Sleep disorders in individuals without sleep apnea increase the risk of peripheral arterial disorder: A Nationwide Population- based Retrospective Cohort Study
Chia-Hsiang Li, MD1, 2, Kuo-Yang Huang, MD1, 2, Wei-Chun Chen, MD1, 2, Chia-Hung Chen, MD1, 3, 4, Chih-Yen Tu, MD1, 5, 6, Cheng-Li Lin, MSc7, 8, Wu-Huei Hsu, MD, FCCP1,
5, Chi-Jung Chung, PhD9, 10, Chin-Ching Wu8
1 Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan
2 China Medical University, Taichung, Taiwan
3 Graduate institute of clinical medical science, China Medical University, Taichung, Taiwan
4 Department of Respiratory Therapy, China Medical University, Taichung, Taiwan
5 School of Medicine, China Medical University, Taichung, Taiwan
6 Department of Life Science, National Chung Hsing University
7 Management Offices for Health Data, China Medical University Hospital, Taichung, Taiwan
8 Department of Public Health, China Medical University, Taichung, Taiwan
9 Department of Health Risk Management, College of Public Health, China Medical University, Taichung, Taiwan;
10 Department of Medical Research, China Medical University Hospital, Taichung, Taiwan;
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Corresponding authors:
Chi-Jung Chung, PhD, Department of Health Risk Management, China Medical University, No. 91 Hsueh-Shih Road, Taichung 404, Taiwan, E-mail:
cjchung@mail.cmu.edu.tw, TEL: 886-4-22053366, ext. 6505, FAX: 886-4-22070429 Chin-Ching Wu, PhD, Department of Public Health, China Medical University, No. 91 Hsueh-Shih Road, Taichung 404, Taiwan, E-mail: wucc@mail.cmu.edu.tw, TEL: 886-4- 22053366, ext. 6115, FAX: 886-4-22019901
Acknowledgments:
This study was funded by the Taiwan Ministry of Health and Welfare Clinical Trial and Research Center of Excellence (MOHW103-TDU-B-212-113002). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study.
The contributions of each author are as follows:
Conception and design: Chia-Hsiang Li, Kuo-Yang Huang, Wei-Chun Chen, Chia-Hung Chen, Chih-Yen Tu , Wu-Huei Hsu and Chi-Jung Chung.
Administrative support: Cheng-Li Lin.
Collection and assembly of data: All authors.
Data analysis and interpretation: Chia-Hsiang Li, Kuo-Yang Huang, Wei-Chun Chen, Chia-Hung Chen, Chih-Yen Tu , Wu-Huei Hsu Chi-Jung Chung, and Chin-Ching Wu.
Manuscript writing: All authors.
Final approval of manuscript: All authors.
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Conflict of interest
The authors declare that there are no conflicts of interest.
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Key Words
Non-apnea sleep disorder, insomnia, peripheral arterial disease, cardiovascular disease
Abbreviations
Non-apnea sleep disorder: NASD Peripheral arterial disease: PAD
National Health Insurance Research Database: NHIRD National Health Insurance: NHI
National Health Research Institute: NHRI 1
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Abstract
Study Objectives
Previous literature lacks analysis of non-apnea sleep disorder (NASD) and peripheral arterial disease (PAD). The aim of this study was to evaluate the association between NASD and risk of developing PAD using retrospective data from a national database in Taiwan.
Design, setting, and participants:
We identified 46,064 patients with NASD using the catastrophic illness registry of the Taiwan National Health Insurance Research Database (NHIRD) from 1996 to 2010. We also selected a comparison cohort of 92,128 subjects who were random frequency- matched by age, sex, and entry year of the NASD cohort from the same database.
Interventions: NASD
Main outcome and measurements
The study followed all subjects from their entry date to the occurrence of PAD. We evaluated the risks of PAD using Cox proportional hazards regression models. The survival function for PAD was assessed using the Kaplan-Meier method.
Results:
The risk of PAD was 1.49-fold in patients with NASD compared with patients without NASD after adjusting for age, sex and comorbidities. Patients with NASD and diabetes or with NASD and hyperlipidemia had increased risk of PAD compared to those without NASD and diabetes or hyperlipidemia.
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Conclusions
We demonstrated the significantly increased risk of PAD in NASD patients through a nationwide population-based retrospective cohort study.
