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Prevalence and determinants of cervical cancer awareness among women of reproductive age: evidence from Benin and Zimbabwe population-based data

Prevalence and determinants of cervical cancer awareness among women of reproductive age:... Background: Cervical cancer is a prominently diagnosed form of cancer in several resource-constrained settings particularly within the sub-Saharan African region. Globally, Africa region has the highest incidence and mortality rates of cervical cancer. The high prevalence has been attributed to several factors including lack of awareness of the disease. The aim of this paper is to explore the prevalence and factors associated with awareness of cervical cancer among women of reproductive age in Republic of Benin and Zimbabwe, sub-Saharan Africa. Methods: We used population-based cross-sectional data from Benin Demographic and Health Survey (BDHS) and Zimbabwe Demographic and Health Survey (ZDHS) respectively. BDHS 2017–18 and ZDHS - 2015 are the 5th and 6th rounds of the surveys respectively. About 15,928 and 9955 women aged 15–49 years were included in this study respectively. The awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe was measured dichotomously; yes (if a woman heard of cervical cancer) vs. no (if a woman has not heard of cervical cancer). All significant variables from the bivariate analysis were included in the multivariable logistic regression model to calculate the adjusted odds ratios (AOR) with corresponding 95% confidence interval. (Continued on next page) * Correspondence: mic42006@gmail.com Amadou Barrow and Michael Ekholuenetale are authors contributed equally and are joint first authors. Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Barrow et al. Applied Cancer Research (2020) 40:8 Page 2 of 13 (Continued from previous page) Results: While majority (79.2%) of women from Zimbabwe have heard about cervical cancer, only about one-tenth (10.2%) of their Beninese counterparts have heard about the disease. Advanced maternal age, having formal education, use of internet, having professional/technical/managerial occupation significantly increased the odds of awareness of cervical cancer after adjusting for other confounders. However, in Benin, women who resided in the rural area and those of Islamic belief had 20% (AOR = 0.80; 95%CI: 0.64, 0.99) and 35% (AOR = 0.65; 95%CI: 0.50, 0.86) reduction in the odds of awareness of cervical cancer respectively, when compared with women from urban residence and Christianity. Results from the predictive marginal effects showed that, assuming the distribution of all factors remained the same among women, but every woman is an urban dweller, we would expect 11.0 and 81.0% level of awareness of cervical cancer; If everywoman had higher education, we would expect 20.0 and 90% level of awareness of cervical cancer and if instead the distribution of other maternal factors were as observed and other covariates remained the same among women, but all women were in the richest household wealth quintile, we would expect about 11.0 and 83.0% level of awareness of cervical cancer, among women of reproductive age from Benin and Zimbabwe respectively. Conclusion: The study has revealed that socio-demographical factors including geographical location and selected economic factors explained the inequality in distribution of women’s awareness on cervical cancer in both countries. Designing an effective population-based health education and promotion intervention programs on cervical cancer will be a great way forward to improving women’s awareness level on cervical cancer. Keywords: Knowledge, Human papillomavirus, HPV, Maternal health, Health education, Africa Background cervical cancer, Human Papilloma Virus (HPV), screen- Cervical cancer has been reported to be the fourth most ing and treatment of cervical pre-cancer, diagnosis and commonly detected cancer among women globally [1]. It treatment of invasive cervical cancer and provision of ranks secondbehindbreastcancer asthe most incident palliative care to patients with cervical cancer [4]. It is and mortal cancer among women in lower human devel- against this backdrop that all member nations especially opment index (HDI) settings. It is also the most com- poor-resource countries are encouraged to key into this monly diagnosed cancer in 28 countries and the leading guideline to make sure that the burden of cervical cancer cause of cancer death in 42 countries, with majority of is effectively reduced. A strict adherence to this guide- which are sub-Saharan Africa (SSA) and South Eastern line will ensure that the Sustainable Development Goals Asia [1]. Africa has the highest incidence and mortality 3 (especially 3.3, 3.4, 3.7 and 3.8) of the United Nations rates of cervical cancer among other regions of the world; that advocates for good healthy living and promotion of the rates are elevated in the Southern Africa countries wellbeing for all at all ages [5], will be met. with Swaziland having the highest incidence rate; followed Several factors have been identified to be associated by Eastern Africa with Malawi having the highest rate of with cervical cancer; these include poor cervical cancer death followed by Zimbabwe; and Western Africa, with screening, lack of awareness and knowledge of cervical Guinea, Burkina Faso, and Mali taking the lead in that cancer; biological factors such as poor nutrition, infec- order [1]. Nearly 80% of all cervical cancers and 90% of tions with human immunodeficiency virus (HIV), tuber- deaths occur in the poor-resource countries of the world culosis (TB), malaria; socioeconomic and socio-cultural with SSA bearing the highest burden [2]. It was also esti- factors with political inequities, have been implicated in mated that if cervical cancer prevention, screening and the high prevalence of cervical cancer in SSA countries treatment are not immediately and urgently scaled up, [6]. Though cervical cancer is the most common cancer there could be a 50% increase in mortality over 2018 levels among women living with HIV, persistent infection with by 2040 [2]. Unfortunately, the west African region has a HPV has been implicated as the most common cause of total annual new cases of cervical cancer of 31,955 at a the cancer of the cervix. Women living with HIV are up crude incidence and age-standardized rates of 16.8 and to five times more likely to develop invasive cervical can- 29.6 (cases of cancer per 100,000 women per year) [3]. cer than other women. In SSA, cervical cancer is report- In 2014, the World Health Organization (WHO) pub- edly a prominent cancer killer of women [6]. lished an updated guideline from the previous 2006 Cervical cancer is known to be the most frequently di- guideline on the prevention and control of cervical can- agnosed cancer amongst Zimbabwean women and it ac- cer [4]. This was to be achieved through community counts for about a third of all cancers in this mobilization, education and counseling, vaccination of Zimbabwean key population [7]. Report has shown that girls 9–13 years against the major known cause of 3186 new cases of cervical cancer and 2151 deaths occur Barrow et al. Applied Cancer Research (2020) 40:8 Page 3 of 13 as a result of the disease every year in Zimbabwe [8]. available in the public domain and accessed at; http:// This data projects that about 4.5 million Zimbabwean dhsprogram.com/data/available-datasets.cfm. women are at the risk of cervical cancer in their life time [9]. Evidence shows that only about a third of Zimbab- Study design wean women had ever been screened for cervical cancer DHS project is funded by the United States Agency for and affiliation to major religious groups and non-visit to International Development (USAID) with support from health facilities were negative contributory factors to other donors and host countries, has conducted over poor screening uptake [10]. Furthermore, in the republic 230 nationally representative and internationally com- of Benin, just as in many other SSA countries, the issue parable household surveys in more than 80 countries of cervical cancer is still a great public health problem. since its inception in 1984. The first three of the DHS’s Though there are no available data from Cancer Registry six phases were implemented between 1984 and 1997. in Benin for cervical cancer [3], Globocon 2018 and Thereafter the project was folded into a family of USAID International Agency for Research in Cancer (IARC) monitoring and evaluation projects and was renamed 2019 survey data show that cervical cancer ranks the MEASURE DHS. DHS originally collected comparable third most incident and most prevalent cancer among population-based data on fertility, contraception, mater- Beninese after breast cancer and prostate cancer in that nal and child health and nutrition in developing coun- order, with an annual new diagnosed cases of 783 and tries. Today, DHS core questionnaires cover a wider the second most common cancer and cause of cancer range of population and health topics. DHS used a two- death, with annual death of 652 among Beninese women stage stratified cluster sampling method to select enu- [1, 3, 11]. The death rate caused by cervical cancer is meration areas (EAs) and household samples. The first number 3 among all types of cancer. The age- stage involves the selection of EAs with probability pro- standardized rate in terms of incidence among the fe- portional to the size. Secondly, from the total residential male Beninese population is about one-quarters [1, 3, households selected, a number of households were se- 11]. lected per EA. All women of reproductive age (15 to 49 SSA region has the highest incidence rate of cervical years) were selected for the component of the survey in- cancer when compared with other regions of the world, cluding respondents’ characteristics. The survey design, with associated high mortality affecting women at their sampling technique, data collection instruments, data prime [6]. Screening programs are grossly inadequate or quality assurance, ethical approval and subject consent non-available thereby making early detection of precan- for DHS were conducted appropriately in line with inter- cerous lesions inefficient or in many instances practically national standard [12, 13]. The DHS were initially de- impossible, within the countries in the region. Most signed to expand on demographic, fertility and family screening activities are done as pilot or research projects planning data collected in the World Fertility Surveys and which are discontinued on completion [6]. This has Contraceptive Prevalence Surveys, but continue to provide made awareness of cervical cancer, its screening and risk an important resource for the monitoring of vital statistics factors among the women population in most parts of and population health indicators. DHS collects a wide this region very poor, thereby resulting in high inci- range of data with a focus on indicators of fertility, repro- dence, prevalence, and mortality rate [1, 3, 8, 11]. In the ductive health, maternal and child health, mortality, nutri- light of the above, we undertake this paper to explore tion and health behaviours. DHS data is useful in public the prevalence and factors associated with awareness of health research focused on monitoring of prevalence, cervical cancer among women of reproductive age in Re- trends and inequalities. During the survey, multi-stage public of Benin and Zimbabwe, sub-Saharan Africa. stratified cluster sampling approach was used to select the respondents based on allocation of specific numbers of Methods clusters to urban and rural settlements in the country. Dif- Data extractionges ferent questionnaires were designed to obtain information We used population-based cross-sectional data from related to women, men, households, children and couples. Benin Demographic and Health Survey (BDHS) and The reliability and validity of the questionnaires were well Zimbabwe Demographic and Health Survey (ZDHS) re- conducted using standard methods. An overview of the spectively. BDHS 2017–18 and ZDHS - 2015 are the 5th DHS along with an introduction to the potential scope for and 6th rounds of the surveys respectively. About 15,928 these data is reported elsewhere. and 9955 women of reproductive age from Benin and Zimbabwe were included in this study respectively. By Study area implication, the data analyzed in this study included The geographical regions in Benin, include; Alibori, Ata- women aged 15–49 years. BDHS and ZDHS have re- cora, Atlantique, Borgou, Collines, Couffo, Donga, sponse rates of 98.1 and 96.2% respectively. The data is Littoral, Mono, Quémé, Plateau and Zou. The country Barrow et al. Applied Cancer Research (2020) 40:8 Page 4 of 13 spans from north to south and a long stretched country Masvingo, 9 = Harare & 10 = Bulawayo. These factors in West Africa, located west of Nigeria and east of Togo, were included based on previous studies that examined it is bordered to the north by Niger and Burkina Faso, in the factors associated with awareness of cervical cancer south by the Bight of Benin, in the Gulf of Guinea, that [16–18]. Household wealth quintile: principal compo- part of the tropical North Atlantic Ocean which is nents analysis (PCA) was used to assign the wealth indi- roughly south of West Africa. Benin’s coastline is ap- cator weights. This procedure assigned scores and proximately 121 km