
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

MD-D-23-11340
00067
10.1097/MD.0000000000039341
3
6600
Research Article
Observational Study
Associations between sleep-related disorders and cardiovascular disease risk in hypertensive patients: Insights from the National Health and Nutrition Examination Survey (NHANES): A cross-sectional study
https://orcid.org/0000-0002-5917-0325
Liu Chunhua MD 365487018@qq.com
a
Chen Liping MD clp0124@aliyun.com
a
Zhang Songhua BD 376793498@qq.com
a
Wang Huaqiang PhD 018079145@qq.com
a
Liu Xiang MD 365487018@qq.com
a
Ma Jun BD lsszxyymj@163.com
b
Qiu Weiwen PhD weiwenq@hotmail.com
a
https://orcid.org/0009-0005-3446-3745
Ye Zegen BD a*
a Department of Rehabilitation, Lishui Hospital of Traditional Chinese Medicine, Affiliated to Zhejiang University of Traditional Chinese Medicine, Lishui City, China
b Lishui Central Hospital, Lishui City, China.
* Correspondence: Zegen Ye, Department of Rehabilitation, Lishui Hospital of Traditional Chinese Medicine, Zhejiang University of Chinese Medicine, 800 Zhongshan Street, Lishui City, Zhejiang 323000, China (e-mail: 932622329@qq.com).
13 9 2024
13 9 2024
103 37 e3934119 12 2023
08 2 2024
26 7 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

Both sleep-related disorders (SRD) and hypertension (HTN) are closely related to the occurrence of cardiovascular disease (CVD); however, few studies have explored their combined effect. Based on the National Health and Nutrition Examination Survey (NHANES) database, we comprehensively analyzed the combined effect of SRD and HTN on the occurrence of CVD. The weighted multivariate logistic regression analysis was adopted to explore how SRD and HTN can affect the occurrence of CVD. Specifically, the additive interaction was evaluated by the relative excess risk due to interaction (RERI), attributable proportion (AP), and the synergy index (SI), and the multiplicative interaction was evaluated by the odds ratio (OR) along with 95% confidence interval (CI) from the product term. All the 33,383 participants from the NHANES database were divided into 2 groups, i.e., the CVD (n = 3712) and non-CVD (n = 29,671) groups. The results indicated that SRD (Model 3: OR = 1.90, 95% CI: 1.60–2.25) and HTN (Model 3: OR = 2.28, 95% CI: 1.87–2.79) were both significantly associated with an increased risk of CVD. Additionally, we observed a significant additive interaction (RERI = 0.88, 95% CI: 0.03–0.65; AP = 0.22, 95% CI: 0.01–0.21; SI = 1.15, 95% CI: 1.07–1.33) and a significant multiplicative interaction (OR = 1.07, 95% CI: 1.03–1.10) between SRD and HTN on the occurrence of CVD. While both SRD and HTN are associated with CVD occurrence, their interaction can also contribute to the development of CVD.

cardiovascular disease
hypertension
interaction effect
NHANES
sleep-related disorders
OPEN-ACCESSTRUE
SDCT
==== Body
pmc1. Introduction

Cardiovascular disease (CVD) is a major chronic non-communicable condition with high morbidity and mortality, globally ranking as a leading cause of death and disability.[1] Based on the American College of Cardiology’s latest annual report, in 2019, CVD affected 9.3% of adults (26.1 million individuals), resulting in approximately 874,613 CVD-related deaths.[2] Moreover, the Global Burden of Disease (GBD) study revealed an increase of ~93% in CVD occurrence over the past 3 decades, affecting ~523 million people as of 2019.[3] With the population aging, CVD poses growing societal and economic challenges. Identifying risk factors for CVD is crucial for its prevention and treatment. Beyond conventional blood pressure management, interfering mental and behavioral conditions provides a novel approach to reducing CVD risk and burden.[4]

Hypertension (HTN) is a well-known major risk factor for CVD, contributing significantly to CVD-related deaths and disabilities globally.[5,6] For example, according to the survey data, ~10 million people worldwide succumb to CVD caused by HTN annually.[7] Mechanistically, chronic HTN can lead to vascular overload, which can further damage blood vessels, the heart, and the kidneys.[8] Improved analytical techniques and a revised broader definition of hypertension have resulted in heightened awareness of its role in CVD.[9] It is estimated that about 25% and 50% of CVD risk is linked to coronary heart disease and stroke, respectively.[10] Moreover, numerous high-quality meta-analyses confirm that lower blood pressure is strongly associated with reduced occurrence of CVD.[11–13] In addition, lifestyle factors, such as smoking, physical activity, psychosocial behavior, and poor diet, can also influence the risk of developing CVD.

Sleep duration and sleep onset time are 2 key factors in assessing sleep health. Over the past few decades, an increasing number of studies have been focused on investigating sleep and its impact on human health.[14,15] Evidence from recent studies suggests a strong association between sleep-related disorders (SRDs) and a significantly increased risk of CVD.[4,16] SRDs are characterized by sleep-related issues such as lack of sleep, insomnia, and difficulty falling asleep, which may lead to the occurrence of CVD by adversely affecting the body’s immune system and metabolism.[17] Moreover, studies have revealed elevated cortisol levels, decreased immunity, and increased markers of sympathetic nervous activity in both sleep-deprived healthy subjects and those suffering from chronic insomnia.[18–20] Several studies have also linked sleep duration to the risk of developing CVD (e.g., coronary heart disease and stroke) and mortality.[21,22] In addition, large population-based studies have shown that patients experiencing different sleep problems may have a 27% to 45% increased risk of developing CVD.[23] Recent studies have also indicated a close relationship between sleep difficulties and a high incidence of HTN.[16,24,25] Numerous studies have evaluated the relationship between sleep disorders and CVD risk, which consistently showed that sleep-related disturbances are associated with an increased risk of developing CVD and all-cause mortality.[26–28] Therefore, the co-occurrence of HTN and SRD in the same patients may synergistically impact CVD development, underscoring the need to study their combined effect. However, there is currently limited research on this critical issue.

In this study, we investigated the relationship between SRD, HTN, and the risk of CVD using data from the National Health and Nutrition Examination Survey (NHANES). We defined CVD as congestive heart failure (CHF), coronary heart disease (CHD), angina pectoris (AP), heart attack (HA), or stroke. Of note, since there is a lack of relevant information on stroke type in NHANES, all patients with stroke were included. We analyzed the individual and combined effects of SRD and HTN on CVD risk, while also compared demographic factors like age, sex, body mass index (BMI), and race.

2. Materials and methods

2.1. Study population

We conducted a cross-sectional study using data from 7 NHANES survey cycles spanning from 2005 to 2018, involving a total of 70,190 participants.[29,30] Exclusion criteria were as follows: age below 18 (n = 28,047), incomplete hypertension questionnaire data (n = 64), incomplete sleep disturbance questionnaire data (n = 485), missing important covariates (n = 2422), and no self-reported CVD information (n = 5739). The NHANES survey received approval from the Institutional Review Board/Ethical Review Board of the National Center for Health Statistics, and informed consent was obtained from participants who continued in the study after home interviews and tests.

We assigned the final 33,383 subjects into 2 groups: CVD (n = 3712) and non-CVD (n = 29,671). Ethical approval was waived by the Institutional Review Board of Lishui Hospital of Traditional Chinese Medicine Affiliated with Zhejiang University of Traditional Chinese Medicine, as the data used in this study were solely from NHANES. All research methods followed the guidelines proposed in the Declaration of Helsinki. The subject selection process is shown in Figure 1.

Figure 1. Flowchart showing the selection of participants in this study.

