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

Examining the Impact of Health Education Interventions on Breast Cancer Knowledge (Awareness) Among Women in Underserved Communities of West Coast Region, The Gambia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Examining the Impact of Health Education Interventions on Breast Cancer Knowledge (Awareness) Among Women in Underserved Communities of West Coast Region, The Gambia Lamin F Barrow, Asaolu Segun, Bo Zhang, Samba Camara, Buba Bah, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4369920/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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 Introduction 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. Methods 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 = z 2 pq/d 2 , 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. Results 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 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 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 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 COR 95% Confidence Interval P-value AOR 95% Confidence Interval P-value Good Poor 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 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 COR 95% Confidence Interval P-value AOR 95% Confidence Interval P-value Good Poor 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 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. Discussion 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. Conclusions 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. Abbreviations BSE: breast self-examination CBE: Clinical Breast Examination CDC: Center for Disease Control and Prevention GIS: Geographic Information Systems WHO: World Health Organization Declarations 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. References WHO. Breast cancer [Internet]. 2020 [cited 2023 Sep 9]. 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Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265881 Potluri TS, Vadlamani S, Gujjarlapudi C, Nerusu NG, Rongala M V. An educational intervention study to enhance breast cancer awareness among women and primary healthcare providers of an urban health center area, Visakhapatnam. J Fam Med Prim Care [Internet]. 2023 Aug [cited 2023 Dec 21];12(8):1697. Available from: /pmc/articles/PMC10521838/ Bhatt J, Bathija P. Ensuring Access to Quality Health Care in Vulnerable Communities. Acad Med [Internet]. 2018 [cited 2023 Sep 9];93(9):1271. Available from: /pmc/articles/PMC6112847/ Chart 1 and 2 Chart 1 and 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files 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 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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13:47:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2416145,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4369920/v1/778f87a0-5332-4ad7-bea7-72785ead3673.pdf"},{"id":56271692,"identity":"5e2beb9c-8011-4f0b-ad9b-ed3693373ba7","added_by":"auto","created_at":"2024-05-10 18:22:56","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23983,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChart 1: \u003c/strong\u003eParticipants Awareness about Breast Cancer Risk Factors in Pre and Post Intervention\u003c/p\u003e","description":"","filename":"Chart1.png","url":"https://assets-eu.researchsquare.com/files/rs-4369920/v1/dae16e958738ac884b17c4c7.png"},{"id":56271674,"identity":"8b285d55-f683-45ec-81c9-9d708e9fd4a0","added_by":"auto","created_at":"2024-05-10 18:22:08","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24902,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChart 2: \u003c/strong\u003eParticipants Knowledge about Breast Cancer Signs and Symptoms in Pre and Post Intervention\u003c/p\u003e","description":"","filename":"Chart2.png","url":"https://assets-eu.researchsquare.com/files/rs-4369920/v1/64917c5e55d68c6cafdf37b5.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Examining the Impact of Health Education Interventions on Breast Cancer Knowledge (Awareness) Among Women in Underserved Communities of West Coast Region, The Gambia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast 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\u0026nbsp;million new cases of breast cancer, making it a significant contributor to cancer-related morbidity and mortality (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). 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(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Its pervasive impact is not limited to affluent nations; breast cancer knows no borders and affects individuals across all demographic and socioeconomic backgrounds (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, regional disparities within countries, especially among underserved communities, persist in the diagnosis and outcomes of breast cancer (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). 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. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDespite 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. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). 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(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMany 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 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). While significant progress has been made in diagnosing and treating breast cancer over the years, disparities in breast cancer outcomes persist among various populations (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Underserved communities, characterized by limited access to healthcare resources, economic disparities, and often marginalized social status, bear a disproportionate burden of this disease (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). 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(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). 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(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA 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. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn 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 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). 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 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Longer distances to diagnostic and treatment facilities have been associated with delayed diagnosis and late stage at diagnosis in sub Saharan Africa (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHealth education interventions play a central role in bridging the gap between underserved communities and breast cancer awareness, knowledge, and screening practices(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These interventions encompass a wide range of activities, including community workshops, educational campaigns, culturally sensitive materials, and collaborations with healthcare providers(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 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(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThis is an intervention study aimed at analysing the effects of health education on women\u0026rsquo;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.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Population\u003c/h2\u003e \u003cp\u003eA 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Area\u003c/h2\u003e \u003cp\u003eThe 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 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) basic health facilities, thirteen (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) community clinics, twelve (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) Non-Governmental Organization (NGO) or faith-based health facilities, and seven (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) private health facilities. The region stretches from Busumbala to Kalagi, along the trans Gambia highway.