| Literature DB >> 28846616 |
Tongtong Liu1,2, Shunping Li3,4, Julie Ratcliffe5, Gang Chen6.
Abstract
There is a heavy burden of cervical cancer in China. Although the Chinese government provides free cervical cancer screening for rural women aged 35 to 59 years, the screening rate remains low even in the more developed regions of eastern China. This study aimed to assess knowledge and attitudes about cervical cancer and its screening among rural women aged 30 to 65 years in eastern China. A cross-sectional study was conducted in four counties of Jining Prefecture in Shandong Province during August 2015. In total, 420 rural women were randomly recruited. Each woman participated in a face-to-face interview in which a questionnaire was administered by a trained interviewer. A total of 405 rural women (mean age 49 years old) were included in the final study. Among them, 210 (51.9%) participants had high knowledge levels. An overwhelming majority, 389 (96.0%) expressed positive attitudes, whilst only 258 (63.7%) had undergone screening for cervical cancer. Related knowledge was higher amongst the screened group relative to the unscreened group. Age, education and income were significantly associated with a higher knowledge level. Education was the only significant factor associated with a positive attitude. In addition, women who were older, or who had received a formal education were more likely to participate in cervical cancer screening. The knowledge of cervical cancer among rural women in eastern China was found to be poor, and the screening uptake was not high albeit a free cervical cancer screening program was provided. Government led initiatives to improve public awareness, knowledge, and participation in cervical cancer screening programs would likely be highly beneficial in reducing cervical cancer incidence and mortality for rural women.Entities:
Keywords: China; attitude; cervical cancer; knowledge
Mesh:
Year: 2017 PMID: 28846616 PMCID: PMC5615504 DOI: 10.3390/ijerph14090967
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Socio-demographic characteristics of the participants in the four counties, n (%).
| Demographic Characteristics | County | ||||
|---|---|---|---|---|---|
| Qufu | Yutai | Sishui | Rencheng | Total | |
| 30–44 | 27 (26.0%) | 24 (23.8%) | 31 (31.3%) | 28 (27.7%) | 110 (27.2%) |
| 45–54 | 41 (39.4%) | 45 (44.5%) | 46 (46.5%) | 53 (52.5%) | 185 (45.6%) |
| 55–65 | 36 (34.6%) | 32 (31.7%) | 22 (22.2%) | 20 (19.8%) | 110 (27.2%) |
| Married | 100 (96.2%) | 99 (98.0%) | 96 (97.0%) | 95 (94.1%) | 390 (96.3%) |
| Divorced or widowed | 4 (3.8%) | 2 (2.0%) | 3 (3.0%) | 6 (5.9%) | 15 (3.7%) |
| No school | 21 (20.2%) | 26 (25.7%) | 50 (50.5%) | 14 (13.8%) | 111 (27.4%) |
| Primary school | 25 (24.0%) | 35 (34.7%) | 31 (31.3%) | 33 (32.7%) | 124 (30.6%) |
| Middle school | 47 (45.2%) | 31 (30.7%) | 13 (13.1%) | 43 (42.6%) | 134 (33.1%) |
| High school or above | 11 (10.6%) | 9 (8.9%) | 5 (5.1%) | 11 (10.9%) | 36 (8.9%) |
| <10,000 (1606) | 14 (13.5%) | 20 (19.8%) | 60 (60.6%) | 10 (9.9%) | 104 (25.7%) |
| 10,000–20,000 (1606–3212) | 21 (20.2%) | 28 (27.7%) | 19 (19.2%) | 36 (35.6%) | 104 (25.7%) |
| 20,000–30,000 (3212–4818) | 28 (26.9%) | 28 (27.7%) | 10 (10.1%) | 25 (24.8%) | 91 (22.4%) |
| >30,000 (4818) | 41 (39.4%) | 25 (24.8%) | 10 (10.1%) | 30 (29.7%) | 106 (26.2%) |
| 104 (25.7%) | 101 (24.9%) | 99 (24.5%) | 101 (24.9%) | 405 (100%) | |
According to the Organisation for Economic Co-operation and Development (OECD) data (https://data.oecd.org/conversion/exchange-rates.htm), the average annual exchange rate between US$ and RMB in 2015 was: US$1 = RMB 6.227. * Per capita disposable income of rural residents in China was RMB 11,422 (US$1834) (Year 2015). Per capita disposable income of rural residents in Shandong Province was RMB 12,930 (US$2077) (Year 2015).
