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Oncology
Original research
Towards a cervical cancer-free future: women’s healthcare decision making and cervical cancer screening uptake in sub-Saharan Africa
  1. Joshua Okyere1,2,
  2. Richard Gyan Aboagye3,
  3. Abdul-Aziz Seidu4,5,
  4. Bernard Yeboah-Asiamah Asare6,7,
  5. Bupe Mwamba8,
  6. Bright Opoku Ahinkorah9
  1. 1Department of Population and Health, University of Cape Coast, Cape Coast, Ghana
  2. 2Department of Nursing, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
  3. 3Department of Family and Community Health, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Ho, Ghana
  4. 4College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia
  5. 5Centre for Gender and Advocacy, Takoradi Technical University, Takoradi, Western Region, Ghana
  6. 6Health Psychology, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
  7. 7Curtin School of Population Health, Curtin University, Perth, WA, Australia
  8. 8Centre for Midwifery, Family and Child Health, University of Technology Sydney, Sydney, New South Wales, Australia
  9. 9School of Public Health, Faculty of Health, University of Technology Sydney, Sydney, New South Wales, Australia
  1. Correspondence to Joshua Okyere; joshuaokyere54{at}gmail.com

Abstract

Objective We investigated the association between women’s healthcare decision making and cervical cancer screening uptake in sub-Saharan Africa.

Design Secondary data from the Demographic and Health Surveys of six countries in sub-Saharan Africa were used. We employed multilevel binary logistic regression modelling.

Setting Sub-Saharan Africa.

Participants Women aged 15–49 years in Benin (n=5282), Côte d’Ivoire (n=1925), Cameroon (n=7558), Kenya (n=6696), Namibia (n=1990) and Zimbabwe (n=5006).

Primary outcome measures Cervical cancer screening uptake.

Results The overall prevalence of cervical cancer screening across the six sub-Saharan African countries was 13.4%. Compared with women whose healthcare decisions were made solely by husbands/partners/someone else, the likelihood of cervical cancer screening uptake was significantly higher among women who took healthcare decisions in consultation with their husbands/partners (aOR=1.38; 95% CI 1.19 to 1.59), but highest among those who made healthcare decisions alone (aOR=1.66; 95% CI 1.44 to 1.91). Women aged between 40 and 45 years (aOR=5.18; 95% CI 3.15 to 8.52), those with higher education (aOR=2.13; 95% CI 1.57 to 2.88), those who had ever heard of cervical cancer (aOR=32.74; 95% CI 20.02 to 53.55), read newspaper or magazine at least once a week (aOR=2.11; 95% CI 1.83 to 2.44), listened to the radio at least once a week (aOR=1.35; 95% CI1.18 to 1.52) and those in households with richest wealth index (aOR=1.55; 95% CI 1.20 to 2.00) had significantly higher odds of screening for cervical cancer compared to their counterparts.

Conclusion Women who are able to make autonomous healthcare decisions and those who practice shared decision making are more likely to uptake cervical cancer screening. Therefore, policy interventions should focus on empowering women to be able to take autonomous healthcare decisions or shared decision making while targeting subpopulations (ie, multiparous and rural-dwelling women, as well as those in other religious affiliations aside from Christianity) that are less likely to uptake cervical cancer screening. Also, the radio and print media could be leveraged in raising awareness about cervical cancer screening to accelerate cervical cancer screening uptake in sub-Saharan Africa.

  • Cancer pain
  • Public health
  • Quality in health care

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. The dataset is freely accessible via this link: https://dhsprogram.com/data/available-datasets.cfm.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjopen-2021-058026

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    Strengths and limitations of this study

    • The use of nationally representative data enhances the generalisability of the findings.

    • The use of multilevel binary logistic regression enhanced the accuracy of the findings.

    • Causal inference cannot be established between women’s decision-making autonomy and cervical cancer screening uptake due to the cross-sectional nature of the Demographic and Health Surveys datasets.

    • This study analyses self-report data that are subject to recall and social desirability biases.

    • Residual confounders such as cultural norms could not be accounted for due to the use of secondary datasets that did not have variables on these factors.

    Introduction

    Cervical cancer is ranked as the fourth most common cancer after breast cancer (2.1 million cases), colorectal cancer (0.8 million) and lung cancer (0.7 million), and it is the leading cause of cancer deaths in women worldwide.1 2 In 2020, the GLOBOCAN estimated 604 127 new cases of cervical cancer and 341 831 deaths worldwide, with about 90% of deaths occurring in low-and middleincome -income countries. Sub-Saharan Africa (SSA) recorded the highest incidence and mortality.2–4 The risk factors for cervical cancer have been indicated as infection with high-risk human papillomavirus (HPV), smoking, increased number of childbirths and HIV infection with infection with high-risk HPV accounting for about 99% of all cervical cancer cases.4–6

    Cervical cancer could be prevented and/or cured through highly effective primary HPV vaccination and secondary prevention measures of screening combined with treatment.2–6 High-performing screening test allows for the early detection and prompt treatment of precancer lesions and is regarded as a significant measure of safeguarding women who have not been vaccinated against the ‘oncogenic subtypes’, which existing vaccines are not effective for.2–7 Early screening with prompt treatment is indicated to be an economical way to prevent cervical cancer.7 The WHO has recommended cervical cancer screening to begin at the age of 30 years for all sexually active women and beginning at an earlier age for all sexually active and HIV positive women.7 There are currently in existence a number of screening methods including cytology or Papanicolaou (Pap) smear testing, visual inspection using acetic acid or Lugol’s iodine and HPV test.8 The most common in low-and middle-income countries is Pap smear. However, HPV detection has proven its superiority to cervical cytology in primary screening for prevention of cervical cancer,9 10 and more and more countries are now changing towards molecular HPV testing. WHO has recommended that women aged 30–49 years be screened with validated tests that detect HPV in cervical or vaginal samples.11 These tests are more sensitive than visual inspection with acetic acid (VIA) or Pap smears, allow for longer screening intervals11 and can be done with self-collected vaginal samples.12 13

