Determinantes Sociodemográficos de la nutrición infantil en Colombia

 Objetivo: Estimar los determinantes sociodemográficos de la nutrición infantil en Colombia. Materiales y métodos: Estudio transversal a partir del microdato de la Encuesta Nacio- nal de Demografía y Salud 2010, agrupados por regiones. Se estimaron cuatro modelos de regresión múltiple, en los que las variables dependientes fueron el puntaje Z de la Talla para la Edad (TPE) y del Peso para la Edad (PPE) con el fin de establecer los factores sociodemográ- ficos de mayor incidencia, utilizando el método de Mínimos Cuadrados Ordinarios (MCO). Resultados: La región Caribe y Bogotá presentaron mayores problemas de desnutrición infantil. En el quintil de ingreso más bajo el promedio de TPE en la región Caribe fue de -1,18 (RIC -1,91 a -0,42), mientras que en el quintil más alto fue de -0,29 (RIC -1,57 a -0,12). En Bogotá el promedio fue de -2,22 (RIC -2,37 a -2,06) en el primer quintil de ingreso y -0,83 (RIC-1,38 a -0,26) en el quinto quintil. El ingreso, el índice de masa corporal y la educación de la madre tienen un impacto positivo en la nutrición de los niños. El orden de nacimiento y la edad del niño mostraron que tienen incidencia negativa. Conclusiones: En las regiones las diferencias en la talla de los niños son significativas según la posición socioeconómica del hogar. Elevar el nivel de ingresos de la población y los años de escolaridad, así como la prevención de embarazos en adolescentes, podría jugar un papel fundamental en la disminución de la de desnutrición

Costos asociados a enfermedades transmitidas por alimentos en el régimen subsidiado en salud – Bolívar

Objectives: Estimate the direct costs of Foodborne diseases in the insured poor population in the department of Bolivar, Colombia. Methods: Cross-sectional descriptive and analytical retrospective study based on the microdata of the Individual Registries of Health Services Delivery (RIPS) of the year 2017 of an insurer of the department of Bolívar. The ICD-10 diagnostic codes included were A01 - A04, A09, A23 and B23. The costs were estimated in US dollars (USD) of 2017, with the perspective of the third payer. Results: 68.6% of the costs were generated by male people, with respect to age groups, it was obtained that people over 45 years generated costs of 228,582 USD (54.2%), followed by people between 15 and 44 years 65,960 USD (15.6%), children between 1 and 4 years 63,972 USD (15.2%), children under one year 46,377 USD (11.0%) and people between 5 and 14 years 17,202 USD (4.1%). In terms of services, hospitalization accounted for 52.3%, followed by emergencies (13.2%), medications (12.6%) and diagnostic support (11.5%). Finally, the diagnosis of Diarrhea and gastroenteritis of presumed infectious origin represented 90% of the cost (USD 382,645). Conclusions: The use of health services and the direct costs of Foodborne diseases in Colombia are high and are related to the severity of the symptoms. Health policies at the national level aimed at the effective control of the social determinants of health are necessary and will play an important role in reducing the associated economic impact.Objetivos: Estimar los costos directos de las enfermedades transmitidas por los alimentos en la población pobre asegurada en el departamento de Bolívar, Colombia. Métodos: Estudio retrospectivo, descriptivo y descriptivo transversal, basado en los microdatos de los Registros Individuales de Prestación de Servicios de Salud (RIPS) del año 2017 de una aseguradora del departamento de Bolívar. Los códigos de diagnóstico CIE-10 incluidos fueron A01 - A04, A09, A23 y B23. Los costos se estimaron en dólares estadounidenses (USD) de 2017, desde la perspectiva del tercer pagador. Resultados: el 68.6% de los costos fueron generados por hombres, con respecto a los grupos de edad, se obtuvo que las personas mayores de 45 años generaron costos de 228,582 USD (54.2%), seguidos por personas entre 15 y 44 años 65,960 USD (15.6%), niños entre 1 y 4 años 63,972 USD (15.2%), niños menores de un año 46,377 USD (11.0%) y personas entre 5 y 14 años 17,202 USD (4.1%). En términos de servicios, la hospitalización representó el 52,3%, seguida de las emergencias (13,2%), los medicamentos (12,6%) y el apoyo diagnóstico (11,5%). Finalmente, el diagnóstico de diarrea y gastroenteritis de presunto origen infeccioso representó el 90% del costo (USD 382,645). Conclusiones: el uso de servicios de salud y los costos directos de las enfermedades transmitidas por los alimentos en Colombia son altos y están relacionados con la gravedad de los síntomas. Las políticas de salud a nivel nacional dirigidas al control efectivo de los determinantes sociales de la salud son necesarias y desempeñarán un papel importante en la reducción del impacto económico asociado

