Determinants of livelihood diversification and its contribution to food security of rural households in Gozamin Woreda, Ethiopia

Taye, Anteneh Tenaw; Damtie, Yilebes Addisu; Kassie, Tesfahun Asmamaw Article Determinants of livelihood diversification and its contribution to food security of rural households in Gozamin Woreda, Ethiopia Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Taye, Anteneh Tenaw; Damtie, Yilebes Addisu; Kassie, Tesfahun Asmamaw (2024) : Determinants of livelihood diversification and its contribution to food security of rural households in Gozamin Woreda, Ethiopia, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 12, Iss. 1, pp. 1-19, https://doi.org/10.1080/23322039.2024.2384962 This Version is available at: https://hdl.handle.net/10419/321555 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Economics & Finance ISSN: 2332-2039 (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Determinants of livelihood diversification and its contribution to food security of rural households in Gozamin Woreda, Ethiopia Anteneh Tenaw Taye, Yilebes Addisu Damtie & Tesfahun Asmamaw Kassie To cite this article: Anteneh Tenaw Taye, Yilebes Addisu Damtie & Tesfahun Asmamaw Kassie (2024) Determinants of livelihood diversification and its contribution to food security of rural households in Gozamin Woreda, Ethiopia, Cogent Economics & Finance, 12:1, 2384962, DOI: 10.1080/23322039.2024.2384962 To link to this article: https://doi.org/10.1080/23322039.2024.2384962 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 05 Aug 2024. Submit your article to this journal Article views: 1205 View related articles View Crossmark data Citing articles: 2 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE Determinants of livelihood diversification and its contribution to food security of rural households in Gozamin Woreda, Ethiopia Anteneh Tenaw Taye, Yilebes Addisu Damtie and Tesfahun Asmamaw Kassie Institute of Disaster Risk Management and Food Security Studies, Bahir Dar University, Bahir Dar, Ethiopia ABSTRACT This study was conducted to assess the determinants of rural households’livelihood diversification and its contribution to household food security status in Gozamin Woreda, Amhara region, Ethiopia. A cross-sectional research design and mixed research approach were used. Primary data were collected with the aid of household surveys, key informant interviews, and focus group discussions. A multi-stage stratified random sampling method was used to select 218 households. The Simpson diversity index result showed that 22.94%, 11.93%, 44.5%, and 20.64% of the households were no, low, average, and high livelihood diversifiers. The food consumption score result indicated that 41.28%, 10.09%, and 48.62% of households were found in poor, borderline, and acceptable food security status respectively. In addition, the ordered logistic regression model revealed that education level, agroecology, memberships of cooperative, access to training, access to transport, access to credit, agricultural risk, and total annual income positively affect while sex negatively affect the status of livelihood diversifications. The ordered logistic regression analysis also revealed that the status of livelihood diversification with has a positive and highly significant effect on the status of food security. The study concluded that when the status of households’ livelihood diversification increased, the status of food security also highly increased in the study area. Therefore, to improve the status of food security, extension workers, local governmental and non-governmental organization and policymakers should give higher attention to increasing the status of livelihood diversification of rural households. Finally, policy implications were made according to the finding of the study. IMPACT STATEMENT Rural livelihood diversification is a key issue to improve food security. This study aims to identify the determinants of livelihood diversification and its contribution to food security of rural households. As a result, this study revealed that education level, agroecology, memberships of cooperative, access to training, access to transport, access to credit, agricultural risk, and total annual income are the determinants of rural livelihood diversification in Gozamin Woreda, Ethiopia. ARTICLE HISTORY Received 26 October 2023 Revised 19 July 2024 Accepted 23 July 2024 KEYWORDS Livelihood diversification; food security; determinants SUBJECTS Economic Theory & Philosophy; Rural Development; Development Theory 1. Background In Ethiopia, like in many other African nations, there is an urgent need to enhance household food security. Food insecurity in Ethiopia is closely related to reliance on undiversified livelihoods based on low-input and low-output rain-fed agriculture (Kassegn & Endris, 2021). Furthermore, agriculture is the primary source of food and income for many rural households in Ethiopia, making it a critical component of initiatives aimed at alleviating poverty and achieving food security. Since the sector is faced with many challenges, rural households are compelled