European Journal of Cardiovascular Medicine

Obstructive Sleep Apnea (OSA) is a prevalent sleep-related breathing disorder characterized by repeated episodes of upper airway obstruction during sleep, leading to intermittent hypoxia, arousals, and disrupted sleep architecture. It has emerged as a significant public health concern due to its established links with cardiovascular morbidity, metabolic dysfunction, neurocognitive decline, and increased all-cause mortality. ¹˒²

Obesity is one of the most important modifiable risk factors for OSA. The accumulation of adipose tissue in the neck and upper airway, along with altered chest wall mechanics in obese individuals, significantly contributes to pharyngeal airway narrowing and collapsibility during sleep.³ The risk of OSA rises progressively with increasing BMI, and nearly 70% of individuals with OSA are either overweight or obese.⁴ Despite the high burden of obesity-associated OSA, the condition frequently remains underdiagnosed, especially in individuals presenting with vague symptoms such as fatigue, poor concentration, and excessive daytime sleepiness.⁵

In developing countries like India, the rising trend in obesity, coupled with limited awareness about sleep disorders, exacerbates the diagnostic gap. Studies from similar healthcare settings have highlighted that early recognition of OSA among obese individuals is vital for preventing long-term complications. ³˒⁶ Effective screening and targeted interventions such as lifestyle modification, weight loss, and continuous positive airway pressure (CPAP) therapy—can significantly reduce the clinical and economic burden of OSA.²˒⁴

This study was undertaken to estimate the prevalence of OSA and evaluate the associated demographic and clinical risk factors among obese adults attending a tertiary care hospital. The findings aim to enhance awareness, guide screening strategies, and inform clinical decision-making in obesity-related sleep disorders.

Study Design and Setting:
This was a cross-sectional, observational study conducted at the Government General and Chest Hospital, Hyderabad, a tertiary care referral center for respiratory and sleep disorders.

Study Period:
The study was carried out over a period of twelve months, from February 2024 to January 2025.

Study Population:
The study included 100 adult patients aged 18 to 65 years with body mass index (BMI) ≥30 kg/m², who attended the outpatient or inpatient departments of the hospital during the study period. Patients were enrolled after obtaining written informed consent.

Inclusion Criteria:

• Adults aged 18–65 years.
• BMI ≥30 kg/m² (obese individuals).
• Willingness to undergo overnight polysomnography and participate in the study.

Exclusion Criteria:

• Known cases of central sleep apnea or other non-obstructive sleep disorders.
• Unstable cardiorespiratory or neurological conditions.
• Use of sedatives or alcohol within the past 24 hours.
• Previous diagnosis or treatment for OSA.

Data Collection:
Demographic data, medical history, anthropometric measurements (height, weight, BMI, neck circumference), and lifestyle factors (smoking status) were recorded. Each participant completed the Epworth Sleepiness Scale (ESS) to assess daytime sleepiness.

Polysomnography:
All participants underwent overnight attended Level I polysomnography in the hospital's sleep lab. Obstructive Sleep Apnea was diagnosed based on Apnea-Hypopnea Index (AHI) ≥5 events/hour, and its severity was classified as:

Mild: AHI 5–14

Moderate: AHI 15–29

Severe: AHI ≥30

Statistical Analysis:
Data were entered into Microsoft Excel and analyzed using SPSS version 25. Continuous variables were expressed as mean ± standard deviation, and categorical variables as frequencies and percentages. Chi-square test and independent t-test were used to assess associations between risk factors and OSA. A p-value <0.05 was considered statistically significant.

A total of 100 obese adults were included in the present study to determine the prevalence and associated risk factors of Obstructive Sleep Apnea (OSA). The mean age of participants was 44.2 ± 10.5 years, and the majority were female (62%). The overall prevalence of OSA among the study population was 56%.

Prevalence by Obesity Class

The prevalence of OSA increased progressively with higher classes of obesity. Among individuals with Class I obesity (BMI 30–34.9), OSA was detected in 44.2%. This increased to 60.0% in Class II (BMI 35–39.9) and 83.3% in Class III obesity (BMI ≥40), indicating a statistically significant association between obesity severity and OSA prevalence (Table 1).

