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Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis
The primary method for preventing health and health-related problems in diabetic people is glycemic control. Numerous studies have documented the importance of glycemic control and the factors that influence it. However, the results are dispersed. This study sought to identify the prevalence of poor...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10071101/ https://www.ncbi.nlm.nih.gov/pubmed/36852627 http://dx.doi.org/10.1177/00469580231155716 |
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author | Bitew, Zebenay Workneh Alemu, Ayinalem Jember, Desalegn Abebaw Tadesse, Erkihun Getaneh, Fekadeselassie Belege Seid, Awole Weldeyonnes, Misrak |
author_facet | Bitew, Zebenay Workneh Alemu, Ayinalem Jember, Desalegn Abebaw Tadesse, Erkihun Getaneh, Fekadeselassie Belege Seid, Awole Weldeyonnes, Misrak |
author_sort | Bitew, Zebenay Workneh |
collection | PubMed |
description | The primary method for preventing health and health-related problems in diabetic people is glycemic control. Numerous studies have documented the importance of glycemic control and the factors that influence it. However, the results are dispersed. This study sought to identify the prevalence of poor glycemic control and associated factors in Ethiopia. Findings will be crucial to reduce the burden of poor glycemic control. Comprehensive search was performed from databases: PubMed, Global Health, CINAHL, IRIS, and FSTA. Gray literature sources were also explored. This document was prepared based on the PRISMA flowchart. The protocol is registered in PROSPERO (ID: CRD42022296583). STATA software was used for data analyses and I(2) test with Cochrane Q statistics, and forest plot were used to verify heterogeneity. When the I(2) value was higher than 50% and the p-value was 0.05, heterogeneity was deemed significant. To confirm publication bias, a funnel plot with an Egger’s regression test was performed. The factors related to poor glycemic control were reported using pooled odds ratios (POR) and a 95% confidence interval. In this study, 46 papers totaling 15 457 people were used to calculate the pooled estimates. It was determined that 32.6% (95% CI: 28.3, 36.9) and 61.92% (95% CI: 57.92, 65.92) of the subjects, respectively, had good and poor glycemic control. Being male protected against poor glycemic control, while poor diet adherence, lack of exercise, poor adherence to anti-diabetic medications, and smoking increased the likelihood of poor glycemic control. Lack of formal education, no family history of diabetes, lack of glucometer for blood glucose monitoring, comorbidity, being overweight and prolonged length of stay with diabetes all contributed to poor glycemic control. Ethiopia had a fairly high rate of poor glycemic control. The main determinants are lifestyle factors. Therefore, it is important to focus on behavioral interventions. |
format | Online Article Text |
id | pubmed-10071101 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-100711012023-04-05 Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis Bitew, Zebenay Workneh Alemu, Ayinalem Jember, Desalegn Abebaw Tadesse, Erkihun Getaneh, Fekadeselassie Belege Seid, Awole Weldeyonnes, Misrak Inquiry Nutrition in Developing Countries The primary method for preventing health and health-related problems in diabetic people is glycemic control. Numerous studies have documented the importance of glycemic control and the factors that influence it. However, the results are dispersed. This study sought to identify the prevalence of poor glycemic control and associated factors in Ethiopia. Findings will be crucial to reduce the burden of poor glycemic control. Comprehensive search was performed from databases: PubMed, Global Health, CINAHL, IRIS, and FSTA. Gray literature sources were also explored. This document was prepared based on the PRISMA flowchart. The protocol is registered in PROSPERO (ID: CRD42022296583). STATA software was used for data analyses and I(2) test with Cochrane Q statistics, and forest plot were used to verify heterogeneity. When the I(2) value was higher than 50% and the p-value was 0.05, heterogeneity was deemed significant. To confirm publication bias, a funnel plot with an Egger’s regression test was performed. The factors related to poor glycemic control were reported using pooled odds ratios (POR) and a 95% confidence interval. In this study, 46 papers totaling 15 457 people were used to calculate the pooled estimates. It was determined that 32.6% (95% CI: 28.3, 36.9) and 61.92% (95% CI: 57.92, 65.92) of the subjects, respectively, had good and poor glycemic control. Being male protected against poor glycemic control, while poor diet adherence, lack of exercise, poor adherence to anti-diabetic medications, and smoking increased the likelihood of poor glycemic control. Lack of formal education, no family history of diabetes, lack of glucometer for blood glucose monitoring, comorbidity, being overweight and prolonged length of stay with diabetes all contributed to poor glycemic control. Ethiopia had a fairly high rate of poor glycemic control. The main determinants are lifestyle factors. Therefore, it is important to focus on behavioral interventions. SAGE Publications 2023-02-28 /pmc/articles/PMC10071101/ /pubmed/36852627 http://dx.doi.org/10.1177/00469580231155716 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial 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 | Nutrition in Developing Countries Bitew, Zebenay Workneh Alemu, Ayinalem Jember, Desalegn Abebaw Tadesse, Erkihun Getaneh, Fekadeselassie Belege Seid, Awole Weldeyonnes, Misrak Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis |
title | Prevalence of Glycemic Control and Factors Associated With Poor
Glycemic Control: A Systematic Review and Meta-analysis |
title_full | Prevalence of Glycemic Control and Factors Associated With Poor
Glycemic Control: A Systematic Review and Meta-analysis |
title_fullStr | Prevalence of Glycemic Control and Factors Associated With Poor
Glycemic Control: A Systematic Review and Meta-analysis |
title_full_unstemmed | Prevalence of Glycemic Control and Factors Associated With Poor
Glycemic Control: A Systematic Review and Meta-analysis |
title_short | Prevalence of Glycemic Control and Factors Associated With Poor
Glycemic Control: A Systematic Review and Meta-analysis |
title_sort | prevalence of glycemic control and factors associated with poor
glycemic control: a systematic review and meta-analysis |
topic | Nutrition in Developing Countries |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10071101/ https://www.ncbi.nlm.nih.gov/pubmed/36852627 http://dx.doi.org/10.1177/00469580231155716 |
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