HEALTH SERVICE RESEARCH CSIRO PUBLISHING
Australian Health Review, 2015, 39, 568–576 http://dx.doi.org/10.1071/AH14254
South Asians and Anglo Australians with heart disease in Australia Sabrina Gupta1,2,5 BHSc (Hons), PhD candidate, Associate Lecturer Rosalie Aroni1 PhD, Senior Lecturer Siobhan Lockwood3 MBBS, Consultant Cardiologist Indra Jayasuriya4 MBBS, Consultant Endocrinologist Helena Teede4 MBBS, FRACP, PhD, NHMRC Fellow, Head 1
Health Services Management Unit, Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Level 3 Burnet Tower (Alfred Hospital), 89 Commercial Road, Melbourne, Vic. 3004, Australia. Email: [email protected] 2 Department of Public Health, School of Psychology and Public Health, College of Science, Health and Engineering, La Trobe University, Melbourne, Vic. 3086, Australia. 3 Monash HEART, Southern Health, Melbourne, Vic., Australia. Email: [email protected] 4 Department of Diabetes, Southern Health, Melbourne, Vic., Australia. Email: [email protected]; [email protected] 5 Corresponding author. Email: [email protected]
Abstract Objectives. The aim of the present study was to determine cardiovascular disease (CVD) risk factors and compare presentation and severity of ischaemic heart disease (IHD) among South Asians (SAs) and Anglo Australians (AAs). Methods. A retrospective clinical case audit was conducted at a public tertiary hospital. The study population included SA and AA patients hospitalised for IHD. Baseline characteristics, evidence of diabetes and other CVD risk factors were recorded. Angiography data were also included to determine severity, and these were assessed using a modified Gensini score. Results. SAs had lower mean ( s.d.) age of IHD presentation that AAs (52 9 vs 55 9 years, respectively; P = 0.02), as well as a lower average body mass index (BMI; 26 4 vs 29 6 kg/m2, respectively; P = 0.005), but a higher prevalence of type 2 diabetes (57% vs 31%, respectively; P = 0.001). No significant differences were found in coronary angiography parameters. There were no significant differences in the median (interquartile range) Gensini score between SAs and AAs (43.5 (27–75) vs 44 (26.5–68.5), respectively), median vessel score (1 (1–2) vs 2 (1–3), respectively) or multivessel score (37% (33/89) vs 54% (22/41), respectively). Conclusions. The findings show that in those with established IHD, cardiovascular risk factors, such as age at onset and BMI, differ between SAs and AAs and these differences should be considered in the prevention and management of IHD. What is known about the topic? There is much evidence on CVD and SAs, it being a leading cause of mortality and morbidity for this population both in their home countries and in countries they have migrated to. Studies conducted in Western nations other than Australia have suggested a difference in the risk profiles and presentations of CVD among SA migrants compared with the host populations in developed countries. Although this pattern of cardiovascular risk factors among SAs has been well documented, there is insufficient knowledge about this population, currently the largest population of incoming migrants, and CVD in the Australian setting. What does this paper add? This paper confirms that a similar pattern of CVD exists in Australia among SAs as does in other Western nations they have migrated to. The CVD pattern found in this population is that of an earlier age of onset at lower BMI compared with the host AA population, as well as a differing cardiovascular risk profile, with higher rates of type 2 diabetes and lower smoking rates. In addition, this study finds similar angiographic results for both the SAs and AAs; however, the SAs exhibit these similar angiographic patterns at younger ages. What are the implications for practitioners? SAs in Australia represent a high cardiovascular risk group and should be targeted for more aggressive screening at younger ages. Appropriate preventative strategies should also be considered bearing in mind the differing risk factors for this population, namely low BMI and high rates of type 2 diabetes. More intensive treatment strategies should also be regarded by practitioners. Importantly, both policy makers and health professionals must consider that all these strategies should be culturally targeted and tailored to this population and not assume a ‘one-size fits all’ approach. Journal compilation AHHA 2015
www.publish.csiro.au/journals/ahr
Heart disease in South Asians and Anglo Australians
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Received 14 January 2015, accepted 17 April 2015, published online 30 June 2015
Introduction Australia, along with several Western nations including the UK, US and Canada, is an ethnically diverse society. Approximately 28% (6.6 million people) of the total Australian population was born overseas.1 Recent Australian immigration policies have resulted in increased migration from South Asian (SA) countries, which include India, Sri Lanka, Pakistan and Bangladesh. Indians are now the fourth largest overseas-born group in Australia and the highest source of recent immigrants to Australia, with Sri Lanka in 10th place.1,2 Not only are SAs a large community within Australia, but they represent one-fifth of the global population.3 In Australia, cardiovascular disease (CVD), including ischaemic heart disease (IHD), peripheral and cerebral vascular disease, has been accorded national health priority status because it affects nearly one-quarter of the population,4 is recognised as the second leading disease burden5,6 and, in 2004–05, accounted for 11.2% of health expenditure (A$5.9 billion).5 CVD is the leading cause of mortality and morbidity among SAs in their native countries7–10 and this trend has continued after migration to developed countries such as the UK, Canada and US.11–14 Several Australian studies have shown that ethnic groups differ in their susceptibility to and incidence of CVD and cardiovascular risk factors (CVRFs) compared with the host Anglo Australian (AA) population.15–21 However, many of these studies were conducted over a decade ago. More recent Australian research16–18 has indicated that there is a higher prevalence of CVD and CVRFs among some migrant groups to Australia compared with the host AA population. Studies suggest a difference in the risk profiles and presentations of CVD among SA migrants compared with the host populations in developed countries.12,22–24 Although the pattern of CVRFs among SAs has been well documented in many developed countries, there is still insufficient knowledge about this population in the Australian setting. Similarly, a systematic review of immigrant risk of CVD has been conducted in Australia,16 very few of the 12 studies reviewed in that systematic review adequately differentiated between the migrant groupings examined or focused on SAs. In addition, few studies to date have explored the severity of coronary vessel disease when comparing CVD risk and severity across populations.25 Given the apparent increased CVRFs in SAs internationally,12,19,26,27 the question asked in the present study was whether this pattern holds true in Australia. If so, are there any distinctive features that may inform the development of more effective prevention programs and/or affect clinical practice and selfmanagement in Australia? The aim of the present study was to comprehensively audit and compare SAs (i.e. Indians and Sri Lankans) and AAs living in Victoria, Australia, who presented with an acute cardiac event at a tertiary teaching hospital. The aim was to assess CVRFs of those presenting with IHD events as well as angiographic severity of IHD and compare these across SA and AA groups.
