and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEWThe GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).FINDINGS In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCEThe results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Summary Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast,...

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3•5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.

Background Dysmenorrhea is an important health problem of adolescents in school, as well as health practitioners, that badly affects the daily activities and quality of life. The aim of this study was to measure the prevalence of dysmenorrhea and assess its management practice among University of Gondar students. Methods A cross-sectional study was done from April 06 to May 08, 2016, on female students of University of Gondar. Descriptive and binary logistic regression analyses were used to describe and assess the association between different variables. Results More than two-thirds (75.3%) of the respondents were nonmedical students and the prevalence of dysmenorrhea was 77.6%. About half (50.6%) of the participants reported that they have a family history of dysmenorrhea and experienced continuous type of pain (53%) which lasts 1-2 days (47.8%). Abdominal spasm (70.4%), back pain (69.7%) fatigue, and weakness (63.5%) were the most commonly experienced dysmenorrhea symptoms. More than half (63%) of the respondents had encountered social withdrawal and decrease in academic performance (51.4%). More than two-thirds (63.8%) of the respondents use home remedies as a primary management option. Ibuprofen and diclofenac were the most commonly used medications to manage dysmenorrhea. Conclusions The present study revealed that high proportion of University of Gondar female students had dysmenorrhea. Findings suggest the need for educating adolescent girls on appropriate and effective management of dysmenorrhea.

ObjectiveThe aim of this study was to assess the pattern of cardiovascular diseases (CVDs), their clinical characteristics, and associated factors in the outpatient department of the chronic illness clinic of Gondar University Referral Hospital.MethodA retrospective cross-sectional study was conducted among patients on follow-up at the outpatient chronic illness clinic of the hospital from October 2010 to October 2015. The source population for the study included patients with a diagnosis of CVD whose medical records have the required socio-demographic information during the study period. The data were collected from August 2015 to December 2015. Chi-square and binary logistic regression tests were performed to test the significance of difference among predictive variables and CVDs.ResultsOf 1105 patient medical records, 862 fulfilled the inclusion criteria. The majority of the patients were females (65%) and living in urban areas (62.7%). Hypertension accounted for the majority (62.3%) of CVDs followed by heart failure (HF) (23.9%). Headache was the leading chief complaint among the patients (37.7%) upon diagnosis and was the prominent clinical feature in more than half of the patients during their course of follow-up. Higher proportions of dyslipidemia (85.7%), hypertension (72.8%), and ischemic heart disease (IHD) (73.2%) were associated with urban residency (P<0.01). Patients from rural areas (crude odds ratio [COR] =1.306 [95% confidence interval 1.026–2.166], adjusted odds ratio [AOR] =1.272 [95% confidence interval 1.017–2.030]) and those with comorbidity illnesses (COR= 1.813 [1.279–2.782], AOR =1.551 [95% confidence interval 1.177–2.705]) were more likely to have poor CVD outcome (P<0.05).ConclusionHypertension was found to be the most frequent CVD followed by HF, and hypertensive heart disease was the leading cause of cardiac diseases. Most of the patients had improved assessment in the last follow-up, but patients from rural regions and those with comorbidty had higher likelihood of poor cardiovascular outcome.

Background: Globally, heart failure (HF) has been recognized as one of the major cardiovascular disorder with high morbidity, mortality and considerable social impact. In Sub Saharan African countries, HF has turned out as a leading form of cardiovascular diseases, and has considerable socioeconomic impact. However, there are differences in clinical characteristics and survival status among patients with preserved (HFpEF) and reduced (HFrEF) ejection fraction. The aim of this study is to outline the clinical characteristics and medication profile, assess the survival status and prognostic factors of Ethiopian HF patients with HFrEF and HFpEF. Methods: A retrospective cohort study was carried out and we employed medical records of patient's, admitted as a result of HF to the University of Gondar Referral Hospital in the period between December 02, 2010 and December 01, 2015 due to HF. Kaplan Meier curve was used to analyze the survival status and log rank test was used to compare the curves. Cox regression was used to analyze independent predictors of mortality in all HF patients. Results: Of the 850 patients who were admitted due to HF, 311 patients met the inclusion criteria. Majority of the patients had HFpEF (52.73%) and tend to be women (76.22%). They predominantly had etiologies of valvular and hypertensive heart diseases, and took calcium channel blockers and anticoagulants. Conversely, patients with HFrEF had etiologies of ischemic heart disease and dilated cardiomyopathy and were prescribed angiotensine converting inhibitors (ACEI) and beta blockers. Kaplan Meier curves and Log rank test (p = 0.807) showed that there was no statistically significant difference in the mortality difference among patients with HFpEF and HFrEF. On the other hand, Cox regression analysis showed advanced age, lower sodium level, higher creatinine level and absence of medications like ACEI, spironolactone and statins independently predicted mortality in all HF patients. Conclusions: Different clinical characteristics were found in both groups of HF patients. There was no difference in survival outcome between patients with HFrEF and HFpEF.

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8·8 trillion (95% uncertainty interval [UI] 8·7–8·8) or $1132 (1119–1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40·4 billion (0·5%, 95% UI 0·5–0·5) was development assistance for health provided to low-income and middle-income countries, which made up 24·6% (UI 24·0–25·1) of total spending in low-income countries. We estimate that $54·8 billion in development assistance for health was disbursed in 2020. Of this, $13·7 billion was targeted toward the COVID-19 health response. $12·3 billion was newly committed and $1·4 billion was repurposed from existing health projects. $3·1 billion (22·4%) of the funds focused on country-level coordination and $2·4 billion (17·9%) was for supply chain and logistics. Only $714·4 million (7·7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34·3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448–1591) per person in 2050, although spending across countries is expected to remain varied. Interpretatio...

BackgroundA considerable proportion of cardiovascular events could be attributed to poor adherence to antihypertensive medications. Adverse effects can be severe enough to affect adherence to antihypertensive medications. This study aimed to measure the contribution of adverse effects on antihypertensive medications adherence.MethodsThe study was conducted from May 1 to June 30, 2017, at the ambulatory clinic of University of Gondar Comprehensive Specialized Hospital (UOGCSH) in Gondar town. A binary logistic regression was performed to determine the significance of the association between adverse effects and adherence to antihypertensive medications. An institution-based cross-sectional study was conducted by administering a questionnaire to hypertensive patients who came for follow-up at the ambulatory clinic of UOGCSH. Level of adherence to antihypertensive medications was used as outcome measure.ResultsA total of 249 patients were included in the final analysis with a mean age of 56.51 years and a female majority (53%). The following variables were identified as predictors of poor adherence: tiredness [AOR (95% CI): 3.802 (1.723–8.391), p = 0.001], muscle pain [AOR (95% CI): 5.199 (1.407–19.214), p = 0.013], poor sleep [AOR (95% CI): 4.891 (1.578–15.160), p = 0.006] and, believing that the symptoms were caused by antihypertensive medications [AOR (95% CI): 3.249 (1.248–8.456), p = 0.016].ConclusionAdverse effect significantly contributes to antihypertensive medication non-adherence among hypertensive patients.