The vast amount of recombination information in the human genome has long been ignored or deliberately avoided in studies on human population genetic relationships. One reason is that estimation of the recombination parameter from genotyping data is computationally challenging and practically difficult. Here we propose chromosome-wide haplotype sharing (CHS) as a measure of genetic similarity between human populations, which is an indirect approach to integrate recombination information. We showed in both empirical and simulated data that recombination differences and genetic differences between human populations are strongly correlated, indicating that recombination events in different human populations are evolutionarily related. We further demonstrated that CHS can be used to reconstruct reliable phylogenies of human populations and the majority of the variation in CHS matrix can be attributed to recombination. However, for distantly related populations, the utility of CHS to reconstruct correct phylogeny is limited, suggesting that the linear correlation of CHS and population divergence could have been disturbed by recurrent recombination events over a large time scale. The CHS we proposed in this study is a practical approach without involving computationally challenging and time-consuming estimation of recombination parameter. The advantage of CHS is rooted in its integration of both drift and recombination information, therefore providing additional resolution especially for populations separated recently.