scholarly journals Spatial distribution and geographical heterogeneity factors associated with poor consumption of foods rich in vitamin A among children age 6–23 months in Ethiopia: Geographical weighted regression analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252639
Author(s):  
Sofonyas Abebaw Tiruneh ◽  
Dawit Tefera Fentie ◽  
Seblewongel Tigabu Yigizaw ◽  
Asnakew Asmamaw Abebe ◽  
Kassahun Alemu Gelaye

Introduction Vitamin A deficiency is a major public health problem in poor societies. Dietary consumption of foods rich in vitamin A was low in Ethiopia. This study aimed to assess the spatial distribution and spatial determinants of dietary consumption of foods rich in vitamin A among children aged 6–23 months in Ethiopia. Methods Ethiopian 2016 demographic and health survey dataset using a total of 3055 children were used to conduct this study. The data were cleaned and weighed by STATA version 14.1 software and Microsoft Excel. Children who consumed foods rich in vitamin A (Egg, Meat, Vegetables, Green leafy vegetables, Fruits, Organ meat, and Fish) at least one food item in the last 24 hours were declared as good consumption. The Bernoulli model was fitted using Kuldorff’s SaTScan version 9.6 software. ArcGIS version 10.7 software was used to visualize spatial distributions for poor consumption of foods rich in vitamin A. Geographical weighted regression analysis was employed using MGWR version 2.0 software. A P-value of less than 0.05 was used to declare statistically significant predictors spatially. Results Overall, 62% (95% CI: 60.56–64.00) of children aged 6–23 months had poor consumption of foods rich in vitamin A in Ethiopia. Poor consumption of foods rich in vitamin A highly clustered in Afar, eastern Tigray, southeast Amhara, and the eastern Somali region of Ethiopia. Spatial scan statistics identified 142 primary spatial clusters located in Afar, the eastern part of Tigray, most of Amhara and some part of the Oromia Regional State of Ethiopia. Children living in the primary cluster were 46% more likely vulnerable to poor consumption of foods rich in vitamin A than those living outside the window (RR = 1.46, LLR = 83.78, P < 0.001). Poor wealth status of the household, rural residence and living tropical area of Ethiopia were spatially significant predictors. Conclusion Overall, the consumption of foods rich in vitamin A was low and spatially non-random in Ethiopia. Poor wealth status of the household, rural residence and living tropical area were spatially significant predictors for the consumption of foods rich in vitamin A in Ethiopia. Policymakers and health planners should intervene in nutrition intervention at the identified hot spot areas to reduce the poor consumption of foods rich in vitamin A among children aged 6–23 months.

2019 ◽  
Author(s):  
Sofonayas Abebaw Tiruneh ◽  
Dawit Tefera Fentie ◽  
Seblewongel Tigabu Yigizaw ◽  
Asnakew Asmamaw Abebe ◽  
Kassahun Alemu Gelaye

Abstract Introduction: Vitamin A deficiency is a major nutritional public health problem in poor societies. Dietary consumption of foods rich in vitamin A was low in Ethiopia. This study aimed to assess the spatial distribution and its determinants of dietary consumption of foods rich in vitamin A among children age 6-23 months in Ethiopia. Methods: A total of 3055 children were included and data were accessed from 2016 Ethiopian Demographic and Health Survey dataset . The data was cleaned and weighted by STATA version 14.1 software and Microsoft excel. The Bernoulli model fitted using Kuldorff’s SaTScan version 9.6 software. ArcGIS version 10.7 software was used to visualize spatial distribution for poor consumption of foods rich in vitamin A. Geographical weighted regression analysis was employed by MGWR version 2.0 software. A P-value of less than 0.05 was used to declare statistically significant predictors locally. Results: Overall, 62% (95% CI: 60.56, 64.00) of children age 6-23 months had poor consumption of foods rich in Vitamin A in Ethiopia. Poor consumption of foods rich in vitamin A highly clustered at Afar, eastern Tigray, southeast of Amhara, and eastern Somali region of Ethiopia. Spatial scan statistics identified 142 primary spatial clusters located at Afar, the eastern part of Tigray, most part of Amhara and some part of Oromia Regional State of Ethiopia. Children living in the primary cluster were 46% more likely venerable poor consumption of foods rich in vitamin A than outside the window (RR= 1.46, LLR = 83.78, P < 0.001). Poor wealth status of the household, rural residence and living tropical area of Ethiopia were statistically significant predictors spatially. Conclusion: Overall, the consumption of foods rich in vitamin A was low and spatially non-random in Ethiopia. Poor wealth status of the household, rural residence and living tropical area were significant predictors for the consumption of foods rich vitamin A locally in Ethiopia. Policymakers and health planners should intervene in nutrition intervention at the identified hot spot areas to reduce poor consumption of foods rich in vitamin A among children age 6-23 months.


