“Survival Model to Analyze Unmet Needs of Demographic and Health Survey Data of Maharashtra State, India Using Cox-Regression and Aalen’s Additive Model”

Abstract

Several studies shown that many statistical tests are useful and adapted to evaluate the influence of other variables on unmet need. Every researcher has applied statistical test by considering has its own features and limitation. For this study the data from District Level Household Survey (DHS) data of Maharashtra state, India. In this study is used to see the influence of time related variables Respondent Current Age (V012) and Age at First time Sex (V525) influence on Unmet Need of Contraception associated with other statistically significant variable through the tools of survival analysis.

The hazard ratio using cox regression analysis were found for Had your uterus removed (S253) 5.92 (95% CI 1.52, 23.0, p = 0.010), Daughters at home (V203) 3.86 (95% CI 2.05, 7.28, p = <0.001), Daughters who have died (V207) 4.25 (95% CI 1.38, 13.1, p = 0.012), Age of respondent at 1st birth (V212) 0.83 (95% CI 0.69, 1.00, p =0.049), Contraceptive use and intention (V364) 3.16 (95% CI 1.04, 9.54, p = 0.042), Currently amenorrheic (V405) 5.83 (95% CI 1.31, 25.9, p =0.020), Currently abstaining (V406) 2.60 (95% CI 1.15, 5.89, p = 0.022), Covered by health insurance (V481) 5.70 (95% CI 2.42, 13.4, p = <0.001), Respondent's current age (V012) 0.79 ( 95% CI 0.68, 0.92, 0.002), and Ideal number of children (V613)  0.65 (95% CI 0.45, 0.96, p = 0.030) were observed as shown in Table 2 statistically significant while rest were non-significant p-value for hazard ratio.