The Association Between Sexual Orientation and Sleep: A Meta-Analytic Review

Abstract

Purpose:

The goal of the current meta-analytic review was to systematically examine whether sleep outcomes across several dimensions of sleep differ between lesbian, gay, and bisexual (LGB) and heterosexual individuals, as well as to examine potential study-level moderators of these associations.

Methods:

Systematic searches of PsycInfo, Medline, and PubMed databases were conducted to identify relevant observational studies published in English between January 1, 2000, and January 31, 2026. Studies were eligible if they reported an effect size comparing LGB and heterosexual groups on at least one measure of sleep.

Results:

This systematic search yielded a total of 44 studies with 69 effect sizes. Effect size data were analyzed using a random effects model. LGB individuals were more likely to report shorter sleep duration, longer sleep onset latency, and poorer sleep quality than heterosexual individuals (all p < 0.001). Effect sizes for associations between sexual orientation and sleep duration were larger in studies with more LGB women/girls, bisexual individuals, and racial/ethnic minority individuals (all p < 0.05).

Conclusion:

These findings indicate that LGB individuals experience poorer sleep health than heterosexual individuals, and that sleep problems across different dimensions of sleep may be greater for LGB women/girls, bisexual individuals, and racial/ethnic minority individuals. These findings may help to explain mental health disparities among LGB individuals, and future studies should examine the role of minority stress in LGB sleep health.

Keywords

health disparities LGB mental health minority stress sexual minority

Introduction

Adequate sleep is important for overall mental and physical health outcomes.¹ Despite the importance of sleep in health outcomes, little is known about sleep health among lesbian, gay, and bisexual (LGB) individuals, a population at significantly greater risk for health disparities.² Recommended daily sleep to promote health is 8–10 hours in adolescents and 7–9 hours in adults.³ Several dimensions of sleep are used to determine overall sleep health including duration, timing, regularity, daytime functioning, satisfaction, and continuity.⁴ Sleep quality is a commonly reported overarching construct that captures sleep health across several dimensions of sleep including sleep duration, sleep efficiency (i.e., ratio of sleep time to time spent in bed), sleep onset latency (SOL; i.e., time taken to fall asleep), and wake after sleep onset.⁵

Problems across several dimensions of sleep are associated with poor health outcomes. Poor sleep is known to contribute to poor health outcomes including type II diabetes, hypertension, cardiovascular disease, coronary heart disease, obesity, and overall mortality.^6,7 In addition to physical health outcomes, sleep problems across several dimensions are also associated with poor mental health outcomes. For example, short sleep duration and poor sleep quality are associated with greater anxiety and depression.^8–12 Long sleep duration has also been associated with greater depression.^8,12 Shorter sleep duration and poor sleep patterns predict problematic alcohol use,¹³ as well as heavy, dangerous, and/or problematic drug use, whereas good sleep quality may be a protective factor against these behaviors.¹⁴

Associations are also found between sleep and suicidality. Poor sleep is predictive of suicidality¹⁵ and may exacerbate preexisting suicidal ideation, even after controlling for other risk factors including substance use.¹⁶ Prolonged SOL is associated with increased risk of suicidal thoughts and attempts.¹⁷ The relationship between poor sleep and mental health is understood to be bidirectional,^18–20 although some studies suggest that poor sleep may be a precursor of mental health concerns and that targeting sleep may attenuate the development of psychological symptoms.^21,22

LGB individuals are at increased risk for poor health outcomes that overlap with those linked to sleep problems,²³ including poorer mental health outcomes. LGB individuals display a greater risk of anxiety, depression, suicidal thoughts, and suicidal attempts compared to heterosexual individuals.^24–29 LGB individuals are more likely to use substances including alcohol, cannabis, and tobacco and display higher rates of substance use disorders.^30,31 Consistent with these findings, a recent meta-analysis found that LGB individuals have a significantly higher risk for depression, anxiety, alcohol use disorder, and suicidality compared to heterosexual individuals.²

Stress is an important contributor to poor sleep outcomes. Greater experienced stress during the day predicts shorter duration and lower quality sleep.^32,33 Chronic stress is also a driver of poor sleep health.³⁴ The most prevalent mechanism underlying the relationship between stress and sleep is allostatic load, which links poor sleep to adverse health outcomes. Allostatic load refers to the overall toll taken on the body in response to stress, as measured by the collection of biomarkers and physiological mechanisms important for maintaining stability and regulation (e.g., diastolic blood pressure, cortisol levels, heart rate variability, etc.).³⁵

Higher allostatic load is significantly associated with poorer sleep³⁶ and contributes to poorer overall physical and mental health.³⁷ Poor sleep quality is shown to mediate the relationship between chronic stress and depression.³⁸ Importantly, the relationship between sleep and stress is reciprocal, in that poor sleep also predicts greater perceived stress, which contributes to the maintenance of sleep problems.³⁹

The minority stress model posits that LGB individuals experience identity-related stressors as a result of their marginalized and stigmatized sexual identity that in turn leads to poorer health outcomes. These stressors can include both distal stressors (i.e., discrimination or victimization) and proximal stressors (i.e., expectations of rejection, concealment of identity, or heterosexism/internalized homophobia).⁴⁰ Meta-analyses have summarized the relationship between minority stressors, such as internalized homophobia and perceived discrimination, with poorer mental health outcomes among marginalized populations including LGB individuals.^41,42 The presentation of mental health disparities in response to these stressors may also differ between LGB men and women (i.e., externalizing vs. internalizing).⁴³

Exposure to online heterosexist experiences were shown to be related to poorer mental health, mediated by higher expectations of rejection among LGB and other sexual minority individuals (e.g., pansexual, queer),⁴⁴ suggesting that the accumulation of minority stressors also contributes to adverse health outcomes. The relationship between concealment of LGB identity and mental health is less consistent than other minority stressors. Lack of disclosure may be protective against discrimination in LGB individuals, and therefore may be indirectly protective against poor mental health outcomes,⁴⁵ although studies in gay and bisexual men have shown that concealment is associated with greater self-stigma and internalized homophobia, which may contribute to poor mental health outcomes.^46,47 Concealment in combination with other minority stressors may contribute to adverse psychological outcomes.^48–50

