Prevalence and clinical profile of metabolic obesity and phenotypic obesity in Asian Indians

The prevalence of metabolically healthy obesity and healthy status and related risk factors among Iranian adults: a cohort-based cross-sectional study

Objectives

this study aims to determine the prevalence and determinants of metabolically healthy obesity (MHO) and metabolically healthy status (MHS) within a large Iranian population.

Methods

This cross-sectional study involved 10,134 participants from the Fasa Adult Cohort Study (FACS) in southern Iran. Following the extraction of metabolic, demographic, and socioeconomic variables, prevalence rates were estimated. Logistic regression analysis was conducted using SPSS 22 to examine the relationship between risk factors.

Results

Among all participants, 19.9% (32.7% in men) exhibited metabolically healthy status (MHS), while 31.4% (37.5% in men) were classified as metabolically healthy obese (MHO). The likelihood of MHO was found to be 18% higher in illiterate individuals compared to their literate counterparts. Additionally, for each 1 cm increase in waist circumference, the probability of MHO increased by 5%, while a 1-year increase in age raised the probability by 1.7%, and a 1 MET increase in physical activity reduced the probability by 1.3%. Furthermore, the likelihood of having MHS was 2.4 times greater in women than in men. Employed individuals had a 17% lower probability of MHS compared to unemployed individuals. For every 1 MET increase in physical activity, the probability of MHS decreased by 0.9%, whereas a 1-year increase in age and a 1 cm increase in waist circumference increased the probability by 1.7% and 12%, respectively.

Conclusions

It seems that MHS and MHO is relatively high in studied population and although their multifactorial nature was determined, at the same time, in order to evaluate the changes, it is necessary to pay serious attention to longitudinal monitoring.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01555-8.

Metabolically healthy overweight/obesity with no metabolic abnormalities and incident hyperglycaemia in Chinese adults: analysis of a retrospective cohort study

OBJECTIVES

To explore whether metabolically healthy overweight (MHOW) and/or metabolically healthy obesity (MHO) increase hyperglycaemia risk in a Chinese population with a broad age range.

DESIGN

Retrospective cohort study.

SETTING

Secondary analysis of data from the DATADRYAD database, comprising health check records of participants from 32 regions and 11 cities in China between 2010 and 2016.

PARTICIPANTS

A total of 47 391 metabolically healthy participants with none of the metabolic abnormalities were selected.

OUTCOME MEASURES

Hyperglycaemia includes incident diabetes and impaired fasting glucose (IFG). Diabetes was diagnosed with fasting blood glucose ≥7.0 mmol/L and typical clinical symptoms and/or on self-report during follow-up. The fasting plasma glucose level of IFG was from 5.6 to 6.9 mmol/L.

RESULTS

With an average follow-up of 3.06 years, 5274 participants (11.13%) developed hyperglycaemia over 144 804 person-years, with an incidence rate of 36.42 per 1000 person-years. Adjusted model revealed a higher risk of incident hyperglycaemia in the MHOW group (HR=1.23, 95% CIs 1.16 to 1.30) and the MHO group (HR=1.49, 95% CI 1.33 to 1.67) compared with the metabolically healthy normal weight group. With 1 unit increase of body mass index, the risk of hyperglycaemia increased by 6% (HR=1.06, 95% CI 1.04 to 1.07). The stratified analyses and interaction tests showed the robustness of the association, and there was a stronger association in women (p for interaction<0.001).

CONCLUSIONS

The MHOW and MHO phenotypes were positively associated with a higher risk of hyperglycaemia in this population, and the association was particularly stronger in women.

Protective Effects of Sulforaphane Preventing Inflammation and Oxidative Stress to Enhance Metabolic Health: A Narrative Review

The worldwide obesity epidemic has led to a drastic increase in diabetes and cardiovascular disease in younger generations. Further, maintaining metabolic health during aging is frequently a challenge due to poor diets and decreased mobility. In this setting, bioactive nutrients that are naturally occurring antioxidants, such as sulforaphane (SFN), are of high nutritional interest. SFN, a bioactive compound that is present in cruciferous vegetables, is a molecule that protects cells from cytotoxic damage and mitigates oxidative stress, protecting against disease. It exerts its action through the activation of the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2). Many studies have been performed in animals and humans to evaluate its effects on cancer, brain health, and neurodegenerative disorders. However, fewer clinical studies have been performed to evaluate its effects on insulin resistance and the development of type 2 diabetes mellitus (T2DM) across the lifespan. Given that, in some parts of the world, particularly in Europe, the population is growing older at a significant rate, it is crucial to promote healthy habits (healthy foods, dietary pattern, precision nutrition, and physical activity) from an early stage in life and across the lifespan to avoid debilitating health conditions occurring during adulthood and aging. Thus, in this narrative review, we discuss the protective effects of SFN supplementation on inflammatory and oxidative stress pathways and relate them to metabolic disease.

Central and Peripheral Sensitivity to Thyroid Hormones Correlate to Metabolically Obesity Phenotypes in Chinese Euthyroid Adults: A Cross-Sectional Study

AIMS

Thyroid hormones impact lipid metabolism and glucose homoeostasis through both central and peripheral regulation; however, little research has delved into the association between thyroid hormone sensitivity and metabolically obese phenotypes. We aimed to investigate the correlation between indices of central and peripheral sensitivity to thyroid hormones and metabolically obese phenotypes in euthyroid Chinese adults.

METHODS

This cross-sectional study included 20,084 euthyroid individuals. Central thyroid hormone sensitivity was assessed using the thyroid feedback quantile-based index (TFQI), parametric thyroid feedback quantile-based index (PTFQI), thyroid-stimulating hormone index (TSHI), and thyrotropin thyroxine resistance index (TT4RI), while peripheral thyroid hormone sensitivity was measured by FT3/FT4. Metabolically obesity phenotypes included metabolically healthy non-obesity (MHNO), unhealthy non-obesity (MUNO), metabolically healthy obesity (MHO), and unhealthy obesity (MUO). Multinomial logistic regression and restricted cubic spline analyses were conducted to investigate the association between thyroid hormone sensitivity indices and metabolically obese phenotypes risk. Subgroup analysis was also performed to examine this association stratified by sex and age. Mediation analysis was performed to estimate direct and indirect effects of BMI.

RESULTS

Prevalence of MHNO, MUNO, MHO and MUO was 66.1% (n = 13,273), 21.3% (n = 4271), 5.3% (n = 1055), and 7.4% (n = 1485) respectively. After adjustment for potential confounders, the odds ratios (ORs) (95% CI) for MUNO and MUO were increased with all elevated thyroid hormones sensitivity indices (per SD increase) [MUNO: TFQI 1.14(1.09-1.19), PTFQI 1.18(1.23-1.23); TSHI 1.26(1.19-1.33), TT4RI 1.41, (1.31-1.53), FT3/FT4 1.20(1.14-1.25) and [MUO: TFQI 1.20(1.11-1.31), PTFQI 1.26(1.16-1.37), TSHI 1.39 (1.26-1.54), TT4RI 1.70(1.48-1.95), FT3/FT4 1.26 (1.16-1.37)] (p value < 0.001), and only TSHI and TT4RI (per SD increase) significantly increased the risk of MHO (TSHI: OR = 1.12, 95% CI 1.01-1.24; TT4RI: OR = 1.25, 95%CI 1.08-1.4) (p value < 0.05). Non-linear relationships were observed between central thyroid hormones sensitivity indices and MUNO and MUO(p for nonlinearity < 0.05). Conversely, a linear relationship between FT3/FT4 and metabolically obese phenotypes was noted in all subjects (p for nonlinearity > 0.05). Besides, subgroup analysis indicated that this association remained consistent among sex and age (p for interaction > 0.05). The proportions mediated by BMI on the association of TFQI, PTFQI, TSHI, TT4RI, FT3/FT4 and risk of metabolically unhealthy conditions were 13.73%, 25.38%, 22.75%, 17.94% and 62.28%, respectively.

CONCLUSIONS

In euthyroid adults, central and peripheral sensitivity to thyroid hormones indices are positively associated with metabolically obese phenotypes risk, especially MUNO and MUO phenotypes.

The Role of the Atherogenic Index of Plasma and the Castelli Risk Index I and II in Cardiovascular Disease

INTRODUCTION

Metabolic syndrome (MS), identified by abdominal obesity, insulin resistance, hypertension, and/or dyslipidemia, occurs across all BMI (body mass index) ranges and increases the risk of atherosclerotic cardiovascular (CV) diseases and type II diabetes. The Atherogenic Index of Plasma (AIP) and Castelli Risk Index (CRI) I & II are ratios that can be calculated from a simple lipid profile test. These ratios are independent risk factors for CV diseases and have been shown to be increased in angiographically confirmed coronary artery disease (CAD) patients. This study aimed to assess CV risk across the different subtypes of obesity: metabolically obese non-obese (MONO), metabolically healthy non-obese (MHNO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) using AIP and CRI I & II and to study the association of AIP, CRI I & II with other CV risk factors such as total body fat percentage (BF%), visceral fat percentage (VF%), and BMI. Assessing CV risk in an individual based on the person's subtype of obesity using ratios calculated from simple lipid profile parameters may prove beneficial to developing better screening strategies.

