Examining the Impact of Health Education Interventions on Breast Cancer Knowledge (Awareness) Among Women in Underserved Communities of West Coast Region, The Gambia

doi:10.21203/rs.3.rs-4369920/v1

Background

The burden of breast cancer among women in the underserved areas continue to remain high despite availability of modern screening and diagnosis facilities. It is believed that most women have limited access to such services due to limited awareness on breast cancer signs and symptoms, risk factors and screening services thus leading to a late-stage detection of the condition in many. This research seeks to address this gap by examining the impact of health education interventions on breast cancer knowledge and awareness among women aged 25 years and above in underserved communities of West Coast region of the Gambia and highlight associated barriers.

Methods

A cross-sectional study was conducted involving 315 women from two Urban and two Peri-Urban communities (Western Health Region 2) of the West Coast region of the Gambia. We administered an adopted structured questionnaire using face to face interviews in pre and post health education intervention in a 3-month interval. To evaluate the effect of the intervention, the mean knowledge score after three months was compared with the baseline phase using a paired sample t-test, Pearson chi square, binary and multiple logistic regression analyses. The differences in the means were compared and the knowledge enhancement percentage was established.

Results

The participants knowledge improved from 16.5% before the intervention to 61.3% after the intervention on the 20 points knowledge and awareness item including signs and symptoms, and risk factors of breast cancer. The paired sample t-test reveals that participants knowledge has improved in all the various dimensions of the assessment with a general increase from pre (M = 6.08; SD = ± 3.35) to Post (M = 13.34; SD = ± 5.33) at the 0.05 level of significance, t(-24.2) = 5.23, n = 305, p < 0.05, [95% CI: -6.67,-7.85]. There was a statistically significant association between sociodemographic variables and the increase in the knowledge score. Participants from urban and peri-urban have different options of public health education measures suitable for such intervention in underserved communities.

Conclusions

The use of health education intervention was very effective in improving breast cancer knowledge and awareness among women living in underserved communities despite so many challenges. Lack of information and cultural belief or stigma remains as major barriers to breast cancer awareness.

Awareness

Breast cancer

Health education

Intervention

Knowledge

Women

Breast cancer is a global health concern that transcends geographical, socioeconomic, and cultural boundaries. According to the World Health Organization (WHO), breast cancer is the most common cancer among women worldwide, affecting both high-income and low-income countries. In 2020 alone, there were an estimated 2.3 million new cases of breast cancer, making it a significant contributor to cancer-related morbidity and mortality (1). Breast cancer is the most prevalent cancer among women worldwide, accounting for nearly one in four cancer cases diagnosed in women, and remains one of the leading causes of cancer-related deaths worldwide(2). Its pervasive impact is not limited to affluent nations; breast cancer knows no borders and affects individuals across all demographic and socioeconomic backgrounds (3). However, regional disparities within countries, especially among underserved communities, persist in the diagnosis and outcomes of breast cancer (4). Breast cancer is not only diagnosed in elderly women but also among women as young as 25 years of age and problems such as reproductive history, genetics, physical inactivity and overweight or obesity after menopause are contributory factors of breast cancer in both high- and low-income countries. (5)

Despite advancements in early detection methods and effective treatment protocol, the impact of breast cancer remains profound, touching the lives of millions of individuals and their families. Breast cancer is a disease in which abnormal breast cells grow out of control and form tumours. If left unchecked, the tumours can metastasize and become fatal. Breast cancer cells begin inside the milk ducts and/or the milk-producing lobules of the breast. The earliest form (in situ) is not life-threatening. Cancer cells can spread into nearby breast tissue (invasion), which creates tumours that cause lumps or thickening. (6). The Centre for Disease Control (CDC) of the United States highlighted the following symptoms of breast cancer; a new lump in the breast or underarm, change in size, shape or appearance of the breast, Pain in any area of the breast, dimpling, redness, pitting or other changes in the skin, change in nipple appearance or the skin surrounding the nipple (areola) and abnormal or bloody fluid from the nipple(7).

Many factors over the course of a lifetime can influence breast cancer risk. Some factors cannot change such as getting older or family history, but individuals can help lower the risk of breast cancer and improve chances of surviving cancer if it occurs, by screening and staying healthy throughout ones life (7). While significant progress has been made in diagnosing and treating breast cancer over the years, disparities in breast cancer outcomes persist among various populations (8). Underserved communities, characterized by limited access to healthcare resources, economic disparities, and often marginalized social status, bear a disproportionate burden of this disease (9). Findings from a breast cancer awareness study among future health professionals in Ghana demonstrated moderate awareness of the modalities of breast cancer screening and the risk factors of breast cancer among the students. However, there exists a gap between awareness and practice of breast cancer screening, which was assume to be influenced by optimism in breast cancer risk perception and religion(10). In a study on barriers to early presentation of breast cancer among women in Soweto, South Africa reveals that limited patient education, breast cancer knowledge and awareness, and health system inefficiencies were associated with advanced stage at diagnosis and recommended that sustained community and healthcare worker education may down-stage disease and improve cancer outcomes(11).

A community-based study in a low socio-economic area of Mumbai in India reveals that women who were aware of breast cancer considered lump in breast (75%), change in shape and size of breast (57%), lump under armpit (56%), pain in one breast (56%) as the important and common symptoms. Meanwhile, less than one-fifth of the women who were aware of breast cancer reported early menstruation (5.6%), late menopause (10%), hormone therapy (13%), late pregnancy (15%) and obesity (19%) as the risk factors for breast cancer. (12)

In the Gambia, Breast cancer screening is mainly performed through clinical breast examination and is available in 52 facilities. Seven facilities provide pathologic diagnosis and surgical management of breast cancer. The proportion of the Gambian population with access to screening, pathologic diagnosis, and surgical management is 72, 53, and 62%, respectively (13). The spatial analysis found that 72% of The Gambian population lives within 10 km of breast cancer screening with clinical breast examination (CBE) but due to limited awareness, screening uptake remains challenging (13). Longer distances to diagnostic and treatment facilities have been associated with delayed diagnosis and late stage at diagnosis in sub Saharan Africa (14).