Given the known relationship between stress and sleep, minority stress may impact sleep health among LGB individuals, although few studies have examined the relationship between minority stressors and sleep outcomes. A small but growing body of work suggests that minority stressors including greater experiences of discrimination and stigma, anticipation of rejection, and internalized homophobia are associated with poorer sleep outcomes among LGB individuals.^51–55 Recent empirical work shows that sleep disparities are prevalent among LGB individuals and may help to explain subsequent socioemotional and health disparities after controlling for demographic variables.^56,57

Review articles summarizing this growing area of interest have concluded that disparities likely exist between sexual and gender minority and cisgender heterosexual individuals,^58–60 although this has not yet been quantitatively summarized. If sleep disparities are found by sexual orientation, this may provide an avenue to explore possible mechanisms underlying mental health disparities, as well as highlight a potential target for intervention. The primary aim of the current study was to meta-analyze the difference in sleep outcomes between LGB and heterosexual individuals. We hypothesized that the overall mean effect size would indicate that LGB individuals experience poorer sleep across all dimensions of sleep examined. Moderation analyses of the following study-level variables were also examined: publication year, country, sex distribution of the LGB group, sample type (i.e., adolescent vs. adult), LGB subgroup, and race/ethnicity.

Methods

The current meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 reporting statement guidelines⁶¹ and was preregistered in PROSPERO (ID# CRD42024554798). Institutional review board approval was not needed for the current meta-analysis, given that only publicly available, deidentified data from previously published research were used and synthesized.

Search strategy and study selection

Systematic searches using Medline, PsycINFO, and PubMed databases were conducted in June 2024, January 2026, and April 2026. The following search string using Boolean operators was used to identify relevant articles: (“sexual minorit*” OR “lesbian*” OR “gay” OR “bisexual*” OR “LGBT” OR “LGB” OR “LGBTQ” OR “homosexual*” OR “non-heterosexual*” OR “same-sex” OR “queer” OR “sexual orientation” OR “sexual identity”) AND (“sleep” OR “sleep quality” OR “sleep problems” OR “sleep disturbance” OR “sleep deprivation” OR “sleep difficult*” OR “sleep duration” OR “total sleep time” OR “sleep quantity” OR “sleep latency” OR “sleep onset latency” OR “inadequate sleep” OR “insufficient sleep” OR “insomnia” OR “sleep disorder*” OR “dyssomnia” OR “circadian rhythm”).

Article title and abstract were initially screened to exclude all unrelated articles. Full text of the articles retained were screened for eligibility. All articles were screened for inclusion at each stage by two independent raters, with a full consensus reached for all included studies.

Articles were considered eligible if they met the following inclusion criteria: (1) Published in English between January 1, 2000, and January 31, 2026; (2) Included an LGB group or subgroup (e.g., gay, lesbian, or bisexual participants); (3) Included a heterosexual comparison group; (4) Consisted of healthy participants; (5) Contained at least one measure of sleep; (6) Primary empirical study published in a peer-reviewed journal; and (7) Reports an effect size for the difference between LGB and heterosexual groups on at least one sleep outcome.

Restricting inclusion to articles published from 2000 was in large part due to the vast majority of research examining sleep among LGB individuals having been published relatively recently, with a large and rapid increase occurring only within the last decade. In addition, the shift in the late 20th century toward internationally depathologizing sexual minority identities (e.g., “homosexuality” removed from the International Classification of Diseases),⁶² makes the already limited available research published prior to 2000 potentially subject to greater bias.

Studies were excluded according to the following criteria: (1) Reported effect size combines the effect for LGB participants with gender minority participants; (2) Sample consisted entirely of gender minority participants; and (3) Sample/dataset was a duplicate of another included study. Corresponding authors of eligible studies missing only effect size data were contacted and data were requested.

Study quality assessment

Study quality for all included studies was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies developed by the National Heart, Lung, and Blood Institute.⁶³ This tool contains 14 items assessing the quality of study procedure and methods, including risk of potential bias (e.g., selection bias, measurement bias, confounding). All included studies were assessed for study quality by two independent coders.

Example items from the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies include, “Was the participation rate of eligible persons at least 50%” and “Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?” Items were rated 1 = yes, 0 = no, or Other (i.e., cannot determine, not applicable, or not reported) for a total minimum score of zero and total maximum score of 14. Higher scores indicate better study quality and lower risk of bias, whereas lower scores indicate lower study quality and higher risk of bias.

Certainty of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool.⁶⁴ This tool systematically assesses certainty of evidence across several factors that affect certainty including study design, risk of bias, inconsistency, indirectness, imprecision, and publication bias. Specific factors that reduce confidence include limitations in study design, inconsistency of results, indirectness of evidence, imprecision, and publication bias. Factors that increase the quality of evidence include large magnitude of effect, dose–response gradient, and direction of plausible bias. An overall rating of high, moderate, low, or very low certainty are assigned to the evidence.

Data extraction and coding

Basic study information for all key variables including LGB subgroups included in the study, sleep outcome(s), and available effect size data for each sleep outcome from all included studies were coded independently by the first and second author. The following additional data were extracted by the first author from all included studies: measurement tool(s) used to assess sleep outcomes, operationalization of sexual orientation, sample size, sample type (i.e., adult vs. adolescent), mean age of full sample, proportion of the full sample identifying as White, proportion of LGB group(s) reporting a racial/ethnic minority identity, proportion of LGB group(s) identifying as female, country, and publication year.

The focus of this review, primarily on LGB individuals, was an a priori decision made within the minority stress theoretical framework to prevent generalizing results across sexual minority groups, given the well-documented and unique stress experiences of LGB individuals and potential distinct differences in experiences between LGB individuals and other sexual minority groups (e.g., asexual, questioning) including differences in experiences of minority stress such as disclosure or concealability.⁴⁸ However, following systematic screening, combined effect sizes that included participants who identified as a sexual minority identity other than lesbian, gay, or bisexual (e.g., pansexual, questioning, queer) were included in the current analyses if participants were included within the larger LGB group in order to maximize the number of studies included and increase the LGB sample size.

