Geographical variation in hotspots of stunting among under-five children in Ethiopia: A geographically weighted regression and multilevel robust Poisson regression analysis.

INTRODUCTION: Childhood stunting is a global public health concern, associated with both short and long-term consequences, including high child morbidity and mortality, poor development and learning capacity, increased vulnerability for infectious and non-infectious disease. The prevalence of stunting varies significantly throughout Ethiopian regions. Therefore, this study aimed to assess the geographical variation in predictors of stunting among children under the age of five in Ethiopia using 2019 Ethiopian Demographic and Health Survey. METHOD: The current analysis was based on data from the 2019 mini Ethiopian Demographic and Health Survey (EDHS). A total of 5,490 children under the age of five were included in the weighted sample. Descriptive and inferential analysis was done using STATA 17. For the spatial analysis, ArcGIS 10.7 were used. Spatial regression was used to identify the variables associated with stunting hotspots, and adjusted R2 and Corrected Akaike Information Criteria (AICc) were used to compare the models. As the prevalence of stunting was over 10%, a multilevel robust Poisson regression was conducted. In the bivariable analysis, variables having a p-value < 0.2 were considered for the multivariable analysis. In the multivariable multilevel robust Poisson regression analysis, the adjusted prevalence ratio with the 95% confidence interval is presented to show the statistical significance and strength of the association. RESULT: The prevalence of stunting was 33.58% (95%CI: 32.34%, 34.84%) with a clustered geographic pattern (Moran's I = 0.40, p<0.001). significant hotspot areas of stunting were identified in the west and south Afar, Tigray, Amhara and east SNNPR regions. In the local model, no maternal education, poverty, child age 6-23 months and male headed household were predictors associated with spatial variation of stunting among under five children in Ethiopia. In the multivariable multilevel robust Poisson regression the prevalence of stunting among children whose mother's age is >40 (APR = 0.74, 95%CI: 0.55, 0.99). Children whose mother had secondary (APR = 0.74, 95%CI: 0.60, 0.91) and higher (APR = 0.61, 95%CI: 0.44, 0.84) educational status, household wealth status (APR = 0.87, 95%CI: 0.76, 0.99), child aged 6-23 months (APR = 1.87, 95%CI: 1.53, 2.28) were all significantly associated with stunting. CONCLUSION: In Ethiopia, under-five children suffering from stunting have been found to exhibit a spatially clustered pattern. Maternal education, wealth index, birth interval and child age were determining factors of spatial variation of stunting. As a result, a detailed map of stunting hotspots and determinants among children under the age of five aid program planners and decision-makers in designing targeted public health measures.

Multilevel multinomial regression analysis of factors associated with birth weight in sub-Saharan Africa.

Birth weight significantly determines newborns immediate and future health. Globally, the incidence of both low birth weight (LBW) and macrosomia have increased dramatically including sub-Saharan African (SSA) countries. However, there is limited study on the magnitude and associated factors of birth weight in SSA. Thus, thus study investigated factors associated factors of birth weight in SSA using multilevel multinomial logistic regression analysis. The latest demographic and health survey (DHS) data of 36 sub-Saharan African (SSA) countries was used for this study. A total of a weighted sample of 207,548 live births for whom birth weight data were available were used. Multilevel multinomial logistic regression model was fitted to identify factors associated with birth weight. Variables with p-value < 0.2 in the bivariable analysis were considered for the multivariable analysis. In the multivariable multilevel multinomial logistic regression analysis, the adjusted Relative Risk Ratio (aRRR) with the 95% confidence interval (CI) was reported to declare the statistical significance and strength of association. The prevalence of LBW and macrosomia in SSA were 10.44% (95% CI 10.31%, 10.57%) and 8.33% (95% CI 8.21%, 8.45%), respectively. Maternal education level, household wealth status, age, and the number of pregnancies were among the individual-level variables associated with both LBW and macrosomia in the final multilevel multinomial logistic regression analysis. The community-level factors that had a significant association with both macrosomia and LBW were the place of residence and the sub-Saharan African region. The study found a significant association between LBW and distance to the health facility, while macrosomia had a significant association with parity, marital status, and desired pregnancy. In SSA, macrosomia and LBW were found to be major public health issues. Maternal education, household wealth status, age, place of residence, number of pregnancies, distance to the health facility, and parity were found to be significant factors of LBW and macrosomia in this study. Reducing the double burden (low birth weight and macrosomia) and its related short- and long-term effects, therefore, calls for improving mothers' socioeconomic status and expanding access to and availability of health care.

Determinants of normal haemoglobin concentration among under-five children in Sub-Saharan Africa: a Positive deviance inquiry using cross-sectional study design.

