Seasonality and Nutrition-Sensitive Agriculture in Kenya: Evidence from Mixed-Methods Research in Rural Lake Naivasha Basin

Sassi, Maria

doi:10.3390/su11226223

Cited by 8 publications

(15 citation statements)

References 34 publications

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“…Moreover, other evidence has also linked markets to better food security and nutrition outcomes [11,12]. However, other evidence suggests that if households are able to produce various crops or livestock (farm production diversity), households can then directly consume this produce thus resolving hunger, food insecurity and malnutrition problems [2,5,7,[13][14][15][16][17]. Therefore, evidence is mixed and it would be an oversight to assume that mechanisms through which farm production diversity interlinks with nutrition outcomes can be universally deployed to produce similar nutrition outcomes.…”

Section: Introductionmentioning

confidence: 99%

Household Farm Production Diversity and Micronutrient Intake: Where Are the Linkages? Panel Data Evidence from Uganda

Sekabira¹,

Nalunga²,

Umwungerimwiza

et al. 2021

Sustainability

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Hunger and malnutrition are key global challenges whose understanding is instrumental to their elimination, thus realization of important sustainable development goals (SDGs). However, understanding linkages between farm production diversity (FPD) and household micronutrient intake is important in mapping micronutrient deficiencies and hidden hunger. Such understanding would inform appropriate interventions against malnutrition. Unfortunately, empirical literature is scarce to sufficiently inform such understanding. Using nationally representative panel survey data covering about 3300 households, we study linkages between FPD and nutrition, and associated impact pathways. We analyze data using panel regression models. Results show that at least half of sample was deficient in daily energy, iron, zinc, and vitamin A intake vis-à-vis FAO recommendations. Deficiencies were most severe (85%) with vitamin A. Positive and significant associations (about 1% for each added crop/livestock species) exist between FPD and daily household energy, iron, zinc, and vitamin A intake. FPD impacts energy and micronutrient intake via two main consumption pathways; markets (about 0.01% for each shilling), and own farm production (about 0.1% for each shilling). Therefore, own farm production yields better outcomes. Gender effects also exist. Male-headed households exhibited better nutrition outcomes (energy—11%, iron—8%, and zinc—12%) mostly via markets. Effects on Vitamin A were also positive although insignificant.

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Section: Introductionmentioning

confidence: 99%

Household Farm Production Diversity and Micronutrient Intake: Where Are the Linkages? Panel Data Evidence from Uganda

Sekabira¹,

Nalunga²,

Umwungerimwiza

et al. 2021

Sustainability

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“…As a result, its auto-consumption exhibits a limited role in decreasing the overall inequality. Nonetheless, we observe a positive effect of its auto-consumption with the increased availability of vegetable protein sources after the harvesting season of beans in May, as beans constitute a major component of protein sources in our research area (Sassi 2019).…”

Section: Food Categories For Which the Role Of Auto-consumption Is Stmentioning

confidence: 54%

“…4 also suggests a fluctuation in the household level dietary composition and diversity in different seasons. We can observe that the dietary composition is particularly more diverse after the harvesting season of Maize (after August) than during the season of long rains (March, April, and May) when households replace the consumption of vegetables and fruits with traditional species as the production of vegetables and fruits gets relatively low (Sassi 2019).…”

Section: Gini Decomposition By Food Categoriesmentioning

confidence: 98%

“…Afterwards, the annual level of inequality begins to show upward trends in May as opposed to what would have been observed on a monthly basis, thus, overestimating the household income inequality. The harvesting season of vegetables and cereals starts in May as suggested by Sassi (2019), and it is, thus, unsurprising that the level of inequality coincides with the seasonality of harvesting season for crops. This seasonal variation in consumption inequality calls for an analysis of its sources that might exhibit different patterns in different months over the year, and therefore, requiring specific policy solutions to ensure that the fluctuating levels of inequality in food consumption do not progress into chronic nutrition and food insecurity in the research area.…”

