1 “Could the racial inequalities of COVID-19 been foreseen and prevented?” Dissertation

“Could the racial inequalities of COVID-19 been foreseen and prevented?”
This research project was based on critically analysing if the racial inequalities of covid-19 could have been foreseen and prevented. Its key objectives included to analyse experience of BAME groups relative to the whole UK population by using a case study approach based on a comparative analysis looking at two health issues (diabetes and cardiovascular disease) prior to covid-19 in the country; to identify the extent to which membership of a BAME group dictates health outcomes; and to explore whether or not the UK could have been better prepared to deal with any inequalities experienced by such groups in the face of the recent pandemic of covid-19. A holistic case study with embedded units design was adopted by focusing on two diseases among the BAME community. Overall, it has been found that BAME ethnic groups in the UK population show disparities in terms of sicknesses. There exist varying patterns of ethnic inequalities in health conditions on the basis of gender, age, and ethnicity of people. Moreover, the extent to which membership of a BAME group dictates health outcomes is driven by structural factors, socio-economic factors and ethnic factors of culture and lifestyle. On the other hand, genetics does not play a significant role in health-based complications (such as covid-19) among BAME groups. In short, the study implies that racial inequalities of covid-19 could have been foreseen and prevented, because this recent pandemic has uncovered the historical inequalities, vulnerabilities and fragility within BAME community in the UK. The case study findings have revealed socio-economic and racial inequalities amidst cardiovascular disease and diabetic people, which adversely affect relative health outcomes for BAME people disproportionately. So, the UK could have been better prepared to deal with inequalities experienced by BAME groups in the face of the recent pandemic of covid-19. However, even though Public Health UK, Non-Government Organisations (NGOs), and other entities have adopted various initiatives in the UK to address racial inequalities faced by BAME group members, there exists limited prevalence and application of measures and initiatives to address health inequalities among BAME groups in the UK.
1.1 Research Outline 6
1.2 Introduction to the Research 6
1.3 Rationale for the Research 7
1.4 Aim and Objectives 9
1.5 Research Questions 9
2.1 Racial Inequality 11
2.2 Causes of Health Inequalities 12
2.2.1 Social Determinants of Health 13
2.2.2 Discrimination 14
2.2.3 Cultural Racism 14
2.3 Consequences of Racial Inequalities 17
2.4 Relationship between Racism and Health in terms of Ethnic Factors 17
2.4.1 Genetic Effects 18
2.4.2 Migration 19
2.4.3 Socio-economic Deprivation 20
2.4.4 Lifestyle and Cultural practices 21
2.5 Overview of BAME groups in the UK 22
2.6 Health Issues for BAME groups in the UK 23
2.6.1 Diabetes in BAME groups 23
2.6.2 Cardiovascular disease in BAME groups 25
2.7 Research Problem and Rationale 25
3.1 Philosophical Foundations 27
3.2 Research Design 28
3.3 Research Population and Sampling 30
3.4 Data Collection and Analysis Methods 30
3.4.1 Case Study Quality or Trustworthiness 31
3.5 Limitations of the Methodology 31
4.1 Introduction 33
4.2 Are individuals in BAME groups more likely to be diagnosed with diabetes and cardiovascular disease? 33
4.2.1 Cardiovascular Disease’s Diagnosis among BAME groups 33
4.2.2 Diabetes Diagnosis among BAME groups 36
4.3 Are individuals with BAME backgrounds more likely to be led to mortality? 37
4.4 Are there any social, ethnic, and structural determinants/factors of health that lead to disparities in BAME groups and affect consequent health outcomes of covid-19? 39
4.4.1 Ethnic Factor: Lifestyle, Habits and Behaviours 40
4.4.2 Socio-economic Factors 42
4.4.3 Ethnic Factor: Genetics 43
4.4.4 Structural Factors 44
4.5 How Health Inequalities are addressed in the UK regarding BAME groups? 45
4.5.1 National Resource Document by Public Health England 46
4.5.2 Diabetes Education for BAME in Hampshire – The (DEBI-H) Project 46
4.5.3 Diabetes UK’s Research Strategy 47
5.1 Introduction 49
5.2 Objective # 1: To analyse experience of BAME groups relative to the whole UK population by using a case study approach based on a comparative analysis looking at two health issues (diabetes and cardiovascular disease) prior to covid-19 in the country 49
5.3 Objective # 2: To identify the extent to which membership of a BAME group dictates health outcomes 51
5.4 Current Initiatives related to addressing health inequalities in the UK regarding BAME groups? 53
5.5 Objective # 3: To explore whether or not the UK could have been better prepared to deal with any inequalities experienced by such groups in the face of the recent pandemic of covid-19 54
5.6 Strengths and Weaknesses of the Study 54
6.1 Conclusion 56
6.2 Recommendations for Future Practice 56
6.3 Recommendations for Future Researchers 57
References 58
Table 1: The representation of prevalence of Type 2 diabetes mellitus in BAME and white ethnic groups………………………………………………………………………………….25
Table 2: Diagnosis of Cardiovascular disease in BAME and white ethnic groups…………..35
Table 3: Diagnosis of Types of Cardiovascular disease in different ethnic groups (BAME community) and White group…………………………………………………………………36
Figure 1: Percentage of BAME vs White people involved in physical activity who are aged 16 years or above…………………………………………………………………………………42
1.1 Research Outline
The research is conducted in a series of seven chapters. This introductory chapter has briefly introduced the research projects, provided its rationale, and outlined the research structure. The second chapter will provide an informed review and background of the research methodically. It will also present a synthesised and summarised literature review, and critically analyse. Additionally, it will state the research aim and objectives. The third chapter will present the research methodology by indicating the nature of the study, and explaining and justifying research methods and strategic decisions made for the research. The fourth chapter will explain the research conduction process by explaining the study sample, sampling method, data collection methods, and analytical strategy (data analysis). The fifth chapter will explain and provide an overview of the results. The sixth chapter will present the implication of main findings by discussing results in terms the research aims and objectives. This chapter will also state weaknesses and strengths of the research. The last chapter will conclude the research by summarising its main findings, and making suggestions for the future research and practice.
1.2 Introduction to the Research
Covid-19 has emerged as the most critical and challenging pandemic worldwide. It has affected the UK severely, which is evident from the high number of deaths and illness reported due to coronavirus (Clementi, 2020). During that time, the government and official health authorities in the country stressed that this disease does not discriminate, and thus, all people were ensured of being together in the prevalent pandemic (Razai et al., 2021). However, this is not the real case. The post-covid-19 examination revealed that old people, those who belonged to deprived communities, those who lived with comorbidities, and minority ethnic groups are dying and being affected by this illness severely and disproportionately (Public Health England, 2020). As per the statistical findings, mortality rates due to covid-19 are highest among BAME (Black Asian and Minority Ethnic) communities such that there exists 3.3% higher probability of Black males to die in contrast to white males in the country (Commission on race and ethnic disparities: the report, 2021).
This reflects that there exists an integrated and complex effect of covid-19 on minorities in the UK, which ranges from biological factors, living condition, geographical regions, to employment (Clementi, 2020). As per findings of the report by Public Health England (2020), covid-19 is an economic and social crisis than merely being a health calamity. It affects people in various ways, such that the evidence related to its actual impact on socioeconomically deprived communities, such as BAME, is still developing gradually (Jaspal and Lopes, 2021). In this way, this pandemic has exposed fragility and weaknesses of the UK society, which in turn has highlighted and intensified previous socioeconomic and racial disparities. Consequently, it is adversely affecting health outcomes for BAME people in the country (Commission on race and ethnic disparities: the report, 2021). Krieger (2021) stress that ancient structural disparities and socioeconomic health factors further aggravate this inequality.
