Association of bedtime with co-morbid hypertension in OSA: a community-based study

Abstract

Objective

Obstructive sleep apnea (OSA) is a recognized risk factor for hypertension, contributing to cardiovascular disease through mechanisms like nocturnal hypoxia and sympathetic dysfunction. The role of bedtime habits in OSA-associated hypertension remains underexplored. This study investigates the association between bedtime habits and hypertension in OSA patients.

Methods

A cross-sectional study analyzed baseline data from 6,193 community-dwelling adults in Guangdong Province, China, were analyzed. Sleep behavior habits and quality were assessed using the Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI). Self-reported bedtime was categorized as early (≤ 21:59), moderate (22:00–23:59), or late (≥ 00:00). OSA was diagnosed using a Type IV wearable intelligent sleep monitor. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or self-reported hypertension history.

Result

OSA was present in 2,660 participants (42.9%). Among individuals with OSA, hypertension prevalence was 56.6% in early bedtimes, 36.9% in moderate bedtimes, and 30.7% in late bedtimes (P < 0.001). In the fully adjusted model, moderate bedtime (OR 0.64, 95% CI 0.48–0.86) and late bedtime (OR 0.67, 95% CI 0.47–0.95) were associated with lower odds of prevalent hypertension compared with early bedtime (reference). Early bedtime remained associated with longer sleep latency, lower sleep efficiency, and higher Pittsburgh Sleep Quality Index and Insomnia Severity Index scores (all P < 0.05).

Conclusion

Early bedtime (≤ 21:59) was independently associated with higher odds of comorbid hypertension in adults with OSA, while moderate and late bedtimes were associated with lower odds after comprehensive adjustment. Bedtime represents a volitional lifestyle behavior that may be targeted for cardiovascular risk reduction in OSA.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11325-026-03579-1.

Introduction

Sleep duration, sleep quality, and chronotype have each been independently associated with cardiovascular risk in large population cohorts [1, 2]. More recently, bedtime itself has emerged as a distinct behavioural exposure. In the UK Biobank, sleep onset between 22:00 and 22:59 was associated with the lowest incidence of cardiovascular events [3]. Disruptions to circadian rhythms from irregular sleep schedules can increase inflammation, impair insulin sensitivity, and alter neurotransmitter systems, elevating the risk of psychiatric disorders [4].

OSA is characterized by recurrent upper airway collapse and intermittent hypoxia during sleep [5]. OSA is an established independent risk factor for hypertension. Approximately 30% to 50% of patients with OSA have hypertension, and conversely, OSA is present in about 50% of hypertensive patients [6]. The comorbidity is primarily driven by nocturnal hypoxemia and microarousals, which activate the sympathetic nervous system and lead to elevated blood pressure [7]. A meta-analysis indicates that OSA patients are 4.16 times more likely to develop treatment-resistant hypertension compared to those without OSA [8].This high prevalence and comorbidity increase treatment challenges and disease burden. However, not all OSA patients develop hypertension, suggesting individual variations in risk.

OSA patients exhibit distinct sleep behavioral characteristics compared to the general population due to nocturnal apneas that disrupt sleep architecture. Irregular sleep-wake patterns are more common in OSA patients and are associated with increased hypertension risk [9].The SAVE study found that OSA patients with cardiovascular disease and sleep durations exceeding 8 h faced a higher risk of cerebrovascular events [10], while excessively short sleep durations were linked to elevated hypertension risk [11]. Although sleep duration has been studied in relation to cardiovascular outcomes in OSA, whether habitual bedtime is associated with hypertension in this high-risk population remains unknown. Besides bedtime represents a highly volitional lifestyle behaviour that individuals can directly control, whereas sleep duration and quality are frequently disrupted by the respiratory events and arousals that define OSA itself. We therefore examined the cross-sectional association between bedtime and prevalent hypertension among community-dwelling Chinese adults with OSA. We also examined whether the associations varied by age, given age-related differences in sleep architecture and circadian regulation.

Methods

Study population

This cross-sectional study utilized baseline data from the Guangdong Sleep Health Study (GSHS) and the National Health Survey (CNHS) in Guangdong Province, China [12, 13].

