Knowledge, Attitudes and Practices of Congolese Women in Kinshasa on Breast Cancer ()
1. Introduction
Breast cancer is a malignant tumour that develops in the mammary gland [1].
Its incidence, already high in the 1970s, is still rising in both developed and developing countries [2]. Between 1975 and 2000, incidence rose by between 0.5% and 1.5% in many countries [3]. In Asia and China in particular, this increase has reached 3% to 5% per year over the last three decades [4]. In Europe, the highest levels of incidence are observed in Western European countries, in contrast to Eastern European countries [5]. In Africa, taking current trends into account, the number of new cases of breast cancer is expected to double by 2040 [6].
Its management, particularly clinical management, requires high-quality, long-term medical care adapted to its chronic nature and metastatic potential. Among many prognostic factors, the clinical stage of the tumor at diagnosis is one of the most important determinants of post-treatment outcome, whatever the technical platform [7]. The average cost of this treatment, estimated at $1000 per patient every three weeks, represents a considerable financial burden for healthcare systems, patients and their families [8], especially in developing countries. Since 2020, breast cancer has become the leading cause of cancer mortality worldwide [9].
Faced with this problem, the international community, through the WHO, has observed that to guarantee women’s health in the face of breast cancer, the fight must be waged through two essential measures: mass screening and early diagnosis and treatment [10]:
- For mass screening, the standard tripod recommended is the clinical breast examination, combined with breast ultrasound and mammography [11].
- As for early diagnosis and treatment, women should examine their own breasts regularly, and consult their doctor immediately in the event of any abnormality [12].
Given that the first measure requires financial outlay for the acquisition of screening tools [8], particular emphasis is placed on women’s effective participation in their own destiny in the face of breast cancer through the second measure, which entails no financial outlay. So far, however, this recommendation does not seem to have been fully taken on board, given the continuing high incidence of late-stage breast cancer at diagnosis, especially in developing countries.
In the DRC, breast cancer mortality is also high [13]. To explain this level of mortality, Espina C et al. [14] cite the late arrival of patients in the advanced stages of their disease, without saying whether this was due to ignorance or environmental obstacles, and deplore the limitations associated with care due to a rudimentary technical platform, precarious economic conditions and the absence of a health insurance system.
Several other studies on breast cancer have been carried out in the DRC, and numerous aspects have been addressed. However, to date, no study assessing the knowledge, attitudes and practices of Congolese women with regard to breast cancer is available, and is likely to justify their behavior in the face of this cancer, understand their late consultations and help refine strategies to reduce its mortality, even though the national strategic plan to combat cervical and breast cancers [15] deplores the lack of information on these two cancers since 2015.
Bearing in mind the above-mentioned characteristics, we felt it appropriate to initiate the present study with the aim of assessing the knowledge, attitudes and practices of Congolese women in Kinshasa regarding breast cancer.
2. Methods
Our cross-sectional descriptive study with analytical aims based on a mixed method (qualitative and quantitative) was conducted in the city of Kinshasa from June to September 2023.
Our sampling is of the 3-stage cluster probability type.
First stage: 8 communes were drawn at random from the 24 communes of the city of Kinshasa, with 2 communes per district,
2nd stage: 2 districts per commune were randomly selected, for a total of 16 districts,
3rd stage: 4 avenues per district were randomly selected, for a total of 64 avenues,
Avenues: with the sampling step, 15 to 20 plots per avenue were retained, given that not all avenues had the same number of plots. A total of 1152 plots were included in the study. When a plot was uninhabited or inaccessible for an obvious reason, it was replaced by the next plot.
To minimize information bias, interviewers were recruited, trained, tested and selected based on their performance, a pre-test of the questionnaire was carried out, collection forms were checked daily by the person in charge of the survey, and incomplete or badly filled-in forms were discarded.
The sample size was calculated using the following formula:
n = minimum sample size.
Z = 1.96 (95% confidence coefficient).
P = 0.6 (proportion of women who performed breast self-examination).
d = 0.05 (degree of precision).
The sample size was 386 women. This sample size was increased by 30% to 499%.
However, to obtain as much information as possible and increase the accuracy of statistical tests, the sample size was increased to 1170 by interviewing at least one person meeting our inclusion criteria in each plot.