METHODS

 A cross-sectional study was conducted on 128 adults with BMI ≥18.5 kg/m2 with and without MS, presenting to the General Medicine/Internal Medicine Outpatient Department in M S Ramaiah Medical College Hospital, Bangalore, Karnataka State, India. The sample size was calculated to be a minimum of 82 subjects based on a study that showed that AIP and CRI I & II had a positive association with BMI. After a detailed history, physical examination, anthropometric measurements (height, weight, and waist circumference), VF%, and BF% by bio-impedance were recorded. A blood sample was processed for lipid profile and fasting blood sugar on a Vitros 5600 auto-analyzer (Quidel Corporation and Ortho Clinical Diagnostics, San Diego, CA, USA). Subjects were divided into MONO (non-obese subjects with BMI < 25 kg/m2 having MS), MHNO (no obesity or MS), MOO (obese BMI ≥ 25 kg/m2 having MS), and MHO (obese BMI ≥ 25 kg/m2 not having MS) groups. AIP and CRI I & II were calculated. Statistical analysis was performed using the chi-square test, ANOVA, Pearson correlation coefficient, and receiver operating characteristic curve (ROC).

RESULTS

 MONO, MHNO, MOO, and MHO constituted 26 (20.3%), 48 (37.5%), 28 (21.8%), and 26 (20.3%) of the 128 subjects, respectively. AIP ≥0.24 was found in 16 (61.5%) of MONO and in 16 (51.1%) of MOO subjects. CRI-I >4 was found in 19 (73.1%) and 16 (57.1%) subjects of the MONO and MOO groups, respectively. Eleven (42.3%) and 12 (42.9%) of MONO and MOO subjects, respectively, had CRI-II >3. Pearson's correlation revealed for AIP r=0.32, p=0.000 and r=0.43, p=0.000 with VF% and BMI, respectively. The area under the curve (AUC) for AIP and CRI I & II to detect the presence of MS were 0.84, 0.74, and 0.73, respectively.

CONCLUSION

CV risk, as assessed by AIP and CRI I & II in the different subtypes of obesity, was found to be highest in the MONO group, followed by the MOO group. With BMI and VF%, AIP showed a moderately positive linear correlation. API and CRI could be tools of low cost and moderate reliability in screening the general population for risk of CV disease.

Circulatory levels of lysophosphatidylcholine species in obese adolescents: Findings from cross-sectional and prospective lipidomics analyses

BACKGROUND AND AIMS

Obesity has reached epidemic proportions, emphasizing the importance of reliable biomarkers for detecting early metabolic alterations and enabling early preventative interventions. However, our understanding of the molecular mechanisms and specific lipid species associated with childhood obesity remains limited. Therefore, the aim of this study was to investigate plasma lipidomic signatures as potential biomarkers for adolescent obesity.

METHODS AND RESULTS

A total of 103 individuals comprising overweight/obese (n = 46) and normal weight (n = 57) were randomly chosen from the baseline ORANGE (Obesity Reduction and Noncommunicable Disease Awareness through Group Education) cohort, having been followed up for a median of 7.1 years. Plasma lipidomic profiling was performed using the UHPLC-HRMS method. We used three different models adjusted for clinical covariates to analyze the data. Clustering methods were used to define metabotypes, which allowed for the stratification of subjects into subgroups with similar clinical and metabolic profiles. We observed that lysophosphatidylcholine (LPC) species like LPC.16.0, LPC.18.3, LPC.18.1, and LPC.20.3 were significantly (p < 0.05) associated with baseline and follow-up BMI in adolescent obesity. The association of LPC species with BMI remained consistently significant even after adjusting for potential confounders. Moreover, applying metabotyping using hierarchical clustering provided insights into the metabolic heterogeneity within the normal and obese groups, distinguishing metabolically healthy individuals from those with unhealthy metabolic profiles.

CONCLUSION

The specific LPC levels were found to be altered and increased in childhood obesity, particularly during the follow-up. These findings suggest that LPC species hold promise as potential biomarkers of obesity in adolescents, including healthy and unhealthy metabolic profiles.

The utility of coronary artery calcium scoring to enhance cardiovascular risk assessment for South Asian adults

South Asian individuals represent a highly diverse population and are one of the fastest growing ethnic groups in the United States. This population has a high prevalence of traditional and non-traditional cardiovascular disease (CVD) risk factors and a disproportionately high prevalence of coronary heart disease. To reflect this, current national society guidelines have designated South Asian ancestry as a "risk enhancing factor" which may be used to guide initiation or intensification of statin therapy. However, current methods of assessing cardiovascular risk in South Asian adults may not adequately capture the true risk in this diverse population. Coronary artery calcium (CAC) scoring provides a reliable, reproducible, and highly personalized method to provide CVD risk assessment and inform subsequent pharmacotherapy recommendations, if indicated. This review describes the utility of CAC scoring for South Asian individuals.

Exploring the link between obesity and hypothyroidism in autoimmune thyroid diseases: a metabolic perspective

Background: The management of primary hypothyroidism demands a comprehensive approach that encompasses both the implications of autoimmune thyroid disease and the distinct effects posed by obesity and metabolic irregularities. Despite its clinical importance, the interplay between obesity and hypothyroidism, especially in the context of metabolic perspectives, is insufficiently explored in existing research. This study endeavors to classify hypothyroidism by considering the presence of autoimmune thyroid disease and to examine its correlation with various metabolic obesity phenotypes. Method: This research was conducted by analyzing data from 1,170 individuals enrolled in the Thyroid Disease Database of Shandong Provincial Hospital. We assessed four distinct metabolic health statuses among the participants: Metabolically Healthy No Obese Metabolically Healthy Obese Metabolically Unhealthy No Obese and Metabolically Unhealthy Obese Utilizing logistic regression, we investigated the association between various metabolic obesity phenotypes and hypothyroidism. Results: The study revealed a significant correlation between the Metabolically Unhealthy Obese (MUO) phenotype and hypothyroidism, particularly among women who do not have thyroid autoimmunity. Notably, the Metabolically Unhealthy No Obese (MUNO) phenotype showed a significant association with hypothyroidism in individuals with thyroid autoimmunity, with a pronounced prevalence in women. Furthermore, elevated levels of triglycerides and blood glucose were found to be significantly associated with hypothyroidism in men with thyroid autoimmunity and in women without thyroid autoimmunity. Conclusion: Effective treatment of hypothyroidism requires a thorough understanding of the process of thyroid autoimmune development. In patients without concurrent thyroid autoimmunity, there is a notable correlation between obesity and metabolic issues with reduced thyroid function. Conversely, for patients with thyroid autoimmunity, a focused approach on managing metabolic abnormalities, especially triglyceride levels, is crucial.

Body fat patterning in lean Asian Indians with diabetes: Case-control study

AIM

To perform body fat patterning in Asian-Indian individuals with T2D.

METHODS

A total of 53 patients with recent-onset diabetes and 106 non-diabetic controls were included from screened 261 individuals. Data was divided into 2 groups; overweight/obese [(BMI ≥23 kg/m²); 45 diabetic, 84 non-diabetic] and lean [(BMI <23 kg/m²); 8 diabetic, 22 non-diabetic]. Anthropometry (weight, height, BMI, waist, hip circumference, waist-hip ratio) and lipids, adiponectin and hsCRP were measured. Body composition (BC) was assessed by bioimpedance analysis (BIA) and Dual Energy X-ray absorptiometry (DEXA). We analyzed the association of visceral adipose tissue (VAT) with anthropometric measures to identify predictors of diabetes.

RESULTS

Total body fat percentage was comparable between patients with T2D and non-diabetic controls in both, obese [35.0 ± 9.1% vs 36.8 ± 8.4%, p = 0.29 (BIA), 40.1 ± 6.7 vs 46.6 ± 4.1%, p = 0.052 (DEXA) and lean [25.1 ± 5.6% vs 26.0 ± 6.7%, p = 0.74 (BIA), 35.3 ± 4.8% vs 34.1 ± 6.3%, p = 0.72 (DEXA) study group. Individuals of T2D (obese or lean) had significantly higher visceral fat rating (BIA), VAT area, volume, mass and VAT corrected for total body fat percentage (DEXA). Obese T2D had lower muscle mass (57.0 ± 6.4% vs 60.0 ± 5.5%, p = 0.03) than obese controls. Intra-abdominal visceral fat (IAVF) [(VFR, VAT (mass/area/volume) and VAT mass corrected for body fat)] had the best sensitivity (71%) for incident diabetes.

CONCLUSION

Higher Intra-abdominal visceral fat and not total body fat is associated with incident diabetes independent of BMI. IAVF estimation by either BIA or DEXA should be performed to predict diabetes especially in lean individuals.

