Abstract
Purpose
Obstructive sleep apnea (OSA) affects nearly 1 billion people worldwide and is associated with significant cardiometabolic, neurocognitive, and psychosocial consequences. Gender differences in symptom presentation may contribute to underdiagnosis and unmet needs, particularly among women. This study aimed to assess gender-specific differences in the psychosocial burden of OSA using the Sleep Health Inquiries on Needs and Emotions (SHINE) survey.
Methods
The SHINE survey was conducted in 2024 among 1,500 U.S. adults with self-reported OSA. Participants completed validated items across five domains: work productivity, daily non-work activities, OSA symptoms, relationships, and negative feelings. Gender differences were examined using descriptive statistics, chi-square tests, and multivariable generalized linear models adjusted for demographics, comorbidities, and OSA severity.
Results
Respondents included 755 men (50.3%) and 745 women (49.7%). Women were younger, had higher rates of psychological comorbidities (e.g., anxiety: 64.6% vs. 43.2%, p<0.001), and reported more non-classic OSA symptoms, while men more frequently reported cardiometabolic conditions. In adjusted analyses, women were 46% more likely to report OSA impacting daily non-work activities (p=0.01) and 52% more likely to experience ≥2 OSA symptoms in the prior 30 days (p=0.04). No significant gender differences were observed in work productivity impairment after adjustment, although greater symptom burden and negative feelings were associated with work limitations across both sexes.
Conclusions
Women with OSA reported broader symptom profiles, more daily activity limitations, and greater emotional burden than men. These findings highlight the need for gender-sensitive screening and personalized treatment approaches to improve diagnosis and management of OSA.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11325-026-03636-9.
Keywords: Obstructive sleep apnea, OSA, Gender differences, Psychosocial burden, Patient-reported outcomes, Sleep health
Introduction
Obstructive sleep apnea (OSA) is a serious, chronic disease caused by sleep-related neuromuscular dysfunction and predisposing anatomic abnormalities, characterized by recurrent partial or complete upper airway obstruction during sleep [1]. These pathophysiological mechanisms result in chronic intermittent hypoxia, contributing to a range of adverse health outcomes, including increased risk of long-term cardiometabolic and neurocognitive sequelae as well as early mortality [2–6].
OSA is estimated to affect nearly 1 billion people worldwide, including more than 80 million adults in the United States [7, 8]. Prevalence estimates of OSA in the general population indicate a male to female ratio of between 3:1 and 8:1, although there is ample evidence that women are underdiagnosed [9]. Sleep apnea severity also increases with age, often more so for women after menopause [9, 10].
Common symptoms of OSA include excessive daytime sleepiness, fatigue, snoring, disrupted breathing, and morning headaches. Symptoms of OSA may be absent in up to half of individuals, and are poorly correlated with OSA severity, as measured by the Apnea-hypopnea Index (AHI) [11–13]. When present, symptom profiles can vary by sex due to underlying anatomical, biological, and physiological differences, resulting in distinct disease experiences. Males are more likely to exhibit classic symptoms such as loud snoring and noticeable breathing pauses, largely due to more airway adiposity, greater neck circumference, and higher airway susceptibility contributing to elevated AHI. Whereas females tend to have lower loop gain, less airway collapsibility, and lower arousal threshold in non-rapid eye-movement sleep [9, 10], resulting in fewer apneas with more hypopneas and a higher rapid eye-movement associated sleep apnea [14]. Women more commonly report fatigue, insomnia, depression, anxiety and mood disturbances [15].
Physiologically, estrogen and progesterone in women tend to be protective in pre-menopausal women decreasing the risk and severity of OSA; however, declining hormone lower levels after menopause increase OSA risk and severity, approaching that seen in men [16]. Sex differences also influence symptom perception and reporting of OSA [17].
Due to these biological and physiological differences in OSA manifestations, a sex and gender lens is being applied to epidemiologic, diagnostic, and treatment data to identify the gaps in understanding of OSA pathophysiology and improving current treatment pathways toward personalized care. Misdiagnosis and undertreatment in women with OSA remain major concerns, driven in part by physician bias and limited awareness that women present their symptoms differently than men [18]. Sex-specific screening tools for women do not currently exist, and additional research is needed to refine diagnostic criteria and to better identify women at risk. Furthermore, understanding how various therapies affect underlying physiological mechanisms (endotypes) and their resulting clinical presentations of OSA (phenotypes) in both sexes may lead to improved patient outcomes and pave the way for personalized treatment approaches [9]. Recognizing sex-specific symptom burden may also help reduce implicit and explicit clinician bias during patient evaluation.
