International Journal of Cardiology 176 (2014) 1044–1047
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Letter to the Editor
Insomnia and risk of cardiovascular disease: A meta-analysis of cohort studies Min Li, Xiao-Wei Zhang, Wen-Shang Hou, Zhen-Yu Tang ⁎ Department of Neurology, The Second Affiliated Hospital, School of Medicine, Nanchang University, Nanchang 330006, Jiangxi Province, People's Republic of China
a r t i c l e
i n f o
Article history: Received 1 June 2014 Accepted 26 July 2014 Available online 12 August 2014 Keywords: Insomnia Cardiovascular Meta-analysis
from studies included by previous meta-analysis were limited to December 2011. To our knowledge, some new cohort studies on the association between insomnia and risk of CVD have been published since than [8–13]. Therefore, we carried out a meta-analysis of cohort studies to quantitatively estimate whether insomnia independently increases the risk of CVD, using the most recent data. This meta-analysis was performed and reported according to the standard criteria of the Meta-analyses of Observational Studies in Epidemiology (MOOSE) conference statement [15]. A systematic search of published articles (through 17 May 2014) was performed by using electronic databases including PubMed, Cochrane Library, and ISI Web of Science databases. We used the following keywords: insomnia, sleep*,
Insomnia, the most prevalent sleep disorder, defined as a subjective feeling of having difficulty initiating or maintaining sleep or having a feeling of non-restorative sleep [1]. According to the definition, insomnia prevalence varies from 6% to an average of 33% in more than 50 epidemiological studies [2]. In addition, insomnia affects 10% to 30% of the general population in the United States [3], it has been estimated that the annual expenditure on insomnia is estimated at 92.5 to 107.5 billion [4], this creates a major public health burden. From the public health perspective, the issue of sleep problems is important. During the last years, insomnia was of particular concern because it could increase the risk of depression [5], hypertension [6], and metabolic syndrome [7]. Meanwhile, a considerable number of cohort studies showed a significant association between insomnia and cardiovascular diseases (CVDs) [8–13]. Nevertheless, whether insomnia independently increases myocardial infarction (MI) risks, stroke risks, and coronary heart disease (CHD) risks specifically, or whether insomnia independently increases CVD mortality, results to date have been inconsistent. Meta-analysis might help to resolve this inconsistency. A recent published meta-analysis of 13 prospective studies showed that insomnia was associated with an increased risk of fatal and/or non-fatal from CVD (pooled relative risk = 1.45, 95% confidence interval: 1.29–1.62) [14]. However, that meta-analysis found insufficient evidence on the association between insomnia and risk of individual types of CVD, including MI, stroke, CHD, and cardiovascular mortality. Moreover, the data
⁎ Corresponding author at: Department of Neurology, The Second Affiliated Hospital, Nanchang University, No. 1, Minde Road, Nanchang 330006, Jiangxi, People's Republic of China. Tel.: +86 791 86311759; fax: +86 791 86292217. E-mail address: [email protected] (Z.-Y. Tang).
http://dx.doi.org/10.1016/j.ijcard.2014.07.284 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
Fig. 1. Flow chart of study selection.
Table 1 Characteristic of included cohort studies. Publication, (year)
Country
Cohort
Sex
Sample size (n)
Outcome(s)
Follow-up. (year)
Age, (year)
Outcome assessment
Insomnia assessment
Exposure categories
Adjusted variables
Eaker et al [17]
1992
USA
Framingham Study
F
749
20
45–64
Yes/No
Age, SBP, TC/HDL, diabetes, cigarettes, BMI
1998
USA
FM
2960
3
65–101
TFA
2002
Sweden
Piedmont Health Survey County of Dalarna registry
Clinical manifestations and hospital records ICD-9
TFA
Schwartz et al [18] Mallon et al [19]
MI, CVD mortality MI
FM
1870
CVD mortality
12
45–65
ICD-9
DIS
Most of the time/Never Yes/No
Elwood et al [20] Phillips et al [21]
2006
UK
M
1874
CHD, Stroke
5
55–69
ICD-10
Insomnia
Frequent/None
2007
USA
Caerphilly cohort study ARIC study
FM
11,863
CHD
6.3
44–64
Hospital records and standardized diagnoses
