OSA is characterized by the complete or partial collapse of the upper airway for at least 10 s during sleep, leading to complete cessation (apnea) or decreased airflow (hypoventilation). Excessive daytime drowsiness is a prominent symptom of OSA (1, 2). Epidemiological data indicate that OSA affects approximately 17% of females and 34% of males aged 30 to 70 in the United States (3). Without any treatment in time, OSA will result in serious health complications such as cardiovascular diseases (4, 5), hypertension (6) and diabetes mellitus (DM) (7). Therefore, identifying precise and novel biomarkers for the early detection of OSA is crucial.

OSA is widely recognized as a significant complication correlated with obesity (8). Obesity is typified by the accumulation of visceral adipose tissues (VAT). Conventional metrics, such as body mass index (BMI), can only provide a general assessment on obesity and fail to distinguish visceral from subcutaneous fat. In recent developments, Bello-Chavolla et al. (9) introduced a novel visceral adiposity score, termed METS-VF, which is markedly superior to traditional obesity indexes in estimating VAT. METS-VF, encompassing variables such as WHtR, BMI, HDL-C, FPG, TG, gender, and age, can offer a comprehensive assessment on VAT and its metabolic implications, which can not only evaluate the glycolipid metabolism and distribution of body fat, but also incorporate gender and age-specific variations in VAT. Recent research has highlighted the superiority of METS-VF compared to traditional obesity indexes in predicting and assessing the risk of metabolic diseases, such as hyperuricemia, hypertension, DM, and chronic kidney dysfunction (CKD) (10–14). To date, however, no published studies have explored the correlation between METS-VF and the prevalence of OSA.

In this study, the data from the NHANES database were analyzed to explore the correlation between METS-VF and the prevalence of OSA in a nationally representative sample.

This cross-sectional study encompassing 8,284 representative adults identified a notable positive correlation between METS-VF and the probability of having OSA. This correlation was particularly pronounced among subjects who were female, younger and Mexican Americans. Notably, linear correlation was identified between OSA and METS-VF, without threshold effects.

METS-VF, a novel estimator of VAT recently developed by Bello Chavolla OY et al. (9) has been meticulously developed and validated, as documented in prior literature. Due to the computational simplicity and high accuracy of METS-VF in predicting visceral obesity, increasing researchers have explored and validated its superior efficacy in assessing and predicting the risk of having the diseases correlated with visceral obesity. In the study, Yu et al. demonstrated that METS-VF can exhibit a robust predictive capacity for CKD compared to other markers of central adiposity (10). Additionally, compared to other obesity evaluation indexes, METS-VF can exhibit both applicability and reliability as a predictor of DM and hypertension within Chinese population (11, 12). A study involving 36,876 subjects identified a positive correlation between asthma and METS-VF (20). For non-obese females, METS-VF has been proven to be beneficial in guiding the management and prevention of hyperuricemia (13). Numerous studies have corroborated the strong correlation between these diseases and OSA (21–23). These findings provide indirect evidence of the robust diagnostic capability of METS-VF for identifying OSA. This study revealed a significant linear positive correlation between METS-VF and the probability of having OSA in a nationally representative sample for the first time.

The correlation between OSA and obesity is characterized by a complex interdependence (8). Notably, obesity, particularly the accumulation of excess abdominal fat, is a major risk factor for the exacerbation and development of OSA. Abdominal obesity can not only elevate intra-abdominal pressure and reduce lung volume, thereby heightening the risk of upper airway collapse (24), but it is also correlated with an increase in visceral fat, secreting various inflammatory and adipose-derived factors, leading to oxidative stress and systemic inflammation. These processes affect muscle activities in the upper respiratory tract, promote the proliferation of adipose tissues around the upper respiratory tract, and thus increase the risk of having OSA (25, 26). In addition, irregular sleep patterns and frequent awakenings correlated with OSA can disrupt hormonal regulation, leading to increased hunger and a preference for high-calorie foods (27–29). Additionally, evidence indicates that OSA can alter the lipid profile (30), which can exacerbate lipid abnormalities by enhancing inflammatory responses. And OSA itself can exacerbate lipid abnormalities by increasing IR and inflammatory responses, thereby creating a negative feedback loop (31, 32). Furthermore, aging is correlated with the accumulation of senescent adipocytes in adipose tissues, leading to disruptions in lipid metabolism, glucose metabolism, immune regulation and endocrine function, within adipose tissues (33, 34). METS-VF can incorporate the aforementioned parameters (WHtR, age, lipid profile, and insulin resistance) to evaluate the metabolic status of visceral fat, which may can partially indicate the risk of having OSA.

Subgroup analyses in this study have uncovered a novel finding that elevated METS-VF was significantly correlated with an increased prevalence of OSA in individuals under 50 years old. This increased risk may be correlated with age-related physiological and metabolic changes, including alterations in lipid distribution and related metabolic markers (35, 36). Older adults are more prone to have hypertension, cardiovascular diseases, and DM, which can affect both metabolic indexes and sleep quality, which may consequently attenuate the correlation between METS-VF and OSA. Notably, Hai Deng et al. (8) have elucidated this phenomenon by proposing that the divergent effects of adipose tissue distribution in older adults may account for this discrepancy. Furthermore, it was identified that gender influences the correlation between METS-VF and OSA. Females typically exhibit a higher proportion of body fat compared to males and experience a reduction in estrogen levels after menopause, which may increase the risk of having OSA during menopause (37, 38).

This study carries important implications for clinical practice, particularly given the increasing annual prevalence of cardiovascular and cerebrovascular diseases correlated with OSA (39). OSA has emerged as a notable health issue impacting public well-being. Nevertheless, the diagnosis of OSA is frequently a lengthy, resource-intensive, and costly process for patients. Therefore, there is a pressing clinical necessity to pinpoint a convenient and effective diagnostic approach for OSA. METS-VF, a cost-efficient and readily measurable metric, satisfactorily fulfills these clinical needs. The results of this study provide important insights for healthcare professionals in efficiently evaluating the risk of having OSA in patients.

The study’s primary strength is its distinction as the first cross-sectional analysis to explore the correlation between METS-VF and OSA, supported by a sufficiently large and representative sample size. However, it is crucial to acknowledge the limitations inherent in this study. Firstly, the establishment of a causal relationship between METS-VF and OSA was not feasible through cross-sectional studies. As discussed above, a bidirectional relationship may exist. Secondly, its reliance on data solely from US adults, which may impede the generalizability of the results to other populations. Thirdly, there are numerous potential influencing factors for OSA and METS-VF. Although as many relevant covariates as possible have been incorporated into the models, it is still challenging to completely exclude the influence of other potential covariates, such as diet and genetic factors. Fourthly, in this study, the risk of having OSA was assessed through three questions, which suggests a high risk of having OSA rather than a confirmed diagnosis, and also lead to recall bias. Ideally, diagnosing OSA requires overnight polysomnography or polygraphy. Future research should incorporate prospective cohort studies and richer datasets to overcome these limitations and should also aim at uncovering the underlying mechanisms linking these conditions.

This study revealed a notable correlation between elevated METS-VF and OSA. METS-VF can function as an independent predictor of OSA, aiding in early detection and diagnosis to mitigate the risks correlated with the conditions.