E Stativa1, A V Rus2, A Stanescu1, J S Pennings3, S R Parris4, R Wenyika5. 1. The Institute for Mother and Child Care 'Alfred Rusescu', Bucharest, Romania. 2. Department of Social and Behavioral Sciences, Southwestern Christian University, 7210 NW 39th Expressway, Bethany, OK 73008, USA. 3. Elite Research, LLC, Irving, TX 75063, USA. 4. Institute of Child Development, Texas Christian University, Fort Worth, TX 76129, USA. 5. African Institute of Biomedical Sciences and Technology, Harare, Zimbabwe.
Abstract
BACKGROUND: Anaemia is a public health problem that can lead to a variety of detrimental effects on physical and neurodevelopment in young children. The present study explored the epidemiology of anaemia among infants in Romania, identified risk factors and created a model for predicting it. METHODS: Data from 1532 infants aged 6-24 months were selected from a larger nationally representative cross-sectional survey. Demographic predictor variables and haemoglobin concentration were extant variables in the data set. Multiple logistic regression was used to determine the best predictors of anaemia. RESULTS: Overall, 46% of 6-24 month olds in the sample had anaemia (Hb < 11.0 g/dl). A variety of risk factors were associated with significantly greater odds of anaemia, but a five-factor model best predicted it (67.9% accuracy). These predictors included being male, living in a rural area, being third born or later, being a Hungarian and living in the South, South-West or West region of Romania. CONCLUSIONS: While data indicate a modest decrease in anaemia from earlier Romanian studies, it remains a significant problem. Models like this one have the potential to improve identification and treatment of anaemia in young children.
BACKGROUND:Anaemia is a public health problem that can lead to a variety of detrimental effects on physical and neurodevelopment in young children. The present study explored the epidemiology of anaemia among infants in Romania, identified risk factors and created a model for predicting it. METHODS: Data from 1532 infants aged 6-24 months were selected from a larger nationally representative cross-sectional survey. Demographic predictor variables and haemoglobin concentration were extant variables in the data set. Multiple logistic regression was used to determine the best predictors of anaemia. RESULTS: Overall, 46% of 6-24 month olds in the sample had anaemia (Hb < 11.0 g/dl). A variety of risk factors were associated with significantly greater odds of anaemia, but a five-factor model best predicted it (67.9% accuracy). These predictors included being male, living in a rural area, being third born or later, being a Hungarian and living in the South, South-West or West region of Romania. CONCLUSIONS: While data indicate a modest decrease in anaemia from earlier Romanian studies, it remains a significant problem. Models like this one have the potential to improve identification and treatment of anaemia in young children.