Differences in metabolic characteristics between Metabolically Healthy Obesity (MHO) and Metabolically Unhealthy Obesity (MUO) in weight reduction therapy.

Metabolically Healthy Obesity (MHO) is generally recognized as the absence of any metabolic disorders and cardiovascular diseases, including type 2 diabetes, dyslipidemia, and hypertension, in obese individuals; however, it is not clearly defined. Therefore, the present study investigated differences in metabolic characteristics between individuals with MHO and Metabolically Unhealthy Obesity (MUO) during weight reduction therapy. The key factors defining MHO and the importance of weight reduction therapy for MHO were also examined. Cohort data from the Japan Obesity and Metabolic Syndrome (JOMS) study were analyzed. Subjects were divided into the MHO (n = 25) and MUO (n = 120) groups. Prior to weight reduction therapy, serum adiponectin levels were significantly higher in the MHO group than in the MUO group. Serum adiponectin levels also negatively correlated with the area of subcutaneous adipose tissue (SAT) and Homeostasis model assessment (HOMA)-R in the MHO group, but not in the MUO group. Collectively, the present results suggest the importance of adiponectin for maintaining metabolic homeostasis in the MHO group. On the other hand, no significant differences were observed in inflammatory markers between the MHO and MUO groups, suggesting the presence of chronic inflammation in both groups. Furthermore, a positive correlation was noted between changes in serum cystatin C levels and waist circumference in the MHO group, which indicated that despite the absence of metabolic disorders, the MHO group exhibited anti-inflammatory responses during weight reduction therapy. These results underscore the significance of weight reduction even for individuals with MHO.

Does metabolically healthy obesity exist? A 32-year-old man with BMI 78 kg/m2 - to treat or not to treat?

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Metabolically Healthy Obesity (MHO)-New Research Directions for Personalised Medicine in Cardiovascular Prevention.

PURPOSE OF REVIEW: To discuss new findings on the heterogeneity of obesity and associated risks. RECENT FINDINGS: Obesity is a public health problem of immense importance on a global scale. However, epidemiological findings and clinical studies have revealed that obesity is a heterogeneous phenotype and that not all obese subjects run the same risk for complications. Current research has tried to describe so-called metabolically healthy obesity (MHO), defined by lack of risk factors included in the metabolic syndrome. These subjects will not escape long-term complications, but mortality risk is not increased. However, a new definition of MHO has recently been proposed, based on the lack of hospitalisation for somatic disease for decades in middle life. MHO subjects defined in this way are characterised by being "fat and fit" and also run a lower risk of long-term complications. If MHO could be better understood, this could contribute to a more diverse clinical approach to obesity based on personalised medicine.

Effects of a long-term lifestyle intervention on metabolically healthy women with obesity: Metabolite profiles according to weight loss response.

BACKGROUND & AIMS: The benefits of weight loss in subjects with metabolically healthy obesity (MHO) are still a matter of controversy. We aimed to identify metabolic fingerprints and their associated pathways that discriminate women with MHO with high or low weight loss response after a lifestyle intervention, based on a hypocaloric Mediterranean diet (MedDiet) and physical activity. METHODS: A UPLC-Q-Exactive-MS/MS metabolomics workflow was applied to plasma samples from 27 women with MHO before and after 12 months of a hypocaloric weight loss intervention with a MedDiet and increased physical activity. The subjects were stratified into two age-matched groups according to weight loss: <10% (low weight loss group, LWL) and >10% (high weight loss group, HWL). Random forest analysis was performed to identify metabolites discriminating between the LWL and the HWL as well as within-status effects. Modulated pathways and associations between metabolites and anthropometric and biochemical variables were also investigated. RESULTS: Thirteen metabolites discriminated between the LWL and the HWL, including 1,5-anhydroglucitol, carotenediol, 3-(4-hydroxyphenyl)lactic acid, N-acetylaspartate and several lipid species (steroids, a plasmalogen, sphingomyelins, a bile acid and long-chain acylcarnitines). 1,5-anhydroglucitol, 3-(4-hydroxyphenyl)lactic acid and sphingomyelins were positively associated with weight variables whereas N-acetylaspartate and the plasmalogen correlated negatively with them. Changes in very long-chain acylcarnitines and hydroxyphenyllactic levels were observed in the HWL and positively correlated with fasting glucose, and changes in levels of the plasmalogen negatively correlated with insulin resistance. Additionally, the cholesterol profile was positively associated with changes in acid hydroxyphenyllactic, sphingolipids and 1,5-AG. CONCLUSIONS: Higher weight loss after a hypocaloric MedDiet and increased physical activity for 12 months is associated with changes in the plasma metabolome in women with MHO. These findings are associated with changes in biochemical variables and may suggest an improvement of the cardiometabolic risk profile in those patients that lose greater weight. Further studies are needed to investigate whether the response of those subjects with MHO to this intervention differs from those with unhealthy obesity.

