Long Sleep Duration and Stroke—Highly Linked, Poorly Understood
Abstract
:1. Introduction
2. Long Sleep Duration and Stroke Prevalence
3. Long Sleep Duration and Stroke Incidence
4. Long Sleep Duration and Stroke Mortality
5. Long Sleep Duration and Stroke—Links
5.1. Diabetes
5.2. Atrial Fibrillation
5.3. Arterial Stiffness
5.4. Inflammation
5.5. Blood Pressure Variability
6. Long Sleep Duration and Stroke—Genetic Studies
7. Long Sleep Duration and Stroke—Mediating Factors
8. Sleep Duration and Sleep Quality
9. Evidence Supporting Long Sleep Duration as a Risk Factor for Stroke
10. Evidence Supporting Long Sleep Duration as a Marker for Stroke
11. Clinical Implications
12. Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study | Sample Size | Sleep Duration (Hours/Day) | Long Sleeper % | Odds Ratio (95% CI) | Country | ||
---|---|---|---|---|---|---|---|
Long | Short | Long | Short | ||||
2019, Guo [19] | 18,670 | ≥10 | <6 | 9.5% | 1.63 (1.30–2.04) | 1.19 (0.86–1.66) | China |
2013, Liu [20] | 54,269 | ≥10 | ≤6 | 4.1% | 2.23 (1.71–2.92) | 1.22 (1.03–1.45) | USA |
2018, Ke [21] | 10,657 | >9 | <5 | 4.7% | 2.13 (1.34–3.39) | 1.22 (0.68–2.19) | China |
2018, Seixas [13] | 288,888 | ≥9 | <7 | 8.7% | 1.80 | 1.29 | USA |
2020, Krittanawong [14] | 32,152 | >9 | <7 | 3.3% | 1.81 (1.37–2.34) | 1.45 (1.23–1.70) | USA |
2017, Wang [22] | 39,515 | ≥9 | <6 | 46.8% | 1.35 (1.05–1.73) | 1.24 (0.53–2.93) | China |
2014, Fang [23] | 154,599 | ≥9 | ≤6 | 9.0% | 1.80 (1.63–1.99) | 1.20 (1.11–1.29) | USA |
2012, Altman [7] | 30,934 | ≥10 | <5 | 3.8% | 1.86 (1.21–2.52) | 2.51 (0.97–4.06) | USA |
2018, Hu [24] | 15,269 | >8 | <6 | 13.8% | 1.86 (1.29–2.69) | 1.41 (0.92–2.15) | China |
2012, Magee [25] | 218,155 | ≥9 | <6 | 19.7% | 1.50 (1.38–1.62) | 1.54 (1.36–1.75) | Australia |
2019, Nuyujukian [26] | 14,536 | ≥8 | ≤6 | 39.3% | 1.36 | 1.43 | USA |
2022, Liu [27] | 5065 | >9 | <7 | 19.6% | 2.11 (1.39–3.19) | 1.67 (0.91–3.07) | China |
2016, Akinseye [28] | 26,364 | ≥9 | ≤6 | 14% | 1.46 (1.16–1.84) | 1.15 (0.95–1.40) | USA |
2020, Hu [29] | 10,516 | >8 | <6 | 18.8% | 1.59 (1.07–2.38) | 1.21 (0.73–2.01) | China |
2010, Sabanayagam [30] | 30,397 | ≥9 | ≤5 | 8.8% | 2.22 (1.69–2.91) | 2.01 (1.50–2.70) | USA |
2017, Pergola [31] | 5101 | ≥10 | <5 | 2.8% | 7.17 (3.28–15.65) | 2.41 (1.14–5.11) | USA |
2021, Li [32] | 4785 | >8 | <7 | 24% | 1.86 (1.08–3.21) | 2.11 (1.30–3.44) | China |
2016, Wen [33] | 880 | ≥9 | <7 | 6.6% | 2.00 (1.16–3.46) | 0.94 (0.59–1.49) | China |
2022, Wang [34] | 10,442 | ≥8 | <6 | 33.0% | 1.31 (0.86–1.99) | 1.95 (1.19–3.19) | USA |
