The age range (20-30years) is the most common (38.7%). (Figure 1)
Single were the predominant portion (47.8%) of the sample, followed by (44.4%) for married participants. (Figure 2)
University level education prevailed above other levels of education with 53.8%, followed by secondary school level with percentage of 29.9%. (Figure 3)
Currently unemployed was the most common work status with a total of 158 candidates (41%). The second were housewives who constituted 34.8% of my sample. (Figure 4)
The sample was distributed between Ummbadda’s locality (54.3%), and Omdurman’s locality (45.7%) for Omdurman’s. (Figure 5)
The majority of study subjects reported being of middle income class(83.6%), defined by the study as relying on more than 30,000 SDG and less than 150,000 SDG a month. (Figure 6)
Demographic data are shown in (Table 2).
According to findings on (Table .3), 30.6% of the candidates reported no knowledge of any BC Case in their social circle. The rest (215- 55.8%) knew someone with BC, with 79 candidates (20.5%) knew more than one person. The most prevalent answer between those who knew BC cases was “somebody you know” (19.8%), followed by a second degree relative (18.3%). 3.9% of the study subjects had breast cancer themselves and 1.5% preferred not to answer this question. (Figure 7)
As evident from (Table .4), the cumulative percentage of positive replies was only (42.8%). (35.7%) stayed neutral by acknowledging their lack of knowledge, and 21.5% actively stated that the signs are not related to BC. The most widely recognised sign was “ a lump or thickening in your breast” with 59.7% candidate replying with yes, followed by “ a lump or thickening under your armpit” and “ a change in the size of your breast” with 57.7% and 54.5%, respectively. The least recognized sign was a change in the position of your nipple (23.4%). Of the 11 signs tested, only 4 of them gained more than half agreement between the candidates.
Of the 9 risk factors measured, the responses to only a single question of the nine exceeded half of candidates (familial predisposition, 59.7%). Of all the remaining 8 replies less than half of the candidates positively accounted for them(with 6 of them being less than 30%). Most of the subjects confessed their poor knowledge of risk factors, 41.3% said they don’t know. The cumulative percentage of subjects who positively replied to the questions was only 30.7%. (Table .5)
A total of 172 (44.7%) replied with yes. This means that less than half of the candidates were aware of the screening program run by FMoH. (Figure 8). Of the 44.7% who replied positively to the previous question, none has replied correctly to the age at which women should start participating in such program- as per World Health Organization’s (WHO) recommendations of 50 years. 37.4% stated they don’t know the exact age.
(Table .6) (Table .7)
Only 6% answered correctly- in the age of 70 years, with an overwhelming majority of 102 participant (59.3%) acknowledging they don’t know. (Table .8)
The majority stated that they haven’t been invited before (78.4%). 5.5% didn’t know (remember) whether they have been invited, and only a minority of 16.1% said they have been invited to a screening program. (Table .9)
According to (Table .10) the majority of the participants have never been screened (84.7), only 10.1% claimed they have been screened before.
The majority of respondents didn’t reply positively to this question, 33.2% didn’t know what BSE is and 28.6% didn’t know the right method of BSE ( with a cumulative percentage of 61.8%). Only 38.2% knew the right method of BSE (Table .11)
Of the 38.2% who knew the right method BSE, 71 (48.3%) rarely or never engaged in BSE. This is followed by another 15% who practiced it only once every 6 months (a cumulative percentage of 63.3%). The percentage of those who practiced it at the recommended interval of once monthly or more was only 38.8% ( constituting only 14.1% of the study subjects). (Table .12)
This is an artefact, because although 76.9% responded they are, to some degree, confident they’d notice a change in breast tissue 71% of them were actually the ones who admitted that they rarely practiced BSE.
(Table .13)
Then I asked the latter group about the reason behind them not visiting the doctor. They gave various accounts, the most consistent of which were: 44.3% or 65 candidates said they didn’t seek medical consultation because they had unimportant issues. 35.5% said it was primarily because of financial limitations.
Based on (Table .14), 50.6% never noticed a change (which was the predominant reply). A significant proportion have stated that they noticed a change but didn’t seek medical consultation, and 11.2% have looked for medical advice after noticing a change in their breast tissue.
