative to causes with narrower UIs. Fourth, in general, the epidemiological data coverage for the period 2006 to 2013 was relatively lower than the period 1998 to 2005, although there were variations by disease. For example, the percentages of countries that have epidemiological data on low back and neck pain for the periods 1998 to 2005 and 2006 to 2013 were 41.5% and 13.3%, respectively. The lower coverage for the latter might be explained by the lag in data collection, analyses, and publications.5 For some diseases such as tuberculosis, the data coverage is higher for the recent years (91.5% for the period 1998-2005 vs 98.4% for 2006-2013). A systematic quantification of the geographical and temporal coverage of the input epidemiological data by cause has been reported in detail previously.5 Making estimates for every country over time is challenging especially for those with little or no data. We had to make use of sophisticated modeling techniques to borrow strength across geography and covariates to help predict for countries and years with sparse data. The lack of data for a particular geography is reflected by wider UIs. Finally, for some causes of disability, long-term consequences in later years of life are not reflected in this article. For example, long-term impairments due to preterm birth complications, neonatal encephalopathy, and Down syndrome after age 19 years were not counted in the DALY rankings because we focused only on the burden of disease experienced by those aged 0 to 19 years.

Understanding the levels and trends as well as geography of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies. Monitoring these trends over time is also key to understanding where interventions are having an effect and where more attention is needed. The vast majority of deaths in children and adolescents are preventable. Proven interventions exist to prevent diarrheal and respiratory diseases, neonatal conditions, iron deficiency anemia, and road injuries, which result in some of the highest burdens of unnecessary death and disability among children and adolescents. The findings presented herein show that these and other available interventions are underused and point to where more attention is needed. The findings indicate that proven health interventions could save millions of lives. Despite the general decline in mortality, the speed of the decline could still be faster.

Corresponding Author: Theo Vos, PhD, MSc, Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Ave, Ste 600, Seattle, WA 98121 (tvos@uw.edu).

Accepted for Publication: November 18, 2015.

Published Online: January 25, 2016. doi:10.1001/jamapediatrics.2015.4276.

The Global Burden of Disease Pediatrics Collaboration: Hmwe H. Kyu, MBBS, MPH, PhD; Christine Pinho, BA; Joseph A. Wagner, BS; Jonathan C. Brown, BA, MAIS; Amelia Bertozzi-Villa, BA; Fiona J. Charlson, MPH; Luc Edgar Coffeng, MD, PhD; Lalit Dandona, MPH, MD; Holly E. Erskine, BPsySc; Alize J. Ferrari, BPsySc, PhD; Christina Fitzmaurice, MD, MPH; Thomas D. Fleming, BS; Mohammad H. Forouzanfar, MD; Nicholas Graetz, BS; Caterina Guinovart, MD, PhD; Juanita Haagsma, MSc, PhD; Hideki Higashi, PhD; Nicholas J. Kassebaum, MD; Heidi J. Larson, MA, PhD; Stephen S. Lim, BA, BSc, PhD; Ali H. Mokdad, PhD; Maziar Moradi-Lakeh, MD, MPH; Shaun V. Odell, MD; Gregory A. Roth, MD, MPH; Peter T. Serina, MPH; Jeffrey D. Stanaway, PhD; Awoke Misganaw, PhD; Harvey A. Whiteford, MBBS, PhD; Timothy M. Wolock, BA; Sarah Wulf Hanson, BS, MPH; Foad Abd-Allah, MD; Semaw Ferede Abera, BSc, MSc; Laith J. Abu-Raddad, PhD; Fadia S. AlBuhairan, MD; Azmeraw T. Amare, MSc, MPH, MPHM; Carl Abelardo T. Antonio, MD, MPH; Al Artaman, PhD, MD, MHA; Suzanne L. Barker-Collo, PhD; Lope H. Barrero, BE, MSc, ScD; Corina Benjet, PhD; Isabela M. Bensenor, MD, PhD; Zulfiqar A. Bhutta, MBBS, DCH, MRCP, FCPS, FRCP, PhD, FRCPCH; Boris Bikbov, PhD, MD; Alexandra Brazinova, MD, PhD, MPH; Ismael Campos-Nonato, MSc, PhD, MD; Carlos A. Castañeda-Orjuela, MSc, MD; Ferrán Catalá-López, PhD, MPH; Rajiv Chowdhury, MD, PhD; Cyrus Cooper, FMedSci, MD; John A. Crump, MBChB, MD, DTM&H; Rakhi Dandona, PhD; Louisa Degenhardt, BA, PhD, MPsychology (Clinical); Robert P. Dellavalle, MD, PhD, MSPH; Samath D. Dharmaratne, MBBS, MSc, MD; Emerito Jose A. Faraon, BSPH, MD, MBA; Valery L. Feigin, MD, PhD; Thomas Fürst, MA, PhD; Johanna M. Geleijnse, PhD; Bradford D. Gessner, MD, MPH; Katherine B. Gibney, MPH, MBBS, BMedSci, FRACP, FAFPHM; Atsushi Goto, MD, PhD, MPH; David Gunnell, MBChB, PhD, DSc; Graeme J. Hankey, MD, FRACP, FRCP, FRCPE, MBBS; Roderick J. Hay, MA, DM, FRCP, FRCPath; John C. Hornberger, MD, MS; H. Dean Hosgood, MPH, PhD; Guoqing Hu, PhD; Kathryn H. Jacobsen, MPH, PhD; Sudha P. Jayaraman, MD, MSc; Panniyammakal Jeemon, PhD, MPH; Jost B. Jonas, MD; André Karch, MD, MSc; Daniel Kim, MD, DrPH; Sungroul Kim, MS, PhD; Yoshihiro Kokubo, PhD, MD, FESC, FESO; Barthelemy Kuate Defo, BS, MS, DEA, MPH, PhD; Burcu Kucuk Bicer, PhD, MD; G. Anil Kumar, PhD; Anders Larsson, MD, PhD; Janet L. Leasher, OD, MPH; Ricky Leung, PhD; Yongmei Li, BA, MPH, PhD; Steven E. Lipshultz, MD; Alan D. Lopez, MS, PhD; Paulo A. Lotufo, MD, DrPH; Raimundas Lunevicius, MD, PhD, DSc; Ronan A. Lyons, MD; Marek Majdan, PhD; Reza Malekzadeh, MD; Taufiq Mashal, MD, PhD; Amanda J. Mason-Jones, PhD, MPH, MSc, BA; Yohannes Adama Melaku, BSc, MPH; Ziad A. Memish, MD, FRCPC; Walter Mendoza, MD; Ted R. Miller, PhD; Charles N. Mock, MD, PhD; Joseph Murray, BA, MPhil, PhD; Sandra Nolte, BA, PhD; In-Hwan Oh, MPH, PhD, MD; Bolajoko Olubukunola Olusanya, MBBS, FMCPaed, FRCPCH, PhD; Katrina F. Ortblad, MPH; Eun-Kee Park, MS, PhD; Angel J. Paternina Caicedo, MD, MSc; Scott B. Patten, MD, PhD; George C. Patton, MD, MBBS; David M. Pereira, MsC, PhD; Norberto Perico, MD; Frédéric B. Piel, PhD; Suzanne Polinder, PhD; Svetlana Popova, MD, PhD, MPH; Farshad Pourmalek, MPH, PhD, MD; D. Alex Quistberg, PhD, MPH; Giuseppe Remuzzi, MD; Alina Rodriguez, PhD; David Rojas-Rueda, MPH, PhD, MD; Dietrich Rothenbacher, MD, MPH; David H. Rothstein, MD, MS; Juan Sanabria, MD, MSc, FRCSC; Itamar S. Santos, PhD, MD; David C. Schwebel, PhD; Sadaf G. Sepanlou, MPH, PhD, MD; Amira Shaheen, PhD; Rahman Shiri, MPH, PhD, MD; Ivy Shiue, MS, PhD; Vegard Skirbekk, PhD; Karen Sliwa, MD, PhD; Chandrashekhar T. Sreeramareddy, MBBS, MD, MSc; Dan J. Stein, PhD, MD; Timothy J. Steiner, MB, BS, PhD; Lars Jacob Stovner, PhD; Bryan L. Sykes, MA, PhD; Karen M. Tabb, PhD, MSW; Abdullah Sulieman Terkawi, MD; Alan J. Thomson, BSc, MSc, PhD, DLSHTM; Andrew L. Thorne-Lyman, ScD, MHS, BA; Jeffrey Allen Towbin, BS, MS, MD; Kingsley Nnanna Ukwaja, MD; Tommi Vasankari, MD, PhD; Narayanaswamy Venketasubramanian, MBBS, MMed, MSc, DLHTM, MHlthSc, FRCP; Vasiliy Victorovich Vlassov, MD; Stein Emil Vollset, MD, DrPH; Elisabete Weiderpass, MD, MSc, PhD; Robert G. Weintraub, MB, BS; Andrea Werdecker, Dipl.oec.troph; James D. Wilkinson, MD, MPH; Solomon Meseret Woldeyohannes, BSc, MPH; Charles D. A. Wolfe, MBBS, MRCOG, MD, MFPH, FFPH, FRCOG; Yuichiro Yano, PhD, MD; Paul Yip, PhD; Naohiro Yonemoto, MPH; Seok-Jun Yoon, MD, PhD; Mustafa Z. Younis, DrPH, MA, MBA; Chuanhua Yu, PhD; Maysaa El Sayed Zaki, MD; Mohsen Naghavi, PhD; Christopher J. L. Murray, DPhil; Theo Vos, PhD, MSc.