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSample Size\u003c/strong\u003e \u003cp\u003eIt 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\u0026rsquo;s single proportion formula to get the desired level of precision, confident level, and the estimated sample size for the study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe formula is denoted as:\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;z\u003csup\u003e2\u003c/sup\u003e pq/d\u003csup\u003e2\u003c/sup\u003e,\u003c/p\u003e \u003cp\u003eWhere n\u0026thinsp;=\u0026thinsp;sample size, z\u0026thinsp;=\u0026thinsp;z-score at 95% confidence level, p\u0026thinsp;=\u0026thinsp;estimated proportion of an attribute that is present in the population, q\u0026thinsp;=\u0026thinsp;1-p, d\u0026thinsp;=\u0026thinsp;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 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). 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.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSampling Technique\u003c/h3\u003e\n\u003cp\u003eA 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\u0026rsquo;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.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDescription of processes\u003c/h2\u003e \u003cp\u003eIn 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.\u003c/p\u003e \u003cp\u003eThe 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.\u003c/p\u003e \u003cp\u003eThe 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutline of the Health education intervention\u003c/h2\u003e \u003cp\u003eThe 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. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBelow 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.\u003c/p\u003e \u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eUnit One provides general information on the anatomy and physiology of a normal breast for the participants to have a clear understanding of the topic.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eUnit Two gives information and knowledge of BC. It further explores BC symptoms, BC stages, BC risk factors to increase the participants\u0026rsquo; knowledge of BC.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eUnit three explains the barriers to BCA and BSE procedure to understand the barriers that hinders BCA and raise the participants\u0026rsquo; awareness of BC symptoms and motivate them to follow this procedure.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e 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.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e \u003cp\u003eThe 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.\u003c/p\u003e \u003cp\u003e(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 .\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e(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.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e(c) A fifteen-minute session was held on communication and its different types including their advantages and disadvantages.\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e(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\u0026rsquo; room.\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e(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 (\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\n\u003c/span\u003e\n \u003cp\u003e \u003cstrong\u003eStatistical Analysis\u003c/strong\u003e \u003cp\u003eA 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.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eScoring 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 (\u0026ldquo;yes\u0026rdquo;) was scored one (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) point, and each wrong response (\u0026ldquo;no\u0026rdquo;) was scored zero (0) thus a maximum score was 20. Respondents with score 0\u0026ndash;10 points were considered to have a poor knowledge in this study and those with 11\u0026ndash;20 points were considered to have a good knowledge.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSocio demographic characteristics of research participants.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table \u003cspan\u003e1\u003c/span\u003e, 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 \u0026plusmn;\u0026thinsp;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\u0026rsquo; 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.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSocio demographic characteristics of research participants.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026ndash;44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026ndash;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eName of Community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeri-Urban\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNyambai \u0026amp;Wellingara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGidda \u0026amp; Darsilameh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRural\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFaraba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePirang\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMandinka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eManjako\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSarahuli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWollof\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostgraduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSenior school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJunior school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;D10,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD10,000\u0026ndash;20,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;D20,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBusiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCivil Servant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003ePre and Post Intervention Knowledge level of participants\u003c/h2\u003e\n \u003cp\u003eThe data collected from pre-intervention and post-intervention were tabulated to investigate the effectiveness of health education intervention on Breast Cancer awareness. Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e depicts the overall score for both test and the participant\u0026rsquo;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.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eFrequency Distribution of Pre and Post Intervention Knowledge level of participants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePre-Intervention\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePost-Intervention\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMark\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercent\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor Knowledge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGood Knowledge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026ndash;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMissing Data\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eComparison of Pre-Intervention and Post-Intervention Knowledge Score showing Enhancement across Different Demographic Variables\u003c/h2\u003e\n \u003cp\u003eFrom the data on knowledge enhancement, the age cohort 35\u0026ndash;44 shows the highest (49%) change in average knowledge score while age 25\u0026ndash;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.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison of Pre-Intervention and Post-Intervention Knowledge Score showing enhancement across different Demographic variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePre-Intervention\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-Intervention\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEnhancement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEnhancement %\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e65.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026ndash;44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e73.