Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort

Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participa...
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Autor*in:	Jingyi Zhang [verfasserIn] Lan Chen [verfasserIn] Shiyu Zhang [verfasserIn] Miao Cai [verfasserIn] Hongtao Zou [verfasserIn] Michael G. Vaughn [verfasserIn] Maya Tabet [verfasserIn] Zhengmin (Min) Qian [verfasserIn] Hualiang Lin [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	cardiovascular multimorbidity multistate model sleep patterns

Übergeordnetes Werk:	In: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease - Wiley, 2012, 12(2023), 19
Übergeordnetes Werk:	volume:12 ; year:2023 ; number:19

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1161/JAHA.123.029463

Katalog-ID:	DOAJ090796314

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520			\|a Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases.
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700	0		\|a Hongtao Zou \|e verfasserin \|4 aut
700	0		\|a Michael G. Vaughn \|e verfasserin \|4 aut
700	0		\|a Maya Tabet \|e verfasserin \|4 aut
700	0		\|a Zhengmin (Min) Qian \|e verfasserin \|4 aut
700	0		\|a Hualiang Lin \|e verfasserin \|4 aut
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allfields	10.1161/JAHA.123.029463 doi (DE-627)DOAJ090796314 (DE-599)DOAJa1d06909a15a4008bdb1714d37e789b7 DE-627 ger DE-627 rakwb eng RC666-701 Jingyi Zhang verfasserin aut Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases. cardiovascular multimorbidity multistate model sleep patterns Diseases of the circulatory (Cardiovascular) system Lan Chen verfasserin aut Shiyu Zhang verfasserin aut Miao Cai verfasserin aut Hongtao Zou verfasserin aut Michael G. Vaughn verfasserin aut Maya Tabet verfasserin aut Zhengmin (Min) Qian verfasserin aut Hualiang Lin verfasserin aut In Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease Wiley, 2012 12(2023), 19 (DE-627)688605427 (DE-600)2653953-6 20479980 nnns volume:12 year:2023 number:19 https://doi.org/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/article/a1d06909a15a4008bdb1714d37e789b7 kostenfrei https://www.ahajournals.org/doi/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/toc/2047-9980 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 19
spelling	10.1161/JAHA.123.029463 doi (DE-627)DOAJ090796314 (DE-599)DOAJa1d06909a15a4008bdb1714d37e789b7 DE-627 ger DE-627 rakwb eng RC666-701 Jingyi Zhang verfasserin aut Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases. cardiovascular multimorbidity multistate model sleep patterns Diseases of the circulatory (Cardiovascular) system Lan Chen verfasserin aut Shiyu Zhang verfasserin aut Miao Cai verfasserin aut Hongtao Zou verfasserin aut Michael G. Vaughn verfasserin aut Maya Tabet verfasserin aut Zhengmin (Min) Qian verfasserin aut Hualiang Lin verfasserin aut In Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease Wiley, 2012 12(2023), 19 (DE-627)688605427 (DE-600)2653953-6 20479980 nnns volume:12 year:2023 number:19 https://doi.org/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/article/a1d06909a15a4008bdb1714d37e789b7 kostenfrei https://www.ahajournals.org/doi/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/toc/2047-9980 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 19
allfields_unstemmed	10.1161/JAHA.123.029463 doi (DE-627)DOAJ090796314 (DE-599)DOAJa1d06909a15a4008bdb1714d37e789b7 DE-627 ger DE-627 rakwb eng RC666-701 Jingyi Zhang verfasserin aut Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases. cardiovascular multimorbidity multistate model sleep patterns Diseases of the circulatory (Cardiovascular) system Lan Chen verfasserin aut Shiyu Zhang verfasserin aut Miao Cai verfasserin aut Hongtao Zou verfasserin aut Michael G. Vaughn verfasserin aut Maya Tabet verfasserin aut Zhengmin (Min) Qian verfasserin aut Hualiang Lin verfasserin aut In Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease Wiley, 2012 12(2023), 19 (DE-627)688605427 (DE-600)2653953-6 20479980 nnns volume:12 year:2023 number:19 https://doi.org/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/article/a1d06909a15a4008bdb1714d37e789b7 kostenfrei https://www.ahajournals.org/doi/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/toc/2047-9980 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 19
allfieldsGer	10.1161/JAHA.123.029463 doi (DE-627)DOAJ090796314 (DE-599)DOAJa1d06909a15a4008bdb1714d37e789b7 DE-627 ger DE-627 rakwb eng RC666-701 Jingyi Zhang verfasserin aut Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases. cardiovascular multimorbidity multistate model sleep patterns Diseases of the circulatory (Cardiovascular) system Lan Chen verfasserin aut Shiyu Zhang verfasserin aut Miao Cai verfasserin aut Hongtao Zou verfasserin aut Michael G. Vaughn verfasserin aut Maya Tabet verfasserin aut Zhengmin (Min) Qian verfasserin aut Hualiang Lin verfasserin aut In Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease Wiley, 2012 12(2023), 19 (DE-627)688605427 (DE-600)2653953-6 20479980 nnns volume:12 year:2023 number:19 https://doi.org/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/article/a1d06909a15a4008bdb1714d37e789b7 kostenfrei https://www.ahajournals.org/doi/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/toc/2047-9980 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 19
