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This work focuses on the clustering in Wireless Body Area Network (WBAN). Recently, it was found that less attention was given to Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) clustering in WBAN. Past works on LoS clustering WBAN consider the problem of enhancing the network throughput and end-to-end delay of the network. However, the problem of necessary hop count for packet transmission has not been considered. The non-consideration of necessary nodes hop count degrades the performance of cluster-based WBAN as throughput of the network is reduced in addition to high end-to-end delay. This work develops a hop count aware WBAN for enhancing the performance of body nodes called improved Dual Sink Approach using Clustering in Body Area Network (iDSCB). The simulation results depicted that the hop distance criterion of iDCSB improved the performance of WBAN in terms of end-to-end delay and throughput by 3.16% and 6.59%, respectively.