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Proximity of households to comprehensive obstetric care is a key determinant for preventing maternal mortality due to obstetric emergencies. The relationship between proximity to comprehensive care and facility delivery is further complicated by the use of varied methods in measuring facility obstetric capacity-which may misrepresent the real scenario of obstetric care availability in a service environment. We investigated the joint effects of proximity and two emergency obstetric care assessment (EmOC) methods on women's place of delivery in Malawi and Haiti. Household level and health facility data were obtained from the 2013-2018 Demographic and Health Surveys and Service Provision Assessment surveys. Records of women aged 15 to 49 years who had a childbirth in the last 5 years were linked to obstetric facilities within 5km, 10km and 15km from their households using Kernel Density Estimation. Log-binomial models were fitted to estimate the joint effects of proximity to comprehensive facilities on place of delivery and two EmOC methods (1. the facility's recent performance of signal functions only, and 2. a composite index of obstetric care), and whether this varied by urban/rural setting. Proximity to comprehensive facilities was significantly associated with facility delivery in Malawi among women living 5km of a comprehensive facility (using EmOC method 2), in addition, living further (15km) from facilities with high capacity of EmOC was associated with reduced likelihood for facility delivery in urban settings in stratified analyses. In contrast, positive associations were present in Haiti in both urban and rural settings, with the likelihood of facility delivery being higher with greater proximity of women to comprehensive facilities, regardless of methods to define EmOC. Women living within 5km of a comprehensive facility in Haiti were the most likely to deliver in facilities based on EmOC method 1 (APR: 1.81, 95% CI 1.56, 2.09). Findings from Malawi elucidates the relevance of context and suggests the need for research in diverse settings.
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BACKGROUND: The current focus on monitoring health inequalities and the complexity around ethnicity requires careful consideration of how ethnic disparities are measured and presented. This paper aims to determine how inequalities in maternal healthcare by ethnicity change according to different criteria used to classify indigenous populations. METHODS: Nationally representative demographic surveys from Bolivia, Guatemala, Mexico, and Peru (2008-2016) were used to explore coverage gaps across maternal health care by ethnicity using different criteria. Women were classified as indigenous through self-identification (SI), spoken indigenous language (SIL), or indigenous household (IH). We compared the gaps through measuring coverage ratios (CR) with adjusted Poisson regression models. RESULTS: Proportions of indigenous women changed significantly according to the identification criterion (Bolivia:SI-63.1%/SIL-37.7%; Guatemala:SI-49.7%/SIL-28.2%; Peru:SI-34%/SIL-6.3% & Mexico:SI-29.7%/SIL-6.9%). Indigenous in all countries, regardless of their identification, had less coverage. Gaps in care between indigenous and non-indigenous populations changed, for all indicators and countries, depending on the criterion used (e.g., Bolivia CR for contraceptive-use SI = 0.70, SIL = 0.89; Guatemala CR for skilled-birth-attendant SI = 0.77, SIL = 0.59). The heterogeneity persists when the reference groups are modified and compare just to non-indigenous (e.g., Bolivia CR for contraceptive-use under SI = 0.64, SIL = 0.70; Guatemala CR for Skilled-birth-attendant under SI = 0.77, SIL = 0.57). CONCLUSIONS: The indigenous identification criteria could have an impact on the measurement of inequalities in the coverage of maternal health care. Given the complexity and diversity observed, it is not possible to provide a definitive direction on the best way to define indigenous populations to measure inequalities. In practice, the categorization will depend on the information available. Our results call for greater care in the analysis of ethnicity-based inequalities. A greater understanding on how the indigenous are classified when assessing inequalities by ethnicity can help stakeholders to deliver interventions responsive to the needs of these groups.