Alterations in metabolic status of healthy individuals with and without obesity during transition from adolescence to young adulthood

Aim: Extensive research is carried out throughout the world in healthy persons with obesity phenotype in concern with prevalence, metabolic profiling, etc. To the best of the authors’ knowledge, not many studies have investigated the status of adiponectin, specific inflammatory changes, oxidative damage in healthy adolescents and young adults with obesity. Present study was undertaken in adolescents and young adults of urban population in a district of North Karnataka, India, in a view to understand relationship between hormone adiponectin, oxidative stress markers like C3, C4, high sensitivity C-reactive protein (hs-CRP) in non-hypertensive, non-diabetic, euthyroid individuals with and without obesity. Methods: Participant selection was done using cluster sampling technique. Participating adolescents and young adults, each with and without obesity were included in the study. Screening of participants for diabetes, hypertension, and thyroid disorders was done, their serum level of adiponectin, hs-CRP, C3, C4, ceruloplasmin (Cp), thiobarbituric acid reactive substances (TBARS), and total antioxidant capacity (TAC) were estimated using standardized methods in National Accreditation Board for Testing and Calibration Laboratories (NABL) laboratory. Results: Adiponectin (young adults lower than adolescents, P = 0.01) levels were low, while hs-CRP and Cp (young adults higher than adolescents, P = 0.01) levels were high with increasing age in non-obese. While in persons having obesity, aging adiponectin levels were low while hs-CRP, C3, Cp levels were high significantly. Females without obesity had significantly higher values of C3 than males. Adiponectin showed higher levels in females than males, however, statistical significance could not be achieved (P = 0.308). While females with obesity, exhibited statistically lower levels of adiponectin, and higher levels of C3 and C4. Conclusions: Being non-diabetic and non-hypertensive yet obese, tagged by one time of assay, does not suffice to be categorized as healthy. Healthy young adults with obesity are exhibiting lower levels of adiponectin and higher levels of inflammatory and oxidative stress markers compared to adolescents with obesity. This implies, the so categorized “healthy obese” participants are in a phase of transition towards an unhealthy state.

The Role of Nutraceutical Containing Polyphenols in Diabetes Prevention

Research in pharmacological therapy has led to the availability of many antidiabetic agents. New recommendations for precision medicine and particularly precision nutrition may greatly contribute to the control and especially to the prevention of diabetes. This scenario greatly encourages the search for novel non-pharmaceutical molecules. In line with this, the daily and long-term consumption of diets rich in phenolic compounds, together with a healthy lifestyle, may have a protective role against the development of type 2 diabetes. In the framework of the described studies, there is clear evidence that the bio accessibility, bioavailability, and the gut microbiota are indeed affected by: the way phenolic compounds are consumed (acutely or chronically; as pure compounds, extracts, or in-side a whole meal) and the amount and the type of phenolic compounds (ex-tractable or non-extractable/macromolecular antioxidants, including non-bioavailable polyphenols and plant matrix complexed structures). In this review, we report possible effects of important, commonly consumed, phenolic-based nutraceuticals in pre-clinical and clinical diabetes studies. We highlight their mechanisms of action and their potential effects in health promotion. Translation of this nutraceutical-based approach still requires more and larger clinical trials for better elucidation of the mechanism of action toward clinical applications.

The Study of the Association of Serum Parathyroid Hormone Level with Obesity in Patients Admitted to a Tertiary Care Center in Basrah

Background: Parathyroid hormone (PTH) has been reported to have a positive correlation with insulin resistance and the development of the metabolic syndrome. This study aims to evaluate if there is an association between obesity and serum PTH levels. Methods: This case-control study was conducted at the Faiha Specialized Diabetes Endocrine and Metabolism Center in Basrah (Southern Iraq) from September 2018 to July 2019. A total of 230 patients were recruited for this study (103 male and 127 female), divided into 2 groups according to the BMI: <30 kg/m2 were considered as the control group (83 persons) and ≥30 kg/m2 were considered as obese persons (147 persons). The study groups were also subdivided into 3 groups according to the serum level of PTH: <40 pg/mL, 40–65 pg/mL, and >65 pg/mL. Results: The mean age of the obese and control groups was 44.39 ± 10.64 and 30.12 ± 8.95 years, respectively. About 46.25% of obese were men and 53.75% were women, while 42% of the control group were men and 58% were women. Serum PTH level was significantly higher (p < 0.001) among obese persons with a mean level of 53.21 ± 19.58 pg/mL for obese and 37.63 ± 21.8 pg/mL for control. Vitamin D deficiency was seen in 84.4% of the obese group while in 71.1% of the control group (p value 0.04). Females turned to have higher PTH levels than males in both the obese and the control group (p value <0.001). However, age and the presence of diabetes mellitus were not associated with higher PTH levels (p value 0.155 and 0.6, respectively). Conclusion: Obesity was associated with a higher serum PTH level related to the severity of vitamin D deficiency.

Metabolic syndrome in non-obese patients with OSA: learning points of a cross-sectional study from a tertiary care hospital in Central India

STUDY OBJECTIVES

Obesity is often considered mandatory for the diagnosis of Metabolic Syndrome (MS). Data on the prevalence of MS in non-obese patients with Obstructive Sleep Apnea (OSA) is scarce. This study was aimed to determine the prevalence of MS in non-obese patients with OSA.

METHODOLOGY

All consecutively diagnosed patients with OSA between October 2018 and November 2019 were screened for metabolic syndrome. Patients with OSA and BMI < 25 kg/m² (NOOSA) vs BMI > 25 kg/m² (obese OSA) were compared. Lean waist NOOSA was defined as BMI < 25 kg/m² and WC < 80 cm (32 in.) for women or < 90 cm (36 in.) for men.

RESULTS

During the study period, 502 patients were diagnosed with OSA. MS was observed in 35% of patients with NOOSA compared to obese patients with OSA (79%). In the NOOSA group, hypertension, impaired fasting glucose, diabetes mellitus and dyslipidemia were observed in 65, 48, 14 and 61% respectively and all of these parameters were significantly more common in the obese group (p < 0.001). Parameters of OSA severity (apnea-hypopnea index or AHI, time spent below 90% saturated or T90, and nadir oxygen) were significantly more severe in the obese group with OSA. Approximately 83% of patients in the NOOSA group had at least two metabolic risk factors, compared to the obese OSA group, in which 95% had two or more metabolic risk factors. Sixty-four percent of patients with NOOSA with lean waist had at least two metabolic risk factors. At BMI cut-offs of < 25, < 27 and < 30 kg/m2; 35, 46 and 57% of patients with OSA respectively had metabolic syndrome.

CONCLUSION

Metabolic syndrome was observed in approximately one in three patients with OSA and BMI < 25 kg/m². Approximately two of every three lean waist non-obese patients with OSA had at least two markers of metabolic syndrome. The role of OSA in the development of metabolic syndrome in non-obese individuals needs further exploration.

Association between different obesity phenotypes and hypothyroidism: a study based on a longitudinal health management cohort

PURPOSE

Obese individuals have an increased risk of hypothyroidism. This study investigated the sex-specific association between obesity phenotypes and the development of hypothyroidism.

METHODS

The study population was derived from a health management cohort in Shandong Provincial Hospital from 2012 to 2016. In total, 9011 baseline euthyroid adults were included and classified into four groups according to obesity phenotype: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy nonobese (MUNO), and metabolically unhealthy obese (MUO). The median follow-up time was 1.92 (1.00-2.17) years. Incidence density was evaluated and a generalized estimation equation method was used to investigate the associations between obesity phenotypes and the development of hypothyroidism.

RESULTS

The incidence densities of hypothyroidism in males with a consistent obesity phenotype were 12.19 (8.62-16.76), 15.87 (11.39-21.56), 14.52 (6.74-27.57), and 19.88 (14.06-27.34) per 1000 person-years in the MHNO, MHO, MUNO, and MUO groups, respectively. After adjusting for confounding factors, compared with the MHNO phenotype, the MHO, MUNO, and MUO phenotypes were independent risk factors for developing hypothyroidism in males. In the subgroup analysis, the MHO and MUO phenotypes were independent risk factors for developing hypothyroidism in males under 55 years, while the MUNO phenotype was an independent risk factor in males over 55 years. The MHO, MUNO, and MUO phenotypes were not independent risk factors for hypothyroidism in females.

CONCLUSION

Both obesity and metabolic abnormities are associated with a higher risk of hypothyroidism in males. The underlying mechanism of the sex and age differences in this association needs further investigation.

