Reducing acute respiratory infections in under-five children in Nigeria through the mirror of risk factors: a cross-sectional study.

BACKGROUND

Globally, acute respiratory infections (ARIs) account for nearly 20% of all deaths among children under five years old. In low- and middle-income countries, the prevalence of ARIs ranges from 1.9 to 60.2%, with socioeconomic conditions significantly increasing the risk. Despite advancements in the management of ARIs in Nigeria, the country has not yet met global control targets.

METHODS

This cross-sectional study investigated the spatial heterogeneity of identified ARI risk factors in under-five children in Nigeria with the goal of determining which to address in each location, utilizing data from the 2021 Multiple Indicator Cluster Survey (MICS) and the 2018 Nigeria Demographic and Health Survey. The study employed multiple linear regression (MLR) and geographically weighted regression (GWR) analyses, taking the percentage of children aged 0-59 months for whom the mother/caretaker reported symptoms of ARI during the 2021 MICS as the dependent variable and the identified risk factors as independent variables, at 0.05 significance level.

RESULTS

A north-south divide was noted in the reported ARIs cases, with higher number of cases in the northern region. The fitted MLR model was significant, with multiple R of 0.61 and adjusted R of 0.42, indicating that the model explained a substantial portion of the variance in ARIs. Poor sanitation emerged as the only significant risk factor of ARIs. The GWR analysis yielded a quasi R of 0.66. The coefficients of the ARI risk factors showed considerable spatial variation. Factors such as low housing quality, poverty, inadequate sanitation, and the percentage of mothers who had their first live birth during their teenage years appear to be the primary contributors to the high burden of ARIs in northern Nigeria.

CONCLUSION

While the study highlights the spatial heterogeneity of ARI risk factors, it provides information on the factors to prioritize per state for effective control interventions.