2.2. Data collection

We gathered demographic and health-related data, including age, sex, BMI, race, education level, income, alcohol and smoking history, diabetes, HTN, SRD, triglyceride levels, total cholesterol levels, and CVD status for all participants. To facilitate the analyses, we reclassified and preprocessed some indices from the original survey records.

First, the poverty index ratio was divided into 3 groups, i.e., ratio less than 1.3, 1.3 to 3.5, and greater than 3.5. Second, lifestyle factors, such as smoking status and drinking status, which were self-reported features, were reclassified as well. Based on the number of cigarettes smoked in an individual’s lifetime and whether he currently smokes, smoking status is divided into 3 groups, i.e., never smokers (less than 100 cigarettes in their lifetime), former smokers (more than 100 cigarettes in their lifetime and have quit smoking), and current smokers (more than 100 cigarettes in their lifetime and still smoke every day), respectively. Similarly, drinking status was classified according to the frequency of drinking per month into 3 groups, i.e., nondrinkers (1–5 times per month), slight drinkers (5–10 times per month), and heavy drinkers (more than 10 times per month). Third, obesity was divided into 2 groups, i.e., BMI less than 30 or greater than 30.[31] In addition, diabetes was defined as having at least one of the following conditions: glycosylated hemoglobin (HbA1c) level greater than 6.5%; random blood glucose level greater than or equal to 11.1 mmol/L; and use of drugs or insulin therapy for diabetes treatment.

2.3. Assessment of cardiovascular diseases

CVD was defined based on medical records and personal interview data, which included self-reports of various health issues. During the interview, the participants were asked the following question: “Have you been told by a doctor or other health professional that you had coronary artery disease, angina, heart attack, or stroke?” Participants who answered yes affirmatively were classified as having CVD. Alternatively, participants with a medical history of CVD were also classified as having CVD.[32,33]

2.4. Definition of HTN

HTN was also defined based on medical records and personal interview data; this definition of HTN is consistent with previously published literature.[25,34] During the interview, the participants were asked the following question: “Have you been told by a doctor or other health professional that you have high blood pressure?”; this question has been used for screening HTN in clinical research.[35] Participants were defined as having HTN if they answered yes affirmatively. Alternatively, the blood pressure measurements from NHANES (an average of 3 parameters) can be used to judge whether the participants had HTN. Participants would be classified as having HTN if the systolic blood pressure ≥ 130 mm Hg and diastolic blood pressure ≥ 80 mm Hg; this classification method has been widely used in previous studies.[25,34,36]

2.5. Assessment of SRD

SRD was determined by personal interview data. During the interview, the participants were asked the following question: “Have you ever told a doctor or other health professional that you have trouble sleeping/Have you ever been told by a doctor or other health professional that you have a sleep disorder?.” If the participant answered yes affirmatively, they would be classified as having SRD.

In addition, we defined other sleep-related factors, including sleep duration and sleep-onset latency, based on the NHANES sleep questionnaire, into different groups. Three groups were defined based on sleep duration (i.e., the length of sleep at night) as follows: sleep deprivation (less than 7 hours/night), normal sleep (7–8 hours/night), and hypersomnia (more than 8 hours/night); Three groups were defined based on sleep onset latency (i.e., the length of time required to fall asleep) as follows:, fast sleep onset (less than 5 minutes/night), normal sleep onset (5–30 minutes/night) and long sleep difficulty (more than 30 minutes/night).[37,38]

2.6. The additive interaction effects model

Based on the additive model, we used relative excess risk due to interaction (RERI), AP, and synergy index (SI) to evaluate the effect of additive interaction between HTN and SRP on the risk of CVD. Furthermore, we also evaluated the effect of multiplicative interaction between HTN and SRP on the risk of CVD.

Participants with different HTN and SRD statuses were defined as follows: R11 indicates the presence of both HTN and SRD; R10 indicates the presence of only HTN but not SRD; R01 indicates the presence of only SRD but not HTN; RERI = R11 − R10 − R01 + 1 represents the difference between the combined effect of the 2 factors and the sum of their individual effects, and indicates the degree of risk of the interaction, compared to all other factors except HTN and SRD. API = RERI/R11 indicates the proportion of the interaction effect in the total effect. SI = R11/ (R10 × R01) has the same definition as RERI. An additive interaction was determined if the 95% CI range for RERI or API did not cover 0, or the 95% CI range for SI did not cover 1.[39]

2.7. Statistical analysis

We employed weighted analysis to account for NHANES’ complex sampling design, utilizing interview weights (WTMEC2YR) and sampling weights for design variables (SDMVPSU and SDMVSTRA). Distribution variables were expressed as mean ± SD and compared between CVD and non-CVD groups using Student t test. Categorical data, presented as counts (n) and percentages (%), were compared using the Rao-Scott chi-square test. Statistical analyses were conducted using SPSS (version 23.0, IBM SPSS Statistics, IBM Corporation, Armonk) and R (version 4.1.2) software.

We initially used weighted univariate logistic regression to identify confounding factors. Subsequently, we employed weighted multivariate logistic regression to examine the associations between HTN or SRD and CVD risk. Our analyses were carried out using 3 models, i.e., Model 1, which was adjusted for age and sex, Model 2, which was adjusted for age, sex, race, education, and the poverty index ratio, and Model 3, which was adjusted for significant covariates including age, sex, race, education, the poverty index ratio, BMI, smoking and alcohol status, diabetes, triglyceride levels, and total cholesterol levels. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for all the 3 models.

In addition, we assessed the combined effect of HTN and SRD on CVD risk using weighted multiple regression analysis. For this, we assessed how SRD and HTN interact to influence CVD risk using statistical measures, including relative excess risk due to interaction (RERI), attributable ratio (AP), and synergy index (SI). Additive interaction was defined if the 95% CI of RERI or AP did not include 0, or if the 95% CI of SI did not include 1. OR was used to evaluate the multiplicative interaction between SRD and HTN on CVD risk. Multiplicative interaction was defined if the 95% CI of the product term did not include 1. Further, we performed subgroup (age, sex, race, and BMI) analysis to explore the interaction of HTN and SRD on CVD risk in different populations. We considered P < .05 to be statistically significant. For samples with missing data, we employed multiple interpolation methods and performed sensitivity analysis (File S1, Supplemental Digital Content, http://links.lww.com/MD/N505 and Files S2, Supplemental Digital Content, http://links.lww.com/MD/N505).

3. Results

3.1. General characteristics of participants

A total of 33,383 individuals (52% male and 48% female) were included in the study. The baseline characteristics of the participants are shown in Table 1. The incidence of CVD was found to be 9%, with 3712 individuals affected by this disease. The mean age of the participants was 65 ± 14 years. Non-hispanic whites make up 74% of all races, followed by non-Hispanic blacks at 12% and all other races at 14%.

Table 1 Comparisons of the characteristics between patients with and without CVD.

