Aging in place (AiP), as a lifestyle choice policy, has been adopted internationally as a response to population aging. Range aggregation, which is a process that computes the total number of counts for a configured range, is one of the most fundamental methods in AiP to enable the healthcare center to have a comprehensive view of health trends and better monitor the overall health and well-being of the elderly in a given area. However, this aggregation process inevitably introduces security and privacy risks attracting significant research attention. While many privacy-preserving schemes supporting aggregation have been proposed, they either fail to match the range aggregation in the AiP scenario, or incur high computational costs when aggregating numerous data due to the employed homomorphic encryption. To address these challenges, we propose an efficient edge-based privacy-preserving range aggregation scheme for the AiP system. Our scheme employs the superincreasing sequence technique to encode the query vector so that the query user can obtain multiple types of aggregation results within a query and utilizes the one-time matrix encryption technique and the additive secret sharing technique to safeguard sensitive information. Security analysis demonstrates that our proposed scheme can achieve privacy preservation in the range aggregation. In addition, extensive experiments also indicate its high efficiency.