Diets of minority ethnic groups in the UK: influence on chronic disease risk and implications for prevention

Improving access and quality for ethnic minority women— panel discussion

Evidence suggests that Dutch people smoke substantially more than their British counterparts. These differences have been suggested to relate, in part, to the health-related policy differences between the two countries. It is unclear whether these differences affect smoking among ethnic minority groups in similar ways. We assessed whether the lower smoking prevalence in the U.K. general population compared with the Netherlands is also observed in ethnic minority groups (i.e., Dutch vs. English South Asians and Dutch- vs. English-Africans). We used similar surveys from the United Kingdom and the Netherlands to explore these questions. The response rate ranges from 60% in the Health Survey for England and the SUNSET study to 67.5% in Newcastle Heart Project (n = 21,429). After adjustment for other factors, compared with White-Dutch, the prevalence ratio (PR) of current smoking was lower in White-English men (PR = 0.58, 95% CI: 0.49-0.67) and women (PR = 0.56, 0.49-0.65). Among African groups, compared with Dutch-African, the prevalence of current smoking was lower in English- African Caribbean men (PR = 0.48, 0.31-0.75) and women (PR = 0.47, 0.39-0.69) and Sub-Saharan African men (PR = 0.53, 0.29-0.99) and women (PR = 0.37, 0.14-0.99). Among South Asian groups, compared with Dutch South Asian, the prevalence of smoking was lower in English-Indian men (PR = 0.67, 0.51-0.89) and women (PR = 0.16, 0.07-0.37), Pakistani men (PR = 0.62, 0.46-0.82) and women (PR = 0.13, 0.05-0.33), and Bangladeshi men (PR = 0.77, 0.59-0.99) and women (PR = 0.11, 0.03-0.45). Ever-smoking rates were lower and smoking cessation rates were higher in the English ethnic groups than in the Dutch ethnic groups except for smoking cessation among the South Asian women. Similar to the White group, the prevalence of smoking was lower in South Asian and African men and women in England than their corresponding Dutch counterparts. These differences suggest that, among other factors, antismoking policies might have a similar influence on both ethnic majority and minority groups and illustrate the potential importance of national context on public health policy on ethnic minority groups' smoking behavior.

Indigenous food systems can affect multiple aspects of Indigenous people's health. In China, the government declared that there are no Indigenous people in China and used the term “ethnic minority groups” instead. However, to date, no attempt has been made to investigate the nutrition status and dietary practices of all 55 ethnic minority groups. To understand this pertinent issue, a systematic review is required. The main selection criteria were publications should be about nutrition status or dietary practices among ethnic minority groups in China, specify the name of the ethnic minority group, and be published within the past 10 years. For this literature review, 111 publications were selected through Wanfang Med Online for Chinese publications and Google Scholar for English publications. Linear regressions were applied to explore what factors can affect the total number of publications for an ethnic minority group. The main findings include that only 15 ethnic minority groups have dietary intake data representing the general people of the ethnic group; only seven ethnic minority groups have data for both nutrition status (anthropometric and nutrients intake/deficiency) and dietary practices (dietary intake and dietary habits); there are still 10 ethnic minority groups with a total number of population 845,420 that lack studies on both nutrition status and dietary practices; ethnic minority groups are suffering from double-burden malnutrition and consuming unbalanced diets; primary and middle school students are the most prevalent study population than any other age group due to easy access; and an ethnic minority group is likely to have more publications about nutrition status and dietary practices if they have a larger population or are unique to a region. The results indicate that more national-level programs and timely nutrition and dietary reports should be implemented to address double-burden malnutrition and unbalanced diets among ethnic minority groups in China. More studies involving maternal nutrition, targeting underrepresented ethnic minority groups and age groups, and exploring traditional food systems in China are also essential to better understand and address this issue.

Does Stigma Keep Poor Young Immigrant and U.S.-Born Black and Latina Women From Seeking Mental Health Care?

