The integrated electricity-heat microgrid (IEHM) is characterized by low inertia and a high share of renewable generation. Although sector coupling in the IEHM enhances energy efficiency, the integration of electricity and heat systems restricts the primary frequency regulation (PFR) ability of coupling equipment, further threatening frequency security. This paper presents a frequency-secured planning method for virtual inertia suppliers and combined heat and power (CHP) units in the IEHM. First, we examine the PFR in IEHMs from both device and system perspectives. We develop steady-state models for sector-coupled equipment, specifically CHP units and large-scale heat pumps, for PFR and sizing purposes. To describe the system's frequency response under emergency conditions, we explicitly derive frequency constraints that account for varying system inertia of heterogeneous resources. Furthermore, we conduct a comprehensive analysis of the impact of PFR on heating systems within the IEHM. Second, we propose a frequency-constrained planning model for IEHMs based on the aforementioned modeling framework. This model balances the power supply, heating supply, and PFR reserves deployment of IEHM by properly sizing the regulation resources. It also leverages distributionally robust (DR) chance constraints to address uncertain wind power generation. To improve the tractability of this model, we introduce a well-tailored reformulation approach that handles the nonconvexity of system inertia and DR chance constraints. Case studies conducted on two test systems demonstrate the effectiveness of the proposed method in securing frequency stability while improving the economic performance of IEHM. This method ensures both dynamic and static frequency security across 100% of time steps by optimally deploying system inertia and PFR reserves. Moreover, by coordinating heterogeneous PFR resources with time-varying system inertia, the proposed approach yields superior economic performance, achieving over a 9% reduction in total capacity compared to average benchmarks.