Abstract
Background and purpose
Hypertension significantly contributes to stroke. Previous research has indicated a connection between daytime napping and stroke. Research on the connection between daytime napping duration and first stroke in hypertensive individuals is lacking nevertheless.
Methods
This research, which ran from 24 August 2013 to 31 December 2022, recruited 11,252 individuals with hypertension and without a history of stroke from the China Stroke Primary Prevention Trial. To determine the relationship between daytime napping duration and stroke onset in hypertensive individuals, we conducted analyses for threshold effects, multivariate‐adjusted Cox proportional hazard regression models, and Kaplan–Meier survival curves.
Results
The duration of daytime napping (<75 min) was positively correlated with stroke risk; beyond 75 min, the risk did not increase further. When compared to hypertensive individuals who napped for 1–30 min, daytime napping 31–60 min (hazard ratio [HR] = 1.27, 95% confidence interval [CI] = 1.06–1.53) and >60 min (HR = 1.37, 95% CI = 1.14–1.65) were substantially related with a greater risk of first stroke. Additionally, this correlation was absent in cases of hemorrhagic stroke, but present in cases of ischemic stroke, specifically for hypertensive individuals who napped for 31–60 min or >60 min (p < 0.05). Kaplan–Meier survival curves displayed that hypertensive individuals who extended daytime napping had an elevated incidence of stroke.
Conclusions
Hypertensive individuals who take longer daytime naps (>30 min) are at an elevated risk of stroke onset, particularly ischemic stroke, irrespective of other factors.
Keywords: CSPPT, daytime napping duration, hypertensive individuals, stroke, stroke subtypes
Daytime napping duration and the risk of first stroke in hypertensive individuals.
INTRODUCTION
Stroke is a significant contributor to disability and mortality in humans, jeopardizing people's health [1]. Despite recent significant advancements in the prevention and treatment of stroke, the incidence of stroke remains high. According to statistics from the Global Burden of Diseases, Injuries, and Risk Factors Study, China had an incidence of 45 cases of hemorrhagic stroke and 145 cases of ischemic stroke per 100,000 people in 2019 [2]. Furthermore, hypertension is the primary risk factor for stroke, responsible for 48% of the population's attributable risk [3]. As individuals with hypertension are at high risk for stroke, it is crucial to identify stroke risk factors to prevent strokes in this population.
Daytime napping, a common lifestyle for Chinese residents [4], has sparked the interest of many scholars for its relationship with cardiovascular and cerebrovascular diseases. Chen et al. [5] demonstrated a causal relationship between daytime napping and an elevated risk of hypertension. Research on the correlation between daytime napping and stroke risk has produced conflicting results. Mohammad [6] discovered that daytime napping was related to a lower risk of ischemic stroke; other studies, however, have shown that daytime napping is associated with an increased risk of stroke [7, 8, 9]. Furthermore, research on daytime napping and its relationship to the risk of developing various subtypes of stroke remains sparse.
Accordingly, we hypothesized that daytime napping is linked to a higher risk of first stroke in hypertensive individuals and longitudinally explored the correlation between daytime napping and the risk of first stroke and its subtypes in hypertensive individuals from rural China through long‐term follow‐up after the China Stroke Primary Prevention Trial (CSPPT), aiming to provide a reference basis for the health management of hypertensive individuals.
METHODS
Approval for this work was granted by the ethics committees of the First People's Hospital of Lianyungang and Anhui Medical University. Written informed consent was given by each subject.
Participant enrollment
The CSPPT's methodology and key findings have been published elsewhere [10, 11]. The CSPPT, a randomized, double‐blind clinical research, enrolled 20,702 hypertensive individuals from 32 communities in the Chinese provinces of Jiangsu and Anhui, who were randomly given either enalapril or enalapril folic acid for intervention follow‐up. This research was conducted from 24 August 2013, to 31 December 2022. Of all the 15,486 individuals that were registered at the Lianyungang center, 12,558 finished the exit site visit. As seen in Figure 1, the final analysis comprised 11,252 hypertensive individuals from the CSPPT after excluding participants with stroke history (n = 841), incomplete or erroneous daytime napping data, and extremes in daytime napping duration (n = 465).
FIGURE 1.
Flow chart of the research participants.
Assessment of daytime napping duration
Data about daytime napping were gathered using the inquiry, “Do you take a nap during the day?” After responding favorably, participants were asked, “When you nap, how long (in minutes) do you usually nap?” Based on the relevant literature and to ensure a balanced sample size for each subgroup, the study participants were categorized into four groups according to daytime napping duration: no naps (0 min), 1–30 min, 31–60 min, and >60 min [12, 13]. Previous research showed that ≤30‐min naps may be advantageous; thus, we utilized 1–30‐min daily naps as reference [14].
Ascertainment of first stroke
First stroke, which is defined as the first stroke incident throughout the follow‐up period ending on 31 December 2022, was the main outcome. The secondary outcomes comprised ischemic and hemorrhagic strokes. The local Centers for Disease Control and Prevention will confirm all initial stroke cases after they are reported, making sure no instances are missing or duplicated. Additionally, 5% of the cases that are submitted are chosen at random and confirmed through home or phone interviews [15].