Characteristic	N*	Overall, N = 33,383 (100%)†	Disease group	P value‡	
CVDs§, N = 3712 (9%)†	Non-CVDs§, N = 29,671 (91%)†	
Age (years), Median (Mean, SD)	33,383	46 (47, 17)	67 (65, 14)	44 (45, 17)	<.001	
Age group, n (%)	33,383				<.001	
 <65 years		25,672 (82)	1458 (44)	24,214 (86)		
 ≥ 65 years		7711 (18)	2254 (56)	5457 (14)		
Sex	33,383				<.001	
 Female		17,338 (52)	1703 (48)	15,635 (53)		
 Male		16,045 (48)	2009 (52)	14,036 (47)		
Race, n (%)	33,383				<.001	
 Mexican American		5297 (8.2)	372 (4.7)	4925 (8.5)		
 Other hispanic		3034 (5.1)	249 (3.3)	2785 (5.3)		
 Non-hispanic white		14,550 (68)	2022 (74)	12,528 (68)		
 Non-hispanic black		7342 (11)	841 (12)	6501 (11)		
 Other/multiracial		3160 (7.1)	228 (5.8)	2932 (7.2)		
Race subgroup, n (%)	33,383				<.001	
 White		14,550 (68)	2022 (74)	12,528 (68)		
 Black		7342 (11)	841 (12)	6501 (11)		
 Mexican American		5297 (8.2)	372 (4.7)	4925 (8.5)		
 Other races/ethnicity		6194 (12)	477 (9.2)	5717 (13)		
Poverty-income ratio, Median (Mean, SD)	30,459	2.92 (2.96, 1.65)	2.16 (2.53, 1.54)	3.03 (3.00, 1.66)	<.001	
Poverty-income ratio, n (%)	30,459				<.001	
 <1.33		10,379 (23)	1327 (29)	9052 (22)		
 1.33–3.5		11,047 (35)	1349 (42)	9698 (34)		
 >3.5		9033 (42)	686 (29)	8347 (43)		
Education level, n (%)	31,471				<.001	
 ≤High school		8201 (17)	1287 (25)	6914 (16)		
 >High school		23,226 (83)	2419 (74)	20,807 (84)		
 Miss		44 (<0.1)	6 (<0.1)	38 (<0.1)		
BMI (kg/m2), Median (Mean, SD)	31,722	28 (29, 7)	30 (31, 7)	28 (29, 7)	<.001	
BMI subgroup, n (%)	31,722				<.001	
 Underweight (<18.5)		601 (1.8)	50 (1.4)	551 (1.8)		
 Normal (18.5 to <25)		9087 (29)	687 (19)	8400 (30)		
 Overweight (25 to <30)		10,240 (32)	1082 (32)	9158 (33)		
 Obese (≥30)		11,794 (36)	1581 (48)	10,213 (35)		
BMI subgroup 2, n (%)	31,722				<.001	
 BMI < 30		19,928 (64)	1819 (52)	18,109 (65)		
 BMI ≥ 30		11,794 (36)	1581 (48)	10,213 (35)		
Waist circumference (cm), Median (Mean, SD)	30,312	97 (99, 17)	105 (106, 16)	96 (98, 17)	<.001	
TG‖ (mg/dL), Median (Mean, SD)	14,656	105 (130, 107)	118 (145, 117)	103 (128, 106)	<.001	
TC¶ (mg/dL), Median (Mean, SD)	30,242	191 (194, 42)	175 (181, 45)	192 (195, 41)	<.001	
Diabetes, n (%)	33,383	5370 (12)	1491 (36)	3879 (10)	<.001	
Hypertension group, n (%)	33,383				<.001	
 Non-hypertension		21,623 (68)	919 (28)	20,704 (72)		
 Hypertension		11,760 (32)	2793 (72)	8967 (28)		
Alcohol consumption status, n (%)	26,669				<.001	
 Non-drinker		7744 (23)	964 (29)	6780 (23)		
 1–5 drinks/month		13,100 (50)	1503 (52)	11,597 (50)		
 5–10 drinks/month		2080 (9.5)	124 (4.2)	1956 (10)		
 10+ drinks/month		3738 (17)	365 (15)	3373 (18)		
 Miss		7 (<0.1)	1 (<0.1)	6 (<0.1)		
Smoking status, n (%)	33,383				<.001	
 Never		18,842 (55)	1492 (39)	17,350 (56)		
 Current		6787 (21)	784 (22)	6003 (21)		
 Former		7754 (24)	1436 (39)	6318 (23)		
Sleep onset latency time, n (%)	11,755				<.001	
 <5 min		1215 (11)	119 (10)	1096 (11)		
 5–30 min		8144 (71)	820 (65)	7324 (71)		
 >30 min		2396 (18)	332 (25)	2064 (17)		
Sleep duration, n (%)	30,205				<.001	
 7–8 h/night		16,092 (56)	1437 (50)	14,655 (57)		
 <7 h/night		11,584 (36)	1272 (39)	10,312 (36)		
 >8 h/night		2529 (7.5)	397 (12)	2132 (7.2)		
Sleep disorder/trouble, n (%)	33,383				<.001	
 No sleep disorder		22,752 (65)	1792 (46)	20,960 (66)		
 Sleep disorder		10,631 (35)	1920 (54)	8711 (34)		
BMI = body mass index, CVD = cardiovascular disease.

* N not Missing (unweighted).

† Median (IQR) for continuous; n (%) for categorical.

‡ Wilcoxon rank-sum test for complex survey samples; chi-squared test with Rao & Scott’s second-order correction.

§ Cardiovascular diseases.

‖ Triglyceride.

¶ Total cholesterol.

Participants in the non-CVD and CVD groups were compared in terms of age, sex, education, race, BMI, the poverty index ratio, smoking status, alcohol drinking status, hypertension status, triglyceride level, total cholesterol level, diabetes status, and sleep-related factors include sleep onset latency time and sleep duration. The results showed that all these features were significantly different between the 2 groups. In addition, the incidence of SRD was higher in the CVD group than in the non-CVD group (Table 1).

3.2. The association between SRD or HTN and the risk of CVD

As shown in Table 2, HTN was positively associated with an increased risk of CVD (model 1: OR = 3.14, 95% CI: 2.79–3.53, P < .001; model 2: OR = 3.00, 95% CI: 2.63–2.43, P < .001; Model 3: OR = 2.28, 95% CI: 1.87–2.79, P < .001). Similarly, sleep difficulties were positively associated with an elevated CVD risk (Model 1: OR = 2.07, 95% CI: 1.89–2.28, P < .001; Model 2: OR = 2.11, 95% CI: 1.91–2.34, P < .001; Model 3: OR = 1.90, 95% CI: 1.60–2.25, P < .001). A subgroup analysis of sleep-related problems showed that sleep latency of more than 30 minutes was associated with an increased risk of CVD (model 1: OR = 1.90, 95% CI: 1.40–2.59, P < .001; model 2: OR = 1.56, 95% CI: 1.13–2.16, P = .01; model 3: OR = 1.82, 95% CI: 1.09–3.03, P = .026).

Table 2 Relationship between HTN, SRD, and sleep-related characteristics and risk of CVD in a multiple logistic regression analysis model.

Characteristic	Model 1
OR (95% CI)	P value	Model 2
OR (95% CI)	P value	Model 3
OR (95% CI)	P value	
Sleep duration	
 7–8 h/night	Reference		Reference		Reference		
 <7 h/night	1.47 (1.30–1.65)	<.001	1.39 (1.22–1.59)	<.001	1.18 (0.95–1.48)	.14	
 >8 h/night	1.39 (1.15–1.69)	.001	1.35 (1.11–1.63)	.003	0.92 (0.67–1.25)	.6	
Sleep-onset latency time	
 <5 min	Reference		Reference		Reference		
 5–30 min	1.06 (0.77–1.47)	.7	0.99 (0.70–1.39)	>.9	0.93 (0.54–1.60)	.8	
 >30 min	1.90 (1.40–2.59)	<.001	1.56 (1.13–2.16)	.01	1.82 (1.09–3.03)	.026	
Sleep disorder/trouble	
 No sleep disorder/trouble	Reference		Reference		Reference		
 Sleep disorder/trouble	2.07 (1.89–2.28)	<.001	2.11 (1.91–2.34)	<.001	1.90 (1.60–2.25)	<.001	
Hypertension	
 Non-hypertension	Reference		Reference		Reference		
 Hypertension	3.14 (2.79–3.53)	<.001	3.00 (2.63–3.43)	<.001	2.28 (1.87–2.79)	<.001	
Model 1, adjustment for age and gender; Model 2, adjustment for age, gender, race, education, and family income to poverty levels; Model 3, adjustment for age, gender, race, education, family income to poverty levels, BMI, alcohol consumption status, smoking status, total cholesterol, triglyceride, and diabetes.

