2016
DOI: 10.1186/s40795-016-0116-0
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Gender and education as predictors of food insecurity among coffee farming households of the Jimma zone, Southwest of Ethiopia

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Cited by 11 publications
(13 citation statements)
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“…Children from households with heads who were unable to read and write were 1.54 (1.07-2.21) times, and those with heads only able to read and write were 1.60 (1.11-2.30) times, respectively, more likely to experience different levels of child food insecurity compared with those children from households with heads who completed secondary school education. This more likelihood of experiencing different levels of child food insecurity with the illiteracy of head of the household was supported by the findings of studies from Ethiopia conducted in households by considering children as members of the household [ 25 27 ]. This significant association between child food insecurity and illiteracy of heads of the household might be explained in the fact that illiterate heads of the household might not have better economic opportunity since being educated heads of the household is important to maintain children food security.…”
Section: Discussionmentioning
confidence: 83%
“…Children from households with heads who were unable to read and write were 1.54 (1.07-2.21) times, and those with heads only able to read and write were 1.60 (1.11-2.30) times, respectively, more likely to experience different levels of child food insecurity compared with those children from households with heads who completed secondary school education. This more likelihood of experiencing different levels of child food insecurity with the illiteracy of head of the household was supported by the findings of studies from Ethiopia conducted in households by considering children as members of the household [ 25 27 ]. This significant association between child food insecurity and illiteracy of heads of the household might be explained in the fact that illiterate heads of the household might not have better economic opportunity since being educated heads of the household is important to maintain children food security.…”
Section: Discussionmentioning
confidence: 83%
“…Sample size was calculated assuming the prevalence of stunting among under 24-month-old children in Jimma Zone of 25.4%, a design effect of 2 and a margin of error of 0.05 (Kiyak and Fikreyesus, 2015). In our earlier study in the setting (farming livelihood) a non-response rate of 5% was noted (Hassen et al, 2016), thus, adjusting for the non-response rate, a sample of 582 children aged 6–23 months was estimated to give us a power of 80, calculated using Epi info version 7. Being an infant or young child of a permanently registered resident farming household of the wereda was the inclusion criterion, while exclusions were made for any child with severe acute malnutrition warranting referral to a nutrition rehabilitation programme, severe illness with clinical complications warranting hospital referral, and presence of obvious congenital or chronic abnormalities that impair feeding or physical growth measurements.…”
Section: Methodsmentioning
confidence: 99%
“…Our earlier study in the setting, aimed at assessing the households’ food security situation, revealed an alarming level of food insecurity, leading to the conduct of the current study (Hassen et al, 2016). There has been no study documenting child nutritional outcome in the coffee-farming or cash crop setting in Ethiopia thus far.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, they can allow for a rapid and robust assessment of different aspects of food security aspects at the household level [28]. Relying on multiple metrics is essential for multi-dimensional concepts such as food security [31], with such standardized metrics being increasingly used to assess food security impacts in industrial crop settings of SSA (e.g., [32][33][34][35]). Essentially such approaches can reduce the complexity (and increase the consistency) of food security assessments considering the multiple interacting mechanisms that that are often at play in such industrial crop settings of SSA, for example, [1,8,9,36].…”
Section: Data Collectionmentioning
confidence: 99%