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Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults
BACKGROUND: Obesity and overweight are related to changes in blood pressure, but existing research has mainly focused on the impact of body mass index (BMI) on short-term blood pressure variability (BPV). The study aimed to examine the impact of BMI on long-term BPV. METHODS: Participants in the Kai...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196453/ https://www.ncbi.nlm.nih.gov/pubmed/30348124 http://dx.doi.org/10.1186/s12889-018-6083-4 |
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author | Chen, Haojia Zhang, Ruiying Zheng, Qiongbing Yan, Xiuzhu Wu, Shouling Chen, Youren |
author_facet | Chen, Haojia Zhang, Ruiying Zheng, Qiongbing Yan, Xiuzhu Wu, Shouling Chen, Youren |
author_sort | Chen, Haojia |
collection | PubMed |
description | BACKGROUND: Obesity and overweight are related to changes in blood pressure, but existing research has mainly focused on the impact of body mass index (BMI) on short-term blood pressure variability (BPV). The study aimed to examine the impact of BMI on long-term BPV. METHODS: Participants in the Kailuan study who attended all five annual physical examinations in 2006, 2008, 2010, 2012, and 2014 were selected as observation subjects. In total, 32,482 cases were included in the statistical analysis. According to the definition of obesity in China, BMI was divided into four groups: underweight (BMI < 18.5 kg/m(2)), normal weight (18.5 ≤ BMI < 24.0 kg/m(2)), overweight (24.0 ≤ BMI < 28.0 kg/m(2)), and obese (BMI ≥ 28.0 kg/m(2)). We used average real variability to evaluate long-term systolic BPV. The average real variability of systolic blood pressure (ARV(SBP)) was calculated as (|sbp2 − sbp1| + |sbp3 − sbp2 | + |sbp4 − sbp3| + |sbp5 − sbp4|)/4. Differences in ARV(SBP) by BMI group were analyzed using analysis of variance. Stepwise multivariate linear regression and multiple logistic regression analyses were used to assess the impact of BMI on ARV(SBP). RESULTS: Participants’ average age was 46.6 ± 11.3 years, 24,502 were men, and 7980 were women. As BMI increases, the mean value of ARVSBP gradually increases. After adjusting for other confounding factors, stepwise multivariate linear regression analysis showed that ARVSBP increased by 0.077 for every one-unit increase in BMI. Multiple logistic regression analysis indicated that being obese or overweight, compared with being normal-weight, were risk factors for an increase in ARVSBP. The corresponding odds ratios of being obese or overweight were 1.23 (1.15–1.37) and 1.10 (1.04–1.15), respectively. CONCLUSIONS: There was a positive correlation between BMI and ARVSBP, with ARVSBP increasing with a rise in BMI. BMI is a risk factor for an increase in ARVSBP. TRIAL REGISTRATION: Registration No.: CHiCTR-TNC1100 1489; Registration Date: June 01, 2006. |
format | Online Article Text |
id | pubmed-6196453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61964532018-10-30 Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults Chen, Haojia Zhang, Ruiying Zheng, Qiongbing Yan, Xiuzhu Wu, Shouling Chen, Youren BMC Public Health Research Article BACKGROUND: Obesity and overweight are related to changes in blood pressure, but existing research has mainly focused on the impact of body mass index (BMI) on short-term blood pressure variability (BPV). The study aimed to examine the impact of BMI on long-term BPV. METHODS: Participants in the Kailuan study who attended all five annual physical examinations in 2006, 2008, 2010, 2012, and 2014 were selected as observation subjects. In total, 32,482 cases were included in the statistical analysis. According to the definition of obesity in China, BMI was divided into four groups: underweight (BMI < 18.5 kg/m(2)), normal weight (18.5 ≤ BMI < 24.0 kg/m(2)), overweight (24.0 ≤ BMI < 28.0 kg/m(2)), and obese (BMI ≥ 28.0 kg/m(2)). We used average real variability to evaluate long-term systolic BPV. The average real variability of systolic blood pressure (ARV(SBP)) was calculated as (|sbp2 − sbp1| + |sbp3 − sbp2 | + |sbp4 − sbp3| + |sbp5 − sbp4|)/4. Differences in ARV(SBP) by BMI group were analyzed using analysis of variance. Stepwise multivariate linear regression and multiple logistic regression analyses were used to assess the impact of BMI on ARV(SBP). RESULTS: Participants’ average age was 46.6 ± 11.3 years, 24,502 were men, and 7980 were women. As BMI increases, the mean value of ARVSBP gradually increases. After adjusting for other confounding factors, stepwise multivariate linear regression analysis showed that ARVSBP increased by 0.077 for every one-unit increase in BMI. Multiple logistic regression analysis indicated that being obese or overweight, compared with being normal-weight, were risk factors for an increase in ARVSBP. The corresponding odds ratios of being obese or overweight were 1.23 (1.15–1.37) and 1.10 (1.04–1.15), respectively. CONCLUSIONS: There was a positive correlation between BMI and ARVSBP, with ARVSBP increasing with a rise in BMI. BMI is a risk factor for an increase in ARVSBP. TRIAL REGISTRATION: Registration No.: CHiCTR-TNC1100 1489; Registration Date: June 01, 2006. BioMed Central 2018-10-22 /pmc/articles/PMC6196453/ /pubmed/30348124 http://dx.doi.org/10.1186/s12889-018-6083-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Chen, Haojia Zhang, Ruiying Zheng, Qiongbing Yan, Xiuzhu Wu, Shouling Chen, Youren Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults |
title | Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults |
title_full | Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults |
title_fullStr | Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults |
title_full_unstemmed | Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults |
title_short | Impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of Chinese adults |
title_sort | impact of body mass index on long-term blood pressure variability: a cross-sectional study in a cohort of chinese adults |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196453/ https://www.ncbi.nlm.nih.gov/pubmed/30348124 http://dx.doi.org/10.1186/s12889-018-6083-4 |
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