












































 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e1                                              Cancer Health Disparities 

RESEARCH 

Prostate Cancer Risk-Reduction Behaviors 
among US Black Males Less Than 40 
Years Old 
Motolani E. Ogunsanya*,1,7, Folakemi T. Odedina2,7, Ernest Kaninjing3,7, Sunday E. Atawodi4,7, Titilola 
Akinremi5,7, Anthonia Sowunmi6,7 

1College of Pharmacy, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73117, USA 
2Department of Pharmacotherapy and Translational Research and Department of Radiation Oncology, University of 
Florida, Lake Nona Campus, FL, 32832, USA 
3College of Health Sciences, School of Health and Human Performance, Georgia College, GA 31061, USA 
4Department of Biochemistry, Ahmadu Bello University, Zaria, Nigeria 
5Department of Pathology, Federal Medical Center, Abeokuta, Nigeria 
6Department of Radiotherapy, Lagos University Teaching Hospital, Nigeria 
7Prostate Cancer Transatlantic Consortium (CaPTC) 
*Corresponding author:  Motolani-ogunsanya@ouhsc.edu 
 

ABSTRACT 
Prostate cancer (CaP) is the leading cause of cancer deaths among Black men and modifications in 
lifestyle represent an important means of primary CaP prevention in young Black men. Thus, this study 
aimed to explore the cognitive-behavioral and demographic factors related to prostate cancer risk-
reduction behaviors (CaPB) among young Black men in Texas, United States and to examine 
relationships between these factors. This was a cross-sectional study of 267 Black men aged 18 to 40 
years. A survey collected information on demographics, exercise, knowledge of CaP and screening, cues 
to action, and current engagement in CaPB. Participants were young Black males of different ethnicities 
and education levels recruited from local universities, churches, organization, and fraternities. 
Descriptive statistics (means, standard deviations, and frequencies) were calculated for all variables, and 
multiple regression was employed to determine the significant (p<0.05) predictors of CaPB. Participants 
had low knowledge levels (mean=5.25±3.81; range 0-14), engaged in moderate levels, duration, and 
intensity of exercise (mean=6.44±3.147; range 0-10), mostly reported negative cues to action (79.4%), 
and engaged in low levels of CaPB (mean=13.7±5.62; range 0-40). Knowledge, academic classification, 
major field of study, and regular source of care were significant predictors of CaP risk-reduction 
behaviors, and the overall model accounted for 39% (p<0.01) of the behaviors. The significant, 
modifiable factors (such as knowledge levels and regular source of care) should be considered in the 
development of strategies aimed at increasing younger Black men’s engagement in CaPB. 

KEYWORDS: prostate cancer, young Black men, risk-reduction, health behaviors 

Citation: Ogunsanya et al. (2019) Prostate Cancer Risk-Reduction Behaviors among US Black Males Less 
Than 40 Years Old. Cancer Health Disparities 4: e1-e14. doi:10.9777/chd.2019.1004

mailto:Motolani-ogunsanya@ouhsc.edu


 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e2                                              Cancer Health Disparities 
 

RESEARCH 

INTRODUCTION 

Black men have the highest incidence of prostate 
cancer (CaP) in the US (Siegel et al., 2014). The 
CaP disparities observed in Black men are 
alarming when compared to men from other 
ethnicities on survival rates (Li et al., 2012), 
morbidity (Powell et al., 2010), or mortality 
(Odedina et al., 2009). Compared to Caucasian 
men, Black men have a CaP incidence rate more 
than 60% higher and a mortality rate almost three 
times greater (Odedina et al., 2009). Despite the 
controversies associated with CaP screening (Lin et 
al., 2011; McNaughton-Collins and Barry, 2011; 
Moyer, 2012), it still remains the only method of 
detecting the disease early. While the survival rate 
for CaP when diagnosed and treated early can be 
as high as 100%, Black men still have worse CaP 
prognosis when compared to other men (Sanchez 
et al., 2007). 

A review of the literature indicates that, despite 
attempts to increase awareness of and access to 
CaP screening, there have been delays among 
Black men in utilizing primary health care services 
(Cheatham et al., 2008). Black men often forgo 
preventive services, choosing instead to delay 
treatment or avoid health care altogether 
(Cheatham et al., 2008). Further, several studies 
conducted in Black men have demonstrated low 
knowledge levels regarding CaP, especially its risk 
factors like positive family history and ethnicity 
(Lee et al., 2012; Ogunsanya et al., 2017). This 
knowledge gap is especially important because 
two of the major risk factors associated with CaP 
are race (Black race) and ethnicity (Scher et al., 
2015; Tourville and Nguyen, 2013). 

While there have been mixed findings on the 
relationship between lifestyle choices and CaP, 

increased intake of dietary fat have been found to 
play an independent role in the development of 
CaP (Odedina et al., 2011a; Tourville and Nguyen, 
2013). Cumulative exposure to androgens and 
high-fat diets, for example, have been reported to 
increase CaP risk (Wu and Modlin, 2012). This 
pattern of exposure has been established across 
case-control studies, ecologic studies, animal 
models, and studies involving immigrants 
(Mauermann et al., 2011; Simopoulos, 2010; Wigle 
et al., 2008). Conversely, studies have 
demonstrated the potential anticancer and 
antioxidant effects of lycopene or tomato 
products, especially against CaP (Giovannucci et 
al., 2002). However, these studies also reported a 
lower consumption of tomato-based products 
among Black men compared to other ethnic 
groups, which translated to lower serum lycopene 
levels and a higher risk of CaP. Physical activity has 
also been associated with reduced risk of CaP, 
especially beginning from the mid-teens (Liu et al., 
2011). Other lifestyle modifications such as smoking 
cessation, weight control, and the use of 
chemopreventive agents can decrease CaP risk 
(Cuzick et al., 2014). However, other studies have 
reported no additive benefits of these primary 
modes of cancer prevention (Lippman et al., 2009; 
Whittemore et al., 1995). 

