Background— Although preventive drug therapy is a priority after acute coronary syndrome, less is known about adherence to behavioral recommendations. The aim of this study was to examine the influence of adherence to behavioral recommendations in the short term on risk of cardiovascular events.
Methods and Results— The study population included 18 809 patients from 41 countries enrolled in the Organization to Assess Strategies in Acute Ischemic Syndromes (OASIS) 5 randomized clinical trial. At the 30-day follow-up, patients reported adherence to diet, physical activity, and smoking cessation. Cardiovascular events (myocardial infarction, stroke, cardiovascular death) and all-cause mortality were documented to 6 months. About one third of smokers persisted in smoking. Adherence to neither diet nor exercise recommendations was reported by 28.5%, adherence to either diet or exercise by 41.6%, and adherence to both by 29.9%. In contrast, 96.1% of subjects reported antiplatelet use, 78.9% reported statin use, and 72.4% reported angiotensin-converting enzyme/angiotensin receptor blocker use. Quitting smoking was associated with a decreased risk of myocardial infarction compared with persistent smoking (odds ratio, 0.57; 95% confidence interval, 0.36 to 0.89). Diet and exercise adherence was associated with a decreased risk of myocardial infarction compared with nonadherence (odds ratio, 0.52; 95% confidence interval, 0.4 to 0.69). Patients who reported persistent smoking and nonadherence to diet and exercise had a 3.8-fold (95% confidence interval, 2.5 to 5.9) increased risk of myocardial infarction/stroke/death compared with never smokers who modified diet and exercise.
Conclusions— Adherence to behavioral advice (diet, exercise, and smoking cessation) after acute coronary syndrome was associated with a substantially lower risk of recurrent cardiovascular events. These findings suggest that behavioral modification should be given priority similar to other preventive medications immediately after acute coronary syndrome.
Smoking, poor diet, and lack of exercise are important risk factors for coronary heart disease.1 Population studies attribute a substantial proportion of the decline in cardiovascular diseases seen in some high-income countries (HICs) in recent decades to falling rates of smoking secondary to aggressive policy interventions and improved diets as a consequence of specific food policies, improved trade, and increased availability of fruit and vegetables.2–6 Smoking cessation is effective in the secondary prevention of coronary heart disease. A recent systematic review found that smoking cessation in persons with known coronary heart disease was associated with an ≈30% lower crude risk rate of death and myocardial infarction (MI) during the subsequent 3 to 7 years.7 However, many of these studies enrolled persons with established coronary heart disease (not presenting with acute events), had limited information on confounding factors (such as risk factors or secondary preventive treatments), and did not examine whether benefits occurred early after an acute event. Some small studies have indicated that benefits may occur as early as 1 year after acute coronary syndrome (ACS) presentation, but they have not been large enough to evaluate whether such benefits persist after controlling for risk factors or the use of proven pharmacological or interventional therapies.8,9 Certain dietary recommendations (eg, Mediterranean diet) and exercise have also been shown to be effective in the secondary prevention of coronary heart disease.10,11 Cardiac rehabilitation programs that target health behaviors and adherence to drugs have also been associated with better outcomes.12 Some of these benefits may occur early, but this is unclear.13
The main aim of these analyses was to examine the influence of adherence to behavioral recommendations on risk for short-term (<6 months after the index event) cardiovascular outcomes and whether there is incremental benefit in modifying multiple lifestyle behaviors after controlling for the use of pharmacological secondary prevention measures.
Methods
The Organization to Assess Strategies in Acute Ischemic Syndromes (OASIS) 5 was a randomized, double-blind, double-dummy trial in which fondaparinux was compared with enoxaparin in patients with unstable angina or MI without ST-segment elevation.14 In total, 20 078 patients from 576 centers in 41 countries were recruited between April 9, 2003 and May 30, 2005; 11 558 came from HICs and 8520 came from low- and middle-income countries (LMICs) (http://web-worldbank.org). Patients were eligible if they met at least 2 of the 3 criteria: age of at least 60 years, an elevated level of troponin or creatine kinase-MB isoenzyme, or ECG changes indicative of ischemia. Patients with contraindications to low-molecular-weight heparin, recent hemorrhagic stroke, indications for anticoagulation other than an ACS, or a serum creatinine level of at least 3 mg/dL (265 μmol/L) were excluded. Further details are reported elsewhere.15
At baseline, data on demographics, risk factors, and comorbidities were collected. At follow-up visits at 30, 90, and 180 days, the following simple questions on behavioral modification were included: Smoking was assessed with the question, “Is the patient currently smoking?” Answer options were ‘”yes” and “no.” Currently smoking was defined as smoking at least 1 cigarette (or cigar or pipe) per day within the last month. Those who used only chewing tobacco were recorded as never smokers. Exercise was assessed with the question, “Is the patient exercising regularly (>30 minutes 3 times a week)?” Answer options were “yes” and “no.” Exercise was noted to include walking uninterrupted or as part of an exercise program. Details on type of exercise or exercise intensity were not recorded. Diet was assessed with the question, “Has patient received counseling for dietary modification?” Answer options were “yes” and “no.” If the response was affirmative, then the follow-up question was, “Is the patient compliant?” Answer options were “yes” and “no.” Diet counseling was described as formal counseling individually, in a group with a dietitian or professional nutritionist, or at a secondary rehabilitation clinic. Details on the nature of the dietary advice or intensity of the program attended were not recorded.
