Abstract
Background
Timely presentation and diagnosis of cervical cancer (CC) are crucial to decrease its mortality especially in low- and middle-income countries like Palestine. This study aimed to evaluate the knowledge of Palestinian women about CC warning signs and determine the factors associated with good knowledge.
Methods
This was a national cross-sectional study conducted between July 2019 and March 2020 in Palestine. Stratified convenience sampling was used to recruit adult women from hospitals, primary healthcare centers, and public spaces of 11 governorates. A translated-into-Arabic version of the validated CC awareness measure (CeCAM) was used to assess women’s knowledge of 12 CC warning signs.
Results
Of 8086 approached, 7223 participants completed the CeCAM (response rate = 89.3%). A total of 7058 questionnaires were included in the analysis: 2655 from the Gaza Strip and 4403 from the West Bank and Jerusalem (WBJ). The median age [interquartile range] for all participants was 34.0 [24.0, 42.0] years. Participants recruited from the WBJ were older, getting higher monthly income, and having more chronic diseases than those recruited from the Gaza Strip.
The most frequently identified warning sign was ‘vaginal bleeding after menopause’ (n = 5028, 71.2%) followed by ‘extreme generalized fatigue’ (n = 4601, 65.2%) and ‘unexplained weight loss’ (n = 4578, 64.9%). Only 1934 participants (27.4%) demonstrated good knowledge of CC warning signs. Participants from the Gaza Strip were slightly more likely than participants from the WBJ to have a good level of knowledge. Factors associated with having good knowledge included having a bachelor or postgraduate degree, being married, divorced, or widowed as well as knowing someone with cancer.
Conclusion
The overall awareness of CC warning signs was low. Educational interventions are needed to increase Palestinian women’s awareness of CC warning signs.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-021-11792-8.
Keywords: Cervical cancer, Early detection, Survival, Symptom, Warning sign, Awareness, Knowledge, Early presentation, Palestine
Background
Cervical cancer (CC) is the most common gynecological cancer worldwide [1, 2]. The global annual deaths related to CC are over 300,000 with half of these deaths occurring in countries with low and medium human development indices [2]. In a recent international report, the age-standardized incidence and mortality rates of CC were 13.3 and 7.3 per 100,000 females, respectively [2]. In the Eastern Mediterranean region, the estimated age-standardized incidence and mortality rates of CC were 5.3 and 3.4 per 100,000 females, respectively [3]. In 2018, Palestine had a relatively low age-standardized incidence rate of 2.5 per 100,000 females. However, Palestine had a higher age-standardized mortality rate of 1.9 per 100,000 females than some other countries in the region such as Iraq (1.3 per 100,000 females), Yemen (1.4 per 100,000 females), Saudi Arabia (1.5 per 100,000 females), and Jordan (1.8 per 100,000 females) [4].
CC is one of the most preventable and treatable cancers especially if the premalignant lesions are detected and treated early before progressing to malignancy [5]. Survival rates of CC also vary depending on the stage at the time of diagnosis with better prognosis among women diagnosed with early-stage disease [6–8]. Therefore, early diagnosis is crucial to decrease mortality related to CC. Several factors were reported to play a role in delaying the diagnosis of CC including low awareness of CC warning signs, limited access to healthcare services, and emotional barriers to seek medical advice (e.g., feeling scared) [9–12].
In Palestine, there are no screening programs for CC or vaccination program for the main cause of CC, human papillomavirus (HPV) [13]. This further increases the importance of determining women’s knowledge of CC warning signs as it may impact their decision to visit doctors [12, 14]. In addition, assessment of the existing awareness of CC warning signs will help to guide future educational interventions aiming to increase public awareness [14, 15]. Greater public awareness of CC warning signs may lead to shortening the time to seek medical advice, which in turn facilitates early detection of CC and increases survival rates [16–18]. This is especially important where no screening programs for CC exist as in Palestine.
This national study aimed to: (i) assess the women’s level of knowledge of CC warning signs in the Palestinian community, (ii) compare this knowledge among women recruited from the Gaza Strip vs. the West Bank and Jerusalem (WBJ), and (iii) determine the factors associated with good knowledge of CC warning signs.
Methods
Study design, population, and settings
A national cross-sectional study was conducted from July 2019 to March 2020 in Palestine. Adult Palestinian women were the target population and were recruited to participate in this study from hospitals, primary healthcare centers (PHCs), and public spaces. Governmental hospitals and PHCs are the main sites for providing healthcare services in Palestine and are distributed in two main geographical areas: (i) the Gaza Strip and (ii) the WBJ. Governmental general hospitals with a bed capacity of more than 100 and PHCs with level four services (i.e., providing all primary healthcare services) were eligible. Public spaces in the same governorates of hospitals and PHCs were also involved. These included markets, downtowns, mosques, churches, parks, malls, and restaurants.
In 2020, the unemployment rate of Palestinian women was 40.1% (46.6% in the Gaza Strip vs. 15.7% in the WBJ) [19]. In 2021, 1,454,846 women are 18 years or over, representing 27.9% of the total population of 5,222,748 [20]. Palestinian adult women (aged 18 or older), attending one of the data collection sites, were invited to participate. Participants were excluded if they were holding a citizenship other than Palestinian, visiting the oncology departments, and working or studying in a health-related field.
Sampling methods
The Palestinian MoH has 43 hospitals; 29 of them are in the West Bank and 14 are in the Gaza Strip. There are 11 general MoH hospitals with a bed capacity of more than 100; six in the West Bank and five in the Gaza Strip [17]. Jerusalem has no hospitals that belong to the MoH. However, non-governmental organizations (NGOs) own two general hospitals with a bed capacity of more than 100. The Palestinian MoH also has 475 PHCs. Among them, 26 are level four: 17 are in the WBJ and nine in the Gaza Strip [17]. In 2019, the estimated female population aged 15 years or older in the WBJ was 947,100 females while that in the Gaza Strip was 587,271 females (ratio 1:1.6) [21]. Therefore, stratified convenience sampling was used to achieve a similar ratio in the two regions and participants were recruited from 11 hospitals, 12 PHCs, and public spaces in 11 out of 16 governorates of Palestine: seven in the WBJ and four in the Gaza Strip.
Questionnaire and data collection
The Cervical Cancer Awareness Measure (CeCAM), which is a validated standardized questionnaire developed to measure the awareness of CC in the general population, was used [8]. The questionnaire consisted of two sections. The first section included socio-demographic questions such as age, menarche, highest level of education, occupation, monthly income, marital status, place of residency, having a chronic disease, and knowing someone with cancer. The second section comprised of one question based on a 4-point Likert scale (1 = not at all confident, 4 = very confident) to ask the participants about their confidence on noticing possible CC warning signs and 12 questions using a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) to assess their knowledge of CC warning signs.
To minimize the possibility of participants answering questions randomly, the questions in the original CeCAM with yes/no/unknown responses were modified into 5-point Likert scale questions. Meanwhile, the participants’ responses were converted to correct/incorrect responses similar to what was done in previous studies [11, 12]. The sign of ‘extreme generalized fatigue’ was added to the questionnaire since it was mentioned in other forms of the Cancer Awareness Measure [22, 23], and it was thought that it would be helpful to include it in the context of CC.
The questionnaire passed through the process of translation and adaptation of instruments recommended by the World Health Organization [24]. It was translated from English to Arabic by two bilingual healthcare professionals and then back-translated into English by another two bilingual healthcare professionals who had relevant clinical and research experiences in gynecology, public health, and survey design. A pilot study was conducted with 130 respondents to test the clarity of the questions of the Arabic CeCAM. These were not included in the final study. Internal consistency was measured using Cronbach’s Alpha, which reached an acceptable value (α =0.816).
