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Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)

Few studies have examined the secular trend of energy intake distribution. This study aims to describe trajectories of energy intake distribution and determine their association with dyslipidemia risk. Data of 2843 adult participants from the China Health and Nutrition Survey (CHNS) were analyzed. T...

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Autores principales: Song, Xiaoyun, Wang, Huijun, Su, Chang, Wang, Zhihong, Du, Wenwen, Huang, Feifei, Zhang, Jiguo, Jia, Xiaofang, Jiang, Hongru, Ouyang, Yifei, Li, Li, Bai, Jing, Zhang, Xiaofan, Ding, Gangqiang, Zhang, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8538511/
https://www.ncbi.nlm.nih.gov/pubmed/34684489
http://dx.doi.org/10.3390/nu13103488
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author Song, Xiaoyun
Wang, Huijun
Su, Chang
Wang, Zhihong
Du, Wenwen
Huang, Feifei
Zhang, Jiguo
Jia, Xiaofang
Jiang, Hongru
Ouyang, Yifei
Li, Li
Bai, Jing
Zhang, Xiaofan
Ding, Gangqiang
Zhang, Bing
author_facet Song, Xiaoyun
Wang, Huijun
Su, Chang
Wang, Zhihong
Du, Wenwen
Huang, Feifei
Zhang, Jiguo
Jia, Xiaofang
Jiang, Hongru
Ouyang, Yifei
Li, Li
Bai, Jing
Zhang, Xiaofan
Ding, Gangqiang
Zhang, Bing
author_sort Song, Xiaoyun
collection PubMed
description Few studies have examined the secular trend of energy intake distribution. This study aims to describe trajectories of energy intake distribution and determine their association with dyslipidemia risk. Data of 2843 adult participants from the China Health and Nutrition Survey (CHNS) were analyzed. Trajectory groups of energy intake distribution were identified by multi-trajectory model over 27 years. Multilevel mixed-effects modified Poisson regression with robust estimation of variance was used to calculate risk ratio for incident dyslipidemia in a 9-year follow-up. Four trajectory groups were identified: “Energy evenly distributed group” (Group 1), “Lunch and dinner energy dominant group” (Group 2), “Dinner energy dominant group” (Group 3), “breakfast and dinner energy dominant group” (Group 4). Compared with Group 1, Group 3 was associated with higher risk of dyslipidemia (RR = 1.48, 95% CI = 1.26, 1.75), hypercholesterolemia (RR = 1.96, 95% CI = 1.37, 2.81) and high low-density lipoproteins cholesterols (LDL-C) (RR = 2.41, 95% CI = 1.82, 3.20). A U-shape was observed between cumulative average proportion of dinner energy and dyslipidemia risk (p for non-linear = 0.01), with stronger relationship at 40% and above. Energy intake distribution characterized by higher proportion of dinner energy, especially over 40% was associated with higher dyslipidemia risk in Chinese adults.
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spelling pubmed-85385112021-10-24 Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018) Song, Xiaoyun Wang, Huijun Su, Chang Wang, Zhihong Du, Wenwen Huang, Feifei Zhang, Jiguo Jia, Xiaofang Jiang, Hongru Ouyang, Yifei Li, Li Bai, Jing Zhang, Xiaofan Ding, Gangqiang Zhang, Bing Nutrients Article Few studies have examined the secular trend of energy intake distribution. This study aims to describe trajectories of energy intake distribution and determine their association with dyslipidemia risk. Data of 2843 adult participants from the China Health and Nutrition Survey (CHNS) were analyzed. Trajectory groups of energy intake distribution were identified by multi-trajectory model over 27 years. Multilevel mixed-effects modified Poisson regression with robust estimation of variance was used to calculate risk ratio for incident dyslipidemia in a 9-year follow-up. Four trajectory groups were identified: “Energy evenly distributed group” (Group 1), “Lunch and dinner energy dominant group” (Group 2), “Dinner energy dominant group” (Group 3), “breakfast and dinner energy dominant group” (Group 4). Compared with Group 1, Group 3 was associated with higher risk of dyslipidemia (RR = 1.48, 95% CI = 1.26, 1.75), hypercholesterolemia (RR = 1.96, 95% CI = 1.37, 2.81) and high low-density lipoproteins cholesterols (LDL-C) (RR = 2.41, 95% CI = 1.82, 3.20). A U-shape was observed between cumulative average proportion of dinner energy and dyslipidemia risk (p for non-linear = 0.01), with stronger relationship at 40% and above. Energy intake distribution characterized by higher proportion of dinner energy, especially over 40% was associated with higher dyslipidemia risk in Chinese adults. MDPI 2021-10-01 /pmc/articles/PMC8538511/ /pubmed/34684489 http://dx.doi.org/10.3390/nu13103488 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Song, Xiaoyun
Wang, Huijun
Su, Chang
Wang, Zhihong
Du, Wenwen
Huang, Feifei
Zhang, Jiguo
Jia, Xiaofang
Jiang, Hongru
Ouyang, Yifei
Li, Li
Bai, Jing
Zhang, Xiaofan
Ding, Gangqiang
Zhang, Bing
Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)
title Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)
title_full Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)
title_fullStr Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)
title_full_unstemmed Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)
title_short Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)
title_sort trajectories of energy intake distribution and risk of dyslipidemia: findings from the china health and nutrition survey (1991–2018)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8538511/
https://www.ncbi.nlm.nih.gov/pubmed/34684489
http://dx.doi.org/10.3390/nu13103488
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