Health education interventions play a central role in bridging the gap between underserved communities and breast cancer awareness, knowledge, and screening practices(15). These interventions encompass a wide range of activities, including community workshops, educational campaigns, culturally sensitive materials, and collaborations with healthcare providers(16).

In a cervical cancer screening uptake study at selected health centers in Addis Ababa, it was concluded that providing focused health education supported by printed educational materials increased the uptake of cervical cancer screening services by 74%. Similarly, Integrating one-to-one health education and providing a take-home educational material into the existing maternal and child health services can help increase cervical cancer screening uptake(17)

This is an intervention study aimed at analysing the effects of health education on women’s knowledge and awareness on breast cancer in the Gambia, because less attention is given to breast cancer in the routine health services. It remains challenging to give correct and real time statistics due to limited research in the area couple with concentration of efforts on the prevention of other cancers such cervical and liver cancers. The intersection of these factors creates formidable barriers to early detection and appropriate care. To address these disparities, there is a pressing need to examine the impact of health education interventions for underserved communities. In this comprehensive exploration, we examined the impact of health education interventions on breast cancer knowledge and cultural practices within underserved communities. This research sought to unravel the impact of these interventions, uncovering strategies to bridge the knowledge gap, reduce barriers, and promote proactive health behaviors.

Study Design and Population

A cross-sectional study was conducted from July 2023 to December 2023 to comprehensively examine the impact of health education interventions on enhancing breast cancer knowledge and awareness among women in these communities. The study applied quantitative research approach and primarily involved women aged 25 and above within underserved communities who are at risk of experiencing disparities in breast cancer knowledge and awareness. Four communities were selected for this study, two from Urban area (Brikama Wellingara and Brikama Gidda) and two from peri-urban area (Pirang and Faraba) of Western Health Region 2. The participants were asked for their ages during enrolment into the study.

Study Area

The Western Health Region 2 is the biggest health region in the country with a projected population of 514,999 in the year 2023 and an annual population growth rate of 5.7% (GBOS, 2013). It has seven (7) basic health facilities, thirteen (13) community clinics, twelve (12) Non-Governmental Organization (NGO) or faith-based health facilities, and seven (7) private health facilities. The region stretches from Busumbala to Kalagi, along the trans Gambia highway.

Sample Size

It has been almost a decade since the last census of the Gambia was conducted and the exact denominator was unknown for the study population. To obtain the sample size for this study we used Cochran’s single proportion formula to get the desired level of precision, confident level, and the estimated sample size for the study.

The formula is denoted as:

n = z² pq/d²,

Where n = sample size, z = z-score at 95% confidence level, p = estimated proportion of an attribute that is present in the population, q = 1-p, d = margin of error. This study assume a margin of error(d) of 0.05 at 95% confidence level and an estimated proportion of 73% women aware of breast cancer (10). A total of 300 participants was obtained and a non-response rate of 5% was adjusted, approximately 315 participants was randomly selected from the total population of women.

Sampling Technique

A multi-stage simple random sampling techniques was used. Firstly, two districts were randomly selected from the 8 districts in the health region and subsequently two communities from each district. These communities were put on strata based on the Gambia’s enumeration area and the required number of participants were randomly selected from these communities. We got to the center of each selected community, spin a bottle, and start with the compound that the bottle pointed. We got into the compound and ask for all women aged 25 years and above. One woman is randomly selected in each compound based on the inclusion criteria. Thereafter, we consecutively enter compound on the right-hand side of the selected compound and the process continues until a required number was achieved. This technique was used to ensure that all communities are well represented in the study.

Description of processes

In this study a structured questionnaire was administered using face to face interviews in pre and post health education intervention. A health education intervention was conducted within 3 months after the baseline data collection in the target communities. Both at the baseline and three months post-intervention, breast cancer knowledge and awareness was measured to assess the impact of the intervention.

The questionnaire consists of both closed-ended and open-ended questions. It was adopted from previously published studies and is divided into the following parts: Demographic information, Breast Cancer Knowledge, Cultural barriers to breast cancer knowledge and health education intervention that can enhance breast cancer knowledge and screening uptake.

The data collection was done through administration of questionnaire by the research assistants. Women were targeted during their monthly clinic visits and information is sent to the participants through telephone calls and community agents including those who are not attending clinics but are already part of the participants to meet the data collectors at the meeting point within the clinic duration. The consent statement is first read and clearly explained to the participants and privacy and confidentiality were ensured. Each participant was given an identifier and a contact number was collected for follow-ups, if necessary, but were asured that it will be deleted once the post data collection is completed. The principal investigator was always around to monitor the interview process and clarified any doubt or questions. Each interview lasted for approximately 20 minutes. The researcher work with the district public health officers in the areas to facilitated the implementation of the whole exercise.

Outline of the Health education intervention

The educational intervention approach was customized and adopted from a study protocol for a cluster-randomized controlled trial on the effectiveness of an educational intervention of breast cancer screening practices uptake, knowledge, and beliefs among Yemeni female school teachers in Klang valley, Malaysia. (15).

Below is an outline of the educational intervention on breast cancer knowledge (BCK) along with the application of the Health Belief Model (HBM) concepts in the educational intervention. The educational intervention consists of four units.

Unit One provides general information on the anatomy and physiology of a normal breast for the participants to have a clear understanding of the topic.

Unit Two gives information and knowledge of BC. It further explores BC symptoms, BC stages, BC risk factors to increase the participants’ knowledge of BC.