Understanding the reasons for poor asthma outcomes in ethnic minorities: welcome progress, but important questions remain

There has been a considerable amount of literature implying a group of people with a shared distinctive culture and a common language, and as such represents published on different aspects of health in ethnic minority groups resident in the UK [1]. The central issue of a shared national identity. In considering both the reporting of pain and consultation patterns, such ‘nonsuch health research has been on the differential occurrence of specific diseases or medical conditions in ethnic biological’ cultural factors may be particularly important. minority groups in relation to indigenous UK populations. Such differential rates of occurrence may, through In the UK, ethnic minority groups represent almost 5% of the total population. It is evident from reviewing epidemiological investigation, provide clues to the aetiology of disease. The main aim of this article is to the literature that consultation patterns, reporting of pain and co-morbidities such as psychiatric distress vary review research carried out investigating ethnicity and the experience of pain and related health-seeking behaviconsiderably between different ethnic minority groups (e.g. Afro-Caribbean and South Asian ethnic groups our in individuals of South Asian origin resident in the UK. First, the review will determine whether there is have been documented as having very different rates of psychiatric morbidity [3, 4]). For this reason, the current any evidence for differential rates in the occurrence of pain in ethnic minorities of South Asian origin relative review focuses on the largest ethnic minority group: those of South Asian origin (with an ancestry from the to the indigenous population of the UK. Possible explanations for differential reporting of pain will then Indian Subcontinent: India, Pakistan or Bangladesh), which represent approximately half of all ethnic minority be assessed, including issues relating to social difficulties and acculturation, but with specific emphasis on cultural groups in the UK. interpretation of pain and pain thresholds (the subject of much research in the literature). Finally, the literature Consultation behaviour describing the experience of psychiatric distress, which is a common co-morbidity of the chronic pain experiA consistent finding in the literature is that adult Asians attend general practices more frequently compared with ence, in ethnic minority groups of South Asian origin will be appraised. the European population [5, 6 ]. A large-scale community survey comparing aspects of illness behaviour in Asian-born and British-born residents in London, UK, Defining ethnicity found that Asian men were more than twice as likely to consult their general practitioner (GP) in the previous The term ‘ethnic group’ is used in preference to ‘race’ in this review. Although it is evident that ‘race’ is used 2 weeks, irrespective of self-assessment of health or presence of illness/disability. Balarajan et al. [6 ] examconsiderably more frequently in the medical literature (a Medline search from 1985 to 1990 found that ‘race’ ined the levels of GP consultations among the different ethnic groups resident in Britain, and noted a 2-fold was mentioned in 5892 publications compared with 762 publications using the term ‘ethnicity’ or ‘ethnic group’ excess of consultations for Pakistani men aged 16–44 yr in comparison with European men, with higher rates also [1]), such terminology has been criticized as giving an inaccurate description of causation [2]. Race implies a evident for Pakistani women aged 16–44 yr relative to European women. A further study of a group general genetic basis when considering differential health status, suggesting that differences identified between individuals practice in London found a marked increase in the standardized consultation ratio for Asians [7]. Such are fixed or predisposed. Ethnicity is a cultural term, differences in health-seeking behaviour are not just evident in adults of the Asian population—children and Submitted 9 June 1999; revised version accepted 21 June 1999. young people from South Asian ethnic groups have also Correspondence to: D. Pope, Arthritis Research Campaign been found to be more likely to consult a GP compared Epidemiology Unit, School of Epidemiology and Health Sciences, The with European children and children of other ethnic University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK. groups [8]. However, it is not clear whether such findings

A Systematic Review and Meta-Analysis of Ethnic Differences in Use of Dementia Treatment, Care, and Research