BMI = body mass index, CI = confidence interval, CVD = cardiovascular disease, HTN = hypertension, OR = odds ratio, SRD = sleep-related disorder.

3.3. The co-occurrence of HTN and SRD on the risk of CVD

We established an interaction term between HTN and SRD to assess the impact of their additive interactions on CVD risk. After adjusting for confounders, we observed an additive interaction between HTN and SRD (RERI = 0.88, 95% CI: 0.03–0.65; AP = 0.22, 95% CI: 0.01–0.21; SI = 1.15, 95% CI: 1.07–1.33), suggesting a synergistic effect between them (Table 3).

Table 3 The additive interaction of SRD and HTN on the risk of CVD.

Sleep disorder/trouble	Hypertension	Model 1
OR (95% CI)	P value	Model 2
OR (95% CI)	P value	Model 3
OR (95% CI)	P value	
No	No	Reference		Reference		Reference		
Yes	No	1.90 (1.57–2.31)	<.001	2.01 (1.66–2.45)	<.001	1.84 (1.44–2.35)	<.001	
No	Yes	2.97 (2.56–3.43)	<.001	2.90 (2.50–3.38)	<.001	2.21 (1.70–2.86)	<.001	
Yes	Yes	5.43 (4.70–6.28)	<.001	5.26 (4.52–6.12)	<.001	3.93 (3.17–4.86)	<.001	
RERI (95% CI)	2.56 (1.54–2.06)		1.35 (1.29–1.81)		0.88 (0.03–0.65)		
API (95% CI)	0.47 (0.25–0.33)		0.26 (0.22–0.29)		0.22 (0.01–0.21)		
SI (95% CI)	2.06 (1.95–2.31)		2.01 (1.91–2.15)		1.15 (1.07–1.33)		
Model 1, adjustment for age and gender; Model 2, adjustment for age, gender, race, education, and family income to poverty levels; Model 3, adjustment for age, gender, race, education, family income to poverty levels, BMI, alcohol consumption status, smoking status, total cholesterol, triglyceride, and diabetes.

API = attribution proportion of interaction, BMI = body mass index, CI = confidence interval, CVD = cardiovascular disease, HTN = hypertension, OR = odds ratio, RERI = relative excess risk of interaction, SI = synergy index, SRD = sleep-related disorder.

Furthermore, we assessed the multiplicative interaction of HTN and SRD on the risk of CVD (Table 4). After incorporating HTN, SRD, and the product of HTN and SRD into the multiple logistic regression model, we observed a statistically significant contributing effect of the product of HTN and SRD on CVD risk (OR = 1.07, 95% CI: 1.03–1.10, P < .001), suggesting that HTN and SRD have a possible synergistic effect. Moreover, the likelihood ratio test statistic was 2.368 (P = .0005), further suggesting an interaction between HTN and SRD influencing CVD risk.

Table 4 The multiplicative interaction of SRD and HTN on the risk of CVD.

Variables	Model 1	Model 2	Model 3	
OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	
Hypertension	1.07 (1.06–1.08)	<.001	1.06 (1.05–1.08)	<.001	1.04 (1.02–1.06)	<.001	
Sleep-related disorders	1.01 (1.00–1.02)	.002	1.02 (1.01–1.03)	<.001	1.01 (1.00–1.03)	.027	
Hypertension*Sleep-related disorders	1.06 (1.04–1.08)	<.001	1.05 (1.03–1.08)	<.001	1.07 (1.03–1.10)	<.001	
Model 1, adjustment for age and gender; Model 2, adjustment for age, gender, race, education, and family income to poverty levels; Model 3, adjustment for age, gender, race, education, family income to poverty levels, BMI, alcohol consumption status, smoking status, total cholesterol, triglyceride, and diabetes.

BMI = body mass index, CI = confidence interval, CVD = cardiovascular disease, HTN = hypertension, OR = odds ratio, SRD = sleep-related disorder.

3.4. The co-occurrence of HTN and SRD on the risk of CVD based on age, gender, ethnicity, and BMI

We further conducted subgroup analyses based on age, sex, race, and BMI. As shown in Table 5, except for individuals with a BMI of 30 or higher and the Mexican-American group, all other subgroups showed an additional interaction between HTN and SRD in influencing CVD risk. Similarly, as shown in Table 6, except for those with a BMI of 30 or higher and the Mexican-American group, all other subgroups exhibited a multiplicative interaction between HTN and SRD in influencing CVD risk.

Table 5 Associations of SRD or HTN and risk of CVD in different demographic subgroups.