Section: Gi Coefficient and Decomposition By Access Typologiesmentioning

confidence: 99%

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Beyond the Annual and Aggregate Measurement of Household Inequality: The Case Study of Lake Naivasha Basin, Kenya

2021

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This paper investigates household seasonal food expenditure inequality in the rural Lake Naivasha Basin, Kenya using the extended decomposition of Gini and primary data referred from February 2018 to January 2019. The new elements introduced by the paper are the disaggregation of the food expenditure by source of access (purchase, auto-consumption, and gifts); inclusion of traditional species in the food categories; the features of the area investigated; a novel focus on household economic disparities in flower enclave; and the comparison between the annual and monthly level of inequality to understand the seasonality in household inequality. The results highlight the positive contribution of the subsistence sector to the reduction of inequality during the harvesting period of respective food category; and the need for a well-coordinated set of poverty, food security and agricultural development policies to contribute to the achievement of the first goal of Agenda 2030.

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“…As highlighted in Sassi (2019), rural households face different vulnerabilities to food security in these two typologies of clusters, and seasonality stands as a critical dimension affecting their food and nutrition security. This situation allowed us to test whether the latent growth process of food security is cluster-specific and if such a process favours the characteristics of the market-based commercial food system being promoted in East Africa (Pinstrup-Andersen, 2013;Sassi, 2019). In Kenya, the government and subsequently the Nakuru County where the investigated area is located, have adopted food security and agricultural development policies highlighting the important role of agriculture for the eradication of food insecurity and poverty (Republic of Kenya, 2007Kenya, , 2011Kenya, , 2013Kenya, , 2016.…”

Section: Introductionmentioning

confidence: 99%

A latent growth curve modelling approach to seasonal and spatial dynamics of food security heterogeneities in rural Lake Naivasha Basin, Kenya

Sassi

Trital

2021

Food Sec.

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The increasing complexity of food insecurity, malnutrition, and chronic poverty faced by Sub-Saharan Africa warrants urgent categorisation and tracking of household food security along both temporal and spatial dimensions. This will help to effectively target, monitor and evaluate population-level programs and specific interventions aimed at addressing food insecurity. Traditional longitudinal analysis does not address the dynamics of inter- and intrahousehold heterogeneities within the seasonal and spatial context of household-level food security. This study is the first to overcome such limitations by adopting a multi-group piecewise latent growth curve model in the analysis of the food security situation in a statistically representative sample of 601 households involved in subsistence and cut-flower commercial agriculture, around Lake Naivasha. We considered food security as a latent concept, which manifests as food security outcomes in our primary longitudinal dataset from March 2018 to January 2019. Our analysis highlights the temporal and spatial dynamics of food security and advances new evidence on inter- and intrahousehold heterogeneities in food security across different seasons for the subsistence and commercial farming clusters. These heterogeneities were demonstrated primarily during the hunger season from March to June, and persisted in both the clusters and across months, albeit with different intensities. Moreover, our results indicate the importance of commercial agriculture in achieving food security in the hunger season. Our study suggests the need of a multidisciplinary approach to food security and the introduction of well-coordinated interventions for the development of subsistence and commercial agriculture considering the seasonal and cluster-level specificities.

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Seasonality and Nutrition-Sensitive Agriculture in Kenya: Evidence from Mixed-Methods Research in Rural Lake Naivasha Basin

Cited by 8 publications

References 34 publications

Household Farm Production Diversity and Micronutrient Intake: Where Are the Linkages? Panel Data Evidence from Uganda

Household Farm Production Diversity and Micronutrient Intake: Where Are the Linkages? Panel Data Evidence from Uganda

Beyond the Annual and Aggregate Measurement of Household Inequality: The Case Study of Lake Naivasha Basin, Kenya

A latent growth curve modelling approach to seasonal and spatial dynamics of food security heterogeneities in rural Lake Naivasha Basin, Kenya

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