THE RELATIONSHIP BETWEEN SELECTED NEONATAL, MATERRNAL ANTHROPOMETRIC CHARACTERISTICS AND BIRTH WEIGHT AS PREDICTORS OF NEONATAL WELL- BEING, AMONGFULL-TERM SINGLETON BABIES

(A CASE STUDY OF KANO STATE NIGERIA)

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Author

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Department of Medicine

ABSTRACT
Neonatal and maternal anthropometric characteristics are fundamental in health management. Numerous studies have established the relationship between birth weight and other neonatal and maternal anthropometric parameters. Hospitals in rural (or busy) settings in many cases lack appropriate tools for the measurement of neonatal as well as maternal anthropometric parameters. The aim of the study is to evaluate impact of the relationship between selected neonatal, maternal anthropometric characteristics and birth weight as predictors of neonatal well- being, among full-term singleton babies in Kano state nigeria. And (also) to develop appropriate stepwise multiple linear regression equation models and to determine the cut off values for the select neonatal parameters that discriminate between low and high birth weight for the urban and rural deliveries in Kano State, Nigeria. The study involved a total of 1,203 mother-child pair from the urban and rural hospitals in Kano State. Several selected neonatal anthropometric parameters such as birth length, hand breadth, thigh circumference among others were measured. Similarly, maternal anthropometric characteristics such as maternal height, maternal arm circumference, and symphysio-fundal height together with maternal haemoglobin, age, parity and educational level were also considered. The entire data were collected from six hospitals (three from the urban and three from the rural areas). Data collected were expressed as mean ± SD, independent sample t-test was used to determine the differences between the variables. Pearson‘s correlation was used in relating the variables with one another. Binary logistic regression was employed to determine the effect of maternal characteristics, and Apgar score on the birth weight. Stepwise multiple linear regression analyses were all carried out to provide models for predicting birth weight among the neonates. The predictive probabilities for the variables to discriminate between low and high birth weight were analyzed using ROC curves. The data analyses were carried out using IBM SPSS version 25.0 statistical software (Armonk, NY: IBM Corp.), and a P value of < 0.05 was considered statistically significant. The study found a significant impact of the relationship between the neonatal and maternal anthropometric characteristics (P < 0.001) on birth weight. The mean birth weight, mean placental weight, mean value of ponderal index as well as the placental-birth weight ratio among the neonates were also found to be 3079.30 ± 491.77kg, 526.02 ± 83.09kg, 2.66 ± 0.63 and 17.17 ± 1.73 (1:6) respectively. Among the maternal anthropometric parameters, the mean maternal height stood at 160.22 ± 5.82cm. Other parameters such as the mean maternal arm circumference, the mean symphysio-fundal height and the mean maternal haemoglobin level were also determined as 26.60 ± 3.15cm, 37.46 ± 0.93 cm and 12.18 ± 1.40g/dl respectively. Furthermore, stepwise multiple linear regression models were formed to ease birth weight estimation among the neonates in Kano State, Nigeria. In conclusion, the study has determined the mean values of the select neonatal and maternal anthropometric characteristics in Kano State, Nigeria. Significant variations exist among the maternal and the neonatal anthropometric parameters in the urban and rural areas of Kano State. Stepwise multiple linear regression models were formed for the estimation of birth weight. Receiver operator characteristic curve was also employed to discriminate between low and high birth weight.