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Análise da mortalidade materna na província de Nampula e fatores associados: uma aplicação do modelo logístico
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Abstract(s)
Nas últimas décadas do último século, em todo o mundo, foram registados avanços significativos e louváveis na área científica e tecnológica, principalmente nas áreas de atendimento a mulher e criança. Por essa razão, tornou-se praticamente inadmissível que o processo de reprodução cause sequelas às mulheres assim como os seus bebés, levando-os à morte por qualquer fator ou causa.
Em Moçambique, a redução do rácio da mortalidade materna constitui um dos pilares dos objetivos do desenvolvimento sustentável no seu número 3.1. O mesmo figura dentre os indicadores de saúde mais utilizados para identificar os riscos à saúde de grupos populacionais considerados de risco (mulheres grávidas e crianças).
Para a análise dos dados foi aplicada a regressão logística como técnica estatística utilizada na relação entre variáveis. Procurou-se encontrar a influência ou relação das variáveis: número de Consultas Pré-Natais, idade gestacional, número de gestações, número de filhos, causa básica e causa direta de morte em relação à variável explicada Evitabilidade, tendo em conta que para o comité de auditoria toda a morte materna deve ser classificada como Evitável e Não evitável. Foram analisados 173 processo de óbitos maternos, dos quais se notou que 82% era evitável e cerca de 18% não evitável.
O modelo final selecionado tem como preditores significativos as variáveis, “Fez consultas pré-natal e número de consultas feitas”. Em relação os fatores que influenciaram nas mortes maternas foi possível verificar que a maioria (97 mortes) foi por fatores pessoais ou familiares, fatores institucionais 32 mortes (inclui a falta de equipamentos/consumíveis na unidade sanitária, medicamentos, falta de sangue e noutros casos falta de pessoal capacitado para dar resposta as emergências obstétricas), o terceiro grupo de fatores que mais influencia nas mortes foi o logístico com 25 mortes.
Dos fatores acima descritos, tem se que a maioria das mortes podia ser evitável ao nível das unidades sanitária.
In the last decades of the last century, throughout the world, significant and commendable advances were recorded in the scientific and technological area, mainly in the areas of care for women and children. For this reason, it has become practically unacceptable that the reproduction process causes consequences to women as well as their babies, leading to their death due to any factor or cause. In Mozambique, reducing the maternal mortality ratio is one of the pillars of the sustainable development goals in number 3.1. It is among the health indicators most used to identify health risks for population groups considered at risk (pregnant women and children). For data analysis, logistic regression was applied as a statistical technique used in the relationship between variables. We sought to find the influence or relationship of the variables: number of Prenatal Consultations, gestational age, number of pregnancies, number of children, underlying cause and direct cause of death in relation to the explained variable Preventability, considering that for the audit committee all maternal deaths must be classified as Preventable and Non-preventable. 173 maternal death cases were analyzed, of which it was noted that 82% were preventable and approximately 18% were non-preventable. The final model selected has as significant predictors the variables, “Had prenatal consultations and number of consultations made”. Regarding the factors that influenced maternal deaths, it was possible to verify that the majority (97 deaths) were due to personal or family factors, institutional factors 32 deaths (including the lack of equipment/consumables in the health unit, medicines, lack of blood and in other cases lack of trained personnel to respond to obstetric emergencies), the third group of factors that most influenced deaths was logistical with 25 deaths. From the factors described above, it is clear that most deaths could have been prevented at the level of health units.
In the last decades of the last century, throughout the world, significant and commendable advances were recorded in the scientific and technological area, mainly in the areas of care for women and children. For this reason, it has become practically unacceptable that the reproduction process causes consequences to women as well as their babies, leading to their death due to any factor or cause. In Mozambique, reducing the maternal mortality ratio is one of the pillars of the sustainable development goals in number 3.1. It is among the health indicators most used to identify health risks for population groups considered at risk (pregnant women and children). For data analysis, logistic regression was applied as a statistical technique used in the relationship between variables. We sought to find the influence or relationship of the variables: number of Prenatal Consultations, gestational age, number of pregnancies, number of children, underlying cause and direct cause of death in relation to the explained variable Preventability, considering that for the audit committee all maternal deaths must be classified as Preventable and Non-preventable. 173 maternal death cases were analyzed, of which it was noted that 82% were preventable and approximately 18% were non-preventable. The final model selected has as significant predictors the variables, “Had prenatal consultations and number of consultations made”. Regarding the factors that influenced maternal deaths, it was possible to verify that the majority (97 deaths) were due to personal or family factors, institutional factors 32 deaths (including the lack of equipment/consumables in the health unit, medicines, lack of blood and in other cases lack of trained personnel to respond to obstetric emergencies), the third group of factors that most influenced deaths was logistical with 25 deaths. From the factors described above, it is clear that most deaths could have been prevented at the level of health units.
Description
Mestrado em Bioestatística e Biometria, apresentada à Universidade Aberta
Keywords
Mortalidade materna Fatores associados Regressão logística múltipla Moçambique Maternal mortality Associated factors Multiple logistic regression