With the prevalence of chronic diseases that account for a significant portion of deaths, a new approach to life insurance has emerged to address this issue. The new approach integrates health rewards programs with life insurance products; the insured are classified by fitness statuses according to their level of participation and would get premium reductions at the superior statuses. We introduce a Markov chain process to model the dynamic transition of the fitness statuses, which are linked to corresponding levels of mortality risks reduction. We then embed this transition process into a stochastic multi-state model to describe the new life insurance product. Formulas are given for calculating its benefit, premium, reserve and surplus. These results are compared with those of the traditional life insurance. Numerical examples are given for illustration.