Table 1.
MI cases (N = 276) | Stroke cases (N = 151) | Subcohort (N = 778) | |
---|---|---|---|
Male sex (N, %) | 219 (79)⁎ | 96 (64)⁎ | 355 (46) |
Age at blood draw (years) | 55.6 ± 6.3⁎ | 55.6 ± 7.1⁎ | 50.6 ± 8.0 |
Age at diagnosis (years) | 60.7 ± 6.9 | 60.6 ± 7.8 | – |
University degree (N, %) | 66 (24)⁎ | 39 (26) | 244 (31) |
Physically inactive (N, %) | 42 (15) | 25 (17) | 89 (11) |
BMI (kg/m2) | 27.9 ± 4.0⁎ | 27.3 ± 3.9⁎ | 25.7 ± 4.2 |
Lifetime alcohol intake (g/day) | 24.9 ± 30.5⁎ | 22.2 ± 29.3⁎ | 16.8 ± 24.4 |
Red and processed meat intake ≥ 120 g/day (N, %)a | 96 (35)⁎ | 43 (28) | 170 (22) |
Smoking status (N, %) | |||
Never smokers | 85 (31) | 48 (32) | 338 (43) |
Former smokers ≥ 10 years | 55 (20) | 37 (25) | 175 (22) |
Former smokers < 10 years | 23 (8) | 13 (9) | 84 (11) |
Current smokers < 15 cig/day | 28 (10) | 13 (9) | 79 (10) |
Current smokers ≥ 15 cig/day | 85 (31)⁎ | 40 (26)⁎ | 102 (13) |
Hyperlipidemia (N, %)b | 145 (53)⁎ | 76 (50)⁎ | 263 (34) |
Use of lipid-lowering drugs (N, %)c | 42 (29) | 19 (25) | 66 (25) |
Hypertension (N,%)b | 126 (46)⁎ | 71 (47)⁎ | 209 (27) |
Use of anti-hypertensive drugs (N, %)c | 92 (73) | 51 (72) | 134 (64) |
Use of NSAIDs (N, %)b | 33 (12) | 17 (11) | 68 (9) |
Use of calcium supplements (N, %)b | 13 (5)⁎ | 4 (3) | 16 (2) |
Laboratory measurements of T cell subsets (median, range) | |||
% CD3 + tTL of leukocytes | 19.7 (3.9–48.7) | 19.9 (8.6–41.5) | 20.0 (4.0–61.3) |
% Foxp3 + Treg cells of leukocytes | 1.0 (0.3–3.1) | 1.0 (0.3–2.4) | 1.0 (0.2–4.9) |
Treg/tTL ratiod | 5.2 (1.7–14.0) | 5.1 (1.8–12.0) | 5.1 (1.5–15.5) |
BMI: body mass index. NSAIDs: non-steroidal anti-inflammatory drugs. tTL: total CD3 + T-lymphocytes.
Values are means ± standard deviation or percentages unless otherwise stated.
Data are missing for lipid-lowering (n = 2) medication.
Adjusted for total energy intake using the residual method.
Prevalent.
Among individuals with prevalent hypertension or hyperlipidemia, respectively.
Ratio multiplied by 100.
P < 0.05 for case vs. subcohort. P-value for difference was calculated using the chi-squared test for categorical variables and the t-test for continuous variables.