Sage Journals: Discover world-class research

Abstract

Studies that focus on the relationship between sex and the risk of acute coronary syndrome (ACS) are scant. The current study investigated the effects of sex differences in the risk of developing ACS in patients with sleep disorders (SDs). This longitudinal population-based cohort study evaluated the incidence and risk of ACS development in 40,232 men and 65,519 women newly diagnosed with SDs between 2002 and 2008 from the Longitudinal Health Insurance Database. The follow-up period began from the entry date and ended on the date of an ACS event or December 31, 2010. Univariable and multivariable Cox proportional hazard regression models were conducted to estimate the sex differences in the risk of ACS. Men with SDs exhibited an increased incidence of ACS compared with women with SDs in all age- and comorbidity-specific subgroups. After covariates were adjusted, the men with SDs exhibited a 1.48-fold adjusted hazard ratio (aHR) of ACS compared with the women with SDs (95% confidence interval [CI] = 1.36-1.60). After age group stratification, the men with SDs in the young adult group exhibited the highest risk of subsequent ACS development compared with the women with SDs (aHR = 2.07, 95% CI = 1.69-2.55), followed by those in middle-aged adults (aHR = 1.52, 95% CI = 1.32-1.76) and older adults groups (aHR = 1.24, 95% CI = 1.11-1.39). This study determined that men with SDs, particularly young men, are at a higher risk of subsequent ACS development compared with women with SDs.

Keywords

sleep disorders acute coronary syndrome population-based cohort study

Introduction

Problems of falling asleep, frequent waking, and poor sleep quality are prevalent in the general population worldwide (Laugsand, Vatten, Platou, & Janszky, 2011; Ohayon & Hong, 2002; Tsou, 2013). Women have more sleep-related complaints than men (Krishnan & Collop, 2006). However, men have been reported to exhibit worse sleep quality compared with women, with a shorter sleep time, longer sleep-onset latency, and lower sleep efficiency (Krishnan & Collop, 2006). The results of studies on sleep problems have supported a female predominance but increased divergence of prevalence between men and women with an older age (Zhang & Wing, 2006).

Sleep plays a vital modulator on the autonomic nervous system, systemic hemodynamics, endothelial function, coagulation, and cardiac function (Plante, 2006). Disruption in sleep can increase the risk of hypertension (Calhoun & Harding, 2010; Vozoris, 2013). Sleep problems in older people are associated with atherosclerosis risk (Nakazaki et al., 2012). Sleep disturbances also showed higher risk of diabetes (Chaput, Despres, Bouchard, Astrup, & Tremblay, 2009; Kawakami, Takatsuka, & Shimizu, 2004). Epidemiologic studies have reported that sleep disorders (SDs) are an independent risk factor for cerebrovascular disease (Huang et al., 2013; Yaggi & Mohsenin, 2003).

A previous study has demonstrated that an SD cohort exhibited a 1.43-fold increased risk of acute coronary syndrome (ACS) compared with a non-SD cohort after adjustment for potential covariates (Chung et al., 2013). ACS still remains the major cause of morbidity and mortality despite advances in treatment worldwide (Kolansky, 2009; Nikus et al., 2007). Hypertension, diabetes, and hyperlipidemia are traditional risk factors for atherosclerosis development, which contributes to the progression of ACS (Picariello et al., 2011; Sethi, Akl, & Farkouh, 2012; Vondrakova, Ostadal, & Kruger, 2010). Stable coronary artery disease (CAD) and old myocardial infarction are common predictors for ACS occurrence (Thune et al., 2011; Zouridakis, Avanzas, Arroyo-Espliguero, Fredericks, & Kaski, 2004).

Celen, Hedner, Carlson, and Peker (2010) indicated that the contribution of obstructive sleep apnea to developing diabetes is higher in women than in men. However, no studies have investigated sex differences of ACS development in patients with SDs. Therefore, the authors conducted a population-based cohort study to determine whether sex differences exist in the risk of ACS development in patients with SDs.