Participants were invited to face-to-face interviews for the completion of the questionnaire. Data were collected utilizing the secure, user-friendly data collection tool ‘Kobo Toolbox’ which is accessed via smartphones [25]. It allowed using a pre-designed data collection sheet with tick boxes and dropdown menus for easy and quick data collection and entry. Female data collectors with a medical background were trained on how to use the electronic tool and how to recruit participants, approach them, and facilitate completion of the questionnaire.
Statistical analysis
Descriptive statistics were utilized to summarize participant characteristics. For continuous non-normally distributed variables, the median and interquartile range were used to describe them. Categorical variables were summarized using frequencies and percentages. Age was categorized into three groups to reflect the age-associated risk of CC (21–40 years) [8]. The minimum wage in Palestine is 1450 NIS, which is about $450 [26]. Therefore, it was used to divide the participants in terms of their monthly income into two groups. Baseline characteristics of participants from the Gaza Strip vs. the WBJ were compared using Kruskal-Wallis test if they were continuous or using Pearson’s Chi-square test if they were categorical.
Frequencies and percentages were used to describe the confidence of participants to detect possible CC warning signs with a comparison being made using Pearson’s Chi-Square test. As for recognizing CC warning signs, answering with ‘strongly agree’ or ‘agree’ was considered as a correct answer, while answering with ‘strongly disagree’, ‘disagree’, or ‘not sure’ was considered as an incorrect answer. CC warning signs were categorized into three categories: signs with blood, signs with pain, and signs of a non-specific nature. Frequencies and percentages were utilized to describe the recognition of each of the CC warning signs with comparisons being performed using Pearson’s Chi-Square test. Then, bivariable and multivariable logistic regression analyses were used to test the association between recognizing each warning sign and participant characteristics. Results of the bivariable analyses are provided in the supplementary materials, please see Additional file 1. The model of the multivariable analysis included all participants and adjusted for the following variables: age-group, educational level, occupation, monthly income, place of residency, marital status, having a chronic disease, knowing someone with cancer, and site of data collection. The model was pre-specified based on previous studies [8, 27–29].
To evaluate the participants’ knowledge level of CC warning signs, a scoring system was adopted from previous studies [11, 18]. Each correct answer was given one point. The total score was calculated and ranged from 0 to 12. It was then categorized into three categories: poor knowledge (0 to 4), fair knowledge (5 to 8), and good knowledge (9 to 12). A comparison in the knowledge level between the Gaza Strip vs. the WBJ was made using Pearson’s Chi-Square test. The association between participant characteristics and having a good level of knowledge was tested using bivariable and multivariable logistic regression with the same model mentioned above. Missing data were completely random and were handled using complete case analysis. Data were analyzed using Stata software version 15.0 (StataCorp, College Station, Texas, United States).
Results
Characteristics of participants
Of the 8086 participants approached, 7223 completed the questionnaire (response rate = 89.3%). A total of 7058 questionnaires was included in the analysis (30 did not meet inclusion criteria and 135 had missing values); 2655 from the Gaza Strip and 4403 from the WBJ. The median age [IQR] for all participants was 32.0 years [24.0, 42.0] (Table 1). Participants recruited from the WBJ were older, getting higher monthly income, and having more chronic diseases than those recruited from the Gaza Strip.
Table 1.
Characteristics of study participants
| Characteristic | Total (n = 7058) |
Gaza Strip (n = 2655) |
WBJ (n = 4403) |
p-value |
|---|---|---|---|---|
| Age, median [IQR] | 32 [24, 42] | 30 [24, 39] | 33 [24, 44] | < 0.001 |
| Age group, n (%) | ||||
| 18 to 20 | 756 (10.7) | 249 (9.4) | 507 (11.5) | < 0.001 |
| 21 to 40 | 4331 (61.4) | 1809 (68.1) | 2522 (57.3) | |
| 41 or older | 1971 (27.9) | 597 (22.5) | 1374 (31.2) | |
| Educational level, n (%) | ||||
| Illiterate | 127 (1.8) | 37 (1.4) | 90 (2.0) | < 0.001 |
| Primary | 409 (5.8) | 127 (4.8) | 282 (6.4) | |
| Preparatory | 1064 (15.1) | 378 (14.2) | 686 (15.6) | |
| Secondary | 2293 (32.5) | 955 (36.0) | 1338 (30.4) | |
| Diploma | 766 (10.9) | 303 (11.4) | 463 (10.5) | |
| Bachelor | 2261 (32.0) | 817 (30.8) | 1444 (32.8) | |
| Postgraduate | 138 (1.9) | 38 (1.4) | 100 (2.3) | |
| Occupation, n (%) | ||||
| Housewife | 4647 (65.8) | 2008 (75.6) | 2639 (59.9) | < 0.001 |
| Employed | 1476 (20.9) | 348 (13.1) | 1128 (25.6) | |
| Retired | 69 (1.0) | 11 (0.4) | 58 (1.3) | |
| Student | 866 (12.3) | 288 (10.9) | 578 (13.2) | |
| Monthly income ≥ 1450 NIS, n (%) | 4666 (66.1) | 693 (26.1) | 3973 (90.2) | < 0.001 |
| Having a chronic disease, n (%) | 1397 (19.8) | 417 (15.7) | 980 (22.3) | < 0.001 |
| Knowing someone with cancer, n (%) | 4083 (57.9) | 1483 (55.9) | 2600 (59.1) | < 0.001 |
| Marital status, n (%) | ||||
| Single | 1657 (23.4) | 527 (19.8) | 1130 (25.6) | < 0.001 |
| Married | 5058 (71.7) | 2025 (76.3) | 3033 (68.9) | |
| Divorced | 154 (2.2) | 45 (1.7) | 109 (2.5) | |
| Widowed | 189 (2.7) | 58 (2.2) | 131 (3.0) | |
| Site of data collection, n (%) | ||||
| Public spaces | 2695 (38.2) | 863 (32.5) | 1832 (41.7) | < 0.001 |
| Hospitals | 1890 (26.8) | 642 (24.2) | 1248 (28.3) | |
| Primary healthcare centers | 2473 (35.0) | 1150 (43.3) | 1323 (30.0) | |
n number of participants, IQR interquartile range, WBJ West Bank and Jerusalem
Confidence and recognition of CC warning signs
Only 2122 participants (30.0%) felt confident to notice a possible CC warning sign. Participants from the Gaza Strip were more likely to have confidence than participants from the WBJ (33.9% vs 27.7%). Warning signs with blood were the most commonly recognized signs followed by signs of a nonspecific nature and those with pain (Table 2). The most frequently identified sign was ‘vaginal bleeding after menopause’ (n = 5028, 71.2%) followed by ‘extreme generalized fatigue’ (n = 4601, 65.2%) and ‘unexplained weight loss’ (n = 4578, 64.9%). Those warning signs were also the most identified signs in both the Gaza Strip and WBJ.
Table 2.
