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The movement of real users often follows patterns that can be characterized by certain statistical metrics of the contacts. Such metrics are useful for routing decisions, especially in sparse mobile ad hoc networks where node connectivity is opportunistic and messages are delivered using store-carry-forward routing. Past analysis on real-world data traces indicates that human behaviors affect the node contact pattern and spatial dependency exists among mobile nodes. A new metric called the expected dependent delay that characterizes the expected delay of a contact dependent on the previous hop is proposed. It characterizes the spatial dependency between neighboring contact pairs and reflects the regularity in node movement. In sparse opportunistic mobile ad hoc networks, a good approximation of the expected delay of a multihop path can be derived as the sum of the expected delay of the first hop and the expected dependent delays of later hops. We apply the proposed path-delay estimation to end-to-end routing. Simulation results show that compared with routing schemes that consider only the delivery probability or the expected delay, the proposed scheme can reduce the message delay significantly, when the network is sufficiently sparse and the spatial dependency is quantitatively constant over time. Moreover, the proposed method is tractable and can be easily implemented in combination with other routing techniques such as multipath routing and per-contact routing.