Templates modeling just the dominant mode of gravitational radiation are generally sufficient for the unbiased parameter inference of near-equal-mass compact binary mergers. However, neglecting the subdominant modes can bias the inference if the binary is significantly asymmetric, very massive, or has misaligned spins. In this work, we explore if neglecting these subdominant modes in the parameter estimation of nonspinning binary black hole mergers can bias the inference of their population-level properties such as mass and merger redshift distributions. Assuming the design sensitivity of the advanced LIGO-Virgo detector network, we find that neglecting subdominant modes will not cause a significant bias in the population inference, although including them will provide more precise estimates. This is primarily because asymmetric binaries are expected to be rarer in our detected sample, due to their intrinsic rareness and the observational selection effects. The increased precision in the measurement of the maximum black hole mass can help in better constraining the upper mass gap in the mass spectrum.