Exploring and modeling recurrent birth events in Ethiopia: EMDHS 2019.

BACKGROUND: Globally, the estimated recurrent childbirth of one forth of women happens every two years or fewer. Next to Nigeria, Ethiopia is the second populist country in Africa and the first populist country in sub-Saharan Africa which consists of over 114 million population. There are prevalent short successive birth intervals problems in underdeveloped nations such as Ethiopia that contributes to adverse effects on mother and child health. However, studies that explore recurrent birth events and associated factors are very limited. Thus, this study aimed to explore and model the recurrent birth event by considering its subsequent within a mother and identifying its important determinants. As a result, the research findings of this study will be one of the preliminary research papers on the recurrent birth events that take into account the subsequent event and enable to be input for the policymakers, health institutions, and future researchers. METHODS: A total of 4676 mothers with their 16833 corresponding children were involved in this study. The data was obtained from the 2019 Ethiopian Mini Demographic and Health Survey (EMDHS). In this study, extended cox regression models such as Andersen-Gill (AG), Prentice, Williams, and Peterson total time (PWP-TT) model, PWP-gap time (PWP-GT) model, and Frailty model were employed. These all models are used to consider recurrent events within mothers and determine the potential determinants. AG, PWP-TT, and PWP-GT estimate the effect of covariates by considering the correlation between event times for a person can be explained by past events given the covariates, kth event since the entry time, kth event since the time from the previous event, respectively. RESULTS: Among mothers who have first and ninth recurrent birth events, 75.5% and 80.1% of them respectively were rural residents while 57.6% and 70.6% of them respectively were a place of delivery in the health sector. The highest prevalence of first recurrent births (44.3%) was obtained from Muslim mothers. Mothers' education level (HR: 1.210; 95%CI: 1.010, 1.460), mothers' age at first birth (HR: 0.713; 95% CI: 0.614, 0.828), household wealth index (HR: 0.776; 95% CI: 0.625, 0.965), child mortality (HR: 0.673; 95%CI: 0.514, 0.881), household size (HR: 1.914; 95%CI:1.539,2.381) and sex of child (HR:0.836; 95%CI = 0.755,0.926) were important determinants of recurrent birth event. This indicates mothers' education level and household size were positively associated with recurrent birth events. Whereas mothers' age at first birth, household wealth index, child mortality, and sex of the child was negatively associated with recurrent birth events. CONCLUSION: The WHO recommends a minimum of 33 months between two consecutive births, which is longer than the Ethiopian recurrent birth intervals observed in this study. The highest recurrent birth occurred during the age of fewer than twenty years old of mothers at first birth as compared to mothers whose age was older at first birth. Mothers, children, and household characteristics had significant effects on recurrent birth events. We authors would like to recommend communities, governmental and non-governmental stakeholders consider the associated factors of frequent recurrence of birth noticed in this study. Besides, we would also like to recommend women start birth while they got mature in age to reduce frequent recurrent birth and its corresponding adverse effects.

Space-time dynamics regression models to assess variations of composite index for anthropometric failure across the administrative zones in Ethiopia.

BACKGROUND: A single anthropometric index such as stunting, wasting, or underweight does not show the holistic picture of under-five children's undernutrition status. To alleviate this problem, we adopted a multifaceted single index known as the composite index for anthropometric failure (CIAF). Using this undernutrition index, we investigated the disparities of Ethiopian under-five children's undernutrition status in space and time. METHODS: Data for analysis were extracted from the Ethiopian Demographic and Health Surveys (EDHSs). The space-time dynamics models were formulated to explore the effects of different covariates on undernutrition among children under five in 72 administrative zones in Ethiopia. RESULTS: The general nested spatial-temporal dynamic model with spatial and temporal lags autoregressive components was found to be the most adequate (AIC = -409.33, R2 = 96.01) model. According to the model results, the increase in the percentage of breastfeeding mothers in the zone decreases the CIAF rates of children in the zone. Similarly, the increase in the percentages of parental education, and mothers' nutritional status in the zones decreases the CIAF rate in the zone. On the hand, increased percentages of households with unimproved water access, unimproved sanitation facilities, deprivation of women's autonomy, unemployment of women, and lower wealth index contributed to the increased CIAF rate in the zone. CONCLUSION: The CIAF risk factors are spatially and temporally correlated across 72 administrative zones in Ethiopia. There exist geographical differences in CIAF among the zones, which are influenced by spatial neighborhoods of the zone and temporal lags within the zone. Hence these findings emphasize the need to take the spatial neighborhood and historical/temporal contexts into account when planning CIAF prevention.