In short, covid-19 has exposed various factors such as traditional racism, social deficiency, health and ethnic vulnerabilities, and poverty, which in turn result into lack of resources that explains continual racial disparities (Razai et al., 2021). Therefore, the purpose of this research project is to explore and identify vulnerabilities and differences/inequalities of health outcomes for BAME communities in the UK. Another key purpose of this research is to explore and assess whether the effect of covid-19 could have prevented on these communities. This will be done by shedding light and providing a better understanding of social justice aspects and practical health outcomes for such communities in the country.
1.3 Rationale for the Research
Social justice, often termed as distributive justice, makes philosophical and political decisions related to distribution of bad and good things in life among the society. These include wealth, housing, income, education, and health etc. (Craig, 2007). Crossley (2017) considered three main principles for explaining the idea of social justice. These include things that people deserve in the society, things which people need, and equality. Considering the context of minorities in the UK, there exists lack of social justice due to unequal access to services, goods, and welfare provision. This lack of social justice is a historical phenomenon that has been affecting poor and deprived people in the UK ever since the 16th century (Craig, 2007). In other words, the key factor of ethnicity shapes the opportunity of accessing different welfare aspects, including the health service.
In the current era, minority groups such as BAME still dwell in the most deprived areas of the UK, and have lack of access to suitable health provision. These are due to the fact that health services are not efficient enough to fulfil particular cultural needs (Crossley, 2017). For instance, people from BAME groups have lack of access to ethnically-matched health services provision. Often, female doctors are not offered to women despite of their requests (Craig, 2007). A study by Kwate (2014) revealed that black patients are misdiagnosed as schizophrenic patients, and mistreated by using intense therapies. In other words, it can be seen that BAME groups have lack pf access to equality-based outcomes. Consequently, it can be deduced that no social justice is offered to them. Here, it must be noted that these findings do not reflect that each policy, structure or person in the UK undergo racist welfare provision. However, majority of minorities still face individual and institutional racism to a large extent, which adversely affect their life chances (Craig, 2007). In short, even though few minority groups might attain well regardless of potential hurdles, there still exist challenges for specific minority groups such as BAME in the UK.
The social factors of health help in terms of realising the different and unequal impact of mortality and disease on different populace. Considering the context of the UK, it has been revealed that poor health outcomes and higher disease rates are more widely prevalent in monitory ethnic groups in contrast to white country fellows (Razai et al., 2021). Moreover, it must be noted that such health disadvantages keep worsening with the passage of time. Consequently, this leads to more critical health outcomes due to disease among minorities in the country. Considering the rise in ethnic diversity in the UK, it is reported that health outcomes of black and south Asians are still inferior to those of majority white people (Clementi, 2020). This is unfair since poor health outcomes due to discrimination can aggravate the minority stress and lower life satisfaction. Thus, it is important to address differences that lead to such adverse outcomes owing to the fact that race or ethnicity must not dictate health outcomes of minorities in a country.
So far, it has been seen that there exist heath inequalities between white groups and ethnic minority groups. As an example, the two most critical diseases in the UK are cardiovascular disease and diabetes, which contribute to most of National Health Service consultations and healthcare expenditure. As per statistical findings, diabetes only contributes to 10% of the NHS healthcare budget for Wales and England. It is more prevalent among South Asian groups in the UK, such that these are diseases are 6 times more incident and twice more prevalent in the country in contrast to the White populace (Commission on race and ethnic disparities: the report, 2021). Based on these findings, it can be deduced that minority groups in the UK are more burdened with critical diseases such as diabetes and cardiovascular diseases, which in turn increase the risk of covid-19.
Even though various surveys have been conducted in the country to identify outcomes, risk and mortality rates due to such diseases among ethnic groups, there exists lack of recent evidence that have explored ethnic disparities in the UK related to cardio-diabetic incidence and mortality. In other words, the discrimination in health outcomes for minorities is a complex occurrence due to lack of top-notch quality of data. Moreover, there is a need to examine association between ethnicity and health outcomes in the UK by gathering wider secondary data in terms of online health databases and records. This will help in terms of offering anonymised data from health industry of the UK, and thus, represent the general population (Razai et al., 2021). Thus, conduction of this research will focus on gathering secondary health records, disease registries, social deprivation measures, and death records for identifying the association between ethnical inequalities and health outcomes for BAME group in the UK.
1.4 Aim and Objectives
This research project is based on critically analysing if the racial inequalities of covid-19 could have been foreseen and prevented. Consequently, it aims to consider practical health outcomes for those from a BAME background by identifying if and why there are differences in health outcomes for those of a BAME background, and whether public health should or could make a difference and address any inequalities in this regard.
The research will fulfil this aim by attaining the following objectives:
To analyse experience of BAME groups relative to the whole UK population by using a case study approach based on a comparative analysis looking at two health issues (diabetes and cardiovascular disease) prior to covid-19 in the country
To identify the extent to which membership of a BAME group dictates health outcomes
To explore whether or not the UK could have been better prepared to deal with any inequalities experienced by such groups in the face of the recent pandemic of covid-19
1.5 Research Questions
This research is centred on the following main question:
Could the racial inequalities of COVID-19 been foreseen and prevented?”
This question has been attained by seeking answers for the following sub-questions:
Are individuals in BAME groups more likely to be diagnosed with diabetes and cardiovascular disease?
Are individuals with BAME backgrounds more likely to be led to mortality?
Are there any ethnic, social, and structural determinants/factors of health that lead to disparities in BAME groups and affect consequent health outcomes of covid-19?
How health inequalities are addressed in the UK regarding BAME groups?
How should Public Health make a difference and address any inequalities in the UK regarding BAME groups amidst the recent pandemic of covid-19?
2.1 Racial Inequality
Racism is a systematic and organised social system in which the dominating racial group ranks people into social groups as per their ideology of inferiority. It uses the power to disempower, devalue, and allocate societal opportunities differently to the groups that are defined as inferior (Calanzani et al., 2013). Race is a category which is based on ethnicity, nationality or other social differences that capture the different access to power and opportunities/resources in society (Krieger, 2021). Racism functions on multiple levels from the individual to the structural. These definitions reflect that racism is totally wrong. It cannot be justified at all since it is against the law to treat people unfairly. Racism can deteriorate ability of people to study, attain future goals, work, or even general well-being when they face challenges while accessing services, jobs, and education.
Racism is still prevalent as a critical problem, due to which minorities continue to undergo extreme dissemination. In the context of the UK, racism was banned as per the Equality Act 2010 on the basis of nationality, ethnicity, colour, and national origin. Due to this, race is secured as per the latest equality law (Keys et al., 2021). However, regardless of these legal efforts, racial inequalities persist in the country in different domains, such as work, criminal justice, education and health (Public Health England, 2020). A study by Hackett et al. (202) persists that, in Europe, ethnic inequality is the most common type of discrimination, such that 64% adults were perceived to be discriminated racially among 27,718 surveyed people. In 2017, 26% of a sample was found to be racially discriminated in the UK (Keys et al., 2021). The study further showed that race is a key factor that motivates hate crime incidents in the country. Moreover, another indicator of increase in racial inequality in the UK is the rise in right-wing nationalist movements and hostility towards migrants, which eventually resulted into Brexit (Ethnic disparities and inequality in the UK, 2020). These findings reflect that racism is still very real, and has not reduced at all in the country with the passage of time.
