Factors associated with mortality of TB/HIV co-infected patients in Ethiopia

Background: Despite the large number of TB patients on ART in Ethiopia, their mortality remains high. This study reports the effect of TB on HIV related mortality and determinants of TB/HIV co-infection related mortality.Methods: A longitudinal study design was employed as part of the Advanced Clinical Monitoring of ART (ACM) in Ethiopia. All patients started on ART at or after January 1, 2005 were included. Survival analysis was done to compare survival patterns of HIV patients with TB against HIV patients without TB. In addition, determinants of survival among TB/HIV co-infected patients were analyzed. Adjusted effects of the different factors on time to death were generated using Cox-proportional hazards regression.Results: A total of 3,889 patients were enrolled in the ACM study, of which 355 TB cases were identified, making the crude prevalence 9% (95% CI 8.3 – 10.2). Overall, incidence of TB was 2.2 (95% CI 1.9-2.4) per 100 person-years. TB was highest in the first 2 months and declined with time on ART to reach 1 per 100 person years after 24 months on ART. TB was significantly associated with mortality among HIV patients on HAART (AHR 2.0, 95% CI 1.47-2.75). Male gender was associated with mortality among TB/HIV co-infected patients.Conclusion: Tuberculosis plays a key role in HIV associated mortality. Targeted interventions which can keep patients free of TB in the early stages of their treatment are required to reduce TB related mortality.Key Words: Tuberculosis, Antiretroviral therapy, Mortalit

Prevalence and determinants of poor sleep quality among diabetic patients in Ethiopia: systematic review

BackgroundPoor sleep quality can exacerbate many other physiological functions, such as obesity, cardiovascular disease, and high blood pressure. Although primary studies were conducted in Ethiopia, no studies concluded the pooled prevalence of poor sleep quality in Ethiopia. Therefore, this study was conducted to determine the pooled prevalence and its determinants of sleep quality among diabetes in Ethiopia.ObjectiveAssess the pooled prevalence and its determinants of sleep quality among diabetes in Ethiopia.MethodsThe studies were searched systematically using international databases from PubMed, Google Scholar, Cochrane Library, Embase, and CINAHL. The quality of the articles searched was assessed using the New Castle Ottawa scale for a cross-sectional study design. Statistical analysis was performed using STATA version 14 and a systematic review was performed using a random effect model method. The Preferred Reporting Item for Systematic Review and Meta-analyses (PRISMA) guideline was followed for reporting results.ResultsFrom the total of 728 records screened, 8 studies with 2,471 participants who met the inclusion criteria were included in this systematic review. The estimated pooled prevalence of poor sleep quality in Ethiopia was 48.54%.ConclusionAlmost half of diabetes patients had poor sleep quality. The preparation of brochures on diabetic information and the organization of health education about the negative impact of poor sleep quality on patients are among the best modalities to improve the problem of poor sleep quality

Factors associated with pregnancy termination in six sub-Saharan African countries.

Pregnancy termination continues to be a leading cause of maternal morbidity and mortality among young women in Africa. The sub-Saharan Africa region has the highest rate of abortion-related deaths in the world, at 185 maternal deaths per 100,000 abortions. The aim of this study is to investigate the factors associated with pregnancy termination among women aged 15 to 29 years in six sub-Saharan African countries. We used secondary data from the most recent Demographic and Health Survey of six sub-Saharan African countries: Kenya, Tanzania, Ethiopia, Burundi, Nigeria, and Rwanda. A total weighted sample of 74,652 women aged 15-29 were analyzed. A multivariable logistic regression model was used to identify the factors associated with pregnancy termination at a p-value < 0.05. Results were presented using adjusted odds ratios (AOR) with 95% confidence interval. The study showed that 6.3% of women aged 15-29 reported pregnancy termination with a higher prevalence rate in Tanzania (8.8%) and lowest in Ethiopia (4%). Highest odds of pregnancy termination occurred among women aged 20-24 as compared to women aged 15-19 in Rwanda (AOR: 4.04, 95%CI 2.05, 7.97) followed by Nigeria (AOR: 2.62, 95% CI 1.99, 3.43), Kenya (AOR: 2.33, 95%CI 1.48, 3.66), Burundi (AOR: 1.99 95%CI 1.48, 2.85), Tanzania (AOR: 1.71 95%CI 1.29, 2.27), and Ethiopia (AOR: 1.69, 95% CI 1.19, 2.42). Women with no education had 4 times higher odds of pregnancy termination compared to women with higher education in Tanzania (AOR: 4.03 95%CI 1.00, 16.13) while women with no education and primary level education were 1.58 times (AOR: 1.58 95% CI 1.17, 2.13) and 1.78 times (AOR: 1.78 95% CI 1.34, 2.37) as likely to terminate pregnancy in Ethiopia. In Tanzania, the likelihood of a pregnancy termination was associated with a relationship to the household head; head (AOR: 3.66, 95% CI (2.32, 5.78), wife (AOR: 3.68, 95% CI 2.60, 5.12), and in-law (AOR:2.62, 1.71, 4.03). This study revealed that a significant number of women had pregnancy termination. Being in the age group of 20-24 & 25-29, having a lower level of education, being a domestic employee and professional, being single/never-in-union, being in the poorest and richer wealth quantile category, and being head, wife, daughter, and in-law to the household head were the significantly associated with pregnancy termination. Taking these socio-economic factors into consideration by stakeholders and specific sexual education targeted to women aged 15 to 29 would help tackle the problem