Method

Study Design and Data Source

A population-based retrospective cohort design was adopted. The Longitudinal Health Insurance Database (LHID), released by the Taiwan National Health Insurance Administration (NHIA), was used in the current study. The National Health Insurance (NHI) program has been implemented in Taiwan since 1995 and currently covers 99% of the 23.74 million people in Taiwan (T. M. Cheng, 2009). The LHID contains information on one million beneficiaries randomly sampled from the population of all NHI beneficiaries. The database contains a comprehensive registry and claims data from this health insurance system, including demographic data and prescribed orders from ambulatory to inpatient care. The privacy of patients and health care providers is protected, and no personal information can be identified because researchers who use the database are required to submit their study protocols for evaluation by the NHIA. The Institutional Review Board of Taoyuan General Hospital approved this study. Diseases are coded according to the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM), 2001 edition. The validity and reliability of ACS diagnoses in the LHID have been reported in previous studies (C. L. Cheng et al., 2014; Chung et al., 2013; Chung et al., 2014).

Study Population

A cohort was constructed by identifying patients in the LHID who were newly diagnosed with SDs (ICD-9-CM code 307.4 and 780.5) between January 1, 2002, and December 31, 2008. The definition of SD was based on three or more ambulatory claims for SDs or at least one hospitalization with an additional SD diagnosis. The first date of SD diagnosis was defined as the entry date. Patients younger than 20 years and those with incomplete age or sex information were excluded. Those with a history of SD before 2002 were excluded (Figure 1).

Figure 1.

Flow diagram of the study participants.

Identifying the Outcome Variable

All the participants were followed-up to evaluate the occurrence of ACS until December 31, 2010, or they were censored because of death, withdrew from the NHI program, or were lost to follow-up. The confirmation of ACS events was based on ICD-9-CM discharge codes 410, 411.1, and 411.8 in the LHID. The Taiwan NHIA audits the diagnosis and management codes through systematic peer reviews.

Covariates and Comorbid Diseases

Participants were stratified according to age into the following groups: young adults (20-49 years), middle-aged adults (50-64 years), and older adults (≥65 years). The following medical comorbid diseases associated with an increased risk of ACS development were included: diabetes, hypertension, hyperlipidemia, CAD, and old myocardial infarction, which were identified on the basis of diagnoses to manage the potential confounding effect on the risk of ACS development.

Statistical Analysis

All statistical analyses were performed using SPSS 17.0 software (SPSS Inc., Chicago, IL). A chi-squared test was performed to compare and test the differences in the proportional distribution of age and comorbidities between the men and women. Student’s t test was used to measure and test the mean ages between the men and women. The follow-up person-years were used to estimate the incidence density of ACS. The overall, age-specific, and comorbidity-specific incidence of ACS was assessed in both sexes, and univariable and multivariable Cox proportional hazard regression analyses were used to estimate the crude hazard ratio (HR) and adjusted HR (aHR) with 95% confidence intervals (CIs) for ACS development in the men, and the results were compared with those in the women. In addition, the incidence and HRs of ACS development associated with the interaction between SDs and comorbidities was measured. All p values were tested at a 2-tailed significance level of .05.

Results

Demographic Characteristics and Comorbidity in Patient With SDs

A total of 105,751 patients were followed-up for 769,041 person-years. The average durations of follow-up were 7.16 and 7.34 years for the men with SDs and women with SDs, respectively (data not reported). The mean age of the men was older than that of the women (49.7 ± 16.9 years vs. 47.9 ± 16.9 years). The men with SDs exhibited a higher proportion of comorbidities than did the women with SDs. The most prevalent comorbidities for the patients with SDs were hypertension, followed by hyperlipidemia, diabetes, CAD, and old myocardial infarction (Table 1).

Table 1.

Demographic Characteristics and Comorbidity in Patients With Sleep Disorders.

Variable	Sleep disorders		p value
Variable	Men (N =40,232)	Women (N = 6,5519)	p value
Age (years),^a n (%)			<.001
<50	22,287 (55.4)	38,880 (59.3)
50-64	9,377 (23.3)	16,229 (24.8)
≥65	8,568 (21.3)	10,410 (15.9)
Age, M (SD)^b	49.7 (16.9)	47.9 (15.9)	<.001
Comorbidity^a
Diabetes	5,025 (12.5)	6,772 (10.3)	<.001
Hypertension	11,928 (29.6)	16,512 (25.2)	<.001
Hyperlipidemia	5,256 (13.1)	8,178 (12.5)	.006
Old myocardial infarction	104 (0.3)	52 (0.1)	<.001
Coronary artery disease	4,117 (10.2)	5,382 (8.2)	<.001

Chi-square test. ^bTwo-sample t test.