The CNHS (2012–2017) was a nationwide, stratified multistage cluster survey of adults aged 20–80 years designed to establish reference intervals for physiological constants and determinants of noncommunicable diseases [12]. The GSHS is a community-based cohort in Guangdong Province that used multistage stratified cluster sampling to recruit permanent residents from selected districts in Shantou and Meizhou cities; the detailed protocol has been published elsewhere [13].

Participants were permanent residents aged ≥ 20 years at the time of the baseline survey. The study protocol was approved by the Ethics Committee of Guangdong Provincial People’s Hospital (Approval No. GDREC2020221H, KY-Z-2022-391-03), and all participants provided written informed consent.

Data collection

Data were collected through face-to-face questionnaires, physical examinations, and sleep monitoring. Trained staff administered questionnaires to capture demographic characteristics, socioeconomic status, medical history, and lifestyle factors (e.g., smoking, alcohol consumption, physical activity, dietary habits). Data quality was ensured through one-on-one interviews, reviewer verification, and double-entry data input. Physical measurements, including height and weight, were conducted in a fasting state.

Obstructive sleep apnea diagnosis

Obstructive sleep apnea (OSA) was diagnosed using a Type IV wearable intelligent sleep monitor (WISM; Chengdu Yunwei Kang Medical Technology Co., Ltd., Chengdu, China), which records oxygen saturation, pulse rate, and somatic movement signals overnight. This same device model was previously validated against simultaneous in-laboratory polysomnography by our group in 196 participants, demonstrating sensitivity/specificity of 93%/77% for AHI ≥ 5/h and 92%/89% for AHI ≥ 15/h [14]. OSA was defined as ≥ 5 oxygen desaturation events per hour [15].

Hypertension diagnosis

Blood pressure was measured using an electronic sphygmomanometer (Omron HEM-907, Omron, Japan) after participants rested for ≥ 5 min, following a period of fasting and the avoidance of medications that could affect blood pressure. Three consecutive measurements were averaged. Hypertension was defined as mean systolic blood pressure ≥ 140 mmHg, mean diastolic blood pressure ≥ 90 mmHg, current use of antihypertensive medication, or self-reported physician-diagnosed hypertension.

Assessment of sleep behavioral habits

Sleep behavioral habits were assessed via self-reported responses in a sleep questionnaire, using the Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI). The PSQI evaluated sleep quality over the past month, covering bedtime, sleep latency, duration, efficiency, disturbances, sleep medication use, and daytime dysfunction (score range: 0–21). The ISI assessed insomnia severity over the past week (score range: 0–28). Higher scores indicate poorer sleep quality. Bedtime was obtained directly from item 1 of the Pittsburgh Sleep Quality Index (PSQI), in which participants reported their usual bedtime over the past month (open-ended response in hours and minutes, e.g., “10:30 PM”). Responses were recorded in 24-hour format, standardized to Beijing time (UTC + 8) to account for any regional differences within the study area, and subsequently categorized into three groups for analysis: early (≤ 21:59), moderate (22:00–23:59), and late (≥ 00:00). Sleep duration was derived from PSQI responses, and sleep efficiency was calculated as (total sleep duration/total time in bed) × 100%. Participants were classified as using or not using sleep medications based on PSQI responses.

Data analysis

Data were analyzed using R software (version 4.3.2; R Foundation for Statistical Computing). Missing data were imputed using multiple imputation by the random forest method (mice package, version 3.16.0). Continuous variables were reported as means ± standard deviations, and categorical variables as counts (percentages). Multivariable logistic regression was used to examine the association between bedtime categories and hypertension, adjusting for potential confounders (e.g., age, sex, BMI, lifestyle factors). All tests were two-sided with a significance level of α = 0.05. Effect sizes were reported as odds ratios (ORs) with 95% confidence intervals (CIs). Pre-specified subgroup analyses were conducted stratified by age groups (20–44, 45–59, and ≥ 60 years) to explore potential heterogeneity.

Results

Participants characteristics

Of the 12,159 residents in the baseline cohort, 6,193 were included after excluding those without sleep monitoring or with incomplete sleep and blood pressure data (Fig. 1). The prevalence of OSA was 42.95% (n = 2,660). Compared to non-OSA participants, those with OSA were older, had higher body mass index (BMI), and a greater prevalence of hypertension, diabetes, and dyslipidemia (all P < 0.05; Supplementary Table S1) (Table 1 & 2).

Fig. 1.

Flow diagram of participant screening

Table 1.

