Correction: Optimal complementary feeding practice and associated factors among children in Konso Zone, South Ethiopia

Abstract

1.IntroductionAdequate nutrition throughout infancy is vital for a child's optimal growth and development later in life [1]. The first two years are critical for physical and cognitive development, yet infants are vulnerable to developmental insults caused by inadequate nutrition and diseases [2]. Optimal complementary feeding practice entails fulfilling dietary diversity, meal frequency, early breastfeeding initiation, exclusive breastfeeding up to six months, and continued breastfeeding until the age of two [3,4]. At six months, an infant's energy and nutrient demand increases. Complementary feeding should be timely initiated, nutritionally adequate, and diverse to meet the child’s growing needs while continuing breastfeeding [5,6]. However, many infants and children do not receive adequate or appropriate feeding. Globally, only 44% of infants are exclusively breastfed for six months, 29.4% receive the minimum dietary diversity, and 52.2% receive the minimum required meal frequency [7]. In Ethiopia, only 59% of children aged 0-6 months were exclusively breastfed, and just 8% of infants aged 6–23 months received complementary foods while continuing breastfeeding. The 2019 Ethiopian Demographic and Health Survey (EDHS) reported minimum dietary diversity (MDD) at 14%, minimum meal frequency (MMF) at 55%, and minimum acceptable diet (MAD) at 11% [8,9]. A study conducted in the Somali regional state of Ethiopia revealed that 49.40% had optimal complementary feeding practices, with 57% initiating complementary feeding between 6–8 months, 52% achieving minimal meal frequency, and 45% attaining dietary diversity [10]. Similarly, a study conducted in the Jimma Zone of West Ethiopia found the overall proportion of optimal complementary feeding practices (OCFP) was 9.40% [11]. Several factors influence optimal breastfeeding and complementary feeding, including maternal knowledge gaps, perceived breast milk insufficiency, excessive workload, limited partner support, and food price inflation [12,13]. Childhood malnutrition remains a pressing issue in low- and middle-income countries, driven by inadequate nutrition and poor feeding practices in infancy [14]. Recognizing the importance of adequate and appropriate nutrition for child health and survival, the Ethiopian government implements health extension programs at the household and community level to improve optimal complementary feeding for children aged 6–23 months [15]. Despite child health being a priority under Ethiopia’s Health care development program [16], the national prevalence of appropriate complementary feeding practices among children aged 6–23 months was extremely low and is below international standards. There was evidence of gaps in optimal complementary feeding practices, and related factors are crucial for prioritizing, designing, and implementing intervention programs to reduce childhood undernutrition. Thus, this study aimed to assess optimal complementary feeding practices and associated factors among children aged 6–23 months in the Konzo Zone, South Ethiopia. 2.Materials and methods 2.1.Study settings and target population A community-based cross-sectional study was undertaken among 337 mothers who had children aged 6-23 months in Konso Zone, Southern Ethiopia, from May 10 to June 30, 2024. In this zone there are 3 districts, which consist of 3-5 health posts and 3-8 Kebeles. The Zone is characterized by rugged and rocky highlands cut by deep valleys. The altitude of the area is between 501 and 2000 meters above sea level, and the main agro-ecological divisions of Konso are 70% lowland and 30% tropical midland [17]. 2.2.Sample size determination and procedures The sample size was determined by using the single population proportion estimation formula. To calculate the actual sample size, a 30% proportion from a previous related study on optimal complementary feeding practice [18], 95% confidence level, 5% margin of error, and a 10% non-response rate were considered. The final sample size comprised 354 children aged 6 to 23 months paired with their mothers. Two districts were selected randomly from a total of 3 districts in the Konso Zone, South Ethiopia. In the case of Ethiopia, at least one health post was built for one to two kebeles for the provision of primary health care. From each district, one kebele that had a nearby health post was selected purposively. Then a census was conducted in two kebeles who had nearby health posts (the lowest administrative level in the case of Ethiopia) to register eligible households who had children aged 6-23 months. After getting the number of mothers who had children 6-23 months of age from all selected kebeles. The number of children assigned is based on the proportion of the size of the eligible population at all levels. Finally, the required number of mothers who had children in each kebele was selected randomly for interview. 