Socio-demographic characteristics between screened and unscreened groups, n (%).
| Demographic Characteristics | Screened Group | Unscreened Group | χ2 | |
|---|---|---|---|---|
| 4.51 | 0.11 | |||
| 30–44 | 64 (24.8%) | 46 (31.3%) | ||
| 45–54 | 128 (49.6%) | 57 (38.8%) | ||
| 55–65 | 66 (25.6%) | 44 (29.9%) | ||
| 0.63 | 0.43 | |||
| Married | 247 (95.7%) | 143 (97.3%) | ||
| Divorced or widowed | 11 (4.3%) | 4 (2.7%) | ||
| 32.46 | 0.00 | |||
| No school | 47 (18.2%) | 64 (43.5%) | ||
| Primary school | 83 (32.2%) | 41 (27.9%) | ||
| Middle school | 100 (38.8%) | 34 (23.1%) | ||
| High school or above | 28 (10.8%) | 8 (5.5%) | ||
| 7.13 | 0.07 | |||
| <10,000 (1606) | 55 (21.3%) | 49 (33.3%) | ||
| 10,000–20,000 (1606–3212) | 71 (27.5%) | 33 (22.5%) | ||
| 20,000–30,000 (3212–4818) | 61 (23.7%) | 30 (20.4%) | ||
| >30,000 (4818) | 71 (27.5%) | 35 (23.8%) | ||
Related knowledge of cervical cancer and its screening among rural women of screened and unscreened groups, n (%).
| Screened Group | Unscreened Group | χ2 | ||
|---|---|---|---|---|
| Have you heard about cervical cancer? | 258 (100%) | 85 (57.8%) | 128.49 | 0.00 |
| Cervical cancer is not a genetic disease. | 162 (62.8%) | 39 (26.5%) | 49.25 | 0.00 |
| Cervical cancer has a long precancerous lesions period. | 169 (65.5%) | 60 (40.8%) | 23.23 | 0.00 |
| Cervical cancer can be detected in its earliest stages. | 206 (79.8%) | 65 (44.2%) | 53.69 | 0.00 |
| Cervical cancer is curable if detected early. | 155 (60.1%) | 41 (27.9%) | 38.85 | 0.00 |
| Patients can expect to live 10 more years after active treatments. | 87 (33.7%) | 18 (12.2%) | 22.49 | 0.00 |
| Postmenopausal women still have the risk of getting cervical cancer. | 166 (64.3%) | 53 (36.1%) | 30.17 | 0.00 |
| HPV infection is a necessary factor inducing cervical cancer. | 99 (38.4%) | 34 (23.1%) | 9.87 | 0.00 |
| HPV-positive women may not have cervical cancer. | 80 (31.0%) | 22 (15.0%) | 12.79 | 0.00 |
| Maintaining sexual hygiene can prevent cervical cancer. | 227 (88.0%) | 77 (52.4%) | 63.41 | 0.00 |
| Cervical cancer has no symptoms in the precancerous lesions period. | 150 (58.1%) | 55 (37.4%) | 16.09 | 0.00 |
| Postcoital bleeding is one of the symptoms of cervical cancer. | 75 (29.1%) | 19 (12.9%) | 13.70 | 0.00 |
| Early sexual activity is one of the risk factors of cervical cancer. | 70 (27.1%) | 23 (15.6%) | 6.98 | 0.01 |
| Cervical precancerous lesions may be detected by screening. | 231 (89.5%) | 74 (50.3%) | 77.37 | 0.00 |
| Women should be screened for cervical cancer at least every three years. | 7 (2.7%) | 1 (0.7%) | 1.09 | 0.30 |
| Cervical smear cytological examination is a major method for cervical cancer screening. | 60 (23.3%) | 13 (8.8%) | 13.16 | 0.00 |
| The main aim of cervical cancer screening is to discover precancerous lesion early. | 195 (75.6%) | 61 (41.5%) | 46.78 | 0.00 |
HPV: Human papillomavirus.