2.1. Inclusion Criteria
In this study, we included Congolese women living in Kinshasa, aged 18 to 65, who agreed to participate freely in the study.
2.2. Non-Inclusion Criteria
Women under 18 or over 65, healthcare personnel, and women who refused to participate in the study.
Statistical analyses: the T student test was used for the comparison of means, while the chi-square test was used for the comparison of proportions and Backward step-wise logistic regression to determine associations. The significance level was set at P ≤ 0.05.
2.3. Data Collection
Data were collected using an online questionnaire designed on kobocollect. https://ee.kobotoolbox.org/single/ea763d1799a8e392dee1649ffc09f059.
2.4. Study Variables
Our variables of interest were sociodemographic, disease history, knowledge, attitudes and practices.
2.5. Evaluation Plan for Dependent Variables (Knowledge, Attitudes, and Practices)
2.5.1. Knowledge of Breast Cancer
To identify knowledge, we asked each respondent twelve main questions, each coupled with a secondary question to check the consistency between the answer given to the secondary question and the main question. These questions are summarized in the table. Knowledge was considered accurate if it was consistent, and erroneous if it was not.
Assessment of knowledge levels
For each correct answer, the score equals 1. Otherwise, the score equals 0.
Thus, the total points to be earned by each respondent on the twelve pairs of questions each had to answer equals 12.
Based on this principle, the different levels of knowledge into which each respondent was to be placed according to her score are:
Insufficient knowledge of breast cancer if the score varied from 0 to 6:
Poor knowledge for a total score of 0 to 3 points,
Limited knowledge for a total of 4 to 6 points.
Sufficient knowledge of breast cancer if score ranged from 7 to 12.
Good knowledge for a total of 7 to 9 points.
Very good knowledge for a total of 10 to 12 points.
To facilitate and simplify statistical calculations, we have divided the respondents into two groups: those with insufficient knowledge and those with sufficient knowledge.
Identification of factors associated with knowledge
At this stage, we began by comparing the profile of respondents with insufficient knowledge with that of respondents with sufficient knowledge about breast cancer, and then looked for factors associated with insufficient knowledge.
2.5.2. Attitudes about Breast Cancer
The ten questions asked of each respondent to identify attitudes are presented in the table below.
Assessment of attitude levels
An attitude was considered positive and rated 1 if it could be justified by validated theoretical data on breast cancer. Otherwise, it was rated 0.
Thus, the total points to be earned by each respondent on the ten questions equals 10.
Based on this principle, the different levels of attitude considered are: Negative attitude if the rating goes from 0 to 5.
Very negative attitude for a total of points from 0 to 2.
Fairly negative attitude for a total of points from 3 to 5.
Positive attitude for ratings of 6 to 10 points.
Reasonably positive attitude for a total of 6 to 8 points.
Very positive attitude for a total of 9 to 10 points.
To facilitate and simplify statistical calculations, we have dichotomized the respondents into two groups: a first group, those with negative attitudes, and a second group, those with positive attitudes.
Identification of factors associated with attitudes
At this stage we began by comparing the profile of respondents with negative attitudes to that of respondents with positive attitudes about breast cancer, and then looked for factors associated with negative attitudes.
2.5.3. Breast Cancer Practices
The four questions asked of each respondent to identify practices are presented in the table below:
Assessment of practice levels:
The practice was judged beneficial and rated 1 if it was not contradicted by validated theoretical data on breast cancer. Otherwise, it was rated 0.
Thus, the total points to be gained by each respondent on the four questions asked about practices is equal to 4.
Based on this principle, the different levels of practices considered are:
Non-beneficial practices on breast cancer if the score is 0 to 2.
Inadequate practices for a total score of 0 to 1.
Borderline practices for a total score of 2.
Practices beneficial to breast cancer if rated 3 to 4.
Acceptable practices for a total of 3 ratings.
Adequate practices for a total score of 4.
To facilitate and simplify statistical calculations, we have dichotomized the respondents into two groups: a first group with non-beneficial practices and a second group with beneficial practices.
Identification of factors associated with practices
At this stage, we began by comparing the profile of respondents with non-beneficial practices with that of respondents with beneficial practices in relation to breast cancer, and then looked for factors associated with non-beneficial practices in relation to breast cancer.