Association of Concurrent Changes in Metabolic Health and Weight on Cardiovascular Disease Risk: A Nationally Representative Cohort Study.

Background The combined effect of transitions of metabolic health and weight on cardiovascular disease (CVD) remains unclear. We aimed to examine the association of concurrent changes of metabolic health and weight on CVD over time. Methods and Results The study population consisted of 205 394 from the Korean National Health Insurance Service. Metabolic health was determined by fasting serum glucose, total cholesterol, and blood pressure levels, while obesity was determined by body mass index. All participants were divided into either metabolically healthy nonobese (MHNO), metabolically healthy obese, metabolically unhealthy nonobese, or metabolically unhealthy obese for each of the first (2002-2003) and second (2004-2005) health screening periods, after which participants were followed-up for CVD from 2006 to 2015. Cox proportional hazards regression was used to determine adjusted hazard ratios (aHRs) and 95% CIs. Among initial MHNO participants, those who became metabolically healthy obese (aHR, 1.25; 95% CI, 1.10-1.41), metabolically unhealthy nonobese (aHR, 1.23; 95% CI, 1.15-1.31), and metabolically unhealthy obese (aHR, 1.34; 95% CI, 1.12-1.61) had elevated risk for CVD compared with those who remained MHNO. Conversely, improving metabolic health and obesity were associated with reduced CVD risk among initially metabolically unhealthy nonobese to secondary MHNO (aHR, 0.79; 95% CI, 0.73-0.84), metabolically unhealthy obese to MHNO (aHR, 0.68; 95% CI, 0.58-0.81), and metabolically unhealthy obese to metabolically healthy obese (aHR, 0.73; 95% CI, 0.66-0.80) participants. Conclusions Changes toward metabolically unhealthy or obese states resulted in increased CVD risk. Improving metabolic health along with reducing weight may lead to decreased risk of CVD.

Metabolically healthy versus metabolically unhealthy obesity.

Obesity-related disease complications reduce life quality and expectancy and increase health-care costs. Some studies have suggested that obesity not always entails metabolic abnormalities and increased risk of cardiometabolic complications. Because of the lack of universally accepted criteria to identify metabolically healthy obesity (MHO), its prevalence varies widely among studies. Moreover, the prognostic value of MHO is hotly debated, mainly because it likely shifts gradually towards metabolically unhealthy obesity (MUO). In this review, we outline the differential factors contributing to the metabolic heterogeneity of obesity by discussing the behavioral, genetic, phenotypical, and biological aspects associated with each of the two metabolic phenotypes (MHO and MUO) of obesity and their clinical implications. Particular emphasis will be laid on the role of adipose tissue biology and function, including genetic determinants of body fat distribution, depot-specific fat metabolism, adipose tissue plasticity and, particularly, adipogenesis. Finally, the emerging role of gut microbiota in obesity and adipose tissue dysfunction as well as the search for novel biomarkers for the obesity-related metabolic traits and associated diseases will be briefly presented. A better understanding of the main determinants of a healthy metabolic status in obesity would allow promotion of this favorable condition by targeting the relevant pathways.

