Differences in initiation and discontinuation of preventive medications and use of non-pharmacological interventions after acute coronary syndrome among migrants and Danish-born

Differences in initiation and discontinuation of preventive medications and use of... Abstract Aims The aim of this article is to assess initiation and discontinuation of preventive medication and use of non-pharmacological prevention interventions after acute coronary syndrome (ACS) among migrants to Denmark compared to the local-born Danish population, taking differences in comorbidity and sociodemographic factors into account. Methods and results In this large cohort study, we selected the population (n = 33 199) from nationwide registers and followed each individual among migrants and Danish-born 180 days after ACS. We identified the initiation and discontinuation of medications and the initiation and number of contacts for non-pharmacological interventions in the Register of Medicinal Products Statistics and the National Patient Register, and adjusted for comorbidity and sociodemographic factors. Non-Western migrants had lower relative risks for initiating adenosine diphosphate receptor (ADP)- and angiotensin-converting enzyme (ACE)-inhibitors (0.93, CI: 0.90; 0.96, and 0.91, CI: 0.87; 0.96) and patient education (0.95, CI: 0.92; 0.98). Further, non-Western migrants had higher hazard ratios for discontinuing medications (statins: 1.64, CI: 1.45; 1.86, ADP-inhibitors: 1.72, CI: 1.50; 1.97, β-blockers: 1.52, CI: 1.40; 1.64, and ACE-inhibitors: 1.72, CI: 1.46; 2.02), and fewer contacts for physical exercise and patient education (P < 0.001 and P = 0.011). Conclusion We identified differences between non-Western migrants and Danish-born in initiation and discontinuation of preventive medications and use of non-pharmacological interventions after ACS. These differences could not be explained by differences in comorbidity or sociodemographic factors. View largeDownload slide View largeDownload slide Secondary prevention, Migrants, Acute coronary syndrome, Equity of care, Register studies Introduction Migrants in Europe are expected to form a larger share of patients with acute coronary syndrome (ACS) due to the recent increase in the influx of refugees from conflict-affected areas and the ageing of those who entered Europe during earlier waves of immigration. To ensure equity of care, health care systems must adapt to these demographic changes. This challenge is evident when it comes to equal access to acute treatment but may in fact be even larger when it comes to secondary prevention. The clinical and public health importance of secondary prevention is supported by scientific evidence demonstrating that medications and other secondary prevention interventions reduce mortality and readmissions and may improve quality of life.1–3 Preventive medications after ACS includes treatment with aspirin, statins, adenosine diphosphate receptor inhibitors (ADP-inhibitors) and β-blockers, as well as angiotensin-converting enzyme inhibitors (ACE-inhibitors) in selected patients.2,3 Non-pharmacological preventive interventions include physical exercise, dietary counselling and patient education on medications, life-style, smoking cessation, and psychosocial management.1–3 Despite strong evidence for their benefits, low use of preventive interventions have been found in general populations after coronary heart disease (CHD), associated with comorbidity and the sociodemographic factors of advanced age, distance from providers and living alone.4–7 In the case of migrants, several barriers to health care in general have been documented.8 European research on migrants’ use of preventive interventions following CHD is based on small populations or shows contradictory findings.7,9–12 A large study by Sumner et al. (n = 98 880) assessed ethnic minority status as one of the several potential predictors for use of non-pharmacological interventions. However, the results were prone to selection bias because only subjects who had participated in an assessment session were included, and the study did not include medications.7 Hence, the objectives of this study are to test the hypothesis that migrants to Denmark, compared to Danish-born patients, show lower use of preventive medications, physical exercise, dietary advice, and patient education post-ACS. Material and methods This study followed the STROBE guidelines: Strengthening the Reporting of Observational Studies in Epidemiology.13 Setting Denmark has a background population of about 5.5 million people. The health care system is tax-funded with free access to health care services, and part-coverage of the costs of prescribed medicines for all subjects with a Danish citizenship or long-term residency permit. Study design and patient population We conducted a nationwide, population-based follow-up study using anonymized data from the Danish National Patient Register (NPR), including relevant patients from 1 January 2010 to 31 December 2013 (Figure 1). Danish National Patient Register contains information on discharge diagnoses, hospital, hospital-based activities such as physiotherapy, and day of discharge for in- and outpatients.14 International Classification of Diseases 10th revision (ICD-10) has been used for diagnose-classification since 1994. Data on death and age were retrieved from the Central Person Register (CPR), containing basic data on legal Danish residents, including date and place of birth, address, and death. We included subjects hospitalized on an acute basis according to the criteria: (i) ≥18 years of age with a CPR-number; (ii) discharged alive between 1 January 2010 and 31 December 2013 from a department of cardiology; and (iii) suffering acute coronary syndrome (ACS), with diagnoses of acute myocardial infarction (AMI) and unstable angina pectoris (UAP) (ICD10: DI21, DI248, DI249, DI240, DI200). Patients were excluded if they had been given an ischaemic heart disease diagnosis within the previous 12 months. Only the first admission was included for patients with multiple admissions during the study period. Figure 1 View largeDownload slide Flowchart of inclusion in the population based on data from the Danish National Patient Register, the Central Person Register, and Statistics Denmark. Figure 1 View largeDownload slide Flowchart of inclusion in the population based on data from the Danish National Patient Register, the Central Person Register, and Statistics Denmark. Data collection and definitions Migrant status The study population was linked to registers at Statistics Denmark containing information on country of origin and socio-demography. Subjects were classified as Danish-born (n = 30 686), Western (n = 882), or non-Western migrants (n = 1631) according to Statistics Denmark’s categorizations. Descendants of migrants were excluded. We divided non-Western migrants into subgroups at the country level and compared Danish-born with the three largest such subgroups, namely Turks (n = 363), nationals from the former republic of Yugoslavia (n = 291), and Pakistanis (n = 193). Nationals from the former republic of Yugoslavia were merged into one group. Outcomes Outcomes were (i) initiation of medications, (ii) initiation of non-pharmacological interventions, (iii) time to discontinuation of medications, and (iv) number of contacts for non-pharmacological interventions. Medications included statins (C10A), ADP-inhibitors (B01AC04, B01AC22, and B01AC24), β-blockers (C07), and ACE-inhibitors (C09). Initiation of medications was defined as subjects having claimed reimbursement of at least one prescription within the 180 days observational period. Discontinuation of medications was defined as failing to claim reimbursement of a new prescription for relevant medication within 90 days after estimated date of expiry of a reimbursed prescription. Data on reimbursed prescriptions included the years 2010–2014 and were retrieved from the Register of Medicinal Products Statistics.15 Aspirin can be bought over the counter and was not included. Initiation of physical exercise, dietary advice, and patient education was defined as having at least one contact per type of intervention. Lastly, the number of contacts for each type of non-pharmacological intervention was determined. Data on non-pharmacological interventions were retrieved from NPR, following the definitions used in the Danish Cardiac Rehabilitation Database (DHRD).16 Follow-up period for non-pharmacological interventions was 180 days from the date of discharge. Covariates and confounding variables Central Person Register provided data on age and sex, Statistics Denmark on family income, education, employment and cohabiting status, and NPR on comorbidity and whether non-pharmacological interventions were delivered by university-affiliated hospitals. We used the Charlson Comorbidity Index (CCI) as a comorbidity measure.17 Congestive heart failure (CHF) and types I and II diabetes were expected to influence the outcomes