Use of drugs and treatments of percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) were recorded at baseline, discharge, and 30, 90, and 180 days. Patients were followed up for 180 days, and the outcomes of MI, death, and stroke were systematically recorded. All of the events were adjudicated by a central committee according to standardized operational definitions. In brief, stroke was defined as the presence of a new focal neurological deficit thought to be vascular in origin with signs or symptoms lasting >24 hours. MI was defined as either pathological findings or a typical rise in enzymes with at least 1 of the following: ischemic symptoms, new Q waves, ECG changes indicative of ischemia (ST elevation or depression), or coronary artery intervention. For patients with prior MI, PCI, or CABG, a modified MI definition was used as detailed previously.15
Analysis
Patients included in this analysis were those who survived ≥30 days and reported information on lifestyle behaviors at the 30-day follow-up visit. Smoking status was classified according to self-report into 4 categories: never smokers, former smokers (ex-smokers who quit before entry into the OASIS 5 study), recent quitters (those that reported not smoking at the 30-day follow-up visit but who were current smokers at study entry), or persistent smokers (those who were smokers at study entry and reported smoking at the 30-day follow-up).
Diet/exercise program adherers were classified into 3 categories: no diet/exercise (those who responded “no” to regular exercise and diet questions at the 30-day follow-up, either diet or exercise (those who responded “yes” to exercise or diet questions), or both diet and exercise (those who responded “yes” to all exercise and diet questions). Unadjusted subject characteristics are reported by these groups.
The associations between smoking status and outcomes and diet/exercise and outcomes were examined in separate age- and sex-adjusted logistic regression models and in multivariable logistic regression models. For multivariable analysis, a forward variable selection procedure was used. The final model included factors that increased the area under the curve of the model and decreased the Akaike information criteria of the model or were known strong predictors of outcomes. The final model included baseline risk factors of age, sex, region of origin, history of hypertension, history of diabetes, body mass index, creatinine, and history of prior MI; PCI/CABG interventions before 30 days; and reported use of secondary preventive medications at 30 days, including β-blockers, statins, antiplatelets, and angiotensin-converting enzyme/angiotensin receptor blocker (ACE/ARB) use. Total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides were not included in final models because they were available in only about half of the subjects. Occupation also was not included because the majority of participants (77%) were retired and prior occupation information for this group was not collected.
In sensitivity analyses, adjustment for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, unemployment, occupation, history of cancer, heart failure, and peak creatine kinase resulted in minor changes to the adjusted odds ratio (OR) for each outcome. Among these parameters, the greatest increase in area under the curve for the total model occurred with addition of low-density lipoprotein cholesterol. For example, the area under the curve of the final model predicting MI including all risk factors increased by 3% from 0.726 to 0.748 with the addition of low-density lipoprotein cholesterol. All of the analyses were performed with the statistical software Stata/SE 10 (StataCorp LP, College Station, Tex) and repeated with SAS version 9.1 for Unix (SAS Institute Inc, Cary, NC).
Results
Patient Characteristics, Medications, and Lifestyles
Of the 20 078 persons enrolled in the OASIS study, 18 809 persons were alive and reported on behaviors at the 30-day follow-up visit. The average age of this group was 66.8 years (range, 21.4 to 97.8 years); 38.2% were women; 54.6% had MI without ST elevation and 45.4% had unstable angina at study entry; and 37.5% had PCI and 9.9% had CABG before discharge or within 30 days of the event. Adherence to secondary preventive drugs at the 30-day and 6-month follow-up was generally better (Table 1) than adherence to behavioral modification (Figure 1&2).
Table 1. Adherence to Secondary Preventive Medications at 30-Day and 6-Month Follow-Up
Medication
At Discharge, n (%)
At 30 Days, n (%)
At 6 Months, n (%)
Percentage adherence compared with previous visit.
Antiplatelet
18 145 (96.5)
18 069 (96.1)
17 106 (94.7)
Statin
14 820 (78.8)
14 792 (78.0)
13 389 (90.5)
ACE/ARB
13 705 (72.9)
13 643 (72.5)
12 251 (89.8)
β-blocker
15 506 (82.4)
9100 (48.4)
7110 (78.1)
Figure 1. Quitting or persisting in smoking at the 30-day and 6-month follow-up. At 6 months, there were 458 deaths and 87 missing.