	Sleep-related disorders	Hypertension	Model 1
OR (95% CI)	P value	Model 2
OR (95% CI)	P value	Model 3
OR (95% CI)	P value	
Age subgroup	
 <65 years									
	No	No	Reference		Reference		Reference		
Yes	No	1.02 (1.02–1.03)	<.001	1.02 (1.02–1.03)	<.001	1.01 (1.00–1.03)	.018	
No	Yes	1.08 (1.07–1.09)	<.001	1.08 (1.07–1.09)	<.001	1.06 (1.03–1.08)	<.001	
Yes	Yes	1.17 (1.15–1.19)	<.001	1.16 (1.14–1.18)	<.001	1.13 (1.10–1.16)	<.001	
	RERI (95% CI)	0.07 (0.06–0.52)		0.06 (0.04–0.51)		0.06 (0.03–0.49)		
	API (95% CI)	0.06 (0.05–0.51)		0.05 (0.03–0.50)		0.05 (0.04–0.48)		
	SI (95% CI)	1.70 (1.25–2.15)		1.60 (1.15–2.05)		2.17 (1.74–2.59)		
 ≥65 years									
	No	No	Reference		Reference		Reference		
Yes	No	1.06 (1.01–1.12)	.024	1.08 (1.03–1.14)	.004	1.08 (1.01–1.16)	.03	
No	Yes	1.15 (1.11–1.19)	<.001	1.15 (1.11–1.19)	<.001	1.11 (1.05–1.16)	<.001	
Yes	Yes	1.25 (1.20–1.30)	<.001	1.25 (1.20–1.30)	<.001	1.26 (1.18–1.35)	<.001	
	RERI (95% CI)	0.96 (0.36–1.56)		0.98 (0.51–1.45)		0.93 (0.30–1.56)		
	API (95% CI)	0.77 (0.17–1.37)		0.78 (0.31–1.25)		0.74 (0.11–1.37)		
	SI (95% CI)	1.19 (0.59–1.79)		1.09 (0.62–1.56)		1.37 (1.14–1.99)		
Gender subgroup	
 Female									
	No	No	Reference		Reference		Reference		
	Yes	No	1.01 (1.00–1.02)	.047	1.01 (1.00–1.02)	.024	1.01 (1.00–1.02)	.11	
	No	Yes	1.07 (1.05–1.08)	<.001	1.06 (1.04–1.08)	<.001	1.04 (1.01–1.07)	.006	
	Yes	Yes	1.14 (1.12–1.16)	<.001	1.12 (1.10–1.14)	<.001	1.13 (1.09–1.16)	<.001	
	RERI (95% CI)	0.06 (0.45–0.57)		0.95 (0.43–1.47)		0.92 (0.42–1.42)		
	API (95% CI)	0.05 (0.46–0.57)		0.85 (0.33–1.38)		0.81 (0.31–1.31)		
	SI (95% CI)	2.00 (1.49–2.51)		2.00 (1.48–2.52)		3.25 (2.75–3.75)		
 Male									
	No	No	Reference		Reference		Reference		
	Yes	No	1.01 (1.00–1.03)	.036	1.02 (1.01–1.03)	.005	1.02 (0.99–1.04)	.2	
	No	Yes	1.07 (1.06–1.09)	<.001	1.07 (1.05–1.09)	<.001	1.04 (1.02–1.07)	.002	
	Yes	Yes	1.17 (1.14–1.20)	<.001	1.17 (1.14–1.19)	<.001	1.13 (1.08–1.17)	<.001	
	RERI (95% CI)	0.09 (0.29–0.47)		0.08 (0.27–0.43)		0.93 (0.45–1.45)		
	API (95% CI)	0.08 (0.29–0.45)		0.07 (0.29–0.42)		0.82 (0.36–1.37)		
	SI (95% CI)	2.43 (2.06–2.81)		2.43 (2.08–2.78)		2.17 (1.65–2.69)		
BMI subgroup	
 BMI < 30									
	No	No	Reference		Reference		Reference		
	Yes	No	1.01 (1.00–1.02)	.033	1.01 (1.00–1.02)	.012	1.01 (0.99–1.02)	.5	
	No	Yes	1.09 (1.07–1.11)	<.001	1.08 (1.06–1.10)	<.001	1.06 (1.03–1.09)	<.001	
	Yes	Yes	1.15 (1.12–1.17)	<.001	1.13 (1.10–1.15)	<.001	1.15 (1.10–1.19)	<.001	
	RERI (95% CI)	0.05 (0.35–0.45)		0.04 (0.34–0.42)		0.08 (0.31–0.47)		
	API (95% CI)	0.04 (0.35–0.44)		0.04 (0.34–0.41)		0.07 (0.32–0.46)		
	SI (95% CI)	1.88 (1.48–2.27)		1.63 (1.25–2.00)		2.50 (2.11–2.89)		
 BMI≥30									
	No	No	Reference		Reference		Reference		
	Yes	No	1.02 (1.00–1.04)	.038	1.02 (1.01–1.04)	.006	1.03 (1.01–1.06)	.019	
	No	Yes	1.03 (1.02–1.05)	<.001	1.03 (1.01–1.05)	.002	1.02 (0.98–1.05)	.4	
	Yes	Yes	1.14 (1.11–1.16)	<.001	1.13 (1.11–1.16)	<.001	1.10 (1.06–1.14)	<.001	
	RERI (95% CI)	0.09 (–0.28–0.46)		0.08 (–0.26–0.42)		0.05 (–0.42–0.52)		
	API (95% CI)	0.08 (–0.29–0.45)		0.07 (–0.27–0.41)		0.05 (–0.43–0.52)		
	SI (95% CI)	2.80 (2.43–3.17)		4.33 (3.99–4.67)		2.00 (1.53–2.47)		
Race subgroup	
 White									
	No	No	Reference		Reference		Reference		
	Yes	No	1.01 (1.00–1.02)	.061	1.01 (1.00–1.02)	.022	1.01 (0.99–1.03)	.3	
	No	Yes	1.06 (1.05–1.08)	<.001	1.06 (1.04–1.08)	<.001	1.03 (1.00–1.06)	.026	
	Yes	Yes	1.13 (1.11–1.16)	<.001	1.12 (1.10–1.14)	<.001	1.1 (1.07–1.14)	<.001	
	RERI (95% CI)	0.06 (0.29–0.41)		0.05 (0.29–0.39)		0.06 (0.32–0.64)		
	API (95% CI)	0.05 (0.30–0.41)		0.05 (0.21–0.39)		0.06 (0.33–0.64)		
	SI (95% CI)	2.17 (1.81–2.52)		2.40 (2.05–2.75)		5.00 (4.42–5.58)		
 Black									
	No	No	Reference		Reference		Reference		
	Yes	No	1.01 (1.00–1.03)	.091	1.02 (1.00–1.04)	.044	1.03 (1.00–1.07)	.075	
	No	Yes	1.07 (1.05–1.09)	<.001	1.07 (1.05–1.09)	<.001	1.06 (1.03–1.09)	<.001	
	Yes	Yes	1.20 (1.17–1.23)	<.001	1.20 (1.16–1.23)	<.001	1.19 (1.14–1.25)	<.001	
	RERI (95% CI)	0.12 (0.47–0.69)		0.11 (0.39–0.61)		0.10 (0.42–0.62)		
	API (95% CI)	0.10 (0.47–0.67)		0.09 (0.41–0.59)		0.08 (0.44–0.61)		
	SI (95% CI)	3.30 (2.73–3.87)		2.86 (2.36–3.36)		3.17 (2.65–3.69)		
 Mexican American									
	No	No	Reference		Reference		Reference		
	Yes	No	1.03 (1.01–1.06)	.018	1.04 (1.01–1.07)	.019	1.05 (1.00–1.11)	.049	
	No	Yes	1.09 (1.06–1.12)	<.001	1.09 (1.05–1.12)	<.001	1.07 (1.01–1.13)	.024	
	Yes	Yes	1.15 (1.11–1.19)	<.001	1.14 (1.10–1.17)	<.001	1.10 (1.04–1.17)	.002	
	RERI (95% CI)	0.03 (–0.59–0.65)		0.09 (–0.51–0.69)		0.02 (–0.64–0.59)		
	API (95% CI)	0.03 (–0.59–0.64)		0.08 (–0.52–0.68)		0.02 (–0.63–0.59)		
	SI (95% CI)	1.25 (0.63–1.87)		1.08 (0.48–1.68)		0.83 (0.22–1.45)		
 Other races/ethnicity									
	No	No	Reference		Reference		Reference		
	Yes	No	1.03 (1.01–1.05)	.003	1.03 (1.01–1.05)	.006	1.02 (0.98–1.05)	.3	
	No	Yes	1.07 (1.05–1.10)	<.001	1.07 (1.04–1.10)	<.001	1.07 (1.02–1.12)	.009	
	Yes	Yes	1.21 (1.15–1.28)	<.001	1.21 (1.14–1.28)	<.001	1.22 (1.12–1.32)	<.001	
	RERI (95% CI)	0.11 (0.35–0.87)		0.11 (0.35–0.87)		0.13 (0.38–0.84)		
	API (95% CI)	0.09 (0.47–0.86)		0.09 (0.37–0.86)		0.11 (0.41–0.82)		
	SI (95% CI)	2.10 (1.34–2.86)		2.10 (1.34–2.86)		2.44 (1.73–3.16)		
Model 1, adjustment for age and gender; Model 2, adjustment for age, gender, race, education, and family income to poverty levels; Model 3, adjustment for age, gender, race, education, family income to poverty levels, BMI, alcohol consumption status, smoking status, total cholesterol, triglyceride, and diabetes.

API = attribution proportion of interaction, BMI = body mass index, CI = confidence interval, CVD = cardiovascular disease, HTN = hypertension, OR = odds ratio, RERI = relative excess risk of interaction, SI = synergy index, SRD = sleep-related disorder.

Table 6 The multiplicative interaction of HTN and SRD on the risk of different demographic subgroups.