2020 ◽  
Vol 8 (S1) ◽  
pp. 19-32
Author(s):  
Iyyanki M ◽  
Prisilla J ◽  
Kandle S

The coronavirus disease 2019 (COVID-19) outbreak in India from January 31, 2020, onwards to June 15, 2020, has reached confirmed cases over 3,32,424 that are being reported. The aim of this study is to predict and explore the spatial distribution of COVID-19 data of India using three models – geographical weighted regression (GWR), generalized linear regression (GLR), and ordinary least square (OLS). In this paper, the swift rise in COVID-19 cases is experiential after the lockdown period. This is explored using ArcGIS on the confirmed case of June 15, 2020, as the response with the explanatory of COVID-19 cases, i.e March 15, 2020, April 7, April 12, May 12, and June 1, 2020. The confirmed cases of the dataset is classified into three cases ie. case-1: June 15, 2020, vs March 15 and April 7, 2020; case-2: June 15, 2020 vs April 12, May 12 and June 1, 2020; and case-3: June 15, 2020 Vs all dates mentioned in discussion Hence, the prediction using GWR gave the much closer values for June 16, 2020. AICc of GWR (618.9038) was found to have the minimum value over GLR and OLS models. The day-wise increase and samples tested per day in twelve different states is analyzed using STATA. The number of testing varies with states to states, depending on the population and testing labs available. The percentage for each slope is achieved as m1 (-5.714 %), m2 (39.393%), m3 (6.521%) and m4 (46.938%). Keywords: COVID-19; GIS; spatial data; spatial models; testing samples


2020 ◽  
Author(s):  
Zemenu Tessema Tadesse ◽  
Melkalem Mamuye Azanaw ◽  
Yeaynmarnesh Asmare ◽  
Kassahun Alemu Gelaye

Abstract Background Maternal and child mortality is the main public health problem worldwide and it is the major health concern in developing countries such as Africa and Asia. Fertility behavior of women characterized in relation to maternal age, birth spacing, and order which has an impact on the health of women and children. The aim of this study was to assess the geographically vary Risk factors of High-Risk Fertility Behavior(HRFB) among reproductive-age women in Ethiopia. Methods A total of 11,022 reproductive-age women were included in this study. The data was cleaned and weighted by STATA 14.1 software. Bernoulli based spatial scan statistics were used to identify the presence of purely spatial clusters HRFB using Kulldorff’s SaTScan version 9.6 software. ArcGIS 10.7 was used to visualize spatial distribution for HRFB. Geographical weighted regression analysis was employed by Multiscale Geographical weighted regression version 2.0 software. A P-value of less than 0.05 was used to declare statistically significant predictors locally. Results Overall, 76% with 95% confidence interval of 75.60 to 77.20 of reproductive age women were faced with High-Risk Fertility problems in Ethiopia. High-Risk Fertility Behavior was highly clustered at the Somali, and Afar regions of Ethiopia. SaTScan identified 385 primary spatial clusters (RR= 1.13, P < 0.001) located at Somali, Afar, and some parts of Oromia Regional State of Ethiopia. Women live in primary clusters were 13% more likely venerable HRFB than outside the cluster. In geographically weighted regression not contraceptive use, and home delivery were statistically significant spatially vary risk factors affecting HRFB. Conclusion In Ethiopia, HRFB had to vary geographically across regions. Statistically, a significant-high hot spot of HRFB was identified at Somali and Afar. This study showed that predictor variables for HRFB were varied spatially in Ethiopia. Not use a contraceptive, and home delivery were statistically significant predictors locally in different regions of Ethiopia. Therefore, policymakers and health planners should design an effective intervention program at Somali, and Afar to reduce HRFB and Special attention needs about health education on the advantage of contraceptive utilization and health facility delivery to reduce HRFB.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Seblewongel Tigabu ◽  
Alemneh Mekuriaw Liyew ◽  
Bisrat Misganaw Geremew

Abstract Background In developing countries, 20,000 under 18 children give birth every day. In Ethiopia, teenage pregnancy is high with Afar and Somalia regions having the largest share. Even though teenage pregnancy has bad maternal and child health consequences, to date there is limited evidence on its spatial distribution and driving factors. Therefore, this study is aimed to assess the spatial distribution and spatial determinates of teenage pregnancy in Ethiopia. Methods A secondary data analysis was conducted using 2016 EDHS data. A total weighted sample of 3381 teenagers was included. The spatial clustering of teenage pregnancy was priorly explored by using hotspot analysis and spatial scanning statistics to indicate geographical risk areas of teenage pregnancy. Besides spatial modeling was conducted by applying Ordinary least squares regression and geographically weighted regression to determine factors explaining the geographic variation of teenage pregnancy. Result Based on the findings of exploratory analysis the high-risk areas of teenage pregnancy were observed in the Somali, Afar, Oromia, and Hareri regions. Women with primary education, being in the household with a poorer wealth quintile using none of the contraceptive methods and using traditional contraceptive methods were significant spatial determinates of the spatial variation of teenage pregnancy in Ethiopia. Conclusion geographic areas where a high proportion of women didn’t use any type of contraceptive methods, use traditional contraceptive methods, and from households with poor wealth quintile had increased risk of teenage pregnancy. Whereas, those areas with a higher proportion of women with secondary education had a decreased risk of teenage pregnancy. The detailed maps of hotspots of teenage pregnancy and its predictors had supreme importance to policymakers for the design and implementation of adolescent targeted programs.


Bone ◽  
2015 ◽  
Vol 79 ◽  
pp. 110-115 ◽  
Author(s):  
Geng-dong Chen ◽  
Ying-Ying Zhu ◽  
Yi Cao ◽  
Jun Liu ◽  
Wen-qi Shi ◽  
...  

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