Multilevel Count Regression Analysis of Factors Associated with the Desired Number of Antenatal Care Service Visits in Ethiopia.

BACKGROUND: Visiting the desired number of antenatal care services improve the success of maternal health programs in terms of mother and child health. The study aimed to identify the factors associated with differences in the number of antenatal care service visits across and within regions of Ethiopia by using the 2019 Ethiopian Mini Demographic Health Survey (EMDHS). METHODS: A total of 3979 women who were pregnant or gave birth within 5 years preceding the survey from the 2019 Ethiopian Mini Demographic Health Survey were included in the analysis. A multi-level Hurdle negative binomial regression model was selected to consider the hierarchical nature of the data in determining the factors associated with the barriers to the desired number of antenatal care service visits. RESULTS: About one-fourth (26.2%) of mothers did not visit any antenatal care, and only 137 (3.4%) women visited the service eight times and above. The random intercept with the fixed coefficient of multilevel Hurdle negative binomial model results has shown that women in the age group between 25 and 34 (AOR = 1.057), in the age group between 35 and 49 (AOR = 1.108), protestant religion follower women (AOR = 0.918), Muslim women (AOR = 0.945), other religion follower women (AOR = 0.768), mothers in primary educational level (AOR = 1.123), secondary and higher education level (AOR = 1.228), rich mothers (AOR = 1.134), and mothers living in rural (AOR = 0.789) were statistically associated with regional variation regarding the frequency of ANC service visits. CONCLUSIONS: The majority of pregnant women did not visit antenatal care services according to the findings of this study. This study's results revealed that the predictor variables such as mother's age, education level, religion, place of residence, marital status, and wealth index were significant, and the findings revealed that there were regional differences in ANC visits in Ethiopia. Women's economic and educational interventions should be a top priority.

Prevalence and associated factors of insomnia symptoms during the COVID-19 pandemic lockdown among Mettu town residents.

BACKGROUND: Insomnia is a prevalent sleep disorder that affects people all over the world. Creating suitable interventions will require a better understanding of the magnitude and determinants of insomnia. This study aimed to assess the prevalence and associated factors of insomnia symptoms among residents of Mettu town during the pandemic lockdown. METHODOLOGY: A community-based cross-sectional study was conducted among residents of Mettu town from October 1st to October 15th, 2020. Residents who lived in Mettu town at least for six months were included. To determine the prevalence and determinants of insomnia symptoms, both descriptive and inferential analyses were used. The chi-squared test of association and logistic regression was used to identify predictors of insomnia symptoms among residents of Mettu town. We used SPSS version 25 for all statistical analyses. PRINCIPAL FINDINGS: The prevalence of depressive symptoms among residents of Mettu town was 52.6%. According to results of multivariable binary logistic regression, being female [AOR = 3.677, 95%CI: 2.124-6.365], being aged between 19 and 40 [AOR = 13.261, 95%CI: 6.953-25.291], being aged above 41 [AOR = 2.627, 95%CI: 1.120-6.159], smoking [AOR = 15.539, 95%CI: 7.961-30.329], satisfaction with information available [AOR = 0.310, 95%CI: 0.168-0.570], fear Corona Virus Disease 2019 (COVID-19), [AOR = 2.171, 95%CI: 1.262-3.733], feeling alienated from others [AOR = 3.288, 95%CI: 1.897-5.699], having somatic symptoms [AOR = 2.298, 95% CI: 1.360-3.884], having depressive symptoms [AOR = 1.841, 95% CI: 1.073-3.160], and experiencing psychological distress [AOR = 1.962, 95% CI: 1.173-3.281] were significantly associated with insomnia symptoms. CONCLUSION: In this study, the prevalence of insomnia symptoms was found to be high among residents of Mettu town. Being female, being aged between 19 and 40, being aged above 41 years, smoking, fear of Corona Virus Disease 2019, feeling alienated from others, having somatic symptoms, having depressive symptoms, and experiencing psychological distress were all associated with an increased risk of developing insomnia symptoms while being satisfied with the information available decreased the risk of insomnia symptoms among residents of Mettu town. Interventions should be put in place to promote healthy sleep among residents of Mettu town.

