Age-specific markers of adiposity in patients with obstructive sleep apnea

Evaluating Anthropometric Indices for Malnutrition Assessment in Older Adults: Scoping Review

Purpose of Review

The demographic transition in both global and national populations indicates a growing trend in the older population. This burgeoning older population brings about constraints marked by the effective presence of malnutrition alongside functional and physiological changes. Conducting screenings and assessments to prevent malnutrition and enable early intervention is crucial. In epidemiological and clinical studies, these screenings and assessments are often conducted through anthropometric measurements and a range of indices derived from them, encompassing both traditional ones like BMI (Body Mass Index) and newer ones like BRI (Body Roundness Index), BAI (Body Adiposity Index), ABSI (A Body Shape Index), CI (Conicity Index), WWI (Waist adjusted Weight Index), AVI (Abdominal Volume Index), Demiquet, and Mindeks. There is a lack of scrutiny regarding studies comparing these indices based on the type of malnutrition in the older population, hence this review aims to address the gap in the literature.

Recent Findings

Analysis of existing research reveals that BRI and waist-to-height ratio serve as predictors of obesity-related body fat quantity/distribution and metabolic risks, while WWI stands out in sarcopenic obesity, and Demiquet and Mindeks are prominent indices for screening inadequate nutrition.

Summary

Choosing anthropometric indices that do not include height in the older populations can have certain advantages. However, the selection of these indices should depend on the specific variable being assessed or screened such as obesity, malnutrition, or sarcopenic obesity.

Association of Craniofacial Skeletal and Soft Tissue Characteristics With Severe Obstructive Sleep Apnea in Age-specific and BMI-specific Patient Groups

PURPOSE

To identify the key craniofacial anatomic characteristics associated with the prevalence of severe obstructive sleep apnea (OSA) in patient cohorts stratified by age and body mass index (BMI).

METHODS

This prospective study was conducted at the Beijing Anzhen Hospital Center for Sleep Medicine and Science between December 2023 and March 2024. Patients suspected of having OSA underwent overnight polysomnography, along with computed tomography scans of the head and neck, to evaluate the skeletal and soft tissue characteristics. Multivariable analysis was conducted to explore the independent risk factors associated with the prevalence of severe OSA (apnea hypopnea index ≥30 events/h) after adjusting for age, sex, BMI, and neck circumference.

RESULTS

Among the 118 participants, 75 (63.6%) were diagnosed with severe OSA. Skeletal variables, such as vertical airway length, and soft tissue-related variables, like soft palate length, were independently correlated with the prevalence of severe OSA. Furthermore, subgroup analysis revealed that all skeletal variables and a few soft tissue parameters were associated with severe OSA in patients aged older than 40 years, whereas only a specific soft tissue variable was independently associated with the occurrence of severe OSA in those aged younger than or equal to 40 years. In addition, certain soft tissue-related variables were notably associated with severe OSA in obese patients (BMI >28 kg/m2), whereas only specific skeletal variables were acted independent risk factors for severe OSA in non-obese patients (BMI ≤28 kg/m2).

CONCLUSION

Craniofacial skeletal and soft tissue features play essential roles in the prevalence of severe OSA, with variations observed based on age and BMI.

Effect of Weight Loss on the Apnea Hypopnea Index is Related to Waist Circumference in Chinese Adults with Overweight and Obesity

Purpose

The present study aimed to evaluate the efficiency of traditional anthropometric and body composition parameters in predicting apnea hypopnea index (AHI) change after weight loss.

Patients and Methods

Chinese adults with overweight and obesity were included into this study containing two parts. A cross-sectional study was conducted in 137 individuals using the baseline data from two weight loss intervention trials. The second part was the weight-loss intervention study conducted in 60 overweight and obese patients with obstructive sleep apnea (OSA). All participants underwent physical examination, bioelectrical impedance analysis and overnight polysomnography. Multivariate linear regression models were used to identify the most accurate parameters to predict AHI and the mediation analysis to evaluate the mediators between weight loss and AHI reduction.

Results

Waist circumference (WC), body mass index and fat mass were positively associated with AHI after adjusting multiple collinearities in the cross-sectional study. After weight-loss intervention, body weight decreased from 94.6 ± 15.3 to 88.0 ± 13.9 kg, and AHI decreased from 41.9 (13.0,66.9) to 20.7 (8.7,51.2) events/h. Among these parameters, only percentage changes in WC and AHI across the intervention were positively intercorrelated after controlling for covariates (adjusted r = 0.271, P = 0.041). The mediation analysis supported WC as a mediator between weight loss and AHI reduction (standardized indirect effect [95% CI] = 4.272[0.936,7.999]).

