Metabolically healthy obese and metabolically unhealthy non-obese phenotypes in a Russian population

Associations between residential greenness and obesity phenotypes among adults in Southwest China

BACKGROUND

Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations.

METHODS

We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level.

RESULTS

Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes.

CONCLUSIONS

Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.

Hyperuricemia as an effect modifier of the association between metabolic phenotypes and nonalcoholic fatty liver disease in Chinese population

BACKGROUND

Different metabolic phenotypes may be related to nonalcoholic fatty liver disease (NAFLD), but such association whether modified by serum uric acid levels is unknown. We examined the association between different metabolic phenotypes and NAFLD and further explore whether hyperuricemia could modify this association.

METHODS

A total of 2959 participants (mean age: 55.02 years) with medical checkups were recruited from Tianjin Medical University General Hospital. Participants were categorized into four groups according to their BMI levels and metabolically healthy status: metabolically healthy normal weight (MHNW), metabolically healthy overweight or obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy overweight or obese (MUO). Blood samples (including serum uric acid) were collected from participants after an overnight fast. NAFLD was diagnosed based on abdominal ultrasonography scanning. Data were analyzed using logistic regression models and the interaction effect model.

RESULTS

The prevalence of NAFLD in MHNW, MHO, MUNW, and MUO groups was 9.9% (7.9-12.0%), 42.8% (39.5-46.1%), 36.5% (31.2-41.9%), and 69.7% (66.8-72.6%), respectively. In multi-adjusted logistic models, the ORs (95% CIs) of NAFLD were 5.32 (4.01-7.04) for participants with MHO, 4.51 (3.17-6.40) for those with MUNW, and 13.68 (10.23-18.30) for those with MUO compared to those with MHNW. In the stratified analysis by uric acid levels, the prevalence of NAFLD was significantly higher in participants with MHO, MUNW, and MUO in the hyperuricemia group than those in the normal uric acid group, and the interaction effect of metabolic phenotypes and uric acid on NAFLD was statistical significant (P < 0.05).

CONCLUSIONS

MHO, MUNW, and MUO were associated with higher prevalence of NAFLD. Serum uric acid levels may modify the association between metabolically phenotypes and NAFLD.

Prediction of MAFLD and NAFLD using different screening indexes: A cross-sectional study in U.S. adults

INTRODUCTION

Metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD), has become the most common chronic liver disease worldwide. We aimed to explore the gender-related association between nine indexes (BMI/WC/VAI/LAP/WHtR/TyG/TyG-BMI/TyG-WC/TyG-WHtR) and MAFLD/NAFLD and examine their diagnostic utility for these conditions.

METHODS

Eligible participants were screened from the 2017-2018 cycle data of National Health and Nutrition Examination Survey (NHANES). Logistic regression and receiver operating characteristic (ROC) curve were used to assess the predictive performance of 9 indexes for MAFLD/NAFLD.

RESULTS

Among the 809 eligible individuals, 478 had MAFLD and 499 had NAFLD. After adjusting for gender, age, ethnicity, FIPR and education level, positive associations with the risk of MAFLD/NAFLD were found for all the nine indexes. For female, TyG-WHtR presented the best performance in identifying MAFLD/NAFLD, with AUC of 0.845 (95% CI = 0.806-0.879) and 0.831 (95% CI = 0.791-0.867) respectively. For male, TyG-WC presented the best performance in identifying MAFLD/NAFLD, with AUC of 0.900 (95% CI = 0.867-0.927) and 0.855 (95% CI = 0.817-0.888) respectively.

CONCLUSION

BMI/WC/VAI/LAP/WHtR/TyG/TyG-BMI/TyG-WC/TyG-WHtR are important indexes to identify the risk of MAFLD and NAFLD.

Serum Lipids and Risk of Incident Psoriasis: A Prospective Cohort Study from the UK Biobank Study and Mendelian Randomization Analysis

The association between dyslipidemia and psoriasis has been studied widely. However, which individual indicators of serum lipids determine an increasing risk of incident psoriasis is still underappreciated in prospective cohorts. On the basis of UK Biobank, we investigate the causal relationship between four serum lipids and incident psoriasis by Cox proportional hazard model and Mendelian randomization analysis. After adjusting for covariates, high-density lipoprotein deficiency (<1.0 mmol/l for men, <1.3 mmol/l for women) and high triglyceride level (≥1.7 mmol/l) at baseline were associated with 16.6% and 10.6% increased risk of incident psoriasis, respectively. The effects were more pronounced in women, with 16.9 and 19.7% additional risk of psoriasis, respectively. The effects in the younger group (aged <60 years) and obese group in women were also more pronounced. No similar effect was observed in low-density lipoprotein and total cholesterol. Our subsequent Mendelian randomization analysis reinforced the main finding that high-density lipoprotein deficiency and high triglyceride cause incident psoriasis genetically. In conclusion, serum high-density lipoprotein/triglyceride levels predict psoriasis, particularly in women, indicating a distinct role of lipids engaging in the pathogenesis of psoriasis modified by sex. More metabolic-targeted, sex-specific management of psoriasis is suggested in the future.

