Modeling determinants of time-to-premarital cohabitation among Ethiopian women using parametric shared frailty models.

BACKGROUND: Premarital cohabitation is rampant and currently practiced worldwide, particularly in sub-Saharan Africa. It is a known cause of marital instability and divorce. It is also associated with intimate partner violence and harms the psychology of children in later life. However, in Ethiopia, there has been limited attention given to premarital cohabitation. OBJECTIVE: The main goal of this study was to identify the determinants of time-to-premarital cohabitation among Ethiopian women. METHODS: The 2016 EDHS data was used to achieve the study's goal. The survival information of 15683 women was analyzed based on their age at premarital cohabitation. The regional states of the women were used as a clustering effect in the models. Exponential, Weibull, and Log-logistic baseline models were used to identify factors associated with age at premarital cohabitation utilizing socioeconomic and demographic characteristics. RESULTS: The median age of premarital cohabitation was found to be 18 years. Surprisingly, 72.7% of participants were cohabitated in the study area. According to the Log-logistic-Gamma shared frailty model, place of residence, occupation, educational status, and being pregnant were found to be factors determining the time to premarital cohabitation. CONCLUSION: Premarital cohabitation among Ethiopian women was higher compared to women in the sub-Saharan Africa and East Africa. Place of residence, occupation, educational status, and being pregnant were found to be factors determining the time for premarital cohabitation. Therefore, we recommend the concerned bodies set out strategies to educate women about the influencing factors and dangers of premarital cohabitation.

Modeling Survival Time to Death among Stroke Patients at Jimma University Medical Center, Southwest Ethiopia: A Retrospective Cohort Study.

Background: Stroke is a life-threatening condition that occurs due to impaired blood flow to brain tissues. Every year, about 15 million people worldwide suffer from a stroke, with five million of them suffering from some form of permanent physical disability. Globally, stroke is the second-leading cause of death following ischemic heart disease. It is a public health burden for both developed and developing nations, including Ethiopia. Objectives: This study is aimed at estimating the time to death among stroke patients at Jimma University Medical Center, Southwest Ethiopia. Methods: A facility-based retrospective cohort study was conducted among 432 patients. The data were collected from stroke patients under follow-up at Jimma University Medical Center from January 1, 2016, to January 30, 2019. A log-rank test was used to compare the survival experiences of different categories of patients. The Cox proportional hazard model and the accelerated failure time model were used to analyze the survival analysis of stroke patients using R software. An Akaike's information criterion was used to compare the fitted models. Results: Of the 432 stroke patients followed, 223 (51.6%) experienced the event of death. The median time to death among the patients was 15 days. According to the results of the Weibull accelerated failure time model, the age of patients, atrial fibrillation, alcohol consumption, types of stroke diagnosed, hypertension, and diabetes mellitus were found to be the significant prognostic factors that contribute to shorter survival times among stroke patients. Conclusion: The Weibull accelerated failure time model better described the time to death of the stroke patients' data set than other distributions used in this study. Patients' age, atrial fibrillation, alcohol consumption, being diagnosed with hemorrhagic types of stroke, having hypertension, and having diabetes mellitus were found to be factors shortening survival time to death for stroke patients. Hence, healthcare professionals need to thoroughly follow the patients who pass risk factors. Moreover, patients need to be educated about lifestyle modifications.

Prevalence and associated factors of stunting among under-five children in Ethiopia: Application of marginal models analysis of 2016 Ethiopian demographic and health survey data.

BACKGROUND: Stunting, short for age, affects the overall growth and development of the children. It occurs due to chronic under nutrition. Stunting vastly occurs in impoverished regions of the world, including Ethiopia. OBJECTIVE: This study aimed to investigate the prevalence and correlates of stunting among under-five children in Ethiopia using marginal models. METHODS: Data were taken from the 2016 Ethiopian Demographic Health Survey, which is a nationally representative survey of children in the 0-59 month age group. For marginal models, generalized estimating equations and alternating logistic regression models were used for the analysis. RESULTS: The prevalence of stunting among the under-five children was 34.91% in the area. The proportion was slightly higher among male (36.01%) than female (33.76%) child. The Alternating Logistic Regression model analysis revealed that the child's age, the mother's education level, the mother's body mass index, the place of residence, the wealth index, and the previous birth interval were found to be significant determinants of childhood stunting, and the result shows that children born with a lower previous birth interval (less than 24 months) were more likely to be stunted than those born within a higher birth interval. Children in rural Ethiopia were more likely to be stunted than children in urban Ethiopia. CONCLUSION: This study found that more than one third of children were stunted in the area. The study also determined that child's age, the mother's education, the mother's body mass index, the place of residence, the wealth index, and birth interval influence stunting. Therefore, it is better enhancing the nutritional intervention programs.