Figure 2. Adherence to exercise and diet at the 30-day and 6-month follow-up. At 6 months, there were 458 deaths, 92 missing from exercise adherence, and 86 missing from diet adherence.
Variations by Region and Country Economic Classification
In HICs and LMICs and across all regions, the use of antiplatelet medication was similarly high (Tables 2 and 3). However, variations existed for other medication use. Use of statins was higher in HICs than in LMICs. South Africa reported the lowest rates of statin use at 55.1%. ACE/ARBs, β-blockers, and any blood pressure–lowering therapy (β-blockers, calcium channel blockers, diuretics) use was slightly higher in LMICs compared with HICs. Both PCI and CABG were more frequent in HICs, particularly North America.
Table 2. Key Characteristics by Economic Regions
Characteristics
HICs
LMICs
P
BMI indicates body mass index; CAD, coronary artery disease; CK, creatine kinase; and BP, blood pressure. Values are mean (SD) or frequency (%) as appropriate.
Baseline
Age, y
67 (11.2)
66.5 (10.3)
0.0027
Women, n (%)
3608 (33.3)
3574 (44.8)
<0.0001
Unemployed, n (%)
513 (4.7)
658 (8.2)
<0.0001
BMI, kg/m2
27.5 (4.6)
27.2 (4.4)
<0.0001
Total cholesterol, mmol/L
5.2 (1.4)
5.5 (1.8)
<0.0001
Creatinine, mmol
93.1 (27.1)
94 (30.9)
0.0318
Diabetes, n (%)
2666 (24.6)
1975 (24.8)
0.8114
Hypertension, n (%)
6592 (60.9)
5997 (75.2)
<0.0001
Family history of CAD, n (%)
2572 (23.7)
1241 (15.6)
<0.0001
Former smoking, n (%)
3916 (36.1)
2103 (26.4)
<0.0001
Current smoking, n (%)
2648 (24.4)
1606 (20.1)
<0.0001
Never smoking, n (%)
4267 (39.4)
4267 (53.5)
<0.0001
Previous MI, n (%)
2627 (24.2)
2140 (26.8)
<0.0001
In-hospital stay
Hospital stay, d
8.9 (5.8)
11.3 (6.4)
<0.0001
Heart failure, n (%)
1137 (10.5)
1689 (21.2)
<0.0001
Peak total CK
253.9 (355.3)
253.8 (365)
0.9865
PCI in first 30 d, n (%)
5094 (47)
1954 (24.5)
<0.0001
CABG in first 30 d, n (%)
1343 (12.4)
527 (6.6)
<0.0001
Post-MI treatments, n (%)
Antiplatelet
10371 (95.7)
7698 (96.5)
0.0066
β-blocker
4342 (40.1)
4758 (59.7)
<0.0001
ACE/ARB
7409 (68.4)
6234 (78.2)
<0.0001
Statin
8697 (80.3)
6095 (76.4)
<0.0001
Any BP lowering
10 035 (92.6)
7574 (95)
<0.0001
Post-MI behaviors, n (%)
Diet modification
5553 (51.3)
5499 (68.9)
<0.0001
Regular exercise
4987 (46)
3038 (38.1)
<0.0001
Smoking cessation (% of current smokers)
1679 (63.4)
1123 (69.9)
0.0069
Table 3. Key Characteristics by Region
Characteristics
North America
Latin America
Western Europe
Eastern Europe
Australia
South Africa
East Asia
India
P
Abbreviations as in Table 1. Values are mean (%) when appropriate.
