Chest circumference in full-term newborns: how can it be predicted?
Open Access
- 26 September 2019
- journal article
- research article
- Published by Springer Science and Business Media LLC in BMC Pediatrics
- Vol. 19 (1), 1-6
- https://doi.org/10.1186/s12887-019-1712-3
Abstract
Although over the years a number of studies have used chest circumference (CC) as a sensitive tool to identify the health status of infants, a particularly important aspect for this population is the lack of data on normal values and prediction equations. In order to facilitate and validate the interpretation of CC data in newborn (NB), the aim was to study the relation between CC and other anthropometric variables and develop a predictive equation for CC in a population of full-term newborns. Cross-sectional study, carried out with full-term infants. The anthropometric (CC, head circumference - HC, length, age and weight) and hemodynamic variables were evaluated during the first 24 h of life. Bivariate analysis was performed between CC and HC, weight, length and type of delivery, followed by multiple linear regression analysis, including variables that were significant in the bivariate analysis. For data analysis, we used the SPSS program, considering p < 0.05 and 95% CI. The birth weight of the 120 NB varied between 2580 and 4225 g (mean 3360 g) and the gestational age between 37 and 42 weeks (mean 39 weeks). Approximately 61% of the sample were delivered vaginally and 67 (56%) were boys. The variables that remained statistically associated with CC after multivariate analysis were weight (β 0.003, CI: 0.002: 0.003, p = 0.001) and HC (β 0.287, CI: 0.156: 0.417, p = 0.001). For the linear regression model, the predictive equation of CC was 14.87+ (0.003 x weight) + (0.287 x HC), with a prediction of 76%. The results show a positive correlation between CC and weight, length and HC, and based on the linear regression model, the predictive equation for CC is based only on weight and HC.Keywords
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