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026ndash;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e70.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e57.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMandinka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e68.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eManjako\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e66.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSarahuli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e70.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e75.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWollof\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e57.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePost_Gra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e81.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e87.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSenior_S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJunior_S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e59.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eprimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e59.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e62.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e75.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e81.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBusiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCivil Servant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10000\u0026ndash;20000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;20000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eRelationship between Knowledge and Socio-demographic Variables at Pre-Intervention stage using Binary and Multiple Logistic Regression Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe result of the multiple logistic regression (Table \u003cspan\u003e4\u003c/span\u003e) highlighted that several socio-demographic variables show some subcategories such as age (35\u0026ndash;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\u0026ndash;19.353)]. Women who obtained college level education has an odd of [AOR: 0.072, 95% CI: (0.03\u0026ndash;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\u0026ndash;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.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4: Relationship between Knowledge and Socio-demographic Variables\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eat Pre-Intervention stage\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eusing Binary and Multiple Logistic Regression Analysis, N=315\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"955\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.794979079497908%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.84100418410042%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eKnowledge N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.78661087866109%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-Intervention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.57740585774059%\" colspan=\"4\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.440993788819876%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.757763975155278%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence Interval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.956521739130435%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.664596273291925%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.22360248447205%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence Interval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.956521739130435%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.13588110403397%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGood\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.046709129511676%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.348195329087048%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.348195329087048%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.348195329087048%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.772823779193207%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e40 (76.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e172 (65.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e03 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e52 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e4.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e13.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.024*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e5.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e19.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e45-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e07 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e27 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e2.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e3.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.751\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e02 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e12 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e6.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e5.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.778\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eMandinka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e28 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e135 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eFula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e14 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e49 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e3.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.578\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eWolof\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e03 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e21 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e5.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e2.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e9.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.295\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eJola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e02 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e33 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e3.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e15.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e3.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e18.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e05 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e25 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e2.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e5.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.584\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e00 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e78 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eJunior secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e05 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e39 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e7.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e3.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e19.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e1.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eSenior secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e11 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e100 (38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e9.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e4.878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e16.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e1.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eCollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e34 (65.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e35 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e.418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003ePost-graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e02 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e11 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e5.