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Analysis of the interrelationships between factors influencing blood pressure in adults
OBJECTIVE: To investigate the interrelationships between sociodemographic, behavioral and clinical factors associated with high blood pressure in a population of Brazilian adults. METHODS: Data from a cross-sectional population-based study conducted with adults were used. In the hypothetical model d...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Faculdade de Saúde Pública da Universidade de São Paulo
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726937/ https://www.ncbi.nlm.nih.gov/pubmed/33331490 http://dx.doi.org/10.11606/s1518-8787.2020054002123 |
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author | Freire, Rafael Silveira Reis, Vivianne Margareth Chaves Pereira Brito, Alexandre Botelho Brito, Maria Fernanda Santos Figueiredo de Pinho, Lucinéia Silva, Rosângela Ramos Veloso Silveira, Marise Fagundes |
author_facet | Freire, Rafael Silveira Reis, Vivianne Margareth Chaves Pereira Brito, Alexandre Botelho Brito, Maria Fernanda Santos Figueiredo de Pinho, Lucinéia Silva, Rosângela Ramos Veloso Silveira, Marise Fagundes |
author_sort | Freire, Rafael Silveira |
collection | PubMed |
description | OBJECTIVE: To investigate the interrelationships between sociodemographic, behavioral and clinical factors associated with high blood pressure in a population of Brazilian adults. METHODS: Data from a cross-sectional population-based study conducted with adults were used. In the hypothetical model developed socioeconomic status, fruit and vegetable intake, adiposity and blood pressure were treated as latent variables and age, gender, glycemia, physical activity, smoking, alcohol consumption and control of arterial hypertension were considered observed variables. Confirmatory factorial analysis was used to construct the latent variables measurement models and the structural equation modeling was used to adjust the final model. RESULTS: The study included 808 individuals, with mean age of 44.2 years (± 17.8), 52.7% being female. It verified that age exerted a positive direct effect on blood pressure (β = 0.39), adiposity (β = 0.44), glycemia (β = 0.26) and smoking (β = 0.30). Age had a negative direct effect on physical activity (β=-0.17) and alcohol consumption (β = -0.10). Males were positively associated with blood pressure (β = 0.13), smoking (β = 0.28; p < 0.001) and alcohol consumption (β = 0.18). Adiposity had a positive direct effect on blood pressure (β = 0.23) and glycemia (β = 0.16) and alcohol consumption produced a positive effect (β = 0.09) on adiposity. Fruit and vegetable intake had a negative direct effect on blood pressure (β = -0.11), while socioeconomic status had a positive direct effect on fruit and vegetable consumption (β = 0.47). We adjusted the structural model according to the variable medical control of arterial hypertension, which had a negative direct effect on blood pressure (β = -0.10). CONCLUSIONS: Results suggest that increasing age is associated with increased blood pressure, adiposity, glycemia and smoking, as well as with reduced physical activity and alcohol consumption. Males were associated with increased blood pressure and greater use of alcohol and cigarettes. Higher adiposity indicators were correlated with increased blood pressure and glycemic levels; higher alcohol consumption was associated with increased adiposity. Higher consumption of fruits and vegetables, as well as active control of hypertension were associated with reduced blood pressure. Better socioeconomic status was associated with higher consumption of fruits and vegetables. |
format | Online Article Text |
id | pubmed-7726937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Faculdade de Saúde Pública da Universidade de São Paulo |
record_format | MEDLINE/PubMed |
spelling | pubmed-77269372020-12-11 Analysis of the interrelationships between factors influencing blood pressure in adults Freire, Rafael Silveira Reis, Vivianne Margareth Chaves Pereira Brito, Alexandre Botelho Brito, Maria Fernanda Santos Figueiredo de Pinho, Lucinéia Silva, Rosângela Ramos Veloso Silveira, Marise Fagundes Rev Saude Publica Original Article OBJECTIVE: To investigate the interrelationships between sociodemographic, behavioral and clinical factors associated with high blood pressure in a population of Brazilian adults. METHODS: Data from a cross-sectional population-based study conducted with adults were used. In the hypothetical model developed socioeconomic status, fruit and vegetable intake, adiposity and blood pressure were treated as latent variables and age, gender, glycemia, physical activity, smoking, alcohol consumption and control of arterial hypertension were considered observed variables. Confirmatory factorial analysis was used to construct the latent variables measurement models and the structural equation modeling was used to adjust the final model. RESULTS: The study included 808 individuals, with mean age of 44.2 years (± 17.8), 52.7% being female. It verified that age exerted a positive direct effect on blood pressure (β = 0.39), adiposity (β = 0.44), glycemia (β = 0.26) and smoking (β = 0.30). Age had a negative direct effect on physical activity (β=-0.17) and alcohol consumption (β = -0.10). Males were positively associated with blood pressure (β = 0.13), smoking (β = 0.28; p < 0.001) and alcohol consumption (β = 0.18). Adiposity had a positive direct effect on blood pressure (β = 0.23) and glycemia (β = 0.16) and alcohol consumption produced a positive effect (β = 0.09) on adiposity. Fruit and vegetable intake had a negative direct effect on blood pressure (β = -0.11), while socioeconomic status had a positive direct effect on fruit and vegetable consumption (β = 0.47). We adjusted the structural model according to the variable medical control of arterial hypertension, which had a negative direct effect on blood pressure (β = -0.10). CONCLUSIONS: Results suggest that increasing age is associated with increased blood pressure, adiposity, glycemia and smoking, as well as with reduced physical activity and alcohol consumption. Males were associated with increased blood pressure and greater use of alcohol and cigarettes. Higher adiposity indicators were correlated with increased blood pressure and glycemic levels; higher alcohol consumption was associated with increased adiposity. Higher consumption of fruits and vegetables, as well as active control of hypertension were associated with reduced blood pressure. Better socioeconomic status was associated with higher consumption of fruits and vegetables. Faculdade de Saúde Pública da Universidade de São Paulo 2020-12-04 /pmc/articles/PMC7726937/ /pubmed/33331490 http://dx.doi.org/10.11606/s1518-8787.2020054002123 Text en https://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Freire, Rafael Silveira Reis, Vivianne Margareth Chaves Pereira Brito, Alexandre Botelho Brito, Maria Fernanda Santos Figueiredo de Pinho, Lucinéia Silva, Rosângela Ramos Veloso Silveira, Marise Fagundes Analysis of the interrelationships between factors influencing blood pressure in adults |
title | Analysis of the interrelationships between factors influencing blood pressure in adults |
title_full | Analysis of the interrelationships between factors influencing blood pressure in adults |
title_fullStr | Analysis of the interrelationships between factors influencing blood pressure in adults |
title_full_unstemmed | Analysis of the interrelationships between factors influencing blood pressure in adults |
title_short | Analysis of the interrelationships between factors influencing blood pressure in adults |
title_sort | analysis of the interrelationships between factors influencing blood pressure in adults |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726937/ https://www.ncbi.nlm.nih.gov/pubmed/33331490 http://dx.doi.org/10.11606/s1518-8787.2020054002123 |
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