Modifications in lifestyle are the most likely means 
of primary prevention of CaP. There are mixed or 
inconclusive findings from research concerning the 
relationship between lifestyle modification and 
CaP, but given the known relationship between 
diet, exercise, smoking, and other modifiable 
factors related to other common cancers, lifestyle 
modification can be an important prevention 
consideration (Verma et al., 2014). Diet remains the 
only known risk factor that may be modified to 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e3                                              Cancer Health Disparities 
 

RESEARCH 

reduce a man’s chance of developing CaP, thus an 
important element in primary prevention. Some 
research studies indicate that meat cooked at high 
temperatures contain considerable levels of 
mutagens that can lead to an elevated level of CaP 
risk (Daniel et al., 2011; Mandair et al., 2014). A diet 
low in fat and high in vegetable intake may have 
some preventive effects (Kolonel et al., 2000), 
however many men do not meet the 
recommended dietary guidelines and therefore 
appear to be at increased risk of developing CaP 
(Dixon et al., 2007). 

Millon-Underwood and Sanders (Millon-
Underwood and Sanders, 1990) examined the 
factors responsible for health promotion behaviors 
in Black men (N=177). This study was specifically 
focused on modifiable behaviors that reduced 
cancer risk, or that can detect cancer early. 
Findings from the study showed that beliefs 
related to cancer risk, decreasing carcinogen 
exposures, and beliefs related to the influence of 
health care providers significantly contributed to 
explaining 72% of the variance in health-
promoting behaviors. Further, the Black men in the 
study did not consider themselves very health-
conscious with just over half of the sample (56%) 
having reported paying attention to their bodies 
while only 42% stated that they were involved in 
one form of physical activity or the other. Twenty-
three percent of the men in the survey reported 
that their diet consisted of an adequate amount of 
vitamins, minerals, fiber, and dietary fat. Some 
chemoprevention agents such as 5-α-reductase 
inhibitors, NSAIDs, selenium, allium vegetables, 
soy/isoflavones, green tea polyphenols, vitamins D 
and E, and statins, have been considered for 
reduction of CaP and may reduce CaP mortality 
(Colli and Amling, 2009). While there is no 

conclusive evidence for the chemopreventive 
benefit of nutrients or vitamins, it remains a 
significant part of CaP prevention and early 
detection. 

In order to limit the focus of this study to 
behaviors conformable to interventions on cancer-
related outcomes in Black males, this study was 
based on the following assumptions: (1) starting 
the conversation about preventive health 
behaviors in the early adult years can increase the 
likelihood of risk-reduction behaviors and early 
detection of CaP in later years; (2) informed 
decision-making regarding CaP screening among 
high-risk men (Black ethnicity and familial history) 
will reduce mortality and morbidity rates; (3) and 
that when adequately informed about the 
potential risks of this disease, younger men can be 
proactive in reducing some of the modifiable risks 
associated with CaP. Thus, the primary objective of 
this study was to explore the cognitive-behavioral 
and demographic factors related to CaPB among 
young Black men and to examine the relationships 
between these factors. 

Methods 

Research Design and Participants 
This was a cross-sectional survey design study 
using questionnaires. Young Black males (aged 
between 18 and 40 years), who identified as Black 
and understood written and spoken English were 
included in the study. Non-Black males, non-
English speaker, and those aged under 18 or over 
40 years were excluded from the study. 
Participants were recruited from churches, local 
organizations, and colleges and universities 
surrounding The University of Texas at Austin in 
Texas. 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e4                                              Cancer Health Disparities 
 

RESEARCH 

Measures 
A 39-item instrument was administered to 
participants. The questionnaire contained a 10-
item scale measuring current engagement in CaP 
risk-reduction behaviors and 29 items measuring: 
age (1 item), cues to action (1 item), knowledge (14 
items), exercise (3 items), and 
demographic/personal factors (10 items). 

Study Variables 
Dependent Variable 
Current engagement in risk reduction behaviors 
was measured using the 10-item Prostate Cancer 
Prevention Behavior (CaPB) Scale from The 
Personal Integrative Model of Prostate Cancer 
Disparity (PIPCaD) developed by Odedina et 
al.(Odedina et al., 2011b) The items in the PIPCaD 
scale assessed participants’ engagement in lifestyle 
activities to reduce CaP risk factors, including low-
fat diet consisting mainly of fruits and vegetables, 
and the use of supplements within the last week. 
Items were measured on a 5-point scale ranging 
from never (0) to 2 or more times a day (4), with 
higher scores indicating higher levels of 
engagement in CaPB. Scores ranged from 0 to 40. 
Participants were asked to indicate: 1) how often 
they consumed fruits, vegetables, meat products, 
dairy products, and butter/oil within the last week, 
and 2) if they have taken the following 
supplements - selenium, lycopene, Vitamin A and 
other retinoids, Vitamin D and soy within the last 
week. The PIPCaD has been used in other studies 
(Cobran et al., 2014; Morrison et al., 2017) and 
reported to have high internal consistency. 

Independent Variables 
Age 

Age was calculated by subtracting the year of birth 
reported by participants from the year of study 
(2014).  

Cues to Action 
Using a Yes (1)/No or Don’t Know (0) response 
scale, a single item was used to measure 
participants’ cues to action. The measure asked 
about CaP histories from person(s) close to the 
participants. Those who responded to ‘No’ or 
‘Don’t Know’ were coded as ‘0,’ while those who 
responded ‘Yes’ to knowing someone with CaP 
were coded as ‘1.’ 

