Coping Strategies to Mitigate Food Insecurity at Household Level: Evidence From Urban Setting in Addis Ababa,Ethiopia

Abstract

Food insecurity is the limited or uncertain ability of households to acquire nutritionally adequate and safe foods in socially acceptable ways. There is paucity of empirical evidence on household food insecurity, level of expenditure, and coping strategies in urban setting of Ethiopia. The objective of this paper is to examine the coping strategies of food insecure households in an urban area setting of Addis Ababa, Ethiopia. This study is based on data collected from 632 mothers interviewed in 2017. Multi-stage sampling techniques were carried out to identify the study unit from selected sub-cites. From each sub-city, proportion to population sampling was applied to obtain the sample size. Simple random sampling method was used to select districts in each sub-city. Multivariable logistic regression model was used to identify factors associated with food security status. The most common coping strategies households used in response to food insecurity were: rely on less preferred and less expensive foods, borrow food, or borrow money to buy food and purchase of food on credit. Food insecure households were 3 times more likely to rely on help from a relative or friend outside the household [AOR = 2.37; 95% CI: (1.01, 5.53); P < .047] compared to food secure households. Similarly, food insecure households were approximately 4 times more likely to limit portions at mealtimes [AOR = 3.55; 95% CI: (1.36, 9.30); P < .010] compared to food secure households. Furthermore, households with no access to a bank or microfinance savings account were 3 times [AOR = 2.62; 95%: (1.21, 5.66); P < .014] more likely to become food insecure compared to those with access to financial services. Households rely on less preferred cheap foods or lending to cope with food insecurity in urban settings of Ethiopia. Encouraging households to practice urban gardening, social protection through integrated national safety net programs, and improving access to microfinance services would be vital to address food insecurity among urban households of the country to bring successful social and economic development.

Keywords

food insecurity coping strategies expenditure Ethiopia

What do we already know about this topic?

Household food insecurity occurs when individuals experience uncertainty about future food availability and access, insufficiency in the amount and kind of food required for health, or the need to use socially unacceptable ways to acquire food. The food security strategy of Ethiopia identifies low-income and some female-headed urban households as vulnerable to economic shocks, mainly due to rising of food prices. Most of the studies on food insecurity and coping mechanisms in the country are carried out in rural setting.

How does your research contribute to the field?

There is a paucity of empirical evidence on food security, expenditure levels, and coping strategies of households in urban areas. This study sheds some light on coping strategies of food insecure households in an urban setting of Ethiopia.

What are your research’s implications toward theory, practice, or policy?

The study provides evidence on food insecurity and coping mechanisms of urban communities helping promote social protection through integrated national safety net programs, encouraging urban gardening among households, and advocating for policies and strategies that improve access to microfinance services in urban setting of the country to bring successful social and economic development.

Introduction

Food insecurity is the limited availability of nutritionally adequate and safe foods or the uncertain ability to acquire acceptable foods in socially acceptable ways.^1,2 Household food insecurity occurs when an individual experiences uncertainty about future food availability and access, insufficiency in the amount and kind of food required for health, or the need to use socially unacceptable ways to acquire food.^3
-6 Food insecurity is associated with increased risk for multiple chronic diseases and conditions, such as obesity, type 2 diabetes, cardiovascular disease, and mental health disorders.^7
-12 Food security plays a dynamic role in children’s nutritional status. Understanding of the status of food insecurity may be used to improve children’s access to nutritious foods and informing parents and children about food insecurity.¹³ Studies indicate that the food insecurity, 256.1 million people (20% of the total population) in Africa are undernourished; and 239.1 million live in sub-Saharan Africa. eastern Africa has the highest burden in terms of numbers (133.1 million). The global rates of food insecurity are estimated at 27%, with the highest burden in low-income economies, followed by lower-middle income.¹⁴ The consequences of energy and nutrient deficiencies have been researched in less developed countries. It was recognized that there may be inadequate dietary intakes in terms of micronutrient intakes such as those high in Ca, Fe, and vitamins A and C that helps for immunological functions and growth in children,¹⁵ when diets lack diversity and are dominated by staple foods in lower and middle-income countries (LMICs).^15,16 Furthermore, there is a distinction between adults and children in terms of facing food insecurity as children experiencing cognitive and physical awareness of food insecurity.¹⁷ In the country, the prevalence of household food insecurity was 44.8% in South Ari district, Southern Ethiopia.¹⁸ In the Addis Ababa, where the study carried out, the prevalence of food insecurity were 77.1% among urban productive safety net program beneficiary households,¹⁹ 75% of households were food insecure and 23% were in a state of hunger.²⁰