There was significant heterogeneity in the inclusion and/or selection of covariates across studies. Unadjusted effect sizes were included when available. Effect sizes were included if only demographic variables (e.g., age, education level, race/ethnicity, etc.) were controlled for. The effect size with the fewest number of covariates was used when models were reported in a stepwise fashion.

Effect size calculation

The majority of studies reported effect size as an odds ratio (OR). For studies reporting other relevant effect size data, these data were extracted and converted into an OR.⁶⁵ For studies that reported sleep outcomes for LGB subgroups separately, these effect sizes were combined to produce a single composite effect size for each sleep outcome to increase the sample size for the LGB group, maximize the number of studies included, and adequately power comparisons.

Data analytic plan

Statistical analyses were conducted using the Comprehensive Meta-Analysis Software V2. A random effects model was used to calculate an overall weighted mean effect size for each sleep outcome. For studies that reported effect sizes for LGB subgroups separately, fixed-effect meta-analysis was used to compute a single composite effect size for each sleep outcome.

Several study-level variables were examined as potential moderator variables for the relationship between sexual orientation and each sleep outcome. These study-level variables include publication year, country, percentage of LGB groups identifying as female, sample type (i.e., adolescent vs. adult), percentage of LGB groups identifying as bisexual, and percentage of LGB groups identifying as a racial/ethnic minority individual. Demographic variables used as moderators (e.g., race/ethnicity) reported separately by sex and/or LGB identity were combined across groups to compute a single weighted average.

Moderation analyses were conducted using a mixed effects model for categorical variables, in that subgroups were combined using a fixed-effects model, and a random-effects model was used to combine effect sizes across subgroups to determine the overall effect. Moderation analyses for continuous variables were conducted using a random effects meta-regression. Moderation analyses were only conducted for analyses that included at least 10 studies.⁶⁶ Statistical significance was determined using a p-value of <0.05, and 95% confidence intervals (CI) were used for precision estimates. Heterogeneity among the effect sizes was assessed using the Q-test, and the magnitude of heterogeneity was assessed using I² index. Publication bias was assessed using funnel plots, Fail-safe N, and Egger’s test.

Results

The article screening process yielded 43 eligible studies. Fifteen authors of excluded studies were contacted for missing effect size data; one author replied, providing data from one additional study. A total of 44 studies were included for analyses (see Fig. 1).^57,67–109 Sixty-nine effect sizes were included in the current analysis: 26 effects examined sleep duration,^{67,68,70–74,77,78,81,82,85,86,88,90–92,94,97,100,101,103–105,107,109} 32 effects examined sleep quality,^{57,69,70,72,74–76,79–81,83–89,91–93,95–102,104–106,108} and 11 effects examined sleep onset latency.^{57,76,81,86,88,91,97,100,101,104,105}

Fig. 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 flow diagram for the systematic literature search and article selection.⁶¹ LGB, lesbian, gay, and bisexual; TGD, transgender and gender diverse.

The majority of studies measured sexual orientation using self-reported identity and/or attraction,^{57,67–69,71–77,79–107,109} whereas three studies used sexual behavior^70,78,108 and one study used relationship type (e.g., same-sex vs. heterosexual).⁹⁰ Seventeen studies included participants with sexual minority identities other than lesbian, gay, or bisexual (e.g., pansexual, queer, questioning, “mostly” heterosexual, not sure, “other,” etc.) in a single larger overall sexual minority group with LGB individuals.^{57,67,74–76,82,83,85,88,91,95,96,99–102,104} Most studies report effect sizes for LGB men/boys and women/girls, including broken down by either LGB subgroup and/or sex. However, several studies reported effect sizes only for select LGB subgroups including gay/lesbian women (n = 2),^70,71 lesbian and bisexual women (n = 3),^69,96,105 gay and bisexual men (n = 3),^79,89,108 and gay men and lesbian women (n = 1).⁹⁰ Included studies consisted of 32 cross-sectional studies,^{68,69,72–87,91–95,97,99,100,103,105–109} 8 longitudinal studies,^{57,88,89,96,98,101,102,104} 3 daily diary studies,^67,70,71 and one 24-hour time diary study.⁹⁰ All but one study¹⁰¹ assessed sleep outcomes using subjective self-reported measures of sleep.

The three most frequently reported sleep dimensions are reported in the current review: sleep quality, sleep duration, and sleep onset latency. Dimensions of sleep were operationalized and measured in several different ways across studies. Sleep quality was defined broadly in the current meta-analysis as done similarly in a previous review of the literature,⁵ due to heterogeneity in the terminology used to describe sleep quality-related outcomes. Effect size estimates that reported quality of sleep or a closely related term (e.g., sleep satisfaction), or insomnia symptoms (e.g., difficulty staying asleep, poor/inadequate sleep, etc.) were categorized as sleep quality.

Effect size estimates that report hours/minutes of sleep or short sleep were categorized as sleep duration. Most studies defined short sleep as less than the recommended amount of sleep (i.e., <7 hours for adults, <8 hours for adolescents). Given that nearly all studies reported effect sizes for short sleep duration, studies that reported effect sizes for combined short and long sleep (e.g., >10 hours) duration were excluded from analyses to allow for uniformity in the direction of associations. Effect size estimates that report time to fall asleep, trouble falling asleep, or prolonged sleep latency were categorized as SOL. Most studies reporting prolonged SOL defined this as >30 minutes to fall asleep.

There was significant heterogeneity in the measurement of sleep across all three sleep outcomes. Sleep duration was most commonly assessed using a single self-report item (n = 21), as well as the component score from a validated scale (n = 4) and objectively measured average hours/mins of sleep (n = 1). Of the single self-reported items, sleep duration effect sizes were reported as average hours and/or minutes of sleep (n = 6), short or very short sleep duration (n = 10), proportion of participants meeting sleep recommendations (n = 3), and perception of current adequate sleep duration (n = 2). The cutoff scores for items assessing short or very short sleep duration also differed across studies. Of the items reporting short or very short sleep duration, this was defined across studies as <8 hours (n = 1), <7 hours (n = 4), ≤ 6 hours (n = 1), <6 hours (n =1), 5–6 hours (n = 1), and ≤5 hours (n = 2) on average.