2.6. Calculating Levels of Knowledge, Attitudes and Practices
We proceeded by establishing a rating scale to be obtained by the respondents, determining bounds by the median and then the quartile to obtain a percentage scale, and transforming the percentage scale into a qualitative ordinal scale.
This study was designed and financed by our own funds.
2.7. Ethical Considerations
This project has been prepared in accordance with the Declaration of Helsinki and has been approved by the Ethics Committee of the Department of Obstetrics and Gynecology of the University Clinics of Kinshasa.
3. Results
At the end of this survey, we recorded 1170 questionnaires which had fulfilled all the inclusion criteria. About socio-demographic characteristics (Table 1), the average age of the respondents was 41.12 ± 14.59 years. The most numerous were those aged 50 or over (42.4%), with secondary education (57%), shopkeepers (39.2%), followers of revivalist churches (51.4%) and living in the Tshangu district (41%).
About level of knowledge, an analysis of Table 2 reveals that 60% are insufficiently knowledgeable.
Referring to the factors associated with insufficient knowledge, Table 3 shows that the factors most strongly and positively associated with insufficient knowledge are: residence in the Tshangu district (aOR = 5.92; IC 95% 3.48 - 10.39; p = 0.001), primary education (aOR = 3.71; IC 95% 2.20 - 6.34; p = 0.001), membership of revivalist churches (aOR = 2.40 IC 95% 1.43 - 4.07; p = 0.00), unemployment (aOR = 4.96; IC 95% 2.80 - 9.20; p = 0.001), nulliparity (aOR = 2.49; IC 95% 1.72 - 3.63; p = 0.001) and absence of breastfeeding (aOR = 1.668; IC 95% 1.237 - 2.249; p = 0.000).
Table 1. Socio-demographic characteristics of breast cancer respondents.
| Variables |
Headcount |
% |
| Age (in years) |
|
|
| 41 ± 15 years |
|
|
| <30 years |
359 |
30.6 |
| 30 - 49 years |
314 |
26.8 |
| ≥50 years |
497 |
42.4 |
| Levels of education |
|
|
| Primary |
235 |
20.0 |
| Secondary |
665 |
56.8 |
| Higher education |
270 |
23.0 |
| Profession |
|
|
| Business |
459 |
39.2 |
| Unemployment: |
288 |
24.6 |
| Civil servant |
245 |
20.9 |
| Private sector |
106 |
9.0 |
| Farming |
72 |
6.1 |
| Religion |
|
|
| Catholic |
177 |
15.1 |
| Protestant |
168 |
14.3 |
| Kimbanguist |
131 |
11.1 |
| Muslim |
92 |
7.8 |
| Revivalist |
602 |
51.4 |
| Adress |
|
|
| Funa |
184 |
15.7 |
| Mont Amba |
191 |
16.3 |
| Tshangu |
479 |
40.9 |
| Lukunga |
316 |
27.0 |
Table 2. Level of knowledge about breast cancer.
| Knowledge levels |
Headcount |
% |
| sufficient |
469 |
40.1 |
| insufficient |
701 |
59.9 |
| Total |
1170 |
100 |
In terms of attitudes, this study shows that 74.4% of respondents’ attitudes towards breast cancer were negative (Table 4).
Table 3. Factors associated with insufficient knowledge.