Coping Strategy Indices (CSI) assess strategies used by households or individuals that are unable to access adequate amounts of food. Because numerous strategies were adopted for coping with food insecurity, it is often quicker and less costly to quantify the existence of these coping strategies than directly recording consumption data.²¹ In a Bangladesh study, coping strategies were also commonly observed with 40% of its households being food insecure and food price shock on a regular basis due to food insecurity at the household level.²² In urban area, consumption of low quality diet or eat less preferred foods were reported which is the case in urban cities.²³ Households and communities who encountered acute food shortages are obliged to adopt coping strategies to meet the immediate food requirements of their families.²⁴ The major factors contributing to food insecurity included inappropriate production systems and marketing services, drought and variability of rainfall, urban expansion, in-and off-farm unemployment^25
-27 and cultivated land size, livestock ownership, total income of the household,²⁸ and average monthly expenditures and non-farm income.²⁷ Studies in Ethiopia supported that households’ participation in rural social protection or productive safety net program (PSNP) were livestock unit, labor force, cultivated land, off-farm income, and credit access²⁹ and off-farming activities seem more of a coping mechanism for farming households than a way to accumulate wealth and sustain their livelihood.³⁰ In the same line, adopting livestock sales to cope with food insecurity challenges³¹ and family size, diversity of income sources, livestock ownership, use of improved seeds with fertilizer, access to credit services, and assistance received; were the determinants of household resilience to food insecurity³² and household food security confirmed that education, size of farm land, tropical livestock unit, total annual cereal yields, on-farm income, off-farm income, use of agricultural input, and use of credits affect positively.³³

There are different circumstances such as cost of living, rural versus urban culture, education and employment status that determine the level of food insecurity and coping behaviors. The urban low-income households might utilize different specific coping mechanisms to deal with income and food insufficiency than rural households. Likewise, various aspects of coping mechanisms including definition, sequence of importance or severity, short-term versus long-term changes³⁴ might differ between locations like urban versus rural as well as coping strategies vary across the different settings. There is paucity of empirical evidence on household food insecurity, level of expenditure, and coping strategies in urban setting of Ethiopia. The objective of this paper is to examine the coping strategies of food insecure households in an urban area setting of Addis Ababa, Ethiopia.

Methods

Study Setting and Sample

A community-based cross-sectional design was employed in Addis Ababa, Ethiopia. Household interviews were conducted from May to July 2017 among the city residents in their households. According to the updated report from Central Statistical Authority (CSA), Ethiopia’s population residing in homes in June 2013 was estimated to be 80 444 148. Of these individuals, 40 333 493 (50.1%) were males and 40 108 655 (49.9%) were females.³⁵ Addis Ababa represents the largest urban center in Ethiopia, hosting about 25% of the urban population in the country. The city is organized into 10 sub-cities, each of which are further divided into 9 or 10 administrative units known as “kebeles,” making up a total of 99 kebeles. The study was conducted in selected sub-cities in Addis Ababa including: Bole, Gulele, Kolfe Keranio, Nifas Silk-Lafto, and Yeka (Figure 1).

Figure 1.

Administrative map of the study area.

This study is based on the data collected from 632 mothers in Addis Ababa, Ethiopia. The study samples were drawn from urban area of Addis Ababa. The study population included the sample size of mothers present during the data collection period in the selected sub-cities. Structured household questionnaires were used to collect data on household food security, coping strategies, and economic variables. The questionnaires were administered by the interviewer and were translated to the local language (Amharic) for data collection purposes and then re-translated back to English by another person to check and maintain its consistency. Data was collected by trained data collectors using standardized, structured, and pre-tested questionnaires.

Multi-stage sampling techniques were carried out to identify the study unit from selected sub-cites. From each sub-city, proportion to population sampling was applied to obtain the sample size. Simple random sampling method was used to select districts in each sub-city. One child was selected from single-child households, and in some instances, random selection of 1 child was done when the number of children in a household was greater than 1. In this case, a child was randomly selected using the lottery method. If a selected household did not have an eligible child, the next household was considered.

