Association Between Sleep Duration and Hypertension Development in Women: A Meta-Analysis

By Yan Bai^1,2, Deying Kong³, Jie Hou⁴, Li Bai³

Affiliations

1. School of Public Health, Jiamusi University, Jiamusi, China
2. Sexually Transmitted Diseases and AIDS Prevention and Control Institute, Harbin Centre for Disease Control and Prevention, Harbin, China
3. School of Public Health, Qiqihar Medical University, Qiqihar, China
4. Immunization Planning Institute, Harbin Centre for Disease Control and Prevention, Harbin, China

doi: 10.29271/jcpsp.2026.08.1045

ABSTRACT
This study examined the association between females' sleep duration and the development of hypertension (HTN). Searches were conducted in Embase, PubMed, Cochrane Library, Web of Science, CNKI, VIP, and Wanfang databases up to March 15, 2024. Using RR as the effect measure, the combined RR and 95% CI were calculated using Stata 15.0. A total of 10 articles, comprising 12 cohort studies, were included in the meta-analysis. Inadequate sleep duration is associated with HTN in women (RR: 1.10, 95% CI: 1.06-1.13, p <0.001). However, long sleep duration was not associated with HTN in women (RR: 1.00, 95% CI: 0.96-1.05, p = 0.958). Short- and long-sleep duration groups showed no publication bias. Subgroup and meta-regression analyses indicated that age and variation in the operational definition of sleep duration were the principal sources of heterogeneity. In age-stratified analysis, both <50 years (RR = 1.19, 95% CI: 1.11-1.28, p <0.001) and ≥50 years (RR = 1.06, 95% CI: 1.00-1.12, p = 0.036) showed increased HTN risk among women with short sleep duration. The dose–response association was L-shaped; using 4 hours/day as the reference, the lowest risk was observed at approximately 7.5 hours/day. For women, insufficient sleep duration is linked to a higher risk of developing HTN.

Key Words: Hypertension, Women, Sleep duration, Prospective cohort study, Meta-analysis.

INTRODUCTION

Hypertension (HTN), a modifiable risk factor, has been established as a significant contributor to cardiovascular disease (CVD), as well as other health complications, including cognitive decline, dementia, and renal disease.^1-3 In this regard, HTN could substantially impact disease onset and progression, even causing premature mortality. Furthermore, the 2023 Global Hypertension Report revealed that HTN affects 33% of individuals aged 30-79 worldwide, with males (34%) having a slightly higher incidence than females (32%).⁴

In addition to other factors, such as diet, physical activity, and genetics, the association between HTN and sleep dura- tion has recently attracted considerable attention. Although numerous studies have identified an association between HTN and sleep duration, their findings have been inconsistent.
 

Specifically, some studies suggested a correlation between increased HTN risk and extended sleep duration,^{5, 6} whereas others reported a higher prevalence of HTN among individuals with shortened sleep durations.^7-9 According to a previous dose-response meta-analysis, HTN risk decreases by 0.3207% for every additional hour of sleep per day.¹⁰ Furthermore, a previous cross-sectional study involving >700,000 partici- pants linked HTN with both insufficient and excessive sleep durations, with cohort studies later corroborating these fin- dings.^{11, 12} Additionally, a study involving women revealed a U-shaped correlation between sleep duration and HTN onset, a pattern  not  observed  in  men.¹³

Numerous studies have also suggested that gender diffe- rences may affect the generalisability of research findings. In this regard, the National Institutes of Health (NIH) in the United States recommended gender integration as a biological variable in planning, analysing, and publishing research outcomes on vertebrate animals and humans.¹⁴ Moreover, gender dis- parities in physiological makeup could cause substantial variations in regulating blood pressure (BP) stability at the tissue, cellular, and molecular levels, resulting in susceptibility, pre- valence, and response differences to HTN treatment among males and females.¹⁵ It is also noteworthy that although women exhibit a lower HTN risk and severity than men before menopause, the risk sharply rises after menopause.¹⁶

Owing to the scarcity of comprehensive data, this study explored the association between sleep duration and HTN in women. It aimed to inform the management of BP and the development of preventive measures for this population.
 