Affiliations of The Global Burden of Disease Pediatrics Collaboration: Institute for Health Metrics and Evaluation, University of Washington, Seattle (Kyu, Pinho, Wagner, Brown, Bertozzi-Villa, Charlson, Coffeng, L. Dandona, Erskine, Ferrari, Fitzmaurice, Fleming, Forouzanfar, Graetz, Guinovart, Haagsma, Higashi, Kassebaum, Larson, Lim, Mokdad, Moradi-Lakeh, Roth, Serina, Stanaway, Misganaw, Whiteford, Wolock, Wulf Hanson, Naghavi, C. J. L. Murray, Vos); School of Public Health, University of Queensland, Brisbane, Australia (Charlson, Erskine, Ferrari, Whiteford); Queensland Centre for Mental Health Research, Brisbane, Australia (Charlson, Erskine, Ferrari, Whiteford); Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands (Coffeng, Haagsma, Polinder); Public Health Foundation of India, New Delhi, India (L. Dandona, R. Dandona, Kumar); Division of Hematology, Department of Medicine, University of Washington, Seattle (Fitzmaurice); Fred Hutchinson Cancer Research Center, Seattle, Washington (Fitzmaurice); Department of Anesthesiology and Pain Medicine, Seattle Children’s Hospital, Seattle, Washington (Kassebaum); Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, England (Larson); Department of Community Medicine, Iran University of Medical Sciences, Tehran, Iran (Moradi-Lakeh); University of Washington Medical Center, Seattle (Odell); Seattle Children’s Hospital, Seattle, Washington (Odell); Intermountain Healthcare, Salt Lake City, Utah (Odell); Department of Neurology, Cairo University, Cairo, Egypt (Abd-Allah); Kilte Awlaelo Health and Demographic Surveillance Site, Mekelle, Ethiopia (Abera); School of Public Health, College of Health Sciences, Mekelle University, Mekelle, Ethiopia (Abera, Melaku); Infectious Disease Epidemiology Group, Weill Cornell Medical College in Qatar, Doha, Qatar (Abu-Raddad); King Abdullah Specialized Children’s Hospital, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia (AlBuhairan); King Abdullah International Medical Research Center, Riyadh, Saudi Arabia (AlBuhairan); Department of Epidemiology, University of Groningen, Groningen, the Netherlands (Amare); College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia (Amare); Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, Australia (Amare); Department of Health Policy and Administration, College of Public Health, University of the Philippines Manila, Manila, Philippines (Antonio, Faraon); Consultant, Windsor, Ontario, Canada (Artaman); School of Psychology, University of Auckland, Auckland, New Zealand (Barker-Collo); Department of Industrial Engineering, School of Engineering, Pontificia Universidad Javeriana, Bogotá, Colombia (Barrero); National Institute of Psychiatry Ramon de la Fuente, Mexico City, Mexico (Benjet); University of São Paulo, São Paulo, Brazil (Bensenor, Lotufo); Medical Center, Aga Khan University, Karachi, Pakistan (Bhutta); The Hospital for Sick Children, Toronto, Ontario, Canada (Bhutta); A. I. Evdokimov Moscow State University of Medicine and Dentistry, Moscow, Russia (Bikbov); Academician V. I. Shumakov Federal Research Center of Transplantology and Artificial Organs, Moscow, Russia (Bikbov); International Neurotrama Research Organization, Vienna, Austria (Brazinova); Faculty of Health Sciences and Social Work, Trnava University, Trnava, Slovakia (Brazinova, Majdan); National Institute of Public Health, Cuernavaca, Mexico (Campos-Nonato); School of Public Health, Harvard University, Boston, Massachusetts (Campos-Nonato); Colombian National Health Observatory, Instituto Nacional de Salud, Bogotá, Colombia (Castañeda-Orjuela); Epidemiology and Public Health Evaluation Group, Public Health Department, Universidad Nacional de Colombia, Bogotá, Colombia (Castañeda-Orjuela); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada (Catalá-López); Department of Medicine, University of Valencia, INCLIVA/CIBERSAM, Valencia, Spain (Catalá-López); Department of Public Health and Primary Care, University of Cambridge, Cambridge, England (Chowdhury); MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, England (Cooper); National Institute for Health Research Biomedical Research Centre, University of Southampton and University Hospital Southampton National Health Service Foundation Trust, Southampton, England (Cooper); National Institute for Health Research Musculoskeletal Biomedical Research Centre, University of Oxford, Oxford, England (Cooper); Centre for International Health, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand (Crump); National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia (Degenhardt); University of Colorado School of Medicine and the Colorado School of Public Health, Aurora (Dellavalle); Department of Community Medicine, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka (Dharmaratne); Office for Technical Services, Department of Health, Manila, Philippines (Faraon); National Institute for Stroke and Applied Neurosciences, Auckland University of Technology, Auckland, New Zealand (Feigin); Department of Infectious Disease Epidemiology, Imperial College London, London, England (Fürst); Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands (Geleijnse); Agence de Medecine Preventive, Paris, France (Gessner); Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Gibney); Melbourne Health, Parkville, Australia (Gibney); Department of Public Health, Tokyo Women’s Medical University, Tokyo, Japan (Goto); School of Social and Community Medicine, University of Bristol, Bristol, England (Gunnell); School of Medicine and Pharmacology, University of Western Australia, Perth, Australia (Hankey); Harry Perkins Institute of Medical Research, Nedlands, Australia (Hankey); Western Australian Neuroscience Research Institute, Nedlands, Australia (Hankey); International Foundation for Dermatology, London, England (Hay); King’s College London, London, England (Hay); Cedar Associates, Menlo Park, California (Hornberger); Stanford University, Stanford, California (Hornberger); Albert Einstein College of Medicine, Bronx, New York (Hosgood); Department of Epidemiology and Health Statistics, School of Public Health, Central South University, Changsha, China (Hu); George Mason University, Fairfax, Virginia (Jacobsen); Department of Surgery, Virginia Commonwealth University, Richmond (Jayaraman); Centre for Chronic Disease Control, New Delhi, India (Jeemon); Centre for Control of Chronic Conditions, Public Health Foundation of India, New Delhi, India (Jeemon); Department of Ophthalmology, Medical Faculty Mannheim, Ruprecht-Karls-Universität Heidelberg, Mannheim, Germany (Jonas); Epidemiological and Statistical Methods Research Group, Helmholtz Centre for Infection Research, Braunschweig, Germany (Karch); Hannover-Braunschweig Site, German Center for Infection Research, Braunschweig, Germany (Karch); Department of Health Sciences, Northeastern University, Boston, Massachusetts (D. Kim); Soonchunhyang University, Seoul, South Korea (S. Kim); Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita, Japan (Kokubo); Department of Social and Preventive Medicine, School of Public Health, University of Montreal, Montreal, Québec, Canada (Kuate Defo); Department of Demography, University of Montreal, Montreal, Québec, Canada (Kuate Defo); Public Health Research Institute, University of Montreal, Montreal, Québec, Canada (Kuate Defo); Institute of Public Health, Hacettepe University, Ankara, Turkey (Kucuk Bicer); Department of Medical Sciences, Uppsala University, Uppsala, Sweden (Larsson); Nova Southeastern University College of Optometry, Fort Lauderdale, Florida (Leasher); State University of New York at Albany, Rensselaer (Leung); Genentech, South San Francisco, California (Li); School of Medicine, Wayne State University, Detroit, Michigan (Lipshultz, Wilkinson); Children’s Hospital of Michigan, Detroit (Lipshultz, Wilkinson); Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia (Lopez); Aintree University Hospital National Health Service Foundation Trust, Liverpool, England (Lunevicius); School of Medicine, University of Liverpool, Liverpool, England (Lunevicius); Farr Institute, Swansea University, Swansea, Wales (Lyons); Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran (Malekzadeh, Sepanlou); Ministry of Public Health, Kabul, Afghanistan (Mashal); Department of Health Sciences, University of York, York, England (Mason-Jones); School of Public Health, Mekelle University, Mekelle, Ethiopia (Melaku); School of Medicine, University of Adelaide, Adelaide, Australia (Melaku); Saudi Ministry of Health, Riyadh, Saudi Arabia (Memish); College of Medicine, Alfaisal University, Riyadh, Saudi Arabia (Memish); United Nations Population Fund, Lima, Peru (Mendoza); Pacific Institute for Research and Evaluation, Calverton, Maryland (Miller); Centre for Population Health Research, Curtin University, Perth, Australia (Miller); Harborview Injury Prevention and Research Center, University of Washington, Seattle (Mock, Quistberg); Department of Psychiatry, University of Cambridge, Cambridge, England (J. Murray); Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin, Berlin, Germany (Nolte); Population Health Strategic Research Centre, School of Health and Social Development, Deakin University, Melbourne, Australia (Nolte); Department of Preventive Medicine, School of Medicine, Kyung Hee University, Seoul, South Korea (Oh); Center for Healthy Start Initiative, Ikoyi, Nigeria (Olusanya); Harvard T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts (Ortblad); Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan, South Korea (Park); Universidad de Cartagena, Cartagena, Colombia (Paternina Caicedo); Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada (Patten); Murdoch Childrens Research Institute, University of Melbourne, Melbourne, Australia (Patton); REQUIMTE/LAQV, Laboratório de Farmacognosia, Departamento de Química, Faculdade de Farmácia, Universidade do Porto, Porto, Portugal (Pereira); Istituto di Ricovero e Cura a Carattere Scientifico, Mario Negri Institute for Pharmacological Research, Bergamo, Italy (Perico); Department of Zoology, University of Oxford, Oxford, England (Piel); Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada (Popova); School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (Pourmalek); Department of Pediatrics, University of Washington, Seattle (Quistberg); Centro Anna Maria Astori, Istituto di Ricovero e Cura a Carattere Scientifico, Mario Negri Institute for Pharmacological Research, Bergamo, Italy (Remuzzi); Azienda Ospedaliera Papa Giovanni XXIII, Bergamo, Italy (Remuzzi); Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, England (Rodriguez); Mid Sweden University, Östersund, Sweden (Rodriguez); Centre for Research in Environmental Epidemiology, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain (Rojas-Rueda); Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany (Rothenbacher); Department of Pediatric Surgery, Women and Children’s Hospital of Buffalo, Buffalo, New York (Rothstein); Department of Surgery, University at Buffalo, State University of New York, Buffalo (Rothstein); Case Western Reserve University, Cleveland, Ohio (Sanabria); Chicago Medical School, Rosalind Franklin University of Medicine and Science, Cancer Treatment Centers of America, North Chicago, Illinois (Sanabria); Internal Medicine Department, University of São Paulo, São Paulo, Brazil (Santos); University of Alabama at Birmingham, Birmingham (Schwebel); Department of Public Health, An-Najah National University, Nablus, Palestine (Shaheen); Finnish Institute of Occupational Health, Helsinki, Finland (Shiri); School of Health Sciences, University of Tampere, Tampere, Finland (Shiri); Health and Life Sciences, Northumbria University, Newcastle upon Tyne, England (Shiue); Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, Scotland (Shiue); Columbia University, New York, New York (Skirbekk); Faculty of Health Sciences, Hatter Institute for Cardiovascular Research in Africa, University of Cape Town, Cape Town, South Africa (Sliwa); Department of Community Medicine, International Medical University, Kuala Lumpur, Malaysia (Sreeramareddy); Department of Psychiatry, University of Cape Town, Cape Town, South Africa (Stein); South African Medical Research Council Unit on Anxiety and Stress Disorders, Cape Town, South Africa (Stein); Division of Brain Sciences, Imperial College London, London, England (Steiner); Department of Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway (Steiner, Stovner); Norwegian Advisory Unit on Headache, St Olavs Hospital, Trondheim, Norway (Stovner); Department of Criminology, Law and Society, University of California, Irvine (Sykes); Department of Sociology, University of California, Irvine (Sykes); Department of Public Health, University of California, Irvine (Sykes); School of Social Work, University of Illinois at Urbana-Champaign, Champaign (Tabb); Department of Anesthesiology, University of Virginia, Charlottesville (Terkawi); Outcomes Research Consortium, Cleveland Clinic, Cleveland, Ohio (Terkawi); Department of Anesthesiology, King Fahad Medical City, Riyadh, Saudi Arabia (Terkawi); Adaptive Knowledge Management, Victoria, British Columbia, Canada (Thomson); Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts (Thorne-Lyman); WorldFish, Penang, Malaysia (Thorne-Lyman); Le Bonheur Children’s Hospital, Memphis, Tennessee (Towbin); University of Tennessee Health Science Center, Memphis (Towbin); St Jude Children’s Research Hospital, Memphis, Tennessee (Towbin); Department of Internal Medicine, Federal Teaching Hospital, Abakaliki, Nigeria (Ukwaja); UKK Institute for Health Promotion Research, Tampere, Finland (Vasankari); Raffles Neuroscience Centre, Raffles Hospital, Singapore, Singapore (Venketasubramanian); National Research University Higher School of Economics, Moscow, Russia (Vlassov); Norwegian Institute of Public Health, Oslo, Norway (Vollset); Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway (Vollset); Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden (Weiderpass); Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway (Weiderpass); Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway (Weiderpass); Genetic Epidemiology Group, Folkhälsan Research Center, Helsinki, Finland (Weiderpass); University of Melbourne, Melbourne, Australia (Weintraub); Royal Children’s Hospital, Melbourne, Australia (Weintraub); Murdoch Childrens Research Institute, Melbourne, Australia (Weintraub); Competence Center Mortality Follow-up of the German National Cohort, Federal Institute for Population Research, Wiesbaden, Germany (Werdecker); Department of Epidemiology and Biostatistics, Institute of Public Health, University of Gondar, Gondar, Ethiopia (Woldeyohannes); Division of Health and Social Care Research, King’s College London, London, England (Wolfe); National Institute for Health Research Comprehensive Biomedical Research Centre, Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London, London, England (Wolfe); Department of Preventive Medicine, Northwestern University, Chicago, Illinois (Yano); Social Work and Social Administration Department, University of Hong Kong, Hong Kong, China (Yip); Hong Kong Jockey Club Centre for Suicide Research and Prevention, University of Hong Kong, Hong Kong, China (Yip); National Center of Neurology and Psychiatry, Kodaira, Japan (Yonemoto); Department of Preventive Medicine, College of Medicine, Korea University, Seoul, South Korea (Yoon); Jackson State University, Jackson, Mississippi (Younis); Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China (Yu); Global Health Institute, Wuhan University, Wuhan, China (Yu); Mansoura Faculty of Medicine, Mansoura, Egypt (El Sayed Zaki).

