| Abstract|| |
Context: Cervical cancer is first cancer in women in Africa. The disease is often diagnosed at a late stage. Aims: The purpose of this survey is to study the factors of cervical cancer screening. Settings and Design: This is a descriptive and analytical cross-sectional survey carried out in the health district of Thiès in Senegal. Subjects and Methods: Sampling was in two-stage clusters. The data were collected during an individual interview at home. The collection focused on knowledge, attitudes, and practices on cervical cancer. Statistical Analysis Used: Logistic regression was used for data analysis. Results: A total of 498 women were interviewed; 77% of them lived in urban areas, 38% have not been to school, and 82% were married. Nearly, 82.7% of them have already heard about the disease. Infection was the most reported risk factor (55.8%). The screening practice was 35.5% in our sample. Nonschooling reduced screening, while women living in urban areas were seven times more likely to be screened. Screening increased from the poorest quartile to the richest quartile. The knowledge of risk factors and the possibility of recovery increased by 4.80 and 2.34, respectively, the chance of being screened. Conclusions: Improved screening requires multiple strategies that target particularly poor uneducated people living in rural areas but also the strengthening of the capacity of health-care providers.
Keywords: Cervical cancer, knowledge, screening, Senegal
|How to cite this article:|
Faye A, Diagne N, Niang K, Dia AT. Screening for cervical cancer in Senegal: Contributing factors. Ann Trop Med Public Health 2017;10:1474-8
|How to cite this URL:|
Faye A, Diagne N, Niang K, Dia AT. Screening for cervical cancer in Senegal: Contributing factors. Ann Trop Med Public Health [serial online] 2017 [cited 2019 Nov 13];10:1474-8. Available from: http://www.atmph.org/text.asp?2017/10/6/1474/222652
| Introduction|| |
With an estimated global prevalence of 2.3 million women, an estimated global annual incidence of 528,000 new cases and an estimated mortality of 266,000 cases each year, cervical cancer is the second most common cancer in women in the world. This cancer is the most frequent one in sub-Saharan Africa with 75,000 new cases and almost 50,000 deaths each year. In Senegal, cervical cancer ranks first among cancers diagnosed at the Curie Institute in Dakar.
Human papillomavirus vaccination is an effective strategy for preventing this disease. However, it is not yet integrated into a certain vaccination program as it is the case in Senegal. Hence, the importance of screening which consists in the early identification of precancerous lesions. In developing countries, it has led to a significant reduction in cancer mortality. However, in our countries, the screening rate is still low, so diagnosis is often late.,,
There are several factors related to the low rate of screening. Studies on women's knowledge and practice in India and Venezuela have shown that specific knowledge about cervical cancer screening is an essential element that determines whether a woman is going to do the test or not., Geographical and financial inaccessibility and sociocultural factors have also been found. However, in Senegal, there are little data on the practice of screening for cervical cancer and the factors associated with it. Knowledge of this information can help to develop a more adequate prevention program to improve the use of early screening in women and in so doing contribute to the reduction of morbidity and mortality related to this cancer. The general objective of this work is to study the factors associated with the screening of cervical cancer.
| Subjects and Methods|| |
Senegal, a resource-limited country, is located in West Africa. Its population is about 15 million inhabitants with a pyramidal health system. The country has 14 medical regions and 76 health districts. The health district of Thiès is 70 km away from Dakar the capital of Senegal. Its population is estimated at 430,727 inhabitants, 79% of them live in urban areas. Women represent 53% of the population. The health district includes 1 reference health center, 3 hospitals including 2 private ones, 43 health posts including 33 public and 44 clinics and medical offices. In terms of geographical accessibility, 93% of the district's population lives around <5 km away from a structure. As for the staff, the district has one doctor for 51,000 inhabitants, 1 nurse for 11,660 inhabitants, and one midwife for 2400 women at reproductive age.
Type of study
It is a cross-sectional, descriptive, and analytical study.
The study population is represented by women aged between 35 and 65 years living in the study area on the one hand, and by providers of public and private health facilities in the district on the other hand.
