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Variations in familial neonatal mortality risks in four countries

Published online by Cambridge University Press:  31 July 2008

Siân L. Curtis  and
Fiona Steele
Siân L. Curtis
Affiliation:
Macro International, Calverton, Maryland, USA
Fiona Steele
Affiliation:
Department of Social Statistics, University of Southampton
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Summary

This paper investigates variations in the strength and structure of familial association in neonatal mortality risks in four populations; Bolivia, Kenya, Peru, and Tanzania. Exploratory analyses of the structure of the familial association are presented for each population. Random effects logistic models are then used to estimate the strength of familial association in neonatal mortality risks using a standard set of control variables. The results suggest that the strength of familial association in neonatal mortality risks is quite similar in these four populations which would be consistent with a biological explanation for the association. However, some differences were found, particularly in the form of the association in Peru, which may suggest at least a small role of other factors.

Type
Research Article
Information
Journal of Biosocial Science , Volume 28 , Issue 2 , April 1996 , pp. 141 - 159
Copyright
Copyright © Cambridge University Press 1996

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References

Anderson, D. A. & Aitkin, M. (1985) Variance component models with binary responses: interviewer variability. J. roy. statist. Soc. 47, 203.Google Scholar
Ashworth, A. & Feachem, R. G. (1985) Interventions for the control of diarrhoeal diseases among young children: prevention of low birth weight. Bull. Wld Hlth Org. 639, 165.Google Scholar
Bakketeig, L. S., Hoffman, H. J. & Harley, E. E. (1979) The tendency to repeat gestational age and birth weight in successive births. Am. I Obstet. Gynec. 135, 1086.CrossRefGoogle ScholarPubMed
Bicego, G. T. & Boerma, J. T. (1991) Maternal education and child survival: a comparative analysis of DHS data. In: Proceedings of the Demographic and Health Surveys World Conference,Washington. DC, 1991, Vol. 1. IRD/Macro International, Columbia, Maryland.Google Scholar
Bureau of Statistics (1991) The 1988 Population Census—National Profile: Summary. United Republic of Tanzania, Dar es Salaam.Google Scholar
Carvalho, J. A. M. de & Wood, C. H. (1978) Mortality, income distribution and rural—urban residence in Brazil. Popul. Dev. Rev. 4, 405.CrossRefGoogle Scholar
Casterline, J. B., Cooksey, E. C. & Ismail, A. F. E. (1989) Household income and child survival in Egypt. Demography, 16, 15.CrossRefGoogle Scholar
Cleland, J. G. & Sathar, Z. A. (1984) The effect of birth spacing on childhood mortality in Pakistan. Popul. Stud. 38, 401.CrossRefGoogle ScholarPubMed
Cleland, J. G. & Van Ginneken, J. K. (1988) Maternal education and child survival in developing countries: the search for the pathways of influence. Social Sci. Med. 27, 1357.CrossRefGoogle ScholarPubMed
Curtis, S. L., Diamond, I. & McDonald, J. W. (1993) Birth interval and family effects on post-neonatal mortality in Brazil. Demography, 30, 33.CrossRefGoogle Scholar
Das Gupta, M. (1990) Death clustering, mother's education and the determinants of child mortality in rural Punjab, India. Popul. Stud. 44, 489.CrossRefGoogle Scholar
Da Vanzo, J., Butz, W. P. & Habicht, J-P. (1983) How biological and behavioral influences on mortality in Malaysia vary during the first year of life. Popul. Stud. 37, 381.CrossRefGoogle Scholar
Ferraz, E. M., Gray, R. H., Flemming, P. L. & Maia, T. M. (1988) Interpregnancy interval and low birth weight: findings from a case control study. Am. J. Epidemiol. 128, 1111.CrossRefGoogle ScholarPubMed
Gubhaju, B. B. (1985) The effect of previous child death on infant and child mortality in rural Nepal. Stud Fam. Plann. 16, 231.CrossRefGoogle ScholarPubMed
Guo, G. (1993) Use of sibling data to estimate family mortality effects in Guatemala. Demography, 30, 15.CrossRefGoogle ScholarPubMed
Im, S. & Gianola, D. (1988) Mixed models for binomial data with an application to lamb mortality. Appl. Statist. 37, 196.CrossRefGoogle Scholar
Instituto Nacional De Estadistica and Institute for Resource Development/Macro Systems (1990) Bolivia Encuesta Nacional de Demografia y Salud 1989. IRD/Macro Systems, Columbia, Maryland.Google Scholar
Instituto Nacional De Estadistica E Informatica, Associacion Benefica Prisma, & Macro International (1992) Peru Encuesta Demogragica y de Salud Familiar 1991/92. Macro International, Columbia, Maryland.Google Scholar
Mturi, A. J. & Curtis, S. L. (1995) The determinants of infant and child mortality in Tanzania. Hlth Policy Plann. in press.CrossRefGoogle Scholar
National Council for Population and Development & Institute for Resource Development/Macro Systems (1989) Kenya Demographic and Health Survey 1989. IRD/Macro Systems, Columbia, Maryland.Google Scholar
Neuhaus, J. M., Kalbfleisch, J. D. & Hauck, W. W. (1991) A comparison of cluster-specific and population-averaged approaches for analysing correlated binary data. Int. statist. Rev. 59, 25.CrossRefGoogle Scholar
Pebley, A. R. & Stupp, P. W. (1987) Reproductive patterns and child mortality in Guatemala. Demography, 24, 43.CrossRefGoogle ScholarPubMed
Pierce, D. A. & Sands, B. R. (1975) Extra Binomial Variation in Binary Data. Technical Report No. 46, Department of Statistics, Oregon State University.Google Scholar
Statistics and Epidemiology Research Corporation (1986) EGRET Seattle, Washington.Google Scholar
Us Department of Health and Human Services (1993) Mortality Vital Statistics Report. No. 41(13). Hyattsville, USA.Google Scholar
Zenger, E. A. (1993) Neonatal mortality risks and birth spacing in Bangladesh. Demography, 30, 477.CrossRefGoogle ScholarPubMed