The racial minorities also carry the burden of mortality and morbidity disproportionately. It is being evident through literature that health inequalities among the racial minorities are dominant, persistent. and pervasive. The studies claim that individuals who experience racism exhibit worse health as compared to the individuals who do not report it (Gravlee, 2009; Heise et. al., 2019; Ho and Dascalu, 2020). In short, racism drives ethnical inequalities in healthcare sector, and is considered as a social determinant of health (Hackett et al., 2020). It is based on an organised yet complex system of past and socio-political events that divide ethnic group into social pyramids. Ideologically, differential values are given to these groups, which result into differences in terms of accessing resources, power and opportunities (Keys et al., 2021). As a result of this inequal access, minorities suffer in terms of lack of access to quality education, less safe social system, job discrimination, and poor outcomes related to the criminal justice system.
Most importantly, it must be noticed that racial inequality is based on individual and structural levels. Here, structural racism is defined as interacting social forces, ideologies, macro-level systems, and institutions that exert inequalities among ethnic and racial groups at the most powerful socio-ecologic levels (Krieger, 2021). Structural racism allows the dominant group to have greater access to employment and other resources. It also affects healthcare laws and policies, which in turn results into poverty and racial health discrimination among minority groups. Minority groups either cannot afford healthcare expenses or they do not get health insurance from their employers (Yearby, 2018). Moreover, among the major types of racism, structural racism has been found to affect health outcomes most adversely. For instance, a systematic review by Williams et al. (2019) revealed that there exists a relationship between discrimination and poor survival rates and delayed diagnosis among African Americans who suffer with breast cancer or lung disorder (Krieger, 2021).
This reflects that structural racism is not based on individual actions, rather, it continually rebuilds conditions that ensure continuation of such actions and relevant causes (Gee and Ford, 2011). This can be supported by the study of Hackett et al. (2020), who asserted that even though interpersonal racism is eradicated completely on an interpersonal level, persistent structural racism would keep supporting racial inequalities. Overall, it can be deduced that structural racism promotes racial inequality, which leads to undertreatment of minorities and consequently their poor health conditions and outcomes.
2.2 Causes of Health Inequalities
There are various reasons that cause racial inequalities in terms of health outcomes. In general terms of racism, most common causes of ethnic disparities include cultural racism, structural racism, discrimination, and several social determinants of health (Krieger, 2021). Another study showed that ethnic minority groups live in deprived, urban, and overcrowded areas, and are offered lesser pays in contrast to other populace, as a result of which they are exposed to high risk of prevalent diseases or illnesses (Calanzani et al., 2013). Since structural racism has been explained in the previous section, following is the detailed overview of remaining causes of ethnic disparities:
2.2.1 Social Determinants of Health
In terms of social determinants of health, potential causes include socioeconomic status, risky jobs, cultural limitations, overcrowded and poor housing, and high burden of comorbidities such as diabetes and cardiovascular disease (Calanzani et al., 2013). Ethnic minority groups are exposed to barriers in healthcare services due to culturally insensitive environment and relative negative experiences (Ethnic disparities and inequality in the UK, 2020). According to Stead et al. (2019), racial discrimination and marginalisation is evident in the UK in terms of lack of access to healthcare services, and bad experiences of ethnic minorities related to healthcare and treatment. A recent report published by the UK government shed light on ethnic disparities amidst the recent pandemic of covid-19. It showed that ethnic minority groups are exposed to high-risk despite of reporting geographical and socioeconomic factors including population density, former health conditions, job exposure, and household composition (HM Government, 2020). Another Public Health England report revealed that ethnic minority groups are more exposed to the recent pandemic of covid-19 and dying due to prevailing discrimination and racism (Public Health England, 2020).
Stead et al. (2019) stressed that there exist challenges for ethnic minority staff in the NHS (National Health Service) in terms of not being able to discuss problems related to personal protective equipment (PPE) and testing concerns. However, it must be noted that ethnic disparities are not only prominent in covid-19 pandemic and relative outcomes, rather, it is a historical phenomenon. In the past, ethnic minority groups were more exposed to diseases. They were the first ones to get any disease, and suffered from aggrieve progression of severe illnesses. Moreover, they showed poor rates of surviving amidst such pandemics (Williams, 2012). This can be supported by a report of the UK government which showed that there exists 5% higher rate of death among black pregnant women in the UK in contrast to white pregnant women. Moreover, the report revealed that as per the Mental health Act, black people are more likely to be detained in the UK in contrast to white people (Department of Health and Social Care, 2018). Furthermore, it has been found that health conditions of immigrants are deteriorating with the passage of time. For instance, in the US, health profiles of Mexican and Mexican Americans immigrants are similar to those of African Americans (Kaestner, 2009). All of the aforementioned findings reflect that health inequalities and adverse health outcomes in ethnic minority groups are due to the historical factor of racism. In short, racism is a social concept that maintains, captures, and justifies the ethnicity and nationality-based differences for accessing societal resources and power (Keys et al., 2021).
2.2.2 Discrimination
There are various effects of discrimination on health. First of all, discrimination creates ethnic disparities in socio-economic status. A study Hackett et al. (2020) showed that ethnic disparities in education, income, health, and unemployment can be reduced by eliminating discrimination. Moreover, it must be noted that discrimination is related to access to opportunity at a national level. As per findings of Evandrou et al. (2016), below 5% black children have access to good resources in neighbourhoods. Besides this, discrimination is also related to lack of job opportunities and poor quality of education. Furthermore, discrimination deteriorates health outcomes since it gives rise to poor housing communities and environments. Calanzani et al. (2013) stress that poor neighbourhoods in a country are exposed to high risks of acute psychosocial stressors and multiple chronic diseases, lack of access to wide-ranging resources, high risk of unwanted physical and social environmental conditions, and lack of healthcare services.
In the context of the UK, Pakistani and Bangladeshi people are highly discriminated (Brady, 2016). As per national data compiled by the UK government (2020), it has been found that there exists overrepresentation of socially denounced ethnic groups in highly disadvantaged communities in England. The study further showed that only 9% UK people live 10% of the most deprived neighbourhoods in contrast to 18% black Caribbean people, 20% black African, 28% Bangladeshi, and 31% Pakistani. These findings reflect that ethnic minorities in the UK dwell in deprived neighbourhoods, and thus, they are exposed to high risks of poor health conditions.
2.2.3 Cultural Racism
Cultural racism is another crucial type of racism which focuses on stereotypes. People and racial groups communicate cultural racism in daily activities, and pass it from one generation to another. It occurs when a group exercises power for outlining societal cultural values (Cogburn, 2019). El-Khatib et al. (2020) assert that cultural racism shows partial inclination towards a heritage, culture, and values of a certain group, which is also termed as ethnocentrism. Moreover, it imposes that culture on other groups. Cultural racism is a historical phenomenon, which is currently being associated with racism related to physical aspects. These include manners, religion, moral practices, aesthetics values, social customs, behaviour, moral beliefs, language, and leisure activities (Cogburn, 2019). Based on this, cultural racism is described as culture-based discrimination towards people. This leads to the adverse outcomes in terms of reluctance of minorities from their own culture, and rather, inclination towards the majority culture (Nerenz et al., 2006). Most importantly, cultural racism is centred on the key factor of whiteness for assessing racist frames and racism. The whiteness-based viewpoints depict cultural systems, which assume that white people are powerful and superior than others across cultural, institutional, and social environments (Cogburn, 2019). In short, cultural racism includes factors such as ideology, values and practices, which promote racial oppression in a community.