Studying latent change process in height growth of children in Ethiopia, India, Peru and Vietnam.

BACKGROUND: Anthropometric measurements of healthy children differ in different parts of the world due to the diverse ethnicity and cultural backgrounds of families. In longitudinal studies, appropriate modeling of repeated anthropometric measures can improve the understanding of patterns of change, determinants of patterns, and variations in patterns of change over time. The objective of this study was to examine the latent change in physical height of children in Ethiopia, India, Peru, and Vietnam. METHOD: Longitudinal data of 6601 children aged 1 to 15 years were obtained from the Young Lives cohort study. The data were analyzed using a latent basis growth curve model. RESULTS: The findings of the study revealed that the rates of growth did not remain constant across the time intervals, which indicates the nonlinearity of the growth trajectory over time. For instance, children had the highest rate of growth between age 1 and 5 years, then between age 8 and 12 years, and a low rate of growth was observed between age 12 and 15 years. At the first measurement occasion (age 1 year) females were 0.826 cm (p < 0.0001) times shorter than males. The mean height at one year of age ranged from 72.13 cm in Ethiopia to 72.62 cm in India. Children in India and Vietnam had higher mean height at age one year. However, no significant difference in mean height at age one year was found between Ethiopian and Peruvian children, ([Formula: see text]). Peruvian and Vietnamese children grew at a faster rate, while Indian children grew at a slower rate than Ethiopian children. CONCLUSION: We found substantial latent growth variations among children in four low- and middle-income countries. The latent trajectories differed by gender and country. The outcomes of the study could aid in detecting inequalities in children's height growth.

Assessing the prevalence and association between physical, emotional, and sexual of intimate partner violence against women in Nigeria.

BACKGROUND: Several studies were carried out on prevalence and associated factors of physical, emotional, and sexual violence against women. However, little attention was given to a comprehensive study that assesses the association between physical, emotional, and sexual violence against women. Thus, this study aimed to assess the association between physical, emotional, and sexual violence against women and their prevalence. METHODS: A retrospective cross-sectional design was implemented based on the 2018 Nigeria Demographic and Health Survey involving 8061 married women aged 15-49. A log-linear statistical model for the three-way table was used to assess the association between emotional, physical, and sexual violence. SAS statistical software was used for data management and parameter estimation. RESULTS: Among a total of 8061 women considered in the study 3022 (37.49%), 4216 (52.3%) and 1186 (14.71%) women have experienced physical, emotional, and sexual violence, respectively. The estimated odds of the interaction between emotional and physical violence (e1.9281 = 6.876); physical and sexual violence (e-2.0529 = 0.128) were significantly differ from 1.0 with p-values < 0:0001 and 0.0201, respectively. CONCLUSION: Over 33 percent of women experienced at least one incident of physical, emotional, or sexual violence in their lifetime. Physical violence against women has a significant association with emotional and sexual violence. However, it does not imply physical violence causes the other violence since cross-sectional data used for the analysis and other factors were not taken into consideration. The lack of a three-way association between emotional, physical, and sexual violence was also perceived. Therefore, as the prevalence of intimate partner violence against women s high, Nigeria as a country needs to strive to reduce it with the collaboration of other nations in the world to achieve Sustainable Development Goal (SDG). Design and apply guidelines to aware of the community about intimate partner violence against women and besides, take appropriate sentencing on those who commit the violence are the better approaches to prevent violence. Traditional habits that might be the cause of violence should be avoided to reduce or prevent the burden of women due to violence.