to develop strategies through diversification to cope with the increasing vulnerability associated with agricultural production (Abebe et al., 2021). Moreover, in Ethiopia, undiversified livelihood alternatives and total reliance on agricultural output are the key issues that cause food insecurity in rural regions. The capacity to diversify at all is frequently CONTACT Anteneh Tenaw Taye [email protected] Institute of Disaster Risk Management and Food Security Studies, Bahir Dar University, Bahir Dar, Ethiopia ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. COGENT ECONOMICS & FINANCE 2024, VOL. 12, NO. 1, 2384962 https://doi.org/10.1080/23322039.2024.2384962 vital to the food security of the most vulnerable rural people (Ellis & Freeman, 2004). As Zeleke et al. (2017) the limited opportunity for livelihood diversification, due to the absence of supplementary income from other non-farm activities has made the Ethiopian rural poor more vulnerable. In addition to the above, Zeleke et al. (2017) also specified the inability of most Ethiopian smallholders to make a living from agriculture, because of resource constraints and recurrent shocks, increasing policy attention has turned to support alternative livelihood activities. Similarly, the decline in the size of cultivable land is envisaged to further exasperate the currently observed worse food insecurity situation unless nonfarm activities are made to compensate for the livelihood stress prevalent in the rural areas. Further, according to FDRE (2002), rural livelihood diversification aims to reduce risk which is related to agricultural activity and to supplement farm income. Although livelihoods are predominantly agriculture-based, labor productivity is low and most Ethiopians are net cereal buyers. Because of the primary dependence on subsistence crop production in the country, harvest failure leads to household food deficits, which in the absence of off and non-farm income opportunities leads to asset depletion and, increasing levels of destitution at the household level (FDRE, 2002). Even though agriculture is the dominant economic activity and the primary source of livelihood in rural households, to solve the above problem in Ethiopia people to look for alternative employment options other than agriculture for achieving food security and reducing poverty in rural areas due to small farm size and uncontrolled population growth, agricultural production has declined over time and has forced (Abebe et al., 2021). Nowadays, due to the issue of food insecurity is increased, to solve this problem, several scholars studied livelihood diversification and food security. As a result, related to this study in different countries different scholars at different times studied to solve the problem of food insecurity (Abebe et al., 2021; Amaka & Muhammad, 2022; Chavas et al., 2022; Dedehouanou & McPeak, 2020; Dev et al., 2016; Ebenezer & Abbyssinia, 2018; Echebiri et al., 2017; Matsuura-Kannari et al., 2023; Osarfo et al., 2016; Yazdanpanah et al., 2021; Yenesew & Masresha, 2019; Zeleke et al., 2017) Similarly related to this research in Ethiopia, some research is conducted (Asfaw et al., 2019; Challa et al., 2019; Kassegn & Endris, 2021; Weldegebriel, 2016). Therefore, to do this research, there were three reasons. The first and major reason was by using similar and different methodologies studied at different places and times, determinates of livelihood diversification were different. For example, Bekata (2016) studied determinants of household livelihood diversification status in the Hawassa Zuria District of Sidama Zone using ordered logistic regression. He found that education, land size, extension service, membership of cooperatives, credit access, and household income positively affected household livelihood diversification, while age and family size of the household head negatively affected livelihood diversification. Gebru et al. (2018) conducted on determinants of livelihood diversification strategies in the Eastern Tigray Region of Ethiopia, using the multinomial logistic regression model. They found that the households’level of education, access to credit, income, membership of cooperatives, remittance income, farmland, access to irrigation, and access to credit positively affected households’choice and adoption of livelihood diversification strategies. Whereas age, dependency ratio, family size, access to extension services, distance to market, livestock ownership, and agroecology were found to have negative relationships and significantly affect households’choice and adoption of livelihood diversification strategies (Gao & Mills, 2018). Wondem (2020) also studied similar to this research in Degadamot District, Amhara National Regional State, Ethiopia using ordered logistic regression. He found that age, educational level, access to transport, and total annual income of household heads positively affected the livelihood diversification status of the households, whereas, land size and market distance of household heads negatively affected their livelihood diversification status. Moreover, Yenesew