Geo-Additive Models of Childhood Undernutrition in Three Sub-Saharan African Countries

Kandala, Ngianga Bakwin; Fahrmeir, Ludwig; Klasen, Stephan

doi:10.2139/ssrn.321043

Cited by 25 publications

(47 citation statements)

References 17 publications

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“…Studies elsewhere as well as in the country supported the non random distribution of child malnutrition. Studies from West Africa [23], SSA [24], Nigeria [25] and Ethiopia [16, 26] indicated a clear spatial pattern in child under- nutrition across different geographical locations [16, 25–27]. …”

Section: Discussionmentioning

confidence: 99%

Non random distribution of child undernutrition in Ethiopia: spatial analysis from the 2011 Ethiopia demographic and health survey

Alemu

Ahmed

Yalew

et al. 2016

Int J Equity Health

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BackgroundChild undernutrition showed geographical inequalities due to variations in contextual determinants from area to area which indicates that location is an important factor in child undernutrition. However, there are limited studies on spatial epidemiology of child undernutrition in Ethiopia. This study was aimed to identify the SaTScan spatial clusters of child undernutrition in Ethiopia.MethodsNutritional indices of children (0–59 months) with Global Positioning System (GPS) location data were accessed from the 2011 Ethiopia Demographic and Health Survey (EDHS) after getting permission from the MEASURES Demographic and Health Survey (DHS) Program. The Bernoulli Model was fitted using SaTScan™ software, version 9.4. for SaTScan cluster analysis. Log Likelihood Ratio (LLR) test was used for each SaTScan cluster and size of the scanning SaTScan cluster to test the alternative hypothesis that there is an elevated risk within the SaTScan cluster compared to outside the SaTScan cluster. Less than 0.05 for LLR was considered as statistically significant level.ResultsThe SaTScan spatial analysis result detected Liben, Afder and Borena administrative zones around the South East Ethiopia as the most likely primary spatial SaTScan clusters (LLR = 28.98, p < 0.001) for wasting. In the Northern, Middle, North East and North West areas of Ethiopia particularly from all administrative zones of Amhara, Tigray, Afar, Ben. Gumz regional states and East Welega and North Showa zones from Oromiya Regional State (LLR = 60.27, p < 0.0001) were detected as the most likely primary SaTScan clusters for child underweight. Also in the Northern, Middle, North East and North West areas of all administrative zones of Tigray, Amhara, Ben. Gumz and Afar regional states and West and North Showa and East Welega from Oromiya Regional States (LLR = 97.28, P < 0.0001) were primary SaTScan clusters for child stunting.ConclusionThe study showed geographical variability of child stunting, underweight and wasting in the Country which demands risk based local nutritional interventions. Further study will be important to assess the temporal nature of the problem and to identify community level factors that create this spatial variation.

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Section: Discussionmentioning

confidence: 99%

Non random distribution of child undernutrition in Ethiopia: spatial analysis from the 2011 Ethiopia demographic and health survey

Alemu

Ahmed

Yalew

et al. 2016

Int J Equity Health

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“…DHS and MICS include a wide variety of other variables that can be used to assess the factors driving undernutrition. In fact, a vast literature has emerged as a result of the wide availability of these data sets (e.g., Smith et al 2003;Foraita et al, 2008;Kandala et al, 2009). Correspondingly, these surveys can be used to design and monitor nutrition interventions.…”

Section: Strengths and Weaknesses Of Anthropometric Approachesmentioning

confidence: 99%

What do we really know? Metrics for food insecurity and undernutrition

2011

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in What do we really know? Metrics for food insecurity and undernutritionAbstract. In this article, we critically review the three most common approaches of assessing chronic food insecurity and undernutrition: (i) the FAO indicator of undernourishment, (ii) household food consumption surveys, and (iii) childhood anthropometrics. There is a striking and worrying degree of inconsistency when one compares available estimates, which is due to methodological and empirical problems associated with all three approaches. Hence, the true extent of food insecurity and undernutrition is unknown. We discuss strengths and weaknesses of each approach and make concrete suggestions for improvement, which also requires additional research. A key component will be the planning and implementation of more comprehensive, standardized, and timely household surveys that cover food consumption and anthropometry, in addition to other socioeconomic and health variables.Such combined survey data will allow much better assessment of the problems' magnitude, as well as of trends, driving forces, and appropriate policy responses.

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“…Even during the dry season, due to the increase in evaporation rate and decrease in groundwater level, cultivation of winter crops and aquaculture is prohibited. Villagers remain isolated with poor road accessibility and transport links, which may have implications for access to health facilities and other welfare services (Kandala et al, 2009). These issues deserve closer attention: this study is merely able to highlight the important spatial patterns of undernutrition without being able to fully explain them.…”

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confidence: 95%

Fragile Environment, Seasonality and Maternal and Childhood Undernutrition in Bangladesh

et al. 2017

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Summary. This study assessed whether agricultural and household incomes were the same across different agro-ecological environments in Bangladesh. An in-depth analysis of the effect of unfavourable ecologies on maternal and child malnutrition was carried out. Data were from a longitudinal data set comprising a nationally representative data sample collected in 2014 and the Food Security Nutrition Surveillance Project (FSNSP) conducted in 2011 and 2012. Anthropometric indices were used to assess the nutritional status of mothers and under-five children. The key variables of interest were food seasonality and geographical location. Data were analysed using the General Linear Model and multinomial and binary logistic regression analysis. Panel data analysis showed that household income was not equal across agro-ecological zones, indicating that the fragility of the environment affects a household's ability to access food, and thus the nutritional status of mothers and children. Coastal areas of Bangladesh were found to be less dependent on agriculture, particularly cultivation, which had diminished during last few decades. Per capita income has been increasing in coastal areas of Bangladesh, led by remittance (money sent home by migrant workers) growing at 8% per year against 6% in other areas. Regression analysis showed that a household in a coastal zone earned 19% less than one in more favourable zones. Although the income from farm practices was found to be lower in unfavourable areas, the deficiency was compensated by increased nonfarm incomes. The results from the FSNSP data showed that overall the rates of stunting and wasting among under-five children were 37% and 11.7%, respectively, and nearly 28% of mothers suffered from undernutrition. A highly significant regional heterogeneity in undernutrition was found, with alarmingly high levels in the Haor Basin and coastal belt areas. There were significantly higher rates of 1 Corresponding author.

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Geo-Additive Models of Childhood Undernutrition in Three Sub-Saharan African Countries

Cited by 25 publications

References 17 publications

Non random distribution of child undernutrition in Ethiopia: spatial analysis from the 2011 Ethiopia demographic and health survey

Non random distribution of child undernutrition in Ethiopia: spatial analysis from the 2011 Ethiopia demographic and health survey

What do we really know? Metrics for food insecurity and undernutrition

Fragile Environment, Seasonality and Maternal and Childhood Undernutrition in Bangladesh

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