Atenção Primária à Saúde no Norte e Nordeste do Brasil: mapeando disparidades na distribuição de equipes

Abstract

Resumo Objetiva-se analisar o padrão espacial de implantação de equipes da Atenção Primária à Saúde (APS) no Norte e Nordeste do Brasil em 2017. Estudo ecológico das taxas de Agentes Comunitários de Saúde (ACS), equipes Saúde da Família (eSF), equipes Saúde Bucal (eSB) e Núcleo Ampliado de Saúde da Família (NASF), a partir de dados do Ministério da saúde (MS). A análise dos dados de área permitiu a identificação de padrões de dependência espacial dos municípios para as taxas, utilizando os índices e mapas de Moran para visualizar clusters de áreas críticas (95% de confiança). Os municípios do Norte (n=450) e Nordeste (n=1.794) apresentaram 132,2 mil ACS, 18,4 mil eSF, 13 mil eSB e 2,2 mil NASF. A proporção de municípios com taxas dentro do preconizado pelo MS: ACS (>1,33/mil) 96% no Norte e 98,5% no Nordeste; eSF (>2,9/10 mil) 54% e 80% nas respectivas regiões; eSB (>2,9/10 mil) 28% e 59% nestas respectivas regiões. Equipes NASF foram implantadas em 70% do Norte e 89% do Nordeste. Exceto ACS, a região Norte constituiu-se em área crítica de equipes, principalmente no Pará, Rondônia, Amazonas e Amapá. No Nordeste, essas áreas foram menores e concentradas a oeste da Bahia e leste do Maranhão. O Nordeste exibiu melhor composição de equipes e menor extensão de áreas críticas.

The tendency of stunting among children under five in the Northern Region of Brazil, according to the Food and Nutrition Surveillance System, 2008-2017

“… 30 Data on the structuring of primary care point to the North Region as a critical area. 31 Factors such as difficulty in regionalizing primary care, centralization of service provision at the headquarters of municipalities, and long distances between users and services - caused by the low population density of this region, especially the Amazon - explain the worse structuring of health care networks. 31 Geographical characteristics, such as the rivers and forests, become great challenges to be overcome; the low availability of transportation, among other difficulties, contribute to the concentration of health care centers in the urban areas and make it difficult for many communities to access health care.…”

Excess maternal mortality in Brazil: Regional inequalities and trajectories during the COVID-19 epidemic

“…Part of the differences found in excess maternal mortality in our study may be explained by the striking socioeconomic inequalities in the North and Northeast regions of Brazil [ 39 , 40 ] which have the worst infrastructure and access to health services in the country [ 41 ]. The North region, most harshly punished across all trimesters assessed, was not as prepared to face the epidemic since, proportionally, it possessed the lowest number of ICU beds, physicians, and ventilators, an essential device for facing COVID-19 complications [ 42 ], of all macroregions.…”

Internações por diabetes mellitus em idosos no Brasil de 2001 a 2020: tendência temporal e padrões espaciais

“…When the hospitalization rates and FHS coverage were investigated, it was identified that in the North, despite the high hospitalization rates, there was no cluster formation with FHS coverage in a large extent of the region. Soares 28 states in his study that the structuring of FHS in the North is unfavorable and insufficient, and this is due to the deployment of teams in places outside its coverage area, which denotes a weakness in the service and makes it difficult for the user to bond with the health unit.…”