The relationship between adiposopathy and glucose-insulin homeostasis is not affected by moderate-intensity aerobic training in healthy women with obesity

The contribution of adiposopathy to glucose-insulin homeostasis remains unclear. This longitudinal study examined the potential relationship between the adiponectin/leptin ratio (A/L, a marker of adiposopathy) and insulin resistance (IR: homeostasis model assessment (HOMA)), insulin sensitivity (IS: Matsuda), and insulin response to an oral glucose tolerance test before and after a 16-week walking program, in 29 physically inactive pre- and postmenopausal women with obesity (BMI, 29-35 kg/m2; age, 47-54 years). Anthropometry, body composition, VO2max, and fasting lipid-lipoprotein and inflammatory profiles were assessed. A/L was unchanged after training (p = 0.15), despite decreased leptin levels (p < 0.05). While the Matsuda index tended to increase (p = 0.07), HOMA decreased (p < 0.05) and fasting insulin was reduced (p < 0.01) but insulin area under the curve (AUC) remained unchanged (p = 0.18) after training. Body fatness and VO2max were improved (p < 0.05) while triacylglycerols increased and HDL-CHOL levels decreased after training (p < 0.05). At baseline, A/L was positively associated with VO2max, HDL-CHOL levels, and Matsuda (0.37 < ρ < 0.56; p < 0.05) but negatively with body fatness, HOMA, insulin AUC, IL-6, and hs-CRP levels (− 0.41 < ρ < − 0.66; p < 0.05). After training, associations with fitness, HOMA, and inflammation were lost. Multiple regression analysis revealed A/L as an independent predictor of IR and IS, before training (partial R2 = 0.10 and 0.22), although A/L did not predict the insulin AUC pre- or post-intervention. A significant correlation was found between training-induced changes to A/L and IS (r = 0.38; p < 0.05) but not with IR or insulin AUC. Although changes in the A/L ratio could not explain improvements to glucose-insulin homeostasis indices following training, a relationship with insulin sensitivity was revealed in healthy women with obesity

An Overview and Update on Obesity and the Obesity Paradox in Cardiovascular Diseases.

Obesity increases a number of cardiovascular disease (CVD) risk factors, but patients with many types of CVD may have a better prognosis if classified as overweight or obese, a phenomenon known as the "obesity paradox". This paradoxical benefit of a medically unfavorable phenotype is particularly strong in the overweight and class I obesity, and less pronounced in the more severe or morbidly obese populations (class II-III and greater). Rather than an obesity paradox, it is possible that this phenomenon may represent a "lean paradox", in which individuals classified as normal weight or underweight may have a poorer prognosis with respect to CVD, as a result of a progressive catabolic state and lean mass loss. Cardiorespiratory fitness (CRF) is a fundamental part of this discussion. A greater CRF is associated with lower CVD risk, regardless of body mass index (BMI). Also, the assessment of body composition compartments (i.e., fat mass, fat-free mass, lean mass) and the presence of metabolic derangements may be better indicators of CVD risk than BMI alone. The focus of this review is to summarize the current evidence of the obesity paradox. Moreover, we discuss the utility and limitations of BMI for cardiometabolic risk stratification, in addition to concepts such as "metabolically healthy obesity" (MHO) and the "fat but fit" phenomenon, which describe patients who are diagnosed with obesity using BMI, but without major metabolic derangements and with greater CRF, respectively. Finally, we propose that obese patients presenting with an excess body fat, yet without metabolic abnormalities, should still be viewed as an "at risk" population, and as such should receive advice to change their lifestyle to improve their CRF and to prevent the development of impaired fasting glucose, diabetes mellitus and other CVD risk factors as a form of primary prevention.

Obesity and Kidney Disease.

Obesity is a systemic disease of the white adipose tissue, which has evolved into a global epidemic. It is associated with a plethora of adipocyte hormonal (adipokine) imbalances, dysregulation of the energy-balance system, imbalances in metabolic homeostasis, a pro-inflammatory state and multiple target organ damages. Clinically, the obesity phenotype is not homogenous and is more likely to represent a spectrum with varying degrees of metabolic un-health; metabolically-unhealthy obesity is often a part of the metabolic syndrome. The links between obesity and chronic kidney disease are numerous, bidirectional, multi-layered and complex; this complexity may be explained by shared pathophysiological pathways (e.g. chronic inflammation, increased oxidative stress, and hyper-insulinemia), shared clusters of risk factors as well as associated diseases (e.g. insulin resistance, hypertension and dyslipidemia). We will review these links and their clinical manifestations, and offer a summary of available non-pharmacological as well as pharmacological therapeutic strategies.

Obesity and the Obesity Paradox in Heart Failure.