In this study, we aimed to assess gender differences on the impact of OSA on various psychosocial factors and better understand the unmet need of people living with OSA using the Sleep Health Inquiries on Needs and Emotions (SHINE) survey, in collaboration with sleep health patient advocacy groups and experts. Administered online to 1,500 adults with OSA in the United States, the SHINE survey encompassed five psychosocial domains: work productivity, daily (non-work) activities, OSA symptoms, relationships, and negative feelings. The objective of this study was to evaluate the relationship between gender and OSA in the context of all five psychosocial domains from the SHINE survey.
Methods
SHINE survey design and participants
Study data came from the cross-sectional SHINE survey, in collaboration with the Alliance of Sleep Apnea Partners (ASAP), Project Sleep, and OSA experts (the survey is available in the Supplementary Material). The SHINE survey recruited participants from an online panel of adults in the United States (US) by four survey and market research companies with the primary objective to understand the unmet psychosocial needs of a person living with OSA. The survey was conducted between July and August of 2024, and participant inclusion was defined by self-reported diagnosis of OSA, minimum age of 18 years, ability to read English, and confirmed informed consent.
The survey collected information on the following categories: demographics; diagnosis, OSA symptoms, and treatment; relationships; productivity and activities; stigma and self-image; hopes, fears, and challenges; health care professional engagement; and future OSA state. These categories were informed by OSA experts (a patient advocate, a research psychologist with expertise in sleep, a sleep medicine physician, a public health sleep research expert) and developed to reflect the day-to-day functional impact of OSA. Questions were worded to be easily understood by patients and reflect real-world clinical discussions about OSA. Responses were formatted to be either categorical or on a Likert scale and provided specific recall periods where relevant (either the past 7 or 30 days). Sampling methodology was established a priori to ensure minimum quotas for representation across gender, age, race, and employment status. Survey data were assessed for missingness and quality issues, which were found to be minimal due to the survey’s internal quality control and inclusion criteria for representativeness. The use of survey data was found to be exempt from requiring Institutional Review Board (IRB) approval due to the deidentified nature of the dataset.
Study variables
Variables in the analysis included participants’ age, gender, body-mass index (BMI, kg/m2) category, race, region, employment/unemployment status, income level, OSA severity, comorbidities, and time since diagnosis with OSA. Patient-reported impact of work activities (if employed) and impact on non-work activities were also captured. Patients were defined as agreeing that OSA affected their work or non-work activities if they reported a 3 or higher on a 5-point Likert scale. In addition, the study analyzed OSA symptoms in the past 30 days, including daytime sleepiness, fatigue, irritability, mood changes, loud snoring, morning headaches, and inability to concentrate or focus. Patients were defined as experiencing at least 2 OSA symptoms in the past 30 days if they reported 2 or more symptoms from the 7 options. Moreover, the analysis also examined negative impacts of OSA on one’s relationship and OSA-induced negative feelings, including hopeless, depressed, frustrated, misunderstood, anxious, irritable, angry, not dependable, isolated/alone, ashamed, embarrassed, scared, low self-esteem, and others.
Statistical analysis
Descriptive statistics were summarized for all variables of interest, including demographic, clinical, and psychosocial characteristics; summaries were presented for the overall cohort and by gender. Tests of significance were conducted to compare characteristics across genders; chi-square tests were used for categorical variables, and t-tests and Mann-Whitney U tests were used for continuous variables.
To assess the association between patient characteristics and outcomes of interest, we estimated four generalized linear models (GLMs) with binomial distribution and logit link function. The first three models were performed on the full survey cohort and assessed the impact of gender on the following outcomes: (1) whether OSA affected work productivity, (2) whether OSA affected patients’ ability to engage in regular, non-work activities, and (3) whether patients experienced ≥ 2 OSA symptoms in the past 30 days. Beyond gender, these models controlled for age group, BMI category, race, region, income level, comorbidities, OSA severity, and time since diagnosis.