Objective: To compare the prevalence of growth retardation in students aged 7-18 years from 26 minority ethnic groups in China and provides reference evidence to promote the growth and improve the health status of students in minority ethnic groups. Methods: The body height data of students aged 7-18 years in 26 minority ethnic groups in 2014 Chinese National Surveys on Students' Constitution and Health were used for the analysis and comparison. Growth retardation was defined according to the school-aged child and adolescent malnutrition screening standard (WS/T 456-2014). Results: In 2014, the average body heights of school boys and school girls aged 18 years in 26 ethnic minority groups were (168.3±6.8) cm and (156.2±5.9) cm respectively. The overall growth retardation prevalence rate of school boys and school girls in 26 ethnic groups were 5.4% and 5.1%, respectively. The growth retardation prevalence rate was highest in students of Shui ethnic group (24.5% for boys and 23.0% for girls), and lowest in students of Hui ethnic group (0.1% for boys and 0.3% for girls). The growth retardation prevalence rates in 9 ethnic minority groups were higher than the average level, in these 9 ethnic groups, the differences in prevalence rates of boys of Buyi ethnic group, girls of Lisu ethnic group and girls of Hani ethnic group had no significance among four age groups. Growth retardation in students of Sala ethnic group was mainly observed in age group 7-9 years, but in others ethnic group, for example, Wa ethnic, it was mainly observed in older age group. The students in minority ethnic groups in southwestern China had the highest growth retardation prevalence rate (8.1%), significantly higher than that in northern China (0.8%) (OR=10.6, 95%CI: 7.8-14.4). The overall growth retardation prevalence rate between 7 and 17 years old was negatively correlated with the body height of 18 years old (boys: r=-0.811, P<0.001; girls: r=-0.715, P<0.001). Conclusions: In 2014, the differences in body height among students aged 18 years in 26 minority ethnic groups in China were significant. In general, the first five minority ethnic groups with high detection rate of growth retardation in boys were Shui, Wa, Buyi, Yao and Yi, and the five minority ethnic groups with high detection rate of growth retardation in girls were Shui, Yao, Buyi, Wa and Miao. The detection rate of growth retardation was highest in students of minority ethnic groups in southwestern China. Nutritional interventions and healthy education should be carried out in minority ethnic groups and areas with high growth retardation prevalence rate to promote the growth of the students.

Mary Gatineau and Shireen Mathrani from the National Obesity Observatory explore the relationship between ethnicity and obesity in the UK There is no straightforward relationship between obesity and ethnicity. Obesity prevalence varies substantially between ethnic groups in the UK and interpretation of data is difficult because of uncertainty about appropriate obesity thresholds and associated levels of health risk. In addition, health behaviours both across and within minority ethnic groups are influenced by a complex interplay of cultural, lifestyle and socioeconomic factors.1 Obesity prevalence The most current data on adult obesity by ethnic group are from the Health Survey for England (HSE) 2004. Findings suggest that compared to the general population, obesity prevalence is lower among men from black African, Indian, Pakistani and most markedly, Bangladeshi and Chinese communities. Among women, obesity prevalence appears to be higher for those from Black African, Black Caribbean and Pakistani groups than for women in the general population and lower for women from the Chinese ethnic group.2 The National Child Measurement Programme (NCMP) provides the most robust data on child obesity in the UK and includes a detailed breakdown by ethnic sub-group. Recent analysis by the National Obesity Observatory (NOO)i shows that in Reception class, obesity prevalence is especially high for boys and girls from Black African and Black other ethnic groups and boys from the Bangladeshi ethnic group.ii The pattern for girls in Year 6 is broadly similar to that of girls in Reception, while for boys in Year 6, obesity prevalence is significantly higher for all ethnic groups compared to White British, with boys of Bangladeshi ethnicity having the highest prevalence. The analysis also finds a trend of rising obesity prevalence for both boys and girls of Bangladeshi ethnicity, with no significant changes in any other ethnic groups.3 Figure 1 provides a summary of this rising trend for Bangladeshi children in Year 6 compared to all other ethnic groups combined. Obesity measures and thresholds There are a number of issues associated with the measurement of obesity and the thresholds used for minority ethnic groups in the UK. Different ethnic groups are associated with a range of different body shapes and different physiological responses to fat storage. Body mass index (BMI) is not always an accurate predictor of body fat or fat distribution in individuals. Research has shown that for the same level of BMI, people of African ethnicity appear likely to carry less fat and people of South Asian ethnicity more fat than the general population. This may have led to an overestimation of obesity among African and an underestimation among South Asian groups.4 South Asian and Chinese populations have been found to be at risk of chronic diseases and mortality at lower levels than European populations. Revised BMI thresholds and waist circumference measures have been recommended for these groups. NCMP findings demonstrate a very high prevalence of obesity among boys of Bangladeshi ethnicity. These findings are in contrast with the general perception that children from Black ethnic groups have the highest obesity prevalence. The high odds of children from Black groups being classified as obese may in fact be due to physical characteristics related to ethnicity and, in particular, height, which can lead to skewed BMI.3,iii Factors determining obesity riskiv Dietary patterns of minority ethnic groups are influenced by many factors including availability of food, level of income, health, food beliefs, religion, cultural patterns and customs.5 While many people from these groups have healthier eating patterns than the White population, less healthy diets are known to be of concern in some groups, in particular those of South Asian origin. Migration to the UK has a significant impact on dietary habits. …

