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The Relationship between the Indoor Environmental Quality and Obstructive Sleep Apnea
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Received: ,
Accepted: ,
How to cite this article: Khan W, Badri HM, Banah OA, Bushara MO, Alzhrani AM, Shah M. The Relationship between the Indoor Environmental Quality and Obstructive Sleep Apnea. Glob J Med Pharm Biomed Update. 2026;21;15. doi: 10.25259/GJMPBU_21_2026
Abstract
Objectives:
Obstructive sleep apnea (OSA) is a common sleep disorder that can increase the risk of cardiovascular, metabolic, and neurocognitive diseases. Recent evidence suggests that indoor environmental quality (IEQ), such as air quality, thermal comfort, ventilation, noise, humidity, and odors, may increase the risk of OSA; however, more studies are needed to better understand this relationship.
Material and Methods:
The current study conducted a cross-sectional survey of 451 adults aged at least 18 years and living in Saudi Arabia. OSA risk was assessed using the Berlin Questionnaire, and the indoor environment quality was assessed using the Environmental-Quality Satisfaction. Multivariable logistic regression, adjusted for age, sex, and body mass index, identified independent IEQ predictors of high-risk OSA.
Results:
High-risk individuals reported significantly lower satisfaction with daytime temperature, noise, lighting, and ventilation, as well as smaller room and window dimensions and more frequent unpleasant odors (all p < 0.001). Internal bedroom noise was the most common disturbance in high-risk participants (>60%). Logistic models revealed that each one-unit increase in daytime comfort (temperature, noise, lighting), room-size satisfaction, and ventilation reduced the odds of high-risk OSA by 21–29%, whereas each unit increase in odor frequency increased the odds by 31%.
Conclusion:
Poor IEQ is strongly associated with elevated OSA risk. Interventions targeting ventilation, thermal regulation, noise reduction, and odor control may be used for OSA prevention and management inside houses.
Keywords
Environment
Indoor environmental quality
Public health
Sleep apnea
INTRODUCTION
Obstructive sleep apnea (OSA) is one of the most common yet underrecognized sleep disorders in modern medicine. The condition is characterized by repeated airway collapse during sleep, triggering a series of oxygen desaturation and sleep discontinuity events. A recent study stated that approximately 1 in 7 adults worldwide meet diagnostic criteria for OSA.[1] To detect the severity of OSA, the apnea–hypopnea index can be used.[1] OSA can increase the risk of other diseases such as cardiovascular, metabolic, neurological diseases and concerning associations with both occupational hazards and reduced life expectancy.[1] In addition, OSA is one of the most important contributors to the onset of hypertension and diabetes with a clear and a well-known pathophysiological pathway.[1] OSA is a serious medical condition that can increase the risk of many other chronic diseases, thus, studying all possible risk factors for OSA must be a priority for public health personnel.
Indoor environmental quality (IEQ) refers to the quality of the indoor surroundings, including air quality, thermal comfort, lighting (visual comfort), and acoustics (noise levels). A healthy IEQ can improve quality of life and reduce stress, according to a recent report.[2] A sleep environment is shaped by these environmental components in residential settings where people spend a long time of their lives, especially in bedrooms during sleep. It is possible to influence sleep health by assessing each factor of IEQ: Air quality is concerned with pollutant levels and freshness of the air, thermal comfort is concerned with ambient temperature and humidity, lighting is concerned with natural and artificial light, and acoustics is concerned with sound levels. Poor IEQ conditions may disturb sleep and worsen sleep disorders such as OSA.[2]
OSA can be influenced by indoor air pollutants and inadequate ventilation. Sleep becomes more fragmented with high levels of carbon dioxide (CO2) due to poor ventilation in the bedroom. Better ventilation, which lowers CO2, subjectively and objectively improves sleep quality.[3,4] For instance, people who sleep with windows open to reduce CO2 and stuffiness experience less awakenings and better sleep efficiency.[4] In addition to OSA discomfort, certain indoor air pollutants may pose a greater risk. A recent study from South Korea highlighted an association between formaldehyde exposure and increased OSA risk.[5] Moreover, fine particulate matter (PM) 2.5 and other traffic-related air pollutants are known to worsen OSA.[3] Pollutants, especially if trapped indoor, can worsen OSA.