BACKGROUND: Low haemoglobin level in children is linked with short-term and long-term consequences including developmental delay. Globally, over half of the children under the age of five years had low haemoglobin concentration. However, there is limited research on the prevalence and determinants of normal haemoglobin concentration among under-five children in sub-Saharan Africa. OBJECTIVE: To assess determinants of normal haemoglobin concentration among under-five children in SSA. DESIGN: Cross-sectional study design using a positive deviance approach SETTING: 33 SSA countries. PARTICIPANTS: 129 408 children aged 6-59 months PRIMARY AND SECONDARY OUTCOME MEASURES: A multilevel Poisson regression model with robust variance was fitted to identify determinants of normal haemoglobin concentration. An adjusted prevalence ratio with a 95% CI was reported to declare the statistical significance. RESULT: The pooled prevalence of normal haemoglobin concentration among under-five children in SSA was 34.9% (95% CI: 34.6% to 35.1%). High maternal education, middle and rich household wealth, female child, frequent antenatal care visits, non-anaemic mothers, taking anthelmintic drugs and normal nutritional status were associated with increased odds of normal haemoglobin concentration. On the other hand, higher birth order, having fever and diarrhoea, rural residence were associated with lower odds of normal haemoglobin levels. CONCLUSION: According to our finding, only four out of 10 under-five children in SSA had a normal haemoglobin level. This finding proved that anaemia among children in SSA remains a serious public health concern. Therefore, improving maternal education, provision of drugs for an intestinal parasite and early detection and treatment of maternal anaemia, febrile illness and diarrhoeal disease is important.

Comprehensive knowledge about HIV/AIDS and associated factors among reproductive age women in Liberia.

INTRODUCTION: Acquired Immune Deficiency Syndrome (AIDS) continues to be a deadly pandemic and a serious threat to public health. Globally, reproductive age women are more likely to be infected with Human Immunodeficiency Virus (HIV). Comprehensive knowledge about HIV/AIDS is pivotal in the fight against AIDS. However, comprehensive HIV/AIDS knowledge is low in Sub-Saharan African (SSA) nations including Liberia, which contributes to the high incidence of HIV in these nations. This study assessed the level of comprehensive knowledge about HIV/AIDS and its associated factors among reproductive age women in Liberia. METHODS: The prevalence and associated factors of comprehensive knowledge about HIV/AIDS among reproductive age women in Liberia were determined using secondary data analysis of 2019-2020 Liberia Demographic and Health Surveys (LDHS). Comprehensive knowledge about HIV/AIDS was a composite variable computed from six variables available in the Demographic and Health Survey (DHS). The study included 7,621 reproductive age women in weighted samples. A generalized linear mixed model with robust error variance was used. For the variables included in the final model, adjusted prevalence ratios (aPR) with 95% confidence intervals (CI) were calculated. RESULTS: The prevalence of comprehensive HIV/AIDS knowledge among Liberian women aged 15-49 was 33.5%. Women's age and education, and distance to health facility were positively associated with comprehensive knowledge about HIV/AIDS among Liberian reproductive age women. In contrast, community poverty level was negatively associated with comprehensive knowledge about HIV/AIDS. CONCLUSION AND RECOMMENDATIONS: This study demonstrates that the prevalence of good comprehensive HIV/AIDS knowledge was relatively low among reproductive age women in Liberia. Hence, health practitioners and policymakers should strengthen HIV/AIDS sensitization programmes to increase women's knowledge about HIV/AIDS.

Prediction of unplanned cesarean section using measurable maternal and fetal characteristics, Ethiopia, a retrospective cohort study.

BACKGROUND: When a pregnant woman experiences unusual circumstances during a vaginal delivery, an unplanned cesarean section may be necessary to save her life. It requires knowledge and quick assessment of the risky situation to decide to perform an unplanned cesarean section, which only occurs in specific obstetric situations. This study aimed to develop and validate a risk prediction model for unplanned cesarean sections among laboring women in Ethiopia. METHOD: A retrospective follow-up study was conducted. The data were extracted using a structured checklist. Analysis was done using STATA version 14 and R version 4.2.2 software. Logistic regression was fitted to determine predictors of unplanned cesarean sections. Significant variables were then used to develop a risk prediction model. Performance was assessed using Area Under the Receiver Operating Curve (AUROC) and calibration plot. Internal validation was performed using the bootstrap technique. The clinical benefit of the model was assessed using decision curve analysis. RESULT: A total of 1,000 laboring women participated in this study; 28.5% were delivered by unplanned cesarean section. Parity, amniotic fluid status, gestational age, prolonged labor, the onset of labor, amount of amniotic fluid, previous mode of delivery, and abruption remained in the reduced multivariable logistic regression and were used to develop a prediction risk score with a total score of 9. The AUROC was 0.82. The optimal cut-off point for risk categorization as low and high was 6, with a sensitivity (85.2%), specificity (90.1%), and accuracy (73.9%). After internal validation, the optimism coefficient was 0.0089. The model was found to have clinical benefits. CONCLUSION: To objectively measure the risk of an unplanned Caesarean section, a risk score model based on measurable maternal and fetal attributes has been developed. The score is simple, easy to use, and repeatable in clinical practice.