    Cervical cancer screening programmes and their uptake are limited in low-income and middle-income countries, particularly in SSA.14–16 The prevalence of screening for cervical cancer in the lifetime of women in low-and middle-income countries is indicated to be 43.6%, with countries from the sub-Saharan African region recording the lowest prevalence (country-level median, 16.9%; range 0.9%–50.8%) compared with the prevalence of more than 60% reported in high income nations.2–14

    In SSA, several factors including increasing age, higher education, higher household wealth index and being employed have been documented to be associated with increased uptake of screening for cervical cancer.16–21 It has also been documented that staying in rural areas, low level of awareness of services, cost of accessing services and the distance to health facility reduces the uptake of cervical cancer screening.16–19 Studies have identified factors including being informed about services and/or suggested by a health personnel, knowing somebody to have screened and receiving support from partners to be associated with increase uptake of cervical cancer screening.20 22 A recent study in Eswatini has also revealed that women prefer to seek cervical cancer screening in health facilities and from nurses who are not from their locality due to the fear of judgement and gossips in cervical cancer screening facilities.23

    Beyond these issues, the independence of women’s decision making associated with gender roles have been highlighted to influence screening for cervical cancer.24 In sub-Saharan African countries, gender norms are indicated to influence the access and utilisation of reproductive health services among women, particularly among women living in rural areas.25 26 Cultural practices and gender norms influence the movement of women and their household decision making, including the decision to use healthcare services.27 28 Women’s healthcare decision making may influence the uptake of cervical cancer screening. For instance, a study has found women with an autonomy of household decision-making power to be more likely to use maternal healthcare services.21 Another study has also found women’s own healthcare decision-making with the support from their partners and others to significantly predict the utilisation of reproductive healthcare services.29

    Previous studies have largely focused on examining the effects of individual-level and health facility-level factors on the uptake of cervical cance screening, with limited studies focusing on the relationship between women’s decision-making autonomy and cervical cancer screening.8 This study sought to examine the influence of women healthcare decision making on the uptake of cervical cancer screening in SSA. This comprehensive analysis across several sub-Saharan African countries could help clarify the role of women’s healthcare decision making in cervical cancer screening uptake in the region.

    Connell’s Theory of Gender and Power guided our investigation on the association between women’s healthcare decision-making capacity and cervical cancer screening uptake. The Theory of Gender and Power postulates that men and women’s power dynamics are displayed in three key structures: sexual division of labour, sexual division of power and affective attachments and social norms.21 30 These structures explain the gendered relationships that exist between men and women and explain how power and role dynamics shift from males to females. In this gendered relationships, males are considered as more dominant and females subordinate.30 Hence, a woman’s decision go for cervical cancer screening could be influenced by her and her partner’s equality, cultural expectations and conventions on who makes healthcare decisions. The decision is also influenced by whether or not there is male dominance in the home. Although the three structures differ, they overlap and hence cannot be considered separately.30 These patterns are also influenced by social mechanisms at the societal and institutional levels, which include individual sociodemographic factors.31

    Methods

    Data source and study design

    We analysed cross-sectional data from the Demographic and Health Surveys (DHS) of six countries in SSA. Only these six countries had data on cervical cancer screening between 2011 and 2020. The DHS is a nationally representative and comparative survey conducted periodically in over 85 low-income and middle-income countries to collect data on health and social indicators such as cervical cancer screening and women’s healthcare decision-making capacity.32 The main purpose of the DHS Program is to improve the collection, analysis and distribution of demographic, health and nutrition data, as well as to make these data more usable for planning, policymaking and programme management. The study population in the DHS consisted of men, women and children. During the data collection, only the respondents who were either permanent residents of selected households or visitors who stayed the night before the survey were included. Respondents who were living in nomadic and institutional populations such as hotels, barracks and prisons were excluded from the survey. The survey was conducted using a descriptive cross-sectional design. Structured questionnaires were used to obtain data from the respondents using validated and pretested structured questions. A two-stage cluster sampling technique was used to conduct the survey. To begin, a stratified sample of enumeration areas (EAs) was selected using probability proportional to size, in which a sample of a predetermined number of EAs is selected independently in each stratum using probability proportional to the EA’s size measure. In the designated EAs, a listing technique was used to ensure that all dwellings/households were listed. Second, equal probability systematic sampling was used to select households in the designated EAs. The data collection took place at the residence of the respondents. In this study, a total of 28 457 women of reproductive age were included in the final analysis (table 1). We relied on the ‘Strengthening the Reporting of Observational Studies in Epidemiology’ statement in writing the manuscript.33 The dataset is freely accessible via this link: https://dhsprogram.com/data/available-datasets.cfm.

    View this table:
    Table 1

    Description of sample

    Variables

    Outcome variable

    Cervical cancer screening was the outcome variable in the study. To derive this variable, the respondents were asked the question ‘Have you ever been tested or examined for cervical cancer?’. The response options were 0=no, 1=yes and 8=don’t know. For this study, those that responded ‘don’t know’ were dropped as the interest was on those who provided definite responses. The utilisation and coding were informed by literature.18

    Key explanatory variable

    The main explanatory variable was healthcare decision making. This variable was assessed using the question ‘Who usually makes decisions about healthcare for yourself: you, your (husband/partner), you and your (husband/partner) jointly, or someone else?’. The response categories were 1=respondent alone; 2=respondent and the husband/partner; 3=husband/partner alone; 4=someone else; and 5=others. We recoded these responses into 0=husband/partner/someone else/ other; 1=respondent alone; and 2=respondent and husband/partner. Our recoding was informed by a previous study that used the DHS datasets.34

    Covariates

    We included 12 variables as covariates in this study. These variables were grouped into individual-level variables (women’s age, marital status, educational level, current working status, religion, parity, heard of cervical cancer, frequency of watching television, frequency of listening to radio and frequency of reading newspapers/magazines) and contextual-level variables (wealth index and place of residence). We maintained and used the existing coding for women’s age, educational level, current working status, heard of cervical cancer, wealth index and place of residence as found in the DHS datasets. Marital status was recoded into ‘married’ and ‘cohabiting’. Religious affiliation was recoded into ‘Christianity’, ‘Islamic’, ‘African Traditional’, ‘no religion’ and ‘others’. Parity was recoded into ‘zero births’, ‘one birth’, ‘two births’, ‘three births’ and ‘four or more births’. The frequencies of listening to radio, watching television and reading newspaper/magazine were recoded into ‘not at all’, ‘less than once a week’ and ‘at least one a week’. All the covariates were selected based on their significant association from literature,16–18 35 as well as their availability in the DHS datasets.