The fourth model, a GLM with binomial distribution and logit link function, also had the outcome of whether OSA affected work activities (defined as a reported 3 or higher on a 5-point Likert scale of agreement) but was performed on only participants reporting full- or part-time employment. Categories considered “not employed” included unemployed, retired, disabled, homemaker, student, and other. The primary covariates of interest in this model were the number of symptoms and number of negative feelings associated with OSA, each included as count variables. The model was adjusted for age group, gender, OSA severity, BMI category, race, region, income, comorbidities, and an indicator of OSA treatment use. All analyses were performed using RStudio (Posit team, 2025) in conjunction with R statistical software.
Results
Sample characteristics
Among 1,500 adult respondents, 755 (50.3%) were men and 745 (49.7%) were women, with mean ages 50.7 (SD 14.5) and 41.2 (14.4) years, respectively. Women reported a higher average BMI of 31.0 (SD 12.4) than men (mean 29.5, SD 9.9, p = 0.011). (Table 1) Approximately 62% of the total sample reported they were employed, with 71% of respondents reporting income of less than $100,000 per year. Among all respondents, 13% reported mild, 54% moderate, and 30% severe OSA; women were more highly represented than men in mild and moderate groups (11.1% vs. 14.5% in mild, 48.2% vs. 59.5% in moderate, for men vs. women, respectively) while men had a higher proportion in the severe group (37.4% vs. 22.6% for men vs. women, respectively). Most respondents in both genders reported currently being on treatment (93.6% vs. 93.8% for men vs. women, respectively).
Table 1.
Patient population demographic and clinical characteristics by gender
| Total | Gender | ||||||
|---|---|---|---|---|---|---|---|
| Male | Female | p-value | |||||
| Number of participants (N, % of Total in Row) | 1500 (100.0%) | 755 (50.3%) | 745 (49.7%) | ||||
| Age, years | |||||||
| Mean (SD) | 46.0 | (15.2) | 50.7 | (14.5) | 41.2 | (14.4) | 0.000 |
| Median (IQR) | 43.0 | (35.0–57.0) | 47.0 | (40.0–64.0) | 38.0 | (30.0–51.0) | |
| Body Mass Index (BMI), kg/m2 | |||||||
| Mean (SD) | 30.3 | (11.2) | 29.5 | (9.91) | 31.0 | (12.4) | 0.011 |
| Median (IQR) | 29.3 | (23.5–36.5) | 28.7 | (23.5–34.9) | 30.0 | (23.5–37.8) | |
| Race (N, %) | |||||||
| White | 1132 | (75.5%) | 550 | (72.8%) | 582 | (78.1%) | 0.021 |
| Black/African American | 278 | (18.5%) | 136 | (18.0%) | 142 | (19.1%) | 0.649 |
| American Indian | 43 | (2.9%) | 20 | (2.6%) | 23 | (3.1%) | 0.724 |
| Alaska Native | 26 | (1.7%) | 26 | (3.4%) | 0 | (0%) | 0.000 |
| Native Hawaiian | 3 | (0.2%) | 1 | (0.1%) | 2 | (0.3%) | 0.622 |
| Other Pacific Island | 4 | (0.3%) | 1 | (0.1%) | 3 | (0.4%) | 0.371 |
| Asian | 37 | (2.5%) | 23 | (3.0%) | 14 | (1.9%) | 0.197 |
| Other | 45 | (3.0%) | 23 | (3.0%) | 22 | (3.0%) | 1.000 |
| Prefer not to answer | 1 | (0.1%) | 0 | (0%) | 1 | (0.1%) | 0.497 |
| Region (N, %) | |||||||
| Northeast | 255 | (17.0%) | 129 | (17.1%) | 126 | (16.9%) | 0.003 |
| Midwest | 311 | (20.7%) | 142 | (18.8%) | 169 | (22.7%) | |
| South | 676 | (45.1%) | 328 | (43.4%) | 348 | (46.7%) | |
| West | 258 | (17.2%) | 156 | (20.7%) | 102 | (13.7%) | |
| Employment/Unemployment Status (N, %) | |||||||
| Employed | 934 | (62.3%) | 485 | (64.2%) | 449 | (60.3%) | 0.102 |