Assessment of covariates
Baseline information was collected by using standardized questionnaires, including age, sex, treatment group, study centers, education, occupation, marital status, living standard, physical activity, smoking history, alcohol history, stress, depression, medical history (diabetes, high cholesterol, heart disease, and cancer), medication use (including drugs for hypertension, cholesterol, and antiplatelet), sleep duration, insomnia, sleep quality, snoring, and chronotype. Smoking was defined as consuming at least one cigarette per day for >1 year or a minimum of 18 packs annually in total. Alcohol consumption was defined as an average of two or more drinks per week for >1 year. Depression was assessed by the PHQ‐9 (nine‐item Patient Health Questionnaire) scale.
The physical examination measured height, weight, waist circumference, hip circumference, and blood pressure (BP). Body mass index is calculated by dividing weight (in kilograms) by height (in meters) squared. Waist‐to‐hip ratio (WHR) equals waist circumference (in centimeters) divided by hip circumference (in centimeters). Blood pressure was measured three times in the right brachial artery with an electronic blood pressure monitor, and the average of the three readings was calculated at the conclusion.
At baseline, each research participant provided an overnight fasting venous blood sample. The TaqMan assay was used to identify MTHFR C677T (rs1801133) single nucleotide polymorphisms. Homocysteine (Hcy), lipids, and fasting glucose were analyzed using Beckman Coulter automated clinical analyzers. Folic acid was assessed by a chemiluminescent immunoassay. For the purpose of determining estimated glomerular filtration rate (eGFR), the Collaborative Epidemiologic Equation for Chronic Kidney Disease is utilized [16].
Statistical analysis
For continuous variables, baseline characteristics are shown as mean (SD), and for categorical variables as proportion. Analysis of variance tests or χ 2 tests, if appropriate, were used to examine differences in baseline characteristics. The median follow‐up time was determined using the reverse Kaplan–Meier method. To identify variables related to the incidence of stroke in hypertensive individuals, univariate and multivariate Cox regression analyses were conducted (Tables S1–S3). The dose–response relationship was estimated using restricted cubic spline (RCS) and threshold effect analysis. To demonstrate the relationships elucidated by the covariates, five Cox proportional hazard regression models were constructed by gradually adjusting the variables. This study estimated the risk of the first stroke among hypertensive individuals with varying durations of daytime napping using Kaplan–Meier survival curves. Additionally, we conducted several sensitivity analyses, including (i) analyzing the entire population without excluding extreme daytime napping duration and (ii) analyzing the entire population after excluding individuals who do not nap.
In every analysis, statistical significance was determined if the dual‐tailed p‐value was <0.05. All analyses were carried out using Empower (www.empowerstats.com) and R software (http://www.R‐project.org).
RESULTS
Study participants and characteristics