Sleep quality effect sizes were measured using total scores on full-length validated self-report scales of sleep quality or insomnia symptoms (e.g., Pittsburgh Sleep Quality Index, Insomnia Severity Index; n = 15), self-reported single items (n = 16), and objective measurement of percentage of time in bed spent asleep (n = 1). Self-reported single items reported either subjective perceived sleep quality or satisfaction (n = 4) or insomnia symptoms (e.g., difficulty staying asleep, poor/inadequate sleep, etc.; n = 12). SOL was measured using a component score from a validated scale (n = 4), a single item assessing difficulty falling asleep (n = 6), and objective measurement of number of minutes to fall asleep (n = 1).

See Table 1 for study characteristics. Included studies were published between 2002 and 2025, with a median publication year of 2021. The sample size of included studies ranged from 66 to 320,804 with a mean of 33,476, standard deviation of 62,969, and median of 2,755. The total sample size for the current analysis was 1,472,956 (1,388,224 heterosexual; 84,732 LGB).

Table 1.

Characteristics of Studies Included in the Meta-Analysis

Authors, year of publication, and reference	Population	N	Mean age	% Female	% White	% SM	Country	LGB subgroup(s)	Sleep outcome(s)
Wong et al. (2024)⁵⁷	Adolescents	8822	13.8	51.5%	80%	20.2%	UK	LGB^a	Sleep quality; SOL
Austin et al. (2016)⁶⁷	Adults	1670	24.8	68.9%	94.0%	33.0%	USA	LGB^a	Sleep duration
Baiden et al. (2020)⁶⁸	Adolescents	13,659	NR	51.8%	43.3%	14.5%	USA	LGB	Sleep duration
Blosnich et al. (2013)⁶⁹	Adults	898	53.7	100%	81.8%	5.9%	USA	L/B women	Sleep quality
Brown et al. (2008)⁷⁰	Adults	66	26.1	100%	NR	NR	USA	L women^b	Sleep duration; Sleep quality
Burleson et al. (2002)⁷¹	Adults	236	33.4	100%	NR	37.7%	USA	L women	Sleep duration
Caceres and Hickey (2020)⁷²	Adults	16,114	37.9	49.2%	59.0%	4.4%	USA	LGB	Sleep duration; Sleep quality
Caceres et al. (2019)⁷³	Adults	151,537	NR	55.1%	65.9%	3.8%	USA	LGB	Sleep duration
Chaput et al. (2024)⁷⁴	Adults	38,047	NR	55.6%	85.1%	3.0%	Canada	LGB^a	Sleep duration; Sleep quality
Christensen et al. (2024)⁷⁵	Adults	1534	21.3	50.4%	66.4%	17.0%	USA	LGB^a	Sleep quality
Crawford and Ridner (2018)⁷⁶	Adults	86	NR	61.6%	75.6%	50%	USA	LGB^a	Sleep quality; SOL
Dai et al. (2020)⁷⁷	Adolescents	14,200	NR	58.0%	49.6%	11.2%	USA	LGB	Sleep duration
Deraz et al. (2023)⁷⁸	Adults	164,230	46	53.6%	NR	5.2%	France	LGB^a	Sleep duration
Dickerson-Amaya and Coston (2019)⁷⁹	Adults	2088	NR	0%	NR	36.2%	USA	G/B men	Sleep quality
Duncan et al. (2018)⁸⁰	Adults	1192	NR	53.4%	35.0%	10.8%	USA	LGB	Sleep quality
Galinsky et al. (2018)⁸¹	Adults	102,940	NR	54.5%	65.6%	2.3%	USA	LGB	Sleep duration; Sleep quality; SOL
Hope et al. (2023)⁸²	Adults	1483	NR	59.5%	96.5%	12.0%	UK	LGB^a	Sleep duration
Jacob et al. (2021)⁸³	Adults	7310	46.3	51.4%	85.1%	6.8%	UK	LGB^a	Sleep quality
Langvik et al. (2019)⁸⁴	Adolescents	1401	17.7	58.7%	NR	10.3%	Norway	LGB	Sleep quality
Levenson et al. (2021)⁸⁵	Adolescents	744	16	83.0%	66.0%	80%	USA	LGB^a	Sleep duration; Sleep quality
Li et al. (2017)⁸⁶	Adolescents	123,459	15.3	47.8%	NR	5.0%	China	LGB	Sleep duration; Sleep quality; SOL
Li et al. (2021)⁸⁷	Adults	44,472	NR	52.0%	78.8%	2.9%	USA	LGB	Sleep quality
Luk et al. (2019)⁸⁸	Adults	1946	NR	59.1%	59.0%	6.3%	USA	LGB^a	Sleep duration; Sleep quality; SOL
Marmet et al. (2021)⁸⁹	Adults	2345	29.1	0%	NR	13.2%	Switzerland	G/B men	Sleep quality
Martin-Storey et al. (2018)⁹⁰	Adults	16,821	48.8	50.1%	73.3%	0.6%	USA	L women; G men^b	Sleep duration
Oh and Patterson (2024)⁹¹	Adults	481	27.5	51.1%	64.3%	67.4%	USA	LGB^a	Sleep duration; Sleep quality; SOL
Rodrigues et al. (2024)⁹²	Adults	28,969	NR	52.1%	93.5%	2.1%	Canada	LGB	Sleep duration; Sleep quality
Seelig et al. (2023)⁹³	Adults	80,225	37	78.0%	78.0%	6.0%	USA	LGB	Sleep quality
Seo et al. (2015)⁹⁴	Adolescents	11,829	15.6	40.3%	NR	7.5%	Korea	LGB	Sleep duration
Suárez et al. (2021)⁹⁵	Adults	554	20.6	58.7%	NR	14.8%	Colombia	LGB^a	Sleep quality
Webermann et al. (2023)⁹⁶	Adults	263	49.5	100%	74.1%	9.9%	USA	L/B women^a	Sleep quality
Wu et al. (2021)⁹⁷	Adults	27,065	19.9	57.2%	NR	4.2%	China	LGB	Sleep duration; Sleep quality; SOL
Yazdani et al. (2025)⁹⁸	Adults	707	20	61.0%	55.4%	28.9%	USA	LGB	Sleep quality
Chang et al. (2025)⁹⁹	Adults	820	56.12	12.4%	75.9%	12.1%	USA	LGB^a	Sleep quality
Gaston et al. (2025)¹⁰⁰	Adults	147,907	47.2	50.9%	70.6%	3.2%	USA	LGB^a	Sleep duration; Sleep quality; SOL
Gillis et al. (2025)¹⁰¹	Adolescents	2979	11.96	51.2%	61.3%	7.1%	USA	LGB^a	Sleep duration; Sleep quality; SOL
Irani et al. (2025)¹⁰²	Adults	766	38.6	81.7%	79.0%	19.7%	USA	LGB^a	Sleep quality
Kreski and Keyes (2025)¹⁰³	Adolescents	14,894	NR	NR	NR	17.2%	USA	LGB	Sleep duration
Kwon et al. (2025)¹⁰⁴	Adolescents	847	14.4	57.5%	81.0%	19.4%	USA	LGB^a	Sleep duration; Sleep quality; SOL
Martinez-Miller et al. (2025)¹⁰⁵	Adults	50,790	NR	100%	85.9%	2.2%	USA	L/B women	Sleep duration; Sleep quality; SOL
Morgan et al. (2025)¹⁰⁶	Adults	1902	20.1	64.4%	45.3%	20.1%	USA	LGB	Sleep quality
Real et al. (2025)¹⁰⁷	Adolescents	320,804	NR	49.8%	31.7%	9.3%	USA	LGB	Sleep duration
Yu et al. (2024)¹⁰⁸	Adults	2531	20.2	0%	NR	11.5%	China	G/B men^b	Sleep quality
Zhu et al. (2025)¹⁰⁹	Adults	61,323	NR	53.4%	75.5%	3.9%	USA	LGB	Sleep duration