Yes/No
Meisinger et al [22]
2007
Germany
MONICA/KORA
FM
6896
MI
10.1
45–75
ICD-9, ESC and ACC criteria
TFA/sleep continuity disturbance/nonrestorative sleep DIS/TFA
Age, sex, race, education, prescriptions, selfrated health, depression Age, not married, living alone, smoking habit, BMI N 28, HT, cardiac disease, respiratory disease, diabetes, joint pain, GID, depression, sleep duration, snoring, sleeping pill usage Age, social class, smoking habit, alcohol consumption, BMI, neck circumference Age, sex, race, education, BMI, depression, lung function, smoking habit, diabetes
Suzuki et al [23]
2009
Japan
Shizuoka study
FM
11,395
CVD mortality
5.3
65–85
ICD-10
DFA
Yes/No
Chien et al [24]
2010
China
Chin-Shan community study
FM
3430
CVD mortality
15.9
N35
Official death certificates and househouse visits
Frequency of insomnia
Nearly every day/No
Chandola et al [25]
2010
UK
Whitehall II
FM
10,308
MI, CVD mortality
15
35–55
ICD-10
Restless, disturbed nights
More than usual/No
Hulvej Rod et al [26]
2011
France
GAZEL cohort study
M
12,524
CVD mortality
19
36–52
ICD-9, ICD-10
DFA
Yes/No
Laugsand et al [27]
2011
Norway
Nord-Trondelag Health Study
FM
52,610
MI
11.4
≥65
ESC and ACC criteria
DIS
Almost every night/Never
Westerlund et al [8]
2013
Sweden
Nation March Cohort study
FM
41,192
CVD mortality
13.2
52.8
ICD-9, ICD-10
DFA
Mostly/always/ Never
Sands-Lincoln et al [9]
2013
USA
Women's Health Initiative
F
86,329
CHD, CVD mortality
10.3
50–79
medical records, death certificates
WHIIRS
WHIIRS ≥ 9/b3
Hulvej Rod et al [10] Canivet et al [11]
2014
France
Whitehall II
FM
9098
22
35–55
ICD-9, ICD-10
2014
Sweden
Malmo Diet and Cancer study
FM
13,277
CVD mortality CVD mortality
13
45–64
ICD-9, ICD-10
Restless, disturbed nights DSM-IV
More than usual/Not at all Yes/No
Li et al [12]
2014
USA
Health Professionals Follow-Up study
M
23,447
CVD mortality
6
68.6
ICD-8
DFA
Most of the time/Never
Wu et al [13]
2014
China
NHIRD
FM
21,438
Stroke
4
52
ICD-9
ICD-9
Yes/No
Yes/No
Age, survey, BMI, education, dyslipidemia, alcohol intake, parental history of MI, physical activity, smoking habit, HT, diabetes Age, sex, BMI, smoking habit, alcohol, physical activity, socioeconomic status, mental health, HT, diabetes Age, sex, BMI, smoking habit, alcohol, marital status, education, occupation, exercise, family history of CHD, HT, diabetes, lipids, glucose, uric acid Age, sex, ethnicity, employment grade, car access, housing tenure, self-rated health status, cholesterol, HT, BMI, diabetes, smoking habit, alcohol, exercise, fruit and vegetable consumption Age, socioeconomic status, marital status, smoking habit, alcohol, BMI, night work, HT, diabetes Age, sex, education, marital status, shift work, SBP, cholesterol, diabetes, BMI, physical activity, smoking habit, depression, anxiety Age, sex, education, employment status, smoking, alcohol, snoring, work schedule, depressive symptoms, self-rated health, physical activity, BMI, diabetes, lipid disturbance, HT Age, race, education, income, smoking, BMI, physical activity, alcohol intake, depression, diabetes, high blood pressure, hyperlipidemia, comorbid conditions Age, employments grade, ethnicity, marital status
M. Li et al. / International Journal of Cardiology 176 (2014) 1044–1047
Author
Age,socieconomic position, marital status, social participation, smoking status, low physical activity, obesity, HT, diabetes mellitus, neck, shoulder, lumbar pain Age, ethnicity, smoking status, alcohol drinking, BMI, physical activity, alternate healthy eating index, marriage status, living status, regular use of aspirin, Age, sex, comorbidities, socioeconomic status, geographic region
1045
TFA: trouble falling asleep; DFA: difficulty initiating sleep; DIS: difficulty initiating sleep; ICD: International Classification of Diseases; CVD: cardiovascular disease; CHD: coronary heart disease; MI: myocardial infarction; F: female; M: male; and WHIIRS: The Women's Health Initiative Insomnia Rating Scale; NHIRD. National Health Insurance Research Database; BMI: body mass index; SBP: systolic blood pressure; HT: hypertension; TC: total cholesterol; HDL: high density lipoprotein; GID: gastrointestinal disease. ESC: the European Society of Cardiology; and ACC: American College of Cardiology.
