Validation of MINORMIX Approach for Estimation of Low Birthweight Prevalence Using a Rural Nepal Dataset

Abstract

Background The Global Nutrition Target of reducing low birthweight (LBW) by at least 30% between 2012 and 2025 has led to renewed interest in producing accurate, population-based, national low birthweight (LBW) estimates. Low- and middle-income countries rely on household surveys for birthweight data. These data are frequently incomplete and exhibit strong “heaping”. Standard survey adjustment methods produce estimates with residual bias. The global database used to report against the LBW Global Nutrition Target adjusts survey data using a new MINORMIX approach: 1) multiple imputation to address missing birthweights, followed by 2) use of a two-component normal mixture model to account for heaping of birthweights. Objective We evaluated the performance of the MINORMIX birthweight adjustment approach and alternative methods against gold-standard measured birthweights in rural Nepal. Design As part of a community-randomized trial in rural Nepal, we measured “gold-standard” birthweights at birth and returned 1–24 months later to collect maternally reported birthweights using standard survey methods. We compared estimates of LBW from maternally reported data derived using: 1) the new MINORMAX approach; 2) the previously used Blanc-Wardlaw adjustment; 3) no adjustment for missingness or heaping against our gold-standard. We also assessed the independent contribution of multiple imputation and curve fitting to LBW adjustment. Results Our gold-standard found 27.7% of newborns were LBW. The unadjusted LBW estimate based on maternal report with simulated missing birthweights was 14.5% (95%CI: 11.6–18.0%). Application of the Blanc-Wardlaw adjustment increased the LBW estimate to 20.6%. The MINORMIX approach produced an estimate of 26.4% (95%CI: 23.5–29.3%) LBW, closest to and with bounds encompassing the measured point estimate. Conclusions In a rural Nepal validation dataset, the MINORMIX method generated a more accurate LBW estimate than the previously applied adjustment method. This supports the use of the MINORMIX method to produce estimates for tracking the LBW Global Nutrition Target. Clinical Trial Registry: NCT01177111 at https://clinicaltrials.gov/ct2/show/NCT01177111.

Study protocol for UNICEF and WHO estimates of global, regional, and national low birthweight prevalence for 2000 to 2020

“…Following evidence from previous research 25 , 26 , five imputations will be performed for each survey, and a mixture model of two normal distributions will then be fitted to each of the five datasets of recorded and imputed birthweights. The approach provides an estimate of the proportion of birthweights <2,500g that accounts for missing values and heaping, and produces 95% confidence intervals that account for uncertainty arising from both the estimation of the parameters of the two normal distributions and from the imputation step 27 .…”