Asunto(s)
Equidad en Salud , Disparidades en Atención de Salud/etnología , Indígenas Sudamericanos , Pueblos Indígenas , Servicios de Salud Materna , Salud Materna/etnología , Adolescente , Adulto , Bolivia , Etnicidad , Composición Familiar , Femenino , Guatemala , Humanos , Lenguaje , América Latina , México , Parto , Perú , Embarazo , Indicadores de Calidad de la Atención de Salud , Identificación Social , Adulto JovenRESUMEN
BACKGROUND: Monitoring and reducing inequalities in health care has become more relevant since the adoption of the Sustainable Development Goals (SDGs). The SDGs bring an opportunity to put the assessment of inequalities by ethnicity on the agenda of decision-makers. The objective of this qualitative study is to know how current monitoring is carried out and to identify what factors influence the process in order to incorporate indicators that allow the evaluation of inequalities by ethnicity. METHODS: We conducted 17 semi-structured interviews with key informants from the health ministry, monitoring observatories, research centers, and international organizations, involved in maternal health care monitoring in Mexico. Our analysis was interpretative-phenomenological and focused on examining experiences about monitoring maternal health care in order to achieve a full picture of the current context in which it takes place and the factors that influence it. RESULTS: The obstacles and opportunities pointed out from the participants emerge from the limitations or advantages associated with the accuracy of evaluation, availability of information and resources, and effective management and decision-making. Technicians, coordinators, researchers or decision-makers are not only aware of the inequalities but also of its importance. However, this does not lead to political decisions permitting an indicator to be developed for monitoring it. As for opportunities, the role of international organizations and their links with the countries is crucial to carry out monitoring, due to political and technical support. CONCLUSIONS: The success of a monitoring system to help decision-makers reduce inequalities in health care depends not only on accurate evaluations but also on the context in which it is implemented. Understanding the operation, obstacles and opportunities for monitoring could be a key issue if the countries want to advance towards assessing inequalities and reducing health inequities with the aid of concrete policies and initiatives.
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Disparidades en Atención de Salud , Pueblos Indígenas , Servicios de Salud Materna/organización & administración , Salud Materna , Factores Socioeconómicos , Toma de Decisiones en la Organización , Femenino , Necesidades y Demandas de Servicios de Salud/organización & administración , Humanos , México , Embarazo , Investigación Cualitativa , Mejoramiento de la Calidad , Desarrollo SostenibleRESUMEN
Latin America and the Caribbean still have high maternal mortality rates and access to health care is very uneven in some countries. Indigenous women, in particular, have poorer maternal health outcomes than the majority of the population and are less likely to benefit from health-care services. Therefore, inequities in maternal health between different ethnic groups should be monitored to identify critical factors that could limit health-care coverage. In adopting the United Nations' sustainable development goals, governments have committed to providing equitable and universal health coverage. It is, therefore, the right time to assess ethnic disparities in maternal health care. However, finding a standard method of identifying ethnicity has been difficult, because ethnicity involves several features, such as language, religion, tribe, territory and race. In this study, spoken indigenous language was used successfully as a proxy for ethnicity to detect inequities in maternal health-care coverage between indigenous and non-indigenous populations in four Latin American countries: Guatemala, Mexico, Peru and the Plurinational State of Bolivia. Although, quantifying ethnic inequities in health care is just a starting point, this quantification can help policy-makers and other stakeholders justify the need for monitoring these inequities. This monitoring is essential for designing more culturally appropriate programmes and policies that will reduce the risks associated with maternity among indigenous woman. As long as inequities persist, identifying them is an important step towards their elimination.
L'Amérique latine et les Caraïbes continuent d'afficher des taux de mortalité maternelle élevés et dans certains pays, l'accès aux soins de santé est très inégal. Les femmes autochtones, en particulier, sont dans un plus mauvais état de santé maternelle que la majorité de la population et sont moins susceptibles de bénéficier des services de santé. Il convient donc de suivre les inégalités relatives à la santé maternelle entre les différents groupes ethniques pour identifier les facteurs déterminants qui peuvent limiter la couverture sanitaire. En adoptant les objectifs de développement durable des Nations Unies, les gouvernements se sont engagés à fournir une couverture sanitaire équitable et universelle. Il est donc temps d'évaluer les disparités ethniques en matière de soins de santé maternelle. Il s'est néanmoins avéré difficile de trouver une méthode standard permettant de définir l'appartenance ethnique, car cette dernière implique plusieurs caractéristiques, telles que la langue, la religion, la tribu, le territoire et la race. Dans cette étude, la langue autochtone parlée a été utilisée avec succès en tant qu'indicateur d'appartenance ethnique pour détecter les inégalités concernant la couverture des soins de santé maternelle entre les populations autochtones et non autochtones de quatre pays latino-américains: l'État plurinational de Bolivie, le Guatemala, le Mexique et le Pérou. Bien que la quantification des inégalités ethniques en matière de soins de santé ne soit qu'un point de départ, elle peut aider les responsables politiques et d'autres parties prenantes à justifier la nécessité d'un suivi de ces inégalités. Ce suivi est essentiel pour concevoir des programmes et des politiques mieux adaptés à la culture des populations et réduire ainsi les risques associés à la maternité chez les femmes autochtones. Tant que des inégalités persistent, les identifier est une étape importante vers leur élimination.