independently, and were therefore excluded from CCI, and adjusted for separately. Statistical analysis We carried out binomial regression analyses to evaluate relative risks (RRs) for initiating medication and non-pharmacological interventions. Time to medication discontinuation was compared among patients who initiated medication, using Cox proportional hazards regression analyses and presented as hazard ratios (HRs). Follow-up started at the time of reimbursement of the first prescription. Subjects were censored at the time of death or emigration if these events occurred during the follow-up period. The assumptions of proportional hazards in the data set were assessed visually and found to be appropriate. In addition, a Fine and Gray model was used to construct cumulative incidence curves of medication discontinuation. Death or emigration was considered as competing risks when computing the cumulative incidence. Patients not initiating medication therapy during the first 6 months were included as discontinued at baseline. Gray’s test was used to compare curves. In order to assess differences in number of contacts for non-pharmacological interventions, we applied the Wilcoxon–Mann–Whitney two-sample rank-sum test. The choice of test depended on data being ordinal and not meeting the assumptions of parametric tests. The sum of contacts for each non-pharmacological intervention was compared between Danish-born and Western and non-Western migrants respectively, including the subgroups of Turks, former Yugoslavs, and Pakistanis. Relative risks and HRs were presented as crude and adjusted by multivariable analyses, with inclusion of all covariates as potential confounders. Statistical analyses were performed with SAS 9.4 statistical software (SAS Institute Inc., Cary, NC, USA). Results A flowchart of the population selection is provided in Figure 1. Population characteristics The study population included 33 199 subjects, out of which 14 emigrated and 3058 died during the 180 days of follow-up. Danish-born had the highest mortality during follow-up, which was expected due to higher age. The unadjusted descriptive data showed that, compared to Danish-born, non-Western migrants were younger and more likely to be men, have a lower family income and be in receipt of welfare support other than retirement support (Table 1). Furthermore, they had less comorbidity, although types I and II diabetes were more frequent. Western migrants deviated little from Danish-born. Characteristics of the subgroups is available in Supplementary material online. Subgroups were similar to the non-Western migrants, except Pakistanis had higher prevalence of CHF (n = 34, 17.6%), diabetes (n = 69, 35.8%), and UAP (n = 58, 30.1%), lower incidence of AMI (n = 130, 67.4%), and were more often discharged from university-affiliated hospitals (n = 85, 95.9%). Former Yugoslavs had higher prevalence of AF (n = 31, 10.7%). Table 1 Characteristics of the study population showing Danish-born compared to migrants Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Values are numbers (percentages) unless otherwise stated. NSTEMI, Non-S-T-segment elevation myocardial infarction; STEMI, S-T-segment elevation myocardial infarction. a Cut-offs: International Standard Classification of Education. b Tertiles. c During index admission. d Excluding CHF and types I and II diabetes. Table 1 Characteristics of the study population showing Danish-born compared to migrants Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Values are numbers (percentages) unless otherwise stated. NSTEMI, Non-S-T-segment elevation myocardial infarction; STEMI, S-T-segment elevation myocardial infarction. a Cut-offs: International Standard Classification of Education. b Tertiles. c During index admission. d Excluding CHF and types I and II diabetes. Initiation of medications and non-pharmacological interventions Compared to Danes, non-Western migrants had lower RRs for initiating ADP- and ACE-inhibitors (0.93, CI: 0.90; 0.96 and 0.91, CI: 0.87; 0.96). Sensitivity analyses only including subjects who had not died or emigrated during follow-up resulted in RRs that were virtually unchanged. For non-pharmacological interventions, median follow-up ranged from 166 days among Danish-born to 170 among the Pakistani subgroup. For initiation of non-pharmacological interventions, non-Western migrants showed lower RRs for patient education (0.95, CI: 0.92; 0.98). Western migrants did not deviate significantly from Danish-born. The proportions of Danish-born, Western, and non-Western migrants, which initiated neither medications nor non-pharmacological interventions, were 3.7%, 4.0%, and 4.4%. Furthermore, proportions of subjects who initiated all medications and non-pharmacological interventions were 9.4%, 11.0%, and 9.4%. Subgroups of non-Western migrants Subgroups were also compared to Danish-born (Table 2). Lower initiation was found for ADP-inhibitors among Turks (0.92, CI: 0.87; 0.98) and Pakistanis (0.83, CI: 0.75; 0.92) and for ACE-inhibitors among Turks (0.81, CI: 0.72; 0.91). Lower initiation rates were found for physical exercise, dietary advice, and patient education among Turks (0.83, CI: 0.73; 0.94, 0.80, CI: 0.68; 0.95, and 0.90, CI: 0.84; 0.97). Table 2 Initiation of medications and non-pharmacological interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university hospital. Table 2 Initiation of medications and non-pharmacological interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university hospital. Discontinuation of medications Median follow-up for statins ranged from 814 days among Danish-born to 749 days among non-Western migrants. For β-blockers, the range was 540 days for Danish-born to 395 among Turks. Adenosine diphosphate receptor- and ACE-inhibitors had median follow-up equivalent to those seen for statins. The combined effect of lack of medication initiation and discontinuation of medication during follow-up for the entire study population is shown in cumulative incidence curves in Take home figure, including P-values for Gray’s test for equality. When focusing on the patients, who did initiate medication therapy, non-Western migrants had a higher adjusted HR of discontinuation of all medication groups (statins: 1.64, CI: 1.45; 1.86, ADP-inhibitors: 1.72, CI: 1.50; 1.97, β-blockers: 1.52, CI: 1.40; 1.64, and ACE-inhibitors: 1.72, CI: 1.46; 2.02) compared to Danes (Table 3). Among Western migrants, the risk of discontinuation was only elevated for ACE-inhibitors (1.38, CI: 1.11; 1.72). Table 3 Risks of discontinuation of medications and differences in number of contacts for non-pharmacological preventive interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university-affiliated hospital. Table 3 Risks of discontinuation of medications and differences in number of contacts for non-pharmacological preventive interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university-affiliated hospital. Take home figure View largeDownload slide Combined lack of medication initiation and discontinuation of initiated medication. Time zero is the date of the first reimbursement of a prescription. Coloured spectrums indicate confidence intervals. Gray’s test for equality of cumulative incidence functions: statins: P = 0.013; ADP-inhibitors, β-blockers, and ACE-inhibitors: P < 0.001. Take home figure View largeDownload slide Combined lack of medication initiation and discontinuation of initiated medication. Time zero is the date of the first reimbursement of a prescription. Coloured spectrums indicate confidence intervals. Gray’s test for equality of cumulative incidence functions: statins: P = 0.013; ADP-inhibitors, β-blockers, and ACE-inhibitors: P < 0.001. Contacts for non-pharmacological interventions For physical exercise, non-Western migrants had significantly fewer contacts when compared to Danish-born (median 7 vs. 9, P < 0.001) (Table 3). Western and non-Western migrants had statistically significant fewer contacts for patient education when compared to Danish-born, although the median number of contacts were similar (median 4 vs. 4, P = 0.036 and median 4 vs. 4, P = 0.011). Subgroups of non-Western migrants The risks of discontinuing medications were also elevated in all subgroups, the highest being observed amongst Pakistanis (2.70, CI: 1.89; 3.85) (Table 3). Compared to Danish-born, former Yugoslavs and Pakistanis had fewer contacts for physical exercise (median 9 vs. 5, P < 0.001 and median 9 vs. 4, P < 0.001).Turks showed a probability of fewer contacts for physical exercise close to the significant cut-off point of 0.05 (median 9 vs. 8, P = 0.051). Former Yugoslavs had fewer contacts for dietary advice (median 1 vs. 2, P = 0.006), and fewer contacts for patient education were observed among Turks (median 4 vs. 3, P = 0.029) and Pakistanis (median 4 vs. 3, P = 0.040). Discussion In this large nationwide cohort study (n = 33 199), we compared post-ACS use of secondary prevention among non-Western and Western migrants and Danish-born. Non-Western