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Relevant bibliographies by topics / Syndromic obesity

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Academic literature on the topic 'Syndromic obesity'

Author: Grafiati

Published: 5 June 2025

Last updated: 25 June 2025

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Journal articles on the topic "Syndromic obesity"

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Sohn, Young Bae. "Genetic obesity: an update with emerging therapeutic approaches." Annals of Pediatric Endocrinology & Metabolism 27, no. 3 (2022): 169–75. http://dx.doi.org/10.6065/apem.2244188.094.

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Based on the genetic contribution, childhood obesity can be classified into 3 groups: common polygenic obesity, syndromic obesity, and monogenic obesity. More genetic causes of obesity are being identified along with the advances in the genetic testing. Genetic obesities including syndromic and monogenic obesity should be suspected and evaluated in children with early-onset morbid obesity and hyperphagia under 5 years of age. Patients with syndromic obesity have early-onset severe obesity associated specific genetic syndromes including Prader-Willi syndrome, Bardet-Biedle syndrome, and Alstrom syndrome. Syndromic obesity is often accompanied with neurodevelopmental delay or dysmorphic features. Nonsyndromic monogenic obesity is caused by variants in single gene which are usually involved in the regulation of hunger and satiety associated with the hypothalamic leptin-melanocortin pathway in central nervous system. Unlike syndromic obesity, patients with monogenic obesity usually show normal neurodevelopment. They would be presented with hyperphagia and early-onset severe obesity with additional clinical symptoms including short stature, red hair, adrenal insufficiency, hypothyroidism, hypogonadism, pituitary insufficiencies, diabetes insipidus, increased predisposition to infection or intractable recurrent diarrhea. Identifying patients with genetic obesity is critical as new innovative therapies including melanocortin 4 receptor agonist have become available. Early genetic evaluation enables to identify treatable obesity and provide timely intervention which may eventually achieve favorable outcome by establishing personalized management.

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Horwitz, Avital, and Ruth Birk. "Adipose Tissue Hyperplasia and Hypertrophy in Common and Syndromic Obesity—The Case of BBS Obesity." Nutrients 15, no. 15 (2023): 3445. http://dx.doi.org/10.3390/nu15153445.

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Obesity is a metabolic state generated by the expansion of adipose tissue. Adipose tissue expansion depends on the interplay between hyperplasia and hypertrophy, and is mainly regulated by a complex interaction between genetics and excess energy intake. However, the genetic regulation of adipose tissue expansion is yet to be fully understood. Obesity can be divided into common multifactorial/polygenic obesity and monogenic obesity, non-syndromic and syndromic. Several genes related to obesity were found through studies of monogenic non-syndromic obesity models. However, syndromic obesity, characterized by additional features other than obesity, suggesting a more global role of the mutant genes related to the syndrome and, thus, an additional peripheral influence on the development of obesity, were hardly studied to date in this regard. This review summarizes present knowledge regarding the hyperplasia and hypertrophy of adipocytes in common obesity. Additionally, we highlight the scarce research on syndromic obesity as a model for studying adipocyte hyperplasia and hypertrophy, focusing on Bardet–Biedl syndrome (BBS). BBS obesity involves central and peripheral mechanisms, with molecular and mechanistic alternation in adipocyte hyperplasia and hypertrophy. Thus, we argue that using syndromic obesity models, such as BBS, can further advance our knowledge regarding peripheral adipocyte regulation in obesity.

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Mahmoud, Ranim, Virginia Kimonis, and Merlin G. Butler. "Genetics of Obesity in Humans: A Clinical Review." International Journal of Molecular Sciences 23, no. 19 (2022): 11005. http://dx.doi.org/10.3390/ijms231911005.

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Obesity is a complex multifactorial disorder with genetic and environmental factors. There is an increase in the worldwide prevalence of obesity in both developed and developing countries. The development of genome-wide association studies (GWAS) and next-generation sequencing (NGS) has increased the discovery of genetic associations and awareness of monogenic and polygenic causes of obesity. The genetics of obesity could be classified into syndromic and non-syndromic obesity. Prader–Willi, fragile X, Bardet–Biedl, Cohen, and Albright Hereditary Osteodystrophy (AHO) syndromes are examples of syndromic obesity, which are associated with developmental delay and early onset obesity. Non-syndromic obesity could be monogenic, polygenic, or chromosomal in origin. Monogenic obesity is caused by variants of single genes while polygenic obesity includes several genes with the involvement of members of gene families. New advances in genetic testing have led to the identification of obesity-related genes. Leptin (LEP), the leptin receptor (LEPR), proopiomelanocortin (POMC), prohormone convertase 1 (PCSK1), the melanocortin 4 receptor (MC4R), single-minded homolog 1 (SIM1), brain-derived neurotrophic factor (BDNF), and the neurotrophic tyrosine kinase receptor type 2 gene (NTRK2) have been reported as causative genes for obesity. NGS is now in use and emerging as a useful tool to search for candidate genes for obesity in clinical settings.

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Brandsma, Annelies E., Romy Gaillard, Lotte Kleinendorst, et al. "OR14-2 Age of Onset of Obesity and Childhood BMI Trajectories in Rare Genetic Obesity Disorders." Journal of the Endocrine Society 6, Supplement_1 (2022): A613. http://dx.doi.org/10.1210/jendso/bvac150.1272.

