Methods

Participants were enrolled in the Heart and Soul Study, a cohort of outpatients with known CHD recruited from 2000 to 2002 from the San Francisco VA Medical Center, VA Palo Alto Health Care System, the University of California, San Francisco, Medical Center, and 9 public health clinics in the Community Health Network of San Francisco, California. A total of 1,024 participants were enrolled in the original cohort. Eligible participants had documented CHD, defined as a history of myocardial infarction, coronary revascularization, angiographic evidence of ≥50% stenosis in ≥1 coronary vessel, or evidence of exercise-induced ischemia on a previous treadmill or nuclear stress test. Participants were excluded if they reported myocardial infarctions in the previous 6 months, were unable to walk 1 block, or were planning to move out of the local area within 3 years. Participants attended a baseline examination, which included a fasting blood draw, a physical examination, questionnaires, echocardiography, and a maximal exercise treadmill test. At 5 years, 667 participants (80% of the 829 survivors) completed a 5-year follow-up examination that repeated the baseline protocol, including a fasting blood draw. The present study was limited to 656 participants who had physical activity and biomarker assessments from the 2 time points. The study was approved by the appropriate institutional review boards, and all participants provided informed consent before enrollment.

Physical activity frequency was determined by self-report using the question “Which of the following statements best describes how physically active you have been during the last month, that is, done activities such as 15-20 minutes of brisk walking, swimming, general conditioning, or recreational sports?” Possible responses included “not at all active,” “a little active (1-2 times per month),” “fairly active (3-4 times per month),” “quite active (1-2 times per week),” “very active (3-4 times per week),” and “extremely active (5 or more times per week).” Participants who answered “not at all active” or “a little active” were grouped into the low-activity group, whereas those who reported being “fairly active,” “quite active,” “very active,” and “extremely active” were grouped into the high-activity group. This is consistent with previous classifications of physical activity in this cohort and has been shown to be a strong predictor of incident CHD events. Single-item self-report measures of physical activity have also been shown to be valid and reliable measures of cardiovascular fitness. We used data from baseline and year 5 to categorize participants into 4 groups: (1) stable low activity included participants reporting low activity frequency at baseline and year 5, (2) decreasing activity included those with high activity frequency at baseline and low activity frequency at year 5, (3) increasing activity included those with low activity frequency at baseline and high activity frequency at year 5, and (4) stable high activity included those with high activity frequency at baseline and year 5.

Using baseline data, we also assessed the extent to which participants engaged in activities of different intensities within the past month for ≥15 to 20 minutes per episode, such as light-intensity activity (walking at an average pace, sweeping, vacuuming), moderate-intensity activity (brisk walking, lawn mowing, golf, dancing, light cycling), or heavy-intensity activity (swimming laps, basketball, jogging, vigorous cycling, hiking, or weightlifting). Possible responses were “not at all,” “less than 1 time per week,” “1-2 times per week,” and “3 or more times per week.”

Blood samples were collected after an overnight fast. High-sensitivity C-reactive protein (CRP) was measured using the Roche Integra assay (Roche Diagnostics, Indianapolis, Indiana) for the first 229 participants or (because of a change in the laboratory) the Beckman Extended Range assay (Beckman, Galway, Ireland). Results from the 2 assays were highly correlated (r = 0.99) in a sample of 189 participants. The interassay coefficients of variation were 3.2% for the Roche Integra assay and 6.7% for the Beckman Extended Range assay. A Quantikine High Sensitivity Immunoassay kit (R&D Systems, Minneapolis, Minnesota) was used to assess interleukin-6 serum concentration. The coefficient of variation for interleukin-6 ranged from 6.5% to 9.6%. Fibrinogen was measured using the Clauss assay, with a coefficient of variation of <3%. Fasting serum samples were used to measure glucose, insulin, glycated hemoglobin, total cholesterol, high-density lipoprotein cholesterol, and triglyceride concentrations. Low-density lipoprotein cholesterol concentrations were calculated.

Age, gender, race and ethnicity, smoking status, highest educational achievement, and income level were determined by self-report. Co-morbidities were determined by asking if participants had ever received diagnoses from a list of medical conditions. Blood pressure, height, and weight were measured. Body mass index was calculated. All participants were instructed to bring in their current medication bottles for study personnel to record. Physical fitness was assessed by maximal exercise treadmill testing using a standard or modified Bruce protocol to determine maximal exercise capacity in METs. Rest and peak exercise 2-dimensional echocardiography was performed. Inducible ischemia was defined as the presence of new wall motion abnormalities at maximum exercise by an expert echocardiographer.

Other covariates were evaluated by self-report. Medication nonadherence was defined as taking medications ≤75% of the time. Depressive symptoms were assessed using the 9-item Patient Health Questionnaire, and standard cut-point of ≥10 points was used to define depression. Posttraumatic stress disorder was evaluated using the Computerized Diagnostic Interview Schedule for the Diagnostic and Statistical Manual of Mental Disorders , Fourth Edition.