Baseline demographic and clinical characteristics of participants with obstructive sleep apnea, stratified by hypertension status

Variables		All OSA patients	Without hypertension	With hypertension	P-value
n		2660	1655	1005
Age, years		55.3 ± 12.7	51.9 ± 12.8	60.9 ± 10.2	< 0.001
Age, n (%)	20–44	533(20.0)	482(29.1)	51(5.1)	< 0.001
	45–59	1102(41.4)	700(42.3)	402(40.0)
	60+	1025(38.5)	473(28.6)	552(54.9)
BMI, kg/m2		24.69 ± 3.52	24.05 ± 3.41	25.75 ± 3.45	< 0.001
Sex, n (%)	Male	1103(41.5)	640(38.7)	463(46.1)	< 0.001
	Female	1557(58.5)	1015(61.3)	542(53.9)
Residence, n (%)	City	1992(74.9)	1254(75.8)	738(73.4)	0.193
	Country	668(25.1)	401(24.2)	267(26.6)
Hyertension, n (%)	No	1655(62.2)	1655(100.0)	0(0.0)	< 0.001
	Yes	1005(37.8)	0(0.0)	1005(100.0)
Diabetes, n (%)	No	2173(81.7)	1406(85.0)	767(76.3)	< 0.001
	Yes	217(8.2)	77(4.7)	140(13.9)
	Unknown	270(10.2)	172(10.4)	98(9.8)
Dyslipidemia, n (%)	No	1648(62.0)	1089(65.8)	559(55.6)	< 0.001
	Yes	352(13.2)	161(9.7)	191(19.0)
	Unknown	660(24.8)	405(24.5)	255(25.4)
Smoking status, n (%)	Never	2062(77.5)	1325(80.1)	737(73.3)	< 0.001
	Former	177(6.7)	79(4.8)	98(9.8)
	Current	421(15.8)	251(15.2)	170(16.9)
Alcohol status, n (%)	Never	2007(75.5)	1286(77.7)	721(71.7)	< 0.001
	Former	90(3.4)	41(2.5)	49(4.9)
	Current	563(21.2)	328(19.8)	235(23.4)
Exercise Status, n (%)	5–7 day per week	1278(48.0)	739(44.7)	539(53.6)	< 0.001
	3–4 day per week	276(10.4)	184(11.1)	92(9.2)
	1–2 day per week	311(11.7)	213(12.9)	98(9.8)
	< 4 day per month	224(8.4)	162(9.8)	62(6.2)
	Never	571(21.5)	357(21.6)	214(21.3)

Mean ± SD for continuous variables; % for categorical variables

Table 2.

Detailed sleep characteristics of OSA patients

Variables	Total	OSA		P-value
		Non-hypertension	Hypertension
n	2660	1655	1005
ODI,/h	12.9 ± 8.7	11.8 ± 7.7	14.7 ± 9.9	< 0.001
Bedtime (h: min)	22:55 ± 1:08	23:02 ± 1:06	22:43 ± 1:09	< 0.001
Waketime (h: min)	6:32 ± 1:07	6:37 ± 1:06	6:22 ± 1:08	< 0.001
PSQI Score	5.8 ± 3.2	5.7 ± 3.1	5.9 ± 3.4	0.025
ISI Score	6.3 ± 6.3	6.1 ± 6.3	6.6 ± 6.3	0.068
Sleep Duration, hours	6.50 ± 1.37	6.55 ± 1.32	6.41 ± 1.44	0.015
Sleep Latency, min	31.71 ± 33.28	30.26 ± 31.01	34.08 ± 36.60	0.004
Sleep efficiency (%)	84.43 ± 14.58	85.29 ± 13.73	83.01 ± 15.79	< 0.001
sleeping pills used, n(%)	109(4.1)	62(3.7)	47(4.7)	0.283

Mean ± SD for continuous variables; % for categorical variables

PSQI Pittsburgh Sleep Quality Index; ODI oxygen desaturation index; ISI Insomnia Severity Index

Sleep behavioral habits

The mean bedtime was 22:56 ± 1:08 and the mean wake-up time was 6:33 ± 1:08. The prevalence of OSA was 42.95%. In patients with OSA, the mean bedtime was 22:55 ± 1:08 and the mean wake-up time was 6:32 ± 1:07. The proportions of patients with OSA in the early-bedtime, normal-bedtime, and late-bedtime groups were 8.3%, 65.3%, and 26.4% (patients with OSA alone), and 17.8%, 62.9%, and 19.3% (patients with OSA combined with hypertension), respectively. Among OSA patients, the early bedtime group had the longest sleep duration but the lowest sleep quality and efficiency, while the late bedtime group had the shortest sleep latency and highest sleep quality despite shorter sleep duration (Table 3).