Development and validation of a nomogram for predicting low birth weight among pregnant women who had antenatal care visits at Debre Markos Comprehensive and Specialized Hospital, Ethiopia.

Background: Birth weight is a crucial factor linked to a newborn's survival and can also affect their future health, growth, and development. Earlier, researchers focused on exploring maternal and fetal factors contributing to low birth weight. However, in recent years, there has been a shift toward effectively predicting low birth weight by utilizing a combination of variables. This study aims to develop and validate a nomogram for predicting low birth weight in Ethiopia. Methods: A retrospective follow-up study was conducted, and a total of 1,120 pregnant women were included. Client charts were selected using a simple random sampling technique. Data were extracted using a structured checklist prepared on the KoboToolbox (Cambridge, Massachusetts in the United States) and exported to STATA version 14 (Computing Resource Center in California) and R version 4.2.2 (University of Auckland, New Zealand) for data management and analysis. A nomogram was developed based on a binary logistic model, and its performance was assessed by discrimination power and calibration. Internal validation was performed using bootstrapping. To evaluate the clinical impact, decision curve analysis was applied. Results: The nomogram included gestational age, hemoglobin, primigravida, unplanned pregnancy, and preeclampsia. The AUROC of the predicted nomogram was 84.3%, and internal validation was 80.1%. The calibration plot indicated that the nomogram was well calibrated. The model was found to have clinical benefit. Conclusion: The nomogram demonstrates strong discrimination performance and can predict low birth weight clinically. As a result, it can be used in clinical practice, which will help clinicians in making quick and personalized predictions simply and rapidly, enabling the early identification and medical intervention. For broader applicability, the nomogram must be externally validated.

Development and Validation of a Risk Prediction Model to Estimate the Risk of Stroke Among Hypertensive Patients in University of Gondar Comprehensive Specialized Hospital, Gondar, 2012 to 2022.

Background: A risk prediction model to predict the risk of stroke has been developed for hypertensive patients. However, the discriminating power is poor, and the predictors are not easily accessible in low-income countries. Therefore, developing a validated risk prediction model to estimate the risk of stroke could help physicians to choose optimal treatment and precisely estimate the risk of stroke. Objective: This study aims to develop and validate a risk prediction model to estimate the risk of stroke among hypertensive patients at the University of Gondar Comprehensive Specialized Hospital. Methods: A retrospective follow-up study was conducted among 743 hypertensive patients between September 01/2012 and January 31/2022. The participants were selected using a simple random sampling technique. Model performance was evaluated using discrimination, calibration, and Brier scores. Internal validity and clinical utility were evaluated using bootstrapping and a decision curve analysis. Results: Incidence of stroke was 31.4 per 1000 person-years (95% CI: 26.0, 37.7). Combinations of six predictors were selected for model development (sex, residence, baseline diastolic blood pressure, comorbidity, diabetes, and uncontrolled hypertension). In multivariable logistic regression, the discriminatory power of the model was 0.973 (95% CI: 0.959, 0.987). Calibration plot illustrated an overlap between the probabilities of the predicted and actual observed risks after 10,000 times bootstrap re-sampling, with a sensitivity of 92.79%, specificity 93.51%, and accuracy of 93.41%. The decision curve analysis demonstrated that the net benefit of the model was better than other intervention strategies, starting from the initial point. Conclusion: An internally validated, accurate prediction model was developed and visualized in a nomogram. The model is then changed to an offline mobile web-based application to facilitate clinical applicability. The authors recommend that other researchers eternally validate the model.

Geographic weighted regression analysis of hot spots of modern contraceptive utilization and its associated factors in Ethiopia.