and Masresha (2019) studied the impact of livelihood diversification on rural household food security in Goncha-Siso Enesie woreda of Amhara Regional State using Binary logistic and PSM model they found that farm size, adult-equivalent, irrigation, and crop diversification determined diversification of household’s livelihood negatively. On the other hand, cart ownership, mobile phone, and access to formal credit were statistically influencing livelihood diversification positively. The second reason, even in Ethiopia these some researchers (Abebe et al., 2021; Wondem, 2020; Yenesew & Masresha, 2019; Zeleke et al., 2017) have done similar to this study, there is limited empirical evidence to assess factors affecting of the status of livelihood diversification and its effect on food security in a rural 2 A.T. TAYE ET AL. household. The last reason was in the Gozamn woreda had not studied like to this study yet. Therefore, to fill these gaps the researchers studied with more focus on factors affecting the status of livelihood diversification and its relationship with food security in rural households in the Gozamn woreda, Amhara Regional State, Ethiopia. 2. Conceptual framework of the study The review of the literature leads to the development of a conceptual framework that defines the relationship between dependent and independent variables. The conceptual framework serves as the foundation for the data-collecting process, displaying the data that must be gathered, processed, and evaluated. It connects the determining elements associated with wealth accumulation and livelihood activities to household food security. The conceptual framework for this study (Figure 1) is based on the context of the study area, which is taken from institutional, socioeconomic, and demographic variables. This framework consists of variables of household endowment that affect the behavior of these households in terms of livelihood diversification. Asset endowments have a significant effect on rural household activity participation in livelihood diversification status (Amare & Belaineh, 2013; Gebru et al., 2018). These assets serve as the foundation for a household’s ability to engage in income-generating activities and livelihood diversification and also household assets are the ability to improve their status of food security (Abebe et al., 2021; Yenesew & Masresha, 2019; Zeleke et al., 2017). Therefore, based on the empirical literature evidence the assumption is dependent variables which is the status of livelihood diversification is influenced by independent variables (institutional, socioeconomic, geographical, and demographic variables) (Getinet & Lorato, 2020; Kassegn & Endris, 2021). And also as explanatory variable livelihood diversification influences the status of food security. 3. Methodology 3.1. Description of the study area Gozamen is one of the 18 woredas in the East Gojjam zone of Amhara National Regional State. It is located in the southwest part of the zone between 37 0 23’50’’ E latitude and 37 0 55’03’’ E and 10 0 00’50’’ N and 10 Figure 1. Conceptual Framework of the Study. Source: Developed by authors (2023). COGENT ECONOMICS & FINANCE 3 41’10’’ N, longitude and at a distance of 300 and 264 km from Addis Ababa and Bahir Dar, respectively (Figure 2). It has a total area of 1174 Km 2 (GDAO, 2022). Debre Markos is the capital of the woreda and it contains 25 rural kebeles. The woreda has a projection of a total population of 162,070 of which 80,419 and 81,651 are male and female respectively where a 4.82% of the population lives in urban and 95.18% in rural areas (GDAO, 2022). The woreda has an altitudinal difference of 1200–3510 meters above sea level. Based on these altitudinal differences, the woreda has three agro-climatic zones namely, high-land, midland, and lowland meters above sea level. The average annual rainfall of the district was 1628 mm. The maximum and minimum average temperatures are 25 C and 11 C, respectively. Agriculture is the mainstay of farmers in the woreda which is characterized by mixed crop-livestock production systems (Negussie & Leul, 2006). The most important crops grown in the woreda are cereals like wheat, teff, maize, barley, and oats. Pulse crops such as horse beans and chickpeas are produced. Oil seed crops [linseed and Niger seed], Vegetables [onion, garlic, potato, tomato, pepper, and carrot], and fruits [banana, mango, papaya, orange, and lemon] are also produced in the woreda (Negussie & Leul, 2006). The woreda has a livestock population of 155,287 cattle, 97,263 sheep, 8577 goats, 25,473 equines, 56,920 poultry, and 10,019 beehives (Gashe et al., 2017). 