Depressive symptoms among residents of south Wollo zone in Northern Ethiopia after the liberation of invasion of TPLF led force.

Background: Depressive symptom is the most widely reported mental health consequence of natural or man-made disasters and traumatic events. Research on depressive symptoms in low-income nations is still scarce, although it can be a public health burden in post-conflict situations. Therefore, the primary objective of this study was to identify the prevalence and contributing factors of depressive symptoms among people of south Wollo zones following liberation from TPLF-led army invasions. Methods: A community-based cross-sectional study was conducted on South Wollo zone residents after the liberation of invasions of the TPLF-led force, from May 1st to June 1st, 2022. A self-administered questionnaire was used to collect data from residents chosen using a simple random sampling technique. This study used both descriptive and inferential analysis. To investigate the relationship between response and predictor variables, the chi-squared test of association was performed. The logistic regression was performed to identify predictors of depressive symptoms among residents. Results: The overall prevalence of depressive symptoms among residents was 51.0% [95% C.I: 48.01, 53.99]. Being female [AOR = 1.428, 95% C.I: 1.044-1.955], being an alcohol consumer [AOR = 2.051, 95% C.I: 1.349-3.119], chewing Khat [AOR = 4.617, 95% C.I: 2.873-7.418], history of mental illness [AOR = 4.316, 95% C.I: 1.263-14.751], destruction of personal property [AOR = 2.909, 95% C.I: 2.028-4.175], lacked basic needs such as food and water [AOR = 2.738, 95% C.I: 1.922-3.900], and illness without medical care [AOR = 2.369, 95% C.I: 1.684-3.331] were all found to be statistically significant at the 5% level of significance in a multivariable binary logistic regression. Conclusions: The main finding of this study discovered that residents had a higher prevalence of depressive symptoms following liberation from TPLF-led army invasions. Being an alcoholic, chewing Khat, having a previous history of mental illness, destruction of personal property, lack of food or water, and illness without medical care were associated with an increased risk of developing depressive symptoms. Interventions based on influencing factors should be performed to ensure residents' mental health.

The Prevalence and Predictors of Depressive, Anxiety, and Stress Symptoms Among Tepi Town Residents During the COVID-19 Pandemic Lockdown in Ethiopia.

BACKGROUND: As a result of the coronavirus disease 2019 (COVID-19) outbreak, many countries have imposed movement restrictions and implemented lockdowns. However, evidence from a variety of nations showed that the COVID-19 outbreak and its associated quarantine measures triggered a wide range of psychological problems, such as anxiety, depression, and stress in the general population. As a result, the purpose of this study was to determine the prevalence and predictors of depression, anxiety, and stress symptoms among Tepi town residents during the pandemic lockdown. METHODOLOGY: A community-based cross-sectional survey was conducted among residents of Tepi town from September 15 through September 25, 2020, and residents who have lived in Tepi town for at least 6 months were included. We have employed the depression, anxiety, and stress scale 21 (DASS-21) to evaluate depression, anxiety, and stress. The Chi-squared test of association and logistic regression were used to identify factors associated with depression, anxiety, and stress among residents of Tepi town. For all statistical analysis, we used (IBM) SPSS version 25. RESULTS: According to the current study, the prevalence of depression, anxiety, and stress symptoms were 37.7%, 39.0%, and 44.2%, respectively, among residents of Tepi town. Estimated odds of having depression, anxiety, and stress were as follows: for being female 6.315, 4.591, and 3.155; smoking 1.787, 1.883, and 1.787; sleep problem 2.613, 2.254, and 1.721; chewing Khat 2.156, 2.053, and 2.110; quarantine for 14 days 2.251, 1.902, and 1.960; and frequent use of social media 3.126, 1.849, and 3.126 times more likely as compared to their corresponding reference group respectively. The odds of developing depression and anxiety respectively were as follows: for alcohol consumption 2.438 and 1.797 times higher than their corresponding reference group respectively. Those exposed to COVID-19 were 3.870 times more likely to develop depression symptoms. Estimated odds of having anxiety and stress symptoms for fear of COVID-19 were 1.776 and 1.835; social interactions altered were 3.197 and 2.069, moderate levels of hope were 2.687 and 2.849 respectively. The odds ratio for those taking traditional preventive medicine, and having family members infected with COVID-19 were 2.475 and 1.837 times more likely to experience anxiety symptoms respectively. CONCLUSION: In this study, the prevalence of depression, anxiety, and stress symptoms was found to be high among residences in Tepi town. Being female, chewing Khat, smoking, being quarantined for 14 days, frequently using social media, and having sleeping problems were all found to be significantly associated with an increased risk of developing depression, anxiety, and stress symptoms, whereas alcohol consumption and family members infected by COVID-19 were considerably linked to depression and anxiety symptoms. Fear of COVID-19, influence on social interaction and having a moderate level of hope were substantially related to stress and anxiety symptoms, while taking preventive medicine was found to be a significant factor in anxiety symptoms among Tepi town residences. Interventions should be made to improve the mental health of Tepi residents.