Among the 11,252 hypertensive individuals (4259 men, mean age = 63.7 ± 7.4 years), 8702 (77.3%) had daytime napping, including 1217 (10.8%) with 1–30 min, 4329 (38.5%) with 31–60 min, and 3156 (28.0%) with >60 min. Over a median follow‐up of 9.4 years, 1698 first strokes were diagnosed, with 1494 being ischemic and 204 hemorrhagic. The risk of stroke, particularly ischemic stroke, was shown to be higher in hypertensive individuals who reported never napping, daytime napping for 31–60 min, or >60 min, as compared to those who reported napping for 1–30 min (Table 1).
TABLE 1.
Characteristics by the duration of daytime napping in hypertensive individuals (n = 11,252).
| Variable | Total | Daytime napping duration, min | p | |||
|---|---|---|---|---|---|---|
| 0 | 1–30 | 31–60 | >60 | |||
| n | 11,252 | 2550 | 1217 | 4329 | 3156 | |
| Age, years | 63.71 (7.44) | 63.52 (7.42) | 62.72 (7.38) | 63.87 (7.34) | 64.03 (7.58) | <0.001 |
| Sex | <0.001 | |||||
| Male | 4259 (37.9) | 749 (29.4) | 321 (26.4) | 1709 (39.5) | 1480 (46.9) | |
| Female | 6993 (62.1) | 1801 (70.6) | 896 (73.6) | 2620 (60.5) | 1676 (53.1) | |
| Treatment group | 0.113 | |||||
| Enalapril group | 5642 (50.1) | 1290 (50.6) | 570 (46.8) | 2185 (50.5) | 1597 (50.6) | |
| Enalapril–folic acid group | 5610 (49.9) | 1260 (49.4) | 647 (53.2) | 2144 (49.5) | 1559 (49.4) | |
| Study centers | <0.001 | |||||
| Donghai | 7018 (62.4) | 1666 (65.3) | 761 (62.5) | 2608 (60.2) | 1983 (62.8) | |
| Ganyu | 4234 (37.6) | 884 (34.7) | 456 (37.5) | 1721 (39.8) | 1173 (37.2) | |
| Education | <0.001 | |||||
| Illiterate | 6718 (59.7) | 1664 (65.3) | 762 (62.6) | 2551 (58.9) | 1741 (55.2) | |
| Primary school | 2367 (21.0) | 490 (19.2) | 231 (19.0) | 878 (20.3) | 768 (24.3) | |
| Middle school or higher | 2167 (19.3) | 396 (15.5) | 224 (18.4) | 900 (20.8) | 647 (20.5) | |
| Occupation | 0.001 | |||||
| Farmers | 6470 (57.5) | 1426 (55.9) | 657 (54.0) | 2526 (58.4) | 1861 (59.0) | |
| Workers | 352 (3.1) | 77 (3.0) | 34 (2.8) | 143 (3.3) | 98 (3.1) | |
| All kinds of professionals | 229 (2.0) | 38 (1.5) | 27 (2.2) | 99 (2.3) | 65 (2.1) | |
| Administrators | 53 (0.5) | 10 (0.4) | 6 (0.5) | 23 (0.5) | 14 (0.4) | |
| Service workers | 119 (1.1) | 41 (1.6) | 12 (1.0) | 37 (0.9) | 29 (0.9) | |
| Housework | 3173 (28.2) | 748 (29.3) | 381 (31.3) | 1219 (28.2) | 825 (26.1) | |
| Military | 1 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 1 (0.0) | |
| Others | 855 (7.6) | 210 (8.2) | 100 (8.2) | 282 (6.5) | 263 (8.3) | |
| Marital status | 0.087 | |||||
| Unmarried | 91 (0.8) | 24 (0.9) | 7 (0.6) | 34 (0.8) | 26 (0.8) | |
| Married | 9577 (85.1) | 2117 (83.0) | 1037 (85.2) | 3713 (85.8) | 2710 (85.9) | |
| Divorced | 18 (0.2) | 7 (0.3) | 0 (0.0) | 7 (0.2) | 4 (0.1) | |
| Widowed | 1562 (13.9) | 402 (15.8) | 172 (14.1) | 574 (13.3) | 414 (13.1) | |
| Other | 4 (0.0) | 0 (0.0) | 1 (0.1) | 1 (0.0) | 2 (0.1) | |
| Living standard | 0.031 | |||||
| Better | 2137 (19.0) | 468 (18.4) | 235 (19.3) | 845 (19.5) | 589 (18.7) | |
| Fair | 8539 (75.9) | 1922 (75.4) | 913 (75.0) | 3274 (75.6) | 2430 (77.0) | |
| Poor | 576 (5.1) | 160 (6.3) | 69 (5.7) | 210 (4.9) | 137 (4.3) | |
| Physical activity | 0.038 | |||||
| Low | 5055 (44.9) | 1168 (45.8) | 562 (46.2) | 1927 (44.5) | 1398 (44.3) | |
| Moderate | 4560 (40.5) | 1000 (39.2) | 474 (38.9) | 1823 (42.1) | 1263 (40.0) | |
| High | 1637 (14.5) | 382 (15.0) | 181 (14.9) | 579 (13.4) | 495 (15.7) | |
| Smoking history | <0.001 | |||||
| Never | 7800 (69.3) | 1945 (76.3) | 970 (79.7) | 2962 (68.4) | 1923 (60.9) | |
| Former | 1130 (10.0) | 204 (8.0) | 96 (7.9) | 468 (10.8) | 362 (11.5) | |
| Current | 2322 (20.6) | 401 (15.7) | 151 (12.4) | 899 (20.8) | 871 (27.6) | |
| Alcohol history | <0.001 | |||||
| Never | 8305 (73.8) | 2057 (80.7) | 996 (81.8) | 3189 (73.7) | 2063 (65.4) | |
