Birthweight by gestational age in preterm babies according to a Gaussian mixture model

Abstract

Objective To provide a statistically sound criterion for identifying implausibly large birthweights for gestational age. Design Review of ISTAT 1990-1994 national newborn records. Setting ItalyPopulation Forty-two thousand and twenty-nine single first and second liveborn preterm babies.Methods Two-component Gaussian mixture models are used to describe the birthweight distributions stratified by gestational age. Implausibly large babies are identified through model-based probabilistic clustering. Main outcome measures Gestational age misclassification and weight-for-gestational age centile curvesResults Gestational age appears under-estimated by about six weeks in 12.3% of the cases. Large babies are equally present in males and females, but are more frequent in second-borns than in first-borns, even when parity-specific models are fitted. Conclusions The approach allows for a quantification of the gestational age under-estimate error and for data correction through model-based clustering. Correct birthweight distributions and growth curves are also provided.

A new birthweight reference in Guangzhou, southern China, and its comparison with the global reference

“…Whether a given observation (x, y) belongs to the f p component depends on the weight estimation: w=qf p /f. The birthweight values that had a lower probability of belonging to primary component than 0.5 were considered outliers 14. After 34 weeks of gestation, the bimodality of birthweight distributions increasingly disappeared 14 15.…”

“…The birthweight values that had a lower probability of belonging to primary component than 0.5 were considered outliers 14. After 34 weeks of gestation, the bimodality of birthweight distributions increasingly disappeared 14 15. The distributions tended to be symmetric unimodal, with long tails (see online supplementary figure 1), so we performed robust regression with iteratively reweighted least square (IRLS) procedure to identify implausible birth weights at 35–43 weeks of gestation 16.…”

Post-Natal Gestational Age Assessment Using Sonographic Measurement of Femoral Length

“…Problems with the accuracy of gestational age computed by LMP on birth certifi cates have been documented 6,7,8,9,10 were between 31 and 35 days, and 3% were 36 days or longer, while 5% were too irregular to say 13 .…”

Multiple mortality optima due to heterogeneity in the birth cohort: A continuous model of birth weight by gestational age‐specific infant mortality

“…Recently, semi-parametric (Umbach and Wilcox, 1996;Wilcox and Russell, 1983) and fully parametric (Fryer et al, 1984;Gage, 2000Gage, , 2002bGage, , 2003Gage and Therriault, 1998;Oja et al, 1991;Platt et al, 2001;Tentoni et al, 2004) mixture models have been applied to the study of birth outcome distributions. One line of research divides a birth cohort into several probabilistically defined latent subpopulations and interprets them as ''normal'' versus ''compromised'' births (Fryer et al, 1984;Gage, 2000Gage, , 2002bGage, , 2003Gage and Therriault, 1998;Umbach and Wilcox, 1996;Wilcox and Russell, 1983).…”

“…One line of research divides a birth cohort into several probabilistically defined latent subpopulations and interprets them as ''normal'' versus ''compromised'' births (Fryer et al, 1984;Gage, 2000Gage, , 2002bGage, , 2003Gage and Therriault, 1998;Umbach and Wilcox, 1996;Wilcox and Russell, 1983). Another line of research stratifies births by gestational age and decomposes the birth weight distribution into two subpopulations interpreted as ''accurate'' and ''erroneous'' birth weight for gestational age (Oja et al, 1991;Platt et al, 2001;Tentoni et al, 2004). Except for the interpretation and the stratification on gestational age, the mixture models of these two methods are very similar.…”