scholarly journals Using geographically weighted regression analysis to cluster under-nutrition and its predictors among under-five children in Ethiopia: Evidence from demographic and health survey

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0248156
Author(s):  
Amare Muche ◽  
Mequannent Sharew Melaku ◽  
Erkihun Tadesse Amsalu ◽  
Metadel Adane
Keyword(s):  
Geographically Weighted Regression ◽  
Hot Spot ◽  
Least Square ◽  
Weighted Regression ◽  
Amhara Region ◽  
Under Five ◽  
Under Five Children ◽  
Tigray Region ◽  
Under Nutrition ◽  
Afar Region

Background Malnutrition among under-five children is a common public health problem and it is one of the main cause for the mortality of under-five children in developing countries, including Ethiopia. Therefore, lack of evidence about geographic heterogeneity and predictors of under-nutrition hinders for evidence-based decision-making process for the prevention and control programs of under-nutrition in Ethiopia. Thus, this study aimed to address this gap. Methods The data were obtained from the Ethiopian Demographic and Health Survey (EDHS) 2016. A total of 9,384 under-five children nested in 645 clusters were included with a stratified two-stage cluster sampling. ArcGIS version 10.5 software was used for global, local and ordinary least square analysis and mapping. The spatial autocorrelation (Global Moran’s I) statistic was held in order to assess the pattern of wasting, stunting, and underweight whether it was dispersed, clustered, or randomly distributed. In addition, a Bernoulli model was used to analyze the purely spatial cluster detection of under-nutrition indicators through SaTScan version 9.6 software. Geographically weighted regression (GWR) version 4.0 software was used to model spatial relationships in the GWR analysis. Finally, a statistical decision was made at p-value<0.05 with 95%CI for ordinary least square analysis and geographically weighted regression. Main findings Childhood under-nutrition showed geographical variations at zonal levels in Ethiopia. Accordingly, Somali region (Afder, Gode, Korahe, Warder Zones), Afar region (Zone 2), Tigray region (Southern Zone), and Amhara region (Waghmira Zones) for wasting, Amhara region (West Gojam, Awi, South Gondar, and Waghmira Zones) for stunting and Amhara region (South Wollo, North Wollo, Awi, South Gondar, and Waghmira zones), Afar region (Zone 2), Tigray region (Eastern Zone, North Western Zone, Central Zone, Southern Zone, and Mekele Special Zones), and Benshangul region (Metekel and Assosa Zones) for underweight were detected as hot spot (high risk) regions. In GWR analysis, had unimproved toilet facility for stunting, wasting and underweight, father had primary education for stunting and wasting, father had secondary education for stunting and underweight, mothers age 35–49 years for wasting and underweight, having female children for stunting, having children eight and above for wasting, and mother had primary education for underweight were significant predictors at (p<0.001). Conclusions Our study showed that the spatial distribution of under-nutrition was clustered and high-risk areas were identified in all forms of under-nutrition indicators. Predictors of under-nutrition were identified in all forms of under-nutrition indicators. Thus, geographic-based nutritional interventions mainly mobilizing additional resources could be held to reduce the burden of childhood under-nutrition in hot spot areas. In addition, improving sanitation and hygiene practice, improving the life style of the community, and promotion of parent education in the identified hot spot zones for under-nutrition should be more emphasized.

scholarly journals Prevalence and Determinants of Under-Nutrition Among Under-Five Children in Afar Region, Ethiopia: Evidence From 2016 Ethiopian Demographic and Health Survey

2022 ◽  
Author(s):  
Damitie Kebede Mengesha ◽  
Demewez Moges Haile
Keyword(s):  
Public Health ◽  
Health Survey ◽  
Household Wealth ◽  
Demographic And Health Survey ◽  
Binary Logistic Regression Analysis ◽  
Health Concerns ◽  
Under Five ◽  
Under Five Children ◽  
Under Nutrition ◽  
Afar Region