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Abstract Introduction Early-onset obesity is a cardinal feature of rare genetic obesity disorders. According to the Endocrine Society guideline, genetic screening is indicated in selected cases with age of onset (AoO) of severe obesity (grade ≥2) &lt;5 years. However, this cut-off is not validated. Aims To present the detailed BMI characteristics of children and adolescents with rare genetic obesity disorders; to evaluate whether the following growth chart characteristics can aid in assessing which children should be screened for genetic obesity disorders: AoO of obesity, AoO of severe obesity, BMI standard deviation scores (SDS) at yearly age intervals. Methods In this prospective observational study, children with non-syndromic and syndromic genetic obesity disorders treated at our tertiary obesity center were included. Growth measurements from birth onwards were collected. Children with obesity from a population-based cohort study with follow-up until age 10 years were included as an unselected reference cohort. Diagnostic performance (sensitivity [sens], specificity [spec], positive likelihood ratio [LR+], area-under-the-curve [AUC]) for AoO of obesity and severe obesity and for BMI-SDS at yearly age intervals was calculated. Results We included 64 children with genetic obesity disorders (32 non-syndromic, 32 syndromic) and 298 control children with obesity. At intake, median age of children with genetic obesity was 10.5 years (IQR 7.0–14.7) and mean BMI-SDS +3.1 ± 1.1. Median AoO of obesity was 1.2 years (IQR 0.6–3.7) in non-syndromic genetic obesity, 2.1 years (IQR 0.9–4.2) in syndromic genetic obesity, and 3.8 years (IQR 2.3–6.2) in the control population. For non-syndromic genetic obesity, optimal cut-off value for AoO of obesity was ≤1.5 years: sens 0.60, spec 0.88, LR+ 5.22, AUC 0.79 (p&lt;0.001). For syndromic genetic obesity, optimal cut-off was ≤3.0 years: sens 0.68, spec 0.68, LR+ 2.06, AUC 0.67 (p=0.001). AoO of severe obesity showed worse diagnostic performance than AoO of obesity in both non-syndromic (AUC 0.58, p=0.20) and syndromic genetic obesity (AUC 0.58, p=0.21). Moreover, when the guideline cut-off &lt;5 years was used, AoO of severe obesity showed a negative diagnostic performance (non-syndromic genetic obesity: sens 0.76, spec 0.13, LR+ 0.88; syndromic genetic obesity: sens 0.85, spec 0.14, LR+ 0.98). BMI-SDS showed good diagnostic performance for non-syndromic genetic obesity across the age intervals (AUCs 0.79-0.89, all P&lt;0.001) but not for syndromic genetic obesity (AUCs 0.54-0.71, P-values ranging from &lt;0.001-0.50). Conclusion This study shows that growth charts characteristics such as BMI-SDS and AoO of obesity (grade 1), but not AoO of severe obesity (grade ≥2), could be useful to distinguish between children with genetic obesity disorders and children with obesity from a population-based cohort study. However, all investigated growth charts characteristics showed misclassification, especially in syndromic genetic obesity, indicating that additional clinical features should be present to warrant genetic testing in these children. Presentation: Sunday, June 12, 2022 11:15 a.m. - 11:30 a.m.

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Alsaeed, Suliman, Nelly Huynh, David Wensley, et al. "Orthodontic and Facial Characteristics of Craniofacial Syndromic Children with Obstructive Sleep Apnea." Diagnostics 13, no. 13 (2023): 2213. http://dx.doi.org/10.3390/diagnostics13132213.

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Introduction: Obstructive sleep apnea (OSA) is a disorder in which ventilation becomes disrupted due to a complete or partial upper airway obstruction Altered craniofacial morphology is one of the most important anatomical factors associated with obstructive sleep apnea (OSA). Studies have assessed craniofacial features in the non-syndromic pediatric population. The aim of this study was to analyze the orthodontic and facial characteristic of craniofacial syndromic children referred for polysomnography (PSG) and to assess the correlation with the apnea–hypopnea index (AHI). Methods: In the current cross-sectional study, consecutive syndromic patients referred for PSG were invited to participate. A systematic clinical examination including extra- and intra-oral orthodontic examination was performed by calibrated orthodontists. Standardized frontal and profile photographs with reference points were taken and analyzed using ImageJ® software to study the craniofacial morphology. PSG data were analyzed for correlation with craniofacial features. STROBE guidelines were strictly adopted during the research presentation. Results: The sample included 52 syndromic patients (50% females, mean age 9.38 ± 3.36 years) diagnosed with 17 different syndromes, of which 24 patients had craniofacial photography analysis carried out. Most of the sample (40%) had severe OSA, while only 5.8% had no OSA. Down’s syndrome (DS) was the most common syndrome (40%) followed by Goldenhar syndrome (5%), Pierre Robin Sequence (5%), and other syndromes. The severity of AHI was significantly correlated with decreased midfacial height. increased thyromental angle and cervicomental angle, decreased mandibular angle, and decreased upper facial height. All patients with DS were diagnosed with OSA (57% severe OSA), and their ODI was significantly correlated with increased intercanthal distance. Obesity was not correlated to the severity of AHI for syndromic patients. Conclusions: Decreased midfacial height and obtuse thyromental angle were correlated with increased AHI for syndromic patients. Increased intercanthal distance of DS patients could be a major predictor of OSA severity. Obesity does not seem to play a major role in the severity of OSA for syndromic patients. Further studies with larger samples are necessary to confirm these findings.

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Poitou, C., H. Mosbah, and K. Clément. "MECHANISMS IN ENDOCRINOLOGY: Update on treatments for patients with genetic obesity." European Journal of Endocrinology 183, no. 5 (2020): R149—R166. http://dx.doi.org/10.1530/eje-20-0363.

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Obesity, defined by an excess of body fat impacting on health, is a complex disease resulting from the interaction between many genetic/epigenetic factors and environmental triggers. For some clinical situations with severe obesity, it has been possible to classify these obesity forms according to the molecular alterations. These include: (i) syndromic obesity, which associates severe early-onset obesity with neurodevelopmental disorders and/or polymalformative syndrome and (ii) non-syndromic monogenic obesity, due to gene variants most often located in the leptin-melanocortin pathway. In addition to severe obesity, patients affected by these diseases display complex somatic conditions, eventually including obesity comorbidities, neuropsychological and psychiatric disorders. These conditions render the clinical management of these patients particularly challenging. Patients’ early diagnosis is critical to allow specialized and multidisciplinary care, with a necessary interaction between the health and social sectors. Up to now, the management of genetic obesity was only based, above all, on controlling the patient's environment, which involves limiting access to food, ensuring a reassuring daily eating environment that limits impulsiveness, and the practice of adapted, supported, and supervised physical activity. Bariatric surgery has also been undertaken in genetic obesity cases with uncertain outcomes. The context is rapidly changing, as new innovative therapies are currently being tested both for syndromic and monogenic forms of obesity. This review focuses on care management and new therapeutic opportunities in genetic obesity, including the use of the melanocortin 4 agonist, setmelanotide. The results from ongoing trials will hopefully pave the way to a future precision medicine approach for genetic obesity.

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Babayan, M. L., and L. A. Kharitonova. "Syndromic obesity in children (using the example of clinical cases)." Experimental and Clinical Gastroenterology, no. 6 (October 22, 2024): 215–20. http://dx.doi.org/10.31146/1682-8658-ecg-226-6-215-220.