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e24.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.027*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e21 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e191 (72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e30 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e67 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e2.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e3.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e1.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.248\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eDivorced/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e01 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e05 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e5.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e42.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e19.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.875\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eFarmers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e00 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e10 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eBusiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e10 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e68 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e6.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e3.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e13.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e12.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e2.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e60.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eCivil Servant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e24 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e25 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e4.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e26.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e07 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e124 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e17.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e8.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e37.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e20.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e5.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e80.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eStudents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e07 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e19 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e2.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e6.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.024*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e12.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e86.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.013*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e04 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e17 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e4.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e12.630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e21.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e2.730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e164.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Monthly Income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e24 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e125 (47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e10,000 \u0026ndash; 20,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e17 (32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e98 (37.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e2.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e2.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e7.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;20,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e11 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e40 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e5.455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cem\u003eN = Frequency, COR = Crude Odds Ratio, AOR = Adjusted Odds Ratio \u0026nbsp; \u0026nbsp; \u0026nbsp; * P-Value Significant at\u0026nbsp;\u003c/em\u003e\u0026le;\u003cem\u003e0.05\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5: Relationship between Knowledge and Socio-demographic Variables\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eat Post-Intervention stage\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;using Binary and Multiple Logistic Regression Analysis, N=305\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"955\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.794979079497908%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.84100418410042%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eKnowledge N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.78661087866109%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.57740585774059%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost-Intervention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.440993788819876%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.757763975155278%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence Interval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.956521739130435%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.664596273291925%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.22360248447205%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence Interval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.956521739130435%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.13588110403397%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGood\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.046709129511676%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.348195329087048%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.348195329087048%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.348195329087048%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.772823779193207%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e125 (64.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e79 (70.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e40 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e14 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e45-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e21 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e12 (10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e1.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e7 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e7 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e2.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e8.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.474\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eMandinka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e107 (55.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e51 (45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.Ref\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eFula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e41 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e19 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.006*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.805\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eWolof\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e10 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e14 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e3.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e3.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e11.525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.034*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eJola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e17 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e17 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e18 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e11 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e2.