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Status and Determinant of Food Insecurity in Girar Jarso Woreda of North Showa Zones, Oromia, Ethiopia

Received: 14 May 2021     Accepted: 14 July 2021     Published: 23 July 2021
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Abstract

The main goal of this study was to look at food insecurity and its major determinant factors of households in Girar Jarso Woreda, North Shoa Zone, and Oromia Regional State, Ethiopia. In order to achieve this goal, demographic and socioeconomic data were collected from 110 randomly selected farm households in the Girar Jarso Woreda's as a special name Torban Ashe and Koticho Kebeles. Two kebeles were chosen using a purposive sampling method. A survey was done to collect primary data from sampled household in the study areas using a structured questionnaire to acquire qualitative and quantitative data on household demographic characteristics. Secondary data was gathered from a variety of sources, including Woreda and kebeles documents, as well as academic research publications, to supplement primary data. The collected data was analyzed using both descriptive and econometric models of analysis. The current household's food insecurity level was determined using the total kilocalorie consumption per adult equivalency per day. A bivariate analysis was used to examine the effect of each predictor variable on the household food insecurity status. Finally, the descriptive analysis revealed that approximately 28 household (25.45%) were food insecure, while 82 households (74.55%) were food secure. Furthermore, the logistic regression model estimates that six of the 13 variables in the logistic model were significant at various probability levels (1, 5, and 10). The age of the household head, the size of the household, the annual farm income, the size of the farm land, the adoption of technology, and the frequency with which the home receives extension services are all factors to consider. Generally, the direction of policy implication and governments has to emphasis on strengthening farmer’s knowledge on adoption of technology by arranging farmer training, field visit and demonstration, and increasing awareness of effective family planning and impact of a high family size on food security.

Published in International Journal of Food Engineering and Technology (Volume 5, Issue 2)
DOI 10.11648/j.ijfet.20210502.11
Page(s) 19-31
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Food Insecurity, Logit, Ethiopia

References
[1] Abduselam A (2017). Food Security Situation in Ethiopia: A Review Study. International Journal of Health Economics and Policy pp. 86-96.
[2] Africa development bank (2012). Highlights of the food security situation in Africa. Quarterly bulletin issue.
[3] Alemu, A., Yenealem, A., Feleke, A. and Meseret, S., 2013. Health related quality of life assessment and associated factors among people on highly active antiretroviral therapy at Felege Hiwot Referral Hospital, Bahir Dar, North West Ethiopia. J AIDS Clin Res, 5 (1), p. 000272.
[4] Cochran, W. G. (1977). Sampling Techniques. 3rd ed. John Wiley & Sons Inc., Singapore.
[5] CSA (2008). Summary and Statistical Report of the 2007 population and Housing census, Federal Democratic Republic of Ethiopia population Census Commission.
[6] Ethiopian Health and Nutrition Research Institute/EHNRI/, (2000). Kilo Calories of Different Food Groups.
[7] FAO (2016). Ethiopia Food Security Situation Report
[8] Food and Agricultural Organization (FAO). The state of food insecurity in the world 2013. The multiple dimensions of food security. Rome: FAO; 2013.
[9] Foster, G., Olsen, C. and Shevlin, T., 1984. Earnings releases, anomalies, and the behavior of security returns. Accounting Review, pp. 574-603.
[10] Franken Berger, T. R. (1992). Indicators and data collection methods for assessing household food security. International Fund for Agricultural Development (IFAD), Rome, Italy.
[11] Girar Jarso Woreda Agricultural Office (2010).
[12] Girma Gezimu (2012). Determinants of food insecurity among households in Addis Ababa city, Ethiopia. Thesis submitted Aksum University, Ethiopia.
[13] Guajarati, D. N. (1995). Basic Econometrics. 3rded. McGraw-Hill, New York,
[14] Gujarati, D. N. and Porter, D. C., 1999. Essentials of econometrics (Vol. 2). Singapore: Irwin/McGraw-Hill.
[15] Lemesa F, Berecha G, Mitiku F, Eneyew A (2017). Why Does Food Insecurity Persist in Ethiopia? Trends, Challenges and Prospects of Food Security in Ethiopia. Journal of Development and Agricultural Economics. Retrieved from https://academicjournals.org/journal/JDAE/articleabstract/009821566628.
[16] Mequanent, Y. and Ayele, N., 2014. Effect of harvesting age on the yield of exotic sugarcane Varieties at Metahara Sugar Estate. J. Agric. & Natu. Reso. Sci, 1 (4), pp. 227-231.
[17] Mesfin Welderufael (2014). Determinants of Households Vulnerability to Food Insecurity in Ethiopia: Econometric analysis of Rural and Urban Households. Journal of Economics and Sustainable Development ISSN 2222-1700 (Paper) ISSN 2222-2855 Vol. 5, No. 24.
[18] Stamoulis K. and Zezza A. (2003). A Conceptual Framework for National Agricultural, Rural Development, and Food Security Strategies and Policies. ESA Working Paper No. 03-17. Rome, Italy.
[19] Tilksew and Fikadu (2013). Factors Influencing Rural Household Food Insecurity In Case Of Babile East Hararghe Zone Ethiopia. Journal of development and agricultural economics ISSN2006-9774, vol. 6 (4).
[20] Tsegaye G. (2009). Determinants of food security in rural households of the Tigray region. Thesis submitted to postgraduate studies of Addis Ababa University, Addis Ababa Ethiopia.
[21] WFP (2015). Ethiopia Food Security Outlook Up.
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  • APA Style