Abstract Background: Undernutrition is one of the major public health concerns among infants and young children in the country. Childhood under-nutrition is widespread in low and middle-income countries. This study was initiated to assess the prevalence of under-nutrition and its associated factors among under-five children in Afar Region, Ethiopia. Methods: The data for this study were extracted from the Ethiopian Demographic and Health Survey (EDHS) 2016. The information collected from 937 children born 5 years before the survey was considered in the analysis. A multivariable binary logistic regression analysis was used at a 5% level of significance to determine the individual- and community-level factors associated with childhood malnutrition.Results: The prevalence of stunting, underweight and wasting in Afar region were 41.1%, 36.2% and 17.7%, respectively. About 26.7% of children in Afar region were both stunting and underweight, 12.7% were both underweight and wasting, 7.6% were both stunting and wasting and only 7.0% of children had all the three under-nutrition conditions. Among the factors considered in this study, age of a child in months, anemia level, mothers’ BMI, household wealth index, size of child at birth, number of living children and place of residence were significantly associated with stunting, underweight and wasting in Afar Region. Conclusions: The prevalence of all stunting, underweight and wasting was relatively high. Undernutrition is one of the major public health concerns among children in Afar Region. The effect of these factors should be considered to develop strategies to reduce under-nutrition in the study area. Thus, intervention should be focused on improving the under-nutrition determinants of the children to improve the child's nutritional status and reduce child morbidity and mortality.

Second-hand housing batch evaluation model of zhengzhou city based on big data and MGWR model

2021 ◽  
pp. 1-20
Author(s):  
Chaojie Liu ◽  
Jie Lu ◽  
Wenjing Fu ◽  
Zhuoyi Zhou
Keyword(s):  
Real Estate ◽  
Geographically Weighted Regression ◽  
Euclidean Distance ◽  
Evaluation Model ◽  
Housing Prices ◽  
Information Criterion ◽  
Access Point ◽  
Least Square ◽  
Weighted Regression ◽  
Spatial Error

How to better evaluate the value of urban real estate is a major issue in the reform of real estate tax system. So the establishment of an accurate and efficient housing batch evaluation model is crucial in evaluating the value of housing. In this paper the second-hand housing transaction data of Zhengzhou City from 2010 to 2019 was used to model housing prices and explanatory variables by using models of Ordinary Least Square (OLS), Spatial Error Model (SEM), Geographically Weighted Regression (GWR), Geographically and Temporally Weighted Regression (GTWR), and Multiscale Geographically Weighted Regression (MGWR). And a correction method of Barrier Line and Access Point (BLAAP) was constructed, and compared with three correction methods previously studied: Buffer Area (BA), Euclidean Distance (ED), and Non-Euclidean Distance, Travel Distance (ND, TT). The results showed: The fitting degree of GWR, MGWR and GTWR by BLAAP was 0.03–0.07 higher than by ND. The fitting degree of MGWR was the highest (0.883) by BLAAP but the smallest by Akaike Information Criterion (AIC), and 88.3% of second-hand housing data could be well interpreted by the model.

scholarly journals Parameter estimation of geographically weighted regression (GWR) model using weighted least square and its application

2018 ◽  
Author(s):  
Saskya Mary Soemartojo ◽  
Rima Dini Ghaisani ◽  
Titin Siswantining ◽  
Mariam Rahmania Shahab ◽  
Moch. Muchid Ariyanto
Keyword(s):  
Parameter Estimation ◽  
Geographically Weighted Regression ◽  
Least Square ◽  
Weighted Regression ◽  
Weighted Least Square ◽  
Gwr Model

scholarly journals Estimation of Error Variance-Covariance Parameters Using Multivariate Geographically Weighted Regression Model

2020 ◽  
Vol 2020 ◽  
pp. 1-5 ◽  
Author(s):  
Sri Harini
Keyword(s):  
Statistical Inference ◽  
Geographically Weighted Regression ◽  
Weighting Function ◽  
Likelihood Estimation ◽  
Error Variance ◽  
Least Square ◽  
Weighted Regression ◽  
Inference Procedure ◽  
Geographically Weighted Regression Model ◽  
Estimated Error