Recognition of cervical cancer warning signs
| Category of warning signs | Warning sign | Total (n = 7058) n (%) |
Gaza Strip (n = 2655) n (%) |
WBJ (n = 4403) n (%) |
p-value |
|---|---|---|---|---|---|
| Warning signs with blood | Vaginal bleeding after menopause | 5028 (71.2) | 2051 (77.3) | 2977 (67.6) | < 0.001 |
| Vaginal bleeding between periods | 4190 (59.4) | 1729 (65.1) | 2461 (55.9) | < 0.001 | |
| Having menstrual periods that are heavier or longer than usual | 4142 (58.7) | 1648 (62.1) | 2494 (56.6) | < 0.001 | |
| Vaginal bleeding during or after sex | 3684 (52.2) | 1480 (55.7) | 2204 (50.1) | < 0.001 | |
| Blood in the stool or urine | 3496 (49.5) | 1175 (44.3) | 2321 (52.7) | < 0.001 | |
| Warning signs with pain | Persistent pelvic pain | 4188 (59.3) | 1592 (60.0) | 2596 (59.0) | 0.41 |
| Unusual discomfort or pain during sex | 3308 (46.9) | 1285 (48.4) | 2023 (45.9) | 0.045 | |
| Persistent lower back pain | 2941 (41.7) | 1144 (43.1) | 1797 (40.8) | 0.06 | |
| Warning signs with nonspecific nature | Extreme generalized fatigue | 4601 (65.2) | 1773 (66.8) | 2828 (64.2) | 0.029 |
| Unexplained weight loss | 4578 (64.9) | 1759 (66.3) | 2819 (64.0) | 0.06 | |
| Persistent vaginal discharge that smells un-pleasant | 3123 (44.3) | 1137 (42.8) | 1986 (45.1) | 0.06 | |
| Persistent diarrhea | 1551 (22.0) | 580 (21.8) | 971 (22.1) | 0.84 |
n number of participants, WBJ West Bank and Jerusalem
Recognizing CC warning signs with blood
Women aged 21 to 40 years were less likely than younger women (i.e., 18–20 years) to recognize ‘vaginal bleeding between periods’ (OR = 0.80, 95% CI: 0.65–0.98) (Table 3). In addition, women aged ≥41 years were less likely than younger women to recognize ‘blood in the stool or urine’ (OR = 0.77, 95% CI: 0.61–0.96). Participants who were married, of higher education (i.e., bachelor and above), and were living in the Gaza Strip had a higher likelihood to identify all warning signs with blood except ‘blood in the stool or urine’. Women who knew someone with cancer were more likely than women who did not to recognize all warning signs with blood.
Table 3.
Association between recognizing cervical cancer warning signs with blood and sociodemographic factors
| Characteristic | Vaginal bleeding after menopause | Vaginal bleeding between periods | Having menstrual periods that are heavier or longer than usual | Vaginal bleeding during or after sex | Blood in the stool or urine | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n (%) | AOR (95% CI)a |
p-value | n (%) | AOR (95% CI)a |
p-value | n (%) | AOR (95% CI)a |
p-value | n (%) | AOR (95% CI)a |
p-value | n (%) | AOR (95% CI)a |
p-value | |
| Age group | |||||||||||||||
| 18 to 20 | 551 (11.0) | Ref | Ref | 463 (11.1) | Ref | Ref | 398 (9.6) | Ref | Ref | 301 (8.2) | Ref | Ref | 444 (12.7) | Ref | Ref |
| 21 to 40 | 3098 (61.6) | 0.84 (0.67–1.05) | 0.12 | 2533(60.5) | 0.80 (0.65–0.98) | 0.028 | 2523 (60.9) | 1.04 (0.85–1.27) | 0.70 | 2333 (63.3) | 1.07 (0.87–1.31) | 0.53 | 2141 (61.2) | 0.82 (0.67–1.00) | 0.053 |
| 41 or older | 1379 (27.4) | 0.91 (0.71–1.18) | 0.49 | 1194 (28.5) | 0.99 (0.78–1.24) | 0.92 | 1221 (29.5) | 1.24 (0.98–1.55) | 0.07 | 1050 (28.5) | 1.16 (0.92–1.45) | 0.22 | 911 (26.1) | 0.77 (0.61–0.96) | 0.021 |
| Educational level | |||||||||||||||
| Illiterate | 72 (1.4) | Ref | Ref | 58 (1.4) | Ref | Ref | 65 (1.6) | Ref | Ref | 61 (1.7) | Ref | Ref | 59 (1.7) | Ref | Ref |
| Primary | 256 (5.1) | 1.22 (0.80–1.84) | 0.35 | 210 (5.0) | 1.17 (0.78–1.76) | 0.45 | 236 (5.7) | 1.29 (0.86–1.93) | 0.22 | 173 (4.7) | 0.73 (0.48–1.10) | 0.13 | 183 (5.2) | 0.92 (0.61–1.38) | 0.68 |
| Preparatory | 740 (14.7) | 1.67 (1.13–2.46) | 0.009 | 621 (14.8) | 1.61 (1.10–2.36) | 0.014 | 651 (15.7) | 1.55 (1.06–2.26) | 0.024 | 548 (14.9) | 1.06 (0.73–1.55) | 0.75 | 490 (14.0) | 0.93 (0.64–1.36) | 0.71 |
| Secondary | 1642 (32.7) | 1.94 (1.32–2.83) | 0.001 | 1350 (32.2) | 1.75 (1.20–2.54) | 0.004 | 1358 (32.8) | 1.57 (1.08–2.29) | 0.017 | 1184 (32.1) | 1.25 (0.86–1.82) | 0.24 | 1152 (33.0) | 1.05 (0.72–1.52) | 0.81 |
| Diploma | 553 (11.0) | 2.40 (1.59–3.60) | < 0.001 | 454 (10.8) | 2.03 (1.36–3.03) | < 0.001 | 431 (10.4) | 1.49 (1.01–2.21) | 0.047 | 373 (10.1) | 1.24 (0.83–1.84) | 0.29 | 354 (10.1) | 0.94 (0.63–1.39) | 0.76 |
| Bachelor | 1663 (33.1) | 2.56 (1.73–3.80) | < 0.001 | 1411 (33.7) | 2.38 (1.62–3.50) | < 0.001 | 1313 (31.7) | 1.65 (1.13–2.42) | 0.010 | 1254 (34.0) | 1.78 (1.21–2.61) | 0.003 | 1190 (34.0) | 1.12 (0.77–1.64) | 0.56 |
| Postgraduate | 102 (2.0) | 2.98 (1.72–5.18) | < 0.001 | 86 (2.1) | 2.54 (1.51–4.29) | < 0.001 | 88 (2.1) | 2.02 (1.20–3.40) | 0.008 | 91 (2.5) | 2.76 (1.63–4.68) | < 0.001 | 68 (1.9) | 0.99 (0.59–1.64) | 0.96 |