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Introduction
Peripheral arterial disorder (PAD) is an arterial disease that leads to blood flow
obstruction, arterial lumen narrowing or stenosis. The prevalence of PAD is 1.8% to 25%
in the general population. Related risk factors include age, sex, diabetes mellitus, hypertension, hyperlipidemia, metabolic syndrome and smoking. PAD is usually under- diagnosed and undertreated since most patients with PAD are symptom free. It is also related to some biomarkers, including C-reactive protein, beta 2- macroglobulin, cystain C, lipoprotein, and homocysteine. Patients with renal disease and diabetes mellitus are more likely to have PAD. In addition, patients with symptomatic extremity PAD develop intermittent claudication, chronic limb ischemia or acute limb ischemia, and these
patients often need revascularization, surgical bypass or amputation during the later stages. PAD not only influences the quality of life of the patient but is also associated with increasing mortality and morbidities of developing coronary arterial disease and cerebrovascular disease.
We spend more than 30% of our life sleeping. Sleep problems are a common complaint in the general population. Insomnia, a sleep disorder defined as having a difficulty falling asleep, staying asleep, waking early in the morning or experience non-restorative sleep.
Insomnia is the most noted in Western countries with a prevalence of 27% to 37 %, 22.8% in Korea and 25% in Taiwan. Our study investigates the influence of sleep disorders upon and the pathogenesis of cardiovascular diseases and the progression of heart and vessel diseases.
In a recent cross-sectional study, Utriainen et al. indicated that the prevalence of obstructive sleep apnea (OSA) is common in patients with PAD. Nachtmann et al.
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showed that OSA may contribute to the development of PAD. However, the discussion about sleep disorders and PAD are scarce. Taiwan established its National Health Insurance (NHI) program in 1995, which, using the data available from this program, offers a unique opportunity for research. In the present study, we used a 13-year nationwide population-based dataset to determine the association between NASD and renal PAD.
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Methods and Materials Data Source
Our retrospective cohort study used the reimbursement data acquired for the period from 1996 to 2010 from the National Health Insurance (NHI) system in Taiwan. The NHI program includes the complete medical information of more than 23.74 million
Taiwanese residents, with a coverage rate of over than 99%. For the purpose of research, the Taiwan National Health Research Institute (NHRI) manages and releases the National Health Insurance Research Database (NHIRD) on an annual basis. The identification numbers of patients have been scrambled to protect the privacy of insured residents before releasing the data. The data used in this study is from a sub-dataset of the NHIRD.
The data comprises one million randomly sampled beneficiaries enrolled in the NHI program, which collected all records on these individuals from 1996 to 2010. Diseases diagnoses were identified and coded using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM). This study was exempted from ethical review (IRB permit number: CMU-REC-101-012).
Sampled Participants
Based on the NHI database, subjects with sleep disorders other than sleep apnea (ICD-9- CM codes 307.4 and 780.5) newly diagnosed between January 1998 and December 2001 were included in the non-apnea sleep disorders (NASD) cohort. The first date of non- apnea sleep disorder diagnosis was defined as the entry date. We excluded patients who had sleep apnea syndrome (SA; ICD-9-CM codes 780.51, 780.53, and 780.57) and patients with a history of peripheral arterial disease (PAD) (ICD-9-CM codes 440.2, 1
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443.81, 443.9, 444.2, 444.89) before the entry date. The sample size of the comparison cohort was twice the size of the NASD cohort with similar age and gender frequency. We selected insured residents without a history of sleep disorders, sleep apnea and PAD for the comparison cohort.
Outcome and Relevant Variables
Both the NASD and the comparison cohort were followed until the end of 2010 to estimate the incident cases with the diagnosis of PAD. The diagnosis of PAD began with physical examination and then confirmed by image study that included ultrasound, computed tomographic angiography, or angiography. To compare the effects of different types of NASD on PAD incidence, we further classified it into insomnia (ICD-9-CM:
780.52), sleep disturbance (ICD-9-CM: 780.5, 780.50, 780.54-780.56, 780.58-780.59), and other sleep disorders (ICD-9-CM: 307.4) according to the standardized classification of International Classification of Sleep Disorders, version 2, published in 2005 and the varied nature and diagnostic steps of these disorders (Michael J. Thorpy 2012, 9(4): 687- 701). In addition, variables also relevant to PAD were age, gender, and comorbidities, such as hypertension (ICD 401-405), diabetes (ICD-9-CM codes 250), hyperlipidemia (ICD-9-CM codes 272), CAD (ICD-9-CM code 410-414), stroke (ICD-9-CM codes 430- 438), and heart failure (ICD-9 code 428). All comorbidities were confirmed and validated with at least three medical visits.