Methods Study design In the present comprehensive retrospective case audit, we focused on demographic characteristics, CVRFs (including Type 2 diabetes mellitus (T2DM)) and coronary disease severity on angiograms because this would enable us to compare and determine whether there were any patterns of similarity or difference between the host AA population and the current migrant SA population. We targeted the highest-risk population (i.e. those hospitalised with acute coronary events) and completed a retrospective comprehensive clinical case audit to compare SA with AA subjects based on hospital records. A detailed review and scoring of those who had had an angiogram was performed by an experienced cardiologist (SL). The study was approved by the Southern Health (SH) and Monash University Human Research Ethics Committees. The research was performed at SH, which is a hospital network that encompasses five acute care hospital sites and is the largest healthcare organisation in Victoria: it serves approximately 1.6 million Australians (25% of Victoria’s population, including rural and urban areas). The SH catchment area includes areas that have large migrant populations and SAs account for the highest percentage in this catchment area.18 In the present study, we focused on only two SA migrant populations, specifically migrants from India and Sri Lanka, because they are the largest two SA migrant groups in the SH catchment area.18 Datasets from these two SA groups were merged because results from both were very similar. The audit process for this phase was a directed content analysis28 of the included medical records. Variables that were examined for each case included baseline demographic characteristics (age, sex, post code, country of birth), CVRF status (smoking status, diabetic status and body mass index (BMI)), diagnosis of IHD (year, presentation and age), angiographic details (number of diseased vessels and positioning of blockage) and treatment (medication, surgery and angioplasty and clinical follow-up). Sample Information was drawn from medical records of patients who presented to an SH network hospital over a 2-year period and had confirmed CVD. International Classifications of Diseases (ICD)10 Australian Modification (AM) codes for CVD (I20–I25) were used to determine an in-patient discharge diagnosis of CVD indicating ischaemic heart disease (e.g. angina or myocardial infarct).29 Patients were between 18 and 75 years of age and had India, Sri Lanka or Australia listed as their place of birth. Patients were classified as having T2DM if a health professional had documented it in the medical file using the ICD-10AM, if they were on hypoglycaemic drugs or insulin or if the biochemistry record showed an HbA1c level >7%. Classification of ethnicity Definitions of ethnicity remain contested in most disciplines and in much research.30,31 Although this is recognised, ethnicity
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in the present study was classified using country of birth as a proxy measure given that this was listed in hospital records. We acknowledge the difficulty in ascertaining ethnicity in databases such as a hospital audit, but because only country of birth was available to use as a proxy measure, other indicators that may be more useful combined, such as ancestry, self-identified ethnicity or parental birthplace,32 were not available to give a clearer indication of an individual’s ethnicity. Such a measure also fails to identify later-generation SAs born in Australia, thus excluding them from the study in this instance. We use the term ‘South Asian’ to refer specifically to participants born in either India or Sri Lanka. Although the term ‘South Asian’ is often used more broadly to include people from India, Sri Lanka, Pakistan, Bangladesh and Myanmar, and the United Nations also includes Afghanistan, Iran and Nepal under this term,33 most SA migrants to Australia are from India and Sri Lanka.2 Second-generation SAs were not included in the study. Our comparison population group was labelled ‘Anglo Australians’. Subjects in this group were limited to those born in Australia with Anglo Celtic and/or Anglo Saxon sounding names. Name analysis was chosen as a viable means of determining ethnicity for the purposes of sampling of both groups because ethnicity as a category is not routinely requested in hospital records.34–36 This method has a relatively high degree of accuracy among SAs.36 Typically, SA names are unique to dimensions such as religion, geographic location or religion.36 We have tried to refrain from using the terms ‘White’ or ‘Caucasian’ for our sample despite the fact these terms are used in other studies34,35,37 but, where necessary, have retained use of the terms only when citing directly from the literature. Although the terms ‘White’ and ‘Caucasian’ reflect a European heritage, we limited our definition to ‘Anglo’ in order to reflect British heritage because the dominant host population in Australia is of Anglo ancestry. Nevertheless, we recognise that these terms can produce inferences that are unintended (bigotry, simplistic understanding of the categories) and they too do not have a fixed definition and are reliant on socially agreed characteristics. Once these criteria were satisfied, all retrievable medical record files of SAs and AAs admitted under the ICD codes for CVD (I20–I25) were reviewed. Reasons for irretrievable files (n = 50) included misplaced or archived files, files transferred to some other hospital network or those that were in current use due to readmission of the patient. Given the aims of the present study, SA files were matched with randomly selected AA cases by year of index presentation. No other matching was sought. Computergenerated randomisation (Microsoft Excel, Microsoft Corporation, Seattle, WA, USA; random number generator function) was used to reduce systematic differences between the groups examined. Angiography It is well established that the severity of coronary artery disease is related to IHD outcome. The Gensini score based on coronary angiography is a relatively straightforward method for evaluation of such severity. Sinning et al.38 contend that ‘angiography score data should be routinely included into risk prediction models of incident cardiovascular events’. All available angiograms were analysed for vessel score (number of vessels with >75% stenosis; range 0–3) and stenosis severity using the Gensini scoring
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system.39 The Gensini score is an objective grading system of coronary artery luminal narrowing of the major epicardial coronary arteries according to both degree of stenosis (severity) and lesion position (extent) in the coronary arterial tree (14 defined segments). Each coronary artery segment was scored according to the following grading system: a score of 1 was given for 1%–25% luminal stenosis; a score of 2 was given for 26%–50% stenosis; a score of 4 was given for 51%–75% stenosis; a score of 8 was given for 76%–90% stenosis; a score of 16 was given for 91%–99% stenosis; and a score of 32 was given for total occlusion. These scores were then multiplied by a factor that adjusted for the importance of the lesion position in the coronary arterial tree; for example, 5 for the left main coronary artery and 2.5 for the proximal left anterior descending or circumflex artery. Each coronary angiogram was then assigned a total Gensini score that reflected the severity and extent of the coronary artery disease. Scoring enabled a meaningful comparison across cases. Data analysis Data were coded and stored in Microsoft Excel and analysed using the SPSS version 17.0 for Windows (SPSS, Chicago, IL, USA). Continuous variables were assessed for normality and are reported as the mean s.d. Categorical variables are reported as numbers (percentages). Comparisons between the two groups (SAs vs AAs) were performed using either Student’s t-test, the Chi-squared test for equal proportions or non-parametric tests, as appropriate. To determine the difference in age at onset between ethnic groups, multivariate linear regression analysis adjusted for the presence of diabetes was used. Statistical significance was set at a two-sided P < 0.05. Results Data were retrieved from 182 medical records of patients (61 AAs, 121 SAs (59 Indians and 62 Sri Lankans)). The SAs