Baseline
Age, y
66.5 (11.7)
66.1 (10.9)
67.3 (11.3)
67.1 (10.1)
67.2 (11.3)
60.5 (11.8)
65.5 (10)
62.9 (9.9)
<0.0001
Women, n (%)
706 (33.7)
731 (41.2)
2099 (32.2)
2928 (46.1)
144 (29.1)
64 (34.2)
325 (36.7)
185 (38.1)
<0.0001
Unemployed, n (%)
179 (8.5)
87 (4.9)
242 (3.7)
560 (8.8)
37 (7.5)
22 (11.8)
37 (4.2)
7 (1.4)
<0.0001
BMI, kg/m2
28.5 (5.7)
27.2 (4.5)
27.2 (4.2)
27.8 (4.3)
28.1 (5.1)
27.6 (4.7)
24.6 (3.6)
24.4 (3.7)
<0.0001
Total cholesterol, mmol/L
4.8 (1.3)
5.1 (2.1)
5.2 (1.5)
5.6 (1.5)
4.9 (1.2)
5.6 (1.9)
5.1 (2)
4.8 (1)
<0.0001
Creatinine, mmol
95.9 (28.5)
97.9 (36.2)
91.5 (26.8)
92.4 (25.6)
92.6 (27)
99.2 (35.2)
94.4 (35.5)
105.2 (42.1)
<0.0001
Diabetes, n (%)
592 (28.2)
457 (25.8)
1478 (22.6)
1480 (23.3)
103 (20.9)
52 (27.8)
286 (32.3)
193 (39.7)
<0.0001
Hypertension, n (%)
1403 (66.9)
1311 (73.9)
3703 (56.7)
4869 (76.6)
285 (57.7)
118 (63.1)
611 (69)
289 (59.5)
<0.0001
Family history of CAD, n (%)
763 (36.4)
396 (22.3)
1450 (22.2)
868 (13.7)
164 (33.2)
73 (39)
51 (5.8)
48 (9.9)
<0.0001
Former smoking, n (%)
841 (40.1)
645 (36.4)
2331 (35.7)
1641 (25.8)
236 (47.8)
67 (35.8)
198 (22.4)
60 (12.3)
<0.0001
Current smoking, n (%)
541 (25.8)
390 (22)
1581 (24.2)
1269 (20)
107 (21.7)
66 (35.3)
237 (26.8)
63 (13)
<0.0001
Never smoking, n (%)
715 (34.1)
739 (41.7)
2614 (40)
3448 (54.2)
151 (30.6)
54 (28.9)
450 (50.8)
363 (74.7)
<0.0001
Previous MI, n (%)
556 (26.5)
411 (23.2)
1518 (23.3)
1891 (29.7)
142 (28.7)
54 (28.9)
113 (12.8)
82 (16.9)
<0.0001
Previous stroke, n (%)
131 (6.2)
75 (4.2)
352 (5.4)
425 (6.7)
26 (5.3)
8 (4.3)
94 (10.6)
15 (3.1)
<0.0001
Previous cancer, n (%)
260 (12.4)
57 (3.2)
418 (6.4)
259 (4.1)
67 (13.6)
8 (4.3)
16 (1.8)
0 (0)
<0.0001
In-hospital stay
Hospital stay, d
8.4 (6.2)
9.3 (6.4)
9 (5.7)
11.8 (6.1)
7.9 (5.6)
6.6 (4.4)
11 (7.4)
7.2 (3.9)
<0.0001
Heart failure, n (%)
262 (12.5)
204 (11.5)
608 (9.3)
1410 (22.2)
63 (12.8)
43 (23)
163 (18.4)
73 (15)
<0.0001
Total CK
248.7 (351.8)
249.2 (362.5)
244.8 (345.8)
251.7 (359.5)
274.1 (320.8)
350.1 (412.1)
301.9 (445.5)
311.1 (389.1)
<0.0001
PCI in first 30 d, n (%)
1021 (48.7)
560 (31.6)
3085 (47.3)
1748 (27.5)
147 (29.8)
31 (16.6)
412 (46.6)
44 (9.1)
<0.0001
CABG in first 30 d, n (%)
337 (16.1)
196 (11)
693 (10.6)
427 (6.7)
70 (14.2)
18 (9.6)
79 (8.9)
50 (10.3)
<0.0001
Post-MI treatments, n (%)
Antiplatelet
2020 (96.3)
1703 (96)
6244 (95.6)
6114 (96.2)
483 (97.8)
183 (97.9)
844 (95.4)
478 (98.4)
0.0185
β-blocker
901 (43)
646 (36.4)
2536 (38.8)
3651 (57.4)
230 (46.6)
128 (68.4)
642 (72.5)
366 (75.3)
<0.0001
ACE/ARB
1522 (72.6)
1174 (66.2)
4292 (65.7)
5175 (81.4)
364 (73.7)
143 (76.5)
628 (71)
345 (71)
<0.0001
Statin
1716 (81.8)
1305 (73.6)
5287 (81)
4899 (77.1)
444 (89.9)
103 (55.1)
609 (68.8)
429 (88.3)
<0.0001
Any BP lowering
1939 (92.5)
1588 (89.5)
6053 (92.7)
6125 (96.3)
440 (89.1)
178 (95.2)
821 (92.8)
465 (95.7)
<0.0001
Post-MI behaviors, n (%)
Diet
990 (47.2)
1478 (83.3)
3358 (51.4)
4083 (64.2)
278 (56.3)
73 (39)
364 (41.1)
428 (88.1)
<0.0001
Exercise
913 (43.5)
660 (37.2)
3175 (48.6)
2367 (37.2)
300 (60.7)
48 (25.7)
322 (36.4)
240 (49.4)
<0.0001
Smoking cessation (% of current smokers)
292 (54.0)
318 (81.5)
1014 (38.8)
856 (67.5)
63 (58.9)
26 (39.4)
176 (74.3)
57 (90.5)
<0.0001
Adherence to diet advice was reported more frequently by individuals in LMICs versus HICs, but regular exercise was higher in HICs versus LMICs. Participants from India had the highest rate of dietary adherence (88.1%); participants from South Africa had the lowest rate (39.0%). The highest rate of exercise was in Australia (60.7%), and lowest was in South Africa (25.7%). The highest rates of smoking cessation were in Latin America (81.5%) and India (90.5%), whereas the lowest was in Western Europe (38.8%).