Comparison of Incidence and HR for ACS Stratified According to Age and Comorbidity Between the Men and Women With SDs

The men with SDs exhibited a higher overall incidence of ACS than did the women with SDs, with a 1.67-fold crude HR. After adjustment for covariates, the men with SDs showed a 1.48-fold increased risk of developing ACS compared with the women with SDs (aHR = 1.48, 95% CI = 1.36-1.60). Furthermore, men with SDs had an increased incidence of ACS compared with women with SDs in all age- and comorbidity-specific subgroups. After age group stratification, the men with SDs in the young adult group exhibited the highest risk of subsequent ACS development compared with the women with SDs (aHR = 2.07, 95% CI = 1.69-2.55), followed by those in middle-aged adults (aHR = 1.52, 95% CI = 1.32-1.76) and older adults groups (aHR = 1.24, 95% CI = 1.11-1.39). Men exhibited higher incidence and risk of ACS than did women regardless of whether or not the comorbidity existed (Table 2).

Table 2.

Comparison of Incidence and Hazard Ratio of ACS Stratified by Age and Comorbidity Between Men and Women With Sleep Disorders.

Variables	Sleep disorders						Crude HR (95% CI)	Adjusted HR^b (95% CI)
	Men			Women
	Event	PY	Rate^a	Event	PY	Rate^a
All	1,175	288,067	40.79	1,168	480,974	24.28	1.67 (1.54, 1.81)***	1.48 (1.36, 1.60)***
Age (years)
<50	222	162,758	13.64	156	286,796	5.44	2.50 (2.04, 3.07)***	2.07 (1.69, 2.55)***
50-64	344	67,125	51.25	386	120,128	32.13	1.58 (1.36, 1.82)***	1.52 (1.32, 1.76)***
≥65	609	58,184	104.67	626	74,050	84.54	1.22 (1.09, 1.37)*	1.24 (1.11, 1.39)***
Comorbidity
Diabetes
No	852	254,266	33.51	775	433,382	17.88	1.87 (1.69, 2.06)***	1.62 (1.47, 1.78)***
Yes	323	33,801	95.56	393	47,592	82.58	1.14 (0.99, 1.32)	1.17 (1.01, 1.36)*
Hypertension
No	464	20,6419	22.48	377	363,021	10.39	2.16 (1.89, 2.47)***	1.81 (1.58, 2.08)***
Yes	711	81,648	87.08	791	117,953	67.06	1.28 (1.16, 1.42)***	1.27 (1.15, 1.41)***
Hyperlipidemia
No	921	252,240	36.51	853	423,257	20.15	1.80 (1.64, 1.98)***	1.51 (1.37, 1.66)***
Yes	254	35,827	70.90	315	57,717	54.58	1.28 (1.09, 1.51)**	1.35 (1.14, 1.59)***
Old myocardial infarction
No	1,160	287,407	40.36	1,166	480,572	24.26	1.65 (1.53, 1.79)***	1.48 (1.36, 1.60)***
Yes	15	660	227.27	2	402	49.75	4.06 (0.93, 17.78)	5.02 (1.11, 22.66)*
Coronary artery disease
No	818	260,093	31.45	823	44,2538	18.60	1.68 (1.53, 1.85)***	1.54 (1.40, 1.70)***
Yes	357	27,974	127.62	345	38,436	89.76	1.40 (1.21, 1.62)***	1.36 (1.18, 1.58)***

Note. HR = hazard ratio; CI = confidence interval; PY = person-years.

Rate: incidence rate, per 10,000 person-years. ^bAdjusted HR: multivariable analysis including age and comorbidity of diabetes, hypertension, hyperlipidemia, old myocardial infarction, coronary artery disease.

p < .05. **p < .01. ***p < .001.

Cox Proportional Hazards Regression Analysis for Interaction of Both Sexes With SDs and Comorbidity in the Association With the Risk of ACS

Compared with the women without comorbidity, the highest aHR for ACS was that of the men with comorbidity (aHR = 4.56, 95% CI = 3.91-5.32), followed by those of the women with comorbidity (aHR = 3.44, 95% CI = 2.95-4.01) and men without comorbidity (aHR = 2.17, 95% CI = 1.83-2.59; Table 3).