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e6.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.110\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e38 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e37 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eJunior secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e23 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e21 (18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e3.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.472\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eSenior secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e58 (30.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e48 (42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eCollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e63 (32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e4 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e.890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.034*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003ePost-graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e11 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.324\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e115 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e91 (81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e73 (37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e20 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e1.970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.644\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eDivorced/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e5 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e01 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eFarmers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e6 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e04 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eBusiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e50 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e24 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.785\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eCivil Servant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e45 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e02 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e1.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e53 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e74 (66.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e1.396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.064*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e1.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e3.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.046*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eStudents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e23 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e03 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e2.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.437\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e16 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e05 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e3.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Monthly Income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e69 (35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e78 (69.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e10,000 \u0026ndash; 20,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e83 (43.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e26 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.778474399164054%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;20,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.941483803552769%\" valign=\"top\"\u003e\n \u003cp\u003e41 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.881922675026123%\" valign=\"top\"\u003e\n \u003cp\u003e8 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.717868338557993%\" valign=\"top\"\u003e\n \u003cp\u003e.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.195402298850574%\" valign=\"top\"\u003e\n \u003cp\u003e.192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.25496342737722%\" valign=\"top\"\u003e\n \u003cp\u003e.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.045977011494253%\" valign=\"top\"\u003e\n \u003cp\u003e.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cem\u003eN = Frequency, COR = Crude Odds Ratio, AOR = Adjusted Odds Ratio \u0026nbsp; \u0026nbsp; \u0026nbsp;* P-Value Significant at\u0026nbsp;\u003c/em\u003e\u0026le;\u003cem\u003e0.05\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRelationship between Knowledge and Socio-demographic Variables at Post-Intervention stage using Binary and Multiple Logistic Regression Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe 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\u0026ndash;0.648)]. Women who obtained college level education has an odd of [AOR: 0.209, 95% CI: (0.049\u0026ndash;0.890) compared to those with primary level education. Being a housewife has an odd of [AOR: 0.064, 95% CI: (1.998\u0026ndash;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\u0026ndash;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.\u003c/p\u003e\n \u003cdiv\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eEffectiveness of the Health Education Intervention (A paired Sample T-Test of Participants knowledge in Pre and Post Intervention)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eA 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.\u003c/p\u003e\n \u003cp\u003eFrom 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\u0026thinsp;=\u0026thinsp;6.08; SD\u0026thinsp;=\u0026thinsp;3.35) to Post (M\u0026thinsp;=\u0026thinsp;13.34; SD\u0026thinsp;=\u0026thinsp;5.33) at the 0.05 level of significance, t(-24.2)\u0026thinsp;=\u0026thinsp;5.23, n\u0026thinsp;=\u0026thinsp;305, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, [95% CI: -6.67,-7.85]\u003c/p\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"left\"\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003ePublic Health Education Measures Preferred by Participants in Urban\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eand Peri-Urban Communities.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis 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.\u003c/p\u003e\n \u003cp\u003eMajority 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.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 7\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePublic Health Education Measures Preferred by Participants in Urban and Peri-Urban Communities.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePublic Health Education Measures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePeri-Urban\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSharing Pamphlets or Brochures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVideos or multimedia Presentation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOrganize workshops or community events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial media campaigns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePodcast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote: multiple options were allowed leading to percentages been more than 100%\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e\u003cstrong\u003ePerceived Barriers to Breast Cancer Awareness and Screening Services\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003eThis 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\u0026rsquo; responses on other barriers were very minimal when compared to the two stated above as shown on the table below.