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M. Li et al. / International Journal of Cardiology 176 (2014) 1044–1047
• Study
RR (95% CI)
Eaker 1992
3.90 (1.70, 9.00)
Mallon(male) 2002
3.10 (1.50, 6.30)
Suzuki 2009
1.02 (0.73, 1.43)
Chien 2010
1.78 (1.03, 3.08)
1.16 (0.82, 1.63)
Chandola 2010
1.36 (1.10, 1.68)
Meisinger(female) (2007)
1.30 (0.81, 2.06)
Hulvej Rod 2011
1.18 (0.67, 2.06)
Chandola (2010)
1.36 (1.10, 1.68)
Westerlund 2013
0.91 (0.73, 1.14)
Sands-Lincoln 2013
1.11 (1.03, 2.00)
Laugsand(male) (2011)
1.27 (0.91, 1.78)
Hulvej Rod(male) 2014
1.08 (0.70, 1.66)
Laugsand(female) (2011)
1.70 (1.29, 2.23)
Hulvej Rod(female) 2014
3.04 (1.42, 6.51)
Overall (I-squared = 38.4%, p = 0.136)
1.41 (1.18, 1.67)
Canivet(male) 2014
1.00 (0.90, 1.20)
Canivet(female) 2014
1.40 (1.20, 1.60)
Li 2014
1.55 (1.19, 2.04)
Overall (I-squared = 73.1%, p = 0.000)
1.33 (1.13, 1.57)
Study
RR (95% CI)
Eaker (1992)
3.90 (1.70, 9.00)
Schwartz (1998)
1.22 (0.77, 1.92)
Meisinger(male) (2007)
0.1
1
Decreased risk
Increased risk
9
•
0.1
sleep disorder, sleep disturbance, sleep initiation, disorders of initiating and maintaining sleep, poor sleep quality, sleep complaints, stroke, coronary heart disease, coronary artery disease, coronary stenosis, myocardial infarction, myocardial ischemia, cerebrovascular disorders, cardiovascular disease, heart failure, coronary thrombosis, prospective studies, cohort studies, longitudinal studies, and follow-up studies. There were no language restrictions. Studies were considered eligible if they fulfilled all of the following criteria: (1) the study of adult patients had a cohort design; (2) the exposed subject was a patient with insomnia; (3) the reported quantitative estimates of the multivariateadjusted relative risk (RRs) and 95% confidence intervals (CIs) for CVD outcomes associated with insomnia, hazard ratio/odds ratios were considered equivalent to RRs; (4) the study has a duration longer than 1 year of follow-up; (5) the evaluated subjects are free of CVD at baseline; and (6) the study reports clear definitions of method used to assess sleep complaints. Studies were excluded if they met the following criteria: (1) the study design did not include a cohort (for example, cross-sectional and retrospective case–control studies); (2) the unadjusted RRs and 95% CIs were reported (for example, just adjusted age or sex); and (3) the study has a duration shorter than 1 year of follow-up. The RRs were pooled using the random-effects model [16]. All the statistical analyses were performed in STATA version 11 (StataCorp LP, College Station, TX). p values were 2-sided and p b 0.05 was considered as statistically significant.
RR (95% CI)
Study
Coronary heart disease Elwood 2006
1.47 (0.98, 2.21)
Phillips 2007
1.50 (1.10, 2.00)
Sands-Lincoln 2013
1.19 (1.08, 1.30)
Subtotal (I-squared = 31.3%, p = 0.233)
1.28 (1.10, 1.50)
1 Decreased risk
Fig. 2. Association between insomnia and risk of myocardial infarction.
9 Increased risk
Fig. 4. Association between insomnia and risk of cardiovascular mortality.