Table 3.

Cox Proportional Hazards Regression Analysis for Interaction of Both Sexes With SDs and Comorbidity on Risk of ACS.

Variable		PY	Event	Rate^a	Adjusted HR^b (95% CI)	P value
SDs	Comorbidity^c					<.001
Women	No	315,978	220	6.96	1 (Reference)
Women	Yes	164,996	948	57.46	3.44 (2.95, 4.01)***
Men	No	174,149	302	17.34	2.17 (1.83, 2.59)***
Men	Yes	113,918	873	76.63	4.56 (3.91, 5.32)***

Note. SDs = sleep disorders; ACS = acute coronary syndrome; PY = person-year; HR = hazard ratio; CI = confidence interval.

Rate, incidence rate, per 10,000 person-years. ^bAdjusted HR: multiple analysis including age and sex. ^cComorbidity: Patients with any one of the comorbidities: diabetes, hypertension, hyperlipidemia, old myocardial infarction, coronary artery disease were classified as the comorbidity group.

***

p < .001.

HRs and 95% CIs for ACS Risk Associated With the Number of Comorbidities in Both Sexes With SDs

Compared with the men with SDs and no comorbidity, the risk of ACS increased as the number of comorbidities increased in the men with SDs. Furthermore, the women with SDs and multiple comorbidities seemed to have a considerably higher ACS risk compared with the women with SDs and no comorbidity (Table 4).

Table 4.

Hazard Ratios and 95% Confidence Intervals of ACS Risk Associated With the Number of Comorbidities in Both Sexes With SDs.

	ACS	HR (95% CI)
	Number of cases	Crude	Adjusted^a
Number of comorbidities in women with SD
0	220	1 (Reference)	1 (Reference)
1	369	5.72 (4.84, 6.76)***	2.48 (2.07, 2.96)***
2	314	8.85 (7.45, 10.51)***	3.15 (2.61, 3.79)***
≥3	265	17.02 (14.24, 20.36)***	5.47 (4.51, 6.64)***
Number of comorbidities in men with SD
0	302	1 (Reference)	1 (Reference)
1	356	3.15 (2.71, 3.68)***	1.76 (1.50, 2.06)***
2	306	4.93 (4.20, 5.78)***	2.43 (2.06, 2.87)***
≥3	211	8.09 (6.78, 9.65)***	3.74 (3.11, 4.50)***
p for trend			<.001

Note. ACS = acute coronary syndrome; SDs = sleep disorders; HR = hazard ratio; CI = confidence interval.

Adjusted HR: Multivariable analysis including age, and comorbidities: diabetes, hypertension, hyperlipidemia, old myocardial infarction, coronary artery disease.

***

p < .001.

Kaplan–Meier Analysis Comparing Cumulative Probabilities of ACS Between the Men and Women in the SD Cohort

The men with SDs exhibited a significantly higher risk of subsequent ACS development than did the women with SDs (p < .001; Figure 2).

Figure 2.

Kaplan–Meier analysis comparing cumulative probabilities of ACS between men and women in SD cohort.

Discussion

According to a review of relevant research, this study is the first for an Asian population to investigate the sex differences in the risk of ACS in patients with SDs. This longitudinal cohort study demonstrated that men with SDs exhibited a higher incidence of ACS development than did women with SDs (40.79 vs. 24.28 per 10,000 person-years). Although men with SDs had a higher prevalence of comorbidities than did women with SDs, men still exhibited a 48% increased risk of developing ACS compared with the women in the SD cohort after adjustment for covariates. The findings are consistent with previous studies, which reported that men had a higher prevalence of CAD compared with women (Lloyd-Jones, Larson, Beiser, & Levy, 1999; Towfighi, Zheng, & Ovbiagele, 2009).