Subgroup	Hypertension	Sleep-related disorders	Model 1
OR (95% CI)	P value	Model 2
OR (95% CI)	P value	Model 3
OR (95% CI)	P value	
<65 years	Yes		1.08 (1.07–1.09)	<.001	1.08 (1.07–1.09)	<.001	1.06 (1.03–1.08)	<.001	
	Yes	1.02 (1.02–1.03)	<.001	1.02 (1.02–1.03)	<.001	1.01 (1.00–1.03)	.018	
Hypertension * Sleep-related disorders	1.06 (1.04–1.08)	<.001	1.05 (1.03–1.07)	<.001	1.05 (1.02–1.09)	.003	
≥65 years	Yes		1.15 (1.11–1.19)	<.001	1.15 (1.11–1.19)	<.001	1.11 (1.05–1.16)	<.001	
	Yes	1.06 (1.01–1.12)	.024	1.08 (1.03–1.14)	.004	1.08 (1.01–1.16)	.03	
Hypertension * Sleep-related disorders	1.02 (0.96–1.10)	.5	1.01 (.94–1.08)	.8	1.05 (1.02–1.17)	.03	
Female	Yes		1.07 (1.05–1.08)	<.001	1.06 (1.04–1.08)	<.001	1.04 (1.01–1.07)	.006	
	Yes	1.01 (1.00–1.02)	.047	1.01 (1.00–1.02)	.024	1.01 (1.00–1.02)	.11	
Hypertension * Sleep-related disorders	1.06 (1.03–1.09)	<.001	1.05 (1.02–1.07)	.002	1.07 (1.02–1.12)	.004	
Male	Yes		1.07 (1.06–1.09)	<.001	1.07 (1.05–1.09)	<.001	1.04 (1.02–1.07)	.002	
	Yes	1.01 (1.00–1.03)	.036	1.02 (1.01–1.03)	.005	1.02 (.99–1.04)	.2	
Hypertension * Sleep-related disorders	1.07 (1.04–1.11)	<.001	1.07 (1.03–1.10)	<.001	1.07 (1.01–1.13)	.026	
BMI < 30	Yes		1.09 (1.07–1.11)	<.001	1.08 (1.06–1.10)	<.001	1.06 (1.03–1.09)	<.001	
	Yes	1.01 (1.00–1.02)	.033	1.01 (1.00–1.02)	.012	1.01 (.99–1.02)	.5	
Hypertension * Sleep-related disorders	1.04 (1.01–1.08)	.007	1.03 (1.00–1.06)	.076	1.08 (1.02–1.14)	.011	
BMI≥30	Yes		1.03 (1.02–1.05)	<.001	1.03 (1.01–1.05)	.002	1.02 (.98–1.05)	.4	
	Yes	1.02 (1.00–1.04)	.038	1.02 (1.01–1.04)	.006	1.03 (1.01–1.06)	.019	
Hypertension * Sleep-related disorders	1.08 (1.05–1.11)	<.001	1.07 (1.04–1.10)	<.001	1.05 (.99–1.10)	.082	
White	Yes		1.06 (1.05–1.08)	<.001	1.06 (1.04–1.08)	<.001	1.03 (1.00–1.06)	.026	
	Yes	1.01 (1.00–1.02)	.061	1.01 (1.00–1.02)	.022	1.01 (.99–1.03)	.3	
Hypertension * Sleep-related disorders	1.05 (1.03–1.08)	<.001	1.04 (1.02–1.07)	.001	1.06 (1.01–1.11)	.013	
Black	Yes		1.07 (1.05–1.09)	<.001	1.07 (1.05–1.09)	<.001	1.06 (1.03–1.09)	<.001	
	Yes	1.01 (1.00–1.03)	.091	1.02 (1.00–1.04)	.044	1.03 (1.00–1.07)	.075	
Hypertension * Sleep-related disorders	1.1 (1.07–1.14)	<.001	1.1 (1.06–1.13)	<.001	1.09 (1.02–1.16)	.009	
Mexican American	Yes		1.09 (1.06–1.12)	<.001	1.09 (1.05–1.12)	<.001	1.07 (1.01–1.13)	.024	
	Yes	1.03 (1.01–1.06)	.018	1.04 (1.01–1.07)	.019	1.05 (1.00–1.11)	.049	
Hypertension * Sleep-related disorders	1.02 (0.97–1.07)	.4	1.01 (.97–1.06)	.6	.98 (.92–1.06)	.6	
Other race/ethnicity	Yes		1.07 (1.05–1.10)	<.001	1.07 (1.04–1.10)	<.001	1.07 (1.02–1.12)	.009	
	Yes	1.03 (1.01–1.05)	.003	1.03 (1.01–1.05)	.006	1.02 (.98–1.05)	.3	
Hypertension * Sleep-related disorders	1.1 (1.03–1.17)	.007	1.1 (1.02–1.18)	.013	1.12 (1.01–1.25)	.033	
CI = Confidence Interval, OR = Odds Ratio; Model 1, adjustment for age and gender; Model 2, adjustment for age, gender, race, education, and family income to poverty levels; Model 3, adjustment for age, gender, race, education, family income to poverty levels, BMI, alcohol consumption status, smoking status, total cholesterol, triglyceride, and diabetes.

BMI = body mass index, CI = confidence interval, HTN = hypertension, OR = odds ratio, SRD = sleep-related disorder.

3.5. The co-occurrence of HTN and SRD on the risk of different types of CVD

Subgroup analyses based on different CVD types, including AP, CHD, CHF, HA, and stroke, were also conducted. As shown in Table 7, a significant synergistic effect between HTN and SRD on the risk of 3 types of CVD, namely CHF, HA, and stroke, was observed in Model 3. For the CHF subgroup, the findings are as follows: adjusted RERI = 1.99, 95% CI = 0.24–1.23; adjusted AP = 0.47, 95% CI = 0.10–0.18; adjusted SI = 1.40, 95% CI = 1.10–1.89, suggesting that HTN and SRD have a significant synergistic effect on CHF risk. Similarly, for the HA subgroup, the findings are as follows: adjusted RERI = 0.86, 95% CI = 0.26–0.92; adjusted AP = 0.29, 95% CI = 0.13–0.21; adjusted SI = 1.18, 95% CI = 1.32–2.25, suggesting that HTN and SRD have a significant synergistic effect on HA risk. Lastly, for the stroke subgroup, the findings are as follows: adjusted RERI = 0.67, 95% CI = 0.27–0.69; adjusted AP = 0.21, 95% CI = 0.13–0.16; adjusted S = 1.19, 95% CI = 1.01–1.43, suggesting that HTN and SRD have a significant synergistic effect on stroke risk.

Table 7 Associations of SRD or HTN and risk of CVD with different types of CVD.

