The adoption of new medical technologies often generates losses in efficiency associated with the excess or insufficient acquisition of new equipment, an inappropriate choice (in terms of economic and clinical parameters) of medical equipment, and its poor use. Russia is a good example for exploring the problem of the ineffective adoption of new medical technologies due to the massive public investment in new equipment for medical institutions in 2006–2013. This study examines the procurement of new technologies in Russian hospitals to find the main causes of inefficiency. The research strategy was based on in-depth semistructured interviews with representatives of prominent actors (regional health care authorities, hospital executives, senior physicians). The main result is that inefficiencies arise from the contradiction between hospitals’ and authorities’ motivation for acquiring new technologies: hospitals tend to adopt technologies which bring benefits to their department heads and physicians and minimize maintenance and servicing costs, while the authorities’ main concern is the initial cost of the technology.
The Russian health care system retains the main characteristics of medical care delivery in the Soviet Union. However the transition from socialism to capitalism in the 90s and the economic growth in the 2000s had a significant impact on accessibility of medical care.
Using data collected in 7 local Russian communities in 2011-2015 we discovered several kinds of relationships between legislative and executive branches of local government. In most cases the executive branches clearly dominate over the legislative ones. The ratio of resources and the politics of federal and regional authorities allow us to consider this pattern of relationship as a norm, while others types of relationships are exceptions. Configurations of power resources and instruments of influence used to exercise control over the legislative bodies significantly vary and provide different variations of local government interactions: “domination based on coercion”, “bargaining from the position of strength”, “domination based on persuasion”, “domination under confrontation”. Alternative forms of relationships (“quasi-domination of local legislature”, “temporary parity under confrontation”, “alliance in the face of "external threat"”) occur when the executive bodies are headed by inadequate and/or inexperienced leaders unable to realize the high power potential of their position. This reflects the important role of personalism and the relative weakness of the institutional framework in Russia’s urban politics.
The book is designed for political and social scientists as well as for those interested in the issues of governance and urban politics.
The chapter is based on the outcomes on empirical study in 5 small Russian towns. The process of building coalitions between municipal and business elites is discussed. Several types of coalitions are singled out and analyzed: coalitions with "our people", coalitions with "non-local", electoral coalitions, coalitions for personal gain, coalitions for the sake of the public good.
Background Timely assessment of HIV/AIDS burden is essential for policy-setting and program evaluation. Based on the Global Burden of Disease study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, ART coverage and mortality for 195 countries and territories from 1980 to 2015. Methods For countries without high quality vital registration data, we estimated prevalence and incidence from antenatal clinic data and population-based sero-prevalence surveys and assumptions by age and sex on initial CD4 distribution at infection, CD4 progression rates, on and off antiretroviral therapy mortality (ART), and mortality from all other causes. Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally consistent. Estimation of incidence, prevalence and death uses GBD versions of the EPP and Spectrum software originally developed by UNAIDS. These versions have been recoded for speed and use updated assumptions from systematic reviews of the literature and GBD demographic data. For countries with high quality vital registration data, we developed the Cohort Incidence Bias Adjustment model to estimate HIV incidence and prevalence largely from the number of deaths due to HIV recorded in cause of death statistics. Cause of death statistics have been corrected for garbage coding and HIV misclassification. Findings Globally, HIV incidence reached its peak in 1997 at 3.3 million. Annual incidence has stayed relatively constant at about 2.5 million since 2005 after a period of faster decline between 1997 and 2005. The number of people living with HIV/AIDS has been steadily increasing and reached 38.8 million in 2015. At the same time, mortality due to HIV/AIDS has been declining at a steady pace from its peak at 1.8 million deaths in 2005 to 1.2 million deaths in 2015. There is substantial heterogeneity in the levels and trends of HIV/AIDS across countries. While success stories can be found in many countries with improved mortality due to HIV/AIDS and declines in annual new infections, slowdowns or increases in rate of change in annual new infections has been observed elsewhere. Manuscript Interpretation The global scale-up of ART and PMTCT has been one of the great successes of global health in the last two decades. In the last decade, progress reducing new infections has been very slow, development assistance for health devoted to HIV has stagnated, and low-income country resources for health have grown slowly. New ambitious goals for HIV enshrined in Sustainable Development Goal 3 and the 90-90- 90 UNAIDS targets will be hard to achieve
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.
