Short interpregnancy interval and low birth weight births in India: Evidence from National Family Health Survey 2015-16

SSM Popul Health. 2020 Nov 24:12:100700. doi: 10.1016/j.ssmph.2020.100700. eCollection 2020 Dec.

Abstract

Evidence on the effect of interpregnancy interval (IPI) on low birth weight (LBW) births is limited in developing countries including India. Our study aims to examine association between IPI and LBW births in India. We used data from the fourth round of the National Family Health Survey (NFHS-4) conducted in 2015-16 with a representative sample of 52,825 most recent births for examining the association between IPI and LBW. IPI is defined as the gap between the first month in which the index pregnancy was reported in the reproductive calendar (referred to as the month of conception) and the month of pregnancy outcome (including live births and terminations) of preceding pregnancy. Reproductive calendar data were used to estimate IPI. Association between IPI and LBW were examined using multivariable binary logistic regressions. Seventeen percent of the births in our sample were LBW, and more than half (57.6%) of these were accompanied with IPI less than 18 months. Prevalence of LBW births was highest among mother's who had IPI less than six months (19.4%). Regression results, adjusted for control variables, indicate that the risk of LBW was significantly higher among births whose mothers had IPI less than six months (odds ratio: 1.19, 95% CI:1.05-1.36) compared with those whose mothers had IPI between 18 and 23 months. This study provides additional evidence on the association between short IPI (<6 months) and LBW births in India. Promoting spacing methods of family planning is an option that India may consider for increasing the IPI and thereby reducing LBW births. Ensuring recommended iron and folic acid tablets/equivalent syrup and TT injections for every pregnant woman may offset the adverse consequences of shorter IPI.

Keywords: India; Interpregnancy interval; Low birth weight; Multivariable binary logistic regression; NFHS 2015-16; Reproductive calendar.