Household food security, determinants and coping strategies among small-scale farmers in Kedida Gamela district, Southern Ethiopia

Woleba, Girma; Tadiwos, Temesgen; Bojago, Elias; Senapathy, Marisennayya

doi:10.1016/j.jafr.2023.100597

Cited by 13 publications

(20 citation statements)

References 32 publications

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“…An Ethiopian study shows, 43% were food-secure, while the remaining 57% were food insecure. This number is increased than our estimates due to multiple factors [36]. On the contrary, another study shows that two-thirds of households were food insecure due to severe drought and lack of proper agriculture facilities [37].…”

Section: Discussioncontrasting

confidence: 64%

Determinants of the food insecurity at household level in Pakistan: A multilevel model approach

Mahmood,

Kumar,

Ali

et al. 2023

PLoS ONE

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Food insecurity is a major concern for the developing world and around 37% of the population of Pakistan is food insecure. This paper utilizes the Food Insecurity Experience Scale (FIES) to assess the population prevalence of food insecurity and to identify their risk factors and determinants at the household level in Pakistan. This study employs a multi-level random coefficient model, using the Pakistan Panel Household Survey (PPHS-2010) dataset; representative data from 4,130 households. Factors like; income of the household, gender, education, household size, land ownership, and shocks of food insecurity allow the incidence of idiosyncratic shocks (injuries and/or casualties) at the community level, which affects the food insecurity situation of the community, rather differently were included. The study confirms a statistically significant inverse relationship between household income, household size, and household head education with food insecurity and a positive association of shocks and inflation with food insecurity at the household level. Specifically, with increasing per capita income of the household, food insecurity declines (coefficient: -0.083, statistically significant at 1%) and food insecurity increases with shocks (coefficient: 0.058, statistically significant at 1% significance level). The study also reveals a significant heterogeneity at a one percent significance level in the determinants of food insecurity at the district, community, and household levels. The income of the household, household head gender and education level, household size, household assets, shocks, injuries, and inflationary pressure are important determinants of food insecurity in Pakistan.

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Section: Discussioncontrasting

confidence: 64%

Determinants of the food insecurity at household level in Pakistan: A multilevel model approach

Mahmood,

Kumar,

Ali

et al. 2023

PLoS ONE

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“…The result for family size could be due to the high dependency ratio in large families (Mebrie and Ashagrie, 2023;Agidew and Singh, 2018), for credit access could be using credit for non-productive activities (Adgo et al, 2019) and road distance could be the limited production of commercial crops, reduced market access, inefficient delivery of farm inputs and increased transportation costs (Wudad et al, 2021). The significant and positive effect of farm income and extension contacts on food security for adapters could be that higher income increases access to food (Babatunde and Qaim, 2009) and better extension access enables accessing training, fertilizer, chemicals, and seeds, all of which contributes to increased agricultural productivity and hence food security (Woleba et al, 2023). Sex of the head and extension contacts significantly and positively determine food security of non-adapters while road distance affects it significantly and negatively as expected (Table 3).…”

Section: Determinants Of Adoption Of Climate Change Adaptation Strate...mentioning

confidence: 99%

Impact of Climate Change Adaptation Strategies on Food Security of Farm Households in Rural Dire Dawa Administration, Ethiopia