Unit three explains the barriers to BCA and BSE procedure to understand the barriers that hinders BCA and raise the participants’ awareness of BC symptoms and motivate them to follow this procedure.

Unit four emphasizes communication and its different methods, the merits and demerits were emphasized in a bid to improve their awareness and encourage participants to contextualize the different types.

The educational intervention was sent to some experts in health communication and academics. The experts approved the educational material as efficient and reliable. Their feedback focused on the comprehensibility and simplicity of the content which was adjusted by the researcher with the help of a language translator who was conversant with different local languages in the Gambia. The researcher with the help of four trained assistants, conducted the session for the intervention at each of the four communities. One session was carried out in each community monthly. The implementation date differs from one community to another, but the duration time remains the same. Below is the breakdown of the intervention procedures conducted.

(a) A forty-five minutes PowerPoint presentation was delivered with a five minute video on breast anatomy and physiology, risk factors of breast cancer, sign and symptoms, preventions etc .

(b) A thirty-minute training session on BSE practice using female research assistant who uses pictures and demonstration. During this session, participants were thought on palpation techniques and ways to search as well as signs and symptoms that one needs to note when doing self-breast examination. Participants were asked to perform the practice by following the steps given by the facilitators.

(c) A fifteen-minute session was held on communication and its different types including their advantages and disadvantages.

(d) A thirty-minute session for doubt clearing and sharing of copy of the relevant booklet containing all the information delivered to them in the educational intervention and given of a BC logo sticker to be hung on the participants’ room.

(e) The subsequent two months intervention only lasted for an hour in each community as a refresher training to the participants using power point and video play. For consistency in the educational intervention, the researcher uses the same facilitators in each of the study communities and the same protocol was used throughout. This protocol was adopted and customized from protocol for a cluster-randomized controlled trial on the effectiveness of an educational intervention of Breast cancer screening practices uptake, knowledge, and beliefs among Yemeni female school teachers in Klang valley, Malaysia (15).

Statistical Analysis

A database was established using the IBM SPSS statistical software. Paired sample t-test was used to compare the mean baseline and post-intervention breast cancer knowledge scores, while a Pearson chi square was used to assess the association between categorical variables., Binary logistic regression was used to assess the associations between sociodemographic variables and knowledge level and variables with p-values less than 0.25 (25%) were considered for the multiple regression analysis. The multiple logistic regression analyses were done to assess the predictors of knowledge on breast cancer.

Scoring scheme was used and the Knowledge of breast cancer were assessed by requesting the respondents to answer questions included in the questionnaire. Twenty questions sum up to measure the knowledge of participants including basic knowledge about breast cancer, sign and symptoms, and risk factors of breast cancer. Each correct response (“yes”) was scored one (1) point, and each wrong response (“no”) was scored zero (0) thus a maximum score was 20. Respondents with score 0–10 points were considered to have a poor knowledge in this study and those with 11–20 points were considered to have a good knowledge.

Socio demographic characteristics of research participants.

As shown in Table 1, a total of 315 women were involved in the study and only 305 completed the post intervention data collection and 10 were lost to follow-up. Many of the participants (84.8%) fall within the age cohort of 25 to 44 and the mean age was 34.29 with a staandard deviation of ± 9.7 years. Among the participants, 160 (50.8%) were from the Peri-Urban area and 155(49.2%) were from the Rural area of the West Coast Region. The Mandinka ethnic group represent the large proportion of the participants (51.7%) followed by Fula ethnic group (20%). The Serer and Sarahuli ethnic groups form the lowest number of participants with a proportion of 3.2% and 2.2% respectively. On the educational level, 24.8% of them attended primary level education, 14.0% completed junior secondary level, 35% completed senior secondary level, 21.9% obtained a college level certificate and 4.1% obtained post-graduate degree level. More than half of the participants (67.3%) are married and only 30.8% are single and 1.9% of them are either widowed or divorced. Almost half of the participants’ monthly earning fall below GMD 10,000 and 16.2% of them earned more than GMD 20,000 per month. Majority (41.6%) of the participants were housewives and about a quarter of them were businesswomen.

Table 1

Socio demographic characteristics of research participants.
Variables	Number	Percentage
Age
25–34	212	67.3
35–44	55	17.5
45–54	34	10.8
55>	14	4.4
Name of Community
Peri-Urban
Nyambai &Wellingara	80	25.4
Gidda & Darsilameh	80	25.4
Rural
Faraba	78	24.8
Pirang	77	24.4
Ethnicity
Fula	63	20.0
Jola	35	11.1
Mandinka	163	51.7
Manjako	13	4.1
Sarahuli	7	2.2
Serer	10	3.2
Wollof	24	7.6
Educational Status
Postgraduate	13	4.1
College	69	21.9
Senior school	111	35.2
Junior school	44	14.0
Primary school	78	24.8
Marital Status
Married	212	67.3
Single	97	30.8
Divorced	2	.6
Widowed	4	1.3
Household Income
<D10,000	149	47.3
D10,000–20,000	115	36.5
>D20,000	51	16.2
Occupation
Business	78	24.8
Civil Servant	49	15.6
Farmer	10	3.2
Housewife	131	41.6
Student	26	8.3
Others	21	6.7

Pre and Post Intervention Knowledge level of participants

The data collected from pre-intervention and post-intervention were tabulated to investigate the effectiveness of health education intervention on Breast Cancer awareness. Table 2 depicts the overall score for both test and the participant’s performance were classified into two categories: good and poor. Generally, the participants knowledge has improved remarkably after the intervention. 61.3% of participants achieved good performance in the post intervention as opposed to only 16.5% of participants in the pre-intervention. 3.2% did not participate in the post intervention data collection and their awareness level could not be established.