Numerous possible mechanisms may explain the epiphenomenon of the higher risk of developing ACS in men with SDs compared with women with SDs. Men are more likely to engage in unhealthy daily lives, which includes cigarette smoking, heavy alcohol use, and eating more red meat and fewer vegetables and fruits (Barrett-Connor, 1997; Health Promotion Administration, 2014). Women have a higher level of endogenous estrogen, which exerts direct vasodilation and regulation on metabolic effects, namely, lipids, inflammatory markers, and the coagulation system (Maas & Appelman, 2010). Studies have reported that women with ACS exhibit less extensive obstructive CAD, such as unstable angina and non-ST segment elevation myocardial infarction, which are easily underestimated in an emergency room (Milcent, Dormont, Durand-Zaleski, & Steg, 2007). Furthermore, women tend to exhibit nonobstructive CAD, which may be associated with coronary microvascular dysfunction (Jacobs, 2009; Shaw, Bugiardini, & Merz, 2009). In addition, women may seek frequent health care services and get better outcomes from their medical regimen than men (H. J. Chang et al., 2012; H. T. Chang, Lai, Hwang, Ho, & Hwang, 2010; Feng et al., 2012; Tanghetti, 2011).

Further evaluation of ACS risk in the various age groups revealed that the men with SDs in the young adult age group had the highest risk of developing ACS compared with the women, followed by those in the middle-aged adult and older adult groups. Before menopause, the sex hormone estrogen may exert not only cardioprotective effects against atherosclerosis but also protective effects against ischemic injury on the myocardium (Xu et al., 2006). During menopause for women, systolic blood pressure, total cholesterol, and low-density lipoprotein increase (Dubey, Oparil, Imthurn, & Jackson, 2002; Yamaguchi et al., 2002). Upregulation of the renin–angiotensin system with an increase in plasma renin activity, salt sensitivity, and sympathetic activity easily causes systolic hypertension, left ventricular hypertrophy, and diastolic heart failure in postmenopausal elderly women (Maas & Appelman, 2010; Vitale, Miceli, & Rosano, 2007).

Compared with the women with SDs and no comorbidity, the men with SDs and any comorbidity were at a 4.56-fold increased risk of ACS, women with SDs and any comorbidity were at a 3.44-fold increased risk of ACS, and men with SDs and no comorbidity were at a 2.17-fold increased risk of ACS. Moreover, the risk of ACS development varied according to the number of comorbidities in the SD cohort in both sexes. This finding indicates the importance of multidisciplinary team care for people with SDs in preventing and managing ACS. The women with SDs and multiple comorbidities seemed to have a stronger effect on the risk of ACS compared with those with no comorbidity, as reported in Table 4. Type 2 diabetes increases the risk of CAD more substantially in women than in men (Juutilainen et al., 2004). The results are robust by using Cox proportional-hazards regression models to demonstrate ACS risks of men and women with SDs and their interaction of comorbidity.

Certain limitations existed in the current study, and thus, caution must be taken when interpreting the results. First, the LHID provides no information on personal behaviors, such as cigarette smoking, alcohol consumption, physical activity, and family history, which may become potential confounding factors for the outcome of interest. Cigarette smoking is associated with hypertension, diabetes, and CAD, and the authors adjusted for them to mediate the influence of smoking (Facchini, Hollenbeck, Jeppesen, Chen, & Reaven, 1992; Ockene & Miller, 1997; Yeh, Duncan, Schmidt, Wang, & Brancati, 2010; Yun et al., 2015). Second, the lack of results for objective sleep measurement and other mental health conditions that are highly comorbid with SDs as well as a history of medication use were critical limitations. Finally, a possible survival effect may be another limitation. Despite these limitations, the strength of this study is in using a large longitudinal population-based cohort design to evaluate the effect of sex on the risk of subsequent ACS events in an SD cohort. The NHI beneficiaries are assigned unique personal identification numbers in Taiwan; therefore, every patient could be traced in the LHID records throughout the follow-up period. In addition, the SD diagnoses in this study were made by physicians rather than self-reported by the patients.

In conclusion, it was determined that men with SDs were at a higher risk of subsequent ACS development compared with women with SDs, particularly in the young adult group. The risk of ACS increased with age and depended on the number of comorbidities. The women with SDs and comorbidities seemed to have a substantially increased risk of developing ACS compared with those with no comorbidity. Clinicians should be aware of this epiphenomenon and take proactive action to prevent and manage ACS in patients with SDs of both sexes.