| Occupation | |||||||||||||||
| Housewife | 3361 (66.8) | Ref | Ref | 2784 (66.4) | Ref | Ref | 2787 (67.3) | Ref | Ref | 2515 (68.3) | Ref | Ref | 2226 (63.7) | Ref | Ref |
| Employed | 1008 (20.0) | 0.73 (0.63–0.86) | < 0.001 | 852 (20.3) | 0.86 (0.75–1.00) | 0.051 | 872 (21.1) | 1.05 (0.91–1.22) | 0.49 | 788 (21.4) | 1.00 (0.87–1.16) | 0.98 | 749 (21.4) | 0.94 (0.81–1.08) | 0.37 |
| Retired | 32 (0.6) | 0.30 (0.18–0.50) | < 0.001 | 30 (0.7) | 0.46 (0.28–0.77) | 0.003 | 25 (0.6) | 0.40 (0.24–0.67) | 0.001 | 28 (0.8) | 0.71 (0.42–1.20) | 0.21 | 19 (0.5) | 0.43 (0.25–0.76) | 0.003 |
| Student | 627 (12.5) | 0.92 (0.73–1.16) | 0.48 | 524 (12.5) | 1.02 (0.82–1.27) | 0.86 | 458 (11.1) | 1.03 (0.83–1.27) | 0.82 | 353 (9.6) | 1.01 (0.81–1.25) | 0.94 | 502 (14.4) | 1.03 (0.83–1.27) | 0.80 |
| Monthly income | |||||||||||||||
| < 1450 NIS | 1767 (35.1) | Ref | Ref | 1475 (35.2) | Ref | Ref | 1461 (35.3) | Ref | Ref | 1285 (34.9) | Ref | Ref | 1096 (31.4) | Ref | Ref |
| ≥ 1450 NIS | 3261 (64.9) | 1.16 (0.99–1.35) | 0.06 | 2715 (64.8) | 1.12 (0.97–1.29) | 0.11 | 2681 (64.7) | 0.99 (0.86–1.14) | 0.93 | 2399 (65.1) | 1.02 (0.89–1.18) | 0.98 | 2400 (68.6) | 0.95 (0.83–1.09) | 0.37 |
| Residency | |||||||||||||||
| Gaza Strip | 2051 (40.8) | Ref | Ref | 1729 (41.3) | Ref | Ref | 1648 (39.8) | Ref | Ref | 1480 (40.2) | Ref | Ref | 1175 (33.6) | Ref | Ref |
| WBJ | 2977 (59.2) | 0.58 (0.50–0.67) | < 0.001 | 2461 (58.7) | 0.64 (0.56–0.74) | < 0.001 | 2494 (60.2) | 0.81 (0.71–0.92) | 0.002 | 2204 (59.8) | 0.82 (0.72–0.94) | 0.004 | 2321 (66.4) | 1.48 (1.30–1.69) | < 0.001 |
| Having a chronic disease | |||||||||||||||
| No | 4027 (80.1) | Ref | Ref | 3326 (79.4) | Ref | Ref | 3278 (79.1) | Ref | Ref | 2966 (80.5) | Ref | Ref | 2842 (81.3) | Ref | Ref |
| Yes | 1001 (19.9) | 1.21 (1.04–1.40) | 0.014 | 864 (20.6) | 1.25 (1.09–1.43) | 0.002 | 864 (20.9) | 1.13 (0.99–1.30) | 0.08 | 718 (19.5) | 0.95 (0.83–1.09) | 0.46 | 654 (18.7) | 0.95 (0.83–1.08) | 0.43 |
| Knowing someone with cancer | |||||||||||||||
| No | 2005 (39.9) | Ref | Ref | 1651 (39.4) | Ref | Ref | 1669 (40.3) | Ref | Ref | 1469 (39.9) | Ref | Ref | 1367 (39.1) | Ref | Ref |
| Yes | 3023 (60.1) | 1.34 (1.21–1.50) | < 0.001 | 2539 (60.6) | 1.25 (1.13–1.39) | < 0.001 | 2473 (59.7) | 1.15 (1.04–1.27) | 0.005 | 2215(60.1) | 1.19 (1.07–1.31) | 0.001 | 2129 (60.9) | 1.29 (1.17–1.42) | < 0.001 |
| Marital status | |||||||||||||||
| Single | 1147 (22.8) | Ref | Ref | 943 (22.5) | Ref | Ref | 857 (20.7) | Ref | Ref | 625 (17.0) | Ref | Ref | 911 (23.8) | Ref | Ref |
| Married | 3645 (72.5) | 1.19 (1.01–1.40) | 0.033 | 3058 (73.0) | 1.26 (1.09–1.47) | 0.002 | 3071 (74.1) | 1.38 (1.19–1.61) | < 0.001 | 2869 (77.9) | 2.42 (2.08–2.82) | < 0.001 | 2404 (68.8) | 0.86 (0.75–1.00) | 0.051 |
| Divorced | 111 (2.2) | 1.33 (0.90–1.95) | 0.15 | 85 (2.0) | 1.07 (0.75–1.51) | 0.71 | 96 (2.3) | 1.49 (1.05–2.11) | 0.027 | 90 (2.4) | 2.52 (1.78–3.57) | < 0.001 | 93 (2.7) | 1.43 (1.00–2.02) | 0.047 |
| Widowed | 125 (2.5) | 1.10 (0.77–1.58) | 0.60 | 104 (2.5) | 1.08 (0.77–1.52) | 0.64 | 118 (2.8) | 1.51 (1.07–2.12) | 0.019 | 100 (2.7) | 2.48 (1.78–3.48) | < 0.001 | 88 (2.5) | 0.90 (0.65–1.26) | 0.56 |
| Site of data collection | |||||||||||||||
| Public spaces | 1940 (38.6) | Ref | Ref | 1613 (38.5) | Ref | Ref | 1564 (37.8) | Ref | Ref | 1352 (36.7) | Ref | Ref | 1432 (41.0) | Ref | Ref |
| Hospitals | 1296 (25.8) | 0.88 (0.77–1.01) | 0.07 | 1043 (24.9) | 0.84 (0.74–0.96) | 0.009 | 1067 (25.8) | 0.89 (0.78–1.01) | 0.08 | 983 (26.7) | 1.00 (0.88–1.14) | 0.99 | 833 (23.8) | 0.78 (0.69–0.88) | < 0.001 |
| Primary healthcare centers | 1792 (35.6) | 0.96 (0.84–1.10) | 0.57 | 1534 (36.6) | 1.04 (0.92–1.18) | 0.52 | 1511 (36.5) | 1.03 (0.91–1.16) | 0.63 | 1349 (36.6) | 1.03 (0.92–1.17) | 0.59 | 1231 (35.2) | 1.01 (0.90–1.14) | 0.87 |
AOR adjusted odds ratio, CI confidence interval, WBJ West Bank and Jerusalem
aAdjusted for age-group, educational level, occupation, monthly income, marital status, residency, having a chronic disease, knowing someone with cancer, and site of data collection
Recognizing CC warning signs with pain
Participants aged ≥41 years had a lower likelihood than younger participants (18–20 years) to recognize ‘persistent pelvic pain’ (OR = 0.77, 95% CI: 0.61–0.97) (Table 4). On the other hand, women with high education were more likely than illiterate women to identify ‘persistent pelvic pain’. Additionally, women who were married, divorced, or widowed were more likely than single women to identify ‘unusual discomfort or pain during sex’. Participants who knew someone with cancer had a higher likelihood than participants who did not to recognize all warning signs with pain.
Table 4.
