Impact of early infant feeding practices on mortality in low birth weight infants from rural Ghana.
OBJECTIVE
To assess the impact of early infant feeding practices on low birth weight- (LBW) specific neonatal mortality in rural Ghana.


METHODS
A total of 11 787-breastfed babies were born between July 2003 and June 2004 and survived to day 2. Overall, 3411 (30.3%) infants had weight recorded within 48 h. Two hundred and ninety-six (8.7%) infants were <2.5 kg and 15 died in the neonatal period. Associations were examined using multivariate logistic regression.


RESULTS
Initiation of breastfeeding after day 1 was associated with a threefold increase in mortality risk (adjusted odds ratio (adjOR) 3.23, 95% confidence interval (95% CI) (1.07-9.82)) in infants aged 2 to 28 days. Prelacteal feeding was associated with a threefold significantly increased mortality risk (adjOR 3.12, 95% CI (1.19-8.22)) in infants aged 2 to 28 days but there was no statistically significant increase in risk associated with predominant breastfeeding (adjOR 1.91, 95% CI (0.60-6.09)). There were no modifications of these effects by birth weight. The sample size was insufficient to allow assessment of the impact of partial breastfeeding.


CONCLUSIONS
Improving early infant feeding practices is an effective, feasible, low-cost intervention that could reduce early infant mortality in LBW infants in developing countries. These findings are especially relevant for sub-Saharan Africa where many LBW infants are born at home, never taken to a health facility and mortality rates are unacceptably high.
Edmond
K M
KM
Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. Karen.Edmond@lshtm.ac.uk
Kirkwood
B R
BR
Tawiah
C A
CA
Owusu Agyei
S
S
Agyei
S O
SO
D000367:Age Factors; D001942:Breast Feeding / Q000706:statistics & numerical data; D005869:Ghana; D006801:Humans; D007226:Infant Mortality; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D007236:Infant, Small for Gestational Age; D016015:Logistic Models; D012424:Rural Population