60 research outputs found
Perfil das Pisciculturas nas Microrregiões do Sudeste do Pará e Impactos da Pandemia da COVID-19 / Fish Farms Profile in the Southeast Microregions of Pará and Impacts of the COVID-19 Pandemic
O estado do Pará possui grande capacidade hídrica para aumentar a produção de peixes, entretanto a atividade aquícola no estado é incipiente. O objetivo do projeto foi caracterizar o perfil dos piscicultores e as pisciculturas na Mesorregião do Sudeste Paraense, com isso, foram entrevistados 24 piscicultores das Microrregiões de Redenção do Pará e Parauapebas (M1), Marabá e Tucuruí (M2) e São Félix do Xingu (M3). Os resultados levantados evidenciaram que a prática aquícola é exercida a mais de cinco anos nas microrregiões M1 e M2, sendo mais de 50% da produção para a comercialização, porém na região M3 a atividade é mais recente entre um a cinco anos e a produção para o comércio e lazer ou para subsistência familiar. A maioria dos piscicultores da região M1 já realizaram treinamento técnico para produção de peixes e mesmo que boa parte deles possuam apenas ensino fundamental completo e incompleto, a grande maioria realiza o controle financeiro. Em todas as microrregiões entrevistadas, os principais peixes produzidos são o tambaqui e seus híbridos (tambacu e tambatinga), seguido da tilápia, sendo que a maioria dos piscicultura nas regiões M2 e M3 comercializam menos que 100kg/peixes/mês em menos de cinco hectares de lâmina d’água, com sistema de produção semi-intensivo a extensivo, respectivamente. A mão de obra na microrregião M3 é predominantemente familiar com uma pessoa trabalhando diretamente na atividade. O escoamento da produção é realizado predominantemente na forma informal, com a venda dos peixes vivos tanto direto para os consumidores finais como para os atravessadores. Nas regiões M1 e M2 mais da metade dos piscicultores realizam a prática da quarentena nas propriedades e esse manejo é refletido no índice de problemas sanitários das propriedades, onde mais de 60% disseram que nunca tiveram problemas graves de mortalidade, diferentemente da microrregião M3 que a prática da quarentena é baixa, incidindo diretamente na presença de doenças nos peixes produzidos. Com a pandemia da COVID-19 os piscicultores tiveram redução de razoável a drástica com a produção dos peixes, devido ao aumento do preço dos insumos e a comercialização foi variável, pois na microrregião M1 a redução foi de até 60% e nas regiões M2 e M3 de 50% a 12,5%, respectivamente. A falta de incentivos governamentais para implementação de políticas públicas para auxiliar os pequenos produtores na legalização das propriedades como a oferta de assistência técnica gratuita, os valores elevados das rações e a ausência de frigoríficos para comercialização dos peixes no mercado formal são os maiores problemas encontrados na produção e comercialização de pescados nas Microrregiões do Sudeste do Pará
Perfil socioeconômico dos consumidores de peixes na microrregião de Redenção do Pará / Socio-economic profile of fish consumers in the microregion of the Redenção of Pará
O objetivo do projeto foi avaliar o perfil socioeconômico e de consumo de peixe da população da microrregião de Redenção do Pará. Foram entrevistadas 498 pessoas entre 0 a 80 anos de idade e a coleta dos dados foi realizada por meio de um questionário semi-estruturado, com 18 perguntas e aplicadas em escolas públicas e privadas do ensino médio, em universidade, feiras livres, mercados e pontos de comércio. O questionário foi elaborado com perguntas abordando três temáticas: consumo de pescado, fatores que influenciam o consumo e os fatores socioeconômicos dos consumidores de peixe. Foi verificado que 88,82% dos entrevistados consomem peixe, porém a preferência de consumo por proteína de origem animal é a carne bovina, seguida do frango, suíno, ovos e pescados. Os maiores consumidores de peixe foram as mulheres jovens entre na classe de 0-20 anos de idade, com frequência de consumo de uma vez ao mês ou em datas comemorativas. Os peixes redondos como o tambaqui e seus híbridos mais consumidos na região, seguido da tilápia. A aquisição dos peixes é realizada, na maioria das vezes, diretamente dos pescadores e piscicultores, feiras livres e supermercados, sendo adquirido o peixe fresco e inteiro. Na avaliação socioeconômica, verificou-se que grande parte dos consumidores de peixe, residem com três a seis pessoas na família, com renda salarial média de até dois salários mínimos. Os resultados mostraram que a renda salarial não é um fator impeditivo para o consumo de peixe, porém o baixo consumo ocorre pelo hábito alimentar da população
CARACTERIZAÇÃO DA EPIDEMIOLOGIA E PREVENÇÃO DOS AGENTES DE MICOSES SUPERFICIAIS EM PACIENTES DO LACT-FAR (SEXTA EDIÇÃO)
HERV-K and HERV-W transcriptional activity in myalgic encephalomyelitis/chronic fatigue syndrome.
BACKGROUND: Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/MS) is an incapacitating chronic disease that dramatically compromise the life quality. The CFS/ME pathogenesis is multifactorial, and it is believed that immunological, metabolic and environmental factors play a role. It is well documented an increased activity of Human endogenous retroviruses (HERVs) from different families in autoimmune and neurological diseases, making these elements good candidates for biomarkers or even triggers for such diseases. METHODS: Here the expression of Endogenous retroviruses K and W (HERV-K and HERV-W) was determined in blood from moderately and severely affected ME/CFS patients through real time PCR. RESULTS: HERV-K was overexpressed only in moderately affected individuals but HERV-W showed no difference. CONCLUSIONS: This is the first report about HERV-K differential expression in moderate ME/CFS. Although the relationship between HERVs and ME/CFS has yet to be proven, the observation of this phenomenon deserves further attention
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
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 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
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
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 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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