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Background: In Ethiopian, the prevalence of anemia among preschool aged children widely varied across regions. Since anemia adversely affects the cognitive and physical development of the children, it is important to determine its burden for implementing appropriate measurements. Therefore, this study was aimed at determining the anemia prevalence and associated factors among preschool aged children. Method: A community based cross-sectional study was conducted on a total of 432 preschool children in Menz Gera Midir district from January to May, 2017. A multi stage sampling procedure was applied to select the target groups. Hemocue analyzer for Haemoglobin determination; anthropometric measurements for assessment nutritional status, structured questionnaires for socio-demographic and economic variables were used for data collection. The morphological appearance of red blood cell was assessed microscopically to determine type of anemia. Descriptive statistics were employed to summarize the data and binary logistic regression was used for inferential statistics. A p value less than 0.05 was considered as statistically significant. Result: The overall prevalence of anemia was 123 (28.5%); of which 38 (30.9%) and 85 (69.1%) were moderate and mild, respectively. Morphologically about 50.4, 37.4 and 12.2% were microcytic hypochromic, normocytic normochromic and macrocytic anemias, respectively. Child age 6-11 months (COR: 5.67, 95% CI: 2.2, 14.86), child age 12-23 months (COR: 5.8, 95% CI: 2.3, 14.7), wasting (COR: 3.5, 95% CI: 1.2, 9.8), stunting (COR: 3.8, 95% CI: 1.92, 7.77), underweight (COR: 2.12, 95% CI: 1.07, 4.38), MUAC measurement below 13 cm (COR: 5.6, 95% CI: 2.83, 11.15), household headed by female (COR: 3.24, 95% CI: 1.1, 9.63), maternal anemia (COR: 4, 95% CI: 2.2, 7.23) and household food insecurity (COR: 2.12, 95% CI: 1.09, 4.12) were significantly associated with anemia. Conclusion: The prevalence of anemia among the children was found to be high and associated with child age group, child nutritional status, house hold headed by female, maternal anemia and household food insecurity. Further studies on nutritional anemia, community based nutritional education, iron supplementation to children at risk should be promoted.
A community based cross-sectional study was conducted on a total of 432 preschool children in Menz Gera Midir district from January to May, 2017. The district is located in Semien Shewa Zone, Eastern Amhara state, Ethiopia. The administrative center of this district is Mehal Meda town which is located 295 km away from Addis Ababa and 165 km from its zonal town (Debre Birhan). The town is also elevated 3037 m above sea level with latitude/longitude of 10018′17″ N/390 39′ 31″E. According to the population projection of Ethiopia from 2014 to 2017, this district has a total population of 138,708 with 16,361(11.8%) urban inhabitants [18]. Children aged 6–59 months reside in the selected kebeles for at least 6 months and whose parents/guardians are willing to fully participate in the study were included. While, children with active hemorrhage, history of blood transfusion within the last 2 months, history of surgery within the last 2 months were excluded from the study. To determine the required sample size for study, a single population proportion formula was used as denoted below Where z = Z score for 95% confidence interval, which is 1.96 p = expected prevalence of anemia, which was 25% taken from Menz Keya [19]. d = tolerable error between the sample and true population, which is 5% Considering affordable resources for investigations, a design effect of 1.5 for sampling error was taken and 288*1.5 = 432 children were included. A multi-stage sampling procedure was used; at the first stage, sample was determined to collect from one fourth of the total kebeles; out of 28 kebeles, seven kebeles (1 urban and 6 rural) were selected randomly. Kebele (neighbourhood) is the smallest administrative unit in Ethiopia. At the second stage, the number of households included from each kebeles were proportionally allocated. Then a systematic sampling method was used to select each household (Fig. 1). The total numbers of households in each kebele was taken from each administrative kebele and used to calculate the sampling interval (K) which was 26. After the first household randomly selected, households every 26th interval were approached. If a household was with two or more eligible childern, only one of them was chosen randomly by lottery method. On the otherhand, when the selected household was closed even after revisit or child was not eligible, the next household was included. Schematic representation of sampling procedure. N.B: K = kebele, SRS: Systematic random sampling, nf: final sample size A pretested structured questionnaire which was prepared based on the national survey questionnaire and accordingly modified based on the reviewed literature [20] was used. The questionnaire consisted of socio-demographic characteristics of the child and their parents, household