Abstract
This paper uses data mining approach to analyse patterns of contraceptive use in India by comparing contraceptive use among groups of women with distinct demographic, economic, cultural, and social characteristics. The analysis suggests that currently married, nonpregnant women aged 15–49 years in India can be classified into 13 mutually exclusive groups on the basis of six characteristics of women—surviving children, household standard of living, religion, women’s years of schooling, husbands’ education, and residence. Contraceptive use pattern in these 13 groups is essentially different and reflects the orientation of family planning efforts, especially, official family planning efforts in the country. The observed differences in the patterns of contraceptive use have important policy and programme implications in the context of universal access to family planning.
Highlights
Contraception is one of the proximate determinants of fertility and the most important predictor of fertility transition [1, 2]
classification and regression tree (CART) (Classification and regression tree) is a nonparametric technique that can select from a large number of variables those variables and their interaction that are most important in determining the outcome variable to be explained [10]
Data for the present analysis are derived from the district level household and facility survey (DLHS) 2007-08 which covered more than 720 thousand households in all districts of 28 states and 6 union territories of the country as they existed at the time of the survey [5]
Summary
Contraception is one of the proximate determinants of fertility and the most important predictor of fertility transition [1, 2]. The choice of the contraceptive method, is influenced by a host of interdependent demographic, cultural, economic, and social factors which means that a multidimensional approach needs to be adopted for analysing the contraceptive use pattern. We analyse the pattern of contraceptive use in India through data mining approach. CART (Classification and regression tree) is a nonparametric technique that can select from a large number of variables those variables and their interaction that are most important in determining the outcome variable to be explained [10]. We apply CART decision tree algorithm to identify women with distinct social, economic, cultural, and demographic characteristics who have different contraceptive use pattern and analyse how the pattern of contraceptive use varies across these groups.
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