Knowledge 
Knowledge was assessed using a 14-item scale 
with six domains (limitations, side effects from 
treatment, symptoms, risk factors, screening age 
guidelines, and screening controversy). The 
knowledge scale comprised of twelve items from 
the Knowledge about Prostate Cancer Screening 
Questionnaire by Weinrich et al. (Weinrich et al., 
2004) and two items assessing dietary knowledge 
and screening controversy by Odedina et al. 
(Odedina et al., 2011b). 

Exercise 
Participants’ exercise level, frequency, and duration 
were measured using three items derived from the 
Personal Integrative Model of Prostate Cancer 
Disparity (PIPCaD model) by Odedina et al. 
(Odedina et al., 2011b). The three items were 
summed up to create a composite score for 
exercise with higher scores indicating higher 
exercise time, intensity, and level. Composite 
scores ranged from 0 to 10. 

Demographic/Personal Factors 

Ten items assessed demographic/personal factors. 
They include: 1) academic classification (less than 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e5                                              Cancer Health Disparities 
 

RESEARCH 

high school or high school graduate or GED, 
college freshman, college sophomore, college 
junior, college senior, graduate student, or 
postgraduate); 2) income (<$30,000 or ≥$30,001); 
3) ethnicity (African American of American origin 
[born and grew up in America], African, African 
American of African origin [born in Africa but now 
American citizen], African American of Caribbean 
origin [born in one of the Caribbean Islands but 
now American citizen], or Caribbean); 4) family 
history of CaP (yes, no); 5) health insurance status 
(private insurance [e.g., BlueCross/ Blue Shield, 
Humana], no insurance/self-pay, public insurance 
[e.g., Medicaid] or not sure); 6) major/field of study 
(professional and applied sciences (e.g., 
architecture, business, communication, education, 
engineering and law), humanities (e.g., fine arts, 
liberal arts and public affairs) and 
natural/healthcare sciences (e.g., natural sciences, 
nursing, pharmacy, social work and medicine)); 7) 
marital status (single, not in a relationship; single, 
in a relationship; and married/partner/ living 
together); 8) perception of health status (fair, 
good, excellent); 9) regular source of care (none, 
less than 1 year, 1–5 years, 6–10 years, more than 
10 years); and 10) residency (rural, urban, 
suburban). 

Prior to administering the study questionnaire, it 
was pretested among 15 Black men to ensure 
content validity and readability of all questions and 
response categories. 

Recruitment of Participants and Data Collection 
The Institutional Review Board (IRB) at The 
University of Texas at Austin approved the study. 
Following IRB approval, participants were recruited 
from colleges and universities located around The 
University of Texas at Austin, as well as local 
organizations, community liaisons, and churches. A 

$20 VISA gift card was provided to participants as 
compensation for the time spent in completing the 
survey. Data was collected from local universities, 
churches, organization, and fraternities between 
February 2014 to April 2014, in Austin Texas using 
a mixed mode of survey distribution (paper-pencil 
and web-based using Qualtrics). 

Data Analyses 
All study variables were summarized using 
descriptive statistics (frequencies, means, and 
standard deviations). The reliability of the multi-
item scales, CaPB, and knowledge, were evaluated 
via Cronbach’s alpha. To develop a more 
parsimonious model, demographic/personal 
factors that were not related to the dependent 
variable were excluded from the multivariate 
analyses. Multiple regression models were 
constructed to examine statistically significant 
predictors of CaPB. The significance levels were set 
at 0.05 and data analyses were conducted using 
statistical package SPSS 24 (International Business 
Machine Corp., Armonk, New York). 

RESULTS 

A total of 267 Black men participated in the study, 
with an average age of 26±7 years (range, 18-40). 
Of the 267 participants, 171 (64%) were African-
American of American origin, 50 (18.9%) reported 
their academic classification as college freshmen. 
More than 70% (n=212) reported negative cues to 
action and majority (n=233; 87.6%) reported a 
negative family history of CaP. More than half 
(n=138; 52.5%) of the participants perceived their 
health to be good and more than 30% (n=90) had 
private insurance. Most participants (n=134; 51.0%) 
resided in urban areas and 41.9% (n=112) reported 
having no regular source of care. The exercise 
scale had a mean of 6.44±3.14 out of a possible 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e6                                              Cancer Health Disparities 
 

RESEARCH 

score of 0-10 (higher scores indicate a higher level, 
duration, and intensity of exercise). Mean 
knowledge levels were low among respondents 
with a score of 5.25 ± 3.81 (possible range of 0 to 
14). Descriptive characteristics of all other 
demographic variables are reported in Table 1. To 
build the parsimonious model, bivariate 
comparisons of CaP risk-reduction behavior scores 

were made with the independent variables. 
Academic classification, cues to action, family 
history of CaP, major field of study, and regular 
source of care were the only significant predictors 
of CaP risk-reduction behavior and were included 
in the final multivariate model. The results are 
summarized in Table 1. 

