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Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong

OBJECTIVE: To explore the association between cardiometabolic dysregulation, an integral component of allostatic load, and health risk behaviours (HRBs) of the Hong Kong healthy adult population. DESIGN: Secondary analysis of cross-sectional anonymous data. SETTING: Data on sociodemographics, self-r...

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Autores principales: Yu, Esther Yee Tak, Yeung, Caitlin Hon Ning, Wan, Eric Yuk Fai, Tang, Eric Ho Man, Wong, Carlos King Ho, Cheung, Bernard Man Yung, Lam, Cindy Lo Kuen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273464/
https://www.ncbi.nlm.nih.gov/pubmed/34244247
http://dx.doi.org/10.1136/bmjopen-2020-043503
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author Yu, Esther Yee Tak
Yeung, Caitlin Hon Ning
Wan, Eric Yuk Fai
Tang, Eric Ho Man
Wong, Carlos King Ho
Cheung, Bernard Man Yung
Lam, Cindy Lo Kuen
author_facet Yu, Esther Yee Tak
Yeung, Caitlin Hon Ning
Wan, Eric Yuk Fai
Tang, Eric Ho Man
Wong, Carlos King Ho
Cheung, Bernard Man Yung
Lam, Cindy Lo Kuen
author_sort Yu, Esther Yee Tak
collection PubMed
description OBJECTIVE: To explore the association between cardiometabolic dysregulation, an integral component of allostatic load, and health risk behaviours (HRBs) of the Hong Kong healthy adult population. DESIGN: Secondary analysis of cross-sectional anonymous data. SETTING: Data on sociodemographics, self-reported health status, HRBs and biomarkers were extracted from the Hong Kong Population Health Survey 2014/2015. PARTICIPANTS: One thousand five hundred and fifty-one participants aged 18–64 years without self-reported diagnoses of hypertension, diabetes mellitus, hyperlipidaemia, cardiovascular disease, cognitive impairment or cancer. PRIMARY OUTCOME MEASURES: Cardiometabolic dysregulation index (CMDI), ranging from 0 to 6, was calculated by counting the number of biomarkers including systolic blood pressure, diastolic blood pressure, waist to hip ratio, glycated haemoglobin, total cholesterol to high-density lipoprotein cholesterol ratio, and triglycerides that were above the respective normal level suggested by international guidelines and literature. HRBs including smoking, dietary habits and sleeping hours were collected by self-report questionnaire. Alcohol consumption was assessed by the 10-item Alcohol Use Disorders Identification Test, while physical activity level was measured using the Global Physical Activity Questionnaire. A composite HRB score, ranging from 0 to 5, was calculated as the cumulative number of HRBs. The effect of HRB on CMDI was evaluated by negative binomial regression with adjustment for socioeconomic status, health awareness and comorbidities of the participants. RESULTS: The mean CMDI of the studied population was 1.6; 29.5% had a CMDI of 0, whereas 1.5% had a CMDI of 6. Significant difference was observed in mean CMDI between gender and different age groups. Sleeping less than 6 hours (incidence rate ratio (IRR)=1.26, p<0.001), smoking (IRR=1.15, p=0.027), insufficient physical activity (IRR=1.12, p=0.007) and higher composite HRB score (IRR=1.12, 95% CI 1.06 to 1.18) were significantly associated with higher CMDI. CONCLUSION: Smoking, physical inactivity and inadequate sleep—an essential yet often overlooked health behaviour—were associated with higher CMDI in the Hong Kong healthy adult population.
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spelling pubmed-82734642021-07-23 Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong Yu, Esther Yee Tak Yeung, Caitlin Hon Ning Wan, Eric Yuk Fai Tang, Eric Ho Man Wong, Carlos King Ho Cheung, Bernard Man Yung Lam, Cindy Lo Kuen BMJ Open Public Health OBJECTIVE: To explore the association between cardiometabolic dysregulation, an integral component of allostatic load, and health risk behaviours (HRBs) of the Hong Kong healthy adult population. DESIGN: Secondary analysis of cross-sectional anonymous data. SETTING: Data on sociodemographics, self-reported health status, HRBs and biomarkers were extracted from the Hong Kong Population Health Survey 2014/2015. PARTICIPANTS: One thousand five hundred and fifty-one participants aged 18–64 years without self-reported diagnoses of hypertension, diabetes mellitus, hyperlipidaemia, cardiovascular disease, cognitive impairment or cancer. PRIMARY OUTCOME MEASURES: Cardiometabolic dysregulation index (CMDI), ranging from 0 to 6, was calculated by counting the number of biomarkers including systolic blood pressure, diastolic blood pressure, waist to hip ratio, glycated haemoglobin, total cholesterol to high-density lipoprotein cholesterol ratio, and triglycerides that were above the respective normal level suggested by international guidelines and literature. HRBs including smoking, dietary habits and sleeping hours were collected by self-report questionnaire. Alcohol consumption was assessed by the 10-item Alcohol Use Disorders Identification Test, while physical activity level was measured using the Global Physical Activity Questionnaire. A composite HRB score, ranging from 0 to 5, was calculated as the cumulative number of HRBs. The effect of HRB on CMDI was evaluated by negative binomial regression with adjustment for socioeconomic status, health awareness and comorbidities of the participants. RESULTS: The mean CMDI of the studied population was 1.6; 29.5% had a CMDI of 0, whereas 1.5% had a CMDI of 6. Significant difference was observed in mean CMDI between gender and different age groups. Sleeping less than 6 hours (incidence rate ratio (IRR)=1.26, p<0.001), smoking (IRR=1.15, p=0.027), insufficient physical activity (IRR=1.12, p=0.007) and higher composite HRB score (IRR=1.12, 95% CI 1.06 to 1.18) were significantly associated with higher CMDI. CONCLUSION: Smoking, physical inactivity and inadequate sleep—an essential yet often overlooked health behaviour—were associated with higher CMDI in the Hong Kong healthy adult population. BMJ Publishing Group 2021-07-09 /pmc/articles/PMC8273464/ /pubmed/34244247 http://dx.doi.org/10.1136/bmjopen-2020-043503 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Public Health
Yu, Esther Yee Tak
Yeung, Caitlin Hon Ning
Wan, Eric Yuk Fai
Tang, Eric Ho Man
Wong, Carlos King Ho
Cheung, Bernard Man Yung
Lam, Cindy Lo Kuen
Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong
title Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong
title_full Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong
title_fullStr Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong
title_full_unstemmed Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong
title_short Association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in Hong Kong
title_sort association between health behaviours and cardiometabolic dysregulation: a population-based survey among healthy adults in hong kong
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273464/
https://www.ncbi.nlm.nih.gov/pubmed/34244247
http://dx.doi.org/10.1136/bmjopen-2020-043503
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