Author Contributions: Drs Kyu and Vos had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Kyu, Brown, Forouzanfar, Kassebaum, Mokdad, Barker-Collo, Kokubo, Lyons, Malekzadeh, Mashal, Miller, Shiue, Skirbekk, Weiderpass, C. J. L. Murray, Vos.

Acquisition, analysis, or interpretation of data: Kyu, Pinho, Wagner, Bertozzi-Villa, Charlson, Coffeng, L. Dandona, Erskine, Ferrari, Fitzmaurice, Fleming, Forouzanfar, Graetz, Guinovart, Haagsma, Higashi, Kassebaum, Larson, Lim, Mokdad, Moradi-Lakeh, Odell, Roth, Serina, Stanaway, Misganaw, Whiteford, Wolock, Wulf Hanson, Abd-Allah, Abera, Abu-Raddad, AlBuhairan, Amare, Antonio, Artaman, Barker-Collo, Barrero, Benjet, Bensenor, Bhutta, Bikbov, Brazinova, Campos-Nonato, Castañeda-Orjuela, Catalá-López, Chowdhury, Cooper, Crump, R. Dandona, Degenhardt, Dellavalle, Dharmaratne, Faraon, Feigin, Fürst, Geleijnse, Gessner, Gibney, Goto, Gunnell, Hankey, Hay, Hornberger, Hosgood, Hu, Jacobsen, Jayaraman, Jeemon, Jonas, Karch, D. Kim, S. Kim, Kuate Defo, Kucuk Bicer, Kumar, Larsson, Leasher, Leung, Li, Lipshultz, Lopez, Lotufo, Lunevicius, Majdan, Malekzadeh, Mason-Jones, Melaku, Memish, Mendoza, Miller, Mock, J. Murray, Nolte, Oh, Olusanya, Ortblad, Park, Paternina Caicedo, Patten, Patton, Pereira, Perico, Piel, Polinder, Popova, Pourmalek, Quistberg, Remuzzi, Rodriguez, Rojas-Rueda, Rothenbacher, Rothstein, Sanabria, Santos, Schwebel, Sepanlou, Shaheen, Shiri, Shiue, Sliwa, Sreeramareddy, Stein, Steiner, Stovner, Sykes, Tabb, Terkawi, Thomson, Thorne-Lyman, Towbin, Ukwaja, Vasankari, Venketasubramanian, Vlassov, Vollset, Weiderpass, Weintraub, Werdecker, Wilkinson, Woldeyohannes, Wolfe, Yano, Yip, Yonemoto, Yoon, Younis, Yu, El Sayed Zaki, Naghavi, Vos.

