A study on initiation of postpartum family planning in India based on NFHS-4: does urban poor differ significantly from rural?

OBJECTIVE: To explore the differentials of postpartum contraceptive adoption between rural and urban poor after adjusting for utilization of MCH services and other selected socioeconomic and demographic covariates. METHODS: The data for this study is taken from the 4th round of NFHS survey conducted in India during 2015-16. The analysis is limited to 125,340 currently married women whose menses had returned at the time of survey. Discrete time complementary log-log multilevel model was applied.  RESULTS: The results clearly indicate that women from rural areas had a lower chance of early initiation of modern spacing methods after having recent birth as compare to that of Urban Poor and Urban non-poor areas. The contributions of several socioeconomic and demographic characteristics that were important for family planning practice were also highlighted in this study. CONCLUSION: There is an urgent need of designing an intervention that will result in effective delivery of services to achieve the greatest impact. Policy planners must focus on targeted interventions for family planning use in the postpartum period than simply focusing on family planning.

Experiments in modeling recent Indian fertility pattern.

Modelling is a well-established concept for understanding the typical shape and pattern of age-specific fertility. The distribution of India's age-specific fertility rate (ASFR) is unimodal and positively skewed and is distinct from the ASFR of the developed countries. The existing models (P-K model, Gompertz model, Skew-normal model and G-P model considered here) that were developed, based on the experiences of the developed countries, failed to fit the single-year age-specific fertility pattern for India as a whole and for the six selected states. Our study has proposed four flexible models, to capture the diverse age pattern of fertility, observed in the Indian states. The proposed models were compared in three ways; among themselves, with the original models and with the popular Hadwiger model. The parameters of these proposed models were estimated through the Non-Linear Least Squares Method. To find the model with best fit, we used the corrected version of Akaike's Information Criterion (AICc). Optimization of the four original models was successfully done. When the model was fitted to the empirical data of the 4th round of the National Family Health Survey conducted in 2015-2016, the results of this study showed that all the four proposed models outperform their corresponding original models and the Hadwiger model. When comparison among the proposed models was done, the Modified Gompertz Model provided the best fit for India, Uttar Pradesh and Gujarat. Whereas, the Modified P-K model gave the best fit for West Bengal, Tripura and Karnataka. The Modified G-P model is the most suitable model for Punjab. Although our proposed models illustrated the fitting of ASFR for India as a whole and the selected six states only, it provides an important tool for the policymakers and the government authorities to project fertility rates and to understand the fertility transitions in India and various other states.

Disaggregated analysis of birth averted due to family planning use in India: An evidence from NFHS-4 (2015-16).

BACKGROUND AND OBJECTIVE: India contributes a major share of global unintended births. It is established that contraception plays a significant role in preventing unintended pregnancies, maternal mortality and induced abortion. In this study, to analyze the effectiveness of our family welfare program, we tried to give district-level estimates of number of births averted due to contraception. DATA AND METHODS: Data for this study came from the cross-sectional, population-based data from the fourth round of National Family Health Survey (NFHS-4) conducted in 2015-16. Here, we discussed two methods based on robust regression for computing number of births averted at district level. Further, we analyzed the percentage increase in births (PIB) that would be experienced by each district in the absence of contraception. RESULTS: Findings of this study clearly showed that there was a huge variation in the estimates of number of births averted among different districts as well as states of India. Out of 640 districts, 315 districts achieved below-replacement fertility and 365 districts have contraceptive prevalence rate (CPR) more than 50 percent. Method 1 found around 22 percent districts showed less than 15 percent reduction in births while Method 2 suggested nearly 14 percent districts predominantly located in Uttar Pradesh, Bihar, Jharkhand, Arunachal Pradesh, Meghalaya and Manipur exhibited less than 30 percent reduction of births due to use of all forms of contraception. At all India level, an average estimate obtained by two methods, nearly 63 million births would have been averted by the use of contraception or 40 percent more than the number of births occurred during that period. CONCLUSION: The study successfully identified the districts that were not performing well at the front of utilization of various family planning methods for birth control. To achieve objectives of National Population Policy (2000), poor-performing districts must be monitored like the government keeps monitoring of Aspirational districts.

The role of change in fertility desire on change in family planning use: A longitudinal investigation in urban Uttar Pradesh, India.

Background: Reproductive choice is one of the rights of any woman, but women are often ambivalent towards fertility desires and choice of contraception. Our study explores how the change in fertility desires influence the change in use of modern contraception over time in six cities of Uttar Pradesh, India. Methods : Data for this study comes from the Measurement, Learning and Evaluation (MLE) Project for Urban Health Initiative in six cities of Uttar Pradesh. Our study sample consists of 8735 women (weighted n=8655) who were fertile, non-sterilized and non-pregnant at the time of baseline survey. Potential bias due to lost to follow up was addressed using inverse probability weighing and then generalized estimating equations were applied to get odds for change in use of modern contraceptives.  Results: Contraceptive use increased by different magnitudes from baseline to endline across all six cities. At baseline and endline, women who desired no more children reported a higher use of modern contraception than those who desired more children over time. Women from all cities who desired no more children at baseline had higher odds of modern contraceptive use than that of women who desired more children. The tempo of change in use of modern contraception over time among women with different fertility desires differed across the considered cities. Conclusion : Although there were city-wise differences observed, women's fertility intentions have an impact on their use of modern contraceptives over the time period between baseline to endline. To obtain greater insight into city-level differences, mixed method studies will be more effective.