The contribution of modifiable risk factors to the increasing global and regional burden of stroke is unclear, but knowledge about this contribution is crucial for informing stroke prevention strategies. We used data from the Global Burden of Disease Study 2013 (GBD 2013) to estimate the population-attributable fraction (PAF) of stroke-related disability-adjusted life-years (DALYs) associated with potentially modifiable environmental, occupational, behavioural, physiological, and metabolic risk factors in different age and sex groups worldwide and in high-income countries and low-income and middle-income countries, from 1990 to 2013.
We used data on stroke-related DALYs, risk factors, and PAF from the GBD 2013 Study to estimate the burden of stroke by age and sex (with corresponding 95% uncertainty intervals [UI]) in 188 countries, as measured with stroke-related DALYs in 1990 and 2013. We evaluated attributable DALYs for 17 risk factors (air pollution and environmental, dietary, physical activity, tobacco smoke, and physiological) and six clusters of risk factors by use of three inputs: risk factor exposure, relative risks, and the theoretical minimum risk exposure level. For most risk factors, we synthesised data for exposure with a Bayesian meta-regression method (DisMod-MR) or spatial-temporal Gaussian process regression. We based relative risks on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks, such as high body-mass index (BMI), through other risks, such as high systolic blood pressure (SBP) and high total cholesterol.
Globally, 90·5% (95% UI 88·5–92·2) of the stroke burden (as measured in DALYs) was attributable to the modifiable risk factors analysed, including 74·2% (95% UI 70·7–76·7) due to behavioural factors (smoking, poor diet, and low physical activity). Clusters of metabolic factors (high SBP, high BMI, high fasting plasma glucose, high total cholesterol, and low glomerular filtration rate; 72·4%, 95% UI 70·2–73·5) and environmental factors (air pollution and lead exposure; 33·4%, 95% UI 32·4–34·3) were the second and third largest contributors to DALYs. Globally, 29·2% (95% UI 28·2–29·6) of the burden of stroke was attributed to air pollution. Although globally there were no significant differences between sexes in the proportion of stroke burden due to behavioural, environmental, and metabolic risk clusters, in the low-income and middle-income countries, the PAF of behavioural risk clusters in males was greater than in females. The PAF of all risk factors increased from 1990 to 2013 (except for second-hand smoking and household air pollution from solid fuels) and varied significantly between countries.
Our results suggest that more than 90% of the stroke burden is attributable to modifiable risk factors, and achieving control of behavioural and metabolic risk factors could avert more than three-quarters of the global stroke burden. Air pollution has emerged as a significant contributor to global stroke burden, especially in low-income and middle-income countries, and therefore reducing exposure to air pollution should be one of the main priorities to reduce stroke burden in these countries.
Bill & Melinda Gates Foundation, American Heart Association, US National Heart, Lung, and Blood Institute, Columbia University, Health Research Council of New Zealand, Brain Research New Zealand Centre of Research Excellence, and National Science Challenge, Ministry of Business, Innovation and Employment of New Zealand.
Cancer is the second leading cause of death worldwide. Current estimates on the burden of cancer are needed for cancer control planning.
To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 32 cancers in 195 countries and territories from 1990 to 2015.
Cancer mortality was estimated using vital registration system data, cancer registry incidence data (transformed to mortality estimates using separately estimated mortality to incidence [MI] ratios), and verbal autopsy data. Cancer incidence was calculated by dividing mortality estimates through the modeled MI ratios. To calculate cancer prevalence, MI ratios were used to model survival. To calculate YLDs, prevalence estimates were multiplied by disability weights. The YLLs were estimated by multiplying age-specific cancer deaths by the reference life expectancy. DALYs were estimated as the sum of YLDs and YLLs. A sociodemographic index (SDI) was created for each location based on income per capita, educational attainment, and fertility. Countries were categorized by SDI quintiles to summarize results.