General Characteristics of Behavior Modifiers Versus Nonmodifiers
Smoking Categories
Nonsmokers and former smokers were older at presentation compared with quitters and persistent smokers. Persistent smokers and recent quitters were generally similar; however, quitters reported higher rates of dietary adherence (60.8% versus 47.2%) and exercise (49.9% versus 42.2%) (Table 4).
Table 4. Characteristics of ACS Patients by Smoking Status
Adherers to both diet and exercise were younger than nonadherers. Length of hospital stay was similar across categories, but prevalence of heart failure was lower in adherers. Rates of never smoking were similar across groups, but recent quitting was more common in adherers to diet and exercise. Use of aspirin, β-blockers, and ACE/ARB was similar across groups, but statin use was higher in adherers despite lipid levels being similar. There was a significant trend to increased weight loss in the first 30 days in adherers to diet/exercise compared with other groups (Table 5).
Table 5. Characteristics of ACS Patients According to Health Behaviors
*Weight data at baseline and 30 days were available for 4211 in the no modification group, 6654 in the either modification group, and 5039 in the both modifications group.
n
5356 (28.5)
7829 (41.6)
5624 (29.9)
…
Baseline
Women, n (%)
2323 (43.4)
3131 (40.0)
1728 (30.7)
<0.0001
Unemployed, n (%)
400 (7.5)
433 (5.5)
338 (6.0)
<0.0001
Age, y
68.7 (10.8)
67.2 (10.6)
64.3 (10.8)
<0.0001
BMI, kg/m2
27.3 (4.6)
27.4 (4.5)
27.5 (4.4)
0.0149
Diabetes, n (%)
1396 (26.1)
1975 (25.2)
1270 (22.6)
<0.0001
Hypertension, n (%)
3679 (68.7)
5315 (67.9)
3595 (63.9)
<0.0001
Family history of CAD, n (%)
1046 (19.5)
1641 (21.0)
1126 (20.0)
0.1141
Previous MI, n (%)
1480 (27.6)
2041 (26.1)
1246 (22.2)
<0.0001
Previous stroke, n (%)
371 (6.9)
482 (6.2)
273 (4.9)
<0.0001
Previous cancer, n (%)
374 (7.0)
450 (5.7)
261 (4.6)
<0.0001
Total cholesterol, mmol/L
5.2 (1.5)
5.3 (1.6)
5.3 (1.7)
0.0003
LDL cholesterol, mmol/L
3.2 (1.1)
3.3 (1.2)
3.3 (1.1)
<0.0001
HDL cholesterol, mmol/L
1.2 (0.4)
1.2 (0.5)
1.2 (0.5)
0.0772
Triglycerides, mmol/L
1.8 (1.3)
1.9 (1.6)
1.9 (1.4)
0.1545
Creatinine, mmol/L
94.6 (30.4)
93.8 (29.6)
92 (25.9)
<0.0001
Never smoker, n (%)
2533 (47.3)
3545 (45.3)
2456 (43.7)
0.0007
Former smoker, n (%)
1627 (30.4)
2574 (32.9)
1818 (32.3)
0.0085
Current smoker, n (%)
1195 (22.3)
1709 (21.8)
1350 (24)
0.0098
In hospital
Hospital stay, mean, d
10.2 (6.7)
10 (6.3)
9.5 (5.4)
<0.0001
Total CK
230.7 (324.3)
257.2 (363.6)
271.4 (383.6)
<0.0001
Heart failure at admission, n (%)
896 (16.7)
1219 (15.6)
711 (12.6)
<0.0001
PCI in first 30 d, n (%)
1847 (34.4)
2841 (36.3)
2360 (42.0)
<0.0001
CABG in first 30 d, n (%)
510 (9.5)
800 (10.2)
560 (10.0)
0.4222
Secondary prevention, 30 d, n (%)
Aspirin
4910 (91.7)
7251 (92.6)
5311 (94.4)
<0.0001
Antiplatelet
5085 (94.9)
7506 (95.9)
5478 (97.4)
<0.0001
β-blocker
2635 (49.2)
3921 (50.1)
2544 (45.2)
<0.0001
ACE/ARB
3917 (73.1)
5717 (73.0)
4009 (71.2)
0.0425
Any BP lowering
5042 (94.1)
7316 (93.4)
5251 (93.4)
0.1836
Statin
3981 (74.3)
6166 (78.8)
4645 (82.6)
<0.0001
Recently quit (% overall)
676 (12.6)
1148 (14.7)
978 (17.4)
<0.0001
Weight loss between baseline and 30 d, mean (SD), kg*
0.503 (2.66)
0.789 (2.83)
0.888 (3.13)
<0.001
PCI >30 d to 6 mo
278 (5.5)
435 (5.9)
353 (5.5)
0.7348
CABG >30 d to 6 mo
140 (2.8)
288 (3.9)
240 (3.9)
0.0016
Relationship Between Behavioral Change and Cardiovascular Outcomes
Among the study population that survived to 30 days after ACS presentation, 455 (2.4%) had a subsequent MI, 120 (0.6%) had a subsequent stroke, and 481 (2.6%) died by the end of the 6-month follow-up period.