Predictors of unintended pregnancy in Kersa, Eastern Ethiopia, 2010

<p>Abstract</p> <p>Background</p> <p>In Ethiopia, little is known about pregnancy among rural women. Proper maternal health care depends on clear understanding of the reproductive health situation. The objective of this study was to identify predictors of unintended pregnancy in rural eastern Ethiopia.</p> <p>Methodology</p> <p>This study was part of pregnancy surveillance at Kersa Demographic Surveillance and Health Research Center, East Ethiopia. Pregnant women were assessed whether their current pregnancy was intended or not. Data were collected by lay interviewers using uniform questionnaire. Odds Ratio, with 95% confidence interval using multiple and multinomial logistic regression were calculated to detect level of significance.</p> <p>Results</p> <p>Unintended pregnancy was reported by 27.9% (578/2072) of the study subjects. Out of which, 440 were mistimed and 138 were not wanted. Unintended pregnancy was associated with family wealth status (OR 1.47; 95% CI 1.14, 1.90), high parity (7 +) (OR 5.18; 95% CI 3.31, 8.12), and a longer estimated time to walk to the nearest health care facility (OR 2.24; 95% CI: 1.49, 3.39).</p> <p>In the multinomial regression, women from poor family reported that their pregnancy was mistimed (OR 1.69; 95% CI 1.27, 2.25). The longer estimated time (80 + minutes) to walk to the nearest health care facility influenced the occurrence of mistimed pregnancy (OR 2.58; 95% CI: 1.65, 4.02). High parity (7+) showed a strong association to mistimed and unwanted pregnancies (OR 3.11; 95% CI 1.87, 5.12) and (OR 14.34; 95% CI 5.72, 35.98), respectively.</p> <p>Conclusions</p> <p>The economy of the family, parity, and walking distance to the nearest health care institution are strong predictors of unintended pregnancy. In order to reduce the high rate of unintended pregnancy Efforts to reach rural women with family planning services should be strengthened.</p

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49\ub74% (95% uncertainty interval [UI] 46\ub74–52\ub70). The TFR decreased from 4\ub77 livebirths (4\ub75–4\ub79) to 2\ub74 livebirths (2\ub72–2\ub75), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83\ub78 million people per year since 1985. The global population increased by 197\ub72% (193\ub73–200\ub78) since 1950, from 2\ub76 billion (2\ub75–2\ub76) to 7\ub76 billion (7\ub74–7\ub79) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2\ub70%; this rate then remained nearly constant until 1970 and then decreased to 1\ub71% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2\ub75% in 1963 to 0\ub77% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2\ub77%. The global average age increased from 26\ub76 years in 1950 to 32\ub71 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59\ub79% to 65\ub73%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1\ub70 livebirths (95% UI 0\ub79–1\ub72) in Cyprus to a high of 7\ub71 livebirths (6\ub78–7\ub74) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0\ub708 livebirths (0\ub707–0\ub709) in South Korea to 2\ub74 livebirths (2\ub72–2\ub76) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0\ub73 livebirths (0\ub73–0\ub74) in Puerto Rico to a high of 3\ub71 livebirths (3\ub70–3\ub72) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2\ub70% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Funding: Bill &amp; Melinda Gates Foundation