Seventeen cohort studies with a total of 311,260 participants were included in this meta-analysis [8–13,17–27] (Fig. 1). The main characteristics of studies in the meta-analysis were presented in Table 1. A total of seven comparisons (two studies did have sex specific data) investigated the association between insomnia and risk of MI [17,18,22, 25,27]. The ascertainment of insomnia and ascertainment of CVD outcomes varied across studies. Pooling all 7 comparisons, insomnia was associated with a significantly increased risk of MI (RR, 1.41; 95% CI, 1.18 to 1.67; p = 0.000) (Fig. 2). Fig. 3 showed the results from random-effects models combining the RRs for CHD and stroke. The overall combined RRs in relation to insomnia were 1.28 (95% CI, 1.10 to 1.50; p = 0.002) for CHD and 1.55 (1.39 to 1.72; p = 0.000) for stroke, respectively. Thirteen comparisons (two studies did have sex specific data) evaluated the association between insomnia and risk of CVD mortality [8–12,17,19,23–26]. Insomnia significantly increased the risk of CVD mortality (RR, 1.33; 95% CI, 1.13 to 1.57; p = 0.001) (Fig. 4). Our meta-analysis of 17 cohort studies provides evidence that insomnia is significantly associated with increased risk of cardiovascular outcomes and mortality after adjustment of established cardiovascular risk factors. For the moment, the mechanisms that underlie this possible association have been reported both by epidemiologic and experimental studies but are not completely understood. Results in metabolic or endocrine changes, through sympathetic activation and elevated levels of inflammatory cytokines, may link the development of poor quality sleep with the pathogenesis of CVD events [28,29]. To efficiently assess the causality of insomnia on CVD events, future research is warranted, especially experimental and clinical studies probing mechanisms underlying the insomnia-mortality associations.
Conflict of interest statement
.
None.
Stroke Elwood 2006
1.75 (1.02, 3.01)
Wu 2014
1.54 (1.38, 1.72)
Subtotal (I-squared = 0.0%, p = 0.650)
1.55 (1.39, 1.72)
Acknowledgments
. •
0.3
Decreased risk
1
Increased risk
3
Fig. 3. Association between insomnia and risk of coronary heart disease and stroke.
ZYT and ML conceived and designed the experiments. WSH, ML and XWZ analyzed the data. ML and ZYT wrote the paper. WSH, XWZ and ZYT performed the literature search and the data extraction. All authors saw and approved the final version of the manuscript. We thank the editors of the International Journal of Cardiology for editing the manuscript.
M. Li et al. / International Journal of Cardiology 176 (2014) 1044–1047
References [1] Buysse DJ. Insomnia. JAMA 2013;309:706–16. [2] Ohayon MM. Epidemiology of insomnia: what we know and what we still need to learn. Sleep Med Rev 2002;6:97–111. [3] Roth T. Insomnia: definition, prevalence, etiology, and consequences. J Clin Sleep Med 2007;3:S7–S10. [4] Stoller MK. Economic effects of insomnia. Clin Ther 1994;16:873–97. [5] Baglioni C, Battagliese G, Feige B, et al. Insomnia as a predictor of depression: a metaanalytic evaluation of longitudinal epidemiological studies. J Affect Disord 2011;135: 10–9. [6] Meng L, Zheng Y, Hui R. The relationship of sleep duration and insomnia to risk of hypertension incidence: a meta-analysis of prospective cohort studies. Hypertens Res 2013;36:985–95. [7] Troxel WM, Buysse DJ, Matthews KA, et al. Sleep symptoms predict the development of the metabolic syndrome. Sleep 2010;33:1633–40. [8] Westerlund A, Bellocco R, Sundstrom J, et al. Sleep characteristics and cardiovascular events in a large Swedish cohort. Eur J Epidemiol 2013;28:463–73. [9] Sands-Lincoln M, Loucks EB, Lu B, et al. Sleep duration, insomnia, and coronary heart disease among postmenopausal women in the Women's Health Initiative. J Womens Health (Larchmt) 2013;22:477–86. [10] Rod NH, Kumari M, Lange T, et al. The joint effect of sleep duration and disturbed sleep on cause-specific mortality: results from the Whitehall II cohort study. PLoS One 2014;9:e91965. [11] Canivet C, Nilsson PM, Lindeberg SI, et al. Insomnia increases risk for cardiovascular events in women and in men with low socioeconomic status: a longitudinal, register-based study. J Psychosom Res 2014;76:292–9. [12] Li Y, Zhang X, Winkelman JW, et al. Association between insomnia symptoms and mortality: a prospective study of U.S. men. Circulation 2014;129:737–46. [13] Wu M, Lin H, Weng S, et al. Insomnia subtypes and the subsequent risks of stroke: report from a nationally representative cohort. Stroke 2014;45:1349–54. [14] Sofi F, Cesari F, Casini A, et al. Insomnia and risk of cardiovascular disease: a metaanalysis. Eur J Prev Cardiol 2014;21:57–64. [15] Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000;283:2008–12.