| Former | 625 (5.6) | 118 (4.6) | 54 (4.4) | 239 (5.5) | 214 (6.8) | |
| Current | 2322 (20.6) | 375 (14.7) | 167 (13.7) | 901 (20.8) | 879 (27.9) | |
| BMI, kg/m2 | 25.47 (3.75) | 25.12 (3.64) | 25.53 (3.72) | 25.49 (3.71) | 25.72 (3.89) | <0.001 |
| WHR | 0.92 (0.07) | 0.91 (0.07) | 0.92 (0.06) | 0.92 (0.07) | 0.93 (0.07) | <0.001 |
| SBP, mmHg | 136.46 (17.41) | 135.86 (17.21) | 136.68 (17.88) | 136.71 (17.45) | 136.54 (17.32) | 0.243 |
| DBP, mmHg | 82.65 (10.88) | 82.03 (10.74) | 82.94 (10.65) | 82.73 (11.00) | 82.94 (10.90) | 0.008 |
| Stress | 0.024 | |||||
| Never | 9007 (80.0) | 2006 (78.7) | 951 (78.1) | 3475 (80.3) | 2575 (81.6) | |
| Moderate | 1804 (16.0) | 425 (16.7) | 220 (18.1) | 697 (16.1) | 462 (14.6) | |
| High | 441 (3.9) | 119 (4.7) | 46 (3.8) | 157 (3.6) | 119 (3.8) | |
| Depression | 0.008 | |||||
| No depression | 8991 (79.9) | 1990 (78.0) | 952 (78.2) | 3552 (82.1) | 2497 (79.1) | |
| Mild depression | 1823 (16.2) | 446 (17.5) | 216 (17.7) | 637 (14.7) | 524 (16.6) | |
| Moderate depression | 333 (3.0) | 84 (3.3) | 35 (2.9) | 112 (2.6) | 102 (3.2) | |
| Moderately severe depression | 75 (0.7) | 20 (0.8) | 10 (0.8) | 19 (0.4) | 26 (0.8) | |
| Major depression | 30 (0.3) | 10 (0.4) | 4 (0.3) | 9 (0.2) | 7 (0.2) | |
| Medical history | ||||||
| Diabetes mellitus | 0.009 | |||||
| No | 10,981 (97.6) | 2502 (98.1) | 1186 (97.5) | 4236 (97.9) | 3057 (96.9) | |
| Yes | 271 (2.4) | 48 (1.9) | 31 (2.5) | 93 (2.1) | 99 (3.1) | |
| High cholesterol | 0.042 | |||||
| No | 11,064 (98.3) | 2505 (98.2) | 1199 (98.5) | 4272 (98.7) | 3088 (97.8) | |
| Yes | 188 (1.7) | 45 (1.8) | 18 (1.5) | 57 (1.3) | 68 (2.2) | |
| Angina pectoris | 0.064 | |||||
| No | 11,210 (99.6) | 2538 (99.5) | 1208 (99.3) | 4315 (99.7) | 3149 (99.8) | |
| Yes | 42 (0.4) | 12 (0.5) | 9 (0.7) | 14 (0.3) | 7 (0.2) | |
| Myocardial infarction | 0.326 | |||||
| No | 11,204 (99.6) | 2544 (99.8) | 1211 (99.5) | 4306 (99.5) | 3143 (99.6) | |
| Yes | 48 (0.4) | 6 (0.2) | 6 (0.5) | 23 (0.5) | 13 (0.4) | |
| Heart failure | 0.882 | |||||
| No | 11,238 (99.9) | 2548 (99.9) | 1215 (99.8) | 4323 (99.9) | 3152 (99.9) | |
| Yes | 14 (0.1) | 2 (0.1) | 2 (0.2) | 6 (0.1) | 4 (0.1) | |
| Atrial fibrillation | 0.741 | |||||
| No | 11,234 (99.8) | 2544 (99.8) | 1215 (99.8) | 4323 (99.9) | 3152 (99.9) | |
| Yes | 18 (0.2) | 6 (0.2) | 2 (0.2) | 6 (0.1) | 4 (0.1) | |
| Other arrhythmia | 0.106 | |||||
| No | 11,083 (98.5) | 2510 (98.4) | 1192 (97.9) | 4260 (98.4) | 3121 (98.9) | |
| Yes | 169 (1.5) | 40 (1.6) | 25 (2.1) | 69 (1.6) | 35 (1.1) | |
| Cancer | 0.752 | |||||
| No | 11,209 (99.6) | 2542 (99.7) | 1212 (99.6) | 4314 (99.7) | 3141 (99.5) | |
| Yes | 43 (0.4) | 8 (0.3) | 5 (0.4) | 15 (0.3) | 15 (0.5) | |
| Medication use | ||||||
| Antihypertensive drugs | 0.223 | |||||
| No | 314 (2.8) | 76 (3.0) | 40 (3.3) | 119 (2.7) | 79 (2.5) | |
| Yes | 10,933 (97.2) | 2474 (97.0) | 1175 (96.5) | 4209 (97.2) | 3075 (97.4) | |
| Unknown | 5 (0.0) | 0 (0.0) | 2 (0.2) | 1 (0.0) | 2 (0.1) | |
| Lipoprotein‐lowering drugs | 0.143 | |||||
| No | 11,073 (98.4) | 2512 (98.5) | 1194 (98.1) | 4271 (98.7) | 3096 (98.1) | |
| Yes | 167 (1.5) | 37 (1.5) | 20 (1.6) | 52 (1.2) | 58 (1.8) | |
| Unknown | 12 (0.1) | 1 (0.0) | 3 (0.2) | 6 (0.1) | 2 (0.1) | |
| Antiplatelet drugs | 0.067 | |||||
| No | 10,943 (97.3) | 2492 (97.7) | 1172 (96.3) | 4214 (97.3) | 3065 (97.1) | |
| Yes | 301 (2.7) | 56 (2.2) | 43 (3.5) | 115 (2.7) | 87 (2.8) | |
| Unknown | 8 (0.1) | 2 (0.1) | 2 (0.2) | 0 (0.0) | 4 (0.1) | |