long, with an area of 112,622 km . standardized the wealth indicator variables such as; bi- Benin’s former name, until 1975, was Dahomey. Benin cycle, motorcycle/scooter, car/truck, main floor material, has a population of 10 million people (in 2013), Porto- main wall material, main roof material, sanitation facil- Novo, a port on an inlet of the Gulf of Guinea is the na- ities, water source, radio, television, electricity, refriger- tion’s capital city, largest city and economic capital is ator, cooking fuel, furniture, number of persons per Cotonou. Spoken languages are French (official), Fon room. The factor coefficient scores (factor loadings) and and Yoruba [14]. Furthermore, Zimbabwe has nine [9] z-scores were calculated. For each household, the indica- geographical regions, namely; Manicaland, Manicaland tor values were multiplied by the loadings and summed Central, Manicaland East, Manicaland West, Manicaland to produce the household’s wealth index value. The North, Manicaland South, Midlands, Masvingo, Harare & standardized z-score was used to disentangle the overall Bulawayo. Zimbabwe is a landlocked country in southern assigned scores to poorest/poorer/middle/richer/richest Africa lying wholly within the tropics. It has a total land categories [19, 20]. area of about 390,000 km and a population of about 15 million. It shares a 125-mile (200-km) border on the south Ethical consideration with the Republic of South Africa and is bounded on the This study was based on an analysis of population-based southwest and west by Botswana, on the north by Zambia, dataset available in public domain/ online with all identi- and on the northeast and east by Mozambique. The cap- fier information removed. The authors communicated ital is Harare (formerly called Salisbury). More than two- with MEASURE DHS/ICF International and permission thirds of Zimbabweans speak Shona as their first language, was granted to download and use the data. The DHS while about one out of six speak Ndebele [15]. project obtained the required ethical approvals from the relevant research ethics committee in Benin and Outcome variable Zimbabwe, before the survey was conducted to ensure The awareness of cervical cancer among women of re- that the protocols are in compliance with the U.S. De- productive age in Benin and Zimbabwe was measured partment of Health and Human Services regulations for dichotomously; yes (if a woman heard of cervical cancer) the protection of human subjects. Written informed vs. no (if a woman has not heard of cervical cancer). consents were obtained from participants before being allowed in the surveys. Explanatory variables Age (years) of respondent: 15–19, 20–24, 25–29, 30–34, Statistical analysis 35–39, 40–44, 45–49; residential status: urban vs. rural; In Stata, the Survey (‘svy’) module was used to adjust for educational attainment: no formal education, primary, stratification, clustering and sampling weights to com- secondary, higher; religious background: Christianity, pute the estimates of awareness on cervical cancer. The Islam, traditional/others; literacy: cannot read at all/able collinearity testing approach adopted the correlation to read only part of sentence, able to read whole sen- analysis to detect interdependence between variables. A tence; read newspaper: not at all, less than once a week, cut-off of 0.7 was used to examine the multicollinearity at least once a week; listen to radio: not at all, less than known to cause major concerns [21]. No variable from once a week, at least once a week; watch TV: not at all, the correlation matrix was removed in the model due to less than once a week, at least once a week; marital sta- lack of multicollinearity. Women’s characteristics were tus: never in union, currently in union/living with a obtained using percentages. Chi-square test was used to man, formerly in union/lived with a man; occupation: examine the association between awareness on cervical not working, professional/technical/managerial, sales, and the explanatory variables. All significant variables agricultural, services, skilled manual; geographical re- from the bivariate analysis were included in the multi- gion: Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = variable logistic regression model to calculate the ad- Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, justed odds ratios (with corresponding 95%CI). In 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou; addition, we obtained the marginal predictive effects of Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = the factors. Based on the estimation of multivariable lo- Manicaland East, 4 = Manicaland West, 5 = Manicaland gistic regression model, we predicted the probability of North, 6 = Manicaland South, 7 = Midlands, 8 = awareness on cervical cancer. Thus; Barrow et al. Applied Cancer Research (2020) 40:8 Page 5 of 13 Determinants of awareness of cervical cancer among PrðÞ Y ¼ 1jSet½ E ¼ e¼ p PrðÞ Z ¼ z ; ez women aged 15–49 years in Benin and Zimbabwe In Table 2, several factors were statistically significant with Where Set [E = e] reflects putting all observations to a awareness of cervical cancer using multivariable logistic single exposure level e, and Z = z refers to a given set of regression model. In both countries, advanced maternal observed values for the covariate vector Z. Furthermore, age, having formal education, use of internet, having pro- p is the predicted probabilities of awareness on cervical fessional/technical/managerial occupation significantly in- ez cancer for any E = e and Z = z. The marginal effects indi- creased the odds of awareness on cervical cancer after cate a weighted average over the distribution of the co- adjusting for other confounders. However, in Benin, variates and are equal to estimates got by standardizing women who resided in the rural area and those who had to the entire population. As a post logistic regression test, Islamic belief had 20% (OR = 0.80; 95%CI: 0.64, 0.99) and the exposure E is set to the level e forall womeninthe data- 35% (OR = 0.65; 95%CI: 0.50, 0.86) reduction in the odds set, and the logistic regression coefficients are used to com- of awareness on cervical cancer respectively, when com- pute predicted probabilities for every woman at their pared with women from urban residence and Christianity observed covariate pattern and newly exposure value. Be- after adjusting for other covariates. Women who watch cause predicted probabilities are computed under the same television had higher odds of awareness on cervical cancer, distribution of Z, there is no covariate of the corresponding compared with women who do not watch television at all effect measure estimates [22]. Statistical significance was de- after adjusting for other covariates. In Zimbabwe, women termined at p < 0.05. Data analysis was conducted using Stata who are able to read at least part of a sentence, read news- Version 14 (StataCorp., College Station, TX, USA). paper/magazine, listen to radio, had increase in the odds of awareness on cervical cancer, when compared with Results women who cannot read at all, do not read newspaper/ The results from Fig. 1 showed that while majority (79.2%) magazine, do not listen to radio after adjusting for other of women from Zimbabwe reportedly have heard about cer- confounders. Furthermore, increased household wealth vical, only about one-tenth (10.2%) of women from Benin quintile level and ever being married increased the odds of have heard about cervical cancer. See Fig. 1 for the details. awareness on cervical cancer among women, when com- The results from Table 1 showed that the proportion of pared with women from poorest household and those women who have ever heard about cervical cancer some- who were never in union after adjusting for other covari- what increased by increases in age in both countries. ates. See Table 2 for the details. Clearly, women from urban residence, higher educational attainment, able to read whole sentence, read newspaper/ Predictive marginal effects of the factors associated with magazine, listen to radio, watch television, use internet, awareness of cervical cancer among women aged 15–49 non-poor and have professional/technical/managerial occu- years in Benin and Zimbabwe pation reportedly have higher proportion of ever heard of In Table 3, marginal effect analysis was used to decipher cervical cancer in Benin and Zimbabwe respectively. In the effects of the factors associated with awareness of addition, all explanatory variables were statistically signifi- cervical cancer among women of reproductive age in cant with awareness of cervical cancer using Chi-square Benin and Zimbabwe. Overall, advanced maternal age, test. See Table 1 for the details. urban residence, higher education, Christianity faith, Fig. 1 Awareness and screening of cervical cancer among women of age in Benin and Zimbabwe Barrow et al. Applied Cancer Research (2020) 40:8 Page 6 of 13 Table 1 Awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa Variable Benin Zimbabwe n (%) Heard about cervical p n (%) Heard about cervical p cancer cancer No (%) Yes (%) No (%) Yes (%) Age (years) of respondent < 0.001* < 0.001* 15–19 3335 (20.9) 93.7 6.3 2156 (21.7) 43.2 56.8 20–24 2916 (18.3) 88.8 11.2 1782 (17.9) 22.7 77.3 25–29 2971 (18.7) 88.0 12.0 1656 (16.6) 15.0 85.0 30–34 2195 (13.8) 89.6 10.4 1591 (16.0) 11.1 88.9 35–39 1905 (12.0) 89.5 10.5 1209 (12.1) 10.7 89.3 40–44 1333 (8.4) 87.9 12.1 966 (9.7) 10.7 89.3 45–49 1273 (8.0) 89.4 10.6 595 (6.0) 12.3 87.7 Residential status < 0.001* < 0.001* Urban 7045 (44.2) 84.9 15.1 4521 (45.4) 12.4 87.6 Rural 8883 (55.8) 93.8 6.2 5434 (54.6) 27.7 72.3 Education level < 0.001* < 0.001* None 8762 (55.0) 95.0 5.0 106 (1.1) 40.6 59.4 Primary 3116 (19.6) 91.0 9.0 2385 (24.0) 33.3 66.7 Secondary 3685 (23.1) 81.0 19.0 6637 (66.7) 18.3 81.7 Higher 365 (2.3) 48.1 51.9 827 (8.3) 2.1 97.9 Religious belief < 0.001* 0.002* Christianity 8784 (55.1) 86.1 13.9 9385 (94.3) 20.4 79.6 Islam 4677 (29.4) 94.9 5.1 30 (0.3) 20.0 80.0 Traditional/others 2467 (15.5) 93.3 6.7 540 (5.4) 26.9 73.1 Literacy < 0.001* < 0.001* Cannot read at all 10,359 (65.4) 94.3 5.7 495 (5.0) 44.2 55.8 Able to read only part of sentence 1133 (7.1) 91.6 8.4 734 (7.4) 28.2 71.8 Able to read whole sentence 4357 (27.5) 78.6 21.4 8698 (87.6) 18.7 81.3 Frequency of reading newspaper/magazine < 0.001* < 0.001* Not at all 14,419 (90.5) 91.4 8.6 5446 (54.7) 28.1 71.9 Less than once a week 878 (5.5) 73.9 26.1 2778 (27.9) 13.4 86.6 At least once a week 631 (4.0) 76.7 23.3 1731 (17.4) 9.5 90.5 Frequency of listening to radio < 0.001* < 0.001* Not at all 6840 (42.9) 94.1 5.9 4482 (45.0) 26.8 73.2 Less than once a week 3408 (21.4) 89.7 10.3 2112 (21.2) 19.0 81.0 At least once a week 5680 (35.7) 84.8 15.2 3361 (33.8) 13.7 86.3 Frequency of watching television < 0.001* < 0.001* Not at all 9775 (61.4) 94.5 5.5 5054 (50.8) 27.1 72.9 Less than once a week 2741 (17.2) 87.6 12.4 1381 (13.9) 17.3 82.7 At least once a week 3412 (21.4) 78.0 22.0 3520 (35.4) 12.9 87.1 Frequency of using internet < 0.001* < 0.001* Not at all 14,845 (93.2) 92.2 7.8 7325 (73.6) 25.4 74.6 Less than once a week 141 (0.9) 70.8 29.2 214 (2.1) 12.1 87.9 At least once a week 281 (1.8) 68.6 31.4 413 (4.1) 10.2 89.8 Almost every day 661 (4.1) 50.5 49.5 2003 (20.1) 7.0 93.0 Wealth quintile < 0.001* < 0.001* Barrow et al. Applied Cancer Research (2020) 40:8 Page 7 of 13 Table 1 Awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa (Continued) Variable Benin Zimbabwe n (%) Heard about cervical p n (%) Heard about cervical p cancer cancer No (%) Yes (%) No (%) Yes (%) Poorest 2856 (17.9) 96.3 3.7 1499 (15.1) 36.4 63.6 Poorer 2976 (18.7) 95.4 4.6 1452 (14.6) 28.6 71.4 Middle 2985 (18.7) 92.7 7.3 1549 (15.6) 24.7 75.3 Richer 3281 (20.6) 90.5 9.5 2558 (25.7) 15.4 84.6 Richest 3830 (24.0) 77.3 22.7 2897 (29.1) 11.3 88.7 Marital status < 0.001* < 0.001* Never in union 3897 (24.5) 88.5 11.5 2666 (26.8) 35.3 64.7 Currently in union/living with a man 11,170 (70.1) 90.7 9.3 6015 (60.4) 15.5 84.5 Formerly in union/lived with a man 861 (5.4) 84.3 15.7 1274 (12.8) 15.1 84.9 Occupation < 0.001* < 0.001* Not working 3527 (23.0) 91.7 8.3 4897 (54.3) 27.8 72.2 Professional/technical/managerial 543 (3.5) 60.8 39.2 615 (6.8) 2.4 97.6 Sales 4537 (29.6) 87.7 12.3 1794 (19.9) 12.5 87.5 Agricultural 3065 (20.0) 97.0 3.0 742 (8.2) 18.3 81.7 Services 1842 (12.0) 86.5 13.5 728 (8.1) 11.7 88.3 Skilled manual 1825 (11.9) 93.8 6.2 249 (2.8) 14.9 85.1 Geographical region < 0.001* < 0.001* 1 1697 (10.7) 96.4 3.6 1019 (10.2) 23.2 76.8 2 1392 (8.7) 91.6 8.4 993 (10.0) 18.2 81.2 3 1702 (10.7) 85.4 14.6 910 (9.1) 17.1 82.9 4 1765 (11.1) 98.6 1.4 1054 (10.6) 16.3 83.7 5 1403 (8.8) 87.3 12.7 849 (8.5) 32.4 67.6 6 1012 (6.4) 89.9 10.1 829 (8.3) 34.3 65.7 7 964 (6.1) 94.5 5.5 1062 (10.7) 24.3 75.7 8 1415 (8.9) 70.3 29.7 1046 (10.5) 24.2 75.8 9 816 (5.1) 87.9 12.1 1235 (12.4) 9.1 90.9 10 1260 (7.9) 92.0 8.0 958 (9.6) 14.5 85.5 11 952 (6.0) 95.5 4.5 12 1550 (9.7) 88.0 12.0 Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou. Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = Manicaland East, 4 = Manicaland West, 5 = Manicaland North, 6 = Manicaland South, 7 = Midlands, 8 = Masvingo, 9 = Harare & 10 = Bulawayo. *Significant at p < 0.005 ability to read whole sentence and/or newspaper or cervical cancer among women of reproductive age from magazine, listening to radio at least once a week, watch- Benin and Zimbabwe respectively. If everywoman had ing television at least once a week, using internet almost higher education, we would expect 20.0 and 90% level of every day, richest households and professional/technical/ awareness of cervical cancer among women of repro- managerial occupation have higher marginal effects of ductive age from Benin and Zimbabwe respectively. If awareness of cervical cancer among women of repro- instead the distribution of other maternal factors were as ductive age from Benin and Zimbabwe respectively. observed and other covariates remained the same among Clearly, from the predictive marginal effects results, as- women, but all women were in the richest household suming the distribution of all factors remained the same wealth quintile, we would expect about 11.0 and 83.0% among women, but every woman is an urban dweller, level of awareness of cervical cancer among women of we would expect 11.0 and 81.0% level of awareness of reproductive age from Benin and Zimbabwe respectively. Barrow et al. Applied Cancer Research (2020) 40:8 Page 8 of 13 Table 2 Factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub- Saharan Africa Variable Benin Zimbabwe Adjusted odds ratio (95%CI) P Adjusted odds ratio (95%CI) P Age (years) of respondent (ref: 15–19) 20–24 1.99 (1.42–2.78) < 0.001* 1.77 (1.46–2.14) < 0.001* 25–29 2.51 (1.72–3.67) < 0.001* 2.80 (2.24–3.51) < 0.001* 30–34 2.48 (1.62–3.80) < 0.001* 3.89 (3.06–4.93) < 0.001* 35–39 2.74 (1.78–4.25) < 0.001* 4.49 (3.44–5.85) < 0.001* 40–44 3.91 (2.47–6.17) < 0.001* 4.58 (3.45–6.09) < 0.001* 45–49 3.11 (1.96–4.95) < 0.001* 5.01 (3.61–6.96) < 0.001* Residential status (ref: Urban) Rural 0.80 (0.64–0.99) 0.043* 0.80 (0.62–1.03) 0.084 Education level (ref: None) Primary 1.34 (1.01–1.81) 0.049* 1.50 (0.93–2.40) 0.097 Secondary 2.53 (1.70–3.78) < 0.001* 2.91 (1.78–4.76) < 0.001* Higher 4.19 (2.36–7.44) < 0.001* 6.34 (2.98–13.46) < 0.001* Religious belief (ref: Christianity) Islam 0.65 (0.50–0.86) 0.002* 0.50 (0.19–1.33) 0.165 Traditional/others 0.85 (0.64–1.13) 0.258 0.94 (0.74–1.19) 0.606 Literacy (ref: Cannot read at all) Able to read only part of sentence 0.88 (0.59–1.31) 0.526 1.93 (1.43–2.59) < 0.001* Able to read whole sentence 1.12 (0.78–1.59) 0.545 1.63 (1.27–2.08) < 0.001* Frequency of reading newspaper/magazine (ref: Not at all) Less than once a week 0.99 (0.73–1.35) 0.968 1.68 (1.43–1.96) < 0.001* At least once a week 0.70 (0.48–1.03) 0.068 1.59 (1.28–1.98) < 0.001* Frequency of listening to radio (ref: Not at all) Less than once a week 1.07 (0.83–1.38) 0.608 1.07 (0.92–1.26) 0.365 At least once a week 1.21 (0.96–1.52) 0.100 1.59 (1.37–1.84) < 0.001* Frequency of watching television (ref: Not at all) Less than once a week 1.50 (1.16–1.93) 0.002* 1.14 (0.94–1.38) 0.194 At least once a week 1.44 (1.10–1.89) 0.008* 1.05 (0.87–1.27) 0.586 Frequency of using internet (ref: Not at all) Less than once a week 2.40 (1.25–4.59) 0.008* 1.68 (1.02–2.76) 0.042* At least once a week 1.83 (1.17–2.84) 0.008* 1.52 (1.06–2.20) 0.023* Almost every day 2.77 (1.96–3.93) < 0.001* 1.90 (1.50–2.39) < 0.001* Wealth quintile (ref: Poorest) Poorer 0.88 (0.60–1.30) 0.529 1.20 (1.01–1.43) 0.050* Middle 1.09 (0.75–1.58) 0.660 1.30 (1.08–1.57) 0.007* Richer 1.06 (0.72–1.53) 0.766 1.45 (1.13–1.88) 0.004* Richest 1.21 (0.81–1.82) 0.356 1.68 (1.20–2.34) 0.002* Marital status (ref: Never in union) Currently in union/living with a man 0.86 (0.65–1.15) 0.321 1.95 (1.63–2.33) < 0.001* Formerly in union/lived with a man 1.05 (0.68–1.60) 0.832 1.83 (1.42–2.36) < 0.001* Occupation (ref: Not working) Professional/technical/managerial 1.74 (1.20–2.54) 0.004* 2.24 (1.27–3.95) 0.005* Barrow et al. Applied Cancer Research (2020) 40:8 Page 9 of 13 Table 2 Factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub- Saharan Africa (Continued) Variable Benin Zimbabwe Adjusted odds ratio (95%CI) P Adjusted odds ratio (95%CI) P Sales 1.45 (1.11–1.91) 0.007* 1.17 (0.98–1.39) 0.080 Agricultural 0.63 (0.41–0.95) 0.028* 1.08 (0.86–1.35) 0.521 Services 1.84 (1.35–2.50) < 0.001* 1.27 (0.98–1.65) 0.074 Skilled manual 0.91 (0.63–1.31) 0.628 0.89 (0.60–1.33) 0.583 Geographical region (ref: 1) 2 2.09 (1.24–3.51) 0.005* 1.62 (1.26–2.08) < 0.001* 3 1.47 (0.90–2.40) 0.127 1.39 (1.07–1.81) 0.014* 4 0.22 (0.10–0.46) < 0.001* 1.52 (1.17–1.95) 0.001* 5 2.54 (1.55–4.17) < 0.001* 0.74 (0.58–0.94) 0.016* 6 2.08 (1.22–3.57) 0.007* 0.60 (0.47–0.78) < 0.001* 7 1.22 (0.68–2.19) 0.507 0.93 (0.73–1.18) 0.533 8 1.93 (1.18–3.19) 0.009* 0.93 (0.74–1.18) 0.576 9 1.53 (0.88–2.67) 0.131 1.66 (1.23–2.23) 0.001* 10 0.78 (0.46–1.33) 0.373 0.89 (0.66–1.21) 0.465 11 0.66 (0.35–1.24) 0.202 12 1.67 (1.01–2.77) 0.048* Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou. Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = Manicaland East, 4 = Manicaland West, 5 = Manicaland North, 6 = Manicaland South, 7 = Midlands, 8 = Masvingo, 9 = Harare & 10 = Bulawayo. *Significant at p < 0.05 In Table 3, we practically obtained the predictive mar- of cervical cancer [25], among Ethiopian women of ginal effects of the factors associated with level of aware- childbearing age, there was low level of awareness [26]; ness of cervical cancer among women of reproductive while similar studies in India reported that one in twelve age from Benin and Zimbabwe respectively. See Table 3 women and one-third of women had heard and were for the details. aware of cervical cancer [27, 28]. In this study, the use of print and electronic media Discussion were major factors that enhanced awareness of cervical This study revealed low awareness of cervical cancer cancer among women. Similar to the findings from pre- specifically in Benin as opposed to Zimbabwe. It is pos- vious studies, different media platforms such as radio, sible that low literacy levels, poor use of the media, in- print media, internet, TV and organized educational pro- cluding; listening to radio, watching TV and internet use grams positioned women to be advantageous in accessi- may have been linked to these findings. This is in line bility to health information [29]; as also found in both with a systematic review in SSA which stated low aware- Benin and Zimbabwe. It was also found that rural com- ness of cervical cancer among women [23]. This study munities are an underserved portion of the population demonstrated that in Zimbabwe, although 79.2% of with limited access to health information [30–32]. women had heard of cervical cancer, only 17% had been Awareness of cervical cancer by residential status re- screened. Obviously the scenario is still worse in Benin; markably varied especially as in the case of Benin Re- hence this study becomes crucial to contribute to the public. This could be due to the fact that women in knowledge base. Generally, the low level of awareness of rural settings have low knowledge and access to cervical cervical cancer has been recognized as one of the factors cancer information and services. Health information dis- leading to the high prevalence of cervical cancer in semination is a major growth area for the media, prob- resource-constrained settings compared to the devel- ably because it is in demand by the populace and it is oped world [24]. Women’s knowledge of core health is- profitable. Nonetheless, media coverage of medical news sues including prevention and control of cervical cancer is generally and may be of diverse quality, especially has been poor in resource-constrained settings. For ex- messages about screening channels and new treatments ample, in a study carried out in two urban slums in [33]. The media can have a substantial positive public Lagos, Nigeria, about one in twenty women were aware health role in communicating simple warnings about the Barrow et al. Applied Cancer Research (2020) 40:8 Page 10 of 13 Table 3 Marginal predictive models of the factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa Variable Benin Zimbabwe Marginal effects (95%CI) P Marginal effects OR (95%CI) P Age (years) of respondent 15–19 0.05 (0.04–0.07) < 0.001* 0.67 (0.64–0.69) < 0.001* 20–24 0.09 (0.08–0.11) < 0.001* 076 (0.74–0.78) < 0.001* 25–29 0.11 (0.10–0.13) < 0.001* 0.83 (0.81–0.85) < 0.001* 30–34 0.11 (0.09–0.13) < 0.001* 0.86 (0.84–0.88) < 0.001* 35–39 0.12 (0.10–0.14) < 0.001* 0.88 (0.86–0.90) < 0.001* 40–44 0.15 (0.12–0.18) < 0.001* 0.88 (0.86–0.90) < 0.001* 45–49 0.13 (0.10–0.16) < 0.001* 0.89 (0.86–0.91) < 0.001* Residential status Urban 0.11 (0.09–0.12) < 0.001* 0.81 (0.79–0.84) < 0.001* Rural 0.09 (0.08–0.10) < 0.001* 079 (0.77–0.80) < 0.001* Education level None 0.07 (0.06–0.08) < 0.001* 0.66 (0.58–0.74) < 0.001* Primary 0.09 (0.07–0.10) < 0.001* 0.73 (0.71–0.75) < 0.001* Secondary 0.14 (0.12–0.17) < 0.001* 0.82 (0.81–0.83) < 0.001* Higher 0.20 (0.14–0.27) < 0.001* 0.90 (0.85–0.94) < 0.001* Religious belief Christianity 0.11 (0.10–0.12) < 0.001* 0.80 (0.79–0.81) < 0.001* Islam 0.08 (0.06–0.09) < 0.001* 0.70 (0.54–0.85) < 0.001* Traditional/others 0.09 (0.08–0.11) < 0.001* 0.79 (0.76–0.82) < 0.001* Literacy Cannot read at all 0.10 (0.08–0.11) < 0.001* 0.73 (0.69–0.76) < 0.001* Able to read only part of sentence 0.09 (0.06–0.11) < 0.001* 0.82 (0.79–0.84) < 0.001* Able to read whole sentence 0.10 (0.09–0.12) < 0.001* 0.80 (0.79–0.81) < 0.001* Frequency of reading newspaper/magazine Not at all 0.10 (0.09–0.11) < 0.001* 0.77 (0.76–0.78) < 0.001* Less than once a week 0.10 (0.08–0.12) < 0.001* 0.84 (0.82–0.85) < 0.001* At least once a week 0.08 (0.06–0.10) < 0.001* 0.83 (0.81–0.85) < 0.001* Frequency of listening to radio Not at all 0.09 (0.08–0.10) < 0.001* 0.77 (0.76–0.79) < 0.001* Less than once a week 0.10 (0.08–0.11) < 0.001* 0.78 (0.77–0.80) < 0.001* At least once a week 0.11 (0.10–0.12) < 0.001* 0.83 (0.82–0.85) < 0.001* Frequency of watching television Not at all 0.08 (0.07–0.09) < 0.001* 0.79 (0.78–0.80) < 0.001* Less than once a week 0.11 (0.10–0.13) < 0.001* 0.81 (0.79–0.83) < 0.001* At least once a week 0.11 (0.10–0.13) < 0.001* 0.80 (0.78–0.82) < 0.001* Frequency of using internet Not at all 0.09 (0.08–0.10) < 0.001* 0.78 (0.77–0.79) < 0.001* Less than once a week 0.17 (0.09–0.25) < 0.001* 0.85 (0.79–0.90) < 0.001* At least once a week 0.14 (0.10–0.18) < 0.001* 0.84 (0.80–0.88) < 0.001* Almost every day 0.19 (0.15–0.23) < 0.001* 0.86 (0.84–0.88) < 0.001* Wealth quintile Barrow et al. Applied Cancer Research (2020) 40:8 Page 11 of 13 Table 3 Marginal predictive models of the factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa (Continued) Variable Benin Zimbabwe Marginal effects (95%CI) P Marginal effects OR (95%CI) P Poorest 0.09 (0.07–0.11) < 0.001* 0.76 (0.74–0.78) < 0.001* Poorer 0.08 (0.06–0.10) < 0.001* 0.78 (0.76–0.81) < 0.001* Middle 0.10 (0.08–0.12) < 0.001* 0.80 (0.77–0.81) < 0.001* Richer 0.10 (0.08–0.11) < 0.001* 0.81 (0.79–0.83) < 0.001* Richest 0.11 (0.09–0.12) < 0.001* 0.83 (0.80–0.85) < 0.001* Marital status Never in union 0.11 (0.09–0.12) < 0.001* 0.73 (0.71–0.75) < 0.001* Currently in union/living with a man 0.10 (0.09–0.11) < 0.001* 0.82 (0.81–0.83) < 0.001* Formerly in union/lived with a man 0.11 (0.08–0.14) < 0.001* 0.82 (0.79–0.84) < 0.001* Occupation Not working 0.08 (0.07–0.10) < 0.001* 0.79 (0.78–0.80) < 0.001* Professional/technical/managerial 0.13 (0.10–0.16) < 0.001* 0.88 (0.83–0.93) < 0.001* Sales 0.11 (0.10–0.12) < 0.001* 0.81 (0.79–0.83) < 0.001* Agricultural 0.06 (0.04–0.07) < 0.001* 0.80 (0.77–0.82) < 0.001* Services 0.13 (0.11–0.15) < 0.001* 0.82 (0.79–0.85) < 0.001* Skilled manual 0.08 (0.06–0.10) < 0.001* 0.77 (0.72–0.83) < 0.001* Geographical region 1 0.08 (0.05–0.10) < 0.001* 0.79 (0.76–0.81) < 0.001* 2 0.13 (0.10–017) < 0.001* 0.85 (0.83–0.87) < 0.001* 3 0.10 (0.08–0.12) < 0.001* 0.83 (0.80–0.85) < 0.001* 4 0.02 (0.01–0.03) 0.001* 0.84 (0.82–0.86) < 0.001* 5 0.15 (0.12–0.18) < 0.001* 0.74 (0.72–0.77) < 0.001* 6 0.13 (0.10–0.16) < 0.001* 0.71 (0.68–0.74) < 0.001* 7 0.09 (0.06–0.12) < 0.001* 0.78 (0.75–0.80) < 0.001* 8 0.13 (0.10–0.15) < 0.001* 0.78 (0.75–0.80) < 0.001* 9 0.11 (0.08–0.13) < 0.001* 0.85 (0.82–0.87) < 0.001* 10 0.06 (0.05–0.08) < 0.001* 0.77 (0.74–0.81) < 0.001* 11 0.05 (0.03–0.08) < 0.001* 12 0.11 (0.09–0.13) < 0.001* Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou. Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = Manicaland East, 4 = Manicaland West, 5 = Manicaland North, 6 = Manicaland South, 7 = Midlands, 8 = Masvingo, 9 = Harare & 10 = Bulawayo. *Significant at p < 0.05 link between a disease and the possible prevention and Zimbabwe is reportedly high, centralized in urban set- control strategies. tings, competing priorities, with limited resources con- The findings from both countries (Benin and fronting their healthcare system; there is a relatively Zimbabwe) showed that the disparities in terms of marginal difference in the awareness of women on cer- women’s awareness of cervical cancer on the basis of age vical cancer through the country’s establishment of a groups and across regions. The awareness level of policy framework to drive this agenda [37]. women on cervical cancer differs in different geograph- Furthermore, awareness of cervical cancer was also as- ical regions of Benin republic [34]. Previous studies re- sociated with women’s age, educational level, household ported that lack of awareness on cervical cancer was wealth quintile, religious belief, marital status, occupa- associated with poor cervical cancer screening practices tion and geographical region. Women who are engaged in third-world countries [4, 24, 35, 36]. Though the cost in professional, technical and managerial jobs have the of cervical cancer services including its information in capacity to understand various health information from Barrow et al. Applied Cancer Research (2020) 40:8 Page 12 of 13 different media platforms which could be attributed to Conclusion the improved odds in awareness of cervical cancer. Such There were disparities and potential barriers to the women could interact with different electronic gadgets awareness levels on cervical cancer in Benin and such as android phones, computers, internet and so Zimbabwe. The study revealed that socio-demographical forth; which will avail them the opportunity to have in- factors including geographical location and selected eco- creased awareness about cervical cancer. The same logic nomic factors greatly explained the unequal coverage of is applicable to women that are rich as compared with women awareness on cervical cancer in both countries. poor women. The differentials in the awareness level be- Overall, multi-sectoral approaches are recommended to tween Muslim women as compared to Christians could address all the multifaceted factors with a view to im- be attributed to the low level of education and cultural proving people’s awareness level on cervical cancer in conservativeness among the Muslim folks. These could resource-constrained settings. further affect their utilization of screening services in- Acknowledgements cluding information regarding cervical cancer. Women The authors appreciate the MEASURE DHS project for the approval and that are currently married have continual and engaged access to the original data. visits to health facilities to access healthcare services Authors’ contributions which include those related to cervical cancer screening ME conceived and designed the study, performed data analysis and wrote and care. These factors were also examined in a previous the results, reviewed the literature, wrote the discussion of the findings. All authors contributed in the review of literature, the discussion of the findings, study [26]. These results suggest that an increase in critically reviewed the manuscript for its intellectual content. ME had the women’s educational level is effective in influencing responsibility to submit the manuscript. All authors read and approved the awareness about diseases including cervical cancer. The final manuscript. findings could also suggest that as women’s educational Funding level increases, they are often more empowered with in- This research received no grant from any funding agency in the public, formation and enlightened to understand more of their commercial or not-for-profit sectors. health issues including cervical cancer risk factors and Availability of data and materials prevention approaches [29, 38]. Data for this study were sourced from Demographic and Health surveys The study revealed the influence of age on the aware- (DHS) and available here: http://dhsprogram.com/data/available-datasets.cfm. ness level of cervical cancer in both settings. As women Ethics approval and consent to participate aged, they have the potential of increased awareness of Ethics approval for this study was not required since the data is secondary various diseases that can affect women including cervical and is available in the public domain. More details regarding DHS data and ethical standards are available at: http://dhsprogram.com/data/available- cancer which is consistent with the findings from the datasets.cfm study by Mitiku & Tefera [16] and a study in Nigeria that reported the influence of age on awareness of cervical can- Consent for publication Demographic and Health Survey is a de-identified open-source dataset. cer [39]as well asinZimbabwe [37]. This can be attrib- Therefore, the requirement of consent for publication is not applicable. uted to their number of parity which includes antenatal care services where they have interactions with healthcare Competing interests workers including health education sessions on maternal The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential health and risk issues with dysfunctional national cervical conflict of interest. cancer screening programme as well as the limited avail- ability of screening centres [40]. Our results also were in Author details Department of Public & Environmental Health, School of Medicine & Allied agreement with a similar study in Zimbabwe, which Health Sciences, University of The Gambia, Kanifing, The Gambia. Project showed that knowledge/awareness of cervical cancer was Management Unit, Management Sciences for Health, Abuja, Nigeria. associated with having at least secondary education [41]. Department of Community Health, Center of Excellence in Reproductive Health Innovation (CERHI), College of Medical Sciences, University of Benin, Benin City, Nigeria. Department of Epidemiology and Medical Statistics, Strengths and limitations Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, The strength of this study is the use of current na- Nigeria. tionally representative datasets to measure prevalence Received: 25 December 2019 Accepted: 6 October 2020 and determinants of awareness cervical cancer in Benin and Zimbabwe. The findings make plausible References comparison and are generalizable to women of repro- 1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer ductive age in both countries. However, the study uti- statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide lized cross-sectional data, hence, only associations and for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. 2. UNAIDS. It’s time to make Cervical Cancer history. UNAIDS Feature story. 04 no causal relationships are established. The unavail- February 2019. 2019. ability of endogenous variables was another limitation 3. Bruni L, Albero G, Serrano B, Mena M, Gómez D, Muñoz J, Bosch FX de SS. in the use of secondary data. ICO/IARC Information Centre on HPV and Cancer (HPV Information Centre). Barrow et al. Applied Cancer Research (2020) 40:8 Page 13 of 13 Human Papillomavirus and Related Diseases in Benin. Summary Report 17 28. Naik DD, Donta B, Nair S, Mali BN. Awareness of sexually transmitted June 2019. 2019;(June). infections and cervical cancer among women in urban slums of Mumbai, 4. World Health Organization (WHO). Comprehensive Cervical Cancer Control; Maharashtra, India. Int J Community Med Public Health. 2017;4(2):400. A guide to essential practice 2 edition. 29. Olubodun T, Odukoya OO, Balogun MR. Knowledge, attitude and practice of Httpswhointreproductivehealthtopicscancerhpv-Vaccininationen. 2014; 2nd cervical cancer prevention, among women residing in an urban slum in Edition (December). Lagos, South West, Nigeria. Pan Afr Med J. 2019;32 [cited 2019 Oct 26]. Available from: http://www.panafrican-med-journal.com/content/ 5. Rosa W. Transforming Our World: The 2030 Agenda for Sustainable article/32/130/full/. Development. In: A New Era in Global Health. New York: Springer 30. Dutta MJ. Health information processing from television: the role of health Publishing Company; 2017. [cited 2019 Feb 14]. Available from: http:// orientation. Health Commun. 2007;21(1):1–9. connect.springerpub.com/lookup/doi/10.1891/9780826190123.ap02. 31. Dutta-Bergman MJ. Primary sources of health information: comparisons in 6. Ntekim A. Cervical Cancer in sub Sahara Africa, topics on cervical cancer the domain of health attitudes, health cognitions, and health behaviors. with an advoocacy for prevention. Dr R Rajamanickam Ed; 2012. p. 51–74. Health Commun. 2004;16(3):273–88. 7. Chin’ombe N, Sebata NL, Ruhanya V, Matarira HT. Human papillomavirus 32. Schwitzer G, Mudur G, Henry D, Wilson A, Goozner M, Simbra M, et al. What genotypes in cervical cancer and vaccination challenges in Zimbabwe. are the roles and responsibilities of the media in disseminating health Infect Agent Cancer. 2014;9:16–9. information? PLoS Med. 2005;2(7):8. 8. Globocan. Zimbabwe Source: Globocan 2018. The global cancer 33. Moynihan R, Bero L, Ross-Degnan D, Henry D, Lee K, Watkins J, et al. observatory. All Right Reserved-May, 2019. 2019. Coverage by the news media of the benefits and risks of medications. N 9. Bruni L, Barrionuevo-Rosas L, Alberto G, Serrano B, Valencia S, Brotons M, Engl J Med. 2000;342(22):1645–50. Mena M, Cosano R, Munoz J, Bosch FX, de Sanjose S CX. Human 34. Piras F, Piga M, De Montis A, Zannou AR, Minerba L, Perra MT, et al. Papillomavirus and Related Diseases Report. ICO HPV Inf Cent. 2015;. Prevalence of human papillomavirus infection in women in Benin. West 10. Tapera O, Kadzatsa W, Nyakabau AM, Mavhu W, Dreyer G, Sjh H. Africa Virol J. 2011;8(1):514. Sociodemographic inequities in cervical cancer screening , treatment and 35. Finocchario-Kessler S, Wexler C, Maloba M, Mabachi N, Ndikum-Moffor F, care amongst women aged at least 25 years : evidence from surveys in Bukusi E. Cervical cancer prevention and treatment research in Africa: a Harare , Zimbabwe. BMC Public Health. 2019;19:1–12. systematic review from a public health perspective. BMC Womens Health. 11. Globocan. Benin Source: Globocan 2018. The Global Cancer Observatory. All 2016;16(1):29. Right Reserved-May, 2019. 36. Drolet M, Bénard É, Boily M-C, Ali H, Baandrup L, Bauer H, et al. Population- 12. Corsi DJ, Neuman M, Finlay JE, Subramanian S. Demographic and health level impact and herd effects following human papillomavirus vaccination surveys: a profile. Int J Epidemiol. 2012;41(6):1602–13. programmes: a systematic review and meta-analysis. Lancet Infect Dis. 2015; 13. Short Fabic M, Choi Y, Bird S. A systematic review of demographic and 15(5):565–80. health surveys: data availability and utilization for research. Bull World 37. Tapera O, Dreyer G, Kadzatsa W, Nyakabau AM, Stray-Pedersen B, Hendricks SJH. Health Organ. 2012;90(8):604–12. Determinants of access and utilization of cervical cancer treatment and palliative 14. Republic of Benin - Country Profile. Benin - Country Profile - Nations Online care services in Harare, Zimbabwe. BMC Public Health. 2019;19(1):1018. Project. [cited 2019 Dec 13]. Available from: http://www.nationsonline.org/ 38. Tapera O, Dreyer G, Kadzatsa W, Nyakabau AM, Stray-Pedersen B, Sjh H. oneworld/benin.htm. Cervical cancer knowledge, attitudes, beliefs and practices of women aged 15. Ploch L. Zimbabwe: Background - congressional research service; 2010. p. 52. at least 25 years in Harare, Zimbabwe. BMC Womens Health. 2019;19(1):91. 16. Mitiku I, Tefera F. Knowledge about cervical cancer and associated factors 39. Ayinde OA, Ogunbode OO, Adebayo OJ. Determinants of cervical cancer among 15–49 year old women in Dessie town, Northeast Ethiopia. knowledge and the utilisation of screening among a Nigerian female Paraskevis D, editor. PLOS ONE. 2016;11(9):e0163136. population. Trop J Obstet Gynaecol. 2006;22(1):21–4. 17. Ayinde OA, Ogunbode OO, Adebayo OJ. Determinants of cervical cancer 40. Ziba F, Baffoe P, Dapare P, Shittu S, Antuamwine B. Awareness and knowledge and the utilisation of screening among a Nigerian female knowledge level of cervical cancer among women of reproductive age in population. Trop J Obstet Gynaecol. 2005;22(1):21–24–24. Bolgatanga municipality. J Med Biomed Sci. 2015;4(2):1. 18. Moshi FV, Vandervort EB, Kibusi SM. Cervical cancer awareness among 41. Mutambara J, Mutandwa P, Mahapa M, Chirasha V, Nkiwane S, women in Tanzania: an analysis of data from the 2011-12 Tanzania HIV and Shangahaidonhi T. Knowledge, attitudes and practices of cervical cancer malaria indicators survey. Int J Chronic Dis. 2018;7. screening among women who attend traditional churches in Zimbabwe. J 19. Rutstein SO, Staveteig S. Making the demographic and health surveys Cancer Res Pract. 2017;4(2):53–8. wealth index comparable; 2014. p. 43. 20. Hruschka DJ, Gerkey D, Hadley C. Estimating the absolute wealth of households. Bull World Health Organ. 2015;93(7):483–90. Publisher’sNote 21. Midi H, Sarkar SK, Rana S. Collinearity diagnostics of binary logistic Springer Nature remains neutral with regard to jurisdictional claims in regression model. J Interdiscip Math. 2010;13(3):253–67. published maps and institutional affiliations. 22. Williams R. Using the margins command to estimate and interpret adjusted predictions and marginal effects. Stata J Promot Commun Stat Stata. 2012; 12(2):308–31. 23. Perlman S, Wamai RG, Bain PA, Welty T, Welty E, Ogembo JG. Knowledge and awareness of HPV vaccine and acceptability to vaccinate in Sub- Saharan Africa: a systematic review. Hozbor DF, editor. PLoS ONE. 2014;9(3): e90912. 24. World Health Organization, editor. Cervical cancer screening in developing countries: report of a WHO consultation. Geneva: World Health Organization; 2002. p. 75. 25. Balogun MR, Odukoya OO, Oyediran M, Ujomu P. Cervical cancer awareness and preventive practices: a challenge for female urban slum dwellers in Lagos, Nigeria. Afr J Reprod Health. 2012;16(1):75–82. 26. Aweke YH, Ayanto SY, Ersado TL. Knowledge, attitude and practice for cervical cancer prevention and control among women of childbearing age in Hossana Town, Hadiya zone, Southern Ethiopia: Community-based cross- sectional study. Robboy SJ, editor. PLOS ONE. 2017;12(7):e0181415. 27. Bathija G, Mallesh S, Gajula M. A study on awareness of cervical cancer among women of reproductive age group in urban slums of old Hubli, Karnataka, India. Int J Community Med Public Health. 2016:2579–83. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Cancer Research Springer Journals

Prevalence and determinants of cervical cancer awareness among women of reproductive age: evidence from Benin and Zimbabwe population-based data

