The contribution of dietary and non-dietary factors to socioeconomic inequality in childhood anemia in Ethiopia: a regression-based decomposition analysis

Mohammed, Shimels Hussien; Muhammad, Fatima; Esmaillzadeh, Ahmad

doi:10.1186/s13104-019-4691-4

Cited by 8 publications

(10 citation statements)

References 17 publications

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“…Almost half of the sample were found to have mean hemoglobin levels below the WHO cutoff value for anemia ( 1 ). The results of the present study indicate that there is an interlinked association between nutritional intake and sociodemographic factors in the development of the disease, which is consistent with other studies ( 11 , 18 , 41 ). The sole deficiency of certain nutrients is rarely found as a single nutritional anemia associated factor.…”

Section: Discussionsupporting

confidence: 93%

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Cluster Analysis and Classification Model of Nutritional Anemia Associated Risk Factors Among Palestinian Schoolchildren, 2014

Qasrawi

Al-Halawa

2022

Front. Nutr.

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Nutritional inadequacy has been a major health problem worldwide. One of the many health problems that result from it is anemia. Anemia is considered a health concern among all ages, particularly children, as it has been associated with cognitive and developmental delays. Researchers have investigated the association between nutritional deficiencies and anemia through various methods. As novel analytical methods are needed to ascertain the association and reveal indirect ones, we aimed to classify nutritional anemia using the cluster analysis approach. In this study, we included 4,762 students aged between 10 and 17 years attending public and UNRWA schools in the West Bank. Students' 24-h food recall and blood sample data were collected for nutrient intake and hemoglobin analysis. The K-means cluster analysis was used to cluster the hemoglobin levels into two groups. Vitamin B12, folate, and iron intakes were used as the indicators of nutrient intake associated with anemia and were classified as per the Recommended Dietary Allowance (RDA) values. We applied the Classification and Regression Tree (CRT) model for studying the association between hemoglobin clusters and vitamin B12, folate, and iron intakes, sociodemographic variables, and health-related risk factors, accounting for grade and age. Results indicated that 46.4% of the students were classified into the low hemoglobin cluster, and 60.7, 72.5, and 30.3% of vitamin B12, folate, and iron intakes, respectively, were below RDA. The CRT analysis indicated that vitamin B12, iron, and folate intakes are important factors related to anemia in girls associated with age, locality, food consumption patterns, and physical activity levels, while iron and folate intakes were significant factors related to anemia in boys associated with the place of residence and the educational level of their mothers. The deployment of clustering and classification techniques for identifying the association between anemia and nutritional factors might facilitate the development of nutritional anemia prevention and intervention programs that will improve the health and wellbeing of schoolchildren.

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Section: Discussionsupporting

confidence: 93%

“…In this study, we acquired hemoglobin levels as an indicator of anemia. The use of hemoglobin as a single anemia parameter has been applied in various research studies ( 10 , 38 , 41 ). In this study, the K-means clustering method was used for identifying the hemoglobin groups ( 42 ).…”

Section: Methodsmentioning

confidence: 99%

Cluster Analysis and Classification Model of Nutritional Anemia Associated Risk Factors Among Palestinian Schoolchildren, 2014

Qasrawi

Al-Halawa

2022

Front. Nutr.

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“…The problem of child malnutrition is highly concentrated in low and middle income countries, whereby at least one-third of children are malnourished [4,5]. South Africa has come a long way in eradicating poverty and malnutrition [6].…”

Section: Introductionmentioning

confidence: 99%

A Review of Selected Studies on the Factors Associated with the Nutrition Status of Children Under the Age of Five Years in South Africa