Data Collection Procedure

The quantitative study was conducted by interviewing teams which conduct the data collection process. A team of data collector/interviewer were assigned to each selected sub-city; the team consisted of 1 team supervisor, 2 female interviewers, and 2 male interviewers. The supervisors oversaw the coordination aspect of data collection in the sub-cities. One male and 1 female interviewer were allocated per household. Five supervisors, 10 female interviewers, and 10 male interviewers participated in the data collection process. In this study, data saturation was achieved. Data was collected by interviewing mothers in their place of residence at each selected household. Data collectors were well-qualified health professionals who practice in the health facilities in Addis Ababa. The data was monitored both at the time of data collection and at data entry level. The tool was translated to local languages and translated back to English by a translator who was blind to the original tool. The final version of the questionnaire was used for data collection purposes. Supervisors were trained in data quality control procedures and fieldwork coordination. Several rounds of supervision were carried out by principal investigators to assess the quality of field operations and to ensure proper listing of enumeration area/households in each sub-city. Adequate training was offered for supervisors and data collectors before going to the field. The supervisors and principal investigator closely monitored the entire process of data collection.

Measurements

Household food insecurity

Household food security was measured using the Household Food Insecurity Access Scale (HFIAS) of the Food and Nutrition Technical Assistance Project (HFIAS/FANTA)/US Agency for International Development (USAID), which offers information on behavior and insights linked to household food insecurity status including anxiety, depression, and inadequate diet quality. All the questions were asked for the 30-day period preceding the survey. The households were categorized into food secure and food insecure groups.³⁶

Coping Strategies Index

The CSI elucidates frequency and severity of coping measures of households confronted with short-term food insufficiencies. The CSI was also able to track caloric indicators to incorporate elements of future vulnerability as well as decisions households encounter regarding food insecurity. CSI assess strategies used by households or individuals that are unable to access adequate amounts of food. Because numerous strategies were adopted for coping with food insecurity, it is often quicker and less costly to quantify the existence of these coping strategies than directly recording consumption data.³⁷

Study variables

The dependent variable is household food security status and other covariates such as socio-demographic and socioeconomic characteristics, household expenditures, and coping strategy variables were considered as independent variables.

Statistical Analysis

All quantitative data was checked for completeness and consistency. Data was entered into SPSS Version 21 and analysis was carried out using Stata 15.0 (Stata Corporation, College Station, TX). The analysis included descriptive analysis to characterize variables including the study population, socio-demographic and socioeconomic characteristics, household expenditures, household food security status, and coping strategies. For categorical outcomes, chi square analysis and the independent sample T-test were used and analyzed to detect the mean differences between groups to assess statistical significance. Concordance between the CSI score with wealth index/socioeconomic status and the HFIAS score was determined through Pearson’s correlation coefficients. Correlation effect sizes are designated as small (.10-.29), medium (.30-.49), and large (≥.50).³⁸ The 2 categories, food secure and food insecure households were also used in the multivariable logistic regression analysis after controlling for potential confounding factors. Variables entered into the model building with the logistic models was based on the combination of variables that were statistical significance with food security status and variables with unadjusted odds ratios significant at P < .05. Multivariable logistic regression model was used to identify factors associated with food security status. Adjusted odds ratio (AOR) with 95% confidence interval (CI) and P-value ≤.05 in the final model were considered statistically significant.

Results

About 115 (18.3%) of households experienced food insecurity while 514 (81.72%) of households remained food secure. In general, the food insecure households were characterized by male headed households, above 40 years of age, having no-formal education, being employed and working in private business/sectors, smaller household size, poorest wealth quintile, and less access to bank accounts or microfinance (Table 1).

Table 1.

Demographic and Socioeconomic Characteristics of Food Secure and Food Insecure Households in Addis Ababa, Ethiopia.

