Predictors of Low Birth Weight at Lumbini Provincial Hospital, Nepal: A Hospital-Based Unmatched Case Control Study

BACKGROUND: Low birth weight (LBW) is defined as the birth weight of live born infants below 2500 g, regardless of gestational age. It is a public health problem caused by factors that are potentially modifiable. The purpose of this study was to determine the socioeconomic, obstetric, and maternal factors associated with LBW in Lumbini Provincial Hospital, Nepal. METHODS: The study was conducted using case control study design with 1 : 2 case control ratio. A total of 105 cases and 210 controls were taken in this study. Data were entered on Epi data software version 3.1 and exported to Statistical Package for Social Science (SPSS) software version 25 for analysis. Characteristics of the sample were described using mean and standard deviation. Bivariate analysis was done to assess the association between dependent and independent variables. The ultimate measure of association was odds ratio. Variables found to be associated with bivariate analysis were entered into a multivariable logistic regression model to identify predictors of LBW. RESULTS: The mean age of the participants was 25.98 years with ±4.40 standard deviation. Mothers with literate educational background (AOR 0.32, 95% CI 0.13–0.81), housewife (AOR 2.63, 95% CI 1.11–6.20), vaginal mode of delivery (AOR 0.45, 95% CI 0.25–0.82), gestational age <37 weeks (AOR 2.51, 95% CI 1.15–5.48), history of LBW (AOR 5.12, 95% CI 1.93–13.60), and maternal weight <50 kilograms (AOR 2.23, 95% CI 1.23–4.02) were significantly associated with LBW. CONCLUSION: Educational and occupational status, mode of delivery, gestational age, maternal weight, and history of LBW were found to be independent predictors of LBW. There is need of developing coordination with education sector for increasing educational status of mothers and adolescent girls. Social determinants of health need to be considered while developing interventional programs. Similarly, interventional programs need to be developed considering identified predictors of low birth weight.