Event Rates in Relationship to Smoking Behavior
Compared with persistent smokers, quitters had an OR (from fully adjusted models) of 0.57 (95% confidence interval [CI], 0.36 to 0.89; P=0.0145) for MI and an OR of 0.74 (95% CI, 0.53 to 1.02; P=0.0698) for MI/stroke/death (Table 6).
Table 6. Relationship Between Diet/Exercise Modification and Repeat Cardiovascular Events in Patients With ACS
Category
Risk of MI
Risk of Stroke
Risk of Death
Risk of Death/MI/Stroke
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
Models were adjusted for age; sex; region; history of hypertension, diabetes, and prior MI; body mass index; creatinine; PCI/CABG before 30 days; and use of β-blockers, statins, antiplatelets, and ACE/ARB drugs at 30 days.
No diet/exercise
Reference
Reference
Reference
Reference
Diet only
0.93 (0.74–1.16)
0.5137
0.84 (0.54–1.31)
0.4357
0.91 (0.73–1.13)
0.3986
0.91 (0.77–1.07)
0.2605
Exercise only
0.78 (0.56–1.1)
0.1547
0.94 (0.52–1.68)
0.8256
0.61 (0.42–0.88)
0.0091
0.69 (0.54–0.89)
0.0037
Both diet and exercise
0.52 (0.40–0.69)
<0.0001
0.46 (0.26–0.82)
0.0079
0.45 (0.33–0.60)
<0.0001
0.46 (0.38–0.57)
<0.0001
Diet and Physical Activity Behaviors
Compared with nonadherers to either diet or exercise, people who were adherent to either diet or exercise had an OR for MI, stroke, or death (from fully adjusted models) of 0.85 (95% CI, 0.73 to 0.99; P=0.03), and people who were adherent to both diet and exercise had an OR of 0.46 (95% CI, 0.38 to 0.57; P<0.0001) (Table 7). ORs calculated from fully adjusted models were not materially different from those calculated by age- and sex-adjusted models. Analyses were repeated with a hierarchical model to control for country within region and center within country, and results were similar to those reported here.
Table 7. Relationship Between Smoking and Repeat Cardiovascular Events in Patients With ACS
Category
Risk of MI
Risk of Stroke
Risk of Death
Risk of Death/MI/Stroke
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
Models were adjusted for age; sex; region; history of hypertension, diabetes, and prior MI; body mass index; creatinine; PCI/CABG before 30 days; and use of β-blockers, statins, antiplatelets, and ACE/ARB drugs at 30 days.
Persistent smoker
Reference
Reference
Reference
Reference
Quitter
0.57 (0.36–0.89)
0.0145
0.40 (0.14–1.17)
0.0930
0.93 (0.59–1.46)
0.7594
0.74 (0.53–1.02)
0.0698
Ex-smoker
0.68 (0.48–0.98)
0.3990
0.79 (0.36–1.74)
0.5547
0.65 (0.44–0.97)
0.0360
0.68 (0.51–0.90)
0.0067
Never smoker
0.49 (0.34–0.71)
0.0002
0.83 (0.38–1.82)
0.6397
0.59 (0.40–0.89)
0.0108
0.59 (0.44–0.78)
0.0002
Effects of Multiple Lifestyle Changes
For each category of smoker, change in diet and exercise had additive effects in decreasing risk of cardiovascular events. Persistent smokers who did not modify diet or exercise had the highest risk of a repeat cardiovascular event (fully adjusted OR, 3.77; 95% CI, 2.40 to 5.91; Figure 3).
Figure 3. Risk of repeat cardiovascular events (MI/stroke/death) with progressive behavioral change. Models were adjusted for age; sex; region; history of hypertension, diabetes, prior MI, body mass index, creatinine, v n30days. The reference category is “never smoker and diet and exercise.”