Another important IEQ factor affecting sleep and potentially OSA is thermal comfort. The temperature of the surroundings has a significant impact on sleep. Conditions that are too hot or cold might disrupt the natural architecture of sleep and induce micro-arousals. Significantly, current extensive data have connected elevated ambient temperatures to heightened severity of OSA. Lechat et al. (2025) showed that the likelihood of an individual suffering OSA was 45% greater on nights with extremely high outdoor temperatures (upper 99th percentile ~27°C vs. more temperate ~6°C).[1] According to this investigation, which followed over 116,000 individuals, heat can significantly exacerbate OSA breathing episodes, most likely by decreasing total sleep depth and raising susceptibility to apneic episodes. It is believed that warmer indoor bedroom temperatures have comparable effects by disrupting the thermoregulatory systems that promote sound sleep. Thermal stress, particularly heat, fragments sleep and may increase the amount of time spent in lighter sleep stages, which are more likely to cause apneas and hypopneas. These results are consistent with larger evidence that having an appropriately cold, comfortable bedroom (around 18–21°C for most individuals) is advantageous for uninterrupted sleep, even if the association between bedroom thermal environment and OSA in home settings is still being studied. The relationship between the thermal environment and OSA is becoming a more significant area of academic interest as nighttime temperatures rise due to climate change.[1]
Lighting and acoustics in the bedroom may interact with sleep health. Light exposure during the night or during usual sleep times may negatively impact circadian rhythm and sleep quality. Exposure to light at night, especially artificial light that comes from screens or lighting, can disrupt melatonin release and increase alertness, which leads to difficulties in both sleep initiation and continuity.[3] Findings from a recent experimental study support this, as even moderate exposure to artificial lights during sleep can impact sleep quality and increase sleep fragmentation.[3] Exposure to light may not cause OSA, but poorer sleep conditions, including quality, due to light exposure may impact and worsen the consequences of OSA by increasing sleep fragmentation.
Noise is also known to be a common cause of interrupted sleep. Environmental noise can result in lighter sleep, more frequent micro-arousals, and even the activation of the sympathetic nervous system while you sleep.[3] This includes noise from airplanes, traffic, and noisy neighbors. These sleep architecture disruptions are similar to those observed in intrinsic sleep disorders. Indeed, prolonged nighttime noise exposure frequently causes drowsiness and deficits the following day that are comparable to those of untreated OSA.[6] While noise exposure does not directly trigger OSA episodes, it can worsen the overall sleep disturbance. Higher levels of noise, especially at night, may cause more fragmentation by waking an OSA patient after apnea-induced arousals, impacting their sleep quality.
Current literature needs more investigations, especially on all IEQ factors and their combined effect, not focusing on a single factor. Many studies focused on a single parameter, without accounting for the combined effect of a typical home environment.[4] Studying multiple factors can better reflect real-life living conditions and identify which environmental modifications would be most effective for improving sleep and reducing OSA severity. Given the high prevalence of OSA and its serious health impacts, even a simple contribution of modifiable IEQ factors could have significant public health implications. Improving IEQ may introduce a new preventative measure for OSA, but more evidence to support this claim is needed. Therefore, this study aims to investigate and assess the indoor residential environment (IEQ) and its effect on OSA.
MATERIAL AND METHODS
Design
This cross-sectional study used an electronic survey that was conducted between March 01, and April 30, 2025 to assess whether the indoor environment predicts the likelihood of OSA among participants. The questionnaire was administered online through Microsoft Forms and ethical approval was taken from Umm Al-Qura University Ethical Committee (approval number: CCBE150321). Electronic informed consent was obtained from all participants before the beginning of the survey. This investigation formed part of a larger population-based project, with eligibility criteria stipulating that respondents be aged 18 years or older and current residents of Saudi Arabia. Of the individuals who accessed the survey, 451 completed all required items and were included in the final analytic sample.