Characteristics/variables	Categories	Food security status		P-value
Characteristics/variables	Categories	Food secure n (%)	Food insecure n (%)	P-value
Sex of household head	Male	399 (77.63)	79 (68.70)	.043
Sex of household head	Female	115 (22.37)	36 (31.30)	.043
Age group of household head	<40 years	172 (33.46)	57 (49.57)	.001
Age group of household head	≥40 years	342 (66.54)	58 (50.43)	.001
Maternal education	No formal education	182 (35.41)	60 (52.17)	.001
Maternal education	Formal education	332 (64.59)	55 (47.83)	.001
Maternal occupation	Unemployed	180 (35.02)	30 (26.09)	.171
	Private business	99 (19.26)	27 (23.48)
	Employed*	235 (45.72)	58 (50.4)
Family size	<5	241 (46.98)	78 (67.83)	.000
Family size	≥5	272 (53.02)	37 (32.17)	.000
Housing ownership	Owns house	325 (63.23)	42 (36.52)	.000
	Government rented	78 (15.18)	31 (26.96)
	Private rented	111 (21.60)	42 (36.52)
Wealth index	Poorest	67 (14.19)	49 (46.23)	.000
	Poorer	95 (20.13)	23 (21.70)
	Middle	104 (22.03)	19 (17.92)
	Richer	104 (22.03)	7 (6.60)
	Richest	102 (21.61)	8 (7.55)
Access to bank or microfinance savings account	Yes	468 (91.05)	90 (78.26)	.000
Access to bank or microfinance savings account	No	46 (8.95)	25 (21.74)	.000
Mother’s income (Eth) Mean (SD)**		4289.8 (3312.3)	2771.6 (1646.7)	.0001
Household income (Eth) Mean (SD)**		7848.9 (5586.6)	4632.7 (3046.4)	.0000

Employed—Government and NGO employee.

ETB Ethiopian Birr [1 USD≈22.89 Birr (as of May 10, 2017)].

Table 2 shows the correlation between the HFIAS score and the wealth index level with each coping strategy used by households. Results from the Spearman correlation shows that all coping strategies were negatively and positively correlated with the HFIAS and wealth index and all were significant at 5% level of significance. There is a strong positive correlation (5% level of significance) between wealth index and coping strategies including: relying on less preferred and less expensive foods (r = .4074, P < .001), borrowing food or borrowing money to buy food (r = .2742, P < .001), purchasing food using credit (r = .2979, P < .001), relying on help from a relative or friend outside the household (r = .1652, P < .001), limiting portions at mealtimes (r = .3098, P < .001), rationing the littlemoney you have to household members to buy street foods (r = .3062, P < .001), limiting your own intake to ensure your child has enough (r = .2710, P < .001), reducing number of meals eaten in a day (r = .3218, P < .001) and skipping whole days without eating (r = .0688, P < .0981).

Table 2.

Coping Strategy Index (CSI) Score With Wealth Index and HFIAS Score Correlations With Survival Strategies Used by Households in Ethiopia.

Coping strategies	Correlations with survival strategies
Coping strategies	Mean	Standard deviation (SD)	Correlation with wealth index	Correlation with HFIAS score
Rely on less preferred and less expensive foods?	4.23	1.24	0.4074	−0.3447
Borrow food or borrow money to buy food?	4.77	0.56	0.2742	−0.3694
Purchase of food on credit?	4.75	0.58	0.2979	−0.4063
Rely on help from a relative or friend outside household	4.82	0.53	0.1652	−0.4015
Limit portions at mealtimes	4.77	0.62	0.3098	−0.6039
Ration the little money you have to household members to buy street foods?	4.78	0.61	0.3062	−0.5763
Limit your own intake to ensure child gets enough?	4.74	0.70	0.2710	−0.4900
Reduce number of meals eaten in a day?	4.78	0.63	0.3218	−0.6029
Skip whole days without eating	4.93	0.38	0.0688*	−0.1585**

Note. P = sig (2 tailed) results.

Sig. at P < .0981.

Sig. at P = .0001.

The rest of the value is P-value = .0000.

The positive correlation implies that the lower the level of wealth index or socioeconomic status of the household, the lower the number of coping strategies are needed. Likewise, there was a weak negative correlation between the HFIAS score of households and the following coping strategies: relying on less preferred and less expensive foods (r = −.3447, P < .001), borrowing food or borrowing money to buy food (r = −.3694, P < .001), purchasing food using credit (r = −.4063, P < .001), relying on help from relative or friend outside household (r = −.4015, P < .001), limiting portions at mealtimes (r = −.6039, P < .001), rationing the little money you have to household members to buy street foods (r = −.5763, P < .001), limiting your own intake to ensure child gets enough (r = −.4900, P < .001), reducing the number of meals eaten in a day (r = −.6029, P < .001) and skipping whole days without eating (r = −.1585, P = .0001 ) (Table 2). The negative correlation implies that the lower the HFIAS score of the household, the higher the number of coping strategies needed.