Even though studies were carried out on physical, emotional, and sexual violence against women, and prevalence and associated factors, little attention was given to a comprehensive study that assesses the association between physical, emotional, and sexual violence against women. As a result, this study aimed to assess the association between physical, emotional, and sexual acts of violence against women in Nigeria. The data was obtained from the 2018 Nigeria Demographic and Health Survey (NDHS). A total of 8061 ever married/cohabited women aged 15­49 years who were residents of the study community for at least 6 months were considered. The log-linear statistical model was used to assess the association between physical, emotional, and sexual violence against women.Of the 8061 women considered in this study, 516(6.40%) have ever been physically forced into unwanted sex by a husband/partner. About 1346 (16.70%) and 1467(18.20%) women have ever been slapped and humiliated by their husbands/partners, respectively. Whereas 3022 (37.49%), 4216 (52.3%), and 1186 (14.71%) women have experienced physical, emotional, and sexual violence, respectively. Four hundred sixty-six women were victims of physical, emotional, and sexual violence. Besides, 40, 755, and 144 women have experienced both physical and sexual violence; emotional and physical violence; and emotional and sexual violence respectively. Physical violence against women has a significant association with emotional and sexual violence. However, it does not imply physical violence causes the other violence since cross-sectional data used for the analysis and other factors were not taken into consideration.

Small Area Estimation of Undernutrition under Age Five Children Based on Spatial-Temporal Models.

The mean flow of direct survey estimates is mainly concerning the sample adequacy fulfillment unless it has been produced large variance estimates, and therefore, the small area estimations are developed to manage this flaw of the path. Small area estimation improved the direct survey estimates by borrowing strength from the census data and at the same time by using historical data from consecutive surveys. In this paper, we applied the spatiotemporal Fay-Herriot (STFH) model for producing fairly reliable disaggregate-level estimates of undernutrition indicators across all zones. The STFH model is an appropriately fitted model to the undernutrition data since it has the lowest information criteria (IC) value. The spatiotemporal estimates improved both the direct and spatial estimates of undernutrition under the FH model and have brought efficiency gain in the percent coefficient of variation (CV). These results may provide useful information to the government's planners, policymakers, and legislative organs for effective policy formulation and budget allocation in all zones.

Spatial data analysis of malnutrition among children under-five years in Ethiopia.

BACKGROUND: Childhood malnutrition is a major cause of child mortality under the age of 5 in the sub-Saharan Africa region. This study sought to identify the risk factors and spatial distribution of the composite index of anthropometric failure (CIAF). METHODS: Secondary data from 2000, 2005, 2011, and 2016 Ethiopian Health and Demographic Survey (EDHS) were used. The generalized geo-additive mixed model was adopted via the Integrated Nested Laplace Approximation (INLA) with a binomial family and logit link function. RESULTS: The CIAF status of children was found to be positively associated with the male gender, the potency of contracting a disease, and multiple births. However, it was negatively associated with family wealth quartiles, parental level of education, place of residence, unemployment status of mothers, improved sanitation, media exposure, and survey years. Moreover, the study revealed significant spatial variations on the level of CIAF among administrative zones. CONCLUSIONS: The generalized geo-additive mixed-effects model results identified gender of the child, presence of comorbidity, size of child at birth, dietary diversity, birth type, place of residence, age of the child, parental level of education, wealth index, sanitation facilities, and media exposure as main drivers of CIAF. The results would help decision-makers to develop and carry out target-oriented programs.

A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones.

BACKGROUND: Undernutrition is the main cause of child death in developing countries. This paper aimed to explore the efficacy of machine learning (ML) approaches in predicting under-five undernutrition in Ethiopian administrative zones and to identify the most important predictors. METHOD: The study employed ML techniques using retrospective cross-sectional survey data from Ethiopia, a national-representative data collected in the year (2000, 2005, 2011, and 2016). We explored six commonly used ML algorithms; Logistic regression, Least Absolute Shrinkage and Selection Operator (L-1 regularization logistic regression), L-2 regularization (Ridge), Elastic net, neural network, and random forest (RF). Sensitivity, specificity, accuracy, and area under the curve were used to evaluate the performance of those models. RESULTS: Based on different performance evaluations, the RF algorithm was selected as the best ML model. In the order of importance; urban-rural settlement, literacy rate of parents, and place of residence were the major determinants of disparities of nutritional status for under-five children among Ethiopian administrative zones. CONCLUSION: Our results showed that the considered machine learning classification algorithms can effectively predict the under-five undernutrition status in Ethiopian administrative zones. Persistent under-five undernutrition status was found in the northern part of Ethiopia. The identification of such high-risk zones could provide useful information to decision-makers trying to reduce child undernutrition.