| Laboratory results | ||||||
| Total cholesterol, mmol/L | 5.39 (1.08) | 5.34 (1.07) | 5.37 (1.05) | 5.38 (1.08) | 5.44 (1.09) | 0.005 |
| Triglycerides, mmol/L | 1.86 (1.53) | 1.75 (1.43) | 1.88 (1.27) | 1.85 (1.50) | 1.94 (1.74) | <0.001 |
| HDL cholesterol, mmol/L | 1.28 (0.31) | 1.29 (0.30) | 1.25 (0.29) | 1.27 (0.31) | 1.28 (0.32) | 0.01 |
| Fasting glucose, mmol/L | 6.33 (2.07) | 6.24 (1.83) | 6.27 (1.95) | 6.34 (2.07) | 6.43 (2.29) | 0.005 |
| Homocysteine, μmol/L | 13.44 (6.91) | 13.06 (6.49) | 12.49 (5.09) | 13.48 (6.44) | 14.07 (8.28) | <0.001 |
| Folic acid, nmol/L | 17.88 (13.59) | 18.21 (13.86) | 18.18 (13.04) | 18.04 (14.18) | 17.28 (12.70) | 0.032 |
| eGFR, ml/min/1.73 m2 | 89.37 (14.44) | 89.52 (14.45) | 90.90 (14.01) | 89.08 (14.40) | 89.05 (14.64) | 0.001 |
| MTHFR C677T polymorphisms | 0.489 | |||||
| CC | 2638 (23.4) | 635 (24.9) | 294 (24.2) | 983 (22.7) | 726 (23.0) | |
| CT | 5631 (50.0) | 1241 (48.7) | 604 (49.6) | 2198 (50.8) | 1588 (50.3) | |
| TT | 2983 (26.5) | 674 (26.4) | 319 (26.2) | 1148 (26.5) | 842 (26.7) | |
| Sleep duration, h/night | <0.001 | |||||
| ≥10 | 619 (5.5) | 115 (4.5) | 43 (3.5) | 205 (4.7) | 256 (8.1) | |
| 7 to 9 | 8432 (74.9) | 1784 (70.0) | 905 (74.4) | 3313 (76.5) | 2430 (77.0) | |
| 5 to 6 | 1836 (16.3) | 502 (19.7) | 215 (17.7) | 710 (16.4) | 409 (13.0) | |
| ≤4 | 365 (3.2) | 149 (5.8) | 54 (4.4) | 101 (2.3) | 61 (1.9) | |
| Insomnia | <0.001 | |||||
| Never | 6647 (59.1) | 1429 (56.0) | 659 (54.1) | 2568 (59.3) | 1991 (63.1) | |
| Sometimes | 3716 (33.0) | 795 (31.2) | 433 (35.6) | 1489 (34.4) | 999 (31.7) | |
| 1–6 months | 378 (3.4) | 144 (5.6) | 39 (3.2) | 129 (3.0) | 66 (2.1) | |
| >6 months | 511 (4.5) | 182 (7.1) | 86 (7.1) | 143 (3.3) | 100 (3.2) | |
| Sleep quality | <0.001 | |||||
| Good | 5145 (45.7) | 1049 (41.1) | 459 (37.7) | 2024 (46.8) | 1613 (51.1) | |
| Fair | 4893 (43.5) | 1070 (42.0) | 590 (48.5) | 1944 (44.9) | 1289 (40.8) | |
| Bad | 1214 (10.8) | 431 (16.9) | 168 (13.8) | 361 (8.3) | 254 (8.0) | |
| Snoring | <0.001 | |||||
| Never | 5435 (48.3) | 1407 (55.2) | 603 (49.5) | 2018 (46.6) | 1407 (44.6) | |
| Does | 5227 (46.5) | 1017 (39.9) | 540 (44.4) | 2082 (48.1) | 1588 (50.3) | |
| Do not know | 590 (5.2) | 126 (4.9) | 74 (6.1) | 229 (5.3) | 161 (5.1) | |
| Chronotype | 0.431 | |||||
| Clearly “early morning type” | 5930 (52.7) | 1323 (51.9) | 632 (51.9) | 2291 (52.9) | 1684 (53.4) | |
| Clearly “night type” | 381 (3.4) | 78 (3.1) | 52 (4.3) | 132 (3.0) | 119 (3.8) | |
| Possibly favoring “early morning type” | 4674 (41.5) | 1084 (42.5) | 506 (41.6) | 1803 (41.6) | 1281 (40.6) | |
| Possibly favoring “night type” | 267 (2.4) | 65 (2.5) | 27 (2.2) | 103 (2.4) | 72 (2.3) | |
| Outcome | ||||||
| Total stroke | <0.001 | |||||
| No | 9554 (84.9) | 2190 (85.9) | 1072 (88.1) | 3666 (84.7) | 2626 (83.2) | |
| Yes | 1698 (15.1) | 360 (14.1) | 145 (11.9) | 663 (15.3) | 530 (16.8) | |
| Ischemic stroke | 0.003 | |||||
| No | 9758 (86.7) | 2233 (87.6) | 1090 (89.6) | 3732 (86.2) | 2703 (85.6) | |
| Yes | 1494 (13.3) | 317 (12.4) | 127 (10.4) | 597 (13.8) | 453 (14.4) | |
| Hemorrhagic stroke | 0.019 | |||||
| No | 11,048 (98.2) | 2507 (98.3) | 1199 (98.5) | 4263 (98.5) | 3079 (97.6) | |
| Yes | 204 (1.8) | 43 (1.7) | 18 (1.5) | 66 (1.5) | 77 (2.4) | |
Note: Categorical variables and continuous variables are shown as n (%) and mean (SD), respectively.
Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; HDL, high‐density lipoprotein; SBP, systolic blood pressure; WHR, waist‐to‐hip ratio.
