Menu
Menu
Menu
Menu
Introduction: Adequate dietary diversity is vital for the survival, growth and development of infants and children. Inadequate dietary diversity is the major cause of micronutrient deficiency in Sub-saharan Africa, including Ethiopia, where only less than one-fourth of the children aged 6-23 months obtain adequate diversified diet. Thus country implemented a strategy known as the Sustainable Undernutrtion Reduction (SUR) programs to alleviate the problem. However, empirical evidences are scarce on the impact of the program on children aged 6-23 months. Therefore, this study aimed to compare the level of dietary diversity among children aged 6-23 months in districts covered and not covered by SURE program in West Gojjam zone. Methods: A community based comparative cross-sectional study was conducted in three districts of West Gojjam zone, Ethiopia, from February 29 to April 20, 2019. A total of 832 mother and child pairs were selected by the simple random sampling technique. A pretested and structured interviewer-administered questionnaire was used to collect data. A binary logistic regression model was fitted to identify factors associated with dietary diversity. Crude odds and adjusted odds ratios with 95% confidence intervals (CI) were calculated to assess the strength of associations and significance of the identified factors for dietary diversity score. Result: The overall proportion of adequate dietary diversity among children aged 6-23 months was 29.9% (95% CI: 27.0-33.0), whereas in SURE covered and uncovered districts it was 33.4% (95%CI: 29.0-38.and 26.4%(95% CI: 22.0, 31.0), respectively. ANC (Antenatal care) (AOR = 1.7; 95% CI: 1.16, 2.55) and postnatal care services (AOR = 2.1; 95% CI: 1.38, 3.28), participating in food preparation programs (AOR = 1.9; 95% CI: 1.19, 2.96), GMP (AOR = 2.74,95%CI:1.80, 4.18), vitamin A supplementation (AOR = 2.10,95%CI:1.22, 3.61) and household visits by health extension workers (AOR = 2.0; 95% CI: 1.25, 3.21) were significantly associated with dietary diversity. Conclusion: The proportion of adequate dietary diversity was higher among children in the program than those out of the program. ANC visits, PNC follow-ups, women’s participating in food preparation programs and household visits by health extension workers were significantly associated with dietary diversity. Therefore, and strengthening and scaling up the program to non covered districts and providing health and nutrition counseling on Infant and Young Child Feeding (IYCF) during ANC and PNC services are recommended for achieving the recommended dietary diversity.
A community- based comparative cross-sectional study was conducted in three selected districts of West Gojjam zone from February 29 to April 20, 2019. West Gojjam is one of the administrative zones in Amhara region, North West Ethiopia. It is located 567 km from Addis Ababa, the capital of Ethiopia, and has 16 districts and 444 kebeles. SURE and Save the children programs which were working to strengthen existing efforts in the country covered four of the 16 districts each, that is eight districts. A total of 117,673 mothers who had young children aged 6 to 23 months lived in the SURE covered (Yilimanadennsa) and the uncovered (Bahir-Dar Zuriya and Debub Achffer districts) which largely dependent on agriculture. The zone had 3 hospitals, 104 health centers, and 391 health posts that providing health services including maternal and child health care. All infants and young children aged 6–23 months and their mothers who had lived for at least 6 months in the area participated in the study. As this was a comparative cross-sectional study, the minimum sample size was determined by using the double population proportion formula with the assumptions exposed (intervention applied) and unexposed (intervention not applied) groups. To estimate the minimum sample size, a dietary diversity proportion (13%) was taken as p2 from a previous study [18]. However, since there has been no previous finding for the intervention group, the assumption that intervention increases the proportion of dietary diversity by 15% p1 yielded 28%. The final sample size was calculated using the Epi Info software with the assumption of a 95% confidence interval, 80% power, 1:1 ratio of exposed to unexposed, 3% design effect, and 10% non-response rate. Therefore, the final minimum adequate sample size was 832. A multistage stratified sampling and the simple random sampling technique was employed to select study participants in West Gojjam zone. Initially, districts were categorized as SURE program covered and uncovered. Three districts, one covered and two uncovered were selected using the lottery method for the study. The three selected districts had a total of 85 kebeles (35 covered and 50 uncovered).Out of the 85kebeles, seven in SURE covered and ten in uncovered districts were