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INCIDENCE OF, AND RISK FACTORS FOR, MALNUTRITION AMONG CHILDREN AGED 5–7 YEARS IN SOUTH INDIA

Published online by Cambridge University Press:  06 October 2015

Visalakshi Jeyaseelan
Affiliation:
Department of Biostatistics, Christian Medical College, Vellore, India
Lakshmanan Jeyaseelan*
Affiliation:
Department of Biostatistics, Christian Medical College, Vellore, India
Bijesh Yadav
Affiliation:
Department of Biostatistics, Christian Medical College, Vellore, India
*
1Corresponding author. Email address: [email protected]

Summary

Protein–energy malnutrition is a major health problem contributing to the burden of disease in developing countries. The aim of this study was to assess the incidence of, and risk factors for, malnutrition among school-going children in south India. A total of 2496 children aged 5–7 years from rural and urban areas of south India were recruited in 1982 and followed up for malnutrition over a period of 9 years. Their body heights and weights were measured every six months and socio-demographic factors such as mother’s education and father’s education and relevant household characteristics and hygiene practices collected. Body mass index and height-for-age z-scores were used to determine children’s levels of underweight and stunting, respectively, classified as normal, mild/moderate or severe. Risk factor analysis was done for pre-pubertal ages only using Generalized Estimating Equations with cumulative odds assumption. There was a significant difference between male and female children in the incidence of severe underweight and stunting (6.4% and 4.2% respectively). Children in households with no separate kitchen had 1.3 (1.0–1.6) times higher odds of being severely underweight (p=0.044) compared with those with a kitchen. Children without a toilet facility had significantly higher odds of severe underweight compared with those who did. Children with illiterate parents had higher odds of severe stunting than those with literate parents. In conclusion, the prevalence of malnutrition among these south Indian children has not changed over the years, and the incidence of severe malnutrition was highest in children when they were at pubertal age. The risk factors for stunting were mostly poverty-related, and those for underweight were mostly hygiene-related. Adolescent children in south India should be screened periodically at school for malnutrition and provided with nutritional intervention if necessary.