Spatial regression models to assess variations of composite index for anthropometric failure across the administrative zones in Ethiopia.

BACKGROUND: There are a number of previous studies that investigated undernutrition and its determinants in Ethiopia. However, the national average in the level of undernutrition conceals large variation across administrative zones of Ethiopia. Hence, this study aimed to determine the geographic distribution of composite index for anthropometric failure (CIAF) and identify the influencing factors it' might be more appropriate. METHODS: We used the zonal-level undernutrition data for the under-five children in Ethiopia from the Ethiopian Demographic and Health Survey (EDHS) dataset. Different spatial models were applied to explore the spatial distribution of the CIAF and the covariates. RESULTS: The Univariate Moran's I statistics for CIAF showed spatial heterogeneity of undernutrition in Ethiopian administrative zones. The spatial autocorrelation model (SAC) was the best fit based on the AIC criteria. Results from the SAC model suggested that the CIAF was positively associated with mothers' illiteracy rate (0.61, pvalue 0.001), lower body mass index (0.92, pvalue = 0.023), and maximum temperature (0.2, pvalue = 0.0231) respectively. However, the CIAF was negatively associated with children without any comorbidity (-0.82, pvalue = 0.023), from families with accessibility of improved drinking water (-0.26, pvalue = 0.012), and minimum temperature (-0.16). CONCLUSION: The CIAF across the administrative zones of Ethiopia is spatially clustered. Improving women's education, improving drinking water, and improving child breast feeding can reduce the prevalence of undernutrition (CIAF) across Ethiopian administrative zones. Moreover, targeted intervention in the geographical hotspots of CIAF can reduce the burden of CIAF across the administrative zones.

Correlates of age at first birth among women in Ethiopia: use of multilevel survival analysis models.

Introduction: the timing of birth of the first child has a direct relationship with fertility in general and health and future career including further education of a mother in particular. The objective of this study was to identify factors significantly associated with the time to the first birth among women in Ethiopia. Methods: a cross-sectional study was conducted using data from the 2016 Ethiopian Demographic and Health Survey (EDHS). The study subjects were married women and men aged 15 to 49 in randomly selected households across Ethiopia and two stage stratified random sampling technique was used to select study subjects. Log logistic-Gamma shared frailty model was used to identify factors associated with the length of time spent until the first birth. Results: the median age at first birth for women living in Ethiopia was 20 years, whereas the minimum and maximum ages at first birth were 11 and 49 years respectively. Age at first sex, age at first cohabitation, sex of household head, place of residence, religion, education level, contraceptive use and exposure to media were significant correlates of age at first birth of women in Ethiopia. Higher level of education was associated with increased age at first birth. Women who use contraceptive, women living in urban areas, women having exposure to media and female headed households had longer time to first birth compared to their counterparts. Conclusion: the different regions of Ethiopia have significant differences in the age of women during their first birth. Most of the factors associated with the time to first child in this study were related to education of women. Investing in education and educating women plays critical roles in regulating fertility of a nation and health of women.

Analysis of heterogeneous growth changes in longitudinal height of children.