Experiencing Food Insecurity and Consumption

About 486 (77.0%) of participants believed and reported that all members of the household were fed the type of food they wanted both in quality and quantity in the preceding 4 weeks. From those respondents that mentioned not having good quality of food, 44 (45.5%) stated the reason as they couldn’t buy food was due to an increase in price, 39 (26.9%) said they couldn’t buy food due to loss of family income, and 32 (22.1%) were unable to prepare due to lack of time. Additionally, 4 (2.76%) stated they had illness and loss of appetite, 3 (2.07%) stated that food was not available at home or the market, and 1 (0.69%) had an “other” reason (Figure 2). The mean (SD) of monthly expenditures of the household of participants (n = 540) was 5648.4 (5590.4) Ethiopian birr (ETB) [1 USD≈ 22.89 ETB (as of May 10, 2017)]. Respondents (n = 600) stated their main source of household food consumption was as follows: 587 (97.8%) purchased from market, 10 (1.67%) from own production, 2 (0.33%) from remittance from any agent, and 1 (0.17%) from other sources (data not shown). The mean share of commodities in household expenditures as depicted in Table 3 included 2439.12 ETB for food items, 1081.9 ETB for education for children, 966.2 ETB for house rent, and 463.1 ETB for fuel/charcoal/electricity. There is a statistically significant difference observed concerning expenditures of food secure and food insecure households regarding food items, water and light, educational fee for the children, and social event or activities (P < .05) (Table 3).

Figure 2.

Reason for family member not feeding type of food they want both in quality and quantity in the past 4 weeks preceding the study in Addis Ababa, Ethiopia, 2018.

Table 3.

Mean and SD of Share of Commodities in Household Expenditure of Food Secure and Food Insecure Households in Addis Ababa, Ethiopia.

Types of major expenditures for	Observations	Combined food secure		Food secure		Food insecure		P-value
Types of major expenditures for	Observations	Mean	SD	Mean	SD	Mean	SD	P-value
Food items	398	2439.1	2137.5	2710.8	2198.7	1165.9	1174.6	<.001
House rent	178	966.2	1818.9	1093.3	2007.24	611.7	1081.1	.1197
Cooking fuel/charcoal/electricity	326	463.1	1018.0	479.9	865.8	395.8	1487.15	.5522
Water and light	373	327.4	585.8	356.3	611.2	193.1	427.7	.0399
Education	333	1081.9	1478.8	1194.9	1534.3	510.0	985.7	.0016
Transport	303	314.8	603.74	336.7	635.34	198.5	379.8	.1460
Social	314	193.7	269.4	208.7	281.7	131.6	201.1	.0445
Alcohol/other substances	120	228.8	296.9	236.0	290.0	199.7	328.1	.5945

Household Food Access and Coping Strategies

The data showed that there is a decrease in frequency in line with the severity of the strategy applied which is in line with the normal expectation. The participants stated that going whole days without eating as the most common strategy reported, relying on help from relative or friend outside household as the second common coping strategy, and limiting their own intake to ensure their child has enough to eat as the third most common coping strategy. Among the strategies least mentioned were purchasing food on credit and reducing number of meals eaten in a day. The least common reported strategy by the respondents was dietary change toward cheaper foods (Table 4). The majority of the study participants 551 (90.5%) reported that they did not sell any type of household assets to cover household expenditures in the in the last 6 months.

Table 4.

Food Consumption Pattern Related Coping Strategies Adopted to Minimize Food Insecurity: Frequencies and Proportions Among Households in Addis Ababa, Ethiopia.

