Michael Kutz

Mapping Plasmodium falciparum Mortality in Africa between 1990 and 2015

BACKGROUND Malaria control has not been routinely informed by the assessment of subnational variation in malaria deaths. We combined data from the Malaria Atlas Project and the Global Burden of Disease Study to estimate malaria mortality across sub-Saharan Africa on a grid of 5 km2 from 1990 through 2015. METHODS We estimated malaria mortality using a spatiotemporal modeling framework of geolocated data (i.e., with known latitude and longitude) on the clinical incidence of malaria, coverage of antimalarial drug treatment, case fatality rate, and population distribution according to age. RESULTS Across sub-Saharan Africa during the past 15 years, we estimated that there was an overall decrease of 57% (95% uncertainty interval, 46 to 65) in the rate of malaria deaths, from 12.5 (95% uncertainty interval, 8.3 to 17.0) per 10,000 population in 2000 to 5.4 (95% uncertainty interval, 3.4 to 7.9) in 2015. This led to an overall decrease of 37% (95% uncertainty interval, 36 to 39) in the number of malaria deaths annually, from 1,007,000 (95% uncertainty interval, 666,000 to 1,376,000) to 631,000 (95% uncertainty interval, 394,000 to 914,000). The share of malaria deaths among children younger than 5 years of age ranged from more than 80% at a rate of death of more than 25 per 10,000 to less than 40% at rates below 1 per 10,000. Areas with high malaria mortality (>10 per 10,000) and low coverage (<50%) of insecticide-treated bed nets and antimalarial drugs included much of Nigeria, Angola, and Cameroon and parts of the Central African Republic, Congo, Guinea, and Equatorial Guinea. CONCLUSIONS We estimated that there was an overall decrease of 57% in the rate of death from malaria across sub-Saharan Africa over the past 15 years and identified several countries in which high rates of death were associated with low coverage of antimalarial treatment and prevention programs. (Funded by the Bill and Melinda Gates Foundation and others.).

US County-Level Trends in Mortality Rates for Major Causes of Death, 1980-2014

Importance County-level patterns in mortality rates by cause have not been systematically described but are potentially useful for public health officials, clinicians, and researchers seeking to improve health and reduce geographic disparities. Objectives To demonstrate the use of a novel method for county-level estimation and to estimate annual mortality rates by US county for 21 mutually exclusive causes of death from 1980 through 2014. Design, Setting, and Participants Redistribution methods for garbage codes (implausible or insufficiently specific cause of death codes) and small area estimation methods (statistical methods for estimating rates in small subpopulations) were applied to death registration data from the National Vital Statistics System to estimate annual county-level mortality rates for 21 causes of death. These estimates were raked (scaled along multiple dimensions) to ensure consistency between causes and with existing national-level estimates. Geographic patterns in the age-standardized mortality rates in 2014 and in the change in the age-standardized mortality rates between 1980 and 2014 for the 10 highest-burden causes were determined. Exposure County of residence. Main Outcomes and Measures Cause-specific age-standardized mortality rates. Results A total of 80 412 524 deaths were recorded from January 1, 1980, through December 31, 2014, in the United States. Of these, 19.4 million deaths were assigned garbage codes. Mortality rates were analyzed for 3110 counties or groups of counties. Large between-county disparities were evident for every cause, with the gap in age-standardized mortality rates between counties in the 90th and 10th percentiles varying from 14.0 deaths per 100 000 population (cirrhosis and chronic liver diseases) to 147.0 deaths per 100 000 population (cardiovascular diseases). Geographic regions with elevated mortality rates differed among causes: for example, cardiovascular disease mortality tended to be highest along the southern half of the Mississippi River, while mortality rates from self-harm and interpersonal violence were elevated in southwestern counties, and mortality rates from chronic respiratory disease were highest in counties in eastern Kentucky and western West Virginia. Counties also varied widely in terms of the change in cause-specific mortality rates between 1980 and 2014. For most causes (eg, neoplasms, neurological disorders, and self-harm and interpersonal violence), both increases and decreases in county-level mortality rates were observed. Conclusions and Relevance In this analysis of US cause-specific county-level mortality rates from 1980 through 2014, there were large between-county differences for every cause of death, although geographic patterns varied substantially by cause of death. The approach to county-level analyses with small area models used in this study has the potential to provide novel insights into US disease-specific mortality time trends and their differences across geographic regions.