The Multivariate Geographically Weighted Regression (MGWR) model is a development of the Geographically Weighted Regression (GWR) model that takes into account spatial heterogeneity and autocorrelation error factors that are localized at each observation location. The MGWR model is assumed to be an error vector ε that distributed as a multivariate normally with zero vector mean and variance-covariance matrix Σ at each location ui,vi, which Σ is sized qxq for samples at the i-location. In this study, the estimated error variance-covariance parameters is obtained from the MGWR model using Maximum Likelihood Estimation (MLE) and Weighted Least Square (WLS) methods. The selection of the WLS method is based on the weighting function measured from the standard deviation of the distance vector between one observation location and another observation location. This test uses a statistical inference procedure by reducing the MGWR model equation so that the estimated error variance-covariance parameters meet the characteristics of unbiased. This study also provides researchers with an understanding of statistical inference procedures.

scholarly journals Nutritional status of under- five children in a city of Maharashtra: a community based study

2017 ◽  
Vol 4 (4) ◽  
pp. 1171 ◽  
Author(s):  
Laxmikant Purohit ◽  
Priyanka Sahu ◽  
Lata B. Godale
Keyword(s):  
Socioeconomic Status ◽  
Birth Weight ◽  
Birth Order ◽  
Maternal Education ◽  
Sampling Technique ◽  
Community Based ◽  
Cross Sectional ◽  
Under Five ◽  
Under Five Children ◽  
Under Nutrition

Background: Children are considered to be the backbone of any nation. Nutritional problems among children cause major morbidity and mortality in India. India is home to the largest number of underweight and stunted children in the world. Aim and objectives: 1) To assess prevalence of underweight, stunting and wasting among under-five children 2) To study factors associated with underweight, stunting and wasting among under-five childrenMethods: It was community based descriptive cross sectional study conducted during January 2010 to December 2011 at Urban Health Center of the Department of Preventive and Social Medicine catering approximately 27000 populations. 650 under- fives residing in urban field practice area were included in the study with the help of Stratified random sampling technique. Data was analyzed using SPSS software 16 version and OpenEpi Software Version 2.3.Results: 40.46% under five children were stunted, 38.15% were underweight, and 16% were wasted. The difference observed between stunted and normal study subjects with reference to type of family, education of mother, birth weight and birth order were statistically significant. The proportion of under- five children with underweight showed significant association with their age, socioeconomic status, education mother, birth weight and birth order. Proportion of under-five children with SAM and MAM decreased significantly with increase in education status of mother. Significantly higher proportion of under-five children with birth weight less than 2.5 kg and higher birth order were grouped as SAM and MAM.Conclusions: Maternal education, birth weight and birth order of children were significantly associated with all three types of under nutrition i.e. underweight, stunting and wasting. Proportion of children with underweight increases significantly with increase in age and decrease in socioeconomic status. There was no religion wise or gender wise variation in proportion of children with under nutrition was reported among study subjects.

scholarly journals Tracking Progress in Anthropometric Failure Among Under-five Children in Ethiopia: A Geospatial and Multilevel Analysis.

2020 ◽  
Author(s):  
Binyam Tariku Seboka ◽  
Samuel Hailegebreal ◽  
Delelegn Emwodew Yehualashet ◽  
Abel Desalegn Demeke
Keyword(s):  
Logistic Regression ◽  
Associated Factors ◽  
Composite Index ◽  
Temporal Distribution ◽  
Health Concern ◽  
Multilevel Logistic Regression ◽  
Statistical Tool ◽  
Under Five ◽  
Under Five Children ◽  
Under Nutrition