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[16] DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7: 177–88. [17] Eaker ED, Pinsky J, Castelli WP. Myocardial infarction and coronary death among women: psychosocial predictors from a 20-year follow-up of women in the Framingham Study. Am J Epidemiol 1992;135:854–64. [18] Schwartz SW, Cornoni-Huntley J, Cole SR, et al. Are sleep complaints an independent risk factor for myocardial infarction. Ann Epidemiol 1998;8:384–92. [19] Mallon L, Broman JE, Hetta J. Sleep complaints predict coronary artery disease mortality in males: a 12-year follow-up study of a middle-aged Swedish population. J Intern Med 2002;251:207–16. [20] Elwood P, Hack M, Pickering J, et al. Sleep disturbance, stroke, and heart disease events: evidence from the Caerphilly cohort. J Epidemiol Community Health 2006; 60:69–73. [21] Phillips B, Mannino DM. Do insomnia complaints cause hypertension or cardiovascular disease. J Clin Sleep Med 2007;3:489–94. [22] Meisinger C, Heier M, Lowel H, et al. Sleep duration and sleep complaints and risk of myocardial infarction in middle-aged men and women from the general population: the MONICA/KORA Augsburg cohort study. Sleep 2007;30:1121–7. [23] Suzuki E, Yorifuji T, Ueshima K, et al. Sleep duration, sleep quality and cardiovascular disease mortality among the elderly: a population-based cohort study. Prev Med 2009;49:135–41. [24] Chien KL, Chen PC, Hsu HC, et al. Habitual sleep duration and insomnia and the risk of cardiovascular events and all-cause death: report from a community-based cohort. Sleep 2010;33:177–84. [25] Chandola T, Ferrie JE, Perski A, et al. The effect of short sleep duration on coronary heart disease risk is greatest among those with sleep disturbance: a prospective study from the Whitehall II cohort. Sleep 2010;33:739–44. [26] Rod NH, Vahtera J, Westerlund H, et al. Sleep disturbances and cause-specific mortality: results from the GAZEL cohort study. Am J Epidemiol 2011;173: 300–9. [27] Laugsand LE, Vatten LJ, Platou C, et al. Insomnia and the risk of acute myocardial infarction: a population study. Circulation 2011;124:2073–81. [28] Copinschi G. Metabolic and endocrine effects of sleep deprivation. Essent Psychopharmacol 2005;6:341–7. [29] Taheri S, Lin L, Austin D, et al. Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Med 2004;1:e62.
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Letter to the Editor
Insomnia and risk of cardiovascular disease: A meta-analysis of cohort studies Min Li, Xiao-Wei Zhang, Wen-Shang Hou, Zhen-Yu Tang ⁎ Department of Neurology, The Second Affiliated Hospital, School of Medicine, Nanchang University, Nanchang 330006, Jiangxi Province, People's Republic of China
a r t i c l e
i n f o
Article history: Received 1 June 2014 Accepted 26 July 2014 Available online 12 August 2014 Keywords: Insomnia Cardiovascular Meta-analysis
from studies included by previous meta-analysis were limited to December 2011. To our knowledge, some new cohort studies on the association between insomnia and risk of CVD have been published since than [8–13]. Therefore, we carried out a meta-analysis of cohort studies to quantitatively estimate whether insomnia independently increases the risk of CVD, using the most recent data. This meta-analysis was performed and reported according to the standard criteria of the Meta-analyses of Observational Studies in Epidemiology (MOOSE) conference statement [15]. A systematic search of published articles (through 17 May 2014) was performed by using electronic databases including PubMed, Cochrane Library, and ISI Web of Science databases. We used the following keywords: insomnia, sleep*,
Insomnia, the most prevalent sleep disorder, defined as a subjective feeling of having difficulty initiating or maintaining sleep or having a feeling of non-restorative sleep [1]. According to the definition, insomnia prevalence varies from 6% to an average of 33% in more than 50 epidemiological studies [2]. In addition, insomnia affects 10% to 30% of the general population in the United States [3], it has been estimated that the annual expenditure on insomnia is estimated at 92.5 to 107.5 billion [4], this creates a major public health burden. From the public health perspective, the issue of sleep problems is important. During the last years, insomnia was of particular concern because it could increase the risk of depression [5], hypertension [6], and metabolic syndrome [7]. Meanwhile, a considerable number of cohort studies showed a significant association between insomnia and cardiovascular diseases (CVDs) [8–13]. Nevertheless, whether insomnia independently increases myocardial infarction (MI) risks, stroke risks, and coronary heart disease (CHD) risks specifically, or whether insomnia independently increases CVD mortality, results to date have been inconsistent. Meta-analysis might help to resolve this inconsistency. A recent published meta-analysis of 13 prospective studies showed that insomnia was associated with an increased risk of fatal and/or non-fatal from CVD (pooled relative risk = 1.45, 95% confidence interval: 1.29–1.62) [14]. However, that meta-analysis found insufficient evidence on the association between insomnia and risk of individual types of CVD, including MI, stroke, CHD, and cardiovascular mortality. Moreover, the data
⁎ Corresponding author at: Department of Neurology, The Second Affiliated Hospital, Nanchang University, No. 1, Minde Road, Nanchang 330006, Jiangxi, People's Republic of China. Tel.: +86 791 86311759; fax: +86 791 86292217. E-mail address: [email protected] (Z.-Y. Tang).