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.

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.

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.

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.

Determining factors associated with the prevalence of knowledge, attitude, and practice in seeking skilled maternal healthcare services among women in a remote area of Gesha district.

BACKGROUND: Skilled health care is essential for the mother's and newborn's health and well-being during pregnancy, labor, and the postpartum period. This study aimed to analyze women's knowledge, attitudes, and practices while requesting competent assistance for maternity healthcare in Gesha District, Southwest Region of Ethiopia. METHODS: A community-based cross-sectional study design was conducted from September 20, 2021 to October 19, 2021. A total of 424 mothers participated in this study and a systematic sampling technique was used to select the respondents. The data were collected using a pretested and structured questionnaire. Statistical software SPSS-20 and R-4.1.2 were used to enter and analyze the data respectively. The factors associated with the prevalence of Knowledge, Attitude, and Practice in seeking Skilled Maternal Healthcare Services were identified using descriptive analysis and a binary logistic regression model. RESULTS: This study result revealed that the overall proportions of good knowledge, positive attitude, and good practice in seeking skilled maternal health care services were 39.15%, 37.5%, and 34.67% respectively. Estimated odds of having knowledge, attitude, and practice were as follows: for having age between 20-24 years at first pregnancy 1.859, 1.86, and 1.799; having a plan for pregnancy 2.74,2.315 and 2.579; mothers attended elementary education 2.337, 2.565 and 3.312; having maternal age 20-24 years 4.336,4.989 and 5.870; maternal age 25-29 years 2.917, 3.794 and 4.017; maternal age 35-49 years 2.837, 2.991 and 3.412; having husbands who had attended elementary education level 2.736, 2.542 and 2.134; secondary and above education 3.464, 3.360 and 2.508; rich mothers 2.261, 1.995 and 2.452; having antenatal care 4 times and above 2.606, 2.570, 2.682; having transportation access 1.921, 1.956 and 2.404; having media access 1.979, 2.171 and 2.715 respectively. The odds of having attitude and practice respectively were as follows: married 1.762, and 2.208; having medium wealth index 1.933 and 2.424. The odds of having previous pregnancy complications was 2.147 which significantly affect the practice of seeking skilled maternal care assistance. CONCLUSIONS: This study discovered that the study participants' knowledge, attitude, and practice of skilled maternal health care are low. Associated factors included age at first pregnancy, planned pregnancy, maternal education level, husband's education level, maternal age, antenatal care service visits, transport access, and access to media were found to significantly affect the knowledge, attitude, and practice of the respondents in seeking skilled maternal care assistance in common. The household wealth index was also associated with attitude. Pregnancy complications, current marital status, and household wealth index also significantly affect the practice of seeking skilled maternal care assistance. As a result of the findings, initiatives to increase women's knowledge, attitudes, and use of expert maternal health services in the research area are needed for women residing in rural areas.

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.

Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm.

The drones can be used to detect a group of people who are unmasked and do not maintain social distance. In this paper, a deep learning-enabled drone is designed for mask detection and social distance monitoring. A drone is one of the unmanned systems that can be automated. This system mainly focuses on Industrial Internet of Things (IIoT) monitoring using Raspberry Pi 4. This drone automation system sends alerts to the people via speaker for maintaining the social distance. This system captures images and detects unmasked persons using faster regions with convolutional neural network (faster R-CNN) model. When the system detects unmasked persons, it sends their details to respective authorities and the nearest police station. The built model covers the majority of face detection using different benchmark datasets. OpenCV camera utilizes 24/7 service reports on a daily basis using Raspberry Pi 4 and a faster R-CNN algorithm.