allfieldsSound	10.1161/JAHA.123.029463 doi (DE-627)DOAJ090796314 (DE-599)DOAJa1d06909a15a4008bdb1714d37e789b7 DE-627 ger DE-627 rakwb eng RC666-701 Jingyi Zhang verfasserin aut Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases. cardiovascular multimorbidity multistate model sleep patterns Diseases of the circulatory (Cardiovascular) system Lan Chen verfasserin aut Shiyu Zhang verfasserin aut Miao Cai verfasserin aut Hongtao Zou verfasserin aut Michael G. Vaughn verfasserin aut Maya Tabet verfasserin aut Zhengmin (Min) Qian verfasserin aut Hualiang Lin verfasserin aut In Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease Wiley, 2012 12(2023), 19 (DE-627)688605427 (DE-600)2653953-6 20479980 nnns volume:12 year:2023 number:19 https://doi.org/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/article/a1d06909a15a4008bdb1714d37e789b7 kostenfrei https://www.ahajournals.org/doi/10.1161/JAHA.123.029463 kostenfrei https://doaj.org/toc/2047-9980 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 19
language	English
source	In Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease 12(2023), 19 volume:12 year:2023 number:19
sourceStr	In Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease 12(2023), 19 volume:12 year:2023 number:19
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	cardiovascular multimorbidity multistate model sleep patterns Diseases of the circulatory (Cardiovascular) system
isfreeaccess_bool	true
container_title	Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
authorswithroles_txt_mv	Jingyi Zhang @@aut@@ Lan Chen @@aut@@ Shiyu Zhang @@aut@@ Miao Cai @@aut@@ Hongtao Zou @@aut@@ Michael G. Vaughn @@aut@@ Maya Tabet @@aut@@ Zhengmin (Min) Qian @@aut@@ Hualiang Lin @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	688605427
id	DOAJ090796314
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ090796314</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414013234.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240412s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1161/JAHA.123.029463</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ090796314</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJa1d06909a15a4008bdb1714d37e789b7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC666-701</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Jingyi Zhang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. 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callnumber-first	R - Medicine
author	Jingyi Zhang
spellingShingle	Jingyi Zhang misc RC666-701 misc cardiovascular multimorbidity misc multistate model misc sleep patterns misc Diseases of the circulatory (Cardiovascular) system Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort
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topic_title	RC666-701 Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort cardiovascular multimorbidity multistate model sleep patterns
topic	misc RC666-701 misc cardiovascular multimorbidity misc multistate model misc sleep patterns misc Diseases of the circulatory (Cardiovascular) system
topic_unstemmed	misc RC666-701 misc cardiovascular multimorbidity misc multistate model misc sleep patterns misc Diseases of the circulatory (Cardiovascular) system
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title	Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort
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title_full	Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort
author_sort	Jingyi Zhang
journal	Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
journalStr	Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
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author_browse	Jingyi Zhang Lan Chen Shiyu Zhang Miao Cai Hongtao Zou Michael G. Vaughn Maya Tabet Zhengmin (Min) Qian Hualiang Lin
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doi_str_mv	10.1161/JAHA.123.029463
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title_sort	associations of sleep patterns with dynamic trajectory of cardiovascular multimorbidity and mortality: a multistate analysis of a large cohort
callnumber	RC666-701
title_auth	Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort
abstract	Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases.
abstractGer	Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases.
abstract_unstemmed	Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases.
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title_short	Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort
url	https://doi.org/10.1161/JAHA.123.029463 https://doaj.org/article/a1d06909a15a4008bdb1714d37e789b7 https://www.ahajournals.org/doi/10.1161/JAHA.123.029463 https://doaj.org/toc/2047-9980
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up_date	2024-07-03T16:43:13.349Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ090796314</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414013234.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240412s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1161/JAHA.123.029463</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ090796314</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJa1d06909a15a4008bdb1714d37e789b7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC666-701</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Jingyi Zhang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality. Methods and Results This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or <8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM. Conclusions Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. 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Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort

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