Association between recognizing cervical cancer warning signs with pain and sociodemographic factors
| Characteristic | Persistent pelvic pain | Unusual discomfort or pain during sex | Persistent lower back pain | ||||||
|---|---|---|---|---|---|---|---|---|---|
| n (%) | AOR (95% CI)a | p-value | n (%) | AOR (95% CI)a | p-value | n (%) | AOR (95% CI)a | p-value | |
| Age group | |||||||||
| 18 to 20 | 473 (11.3) | Ref | Ref | 288 (8.7) | Ref | Ref | 300 (10.2) | Ref | Ref |
| 21 to 40 | 2627 (62.7) | 0.85 (0.70–1.04) | 0.12 | 2084 (63.0) | 0.94 (0.77–1.15) | 0.53 | 1818 (61.8) | 1.01 (0.83–1.24) | 0.91 |
| 41 or older | 1088 (26.0) | 0.77 (0.61–0.97) | 0.025 | 936 (28.3) | 0.95 (0.75–1.19) | 0.64 | 823 (28.0) | 1.09 (0.87–1.37) | 0.47 |
| Educational level | |||||||||
| Illiterate | 56 (1.3) | Ref | Ref | 58 (1.8) | Ref | Ref | 55 (1.9) | Ref | Ref |
| Primary | 200 (4.8) | 1.14 (0.76–1.70) | 0.54 | 168 (5.1) | 0.81 (0.54–1.21) | 0.30 | 165 (5.6) | 0.92 (0.61–1.38) | 0.68 |
| Preparatory | 593 (14.2) | 1.44 (0.99–2.11) | 0.06 | 482 (14.6) | 0.96 (0.66–1.40) | 0.84 | 398 (13.5) | 0.80 (0.55–1.17) | 0.25 |
| Secondary | 1343 (32.1) | 1.62 (1.11–2.35) | 0.011 | 1058 (32.0) | 1.13 (0.78–1.64) | 0.52 | 924 (31.4) | 0.93 (0.64–1.36) | 0.71 |
| Diploma | 452 (10.8) | 1.80 (1.21–2.67) | 0.004 | 337 (10.2) | 1.12 (0.76–1.67) | 0.57 | 308 (10.5) | 0.98 (0.66–1.46) | 0.92 |
| Bachelor | 1445 (34.5) | 2.10 (1.43–3.08) | < 0.001 | 1133 (34.3) | 1.54 (1.05–2.26) | 0.027 | 1022 (34.8) | 1.20 (0.81–1.76) | 0.36 |
| Postgraduate | 99 (2.4) | 3.06 (1.79–5.22) | < 0.001 | 72 (2.2) | 1.64 (0.98–2.73) | 0.06 | 69 (2.3) | 1.44 (0.86–2.40) | 0.16 |
| Occupation | |||||||||
| Housewife | 2702 (64.5) | Ref | Ref | 2249 (68.0) | Ref | Ref | 1932 (65.7) | Ref | Ref |
| Employed | 920 (22.0) | 1.04 (0.90–1.20) | 0.61 | 709 (21.4) | 0.99 (0.85–1.14) | 0.86 | 635 (21.6) | 0.93 (0.80–1.07) | 0.32 |
| Retired | 24 (0.6) | 0.40 (0.24–0.67) | 0.001 | 28 (0.8) | 0.87 (0.52–1.46) | 0.59 | 20 (0.7) | 0.58 (0.34–1.01) | 0.053 |
| Student | 542 (12.9) | 1.10 (0.88–1.36) | 0.41 | 322 (9.7) | 0.90 (0.73–1.12) | 0.36 | 354 (12.0) | 0.94 (0.76–1.17) | 0.58 |
| Monthly income | |||||||||
| < 1450 NIS | 1394 (33.3) | Ref | Ref | 1126 (34.0) | Ref | Ref | 1007 (34.2) | Ref | Ref |
| ≥ 1450 NIS | 2794 (66.7) | 1.04 (0.91–1.20) | 0.57 | 2182 (66.0) | 1.02 (0.89–1.17) | 0.76 | 1934 (65.8) | 1.00 (0.87–1.15) | 0.98 |
| Residency | |||||||||
| Gaza Strip | 1592 (38.0) | Ref | Ref | 1285 (38.8) | Ref | Ref | 1144 (38.9) | Ref | Ref |
| WBJ | 2596 (62.0) | 0.95 (0.83–1.09) | 0.45 | 2023 (61.2) | 0.91 (0.80–1.04) | 0.17 | 1797 (61.1) | 0.91 (0.80–1.04) | 0.18 |
| Having a chronic disease | |||||||||
| No | 3396 (81.1) | Ref | Ref | 2657 (80.3) | Ref | Ref | 2378 (80.9) | Ref | Ref |
| Yes | 792 (18.9) | 1.04 (0.91–1.19) | 0.57 | 651 (19.7) | 0.97 (0.85–1.12) | 0.71 | 563 (19.1) | 0.93 (0.81–1.07) | 0.31 |
| Knowing someone with cancer | |||||||||
| No | 1642 (39.2) | Ref | Ref | 1308 (39.5) | Ref | Ref | 1163 (39.5) | Ref | Ref |
| Yes | 2546 (60.8) | 1.34 (1.21–1.48) | < 0.001 | 2000 (60.5) | 1.22 (1.10–1.34) | < 0.001 | 1778 (60.5) | 1.23 (1.11–1.35) | < 0.001 |
| Marital status | |||||||||
| Single | 983 (23.5) | Ref | Ref | 581 (17.6) | Ref | Ref | 662 (22.5) | Ref | Ref |
| Married | 3009 (71.8) | 1.24 (1.07–1.44) | 0.005 | 2555 (77.2) | 2.12 (1.82–2.46) | < 0.001 | 2122 (72.2) | 1.15 (0.99–1.33) | 0.07 |
| Divorced | 98 (2.3) | 1.41 (0.99–2.01) | 0.06 | 80 (2.4) | 2.15 (1.53–3.04) | < 0.001 | 71 (2.4) | 1.34 (0.95–1.89) | 0.10 |
| Widowed | 98 (2.3) | 1.18 (0.85–1.65) | 0.33 | 92 (2.8) | 2.23 (1.60–3.12) | < 0.001 | 86 (2.9) | 1.39 (0.99–1.95) | 0.053 |
| Site of data collection | |||||||||
| Public spaces | 1630 (38.9) | Ref | Ref | 1240 (37.5) | Ref | Ref | 1174 (39.9) | Ref | Ref |
| Hospitals | 1086 (25.9) | 0.99 (0.87–1.13) | 0.89 | 915 (27.7) | 1.04 (0.91–1.18) | 0.56 | 713 (24.2) | 0.82 (0.72–0.93) | 0.002 |
| Primary healthcare centers | 1472 (35.1) | 1.04 (0.92–1.17) | 0.55 | 1153 (34.9) | 0.92 (0.82–1.04) | 0.20 | 1054 (35.8) | 0.98 (0.87–1.10) | 0.71 |
AOR adjusted odds ratio, CI confidence interval, WBJ West Bank and Jerusalem
aAdjusted for age-group, educational level, occupation, monthly income, marital status, residency, having a chronic disease, knowing someone with cancer, and site of data collection
Recognizing CC warning signs of a non-specific nature
Women aged 21 to 40 years were less likely than younger women to recognize ‘persistent vaginal discharge that smells unpleasant’ (OR = 0.79, 95% CI: 0.64–0.96) (Table 5). On the contrary, women who had benefitted from higher education were more likely than illiterate women to recognize all warning signs of a nonspecific nature except ‘persistent diarrhea’ for which, no differences were found. Similarly, participants who knew someone with cancer had a higher likelihood than participants who did not get to know someone with cancer to identify all warning signs of a nonspecific nature except ‘persistent diarrhea’, where no differences were noticed. Married participants were more likely than single participants to identify ‘unexplained weight loss’ (OR = 1.37, 95% CI: 1.18–1.60) and ‘extreme generalized fatigue’ (OR = 1.41, 95% CI: 1.21–1.64).
Table 5.