Discussion
This study found that adherence to recommendations regarding smoking, diet, and exercise at 30 days after ACS is associated with a substantially lower rate of short-term major cardiovascular outcomes and all-cause mortality. Compared with persistent smokers, recent quitters had a lower risk of MI and a marginally lower risk of the composite outcome. Adherers to diet and exercise had a 50% lower risk for all major events in 6 months compared with nonadherers. The risk associated with diet alone or exercise alone was similar for MI and stroke, but for death, exercise may be more important. Persistent smokers who did not diet or exercise had an ≈4-fold risk of cardiovascular events compared with never smokers who dieted and exercised. Excess risk for all of the categories was apparent after accounting for multiple confounders, including drug treatments, PCI, and CABG, suggesting that the benefits of adherence to lifestyle modification are additional to the benefits conferred by drugs and interventions.
Our study suggests that these benefits accrue early (by 6 months). Smoking cessation may lead to early benefit through reversal of platelet activation, coronary artery spasm, and ventricular arrhythmias.16 Diet and exercise may have early benefits through risk factor control,12,17 improved plaque stabilization in response to less oxidative stress damage, and fewer arrhythmias resulting from membrane stabilization.18,19
An important potential explanation for the benefits seen in adherers is that adherence per se is a marker of adherence to other beneficial treatments and healthy behaviors in unmeasured ways. That is, the effects seen with lifestyle behaviors here are not a true effect of diet and exercise per se but are related to characteristics of adherers. This study did not demonstrate substantial differences in characteristics or drug treatments in adherers to diet/exercise or smoking cessation compared with nonadherers. We also examined whether those who do not change behavior are more or less compliant with medications and did not identify a relationship (analyses not shown). Supportive of the above notion is that good lifestyle behaviors appear to cluster (eg, persons who quit smoking had higher rates of adherence to diet and exercise). Randomized studies have found that those with improved adherence to either study drug or placebo are relatively protected compared with nonadherers and postulate that this may be due to other unmeasured health attitudinal characteristics.20
Although it is not clear what the cause of the decreased risk is in adherers to lifestyle recommendations, this study adds to the body of evidence that behavior modification is associated with substantial benefits. This study highlights the early benefits of lifestyle modification and the incremental benefits of multiple behavior changes and underscores the relatively poor adherence to lifestyle recommendations (compared with preventive drug therapy) in a well-treated clinical trial population.
The strengths of this study are its large size and its inclusion of patients with ACS from a wide range of centers in multiple countries. The study had detailed records of the use of secondary preventive medications at follow-up visits, enabling us to assess the effect of this important potential confounder. An additional strength is the rigorous, systematic reporting of events and highly complete follow-up resulting from the study being principally a large clinical trial.
Potential limitations of this study are that information on secondary preventive lifestyle behaviors was collected with simple self-report questions. The definitions of quitting and persistent smoking relied on self-report and were not validated by cotinine measurements. Similarly, we did not collect details on actual diet or exercise and hence cannot quantify them or describe which elements of diet or exercise programs are associated with the lower risk.
We acknowledge that unmeasured baseline characteristics may have had an impact on subsequent events (eg, socioeconomic status, physical disability). Reporting of compliance may vary substantially according to geographic region or cultural traditions. There could be a potential for misclassification because adherers/nonadherers were categorized at the 30-day follow-up; however, such misclassifications would tend to minimize real differences between groups, so our data may be an underestimate of the true benefits of behavioral change after ACS.
This study found that individuals who change their behavior (quit smoking and modify diet and exercise) after ACS are at substantially lower risk of repeat cardiovascular events. These benefits are seen early (<6 months), and the benefits from each behavior modification are additive. These results indicate that adherence to behavioral recommendations in the immediate postevent care of patients with ACS should be given as high a priority by physicians and caregivers as other secondary preventive medications and invasive strategies and justify a significant investment in establishing programs that systematically enhance early lifestyle modification and secondary prevention.
Acknowledgments
We thank Rizwan Afzal, senior statistician, for advice.
Sources of Funding
Dr Chow is supported by a Cottrell Fellowship from the Royal Australasian College of Physicians and Public Health (Sidney Sax) Overseas Fellowship cofunded by the National Health and Medical Research Council and National Heart Foundation of Australia. Dr Yusuf holds an endowed research chair of the Heart and Stroke Foundation of Ontario. Dr Anand holds the May Cohen Eli Lilly Chair in Women’s Health Research and Michael G. DeGroote Heart and Stroke Foundation Chair in Population Health. The OASIS study was funded by Sanofi-Aventis, Organon, and GlaxoSmithKline. The funding sources had no involvement in the analyses presented here.
Disclosures
None.
