Determinants of Low Birthweight in Ghana

ABSTRACT

The study objectives are to determine the key factors that may be accounting for birthweight of infants, estimate its distribution, prevalence and proposes a statistical model that can be useful in epidemiological studies in Ghana. Both estimation (Linear) and classification (Logistic) analysis was conducted using data from GDHS. Covariates found to statistically associated with newborn’s weight are gender, size of child at birth, region, wealth index, birth order, total number children ever had, delivery place, preceding birth interval, and birth type. Size of child (Very Large) was the largest contributor to the explained variation in birthweight in the Multiple Linear regression. The Multivariable Logistic regression, for every one-unit change in mothers height, the log odds of low birthweight (against normal birthweight) of a child decreases by -0.107kg with an odds ratio of 0.898kg and for a unit decrease in birth order of the infant, the log odds of being low weight decreases by -0.714kg with an odds ratio of 0.490kg. Region depicted that (Brong Ahafo, Central, Greater Accra, Upper East and Volta) was found to be significantly related to newborn’s weight, implying that a mother from any of these regions is more likely to have a NBW as compared to a mother from Ashanti. A male child was 0.397 times more likely to be NBW as compared to a female child. Single birth babies were 0.001 times more likely to be NBW as compared to multiple births. Only mothers from the poorest class was found to be significantly related to birthweight which implied that the newborns whose mothers are under the poorest class would 1.973 times more likely to be NBW as compared to mothers belonging to the middle class. Size of a child at birth was found to be significantly related to birthweight of a newborn. The study has contributed to the understanding of maternal determinants associated with infant birthweight at the population level. Findings have therefore, provided a starting point towards identifying risk factors and providing clues to health service providers on maternal determinants and birth outcomes factor to concentrate health promotion messages on.