dc.description.abstract |
Majority of the population of East African households are malnourished and much of the
effort to address the problem of stunting, wasting and underweight have focused on
interventions that are designed directly to address its immediate causes. It is expected that the
adoption of multiple agricultural technologies such as improved beans varieties, bio-fortified
maize variety, grafted fruit trees, and garden vegetable techniques can be a means by which
malnourished rural households who may have less access to diverse meals, supplements, and
fortified foods can enhance their balanced diet but malnutrition still remain a salient problem
facing rural households in East Africa. This study determined the factors that affect the
adoption of joint multi-agricultural technologies then analyze the impact of the best four
combinations adopted in East Africa countries that is; improved beans variety, biofortified
maize variety, grafted fruit trees, and use of garden vegetables techniques on the household
nutrition outcome indicators of underweight (WAZ), wasting(WHZ) and stunting(HAZ).
Where TC = base with no technology used, TC1 = Improved beans variety, biofortified maize
variety, and grafted fruit trees, TC2 = Improved beans variety, biofortified maize variety, and
garden vegetable techniques, TC3 = biofortified maize variety, garden vegetable techniques,
and grafted fruit trees, TC4 = Improved beans variety, garden vegetable techniques, and
grafted fruit trees. The study utilized a secondary household panel data of Kenya, Tanzania,
and Uganda that was collected by IFRI for ten waves from 2007 to 2017 and each country
with 500 households. This study utilized multinomial endogenous regression model so as to
casual the impact of technology adoption and to correct for the self-selection bias. It was
conceptualized that the decision to adopt a combination of multiple agricultural technologies
(MATs) is modeled in consumer theory, specifically, a random utility framework. The latent
model (U*jit) which describes the ith farmer’s behavior in adopting MATs j(j=1,...4) at time t
over any alternative MATs combination was utilized in three stages. In the first stage, the
analysis determined the factors for adopting multi-agricultural technologies using a
multinomial endogenous switching regression. In the second stage, the inverse mills ration
generated in stage one is used as linkage between adoption of technologies nutrition outcome,
and on the third stage, the treatment effect was used to establish the relationship between
adopters of the joint multiple agricultural technologies and non-adopters. The results show
that year increase of the education of household head, general participation in community
meetings and barazas increases the adoption of TC1 (45%), TC2 (44%), TC3 (25%), and TC4
(35%) respectively. The 1% percent increase in the adoption of joint technologies, the
prevalence of stunting reduces by 17.4%, wasting 15.4%, and underweight by 16.8%. Results
of the average treatment effects show that the households who adopted joint multiple
agricultural technologies had a positive significant impact (HAZ β= .62, p<0.01), WAZ (β =
.72, p<0.01), and WHZ (β = .74, p<0.01) which improves the nutrition status by HAZ
(103%), WAZ (87%), and WHZ (84%). The best technology combination was TC3 which
impacted all nutrition outcome at the highest percentage HAZ (25.8%), WHZ (24.2%), and
WAZ (25.3%). Kenya(reference) had a higher significant propensity of adoption hence higher
impact on nutrition outcome than Uganda (β = -.128, p<0.01) and Tanzania (β = -.155,
p<0.01). This study concludes that adoption of multiple agricultural technologies improves
household nutrition outcome. The household that adopted the joint multiple agricultural
technologies had systematically higher nutrition outcome than the households who did not
adopt even after controlling for all confounding factors. Among the three countries Kenya has
a higher significant propensity on nutrition outcome. This study offers insight to
policymakers, researchers, and extension workers regarding the advancement of factors
suitable for joint technology combination to be adopted by the East Africa households.
Consequently, this study recommends that household should focus on adopting the multiple
agricultural technologies to improve their nutrition status. And more so focus more on the
combination of TC3 (Biofortified maize variety, garden vegetable techniques, and grafted
fruit trees) since it was the combination with greatest impact on nutrition outcome. |
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