    Gemechu Beri Abdeta. (2021). Status and Determinant of Food Insecurity in Girar Jarso Woreda of North Showa Zones, Oromia, Ethiopia. International Journal of Food Engineering and Technology, 5(2), 19-31. https://doi.org/10.11648/j.ijfet.20210502.11

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    ACS Style

    Gemechu Beri Abdeta. Status and Determinant of Food Insecurity in Girar Jarso Woreda of North Showa Zones, Oromia, Ethiopia. Int. J. Food Eng. Technol. 2021, 5(2), 19-31. doi: 10.11648/j.ijfet.20210502.11

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    AMA Style

    Gemechu Beri Abdeta. Status and Determinant of Food Insecurity in Girar Jarso Woreda of North Showa Zones, Oromia, Ethiopia. Int J Food Eng Technol. 2021;5(2):19-31. doi: 10.11648/j.ijfet.20210502.11

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  • @article{10.11648/j.ijfet.20210502.11,
      author = {Gemechu Beri Abdeta},
      title = {Status and Determinant of Food Insecurity in Girar Jarso Woreda of North Showa Zones, Oromia, Ethiopia},
      journal = {International Journal of Food Engineering and Technology},
      volume = {5},
      number = {2},
      pages = {19-31},
      doi = {10.11648/j.ijfet.20210502.11},
      url = {https://doi.org/10.11648/j.ijfet.20210502.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijfet.20210502.11},
      abstract = {The main goal of this study was to look at food insecurity and its major determinant factors of households in Girar Jarso Woreda, North Shoa Zone, and Oromia Regional State, Ethiopia. In order to achieve this goal, demographic and socioeconomic data were collected from 110 randomly selected farm households in the Girar Jarso Woreda's as a special name Torban Ashe and Koticho Kebeles. Two kebeles were chosen using a purposive sampling method. A survey was done to collect primary data from sampled household in the study areas using a structured questionnaire to acquire qualitative and quantitative data on household demographic characteristics. Secondary data was gathered from a variety of sources, including Woreda and kebeles documents, as well as academic research publications, to supplement primary data. The collected data was analyzed using both descriptive and econometric models of analysis. The current household's food insecurity level was determined using the total kilocalorie consumption per adult equivalency per day. A bivariate analysis was used to examine the effect of each predictor variable on the household food insecurity status. Finally, the descriptive analysis revealed that approximately 28 household (25.45%) were food insecure, while 82 households (74.55%) were food secure. Furthermore, the logistic regression model estimates that six of the 13 variables in the logistic model were significant at various probability levels (1, 5, and 10). The age of the household head, the size of the household, the annual farm income, the size of the farm land, the adoption of technology, and the frequency with which the home receives extension services are all factors to consider. Generally, the direction of policy implication and governments has to emphasis on strengthening farmer’s knowledge on adoption of technology by arranging farmer training, field visit and demonstration, and increasing awareness of effective family planning and impact of a high family size on food security.},
     year = {2021}
    }
    

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  • TY  - JOUR
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    AU  - Gemechu Beri Abdeta
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    AB  - The main goal of this study was to look at food insecurity and its major determinant factors of households in Girar Jarso Woreda, North Shoa Zone, and Oromia Regional State, Ethiopia. In order to achieve this goal, demographic and socioeconomic data were collected from 110 randomly selected farm households in the Girar Jarso Woreda's as a special name Torban Ashe and Koticho Kebeles. Two kebeles were chosen using a purposive sampling method. A survey was done to collect primary data from sampled household in the study areas using a structured questionnaire to acquire qualitative and quantitative data on household demographic characteristics. Secondary data was gathered from a variety of sources, including Woreda and kebeles documents, as well as academic research publications, to supplement primary data. The collected data was analyzed using both descriptive and econometric models of analysis. The current household's food insecurity level was determined using the total kilocalorie consumption per adult equivalency per day. A bivariate analysis was used to examine the effect of each predictor variable on the household food insecurity status. Finally, the descriptive analysis revealed that approximately 28 household (25.45%) were food insecure, while 82 households (74.55%) were food secure. Furthermore, the logistic regression model estimates that six of the 13 variables in the logistic model were significant at various probability levels (1, 5, and 10). The age of the household head, the size of the household, the annual farm income, the size of the farm land, the adoption of technology, and the frequency with which the home receives extension services are all factors to consider. Generally, the direction of policy implication and governments has to emphasis on strengthening farmer’s knowledge on adoption of technology by arranging farmer training, field visit and demonstration, and increasing awareness of effective family planning and impact of a high family size on food security.
    VL  - 5
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Author Information
  • Department of Agricultural Economics, Ethiopian Institute of Agricultural Research, Addis Ababa, Ethiopia

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