The Burden of Primary Liver Cancer and Underlying Etiologies From 1990 to 2015 at the Global, Regional, and National Level: Results From the Global Burden of Disease Study 2015

Importance Liver cancer is among the leading causes of cancer deaths globally. The most common causes for liver cancer include hepatitis B virus (HBV) and hepatitis C virus (HCV) infection and alcohol use. Objective To report results of the Global Burden of Disease (GBD) 2015 study on primary liver cancer incidence, mortality, and disability-adjusted life-years (DALYs) for 195 countries or territories from 1990 to 2015, and present global, regional, and national estimates on the burden of liver cancer attributable to HBV, HCV, alcohol, and an “other” group that encompasses residual causes. Design, Settings, and Participants Mortality was estimated using vital registration and cancer registry data in an ensemble modeling approach. Single-cause mortality estimates were adjusted for all-cause mortality. Incidence was derived from mortality estimates and the mortality-to-incidence ratio. Through a systematic literature review, data on the proportions of liver cancer due to HBV, HCV, alcohol, and other causes were identified. Years of life lost were calculated by multiplying each death by a standard life expectancy. Prevalence was estimated using mortality-to-incidence ratio as surrogate for survival. Total prevalence was divided into 4 sequelae that were multiplied by disability weights to derive years lived with disability (YLDs). DALYs were the sum of years of life lost and YLDs. Main Outcomes and Measures Liver cancer mortality, incidence, YLDs, years of life lost, DALYs by etiology, age, sex, country, and year. Results There were 854 000 incident cases of liver cancer and 810 000 deaths globally in 2015, contributing to 20 578 000 DALYs. Cases of incident liver cancer increased by 75% between 1990 and 2015, of which 47% can be explained by changing population age structures, 35% by population growth, and −8% to changing age-specific incidence rates. The male-to-female ratio for age-standardized liver cancer mortality was 2.8. Globally, HBV accounted for 265 000 liver cancer deaths (33%), alcohol for 245 000 (30%), HCV for 167 000 (21%), and other causes for 133 000 (16%) deaths, with substantial variation between countries in the underlying etiologies. Conclusions and Relevance Liver cancer is among the leading causes of cancer deaths in many countries. Causes of liver cancer differ widely among populations. Our results show that most cases of liver cancer can be prevented through vaccination, antiviral treatment, safe blood transfusion and injection practices, as well as interventions to reduce excessive alcohol use. In line with the Sustainable Development Goals, the identification and elimination of risk factors for liver cancer will be required to achieve a sustained reduction in liver cancer burden. The GBD study can be used to guide these prevention efforts.

The increasing burden of diabetes and variations among the states of India: the Global Burden of Disease Study 1990–2016