Socioeconomic determinants of nutritional status in children under five attended at the Hospital Infantil Napoleón Franco Pareja

Objetivo: Determinar los factores sociales y económicos que afectan el estado nutricional de los niños menores de cinco años. Metodología: Se llevó a cabo un estudio de corte transversal con una muestra de 600 menores que asistieron al Hospital Infantil Napoleón Franco Pareja (HINFP) a cuyas madres se les aplicó un instrumento estandarizado para capturar la información socioeconómica y el estado nutricional del niño y de la madre. Se estimaron dos modelos econométricos de Umbral Generalizado, tomando como variable dependientes talla para la edad y peso para la talla y como variables independientes: peso al nacer del menor, número de controles prenatales, nivel de ingresos del hogar, uso de servicios de alcantarillado y acueducto, índice de masa corporal (IMC) de la madre, entre otras.  Resultados: De acuerdo al indicador de talla para la edad, el 48.05% de los niños sufren de desnutrición crónica. El indicador de peso para la talla reflejó que el 22.09% de los niños tuvieron un déficit en su masa corporal (desnutrición aguda) y un 13.53% se encontraba en sobrepeso u obesidad. El 76.02% de las madres con hijos con talla para la edad normal tienen educación media o superior. El 56% de los niños pertenecientes a hogares con ingresos inferiores al salario mínimo mensual legal vigente tuvieron problemas de desnutrición aguda. Respecto a los determinantes, mayores ingresos reducen la probabilidad de que un niño sufra desnutrición. El tiempo de lactancia materna, la ocupación y el estado nutricional de la madre resultaron ser factores protectores. El incremento de la edad gestacional al nacimiento, aumenta la probabilidad de tener una talla normal. Conclusiones: La presente investigación genera evidencia para revisar la política sanitaria de nutrición infantil. Elevar el nivel de ingresos y promover la lactancia materna mejorarían el estado nutricional de los niños.Objective: To determine the social and economic factors that affect he nutritional status of children under five years of age. Methods: A cross-sectional study carried out with a sample of 600 children were attended the Children’s Hospital Napoleón Franco Pareja (HINFP) whose mothers were administered a standardized instrument to capture the socioeconomic information and nutritional status of the child. Two econometric models were estimated using Generalized Threshold, taking as dependent variable-height for age and weight for height and as independent variables: birth weight of the child, number of prenatal controls, level of household income, use of sewerage and aqueduct services, mother’s body mass index (BMI), among others. Results: According to the height for age indicator, 48.05% of children suffer from chronic malnutrition. The indicator weight for height showed that 22.09% of children have a deficit in their body mass (acute malnutrition) and 13.53% were overweight or obese. 76.02% of mothers of children with normal height for age have completed secondary or higher education. 56% of children in households with incomes below current legal monthly minimum wage have acute malnutrition problems. Regarding the determinants, higher incomes reduce the likelihood that a child would suffer malnutrition. Breastfeeding time, occupation and maternal nutritional status are protective factors. Increasing gestational age at birth increases the likelihood of a normal size. Conclusions: This research generated evidence for health policy review of child nutrition. The raising of incomes and the promotion breastfeeding would improve the nutritional status of children.&nbsp

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

Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

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$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

Background The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic; characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic; and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95$7·3 trillion (95% UI 7·2–7·4) in 2019; 293·7 times the $24·8 billion (95$43·1 billion in development assistance was provided to maintain or improve health. The pandemic led to an unprecedented increase in development assistance targeted towards health; in 2020 and 2021, $1·8 billion in DAH contributions was provided towards pandemic preparedness in LMICs, and$37·8 billion was provided for the health-related COVID-19 response. Although the support for pandemic preparedness is 12·2% of the recommended target by the High-Level Independent Panel (HLIP), the support provided for the health-related COVID-19 response is 252·2% of the recommended target. Additionally, projected spending estimates suggest that between 2022 and 2026, governments in 17 (95% UI 11–21) of the 137 LMICs will observe an increase in national government health spending equivalent to an addition of 1% of GDP, as recommended by the HLIP. Interpretation There was an unprecedented scale-up in DAH in 2020 and 2021. We have a unique opportunity at this time to sustain funding for crucial global health functions, including pandemic preparedness. However, historical patterns of underfunding of pandemic preparedness suggest that deliberate effort must be made to ensure funding is maintained

Diseño de un modelo de gestión de riesgos en la comercialización internacional de mercancías en las Pymes