METHODOLOGY

Pertinent articles were searched in seven electronic databases (Embase, PubMed, Cochrane Library, Web of Science, CNKI, VIP, and Wanfang Database) from inception to March 15, 2024. The Cochrane Library was used as an example in devising the search strategy. All combinations of HTN, high BP, sleep duration, and sleep quantity were used. The inclusion criteria were full-text articles that were readily available; prospective cohort studies; studies providing all necessary female-specific data; studies report- ing data on sleep duration categories and their association with HTN risk, with results expressed as odds ratios (ORs), hazard ratios (HRs), relative risks (RRs), and 95% confidence intervals (CIs); and, when multiple studies included overlapping data from the same population, the study with the largest sample size or the most recent publication. The exclusion criteria were studies with duplicate or overlapping data; irrelevant study topics; participants aged <18 years or pregnant women; studies from which essential female-specific data, sleep duration categories, or study outcomes could not be extracted; and reviews, conference reports, clinical trials, animal studies, graduate theses, case-control studies, and cross-sectional studies.

The primary data extraction details included articles' primary author, publication year, study country, follow-up duration, female sample size, age range, sleep duration measurement approach, HTN definition, sleep time reference, definitions for short and long sleep durations, adjustment for confounding variables, and effect indicators post-adjustment (including respective RR, OR, HR, and 95% CI values). The quality of the included cohort studies was assessed using the Newcastle–Ottawa Scale (NOS),¹⁷ a tool designed to evaluate the quality of non-randomised studies. The NOS has a maximum score of 9, with higher scores indicating superior methodological quality, and evaluates three domains: selection of study groups, comparability between groups, and outcome assessment. In line with these domains, the quality appraisal considered the characteristics of the study population, the method used to assess sleep duration, the approach to diagnosing HTN, the length of follow-up, and the control of potential confounders in the statistical analyses. Studies scoring ≥7 were classi- fied as high quality. Two reviewers independently perfor-med study screening, full-text review, and data extraction, cross-checked data quality, and conducted the quality assessment according to prespecified criteria. Any discre- pancies in scoring were resolved through discussion, and a third senior reviewer adjudicated unresolved disagreements.

The RR effect indicator was determined by combining RR and 95% CI computation to evaluate the correlation between short or long sleep durations and HTN in women. Heterogeneity among the studies was assessed using the Q test and I². If I² >50% and p ≤0.1, indicating significant heterogeneity, a random-effects model was used for the analysis. Otherwise, a fixed-effects model was used. Subgroup analyses and meta-regression were performed by categorising the definitions of age, location, follow-up, and short or long sleep into different subgroups to explore the sources of heterogeneity. Univariable meta-regression analyses were first undertaken to assess the association of each covariate. Variables with p <0.10 were then entered into a multivariable model to identify independent predictors, adjusting for other covariates. Between-study variance was estimated using restricted maximum likelihood (REML), and the Knapp-Hartung adjustment was applied to account for uncertainty in the estimate of tau². Publication bias was evaluated using Funnel plots and Egger's test, with significance set at p <0.05. During the literature review, sensitivity analyses were conducted using the one-by-one exclusion approach. A dose–response meta-analysis was conducted to model potential non-linearity using generalised least squares trend estimation (GLST) with a three-knot restricted cubic spline (knots at the 10%, 50%, and 90%). Non-linearity was assessed using a Wald test, with a p-value of <0.05 taken as evidence of a non-linear dose–response association. In the dose-response meta-analysis, a common reference of 4 hours/day (the lowest dose) was adopted to standardise for varying reference categories across the included studies. All study-specific estimates were re-referenced to this level using a macro developed in Microsoft Excel 2019.^18,19 Data processing and analysis were performed using Stata version 15.0.

RESULTS

Figure 1 shows that, Hereinafter, 12,701 articles were initially retrieved from various electronic databases. Duplicate records were removed, after which the remaining 10,513 articles were subjected to a screening process involving scrutinising the titles and abstracts. Based on the aforementioned inclusion and exclusion criteria, 76 were selected for thorough full-text examination, and ten articles were ultimately included in the final analysis,^13,20-28 encompassing findings from 12 prospective cohort studies.