Prevalence and Associated Factors of Depressive Symptoms Among Mizan-Tepi University Students During the COVID-19 Pandemic.

BACKGROUND: Depression is an extremely common and widespread problem among university students. A better understanding of the magnitude and determinants of depressive symptoms is required to create appropriate interventions for those groups. This study aimed to assess the prevalence and predictors of depressive symptoms among Mizan-Tepi University students during the pandemic lockdown. METHODS: From September 11th to September 25th, 2020, 779 Mizan-Tepi University students participated in this web-based cross-sectional study. The link was created with a Google Form, and the questionnaire was distributed to participants via e-mail, WhatsApp, Telegram, and other social media accounts. To determine the prevalence and determinants of depressive symptoms, both descriptive and inferential analyses were used. The chi-squared test of association and logistic regression were used to identify predictors of depressive symptoms among university students. We used (IBM) SPSS version 20 for all statistical analyses. RESULTS: The prevalence of depressive symptoms among university students was 39.5%. According to results of multivariable binary logistic regression, being female (AOR = 0.339, 95%CI: 0.220-0.522), being an alcoholic (AOR = 2.101, 95%CI: 1.452-3.041), smoking (AOR = 2.088, 95%CI: 1.460-2.986), being quarantined for 14 days (AOR = 1.775, 95%CI: 1.231-2.560), frequently using social media (AOR = 1.510, 95%CI: 1.063-2.145), fearing COVID-19 (AOR = 5.058, 95%CI: 3.508-7.292), having sleeping problems (AOR = 1.703, 95%CI: 1.051-2.760), having a family member infected with COVID-19 (AOR = 1.829, 95%CI: 1.211-2.763), being exposed to COVID-19 (AOR = 1.748, 95%CI: 1.114-2.743), monthly disposable income ≥ 501 ETB (AOR = 0.531, 95%CI: 0.359-0.784), having a higher level of hope (AOR = 0.158, 95%CI:0.056-0.447), and having high social support (AOR = 0.546, 95%CI: 0.374-0.797) were significantly associated with depressive symptoms among students. CONCLUSION: In this study, the prevalence of depressive symptoms was found to be high among university students. Being an alcoholic, smoking, quarantined for 14 days, frequently using social media, fearing COVID-19, having sleep problems, having a family member infected with COVID-19, and being exposed to COVID-19 were all associated with an increased risk of developing depressive symptoms, while being a female, having a high level of disposable monthly income, hope, and social support decreased the risk of depressive symptoms among university students. Interventions should be put in place to promote mental health among university students.

Modeling Survival Time to Death Among TB and HIV Co-infected Adult Patients: an Institution-Based Retrospective Cohort Study.

