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The objective of this study is to investigate the effects of respiratory motion (RM) on defect detection in Tc-99m sestamibi myocardial perfusion SPECT (MPS) using a phantom population that includes patient variability. Three RM patterns are included, namely breath-hold, slightly enhanced normal breathing, and deep breathing. For each RM pattern, six 4-D NCAT phantoms were generated, each with anatomical variations. Anterior, lateral and inferior myocardial defects with different sizes and contrasts were inserted. Noise-free SPECT projections were simulated using an analytical projector. Poisson noise was then added to generate noisy realizations. The projection data were reconstructed using the OS-EM algorithm with 1 and 4 subsets/iteration and at 1, 2, 3, 5, 7, and 10 iterations. Short-axis images centered at the centroid of the myocardial defect were extracted, and the channelized Hotelling observer (CHO) was applied for the detection of the defect. The CHO results show that the value of the area under the receiver operating characteristics (ROC) curve (AUC) is affected by the RM amplitude. For all the defect sizes and contrasts studied, the highest or optimal AUC values indicate maximum detectability decrease with the increase of the RM amplitude. With no respiration, the ranking of the optimal AUC value in decreasing order is anterior then lateral, and finally inferior defects. The AUC value of the lateral defect drops more severely as the RM amplitude increases compared to other defect locations. Furthermore, as the RM amplitude increases, the AUC values of the smaller defects drop more quickly than the larger ones. We demonstrated that RM affects defect detectability of MPS imaging. The results indicate that developments of optimal data acquisition methods and RM correction methods are needed to improve the defect detectability in MPS.