Prevalence and Determinants of Contraceptive Utilization among Women in the Reproductive Age Group in Ethiopia.

INTRODUCTION: Despite the huge advantages of family planning programs, contraception use in Ethiopia remains low. Determining the magnitude and associated factors of contraceptive utilization helps to take action for further improvement. Therefore, this study aimed to assess the prevalence and identify determinants of using contraceptives among women of reproductive age in Ethiopia. METHODS: The 2019 Ethiopian Mini Demographic and Health Survey 2019 (EMDHS 2019) dataset was utilized in this population-based investigation. In the current study, 8885 reproductive-age women were included. Binary logistic regression analysis was employed to examine significant factors associated with the utilization of contraceptive methods. The analysis was done using SPSS software version 20. RESULTS: The prevalence of contraceptive utilization amongst women's reproductive age in Ethiopia was 37.6%. Of all contraceptive users, a large number of women, 57.0%, used injectable kinds of contraceptives followed by implants (24.3%). Participants aged 20-29 (AOR = 2.32, 95%CI: 1.79-3.01) and aged 30-39 years (AOR = 3.12, 95%CI: 2.58-3.78); from Addis Ababa (AOR = 3.27, 95%CI:2.42-4.43), Dire Dawa (AOR = 2.96, 95%CI:2.28-3.84), and urban residence (AOR = 2.49, 95%CI:2.13-2.91); who had secondary education level 1.391(AOR = 1.14-1.70), diploma and above (AOR = 1.39, 95%CI:1.12-1.72); being in rich wealth index (AOR = 1.260, 95%CI:1.06-1.50); having five or more children (AOR = 1.37, 95%CI:1.17-1.61); and who had knowledge about contraceptives (AOR = 1.88, 95%CI:1.42-2.48) and being married (AOR = 5.82, 95%CI: 4.60-7.36) had higher odds of utilizing contraceptives, while women aged 40-49 years (AOR = 0.93, 95%CI: 0.89-0.96) and from residential region of Oromia (AOR = 0.516, 95%CI: 0.40-0.67), Somalia (AOR = 0.48, 95%CI: 0.38-0.62) and Benishangul (AOR = 0.53, 95%CI: 0.40-0.70) had lower odds of using contraception. CONCLUSIONS: The study concluded that the use of contraceptives remained very low (found below the national target) in Ethiopia. Factors like age, educational level, number of children, and region of the women, religion, wealth index, and marital status are determinant factors associated with contraceptive use among reproductive-age women in Ethiopia. For a more successful intervention approach that encourages the use of contraceptive methods, these variables should be considered.

A Case Study on Modeling the Time to Recurrence of Gastric Cancer Patients.

BACKGROUND: Gastric cancer is a malignant tumor of the stomach and it is one of the leading causes of death worldwide. The study aimed to model the time to first recurrence of gastric cancer patients at the Tikur Anbesa specialized hospital. METHODS: The data for this study were gastric cancer patients followed up from January 1, 2013 to February 29, 2020 at Tikur Anbesa Specialized Hospital, Oncology Center, Addis Ababa. We used Weibull, log-logistic and lognormal as baseline hazard functions with the gamma and the inverse Gaussian frailty distributions. Data analyzed with the statistical software R. RESULTS: The median recurrence time of the patients was about 23.96 months with a maximum recurrence time of 60.81 months, of which about 61.2% had first recurrences of gastric cancer. The clustering effect is significant in modeling the time to recurrence of gastric cancer. According to the result of the log-logistic inverse Gaussian frailty model, the sex of the patient, the tumor size, smoking habit, the treatment carried out, the vascular invasion, the stage of the disease, the helicobacter pylori infection and the histological type were the significant prognostic factors  at 5% level of significance. CONCLUSION: Inverse Gaussian frailty model is the model that best describes the time to recurrence of the gastric cancer data set. Gender of the patients, tumor size, treatment taken, vascular invasion, disease stage, helicobacter pylori infection and histological type were the determining prognostic factors. This requires measures to improve patient health and prevent relapse based on significant risk factors, and particular attention should be paid to patients with such factors.