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Obesity is a heterogeneous group of hereditary and acquired diseases associated with excessive accumulation of adipose tissue in the body. One example of syndromic obesity in children is Bardet-Biedl syndrome. This is a rare autosomal recessive disease from the group of ciliopathies, characterized by retinal dystrophy, obesity, polydactyly, mental retardation, hypogonadism, and renal dysfunction. The article presents two clinical cases of Bardet-Biedl syndrome. Diagnostic criteria for the disease are given, and the need for molecular genetic research methods in the early stages of the diagnostic search is shown. Promising directions in the treatment of the syndrome are considered.

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Kalinderi, Kallirhoe, Vasiliki Goula, Evdoxia Sapountzi, Vasiliki Rengina Tsinopoulou, and Liana Fidani. "Syndromic and Monogenic Obesity: New Opportunities Due to Genetic-Based Pharmacological Treatment." Children 11, no. 2 (2024): 153. http://dx.doi.org/10.3390/children11020153.

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Obesity is a significant health problem with a continuously increasing prevalence among children and adolescents that has become a modern pandemic during the last decades. Nowadays, the genetic contribution to obesity is well-established. For this narrative review article, we searched PubMed and Scopus databases for peer-reviewed research, review articles, and meta-analyses regarding the genetics of obesity and current pharmacological treatment, published in the English language with no time restrictions. We also screened the references of the selected articles for possible additional articles in order to include most of the key recent evidence. Our research was conducted between December 2022 and December 2023. We used the terms “obesity”, “genetics”, “monogenic”, “syndromic”, “drugs”, “autosomal dominant”, “autosomal recessive”, “leptin-melanocortin pathway”, and “children” in different combinations. Recognizing the genetic background in obesity can enhance the effectiveness of treatment. During the last years, intense research in the field of obesity treatment has increased the number of available drugs. This review analyzes the main categories of syndromic and monogenic obesity discussing current data on genetic-based pharmacological treatment of genetic obesity and highlighting the necessity that cases of genetic obesity should follow specific, pharmacological treatment based on their genetic background.

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Milani, Donatella, Marta Cerutti, Lidia Pezzani, Pietro Maffei, Gabriella Milan, and Susanna Esposito. "Syndromic obesity: clinical implications of a correct diagnosis." Italian Journal of Pediatrics 40, no. 1 (2014): 33. http://dx.doi.org/10.1186/1824-7288-40-33.

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Walley, Andrew J., Julian E. Asher, and Philippe Froguel. "The genetic contribution to non-syndromic human obesity." Nature Reviews Genetics 10, no. 7 (2009): 431–42. http://dx.doi.org/10.1038/nrg2594.

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Dissertations / Theses on the topic "Syndromic obesity"

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Zheng, Yue. "Adipose Related Signaling in Syndromic Obesity." Fogler Library, University of Maine, 2009. http://www.library.umaine.edu/theses/pdf/ZhengY2009.pdf.

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Sivam, Sheila. "Clinical Aspects of Obesity Hypoventilation Syndrome." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/18741.

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Obesity hypoventilation syndrome (OHS) represents the most severe form of sleep disordered breathing occurring in obese individuals and results in hypoventilation, both during sleep and in wakefulness. OHS is associated with significant morbidity and increased health, social and economic burdens for the individual and health care system. Mortality in OHS has been shown to be significantly higher than in individuals with eucapnic obstructive sleep apnoea (OSA), even when effective treatment with positive airway pressure (PAP) therapy has been established. In these individuals, it is cardiovascular disease rather than respiratory failure, which is the most common cause of death. The work presented in this thesis focuses on 3 aspects of OHS: development of a predictive model for early identification of obese patients with nocturnal-only hypoventilation, thought to represent an earlier stage of OHS; comparison of neurocognitive function pre and post PAP therapy in OHS and equally obese individuals with OSA; and the impact of PAP therapy on cardio-metabolic and renal biomarkers in OHS patients, comparing this with equally obese individuals with OSA.

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Camerotto, C. "OBESITY AND METABOLIC SYNDROME: PLASMA LIPOPROTEINS ALTERATIONS." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/151781.

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Obesity, especially if associated with metabolic syndrome, promotes oxidative stress, a low grade chronic inflammatory state, and modify the composition and function of plasma lipoproteins. Oxidative damage to lipoproteins not only make LDL atherogenic but can also alter HDL reducing their anti-atherogenic properties. The possibility of monitoring the lipid peroxidation of the individual regions of LDL and HDL could lead to more detailed information on the molecular mechanisms that are the basis of the increased risk of cardiovascular diseases observed in obesity and metabolic syndrome. The object of this study was to investigate the susceptibility to peroxidation of plasma and of the hydrophobic core and the surrounding envelope of LDL and HDL in obese male (BMI between 25 and 35 Kg mq) with (SM, n=20)) or without (OB, n =40) metabolic syndrome. The susceptibility of plasma to peroxidation was higher in SM and OB than in normo-weight controls (CT, n=60), but not significant differences were observed between these two obese groups. Also the susceptibility to peroxidation of isolated LDL and HDL was higher in both obese groups than in CT. LDL and HDL in SM presented an higher content of triacylglicerols than the corresponding HDL of OB. Moreover, the hydrophobic core of HDL showed a risk of peroxidation significantly higher in SM than in OB. This last parameter was inversely correlated with the waist to hip ratio, an index of visceral obesity. This last evidence seems to indicate that the increase of inflammation typical of the visceral adipose tissue could be one of the major causes of the higher susceptibility to peroxidation found in the hydrophobic core of HDL. The evaluation of the susceptibility to peroxidation of the core and the envelope of LDL and HDL might contribute to the identification of a subset of patients at increased risk of metabolic and cardiovascular complications. Future “ad hoc” randomized clinical trials should be designed to address the effects of weight reduction and /or different diet and/or nutritional supplementation on these parameters.

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Basil, Janet S. "Retrospective Study of Obesity in Children with Down Syndrome." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427882782.

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Juanola, Falgarona Martí. "Glycemic index in the management of Obesity and Metabolic syndrome." Doctoral thesis, Universitat Rovira i Virgili, 2014. http://hdl.handle.net/10803/319948.