Table I shows the basic characteristics of the 12 cohort studies considered in this meta-analysis. These studies were published between 2007 and 2023, with four, two, one and five conducted in China, the UK, South Korea, and the US, respectively. Participants' ages in these 12 studies ranged between 18 and 98 years, and most studies had a follow-up duration of ≥2 years. The cumulative female sample size was 283,172, with 66,126 HTN instances recorded. In most studies, the reference sleep duration was 7-8 hours, and each study had its own criteria for classifying long or short sleep durations.

Table I: Basic characteristics of included literature.

First author	Year	Country	Follow-up (years)	N	Age	Method of obtaining sleep duration	Definition of HTN	Sleep duration reference	Short, long sleep time definitions	Adjusted variables	NOS
Lunyera et al.20	2021	America	9-15	33,497	35-74	Interviews	Doctor-diagnosed	7-9 hours/night	<7 hours/night, >9 hours/night	A factors*, income level, BMI, race/ethnicity, alcohol use, employment status, marital status, binge drinking, diabetes, educational attainment, healthy eating index score, waist-to-hip ratio, and antidepressant use	9
Song et al.21	2016	China	3.98	8,545	46.32 ± 11.50 (mean)	Interviews	BP >140/90mmHg	7 hours/night	≤5 hours/night, ≥9 hours/night	A factors*, diabetes drug, BMI, alcohol use, diabetes, resting heart rate, family history of HTN, baseline BP, sodium consumption, cholesterol-lowering medication, and hyperlipidaemia	8
Wu et al.23	2016	China	2	653	40-70	Questionnaire	Current antihypertensive treatment or BP ≥140/90mmHg	7-7.9 hours/day	≤4.9 hours/day, ≥8 hours/day	A factors*, baseline BP, diabetes mellitus, BMI, personality, UA, TC, TG, LDL-C, HDL-C, hs-CRP, and drinking,	7
Cappuccio et al.24	2007	Britain	5	1,005	54.7-56.8 (mean)	Questionnaire	Current antihypertensive treatment, or BP≥140/90mmHg	7 hours/night	≤5 hours/night, ≥9 hours/night	A factors*, hypnotics use, SF36 Mental, employment, BMI, CVD drugs, depression cases, SF36 Physical, and alcohol consumption	7
Jackowska et al.27	2015	Britain	4	2,214	50≥	Self-report	BP>140/90mmHg	7-8 hours/day	≤5 hours/day, >8 hours/day	A factors*, wealth, BMI, limiting long-standing illness, and depressive symptoms	8
Gangwisch et al.25	2013	America	6	60,009	40-65	Questionnaire	Doctor-diagnosed	7 hours/night	≤5 hours/night, ≥9 hours/night	A factors*, alcohol use, BMI, race, Hispanic ethnicity, caffeine, diabetes, aspirin, menopause, shift work, snoring, diet for controlling HTN, family history of HTN, acetaminophen, nonaspirin non-steroidal anti-inflammatory drugs, and hypercholesterolemia	7
Gangwisch et al.25	2013	America	6	32,105	54-79	Questionnaire	Doctor-diagnosed	7 hours/night	≤5 hours/night, ≥9 hours/night	A factors*, alcohol use, BMI, race, Hispanic ethnicity, caffeine, diabetes, aspirin, menopause, shift work, snoring, diet for controlling HTN, family history of HTN, acetaminophen, nonaspirin non-steroidal anti-inflammatory drugs, and hypercholesterolemia	7
Gangwisch et al.25	2013	America	6	68,784	37-54	Questionnaire	Doctor-diagnosed	7 hours/night	≤5 hours/night, ≥9 hours/night	A factors*, alcohol use, BMI, race, Hispanic ethnicity, caffeine, diabetes, aspirin, menopause, shift work, snoring, diet for controlling HTN, family history of HTN, acetaminophen, nonaspirin non-steroidal anti-inflammatory drugs, and hypercholesterolemia	7
Li et al.13	2015	China	4.4	2,278	30-65	Questionnaire	SBP ≥130 mmHg, and/or DBP ≥ 85mmHg	7 - <8 hours/night	<6 hours/night, ≥9 hours/night	A factors*, education, stroke, alcohol use, bad mood, snoring, psychological pressure, WC, FBG, sleep in daytime, mental illness, sleep quality, hypnotics, CVD, insomnia, and menopausal status	7
Kim et al.28	2012	Korean	6	2,635	40-69	Questionnaire	Current antihypertensive treatment or BP ≥140/90mmHg	5-7 hours/night	<5 hours/night, >7 hours/night	A factors*, job, BMI, education, alcohol use, Epworth sleepiness scale, area, income, snoring, and diabetes	7
Wang et al.22	2017	China	5	5,325	60.9 (mean)	Questionnaire	Doctor-diagnosed, or current antihypertensive treatment, or BP ≥140/90mmHg	7-8 hours/night	<7 hours/night, ≥9 hours/night	A factors*, marital, tea, status, education, BMI, alcohol use, chronic diseases, family history of HTN, shift work, coffee, life pressure, WC, sleep quality, midday napping, sleep apnoea, hypnotics and CVD drugs, sleep duration, and snoring	8
Haghayegh et al.26	2023	America	16	66,122	37-54	Questionnaire	Doctor-diagnosed, or current antihypertensive treatment	7-8 hours/day	≤6 hours/day, ≥9 hours/day	A factors *, race, BMI, diet quality, alcohol consumption, maternal and paternal history of HTN, sleep apnoea, menopausal status, night-shift work, difficulty falling or staying asleep, and chronotype	7
A factors * includes age, smoking, and physical activity; UA: Uric acid; TG: Triglycerides; TC: Total cholesterol; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; hs-CRP: High-sensitivity C-reactive protein; WC: Waist circumference; FBG: Fasting blood glucose.

