Time to Treatment Failure and Its Predictors Among Second-Line ART Clients in Amhara Region, Ethiopia: A Retrospective Follow-Up Study

Background

Second-line antiretroviral treatment failure has become a major public health issue, and the time to treatment failure among second-line ART clients varies globally, and the Sub-Saharan African region having a high rate of second-line ART treatment failures. In addition, after the ART treatment guideline changed there is limited information on Ethiopia. Therefore, this study aimed to assess time to treatment failure and its determinants among second-line ART clients in Amhara Region, Ethiopia.

Methods

A multi-centered retrospective follow-up study was conducted. A random sample of 860 people on second-line ART was selected by using a computer-generated simple random sampling technique from January 30, 2016, to January 30, 2021, at the University of Gondar Compressive Specialized Hospital, Felege Hiwot Compressive Specialized Referral Hospital, and Debre Tabor Compressive Specialized Referral Hospital, in Amhara region, Ethiopia. Data was captured using a checklist.

Results

A total of 81 (9.4%) ART clients developed second-line treatment failure, with a median follow-up time of 29 months with an interquartile range (IQR: 18, 41]. The risk of second-line treatment failure is higher among patients aged 15 to 30 years (adjusted hazard ratio (AHR) = 2.01, 95% confidence interval (CI): [1.16, 3.48]). Being unable to read and write (AHR = 1.312, 95% CI: [1.068, 1.613]), and poor ART drug adherence (AHR = 3.067, 95% CI: [1.845, 5.099]) were significant predictors of second-line ART treatment failures.

Conclusion

In the current study, the time to second-line ART treatment failure was high compared with a previous similar study in Ethiopia. Factors like being younger age, ART clients who are not being able to read and write, and having poor ART drug adherence was significant predictors of second-line ART treatment failure.

Geospatial variation of exclusive breastfeeding and its determinants among mothers of infants under 6 months in Ethiopia: spatial and geographical weighted regression analysis

BACKGROUND

Exclusive breastfeeding (EBF) is a major public health problem in Ethiopia. However, the spatial variation of EBF and the associated factors have not been studied as much as we have searched. This study aimed at assessing geospatial variation and the predictors of EBF using geographically weighted regression.

METHODS

A cross-sectional study was conducted using the 2019 Mini-Ethiopian Demographic and Health Survey data set. The study used a total weighted sample of 548 infants. Hotspot spatial analysis showed the hotspot and cold spot areas of EBF. The spatial distribution of EBF was interpolated for the target population using spatial interpolation analysis. SaTScan V.9.6 software was used to detect significant clusters. Ordinary least squares regression analysis identified significant spatial predictors. In geographically weighted regression analysis, the effect of predictor variables on the spatial variation of EBF was detected using local coefficients.

RESULTS

The weighted prevalence of EBF in Ethiopia was 58.97% (95% CI 52.67% to 64.99%), and its spatial distribution was found to be clustered (global Moran's I=0.56, p<0.001). Significant hotspot areas were located in Amhara, Tigray, Southern Nations, Nationalities, and Peoples' Region, and Somali regions, while significant cold spots were located in Dire Dawa, Addis Ababa and Oromia regions. Kulldorff's SaTScan V.9.6 was used to detect significant clusters of EBF using a 50% maximum cluster size per population. The geographically weighted regression model explained 35.75% of the spatial variation in EBF. The proportions of households with middle wealth index and married women were significant spatial predictors of EBF.

CONCLUSION

Middle wealth index and married women were significant spatial predictors of EBF. Our detailed map of EBF hotspot areas will help policymakers and health programmers encourage the practice of EBF in hotspot areas and set national and regional programmes focused on improving EBF in cold spots by considering significant predictor variables.

Spatial variation and associated factors of inadequate counselling regarding pregnancy danger signs during antenatal care visits among pregnant women in Ethiopia: a Geographically Weighted Regression Model

INTRODUCTION

Inadequate counselling of pregnant women regarding pregnancy danger signs contributes to a delay in deciding to seek care, which causes up to 77% of all maternal deaths in developing countries. However, its spatial variation and region-specific predictors have not been studied in Ethiopia. Hence, the current study aimed to model its predictors using geographically weighted regression analysis.

METHODS

The 2019 Ethiopian Mini Demographic and Health Survey data were used. A total weighted sample of 2922 women from 283 clusters was included in the final analysis. The analysis was performed using ArcGIS Pro, STATA V.14.2 and SaTScan V.10.1 software. The spatial variation of inadequate counselling was examined using hotspot analysis. Ordinary least squares regression was used to identify factors for geographical variations. Geographically weighted regression was used to explore the spatial heterogeneity of selected variables to predict inadequate counselling.

RESULTS

Significant hotspots of inadequate counselling regarding pregnancy danger signs were found in Gambella region, the border between Amhara and Afar regions, Somali region and parts of Oromia region. Antenatal care provided by health extension workers, late first antenatal care initiation and antenatal care follow-up at health centres were spatially varying predictors. The geographically weighted regression model explained about 66% of the variation in the model.

CONCLUSION

Inadequate counselling service regarding pregnancy danger signs in Ethiopia varies across regions and there exists within country inequality in the service provision and utilisation. Prioritisation and extra efforts should be made by concerned actors for those underprivileged areas and communities (as shown in the maps), and health extension workers, as they are found in the study.

Incidence and predictor of diabetic foot ulcer and its association with change in fasting blood sugar among diabetes mellitus patients at referral hospitals in Northwest Ethiopia, 2021

Background

Diabetes mellitus is one of the global public health problems and fasting blood sugar is an important indicator of diabetes management. Uncontrolled diabetes can lead to diabetic foot ulcers, which is a common and disabling complication. The association between fasting blood glucose level and the incidence of diabetic foot ulcers is rarely considered, and knowing its predictors is good for clinical decision-making. Therefore, the aim of this study was to determine the incidence and predictors of diabetic foot ulcers and its association with changes in fasting blood sugar among diabetes mellitus patients at referral hospitals in Northwest Ethiopia.

Methods

A multicenter retrospective follow-up study was conducted at a referral hospital in Northwest Ethiopia. A total of 539 newly diagnosed DM patients who had follow-up from 2010 to 2020 were selected using a computer-generated simple random sampling technique. Data was entered using Epi-Data 4.6 and analyzed in R software version 4.1. A Cox proportional hazard with a linear mixed effect model was jointly modeled and 95% Cl was used to select significant variables. AIC and BIC were used for model comparison.

Result

A total of 539 diabetes patients were followed for a total of 28727.53 person-month observations. Overall, 65 (12.1%) patients developed diabetic foot ulcers with incidence rate of 2.26/1000-person month observation with a 95% CI of [1.77, 2.88]. Being rural (AHR = 2.30, 95%CI: [1.23, 4.29]), being a DM patient with Diabetic Neuropathy (AHR = 2.61, 95%CI: [1.12, 6.06]), and having peripheral arterial disease(PAD) (AHR = 2.96, 95%CI: [1.37, 6.40]) were significant predictors of DFU. The time-dependent lagged value of fasting blood sugar change was significantly associated to the incident of DFU (α = 1.85, AHR = 6.35, 95%CI [2.40, 16.79]).

Conclusion and recommendation

In this study, the incidence of DFU was higher than in previous studies and was influenced by multiple factors like rural residence, having neuropathy, and PAD were significant predictors of the incidence of DFU. In addition, longitudinal changes in fasting blood sugar were associated with an increased risk of DFU. Health professionals and DM patients should give greater attention to the identified risk factors for DFU were recommended.