A new sensitive and accurate model to predict moderate to severe obstructive sleep apnea in patients with obesity
Sofie AhlinMelania MancoSimona PanunziOrnella VerrastroGiulia GiannettiA.A. PreteCaterina GuidoneAlessandro Di Marco BerardinoLuca VigliettaAnna Filomena FerravanteGeltrude MingroneDina ViscaEsmeralda Capristo
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Abstract Obstructive sleep apnea (OSA) has a high prevalence in patients with obesity. Only patients with clinical symptoms of OSA are admitted to polysomnography; however, many patients with OSA are asymptomatic. We aimed to create and validate a population-based risk score that predicts the severity of OSA in patients with obesity. We here report the cross-sectional analysis at baseline of an ongoing study investigating the long-term effect of bariatric surgery on OSA. One-hundred sixty-one patients of the Obesity Center of the Catholic University Hospital in Rome, Italy were included in the study. The patients underwent overnight cardiorespiratory monitoring, blood chemistry analyses, hepatic ultrasound, and anthropometric measurements. The patients were divided into 2 groups according OSA severity assessed by the apnea-hypopnea index (AHI): AHI < 15 = no or mild and AHI ≥ 15 moderate to severe OSA. A statistical prediction model was created and validated. C statistics was used to evaluate the discrimination performance of the model. The prevalence of OSA was 96.3% with 74.5% of the subjects having moderate/severe OSA. Sex, body mass index, diabetes, and age were included in the final prediction model that had excellent discrimination ability (C statistics equals to 83%). An OSA risk chart score for clinical use was created. Patients with severe obesity are at a very high risk for moderate or severe OSA in particular if they are men, older, more obese, and/or with type 2 diabetes. The OSA risk chart can be useful for general practitioners and patients as well as for bariatric surgeons to select patients with high risk of moderate to severe OSA for further polysomnography.Keywords:
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Abstract Obesity treatment studies report attrition rates front 20% to 45%. To reduce attrition, researchers have proposed matching patients to treatment based upon level of obesity. The current study attempted to validate the commonly held assumption that a mismatch between obesity level and treatment will promote attrition. The level of obesity and attrition rates of 39 adults who enrolled in a 12‐session behavior therapy program were examined. As obesity level increased, so did attrition. Sixty‐nine percent of subjects with mild obesity, 43% of subjects with moderate obesity and 0% of subjects with severe obesity completed treatment.
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Significant childhood adversity and chronic life stress are highly prevalent in patients with severe obesity. Such stress has been found to increase risk of adulthood obesity by up to 50%, and it can also substantially degrade the effectiveness of evidence-based treatments for this chronic disease condition. Despite general appreciation of these facts, though, stress is not frequently measured in obesity research or routinely assessed during treatment for obesity or obesity-related complications. To address this important issue, we describe several validated tools that can be used for assessing life stress and discuss how information obtained from these instruments can be integrated into obesity treatment and research. Given the documented relevance of stress for obesity, we argue that stress assessment and management should be included in clinical treatments for obesity and that stress should be routinely measured in studies examining the long-term effects of obesity and obesity treatment.
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Abstract The prevalence of obesity has increased in recent years and is now considered a global epidemic. Due to the serious health and economic impacts of weight gain, an understanding of the consequences and causes of obesity is necessary in order to develop effective weight management strategies and implement weight loss programs. The objective of this chapter is to review the epidemiology, implications, etiology, and treatment of adult obesity. Obesity prevalence and trends, the health and economic implications of obesity, environmental and genetic determinants of obesity, benefits of weight loss treatment and treatment goals, obesity assessment, lifestyle, behavioral, and medical obesity treatment, and weight loss maintenance will be discussed.