	Sleep disorder/trouble	Hypertension	Model 1
OR (95% CI)	P value	Model 2
OR (95% CI)	P value	Model 3
OR (95% CI)	P value	
AP subgroup	No	No							
Yes	No	1.97 (1.29–3.00)	.002	2.09 (1.36–3.22)	<.001	1.8 (0.98–3.30)	.057	
No	Yes	2.97 (2.07–4.26)	<.001	3.03 (2.06–4.47)	<.001	2.74 (1.41–5.33)	.004	
Yes	Yes	6.83 (4.91–9.49)	<.001	6.84 (4.83–9.70)	<.001	4.61 (2.69–7.93)	<.001	
	RERI (95% CI)	3.89 (2.55–3.23)		2.72 (2.41–3.95)		1.07 (0.3–1.29)		
	API (95% CI)	0.57 (0.27–0.66)		0.39 (0.25–0.82)		0.23 (−0.11 to 0.16)		
	SI (95% CI)	2.66 (1.82–3.21)		2.92 (1.80–3.19)		2.03 (1.52–1.62)		
CHD subgroup	No	No							
Yes	No	1.7 (1.24–2.34)	.001	1.79 (1.29–2.49)	<.001	1.65 (1.02–2.69)	.042	
No	Yes	2.78 (2.17–3.55)	<.001	2.96 (2.33–3.75)	<.001	2.55 (1.69–3.84)	<.001	
Yes	Yes	4.75 (3.82–5.91)	<.001	4.90 (3.96–6.06)	<.001	3.86 (2.65–5.62)	<.001	
	RERI (95% CI)	0.27 (1.02–1.41)		1.15 (0.82–1.34)		0.66 ((0.09–0.94)		
	API (95% CI)	0.06 (0.24–0.27)		0.24 (0.20–0.22)		0.17 (−0.03 to 0.17)		
	SI (95% CI)	1.45 (1.10–1.34)		1.71 (1.46–1.99)		1.09 (0.99–1.62)		
CHF subgroup	No	No							
Yes	No	1.93 (1.30–2.85)	.001	2.03 (1.34–3.08)	.001	2.06 (1.06–4.01)	.034	
No	Yes	3.02 (2.16–4.22)	<.001	2.66 (1.85–3.82)	<.001	2.16 (1.23–3.79)	.008	
Yes	Yes	6.59 (4.88–8.89)	<.001	6.11 (4.46–8.36)	<.001	4.21 (2.52–7.04)	<.001	
	RERI (95% CI)	2.64 (2.42–2.82)		2.42 (1.27–2.46)		1.99 (0.24–1.23)		
	API (95% CI)	0.40 (0.27–0.58)		0.39 (0.15–0.55)		0.47 (0.10–0.18)		
	SI (95% CI)	2.11 (1.75–3.19)		1.57 (1.20–2.31)		1.40 (1.10–1.89)		
HA subgroup	No	No							
Yes	No	1.72 (1.28–2.30)	<.001	1.71 (1.28–2.30)	<.001	1.3 (0.83–2.03)	.2	
No	Yes	2.36 (1.85–3.01)	<.001	2.28 (1.79–2.90)	<.001	1.81 (1.25–2.63)	.002	
Yes	Yes	4.34 (3.47–5.43)	<.001	4.23 (3.38–5.29)	<.001	2.97 (2.00–4.40)	<.001	
	RERI (95% CI)	0.26 (0.12–1.34)		0.24 (−0.91 to 0.29)		0.86 (0.26–0.92)		
	API (95% CI)	0.06 (0.03–0.25)		0.06 (−0.27 to 0.06)		0.29 (0.13–0.21)		
	SI (95% CI)	1.79 (1.77–2.16)		1.39 (1.25–1.62)		1.18 (1.32–2.25)		
Stroke subgroup	No	No							
Yes	No	1.93 (1.43–2.59)	<.001	2.13 (1.57–2.91)	<.001	1.46 (0.94–2.26)	.09	
No	Yes	3.46 (2.76–4.34)	<.001	3.31 (2.58–4.23)	<.001	2.13 (1.45–3.11)	<.001	
Yes	Yes	5.38 (4.23–6.83)	<.001	5.14 (3.96–6.67)	<.001	3.26 (2.08–5.10)	<.001	
	RERI (95% CI)	0.99 (−0.10 to 0.04)		0.70 (−0.47 to 0.81)		0.67 (0.27–0.69)		
	API (95% CI)	0.18 (−0.02 to 0.01)		0.14 (−0.12 to 0.12)		0.21 (0.13–0.16)		
	SI (95% CI)	1.49 (1.32–2.04)		1.15 (1.21–1.62)		1.19 (1.01–1.43)		
Model 1, adjustment for age and gender; Model 2, adjustment for age, gender, race, education, and family income to poverty levels; Model 3, adjustment for age, gender, race, education, family income to poverty levels, BMI, alcohol consumption status, smoking status, total cholesterol, triglyceride, and diabetes.

AP = angina pectoris, API = attribution proportion of interaction, CHD = coronary heart disease, CHF = congestive heart failure, CI = confidence interval, CVD = cardiovascular disease, HA = heart attack, HTN = hypertension, OR = odds ratio, RERI = relative excess risk of interaction, SI = synergy index, SRD = sleep-related disorder.

To further evaluate the multiplicative interaction of HTN and SRD on the risk of different types of CVD, we conducted additional analyses as presented in Table 8. By incorporating HTN, SRD, and their product into a multivariable logistic regression model, we observed a potential synergistic effect between HTN and SRD on the risk of 3 types of CVD, i.e., CHF, HA, and stroke.

Table 8 The multiplicative interaction of HTN and SRD on the risk with different types of CVD subgroups.

Disease	Hypertension	Sleep-related disorders	Model 1
OR (95% CI)	P value	Model 2
OR (95% CI)	P value	Model 3
OR (95% CI)	P value	
AP subgroup	Yes		1.01 (1.01–1.02)	<.001	1.01 (1.01–1.02)	<.001	1.01 (1.00–1.03)	.084	
	Yes	1.00 (1.00–1.01)	.092	1.00 (1.00–1.01)	.052	1.00 (1.00–1.01)	.5	
Hypertension * Sleep-related disorders	1.03 (1.02–1.05)	<.001	1.03 (1.02–1.05)	<.001	1.03 (1.00–1.05)	.054	
CHD subgroup	Yes		1.03 (1.02–1.04)	<.001	1.03 (1.02–1.04)	<.001	1.02 (1.01–1.04)	.008	
	Yes	1.00 (1.00–1.01)	.2	1.00 (1.00–1.01)	.2	1.00 (0.99–1.01)	.5	
Hypertension * Sleep-related disorders	1.03 (1.01–1.04)	.001	1.02 (1.01–1.04)	.005	1.02 (1.00–1.05)	.085	
CHF subgroup	Yes		1.02 (1.01- 1.02)	<.001	1.01 (1.01–1.02)	<.001	1.01 (1.00–1.02)	.2	
	Yes	1.00 (1.00–1.01)	.2	1.00 (1.00–1.01)	.11	1.00 (1.00–1.01)	.3	
Hypertension * Sleep-related disorders	1.04 (1.02–1.05)	<.001	1.03 (1.02–1.05)	<.001	1.03 (1.01–1.06)	.007	
HA subgroup	Yes		1.02 (1.01–1.03)	<.001	1.02 (1.01–1.03)	<.001	.00–1.02)	.056	
	Yes	1.01 (1.00–1.01)	.057	1.00 (1.00–1.01)	.072	1.00 (0.99–1.01)	>.9	
Hypertension * Sleep-related disorders	1.03 (1.01–1.04)	<.001	1.03 (1.01–1.04)	<.001	1.03 (1.01–1.06)	.014	
Stroke subgroup	Yes		1.03 (1.02–1.04)	<.001	1.03 (1.02–1.03)	<.001	1.02 (1.01–1.03)	.004	
	Yes	1.00 (1.00–1.01)	.057	1.01 (1.00–1.01)	.01	1.00 (0.99–1.01)	.7	
Hypertension * Sleep-related disorders	1.02 (1.01–1.03)	<.001	1.02 (1.01–1.03)	.002	1.02 (1.01–1.04)	.009	
Model 1, adjustment for age and gender; Model 2, adjustment for age, gender, race, education, and family income to poverty levels; Model 3, adjustment for age, gender, race, education, family income to poverty levels, BMI, alcohol consumption status, smoking status, total cholesterol, triglyceride, and diabetes.

AP = angina pectoris, CHD = coronary heart disease, CHF = congestive heart failure, CI = confidence interval, CVD = cardiovascular disease, HA = heart attack, HTN = hypertension, OR = odds ratio, SRD = sleep-related disorder.

Furthermore, we investigated the relationship between HTN/SRD and overall CVD, as well as specific types of CVD, risk. The results showed that HTN was positively associated with an increased risk of overall CVD, as well as specific CVD (i.e., AP, CHF, CHD, HA, and stroke) (File S2, Supplemental Digital Content, http://links.lww.com/MD/N505); and SRD was positively associated with an increased risk of overall, as well as specific CVD (i.e., AP, CHF, CHD, HA, and stroke). Interestingly, we also found that participants with a sleep onset latency of more than 30 minutes had a significantly increased risk of overall and specific (i.e., stroke) CVD compared with participants with a sleep onset latency of less than 5 minutes (File S1, Supplemental Digital Content, http://links.lww.com/MD/N505).