Cultural racism also affects health adversely by giving rise to an unconscious bias. A report by Smedley et al. (2003) showed that in the US, black and other minority groups have lack of access to quality healthcare service. Another study by Evandrou et al. (2016) examined the provision of analgesia to white Americana and Hispanic patients who suffered with long bone fractures. The study showed that there existed 2 times more chances of white patients to get analgesia in contrast to Hispanic patients despite the critical factors that needed considerations, such as clinical aspects and type of injury of each patient. A study by Purnell et al. (2016) showed biased score among physicians because they recommended biased treatment for black patients. Furthermore, it must be noted that the quality of non-verbal behaviour and patient interaction are affected by implicit biases (Keys et al., 2021). A study by Cooper et al. (2012) showed that physicians established poor quality of communication with patients based on high score of implicit bias. In short, these studies reflect that health inequalities are deep-rooted in cultural racism.
There is a need to examine cultural racism thoroughly for attainment of health equality and development of a culture of health. Cultural racism is discussed below in terms of two groups such as symbolic margins of community and status hierarchies. Symbolic Margins of Community
Cultural processes affect racial inequalities in health in various ways that lead to social inequality. One of such processes include identification and rationalisation, which form social inequality and associate cultural racism with racial inequality in health (Cogburn, 2019). Identification means processes through which social groups and actors are defined. It also means attaching social meanings to racialised entities or race, in addition to identifying basic stereotypes and racial values (Andersen and Curtis, 2012). Rationalisation is based on assessment and standardization. Here, assessment means processes that identify social value, and standardisation means efforts exerted towards standardization of fair and equal social rules and norms (Cogburn, 2019).
El-Khatib et al. (2020) stress that identification and rationalisations processes form the basis of social ideologies of races. These processes present a traditional picture of racialised social trends, and assume that social rules and norms are equally exploited by different groups. However, this is not a true case. This can be explained with racial frames, which are defined as schemas that are controlled by shared histories and memories, which in turn guide attitudes, actions, and behaviours related to wide-ranging racial problems (Nerenz et al., 2006). Racial frames drive various cultural practices and processes. For example, colour-blind racism and white racial frame rationalise racial status by white people, and result into racial inequalities in health. Racial frames affect health outcomes in healthcare institutions by shaping decision-making and behaviour of healthcare authorities invisibly (Cogburn, 2019). Status Hierarchies
There exist certain informal cultures in institutions besides formal regulations and laws, which normalise specific behaviour and agree to their certain meanings and viewpoints. This is often termed as a socio-political setting for racism, which is evident from public and political discussion on racial ideology, practices, race, and policies within different institutions (Cogburn, 2019). This can be supported with the study of Nerenz et al. (2006), who implemented the white racial frame within healthcare institutions, and stressed that racist images, emotions, ideologies, narratives, and practical discrimination result into racial inequalities within healthcare provision. Another study by El-Khatib et al. (2020) revealed that white supremacy ideas are deeply rooted in public health practice, which is evident from public health management focus on freeing coloured people from destructive health habits, converting minority groups into better western groups, and considering whites as a basis for development of healthcare norms. These findings reflect that integration of racial disparities within cultural models and healthcare interventions can help to eradicate structural barriers and minimise racial narrative related to health behaviour.
In short, it can be deduced that there exist cultural threats to health and social equality. There exist certain cultural processes based on racism and cultural model, which control social resources and materials, and thus, pose risk to health of monitory groups. Thus, there is a need to develop a culture of health for better examining cultural racism and reducing racial inequalities in health.
2.3 Consequences of Racial Inequalities
These experiences of racial inequalities by minority groups have resulted into acceptance of such negative stereotypes by ethnic minority patients. This process of confirmed negative views is titled as an Internalised racism, which is interlinked with various health outcomes such as distress, psychological, and obesity in ethnic minority groups (Keys et al., 2021). A systematic review by Williams et al. (2019) showed that health outcomes are associated with self-reported discrimination. The study further identified relationship between self-reported discrimination and incident disease (such as hypertension, cardiovascular outcomes, diabetes, and breast cancer), poor mental health (psychological distress, low psychological well-being and mental disorders), poor health behaviour (smoking, over eating, and substance use), pre-clinical indicators of disease (visceral fat, inflammation, coronary artery calcification, and varying heart rate), lack of adherence to medical standards, and poor access to healthcare services. Calanzani et al. (2013) stress that racial inequality affects health in terms of weathering, as per which ethnic minority groups are exposed to discrimination in terms of physical, psychosocial and chemical stressors that fasten the biological ageing and deteriorates health. For instance, as per findings of Hackett et al. (2020), constant stress in the environment deteriorates health of black women fast in contrast to those of white women. In short, it can be deduced that individual and societal racism affects health negatively in both indirect and direct terms.
These aforementioned adverse consequences of racial inequalities in health reflect that there is a need to identify and assess ethnic differences and factors that affect healthcare outcomes and medical decision-making related to minority groups in contrast to majority groups in a country. Additionally, the existing evidence pose questions to racial bias and discrimination among minority groups, specifically BAME communities in the UK. Hence, this current research will identify social and structural determinants of health that cause healthcare disparities. Consequently, this will help in identification of suitable strategies for eliminating adverse impacts of such social and structural determinants on health.
2.4 Relationship between Racism and Health in terms of Ethnic Factors
The relationship between racism and health is based on several ethnic factors that in turn determine health outcomes. These factors have various aspects related with ethnicity such as socio-economic deprivation, cultural practices and lifestyle, genetic effects, and migration status. These ethnic factors are distributed unequally in various populace, which eventually results into racism or racial discrimination (Kwate, 2014). These ethnic factors are detailed below:
2.4.1 Genetic Effects
Kopel et al. (2020) stress that racial inequalities of covid-19 among minority groups can be explained by focusing on genetic predisposition besides economic, social, and health inequalities. Currently, it is being stated that ethnic disparities in covid-19 mortality is due to genetic aspects. Scientists assert that there might be genetic factors that are aggravating the severity of coronavirus among ethnic minorities (Egede and Walker, 2020). Therefore, there is a need to consider the genetic outlook for examining systemic racism and formulating relevant interventions.
Ethnicity, which is known to be a complex entity, results from the intersection of social constructs, genetic makeup, cultural identity and behavioural pattern (Whaley, 2020). Despite the fact that the recent usage of ethnicity is based on social health factors, it does not avoid the existence of various biological and pertinent dissimilarity (Johnson, 2014). For instance, BRCA gene for breast cancer is more prevalent among Jews, whereas, the gene for sickle cell trait is widely prevalent among people in Africa, Southern Europe, and the Caribbean (Whaley, 2020). Likewise, in the UK, clinical practice guidelines are now based on biological differences related to ethnicity. For example, South Asian groups are more exposed to risks of cardiovascular disease and type-II diabetes. Consequently, it is suggested to use different thresholds for obese and overweight populace (Offer et al., 2015).