Mean age is reported in years.

Overall LGB group included additional sexual minority identities (e.g., pansexual, queer, questioning, “mostly” heterosexual, not sure, “other,” etc.).

Sexual orientation was assessed using attraction, sexual behavior, and/or relationship type rather than self-report identity.

B, bisexual; G, gay; L, lesbian; LGB, lesbian, gay, and bisexual; NR, not reported; SOL, sleep onset latency; UK, United Kingdom; USA, United States of America.

Several included studies reported demographic data broken down by subgroup and required calculation of a single weighted mean or stratified demographic information into ranges with no mean reported; therefore, demographic variables for the full sample are best estimates. The approximate weighted mean age of the full sample (when reported) was 36 years old. The full sample was approximately 54.9% female, 60.7% White, and 5.8% LGB persons. Included studies consisted of 33 adult samples (i.e., 18 years of age or older) and 11 adolescent samples. Most included studies were conducted in the United States (k = 31).

Primary outcomes

LGB individuals were more likely than heterosexual individuals to report worse sleep outcomes across all three domains of sleep. LGB individuals were at 1.38 times higher odds of having a shorter sleep duration (OR = 1.38, 95% CI: 1.15–1.56, z = 3.71, p < 0.001), 1.35 higher odds of a longer SOL (OR = 1.35, 95% CI: 1.22–1.49, z = 5.70, p < 0.001), and 1.56 higher odds of poorer sleep quality (OR = 1.56, 95% CI: 1.42–1.73, z = 8.735, p < 0.001).

Moderation outcomes

Publication year

Study publication year moderated the relationship between sexual orientation and sleep duration (β = 0.03, 95% CI: 0.027–0.038, z = 13.06, p < 0.001) and sleep quality (β = −0.01, 95% CI: −0.02 to −0.003, z = −2.73, p = 0.01). These findings suggest that sleep duration effect sizes were larger for more recent studies, whereas sleep quality effect sizes were smaller. The relationship between sexual orientation and SOL was not moderated by study publication year (p > 0.05).

Sex

The relationship between sexual orientation and sleep duration was significantly moderated by the proportion of the LGB sample identifying as female (β = 0.001, 95% CI: 0.0005–0.02, z = 3.33, p < 0.001, k = 19). This finding suggests that effect sizes increased as the proportion of LGB females increased. Sex did not moderate the relationship between sexual orientation and sleep quality or SOL (all p > 0.05).

LGB subgroup

The proportion of the LGB sample identifying as bisexual moderated the relationship between sexual orientation and sleep duration (β = 0.0035, 95% CI: 0.0031–0.004, z = 16.41, p < 0.001, k = 14) and sleep quality (β = 0.003, 95% CI: 0.002–0.004, z = 6.23, p < 0.001, k = 12). These findings suggest that effect sizes increased as the percentage of individuals identifying as bisexual increased. Less than 10 studies (k = 3) examining SOL as an outcome reported LGB subgroup breakdown; therefore, moderation analyses were not conducted.

Race/ethnicity

Race/ethnicity significantly moderated the relationship between sexual orientation and both sleep duration (β = 0.01, 95% CI: 0.0008–0.016, z = 6.39, p < 0.001, k = 11) and sleep quality (β = 0.009, 95% CI: 0.004–0.016, z = 3.06, p = 0.002, k = 14), such that effect sizes increased as the proportion of LGB persons identifying as racial/ethnic minority increased. Less than 10 studies (k = 7) examining SOL as an outcome reported the proportion of LGB persons identifying as racial/ethnic minority. Therefore, moderation analyses were not conducted.

Sample type

A significant moderation was found by sample type on the relationship between sexual orientation and sleep duration (OR = 1.21, 95% CI: 1.12–1.31, z = 4.81, p < 0.001), sleep quality (OR = 1.58, 95% CI: 1.42–1.76, z = 8.45, p < 0.001), and SOL (OR = 1.37, 95% CI: 1.23–1.52, z = 5.78, p < 0.001). For sleep quality and SOL, respectively, these findings indicate that studies with adult samples (OR = 1.63, 95% CI: 1.46–1.84, z = 8.21, p < 0.001; OR = 1.48, 95% CI: 1.29–1.52, z = 5.78, p < 0.001) displayed a significantly higher overall effect size than studies with adolescent samples (OR=1.35, 95% CI: 1.06–1.72, z = 2.43, p = 0.015; OR = 1.22, 95% CI: 1.04–1.44, z = 2.38, p = 0.017). However, moderation was found in the inverse direction for sleep duration, such that adolescents (OR = 1.63, 95% CI: 1.35–1.96, z = 5.10, p < 0.001) displayed a higher overall effect size than adults (OR = 1.14, 95% CI: 1.05–1.24, z = 2.96, p = 0.003).