Mkhize

Sibanda

2020

IJERPH

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Malnutrition is a considerable contributor to child mortality and morbidity. Child malnutrition further affects the country’s economic development. Child malnutrition in South Africa is persistent, continuing to be an alarming burden. The nutritional status of kids under the age of five years is a critical indicator of the country’s economic condition and health status. An understanding of the influencers of the nutritional status of children can act as a catalyst in combatting all forms of malnutrition. The purpose of this paper was to review selected studies concerning the factors that affect the nutritional status of children in South Africa. Studies were selected from electronic databases, which were PubMed, Google Scholar, Science Direct, Sabinet African Journals, and the University of Zululand library catalog. The keywords that were used to search studies and articles from the selected database were: risk factors, child nutritional status, children under the age of five years, South Africa, malnutrition, underweight, stunted, wasting, and over-nutrition. Studies and surveys published from 2010–2019 that reported on the factors influencing the nutritional status of children under the age of five years were included in this review. Twenty-seven articles met the inclusion criteria of the study. The 27 articles were made up of 21 cross-sectional articles and six longitudinal articles. The finding from this review highlights that there is a lack of studies conducted in urban areas. The results show that the nutritional status of children is affected by several factors. These include household food insecurity, low household income, illiterate caregivers, unemployment, inadequate dietary intake, low birth weight, consumption of monotonous diets, poor caregiver’s nutritional knowledge, poor access to water and sanitation, poor weaning practices, age of the caregiver, and demographic characteristics of a child (age and gender). It is critical to have an understanding of the factors that affect the nutritional status of children. Such knowledge can significantly contribute to formulating policies that can enhance nutrition security and the country’s economy. Moreover, insights into strategic interventions to eradicate all forms of malnutrition can be made.

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“…Household wealth index was significantly associated with the anemia status of children (p < 0.0001). This association is supported by some studies [13,24,25], however, other studies in Ethiopia [14,26,27] have reported that there was no statistically significant relationship between household wealth and anemia. The strength of association between anemia and wealth quintile increased from weak (χ 2 = 61.6, V = 0.079) in 2011 to moderate (χ 2 = 166.9, V = 0.134), moreover, the gap between the highest and lowest quintiles increased from 12% in 2011 to 20% in 2016 (Table 1).…”

Section: Discussionmentioning

confidence: 65%

What factors are associated with the increase of anemia in Ethiopian children aged 6 to 59 months between 2011 and 2016?

Amaha

2020

BMC Nutr

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Background In Ethiopia more than half of the children under 5 years are anemic and between 2011 and 2016 anemia in children under-5 increased by 28.7%. This study aimed to analyze this increase in anemia by socio-demographic characteristics. Method This study was a secondary analysis of the data from the Ethiopian Demographic Health Surveys (EDHS) for 2011 and 2016. The increase of anemia was calculated using percentage change. The chi-square test was used to determine the association between anemia and six predictor variables of age, sex, mother’s educational level, residence, wealth quintile and region. The strength of association was measured using Cramer’s V. Results Anemia increased in all age groups, both sexes, urban and rural residencies, across all wealth quintiles, all maternal education levels and all regions of Ethiopia except Benishangul Gumuz. The highest increase of anemia was seen among children born to mothers with above secondary education (65.8%), living in urban areas (40.1%), in the lowest wealth quintile (41.5%), and children from Tigray region (42.9%). Severe anemia increased in all age categories except in infants aged 9–11 months. Children of mothers with above secondary educational level had the highest increase of mild and moderate anemia. Severe anemia decreased in the second and middle wealth quintiles whereas it increased in the rest quintiles. Benishangul Gumuz is the only region where mild, moderate, and severe anemia decreased. Pearson’s chi-square (χ2) test showed that all the predictor variables except sex were significantly associated with anemia. Although highly significant (p < 0.001) using the chi-square test, Cramer’s V showed that residence (V = 0.052–0.066) and maternal education (V = 0.041–0.044) were only weakly associated with anemia. Conclusion Anemia in children under-5 continues to be a severe public health problem in Ethiopia. Benishangul Gumuz region is the only region that was able to reduce the prevalence of all forms of anemia under-5 between 2011 and 2016, consequently other regions of Ethiopia could learn from this experience. The high increase of anemia in children born to mothers with above secondary education and highest wealth quintiles points to poor dietary practices, therefore, community based nutrition education for mothers needs to be strengthened.

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The contribution of dietary and non-dietary factors to socioeconomic inequality in childhood anemia in Ethiopia: a regression-based decomposition analysis

Cited by 8 publications

References 17 publications

Cluster Analysis and Classification Model of Nutritional Anemia Associated Risk Factors Among Palestinian Schoolchildren, 2014

Cluster Analysis and Classification Model of Nutritional Anemia Associated Risk Factors Among Palestinian Schoolchildren, 2014

A Review of Selected Studies on the Factors Associated with the Nutrition Status of Children Under the Age of Five Years in South Africa

What factors are associated with the increase of anemia in Ethiopian children aged 6 to 59 months between 2011 and 2016?

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