Association between recognizing cervical cancer warning signs of a non-specific nature and sociodemographic factors
| Characteristic | Extreme generalized fatigue | Unexplained weight loss | Persistent vaginal discharge that smells un-pleasant | Persistent diarrhea | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n (%) | AOR (95% CI)a |
p-value | n (%) | AOR (95% CI)a |
p-value | n (%) | AOR (95% CI)a |
p-value | n (%) | AOR (95% CI)a |
p-value | |
| Age group | ||||||||||||
| 18 to 20 | 488 (10.6) | Ref | Ref | 499 (9.8) | Ref | Ref | 346 (11.1) | Ref | Ref | 139 (9.0) | Ref | Ref |
| 21 to 40 | 2866 (62.3) | 0.82 (0.67–1.01) | 0.06 | 2815 (61.5) | 0.99 (0.81–1.22) | 0.94 | 1862 (59.6) | 0.79 (0.64–0.96) | 0.017 | 944 (60.9) | 1.17 (0.91–1.49) | 0.23 |
| 41 or older | 1247 (27.1) | 0.79 (0.62–0.99) | 0.049 | 1314 (28.7) | 1.03 (0.82–1.31) | 0.79 | 915 (29.3) | 0.94 (0.75–1.18) | 0.62 | 468 (30.2) | 1.17 (0.89–1.55) | 0.27 |
| Educational level | ||||||||||||
| Illiterate | 62 (1.3) | Ref | Ref | 67 (1.5) | Ref | Ref | 45 (1.4) | Ref | Ref | 37 (2.4) | Ref | Ref |
| Primary | 245 (5.3) | 1.39 (0.92–2.09) | 0.11 | 276 (0.6) | 1.69 (1.11–2.55) | 0.014 | 181 (5.8) | 1.48 (0.97–2.25) | 0.07 | 113 (7.3) | 1.10 (0.70–1.72) | 0.69 |
| Preparatory | 683 (14.8) | 1.64 (1.12–2.40) | 0.011 | 726 (15.9) | 1.76 (1.20–2.59) | 0.004 | 446 (14.3) | 1.39 (0.94–2.06) | 0.10 | 257 (16.6) | 0.91 (0.59–1.39) | 0.66 |
| Secondary | 1509 (32.8) | 1.93 (1.32–2.81) | 0.001 | 1534 (33.5) | 1.88 (1.29–2.74) | 0.001 | 994 (31.8) | 1.58 (1.07–2.32) | 0.020 | 487 (31.4) | 0.77 (0.50–1.17) | 0.21 |
| Diploma | 483 (10.5) | 2.10 (1.41–3.13) | < 0.001 | 461 (10.1) | 1.58 (1.06–2.35) | 0.025 | 312 (10.0) | 1.50 (1.00–2.25) | 0.052 | 161 (10.4) | 0.74 (0.47–1.15) | 0.18 |
| Bachelor | 1523 (33.1) | 2.64 (1.79–3.88) | < 0.001 | 1429 (31.2) | 1.87 (1.27–2.75) | 0.002 | 1076 (34.5) | 2.05 (1.38–3.05) | < 0.001 | 462 (29.8) | 0.70 (0.45–1.07) | 0.10 |
| Postgraduate | 96 (2.1) | 3.30 (1.93–5.63) | < 0.001 | 85 (1.9) | 1.78 (1.06–3.00) | 0.031 | 69 (2.2) | 2.25 (1.34–3.78) | 0.002 | 34 (2.2) | 0.84 (0.47–1.50) | 0.56 |
| Occupation | ||||||||||||
| Housewife | 3131 (68.1) | Ref | Ref | 3139 (68.6) | Ref | Ref | 2049 (65.6) | Ref | Ref | 1045 (67.4) | Ref | Ref |
| Employed | 896 (19.5) | 0.70 (0.60–0.81) | < 0.001 | 909 (19.9) | 0.88 (0.76–1.02) | 0.08 | 665 (21.3) | 0.89 (0.77–1.03) | 0.12 | 329 (21.2) | 1.00 (0.84–1.19) | 0.98 |
| Retired | 31 (0.7) | 0.43 (0.26–0.71) | 0.001 | 33 (0.7) | 0.55 (0.33–0.92) | 0.023 | 28 (0.9) | 0.74 (0.45–1.24) | 0.26 | 11 (0.7) | 0.79 (0.40–1.56) | 0.51 |
| Student | 543 (11.8) | 0.87 (0.70–1.08) | 0.21 | 497 (10.9) | 0.87 (0.70–1.08) | 0.20 | 381 (12.2) | 0.88 (0.71–1.08) | 0.23 | 166 (10.7) | 0.90 (0.69–1.17) | 0.43 |
| Monthly income | ||||||||||||
| < 1450 NIS | 1573 (34.2) | Ref | Ref | 1579 (34.5) | Ref | Ref | 1015 (32.5) | Ref | Ref | 554 (35.7) | Ref | Ref |
| ≥ 1450 NIS | 3028 (65.8) | 1.07 (0.93–1.24) | 0.33 | 2999 (65.5) | 1.03 (0.89–1.18) | 0.74 | 2108 (67.5) | 1.03 (0.90–1.18) | 0.68 | 997 (64.3) | 0.84 (0.71–0.99) | 0.037 |
| Residency | ||||||||||||
| Gaza Strip | 1773 (38.5) | Ref | Ref | 1759 (34.4) | Ref | Ref | 1137 (36.4) | Ref | Ref | 580 (37.4) | Ref | Ref |
| WBJ | 2828 (61.5) | 0.96 (0.84–1.11) | 0.61 | 2819 (61.6) | 0.94 (0.82–1.08) | 0.42 | 1986 (63.6) | 1.06 (0.93–1.21) | 0.36 | 971 (62.6) | 1.07 (0.91–1.25) | 0.42 |
| Having a chronic disease | ||||||||||||
| No | 3692 (80.2) | Ref | Ref | 3640 (79.5) | Ref | Ref | 2484 (79.5) | Ref | Ref | 1228 (79.2) | Ref | Ref |
| Yes | 909 (19.8) | 1.10 (0.96–1.27) | 0.19 | 938 (20.5) | 1.05 (0.91–1.21) | 0.51 | 639 (20.5) | 1.04 (0.91–1.19) | 0.53 | 323 (20.8) | 0.99 (0.84–1.16) | 0.88 |
| Knowing someone with cancer | ||||||||||||
| No | 1830 (39.8) | Ref | Ref | 1749 (38.2) | Ref | Ref | 1228 (39.3) | Ref | Ref | 682 (44.0) | Ref | Ref |
| Yes | 2771 (60.2) | 1.31 (1.18–1.45) | < 0.001 | 2829 (61.8) | 1.51 (1.36–1.67) | < 0.001 | 1895 (60.7) | 1.22 (1.11–1.35) | < 0.001 | 869 (56.0) | 0.92 (0.82–1.04) | 0.19 |
| Marital status | ||||||||||||
| Single | 981 (21.3) | Ref | Ref | 940 (20.5) | Ref | Ref | 709 (22.7) | Ref | Ref | 323 (20.8) | Ref | Ref |
| Married | 3399 (73.9) | 1.41 (1.21–1.64) | < 0.001 | 3410 (74.5) | 1.37 (1.18–1.60) | < 0.001 | 2247 (72.0) | 1.14 (0.98–1.32) | 0.09 | 1140 (73.5) | 1.18 (0.98–1.41) | 0.07 |
| Divorced | 109 (2.4) | 1.91 (1.31–2.79) | 0.001 | 101 (2.2) | 1.41 (0.98–2.02) | 0.06 | 81 (2.6) | 1.59 (1.13–2.24) | 0.008 | 38 (2.5) | 1.19 (0.79–1.77) | 0.41 |
| Widowed | 112 (2.4) | 1.29 (0.92–1.82) | 0.14 | 127 (2.8) | 1.55 (1.08–2.21) | 0.016 | 86 (2.8) | 1.19 (0.86–1.67) | 0.30 | 50 (3.2) | 1.17 (0.79–1.72) | 0.43 |
| Site of data collection | ||||||||||||
| Public spaces | 1665 (36.2) | Ref | Ref | 1670 (36.5) | Ref | Ref | 1219 (39.0) | Ref | Ref | 700 (45.1) | Ref | Ref |
| Hospitals | 1159 (25.2) | 0.98 (0.86–1.11) | 0.78 | 1237 (27.0) | 1.05 (0.92–1.20) | 0.47 | 809 (25.9) | 0.95 (0.84–1.08) | 0.41 | 369 (23.8) | 0.62 (0.53–0.72) | < 0.001 |
| Primary healthcare centers | 1777 (38.6) | 1.52 (1.33–1.72) | < 0.001 | 1671 (36.5) | 1.14 (1.00–1.29) | 0.045 | 1095 (35.1) | 1.00 (0.89–1.13) | 0.97 | 482 (31.1) | 0.62 (0.53–0.71) | < 0.001 |
AOR adjusted odds ratio, CI confidence interval, WBJ West Bank and Jerusalem
aAdjusted for age-group, educational level, occupation, monthly income, marital status, residency, having a chronic disease, knowing someone with cancer, and site of data collection
Good knowledge and its associated factors
Only 1934 participants (27.4%) had good knowledge of CC warning signs (Table 6). Participants from the Gaza Strip were slightly more likely than participants from the WBJ to have a good level of knowledge (29.7% vs 26.0%). The multivariable analysis identified factors associated with an increase in the odds of having good knowledge of CC warning signs, which were having a bachelor or postgraduate degree, being married, divorced, or widowed as well as knowing someone with cancer (Table 7). On the other hand, being employed or retired was associated with a decrease in the odds of having good knowledge.