were merged because of very similar results. The mean age of SAs and AAs was 55 and 58 years, respectively (Table 1). There were more males in each group (79% SAs, 67% AAs). Employment status was recorded where data were available. Differences were found for the prevalence of CVRFs (Table 2), with SA patients being significantly younger than AA patients at first presentation of IHD (adjusted difference –3.7 years; 95% confidence interval (CI) –6.7, –0.70 years; P = 0.02)). This difference persisted even when diabetes status was accounted for. In addition, the prevalence of T2DM was greater in the SA versus AA group (57% vs 31%, respectively; P = 0.01), suggesting that the SAs were at a 1.8-fold greater risk of diabetes. However, we noted that the mean BMI of SAs was significantly lower than that of AAs (26 4 vs 29 6 kg/m2, respectively; P = 0.005). Smoking practices were self-reported. The proportion of smoking rates (past or current) tended to be lower among SA males than AA males (22% vs 36%, respectively; P = 0.07), but the difference did not reach statistical significance. However, the smoking rate (past or current) was significantly lower in SA females) than AA females (0% vs 29%, respectively; P = 0.04). Angiography was conducted in 87% of the original cohort, with 82% (130 of a possible 158) of these available for review and scoring. This represents the majority of patient records included in
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Table 1. Demographic characteristics of the study population Data are given as the mean s.d. or as the number of subjects in each group, with percentages in parentheses
Age (years) Gender Female Male Marital status Married/de facto Unmarried Employment statusA Unemployed Employed A
South Asian (n = 121)
Anglo Australian (n = 61)
P-value
55.0 ± 8.9
58.2 ± 8.2
0.03
25 (21%) 96 (79%)
20 (33%) 41 (67%)
0.07
103 (87%) 16 (13%)
38 (62%) 23 (38%)
23 (32%) 50 (68%)
17 (46%) 20 (54%)
2; 37% (33/89) vs 54% (22/41), respectively). Therefore, there were no significant differences in the coronary angiography results between the two groups, despite the younger age of the SA group. Discussion The present study found that the CVRF pattern described in other studies of SAs with IHD (i.e. presenting at a younger age with a lower BMI and a higher rate of T2DM)22–24,27,40–42 held true in the present Australian sample. Our novel data show that despite younger age and lower BMI evident in the SA records, IHD
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severity on angiography was comparable between AAs and SAs. In addition, smoking rates were higher among the AAs, with a significantly higher rate among AA females than SA females. Epidemiological studies internationally have documented a similar clinical presentation and CVD risk profile in both SA countries of origin7–10,43,44 and countries to which SAs have migrated, including the UK, Canada, US, South Africa, Singapore, Trinidad, Fiji and Mauritius.14,42,45–52 In the US and Canada, SAs not only had an earlier onset of CVD and greater severity than the host population,25,53,54 but were also younger at the time of cardiac catheterisation.25 As stated earlier, epidemiological research on this issue in Australia is limited. However, one Australian study that considered country of birth as a risk factor for acute hospitalisation for IHD17 found that SA males and females had higher risk of hospitalisation for acute myocardial infarction (AMI) than their Australian-born counterparts. Of concern, UK data suggest these patterns continue across the generational divide. Initially, UK research demonstrated that Indians 25 kg/m2), their mean BMI was lower than that of the AA participants. Nevertheless, because BMI does not enable measurement of body fat distribution, specifically central adiposity, our results may have underestimated the risk associated with body fat among SAs. Alternatively, another explanation for high IHD risk in SAs has focused on specific anatomical factors, including the fact that vessel size may be smaller in SAs, potentially contributing to higher IHD event rates.21 However, our novel data indicate that despite younger age and lower BMI, vessel size and coronary disease severity on angiography was comparable in the SA group compared with the AA group. Limitations The limitations of the present study are those of any retrospective clinical audit including incomplete or inaccurate hospital case records. There was also the potential of non-disclosure or lack of awareness of CVRFs. Analysis of variables such as the waist: hip ratio was not possible, because these were not part of routine hospital data collection. Although country of birth and name analysis were conjointly used as a proxy for ethnic identity, identification of ethnic identity for purposes of sampling remains contested. Country of birth analysis may have included AAs born in India or Sri Lanka but excluded later-generation SAs born in Australia. It was also not possible to determine the date of migration to Australia because this is not a requirement for hospital records. Therefore, we were unable to comment on the efficacy of the acculturation theory regarding potential implications of duration of stay on health-related behaviours.75 We do recognise that SAs are a heterogeneous population. However, hospital records did not include self-identified regional differences; hence, our classification as one group, SAs, raises issues of generalisability. Despite these limitations in access to ethnocultural data (which we regard as a systemic problem of hospital record construction in Australia),32 case audits can provide useful real-life data on clinical presentations and can inform future targeted research in the area. Although we did not have access to sufficient data on migration, it is important to note that SA migration to Australia is relatively recent compared with SA migration patterns to other developed nations, such as the US,76 Canada77 and particularly the UK.78 This heterogeneity of time and place of migration of different cohorts of SA migrant populations across international settings may affect the interpretation of our findings. Notwithstanding the differences in reasons for migration and in governance of immigration across countries and time periods, there is a consistency in the CVD disease pattern of SA with similarities with the UK, US and Canada.
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Conclusion The results of the present study are consistent with findings in the international literature from both SA countries of origin and developed countries, with Australian SA immigrants having IHD onset at earlier ages than the host population. In the present study, CVRF patterns in SAs with IHD included presentation at a younger age with a lower BMI and a higher rate of T2DM. We also progress the field with novel data showing that despite younger age and lower BMI of SAs, IHD severity on angiography was comparable between AAs and SAs. In addition, smoking rates were higher among the AAs, with a significantly higher rate among AA females than SA females. Additional research is needed to further characterise CVRF in SAs across Australia and to develop and/or modify appropriate risk calculation tools. Given Australia is an ethnically diverse nation, research needs to focus not only on behaviours, environmental influences and interactions with the healthcare system, but also on the impact of ethnicity and migration on IHD and CVD more broadly. Hence, we agree with Abouzeid et al.32 that the use of ethnicity-related variables should be mandated in the health sector. Further research is needed that focuses on the development and implementation of culturally relevant clinical management and culturally targeted screening and prevention strategies to provide the community, health professionals and policy makers with pertinent information for producing effective outcomes for CVD in this group at high risk. Competing interests None declared. Acknowledgements This work was supported by a part-time PhD scholarship for SG from The Jean Hailes Research Unit, Monash University. The authors thank Eldho Paul (Statistician, School of Public Health and Preventive Medicine, Monash University) for his assistance with manuscript preparation. HT is supported by a National Health and Medical Research Council of Australia fellowship.