migrants had lower initiation of ADP- and ACE-inhibitors and a higher risk of discontinuation of all medications included in the study. For non-pharmacological interventions, lower initiation of patient education and fewer contacts for physical exercise and patient education were found in non-Western migrants. Adjustment for comorbidity and sociodemographic factors did not explain the observed differences. Medication persistence Previous studies have compared migrants’ and local-born CHD patients’ use of preventive medications, but results are conflicting, applied analyses are weak, or studies have been underpowered. Conflicting results of two Swedish studies may be explained by period, population size, and whether previous drug use was included in the analysis.10,11 A Canadian study found higher discontinuation rates from treatment with ACE-inhibitors, but included only South Asian and Chinese ethnic groups above the age of 66, and assessed discontinuation on dichotomized outcomes, instead of Cox regression analysis, which allows for a more detailed analysis.18 A smaller Danish study found discontinuation risks equivalent to ours, albeit the study was probably underpowered with fewer significant differences.12 Hence, our study adds new insights relating to population size, statistical analysis, role of confounding variables, and the assessment of both use of medications and non-pharmacological interventions. Use of non-pharmacological interventions There are very few European studies of the use of non-pharmacological interventions that focus on migrants or ethnic minority patients. One study found that ethnic minority status was not an independent predictor for uptake, but the study was prone to selection bias,7 and, in a UK survey on uptake, data quality on ethnic minorities was too poor to be representative.9 North American studies show lower use among ethnic minorities, but transferability to a European context is low.18,19 Hence, our documentation of lower use of non-pharmacological interventions among non-Western migrants in a European welfare state provides new and important findings. However, while the documented differences meet statistical significance, the difference of, at most, two contacts for physical exercise, and one for dietary advice and patient education, do not necessarily imply clinically important differences. The findings therefore add new knowledge related to inequities in access, but the clinical implications of this are yet to be fully clarified. Western and non-Western migrants and subgroups The observed differences call for cautious interpretation. First, the origin of migrant populations and health care utilization patterns may differ across the European countries. Secondly, the heterogeneous non-Western and Western migrant groups may not be representative of specific subgroups, as was particularly the case for former Yugoslavs, and which has been discussed in a previous article.20 A complex of pre-migration, migration and post-migration circumstances affecting health care needs, language skills, and other factors associated with acculturation may explain these findings.21 The lower use of secondary prevention among non-Western migrants is worrying and may be associated with higher mortality and rehospitalization rates and a lower health-related quality of life.1–3 However, there is a lack of studies which assess mortality, rehospitalization, or quality of life in comparable migrant populations. Comorbidity and sociodemographic factors We found limited confounding by comorbidity and sociodemographic factors. This may be due to the setting, with free access to health services and partial reimbursement of medication costs. However, the largest between-group differences were found in medication persistence, and similarly, a previous Danish study found that under-use of health care among non-Western migrants was only present for services where user-payment was demanded, despite adjustment for sociodemographic factors.22 Therefore, it is possible that differences between migrants and native born in uptake of secondary prevention may be even larger in countries with higher user-payment of health care services, regardless of the socioeconomic position of the migrant population. Differences may also be explained by barriers at the system and provider levels, where, for example, professionals’ knowledge and attitudes may affect their ability to meet the needs of people of different ethnic backgrounds.8 We therefore need studies of the role of health care providers and health care systems, in secondary prevention of CHD. Furthermore, studies of migrants’ perceptions of secondary prevention may contribute to a better understanding of our findings. Studies from the UK and Canada have found individually perceived barriers related to previous negative experiences communication difficulties, and cultural acceptability.21 However, with dissimilar migrant populations and health care systems, these studies may not be fully applicable to the context of a Nordic welfare state. Strengths and limitations of the study Nationwide registers enabled us to focus on a large population, to include data on medications and non-pharmacological interventions, to assess initiation, discontinuation, and number of health care contacts, and to include all eligible subjects, including the elderly and those with low native-language proficiency, who are frequently under-represented in research.9,23 However, we did not have information about contraindications to secondary prevention measures, including terminal illness and patient preferences. Other potential weaknesses include the fact that administrative registers are not created for research purposes and can be incomplete or biased. We used NPR data to establish our population, where the predictive value of the ACS diagnosis has been found to be valid,24 and also to provide information on use of non-pharmacological interventions. Danish National Patient Register is used for hospitals’ financial reimbursements, which might encourage a practice of less thorough registrations of services with lower reimbursements. However, as biased registration is unlikely to be associated with patients' migration backgrounds, our comparative design eliminates this risk, and a previous study validate our findings.12 Furthermore, results are in accordance with quality standards of the DHRD,16 where initiation of statin treatment in 80% of all patients is considered acceptable. Finally, one shortcoming is that we were unable to make causal inferences to explain the noted differences. It is noteworthy that non-Western migrants’ lower use of patient education was found in conjunction with lower medication persistence and that clinical guidelines recommend patient education to increase medication persistence in CHD.1 However, a recent meta-analysis only finds effects of patient education on quality of life and health care costs, and results may be affected by type II errors. Thus, there is a call for more research on patient education, particularly among under-represented ethnic minority groups.23 Finally, non-Western migrants comprise a smaller part of European populations, and efforts to increase their use of preventive measures may only have minor effects at national population levels. However, measures that improve use of secondary prevention in the entire post-ACS population may be of benefit to all, given that the interventions are widely accessible and sensitive to diverse needs. Conclusion After adjustment for comorbidity and socio-demography, we found substantial differences between Danish-born and non-Western migrants in medication persistence, which are likely to be of clinical importance. Differences in use of non-pharmacological interventions were less substantial, and possibly of less clinical importance, but reflect general inequities in migrants’ access to health services. There is thus a need for actions to improve migrants’ access to both medications and non-pharmacological interventions post-ACS. Supplementary material Supplementary material is available at European Heart Journal online. Funding Capital Region of Denmark and the Danish Heart Association (14-R97-A5261-22875). Conflict of interest: S.P.J. has received fees from Bristol-Myers Squibb, grants and personal fees from Pfizer, personal fees from Bayer, personal fees from Boehringer-Ingelheim, outside the submitted work. 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This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Heart Journal Oxford University Press

Differences in initiation and discontinuation of preventive medications and use of non-pharmacological interventions after acute coronary syndrome among migrants and Danish-born

European Heart Journal , Volume Advance Article (25) – Apr 30, 2018

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Oxford University Press
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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com.