Admasu,

Haji,

Siyum

et al. 2024

SAR

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Background: The impact of climate change on smallholder farmers in underdeveloped countries—specifically, Ethiopia is widely recognized. Farm households employ a range of geographically and temporally varying adaptation strategies to cope with the adverse consequences of climate change. Therefore, it is critical to examine the few empirical studies that examine how rural Ethiopian farm households confronting drought have responded to climate change to ensure food security. Primary data were collected from 385 randomly selected farm households using a semi-structured survey form. Data analysis was performed using endogenous switching regression models and descriptive statistics. Result: Results show that the majority of the sample households (76.7%) adopted climate change adaptation strategies (livelihood diversification, soil and water conservation, and chemical fertilizers separately or in combination) while the remaining 23.3% are non-adopters. Climate change knowledge is validated as an instrumental variable. Model results revealed that adopter farmers would have significantly lower (11.6%) daily calorie intake if they had not adopted them, and non-adopter farmers would have gained significantly higher (12.8%) daily calorie intake if they had adopted them. Sex, marital status, land fragmentation, education, family size, farm size, credit access, extension contacts, and livestock ownership are significantly associated with the likelihood of adoption. Results also show systematic differences where the sex of the head variable is inversely related to the food security of adopters and vice versa for non-adopters. Conclusion: The majority of farm households in the study area know the implications of climate change (73.5%) and suffer from food insecurity (59%). Farmers' knowledge about climate change and variability varies, affecting social, economic, biophysical, and institutional issues. This was shown using descriptive statistics and OLM data. Farm households led by young, male farmers who are married, frequently interact with extension agents, have access to loans and information about climate change, and have non-fragmented plots possess greater knowledge about climate change than other households. Adaptation interventions should consider the above factors and heterogeneities to increase adoption and improve the food security of farm households in the study area.

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“…To ensure accurate predictions, the presence of multicollinearity was tested using the variance inflation factor (VIF) for continuous variables and the contingency coefficient for discrete variables. If the mean VIF exceeds 10, the variable is highly collinear [32,33]. A contingency coefficient that is greater than or equal to 0.75 indicates serious multicollinearity [32,33].…”

Section: Socioeconomic Characteristicsmentioning

confidence: 99%

“…If the mean VIF exceeds 10, the variable is highly collinear [32,33]. A contingency coefficient that is greater than or equal to 0.75 indicates serious multicollinearity [32,33]. The Pearson Goodness-of-fit, Nagelkerke R-squared, and Hosmer-Lemeshow tests were applied to evaluate the goodness of fit and assess the binary logistic regression model's overall performance [32].…”

Section: Socioeconomic Characteristicsmentioning

confidence: 99%

Assessing the Contribution of Smallholder Irrigation to Household Food Security in Zimbabwe

Mupaso,

Makombe,

Mugandani

et al. 2024

Agriculture

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Sustainable Development Goal (SDG) 2 seeks to end hunger and guarantee food and nutrition security worldwide by 2030. Smallholder irrigation development remains a key strategy to achieve SDG 2. This study assesses how smallholder irrigation contributes to household food security in Mberengwa district, Zimbabwe. Primary data were gathered from a randomly chosen sample of 444 farmers (344 irrigators and 100 non-irrigators) using a structured questionnaire. Microsoft Excel and Statistical Package for Social Sciences version 27 software packages were used to analyse the data. Descriptive statistics, chi-square test, t-test, and binary logistic regression were performed. The t-test results show significant differences in mean between irrigators and non-irrigators for household size, the dependency ratio, farming experience, farm income, food expenditure share, and livestock owned (p < 0.05). Irrigators had significantly higher area planted, yield, and quantity sold for maize during the summer than non-irrigators (p < 0.05). Food Consumption Score results show that 97% of irrigators and 45% of non-irrigators were food secure. Binary logistic regression results reveal a significant association between food security and household size, irrigation access, and farm income (p < 0.05). In conclusion, access to smallholder irrigation increases household food security. The government and its development partners should prioritise investments in smallholder irrigation development, expansion, and rehabilitation.

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Household food security, determinants and coping strategies among small-scale farmers in Kedida Gamela district, Southern Ethiopia

Cited by 13 publications

References 32 publications

Determinants of the food insecurity at household level in Pakistan: A multilevel model approach

Determinants of the food insecurity at household level in Pakistan: A multilevel model approach

Impact of Climate Change Adaptation Strategies on Food Security of Farm Households in Rural Dire Dawa Administration, Ethiopia

Assessing the Contribution of Smallholder Irrigation to Household Food Security in Zimbabwe

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