BACKGROUND: Tuberculosis is a serious health threat, particularly for people living with human immunodeficiency virus (HIV), and HIV-positive people are more likely than others to contract the disease. Globally, tuberculosis (TB) is one of the leading causes of death among people living with HIV. The purpose of the current study was to identify factors associated with survival rates of TB/HIV co-infected patients using survival models. METHODS: A retrospective study was conducted on TB/HIV co-infected adult patients registered and under follow-up at Tepi General Hospital (TGH) and Mizan-Tepi University Teaching Hospital (MTUTH), southwest Ethiopia. All TB/HIV co-infection patients who were registered and under follow-up from 1st January 2015 through 1st January 2020 were considered. The global Schoenfeld test was used to test the proportional hazard (PH) assumption. Various accelerated failure time (AFT) models were compared to determine the best model for the time to death of TB/HIV co-infected patients' data set. Among the most commonly used accelerated failure time models (AFT models), the study used exponential, Weibull, log-logistic, and log-lognormal AFT models. AIC and BIC were used to compare the performance of fitted models. The data were analyzed with the statistical software R. RESULTS: Of 363 TB/HIV co-infected patients followed for 60 months, 79 (21.8%) died, while the remaining 284 (78.2%) were censored. The overall median survival time was 15.6 months. The proportional hazard assumption was checked and it was violated. In comparison to other models, the lognormal AFT model performed better. The results of the multivariable lognormal AFT model showed that age, residence, substance use, educational status, clinical stages of the disease, cluster of differentiation 4 (CD4 count/mm3), functional status, cotrimoxazole prophylactic therapy use (CPT use), and INH were all found to be significant factors, while gender, illness other than TB, and disclosure of status were insignificant variables at 5% level of significance. CONCLUSION: Current study results revealed that older age, substance use, advanced WHO clinical stages of the disease (stage IV), bedridden functional status, and CD4 less than 200 count/mm3 were significantly associated with shorter survival time to death of HIV/TB co-infected patients while having advanced educational status, being from urban residence, CPT use, and INH significantly increase the survival time to death of TB/HIV co-infected patients. Patients with TB/HIV co-infection should be given special attention based on these important factors to improve their health and prolong their lives. HIV-positive patients are more likely than others to contract the TB disease. The risk of death among TB/HIV co-infected patients was found to be high. Out of all patients, 79 (21.8%) died. Accelerated failure time models are good alternatives for scenario Cox proportional hazard assumptions not met.

Application of Parametric Shared Frailty Models to Analyze Time-to-Death of Gastric Cancer Patients.

BACKGROUND: Despite its declining incidence, gastric cancer (GC) is one of the world's leading malignancies and a major global health concern due to its high prevalence and fatality rate. Furthermore, it is the world's fourth most common cancer and the second leading cause of cancer death. Studying the determinants of time to death of gastric cancer patients will give clinicians more information to develop specific treatment plans, forecast prognosis, and track the progress of death cases. The application of the frailty model can help account for random variation in survival that may exist due to unobserved factors, as well as show the impact of latent factors on death risk. As a result, the purpose of this study was to assess the determinants of time to death of GC patients' by applying the parametric shared frailty models. METHODS: The data for this study were obtained from gastric cancer patients admitted to the Tikur Anbesa Specialized Hospital, Addis Ababa, from January 1, 2015, to February 29, 2020. With the aim of coming up with an appropriate survival model that determines factors that affect the time to death of gastric cancer patients, various parametric shared frailty models were compared. In all of the frailty models, patient regions were used as a clustering variable. The current study implemented exponential, Weibull, log-logistic, and lognormal distributions for baseline hazard functions with gamma and inverse Gaussian's frailty distributions. The performance of all models was compared using the AIC and BIC criteria. R statistical software was used to conduct the analysis. RESULTS: A retrospective study was undertaken on a total of 407 gastric cancer patients under follow-up at Tikur Anbesa Specialized Hospital. Of all 407 GC patients, 56.3% died while the remaining 43.7% were censored. The patients' median time to death was 21.9 months, with a maximum survival time of 49.6 months. In the current study, the clustering effect was significant in modeling the time to death from gastric cancer. The Weibull model with inverse Gaussian frailty has the minimum AIC and BIC value among the candidate models compared. The dependency within the clusters for the Weibull-inverse Gaussian frailty model was [Formula: see text] (13.4%). According to the results of our best model (Weibull-inverse Gaussian), the sex of the patient, the smoking status, the tumor size, the treatment taken, the vascular invasion, and the disease stage was found to be statistically significant at an alpha = 0.05 significance level. CONCLUSION: Time to death of GC patient's data set was well described by the Weibull-inverse Gaussian shared frailty. Furthermore, Weibull baseline distribution best fits the GC data set as it enables proportional hazard and accelerated failure time model, for time to failure data. There is unobserved heterogeneity between clusters (patient regions), indicating the need to account for this clustering effect. In this study, survival time to death among GC patients was discovered to be small. Covariates like older age, being male, having higher (advanced) stage of GC disease (stage three and stage four), advanced tumor size, being smoker, infected by Helicobacter pylori, and existence of vascular invasion significantly accelerate the time to death of GC patients. In contrast, talking combination of more treatments prolongs the time to death of patients. To improve the health of patients, interventions should be taken based on significant prognostic factors, with special attention dedicated to patients with such factors to prevent GC death.

