Descriptions of the Study Area
The Kindo Didaye District is found in Wolaita Zone, Southern Nation Nationalities, and Peoples Regional State. It is located 450 km far from Addis Ababa, the capital city of Ethiopia. There are three agro-climatic zones in the study area which are kolla (58%), Woyina Dega (37%), and Dega (5%) (Extracted from DEM, SRTM by Author, 2020) (). The annual range of temperature varies from 12.4 oC to 31.3°C. The area is characterized by a unimodal rainfall pattern. The study District has a total area of 347 sq. Km. As per CSA data of the 2007 census, the district has an estimated total population of 131582. Of these, 56,581 are male and 75,001 are female (14). The total number of households in the study area is 37,152. The district comprises 16 Kebele administrations. Only 2% of the population lived in urban areas.
Fig 1: Location map of the study area (Extracted from CSA, 2007 by the Author, 2020)
Study Design and period
Community based comparative cross-sectional study was conducted in the kindo didaye district from September 1st to 30st, 2020.
Sampling size and sampling Procedure
The sample size of households for the study was identified by using the simplified formula provided by (15), statistically estimated at 95% confidence level, the degree of variability = 0.05.
Whereas;
Where n is the sample size, N is the population size (total household size), and e is the level of precision.
A two-stage stage sampling procedure was followed to select the respondent household for the study. In the first stage, three kebeles were selected randomly from those kebeles which have small-scale irrigation access. In the second stage, in the three selected sample Kebeles, households were ratified into two strata, 160 irrigation users and 163 non-users, from which sampled households were randomly selected. The calculated sample size was proportionally allocated for each Kebeles.
Data Types and Sources
Both primary and secondary data sources were used. The data were collected by administering pre-tested structured questionnaires. The questionnaires were designed and pre-tested before starting the actual data collection. The data collection tool includes socio-demographic, socio-economic characteristics, institutional aspect, food security status, in both groups of the households, the household characteristics (age, educational level, and farming experience), and total land size.
Data Collection Techniques
A structured questionnaire was developed from the literature to include all necessary information to the objectives of the study. The household survey included personal information, household resources, production and income issues related to irrigation practice, and food security. The questionnaire was prepared in English and later translated into the local language (Wolaytegna) so that the respondents can easily understand the questions. Three enumerators, one for each kebele, were employed based on their ability of local language and culture, and experiences in data collection. The one-day training was provided to the enumerators on the procedure to follow while interviewing respondents and deep discussion was also held to make the questionnaire clear. Supervision was made by the investigator in addition to any data collected during the detailed questionnaire survey administration process.
Data Analysis
Data were entered to EpiData version 3.1 and exported to Stata version 14 software for analysis. Descriptive statistics including proportions, frequency, charts, mean, and standard deviation was employed to describe the quantitative data. As inferential statistics, chi-square was used to identify the associations between categorical variables, and an independent t-test was also used to compare mean differences. Logistic regression was fitted to identify factors associated with food security. The goodness-of-fit of the final model was checked Hosmer-Lemeshow (p-value =0.820) it was met the assumption of logistic regression. An adjusted odds ratio with their 95% confidence intervals (CI) was calculated and the statistical significance was accepted at the 5% level of significance (p < 0.05).
Study variables
Dependent variable
Household food insecurity was measured by a modified form of a simple equation termed as Household Food Balance Model. The dependent variable was coded as the following: Household food security status (0= food insecure, 1= food secure). A modified form of a simple equation termed as Household Food Balance Model was used to measure the sample household food security.
Independent variables
Household Size; Sex of Household Head; Educational Level of Household Head; Age of Household Head in years; dependency ratio; Irrigation use; Access to the extension service (household head received training regularly during the last 1 year); Livestock owners; cultivated land size; Distance to the market; Credit used by the household; Involvement of the household members in off-frame activity and developmental agent contact
Measurements of variables
A modified form of a simple equation termed as Household Food Balance Model, originally adapted by (16) from the FAO Regional Food Balance Model and thenceforth used by different researchers in this field (17) was used to calculate the per capita food available which is
NGA= GP + GB + FA + GG) - (HL+ GU + GS +GV) Where,
NGA= Net grain available/year/household
GP= Total grain produced/year/household
GB= Total grain bought/year/household
FA= Quantity of food aid obtained/year/household
GG= Total grain obtained through gift or remittance/year/household
HL= post-harvest losses/year
GU=Quantity of grain reserved for seed/year/household
GS=Amount of grain sold/year/household
GV=Grain given to others within a year (17).
The net grain available by sample households' calorie content was computed using the calorie conversion table (18). Household members were also converted to their adult equivalent. Then, the amounts of total calories available by each sample household were computed and divided by 365 days to get per day calorie available for the household. This figure was divided into the Adult Equivalent (AE) of respective households, which finally was given the number of calories available per AE for each sampled household. Hence, households whose caloric consumption is greater than or equal to 2100 kcal/day/AEU were categorized as food security. While households whose caloric consumption is less than 2100 kcal/day/AEU were categorized as food insecure (19). To quantify the livestock numbers of various species as a single figure that expresses the total amount of livestock present, the Tropical Livestock Unit (TLU) was used. The Tropical Livestock Unit is a common unit used to describe livestock numbers of various species as a single figure that expresses the total amount of livestock present irrespective of the specific composition. A tropical livestock unit (TLU) is equivalent to 250 kilograms of live weight and refers to the total livestock ownership of the household head. Each livestock of a household was changed to its equivalent TLU using conversion factors (1 cattle = 1TLU; 1 goat = 0.15 TLU; 1 horse = 1 TLU; 1 mule = 1.15 TLU; 1 donkey = 0.65 TLU; and 1 poultry = 0.005 TLU) (20)
Ethical consideration
Ethical clearance was obtained from Hawassa University, college of agriculture, and submitted to the agriculture office and the Administrative of Kindo didaye district for their permission and support. Then, permission was obtained from each kebele administration office. Respondents were fully informed about the purpose of the study and gave verbal consent. Confidentiality of the information was assured by all the data collectors and investigators.