Drafting of the manuscript: Kyu, Pinho, Fleming, Dharmaratne, Faraon, Jayaraman, S. Kim, Olusanya, Pereira, Skirbekk, Tabb, Weiderpass, Vos.

Critical revision of the manuscript for important intellectual content: Kyu, Wagner, Brown, Bertozzi-Villa, Charlson, Coffeng, L. Dandona, Erskine, Ferrari, Fitzmaurice, Forouzanfar, Graetz, Guinovart, Haagsma, Higashi, Kassebaum, Larson, Lim, Mokdad, Moradi-Lakeh, Odell, Roth, Serina, Stanaway, Misganaw, Whiteford, Wolock, Wulf Hanson, Abd-Allah, Abera, Abu-Raddad, AlBuhairan, Amare, Antonio, Artaman, Barker-Collo, Barrero, Benjet, Bensenor, Bhutta, Bikbov, Brazinova, Campos-Nonato, Castañeda-Orjuela, Catalá-López, Chowdhury, Cooper, Crump, R. Dandona, Degenhardt, Dellavalle, Feigin, Fürst, Geleijnse, Gessner, Gibney, Goto, Gunnell, Hankey, Hay, Hornberger, Hosgood, Hu, Jacobsen, Jayaraman, Jeemon, Jonas, Karch, D. Kim, S. Kim, Kokubo, Kuate Defo, Kucuk Bicer, Kumar, Larsson, Leasher, Leung, Li, Lipshultz, Lopez, Lotufo, Lunevicius, Lyons, Majdan, Malekzadeh, Mashal, Mason-Jones, Melaku, Memish, Mendoza, Miller, Mock, J. Murray, Nolte, Oh, Olusanya, Ortblad, Park, Paternina Caicedo, Patten, Patton, Pereira, Perico, Piel, Polinder, Popova, Pourmalek, Quistberg, Remuzzi, Rodriguez, Rojas-Rueda, Rothenbacher, Rothstein, Sanabria, Santos, Schwebel, Sepanlou, Shaheen, Shiri, Shiue, Sliwa, Sreeramareddy, Stein, Steiner, Stovner, Sykes, Tabb, Terkawi, Thomson, Thorne-Lyman, Towbin, Ukwaja, Vasankari, Venketasubramanian, Vlassov, Vollset, Weiderpass, Weintraub, Werdecker, Wilkinson, Woldeyohannes, Wolfe, Yano, Yip, Yonemoto, Yoon, Younis, Yu, El Sayed Zaki, Naghavi, C. J. L. Murray, Vos.

Statistical analysis: Kyu, Pinho, Bertozzi-Villa, Charlson, Coffeng, Erskine, Ferrari, Fitzmaurice, Fleming, Forouzanfar, Graetz, Guinovart, Haagsma, Higashi, Kassebaum, Lim, Moradi-Lakeh, Odell, Roth, Serina, Stanaway, Whiteford, Wolock, Wulf Hanson, Abera, Amare, Jeemon, Karch, S. Kim, Kuate Defo, Larsson, Ortblad, Park, Pereira, Sreeramareddy, Sykes, Thomson, Weiderpass, Woldeyohannes, Yip, Younis, Yu, Naghavi, Vos.

Obtained funding: Mokdad, Barker-Collo, Lyons, Memish, Weiderpass.

Administrative, technical, or material support: Pinho, Wagner, Brown, L. Dandona, Higashi, Kassebaum, Mokdad, Whiteford, Abd-Allah, Abera, Barker-Collo, Bensenor, Campos-Nonato, Catalá-López, Chowdhury, R. Dandona, Hay, Hosgood, Jonas, Kokubo, Kucuk Bicer, Kumar, Larsson, Leung, Lopez, Malekzadeh, Mashal, Melaku, Mock, Olusanya, Paternina Caicedo, Pereira, Quistberg, Rojas-Rueda, Shaheen, Shiue, Sliwa, Terkawi, Thorne-Lyman, Ukwaja, Vasankari, Weiderpass, El Sayed Zaki.

Study supervision: Kyu, Brown, Coffeng, Kassebaum, Lim, Mokdad, Cooper, Crump, Jeemon, S. Kim, Lipshultz, Olusanya, Remuzzi, Sanabria, Shiue, Weiderpass, Wilkinson, El Sayed Zaki, C. J. L. Murray, Vos.

Conflict of Interest Disclosures: Dr Kassebaum reported receiving personal fees and nonfinancial support from Vifor Pharmaceuticals, Axon Communications LLC, and Merck & Co outside the submitted work. Dr Gibney was awarded the National Health and Medical Research Council Gustav Nossal Postgraduate Award sponsored by CSL; this award is peer reviewed and CSL had no part in selecting the awardee. Prof Lotufo reported receiving honoraria from Abbvie for 1 lecture. Prof Santos reported receiving a grant from São Paulo Research Foundation/FAPESP for research purposes. Dr Stein reported receiving research grants and/or consultancy honoraria from AMBRF, Biocodex, Cipla, Lundbeck, National Responsible Gambling Foundation, Novartis, Servier, and Sun in the past 3 years. No other disclosures were reported.

Funding/Support: The Institute for Health Metrics and Evaluation was supported by the Bill and Melinda Gates Foundation. Dr Catalá-López was supported in part by grant PROMETEOII/2015/021 from Generalitat Valenciana. Dr Fitzmaurice was supported by grant 5T32HL007093-40 from the National Institutes of Health. Dr J. Murray was supported by grant 089963/Z/09/Z from the Wellcome Trust.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The United Nations Population Fund does not necessarily endorse the study.

