Relationship between health behavior and metabolic syndrome progression: The parallel latent growth curve model

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Somkiat Tonphu
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Published: Feb 26, 2022
DOI: https://doi.org/10.31524/bkkmedj.2022.11.001

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Somkiat Tonphu, MBA, BPH, BA, BSc
Graduate School of Applied Statistics,Business Analytics and Intelligence, National Institute of Development Administration, Bangkok, Thailand.
Sumith Tanaprakob, MD
Health Promotion Center 2, Bangkok Hospital, Bangkok Hospital Group, Bangkok, Thailand.
Phunlerd Piyaraj, MD, PhD
Department of Parasitology, Phramongkutklao College of Medicine, Bangkok, Thailand. Bangkok Health Research Center, Bangkok Dusit Medical Services Public Company Limited, Bangkok, Thailand.
Arnond Sakworawich, PhD, MBA, MA, BBA
Graduate School of Applied Statistics, Business Analytics and Intelligence, National Institute of Development Administration, Bangkok, Thailand.

Abstract

OBJECTIVES: This research aims to develop a measurement model to assess an relationship between Metabolic Syndrome (MetS) progression and health behavior changes. 


MATERIAL AND METHODS: Medical records of selected patients attending checkup clinics of a private hospital from 2006 - 2017 was reviewed. Clinical and questionnaire data that assessed exercise (EXE), smoking (SMK), and failure to control weight (FCW) including waist circumference (WC) and BMI as well as laboratory results i.e. Blood pressure, high density lipoprotein (HDL), low density lipoprotein (LDL), triglycerides (TG), and fasting blood sugar (FBS) were retrieved.  The NCEP ATP III was applied to diagnose Metabolic Syndrome (MetS) and a parallel latent growth curve model was used to assess relationships between MetS progression and health-related behaviors using R-code with lavaan (latent variable analysis) version 0.6-1 package.  χ2/df, CFI, TLI, GFI, SRMR, RMSEA and Analysis of Covariate (ANCOVA) were used to determine goodness of fit and influence of sex and age as co-variates of the model.  


RESULT: Among 1,296 patients, 61 (4.7%), 64 (4.9%), 70 (5.4%), 73 (5.6%) and 87 (6.7%) patients had MetS each year.  FCW had strong effects on prevalence (coefficient 0.69) and trend (0.57) of MetS progression while EXE had small negative (-0.05 and -0.07) and SMK had small and positive (0.01 and 0.03) effects.  Age and gender contributed to MetS indirectly through FCW.  Decomposition of effects revealed high relationship between FCW and prevalence (0.69) and trend (0.57) of MetS.  SMK had indirect effect on TG (0.66) and HDL (-0.61) but these effects were diluted off after controlled for effects of other variables.    


CONCLUSION: 


We have brought to light the hidden (latent) aspect that age and sex result in MetS through FCW.  With the significance of FCW, which subsequently increases risks for several NCDs, healthy eating should be the most important health promotion topic to avoid MetS progression. The LGC model can be used to supplement the diagnostic and prognostic scores for both physicians and health teams because it provides more detailed information of hidden (latent) relationships. Mobile phone applications using this model should be developed in order to promote self-regulation among MetS patients. Future research should be conducted for revision, calibration and validation of the ATP III criteria and the current research risk scores.

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How to Cite
1.
Tonphu, MBA, BPH, BA, BSc S, Tanaprakob, MD S, Piyaraj, MD, PhD P, Sakworawich, PhD, MBA, MA, BBA A. Relationship between health behavior and metabolic syndrome progression: The parallel latent growth curve model. BKK Med J [Internet]. 2022 Feb. 26 [cited 2024 Nov. 22];18(1):1. Available from: https://he02.tci-thaijo.org/index.php/bkkmedj/article/view/252432
Issue
Vol. 18 No. 1 (2022): February
Section
Original Article
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