Table 3.

Sleep characteristics of OSA patients in different bedtime

Variables	Total	Bedtime			P-value
		Before 22:00	22:00–23:59	At or after 0:00
n	2660	316	1713	631
ODI,/h	12.9 ± 8.7	13.3 ± 9.3	12.9 ± 8.7	12.6 ± 8.6	0.439
Waketime (h: min)	6:32 ± 1:08	5:39 ± 1:04	6:23 ± 0:53	7:21 ± 1:13	< 0.001
PSQI Score	5.8 ± 3.2	6.0 ± 3.2	5.8 ± 3.2	5.5 ± 3.1	0.049
ISI Score	6.3 ± 6.3	7.1 ± 6.1	6.5 ± 6.4	5.2 ± 6.0	< 0.001
Sleep Duration, hours	6.50 ± 1.37	6.94 ± 1.79	6.51 ± 1.30	6.24 ± 1.23	< 0.001
Sleep Latency, min	31.71 ± 33.28	38.02 ± 43.90	32.12 ± 31.87	27.42 ± 30.20	< 0.001
Sleep efficiency (%)	84.43 ± 14.58	80.01 ± 17.63	83.98 ± 14.51	87.85 ± 12.15	< 0.001
Sleeping pills used, n(%)	109(4.1)	13(4.1)	83(4.8)	13(2.1)	0.011

Mean ± SD for continuous variables; % for categorical variables

PSQI Pittsburgh Sleep Quality Index; ODI oxygen desaturation index; ISI Insomnia Severity Index

Association between sleep behavioral habits and hypertension in OSA patients

Compared to OSA patients without hypertension, those with comorbid hypertension had earlier bedtimes and wake-up times (Table 2). Hypertension prevalence was highest in the early bedtime group (56.6%), followed by the normal (36.9%) and late bedtime groups (30.7%). In the primary fully adjusted model (Model 3), compared with the early bedtime group (≤ 21:59), the moderate (22:00–23:59) and late (≥ 00:00) bedtime groups had lower odds of hypertension (odds ratio [OR] = 0.64, 95% CI 0.48–0.86; and OR = 0.67, 95% CI 0.47–0.95, respectively; Table 4). Similar associations were observed in Models 1 and 2 (Table 4). Age-stratified analyses were conducted to explore potential effect modification by age (Fig. 2). In participants aged 60 years and older, moderate (22:00–23:59) and late (≥ 00:00) bedtimes were associated with lower odds of hypertension compared with early bedtime (≤ 21:59) in the fully adjusted model (OR = 0.60, 95% CI 0.46–0.78; OR = 0.65, 95% CI 0.44–0.97, respectively). The P value for interaction across age subgroups was 0.228, indicating no statistically significant effect modification by age. To assess dose–response, bedtime was entered as a continuous variable (hours after midnight). In participants with OSA, each 1-hour later bedtime was associated with lower systolic blood pressure (− 0.89 mmHg, 95% CI − 1.56 to − 0.21, P = 0.010) and diastolic blood pressure (− 0.46 mmHg, 95% CI − 0.89 to − 0.03, P = 0.038) in the fully adjusted model (Supplementary Table S2) (Fig. 3).

Table 4.

Multivariable-adjusted odds ratios and 95% confidence intervals of hypertension in OSA, according to bedtime

Bedtime	Before 22:00	22:00–23:59	At or after 0:00
n	316(2660)	1713(2660)	631(2660)
Model 1	1.00 (ref)	0.68, (0.52,0.89)	0.71, (0.52,0.98)
Model 2	1.00 (ref)	0.66, (0.50,0.86)	0.69, (0.50,0.95)
Model 3	1.00 (ref)	0.64, (0.48,0.86)	0.67, (0.47,0.95)

Model 1: Adjusted for age, sex, BMI, Ethnicity

Model 2: Further adjusted for lifestyle factors (Smoking status, Alcohol status, Exercise Status), Diabetes, Dyslipidemia

Model 3: Further adjusted for DOI, PSQI Score, ISI Score, Sleep duration, Sleep Latency, Sleep efficiency

PSQI Pittsburgh Sleep Quality Index; ODI oxygen desaturation index; ISI Insomnia Severity Index

Fig. 2.

