Benn Sartorius
My academic qualifications include a PhD in applied epidemiology/biostatistics, a 2-year applied field epidemiology fellowship (European Programme for Intervention Epidemiology Training [EPIET]) and an MSc in epidemiology and biostatistics. I’m Full Research Professor within the College of Health Sciences at University of KwaZulu-Natal. I also currently manage multiple staff statisticians who provide biostatistical support to the College of Health Sciences. I have subsequently be invited to join the Scientific Council for the GBD, which I have accepted and have as such joined their key scientific decision-making body. The Council is comprised of leading experts in fields relating to the GBD. These data have much utility for further subnational analysis in South Africa and my intention is to further delve into cancer related mortality, DALYs, YLLs and risk factors at provincial level. These are likely to yield additional publications in high impact journals.I have a 180 publications (https://scholar.google.co.za/citations?user=-j6OIboAAAAJ
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An understanding of the trends in tuberculosis incidence, prevalence, and mortality is crucial to tracking of the success of tuberculosis control programmes and identification of remaining challenges. We assessed trends in the fatal and non-fatal burden of tuberculosis over the past 25 years for 195 countries and territories.
Methods
We analysed 10 691 site-years of vital registration data, 768 site-years of verbal autopsy data, and 361 site-years of mortality surveillance data using the Cause of Death Ensemble model to estimate tuberculosis mortality rates. We analysed all available age-specific and sex-specific data sources, including annual case notifications, prevalence surveys, and estimated cause-specific mortality, to generate internally consistent estimates of incidence, prevalence, and mortality using DisMod-MR 2.1, a Bayesian meta-regression tool. We assessed how observed tuberculosis incidence, prevalence, and mortality differed from expected trends as predicted by the Socio-demographic Index (SDI), a composite indicator based on income per capita, average years of schooling, and total fertility rate. We also estimated tuberculosis mortality and disability-adjusted life-years attributable to the independent effects of risk factors including smoking, alcohol use, and diabetes.
Findings
Globally, in 2015, the number of tuberculosis incident cases (including new and relapse cases) was 10·2 million (95% uncertainty interval 9·2 million to 11·5 million), the number of prevalent cases was 10·1 million (9·2 million to 11·1 million), and the number of deaths was 1·3 million (1·1 million to 1·6 million). Among individuals who were HIV negative, the number of incident cases was 8·8 million (8·0 million to 9·9 million), the number of prevalent cases was 8·9 million (8·1 million to 9·7 million), and the number of deaths was 1·1 million (0·9 million to 1·4 million). Annualised rates of change from 2005 to 2015 showed a faster decline in mortality (−4·1% [−5·0 to −3·4]) than in incidence (−1·6% [−1·9 to −1·2]) and prevalence (−0·7% [−1·0 to −0·5]) among HIV-negative individuals. The SDI was inversely associated with HIV-negative mortality rates but did not show a clear gradient for incidence and prevalence. Most of Asia, eastern Europe, and sub-Saharan Africa had higher rates of HIV-negative tuberculosis burden than expected given their SDI. Alcohol use accounted for 11·4% (9·3–13·0) of global tuberculosis deaths among HIV-negative individuals in 2015, diabetes accounted for 10·6% (6·8–14·8), and smoking accounted for 7·8% (3·8–12·0).
Interpretation
Despite a concerted global effort to reduce the burden of tuberculosis, it still causes a large disease burden globally. Strengthening of health systems for early detection of tuberculosis and improvement of the quality of tuberculosis care, including prompt and accurate diagnosis, early initiation of treatment, and regular follow-up, are priorities. Countries with higher than expected tuberculosis rates for their level of sociodemographic development should investigate the reasons for lagging behind and take remedial action. Efforts to prevent smoking, alcohol use, and diabetes could also substantially reduce the burden of tuberculosis.
and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases,
Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence,
and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
Methods We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal
consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring
consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes,
we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were
estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for
comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of
income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and
Transparent Health Estimates Reporting (GATHER).
Findings Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major
depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval
[UI] 40·8–75·9 million [7·2%, 6·0–8·3]), 45·1 million (29·0–62·8 million [5·6%, 4·0–7·2]), 36·3 million
(25·3–50·9 million [4·5%, 3·8–5·3]), 34·7 million (23·0–49·6 million [4·3%, 3·5–5·2]), and 34·1 million
(23·5–46·0 million [4·2%, 3·2–5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined
decreased between 1990 and 2016 by 2·7% (95% UI 2·3–3·1). Despite mostly stagnant age-standardised rates, the
absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly
because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of
YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined
were 10·4% (95% UI 9·0–11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer’s disease
and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the
main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use
disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted
much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a
less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate
(China, 9201 YLDs per 100000, 95% UI 6862–11943) and highest rate (Yemen, 14774 YLDs per 100000, 11018–19228).