BACKGROUND: Utilization of modern contraceptives is a common healthcare challenge in Ethiopia. Prevalence of modern contraception utilization is varying across different regions. Therefore, this study aimed to investigate Geographic weighted regression analysis of hotspots of modern contraceptive utilization and its associated factors in Ethiopia, using Ethiopian Demographic and Health Survey 2016 data. METHODS: Based on the 2016 Ethiopian Demographic Health Survey data, a total weighted sample of 8,673 women was included in this study. For the Geographic Weighted Regression analysis, Arc-GIS version 10.7 and SaTScan version 9.6, statistical software was used. Spatial regression was done to identify factors associated with the hotspots of modern contraceptive utilization and model comparison was carried out using adjusted R2 and AICc. Variables with a p-value < 0.25 in the bi-variable analysis were considered for the multivariable analysis. Multilevel robust Poisson regression analysis was fitted for associated factors since the prevalence of modern contraceptive was >10%. In the multilevel robust Poisson regression analysis, the adjusted prevalence ratio with the 95% confidence interval was reported to declare the statistical significance and strength of association. RESULT: The prevalence of modern contraceptive utilization in Ethiopia was 37.25% (95% CI: 36.23%, 38.27%). Most of the hotspot areas were located in Oromia and Amhara regions, followed by the SNNPR region and Addis Ababa City administration. Single Women, poor Women, and more fertility preference were significant predictors of hotspots areas of modern contraceptive utilization. In the multivariable multilevel robust Poisson regression analysis, Women aged 25-34 years (APR = 0.88, 95% CI: 0.79, 0.98), 35-49 years (APR = 0.71, 95% CI: 0.61, 0.83), married marital status (APR = 2.59, 95% CI: 2.18, 3.08), Others religions (APR = 0.76, 95% CI: 0.65, 0.89), number of children 1-4 (APR = 1.18, 95% CI: 1.02, 1.37), no more fertility preference (APR = 1.21, 95% CI: 1.11, 1.32), Afar, Somali, Harari, and Dire Dawa: (APR = 0.42, 95% CI: 0.27, 0.67), (APR = 0.06, 95% CI: 0.03, 0.12), (APR = 0.78, 95% CI: 0.62, 0.98), and (APR = 0.75, 95% CI: 0.58, 0.98), respectively. Amhara region (APR = 1.34, 95% CI: 1.13, 1.57), rural residence (APR = 0.80, 95% CI: 0.67, 0.95) High community wealth index (APR = 0.78, 95% CI: 0.67, 0.91) were significantly associated with modern contraceptive utilization. CONCLUSION AND RECOMMENDATION: There were significant spatial variations of factors affecting modern contraceptive use across regions in Ethiopia. Therefore, public health interventions targeting areas with low modern contraceptive utilization will help to increase modern contraception use considering significant factors at individual and community levels.The detailed map of modern contraceptive use cold spots among reproductive age group and its predictors could assist program planners and decision-makers to design targeted public health interventions.Government of Ethiopia must develop more geographic targeted strategies for improving socioeconomic status of women and availability & accessibility of health facilities in rural areas of the countries.

Factors associated with short birth interval among reproductive-age women in East Africa.

BACKGROUND: Child and maternal mortality continue as a major public health concern in East African countries. Optimal birth interval is a key strategy to curve the huge burden of maternal, neonatal, infant, and child mortality. To reduce the incidence of adverse pregnancy outcomes, the World Health Organization recommends a minimum of 33 months between two consecutive births. Even though short birth interval is most common in many East African countries, as to our search of literature there is limited study published on factors associated with short birth interval. Therefore, this study investigated factors associated with short birth intervals among women in East Africa. OBJECTIVE: To identify factors associated with short birth intervals among reproductive-age women in East Africa based on the most recent demographic and health survey data. DESIGN: A community-based cross-sectional study was conducted based on the most recent demographic and health survey data of 12 East African countries. A two-stage stratified cluster sampling technique was employed to recruit the study participants. METHODS AND ANALYSIS: A total weighted sample of 105,782 reproductive-age women who had two or more births were included. A multilevel binary logistic regression model was fitted to identify factors associated with short birth interval. Four nested models were fitted and a model with the lowest deviance value (-2log-likelihood ratio) was chosen. In the multivariable multilevel binary logistic regression analysis, the adjusted odds ratio with the 95% confidence interval was reported to declare the statistical significance and strength of association between short birth interval and independent variables. RESULTS: The prevalence of short birth interval in East Africa was 16.99% (95% confidence interval: 16.76%, 17.21%). Women aged 25-34 years, who completed their primary education, and did not perceive the distance to the health facility as a major problem had lower odds of short birth interval. On the contrary, women who belonged to the poorest household, made their own decisions with their husbands/partners or by their husbands or parents alone, lived in households headed by men, had unmet family planning needs, and were multiparous had higher odds of having short birth interval. CONCLUSION: Nearly one-fifth of births in East Africa had short birth interval. Therefore, it is essential to promote family planning coverage, improve maternal education, and empower women to decrease the incidence of short birth intervals and their effects.

Development and validation of a prognosis risk score model for preterm birth among pregnant women who had antenatal care visit, Northwest, Ethiopia, retrospective follow-up study.

BACKGROUND: Prematurity is the leading cause of neonatal morbidity and mortality, specifically in low-resource settings. The majority of prematurity can be prevented if early interventions are implemented for high-risk pregnancies. Developing a prognosis risk score for preterm birth based on easily available predictors could support health professionals as a simple clinical tool in their decision-making. Therefore, the study aims to develop and validate a prognosis risk score model for preterm birth among pregnant women who had antenatal care visit at Debre Markos Comprehensive and Specialized Hospital, Ethiopia. METHODS: A retrospective follow-up study was conducted among a total of 1,132 pregnant women. Client charts were selected using a simple random sampling technique. Data were extracted using structured checklist prepared in the Kobo Toolbox application and exported to STATA version 14 and R version 4.2.2 for data management and analysis. Stepwise backward multivariable analysis was done. A simplified risk prediction model was developed based on a binary logistic model, and the model's performance was assessed by discrimination power and calibration. The internal validity of the model was evaluated by bootstrapping. Decision Curve Analysis was used to determine the clinical impact of the model. RESULT: The incidence of preterm birth was 10.9%. The developed risk score model comprised of six predictors that remained in the reduced multivariable logistic regression, including age < 20, late initiation of antenatal care, unplanned pregnancy, recent pregnancy complications, hemoglobin < 11 mg/dl, and multiparty, for a total score of 17. The discriminatory power of the model was 0.931, and the calibration test was p > 0.05. The optimal cut-off for classifying risks as low or high was 4. At this cut point, the sensitivity, specificity and accuracy is 91.0%, 82.1%, and 83.1%, respectively. It was internally validated and has an optimism of 0.003. The model was found to have clinical benefit. CONCLUSION: The developed risk-score has excellent discrimination performance and clinical benefit. It can be used in the clinical settings by healthcare providers for early detection, timely decision making, and improving care quality.