Relationship of daytime napping duration with first stroke in hypertensive individuals
Multivariate‐adjusted RCS analysis showed a nonlinear correlation between the duration of daytime napping and the risk of total stroke and ischemic stroke. Furthermore, threshold effect analyses showed a positive correlation between daytime napping duration (<75 min) and risk of first stroke. For daytime napping of ≥75 min, the risk of first stroke did not increase further (refer to Figure 2a and Table 2).
FIGURE 2.
Relationship of daytime napping duration with first stroke in hypertensive individuals using a restricted cubic spline regression model of analysis: (a) stroke, (b) ischemic stroke, (c) hemorrhagic stroke. Data were adjusted for age, sex, treatment group, study centers, education, occupation, marital status, living standard, physical activity, smoking history, alcohol history, body mass index, waist‐to‐hip ratio, systolic blood pressure, diastolic blood pressure, stress, depression, medical history, medication use, laboratory results (total cholesterol, triglycerides, high‐density lipoprotein cholesterol, fasting glucose, homocysteine, folic acid, estimated glomerular filtration rate, MTHFR C677T), sleep duration, insomnia, sleep quality, snoring, and chronotype. CI, confidence interval; HR, hazard ratio.
TABLE 2.
Threshold effect analysis of daytime napping duration and first stroke in hypertensive individuals.
| Adjusted HR (95% CI) | p | |
|---|---|---|
| One‐line linear regression model | 1.002 (1.000–1.003) | 0.024 |
| Two‐piecewise linear regression model | ||
| Threshold | 75 | |
| Daytime napping duration < 75 min | 1.006 (1.002–1.011) | 0.008 |
| Daytime napping duration > 75 min | 0.999 (0.997–1.002) | 0.628 |
| LRT test | 0.036 |
Note: Adjusted for age, sex, treatment group, study centers, education, occupation, marital status, living standard, physical activity, smoking history, alcohol history, body mass index, waist‐to‐hip ratio, systolic blood pressure, diastolic blood pressure, stress, depression, medical history, medication use, laboratory results, sleep duration, insomnia, sleep quality, snoring, and chronotype.
Abbreviation: LRT, logarithmic likelihood ratio.
Kaplan–Meier survival curves indicated that appropriate daytime napping (1–30 min) may have the lowest incidence of stroke, particularly ischemic stroke (Figure 3). After multivariate adjustment, compared to daytime napping for 1–30 min, daytime napping for 31–60 min (hazard ratio [HR] = 1.27, 95% confidence interval [CI] = 1.06–1.53) and >60 min (HR = 1.37, 95% CI = 1.14–1.65) were associated with a 27% and 37% higher risk of first stroke, respectively. Moreover, significant associations were also obtained for ischemic stroke with daytime napping of 31–60 min (HR = 1.31, 95% CI = 1.08–1.58) and >60 min (HR = 1.33, 95% CI = 1.08–1.62). However, this association with hemorrhagic stroke has not been found (Table 3). More importantly, when we reran the sensitivity analysis, we observed similar results (Figures [Link], [Link], [Link], [Link], [Link], [Link], Tables S4–S15).
FIGURE 3.
Kaplan–Meier survival curves for daytime napping duration: (a) stroke, (b) ischemic stroke, (c) hemorrhagic stroke.
TABLE 3.
Association of daytime napping duration with first stroke in hypertensive individuals using different models of analysis.
| Daytime napping duration, min | Cases, n/N (%) | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | HR (95% CI) | p | HR (95% CI) | p | HR (95% CI) | p | ||
| Stroke | |||||||||||
| Duration | 1698/11,252 (15.1) | 1.00 (1.00–1.00) | <0.001 | 1.00 (1.00–1.00) | 0.002 | 1.00 (1.00–1.00) | 0.007 | 1.00 (1.00–1.00) | 0.007 | 1.00 (1.00–1.00) | 0.016 |
| Categories | |||||||||||
| 0 | 360/2550 (14.1) | 1.21 (0.99–1.46) | 0.057 | 1.17 (0.97–1.42) | 0.108 | 1.17 (0.97–1.42) | 0.106 | 1.18 (0.98–1.44) | 0.088 | 1.19 (0.98–1.45) | 0.072 |
| 1–30 | 145/1217 (11.9) | Ref | Ref | Ref | Ref | Ref | |||||
| 31–60 | 663/4329 (15.3) | 1.32 (1.11–1.58) | 0.002 | 1.27 (1.06–1.52) | 0.009 | 1.28 (1.07–1.54) | 0.007 | 1.28 (1.07–1.53) | 0.008 | 1.27 (1.06–1.53) | 0.009 |
| >60 | 530/3156 (16.8) | 1.47 (1.22–1.77) | <0.001 | 1.40 (1.17–1.69) | <0.001 | 1.38 (1.14–1.66) | <0.001 | 1.38 (1.15–1.67) | <0.001 | 1.37 (1.14–1.65) | <0.001 |
| p for trend | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | ||||||
| Ischemic stroke | |||||||||||
| Duration | 1494/11,252 (13.3) | 1.00 (1.00–1.00) | 0.004 | 1.00 (1.00–1.00) | 0.017 | 1.00 (1.00–1.00) | 0.043 | 1.00 (1.00–1.00) | 0.041 | 1.00 (1.00–1.00) | 0.077 |
| Categories | |||||||||||
