|Determinants of birth registration in India: Evidence from NFHS 2015-16|
||Krishna Kumar, Nandita Saikia
||PLOS ONE , Volume 16, no. 9; DOI:https://doi.org/10.1371/journal.pone.0257014
Official data on birth is important to monitor the specific targets of SDGs. About 2.7 million children under age five years do not have official birth registration document in India. Unavailability of birth registration document may deprive the children from access to government-aided essential services such as fixed years of formal education, healthcare, and legal protection. This study examines the effect of socioeconomic, demographic and health care factors on birth registration in India. We also examined the spatial pattern of completeness of birth registration that could be useful for district level intervention.
We used data from the National Family Health Survey (NFHS-4), 2015–16. We carried out the descriptive statistics and bivariate analysis. Besides, we used multilevel binary logistic regression to identify significant covariates of birth registration at the individual, district, and state levels. We used GIS software to do spatial mapping of completeness of birth registration at district level.
The birth registration level was lower than national average (80.21%) in the 254 districts. In Uttar Pradesh, 12 out of 71 districts recorded lower than 50% birth registration. Also, some districts from Arunachal Pradesh, J&K, and Rajasthan recorded lower than 50% birth registration. We also found a lower proportion of children are registered among children of birth order three and above (62.83%) and rural resident (76.62%). Children of mothers with no formal education, no media exposure, poorest wealth quintile, OBC and muslims religion have lower level of birth registration. Multilevel regression result showed 25 percent variation in birth registration lie between states while the remaining 75 percent variation lie within states. Moreover, children among illiterate mother (AOR = 0.57, CI [0.54, 0.61], p<0.001), Muslims households (AOR = 0.90, CI [0.87, 0.94], p<0.001), and poorest wealth quintile (AOR = 0.38, CI [0.36, 0.41], p<0.001) showed lower odds for child’s birth registration.
We strongly suggest linking the birth registration facilities with health institutions.