This study evaluates Nigeria's regional monitoring networks systems by assessing their effectiveness in reducing risk factors. A Bayesian hierarchical model was employed to analyse the data from Nigeria's regional monitoring networks. The model incorporates spatial and temporal variability with robust standard errors to account for uncertainty in measurements. The analysis revealed a significant reduction (p < 0.05) in risk factors across monitored regions, indicating effective implementation of the monitoring systems. The Bayesian hierarchical model demonstrates promise as an analytical tool for evaluating and improving regional monitoring networks in Nigeria. Further research should focus on integrating these models into existing monitoring frameworks to enhance their predictive accuracy and impact. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.