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Background: Food insecurity influences children nutritional status by limiting the quantity and quality of dietary intake. Studies conducted across different parts of the world revealed controversial evidences about the relationship between household food insecurity and child nutritional status. Although child malnutrition and food insecurity are the main problems in Ethiopia, to what extent food insecurity contributes to children nutritional status is not yet well studied. Therefore, this study was conducted to compare children nutritional status in food secure and insecure housholds. Method: A community based comparative cross sectional study was conducted in Sekela District,Western Ethiopia from February 5-27, 2014. The total sample size was 576 households having at least one children less than 5 year’s old. Two stage cluster stratified sampling technique was used to select study participants. Data were collected using a pre tested structured questionnaire and anthropometric measurements. Household food insecurity was measured using household food insecurity access scale. Anthropometry indices were calculated using WHO Anthro 3.1.0 and interpreted according to WHO 2006 cutoff points. Data were entered using Epi.Data 3.2. and exported to SPSS 21.0 for analysis. Logistic regression analysis was employed to identify independent predictors of children under nutrition. Result: The mean of household food insecurity score was 8.16 ± 6.01 and the prevalence of food insecurity was 74.1%. Of children in food insecure households 38.9% were stunted, 22.6% were underweighted and 12.9% were wasted while the respective prevalence of stunting, underweight and wasting were 31.3%, 11.8% and 7.6% among children in food secure households. Food insecurity had association with children underweight (AOR = 2.25; 95% CI = 1.29, 3.94), but not with stunting and wasting. Children under nutrition had independent association with sex and age of the child, colostrum feeding, upper respiratory infection, fever, and maternal literacy. Conclusion: Household food insecurity and child under nutrition were critical problems in the study setting. Socio demographic factors, poor child caring practices, infection and food insecurity had positive association with children under nutrition. Thus, due emphasis should be given for the designing and implementation of multi sectorial community based nutrition interventions and initiation of income generating livelihood to the community to curtail under nutrition and household food insecurity in the locality.
The study was conducted in Sekela District, Western Ethiopia. It is located about 440 km northwest of the capital Addis Ababa. Agriculture, mainly cereal crop production, is the means of livelihood for the majority of inhabitants. The main types of crops produced are teff (Eragrostis tef), bean, barely, oat and cowpea [16]. The district has four distinct seasons; spring (September- November); winter (December – February), autumn (March- May) and summer (June-August). The end of spring and the beginning of winter is the harvesting time. The data collection period was during the post-harvest season. A community based comparative cross sectional study was conducted among under five children living in food secure and food insecure households from February 5–21, 2014 in Sekela District, Western Ethiopia. Sample size was determined considering P1 = 0.487 and P2 = 0.32 [13], confidence level of 95%, power of 80% and using the following formula. Where; P1 and P2 denotes proportions of event of interest (outcome) for group I and group II, P denotes P 1 + P 2/2, Zα/2 denotes normal deviate at a level of significance and Z1-β denotes the normal deviate at 1-β% power with β% of type II error. Based on the above formula, assumptions and parameters, the calculated sample size was 262. We considered a design effect of two and a nonresponse rate of 10% and the total sample was 576 households with under five children. Study participants were selected using two stage stratified cluster sampling technique. Villages in Sekela District were stratified by agro-ecological zones. There are 27 villages in the district; of which 21villages are cool humid mid highlands & six villages are cool sub-humid mid highland [17]. Using a lottery method, one village was selected from six cool sub-humid mid highland villages and three villages were selected from 21 cool humid mid highland villages. The lists of households with under five children in the four villages were obtained by census two weeks prior to the actual data collection. From the organized list, 576 households with at least one under five children were selected using simple random sampling technique. If more than one under five children were living in a household, one was selected using a lottery method. Children with diagnosed chronic illness/bed ridden, caught serious acute disease, and had physical deformity in lower extremity and spine were excluded from the study. Structured and pretested questionnaire was used to collect data on socio demographic characteristics, environmental condition, child feeding habit, illness in past two weeks and the use of preventive health care services. Age of the child was taken from growth monitoring and immunization card. For those who missed the card, their age were recorded relying on the date given by the mothers or caretakers. The questionnaire was initially prepared in English and translated to Amharic (local language) version by fluent speakers and back to English to check the consistency. The data collectors and supervisors were given two days intensive training about obtaining informed consent and participants’ rights, interview techniques, anthropometry measurements and use of survey instruments. Supervisors had checked the data collection process and filled questionnaires daily to ensure accuracy of the data. Household food insecurity was measured using household food insecurity access scale (HFIAS) developed mainly by Food and Nutrition Technical Assistance (FANTA) for use in