BACKGROUND: There have been methodologies developed for a wide range of longitudinal data types; nevertheless, the conventional growth study is restricted if individuals in the sample have heterogeneous growth trajectories across time. Using growth mixture modeling approaches, we aimed to investigate group-level heterogeneities in the growth trajectories of children aged 1 to 15 years. METHOD: This longitudinal study examined group-level growth heterogeneities in a sample of 3401 males and 3200 females. Data were analyzed using growth mixture modeling approaches. RESULTS: We examined different trajectories of growth change in children across four low- and middle-income countries using a data-driven growth mixture modeling technique. The study identified two-group trajectories: the most male samples group (n = 4260, 69.7%) and the most female samples group (n = 2341, 81.6%). The findings show that the two groups had different growth trajectories. Gender and country differences were shown to be related to growth factors; however, the association varied depending on the trajectory group. In both latent groups, females tended to have lower growth factors (initial height and rate of growth) than their male counterparts. Compared with children from Ethiopia, children from Peru and Vietnam tended to exhibit faster growth in height over time: In contrast, children from India showed a lower rate of change in both latent groups than that of children from Ethiopia. CONCLUSIONS: The height of children in four low- and middle-income countries showed heterogeneous changes over time with two different groups of growth trajectories.

Latent growth analysis of children's height growth trajectories.

Characterizing and quantifying the trajectories of variables of interest through time in their field of study is of interest to a range of disciplines. The aim of this study was to investigate the growth speed in height of children and its determinants. A total of 3401 males and 3200 females from four low- and middle-income countries with measured height on five occasions from 2002 to 2016 were included in the study. Data were analyzed using a latent growth model. The results of the study reported that children in four low- and middle-income countries exhibited substantial growth inequalities. There was a significant gender difference in change of growth with males had a higher baseline, rate of change, and acceleration in height growth than females. Comparing the component of slopes across countries, the growth change inequalities were observed among children. These inequalities were statistically significant, with the highest rate of change observed in Peru and Vietnam.

Incidence and Predictors of Aspiration Pneumonia Among Stroke Patients in Western Amhara Region, North-West Ethiopia: A Retrospective Follow Up Study.

Background: Aspiration pneumonia is one of the major complications among hospitalized stroke patients, with global incidence ranging from 5-83% and hospital mortality rate of up to 70%. This study aimed to assess the incidence and identify predictors of aspiration pneumonia among stroke patients in Western Amhara region, North-West Ethiopia. Methods: An institution-based retrospective follow-up study was conducted on a simple random sample of 568 stroke patients in Western Amhara region admitted at Felege Hiwot Referral Hospital. Log binomial regression model, a generalized linear model with log link, was applied to identify significant predictors of aspiration pneumonia. Results: Cumulative incidence of aspiration pneumonia among the 568 sampled patients was 23.06%. Males were 1.71 times more at risk to acquire aspiration pneumonia than females (ARR = 1.71, 95% CI 1.07-2.74). Patients with vomiting and dysphagia were at more risk of acquiring aspiration pneumonia as compared with patients without vomiting and dysphagia (ARR = 1.81, 95% CI 1.04-3.14 and ARR = 1.95, 95% CI 1.10-3.48, respectively). Patients who received antibiotic prophylaxis and patients with Glasgow Coma Scale greater than 12 had less risk of acquiring aspiration pneumonia as compared with those who did not receive antibiotic prophylaxis and patients with Glasgow Coma Scale less than 8 (ARR = 0.10, 95% CI 0.04-0.28 and ARR = 0.45, 95% CI 0.22-0.94, respectively). Conclusion: The cumulative incidence of aspiration pneumonia among sampled patients was 23.06%. Vomiting, dysphagia, antibiotic treatment and Glasgow Coma Scale showed significant correlation with the acquiring of aspiration pneumonia. Therefore, we recommend health-care providers should give special attention for patients with these risk factors to prevent aspiration pneumonia.

Seasonal and spatial variations of malaria transmissions in northwest Ethiopia: Evaluating climate and environmental effects using generalized additive model.