food security status (HFSS), child feeding practices, food consumption pattern and health condition of the children. Household food security (HHFS) status was assessed by using the standardized questionnaire developed by Food and Nutritional Technical Assistance (FANTA) [21, 22]. Food consumption pattern and dietary diversity scores (DDS) were determined by using a modified Helen Keller International Food Frequency Questionnaire (FFQ) and a 24-h dietary recall, respectively [22–24]. Altitude for each kebele was measured using an accurate altimeter app android installed on smart phone. Wealth index was determined to assess inequalities in household characteristics, in the use of health and other services. It used as an indicator of level of household wealth. The index was determined using household assets and type of house. A principal component analysis (PCA) was used to produce a common factor score for each household. Variables were coded between 0 and 1, entered and analyzed. Then variables with communality values of > 0.5 were used to produce factor scores. Factor scores were summed and categorized into three relative measures of socio economic status of households as low, medium and rich [22]. The Food and Nutritional Technical Assistance (FANTA) scale guideline questions were used to assess household food security status. The questionnaire was adapted from household food insecurity access scale and validated for developing countries. A household was considered as food secured if it had experience of less than the first 2 food insecurity indicators from the 27. Each question was responded as never, rarely, sometimes, or often. Households were considered as “food secure,” if they “never” or “rarely” worried about the deficiency of food in their households [21, 25]. Food frequency was assessed with a questionnaire consisted of ten groups of food items was used. The food items were grouped in to cereals, legumes, meat, egg, vegetables, fruits, dairy products, fish and sea foods, sweet foods made with sugar, honey, oil, fat, or butter and any other foods, such as condiments, coffee, tea. Then dietary diversity scores (DDS) was calculated from these food groups and categorized as high (DDS ≥ 7), medium (DDS = 4–6), and low (DDS ≤ 3) [22]. Child age, weight, height and mid-upper arm circumference (MUAC) were measured according to the 2008 WHO recommendation for nutritional status assessment [26]. All Childrens’ weight was measured while wearing light-weight cloth with a portable weight scale to the nearest 0.1 kg. The weighing scale was calibrated using the standard calibration weight of 2 kg iron bars. Child height was measusered using a locally manufactured wooden standiometre with a sliding head bar to the nearest 0.1 cm in Frankfurt position (head, shoulder, buttocks, knee, and heals touch the vertical board). Children height aged below 24 months was taken while lying down and for those older children heights were measured at standing position. Measurements of weight and height were taken twice and the average was recorded. Then the data were entered into WHO Anthro 3.2.2.1 for the calculation of weight-for-age (WAZ), weight-for-height (WHZ) and height-for-age (HAZ) standard Z-scores. Children were classified as stunted, underweight and wasted when HAZ, WAZ and WHZ scores were 3000 m above sea level, results of Hgb were adjusted to its respective sea level by subtracting 1.9 g/dL as it is recommended by WHO [28]. Anemia was defined when Hgb level is < 11 g/dL for both genders. Regarding to anemia severity Hgb value of 10 to 10.9 g/dL, 7 to 9.9 g/dL and < 7 g/dL were considered as mild, moderate and severe anemia, respectively [28]. The morphological characteristics of RBC were assessed by using 100x (oil immersion) high magnification power light microscope. The type of anemia then was classified based on the characteristics of RBC morphology as microcytic, normocytic and macrocytic anemias. For intestinal parasite examination, stool samples were collected from study participants and wet mount was prepared by using normal saline for direct microscopy. The remaining portion of the collected sample was preserved by using 10% formalin andconcentration techniques. Finally, examination of stool by using concentration technique for ova or parasite was performed within 24 h of collection. Firstly, data were checked for completeness and coded manually. After coding, data were double entered and stored using EPI-info 7 and exported to SPSS 20 for further analysis. Descriptive statistics were used to summarize the characteristics of the study population. To determine factors associated with anemia, bivariate logistic regression analyses was done and the 95% confidence (CI) level was used determined the strength of association between the predictors and dependent variables. Those variables with a P value of < 0.2 in bivariate analysis were fitted in to multivariate logistic regression analysis. A P value < 0.05 in multivariable analysis was considered as statistically significant.
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