    Conceptual framework

    The Health Care Services Utilisation Model by Anderson and Newman35 guided the selection of the explanatory variable and the covariates. The model focuses on the conditions that either promote or hinder the utilisation of healthcare services.36 The main constructs of the model are predisposing factors, enabling factors and need for care factors.

    The predisposing factors refer to the demographic, social structure and health belief characteristics.35,36 In this study, the predisposing factors were healthcare decision making, maternal age, marital status, educational level, current working status, religion, exposure to media and parity. Enabling factors are the resources or means that are available to an individual to seek healthcare services.36 In this study, the enabling factors included place of residence and wealth index.

    Need for care factors refer to an individual’s perception of his or her own general health and functional condition, as well as how familiar they are with the signs and symptoms of ill health, agony and concerns about their health.29 The need for care factors are influenced by the predisposing and enabling factors. In this study, the need for care factor was knowledge about cervical cancer (figure 1).

    Figure 1
    Figure 1

    Conceptual framework (the Health Care Services Utilisation Model by Anderson and Newman35).

    Patient and public involvement statement

    Study participants or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.

    Statistical analyses

    We performed the analysis using Stata software V.16.0 (Stata Corporation). In each country’s dataset, we first selected the variables of interest. As recommended by the MEASURE DHS, we weighted each of the countries dataset employing the command ‘gen wt=v005/1000000’ and subsequently adjusted for the strata using the Stata command ‘svyset v021 [pw=wt], strata(stratum)’. Afterwards, the dataset from the six countries were appended as one dataset. Later, we cleaned the dataset by recoding and dropping missing observations from all the variables of interest. A sample size of 28 457 was arrived at after dropping the missing observations. Furthermore, percentages were used to present the results of the prevalence of cervical cancer screening uptake (table 2) and healthcare decision making (figure 2) . We performed a χ2 test of independence to determine the association between the outcome variable and the key explanatory variable and covariates (table 3). Cross-tabulations were also used to show the distribution of cervical cancer screening across the key explanatory variable and the covariates (table 3). We used a multilevel binary logistic regression to examine the association between healthcare decision making and cervical cancer screening uptake. Four different models were built to determine this association. The first model (model O) was fitted to include only cervical cancer screening uptake attributed to the clustering of the primary sampling units (PSUs). Model I was fitted to include the key explanatory variable and the individual-level variables. Model II contained only the contextual-level variables, while the last model (model III) was fitted to include the key explanatory variable and all the covariates. The results of the regression analyses were presented using adjusted ORs with their respective 95% confidence interval (CI). The level of significance was set at p<0.05 in the χ2 test and regression analysis. We used the Stata command ‘melogit’ in building all four models. Model fitness was checked using Akaike’s information criterion.

    Figure 2
    Figure 2

    Level of women’s healthcare decision making.

    View this table:
    Table 2

    Prevalence of cervical cancer screening

    View this table:
    Table 3

    Bivariate analysis of healthcare decision making and cervical cancer screening

    Ethical consideration

    Ethical approval was not sought for this study due to the public availability of the DHS dataset. We obtained permission to use the dataset for publication from the MEASURE DHS on registration. The ethical guidelines regarding the analysis of secondary datasets for publication were followed. Detailed information about the data and ethical standards can be found at http://goo.gl/ny8T6X.

    Results

    Prevalence of cervical cancer screening

    The overall prevalence of cervical cancer screening across the six countries was 13.4%. Namibia had the highest prevalence of cervical cancer screening (51.6%), whereas Benin reported the lowest prevalence (0.5%) of cervical cancer screening (table 2).

    Women’s healthcare decision making

    In figure 2, the proportions of women’s healthcare decision making across the selected countries in SSA was shown. The results indicate that overall, 40% of women made decisions concerning their healthcare in consultation with their husbands or partners, while 33.7% reported that their healthcare decisions were made solely by their husbands/partners/someone else/others. Only 24.3% of the women in this study autonomously made their healthcare decisions. At the intercountry level, the results showed that Cote d’Ivoire (55.6%) had the highest proportion of women reporting that their healthcare decision making was done solely by their husbands partners/someone else/others. Namibia on the other hand reported the lowest proportion of women who reported that their healthcare decision making was done solely by their husbands/ partners/someone else/others (9.5%). At the same time, Namibia reported the highest proportion of women who took healthcare decisions alone (48%).

    Bivariate analysis of healthcare decision making and cervical cancer screening uptake

    Table 3 shows the results of the bivariate analysis on the healthcare decision making and the cervical cancer screening uptake, as well as across the covariates. The results showed that healthcare decision making had significant association with cervical cancer screening uptake at 95% CI. Women who made healthcare decisions alone reported the highest prevalence of cervical cancer screening (22.2%), while those whose husbands/partner/someone else/ others took the decisions reported the lowest prevalence of cervical cancer screening uptake. In terms of the covariates, the findings indicate that all of the covariates (ie, age, marital status, educational level, current working status, religion, parity, heard of cervical cancer, exposure to the media (frequency of watching television, listening to radio, reading of newspapers/magazines), wealth index and place of residence) were significantly associated with the prevalence of cervical cancer screening uptake.

    Association between healthcare decision making and cervical cancer screening

    Fixed effects results

    Table 4 presents the findings from the multilevel logistic regression. The final model (model III) is the complete model and shows the association between healthcare decision making and cervical cancer screening uptake in SSA. The results indicate that compared with women’s healthcare decision making made solely by husbands/partners/someone else/others, the likelihood of cervical cancer screening uptake was significantly higher among women who took healthcare decisions in consultation with their husbands or partners (aOR=1.38; 95% CI 1.19 to 1.59), but highest among those who made healthcare decisions alone (aOR=1.66; 95% CI 1.44 to 1.91).