| Variables |
breast cancer knowledge |
Cross OR (IC 95%) |
p |
Adjusted OR (IC 95%) |
p |
| insufficient (n = 701) |
sufficient (n = 469) |
| Age (years) |
| ≥50 |
272 |
225 |
1 |
|
1 |
|
| 30 - 49 |
199 |
115 |
0.226 (0.176 - 0.293) |
0.008 |
0.65 (0.44 - 0.96) |
0.031 |
| <30 |
230 |
129 |
1.585 (0.947 - 2.527) |
0.079 |
1.34 (0.94 - 1.91) |
0.108 |
| Adress |
| Lukunga |
246 |
203 |
1 |
|
1 |
|
| Funa |
139 |
76 |
1.664 (1.466 - 1.888) |
0.079 |
1.12 (0.82 - 1.53) |
0.489 |
| Mont -amba |
156 |
87 |
1.117 (0.939 - 1.328) |
0.324 |
1.98 (1.08 - 3.68) |
0.028 |
| Tshangu |
166 |
103 |
1.208 (0.614 - 1.194) |
0.000 |
5.92 (3.48 - 10.39) |
0.001 |
| Level of education |
| Higher |
97 |
100 |
1 |
|
1 |
|
| Secondary |
218 |
63 |
1.186 (1.002 - 1.404) |
0 .413 |
0.91 (0.63 - 1.31) |
0.599 |
| Primary |
386 |
306 |
1.586 (0.947 - 2.587) |
0.000 |
3.71 (2.20 - 6.34) |
0.001 |
| Religion |
| Catholic |
190 |
112 |
1 |
|
1 |
|
| Revival |
252 |
146 |
1.774 (0.38 - 8.093) |
0.234 |
2.40 (1.43 - 4.07) |
0.001 |
| Muslim |
63 |
53 |
0.262 (0.617 - 1.897) |
0.006 |
1.95 (1.09 - 3.49) |
0.024 |
| Kimbanguist |
57 |
33 |
1.692 (1.134 - 2.526) |
0.001 |
1.82 (1.09 - 3.03) |
0.022 |
| Protestant |
139 |
125 |
0.844 (0.342 - 2.443) |
0.042 |
1.02 (0.63 - 1.66) |
0.933 |
| Profession |
| Civil servant |
225 |
33 |
1 |
|
1 |
|
| Unemployment |
195 |
50 |
1.009 (0.712 - 1.436) |
0.006 |
4.96 (2.80 - 9.20) |
0.001 |
| Private trader |
71 |
35 |
1.206 (0.679 - 2.119] |
0.531 |
1.53 (0.90 - 2.28) |
0.356 |
| Business |
355 |
104 |
2.224 (1.134 - 4.362) |
0.002 |
1.43 (0.99 - 2.07) |
0.054 |
| farmer |
55 |
15 |
0.849 (0.476 - 1.533) |
0.000 |
2.68 (1.56 - 4.64) |
0.001 |
| Parity |
| Multipare |
232 |
188 |
1 |
|
1 |
|
| Paucipare |
188 |
74 |
0.456 (0.331 - 0.629) |
0.000 |
1.63 (1.06 - 1.90) |
0.008 |
| Nullipare |
281 |
207 |
1.142 (0.941 - 1.221) |
0.646 |
2.49 (1.72 - 3.63) |
0.001 |
| Breastfeeding |
| yes |
528 |
392 |
1 |
|
1 |
|
| No |
173 |
77 |
1.206 (1.091 - 1.332) |
0.001 |
1.668 (1.237 - 2.249) |
0.000 |
| History of breast cancer |
| Yes |
230 |
168 |
1 |
|
1 |
|
| No |
467 |
301 |
1.114 (0.871 - 1.424) |
0.340 |
2.314 (0.946 - 4.035) |
0.016 |
Table 4. Level of attitudes about breast cancer.
| Attitude level |
Number |
Percentage |
| Positive |
299 |
25.6 |
| Negative |
871 |
74.4 |
| Total |
1170 |
100 |
Table 5 shows that the factors most strongly and positively associated with negative attitudes are age < 30 years (aOR = 6.66; CI 95% 4.42 - 10.15; p = 0.001), living in Tshangu (aOR = 9.34; CI 95% 4.02 - 23.75; p = 0.001), primary education (aOR = 5.77; CI 95% 2.94 - 11.69; p = 0.001), belonging to the Muslim religion (aOR = 5.83; CI 95 2.83 - 10.25; p = 0.001), occupation as a farmer (aOR = 8.29; CI 95% 3.93 - 18.46; p = 0.001), nulliparity (aOR = 2.61; CI 95% 1.37 - 4.98; p = 0.003), absence of breastfeeding (aOR = 3.86; CI 65% 5.84 - 36.85; p = 0.001) and insufficient knowledge of breast cancer (aOR = 3.98; CI 95% 2.43 - 5.48; p = 0.001).
