37 research outputs found

    Risk-Returns of Forward Contracting Southern Row Crops with Crop Revenue Insurance

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    This study evaluated the risk and return associated with various levels of forward contracting for southern row crops, specifically corn, soybean, and rice, in conjunction with different coverage levels of the Revenue Protection (RP) crop insurance program and government support plans. Forward contracting is a strategy to manage price risk by transferring ownership of physical grain from a seller to a buyer at a pre-agreed time. RP is a return-based crop insurance program offering coverage levels ranging from 50-85 percent in 5 percent increments, which allows producers to hedge against yield or price risks. Additionally, the study analyzed the effectiveness of the Agricultural Risk Coverage (ARC) and Price Loss Coverage (PLC) commodity programs, both of which fall under Title I of the 2014 farm bill, to support farmers during return or price declines. Finally, the expected-utility conceptual framework and certainty equivalent were utilized to quantify the risk and return during different times, level of forward contracting, and level of RP for producers

    Risk-Returns of Forward Contracting Southern Row Crops with Crop Revenue Insurance

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    This study evaluated the risk and return associated with various levels of forward contracting for southern row crops, specifically corn, soybean, and rice, in conjunction with different coverage levels of the Revenue Protection (RP) crop insurance program and government support plans. Forward contracting is a strategy to manage price risk by transferring ownership of physical grain from a seller to a buyer at a pre-agreed time. RP is a return-based crop insurance program offering coverage levels ranging from 50-85 percent in 5 percent increments, which allows producers to hedge against yield or price risks. Additionally, the study analyzed the effectiveness of the Agricultural Risk Coverage (ARC) and Price Loss Coverage (PLC) commodity programs, both of which fall under Title I of the 2014 farm bill, to support farmers during return or price declines. Finally, the expected-utility conceptual framework and certainty equivalent were utilized to quantify the risk and return during different times, level of forward contracting, and level of RP for producers

    Effects of different combinations of poultry manure and urea on growth, yield and economics of garlic (Allium sativum L.)

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    A field experiment was carried out in garlic (Allium sativum L.) in Randomized Complete Block Design (RCBD) with four replications and five treatments in horticulture farm of Agriculture and Forestry University, Chitwan, Nepal to find out the efficacy of different combination of poultry manure and Urea as nitrogen fertilizers in its yield and yield attributes. The five treatments used for experiment were designed altering the recommended nitrogen dose through different sources i.e. (T1) 100% Urea, (T2) 7% Urea and 25% poultry manure, (T3) 50% Urea and 50% poultry manure, (T4) 25% Urea and 75% poultry manure and (T5) 100% poultry manure. The data regarding to the plant height, number of cloves, diameter of bulbs and fresh bulb weight were taken. In case of plant height, non-significant result was found between various treatments. The number of cloves was found highest in T5 (24.69±1.30), the diameter of bulb was found highest in T2 (3.93±0.39 cm), fresh bulb weight was found highest in T2 (14.32±0.39 gm) and total bulb yield was found highest in T2 (7.16±0.19 t/ha) which were significant at 5 % level of significance. The total bulb yield was found positively correlated (r=0.53) with diameter of bulb at 1 % level of significance. The benefit cost (B/C) ratio was found highest in T2 (1.54) and lowest in T3 (1.28). So 75% Urea and 25 % Poultry Manure stood one of the best combinations of nitrogen fertilizers providing higher economic yields

    Factors Affecting the Productivity of Coffee in Gulmi and Arghakhanchi Districts of Nepal

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    Coffee is one of the major potential cash crops with lucrative export value grown in mid-hills of Nepal. Nepalese coffee production has suffered long by low productivity. Research was conducted from February to May, 2019 to analyze the factors affecting the productivity of coffee in Arghakhanchi and Gulmi districts of Nepal. These two districts were, purposively selected for this study taking account of comparative advantage and past studies recommendations for coffee sector. Altogether, 100 coffee growing households 50 from each, Arghakhanchi and Gulmi, were sampled by using multistage sampling technique. A pre-tested semi-structured interview schedule was used to collect the primary information while secondary information was collected reviewing the relevant publications. Ordinary Least Square (OLS) regression model was used to determine the factors affecting the productivity of coffee. The study revealed that the number of active family members involved in coffee production (0.000), adoption of income diversification through intercropping (0.005), training (0.072) and technical assistance (0.021) had positive and significant effect on coffee productivity. Encouraging the household to have coffee production as their primary occupation, providing technical assistance on rational land utilization and intercropping and strengthening the skill and knowledge of farmers through trainings could significantly support in increasing the productivity of coffee