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 8\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cstrong\u003ePerceived Barriers to Breast Cancer Awareness and Screening Services\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePerceived Barriers to Breast Cancer Awareness and Screening Services\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePeri-Urban\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of information or awareness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinancial Constraints\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLanguage Barriers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCultural Beliefs or Stigma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFear or Anxiety About Screening\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of Access to Healthcare Facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTransportation Issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eParticipants Awareness about Breast Risk Factors in Pre and Post Intervention data Collection.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eConsistently, the data shows an increase in the participant awareness on the risk factors of breast cancer from the pre-intervention data collection (M\u0026thinsp;=\u0026thinsp;56.14; SD\u0026thinsp;=\u0026thinsp;66.79) to post-intervention data collection (M\u0026thinsp;=\u0026thinsp;169.85; SD\u0026thinsp;=\u0026thinsp;41.67). Family history and alcohol drinking were found to be the highest attributable risk factors mentioned by participants (N\u0026thinsp;=\u0026thinsp;241 and N\u0026thinsp;=\u0026thinsp;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)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eParticipants Awareness about Breast Cancer Signs and Symptoms Pre and Post Intervention data Collection.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe 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\u0026thinsp;=\u0026thinsp;230) followed by lump in the breast (n\u0026thinsp;=\u0026thinsp;200), Nipple discharge liquid (n\u0026thinsp;=\u0026thinsp;183), Nipple retraction (n\u0026thinsp;=\u0026thinsp;178) and Axillary nodes (n\u0026thinsp;=\u0026thinsp;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.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe impact of health education interventions on breast cancer knowledge and awareness and cultural acceptable practices within underserved communities were explored in this study.\u003c/p\u003e \u003cp\u003eThe 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\u0026ndash;70 years had poor awareness of breast cancer (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Similarly, this study\u0026rsquo;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. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). 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.\u003c/p\u003e \u003cp\u003eThe 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\u0026rsquo;s interaction with service providers in special clinic days coupled with this study\u0026rsquo;s educational intervention potentially produced a synergistic effect on their knowledge of breast cancer.\u003c/p\u003e \u003cp\u003eConsistently, 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 \u0026ldquo;blood\u0026rdquo; 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 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Although there was a general post-intervention improvement in the participants\u0026rsquo; 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.\u003c/p\u003e \u003cp\u003eThe 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 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe multiple logistic regression results showed that knowledge and awareness level of breast cancer was associated with participants\u0026rsquo; 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\u0026ndash;0.648)]. Women who obtained college level education has an odd of [AOR: 0.209, 95% CI: (0.049\u0026ndash;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\u0026ndash;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\u0026thinsp;=\u0026thinsp;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.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWomen 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\u0026ndash;84.4%) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). 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 (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs 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 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 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\u0026rsquo; knowledge on breast cancer leading to the rejection of the research\u0026rsquo;s null hypothesis, and the acceptance of the alternative. The study\u0026rsquo;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(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt 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(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAn 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%(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) 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\u0026rsquo;s health.\u003c/p\u003e \u003cp\u003eThe limitation of this research is its inability to explore the relationship between proximity to health facilities and community demographics that affect participants\u0026rsquo; knowledge on breast cancer.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe 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.\u003c/p\u003e \u003cp\u003eThis 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.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBSE:\u0026nbsp;breast self-examination\u003c/p\u003e\n\u003cp\u003eCBE: Clinical Breast Examination\u003c/p\u003e\n\u003cp\u003eCDC: Center for Disease Control and Prevention\u003c/p\u003e\n\u003cp\u003eGIS:\u0026nbsp;Geographic Information Systems\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEthical 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.\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eConsent for publication.\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this article.\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll the authors declare no competing interest.\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNo funding available\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll 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\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003eLamin F Barrow\u003cstrong\u003e\u0026nbsp;:\u0026nbsp;\u003c/strong\u003eThe Department of Public and Environmental Health, School of Medicine and Allied\u0026nbsp;Health Sciences, University of The Gambia.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAsaolu Segun:\u0026nbsp;Food Safety and Health Research Centre, School of Public Health, Southern Medical University,\u0026nbsp;Guangzhou City, China.\u003c/li\u003e\n \u003cli\u003eBo Zhang: Department： Food Safety and Health Research Centre, School of Public Health, Southern Medical University, Guangzhou City, China.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSamba Camara: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBuba Bah: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eManjally Ndow: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLamin M Ceesay: The Department of Public and Environmental Health, School of Medicine and Allied Health Sciences, University of The Gambia.\u003c/li\u003e\n\u003c/ul\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSincere 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.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. Breast cancer [Internet]. 2020 [cited 2023 Sep 9]. Available from: https://www.who.int/news-room/fact-sheets/detail/breast-cancer\u003c/li\u003e\n\u003cli\u003eWilkinson L, Gathani T. Understanding breast cancer as a global health concern 1. 2022 [cited 2023 Sep 9]; Available from: https://doi.org/10.1259/bjr.20211033\u003c/li\u003e\n\u003cli\u003eRicks-Santi LJ, Barley B, Winchester D, Sultan D, McDonald J, Kanaan Y, et al. Affluence Does Not Influence Breast Cancer Outcomes in African American Women. J Health Care Poor Underserved [Internet]. 