Table 5. Factors associated with negative attitudes.
| Variables |
Attitudes |
CROSS OR (IC 95 %) |
p |
Adjusted OR (IC 95%) |
p |
| Negative (n = 871) |
Positive (n = 299) |
| Age (years) |
| ≥50 |
339 |
158 |
1 |
|
1 |
|
| 30 - 49 |
257 |
57 |
1.52 (1.12 - 2.07) |
0.007 |
0.55 [0.34 - 0.88] |
0.013 |
| <30 |
275 |
84 |
2.10 (1.49 - 2.96) |
0.000 |
6.66 [4.42 - 10.15] |
0.001 |
| Adress |
| Lukunga |
246 |
97 |
1 |
|
1 |
|
| Funa |
139 |
76 |
1.07 (0.82 - 1.39) |
0.609 |
5.10 (2.64 - 10.14) |
0.001 |
| Mont -amba |
156 |
87 |
1.05 (0.86 - 1.28) |
0.018 |
0.93 (0.64 - 1.38) |
0.731 |
| Tshangu |
330 |
39 |
1.05 (0.86 - 1.02) |
0.000 |
9.34 (4.02 - 23.75) |
0.001 |
| Level of education |
| Higher |
95 |
49 |
1 |
|
1 |
|
| Secondary |
221 |
110 |
1.009 (0.71 - 1.43) |
0.002 |
1.55 (1.02 - 2.37) |
0.043 |
| Primary |
555 |
140 |
2.908 (1.75 - 4.80) |
0.000 |
5.77 (2.94 - 11.69) |
0.001 |
| Religion |
| Catholic |
160 |
19 |
1 |
|
1 |
|
| Revival |
456 |
146 |
3.01 (1.76 - 5.13) |
0.000 |
2.36 (1.45 - 3.92) |
0.001 |
| Muslim |
47 |
45 |
0.30 (0.19 - 0.48) |
0.000 |
5.83 (2.83 - 10.25) |
0.001 |
| Kimbanguist |
76 |
55 |
1.26 (0.82 - 1.92) |
0.278 |
4.17 (2.22 - 7.94) |
0.003 |
| Protestant |
134 |
34 |
0.44 (0.29 - 0.65) |
0.000 |
1.94 (1.10 - 3.45) |
0.024 |
| Profession |
| Civil servant |
183 |
62 |
1 |
|
1 |
|
| Unemployment |
246 |
42 |
1.47 (0.87 - 2.50) |
0.149 |
1.92 (1.10 - 3.37) |
0.023 |
| private sector |
63 |
43 |
0.98 (0.58 - 1.65) |
0.958 |
1.36 (0.65 - 2.81) |
0.411 |
| Business |
318 |
121 |
0.45 (0.24 - 0.83) |
0.012 |
2.58 (1.54 - 4.09) |
0.001 |
| farmer |
61 |
11 |
0.73 (0.44 - 1.21) |
0.233 |
8.29 (3.93 - 18.46) |
0.001 |
| Parity |
| Multipare |
175 |
87 |
1 |
|
1 |
|
| Paucipare |
397 |
91 |
0.81 (0.58 - 1.13) |
0.225 |
1.35 (0.83 - 2.21) |
0.235 |
| Nullipare |
299 |
121 |
1.76 (1.29 - 2.40) |
0.000 |
2.61 (1.37 - 4.98) |
0.003 |
| Breastfeeding |
| yes |
693 |
225 |
1 |
|
1 |
|
| No |
178 |
74 |
1.23 (0.90 - 1.68) |
0.185 |
3.86 (5.84 - 36.85) |
0.001 |
| History of breast cancer |
| Yes |
579 |
189 |
1 |
|
1 |
|
| No |
282 |
110 |
1.03 (0.96 - 1.11) |
0.305 |
2.60 (0.56 - 3.51) |
0.040 |
| knowledge |
| sufficient |
90 |
379 |
1 |
|
1 |
|
| insufficient |
147 |
554 |
0.89 (0.66 - 1.20) |
0.458 |
3.98 (2.43 - 5.48) |
0.001 |
80% of respondents’ breast cancer practices were non-beneficial (Table 6).
Table 6. Level of practices on breast cancer.
| Practices |
number |
Percentage |
| Beneficial |
235 |
20.3 |
| No beneficial |
933 |
79.7 |
| Total |
1170 |
100 |
With regard to factors associated with non-beneficial breast cancer practices, Table 7 shows that the factors most strongly and positively associated with respondents’ non-beneficial breast cancer practices are secondary education (aOR = 2.06; 95% CI 1.33 - 3.21; p = 0.001), membership of revivalist churches (aOR = 2.69, CI 95% 1.04 - 3.18, p = 0.038), nulliparity (aOR = 5.91, CI 95% 2.08 - 10.7, p = 0.001), absence of sporting activities (aOR = 1.51; CI 95% 1.33 - 1.69; p = 0.000) and insufficient knowledge of breast cancer (aOR = 1.64; CI 95 1.15 - 2.33; p = 0.006).