http://dx.doi.org/10.1016/j.ijcard.2014.07.284 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
Fig. 1. Flow chart of study selection.
Table 1 Characteristic of included cohort studies. Publication, (year)
Country
Cohort
Sex
Sample size (n)
Outcome(s)
Follow-up. (year)
Age, (year)
Outcome assessment
Insomnia assessment
Exposure categories
Adjusted variables
Eaker et al [17]
1992
USA
Framingham Study
F
749
20
45–64
Yes/No
Age, SBP, TC/HDL, diabetes, cigarettes, BMI
1998
USA
FM
2960
3
65–101
TFA
2002
Sweden
Piedmont Health Survey County of Dalarna registry
Clinical manifestations and hospital records ICD-9
TFA
Schwartz et al [18] Mallon et al [19]
MI, CVD mortality MI
FM
1870
CVD mortality
12
45–65
ICD-9
DIS
Most of the time/Never Yes/No
Elwood et al [20] Phillips et al [21]
2006
UK
M
1874
CHD, Stroke
5
55–69
ICD-10
Insomnia
Frequent/None
2007
USA
Caerphilly cohort study ARIC study
FM
11,863
CHD
6.3
44–64
Hospital records and standardized diagnoses
Yes/No
Meisinger et al [22]
2007
Germany
MONICA/KORA
FM
6896
MI
10.1
45–75
ICD-9, ESC and ACC criteria
TFA/sleep continuity disturbance/nonrestorative sleep DIS/TFA
Age, sex, race, education, prescriptions, selfrated health, depression Age, not married, living alone, smoking habit, BMI N 28, HT, cardiac disease, respiratory disease, diabetes, joint pain, GID, depression, sleep duration, snoring, sleeping pill usage Age, social class, smoking habit, alcohol consumption, BMI, neck circumference Age, sex, race, education, BMI, depression, lung function, smoking habit, diabetes
Suzuki et al [23]
2009
Japan
Shizuoka study
FM
11,395
CVD mortality
5.3
65–85
ICD-10
DFA
Yes/No
Chien et al [24]
2010
China
Chin-Shan community study
FM
3430
CVD mortality
15.9
N35
Official death certificates and househouse visits
Frequency of insomnia
Nearly every day/No
Chandola et al [25]
2010
UK
Whitehall II
FM
10,308
MI, CVD mortality
15
35–55
ICD-10
Restless, disturbed nights
More than usual/No
Hulvej Rod et al [26]
2011
France
GAZEL cohort study
M
12,524
CVD mortality
19
36–52
ICD-9, ICD-10
DFA
Yes/No
Laugsand et al [27]
2011
Norway
Nord-Trondelag Health Study
FM
52,610
MI
11.4
≥65
ESC and ACC criteria
DIS
Almost every night/Never
Westerlund et al [8]
2013
Sweden
Nation March Cohort study
FM
41,192
CVD mortality
13.2
52.8
ICD-9, ICD-10
DFA
Mostly/always/ Never
Sands-Lincoln et al [9]
2013
USA
Women's Health Initiative
F
86,329
CHD, CVD mortality
10.3
50–79
medical records, death certificates
WHIIRS
WHIIRS ≥ 9/b3
Hulvej Rod et al [10] Canivet et al [11]
2014
France
Whitehall II
FM
9098
22
35–55
ICD-9, ICD-10
2014
Sweden
Malmo Diet and Cancer study
FM
13,277
CVD mortality CVD mortality
13
45–64
ICD-9, ICD-10
Restless, disturbed nights DSM-IV
More than usual/Not at all Yes/No
Li et al [12]
2014
USA
Health Professionals Follow-Up study
M
23,447
CVD mortality
6
68.6
ICD-8
DFA
Most of the time/Never
Wu et al [13]
2014
China
NHIRD
FM
21,438
Stroke
4
52
ICD-9
ICD-9
Yes/No
Yes/No
Age, survey, BMI, education, dyslipidemia, alcohol intake, parental history of MI, physical activity, smoking habit, HT, diabetes Age, sex, BMI, smoking habit, alcohol, physical activity, socioeconomic status, mental health, HT, diabetes Age, sex, BMI, smoking habit, alcohol, marital status, education, occupation, exercise, family history of CHD, HT, diabetes, lipids, glucose, uric acid Age, sex, ethnicity, employment grade, car access, housing tenure, self-rated health status, cholesterol, HT, BMI, diabetes, smoking habit, alcohol, exercise, fruit and vegetable consumption Age, socioeconomic status, marital status, smoking habit, alcohol, BMI, night work, HT, diabetes Age, sex, education, marital status, shift work, SBP, cholesterol, diabetes, BMI, physical activity, smoking habit, depression, anxiety Age, sex, education, employment status, smoking, alcohol, snoring, work schedule, depressive symptoms, self-rated health, physical activity, BMI, diabetes, lipid disturbance, HT Age, race, education, income, smoking, BMI, physical activity, alcohol intake, depression, diabetes, high blood pressure, hyperlipidemia, comorbid conditions Age, employments grade, ethnicity, marital status