2018 Feb 1 [cited 2023 Sep 9];29(1):509\u0026ndash;29. Available from: https://pubmed.ncbi.nlm.nih.gov/29503315/\u003c/li\u003e\n\u003cli\u003eYedjou CG, Sims JN, Miele L, Noubissi F, Lowe L, Fonseca DD, et al. Health and Racial Disparity in Breast Cancer. Adv Exp Med Biol [Internet]. 2019 [cited 2023 Sep 9];1152:31. Available from: /pmc/articles/PMC6941147/\u003c/li\u003e\n\u003cli\u003eŁukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast Cancer-Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies-An Updated Review. Cancers (Basel). 2021 Aug;13(17). \u003c/li\u003e\n\u003cli\u003eWHO. Breast cancer [Internet]. 2023 [cited 2023 Sep 12]. Available from: https://www.who.int/news-room/fact-sheets/detail/breast-cancer\u003c/li\u003e\n\u003cli\u003eCDC. What Are the Symptoms of Breast Cancer? | CDC [Internet]. 2023 [cited 2023 Sep 12]. Available from: https://www.cdc.gov/cancer/breast/basic_info/symptoms.htm\u003c/li\u003e\n\u003cli\u003eWheeler SB, Reeder-Hayes KE, Carey LA. Disparities in Breast Cancer Treatment and Outcomes: Biological, Social, and Health System Determinants and Opportunities for Research. Oncologist [Internet]. 2013 Sep 1 [cited 2023 Sep 9];18(9):986. Available from: /pmc/articles/PMC3780646/\u003c/li\u003e\n\u003cli\u003eBaah FO, Teitelman AM, Riegel B. Marginalization: Conceptualizing patient vulnerabilities in the framework of social determinants of health \u0026ndash; An integrative review. Nurs Inq [Internet]. 2019 Jan 1 [cited 2023 Sep 9];26(1):e12268. Available from: /pmc/articles/PMC6342665/\u003c/li\u003e\n\u003cli\u003eOsei-Afriyie S, Addae AK, Oppong S, Amu H, Ampofo E, Osei E. Breast cancer awareness, risk factors and screening practices among future health professionals in Ghana: A cross-sectional study. PLoS One [Internet]. 2021 Jun 1 [cited 2023 Sep 28];16(6):e0253373. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0253373\u003c/li\u003e\n\u003cli\u003eJoffe M, Ayeni O, Norris SA, McCormack VA, Ruff P, Das I, et al. Barriers to early presentation of breast cancer among women in Soweto, South Africa. PLoS One [Internet]. 2018 Feb 1 [cited 2023 Sep 29];13(2):e0192071. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0192071\u003c/li\u003e\n\u003cli\u003ePrusty RK, Begum S, Patil A, Naik DD, Pimple S, Mishra G. Knowledge of symptoms and risk factors of breast cancer among women: a community based study in a low socio-economic area of Mumbai, India. BMC Womens Health [Internet]. 2020 May 18 [cited 2023 Dec 23];20(1). Available from: /pmc/articles/PMC7236367/\u003c/li\u003e\n\u003cli\u003eOusman Sanyang, Fidel Lopez-Verdugo, Meghan Mali, Moustafa Moustafa, Jonathan Nellermoe, Justin Sorensen, Mustapha Bittaye, Ramou Njie, Yankuba Singhateh, Ngally Aboubacarr Sambou, Alison Goldsmith, Nuredin I. Mohammed, Ki andEdward S. Geospatial analysis and impact of targeted development of breast cancer care in The Gambia: a cross-sectional study | Enhanced Reader. 2021. \u003c/li\u003e\n\u003cli\u003eTogawa K, Anderson BO, Foerster M, Galukande M, Zietsman A, Pontac J, et al. Geospatial barriers to healthcare access for breast cancer diagnosis in sub-Saharan African settings: The African Breast Cancer\u0026mdash;Disparities in Outcomes Cohort Study. Int J Cancer [Internet]. 2021 May 1 [cited 2023 Sep 13];148(9):2212\u0026ndash;26. Available from: https://onlinelibrary.wiley.com/doi/full/10.1002/ijc.33400\u003c/li\u003e\n\u003cli\u003eNoman S, Shahar HK, Rahman HA, Ismail S. Effectiveness of an Educational Intervention of Breast Cancer Screening Practices Uptake, Knowledge, and Beliefs among Yemeni Female School Teachers in Klang Valley, Malaysia: A Study Protocol for a Cluster-Randomized Controlled Trial. Int J Environ Res Public Health [Internet]. 2020 Feb 1 [cited 2023 Sep 11];17(4). Available from: /pmc/articles/PMC7068409/\u003c/li\u003e\n\u003cli\u003eKumar S, Preetha GS. Health Promotion: An Effective Tool for Global Health. Indian J Community Med [Internet]. 2012 Jan [cited 2023 Sep 11];37(1):5. Available from: /pmc/articles/PMC3326808/\u003c/li\u003e\n\u003cli\u003eAbu SH, Woldehanna BT, Nida ET, Tilahun AW, Gebremariam MY, Sisay MM. The role of health education on cervical cancer screening uptake at selected health centers in Addis Ababa. PLoS One [Internet]. 2020 Oct 1 [cited 2023 Sep 29];15(10):e0239580. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0239580\u003c/li\u003e\n\u003cli\u003eLiu LY, Wang F, Yu LX, Ma ZB, Zhang Q, Gao DZ, et al. Breast cancer awareness among women in Eastern China: A cross-sectional study. BMC Public Health. 2014;14(1):1\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eAssfa K, Id M. Perceptions and knowledge of breast cancer and breast self-examination among young adult women in southwest Ethiopia: Application of the health belief model. PLoS One [Internet]. 2022 [cited 2023 Sep 28];17(9):e0274935. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0274935\u003c/li\u003e\n\u003cli\u003eAlam AA. Knowledge of breast cancer and its risk and protective factors among women in Riyadh. Ann Saudi Med [Internet]. 2006 [cited 2023 Dec 6];26(4):272. Available from: /pmc/articles/PMC6074496/\u003c/li\u003e\n\u003cli\u003ePan American Health Organization. Knowledge Summary Early Detection: Breast Health Awareness and Early Detection Strategies. 2016;1\u0026ndash;3. \u003c/li\u003e\n\u003cli\u003eChangkun Z, Bishwajit G, Ji L, Tang S. Sociodemographic correlates of cervix, breast and oral cancer screening among Indian women. PLoS One [Internet]. 2022 May 1 [cited 2023 Sep 28];17(5):e0265881. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265881\u003c/li\u003e\n\u003cli\u003ePotluri TS, Vadlamani S, Gujjarlapudi C, Nerusu NG, Rongala M V. An educational intervention study to enhance breast cancer awareness among women and primary healthcare providers of an urban health center area, Visakhapatnam. J Fam Med Prim Care [Internet]. 2023 Aug [cited 2023 Dec 21];12(8):1697. Available from: /pmc/articles/PMC10521838/\u003c/li\u003e\n\u003cli\u003eBhatt J, Bathija P. Ensuring Access to Quality Health Care in Vulnerable Communities. Acad Med [Internet]. 2018 [cited 2023 Sep 9];93(9):1271. Available from: /pmc/articles/PMC6112847/\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Chart 1 and 2","content":"\u003cp\u003eChart 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Awareness, Breast cancer, Health education, Intervention, Knowledge, Women","lastPublishedDoi":"10.21203/rs.3.rs-4369920/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4369920/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe 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.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA 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.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe 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\u0026thinsp;=\u0026thinsp;6.08; SD\u0026thinsp;=\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35) to Post (M\u0026thinsp;=\u0026thinsp;13.34; SD\u0026thinsp;=\u0026thinsp;\u0026plusmn;\u0026thinsp;5.33) at the 0.05 level of significance, t(-24.2)\u0026thinsp;=\u0026thinsp;5.23, n\u0026thinsp;=\u0026thinsp;305, p\u0026thinsp;\u0026lt;\u0026thinsp;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.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe 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.\u003c/p\u003e","manuscriptTitle":"Examining the Impact of Health Education Interventions on Breast Cancer Knowledge (Awareness) Among Women in Underserved Communities of West Coast Region, The Gambia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-10 18:03:09","doi":"10.21203/rs.3.rs-4369920/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"869522f1-b344-4941-b089-b58d837df0b4","owner":[],"postedDate":"May 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-04T13:39:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-10 18:03:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4369920","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4369920","identity":"rs-4369920","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}