Population-Modifiable Risk Factors Associated With Childhood Stunting in Sub-Saharan Africa.

Importance: Identifying modifiable risk factors associated with childhood stunting in sub-Saharan Africa (SSA) is imperative for the development of evidence-based interventions and to achieve the Sustainable Development Goals. Objective: To evaluate key modifiable risk factors associated with childhood stunting in SSA. Design, Setting, and Participants: This cross-sectional study examined the most recent (2014-2021) Demographic and Health Surveys data for children younger than 5 years from 25 SSA countries. Exposures: Modifiable risk factors included history of diarrhea within 2 weeks, consumption of dairy products, maternal body mass index, maternal educational level, antenatal care visits, place of birth, wealth index, type of toilet, and type of cooking fuel. Main Outcomes and Measures: Stunting and severe stunting, measured using the height-for-age z score, were the main outcomes. Children who scored below -2.0 SDs or -3.0 SDs were classified as having stunted or severely stunted growth, respectively. Relative risks and 95% CIs were computed using generalized linear latent and mixed models and log-binomial link functions. Population-attributable fractions (PAFs) were calculated using adjusted relative risks and prevalence estimates for key modifiable risk factors. Results: This study included 145 900 children from 25 SSA countries. The mean (SD) age of the children was 29.4 (17.3) months, and 50.6% were male. The highest PAFs of severe childhood stunting were observed for mothers lacking a formal education (PAF, 21.9%; 95% CI, 19.0%-24.8%), children lacking consumption of dairy products (PAF, 20.8%; 95% CI, 16.8%-24.9%), unclean cooking fuel (PAF, 9.5%; 95% CI, 2.6%-16.3%), home birth (PAF, 8.3%; 95% CI, 6.3%-10.0%), and low-income household (PAF, 5.8%; 95% CI, 3.4%-8.0%). These 5 modifiable risk factors were associated with 51.6% (95% CI, 40.5%-60.9%) of the severe childhood stunting in SSA. Conclusions and Relevance: This cross-sectional study identified 5 modifiable risk factors that were associated with 51.6% of severe childhood stunting in SSA. These factors should be a priority for policy makers when considering future child health interventions to address chronic malnutrition in SSA.

Machine Learning Techniques to Predict Timeliness of Care among Lung Cancer Patients.

Delays in the assessment, management, and treatment of lung cancer patients may adversely impact prognosis and survival. This study is the first to use machine learning techniques to predict the quality and timeliness of care among lung cancer patients, utilising data from the Victorian Lung Cancer Registry (VLCR) between 2011 and 2022, in Victoria, Australia. Predictor variables included demographic, clinical, hospital, and geographical socio-economic indices. Machine learning methods such as random forests, k-nearest neighbour, neural networks, and support vector machines were implemented and evaluated using 20% out-of-sample cross validations via the area under the curve (AUC). Optimal model parameters were selected based on 10-fold cross validation. There were 11,602 patients included in the analysis. Evaluated quality indicators included, primarily, overall proportion achieving "time from referral date to diagnosis date ≤ 28 days" and proportion achieving "time from diagnosis date to first treatment date (any intent) ≤ 14 days". Results showed that the support vector machine learning methods performed well, followed by nearest neighbour, based on out-of-sample AUCs of 0.89 (in-sample = 0.99) and 0.85 (in-sample = 0.99) for the first indicator, respectively. These models can be implemented in the registry databases to help healthcare workers identify patients who may not meet these indicators prospectively and enable timely interventions.

Factors associated with mother's healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children in sub-Saharan Africa: a multilevel robust Poisson regression modelling.