Table II: Heterogeneity test for different sleep duration subgroups.
 

Subgroup	Short sleep duration			Subgroup	Long sleep duration
	n	I2	p-values		n	I2	p-values
Age group	-	-	-	-	-	-	-
<50	3	0.00%	0.882	<50	4	67.4%	0.027
≥50	9	35.6%	0.134	≥50	8	0.0%	0.624
Location	-	-	-	-	-	-	-
Asia	5	62.7%	0.030	Asia	5	63.1%	0.028
Europe	2	0.0%	1	Europe	2	0.0%	0.989
North America	5	37.0%	0.174	North America	5	45.1%	0.121
Follow-up	--	-	-	-	-	-	-
<5	4	0.0%	0.997	<5	4	64.2%	0.039
≥5	8	49.6%	0.053	≥5	8	0.0%	0.477
Definition of short or long sleep	-	-	-	-	-	-	-
≤5	8	2.30%	0.412	>7	1	-	-
≤6	2	20.8%	0.261	≥8	2	0.0%	0.457
<7	2	74.6%	0.047	≥9	9	54.7%	0.024
Only one article in the subgroup analysis had a long sleep duration defined as ≤5 hours; hence, the heterogeneity test data could not be obtained.

The HTN diagnostic criteria included BP readings ≥140/90 mmHg, a physician's diagnosis, or current use of antihyper- tensive medication. The cumulative NOS score of all studies amounted to ≥7 points, indicating a notable quality standard of the included studies. 
 

This meta-analysis explored the association between sleep duration and the risk of HTN in women across 12 cohort studies. Most studies defined short sleep duration as ≤5 hours, while others defined it as ≤6 hours or <7 hours. Notably, the studies showed minimal heterogeneity (I² = 37.1%, p = 0.094, Figure 2A); hence, a fixed-effects model was employed for data analysis. The pooled RR was 1.10 (95% CI: 1.06–1.13; p <0.001), indicating a significant association between short sleep duration and the risk of HTN in women. All 12 cohort studies clearly defined long sleep duration, mostly as ≥9 hours. No significant heterogeneity was detected (I² = 39.8%, p = 0.076, Figure 2B), prompting the utilisation of a fixed-effects data aggregation model. Furthermore, the com- bined RR for long sleep duration was 1.00 (95% CI: 0.96-1.05, p = 0.958), indicating no substantial correlation between long sleep duration and HTN risk in women.

Figure 1: Literature screening process flowchart.

Figure 2: Forest plot of the relationship between sleep duration and HTN risk in women.

Figure 3: Funnel plot of publication bias in the short and long sleep duration groups.