    View this table:
    Table 4

    Fixed and random effect analyses of the association between healthcare decision making and cervical cancer screening

    For the covariates, the results show that the likelihood of cervical cancer screening uptake significantly increased with age with those aged between 40 and 45 years being most likely to get screened (aOR 5.18; 95% CI 3.15 to 8.52) as compared with those aged between 15 and 19 years. Compared with women with no formal education, those with primary (aOR=1.47; 95% CI 1.14 to 1.90), secondary (aOR=1.51; 95% CI 1.18 to 1.95) or higher education (aOR=2.13; 95% CI 1.57 to 2.88) had higher odds of undergoing cervical cancer screening. Also, awareness of cervical cancer (aOR=32.74; 95% CI 20.02 to 53.55), reading newspaper or magazine at least once a week (aOR=2.11; 95% CI 1.83 to 2.44), listening to the radio at least once a week (aOR=1.35; 95% CI 1.18 to 1.52) and belonging to the richest wealth index (aOR=1.55; 95% CI 1.20 to 2.00) were associated significantly higher odds of screening for cervical cancer. Cohabiting women (aOR=0.79; 95% CI 0.69 to 0.91), those with four or more parities (aOR=0.70; 95% CI 0.55 to 0.89) and rural-dwelling women (aOR=0.81; 95% CI 0.69 to 0.95) reported significantly lower odds of cervical cancer screening uptake. Compared with women who were Christians, women of all other religious categories reported lower odds of screening for cervical cancer.

    Random effects results

    Model III was considered the model of best fit for predicting the association between women’s healthcare decision making and cervical cancer screening. This model explained 7% of the observed variations (ICC=0.07). The percentage of variance explained at the empty model was 0.13, which decreased to 0.08 in model I but increased to 0.12 in model II (Table 4).

    Discussion

    In line with the Global Strategy to Accelerate the Elimination of cervical cancer, otherwise known as the 90-70-90 strategy,7 this study examined the influence of women’s health decision making on the uptake of cervical cancer screening in SSA. Overall, the prevalence of cervical cancer screening within the subregion was low (13.4%), which is lower compared with the pooled prevalence reported in a study conducted using five countries in SSA (19.0%)36 and a single study conducted in Kenya (18.2%).37 This low prevalence has significant implications on Africa’s capacity to achieve the Sustainable Development Goals, especially SDG 3 (targets 3.4, 3.7 and 3.8), as well as the ‘70’ component of the 90-70-90 strategy, which envisions that, by 2030, 70% of women should be screened by high-performance screening tests by age 35 years and another one at age 45 years.7 Intercountry comparison showed that Namibia had the highest prevalence of cervical cancer screening, while Benin reported the lowest prevalence. This finding is consistent with the results from a multicountry study involving SSA countries that reported the highest and lowest prevalence of cervical cancer screening in Namibia (45.9%) and Benin (0.7%), respectively.36 The observed high prevalence of cervical cancer screening in Namibia could be linked to the response by the Namibian government such as the introduction of VIA and cryotherapy to ‘Screen and Treat’ women, as well as the implementation of a national awareness and screening campaign in the country.38 Notwithstanding, the findings call for regional and national level strategies to increase awareness about the preventive and curative nature of cervical. When that is done, women within the sub region would be encouraged to take up cervical cancer screening.

    Our study revealed that women’s healthcare decision making significantly influenced the uptake of cervical cancer screening. The results indicate that women who take decisions concerning their healthcare on their own have the highest likelihood of undertaking cervical cancer screening as compared with those whose healthcare decision making was done by their husband/partner or someone else. It is therefore not surprising that Namibia, which reported the highest proportion of autonomous healthcare decision making in this study, also reported the highest prevalence of cervical cancer screening. This finding is in agreement with Connell’s Theory of Gender and Power, which explains that hegemonic masculinity practised at the household level serves as a barrier to health seeking among women.27 39 Our finding also aligns with those of Viens, Clouston and Messina that found that women who made decisions on their own tend to more likely undergo a cervical cancer screening.31 A plausible explanation for this finding could be that women whose healthcare decisions are determined by their husbands or partners often face high level of objections to get screened, primarily because they lack understanding about cervical cancer and the relevance of screening as a primary preventive measure.40 Also, in Africa, sociocultural practices and gender norms are critical in determining women’s decision and access to particularly reproductive health services.41 42 Consistent with other studies43 44 that have found a significant association between shared decision making and the likelihood of cervical cancer screening, our study showed that women who made healthcare decisions in consultation with their husbands or partners had higher odds of undertaking cervical cancer screening, although this likelihood is a bit lower when compared with women who autonomously make healthcare decisions.

    Consistent with studies conducted in Ethiopia45 and South Africa,46 our study found significant association between increasing age and the up-taking cervical cancer screening. From our findings, it is indicative that aged between 40 and 45 years were five times more likely to get screened as compared with those aged between 15 and 19 years. This aligns with a study in Cameroon that found women aged 45 years to be eight times as likely to be screened for cervical cancer compared with women of younger age.18 Plausibly, this age disparity in cervical cancer screening can be explained by the global screening recommendation that posits that the screening by high-performance should begin by age 35 years and another one at age 45 years.7 Another possible justification for the steadily increase in age and screening practice could be due to the fact that lesions that develop to cervical cancer take years.47 As such, the older a woman gets, the more likely they are at risk to develop cervical cancer. Hence, their decision to take up cervical cancer screening as they age.

    Besides the age differences in screening for cervical cancer, our study revealed that women with formal education had greater odds of getting screened as compared with their counterparts who had no formal education. The finding is similar with studies conducted in Cameroon18 and five SSA countries.36 Formal education is likely to expose women to cervical cancer and raise their awareness and knowledge about the relevance of taking up screening as a preventive measure. Related to this was our findings that having heard of cervical cancer is associated with higher likelihood of screening. This is consistent with previous studies,18 48 that have postulated that women’s awareness of the disease significantly influenced their decision to get screened. We argue that women who are aware of cervical cancer would be knowledgeable about its adverse effect on their physical and social health. They would also be knowledgeable about the fact that it is only through early screening that cervical cancer can be detected and treated. This implies that investing in national awareness and campaign programmes could significantly lead to better health-seeking behaviour.

