A Mediterranean Dietary Pattern Predicts Better Sleep Quality in US Women from the American Heart Association Go Red for Women Strategically Focused Research Network
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants and Procedures
2.2. Dietary Assessment
2.3. Sleep Assessment
2.4. Statistical Analysis
3. Results
4. Discussion
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Characteristic | Mean ± SD/n (%) |
---|---|
Demographic and physical | |
Age (years) | 37 ± 15 |
Race | |
White | 247 (57) |
Black/African American | 84 (19) |
Asian | 80 (19) |
Other | 21 (5) |
Race/Ethnicity | |
White/Non-Hispanic | 172 (40) |
Minority/Hispanic | 260 (60) |
Health Insurance | |
Private/Medicare | 276 (64) |
Do not have/Unknown/Medicaid | 156 (36) |
Education | |
>College degree | 139 (32) |
≤College degree | 293 (67) |
Body Mass Index (BMI) (kg/m2) | 25.9 ± 5.5 |
<25 kg/m2 | 232 (54) |
≥25 kg/m2 | 200 (46) |
Dietary Intakes | |
Alternate Mediterranean Diet (aMed) Score | 4.3 ± 1.5 |
Fruits and vegetables a | 3.8 ± 2.3 |
Legumes a | 0.9 ± 1.0 |
Nuts a | 0.7 ± 0.8 |
Dark breads a | 0.3 ± 0.4 |
Red/processed meat a | 1.2 ± 1.3 |
Fish b | 12.6 ± 15.0 |
MUFA to SFA ratio | 1.3 ± 0.4 |
Alcohol c | 4.4 ± 5.6 |
Unsaturated fat c | 23.5 ± 5.3 |
Saturated fat c | 12.7 ± 3.0 |
Plant protein b | 5.9 ± 1.7 |
Animal protein b | 10.0 ± 3.8 |
Fiber b | 11.5 ± 4.5 |
Sleep Characteristic | Baseline | 1-y Follow-Up | p-Value |
---|---|---|---|
Total PSQI score a | 5.5 ± 3.6 | 5.1 ± 3.3 | <0.01 |
Sleep onset latency (min) b | 24.3 ± 29.3 | 21.2 ± 21.0 | 0.02 |
Sleep efficiency (%) b | 88.3 ± 11.4 | 87.5 ± 11.3 | 0.24 |
Sleep disturbance score b | 6.1 ± 4.4 | 5.8 ± 4.2 | 0.05 |
Predictor | Outcome | β (SE) b | p-Value | β (SE) c | p-Value |
---|---|---|---|---|---|
aMed diet score | PSQI total score | −0.30 (0.10) | <0.01 | −0.31 (0.08) | <0.0001 |
Sleep onset latency | −0.61 (0.65) | 0.35 | −0.71 (0.59) | 0.23 | |
Sleep efficiency | 1.20 (0.35) | <0.001 | 1.21 (0.33) | <0.001 | |
Sleep disturbances | −0.30 (0.12) | 0.01 | −0.35 (0.10) | <0.001 | |
Fruits and vegetables | PSQI total score | −0.16 (0.07) | 0.02 | −0.19 (0.05) | <0.001 |
Sleep onset latency | −0.41 (0.44) | 0.36 | −0.31 (0.40) | 0.44 | |
Sleep efficiency | 0.56 (0.24) | 0.02 | 0.52 (0.22) | 0.02 | |
Sleep disturbances | −0.18 (0.08) | 0.03 | −0.15 (0.07) | 0.02 | |
Legumes | PSQI total score | −0.10 (0.16) | 0.55 | −0.24 (0.13) | 0.06 |
Sleep onset latency | −1.13 (1.03) | 0.27 | −1.21 (0.94) | 0.20 | |
Sleep efficiency | 1.36 (0.55) | 0.01 | 1.46 (0.52) | <0.01 | |
Sleep disturbances | 0.17 (0.19) | 0.39 | −0.08 (0.16) | 0.62 | |
Nuts | PSQI total score | 0.01 (0.21) | 0.96 | 0.02 (0.17) | 0.92 |
Sleep onset latency | 0.09 (1.35) | 0.95 | 0.25 (1.23) | 0.84 | |
Sleep efficiency | −0.47 (0.72) | 0.51 | −0.36 (0.68) | 0.60 | |
Sleep disturbances | −0.26 (0.25) | 0.31 | −0.09 (0.20) | 0.65 | |
Dark breads | PSQI total score | −0.68 (0.39) | 0.08 | −0.55 (0.30) | 0.07 |
Sleep onset latency | −0.94 (2.48) | 0.71 | −1.09 (2.26) | 0.63 | |
Sleep efficiency | 2.07 (1.33) | 0.12 | 1.96 (1.26) | 0.12 | |
Sleep disturbances | −0.43 (0.47) | 0.36 | −0.67 (0.38) | 0.08 | |
Fish | PSQI total score | 0.00 (0.01) | 0.99 | −0.004 (0.01) | 0.67 |
Sleep onset latency | 0.02 (0.07) | 0.74 | −0.02 (0.06) | 0.73 | |
Sleep efficiency | −0.01 (0.04) | 0.73 | −0.01 (0.03) | 0.76 | |
Sleep disturbances | −0.01 (0.01) | 0.32 | −0.01 (0.01) | 0.36 | |
Red/processed meat | PSQI total score | −0.02 (0.12) | 0.89 | 0.07 (0.10) | 0.49 |
Sleep onset latency | −0.00 (0.80) | 0.99 | 0.22 (0.73) | 0.76 | |
