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Structural equation modeling to identify the risk factors of diabetes in the adult population of North India
BACKGROUND: A non-communicable disease risk factor survey (based on World Health Organization STEP approach to Surveillance, i.e., WHO-STEPS) was done in the state of Punjab, India in a multistage stratified sample of 5127 individuals. The study subjects were administered the WHO STEPS questionnaire...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019304/ https://www.ncbi.nlm.nih.gov/pubmed/29983621 http://dx.doi.org/10.1186/s41182-018-0104-y |
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author | Tripathy, Jaya Prasad Thakur, J S Jeet, Gursimer Jain, Sanjay |
author_facet | Tripathy, Jaya Prasad Thakur, J S Jeet, Gursimer Jain, Sanjay |
author_sort | Tripathy, Jaya Prasad |
collection | PubMed |
description | BACKGROUND: A non-communicable disease risk factor survey (based on World Health Organization STEP approach to Surveillance, i.e., WHO-STEPS) was done in the state of Punjab, India in a multistage stratified sample of 5127 individuals. The study subjects were administered the WHO STEPS questionnaire and also underwent anthropometric and biochemical measurements. This study aimed at exploring the risk factors of diabetes using a Structural Equation Modeling (SEM) approach in the North Indian state of Punjab. RESULTS: Overall prevalence of diabetes mellitus among the study participants was found out to be 8.3% (95% CI 7.3–9.4%). The final SEM had excellent fit considering the model parameters. The following risk factors deemed to have a direct statistically significant effect on blood sugar status: family history of diabetes (4.5), urban residence (3.1), triglycerides (0.46), increasing waist circumference (0.18), systolic blood pressure (0.11), and increasing age (0.05). There are specific indirect effects of alcohol use (1.43, p = 0.001), family h/o diabetes (0.844, p = 0.001), age (0.156, p < 0.001), waist circumference (0.028, p = < 0.001) and weekly fruit intake (− 0.009, p = 0.034) on fasting blood glucose. Indirect effects of waist circumference, alcohol intake and age on blood sugar levels are mediated by raised blood pressure. Waist circumference mediates the indirect effects of age, family h/o of diabetes, alcohol intake and weekly fruit intake on blood sugar levels. Triglycerides also mediated the indirect effects between age and diabetes. CONCLUSIONS: Family history of diabetes, urban residence, alcohol use, increasing age, and waist circumference are the key variables affecting diabetes status in the Indian population. The results of this study further strengthens the evidence that lifestyle changes in the form of physical activity and healthy diet are required to prevent and control diabetes. Those with family h/o diabetes constitute a high risk group and should be targeted with regular screening and lifestyle intervention package. |
format | Online Article Text |
id | pubmed-6019304 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60193042018-07-06 Structural equation modeling to identify the risk factors of diabetes in the adult population of North India Tripathy, Jaya Prasad Thakur, J S Jeet, Gursimer Jain, Sanjay Trop Med Health Research BACKGROUND: A non-communicable disease risk factor survey (based on World Health Organization STEP approach to Surveillance, i.e., WHO-STEPS) was done in the state of Punjab, India in a multistage stratified sample of 5127 individuals. The study subjects were administered the WHO STEPS questionnaire and also underwent anthropometric and biochemical measurements. This study aimed at exploring the risk factors of diabetes using a Structural Equation Modeling (SEM) approach in the North Indian state of Punjab. RESULTS: Overall prevalence of diabetes mellitus among the study participants was found out to be 8.3% (95% CI 7.3–9.4%). The final SEM had excellent fit considering the model parameters. The following risk factors deemed to have a direct statistically significant effect on blood sugar status: family history of diabetes (4.5), urban residence (3.1), triglycerides (0.46), increasing waist circumference (0.18), systolic blood pressure (0.11), and increasing age (0.05). There are specific indirect effects of alcohol use (1.43, p = 0.001), family h/o diabetes (0.844, p = 0.001), age (0.156, p < 0.001), waist circumference (0.028, p = < 0.001) and weekly fruit intake (− 0.009, p = 0.034) on fasting blood glucose. Indirect effects of waist circumference, alcohol intake and age on blood sugar levels are mediated by raised blood pressure. Waist circumference mediates the indirect effects of age, family h/o of diabetes, alcohol intake and weekly fruit intake on blood sugar levels. Triglycerides also mediated the indirect effects between age and diabetes. CONCLUSIONS: Family history of diabetes, urban residence, alcohol use, increasing age, and waist circumference are the key variables affecting diabetes status in the Indian population. The results of this study further strengthens the evidence that lifestyle changes in the form of physical activity and healthy diet are required to prevent and control diabetes. Those with family h/o diabetes constitute a high risk group and should be targeted with regular screening and lifestyle intervention package. BioMed Central 2018-06-25 /pmc/articles/PMC6019304/ /pubmed/29983621 http://dx.doi.org/10.1186/s41182-018-0104-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Tripathy, Jaya Prasad Thakur, J S Jeet, Gursimer Jain, Sanjay Structural equation modeling to identify the risk factors of diabetes in the adult population of North India |
title | Structural equation modeling to identify the risk factors of diabetes in the adult population of North India |
title_full | Structural equation modeling to identify the risk factors of diabetes in the adult population of North India |
title_fullStr | Structural equation modeling to identify the risk factors of diabetes in the adult population of North India |
title_full_unstemmed | Structural equation modeling to identify the risk factors of diabetes in the adult population of North India |
title_short | Structural equation modeling to identify the risk factors of diabetes in the adult population of North India |
title_sort | structural equation modeling to identify the risk factors of diabetes in the adult population of north india |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019304/ https://www.ncbi.nlm.nih.gov/pubmed/29983621 http://dx.doi.org/10.1186/s41182-018-0104-y |
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