Figure 4: Sensitivity analysis in short and long sleep duration groups.

Figure 5: Forest plot of subgroup analysis for short and long sleep duration.

Figure 6: Dose-response relationship between sleep duration and HTN risk in women.

The funnel plot for the short sleep duration group (Figure 3A) showed slight asymmetry, with Egger's test results of p = 0.808 >0.05, indicating no significant publication bias. On the other hand, the funnel plot for the extended sleep duration group (Figure 3B) was symmetrical, which was corroborated by Egger's test (p = 0.403, >0.05), indicating no significant publication bias.

Sensitivity analyses via iteratively excluding individual studies revealed a range of combined RR values for both the short and long-sleep duration groups. Specifically, RR fluctuated between 1.08 (95% CI: 1.04-1.12) and 1.11 (95% CI: 1.07-1.15, Figure 4A) and between 1.00 (95% CI: 0.94-1.04) and 1.03 (95% CI: 0.98-1.09, Figure 4B) for the short and long sleep duration groups, respectively. Notably, the consistency of the results before and after excluding individual studies underscored the stability of the findings for both the short and long-sleep duration groups.

An additional stratified analysis of short and long sleep periods was conducted based on age, research institute location, follow-up duration, and definitions of short and long sleep durations (Figure 5A, B). In the analysis of short sleep periods, no substantial heterogeneity was observed in the <50 years (I² = 0.00%, p = 0.882) and ≥50 years (I² = 35.6%, p = 0.134) age groups (Table II). Furthermore, there was no significant change in the overall heterogeneity for short sleep duration (I² = 37.1%, p = 0.094), implying that age did not significantly affect short sleep duration heterogeneity. Aside from the subgroup analyses for Asia and Europe involving short sleep durations of <7 hours, all other subgroup analyses were significantly linked to HTN onset in women. Specifically, both age groups, <50 years (RR = 1.19, 95% CI: 1.11-1.28, p <0.001) and ≥50 years (RR = 1.06, 95% CI: 1.00-1.12, p = 0.036), showed an elevated HTN risk in women with short sleep periods. Furthermore, HTN risk was heightened among women in the ≤5 hours (RR = 1.12, 95% CI: 1.07-1.18, p <0.001) and ≤6 hours (RR = 1.11, 95% CI: 1.05-1.16, p <0.001) short sleep duration groups. Conversely, all subgroup analyses of long sleep durations showed no significant link between long sleep periods and HTN risk in women across different factors such as age, location, follow-up durations, and definitions of long sleep periods (p >0.05).

To investigate sources of heterogeneity, meta-regression analyses were performed. In univariable models, the mean age of females was inversely associated with the risk ratio (β = −0.008, 95% CI: −0.013-−0.003, p = 0.005, adj R² = 78.36%), indicating a stronger association in younger women and accounting for 78.36% of the heterogeneity. The definition of short sleep (hours) showed a borderline association (β = −0.021, 95% CI: −0.046-0.004, p = 0.095, adj R² = 42.68%). Neither follow-up duration (β = 0.003, 95% CI: −0.009-0.016, p = 0.607) nor region (β = 0.014, 95% CI: −0.088-0.116, p = 0.779) was significant. In the multivariable model, age (β = −0.008, 95% CI: −0.0127-−0.0025, p = 0.006) and the short sleep definition (β = −0.019, 95% CI: −0.038-−0.001, p = 0.043) together fully explained the heterogeneity (adj R² = 100%), while follow-up duration and region remained non-significant.

Meta-regression corroborated the difference between age subgroups (<50 years: RR = 1.19; ≥50 years: RR = 1.06). It also supported a graded dose effect across short-sleep thresholds, with higher risk estimates for stricter definitions (≤5 hours: RR = 1.12; ≤6 hours: RR = 1.11) and a lower estimate for <7 hours (RR = 0.96). The regression further suggested that some subgroup differences were likely due to random variation (e.g., follow-up <5 years; ≥5 years) or confounding (e.g., regional differences correlated with the extent of covariate adjustment).