Deciphering Biochemical and Molecular Signatures Associated with Obesity in Context of Metabolic Health

This study aims to identify the clinical and genetic markers related to the two uncommon nutritional statuses—metabolically unhealthy normal-weight (MUNW) and metabolically healthy overweight/obese (MHOW) individuals in the physically active individuals. Physically active male volunteers (n = 120) were recruited, and plasma samples were analyzed for the clinical parameters. Triglycerides, HDL-Cholesterol, LDL-cholesterol, total cholesterol, C-reactive protein, and insulin resistance were considered as markers of metabolic syndrome. The subjects were classified as ‘healthy’ (0 metabolic abnormalities) or ‘unhealthy’ (≥1 metabolic abnormalities) in their respective BMI group with a cut-off at 24.9 kg/m². Analysis of biochemical variables was done using enzyme linked immunosorbent assay (ELISA) kits with further confirmation using western blot analysis. The microarray was conducted, followed by quantitative real-time PCR to identify and analyze differentially expressed genes (DEGs). The MHOW group constituted 12.6%, while the MUNW group constituted 32.4% of the total study population. Pro-inflammatory markers like interleukin-6, tumor necrosis factor (TNF)-α, and ferritin were increased in metabolically unhealthy groups in comparison to metabolically healthy groups. Gene expression profiling of MUNW and MHOW individuals resulted in differential expression of 7470 and 5864 genes, respectively. The gene ontology (GO) biological pathway analysis showed significant enrichment of the ‘JAK/STAT signaling pathway’ in MUNW and ‘The information-processing pathway at the IFN-β enhancer′ pathway in MHOW. The G6PC3 gene has genetically emerged as a new distinct gene showing its involvement in insulin resistance. Biochemical, as well as genetic analysis, revealed that MUNW and MHOW are the transition state between healthy and obese individuals with simply having fewer metabolic abnormalities. Moreover, it is possible that the state of obesity is a biological adaptation to cope up with the unhealthy parameters.

Genetic and Non-genetic Determinants of Cardiovascular Disease in South Asians

South Asians (SAs), people from the Indian subcontinent (e.g., India, Pakistan, Bangladesh, Sri Lanka, and Nepal) have a higher prevalence of cardiovascular disease (CVD) and suffer from a greater risk of CVD-associated mortality compared to other global populations. These problems are compounded by the alterations in lifestyles due to urbanization and changing cultural, social, economic, and political environments. Current methods of CV risk prediction are based on white populations that under-estimate the CVD risk in SAs. Prospective studies are required to obtain actual CVD morbidity/mortality rates so that comparisons between predicted CVD risk can be made with actual events. Overwhelming data support a strong influence of genetic factors. Genome-Wide Association Studies (GWAS) serve as a starting point for future genetic and functional studies since the mechanisms of action by which these associated loci influence CVD is still unclear. It is difficult to predict the potential implication of these findings in clinical settings. This review provides a systematic assessment of the risk factors, genetics, and environmental causes of CV health disparity in SAs, and highlights progress made in clinical and genomics discoveries in the rapidly evolving field, which has the potential to show clinical relevance in the near future.

Metabolically Healthy Obesity

Obesity contributes to reduced life expectancy, impaired quality of life, and disabilities, mainly in those individuals who develop cardiovascular diseases, type 2 diabetes, osteoarthritis, and cancer. However, there is a large variation in the individual risk to developing obesity-associated comorbid diseases that cannot simply be explained by the extent of adiposity. Observations that a proportion of individuals with obesity have a significantly lower risk for cardiometabolic abnormalities led to the concept of metabolically healthy obesity (MHO). Although there is no clear definition, normal glucose and lipid metabolism parameters-in addition to the absence of hypertension-usually serve as criteria to diagnose MHO. Biological mechanisms underlying MHO lower amounts of ectopic fat (visceral and liver), and higher leg fat deposition, expandability of subcutaneous adipose tissue, preserved insulin sensitivity, and beta-cell function as well as better cardiorespiratory fitness compared to unhealthy obesity. Whereas the absence of metabolic abnormalities may reduce the risk of type 2 diabetes and cardiovascular diseases in metabolically healthy individuals compared to unhealthy individuals with obesity, it is still higher in comparison with healthy lean individuals. In addition, MHO seems to be a transient phenotype further justifying therapeutic weight loss attempts-even in this subgroup-which might not benefit from reducing body weight to the same extent as patients with unhealthy obesity. Metabolically healthy obesity represents a model to study mechanisms linking obesity to cardiometabolic complications. Metabolically healthy obesity should not be considered a safe condition, which does not require obesity treatment, but may guide decision-making for a personalized and risk-stratified obesity treatment.

Association Between Forearm Bone Mineral Density and Metabolic Obesity in a Northern Chinese Population

Context: The link between obesity and bone health is controversial. Most studies classify obesity based on body mass index. However, differences in metabolic status may affect bone health. Purpose: To explore the potential relationship of metabolic obesity with forearm bone mineral density (BMD) in a northern Chinese population. Methods: This is a retrospective study involving a total of 2122 subjects divided into four groups: a metabolically healthy normal-weight (MHNW) group, a metabolically healthy obesity (MHO) group, a metabolically unhealthy, but normal-weight (MUNW) group, and a metabolically unhealthy obesity (MUO) group. Analysis of covariance was performed to compare forearm BMD among the groups. The covariates included age, weight, and height, along with menopause status in women. Partial correlation analysis and multiple linear regression models were used to explore the associations of forearm BMD with clinical parameters. Results: Young middle-aged men with MHO had significantly higher forearm BMD than those in the MUO group. In addition, forearm BMD of young middle-aged women was higher in the MHNW group than in the MUNW group. Partial correlation analysis and multiple linear regression analysis suggested that homeostasis model assessment of insulin resistance (HOMA-IR) was negatively correlated with forearm BMD in young middle-aged male subjects with MUO, and waist circumference (WC) and low-density lipoprotein cholesterol (LDL-C) showed a significant negative relationship with forearm BMD in young middle-aged female MUNW subjects. Conclusions: Men in the MUO group and women in the MUNW group were more likely to have lower forearm BMD if they were of young middle age. Metabolic obesity could be a better method for defining obesity when exploring the relationship between obesity and bone health in Chinese individuals. WC, LDL-C, and insulin resistance might be negative predictors of bone health.

Metabolically healthy obese and metabolic syndrome of the lean: the importance of diet quality. Analysis of MAGNETIC cohort

BACKGROUND

Obesity is considered as an indispensable component of metabolic health assessment and metabolic syndrome diagnosis. The associations between diet quality and metabolic health in lean, young adults have not been yet established whilst data addressing this issue in overweight and obese subjects is scarce. Our analysis aimed to establish the link between diet quality (measured with data-driven dietary patterns and diet quality scores) and metabolic syndrome (MS) in young adults, regardless of their adiposity status.

METHODS

A total of 797 participants aged 18-35 years old were included in the study. Participants were assigned into metabolic syndrome (MS) group if at least two abnormalities within the following parameters were present: blood pressure, triglycerides, total cholesterol, HDL cholesterol, blood glucose. Participants with one or none abnormalities were considered as metabolically healthy subjects (MH), Diet quality was assessed with two approaches: 1) a posteriori by drawing dietary patterns (DPs) with principal component analysis (PCA) and 2) a priori by establishing diet quality scores and the adherence to pro-Healthy-Diet-Index (pHDI) and non-Healthy-Diet-Index (nHDI). Logistic regression with backward selection based on Akaike information criterion was carried out, to identify factors independently associated with metabolic health.

RESULTS

Within the MS group, 31% were of normal weight. Three PCA-driven DPs were identified, in total explaining 30.0% of the variance: "Western" (11.8%), "Prudent" (11.2%) and "Dairy, breakfast cereals & treats" (7.0%). In the multivariate models which included PCA-driven DPs, higher adherence to middle and upper tertiles of "Western" DP (Odds Ratios [OR] and 95% Confidence Intervals [95% CI]: 1.72, 1.07-2.79 and 1.74, 1.07-2.84, respectively), was associated with MS independently of clinical characteristics including BMI and waist-hip ratio (WHR). Similar results were obtained in the multivariate model with diet quality scores - MS was independently associated with higher scores within nHDI (2.2, 0.92-5.28).

CONCLUSIONS

Individuals with MS were more likely to adhere to the western dietary pattern and have a poor diet quality in comparison to metabolically healthy peers, independently of BMI and WHR. It may imply that diet composition, as independent factor, plays a pivotal role in increasing metabolic risk. Professional dietary advice should be offered to all metabolically unhealthy patients, regardless of their body mass status.

The Relationship between Thyroid Function and Different Obesity Phenotypes in Korean Euthyroid Adults

BACKGROUND

Thyroid disease and metabolic syndrome are both associated with cardiovascular disease. The aim of this study was to investigate the correlation between thyroid hormones and obesity sub-phenotypes using nationwide data from Korea, a country known to be iodine replete.

METHODS

This study was based on data obtained from the sixth Korea National Health and Nutrition Examination Survey, administered from 2013 to 2015. A total of 13,873 participants aged ≥19 years were included, and classified into four groups: metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO), and metabolically unhealthy obesity (MUO) by body fat on the basis of body mass index and metabolic health.

