Multilevel analysis of early initiation of breastfeeding in Ethiopia.

Introduction: Breast milk is the ideal food for the infant and is associated with various public health benefits for both the infant and the mother. The recommended time for early initiation of breastfeeding is within one hour after birth. The prevalence of early initiation of breastfeeding was lower than the plan of the Ethiopian Ministry of Health Sector Development program. Thus, the main objective of this study was to identify individual and group-level factors associated with the early initiation of breastfeeding in Ethiopia. Methods: Secondary data on children was obtained from the 2019 Ethiopia mini-demographic and health survey. The survey was a population-based cross-sectional study and was downloaded from the Measure Demographic and Health Survey website (http://www.measuredhs.com). The study included a random sample of 2,125 last-born infants who were born within 24 months before the survey. A multilevel binary logistic regression analysis was employed to identify the factors associated with the early initiation of breastfeeding in Ethiopia. Statistical data was analyzed using the Statistical Analysis System (SAS 9.4). Results: The prevalence of early breastfeeding initiation was 72%. The higher preceding birth interval (AOR = 1.18, 95% CI: 1.1076, 1.5451), the higher gestational age of infants (AOR = 1.38, 95% CI: 1.2796, 1.4782), the higher number of antenatal care visits (AOR = 1.26, 95% CI: 1.2340, 1.2934), delivery at a health facility (AOR = 1.60, 95% CI: 1.4585, 1.7515), vaginal delivery (AOR = 1.11, 95% CI: 1.1019, 1.1123), mothers with primary education (AOR = 1.14, 95% CI: 1.0204, 1.2738), mothers with secondary education (AOR = 1.54, 95% CI: 1.4678, 1.6190), and mothers with higher education (AOR = 2.62, 95% CI: 2.2574, 3.0526) were associated with higher odds of early initiation of breastfeeding. Being a rural dweller (AOR = 0.63, 95% CI: 0.5684, 0.7038) and the age of mothers (AOR = 0.44, 95% CI: 0.3921, 0.4894) were associated with lower odds of early initiation of breastfeeding. Conclusion: Since the prevalence of early initiation of breastfeeding was minimal among rural mothers who delivered their child by caesarean section, this study strongly suggests special supportive care for these mothers.

Multilevel analysis of women's education in Ethiopia.

BACKGROUND: Women's education is the base for faster economic growth, longer life expectancy, lower population growth, improved quality of life, and a high rate of investment return in developing countries. Historically, girls were denied opportunities for schooling in most of the regions and societies of Ethiopia. So this study targeted a multilevel analysis of women's education in Ethiopia using the 2016 Ethiopian Demographic and Health Survey data. METHODS: Secondary data on women's data sets were obtained from the 2016 Ethiopia Demographic and Health Survey. A population-based cross-sectional study design was used for the survey. The sampling technique used for the survey was the two-stage sampling technique, which is stratified in the first stage and equal probability systematic selection technique in the second stage. The multi-level ordinal logistic regression model was fitted to identify the determinants of women's education in Ethiopia. RESULTS: Among the random sample of 17137 women, the majority, 65.6 percent were rural residents. Somali regional state (75.3 percent) and the capital city Addis Ababa (8.6 percent) had the highest and lowest percentages of women illiteracy respectively than the remaining administrative units of Ethiopia. The minimum values for the fit statistics and the indicative value of the intra-class correlation (68.3%) of the multilevel model showed its appropriateness to the data. Among the predictors in the final multilevel ordinal logistic regression analysis, women's age at first marriage, residence, and family's wealth index were significant predictors of women's education in Ethiopia. Moreover, the estimates from the random effect result revealed that there is more variation in women's education between the enumeration areas than within the enumeration areas. CONCLUSION: A multi-level ordinal logistic regression analysis has determined higher-level differences in women's education that could not be addressed by a single-level approach. So, the application of standard models by ignoring this variation ought to embrace spurious results, then for such hierarchical data, multilevel modeling is recommended.

Application of joint modeling on the determinants of TB Status and CD4 cell count among antiretroviral therapy attendants in Gondar teaching referral hospital, Gonder, Ethiopia.