Statistical Analysis 1
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The Chi-square test and t-test were used to respectively evaluate the distributions of discrete and continuous variables between the NASD cohort and the comparison cohort.
The incidence densities of PAD were calculated by sex, age and comorbidity for each cohort. Our study used univariable and multivariable Cox proportional hazard regression models to assess the risk of PAD in the NASD cohort compared to comparison cohort.
We included baseline characteristics variables such as age, gender, and comorbidities in the multivariate model for adjustment. We estimated the hazard ratio (HR) and 95%
confidence interval (CI) in the Cox model. We used multiplicative analysis to evaluate the interaction effect of NASD and comorbidities on PAD risk. To assess the difference in the PAD-free rates between the two cohorts, we applied the Kaplan-Meier analysis and the log-rank test. We performed all statistical analyses using SAS 9.2 (SAS Institute Inc., Cary, NC, USA), with P <0.05 in two-tailed tests considered significant.
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Results
Females represented the majority of the study cohorts (63.6%); half of subjects were less than 50 years old (Table 1). Compared to the comparison cohort, the NASD cohort had a higher prevalence of common comorbidities, including hypertension, diabetes,
hyperlipidemia, CAD, stroke, heart failure, anxiety and depression (all p values <0.0001).
Kaplan-Meier survival analysis indicated that the PAD-free rate was 2% lower in the NASD cohort than in the comparison cohort (log-rank test, P < .0001) (Fig. 1). The overall incidence of PAD was 1.79-times greater in the NASD cohort than in the
comparison cohort (3.83 and 2.15 per 10,000 person-years, respectively) (Table 2). After adjusting for covariates, the risk of developing PAD remained significant for patients with NASD (adjusted HR = 1.49; 95% CI: 1.39-1.59). The incidence rate of PAD
increased with age and was slightly higher for males than for females in both cohorts. We analyzed the association between NASD and the risk of PAD stratified by comorbidity and found an approximately 1.3-fold PAD risk was observed in patients without comorbidities (adjusted HR=1.27, 95% CI: 1.18-1.37) or with comorbidity (adjusted HR=1.35, 95% CI: 1.25-1.46). We further stratified according to the status of NASD and evaluated the association between comorbidities and PAD risk in Table 3. Except heart failure in the NASD cohort, almost all comorbidities were significantly related to PAD incidence. Among these comorbidities, diabetes and hyperlipidemia were dominant factors that result in an over 2.3-fold PAD risk. Therefore, we illustrated the interactions of NASD and diabetes or hyperlipidemia on PAD risk in Table 4. We observed
statistically significant higher risk for patients with both NASD and diabetes (adjusted HR=3.58, 95% CI: 3.18-4.02) or both with NASD and hyperlipidemia (adjusted 1
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HR=3.06, 95% CI: 2.80-3.35) than those without NASD, diabetes and hyperlipidemia. In addition, there was significant interaction of NASD and diabetes, or NASD and
hyperlipidemia on PAD risk (all interaction p value <0.01). Table 5 shows different types of NASD associated with the relative risks and hazards of PAD. Compared to the non- NASD cohort, patients with sleep disturbance were 1.54-fold more likely to develop PAD (95% CI: 1.42–1.67). In addition, we found the adjusted HR is 1.46 for insomnia (95%
CI: 1.34-1.59) and 1.39 for other sleep disorders (95% CI: 1.20-1.62) after adjustment for other risk factors.
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Discussion
This nationwide population-based retrospective cohort study evaluated the association between NASD and PAD in Taiwan. We used data from the NHI national database, which covers more than 99% of the population of Taiwan. Therefore, the results can be generalized. We observed that the overall incidence rate of PAD was 79%
higher in the NASD cohort than in the non-NASD cohort, with an adjusted HR of 1.49 in the following 13 years after adjusting for sex, age, and comorbidities.
The process of sleep is complex and dynamic. The change from clear consciousness to the stage of sleep can alter the regulation of respiratory and cardiovascular systems.