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Abstract

Background: Cervical cancer is a prominently diagnosed form of cancer in several resource-constrained settings particularly within the sub-Saharan African region. Globally, Africa region has the highest incidence and mortality rates of cervical cancer. The high prevalence has been attributed to several factors including lack of awareness of the disease. The aim of this paper is to explore the prevalence and factors associated with awareness of cervical cancer among women of reproductive age in Republic of Benin and Zimbabwe, sub-Saharan Africa. Methods: We used population-based cross-sectional data from Benin Demographic and Health Survey (BDHS) and Zimbabwe Demographic and Health Survey (ZDHS) respectively. BDHS 2017–18 and ZDHS - 2015 are the 5th and 6th rounds of the surveys respectively. About 15,928 and 9955 women aged 15–49 years were included in this study respectively. The awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe was measured dichotomously; yes (if a woman heard of cervical cancer) vs. no (if a woman has not heard of cervical cancer). All significant variables from the bivariate analysis were included in the multivariable logistic regression model to calculate the adjusted odds ratios (AOR) with corresponding 95% confidence interval. (Continued on next page) * Correspondence: mic42006@gmail.com Amadou Barrow and Michael Ekholuenetale are authors contributed equally and are joint first authors. Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Barrow et al. Applied Cancer Research (2020) 40:8 Page 2 of 13 (Continued from previous page) Results: While majority (79.2%) of women from Zimbabwe have heard about cervical cancer, only about one-tenth (10.2%) of their Beninese counterparts have heard about the disease. Advanced maternal age, having formal education, use of internet, having professional/technical/managerial occupation significantly increased the odds of awareness of cervical cancer after adjusting for other confounders. However, in Benin, women who resided in the rural area and those of Islamic belief had 20% (AOR = 0.80; 95%CI: 0.64, 0.99) and 35% (AOR = 0.65; 95%CI: 0.50, 0.86) reduction in the odds of awareness of cervical cancer respectively, when compared with women from urban residence and Christianity. Results from the predictive marginal effects showed that, assuming the distribution of all factors remained the same among women, but every woman is an urban dweller, we would expect 11.0 and 81.0% level of awareness of cervical cancer; If everywoman had higher education, we would expect 20.0 and 90% level of awareness of cervical cancer and if instead the distribution of other maternal factors were as observed and other covariates remained the same among women, but all women were in the richest household wealth quintile, we would expect about 11.0 and 83.0% level of awareness of cervical cancer, among women of reproductive age from Benin and Zimbabwe respectively. Conclusion: The study has revealed that socio-demographical factors including geographical location and selected economic factors explained the inequality in distribution of women’s awareness on cervical cancer in both countries. Designing an effective population-based health education and promotion intervention programs on cervical cancer will be a great way forward to improving women’s awareness level on cervical cancer. Keywords: Knowledge, Human papillomavirus, HPV, Maternal health, Health education, Africa Background cervical cancer, Human Papilloma Virus (HPV), screen- Cervical cancer has been reported to be the fourth most ing and treatment of cervical pre-cancer, diagnosis and commonly detected cancer among women globally [1]. It treatment of invasive cervical cancer and provision of ranks secondbehindbreastcancer asthe most incident palliative care to patients with cervical cancer [4]. It is and mortal cancer among women in lower human devel- against this backdrop that all member nations especially opment index (HDI) settings. It is also the most com- poor-resource countries are encouraged to key into this monly diagnosed cancer in 28 countries and the leading guideline to make sure that the burden of cervical cancer cause of cancer death in 42 countries, with majority of is effectively reduced. A strict adherence to this guide- which are sub-Saharan Africa (SSA) and South Eastern line will ensure that the Sustainable Development Goals Asia [1]. Africa has the highest incidence and mortality 3 (especially 3.3, 3.4, 3.7 and 3.8) of the United Nations rates of cervical cancer among other regions of the world; that advocates for good healthy living and promotion of the rates are elevated in the Southern Africa countries wellbeing for all at all ages [5], will be met. with Swaziland having the highest incidence rate; followed Several factors have been identified to be associated by Eastern Africa with Malawi having the highest rate of with cervical cancer; these include poor cervical cancer death followed by Zimbabwe; and Western Africa, with screening, lack of awareness and knowledge of cervical Guinea, Burkina Faso, and Mali taking the lead in that cancer; biological factors such as poor nutrition, infec- order [1]. Nearly 80% of all cervical cancers and 90% of tions with human immunodeficiency virus (HIV), tuber- deaths occur in the poor-resource countries of the world culosis (TB), malaria; socioeconomic and socio-cultural with SSA bearing the highest burden [2]. It was also esti- factors with political inequities, have been implicated in mated that if cervical cancer prevention, screening and the high prevalence of cervical cancer in SSA countries treatment are not immediately and urgently scaled up, [6]. Though cervical cancer is the most common cancer there could be a 50% increase in mortality over 2018 levels among women living with HIV, persistent infection with by 2040 [2]. Unfortunately, the west African region has a HPV has been implicated as the most common cause of total annual new cases of cervical cancer of 31,955 at a the cancer of the cervix. Women living with HIV are up crude incidence and age-standardized rates of 16.8 and to five times more likely to develop invasive cervical can- 29.6 (cases of cancer per 100,000 women per year) [3]. cer than other women. In SSA, cervical cancer is report- In 2014, the World Health Organization (WHO) pub- edly a prominent cancer killer of women [6]. lished an updated guideline from the previous 2006 Cervical cancer is known to be the most frequently di- guideline on the prevention and control of cervical can- agnosed cancer amongst Zimbabwean women and it ac- cer [4]. This was to be achieved through community counts for about a third of all cancers in this mobilization, education and counseling, vaccination of Zimbabwean key population [7]. Report has shown that girls 9–13 years against the major known cause of 3186 new cases of cervical cancer and 2151 deaths occur Barrow et al. Applied Cancer Research (2020) 40:8 Page 3 of 13 as a result of the disease every year in Zimbabwe [8]. available in the public domain and accessed at; http:// This data projects that about 4.5 million Zimbabwean dhsprogram.com/data/available-datasets.cfm. women are at the risk of cervical cancer in their life time [9]. Evidence shows that only about a third of Zimbab- Study design wean women had ever been screened for cervical cancer DHS project is funded by the United States Agency for and affiliation to major religious groups and non-visit to International Development (USAID) with support from health facilities were negative contributory factors to other donors and host countries, has conducted over poor screening uptake [10]. Furthermore, in the republic 230 nationally representative and internationally com- of Benin, just as in many other SSA countries, the issue parable household surveys in more than 80 countries of cervical cancer is still a great public health problem. since its inception in 1984. The first three of the DHS’s Though there are no available data from Cancer Registry six phases were implemented between 1984 and 1997. in Benin for cervical cancer [3], Globocon 2018 and Thereafter the project was folded into a family of USAID International Agency for Research in Cancer (IARC) monitoring and evaluation projects and was renamed 2019 survey data show that cervical cancer ranks the MEASURE DHS. DHS originally collected comparable third most incident and most prevalent cancer among population-based data on fertility, contraception, mater- Beninese after breast cancer and prostate cancer in that nal and child health and nutrition in developing coun- order, with an annual new diagnosed cases of 783 and tries. Today, DHS core questionnaires cover a wider the second most common cancer and cause of cancer range of population and health topics. DHS used a two- death, with annual death of 652 among Beninese women stage stratified cluster sampling method to select enu- [1, 3, 11]. The death rate caused by cervical cancer is meration areas (EAs) and household samples. The first number 3 among all types of cancer. The age- stage involves the selection of EAs with probability pro- standardized rate in terms of incidence among the fe- portional to the size. Secondly, from the total residential male Beninese population is about one-quarters [1, 3, households selected, a number of households were se- 11]. lected per EA. All women of reproductive age (15 to 49 SSA region has the highest incidence rate of cervical years) were selected for the component of the survey in- cancer when compared with other regions of the world, cluding respondents’ characteristics. The survey design, with associated high mortality affecting women at their sampling technique, data collection instruments, data prime [6]. Screening programs are grossly inadequate or quality assurance, ethical approval and subject consent non-available thereby making early detection of precan- for DHS were conducted appropriately in line with inter- cerous lesions inefficient or in many instances practically national standard [12, 13]. The DHS were initially de- impossible, within the countries in the region. Most signed to expand on demographic, fertility and family screening activities are done as pilot or research projects planning data collected in the World Fertility Surveys and which are discontinued on completion [6]. This has Contraceptive Prevalence Surveys, but continue to provide made awareness of cervical cancer, its screening and risk an important resource for the monitoring of vital statistics factors among the women population in most parts of and population health indicators. DHS collects a wide this region very poor, thereby resulting in high inci- range of data with a focus on indicators of fertility, repro- dence, prevalence, and mortality rate [1, 3, 8, 11]. In the ductive health, maternal and child health, mortality, nutri- light of the above, we undertake this paper to explore tion and health behaviours. DHS data is useful in public the prevalence and factors associated with awareness of health research focused on monitoring of prevalence, cervical cancer among women of reproductive age in Re- trends and inequalities. During the survey, multi-stage public of Benin and Zimbabwe, sub-Saharan Africa. stratified cluster sampling approach was used to select the respondents based on allocation of specific numbers of Methods clusters to urban and rural settlements in the country. Dif- Data extractionges ferent questionnaires were designed to obtain information We used population-based cross-sectional data from related to women, men, households, children and couples. Benin Demographic and Health Survey (BDHS) and The reliability and validity of the questionnaires were well Zimbabwe Demographic and Health Survey (ZDHS) re- conducted using standard methods. An overview of the spectively. BDHS 2017–18 and ZDHS - 2015 are the 5th DHS along with an introduction to the potential scope for and 6th rounds of the surveys respectively. About 15,928 these data is reported elsewhere. and 9955 women of reproductive age from Benin and Zimbabwe were included in this study respectively. By Study area implication, the data analyzed in this study included The geographical regions in Benin, include; Alibori, Ata- women aged 15–49 years. BDHS and ZDHS have re- cora, Atlantique, Borgou, Collines, Couffo, Donga, sponse rates of 98.1 and 96.2% respectively. The data is Littoral, Mono, Quémé, Plateau and Zou. The country Barrow et al. Applied Cancer Research (2020) 40:8 Page 4 of 13 spans from north to south and a long stretched country Masvingo, 9 = Harare & 10 = Bulawayo. These factors in West Africa, located west of Nigeria and east of Togo, were included based on previous studies that examined it is bordered to the north by Niger and Burkina Faso, in the factors associated with awareness of cervical cancer south by the Bight of Benin, in the Gulf of Guinea, that [16–18]. Household wealth quintile: principal compo- part of the tropical North Atlantic Ocean which is nents analysis (PCA) was used to assign the wealth indi- roughly south of West Africa. Benin’s coastline is ap- cator weights. This procedure assigned scores and proximately 121 km long, with an area of 112,622 km . standardized the wealth indicator variables such as; bi- Benin’s former name, until 1975, was Dahomey. Benin cycle, motorcycle/scooter, car/truck, main