    Factors affecting the productivity of coffee in Gulmi and Arghakhanchi districts of Nepal

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    Coffee is one of the major potential cash crops with lucrative export value grown in mid-hills of Nepal. Nepalese coffee production has suffered long by low productivity. Research was conducted from February to May, 2019 to analyze the factors affecting the productivity of coffee in Arghakhanchi and Gulmi districts of Nepal. These two districts were, purposively selected for this study taking account of comparative advantage and past studies recommendations for coffee sector. Altogether, 100 coffee growing households 50 from each, Arghakhanchi and Gulmi, were sampled by using multistage sampling technique. A pre-tested semi-structured interview schedule was used to collect the primary information while secondary information was collected reviewing the relevant publications. Ordinary Least Square (OLS) regression model was used to determine the factors affecting the productivity of coffee. The study revealed that the number of active family members involved in coffee production (0.000), adoption of income diversification through intercropping (0.005), training (0.072) and technical assistance (0.021) had positive and significant effect on coffee productivity. Encouraging the household to have coffee production as their primary occupation, providing technical assistance on rational land utilization and intercropping and strengthening the skill and knowledge of farmers through trainings could significantly support in increasing the productivity of coffee

    Determinants of gross income from carp production in Bara district, Nepal

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    A study was conducted from March to June 2020 to analyze the determinants of gross income from carp production in the Bara district of Nepal. Altogether, 90 carp producers, 45 each from Simraungadh and Pachrauta municipality in equal basis were sampled by using cluster sampling technique. Primary information was collected through a pre-tested semi-structured interview-based schedule while secondary information was collected reviewing the relevant publications. Data was entered in SPSS 25 and analyzed using STATA 12.1. The results  revealed that the cost of labor, cost of feed, assistances and services, and training had significant positive effect on gross income from carp prodcuiton. Furthermore, lack of quality inputs was identified as the most severe production problems whereas Dhalta to be given was recognized as the most severe marketing problems. Thus, encouraging the carp producer to manage the cost of labor and cost of feed deliberately, rationally providing the assistance and services and strengthening the skills and knowledge of producer through training could significantly increase gross income from carp production

    Global, regional, and national mortality among young people aged 10–24 years, 1950–2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Summary: Background Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. We aimed to analyse data on the number of deaths, years of life lost, and mortality rates by sex and age group in people aged 10–24 years in 204 countries and territories from 1950 to 2019 by use of estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods We report trends in estimated total numbers of deaths and mortality rate per 100 000 population in young people aged 10–24 years by age group (10–14 years, 15–19 years, and 20–24 years) and sex in 204 countries and territories between 1950 and 2019 for all causes, and between 1980 and 2019 by cause of death. We analyse variation in outcomes by region, age group, and sex, and compare annual rate of change in mortality in young people aged 10–24 years with that in children aged 0–9 years from 1990 to 2019. We then analyse the association between mortality in people aged 10–24 years and socioeconomic development using the GBD Socio-demographic Index (SDI), a composite measure based on average national educational attainment in people older than 15 years, total fertility rate in people younger than 25 years, and income per capita. We assess the association between SDI and all-cause mortality in 2019, and analyse the ratio of observed to expected mortality by SDI using the most recent available data release (2017). Findings In 2019 there were 1·49 million deaths (95% uncertainty interval 1·39–1·59) worldwide in people aged 10–24 years, of which 61% occurred in males. 32·7% of all adolescent deaths were due to transport injuries, unintentional injuries, or interpersonal violence and conflict; 32·1% were due to communicable, nutritional, or maternal causes; 27·0% were due to non-communicable diseases; and 8·2% were due to self-harm. Since 1950, deaths in this age group decreased by 30·0% in females and 15·3% in males, and sex-based differences in mortality rate have widened in most regions of the world. Geographical variation has also increased, particularly in people aged 10–14 years. Since 1980, communicable and maternal causes of death have decreased sharply as a proportion of total deaths in most GBD super-regions, but remain some of the most common causes in sub-Saharan Africa and south Asia, where more than half of all adolescent deaths occur. Annual percentage decrease in all-cause mortality rate since 1990 in adolescents aged 15–19 years was 1·3% in males and 1·6% in females, almost half that of males aged 1–4 years (2·4%), and around a third less than in females aged 1–4 years (2·5%). The proportion of global deaths in people aged 0–24 years that occurred in people aged 10–24 years more than doubled between 1950 and 2019, from 9·5% to 21·6%. Interpretation Variation in adolescent mortality between countries and by sex is widening, driven by poor progress in reducing deaths in males and older adolescents. Improving global adolescent mortality will require action to address the specific vulnerabilities of this age group, which are being overlooked. Furthermore, indirect effects of the COVID-19 pandemic are likely to jeopardise efforts to improve health outcomes including mortality in young people aged 10–24 years. There is an urgent need to respond to the changing global burden of adolescent mortality, address inequities where they occur, and improve the availability and quality of primary mortality data in this age group