Summary Background The burden of diabetes is increasing rapidly in India but a systematic understanding of its distribution and time trends is not available for every state of India. We present a comprehensive analysis of the time trends and heterogeneity in the distribution of diabetes burden across all states of India between 1990 and 2016. Methods We analysed the prevalence and disability-adjusted life-years (DALYs) of diabetes in the states of India from 1990 to 2016 using all available data sources that could be accessed as part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, and assessed heterogeneity across the states. The states were placed in four groups based on epidemiological transition level (ETL), defined on the basis of the ratio of DALYs from communicable diseases to those from non-communicable diseases and injuries combined, with a low ratio denoting high ETL and vice versa. We assessed the contribution of risk factors to diabetes DALYs and the relation of overweight (body-mass index 25 kg/m2 or more) with diabetes prevalence. We calculated 95% uncertainty intervals (UIs) for the point estimates. Findings The number of people with diabetes in India increased from 26·0 million (95% UI 23·4–28·6) in 1990 to 65·0 million (58·7–71·1) in 2016. The prevalence of diabetes in adults aged 20 years or older in India increased from 5·5% (4·9–6·1) in 1990 to 7·7% (6·9–8·4) in 2016. The prevalence in 2016 was highest in Tamil Nadu and Kerala (high ETL) and Delhi (higher-middle ETL), followed by Punjab and Goa (high ETL) and Karnataka (higher-middle ETL). The age-standardised DALY rate for diabetes increased in India by 39·6% (32·1–46·7) from 1990 to 2016, which was the highest increase among major non-communicable diseases. The age-standardised diabetes prevalence and DALYs increased in every state, with the percentage increase among the highest in several states in the low and lower-middle ETL state groups. The most important risk factor for diabetes in India was overweight to which 36·0% (22·6–49·2) of the diabetes DALYs in 2016 could be attributed. The prevalence of overweight in adults in India increased from 9·0% (8·7–9·3) in 1990 to 20·4% (19·9–20·8) in 2016; this prevalence increased in every state of the country. For every 100 overweight adults aged 20 years or older in India, there were 38 adults (34–42) with diabetes, compared with the global average of 19 adults (17–21) in 2016. Interpretation The increase in health loss from diabetes since 1990 in India is the highest among major non-communicable diseases. With this increase observed in every state of the country, and the relative rate of increase highest in several less developed low ETL states, policy action that takes these state-level differences into account is needed urgently to control this potentially explosive public health situation. Funding Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

Gender differentials and state variations in suicide deaths in India: the Global Burden of Disease Study 1990–2016

Summary Background A systematic understanding of suicide mortality trends over time at the subnational level for Indias 1·3 billion people, 18% of the global population, is not readily available. Thus, we aimed to report time trends of suicide deaths, and the heterogeneity in its distribution between the states of India from 1990 to 2016. Methods As part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016, we estimated suicide death rates (SDRs) for both sexes in each state of India from 1990 to 2016. We used various data sources for estimating cause-specific mortality in India. For suicide mortality in India before 2000, estimates were based largely on GBD covariates. For each state, we calculated the ratio of the observed SDR to the rate expected in geographies globally with similar GBD Socio-demographic Index in 2016 (ie, the observed-to-expected ratio); and assessed the age distribution of suicide deaths, and the men-to-women ratio of SDR over time. Finally, we assessed the probability for India and the states of reaching the Sustainable Development Goal (SDG) target of a one-third reduction in SDR from 2015 to 2030, using location-wise trends of the age-standardised SDR from 1990 to 2016. We calculated 95% uncertainty intervals (UIs) for the point estimates. Findings There were 230 314 (95% UI 194 058–250 260) suicide deaths in India in 2016. Indias contribution to global suicide deaths increased from 25·3% in 1990 to 36·6% in 2016 among women, and from 18·7% to 24·3% among men. Age-standardised SDR among women in India reduced by 26·7% from 20·0 (95% UI 16·5–23·5) in 1990 to 14·7 (13·1–16·2) per 100 000 in 2016, but the age-standardised SDR among men was the same in 1990 (22·3 [95% UI 14·4–27·4] per 100 000) and 2016 (21·2 [14·6–23·6] per 100 000). SDR in women was 2·1 times higher in India than the global average in 2016, and the observed-to-expected ratio was 2·74, ranging from 0·45 to 4·54 between the states. SDR in men was 1·4 times higher in India than the global average in 2016, with an observed-to-expected ratio of 1·31, ranging from 0·40 to 2·42 between the states. There was a ten-fold variation between the states in the SDR for women and six-fold variation for men in 2016. The men-to-women ratio of SDR for India was 1·34 in 2016, ranging from 0·97 to 4·11 between the states. The highest age-specific SDRs among women in 2016 were for ages 15–29 years and 75 years or older, and among men for ages 75 years or older. Suicide was the leading cause of death in India in 2016 for those aged 15–39 years; 71·2% of the suicide deaths among women and 57·7% among men were in this age group. If the trends observed up to 2016 continue, the probability of India achieving the SDG SDR reduction target in 2030 is zero, and the majority of the states with 81·3% of Indias population have less than 10% probability, three states have a probability of 10·3–15·0%, and six have a probability of 25·1–36·7%. Interpretation Indias proportional contribution to global suicide deaths is high and increasing. SDR in India is higher than expected for its Socio-Demographic Index level, especially for women, with substantial variations in the magnitude and men-to-women ratio between the states. India must develop a suicide prevention strategy that takes into account these variations in order to address this major public health problem. Funding Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

