Determinants of neonatal mortality in rural Haryana: a retrospective population based study

Indian Pediatr. 2012 Apr;49(4):291-4. doi: 10.1007/s13312-012-0044-2. Epub 2011 Aug 15.

Abstract

Objective: To identify the determinants of neonatal mortality.

Study design: Nested case-control study.

Study setting: 28 villages under the intensive field practice area of Comprehensive Rural Health Services Project, Ballabgarh, Haryana serving a population of 87,016, as on 31st December 2009. The study period was from 2005 to 2009.

Methods: The data were obtained from Health Management Information System and analyzed using multivariate logistic regression analysis. A hierarchical approach was used to analyze the factors associated with neonatal deaths, using community level factors, socio-economic status and biological determinants. The population attributable fractions were estimated for significant variables.

Results: The total live births during the study period were 10392 and neonatal deaths were 248. The infant and neonatal mortality rates during the study period were 45.6 and 23.8 per 1000 live births, respectively. Socio-economic determinants (Low educational status of parents [OR 2.1, 95% CI; 1.4, 3.3]; fathers occupation [OR 1.8, 95% CI; 1.0, 3.0]; Rajput caste [OR 2.0, 95% CI; 1.2, 3.4] appeared to explain a major fraction (45.7%) of neonatal deaths. Community level factors (villages with no health facility [OR 1.5, 95% CI; 1.0, 2.1]; villages with population >6000 [OR 1.7, 95% CI; 1.2, 2.5]) were associated with 27.3% of all neonatal deaths. Proximate determinants (early childbearing age of mother (<20 years) [OR 2.0, 95% CI; 1.2, 3.2]) were least important. All the three level of variables seemed to act independently with little mediation among them.

Conclusion: Neonatal mortality is affected by socioeconomic, community level and proximate biological determinants.

MeSH terms

  • Adult
  • Female
  • Humans
  • India / epidemiology
  • Infant Mortality*
  • Infant, Newborn
  • Logistic Models
  • Male
  • Odds Ratio
  • ROC Curve
  • Retrospective Studies
  • Risk Factors
  • Rural Population / statistics & numerical data*
  • Socioeconomic Factors