Measures
Demographic information, including age, sex, body mass index [BMI], region (state), employment status, and household size, was self-reported by participants. OSA risk was evaluated by Berlin Questionnaire where scoring was done using standard guidelines.[7] Environmental Quality Satisfaction (EQS) was measured using a validated tool, assessing comfort with temperature, noise, lighting, ventilation, satisfaction with room and window dimensions, frequency of unpleasant odors, excess humidity, and excess dryness. In addition, two categorical items identified the primary source of noise during the day and at night (outside window, adjacent room, inside room, corridor, none).[8]
Statistical Analysis
Analyses were done in JASP software, Macintosh version. Descriptive statistics were computed for OSA risk and all EQS variables. Point-biserial correlations (Pearson r) quantified bivariate associations between the dichotomous OSA variable (0 = low, 1 = high) and the 13 continuous EQS items. Chi-square tests of independence examined differences in OSA prevalence across daytime and nighttime noise categories; Cramer’s V indexed effect size. Multivariable logistic regression predicted high-risk OSA from the continuous EQS items, adjusting for age, sex, and BMI. Odds ratios (OR) with 95 % confidence intervals (CI) are reported.
RESULTS
Table 1 shows the demographic characteristics of study participants (n = 451). The mean age was (34.29 ± 15.10 years), and the mean household residents was (6.48 ± 3.70). The average BMI of respondents was (27.31 ± 8.45), and slightly more males (51.0%, n = 230) responded to the survey. Most participants were from the Makkah region (n = 366, 81.2%), and about 166 participants (36.8%) were students, 145 (32.2%) were employed, and 58 (12.9%).
| Characteristic | n | M±SD/n (%) |
|---|---|---|
| Continuous variables | ||
| Age (years) | 451 | 34.29±15.10 |
| BMI (kg m-2) | 441 | 27.31±8.45 |
| Household residents (no.) | 451 | 6.48±3.70 |
| Sex | ||
| Male | 230 | 51.0 |
| Female | 221 | 49.0 |
| Region of residence | ||
| Makkah | 366 | 81.2 |
| Asir | 23 | 5.1 |
| Eastern Province | 20 | 4.4 |
| Riyadh | 16 | 3.5 |
| Other regionsa | 26 | 5.8 |
| Employment status | ||
| Student | 166 | 36.8 |
| Employed | 145 | 32.2 |
| Retired | 58 | 12.9 |
| Unemployed | 36 | 8.0 |
| Homemaker | 36 | 8.0 |
| Self-employed | 10 | 2.2 |
aIncludes Al Bahah, Madinah, Qassim, Najran, Jazan, and Tabuk, M: Mean: SD: Standard deviation, BMI: Body mass index
Participants at high risk for OSA reported significantly lower comfort with daytime temperature (p < 0.001) and nighttime temperature (p = 0.019), less comfort with daytime noise (p < 0.001) and nighttime noise (p = 0.011), reduced daytime lighting comfort (p = 0.001), and lower satisfaction with room size (p = 0.001), window size (p = 0.007), and window view (p = 0.017). They also noted more frequent unpleasant odors (p = 0.001), excess humidity (p = 0.001), and excess dryness (p = 0.004), as well as lower satisfaction with ventilation (p < 0.001) [Table 2].