The burden of chronic respiratory diseases and their heterogeneity across the states of India: the Global Burden of Disease Study 1990–2016

Summary Background India has 18% of the global population and an increasing burden of chronic respiratory diseases. However, a systematic understanding of the distribution of chronic respiratory diseases and their trends over time is not readily available for all of the states of India. Our aim was to report the trends in the burden of chronic respiratory diseases and the heterogeneity in their distribution in all states of India between 1990 and 2016. Methods Using all accessible data from multiple sources, we estimated the prevalence of major chronic respiratory diseases and the deaths and disability-adjusted life-years (DALYs) caused by them for every state of India from 1990 to 2016 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016. We assessed heterogeneity in the burden of chronic obstructive pulmonary disease (COPD) and asthma across the states of India. The states were categorised into four groups based on their epidemiological transition level (ETL). ETL was defined as the ratio of DALYs from communicable diseases to those from non-communicable diseases and injuries combined, with a low ratio denoting high ETL and vice versa. We also assessed the contribution of risk factors to DALYs due to COPD. We compared the burden of chronic respiratory diseases in India against the global average in GBD 2016. We calculated 95% uncertainty intervals (UIs) for the point estimates. Findings The contribution of chronic respiratory diseases to the total DALYs in India increased from 4·5% (95% UI 4·0–4·9) in 1990 to 6·4% (5·8–7·0) in 2016. Of the total global DALYs due to chronic respiratory diseases in 2016, 32·0% occurred in India. COPD and asthma were responsible for 75·6% and 20·0% of the chronic respiratory disease DALYs, respectively, in India in 2016. The number of cases of COPD in India increased from 28·1 million (27·0–29·2) in 1990 to 55·3 million (53·1–57·6) in 2016, an increase in prevalence from 3·3% (3·1–3·4) to 4·2% (4·0–4·4). The age-standardised COPD prevalence and DALY rates in 2016 were highest in the less developed low ETL state group. There were 37·9 million (35·7–40·2) cases of asthma in India in 2016, with similar prevalence in the four ETL state groups, but the highest DALY rate was in the low ETL state group. The highest DALY rates for both COPD and asthma in 2016 were in the low ETL states of Rajasthan and Uttar Pradesh. The DALYs per case of COPD and asthma were 1·7 and 2·4 times higher in India than the global average in 2016, respectively; most states had higher rates compared with other locations worldwide at similar levels of Socio-demographic Index. Of the DALYs due to COPD in India in 2016, 53·7% (43·1–65·0) were attributable to air pollution, 25·4% (19·5–31·7) to tobacco use, and 16·5% (14·1–19·2) to occupational risks, making these the leading risk factors for COPD. Interpretation India has a disproportionately high burden of chronic respiratory diseases. The increasing contribution of these diseases to the overall disease burden across India and the high rate of health loss from them, especially in the less developed low ETL states, highlights the need for focused policy interventions to address this significant cause of disease burden in India. Funding Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.