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La obesitat y la síndrome metabòlica (SMet) són una de les principals causes de mortalitat arreu del món. L’índex glucémic (IG) i la càrrega glucémica (CG) han estat associades a un augment del risc de desenvolupar obesitat, diabetis tipus 2, SMet i malalties cardiovasculars. Actualment la evidència científica suggereix possibles beneficis de l’IG/CG per a la prevenció i tractament de la obesitat i la SMet. El nostre objectiu va ser analitzar la associació entre IG/CG de la dieta i el risc de desenvolupar SMet i els seus components, a més a més de analitzar la relació entre l’IG/CG i marcadors d’inflamació perifèrics. Per altra banda, vam analitzar la efectivitat d’una dieta de alt IG/CG contra una dieta baixa amb IG/CG i una dieta baixa en greix sobre la pèrdua de pes i la millora del perfil metabòlic, a través de la modulació d’uns mecanismes relacionats amb la sacietat, la inflamació i altres marcadors metabòlics. Aquesta tesi ha estat realitzada en el marc de l’estudi PREDIMED, un assaig clínic nutricional, multicèntric i aleatoritzat; i de l’estudi GLYNDIET, un assaig clínic en paral•lel, aleatoritzat i controlat de 6 mesos de duració. Els resultats obtinguts mostren com les dietes amb alt IG/CG podrien jugar un paper important en el desenvolupament de la SMet i alguns dels seus components. A més, el consum d’aquestes dietes també podria modular alguns marcadors cardiometabolics que contribuirien al guany de pes i al desenvolupament de malalties cardiovasculars. Finalment, vam observar com el consum d’una dieta amb baix IG i un moderat contingut de carbohidrats era més efectiva per la pèrdua de pes i la millora de la sensibilitat i resistència a la insulina que una dieta de alt IG i un moderat contingut de carbohidrats o una dieta baix en greix.<br>La obesidad y el síndrome metabólico (SMet) son una de las principales causas de la mortalidad a nivel mundial. El índice glucémico (IG) i la carga glucémica (CG) han estado asociados a un mayor riesgo de obesidad, diabetes tipo 2, SMet y enfermedades cardiovasculares. Actualmente la evidencia científica sugiere posibles beneficios del IG/CG para la prevención y tratamiento de la obesidad y SMet. Nuestro objetivo fue analizar la asociación entre el IG/CG de la dieta y el riesgo de desarrollar SMet i sus componentes, además de analizar la relación del IG/CG y marcadores de inflamación periféricos. Por otro lado, analizamos la efectividad de una dieta de alto IG/CG contra una dieta baja en IG/CG y una dieta baja en grasa sobre la pérdida de peso i la mejora del perfil metabólico, a través de la modulación de mecanismos relacionados con la saciedad, la inflamación y otros marcadores metabólicos. Esta tesis se ha realizado dentro del marco del estudio PREDIMED, una ensayo clínico nutricional, multicéntrico i aleatorizado; y el estudio GLYNDIET, un ensayo clínico en paralelo, aleatorizado y controlado de 6 meses de duración. Los resultados obtenidos muestran como las dietas de alto IG/CG podrían jugar un papel importante en el desarrollo del SMet y alguno de sus componentes. Además, el consumo de estas dietas también podría modular algunos marcadores cardiometabólicos que contribuyen a la ganancia de peso y al desarrollo de enfermedades cardiovasculares. Finalmente, observamos como el consumo de una dieta de bajo IG y una moderada cantidad de carbohidratos era más efectiva para la pérdida de peso y la mejora de la sensibilidad y la resistencia a la insulina que una dieta de alto IG y una moderada cantidad de carbohidratos o una dieta baja en grasa.<br>Obesity and Metabolic Syndrome (MetS) are one of the main causes of disability and death worldwide. It has been proposed that high glycemic index (GI) and high glycemic load (GL) diets are associated with increased risks of obesity, type 2 diabetes mellitus, MetS and cardiovascular disease. To date, evidence suggests possible benefits of the GI/GL for the prevention and management of obesity and MetS. We aimed to analyze the association between dietary GI and GL and the risk of to develop MetS and its features, as well as, the relationship between dietary GI and GL, peripheral adipokines and inflammatory markers. Also, we aimed to analyze the effectiveness of a high GI/GL diet versus a low-GI/GL and a low-fat diet in body weight loss and the improvement of metabolic profile, through the modulation of some mechanisms related to satiety, inflammation and other metabolic risk markers. This thesis has been conducted in the framework of the PREDIMED Study, multicenter randomized nutrition trial, and the GLYNDIET study, a 6-month randomized, parallel, controlled clinical trial. Our results suggest that high dietary GI and GL have a potential role in the development of MetS and some of its components. The consumption of diets with high-GI foods or high dietary GL may also modulate some cardiometabolic markers thus contributing to weight gain and cardiovascular disease. Finally, we found that a moderate-CH low-GI diet may be more effective for weight loss than a moderate-CH high-GI diet or a conventional low-fat diet. The metabolic benefits observed for insulin resistance and sensitivity in those subjects following a low-GI diet, and the tendency to improve other inflammatory and associated metabolic risk markers, also indicate that low-GI diets are better tools for managing obesity and its associated comorbidities.

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Barber, T. "Polycystic ovary syndrome: The role of the genes and obesity." Thesis, University of Oxford, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.489409.

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There is a frequent concurrence of obesity and polycystic ovary syndrome (PCOS). To confirm the mechanistic link between these two common conditions, the studies detailed in this thesis have employed both genetic and physiological approaches.

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Retallick, Christopher. "Arterial stiffness, obesity and metabolic syndrome in children and adolescents." Thesis, University of South Wales, 2012. https://pure.southwales.ac.uk/en/studentthesis/arterial-stiffness-obesity-and-metabolic-syndrome-in-children-and-adolescents(cd768264-d8af-45ba-b858-285979d05ba2).html.