| EQS variable | Low-risk OSA (M±SD) | High-risk OSA (M±SD) | t | p-value | d |
|---|---|---|---|---|---|
| Comfort—temperature (day) | 3.82±0.90 | 3.50±0.95 | 3.66 | <0.001 | 0.35 |
| Comfort—temperature (night) | 4.11±0.80 | 3.92±0.88 | 2.35 | 0.019 | 0.23 |
| Comfort—noise (day) | 3.57±0.97 | 3.18±1.06 | 3.77 | <0.001 | 0.37 |
| Comfort—noise (night) | 3.33±1.05 | 3.06±1.15 | 2.54 | 0.011 | 0.25 |
| Comfort—lighting (day) | 3.82±1.02 | 3.50±1.09 | 3.29 | 0.001 | 0.31 |
| Comfort—lighting (night) | 4.04±0.93 | 3.86±1.02 | 1.94 | 0.053 | 0.19 |
| Satisfaction—room size | 4.08±0.96 | 3.74±1.05 | 3.48 | 0.001 | 0.33 |
| Satisfaction—window size | 3.80±1.10 | 3.50±1.18 | 2.73 | 0.007 | 0.26 |
| Satisfaction—window view | 3.10±1.31 | 2.80±1.34 | 2.40 | 0.017 | 0.23 |
| Frequency—unpleasant odors | 2.44±0.93 | 2.76±1.03 | −3.40 | 0.001 | 0.32 |
| Frequency—excess humidity | 2.30±0.83 | 2.58±0.90 | −3.26 | 0.001 | 0.31 |
| Frequency—excess dryness | 2.35±0.92 | 2.61±0.97 | −2.86 | 0.004 | 0.27 |
| Satisfaction—ventilation | 3.82±0.90 | 3.45±0.98 | 4.15 | <0.001 | 0.39 |
p < 0.05 indicates statistical significance. M: Mean: SD: Standard deviation, EQS: Environmental quality satisfaction, OSA: Obstructive sleep apnea
Table 3 shows the daytime noise sources reported by study participants for both low- and high-risk OSA. The majority of high OSA risk reported noise inside the room (59.3%), followed by the adjacent room (49.2%) and the corridor (39.5%). Noise from outside the window was reported by 89 of 264 high OSA risk (33.7%), whereas 14 of 59 high OSA risk participants (23.7%) indicated no daytime noise disturbance.
| Day-time noise source | Low-risk, n | High-risk, n | High-risk, % |
|---|---|---|---|
| Outside window | 175 | 89 | 33.7 |
| Adjacent room | 32 | 31 | 49.2 |
| None | 45 | 14 | 23.7 |
| Corridor | 23 | 15 | 39.5 |
| Inside room | 11 | 16 | 59.3 |
OSA: Obstructive sleep apnea
Table 4 shows the nighttime noise sources reported by study participants for both low- and high-risk OSA. The majority of high OSA risk reported noise came from inside the room (62.2%), followed by the adjacent room (48.7%). Noise from outside the window was reported by 71 of 225 high OSA risk participants (31.6%), while 19 of 78 high OSA risk participants (24.4%) reported no nighttime noise disturbance. Corridor noise was the least common source, affecting 9 of 33 high OSA risk participants (27.3%).
| Night-time noise source | Low-risk, n | High-risk, n | High-risk, % |
|---|---|---|---|
| Outside window | 154 | 71 | 31.6 |
| Adjacent room | 40 | 38 | 48.7 |
| None | 59 | 19 | 24.4 |
| Inside room | 14 | 23 | 62.2 |
| Corridor | 24 | 9 | 27.3 |
OSA: Obstructive sleep apnea
In a multivariable logistic regression adjusting for age, sex, and BMI, several EQS items were independently associated with high OSA risk. Each one-unit increase in daytime temperature comfort was associated with 24% lower odds of high-risk OSA (OR = 0.76, 95% CI [0.62, 0.93], p = 0.007), and each one-unit increase in daytime noise comfort corresponded to 29% lower odds (OR = 0.71, 95% CI [0.58, 0.87], p = 0.001). Greater daytime lighting comfort also reduced odds by 21% per unit (OR = 0.79, 95% CI [0.64, 0.97], p = 0.024), and each unit increase in room-size satisfaction decreased odds by 26% (OR = 0.74, 95% CI [0.60, 0.92], p = 0.006). Conversely, each one-unit increase in the frequency of unpleasant odors was associated with 31% higher odds of high-risk OSA (OR = 1.31, 95% CI [1.07, 1.60], p = 0.008). Finally, better ventilation satisfaction was linked to 22% lower odds per unit (OR = 0.78, 95% CI [0.63, 0.97], p = 0.025) [Table 5].
