This paper presents a scenario-analysis framework for evaluating the impacts of local energy communities on distribution network performance and associated economic implications. A distribution network comprising residential, commercial, and industrial prosumers, defined as per their demand profiles, is considered. Scenarios are constructed based on all possible community compositions and benchmarked against a reference case in which prosumers purchase electricity under a self-consumption strategy. Each scenario is implemented in two stages. First, operating schedules are optimized to minimize total energy procurement cost. Second, optimized schedules are evaluated using linearized distribution power flow equations to assess network performance. Each scenario is evaluated using network KPIs, including maximum feeder loading and minimum nodal voltage, and economic KPIs, including energy cost, peak cost, and overall cost. The results suggest that local energy communities primarily achieve overall cost minimization through reductions in peak-related costs. Across all local energy community configurations, 13% cases exhibit a higher maximum line loading than in the reference case, with these instances predominantly associated with homogeneous prosumer compositions. This effect arises from the mismatch between local community demand patterns and aggregate feeder demand. While batteries reduce the peak of a homogeneous community, their charging during community low-demand hours can coincide with the feeder peak, leading to higher maximum line loading at the network level.