We have used the Schwartz formula to calculate the sample size.
- N = (Zα2. P [1 − P])/e2
- Zα = 1.96: Discrepancy corresponding to the risk granted (α = 5%, zα = 1.96)
- P: Proportion of women screened = 18%
- E: Margin of error (set at 5%).
Thus, the calculated sample size is 333 women; if we consider a nonresponse rate of 2% and a cluster effect of 1.5, we find a size at 495.
The sample was divided into 30 census districts (DRs) of 20. Thirty DRs were identified and were distributed in the various boroughs and rural communities of the district taking into account the representativeness of each borough or rural community. An initial drawing was made to identify the different districts and boroughs where the women to be interviewed will be selected. In each neighborhood or borough, a first concession was made. In each concession, all the women meeting the inclusion criteria are interviewed. Concessions are chosen consecutively until we reach the number of people to be surveyed in a cluster.
All providers of public and private health facilities who agreed to participate in the study and met the criteria and were interviewed.
Before data collection, we proceeded by the training of interviewers at the district level for 1 day. The collection of information was done by means of a questionnaire during an individual interview at home on the women's consent. The questionnaire included the following parts: sociodemographic characteristics, knowledge; the women's attitudes and practices on cervical cancer. The socioeconomic standard was calculated on the basis of the index of economic well-being. This index is calculated from the data on household properties (television, radio, car, etc.) and on the housing equipment (electricity, toilet, flooring materials, etc.). Thus, the score obtained was divided into four categories. Screening is estimated by three tests: cervicovaginal smear, colonoscopy or visual inspection using acetic acid (IVA) or lugol (IVL). The interviews with providers were held at their working place. The information we collected was about their occupational characteristics, about their knowledge and practices on cancer.
Qualitative variables were described as a proportion of their confidence interval and the quantitative variables as a mean with their standard deviation. The comparison between the dependent variable, which is the screening itself and the qualitative variables, was performed with a Pearson Chi-square test. A downward logistic regression was performed. The dependent variable is the practice of the screening. All independent variables with a P < 0.25 in the bi-varied analysis were included in the multivariate analysis. The comparison of the models was done by the test of the likelihood ratio with a top-down procedure. The suitability of the model was studied by the Hosmer and Lemeshow test. The association measure was the adjusted odds ratio, and its confidence interval was 95%.
| Results|| |
Women's sociodemographic characteristics
The average age of the interviewed women was 43 years (±7.1). The average number of children per woman was 4.2 (±2.2). Married women represented 82% of our sample, and 38% of the interviewed women did not attend school. Seventy-seven percent lived in urban areas. The interviewed women belonged to the poorest quartile in 35% of the cases, and the majority (82.7%) of interviewed women has already heard of cervical cancer. Television was the most important channel of information (78.7%). Among risk factors, infection was the most reported risk factor (55.8%) followed by multiparity (31.5%) and tobacco (29.1%). Bleeding and pain during sexual intercourse were the most common (31%) symptoms followed by bleeding out of menstruation (28%) and seizure flow (27%). Only 15% of women had cancer cases in their environment. In total, 35.5% of women have already experienced cervical cancer screening, free consultation being the prime cause (82.9%). The cost of screening was considered high in 41.8% of cases.
Providers' sociodemographic characteristics
Altogether, 68 providers were interviewed in 41 health facilities. The average age of providers is 44 years (±11 years) with an average work experience of 14 years (±10). Midwives were the most represented with 55%. Regarding cervical cancer training, only 35% of providers reported having been trained. And for some of these providers, the training dates back to >9 years. Almost 25% of the providers came from private health facilities.
The most widely available screening technique was the IVA/IVL (31%). The screening proposal is systematic in 33% of the interviewed providers. Age (82%) and metrorrhagia (87%) were the most frequent reasons why providers proposed screening to women. Among the reasons for nonscreening, lack of information was the most common reason (51%) followed by fear (20%) and ignorance (20%).