RESULTS

At baseline, serum free thyroxine (fT4) values were significantly higher in the MHNO phenotype (MHNO, 1.27±0.01 ng/dL; MHO, 1.25±0.01 ng/dL; MUNO, 1.24±0.01 ng/dL; MUO, 1.24±0.01 ng/dL, P<0.001) in total study population. However, this significant association no longer remained after adjustment for age, urine iodine concentration, and smoking (P=0.085). After adjustment for confounders, statistically significant association was observed between lower thyroid stimulating hormone (TSH) and MHNO phenotype (P=0.044). In men participants (not women), higher fT4 values were significantly associated with MHNO phenotype (P<0.001). However, no significant association was observed between thyroid function (TSH or fT4) and obesity phenotypes in groups classified by age (cutoff age of 55 years).

CONCLUSION

Although there was a difference by age and sex, we found that the decrease of TSH and the increase of fT4 values were associated with MHNO.

The long-term prognosis of heart diseases for different metabolic phenotypes: a systematic review and meta-analysis of prospective cohort studies

PURPOSE

This meta-analysis aimed to assess the association of different categories of weight and metabolic status with risk of heart diseases including myocardial infarction (MI), cardiovascular diseases (CVDs), and heart failure (HF).

METHODS

Data from relevant studies were identified systematically by searching PubMed and Scopus search engines up to 29 May 2018. Prospective studies were included in the analyses with metabolically healthy normal weight (MHNW) as the reference. Pooled RRs and 95% CI were calculated using random-effects or fixed-effect models when appropriate. Subgroup analysis was applied to define possible sources of heterogeneity.

RESULTS

Overall, 21 studies (n = 778,401 participants) were eligible for the present meta-analysis. Generally, the risk of CVDs for all metabolic phenotypes in metabolically unhealthy obese increased compared with the MHNW group. A significant positive association between all metabolic phenotypes and the risk of HF was also observed expect for MHOW (RR = 1.10, 95% CI: 0.60-2.00, P = 0.76) and MHO phenotypes (RR = 0.96, 95% CI: 0.25-3.77, P = 0.95). Moreover, MUHO phenotype was associated with greater risk of MI compared with the MHNW phenotype (RR = 1.82, 95% CI: 1.50-2.22, P < 0.001, respectively).

CONCLUSIONS

Our findings showed that all metabolically unhealthy phenotypes in different categories of weight were associated with increased incident of CVDs/HF and MI. Furthermore, healthy overweight and obese subjects had increased risk of CVDs.

Increased Plasma Dipeptidyl Peptidase-4 (DPP4) Activity Is an Obesity-Independent Parameter for Glycemic Deregulation in Type 2 Diabetes Patients

Background: Increase in circulating dipeptidyl peptidase-4 (DPP4) activity and levels has been reported to associate both with hyperglycemia and obesity. Here we aim to decipher the role of enhanced plasma DPP4 activity in obese type 2 diabetes (T2DM) patients. Materials and methods: Plasma DPP4 levels and activity were measured in obese and non-obese newly diagnosed T2DM patients (n = 123). Visceral and subcutaneous adipose tissue DPP4 expression and activity were determined in 43 obese subjects (T2DM = 21 and non-T2DM = 22). 20 subjects undergoing Mini-Gastric Bypass (MGB) surgery were followed up over 4-6 weeks for plasma DPP4. Results: Plasma DPP4 levels and activity both were increased in T2DM patients compared to control group. However, DPP4 levels and not DPP4 activity were increased in obese T2DM patients compared to non-obese T2DM (62.49 ± 26.27 μg/ml vs. 48.4 ± 30.98 μg/ml, respectively, p = 0.028). DPP4 activity in visceral adipose tissue (VAT) from obese T2DM and obese non-T2DM groups were similar (5.05 ± 3.96 nmol/min/ml vs. 5.83 ± 4.13 nmol/min/ml respectively, p = 0.548) in spite of having increased DPP4 expression in the obese T2DM group. Moreover, in obese patients, plasma DPP4 levels and activity did not show any significant change after weight reduction and glycemic control following MGB surgery. Conclusion: Enhanced plasma DPP4 activity in T2DM occurs independently of obesity. Thus, adipose derived DPP4 may not be playing any significant role in glycemic deregulation in obese T2DM patients.

Phenotypic and metabolic dichotomy in obesity: clinical, biochemical and immunological correlates of metabolically divergent obese phenotypes in healthy South Asian adults

INTRODUCTION

Metabolic heterogeneity among obese individuals is thought to translate into variations in cardiovascular risk. Identifying obese people with an unfavourable metabolic profile may allow preventive strategies to be targeted at high-risk groups. This study aimed to identify clinical, biochemical and immunological differences between insulin-sensitive and insulin-resistant obese subgroups, to understand the population-specific pathophysiological basis of the adverse cardiovascular risk profile in the latter group.

METHODS

Cardiovascular risk indicators, including anthropometric parameters, blood pressure, acanthosis nigricans area, and related biochemical, endocrine and inflammatory markers, were determined in 255 healthy South Asian volunteers aged 18-45 years, with a 2:1 ratio of obese/overweight to normal-weight individuals. Lifetime atherosclerotic cardiovascular disease (ASCVD) risk was also calculated.

RESULTS

Body mass index (BMI) and insulin sensitivity-based tertiles independently showed incremental trends in waist-hip ratio, skinfold thickness, acanthosis nigricans area, blood pressure, serum lipids, hepatic enzymes, adipokines, inflammatory markers and ten-year ASCVD risk. The anthropometric, biochemical and inflammatory parameters of obese insulin-sensitive and obese insulin-resistant groups differed significantly. Extreme group analysis after excluding the middle tertiles of both insulin resistance and BMI also showed significant difference in anthropometric indicators of cardiovascular risk and estimated lifetime ASCVD risk between the two obese subgroups.

CONCLUSION

Obese insulin-sensitive individuals had a favourable metabolic profile compared to the obese insulin-resistant group. The most consistent discriminative factor between these phenotypic classes was anthropometric parameters, which underscores the importance of clinical parameters as cardiovascular risk indicators in obesity.

Favourable metabolic profile sustains mitophagy and prevents metabolic abnormalities in metabolically healthy obese individuals

BACKGROUND

Obesity-mediated oxidative stress results in mitochondrial dysfunction, which has been implicated in the pathogenesis of metabolic syndrome and T2DM. Recently, mitophagy, a cell-reparative process has emerged as a key facet in maintaining the mitochondrial health, which may contribute to contain the metabolic abnormalities in obese individuals. However, the status of mitophagy in metabolically healthy obese (MHO) and metabolically abnormal diabetic obese (MADO) subjects remains to be elucidated. Hence, the present study aims to unravel the alterations in mitochondrial oxidative stress (MOS) and mitophagy in these subjects.

METHODS

60 subjects including MHNO (metabolically healthy non-obese), MHO and MADO were enrolled as per the Asian criteria for obesity (n = 20 each). Biochemical parameters, MOS indices, transcriptional and translational expression of mitophagy markers (PINK1, PARKIN, MFN2, NIX, LC3-II, and LAMP-2), and transmission electron microscopic (TEM) studies were performed in peripheral blood mononuclear cells.

RESULTS

The MHO subjects displayed a favorable metabolic profile, despite accompanied by an increased adiposity as compared to the MHNO group; while MADO group exhibited several metabolic abnormalities, inspite of similar body composition as MHO subjects. A progressive rise in the MOS was observed in MHO and MADO subjects as compared to the MHNO group, and it showed a positive and significant correlation with the body composition in these groups. Further, mitophagy remained unaltered in the MHO group, while it was significantly downregulated in the MADO group. In addition, TEM studies revealed a significant increase in the percentage of damaged mitochondria in MADO patients as compared to other groups, while MHO and MHNO groups did not show any significant alterations for the same.

CONCLUSION

A favorable metabolic profile and moderate levels of MOS in the MHO group may play a crucial role in the sustenance of mitophagy, which may further limit the aggravation of MOS, inflammation, and emergence of metabolic aberrations in contrast to MADO subjects, who exhibited multiple metabolic abnormalities and attenuated mitophagy. Therefore, these MHO subjects are likely to be at a lower risk of developing metabolic syndrome and T2DM.

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.

Metabolically Healthy Obesity and Ischemic Heart Disease: A 10-Year Follow-Up of the Inter99 Study

CONTEXT

Recent studies have suggested that a subgroup of obese individuals is not at increased risk of obesity-related complications. This subgroup has been referred to as metabolically healthy obese.

OBJECTIVE

To investigate whether obesity is a risk factor for development of ischemic heart disease (IHD) irrespective of metabolic health.

DESIGN

In all, 6238 men and women from the Danish prospective Inter99 study were followed during 10.6 (standard deviation = 1.7) years.

SETTING

General community.