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22 Singh RB, Tomlinson B, Thomas GN, Sharma R. Coronary artery disease and coronary risk factors: the South Asian paradox. J Nutr Environ Med 2001; 11: 43–51. doi:10.1080/13590840020030258 23 White C. Suspected research fraud: difficulties of getting at the truth. BMJ 2005; 331: 281–8. doi:10.1136/bmj.331.7511.281 24 Pella D, Thomas N, Tomlinson B, Singh RB. Prevention of coronary artery disease: the south Asian paradox. Lancet 2003; 361: 79. doi:10.1016/S0140-6736(03)12139-3 25 Gupta M, Singh N, Warsi M, Reiter M, Ali K. Canadian South Asians have more severe angiographic coronary disease than European Canadians despite having fewer risk factors. Can J Cardiol 2001; 17(Suppl C): 226C. 26 Bhopal R, Unwin N, White M, Yallop J, Walker L, Alberti KG, Harland J, Patel S, Ahmad N, Turner C, Watson B, Kaur D, Kulkarni A, Laker M, Tavridou A. Heterogeneity of coronary heart disease risk factors in Indian, Pakistani, Bangladeshi, and European origin populations: cross sectional study. BMJ 1999; 319: 215–20. doi:10.1136/bmj.319.7204.215 27 Gupta M, Doobay A, Singh N, Anand S, Raja F, Mawji F, Kho J, Karavetian A, Yi Q, Yusuf S. Risk factors, hospital management and outcomes after acute myocardial infarction in South Asian Canadians and matched control subjects. CMAJ 2002; 166: 717–22. 28 Hsieh H-F, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005; 15: 1277–88. doi:10.1177/104973 2305276687 29 National Centre for Classification in Health. International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification 6th edition ICD-10-AM, 6th edn. Canberra: Australian Institute of Health and Welfare; 2008. Available at: http:// meteor.aihw.gov.au/content/index.phtml/itemId/360927 [verified 30 April 2015]. 30 Bhopal R. Is research into ethnicity and health racist, unsound, or important science? BMJ 1997; 314: 1751. doi:10.1136/bmj.314.7096. 1751 31 Gunaratnam Y. Researching ‘race’ and ethnicity: methods, knowledge and power. London: SAGE Publications; 2003. 32 Abouzeid M, Bhopal RS, Dunbar JA, Janus ED. The potential for measuring ethnicity and health in a multicultural milieu: the case of type 2 diabetes in Australia. Ethn Health 2013; doi:10.1080/1355785 8.2013.828828 33 United Nations Statistics Division. Composition of macro geographical (continental) regions, geographical sub-regions, and selected economic and other groupings. 2009. Available at: http://unstats.un.org/unsd/methods/m49/m49regin.htm#asia [verified 30 April 2015]. 34 Tillin T, Forouhi N, Johnston DG, McKeigue PM, Chaturvedi N, Godsland IF. Metabolic syndrome and coronary heart disease in South Asians, African-Caribbeans and white Europeans: a UK populationbased cross-sectional study. Diabetologia 2005; 48: 649–56. doi:10.1007/s00125-005-1689-3 35 Whitty CJM, Brunner EJ, Shipley MJ, Hemingway H, Marmot MG. Differences in biological risk factors for cardiovascular disease between three ethnic groups in the Whitehall II study. Atherosclerosis 1999; 142: 279–86. doi:10.1016/S0021-9150(98)00239-1 36 Mateos P. A review of name-based ethnicity classification methods and their potential in population studies. Popul Space Place 2007; 13: 243–63. doi:10.1002/psp.457 37 Wilkinson P, Sayer J, Laji K, Grundy C, Marchant B, Kopelman P, Timmis AD. Comparison of case fatality in South Asian and White patients after acute myocardial infarction: observational study. BMJ 1996; 312: 1330–3. doi:10.1136/bmj.312.7042.1330 38 Sinning C, Lillpopp L, Appelbaum S, Ojeda F, Zeller T, Schnabel R, Lubos E, Jagodzinski A, Keller T, Munzel T, Bickel C, Blankenberg S. Angiographic score assessment improves cardiovascular risk prediction: the clinical value of SYNTAX and Gensini application. Clin Res Cardiol 2013; 102: 495–503. doi:10.1007/s00392-013-0555-4
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39 Gensini GG. A more meaningful scoring system for determining the severity of coronary heart disease. Am J Cardiol 1983; 51: 606. doi:10.1016/S0002-9149(83)80105-2 40 Joshi P, Islam S, Pais P, Reddy S, Dorairaj P, Kazmi K, Pandey MR, Haque S, Mendis S, Rangarajan S, Yusuf S. Risk factors for early myocardial infarction in South Asians compared with individuals in other countries. JAMA 2007; 297: 286–94. doi:10.1001/jama.297.3.286 41 Singh RB, Niaz MA, Ghosh S, Beegom R, Agarwal P, Nangia S, Moshiri M, Janus ED. Low fat intake and coronary artery disease in a population with higher prevalence of coronary artery disease: the Indian paradox. J Am Coll Nutr 1998; 17: 342–50. doi:10.1080/07315724.1998. 10718773 42 Tillin T, Hughes A, Mayet J, Whincup P, Sattar N, Forouhi N, McKeigue PM, Chaturvedi N. The relationship between metabolic risk factors and incident cardiovascular disease in Europeans, South Asians, and African Caribbeans: SABRE (Southall and Brent Revisited), a prospective population-based study. J Am Coll Cardiol 2013; 61: 1777–86. doi:10.1016/j.jacc.2012.12.046 43 Chadha SL, Radhakrishnan S, Ramachandran K, Kaul U, Gopinath N. Epidemiological study of coronary heart disease in urban population of Delhi. Indian J Med Res 1990; 92: 424–30. 44 Pais P, Pogue J, Gerstein H, Zachariah E, Savitha D, Jayprakash S, Nayak PR, Yusuf S. Risk factors for acute myocardial infarction in Indians: a case-control study. Lancet 1996; 348: 358–63. doi:10.1016/ S0140-6736(96)02507-X 45 Chiu M, Austin PC, Manuel DG, Tu JV. Comparison of cardiovascular risk profiles among ethnic groups using population health surveys between 1996 and 2007. CMAJ 2010; 182: E301–10. doi:10.1503/ cmaj.091676 46 Derry C, Bourne D, Sayed A, Disler PB, Rip MR, Taylor SP, Whittaker S, Klopper JM, Epstein L. Variations in mortality of the Coloured, White and Asian population groups in the RSA, 1978–1982. VI. Ischaemic heart disease. S Afr Med J 1987; 72: 698–700. 47 Gupta M, Brister S. Is South Asian ethnicity an independent cardiovascular risk factor? Can J Cardiol 2006; 22: 193–7. doi:10.1016/S0828282X(06)70895-9 48 Hughes K, Lun K, Yeo P. Cardiovascular diseases in Chinese, Malays, and Indians in Singapore. I. Differences in mortality. J Epidemiol Community Health 1990; 44: 24–8. doi:10.1136/jech.44.1.24 49 McKeigue PM, Miller GJ, Marmot MG. Coronary heart disease in South Asians overseas: a review. J Clin Epidemiol 1989; 42: 597–609. doi:10.1016/0895-4356(89)90002-4 50 Miller G, Beckles G, Maude G, Carson D, Alexis S, Price S, Byam NTA. Ethnicity and other characteristics predictive of coronary heart disease in a developing community: principal results of the St. James survey, Trinidad. Int J Epidemiol 1989; 18: 808–17. doi:10.1093/ije/ 18.4.808 51 Tuomilehto J, Li N, Dowse G, Gareeboo H, Chitson P, Fareed D, Min Z, Alberti KGMM, Zimmet P. The prevalence of coronary heart disease in the multi-ethnic and high diabetes prevalence population of Mauritius. J Intern Med 1993; 233: 187–94. doi:10.1111/j.1365-2796.1993. tb00672.x 52 Wild S, Laws A, Fortmann S, Varady A, Byrne C. Mortality from coronary heart disease and stroke for six ethnic groups in California, 1985–1990. Ann Epidemiol 1995; 5: 432–9. doi:10.1016/1047-2797(95) 00058-5 53 Bhattacharya G, Schoppelrey S. Preimmigration beliefs of life success, postimmigration experiences, and acculturative stress: South Asian immigrants in the United States. J Immigr Health 2004; 6: 83–92. doi:10.1023/B:JOIH.0000019168.75062.36 54 Enas E, Garg A, Davidson M, Nair V, Huet B, Yusuf S. Coronary heart disease and its risk factors in first-generation immigrant Asian Indians to the United States of America. Indian Heart J 1996; 48: 343–53.