Country

The moderation analysis for the country was dichotomized into studies conducted within the United States versus outside of the United States, given that examining moderation across all countries was not possible due to several countries contributing only one study. A significant moderation was found by country on the relationship between sexual orientation and sleep duration (OR = 1.29, 95% CI: 1.12–1.48, z = 3.55, p < 0.001), such that studies conducted within the United States displayed a higher overall effect (OR = 1.42, 95% CI: 1.17–1.71, z = 3.58, p < 0.001) than studies outside of the United States (OR = 1.15, 95% CI: 0.94–1.42, z = 1.35, p = 0.18). Similar results were found for sleep quality (OR = 1.57, 95% CI: 1.41–1.74, z = 8.49, p < 0.001), such that U.S. samples displayed a larger overall effect (OR = 1.55, 95% CI: 1.36–1.76, z = 6.58, p < 0.001) than non-US samples (OR = 1.6, 95% CI: 1.35–1.89, z = 5.38, p < 0.001).

Moderation analysis for SOL by country was significant (OR = 1.38, 95% CI: 1.33–1.44, z = 16.51, p < 0.001), although in the opposite direction from sleep duration and quality. For SOL, non-US samples (OR = 1.39, 95% CI: 1.33–1.44, z = 16.31, p < 0.001) displayed a larger overall effect than US samples (OR = 1.30, 95% CI: 1.07–1.57, z = 2.66, p = 0.008) than non-US samples (OR = 1.39, 95% CI: 1.33–1.44, z = 16.31, p < 0.001).

Heterogeneity tests

The heterogeneity tests indicated that there was significant heterogeneity in effect sizes for the relationship between sexual orientation and sleep duration (Q = 1803.42, p < 0.001), sleep quality (Q = 328.64, p < 0.001), and SOL (Q = 67.11, p < 0.001). Between-study heterogeneity was also shown for all three outcomes indicated by a large amount of heterogeneity in effect sizes across studies for the relationship between sexual orientation and sleep duration ( $I^{2}$ = 98.61), sleep quality ( $I^{2}$ = 90.57), and SOL ( $I^{2}$ = 85.10).

Risk of bias assessment

Publication bias was assessed using examination of funnel plots, which showed reasonably symmetrical distributions for sleep duration, sleep onset latency, and sleep quality. This was supported by the Egger’s test, which indicated nonsignificance for sleep duration (t = 1.58, 95% CI: −8.74 to 1.16, p = 0.13), sleep quality (t = 0.34, 95% CI: −1.67 to 2.33, p = 0.74, and SOL (t = 0.66, 95% CI: −3.83 to 2.10, p = 0.53). The Fail-safe N for each outcome suggested that 5351 additional studies (for sleep duration), 5290 additional studies (for sleep quality), and 754 additional studies (for SOL) with an OR of 1.0 would be needed before the main effect would become nonsignificant.

All included studies scored between 5 and 10 on study quality assessment ratings, with a median score of 7, indicating overall fair quality of included studies and moderate risk of bias. The most common reasons for loss of points on the overall rating score across studies included the use of cross-sectional design and analyses, lack of sample size justification, lack of inclusion of key confounding variables, and low participation rate of eligible persons. Study quality ratings for all included studies can be found in Table 2. An overall rating of moderate certainty was assigned to the evidence when considering all relevant certainty factors of the GRADE tool⁶⁴ in the current body of evidence (e.g., study designs, risk of bias, inconsistency of results, imprecision, indirectness of evidence, publication bias, effect size, and direction of plausible effect).

Table 2.

Quality Assessment Ratings for All Included Studies on the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies

Authors, year of publication, and reference	Rating
Wong et al. (2024)⁵⁷	10
Austin et al. (2016)⁶⁷	8
Baiden et al. (2020)⁶⁸	9
Blosnich et al. (2013)⁶⁹	6
Brown et al. (2008)⁷⁰	9
Burleson et al. (2002)⁷¹	8
Caceres and Hickey (2020)⁷²	7
Caceres et al. (2019)⁷³	8
Chaput et al. (2024)⁷⁴	7
Christensen et al. (2024)⁷⁵	8
Crawford and Ridner (2018)⁷⁶	8
Dai et al. (2020)⁷⁷	8
Deraz et al. (2023)⁷⁸	6
Dickerson-Amaya and Coston (2019)⁷⁹	7
Duncan et al. (2018)⁸⁰	6
Galinsky et al. (2018)⁸¹	7
Hope et al. (2023)⁸²	6
Jacob et al. (2021)⁸³	7
Langvik et al. (2019)⁸⁴	6
Levenson et al. (2021)⁸⁵	6
Li et al. (2017)⁸⁶	5
Li et al. (2021)⁸⁷	8
Luk et al. (2019)⁸⁸	9
Marmet et al. (2021)⁸⁹	7
Martin-Storey et al. (2018)⁹⁰	9
Oh and Patterson (2024)⁹¹	7
Rodrigues et al. (2024)⁹²	7
Seelig et al. (2023)⁹³	10
Seo et al. (2015)⁹⁴	6
Suárez et al. (2021)⁹⁵	7
Webermann et al. (2023)⁹⁶	8
Wu et al. (2021)⁹⁷	7
Yazdani et al. (2025)⁹⁸	8
Chang et al. (2025)⁹⁹	7
Gaston et al. (2025)¹⁰⁰	7
Gillis et al. (2025)¹⁰¹	9
Irani et al. (2025)¹⁰²	9
Kreski and Keyes (2025)¹⁰³	8
Kwon et al. (2025)¹⁰⁴	6
Martinez-Miller et al. (2025)¹⁰⁵	6
Morgan et al. (2025)¹⁰⁶	7
Real et al. (2025)¹⁰⁷	6
Yu et al. (2024)¹⁰⁸	7
Zhu et al. (2025)¹⁰⁹	6

All ratings are out of a total possible score of 14, with higher scores indicating better study quality.