developing country settings. The tool consisted of nine questions that represent generally increasing level of severity of food insecurity and four frequency of occurrence. The nine generic occurrence question relate to three domains of food insecurity. The first generic question relates to anxiety and uncertainty about the household food supply; the next three generic question relate to insufficient diet quality; and the rest five generic question relate to insufficient food intake and its physical consequences [18]. We used the Amharic version of HFIAS questionnaire, which was previously adapted and validated in Ethiopia [19]. Before data collection begun, the Amharic version of the questionnaire was pretested on 58 households in the nearby village of the study area. There was also a focused group discussion with eight key informants who were familiar with the conditions and experiences of household food insecurity in the area. Some type of food items in the HFIAS questions, that provide locally relevant examples when the respondent requires further prompting, were modified to suit the study setting contexts. The reliability test indicated that our HFIAS tool had an adequate internal consistency (Cronbach’s alpha = 0.88). Anthropometric measurements were taken from children. For children aged 6–23 months length was measured in a recumbent position to the nearest one millimeter using length board. For children 24 months older height was measured in a standing-up position to the nearest one millimeter using height measuring board. Weight of child was measured to the nearest 10g for children aged 6–23 months using salter scale and to the nearest 100 g using electronic weighing scales for a child 24 months and older. Data collectors had taken at least two height and weight measurements for an individual. They had repeated the measurements when the variation of the two measures was greater than 0.1 kg for weight and greater than a 0.1 cm for height. Functionality of digital scales were checked using known weight every morning before data collection begun. Data collectors assured the scale reading exactly at Zero before every weight measurement. Data collectors’ accuracy of anthropometric measurements were standardized to the desired precision with their trainer/through repeated measurements during training and pretesting. The data were checked for completeness, cleaned and double entered into Epi Data 3.1and exported to Statistical Package for Social Science 21.0 for further analysis. Based on responses given to the nine questions and frequency of occurrence over the past 30 days, households were assigned a score that ranges from 0 to27. A higher HFIAS score is indicative of poorer access to food and greater household food insecurity. A household was classified as food secure if respondent did not experience none of the food insecurity conditions, or just experienced worry rarely, otherwise as food insecure. Food insecure households were further classified as mild, moderate and severe food insecure as follows. A household was classified as mildly food insecure if the respondent was worried about not having enough food sometimes or often, and/or any of the household’s member rarely scarified quality of dietary intake. A household was classified as moderately food insecure if any of the household’s members sacrificed quality more frequently and/or had started to cutting back on quantity by reducing the size of meals or number of meals, rarely or sometimes. A household was classified as severely food insecure if any of the household’s member was graduated to cutting back on meal size or number of meals often, and/or experiences any of the three most severe conditions (running out of food, going to bed hungry, or going a whole day and night without eating), even as infrequently as rarely [18]. Respondents’ response to the nine HFIAS questions and their frequency of occurrence were summarized using frequency table, and mean ± SD (standard deviation) and median HFIAS scores. Children’s characteristics were compared by household food insecurity using t-test and Chi-Square test. Nutrition indices were computed using WHO Anthro 3.1.0 and the results were classified according to World Health Organization 2006 cut-off points [20]. The Length/height for age Z-score (HAZ), weight for age Z-score (WAZ) and weight for length/height Z-score (WHZ) of children were calculated. The mean HAZ, WAZ and WHZ of children living in food secure and insecure households were compared using t-test. The outcome variables, nutritional status of under five children, were defined as follows by using WHO growth standards. Children whom HAZ-score less than -2SD (standard deviation) were stunted, WAZ-score less than -2SD were underweight and WHZ less than -2SD were wasted. Those children with HAZ, WAZ and WHZ scores greater than or equal to -2SD were considered as normal. The multicollinearity of independent variables were assessed using variable inflation factor (VIF). Binary logistic regression model was used to identify the independent predictors of children under nutrition. Statistical association was asserted based on 95% CI and two sided 5% level of significance (α < 0.05). Bivariate analysis was conducted to assess the relationship between outcome variables and explanatory variables. Variables with p value < 0.2 in bivariate analysis entered in to the multivariate analysis to control all possible confounders and to detect true predictors of stunting, underweight and wasting. A letter of ethical clearance was obtained from Haramaya University College of Health and Medical Sciences Institutional Health Research Ethical Review Committee. The purpose, risk, benefit, confidentiality, nature of the study and their degree of involvement were fully explained to parents or caregivers by the local language. Data were collected after the parent/caregiver agreed and signed the informed written consent. Severe acutely malnourished children in the study were identified and treated in government health institution.
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