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Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil

BACKGROUND: Although the use of biomarkers to assess health outcomes has recently gained momentum, literature is still scarce for low- to middle-income countries. This paper explores the relationship between primary care coverage and individual health in Brazil using a dataset of blood-based biomark...

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Autores principales: Postali, Fernando Antonio Slaibe, Diaz, Maria Dolores Montoya, Ferreira-Batista, Natalia Nunes, Teixeira, Adriano Dutra, Moreno-Serra, Rodrigo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642960/
https://www.ncbi.nlm.nih.gov/pubmed/34863160
http://dx.doi.org/10.1186/s12913-021-07329-9
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author Postali, Fernando Antonio Slaibe
Diaz, Maria Dolores Montoya
Ferreira-Batista, Natalia Nunes
Teixeira, Adriano Dutra
Moreno-Serra, Rodrigo
author_facet Postali, Fernando Antonio Slaibe
Diaz, Maria Dolores Montoya
Ferreira-Batista, Natalia Nunes
Teixeira, Adriano Dutra
Moreno-Serra, Rodrigo
author_sort Postali, Fernando Antonio Slaibe
collection PubMed
description BACKGROUND: Although the use of biomarkers to assess health outcomes has recently gained momentum, literature is still scarce for low- to middle-income countries. This paper explores the relationship between primary care coverage and individual health in Brazil using a dataset of blood-based biomarkers collected by the Brazilian National Health Survey. Both survey data and laboratory results were crossed with coverage data from the Family Health Strategy (ESF) program, the most important primary care program in Brazil; the coverage measures aim to capture both direct (household) and indirect (spill-over) effects. METHODS: The empirical strategy used a probit model to estimate the relationship between ESF program coverage and the likelihood of abnormal biomarker levels while controlling for a rich set of individual and household characteristics based on data from the national survey. RESULTS: Household ESF coverage was associated with a lower likelihood of abnormal results for biomarkers related to anemia (marginal effect between − 2.16 and − 2.18 percentage points), kidney failure (between − 1.01 and − 1.19 p.p.), and arterial hypertension (between − 1.48 and − 1.64 p.p). The likelihood of abnormal levels of white blood cells and thrombocytes was negatively related to primary care coverage (marginal effect between − 1.8 and − 2 p.p.). The spillover effects were relevant for kidney failure and arterial hypertension, depending on the regional level. Although not sensitive to household coverage, diabetes mellitus was negatively associated with the state supply of primary care, and abnormal cholesterol levels did not present any relationship with ESF program coverage. CONCLUSIONS: The presence of spillover effects of ESF program coverage regarding these conditions reveals that the strengthening of primary care by increasing the household registration and the regional density of ESF teams is an efficient strategy to address important comorbidities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-07329-9.
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spelling pubmed-86429602021-12-06 Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil Postali, Fernando Antonio Slaibe Diaz, Maria Dolores Montoya Ferreira-Batista, Natalia Nunes Teixeira, Adriano Dutra Moreno-Serra, Rodrigo BMC Health Serv Res Research BACKGROUND: Although the use of biomarkers to assess health outcomes has recently gained momentum, literature is still scarce for low- to middle-income countries. This paper explores the relationship between primary care coverage and individual health in Brazil using a dataset of blood-based biomarkers collected by the Brazilian National Health Survey. Both survey data and laboratory results were crossed with coverage data from the Family Health Strategy (ESF) program, the most important primary care program in Brazil; the coverage measures aim to capture both direct (household) and indirect (spill-over) effects. METHODS: The empirical strategy used a probit model to estimate the relationship between ESF program coverage and the likelihood of abnormal biomarker levels while controlling for a rich set of individual and household characteristics based on data from the national survey. RESULTS: Household ESF coverage was associated with a lower likelihood of abnormal results for biomarkers related to anemia (marginal effect between − 2.16 and − 2.18 percentage points), kidney failure (between − 1.01 and − 1.19 p.p.), and arterial hypertension (between − 1.48 and − 1.64 p.p). The likelihood of abnormal levels of white blood cells and thrombocytes was negatively related to primary care coverage (marginal effect between − 1.8 and − 2 p.p.). The spillover effects were relevant for kidney failure and arterial hypertension, depending on the regional level. Although not sensitive to household coverage, diabetes mellitus was negatively associated with the state supply of primary care, and abnormal cholesterol levels did not present any relationship with ESF program coverage. CONCLUSIONS: The presence of spillover effects of ESF program coverage regarding these conditions reveals that the strengthening of primary care by increasing the household registration and the regional density of ESF teams is an efficient strategy to address important comorbidities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-07329-9. BioMed Central 2021-12-04 /pmc/articles/PMC8642960/ /pubmed/34863160 http://dx.doi.org/10.1186/s12913-021-07329-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Postali, Fernando Antonio Slaibe
Diaz, Maria Dolores Montoya
Ferreira-Batista, Natalia Nunes
Teixeira, Adriano Dutra
Moreno-Serra, Rodrigo
Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil
title Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil
title_full Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil
title_fullStr Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil
title_full_unstemmed Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil
title_short Primary care coverage and individual health: evidence from a likelihood model using biomarkers in Brazil
title_sort primary care coverage and individual health: evidence from a likelihood model using biomarkers in brazil
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642960/
https://www.ncbi.nlm.nih.gov/pubmed/34863160
http://dx.doi.org/10.1186/s12913-021-07329-9
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