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Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study

BACKGROUND: Body mass index (BMI) has been widely recognized as a risk factor for metabolic syndrome (MetS). However, the relationship between the trajectory of BMI and cumulative incident MetS is still unclear. We investigate the associations of long-term measurements of BMI with MetS among young a...

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Autores principales: Ying, Ming, Hu, Xiangming, Li, Qiang, Dong, Haojian, Zhou, Yingling, Chen, Zhujun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9773063/
https://www.ncbi.nlm.nih.gov/pubmed/36568079
http://dx.doi.org/10.3389/fendo.2022.915394
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author Ying, Ming
Hu, Xiangming
Li, Qiang
Dong, Haojian
Zhou, Yingling
Chen, Zhujun
author_facet Ying, Ming
Hu, Xiangming
Li, Qiang
Dong, Haojian
Zhou, Yingling
Chen, Zhujun
author_sort Ying, Ming
collection PubMed
description BACKGROUND: Body mass index (BMI) has been widely recognized as a risk factor for metabolic syndrome (MetS). However, the relationship between the trajectory of BMI and cumulative incident MetS is still unclear. We investigate the associations of long-term measurements of BMI with MetS among young adults in the China Health and Nutrition Survey. METHODS: We enrolled individuals aged 10 to 20 at baseline with recorded BMI at each follow-up interview, and 554 participants were finally included in our study. The assessment and incidence of MetS were evaluated by blood tests and physical examinations in their adulthood. A latent class growth mixed model was used to identify three BMI trajectory patterns: a low baseline BMI with slow development (low-slow, n=438), a low baseline BMI with fast development (low-fast, n=66), and a high baseline BMI with fast development (high-fast, n=50). Logistic regression was used to explore the relationship between different BMI trajectories and the incidence of MetS. RESULT: During a follow-up of 16 years, 61 (11.01%) participants developed MetS. The combination of elevated triglycerides and reduced high-density lipoprotein cholesterol was most frequent in diagnosed MetS. In multivariate adjusted models, the low-fast and high-fast BMI trajectories showed a significantly higher risk of MetS than those with the low-slow BMI trajectory (low-high: OR = 3.40, 95% CI: 1.14-10.13, P < 0.05; high-fast: OR = 5.81, 95% CI: 1.63-20.69, P < 0.05). CONCLUSION: Our study identified three BMI trajectories in young adults and found that long-term measurements of BMI were also associated with cumulative incident MetS.
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spelling pubmed-97730632022-12-23 Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study Ying, Ming Hu, Xiangming Li, Qiang Dong, Haojian Zhou, Yingling Chen, Zhujun Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Body mass index (BMI) has been widely recognized as a risk factor for metabolic syndrome (MetS). However, the relationship between the trajectory of BMI and cumulative incident MetS is still unclear. We investigate the associations of long-term measurements of BMI with MetS among young adults in the China Health and Nutrition Survey. METHODS: We enrolled individuals aged 10 to 20 at baseline with recorded BMI at each follow-up interview, and 554 participants were finally included in our study. The assessment and incidence of MetS were evaluated by blood tests and physical examinations in their adulthood. A latent class growth mixed model was used to identify three BMI trajectory patterns: a low baseline BMI with slow development (low-slow, n=438), a low baseline BMI with fast development (low-fast, n=66), and a high baseline BMI with fast development (high-fast, n=50). Logistic regression was used to explore the relationship between different BMI trajectories and the incidence of MetS. RESULT: During a follow-up of 16 years, 61 (11.01%) participants developed MetS. The combination of elevated triglycerides and reduced high-density lipoprotein cholesterol was most frequent in diagnosed MetS. In multivariate adjusted models, the low-fast and high-fast BMI trajectories showed a significantly higher risk of MetS than those with the low-slow BMI trajectory (low-high: OR = 3.40, 95% CI: 1.14-10.13, P < 0.05; high-fast: OR = 5.81, 95% CI: 1.63-20.69, P < 0.05). CONCLUSION: Our study identified three BMI trajectories in young adults and found that long-term measurements of BMI were also associated with cumulative incident MetS. Frontiers Media S.A. 2022-12-08 /pmc/articles/PMC9773063/ /pubmed/36568079 http://dx.doi.org/10.3389/fendo.2022.915394 Text en Copyright © 2022 Ying, Hu, Li, Dong, Zhou and Chen https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Ying, Ming
Hu, Xiangming
Li, Qiang
Dong, Haojian
Zhou, Yingling
Chen, Zhujun
Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study
title Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study
title_full Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study
title_fullStr Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study
title_full_unstemmed Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study
title_short Long-term trajectories of BMI and cumulative incident metabolic syndrome: A cohort study
title_sort long-term trajectories of bmi and cumulative incident metabolic syndrome: a cohort study
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9773063/
https://www.ncbi.nlm.nih.gov/pubmed/36568079
http://dx.doi.org/10.3389/fendo.2022.915394
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