M. Li et al. / International Journal of Cardiology 176 (2014) 1044–1047
Author
Age,socieconomic position, marital status, social participation, smoking status, low physical activity, obesity, HT, diabetes mellitus, neck, shoulder, lumbar pain Age, ethnicity, smoking status, alcohol drinking, BMI, physical activity, alternate healthy eating index, marriage status, living status, regular use of aspirin, Age, sex, comorbidities, socioeconomic status, geographic region
1045
TFA: trouble falling asleep; DFA: difficulty initiating sleep; DIS: difficulty initiating sleep; ICD: International Classification of Diseases; CVD: cardiovascular disease; CHD: coronary heart disease; MI: myocardial infarction; F: female; M: male; and WHIIRS: The Women's Health Initiative Insomnia Rating Scale; NHIRD. National Health Insurance Research Database; BMI: body mass index; SBP: systolic blood pressure; HT: hypertension; TC: total cholesterol; HDL: high density lipoprotein; GID: gastrointestinal disease. ESC: the European Society of Cardiology; and ACC: American College of Cardiology.
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M. Li et al. / International Journal of Cardiology 176 (2014) 1044–1047
• Study
RR (95% CI)
Eaker 1992
3.90 (1.70, 9.00)
Mallon(male) 2002
3.10 (1.50, 6.30)
Suzuki 2009
1.02 (0.73, 1.43)
Chien 2010
1.78 (1.03, 3.08)
1.16 (0.82, 1.63)
Chandola 2010
1.36 (1.10, 1.68)
Meisinger(female) (2007)
1.30 (0.81, 2.06)
Hulvej Rod 2011
1.18 (0.67, 2.06)
Chandola (2010)
1.36 (1.10, 1.68)
Westerlund 2013
0.91 (0.73, 1.14)
Sands-Lincoln 2013
1.11 (1.03, 2.00)
Laugsand(male) (2011)
1.27 (0.91, 1.78)
Hulvej Rod(male) 2014
1.08 (0.70, 1.66)
Laugsand(female) (2011)
1.70 (1.29, 2.23)
Hulvej Rod(female) 2014
3.04 (1.42, 6.51)
Overall (I-squared = 38.4%, p = 0.136)
1.41 (1.18, 1.67)
Canivet(male) 2014
1.00 (0.90, 1.20)
Canivet(female) 2014
1.40 (1.20, 1.60)
Li 2014
1.55 (1.19, 2.04)
Overall (I-squared = 73.1%, p = 0.000)
1.33 (1.13, 1.57)
Study
RR (95% CI)
Eaker (1992)
3.90 (1.70, 9.00)
Schwartz (1998)
1.22 (0.77, 1.92)
Meisinger(male) (2007)
0.1
1
Decreased risk
Increased risk
9
•
0.1
sleep disorder, sleep disturbance, sleep initiation, disorders of initiating and maintaining sleep, poor sleep quality, sleep complaints, stroke, coronary heart disease, coronary artery disease, coronary stenosis, myocardial infarction, myocardial ischemia, cerebrovascular disorders, cardiovascular disease, heart failure, coronary thrombosis, prospective studies, cohort studies, longitudinal studies, and follow-up studies. There were no language restrictions. Studies were considered eligible if they fulfilled all of the following criteria: (1) the study of adult patients had a cohort design; (2) the exposed subject was a patient with insomnia; (3) the reported quantitative estimates of the multivariateadjusted relative risk (RRs) and 95% confidence intervals (CIs) for CVD outcomes associated with insomnia, hazard ratio/odds ratios were considered equivalent to RRs; (4) the study has a duration longer than 1 year of follow-up; (5) the evaluated subjects are free of CVD at baseline; and (6) the study reports clear definitions of method used to assess