Conclusion

Both general and abdominal obesity are of high prognostic value for OSA. WC as an easily accessible parameter mediates the effects of weight loss in decreasing OSA severity.

The Cervical Fat Tissue Volume is a Predictor for Moderate to Severe OSA

Objective  Obstructive sleep apnea (OSA) is a disorder characterized by recurrent pharyngeal obstruction during sleep, in which upper airway anatomy plays a key role in its pathogenesis. The aim of this study was to describe whether the quantification of cervical fat tissue volume (CFTV) obtained by Computed Tomography (CT)cephalometry is related to the severity of OSA. Methods  Retrospective study between 2018 and 2020 in those patients > 18 years old, with diagnosis of OSA who performed a volumetric cephalometric imaging. Three-dimensional reconstruction of the images was performed and CFTV was measured. Results  91 patients were included in this study of which: without OSA (n: 7), mild (n: 19), moderate (n: 39) and severe OSA (n: 26). We observed a progressive increase of CFTV related to OSA severity has been observed (without OSA: 58.9 ml (47.9-87.5), mild: 59.1ml (48.4-78.3), moderate: 71 ml (42.6-127.1) and severe OSA 103.6 ml (81-153); p < 0.01); nevertheless, no differences were found in the airway volume and neck area. It was showed a significant correlation between CFTV and OSA indicators: AHI, ODI and T90 (Sp r: 0.48; 0.38 and 0.36; p < 0.01 respectively). CFTV cut-off value to discriminate AHI >15 ev/h with best sensitivity-specificity relationship was 64.1 ml with an area under the curve of 0.6 ± 0.06. Multivariate analysis showed that CFTV is a predictor for moderate to severe OSA (OR:3.05, IC95%: 1.14-8.17). Conclusion  Cervical fat quantification by CT cephalometry correlates with OSA severity in adults. Fat volume > 64.1 ml increased more than three times the risk of OSA moderate to severe.

Association of Hypertriglyceridemic Waist Phenotype with Obstructive Sleep Apnea: A Cross-Sectional Study

OBJECTIVE

Hypertriglyceridemic waist (HTGW) phenotype is an independent risk factor for metabolic disorders. Although obstructive sleep apnea (OSA) is associated with metabolic disorders, it is unclear whether there is an association between HTGW phenotype and OSA.

METHODS

We enrolled consecutive participants presenting to a sleep center in Shanghai, China. Full-night polysomnography was performed, and serum triglyceride (TG) levels and waist circumference (WC) were calculated. HTGW phenotype was defined as increased WC (men > 90 cm, women > 80 cm) and elevated TG levels (> 1.7 mmol/L). Participants were classified into four groups: normal TG with normal WC (NTNW); normal TG with increased WC (NTGW); elevated TG with normal WC (HTNW); and elevated TG with enlarged WC, namely HTGW. The relationships between HTGW phenotypes and OSA were assessed using binary (apnea hypopnea index, [AHI]≥5/hr) and multinomial logistic regression analyses (clinical AHI severity categories).

RESULTS

We included 3190 participants in this cross-sectional study. Compared to the NTNW phenotype, participants with NTGW and HTGW phenotypes had the significantly higher risk of OSA (AHI ≥5/hr, odds ratio [OR] = 2.51, 95% confidence interval [CI] = 1.91-3.31; OR = 3.76, 95% CI = 2.67-5.31, respectively), after adjustment for confounders. In subgroup analyses categorised by age, sex, and BMI, the aforementioned associations remained significant. The association between the NTGW, HTGW phenotype and OSA risk remained significant across the OSA severity groups. Multinomial logistic regression also revealed that the mild (OR = 1.63, 95% CI = 1.07-2.50), moderate (OR = 1.875, 95% CI = 1.22-2.88), and severe OSA (OR = 3.18, 95% CI = 2.14-4.73) were associated with HTGW phenotype.

CONCLUSION

Both NTGW and HTGW phenotype were positively associated with OSA risk in all subgroups. Further longitudinal follow-up studies are needed to determine the causal link and prognostic role of these metabolic factors.