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Atherosclerotic cardiovascular disease (CVD) is the leading cause of death in Western Societies. The pathological processes and risk factors associated with its development begin in childhood, long before clinical consequences emerge. Cardiovascular risk factors have been shown to cluster together in adults and children, particularly in the presence of obesity. Exposure to these risk factors in the first decade of life has been shown to cause vascular endothelial dysfunction and autopsy documented atherosclerosis. Childhood overweight and obesity is increasing in worldwide, Western populations and is strongly associated with vascular dysfunction and arterial stiffness. The aim of this research program was to collect anthropometrical, haematological and physiological data from a large number of apparently healthy Welsh children and adolescents with the purpose of examining central and peripheral haemodynamic indices of arterial stiffness and their association with CVD risk factors. In addition it sought to examine the prevalence of overweight and obesity, the prevalence of metabolic syndrome and examine relationships with emerging risk factors. This study has shown that the prevalence of overweight and obesity in children and adolescents is high yet varies greatly dependent on the measurement methods and cut-off criteria applied. Prevalence estimates for metabolic syndrome ranged from 0% to 3.5%. All measures of adiposity showed significant associations with insulin resistance and with 2 or more components of the metabolic syndrome. Aortic pulse wave velocity increased with increasing BMI status. A negative association was found between arterial stiffness and aerobic fitness. The overall prevalence of hypertension was 9.8% with 4.4% of individuals identified with isolated systolic hypertension. The mechanisms underlying isolated systolic hypertension could not be confirmed through this study. Elevations in alanine aminotransferase were highly prevalent and strongly associated with insulin resistance, fasting insulin, body composition, clustering of metabolic risk factors and inversely related to aerobic fitness.

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Chen, Pin-Yen. "Identification of biomarkers for obesity with metabolic syndrome using machine learning models." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/401351.

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Metabolic syndrome (MetS) is a condition that is linked to the increased risk of developing chronic diseases, including type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). The association between MetS and chronic disease development lies in the cardiometabolic risk factors that comprise MetS: abdominal obesity, hypertension, hyperglycaemia and dyslipidaemia [1]. The development of MetS is also associated with the dysregulation of many different body systems, such as the immune system [2] and gut microbiome [3]. Due to its multifactorial nature, research in MetS requires the simultaneous analysis of multiple biomarkers across different body systems. As most research thus far have utilised univariate analysis, no biomarker profile has been identified to characterise individuals more at risk of MetS and related diseases. The current study has therefore implemented the use of correlationbased network analysis (CNA) and multiple classification models to identify the biomarkers that collectively link to increased MetS development. Four variable groups comprising of multiple different measurements were obtained from 117 healthy weight controls and 35 obese with MetS individuals. The four variable groups consisted of: anthropometric measures, haematological measures, gene expression levels and gut microbial counts. The use of CNA allowed a better understanding of the relationships between biomarkers affected by MetS. As expected, the obese with MetS network was denser than the healthy weight control network, demonstrating the complex nature of MetS. The results found molecular interactions supporting the findings of previous literature, particularly correlations that demonstrated the development of anaemia of inflammation in the obese with MetS network. There were also three key hubs identified using gene expression levels, involving transcription factor EB (TFEB), lipocalin 2 (LCN2), and cluster of differentiation- (CD-) 68. The three genes are associated with regulatory T cells and neutrophils, two prominent cells in regulating the inflammatory state. As obesity and MetS are often described as a state of chronic low-grade inflammation, the findings of CNA correspond with that of previous studies. Classification models are another type of analytical tool that have demonstrated high predictive ability in many diseases, including T2DM and CVD. The use of classification models for the prediction of diseases allows the risk of disease development to be evaluated. The current study applied classification models for the prediction of MetS using three of the four variable groups measured: haematological measures, gene expression levels and gut microbial counts. Classification models are not only able to assess the relevance of these variable groups to MetS but also identify the specific variables that contributed the most to MetS development. There are a range of classification models that can be used and due to MetS being a relatively new area of research, the most appropriate model for MetS prediction has yet to be determined. As such, the current study predicted MetS using four different types of classification models and compared the predictive abilities of each model. The four models that were used in the current study were: logistic regression (LR), decision tree (DT), support vector machine (SVM) and artificial neural network (ANN). The performance of each classification model was evaluated using 10-fold cross-validation, which splits the dataset into 10 training and testing sets. Each model is then built using the training sets and evaluated using the testing sets to ensure that the model was not fit too closely to the training data. The model with the highest performance when predicting MetS using haematological measures and gut microbial counts was ANN, while SVM had the highest performance when using gene expression levels. However, ANN was also able to attain a high area under the curve (AUC) value of 0.804 when predicting MetS using gene expression levels. As such, the prediction model that had the highest performance overall was ANN. Each model has their own strengths and limitations dealing with specific types of data and the most appropriate model depends on the research question being asked. Although SVM and ANN are both very powerful algorithms, capable of handling high-dimensional data, both models have difficulty producing clinically significant results. On the other hand, LR and DT models are both able to identify specific biomarkers that should be further investigated for links to diseases development, deeming them more suitable for clinical applications. For each of the 10 LR and DT models, constructed using the 10 training sets, the haematological measurement that was found to be most important was triglycerides (TG). Additionally, the best performing LR model, out of the 10 constructed models, found measurements of TG, platelets (PLT), erythrocyte sedimentation rate (ESR), fasting plasma glucose (FPG), haemoglobin (HG) and glycated haemoglobin A1c (HbA1c) to be associated with MetS development. At the same time, high-density lipoprotein-cholesterol (HDL-C) was linked to a reduced risk of MetS development. Using DT, the important measurements in MetS development were TG, PLT, HDL-C, age, HG, C-reactive protein (CRP) and white cell counts. Each variable identified has been found to be linked to either a cardiometabolic risk factor or inflammation and thus the results of the current study are supportive of previous literature on obesity and MetS. Logistic regression also found the expression of AKT serine/threonine kinase 3 (AKT3), Fc fragment of IgE receptor II (FCER2), cathelicidin antimicrobial peptide (CAMP), interleukin- 11 receptor subunit alpha (IL11RA) and granzyme H (GZMH) to increase the odds of developing MetS while C-X-C motif chemokine receptor 6 (CXCR6), C-C motif chemokine ligand- (CCL-)3, suppressor of cytokine signalling 1 (SOCS1) and killer cell lectin like receptor C2 (KLRC2) expression reduces these odds. Consistent with these findings, DTs also predicted individuals with high AKT3, FCER2 and CAMP expression to be obese with MetS while healthy weight controls had higher CXCR6, CCL3 and KLRC2 expression. The findings of the current study were partially supportive of previous literature, with FCER2 and CAMP expression being associated with obesity and inflammation [4, 5] and KLRC2 expression being inversely associated with obesity and inflammation [6, 7]. On the other hand, AKT3 is associated with glucose and lipid metabolism [8] with evidence of its expression leading to the protection against insulin resistance. As such, the high AKT3 expression found in the obese with MetS cohort was not consistent with current literature. Similarly, the association between the expression of CXCR6 and CCL3 with a healthy weight control classification could not be explained as both genes are typically linked to inflammation [9, 10]. Finally, LR and DT found microbial species belonging to the Firmicutes and Bacteroidetes phyla to both be associated with the increased and reduced risk of developing obesity with MetS. Obesity with MetS is largely characterised by a high Firmicutes-to-Bacteroidetes ratio, particularly when compared to healthy weight controls [11]. While this pattern was not clearly evident in the current study, the cause of discrepancy with previous literature may be due to gut microbial studies in obesity and MetS not being typically reported at the species level. While LR and DT are both able to identify the variables that are likely to contribute to MetS development in a clinical setting, the performances of either model were not able to compete with that of ANN or SVM. At the same time, despite having the highest performance overall, ANN is unable to produce easily interpretable results with clinical significance. As such, its high predictive ability is not enough to convince researchers to choose ANN for clinical use. To overcome this issue, many researchers combine ANN with a feature selection technique, such as genetic algorithm (GA). Feature selection techniques are able to identify the best combination of biomarkers for the prediction of diseases. In the current study, the variables that were recognised to be significant by the hybrid model supported the findings of LR and DT. The haematological biomarkers that were consistently recognised as important by all three prediction models were measures of TG and HG. Additionally, CCL3 and CXCR6 expression, as well as three gut microbial species belonging to the Firmicutes and Bacteroidetes phyla, were also found to be important for MetS development. Other than the identification of important variables, the hybrid model was also able to improve the performance of ANN when predicting MetS using gene expression levels and gut microbial counts. Consequently, the current study concluded that the hybrid GA with ANN model was considered to be the most appropriate for MetS prediction. Another analytical method that was used by the current study was weighted majority voting, which combines the final predicted outcomes of the other classification models to determine whether the performance could be further improved. The weighted majority voting method was able to achieve the highest AUC value for the prediction of MetS using gut microbial counts as well as the second highest AUC when using haematological measures and gene expression levels. However, the dependency of the weighted majority voting method on the performance of individual classification models used was demonstrated in the study. The low sensitivity values attained by DT in the testing set of all three variable groups is likely what prevented the weighted majority voting method from outperforming all the other classification models in the prediction of MetS. In spite of the limitation caused by DT, however, the method was still able to achieve a high performance. As such, the combination of the results from different classification models into a weighted majority voting method to increase the overall predictive ability was found to be a viable choice. The classification model that was found to be most suitable for the prediction of MetS was the hybrid GA with ANN model. Not only was the model able to achieve high predictive ability due to the ANN portion of the model, it was also able to reveal the optimal combination of variables that contributed the most to an accurate MetS prediction. The variables that were identified were also supportive of the findings of both LR and DT. The measurements used by the current study (haematological measures, gene expression levels and gut microbial counts) were all found to be suitable for the prediction of MetS. Future studies may consider the use of other biomarkers, including measurements from adipose tissue, for the prediction of MetS using the hybrid GA with ANN model.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Medical Science<br>Griffith Health<br>Full Text