Obesity continues to be a public health problem in the general population, and also significantly increases the risk for the development of new-onset heart failure (HF). However, in patients with already-established, chronic HF, overweight and mild to moderate obesity is associated with substantially improved survival compared to normal weight patients; this has been termed the "obesity paradox". The majority of studies measure obesity by body mass index, but studies utilizing less-frequently used measures of body fat and body composition, including waist circumference, waist-hip ratio, skinfold estimates, and bioelectrical impedance analysis also confirm the obesity paradox in HF. Other areas of investigation such as the relationship of the obesity paradox to cardiorespiratory fitness, gender, and race are also discussed. Finally, this review explores various explanations for the obesity paradox, and summarizes the current evidence for intentional weight loss treatments for HF in context.

The relationship between adiposopathy and glucose-insulin homeostasis is not affected by moderate-intensity aerobic training in healthy women with obesity.

The contribution of adiposopathy to glucose-insulin homeostasis remains unclear. This longitudinal study examined the potential relationship between the adiponectin/leptin ratio (A/L, a marker of adiposopathy) and insulin resistance (IR: homeostasis model assessment (HOMA)), insulin sensitivity (IS: Matsuda), and insulin response to an oral glucose tolerance test before and after a 16-week walking program, in 29 physically inactive pre- and postmenopausal women with obesity (BMI, 29-35 kg/m2; age, 47-54 years). Anthropometry, body composition, VO2max, and fasting lipid-lipoprotein and inflammatory profiles were assessed. A/L was unchanged after training (p = 0.15), despite decreased leptin levels (p < 0.05). While the Matsuda index tended to increase (p = 0.07), HOMA decreased (p < 0.05) and fasting insulin was reduced (p < 0.01) but insulin area under the curve (AUC) remained unchanged (p = 0.18) after training. Body fatness and VO2max were improved (p < 0.05) while triacylglycerols increased and HDL-CHOL levels decreased after training (p < 0.05). At baseline, A/L was positively associated with VO2max, HDL-CHOL levels, and Matsuda (0.37 < ρ < 0.56; p < 0.05) but negatively with body fatness, HOMA, insulin AUC, IL-6, and hs-CRP levels (- 0.41 < ρ < - 0.66; p < 0.05). After training, associations with fitness, HOMA, and inflammation were lost. Multiple regression analysis revealed A/L as an independent predictor of IR and IS, before training (partial R2 = 0.10 and 0.22), although A/L did not predict the insulin AUC pre- or post-intervention. A significant correlation was found between training-induced changes to A/L and IS (r = 0.38; p < 0.05) but not with IR or insulin AUC. Although changes in the A/L ratio could not explain improvements to glucose-insulin homeostasis indices following training, a relationship with insulin sensitivity was revealed in healthy women with obesity.

"Metabolically Healthy" Obesity: Fact or Threat?

INTRODUCTION: Obesity is a serious, worldwide and growing problem, with associated complications ranging from cardiovascular disease to cancer. It has been suggested that a subgroup of obese patients- the "metabolically healthy" (MH)- would constitute a phenotype whose cardiovascular risk would be closer to that of normal weight individuals and lower than that of obese patients with other risk factors. The definitions of MH obesity are heterogeneous, what makes the estimation of its prevalence quite difficult. Besides that, data are still controversial about the risk of incident cardiovascular disease in these patients and therefore this remains an unresolved matter. In parallel, the possibly lower risk of MH obesity may raise questions about the need for weight loss in MH obese patients. CONCLUSION: This issue should be carefully addressed, and evidence for a "benign" profile of MH obesity critically evaluated, as obesity is a risk factor for numerous health outcomes, and weight loss in obese people additionally offers protection against these nonmetabolic diseases.

The design and rationale of an interdisciplinary, non-prescriptive, and Health at Every Size®-based clinical trial: The "Health and Wellness in Obesity" study.