Background: East African regions were highly affected by tuberculosis and the human immunodeficiency virus. The main objective was to identifying the associated factors with tuberculosis and CD4 cell count of patients in Gonder teaching referral hospital, Gonder, Ethiopia. Methods: A retrospective cohort study was conducted on AIDS patients from 1st January 2018 - to 30th January 2020. This study used joint mixed model, and individual profile plot to identify factors and the changeability inside and between patients respectively. Results: The mean with a standard deviation of weight and a serum hemoglobin concentration of patients were 55.48 (10.21) kilograms and 18.25 (33.028) grams per decilitre respectively.This study shows an opportunistic infection, weight, and serum hemoglobin concentration were significantly associated with the log CD4 cell count and tuberculosis status of patients. Conclusion: The patient who has other diseases is 5.04 more likely to be co-infected with HIV and TB diseases. And also, the estimated odds of being co-infected in both diseases were increased by 1.14 and 1.05 times when a unit change in weight and hemoglobin respectively. Moreover, the estimated odd of patients who have no other related disease were 51.13% less likely to be co-infected with both diseases.

Application of two level count regression modeling on the determinants of fertility among married women in Ethiopia.

BACKGROUND: Fertility is the element of population dynamics that has a vital contribution toward changing population size and structure over time. The global population showed a major increment from time to time due to fertility. This increment was higher in south Asia and sub-Saharan Africa including Ethiopia. So this study targeted the factors affecting fertility among married women in Ethiopia through the framework of multilevel count regression analysis using the 2016 Ethiopian Demographic and Health Survey data. METHODS: Secondary data set on the birth records were obtained from the 2016 Ethiopia Demographic and Health Survey. The survey was a population-based cross-sectional study with a two-stage stratified cluster sampling design, where stratification was achieved by separating every region into urban and rural areas except the Addis Ababa region because it is entirely urban. A two-level negative binomial regression model was fitted to spot out the determinants of fertility among married women in Ethiopia. RESULTS: Among the random sample of 6141 women in the country, 27,150 births were recorded based on the 2016 Ethiopian Demographic and Health Survey report. The histograms showed that the data has a positively skewed distribution not extremely picked at the beginning. Findings from the study revealed that the contraception method used, residence, educational level of women, women's age at first birth, and proceeding birth interval were the major predictors of fertility among married women in Ethiopia. Moreover, the estimates from the random effect result revealed that there is more fertility variation between the enumeration areas than within the enumeration areas. CONCLUSION: Unobserved enumeration area fertility differences that cannot be addressed by a single-level approach were determined using a two-level negative binomial regression modeling approach. So, the application of standard models by ignoring this variation ought to embrace spurious results, then for such hierarchical data, multilevel modeling is recommended.

Survival time to complications of congestive heart failure patients at Felege Hiwot comprehensive specialized referral hospital, Bahir Dar, Ethiopia.

BACKGROUNDS: Congestive heart failure is a serious chronic condition when the heart's muscles become too damaged and a condition in which one or both ventricles cannot pump sufficient blood to meet the metabolic needs of the body. This study aimed to identify factors affecting the complications time of congestive heart failure patients treated from January 2016 to December 2019 at Felege Hiwot comprehensive specialized referral hospital in Bahir Dar, Ethiopia. METHODS: A hospital-based retrospective data collection was collected from the medical charts of 218 randomly selected congestive heart failure patients. The Kaplan-Meier curve and the Cox proportional hazards model were used to compare and identify the factors associated with time to complication in patients with congestive heart failure. RESULTS: The median complication time of congestive heart failure patients was 22 months [95% CI: 21.98-28.01]. About 194 (88.99%) of the patients were complicated. The Kaplan-Meier curve depicts the survival probability of complicated patients decreasing as the complication time increases. The hazard ratios for serum sodium concentration, left ventricular ejection fraction, patients from rural areas, age of patients, serum hemoglobin concentration, and New York heart association classes I, II, and III were given 0.94 [95% CI: 0.90-1.00], 0.74 [95% CI: 0.65-0.85], 0.75 [95% CI: 0.68-0.84], 1.28 [95% CI: 1.12-1.46], 0.89 [95% CI: 0.85-0.94], 0.44 [95% CI: 0.36-0.53], 0.54 [95% CI: 0.47-0.62] and 0.73 [95% CI: 0.65-0.81] respectively, and they are statistically associated with the complication time of congestive heart failure patients. CONCLUSIONS: The median complication time of congestive heart failure patients was 22 months. This study strongly suggests that healthcare awareness should be strengthened earlier about the potential complications for patients with lower serum sodium concentrations below the threshold and aged congestive heart failure patients to reduce the risk of developing complications.