Table 1. Mean Prostate Cancer Risk Reduction Behavior Scores by Study Variables (N=267)a. 
Demographics na (%) Mean ± SD of Intention Scores t or F p 
Academic Classification   2.81 0.019* 

Less than high school/GED/High School 
Graduate 22 (8.3) 15.00 ± 5.54   

Freshman (College) 50 (18.9) 13.36 ± 6.03   
Sophomore (College) 35 (13.3) 12.69 ± 5.44   
Junior (College) 47 (17.8) 12.80 ± 5.56   
Senior (College) 48 (18.2) 12.93 ± 5.54   
Graduate Student 30 (11.4) 15.83 ± 5.76   
Postgraduate (e.g., MS, JD, MD, PhD) 32 (12.1) 14.97 ± 5.04   

Cues to Actionb   3.94 0.033* 
No 212 (79.4) 10.50 ± 5.43   
Yes 55 (20.6) 14.39 ± 6.23   

Ethnicity   1.28 0.283 
African-American of American origin 171 (64.0) 13.80 ± 6.02   
African 45 (16.9) 12.95 ± 4.88   
African-American of African origin 28 (10.5) 15.18 ± 4.55   
African-American of Caribbean 
origin/Caribbean 23 (8.6) 12.45 ± 4.81   

Family History of Prostate Cancer   8.18 0.005** 
No 233 (87.6) 13.64 ± 5.39   
Yes 33 (12.4) 14.21 ± 7.10   

Health Insurance   1.07 0.364 
Private Insurance (E.g., BlueCross/Blue Shield) 90 (34.7) 13.78 ± 5.86   
Public Insurance (E.g., CHIP, Medicaid) 48 (18.5) 14.87 ± 5.22   
Not Sure 41 (15.8) 12.73 ± 5.73   
No Insurance/Self-Pay 80 (30.9) 13.73 ± 5.65   

Income   0.70 0.404 
≤$30,000 126 (47.9) 13.04 ± 5.35   
≥ $30,001 137 (52.1) 14.06 ± 5.69   

Major/Field of Study   3.73 0.025* 
Professional & Applied Sciences 153 (58.1) 13.00 ± 5.29   
Natural & Healthcare Sciences 65 (24.3) 15.29 ± 5.81   



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e7                                              Cancer Health Disparities 
 

RESEARCH 

Humanities 47 (17.6) 13.83 ± 6.08   
Marital Status   1.19 0.305 

Single, NOT in a relationship 121 (46.2) 13.76 ± 5.62   
Single, IN a relationship 88 (33.6) 13.15 ± 5.60   
Married/ Partner/Living together 53 (20.2) 14.69 ± 5.78   

Perception of Health Status   1.22 0.297 
Fair 44 (16.7) 14.73 ± 6.27   
Good 138 (52.5) 13.28 ± 5.19   
Excellent 81 (30.8) 14.00 ± 5.82   

Regular Source of Care   3.83 0.026* 
None 112 (41.9) 12.99 ± 5.17   
Less than 1 year 55 (20.6) 14.94 ± 5.64   
1 – 5 years 60 (22.5) 13.13 ± 5.75   
More than 6 years 40 (15.0) 14.78 ± 6.29   

Residency   0.84 0.433 
Urban 134 (51.0) 13.73 ± 5.51   
Suburban 110 (41.2) 13.51 ± 5.67   
Rural 19 (7.1) 15.32 ± 5.93   

aTotal does not equal 267 due to missing responses 
bCues to action was collapsed into two categories: “0” represents those who answered “No” to having 
someone close to them who has ever had prostate cancer and “1” represents those who answered “Yes” to 
having someone close to them who has ever had prostate cancer 
*Indicates significance at p < 0.05 
**Indicates significance at p < 0.01 

Prostate Cancer Risk-Reduction Behavior (CaPB) 
The CaPB scale showed acceptable reliability as measured via internal consistency (Cronbach’s α=0.68). 
The CaPB scale had a mean of 13.70 ± 5.62 (range of 0-40). Many of the participants ate fruits (n=111; 
41.6%), vegetables (n=94; 35.5%), dairy products (n=83; 31.4%), and butter/oil 1-3 times a week (n=83; 
31.4%). More than one-third (n=97; 36.5%) of participants consumed meat products two or more times a 
day. Finally, the majority of the participants did not use chemoprevention products such as selenium, 
lycopene, Vitamins A, and D, retinoid, and soy within the last week [See Table 2]. 

 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e8                                              Cancer Health Disparities 
 

RESEARCH 

Table 2. Frequency Distribution of Participants’ Risk Reduction Behaviors (N=267) 
Q. Think about your eating habits within THE LAST WEEK. Counting breakfast, lunch, dinner, snacks and eating out, please state how often you ate the 
stated food or took the stated nutrients: 

  Frequency Distribution of Response Choices N (%) 
  Na Mean SD Never 

(0) 
1 – 3 

times a WEEK (1) 
4 – 6 times 
a WEEK (2) 

Once a 
DAY (3) 

2 or more times 
a DAY (4) 

1.  Fruit (fresh, canned or juice but not sodas). 267 1.88 1.10 12 
(4.5) 

111 
(41.6) 

71 
(26.6) 

43 
(16.1) 

30 
(11.2) 

2.  Vegetables (such as greens, vegetable soup, stew, green 
salad, string beans, peas, corn, broccoli). 

265 2.02 1.08 8 
(3.0) 

94 
(35.5) 

82 
(30.9) 

47 
(17.7) 

34 
(12.8) 

3.  Meat products (such as beef, goat, chicken, pork, steaks, 
roasts, ribs, hamburgers, ground beef, hotdog, sausage).d 

266 1.27 1.16 7 
(2.6) 

33 
(12.4) 

82 
(30.8) 

47 
(17.7) 

97 
(36.5) 

4.  Dairy products (such as milk, cheese, eggs). 264 1.86 1.10 7 
(2.6) 

83 
(31.4) 

75 
(28.4) 

63 
(23.9) 

36 
(13.6) 

5.  Butter or oil on food or in cooking. 267 1.91 1.09 10 
(3.7) 

83 
(31.4) 

81 
(30.3) 

60 
(22.5) 

33 
(12.4) 

6.  Selenium to prevent prostate cancer. 266 0.63 0.99 173 
(65.0) 

40 
(15.0) 

33 
(12.4) 

18 
(6.8) 