2.3.Data collection tools and measurement A structured and pretested questionnaire was used to collect data on socio-demographic characteristics [19], dietary practices, and related characteristics. Data on dietary diversity and meal frequency data were collected by using a 24-hour recall method [20]. Mothers were asked to recall all food items given to their children in the past 24 hours before the day of the survey. According to the WHO 2021 guidelines, minimum dietary diversity for children 6-23 months was collected by using eight food groups: (1) grains, roots, or tubers; (2) legumes and nuts; (3) vitamin A-rich FV; (4) other fruits or vegetables; (5) flesh foods (meat, poultry, fish, organ meat); (6) eggs; (7) dairy products (milk, yogurt, cheese); and (8) breast milk [6]. In addition, the household food security was collected using the Household Food Insecurity Access Scale (HFIAS) to measure the degree of food security level in the past 30 days [21].Exchange of food items grown on their own land, including sorghum, maize, and moringa leaf cabbage. After selling this product, mothers purchase food items like avocados and some cereals like barley and wheat from local markets that are not cultivated in the area for preparing complementary diets [22]. Additional data was collected to measure household accessibility and availability of fruit and vegetables using questionnaires that measure the existence of different fruits and vegetables at home during the data collection period, either from their own agricultural cultivation or purchasing from local markets [23,24]. After pre-testing, the questionnaire was loaded onto Kobo Toolbox for face-to-face interviews at household level. 2.4. Data quality control Data quality was ensured in all phases of the research activities from methodological design to data analysis. The questionnaire was prepared in English first and then translated into Amharic for consistency for interviews. A pre-test was conducted on 5% of the total sample of the population of similar profiles but not included in the main study. Four health professionals who had previous data collection experience were recruited. Before actual data collection, training was provided to data collectors on the sampling procedures and interview techniques of the study. The data collectors and supervisors were also proficient in the local language.2.5. Operational measurement Optimal complementary feeding practice: Quantified using a composite indicator comprising three of the WHO core infant child feeding indicators that relate closely to complementary feeding. These are the timely introduction of solid complementary feeding, minimum dietary diversity, and minimum meal frequency. If a child fulfilled the above three criteria, classify them as having received optimal complementary food [6]. Minimum dietary diversity (MDD) score: Ranges from 0 to 8 diversified food groups. In this study, children who received 5 or more from 8 food groups within 24 hours were considered to have MDD [6]. Timely introduction of complementary feeding: Measured as the proportion of infants 6–23 months of age who received solid, semi-solid, or soft foods at 6 months [6]. Minimum meal frequency (MMF): Is the proportion of children who received at least the recommended minimum meal frequency appropriate for age in the last 24 hours prior to the survey: at least 2 feeding times daily for infants aged 6–8 months and at least 3 times daily for young children aged 9–23 months within 24 hours [6]. Food-insecure household: A household that experiences one of the three levels of food insecurity conditions mildly, moderately, or severely food insecure or access conditions in the past 4 weeks is categorized as food insecure [21]. Exchange of food items from the market: Measured using a questionnaire to assess household selling of food items produced by their own agricultural cultivation, such as sorghum, maize, and moringa leaf cabbage. After selling this agricultural own cultivation product, mothers purchase from the local market food items like avocado and some cereals like barley and wheat that are not cultivated in the area [22]. Accessibility and availability of fruit and vegetables: Accessibility and availability of fruits and vegetables were measured using questionnaires that measured the household existence of different fruits and vegetables, either from their own agricultural cultivation or from purchases at local markets during 24-hour recalls [23,24]. Nutrition education: measured using questionnaires that address whether a child's mother gets nutrition education about breast and complementary feeding during pregnancy, at the time of birth and in the postnatal period from health professionals and health extension workers. Then mother nutrition education status is categorized as getting nutrition education (Yes) if mothers get nutrition education by health professionals and health extension workers at health and community settings and not getting nutrition education (No) if those who did not get any nutrition education about child breast and complementary feeding by health professionals and health extension workers are categorized as not getting nutrition education (No) [25,26]. 2.6. Data Analysis Data was exported from Kobo Toolbox to an Excel sheet and SPSS version 26 for analysis. A descriptive analysis was conducted to characterize the data using frequencies, percentages, means, and standard deviations. Socio-demographic variables of the child, such as sex and age of the child, and the child’s mother’s education and occupation, were categorized based on related literature and biological classification [19,20]. The wealth index of households was measured using principal component analysis [27]. Kaiser–Meyer–Olkin (KMO; value of p > 0.05) and Bartlett’s test of sphericity (value of p < 0.05) were used to check the adequacy of the sample-to-factors ratio. The existence of a correlation between each item was determined for each step of factor analysis [28,29]. In PCA, factor scores were generated using variables with a commonality value greater than 0.5. Finally, the household’s wealth index was calculated as non-dummy variables were divided into three categories: highest, medium, and lowest household wealth index [28]. Multicollinearity was assessed by conducting variance inflation factor [30]. After testing, the multicollinearity variance inflation factor of variables was below 10 (VIF<10) and the SE was < 2. This result indicated there was no existence of multicollinearity among variable which entered to multivariable logistic regression model. Then binary logistic regression analysis was used to identify factors associated with optimal complementary feeding practices. In addition, before conducting multivariable logistic regression analysis Model fitness was tested by the Hosmer–Lemeshow test (P =0.638). All variables with a p-value less than 0.25 in the binary logistic regression analysis were included in the multivariable logistic regression analysis model. Variables with a p-value < 0.05 and AOR with a 95% Confidence Interval (CI) were considered statistically significant. 