Discussion

The primary aim of this review was to systematically and quantitatively summarize the literature on sexual orientation and sleep outcomes. This is the first meta-analysis to compare sleep outcomes between LGB and heterosexual individuals. As hypothesized, the results of the current meta-analysis indicate that LGB individuals have greater likelihood of poor sleep outcomes than their heterosexual counterparts, including shorter sleep duration, poorer sleep quality, and longer sleep onset latency. These findings contribute to the large body of literature documenting health disparities among LGB individuals.

Sleep health is an important determinant of physical and mental health outcomes.^6–9,12,15 The relationship between sexual orientation and sleep health is only just beginning to garner attention. The findings of the current meta-analysis are in line with previous reviews examining differences in sleep outcomes between LGB and heterosexual individuals that concluded that LGB individuals are at increased risk of poorer sleep outcomes.^58,60

One possible explanation for these sleep disparities is the impact of greater stress experienced by LGB persons. Recent studies have found a relationship between minority stressors and sleep among LGB and gender minority persons.^51,53,55,110 For example, LGB adults who reported experiences of discrimination in the past 12 months had higher rates of poor sleep quality, prolonged sleep onset latency, and felt less rested than LGB adults who had not experienced discrimination.⁵³ Similarly, sexual and gender minority persons who reported stigma were 1.39 times more likely to report a sleep disorder diagnosis than those who did not report stigma.⁵⁵ However, only higher internalized homophobia was associated with greater likelihood of sleep disorder diagnosis.⁵⁵

Chan and Fung found that both experienced and anticipated discrimination were associated with poorer sleep through an increase in primal threat among LGB individuals.⁵² These poorer sleep outcomes in response to discrimination were in turn linked to poorer physical and mental health.⁵² These findings suggest that minority stress may help to explain poor sleep outcomes and in turn, help explain health disparities between LGB and heterosexual individuals, although underlying mechanisms of this relationship remain unclear.

LGB individuals are at greater risk of cardiovascular disease than heterosexual individuals, with several multilevel mechanistic pathways theorized including minority stress and poor sleep.¹¹¹ Despite limited research available among LGB individuals, work with other marginalized groups (e.g., racial and ethnic minority groups) suggests that discrimination is associated with changes in indicators of allostatic load such as heart rate variability, blood pressure, and cortisol^112–114 that may negatively impact both sleep and health outcomes.¹¹⁴ One recent study conducted with sexual and gender minority people has shown that intersectional discrimination experiences were directly associated with greater allostatic load and poorer sleep quality, although the relationship between discrimination and allostatic load was not shown to be mediated by sleep.¹¹⁵ Another study showed that poorer sleep outcomes found in response to greater discrimination among LGB individuals were linked to poorer mental and physical health.⁵²

Studies have found that poorer sleep health among sexual and gender minority individuals are associated with significantly greater risk of suicide¹¹⁶ that may in part be explained by minority stressors.¹¹⁷ Tepman and Wong found that victimization among LGB youth prospectively predicted self-harm behavior and depressive symptoms, mediated by difficulty staying asleep through the night.¹¹⁸ The findings of the current meta-analysis support this growing body of work suggesting that poorer sleep outcomes among LGB individuals may be a potentially important factor underlying physical and mental health disparities among LGB individuals by clarifying and quantitatively summarizing poorer sleep outcomes across several sleep domains between LGB and heterosexual individuals.

Moderation analyses

Results of moderation analyses found that several study-level variables moderated the relationship between sexual orientation and sleep outcomes. The current study’s findings suggest that sleep disparities are most pronounced among individuals in the United States for sleep duration and sleep quality. However, the majority of included studies were conducted in the United States, and studies outside of the United States were largely conducted in Western countries that generally have greater social acceptance of LGBT individuals compared with the United States,¹¹⁹ which may be driving these results.

In addition, results in the opposite direction were found for SOL, such that countries outside of the United States displayed longer SOL. It is unclear why these findings were mixed, although only three studies examined SOL in individuals outside of the United States, and therefore, analyses may have been underpowered. Additional research is needed to clarify findings across sleep domains by country.

Sleep disparities in sleep quality and SOL were found to be greater among adults than adolescents in the current review, whereas sleep duration was found to be shorter in adolescents. It is unclear why these findings were mixed. A large body of research has found that adolescents generally experience poor sleep health¹²⁰ that is associated with a greater likelihood of suicidal ideation, with LGB identity found to be an added risk factor.⁶⁸ However, the majority of the research examining sleep health among LGB adolescents focuses on sleep duration and suicidality and little work has examined these associations across different dimensions of sleep.^116,121 The current study’s findings highlight the need for greater focus on specific dimensions of sleep in LGB individuals across the lifespan and their unique impact on mental health outcomes.

The current findings suggest that LGB women/girls may have the shortest sleep duration. This finding is consistent with previous literature that has found LGB women experience poorer sleep outcomes⁵⁹ and show increased risk for poorer mental health outcomes.^28,31 These findings suggest a greater need for examination of sex differences in the relationship between sexual orientation and sleep.

The current findings suggest that bisexual individuals experience shorter sleep duration and poorer sleep quality than lesbian/gay individuals. These findings are consistent with previous studies that have found bisexual individuals experience the poorest sleep outcomes.^122,123 A previous review by Butler et al.⁵⁸ concluded that bisexual individuals may be at increased risk for poor sleep, although this was not directly tested. Additional work is needed to clarify subgroup differences in sleep outcomes among LGB individuals.

When examining sex differences within LGB subgroups, previous literature suggests that bisexual women in particular may be at increased risk for mental health disparities such as suicidality and self-injury.²⁸ Recent work has also found that among LGB adults, bisexual women display the highest rates of insomnia symptoms.¹²⁴ Bisexual women, but not bisexual men, also display higher rates of daytime tiredness and sleep medication use.¹²³ Therefore, in tandem with our current findings that LGB women/girls may be at greater risk for sleep disparities, it is possible that bisexual women in particular are driving these findings in the literature. Future work should examine the intersection of gender and sexual identity to clarify potential differences in sleep outcomes within and across LGB subgroups.