3.2. Research design and research approach A cross-sectional research design was used for this research. The purpose of adopting a cross-sectional research design for the study was to assess the factors that affect the status of livelihood diversification, and its contributions to food security at a given point in time. To conduct the study in a representative way and to increase its reliability and validity, both purposive and simple random sampling procedures were employed. For this study, mixed research approaches were employed which include both qualitative and quantitative research approaches. A qualitative approach was used to gain a deep understanding of the sources of household, livelihood diversification, and opinions of households regarding how to improve livelihood diversification and ensure food security in the study areas. Semi-structured interviews and focus group discussions were carried out to gather qualitative data. The quantitative approach involves the measurement of quantity or amount and was used to quantify and see the relationship among variables. The household survey was carried out to conduct a cross-sectional study to collect data on the socioeconomic and demographic information of households, the factors that affect the status of rural livelihood diversification, and its relationships to food security. Figure 2. Maps of the study area. Source: Authors production, 2023. 4 A.T. TAYE ET AL. 3.3. Sampling technique and sample size determination Sampling technique For this study, multi-stage stratifying random sampling was used to choose the sample region and sample respondents. First, the East Gojam zone is purposively selected from the entire Amhara region zone, because the East Gojam zone was one of the highest prevalence of food insecure area because of the highly cereal-based which is a crop-producing area, and the diet of the households lacks animal source foods and vegetables (Wolelie, 2021). And then, from the entire 18 East Gojam zone woreda, the Gozamin woreda was purposively selected because, in Gozamin woreda, 49% of rural households live below the poverty line (Molla et al., 2014). And also no prior research has been conducted on the factors that effect on the status rural household livelihood diversification and its contributions to food security in the Gozamin woreda. Second, by stratifying into three strata, three rural Kebele Administrations, Enrata from 5 high-lands, Aba Libanous from 18 mid-lands, and Chimit from 2 low-land kebeles randomly were chosen from the 25 kebeles. Third, 218 sample households were chosen at random from a total of 3090 households in three different kebeles. Sample size determination Choucheran’s formula was used to get the sample size for this study. To determine the right sample size, three criteria (parameters) must be stated. These include precision (e ¼5%), confidence or risk (t ¼1.96), and degree of variability in the qualities being assessed (p) (Greene, 2017; A. S. Singh & Masuku, 2014). When p is uncertain, it is usually advisable to set it to 0.5 (Greene, 2017). However, a proportion of 50% indicates a higher level of variability than either 80% or 20% (Greene, 2017; A. S. Singh & Masuku, 2014) and a proportion of 0.5 indicates the maximum variability in a population, and it is frequently used in determining a more conservative sample size, that is, the sample size may be larger than if the true variability of the population attributes were taken into account. But, for this study, according to Molla et al. (2014), the proportion of the population to be included in the sample is 9.5%. Therefore n¼t2pð1-pÞ e2¼ð1:96Þ20:095ð1−0:095Þ ð0:05Þ2¼132 where t ¼1.96, P ¼0.095, q ¼1−p, e ¼0.05 Considering the design effect as 1.5 from the multi-stage stratifying random sampling technique and a non-response rate of 10%, the total sample size becomes (132 þ10%) 1.5 ¼217.8 218. 3.4. Method of data collection This study used both quantitative and qualitative data which was collected from both secondary and primary sources. Primary data source Primary data was collected by using the household survey to collect quantitative data and also focus group discussion, and key informant interviews were used to gather qualitative data. A household survey was used to collect quantitative data. The questionnaire was pre-tested with randomly selected 10 maleheaded and 10 female-headed households who were not members of the sampled households. In addition, key informats interview were employed with purposively selected local leaders, extension workers, elders and credit and saving association leaders. Furthermore, Focus Group Discussion (FGDs) were per kebele engaging 8 participants. Secondary data source In addition to primary data collection techniques, intensive desk reviews of published and unpublished literature such as journals, books, articles, thesis, dissertations, and reports of relevant offices to get information on the total population living in the study area and the numbers of household live in three kebeles were used. COGENT ECONOMICS & FINANCE 5 3.5. Method of data analysis Quantitative data analysis method The raw quantitative data collected from the household survey was edited, coded, entered, and analyzed using Excel and STATA-17 software. To analyze the collected data the study used descriptive statistics and inferential statistics. Descriptive statistics such as frequency, percentage, minimum, maximum, mean, and standard deviation, and tables, and bar graphs were used to summarize and present the data in a manageable form, and to describe the socioeconomic