To quantify changes in HTN risk, a dose-response meta- analysis was performed with the shortest sleep duration (4 hours/day) serving as the reference (RR = 1.00). This analysis revealed a significant non-linear association (χ² = 11.35, p = 0.001), characterised by an L-shaped curve (Figure 6). The lowest risk was observed at approximately 7.5 hours/day (RR = 0.88; 95% CI: 0.84–0.93), representing a 12% relative reduction compared with the 4 hours/day refe- rence. At 9.5 hours, the risk was elevated relative to the nadir (RR = 0.91, 95% CI: 0.85-0.98).

DISCUSSION

According to research, HTN, a widespread public health concern influenced by sleep patterns, is a significant contributor to CVD-related morbidity and mortality.²⁹ To the best of the authors’ knowledge, this meta-analysis is the first to examine the correlation between sleep duration and HTN in women. Herein, only prospective cohort investigations were included for a more comprehensive insight into the sleep duration-HTN association in women. Both short and long sleep durations were scrutinised, revealing that women with short sleep periods were at a heightened HTN risk. Conversely, the long sleep duration group showed no significant HTN risk. Furthermore, the included studies showed no evidence of publication bias, supporting the credibility of the study findings. Moreover, the sensitivity analysis confirmed the robustness of this study's results. The dose-response meta-analysis revealed a characteristic L-shaped association between sleep duration and HTN risk in women. This pattern is consistent with prior evidence.³⁰ Using 4 hours as the reference category, risk declined rapidly with increasing sleep duration, reaching a minimum at approximately 7.5 hours. Although durations exceeding 8 hours showed a tendency towards higher risk, this did not reach statistical significance. This pattern further confirms that women with shorter sleep have a significantly increased risk of HTN, whereas longer sleepers do not exhibit a clear excess risk. These findings highlight the public health importance of extending sleep duration among short sleepers to prevent HTN and underscore that obtaining adequate, but not excessive, sleep is critical for cardiovascular health.

According to the 2023 World Health Statistics report, sleep disturbances are a critical HTN risk factor, particularly among middle-aged and elderly individuals.³¹ A major cohort study involving >320,000 adult subjects revealed that maintaining a daily sleep duration of 7 hours reduced all-cause mortality rates, including CVDs, to their lowest levels.³² A previous meta-analysis reported the disappearance of the U-shaped sleep duration-HTN relationship in longitudinal studies and that short and long sleep durations may variably affect BP, with HTN risk significantly correlating with insufficient sleep.³³ These findings align with the results of the current study, which confirmed an elevated HTN risk in females with short sleep durations. No clear excess risk of HTN was observed among women with longer sleep duration, which aligns with previous studies.^10,34,35

Numerous experimental studies have consistently shown that inadequate sleep negatively impacts healthy individuals' cardiovascular systems.^30,36,37 When interpreting these findings, it is important to note that while the present meta- analysis found no significant association between long sleep and HTN in women, considerable evidence links prolonged sleep to increased HTN risk.²⁹ However, the precise mechanism underlying the relationship between long sleep durations and HTN remains unclear. In this regard, whether sleep duration poses a health risk or is a marker for other underlying risk factors requires further elucidation, highlighting the dearth of conclusive empirical evidence.³⁰ Multiple potential explanations have emerged for the correlation between prolonged sleep duration and HTN. Firstly, it has been hypothesised that obstructive sleep apnoea (OSA) may prompt a compensatory extension of sleep duration to counteract deficits caused by sleep fragmentation.^12,34,38 Notably, excessive time in bed is itself associated with greater sleep fragmentation, increased wake after sleep onset (WASO), and prolonged sleep latency-factors linked to a range of adverse health outcomes.³⁹ Secondly, longer sleep duration may be a marker for multiple HTN risk factors, including depressive symptoms, use of antidepressant or benzodiazepine medications, physical inactivity, and social disadvantages such as lower socioeconomic status.⁴⁰ Furthermore, inflammation may contribute to prolonged sleep, as elevated cytokine levels in inflammatory states exert somnogenic effects.^12,40 Nonetheless, additional research is required to further elucidate these potential mechanisms,¹² particularly given that discrepancies in research findings may arise from variations in sample characteristics, definitions of short and long sleep durations, and methods for controlling variables.²²