Interpretation The decrease in death rates since 1990 for most causes has not been matched by a similar decline in
age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some
causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases
steeply with age, health systems will face increasing demand for services that are generally costlier than the
interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-todate
information about the trends of disease and how this varies between countries is essential to plan for an adequate
health-system response.
Funding Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental
Health of the National Institutes of Health.
one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as
they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors
Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for
188 countries, and then on the basis of these past trends, we projected indicators to 2030.
Methods We used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an
increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure,
which focuses on coverage of essential health services, to also represent personal health-care access and quality for
several non-communicable diseases. We transformed each indicator on a scale of 0–100, with 0 as the 2·5th percentile
estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all
37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the
basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and
country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on
out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against
which we assessed attainment.
Findings Globally, the median health-related SDG index was 56·7 (IQR 31·9–66·8) in 2016 and country-level
performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6–88·9), Iceland (86·0,
84·1–87·6), and Sweden (85·6, 81·8–87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6–11·9), the
Central African Republic (11·0, 8·8–13·8), and Somalia (11·3, 9·5–13·1) recording the lowest. Between 2000
and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia,
Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the
Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on
projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2–8) of the 24 defined
targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging
from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal
mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets,
including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related
SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved
in the past.
Interpretation GBD 2016 provides an updated and expanded evidence base on where the world currently stands in
terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health
services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting
defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of
SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic
effects of adopting the Millennium Development Goals after 2000. With the SDGs’ broader, bolder development
agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all
populations.
Funding Bill & Melinda Gates Foundation.
epidemiological patterns against health system performance and identify specific needs for resource allocation in
research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and
Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population
health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track
trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI).
Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 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 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each
location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability
per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric
mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate.
Findings The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years
(95% uncertainty interval 71·9–78·6) for females and 72·0 years (68·8–75·1) for males. The lowest for females was
in the Central African Republic (45·6 years [42·0–49·5]) and for males was in Lesotho (41·5 years [39·0–44·0]). From
1990 to 2016, global HALE increased by an average of 6·24 years (5·97–6·48) for both sexes combined. Global HALE
increased by 6·04 years (5·74–6·27) for males and 6·49 years (6·08–6·77) for females, whereas HALE at age 65 years
increased by 1·78 years (1·61–1·93) for males and 1·96 years (1·69–2·13) for females. Total global DALYs remained
largely unchanged from 1990 to 2016 (–2·3% [–5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and
nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The
exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were
Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic
heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs
and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY
burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally.
Interpretation At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that
many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative
years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression
of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace
with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and
their relationship to SDI represents a robust framework with which to benchmark location-specific health performance.
Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform
health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for
health, including financial and research investments for all countries, regardless of their level of sociodemographic
development. The presence of countries that substantially outperform others suggests the need for increased scrutiny
for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming
countries suggests the need for devotion of extra attention to health systems that need more robust support.
Funding Bill & Melinda Gates Foundation.
comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a
long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates
on the importance of addressing risks in context.
Methods We used the comparative risk assessment framework developed for previous iterations of GBD to estimate
levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group,
sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks
from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or
probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised
controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according
to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure
level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we
explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure,
and all other factors combined.
Findings Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and
decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and
household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high
fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors
in terms of attributable DALYs at the global level for men were smoking (124·1 million DALYs [95% UI 111·2 million to
137·0 million]), high systolic blood pressure (122·2 million DALYs [110·3 million to 133·3 million], and low birthweight
and short gestation (83·0 million DALYs [78·3 million to 87·7 million]), and for women, were high systolic blood
pressure (89·9 million DALYs [80·9 million to 98·2 million]), high body-mass index (64·8 million DALYs [44·4 million
to 87·6 million]), and high fasting plasma glucose (63·8 million DALYs [53·2 million to 76·3 million]). In 2016 in
113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained
among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the
leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important
drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an
9·3% (6·9–11·6) decline in deaths and a 10·8% (8·3–13·1) decrease in DALYs at the global level, while population
ageing accounts for 14·9% (12·7–17·5) of deaths and 6·2% (3·9–8·7) of DALYs, and population growth for 12·4%
(10·1–14·9) of deaths and 12·4% (10·1–14·9) of DALYs. The largest contribution of trends in risk exposure to disease
burden is seen between ages 1 year and 4 years, where a decline of 27·3% (24·9–29·7) of the change in DALYs between
2006 and 2016 can be attributed to declines in exposure to risks.