Table 1: Prevalence of OSA by Obesity Class (n = 100)

Risk Factors Associated with OSA

Key clinical and demographic risk factors were compared between participants with and without OSA. Male gender (50.0% vs 22.7%, p = 0.004), neck circumference >40 cm (66.1% vs 27.3%, p < 0.001), hypertension (51.8% vs 29.5%, p = 0.020), daytime sleepiness (Epworth Sleepiness Scale score >10) (73.2% vs 20.5%, p < 0.001), and smoking history (26.8% vs 11.4%, p = 0.045) were all significantly associated with the presence of OSA (Table 2).

Table 2: Risk Factors Associated with OSA

Severity of OSA

Among the 56 participants diagnosed with OSA, 22 (39.3%) had mild OSA, 21 (37.5%) had moderate OSA, and 13 (23.2%) had severe OSA based on Apnea-Hypopnea Index (AHI) scores (Table 3). The distribution demonstrates that a substantial proportion of cases fall into moderate to severe categories, warranting clinical attention.

Table 3: Severity of OSA (Among Diagnosed Patients, n = 56)

Figure 1. Severity of OSA (Among Diagnosed Patients

Sleepiness Scores

Epworth Sleepiness Scale (ESS) scores were significantly higher in participants with OSA (mean ESS = 13.4 ± 2.9) compared to those without OSA (mean ESS = 7.1 ± 2.1), with the difference being statistically significant (p < 0.001) (Table 4).

Table 4: Epworth Sleepiness Scale (ESS) Scores

Figure 2. Epworth Sleepiness Scale (ESS) Scores

The present study demonstrated a high prevalence of Obstructive Sleep Apnea (OSA) among obese adults, with 56% of participants meeting diagnostic criteria based on the Apnea-Hypopnea Index (AHI). This is consistent with existing literature, which highlights obesity as a major contributing factor to OSA, particularly in populations with elevated body mass index (BMI) and central fat distribution.⁷˒⁸

Our findings reveal a progressive increase in OSA prevalence with the severity of obesity. Among Class III obese individuals (BMI ≥40 kg/m²), the prevalence was 83.3%, compared to 60.0% in Class II and 44.2% in Class I. This gradient supports previous studies suggesting a linear relationship between increasing BMI and upper airway obstruction due to adipose tissue deposition in the pharyngeal and parapharyngeal areas.⁹˒¹⁰

Several clinical and demographic risk factors showed significant association with OSA in our study. Male gender, neck circumference >40 cm, hypertension, smoking, and excessive daytime sleepiness (ESS >10) were more common in those with OSA. These findings align with prior studies highlighting the roles of anatomical differences, cardiovascular comorbidities, and behavioral risk factors in the pathophysiology of OSA.⁸˒¹¹˒¹²

The severity distribution in our cohort showed that over 60% of OSA patients had moderate to severe disease, underscoring the importance of early detection and management. Additionally, the mean Epworth Sleepiness Scale (ESS) score was significantly higher in the OSA group (13.4 ± 2.9) compared to the non-OSA group (7.1 ± 2.1), suggesting a substantial impact on daily functioning.

These findings reinforce the need for routine screening of OSA among obese adults, especially those with additional risk factors. In resource-constrained settings, tools such as the ESS can aid in preliminary risk stratification and identify patients who would benefit from polysomnographic evaluation.⁷˒¹³ Early diagnosis and timely intervention can reduce the long-term complications of OSA, including cardiovascular events, metabolic syndrome, and reduced quality of life.¹²˒¹³

Limitations:
This study was limited by its single-center design and relatively small sample size. Additionally, other potential contributors to OSA, such as craniofacial abnormalities or alcohol use, were not comprehensively evaluated.

Implications:
Early identification of OSA among obese patients can reduce the burden of related complications such as cardiovascular disease, poor glycemic control in diabetics, and neurocognitive decline. Integrating OSA screening into obesity management protocols could enhance long-term outcomes.

This study highlights the high prevalence of Obstructive Sleep Apnea (OSA) among obese adults, with over half of the participants being affected, and severity increasing with higher BMI classes. Significant risk factors associated with OSA included male gender, increased neck circumference, hypertension, smoking, and excessive daytime sleepiness. A substantial proportion of cases were moderate to severe in intensity, emphasizing the need for timely identification and intervention. Routine screening for OSA in obese individuals using clinical parameters and tools like the Epworth Sleepiness Scale can aid early diagnosis. Integration of sleep evaluation into obesity management is essential to prevent long-term complications and improve patient outcomes.

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