2 
(0.8) 

7.  Lycopene to prevent prostate cancer. 267 0.60 1.02 183 
(68.5) 

34 
(12.7) 

26 
(9.7) 

21 
(7.9) 

3 
(1.1) 

8.  Vitamin A and other retinoid to prevent prostate cancer. 267 1.15 1.22 113 
(42.3) 

60 
(22.5) 

46 
(17.2) 

38 
(14.2) 

10 
(3.7) 

9.  Vitamin D to prevent prostate cancer. 266 1.53 1.23 72 
(27.1) 

60 
(22.6) 

71 
(26.7) 

47 
(17.7) 

16 
(6.0) 

10.  Soy to prevent prostate cancer. 267 0.78 1.09 154 
(57.7) 

50 
(18.7) 

36 
(13.5) 

21 
(7.9) 

6 
(2.2) 

Score Total 266 13.7b 5.62      
Cronbach’s Alphac 0.68c        
aTotals do not equal 267 due to missing responses  
bThe composite score for the overall scale calculation based on 267 responses, possible scale range 0 to +40 
cCronbach’s alpha based on 10 items 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e9                                              Cancer Health Disparities 
 

RESEARCH 

Predictors of Prostate Cancer Risk-Reduction Behavior (CaPB) 
Knowledge and age were positively correlated with CaPB; the correlation matrix is reported in Table 3. 

Table 3. Correlations (r), Descriptive Statistics, and Reliability Statistics for Prostate Cancer Risk-Reduction 
Behavior Scores, and other Predictor Variables (N=267) 
Prostate cancer risk-reduction 
behavior scores, and other 
predictor variables 

Age Exercise Knowledge Mean (SD) Actual 
Range 

Cronbach’s α 

1. Prostate cancer risk reduction 
behavior 

0.13* -0.02 0.17** 13.70 (5.62) 1 to +30 0.68 

2. Age  -0.14* 0.18** 26.44 (6.67) 18 to 40 - 
3. Exercise   -0.05 6.44 (3.14) 0 to +10 0.85 
4. Knowledge     5.25 (3.81) 0 to +13 0.84 
* p < .05 level (2-tailed); ** p < .01 level (2-tailed) 

The CaPB regression model was statistically significantly different from zero, F=4.12, df = 18, 250; p < 0.01. 
Approximately 39% of the variation in CaPB (R2 = 0.39) was accounted for by the predictor variables, with 
knowledge, academic classification, major/field of study, and regular source of care being significant 
factors. The results of the multiple regression are presented in Table 4. In summary, the model accounted 
for a large variance in engagement in CaPB. 

Table 4. Multiple Regression Analysis of Prostate Cancer Risk-Reduction Behaviors (N=250). 

Variable 
Standardized 
Coefficients 

95.0% Confidence Intervala 
  

 

Beta Lower Bound  Upper Bound P-values 
Intercept  11.31 20.80 <0.01** 
Independent Variables         
     Age -0.31 -0.05 -0.17 0.08 
     Cues to Actionb 0.07 -1.12 2.92 0.39 
     Exercise 0.03 -0.17 0.29 0.61 
     Knowledge  0.26 0.18 0.40 <0.05** 
Covariates     
Academic Classificationc         
     Freshman (College) -0.13 -4.81 1.05 0.21 
     Sophomore (College) -0.28 -5.94 -0.40 0.027* 
     Junior (College) -0.15 -5.10 0.72 0.14 
     Senior (College) -0.22 -5.71 -0.28 0.018* 
     Graduate Student  0.05 -2.21 4.05 0.56 
     Postgraduate (e.g., MS, MD, PhD) -0.02 -3.71 2.97 0.83 
Family History of Prostate Cancerd -0.05 -3.36 1.71 0.52 
Major/Field of Studye         
     Professional & Applied Sciences -0.20 -4.15 -0.54 <0.05** 
     Humanities -0.12 -3.96 0.58 0.14 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e10                                              Cancer Health Disparities 
 

RESEARCH 

Regular Source of Care     
     Less than 1 year 0.11 -0.35 3.62 0.11 
     1 – 5 years -0.05 -2.48 1.25 0.52 
     More than 6 years  0.16 -0.30 3.84 0.03* 
F statistic =4.12; df=18, 250;  Model p-value< 0.01; R2=0.39; Adjusted R2=0.34 
aCI = confidence interval of unstandardized coefficients 
bReference category: No  
cReference category: Less than high school/GED/High School Graduate 
dReference category: No  
eReference category: Natural & healthcare sciences 
*Indicates significance at p < 0.05 
**Indicates significance at p < 0.01 

DISCUSSION 

The summary score on the dependent variable, 
CaPB, was low with an average score of 13.7 
(possible score of 40). This finding could be 
because the majority of the participants sampled 
were not taking vitamins/supplements to prevent 
CaP, which is not unexpected given the age range 
of the participants. Also, young Black men in this 
study consumed more quantities of food 
associated with risk of CaP (e.g., meat, butter) and 
fewer quantities of foods that can decrease risk 
(fruits, Vitamin A, Vitamin D). The low consumption 
of CaP risk-reducing foods such as vegetables has 
been well documented in Blacks, with Black young 
adults consuming a higher intake of saturated fat 
and cholesterol (Zamora et al., 2010) than their 
White counterparts. The CaPB scale was found to 
be reliable in assessing the variables of interest, 
which is consistent with studies done by Cobran et 
al. and Odedina et al. (Cobran et al., 2014; 
Odedina et al., 2011a). Knowledge was positively 
and statistically significant (p<0.01) with 
engagement in CaPB, which shows that as 
knowledge scores increase, the level of 
engagement in CaPB for young Black males 
increases. This relationship indicates that when 