| Unemployed | 565 | (37.7%) | 269 | (35.6%) | 296 | (39.7%) | |
| Income (N, %) | |||||||
| Less than $24,999 | 247 | (16.5%) | 86 | (11.4%) | 161 | (21.6%) | 0.000 |
| $25,000 - $49,999 | 364 | (24.3%) | 137 | (18.1%) | 227 | (30.5%) | |
| $50,000 - $99,999 | 463 | (30.9%) | 254 | (33.6%) | 209 | (28.1%) | |
| $100,000 - $149,999 | 228 | (15.2%) | 151 | (20.0%) | 77 | (10.3%) | |
| $150,000 - $199,999 | 115 | (7.7%) | 80 | (10.6%) | 35 | (4.7%) | |
| $200,000 or more | 83 | (5.5%) | 47 | (6.2%) | 36 | (4.8%) | |
| OSA Severity (N, %) | |||||||
| Mild | 192 | (12.8%) | 84 | (11.1%) | 108 | (14.5%) | 0.000 |
| Moderate | 807 | (53.8%) | 364 | (48.2%) | 443 | (59.5%) | |
| Severe | 450 | (30.0%) | 282 | (37.4%) | 168 | (22.6%) | |
| Don’t know | 51 | (3.4%) | 25 | (3.3%) | 26 | (3.5%) | |
| Comorbidities* (N, %) | |||||||
| Chronic obstructive pulmonary disease (COPD) | 289 | (19.3%) | 151 | (20.0%) | 138 | (18.5%) | 0.510 |
| Diabetes (Type I or II) | 504 | (33.6%) | 291 | (38.5%) | 213 | (28.6%) | 0.000 |
| Heart disease | 236 | (15.7%) | 139 | (18.4%) | 97 | (13.0%) | 0.005 |
| Attention-deficit/hyperactivity disorder (ADHD) or Attention-deficit disorder (ADD) | 352 | (23.5%) | 145 | (19.2%) | 207 | (27.8%) | 0.000 |
| Anxiety | 807 | (53.8%) | 326 | (43.2%) | 481 | (64.6%) | 0.000 |
| Asthma | 428 | (28.5%) | 173 | (22.9%) | 255 | (34.2%) | 0.000 |
| Depression | 725 | (48.3%) | 274 | (36.3%) | 451 | (60.5%) | 0.000 |
| Heart failure/Congestive Heart Failure (CHF) or Atrial Fibrillation (Afib) | 182 | (12.1%) | 119 | (15.8%) | 63 | (8.5%) | 0.000 |
| Hypertension/high blood pressure | 655 | (43.7%) | 364 | (48.2%) | 291 | (39.1%) | 0.000 |
| Insomnia | 513 | (34.2%) | 226 | (29.9%) | 287 | (38.5%) | 0.001 |
| Other | 87 | (5.8%) | 37 | (4.9%) | 50 | (6.7%) | 0.165 |
| No comorbidities besides OSA | 162 | (10.8%) | 106 | (14.0%) | 56 | (7.5%) | 0.000 |
| Time Since Diagnosis with OSA (N, %) | |||||||
| Less than 1 year ago | 236 | (15.7%) | 96 | (12.7%) | 140 | (18.8%) | 0.000 |
| 1–5 years ago | 765 | (51.0%) | 344 | (45.6%) | 421 | (56.5%) | |
| 6–10 years ago | 261 | (17.4%) | 162 | (21.5%) | 99 | (13.3%) | |
| More than 10 years ago | 238 | (15.9%) | 153 | (20.3%) | 85 | (11.4%) | |
Abbreviations: IQR – interquartile range; OSA – obstructive sleep apnea; SD – standard deviation
Notes: “%” denotes percentage of total participants in column total unless otherwise noted. *Indicates levels are not mutually exclusive
P-values that are ≤ 0.05 are bolded and in green to highlight potential significance at the 0.05 level. T-test was used for comparison between continuous variables, and Chi-square/Fisher’s Exact tests were used for comparison between categorical variables
Anxiety, depression, and hypertension were the most frequently reported comorbid conditions overall. Men were more likely than women to report cardiovascular and metabolic comorbidities, such as diabetes (38.5% vs. 28.6%, p < 0.001 for men vs. women, respectively), heart disease (18.4% vs. 13.0%, p = 0.005), chronic heart failure or atrial fibrillation (15.8% vs. 8.5%, p < 0.001), and hypertension (48.2% vs. 39.1%, p < 0.001). Women were more likely than men to report psychological comorbidities, such as anxiety (43.2% vs. 64.6%, p < 0.001 for men vs. women, respectively), depression (36.3% vs. 60.5%, p < 0.001), ADHD/ADD (19.2% vs. 27.8%, p < 0.001), and insomnia (29.9% vs. 38.5%, p = 0.001).