Many ethnic minorities in Europe have a higher type 2 diabetes (T2D) prevalence than their host European populations. The risk size differs between ethnic groups, but the extent of the differences in the various ethnic minority groups has not yet been systematically quantified. We conducted a meta-analysis of published data on T2D in various ethnic minority populations resident in Europe compared to their host European populations. We systematically searched MEDLINE (using PUBMED) and EMBASE for papers on T2D prevalence in ethnic minorities in Europe published between 1994 and 2014. The ethnic minority groups were classified into five population groups by geographical origin: South Asian (SA), Sub-Saharan African (SSA), Middle Eastern and North African (MENA), South and Central American (SCA), and Western Pacific (WP). Pooled odds ratios with corresponding 95 % confidence interval (CI) were calculated using Review Manager 5.3. Twenty articles were included in the analysis. Compared with the host populations, SA origin populations had the highest odds for T2D (3.7, 95 % CI 2.7-5.1), followed by MENA (2.7, 95 % CI 1.8-3.9), SSA (2.6, 95 % CI 2.0-3.5), WP (2.3, 95 % CI 1.2-4.1), and lastly SCA (1.3, 95 % CI 1.1-1.6). Odds ratios were in all ethnic minority populations higher for women than for men except for SCA. Among SA subgroups, compared with Europeans, Bangladeshi had the highest odds ratio of 6.2 (95 % CI 3.9-9.8), followed by Pakistani (5.4, 95 % CI 3.2-9.3) and Indians (4.1, 95 % CI 3.0-5.7). The risk of T2D among ethnic minority groups living in Europe compared to Europeans varies by geographical origin of the group: three to five times higher among SA, two to four times higher among MENA, and two to three times higher among SSA origin. Future research and policy initiatives on T2D among ethnic minority groups should take the interethnic differences into account.

Type 2 diabetes (T2D) is well established as an important risk factor for cardiovascular disease. The global burden of T2D is increasing rapidly, in particular, in low- and middle-income countries. Ethnic minority groups in Europe are up to four times more likely to be affected by T2D compared to Europeans and are also disproportionally affected compared to their compatriots in their countries of origin. The reasons for this disproportionate burden are unclear but are believed to be an interplay between genetic and environmental factors. The underlying pathophysiology of T2D seems to differ between ethnic groups, with most ethnic minority groups having higher insulin resistance compared to Europeans even in a normoglycaemic state. Furthermore, while obesity is an important determinant of T2D across ethnic groups, higher levels of obesity in ethnic minority groups only explain part of their higher T2D burden. Health-related behaviours such as diet and physical activity can contribute to T2D among ethnic minority groups either mediated via obesity or directly. Few genetic factors have been identified that may predispose ethnic minority groups to T2D, but more diversity in genetics research is needed to get a better picture of genetic predispositions for T2D among ethnic minority groups. In the meantime, adaptation of population-based lifestyle interventions to ethnic minority groups, and evaluation of these interventions, is crucial to curb the rise of T2D among ethnic minority groups. Early detection is essential for prevention of micro- and macrovascular complications contributing to cardiovascular disease.