characteristics and types of livelihood strategies of sample households. Likewise, in inferential statistics, the chi-square test and Ftest were used to show the relationship or mean difference between a group of variables or pair of variables for categorical or dummy, and continuous variables respectively. Simpson Diversity Index and Food Consumption Score were used to measure the status of livelihood diversification and status of food security respectively. Spearman’s rank correlation analysis was used to test the relationship between the status of livelihood diversification and the status of food security because these two variables are ordered. And also the Ordered Logistic Regression Model was employed to identify the determinants of livelihood diversification and examine the effects of livelihood diversification on the status of food security in rural households. Qualitative data analysis method For this study, the thematic analysis method was used to analyze the qualitative data in a qualitative form about rural households’perceptions, opinions, and understandings of the status of food security in the study area, types of livelihood strategy activity, the determinates of livelihood diversification, the status of livelihood diversification, and the relationships of livelihood diversification and food security status in rural households in the study area. Because, the thematic analysis was used to analyze data obtained from focus group discussions and key informant interviews and also it was used to support, and triangulation. 3.6. Livelihood diversification and food security analysis method The Simpson Diversity Index (SDI) was used to measure the status of livelihood diversification. Among the several indices available, this study prefers SDI over the various methods because it considers both the number of sources of livelihood income as well as how equally the income distributions amongst the different sources are distributed. SDI has a value between 0 and 1. Thus, zero represents specialization (having only one source of income, where Z ¼1), while one represents the extreme of diversification. Furthermore, SDI was chosen due to its wider application, computational simplicity, and reliability in capturing household income from livelihood diversification. Therefore, SDI ¼1−Pn i¼0Z2 where: SDI is a measure of livelihood diversification and Z is the income share of each activity, and Z is expressed mathematically as Z¼Ki Ktn is the number of income sources; ki is the income from each activity, and kt is the household’s total livelihood diversification strategy income. When SDI is less than 0.01 there is no diversification; between 0.01-0.25 low diversification, Between 0.26-0.50 average diversification, and When greater than 0.50 there is high diversification (Aboaba et al., 2019; Addisu, 2017; Ahmed et al., 2018). For this study, food consumption score was used to measure the status of food security of households because as stated by Jones et al. (2013) food consumption score is very important for monitoring food security measures and it needs to be low cost to collect data. FCS also helps us to assess the linkage between dietary diversity and household food access (WFP, 2008). The food consumption score is a food security metric that considers the diversity, quantity, and adequacy of food intake. It is a frequencyweighted dietary variety score determined using a 7-day recall of the frequency with which a family consumed eight food types (i.e. staples (2), pulses (3), vegetables (1), fruits (1), meat/fish/egg (4), milk (4), sugar (0.5) and oil (0.5)). The frequency of food intake should not exceed 7 times the number of recall periods. The FCS is calculated by multiplying each food intake frequency by its weights (which are given in brackets above) and then summing them. The score goes from 0 to 112, with 0 indicating that a family did not consume any food in the previous 7 days and 112 indicating that the household ingested each food category every day for the previous 7 days. According to WFP (2008), for this study, the 21 and 35 criteria were used to 6 A.T. TAYE ET AL. evaluate food security status. As a result, everything below 21 is regarded bad or poor, anything over 35 is considered good or acceptable, and anything between 21 and 35 is considered borderline (WFP, 2008). 3.7. Econometrics model (ordered logistic regression model) In this study Ordered logistic regression model was used to examine the determinants of rural households’livelihood diversification. The ordered logistic regression model is used to predict an ordinal dependent variable given one or more independent variables. An ordinal variable is a categorical variable for which there is a clear ordering of the category levels. The explanatory variables may be either continuous or categorical (Parry, 2020). In this study, the dependent variable is livelihood diversification status, which includes, income sources of livelihood strategies activities from on-farm only, off-farm, non-farm, on-farm þoff-farm, off-farm þnon-farm, on-farm þnon-farm, and onfarm þoff-farm þnon-farm based