In 2015, there were 17.5 million cancer cases worldwide and 8.7 million deaths. Between 2005 and 2015, cancer cases increased by 33%, with population aging contributing 16%, population growth 13%, and changes in age-specific rates contributing 4%. For men, the most common cancer globally was prostate cancer (1.6 million cases). Tracheal, bronchus, and lung cancer was the leading cause of cancer deaths and DALYs in men (1.2 million deaths and 25.9 million DALYs). For women, the most common cancer was breast cancer (2.4 million cases). Breast cancer was also the leading cause of cancer deaths and DALYs for women (523 000 deaths and 15.1 million DALYs). Overall, cancer caused 208.3 million DALYs worldwide in 2015 for both sexes combined. Between 2005 and 2015, age-standardized incidence rates for all cancers combined increased in 174 of 195 countries or territories. Age-standardized death rates (ASDRs) for all cancers combined decreased within that timeframe in 140 of 195 countries or territories. Countries with an increase in the ASDR due to all cancers were largely located on the African continent. Of all cancers, deaths between 2005 and 2015 decreased significantly for Hodgkin lymphoma (-6.1% [95% uncertainty interval (UI), -10.6% to -1.3%]). The number of deaths also decreased for esophageal cancer, stomach cancer, and chronic myeloid leukemia, although these results were not statistically significant.
Conclusion and Relevance:
As part of the epidemiological transition, cancer incidence is expected to increase in the future, further straining limited health care resources. Appropriate allocation of resources for cancer prevention, early diagnosis, and curative and palliative care requires detailed knowledge of the local burden of cancer. The GBD 2015 study results demonstrate that progress is possible in the war against cancer. However, the major findings also highlight an unmet need for cancer prevention efforts, including tobacco control, vaccination, and the promotion of physical activity and a healthy diet.
Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) provides an up to date synthesis of the evidence on risk factor exposure and the burden of disease attributable to these risks. By providing national and subnational assessments spanning 25 years, the GBD 2015 can help inform debates on the importance of addressing different risks in different contexts. Methods We used the comparative risk assessment (CRA) framework developed for previous iterations of the GBD study to estimate attributable deaths, DALYs, and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks over the period 1990 to 2015. The GBD 2015 study included 388 risk-outcome pairs which met World Cancer Research Fund-defined criteria for convincing or probable evidence. Relative risk estimates were extracted from published and unpublished randomised controlled trials, cohorts, and pooled cohorts. Risk exposures were estimated based on published studies, household surveys, census data, satellite data, and other sources. Statistical models were used to pool data from different sources, adjust for bias in the data, and incorporate explanatory covariates. We developed a metric that allows comparisons of exposure across risk factors – the summary exposure value (SEV) – which is scaled so that 100% is the entire population at maximum risk, and 0% is everyone at lowest risk. Using the counterfactual scenario of theoretical minimum risk level (TMREL) – the level for a given risk that could minimise population level risk if achieved – we estimated the portion of the burden (deaths and DALYs) that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterized how risk exposures change as countries move through the development continuum. GBD 2015 follows the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER), and provides comprehensive and detailed information for the data sources, estimation methods, computational tools, and statistical analysis used to generate estimates of attributable burden. Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting and smoking fell more than 25%. Global exposure for several occupational risks, high body mass index, drug use and ambient air pollution increased more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 58.0% (56.9-59.0%) of global deaths and 41.3% (39.9-42.9%) of DALYs; the largest fraction of global DALYs was attributable to behavioural (30.3% [28.6-32.0%]). In 2015, the 10 largest Level 3 risks in terms of attributable DALYs at the global level were, in order: high systolic blood pressure (9.3% [8.3-10.3%] of global DALYs), smoking (6.0% [5.3-6.8%]), high fasting plasma glucose (5.8% [5.3-6.4%]), high body-mass index (4.9% [3.5-6.4%]), childhood undernutrition 4.6% [4.1-5.1%]), ambient particular matter (4.2% [3.6-4.8%]), high total cholesterol (3.6% [3- 4.3%]), household air pollution (3.5% [2.6-4.4%]), alcohol use (3.5% [3.1-3.8%]) and diets high in sodium (3.4% [2.0-5.3%]).Decomposition analysis showed that from 1990 to 2015 the number of attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and unsafe water, and