Coping strategy proposed	Number	Relative frequency in the past month					Mean score*(SD)
Coping strategy proposed	Number	Every day (7)	3-6 x/wk. (4.5)	1-2 x/wk. (1.5)	<1 x/wk. (0.5)	Never (0)	Mean score*(SD)
Rely on less preferred and less expensive foods?	631	47 (7.45%)	33 (5.23%)	51 (8.08%)	99 (15.69%)	401 (63.55%)	4.23 (1.24)
Borrow food, or borrow money to buy food?	631	1 (0.16%)	9 (1.43%)	12 (1.90%)	88 (13.95%)	521 (82.57%)	4.77 (0.56)
Purchase of food on credit?	631	0	4 (0.63%)	34 (5.39)	77 (12.20%)	516 (81.77%)	4.75 (0.58)
Rely on help from relative or friend outside household	631	1 (0.16%)	6 (0.95%)	17 (2.69%)	56 (8.87%)	551 (87.32%)	4.82 (0.53)
Limit portions at mealtimes	631	0	17 (2.69%)	16 (2.54%)	60 (9.51%)	538 (85.26%)	4.77 (0.62)
Ration the little money you have to household members to buy street foods?	631	3 (0.48%)	13 (2.06%)	16 (2.54%)	55 (8.72%)	544 (86.21%)	4.78 (0.63)
Limit your own intake to ensure child gets enough?	631	2 (0.32%)	9 (1.43%)	23 (3.65%)	59 (9.35%)	538 (85.26%)	4.78 (0.61)
Reduce number of meals eaten in a day?	631	4 (0.63%)	18 (2.85%)	17 (2.69%)	57 (9.03%)	535 (84.79%)	4.75 (0.70)
Skip whole days without eating	631	2 (0.32%)	3 (0.48%)	3 (0.48%)	22 (3.49%)	601 (95.25%)	4.93 (0.38)
Total index score	631
Average CSI score	42.56

Raw score: every day = 7; 3-6 /week = 4.5; 1-2 /week = 1.5; less than 1/week = 0.5; never = 0.

Predictors of Household Food Insecurity

Food insecure households were 3 times more likely to rely on help from a relative or friend outside the household [AOR = 2.37; 95% CI: (1.01, 5.53); P < .047] compared to food secure households. Similarly, food insecure households were approximately 4 times more likely limit portions at mealtimes [AOR = 3.55; 95% CI: (1.36, 9.30); P < .010] compared to food secure households. Furthermore, households with no access to a bank or microfinance savings account were 3 times [AOR = 2.62; 95%: (1.21, 5.66); P < .014] more likely to become food insecure compared to those with access to financial services (Table 5).

Table 5.

Multivariable Logistic Regression Analysis of Predictors of Household Food Insecurity With Demographic, Socioeconomic, and Coping Strategies in Addis Ababa, Ethiopia.

Characteristics/variables	Categories	Food security status		Crude odd ratio	P-value	Adjusted odd ratio	P-value
Characteristics/variables	Categories	Food secure n (%)	Food insecure n (%)	Crude odd ratio	P-value	Adjusted odd ratio	P-value
Rely on help from a relative or friend outside household	No	482 (93.96)	66 (57.39)	1		1
Rely on help from a relative or friend outside household	Yes	31 (6.04)	49 (42.61)	6.94 (4.40,10.94)	.000	2.37 (1.01, 5.53)	.047
Limit portions at mealtimes	No	483 (94.15)	53 (46.09)			1
Limit portions at mealtimes	Yes	30 (5.85)	62 (53.91)	18.83 (11.2,31.7)	.000	3.55 (1.36,9.30)	.010
Access to bank or microfinance savings account	Yes	468 (91.05)	90 (78.26)	1		1
Access to bank or microfinance savings account	No	46 (8.95)	25 (21.74)	2.82 (1.65,4.83)	.000	2.62 (1.21, 5.66)	.014

Discussion

This study examined the survival strategies adopted by households as well as their expenditures to mitigate food insecurity urban areas of Ethiopia. The study found that food insecure households were 3 times more likely to rely on help from a relative or friend outside the household, 4 times more likely limit portions at mealtimes, and households that did not have access to banks or microfinance savings account were 3 times more likely to become food insecure. In urban areas of the capital of Ethiopia, the prevalence of household food insecurity was 66%³⁹ and in a southern Ethiopia, 82% of households in Sidama District confronted mild to severe food insecurity.⁴⁰