The impacts of climate change and environmental predictors on malaria epidemiology remain unclear and not well investigated in the Sub-Sahara African region. This study was aimed to investigate the nonlinear effects of climate and environmental factors on monthly malaria cases in northwest Ethiopia, considering space-time interaction effects. The monthly malaria cases and populations sizes of the 152 districts were obtained from the Amhara public health institute and the central statistical agency of Ethiopia. The climate and environmental data were retrieved from US National Oceanic and Atmospheric Administration. The data were analyzed using a spatiotemporal generalized additive model. The spatial, temporal, and space-time interaction effects had higher contributions in explaining the spatiotemporal distribution of malaria transmissions. Malaria transmission was seasonal, in which a higher number of cases occurred from September to November. The long-term trend of malaria incidence has decreased between 2012 and 2018 and has turned to an increased pattern since 2019. Areas neighborhood to the Abay gorge and Benshangul-Gumuz, South Sudan, and Sudan border have higher spatial effects. Climate and environmental predictors had significant nonlinear effects, in which their effects are not stationary through the ranges of values of variables, and they had a smaller contributions in explaining the variabilities of malaria incidence compared to seasonal, spatial and temporal effects. Effects of climate and environmental predictors were nonlinear and varied across areas, ecology, and landscape of the study sites, which had little contribution to explaining malaria transmission variabilities with an account of space and time dimensions. Hence, exploring and developing an early warning system that predicts the outbreak of malaria transmission would have an essential role in controlling, preventing, and eliminating malaria in areas with lower and higher transmission levels and ultimately lead to the achievement of malaria GTS milestones.

Detection of temporal, spatial and spatiotemporal clustering of malaria incidence in northwest Ethiopia, 2012-2020.

Malaria is one of Ethiopia's most targeted communicable diseases for elimination. Malaria transmission varies significantly across space and time; and Ethiopia had space-time disparity in its transmission intensities. Considering heterogeneity and transmission intensity at the district level could play a crucial role in malaria prevention and elimination. This study aimed to explore temporal, spatial, and spatiotemporal clusters of malaria incidence in northwest Ethiopia. The analysis is based on monthly malaria surveillance data of districts and collected from the Amhara public health institute. The Kulldorff's retrospective space-time scan statistics using a discrete Poisson model were used to detect temporal, spatial, and space-time clusters of malaria incidence with and without adjusting the altitude + LLIN arm. Monthly malaria incidence had seasonal variations, and higher seasonal indices occurred in October and November. The temporal cluster occurred in the higher transmission season between September and December annually. The higher malaria incidence risk occurred between July 2012 and December 2013 (LLR = 414,013.41, RR = 2.54, P < 0.05). The purely spatial clustering result revealed that the most likely cluster occurred in the north and northwest parts of the region while secondary clusters varied in years. The space-time clusters were detected with and without considering altitude + LLIN arm. The most likely space-time cluster was concentrated in northwestern and western parts of the region with a high-risk period between July 2012 and December 2013 (LLR = 880,088.3, RR = 5.5, P < 0.001). We found eight significant space-time clusters using the altitude + LLIN arm. The most likely space-time cluster occurred in the western and northwestern parts of the region in July 2012-December 2013 (LLR = 886,097.7, RR = 5.55, P < 0.05). However, secondary clusters were located in eastern, northwestern, western parts of regions, which had different cases and relative risks in each cluster. Malaria transmission had temporal, spatial, and space-time variation in the region at the district level. Hence, considering these variations and factors contributing to malaria stratification would play an indispensable role in preventing and controlling practices that ultimately leads to malaria eliminations.

Effects of climate variability and environmental factors on the spatiotemporal distribution of malaria incidence in the Amhara national regional state, Ethiopia.

Malaria is a severe public health problem in the Amhara region, Ethiopia. A retrospective study was conducted to model and interpret the effects of climate variability and environmental factors on the monthly malaria surveillance data of 152 districts in the region. The data were analyzed using the Bayesian generalized Poisson spatiotemporal model. Malaria incidence had significant seasonal, temporal, and spatial variations in the region. The risk of malaria incidence was decreased by 24% per 100 m increase in altitude. Monthly minimum temperature decreases the risk of malaria by 2.2% per a 1°C increment. The risk of malaria transmission was increased by 8% per 100 mm rise in the total monthly rainfall of districts. Besides, long-lasting insecticidal net coverage significantly reduces malaria risk by a factor of 0.8955. The finding suggests that malaria transmission was higher in northern and western districts. Hence, concerned bodies should consider seasonal, temporal, and spatial variations and effects of climate and environmental factors for intervention and elimination.