Table 7. Factors associated with non-beneficial practices.
| Variables |
Practices |
CROSS OR (IC 95 %) |
p |
Adjusted OR (IC 95%) |
p |
| No beneficial (n = 933) |
Beneficial (n = 237) |
| Age (years) |
| ≥50 |
416 |
81 |
1 |
|
1 |
|
| 30 - 49 |
224 |
90 |
1.15 (0.80 - 1.65) |
0.425 |
0.72 (0.48 - 1.09) |
0.078 |
| <30 |
293 |
66 |
2.06 (1.46 - 2.90) |
0.000 |
2.45 (0.95 - 6.02) |
0.018 |
| Level of education |
| Higher |
207 |
63 |
1 |
|
1 |
|
| Secondary |
563 |
102 |
1.42 (1.32 - 1.53) |
0.000 |
2.06 (1.33 - 3.21) |
0.001 |
| Primary |
163 |
72 |
3.17 (1.38 - 2.55) |
0.001 |
1.54 (0.83 - 2.87) |
0.173 |
| Religion |
| Catholic |
145 |
32 |
1 |
|
1 |
|
| Revival |
516 |
86 |
2.00 (1.18 - 3.37) |
0.217 |
2.69 (1.04 - 3.18) |
0.035 |
| Muslim |
69 |
23 |
1.32 (0.84 - 2.06) |
0.000 |
1.78 (0.89 - 3.73) |
0.105 |
| Kimbanguist |
81 |
50 |
3.70 (2.43 - 5.63) |
0.000 |
1.98 (1.07 - 3.72) |
0.031 |
| Protestant |
146 |
22 |
2.26 (1.15 - 3.40) |
0.000 |
0.80 (0.42 - 1.49) |
0.478 |
| Profession |
| Civil servant |
195 |
50 |
1 |
|
1 |
|
| Unemployment |
255 |
33 |
0.49 (0.25 - 0.96] |
0.039 |
2.33 (0.94 - 4.56) |
0.038 |
| private sector |
71 |
35 |
1.87 (0.93 - 3.76) |
0.078 |
0.32 (0.18 - 0.57) |
0.001 |
| Business |
355 |
104 |
1.11 (0.60 - 2.04) |
0.730 |
0.54 (0.34 - 0.85) |
0.007 |
| farmer |
55 |
15 |
0.53 (0.26 - 1.07) |
0.079 |
0.51 (0.26 - 1.00) |
0.052 |
| Parity |
| Multipare |
326 |
94 |
1 |
|
1 |
|
| Paucipare |
368 |
120 |
0.33 (0.20 - 0.54) |
0.000 |
|
|
| Nullipare |
239 |
23 |
1.13 (0.83 - 1.53) |
0.434 |
5.91 (2.08 - 10.7) |
0.001 |
| History of breast cancer |
| Yes |
259 |
143 |
1 |
|
1 |
|
| No |
674 |
94 |
1.86 (1.33 - 21.63) |
0.001 |
3.95 (2.94 - 5.32) |
0.062 |
| Sporting activity |
| yes |
262 |
172 |
1 |
|
1 |
|
| No |
671 |
65 |
6.77 (4.92 - 9.34) |
0.000 |
1.51 (1.33 - 1.69) |
0.000 |
| Breastfeeding |
| yes |
705 |
215 |
1 |
|
1 |
|
| No |
228 |
22 |
3.16 (1.98 - 5.02) |
0.000 |
2.83 (0.19 - 0.24) |
0.000 |
| Knowledge |
| Sufficient |
90 |
379 |
1 |
|
1 |
|
| insufficient |
147 |
554 |
0.89 (0.66 - 1.20) |
0.458 |
1.64 (1.15 - 2.33) |
0.006 |
4. Analysis
4.1. Sociodemographic Characteristics
The average age of respondents was 41 ± 15 years, and the majority had a secondary education (57%). This average is higher than the 22.7 ± 3.8 years found by Tchin Darre et al. in 2020 in Togo and the 20.26 ± 6.04 found by Codjo L.V. et al. [16] in 2023 in Benin.