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55 Mammi M, Pavithran P, Abdu , Rahiman P, Pisharody R, Sugathan . Acute MI in North Kerala. A 20-year hospital based study. Indian Heart J 1991; 43: 93–6. 56 Scarborough P, Bhatnagar P, Kaur A, Smolina K, Wickramasinghe K, Rayner M. Ethnic differences in cardiovascular disease 2010. Oxford: British Heart Foundation Health Promotion Research Group, Department of Public Health, University of Oxford; 2010. 57 Whincup P, Gilg J, Papacosta O, Seymour C, Miller G, Alberti K, Cook DG. Early evidence of ethnic differences in cardiovascular risk: cross sectional comparison of British South Asian and White children. BMJ 2002; 324: 635–8. doi:10.1136/bmj.324.7338.635 58 Mackay J, Mensah G. The atlas of heart disease and stroke. Geneva: World Health Organization; 2004. 59 Nazroo JY. Genetic, cultural or socio-economic vulnerability? Explaining ethnic inequalities in health. Sociol Health Illn 1998; 20: 710–30. doi:10.1111/1467-9566.00126 60 Massey DS, Arango J, Hugo G, Kouaouci A, Pellegrino A, Taylor JE. Theories of international migration: a review and appraisal. Popul Dev Rev 1993; 19: 431–66. doi:10.2307/2938462 61 Greenhalgh T, Helman C, Chowdhury AM. Health beliefs and folk models of diabetes in British Bangladeshis: a qualitative study. BMJ 1998; 316: 978–83. doi:10.1136/bmj.316.7136.978 62 Jasso G, Massey DS, Rosenweig MR, Smith JP. Immigrant health: selectivity and acculturation. In: Anderson NB, Bulatao RA, Cohen B, editors. Critical perspectives on racial and ethnic differences in health in late life. Washington, DC: National Academies Press; 2004. Available at: http://www.ncbi.nlm.nih.gov/books/NBK25533/ [verified 30 April 2015]. 63 World Health Organization Study Group. Diet, nutrition and prevention of chronic diseases. Geneva: World Health Organization; 1990. 64 Chandalia M, Lin P, Seenivasan T, Livingston EH, Snell PG, Grundy SM, Abate N. Insulin resistance and body fat distribution in South Asian men compared to Caucasian men. PLoS ONE 2007; 2: e812. doi:10.1371/ journal.pone.0000812 65 Sniderman A, Furberg CD, Keech A, Roeters van Lennep JE, Frohlich J, Jungner I, Walldius G. Apolipoproteins versus lipids as indices of coronary risk and as targets for statin treatment. Lancet 2003; 361: 777–80. doi:10.1016/S0140-6736(03)12663-3 66 Australian Bureau of Statistics. Customised report. national health survey 2007–08. Prevalence of cardiovascular disease for persons born in Southern Asian countries. Canberra: Commonwealth of Australia; 2010. 67 Myers R, Kiely D, Cupples L, Kannel W. Parental history is an independent risk factor for coronary artery disease: the Framingham study. Am Heart J 1990; 120: 963–9. doi:10.1016/0002-8703(90) 90216-K 68 Forouhi N, Sattar N. CVD risk factors and ethnicity: a homogeneous relationship? Atheroscler Suppl 2006; 7: 11–19. doi:10.1016/j.athero sclerosissup.2006.01.003 69 McKeigue PM, Shah B, Marmot MG. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet 1991; 337: 382–6. doi:10.1016/0140-6736 (91)91164-P 70 World Health Organization. The world health report 1995. Bridging the gaps. Report of the Director General. Geneva: World Health Organization; 1995. 71 Tobacco Free Initiative. WHO global report on trends in tobacco smoking 2000–2025. World Health Organization. 2015. Available at: http://www.who.int/gho/tobacco/use/en/ [verified 1 May 2015]. 72 Bhopal R, Hayes L, White M, Unwin N, Harland J, Ayis S, Alberti G. Ethnic and socio-economic inequalities in coronary heart disease, diabetes and risk factors in Europeans and South Asians. J Public Health Med 2002; 24: 95–105. doi:10.1093/pubmed/24.2.95
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73 World Health Organization Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363: 157–63. doi:10.1016/S0140-6736(03) 15268-3 74 Banerji MA, Faridi N, Atluri R, Chaiken RL, Lebovitz HE. Body composition, visceral fat, leptin, and insulin resistance in Asian Indian men. J Clin Endocrinol Metab 1999; 84: 137–44. 75 Satia-Abouta J, Patterson RE, Neuhouser ML, Elder JP. Dietary acculturation: applications to nutrition research and dietetics. J Am Diet Assoc 2002; 102: 1105–18. doi:10.1016/S0002-8223(02)90247-6
76 Kelkar M. South Asian immigration in the United States: a gendered perspective. Harvard J Asian Am Policy Rev 2012; 22: 55–60. 77 Lindsay C. Profiles of ethnic communities in Canada: the South Asian community in Canada 2001. Ottawa: Statistics Canada; 2007. 78 Office for National Statistics. Ethnicity and national identity in England and Wales 2011. 2012. Available at: http://www.ons.gov.uk/ons/rel/ census/2011-census/key-statistics-for-local-authorities-in-england-andwales/rpt-ethnicity.html#tab-Measuring-ethnicity- [verified 4 March 2015].