| 0 | 317/2550 (12.4) | 1.21 (0.99–1.49) | 0.066 | 1.18 (0.96–1.45) | 0.118 | 1.18 (0.96–1.45) | 0.118 | 1.19 (0.97–1.46) | 0.098 | 1.20 (0.97–1.47) | 0.086 |
| 1–30 | 127/1217 (10.4) | Ref | Ref | Ref | Ref | Ref | |||||
| 31–60 | 597/4329 (13.8) | 1.36 (1.12–1.65) | 0.002 | 1.30 (1.08–1.58) | 0.007 | 1.31 (1.08–1.59) | 0.005 | 1.31 (1.08–1.59) | 0.005 | 1.31 (1.08–1.58) | 0.007 |
| >60 | 453/3156 (14.4) | 1.43 (1.18–1.74) | <0.001 | 1.36 (1.12–1.66) | 0.002 | 1.33 (1.09–1.63) | 0.004 | 1.34 (1.10–1.64) | 0.004 | 1.33 (1.08–1.62) | 0.006 |
| p for trend | <0.001 | 0.001 | 0.003 | 0.003 | 0.006 | ||||||
| Hemorrhagic stroke | |||||||||||
| Duration | 204/11,252 (1.8) | 1.00 (1.00–1.01) | 0.02 | 1.00 (1.00–1.01) | 0.028 | 1.00 (1.00–1.01) | 0.04 | 1.00 (1.00–1.01) | 0.038 | 1.00 (1.00–1.01) | 0.061 |
| Categories | |||||||||||
| 0 | 43/2550 (1.7) | 1.14 (0.66–1.98) | 0.634 | 1.12 (0.64–1.93) | 0.698 | 1.12 (0.65–1.94) | 0.687 | 1.12 (0.64–1.95) | 0.692 | 1.15 (0.66–2.01) | 0.612 |
| 1–30 | 18/1217 (1.5) | Ref | Ref | Ref | Ref | Ref | |||||
| 31–60 | 66/4329 (1.5) | 1.04 (0.62–1.75) | 0.888 | 1.01 (0.60–1.70) | 0.976 | 1.02 (0.61–1.73) | 0.927 | 1.01 (0.60–1.71) | 0.974 | 1.01 (0.60–1.71) | 0.969 |
| >60 | 77/3156 (2.4) | 1.67 (1.00–2.80) | 0.049 | 1.62 (0.97–2.72) | 0.067 | 1.61 (0.96–2.71) | 0.072 | 1.61 (0.96–2.71) | 0.074 | 1.60 (0.95–2.71) | 0.078 |
| p for trend | 0.019 | 0.027 | 0.031 | 0.032 | 0.045 | ||||||
Note: Model 1: unadjusted. Model 2: adjusted for age and sex. Model 3: adjusted for covariates in model 2 and treatment group, study centers, education, occupation, marital status, living standard, physical activity, smoking history, alcohol history, body mass index, waist‐to‐hip ratio, systolic blood pressure, diastolic blood pressure, stress, and depression. Model 4: adjusted for covariates in model 3 and medical history, medication use, and laboratory results. Model 5: fully adjusted.
Abbreviations: CI, confidence interval; HR, hazard ratio; Ref, reference.
DISCUSSION
Based on a large‐scale cohort study of hypertension in rural China, this research identified, for the first time, a dose–response relationship between daytime napping duration and first stroke risk; daytime napping for <75 min was positively correlated with the risk of first stroke, and the risk remained relatively stable for daytime napping of 75 min or more. Daytime napping for >30 min was independently related to a higher risk of first stroke in hypertensive individuals, as shown by the results of multivariable‐adjusted Cox proportional hazard regression models. Consistent with the results of our research, Yan et al. [13], based on the Sleep Heart Health Study of 4757 older adults, found that daytime napping for >30 min may increase stroke risk; Mc Carthy et al. [7], in an international case–control study of 4496 older individuals, discovered a significant connection between daytime napping (>60 min) and a higher risk of stroke. However, in a cohort study of 12,268 Swedish twins, Wang et al. [17] demonstrated that daytime napping for 1–30 min and >30 min both had a higher risk of stroke. This finding is inconsistent with the results of our research, which may be attributed to the following factors: (i) our study population was Chinese stroke‐free hypertensive individuals, whereas theirs consisted of Swedish twins without coronary heart disease and stroke history; (ii) our research collected a greater number of covariates that may have influenced the results compared with the study by Wang et al., including occupation, living standard, WHR, BP, stress, medical history, medication use, laboratory results, insomnia, sleep quality, snoring, and chronotype.
Zhou et al. [8], in the China Dongfeng‐Tongji cohort study of 31,750 older persons, revealed that long daytime napping has been linked to a higher risk of ischemic stroke rather than hemorrhagic stroke. Our research further analyzed different subtypes of stroke and found similar results. Daytime napping for >30 min in hypertensive individuals was independently linked to an elevated risk of first ischemic stroke. Of note, a significant association with the risk of first hemorrhagic stroke has not been found. Possible explanations for the absence of linkage include that (i) the incidence of ischemic stroke is much higher than that of hemorrhagic stroke [18] and (ii) the sample size for this research is not large enough. Further research is needed to investigate whether there is a connection between the duration of daytime napping and the risk of experiencing a first hemorrhagic stroke in larger sample sizes.
