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Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia

BACKGROUND: Type 2 diabetes is a lifelong metabolic disease closely related to unhealthy lifestyle behaviours. This study aimed to identify factors explaining the healthy lifestyle behaviours of patients with type 2 diabetes in rural Indonesia. The extended health belief model, demographic character...

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Autores principales: Asril, Nice Maylani, Tabuchi, Keiji, Tsunematsu, Miwako, Kobayashi, Toshio, Kakehashi, Masayuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171987/
https://www.ncbi.nlm.nih.gov/pubmed/32341670
http://dx.doi.org/10.1177/1179551420915856
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author Asril, Nice Maylani
Tabuchi, Keiji
Tsunematsu, Miwako
Kobayashi, Toshio
Kakehashi, Masayuki
author_facet Asril, Nice Maylani
Tabuchi, Keiji
Tsunematsu, Miwako
Kobayashi, Toshio
Kakehashi, Masayuki
author_sort Asril, Nice Maylani
collection PubMed
description BACKGROUND: Type 2 diabetes is a lifelong metabolic disease closely related to unhealthy lifestyle behaviours. This study aimed to identify factors explaining the healthy lifestyle behaviours of patients with type 2 diabetes in rural Indonesia. The extended health belief model, demographic characteristics, clinical lifestyle factors and diabetes knowledge were investigated to provide a complete description of these behaviours. METHOD: A sample of 203 patients with type 2 diabetes representing a cross-section of the population were recruited from community health centres in the rural areas of Bali province. The data were collected through questionnaires. Descriptive statistics and a hierarchical regression test were employed. RESULTS: This study showed demographic characteristics, clinical and lifestyle factors, diabetes knowledge and the extended health belief model accounted for 71.8% of the variance in healthy lifestyle behaviours of patients with type 2 diabetes in rural Indonesia. The significant demographic factors were age, education level, employment status and traditional beliefs. The significant clinical and lifestyle factors were alcohol use, diabetic medicine and duration of symptoms. Finally, the significant extended health belief model factors were perceived severity, susceptibility, barriers, family support, bonding social capital and chance locus of control. CONCLUSIONS: The extended health belief model forms an adequate model for predicting healthy lifestyle behaviours among patients with diabetes in rural Indonesia. The contribution of this model should be strengthened in developing the diabetes management.
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spelling pubmed-71719872020-04-27 Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia Asril, Nice Maylani Tabuchi, Keiji Tsunematsu, Miwako Kobayashi, Toshio Kakehashi, Masayuki Clin Med Insights Endocrinol Diabetes Original Article BACKGROUND: Type 2 diabetes is a lifelong metabolic disease closely related to unhealthy lifestyle behaviours. This study aimed to identify factors explaining the healthy lifestyle behaviours of patients with type 2 diabetes in rural Indonesia. The extended health belief model, demographic characteristics, clinical lifestyle factors and diabetes knowledge were investigated to provide a complete description of these behaviours. METHOD: A sample of 203 patients with type 2 diabetes representing a cross-section of the population were recruited from community health centres in the rural areas of Bali province. The data were collected through questionnaires. Descriptive statistics and a hierarchical regression test were employed. RESULTS: This study showed demographic characteristics, clinical and lifestyle factors, diabetes knowledge and the extended health belief model accounted for 71.8% of the variance in healthy lifestyle behaviours of patients with type 2 diabetes in rural Indonesia. The significant demographic factors were age, education level, employment status and traditional beliefs. The significant clinical and lifestyle factors were alcohol use, diabetic medicine and duration of symptoms. Finally, the significant extended health belief model factors were perceived severity, susceptibility, barriers, family support, bonding social capital and chance locus of control. CONCLUSIONS: The extended health belief model forms an adequate model for predicting healthy lifestyle behaviours among patients with diabetes in rural Indonesia. The contribution of this model should be strengthened in developing the diabetes management. SAGE Publications 2020-04-20 /pmc/articles/PMC7171987/ /pubmed/32341670 http://dx.doi.org/10.1177/1179551420915856 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Article
Asril, Nice Maylani
Tabuchi, Keiji
Tsunematsu, Miwako
Kobayashi, Toshio
Kakehashi, Masayuki
Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia
title Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia
title_full Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia
title_fullStr Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia
title_full_unstemmed Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia
title_short Predicting Healthy Lifestyle Behaviours Among Patients With Type 2 Diabetes in Rural Bali, Indonesia
title_sort predicting healthy lifestyle behaviours among patients with type 2 diabetes in rural bali, indonesia
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171987/
https://www.ncbi.nlm.nih.gov/pubmed/32341670
http://dx.doi.org/10.1177/1179551420915856
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