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Fisher, Kimberly Denise. "Dietary manipulation causes childhood obesity-like characteristics in pigs." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/36176.

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An animal model to study complications resulting from childhood obesity is lacking. Our objective was to develop a porcine model for studying mechanisms underlying diet-induced childhood obesity. Pre-pubertal female pigs, age 35 d, were fed a high-energy diet (HED; n = 12), containing tallow and refined sugars, or a control corn-based diet (n = 11) for 16 wk. Initially, HED pigs self-regulated energy intake similar to controls, but, by wk 5, consumed more (P < 0.001) energy per kg body weight. At wk 15 and 22, pigs were subjected to an oral glucose tolerance test (OGTT); blood glucose increased (P < 0.05) in control pigs and returned to baseline levels within 60 min. HED pigs were hyperglycemic at time 0, and blood glucose did not return to baseline (P = 0.01), even 3 h post-challenge. During OGTT, glucose area under the curve was higher and insulin area under the curve was lower in HED pigs compared to controls (P = 0.001). Pigs given 6 wk of dietary intervention, consuming a control diet, marginally improved glucose area under the curve and LDL-cholesterol although insulin area under the curve was unaffected. Chronic HED intake increased (P < 0.05) subcutaneous, intramuscular, and perirenal fat deposition, and induced hyperglycemia, hypoinsulinemia, and low-density lipoprotein hypercholesterolemia; however, a 6 wk dietary intervention partially recovered a normal physiology. These data suggest pre-pubertal pigs fed HED are a viable animal model for studying childhood obesity.<br>Master of Science

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Kyrou, Ioannis. "Impact of obesity and metabolic syndrome on morbidity, inflammation and adipokines." Thesis, University of Warwick, 2012. http://wrap.warwick.ac.uk/55046/.

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Books on the topic "Syndromic obesity"

1

L, Beales Philip, Farooqi Sadaf, and O'Rahilly S, eds. The genetics of obesity syndromes. Oxford University Press, 2008.

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Bray, George A. The Metabolic Syndrome and Obesity. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-431-5.

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European Society for Clinical Investigation. Meeting. Stress, obesity, and metabolic syndrome. Blackwell Publishing on behalf of the New York Academy of Sciences, 2006.

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Ottar, Sjaastad, Nappi G, and European Headache Federation, eds. Cluster headache syndrome in general practice: Basic concepts. Smith-Gordon, 2000.

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Sears, Barry. Toxic fat: When good fat turns bad. Thomas Nelson, 2008.

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Kiess, W., Arya M. Sharma, Martin Wabitsch, and Claudio Maffeis. Metabolic syndrome and obesity in childhood and adolescence. Karger, 2015.

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von Dorsche, Herwig Hahn, Harald Schäfer, and Milan Titlbach. Histophysiology of the Obesity-Diabetes Syndrome in Sand Rats. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-78945-8.

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1927-, Schäfer Harald, and Titlbach Milan 1928-, eds. Histophysiology of the obesity-diabetes syndrome in sand rats. Springer-Verlag, 1994.

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Genazzani, Andrea R., Lourdes Ibáñez, Andrzej Milewicz, and Duru Shah, eds. Impact of Polycystic Ovary, Metabolic Syndrome and Obesity on Women Health. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63650-0.