PARTICIPANTS

Participants were classified according to body mass index and four metabolic risk factors (low high-density lipoprotein cholesterol, elevated blood pressure, triglycerides, and fasting plasma glucose). Metabolically healthy individuals were defined as having no metabolic risk factors, and metabolically unhealthy individuals were defined as having a minimum of one.

MAIN OUTCOME MEASURES

IHD.

RESULTS

During follow-up, 323 participants developed IHD. Metabolically healthy obese men had increased risk of IHD compared with metabolically healthy normal-weight men [hazard ratio (HR), 3.1; 95% confidence interval (CI), 1.1 to 8.2)]. The corresponding results for women were less pronounced (HR, 1.8; 95% CI, 0.7 to 4.8). Being metabolically healthy but overweight was not associated with higher risk of IHD in men (HR, 1.1; 95% CI, 0.5 to 2.4), and in women the risk was only slightly increased and insignificant (HR, 1.5; 95% CI, 0.8 to 3.0). A substantial proportion of metabolically healthy individuals became metabolically unhealthy after 5 years of follow-up. When these changes in exposure status were taken into account, slightly higher risk estimates were found.

CONCLUSIONS

Being obese is associated with higher incidence of IHD irrespective of metabolic status, and we question the feasibility of denoting a subgroup of obese individuals as metabolically healthy.

Parathyroid hormone and vitamin D are associated with the risk of metabolic obesity in a middle-aged and older Korean population with preserved renal function: A cross-sectional study

BACKGROUND

In general, obesity is a major contributor to metabolic syndrome (MetS) and is associated with insulin resistance (IR). Metabolically obese but normal weight (MONW) individuals present metabolic abnormalities and features of MetS despite having a normal range of body mass index (BMI). In recent years, different subtypes of obesity have been introduced, including metabolically healthy obese (MHO) and metabolically obese obese (MOO). Also, it has been reported that vitamin D and parathyroid hormone (PTH) are possibly linked with MetS.

METHODS AND FINDINGS

In this study, we aimed to evaluate the association between serum 25(OH)D, serum PTH, and the risk of metabolic obesity in four subtypes using nationally representative survey data for a Korean population conducted between 2008 and 2010. Of the 29,235 Korean participants, 18,997 subjects aged under 50 years were excluded. Participants with diabetes (n = 1,520), renal insufficiency (glomerular filtration rate [GFR] < 45 ml/min/1.73 m2, chronic kidney disease [CKD] stage 3b, 4, and 5 according to KDOQI classification [1]) (n = 49), history of treatment for osteoporosis (n = 455), insufficient data (n = 1,613), and fasting time less than 8 hours prior to blood collection (n = 771) were excluded for analysis. Ultimately, 5,830 adults (2,582 men and 3,248 women) were eligible for the present study. And, subtypes of obesity were divided into four types: Metabolically healthy normal weight (MHNW), Metabolically healthy obese (MHO), Metabolically obese but normal weight (MONW), and Metabolically obese obese (MOO). Female subjects with metabolic obesity were more likely to have higher levels of PTH and Male subjects with metabolic health were more likely to have higher serum 25(OH)D levels.

CONCLUSION

We concluded that a positive association between serum PTH concentration and metabolic obesity among female subjects and an inverse relationship between serum 25(OH)D levels and the risk of metabolic obesity were found among male subjects. Further prospective studies are necessary to explore the biological mechanisms underlying these sex-specific findings.

Is the "South Asian Phenotype" Unique to South Asians?: Comparing Cardiometabolic Risk Factors in the CARRS and NHANES Studies

BACKGROUND

In the context of rising obesity in South Asia, it is unclear whether the "South Asian phenotype"(described as high glucose, low high-density lipoprotein cholesterol, and high triglycerides at normal ranges of body weight) continues to be disproportionately exhibited by contemporary South Asians relative to other race/ethnic groups.

OBJECTIVES

We assessed the distinctiveness of the South Asian cardiometabolic profile by comparing the prevalence of combined high glucose, high triglycerides, and low high-density lipoprotein cholesterol (combined dysglycemia and dyslipidemia) in resident South Asians with 4 race/ethnic groups in the United States (Asians, black persons, Hispanics, and white persons) overall and by body mass index (BMI) category.

METHODS

South Asian data were from the 2010 to 2011 Center for Cardiometabolic Risk Reduction in South Asia Study, representative of Chennai and New Delhi, India and Karachi, Pakistan. U.S. data were from the 2011 to 2012 National Health and Nutrition Examination Survey, representative of the U.S.

POPULATION

Combined dysglycemia and dyslipidemia was defined as fasting blood glucose ≥126 mg/dl and triglyceride/high-density lipoprotein cholesterol ratio >4. Logistic regression was used to estimate the relative odds and 95% confidence intervals of combined dysglycemia and dyslipidemia associated with each race/ethnic group (referent, U.S. white persons). Models were estimated among adults aged 20 to 79 years by sex and BMI category and accounted for age, education, and tobacco use. Data from 8,448 resident South Asians, 274 U.S. Asians, 404 U.S. black persons, 308 U.S. Hispanics, and 703 U.S. white persons without previously known diabetes were analyzed.

RESULTS

In the normal body weight range of BMI 18.5 to 24.9 kg/m(2), the prevalence of combined dysglycemia and dyslipidemia among men and women, respectively, was 33% and 11% in resident South Asians, 15% and 1% in U.S. Asians, 5% and 2% in U.S. black persons, 11% and 2% in U.S. Hispanics, and 8% and 2% in U.S. white persons. Compared with U.S. whites persons, South Asians were more likely to present with combined dysglycemia and dyslipidemia at all categories of BMI for men and at BMI 18.5 to 29.9 for women in adjusted models. The most pronounced difference between South Asians and U.S. white persons was observed at normal weight (adjusted odds ratio: 4.98; 95% confidence interval: 2.46 to 10.07 for men) (adjusted odds ratio: 9.09; 95% confidence interval: 2.48 to 33.29 for women).

CONCLUSIONS

Between 8% and 15% of U.S. men and 1% and 2% of U.S. women of diverse race/ethnic backgrounds exhibited dysglycemia and dyslipidemia at levels of body weight considered "healthy," consistent with the cardiometabolic profile described as the "South Asian Phenotype." Urban South Asians, however, were 5 to 9 times more likely to exhibit dysglycemia and dyslipidemia in the "healthy" BMI range compared with any other U.S. race/ethnic group.

Metabolic syndrome among non-obese adults in the teaching profession in Melaka, Malaysia

Background

Non-obese individuals could have metabolic disorders that are typically associated with elevated body mass index (BMI), placing them at elevated risk for chronic diseases. This study aimed to describe the prevalence and distribution of metabolically obese, non-obese (MONO) individuals in Malaysia.

Methods

We conducted a cross-sectional study involving teachers recruited via multi-stage sampling from the state of Melaka, Malaysia. MONO was defined as individuals with BMI 18.5–29.9 kg/m² and metabolic syndrome. Metabolic syndrome was diagnosed based on the Harmonization criteria. Participants completed self-reported questionnaires that assessed alcohol intake, sleep duration, smoking, physical activity, and fruit and vegetable consumption.

Results

A total of 1168 teachers were included in the analysis. The prevalence of MONO was 17.7% (95% confidence interval [CI], 15.3–20.4). Prevalence of metabolic syndrome among the normal weight and overweight participants was 8.3% (95% CI, 5.8–11.8) and 29.9% (95% CI, 26.3–33.7), respectively. MONO prevalence was higher among males, Indians, and older participants and inversely associated with sleep duration. Metabolic syndrome was also more prevalent among those with central obesity, regardless of whether they were normal or overweight. The odds of metabolic syndrome increased exponentially from 1.9 (for those with BMI 23.0–24.9 kg/m²) to 11.5 (for those with BMI 27.5–29.9 kg/m²) compared to those with BMI 18.5–22.9 kg/m² after adjustment for confounders.

Conclusions

The prevalence of MONO was high, and participants with BMI ≥23.0 kg/m² had significantly higher odds of metabolic syndrome. Healthcare professionals and physicians should start to screen non-obese individuals for metabolic risk factors to facilitate early targeted intervention.

•

The prevalence of metabolic syndrome among the non-obese teachers was 17.7%.

•

The odds of metabolic syndrome increased exponentially from a BMI of 23.0 kg/m².

•

Metabolic syndrome was more prevalent among males, Indians, and older teachers.

