Ontology highlight
ABSTRACT: Background
This study examines the geographic variation and the magnitude of wealth inequities in birth registration in India between 2005 and 2015.Methods
Data came from India's 2005 (n = 51,940) and 2015 (n = 250,194) Demographic Health Surveys. We estimated absolute wealth inequities at the national and state-level and specified three-level logistic regression models (children, communities, and states) to calculate the variance partitioning coefficient attributable to each level to examine the variation in birth registration at each time point.Results
National birth registration coverage was 41.2% in 2005 and improved to 79.6% in 2015. Between 2005 and 2015, coverage among children in the poorest quintile (Q1) improved from 23.9% to 63.8% while coverage among the wealthiest children (Q5) improved from 72.4% to 92.8%. Although the absolute wealth inequity decreased from 48.6%-points to 29.1%-points, children in Q1 still had levels of coverage in 2015 that were lower than children in Q5 in 2005. Between 2005 and 2015, birth registration improved in every state and coverage was higher than 90% in 13 states. Wealth inequities decreased in 21 states and increased in 8 states. In adjusted multi-level models the proportion of total variation in birth registration attributable to states (35.7% 2005 and 29% in 2015) was larger than the variation attributable to communities (15% in 2005 and 13.7% in 2015).Conclusion
Birth registration is essential for ensuring inclusive population counts of birth and mortality rates. Efforts to reach universal birth registration in India will require a commitment to reducing wealth inequities within states.
SUBMITTER: Bhatia A
PROVIDER: S-EPMC7823051 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
Bhatia Amiya A Kim Rockli R Subramanian S V SV
SSM - population health 20210112
<h4>Background</h4>This study examines the geographic variation and the magnitude of wealth inequities in birth registration in India between 2005 and 2015.<h4>Methods</h4>Data came from India's 2005 (n = 51,940) and 2015 (n = 250,194) Demographic Health Surveys. We estimated absolute wealth inequities at the national and state-level and specified three-level logistic regression models (children, communities, and states) to calculate the variance partitioning coefficient attributable to each lev ...[more]