Survival rate and predictors of mortality among TB/HIV co-infected adult patients: retrospective cohort study.

Nowadays, Tuberculosis remains the major cause of HIV-associated mortality, which accounts for 1 out of every 5 HIV-related mortality worldwide. This study aimed to determine the survival rate and predictors of mortality among TB/HIV co-infected patients. An institution-based retrospective cohort study was undertaken on adult TB/HIV co-infected individuals between 1st February 2014 and 30th January 2022 at Mettu Karl Referral Hospital. A Cox regression model was used to identify predictors of survival time to death among TB/HIV co-infected patients. This study comprised 402 TB and HIV co-infected adult patients. Among these, 84 (20.9%) died, and 318 (79.1%) were censored. The study subjects have been followed up for 6920 person-months with an overall median survival time of 17.6 months. The overall incidence rate was 12.1 per 1000 person months [95% CI: 9.77-14.98]. The results of a multivariable Cox regression analysis showed that being at an older age, urban residence, WHO clinical stage II & IV, CD4 count of ≥ 200 cells/mm3, bedridden functional status, using INH, and using CPT were associated with the survival time of TB and HIV co-infected patients at a significance level of alpha = 0.05. This retrospective study found that high mortality of TB/HIV co-infected patients occurred in the earlier months of treatment initiation. Close monitoring of patients with low CD4, who do not utilize CPT, who are in advanced WHO stages, and who have poor functional levels can help them improve their health and live longer.

Generalized anxiety disorder among mothers attending perinatal services during COVID-19 pandemic: using ordinal logistic regression model.

Background: Generalized anxiety disorder is characterized by excessive and uncontrollable worry about a variety of events. It is critical to ensure a pregnant mother's mental health in order to reduce pregnancy and birth-related problems. The major goal of current study was to identify the factors associated with generalized anxiety disorder among mothers attending perinatal services in the study area during COVID-19 using ordinal logistic regression. Methods: The institution-based cross-sectional study was conducted from July 10th, 2020 to August 10th, 2020 at Kembata Tembaro zone, Southern Ethiopia. The current study included 423 mothers. The GAD-7 scale was used to assess the anxiety level among mothers. An Ordered logit model was used to identify the determinants of GAD. Brant test of the parallel line was utilized to check proportionality assumption. The statistical significance was determined using an adjusted proportional odd ratio with a 95%CI, and a p-value <5%. STATA software version 14 was used to analyze statistical data. Results: Of all 423 mothers attending perinatal service during COVID-19; 134(31.7%), 171(40.4%), 85(20.1%), and 33 (7.8%) had non/minimal to severe generalized anxiety disorder respectively. The results of multivariable proportional odds model (POM) showed that the variables town residents [aPOR = 1.827; 95% CI:1.233-2.708], having alcohol habit [aPOR = 3.437, 95% CI = 1.397-8.454], having occupation [aPOR = 0.509, 95% CI: 0.303-0.857], being health care worker [aPOR = 0.117, 95% CI = 0.044-0.311], having chronic illness [aPOR = 7.685, 95% CI = 3.045-19.39], having family history of anxiety/mood disorder [aPOR = 7.839, 95% CI = 2.656-23.12], fear of contracting COVID-19 [aPOR = 1.704, 95% CI = 1.152-2.521], having moderate social support [aPOR = 0.648, 95% CI = 0.425-0.989], having strong social support [aPOR = 0.495, 95% CI = 0.272-0.901] were significantly associated with generalized anxiety disorder at 5% level of significance. Conclusion: Current findings concluded that the prevalence of GAD among mothers attending perinatal service during COVID-19 was high. The covariates like being town resident, lower-income status, occupation status, having a chronic illness, having a positive family history of anxiety or mood disorder, perceived social support, and fear of the COVID-19 were significantly associated with generalized anxiety disorder among mothers. Mothers who visit perinatal services should be given special consideration to improve health care services and ensure their mental health.