Most of the participants expressed their willingness to see a doctor in case they notice any change in their breast area(87.3%). (Table .15)
This was for Specific objectives analysis:
I. To test whether such knowledge is affected by the level of education of the candidates.
The p-value of the test was (0.005) which was less than the significance interval, indicating a positive association between the education level and awareness status. In line with that, the mean of postgraduates was the highest (2.0), followed by that of university students (1.9).
II. To assess the attitude of the participants towards changes in breast tissue.
Here, when specifically asked, 38.2% of participants responded that they did notice a change in their breasts at some point, but they never consulted a doctor. When again asked whether they are willing to consult a doctor in the future, 87.3% responded that they will. These are clearly contradicting statement and, in my opinion, can partially be explained by the data collector interviewing the being a medical student. (Table .16) (Table .17)
III. To measure the association between age and awareness status, if any.
To measure the association I used Pearson Correlation test to determine the relationship between them, and the strength and weakness of their relationship, and which direction that taken by this relationship. (Table .18)
IV. To determine if there is an association between length of stay in urban settings and awareness level:
To measure the association I used Pearson Correlation test to determine the relationship between them, and the strength and weakness of their relationship, and which direction that taken by this relationship. the association tested here was of no statistical significance (p-value=0.168, p= 0.05). (Figure 9)
V . To assess whether the level of awareness is affected by the candidate's history of contact with BC:
In order to assess the effect of contact with BC on knowledge related to breast cancer among females, I used ANOVE test to investigate this differentiation and to determine whether there is statistical significant difference. (Table .19)
There is a statistically significant effect on BC awareness (p-value= 0.001, p=0,05). The highest mean in the test was that of a close friend (2.2), thus the effect of contact with BC was clear on the current awareness status of the candidates.
VI. To determine if there is an association between Residence(Omdurman’s locality, Um Badda’s locality) and awareness level:
To measure the association I used Pearson Correlation test to determine the relationship between them, and the strength and weakness of their relationship, and which direction that taken by this relationship. (Table .20) (Figure 10)
Regarding the Pearson's Correlation between Residence and awareness, the association was not significant (Table .21)
Analysis of open ended questions:
I. Name as many early warning signs of BC as you can think of?
When asked to name as much warning signs of BC as possible, 212 (55.06%) said they don’t know any of those signs. Of the rest 77 (20%) succeeded to name only one correct sign, 9.1% named two correct signs, 6.7% (26 subjects) named three correct signs, 13 (3.6%) named four or five correct signs, and only 1 lady named six correct signs (0.26%). The rest (5.28%, 20 candidates) named incorrect signs. The most recognized sign was a lump in the breast or armpits which recurred 134 times(34.8%), followed bleeding or discharge from the nipple, change in the size of the breast, pain in the breast, redness or change in the colour of the breast skin, dimpling of breast skin, ulceration in the breast area, and a change in nipple position (57, 46, 40, 31, 22, 21, and 17 times respectively/ 14.8%, 11.95%, 10.4%, 8.05%, 5.7%, 5.45%, 4.4%), the least correct reported sign was weight loss, reported only 3 times (0.78%).
II. What things do you think affect a woman’s chance of developing breast cancer?
When I asked the participants to name some of the risk factors of breast cancer the results were as follows:
215 candidates (55.8%) couldn’t name any, of the rest, 69 (17.9%) succeeded to name a single correct risk factor, 8.3% named 2 correct risk factors, 13 respondents (3.5%) named 3 correct factors, and a minority (1.6%-6 respondents) named more than 3 correct factors. The remaining 13% gave false accounts. The most widely recognized risk factor was the familial predisposition which occurred in 76 (19.7%) of my data, followed by obesity and unhealthy eating (22- 6%), radiation exposure (16- 4.1%). Lack of breast feeding, and alcohol consumption got 11 each (2.8%), while only 6 candidates identified smoking as a risk factor. Some other correct risk factors were identified but in an insignificant minority.
Chi-Square statistical analysis was performed to infer the general direction of the study, From the table above, general features had significance in all items in confidence interval 0.05.
The proportion of answers from 1 to 12,had three dimensions in each question( yes, no, don't know), a mean for majority ranged between (2 -2.4) among items included in the indexes, is a clear tendency to (don't know) answers (looks at the frequency table). According to triple Likert scale the range should be between (1.67 - 2.33 Neutrality).
In items from 13-22 the mean ranged between (1.7-2.3), also ranged on Neutrality (which is in this case “don’t know”) according to triple Likert scale. (Table .22)