Socio-Economic Determinants of Low Birth Weight in Kenya: An Application of Logistic Regression Model
American Journal of Theoretical and Applied Statistics
Volume 4, Issue 6, November 2015, Pages: 438-445
Received: Sep. 10, 2015; Accepted: Sep. 21, 2015; Published: Oct. 12, 2015
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Edwine Benson Atitwa, Department of Computer and Statistics, Moi University, Eldoret, Kenya
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Babies born with Low-birth weight are at increased risk for serious health problems which are accompanied by disabilities and even death. The purpose of this study was to determine socio-economic factors that lead to low birth weight of children in Kenya. Data used was from Kdhs 2003 and the significant effect of socio-economic determinants on low birth weight was examined using logistic regression analysis data is categorical and continuous in nature, where predictor variables being socio-economic determinants and birth weight being dependent variable. Results indicate that out of six socio-economic factors involved in the study, four (Religion, Time Wanted Pregnancy, Marital Status and Economic Status) revealed some significant effects on the children with low birth weight. Therefore Socio-economic determinants have a significant effect on Low birth weight which suggests a strong negative associated with infant survival in Kenya independent of other risk factors. The logistic function revealed a statistically significant association between the birth weight, Religion, Time Wanted Pregnancy, Marital Status and Economic Status. Predicted probability is 11.4% low birth weight. Researcher recommends that respondents should avoid conceiving unexpectedly since it was associated with high low birth weight. Also to effectively enhance normal birth weight in Kenya, then expectant mothers should keenly focus on the socio-economic determinants by avoiding marital problems like divorce.
Socio-Economics, Birth Weight, Predictor Variables, Logistic Regression Model
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Edwine Benson Atitwa, Socio-Economic Determinants of Low Birth Weight in Kenya: An Application of Logistic Regression Model, American Journal of Theoretical and Applied Statistics. Vol. 4, No. 6, 2015, pp. 438-445. doi: 10.11648/j.ajtas.20150406.14
Agresti, A. (1996). An introduction to categorical Data Analysis.
Arshad I. A, Muhammad F and Ghafoor A (2005).Multivariate analysis of mash data, Journal of Applied sciences 5(1).
Andersson, H. W., Gotlieb S. J. and Nelson K. G. (1997). Home environment and cognitive abilities in infants born small-for-gestational-age. In: Acta Obstetrica Gynecologica Scandinavia Supplement. 165, 76, 82-6.
Angelsen, N. K., T. Vik, G., Jacobsen and L. S. Bakketeig (2001). Breast feeding and cognitive development at age 1 and 5 years. In. Archives of Disease in Childhood. 85, 183-88.
Avchen, R. N., Scott K. G. and Mason C. A. (2001). Birth weight and schoolage disabilities: a population-based study. In: American Journal of Epidemiology. 154, 10, 895-901.
Barker DJ, Osmond C and Lancet (1986). Infant mortality, childhood nutrition, and ischaemic heart disease in England and Wales.
Berghella V (2007). Prevention of Recurrent Fetal Growth Restriction. Obstetrics and Gynecology: volume 110, number 4, pages 904-912.
Boardman J. D., Powers D. A., Padilla Y. C. and Hummer R. A. (2002). Low birth weight, social factors, and developmental outcomes among children in the United States: In: Demography. 39; 2, 353-68.
Cheung, Y. B. (2002). Early origins and adult correlates of psychosomatic distress. In: Social Science and Medicine. 55, 937-48.
Donald Kisilu Kombo and Delno L. A. (2006).Proposal and Thesis Writing. Paulines publications.
Gazi etal (2001).Socio-economic factors the a major predictor of infant death.
Harman, H (1967).Modern factor Analysis. The university of Chicago Press, Chicago, USA.
Honein, M.A., et al(2008). The Association between Major Birth Defects and Preterm Birth. Maternal and Child Health Journal, volume 12:4.
Hora S. C and Wilcox J. B. (1982). Estimation of error rates in several population discriminant analysis. J. of. Marketing Research. 19:57-61.
Kenya Demographic Health Survey (KDHS) 2003: Central Bureau of Statistics, Ministry of Health.
Kelly Y. J., Nazroo J. Y., McMunn A., Boreham R. and Marmot M. (2001).Birth weight and behavioural problems in children.
Kothari C. R. (2004). Research Methodology (Methods and Techniques). New Age International Publishers.
Kramer MS (1998). Socioeconomic determinants of intrauterine growth retardation .European Journal of Clinical Nutrition 52 S1, S21-33.
Mardia K. V (1989).Multivariate Analysis, Academic press, Diego, C.A, USA.
Martin, J. A., et al (2005). National Vital Statistics Reports, volume 56, number 6.
McCormick (1985). The contribution of low birth weight to infant mortality and childhood morbidity. N Engl J Med; 312:82-90.
Were (1998). East African medical journal, Kenya Medical Association, Nairobi.
United Nations Children's Fund, World Health Organization: Low Birth weight: Country, regional and global estimates. New York: UNICEF; 2004 (s).
United Nations Children's Fund: Normal birth weight is critical to future health and development. New York: UNICEF; 2008.
Smith, M. M., M. Durkin, V. J. Hinton, D. Bellinger and L. Kuhn (2003).Influence of breastfeeding on cognitive outcomes at age 6-8 years.
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