2.7. Ethical ConsiderationEthical clearance was obtained from the Hawassa University College of Medicine & Health Sciences institutional review board (Ref. No: IRB/045/16). Informed verbal assent was obtained from all mothers instead of their young children after a clear explanation about the purpose of the study. Then a permission letter was obtained from the Konso Zone Health Office. All the study participants were reassured that they would be anonymous. Names or any personal identifiers were not recorded. 3.Results 3.1.Socio-demographic characteristics of young children and womenA total of 337 women were involved in the study, giving a response rate of 95.19%. The mean age of young children was 13.86 + 5.207 months. In terms of sex of child, 52.50% of children were males and 47.50% were females. More than half of mother had two (61.70%) and above children and the rest 38.30% had one child. More than half of the mothers (58.5%) were aged between 25 and 34 years. Additionally, 75.4% of the respondents had no formal education (Table 1). Table 1: Socio-demographic characteristics of children’s and mothers in the Konso Zone, South Ethiopia, 2024. VariablesCategory Frequency Percentage SexMale17752.5Female16047.5< 1 under five child 129 38.2> two under five child 20861.7Age of child From 6-8 months9026.7From 9-11 months4112.2From 12-23 months20661.1Age of mother18-24 years7121.125-34 years19758.5above 35 years 6920.5Educational status of motherNo formal education25475.4Elementary education6619.6Secondary & above175Occupation of motherFarmer31192.3Government worker267.7Religion of motherOrthodox308.9Protestant 30791.1Wealth indexPoor13540.1Medium6719.9Rich13540.13.2.Optimal complementary feeding practices The prevalence of optimal complementary feeding practice was 14.80% (95% CI: 11.80%, 19.10%) of children. Of which, 92.60% had adequate meal frequency, 20.50% had good dietary diversity practice, and 63.20% had started complementary food at six months. Among all interviewed mothers, 20.50% fed their child five or more food items, and the rest, 79.5%, fed < 5 food items within 24 hours preceding the survey. The dominant food groups fed to their child were cereals, roots, and tubers, which accounted for 79.7%, but low feeding practice was observed in animal source foods (milk, meats, and eggs), and other fruits and vegetables were 7.7%, 13.6%, 15.7%, and 10.1%, respectively (Figure 1). Above half (52.20%) of the households were food secure, while the rest were food insecure with different severity: mildly insecure (9.2%), moderately insecure (27.00%), and severely food insecure (11.60%) (Figure 2). This figure indicates that half of the households in the study setting may face suboptimal dietary practices resulting either from limited access to food supply. This limited access to food supply affected dietary diversity and meal frequency. 3.3.Factors associated with optimal complementary feeding practicesAfter checking the basic assumption of the binary logistic regression model, multiple binary logistic regression models were fitted to identify significant factors. Mothers who were of advanced age (>35 years) (AOR=3.2; 95% CL 1.59, 6.95, P-value 0.001), exchange of food items from the market (AOR=2.23; 95% CL 1.03, 4.77, P-value 0.042), and accessibility and availability of fruit and vegetables (AOR=4.16; 95% CL 1.83, 9.43, P-value 0.001) were significantly associated with optimal complementary feeding practices (Table 2). Table 2: Multivariable logistic regression predicting the likelihood of optimal complementary feeding practices among 6-23 months of children in the Konso Zone, Southern Ethiopia, 2025. Variables Optimal complementary feeding practices COR with 95% Cl AOR 95% CI P-valuesYesNo LCLUCLLCLUCL Age of childFrom 6-8 months14(28.0%)76 (26.5%)11From 9-11 months10(20.0%)31 (10.8%)0.570.231.420.590.221.610.058From 12-23 months26(52.0%)180 (62.7%)1.270.632.58 2.160.974.780.505 Sex of child Male 27(54.0%)150(52.3%) 1.070.591.960.590.221.610.505 Female 23(46.0%)137 (47.7%) 11Age of mothers 18- 34 Years31(62.0%)237 (82.6%)11 0.001** > 35 Years19(38.0%) 50 (17.4%)2.911.525.553.321.596.95Wealth index Poor 19(38.0%)116 (40.4%)1Medium 5 (10.0%)62 (21.6%)1.460.762.780.970.4701.990.931Rich 26(52.0%)109 (38.0%)2.961.08 8.092.470.8447.240.099 Number of under five children Having one child 21(42.0%) 108 (37.6%)11Having more than one children 29(58.0%)179 (62.4%)1.200.652.211.240.632.460.524 Getting Nutrition education Yes17(34.0%)66(23.0%)1.73 0.903.291.730.833.610.147 No 33(66.0%)221 (77.0%)11Exchange of food items from market Yes14 (28.0%)36 (12.5%)2.711.335.512.231.034.770.042** No36(72.0%)251(87.5%) 11 Accessibility and availability of fruit and vegetables Yes9(18.0%)131 (45.6%)3.83 1.798.164.161.839.430.001** No41(82.0%)156(54.4%)1 1 Food security status Food Security30(60.0%) 177 (61.7%)0.930.511.720.670.341.340.261 Food insecurity 20(40.0%) 110 (38.3%) 11** Significant factors (p-value <0.05). 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