Interpretation Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome
pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure
has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to
global disease burden, increasing trends, and variable patterns across countries at the same level of development.
GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively
small part in the past decade.
Funding The Bill & Melinda Gates Foundation, Bloomberg Philanthropies.
OBJECTIVE 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.
EVIDENCE REVIEW 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.
FINDINGS 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 (523000 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.
An understanding of the trends in tuberculosis incidence, prevalence, and mortality is crucial to tracking of the success of tuberculosis control programmes and identification of remaining challenges. We assessed trends in the fatal and non-fatal burden of tuberculosis over the past 25 years for 195 countries and territories.
Methods
We analysed 10 691 site-years of vital registration data, 768 site-years of verbal autopsy data, and 361 site-years of mortality surveillance data using the Cause of Death Ensemble model to estimate tuberculosis mortality rates. We analysed all available age-specific and sex-specific data sources, including annual case notifications, prevalence surveys, and estimated cause-specific mortality, to generate internally consistent estimates of incidence, prevalence, and mortality using DisMod-MR 2.1, a Bayesian meta-regression tool. We assessed how observed tuberculosis incidence, prevalence, and mortality differed from expected trends as predicted by the Socio-demographic Index (SDI), a composite indicator based on income per capita, average years of schooling, and total fertility rate. We also estimated tuberculosis mortality and disability-adjusted life-years attributable to the independent effects of risk factors including smoking, alcohol use, and diabetes.
Findings
Globally, in 2015, the number of tuberculosis incident cases (including new and relapse cases) was 10·2 million (95% uncertainty interval 9·2 million to 11·5 million), the number of prevalent cases was 10·1 million (9·2 million to 11·1 million), and the number of deaths was 1·3 million (1·1 million to 1·6 million). Among individuals who were HIV negative, the number of incident cases was 8·8 million (8·0 million to 9·9 million), the number of prevalent cases was 8·9 million (8·1 million to 9·7 million), and the number of deaths was 1·1 million (0·9 million to 1·4 million). Annualised rates of change from 2005 to 2015 showed a faster decline in mortality (−4·1% [−5·0 to −3·4]) than in incidence (−1·6% [−1·9 to −1·2]) and prevalence (−0·7% [−1·0 to −0·5]) among HIV-negative individuals. The SDI was inversely associated with HIV-negative mortality rates but did not show a clear gradient for incidence and prevalence. Most of Asia, eastern Europe, and sub-Saharan Africa had higher rates of HIV-negative tuberculosis burden than expected given their SDI. Alcohol use accounted for 11·4% (9·3–13·0) of global tuberculosis deaths among HIV-negative individuals in 2015, diabetes accounted for 10·6% (6·8–14·8), and smoking accounted for 7·8% (3·8–12·0).
Interpretation
Despite a concerted global effort to reduce the burden of tuberculosis, it still causes a large disease burden globally. Strengthening of health systems for early detection of tuberculosis and improvement of the quality of tuberculosis care, including prompt and accurate diagnosis, early initiation of treatment, and regular follow-up, are priorities. Countries with higher than expected tuberculosis rates for their level of sociodemographic development should investigate the reasons for lagging behind and take remedial action. Efforts to prevent smoking, alcohol use, and diabetes could also substantially reduce the burden of tuberculosis.
and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases,
Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence,
and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
Methods We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal
consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring
consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes,
we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were
estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for
comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of
income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and
Transparent Health Estimates Reporting (GATHER).
Findings Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major
depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval
[UI] 40·8–75·9 million [7·2%, 6·0–8·3]), 45·1 million (29·0–62·8 million [5·6%, 4·0–7·2]), 36·3 million
(25·3–50·9 million [4·5%, 3·8–5·3]), 34·7 million (23·0–49·6 million [4·3%, 3·5–5·2]), and 34·1 million
(23·5–46·0 million [4·2%, 3·2–5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined
decreased between 1990 and 2016 by 2·7% (95% UI 2·3–3·1). Despite mostly stagnant age-standardised rates, the
absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly
because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of
YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined
were 10·4% (95% UI 9·0–11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer’s disease
and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the
main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use
disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted
much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a
less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate
(China, 9201 YLDs per 100000, 95% UI 6862–11943) and highest rate (Yemen, 14774 YLDs per 100000, 11018–19228).
Interpretation The decrease in death rates since 1990 for most causes has not been matched by a similar decline in
age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some
causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases
steeply with age, health systems will face increasing demand for services that are generally costlier than the
interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-todate
information about the trends of disease and how this varies between countries is essential to plan for an adequate
health-system response.
