Sleep-related Disorders in the Obese

Shahi, Bahram; Praglowski, Bozena; Deitel, Mervyn

doi:10.1381/096089292765560358

Cited by 21 publications

(4 citation statements)

References 34 publications

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“…Snoring affects both genders, including 23% of middle-aged males and 10% of females [ 24 ]. Obese subjects have a higher proportion of snoring than do the nonobese general population (45% versus 35%) [ 25 ]. Interestingly, the current meta-analysis stratified the studies according to gender, which revealed that females with habitual snoring were found to be associated with DM (OR, 1.59; 95% CI, 1.20–2.11).…”

Section: Discussionmentioning

confidence: 99%

Association between Self-Reported Habitual Snoring and Diabetes Mellitus: A Systemic Review and Meta-Analysis

Xiong

Zhong

et al. 2016

Journal of Diabetes Research

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Aim. Several studies have reported an association between self-reported habitual snoring and diabetes mellitus (DM); however, the results are inconsistent. Methods. Electronic databases including PubMed and EMBASE were searched. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the strength of the association between snoring and DM using a random-effects model. Heterogeneity, subgroup, and sensitivity analyses were also evaluated. Begg's, Egger's tests and funnel plots were used to evaluate publication bias. Results. A total of eight studies (six cross sectional and two prospective cohort studies) pooling 101,246 participants were included. Of the six cross sectional studies, the summary OR and 95% CI of DM in individuals that snore compared with nonsnorers were 1.37 (95% CI: 1.20–1.57, p < 0.001). There was no heterogeneity across the included studies (I 2 = 2.9%, p = 0.408). When stratified by gender, the pooled OR (95% CI) was 1.59 (1.20–2.11) in females (n = 12298), and 0.89 (0.65–1.22) in males (n = 4276). Of the two prospective studies, the pooled RR was 1.65 (95% CI, 1.30–2.08). Conclusions. Self-reported habitual snoring is statistically associated with DM in females, but not in males. This meta-analysis indicates a need to paying attention to the effect of snoring on the occurrence of DM in females.

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Section: Discussionmentioning

confidence: 99%

Association between Self-Reported Habitual Snoring and Diabetes Mellitus: A Systemic Review and Meta-Analysis

Xiong

Zhong

et al. 2016

Journal of Diabetes Research

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“…38 Fatty deposition results in airway reduction and predisposes to airway collapse, contributed to by neurologic loss of the normal dilator muscle tone in the neck. 39 The airway deformity improves after weight loss. 40 Polysomnographic sleep, recording is confirmatory, and demonstrates the severity of OSAHS.…”

Section: Further Discussion and Conclusionmentioning

confidence: 99%

Obesity and Obstructive Sleep Apnea-Hypopnea Syndrome: the Impact of Bariatric Surgery

et al. 2007

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Obstructive sleep apnea-hypopnea syndrome (OSAHS) is characterized by successive episodes of cessation or decrease in respiratory airflow, in which obesity is an important risk factor. The prevalence of the disease in morbidly obese patients is approximately 70%. Treatment is based on the use of continuous positive airway pressure (CPAP) and weight loss in obese patients. Weight loss by dieting often produces unsatisfactory results, and the use of CPAP does not show good adherence because of being long-term and uncomfortable. Bariatric surgery has emerged as the treatment for morbid obesity and various associated co-morbidities. This article reviews the principal studies that evaluate the modifications in obstructive sleep apnea after bariatric surgery, showing that surgery is an effective treatment for the management of OSAHS in morbidly obese patients.

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“…The global obesity epidemic has been spreading throughout most countries since the 1980s. Obesity contributes directly to incident cardiovascular risk factors, including dyslipidemia, type 2 diabetes, hypertension, and sleep disorders [1][2][3]. Obesity also leads to the development of cardiovascular diseases independently of other cardiovascular risk factors.…”

Section: Introductionmentioning

confidence: 99%

Personalized Metabolic Avatar: A Data Driven Model of Metabolism for Weight Variation Forecasting and Diet Plan Evaluation

et al. 2022

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Development of predictive computational models of metabolism through mechanistic models is complex and resource demanding, and their personalization remains challenging. Data-driven models of human metabolism would constitute a reliable, fast, and continuously updating model for predictive analytics. Wearable devices, such as smart bands and impedance balances, allow the real time and remote monitoring of physiological parameters, providing for a flux of data carrying information on user metabolism. Here, we developed a data-driven model of end-user metabolism, the Personalized Metabolic Avatar (PMA), to estimate its personalized reactions to diets. PMA consists of a gated recurrent unit (GRU) deep learning model trained to forecast personalized weight variations according to macronutrient composition and daily energy balance. The model can perform simulations and evaluation of diet plans, allowing the definition of tailored goals for achieving ideal weight. This approach can provide the correct clues to empower citizens with scientific knowledge, augmenting their self-awareness with the aim to achieve long-lasting results in pursuing a healthy lifestyle.

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Sleep-related Disorders in the Obese

Cited by 21 publications

References 34 publications

Association between Self-Reported Habitual Snoring and Diabetes Mellitus: A Systemic Review and Meta-Analysis

Association between Self-Reported Habitual Snoring and Diabetes Mellitus: A Systemic Review and Meta-Analysis

Obesity and Obstructive Sleep Apnea-Hypopnea Syndrome: the Impact of Bariatric Surgery

Personalized Metabolic Avatar: A Data Driven Model of Metabolism for Weight Variation Forecasting and Diet Plan Evaluation

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