Relationship between low birth weight and infant mortality: evidence from National Family Health Survey 2019-21,
Arup Jana1, Unnati Rani Saha2, R S Reshmi3
1International Institute for Population Sciences, Deonar, Mumbai, 400088, India. arupjana0000@gmail.com.
Insights
Low birth weight (LBW) significantly increases infant mortality risk in India. Addressing LBW through targeted policies is crucial for reducing infant deaths and improving child survival rates.
Area of Science:
- Public Health
- Epidemiology
- Demography
Background:
- Low birth weight (LBW) is a major risk factor for infant mortality, physical, and mental growth failure.
- Existing research often overlooks the simultaneous influence of observed and unobserved factors on birth weight and infant mortality.
- This study addresses spatial clustering of LBW and its determinants, exploring the LBW-infant mortality link while accounting for unobserved factors.
Purpose of the Study:
- To identify spatial patterns and determinants of low birth weight (LBW) in India.
- To investigate the relationship between LBW and infant mortality, considering unobserved confounding factors.
- To analyze the impact of missing data imputation on the LBW-infant mortality association.
Main Methods:
- Utilized data from the National Family Health Survey (NFHS) round 5 (2019-21).
- Employed directed acyclic graphs (DAGs) to identify potential predictors of LBW and infant mortality.
- Applied conditional mixed process modeling and Moran's I statistics to analyze spatial clustering and simultaneous outcomes, with missing data imputation.
Main Results:
- Punjab and Delhi exhibited the highest LBW rates (approx. 22%), exceeding the national average (18%).
- The impact of LBW on infant mortality was substantially underestimated (marginal effect increased from 12% to 53%) when not accounting for simultaneous occurrences and unobserved factors.
- Missing data imputation revealed significant differences in the estimated impact of LBW on infant mortality.
Conclusions:
- A significant association exists between low birth weight (LBW) and infant mortality in India.
- Prioritizing interventions to improve newborn birth weight is essential for reducing infant mortality.
- Policy initiatives focused on enhancing birth weight can lead to substantial reductions in infant mortality across India.
Background:
Low birth weight (LBW) predisposes physical and mental growth failure and premature death among infants. Studies report that LBW predominately explains infant mortality. However, existing studies rarely demonstrate the phenomenon of both observed and unobserved factors, which may influence the likelihood of birth and mortality outcomes simultaneously. In this study, we identified the spatial clustering of the prevalence of LBW along with its determinants. Further, the relationship between of LBW and infant mortality, considering the unobserved factors, has been explored in the study.
Methods:
Data for this study have been extracted from the National Family Health Survey (NFHS) round 5, 2019-21. We used the directed acyclic graph model to identify the potential predictors of LBW and infant mortality. Moran's I statistics have been used to identify the high-risk areas of LBW. We applied conditional mixed process modelling in Stata software to account for the simultaneous nature of occurrences of the outcomes. The final model has been performed after imputing the missing data of LBW.
Results:
Overall, in India, 53% of the mothers reported their babies' birth weight by seeing health card, 36% reported by recall, and about 10% of the LBW information was observed as missing. The state/union territory of Punjab and Delhi were observed to have the highest levels of LBW (about 22%) which is much higher than the national level (18%). The effect of LBW was more than four times larger compared to the effect in the analysis which does not account for the simultaneous occurrence of LBW and infant mortality (marginal effect; from 12 to 53%). Also, in a separate analysis, the imputation technique has been used to address the missing data. Covariates' effects showed that female children, higher order births, births that occur in Muslim and non-poor families and literate mothers were negatively associated with infant mortality. However, a significant difference was observed in the impact of LBW before and after imputing the missing values.
Conclusions:
The current findings showed the significant association of LBW with infant deaths, highlighting the importance of prioritising policies that help improve the birth weight of new-born children that may significantly reduce the infant mortality in India.
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