Prior to this current pandemic, previous pandemic’s evidenced data suggests that differences in comorbidities, risk of infection and immune profiles to be different in different ethnicities. The research conducted in the UK showed that there seems to be high predisposition to develop the coronary heart disease among the people of South Asian background. Similarly, African or African Caribbean population are more predisposed to develop hypertension and Stroke in comparison to the rest of the white population (Pearce et al. 2004; Phan et al. 2014). Diabetes is more common in South Asian, African and African Caribbean background population. It is also being suggested by some scientists that there is no genetic origin of conditions like diabetes or heart disease. This concept is limited due to the lack of understanding of genetic susceptibility of several diseases.
The alternative theory which is proposed by epidemiologists is on the promotion of the role of environmental factors to be the key determinant of the disease. Such environmental factors conventionally involve the biological, physical and chemical agents that can impinge on health but can be extended to involve the social factors. There are other environmental issues that can directly impact the social economic factors and held off certain population such as poor sanitation, hygiene, pollution, unsafe drinking water. These influences appear to be correlated with large differentiation in health within several populations which also addresses the inherent social economic equality that is significant for the reduction of vulnerability of ethnic minorities (Braun 2002; Pearce et al. 2004; Boehme et al. 2017). These findings reflect that ethnic minorities are exposed to the risk of environmental racism. This is due to the political and historical fact that ethnic minority groups are exposed to water, air, and land pollution that can lead to worse health outcomes.
2.4.2 Migration
The next ethnic factor that affects health and leads to racism is ‘migration’. Even though migration positively affects people and their families in terms of better lifestyle, it leads to negative health outcomes. People undergo immense psycho-social and physical stress because they face lack of social network and language skills in the relocated region, which in turn hinder their access to professional, economic, and social opportunities. Additionally, migrants also face racism and stigma, which eventually result into poor health outcomes for them (Kwate, 2014). This can be supported by the study of Caman (2015) who found that there exists higher possibility of migrants dwelling in deprived areas in contrast to the host populace. Likewise, migrants have lack of access to social and health services.
However, contradictory findings by Sergeyev and Kazanets (2017) showed that new migrants can get beneficial outcomes in terms of better education, healthy life, and lower risk of disadvantage as long as they have migrated long distances. Likewise, Norredam et al. (2007) asserted that 1st generation migrants showed lower chronic disease and mortality in contrast to people of the host country. Yet, with the passage of time, migrants’ health profile has converged with and even surpassed to that of the host country based on the process of acculturation. Here, acculturation means adoption of dietary, lifestyle, and cultural practices of the local country (Caman, 2015).
Besides this, it has been stressed that health of migrants is majorly affected by the timing of migration, which is further due to the fact that different ethnic groups have varying experiences of culturation (Tong and Kawachi, 2020). In the UK, ever since the World War II ended, the country has undergone extensive experiences of immigration when people from poorest or smallest countries migrated to the UK. For instance, before the war, people from the Republic of Ireland constituted the largest group of migrants. Once the war ended, many people migrated to the UK from India and Poland. Afterwards during the 1950s, a large number of people migrated from the Caribbean. Later during the 1960s, other migrants in the UK emerged from Pakistan and India. In the next decade, people from African countries travelled to the UK. In 1980s and onwards, people from Bangladesh comprised a major portion of the UK population (Caman, 2015). As per the recent census in 2019, the non-UK (migrants) population was estimated to be 9.5 million. Among them, the most common group of migrants belonged to India, which was followed by Polish people (Population of the UK by country of birth and nationality – Office for National Statistics, 2021).
These findings reflect migrants face problems in terms of immigration-related limitations, high racism, healthcare obstacles, and worse poverty. Moreover, it has been observed that there exist high mortality rates of covid-19 patients among ethnic minorities in the UK (Dona, 2021). It is further aggravated by high rate of prevalent of pre-existing non-communicable diseases in minority groups, worse socio-economic disparities, weak protection to refugees, and gender inequalities. Moreover, they face further challenges in terms of having lack of access to public health services due to lack of government awareness and minimal inclusion (Gruer et al., 2021). Thus, it can be deduced that various interacting factors pose migrants to the high risk of covid-19.
Based on the rise in the covid-19 pandemic, it is required to inquire about affecting communities or people, such as BAME, and areas that need interventions. This is needed for identifying the historical and uneven health inequalities faced by migrants and racialised communities in the UK. Another rationale for exploring the BAME migrants in this research is that there is a lack of interventions for addressing racial inequalities against this community. It is worthwhile to note that, in this research, BAME community is considered similar to migrants, since BAME migrants also comprise of diverse people such as asylum seekers, refugees, and economic migrants (Tuyisenge and Goldenberg, 2021).
2.4.3 Socio-economic Deprivation
BAME groups are exposed to high risks of severe diseases, infection, and health outcomes due to various ethnic factors and reasons, one of which includes socio-economic factors. It is also termed as socio-economic deprivation that affects health and leads to racism (Mode et al., 2016). The socioeconomic factor is highly influencing in health, such that it has been found that people of have lowest socio-economic rank in the society undergo poorer health outcomes in contrast to less deprived people (Kwate, 2014). Likewise, it has been found that deprivation experiences vary among ethnic groups, such that people belonging to ethnic monitories have least access to job opportunities and dwell in deprived areas in contrast to the general populace (Froehner and Wirth, 2014). These findings are in contrast to those of Robson and Berthoud (2006) who found that ethnic groups undergo similar experiences of disadvantage. Yet, recent research as per the UK census revealed that Chinese and Indian groups dwell in more affluent areas and are less exposed to material deprivation. On the other hand, migrants from Africa and Bangladesh live in deprived areas (Population of the UK by country of birth and nationality – Office for National Statistics, 2021). In other words, it can be deduced in there exists relationship between socio-economic factors and ethnic disparities in health such that majority of ethnic minorities in the UK live in highly deprived areas.
There exists little research related to the extent of role of socioeconomic deprivation/inequalities in higher covid-19 mortality among BAME groups. Moreover, no study has so investigated the independent role of poverty in covid-19 mortality. Therefore, there is a need to identify how socioeconomic factors and ethnicity affects adverse health outcomes related to covid-19 in the UK. It is critical to be investigated since social devastation can lead to long-term inequality (Patel et al., 2020). Thus, recognition of socioeconomic factors will help to explain socioeconomic inequalities among minority groups in the UK amidst the prevalent pandemic of covid-19. Consequently, a better understanding of association between poverty, ethnicity, and mortality will help to suggest control measures and resources for minimising the prevalent risks.
2.4.4 Lifestyle and Cultural practices
Population health and health determinants are widely recognised terms these days, as per which health is considered as a state of mental, physical, and social well-being besides showing an absence of an illness or disease Thomas et al., 2004). Based on this, populace and individuals’ health are examined by considering non-medical determinants of health. However, there exists other factors and forces within environment and lives of people that affect provision of medical services and health condition of individuals. One of such factors include culture (Knibb-Lamouche, 2012). Hence, another ethnic factor that affects health and leads to racism is ‘cultural practices and lifestyle’.