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1522-9645
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10.1093/eurheartj/ehy227
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Abstract

Abstract Aims The aim of this article is to assess initiation and discontinuation of preventive medication and use of non-pharmacological prevention interventions after acute coronary syndrome (ACS) among migrants to Denmark compared to the local-born Danish population, taking differences in comorbidity and sociodemographic factors into account. Methods and results In this large cohort study, we selected the population (n = 33 199) from nationwide registers and followed each individual among migrants and Danish-born 180 days after ACS. We identified the initiation and discontinuation of medications and the initiation and number of contacts for non-pharmacological interventions in the Register of Medicinal Products Statistics and the National Patient Register, and adjusted for comorbidity and sociodemographic factors. Non-Western migrants had lower relative risks for initiating adenosine diphosphate receptor (ADP)- and angiotensin-converting enzyme (ACE)-inhibitors (0.93, CI: 0.90; 0.96, and 0.91, CI: 0.87; 0.96) and patient education (0.95, CI: 0.92; 0.98). Further, non-Western migrants had higher hazard ratios for discontinuing medications (statins: 1.64, CI: 1.45; 1.86, ADP-inhibitors: 1.72, CI: 1.50; 1.97, β-blockers: 1.52, CI: 1.40; 1.64, and ACE-inhibitors: 1.72, CI: 1.46; 2.02), and fewer contacts for physical exercise and patient education (P < 0.001 and P = 0.011). Conclusion We identified differences between non-Western migrants and Danish-born in initiation and discontinuation of preventive medications and use of non-pharmacological interventions after ACS. These differences could not be explained by differences in comorbidity or sociodemographic factors. View largeDownload slide View largeDownload slide Secondary prevention, Migrants, Acute coronary syndrome, Equity of care, Register studies Introduction Migrants in Europe are expected to form a larger share of patients with acute coronary syndrome (ACS) due to the recent increase in the influx of refugees from conflict-affected areas and the ageing of those who entered Europe during earlier waves of immigration. To ensure equity of care, health care systems must adapt to these demographic changes. This challenge is evident when it comes to equal access to acute treatment but may in fact be even larger when it comes to secondary prevention. The clinical and public health importance of secondary prevention is supported by scientific evidence demonstrating that medications and other secondary prevention interventions reduce mortality and readmissions and may improve quality of life.1–3 Preventive medications after ACS includes treatment with aspirin, statins, adenosine diphosphate receptor inhibitors (ADP-inhibitors) and β-blockers, as well as angiotensin-converting enzyme inhibitors (ACE-inhibitors) in selected patients.2,3 Non-pharmacological preventive interventions include physical exercise, dietary counselling and patient education on medications, life-style, smoking cessation, and psychosocial management.1–3 Despite strong evidence for their benefits, low use of preventive interventions have been found in general populations after coronary heart disease (CHD), associated with comorbidity and the sociodemographic factors of advanced age, distance from providers and living alone.4–7 In the case of migrants, several barriers to health care in general have been documented.8 European research on migrants’ use of preventive interventions following CHD is based on small populations or shows contradictory findings.7,9–12 A large study by Sumner et al. (n = 98 880) assessed ethnic minority status as one of the several potential predictors for use of non-pharmacological interventions. However, the results were prone to selection bias because only subjects who had participated in an assessment session were included, and the study did not include medications.7 Hence, the objectives of this study are to test the hypothesis that migrants to Denmark, compared to Danish-born patients, show lower use of preventive medications, physical exercise, dietary advice, and patient education post-ACS. Material and methods This study followed the STROBE guidelines: Strengthening the Reporting of Observational Studies in Epidemiology.13 Setting Denmark has a background population of about 5.5 million people. The health care system is tax-funded with free access to health care services, and part-coverage of the costs of prescribed medicines for all subjects with a Danish citizenship or long-term residency permit. Study design and patient population We conducted a nationwide, population-based follow-up study using anonymized data from the Danish National Patient Register (NPR), including relevant patients from 1 January 2010 to 31 December 2013 (Figure 1). Danish National Patient Register contains information on discharge diagnoses, hospital, hospital-based activities such as physiotherapy, and day of discharge for in- and outpatients.14 International Classification of Diseases 10th revision (ICD-10) has been used for diagnose-classification since 1994. Data on death and age were retrieved from the Central Person Register (CPR), containing basic data on legal Danish residents, including date and place of birth, address, and death. We included subjects hospitalized on an acute basis according to the criteria: (i) ≥18 years of age with a CPR-number; (ii) discharged alive between 1 January 2010 and 31 December 2013 from a department of cardiology; and (iii) suffering acute coronary syndrome (ACS), with diagnoses of acute myocardial infarction (AMI) and unstable angina pectoris (UAP) (ICD10: DI21, DI248, DI249, DI240, DI200). Patients were excluded if they had been given an ischaemic heart disease diagnosis within the previous 12 months. Only the first admission was included for patients with multiple admissions during the study period. Figure 1 View largeDownload slide Flowchart of inclusion in the population based on data from the Danish National Patient Register, the Central Person Register, and Statistics Denmark. Figure 1 View largeDownload slide Flowchart of inclusion in the population based on data from the Danish National Patient Register, the Central Person Register, and Statistics Denmark. Data collection and definitions Migrant status The study population was linked to registers at Statistics Denmark containing information on country of origin and socio-demography. Subjects were