Metabolism rather than obesity is associated with ischemic stroke: a cross-sectional study in rural Northeastern China

Little is known about stroke with different obesity phenotype as determined using the Adult Treatment Panel-III criteria with metabolic health or not. This study aimed to investigate the effects of metabolically healthy and unhealthy obesity on ischemic stroke in a general population. A total of 11,150 adults were examined using a multi-stage cluster sampling method to select a representative sample of individuals 35 years or older. Ischemic stroke was defined as history of a cerebrovascular event, as documented by doctors via either cranial CT or MR scan within the past 2 years. All subjects were categorized as having metabolically healthy non-obesity (MHNO), metabolically unhealthy non-obesity (MUNO), metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) using the Adult Treatment Panel-III criteria. Stratified analysis were done based on different body mass index group. For the total population, multiple regression analyses revealed that individuals with MUNO and MUO were more likely to experience ischemic stroke compared with those with MHNO (OR 2.136, 95 % CI 1.677-2.720; OR 2.712, 95 % CI 1.798-4.092; all p < 0.001). The OR for ischemic stroke did not significantly differ between MHO and MHNO. Stratification based on different BMI group showed that, compared with people who were normal weight without Mes, participants who were in Mes with overweight or obesity had significantly higher OR for ischemic stroke(both p < 0.05); participants who were not in Mes with overweight or obesity did not showed OR significantly higher. Ischemic stroke is likely associated with poor metabolic health rather than with obesity itself.

Prevalence and Determinants of Metabolic Health in Subjects with Obesity in Chinese Population

Background: The study was to investigate the prevalence of metabolic health in subjects with obesity in the Chinese population and to identify the determinants related to metabolic abnormality in obese individuals. Methods: 5013 subjects were recruited from seven provincial capitals in China. The obesity and metabolic status were classified based on body mass index (BMI) and the number of abnormalities in common components of metabolic syndrome. Results: 27.9% of individuals with obesity were metabolically healthy. The prevalence of the metabolically healthy obese (MHO) phenotype was significantly decreased with age in women (p_trend < 0.001), but not significantly in men (p_trend = 0.349). Central obesity (odds ratio [OR] = 4.07, 95% confidence interval [CI] = 1.93–8.59), longer sedentary time (OR = 1.97, 95%CI = 1.27–3.06), and with a family history of obesity related diseases (hypertension, diabetes, dyslipidemia) (OR = 1.85, 95%CI = 1.26–2.71) were significantly associated with having metabolic abnormality in obese individuals. Higher levels of physical activity and more fruit/vegetable intake had decreased ORs of 0.67 (95%CI = 0.45–0.98) and 0.44 (95%CI = 0.28–0.70), respectively. Conclusion: 27.9% of obese participants are in metabolic health. Central obesity, physical activity, sedentary time, fruits/vegetables intake and family history of diseases are the determinants associated with metabolic status in obesity.

Metabolic obesity, adipocytokines, and inflammatory markers in Asian Indians--CURES-124

AIM

This study looked at the association of adipokines, inflammatory and oxidative stress markers in subjects with the following phenotypes: metabolically healthy, nonobese (MHNO), metabolically healthy, obese (MHO), metabolically obese, nonobese (MONO), and metabolically obese, obese (MOO).

MATERIALS AND METHODS

Subjects with MHNO (n=462), MHO (n=192), MONO (n=315), and MOO (n=335) were randomly selected from the Chennai Urban Rural Epidemiology Study. Adiponectin, visfatin, resistin, high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), oxidized low-density lipoprotein (LDL), and monocyte chemoattractant protein-1 (MCP-1) were measured by enzyme-linked immunosorbent assay.

RESULTS

Levels of adiponectin were lowest in the MOO group, followed by the MONO, MHO, and the MHNO groups (P=0.042), whereas the levels of visfatin (P=0.042) and resistin (P=0.043) were highest in the MOO group, followed by the MONO, MHO, and the MHNO groups. Levels of hs-CRP (P=0.029), TNF-α (P=0.036), IL-6 (P=0.042), oxidized LDL (P=0.036), and MCP-1 (P=0.039) increased from the MHNO to MHO to MONO to MOO phenotypes. Linear regression analysis of the parameters with body mass index (BMI) and metabolic syndrome components showed that adiponectin is negatively associated with abdominal obesity (β=-0.060; P=0.039) and BMI (β=-0.076; P=0.009) and that TNF-α is negatively associated with high-density lipoprotein levels (β=0.114, P=0.049) even after adjusting for age and gender. hs-CRP (β=0.112, P=0.020) and oxidized LDL (β=0.114, P=0.050) showed a positive association with systolic blood pressure even after adjusting for age and gender.

CONCLUSIONS

The metabolically obese phenotype is characterized by altered adipokine and inflammatory profiles, which could make this phenotype at high risk for type 2 diabetes mellitus and cardiovascular diseases.

Subclinical impairment of left ventricular function in diabetic patients with or without obesity: A study based on three-dimensional speckle tracking echocardiography

AIMS

The aim of this study was to investigate subclinical left ventricular (LV) changes between type 2 diabetic patients with or without obesity using three-dimensional speckle-tracking echocardiography (3DSTE).

METHODS

A total of 77 type 2 diabetic patients, including 36 subjects with BMI < 25 kg/m(2) and 41 subjects with BMI ≥ 25 kg/m(2), as well as 40 age- and sex-matched controls (BMI: 18.5 ~ 24.5 kg/m(2)) were studied. Waist circumference was measured in diabetic patients with a BMI ≥ 25 kg/m(2) to determine whether abdominal obesity as a complication was present. Real-time three-dimensional (3D) full volume images of the left ventricle were recorded and analyzed. Left ventricular ejection fraction (LVEF), global longitudinal strain (GLS), global circumferential strain (GCS), global area strain (GAS), and global radial strain (GRS) were calculated and compared.

RESULTS

Compared with the controls, diabetic subjects without overall obesity had significantly lower GCS, GAS, and GRS (p < 0.05), as well as markedly lower GLS (p < 0.001). However, 3D-LVEF and all global strains in diabetic subjects with overall obesity were not only markedly lower compared with controls (p  <  0.002 and p < 0.001), but also significantly lower than those in diabetic subjects without overall obesity (p  <  0.002 and p  <  0.05). HbA1c and BMI showed negative impacts on all strains in diabetic patients. Meanwhile, the diabetic subjects with overall and abdominal obesity had significantly reduced GLS, GCS, GAS, and GRS compared with those with overall obesity only (all p  <  0.05).

CONCLUSIONS

Type 2 diabetic patients demonstrated early-stage subclinical LV deformation and dysfunction, whilst coexistent obesity resulted in further damage to myocardial contractility and reduced LVEF. 3DSTE was a sensitive method for detecting these abnormalities.

Are metabolically healthy obese individuals really healthy?

Obesity has become one of the major public health concerns of the past decades, because it is a key risk factor for type 2 diabetes, cardiovascular diseases, dyslipidemia, hypertension, and certain types of cancer, which may lead to increased mortality. Both treatment of obesity and prevention of obesity-related diseases are frequently not successful. Moreover, a subgroup of individuals with obesity does not seem to be at an increased risk for metabolic complications of obesity. In this literature, this obesity subphenotype is therefore referred to as metabolically healthy obesity (MHO). Importantly, individuals with MHO do not significantly improve their cardio-metabolic risk upon weight loss interventions and may therefore not benefit to the same extent as obese patients with metabolic comorbidities from early lifestyle, bariatric surgery, or pharmacological interventions. However, it can be debated whether MHO individuals are really healthy, especially since there is no general agreement on accepted criteria to define MHO. In addition, overall health of MHO individuals may be significantly impaired by several psycho-social factors, psychosomatic comorbidities, low fitness level, osteoarthritis, chronic pain, diseases of the respiratory system, the skin, and others. There are still open questions about predictors, biological determinants, and the mechanisms underlying MHO and whether MHO represents a transient phenotype changing with aging and behavioral and environmental factors. In this review, the prevalence, potential biological mechanisms, and the clinical relevance of MHO are discussed.

The prevalence of metabolically healthy obesity: a systematic review and critical evaluation of the definitions used

We performed a systematic review of the prevalence of metabolically healthy obesity (MHO). Medline, Web of Science and EMBASE were searched for original articles from inception to November 2013. Only prospective and cross-sectional studies were included. After screening 478 titles, we selected 55 publications, of which 27 were population-based studies and were used in the narrative synthesis. From the 27 studies, we identified 30 definitions of metabolic health, mainly based on four criteria: blood pressure, high-density lipoprotein cholesterol, triglycerides and plasma glucose. Body mass index ≥30 kg m(-2) was the main indicator used to define obesity (74% of the studies). Overall, MHO prevalence ranged between 6% and 75%. In the studies that stratified the analysis by sex, prevalence was higher in women (seven out of nine studies) and in younger ages (all four studies). One-third of the studies (n = 9) reported the response rate. Of these, four reported a response rate of ≥70% and they showed MHO prevalence estimates between 10% and 51%. The heterogeneity of MHO prevalence estimates described in this paper strengthens calls for the urgent need for a commonly established metabolic health definition.

The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies

BACKGROUND

Not all obese subjects have an adverse metabolic profile predisposing them to developing type 2 diabetes or cardiovascular disease. The BioSHaRE-EU Healthy Obese Project aims to gain insights into the consequences of (healthy) obesity using data on risk factors and phenotypes across several large-scale cohort studies. Aim of this study was to describe the prevalence of obesity, metabolic syndrome (MetS) and metabolically healthy obesity (MHO) in ten participating studies.