Multilevel analysis of factors associated with utilization of institutional delivery in Ethiopia.

BACKGROUND: The maternal mortality rate in poor nations remains unacceptably high. The purpose of this study was to identify factors associated with institutional delivery usage. METHODS: The data came from the Ethiopian mini demographic and health survey, which was conducted in 2019. This study comprised 3978 women of reproductive age who had given birth within the previous 5 years. To uncover significantly linked parameters associated with institutional delivery, we used a multilevel logistic regression model. Statistical significance was declared at p < 0.05, and we assessed the strength of association using adjusted odds ratios with 95% confidence intervals. RESULTS: More than half of the women (53.67%) among 3978 women with last birth had their babies delivered in a health facility. In the multilevel logistic regression analysis, women in age group 45-49 (AOR = 2.43, 95% CI: 1.280, 4.591), primary educational level (AOR = 2.21, 95% CI: 1.864, 2.625, secondary and above education level (AOR = 6.37, 95% CI: 4.600, 8.837), being Muslim (AOR = 2.57, 95% CI: 1.245, 2.166), women who visited ANC service four up to seven times (AOR = 2.75, 95% CI: 2.175, 3.473), women visited ANC service eight times and above (AOR = 3.295% CI: 1.685, 6.050), women who reside in middle wealth index (AOR = 1.57, 95% CI: 1.273, 1.950), and rich wealth index (AOR = 3.43, 95% CI: 2.782, 4.225) were more likely to give birth at health institution compared to their counterparts. Furthermore, women being in rural area (AOR = 0.34, 95% CI:- 0.283, 0.474) and protestant women (AOR = 0.1.57, 95% CI: 0.479, 0.852) were less likely to deliver at health institution. CONCLUSIONS: Ethiopia still has a low level of institutionalized delivery. Institutional delivery in Ethiopia should be improved through context-specific and personalized programs, such as educating women and enhancing access to ANC services.

Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia.

BACKGROUND: Socioeconomic status (SES) refers to an individual's or group's social position or class, which is often determined by a combination of education, income, and occupation. Knowing factors that affect the SES of the society might help to take action and improve their economy. In addition, using an ordinal logistic regression model for ordered SES outcomes will yield suitable results and conclusions. This study aimed to utilize an ordinal logistic regression model to find the factors associated with SES for households in Tepi town, Southwest Ethiopia. METHODS: The community-based cross-sectional study was carried out in Tepi town, southwest Ethiopia, with data collected from 382 households using a simple random sample technique. The ordinal logistic regression models were evaluated and contrasted for proper accounting of ordinal form. In addition, to come up with a better model, we compared fitted ordinal logistic models with the likelihood-ratio test and AIC criteria. We performed data analysis using STATA version 16. RESULTS: Of all 382 household heads, 170 (45.5%), 120 (31.4%), and 92 (24.1%) were at low, medium, and high SES of households, respectively. According to the result of the multivariable, partial proportional odds model (PPOM), age, education level, family size, and the saving habit were significantly associated with the SES of households at a 5% level of significance. CONCLUSIONS: According to the findings of this study, ordinal regression may be a better option in the event of the ordinal form of the outcome. Furthermore, PPOM may be a preferable option if any of the covariates violate the proportionality requirement. Based on the result of this study, the most likely associated indicators with the SES of families in Tepi town, southwest Ethiopia, were family size, age, saving habit, and education level. It is recommended that action should be taken to improve the SES of households.