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Australian Health Review, 2015, 39, 568–576 http://dx.doi.org/10.1071/AH14254
South Asians and Anglo Australians with heart disease in Australia Sabrina Gupta1,2,5 BHSc (Hons), PhD candidate, Associate Lecturer Rosalie Aroni1 PhD, Senior Lecturer Siobhan Lockwood3 MBBS, Consultant Cardiologist Indra Jayasuriya4 MBBS, Consultant Endocrinologist Helena Teede4 MBBS, FRACP, PhD, NHMRC Fellow, Head 1
Health Services Management Unit, Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Level 3 Burnet Tower (Alfred Hospital), 89 Commercial Road, Melbourne, Vic. 3004, Australia. Email: [email protected] 2 Department of Public Health, School of Psychology and Public Health, College of Science, Health and Engineering, La Trobe University, Melbourne, Vic. 3086, Australia. 3 Monash HEART, Southern Health, Melbourne, Vic., Australia. Email: [email protected] 4 Department of Diabetes, Southern Health, Melbourne, Vic., Australia. Email: [email protected]; [email protected] 5 Corresponding author. Email: [email protected]
Abstract Objectives. The aim of the present study was to determine cardiovascular disease (CVD) risk factors and compare presentation and severity of ischaemic heart disease (IHD) among South Asians (SAs) and Anglo Australians (AAs). Methods. A retrospective clinical case audit was conducted at a public tertiary hospital. The study population included SA and AA patients hospitalised for IHD. Baseline characteristics, evidence of diabetes and other CVD risk factors were recorded. Angiography data were also included to determine severity, and these were assessed using a modified Gensini score. Results. SAs had lower mean ( s.d.) age of IHD presentation that AAs (52 9 vs 55 9 years, respectively; P = 0.02), as well as a lower average body mass index (BMI; 26 4 vs 29 6 kg/m2, respectively; P = 0.005), but a higher prevalence of type 2 diabetes (57% vs 31%, respectively; P = 0.001). No significant differences were found in coronary angiography parameters. There were no significant differences in the median (interquartile range) Gensini score between SAs and AAs (43.5 (27–75) vs 44 (26.5–68.5), respectively), median vessel score (1 (1–2) vs 2 (1–3), respectively) or multivessel score (37% (33/89) vs 54% (22/41), respectively). Conclusions. The findings show that in those with established IHD, cardiovascular risk factors, such as age at onset and BMI, differ between SAs and AAs and these differences should be considered in the prevention and management of IHD. What is known about the topic? There is much evidence on CVD and SAs, it being a leading cause of mortality and morbidity for this population both in their home countries and in countries they have migrated to. Studies conducted in Western nations other than Australia have suggested a difference in the risk profiles and presentations of CVD among SA migrants compared with the host populations in developed countries. Although this pattern of cardiovascular risk factors among SAs has been well documented, there is insufficient knowledge about this population, currently the largest population of incoming migrants, and CVD in the Australian setting. What does this paper add? This paper confirms that a similar pattern of CVD exists in Australia among SAs as does in other Western nations they have migrated to. The CVD pattern found in this population is that of an earlier age of onset at lower BMI compared with the host AA population, as well as a differing cardiovascular risk profile, with higher rates of type 2 diabetes and lower smoking rates. In addition, this study finds similar angiographic results for both the SAs and AAs; however, the SAs exhibit these similar angiographic patterns at younger ages. What are the implications for practitioners? SAs in Australia represent a high cardiovascular risk group and should be targeted for more aggressive screening at younger ages. Appropriate preventative strategies should also be considered bearing in mind the differing risk factors for this population, namely low BMI and high rates of type 2 diabetes. More intensive treatment strategies should also be regarded by practitioners. Importantly, both policy makers and health professionals must consider that all these strategies should be culturally targeted and tailored to this population and not assume a ‘one-size fits all’ approach. Journal compilation AHHA 2015
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Heart disease in South Asians and Anglo Australians
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Received 14 January 2015, accepted 17 April 2015, published online 30 June 2015
Introduction Australia, along with several Western nations including the UK, US and Canada, is an ethnically diverse society. Approximately 28% (6.6 million people) of the total Australian population was born overseas.1 Recent Australian immigration policies have resulted in increased migration from South Asian (SA) countries, which include India, Sri Lanka, Pakistan and Bangladesh. Indians are now the fourth largest overseas-born group in Australia and the highest source of recent immigrants to Australia, with Sri Lanka in 10th place.1,2 Not only are SAs a large community within Australia, but they represent one-fifth of the global population.3 In Australia, cardiovascular disease (CVD), including ischaemic heart disease (IHD), peripheral and cerebral vascular disease, has been accorded national health priority status because it affects nearly one-quarter of the population,4 is recognised as the second leading disease burden5,6 and, in 2004–05, accounted for 11.2% of health expenditure (A$5.9 billion).5 CVD is the leading cause of mortality and morbidity among SAs in their native countries7–10 and this trend has continued after migration to developed countries such as the UK, Canada and US.11–14 Several Australian studies have shown that ethnic groups differ in their susceptibility to and incidence of CVD and cardiovascular risk factors (CVRFs) compared with the host Anglo Australian (AA) population.15–21 However, many of these studies were conducted over a decade ago. More recent Australian research16–18 has indicated that there is a higher prevalence of CVD and CVRFs among some migrant groups to Australia compared with the host AA population. Studies suggest a difference in the risk profiles and presentations of CVD among SA migrants compared with the host populations in developed countries.12,22–24 Although the pattern of CVRFs among SAs has been well documented in many developed countries, there is still insufficient knowledge about this population in the Australian setting. Similarly, a systematic review of immigrant risk of CVD has been conducted in Australia,16 very few of the 12 studies reviewed in that systematic review adequately differentiated between the migrant groupings examined or focused on SAs. In addition, few studies to date have explored the severity of coronary vessel disease when comparing CVD risk and severity across populations.25 Given the apparent increased CVRFs in SAs internationally,12,19,26,27 the question asked in the present study was whether this pattern holds true in Australia. If so, are there any distinctive features that may inform the development of more effective prevention programs and/or affect clinical practice and selfmanagement in Australia? The aim of the present study was to comprehensively audit and compare SAs (i.e. Indians and Sri Lankans) and AAs living in Victoria, Australia, who presented with an acute cardiac event at a tertiary teaching hospital. The aim was to assess CVRFs of those presenting with IHD events as well as angiographic severity of IHD and compare these across SA and AA groups.