Table 6.
Knowledge level of cervical cancer warning signs
| Level | Total n (%) |
Gaza Strip n (%) |
WBJ n (%) |
p-value |
|---|---|---|---|---|
| Poor | 1998 (28.3) | 709 (26.7) | 1289 (29.3) | 0.002 |
| Fair | 3126 (44.3) | 1158 (43.6) | 1968 (44.7) | |
| Good | 1934 (27.4) | 788 (29.7) | 1146 (26.0) |
n number of participants, WBJ West Bank and Jerusalem
Table 7.
Association between having a good knowledge level of cervical cancer warning signs and sociodemographic factors
| Characteristic | Good knowledge | ||||
|---|---|---|---|---|---|
| n (%) | COR (95% CI) | p-value | AOR (95% CI)a | p-value | |
| Age group | |||||
| 18 to 20 | 161 (8.3) | Ref | Ref | Ref | Ref |
| 21 to 40 | 1202 (62.2) | 1.42 (1.18–1.71) | < 0.001 | 1.04 (0.82–1.31) | 0.74 |
| 41 or older | 571 (29.5) | 1.51 (1.23–1.84) | < 0.001 | 1.19 (0.92–1.55) | 0.19 |
| Educational level | |||||
| Illiterate | 30 (1.6) | Ref | Ref | Ref | Ref |
| Primary | 115 (5.9) | 1.26 (0.80–2.01) | 0.32 | 1.18 (0.74–1.89) | 0.49 |
| Preparatory | 280 (14.5) | 1.15 (0.75–1.78) | 0.51 | 1.08 (0.69–1.68) | 0.74 |
| Secondary | 636 (32.9) | 1.24 (0.82–1.89) | 0.31 | 1.29 (0.84–1.99) | 0.25 |
| Diploma | 187 (9.7) | 1.04 (0.67–1.62) | 0.85 | 1.22 (0.77–1.94) | 0.39 |
| Bachelor | 642 (33.2) | 1.28 (0.84–1.95) | 0.25 | 1.60 (1.03–2.50) | 0.038 |
| Postgraduate | 44 (2.3) | 1.51 (0.88–2.61) | 0.14 | 1.95 (1.09–3.46) | 0.023 |
| Occupation | |||||
| Housewife | 1360 (70.3) | Ref | Ref | Ref | Ref |
| Employed | 380 (19.6) | 0.84 (0.73–0.96) | 0.009 | 0.84 (0.72–0.99) | 0.040 |
| Retired | 9 (0.5) | 0.36 (0.18–0.73) | 0.005 | 0.42 (0.20–0.88) | 0.020 |
| Student | 185 (9.6) | 0.66 (0.55–0.78) | < 0.001 | 0.91 (0.71–1.17) | 0.47 |
| Monthly income | |||||
| < 1450 NIS | 691 (35.7) | Ref | Ref | Ref | Ref |
| ≥ 1450 NIS | 1243 (64.3) | 0.89 (0.80–0.99) | 0.045 | 1.01 (0.87–1.18) | 0.87 |
| Marital status | |||||
| Single | 328 (17.0) | Ref | Ref | Ref | Ref |
| Married | 1501 (77.6) | 1.71 (1.49–1.96) | < 0.001 | 1.65 (1.38–1.97) | < 0.001 |
| Divorced | 49 (2.5) | 1.89 (1.32–2.71) | 0.001 | 1.95 (1.34–2.83) | 0.001 |
| Widowed | 56 (2.9) | 1.71 (1.22–2.38) | 0.002 | 1.85 (1.27–2.68) | 0.001 |
| Residency | |||||
| Gaza Strip | 788 (40.7) | Ref | Ref | Ref | Ref |
| WBJ | 1146 (59.3) | 0.83 (0.75–0.93) | 0.001 | 0.88 (0.76–1.02) | 0.09 |
| Having a chronic disease | |||||
| No | 1557 (80.5) | Ref | Ref | Ref | Ref |
| Yes | 377 (19.5) | 0.97 (0.85–1.11) | 0.70 | 0.91 (0.78–1.05) | 0.20 |
| Knowing someone with cancer | |||||
| No | 723 (37.4) | Ref | Ref | Ref | Ref |
| Yes | 1211 (62.6) | 1.29 (1.16–1.44) | < 0.001 | 1.29 (1.15–1.44) | < 0.001 |
| Site of data collection | |||||
| Public Spaces | 700 (36.2) | Ref | Ref | Ref | Ref |
| Hospitals | 477 (24.7) | 0.96 (0.84–1.10) | 0.57 | 0.89 (0.77–1.03) | 0.11 |
| Primary healthcare centers | 757 (39.1) | 1.26 (1.11–1.42) | < 0.001 | 1.12 (0.99–1.28) | 0.08 |
COR crude odds ratio, AOR adjusted odds ratio, CI confidence interval
aAdjusted for age-group, educational level, occupation, monthly income, marital status, residency, having a chronic disease, knowing someone with cancer, and site of data collection
Note The binary outcome of good knowledge was treated as a yes/no variable
Discussion
The overall awareness of CC warning signs in this study was low. Participants from the Gaza Strip were slightly more likely than participants from the WBJ to have a good knowledge level. The factors associated with having good knowledge were having a bachelor or postgraduate degree, being married, divorced, or widowed as well as knowing someone with cancer. The most frequently identified warning sign was ‘vaginal bleeding after menopause’ followed by non-specific warning signs, namely ‘generalized fatigue’ and ‘unexplained weight loss’.
Awareness of CC warning signs is crucial for timely recognition and early seeking to medical advice in order to decrease CC-related mortality [5, 30, 31]. This study assessed the Palestinian women’s awareness level of CC warning signs to support the development of awareness-raising educational campaigns. This is especially essential in low-resource settings, where no prevention approaches and screening programs exist as in Palestine [13].
Knowledge level of CC warning signs
Early CC detection, which is influenced by the level of awareness, remains one of the cornerstones of CC control strategies to improve survival rates in low- and middle-income countries [31–34]. In the absence of screening as well as HPV-vaccination programs, early detection and treatment of CC could be the most effective strategy to reduce resulting mortality and morbidity. Furthermore, multiple barriers to early presentation with cancer warning signs exist among Palestinian women, including financial restrictions, scarcity of female specialists, negative cancer beliefs, and paucity of treatment opportunities [12, 35–40]. Among these barriers, lack of knowledge and awareness is only one factor, but this one can be addressed by effective educational interventions [11, 41]. Low levels of knowledge of CC warning signs were also found by previous studies from the area of the Middle Eastern and North Africa, such as in Tunisia, Kuwait, Jordan, Qatar and Libya [27, 28, 42–44]. This may reflect poor health education about CC warning signs in Arab countries and underline the need for establishing continuous educational programs. A further contributing factor might be that the incidence of CC is relatively low in the Arab world, which leads to less experience and interest to learn more about this specific cancer [45–47].