Employed survey participants were slightly younger than the overall cohort (mean age 41.2, SD 11.5), with similar gender composition (51.9% male) and lower average BMI (mean 28.2, SD 10.9). Three-quarters of total respondents reported that OSA negatively impacted their work productivity moderately to extremely, with women reporting impact on work productivity at a higher percentage than men (78.8% vs. 71.8%, respectively, p = 0.043). (Table 2) A total of 901 patients (60.1%) reported OSA limiting their ability to do regular, daily, non-work activities; women reported this at higher frequency than men (66.7% vs. 53.5%, women vs. men, p < 0.001).
Table 2.
Patient population psychosocial question responses by gender
| Total | Gender | p-value | |||||
|---|---|---|---|---|---|---|---|
| Male | Female | ||||||
| Number of participants (N, % of Total in Row) | 1500 (100.0%) | 755 (50.3%) | 745 (49.7%) | ||||
| Impact on Work Activities | |||||||
| Number of employed participants (N, % of Total in Row) | 934 (100.0%) | 485 (51.9%) | 449 (48.1%) | ||||
|
If Employed (N = 934), how much did your OSA/symptoms affect your work productivity (binary; No = “not at all/slightly,” Yes = “moderately/quite a bit/extremely”) (N, %) | |||||||
| No | 232 | (24.8%) | 137 | (28.2%) | 95 | (21.2%) | 0.043 |
| Yes | 702 | (75.2%) | 348 | (71.8%) | 354 | (78.8%) | |
| Impact on Daily (Non-Work) Activities | |||||||
|
How much does OSA limit your ability to do regular, daily, non-work activities (binary; No = “not at all/slightly,” Yes = “moderately/quite a bit/extremely”) (N, %) | |||||||
| No | 527 | (35.1%) | 316 | (41.9%) | 211 | (28.3%) | 0.000 |
| Yes | 901 | (60.1%) | 404 | (53.5%) | 497 | (66.7%) | |
| OSA Symptoms | |||||||
| OSA Symptoms in past 30 days* (N, %) | |||||||
| Daytime sleepiness | 1068 | (71.2%) | 498 | (66.0%) | 570 | (76.5%) | 0.000 |
| Fatigue | 1112 | (74.1%) | 531 | (70.3%) | 581 | (78.0%) | 0.001 |
| Irritability | 729 | (48.6%) | 314 | (41.6%) | 415 | (55.7%) | 0.000 |
| Mood changes | 708 | (47.2%) | 302 | (40.0%) | 406 | (54.5%) | 0.000 |
| Loud snoring | 792 | (52.8%) | 396 | (52.5%) | 396 | (53.2%) | 0.825 |
| Morning headaches | 690 | (46.0%) | 279 | (37.0%) | 411 | (55.2%) | 0.000 |
| Inability to concentrate or focus | 703 | (46.9%) | 307 | (40.7%) | 396 | (53.2%) | 0.000 |
| Other | 14 | (0.9%) | 5 | (0.7%) | 9 | (1.2%) | 0.406 |
| No symptoms from OSA in past 30 days | 87 | (5.8%) | 66 | (8.7%) | 21 | (2.8%) | 0.000 |
| OSA Negatively Impacting Relationships | |||||||
| Participant agreed the following for Relationships (Scale 1–5 Disagree, 6–7 Agree) * (N, %) | |||||||
| Living with OSA negatively impacts my relationships with my family and friends | 515 | (34.3%) | 238 | (31.5%) | 277 | (37.2%) | 0.024 |
| Having OSA has negatively impacted my current or past relationship with a significant other/spouse | 499 | (33.3%) | 259 | (34.3%) | 240 | (32.2%) | 0.421 |
| Can’t care for my family or friends the way I’d like to, because of my OSA | 429 | (28.6%) | 192 | (25.4%) | 237 | (31.8%) | 0.007 |
| The exhaustion I experience from OSA affects my ability to be present for my loved ones | 626 | (41.7%) | 280 | (37.1%) | 346 | (46.4%) | 0.000 |
| At times, my OSA has caused me to be less socially engaged | 651 | (43.4%) | 294 | (38.9%) | 357 | (47.9%) | 0.001 |
| Negative Feelings | |||||||
| Feelings Living with OSA* (N, %) | |||||||
| Hopeless | 437 | (29.1%) | 175 | (23.2%) | 262 | (35.2%) | 0.000 |
| Depressed | 691 | (46.1%) | 303 | (40.1%) | 388 | (52.1%) | 0.000 |
| Frustrated | 795 | (53.0%) | 350 | (46.4%) | 445 | (59.7%) | 0.000 |