Table 2

Frequency Distribution of Pre and Post Intervention Knowledge level of participants
		Pre-Intervention		Post-Intervention
Grade	Mark	Number	Percent	Number	Percent
Poor Knowledge	0–10	263	83.5	112	35.5
Good Knowledge	11–20	52	16.5	193	61.3
Missing Data		0	0	10	3.2
Total		315	100.0	315	100.0

Comparison of Pre-Intervention and Post-Intervention Knowledge Score showing Enhancement across Different Demographic Variables

From the data on knowledge enhancement, the age cohort 35–44 shows the highest (49%) change in average knowledge score while age 25–34 shows the lowest (33%). Ethnic minorities (Sarahuli and Serere) registered more enhancement (49% and 46% respectively) in the awareness and knowledge while both the largest (Mandinka) and second largest (Fula) ethnic groups show a lower enhancement (37% each). Educational status was enhanced by (30%) among those who attained senior secondary level, (43%) by those who attained College Level and (48%) by those who attained post graduate level. The widowed and divorced has an enhancement of (48%) and (51%) respectively while the married and single has an enhancement of (35% and 38%) respectively. In terms of occupation, civil servants have the highest enhancement (43%) followed by the student category (41%) and the lowest enhancement was registered among farmers (34%) and housewives (32%). The knowledge enhancement improves as the household income improves from 30% among those who earned less than D10000 to 40% among those who earned D10000 - D20000 and 46% among those who earned more than D20000.

Table 3

Comparison of Pre-Intervention and Post-Intervention Knowledge Score showing enhancement across different Demographic variables
Variables		Pre-Intervention		Post-Intervention			Enhancement
		Mean	Mean (%)	Mean		Mean (%)
Age Category	25–34	6.5	32	13.1	65.4		6.6	33
	35–44	4.9	24	14.6	73.0		9.7	49
	45–54	6.7	33	13.5	67.6		6.9	34
	55>	5.3	26	12.1	60.4		6.8	34
Ethnicity	Fula	6.7	33	14.1	70.3		7.4	37
	Jola	5.5	28	11.5	57.4		5.9	30
	Mandinka	6.3	32	13.6	68.1		7.3	37
	Manjako	5.9	30	13.4	66.9		7.5	37
	Sarahuli	4.4	22	14.1	70.7		9.7	49
	Serere	5.9	30	15.1	75.6		9.2	46
	Wollof	5.4	27	11.5	57.7		6.2	31
Educational Status	Post_Gra	6.7	33	16.4	81.9		9.7	48
	College	9.0	45	17.5	87.5		8.5	43
	Senior_S	6.1	31	12.1	60.4		6.0	30
	Junior_S	5.8	29	11.8	59.0		6.0	30
	primary	3.8	19	11.8	59.0		8.0	40
Marital Status	Married	5.5	28	12.5	62.3		7.0	35
	Single	7.6	38	15.2	75.8		7.6	38
	Widowed	6.0	30	16.3	81.3		10.3	51
	Divorced	4.0	20	13.5	67.5		9.5	48
Occupation	Business	6.5	32	13.7	68		7.2	36
	Civil Servant	9.0	45	17.6	88		8.6	43
	Farmer	5.7	29	12.5	63		6.8	34
	Housewife	4.5	23	11.0	55		6.5	32
	Others	7.0	35	14.4	72		7.4	37
	Student	7.5	37	15.7	79		8.3	41
Household Income	< 1000	5.6	28	11.5	57		5.9	30
	10000–20000	6.6	33	14.6	73		8.0	40
	> 20000	6.9	34	16.1	81		9.2	46

Relationship between Knowledge and Socio-demographic Variables at Pre-Intervention stage using Binary and Multiple Logistic Regression Analysis

The result of the multiple logistic regression (Table 4) highlighted that several socio-demographic variables show some subcategories such as age (35–45), education status (college level), occupation and household monthly income been significantly associated with the pre-intervention knowledge and awareness about breast cancer. Women of age 35 to 40 were more likely to have a good knowledge about breast cancer than those between 25 to 34 [AOR: 5.19, 95% CI: (1.392–19.353)]. Women who obtained college level education has an odd of [AOR: 0.072, 95% CI: (0.03–0.418) compared to those with primary level education. Similarly, several occupations such as business, housewife, student, and others were all likely to have a better knowledge about breast cancer than those whose occupation is farming. Household income between 10,000 and 20,000 were almost 3 times more aware [AOR: 2.983, 95% CI: (1.248–7.129)] of breast cancer than those whose household income was less than D10,000. There was no significant association between the pre-intervention knowledge of women and their marital status and ethnicity.

Table 4: Relationship between Knowledge and Socio-demographic Variables at Pre-Intervention stage using Binary and Multiple Logistic Regression Analysis, N=315