household air pollution but most of these declines were driven by reductions in risk-deleted DALY rates and not reductions in exposure. For a wide range of risks, increases in attributable burden were driven by population growth and aging exceeding reductions from risk-deleted DALY rates with exposure change having only a minimal contribution. Rising exposure has contributed to notable increases in attributable DALYs from high body-mass index, high fasting plasma glucose, occupational carcinogens, and drug use. Our assessments of the relationships between increasing development, measured using the Sociodemographic Index, showed that some environmental risks and childhood undernutrition decline steadily with development while a number of risks like low physical activity, high body-mass index, high fasting plasma glucose, smoking and others increase with development until the highest quintile. At the country level, metabolic risks such as high BMI and high fasting plasma glucose increasingly emerged as the leading risk factors for attributable DALYs in 2015. Nonetheless, regional risk profiles showed sizeable heterogeneity, with smoking still ranked among the leading five risk factors for attributable DALYs in 140 countries, and childhood underweight and unsafe sex enduring as primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks such as water, sanitation, and household air pollution have contributed to declines in critical infectious diseases such as diarrhoeal diseases. Many risks do not appear to change as countries move through the development continuum and have not played a major role in trends of the last 25 years. Several key risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, are increasing and contributing to rising burden from some conditions; nevertheless these risks provide opportunities for intervention. Some highly preventable risks such as smoking remain major causes of attributable DALYs even as exposure is declining. Public policy needs to pay careful attention to the risks that are both major contributors to global burden and are increasing
Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development.Methods
We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate.Findings
Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9–3·0) for men and 3·5 years (3·4–3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78–0·92) and 1·2 years (1·1–1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs.Interpretation
Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum.
Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015.Methods
We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores.Findings
We generated 9·3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17·2 billion, 95% uncertainty interval [UI] 15·4–19·2 billion) and diarrhoeal diseases (2·39 billion, 2·30–2·50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2·36 billion (2·35–2·37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20–30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo.Interpretation
Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available.
coBverage of specific reproductive health care services as well as assessment of observed versus expected maternal mortality as a function of Socio-Demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility.
Only ten countries achieved MDG 5, but 122 of 195 countries have already met SDG 3.1. Geographic disparities widened and, in 2015, there were still 24 countries with MMR greater than 400. The proportion of all maternal deaths occurring in the bottom two SDI quintiles, where haemorrhage is the dominant cause of maternal death, increased from roughly 68% in 1990 to more than 80% in 2015. The middle SDI quintile improved the most from 1990 to 2015, but also has the most complicated etiologic profile. Maternal mortality in the highest SDI quintile is mostly due to other direct maternal disorders, indirect maternal disorders, and abortion, ectopic pregnancy, and miscarriage. Historical patterns suggest achievement of SDG 3.1 will require 91% coverage of one antenatal care (ANC) visit, 78% of four ANC visits, 81% of in-facility delivery (IFD), and 87% of skilled birth attendance (SBA).
Several challenges to improving reproductive health lie ahead in the SDG era. Countries should: a) establish or renew systems for collection and timely dissemination of health data; b) expand coverage and improve quality of family planning services, including access to contraception and safe abortion to address high adolescent fertility; c) invest in improving health system capacity, including coverage of routine reproductive health care and of more advanced obstetric care—including emergency obstetric care (EmOC); d) Adapt health systems and data collection systems to monitor and reverse the increase in indirect, other direct, and late maternal deaths, especially in high SDI locations; e) Examine their own performance with respect to their SDI level, using that information to formulate strategies for improving performance and ensuring optimum reproductive health of their population.
Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all‐cause mortality and causes of death estimates due to 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in‐depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all‐cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refining the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under‐5 mortality synthesis by space‐time Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14,294 geography‐year data points. Eight causes, including Ebola virus disease, were added to the GBD 2015 cause list for mortality. Our overall cause of death estimation framework was similar to that of GBD 2013, albeit with several analytic advances, including improved garbage code redistribution algorithms. Six modelling approaches were used to assess cause‐specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for the vast majority of causes. For rare causes or those with limited data availability, we applied alternative modelling strategies, such as natural history models and subcause proportion models. We conducted pathogen counterfactual analyses for lower respiratory infections (LRIs) and diarrhoeal diseases based on updated estimates of pathogen‐specific relative risks or odds ratios for infection. Mortality due to HIV/AIDS was estimated using a modified version of the Estimation and Project Package (EPP)‐Spectrum, which was specifically adapted for GBD to capture HIV treatment effects with greater accuracy, and to strengthen EPP and Spectrum consistencies. For GBD 2015, we conducted a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause‐specific mortality as they relate to the Socio‐Demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors influencing total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, changes in population age structures, and epidemiologic changes contributed to shifts in mortality. Last, we attributed changes in life expectancy to changes in cause of death. We documented each step of GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.2‐62.2) in 1980 to 71.8 years (71.2‐72.4) in 2015. Several countries in sub‐Saharan Africa recorded massive gains in life expectancy since 2005, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. Between 2005 and 2015, male life expectancy in Syria dropped by 11.3 years (3.7‐17.4), to 62.6 years (56.5‐70.2). Total deaths increased 4.1% (2.6‒5.6%) since 2005, rising to 55.8 million (54.9‒56.6 million) in 2015, but age‐standardised death rates fell by 17.0% (15.8‒18.1%) during this time, underscoring population growth and shifts in global age structures. A similar result emerged for non‐communicable diseases (NCDs), with total NCD deaths increasing by 14.2% (12.6‒16.0%) to 39.8 million (39.2‒40.5 million) in 2015 while age‐ standardised rates decreased by 13.2% (11.9‒14.3%). Globally, this mortality pattern emerged for a number of NCDs, including several cancers, ischaemic heart disease (IHD), cirrhosis, and Alzheimer’s disease and other dementias. By contrast, both total deaths and age‐standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined between 2005 and 2015, gains largely attributable to falling mortality rates due to HIV/AIDS (42.2% [39.1‒44.6%]), malaria (43.0% [34.7‒51.8%]), preterm birth complications (29.8% [24.8‒34.9%]), and maternal disorders (29.4% [19.3‒37.1%]). Slower progress occurred for a number of causes, such as LRI and nutritional deficiencies, while fatalities escalated for others, including dengue and drug use disorders. Age‐standardised death rates due to injuries significantly declined since 2005, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. Our pathogen counterfactual analyses identified rotavirus and pneumococcal pneumonia as leading causes of under‐5 deaths due to diarrhoea and LRIs in 2015 (146,480 [118,037‐183,451] and 392,964 [228,367‐532,281]), though pathogen‐specific mortality varied by region. Globally, the effects of population growth, aging, and changes in age‐standardised death rates substantially differed by cause. Our analyses on expected relationships between cause‐specific mortality and SDI document the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (YLLs) and how they differ from the level expected on the basis of SDI alone revealed distinct yet very heterogeneous patterns by region and country or territory. IHD, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many instances, intra‐regional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub‐Saharan Africa, with observed YLLs far exceeding expected YLLs for countries where malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age‐specific mortality has steadily improved over the last 35 years; this pattern of general progress continued in the last decade. Progress has been faster in the majority of countries that expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen declines in life expectancy and some causes age‐standardised rates are increasing. Population growth and aging in most countries, despite progress in reducing age‐standardised death rates, mean that the number of deaths from most non‐communicable causes are increasing, putting increased demands on health systems