From this study, the finding indicated that those households that did not have access to banks or microfinance savings account were 3 times more likely to become food insecure. Evidence documented that lack of access to credit prevents poor households in developing countries from diversifying into income-generating activities that could safeguard them against uncertain shocks and seasonality, leaving them susceptible to food deprivation even when aggregate food supplies are adequate.⁴¹ In a Ugandan study, results showed a decline in food security following the uptake of microcredit.⁴² Studies demonstrate that microcredit has had positive impacts on 3 important sectors of national development: the alleviation of poverty, the empowerment of women and food security.⁴³ The effect of microcredit participation on food security may be non-linear in which participation initially has either no effect on food security or may actually worsen it before improving it in the longer run.⁴¹ Augmenting the above notion that household wealth assets are relevant to make resilient for financial burden of households during events that stress household budgets. Home owners and households with savings have been reported to be less likely to experience food insecurity.⁴⁴ The very basic assumption is that different development strategies aimed at eliminating poverty are now considered microcredit as one of the key sectors in their programs⁴³ in order to alleviate poverty and then improving the food security situations of their community. From Ethiopia study documented that from the total of poor food security status, 70.4% of the respondents had no credit access service and 29.6% had access.²⁹

In this study, the mean share of commodities in household expenditures was 2439.12 ETB for food items, 1081.9 ETB for education for children, 966.2 ETB for house rent, and 463.1 ETB for fuel/charcoal/electricity, and food secure household expend more as compared to food insecure households. Similar studies were found out with our study regarding the expenditure of items where the food secure household expend more money as compared to the food insecure household. In a Malaysian study, the major expenditures were on food, utilities, child education, and loans and transportation with food insecure households spending a higher proportion of their incomes (90%) compared to food secure households (76%).³⁴

In Bolivia, Burkina Faso, and the Philippines with total daily per capita (DPC) (measured as household expenditures), food expenditure, which represented over 60% of the total household consumption, food secure households have a significantly higher (P < .05) total of DPC food expenditures as well as expenditures on animal source foods, vegetables, and fats and oils than moderately and severely food insecure households.⁴⁵ Food secure households had higher mean total expenditures than marginally, moderately, and severely food insecure households and most of the allocation of larger budget share to basic needs.⁴⁶ Similarly, in a Canadian study, as the proportion of income allocated to housing increased, food spending adequacy declined significantly among households in the 3 lowest income quintiles.⁴⁷ Other studies have revealed that urban low-income households may have fixed incomes and the cost of living was high, and they were more likely to experience unexpected expenses in terms of food and non-food items. This may explain the reason for sudden economic changes associated with urban living.³⁴ A multi-country study showed that insufficient food quantity, inadequate food quality, and uncertainty and worry about food were a significant part of the food insecurity experience in all sampled cultures; concerns about social unacceptability emerged in all ethnographic accounts.⁴⁸ The CSI describes the strategies that households utilize to cope with food shortage, and the application of CSI was assessed based on a 30-day recall; this enables the household to buffer or protect adolescents from food insecurity and undernutrition.⁴⁹ In other studies, coping strategies used included decreasing the frequency and portions of meals, borrowing food, and borrowing money.⁵⁰ In our study, about 36.45% of the participants mentioned that relying on less preferred and less expensive foods was the most common coping mechanism employed by households to cope with food insecurity. In rural Ethiopia studies the coping mechanisms mentioned were similar to our finding in that seeking support from the Gov’t/NGOs (35.2%), undertaking more paid work (26.6%), Focusing on less qualified but more quantified foods consumed by adult females (13%).³⁰ Similar findings were observed that due to severe insecurity of food in their household, people often may not have other choices and stay hungry to try to manage the small amount of food in their household.⁵⁰ In another study, 95.8% of the entire population relied on less preferred food. In Nigeria⁵¹ most households would first employ coping strategies with the lowest severity and highest frequency, such as eating less preferred food.³⁷ In response to household food insecurity, households alternatively applied a number of coping strategies, with the consumption of less expensive foods being the most frequently used strategy similar to our finding.^24,52