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Although the medical consequences of obesity are, quite rightly, the central focus of both obesity researchers and clinicians, it has increasingly become clear that the problems associated with obesity are not restricted simply to its effect on health; obesity also has a substantial impact on a person's health-related quality of life (HRQOL). HRQOL is generally regarded as a multidimensional construct encompassing emotional, physical, and social domains that reflect an individual's subjective evaluation and reaction to a health condition (1). Studies using both generic and obesity-specific measures of HRQOL have established that obesity is associated with profound decreases in HRQOL and that the greatest impairment tends to be on physically oriented domains of functioning (2,3). It has also been observed that the degree of HRQOL impairment tends to correspond with the level of obesity; heavier people report the greatest HRQOL impairment. Because the majority of obesity-related HRQOL studies have been conducted with individuals seeking treatment for their weight, typically university-based obesity treatment, it remains unknown whether the HRQOL among obese individuals who do not seek treatment differs markedly from those who do seek treatment. It is also unknown whether HRQOL differs among individuals with obesity seeking different forms of obesity treatment (e.g., outpatient treatment or gastric bypass). In this issue of Obesity Research, Kolotkin et al. (4) address these important questions by measuring obesity-specific HRQOL using the Impact of Weight on Quality of Life-Lite questionnaire (IWQOL-Lite) in a large (n = 3353) geographically and demographically diverse sample of overweight and obese adults who either were or were not seeking obesity treatment. Moreover, among those seeking treatment, the authors were able to capture the HRQOL of individuals along the range of obesity-treatment options from the least intensive (clinical trial involving infrequent meetings) to most intensive (gastric bypass surgery). Thus, this design allowed the authors to evaluate the continuum of available obesity treatments, as well as evaluate and compare HRQOL as a function of whether or not treatment was sought. Results indicated that, after controlling for age and body mass index, obesity-specific HRQOL was significantly more impaired according to the self-esteem, sexual life, work scales, and the IWQOL-Lite total score among treatment seekers compared with overweight/obese adults not currently seeking obesity treatment. Moreover, within treatment seekers, the degree of HRQOL impairment varied by treatment intensity. That is, the greatest level of impairment was found among gastric bypass patients, whereas the least HRQOL impairment was found among clinical-trial participants. Supplementary analyses indicated that greater HRQOL impairment was reported by whites, as well as by individuals with higher body mass indices, and by women in the non-treatment and clinical-trial groups. Although, in my view, this is a definitive study with regard to estimating the HRQOL of individuals with obesity, the non-treatment-seeking group of overweight and obese adults was not randomly selected, raising the possibility that their responses may not have been representative of the population of non-treatment-seeking individuals with obesity. Despite this possibility, the study by Kolotkin et al. (4) adds significantly to our knowledge by suggesting that the degree of HRQOL impairment corresponds with the intensity of the obesity treatment sought. Although we cannot determine from this study the role HRQOL played in a person's decision regarding whether or not to seek treatment or what type of treatment to seek, it is not unreasonable to propose that perceptions of HRQOL are important determinants of not only whether obese i2ndividuals seek treatment, but also the type of treatment they choose. The findings of Kolotkin et al. (4) imply that it may be both possible and worthwhile to use HRQOL assessments in a proactive way to assist obese individuals in making decisions about how to best manage their weight. That is, discussing the results of a HRQOL assessment with obese patients can stimulate a conversation that focuses explicitly on the impact their body weight has had on the way they live their life. Because body weight is generally gained slowly, many obese patients are not aware of the influence their weight has had on important dimensions until specific attention is given. Examining the impact of weight on these dimensions will allow clinicians to personalize the potential benefits that can be conferred from obesity treatment, as well as to help in the exploration of treatment options. For example, one of my former patients had stopped playing golf because his body weight increased by >100 kg. During our discussion of the results of his HRQOL assessment, however, it became evident to him that he had also abandoned many activities that he had previously enjoyed (e.g., mowing his lawn and taking his grandchild on day trips). Thus, as a result of the HRQOL assessment we were able to identify significant areas of impairment that prompted him to focus more acutely on his weight-control efforts so that he could “reclaim” his former life. Thus, HRQOL assessments can help clinicians identify important domains of functioning, set goals, discuss treatment options, and tailor a given treatment approach to the particular desires and needs of the individual. Despite the evidence from the study by Kolotkin et al. (4) and others suggesting that 1) individuals with obesity report decreases in HRQOL, 2) HRQOL varies in predictable ways (i.e., as a function of whether or not treatment is sought and the type of treatment sought), and 3) weight loss improves HRQOL (3,5,6), it is important to note that there is no consensus on what constitutes HRQOL, its domains, or how it is best measured. As it stands now, most generic and disease-specific HRQOL measures (including the IWQOL-Lite) focus on how patients are functioning, including their ability to perform the usual roles in their lives. In essence, these instruments simply measure self-reported health status and are used essentially as proxies for direct assessments of functional performance. Although the conceptualization of HRQOL as self-reported functional capacity has gained ascendancy in recent years, some have argued (7) that unless investigators tap into individual patient values, they are measuring only perceived health status, not HRQOL. In other words, an HRQOL score as typically derived does not reflect the values and meanings an individual places on his or her ability to perform a given function. The incorporation of individual values and preferences into HRQOL assessments will likely require researchers to supplement traditional questionnaire-based methodologies with other approaches (e.g., cognitive interviewing) that gather information on both the personal meanings associated with a given level of functioning and on the cognitive processes involved when one makes HRQOL judgments (8). Expanding both our conceptualization and measurement of HRQOL may not only increase our understanding of how obesity affects quality of life, but may also provide us with new ways to intervene to improve the lives of our patients. Nonetheless, within the current approaches to measuring HRQOL, the results of the study by Kolotkin et al. (4) confirm that the effects of obesity go far beyond its influence on physiological health parameters; obesity hampers an individual's capacity to live a full and satisfying life across a variety of important domains.