4. Discussion

In this study, we determined the significant association between HTN or SRD and an increased CVD risk. Moreover, we showed that the co-occurrence of HTN and SRD is also associated with an increased CVD risk, showing a synergistic effect. These findings offer new insights into the prevention and treatment of CVD in hypertensive patients suffering from sleep disturbance.

HTN is a risk factor for CVD development and relates to many adverse cardiovascular outcomes, including stroke, coronary heart disease, and heart failure. Previous studies have shown that HTN treatment can reduce the incidence of CVD; particularly, it can reduce the risk of stroke and myocardial infarction by 40% and 15%, respectively.[40,41] Moreover, increased overall mortality and CVD-related mortality were observed in treated but uncontrolled hypertensive patients compared with normotensive adults[41,42]; this observation may be attributable to high-risk factors such as old age, obesity, and diabetes. The etiology of HTN is complex and influenced by multiple genetic, lifestyle, and environmental factors. In recent years, many studies have confirmed a close positive association between mental health issues and HTN, including sleep disorders, depression, and anxiety.[4,24,43] Therefore, we hypothesize that mental health problems, including sleep-related disorders, may be potential risk factors for the development of CVD in hypertensive patients with uncontrollable blood pressure.

Here, using an epidemiological approach, the relationship between sleep disturbances and the incidence of CVD in overall and different CVD populations (e.g., grouping based on sex, race, and BMI) was explored. Our findings suggest that prolonged sleep onset latency, difficulty falling asleep, and sleep disturbances are positively associated with CVD incidence. Moreover, participants who reported increased sleep onset latency were more prone to specific types of CVD, such as stroke. Our results are consistent with several previous studies which showed a significant relationship between SRD and CVD.[21,44] For instance, a prospective study involving 385,292 UK Biobank participants showed that healthy sleep patterns (sufficient sleep, absence of sleep problems, absence of sleep disturbances, and absence of frequent excessive daytime sleepiness) are associated with a lower occurrence of CVD, regardless of the participant’s genetic risk level.[45] Similarly, another prospective study also showed that sleep patterns have a significant effect on lifestyle-related CVD risk. The researchers found that among participants with poor sleep patterns, each additional point of poor lifestyle score was associated with a 25% increased risk of developing CVD.[46] However, these 2 studies only focused on exploring healthy combinations of sleep patterns, which might reduce the risk of CVD, and thus different from ours.

Currently, there is limited research on the synergistic effect of HTN and SRD on the development of CVD. In this study, we showed that individuals with HTN and SRD are at a higher risk of developing CVD; moreover, there is a synergistic effect between HTN and SRD, which further contributes to the risk. Further subgroup analyses based on age, sex, BMI, and race showed that the additive and multiplicative interactions of HTN and SRD on CVD risk were related to these factors. Specifically, both additive and multiplicative interactions were observed among participants in subgroups who were non-Hispanic white, white, black, other race/ethnicity, age < 65 years, age ≥ 65 years, BMI < 30, males, and females. Of note, in the subgroups with BMI ≥ 30 and Mexican American race, no statistically significant difference was observed in the additive or multiplicative interactions between HTN and SRD on CVD risk, which may be due to the small sample size (n = 372). Importantly, we fine-grained the classification of CVD (i.e., CHF, HA, and stroke) and explored associations between HTN/SRD and these specific types of CVD. We observed differences in the interactive and multiplicative interactions between HTN and SRD on CVD risk in all 3 CVD subgroups (i.e., CHF, HA, and stroke), consistent with previous findings.[47]

The present study highlights the potential interaction between HTN and SRD in influencing the occurrence of CVD. These potential mechanisms include the following aspects. First, sleep disturbances can lead to increased sympathetic activation, reduced vagal inhibition, and increased hemodynamic load, thereby increasing the risk of HTN.[25] Second, SRD is related to the coagulation system in CVD patients. Studies have shown that SRD may lead to accelerated blood clotting and platelet activation, thus increasing the risk of CVD.[48,49] In addition, systemic inflammation and oxidative stress have also been identified as important risk factors for the occurrence of CVD in HTN and SRD patients. For instance, hypertensive patients are often accompanied by systemic inflammation, which promotes insulin resistance and leads to an imbalance of reactive oxygen species (ROS) and antioxidants, further promoting the development of CVD.[34,50] Meanwhile, sleep disturbances are also associated with higher levels of oxidative stress. When hypertensive patients suffer from SRD, the resulting poor sleep patterns may increase the level of oxidative stress, further increasing the risk of CVD. Those with sleep of good quality are more inclined to sustain healthier dietary patterns and engage in active exercise routines. Conversely, sleep disruptions may negatively impact the management and control of blood pressure in individuals with HTN. In summary, the effects of HTN and SRD on CVD may be intertwined through multiple complex biological mechanisms.

5. Limitations

This cross-sectional study using NHANES data examined the interaction between HTN and SRD in relation to CVD risk. Limitations include potential bias from self-reported data for HTN, SRD, and CVD, as well as exclusion of participants with incomplete data. The definition of the average 3 blood pressure readings may be biased and inaccurate, as many patients may have white-coat hypertension rather than true hypertension. This is also an undeniable source of bias in the data of this study. Another limitation is the challenge in adjusting the confounding factors. For example, individuals who have good sleep may also have healthier lifestyles (e.g., eating healthier, getting more exercise, and smoking less). Due to this limitation, adjusting for these lifestyle factors is relatively difficult in the current study. The study’s cross-sectional nature prevents the establishment of causality. Future research should prioritize exploring causal relationships for a more comprehensive understanding of underlying mechanisms.

6. Conclusions

Both HTN and SRD individually increase CVD risk, and their interaction amplifies this risk. Understanding this interaction can enhance our knowledge of CVD in hypertensive patients. To validate and delve deeper into these findings, additional animal experiments are warranted.

Acknowledgments

We thank Professors Qiu and Ye for their critical reading and guideline; and all the included participants for their contribution.

Author contributions

Conceptualization: Chunhua Liu, Weiwen Qiu.

Data curation: Liping Chen, Huaqiang Wang, Xiang Liu, Zegen Ye.

Formal analysis: Liping Chen, Songhua Zhang, Huaqiang Wang, Xiang Liu, Zegen Ye.

Investigation: Chunhua Liu, Jun Ma, Weiwen Qiu.

Methodology: Songhua Zhang.

Resources: Huaqiang Wang, Jun Ma.

Software: Songhua Zhang, Xiang Liu, Jun Ma.

Supervision: Weiwen Qiu.

Writing – original draft: Chunhua Liu, Zegen Ye.

Writing – review & editing: Weiwen Qiu.

Supplementary Material

Abbreviations:

AP angina pectoris

API attributable proportion of interaction

BMI body mass index

CHD coronary heart disease

CHF congestive heart failure

CVD cardiovascular disease

HA heart attack

HTN hypertension

NHANES National Health and Nutritional Examination Survey

RERI relative excess risk due to interaction

SI synergy index

SRD sleep-related disorder

TG triglyceride

Our study was exempt from ethical approval by the Institutional Review Board at Lishui Hospital of Traditional Chinese Medicine, since all the data used in this study were collected from NHANES. All our methods followed the guidelines proposed by the Declaration of Helsinki.

The authors have no funding and conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

Supplemental Digital Content is available for this article.

How to cite this article: Liu C, Chen L, Zhang S, Wang H, Liu X, Ma J, Qiu W, Ye Z. Associations between sleep-related disorders and cardiovascular disease risk in hypertensive patients: Insights from the National Health and Nutrition Examination Survey (NHANES): A cross-sectional study. Medicine 2024;103:37(e39341).
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