2013, Merikanto [35] | 6258 | ≥9 | ≤6 | 8.0% | 1.7 (0.9–3.2) | 1.9 (1.2–2.9) | Finland |
2021, Li [36] | 4334 | >8 | <7 | 9.1% | 1.58 (0.92–2.70) | 1.81 (1.10–2.97) | China |
2022, Yang [37] | 37,341 | ≥9 | <6 | 10.8% | 1.11 (0.97–1.27) | 1.26 (1.09–1.46) | China |
2018, Kim [38] | 17,601 | ≥9 | ≤6 | 7% | 1.52 (0.93–2.48) | 1.05 (0.79–1.39) | Republic of Korea |
2016, Kim [39] | 1470 | ≥9 | ≤5 | 5.6% | 5.00 (2.18–11.47) | 0.67 (0.36–1.24) | Republic of Korea |
Study | Sample Size | Sleep Duration (Hours/Day) | Long Sleeper % | Follow-Up Duration (Years) | Hazard Ratio (95% CI) | Country | ||
---|---|---|---|---|---|---|---|---|
Long | Short | Long | Short | |||||
2011, Kronholm [41] | 24,025 | ≥10 | ≤5 | 2.6% | 29–34 | 1.4 | 1.15 | Finland |
2020, Zhou [42] | 31,750 | ≥9 | <6 | 23.9% | 6.2 | 1.23 (1.07–1.41) | 1.10 (0.69–1.75) | China |
2008, Chen [40] | 93,175 | ≥9 | ≤5 | 4.6% | 7.5 | 1.70 (1.32–2.21) | 1.14 (0.97–1.33) | USA |
1997, Qureshi [43] | 7844 | >8 | <6 | 8.5% | 10 | 1.5 (1.1–2.0) | 1.0 (0.7–1.5) | USA |
2021, Joundi [16] | 82,795 | ≥10 | <4 | 1.2% | 9.1 | 2.26 (1.02–5.00) | 1.38 (0.63–3.02) | Canada |
2020, Titova [44] | 79,881 | ≥9 | <7 | 6.1% | 14.6 | 1.12 (1.03–1.22) | 1.04 (0.99–1.09) | Sweden |
2012, von Ruesten [45] | 23,620 | ≥9 | <6 | 7.5% | 7.8 | 1.65 (1.00–2.73) | 2.06 (1.18–3.59) | Europe |
2016, Song [46] | 95,023 | >8 | <6 | 1.7% | 7.9 | 1.29 (1.01–1.64) | 0.92 (0.81–1.05) | China |
2020, Butler [47] | 4522 | ≥9 | <6 | 4.9% | 12 | 1.32 (1.02–1.70) | 1.56 (1.06–2.30) | USA |
2018, Li [48] | 1928 | ≥9 | <7 | 10.2% | 4.94 | 2.24 (1.05–4.79) | 1.27 (0.75–2.16) | China |
2015, Leng [49] | 9692 | >8 | <6 | 10% | 9.5 | 1.46 (1.08–1.98) | 1.18 (0.91–1.53) | UK |
2020, Ji [50] | 27,712 | >8 | <6 | 18.9% | 7 | 1.40 (1.08–1.75) | 1.63 (1.23–2.11) | China |
2020, Li [51] | 2687 | >8 | <6 | 30.3% | 3.7 | 1.79 (1.22–2.63) | 1.20 (0.72–2.00) | China |
2018, Petrov [52] | 16,733 | ≥9 | <6 | 6.8% | 6.1 | 1.71 (1.06–2.76) | 1.58 (0.90–2.79) | USA |
2020, Ye [53] | 8968 | >9 | <6 | 9.4% | 3 | 2.01 (1.18–3.43) | 2.25 (0.97–5.20) | China |
2015, Helbig [54] | 15,746 | ≥10 | ≤5 | 4% | 14 | 1.38 (0.98–1.94) | 1.36 (0.95–1.94) | Germany |
2011, Hamazaki [55] | 2282 | ≥8 | <6 | 22.3% | 14 | 2.25 (0.91–5.57) | 1.84 (0.23–4.90) | Japan |
2013, Westerlund [56] | 41,192 | ≥8 | ≤5 | 24.2% | 13.2 | 0.87 (0.72–1.04) | 1.05 (0.80–1.37) | Sweden |
2014, Ruiter Petrov [57] | 5666 | ≥9 | <6 | 5.9% | 3 | 0.96 (0.45–2.05) | 1.55 (0.82–2.91) | USA |
2010, Amagai [58] | 11,367 | ≥9 | <6 | 15.1% | 10.7 | 1.39 (0.92–2.10) | 2.00 (0.93–4.31) | Japan |