Spatiotemporal Trends and Distributions of Malaria Incidence in the Northwest Ethiopia.

Understanding and extracting noticeable patterns of malaria surveillance data at the district level are crucial for malaria prevention, control, and elimination progress. This study aimed to analyze spatiotemporal trends and nonparametric dynamics of malaria incidences in northwest Ethiopia, considering spatial and temporal correlations. The data were analyzed using count regression spatiotemporal models under the Bayesian setups, and parameters were estimated using integrated nested Laplace approximations (INLA). The region had a declining linear trend, and the average annual malaria incidence rate was 24.8 per 1,000 persons between 2012 and 2020. The malaria incidence rate was decreased by 0.984 (95% CI: 0.983, 0.986) per unit increase in months between July 2012 and June 2020. Districts found in the western and northwestern parts of the region had a steeper trend, while districts in the eastern and southern parts had a less steep trend than the average trend of the region. Compared to the regional level trend, the decreasing rate of malaria incidence trends was lower in most town administrations. The nonparametric dynamics showed that the monthly malaria incidence had a sinusoidal wave shape that varied throughout study periods. Malaria incidence had a decreasing linear trend changed across districts of the study region, and the steepness of trends of districts might not depend on incidences. Thus, an intervention and controlling mechanism that considers malaria incidences and district-specific differential trends would be indispensable to mitigate malaria transmission in the region.

Predictors of blood glucose change and vascular complication of type 2 diabetes mellitus patients in Felege Hiwot Referral Hospital, North West Ethiopia.

Vascular complication results in serious physical damages which may lead to the death of Type 2 diabetes mellitus patients. Studying the determinant factors of changes in blood glucose level and duration of time to the development of vascular complications helps to save the lives of citizens. A retrospective cohort study was conducted among type 2 diabetes mellitus (T2DM) patients enrolled between December 2011 and December 2012 at Felege Hiwot Referral Hospital. A total of 159 T2DM patients were included in the study. Joint modelling of longitudinal and survival analysis was employed to identify predictors of Blood Glucose Change and Vascular Complication of Type 2 Diabetes Mellitus Patients. The prevalence of vascular complication in Type 2 diabetes patients was 23.3%. Half of these patients developed an avascular complication after 24 months from the onset of the follow-up. The significant predictors of shorter time to development of vascular complication were positive proteinuria (adjusted hazard ratio (AHR) = 1.62, CI: 1.08-2.41), increase in the level of serum creatinine (AHR = 4.12, CI: 1.94-8.74), cholesterol ≥ 200 mg/dl (AHR = 1.54, CI: 1.01-2.35), and log (fasting blood glucose) (AHR = 1.453, CI: 1.004-2.104). The predictors of progression of fasting blood glucose were duration of treatment (CL: - 0.015, - 0.0001), hypertension (CL: 0.018, 0.098), baseline fasting blood glucose level 126-139 and 140-199 mg/dl (CI: - 0.40, - 0.31) and (CI: - 0.24, - 0.17), respectively. Male T2DM patients, patients with more visits to the hospital and patients who required one oral agent had a relatively lower progression of blood sugar level. Type 2 diabetes mellitus patients having higher cholesterol level, positive proteinuria, higher fasting blood sugar and a lesser number of hospital visits had a higher risk of developing a complication.

Wealth index and other behavioral and sociodemographic characteristics associated with body mass index in Ethiopia.