The following bar graph illustrates the distribution of subjects’ bedtimes

Fig. 3.

Age-stratified analysis of the prevalence of hypertension among patients with OSA

Specificity of the bedtime–hypertension association in participants without OSA

Among the 3,533 participants without OSA, 392 (11.1%), 2,292 (64.9%), and 849 (24.0%) were classified as early (≤ 21:59), moderate (22:00–23:59), and late (≥ 00:00) sleepers, respectively. In contrast to findings in OSA patients, early bedtime was not independently associated with higher hypertension prevalence in individuals without OSA. In the fully adjusted model (Model 3), using early bedtime as the reference, the odds ratios for hypertension were 0.83 (95% CI 0.63–1.09) for moderate bedtime and 0.71 (95% CI 0.50–1.02) for late bedtime (both P > 0.05). These findings suggest that the observed association between early bedtime and hypertension may be specific to individuals with obstructive sleep apnea (Supplementary Table S3).

Associations stratified by OSA severity among participants with OSA

Among the 2,660 participants with OSA (ODI ≥ 5 events/h), we further stratified the analysis into mild (ODI 5–<15), moderate (ODI 15–<30), and severe (ODI ≥ 30 events/h) categories. In the fully adjusted Model 3, later bedtimes (moderate 22:00–23:59 and late ≥ 00:00 vs. early ≤ 21:59) were associated with lower odds of prevalent hypertension in mild OSA, but the association progressively attenuated and became non-significant in moderate and severe OSA (Supplementary Table S4). In severe OSA, point estimates were close to or slightly above 1.0, with very wide confidence intervals reflecting the smaller subgroup size.

Discussion

This study demonstrates that bedtime is associated with hypertension prevalence in community-based patients with OSA. After adjusting for confounders, including age, sex, BMI, lifestyle factors, and sleep parameters, early bedtime (≤ 21:59) was associated with a higher hypertension prevalence compared to normal (22:00–23:59) and late (≥ 00:00) bedtime groups. A clear dose-response relationship was observed: each 1-hour delay in bedtime was associated with lower systolic and diastolic blood pressure levels in OSA patients (Supplementary Table S1).

Early bedtime was also linked to longer sleep latency, lower sleep efficiency, poorer sleep quality, and higher use of sleep medications. These findings suggest that early bedtime in OSA patients may reflect attempted compensation for underlying sleep difficulties rather than an optimal sleep-wake alignment. In contrast, later bedtimes were associated with better sleep continuity and subjective sleep quality, despite shorter sleep duration, and with lower hypertension prevalence.

These observations align with prior evidence in general populations indicating lowest cardiovascular risk with sleep onset between 22:00 and 22:59 [3]. Consistent with this, the moderate bedtime group in our OSA cohort exhibited the lowest hypertension prevalence. Our supplementary analysis in participants without OSA (ODI < 5) revealed no significant bedtime-hypertension association after full adjustment (Supplementary Table S3), suggesting that the observed relationship may be specific to, or amplified by, the presence of OSA-related sleep disruption.

Bedtime represents one of the few sleep-wake parameters that remains largely under volitional control in OSA, unlike sleep duration or efficiency, which are often directly constrained by respiratory events and arousals. By adjusting for these factors in our models, we isolated bedtime as a distinct behavioral target. Concurrently, advancing age induces alterations in circadian rhythms, which manifest as shifts in sleep architecture, poorer sleep quality, and a morning chronotype [16]. Blood pressure naturally follows a daily cycle, rising during waking hours and falling during sleep at night [17]. Such circadian disruptions may further contribute to blood pressure variability in this population. At the same time Early bedtime practices could represent a compensatory mechanism in response to insomnia concerns [18]. For OSA patients with nocturnal intermittent hypoxia, extending bedtime duration alone is unlikely to improve sleep quality and may exacerbate cardiovascular strain through mechanisms such as sleep fragmentation, which could contribute to the increased hypertension prevalence observed in the early bedtime group [19].