selected using the lottery method. Participants were proportionally assigned to each kebele using the community-based demographic and health related information registration book of health extension workers. Finally, mother to child pairs were selected from each keble using the simple random sampling methods after giving codes to each household which had young children aged 6 to 23 months. If there were more than one children in the households, we selected the index child by the lottery method. If children (aged 6–23 months) received at least four food groups out of seven in the preceding 24 h of the interview [10, 19]. Mothers/caregivers of children exposed to media at least once a week by reading newspapers or magazines or listening to the radio or watching TV [11].. Knowledge of mothers about child feeding, if the mothers answered seven knowledge questions out of the ten they have good knowledge [20]. HFIAS (household food insecurity access scale) was assessed from FANTA (Food and Nutrition Technical Assistance) 2007 with nine main question, HFIAS divided into (Food security defines the Household food security level of the summations were ≤ 1 point out of 27 scores while the household food security level of the summations ≥2 points out of 27 scores were food insecure) [21]. Data was collected through a face to face interview, using a structured and pre-tested questionnaire. In order to maintain the quality of data, 2 days training was given to data collectors and supervisors by the principal investigator. A 5% pretest was conducted in non selected districts, and the questionnaire was initially prepared in English and translated to Amharic and retranslated to English by language and public health experts to guarantee consistency. On-site supervision was performed, and each copy of the questionnaire was checked for completeness and accuracy before data entry; 17 clinical nurses and six BSc graduate nursing or public health field supervisors were involved in the data collection process. Dietary diversity practice was collected and calculated as the sum of the number of different food groups consumed by the child in the 24 h prior to the assessment. The list of food groups included, grains, roots, and tubers; legumes and nuts; dairy products (milk, yogurt, cheese); flesh foods (meat, fish, poultry and liver/organ meats); eggs; vitamin-A rich fruits and vegetables and other fruits and vegetables. Finally, if respondents consumed four or more of the food groups, they were considered as having adequate dietary diversity [2]. Household wealth index adopted from EDHS 2011 was determined using the Principal Component Analysis (PCA) by considering household assets, such as livestock, type of house, durable assets and productive assets. First, variables coded between 0 and 1 were entered and analyzed using PCA; then variables with commonality values of greater than 0.5 were used to produce factor scores. Finally, the factor scores were summed and ranked as “poor”, “medium” and “rich”. Food insecurity was measured using the FANTA (Food and Nutrition Technical Assistance Tool) household food insecurity access scale (HFIAS) [21]. It consisted of nine “occurrence questions” that represented a generally increasing level of severity of food insecurity (access) and nine “frequency-of-occurrence” questions that asked as a follow-up to each occurrence question to determine how often the condition occurred. The frequency-of-occurrence question was skipped if respondents reported when the condition described in the corresponding occurrence question was not experienced in the previous 4 weeks (30 days). Finally, individuals were considered as food secure, if they said “no” to all items or just experienced worry but rarely; mildly food insecure households were those who were defined sometimes or often worried about not having enough food and/or unable to eat favorite foods and/ or rarely ate a more monotonous diet than desired. Households that reported they rarely or sometimes ate more monotonous diets than desired sometimes or often and/or had started to cut back on quantity by reducing the size of meals or the number of meals were coded as moderately food insecure. Data were entered into EPI INFO version 7 and analyzed using the Statistical Package for Social Sciences (SPSS) version 20. Descriptive statistics, including frequencies and proportions were used to summarize the variables. A binary logistic regression model was fitted to identify factors associated with dietary diversity practices. Variables with P–values of < 0.2 in the bi-variable analysis were entered in to the multivariable analysis to control possible effects of confounders. The Adjusted Odds Ratio (AOR) with a 95% of confidence interval was used to examine the strength of associations, and a P– values ≤0.05 was used to declare statistical significance in the multivariable analysis.
N/A