Sleep efficiency | −0.06 (0.43) | 0.89 | −0.28 (0.41) | 0.49 | |
Sleep disturbances | 0.04 (0.15) | 0.81 | 0.04 (0.12) | 0.74 |
Predictor | Outcome | β (SE) b | p-Value | β (SE) c | p-Value |
---|---|---|---|---|---|
Monounsaturated fat (MUFA) to saturated fat (SFA) ratio | PSQI total score | −0.84 (0.41) | <0.05 | −0.38 (0.33) | 0.25 |
Sleep onset latency | −2.26 (2.69) | 0.40 | −1.10 (2.45) | 0.65 | |
Sleep efficiency | 3.11 (1.43) | 0.03 | 2.40 (1.36) | 0.08 | |
Sleep disturbances | −0.95 (0.50) | 0.06 | −0.56 (0.40) | 0.17 | |
Unsaturated fat | PSQI total score | −0.07 (0.03) | 0.02 | −0.02 (0.02) | 0.35 |
Sleep onset latency | −0.48 (0.19) | 0.01 | −0.43 (0.17) | 0.01 | |
Sleep efficiency | 0.13 (0.10) | 0.22 | 0.09 (0.10) | 0.38 | |
Sleep disturbances | −0.05 (0.04) | 0.19 | −0.01 (0.03) | 0.75 | |
Saturated fat | PSQI total score | −0.004 (0.05) | 0.93 | 0.04 (0.04) | 0.35 |
Sleep onset latency | −0.47 (0.33) | 0.16 | −0.46 (0.30) | 0.14 | |
Sleep efficiency | −0.09 (0.18) | 0.63 | −0.07(0.17) | 0.70 | |
Sleep disturbances | 0.06 (0.06) | 0.33 | 0.10 (0.05) | 0.05 | |
Plant protein | PSQI total score | −0.14 (0.09) | 0.14 | −0.20 (0.07) | <0.01 |
Sleep onset latency | −0.06 (0.59) | 0.92 | −0.15 (0.54) | 0.78 | |
Sleep efficiency | 0.99 (0.31) | <0.01 | 0.93 (0.30) | <0.01 | |
Sleep disturbances | −0.13 (0.11) | 0.26 | −0.18 (0.09) | <0.05 | |
Animal protein | PSQI total score | −0.02 (0.04) | 0.66 | −0.003 (0.03) | 0.92 |
Sleep onset latency | −0.16 (0.26) | 0.54 | −0.09 (0.24) | 0.71 | |
Sleep efficiency | 0.02 (0.14) | 0.87 | −0.01 (0.13) | 0.92 | |
Sleep disturbances | −0.05 (0.05) | 0.28 | −0.03 (0.04) | 0.47 | |
Fiber | PSQI total score | −0.06 (0.04) | 0.08 | −0.09 (0.03) | <0.01 |
Sleep onset latency | −0.20 (0.22) | 0.38 | −0.18 (0.20) | 0.39 | |
Sleep efficiency | 0.33 (0.12) | <0.01 | 0.34 (0.11) | <0.01 | |
Sleep disturbances | −0.07 (0.04) | 0.09 | −0.09 (0.03) | <0.01 | |
Alcohol | PSQI total score | 0.05 (0.03) | 0.06 | 0.04 (0.02) | 0.05 |
Sleep onset latency | 0.25 (0.18) | 0.17 | 0.33 (0.17) | <0.05 | |
Sleep efficiency | −0.16 (0.10) | 0.11 | −0.15 (0.09) | 0.10 | |
Sleep disturbances | 0.05 (0.03) | 0.12 | 0.03 (0.03) | 0.37 |
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Zuraikat, F.M.; Makarem, N.; St-Onge, M.-P.; Xi, H.; Akkapeddi, A.; Aggarwal, B. A Mediterranean Dietary Pattern Predicts Better Sleep Quality in US Women from the American Heart Association Go Red for Women Strategically Focused Research Network. Nutrients 2020, 12, 2830. https://doi.org/10.3390/nu12092830
Zuraikat FM, Makarem N, St-Onge M-P, Xi H, Akkapeddi A, Aggarwal B. A Mediterranean Dietary Pattern Predicts Better Sleep Quality in US Women from the American Heart Association Go Red for Women Strategically Focused Research Network. Nutrients. 2020; 12(9):2830. https://doi.org/10.3390/nu12092830
Chicago/Turabian StyleZuraikat, Faris M., Nour Makarem, Marie-Pierre St-Onge, Huaqing Xi, Alekha Akkapeddi, and Brooke Aggarwal. 2020. "A Mediterranean Dietary Pattern Predicts Better Sleep Quality in US Women from the American Heart Association Go Red for Women Strategically Focused Research Network" Nutrients 12, no. 9: 2830. https://doi.org/10.3390/nu12092830
APA StyleZuraikat, F. M., Makarem, N., St-Onge, M. -P., Xi, H., Akkapeddi, A., & Aggarwal, B. (2020). A Mediterranean Dietary Pattern Predicts Better Sleep Quality in US Women from the American Heart Association Go Red for Women Strategically Focused Research Network. Nutrients, 12(9), 2830. https://doi.org/10.3390/nu12092830