The mechanisms by which long daytime napping leads to an increased risk of stroke in hypertensive individuals are not fully understood. Possible mechanisms include that after a nap, the second peak of BP occurs. When people wake up from a long nap, the sudden change in sympathetic arousal and physical activity causes a rapid increase in BP, which may trigger a stroke [19, 20]. Second, long daytime napping is linked to higher levels of cortisol in the evening. Elevated nocturnal cortisol levels may result from dysregulation of the hypothalamic–pituitary–adrenal axis, which can elevate BP and potentially lead to a stroke [21, 22]. Third, long daytime napping has been linked to increased levels of specific inflammatory markers such as progranulin and interleukin‐6 [23]. This inflammatory state, in turn, contributes to elevated BP, which subsequently increases the risk of stroke [24, 25]. Fourth, extended daytime napping can increase overall sleep duration, and longer sleep duration has been substantially linked to an elevated risk of stroke [26].
Strengths of this research include that it is the first research, within a large‐scale cohort study of hypertension in rural China, to analyze the correlation between daytime napping duration and first stroke risk. Second, the median follow‐up time in this research was up to 9.4 years. Third, this research not only corrected for common covariates but also for several covariates associated with stroke risk, including the MTHFR C677T gene [27], Hcy [28], folate level [29], and eGFR [30], which are less frequently addressed in other studies. There are a few limitations to be aware of, however. First, information on daytime napping was obtained through a self‐reported questionnaire, which may introduce recall bias and misclassification bias. Notably, in population studies with large sample sizes, objective measurement of sleep is not easy to implement, and previous studies have reported obtaining detailed information about sleep through standardized questionnaires [31, 32]. Second, the impact of daytime napping frequency on stroke risk was not considered in this research. Future studies could explore the relationship between daytime napping frequency and stroke risk in hypertensive individuals. Third, obstructive sleep apnea (OSA) is a significant risk factor for stroke [33]; this research, however, did not use polysomnography to assess OSA objectively. This research collected information on snoring, which is the most common symptom of OSA [34], potentially reducing the biasing effect of OSA on the results. Fourth, our study population consisted of elderly hypertensive individuals without a history of stroke from rural China. Therefore, the results may not be generalizable to populations in different age groups, with other health conditions, or in other countries. Future studies could validate the results of this research further by expanding the sample source.
CONCLUSIONS
Long daytime napping (>30 min) may be an independent risk factor for the first stroke in hypertensive individuals, especially the first ischemic stroke. For hypertensive individuals, the optimal duration of daytime napping maybe 30 min or less.
AUTHOR CONTRIBUTIONS
Jinhong Wu and Lishun Liu: Conceptualization; writing–original draft; formal analysis; data curation; project administration; writing–review and editing. Zena Huang: Formal analysis; data curation; software; writing–review and editing. Li Wang and Fengjiao Cai: Conceptualization; writing–review and editing. Aimin Li, Yong Sun, Binyan Wang, Jianping Li, Yong Huo, and Yan Lu: Supervision; writing–review and editing; conceptualization.
FUNDING INFORMATION
The study was supported by funding from the National Key Research and Development Program of China (2022YFC2009600, 2022YFC2009601); the Guangdong Provincial Key Laboratory of H‐type Hypertension and Stroke Precision Prevention Research and Development Enterprise (2020B121202010); the Science, Technology, and Innovation Committee of Shenzhen (JSGG20201103153807021, KCXFZ20211020163801002); the Development and Reform Commission of Shenzhen Municipality (XMHT20220104055); the fifth “333” high‐level talent training project of Jiangsu Province (BRA2019247); and the Medical Research Project of Jiangsu Provincial Health Commission in 2020 (ZDA2020018).
CONFLICT OF INTEREST STATEMENT
None of the authors has any conflict of interest to disclose.
Supporting information
Data S1.
Figure S1.
Figure S2.
Figure S3.
Figure S4.
Figure S5.
Figure S6.
ACKNOWLEDGMENTS
We appreciate the participants and investigators of CSPPT. We acknowledge the contribution of Wenjun Li. Thanks also to WPS for providing the elements for the graphical abstract.
Wu J, Liu L, Huang Z, et al. Long daytime napping: A silent danger for hypertensive individuals. Eur J Neurol. 2024;31:e16382. doi: 10.1111/ene.16382
Jinhong Wu and Lishun Liu contributed equally to this work.
Registration for clinical studies at https://www.clinicaltrials.gov (NCT00794885).
Contributor Information
Yong Huo, Email: huoyong@263.net.cn.
Yan Lu, Email: luyansxmu@163.com.
DATA AVAILABILITY STATEMENT
Upon a reasonable request to the corresponding author, data supporting the study's results can be provided to qualified investigators.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1.
Figure S1.
Figure S2.
Figure S3.
Figure S4.
Figure S5.
Figure S6.
Data Availability Statement
Upon a reasonable request to the corresponding author, data supporting the study's results can be provided to qualified investigators.