Variable	Knowledge N (%)		Pre-Intervention
	Knowledge N (%)		COR	95% Confidence Interval		P-value	AOR	95% Confidence Interval		P-value
	Good	Poor		Lower	Upper			Lower	Upper
				Lower	Upper			Lower	Upper
Age (years)
25-34	40 (76.9)	172 (65.4)								Ref
35-44	03 (5.8)	52 (19.8)	4.031	1.198	13.566	.024*	5.190	1.392	19.353	.014*
45-54	07 (13.5)	27 (10.3)	.897	.365	2.206	.813	1.201	.387	3.725	.751
≥55	02 (3.8)	12 (4.6)	1.395	.300	6.483	.671	.752	.104	5.458	.778
Ethnicity
Mandinka	28 (53.8)	135 (51.3)				Ref				Ref
Fula	14 (26.9)	49 (18.6)	.726	.353	1.491	.383	1.293	.522	3.203	.578
Wolof	03 (5.8)	21 (8.0)	1.452	.405	5.203	.567	2.197	.504	9.571	.295
Jola	02 (3.8)	33 (12.5)	3.422	.776	15.097	.104	3.845	.785	18.842	.097
Others	05 (9.6)	25 (9.5)	1.037	.365	2.942	.946	1.438	.391	5.292	.584
Educational Status
Primary school	00 (0.0)	78 (29.7)				Ref				Ref
Junior secondary	05 (9.6)	39 (14.8)	7.800	3.074	19.789	.000*	.297	.060	1.470	.137
Senior secondary	11 (21.2)	100 (38.0)	9.091	4.878	16.943	.000*	.313	.068	1.442	.136
College	34 (65.4)	35 (13.3)	1.029	.642	1.650	.904	.072	.013	.418	.003*
Post-graduate	02 (3.8)	11 (4.2)	5.500	1.219	24.813	.027*	.273	.031	2.408	.242
Marital Status
Married	21 (40.4)	191 (72.6)				Ref				Ref
Single	30 (57.7)	67 (25.5)	2.233	1.452	3.435	.000*	.595	.246	1.437	.248
Divorced/Widowed	01 (1.9)	05 (1.9)	5.000	.584	42.797	.142	1.247	.080	19.355	.875
Occupation
Farmers	00 (0.0)	10 (3.8)				Ref				Ref
Business	10 (19.2)	68 (25.9)	6.800	3.501	13.207	.000*	12.441	2.544	60.841	.002*
Civil Servant	24 (46.2)	25 (9.5)	1.042	.595	1.824	.886	4.172	.651	26.725	.132
Housewife	07 (13.5)	124 (47.1)	17.714	8.273	37.932	.000*	20.076	5.003	80.560	.000*
Students	07 (13.5)	19 (7.2)	2.714	1.141	6.457	.024*	12.125	1.707	86.137	.013*
Others	04 (7.7)	17 (6.5)	4.250	1.430	12.630	.009	21.202	2.730	164.635	.003*
Household Monthly Income
<10,000	24 (46.2)	125 (47.5)				Ref				Ref
10,000 – 20,000	17 (32.7)	98 (37.3)	1.107	.563	2.174	.768	2.983	1.248	7.129	.014*
>20,000	11 (21.2)	40 (15.2)	.698	.314	1.550	.377	1.975	.715	5.455	.189

N = Frequency, COR = Crude Odds Ratio, AOR = Adjusted Odds Ratio * P-Value Significant at ≤0.05

Table 5: Relationship between Knowledge and Socio-demographic Variables at Post-Intervention stage using Binary and Multiple Logistic Regression Analysis, N=305

Variable	Knowledge N (%)						Post-Intervention
	Knowledge N (%)		COR	95% Confidence Interval		P-value	AOR	95% Confidence Interval		P-value
	Good	Poor		Lower	Upper			Lower	Upper
				Lower	Upper			Lower	Upper
Age (years)
25-34	125 (64.8)	79 (70.5)				Ref				Ref
35-44	40 (20.7)	14 (12.5)	.350	.190	.643	.001*	.303	.142	.648	.002*
45-54	21 (10.9)	12 (10.7)	.571	.281	1.161	.122	.783	.322	1.903	.589
≥55	7 (3.6)	7 (6.3)	1.000	.351	2.851	1.000	1.754	.377	8.172	.474
Ethnicity
Mandinka	107 (55.4)	51 (45.5)				Ref				.Ref
Fula	41 (21.2)	19 (17.0)	.463	.269	.798	.006*	1.103	.506	2.405	.805
Wolof	10 (5.2)	14 (12.5)	1.400	.622	3.152	.416	3.561	1.100	11.525	.034*
Jola	17 (8.8)	17 (15.2)	1.000	.511	1.959	1.000	1.165	.469	2.893	.742
Others	18 (9.3)	11 (9.8)	.611	.289	1.294	.198	2.272	.830	6.223	.110
Educational Status
Primary school	38 (19.7)	37 (33.0)				Ref				Ref
Junior secondary	23 (11.9)	21 (18.8)	.913	.505	1.650	.763	1.389	.567	3.407	.472
Senior secondary	58 (30.1)	48 (42.9)	.828	.565	1.213	.332	1.374	.651	2.900	.404
College	63 (32.6)	4 (3.6)	.063	.023	.174	.000*	.209	.049	.890	.034*
Post-graduate	11 (5.7)	2 (1.8)	.182	.040	.820	.027	.406	.068	2.436	.324
Marital Status
Married	115 (59.6)	91 (81.3)				Ref				Ref
Single	73 (37.8)	20 (17.9)	.274	.167	.449	.000*	.812	.334	1.970	.644
Divorced/Widowed	5 (2.6)	01 (0.9)	.200	.023	1.712	.142	.197	.017	2.306	.196
Occupation
Farmers	6 (3.1)	04 (3.6)				Ref				Ref
Business	50 (25.9)	24 (21.4)	.480	.295	.781	.003*	1.138	.449	2.886	.785
Civil Servant	45 (23.3)	02 (1.8)	.044	.011	.183	.000*	.250	.040	1.566	.139
Housewife	53 (27.5)	74 (66.1)	1.396	.981	1.987	.064*	1.998	1.013	3.943	.046*
Students	23 (11.9)	03 (2.7)	.130	.039	.434	.001*	.515	.097	2.747	.437
Others	16 (8.3)	05 (4.5)	.313	.114	.853	.023*	.665	.142	3.111	.604
Household Monthly Income
<10,000	69 (35.8)	78 (69.6)				Ref				Ref
10,000 – 20,000	83 (43.0)	26 (23.2)	.313	.202	.487	.000*	.335	.177	.631	.001*
>20,000	41 (21.2)	8 (7.1)	.195	.091	.416	.000*	.192	.074	.500	.001*