CLINICAL PERSPECTIVE
Although preventive drug therapy is a priority after myocardial infarction (MI), less is known about adherence to behavioral recommendations. The aim of this study was to examine the influence of adherence to behavioral recommendations on the risk for repeat MI. The study population included 18 809 patients from 41 countries enrolled in the Organization to Assess Strategies in Acute Ischemic Syndromes (OASIS) 5 randomized clinical trial. One month after presenting with MI, 28.5% reported nonadherence to diet and exercise recommendations, and about one third of smokers persisted in smoking. In models adjusted for known risk factors and medical treatments, quitting smoking was associated with about half the risk of repeat MI compared with persistent smoking (odds ratio, 0.57; 95% confidence interval, 0.36 to 0.89), and diet and exercise adherence was associated with about half the risk of repeat MI compared with nonadherence (odds ratio, 0.52; 95% confidence interval, 0.4 to 0.69). Persistent smoking and nonadherence to diet and exercise were associated with a 3.8-fold (95% confidence interval, 2.5 to 5.9) increased risk of cardiovascular events (MI, stroke, and death) compared with risks in never smokers who modified diet and exercise. These analyses highlight the relatively poor adherence to behavioral advice (diet, exercise, and smoking cessation) after MI and suggest that behavioral modification should be given priority similar to other preventive medications immediately after MI because they are associated with substantial benefits in the prevention of repeat events.
Footnote
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From the Population Health Research Institute (C.K.C., S.J., P.R.-M., S.S.A., S.Y.) and Departments of Medicine (C.K.C., S.S.A., S.Y.) and Epidemiology (S.S.A.), McMaster University, and Hamilton Health Sciences (C.K.C., S.J., P.R.-M., S.S.A., S.Y.), Hamilton, Ontario, Canada; The George Institute for International Health, University of Sydney, Sydney, New South Wales, Australia (C.K.C.); and Centre for Cardiovascular Science, University of Edinburgh, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom (K.A.A.F.).
From the Population Health Research Institute (C.K.C., S.J., P.R.-M., S.S.A., S.Y.) and Departments of Medicine (C.K.C., S.S.A., S.Y.) and Epidemiology (S.S.A.), McMaster University, and Hamilton Health Sciences (C.K.C., S.J., P.R.-M., S.S.A., S.Y.), Hamilton, Ontario, Canada; The George Institute for International Health, University of Sydney, Sydney, New South Wales, Australia (C.K.C.); and Centre for Cardiovascular Science, University of Edinburgh, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom (K.A.A.F.).
From the Population Health Research Institute (C.K.C., S.J., P.R.-M., S.S.A., S.Y.) and Departments of Medicine (C.K.C., S.S.A., S.Y.) and Epidemiology (S.S.A.), McMaster University, and Hamilton Health Sciences (C.K.C., S.J., P.R.-M., S.S.A., S.Y.), Hamilton, Ontario, Canada; The George Institute for International Health, University of Sydney, Sydney, New South Wales, Australia (C.K.C.); and Centre for Cardiovascular Science, University of Edinburgh, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom (K.A.A.F.).
Keith A.A.Fox, BSc (Hons), MB, ChB, FRCP, FESC, FMedSci
From the Population Health Research Institute (C.K.C., S.J., P.R.-M., S.S.A., S.Y.) and Departments of Medicine (C.K.C., S.S.A., S.Y.) and Epidemiology (S.S.A.), McMaster University, and Hamilton Health Sciences (C.K.C., S.J., P.R.-M., S.S.A., S.Y.), Hamilton, Ontario, Canada; The George Institute for International Health, University of Sydney, Sydney, New South Wales, Australia (C.K.C.); and Centre for Cardiovascular Science, University of Edinburgh, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom (K.A.A.F.).
From the Population Health Research Institute (C.K.C., S.J., P.R.-M., S.S.A., S.Y.) and Departments of Medicine (C.K.C., S.S.A., S.Y.) and Epidemiology (S.S.A.), McMaster University, and Hamilton Health Sciences (C.K.C., S.J., P.R.-M., S.S.A., S.Y.), Hamilton, Ontario, Canada; The George Institute for International Health, University of Sydney, Sydney, New South Wales, Australia (C.K.C.); and Centre for Cardiovascular Science, University of Edinburgh, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom (K.A.A.F.).
From the Population Health Research Institute (C.K.C., S.J., P.R.-M., S.S.A., S.Y.) and Departments of Medicine (C.K.C., S.S.A., S.Y.) and Epidemiology (S.S.A.), McMaster University, and Hamilton Health Sciences (C.K.C., S.J., P.R.-M., S.S.A., S.Y.), Hamilton, Ontario, Canada; The George Institute for International Health, University of Sydney, Sydney, New South Wales, Australia (C.K.C.); and Centre for Cardiovascular Science, University of Edinburgh, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom (K.A.A.F.).
Correspondence to Dr Clara K. Chow, Hamilton General Hospital, 237 Barton St E, Hamilton, Ontario, L8L 2X2, Canada. E-mail [email protected] or [email protected]
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Association of Diet, Exercise, and Smoking Modification With Risk of Early Cardiovascular Events After Acute Coronary Syndromes
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