During the months of having insufficient food sources, households use coping mechanisms reduction of food intake and consumption of less preferred food.⁵³ In Ghana, consumption of less preferred or less expensive food was more or less equally applied in urban, peri-urban, and rural places although frequency in rural areas is slightly higher.⁵⁴ In an Edo State Nigeria study, the major coping strategies adopted by households to mitigate the negative effects of food insecurity includes: relying on less preferred food, purchasing food on credit, reducing the number of meals eaten in a day, and relying on help from relatives.⁵⁵ In similar context with this study, households used a variety of coping strategies when faced with rising food prices and food insecurity like reducing the number of meals, shifting to less quality/expensive foods, skipping meals, and reducing non-food expenditures.^20,56 Unlike our study finding, in a multi-country analysis, less preferred food as a coping strategy was perceived as a low severity coping strategy in Ghana, Eritrea, Kenya, Malawi, Zambia, Zimbabwe, and Ethiopia.³⁷

The overall impression of food security and coping strategies is that food insecurity is negatively associated with the linear growth of adolescents, more so with girls⁵⁷ and has negative health consequences (mental health, physical well-being, academic achievement, work performance, etc) with long-term life course consequences.^48
-50 At the same time, in one study in Ethiopia, there was a significant proportion of adolescents were food insecure overtime and it persists in the same way that also show the effect of food insecurity on poor self-rated health.⁵⁸ This is reflected again in the country whereby there is a high rate of childhood stunting in Ethiopia compounded with a lower height in food insecure adolescents compared with their food secure peers.⁵⁷

Study Limitations

The current study has some limitations that need to be acknowledged. As the study is cross-sectional in design; we cannot determine magnitude or direction between the predictor and outcome variables as it simply shows the temporal causal association and relationship between variables stated in the study. The findings cannot be generalized to households in other rural communities or to the country as a whole. In addition to this, recall bias and social desirability bias are the possible bias encountered in this study. Interviewer bias could be another possibility, as the interviewers will have a predetermined understanding of food security and other issues. To some extent, the participants might be misreporting (under or over) for some of the questions forwarded due to the sensitivity nature of the inquiry and might also think that they will get food assistance or other nutrition sensitive interventions from the government or non-governmental organizations which are sometimes related with social class, income and society acceptability of respondents in their respective locality of the sub-cities.

Conclusion

The results from this study demonstrated that all coping strategies were negatively and positively correlated with the HFIAS and wealth index. The mean share of commodities in household expenditures were more on food items, education for children, house rent, and cooking using fuel/charcoal/electricity. The most common coping strategies households used in response to food insecurity included: relying on less preferred and less expensive foods, borrowing food, borrowing money to buy food, and purchasing of food on credit. Food insecure households were 3 times more likely to rely on help from a relative or friend outside the household, 4 times more likely limit portions at meal times and households that did not have access to a bank or microfinance savings account was 3 times more likely to become food insecure.

Recommendation

Encouraging households to practice urban gardening, social protection through integrated national safety net programs, and improving access to microfinance services would be vital to address food insecurity among urban households of the country to bring successful social and economic development.

Supplemental Material

sj-doc-1-inq-10.1177_00469580231206263 – Supplemental material for Coping Strategies to Mitigate Food Insecurity at Household Level: Evidence From Urban Setting in Addis Ababa, Ethiopia

Supplemental material, sj-doc-1-inq-10.1177_00469580231206263 for Coping Strategies to Mitigate Food Insecurity at Household Level: Evidence From Urban Setting in Addis Ababa, Ethiopia by Sibhatu Biadgilign in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

The author acknowledges the participants, data collectors, and supervisors for spending their time on this project. Drs Peter Memiah, Mekitew Letebo, Taddese Alemu Zerfu and Tristi Bond were thanked for copyediting this manuscript.

Author’s Contribution

Sibhatu Biadgilign conceived and designed the study, analyzed the data, interpreted the data, and wrote the manuscript.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Ethics Considerations

This study was conducted in accordance with the Declaration of Helsinki, and all procedures involving human subjects were approved by the Institutional Review Boards of the University of South Africa, Ethical Clearance Committee for Research on Human Subjects (HSHDC/ 575/2016) and Addis Ababa City Administration Health Bureau (A/A/H/B/3542/227). Also, support letter was written from University of South Africa Addis Ababa Regional Office to Addis Ababa City Administration Health Bureau. Verbal informed consent was obtained from all the study respondents before the start of an interview, and the participants were made aware they were free to withdraw from the investigation at any time. Written informed consent was waived by the institutional review board/ethics committee.

ORCID iD

Sibhatu Biadgilign

Supplemental Material

Supplemental material for this article is available online.

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