| Misunderstood | 368 | (24.5%) | 134 | (17.7%) | 234 | (31.4%) | 0.000 |
| Anxious | 577 | (38.5%) | 215 | (28.5%) | 362 | (48.6%) | 0.000 |
| Irritable | 718 | (47.9%) | 310 | (41.1%) | 408 | (54.8%) | 0.000 |
| Angry | 354 | (23.6%) | 165 | (21.9%) | 189 | (25.4%) | 0.123 |
| Not dependable | 305 | (20.3%) | 119 | (15.8%) | 186 | (25.0%) | 0.000 |
| Isolated/alone | 458 | (30.5%) | 192 | (25.4%) | 266 | (35.7%) | 0.000 |
| Ashamed | 332 | (22.1%) | 137 | (18.1%) | 195 | (26.2%) | 0.000 |
| Embarrassed | 450 | (30.0%) | 180 | (23.8%) | 270 | (36.2%) | 0.000 |
| Scared | 245 | (16.3%) | 96 | (12.7%) | 149 | (20.0%) | 0.000 |
| Low self-esteem | 449 | (29.9%) | 164 | (21.7%) | 285 | (38.3%) | 0.000 |
| No negative emotions | 204 | (13.6%) | 146 | (19.3%) | 58 | (7.8%) | 0.000 |
| Other | 21 | (1.4%) | 11 | (1.5%) | 10 | (1.3%) | 1.000 |
Abbreviations: OSA – obstructive sleep apnea
Notes: “%” denotes percentage of total participants in column total unless otherwise noted. *Indicates levels are not mutually exclusive
P-values that are ≤ 0.05 are bolded to highlight potential significance at the 0.05 level. T-test was used for comparison between continuous variables, and Chi-square/Fisher’s Exact tests were used for comparison between categorical variables
When asked about OSA negatively impacting relationships, women agreed with the statement significantly more than men for 4 out of the 5 questions. (Table 2) Women were also significantly more likely than men to agree that living with OSA causes negative feelings for 12 out of 13 listed emotions. Of the seven OSA symptoms in the survey, daytime sleepiness (71.2%) and fatigue (74.1%) were the most prevalent, with other symptoms affecting 46%−53% of participants. In unadjusted analysis, all symptoms beyond loud snoring were significantly more prevalent in women than in men (p ≤ 0.001).
Multivariate regression
Adjusted models: Whether OSA affected work productivity
Among all survey participants, women were 28% more likely to have OSA affect work activities, although this did not reach statistical significance (95% CI [0.87, 1.89], p = 0.21) (Fig. 1). Patients with moderate and severe disease, as compared to those with mild disease, were 2.38 (95% CI [1.46, 3.87]) and 4.05 (95% CI [2.26, 7.23]) times more likely to have OSA affect work activities (p < 0.01). Among the employed participants, (Fig. 2) the likelihood of work being impacted by OSA increased 1.40 times (95% CI [1.24, 1.59], p < 0.01) for each additional reported OSA symptom and 1.13 times (95% CI [1.05, 1.22], p < 0.01) for each additional reported negative feeling.
Fig. 1.
Associations Between Patient Characteristics and OSA’s Impact on Work Activities, OSA’s Impact on Non-Work Activities, and Having ≥ 2 Symptoms of OSA
Abbreviations: CI - Confidence Interval; ref - reference group. Notes: Patients reported OSA affects work activities (Yes/No) is based on the following question: [If employed, how much did your OSA/symptoms affect your work productivity? (binary; No = “not at all/slightly,” Yes = “moderately/quite a bit/extremely”).] Patients reported OSA affects daily (non-work) activities (Yes/No) is based on the following question: [How much does OSA limit your ability to do regular, daily, non-work activities? (binary; No = “not at all/slightly,” Yes = “moderately/quite a bit/extremely”).] OSA symptoms options include the following: daytime sleepiness, fatigue, irritability, mood changes, loud snoring, morning headaches, inability to concentrate or focus, and other symptoms
Fig. 2.
