Factors associated with human papillomavirus infection – findings from a cervical cancer screening program for female employees in Beijing

Figures & data

Table 1 Demographic characteristics and the overall screening results

Characteristics	Total participants (n, %)
Age (years)
<25	45 (0.54%)
25–34	1695 (20.43%)
35–44	2708 (32.64%)
45–54	2452 (29.55%)
55–64	997 (12.02%)
≥65	400 (4.82%)
Occupation
Personnels from authority units and institutions	5898 (71.09%)
Taxi drivers	132 (1.59%)
Factory workers	134 (1.62%)
Sanitation workers	744 (8.97%)
Teachers	744 (8.97%)
Medical workers	645 (7.77%)
Menstrual status
Normal menstruation	5704 (68.75%)
Irregular menstruation	560 (6.75%)
Menopause	2033 (24.50%)
Marital status
Single but with a history of sexual activity	88 (1.06%)
Married	8209 (98.94%)
TCT
NILM	8181 (98.60%)
ASC-US/AGC	26 (0.31%)
ASC-H	15 (0.18%)
LSIL	51 (0.61%)
HSIL	23 (0.28%)
SCC	1 (0.01%)
HPV genotyping test
Negative	7128 (85.91%)
Positive	1169 (14.09%)
HR only	1078 (12.99%)
LR only	55 (0.66%)
HR & LR	36 (0.43%)
Multiple infections
1 type	912 (10.99%)
2 types	195 (2.35%)
3 types	44 (0.53%)
4 types	12 (0.14%)
5 types	2 (0.02%)
6 types	2 (0.02%)
7 types	1 (0.01%)
9 types	1 (0.01%)

Abbreviations: N, number; TCT, thinPrep cytology test; NILM, negative for intraepithelial lesions or malignancy; ASC-US, atypical squamous cells of undetermined significance; AGC, atypical glandular cells; LSIL, low-grade squamous intraepithelial lesion; HSIL, high-grade squamous intraepithelial lesion; ASC-H, atypical squamous cells-cannot exclude HSIL; SCC, squamous cell carcinoma; HPV, human papillomavirus; HR, high risk; LR, low risk.

Figure 1 Flow diagram of screened, enrolled and tested participants.

Figure 2 Distribution of human papillomavirus (HPV) subtypes in the study population.

Table 2 Findings from single-factor analysis

		HPV-positive (n=1169)	HPV-negative (n=7128)	χ^2	P-value
Occupation	Personnels from authority units and institutions	832 (14.11%)	5066 (85.89%)	29.73	0.000
	Taxi drivers	31 (23.48%)	101 (76.52%)
	Factory workers	7 (5.22%)	127 (94.78%)
	Sanitation workers	121 (16.26%)	623 (83.74%)
	Teachers	112 (15.05%)	632 (84.95%)
Medical workers	66 (10.23%)	579 (89.77%)
Menstrual status	Normal menstruation	797 (13.97%)	4907 (86.03%)	0.56	0.756
	Irregular menstruation	76 (13.57%)	484 (86.43%)
Menopause	296 (14.56%)	1737 (85.44%)
Marital status	Single but with a history of sexual activity	25 (28.41%)	63 (71.59%)	15.07	0.000
Married	1144 (13.94%)	7065 (86.06%)
Age (years)	<25	10 (22.22%)	35 (77.78%)	9.19	0.102
	25–34	247 (14.57%)	1448 (85.43%)
	35–44	370 (13.66%)	2338 (86.34%)
	45–54	321 (13.09%)	2131 (86.91%)
	55–64	162 (16.25%)	835 (83.75%)
≥65	59 (14.75%)	341 (85.25%)

Table 3 Findings from multiple binary logistic regression analysis

		β	SE	Wals	OR (95% CI)	P-value
Occupation (reference: personnels from authority units and institutions)	Taxi drivers	0.68	0.21	10.53	1.98 (1.31, 2.99)	0.001
	Factory workers	−1.03	0.39	6.92	0.36 (0.17, 0.77)	0.009
	Sanitation workers	0.20	0.11	3.49	1.22 (0.99, 1.51)	0.062
	Teachers	0.03	0.11	0.05	1.03 (0.82, 1.28)	0.821
Medical workers	−0.40	0.14	8.20	0.67 (0.51, 0.88)	0.004
Menstrual status (reference: normal menstruation)	Irregular menstruation	−0.02	0.14	0.02	0.98 (0.76, 1.28)	0.896
Menopause	−0.06	0.12	0.23	0.94 (0.74, 1.20)	0.636
Marital status (reference: married)	Single but with a history of sexual activity	0.84	0.26	10.91	2.32 (1.41, 3.82)	0.001
Age (years) (reference: <25 years)	25–34	−0.32	0.38	0.71	0.72 (0.34,1.53)	0.399
	35–44	−0.40	0.39	1.06	0.67 (0.32,1.43)	0.304
	45–54	−0.43	0.39	1.24	0.65 (0.30,1.39)	0.266
	55–64	−0.12	0.41	0.09	0.88 (0.40,1.96)	0.762
≥65	−0.24	0.42	0.32	0.79 (0.34,1.81)	0.571
Constant		−1.46	0.38	14.37		0.000

Abbreviations: β, regression co-efficient beta; SE, standard error.