Boolean　range　query　(BRQ)　is　a　typical　type　of　spatial　keyword　query　that　is　widely　used　in　geographic　information　systems,　location-based　services　and　other　applications.　It　retrieves　the　objects　inside　the　query　range　and　containing　all　query　keywords.　Many　privacy-preserving　BRQ　schemes　have　been　proposed　to　support　BRQ　over　encrypted　data.　However,　most　of　them　fail　to　achieve　efficient　retrieval　and　lightweight　result　verification　while　suppressing　access　and　search　pattern　leakage.　Thus,　in　this　paper,　we　propose　an　efficient　verifiable　privacy-preserving　Boolean　range　query　with　suppressed　leakage.　Firstly,　we　convert　BRQ　into　multi-keyword　query　by　using　Gray　code　and　Bloom　filter.　Then,　we　achieve　efficient　oblivious　multi-keyword　query　by　combining　distributed　point　function　and　PRP-based　Cuckoo　hashing,　which　protects　the　access　and　search　patterns.　Moreover,　we　support　lightweight　and　oblivious　result　verification　based　on　oblivious　query,　aggregate　MAC,　keyed-hashing　MAC　and　XOR-homomorphic　pseudorandom　function.　It　enables　query　users　to　verify　the　result　integrity　with　a　proof　whose　size　is　independent　of　the　size　of　the　outsourced　dataset.　Finally,　formal　security　analysis　and　extensive　experiments　demonstrate　that　our　proposed　scheme　is　adaptively　secure　and　efficient　for　practical　applications,　respectively.