Methods Study design In the present comprehensive retrospective case audit, we focused on demographic characteristics, CVRFs (including Type 2 diabetes mellitus (T2DM)) and coronary disease severity on angiograms because this would enable us to compare and determine whether there were any patterns of similarity or difference between the host AA population and the current migrant SA population. We targeted the highest-risk population (i.e. those hospitalised with acute coronary events) and completed a retrospective comprehensive clinical case audit to compare SA with AA subjects based on hospital records. A detailed review and scoring of those who had had an angiogram was performed by an experienced cardiologist (SL). The study was approved by the Southern Health (SH) and Monash University Human Research Ethics Committees. The research was performed at SH, which is a hospital network that encompasses five acute care hospital sites and is the largest healthcare organisation in Victoria: it serves approximately 1.6 million Australians (25% of Victoria’s population, including rural and urban areas). The SH catchment area includes areas that have large migrant populations and SAs account for the highest percentage in this catchment area.18 In the present study, we focused on only two SA migrant populations, specifically migrants from India and Sri Lanka, because they are the largest two SA migrant groups in the SH catchment area.18 Datasets from these two SA groups were merged because results from both were very similar. The audit process for this phase was a directed content analysis28 of the included medical records. Variables that were examined for each case included baseline demographic characteristics (age, sex, post code, country of birth), CVRF status (smoking status, diabetic status and body mass index (BMI)), diagnosis of IHD (year, presentation and age), angiographic details (number of diseased vessels and positioning of blockage) and treatment (medication, surgery and angioplasty and clinical follow-up). Sample Information was drawn from medical records of patients who presented to an SH network hospital over a 2-year period and had confirmed CVD. International Classifications of Diseases (ICD)10 Australian Modification (AM) codes for CVD (I20–I25) were used to determine an in-patient discharge diagnosis of CVD indicating ischaemic heart disease (e.g. angina or myocardial infarct).29 Patients were between 18 and 75 years of age and had India, Sri Lanka or Australia listed as their place of birth. Patients were classified as having T2DM if a health professional had documented it in the medical file using the ICD-10AM, if they were on hypoglycaemic drugs or insulin or if the biochemistry record showed an HbA1c level >7%. Classification of ethnicity Definitions of ethnicity remain contested in most disciplines and in much research.30,31 Although this is recognised, ethnicity
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in the present study was classified using country of birth as a proxy measure given that this was listed in hospital records. We acknowledge the difficulty in ascertaining ethnicity in databases such as a hospital audit, but because only country of birth was available to use as a proxy measure, other indicators that may be more useful combined, such as ancestry, self-identified ethnicity or parental birthplace,32 were not available to give a clearer indication of an individual’s ethnicity. Such a measure also fails to identify later-generation SAs born in Australia, thus excluding them from the study in this instance. We use the term ‘South Asian’ to refer specifically to participants born in either India or Sri Lanka. Although the term ‘South Asian’ is often used more broadly to include people from India, Sri Lanka, Pakistan, Bangladesh and Myanmar, and the United Nations also includes Afghanistan, Iran and Nepal under this term,33 most SA migrants to Australia are from India and Sri Lanka.2 Second-generation SAs were not included in the study. Our comparison population group was labelled ‘Anglo Australians’. Subjects in this group were limited to those born in Australia with Anglo Celtic and/or Anglo Saxon sounding names. Name analysis was chosen as a viable means of determining ethnicity for the purposes of sampling of both groups because ethnicity as a category is not routinely requested in hospital records.34–36 This method has a relatively high degree of accuracy among SAs.36 Typically, SA names are unique to dimensions such as religion, geographic location or religion.36 We have tried to refrain from using the terms ‘White’ or ‘Caucasian’ for our sample despite the fact these terms are used in other studies34,35,37 but, where necessary, have retained use of the terms only when citing directly from the literature. Although the terms ‘White’ and ‘Caucasian’ reflect a European heritage, we limited our definition to ‘Anglo’ in order to reflect British heritage because the dominant host population in Australia is of Anglo ancestry. Nevertheless, we recognise that these terms can produce inferences that are unintended (bigotry, simplistic understanding of the categories) and they too do not have a fixed definition and are reliant on socially agreed characteristics. Once these criteria were satisfied, all retrievable medical record files of SAs and AAs admitted under the ICD codes for CVD (I20–I25) were reviewed. Reasons for irretrievable files (n = 50) included misplaced or archived files, files transferred to some other hospital network or those that were in current use due to readmission of the patient. Given the aims of the present study, SA files were matched with randomly selected AA cases by year of index presentation. No other matching was sought. Computergenerated randomisation (Microsoft Excel, Microsoft Corporation, Seattle, WA, USA; random number generator function) was used to reduce systematic differences between the groups examined. Angiography It is well established that the severity of coronary artery disease is related to IHD outcome. The Gensini score based on coronary angiography is a relatively straightforward method for evaluation of such severity. Sinning et al.38 contend that ‘angiography score data should be routinely included into risk prediction models of incident cardiovascular events’. All available angiograms were analysed for vessel score (number of vessels with >75% stenosis; range 0–3) and stenosis severity using the Gensini scoring
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system.39 The Gensini score is an objective grading system of coronary artery luminal narrowing of the major epicardial coronary arteries according to both degree of stenosis (severity) and lesion position (extent) in the coronary arterial tree (14 defined segments). Each coronary artery segment was scored according to the following grading system: a score of 1 was given for 1%–25% luminal stenosis; a score of 2 was given for 26%–50% stenosis; a score of 4 was given for 51%–75% stenosis; a score of 8 was given for 76%–90% stenosis; a score of 16 was given for 91%–99% stenosis; and a score of 32 was given for total occlusion. These scores were then multiplied by a factor that adjusted for the importance of the lesion position in the coronary arterial tree; for example, 5 for the left main coronary artery and 2.5 for the proximal left anterior descending or circumflex artery. Each coronary angiogram was then assigned a total Gensini score that reflected the severity and extent of the coronary artery disease. Scoring enabled a meaningful comparison across cases. Data analysis Data were coded and stored in Microsoft Excel and analysed using the SPSS version 17.0 for Windows (SPSS, Chicago, IL, USA). Continuous variables were assessed for normality and are reported as the mean s.d. Categorical variables are reported as numbers (percentages). Comparisons between the two groups (SAs vs AAs) were performed using either Student’s t-test, the Chi-squared test for equal proportions or non-parametric tests, as appropriate. To determine the difference in age at onset between ethnic groups, multivariate linear regression analysis adjusted for the presence of diabetes was used. Statistical significance was set at a two-sided P < 0.05. Results Data were retrieved from 182 medical records of patients (61 AAs, 121 SAs (59 Indians and 62 Sri Lankans)). The SAs were merged because of very