Factors That Predict Differences in Childhood Mortality in Nigerian Communities: A Prognostic Model.
OBJECTIVE
To identify predictors of variations of childhood mortality between Nigerian communities and to identify high-risk communities where childhood mortality was higher than expected.


METHODS
Secondary analysis of the 2013 Nigeria Demographic and Health Survey data using prognostic univariable and multivariable mixed Poisson regression models. Likelihood ratio test, Hosmer-Lemeshow goodness-of-fit, and variance inflation factor were used to evaluate the fitness of the final model.


RESULTS
The final adjusted model revealed that communities with high rating of multiple childhood deprivation (relative risk 1.14, 95% CI 1.09-1.19) and maternal socioeconomic deprivation (relative risk 1.22, 95% CI 1.14-1.29) were associated significantly with the risk of childhood mortality. Communities with enhanced maternal hospital-based health-seeking behaviors and more advantageous environmental conditions had reduced risks of childhood mortality. Similarly, children living in communities with high ethnic diversity were significantly less likely to die before their fifth birthday (relative risk 0.96, 95% CI 0.94-0.97). About 64% of the observed heterogeneity in childhood mortality in these communities was explained by the final model. Eleven of the 896 communities had higher than expected childhood mortality rates during the study period.


CONCLUSIONS
Of the 31 482 children included in this survey, 2886 had died before their fifth birthday (128 deaths per 1000 live births). There are variations in childhood mortality across Nigerian communities that are not determined only by health system functions but also by factors beyond the scope of health authorities and healthcare delivery systems.
Division of Health Sciences, University of Warwick Medical School, Coventry, United Kingdom; National Institute for Health Research, Collaboration for Leadership in Applied Health Research and Care (CLAHRC), University of Warwick Medical School, Coventry, United Kingdom. Electronic address: v.t.adekanmbi@warwick.ac.uk.
Victor T
VT
Adekanmbi
Division of Health Sciences, University of Warwick Medical School, Coventry, United Kingdom; Department of Mathematics and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne, United Kingdom; Department of Population Health, Luxembourg Institute of Health, Luxembourg.
Ngianga-Bakwin
NB
Kandala
Division of Health Sciences, University of Warwick Medical School, Coventry, United Kingdom; Department of Population Health, Luxembourg Institute of Health, Luxembourg.
Saverio
S
Stranges
Warwick Center for Applied Health Research and Delivery, Division of Health Sciences, University of Warwick Medical School, Coventry, United Kingdom; Liverpool School of Tropical Medicine, International Health Group, Liverpool, United Kingdom.
Olalekan A
OA
Uthman
D002648:Child; D046688:Child Mortality; D006801:Humans; D015233:Models, Statistical; D009549:Nigeria / Q000453:epidemiology; D011379:Prognosis; D012111:Residence Characteristics; D012306:Risk