Clinical usefulness of the body muscle-to-fat ratio for screening obstructive sleep apnea syndrome in patients with inadequately controlled type 2 diabetes mellitus

Kurinami, Noboru; Sugiyama, Seigo; Ijima, Hiroko; Yoshida, Akira; Hieshima, Kunio; Miyamoto, Fumio; Kajiwara, Keizo; Jinnouch, Katsunori; Jinnouchi, Tomio; Jinnouchi, Hideaki

doi:10.1016/j.diabres.2018.07.008

Cited by 7 publications

(4 citation statements)

References 29 publications

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“… 45 Furthermore, a study examining body composition using bioelectrical impedance analysis in OSA patients with Type 2 Diabetes (DM) showed that the muscle-to-fat ratio could be helpful in screening for OSA in patients with poorly controlled diabetes. 46 This suggests that the muscle-to-fat ratio is likely related to the OSA severity in this population. Although an increase in head and neck fluid volume leads to an increase in neck circumference, and AHI is significantly correlated with changes in neck circumference, it is not directly associated with changes in head and neck fluid volume, and fluid transfer accumulation in the head and neck is not related to OSA.…”

Section: Influence Of Body Composition On Sleep (Physical and Biologi...mentioning

confidence: 89%

Impact of Body Composition on Sleep and Its Relationship with Sleep Disorders: Current Insights

Kawasaki¹,

Kitamura²,

Kasai³

2023

NSS

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Sleep is involved in many physiological processes and is essential for both physical and mental health. Obesity and sleep deprivation due to sleep disorders are major public health issues. Their incidence is increasing, and they have a wide range of adverse health-related consequences, including life-threatening cardiovascular disease. The impact of sleep on obesity and body composition is well-known, and many studies have shown an association between insufficient or excessive sleep duration and obesity, body fat percentage, and weight gain. However, there is growing evidence of the effects of body composition on sleep and sleep disorders (particularly sleep disordered breathing) through anatomical and physiological mechanisms (nocturnal fluid shift, core body temperature, or diet). Although some research has been conducted on the bidirectional effects of sleep-disordered breathing and body composition, the specific effects of obesity and body composition on sleep and the underlying mechanisms that explain these effects remain unclear. Therefore, this review summarizes the findings on the effects of body composition on sleep and draws conclusions and proposals for future research in this field.

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Section: Influence Of Body Composition On Sleep (Physical and Biologi...mentioning

confidence: 89%

Impact of Body Composition on Sleep and Its Relationship with Sleep Disorders: Current Insights

Kawasaki¹,

Kitamura²,

Kasai³

2023

NSS

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“…We measured body composition including body fat mass and body fat percentage using the same method as we described previously [10][11][12][13]. Elementary body composition was measured using a direct segmental multi-frequency bioelectrical impedance analyzer (InBody770; Biospace, Seoul, Korea), and we assessed total fat mass and body fat percentage.…”

Section: Measurement Of Body Fat and Muscle Compositionmentioning

confidence: 99%

Body Muscle-to-Fat Ratio, Rather Than Fat-to-Muscle Ratio, Significantly Correlates With Measured Insulin Resistance in Patients With Type 2 Diabetes Mellitus

et al. 2021

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Background: Insulin resistance (IR) assessment is important in treating type 2 diabetes mellitus (T2DM). We thus compared body muscle-to-fat ratio (BMFR) and fat-to-muscle ratio (FMR) values against M/I values as clinical index of IR.Methods: Subject included 118 untreated T2DM patients. Hyperinsulinemic-euglycemic clamp examination was performed to calculate the M/I as index of IR. Body composition was measured by impedance analysis using InBody770.Results: Simple linear regression analyses confirmed correlations between M/I and BMFR (B: 0.756 (P < 0.01), coefficients of determination (R 2 ): 0.572, mean absolute error (MAE): 3.19, and root mean squared error (RMSE): 4.14), and between M/I and FMR (B: -0.601 (P < 0.01), R 2 : 0.362, MAE: 3.97, and RMSE: 5.05). Against the M/I values, BMFR also showed better goodness-of-fit than did FMR. In comparing correlation coefficients, the BMFR absolute B value was significantly larger than that of FMR (P = 0.027).Conclusions: BMFR is more useful than FMR in quantifying IR in patients with T2DM because the correlation between BMFR and the insulin sensitivity index M/I is significantly greater than that between FMR and M/I.

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“… 14 , 15 Additionally, body fat mass, body fat percentage and body muscle-to-fat ratio (BMFR), which can be measured by bioelectrical impedance analysis (BIA), show a significant association with OSA, and BMFR is a suitable index for screening OSA in patients with T2DM. 16 However, the anthropometric parameters more related to OSA have not been fully clarified.…”

Section: Introductionmentioning

confidence: 99%

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

Ren,

Cui,

Zhu

et al. 2024

DMSO

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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.

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Clinical usefulness of the body muscle-to-fat ratio for screening obstructive sleep apnea syndrome in patients with inadequately controlled type 2 diabetes mellitus

Cited by 7 publications

References 29 publications

Impact of Body Composition on Sleep and Its Relationship with Sleep Disorders: Current Insights

Impact of Body Composition on Sleep and Its Relationship with Sleep Disorders: Current Insights

Body Muscle-to-Fat Ratio, Rather Than Fat-to-Muscle Ratio, Significantly Correlates With Measured Insulin Resistance in Patients With Type 2 Diabetes Mellitus

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

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