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1933-, Simopoulos Artemis P., ed. Nutrition and fitness: Obesity, the metabolic syndrome, cardiovascular disease, and cancer. Karger, 2005.

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Book chapters on the topic "Syndromic obesity"

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Haqq, Andrea M. "Syndromic Obesity." In Pediatric Obesity. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-60327-874-4_4.

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Irizarry, Krystal A., and Andrea M. Haqq. "Syndromic Obesity." In Contemporary Endocrinology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68192-4_9.

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Nguyen, Molly X., Logan Danner, and Vidhu V. Thaker. "Syndromic and Monogenic Obesity." In Managing Pediatric Obesity Using Advanced Therapies. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-37380-0_13.

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Garcha, Shilpa Chugh, and Sanjay Kalra. "Anti-obesity Medications for Monogenic Syndromic Obesity." In Drugs for Medical Management of Obesity. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1651-0_5.

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Duis, Jessica, and Merlin G. Butler. "Monogenic and Syndromic Causes of Obesity." In Management of Prader-Willi Syndrome. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98171-6_4.

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Batsis, John A. "Sarcopenic Obesity." In Metabolic Syndrome. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-11251-0_38.

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Batsis, John A. "Sarcopenic Obesity." In Metabolic Syndrome. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12125-3_38-1.

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Gross, Danae C., Ray Cheever, and John A. Batsis. "Sarcopenic Obesity." In Metabolic Syndrome. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-40116-9_38.

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Gross, Danae C., Ray Cheever, and John A. Batsis. "Sarcopenic Obesity." In Metabolic Syndrome. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-319-12125-3_38-2.

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Mohammadi, Fatemeh, and Nima Rezaei. "Obesity Hypoventilation Syndrome." In Genetic Syndromes. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-319-66816-1_979-1.

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Conference papers on the topic "Syndromic obesity"

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Koleva, Ivet, Radoslav Yoshinov, and Borislav Yoshinov. "ELECTRONIC LIBRARY ON PHYSICAL THERAPY AND REHABILITATION OF METABOLIC SYNDROME AND OBESITY." In 19th International Technology, Education and Development Conference. IATED, 2025. https://doi.org/10.21125/inted.2025.1527.

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Savira, Maya, Rusdiana, Sry Suryani Widjaja, and M. Syahputra. "Comparison Malondialdehyde (MDA) Level between Obesity Non Metabolic Syndrome and Obesity with Metabolic Syndrome Patients." In International Conference of Science, Technology, Engineering, Environmental and Ramification Researches. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0010081806440647.

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Al-Qadi, Mazen O., Easa Al-Ghandour, Zeeshan Chauhan, Brian Casserly, and Franklin D. McCool. "Severity Of Sleep Apnea In Obesity Hypoventilation Syndrome And Simple Obesity." In American Thoracic Society 2011 International Conference, May 13-18, 2011 • Denver Colorado. American Thoracic Society, 2011. http://dx.doi.org/10.1164/ajrccm-conference.2011.183.1_meetingabstracts.a2234.

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Kadhim AL-SHEMERY, Maryam, Rusul Ali AL-MASAOODI, Fadhel Y KHUDHEYER, and Fatema M.Ali AL-KHAFAGE. "THE PREVALENCE OF METABOLIC SYNDROME DURING QUARANTINE PERIOD DUE COVID-19 PANDEMIC." In VI.International Scientific Congress of Pure,Applied and Technological Sciences. Rimar Academy, 2022. http://dx.doi.org/10.47832/minarcongress6-17.

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Obesity, dyslipidemia, and insulin resistance are a cluster of Metabolic syndrome. Also, stress and In Iraqi, the percentage of metabolic syndrome increased due to the risk of depression. The aim of this study was early prediction and diagnosis of the metabolic syndrome, in addition, to determine the effect of quarantine due to the CORONA-19 pandemic on metabolic syndrome in Iraq. We investigated the physiological origins of this clinical observation linking metabolic syndrome with severity and adverse outcome of COVID-19. This cross-sectional study was conducted during the period from April to June 2020 in Iraq. This clinic was chosen for data collection as it introduces medical advice for weight management for large geographical areas in Iraq with different socioeconomic populations. The samples tested were (156) samples which divided to the male group were (56) samples and female group (100) A consecutive sample of adult of both sexes aged 11 to 60 years (with inclusion/exclusion criteria) was collected on a daily basis throughout the study period The result in this study exhibit the percentage of the subject with obesity elevated during the COVID-19 pandemic period. Also, the results reveal a statistically significant increase in BMI, Blood pressure, and the blood sugar of subjects during quarantine periods in comparison with periods before the COVID-19 pandemic period. In conclusion: the potential mechanisms of Metabolic syndrome during quarantine are complex and may involve several shared physiological pathways, such as obesity, an increase in blood pressure, and glucose. The prevalence of metabolic syndrome increase during quarantine due to the COVID-19 pandemic related to changes in their environment, behavior, and lifestyles that cause stress and depression

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Prado, Vanildo, Daniel Buttros, Luciana Buttros de Paula, et al. "EVALUATION OF METABOLIC SYNDROME AND OBESITY IN BREAST CANCER SURVIVORS SUBJECTED TO INTERDISCIPLINARY APPROACH: A PROSPECTIVE COHORT STUDY." In Abstracts from the Brazilian Breast Cancer Symposium - BBCS 2021. Mastology, 2021. http://dx.doi.org/10.29289/259453942021v31s2081.

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Objective: The aim of this study was to assess the occurrence of metabolic syndrome (MetS), obesity, and abdominal obesity during the first year after a diagnosis of breast cancer. Methods: This prospective observational study included women with a recent diagnosis of breast cancer. Women aged ≥40 years, with a recent diagnosis of breast cancer, were included. The clinical, anthropometric, and biochemical analyses were performed. Women with three or more diagnostic criteria were considered with MetS as follows: waist circumference (WC) > 88 cm; triglycerides (TG) ≥150 mg/dL; high-density lipoprotein 30 kg/m2 and abdominal obesity with WC >88cm. The measurements were carried out in three moments: first medical assessment (T0m), six months (T6m), and 12 months later (T12m). All patients underwent the interdisciplinary assessment (i.e., nutritional and psychological) at T0m. For statistical analysis, the ANOVA with repeated measures and the chi-square test of trend were used. Results: A total of 72 women with breast cancer were included, with a mean age of 58.4±10.7 years. In the assessment of MetS, BMI, and WC, no difference was observed in the occurrence between the three moments. When comparing the individual metabolic syndrome criteria between the three moments, there was only a statistical difference in the TG and glycemia criteria. The analysis of blood glucose showed a decrease in mean values, with a value of 106.6 mg/dL-T0m, 100.46 mg/dL-T6m, and 98.96 mg/dL-T12m (p=0.004). Regarding TG, an increase in mean values was observed, with a value of 121 mg/dL-T0m, 139.4 mg/dL-T6m, and 148.46 mg/dL-T12m (p=0.003). No cancer treatment showed an impact on the measured criteria. Conclusion: The interdisciplinary approach on the breast cancer survivors demonstrated a positive impact on the control of metabolic syndrome, obesity, and abdominal obesity on the first year of follow-up. Additionally, glycemic indices showed a significant decrease, but an increase in TG values was observed.

