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International Journal of
            Population Studies                                                  Household food insecurity in urban areas



            2. Data and methods                                ratio of household members aged under 15 and above
                                                               65 to those aged 15 – 64), level of education, income and
            2.1. Study design and area                         food expenditure, employment status, urban agriculture,
            The study was conducted in Lideta subcity, located in the   access to savings and credit, and participation in the urban
            central-western area of Addis Ababa, bordered by Addis   productive safety net program.
            Ketema, Arada, Kirkos, Nifas Silk-Lafto, and Kolfe Keranio.
            The subcity is divided into ten Woredas. For the purpose   2.4. Statistical analysis
            of this study, three Woreds were randomly selected, and   The data were collected using KoboCollect version 3.5 and
            data were collected from respondents at their residencies   subsequently meticulously entered into SPSS 24 software.
            within the subcity. Lideta subcity covers an area of   A data cleansing method was employed to assess correctness
            9.18 km  and has a total population of 284,208, comprising   and identify inconsistencies, ensuring data completeness
                  2
            134,372  males and 149,836  females. This study focuses   and minimizing errors. The Chi-square test (χ ) was
                                                                                                        2
            on a densely populated and economically disadvantaged   employed to identify variables that exhibited a statistically
            district in Addis Ababa, which has a population density of   significant  association  with  household  food  insecurity.
            30,960 people per km  (CSA, 2022b).                In this study, the variables with a p < 0.25 underwent a
                             2
                                                               thorough examination for multicollinearity issues utilizing
            2.2. Sampling design and procedure                 the  variance  inflation  factor.  Following  the  preliminary
            A cross-sectional study design was employed, and data   assessment, the identified variables were incorporated
            between February and March 2023 in Lideta subcity   into the logistic regression model to determine their effect
            were collected. The sampling strategy for this study was   on the outcome variable (household food insecurity).
            determined by the pre-established enumeration areas   Adjusted odds ratios, along with their respective 95%
            within the subcity, delineated by the Central Statistical   confidence intervals (CIs), were computed. A significance
            Service of Ethiopia. Samples were drawn from the   level of 0.05 was considered statistically significant in
            population using a multistage random sampling technique.   this study. To identify the most influential independent
            In the multistage random sampling, three Woredas were   predictors of household food insecurity, logistic regression
            randomly selected in the first stage. Subsequently, within   was conducted using a stepwise selection (LR) method.
            each Woreda, different Ketenas were identified, and from   2.4.1. Measurement of household food insecurity
            each  of  these three  Woredas,  two Ketenas  were  selected
            using random sampling methods. In the final step, a total of   The caloric value of foods that meet the recommended
            six Ketenas were included in the selection process to yield   threshold of 2,200 kcal, as established by the Food and
            692 respondents (household heads). To further clarify,   Agriculture Organization (FAO, 2004) for sustaining a
            Woredas 01, 03, and 10 were selected through a lottery   healthy and moderately active adult, is determined by their
            system. These three Woredas collectively encompass   corresponding national average prices, establishing what
            12,078 households, and the selected Ketenas account for   is known as the food poverty line. In the 2016 Interim
            a total of 3,930 households. Sample households were then   Poverty  Analysis  Report,  the  estimated  cost  was  3,772
            chosen using systematic random samplings, with selection   Birr per year per adult person in Ethiopia. However, this
            proportional to their population within the randomly   cost may not be feasible and needs to be adjusted based
            selected Ketenas.                                  on the current food prices. Notably, the overall inflation
                                                               rate has soared to 122.2% from June 2016 to January 2023.
            2.3. Study variables                               Calculating the annual food inflation, the estimated cost
            The outcome variable for this study is household food   has risen to 11,524.52 Birr per year per adult (CSA, 2022a;
            insecurity, which pertains to the availability of the financial   NBE, 2022). Accordingly, the cost of one kcal is projected
            resources required to consistently access food for the   to be 0.0143 Birr.
            purpose of satisfying dietary, nutritional, and societal   In this paper, the national food poverty line was used
            requirements. In this context, households capable of   to assess food insecurity status. The food poverty line
            affording the purchase of consumption items that generate   determines whether a given household can have enough
            2,200 kcal (daily caloric requirement) are classified as   daily income to meet its members’ minimum daily calorie
            food secure, while those unable to do so are considered   needs. Therefore, households that cannot afford the money
            food insecure. Predictor variables and covariates include   or are unable to source consumer goods for these daily
            a range of  demographic and  socioeconomic  variables,   calorie needs are considered to be food insecure. However,
            such as the age and sex of household head, marital status,   individual access to food depends on household food
            family size, household dependency ratio (the percentage   distribution and gender parity, which in practice means


            Volume 10 Issue 2 (2024)                        93                        https://doi.org/10.36922/ijps.1060
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