The aims of the present study were to investigate the distribution of human papillomavirus (HPV) genotypes in cervical lesions, and the association between different HPV genotypes and cervical lesions. Between January 2013 and June 2014, the HPV type determinations of nucleic acid by use of fluorescence polymerase chain reaction (PCR) method of 15,192 outpatients in China-Japan Friendship Hospital were performed and the infection status was analyzed. The results showed that: i) 2,366 Cases were HPV positive and 12,826 cases were HPV negative, the overall infection rate was 15.57% (2,366/15,192), in which a single genotype of HPV infection rate was 11.63% (1,767/15,192), and multiple genotypes of HPV infection rate was 3.94% (599/15,192); ii) HPV16, HPV52 and HPV58 infections were the most common HPV genotypes, the infection rates were 3.95% (600/15,192), 2.86% (435/15,192) and 2.67% (406/15,192), respectively; and iii) According to the gold standard of histopathological analysis via hematoxylin-eosin staining, HPV16, HPV52 and HPV58 accounted for 58.80% (154/267) of all CIN2 or above squamous epithelial lesions. Furthermore, three cases with pathological changes of the cervical severe glandular epithelium were all HPV18 infection. The difference was statistically significant (chi(2)=60.74, P<0.001). Single HPV subtype infection was primarily associated with HPV16, HPV52 and HPV58. In conclusion, HPV type detection had a may be important in screening of cervical lesions as a difference in pathogenic ability was noted among different HPV genotypes. As cervical cancer is an infectious disease, HPV testing may help detect more precancerous lesions, thus reducing the morbidity and mortality of cervical cancer. HPV16, HPV52 and HPV58 were associated with severe cervical squamous epithelial lesions; HPV18 was associated with cervical severe glandular cell pathological changes, although it was not the most common HPV genotype in China. When positive, a clinical cervical examination should be conducted, including colposcopy and biopsy.