According to Seikkula (2017), shared cultural norms related to diet, religious practices, health-based attitude, and exercise affect health both negatively and positively. For instance, as per findings of the 2019 census on adult smoking habits in the UK, more than 90% of Bangladeshi adults are non-drinkers in contrast to men in England. However, mixed ethnic groups are more exposed to smoking behaviour. Furthermore, considering different ethnic groups, statistical findings of the census revealed highest smoking prevalence among Asian (3% women and 14% men). After that, Black (7% women and 13% men) groups are smokers, followed by Chinese (4% women and 12.6% men). Likewise, it has been estimated that Indian people are less in ratio (5%) in contrast to Polish who are the leading current smokers (25%) in the UK. Based on these varying outcomes, all ethnic groups are provided targeted interventions and services for improving their health conditions (Adult smoking habits in the UK – Office for National Statistics, 2021). These findings reflect differences in cultural practices and lifestyle lead to health disparities.
According to Thomas et al. (2004), health disparities are due to individual behaviours, and cultural and societal values. This reflects cultural practices and lifestyle of people majorly influence efforts towards eradication of health disparities among minority populace. Furthermore, cultural practices and lifestyle of people guide health professionals and policymakers in terms of closing the health gap by providing required medical services and designing effective health interventions (Knibb-Lamouche, 2012). Therefore, there is a need to explore this ethnic factor in this current research for identifying and analysing the role of cultural practices in behaviour and lifestyle of BAME community people in the UK, and the relevant risk factor for cardiovascular disease and diabetes.
2.5 Overview of BAME groups in the UK
BAME includes various people of different ethnic origins, such as Asian, Black British people, Roma, Arabs, Asian British people, Black, Gypsies, people of varying heritage, and travellers. BAME group is often categorised as other White, such as Australian, Polish, White Irish, and French etc. (Keys et al., 2021). Generally, the census helps to categorise BAME people in terms of their ethnic settings. This results into huge diversity among the overall BAME group. Common examples include Asian people belonging to Hong Kong, China and Japan; Southeast Asian people belonging to Thailand and Philippines, and South Asian people belonging to Pakistan, India and Bangladesh etc. (Calanzani et al., 2013).
It is reported that UK has become highly diverse ethnically ever since the past 2 decades. For example, in England, an increase has been reported in proportions and numbers of BAME groups’ people. As per statistical findings, in 2011, the BAME groups comprised 1/5th of the total population of 10 million. Furthermore, Northern Ireland, Wales, and Scotland underwent similar changes in their populace ethnic composition. For instance, in 2011, Pakistani (2%), Indian (3%), and other White (5%) constituted the largest BAME groups in England. However, ethnic groups are not distributed equally across England based on the census data. For instance, White British people represented more than 90% of the total population in the North East. On the other hand, they merely represented less than 50% of the population in London (Population of England and Wales, 2021).
At present, it is being anticipated that BAME groups’ proportions and numbers will increase in the UK, such that a major ratio of older people will be represented by BAME groups. For instance, it is projected by 2026, more than 1.3 million will be aged 65+ who will belong to BAME groups in Wales and England. Furthermore, it is expected that in 2026, more than 50% of BAME groups’ people will be aged more than 70 years. It is also expected that most of such BAME groups people will be the White Irish (36%), next the black Caribbean (13%), Indian and other White (11% each), and other Asian (10%) (Population of England and Wales, 2021).
2.6 Health Issues for BAME groups in the UK
2.6.1 Diabetes in BAME groups
The global prevalence of diabetes worldwide has increased tremendously over the few decades and from 300 to 400 million in 2015, which is equal to 8.8% of the 20 to 79 years of population. However, there can be difference of prevalence levels seen at regional levels specifically in different ethnic groups. It is accepted widely that prevalence of diabetes is higher among the BAME groups in UK. The health survey for England in 2004 collected the data from adults (13500), which suggested that the prevalence of type 2 diabetes was higher in black Caribbean (approximately 7.6% in women and 9.5% in men), Pakistani (8.4% in women and 7.3% in men), Indian (5.9% in women and 9.2% in men) and Bangladeshi (4.5% in women, and 8% in men) in comparison to general population which accounts 3.1% in men and 3.8% in men (Pham et al., 2019) can be seen in Table 1.
Table 1: The representation of prevalence of Type 2 diabetes mellitus in BAME and white ethnic groups (Pham et al., 2019)
Although there had been effective advancements occurring for the management of diabetes in recent years. However, the new estimates regarding its prevalence in different ethnic groups in UK remains limited. This is due to the hampering in the data sets which are limited in regards to the details of ethnicity and inability to tackle some of the challenges that is caused by the data quality and the information available regarding ethnicity. Furthermore, the understanding of patterns of disease in minority ethnic groups is significantly important for the population-based screening of diabetes in terms of designing the lifestyle interventions and the relevant epidemiological research. In addition to it, the introduction of National Health services quality and outcomes framework provided the financial incentives for the management and monitoring of the chronic diseases in primary care that included diabetes has improved the quality of data. The recognition of ethnicity that could be a risk factors to many common illnesses is important to improve the records and to provide the necessity care (Abramovitch et al., 2019).
Opportunities to undertake more ethnicity-related research has arisen from the gradual shift in the management of type 2 diabetes from hospitals towards primary care. This provides potential for studying the association between ethnicity and type 2 diabetes on a large scale using readily available primary care data. Additionally, since the introduction of the National Health Service (NHS)’s Quality and Outcomes Framework (QOF) in 2004, general practitioners have been offered financial incentives for monitoring and managing chronic diseases in primary care including diabetes, hence data quality has improved. Growing recognition of ethnicity as a risk factor for several common long-term illnesses has also led to considerable improvement in the recording of ethnicity in general practice records.
2.6.2 Cardiovascular disease in BAME groups
The mortality from ischemic heart disease is higher in BAME groups in both the genders in comparison to other population in UK, it is accounted to be 1.5 times higher Ref. The reason behind the increased risk of heart disease is probably due to the increased levels of insulin resistance and the associated factors which includes the endothelial dysfunction and inflammation. Similarly, within each ethnic group the traditional risk factors which includes the cholesterol, smoking also predicts the higher risk of having the heart disease. However, there had been lack of evidence on the ethnic differences when it comes to the incidence of cardiovascular diseases and their diagnosis. Despite of the fact that a wide range of studies investigated the ethnic differences in the cardiovascular diseases but they have looked at the limited number of cardiovascular diseases in isolation. It is however unknown that how UK ethnic groups before in the cardiovascular disease hat is first diagnosed in terms of acute and chronic disease diagnosis specifically. This reflects that a disease diagnosis is the turning point in an individual’s life which marks the end of possibility for the primary prevention and begins to look at the needs of considering the secondary prevention therefore total understanding of the ethnic group differences is highly significant. Furthermore, the comparisons across the broad range of populations and the need of large sample size are required to reliably identification of ethnic differences (Chaturvedi 2003).
2.7 Research Problem and Rationale
Racism and discrimination experienced by the BAME communities is due to the exposure risk and the disease progression risk as pointed by the stakeholders. The analysis from the fiscal studies in 2020 showed that there were 3.5 times higher mortality rate among Black Africans in comparison to white British people. The report is specifically striking as it significantly excluded the age, geography and the gender that could be the possible explanations for the disparities. It was even more striking to be revealed that the first 11 doctors in UK who died from COVID- 19 were from also from the BAME background. The emerging data shows that the BAME background population accounted for 63% of COVID-19 related mortalities among the NHS staff, 64% of mortality rates in nursing and support staff, and 95% of the deaths from the medical staff. Due to the pandemic, BAME communities in the UK are being further disadvantaged due to the social distancing measures, social economic fallouts, and the non-significant communication, which is impacting the health apart from the already existing high mortality rates (Anand et al. 2000; Kurian and Cardarelli 2007; Maas and Appelman 2010).