BACKGROUND: Timely and appropriate treatment for childhood illness saves the lives of millions of children. In low-middle-income countries such as sub-Saharan Africa (SSA), poor healthcare-seeking behavior for childhood illnesses is identified as a major contributor to the increased risk of child morbidity and mortality. However, studies are limited on Factors associated with mother's healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children in sub-Saharan Africa. OBJECTIVE: To examine factors associated with a mother's healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children in sub-Saharan Africa. METHODS: A secondary data analysis was conducted based on the latest Demographic and Health Survey (DHS) data of 36 sub-Saharan African countries. A total weighted sample of 16,925 mothers who had under-five children with acute respiratory infection symptoms was considered. The Intraclass Correlation Coefficient (ICC), Median Odds Ratio (MOR), and Likelihood Ratio (LR) tests were done to assess the presence of clustering. Model comparison was made based on deviance (-2LLR) value. Variables with a p-value < 0.2 in the bivariable multilevel robust Poisson analysis were considered for the multivariable analysis. In the multivariable multilevel robust Poisson regression analysis, the Adjusted Prevalence Ratio (APR) with the 95% Confidence Interval (CI) was reported to declare the statistical significance and strength of the association. RESULTS: The prevalence of mother's healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children in SSA was 64.9% (95% CI: 64.2%, 65.7%). In the multivariable analysis; mothers who attained primary education (APR = 1.11, 95% CI: 1.08, 1.15), secondary education (APR = 1.13, 95% CI: 1.09, 1.18), and higher education (APR = 1.19, 95% CI: 1.11, 1.27), belonged to the richest household (APR = 1.07: 95% CI: 1.02, 1.12), had media exposure (APR = 1.11, 95% CI: 1.08, 1.15), currently working (APR = 1.08, 95% CI: 1.06, 1.11), had ANC use (APR = 1.25: 95% CI: 1.17, 1.35), health facility delivery (APR = 1.10, 95% CI: 1.07, 1.14), belonged to West Africa (APR = 1.04, 95% CI: 1.01, 1.08) and being in the community with high media exposure (APR = 1.04, 95% CI: 1.02, 1,07) were significantly associated with higher prevalence of mother's healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children. On the other hand, distance to a health facility (APR = 0.87, 95% CI: 0.84, 0.91), and being in central Africa (APR = 0.87, 95% CI: 0.84, 0.91) were significantly associated with a lower prevalence of mother's healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children. CONCLUSION: Mother's healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children. It was influenced by maternal education, maternal working status, media exposure, household wealth status, distance to the health facility, and maternal health care service use. Any interventions aiming at improving maternal education, maternal healthcare services, and media access are critical in improving mothers' healthcare-seeking behavior for symptoms of acute respiratory infection in under-five children, hence lowering the prevalence of ARI-related death and morbidity.

Socio-demographic and antenatal care-related factors associated with early post-partum family planning use in Ethiopia: evidence from Ethiopian Demographic and Health Survey 2016 data.

Introduction: Initiation of family planning in the early post-partum period is a strategic move to reduce maternal, neonatal, and child mortality due to the negative consequences of short interbirth interval and the complications of unintended pregnancy. Antenatal care (ANC) is the noteworthy predictor of scaling up early initiation of post-partum family planning (PPFP) and preventing unintended pregnancy before menses resume. Despite the great role of ANC, information is scant about the effect of content, timing, and the number of ANC visits on the early initiation of PPFP in Ethiopia. Objective: This study aimed to assess the association of ANC services with the early initiation of PPFP in Ethiopia. Methods: The study was based on Ethiopian Demographic and Health Survey 2016 data, which was a cross-sectional survey from 18 January 2016 to 27 June 2016. A total weighted sample size of 2,920 post-partum women was included. A multilevel logistic regression model was used because of the hierarchical data, and variables with a p-value of ≤0.2 in the bivariable multilevel analysis were taken to multivariable multilevel analysis. An adjusted odds ratio with a 95% confidence interval (CI) was used to declare both the direction and strength of the association, and variables with a p-value of <0.05 were considered as statistically significant for the outcome variable. Results: The early initiation of PPFP was 20.4%. Women with at least four ANC visits [adjusted odds ratio (AOR) = 1.31; CI 1.12-2.32], women who started ANC within the first trimester (AOR = 1.25; CI 1.10-2.23), complete routine ANC (AOR = 1.11; CI 1.01-2.03), post-natal care (AOR = 1.45; CI 1.19-1.87), resumption of menses (AOR = 1.67; CI 1.18-1.93), urban residency (AOR = 2.14; CI 1.18-2.51), and high community women's education (AOR = 1.71; CI 1.51-2.11) were variables significantly associated with the early initiation of PPFP. Conclusion: The early initiation of PPFP in Ethiopia was very low. Attention needs to be given to the quality of ANC, post-natal care, resumption of menses, residency, and community-level education of women to increase the prevalence of the early initiation of PPFP in Ethiopia. Therefore, the government should design a program targeting the quality of ANC in rural communities, considering women without menses and scaling up the education of women at the community level to the culture of the early initiation of PPFP in order to achieve reduced maternal, neonatal, and child mortality.

Double burden of malnutrition and its associated factors among women in low and middle income countries: findings from 52 nationally representative data.