2023, Han [59] | 18,876 | ≥10 | ≤5 | 3.6% | 11.5 | 2.08 (1.44–3.01) | 1.70 (1.23–2.35) | UK |
2022, Cheng [60] | 261,297 | >9 | <7 | 2.4% | 10.9 | 1.22 (1.07–1.38) | 1.18 (1.11–1.25) | UK |
Study | Participants | Follow-Up (Years) | Hazard Ratio (95% CI) | Cohorts | |
---|---|---|---|---|---|
Long | Short | ||||
2011, Cappuccio [64] | 474,684 | 6.9–25 | 1.65 (1.45–1.87) | 1.15 (1.00–1.31) | 24 |
2015, Leng [49] | 559,252 | 7.5–35 | 1.45 (1.30–1.62) | 1.15 (1.07–1.24) | 11 |
2016, Li [63] | 136,110 | 3–18 | 1.53 (1.40–1.66) | 1.19 (1.05–1.36) | 16 |
2017, Yin [61] | 301,992 | 2.3–34 | 1.45 (1.30–1.62) | 1.09 (0.99–1.19) | 20 |
2017, He [62] | 528,653 | 7.8–14.7 | 1.37 (1.23–1.54) | 1.10 (0.97–1.24) | 16 |
2019, Krittanawong [65] | 621,860 | 4–22 | 1.48 (1.31–1.68) | 1.32 (1.18–1.47) | 18 |
2022, Wang [66] | 248,868 | 7–18 | 1.71 (1.50–1.95) | 1.33 (1.19–1.49) | 27 |
Study | Sample Size | Sleep Duration (Hours/Day) | Long Sleeper % | Follow-Up Duration (Years) | Hazard Ratio (95% CI) | Country | ||
---|---|---|---|---|---|---|---|---|
Long | Short | Long | Short | |||||
2013, Kakizaki [68] | 49,256 | ≥10 | ≤6 | 7.9% | 10.8 | 1.51 (1.24–1.85) | 1.05 (0.84–1.30) | Japan |
2013, Kim [17] | 135,685 | ≥9 | ≤5 | 8.3% | 12.9 | 1.35 (1.03–1.75) | 1.02 (0.74–1.40) | US |
2015, Cai [18] | 113,138 | ≥10 | ≤5 | 3.8% | 7.1 | 2.35 (1.78–3.09) | 0.91 (0.70–1.18) | China |
2016, Kawachi [69] | 27,896 | ≥9 | ≤6 | 9% | 16 | 1.51 (1.16–1.97) | 0.77 (0.59–1.01) | Japan |
2014, Pan [67] | 63,257 | ≥9 | ≤5 | 7% | 14.7 | 1.54 (1.28–1.85) | 1.25 (1.05–1.50) | Singapore |
2009, Ikehara [70] | 110,792 | ≥10 | ≤4 | 4% | 14.3 | 1.66 (1.31–2.08) | 1.56 (0.82–2.94) | Japan |
2023, Zhou [71] | 27,254 | ≥9 | ≤5 | 10.2% | 14.3 | 1.37 (1.07–1.75) | 1.27 (1.01–1.59) | China |
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Cai, C.; Atanasov, S. Long Sleep Duration and Stroke—Highly Linked, Poorly Understood. Neurol. Int. 2023, 15, 764-777. https://doi.org/10.3390/neurolint15030048
Cai C, Atanasov S. Long Sleep Duration and Stroke—Highly Linked, Poorly Understood. Neurology International. 2023; 15(3):764-777. https://doi.org/10.3390/neurolint15030048
Chicago/Turabian StyleCai, Chumeng, and Strahil Atanasov. 2023. "Long Sleep Duration and Stroke—Highly Linked, Poorly Understood" Neurology International 15, no. 3: 764-777. https://doi.org/10.3390/neurolint15030048
APA StyleCai, C., & Atanasov, S. (2023). Long Sleep Duration and Stroke—Highly Linked, Poorly Understood. Neurology International, 15(3), 764-777. https://doi.org/10.3390/neurolint15030048