Adequacy of knowledge, attitude towards cervical cancer and its screening.
| % | ||
|---|---|---|
| Score > 8 | 210 | 51.9% |
| Score ≤ 8 | 195 | 48.1% |
| Positive | 389 | 96.0% |
| Negative | 16 | 4.0% |
| Ever screened | 258 | 63.7% |
| Never screened | 147 | 36.3% |
Associations of the adequacy of knowledge, attitude towards cervical cancer and its screening with socio-demographic characteristics.
| Demographic Characteristics | High Knowledge Level | Positive Attitude | Ever Screened | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Crude OR (95% CI) | Adjusted OR (95% CI) | Crude OR (95% CI) | Adjusted OR (95% CI) | Crude OR (95% CI) | Adjusted OR (95% CI) | |||||||
| 30–44 | 1 | - | 1 | - | 1 | - | 1 | - | 1 | - | 1 | - |
| 45–54 | 0.58 (0.36–0.95) | 0.03 | 0.70 (0.42–1.20) | 0.20 | 0.56 (0.06–5.42) | 0.61 | 0.89 (0.09–9.28) | 0.92 | 1.61 (0.99–2.64) | 0.06 | 2.12 (1.24–3.60) | 0.01 |
| 55–65 | 0.31 (0.18–0.54) | 0.00 | 0.48 (0.26–0.90) | 0.02 | 0.08 (0.01–0.59) | 0.01 | 0.25 (0.03–2.31) | 0.22 | 1.08 (0.63–1.85) | 0.78 | 2.22 (1.17–4.20) | 0.02 |
| Married | 1 | - | 1 | - | 1 | - | 1 | - | ||||
| Divorced or widowed | 0.81 (0.29–2.27) | 0.68 | 0.24 (0.05–1.18) | 0.08 | 0.63 (0.11–3.72) | 0.61 | 1.59 (0.50–5.09) | 0.43 | ||||
| No school | 1 | - | 1 | - | 1 | - | 1 | - | 1 | - | 1 | - |
| Primary school | 1.79 (1.05–3.05) | 0.03 | 1.31 (0.74–2.33) | 0.36 | 8.09 (1.78–36.71) | 0.01 | 4.01 (0.77–20.94) | 0.10 | 2.76 (1.62–4.69) | 0.00 | 3.31 (1.85–5.93) | 0.00 |
| Middle school or above | 5.07 (3.02–8.50) | 0.00 | 3.47 (2.00–6.02) | 0.00 | 22.42 (2.89–173.99) | 0.00 | 11.25 (1.33–95.20) | 0.03 | 4.15 (2.48–6.93) | 0.00 | 4.82 (2.72–8.56) | 0.00 |
| <10,000 (1606) | 1 | - | 1 | - | 1 | - | 1 | - | 1 | - | 1 | - |
| 10,000–20,000 (1606–$3212) | 2.43 (1.38–4.28) | 0.00 | 2.03 (1.12–3.67) | 0.02 | 12.18 (1.54–96.18) | 0.02 | 7.62 (0.93–62.64) | 0.06 | 1.92 (1.09–3.37) | 0.02 | 1.66 (0.91–3.03) | 0.10 |
| 20,000–30,000 (3212–$4818) | 3.60 (1.99–6.51) | 0.00 | 2.38 (1.27–4.47) | 0.01 | 3.47 (0.94–12.85) | 0.06 | 1.43 (0.34–5.92) | 0.63 | 1.81 (1.01–3.24) | 0.05 | 1.40 (0.74–2.63) | 0.30 |
| >30,000 (4818) | 4.03 (2.27–7.16) | 0.00 | 2.51 (1.35–4.65) | 0.00 | 12.42 (1.57–98.03) | 0.02 | 4.81 (0.57–40.71) | 0.15 | 1.81 (1.03–3.16) | 0.04 | 1.45 (0.78–2.69) | 0.24 |
Crude OR: odds ratio by univariate analysis; Adjusted OR: odds ratio by binary logistic regression models.