Footnotes

Acknowledgements

We thank the Central Taiwan University of Science and Technology and Taichung Hospital, Ministry of Health and Welfare, for administrative support. However, these institutions had no role in study design, data collection and analysis, decision to publish, or preparation of the article. This work did not receive additional funding.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Barrett-Connor

(1997). Sex differences in coronary heart disease. Why are women so superior? The 1995 Ancel Keys Lecture. Circulation, 95, 252-264.

Calhoun

D. A.

Harding

S. M.

(2010). Sleep and hypertension. Chest, 138, 434-443. doi:10.1378/chest.09-2954

Celen

Y. T.

Hedner

Carlson

Peker

(2010). Impact of gender on incident diabetes mellitus in obstructive sleep apnea: A 16-year follow-up. Journal of Clinical Sleep Medicine, 6, 244-250.

Chang

H. J.

Lai

Y. L.

Chang

C. M.

Kao

C. C.

Shyu

M. L.

Lee

M. B.

(2012). Gender and age differences among youth, in utilization of mental health services in the year preceding suicide in Taiwan. Community Mental Health Journal, 48, 771-780. doi:10.1007/s10597-011-9470-1

Chang

H. T.

Lai

H. Y.

Hwang

I. H.

M. M.

Hwang

S. J.

(2010). Home healthcare services in Taiwan: A nationwide study among the older population. BMC Health Services Research, 10, 274. doi:10.1186/1472-6963-10-274

Chaput

J. P.

Despres

J. P.

Bouchard

Astrup

Tremblay

(2009). Sleep duration as a risk factor for the development of type 2 diabetes or impaired glucose tolerance: Analyses of the Quebec Family Study. Sleep Medicine, 10, 919-924. doi:10.1016/j.sleep.2008.09.016

Cheng

C. L.

Lee

C. H.

Chen

P. S.

Y. H.

Lin

S. J.

Yang

Y. H.

(2014). Validation of acute myocardial infarction cases in the national health insurance research database in Taiwan. Journal of Epidemiology, 24, 500-507.

Cheng

T. M.

(2009). Taiwan’s National Health Insurance system: high value for the dollar. In Okma

K. G. H.

Crivelli

(Eds.), Six countries, six reform models: The health reform experience of Israel, the Netherlands, New Zealand, Singapore, Switzerland and Taiwan (pp. 171-204). Hackensack, NJ: World Scientific.

Chung

W. S.

Lin

C. L.

Chen

Y. F.

Chiang

J. Y.

Sung

F. C.

Chang

Y. J.

Kao

C. H.

(2013). Sleep disorders and increased risk of subsequent acute coronary syndrome in individuals without sleep apnea: A nationwide population-based cohort study. Sleep, 36, 1963-1968. doi:10.5665/sleep.3240

10.

Chung

W. S.

Shen

T. C.

Lin

C. L.

Chu

Y. H.

Hsu

W. H.

Kao

C. H.

(2014). Adult asthmatics increase the risk of acute coronary syndrome: A nationwide population-based cohort study. European Journal of Internal Medicine, 25, 941-945. doi:10.1016/j.ejim.2014.10.023

11.

Dubey

R. K.

Oparil

Imthurn

Jackson

E. K.

(2002). Sex hormones and hypertension. Cardiovascular Research, 53, 688-708.

12.

Facchini

F. S.

Hollenbeck

C. B.

Jeppesen

Chen

Y. D.

Reaven

G. M.

(1992). Insulin resistance and cigarette smoking. Lancet, 339, 1128-1130.

13.

Feng

J. Y.

Huang

S. F.

Ting

W. Y.

Chen

Y. C.

Lin

Y. Y.

Huang

R. M.

. . . Su

W. J.

(2012). Gender differences in treatment outcomes of tuberculosis patients in Taiwan: A prospective observational study. Clinical Microbiology and Infection, 18, E331-E337. doi:10.1111/j.1469-0691.2012.03931.x

14.

Health Promotion Administration. (2014). Taiwan tobacco control annual report 2014. New Taipei City, Taiwan: Taipei Health Promotion Administration, Ministry of Health and Welfare.

15.

Huang

W. S.

Tsai

C. H.

Lin

C. L.

Sung

F. C.

Chang

Y. J.

Kao

C. H.

(2013). Nonapnea sleep disorders are associated with subsequent ischemic stroke risk: A nationwide, population-based, retrospective cohort study. Sleep Medicine, 14, 1341-1347. doi:10.1016/j.sleep.2013.07.017

16.