    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : a systematic analysis for the Global Burden of Disease Study 2019

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    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, most other GBD super-regions had slowed rates of progress in 2010-2019 relative to 1990-2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0.79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388.9 million (358.6-421.3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3.1 billion (3.0-3.2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968.1 million [903.5-1040.3]) residing in south Asia. Interpretation: The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people-the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close-or how far-all populations are in benefiting from UHC

    Adolescent transport and unintentional injuries: a systematic analysis using the Global Burden of Disease Study 2019

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    Background: Globally, transport and unintentional injuries persist as leading preventable causes of mortality and morbidity for adolescents. We sought to report comprehensive trends in injury-related mortality and morbidity for adolescents aged 10–24 years during the past three decades. Methods: Using the Global Burden of Disease, Injuries, and Risk Factors 2019 Study, we analysed mortality and disability-adjusted life-years (DALYs) attributed to transport and unintentional injuries for adolescents in 204 countries. Burden is reported in absolute numbers and age-standardised rates per 100 000 population by sex, age group (10–14, 15–19, and 20–24 years), and sociodemographic index (SDI) with 95% uncertainty intervals (UIs). We report percentage changes in deaths and DALYs between 1990 and 2019. Findings: In 2019, 369 061 deaths (of which 214 337 [58%] were transport related) and 31·1 million DALYs (of which 16·2 million [52%] were transport related) among adolescents aged 10–24 years were caused by transport and unintentional injuries combined. If compared with other causes, transport and unintentional injuries combined accounted for 25% of deaths and 14% of DALYs in 2019, and showed little improvement from 1990 when such injuries accounted for 26% of adolescent deaths and 17% of adolescent DALYs. Throughout adolescence, transport and unintentional injury fatality rates increased by age group. The unintentional injury burden was higher among males than females for all injury types, except for injuries related to fire, heat, and hot substances, or to adverse effects of medical treatment. From 1990 to 2019, global mortality rates declined by 34·4% (from 17·5 to 11·5 per 100 000) for transport injuries, and by 47·7% (from 15·9 to 8·3 per 100 000) for unintentional injuries. However, in low-SDI nations the absolute number of deaths increased (by 80·5% to 42 774 for transport injuries and by 39·4% to 31 961 for unintentional injuries). In the high-SDI quintile in 2010–19, the rate per 100 000 of transport injury DALYs was reduced by 16·7%, from 838 in 2010 to 699 in 2019. This was a substantially slower pace of reduction compared with the 48·5% reduction between 1990 and 2010, from 1626 per 100 000 in 1990 to 838 per 100 000 in 2010. Between 2010 and 2019, the rate of unintentional injury DALYs per 100 000 also remained largely unchanged in high-SDI countries (555 in 2010 vs 554 in 2019; 0·2% reduction). The number and rate of adolescent deaths and DALYs owing to environmental heat and cold exposure increased for the high-SDI quintile during 2010–19. Interpretation: As other causes of mortality are addressed, inadequate progress in reducing transport and unintentional injury mortality as a proportion of adolescent deaths becomes apparent. The relative shift in the burden of injury from high-SDI countries to low and low–middle-SDI countries necessitates focused action, including global donor, government, and industry investment in injury prevention. The persisting burden of DALYs related to transport and unintentional injuries indicates a need to prioritise innovative measures for the primary prevention of adolescent injury. Funding: Bill & Melinda Gates Foundation

    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

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    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, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC
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