We believe that this difference may be explained by the fact that our survey took place in the general population, whereas those of the two foreign studies took place in selective university environments generally frequented by younger, better-educated people.
Most of the respondents were shopkeepers (39%), practicing their faith in revivalist churches (51%), and living in the Tshangu district (40%). We believe that this particularity is because the sample faced the problem of employment, the personal orientation of religious beliefs and the demographic distribution in the city-province of Kinshasa.
4.2. Levels of Knowledge, Attitudes and Practices about Breast Cancer
Our study shows that only 40% of women have sufficient knowledge about breast cancer. This percentage is lower than those found by: Mena M et al. [17] in 2014 in Ghana (80%), Asmare et al. [18] in 2022 in Ethiopia (55%), but close to those found by, Gedif et al. [19] in 2013 in Ethiopia (38%) and by Mamdouh et al. [20] in 2014 in Egypt, (48%), Mahfouz et al. [21] in 2017 in Saudi Arabia (47%).
Our study also shows that 75% of female respondents have negative attitudes towards breast cancer. This result is comparable to that found by Wright et al. [22] in 2013 in South Africa (68%), and Margueritta et al. [23] in 2018 in Lebanon (72%), but far lower than those found by: Tieng’o et al. [24] in 2011 in Botswana (86%), Bouslah et al. [25] in 2014 in Tunisia (93.0%), and Nouessewah et al. [26] in 2021 in Benin (93.0%).
Finally, our study shows that 80% of women surveyed have non-beneficial breast cancer practices. This result is in line with that of Tabrizi et al. [27] in 2019 in Kenya, who reported that 72% of women admit to never having had breast examinations and do not plan to have breast ultrasounds or breast self-examination. This contrasts with those of Habib et al. [28] in 2010 in Saudi Arabia, and kratzke et al. [29] in 2013 in the USA. These two studies respectively found that 61% and 75% of women have positive breast cancer practices.
Based on the data available in the literature, all the above results and their differences are attributable to two essential factors, one environmental and the other hereditary, in addition to fluctuations in sampling and the populations to be evaluated.
As far as environmental factors are concerned, these are most often the collective imagination, which tends to relegate breast cancer to the category of mysterious, incurable diseases due to a family curse, the harmful influence of certain sectarian teachings, inadequate education, inefficient health systems and difficulties in accessing sources of information, etc., all of which often give rise to risky behaviour.
As for hereditary factors, these include a personal or family history of breast cancer, which can make people more risk averse.
4.3. Factors Associated with Negative Attitudes and Non-Beneficial Practices
Insufficient knowledge:
The present study shows a positive association between insufficient knowledge and negative attitudes on the one hand, and insufficient knowledge and non-beneficial practices on the other.
Since attitudinal deficits have a greater impact on psycho-social equilibrium in relation to breast cancer, we have chosen to discuss only the relationship between insufficient knowledge and non-beneficial practices in relation to breast cancer. Indeed, in view of this aspect, our results are in line with those of other studies, notably those by:
- Solikhah et al. [30] in 2021 in Indonesia, who found that women with a good knowledge of breast cancer presented more easily for screening,
- Asadi et al. [31] in 2018 in Tehran found that, knowledge of the risk, signs and symptoms of breast cancer is a determinant of participation in breast cancer screening,
- Agbokey et al., [32] in 2019 in Ghana, found that, women’s inadequate knowledge of breast cancer, combined with widespread misconceptions about the disease, led instead to low uptake of screening programs.
5. Conclusions
Using a descriptive study with an analytical aim applied to a sample of 1170 respondents selected by a 3-stage cluster sampling in the city province of Kinshasa, the results obtained allow us to draw the following conclusions:
- There is a great diversity of knowledge, attitudes and practices regarding breast cancer among Congolese women in Kinshasa.
- Despite this diversity, this knowledge is erroneous at 60%, attitudes are negative at 75% and practices are not beneficial at 80%.
6. Authors’ Contribution
All authors contributed to the design, collection and analysis of data as well as the presentation of the final manuscript.