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Viégas, Jéssica de Vasconcelos Oliveira, Tainá Rodrigues Toqueton, Délio Guerra Drummond Júnior, et al. "Clinical treatment of metabolic syndrome in pregnant women." In II SEVEN INTERNATIONAL MEDICAL AND NURSING CONGRESS. Seven Congress, 2023. http://dx.doi.org/10.56238/iicongressmedicalnursing-022.

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Metabolic syndrome is a medical condition characterized by a set of cardiovascular risk factors, including obesity, hypertension, insulin resistance, and dyslipidemia. During pregnancy, a woman's body undergoes complex metabolic and hormonal changes to facilitate fetal development. However, when the pregnant woman has metabolic syndrome, these changes can be exacerbated, increasing the risk of serious obstetric complications and having a potential impact on maternal-fetal health.

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Grech, Vasiliki Sofia, Kleomenis Lotsaris, Ioanna Grech, Vasiliki Kefala, and Efstathios Rallis. "Semaglutide (Ozempic) and obesity. A comprehensive guide for aestheticians." In 1st Conference of the Hellenic Scientific Society of Aesthetics. PHARMAKON-Press, 2024. http://dx.doi.org/10.61873/rjdb1796.

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Obesity is a complex interplay of biological, genetic, behavioural, and environmental factors. Going beyond the con- ventional Body Mass Index (BMI) evaluation, the complex relationship between obesity and skin diseases unveils the evolving role of aesthetics in health promotion. Adipose tissue, traditionally seen as an energy reservoir, is unveiled as a dynamic endocrine organ, playing a crucial role in the pathophysiological mechanisms of insulin resistance and metabolic syndrome. This article navigates the skin-deep impact of obesity and unravelling its influence on dermato- logical challenges. From disrupted epidermal barriers to diseases such as psoriasis and hidradenitis suppurativa, it further explores how licensed cosmetologists emerge as health advocates. For what is more, semaglutide, a ground- breaking GLP-1 agonist, takes the spotlight, tracing its journey from FDA approval for type 2 diabetes to its recent endorsement for obesity. The article examines its mechanism, efficacy, and unintended consequences of popularity, emphasizing the need for responsible medication use.

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Arisanti, Yuli, and Janri Manullang. "The Obesity Prevalence in Navy Personal and Civil Servants at Lantamal X Jayapura." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.01.29.

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ABSTRACT Background: Central (visceral) obesity, one of the risk factors of metabolic syndrome, is becoming the major public health concern of non-communicable diseases. Predictions estimated that by 2030, 50% of adults will be listed as obese. This study aimed to examine smoking and exercise as the risk factors of central obesity in navy personal and civil servants at Lantamal X Jayapura. Subjects and Method: This was a cross sectional study conducted from November to December 2017 at Lantamal X Jayapura, Indonesia. A sample of 100 navy personal and civil servants was selected by random sampling. The dependent variable was central obesity. The independent variables were smoking and exercise. Waist circumference was measured by metline. The other variables were collected by questionnaires. Data were analyzed by Chi square. Results: The risk of central obesity increased with smoking (OR= 3.13; 95% CI= 1.63 to 5.98; p<0.001) and duration of exercise less than 60 minute per week (OR= 2.49; 95% CI= 1.14 to 5.40; p= 0.017). Conclusion: Risk of central obesity increases with smoking and duration of exercise. Keywords: central obesity, smoking, exercise, navy personal, civil servants Correspondence: Yuli Arisanti. National Institute of Health Research and Development Papua. Jl. Ahmad Yani No. 48, Gurabesi, Jayapura Utara. Email: yuliarisanti88@gmail.com. Mobile: +6281248978639. DOI: https://doi.org/10.26911/the7thicph.01.29

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Terla, V., G. L. Rajbhandari, D. Kurian, and G. R. Pesola. "Right Heart Dysfunction Secondary to Obesity Hypoventilation Syndrome." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a6784.

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Palmer, Kieran, Peter S. P. Cho, Rebecca A. Lyall, Amit S. Patel, and Kai K. Lee. "Screening for obesity hypoventilation syndrome in bariatric patients." In ERS International Congress 2020 abstracts. European Respiratory Society, 2020. http://dx.doi.org/10.1183/13993003.congress-2020.229.

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Reports on the topic "Syndromic obesity"

1

Wang, Rui, Guanghua Chen, Xuan Zhang, Cheng Li, and Yonghua Chen. The effect of bariatric surgery on pancreas fat accumulation: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.4.0072.

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Review question / Objective: This systematic review and meta-analysis aimed to assess the effect of bariatric surgery on pancreas fat accumulation. Condition being studied: Pancreatic steatosis is characterized by increased accumulation of fat in the pancreas. The most common causes are obesity and metabolic syndrome. Due to this close association between obesity and metabolic syndrome, one can assume that, in addition to a rapid and sustained weight loss, bariatric surgery could affect metabolic syndrome and its components. However, it remains unclear whether bariatric surgery and weight loss can reverse abnormalities in pancreatic lipid metabolism in association with their effect on endocrine pancreatic dysfunction. This systematic review and meta-analysis aimed to measure the change of pancreatic fat in a group of patients with severe obesity before and after bariatric surgery.

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Rubin, Daniela A., daniel A. Judelson, Daniel J. Driscoll, Michelle Moutappa, and Jie Weiss. Nutritional and Exercise Aspects of Prader-Willi Syndrome and Childhood Obesity. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada585349.

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