Jacobs

A. K.

(2009). Coronary intervention in 2009: Are women no different than men? Circulation. Cardiovascular Interventions, 2(1), 69-78. doi:10.1161/circinterventions.108.847954

17.

Juutilainen

Kortelainen

Lehto

Ronnemaa

Pyorala

Laakso

(2004). Gender difference in the impact of type 2 diabetes on coronary heart disease risk. Diabetes Care, 27, 2898-2904.

18.

Kawakami

Takatsuka

Shimizu

(2004). Sleep disturbance and onset of type 2 diabetes. Diabetes Care, 27, 282-283.

19.

Kolansky

D. M.

(2009). Acute coronary syndromes: morbidity, mortality, and pharmacoeconomic burden. American Journal of Managed Care, 15(Suppl. 2), S36-S41.

20.

Krishnan

Collop

N. A.

(2006). Gender differences in sleep disorders. Current Opinion in Pulmonary Medicine, 12, 383-389. doi:10.1097/01.mcp.0000245705.69440.6a

21.

Laugsand

L. E.

Vatten

L. J.

Platou

Janszky

(2011). Insomnia and the risk of acute myocardial infarction: A population study. Circulation, 124, 2073-2081. doi:10.1161/CIRCULATIONAHA.111.025858

22.

Lloyd-Jones

D. M.

Larson

M. G.

Beiser

Levy

(1999). Lifetime risk of developing coronary heart disease. Lancet, 353, 89-92. doi:10.1016/s0140-6736(98)10279-9

23.

Maas

A. H.

Appelman

Y. E.

(2010). Gender differences in coronary heart disease. Netherlands Heart Journal, 18, 598-603. doi:10.1007/s12471-010-0841-y

24.

Milcent

Dormont

Durand-Zaleski

Steg

P. G.

(2007). Gender differences in hospital mortality and use of percutaneous coronary intervention in acute myocardial infarction: Microsimulation analysis of the 1999 nationwide French hospitals database. Circulation, 115, 833-839. doi:10.1161/circulationaha.106.664979

25.

Nakazaki

Noda

Koike

Yamada

Murohara

Ozaki

(2012). Association of insomnia and short sleep duration with atherosclerosis risk in the elderly. American Journal of Hypertension, 25, 1149-1155. doi:10.1038/ajh.2012.107

26.

Nikus

K. C.

Eskola

M. J.

Virtanen

V. K.

Harju

Huhtala

Mikkelsson

. . . Niemela

K. O.

(2007). Mortality of patients with acute coronary syndromes still remains high: A follow-up study of 1188 consecutive patients admitted to a university hospital. Annals of Medicine, 39, 63-71. doi:10.1080/08037060600997534

27.

Ockene

I. S.

Miller

N. H.

(1997). Cigarette smoking, cardiovascular disease, and stroke: A statement for healthcare professionals from the American Heart Association. American Heart Association Task Force on Risk Reduction. Circulation, 96, 3243-3247.

28.

Ohayon

M. M.

Hong

S. C.

(2002). Prevalence of insomnia and associated factors in South Korea. Journal of Psychosomatic Research, 53, 593-600.

29.

Picariello

Lazzeri

Attana

Chiostri

Gensini

G. F.

Valente

(2011). The impact of hypertension on patients with acute coronary syndromes. International Journal of Hypertension, 2011, 563657. doi:10.4061/2011/563657

30.

Plante

G. E.

(2006). Sleep and vascular disorders. Metabolism, 55(10 Suppl. 2), S45-S49. doi:10.1016/j.metabol.2006.07.013

31.

Sethi

S. S.

Akl

E. G.

Farkouh

M. E.

(2012). Diabetes mellitus and acute coronary syndrome: Lessons from randomized clinical trials. Current Diabetes Reports, 12, 294-304. doi:10.1007/s11892-012-0272-9

32.

Shaw

L. J.

Bugiardini

Merz

C. N.

(2009). Women and ischemic heart disease: Evolving knowledge. Journal of the American College of Cardiology, 54, 1561-1575. doi:10.1016/j.jacc.2009.04.098

33.

Tanghetti

E. A.

(2011). The noncompliant patient with acne. Skin Therapy Letter, 16(10), 4-5.

34.