Additional Contributions: Adrienne Chew, ND, BA, Brent Christofferson, BA, Rachel Fortunati, BA, William Heisel, BA, Kate Muller, MPH, Kevin O’Rourke, MFA, Amanda Pain, MPH, MSW, Kelsey Pierce, BA, Logan Sandar, BS, and Caitlyn Steiner, MPH, Institute for Health Metrics and Evaluation, Seattle, Washington, contributed to the production of the manuscript; they received no compensation. Katharine Looker, PhD, University of Bristol, Bristol, England, provided herpes simplex virus 2 seroprevalence data, which inform the work; Dr Looker’s work was funded by the World Health Organization. We thank all contributors to the Global Burden of Disease 2013 study.

Naghavi  M, Wang  H, Lozano  R,  et al; GBD 2013 Mortality and Causes of Death Collaborators.  Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;385(9963):117-171.
PubMed   |  Link to Article
Wang  H, Liddell  CA, Coates  MM,  et al.  Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9947):957-979.
PubMed   |  Link to Article
United Nations Children’s Fund (UNICEF). The State of the World’s Children 2011: Adolescence: An Age of Opportunity. New York, NY: United Nations Children’s Fund; 2011. http://www.unicef.org/sowc2011/pdfs/SOWC-2011-Main-Report_EN_02092011.pdf. Accessed May 28, 2015.
Murray  CJL, Ezzati  M, Flaxman  AD,  et al.  GBD 2010: design, definitions, and metrics. Lancet. 2012;380(9859):2063-2066.
PubMed   |  Link to Article
Vos  T, Barber  RM, Bell  B,  et al.  Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries for 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386(9995):743-800. doi:10.1016/S0140-6736(15)60692-4.
Link to Article
Murray  CJ, Barber  RM, Foreman  KJ,  et al; GBD DALYs and HALE Collaborators.  Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition [published online August 27, 2015]. Lancet. doi:10.1016/S0140-6736(15)61340-X.
Lozano  R, Naghavi  M, Foreman  K,  et al.  Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2095-2128.
PubMed   |  Link to Article
Institute for Health Metrics and Evaluation. Cause of death (COD) visualization. http://vizhub.healthdata.org/cod/. Accessed December 10, 2015.
Foreman  KJ, Lozano  R, Lopez  AD, Murray  CJ.  Modeling causes of death: an integrated approach using CODEm. Popul Health Metr. 2012;10:1.
PubMed   |  Link to Article
Ortblad  KF, Lozano  R, Murray  CJL.  The burden of HIV: insights from the Global Burden of Disease Study 2010. AIDS. 2013;27(13):2003-2017.
PubMed   |  Link to Article
Murray  CJ, Ortblad  KF, Guinovart  C,  et al.  Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9947):1005-1070.
PubMed   |  Link to Article
Salomon  JA, Haagsma  JA, Davis  A,  et al.  Disability weights for the Global Burden of Disease 2013 study. Lancet Glob Health. 2015;3(11):e712-e723.
PubMed   |  Link to Article
Institute for Health Metrics and Evaluation. GBD compare. http://vizhub.healthdata.org/gbd-compare/. Accessed December 10, 2015.
Forouzanfar  MH, Alexander  L, Anderson  HR,  et al; GBD 2013 Risk Factors Collaborators.  Global, regional and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013 [published online September 10, 2015]. Lancet. doi:10.1016/S0140-6736(15)00128-2.
World Health Organization. Interventions to reduce indoor air pollution. http://www.who.int/indoorair/interventions/en/. Accessed December 10, 2015.
Smith  LC, Haddad  L.  Reducing child undernutrition: past drivers and priorities for the post-MDG era. World Dev. 2015;68:180-204. doi:10.1016/j.worlddev.2014.11.014.
Link to Article
World Health Organization. Air pollution. http://www.who.int/ipcs/assessment/public_health/air_pollution/en/. Accessed December 10, 2015.
World Health Organization. Global status report on road safety 2013. http://www.who.int/violence_injury_prevention/road_safety_status/2013/en/. Accessed June 1, 2015.
Mann  JJ, Apter  A, Bertolote  J,  et al.  Suicide prevention strategies: a systematic review. JAMA. 2005;294(16):2064-2074.
PubMed   |  Link to Article
World Health Organization. Preventing suicide: a global imperative. http://www.who.int/mental_health/suicide-prevention/world_report_2014/en/. Accessed December 10, 2015.
Gunnell  D, Eddleston  M, Phillips  MR, Konradsen  F.  The global distribution of fatal pesticide self-poisoning: systematic review. BMC Public Health. 2007;7:357.
PubMed   |  Link to Article
Gunnell  D, Fernando  R, Hewagama  M, Priyangika  WDD, Konradsen  F, Eddleston  M.  The impact of pesticide regulations on suicide in Sri Lanka. Int J Epidemiol. 2007;36(6):1235-1242.
PubMed   |  Link to Article
Myung  W, Lee  G-H, Won  H-H,  et al.  Paraquat prohibition and change in the suicide rate and methods in South Korea. PLoS One. 2015;10(6):e0128980.
PubMed   |  Link to Article
Ferrari  AJ, Norman  RE, Freedman  G,  et al.  The burden attributable to mental and substance use disorders as risk factors for suicide: findings from the Global Burden of Disease Study 2010. PLoS One. 2014;9(4):e91936.
PubMed   |  Link to Article
World Health Organization. Global Report on Drowning: Preventing a Leading Killer. Geneva, Switzerland: World Health Organization; 2014. http://www.who.int/violence_injury_prevention/publications/drowning_global_report/Final_report_full_web.pdf. Accessed August 14, 2015.
Centers for Disease Control and Prevention. Unintentional drowning: get the facts. http://www.cdc.gov/HomeandRecreationalSafety/Water-Safety/waterinjuries-factsheet.html. Accessed August 14, 2015.
Linnan  M, Rahman  A, Scarr  J,  et al. Child Drowning: Evidence for a Newly Recognized Cause of Child Mortality in Low and Middle Income Countries in Asia. Florence, Italy: UNICEF Office of Research; 2012.
Idele  P, Gillespie  A, Porth  T,  et al.  Epidemiology of HIV and AIDS among adolescents: current status, inequities, and data gaps. J Acquir Immune Defic Syndr. 2014;66(suppl 2):S144-S153.
PubMed   |  Link to Article
Ferrand  R, Lowe  S, Whande  B,  et al.  Survey of children accessing HIV services in a high prevalence setting: time for adolescents to count? Bull World Health Organ. 2010;88(6):428-434.
PubMed   |  Link to Article
Kranzer  K, Meghji  J, Bandason  T,  et al.  Barriers to provider-initiated testing and counselling for children in a high HIV prevalence setting: a mixed methods study. PLoS Med. 2014;11(5):e1001649.
PubMed   |  Link to Article
Ramsay  LC, Charles  CV. Review of iron supplementation and fortification. In: Claborn  D, ed. Topics in Public Health. Rijeka, Croatia: InTech; 2015.
Bouis  H, Low  J, McEwan  M, Tanumihardjo  S. Biofortification: evidence and lessons learned linking agriculture and nutrition. http://www.fao.org/fileadmin/user_upload/agn/pdf/Biofortification_paper.pdf. Accessed August 14, 2015.
Erskine  HE, Moffitt  TE, Copeland  WE,  et al.  A heavy burden on young minds: the global burden of mental and substance use disorders in children and youth. Psychol Med. 2015;45(7):1551-1563.
PubMed   |  Link to Article
Vos  T, Flaxman  AD, Naghavi  M,  et al.  Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2163-2196.
PubMed   |  Link to Article
Hoy  D, Geere  J-A, Davatchi  F, Meggitt  B, Barrero  LH.  A time for action: opportunities for preventing the growing burden and disability from musculoskeletal conditions in low- and middle-income countries. Best Pract Res Clin Rheumatol. 2014;28(3):377-393.
PubMed   |  Link to Article
World Health Organization. Atlas of headache disorders and resources in the world 2011. http://www.who.int/mental_health/management/atlas_headache_disorders/en/. Accessed July 30, 2015.