on the cut point used by Aboaba et al. (2019), Addisu (2017), and Ahmed et al. (2018): (y <0.01) no diversification, (y ¼0.01 −0.25) low diversification, (y ¼0.26 - 0.50) average diversification, and (y >0.50) high diversification. Based on the conceptual and empirical literature review, explanatory variables which have been logical and rationale in influencing status livelihood diversification in rural households are identified. Thus, this section presents the independent explanatory variables of the study with their hypothesized influence on the dependent variable. Dependent variables Livelihood diversification status is a dependent categorical variable and indicates the level of livelihood diversification of a household engaged in on-the-farm, off-farm, nonfarm, on-farm þoff-farm, on-farmþnonfarm, off-farm þnon-farm, and on-farm þoff-farm þnonfarm income-generating activities (Wondem, 2020). It is measured by Simpson Diversification Index (SDI) as ordered values with four levels of categories such as “No diversification (SDI 0.01); Low level of diversification (SDI ¼0.02-0.25); Average level of diversification (SDI ¼0.26-0.50) and high level of diversification SDI>0.50) because it has wider application, computational simplicity, and reliability in capturing household income from livelihood diversification (Aboaba et al., 2019; Ahmed et al., 2018). Household food security Household food security is a categorical variable. It was measured by using food consumption scores. It is a dependent variable and was examined by taking livelihood diversification status as an explanatory variable. Explanatory variables Based on the information obtained from an in-depth review of both theoretical and empirical literature on similar topics of this study, the potential explanatory variables of livelihood diversification status are identified, and described, and their relationship with the dependent variables is presented in Table 1. The effect of explanatory variables on livelihood diversification status was estimated with the ordered logit model, because livelihood diversification status outcome was ordered or ranked. For more than one independent variable, the ordered logit model can be written as: Yi¼X j j¼1 bjXji þe¼Zi þe Y¼livelihood diversification status of households (0, 1, 2, 3) Prob (Yi ¼j) ¼J¼livelihood diversification status of households in the order set as: j¼0, if no livelihood diversification; j¼1, if low diversification; j¼2, if average livelihood diversification, and j¼3, if high livelihood diversification. COGENT ECONOMICS & FINANCE 7 4.4. Food security status of households According to WFP (2008), for this study, the status of food security of households was calculated by food consumption score. As a result, everything below 21 is regarded bad or poor, anything over 35 is considered good or acceptable, and anything between 21 and 35 is considered borderline (WFP, 2008). Therefore, as shown in Table 5, from the total sample of households 218, 90(41.28%), 22(10.09%), and 106(48.62%) were found to be poor, borderline, and acceptable of the status of food security of rural households respectively. Furthermore, as shown below in Table 5 in low-land (Chimit kebele) from a total of 50 (100%) sample of households 36 (72%), 4 (8%), and 10 (20%) were found in poor, borderline, and acceptable of the status of food security of rural households respectively. In mid-land (Abalibanous kebele) from a total of 95(100%) sample of households 52 (54.74%), 14(14.74%), and 29 (30.53%) were found in the poor, borderline, and acceptable status of food security of rural households respectively. In high-land, (Enrata kebele) from a total of 73(100%) sample of households 2(2.74%), 4 (5.48%), and 67 (91.78%) were found in the poor, borderline, and acceptable status of food security of rural households respectively in Table 5. The mean FCS among the households is 27.15 which indicates that the majority of the households are borderline status of food security. Based on the findings of KII households living in different agroecology zone, even though some households were living in poor and acceptable status of food security, most of the households are living in borderline status of food security in the study area. 4.5. Effects of households’livelihood diversification on food security Under this subsection, to examine the effect of livelihood diversification on the food security status of households in the study area, by taking livelihood diversification status as an explanatory variable and the status of food security as a dependent variable, the study used a similar model to the above second subsection (ordered logistic regression model). The survey result shows that from the total of 50 (22.94%) no livelihood diversification status of households 48 (53.33%), and 2(9.09%) were only found in the poor and borderline status of food security respectively. From the total of 26 (11.93%) low livelihood diversification status households 23 (25.56%), and 3 (13.64) were only found in the poor and borderline status of food security respectively. From the total of 97(44.5%) average