BACKGROUND: This manuscript describes the design and rationale of a clinical trial that aims to investigate the multiple physiological, attitudinal, nutritional, and behavioral effects of a new interdisciplinary intervention based on the Health at Every Size® (HAES®) approach in obese women. METHODS: This will be a prospective, 7-month, randomized (2:1), mixed-method clinical trial. Obese women will be recruited and randomly allocated into two groups. The intervention group (I-HAES®; proposed n = 40) will undertake a novel HAES®-based intervention. Participants will take part in an exercise program, nutrition counseling sessions, and philosophical workshops, all aligned with the principles of the HAES® approach. The control group (CTRL; proposed n = 20) will participate in a program using a traditional HAES®-based group format, characterized by bimonthly lectures about the same topics offered to the experimental group, encouraging the adoption of a healthy lifestyle. The following multiple quantitative outcomes will be assessed pre and post intervention: health-related quality of life, cardiovascular risk factors, anthropometric assessments, physical activity level, physical capacity and function, and psychological and behavioral assessments. Qualitative analysis will be used to evaluate the experiences of the participants throughout the intervention, as assessed by focus groups and semi-structured interviews. CONCLUSIONS: The interdisciplinary research team leading this study has varied and complementary expertise. The knowledge arising from this study will help to guide new interdisciplinary interventions with the potential to holistically improve the health of obese individuals. This trial is registered at Clinicaltrials.gov (NCT02102061).

Text messaging (SMS) as a tool to facilitate weight loss and prevent metabolic deterioration in clinically healthy overweight and obese subjects: a randomised controlled trial.

OBJECTIVE: To examine whether SMS text messaging facilitates a reduction of weight and waist circumference (WC) and favourable changes in lipid profile and insulin levels in clinically healthy overweight and obese subjects. DESIGN: A randomised controlled trial. SETTING AND INTERVENTION: Primary care health centre in Riga, Latvia. Text messaging once in two weeks. SUBJECTS: A total of 123 overweight and obese men and women aged 30-45 years with no cardiovascular diseases (CVDs) or diabetes. MAIN OUTCOME MEASURES: changes in anthropometric parameters (weight, WC, body mass index (BMI)) and biochemical parameters (lipids, fasting glucose and insulin). RESULTS: We found a statistically significant decrease in weight (2.4%), BMI and WC (4.8%) in the intervention group, while the control group showed a statistically non-significant increase in weight and BMI and decrease in WC. Between group results obtained over the course of a year showed statistically significant mean differences between weight (-3.4 kg (95% CI -5.5, -1.3)), BMI kg/m2 (-1.14 (95% CI -1.9, -0.41)), WC (-4.6 cm (95% CI -6.8, -2.3)), hip circumference (-4.0 cm (95% CI -5.9, -2.0)) and fasting insulin (2.43 µU/ml (95% CI 0.6, 4.3)). Mean differences of changes in glucose and lipid levels were statistically non significant: fasting glucose (-0.01 mmol/l (95% CI -0.19, 0.17)), TC mmol/l (-0.04 mmol/l (95% CI -0.29, 0.21)), HDL-C (0.14 mmol/l (95% CI -0.65, 0.09)), LDL-C (-0.02 mmol/l (95% CI -0.22, 0.18)) and TG (0.23 mmol/l (95% CI -0.06, 0.52)). CONCLUSIONS: SMS messaging in clinically healthy overweight and obese subjects facilitates a slight decrease in weight, BMI and WC. It is anticipated that the implications of this strategy might facilitate the design of preventive and promotive strategies among high risk groups in Latvia.

The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: A PRISMA-compliant article.

BACKGROUND: We conducted a systematic review and meta-analysis to firstly obtain a reliable estimation of the prevalence of metabolically healthy obese (MHO) individuals in obesity, then assessed the risk of developing metabolic abnormalities (MA) among MHO individuals. At last, we evaluated the effects of traditional lifestyle interventions on metabolic level for MHO subjects. METHODS: A systematic review and meta-analysis (PRISMA) guideline were conducted, and original studies were searched up to December 31, 2016. The prevalence of MHO in obesity from each study was pooled using random effects models. The relative risks (RRs) were pooled to determine the risk of developing MA for MHO compared with metabolically healthy normal-weight (MHNW) subjects. For the meta-analysis of intervention studies, the mean difference and standardized mean differences were both estimated for each metabolic parameter within each study, and then pooled using a random-effects model. RESULTS: Overall, 40 population-based studies reported the prevalence of MHO in obesity, 12 cohort studies and 7 intervention studies were included in the meta-analysis. About 35.0% obese individuals were metabolically healthy in the obese subjects. There were dramatic differences in the prevalence among different areas. However, 0.49 (95% confidence intervals [CI]: 0.38 to 0.60) of the MHO individuals would develop one or more MA within 10 years. Compared with MHNW subjects, the MHO subjects presented higher risk of incident MA (pooled RR = 1.80, 95%CI: 1.53-2.11). Following intervention, there was certain and significant improvement of metabolic state for metabolically abnormal obesity (MAO) subjects. Only diastolic blood pressure had reduced for MHO individuals after intervention. CONCLUSIONS: Almost one-third of the obese individuals are in metabolic health. However, they are still at higher risk of advancing to unhealthy state. Therefore, it is still needed to advise MHO individuals to maintain or adopt a healthy lifestyle, so as to counterbalance the adverse effects of obesity.