El presente trabajo de investigación muestra el diseño de un modelo de gestión de riegos para la comercialización internacional de mercancías en las Pymes de la ciudad de Cartagena-Colombia. La metodología utilizada fue de tipo aplicada y de estudio de casos, la cual permitió conocer los procedimientos y riesgos a los que están expuestas las empresas seleccionadas (81) en proceso de comercio exterior. Los resultados muestran que las operaciones en el proceso de comercio exterior de las Pymes que presentaron mayor impacto fueron la entrada de nuevos competidores con 66%, los de mayor aversión, el riesgo de contaminación de la mercancía (85%) y de mediano impacto el riesgo de falta de mecanismos inadecuados para el seguimiento y control de los procesos y/u operaciones (74%)

Determinants of Poverty in the Colombian Caribbean Region

Resumen Objetivo: Identificar los factores relacionados con la pobreza en la región Caribe colombiana. Materiales y Métodos: Estudio transversal a partir del micro-dato de la Gran Encuesta Integrada de Hogares (GEIH) 2012. Se estimó un modelo econométrico de Umbral Generalizado, que hace parte de los modelos de respuesta ordenada, la variable dependiente toma tres valores, uno cuando el hogar no es pobre, dos cuando es moderadamente pobre y tres cuando el hogar es extremadamente pobre. Resultados: Respecto a los determinantes, se encontró que el nivel educativo, la ocupación y el tamaño del hogar son las variables de mayor incidencia. Siendo la educación la variable con mayor impacto. Conclusiones: En el periodo estudiado se evidencia que la educación determina la posición socioeconómica del hogar. Incentivar el empleo y evitar incrementar el tamaño del hogar impactan positivamente en la reducción de la pobreza.  To identify factors associated with poverty in the Colombian Caribbean region. Materials and Methods: Cross-sectional study from micro-data of the Great Integrated Household Survey (GEIH) 2012. An econometric model was estimated Generalized Threshold , the dependent variable takes three values , one when the home is not poor , twice when it is moderately poor and three when the home is extremely poor. Results: We found that the educational level, occupation and household size are the variables with the highest incidence. Conclusions: We demonstrated that education determines the socioeconomic status of the household. Promote employment and avoid increasing household size positively impact on reducing povert

Concentration of health spending in an insurer Colombian subsidized regime, 2014

Objetivo: Estimar la concentración del gasto sanitario según grupos de patologías y tipos de servicios en una aseguradora subsidiada que afilia personas pobres (estratos socioeconómicos 1 y 2) al Sistema de Salud de Colombia en 2014. Metodología: Se analizó el gasto sanitario en 1 666 477 afiliados, por grupos de patología y tipos de servicios, en el año 2014. Para la descripción de la concentración del gasto se utilizó el coeficiente de Gini y la curva de Lorenz. Resultados: El gasto sanitario de la aseguradora fue de usd 418 millones. De este, el 81 % se aplicó a servicios contenidos en el Plan Obligatorio de Salud (pos). Los grupos de patologías que concentraron el 43,4 % del gasto sanitario fueron cardiovascular (14,3 %), cáncer (7,8 %), enfermedades respiratorias (7,3 %), enfermedades urinarias (7 %) y traumatismos (6,9 %). Los servicios diagnósticos, curativos y de rehabilitación representaron el 77,8 % del gasto sanitario. La hospitalización fue el grupo de servicio que más impactó el costo (47 %), y las consultas, el más utilizado. Las curvas de Lorenz demostraron que el 70 % del gasto en salud se concentra en aproximadamente el 20 % de los afiliados, generando un coeficiente de Gini de 0,58. Conclusión: El diagnóstico y el tratamiento de las enfermedades crónicas no transmisibles concentran una alta proporción del gasto sanitario, lo cual genera una competencia de recursos para servicios preventivos y de promoción de la salud.Objective: to estimate the concentration of health spending depending on pathology groups and types of services in a subsidized insurance company which enrolled low-income people (social economic strata 1 and 2) in the Colombian Healthcare System in 2014. Methodology: Health spending was analyzed in 1 666 477 members, set up by pathologies and types of services during 2014. To describe the concentration of health spending, researchers used the Gini coefficient and the Lorenz curve. Results: the health spending of the insurance company was US$418 million. Out of this, 81 % was used in service contained in the mandatory Health Plan (in Spanish, Plan Obligatorio de Salud -POS). The pathology groups that concentrated 43.4% of health spending were cardiovascular (14.3%), cancer (7.8%), respiratory diseases (7.3%), urinary diseases (7%) and trauma (6.9%). Diagnostic, healing and rehabilitation services represented 77.8% of health spending. Hospitalization was the service group with the highest impact on costs (47%), and consultations, the most used. The Lorenz curves showed that 70% of the health spending is concentrated in approximately 20% the Affiliated people, resulting in a 0.58 Gini coefficient. Conclusion: Diagnostic and treatment of chronic non-transmittable diseases concentrate a vast part of health spending, which produces a competition of resources for preventive services and healthcare promotion