Individual and community level determinants of iron intake among children 6-59 months old in Ethiopia: multilevel logistic regression analysis.

BACKGROUND: Iron deficiency is one of the most important factors of anemia which is caused by poor iron intake. In addition, children need more iron because of their rapid growth. On the other side, daily intake of iron is also recommended as a standard approach for the treatment and prevention of iron deficiency anemia. In Ethiopia, although more than half of children 6-59 months of age were affected by anemia, the magnitude and factors associated with iron intake among them are understudied. Therefore this study aimed to assess the magnitude and community and individual level determinants of iron intake among 6-59 months children in Ethiopia. METHODS: Demographic and Health Survey datasets (EDHS) were used for this study. The data were weighted using sampling weight to get valid statistical estimates. The total weighted samples of 9,218 children aged 6-59 months were included. A multilevel binary logistic regression model was fitted to identify factors associated with iron intake among 6-59 months of children in Ethiopia. In the final model adjusted odds ratio with a 95% confidence interval and p-value < 0.05 was taken to declare statistical significance. RESULTS: The magnitude of iron intake among children 6-59 months in Ethiopia was 9.24% (95% CI: 8.31%, 10.15%). Individual level variables such as having at least one antenatal care visit (ANC) [AOR = 1.27; 95%CI; 1.01, 1.61], having health institution delivery [AOR = 1.46; 95%CI;1.04, 2.04], age of children ≥ 24 months [AOR = 1.82; 95%CI; 1.29, 2.57], being female child [AOR = 0.81; 95%CI; 0.67, 0.99], being greater than three birth order [AOR = 0.73, 95%CI: 0.55, 0.98], whereas community level variables such as living in large central regions [AOR = 3.68; 95%CI; 1.47, 9.21], and living in community with high women education [AOR = 1.96; 95%CI; 1.28, 2.98] have an association with iron supplements among children 6-59 months years old in Ethiopia. CONCLUSION AND RECOMMENDATIONS: The magnitude of iron intake among children 6-59 months old in Ethiopia is relatively low. Individual level factors such as; ANC visit, institution delivery, age of children, sex of the child, and birth order as well as; community level variables such as regions, and community women's education have a significant association with iron intake among children 6-59 months in Ethiopia. Prior attention should be given for under two years old children, children greater than three birth orders, and children living in small peripheral regions. Moreover, policymakers and other stakeholders had better plan and implement programs that empower women, enhance ANC visits, and health institution delivery to have a sustainable increment in iron intake for children in Ethiopia.

Development and validation of a risk prediction model for lost to follow-up among adults on active antiretroviral therapy in Ethiopia: a retrospective follow-up study.

BACKGROUND: Over 420,000 people have initiated life-saving antiretroviral therapy (ART) in Ethiopia; however, lost-to-follow-up (LTFU) rates continues to be high. A clinical decision tool is needed to identify patients at higher risk for LTFU to provide individualized risk prediction to intervention. Therefore, this study aimed to develop and validate a statistical risk prediction tool that predicts the probability of LTFU among adult clients on ART. METHODS: A retrospective follow-up study was conducted among 432 clients on ART in Gondar Town, northwest, Ethiopia. Prognostic determinates included in the analysis were determined by multivariable logistic regression. The area under the receiver operating characteristic (AUROC) and calibration plot were used to assess the model discriminative ability and predictive accuracy, respectively. Individual risk prediction for LTFU was determined using both regression formula and score chart rule. Youden index value was used to determine the cut-point for risk classification. The clinical utility of the model was evaluated using decision curve analysis (DCA). RESULTS: The incidence of LTFU was 11.19 (95% CI 8.95-13.99) per 100-persons years of observation. Potential prognostic determinants for LTFU were rural residence, not using prophylaxis (either cotrimoxazole or Isoniazid or both), patient on appointment spacing model (ASM), poor drug adherence level, normal Body mass index (BMI), and high viral load (viral copies > 1000 copies/ml). The AUROC was 85.9% (95% CI 82.0-89.6) for the prediction model and the risk score was 81.0% (95% CI 76.7-85.3) which was a good discrimination probability. The maximum sensitivity and specificity of the probability of LTFU using the prediction model were 72.07% and 83.49%, respectively. The calibration plot of the model was good (p-value = 0.350). The DCA indicated that the model provides a higher net benefit following patients based on the risk prediction tool. CONCLUSION: The incidence of LTFU among clients on ART in Gondar town was high (> 3%). The risk prediction model presents an accurate and easily applicable prognostic prediction tool for clients on ART. A prospective follow-up study and external validation of the model is warranted before using the model.

