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Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China

Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Surv...

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Detalles Bibliográficos
Autores principales: Ye, Zirong, Xu, Li, Zhou, Zi, Wu, Yafei, Fang, Ya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800154/
https://www.ncbi.nlm.nih.gov/pubmed/29301286
http://dx.doi.org/10.3390/ijerph15010055
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author Ye, Zirong
Xu, Li
Zhou, Zi
Wu, Yafei
Fang, Ya
author_facet Ye, Zirong
Xu, Li
Zhou, Zi
Wu, Yafei
Fang, Ya
author_sort Ye, Zirong
collection PubMed
description Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Survey (CHNS), including residents over 12 years old in seven provinces from 1991 to 2011. Bayesian B-spline was used in the extended shared component model (SCM) for fitting temporal-related variation to explore spatio-temporal distribution in the odds ratio (OR) of hypertension, reveal gender variation, and explore latent risk factors. Our results revealed that the prevalence of hypertension increased from 14.09% in 1991 to 32.37% in 2011, with men experiencing a more obvious change than women. From a spatial perspective, a standardized prevalence ratio (SPR) remaining at a high level was found in Henan and Shandong for both men and women. Meanwhile, before 1997, the temporal distribution of hypertension risk for both men and women remained low. After that, notably since 2004, the OR of hypertension in each province increased to a relatively high level, especially in Northern China. Notably, the OR of hypertension in Shandong and Jiangsu, which was over 1.2, continuously stood out after 2004 for males, while that in Shandong and Guangxi was relatively high for females. The findings suggested that obvious spatial–temporal patterns for hypertension exist in the regions under research and this pattern was quite different between men and women.
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spelling pubmed-58001542018-02-06 Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China Ye, Zirong Xu, Li Zhou, Zi Wu, Yafei Fang, Ya Int J Environ Res Public Health Article Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Survey (CHNS), including residents over 12 years old in seven provinces from 1991 to 2011. Bayesian B-spline was used in the extended shared component model (SCM) for fitting temporal-related variation to explore spatio-temporal distribution in the odds ratio (OR) of hypertension, reveal gender variation, and explore latent risk factors. Our results revealed that the prevalence of hypertension increased from 14.09% in 1991 to 32.37% in 2011, with men experiencing a more obvious change than women. From a spatial perspective, a standardized prevalence ratio (SPR) remaining at a high level was found in Henan and Shandong for both men and women. Meanwhile, before 1997, the temporal distribution of hypertension risk for both men and women remained low. After that, notably since 2004, the OR of hypertension in each province increased to a relatively high level, especially in Northern China. Notably, the OR of hypertension in Shandong and Jiangsu, which was over 1.2, continuously stood out after 2004 for males, while that in Shandong and Guangxi was relatively high for females. The findings suggested that obvious spatial–temporal patterns for hypertension exist in the regions under research and this pattern was quite different between men and women. MDPI 2018-01-02 2018-01 /pmc/articles/PMC5800154/ /pubmed/29301286 http://dx.doi.org/10.3390/ijerph15010055 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ye, Zirong
Xu, Li
Zhou, Zi
Wu, Yafei
Fang, Ya
Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China
title Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China
title_full Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China
title_fullStr Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China
title_full_unstemmed Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China
title_short Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China
title_sort application of scm with bayesian b-spline to spatio-temporal analysis of hypertension in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800154/
https://www.ncbi.nlm.nih.gov/pubmed/29301286
http://dx.doi.org/10.3390/ijerph15010055
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