Association Between the Level of Reported Good Medication Adherence and the Geographic Location of a Patient's Residence and Presence of a Glucometer Among Adult Patients with Diabetes in Ethiopia: A Systematic and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus (DM) is a major public health problem worldwide that was estimated to have affected the lives of 425 million people globally in 2017. The prevalence and mortality rates of DM have increased rapidly in low- and middle-income countries with an estimated 2.6 million cases of DM occurring in Ethiopia alone in 2015. OBJECTIVE: Considering that Ethiopia is undergoing an epidemiological transition, it is increasingly important to understand the significant influence DM has on Ethiopians annually. A systematic review and meta-analysis of the existing studies were conducted to better understand the factors that are associated with DM medication adherence across Ethiopia and to elucidate areas for further studies. METHODS: Studies were retrieved through search engines in Cumulative Index to Nursing and Allied Health Literature, Embase, Medline, PubMed, Google Scholar, Web of Science, Science Direct, and Scopus. The Newcastle-Ottawa Scale for cross-sectional studies was used to assess the critical appraisal of the included studies. Random effects model was used to estimate the association between the level of medication adherence and the geographic location of a patient's residence and presence of a glucometer at 95% CI with its respective odds ratio. Meta-regression was also used to identify the potential source of heterogeneity. Beggs and Egger tests were performed to determine publication bias. Subgroup analyses, based on the study area, were also performed. RESULTS: A total of 1046 articles were identified through searching, of which 19 articles representing 7756 participants were included for the final analysis stage. Reported good medication adherence among patients with diabetes in Ethiopia was 68.59% (95% CI, 62.00%-75.18%). Subgroup analysis was performed, and the pooled estimate of reported good medication adherence among these patients in regions outside Addis Ababa was 67.81% (95% CI, 59.96%-75.65%), whereas in Addis Ababa it was 70.37% (95% CI, 57.51%-83.23%). Patients who used a glucometer at home had an odds ratio of 2.12 (95% CI, 1.42-3.16) and thus reported good adherence. We found no statistically significant association between the geographic location of a patient's residence and a good level of reported medication adherence (odds ratio, 1.81; 95% CI, 0.78-4.21). CONCLUSIONS: Most adult patients with diabetes in these studies had a good level of reported DM medication adherence. Having a glucometer was significantly associated with reported increased medication adherence. Our findings suggest the need for interventions to improve diabetes medication adherence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.036 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".