Among Employed Respondents (N = 934), Associations Between Self-Reported Work Productivity and Patient Characteristics
Abbreviations: CI - Confidence Interval; ref- reference group Notes: Patients reported OSA affects work activities (Yes/No) is based on the following question: [If employed, how much did your OSA/symptoms affect your work productivity? (binary; No = “not at all/slightly,” Yes = “moderately/quite a bit/extremely”).]*OSA symptoms options include the following: daytime sleepiness, fatigue, irritability, mood changes, loud snoring, morning headaches, inability to concentrate or focus, and other symptoms. ^Negative feelings options include the following: hopeless, depressed, frustrated, misunderstood, anxious, irritable, angry, not dependable, isolated/alone, ashamed, embarrassed, scared, low self-esteem, and other feelings
-
2)
Adjusted model: Whether OSA affected patients’ ability to engage in regular, non-work activities
Women had a 46% higher likelihood of reporting OSA affecting their daily activities (p = 0.01). (Fig. 1) Other significant factors contributing to OSA impacting daily activities included having moderate to severe disease (p < 0.01), being aged 55 years or older (p = 0.01), living in the south (p = 0.02), and having been diagnosed more than 1 year ago (p = 0.01). Comorbidities significantly affecting daily life included COPD (p < 0.01), diabetes (p = 0.03), and hypertension (p = 0.01).
-
3)
Adjusted model: Whether patients experienced ≥ 2 OSA symptoms in the past 30 days
Women were 52% more likely to experience at least 2 OSA symptoms (p = 0.04). (Fig. 1) Other variables significantly associated with ≥ 2 symptoms in adjusted analysis included moderate severity level, being aged 65 or older, and several comorbidities (COPD, anxiety, depression, and insomnia).
Discussion
This study presents findings from the SHINE survey, the largest patient-reported outcomes investigation conducted to date among individuals diagnosed with obstructive sleep apnea (OSA). The primary aim was to assess gender-specific differences in the impact of OSA on symptom burden, work-related and non-work activities, interpersonal relationships, and emotional well-being. In unadjusted analyses, women reported a broader and more severe symptom profile, particularly in psychological, cognitive, and fatigue-related domains. By contrast, men more frequently demonstrated a physiological and cardiovascular comorbidity profile and tended to report fewer subjective symptoms. Adjusted analyses indicated that gender differences were most pronounced in limitations in daily activities and in emotional burden, whereas no significant gender differences were observed for work productivity impairment after adjustment.
People with OSA generally exhibit lower job efficiency, reduced capacity to perform certain tasks, and greater absenteeism [19]. In the 2016 U.S. National Health and Wellness Survey, individuals with OSA and excessive sleepiness reported significantly higher levels of overall work impairment compared to those without OSA, with no significant gender differences on these outcomes [20]. Our findings similarly indicate that gender was not a significant predictor of self-reported impact on work productivity; however, greater symptom burden and negative feelings were strongly associated with patients reporting OSA impact on work productivity. Supporting these results, a Finnish cohort study found that both women and men who were later diagnosed with OSA had an elevated risk of lost workdays, independent of comorbidities. Importantly, this excess risk was evident up to five years prior to diagnosis in women but only one year prior in men [21], suggesting that delayed diagnosis and treatment may disproportionately affect women’s productivity.
Although limited research has addressed this topic, our model identified gender as a significant predictor of OSA-related limitations in daily non-work activities, with women 46% more likely to report such impairments. This may reflect traditional gender roles in which women carry a greater share of unpaid domestic labor. OSA prevalence also increases markedly after menopause, peaking around age 65, suggesting that symptoms often emerge near retirement [22]. In our data, moderate and severe OSA were the strongest predictors of functional non-work impairment. Participants diagnosed more than one year earlier were less likely to report such limitations, potentially reflecting adaptation or treatment benefits, although residual emotional distress persisted in some patients.