So far it has been seen that there exists wide evidence related to the concept of racial inequality; its origin, causes and consequences in the UK; and past statistics of people from BAME groups who suffer from diabetes and cardiovascular disease in the country. However, no recent study has studied such patients in the UK in terms of what sort of and to what extent they still are and have been facing racial inequality in the country, and how this affects their access to and quality of healthcare services. Thus, this research needs to be conducted in order to consider practical health outcomes for BAME groups’ people in the UK. This has been done by focusing on two aspects of racial inequality and health outcomes for BAME groups, and the relationship between these aspects considering people who suffer from diabetes and cardiovascular disease in the country.
3.1 Philosophical Foundations
There exist various research paradigms in social science research among which qualitative and quantitative paradigms are most prevalent. Researchers give preference to both qualitative and quantitative researcher based on their certain strengths and benefits (Adom et al., 2016). On the other hand, some social researchers give preference to combining both qualitative and quantitative approaches in order to get a deeper understanding of a subject or phenomenon. However, this combined approach is often argued for holding varying ontological assumptions (Lauckner et al., 2012). For instance, qualitative (interpretive) viewpoint assumes multiple realities within a context. On the contrary, quantitative (positivist) viewpoint is based on single reality that exists independently (Bhatta, 2018). This reflects that nature of any research, such as a case study research, is shaped by philosophical assumptions.
Philosophical position is highly important in a research design since it identifies epistemological and ontological features of a research. Based on this, there exists vagueness related to philosophical position of a case study research since both non-positivist (interpretivists) and positivist researcher (positivists) employ case study (Baxter and Jack, 2008). This philosophical duality has resulted into more popularity of case study in research practice. Yet, there exists different ways of understanding this, due to which different researchers have shared varying viewpoints of case study. They are usually termed as methodologist, educationist, constructivist, and pragmatist (Rashid et al., 2019). However, research activities are mostly affected by two basic philosophies namely positivism (quantitative) methodology, and interpretivist and constructivist (non-positivism) paradigms (Bhatta, 2018).
Besides the constructivist and positivist case study approaches, there exists more prominence of case study research and its connection with qualitative study. This is so because the basic idea of qualitative research is based on studying complex social phenomenon that cannot be otherwise studied by using quantitative research approach (Crowe et al., 2011). Baxter and Jack (2008) stress that qualitative research is suitable for exploration of complex phenomenon, whereas, quantitative research is preferred for studying simple phenomenon. In other words, there exists different purposes of case study research based on quantitative and qualitative approaches. Nevertheless, case study is mostly employed for qualitative research, because qualitative methods are wide enough to include explanatory, descriptive, exploratory, or interpretive aims (Bhatta, 2018).
Moreover, case study research is preferred since it helps in addressing questions related to qualitative research. It retrieves answers via conduction of study thoroughly, and thus, gaining better understanding of a specific program, organisation, activity, theme, policy, and even within any society. The case study research facilitates qualitative research by focusing on depth of a social problem instead of its scope (Adom et al., 2016). In other words, case study research requires depth of studying a specific social issue, which can be effectively done by adopting qualitative research approach.
Based on aforementioned discussion and analysis, it can be deduced that a clear understanding of research objectives is required in a case research, since it facilitates in terms of choosing the most appropriate philosophical position. This is so because clarity of a research philosophy helps in addressing confusion and issues related to any research approach. For instance, if an amalgam of philosophical positions is adopted, then it creates problems while handling research issues. This is due to the fact that there exist contradictions in qualitative and quantitative research paradigms (Lauckner et al., 2012).
Hence, in this current research, interpretive philosophy was adopted. The rationale for adopting this philosophical paradigm is that it focused on the social context of racial inequality in the UK, and allowed the researcher to analyse the research problem subjectively. Moreover, it offered a thorough understanding of racial inequalities faced by BAME groups in the UK, and relative health outcomes for those suffering from diabetes and cardiovascular disease. Furthermore, qualitative research method was adopted to inquire the research project. Use of qualitative methods allowed the researcher to answer research questions that required conformability, dependability, credibility, and transferability instead of generalizability and reliability (Ćwiklicki and Pilch, 2020). Moreover, based on the qualitative approach, inductive reasoning was followed rather than the deductive reasoning.
3.2 Research Design
Generally, a research purpose guides the choice of a particular case study design (Crowe et al., 2011). Three most common types of case study designs include single case study, holistic case study with embedded units, and multiple case studies (Baxter and Jack, 2008). Besides recognising the case study and its specific type, it is required by researchers to examine practicality of the single case study, or opt for a multiple case study design if there is a need to better understand the phenomenon being studied. However, in any case, it is crucial for researchers to consider the case study context also (Rashid et al., 2019). There are various advantages of a single case study design. First of all, it is not time consuming and costly as multiple case studies. Secondly, single case studies generate better and extra theory of top-notch quality. Thirdly, it offers deeper understanding of the phenomenon being explored (Lobo et al., 2017). On the other hand, single case studies are limited in terms of having a poor internal validity due to less rigorous design, and lack of generalizability (Gustafsson, 2017).
A holistic case study design with embedded units is preferred by researchers when they want to explore at an issue based on different factors. It is an effective design that explores sub-units within a larger case. Normally, this is done in several ways. For instance, researchers examine data within the subunits of a holistic case separately, which is termed as within-case analysis. On the other hand, researchers examine data between various subunits of a holistic case separately, which is termed as between-case analysis. Besides these, researcher often examine data across all subunits of the holistic case separately, which is termed as cross-case analysis (5). In this way, holistic case study design with embedded units offers a rich analysis and sheds better light on the case under scrutinization. However, on a negative side, this case study design is criticised for focusing on an individual sub-unit level and lacking focus on the main global issue (Baxter and Jack, 2008).
Multiple case study design is preferred if there exist multiple cases in a study (Atkinson, 2002). The multiple case study design is different from the holistic case study with embedded units based on the context. The multiple case study facilitates analysis across and within settings. On the other hand, the holistic case study with embedded units provides understanding of one single, critical, and distinct case (Crowe et al., 2011). Another characteristic of the multiple case study is that it offers assessment of several cases, which provides a better understanding of disparities and similarities between all cases (Rashid et al., 2019). The multiple case study design has several uses. These include prediction of similar outcomes, and prediction of opposing outcomes yet as per anticipated reasoning (Crowe et al., 2011). This design has both strengths and limitations. This design is strong in terms of providing reliable and robust evidence. However, it is limited in terms of being costly and very time consuming (Baxter and Jack, 2008).
This current study has adopted the holistic case study with embedded units i.e., it has analysed the case of BAME groups in the UK by using two units of analysis (diabetic people and those suffering with cardiovascular disease). The rationale for adopting holistic case study approach was that it offered specificity and depth in terms of data analysis and collection methods (Baxter and Jack, 2008). Moreover, holistic case study with embedded units allowed the researcher to gather evidence from two types of people in BAME groups. Consequently, it was easier for the researcher to generalise racial inequalities and health outcomes for all BAME people in the UK. Here, it must be noted that holistic case study with embedded units design was the most suitable for the study because there was a need to understand and analyse one critical case of BAME groups in the UK. On the other hand, multiple case study design was not suitable because no other country besides the UK was targeted for this research.
3.3 Research Population and Sampling
This study has investigated the BAME groups people (study sample) within the UK population (target population). Furthermore, the data related to this sample was gathered based on two features of the sample i.e., BAME groups people who are diabetic, and those who suffer from cardiovascular disease.