sleep complaints. Studies were excluded if they met the following criteria: (1) the study design did not include a cohort (for example, cross-sectional and retrospective case–control studies); (2) the unadjusted RRs and 95% CIs were reported (for example, just adjusted age or sex); and (3) the study has a duration shorter than 1 year of follow-up. The RRs were pooled using the random-effects model [16]. All the statistical analyses were performed in STATA version 11 (StataCorp LP, College Station, TX). p values were 2-sided and p b 0.05 was considered as statistically significant.
RR (95% CI)
Study
Coronary heart disease Elwood 2006
1.47 (0.98, 2.21)
Phillips 2007
1.50 (1.10, 2.00)
Sands-Lincoln 2013
1.19 (1.08, 1.30)
Subtotal (I-squared = 31.3%, p = 0.233)
1.28 (1.10, 1.50)
1 Decreased risk
Fig. 2. Association between insomnia and risk of myocardial infarction.
9 Increased risk
Fig. 4. Association between insomnia and risk of cardiovascular mortality.
Seventeen cohort studies with a total of 311,260 participants were included in this meta-analysis [8–13,17–27] (Fig. 1). The main characteristics of studies in the meta-analysis were presented in Table 1. A total of seven comparisons (two studies did have sex specific data) investigated the association between insomnia and risk of MI [17,18,22, 25,27]. The ascertainment of insomnia and ascertainment of CVD outcomes varied across studies. Pooling all 7 comparisons, insomnia was associated with a significantly increased risk of MI (RR, 1.41; 95% CI, 1.18 to 1.67; p = 0.000) (Fig. 2). Fig. 3 showed the results from random-effects models combining the RRs for CHD and stroke. The overall combined RRs in relation to insomnia were 1.28 (95% CI, 1.10 to 1.50; p = 0.002) for CHD and 1.55 (1.39 to 1.72; p = 0.000) for stroke, respectively. Thirteen comparisons (two studies did have sex specific data) evaluated the association between insomnia and risk of CVD mortality [8–12,17,19,23–26]. Insomnia significantly increased the risk of CVD mortality (RR, 1.33; 95% CI, 1.13 to 1.57; p = 0.001) (Fig. 4). Our meta-analysis of 17 cohort studies provides evidence that insomnia is significantly associated with increased risk of cardiovascular outcomes and mortality after adjustment of established cardiovascular risk factors. For the moment, the mechanisms that underlie this possible association have been reported both by epidemiologic and experimental studies but are not completely understood. Results in metabolic or endocrine changes, through sympathetic activation and elevated levels of inflammatory cytokines, may link the development of poor quality sleep with the pathogenesis of CVD events [28,29]. To efficiently assess the causality of insomnia on CVD events, future research is warranted, especially experimental and clinical studies probing mechanisms underlying the insomnia-mortality associations.
Conflict of interest statement
.
None.
Stroke Elwood 2006
1.75 (1.02, 3.01)
Wu 2014
1.54 (1.38, 1.72)
Subtotal (I-squared = 0.0%, p = 0.650)
1.55 (1.39, 1.72)
Acknowledgments
. •
0.3
Decreased risk
1
Increased risk
3
Fig. 3. Association between insomnia and risk of coronary heart disease and stroke.
ZYT and ML conceived and designed the experiments. WSH, ML and XWZ analyzed the data. ML and ZYT wrote the paper. WSH, XWZ and ZYT performed the literature search and the data extraction. All authors saw and approved the final version of the manuscript. We thank the editors of the International Journal of Cardiology for editing the manuscript.
M. Li et al. / International Journal of Cardiology 176 (2014) 1044–1047
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