similar results. The mean age of SAs and AAs was 55 and 58 years, respectively (Table 1). There were more males in each group (79% SAs, 67% AAs). Employment status was recorded where data were available. Differences were found for the prevalence of CVRFs (Table 2), with SA patients being significantly younger than AA patients at first presentation of IHD (adjusted difference –3.7 years; 95% confidence interval (CI) –6.7, –0.70 years; P = 0.02)). This difference persisted even when diabetes status was accounted for. In addition, the prevalence of T2DM was greater in the SA versus AA group (57% vs 31%, respectively; P = 0.01), suggesting that the SAs were at a 1.8-fold greater risk of diabetes. However, we noted that the mean BMI of SAs was significantly lower than that of AAs (26 4 vs 29 6 kg/m2, respectively; P = 0.005). Smoking practices were self-reported. The proportion of smoking rates (past or current) tended to be lower among SA males than AA males (22% vs 36%, respectively; P = 0.07), but the difference did not reach statistical significance. However, the smoking rate (past or current) was significantly lower in SA females) than AA females (0% vs 29%, respectively; P = 0.04). Angiography was conducted in 87% of the original cohort, with 82% (130 of a possible 158) of these available for review and scoring. This represents the majority of patient records included in
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Table 1. Demographic characteristics of the study population Data are given as the mean s.d. or as the number of subjects in each group, with percentages in parentheses
Age (years) Gender Female Male Marital status Married/de facto Unmarried Employment statusA Unemployed Employed A
South Asian (n = 121)
Anglo Australian (n = 61)
P-value
55.0 ± 8.9
58.2 ± 8.2
0.03
25 (21%) 96 (79%)
20 (33%) 41 (67%)
0.07
103 (87%) 16 (13%)
38 (62%) 23 (38%)
23 (32%) 50 (68%)
17 (46%) 20 (54%)
2; 37% (33/89) vs 54% (22/41), respectively). Therefore, there were no significant differences in the coronary angiography results between the two groups, despite the younger age of the SA group. Discussion The present study found that the CVRF pattern described in other studies of SAs with IHD (i.e. presenting at a younger age with a lower BMI and a higher rate of T2DM)22–24,27,40–42 held true in the present Australian sample. Our novel data show that despite younger age and lower BMI evident in the SA records, IHD
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severity on angiography was comparable between AAs and SAs. In addition, smoking rates were higher among the AAs, with a significantly higher rate among AA females than SA females. Epidemiological studies internationally have documented a similar clinical presentation and CVD risk profile in both SA countries of origin7–10,43,44 and countries to which SAs have migrated, including the UK, Canada, US, South Africa, Singapore, Trinidad, Fiji and Mauritius.14,42,45–52 In the US and Canada, SAs not only had an earlier onset of CVD and greater severity than the host population,25,53,54 but were also younger at the time of cardiac catheterisation.25 As stated earlier, epidemiological research on this issue in Australia is limited. However, one Australian study that considered country of birth as a risk factor for acute hospitalisation for IHD17 found that SA males and females had higher risk of hospitalisation for acute myocardial infarction (AMI) than their Australian-born counterparts. Of concern, UK data suggest these patterns continue across the generational divide. Initially, UK research demonstrated that Indians 25 kg/m2), their mean BMI was lower than that of the AA participants. Nevertheless, because BMI does not enable measurement of body fat distribution, specifically central adiposity, our results may have underestimated the risk associated with body fat among SAs. Alternatively, another explanation for high IHD risk in SAs has focused on specific anatomical factors, including the fact that vessel size may be smaller in SAs, potentially contributing to higher IHD event rates.21 However, our novel data indicate that despite younger age and lower BMI, vessel size and coronary disease severity on angiography was comparable in the SA group compared with the AA group. Limitations The limitations of the present study are those of any retrospective clinical audit including incomplete or inaccurate hospital case records. There was also the potential of non-disclosure or lack of awareness of CVRFs. Analysis of variables such as the waist: hip ratio was not possible, because these were not part of routine hospital data collection. Although country of birth and name analysis were conjointly used as a proxy for ethnic identity, identification of ethnic identity for purposes of sampling remains contested. Country of birth analysis may have included AAs born in India or Sri Lanka but excluded later-generation SAs born in Australia. It was also not possible to determine the date of migration to Australia because this is not a requirement for hospital records. Therefore, we were unable to comment on the efficacy of the acculturation theory regarding potential implications of duration of stay on health-related behaviours.75 We do recognise that SAs are a heterogeneous population. However, hospital records did not include self-identified regional differences; hence, our classification as one group, SAs, raises issues of generalisability. Despite these limitations in access to ethnocultural data (which we regard as a systemic problem of hospital record construction in Australia),32 case audits can provide useful real-life data on clinical presentations and can inform future targeted research in the area. Although we did not have access to sufficient data on migration, it is important to note that SA migration to Australia is relatively recent compared with SA migration patterns to other developed nations, such as the US,76 Canada77 and particularly the UK.78 This heterogeneity of time and place of migration of different cohorts of SA migrant populations across international settings may affect the interpretation of our findings. Notwithstanding the differences in reasons for migration and in governance of immigration across countries and time periods, there is a consistency in the CVD disease pattern of SA with similarities with the UK, US and Canada.
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Conclusion The results of the present study are consistent with findings in the international literature from both SA countries of origin and developed countries, with Australian SA immigrants having IHD onset at earlier ages than the host population. In the present study, CVRF patterns in SAs with IHD included presentation at a younger age with a lower BMI and a higher rate of T2DM. We also progress the field with novel data showing that despite younger age and lower BMI of SAs, IHD severity on angiography was comparable between AAs and SAs. In addition, smoking rates were higher among the AAs, with a significantly higher rate among AA females than SA females. Additional research is needed to further characterise CVRF in SAs across Australia and to develop and/or modify appropriate risk calculation tools. Given Australia is an ethnically diverse nation, research needs to focus not only on behaviours, environmental influences and interactions with the healthcare system, but also on the impact of ethnicity and migration on IHD and CVD more broadly. Hence, we agree with Abouzeid et al.32 that the use of ethnicity-related variables should be mandated in the health sector. Further research is needed that focuses on the development and implementation of culturally relevant clinical management and culturally targeted screening and prevention strategies to provide the community, health professionals and policy makers with pertinent information for producing effective outcomes for CVD in this group at high risk. Competing interests None declared. Acknowledgements This work was supported by a part-time PhD scholarship for SG from The Jean Hailes Research Unit, Monash University. The authors thank Eldho Paul (Statistician, School of Public Health and Preventive Medicine, Monash University) for his assistance with manuscript preparation. HT is supported by a National Health and Medical Research Council of Australia fellowship.
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