3.4 Data Collection and Analysis Methods
Wide-ranging sources of data were accessed, which reflects a strategy that leads to higher data credibility and extensive interpretations (Ćwiklicki and Pilch, 2020). Different sources and relevant documents were used for gathering data such as archival records, government documents, books, peer-reviewed journal articles, and reports. Furthermore, quantitative results were retrieved from the gathered evidence in order to make conclusions based on authentic and reliable statistical data. In this way, both qualitative and quantitative evidence were gathered. Furthermore, the researcher attained utmost benefits during the data collection process by using various sources of evidence, and maintaining a chain of evidence (Rashid et al., 2019).
The data analysis process comprised assessment, tabulation, categorisation, and recombination of both qualitative and quantitative evidence for addressing the research questions. In other words, the overall purpose of the data analysis process was to identify patterns in the gathered data. Moreover, case study reliability was enhanced by organising data in terms of notes, tables, and graphs/figures. Afterwards, the data coded from various evidence records were categorised by using the content analysis approach. As per this approach, qualitative and quantitative data related to diabetic BAME people in the UK were grouped under one category, whereas, those suffering from cardiovascular disease were grouped under another category. This helped to identify a trend or similarity in key findings. In short, qualitative data analysis turned out to be an iterative process in which connections between different coded segments (evidence/data) were organised under suitable themes. Quantitative data was presented in tabular and descriptive forms for highlighting key features of case study BAME population in the UK
3.4.1 Case Study Quality or Trustworthiness
Different elements were considered in this research design for enhancing its overall trustworthiness of quality. The quality criteria were set by focusing on the key factors of validity, confirmability, dependability, and credibility while designing and applying the case study research. However, prior to these, the researcher fulfilled responsibility by clearly stating research questions, choosing appropriate case study design, gathering and managing data in a systematic manner, and analysing the gathered data correctly (Ang et al., 2016).
First of all, considering validity, the construct validity was ensured by gathering both qualitative and quantitative data. Secondly, internal validity was ensured by establishing a relationship between racial inequalities among BAME groups and consequent health outcomes for them. Finally, external validity was ensured by generalising findings from case study of diabetic and cardiovascular disease BAME people. Secondly, considering credibility, data was gathered from various sources. This helped to attain multiple perspectives, which led to triangulation of data sources. Besides this, filed notes were maintained and reflection was used for establishing credibility of the research (O’Connor, 2011). Furthermore, completeness of data collection was ensured for making accurate conclusions.
Thirdly, considering dependability, a double coding process was applied for ensuring consistency of the research findings (Tight, n.d.). As per this method, data sets were coded and then re-coded after a short time duration for comparing the results. Next, considering dependability, stability of the findings is generally ensured by using overlapping data collection methods (Ang et al., 2016). However, this was not possible practically in this research. Therefore, the researcher focused on proper documentation of the research study which can be followed by other researchers. Finally, considering confirmability, investigator bias was avoided by gathering data from wide-ranging sources (Gerholz et al., 2020).
3.5 Limitations of the Methodology
The main limitation of this research methodology was that it could not offer generalized results as per the case study design. Consequently, it gathered an intense analysis of existing evidence instead of gathering wider first-hand data from a large population. However, the case study design was still adopted since it is generally preferred for understanding a specific structure or environment, and it does not focus on prediction of results (Snyder, 2015). Despite the fact that Marrelli (2007) asserted that case studies can generalize results through quantification of data gathered from case studies, it is still impossible to offer generalized case studies’ findings for a wider population. Furthermore, case studies are also objective for giving rise to the observer bias (Gerholz et al., 2020). However, the researcher tackled the bias in this research by offering theoretical sensitivity. The quality of sensitivity means offering meaning to occurrences and events in the gathered data (Ang et al., 2016). In this way, the researcher used personal knowledge, relevant literature, and the analytical process for ensuring theoretical sensitivity.
4.1 Introduction
This chapter has presented detailed results of the case study by focusing on health outcomes for those from a BAME background in the UK, by identifying if and why there are differences in health outcomes for those of a BAME background, and by exploring the role of public health in making a difference and addressing any inequalities in this regard. This chapter has been categorised based on the formulated research questions. The 1st section of this chapter has explored probability of diagnoses among BAME groups with diabetes and cardiovascular disease. The 2nd section has explored the possibility of mortality among BAME groups in the UK in contrast to general UK populace. Both of these sections have focused on attaining the first research objective (to analyse experience of BAME groups relative to the whole UK population by using a case study approach based on a comparative analysis looking at two health issues, diabetes and cardiovascular disease, prior to covid-19 in the country).
The 3rd section of this chapter has identified social, ethnic, and structural factors of health that lead to disparities in BAME groups and affect consequent health outcomes of covid-19. This section has focused on attaining the second research objective (to identify the extent to which membership of a BAME group dictates health outcomes). The last section of the chapter has investigated how health inequalities are addressed in the UK regarding BAME groups. All results and evidence from wide-ranging studies have been presented in narrative (descriptive), graphical, and tabular forms.
4.2 Are individuals in BAME groups more likely to be diagnosed with diabetes and cardiovascular disease?
This section has explored and investigated the probability of BAME groups to be diagnosed with diabetes and cardiovascular disease in contrast to other UK population.
4.2.1 Cardiovascular Disease’s Diagnosis among BAME groups
BAME groups in the UK are posed to higher risk of cardiovascular disease in contrast to the UK population, which is evident from higher rate of prevalence of cardiovascular disease among BAME people. This can be explained by exploring extent of prevalent and diagnosis of cardiovascular disease among various ethnic groups within BAME. For instance, Pakistani women and Bangladeshi men are exposed to highest risk of cardiovascular disease among BAME groups in contrast to white UK populace. However, Chinese men and women from BAME group are less diagnosed with cardiovascular disease in contrast to the white group (1). A common type of cardiovascular disease is IHD, which is widely prevalent among South Asian people in contrast to the white group. However, Black people are less diagnosed with IHD in the UK (Gunarathne et al., 2009).
Stroke is another type of cardiovascular disease, which is widely diagnosed among black people. As per statistical findings, black people in BAME groups are 1.5 – 2.5 times more exposed to risk of having a stroke in contrast to white people in the country. Similarly, South Asian people such as Bangladeshi and Pakistani people are also posed to 1.5 time more risk of stroke in contrast to white people. However, Chinese ethnic minorities are less diagnosed with stroke in the country (Watkinson et al., 2021). As per findings of the London Stroke Register, even though diagnosis of stroke among white people have reduced by 40% in the past few years in the UK, people from BAME groups are still exposed to high stroke incidence in the country (George et al., 2017). This can be supported by findings of Bhopal et al. (2013), who showed that South Asian men are 50% more diagnosed with heart attack in contrast to white men. Among South Asians, Bangladeshi people are exposed to highest risks of heart attack. After that, Indians and Pakistanis are diagnosed with heart attack. All of these findings are summarised in table 2 below:
Cardiovascular disease (CVD) and its types
Diagnosis among BAME groups
UK white people
Higher rate
Higher rate
Lowest rate

Lower rate
Higher rate
Higher rate
Higher rate
Lower rate
Lowest rate
1.5 times higher risk
1.5 times higher risk
Lower risk
1.5-2.5 times higher risk
Lowest risk
Heart attack