Background Obstructive sleep apnea (OSA) is the most prevalent sleep-related breathing disorder, affecting a significant number of individuals globally.It is associated with poor quality of life and an increased risk of all-cause mortality. It is estimated that most of the patients suffering from OSA are obese. Anthropometric indices can help guide doctors towardthe diagnosis. Objectives This study aimed to establish specific anthropometric thresholds associated with OSA risk, allowing clinicians to identify individuals more likely to have OSA and who may need further evaluation, such as polysomnography. This targeted screening approach would enable better resource allocation to those at higher risk, potentially enhancing the efficiency of OSA diagnosis and management. Methods We conducted a descriptive study using data from the sole private sleep clinic in Mauritius. We analyzed case files of consecutive patients diagnosed with OSA over a 3.5-year period from January 2015 to June 2018. Results The study population comprised 170 patients (79.4% males) diagnosed with OSA by a polygraphy test.The mean age of OSA diagnosis in men and women was 51.7 ± 14.0 years and 53.8 ± 12.5 years, respectively.The mean neck circumference (NC) for males and females was 41.9 ± 3.9 cm and 38.2 ± 3.9 cm, while the mean waist circumference (WC) was 105.6 ± 12.2 cm for men and 103.4 ± 14.5 cm for women. The body mass index (BMI) was 29.1± 5.0 kg/m2 and 31.4± 6.8 kg/m2 for males and females, respectively. The apnea-hypopnea index (AHI) averaged to 42.1 ± 19.7 events/hour for men and 33.3 ± 16.4 events/hour for women.In male patients, we found a positive significant correlation (p<0.001) between AHI and the following parameters: BMI (r=0.443), WC(r=0.337), WC-to-height ratio (WHr) (r=0.378), NC(r =0.274), and neck-to-height ratio (NHr) (r =0.321).In women, we observed a positive significant correlation between apnea severity and the following: BMI (r=0.396, p=0.029), WC (r=0.462, p=0.005), and WHr (r=0.494, p=0.003).No significant relationships were observed between AHI and the following parameters in women: NC (r=0.317, p=0.064) and NHr (r=0.311, p=0.069). A total of 83.5% of patients had a Mallampati score of 3-4. Conclusion This study represents a pioneering effort on the island. While further research is necessary to establish exact anthropometric cutoff values, the findings offer crucial insights for physicians to identify high-risk individuals. With just a scale, measuring tape, and calculator, healthcare professionals can detect important health markers that extend beyond diagnosing OSA. These simple measurements not only help in predicting OSA but also provide a broader view of an individual's overall health, identifying risks that go beyond sleep issues. This research sets an important foundation for future OSA studies within the Mauritian population.
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