Reduced sleep efficiency, more pronounced in the early bedtime and comorbid hypertension groups, has previously been linked to higher hypertension prevalence in OSA populations [20]. This may relate to heightened sympathetic activity, inflammation, and endothelial dysfunction—pathways implicated in OSA-related cardiovascular complications [9].The observed association between habitual bedtime and hypertension prevalence in OSA patients exhibited a nonlinear, V-shaped pattern, with the lowest prevalence in the moderate bedtime group (22:00–23:59) and higher prevalence in both early and late groups. Although several sleep parameters, such as longer sleep latency and lower sleep efficiency, worsened progressively with earlier bedtimes and partially explained the elevated hypertension prevalence in the early group, these linear trends do not fully account for the uptick in the late bedtime group, where sleep latency was shortest and sleep efficiency highest. This asymmetry suggests distinct mechanisms underlying the two extremes. Early bedtimes in OSA patients may reflect compensatory behavior in response to severe sleep fragmentation and daytime fatigue, potentially leading to prolonged time in bed, misalignment with endogenous circadian phase, or unmeasured factors that independently elevate cardiovascular risk [21]. In contrast, late bedtimes may contribute through circadian misalignment (e.g., delayed melatonin onset relative to clock time), shorter sleep duration, or greater evening sympathetic activation [22, 23].

Although sleep efficiency decreased in patients with OSA co-morbid hypertension, the OSA group and the OSA co-morbid hypertension group did not show statistical differences in ISI scores and rates of sleeping medication use, and the patients’ subjective insomnia perception did not increase in tandem with the need for pharmacological interventions. It is suggested that cognitive impairment due to chronic intermittent hypoxia may have weakened patients’ ability to perceive their own sleep disorders [24]. As well as hypertension-related symptoms (e.g., headache, vertigo) may mask early insomnia symptoms [25]. These results indicate that insomnia symptoms in hypertensive patients with OSA comorbidities may be under-recognized. Therefore, systematic sleep symptom assessment and behavioral analysis should be included as normal in clinical practice to avoid underdiagnosis of potential insomnia problems.

Conclusion

This community-based cross-sectional study demonstrates an association between habitual bedtime and the prevalence of comorbid hypertension in patients with OSA. Early bedtime (≤ 21:59) was associated with higher hypertension prevalence compared with moderate (22:00–23:59) and late (≥ 00:00) bedtimes, with a dose-response relationship indicating progressively lower blood pressure levels with later bedtimes. Notably, this pattern appeared specific to or amplified in OSA, as no significant bedtime-hypertension association was observed in participants without OSA.

These observational findings align with limited prior evidence from general populations suggesting optimal cardiovascular outcomes with moderate sleep onset timing but indicate potential differences in OSA patients, where early bedtimes coincided with poorer sleep continuity. Given the cross-sectional design and scarcity of similar studies in OSA cohorts, longitudinal research is required to confirm these associations and explore their clinical relevance.

Limitations

Several limitations warrant consideration. As a cross-sectional study, the present research cannot infer causal relationships between bedtime and hypertension risk. Additionally, constraints in the available study sample precluded the inclusion of mental health variables, such as anxiety and depression, in the analyses. Type IV monitors remain less accurate than PSG, particularly in individuals with low AHI or substantial comorbid cardiopulmonary disease. Some degree of OSA misclassification therefore cannot be excluded. Bedtime and related sleep parameters were obtained by self-report, which is susceptible to recall bias and may not precisely capture actual sleep timing. Although current antihypertensive medication use was incorporated into the hypertension definition, reliance on self-reported physician diagnosis and medication use may introduce minor recall bias or misclassification. Finally, the study was conducted in a community-based sample from Guangdong Province, China, which may limit generalizability to other populations.

Supplementary Information

Below is the link to the electronic supplementary material.

Funding

This study was funded by the National Natural Science Foundation of China (Grant No. 82470083), the Ministry of Science and Technology of the People’s Republic of China (Grant No. 2022FY100803), and the Science and Technology Program of Guangdong Province (Grant No. 2023B110009), all awarded to Qiong Ou. The funders had no role in the study design, data collection, analysis, interpretation, or writing of the manuscript.

Data Availability

Data analyzed in the current study are available from the corresponding author upon reasonable request.

Declarations

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee (name of institute/committee) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Conflict of interest

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

Informed consent

Informed consent was obtained from all individual participants included in the study.