livelihood diversification status of households 19 (21.11%), 17 (77.27%), and 61 (57.55%) were found in poor, borderline, and acceptable status of food security respectively. Of the total 45(20.64%) high livelihood diversification status of households all 45(100%) were only found in the acceptable status of food security (see Table 6). As hypothesized, Spearman’s rank correlation analysis result showed that livelihood diversification status has a positive and highly statistically significant association with the food security status of households at a 1% level of Table 6. Relationship between livelihood diversification and food security status. Status of Livelihood Diversification Poor Borderline Acceptable Total ῥ-value P-valueFreq % Freq % Freq % Freq % No 48 53.33 2 9.09 0 0 50 22.94 0.787 0.000 Low 23 25.56 3 13.64 0 0 26 11.93 Average 19 21.11 17 77.27 61 57.55 97 44.50 High 0 0 0 0 45 45 45 20.64 Total 90 100 22 100 106 100 218 100 Source: Own survey result (2023). Table 5. Food security status of the households. Agroecology Low-land Mid-land High-land Total MeanFerq % Ferq % Ferq % Freq % Poor 36 72 52 54.74 2 2.74 90 41.28 13.818 Borderline 4 8 14 14.74 4 5.48 22 10.09 27.818 Acceptable 10 20 29 30.53 67 91.78 106 48.62 38.26 Total 50 100 95 100 73 100 118 100 27.15 Source: Own survey result (2023). 14 A.T. TAYE ET AL. significance. This indicated that as livelihood diversification increased, the food security status of the household also increased. The reason is that households diversify their sources of livelihood into onfarm, off-farm, and non-farm livelihood strategy activities providing an additional income that enables them to spend more on their basic needs like food consumption, education, clothing, and health care of household members. An increase in the level of livelihood diversification helped the households to regenerate from the shocks that made them food insecure. The result is consistent with the study of Onunka and Olumba (2017), and Olawuyi and Olawuyi (2022) found that food security among farming households was influenced by livelihood diversification. As per the result shown in Table 7, the status of livelihood diversification affected the status of food security of the household’s head positively and significantly at P <0.01 or 1% (P ¼0.000) probability level. The positive sign indicates that for one unit increase in the status of livelihood diversification, the odds of food security status also increased by 21.683, given that all other variables in the model are held constant. This result is in harmony with the study of Abebe et al. (2021), Wondem (2020), Yenesew & Masresha (2019), and Zeleke et al. (2017). By assuming keeping another variable in the model constant, the marginal effect result indicated that the status of livelihood diversification increased by one unit (more likely), the status of food security poor, and borderline households decreased (less likely) by 26.5% and 9.7% respectively. On the other hand, keeping other influence variables constant, the status of livelihood diversification increased (more likely) by one unit, and the marginal effect indicated that acceptable food security status increased (more likely) by 36.2%. 5. Conclusions and recommendations In general, this study aimed to assess the factors that affect the status of livelihood diversification and its contribution to rural household food security in the Gozamin woreda. Based on descriptive analysis, and FGD, in this woreda, rural households participated in different livelihood diversification strategies, including on-farm activities (crop production and animal production activities, poultry production, and beekeeping), off-farm activities (local daily wage labor at the village level, agricultural work at another person’s farm in exchange for a portion of the harvest in kind, and selling firewood and charcoal), nonfarm activities (handicraft activities like carpentry and house remodeling), and petty trade (grain trade, fruit trade, and vegetable trade) to sustain their life. The result of the Simpson Index of diversity shows that the uppermost (44.5%) households typically diversify their livelihood average status of livelihood diversification. The percentage of no, low and high diversifiers were (22.94%), (11.93%), and (20.64%) respectively. The mean SDI among the households was 0.331 which implies that in the study area, the majority of the households averagely diversify their livelihood. Similarly, the results of the Food Consumption Score revealed that a sample of households (41.28%), (10.09%), and (48.62%) were found in poor, borderline, and acceptable status of food security in rural households respectively. The mean FCS among the households is 27.15 which indicates that in the study woreda, the majority of the households are borderline status of food security. Furthermore, ordered logistic regression model results indicate that out of sixteen explanatory variables, nine variables significantly influenced the livelihood diversification status of households. From these variables, educational level, agroecology, access to training, access to