Figures

Place holder to copy figure label and caption
Figure 1.
Top 25 Global Causes of Death for the 50 Most Populous Countries by Child and Adolescent Population, Both Sexes, Ages 0 to 19 Years, 2013

Colors correspond to the ranking of the leading causes of death, with dark red as the most common cause and dark green as the least common cause for the location indicated. The numbers inside each box indicate the ranking. HIV indicates human immunodeficiency virus infection.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Top 25 Global Causes of Death for the 50 Most Populous Countries by Child and Adolescent Population, Both Sexes, Younger Than 5 Years, 2013

Colors correspond to the ranking of the leading causes of death, with dark red as the most common cause and dark green as the least common cause for the location indicated. The numbers inside each box indicate the ranking. HIV indicates human immunodeficiency virus infection.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.
Top Cause of Death by Country for Children and Adolescents Aged 0 to 19 Years, Both Sexes, 2013

Foreign body indicates foreign body in lung and pulmonary aspiration; HIV, human immunodeficiency virus infection; and neonatal encephalopathy, neonatal encephalopathy following birth trauma and asphyxia. ATG indicates Antigua and Barbuda; BRB, Barbados; COM, Comoros; DMA, Dominica; E Med, Eastern Mediterranean; FJI, Fiji; FSM, Federated States of Micronesia; GRD, Grenada; KIR, Kiribati; LCA, Saint Lucia; MDV, Maldives; MHL, Marshall Islands; MLT, Malta; MUS, Mauritius; SGP, Singapore; SLB, Solomon Islands; SYC, Seychelles; TLS, Timor-Leste; TON, Tonga; TTO, Trinidad and Tobago; VCT, Saint Vincent and the Grenadines; VUT, Vanuatu; W Africa, West Africa; and WSM, Samoa.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 4.
Age-Standardized Rates of Disability-Adjusted Life-Years (DALYs) per 100 000 Children and Adolescents Aged 0 to 19 Years, 2013

Causes are listed in order starting from 0 on the horizontal axes. Developed indicates the rates for developed countries; global, the global rates; and developing, the rates for developing countries. DRC indicates Democratic Republic of the Congo; HIV, human immunodeficiency virus infection; and LRTIs, lower respiratory tract infections.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 5.
Top 25 Global Causes of Disability-Adjusted Life-Years (DALYs) in Children and Adolescents Aged 0 to 19 Years, Both Sexes, 1990 and 2013

Solid lines connecting the 1990 and 2013 charts indicate increased or unchanged rank; dotted lines, decreased rank; COPD, chronic obstructive pulmonary disease; and HIV, human immunodeficiency virus infection.

aCalculated at the 1000 draw level.

bChanges that are statistically significant (P < .05).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 6.
Top 25 Global Causes of Disability-Adjusted Life-Years (DALYs) in Children Younger Than 5 Years, Both Sexes, 1990 and 2013

Solid lines connecting the 1990 and 2013 charts indicate increased or unchanged rank; dotted lines, decreased rank; COPD, chronic obstructive pulmonary disease; and HIV, human immunodeficiency virus infection.

aCalculated at the 1000 draw level.

bChanges that are statistically significant (P < .05).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Number of Deaths and Age-Standardized Rates per 100 000 Children and Adolescents for the Top 10 Global Causes of Death in the 50 Most Populous Countries by Child and Adolescent Population, Aged 0 to 19 Years, Both Sexes, 2013
Table Graphic Jump LocationTable 2.  Number of Deaths and Rates per 100 000 Children and Adolescents for the Top 10 Global Causes of Death in the 50 Most Populous Countries by Child and Adolescent Population, Younger Than 5 Years, Both Sexes, 2013
Table Graphic Jump LocationTable 3.  Number of Prevalent Cases and Age-Standardized Rate for the Top 10 Global Causes of Years Lived With Disability in Children and Adolescents in the 50 Most Populous Countries by Child and Adolescent Population, Aged 0 to 19, Both Sexes, 2013

