This paper explores alternative models to test for clustering and apply them to the 1984 data for Punjab villagers categorized by socioeconomic status education of the mother and the sex of the child and age at death. Interviews were later conducted with mothers and other members of some households with history of multiple child deaths and with matched families with similar socioeconomic status in which there had been no child deaths. The study showed that significant clustering of child deaths was found only among households with lower socioeconomic status and education. Improvements in socioeconomic condition and education appear to decrease child mortality. The extent of clustering is high among the total population were 23% of child death can be attributed to being born into a high-risk family. Improved health care services offer a major contribution to the reduction in deaths among the children in the area. In addition birth intervals seem to be an effect rather than a cause of greater familial susceptibility to child loss. The result also exemplifies a considerable potential for reducing and preventing child death by targeting on high-risk families to receive extra attention in health care. Finally researchers suggest the use of negative binomial model when clustering child mortality in populations in which families are successful in focusing their behavior towards a given number of surviving children.
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Mónica Das Gupta (1997) studied this question.
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