Mobile devices with ever increasing functionality are an important driving force behind innovative mobile applications that enrich our daily life. The ubiquitous availability of wireless data communication networks is an additional driving force. Their ability to support application data flows is one of the performance criteria for successful mobile application deployment. Nevertheless, the quantitative impact of this performance is unknown and practically infeasible to determine at real-time at the application-level due to mobile device resource constraints. We research practical methods for measurementbased application-level performance evaluation of data communication networks that support mobile application data flows. In this paper, we apply the lightweight Comparative Output-Input Analysis (COIA) method that estimates additional delay at observation time scale of interest (e.g. 1 s) induced on the application data flow. The additional delay is the amount of delay exceeding non-avoidable, minimal end-to-end data delay caused by data communication network propagation and transmission delays. We propose Ave COIA methods to estimate the additional delay. We validate their accuracy with measurements obtained from an m-health application, namely health telemonitoring provided by the MobiHealth system. Despite their simplicity, our methods prove to be accurate in relation to the observation time scale of interest, and robust under a variety of network conditions. The methods offer novel insights into the impact of data communication network performance on the application data flow delay behaviour.