    We also found that exposure to the media significantly influenced women’s uptake of cervical cancer screening. Importantly, women who read newspapers or magazine at least once a week, or listened to the radio at least once a week were two times and 1.35 times more likely to undertake cervical cancer screening, respectively. The result aligns with a related study conducted among SSA women.36 This implies that the radio and print media can be used as mediums for awareness creation campaigns about cervical cancer and the available preventive/treatment measures to accelerate cervical cancer screening uptake in SSA. Furthermore, belonging to the richest wealth index was associated with significantly higher odds of screening for cervical cancer as compared with women in the poorest wealth index. This finding is similar to evidence from Cameroon18 and SSA.36 The result highlights the imperativeness of improving the socioeconomic and livelihood status of women in SSA to engineer the necessary efforts to increase cervical cancer screening uptake.

    The present study also shows that rural-dwelling women had the least likelihood of taking cervical cancer screening. This is corroborated by Kangmennaang et al,37 who reported that women who lived in rural residents were less likely to seek cervical cancer screening as compared with those in the urban areas. Screening services such as HPV testing and Pap smear are often located in urban areas, thereby placing rural-dwelling women at a significant disadvantage with regards to cervical cancer screening.18 Moreover, previous studies have shown that rural areas often lack sufficient transportation networks that deter many women from seeking cervical cancer screening.36 49 It is also possible that women in rural areas lack access to sufficient information about the benefits, modalities and point of access to cervical cancer screening.22 Hence, women in rural settings often lack knowledge about the disease and would usually not see the value of getting screened even when they are free from signs and symptoms.

    Concerning the influence of parity, our findings that multiparous women have the least odds of cervical cancer screening uptake is incongruent with a related study in Nepal that found no association between parity and cervical cancer screening uptake.50 However, although the findings are in accordance with a study in Jamaica that found a strong association between parity and the uptake of cervical cancer screening, the direction of association differs.51 Ncube et al51 reported that multiparous women were more likely to be screened for cervical cancer. Probably, multiparous women perceive that they have had sufficient experience with child birth, which did not result in cervical cancer. Hence, they are not encouraged to get screened. This observation is a threat to the realisation of the SDG targets 3.4, 3.7 and 3.8. The findings underscore the need for health and birthing facilities to broaden educational messages provided to mothers. These messages should capture and emphasise cervical cancer screening for all women, especially multiparous women.

    Our study found a strong association between religion and the uptake of cervical cancer screening, mirroring a related study from Kenya,52 that reported lower likelihood of cervical cancer screening uptake among Muslims as compared with those who professed Christianity. A qualitative study found that Muslim women often resisted cervical cancer screening on the basis that it was incompatible with cultural and religious values.53 Another study also pointed out that Muslim women often perceived cervical cancer as a function of the will of God and therefore should not be interrupted.54 These aforementioned reasons could be the possible reasons for the lower likelihood of cervical cancer uptake among Muslim women in comparison with those who profess Christianity. Our findings underscore the importance of targeting Muslim women with more cervical cancer screening interventions.

    Practical implications

    The findings from this study give credence to the need for much interventions and strategies within the sub-Saharan African region that aim at enhancing women’s autonomy in decision making. This could be achieved by investing heavily in girl child and women’s education as well as improving the economic livelihoods of women. Also, the results from the present study underscore the importance of developing the cognition of husbands and partners about cervical cancer and the need for supporting the decision to screen by their wives. This will help to limit the likelihood of resistance on the part of husbands or partners. Our findings also highlight the essential role of designing and implementing culturally and religious sensitive interventions that promote cervical cancer screening uptake across the different religious affiliations of women in SSA. The support of governments and departments of health is urgently needed in ensuring the availability of screening services in rural settlements, communities and regions.

    Strengths and limitations

    Our study has some strengths that are noteworthy. The dataset used for this study was large and nationally representative and therefore makes our findings generalisable to the women population in the countries included in this study. However, a significant limitation of our study is the use of secondary data that used cross-sectional design. Hence, causality could not be established between women’s healthcare decision making and cervical cancer screening. Hence, the findings are limited to associations. There is also the possibility of reverse causality in terms of the association between women’s healthcare decision making and cervical cancer screening. We acknowledge that there is the possibility of social desirability and recall bias that could have affected the results.

    Conclusion

    We conclude that the prevalence of cervical cancer screening is low in SSA. Women who make healthcare decisions alone and those who practise shared decision making with their husbands/partners are more likely to uptake cervical cancer screening. Therefore, policy interventions should focus on empowering women to be able to take autonomous healthcare decisions or shared decision making while targeting subpopulations (ie, multiparous and rural-dwelling women, as well as those in other religious affiliations aside from Christianity) that are less likely to uptake cervical cancer screening. Also, the radio and print media could be leveraged in raising awareness about cervical cancer screening to accelerate cervical cancer screening uptake in SSA.

    Data availability statement

    All data relevant to the study are included in the article or uploaded as supplementary information. The dataset is freely accessible via this link: https://dhsprogram.com/data/available-datasets.cfm.

    Ethics statements

    Patient consent for publication

    Ethics approval

    Not applicable.

    Acknowledgments

    We acknowledge Measure Demographic and Health Survey (DHS) for providing the data.