In addition to sleep duration, sleep disturbances have also been associated with an increased risk of CVD, particularly HTN, diabetes, and dyslipidaemia.⁴¹ Sleep disruptions alter BP responses and amplify HTN risk.⁴² Although the mechanisms linking sleep duration to HTN are not fully elucidated, several pathways have been proposed. Firstly, short sleep disrupts autonomic balance, increasing sympathetic activity and catecholamine release, which directly elevates BP. Prolonged wakefulness also induces chronic stress, increases sodium intake, and, through activation of the sympathetic nervous system and the renin–angiotensin–aldosterone system, reduces renal sodium excretion, leading to fluid retention and an increased cardiac volume load.⁶ Secondly, short sleep causes hormonal dysregulation, characterised by lower leptin and higher ghrelin, thereby stimulating appetite and a preference for energy-dense, salty foods, while also impairing insulin sensitivity. The consequent rise in obesity and type 2 diabetes, key intermediaries, further elevates HTN risk.^6,43-45 Thirdly, associated circadian disruption blunts nocturnal BP dipping, increases BP variability, and elevates the 24-hour BP profile, promoting chronic endothelial injury. HTN, in turn, amplifies inflammatory signalling, creating a vicious cycle.^6,43,44,46

Consistent with various epidemiological studies that consider gender differences, subgroup analyses of the articles included in this study revealed significant connections between shorter sleep durations in specific age groups and a heightened HTN risk in women.^45,47 Meta-regression further validated this finding, confirming that age significantly modified the sleep-HTN association. Furthermore, a decrease in sleep duration by 1.5 hours daily over six weeks was recently found to hinder the endothelial oxidative stress clearance capacity, raising the CVD risk due to continuous endothelial oxidative stress accumulation,⁴⁸ a finding consistent with this meta-analysis. Notably, women generally require more sleep than men; hence, they have a longer average total sleep time.⁷ Furthermore, there are various physiological processes unique to women, such as the menstrual cycle, pregnancy, menopause, and the use of exogenous female hormones (contraceptives and oestrogen supplements), which can impact their HTN risk.^49,50

This meta-analysis has several limitations. Foremost, sleep duration was assessed predominantly by subjective methods (questionnaires or interviews), which are prone to recall bias, may misclassify exposure, and do not capture sleep efficiency or quality. In addition, although some studies adjusted for confounders, key determinants of sleep duration and quality—such as OSA and depression—were not consistently measured or controlled. These factors are both common causes of sleep disturbance and independent risk factors for HTN, so the observed association between short sleep and HTN may be influenced by residual confounding. Future research should incorporate objective assessments (e.g., actigraphy or polysomnography) and systematically collect data on sleep disorders and mental health to clarify the causal relation between sleep duration and HTN. Third, the included studies also showed discrepancies in sleep reference durations, definitions of short and long sleep durations, and HTN diagnostic criteria. Nevertheless, all the included studies were cohort investigations, reducing selection and recall bias. Furthermore, this meta-analysis had a substantial sample size, found no heterogeneity or publication bias, and had consistent sensitivity analyses and dose–response findings that supported the robustness of its outcomes.

In light of these findings, achieving adequate sleep should be promoted as an important, modifiable strategy for HTN prevention in women. Public health initiatives and clinical practice should prioritise sleep health by integrating sleep education into community programmes, raising awareness of the risks of insufficient sleep, and routinely screening sleep duration and quality in primary care to identify high-risk individuals. Low-risk, low-cost sleep hygiene measures, such as maintaining consistent sleep schedules and optimising the sleep environment, should be implemented alongside dietary and physical activity interventions as integral components of cardiovascular prevention strategies.

CONCLUSION

Short sleep duration, rather than long sleep duration, is associated with an increased risk of HTN in women.

FUNDING:
This work was supported by the Excellent Innovation Team Project of the Fundamental Research Funds for Provincial Universities of Heilongjiang Province, China (Grant No. 2019-KYYWF-1277).

COMPETING INTEREST:
The authors declared no conflict of interest.

AUTHORS’ CONTRIBUTIONS:
YB: Designed the research plan, screened the literature, extracted and verified the data, and wrote the manuscript.
DK and JH: Screened the literature, extracted the data, and verified the data.
LB: Proposed the research direction and reviewed and revised the manuscript.
All authors approved the final version of the manuscript to be published.

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