classified as Danish-born (n = 30 686), Western (n = 882), or non-Western migrants (n = 1631) according to Statistics Denmark’s categorizations. Descendants of migrants were excluded. We divided non-Western migrants into subgroups at the country level and compared Danish-born with the three largest such subgroups, namely Turks (n = 363), nationals from the former republic of Yugoslavia (n = 291), and Pakistanis (n = 193). Nationals from the former republic of Yugoslavia were merged into one group. Outcomes Outcomes were (i) initiation of medications, (ii) initiation of non-pharmacological interventions, (iii) time to discontinuation of medications, and (iv) number of contacts for non-pharmacological interventions. Medications included statins (C10A), ADP-inhibitors (B01AC04, B01AC22, and B01AC24), β-blockers (C07), and ACE-inhibitors (C09). Initiation of medications was defined as subjects having claimed reimbursement of at least one prescription within the 180 days observational period. Discontinuation of medications was defined as failing to claim reimbursement of a new prescription for relevant medication within 90 days after estimated date of expiry of a reimbursed prescription. Data on reimbursed prescriptions included the years 2010–2014 and were retrieved from the Register of Medicinal Products Statistics.15 Aspirin can be bought over the counter and was not included. Initiation of physical exercise, dietary advice, and patient education was defined as having at least one contact per type of intervention. Lastly, the number of contacts for each type of non-pharmacological intervention was determined. Data on non-pharmacological interventions were retrieved from NPR, following the definitions used in the Danish Cardiac Rehabilitation Database (DHRD).16 Follow-up period for non-pharmacological interventions was 180 days from the date of discharge. Covariates and confounding variables Central Person Register provided data on age and sex, Statistics Denmark on family income, education, employment and cohabiting status, and NPR on comorbidity and whether non-pharmacological interventions were delivered by university-affiliated hospitals. We used the Charlson Comorbidity Index (CCI) as a comorbidity measure.17 Congestive heart failure (CHF) and types I and II diabetes were expected to influence the outcomes independently, and were therefore excluded from CCI, and adjusted for separately. Statistical analysis We carried out binomial regression analyses to evaluate relative risks (RRs) for initiating medication and non-pharmacological interventions. Time to medication discontinuation was compared among patients who initiated medication, using Cox proportional hazards regression analyses and presented as hazard ratios (HRs). Follow-up started at the time of reimbursement of the first prescription. Subjects were censored at the time of death or emigration if these events occurred during the follow-up period. The assumptions of proportional hazards in the data set were assessed visually and found to be appropriate. In addition, a Fine and Gray model was used to construct cumulative incidence curves of medication discontinuation. Death or emigration was considered as competing risks when computing the cumulative incidence. Patients not initiating medication therapy during the first 6 months were included as discontinued at baseline. Gray’s test was used to compare curves. In order to assess differences in number of contacts for non-pharmacological interventions, we applied the Wilcoxon–Mann–Whitney two-sample rank-sum test. The choice of test depended on data being ordinal and not meeting the assumptions of parametric tests. The sum of contacts for each non-pharmacological intervention was compared between Danish-born and Western and non-Western migrants respectively, including the subgroups of Turks, former Yugoslavs, and Pakistanis. Relative risks and HRs were presented as crude and adjusted by multivariable analyses, with inclusion of all covariates as potential confounders. Statistical analyses were performed with SAS 9.4 statistical software (SAS Institute Inc., Cary, NC, USA). Results A flowchart of the population selection is provided in Figure 1. Population characteristics The study population included 33 199 subjects, out of which 14 emigrated and 3058 died during the 180 days of follow-up. Danish-born had the highest mortality during follow-up, which was expected due to higher age. The unadjusted descriptive data showed that, compared to Danish-born, non-Western migrants were younger and more likely to be men, have a lower family income and be in receipt of welfare support other than retirement support (Table 1). Furthermore, they had less comorbidity, although types I and II diabetes were more frequent. Western migrants deviated little from Danish-born. Characteristics of the subgroups is available in Supplementary material online. Subgroups were similar to the non-Western migrants, except Pakistanis had higher prevalence of CHF (n = 34, 17.6%), diabetes (n = 69, 35.8%), and UAP (n = 58, 30.1%), lower incidence of AMI (n = 130, 67.4%), and were more often discharged from university-affiliated hospitals (n = 85, 95.9%). Former Yugoslavs had higher prevalence of AF (n = 31, 10.7%). Table 1 Characteristics of the study population showing Danish-born compared to migrants Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Values are numbers (percentages) unless otherwise stated. NSTEMI, Non-S-T-segment elevation myocardial infarction; STEMI, S-T-segment elevation myocardial infarction. a Cut-offs: International Standard Classification of Education. b Tertiles. c During index admission. d Excluding CHF and types I and II diabetes. Table 1 Characteristics of the study population showing Danish-born compared to migrants Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Danish Western Non-Western Total n 30686 (92.4) 882 (2.7) 1631 (4.9) 33199 (100) Female 11043 (36.0) 330 (37.4) 389 (23.9) 11762 (35.4) Age  18–64 11670 (38.0) 373 (42.3) 1133 (69.5) 13176 (39.7)  65–74 8130 (26.5) 260 (29.5) 311 (19.1) 8701 (26.2)  ≤75 10886 (35.5) 249 (28.2) 187 (11.5) 11322 (34.1) Tertiary educationa  None 13492 (44.0) 237 (26.9) 738 (45.2) 14467 (43.6)  Short 12015 (39.2) 331 (37.5) 461 (28.3) 12807 (38.6)  Medium 2710 (8.8) 116 (13.2) 106 (6.5) 2932 (8.8)  Long 995 (3.2) 68 (7.7) 71 (4.4) 1134 (3.4)  Missing 1474 (4.8) 130 (14.7) 255 (15.6) 1859 (5.6) Family incomeb  Low 9827 (32.0) 295 (33.4) 972 (59.6) 11094 (33.4)  Medium 9951 (32.4) 263 (29.8) 407 (25.0) 10621 (32.0)  High 9800 (31.9) 278 (31.5) 196 (12.0) 10274 (30.9) Employed 8787 (28.6) 284 (32.2) 450 (27.6) 9521 (28.7)  Retired 20 694 (67.4) 532 (60.3) 854 (52.4) 22080 (66.5)  Other welfare support 867 (2.8) 33 (3.7) 271 (16.6) 1171 (3.5)  Other 338 (1.1) 33 (3.7) 56 (3.4) 427 (1.3) Cohabiting 18 635 (60.7) 502 (56.9) 1104 (67.7) 20241 (61.0) Percutaneous cardiac interventionc 15 618 (50.9) 508 (57.6) 942 (57.8) 17 068 (51.4) Coronary artery bypass graftingc 2745 (8.9) 66 (7.5) 198 (12.1) 3009 (9.1) Acute myocardial infarction 25551 (83.3) 729 (82.7) 1203 (73.8) 27483 (82.8)  STEMI 6596 (21.5) 216 (24.5) 387 (23.7) 7199 (21.7)  NSTEMI 11 771 (38.4) 334 (37.9) 493 (30.2) 12 598 (37.9)  Unspecified 7184 (23.4) 179 (20.3) 323 (19.8) 7686 (23.2) Unstable angina pectoris 4729 (15.4) 141 (16.0) 399 (24.4) 5269 (15.9) Congestive heart failure 3324 (10.8) 91 (10.3) 150 (9.2) 3565 (10.7) Atrial fibrillation 4326 (14.1) 119 (13.5) 95 (5.8) 4540 (13.7) Diabetes, types I and II 3649 (11.9) 89 (10.1) 388 (23.8) 4126 (12.4) Charlson comorbidity indexd  Low (0 points) 16 039 (52.3) 508 (57.6) 988 (60.6) 17 535 (52.8)  Moderate (1–2 points) 10 593 (34.5) 280 (31.7) 515 (31.6) 11 388 (34.3)  High (>3 points) 4054 (13.2) 94 (10.7) 128 (7.8) 4276 (12.9) Discharged from university hospital 14 878 (48.5) 516 (58.5) 1189 (72.9) 16 583 (50.0) Values are numbers (percentages) unless otherwise stated. NSTEMI, Non-S-T-segment elevation myocardial infarction; STEMI, S-T-segment elevation myocardial infarction. a Cut-offs: International Standard Classification of Education. b Tertiles. c During index admission. d Excluding CHF and types I and II diabetes. Initiation of medications and non-pharmacological interventions Compared to Danes, non-Western migrants had lower RRs for initiating ADP- and ACE-inhibitors (0.93, CI: 0.90; 0.96 and 0.91, CI: 0.87; 0.96). Sensitivity analyses only including subjects who had not died or emigrated during follow-up resulted in RRs that were virtually unchanged. For non-pharmacological interventions, median follow-up ranged from 166 days among Danish-born to 170 among the Pakistani subgroup. For initiation of non-pharmacological interventions, non-Western migrants showed lower RRs for patient education (0.95, CI: 0.92; 0.98). Western migrants did not deviate significantly from Danish-born. The proportions of Danish-born, Western, and non-Western migrants, which initiated neither medications nor non-pharmacological interventions, were 3.7%, 4.0%, and 4.4%. Furthermore, proportions of subjects who initiated all medications and non-pharmacological interventions were 9.4%, 11.0%, and 9.4%. Subgroups of non-Western migrants Subgroups were also compared to Danish-born (Table 2). Lower initiation was found for ADP-inhibitors among Turks (0.92, CI: 0.87; 0.98) and Pakistanis (0.83, CI: 0.75; 0.92) and for ACE-inhibitors among Turks (0.81, CI: 0.72; 0.91). Lower initiation rates were found for physical exercise, dietary advice, and patient education among Turks (0.83, CI: 0.73; 0.94, 0.80, CI: 0.68; 0.95, and 0.90, CI: 0.84; 0.97). Table 2 Initiation of medications and non-pharmacological interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university hospital. Table 2 Initiation of medications and non-pharmacological interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 25 255 (82.3) 731 (82.9) 1421 (87.1) 321 (88.4) 257 (88.3) 170 (88.1) RR (Crude) 1.00 1.01 (0.98; 1.04) 1.06 (1.04; 1.08) 1.07 (1.03; 1.12) 1.07 (1.03; 1.12) 1.07 (1.02; 1.13) RR (Adjusteda) 1.00 1.00 (0.98; 1.02) 0.99 (0.98; 1.01) 0.99 (0.96; 1.02) 1.02 (0.99; 1.05) 0.99 (0.95; 1.03) ADP-inhibitors n (%) 22 824 (74.4) 679 (77.0) 1187 (72.8) 265 (73.0) 221 (75.9) 127 (65.8) RR (Crude) 1.00 1.04 (1.00; 1.07) 0.98 (0.95; 1.01) 0.98 (0.92; 1.05) 1.02 (0.96; 1.09) 0.88 (0.80; 0.98) RR (Adjusteda) 1.00 1.03 (0.99; 1.06) 0.93 (0.90; 0.96) 0.92 (0.87; 0.98) 0.98 (0.92; 1.05) 0.83 (0.75; 0.92) β-blockers n (%) 23 832 (77.7) 689 (78.1) 1289 (79.0) 293 (80.7) 235 (80.8) 153 (79.3) RR (Crude) 1.00 1.01 (0.97; 1.04) 1.02 (0.99; 1.04) 1.04 (0.99; 1.09) 1.04 (0.98; 1.10) 1.02 (0.95; 1.10) RR (Adjusteda) 1.00 1.00 (0.97; 1.04) 0.99 (0.96; 1.01) 0.99 (0.95; 1.05) 1.03 (0.97; 1.08) 0.98 (0.91; 1.05) ACE-inhibitors n (%) 16 752 (54.6) 469 (53.2) 820 (50.3) 163 (44.9) 160 (55.0) 107 (55.4) RR (Crude) 1.00 0.97 (0.91; 1.04) 0.92 (0.88; 0.97) 0.82 (0.73; 0.92) 1.01 (0.91; 1.12) 1.02 (0.89; 1.15) RR (Adjusteda) 1.00 1.01 (0.95; 1.07) 0.91 (0.87; 0.96) 0.81 (0.72; 0.91) 1.02 (0.89; 1.15) 0.94 (0.84; 1.07) Non-pharmacological prevention Physical exercise, ≥1 contact n (%) 14 117 (46.0) 410 (46.5) 736 (45.1) 145 (39.9) 143 (49.1) 88 (45.6) RR (Crude) 1.00 1.01 (0.94; 1.09) 0.98 (0.93; 1.04) 0.87 (0.76; 0.99) 1.07 (0.95; 1.20) 0.99 (0.85; 1.16) RR (Adjusteda) 1.00 1.01 (0.94; 1.09) 0.95 (0.90; 1.01) 0.83 (0.73; 0.94) 1.06 (0.95; 1.19) 0.95 (0.81; 1.10) Dietary advice, ≥1 contact n (%) 9301 (30.3) 293 (33.2) 511 (31.3) 99 (27.3) 100 (34.4) 68 (35.2) RR (Crude) 1.00 1.10 (1.00; 1.21) 1.03 (0.96; 1.11) 0.90 (0.76; 1.07) 1.13 (0.97; 1.33) 1.05 (0.81; 1.37) RR (Adjusteda) 1.00 1.06 (0.97; 1.16) 0.96 (0.89; 1.03) 0.80 (0.68; 0.95) 1.16 (0.96; 1.41) 1.03 (0.76; 1.41) Patient education, ≥1 contact n (%) 21 807 (71.1) 608 (68.9) 1137 (69.7) 242 (66.7) 192 (66.0) 147 (76.2) RR (Crude) 1.00 0.97 (0.93; 1.01) 0.98 (0.95; 1.01) 0.94 (0.87; 1.01) 0.93 (0.85; 1.01) 1.07 (0.99; 1.16) RR (Adjusteda) 1.00 0.98 (0.94; 1.03) 0.95 (0.92; 0.98) 0.90 (0.84; 0.97) 0.92 (0.85; 1.00) 1.01 (0.94; 1.09) Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university hospital. Discontinuation of medications Median follow-up for statins ranged from 814 days among Danish-born to 749 days among non-Western migrants. For β-blockers, the range was 540 days for Danish-born to 395 among Turks. Adenosine diphosphate receptor- and ACE-inhibitors had median follow-up equivalent to those seen for statins. The combined effect of lack of medication initiation and discontinuation of medication during follow-up for the entire study population is shown in cumulative incidence curves in Take home figure, including P-values for Gray’s test for equality. When focusing on the patients, who did initiate medication therapy, non-Western migrants had a higher adjusted HR of discontinuation of all medication groups (statins: 1.64, CI: 1.45; 1.86, ADP-inhibitors: 1.72, CI: 1.50; 1.97, β-blockers: 1.52, CI: 1.40; 1.64, and ACE-inhibitors: 1.72, CI: 1.46; 2.02) compared to Danes (Table 3). Among Western migrants, the risk of discontinuation was only elevated for ACE-inhibitors (1.38, CI: 1.11; 1.72). Table 3 Risks of discontinuation of medications and differences in number of contacts for non-pharmacological