N = Frequency, COR = Crude Odds Ratio, AOR = Adjusted Odds Ratio * P-Value Significant at ≤0.05

Relationship between Knowledge and Socio-demographic Variables at Post-Intervention stage using Binary and Multiple Logistic Regression Analysis

The result of the Multiple Logistic Regression has revealed that the post intervention knowledge on breast cancer has a significant association with at least one sub-category of all the socio-demographic variables except for marital status. Women of age 35 to 40 were more likely to have a good knowledge about breast cancer than those between 25 to 34 [AOR: 0.303, 95% CI: (0.142–0.648)]. Women who obtained college level education has an odd of [AOR: 0.209, 95% CI: (0.049–0.890) compared to those with primary level education. Being a housewife has an odd of [AOR: 0.064, 95% CI: (1.998–1.013)] compared to women who are farmers. Monthly household income influences the knowledge level in the post intervention study. However, household income between 10,000 and 20,000 were [AOR: 0.335, 95% CI: (0.177–0.631)] and household income of over D20,000 where [AOR: 0.192, 95% CI: (0.074-0.500)] compared to those whose household income was less than D10,000.

Effectiveness of the Health Education Intervention (A paired Sample T-Test of Participants knowledge in Pre and Post Intervention)

A paired sample t test was conducted to determine if the participants knowledge has improved or declined after the health education intervention. The test was performed on five different dimensions on breast cancer knowledge and awareness and one general aspect that represents all the other dimensions. The five different dimensions include: basic knowledge about breast cancer, knowledge about breast cancer screening and self-breast examination, participation in breast cancer program, knowledge about breast cancer sign and symptoms, and knowledge about breast cancer risk factors.

From the data collected, the test reveals that participants knowledge has improved in all the various dimensions of the assessment with a general increase from pre (M = 6.08; SD = 3.35) to Post (M = 13.34; SD = 5.33) at the 0.05 level of significance, t(-24.2) = 5.23, n = 305, p < 0.05, [95% CI: -6.67,-7.85]

Public Health Education Measures Preferred by Participants in Urban

and Peri-Urban Communities.

This exploration is meant to identify best strategies preferred by communities to tailor health education interventions to better meet the unique needs of underserved communities. Percentages and totals are based on responses and the dichotomy group was tabulated at value 1.

Majority of the participants from peri-urban communities selected sharing of pamphlets or brochures (58.3%) and making videos or multimedia presentation (51.2%) while majority of those from the Urban setting selected organizing workshops or community-based activities and the use of social media campaigns through WhatsApp, Facebook and tik-tok. Only few responses were received on the use of podcast from both settings.

Table 7

Public Health Education Measures Preferred by Participants in Urban and Peri-Urban Communities.
Public Health Education Measures	Urban		Peri-Urban
	Number	Percentage	Number	Percentage
Sharing Pamphlets or Brochures	25	41.7%	35	58.3%
Videos or multimedia Presentation	145	48.8%	152	51.2%
Organize workshops or community events	264	56.3%	205	43.7%
Social media campaigns	121	52.8%	108	47.2%
Podcast	2	50.0%	2	50.0%
Total	557		502
Note: multiple options were allowed leading to percentages been more than 100%

Perceived Barriers to Breast Cancer Awareness and Screening Services

This analysis delves into identifying the barriers that hinder the implementation of health education programs within underserved communities. Many participants reported Lack of information or awareness as the major barriers to breast cancer awareness and screening services with 51.3% from the Peri-urban residents and 48.7% from the Urban residents. Similarly, the second highest response was on cultural belief or stigma with majority of the responses from the Peri-Urban settlers (59.3%) and the remaining from urban settlers. The participants’ responses on other barriers were very minimal when compared to the two stated above as shown on the table below.

Table 8

**Perceived Barriers to Breast Cancer Awareness and Screening Services**
Perceived Barriers to Breast Cancer Awareness and Screening Services	Urban		Peri-Urban
	Number	Percentage	Number	Percentage
Lack of information or awareness	91	48.7%	96	51.3%
Financial Constraints	3	50.0%	3	50.0%
Language Barriers	1	100.0%	0	0.0%
Cultural Beliefs or Stigma	44	40.7%	64	59.3%
Fear or Anxiety About Screening	14	45.2%	17	54.8%
Lack of Access to Healthcare Facilities	0	0.0%	3	100.0%
Transportation Issues	0	0.0%	5	100.0%
Total		153	188

Participants Awareness about Breast Risk Factors in Pre and Post Intervention data Collection.

Consistently, the data shows an increase in the participant awareness on the risk factors of breast cancer from the pre-intervention data collection (M = 56.14; SD = 66.79) to post-intervention data collection (M = 169.85; SD = 41.67). Family history and alcohol drinking were found to be the highest attributable risk factors mentioned by participants (N = 241 and N = 212 respectively) after the intervention. The largest increase was the number who cited alcohol as a risk factor from 43 responses in the pre-intervention data collection to 212 responses in the post-intervention data collection with a difference of 169 responses. Women who had good knowledge where been able to mention menopause at late age, no parity or late childbirth and menarche at age before 12 as other risk factors (149, 143, and 124 respectively)

Participants Awareness about Breast Cancer Signs and Symptoms Pre and Post Intervention data Collection.

The chart below shows an increase in participants knowledge on breast cancer sign and symptoms with a large number been able to recall Local discomfort in the breast (n = 230) followed by lump in the breast (n = 200), Nipple discharge liquid (n = 183), Nipple retraction (n = 178) and Axillary nodes (n = 169). The number who were been able to cite other symptoms such as dimpling, scaling, flaking and redness has also increased from 58 in the pre intervention data collection to 139 in the post intervention data collection.

The impact of health education interventions on breast cancer knowledge and awareness and cultural acceptable practices within underserved communities were explored in this study.