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4–52·0). The TFR decreased from 4·7 livebirths (4·5–4·9) to 2·4 livebirths (2·2–2·5), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3–200·8) since 1950, from 2·6 billion (2·5–2·6) to 7·6 billion (7·4–7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9–1·2) in Cyprus to a high of 7·1 livebirths (6·8–7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07–0·09) in South Korea to 2·4 livebirths (2·2–2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3–0·4) in Puerto Rico to a high of 3·1 livebirths (3·0–3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator

Global, regional, and national burden of meningitis, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Zunt JR, Kassebaum NJ, Blake N, et al. Global, regional, and national burden of meningitis, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurology. 2018;17(12):1061-1082.Background Acute meningitis has a high case-fatality rate and survivors can have severe lifelong disability. We aimed to provide a comprehensive assessment of the levels and trends of global meningitis burden that could help to guide introduction, continuation, and ongoing development of vaccines and treatment programmes. Methods The Global Burden of Diseases, Injuries, and Risk Factors (GBD) 2016 study estimated meningitis burden due to one of four types of cause: pneumococcal, meningococcal, Haemophilus influenzae type b, and a residual category of other causes. Cause-specific mortality estimates were generated via cause of death ensemble modelling of vital registration and verbal autopsy data that were subject to standardised data processing algorithms. Deaths were multiplied by the GBD standard life expectancy at age of death to estimate years of life lost, the mortality component of disability-adjusted life-years (DALYs). A systematic analysis of relevant publications and hospital and daims data was used to estimate meningitis incidence via a Bayesian meta-regression tool. Meningitis deaths and cases were split between causes with meta-regressions of aetiological proportions of mortality and incidence, respectively. Probabilities of long-term impairment by cause of meningitis were applied to survivors and used to estimate years of life lived with disability (YLDs). We assessed the relationship between burden metrics and Socio-demographic Index (SDI), a composite measure of development based on fertility, income, and education. Findings Global meningitis deaths decreased by 21.0% from 1990 to 2016, from 403 012 (95% uncertainty interval [UI] 319426-458 514) to 318 400 (265 218-408 705). Incident cases globally increased from 2.50 million (95% UI 2.19-2.91) in 1990 to 2.82 million (2.46-3.31) in 2016. Meningitis mortality and incidence were dosely related to SDI. The highest mortality rates and incidence rates were found in the peri-Sahelian countries that comprise the African meningitis belt, with six of the ten countries with the largest number of cases and deaths being located within this region. Haemophilus influenzae type b was the most common cause of incident meningitis in 1990, at 780 070 cases (95% UI 613 585-978 219) globally, but decreased the most (-494%) to become the least common cause in 2016, with 397 297 cases (291076-533 662). Meningococcus was the leading cause of meningitis mortality in 1990 (192833 deaths [95% UI 153 358-221 503] globally), whereas other meningitis was the leading cause for both deaths (136 423 [112 682-178 022]) and incident cases (1.25 million [1.06-1.49]) in 2016. Pneumococcus caused the largest number of YLDs (634458 [444 787-839 749]) in 2016, owing to its more severe long-term effects on survivors. Globally in 2016, 1.48 million (1.04-1.96) YLDs were due to meningitis compared with 21.87 million (18.20-28.28) DALYs, indicating that the contribution of mortality to meningitis burden is far greater than the contribution of disabling outcomes. Interpretation Meningitis burden remains high and progress lags substantially behind that of other vaccine-preventable diseases. Particular attention should be given to developing vaccines with broader coverage against the causes of meningitis, making these vaccines affordable in the most affected countries, improving vaccine uptake, improving access to low-cost diagnostics and therapeutics, and improving support for disabled survivors. Substantial uncertainty remains around pathogenic causes and risk factors for meningitis. Ongoing, active cause-specific surveillance of meningitis is crucial to continue and to improve monitoring of meningitis burdens and trends throughout the world. Copyright (C) The Author(s). Published by Elsevier Ltd