Screening was not associated with age and marital status. The proportion of screened women was 58.8% among the educated women compared with 12.4% among the noneducated women (P = 0.0001) [Table 1]. It was 49.5% in urban areas and 11.5% in rural areas. The proportion of screened women increased from the poorest quartile to the richest quartile with 19.5%, 30.5%, 44.6%, and 53.5%, respectively [Table 1]. The screening rate was 56.7% for women who were aware of the risk factors against 14.3% for those who were not. The same remark is done for those who knew of the possibility of recovery (51.1% vs. 22.1%) [Table 1]. The assessment of cost and distance were also factors associated with screening.
|Table 1: Distribution of respondents according to socio-personal characteristics and screening in Senegal|
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The results of [Table 2] shown that Women living in urban areas (2.43 [1.75-3.37]) were more likely to benefit from cervical cancer screening than women who did not attend school (1.54 [1.09-2.17]). Knowledge of risk factors and healing possibility increases screening [Table 2].
| Discussion|| |
The screening rate was 35.1%. The main factors are related to personal characteristics, resources, and needs. This screening rate was significantly higher than the rates found in other studies, in Burkina Faso  (11%), Kenya  (17.5%), and South Africa  (18%). These rates remain relatively low compared to the averages observed in the northern countries. In France, it was 72% in 2009. This detection rate can be explained by the numerous campaigns that have been carried out in the health district of Thiès. In fact, 82.9% of women were screened during the free screening campaigns. Free is part of the logic of social justice aimed at preventing the poorest from being marginalized and falling into a permanent exclusion. In most countries where these policies have been implemented, they have facilitated access to care for the poor,, thus reducing social inequalities in health., However, even with free screening, certain inequalities persist. There is a significant relationship between educational background and screening rate. Education favors access to information and reduces ignorance. Indeed, ignorance is one of the main reasons for lack of screening.
Women in urban areas are more likely to be screened than women in rural area. This may be due to the accessibility and availability of public and private screening facilities that are generally concentrated in the city. The socioeconomic standard and the perception of the high cost of screening have an impact on the use of screening. Indeed, the lack of resources is often a hindrance to access to health services  and screening in particular  because even if screening campaigns are free, they are done at the level of health facilities. The knowledge of risk factors influenced the use of screening as shown in other studies., Knowledge of cancer can increase the perception of risk. It is the same for women who think that cancer can be healed. This seems understandable because the existence of treatment makes women more optimistic and it can also lessen the fear.
The study also found that women who received counseling during the consultation sessions were more frequently screened. Health facilities can play an important role in cervical cancer screening. However, screening is most often done during gynecological consultations, whereas the different types of consultation (ANC, FP) could be opportunities for sensitization and screening. This situation can be explained by the lack of knowledge of the providers knowing that only 33% received training on breast cancer.
| Conclusions|| |
The results of our study show that despite the free screening campaigns conducted in the health district of Thies, the screening rate remains low. The main factors are related to personal characteristics, resources, and health facilities. Improved screening implies the implementation of multiple strategies which target particularly the uneducated poor populations living in rural areas but also the strengthening of health-care providers' capacities.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al.
Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136:E359-86.
De Vuyst H, Alemany L, Lacey C, Chibwesha CJ, Sahasrabuddhe V, Banura C, et al.
The burden of human papillomavirus infections and related diseases in sub-Saharan Africa. Vaccine 2013;31 Suppl 5:F32-46.
Dem A, Traoré B, Dieng MM, Diop PS, Ouadji T, Lalami, MT, et al
. Gynaecological and breast cancers at the Dakar Cancer Institute. Cahiers Santé 2008;18:25-9.
Mboumba Bouassa RS, Prazuck T, Lethu T, Jenabian MA, Meye JF, Bélec L, et al.
Cervical cancer in sub-Saharan Africa: A preventable noncommunicable disease. Expert Rev Anti Infect Ther 2017;15:613-27.
Sawadogo B, Gitta SN, Rutebemberwa E, Sawadogo M, Meda N. Knowledges and beliefs and practices on cervical cancer screening among women aged 20 to 50 years in Ouagadougou, Burkina Faso, 2012: A cross- sectional study. Pan Afr Med J 2014;18:175.