    References

    1. ↵
      1. Arbyn M,
      2. Weiderpass E,
      3. Bruni L, et al
      . Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. Lancet Glob Health 2020;8:e191–203.doi:10.1016/S2214-109X(19)30482-6pmid:http://www.ncbi.nlm.nih.gov/pubmed/31812369
      OpenUrlCrossRefPubMed
    2. ↵
      1. Sung H,
      2. Ferlay J,
      3. Siegel RL, et al
      . Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021;71:209–49.doi:10.3322/caac.21660pmid:http://www.ncbi.nlm.nih.gov/pubmed/33538338
      OpenUrlCrossRefPubMed
    3. ↵
      1. Globocan U
      . New Global Cancer Data. [Internet]. Available: https://www.uicc.org/news/globocan-2020-new-global-cancer-data [Accessed 11 Aug 2021].
    4. ↵
      1. WHO
      . Health topics, 2021. Cervical Cancer. Available: https://www.who.int/health-topics/cervical-cancer#tab=tab_1 [Accessed 11 Aug 2021].
    5. ↵
      1. Stelzle D,
      2. Tanaka LF,
      3. Lee KK, et al
      . Estimates of the global burden of cervical cancer associated with HIV. Lancet Glob Health 2021;9:e161–9.doi:10.1016/S2214-109X(20)30459-9pmid:http://www.ncbi.nlm.nih.gov/pubmed/33212031
      OpenUrlPubMed
    6. ↵
      1. WHO
      . Fact sheets, 2020. Human papillomavirus (HPV) and cervical cancer. [Internet]. Available: https://www.who.int/news-room/fact-sheets/detail/human-papillomavirus-(hpv)-and-cervical-cancer [Accessed 11 Aug 2021].
    7. ↵
      1. World Health Organization
      . Global strategy to accelerate the elimination of cervical cancer as a public health problem. Available: https://www.who.int/publications/i/item/9789240014107
    8. ↵
      1. Tiruneh FN,
      2. Chuang K-Y,
      3. Ntenda PAM, et al
      . Individual-Level and community-level determinants of cervical cancer screening among Kenyan women: a multilevel analysis of a nationwide survey. BMC Womens Health 2017;17:1–4.doi:10.1186/s12905-017-0469-9pmid:http://www.ncbi.nlm.nih.gov/pubmed/29141612
      OpenUrlCrossRefPubMed
    9. ↵
      1. Cuzick J,
      2. Arbyn M,
      3. Sankaranarayanan R, et al
      . Overview of human papillomavirus-based and other novel options for cervical cancer screening in developed and developing countries. Vaccine 2008;26 Suppl 10:K29–41.doi:10.1016/j.vaccine.2008.06.019pmid:http://www.ncbi.nlm.nih.gov/pubmed/18847555
      OpenUrlPubMed
    10. ↵
      IARC Working group on the evaluation of carcinogenic risks to humans. Human papillomaviruses. IARC Monogr Eval Carcinog Risks Hum 2007;90:1–636.
      OpenUrl
    11. ↵
      1. World Health Organization
      . Who guidelines for screening and treatment of precancerous lesions for cervical cancer prevention, 2013. Available: http://apps.who.int/iris/bitstream/10665/94830/1/9789241548694_eng.pdf?ua=1
    12. ↵
      1. Tsu VD,
      2. Njama-Meya D,
      3. Lim J, et al
      . Opportunities and challenges for introducing HPV testing for cervical cancer screening in sub-Saharan Africa. Prev Med 2018;114:205–8.doi:10.1016/j.ypmed.2018.07.012pmid:http://www.ncbi.nlm.nih.gov/pubmed/30031013
      OpenUrlPubMed
    13. ↵
      1. Al-Sadi AM,
      2. Al-Oweisi FA,
      3. Edwards SG, et al
      . Genetic analysis reveals diversity and genetic relationship among Trichoderma isolates from potting media, cultivated soil and uncultivated soil. BMC Microbiol 2015;15:1.doi:10.1186/s12866-015-0483-8
    14. ↵
      1. Lemp JM,
      2. De Neve J-W,
      3. Bussmann H, et al
      . Lifetime prevalence of cervical cancer screening in 55 low- and middle-income countries. JAMA 2020;324:1532–42.doi:10.1001/jama.2020.16244pmid:http://www.ncbi.nlm.nih.gov/pubmed/33079153
      OpenUrlPubMed
    15. ↵
      1. Lim JNW,
      2. Ojo AA
      . Barriers to utilisation of cervical cancer screening in sub Sahara Africa: a systematic review. Eur J Cancer Care 2017;26:e12444.doi:10.1111/ecc.12444pmid:http://www.ncbi.nlm.nih.gov/pubmed/26853214
      OpenUrlPubMed
    16. ↵
      1. Yimer NB,
      2. Mohammed MA,
      3. Solomon K, et al
      . Cervical cancer screening uptake in sub-Saharan Africa: a systematic review and meta-analysis. Public Health 2021;195:105–11.doi:10.1016/j.puhe.2021.04.014pmid:http://www.ncbi.nlm.nih.gov/pubmed/34082174
      OpenUrlPubMed
    17. ↵
      1. Isabirye A,
      2. Mbonye MK,
      3. Kwagala B
      . Predictors of cervical cancer screening uptake in two districts of central Uganda. PLoS One 2020;15:e0243281.doi:10.1371/journal.pone.0243281pmid:http://www.ncbi.nlm.nih.gov/pubmed/33270792
      OpenUrlPubMed
    18. ↵
      1. Okyere J,
      2. Duodu PA,
      3. Aduse-Poku L, et al
      . Cervical cancer screening prevalence and its correlates in Cameroon: secondary data analysis of the 2018 demographic and health surveys. BMC Public Health 2021;21:1–8.doi:10.1186/s12889-021-11024-z
      OpenUrlCrossRefPubMed
    19. ↵
      1. Phaswana-Mafuya N,
      2. Peltzer K
      . Breast and cervical cancer screening prevalence and associated factors among women in the South African GeneralPopulation. Asian Pac J Cancer Prev 2018;19:1465.doi:10.22034/APJCP.2018.19.6.1465pmid:http://www.ncbi.nlm.nih.gov/pubmed/29936716
      OpenUrlPubMed
    20. ↵
      1. Tchounga B,
      2. Boni SP,
      3. Koffi JJ, et al