floor material, has a population of 10 million people (in 2013), Porto- main wall material, main roof material, sanitation facil- Novo, a port on an inlet of the Gulf of Guinea is the na- ities, water source, radio, television, electricity, refriger- tion’s capital city, largest city and economic capital is ator, cooking fuel, furniture, number of persons per Cotonou. Spoken languages are French (official), Fon room. The factor coefficient scores (factor loadings) and and Yoruba [14]. Furthermore, Zimbabwe has nine [9] z-scores were calculated. For each household, the indica- geographical regions, namely; Manicaland, Manicaland tor values were multiplied by the loadings and summed Central, Manicaland East, Manicaland West, Manicaland to produce the household’s wealth index value. The North, Manicaland South, Midlands, Masvingo, Harare & standardized z-score was used to disentangle the overall Bulawayo. Zimbabwe is a landlocked country in southern assigned scores to poorest/poorer/middle/richer/richest Africa lying wholly within the tropics. It has a total land categories [19, 20]. area of about 390,000 km and a population of about 15 million. It shares a 125-mile (200-km) border on the south Ethical consideration with the Republic of South Africa and is bounded on the This study was based on an analysis of population-based southwest and west by Botswana, on the north by Zambia, dataset available in public domain/ online with all identi- and on the northeast and east by Mozambique. The cap- fier information removed. The authors communicated ital is Harare (formerly called Salisbury). More than two- with MEASURE DHS/ICF International and permission thirds of Zimbabweans speak Shona as their first language, was granted to download and use the data. The DHS while about one out of six speak Ndebele [15]. project obtained the required ethical approvals from the relevant research ethics committee in Benin and Outcome variable Zimbabwe, before the survey was conducted to ensure The awareness of cervical cancer among women of re- that the protocols are in compliance with the U.S. De- productive age in Benin and Zimbabwe was measured partment of Health and Human Services regulations for dichotomously; yes (if a woman heard of cervical cancer) the protection of human subjects. Written informed vs. no (if a woman has not heard of cervical cancer). consents were obtained from participants before being allowed in the surveys. Explanatory variables Age (years) of respondent: 15–19, 20–24, 25–29, 30–34, Statistical analysis 35–39, 40–44, 45–49; residential status: urban vs. rural; In Stata, the Survey (‘svy’) module was used to adjust for educational attainment: no formal education, primary, stratification, clustering and sampling weights to com- secondary, higher; religious background: Christianity, pute the estimates of awareness on cervical cancer. The Islam, traditional/others; literacy: cannot read at all/able collinearity testing approach adopted the correlation to read only part of sentence, able to read whole sen- analysis to detect interdependence between variables. A tence; read newspaper: not at all, less than once a week, cut-off of 0.7 was used to examine the multicollinearity at least once a week; listen to radio: not at all, less than known to cause major concerns [21]. No variable from once a week, at least once a week; watch TV: not at all, the correlation matrix was removed in the model due to less than once a week, at least once a week; marital sta- lack of multicollinearity. Women’s characteristics were tus: never in union, currently in union/living with a obtained using percentages. Chi-square test was used to man, formerly in union/lived with a man; occupation: examine the association between awareness on cervical not working, professional/technical/managerial, sales, and the explanatory variables. All significant variables agricultural, services, skilled manual; geographical re- from the bivariate analysis were included in the multi- gion: Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = variable logistic regression model to calculate the ad- Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, justed odds ratios (with corresponding 95%CI). In 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou; addition, we obtained the marginal predictive effects of Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = the factors. Based on the estimation of multivariable lo- Manicaland East, 4 = Manicaland West, 5 = Manicaland gistic regression model, we predicted the probability of North, 6 = Manicaland South, 7 = Midlands, 8 = awareness on cervical cancer. Thus; Barrow et al. Applied Cancer Research (2020) 40:8 Page 5 of 13 Determinants of awareness of cervical cancer among PrðÞ Y ¼ 1jSet½ E ¼ e¼ p PrðÞ Z ¼ z ; ez women aged 15–49 years in Benin and Zimbabwe In Table 2, several factors were statistically significant with Where Set [E = e] reflects putting all observations to a awareness of cervical cancer using multivariable logistic single exposure level e, and Z = z refers to a given set of regression model. In both countries, advanced maternal observed values for the covariate vector Z. Furthermore, age, having formal education, use of internet, having pro- p is the predicted probabilities of awareness on cervical fessional/technical/managerial occupation significantly in- ez cancer for any E = e and Z = z. The marginal effects indi- creased the odds of awareness on cervical cancer after cate a weighted average over the distribution of the co- adjusting for other confounders. However, in Benin, variates and are equal to estimates got by standardizing women who resided in the rural area and those who had to the entire population. As a post logistic regression test, Islamic belief had 20% (OR = 0.80; 95%CI: 0.64, 0.99) and the exposure E is set to the level e forall womeninthe data- 35% (OR = 0.65; 95%CI: 0.50, 0.86) reduction in the odds set, and the logistic regression coefficients are used to com- of awareness on cervical cancer respectively, when com- pute predicted probabilities for every woman at their pared with women from urban residence and Christianity observed covariate pattern and newly exposure value. Be- after adjusting for other covariates. Women who watch cause predicted probabilities are computed under the same television had higher odds of awareness on cervical cancer, distribution of Z, there is no covariate of the corresponding compared with women who do not watch television at all effect measure estimates [22]. Statistical significance was de- after adjusting for other covariates. In Zimbabwe, women termined at p < 0.05. Data analysis was conducted using Stata who are able to read at least part of a sentence, read news- Version 14 (StataCorp., College Station, TX, USA). paper/magazine, listen to radio, had increase in the odds of awareness on cervical cancer, when compared with Results women who cannot read at all, do not read newspaper/ The results from Fig. 1 showed that while majority (79.2%) magazine, do not listen to radio after adjusting for other of women from Zimbabwe reportedly have heard about cer- confounders. Furthermore, increased household wealth vical, only about one-tenth (10.2%) of women from Benin quintile level and ever being married increased the odds of have heard about cervical cancer. See Fig. 1 for the details. awareness on cervical cancer among women, when com- The results from Table 1 showed that the proportion of pared with women from poorest household and those women who have ever heard about cervical cancer some- who were never in union after adjusting for other covari- what increased by increases in age in both countries. ates. See Table 2 for the details. Clearly, women from urban residence, higher educational attainment, able to read whole sentence, read newspaper/ Predictive marginal effects of the factors associated with magazine, listen to radio, watch television, use internet, awareness of cervical cancer among women aged 15–49 non-poor and have professional/technical/managerial occu- years in Benin and Zimbabwe pation reportedly have higher proportion of ever heard of In Table 3, marginal effect analysis was used to decipher cervical cancer in Benin and Zimbabwe respectively. In the effects of the factors associated with awareness of addition, all explanatory variables were statistically signifi- cervical cancer among women of reproductive age in cant with awareness of cervical cancer using Chi-square Benin and Zimbabwe. Overall, advanced maternal age, test. See Table 1 for the details. urban residence, higher education, Christianity faith, Fig. 1 Awareness and screening of cervical cancer among women of age in Benin and Zimbabwe Barrow et al. Applied Cancer Research (2020) 40:8 Page 6 of 13 Table 1 Awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa Variable Benin Zimbabwe n (%) Heard about cervical p n (%) Heard about cervical p cancer cancer No (%) Yes (%) No (%) Yes (%) Age (years) of respondent < 0.001* < 0.001* 15–19 3335 (20.9) 93.7 6.3 2156 (21.7) 43.2 56.8 20–24 2916 (18.3) 88.8 11.2 1782 (17.9) 22.7 77.3 25–29 2971 (18.7) 88.0 12.0 1656 (16.6) 15.0 85.0 30–34 2195 (13.8) 89.6 10.4 1591 (16.0) 11.1 88.9 35–39 1905 (12.0) 89.5 10.5 1209 (12.1) 10.7 89.3 40–44 1333 (8.4) 87.9 12.1 966 (9.7) 10.7 89.3 45–49 1273 (8.0) 89.4 10.6 595 (6.0) 12.3 87.7 Residential status < 0.001* < 0.001* Urban 7045 (44.2) 84.9 15.1 4521 (45.4) 12.4 87.6 Rural 8883 (55.8) 93.8 6.2 5434 (54.6) 27.7 72.3 Education level < 0.001* < 0.001* None 8762 (55.0) 95.0 5.0 106 (1.1) 40.6 59.4 Primary 3116 (19.6) 91.0 9.0 2385 (24.0) 33.3 66.7 Secondary 3685 (23.1) 81.0 19.0 6637 (66.7) 18.3 81.7 Higher 365 (2.3) 48.1 51.9 827 (8.3) 2.1 97.9 Religious belief < 0.001* 0.002* Christianity 8784 (55.1) 86.1 13.9 9385 (94.3) 20.4 79.6 Islam 4677 (29.4) 94.9 5.1 30 (0.3) 20.0 80.0 Traditional/others 2467 (15.5) 93.3 6.7 540 (5.4) 26.9 73.1 Literacy < 0.001* < 0.001* Cannot read at all 10,359 (65.4) 94.3 5.7 495 (5.0) 44.2 55.8 Able to read only part of sentence 1133 (7.1) 91.6 8.4 734 (7.4) 28.2 71.8 Able to read whole sentence 4357 (27.5) 78.6 21.4 8698 (87.6) 18.7 81.3 Frequency of reading newspaper/magazine < 0.001* < 0.001* Not at all 14,419 (90.5) 91.4 8.6 5446 (54.7) 28.1 71.9 Less than once a week 878 (5.5) 73.9 26.1 2778 (27.9) 13.4 86.6 At least once a week 631 (4.0) 76.7 23.3 1731 (17.4) 9.5 90.5 Frequency of listening to radio < 0.001* < 0.001* Not at all 6840 (42.9) 94.1 5.9 4482 (45.0) 26.8 73.2 Less than once a week 3408 (21.4) 89.7 10.3 2112 (21.2) 19.0 81.0 At least once a week 5680 (35.7) 84.8 15.2 3361 (33.8) 13.7 86.3 Frequency of watching television < 0.001* < 0.001* Not at all 9775 (61.4) 94.5 5.5 5054 (50.8) 27.1 72.9 Less than once a week 2741 (17.2) 87.6 12.4 1381 (13.9) 17.3 82.7 At least once a week 3412 (21.4) 78.0 22.0 3520 (35.4) 12.9 87.1 Frequency of using internet < 0.001* < 0.001* Not at all 14,845 (93.2) 92.2 7.8 7325 (73.6) 25.4 74.6 Less than once a week 141 (0.9) 70.8 29.2 214 (2.1) 12.1 87.9 At least once a week 281 (1.8) 68.6 31.4 413 (4.1) 10.2 89.8 Almost every day 661 (4.1) 50.5 49.5 2003 (20.1) 7.0 93.0 Wealth quintile < 0.001* < 0.001* Barrow et al. Applied Cancer Research (2020) 40:8 Page 7 of 13 Table 1 Awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa (Continued) Variable Benin Zimbabwe n (%) Heard about cervical p n (%) Heard about cervical p cancer cancer No (%) Yes (%) No (%) Yes (%) Poorest 2856 (17.9) 96.3 3.7 1499 (15.1) 36.4 63.6 Poorer 2976 (18.7) 95.4 4.6 1452 (14.6) 28.6 71.4 Middle 2985 (18.7) 92.7 7.3 1549 (15.6) 24.7 75.3 Richer 3281 (20.6) 90.5 9.5 2558 (25.7) 15.4 84.6 Richest 3830 (24.0) 77.3 22.7 2897 (29.1) 11.3 88.7 Marital status < 0.001* < 0.001* Never in union 3897 (24.5) 88.5 11.5 2666 (26.8) 35.3 64.7 Currently in union/living with a man 11,170 (70.1) 90.7 9.3 6015 (60.4) 15.5 84.5 Formerly in union/lived with a man 861 (5.4) 84.3 15.7 1274 (12.8) 15.1 84.9 Occupation < 0.001* < 0.001* Not working 3527 (23.0) 91.7 8.3 4897 (54.3) 27.8 72.2 Professional/technical/managerial 543 (3.5) 60.8 39.2 615 (6.8) 2.4 97.6 Sales 4537 (29.6) 87.7 12.3 1794 (19.9) 12.5 87.5 Agricultural 3065 (20.0) 97.0 3.0 742 (8.2) 18.3 81.7 Services 1842 (12.0) 86.5 13.5 728 (8.1) 11.7 88.3 Skilled manual 1825 (11.9) 93.8 6.2 249 (2.8) 14.9 85.1 Geographical region < 0.001* < 0.001* 1 1697 (10.7) 96.4 3.6 1019 (10.2) 23.2 76.8 2 1392 (8.7) 91.6 8.4 993 (10.0) 18.2 81.2 3 1702 (10.7) 85.4 14.6 910 (9.1) 17.1 82.9 4 1765 (11.1) 98.6 1.4 1054 (10.6) 16.3 83.7 5 1403 (8.8) 87.3 12.7 849 (8.5) 32.4 67.6 6 1012 (6.4) 89.9 10.1 829 (8.3) 34.3 65.7 7 964 (6.1) 94.5 5.5 1062 (10.7) 24.3 75.7 8 1415 (8.9) 70.3 29.7 1046 (10.5) 24.2 75.8 9 816 (5.1) 87.9 12.1 1235 (12.4) 9.1 90.9 10 1260 (7.9) 92.0 8.0 958 (9.6) 14.5 85.5 11 952 (6.0) 95.5 4.5 12 1550 (9.7) 88.0 12.0 Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou. Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = Manicaland East, 4 = Manicaland West, 5 = Manicaland North, 6 = Manicaland South, 7 = Midlands, 8 = Masvingo, 9 = Harare & 10 = Bulawayo. *Significant at p < 0.005 ability to read whole sentence and/or newspaper or cervical cancer among women of reproductive age from magazine, listening to radio at least once a week, watch- Benin and Zimbabwe respectively. If everywoman had ing television at least once a week, using internet almost higher education, we would expect 20.0 and 90% level of every day, richest households and professional/technical/ awareness of cervical cancer among women of repro- managerial occupation have higher marginal effects of ductive age from Benin and Zimbabwe respectively. If awareness of cervical cancer among women of repro- instead the distribution of other maternal factors were as ductive age from Benin and Zimbabwe respectively. observed and other covariates remained the same among Clearly, from the predictive marginal effects results, as- women, but all women were in the richest household suming the distribution of all factors remained the same wealth quintile, we would expect about 11.0 and 83.0% among women, but every woman is an urban dweller, level of awareness of cervical cancer among women of we would expect 11.0 and 81.0% level of awareness of reproductive age from Benin and Zimbabwe respectively. Barrow et al. Applied Cancer Research (2020) 40:8 Page 8 of 13 Table 2 Factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub- Saharan Africa Variable Benin Zimbabwe Adjusted odds ratio (95%CI) P Adjusted odds ratio (95%CI) P Age (years) of respondent (ref: 15–19) 20–24 1.99 (1.42–2.78) < 0.001* 1.77 (1.46–2.14) < 0.001* 25–29 2.51 (1.72–3.67) < 0.001* 2.80 (2.24–3.51) < 0.001* 30–34 2.48 (1.62–3.80) < 0.001* 3.89 (3.06–4.93) < 0.001* 35–39 2.74 (1.78–4.25) < 0.001* 4.49 (3.44–5.85) < 0.001* 40–44 3.91 (2.47–6.17) < 0.001* 4.58 (3.45–6.09) < 0.001* 45–49 3.11 (1.96–4.95) < 0.001* 5.01 (3.61–6.96) < 0.001* Residential status (ref: Urban) Rural 0.80 (0.64–0.99) 0.043* 0.80 (0.62–1.03) 0.084 Education level (ref: None) Primary 1.34 (1.01–1.81) 0.049* 1.50 (0.93–2.40) 0.097 Secondary 2.53 (1.70–3.78) < 0.001* 2.91 (1.78–4.76) < 0.001* Higher 4.19 (2.36–7.44) < 0.001* 6.34 (2.98–13.46) < 0.001* Religious belief (ref: Christianity) Islam 0.65 (0.50–0.86) 0.002* 0.50 (0.19–1.33) 0.165 Traditional/others 0.85 (0.64–1.13) 0.258 0.94 (0.74–1.19) 0.606 Literacy (ref: Cannot read at all) Able to read only part of sentence 0.88 (0.59–1.31) 0.526 1.93 (1.43–2.59) < 0.001* Able to read whole sentence 1.12 (0.78–1.59) 0.545 1.63 (1.27–2.08) < 0.001* Frequency of reading newspaper/magazine (ref: Not at all) Less than once a week 0.99 (0.73–1.35) 0.968 1.68 (1.43–1.96) < 0.001* At least once a week 0.70 (0.48–1.03) 0.068 1.59 (1.28–1.98) < 0.001* Frequency of listening to radio (ref: Not at all) Less than once a week 1.07 (0.83–1.38) 0.608 1.07 (0.92–1.26) 0.365 At least once a week 1.21 (0.96–1.52) 0.100 1.59 (1.37–1.84) < 0.001* Frequency of watching television (ref: Not at all) Less than once a week 1.50 (1.16–1.93) 0.002* 1.14 (0.94–1.38) 0.194 At least once a week 1.44 (1.10–1.89) 0.008* 1.05 (0.87–1.27) 0.586 Frequency of using internet (ref: Not at all) Less than once a week 2.40 (1.25–4.59) 0.008* 1.68 (1.02–2.76) 0.042* At least once a week 1.83 (1.17–2.84) 0.008* 1.52 (1.06–2.20) 0.023* Almost every day 2.77 (1.96–3.93) < 0.001* 1.90 (1.50–2.39) < 0.001* Wealth quintile (ref: Poorest) Poorer 0.88 (0.60–1.30) 0.529 1.20 (1.01–1.43) 0.050* Middle 1.09 (0.75–1.58) 0.660 1.30 (1.08–1.57) 0.007* Richer 1.06 (0.72–1.53) 0.766 1.45 (1.13–1.88) 0.004* Richest 1.21 (0.81–1.82) 0.356 1.68 (1.20–2.34) 0.002* Marital status (ref: Never in union) Currently in union/living with a man 0.86 (0.65–1.15) 0.321 1.95 (1.63–2.33) < 0.001* Formerly in union/lived with a man 1.05 (0.68–1.60) 0.832 1.83 (1.42–2.36) < 0.001* Occupation (ref: Not working) Professional/technical/managerial 1.74 (1.20–2.54) 0.004* 2.24 (1.27–3.95) 0.005* Barrow et al. Applied Cancer Research (2020) 40:8 Page 9 of 13 Table 2 Factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub- Saharan Africa (Continued) Variable Benin Zimbabwe Adjusted odds ratio (95%CI) P Adjusted odds ratio (95%CI) P Sales 1.45 (1.11–1.91) 0.007* 1.17 (0.98–1.39) 0.080 Agricultural 0.63 (0.41–0.95) 0.028* 1.08 (0.86–1.35) 0.521 Services 1.84 (1.35–2.50) < 0.001* 1.27 (0.98–1.65) 0.074 Skilled manual 0.91 (0.63–1.31) 0.628 0.89 (0.60–1.33) 0.583 Geographical region (ref: 1) 2 2.09 (1.24–3.51) 0.005* 1.62 (1.26–2.08) < 0.001* 3 1.47 (0.90–2.40) 0.127 1.39 (1.07–1.81) 0.014* 4 0.22 (0.10–0.46) < 0.001* 1.52 (1.17–1.95) 0.001* 5 2.54 (1.55–4.17) < 0.001* 0.74 (0.58–0.94) 0.016* 6 2.08 (1.22–3.57) 0.007* 0.60 (0.47–0.78) < 0.001* 7 1.22 (0.68–2.19) 0.507 0.93 (0.73–1.18) 0.533 8 1.93 (1.18–3.19) 0.009* 0.93 (0.74–1.18) 0.576 9 1.53 (0.88–2.67) 0.131 1.66 (1.23–2.23) 0.001* 10 0.78 (0.46–1.33) 0.373 0.89 (0.66–1.21) 0.465 11 0.66 (0.35–1.24) 0.202 12 1.67 (1.01–2.77) 0.048* Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou. Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = Manicaland East, 4 = Manicaland West, 5 = Manicaland North, 6 = Manicaland South, 7 = Midlands, 8 = Masvingo, 9 = Harare & 10 = Bulawayo. *Significant at p < 0.05 In Table 3, we practically obtained the predictive mar- of cervical cancer [25], among Ethiopian women of ginal effects of the factors associated with level of aware- childbearing age, there was low level of awareness [26]; ness of cervical cancer among women of reproductive while similar studies in India reported that one in twelve age from Benin and Zimbabwe respectively. See Table 3 women and one-third of women had heard and were for the details. aware of cervical cancer [27, 28]. In this study, the use of print and electronic media Discussion were major factors that enhanced awareness of cervical This study revealed low awareness of cervical cancer cancer among women. Similar to the findings from pre- specifically in Benin as opposed to Zimbabwe. It is pos- vious studies, different media platforms such as radio, sible that low literacy levels, poor use of the media, in- print media, internet, TV and organized educational pro- cluding; listening to radio, watching TV and internet use grams positioned women to be advantageous in accessi- may have been linked to these findings. This is in line bility to health information [29]; as also found in both with a systematic review in SSA which stated low aware- Benin and Zimbabwe. It was also found that rural com- ness of cervical cancer among women [23]. This study munities are an underserved portion of the population demonstrated that in Zimbabwe, although 79.2% of with limited access to health information [30–32]. women had heard of cervical cancer, only 17% had been Awareness of cervical cancer by residential status re- screened. Obviously the scenario is still worse in Benin; markably varied especially as in the case of Benin Re- hence this study becomes crucial to contribute to the public. This could be due to the fact that women in knowledge base. Generally, the low level of awareness of rural settings have low knowledge and access to cervical cervical cancer has been recognized as one of the factors cancer information and services. Health information dis- leading to the high prevalence of cervical cancer in semination is a major growth area for the media, prob- resource-constrained settings compared to the devel- ably because it is in demand by the populace and it is oped world [24]. Women’s knowledge of core health is- profitable. Nonetheless, media coverage of medical news sues including prevention and control of cervical cancer is generally and may be of diverse quality, especially has been poor in resource-constrained settings. For ex- messages about screening channels and new treatments ample, in a study carried out in two urban slums in [33]. The media can have a substantial positive public Lagos, Nigeria, about one in twenty women were aware health role in communicating simple warnings about the Barrow et al. Applied Cancer Research (2020) 40:8 Page 10 of 13 Table 3 Marginal predictive models of the factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa Variable Benin Zimbabwe Marginal effects (95%CI) P Marginal effects OR (95%CI) P Age (years) of respondent 15–19 0.05 (0.04–0.07) < 0.001* 0.67 (0.64–0.69) < 0.001* 20–24 0.09 (0.08–0.11) < 0.001* 076 (0.74–0.78) < 0.001* 25–29 0.11 (0.10–0.13) < 0.001* 0.83 (0.81–0.85) < 0.001* 30–34 0.11 (0.09–0.13) < 0.001* 0.86 (0.84–0.88) < 0.001* 35–39 0.12 (0.10–0.14) < 0.001* 0.88 (0.86–0.90) < 0.001* 40–44 0.15 (0.12–0.18) < 0.001* 0.88 (0.86–0.90) < 0.001* 45–49 0.13 (0.10–0.16) < 0.001* 0.89 (0.86–0.91) < 0.001* Residential status Urban 0.11 (0.09–0.12) < 0.001* 0.81 (0.79–0.84) < 0.001* Rural 0.09 (0.08–0.10) < 0.001* 079 (0.77–0.80) < 0.001* Education level None 0.07 (0.06–0.08) < 0.001* 0.66 (0.58–0.74) < 0.001* Primary 0.09 (0.07–0.10) < 0.001* 0.73 (0.71–0.75) < 0.001* Secondary 0.14 (0.12–0.17) < 0.001* 0.82 (0.81–0.83) < 0.001* Higher 0.20 (0.14–0.27) < 0.001* 0.90 (0.85–0.94) < 0.001* Religious belief Christianity 0.11 (0.10–0.12) < 0.001* 0.80 (0.79–0.81) < 0.001* Islam 0.08 (0.06–0.09) < 0.001* 0.70 (0.54–0.85) < 0.001* Traditional/others 0.09 (0.08–0.11) < 0.001* 0.79 (0.76–0.82) < 0.001* Literacy Cannot read at all 0.10 (0.08–0.11) < 0.001* 0.73 (0.69–0.76) < 0.001* Able to read only part of sentence 0.09 (0.06–0.11) < 0.001* 0.82 (0.79–0.84) < 0.001* Able to read whole sentence 0.10 (0.09–0.12) < 0.001* 0.80 (0.79–0.81) < 0.001* Frequency of reading newspaper/magazine Not at all 0.10 (0.09–0.11) < 0.001* 0.77 (0.76–0.78) < 0.001* Less than once a week 0.10 (0.08–0.12) < 0.001* 0.84 (0.82–0.85) < 0.001* At least once a week 0.08 (0.06–0.10) < 0.001* 0.83 (0.81–0.85) < 0.001* Frequency of listening to radio Not at all 0.09 (0.08–0.10) < 0.001* 0.77 (0.76–0.79) < 0.001* Less than once a week 0.10 (0.08–0.11) < 0.001* 0.78 (0.77–0.80) < 0.001* At least once a week 0.11 (0.10–0.12) < 0.001* 0.83 (0.82–0.85) < 0.001* Frequency of watching television Not at all 0.08 (0.07–0.09) < 0.001* 0.79 (0.78–0.80) < 0.001* Less than once a week 0.11 (0.10–0.13) < 0.001* 0.81 (0.79–0.83) < 0.001* At least once a week 0.11 (0.10–0.13) < 0.001* 0.80 (0.78–0.82) < 0.001* Frequency of using internet Not at all 0.09 (0.08–0.10) < 0.001* 0.78 (0.77–0.79) < 0.001* Less than once a week 0.17 (0.09–0.25) < 0.001* 0.85 (0.79–0.90) < 0.001* At least once a week 0.14 (0.10–0.18) < 0.001* 0.84 (0.80–0.88) < 0.001* Almost every day 0.19 (0.15–0.23) < 0.001* 0.86 (0.84–0.88) < 0.001* Wealth quintile Barrow et al. Applied Cancer Research (2020) 40:8 Page 11 of 13 Table 3 Marginal predictive models of the factors associated with awareness of cervical cancer among women of reproductive age in Benin and Zimbabwe, sub-Saharan Africa (Continued) Variable Benin Zimbabwe Marginal effects (95%CI) P Marginal effects OR (95%CI) P Poorest 0.09 (0.07–0.11) < 0.001* 0.76 (0.74–0.78) < 0.001* Poorer 0.08 (0.06–0.10) < 0.001* 0.78 (0.76–0.81) < 0.001* Middle 0.10 (0.08–0.12) < 0.001* 0.80 (0.77–0.81) < 0.001* Richer 0.10 (0.08–0.11) < 0.001* 0.81 (0.79–0.83) < 0.001* Richest 0.11 (0.09–0.12) < 0.001* 0.83 (0.80–0.85) < 0.001* Marital status Never in union 0.11 (0.09–0.12) < 0.001* 0.73 (0.71–0.75) < 0.001* Currently in union/living with a man 0.10 (0.09–0.11) < 0.001* 0.82 (0.81–0.83) < 0.001* Formerly in union/lived with a man 0.11 (0.08–0.14) < 0.001* 0.82 (0.79–0.84) < 0.001* Occupation Not working 0.08 (0.07–0.10) < 0.001* 0.79 (0.78–0.80) < 0.001* Professional/technical/managerial 0.13 (0.10–0.16) < 0.001* 0.88 (0.83–0.93) < 0.001* Sales 0.11 (0.10–0.12) < 0.001* 0.81 (0.79–0.83) < 0.001* Agricultural 0.06 (0.04–0.07) < 0.001* 0.80 (0.77–0.82) < 0.001* Services 0.13 (0.11–0.15) < 0.001* 0.82 (0.79–0.85) < 0.001* Skilled manual 0.08 (0.06–0.10) < 0.001* 0.77 (0.72–0.83) < 0.001* Geographical region 1 0.08 (0.05–0.10) < 0.001* 0.79 (0.76–0.81) < 0.001* 2 0.13 (0.10–017) < 0.001* 0.85 (0.83–0.87) < 0.001* 3 0.10 (0.08–0.12) < 0.001* 0.83 (0.80–0.85) < 0.001* 4 0.02 (0.01–0.03) 0.001* 0.84 (0.82–0.86) < 0.001* 5 0.15 (0.12–0.18) < 0.001* 0.74 (0.72–0.77) < 0.001* 6 0.13 (0.10–0.16) < 0.001* 0.71 (0.68–0.74) < 0.001* 7 0.09 (0.06–0.12) < 0.001* 0.78 (0.75–0.80) < 0.001* 8 0.13 (0.10–0.15) < 0.001* 0.78 (0.75–0.80) < 0.001* 9 0.11 (0.08–0.13) < 0.001* 0.85 (0.82–0.87) < 0.001* 10 0.06 (0.05–0.08) < 0.001* 0.77 (0.74–0.81) < 0.001* 11 0.05 (0.03–0.08) < 0.001* 12 0.11 (0.09–0.13) < 0.001* Benin: 1 = Alibori, 2 = Atacora, 3 = Atlantic, 4 = Borgou, 5 = Collines, 6 = Couffo, 7 = Donga, 8 = Littoral, 9 = Mono, 10 = Oueme, 11 = Plateau & 12 = Zou. Zimbabwe: 1 = Manicaland, 2 = Manicaland Central, 3 = Manicaland East, 4 = Manicaland West, 5 = Manicaland North, 6 = Manicaland South, 7 = Midlands, 8 = Masvingo, 9 = Harare & 10 = Bulawayo. *Significant at p < 0.05 link between a disease and the possible prevention and Zimbabwe is reportedly high, centralized in urban set- control strategies. tings, competing priorities, with limited resources con- The findings from both countries (Benin and fronting their healthcare system; there is a relatively Zimbabwe) showed that the disparities in terms of marginal difference in the awareness of women on cer- women’s awareness of cervical cancer on the basis of age vical cancer through the country’s establishment of a groups and across regions. The awareness level of policy framework to drive this agenda [37]. women on cervical cancer differs in different geograph- Furthermore, awareness of cervical cancer was also as- ical regions of Benin republic [34]. Previous studies re- sociated with women’s age, educational level, household ported that lack of awareness on cervical cancer was wealth quintile, religious belief, marital status, occupa- associated with poor cervical cancer screening practices tion and geographical region. Women who are engaged in third-world countries [4, 24, 35, 36]. Though the cost in professional, technical and managerial jobs have the of cervical cancer