Lastly, current findings suggest that LGB individuals who identify as racial/ethnic minority people experience greater sleep disparities, in line with previous work.⁷³ Intersectional work (i.e., consideration of the intersection of minority stress experiences among individuals with multiple marginalized identities) has found that these intersecting minority stress experiences such as racism and heterosexism may contribute to poorer sleep health outcomes among LGB racial/ethnic minority individuals.⁵¹ The current moderation results further encourage an intersectional approach to examining sleep disparities in LGB individuals.

Clinical implications

The findings of the current meta-analysis suggest that sleep may be an important target for intervention among LGB individuals. Therapeutic intervention for sleep (i.e., cognitive behavioral therapy for insomnia) has shown to be efficacious in improving sleep outcomes in populations with chronic disease (e.g., cancer, chronic pain)¹²⁵ and may reduce the risk of poor health outcomes such as cardiovascular disease.¹²⁶ Interventions to target sleep may also improve health outcomes among LGB individuals.⁵⁸ Sleep interventions have been shown to improve mental health outcomes in the general population.¹²⁷ However, a consideration of the unique stress faced by LGB individuals and its related biological, physiological, and behavioral consequences are necessary to understand adverse health outcomes.¹²⁸ Therefore, tailored sleep interventions are needed in this population, including a greater focus and understanding of the role of minority stressors on sleep outcomes.

Limitations and future directions

Several limitations of the available literature included in the current study should be considered. First, there was significant heterogeneity across included studies in the operationalization and measurement of sleep outcomes, resulting in a broad categorization of dimensions of sleep that may be driving the results of the current study. Future research should work toward standardizing sleep measurement to improve generalizability and interpretation, and allow for greater confidence in findings on sleep disparities between LGB and heterosexual individuals.¹²⁹

Another notable limitation was the heterogeneity in the reporting of sleep outcomes across LGB subgroups and/or sex across studies, resulting in the use of a single overall effect size that combined effect size estimates across all LGB subgroups and does not allow for examination of subgroup-level differences in sleep outcomes that may be present.⁵⁸ Future studies should recruit larger samples of LGB individuals to adequately power and examine sleep differences across both subgroups and the sex of sexual minority individuals. In addition, the included studies displayed overall fair study quality ratings. The majority of included studies used cross-sectional, subjective measures of sleep. Many studies used a single item to assess sleep. Future studies should utilize daily diary, objective measurements of sleep, and validated instruments in order to reduce potential bias and examine directionality of associations.

Summarized demographic information of studies included in the current meta-analysis were best estimates, given that several studies reported demographic information broken down by LGB subgroup and/or stratified. Future studies should fully report all demographic information, including means and standard deviations, for both the full LGB group as well as subgroups to allow for an accurate description of the sample. Lastly, the current sample was majority White, female, and majority residents of the United States or other Western countries. In addition, the current findings suggest that racial/ethnic LGB individuals may be at increased risk for sleep disparities. Future studies are needed with more diverse and non-Western samples to allow for an intersectional approach, increase generalizability, and better understand sleep disparities among LGB individuals.

Several limitations of the current meta-analysis and the review process itself should also be noted. The current meta-analysis used a limited scope of examining LGB individuals, which does not allow for generalizability or insight into sleep health of other sexual minority identities (e.g., pansexual, queer). Future research should recruit larger and more diverse samples of sexual minority individuals across all identities to be able to examine subgroup differences in sleep health, including for other sexual minority identities. Although completed by two independent raters, the current meta-analysis completed systematic screening of articles at several separate time points. This may increase risk of error or bias, and future meta-analyses examining sleep outcomes by sexual orientation should utilize a more concise approach to the systematic study screening/selection process.

Future studies should examine the role of minority stressors in sleep outcomes. A small but growing body of research suggests that minority stress is associated with sleep outcomes among LGB individuals.^51,53,55,110 More work is needed to clarify the role of minority stress in sleep among LGB persons, including the use of physiological and biological markers such as cortisol, heart rate variability, and blood pressure. Intervention studies are also needed to determine whether improving sleep among LGB individuals improves mental health outcomes. Lastly, effect size data for one included study were provided directly from the author upon request, which may be a limitation given the lack of prior peer review of these data.

Conclusion

The current review examined and summarized examined and summarized the relationship between sexual orientation and sleep outcomes. This is the first meta-analysis to systematically and quantitatively assess differences in sleep outcomes between LGB and heterosexual individuals. The study findings indicate that LGB individuals are more likely to experience poorer sleep quality, shorter sleep duration, and longer SOL than heterosexual individuals, and that poor sleep outcomes may be most likely for LGB women/girls, bisexual individuals, and racial and ethnic minority persons. More work is needed to examine poor sleep health across different dimensions of sleep as a potential mechanism of poor mental health outcomes among LGB individuals, as well as potential contributors to poor sleep such as minority stress.

Authors’ Contributions

U.B.: Conceptualization, methodology, writing—original draft, review, and editing, formal analysis, and data curation, visualization; M.E.Q.: Writing—review and editing, validation, and data curation; K.-D.R.: Writing—review and editing, validation, data curation, and formal analysis; J.A.C.: Conceptualization, writing—review and editing, validation, and supervision. All authors approved the final version of the article for publication, agreed to be accountable for all aspects of the work, and resolved any issues related to its accuracy or integrity.

Footnotes

Ethical Considerations

Institutional review board approval was not needed for the current meta-analysis, given that only publicly available, deidentified data from previously published research were used and synthesized.

Consent for Publication

Informed consent was not applicable, as the current study is a meta-analysis of previously published research.

Data Availability

The current project was registered in PROSPERO (ID# CRD42024554798). Data for the current meta-analysis are available upon request to the corresponding author.

Declaration of Conflicting Interest

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding Information

The authors received no financial support for the research, authorship, and/or publication of this article.

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