Wamburu K, Busakhala N, Owuor K, Nyagero J. Association between stage at diagnosis and knowledge on cervical cancer among patients in a Kenyan tertiary hospital: A cross-sectional study. Pan Afr Med J 2016;25:15.
Hoque M, Hoque E, Kader SB. Evaluation of cervical cancer screening program at a rural community of South Africa. East Afr J Public Health 2008;5:111-6.
Aswathy S, Quereshi MA, Kurian B, Leelamoni K. Cervical cancer screening: Current knowledge and practice among women in a rural population of Kerala, India. Indian J Med Res 2012;136:205-10.
] [Full text]
Núñez-Troconis J, Tulliani E, Martínez MG. Knowledge and attitudes as predictors of cervical cancer screening among women in a Venezuelan urban area. Invest Clin 2013;54:20-33.
Williams-Brennan L, Gastaldo D, Cole DC, Paszat L. Social determinants of health associated with cervical cancer screening among women living in developing countries: A scoping review. Arch Gynecol Obstet 2012;286:1487-505.
National agency for statistics and demography. General population census of Senegal. 2015. p. 450.
Hosmer DW, Lemeshow S. Applied Logistic Regression. Wiley-Interscience; 2012.
Guthmann JP, Pelat C, Célant N, Parent du Chatelet I, Duport N, Levy-Bruhl D, et al
. Socio-Economic Determinants of Vaccination and Screening for Cervical Cancer by Cervico-Uterine Smear (FCU). Analysis of the Health and Social Protection Survey (ESPS), 2012. Saint-Maurice: Institut de Veille Sanitaire; 2016. p. 48.
Ensor T, Ronoh J. Effective financing of maternal health services: A review of the literature. Health Policy 2005;75:49-58.
Penfold S, Harrison E, Bell J, Fitzmaurice A. Evaluation of the delivery fee exemption policy in Ghana: Population estimates of changes in delivery service utilization in two regions. Ghana Med J 2007;41:100-9.
Nabyonga J, Desmet M, Karamagi H, Kadama PY, Omaswa FG, Walker O, et al.
Abolition of cost-sharing is pro-poor: Evidence from Uganda. Health Policy Plan 2005;20:100-8.
Xu K, Evans DB, Kadama P, Nabyonga J, Ogwal PO, Nabukhonzo P, et al.
Understanding the impact of eliminating user fees: Utilization and catastrophic health expenditures in Uganda. Soc Sci Med 2006;62:866-76.
Faye A, Diouf M, Niang K, Leye MM, Ndiaye S, Ayad M, et al.
Social inequality and antenatal care: Impact of economic welfare on pregnancy monitoring in Senegal. Rev Epidemiol Sante Publique 2013;61:180-5.
Bansal AB, Pakhare AP, Kapoor N, Mehrotra R, Kokane AM. Knowledge, attitude, and practices related to cervical cancer among adult women: A hospital-based cross-sectional study. J Nat Sci Biol Med 2015;6:324-8.
Morema EN, Atieli HE, Onyango RO, Omondi JH, Ouma C. Determinants of cervical screening services uptake among 18-49 year old women seeking services at the Jaramogi Oginga Odinga Teaching and Referral Hospital, Kisumu, Kenya. BMC Health Serv Res 2014;14:335.
Faye A, Manga NM, Seck I, Niang K, Leye MM, Diagne-Camara M, et al.
Access to Intermittent Preventive Treatment (IPt) in a situation of abolition of user's fee: Role of economic welfare. Bull Soc Pathol Exot 2012;105:215-9.
Sudenga SL, Rositch AF, Otieno WA, Smith JS. Knowledge, attitudes, practices, and perceived risk of cervical cancer among kenyan women: Brief report. Int J Gynecol Cancer 2013;23:895-9.
Institute of Health and Development, Cheikh Anta Diop University, BP 16390, Dakar-Fann, Dakar
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2]