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Background: Anemia is a public health problem affecting both developed and developing countries. Childhood anemia is associated with serious consequences including growth retardation, impaired motor and cognitive development, and increased morbidity and mortality. Hence, this study aimed at assessing the prevalence and factors associated with severity of anemia among children aged 6-59 months in Gondar town, northwest Ethiopia. Method: A community-based cross-sectional study was conducted. A multi-stage sampling technique was employed to select study participants. Socio demographic and socioeconomic data were collected using a pre-tested structured questionnaire. Anthropometric measurements were taken as per WHO recommendation. Hemoglobin (Hb) concentration was measured using a portable HemoCue301 instrument (A Quest Diagnostic Company, Sweden). Mild anemia corresponds to a level of adjusted Hb of 10.0-10.9 g/dl; moderate anemia corresponds to a level of 7.0-9.9 g/dl, while severe anemia corresponds to a level less than 7.0 g/dl. Descriptive statistics were used to describe the study participants. Both bivariable and multivariable ordinal logistic regression were done, and proportional odds ratio (POR) with a 95% confidence interval (CI) was reported to show the strength of association. A p-value < 0.05 was considered statistically significant. Result: Out of the total of 707 children included in this study, more than half (53.5%) of them were male. The median age of children was 30 months. Two hundred two (28.6%) of children were anemic: 124(17.5%) were mildly anemic, 73(10.3%) were moderately anemic, and 5 (0.7%) were severely anemic. The young age of the child, low frequency of child complementary feeding per day, primary maternal educational status, unmarried maternal marital status, and home delivery were factors associated with severity of childhood anemia. Conclusion: Anemia among children aged 6-59 months in Gondar Town was a moderate public health problem. Improving access to education, providing regular health education about childcare and child feeding practices, strengthening the socioeconomic support for single-parent families and conducting regular community-based screening are recommended to reduce childhood anemia.
A community-based cross-sectional study was conducted in April 2015 among children aged 6–59 months in Gondar town, northwest Ethiopia. A sample size of 735 was calculated by single population proportion formula, considering estimated prevalence of anemia (35.1%) among children aged 6–59 month in Amhara region [4], 95%CI, 5% margin of error, design effect of 2, and 5% non- response rate. A multi-stage random sampling technique was employed to select study participants in two stages. At the first stage, four out of twelve kebeles (smallest administrative units) (i.e. 30% of the total area) were selected by simple random sampling technique. At the second stage, a total of 735 households were selected using a systematic random sampling method with proportional allocation to each selected kebeles. The total number of households with children aged between 6 and 59 months was obtained from the respective administrative areas and used to calculate the sampling fraction. In the case where more than one children were found eligible in the selected households, only one of them was chosen randomly using the lottery method. A pretested structured questionnaire was used to collect socio-demographic and economic data from mothers by face-to-face interview. Anthropometric measurements such as weight and height were measured for children according to the 2006 WHO recommendation [24]. Z-scores for weight-for-age (WAZ), height-for-age (HAZ), and weight-for-height (WHZ) were calculated using WHO Anthro software. Nutritional status was defined as underweight if WAZ was less than − 2 standards deviation (SD), stunting if HAZ was less than -2SD, and wasting if WHZ was less than -2SD [25]. Body mass index (BMI) was also calculated for the mothers according to the WHO STEP-wise surveillance manual [26]. Hb was measured by a portable HemoCue301 instrument (A Quest Diagnostic Company, Sweden) from capillary blood. HemoCue method of Hb determination is recommended by WHO to determine population prevalence of anemia, and several studies have established the validity of this instrument [24, 27]. After adjusting Hb concentration for altitude, anemia was defined as mild if Hb was between 10 and 10.9 mg/dl, moderate if between 9.9 and 7 g/dl, and severe if < 7 g/dl [24]. The questionnaire was prepared in English, translated to Amharic and then translated back to English to check for consistency. Data were collected by trained data collectors (BSC nurses and senior medical laboratory technologists) after training was given about the objective of the study, confidentiality issues, study participants’ right, consenting, techniques of interview, and Hb and anthropometric measurements. The data collection process was closely supervised by investigators. All measurements were performed by following the manufacturers’ recommendation. Data were entered using Epi Info version 3.5.3 statistical software, and then exported to SPSS version 20 for analysis. Descriptive statistics including frequencies, percentages, median, and interquartile range were performed to describe the study participants. The bi-variable and multi-variable proportional odds model (POM), the most widely used family of ordinal logistic regression in epidemiological studies, was fitted to identify factors associated with severity of childhood anemia. The proportionality assumptions for POM were checked using Chi-square parallel line tests, (p-value = 0.791) indicating that the assumption was not violated. The Pearson chi-square goodness-of-fit test showed that the model fitted the data well (p = 0.152). All variables with a p-value ≤ 0.2 in the bivariable analysis were fitted into the multivariable analysis to control confounding effects. Adjusted proportional odds ratio (aPOR) with a 95% CI was used to evaluate the strength of statistical association between explanatory and outcome variables. All variables with p-values < 0.05 in the multi-variable analysis were considered to be statistically significant.
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