| Predictor (1-unit ↑) | OR | 95% CI | p-value |
|---|---|---|---|
| Comfort—temperature (day) | 0.76 | 0.62–0.93 | 0.007 |
| Comfort—noise (day) | 0.71 | 0.58–0.87 | 0.001 |
| Comfort—lighting (day) | 0.79 | 0.64–0.97 | 0.024 |
| Satisfaction—room size | 0.74 | 0.60–0.92 | 0.006 |
| Frequency—unpleasant odors | 1.31 | 1.07–1.60 | 0.008 |
| Satisfaction—ventilation | 0.78 | 0.63–0.97 | 0.025 |
p < 0.05 indicates statistical significance. Model: c2 (16)=70.4, p < 0.001, Hosmer–Lemeshow p = 0.59. OR: Odds ratio, CI: Confidence interval, OSA: Obstructive sleep apnea
DISCUSSION
The present findings indicate that dissatisfaction with multiple IEQ parameters is significantly associated with higher OSA risk. Participants at high OSA risk reported poorer comfort with temperature, noise, and lighting, as well as smaller room sizes, worse ventilation, and more frequent unpleasant odors. These associations suggest that a poor bedroom environment may contribute or worsen any current sleep disorders, particularly OSA. For instance, poor thermal conditions may promote sleep fragmentation and worsen apnea episodes; a recent study found that nights with higher ambient temperatures carried a 45% greater likelihood of OSA events compared to cooler nights.[1] Likewise, those at high OSA risk in our study were far more likely to report noise disturbances originating inside the bedroom. Internal noise may cause repeated arousals which may increase sleep fragmentation that is already existing in OSA. Lighting comfort was lower in the high-risk group, which indirectly may worsen OSA by disrupting circadian rhythms and sleep continuity. Finally, the strong associations of poor ventilation and frequent odors with OSA risk reveal a potential role of indoor air quality on irritation of the airway or reduce sleep depth, promoting more apnea episodes. Our results support a conceptual model in which multiple dimensions of the bedroom environment including thermal, acoustic, lighting, spatial, and air quality collectively influence OSA susceptibility.
Poor IEQ may impact sleep, particularly OSA. Recent studies have demonstrated that poor bedroom conditions can impair sleep quality [Table 6]. A recent study reported a dose-dependent relationship between houses with high PM, CO2, noise, and temperature levels and poor sleep quality.[9] This aligns with our findings that perceived poor air quality, noise, and thermal discomfort are linked to worse sleep (higher OSA risk). Our findings about ventilation and odors also aligned with previous research on indoor pollutants and sleep apnea. A nationally representative Korean study found that higher concentrations of formaldehyde inside bedrooms were associated with increased OSA risk in men (approximately 2% higher odds per unit increase in formaldehyde).[5] Similarly, exposure to other indoor volatile organic compounds has been linked to greater odds of moderate-to-severe OSA.[10] These convergent findings reinforce the idea that polluted or stale indoor air can aggravate airway inflammation and sleep-disordered breathing. Our data also emphasize the role of noise: while environmental noise has long been known to fragment sleep, recent evidence confirms that even modest nocturnal noise can reduce sleep efficiency by around 5%.[9] This sleep disruption may be worse with OSA, as apneic patients are especially vulnerable to arousals. Research on lighting and OSA is limited, however, our finding of lower lighting comfort in high-risk individuals is consistent with broader literature showing that light at night impairs sleep continuity.[3] Overall, our study fits within a growing body of evidence that poor IEQ ranging from poor air quality to thermal stress and noise, adversely affects sleep and may increase the risk or severity of OSA.