Natural Course of Metabolically Healthy Overweight/Obese Subjects and the Impact of Weight Change.

Few studies have described the characteristics of metabolically healthy individuals with excess fat in the Chinese population. This study aimed to prospectively investigate the natural course of metabolically healthy overweight/obese (MH-OW/OB) adults, and to assess the impact of weight change on developing metabolic abnormalities. During 2009-2010, 525 subjects without any metabolic abnormalities or other obesity-related diseases were evaluated and reevaluated after 5 years. The subjects were categorized into two groups of overweight/obese and normal weight based on the criteria of BMI by 24.0 at baseline. At follow-up, the MH-OW/OB subjects had a significantly increased risk of developing metabolically abnormalities compared with metabolically healthy normal-weight (MH-NW) individuals (risk ratio: 1.35, 95% confidence interval: 1.17-1.49, p value < 0.001). In the groups of weight gain and weight maintenance, the MH-OW/OB subjects was associated with a larger increase in fasting glucose, triglycerides, systolic blood pressure, diastolic blood pressure and decrease in high-density lipoprotein cholesterol comparing with MH-NW subjects. In the weight loss group, no significant difference of changes of metabolic parameters was observed between MH-OW/OB and MH-NW adults. This study verifies that MH-OW/OB are different from MH-NW subjects. Weight management is needed for all individuals since weight change has a significant effect on metabolic health without considering the impact of weight change according to weight status.

Estimation of energy expenditure using prediction equations in overweight and obese adults: a systematic review.

BACKGROUND: Estimates of energy requirements are needed in weight management and are usually determined using prediction equations. The objective of these two systematic reviews was to identify which equations based on simple anthropometric and demographic variables provide the most accurate and precise estimates of (1) resting energy expenditure (REE) and (2) total energy expenditure (TEE) in healthy obese adults. METHODS: Systematic searches for relevant studies in healthy adults with body mass index (BMI) ≥25 kg m(-2) and published in English were undertaken using Cinahl, Cochrane Library, OpenGrey, PubMed and Web of Science (completed March 2014). Search terms included metabolism, calorimetry, obesity and prediction equations. Data extraction, study appraisal and synthesis followed guidelines from PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses). RESULTS: From 243 REE papers and 254 TEE papers identified, 21 and four studies, respectively, met the inclusion criteria. (1) The most accurate REE predictions varied with BMI subgroup: WHO (weight and height) ≥25 and ≥30 kg m(-2) ; Mifflin 30-39.9 kg m(-2) ; Henry ≥40 kg m(-2) . The most precise REE predictions were obtained using Mifflin in BMI 30-39.9 and ≥40 kg m(-2) , where approximately 75% of predictions were within 10% of measured REE. (2) No accurate or precise predictions of TEE were identified. CONCLUSIONS: No single prediction equation provides accurate and precise REE estimates in all obese adults. Mifflin equations are recommended in this population, although errors exceed 10% in 25% of those assessed. There is no evidence to support the use of prediction equations in estimating TEE in obesity.

Metabolically Healthy Obesity: Personalised and Public Health Implications.

Obesity is a heterogeneous condition; thus, metabolic abnormalities and cardiometabolic risk vary among obese individuals, with a significant proportion considered to be metabolically healthy. However, whether these individuals are truly healthy remains controversial and, therefore, a better understanding of such phenotypes may offer opportunities to improve current obesity diagnosis, intervention, and treatment.