younger Black males have a better understanding 
of domains pertinent to CaP and screening, such 
as limitations, side effects from treatments, 
symptoms, risk factors, screening age guidelines, 
and screening controversy, they are more likely to 
engage in behaviors that reduce their risk of CaP. 
Therefore, efforts made at improving engagement 
in CaPB in this special population could begin with 
assessing knowledge levels. The association found 
in the current study between knowledge and CaPB 
is similar to other study findings conducted in 
older Black males (Odedina et al., 2011b). The 
study by Horwood et al. (Horwood et al., 2014) 
had similar findings but reported that men were 
confused by conflicting messages in the media 
about dietary practices to promote overall health 
and preferred tailored dietary advice from their 
clinicians. While the current study did not assess 
source of information as a measure of cues to 
action, this could be a focal area of interest for 
future studies. Other studies have also shown the 
importance of increasing knowledge levels to aid 
adoptions of healthier cancer risk-reduction 
behaviors (Jepson et al., 2010; Kyle et al., 2013). 

Compared to those in the less than high school 
category, engagement in risk-reduction behavior 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e11                                              Cancer Health Disparities 
 

RESEARCH 

reduced with increasing educational levels (in the 
college sophomore and college senior groups). 
While studies have not yet shown a direct 
relationship between educational levels and 
engagement in CaPBs, other findings have 
suggested that highly educated people tend to be 
more proactive about their health than those with 
low education levels (Arora and McHorney, 2000). 
More studies are needed to clearly understand the 
role of education on preventive behaviors, 
especially among college students. 

Participants in professional and applied sciences 
programs had lower levels of engagement in 
preventive behaviors compared to those in the 
natural/healthcare sciences. An explanation for this 
is that those in the natural/healthcare sciences 
may be more proactive about engaging in CaPB 
because of their scholastic knowledge of healthy 
behaviors. However, it is likely that several 
interrelating factors such as income/finance, 
personal beliefs, and information seeking status 
may also be responsible for this finding (Ross et 
al., 2011). As a result, educational efforts can be 
designed to meet the knowledge needs of 
students from non-natural/healthcare science field 
to fill this gap. 

Having a prolonged and constant source of care, 
which could be a proxy of sustained patient-
provider communication, was a positive and 
significant predictor of engagement in CaPB. This 
can also mean that young Black men who have 
steady interactions with their healthcare providers 
might be receiving pertinent information which 
could inform their decisions to engage in risk-
reduction behaviors. As a result, interventions 
aimed at improving engagement in CaPB could 
explore patient-provider communication and its 
impact on informed decision-making as it relates 

to future CaP screening practices. It is also more 
paramount given that patient-provider interaction 
plays a huge role in engaging in more relevant 
proactive behaviors, such as CaP screening 
(Berglund et al., 2005; Hoffman et al., 2010). 

Age, cues to action, exercise, and family history of 
CaP were not significantly associated with CaPB in 
the overall regression model. However, a positive 
relationship has been demonstrated between cues 
to action and CaPB in a study conducted in older 
Black men (Odedina et al., 2011b). Thus, the 
insignificant relationship observed in the current 
study could be due to participants in this study 
being younger. 

Several study limitations could have affected the 
interpretation and generalizability of the study 
results. The methodology utilized convenience 
sampling which limits the generalizability of study 
findings. Self-report surveys are also prone to 
selection and response bias. Since respondents 
self-reported their behaviors, it is possible that 
some of these were over- or underreported. Recall 
bias is also a limitation as some questions required 
participants to recall activities conducted within the 
previous week. Also, the research design was 
cross-sectional in nature. Thus study findings may 
not reflect causative relationships among variables 
of interest. Finally, other relevant variables of 
correlational interest, such as tobacco and alcohol 
use, were not assessed in the current study. Future 
studies could assess the impact of these variables. 
Future studies can also examine the impact of 
environmental factors, such as promotional 
campaigns, as potential cues in engaging in CaPB. 

CONCLUSION 

Few intervention-based studies have explored 
cognitive-behavioral factors in younger Black men 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e12                                              Cancer Health Disparities 
 

RESEARCH 

with the goal of raising awareness about CaPB. 
The current study highlights the importance of 
raising awareness in the younger population who 
may be at risk of CaP. Thus, interventional efforts 
aimed at targeting this at-risk group should focus 
on improving knowledge gaps. In this population, 
modifiable health behaviors can be targeted to 
help reduce the overall future incidence of CaP. 
The gains from an early start of behavior 
modification can help reduce the overall clinical, 
economic, and humanistic burden of CaP. A 
prospective cohort design in future studies 
tracking cognitive-behavior change among Black 
men (<40 years old) relative to CaP modifiable 
factors would illuminate which behaviors are easily 
amenable to change and what factors influence 
that change. 

Acknowledgments 
We acknowledge and thank all of our study 
participants. 

Conflict of interest 
The authors declare that no competing or conflict of 
interests exists.  

Authors’ contributions 
Motolani Ogunsanya conducted the statistical 
analysis of the project and provided content and 
generated the initial draft of the article.Motolani 
Ogunsanya and Folakemi Odedina contributed to 
the acquisition of data. Folakemi Odedina, Ernest 
Kaninjing, Sunday Atawodi, Titilola Akinremi, and 
Anthonia Sowumni provided content and reviewed 
the final manuscript  

 
REFERENCES 
IBM Corp. Released 2016. IBM SPSS Statistics for Windows, 

Version 24.0. Armonk, NY: IBM Corp. 

. National Cancer Institute. Cancer Trends Progress Report – 
Costs of Cancer Care 2020. 

Arora, N.K., and McHorney, C.A. (2000). Patient preferences 
for medical decision making: who really wants to 
participate? Med Care 38, 335-341. 

Berglund, G., Nilsson, S., and Nordin, K. (2005). Intention to 
test for prostate cancer. European Journal of Cancer 41, 
990-997. 

Cheatham, C.T., Barksdale, D.J., and Rodgers, S.G. (2008). 
Barriers to health care and health-seeking behaviors 
faced by Black men. Journal of the American Academy of 
Nurse Practitioners 20, 555-562. 

Cobran, E.K., Wutoh, A.K., Lee, E., Odedina, F.T., Ragin, C., 
Aiken, W., and Godley, P.A. (2014). Perceptions of 
prostate cancer fatalism and screening behavior between 
United States-born and Caribbean-born Black Males. 
Journal of immigrant and minority health 16, 394-400. 

Colli, J.L., and Amling, C.L. (2009). Chemoprevention of 
prostate cancer: what can be recommended to patients? 
Curr Urol Rep 10, 165-171. 

Cuzick, J., Thorat, M.A., Andriole, G., Brawley, O.W., Brown, 
P.H., Culig, Z., Eeles, R.A., Ford, L.G., Hamdy, F.C., 
Holmberg, L., et al. (2014). Prevention and Early 
Detection of Prostate Cancer. The Lancet Oncology 15, 
e484-e492. 

Daniel, C.R., Cross, A.J., Koebnick, C., and Sinha, R. (2011). 
Trends in meat consumption in the USA. Public health 
nutrition 14, 575-583. 

Dixon, L.B., Subar, A.F., Peters, U., Weissfeld, J.L., Bresalier, 
R.S., Risch, A., Schatzkin, A., and Hayes, R.B. (2007). 
Adherence to the USDA Food Guide, DASH Eating Plan, 
and Mediterranean dietary pattern reduces risk of 
colorectal adenoma. The Journal of nutrition 137, 2443-
2450. 

Giovannucci, E., Rimm, E.B., Liu, Y., Stampfer, M.J., and Willett, 
W.C. (2002). A, prospective study of tomato products, 
lycopene, and prostate cancer risk. Journal of the 
National Cancer Institute 94, 391-398. 

Hoffman, R.M., Lewis, C.L., Pignone, M.P., Couper, M.P., Barry, 
M.J., Elmore, J.G., Levin, C.A., Van Hoewyk, J., and 
Zikmund-Fisher, B.J. (2010). Decision-Making Processes 
for Breast, Colorectal, and Prostate Cancer Screening: 
The DECISIONS Survey. Medical Decision Making 30, 
53s-64s. 

Horwood, J.P., Avery, K.N., Metcalfe, C., Donovan, J.L., Hamdy, 
F.C., Neal, D.E., and Lane, J.A. (2014). Men’s knowledge 
and attitudes towards dietary prevention of a prostate 
cancer diagnosis: a qualitative study. BMC cancer 14, 812. 

Jepson, R.G., Harris, F.M., Platt, S., and Tannahill, C. (2010). The 
effectiveness of interventions to change six health 
behaviours: a review of reviews. BMC public health 10, 
538. 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e13                                              Cancer Health Disparities 
 

RESEARCH 

Kolonel, L.N., Hankin, J.H., Whittemore, A.S., Wu, A.H., 
Gallagher, R.P., Wilkens, L.R., John, E.M., Howe, G.R., 
Dreon, D.M., and West, D.W. (2000). Vegetables, fruits, 
legumes and prostate cancer: a multiethnic case-control 
study. Cancer Epidemiology Biomarkers & Prevention 9, 
795-804. 

Kyle, R.G., Nicoll, A., Forbat, L., and Hubbard, G. (2013). 
Adolescents’ awareness of cancer risk factors and 
associations with health-related behaviours. Health 
Education Research 28, 816-827. 

Lee, D.J., Consedine, N.S., Gonzalez, J.R., and Spencer, B.A. 
(2012). Association of Healthcare Barriers With Prostate-
specific Antigen Screening Among African-American and 
Afro-Caribbean Men. Urology 80, 556-563. 

Li, J., Djenaba, J.A., Soman, A., Rim, S.H., and Master, V.A. 
(2012). Recent trends in prostate cancer incidence by 
age, cancer stage, and grade, the United States, 2001–
2007. Prostate cancer 2012. 

Lin, K., Croswell, J.M., Koenig, H., Lam, C., and Maltz, A. (2011). 
Prostate-specific antigen-based screening for prostate 
cancer: an evidence update for the US Preventive 
Services Task Force. Agency for Healthcare Research and 
Quality. 

Lippman, S.M., Klein, E.A., Goodman, P.J., and et al. (2009). 
Effect of selenium and vitamin e on risk of prostate 
cancer and other cancers: The selenium and vitamin e 
cancer prevention trial (select). JAMA 301, 39-51. 

Liu, Y., Hu, F., Li, D., Wang, F., Zhu, L., Chen, W., Ge, J., An, R., 
and Zhao, Y. (2011). Does physical activity reduce the risk 
of prostate cancer? A systematic review and meta-
analysis. European urology 60, 1029-1044. 

Mandair, D., Rossi, R.E., Pericleous, M., Whyand, T., and 
Caplin, M.E. (2014). Prostate cancer and the influence of 
dietary factors and supplements: a systematic review. 
Nutrition & metabolism 11, 30. 

Mauermann, J., Pouliot, F., and Fradet, V. (2011). Dietary 
omega-3 fatty acids, genetic variation and risk of breast 
and prostate cancers. World Rev Nutr Diet 102, 156-171. 

McNaughton-Collins, M.F., and Barry, M.J. (2011). One Man at 
a Time - Resolving the PSA Controversy. New England 
Journal of Medicine 365, 1951-1953. 

Millon-Underwood, S., and Sanders, E. (1990). Factors 
contributing to health promotion behaviors among 
African-American men. Oncology nursing forum 17, 707-
712. 

Morrison, B.F., Aiken, W.D., Mayhew, R., Gordon, Y., and 
Odedina, F.T. (2017). Prostate cancer knowledge, 
prevention, and screening behaviors in Jamaican men. 
Journal of Cancer Education 32, 352-356. 

Moyer, V.A. (2012). Screening for prostate cancer: U.S. 
Preventive Services Task Force recommendation 
statement. Annals of internal medicine 157, 120-134. 

Odedina, F.T., Akinremi, T.O., Chinegwundoh, F., Roberts, R., 
Yu, D., Reams, R.R., Freedman, M.L., Rivers, B., Green, 
B.L., and Kumar, N. (2009). Prostate cancer disparities in 
Black men of African descent: a comparative literature 
review of prostate cancer burden among Black men in 
the United States, Caribbean, United Kingdom, and West 
Africa. Infectious Agents and Cancer 4 Suppl 1, S2. 

Odedina, F.T., Dagne, G., LaRose-Pierre, M., Scrivens, J., 
Emanuel, F., Adams, A., Pressey, S., and Odedina, O. 
(2011a). Within-group differences between native-born 
and foreign-born Black men on prostate cancer risk 
reduction and early detection practices. J Immigr Minor 
Health 13, 996-1004. 

Odedina, F.T., Scrivens, J.J., Larose-Pierre, M., Emanuel, F., 
Adams, A.D., Dagne, G.A., Pressey, S.A., and Odedina, O. 
(2011b). Modifiable Prostate Cancer Risk Reduction and 
Early Detection Behaviors in Black Men. American Journal 
of Health Behavior 35, 470-484. 

Ogunsanya, M.E., Brown, C.M., Odedina, F.T., Barner, J.C., 
Adedipe, T.B., and Corbell, B. (2017). Knowledge of 
Prostate Cancer and Screening Among Young 
Multiethnic Black Men. Am J Mens Health, 
1557988316689497. 

Powell, I.J., Bock, C.H., Ruterbusch, J.J., and Sakr, W. (2010). 
Evidence Supports a Faster Growth Rate and/or Earlier 
Transformation to Clinically Significant Prostate Cancer in 
Black Than in White American Men, and Influences Racial 
Progression and Mortality Disparity. The Journal of 
Urology 183, 1792-1797. 

Ross, L., Dark, T., Orom, H., Underwood, W., Anderson-Lewis, 
C., Johnson, J., and Erwin, D.O. (2011). Patterns of 
information behavior and prostate cancer knowledge 
among African–American men. Journal of Cancer 
Education 26, 708-716. 

Sanchez, M.A., Bowen, D.J., Hart, A., Jr., and Spigner, C. 
(2007). Factors influencing prostate cancer screening 
decisions among African American men. Ethnicity & 
Disease 17, 374-380. 

Scher, H.I., Leibel, S., Fuks, Z., Cordon-Cardo, C., and 
Scardino, P. (2015). Cancer of the prostate. DeVita, 
Hellman, and Rosenberg's Cancer Principles and 
Practices of Oncology, 932-980. 

Siegel, R., Ma, J., Zou, Z., and Jemal, A. (2014). Cancer 
statistics, 2014. CA Cancer J Clin 64, 9-29. 

Simopoulos, A.P. (2010). Genetic variants in the metabolism of 
omega-6 and omega-3 fatty acids: their role in the 
determination of nutritional requirements and chronic 
disease risk. Exp Biol Med (Maywood) 235, 785-795. 

Tourville, E.A., and Nguyen, M.M. (2013). Prostate cancer 
detection by using digital rectal examination: 
contemporary practice patterns in the united states. 
Clinical genitourinary cancer 11, 263-269. 



 
 
 
 
 

 
www.companyofscientists.com/index.php/chd                   e14                                              Cancer Health Disparities 
 

RESEARCH 

Verma, S.M., Okawa, J., Propert, K.J., and Werth, V.P. (2014). 
The impact of skin damage due to cutaneous lupus on 
quality of life. Br J Dermatol 170, 315-321. 

Weinrich, S., Seger, R., Miller, B.L., Davis, C., Kim, S., Wheeler, 
C., and Weinrich, M. (2004). Knowledge of the limitations 
associated with prostate cancer screening among low-
income men. Cancer nursing 27, 442-453. 

Whittemore, A.S., Kolonel, L.N., Wu, A.H., John, E.M., 
Gallagher, R.P., Howe, G.R., Burch, J.D., Hankin, J., Dreon, 
D.M., West, D.W., et al. (1995). Prostate Cancer in 
Relation to Diet, Physical Activity, and Body Size in Blacks, 
Whites, and Asians in the United States and Canada. 
JNCI: Journal of the National Cancer Institute 87, 652-661. 

Wigle, D.T., Turner, M.C., Gomes, J., and Parent, M.E. (2008). 
Role of hormonal and other factors in human prostate 
cancer. J Toxicol Environ Health B Crit Rev 11, 242-259. 

Wu, I., and Modlin, C.S. (2012). Disparities in prostate cancer in 
African American men: what primary care physicians can 
do. Cleve Clin J Med 79, 313-320. 

Zamora, D., Gordon-Larsen, P., Jacobs Jr, D.R., and Popkin, 
B.M.J.T.A.j.o.c.n. (2010). Diet quality and weight gain 
among black and white young adults: the Coronary 
Artery Risk Development in Young Adults (CARDIA) 
Study (1985–2005)–.  92, 784-793. 

 
 
 
 
 
 


