Cargando…

Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations

BACKGROUND: This study was determined to describe the patterns of lifestyle behaviors and their associations with metabolic profiles among Chinese urban and rural adults. METHODS: This was a cross-sectional study set in the Nanjing (5,824) and Hefei (20,269) Community Cardiovascular Risk Surveys fro...

Descripción completa

Detalles Bibliográficos
Autores principales: Cui, Qian, Chen, Ying, Ye, Xinhua, Cai, Yamei, Qin, Rui, Chen, Tao, Yan, Ting, Yu, Dahai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643223/
https://www.ncbi.nlm.nih.gov/pubmed/36407735
http://dx.doi.org/10.18502/ijph.v51i5.9423
_version_ 1784826473996091392
author Cui, Qian
Chen, Ying
Ye, Xinhua
Cai, Yamei
Qin, Rui
Chen, Tao
Yan, Ting
Yu, Dahai
author_facet Cui, Qian
Chen, Ying
Ye, Xinhua
Cai, Yamei
Qin, Rui
Chen, Tao
Yan, Ting
Yu, Dahai
author_sort Cui, Qian
collection PubMed
description BACKGROUND: This study was determined to describe the patterns of lifestyle behaviors and their associations with metabolic profiles among Chinese urban and rural adults. METHODS: This was a cross-sectional study set in the Nanjing (5,824) and Hefei (20,269) Community Cardiovascular Risk Surveys from 2011–2013, using random cluster sampling. Questionnaires were completed via face-to-face interview, and data on lifestyle behaviors including daily night sleep duration, nap duration (if any) and sitting time, and weekly physical activity (measured using the International Physical Activity Questionnaire, in metabolic equivalents of task × minutes, and separated into walking and moderate-to-vigorous physical activity (MOVPA) according to intensity) was collected. The patterns of physical activity in Chinese urban and rural populations and the metabolic profile in each pattern were identified by the latent class analysis. RESULTS: Six distinct clusters were determined, with the sizes ranging from 45% to 5% of the total population. For example, the most common cluster was associated with a sufficient night and nap sleep duration, a long sitting time, and above WHO recommended physical activities for both walking and MOVPA, and the smallest cluster was featured by its huge amount of MOVPA and limited amount of walking activity. Difference in proportion of each cluster was observed between the two survey sites. No obvious abnormal blood measures were seen in any cluster. CONCLUSION: Common lifestyle behavior clusters were described, leading to a better understanding of people’s routine activities.
format Online
Article
Text
id pubmed-9643223
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Tehran University of Medical Sciences
record_format MEDLINE/PubMed
spelling pubmed-96432232022-11-18 Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations Cui, Qian Chen, Ying Ye, Xinhua Cai, Yamei Qin, Rui Chen, Tao Yan, Ting Yu, Dahai Iran J Public Health Original Article BACKGROUND: This study was determined to describe the patterns of lifestyle behaviors and their associations with metabolic profiles among Chinese urban and rural adults. METHODS: This was a cross-sectional study set in the Nanjing (5,824) and Hefei (20,269) Community Cardiovascular Risk Surveys from 2011–2013, using random cluster sampling. Questionnaires were completed via face-to-face interview, and data on lifestyle behaviors including daily night sleep duration, nap duration (if any) and sitting time, and weekly physical activity (measured using the International Physical Activity Questionnaire, in metabolic equivalents of task × minutes, and separated into walking and moderate-to-vigorous physical activity (MOVPA) according to intensity) was collected. The patterns of physical activity in Chinese urban and rural populations and the metabolic profile in each pattern were identified by the latent class analysis. RESULTS: Six distinct clusters were determined, with the sizes ranging from 45% to 5% of the total population. For example, the most common cluster was associated with a sufficient night and nap sleep duration, a long sitting time, and above WHO recommended physical activities for both walking and MOVPA, and the smallest cluster was featured by its huge amount of MOVPA and limited amount of walking activity. Difference in proportion of each cluster was observed between the two survey sites. No obvious abnormal blood measures were seen in any cluster. CONCLUSION: Common lifestyle behavior clusters were described, leading to a better understanding of people’s routine activities. Tehran University of Medical Sciences 2022-05 /pmc/articles/PMC9643223/ /pubmed/36407735 http://dx.doi.org/10.18502/ijph.v51i5.9423 Text en Copyright © 2022 Cui et al. Published by Tehran University of Medical Sciences https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license (https://creativecommons.org/licenses/by-nc/4.0/). Non-commercial uses of the work are permitted, provided the original work is properly cited.
spellingShingle Original Article
Cui, Qian
Chen, Ying
Ye, Xinhua
Cai, Yamei
Qin, Rui
Chen, Tao
Yan, Ting
Yu, Dahai
Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations
title Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations
title_full Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations
title_fullStr Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations
title_full_unstemmed Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations
title_short Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations
title_sort patterns of lifestyle behaviors and relevant metabolic profiles in chinese adults: latent class analysis from two independent surveys in urban and rural populations
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643223/
https://www.ncbi.nlm.nih.gov/pubmed/36407735
http://dx.doi.org/10.18502/ijph.v51i5.9423
work_keys_str_mv AT cuiqian patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations
AT chenying patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations
AT yexinhua patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations
AT caiyamei patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations
AT qinrui patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations
AT chentao patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations
AT yanting patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations
AT yudahai patternsoflifestylebehaviorsandrelevantmetabolicprofilesinchineseadultslatentclassanalysisfromtwoindependentsurveysinurbanandruralpopulations