Our findings on gender differences in OSA symptom presentation align with prior studies. In our cohort, men were more likely to report no symptoms, which may indicate a lower symptom burden or underreporting due to differences in illness perception or stigma. Consistent with this, a 2018 U.S. registry analysis found that women reported fatigue (OR = 0.57, p = 0.001) and morning headaches (OR = 0.32, p < 0.001) at significantly higher rates than men [23, 24]. More broadly, women more frequently present with non-classic, systemic symptoms—such as fatigue, mood disturbances, and cognitive difficulties—that often fall outside traditional diagnostic criteria [25]. These differences underscore the need for screening tools that incorporate a broader symptom profile or adopt sex-aware diagnostic frameworks to improve detection of OSA in women [26]. Likewise, treatment protocols should address gender-specific symptom patterns and social impacts of OSA. Enhanced screening and targeted interventions for women have the potential to substantially improve quality of life, reduce downstream complications, and generate meaningful cost savings for the health system [27].
Considerable evidence indicates that OSA symptoms negatively affect partners’ sleep; however, little is known about how individuals with OSA perceive the broader impact of their condition on personal and social relationships [28]. In one study conducted in Turkey, women reported significantly poorer quality of life than men in the domain of social relationships, as measured by the WHOQOL-Bref questionnaire [29]. Consistent with this, our findings showed that women were more likely than men to report that OSA adversely affected their relationships, particularly those outside of romantic partnerships. This pattern may reflect gendered expectations surrounding community engagement and caregiving, which could heighten women’s perception of OSA as interfering with both work and personal life. Further research is warranted to explore how OSA treatments influence the mental and social well-being across genders in the United States.
A key strength of this study is its foundation in the SHINE survey, which captured the experiences of a large and diverse patient population in the United States, including groups that are often underrepresented in clinical research. Cross-sectional study designs such as surveys are often necessary first steps for hypothesis generation in novel research areas, such as the psychosocial burden of OSA by gender. The use of self-reported outcomes is both a strength, allowing for insight into the lived experiences of patients, and a limitation, as responses could not be externally validated. Specifically, the survey design did not allow for confirmation of OSA diagnosis by a healthcare professional, nor the confirmation of OSA severity via sleep test results, which could potentially result in patient misclassification. Another limitation of the survey design was the absence of a power analysis to determine the sample size, and the absence of a non-OSA control group. Future research should seek to explore the findings of this pragmatic survey in research paradigms with objective validation.
Conclusion
OSA’s impact extends well beyond sleep, influencing how individuals feel, connect with others, and function in daily life. These effects differ by gender, with women reporting distinct symptoms and a greater impact on their personal and emotional well-being. Our study reinforces what is known about gender differences in patient-reported outcomes, showing that women experience a higher psychosocial burden and more severe lived experience, even after adjusting for baseline characteristics. These findings point to potential shortcomings in current screening tools, diagnostic criteria, and treatment protocols, which may not fully capture or address the experiences of female patients. To advance the quality of care, OSA screening protocols and clinical guidelines should incorporate gender-sensitive approaches, ensuring more precise diagnosis and individualized management for both women and men.
Supplementary Information
Below is the link to the electronic supplementary material.
(PDF 271 KB)
Acknowledgements
We thank Kate Schneider for her contribution to the data collection of the SHINE survey.
Abbreviations
- AHI
Apnea-hypopnea index
- ASAP
Alliance of Sleep Apnea Partners
- BMI
Body Mass Index
- CI
Confidence Interval
- COPD
Chronic Obstructive Pulmonary Disease
- GLM
Generalized linear models
- IRB
Institutional Review Board
- OR
Odds Ratio
- OSA
Obstructive sleep apnea
- SHINE
Sleep Health Inquiries on Needs and Emotions
- US
United States
- WHOQOL
Bref-World Health Organization Quality of Life-Brief
Authors’ contributions
All authors contributed substantially to the conception, drafting, and final approval of this manuscript.
Funding
No funding.
Data availability
The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study uses deidentified survey data collected with patient informed consent and received IRB exemption.
Consent for publication
All authors have reviewed and approved the final manuscript and provide their consent for its publication.
Competing interests
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Institution where work was performed
Statistical analysis was performed by Curta, Inc.
Clinical trial registration
NA.
Ethics of investigation
This study uses deidentified survey data collected with patient informed consent and received IRB exemption.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
(PDF 271 KB)
Data Availability Statement
The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.