Spatial distribution and determinant factors of unmet need for family planning among all reproductive-age women in Ethiopia: a multi-level logistic regression modelling approach.

BACKGROUND: Unmet need for family planning has been remaining high in developing countries than developed countries, notably in sub-Saharan Africa. Data on unmet needs can help countries set service priorities. This study aimed to explore the geographical disparities of unmet need among reproductive-age women in Ethiopia using a 2016 national population-based survey. METHODS: This study was based on the nationally representative 2016 Ethiopian Demographic and Health Survey data. We used a total weighted sample of 15,683 reproductive-aged women. A multi-level logistic regression analysis was used to account for the Demographic Health Survey data's hierarchal nature. In the multivariable multi-level analysis, those variables with a p-value < 0.05 were significantly associated with unmet needs. Spatial autocorrelation techniques were used to explore the clustering tendencies of unmet needss using Getis-Ord Gi* statistics. RESULTS: Overall, 15.2% (95% Confidence Interval (CI): 14.63, 15.76) of women of the reproductive age group in Ethiopia had an unmet need for family planning in 2016. In multivariable multilevel logistic regression analysis; individual-level variables such as being married (Adjusted odds ratio (AOR) = 25.7,95% CI: 11.50,60.42), lowest wealth status (AOR = 1.43,95% CI:1.14,1.79), having five or more children (AOR = 1.98, 95% CI:1.62,2.41), being a follower of Muslim religion (AOR = 1.35,95% CI:1.03,1.76) and protestant religion (AOR = 0.73,95% CI: 0.53,0.99) than orthodox Christian followers were statistically associated factors with unmet need. Among community-level variables; being in rural residency (AOR = 1.37, 95% CI: 1.01, 1.93), belong to the Oromia region (AOR = 1.53, 95%CI: 1.10, 2.11) and Somali region (AOR = 0.37, 95% CI: 0.22, 0.61) were significantly associated unmet need. The spatial analysis of unmet need among all women revealed that Oromia, Southern Nations, and Nationality of People and Gambela regions had high hotspots than other parts of the country. CONCLUSIONS: In this study, the prevalence of unmet needs was high. Significant regional unmet need variation was indicated among reproductive-age women in Ethiopia, specifically in western parts of the country. Wealth status, number of children, marital status, residence, and religion were the most important associated factors with unmet needs. Addressing unmet needs targeted rural residents with low socioeconomic status, and western regions should be given top priority.

In general, the unmet need for family planning has been remaining high in developing countries, notably in sub-Saharan Africa. This study aimed to explore geographical disparities of unmet need for family planning among all reproductive-age women in Ethiopia using a 2016 national population-based survey.We used a secondary data analysis of the 2016 Ethiopian demographic health survey. A total of 15,683 women aged 15­49 years were selected using a two-stage stratified sampling process.Overall, the prevalence of unmet need for family planning was 15.2% (95% CI: 14.63, 15.76) in Ethiopia. The spatial analysis of the unmet need for family planning revealed that Northern and Western parts of Oromia, North of Southern Nations and Nationality of People and Gambela regions had high hotspots than the remaining parts of the country.Generally, the findings indicate significant regional variation in the unmet need for family planning among reproductive-age women in Ethiopia, specifically in western parts of the country. Being in low wealth, having a higher number of living children, being in a Married or union relationship, living in rural areas, older age, being in Muslim and Protestant followers were found associated with unmet need for family planning.

Trends of unmet need for family planning among currently married reproductive age women in Ethiopia: A multivariate decomposition analysis.

INTRODUCTION: Despite decreasing the percentage of women with unmet needs, Ethiopian women still have a higher unmet need for family planning due to different factors. Therefore, addressing the unmet need for FP provides an opportunity for policymakers in all sectors to respond to the expressed fertility preferences of their population. This study aimed to analyze trends and determinants of changes in unmet needs over time among married women of reproductive age in Ethiopia. METHODS: The study used data from three consecutive Demographic and Health Surveys conducted in Ethiopia (2005, 2011, and 2016). These nationally representative household surveys cover all Ethiopia region and city administrations with population health and other relevant indicators). The study included a total weighted sample of 8642 in 2005, 10204 in 2011, and 9824 in 2016 in the final analysis. Factors contributing to the change in unmet need rate were examined using logit-based multivariate decomposition analysis. RESULTS: Among married women, unmet needs declined from 33.8% (95% confidence interval (CI):32.8,34.8) in 2005 to 21.0%(95%CI:20.2,21.9) in 2016. In decomposition analysis, the difference in coefficients was responsible for 90% of the overall change in the unmet need rate. In particular, being at the age of 25-49 years, rural place of residence, agrarian regions, and having more than four children were significant predictors of the increase in unmet need rate. CONCLUSIONS: Unmet needs among women have shown a remarkable decline over the last decade in Ethiopia. Policy and program interventions better targeting younger, agrarian regions and rural dwellers would help to maintain a declining trend in unmet needs.

