Evidence map›Paper›PMID 40136140›Full record

ArticleCadernos de saude publica2025

Integrated health-environment-economy approach in the Brazilian Amazon: mapping production landscape units.

Anielli Rosane de Souza, Maria Isabel Sobral Escada, Ana Paula Dal'Asta, Marcus Vinicius Gonçalves da Silva, Danilo Araújo Fernandes, Antonio Miguel Vieira Monteiro

Abstract read
In one paragraph

Article in Cadernos de saude publica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Anielli Rosane de SouzaInstituto Nacional de Pesquisas Espaciais, São José dos Campos, Brasil.ORCID 0000-0001-6888-8956
Maria Isabel Sobral EscadaInstituto Nacional de Pesquisas Espaciais, São José dos Campos, Brasil.ORCID 0000-0002-5822-8265
Ana Paula Dal'AstaInstituto Nacional de Pesquisas Espaciais, São José dos Campos, Brasil.ORCID 0000-0002-1286-9067
Marcus Vinicius Gonçalves da SilvaUniversidade Federal de Lavras, Lavras, Brasil.ORCID 0009-0001-9904-9001
Danilo Araújo FernandesUniversidade Federal do Pará, Belém, Brasil.ORCID 0000-0003-1326-9626
Antonio Miguel Vieira MonteiroInstituto Nacional de Pesquisas Espaciais, São José dos Campos, Brasil.ORCID 0000-0003-1477-1749

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The agrarian economy, with its social agents and technical systems, mobilizes the elements that generate transformations in the social and natural landscapes in the Brazilian Amazon. Choices for regional development lead to sustainability or unsustainability of the forest ecosystem and its social landscape, while not including health in this debate. We argue that an analytical framework for integrated health-environment-economy approaches needs a territorial representation for the landscapes associated with the ways of living and producing in Amazonian agriculture: the production landscape units (PLU). In this article, we explore machine learning techniques, in the field of supervised classification, with methods based on decision trees, to identify and map the PLU. A case study is developed for the municipalities of Mocajuba and Cametá, in the Baixo Tocantins region, in the State of Pará, for 2021. We describe how to identify and map the PLU in an intra-municipal spatial unit of reference and how to associate them with the types of rural techno-productive trajectories or technological trajectories (TTs) found in the regional agrarian economy. We promote an initial discussion on the use of PLU in the structuring of integrated approaches in health. This article contributes to align debates on strategies for economic development with health promotion in the Brazilian Amazon.

Indexed as

AgricultureConservation of Natural ResourcesEconomic DevelopmentBrazilForestsHumansMachine Learning

Identifiers

PMID40136140
PMCPMC11940853

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.