Multiple regression in fertility and family formation

• Main Authors: Anushri Pradip Patil, Naresh Kumar Tyagi
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2017-01-01
• Series: Indian Journal of Health Sciences and Biomedical Research KLEU
• Subjects: Multiple regression analysis; principal component analysis; total fertility rate
• Online Access: http://www.ijournalhs.org/article.asp?issn=2542-6214;year=2017;volume=10;issue=3;spage=237;epage=240;aulast=Patil

Background: In the present study, attempt has been made to study the determinants of total fertility rate (TFR), by developing the model for TFR so to use TFR determinants for Family Welfare Planning and Programme implementation. Methodology: Principal component analysis was carried out to study the correlates of TFR of Indian states. Further, regression analysis was carried out to estimate TFR, using relevant determinants by studying its correlates and principal components. Results: Two principal components were: (i) “Social Status of Women” explaining 58% of variation comprised “infant mortality rate” with correlation coefficient (−0.95), “Percentage of Literacy of Female” (0.94), “Life Expectancy at Birth” (0.93), “Age at Marriage of Women” (−0.90), and (ii) “Fertility Index” with 20% of variation explained, comprised “Employment Status of Female” (0.762) and “Desire of no more child after Two Living Children” (−0.759). The regression model for TFR with the coefficient of determination (0.466), using desire of no more child after Two Living Children was arrived, with utility to enhance health education and communication to achieve ideal family formation behavior. All Indian states were classified by the regression model (TFR = 3.58–0.019* “Desire of no more child after Two Living Children”) within 68% confidence interval except two states Mizoram and Meghalaya. Conclusions: 'Desire of no more children after two living Children's' has come out the main stay of family formation behavior. Hence, making realize the value of small family size with health education will stabilize the population.