Baseline characteristics were compared among the 4 physical activity groups using chi-square tests for categorical variables and Student’s t tests for continuous variables. Biomarkers with abnormal distributions were log-transformed. Multivariate linear regression models were constructed with the 4 categories of physical activity as the independent variable and follow-up (year 5) inflammatory and insulin resistance biomarkers as the dependent variables. A test for trend was conducted across these models, with stable low activity as the reference group, followed by decreasing activity, increasing activity, and stable high activity. Adjustments were made for all variables that differed by physical activity status at p ≤0.10. Smoking was also added to the models (p = 0.11) because of the known association with the predictor and the outcomes. Models were adjusted sequentially for baseline biomarker levels (model 1); then adding gender, education, chronic obstructive pulmonary disease, and aspirin use (model 2); followed by diabetes, use of any diabetes medications (specifically metformin, insulin, sulfonylureas, and thiazolidinediones), body mass index, and smoking (model 3); and finally depression and posttraumatic stress disorder (model 4). All values entered into the models were baseline values, as covariates did not substantially change within activity groups from baseline to year 5 (see “Results”). Statistical testing was 2 sided, at a significance level of 0.05. All analyses were conducted using SAS version 9.3 (SAS Institute Inc., Cary, North Carolina).

Results

A total of 656 participants were included in the study, with a mean age of 66.1 ± 10.2 years. Sixty percent of participants were white, and 83% were men. Baseline characteristics by physical activity group are listed in Table 1 . Cardiovascular medication use was similar across groups. Use of diabetes medications differed across activity groups despite a nonsignificant difference in rates of diabetes. Notably, mean measured exercise capacity corresponded well with self-reported activity status. Reported levels of light-, moderate-, and heavy-intensity activity at baseline are shown in Supplementary Figure 1 . Most activities reported were of light and moderate intensity. Even in the stable high activity group, <20% reported engaging in heavy-intensity activity ≥3 times per week. Among the entire cohort, only 73 participants (11%) reported engaging in heavy-intensity activities ≥3 times per week.

Median values of biomarkers at baseline and after 5 years of follow-up in each physical activity group are listed in Table 2 . There were significant inverse trends between inflammation and insulin resistance biomarkers and physical activity group at baseline and 5-year follow-up. Nearly all groups were observed to have decreasing or unchanged levels of biomarkers at 5 years, with the exception of interleukin-6. The groups with the lowest activity had the largest increase in interleukin-6.

Table 2

Median levels of biomarkers by activity group at baseline and 5-year follow up

Biomarker	Activity				p-Value for Trend
	Stable Low	Decreasing	Increasing	Stable High
CRP (mg/L)
Baseline	3.08	1.75	2.37	1.63	<0.001
Follow-up	2.16	1.93	1.65	1.15	<0.001
5-year change (% change)	−0.92 (−30%)	0.18 (+10%)	−0.72 (−30%)	−0.48 (−29%)
Interleukin-6 (pg/mL)
Baseline	2.90	2.44	2.73	2.11	<0.001
Follow-up	4.18	4.23	3.46	2.83	<0.001
5-year change (% change)	1.28 (+44%)	1.79 (+73%)	0.73 (+27%)	0.72 (+34%)
Fibrinogen (RU/mL)
Baseline	393	376	389	363	<0.01
Follow-up	382	372	373	357	0.01
5-year change (% change)	−11 (−3%)	−4 (−1%)	−16 (−4%)	−6 (−2%)
Insulin (pg/mL)
Baseline	296	286	272	269	0.25
Follow-up	255	250	228	215	0.08
5-year change (% change)	−41 (−14%)	−36 (−13%)	−44 (−16%)	−54 (−20%)
Glucose (mg/dL)
Baseline	108	108	107	105	0.23
Follow-up	106	108	102	104	0.01
5-year change (% change)	−2 (−2%)	0 (0)	−5 (−5%)	−1 (−1%)
Hemoglobin A1c (%)
Baseline	5.8	5.8	5.7	5.6	0.02
Follow-Up	5.8	5.7	5.6	5.6	0.01
5-year change (% change)	0 (0)	−0.1 (−2%)	−0.1 (−2%)	0 (0)

Only gold members can continue reading. Log In or Register to continue

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Related

Related posts:

1. The Age, Creatinine, and Ejection Fraction Score to Risk Stratify Patients Who Underwent Percutaneous Coronary Intervention of Coronary Chronic Total Occlusion
2. Frequency and Significance of Myocardial Bridging and Recurrent Segment of the Left Anterior Descending Coronary Artery in Patients With Takotsubo Cardiomyopathy
3. Usefulness of Blood Pressure Rise Prior to Exercise Stress Testing to Predict the Risk of Future Hypertension in Normotensive Korean Men
4. Effect of Age on Survival Between Open Repair and Surveillance for Small Abdominal Aortic Aneurysms

Stay updated, free articles. Join our Telegram channel

Join