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Global obesity and hypertension epidemic continues to gain momentum as reported in several studies that association between obstructive sleep apnea, hypertension and weight gain has resulted in a corresponding increase in the frequency of this health issue. Therefore this analytical study was conducted with the help of a selfdeveloped validated questionnaire designed to find the prevalence of sleep apnea and its relationship with obesity and hypertension in 100 male participants. Obtained results revealed that out of 69 obese male individuals, 64 were suffering from sleep apnea along with apparent symptoms of hypertension indicating its high prevalence. If untreated, may affect quality of life, morbidity and mortality.
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Objective To know the trend of obesity in students, to forecast the developing trend, and explore measures for intervention. [Methods] The health survey data from the year 1994 to 2004 of students aged 7-18 years were collected. Using the standard weight for height as the obesity diagnostic standard, the obesity rates were calculated and analyzed. [Results] The obesity rates of students aged 7-18 years old from the year 1994 to 2004 rose 79.48%. The average rate was 13.57% and the average increasing rate per year was 6.82%. Obesity was more prevalent in boys than in girls. The obesity rates of boys were 2.12 times of girls' on average. The older the students, the higher the obesity rates were. [Conclusion] The prevalence of obesity in urban students is so severe that effective, overall and scientific intervention methods should be taken to cope with.
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The prevalence of obesity, a disorder linked to numerous comorbidities and metabolic complications, has recently increased dramatically worldwide and is highly prevalent in men, even at a young age. Compared to female patients, men with obesity more frequently have delayed diagnosis, higher severity of obesity, increased mortality rate, and only a minority of obese male patients are successfully treated, including with bariatric surgery. The aim of this review was to present the current state of knowledge about the clinical and therapeutic implications of obesity diagnosed in males.
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The study purposes were to: (i) Investigate eating behaviours among patients in a paediatric weight management clinical practice and (ii) Compare eating behaviour phenotypes between children with severe obesity and obesity. This was a retrospective cross-sectional study using data collected during clinical encounters. Participants were included if they were 2-12 years old, had a body mass index ≥95th percentile and if a parent or guardian completed the Child Eating Behaviour Questionnaire (CEBQ). Participants (n = 149) were children with severe obesity (n = 108) and obesity (n = 41). The mean Satiety Responsiveness score was significantly lower for children with severe obesity than for children with obesity. Girls with severe obesity had significantly higher Enjoyment of Food and significantly lower Satiety Responsiveness and Slowness in Eating than girls with obesity. The findings demonstrate the potential clinical utility of the CEBQ for informing tailored treatment strategies through identifying eating behaviour phenotypes.
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Conventionally, physiological and psychological differences between children and adults have directed their clinical care pathways, including treatment strategies, physician specialties, and health care facilities. One exception that has occurred gradually over the past few decades relates to the prevention and treatment of obesity. Striking similarities in obesity among adults, children, and adolescents have emerged — specifically, the increasing prevalence of obesity, multiple obesity-related coexisting conditions (medical, social, and psychological), and evolving methods of treatment.1-3 In addition, most adolescents who are obese remain obese as adults,4 and adults with obesity who were obese as adolescents have worse medical outcomes than persons . . .
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