Effect of Weed Interference and Plant Density on Maize Grain Yield

Maize is one of most important food crop grown in Benishangul Gumuz Regional State, Ethiopia. However, its productivity is very low due to  inappropriate weed and soil nutrient management and lower plant density. Thus, a field experiment was carried out during 2016/17 cropping season to  evaluate effect of weeding frequency and plant densities on yield, and yield components of maize at Assosa Agricultural Research Centre. The treatments  consisted of four levels of weeding frequencies (weedy check, once hand weeding, twice hand weeding and weed free) and four levels of plant densities  (31,250,44,444, 53,333 and 62,500 plants ha-1), which were factorial arranged in Randomized Complete Block Design (RCBD) with three replications. The  results of the study revealed that grain yield was significantly (P<0.01) affected by the main effects of weeding frequency and plant density. The highest  grain yields (7394.5, and 7273.6 kg ha-1) were recorded for weed free and twice hand weeding, respectively and the lowest grain yield (918.9 kg ha-1) from  the weedy check. The highest grain yield (5485.8 kg ha-1) was obtained at a plant density of 53,333 plants ha-1 and the lowest (4457.2 kg ha-1) at a  density of 31,250 plants ha- 1. Grain yield was much more reduced due to competition from weeds (87.5%) than due to low plant density (18%). Significant  interaction effect of weeding frequency and plant density was observed on number of ears plant-1, number of kernel rows ear-1, above  ground dry biomass and relative grain yield loss. Twice hand weeding and a plant density of 53,333 plants ha-1 would be some more suitable practices for  attaining optimum grain yield for the hybrid maize BH 546 in the study area. &nbsp

Improving the Quality of Clinical Coding through Mapping of National Classification of Diseases (NCoD) and International Classification of Disease (ICD-10).

AbstractIntroduction: Medical coding is the transformation of healthcare diagnosis, procedures, medical services, and equipment into universal medical alphanumeric codes. Utilization of international disease classification provides higher-quality information for measuring healthcare service quality, safety, and efficacy. The Ethiopian National classification of disease (NCoD) was developed as part of Health Management information System (HMIS) reform with consideration of accommodating code in International Classification of disease (ICD-10). There is limited resource about the utilization status and related determinants of NCoD by health care professionals at tertiary level hospitals. This study is designed to assess the utilization status of NCoD and improve the quality of clinical coding through mapping of NCoD and ICD-10. Methods: Quasi-experimental study considering “Mapping” as an intervention was employed in this study. Retrospective medical record reviews were carried out to assess the utilization of NCoD and its challenges at Tikur Anebsa Specialized Hospital (TASH) for a period of one year (2018/2019). Qualitative approach used to get expert insight on NCoD implementation challenges and design of mapping exercises as an intervention. Seven thousand five hundred forty-seven (20%) of the medical records from the total of 37,734 medical records were selected randomly for review. A data abstraction checklist was developed to collect relevant information on individual patient charts, patient electronic records specific on a confirmed diagnosis. The reference mapping approach was employed for the mapping output between ICD-10 and NCoD. Both ICD-10 and NCoD were mapped side by side using percentage comparison and absolute difference. Result: Data for document review was taken from the electronic medical record database. Out of the total, 3021 (40%) of records were miss-classified based on the national classification of disease. From the miss-coded record, 1749 (58%) of them used ICD code to classify the diagnosis. Reasons provided for poor utilization of NCoD among physicians include, perception of having a limited list of diagnosis in the NCoD, not being familiarized, inadequate capacity building about NCoD use, and absence of enforcing mechanism on the use of standard diagnostic coding among professionals. Utilization of disease classification coding provides higher-quality information for measuring healthcare service quality, safety, and efficacy. This will in turn provide better data for quality measurement and medical error reduction (patient safety), outcomes measurement, operational planning, and healthcare delivery systems design and reporting. Conclusion: Extended NCoD categories were mapped from ICD-10. Standard ways of coding disease diagnosis and coding of new cases into the existing category was established. This study recommends that due emphasis should be given in monitoring and evaluation of medical coding knowledge and adherence of health professionals, and it should be supported with appropriate technologies to improve the accessibility and quality of health information. [Ethiop. J. Health Dev. 2021; 35(SI-1):59-65] Keywords: Mapping, NCoD, ICD, Clinical Coding, Diagnosis, Health Information Syste