| Country | Study | IEQ factor(s) | Key finding |
|---|---|---|---|
| Saudi Arabia | Current study | Temperature, noise, lighting, ventilation, odor, humidity | Each 1-unit increase in daytime comfort reduced high-risk OSA odds by 21–29%; odor frequency increased odds by 31% |
| South Korea | Kim et al. (2025)[5] | Indoor formaldehyde | Higher formaldehyde associated with increased OSA risk in men |
| USA | Basner et al. (2023)[9] | PM2.5, CO2, temperature, humidity, noise | Dose-dependent relationship between IEQ parameters and poor sleep |
| Australia | Lechat et al. (2025)[1] | Ambient temperature | 45% greater OSA likelihood on extreme heat nights |
IEQ: Indoor environmental quality, OSA: Obstructive sleep apnea
Key IEQ such as noise, temperature, and air quality emerge as important contributors to OSA in this study. Nearly two-thirds of high-risk participants identified indoor noise as a disturbance, more than outdoor noise. This suggests that household noise (e.g., televisions, mobile devices, appliances, or other occupants) may be more disruptive to sleep than outdoor noise in our population. Nocturnal noise triggers micro-arousals and the sympathetic nervous system, which in someone with OSA can prolong light sleep and increase apnea frequency.[9] Reducing bedroom noise, through behavioral changes or insulation, may reduce OSA-related sleep fragmentation. Thermal dissatisfaction in the bedroom was linked to higher OSA risk in our study. A previous study found that more apnea episodes were noticed among OSA patients during warmer temperatures.[1] Maintaining a comfortably cool bedroom may be beneficial for OSA patients. In addition, our results indicated that indoor air quality is an important factor for OSA patients. High OSA-risk participants reported poor ventilation and frequent bad odors. Previous studies found a possible relationship between OSA and indoor pollutants, particularly formaldehyde and volatile organic compound.[5,10] In summary, minimizing noise, improving thermal comfort, and air purification/ ventilation emerge as possible factors in the indoor environment to help reduce OSA risk [Figure 1].

Despite the strengths of this study, several limitations must be acknowledged. Causality cannot be detected, as we used self-reported subjective measures for IEQ and OSA risk, and we also used a cross-sectional design. Existing research comparing subjective and objective bedroom assessments found that many people habituate to chronic environmental stresses and report their environment as acceptable even when objective measurements show poor levels.[9] This suggests that our study might have underestimated the true impact of some factors, such as noise or CO2 as they were measured subjectively. Furthermore, it is unclear if poor IEQ impacts the severity of OSA, or if high OSA risk participants happen to experience more environmental discomfort. Different designs such as cohorts and/or randomized trials would be better in detecting causality and confirming that better IEQ could lead to reduced OSA severity. Our sample was drawn mostly from one region (Makkah province), which may limit generalizability to other climates or housing conditions. These limitations underscore the need for future research using objective IEQ measurements (e.g., continuous noise or air quality monitoring) and clinical sleep assessments to validate and extend our findings.
Current results highlight the possible value of integrative environmental interventions for OSA. Modern public health approaches to control or manage OSA should consider the patient’s immediate living environment as a modifiable risk factor. The complex associations reported suggest that a combination of interventions may be effective for controlling OSA severity. A comprehensive indoor or house assessment for OSA patients is needed, offering tailored improvements like reducing ambient light at night, dehumidifying if excess humidity is an issue, or adding room insulation to minimize noise. By addressing multiple IEQ components together, there is potential for synergistic benefits on sleep: a quiet, cool, clean-air bedroom will facilitate deeper, less fragmented sleep, thereby possibly lowering the burden of OSA. Our findings therefore support the inclusion of indoor environment optimization in public health initiatives and clinical management plans for sleep apnea. Occupant behavior, such as keeping windows closed during sleep, using electronic devices in bed, and setting air conditioning at suboptimal temperatures, may mediate the relationship between IEQ conditions and OSA risk. Future interventions should target both environmental modifications and occupant awareness to optimize the sleep environment.
CONCLUSION
This study shows that poor IEQ factors such as temperature, high noise levels, inadequate lighting, poor ventilation, and exposure to odors/pollutants are significantly associated with increased risk of OSA. These findings suggest that OSA or OSA severity may be affected negatively by the spaces in which people live and sleep. The management of OSA or OSA severity induced or affected by poor IEQ could be done through environmental intervention; optimizing ventilation, noise reduction, thermal regulation, and odor control. These aspects may serve as modifiable factors for reducing OSA risk.
Ethical approval:
The research/study was approved by the Institutional Review Board at Umm Al-Qura University, number CCBE150321, dated 9th November, 2024.
Declaration of patient consent:
The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given consent for clinical information to be reported in the journal. The patient understands that the patient’s names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Conflicts of interest:
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation:
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.
Financial support and sponsorship: Nil.
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