Funding Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental
Health of the National Institutes of Health.
one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as
they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors
Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for
188 countries, and then on the basis of these past trends, we projected indicators to 2030.
Methods We used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an
increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure,
which focuses on coverage of essential health services, to also represent personal health-care access and quality for
several non-communicable diseases. We transformed each indicator on a scale of 0–100, with 0 as the 2·5th percentile
estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all
37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the
basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and
country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on
out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against
which we assessed attainment.
Findings Globally, the median health-related SDG index was 56·7 (IQR 31·9–66·8) in 2016 and country-level
performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6–88·9), Iceland (86·0,
84·1–87·6), and Sweden (85·6, 81·8–87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6–11·9), the
Central African Republic (11·0, 8·8–13·8), and Somalia (11·3, 9·5–13·1) recording the lowest. Between 2000
and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia,
Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the
Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on
projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2–8) of the 24 defined
targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging
from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal
mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets,
including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related
SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved
in the past.
Interpretation GBD 2016 provides an updated and expanded evidence base on where the world currently stands in
terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health
services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting
defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of
SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic
effects of adopting the Millennium Development Goals after 2000. With the SDGs’ broader, bolder development
agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all
populations.
Funding Bill & Melinda Gates Foundation.
epidemiological patterns against health system performance and identify specific needs for resource allocation in
research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and
Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population
health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track
trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI).
Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 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 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each
location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability
per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric
mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate.
Findings The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years
(95% uncertainty interval 71·9–78·6) for females and 72·0 years (68·8–75·1) for males. The lowest for females was
in the Central African Republic (45·6 years [42·0–49·5]) and for males was in Lesotho (41·5 years [39·0–44·0]). From
1990 to 2016, global HALE increased by an average of 6·24 years (5·97–6·48) for both sexes combined. Global HALE
increased by 6·04 years (5·74–6·27) for males and 6·49 years (6·08–6·77) for females, whereas HALE at age 65 years
increased by 1·78 years (1·61–1·93) for males and 1·96 years (1·69–2·13) for females. Total global DALYs remained
largely unchanged from 1990 to 2016 (–2·3% [–5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and
nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The
exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were
Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic
heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs
and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY
burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally.
Interpretation At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that
many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative
years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression
of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace
with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and
their relationship to SDI represents a robust framework with which to benchmark location-specific health performance.
Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform
health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for
health, including financial and research investments for all countries, regardless of their level of sociodemographic
development. The presence of countries that substantially outperform others suggests the need for increased scrutiny
for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming
countries suggests the need for devotion of extra attention to health systems that need more robust support.
Funding Bill & Melinda Gates Foundation.
comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a
long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates
on the importance of addressing risks in context.
Methods We used the comparative risk assessment framework developed for previous iterations of GBD to estimate
levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group,
sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks
from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or
probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised
controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according
to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure
level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we
explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure,
and all other factors combined.
Findings Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and
decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and
household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high
fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors
in terms of attributable DALYs at the global level for men were smoking (124·1 million DALYs [95% UI 111·2 million to
137·0 million]), high systolic blood pressure (122·2 million DALYs [110·3 million to 133·3 million], and low birthweight
and short gestation (83·0 million DALYs [78·3 million to 87·7 million]), and for women, were high systolic blood
pressure (89·9 million DALYs [80·9 million to 98·2 million]), high body-mass index (64·8 million DALYs [44·4 million
to 87·6 million]), and high fasting plasma glucose (63·8 million DALYs [53·2 million to 76·3 million]). In 2016 in
113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained
among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the
leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important
drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an
9·3% (6·9–11·6) decline in deaths and a 10·8% (8·3–13·1) decrease in DALYs at the global level, while population
ageing accounts for 14·9% (12·7–17·5) of deaths and 6·2% (3·9–8·7) of DALYs, and population growth for 12·4%
(10·1–14·9) of deaths and 12·4% (10·1–14·9) of DALYs. The largest contribution of trends in risk exposure to disease
burden is seen between ages 1 year and 4 years, where a decline of 27·3% (24·9–29·7) of the change in DALYs between
2006 and 2016 can be attributed to declines in exposure to risks.
Interpretation Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome
pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure
has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to
global disease burden, increasing trends, and variable patterns across countries at the same level of development.
GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively
small part in the past decade.
Funding The Bill & Melinda Gates Foundation, Bloomberg Philanthropies.
OBJECTIVE 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.
EVIDENCE REVIEW 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.
FINDINGS 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 (523000 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.