transport, agricultural risk, and annual total income positively affect the livelihood diversification status of households at less than a 1% level of significance. Membership in cooperatives and access to credit positively affect the livelihood diversification status of households at less than 5℅significance levels. But sex has a negative effect on the level of livelihood diversification at less than 10℅significant levels. In line with this, several factors Table 7. Effect of livelihood diversification on the status of food security. Status of food security Odds ratio Std. Err p>jzj Marginal effect (dy/dx) status of food security Poor Borderline Acceptable SDI 21.683 8.746 000 −0.265 −0.097 0.362 p<.01, indicates significance at less than 1%. Source: - Own survey result (2023). COGENT ECONOMICS & FINANCE 15 such as access to credit, access to transport, lack of resources, lack of awareness, inability to promote a culture of work on different activities, and agroecology hinder the status of household livelihood diversification in the study area as explained by FGD and KII. Finally, as shown in both Spearman correlation and ordered logistic regression analysis results, the status of household livelihood diversification has a positive and statistically highly significant effect on the status of food security at a 1% level of significance. Therefore, the study concluded that when the status of household livelihood diversification increased, the food security status of households also highly increased in the study area. Based on the findings of the study, the following recommendations have been provided for possible interventions and help to enhance the status of household livelihood diversification to improve the status of food security in the study area. On-farm activities (crop production and animal production activities, poultry production, and beekeeping), off-farm activities (local daily wage labor at the village level, agricultural work at another person’s farm in exchange for a portion of the harvest in kind, and selling firewood and charcoal), non-farm activities (handicraft, pottery, activities like carpentry and house remodeling), and petty trade (grain trade, fruit trade, and vegetable trade) should be more expand and continue in this woreda. And also households should get supporting training to strengthen their livelihood strategies activities. Further, to increase the status of household livelihood diversification, governmental and non-governmental organizations, extension workers, policy makers, strategies, programs, and other concerned bodies should give more attention to the variables education level, agroecology, memberships of cooperative, access to training, access to transport, access to credit, agricultural risk, and total annual income. Finally, policies improving the food security status of households in the study area should focus on increasing the status of livelihood diversification. Any policies targeted at promoting food security should go beyond just increase food production only; it needs to diversify rural household livelihood through the development of alternative livelihood opportunities to make it sustainable and self-resilience. Moreover, additional research should be carried out to acquire more empirical findings on the factors that affecting of rural household livelihood diversification and its contribution to the food security status situation in the Gozamn woreda as well as in other similar rural areas in Ethiopia. Consent form The authors provide consent for publication of this manuscript in this journal. Authors contributions Anteneh Tenaw Taye engaged on conception and design, analysis and interpretation of the data; and drafting of the manuscript. Yilebes Addisu Damtie and Tesfahun Asmamaw Kassie worked on advising the overall work, revising it critically for intellectual content; and the final approval of the version to be published. All the authors agree to be accountable for all aspects of the work. Disclosure statement No potential conflict of interest was reported by the author(s). Funding The authors cover the budge need of the study. About the author Anteneh Tenaw Taye, Yilebes Addisu Damtie, and Tesfahun Asmamaw Kassie are all young researchers in Institute of Disaster Risk Management and Food Security Studies. They have ample experience in the area disaster risk management, food security, livelihoods, climate change, early warning systems and related concepts. 16 A.T. TAYE ET AL. Data availability statement The dataset supporting the conclusions and recommendations of the study are included in the article. References Abebe, T., Chalchisa, T., & Eneyew, A. (2021). The impact of rural livelihood diversification on household poverty: Evidence from Jimma Zone, Oromia National Regional State, Southwest Ethiopia. The Scientific World Journal, 2021,1–11. https://doi.org/10.1155/2021/3894610 Aboaba, K., Sowunmi., & Akinade, A. (2019). Nexus between poverty and livelihood diversification among rural households in Nigeria: A multidimensional poverty index approach. 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