Relationship between maternal anthropometry, socio-demographic factors and infant’s anthropometry at birth: The case of the provincial general hospital, Nakuru, Kenya

Abstract

An infant’s anthropometry (weight and length) at birth are important public health indicators for its survival and later development. Low birth weight (LBW) and stunting at birth are among the major causes of infant mortality which is still a worldwide problem. Despite the government’s effort to improve healthcare services, LBW is still a problem at the Provincial General Hospital (PGH) maternity, Nakuru. The main objective of this study was therefore to determine the relationship between maternal anthropometry (delivery weight, Mid Upper-Arm Circumference- MUAC and height), socio-demographic factors and an infant’s anthropometry (weight and length) at birth. The information obtained from this study could be helpful in the screening procedure at hospital to identify mothers at a greater risk of delivering low birth weight infants. A cross-sectional study design was adopted and a purposive sample of 200 mothers was used in this study. Anthropometric measurements of both the mothers and the infants were taken. A semi-structured questionnaire was also used in data collection. Maternal haemoglobin (Hb) levels and other health conditions were obtained from their clinic cards and hospital records. The Statistical Package of Social Sciences (SPSS) version 11.5 was used for data analysis. Stated hypotheses were tested using multiple regression, Chi-square, binary logistic regression analysis and t-test statistics. All tests were computed at α = 0.05. The study findings showed that low birth weight deliveries are still a problem at the hospital with a rate of 17.3%. Logistic regression analysis revealed that parity, age of the mother, level of education, Hb status, number of ANC clinic visits and a mother’s history of a LBW delivery were essential predictors of low birth weight delivery and they were all significant (p<0.05). Maternal delivery weight and MUAC measurements were significantly (p<0.05) associated with the birth weight of an infant after controlling for possible confounding factors and they explained up to 20% (r2=0.20, F=3.34, p=0.00) of the variability in the infant’s birth weight and 24.8% (r2=0.248, F=5.91, p=0.00) variability in infant’s birth length. Any intervention aimed at improving birth outcomes therefore should take into consideration parity, maternal age, level of education, Hb status, number of ANC visits, mothers history of LBW delivery, weight and MUAC measurements during its implementation to help curb the high incidences low birth weight deliveries.