BACKGROUND: Double burden of malnutrition (DBM) is an emerging global public health problem. The United Nations member states adopted eradicating all forms of malnutrition as an integral component of the global agenda. However, there is evidence of a high burden of undernutrition among women and rising rates of overweight and obesity, especially in low and middle income countries (LMICs). Therefore, this study aimed to investigate the prevalence and associated factors of underweight, overweight, and obesity among women of reproductive age in LMICs. METHODS: Data for the study were drawn from a recent 52 Demographic and Health Surveys (DHS) conducted in LMICS. We included a sample of 1,099,187 women of reproductive age. A multilevel multinomial logistic regression model was used to identify factors associated with DBM. Adjusted relative risk ratio (RRR) with a 95% Confidence Interval (CI) was reported to show an association. RESULTS: The prevalence of underweight, overweight, and obesity in LMICs among women of reproductive age was 15.2% (95% CI: 15.1-15.3), 19.0% (95% CI: 18.9- 19.1), and 9.1% (95% CI: 9.0-9.2), respectively. This study found that women aged 24-34 years, aged ≥ 35 years, with primary, secondary, and above educational level, from wealthy households, using modern contraceptives, exposed to media (radio and television), and with high parity (more than one birth) were more likely to have overweight and obesity and less likely to have underweight. Moreover, the risk of having obesity (RRR = 0.59; 95% CI = 0.58-0.60 and overweight (RRR = 0.78; 95% CI = 0.77-0.79) were lower among rural women, while the risk of being underweight was (RRR = 1.13; 95% CI = 1.11-1.15) higher among rural women compared to urban women. CONCLUSION: The prevalence of underweight, overweight, and obesity was high among women of reproductive age in LMICs. Underweight, overweight, and obesity are influenced by sociodemographic, socioeconomic, and behavioral-related factors. This study shows that, in order to achieve Sustainable Development Goal 2, a multifaceted intervention approach should be considered to prevent both forms of malnutrition in women of reproductive age. This can be achieved by raising awareness and promoting healthy behaviors such as healthy eating and physical activity, especially among educated women, women from wealthy households, and women exposed to the media.

Intimate partner violence and its associated factors among reproductive-age women in East Africa:-A generalized mixed effect robust poisson regression model.

BACKGROUND: The World Health Organization (WHO) has published estimates revealing that around one out of every three women across the globe has been a victim of either physical and/or sexual violence from an intimate partner or non-partner throughout their lifetime. The available evidence on intimate partner violence in East Africa is limited Consequently, the objective of this study was to evaluate the occurrence and factors linked to intimate partner violence in East Africa. METHODS: The study utilized the most recent data from the Demographic and Health Surveys (DHS) conducted between 2011 and 2018/19 in 11 countries in Eastern Africa. A total of 59,000 women were included in the study. Descriptive and inferential statistics were used to exmine factors associated with IPV. A mixed effect robust Poisson regression model was fitted to identify factors associated with intimate partner violence. The adjusted prevalence ratio (aPR) and its corresponding 95% confidence interval (CI) were employed to determine the presence of a significant association between intimate partner violence and the independent variables. RESULTS: In this study, the prevalence of intimate partner violence in East Africa was 43.72% with 95% CI 43.32% to 44.12%. In the mixed effect robust Poisson regression model:-Marital status, working status, parity, sex of household headed, wealth index, community poverty, and residence, were significantly associated with intimate partner violence. CONCLUSION: The prevalence of intimate partner violence in East Africa is high as compared to the global prevalence 30%, which hinders The Sustainable Development Goals (SDGs), specifically goal 5, aim to attain gender equality and empower women and girls worldwide by the year 2030 Women being previously married and cohabitated, working, having a high number of children, rural residents were positively associated with IPV and household and community wealth index and sex of household headed were negatively related with IPV in East Africa. Therefore, we recommend establishing effective health and legal response using an integrated policy approach and Special attention should be given to women who live rural and poorest to reduce IPV and to achieve Sustainable Development Goals (SDGs) goal 5.

A Systematic Review of Areal Units and Adjacency Used in Bayesian Spatial and Spatio-Temporal Conditional Autoregressive Models in Health Research.

Advancements in Bayesian spatial and spatio-temporal modelling have been observed in recent years. Despite this, there are unresolved issues about the choice of appropriate spatial unit and adjacency matrix in disease mapping. There is limited systematic review evidence on this topic. This review aimed to address these problems. We searched seven databases to find published articles on this topic. A modified quality assessment tool was used to assess the quality of studies. A total of 52 studies were included, of which 26 (50.0%) were on infectious diseases, 10 (19.2%) on chronic diseases, 8 (15.5%) on maternal and child health, and 8 (15.5%) on other health-related outcomes. Only 6 studies reported the reasons for using the specified spatial unit, 8 (15.3%) studies conducted sensitivity analysis for prior selection, and 39 (75%) of the studies used Queen contiguity adjacency. This review highlights existing variation and limitations in the specification of Bayesian spatial and spatio-temporal models used in health research. We found that majority of the studies failed to report the rationale for the choice of spatial units, perform sensitivity analyses on the priors, or evaluate the choice of neighbourhood adjacency, all of which can potentially affect findings in their studies.