preventive interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university-affiliated hospital. Table 3 Risks of discontinuation of medications and differences in number of contacts for non-pharmacological preventive interventions among Danish-born compared to migrants, including subgroups Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Danish (ref) Western Non-Western Turks Former Yugoslavs Pakistanis Preventive medications Statins n (%) 3531 (14.0) 114 (15.6) 322 (22.7) 74 (23.1) 55 (21.4) 43 (25.3) HR (Crude) 1.00 1.14 (0.95; 1.37) 1.77 (1.58; 1.98) 1.75 (1.40; 2.20) 1.62 (1.24; 2.11) 1.98 (1.46; 2.68) HR (Adjusteda) 1.00 1.12 (0.93; 1.35) 1.64 (1.45; 1.86) 1.62 (1.27; 2.06) 1.47 (1.12; 1.93) 1.81 (1.33; 2.48) ADP-inhibitors n (%) 2576 (11.3) 72 (10.6) 264 (22.2) 61 (23.0) 49 (22.2) 35 (27.6) HR (Crude) 1.00 0.95 (0.75; 1.20) 2.11 (1.86; 2.39) 2.20 (1.71; 2.83) 2.08 (1.57; 2.76) 2.68 (1.93; 3.74) HR (Adjusteda) 1.00 0.95 (0.75; 1.21) 1.72 (1.50; 1.97) 1.77 (1.36; 2.31) 1.79 (1.35; 2.38) 2.04 (1.44; 2.89) β-blockers n (%) 9245 (38.8) 289 (41.9) 704 (54.6) 173 (59.0) 117 (49.8) 90 (58.8) HR (Crude) 1.00 1.13 (1.00; 1.27) 1.60 (1.49; 1.73) 1.81 (1.56; 2.09) 1.35 (1.13; 1.60) 1.84 (1.49; 2.27) HR (Adjusteda) 15 223 (38.4) 1.11 (0.99; 1.25) 1.52 (1.40; 1.64) 1.69 (1.45; 1.97) 1.28 (1.07; 1.53) 1.81 (1.46; 2.24) ACE-inhibitors n (%) 2238 (13.4) 84 (17.9) 188 (22.9) 38 (23.3) 38 (23.8) 37 (34.6) HR (Crude) 1.00 1.40 (1.12; 1.74) 1.85 (1.60; 2.15) 1.81 (1.32; 2.49) 1.91 (1.39; 2.63) 2.97 (2.12; 4.17) HR (Adjusteda) 1.00 1.38 (1.11; 1.72) 1.72 (1.46; 2.02) 1.71 (1.23; 2.38) 1.84 (1.33; 2.54) 2.70 (1.89; 3.85) Non-pharmacological prevention Physical exercise, number of contacts Median (quartiles) 9 (3, 15) 10 (3, 14) 7 (2, 13) 8 (2, 13) 5 (2, 13) 4 (2, 11.5) Two-sided Pr > |Z| 1.00 0.935 <0.001 0.051 <0.001 <0.001 Dietary advice, number of contacts Median (quartiles) 1 (1, 2) 1 (1, 2) 1 (1, 2) 1 (1, 2) 2 (1, 3) 1.5 (1, 2) Two-sided Pr > |Z| 1.00 0.438 0.100 0.962 0.006 0.237 Patient education, number of contacts Median (quartiles) 4 (2, 9) 4 (2, 8) 4 (2, 8) 3 (2, 8) 4 (2, 8) 3 (2, 7) Two-sided Pr > |Z| 1.00 0.036 0.011 0.029 0.783 0.040 Bold values indicate 95% confidence intervals not overlapping the null value. a Adjusted for sex, age, congestive heart failure, type I and II diabetes, comorbidity (excluding congestive heart failure and type I and II diabetes), education, cohabitation, occupation, income, and university-affiliated hospital. Take home figure View largeDownload slide Combined lack of medication initiation and discontinuation of initiated medication. Time zero is the date of the first reimbursement of a prescription. Coloured spectrums indicate confidence intervals. Gray’s test for equality of cumulative incidence functions: statins: P = 0.013; ADP-inhibitors, β-blockers, and ACE-inhibitors: P < 0.001. Take home figure View largeDownload slide Combined lack of medication initiation and discontinuation of initiated medication. Time zero is the date of the first reimbursement of a prescription. Coloured spectrums indicate confidence intervals. Gray’s test for equality of cumulative incidence functions: statins: P = 0.013; ADP-inhibitors, β-blockers, and ACE-inhibitors: P < 0.001. Contacts for non-pharmacological interventions For physical exercise, non-Western migrants had significantly fewer contacts when compared to Danish-born (median 7 vs. 9, P < 0.001) (Table 3). Western and non-Western migrants had statistically significant fewer contacts for patient education when compared to Danish-born, although the median number of contacts were similar (median 4 vs. 4, P = 0.036 and median 4 vs. 4, P = 0.011). Subgroups of non-Western migrants The risks of discontinuing medications were also elevated in all subgroups, the highest being observed amongst Pakistanis (2.70, CI: 1.89; 3.85) (Table 3). Compared to Danish-born, former Yugoslavs and Pakistanis had fewer contacts for physical exercise (median 9 vs. 5, P < 0.001 and median 9 vs. 4, P < 0.001).Turks showed a probability of fewer contacts for physical exercise close to the significant cut-off point of 0.05 (median 9 vs. 8, P = 0.051). Former Yugoslavs had fewer contacts for dietary advice (median 1 vs. 2, P = 0.006), and fewer contacts for patient education were observed among Turks (median 4 vs. 3, P = 0.029) and Pakistanis (median 4 vs. 3, P = 0.040). Discussion In this large nationwide cohort study (n = 33 199), we compared post-ACS use of secondary prevention among non-Western and Western migrants and Danish-born. Non-Western migrants had lower initiation of ADP- and ACE-inhibitors and a higher risk of discontinuation of all medications included in the study. For non-pharmacological interventions, lower initiation of patient education and fewer contacts for physical exercise and patient education were found in non-Western migrants. Adjustment for comorbidity and sociodemographic factors did not explain the observed differences. Medication persistence Previous studies have compared migrants’ and local-born CHD patients’ use of preventive medications, but results are conflicting, applied analyses are weak, or studies have been underpowered. Conflicting results of two Swedish studies may be explained by period, population size, and whether previous drug use was included in the analysis.10,11 A Canadian study found higher discontinuation rates from treatment with ACE-inhibitors, but included only South Asian and Chinese ethnic groups above the age of 66, and assessed discontinuation on dichotomized outcomes, instead of Cox regression analysis, which allows for a more detailed analysis.18 A smaller Danish study found discontinuation risks equivalent to ours, albeit the study was probably underpowered with fewer significant differences.12 Hence, our study adds new insights relating to population size, statistical analysis, role of confounding variables, and the assessment of both use of medications and non-pharmacological interventions. Use of non-pharmacological interventions There are very few European studies of the use of non-pharmacological interventions that focus on migrants or ethnic minority patients. One study found that ethnic minority status was not an independent predictor for uptake, but the study was prone to selection bias,7 and, in a UK survey on uptake, data quality on ethnic minorities was too poor to be representative.9 North American studies show lower use among ethnic minorities, but transferability to a European context is low.18,19 Hence, our documentation of lower use of non-pharmacological interventions among non-Western migrants in