Abstract Background Under-nutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. Additionally, this study provides a Spatio-temporal distribution and associated factors of childhood anthropometric failures across time.Methods Secondary data was obtained from the Ethiopian Demographic and Health Survey for the survey 2005, 2011, and 2016 years. Data included 23,864 samples of children between the ages of 0-59 months, which is a nationally representative sample in Ethiopia. Analytical methods used in this paper include multivariate multilevel logistic regression to identify associated factors and Getis-Ord spatial statistical tool to identify high and low hotspots areas of anthropometric failures. ResultThe prevalence obtained with CIAF in 2005, 2011, and 2016 was, 53.5%, 51%, and 46.2% of children were suffering from under-nutrition respectively. The spatial analysis revealed areas that are at a higher risk of anthropometric failures consistently were found in northern parts of the country, largely in the Amhara, Tigray, and Afar regions. Multilevel logistic regression analysis showed that the risk of anthropometric failure was higher among older children, had low birth weight, had a mother with low BMI, was in a rural area, had mothers and fathers without formal education. Conclusion In addition to identifying wasted, stunted, and overweight children, CIAF also identified children with multiple conditions, which are generally neglected in most nutritional surveys. As revealed by this composite index, the prevalence of anthropometric failure remains considerably high and its spatial distribution also significantly varied across the regions in the country. The identified socio-demographic characteristics and districts at an increased likelihood of anthropometric failure can inform localized intervention and prevention strategies to improve the nutritional status and healthcare of children in Ethiopia.

Time to death among HIV-infected under-five children after initiation of anti-retroviral therapy and its predictors in Oromiya liyu zone, Amhara region, Ethiopia: a retrospective cohort study

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Bereka Tefera Marie ◽  
Weldemariam Sintayehu Argaw ◽  
Bitewa Yibelu Bazezew
Keyword(s):  
Antiretroviral Therapy ◽  
Clinical Stage ◽  
Severe Malnutrition ◽  
Amhara Region ◽  
Time To Death ◽  
Under Five ◽  
Under Five Children ◽  
Risk Of Death ◽  
Cox Proportional Hazard Regression

Abstract Background Human Immunodeficiency Virus (HIV) is infection which mainly attacks immune system of an individual. Its disease progress is rapid in children and if treatment is not initiated nearly half of infected children will die by the second year of infection. In Ethiopia, nearly twenty four percent of HIV related death is happen to under-five children; however studies done in this specific age group are limited are with poor evidence of predictors. Objectives To determine time to death and identify predictors of death in HIV infected under- five children on antiretroviral therapy in Amhara regional state, Oromia ‘liyu’ zone, Northeast Ethiopia, from 2014 to 2019. Methods Institution based retrospective follow up study was conducted in 376 under-five HIV- infected children on antiretroviral therapy from January 2014 to December 2019 in health institutions in Oromia Liyu Zone, Amhara region, Ethiopia. Multivariable Cox-proportional hazard regression model was used to identify independent predictors of mortality in HIV- infected under-five children on antiretroviral therapy. Result At the end of follow up, 304 (80.85%) of HIV-infected children were alive, 39 (10.95%) were lost to follow up, 12 (3.19%) were transferred out and 21 (5.59%) were reported dead due to HIV/AIDS. The cumulative survival probabilities of children after 3, 6, 12, 24 and 36 months were 0.99, 0.98, 0.97, 0.89 and 0.87 respectively. The overall mean time to death was 19.7 months (95%CI = 18.74–20.67) with incidence of 5.9 deaths per 100 child-months (95%CI: 3.89–9.09). Children with severe malnutrition at baseline (AHR = 4.9; 95 CI: 1.04, 23.50), advanced WHO clinical stage at enrolment (AHR = 3.9; CI: 1.37, 10.88), poor adherence to ART (AHR = 6.56; CI: 3.33, 10.14) and with no history of Isoniazide prophylaxis were significantly associated to higher mortality events (AHR = 3.6; CI: 1.24, 10.18). Conclusion Death of HIV-infected under-five children on ART is high within the first one year after enrolment. The risk of death increased if the child was malnourished at beginning of treatment, had poor ART adherence, with advanced WHO clinical stages and lack of Isoniazide prophylaxis during their age of infancy.

Sign in / Sign up

Export Citation Format

Share Document