Type
Research Article
Copyright
Copyright © Cambridge University Press, 2015 

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References

Ahmad, S. & Talat, P. (2013) Cross section study of malnutrition in children of 1–10 years age group in urban slums of Aligarh. Global Journal of Medical Research 13, 4144.Google Scholar
Baitun, N., Tahmeed, A., Kenneth, B. H. & Iqbal, H. M. (2010) Risk factors associated with severe underweight among young children reporting to a diarrhoea treatment facility in Bangladesh. Journal of Health and Population Nutrition 5, 476483.Google Scholar
Ballinger, G. A. (2004) Using generalized estimating equations for longitudinal data analysis. Organizational Research Methods 7, 127150.Google Scholar
Behrman, J. R. (1996) The impact of health and nutrition on education. World Bank Research Observer 11, 2337.Google Scholar
Bellamy, C. (2002) The State of the World’s Children. United Nations Children’s Fund. URL: http://www.unicef.org/sowc/archive/2002.pdf Google Scholar
Berkman, D. S., Lescano, A. G., Gilman, R. H., Lopez, S. L. & Black, M. M. (2002) Effects of stunting, diarrhoeal disease, and parasitic infection during infancy on cognition in late childhood: a follow-up study. Lancet 359, 564571.Google Scholar
Black, M. M. (2003) Micronutrient deficiencies and cognitive functioning. Journal of Nutrition 133, 3927S3931S.Google Scholar
De Onís, M., Blössner, M., Borghi, E., Morris, R. & Frongillo, E. A. (2004) Methodology for estimating regional and global trends of child malnutrition. International Journal of Epidemiology 33, 12601270.Google Scholar
De Onís, M., Monteiro, C., Akré, J. & Glugston, G. (1993) The worldwide magnitude of protein-energy malnutrition: an overview from the WHO Global Database on Child Growth. Bulletin of the World Health Organization 71, 703712.Google Scholar
Engle, P. L. & Fernández, P. D. (2010) INCAP studies of malnutrition and cognitive behavior. Food and Nutrition Bulletin 31, 8394.CrossRefGoogle ScholarPubMed
Faridi, M. M., Gupta, P. & Prakash, A. (1995) Lung functions in malnourished children aged five to eleven years. Indian Pediatrics 32, 3542.Google Scholar
Ghosh, S. & Shah, D. (2004) Nutritional problems in urban slum children. Indian Pediatrics 41, 682696.Google Scholar
Gopalan, C. (2010) Time trends in the nutritional status of Indians from NNMB surveys. Delhi. Nutrition Foundation of India. URL: nutritionfoundationofindia.res.in/pdfs/.../Pages_from_April_2010_2.pdf Google Scholar
Grantham-McGregor, S. (1995) A review of studies of the effect of severe malnutrition on mental development. Journal of Nutrition 125, 22332238.Google Scholar
Hanley, J. A., Negassa, A., Edwardes, M. D. de B & Forrester, J. E. (2003) Statistical analysis of correlated data using generalized estimating equations: an orientation. American Journal of Epidemiology 157, 364375.Google Scholar
Jeyaseelan, L. & Lakshman, M. (1997) Risk factors for malnutrition in south Indian children. Journal of Biosocial Science 29, 93100.Google Scholar
Kain, J., Uauy, R., Lera, L., Taibo, M. & Albala, C. (2005) Trends in height and BMI of 6-year-old children during the nutrition transition in Chile. Obesity Research 13, 21782186.CrossRefGoogle ScholarPubMed
Kar, B. R., Rao, S. L. & Chandramouli, B. A. (2008) Cognitive development in children with chronic protein energy malnutrition. Behavior and Brain Function 4, 3143.CrossRefGoogle ScholarPubMed
Khalil, S. & Khan, Z. (2004) A study of physical growth and nutritional status of rural school going children of Aligarh. Indian Journal of Preventive and Social Medicine 35, 9098.Google Scholar
Kikafunda, J. K., Walker, A. F., Collett, D. & Tumwine, J. K. (1998) Risk factors for early childhood malnutrition in Uganda. Pediatrics 102, 18.Google Scholar
Krishnaveni, G. V., Veena, S. R., Hill, J. C., Karat, S. C. & Fall, C. H. (2014) Cohort profile: Mysore Parthenon Birth Cohort. International Journal of Epidemiology. doi:10.1093/ije/dyu050.Google ScholarPubMed
Mushtaq, M. U., Gull, S., Mushtaq, K., Abdullah, H. M., Khurshid, U., Shahid, U. et al. (2012) Height, weight and BMI percentiles and nutritional status relative to the international growth references among Pakistani school-aged children. BMC Pediatrics 12, 111.Google Scholar
National Family Health Survey (2005–06) The National Family Health Survey-3. URL: http://hetv.org/india/nfhs/index.html Google Scholar
Neelu, S., Bhatnagar, M., Garg, S. K, Chopra, H. & Bajpai, S. K. (2009) Nutritional status of urban primary school children in Meerut. Internet Journal of Epidemiology 8, ispub.com/IJE/8/1/6867 Google Scholar
Owor, M., Tumwine, J. K. & Kikafunda, J. K. (2000) Socio-economic risk factors for severe protein energy malnutrition among children in Mulago Hospital, Kampala. East African Medical Journal 77, 471475.Google Scholar
Raj, M., Sundaram, K. R., Paul, M., Sudhakar, A. & Kumar, R. K. (2009) Dynamics of growth and weight transitions in a pediatric cohort from India. Nutrition Journal 8, 5565.Google Scholar
Twisk, J. W. R. (2003) Applied Longitudinal Data Analysis for Epidemiology: A Practical Guide, 1st edition. Cambridge University Press.Google Scholar
Victoria, C. G., Adair, L., Fall, C., Hallal, P. C., Martorell, R., Richter, L. & Sachdev, H. S. (2008) Maternal and child undernutrition: consequences for adult health and human capital. Lancet 371, 340357.CrossRefGoogle Scholar
WHO (2010) WHO Anthro for Personal Computers, Version 3.1. Software for Assessing Growth and Development of the World’s Children. URL: http://www.who.int/childgrowth/software/en/ Google Scholar
WHO (2012) WHO Child Growth Standards: Methods and Development. URL: http://www.who.int/childgrowth/standards/technical_report/en/ Google Scholar