      . Cervical cancer screening uptake and correlates among HIV-infected women: a cross-sectional survey in Côte d'Ivoire, West Africa. BMJ Open 2019;9:e029882.doi:10.1136/bmjopen-2019-029882pmid:http://www.ncbi.nlm.nih.gov/pubmed/31473620
      OpenUrlAbstract/FREE Full Text
    21. ↵
      1. Tiruneh FN,
      2. Chuang K-Y,
      3. Chuang Y-C
      . Women’s autonomy and maternal healthcare service utilization in Ethiopia. BMC Health Serv Res 2017;17:1–2.doi:10.1186/s12913-017-2670-9
      OpenUrlCrossRef
    22. ↵
      1. Ndejjo R,
      2. Mukama T,
      3. Musabyimana A, et al
      . Uptake of cervical cancer screening and associated factors among women in rural Uganda: a cross sectional study. PLoS One 2016;11:e0149696.doi:10.1371/journal.pone.0149696pmid:http://www.ncbi.nlm.nih.gov/pubmed/26894270
      OpenUrlCrossRefPubMed
    23. ↵
      1. Malambo N
      . "Not from home": Cancer screening avoidance and the safety of distance in Eswatini. Soc Sci Med 2021;268:113440.doi:10.1016/j.socscimed.2020.113440pmid:http://www.ncbi.nlm.nih.gov/pubmed/33120208
      OpenUrlPubMed
    24. ↵
      1. Nguyen AB,
      2. Clark TT,
      3. Belgrave FZ
      . Gender roles and acculturation: relationships with cancer screening among Vietnamese American women. Cultur Divers Ethnic Minor Psychol 2014;20:87–97.doi:10.1037/a0033474pmid:http://www.ncbi.nlm.nih.gov/pubmed/24491129
      OpenUrlPubMed
    25. ↵
      1. Adjiwanou V,
      2. LeGrand T
      . Gender inequality and the use of maternal healthcare services in rural sub-Saharan Africa. Health Place 2014;29:67–78.doi:10.1016/j.healthplace.2014.06.001pmid:http://www.ncbi.nlm.nih.gov/pubmed/24994096
      OpenUrlCrossRefPubMed
    26. ↵
      1. Azuh D,
      2. Fayomi O,
      3. Ajayi L
      . Socio-cultural factors of gender roles in women’s healthcare utilization in Southwest Nigeria. Open J Soc Sci 2015;03:105–17.doi:10.4236/jss.2015.34013
      OpenUrl
    27. ↵
      1. Shamaki MA,
      2. Buang A
      . Sociocultural practices in maternal health among women in a less developed economy: an overview of Sokoto state, Nigeria. Geografia-Malaysian Journal of Society and Space 2017;10.
    28. ↵
      1. Kabakyenga JK,
      2. Östergren P-O,
      3. Turyakira E, et al
      . Influence of birth preparedness, decision-making on location of birth and assistance by skilled birth attendants among women in south-western Uganda. PLoS One 2012;7:e35747.doi:10.1371/journal.pone.0035747pmid:http://www.ncbi.nlm.nih.gov/pubmed/22558214
      OpenUrlPubMed
    29. ↵
      1. Connell RW
      . Gender and power Stanford. CA: Stanford Univesity, 1987.
    30. ↵
      1. Wingood GM,
      2. DiClemente RJ
      Scd, . Application of the theory of gender and power to examine HIV-related exposures, risk factors, and effective interventions for women. Health Educ Behav 2000;27:539–65.doi:10.1177/109019810002700502pmid:http://www.ncbi.nlm.nih.gov/pubmed/11009126
      OpenUrlCrossRefPubMedWeb of Science
    31. ↵
      1. Corsi DJ,
      2. Neuman M,
      3. Finlay JE, et al
      . Demographic and health surveys: a profile. Int J Epidemiol 2012;41:1602–13.doi:10.1093/ije/dys184pmid:http://www.ncbi.nlm.nih.gov/pubmed/23148108
      OpenUrlCrossRefPubMedWeb of Science
    32. ↵
      1. von Elm E,
      2. Altman DG,
      3. Egger M, et al
      . The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Int J Surg 2014;12:1495–9.doi:10.1016/j.ijsu.2014.07.013pmid:http://www.ncbi.nlm.nih.gov/pubmed/25046131
      OpenUrlCrossRefPubMed
    33. ↵
      1. Seidu A-A,
      2. Oduro JK,
      3. Ahinkorah BO, et al
      . Women’s healthcare decision-making capacity and HIV testing in sub-Saharan Africa: a multi-country analysis of demographic and health surveys. BMC Public Health 2020;20:1.doi:10.1186/s12889-020-09660-y
    34. ↵
      1. Viens LJ,
      2. Clouston S,
      3. Messina CR
      . Women's autonomy and cervical cancer screening in the Lesotho demographic and health survey 2009. Soc Sci Med 2016;150:23–30.doi:10.1016/j.socscimed.2015.12.009pmid:http://www.ncbi.nlm.nih.gov/pubmed/26722985
      OpenUrlPubMed
    35. ↵
      1. Andersen R,
      2. Newman JF
      . Societal and individual determinants of medical care utilization in the United States. The Milbank Memorial fund Quarterly. Health and Society 1973;1:95–124.
      OpenUrl
    36. ↵
      1. Ba DM,
      2. Ssentongo P,
      3. Musa J, et al
      . Prevalence and determinants of cervical cancer screening in five sub-Saharan African countries: a population-based study. Cancer Epidemiol 2021;72:101930.doi:10.1016/j.canep.2021.101930pmid:http://www.ncbi.nlm.nih.gov/pubmed/33756434
      OpenUrlPubMed
    37. ↵
      1. Kangmennaang J,
      2. Onyango EO,
      3. Luginaah I, et al
      . The next sub Saharan African epidemic? A case study of the determinants of cervical cancer knowledge and screening in Kenya. Soc Sci Med 2018;197:203–12.doi:10.1016/j.socscimed.2017.12.013pmid:http://www.ncbi.nlm.nih.gov/pubmed/29253722
      OpenUrlPubMed
    38. ↵
      1. Stern E,
      2. Buikema R
      . The relational dynamics of hegemonic masculinity among South African men and women in the context of HIV. Cult Health Sex 2013;15:1040–54.doi:10.1080/13691058.2013.805817pmid:http://www.ncbi.nlm.nih.gov/pubmed/23805918
      OpenUrlCrossRefPubMed
    39. ↵