Thune

J. J.

Signorovitch

J. E.

Kober

McMurray

J. J.

Swedberg

Rouleau

. . . Solomon

S. D.

(2011). Predictors and prognostic impact of recurrent myocardial infarction in patients with left ventricular dysfunction, heart failure, or both following a first myocardial infarction. European Journal of Heart Failure, 13, 148-153. doi:10.1093/eurjhf/hfq194

35.

Towfighi

Zheng

Ovbiagele

(2009). Sex-specific trends in midlife coronary heart disease risk and prevalence. Archives of Internal Medicine, 169, 1762-1766. doi:10.1001/archinternmed.2009.318

36.

Tsou

M. T.

(2013). Prevalence and risk factors for insomnia in community-dwelling elderly in northern Taiwan. Journal of Clinical Gerontology and Geriatrics, 4(3), 75-79.

37.

Vitale

Miceli

Rosano

G. M.

(2007). Gender-specific characteristics of atherosclerosis in menopausal women: Risk factors, clinical course and strategies for prevention. Climacteric, 10(Suppl. 2), 16-20. doi:10.1080/13697130701602712

38.

Vondrakova

Ostadal

Kruger

(2010). Immediate effect of intensive atorvastatin therapy on lipid parameters in patients with acute coronary syndrome. Lipids in Health and Disease, 9, 71. doi:10.1186/1476-511x-9-71

39.

Vozoris

N. T.

(2013). The relationship between insomnia symptoms and hypertension using United States population-level data. Journal of Hypertension, 31, 663-671. doi:10.1097/HJH.0b013e32835ed5d0

40.

Arenas

I. A.

Armstrong

S. J.

Plahta

W. C.

Davidge

S. T.

(2006). Estrogen improves cardiac recovery after ischemia/reperfusion by decreasing tumor necrosis factor-alpha. Cardiovascular Research, 69, 836-844. doi:10.1016/j.cardiores.2005.11.031

41.

Yaggi

Mohsenin

(2003). Sleep-disordered breathing and stroke. Clinics in Chest Medicine, 24, 223-237.

42.

Yamaguchi

Sugimoto

Yano

Yamauchi

Sowa

Chen

Chihara

(2002). Plasma lipids and osteoporosis in postmenopausal women. Endocrine Journal, 49, 211-217.

43.

Yeh

H. C.

Duncan

B. B.

Schmidt

M. I.

Wang

N. Y.

Brancati

F. L.

(2010). Smoking, smoking cessation, and risk for type 2 diabetes mellitus: A cohort study. Annals of Internal Medicine, 152, 10-17. doi:10.7326/0003-4819-152-1-201001050-00005

44.

Yun

Sun

Lai

C. C.

Fernandez

. . . Berenson

G. S.

(2015). Tobacco smoking strengthens the association of elevated blood pressure with arterial stiffness: The Bogalusa Heart Study. Journal of Hypertension, 33, 266-274. doi:10.1097/HJH.0000000000000410

45.

Zhang

Wing

Y. K.

(2006). Sex differences in insomnia: A meta-analysis. Sleep, 29, 85-93.

46.

Zouridakis

Avanzas

Arroyo-Espliguero

Fredericks

Kaski

J. C.

(2004). Markers of inflammation and rapid coronary artery disease progression in patients with stable angina pectoris. Circulation, 110, 1747-1753. doi:10.1161/01.cir.0000142664.18739.92

Sex Differences in the Risk of Developing Acute Coronary Syndrome in Patients With Sleep Disorders: A Population-Based Cohort Study

Abstract

Keywords

Introduction

Method

Study Design and Data Source

Study Population

Identifying the Outcome Variable

Covariates and Comorbid Diseases

Statistical Analysis

Results

Demographic Characteristics and Comorbidity in Patient With SDs

Comparison of Incidence and HR for ACS Stratified According to Age and Comorbidity Between the Men and Women With SDs

Cox Proportional Hazards Regression Analysis for Interaction of Both Sexes With SDs and Comorbidity in the Association With the Risk of ACS

HRs and 95% CIs for ACS Risk Associated With the Number of Comorbidities in Both Sexes With SDs

Kaplan–Meier Analysis Comparing Cumulative Probabilities of ACS Between the Men and Women in the SD Cohort

Discussion

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Funding

References