The overall knowledge score was very low in the baseline across all categories with few exceptions and only 16.5% manifested good knowledge. This study is in consonance with a similar studies conducted in Eastern China in which 18.6% of women aged 25–70 years had poor awareness of breast cancer (18). Similarly, this study’s findings concur partly with the southwest Ethiopian study in which more than 80% of the study participants did not know about breast cancer and BSE. Young adult women were less concerned about breast cancer and had insufficient knowledge of breast cancer and breast self-examination. (19). It is important to note that women in the above study were not expose to any health education intervention and the information given is only based on the baseline data.

The knowledge and awareness level has remarkably improved from 16.5% at the baseline to 61.3% after the health education intervention across all the participants. This increase in knowledge score was associated with the health education interventions conducted within 3 months after the baseline. Furthermore, women who worked as civil servants has a better knowledge score in records with a mean percentage enhancement from 45% in the preintervention to 88% in the post intervention. The plausible explanation for this is that many working-class women in the Gambia often attend clinics in private facilities or special clinic days in public facilities where they had the opportunities to interact and obtained adequate health information from service providers. Therefore, this working-class women’s interaction with service providers in special clinic days coupled with this study’s educational intervention potentially produced a synergistic effect on their knowledge of breast cancer.

Consistently, this study showed an increase mean score in the participants awareness on the risk factors of breast cancer from the pre-intervention data collection to post-intervention data collection. Overall, post-intervention data shows that many participants highlighted family history and alcohol drinking as highest risk factors responsible for increase in breast cancer. Many Gambians do understand that diseases are related to “blood” which in the scientific context means the genetic/family history. The largest increase was the number who cited alcohol as the highest risk factor from 43 responses in the pre-intervention data collection to 212 responses in the post-intervention data collection with a difference of 169 responses. A Muslim-dominated country, where alcohol consumption is shunned, it is easy to convince not only the study participants, so also the general population, about the negative associations between alcohol and non-communicable diseases. Therefore, this post-intervention increases in knowledge score regarding alcohol consumption and the increased risk of breast cancer is not very surprising. However, this findings are in agreement with those from the Eastern China studies were family history of breast cancer was the best accepted risk factor for breast cancer among participants (18). Although there was a general post-intervention improvement in the participants’ knowledge on the risk factors for breast cancer, less that 50% of them agreed that menopause at late age, no parity or late childbirth and menarche at age before 12 increases the risk of breast cancer.

The post-intervention data analysis showed an increase in participants knowledge on breast cancer sign and symptoms, a finding in consonance with a community-based study held in Mumbai, India, in which between 56% and 75% of the participants indicated lump in breast, change in shape and size of breast, lump under armpit, and pain in one breast as important and common symptoms (12).

The multiple logistic regression results showed that knowledge and awareness level of breast cancer was associated with participants’ age, educational level, occupation, and household income. Women aged 35 to 40 were more likely to have a good knowledge about breast cancer compared to the reference category aged 25 to 34 [AOR: 0.303, 95% CI: (0.142–0.648)]. Women who obtained college level education has an odd of [AOR: 0.209, 95% CI: (0.049–0.890) compared to those with primary level education. Monthly household income also influences the knowledge level in the post intervention study and household income between D10,000 and D20,000 were [AOR: 0.335, 95% CI: (0.177–0.631)] and household income of over D20,000 where [AOR: 0.192, 95% CI: (0.074-0.500)] compared to those whose household income was less than D10,000. This is similar to a study conducted in China where a multivariate analysis (α = 0.05) identified age, location, occupation, family history of breast cancer, household annual income, behavioral prevention score, smoking and drinking habits, and overall life satisfaction to independently correlate with breast cancer awareness in China.(18)

Women aged 35 to 44 have the highest enhancement of knowledge with a mean increase from 24% in the pretest to 73% in the post test. The higher a woman educational level is the more their knowledge and awareness level increases after the intervention. This could be related to the following reasons: many of those who have obtained college level education and above falls within this age category and are more likely to be informed consequent of the effect of education, access to information and possible improve socioeconomic status. This could be associated to their literacy competency and the ability to read and make individual research about issues once introduced to them unlike their counterparts who mainly relies on their ears for such opportunities. Obtaining a college level education shows a good knowledge in both pre and post intervention. This shows that higher education is significantly related to breast cancer awareness and knowledge which could be related to both the type of training and the literacy level. Highly educated women are more likely to read journals, magazines and follow news than low educated women in the Gambia. In a study that assess knowledge of breast cancer and sources of information among women in Riyadh were 84% were Saudi national and 67.8% had a university level education. Eighty percent were between the ages of 20 to 50 years. The Knowledge of breast self-examination (BSE) was found to be high; 82% (95% confidence intervals [CI], 79.2–84.4%) (20). Increase in breast health awareness help to educate women about the importance of diagnosing cancer at early stages when treatment is easier, and outcome is better. Advanced cancers demand more extensive therapies and are more likely to metastasize to other organs at which point they no longer can be cured (21).

As participants house income increases so as their knowledge in both pre and post intervention. This could be associated with the fact that those whose earnings are more are predominantly youths, well-educated or those involved in lucrative business that provide them the opportunity to benefit from quality health services and information regardless of their geography. Findings from an Indian study concluded that cancer prevention policies should focus on leveraging the positive effects of better socioeconomic status, employment, health insurance ownership, exposure to electronic media, and better healthcare autonomy because it was found that higher age, urban residence, higher education, having employment, health insurance, use of electronic media, higher household wealth quintile, having healthcare autonomy, showed a positive effect on taking screening services due to increase awareness and knowledge (22).

