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Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China

BACKGROUND: A change in weight or metabolic status is a dynamic process, yet most studies have focused on metabolically healthy obesity (MHO) and the transition between MHO and metabolically unhealthy obesity (MUO); therefore, they have not fully revealed the nature of all possible transitions among...

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Autores principales: Zhang, Hongya, Tang, Xiao, Hu, Dongmei, Li, Guorong, Song, Guirong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9799718/
https://www.ncbi.nlm.nih.gov/pubmed/36589938
http://dx.doi.org/10.3389/fpubh.2022.1026751
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author Zhang, Hongya
Tang, Xiao
Hu, Dongmei
Li, Guorong
Song, Guirong
author_facet Zhang, Hongya
Tang, Xiao
Hu, Dongmei
Li, Guorong
Song, Guirong
author_sort Zhang, Hongya
collection PubMed
description BACKGROUND: A change in weight or metabolic status is a dynamic process, yet most studies have focused on metabolically healthy obesity (MHO) and the transition between MHO and metabolically unhealthy obesity (MUO); therefore, they have not fully revealed the nature of all possible transitions among metabolism-weight phenotypes over the years. METHODS: This was a longitudinal study based on a retrospective health check-up cohort. A total of 9,742 apparently healthy individuals aged 20–60 years at study entry were included and underwent at least two health check-ups. Six metabolism-weight phenotypes were cross-defined by body mass index (BMI) categories and metabolic status as follows: metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), MHO, metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and MUO. A multistate Markov model was used to analyse all possible transitions among these phenotypes and assess the effects of demographic and blood indicators on the transitions. RESULTS: The transition intensity from MUNW to MHNW was the highest (0.64), followed by the transition from MHO to MUO (0.56). The greatest sojourn time appeared in the MHNW state (3.84 years), followed by the MUO state (2.34 years), and the shortest sojourn time appeared in the MHO state (1.16 years). Transition intensities for metabolic improvement gradually decreased with BMI level as follows: 0.64 for MUNW to MHNW, 0.44 for MUOW to MHNW, and 0.27 for MUO to MHO; however, transition intensities for metabolic deterioration, including MHNW to MUNW, MHOW to MUOW, and MHO to MUO, were 0.15, 0.38, and 0.56, respectively. In the middle-aged male group, elevated alanine aminotransferase (ALT), aspartate aminotransferase (AST), and uric acid (UA) increased the risk of deterioration in weight and metabolic status and decreased the possibility of improvement. CONCLUSION: Maintaining a normal and stable BMI is important for metabolic health. More attention should be given to males and elderly people to prevent their progression to an unhealthy metabolic and/or weight status. MHO is the most unstable phenotype and is prone to convert to the MUO state, and individuals with abnormal ALT, AST and UA are at an increased risk of transitioning to an unhealthy weight and/or metabolic status; therefore, we should be alert to abnormal indicators and MHO. Intervention measures should be taken early to maintain healthy weight and metabolic status.
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spelling pubmed-97997182022-12-30 Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China Zhang, Hongya Tang, Xiao Hu, Dongmei Li, Guorong Song, Guirong Front Public Health Public Health BACKGROUND: A change in weight or metabolic status is a dynamic process, yet most studies have focused on metabolically healthy obesity (MHO) and the transition between MHO and metabolically unhealthy obesity (MUO); therefore, they have not fully revealed the nature of all possible transitions among metabolism-weight phenotypes over the years. METHODS: This was a longitudinal study based on a retrospective health check-up cohort. A total of 9,742 apparently healthy individuals aged 20–60 years at study entry were included and underwent at least two health check-ups. Six metabolism-weight phenotypes were cross-defined by body mass index (BMI) categories and metabolic status as follows: metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), MHO, metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and MUO. A multistate Markov model was used to analyse all possible transitions among these phenotypes and assess the effects of demographic and blood indicators on the transitions. RESULTS: The transition intensity from MUNW to MHNW was the highest (0.64), followed by the transition from MHO to MUO (0.56). The greatest sojourn time appeared in the MHNW state (3.84 years), followed by the MUO state (2.34 years), and the shortest sojourn time appeared in the MHO state (1.16 years). Transition intensities for metabolic improvement gradually decreased with BMI level as follows: 0.64 for MUNW to MHNW, 0.44 for MUOW to MHNW, and 0.27 for MUO to MHO; however, transition intensities for metabolic deterioration, including MHNW to MUNW, MHOW to MUOW, and MHO to MUO, were 0.15, 0.38, and 0.56, respectively. In the middle-aged male group, elevated alanine aminotransferase (ALT), aspartate aminotransferase (AST), and uric acid (UA) increased the risk of deterioration in weight and metabolic status and decreased the possibility of improvement. CONCLUSION: Maintaining a normal and stable BMI is important for metabolic health. More attention should be given to males and elderly people to prevent their progression to an unhealthy metabolic and/or weight status. MHO is the most unstable phenotype and is prone to convert to the MUO state, and individuals with abnormal ALT, AST and UA are at an increased risk of transitioning to an unhealthy weight and/or metabolic status; therefore, we should be alert to abnormal indicators and MHO. Intervention measures should be taken early to maintain healthy weight and metabolic status. Frontiers Media S.A. 2022-12-15 /pmc/articles/PMC9799718/ /pubmed/36589938 http://dx.doi.org/10.3389/fpubh.2022.1026751 Text en Copyright © 2022 Zhang, Tang, Hu, Li and Song. 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 Public Health
Zhang, Hongya
Tang, Xiao
Hu, Dongmei
Li, Guorong
Song, Guirong
Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China
title Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China
title_full Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China
title_fullStr Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China
title_full_unstemmed Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China
title_short Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China
title_sort transition patterns of metabolism-weight phenotypes over time: a longitudinal study using the multistate markov model in china
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9799718/
https://www.ncbi.nlm.nih.gov/pubmed/36589938
http://dx.doi.org/10.3389/fpubh.2022.1026751
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