Identifying Predictors of Childhood Anaemia in North-East India

Abstract

Almost 34% of the world population suffers from iron deficiency, with 80% belonging to developing countries where the prevalence of anaemia and iron deficiency is approximately 40% whereas, in developed countries, the occurrence of anaemia is lower than 10% (4). WHO lists iron-deficiency anaemia (IDA) as one of the "top ten risk factors contributing to death" (5). IDA is prevalent in South Asia, predominantly in India, Bangladesh, and Pakistan. However, the prevalence of IDA in Bangladesh and Pakistan has declined to 55% (6). The waning prevalence of IDA is remarkable in the case of China where the occurrence rate has plummeted from 20% to 8% within a decade (7). It is difficult to ascertain the true incidence of IDA as the aetiology of anaemia is multifactorial. A largescale study conducted by Indian Council of Medical Research (ICMR) found that about 53% of children were anaemic (8). A study by National Family Health Survey-2 (NFHS-2) (9) found the occurrence INTRODUCTIONChildhood anaemia is a major public-health concern, with an increasing risk of mortality. Ministry of Health and Family Welfare, Government of India, reports that it is one of the most common diseases due to nutritional deficiency in the world today, and more than half of the population in India is anaemic. The prevalence of anaemia is as high as 70-80% among children and 60% among pregnant women (1). Anaemia is a common conundrum of nutritional deficiency worldwide, and its prevalence is higher in developing countries than developed countries (2,3). Identifying Predictors of ChildhoodAnaemia in North-East India ABSTRACTThe objective of this study is to examine the factors that influence the occurrence of childhood anaemia in North-East India by exploring dataset of the Reproductive and Child Health-II Survey (RCH-II). The study population consisted of 10,137 children in the age-group of 0-6 year(s) from North-East India to explore the predictors of childhood anaemia by means of different background characteristics, such as place of residence, religion, household standard of living, literacy of mother, total children ever born to a mother, age of mother at marriage. Prevalence of anaemia among children was taken as a polytomous variable. The predicted probabilities of anaemia were established via multinomial logistic regression model. These probabilities provided the degree of assessment of the contribution of predictors in the prevalence of childhood anaemia. The mean haemoglobin concentration in children aged 0-6 year(s) was found to be 11.85 g/dL, with a standard deviation of 5.61 g/dL. The multiple logistic regression analysis showed that rural children were at greater risk of severe (OR=2.035; p=0.003) and moderate (OR=1.23; p=0.003) anaemia. All types of anaemia (severe, moderate, and mild) were more prevalent among Hindu children (OR=2.971; p=0.000), (OR=1.195; p=0.010), and (OR=1.201; p=0.011) than among children of other religions whereas moderate (OR=1.406; p=0.001) and mild (OR=1.857; p=0.000) anaemia were more prevalent among Mus...

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Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda

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Prevalence of Undernutrition and Anemia among Santal Adivasi Children, Birbhum District, West Bengal, India

“…There are additional studies on predictors for anemia: an exploration of data of the Reproductive and Child Health-II Survey on children up to six years old, living in the northeastern states of India, revealed the male gender, a low to medium HH living standard, as well as maternal parity increasing the risk of anemia and children of literate mothers had a decreased risk for severe anemia [90]. More than half of a total of 16 surveys including cross-sectional data of different countries (amongst others in Bangladesh) suggest the following predictors for anemia: child's age, current performance of any breastfeeding (both inversely related), malaria, iron deficiency, stunting, underweight, inflammation, low socioeconomic status and poor sanitation [91].…”