METHODS

Ten different cohorts in seven countries were combined, using data transformed into a harmonized format. All participants were of European origin, with age 18-80 years. They had participated in a clinical examination for anthropometric and blood pressure measurements. Blood samples had been drawn for analysis of lipids and glucose. Presence of MetS was assessed in those with obesity (BMI ≥ 30 kg/m2) based on the 2001 NCEP ATP III criteria, as well as an adapted set of less strict criteria. MHO was defined as obesity, having none of the MetS components, and no previous diagnosis of cardiovascular disease.

RESULTS

Data for 163,517 individuals were available; 17% were obese (11,465 men and 16,612 women). The prevalence of obesity varied from 11.6% in the Italian CHRIS cohort to 26.3% in the German KORA cohort. The age-standardized percentage of obese subjects with MetS ranged in women from 24% in CHRIS to 65% in the Finnish Health2000 cohort, and in men from 43% in CHRIS to 78% in the Finnish DILGOM cohort, with elevated blood pressure the most frequently occurring factor contributing to the prevalence of the metabolic syndrome. The age-standardized prevalence of MHO varied in women from 7% in Health2000 to 28% in NCDS, and in men from 2% in DILGOM to 19% in CHRIS. MHO was more prevalent in women than in men, and decreased with age in both sexes.

CONCLUSIONS

Through a rigorous harmonization process, the BioSHaRE-EU consortium was able to compare key characteristics defining the metabolically healthy obese phenotype across ten cohort studies. There is considerable variability in the prevalence of healthy obesity across the different European populations studied, even when unified criteria were used to classify this phenotype.

Lean people with dysglycemia have a worse metabolic profile than centrally obese people without dysglycemia

AIM

This study compared metabolic profiles of Asian Indians with normal waist circumference (WC) and dysglycemia versus those with high WC without dysglycemia.

SUBJECTS AND METHODS

In 2,350 subjects ≥20 years of age from the Chennai Urban Rural Epidemiology Study with full anthropometric and biochemical characterization, high WC was defined as ≥90 cm in males and ≥80 cm in females. Dysglycemia was defined as prediabetes (fasting plasma glucose ≥100 mg/dL and/or 2-h plasma glucose ≥140 mg/dL) or diabetes (fasting plasma glucose ≥126 mg/dL, 2-h plasma glucose ≥200 mg/dL, or treatment for diagnosed diabetes). Coronary artery disease (CAD) was defined as known myocardial infarction or Q waves on electrocardiography. Multivariable logistic regression models were used to explore factors associated with CAD.

RESULTS

Of the subjects, 260 (11.1%) had dysglycemia with normal WC, and 679 (28.9%), had high WC without dysglycemia. Compared with subjects with high WC without dysglycemia, those with dysglycemia/normal WC, adjusted for age, were more likely to be males (P<0.001) and have higher systolic blood pressure (P<0.05), higher serum triglycerides (P<0.001), higher tumor necrosis factor-α (P<0.001), lower high-density lipoprotein cholesterol (P<0.05), and higher prevalence of CAD (6.3% vs. 2.0%; odds ratio 3.25 [95% confidence interval 1.52-6.94]; P=0.002).

CONCLUSIONS

Dysglycemia is associated with a worse cardiometabolic profile than central obesity alone.

Serum magnesium in the metabolically-obese normal-weight and healthy-obese subjects

BACKGROUND

Given that hypomagnesemia is related with hyperglycemia, hypertension, hypertriglyceridemia, and insulin resistance, the objective of this study was to determine whether serum magnesium levels are associated with the metabolically obese normal weight (MONW) and the metabolically healthy obese (MHO) phenotypes.

METHODS

Population-based cross-sectional study that enrolled 427 subjects, men and non-pregnant women aged 20 to 65years, to participate in the study. Subjects were allocated into groups with and without obesity; among non-obese individuals, the subgroup of MONW subjects was compared with a control group of healthy normal-weight individuals. Among obese individuals, the subgroup of MHO subjects was compared with a control group of obese subjects who exhibited at least one metabolic abnormality. In the absence of obesity, the presence of fasting hyperglycemia, insulin resistance, hypertriglyceridemia, and/or hypertension defined the presence of MONW phenotype. In the absence of hypertension, insulin resistance and metabolic abnormalities of fasting glucose and triglycerides levels, the phenotypically obese subjects were defined as MHO individuals.

RESULTS

The sex-adjusted prevalence of MONW and MHO phenotypes was 40.8% and 27.9%. The multivariate logistic regression model adjusted by family history of diabetes, age, body mass index, and waist-circumference, showed a positive association between hypomagnesemia and the MONW phenotype (OR 6.4; 95%CI 2.3-20.4) and negative relationship between serum magnesium and the MHO phenotype (OR 0.32; 95%CI 0.17-0.61).

CONCLUSIONS

Our results show that hypomagnesemia is positively associated with the presence of MONW phenotype, and the normomagnesemia negatively with the MHO phenotype.

Pleiotropic effects of obesity-susceptibility loci on metabolic traits: a meta-analysis of up to 37,874 individuals

AIMS/HYPOTHESIS

Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ratio (WHR) also influence metabolic and cardiovascular traits, independently of obesity-related traits, in meta-analyses of up to 37,874 individuals from six European population-based studies.

METHODS

We examined associations of 32 BMI and 14 WHR loci, individually and combined in two genetic predisposition scores (GPSs), with glycaemic traits, blood lipids and BP, with and without adjusting for BMI and/or WHR.

RESULTS

We observed significant associations of BMI-increasing alleles at five BMI loci with lower levels of 2 h glucose (RBJ [also known as DNAJC27], QPTCL: effect sizes -0.068 and -0.107 SD, respectively), HDL-cholesterol (SLC39A8: -0.065 SD, MTCH2: -0.039 SD), and diastolic BP (SLC39A8: -0.069 SD), and higher and lower levels of LDL- and total cholesterol (QPTCL: 0.041 and 0.042 SDs, respectively, FLJ35779 [also known as POC5]: -0.042 and -0.041 SDs, respectively) (all p < 2.4 × 10(-4)), independent of BMI. The WHR-increasing alleles at two WHR loci were significantly associated with higher proinsulin (GRB14: 0.069 SD) and lower fasting glucose levels (CPEB4: -0.049 SD), independent of BMI and WHR. A higher GPS-BMI was associated with lower systolic BP (-0.005 SD), diastolic BP (-0.006 SD) and 2 h glucose (-0.013 SD), while a higher GPS-WHR was associated with lower HDL-cholesterol (-0.015 SD) and higher triacylglycerol levels (0.014 SD) (all p < 2.9 × 10(-3)), independent of BMI and/or WHR.

CONCLUSIONS/INTERPRETATION

These pleiotropic effects of obesity-susceptibility loci provide novel insights into mechanisms that link obesity with metabolic abnormalities.

Are there still healthy obese patients?

PURPOSE OF REVIEW

Obesity is associated with an increased risk of premature death and represents a fast growing worldwide health problem that is reaching epidemic proportions. Obesity significantly increases the risk of developing metabolic disorders, hypertension, coronary heart disease, stroke, and several types of cancer. However, a subgroup of 'healthy' obese patients seems to be protected against metabolic and cardiovascular obesity comorbidities. This review focuses on potential mechanisms underlying the healthy obese subphenotype.

RECENT FINDINGS

Individuals with obesity typically develop type 2 diabetes, dyslipidemia, fatty liver disease, gout, hypertension, and cardiovascular disease. In the past years it became clear that up to 30% of obese patients are metabolically healthy with insulin sensitivity similar to healthy lean individuals, lower liver fat content, and lower intima media thickness of the carotid artery than the majority of metabolically 'unhealthy' obese patients. Recent studies suggest that protection against development of hepatic steatosis, ectopic fat deposition, inflammation of visceral adipose tissue, and adipose tissue dysfunction contributes to healthy obesity.

SUMMARY

For the stratification of obesity treatment, definition of metabolically healthy or high-risk phenotypes will facilitate the identification of the obese person who will benefit the most from early lifestyle, bariatric surgery, or pharmacological interventions.

Population-based versus high-risk strategies for the prevention of cardiovascular diseases in low- and middle-income countries

Cardiovascular diseases (CVD) are now the number one cause of death in low- and middle-income countries (LMIC), such as those in South East Asia (SEA). It is projected that SEA countries will have the greatest total number of deaths due to non-communicable diseases (NCDs) by 2020. In low resource countries, the rising burden of CVDs imposes severe economic consequences that range from impoverishment of families to high health system costs and the weakening of country economies. There are two possible options to be considered for addressing this issue: a "population-based strategy" and/or a "high risk" strategy. The question is, what is the optimal way to reduce the excessive burden of these diseases in the LMICs. We believe that by applying systematic policy and smoking cessation programs with proven effectiveness, there is a chance that the high smoking prevalence, particularly among SEA.