a European welfare state provides new and important findings. However, while the documented differences meet statistical significance, the difference of, at most, two contacts for physical exercise, and one for dietary advice and patient education, do not necessarily imply clinically important differences. The findings therefore add new knowledge related to inequities in access, but the clinical implications of this are yet to be fully clarified. Western and non-Western migrants and subgroups The observed differences call for cautious interpretation. First, the origin of migrant populations and health care utilization patterns may differ across the European countries. Secondly, the heterogeneous non-Western and Western migrant groups may not be representative of specific subgroups, as was particularly the case for former Yugoslavs, and which has been discussed in a previous article.20 A complex of pre-migration, migration and post-migration circumstances affecting health care needs, language skills, and other factors associated with acculturation may explain these findings.21 The lower use of secondary prevention among non-Western migrants is worrying and may be associated with higher mortality and rehospitalization rates and a lower health-related quality of life.1–3 However, there is a lack of studies which assess mortality, rehospitalization, or quality of life in comparable migrant populations. Comorbidity and sociodemographic factors We found limited confounding by comorbidity and sociodemographic factors. This may be due to the setting, with free access to health services and partial reimbursement of medication costs. However, the largest between-group differences were found in medication persistence, and similarly, a previous Danish study found that under-use of health care among non-Western migrants was only present for services where user-payment was demanded, despite adjustment for sociodemographic factors.22 Therefore, it is possible that differences between migrants and native born in uptake of secondary prevention may be even larger in countries with higher user-payment of health care services, regardless of the socioeconomic position of the migrant population. Differences may also be explained by barriers at the system and provider levels, where, for example, professionals’ knowledge and attitudes may affect their ability to meet the needs of people of different ethnic backgrounds.8 We therefore need studies of the role of health care providers and health care systems, in secondary prevention of CHD. Furthermore, studies of migrants’ perceptions of secondary prevention may contribute to a better understanding of our findings. Studies from the UK and Canada have found individually perceived barriers related to previous negative experiences communication difficulties, and cultural acceptability.21 However, with dissimilar migrant populations and health care systems, these studies may not be fully applicable to the context of a Nordic welfare state. Strengths and limitations of the study Nationwide registers enabled us to focus on a large population, to include data on medications and non-pharmacological interventions, to assess initiation, discontinuation, and number of health care contacts, and to include all eligible subjects, including the elderly and those with low native-language proficiency, who are frequently under-represented in research.9,23 However, we did not have information about contraindications to secondary prevention measures, including terminal illness and patient preferences. Other potential weaknesses include the fact that administrative registers are not created for research purposes and can be incomplete or biased. We used NPR data to establish our population, where the predictive value of the ACS diagnosis has been found to be valid,24 and also to provide information on use of non-pharmacological interventions. Danish National Patient Register is used for hospitals’ financial reimbursements, which might encourage a practice of less thorough registrations of services with lower reimbursements. However, as biased registration is unlikely to be associated with patients' migration backgrounds, our comparative design eliminates this risk, and a previous study validate our findings.12 Furthermore, results are in accordance with quality standards of the DHRD,16 where initiation of statin treatment in 80% of all patients is considered acceptable. Finally, one shortcoming is that we were unable to make causal inferences to explain the noted differences. It is noteworthy that non-Western migrants’ lower use of patient education was found in conjunction with lower medication persistence and that clinical guidelines recommend patient education to increase medication persistence in CHD.1 However, a recent meta-analysis only finds effects of patient education on quality of life and health care costs, and results may be affected by type II errors. Thus, there is a call for more research on patient education, particularly among under-represented ethnic minority groups.23 Finally, non-Western migrants comprise a smaller part of European populations, and efforts to increase their use of preventive measures may only have minor effects at national population levels. However, measures that improve use of secondary prevention in the entire post-ACS population may be of benefit to all, given that the interventions are widely accessible and sensitive to diverse needs. Conclusion After adjustment for comorbidity and socio-demography, we found substantial differences between Danish-born and non-Western migrants in medication persistence, which are likely to be of clinical importance. Differences in use of non-pharmacological interventions were less substantial, and possibly of less clinical importance, but reflect general inequities in migrants’ access to health services. There is thus a need for actions to improve migrants’ access to both medications and non-pharmacological interventions post-ACS. Supplementary material Supplementary material is available at European Heart Journal online. Funding Capital Region of Denmark and the Danish Heart Association (14-R97-A5261-22875). Conflict of interest: S.P.J. has received fees from Bristol-Myers Squibb, grants and personal fees from Pfizer, personal fees from Bayer, personal fees from Boehringer-Ingelheim, outside the submitted work. 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This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

European Heart JournalOxford University Press

Published: Apr 30, 2018

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