Food Insecurity and Not Dietary Diversity Is a Predictor of Nutrition Status in Children within Semiarid Agro-Ecological Zones in Eastern Kenya

Abstract

Machakos and Makueni counties in Kenya are associated with historical land degradation, climate change, and food insecurity. Both counties lie in lower midland (LM) lower humidity to semiarid (LM4), and semiarid (LM5) agroecological zones (AEZ). We assessed food security, dietary diversity, and nutritional status of children and women. Materials and Methods. A total of 277 woman-child pairs aged 15–46 years and 6–36 months respectively, were recruited from farmer households. Food security and dietary diversity were assessed using standard tools. Weight and height, or length in children, were used for computation of nutritional status. Findings. No significant difference (P > 0.05) was observed in food security and dietary diversity score (DDS) between LM4 and LM5. Stunting, wasting, and underweight levels among children in LM4 and LM5 were comparable as were BMI scores among women. However, significant associations (P = 0.023) were found between severe food insecurity and nutritional status of children but not of their caregivers. Stunting was significantly higher in older children (>2 years) and among children whose caregivers were older. Conclusion. Differences in AEZ may not affect dietary diversity and nutritional status of farmer households. Consequently use of DDS may lead to underestimation of food insecurity in semiarid settings.

Predictors of Chronic Under Nutrition (Stunting) Among Children Aged 6-23 Months in Kemba Woreda, Southern Ethiopia: A Community Based Cross-Sectional Study

“…Boys were more likely to be stunted than girls (25.8% vs. 12.5%). The prevalence of stunting in this setting was much lower than as compared findings from different parts of Ethiopia (Bule Hora (47.6%), Jimma arjo (41.4%) [14] and even lower than the regional stunting levels of Ethiopian demographic and health surveillance report [11], Eastern Kenya (33.3%) [15]. This finding was consistent with finding from Johannesburg (18%) [16].…”

Platform, Participation, and Power: How Dominant and Minority Stakeholders Shape Agricultural Innovation

“…Farmers generally employed intercropping methods, with many keeping poultry and larger livestock for meat, eggs, and milk [58]. Rates of household food insecurity were high [59], particularly among women and children [60], with high rates of rural poverty and gender inequality adding further complexity to household food security and agricultural development initiatives [61]. Yatta is primarily inhabited by the Kamba people, who have traditionally been involved in trade but have more recently become widely engaged in small-scale and subsistence agriculture [62,63].…”

“…By identifying key stakeholders, their interests, behaviours, interactions, and relative power to affect change, stakeholder analysis can help to assess some of the drivers of, and barriers to, innovation; the potential impacts of certain policy actions, as well as the broader institutional context within which innovation occurs [69]. Stakeholder analysis also allows marginalized or disempowered groups to be identified [60,67,70,71], providing insights into how participatory approaches to learning, innovation, and food security might best promote mutual trust, collective action, and learning [72,73]. Following the guidelines laid out by Schmeer [74] and adapted by Rastogi et al [75], we sought to determine each stakeholder groups' previous engagement with agricultural innovation projects, as follows: (1) role and interactions-role filled by each stakeholder group within the agricultural sector and their interactions with other stakeholders; (2) knowledge-of relevant agricultural technology, practices, and policy; (3) other resources-that may be mobilized in support or opposition of change; (4) leadership-ability to mobilize collective action; (5) position-on agricultural innovation through commercialization and modernization, as envisioned in the ASDS [64], and potential for conflicts between stakeholder groups; and (6) power-to affect change based on the five preceding factors.…”

Dietary diversity and associated factors among children aged 6–23 months in Sinan Woreda, Northwest Ethiopia: a cross-sectional study

“…In multivariable logistic regression analysis, those mothers who had available media at the household level were 2.77 times more likely to feed their children with optimum [22,26,29,[31][32][33]. The difference might occur due to time of study, socio-economic difference and geographical variation.…”

“…The national prevalence of under-five stunting in Ethiopia is 44% and it is 52% in Amhara [15]. Globally, studies show that different socio-demographic and economic characteristics of mothers/care takers and children are associated with dietary diversity for children aged less than two years [14,[17][18][19][20][21][22][23][24]. Place of residence, age of the child, maternal education, birth order, wealth index and number of children less than five years old in the household were some of the factors which determine minimum dietary diversity [11,25].…”