In concordance with findings of this study, previous studies showed that women with higher levels of education were more likely to recognize CC warning signs [28, 29, 42, 43, 48–50]. This might be related to reading more about health-related topics and having a higher chance of working or meeting with people who similarly had good knowledge of health-related topics. Adlard and colleagues reported that knowing a family member or a friend who experienced cancer was associated with a higher awareness of cancer symptoms and warning signs [49]. This was consistent with the results of this study and with other studies that surveyed women in the United Kingdom [48, 49].
Married women in this study had a higher likelihood than single women to identify more CC warning signs, which was also noticed in previous studies conducted in the United Kingdom and China [48, 50]. Compared with single women, married women may be more concerned to read about topics related to their reproductive health and possibly have more opportunity to come across information when accessing maternity care or sexual and reproductive healthcare.
Comparing knowledge between the Gaza strip and WBJ
Participants from the Gaza Strip were slightly more likely than participants from the WBJ to have a good level of knowledge and a higher likelihood to identify all warning signs with blood. The political situation in Palestine may play a role in this. In the WBJ, the fear of Israeli security forces’ harm and indignity at checkpoints may have created stress and avoidance of accessing healthcare services. This may also have limited women’s interaction with healthcare professionals and visitors to hospitals and clinics that can play a major role in shaping their knowledge level [51, 52].
The closures, barriers, and checkpoints can impact the daily life of Palestinians by adding hours of delay, unpredictability, and inability to seek medical advice and obtain health-related information and instructions. Women living in rural areas in the WBJ were reported to be the most challenged with these difficulties in accessing healthcare services, which negatively impacted their maternal health and chance to benefit from awareness initiatives [53, 54]. The interaction with social networks in the Palestinian community seems to have a key role in building good knowledge. This observation is based on the finding in this study that women who knew someone with cancer were more likely to have a good knowledge level.
Another contributing factor to the difference in knowledge between the Gaza Strip and the WBJ could be the proportion of women living in rural areas. There are more women living in rural areas in the WBJ, which may limit their access to internet and public libraries. This may have resulted in lower chances for the WBJ women to read more about health-related topics.
Recognizing CC warning signs with blood vs other warning signs
In this study, warning signs with bleeding (including ‘irregular bleeding’, ‘unusual time’, and ‘unusual length or quantity’) were the most recognized warning signs of CC. This was also found in other studies conducted in Libya and the United Kingdom [28, 48]. However, ‘persistent vaginal discharge that smells unpleasant’ was less recognized than warning signs with bleeding or other non-specific warning signs. This differs from what was found among British women, where ‘persistent, abnormal or unusual vaginal discharge’ was more reported than ‘unexplained weight loss’ and ‘extreme generalized fatigue’ [48]. A possible reason for this could be that women’s thoughts of warning signs alarming them of the possibility of CC are influenced by the culture of the country where they were raised. In Palestine, it is common among women to believe that vaginal bleeding could be related more often to irregularities of the menstrual cycle. This may drive Palestinian women to read more about the possible causes of warning signs with bleeding; hence, they can have higher recognition of them as CC warning signs. On the other hand, women in high-income countries usually participate in educational health-activities related to sexually transmitted diseases especially during adolescence [55–57], which is not the case in Palestine. This could explain their ability to recognize unusual vaginal discharge more often than Palestinian women who did not acquire such knowledge because of the lack of similar educational programs.
Married women were more likely than single women to identify warning signs with blood and ‘unusual discomfort or pain during sex’. This was also observed in another study conducted in Qatar [43]. A possible explanation for this finding could be that single women in the Palestinian community are not usually sexually active and getting pregnant which may limit their interaction with obstetrics and gynecology clinics. In addition, single women possibly feel shy about reading or talking about CC warning signs they might experience. This is in comparison with married women who already had the opportunity to acquire knowledge from encountering similar problems overtime, hearing their friends’ or relatives’ stories, or through contact with healthcare professionals during their maternal visits.
Future directions
The findings of this study underline the necessity to establish continuous educational programs that should focus on enriching Palestinian women’s knowledge of CC. Awareness campaigns are also needed and should be tailored to be appropriate for the specific cultural needs. Raising awareness of CC may make women feel more confident and encourage them to discuss their warning signs with healthcare professionals as soon as they recognize them. This will facilitate early detection and diagnosis of CC and improve patient prognosis.
Strengths and limitations
The main strengths of this study include the use of a translated version of the validated tool (CeCAM) to assess women’s awareness of CC warning signs and the high response rate. In addition, the large sample size covering most geographical areas of Palestine and the stratified approach allowed direct measurement of knowledge about CC warning signs on different levels in the Palestinian community. This study also has some limitations. The use of stratified convenience sampling limits the generalizability of the findings. However, the large number of participants and the diversity of geographical areas covered in this study may mitigate this limitation. Another limitation could be that the study included participants who did not experience actual CC warning signs and looked at their perceived knowledge. Further research is needed to assess the awareness of women presented with CC warning signs and diagnosed with it afterwards.
Conclusion
The overall knowledge of women included in this study was low with only 27.4% of women demonstrating a good level of knowledge of CC warning signs. Women residing in the Gaza Strip demonstrated a slightly better knowledge than women residing in the WBJ. The most frequently identified warning sign was ‘vaginal bleeding after menopause’ followed by ‘generalized fatigue’ and ‘unexplained weight loss’. The factors associated with having good knowledge of CC warning signs were having a bachelor or postgraduate degree, being married, divorced, or widowed as well as knowing someone with cancer. To increase women’s knowledge about CC warning signs, special health educational programs are needed.
Supplementary Information
Additional file 1. Results of the bivariable analyses for the association between each category of CC warning signs and participant characteristics.
Acknowledgements
The authors would like to thank all participants who took part in the survey.
Abbreviations
- CC
Cervical cancer
- HPV
Human papillomavirus
- WBJ
West Bank and Jerusalem
- PHCs
Primary healthcare centers
- MoH
Ministry of health
- CeCAM
Cervical cancer awareness measure
- CI
Confidence interval
- OR
Odds ratio
Authors’ contributions
ME, IA, HA, and MA contributed to design of the study, data analysis, data interpretation, and drafting of the manuscript. AR, AA, MT, SK, LK, NF, BA, LiK, HK, DE, NA, AN, TA, ZA, SI, GT, MH, HAS, ZAH, HH, MZ, RS, LH, SR, HaA, TR, RZ, and AmA contributed to design of the study, data collection, data entry, and data interpretation. NAE and BB contributed to design of the study, data interpretation, drafting of the manuscript, and supervision of the work. All authors have read and approved the final manuscript. Each author has participated sufficiently in the work to take public responsibility for the content.
Funding
No funding was received for this study.
Availability of data and materials
The dataset used and analyzed during the current study is available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the Helsinki Committee in the Gaza Strip, a committee within the MoH that gives study approvals. Ethical approval was also obtained from the Islamic University of Gaza Ethics Committee and the Human Resources Development department at the Palestinian MoH on 24th of June, 2019. All the methods of the study were carried out in accordance with relevant guidelines and regulations. Informed consents were obtained from the participants before starting the interview. A detailed explanation of the study was given to all participants with the emphasis that participation was completely voluntary, and their decision would not affect the medical care they receive. Data confidentiality was maintained throughout the study.
Consent for publication
Not applicable.
Competing interests
All authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Mohamedraed Elshami, Ibrahim Al-Slaibi, Hanan Abukmail, and Mohammed Alser contributed equally as a first co-author.
Nasser Abu-El-Noor and Bettina Bottcher contributed equally as a senior co-author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Additional file 1. Results of the bivariable analyses for the association between each category of CC warning signs and participant characteristics.
Data Availability Statement
The dataset used and analyzed during the current study is available from the corresponding author on reasonable request.