The hypothesis on the effectiveness of health education intervention among participants which was tested using a paired sample T-test shows a significance difference in the pre intervention and post intervention awareness and knowledge. Improvements in all the various dimensions of the participants’ knowledge on breast cancer leading to the rejection of the research’s null hypothesis, and the acceptance of the alternative. The study’s findings agree to a great extend with a recently published study conducted in India, which concluded that community-based educational interventions were effective in enhancing knowledge regarding breast cancer among women(23).

It is not surprising that many participants cited a lack of information on the awareness about breast cancer because many participants claimed that this research was their first time to participate and adequately interact with health personnel on breast cancer-related programmes. Other perceived barriers to awareness include cultural beliefs and stigma about breast cancer. Sticking to cultural believes on serious health challenges such as breast cancer-related matters could be reduced by working with local authorities and training local women representative to bridge the gap that hinders access to healthcare through culturally acceptable programmes. This though is corroborated by Bhatt and Bathija (2018) that communities encompass a mix population from both low-and-high income individuals that face multifaceted challenges in accessing quality healthcare, which include; limited educational opportunities for some, reduced access to healthcare facilities, cultural barriers, and a lack of health education and awareness intervention(24).

An Ethiopian study on cervical cancer screening uptake study at selected health centres in Addis Ababa concluded that providing focused health education supported by printed educational materials increased the uptake of cervical cancer screening services by 74%(17) The current Gambian study found that the most preferred choice of health education or communication approach by women was the use of pamphlets or brochures and making videos or multimedia presentation in the peri-urban settings, a consequence of the socio-economic context of the area and the previous use of these mediums in health promotion and education programs and interventions. Uptake of maternal and child health services is promising in the Gambia. Therefore, providing a take-home educational material into the existing maternal and child health services can help increase cervical cancer awareness and screening uptake. The formal way of addressing health challenges among women Gambian is through organizing workshops or community-based activities that promotes women involvement in dialogue and education. These enable women in white-coloured jobs take official permission for participation and foster dialogue and participation among the different actors of the women’s health.

The limitation of this research is its inability to explore the relationship between proximity to health facilities and community demographics that affect participants’ knowledge on breast cancer.

The primary objective of this study is to assess the overall effectiveness of health education interventions in underserved communities for enhancing breast cancer knowledge and awareness, with the aim of contributing to closing the gap in breast cancer knowledge disparities in these populations. Despite several interventions and programs such as routine screening and health education activities on other cancers like cervical cancer and Hepatitis B and C in the Gambia, the knowledge and awareness level of breast cancer remains low in underserved communities which also affects its screening practices.

This study affirms the usefulness of reaching out to communities for promoting health enhancing behaviours and practices. The knowledge score enhancement realized about 3 months post-intervention and the increased in the number of women who knows about breast cancer and self breast examination harbingers the need to escalate or replicate such educational interventions to accelerate the detection of any breast abnormalities for possible medical attention. Several factors such as limited information and cultural belief or stigma remains as major barriers to breast cancer awareness.

BSE: breast self-examination

CBE: Clinical Breast Examination

CDC: Center for Disease Control and Prevention

GIS: Geographic Information Systems

WHO: World Health Organization

Ethics approval and consent to participate.

Ethical approval for this study was obtained from the Western 2 Health Regional Directorate-Ministry of Health of The Gambia. Informed consent was obtained from participants and various community leaders.

Consent for publication.

Not applicable

Availability of data and materials

All data generated or analysed during this study are included in this article.

Competing interests

All the authors declare no competing interest.

Funding

No funding available

Authors' contributions

All the authors listed have made substantial, direct, and intellectual contributions to the work and approved it for publication. LB, LC and BZ designed the study and wrote the first draft; SC,BB, and MN were responsible for methodology and data collection; LB, MN, SC,BB and AS were responsible for data input and analysis; LC and MN were responsible for investigation and visualization; AS, LB and LC critically reviewed, discussed, and modified the manuscript. All authors read and approved the final version of the manuscript

Authors' information

Lamin F Barrow : The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.

Asaolu Segun: Food Safety and Health Research Centre, School of Public Health, Southern Medical University, Guangzhou City, China.
Bo Zhang: Department： Food Safety and Health Research Centre, School of Public Health, Southern Medical University, Guangzhou City, China.
Samba Camara: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.
Buba Bah: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.
Manjally Ndow: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.
Lamin M Ceesay: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.

Acknowledgement

Sincere appreciation to the School of International Studies, Southern Medical University and to all our professors (Professor Jun Chen, Emma, Wendy, Zayn, and Rebecca) for their support, assistance and encouragement throughout the program. Special thank goes to the staff of the Department of Public and Environmental Health of the University of The Gambia more specially, Professor Rex A Kuye, Mr Alhaji Jabbi and Mr Sekou O.M Dibba for their academic coaching and support.

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Chart 1 and 2 are available in the Supplementary Files section.

No competing interests reported.

Chart1.png
Chart 1: Participants Awareness about Breast Cancer Risk Factors in Pre and Post Intervention
Chart2.png
Chart 2: Participants Knowledge about Breast Cancer Signs and Symptoms in Pre and Post Intervention

Examining the Impact of Health Education Interventions on Breast Cancer Knowledge (Awareness) Among Women in Underserved Communities of West Coast Region, The Gambia

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Introduction

Methods

Study Design and Population

Study Area

Sampling Technique

Description of processes

Outline of the Health education intervention

Results

Pre and Post Intervention Knowledge level of participants

Comparison of Pre-Intervention and Post-Intervention Knowledge Score showing Enhancement across Different Demographic Variables

Public Health Education Measures Preferred by Participants in Urban

Perceived Barriers to Breast Cancer Awareness and Screening Services

Discussion

Conclusions

Abbreviations

Declarations

References

Chart 1 and 2

Additional Declarations

Supplementary Files

Status:

Version 1