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Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach

OBJECTIVE: To explore the direct and indirect associations of dietary patterns with hypertension using structural equation modelling (SEM). DESIGN: Factor analysis with varimax rotation was used to classify different dietary patterns and SEM was employed to investigate the associations of dietary pa...

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Autores principales: Ye, Junsen, Lv, Yaogai, Li, Zhongmin, Yao, Yan, Jin, Lina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6536898/
https://www.ncbi.nlm.nih.gov/pubmed/30587262
http://dx.doi.org/10.1017/S1368980018003129
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author Ye, Junsen
Lv, Yaogai
Li, Zhongmin
Yao, Yan
Jin, Lina
author_facet Ye, Junsen
Lv, Yaogai
Li, Zhongmin
Yao, Yan
Jin, Lina
author_sort Ye, Junsen
collection PubMed
description OBJECTIVE: To explore the direct and indirect associations of dietary patterns with hypertension using structural equation modelling (SEM). DESIGN: Factor analysis with varimax rotation was used to classify different dietary patterns and SEM was employed to investigate the associations of dietary patterns with hypertension. Total cholesterol to HDL-cholesterol (TC:HDL-C) ratio and LDL-cholesterol to HDL-cholesterol (LDL-C:HDL-C) ratio were used as observed indicator variables of the lipid latent variable. Waist circumference, body fat percentage and BMI, which were associated with hypertension, were used as observed indicator variables of the obesity latent variable. SETTING: International Chronic Disease Cohort (ICDC) that began in 2005 with the purpose of describing the frequency and determinants of chronic diseases in Jilin Province, China. PARTICIPANTS: A total of 1492 adults (40–79 years) were enrolled in the baseline study from August 2010 to August 2011. RESULTS: Hypertension prevalence in our study population was 34·9 %. It was found that the wine pattern, condiment pattern, obesity latent variable, lipid latent variable, glucose, age and family history of hypertension were factors that had an association with hypertension via SEM, and the corresponding coefficients were 0·056, 0·011, 0·230, 0·281, 0·098, 0·232 and 0·116, respectively. CONCLUSIONS: The wine pattern and lipid latent variable had positive direct associations with hypertension. The condiment pattern had a positive indirect association with hypertension via the obesity latent variable. The vegetables pattern, modern pattern and snack pattern were not associated with hypertension.
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spelling pubmed-65368982019-06-10 Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach Ye, Junsen Lv, Yaogai Li, Zhongmin Yao, Yan Jin, Lina Public Health Nutr Research Paper OBJECTIVE: To explore the direct and indirect associations of dietary patterns with hypertension using structural equation modelling (SEM). DESIGN: Factor analysis with varimax rotation was used to classify different dietary patterns and SEM was employed to investigate the associations of dietary patterns with hypertension. Total cholesterol to HDL-cholesterol (TC:HDL-C) ratio and LDL-cholesterol to HDL-cholesterol (LDL-C:HDL-C) ratio were used as observed indicator variables of the lipid latent variable. Waist circumference, body fat percentage and BMI, which were associated with hypertension, were used as observed indicator variables of the obesity latent variable. SETTING: International Chronic Disease Cohort (ICDC) that began in 2005 with the purpose of describing the frequency and determinants of chronic diseases in Jilin Province, China. PARTICIPANTS: A total of 1492 adults (40–79 years) were enrolled in the baseline study from August 2010 to August 2011. RESULTS: Hypertension prevalence in our study population was 34·9 %. It was found that the wine pattern, condiment pattern, obesity latent variable, lipid latent variable, glucose, age and family history of hypertension were factors that had an association with hypertension via SEM, and the corresponding coefficients were 0·056, 0·011, 0·230, 0·281, 0·098, 0·232 and 0·116, respectively. CONCLUSIONS: The wine pattern and lipid latent variable had positive direct associations with hypertension. The condiment pattern had a positive indirect association with hypertension via the obesity latent variable. The vegetables pattern, modern pattern and snack pattern were not associated with hypertension. Cambridge University Press 2018-12-27 2019-04 /pmc/articles/PMC6536898/ /pubmed/30587262 http://dx.doi.org/10.1017/S1368980018003129 Text en © The Authors 2018 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Ye, Junsen
Lv, Yaogai
Li, Zhongmin
Yao, Yan
Jin, Lina
Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach
title Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach
title_full Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach
title_fullStr Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach
title_full_unstemmed Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach
title_short Associations of dietary patterns with hypertension among adults in Jilin Province, China: a structural equation modelling approach
title_sort associations of dietary patterns with hypertension among adults in jilin province, china: a structural equation modelling approach
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6536898/
https://www.ncbi.nlm.nih.gov/pubmed/30587262
http://dx.doi.org/10.1017/S1368980018003129
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