Spatial distribution and geographical heterogeneity factors associated with poor consumption of foods rich in vitamin A among children age 6-23 months in Ethiopia: Geographical weighted regression analysis.

INTRODUCTION: Vitamin A deficiency is a major public health problem in poor societies. Dietary consumption of foods rich in vitamin A was low in Ethiopia. This study aimed to assess the spatial distribution and spatial determinants of dietary consumption of foods rich in vitamin A among children aged 6-23 months in Ethiopia. METHODS: Ethiopian 2016 demographic and health survey dataset using a total of 3055 children were used to conduct this study. The data were cleaned and weighed by STATA version 14.1 software and Microsoft Excel. Children who consumed foods rich in vitamin A (Egg, Meat, Vegetables, Green leafy vegetables, Fruits, Organ meat, and Fish) at least one food item in the last 24 hours were declared as good consumption. The Bernoulli model was fitted using Kuldorff's SaTScan version 9.6 software. ArcGIS version 10.7 software was used to visualize spatial distributions for poor consumption of foods rich in vitamin A. Geographical weighted regression analysis was employed using MGWR version 2.0 software. A P-value of less than 0.05 was used to declare statistically significant predictors spatially. RESULTS: Overall, 62% (95% CI: 60.56-64.00) of children aged 6-23 months had poor consumption of foods rich in vitamin A in Ethiopia. Poor consumption of foods rich in vitamin A highly clustered in Afar, eastern Tigray, southeast Amhara, and the eastern Somali region of Ethiopia. Spatial scan statistics identified 142 primary spatial clusters located in Afar, the eastern part of Tigray, most of Amhara and some part of the Oromia Regional State of Ethiopia. Children living in the primary cluster were 46% more likely vulnerable to poor consumption of foods rich in vitamin A than those living outside the window (RR = 1.46, LLR = 83.78, P < 0.001). Poor wealth status of the household, rural residence and living tropical area of Ethiopia were spatially significant predictors. CONCLUSION: Overall, the consumption of foods rich in vitamin A was low and spatially non-random in Ethiopia. Poor wealth status of the household, rural residence and living tropical area were spatially significant predictors for the consumption of foods rich in vitamin A in Ethiopia. Policymakers and health planners should intervene in nutrition intervention at the identified hot spot areas to reduce the poor consumption of foods rich in vitamin A among children aged 6-23 months.

Sputum smear grading and associated factors among bacteriologically confirmed pulmonary drug-resistant tuberculosis patients in Ethiopia.

BACKGROUND: The sputum smear bacilliary load is a fundamental indicator of the level of infectiousness in DR-TB patients. However, evidence on DR-TB sputum smear grading and its factors in the study setting is limited. This study was aimed to determine the level of sputum smear grading and associated factors among DR-TB patients in Ethiopia. METHODS: This was an institution based cross-sectional study on 520 bacteriological confirmed pulmonary DR-TB patients from September 2010 to December 2017 in the northwest Ethiopia. Epidata 4.2.00 and SPSS 20 were used for data entry and management, respectively. Ordinary logistic regression was fitted. A cut of p-value less than 0.05 in the multivariable ordinary logistic regression was considered to declare statistically significant variables. RESULTS: Of all 520 bacteriological confirmed pulmonary DR-TB patients; 34.42% had 3+, 15.77% had 2+, 18.27% had 1+, 15.19% had scanty, and 16.35% had negative sputum smear grading results. The odds of having higher sputum smear grades were significantly associated with the patient's educational status of secondary (Adjusted Odds Ratio (AOR) = 0.43, 95% Confidence Interval (CI): 0.21, 0.89), body mass index of 16 to 18.49 kg/m2 (AOR = 1.81, 95%CI: 1.16, 2.84), and TB treatment history of two and more times (AOR = 1.78, 95%CI: 1.24, 2.55). CONCLUSIONS: More than a third of the bacteriological confirmed pulmonary DR-TB patients in the study setting was highly infectious with the highest bacillary load. The odds of having a high bacillary load were significantly associated with the patient's TB treatment history, nutritional, and educational status.