Cardiovascular function is affected by many factors including autonomic nervous system, endothelial function and coagulability. Generally, sympathetic activity is pronounced during the day and parasympathetic activity is higher at night. These diurnal changes contribute to decreased hear rate, blood pressure, cardiac output and vascular resistance to non-rapid eye movement, and increased heart rate and blood pressure during rapid eye movement. Changes of endothelial functions in the brachial artery is noted and suggest that the change affects the entire vascular system. The circadian change is also related to platelet aggregation, blood viscosity, tissue plasminogen activators, and fibrinolytic activity. Circadian changes may affect coagulability.
In our study, the prevalence of comorbidities, including hypertension, diabetes, hyperlipidemia, stroke, heart failure, coronary artery disease, anxiety and depression were significantly higher in the NASD cohort than in the non-NASD cohort (p <0.0001).
These comorbidities are risk factors for developing PAD. Abnormal sleep duration with sleep deprivation that increases sleep debt and excess sleep are related to health
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problems. Studies indicate that excess sleep and insomnia increase total mortality. Zhong et al. showed that sleep deprivation increased sympathetic and decreased parasympathetic cardiovascular modulation. These sleep problems impair the endothelial function of vasodilation. People with abnormal sleep duration are more likely to decrease insulin sensitivity. Lai et al. showed that NASD increase the risk of type 2 diabetes mellitus.
Vorona demonstrated that short sleep duration is related to overweight and obesity.
Insufficiency sleep increases the development of hypertension. C-reactive protein (CRP) concentrations, a marker of inflammatory processes, are also elevated. Therefore, sleep problems may contribute to the development of metabolic syndromes. In the other hand, insomnia or sleep disturbance also increase the prevalence of depression. Patients with depressive mood also increase the inflammation activity with increased inflammation marker which may contribute the development of PAD. Current results support the previous findings.
Short sleep duration increases the risk of coronary disease. Chien et al. revealed that insomnia severity and sleep duration were related to cardiovascular disease events (mainly coronary heart disease and stroke) in Taiwan. Huang et al. showed that NASD increases the risk of ischemic stroke. Chung et al. indicated that patients with sleep disorders other than sleep apnea have an increased risk of acute coronary syndrome.
Hypertension and sleep disorders are associated with atherosclerosis risks. The progress of atherosclerosis can further decrease blood flow to the heart, brain and extremities.
From our study, the risk of developing PAD in patients with NASD was slightly higher in men. The adjusted HR was higher in younger individuals (aged < 50 years old), but over all events increased with age. The risk increase with age may be due to that older 1
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individuals have more comorbidities that predispose to the development of PAD. In the multiple analysis, the adjusted HR is 1.27 (95% CI: 1.18-1.37) in patients without comorbidities and 1.35 in patients with comorbidities (95% CI: 1.25-1.46). The risk is slightly increased in patient with comorbidities. To decrease this bias, we conducted a second analysis to elucidate the interaction between NASD and comorbidities. The adjusted HR is significantly higher in patients with both NASD and comorbidities than in patients with only NASD or only comorbidities. We later evaluated the association between the NASD and PAD subgroups. We should know that NASD is heterogenic disease that cannot be three categories only due to its diversity and insomnia is the major part of sleep disorder other the sleep related breathing disorders. Among patient with NASD, 39.2% were diagnosed with insomnia and 42.2% were diagnosed with sleep disturbance. Therefore, we suggest that NASD increases the risk of developing PAD.
This study has certain limitations. Since the data were obtained from the NHI system, we were unable to evaluate the influence of lifestyle risk factors, including diet, exercise, alcohol consumption and smoking. The database does not contain detailed information about blood sugar, blood pressure, lipid profile, homocysteine, body mass index, waistline measurements or the ankle-brachial index. We were also unable to analyze family history. These components may be important confounding factors for the development of PAD. There was no objective evidence of polysomnography or other sleep evaluation in the NASD cohort. Sleep related breathing disorders may be under- diagnosed and may be classified as NASD.這句話寫得看不是很懂? Some occult sleep diseases may also be the confounding factor to the development of PAD. Further
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prospective study is required to evaluate the influence of these factors on NASD related PAD risk.
Conclusion
In conclusion, our results provide that the risk of developing PAD is higher among people with NASD than the general population without NASD. Because of the increasing number patients with sleep disorders, being aware of the early symptoms and signs is crucial for clinical physicians due to the potential disabilities of PAD and further reduction of cardiovascular and cerebrovascular events related morbidity and mortality.
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Figure Legends
Figure 1 Free probabilities of patient peripheral arterial disease for the non-apnea sleep disorders (NASD) (dashed line) and without sleep disorders (solid line) groups
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