      1. Williams MS,
      2. Amoateng P
      . Knowledge and beliefs about cervical cancer screening among men in Kumasi, Ghana. Ghana Med J 2012;46:147.pmid:http://www.ncbi.nlm.nih.gov/pubmed/23661828
      OpenUrlPubMed
    40. ↵
      1. Lowe M,
      2. Chen D-R,
      3. Huang S-L
      . Social and cultural factors affecting maternal health in rural Gambia: an exploratory qualitative study. PLoS One 2016;11:e0163653.doi:10.1371/journal.pone.0163653pmid:http://www.ncbi.nlm.nih.gov/pubmed/27661617
      OpenUrlPubMed
    41. ↵
      1. Mochache V,
      2. Wanje G,
      3. Nyagah L, et al
      . Religious, socio-cultural norms and gender stereotypes influence uptake and utilization of maternal health services among the Digo community in Kwale, Kenya: a qualitative study. Reprod Health 2020;17:1–0.doi:10.1186/s12978-020-00919-6
      OpenUrl
    42. ↵
      1. Adegboyega A,
      2. Aleshire M,
      3. Dignan M, et al
      . Spousal support and knowledge related to cervical cancer screening: are sub-Saharan African immigrant men interested? Health Care Women Int 2019;40:665–81.doi:10.1080/07399332.2019.1615914pmid:http://www.ncbi.nlm.nih.gov/pubmed/31084466
      OpenUrlPubMed
    43. ↵
      1. Han J,
      2. Jungsuwadee P,
      3. Abraham O, et al
      . Shared decision-making and women’s adherence to breast and cervical cancer screenings. Int J Environ Res Public Health 2018;15:1509.doi:10.3390/ijerph15071509
    44. ↵
      1. Gizaw M,
      2. Teka B,
      3. Ruddies F, et al
      . Reasons for not attending cervical cancer screening and associated factors in rural Ethiopia. Cancer Prev Res 2020;13:593–600.doi:10.1158/1940-6207.CAPR-19-0485pmid:http://www.ncbi.nlm.nih.gov/pubmed/32371553
      OpenUrlAbstract/FREE Full Text
    45. ↵
      1. Denny L
      . Cervical cancer in South Africa: an overview of current status and prevention strategies. Continuing Medical Education 2010;28.
    46. ↵
      1. McClung NM,
      2. Gargano JW,
      3. Park IU, et al
      . Estimated Number of Cases of High-Grade Cervical Lesions Diagnosed Among Women - United States, 2008 and 2016. MMWR Morb Mortal Wkly Rep 2019;68:337–43.doi:10.15585/mmwr.mm6815a1pmid:http://www.ncbi.nlm.nih.gov/pubmed/30998672
      OpenUrlPubMed
    47. ↵
      1. Aweke YH,
      2. Ayanto SY,
      3. 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. PLoS One 2017;12:e0181415.doi:10.1371/journal.pone.0181415pmid:http://www.ncbi.nlm.nih.gov/pubmed/28742851
      OpenUrlPubMed
    48. ↵
      1. Eze JN,
      2. Umeora OU,
      3. Obuna JA, et al
      . Cervical cancer awareness and cervical screening uptake at the mater Misericordiae Hospital, Afikpo, Southeast Nigeria. Ann Afr Med 2012;11:238.doi:10.4103/1596-3519.102856pmid:http://www.ncbi.nlm.nih.gov/pubmed/23103924
      OpenUrlPubMed
    49. ↵
      1. Ngugi CW,
      2. Boga H,
      3. Muigai AWT, et al
      . Factors affecting uptake of cervical cancer early detection measures among women in Thika, Kenya. Health Care Women Int 2012;33:595–613.doi:10.1080/07399332.2011.646367pmid:http://www.ncbi.nlm.nih.gov/pubmed/22681745
      OpenUrlCrossRefPubMed
    50. ↵
      1. Pandey RA,
      2. Karmacharya E
      . Cervical cancer screening behavior and associated factors among women of Ugrachandi Nala, Kavre, Nepal. Eur J Med Res 2017;22:1–9.
      OpenUrlCrossRef
    51. ↵
      1. Ncube B,
      2. Bey A,
      3. Knight J, et al
      . Factors associated with the uptake of cervical cancer screening among women in Portland, Jamaica. N Am J Med Sci 2015;7:104.doi:10.4103/1947-2714.153922pmid:http://www.ncbi.nlm.nih.gov/pubmed/25839002
      OpenUrlPubMed
    52. ↵
      1. Dutta T,
      2. Haderxhanaj L,
      3. Agley J, et al
      . Association between individual and intimate partner factors and cervical cancer screening in Kenya. Prev Chronic Dis 2018;15:E157.doi:10.5888/pcd15.180182pmid:http://www.ncbi.nlm.nih.gov/pubmed/30576277
      OpenUrlPubMed
    53. ↵
      1. Matin M,
      2. LeBaron S
      . Attitudes toward cervical cancer screening among Muslim women: a pilot study. Women Health 2004;39:63–77.doi:10.1300/J013v39n03_05pmid:http://www.ncbi.nlm.nih.gov/pubmed/15256356
      OpenUrlPubMed
    54. ↵
      1. Salman KF
      . Health beliefs and practices related to cancer screening among Arab Muslim women in an urban community. Health Care Women Int 2012;33:45–74.doi:10.1080/07399332.2011.610536pmid:http://www.ncbi.nlm.nih.gov/pubmed/22150266
      OpenUrlCrossRefPubMedWeb of Science

    Footnotes

    • Twitter @kojo_asiamah

    • Contributors JO is the guarantor of the study and accepts full responsibility for the work and/or the conduct of the study. JO: conceptualisation, data curation, writing – original draft and writing – review and editing; RGA: conceptualisation, data curation, analysis, methodology, writing – original draft, writing – review and editing; A-AS: data curation, methodology, writing – original draft and writing – review and editing; BY-AA: writing – original draft, writing – review and editing; BM: validation, writing – review and editing; BOA: conceptualisation, methodology, analysis, data curation, writing – original draft, writing – review and editing.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.