BACKGROUND: Nowadays, the burden of non-communicable diseases including obesity has been an increasing public health concern. This menace can be monitored using indexing method like body mass index. Studies indicate that socioeconomic indicators such as income, biology, behavior, and demographic factors associated with body mass index. In Ethiopia, few studies associate wealth index with body mass index in people of ages between 15 and 49. This study was aimed to assess the association of body mass index with wealth index, and behavioral and sociodemographic population characteristics. METHODS: A cross-sectional population-based study was conducted using the 2016 Ethiopian Demographic and Health Survey population of ages 15-49. A total of 10,245 individuals were considered to detect the effect of socioeconomic, biological, behavioral, and demographic factors on body mass index using logistic regression. RESULTS: The prevalence of underweight, overweight, and obesity among men are 23.8%, 6.6%, and 2.0%, respectively, which is lower than that of women (underweight 25.3%, overweight 9.1%, and obesity 2.9%). The poorest men had higher odds of being underweight (adjusted odds ratio = 2.395%; 95% confidence interval = 2.020-3.544) as compared to the richest men. Merchants and government employees have lower odds (adjusted odds ratio = 0.744; 95% confidence interval = 0.588-0.899) compared to men whose occupation is farming and labor, indicating that merchants and government employees are more likely to become overweight and obese compared to men who are farmers and laborers. CONCLUSION: It is concluded that wealth index is an important socioeconomic determinant of body mass index among men and women of age 15-49 in Ethiopia. A high prevalence of underweight, and overweight, and obesity is observed, which increases instances of non-communicable diseases. Effects of socioeconomic, biological, behavioral, and demographic indicators on body mass index differed according to sex.

Disparities in childhood composite index of anthropometric failure prevalence and determinants across Ethiopian administrative zones.

BACKGROUND: The prevalence of under-five children's undernutrition in Ethiopia is among the highest in the world. This study aimed at exploring the prevalence and risk factors of the composite index for anthropometric failure (CIAF) of under-five children in Ethiopia by incorporating the zonal (district) effects. METHODS: The data was drawn from Ethiopian Demographic and Health Surveys (EDHSs), a population-based cross-sectional study of 29,599 under-five year children from 72 Zones in the years 2000, 2005, 2011, and 2016. Fixed effect variables related to child and maternal-household were included in the model. We adopted a generalized mixed model with CIAF as outcome variable and Zones as random effects. RESULTS: The prevalence of CIAF in Ethiopia was 53.78% with the highest prevalence of 61.30% in 2000 and the lowest prevalence of 46.58% in 2016. The model result revealed that being a female child, absence of comorbidity, singleton births, and the first order of birth showed significantly lower CIAF prevalence than their counterparts. Among the household characteristics, children from mothers of underweight body mass index, uneducated parents, poor household sanitation, and rural residents were more likely to be undernourished than their counterparts. Based on the best linear unbiased prediction for the zonal-level random effect, significant variations of CIAF among zones were observed. CONCLUSION: The generalized linear mixed-effects model results identified gender of the child, size of child at birth, dietary diversity, birth type, place of residence, age of the child, parental level of education, wealth index, sanitation facilities, and media exposure as main drivers of CIAF. Disparities of CIAF were observed between and within the Ethiopian administrative Zones over time.

Nonlinear Physical Growth of Children from Infancy to Middle Adolescence in Low- and Middle-Income Countries.

BACKGROUND: The growth curve has a significant role in understanding the growth trajectories over time and examining the mathematical relationship between the outcome variable and time. STUDY DESIGN: A longitudinal prospective cohort study. METHODS: This study aimed to identify a nonlinear growth curve that best represents the growth trajectories in children's physical growth from ages 1 to 15 years. The data were obtained from the Young Lives study conducted in Ethiopia, India, Peru, and Vietnam. Nonlinear growth curves were studied through the families of three-parameter nonlinear mixed-effects models. RESULTS: The study examined the performances of different three-parameter nonlinear growth curves for the growth trajectory analysis, and the Logistic curve was chosen for the trajectory analysis. Gender and country differences had significant effects on the child's growth. Females reached asymptotic height earlier and shorter than males. The mean height values at the end of the growth stage for children in Ethiopia, India, Peru, and Vietnam were 171.78, 170.37, 171.30, 174.31cm, respectively. Children in Ethiopia approached adult height earlier than those in India but later than children in Peru. However, no significant growth change was observed between children in Ethiopia and Vietnam. This indicates that children in Ethiopia and Vietnam have no significant differences regarding approaching adult height. CONCLUSION: The study concludes that the Logistic curve was found to be the best growth curve to describe the growth trajectories. Children in all four countries exhibited different growth parameters.