References

Naghavi  M, Wang  H, Lozano  R,  et al; GBD 2013 Mortality and Causes of Death Collaborators.  Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;385(9963):117-171.
PubMed   |  Link to Article
Wang  H, Liddell  CA, Coates  MM,  et al.  Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9947):957-979.
PubMed   |  Link to Article
United Nations Children’s Fund (UNICEF). The State of the World’s Children 2011: Adolescence: An Age of Opportunity. New York, NY: United Nations Children’s Fund; 2011. http://www.unicef.org/sowc2011/pdfs/SOWC-2011-Main-Report_EN_02092011.pdf. Accessed May 28, 2015.
Murray  CJL, Ezzati  M, Flaxman  AD,  et al.  GBD 2010: design, definitions, and metrics. Lancet. 2012;380(9859):2063-2066.
PubMed   |  Link to Article
Vos  T, Barber  RM, Bell  B,  et al.  Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries for 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386(9995):743-800. doi:10.1016/S0140-6736(15)60692-4.
Link to Article
Murray  CJ, Barber  RM, Foreman  KJ,  et al; GBD DALYs and HALE Collaborators.  Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition [published online August 27, 2015]. Lancet. doi:10.1016/S0140-6736(15)61340-X.
Lozano  R, Naghavi  M, Foreman  K,  et al.  Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2095-2128.
PubMed   |  Link to Article
Institute for Health Metrics and Evaluation. Cause of death (COD) visualization. http://vizhub.healthdata.org/cod/. Accessed December 10, 2015.
Foreman  KJ, Lozano  R, Lopez  AD, Murray  CJ.  Modeling causes of death: an integrated approach using CODEm. Popul Health Metr. 2012;10:1.
PubMed   |  Link to Article
Ortblad  KF, Lozano  R, Murray  CJL.  The burden of HIV: insights from the Global Burden of Disease Study 2010. AIDS. 2013;27(13):2003-2017.
PubMed   |  Link to Article
Murray  CJ, Ortblad  KF, Guinovart  C,  et al.  Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9947):1005-1070.
PubMed   |  Link to Article
Salomon  JA, Haagsma  JA, Davis  A,  et al.  Disability weights for the Global Burden of Disease 2013 study. Lancet Glob Health. 2015;3(11):e712-e723.
PubMed   |  Link to Article
Institute for Health Metrics and Evaluation. GBD compare. http://vizhub.healthdata.org/gbd-compare/. Accessed December 10, 2015.
Forouzanfar  MH, Alexander  L, Anderson  HR,  et al; GBD 2013 Risk Factors Collaborators.  Global, regional and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013 [published online September 10, 2015]. Lancet. doi:10.1016/S0140-6736(15)00128-2.
World Health Organization. Interventions to reduce indoor air pollution. http://www.who.int/indoorair/interventions/en/. Accessed December 10, 2015.
Smith  LC, Haddad  L.  Reducing child undernutrition: past drivers and priorities for the post-MDG era. World Dev. 2015;68:180-204. doi:10.1016/j.worlddev.2014.11.014.
Link to Article
World Health Organization. Air pollution. http://www.who.int/ipcs/assessment/public_health/air_pollution/en/. Accessed December 10, 2015.
World Health Organization. Global status report on road safety 2013. http://www.who.int/violence_injury_prevention/road_safety_status/2013/en/. Accessed June 1, 2015.
Mann  JJ, Apter  A, Bertolote  J,  et al.  Suicide prevention strategies: a systematic review. JAMA. 2005;294(16):2064-2074.
PubMed   |  Link to Article
World Health Organization. Preventing suicide: a global imperative. http://www.who.int/mental_health/suicide-prevention/world_report_2014/en/. Accessed December 10, 2015.
Gunnell  D, Eddleston  M, Phillips  MR, Konradsen  F.  The global distribution of fatal pesticide self-poisoning: systematic review. BMC Public Health. 2007;7:357.
PubMed   |  Link to Article
Gunnell  D, Fernando  R, Hewagama  M, Priyangika  WDD, Konradsen  F, Eddleston  M.  The impact of pesticide regulations on suicide in Sri Lanka. Int J Epidemiol. 2007;36(6):1235-1242.
PubMed   |  Link to Article
Myung  W, Lee  G-H, Won  H-H,  et al.  Paraquat prohibition and change in the suicide rate and methods in South Korea. PLoS One. 2015;10(6):e0128980.
PubMed   |  Link to Article
Ferrari  AJ, Norman  RE, Freedman  G,  et al.  The burden attributable to mental and substance use disorders as risk factors for suicide: findings from the Global Burden of Disease Study 2010. PLoS One. 2014;9(4):e91936.
PubMed   |  Link to Article
World Health Organization. Global Report on Drowning: Preventing a Leading Killer. Geneva, Switzerland: World Health Organization; 2014. http://www.who.int/violence_injury_prevention/publications/drowning_global_report/Final_report_full_web.pdf. Accessed August 14, 2015.
Centers for Disease Control and Prevention. Unintentional drowning: get the facts. http://www.cdc.gov/HomeandRecreationalSafety/Water-Safety/waterinjuries-factsheet.html. Accessed August 14, 2015.
Linnan  M, Rahman  A, Scarr  J,  et al. Child Drowning: Evidence for a Newly Recognized Cause of Child Mortality in Low and Middle Income Countries in Asia. Florence, Italy: UNICEF Office of Research; 2012.
Idele  P, Gillespie  A, Porth  T,  et al.  Epidemiology of HIV and AIDS among adolescents: current status, inequities, and data gaps. J Acquir Immune Defic Syndr. 2014;66(suppl 2):S144-S153.
PubMed   |  Link to Article
Ferrand  R, Lowe  S, Whande  B,  et al.  Survey of children accessing HIV services in a high prevalence setting: time for adolescents to count? Bull World Health Organ. 2010;88(6):428-434.
PubMed   |  Link to Article
Kranzer  K, Meghji  J, Bandason  T,  et al.  Barriers to provider-initiated testing and counselling for children in a high HIV prevalence setting: a mixed methods study. PLoS Med. 2014;11(5):e1001649.
PubMed   |  Link to Article
Ramsay  LC, Charles  CV. Review of iron supplementation and fortification. In: Claborn  D, ed. Topics in Public Health. Rijeka, Croatia: InTech; 2015.
Bouis  H, Low  J, McEwan  M, Tanumihardjo  S. Biofortification: evidence and lessons learned linking agriculture and nutrition. http://www.fao.org/fileadmin/user_upload/agn/pdf/Biofortification_paper.pdf. Accessed August 14, 2015.
Erskine  HE, Moffitt  TE, Copeland  WE,  et al.  A heavy burden on young minds: the global burden of mental and substance use disorders in children and youth. Psychol Med. 2015;45(7):1551-1563.
PubMed   |  Link to Article
Vos  T, Flaxman  AD, Naghavi  M,  et al.  Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2163-2196.
PubMed   |  Link to Article
Hoy  D, Geere  J-A, Davatchi  F, Meggitt  B, Barrero  LH.  A time for action: opportunities for preventing the growing burden and disability from musculoskeletal conditions in low- and middle-income countries. Best Pract Res Clin Rheumatol. 2014;28(3):377-393.
PubMed   |  Link to Article
World Health Organization. Atlas of headache disorders and resources in the world 2011. http://www.who.int/mental_health/management/atlas_headache_disorders/en/. Accessed July 30, 2015.

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