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS: We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS: Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, an

Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-Adjusted life-years for 29 cancer groups, 1990 to 2017 : A systematic analysis for the global burden of disease study

Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-Adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572000 deaths and 15.2 million DALYs), and stomach cancer (542000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601000 deaths and 17.4 million DALYs), TBL cancer (596000 deaths and 12.6 million DALYs), and colorectal cancer (414000 deaths and 8.3 million DALYs). Conclusions and Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care. © 2019 American Medical Association. All rights reserved.Peer reviewe

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic

Implementation of Human Development Model Impact on Data Quality and Information Use in Addis Ababa, Ethiopia

AbstractsBackground: Designing of human development model is a crucial role towards addressing data quality and information use at service delivery point and administrative level. A human development model is implemented through capacity building approach of competence-based training, mentorship, supportive supervision, experience sharing, and quality improvement initiative. This study aimed to synthesize the level and significance of a change in Routine health information systems (RHIS) structure, input data quality and information use because of human development model implementation. Methods: A quasi-experimental study design was employed to assess the impact of the human development model on RHIS structure and implementation, data quality, and administrative data use in Addis Ababa city administration. A total of 31 health centers, three sub-cities, and three hospitals and 954 health workers from respective health facilities and administrative levels were included in this study. Standard Performance of Routine Information System Management data quality and information use assessment tool was used to evaluate the contribution of the model. The data analysis covers the period between 2018 and 2020, 2018 was the base year and 2020 is the end period. The difference in difference data analysis technique was used to capture any change between the two periods and to investigate significant differences in HIS structure and implementation, data quality, and information use at administrative and service delivery points. Result: A total of 954 health workers were trained. The mean difference between pre- and post-training evaluation results was 9.3 with 95% (CI of 3.8-14.6, p-value, &lt;0.001). Substantial changes were documented in the last mentorship session in data quality and information use. Data quality and information use was 96.4 with (95% CI, 94.4-98.4, SD, 5.6) and 80.6 with (95 % CI,76.8-84.4, SD,10.5) respectively at service delivery point. The mean difference before and after implementation of the human development model for data quality and data use was 40.7 with (95% CI, 36.6-44.8, p-value, &lt;0.0001) and 19.7 with (95% CI, 15.6-23.8, p-value, &lt;0.0001), at health facilities level, respectively. The mean score of data quality and information use after implementation of the human development model was 93.0%nd 85.0% at the sub-cities level, respectively. Conclusion: The implementation of the human development model was very timely approach to ensure data quality and information use at all levels. Use of competence-based training, practical application with proper follow-up of application of knowledge and skills gained to real-life activities also contributed to the improvement of data quality and information use. [Ethiop. J. Health Dev. 2021; 35(SI-1):50-58] Keywords: Human development model, Data quality, information use, capacity-building, mentorshi

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016 : a systematic analysis for the Global Burden of Disease Study 2016

Background Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. Methods We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0.5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Sociodemographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. Findings Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86.9 years (95% UI 86.7-87.2), and for men in Singapore, at 81.3 years (78.8-83.7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap between male and female life expectancy increased with progression to higher levels of SDI. Some countries with exceptional health performance in 1990 in terms of the difference in observed to expected life expectancy at birth had slower progress on the same measure in 2016. Interpretation Globally, mortality rates have decreased across all age groups over the past five decades, with the largest improvements occurring among children younger than 5 years. However, at the national level, considerable heterogeneity remains in terms of both level and rate of changes in age-specific mortality; increases in mortality for certain age groups occurred in some locations. We found evidence that the absolute gap between countries in age-specific death rates has declined, although the relative gap for some age-sex groups increased. Countries that now lead in terms of having higher observed life expectancy than that expected on the basis of development alone, or locations that have either increased this advantage or rapidly decreased the deficit from expected levels, could provide insight into the means to accelerate progress in nations where progress has stalled. Copyright (C) The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

MAPPING LOCAL PATTERNS OF CHILDHOOD OVERWEIGHT AND WASTING IN LOW- AND MIDDLE-INCOME COUNTRIES BETWEEN 2000 AND 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic