PRS4799_Dissertation_M00510169_Final

Abstract
BASELINE CARDIOVASCULAR DISEASE KNOWLEDGE, BEHAVIOR, ATTITUDES IN WOMEN, AND
THE EFFICACY OF HEALTH PARTIES AS A METHOD OF ADDRESSING SHORTCOMINGS
BASELINE CARDIOVASCULAR DISEASE
KNOWLEDGE, BEHAVIOR, AND ATTITUDES IN
BAME WOMEN, AND THE EFFICACY OF
HEALTH PARTIES AS A METHOD OF
ADDRESSING SHORTCOMINGS
Author:
Michelle Roxanna Moshiri (M00510169)
Supervisor:
Carmen Aceijas
Dissertation Prepared as Summative Assessment for
PRS 4799: Research Methodology and Dissertation
MSc Applied Public Health
Middlesex University
Submitted: 02 July 2015

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Abstract
This quasi-experimental study examined baseline population cardiovascular disease
(CVD) knowledge levels and behaviors, and the efficacy of a health education intervention.
The project targeted BAME women because of the associated health disparities and because
of their roles as the centers of the family.
CVD is the most common cause of mortality in London, and its risk factors
disproportionately impact the city’s growing BAME population. These inequalities can be
examined through the lens of Freedom Poverty, a framework which describes populations’
freedom to actively participate in society and which contributes to a 3.02 relative risk of
CVD. Because London’s BAME population is disproportionately impacted by Freedom
Poverty, the results of this study were examined through its framework.
The participants in this study were recruited through partnerships with local
organizations; they were given a baseline survey, participation in a CVD workshop, and a
post-seminar survey. The questionnaire included demographic questions, knowledge through
the validated CARRF-KL scale, health behaviors, and two open ended questions to explore
perceived barriers to health and health demands.
Multivariate linear regression showed that CVD knowledge scores were positively
correlated to time spent in the UK and previous exposure to CVD. Behavior had negative
correlations to education, time in the UK, and primary exposure to CVD. Comparisons of
baseline and post-seminar questionnaires showed that the intervention is promising in its
ability to improve participant knowledge and behaviors.
Qualitative analysis of the open ended questions showed that participants were concerned
about their family health, nutrition, and exercise opportunities, indicating a lack of more
access to health resources for traditionally underserved communities.
This project showed that the educational intervention is promising at improving CVD
behavior and knowledge among at risk populations. Observations during the course of the
workshops showed that the social networks were being used to increase community
knowledge levels. Participants were open to learning about local resources in hopes of
improving family health, making expansions of this project promising to fulfill the goals of
increasing knowledge, healthy behaviors, and resource uptake.

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Acknowledgements
I wish to express my appreciation to my supervisor, Carmen Aceijas, for her
encouragement and useful critiques and discussions during the process of developing,
executing, and writing about this project. It was with her inspiration that I was able to
continuously improve my design, work, and presentation as I strove to bring all I produced to
her level of “perfect.”
I would like to thank UCLPartners, the Gargar Foundation, and the South Isleworth for
their cooperation in recruiting participants and providing spaces in which to conduct the
workshops and data collection. I have the upmost gratitude for the participants of the
workshop and surveys, without whose time and effort this thesis would not have been
possible.
Finally, I would like to thank my loved ones for their support and encouragement through
this entire process. I am overwhelmed with gratitude to my fiancé, Philip Warncke, for his
constant reassurances, discussions, support, insight, and breakfast eggs during the
development of this thesis, without which none of this would be possible.

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Table of Contents
Abstract..................................................................................................................................................1
Acknowledgements ...............................................................................................................................2
I. Introduction .......................................................................................................................................7
I. A. Cardiovascular disease and London...........................................................................................7
I. B. London BAME Population - Justification of Targeted Population.............................................7
I. C. Freedom Poverty - Framework of Intervention Design and Analysis ........................................7
I. D. Multidimensional Approach of Project.......................................................................................7
II. Methods.............................................................................................................................................8
II. A. Design........................................................................................................................................8
II. B. Research Aims and Objectives...................................................................................................8
II. C. Participants ...............................................................................................................................9
II. D. Intervention ...............................................................................................................................9
II. E. Data Collection........................................................................................................................10
II. F. Plans of Analysis......................................................................................................................11
II. F. 1. Statistical .........................................................................................................................11
II. F. 2. Qualitative .......................................................................................................................12
III. Explanation of Chosen Focus Variables and Health Behaviors...............................................12
III. A. Education Level......................................................................................................................12
III. B. Time Spent in the UK..............................................................................................................13
III. C. Previous Exposure to CVD.....................................................................................................13
III. D. Chosen Health Behaviors.......................................................................................................13
IV. Literature Review.........................................................................................................................14
IV. A. CVD in London.......................................................................................................................14
IV. B. Introduction to Freedom Poverty ...........................................................................................14
IV. C. Freedom Poverty and BAME Populations .............................................................................15
IV. D. Freedom Poverty Stressors and CVD ....................................................................................15
IV. E. Women and CVD ....................................................................................................................16
IV. F. BAME Women and CVD.........................................................................................................18
IV. G. Previous Interventions............................................................................................................18
IV. H. Introduction to Home Health Parties as used in this Study ...................................................19
V. Results .............................................................................................................................................20
V. A. Included and Excluded Data....................................................................................................20
V. B. Data Transformation................................................................................................................21
V. C. Participant Demographics and Past Exposure........................................................................22
V. D. Baseline Knowledge Levels .....................................................................................................22

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V. D. 1. Bivariate Analysis: Education Level and Knowledge Score............................................23
V. D. 2. Bivariate Analysis: Time in the UK and Knowledge Score.............................................23
V. D. 3. Bivariate Analysis: Primary Exposure to CVD and Knowledge Score ..........................23
V. D. 4. Bivariate Analysis: Secondary Exposure to CVD and Knowledge Score.......................24
V. D. 5. Multivariate Analysis: Model 1 - Education, Time in the UK, Primary Exposure to CVD,
and Secondary Exposure to CVD with relation to Knowledge Score...........................................24
V. D. 6. Multivariate Analysis: Model 2 - Time in the UK, Primary Exposure to CVD, and
Secondary Exposure to CVD with relation to Knowledge Score..................................................24
V. E. Baseline Behavior Levels.........................................................................................................25
V. E. 1. Bivariate Analysis: Education Level and Behavior Level................................................25
V. E. 2. Bivariate Analysis: Time spent in the UK and Behavior Level........................................26
V. E. 3. Bivariate Analysis: Primary Exposure to CVD and Behavior Level ...............................26
V. E. 4. Bivariate Analysis: Secondary Exposure to CVD and Behavior Score ...........................26
V. E. 5. Multivariate Analysis: Education, Time in the UK, Primary Exposure to CVD, and to
CVD with relation to Behavior Score ...........................................................................................26
V. F. Comparison of Knowledge Levels: Baseline and Post-Seminar..............................................27
V. G. Comparison of Behavior Levels: Baseline and Post Seminar .................................................27
V. H. Qualitative Results...................................................................................................................27
V. H. 1. Question: What are some things you feel are keeping you or your loved ones from being
as healthy as possible?..................................................................................................................27
V. H. 2. What are some things you hope to gain from this seminar?............................................28
VI. Discussion of Results ....................................................................................................................28
VI. A. Baseline Knowledge Levels ....................................................................................................28
VI. A. 1. Bivariate Analysis: Education Level and Knowledge Score..........................................28
VI. A. 2. Bivariate Analysis: Time in the UK and Knowledge Score ............................................28
VI. A. 3. Bivariate Analysis: Primary Exposure to CVD and Knowledge Score ..........................29
VI. A. 4. Bivariate Analysis: Secondary Exposure to CVD and Knowledge Score.......................29
VI. A. 5. Multivariate Analysis: Knowledge Model 1 - Education, Time in the UK, Primary
Exposure to CVD, and Secondary Exposure to CVD with relation to Knowledge Score.............30
VI. A. 6. Multivariate Analysis: Knowledge Model 2 - Time in the UK, Primary Exposure to
CVD, and Secondary Exposure to CVD with relation to Knowledge Score.................................30
VI. B. Baseline Behavior Levels........................................................................................................31
VI. B. 1. Bivariate Analysis: Education Level and Behavior Level ..............................................31
VI. B. 2. Bivariate Analysis: Time spent in the UK and Behavior Level.......................................31
VI. B. 3. Bivariate Analysis: Primary Exposure to CVD and Behavior Level..............................32
VI. B. 4. Bivariate Analysis: Secondary Exposure to CVD and Behavior Score..........................32
VI. B. 5. Multivariate Analysis: Behavior Model - Education, Time in the UK, Primary Exposure
to CVD to CVD with relation to Behavior Score ..........................................................................32

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VI. C. Comparison of Knowledge Levels: Baseline and Post Seminar.............................................33
VI. D. Comparison of Behavior Levels: Baseline and Post Seminar................................................33
VI. E. Qualitative Analysis of Open Ended Questions......................................................................34
VII. Scope, Constraints, and Limits..................................................................................................35
IX. Conclusions ...................................................................................................................................37
References............................................................................................................................................39
Appendix 1. Prevalence of CVD by Ethnicity.....................................................................................47
Appendix 2. Overview of Project and Data Analysis ..........................................................................48
Appendix 3: Questionnaire Used in this Project..................................................................................49
Appendix 4: London Unemployment Levels by Ethnicity ..................................................................51
Appendix 5: Figures for Participant Demographics ............................................................................52
Appendix 6: Figures for Baseline Knowledge Levels .........................................................................57
Appendix 7: Figures for Baseline Behavior Levels.............................................................................58
Appendix 8. Comparison of Knowledge Levels: Baseline and Post-Seminar.....................................59
Appendix 9. Comparison of Behavior Levels: Baseline and Post Seminar.........................................60

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List of Tables
Table 1: Bivariate Linear Regression Variables and Knowledge Level ........................................................23
Table 2: Multivariate Linear Regression Knowledge Model 1.....................................................................24
Table 3: Multivariate Linear Regression Knowledge Model 2 .....................................................................25
Table 4: Bivariate Linear Regression Variables and Behavior.....................................................................25
Table 5: Multivariate Linear Regression Behavior Model...........................................................................27
List of Figures
Figure 1: Prevalence of CVD by Sex and Ethnic Group, 2004, England ......................................................47
Figure 2: Overview of Project Phases .......................................................................................................48
Figure 3: Overview of Concurrent Embedded Theory .............................................................................48
Figure 4: London Unemployment Levels by Ethnicity, 2014 3rd Quarter.....................................................51
Figure 5: Unemployment by Ethnic Group................................................................................................51
Figure 6: Participant Education Levels .....................................................................................................52
Figure 7: Time Participants Have Spent in the UK.....................................................................................53
Figure 8: Participant Ethnic Background...................................................................................................54
Figure 9: Previous Primary Exposure to CVD or Precursors .......................................................................55
Figure 10: Participant Secondary Exposure to CVD or Precursors...............................................................56
Figure 11: Baseline Knowledge Levels.....................................................................................................57
Figure 12: Baseline Behavior Levels ........................................................................................................58
Figure 13: Changing Participant Knowledge Levels...................................................................................59
Figure 14: Baseline and Intended Behaviors..............................................................................................60

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I. Introduction
I. A. Cardiovascular disease and London
Cardiovascular disease - CVD - is the most common cause of mortality in London and in
the UK, where it has an annually rising cost of £18.9 billion (Bernick and Davis, 2014). In
London, the mortality rate is 79 deaths per 100,000 people (Commissioning Support for
London, 2014). This number has been achieved after a steady decrease over several years
(ibid.), but upon closer examination, the unequal decreases across deprivation levels is
indicative of the goals of the Marmot review for its role as an indicator of expanding health
inequalities (Marmot and Bell, 2012; Heart UK, 2013).
I. B. London BAME Population - Justification of Targeted Population
London has a large Black Asian and Minority Ethnic - BAME - population with less
than 45% the population identifying as White British (Kerley, 2014). The BAME population
is growing while the white population remains stable (Klodawski, 2013), indicating that CVD
interventions must be focused on these groups. This is crucial as the BAME populations are
disproportionately impacted by CVD - see Appendix 1 (Heart UK, 2013).
I. C. Freedom Poverty - Framework of Intervention Design and Analysis
Environmental stressors are key to understanding and addressing CVD health disparities.
These include mutually enforcive poverty, unemployment, low education status, and
unhealthy diets (The Cardiac Society of Australia and New Zealand, 2014). Because of the
multidimensional nature of CVD risks and inequalities, successful interventions must involve
a multidimensional approach.
I. D. Multidimensional Approach of Project
This project had such a multidimensional approach. It was a free program to address the
problems associated with low income. All discussions from the education were developed
from the wide reaching and easily understood BHF Healthy Hearts Kit, thereby
simultaneously addressing low health literacy and the difficulties associated with low
education status. The topics included: CVD definitions, risks, health behaviors, and resources
available to help make behavior changes possible.

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I. E. Aims and Goals
This project was designed with the following goals in mind:
● Develop a better understanding of baseline knowledge levels of CVD risk with
respect to immigration status and freedom poverty markers
● Develop a better understanding of participants’ perceived barriers to CVD health and
health demands
● Increase participant knowledge of CVD risk factors and behaviors
● Increase participant likelihood of engaging in CVD health promoting behaviors
II. Methods
II. A. Design
This was a mixed methods quasi-experimental study. The intervention centered on a
health seminar which will discuss CVD risk, health promoting behaviors, and already
available heart health resources. It is quasi-experimental as baseline surveys were compared
to a post-seminar survey. The study used mixed methods as it included both a quantitative
component and a qualitative exploratory component.
The mixed methods approach of this study followed the concurrent embedded strategy
(Creswell, 2009; Creswell et al., 2006; Hanson et al., 2005); quantitative and qualitative data
were collected simultaneously but address different questions, thus providing a more
complete understanding of the CVD health of London’s BAME populations (ibid.). The
quantitative analysis assessed baseline levels of risk knowledge and behaviors, as well as the
efficacy of the program; the qualitative portion explored the population experiences and
wider barriers to community health. A more detailed description of the data collection and
analysis will be found later in section II. An overview of the program and data collection can
be found in Appendix 2.
II. B. Research Aims and Objectives
The aims of this study included increased knowledge of CVD risk, health promoting
behaviors, and available health resources. This was done in the hopes of increasing both
healthy behaviors and uptake of resources. The larger goal was to promote CVD health
throughout the wider community by making use of already established social networks,
thereby decreasing the existing levels of health inequality. Another aim of this study was to
establish the population’s baseline risk knowledge levels, and how they are impacted with

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respect to immigrant status and freedom poverty markers. The study will also have the
additional aim of exploring participants’ perceived barriers to health.
There were two measurable objectives of this intervention are: baseline knowledge
levels of CVD and increases in participant knowledge, a quantifiable measure of the
intervention’s efficacy. The qualitative objective was a further understanding of a
disadvantaged population’s perceived barriers to health. Both the knowledge levels and the
descriptions of these perceived barriers made up the outcome variables of this study.
Based on the proposed design, the questions of this research project will attempt to
answer are as follow:
● What are the baseline knowledge levels of CVD risk factors and protective behaviors?
● What are common CVD related protective or detrimental health behaviors that are
currently prevalent in the participating community?
● What are the barriers to optimal use of available CVD health resources?
● How does this program impact participants’ knowledge of CVD and available health
resources?
II. C. Participants
The target population for this study was BAME women. The initial participants were
recruited through UCL Partners’ health promotion outreach, together with a partnership with
the Gargar foundation. Other participants were recruited through partnerships with family
centers including the South Isleworth Children's Centre. As with the original tupperware and
“home health parties,” a host, once recruited, was expected to recruit their friends, family,
and fellow community members. Should the program continue, this type of snowball
recruiting will be used to as future hosts will be contacted and recruited based on the
recommendations and introductions of the participants. This strategy has been shown to be
effective at recruiting hard to reach populations - as with London’s BAME population -
because it makes use of existing social networks and community trust (Sadler et al., 2010).
II. D. Intervention
The “home health parties” of this intervention were modelled after Sadler’s original
program - see section IV.H - but were modified to reduce risk. Rather than taking place in a
home and expose the educator to undue risk, these seminars took place in local churches and
community centers to be physically and culturally near to the heart of the community.

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Culturally sensitive snacks and drinks were provided to spare the host financial
inconvenience. Each seminar had 6-10 participants and lasted 1.5-2 hours.
The content of the educational seminar was adapted from the British Heart Foundation -
BHF- resources to address three specific subject areas: 1) heart disease and its signs,
symptoms, and risks, 2) behaviors that depress or promote health, 3) heart health resources
provided through charities or local councils. The participants were also able to take home free
BHF and local council pamphlets which will include heart health information and resource
contact details. There will be up to ten sessions to determine its overall efficacy.
II. E. Data Collection
All data was collected through three questionnaires. Demographic information collected
included: age, ethnicity, time in the UK, education level. Additional characterizing
information was recorded in exposure to CVD - either directly or through a loved one. This
exposure included high blood pressure, high cholesterol, stroke, coronary heart disease, and
other heart disease.
Knowledge of CVD, its risks, and how to minimize those risks will be analyzed using
the validated CARRF-KL scale, a 28 question tool developed by Public Health Department of
Eskiflehir Osmangazi University in Turkey (Arikan et al., 2009). Finally, there were Finally,
there will be six multiple choice questions which use a five point Likert Scale to determine
current or planned health behaviors.
Participants’ behaviors before the workshop were recorded through a 5 point Likert
Scale ranging from “never” to “always.” Planned behaviors were measured on the post-
workshop survey with three options: “less of, same amount of, and more of.” The behaviors
studied were frequency of exercise, red meat consumption, smoking, visiting GP, sleeping
well, and talking to friends or family about health.
These questions were present on both surveys, while two open ended questions were
included only on the baseline survey. These two questions were: a) “What are some things
you feel are keeping you or your loved ones from being as healthy as possible?” and b)
"What are some things you hope to gain from this seminar?". These two questions were
picked to see perceived barriers to health by the participants and their demands - perhaps a
clearer illustration of the population’s true needs.
All participants took a short baseline survey immediately before the seminar. At the end
of the workshop, they were given a second survey evaluating their new levels of knowledge,
attitudes, beliefs and planned health behaviors.

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The content of the questionnaire was checked using the Flesch–Kincaid reading ease
test using an online tool.1
A copy of the questionnaire can be found in Appendix 3.
Fortunately, because of the availability of translators within the administration of the
Gargar foundation - host to seven of these sessions - the survey did not have to be translated
into any other languages. Should the program be expanded, it would be helpful to translate
both the survey and the workshop in different languages to cater to different levels of
language development and acclimation.
II. F. Plans of Analysis
II. F. 1. Statistical
Because most of the data was collected through multiple choice questions, SPSS was
used for a quantitative analysis and to see changes in knowledge and behaviors by
comparing the baseline and post seminar surveys. This included a multivariate analysis which
will gauged knowledge changes among the participants, and particular traits of the
participants which may have impacted both the baseline knowledge levels and the efficacy of
this program. Because of the strong impact of freedom poverty on the BAME population and
CVD, all data was be examined through this lens - there was particular focus on the impact of
education and health status on the baseline knowledge and efficacy of this program. Another
potential impactor examined was the length of time in the UK, which may have impacted
how well the seminar was understood, as well as the initial knowledge of health resources.
With regards to health poverty, one particularly crucial area to examine was previous
exposure to CVD, which may lead to a higher level of urgency and thus retention. Therefore,
all the data was be broken down to show variances between different groups of participants.
There were a few different scoring systems for this questionnaire. Demographic data
including name, date, age, and education level were open ended questions. Additional
demographic data including time spent in the UK, ethnic background, and whether the
participant was born in the UK were recorded as multiple choice questions. The questions of
the CARRF-KL Scale were scored according to a “correct/incorrect” system. Health
behaviors were scored with a 5 point Likert scale which included: “never, rarely, sometimes,
very often, always.” Similarly, health behaviors including use of available health resources
will be measured with a scaled scoring system which will range from “never” to “daily.”
1 Readability Test Tool: http://read-able.com/

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Previous exposure to heart disease was measured through a “yes/no” system for both “self”
and “loved one.”
II. F. 2. Qualitative
NVivo was used to analyze the qualitative open ended questions included in the surveys
in order to find general trends in the respondents’ perceptions of barriers to health. This can
help plan future interventions.
As part of this analysis, preliminary coding will focus on key words and phrases. It is
expected that this will evolve to general themes and groupings of barriers. Most of the codes
will be developed from the responses. The process of qualitative data analysis will be a
modified form of Cheryl Beck’s recommended method designed for nursing students. This
involves: 1) Establishing a narrative: by reading the responses, 2) Coding: by organizing the
responses in clusters of derived meaning, 3) Interpretation: by finding significant statements
included in the responses, and 4) Confirmation: by tallying the clusters to document, verify,
and test the interpretations (Kawulich, 2004, Beck 2003)
The component of Beck’s design that will not be incorporated is the member checking
component of confirmation - where a member of the studied community reviews and
validates the information collected as being accurate (Beck, 2003). This goes beyond the
scope of the dissertation as the nested model employed is using the exploratory qualitative
portion as a supplementary support for the quantitative study. Further studies may include
focus groups or interviews to firmly validate the results of the open ended survey questions.
III. Explanation of Chosen Focus Variables and Health Behaviors
III. A. Education Level
Education level is one of the key factors involved in Freedom Poverty because of its
relationship to wealth and health literacy, both of which impact cardiovascular disease and its
risk factors (Callander, Schofield and Shrestha, 2013; Jacobsen & Thelle, 1988; Hoeymans,
Smit, Verkleij & Kromhout, 1996; Brunner et al., 1997). In this study, education was also
taken as an indicator of wealth and family income because of the positive correlation between
these two variables (Garson, 2008). Therefore, this variable was taken in lieu of two of the
Freedom Poverty indicators. A wider discussion of the relationship between education,
income, and cardiovascular disease is included in sections IV. B, IV. C, and IV. D.

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III. B. Time Spent in the UK
This will be a particularly interesting variable to examine. Assimilation may increase
participant exposure to health promotion materials in the UK, thereby increasing the
participant’s knowledge of cardiovascular disease. Conversely, it can lead to unhealthy
behaviors as westernization has been associated with poorer diets and lack of exercise
Lassetter & Callister, 2008; Steffen, Smith, Larson & Butler, 2006; Bonow, Smaha, Smith Jr,
Mensah & Lenfant, 2002.
This variable may also be a confounder which may have impacted the results of this
study. Increased assimilation may have led to increased understanding of the questions and
therefore falsely higher scores than their less assimilated counterparts.
III. C. Previous Exposure to CVD
Previous exposure to CVD was included as a variable for two reasons. First, it is
indicative of the heath poverty factor of Freedom Poverty, making it suitable for examining
CVD through this lens. Second, previous exposure to CVD would directly impact both
knowledge and behaviors associated with heart disease. Participants directly impacted by
CVD would have received more materials and discussions with their medical providers about
the disease, risks, and associated behaviors. Those with secondary exposure to CVD would
have also been more likely to have discussed heart disease and related topics with their loved
ones and own medical practitioners. They would also have a vested interest in participating in
and learning from the workshop, making their post-seminar scores have a stronger increase
than their unimpacted counterparts.
III. D. Chosen Health Behaviors
The health behaviors focused on in the questionnaire were chosen primarily because of
their inclusion in the CARRF-KL scale questions, and for the priority given to them in
Healthy Heart Kit educational materials. These included exercise, eating red meat more than
three times a week, smoking, visiting the GP (for screening), and sleeping well. Because one
of the goals of the intervention was to make use of social networks to engage communities in
health promoting dialogues, the last behavior of focus was the discussion of health with
friends and family.

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IV. Literature Review
IV. A. CVD in London
CVD has a strong impact on the London NHS system because of its high prevalence,
mortality, and associated costs (Bernick and Davis, 2014). In London alone, 2.2 % of the GP
registered population is affected by coronary heart disease -CHD- , and 11.0% is affected by
hypertension (Townsend et al., 2012). According to the NICE Evidence Update of January
2014, a 1% decrease in CVD across the UK would save the NHS £30 million a year and
would lead to an increase of 98,000 quality adjusted life years (QALYs). A 5% reduction in
cholesterol or hypertension would save at least £80 million and 260,000 QALYs (Evidence
Update Project Team, 2014). If these issues are not addressed, the disease impact will
continue to burden on the health care system and the larger economy.
Important to managing CVD is surveillance and control. CVD has been tracked through
passive surveillance; cases have been recorded as they are noted by general practitioners (DH
Cardiovascular Disease Team, 2013). Although there have been several programs advocating
uptake of NHS Health Checks, only specific risk factors have been actively tracked in
children, as with the National Child Measurement Programme (ibid.). Most programs aiming
to decrease rates of CVD address risk factors and the environmental health conditions that
lead to them (ibid.).
The impact of deprivation is clear as an examination of London boroughs shows that
Tower Hamlets residents are thrice as likely as Kensington and Chelsea residents to be
impacted by premature mortality from coronary heart disease (Wright and Tidy, 2014). These
disparities are a priority in the standard and service model for CHD (Department of Health,
2000; Bell et al., 2012) as risk factors of CVD are strongly associated with poverty (World
Health Organization, 2015, Peña and Bacallao, 2000) because of income, education, and
general health statuses. For this reason, it is appropriate to study CVD among London’s
BAME population through the lens of Freedom Poverty.
IV. B. Introduction to Freedom Poverty
A study done at the University of Sydney examined the impact multidimensional poverty
had on CVD risk. Drawing upon the ideas of Amartya Sen, the study defined those in poverty
as “lacking the ability and resources to participate adequately in society” (Callander,
Schofield and Shrestha, 2013). Consequently, the authors developed the Freedom Poverty
Measure to identify and examine the multidimensional nature of poverty and disadvantage by

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focusing on income, health, and education status. Their findings showed that relative risk of
Freedom Poverty in those suffering from CVD were 3.02 times higher than in the general
population (ibid.), indicating that any interventions must address the multidimensionality of
disadvantage and enable participants to better engage with and participate in society.
IV. C. Freedom Poverty and BAME Populations
The BAME population of London is disproportionately impacted by Freedom Poverty.
Of those living in poverty, 70% of those in inner London and 50% of those in outer London
live in BAME households (MacInnes and Enway, 2009).
This income poverty may be explained by the high levels of unemployment among the
BAME populations. BAME levels of unemployment ranged from 120% to 300% that of
white Londoners during the 3rd quarter of 2014, as shown in Appendix 4 (A Business in the
Community Initiative, 2014). More, BAME workers make, on average, £4 less than their
white counterparts (Kaye, 2013). This may be due in part to the fact that the BAME
populations have traditionally had lower levels of higher education (von Ahn et al., 2010) ,
and have therefore been pushed to lower paying employment.
Together, lower levels of income and education have an impact on community health, as
seen by the fact that the BAME populations are disproportionately impacted by ill health
(Sproston and Mindell, 2006). This ill health limits employment possibilities, educational
opportunities, and uptake of local programs despite health promotion intentions (Callander,
Schofield and Shrestha, 2011; Callander, Schofield and Shrestha, 2013).
London’s BAME population is disproportionately impacted by Freedom Poverty, and
therefore the associated CVD risk. Therefore, interventions aiming to decrease CVD
inequalities must be similarly multidimensional in order to be effective.
IV. D. Freedom Poverty Stressors and CVD
Freedom Poverty comes from a combination of low income, low education, and low
health. Low income and poor housing are mutually enforcive stressors on environmental
health (Tunstall et al., 2013; Parliamentary Office of Science and Technology, 2011).
Indicators of non-decent housing have been connected to higher rates of CVD (Parliamentary
Office of Science and Technology, 2011). Poorer housing generally occurs in deprived
neighborhoods that also lack available sources of fresh and healthy foods, open areas for
recreational activities, and medical resources proportional to the population (Hood, 2005).
These features further limit the knowledge of and utilization of any resources which may

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potentially be available; any community-wide knowledge may be limited because poor
housing and low income neighborhoods generally discourage people from speaking to
strangers (ibid.). Together, these indicate a need for the development of community networks
for the distribution of knowledge which whic be protective against CVD.
Beyond poor housing, Freedom Poverty is associated with lower paying jobs as lower
qualification levels leads to low income levels (Poverty Site, 2015a). These lower incomes
are, in turn, connected with low health. Almost 40% of all lower income population aged 45-
64 are limited in mobility, employment, and more because of longstanding illness or
disability (Poverty Site, 2015b). Together, this limits the access of populations impacted by
Freedom Poverty to healthy foods, gym memberships, and community involvement, further
limiting population health (Salway et. al., 2007). More, many people with low income jobs
opt to take multiple employment positions in order to supplement their income, further
limiting time for going to GP, community involvement and exchange, and exploring available
resources (ibid.; Evans and Kim, 2010). Again, these would be protective against CVD, and
the lack of availability leaves these populations vulnerable.
The education component of Freedom Poverty has a particularly strong impact on CVD
and community health. A lack of education leads to lower levels of functional literacy - a
status which has been connected to low levels of health literacy (Kickbusch, 2001). Low
levels of health literacy impact how well individuals can react to disease, make use of
available resources including screenings, and developed a lifestyle that is protective against
major diseases such as CVD (Kickbusch, 2001; Heart UK, 2013).
Together, these issues create structural and environmental barriers to BAME health
promotion. According to Heart UK, BAME populations have community wide environmental
vulnerability to CVD. These inequalities are a result of socioeconomic status, poorer health
literacy, access to services, and willingness to use these services (Heart UK, 2013).
Therefore, any successful intervention must consider these issues in addressing CVD health
promotion among London’s BAME population.
IV. E. Women and CVD
Women were targeted by this intervention because of their influential role in family
health and behaviors. However, because of the role of gender in health inequalities (World
Health Organization, 2008), it is useful to examine the state CVD among this more specific
population.

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Although the prevalence of CVD is higher among men in age groups until 75, there is a
persisting misconception that women are not at risk of CVD (Mosca et al., 2005; Mosca,
Barrett-Connor & Kass Wenger, 2011; Wegner, 2012a; Möller-Leimkühler, 2007; World
Heart Federation, 2012; European Society of Cardiology, 2015). In part due to this mistaken
attitude toward female CVD, women have increasingly been suffering from premature CVD
mortality and morbidity, and underdiagnosis has led to the fact that women that have heart
attacks are more likely to die from the incident than are their male counterparts (Desvigne-
Nickens, 2009; Wegner, 2012a; Möller-Leimkühler, 2007; World Heart Federation, 2012;
Mosca, Barrett-Connor & Kass Wenger, 2011; European Society of Cardiology, 2015).
This gender health disparity of CVD is illustrated with the inequalities in the treatment
of risk factors such as diabetes. Diabetes has been associated with a relative risk of 2.99 for
cardiovascular disease (Ford,2005). This association is stronger in women than in men
(Stampfer, Hu, Manson, Rimm & Willett, 2000; Rich-Edwards, Manson, Hennekens &
Buring, 1995). Although women are more likely to suffer from dyslipidemia, they are less
likely to be given lipid controlling medication - proven to decrease the risk of heart disease
(Gouni-Berthold, Berthold, Mantzoros, Bohm & Krone, 2008; Ferrara, Williamson, Karter,
Thompson & Kim, 2004). Similarly, although diabetes patients are recommended to
implement aspirin regimens to prevent CVD, studies have shown that women patients have
consistently underused aspirin (ibid.). Together, these have meant that women in diabetes
have been at increased risk of heart disease, a striking contrast to the falling levels ischemic
heart disease found in diabetic men (Möller-Leimkühler, 2007).
In short, women develop CVD an average of ten years later than their male counterparts
but are more likely to have occurrences of CVD end in death because of misperceptions of
female risk which have led to underdiagnosis and undertreatment risk factors (Mosca,
Barrett-Connor & Kass Wenger, 2011; European Society of Cardiology, 2015).
Incidence and prevalence of CVD in women is difficult to determine because it is
generally underdiagnosed and under-researched (Mikhail, 2005). More, women tend to have
atypical symptoms, leading to misdiagnosis of CVD (Ski, King-Shier & Thompson, 2014;
Canto et al., 2012). What is certain is that CVD kills 54% women and 43% men, giving
another benefit to targeting women in this intervention (Mikhail, 2005;Nichols et al., 2012;
Wegner, 2012b).

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IV. F. BAME Women and CVD
As with wider trends of BAME CVD, minority ethnic women are more likely than their
white counterparts to be impacted by heart disease. This is in part because they have higher
relative risks of the various risk factors of CVD including hypertension, diabetes, and
cholesterol (D'Agostino, Sr, Grundy, Sullivan & Wilson, 2001; Canto et al., 2012; Kurian &
Cardarelli, 2007; King, Khan & Quan, 2009).
Despite this increased risk, ethnic minority women are less likely to have access to
healthcare including those involved in CVD diagnosis (Tillin et al., 2013; Freund, Jacobs,
Pechacek, White & Ash, 2012; King, Khan & Quan, 2009). During the diagnosis process,
they are even less likely than their white counterparts to have typical symptoms, leading to
misdiagnosis (King, Khan & Quan, 2009). After diagnosis, they are less likely to receive
quality healthcare, contributing to the higher CVD mortality rates (Freund, Jacobs, Pechacek,
White & Ash, 2012; King, Khan & Quan, 2009).
A wider study of health assessments showed that minority ethnic women are socially
disadvantaged compared to their white and male counterparts (Anand et al., 2006). This
social disadvantage included smoking, glucose, overweight, abdominal obesity, and CRP,
which compound to increase the relative risk of CVD to 1.25 (ibid.).
A similar study investigated prevention medication usage and prescription by gender
and sex (Kerr et al., 2014). Women are 8% less likely than men to be prescribed important
statins, while minorities are 10% less likely to adhere to these statins (ibid.). This suggests
that addressing these disparities in preventive care is key to addressing the health inequalities
facing minority women and their wider societies in general (ibid.).
IV. G. Previous Interventions
Programs addressing CVD knowledge have been implemented throughout the UK. In
Wigan - where CVD comprises 42% of premature deaths - the Start Well, Live Well, Age
Well program educates local people, empowering them to make effective health choices
(Heart UK, 2013). Meanwhile, case studies in Nottingham, Newcastle, and Tower Hamlets
have shown the importance of the NHS Health Checks Program. Each case stressed the
importance of reaching out to “hard-to-reach and easy-to-overlook groups” (ibid.). When
taken together, the experiences of these vastly different areas suggest that an education
program focusing on healthy behaviors and available health resources may decrease the
health inequalities associated with CVD. The lessons learned from these case studies further

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suggest that programs targeting traditionally underserved populations - as with London’s
BAME population - will be particularly successful at achieving this goal.
Thus far, most of the programs implemented throughout London have focused on the
key risk factors for CVD (DH Cardiovascular Disease Team, 2013; NICE, 2010; Boyce et al.,
2010). Many included screening programs or education through mass media (NICE, 2010).
London programs specifically focused on CVD are more rare, have been conducted at the
level of GPs, and have involved targeted screenings of at risk patients (Boyce et al., 2010).
Free smoking cessation programs, among others, consider one of the provisions of Freedom
Poverty - income - but fail to provide for the issue of education status. If the population
remains unaware of such programs, they cannot take advantage of them. Many smoking
cessation programs are advertised in GP offices, but those that do not have the health,
education, or type of job to easily allow GP visits will not benefit from this kind of
advertising. The limited effectiveness caused by this underutilization of resources is further
illustrated by the estimated levels of undiagnosed hypertension - a very treatable precursor to
CVD (Soljak et al., 2011).
IV. H. Introduction to Home Health Parties as used in this Study
To address the aforementioned shortcomings, it was promising to make use of “Home
health parties,” which have become an established method of increasing utilization of
resources and promoting healthy lifestyles. First conceived by Dr. Sadler of the UCSD
Moores’ Cancer Center to promote the recruitment of African Americans to medical studies
(Sadler et al., 2006), they have been adapted to address other issues including cancer
screenings among Washington’s Hispanic farm workers (Erikson, 2008). Directed at
complementing current health promotion programs, this intervention centered on an
education workshop emphasizing CVD risks, symptoms, protective behaviors, and resources.
By doing this, the program hoped to increase health literacy among the participants.
The “home health parties” targeted women of the BAME populations. As Sadler found,
women tend to be the centers of family and have extensive community networks (Sadler et
al., 2006; Sadler et al., 2010). By utilizing these social and community networks, information
will be passed to larger populations through word of mouth - a phenomenon referred to as the
“snowball effect” (Sadler et al., 2010). It is expected that these networks will further be
strengthened as they prove beneficial to community health and create a society of health
promotion with increased trust in governmental and public health institutions. Therefore, a
long term effect would be increase in use of available health promotion programs.

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The expected success of this program was due to the addressing of Freedom Poverty and
its three components. The intervention was centered on combatting low education status and
the impact it has on health literacy. It was entirely free and advertised other free government
services, thereby addressing the low income factor. Finally, it took community centers, thus
allowing even the unhealthy to attend while improving mental and social health. This
program used this multidimensional approach to effectively complement already established
health promotion campaigns.
V. Results
V. A. Included and Excluded Data
Although these workshops were administered to seventy three women over a set of eight
sessions, much of the data collected was unusable. Because data analysis was done through
the lens of freedom poverty, any questionnaires returned without education status, time spent
in the UK, or previous exposure to CVD were discarded as these would not reflect the key
variables analyzed in this project.
Because the CARRF-KL scale is a validated scale, all surveys which had missing answers
in the knowledge question set were similarly discarded.
Seven of the eight sessions were run within the framework of the Gargar Foundation
partnership. The first two sessions were run on the same day, and had largely useable data for
the baseline questionnaire. Unfortunately, during the course of the workshop, several of the
participants were limited by time and had to leave. The baseline questionnaire of of these
women was retained as an effective representation of community baseline knowledge levels.
Of the remaining participants, all but one were also bound by time constraints and failed to
completely fill out the CARFF-KL questions on the post-intervention questionnaire,
eliminating the possibility of using their data for a comparison of the efficacy of the program.
Thus, all the data from these sessions was taken as indicative of baseline knowledge levels of
the wider community, but the efficacy of this program was not gaugeable with the data
collected.
The largest group of discarded data was the result of the accidental success of the
program. While administering the baseline test during the next five sessions with the Gargar
Foundation, several of the participants were loudly talking to each other; they were
commenting on what they had learned from their acquaintances from the first day of sessions.
Their commentary and discussion was largely correct, thereby simultaneously skewing the

M00510169 - 21
results of any of the questionnaires and showing the efficacy of this program at effectively
educating this community about CVD. This suspected effect was confirmed upon scoring the
questionnaires - the few participants that had completely completed the questionnaire had
scored significantly higher both the baseline knowledge levels and the behavior levels.
However, because it is not entirely certain that this increase can be solely attributed to the
effectiveness of the social networks and the workshop, the data from these five sessions was
also discarded.
The last session was run within the framework of a partnership developed with South
Isleworth Children’s Centre. Of this six person session, five of the participants fully filled out
the secondary questionnaire, making them the data points used for a comparison of baseline
scores and post-intervention. Their data was also used for the wider baseline statistics. The
sixth participant had fully filled out the first survey, making her another data point for the
baseline statistics.
V. B. Data Transformation
The knowledge questions were recorded with a simple “0/1” system, where 0’s
represented incorrect answers while 1’s represented correct answers. Answers of “Don’t
Know” were counted as incorrect. The answers were then tallied to get a total knowledge
score with a maximum of 28 and a minimum of 0.
The behavior questions also had two systems of being recorded. For the baseline survey,
responses were recorded on a scale of 0 to 4, where 0 represented “never” and 4 represented
“always.” These values were reversed for the two health behaviors considered to be
unhealthy - smoking and eating red meat. Totaling these values gave a maximum health score
of 24, and a minimum score of 0. For the post-seminar questionnaire, participant responses
were recorded on a scale of 0 to 2, where 0 represented “less of” and 2 represented “more of.”
Again, the values of supposedly unhealthy behaviors were reversed, giving a maximum total
score of 12, and a minimum of health score of 0.
Previous exposure to heart disease was recorded in the same way for both personal -
primary - exposure to CVD and the exposure of loved ones - secondary. This data was put
into SPSS as either 1 for “yes” or 0 for “no.” The values were then tallied giving a maximum
score of 5 types of past exposure and a minimum of 0 for no past exposure. This simple
system was used in place of a more sophisticated system which would have differentiated
according to the severity of the exposure - something that went beyond the scope of this
thesis.

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V. C. Participant Demographics and Past Exposure
The twenty-one participants were all women and ranged from ages 16 to 69, with an
average age of 41 and a standard deviation of 10.76 years.
With this age profile, the participants had a variety of education levels. The four levels
represented by these groups were: some college (52.4%), college (19.0%), university
(19.0%), and graduate degree (9.5%). This is shown in Figure 6.
The participants came from a variety of backgrounds; they identified as: white UK
(4.8%), white other (23.8), African (14.3%), African/Caribbean (9.5%), Middle Eastern
(9.5%), South Asian (19.0%), and other (19.0%). This is shown in Figure 8. With these
backgrounds, 85.7% were born outside the UK while 14.3% were born in the UK. As Figure
7 shows, the participants had lived in the UK for a variable amount of time, including less
than 6 months (4.8%), 6 months to 1 year (4.8%), 1 to 5 years (28.6%), more than 5 years
(47.6%), or born in the UK (14.3%).
Figures 9 and 10 show the participant exposure to CVD. The majority of the participants
had not had any known primary exposure to CVD. This group made up 81% the participants
included in the data set. A further 4.8% had been exposed to 1 type of heart disease or its
precursors, another 4.8% had been exposed to 2 types, and 9.5% had been exposed to 3 types.
The participants reported more exposure secondary to heart disease through their loved
ones. In this case, 42.9% did not have a loved one with CVD or its precursors, while 33.3%
had exposure to at least 1 type of CVD. A further 9.5% had been exposed to 2 categories of
exposure, and 14.3% had been exposed to 3 types. None of the participants had been exposed
to more than 3 types of CVD or hypertension.
V. D. Baseline Knowledge Levels
Figure 11 shows the overall baseline knowledge levels of the participants. The
participants had an average score of 20.3 and a median score of 20, though their scores
ranged from a low of 15 to a maximum of 27. This is on par with the average scores of other
studies which have also used the CARRF-KL scale - ranging from 19.1 to 19.9. (Andsoy,
Tastan, Iyigun & Kopp, 2015; Arikan, Metintaş, Kalyoncu & Yildiz, 2009; Badir, Tekkas &
Topcu, 2014; Baliz Erkoc, Isikli, metintas & Kalyoncu, 2012; Bayindir, Guleser & Oguzhan,
2015; Gurdogan, Kurt, Gurdogan, 2014; Yalçınöz Baysal, Bilgin, Cantekin & Bilgin, 2014).
The model used to explain variations in scores included education level, time spent in the
UK, and past exposure to CVD. The following sections will include bivariate analysis of each

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of these variables - represented with information found in Table 1 - before using a
multivariate linear regression of the overall model.
Table 1: Bivariate Linear Regression Variables and Knowledge Level
Source: Self-produced using data from questionnaires
Variable/Model Slope Coefficient Significance R Square
Education 0.721 0.174 0.095
Time in the UK 2.073 0.006 0.333
Primary Exposure to CVD 0.910 0.265 0.065
Secondary Exposure to CVD 1.145 0.119 0.123
V. D. 1. Bivariate Analysis: Education Level and Knowledge Score
Table 1 shows the bivariate linear regression which related education to the knowledge
score. This variable had a slope coefficient of 0.721, a significance of 0.174, and an R square
value of 0.095. This means that each increase in education level leads to an average increase
of 0.721 points in the knowledge scale. This particular value explains 9.5% the variation in
the results.
V. D. 2. Bivariate Analysis: Time in the UK and Knowledge Score
Table 1 shows the bivariate linear regression which related the length of time in the UK
with the knowledge score. The variable had a slope coefficient of 2.073, a significance of
0.006, and a R Square value of 0.333. Each recorded point increase in the length of time
living in the UK was associated with a 2.073 increase in the knowledge score. This particular
value explains 33.3% the variation in the results.
V. D. 3. Bivariate Analysis: Primary Exposure to CVD and Knowledge Score
Table 1 shows the bivariate linear regression which related primary exposure to CVD and
its precursors with the knowledge score. The variable had a slope coefficient of 0.910, a
significance of 0.265, and a R Square value of 0.065. Each recorded point increase in the
length of time living in the UK was associated with a 0.910 increase in the knowledge score.
This particular value explains 6.5% the variation in the results.

M00510169 - 24
V. D. 4. Bivariate Analysis: Secondary Exposure to CVD and Knowledge Score
Table 1 shows the bivariate linear regression which related secondary exposure to CVD
with the knowledge score. The variable had a slope coefficient of 1.145, a significance of
0.119, and a R Square value of 0.123. Each recorded point increase in the length of time
living in the UK was associated with a 1.145 increase in the knowledge score. This particular
value explains 12.3% the variation in the results.
V. D. 5. Multivariate Analysis: Model 1 - Education, Time in the UK, Primary Exposure to
CVD, and Secondary Exposure to CVD with relation to Knowledge Score
Table 2 shows the multivariate linear regression which related education, time in the UK,
and primary and secondary exposures to CVD and its precursors to the participants’
knowledge scores. This model had a constant of a significance of 0.011, and an R-Squared
value of 0.422.
Of the variables in the model, education had the lowest significance - it had a slope
coefficient of 0.31 and a significance of 0.945. Time in the UK had a slope coefficient of
2.152, and a significance of 0.004. Primary exposure to CVD and its precursors had a slope
coefficient of 0.606 and a significance of 0.337. The last variable was secondary exposure to
CVD, which had a slope coefficient of 1.342 and a significance of 0.042.
Table 2: Multivariate Linear Regression Knowledge Model 1
Model
1
Educatio
n
Time
in the
UK
Primary
Exposure to
CVD
Secondary
Exposure to CVD
Slope
Coefficient
- 0.310 2.152 0.606 1.342
Significance 0.011 0.945 0.004 0.337 0.042
Constant 10.924 - - - -
R-Squared 0.422 - - - -
V. D. 6. Multivariate Analysis: Model 2 - Time in the UK, Primary Exposure to CVD, and
Secondary Exposure to CVD with relation to Knowledge Score
Table 3 shows the multivariate linear regression which related time in the UK, and
primary and secondary exposures to CVD and its precursors to the participants’ knowledge
scores. This model had a constant of a significance of 0.004, and an R-Squared value of
0.538.

M00510169 - 25
Of these variables, primary exposure to CVD was the least significant with a slope
coefficient of 0.605 and a significance of 0.323. Time in the UK had a slope coefficient of
2.166, and a significance of 0.002. The last variable was secondary exposure to CVD, which
had a slope coefficient of 1.359 and a significance of 0.023.
Table 3: Multivariate Linear Regression Knowledge Model 2
Model 2
Time in
the UK
Primary
Exposure to CVD
Secondary
Exposure to CVD
Slope Coefficient - 2.166 0.605 1.359
Significance 0.004 0.002 0.323 0.023
Constant 10.894 - - -
R-Squared 0.538 - - -
V. E. Baseline Behavior Levels
Figure 12 shows the overall baseline behavior score of the participants. The participants
had an average score of 12.667 and a standard deviation of 2.94, though their scores ranged
from a low of 8 to a maximum of 17.
The model used to explain variations in scores included education level, time spent in the
UK, and past exposure to CVD. The following sections will include bivariate analysis of each
of these variables - represented with information found in Table 4 - before using a
multivariate linear regression of the overall model.
Table 4: Bivariate Linear Regression Variables and Behavior
Variable/Model Slope Coefficient Significance R Square
Education -0.561 0.211 0.081
Time in the UK -0.827 0.230 0.075
Primary Exposure to CVD -0.940 0.167 0.098
Secondary Exposure to CVD 0.073 0.909 0.001
V. E. 1. Bivariate Analysis: Education Level and Behavior Level
Table 4 shows the bivariate linear regression which related education to the behavior
score. This variable had a slope coefficient of -0.561, a significance of 0.211, and an R square

M00510169 - 26
value of 0.081. This means that each increase in education level leads to an average decrease
of 0.561 points in the knowledge scale. This particular value explains 8.1% the variation in
the results.
V. E. 2. Bivariate Analysis: Time spent in the UK and Behavior Level
Table 4 shows the bivariate linear regression which related time spent in the UK to the
behavior score. This variable had a slope coefficient of -0.827, a significance of 0.230, and an
R square value of 0.075. This means that each increase in education level leads to an average
decrease of 0.827 points in the knowledge scale. This particular value explains 7.5% the
variation in the results.
V. E. 3. Bivariate Analysis: Primary Exposure to CVD and Behavior Level
Table 4 shows the bivariate linear regression which related primary exposure to the
behavior score. This variable had a slope coefficient of -0.940, a significance of 0.167, and an
V. E. 4. Bivariate Analysis: Secondary Exposure to CVD and Behavior Score
Table 4 shows the bivariate linear regression which related secondary exposure to the
behavior score. This variable had a slope coefficient of 0.073, a significance of 0.909, and an
V. E. 5. Multivariate Analysis: Education, Time in the UK, Primary Exposure to CVD, and
to CVD with relation to Behavior Score
Table 5 shows the multivariate linear regression which related education, time in the UK,
and primary exposures to CVD and its precursors to the participants’ knowledge scores. This
model had a constant of a significance of 0.260, and an R-Squared value of 0.205.
Of the variables in the model, time in the UK had the lowest significance - it had a slope
coefficient of -0.544 and a significance of 0.434. Education had a slope coefficient of -0.460,
and a significance of 0.309. Primary exposure to CVD and its precursors had a slope
coefficient of -0.854 and a significance of 0.209.

M00510169 - 27
Table 5: Multivariate Linear Regression Behavior Model
Model 2 Education
Time in
the UK
Primary
Exposure to CVD
Slope Coefficient - -0.460 -0.544 -0.854
Significance 0.260 0.309 0.434 0.209
Constant 15.527 - - -
R-Squared 0.205 - - -
V. F. Comparison of Knowledge Levels: Baseline and Post-Seminar
As shown in Figure 13, the baseline and post-workshop knowledge scores of the
participants were compared to measure the efficacy of the intervention. The average baseline
score was 21.8 with a standard deviation of 3.96. After the workshop, the average knowledge
scores was 24.8 with a standard deviation of 2.28. This translate into an average increase of 3
points with a standard deviation of 2.55.
V. G. Comparison of Behavior Levels: Baseline and Post Seminar
Figure 14 shows that the baseline and post-workshop behavior scores of the participants
were compared to measure the efficacy of the intervention. The figure shows that three of the
five participants were inclined towards significantly improving their health related behaviors
while the other two were inclined to maintain their already relatively high level healthy
behaviors. The average planned behavior change scores had a minimum of 6, a maximum of
9, a mean of 7.4, and a standard deviation of 1.1.
V. H. Qualitative Results
V. H. 1. Question: What are some things you feel are keeping you or your loved ones from
being as healthy as possible?
The responses to this question were categorized by coding for different themes. The
categorized responses to this question are listed in order of frequencies:
● Difficulty in finding/making/feeding healthy food (7 times)
● Lack of opportunities to exercise (6 times)
● Lack of proper/comfortable walking spaces (6 times)
● Low levels of happiness (2 times)

M00510169 - 28
V. H. 2. What are some things you hope to gain from this seminar?
The responses to this question were categorized by coding for different themes. The
categorized responses to this question are listed in order of frequencies:
● Learn to improve family health (10 times)
● Learn more about symptoms (8 times)
● Learn how to stay away from bad food (7 times)
● Learn how to incorporate more exercise (7 times)
VI. Discussion of Results
VI. A. Baseline Knowledge Levels
The results of the CARRF-KL scale questions were close to the results acquired by other
groups that have used the same questionnaire in their research, indicating that the scale was
appropriate for the population targeted by this study.
VI. A. 1. Bivariate Analysis: Education Level and Knowledge Score
Education level had a slope coefficient of 0.721 with a significance of 0.174. Although
means that it does not meet the 95% confidence level of significance, it must be
acknowledged that such significance tests generally should not be performed with sample
sizes below 30 data points. Considering that the sample size was only 21 data points, it can be
expected that the actual significance level would be higher should the sample size be
increased. Therefore, it was kept in the model. The R squared value of 0.095 suggests that
this variable needs cross validation to determine its true relationship to the dependent variable
- knowledge.
VI. A. 2. Bivariate Analysis: Time in the UK and Knowledge Score
The length of time that the participants had lived in the UK had a slope coefficient of
2.073 with a significance of 0.006. This clearly meets the criteria for meeting the 95%
confidence level, indicating that it is highly significant despite the relatively small sample
number. This indicates that it is a valid variable to include in the model.
The R squared value was only 0.333. Despite its high level of significance, it must be
noted that the time intervals were not uniform. Should this variable be made more uniform,
this variable may account for a higher level of variation than currently reflected in this
program’s results.

M00510169 - 29
VI. A. 3. Bivariate Analysis: Primary Exposure to CVD and Knowledge Score
The number of types of primary exposure to CVD and its risk factors had a slope
coefficient of 0.910, with a significance of 0.265. Although means that it does not meet the
95% confidence level of significance, it must be acknowledged that such significance tests
generally should not be performed with sample sizes below 30 data points. Considering that
the sample size was only 21 data points, it can be expected that the actual significance level
would be higher should the sample size be increased. Therefore, it was kept in the model. The
R squared value of 0.065 suggests that this variable needs cross validation to determine its
true relationship to the dependent variable - knowledge.
The R squared value was only 0.065. There are two issues of note which must be
considered. First, this was not a perfect measure of exposure to CVD as it did not account for
the varying severity of the examined exposure. Second, this program was partially designed
because CVD is underdiagnosed among women - especially among minority women.
Therefore, there may have been an underreporting of CVD exposure as many of the women
may have had cholesterol or blood pressure problems without being aware of it. Thus, this
variable may be more significant and may explain more of the variation than is reflected in
this study.
VI. A. 4. Bivariate Analysis: Secondary Exposure to CVD and Knowledge Score
coefficient of 1.145, with a significance of 0.119. Although means that it does not meet the
would be higher should the sample size be increased. Therefore, it was kept in the model.
The R squared value was only 0.123. There are two issues of note which must be
considered. First, this was not a perfect measure of exposure to CVD as it did not account for
the varying severity of the examined exposure. Second, this program was partially designed
because CVD is underdiagnosed among people of minority ethnic background. However, this
variable may be more accurately represented than the primary exposure to CVD because it
also leaves room for male loved ones to have been exposed to CVD - they are more likely
than women to have been correctly diagnosed with CVD and its precursors. Thus, this
variable may be more significant and may explain more of the variation than is reflected in
this study, but is better represented than primary exposure to CVD.

M00510169 - 30
VI. A. 5. Multivariate Analysis: Knowledge Model 1 - Education, Time in the UK, Primary
Exposure to CVD, and Secondary Exposure to CVD with relation to Knowledge Score
This model had a constant of a significance of 0.011, and an R-Squared value of 0.422.
This indicates that it is significant to a 95% confidence level, and reflects 42.2% the variation
in the results. This means that the model effectively fits the data.
What is concerning in this model is the low level of significance shown in education - a
variable shown to be relatively significant in the bivariate analysis. This - when taken with
the low R value of the bivariate linear regression - indicates that a confounding variable may
be responsible for the changes in knowledge originally associated with education. Therefore,
it was helpful to develop a second model omitting this variable.
Both time in the UK - slope coefficient 2.152 and significance 0.004 - and secondary
exposure to CVD - slope coefficient 1.342 and significance 0.042 - were highly significant,
indicating the validity of including them in the model.
Primary exposure to CVD and its precursors had a slope coefficient of 0.606 and a
significance of 0.337. Because of the reasons discussed in section VI. A. 3., it is likely that
underdiagnosis of CVD and its precursors, the true significance of this value is higher than
indicated in the results. Thus, it was kept in the second model.
VI. A. 6. Multivariate Analysis: Knowledge Model 2 - Time in the UK, Primary Exposure
to CVD, and Secondary Exposure to CVD with relation to Knowledge Score
This indicates that it is very significant to a 95% confidence level, and reflects 53.8% the
variation in the results. This means that the model effectively fits the data - even more so than
model 1.
Again, both time in the UK - slope coefficient 2.166 and significance 0.002 - and
secondary exposure to CVD - slope coefficient 1.359 and significance 0.023 - were highly
significant, indicating the validity of including them in the model.
Primary exposure to CVD and its precursors had a slope coefficient of 0.605 and a
significance of 0.323. Because of the reasons discussed in section VI. A. 3, it is likely that
underdiagnosis of CVD and its precursors, the true significance of this value is higher than
indicated in the results. When taken together with the overall fit of the model, this
significance level and the likelihood of increased significance, this variable will not be
rejected from Model 2, which is kept as is.

M00510169 - 31
VI. B. Baseline Behavior Levels
VI. B. 1. Bivariate Analysis: Education Level and Behavior Level
Education level had a slope coefficient of -0.561 with a significance of 0.211. Although
means that it does not meet the 95% confidence level of significance, it must be
acknowledged that such significance tests generally should not be performed with sample
sizes below 30 data points. Considering that the sample size was only 21 data points, it can be
expected that the actual significance level would be higher should the sample size be
increased. Therefore, it was kept in the model. The R squared value of 0.081 however
suggests that this variable needs cross validation to determine its true relationship to the
dependent variable - behavior. One potential explanation is that people with higher education
levels have a more realistic understanding of their behaviors and the definitions associated
with behaviors - eg. exercise can be as simple as walking. They may also be of higher
incomes and therefore more about to afford expensive meat, public transportation, or other
conveniences which may make them less likely to engage in healthy behaviors. Thus, wealth
may be a confounding factor associated with both education level and behaviors.
VI. B. 2. Bivariate Analysis: Time spent in the UK and Behavior Level
The length of time that the participants had lived in the UK had a slope coefficient of -
0.827 with a significance of 0.230. This clearly meets the criteria for meeting the 95%
confidence level, indicating that it is highly significant despite the relatively small sample
number. This indicates that it is a valid variable to include in the model.
The R squared value was only 0.075, suggesting that this variable needs cross validation
to determine its true relationship to the dependent variable - behavior. One potential
explanation may be that longer immigration times may be associated with westernization,
different income levels, or any other confounding factor.
Overall, the fact that time in the UK is negatively associated with behaviors is
unsurprising. Longer immigration times are associated with higher degrees of cultural
assimilation (Berry, 1997; Wallendorf & Reilly, 1983). This westernization has in turn been
associated with increased risk of heart disease and a higher rate of behavioral risk factors
(Lassetter & Callister, 2008; Steffen, Smith, Larson & Butler, 2006; Bonow, Smaha, Smith
Jr, Mensah & Lenfant, 2002; Iso, 2008; Shiba, Nochioka, Miura, Kohno & Shimokawa,
2011; Jorgensen, Aycock, Clarkson & Kaplan, 2013).

M00510169 - 32
VI. B. 3. Bivariate Analysis: Primary Exposure to CVD and Behavior Level
coefficient of -0.940, with a significance of 0.167. Although means that it does not meet the
would be higher should the sample size be increased. Therefore, it was kept in the model. The
R squared value of 0.098 suggests that this variable needs cross validation to determine its
true relationship to the dependent variable - behavior. One potential confounder and
explanation of the negative correlation may be found in the type of people affected by heart
disease. Those who have primary exposure to cardiovascular disease are also likely to be the
people who have unhealthy behaviors which led to the incidents of cardiovascular disease to
begin with. Thus, although this variable may have been relatively significant, the R-squared
indicates that this relatively strong correlation may be due to confounding factors rather than
having a causal or explanatory link.
VI. B. 4. Bivariate Analysis: Secondary Exposure to CVD and Behavior Score
The number of types of secondary exposure to CVD and its risk factors had a slope
coefficient of 0.073, with a significance of 0.909. This value is not at all close to being
significant - something supported by the R-squared value of 0.001. Therefore, it was
eliminated from the behavior model. The R squared value was only 0.001.
This variable was strongly associated with knowledge, but was not correlated with
behavior. This indicates that although people may discuss cardiovascular disease with loved
ones impacted by it, secondary exposure to CVD is not a strong enough push to healthy
behaviors.
VI. B. 5. Multivariate Analysis: Behavior Model - Education, Time in the UK, Primary
Exposure to CVD to CVD with relation to Behavior Score
This indicates that it is not yet significant to a 95% confidence level, and explains 20.5% the
variation in the results. Because these tests are generally not performed on datasets with
fewer than 30 data points, this model may still be a significant fit to the data. Therefore the
validity of this model is inconclusive. Further tests for validity will depend on extended data

M00510169 - 33
collection. It is also recommended that future questionnaires include the variables discussed
in the previous sections.
VI. C. Comparison of Knowledge Levels: Baseline and Post Seminar
As shown in Figure 13, the baseline and post-workshop knowledge scores of the
participants were compared to measure the efficacy of the intervention. The average baseline
score was 21.8 with a standard deviation of 3.96. After the workshop, the average knowledge
scores was 24.8 with a standard deviation of 2.28. This translate into an average increase of 3
points with a standard deviation of 2.55, indicating an average increase of 13.8%. With five
data points, any bivariate analyses would not accurately represent the true relationship
between the variable and the knowledge levels. Multivariate analysis is impossible with so
few data points and can only be performed after the program and data collection have been
extended.
Despite the lack of quantitative analysis, the results show that the intervention is
promising in its ability to improve knowledge levels among its participants, possibly helping
them make healthier choices. It may also help the participants recognize risks, signs, and
symptoms of the disease which may help them get the medical attention and resources they
will need to improve and protect their health. Later follow up is required to see if this
knowledge was long term or if it was acted upon.
VI. D. Comparison of Behavior Levels: Baseline and Post Seminar
Figure 14 shows that the baseline and post-workshop behavior scores of the participants
were compared to measure the efficacy of the intervention. The figure shows that three of the
five participants were inclined towards significantly improving their health related behaviors
while the other two were inclined to maintain their already relatively high level healthy
behaviors.
With five data points, any bivariate analyses would not accurately represent the true
relationship between the variable and the knowledge levels. Multivariate analysis is
impossible with so few data points and can only be performed after the program and data
collection have been extended. More, the use of the two different scales means that the values
cannot be quantitatively compared. What is interesting is that the minimum score was a 6,
indicating an no change to health behaviors. The average of 7.4 shows that the participants
were inclined to improve their health behaviors after exposure to the workshop.

M00510169 - 34
Overall, the results of the program - while not quantitatively measurable - seem to
indicate that the program is promising in creating intent to improve health related behaviors.
Later follow up is required to see if these changes were actually made.
VI. E. Qualitative Analysis of Open Ended Questions
The most common responses to the question about barriers to help indicated that the
participants felt the need for better nutritional opportunities, better opportunities for exercise
especially for walking, and low levels of happiness. In their answers to the second open
ended question, the participants expressed the hopes that they would learn how to improve
their family’s health, the symptoms of CVD, how to improve their nutrition, and how to
incorporate more exercise into their live.
These responses indicated that although the participants are generally interested in
improving their health and that of their families, they are having difficulty accessing the
resources they need to make health improvements possible. It is uncertain whether they are
lacking the resources or lack the knowledge about available resources necessary to utilizing
them. A lack of resources may come from the diversity of ethnic and religious backgrounds
the participants had, both of which would make their nutritional needs and ability to make use
of exercise facilities atypical of the general white British population. They may also not know
about burrough programs which deliver produce to those unable to access affordable
resources, thereby rendering the services inaccessible to these populations they are intended
to help. Further exploration into this topic - possibly through focus groups or interviews - are
essential to better understanding these issues.
The most interesting and surprising responses to the health barriers question were the two
comments the participants made about low levels of happiness impacting their heart health. It
is disappointing that these responses could not be more thoroughly explored through
interviews and focus groups in order to better understand what the participants meant by
these statements. The fact that two questionnaires were returned with this response hints that
this is a wider problem which bears more investigation as to its cause and wider health
effects. It cannot be certain at this point if this phenomenon is particular to BAME
populations or if it is a wider mental health issue facing London populations.

M00510169 - 35
VII. Scope, Constraints, and Limits
There are several limitations associated with this project. Perhaps the most difficult
problem will came from determining the program’s efficacy. The post seminar questionnaire
only gave insight into immediate knowledge gain. Further follow up is required to track long
term learning. Ultimately, this is one of the constraints of any education intervention as it is
not feasible to regularly monitor this knowledge over time.
The second measure of efficacy is centered on healthy behaviors which include utilizing
health checks, exercising, and more. A difficulty in determining this comes from reporting
bias. Because participants will have learned about the importance of healthy behaviors, they
are more likely to respond more positively than would accurately reflect their behaviors.
They may also intend to improve their health behaviors, but may lose motivation after
participation in the program. To counter this, a follow up with more specific questions may
be helpful. Because of the size of the cohorts, tracking changes in borough GP and gym
attendance are ineffective markers of the study efficacy, thereby rendering the self-reported
values the most effective measure.
It will not be effective to measure rates of CVD as any effects will be long term. Any
measured changes in prevalence of CVD in a borough, for example, may be attributed to an
increased level of screening should the programs be effective. Thus, the survey and follow up
results will be the most effective methods of short term intervention evaluation.
Another constraint concerns the validity of this study. Because the participants were
recruited through their involvement with different community organizations, they have
shown increased involvement and interest in health, both of which will impact the results.
Second, because there will be no control over the sampled population and its characteristics,
it is impossible apply the results of this study to the general population. Therefore, any results
of this study lack external validity and are limited in their implications for the wider society.
The largest shortcoming of this project comes from the open ended questions which
provided data for the qualitative analysis. The answers were very sparse and superficial,
while the questionnaire format did not leave room for further questions to develop a deeper
understanding of the participant responses. This is the most disappointing piece missing from
this project. Future studies in this section should make use of focus groups and interviews in
order to be able to get deeper understandings of participant concerns, health perceptions, and
health demands. These two methods would allow for a deeper exploration of their answers to
best understand the underlying concerns of the population. Again, however, none of these
methods are limited in their implications for the wider society.

M00510169 - 36
One difficulty from expanding the program will come with language barriers. As this
program targets minority populations, the preferred language of the participants may not be
English. All survey materials, the lecture, and any materials distributed must therefore be
translated to the language of the people attending the seminar. Ideally, this would be done
through focus groups although a simple translator may suffice for all written material. The
seminar would need to be translated and administered by someone who is fluent in both the
language and culture of the participants. For this reason, smaller group sizes are effective in
ensuring that all members of each seminar a single language.
VIII. Resources
The greatest resources for this project came from the partnerships developed during the
course of the program. One of these partnerships was with the BHF. Their “Healthy Hearts
Kit” was ideal for the discussions of healthy behaviors and cardiovascular disease. The
organization was also able to provide information about available some larger health
resources, all of which were provided to the seminar participants. The informational
pamphlets produced by the BHF to address each of the issues addressed were be distributed
to seminar attendees as reference materials, and participants were taught how to request
additional materials. .
Another partnership crucial to this program was with UCL Partners.2
This partnership
lended legitimacy to the project through association with an official health institution. More,
their connections with community organizations helped recruit participants.
The partnerships with the Gargar Foundation and the South Isleworth Children’s Centre
were central to recruiting participants, building a sense of trust with the participants, and
providing locations for the workshops. Because of their roles as centers of the community,
they were invaluable connections to accessing otherwise hard to reach communities.
The costs of this program came from the refreshments provided to the participants and
transportation costs. Should this program be expanded, groups may consider providing
compensation to the participants in the health promoting form of grocery store vouchers
provided through donations by local grocery stores as a form of community outreach and
service. All future seminar leaders may be trained volunteer - as done with the BHF’s
Healthy Hearts training program (British Heart Foundation, 2014).
2 For more information about UCL Partners, see
http://uclpstorneuprod.blob.core.windows.net/cmsassets/140912%20UCLPartners%20value%20business%20m
odel%20company%20sustainability%20final%20for%20web.pdf

M00510169 - 37
Funding for an expanded program may come through grants. Examples include the
Translational Research Project Grant, the Healthy Heart Grant, and the SUBWAY®/HRUK
Healthy Heart Grant from Heart Research UK (Heart Research UK, 2014), as well as grants
from National Prevention Research Initiative (Medical Research Council, 2014). This
payment would be a reimbursement of any costs accrued, but this should be minimal. Should
the intervention be effective, boroughs can also implement it directly.
IX. Conclusions
This was a quasi-experimental project which targeted BAME women with the goal of
improving community CVD knowledge levels and health behaviors. It included an
educational seminar with data collection questionnaires before and after the workshop.
This study found that the baseline knowledge levels - average 20.3 with median 20 - of
the participants were comparable to those found in other studies using the CARRF-KL scale,
showing that scale was valid to use in this population. Education, time spent in the UK, and
past primary and secondary exposure to CVD were each significant in the bivariate analysis
which related each variable to the knowledge score. The R-square value for education was
very low, however, indicating that a confounding variable may have been responsible for this
correlation. This suspicion was confirmed when the Knowledge Model 1 was implemented
and showed that education was not significant despite the strong significance of the overall
model. Education was then omitted in Knowledge Model 2, which had an even stronger
significance and R-Squared value, showing its strength. All of the linear regressions could
have been made stronger by increasing the number of data points through expanding the
program as these tests are not generally used with fewer than 30 data points. Therefore, the
model may fit the wider population much more effectively than reflected in this study.
The overall baseline behavior score of the participants had an average score of 12.667 and
a standard deviation of 2.94. This provides a baseline for future studies to track changes in
health behaviors. What was interesting was that education, time spent in the UK, and primary
exposure to CVD were all negatively correlated with health behaviors, while secondary
exposure to CVD was not significantly associated with these behaviors. Further studies are
needed to explore the reasons behind these relationships, although some hypotheses were
presented in section VI. B.
The efficacy of the intervention was examined by comparing baseline knowledge scores
to the post-seminar questionnaires. The participants included in this analysis had an average

M00510169 - 38
increase of 3 points - roughly 13.7% the original. Similarly, the intended change in behaviors
(behavior change score of 7.1) - although not directly comparable to the baseline values -
indicated a general inclination towards health improvement behavior. With five data points,
linear bivariate or multivariate regression were not possible, but the results showed that this
pilot study is promising for expansion.
The qualitative results of this study showed that participants were generally concerned
about their health but felt as though they lacked the adequate resources to improve their
nutritional and exercise health. This section lacked depth and further studies should consider
focus groups or interviews to better explore community concerns and health barriers.
There are three major shortcomings of this study. The first is that the sample sizes are too
small to effectively confirm or reject the correlations of the examined variables to knowledge
or behavior. Further studies are needed to increase the sample size in order to better
understand the relationship of the freedom poverty indicators and CVD knowledge and
behavior among London’s BAME population.
The second shortcoming comes from the qualitative analysis which should be expanded
to include focus groups and interviews for deeper in depth study of these communities’
barriers to health and health needs.
A third shortcoming was the limited number of variables included in the questionnaire.
Income poverty, for example, should have been more directly addressed instead of assuming
that education was related to the household income. Future studies should expand the
demographic questions to better profile the participants of the study.
Ultimately, this was a project that is promising in its development of knowledge and
behavior models. The intervention of an educational workshop also proved promising to
create improvements in participant and community knowledge and behaviors associated with
CVD. Finally, the questionnaire gave a small but superficial insight into population health
concerns, although these questions must be further examined in order to create more concrete
solutions. It is recommended that this program be expanded and continued in order to
increase community CVD health knowledge, behaviors, and uptake of resources. This
expansion can also help develop more effective CVD programs based on a better
understanding of community needs following an exploration of true population needs.

M00510169 - 39
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