América Latina y el Caribe siguen teniendo altas tasas de mortalidad materna y el acceso a la atención sanitaria es muy desigual en algunos países. Las mujeres indígenas, en particular, tienen peores resultados en salud materna que la mayoría de la población y menos probabilidades de beneficiarse de los servicios de atención sanitaria. Por tanto, deben vigilarse las desigualdades en temas de salud materna entre los diferentes grupos étnicos para determinar los factores críticos que podrían limitar la cobertura de la atención sanitaria. Al adoptar los objetivos de desarrollo sostenible de las Naciones Unidas, los gobiernos se han comprometido a proporcionar una cobertura sanitaria equitativa y universal. Por tanto, es el momento adecuado para evaluar las disparidades étnicas en la atención sanitaria materna. Sin embargo, ha sido difícil encontrar un método estándar para identificar la etnia, pues esta tiene varias características, como el idioma, la religión, la tribu, el territorio y la raza. En este estudio, el idioma indígena hablado se utilizó con éxito como indicador de la etnicidad para detectar las desigualdades en la cobertura de la atención sanitaria materna entre las poblaciones indígenas y no indígenas en cuatro países de América Latina: el Estado Plurinacional de Bolivia, Guatemala, México y Perú. Aunque la cuantificación de las inequidades étnicas en la atención sanitaria es solo un punto de partida, esta cuantificación puede ayudar a los responsables de la formulación de políticas y a otros interesados a justificar la necesidad de monitorizar estas inequidades. Esta monitorización es esencial para diseñar programas y políticas culturalmente más adecuadas que reduzcan los riesgos asociados con la maternidad entre las mujeres indígenas. Mientras persistan las desigualdades, identificarlas es un paso importante hacia su eliminación.
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Accesibilidad a los Servicios de Salud , Disparidades en Atención de Salud , Servicios de Salud Materna , Bolivia , Comparación Transcultural , Países en Desarrollo , Etnicidad , Femenino , Guatemala , Accesibilidad a los Servicios de Salud/estadística & datos numéricos , Encuestas Epidemiológicas , Humanos , Lenguaje , Servicios de Salud Materna/estadística & datos numéricos , Mortalidad Materna , México , Perú , EmbarazoRESUMEN
BACKGROUND: Adverse events (AEs) epidemiology is the first step to improve practice in the healthcare system. Usually, the preferred method used to estimate the magnitude of the problem is the retrospective cohort study design, with retrospective reviews of the medical records. However this data collection involves a sophisticated sampling plan, and a process of intensive review of sometimes very heavy and complex medical records. Cross-sectional survey is also a valid and feasible methodology to study AEs. OBJECTIVES: The aim of this study is to compare AEs detection using two different methodologies: cross-sectional versus retrospective cohort design. SETTING: Secondary and tertiary hospitals in five countries: Argentina, Colombia, Costa Rica, Mexico and Peru. PARTICIPANTS: The IBEAS Study is a cross-sectional survey with a sample size of 11 379 patients. The retrospective cohort study was obtained from a 10% random sample proportional to hospital size from the entire IBEAS Study population. METHODS: This study compares the 1-day prevalence of the AEs obtained in the IBEAS Study with the incidence obtained through the retrospective cohort study. RESULTS: The prevalence of patients with AEs was 10.47% (95% CI 9.90 to 11.03) (1191/11 379), while the cumulative incidence of the retrospective cohort study was 19.76% (95% CI 17.35% to 22.17%) (215/1088). In both studies the highest risk of suffering AEs was seen in Intensive Care Unit (ICU) patients. Comorbid patients and patients with medical devices showed higher risk. CONCLUSION: The retrospective cohort design, although requires more resources, allows to detect more AEs than the cross-sectional design.