The Deadly Triad

Previous studies in the UK have established that minority ethnic groups as a whole experience more ill-health and onset of morbidity at younger ages or at lower levels of risk than the ‘White British’ population. Since the Race Relations Act of 1968, the official collection of ethnic group statistics by all government bodies has been mandated as a pre-requisite for identifying and tackling ethnic inequalities. The capture of ethnicity data in routine health records across the UK National Health Service forms part of this initiative. Although the facility to record ethnicity has been available in primary care since 1991 and in secondary care since 1995, until recently, unsystematic recording resulted in poor quality of the initial data, limiting the usefulness of these data for clinical care, commissioning and research. The incentivisation of ethnicity recording in 2006 as part of the Quality and Outcomes Framework has resulted in an improvement of the quality of these data, though their suitability for use in UK-wide population-based research, at the commencement of this PhD, had not yet been explored. The studies reported in this thesis investigated the utility of electronic health records for research into ethnic differences in health and comprised three sub-studies. Firstly, the completeness, usability and generalisability of ethnicity data captured in primary and secondary care databases were assessed. Results showed that in 2012, valid ethnicity was recorded for 78.3% of patients in the Clinical Practice Research Datalink (CPRD), 79.4% of inpatients, and 50% of A&E patients and outpatients in the Hospital Episode Statistics for England (HES). Over 80% of patients with multiple ethnicities recorded had codes which either were identical or fell into the same five high-level ethnic group categorisation. The ethnic breakdown of the CPRD was found to be comparable to that of the combined censuses for England, Wales, Scotland and Northern Ireland, suggesting that studies of ethnic populations within the CPRD can be generalised to the UK population, particularly when using data from 2006 onwards, where completeness and consistency are highest. Secondly, in collaboration with the UK Biobank study, a pragmatic and comprehensive definition of diabetes mellitus for use in electronic health databases was developed. Once applied to the CPRD, the algorithms identified 34,530 individuals with type 1 diabetes and 355,717 individuals with type 2 diabetes. The incidence of type 2 diabetes was almost doubled in South Asian compared with White groups (70.7 vs 42.0 events per 10,000 person years). After adjustment for gender and age group, the risk of type 2 diabetes was over three times higher in the South Asian group compared with White the group (Hazard Ratio 3.27 95%CI 3.19, 3.35). Finally, a prospective cohort study of 860,000 patients registered with the CPRD was undertaken to quantify ethnic differences in the risk of incident coronary heart disease (CHD) and the extent to which this relationship is modified by the presence of type 2 diabetes. The presence of diabetes increased the risk of CHD by 40%, although this reduced to 22% after accounting for age, gender and deprivation (Hazard Ratio 1.22 CI95 1.20, 1.25). The excess risk associated with diabetes was markedly higher for ethnic minority groups, with an adjusted increase of 60% and 75% in South Asian and Black African/Caribbean groups respectively, compared with 28% in the White groups. Adjusted rates of CHD were consistently higher in South Asian groups and lower in Black African/Caribbean groups, with differences more pronounced amongst men than women. Ethnic differences in CHD risk were consistently more pronounced amongst patients without type 2 diabetes than in those with type 2 diabetes. The studies have generated novel results which provide valuable information about the usability and generalisability of ethnicity data available in UK electronic health records. They have replicated findings from non-database studies of the prevalence and incidence of diabetes and extended our knowledge of the patterning of ethnic differences in heart disease outcomes. They represent the first ever use of UK routine electronic health records to answer these questions in relation to ethnicity. Together, the findings reported in this thesis provide a unique insight into the ways in which routinely recorded ethnicity data can be maximised for the purposes of epidemiological research into health inequalities across the UK.

