Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis.
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| Title: | Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis. |
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| Authors: | Bitew, Zebenay Workneh1,2 zedo2015@gmial.com, Alemu, Ayinalem3, Jember, Desalegn Abebaw1, Tadesse, Erkihun1, Getaneh, Fekadeselassie Belege4, Sied, Awole2,5, Weldeyonnes, Misrak2 |
| Source: | Inquiry (00469580). 2/28/2023, p1-15. 15p. |
| Subject Terms: | *Health education, *Exercise, *Health promotion, Blood sugar monitors, Online information services, CINAHL database, Sedentary lifestyles, Obesity, Length of stay in hospitals, Meta-analysis, Confidence intervals, Social determinants of health, Glycemic control, Systematic reviews, Diabetes, Diet, Hypoglycemic agents, Sex distribution, Psychosocial factors, Disease prevalence, Descriptive statistics, Health behavior, Economic aspects of diseases, MEDLINE, Data analysis software, Odds ratio, Patient compliance, Smoking, People with diabetes, Comorbidity |
| Geographic Terms: | Ethiopia |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Inquiry (00469580) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00469580 |
| DOI: | 10.1177/00469580231155716 |