An Evaluation of Community Health Workers' Knowledge, Attitude and Personal Lifestyle Behaviour in Non-Communicable Disease Health Promotion and Their Association with Self-Efficacy and NCD-Risk Perception.

Community health workers, also known as health extension workers (HEWs), play an important role in health promotion. This study evaluates HEWs' knowledge, attitude, and self-efficacy for non-communicable diseases (NCD) health promotion. HEWs (n = 203) completed a structured questionnaire on knowledge, attitude, behaviour, self-efficacy and NCD risk perception. Regression analysis was used to determine the association between self-efficacy and NCD risk perception with knowledge (high, medium, low), attitude (favourable/unfavourable) and physical activity (sufficient/insufficient). HEWs with higher self-efficacy were more likely to have high NCD knowledge (AOR: 2.21; 95% CI: 1.21. 4.07), favourable attitude towards NCD health promotion (AOR: 6.27; 95% CI: 3.11. 12.61) and were more physically active (AOR: 2.27; 95% CI: 1.08. 4.74) than those with lower self-efficacy. HEWs with higher NCD susceptibility (AOR: 1.89; 95% CI: 1.04. 3.47) and perceived severity (AOR: 2.69; 95% CI: 1.46, 4.93) had higher odds of NCD knowledge than their counterparts. Moreover, sufficient physical activity was influenced by HEWs' perceived NCD susceptibility and perceived benefits of lifestyle change. Therefore, HEWs need to adopt healthy lifestyle choices to become effective role models for the community. Our findings highlight the need to include a healthy lifestyle when training HEWs, which might increase self-efficacy for NCD health promotion.

A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research.

With the advancement of spatial analysis approaches, methodological research addressing the technical and statistical issues related to joint spatial and spatiotemporal models has increased. Despite the benefits of spatial modelling of several interrelated outcomes simultaneously, there has been no published systematic review on this topic, specifically when such models would be useful. This systematic review therefore aimed at reviewing health research published using joint spatial and spatiotemporal models. A systematic search of published studies that applied joint spatial and spatiotemporal models was performed using six electronic databases without geographic restriction. A search with the developed search terms yielded 4077 studies, from which 43 studies were included for the systematic review, including 15 studies focused on infectious diseases and 11 on cancer. Most of the studies (81.40%) were performed based on the Bayesian framework. Different joint spatial and spatiotemporal models were applied based on the nature of the data, population size, the incidence of outcomes, and assumptions. This review found that when the outcome is rare or the population is small, joint spatial and spatiotemporal models provide better performance by borrowing strength from related health outcomes which have a higher prevalence. A framework for the design, analysis, and reporting of such studies is also needed.

HIV testing among women of reproductive age in 28 sub-Saharan African countries: a multilevel modelling.

BACKGROUND: Human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) remains one of the most significant public health challenges globally, particularly in sub-Saharan Africa (SSA). Although HIV testing is a vital step for both prevention and treatment, its uptake is still low in SSA. We therefore examined HIV testing in SSA and its individual/household and community factors among women of reproductive age groups (15-49 y). METHODS: Demographic and Health Survey data collected between 2010 and 2020 from 28 SSA countries were used for this analysis. We analysed the coverage of HIV testing and individual/household and community factors on 384 416 women in the reproductive age groups (15-49 y). Bivariate and multivariable multilevel binary logistic regression analysis were conducted to select candidate variables and to identify significant explanatory variables associated with HIV testing and the results were presented using adjusted odd ratios (AORs) at 95% confidence intervals (CIs). RESULTS: The pooled prevalence of HIV testing among women of reproductive age in SSA was 56.1% (95% CI 53.7 to 58.4), with the highest coverage found in Zambia (86.9%) and the lowest in Chad (6.1%). Age (45-49 y; AOR 0.30 [95% CI 0.15 to 0.62]), women's education level (secondary; AOR 1.97 [95% CI 1.36 to 2.84]) and economic status (richest; AOR 2.78 [95% CI 1.40 to 5.51]) were some of the individual/household factors associated with HIV testing. Similarly, religion (no religion; AOR 0.58 [95% CI 0.34 to 0.97]), marital status (married; AOR 0.69 [95% CI 0.50 to 0.95]) and comprehensive knowledge of HIV (yes; AOR 2.01 [95% CI 1.53 to 2.64]) were significantly associated individual/household factors for HIV testing. Meanwhile, place of residence (rural; AOR 0.65 [95% CI 0.45 to 0.94]) was found to be a significant community-level factor. CONCLUSION: More than half of married women in SSA have been tested for HIV, with between-country variations. Both individual/household factors were associated with HIV testing. Stakeholders should therefore consider all above-mentioned factors to plan an integrated approach to enhancing HIV testing through health education, sensitization, counselling and empowering older and married women, those with no formal education, those who do not have comprehensive HIV/AIDS knowledge and those in rural areas.