Background: International and UK data suggest that Black, Asian and Minority Ethnic (BAME) groups are at increased risk of infection and death from COVID-19. We aimed to explore the risk of death in minority ethnic groups in England using data reported by NHS England. Methods: We used NHS data on patients with a positive COVID-19 test who died in hospitals in England published on 28th April, with deaths by ethnicity available from 1st March 2020 up to 5pm on 21 April 2020. We undertook indirect standardisation of these data (using the whole population of England as the reference) to produce ethnic specific standardised mortality ratios (SMRs) adjusted for age and geographical region. Results: The largest total number of deaths in minority ethnic groups were Indian (492 deaths) and Black Caribbean (460 deaths)groups. Adjusting for region we found a lower risk of death for White Irish (SMR 0.52; 95%CIs 0.45-0.60) and White British ethnic groups (0.88; 95%CIs 0.86-0.0.89), but increased risk of death for Black African (3.24; 95%CIs 2.90-3.62), Black Caribbean (2.21; 95%CIs 2.02-2.41), Pakistani (3.29; 95%CIs 2.96-3.64), Bangladeshi (2.41; 95%CIs 1.98-2.91) and Indian (1.70; 95%CIs 1.56-1.85) minority ethnic groups. Conclusion: Our analysis adds to the evidence that BAME people are at increased risk of death from COVID-19 even after adjusting for geographical region. We believe there is an urgent need to take action to reduce the risk of death for BAME groups and better understand why some ethnic groups experience greater risk. Actions that are likely to reduce these inequities include ensuring adequate income protection (so that low paid and zero-hours contract workers can afford to follow social distancing recommendations), reducing occupational risks (such as ensuring adequate personal protective equipment), reducing barriers in accessing healthcare and providing culturally and linguistically appropriate public health communications.

Background: International and UK data suggest that Black, Asian and Minority Ethnic (BAME) groups are at increased risk of infection and death from COVID-19. We aimed to explore the risk of death in minority ethnic groups in England using data reported by NHS England. Methods: We used NHS data on patients with a positive COVID-19 test who died in hospitals in England published on 28th April, with deaths by ethnicity available from 1st March 2020 up to 5pm on 21 April 2020. We undertook indirect standardisation of these data (using the whole population of England as the reference) to produce ethnic specific standardised mortality ratios (SMRs) adjusted for age and geographical region. Results: The largest total number of deaths in minority ethnic groups were Indian (492 deaths) and Black Caribbean (460 deaths)groups. Adjusting for region we found a lower risk of death for White Irish (SMR 0.52; 95%CIs 0.45-0.60) and White British ethnic groups (0.88; 95%CIs 0.86-0.0.89), but increased risk of death for Black African (3.24; 95%CIs 2.90-3.62), Black Caribbean (2.21; 95%CIs 2.02-2.41), Pakistani (3.29; 95%CIs 2.96-3.64), Bangladeshi (2.41; 95%CIs 1.98-2.91) and Indian (1.70; 95%CIs 1.56-1.85) minority ethnic groups. Conclusion: Our analysis adds to the evidence that BAME people are at increased risk of death from COVID-19 even after adjusting for geographical region, but was limited by the lack of data on deaths outside of NHS settings and ethnicity denominator data being based on the 2011 census. Despite these limitations, we believe there is an urgent need to take action to reduce the risk of death for BAME groups and better understand why some ethnic groups experience greater risk. Actions that are likely to reduce these inequities include ensuring adequate income protection, reducing occupational risks, reducing barriers in accessing healthcare and providing culturally and linguistically appropriate public health communications.