services including its information in capacity to understand various health information from Barrow et al. Applied Cancer Research (2020) 40:8 Page 12 of 13 different media platforms which could be attributed to Conclusion the improved odds in awareness of cervical cancer. Such There were disparities and potential barriers to the women could interact with different electronic gadgets awareness levels on cervical cancer in Benin and such as android phones, computers, internet and so Zimbabwe. The study revealed that socio-demographical forth; which will avail them the opportunity to have in- factors including geographical location and selected eco- creased awareness about cervical cancer. The same logic nomic factors greatly explained the unequal coverage of is applicable to women that are rich as compared with women awareness on cervical cancer in both countries. poor women. The differentials in the awareness level be- Overall, multi-sectoral approaches are recommended to tween Muslim women as compared to Christians could address all the multifaceted factors with a view to im- be attributed to the low level of education and cultural proving people’s awareness level on cervical cancer in conservativeness among the Muslim folks. These could resource-constrained settings. further affect their utilization of screening services in- Acknowledgements cluding information regarding cervical cancer. Women The authors appreciate the MEASURE DHS project for the approval and that are currently married have continual and engaged access to the original data. visits to health facilities to access healthcare services Authors’ contributions which include those related to cervical cancer screening ME conceived and designed the study, performed data analysis and wrote and care. These factors were also examined in a previous the results, reviewed the literature, wrote the discussion of the findings. All authors contributed in the review of literature, the discussion of the findings, study [26]. These results suggest that an increase in critically reviewed the manuscript for its intellectual content. ME had the women’s educational level is effective in influencing responsibility to submit the manuscript. All authors read and approved the awareness about diseases including cervical cancer. The final manuscript. findings could also suggest that as women’s educational Funding level increases, they are often more empowered with in- This research received no grant from any funding agency in the public, formation and enlightened to understand more of their commercial or not-for-profit sectors. health issues including cervical cancer risk factors and Availability of data and materials prevention approaches [29, 38]. Data for this study were sourced from Demographic and Health surveys The study revealed the influence of age on the aware- (DHS) and available here: http://dhsprogram.com/data/available-datasets.cfm. ness level of cervical cancer in both settings. As women Ethics approval and consent to participate aged, they have the potential of increased awareness of Ethics approval for this study was not required since the data is secondary various diseases that can affect women including cervical and is available in the public domain. More details regarding DHS data and ethical standards are available at: http://dhsprogram.com/data/available- cancer which is consistent with the findings from the datasets.cfm study by Mitiku & Tefera [16] and a study in Nigeria that reported the influence of age on awareness of cervical can- Consent for publication Demographic and Health Survey is a de-identified open-source dataset. cer [39]as well asinZimbabwe [37]. This can be attrib- Therefore, the requirement of consent for publication is not applicable. uted to their number of parity which includes antenatal care services where they have interactions with healthcare Competing interests workers including health education sessions on maternal The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential health and risk issues with dysfunctional national cervical conflict of interest. cancer screening programme as well as the limited avail- ability of screening centres [40]. Our results also were in Author details Department of Public & Environmental Health, School of Medicine & Allied agreement with a similar study in Zimbabwe, which Health Sciences, University of The Gambia, Kanifing, The Gambia. Project showed that knowledge/awareness of cervical cancer was Management Unit, Management Sciences for Health, Abuja, Nigeria. associated with having at least secondary education [41]. Department of Community Health, Center of Excellence in Reproductive Health Innovation (CERHI), College of Medical Sciences, University of Benin, Benin City, Nigeria. Department of Epidemiology and Medical Statistics, Strengths and limitations Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, The strength of this study is the use of current na- Nigeria. tionally representative datasets to measure prevalence Received: 25 December 2019 Accepted: 6 October 2020 and determinants of awareness cervical cancer in Benin and Zimbabwe. The findings make plausible References comparison and are generalizable to women of repro- 1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer ductive age in both countries. However, the study uti- statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide lized cross-sectional data, hence, only associations and for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. 2. UNAIDS. It’s time to make Cervical Cancer history. UNAIDS Feature story. 04 no causal relationships are established. The unavail- February 2019. 2019. ability of endogenous variables was another limitation 3. Bruni L, Albero G, Serrano B, Mena M, Gómez D, Muñoz J, Bosch FX de SS. in the use of secondary data. ICO/IARC Information Centre on HPV and Cancer (HPV Information Centre). Barrow et al. Applied Cancer Research (2020) 40:8 Page 13 of 13 Human Papillomavirus and Related Diseases in Benin. Summary Report 17 28. Naik DD, Donta B, Nair S, Mali BN. Awareness of sexually transmitted June 2019. 2019;(June). infections and cervical cancer among women in urban slums of Mumbai, 4. World Health Organization (WHO). Comprehensive Cervical Cancer Control; Maharashtra, India. Int J Community Med Public Health. 2017;4(2):400. A guide to essential practice 2 edition. 29. Olubodun T, Odukoya OO, Balogun MR. Knowledge, attitude and practice of Httpswhointreproductivehealthtopicscancerhpv-Vaccininationen. 2014; 2nd cervical cancer prevention, among women residing in an urban slum in Edition (December). Lagos, South West, Nigeria. Pan Afr Med J. 2019;32 [cited 2019 Oct 26]. Available from: http://www.panafrican-med-journal.com/content/ 5. Rosa W. Transforming Our World: The 2030 Agenda for Sustainable article/32/130/full/. Development. In: A New Era in Global Health. New York: Springer 30. Dutta MJ. Health information processing from television: the role of health Publishing Company; 2017. [cited 2019 Feb 14]. Available from: http:// orientation. Health Commun. 2007;21(1):1–9. connect.springerpub.com/lookup/doi/10.1891/9780826190123.ap02. 31. Dutta-Bergman MJ. Primary sources of health information: comparisons in 6. Ntekim A. Cervical Cancer in sub Sahara Africa, topics on cervical cancer the domain of health attitudes, health cognitions, and health behaviors. with an advoocacy for prevention. Dr R Rajamanickam Ed; 2012. p. 51–74. Health Commun. 2004;16(3):273–88. 7. Chin’ombe N, Sebata NL, Ruhanya V, Matarira HT. Human papillomavirus 32. Schwitzer G, Mudur G, Henry D, Wilson A, Goozner M, Simbra M, et al. What genotypes in cervical cancer and vaccination challenges in Zimbabwe. are the roles and responsibilities of the media in disseminating health Infect Agent Cancer. 2014;9:16–9. information? PLoS Med. 2005;2(7):8. 8. Globocan. Zimbabwe Source: Globocan 2018. The global cancer 33. Moynihan R, Bero L, Ross-Degnan D, Henry D, Lee K, Watkins J, et al. observatory. All Right Reserved-May, 2019. 2019. Coverage by the news media of the benefits and risks of medications. N 9. Bruni L, Barrionuevo-Rosas L, Alberto G, Serrano B, Valencia S, Brotons M, Engl J Med. 2000;342(22):1645–50. Mena M, Cosano R, Munoz J, Bosch FX, de Sanjose S CX. Human 34. Piras F, Piga M, De Montis A, Zannou AR, Minerba L, Perra MT, et al. Papillomavirus and Related Diseases Report. ICO HPV Inf Cent. 2015;. Prevalence of human papillomavirus infection in women in Benin. West 10. Tapera O, Kadzatsa W, Nyakabau AM, Mavhu W, Dreyer G, Sjh H. Africa Virol J. 2011;8(1):514. Sociodemographic inequities in cervical cancer screening , treatment and 35. Finocchario-Kessler S, Wexler C, Maloba M, Mabachi N, Ndikum-Moffor F, care amongst women aged at least 25 years : evidence from surveys in Bukusi E. Cervical cancer prevention and treatment research in Africa: a Harare , Zimbabwe. BMC Public Health. 2019;19:1–12. systematic review from a public health perspective. BMC Womens Health. 11. Globocan. Benin Source: Globocan 2018. The Global Cancer Observatory. All 2016;16(1):29. Right Reserved-May, 2019. 36. Drolet M, Bénard É, Boily M-C, Ali H, Baandrup L, Bauer H, et al. Population- 12. Corsi DJ, Neuman M, Finlay JE, Subramanian S. Demographic and health level impact and herd effects following human papillomavirus vaccination surveys: a profile. Int J Epidemiol. 2012;41(6):1602–13. programmes: a systematic review and meta-analysis. Lancet Infect Dis. 2015; 13. Short Fabic M, Choi Y, Bird S. A systematic review of demographic and 15(5):565–80. health surveys: data availability and utilization for research. Bull World 37. Tapera O, Dreyer G, Kadzatsa W, Nyakabau AM, Stray-Pedersen B, Hendricks SJH. Health Organ. 2012;90(8):604–12. Determinants of access and utilization of cervical cancer treatment and palliative 14. Republic of Benin - Country Profile. Benin - Country Profile - Nations Online care services in Harare, Zimbabwe. BMC Public Health. 2019;19(1):1018. Project. [cited 2019 Dec 13]. Available from: http://www.nationsonline.org/ 38. Tapera O, Dreyer G, Kadzatsa W, Nyakabau AM, Stray-Pedersen B, Sjh H. oneworld/benin.htm. Cervical cancer knowledge, attitudes, beliefs and practices of women aged 15. Ploch L. Zimbabwe: Background - congressional research service; 2010. p. 52. at least 25 years in Harare, Zimbabwe. BMC Womens Health. 2019;19(1):91. 16. Mitiku I, Tefera F. Knowledge about cervical cancer and associated factors 39. Ayinde OA, Ogunbode OO, Adebayo OJ. Determinants of cervical cancer among 15–49 year old women in Dessie town, Northeast Ethiopia. knowledge and the utilisation of screening among a Nigerian female Paraskevis D, editor. PLOS ONE. 2016;11(9):e0163136. population. Trop J Obstet Gynaecol. 2006;22(1):21–4. 17. Ayinde OA, Ogunbode OO, Adebayo OJ. Determinants of cervical cancer 40. Ziba F, Baffoe P, Dapare P, Shittu S, Antuamwine B. Awareness and knowledge and the utilisation of screening among a Nigerian female knowledge level of cervical cancer among women of reproductive age in population. Trop J Obstet Gynaecol. 2005;22(1):21–24–24. Bolgatanga municipality. J Med Biomed Sci. 2015;4(2):1. 18. Moshi FV, Vandervort EB, Kibusi SM. Cervical cancer awareness among 41. Mutambara J, Mutandwa P, Mahapa M, Chirasha V, Nkiwane S, women in Tanzania: an analysis of data from the 2011-12 Tanzania HIV and Shangahaidonhi T. Knowledge, attitudes and practices of cervical cancer malaria indicators survey. Int J Chronic Dis. 2018;7. screening among women who attend traditional churches in Zimbabwe. J 19. Rutstein SO, Staveteig S. Making the demographic and health surveys Cancer Res Pract. 2017;4(2):53–8. wealth index comparable; 2014. p. 43. 20. Hruschka DJ, Gerkey D, Hadley C. Estimating the absolute wealth of households. Bull World Health Organ. 2015;93(7):483–90. Publisher’sNote 21. Midi H, Sarkar SK, Rana S. Collinearity diagnostics of binary logistic Springer Nature remains neutral with regard to jurisdictional claims in regression model. J Interdiscip Math. 2010;13(3):253–67. published maps and institutional affiliations. 22. Williams R. Using the margins command to estimate and interpret adjusted predictions and marginal effects. Stata J Promot Commun Stat Stata. 2012; 12(2):308–31. 23. Perlman S, Wamai RG, Bain PA, Welty T, Welty E, Ogembo JG. Knowledge and awareness of HPV vaccine and acceptability to vaccinate in Sub- Saharan Africa: a systematic review. Hozbor DF, editor. PLoS ONE. 2014;9(3): e90912. 24. World Health Organization, editor. Cervical cancer screening in developing countries: report of a WHO consultation. Geneva: World Health Organization; 2002. p. 75. 25. Balogun MR, Odukoya OO, Oyediran M, Ujomu P. Cervical cancer awareness and preventive practices: a challenge for female urban slum dwellers in Lagos, Nigeria. Afr J Reprod Health. 2012;16(1):75–82. 26. Aweke YH, Ayanto SY, Ersado TL. Knowledge, attitude and practice for cervical cancer prevention and control among women of childbearing age in Hossana Town, Hadiya zone, Southern Ethiopia: Community-based cross- sectional study. Robboy SJ, editor. PLOS ONE. 2017;12(7):e0181415. 27. Bathija G, Mallesh S, Gajula M. A study on awareness of cervical cancer among women of reproductive age group in urban slums of old Hubli, Karnataka, India. Int J Community Med Public Health. 2016:2579–83.

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Applied Cancer Research – Springer Journals

Published: Oct 13, 2020

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