Metabolically Neutral Obesity: Terminology, Prevalence, And Meaning

Determining the leptin level in patients with abdominal obesity without signs of insulin resistance is necessary for stratifying patients into groups with normal (metabolically neutral obesity) and increased adipokine activity. Objective — To compare the prevalence of metabolic disorders and signs of cardiovascular remodeling in young and middle-aged men with "metabolically healthy" and "metabolically neutral" obesity. Material and methods — observational sample survey of 590 men aged 38.5±5.6 years was conducted. Average body weight was assessed on301 men (the control group). Obesity was determined in 289 patients: among them, the criteria for metabolic syndrome were diagnosed for 134 study participants, metabolically healthy obesity (MHO) was diagnosed in 155 men, and 86 patients from MHO with leptin levels <3.5 ng/ml constituted metabolically neutral obesity group. All patients were evaluated by a lipidogram, adipokine, glycemic profiles, and ultrasound examination of the heart and carotid arteries. Results — Criteria for metabolically neutral abdominal obesity in men were determined: weight gain >30 kg/m2 in the presence of no more than two criteria for metabolic syndrome and leptin level <3.5 ng/ml. The metabolically neutral type was characterized by a better lipid profile, which was confirmed by a lower frequency of dyslipidemia (1.7 times); the frequency of prediabetes was 7% and was half as low as in metabolically healthy obesity; atherosclerosis of the carotid arteries was 1.5 times less common in the neutral type of obesity. Conclusion — The selection of a "metabolically neutral" type of obesity is justified since it allows us to determine the stage of the disease at which the frequency of metabolic and cardiovascular disorders is still minimal and non-drug prevention is necessary.

Obesity Prevalence and Associated Socio-Demographic Characteristics and Health Behaviors in Russia and Norway

Associations between obesity and socio-demographic and behavioral characteristics vary between populations. Exploring such differences should throw light on factors related to obesity. We examined associations between general obesity (GO, defined by body mass index) and abdominal obesity (AO, defined by waist-to-hip ratio) and sex, age, socio-economic characteristics (education, financial situation, marital status), smoking and alcohol consumption in women and men aged 40–69 years from the Know Your Heart study (KYH, Russia, N = 4121, 2015–2018) and the seventh Tromsø Study (Tromsø7, Norway, N = 17,646, 2015–2016). Age-standardized prevalence of GO and AO was higher in KYH compared to Tromsø7 women (36.7 vs. 22.0% and 44.2 vs. 18.4%, respectively) and similar among men (26.0 vs. 25.7% and 74.8 vs. 72.2%, respectively). The positive association of age with GO and AO was stronger in KYH vs. Tromsø7 women and for AO it was stronger in men in Tromsø7 vs. KYH. Associations between GO and socio-economic characteristics were similar in KYH and Tromsø7, except for a stronger association with living with spouse/partner in KYH men. Smoking had a positive association with AO in men in Tromsø7 and in women in both studies. Frequent drinking was negatively associated with GO and AO in Tromsø7 participants and positively associated with GO in KYH men. We found similar obesity prevalence in Russian and Norwegian men but higher obesity prevalence in Russian compared to Norwegian women. Other results suggest that the stronger association of obesity with age in Russian women is the major driver of the higher obesity prevalence among them compared to women in Norway.

Dissecting the clinical relevance of polygenic risk score for obesity-a cross-sectional, longitudinal analysis

BACKGROUND

Obesity is a global pandemic disease whose prevalence is increasing worldwide. The clinical relevance of a polygenic risk score (PRS) for obesity has not been fully elucidated in Asian populations.

METHOD

We utilized a comprehensive health check-up database from the Korean population in conjunction with genotyping to generate PRS for BMI (PRS-BMI). We conducted a phenome-wide association (PheWAS) analysis and observed the longitudinal association of BMI with PRS-BMI.

RESULTS

PRS-BMI was generated by PRS-CS. Adding PRS-BMI to a model predicting ten-year BMI based on age, sex, and baseline BMI improved the model's accuracy (p = 0.003). In a linear mixed model of longitudinal change in BMI with aging, higher deciles of PRS were directly associated with changes in BMI. In the PheWAS, significant associations were observed for metabolic syndrome, bone density, and fatty liver. In the lean body population, those having the top 20% PRS-BMI had higher BMI and body fat mass along with better metabolic trait profiles compared to the bottom 20%. A bottom-20% PRS-BMI was a risk factor for metabolically unhealthy lean body (odds ratio 3.092, 95% confidence interval 1.707-6.018, p < 0.001), with adjustment for age, sex and BMI.

CONCLUSIONS

Genetic predisposition to obesity as defined by PRS-BMI was significantly associated with obesity-related disease or trajectory of obesity. Low PRS-BMI might be a risk factor associated with a metabolically unhealthy lean body. Better understanding the mechanisms of these relationships may allow tailored intervention in obesity or early selection of populations at risk of metabolic disease.

Systematic review and meta-analysis: Associations between metabolic syndrome and colorectal neoplasia outcomes

AIM

Metabolic syndrome (MetS) is a cluster of factors including obesity, hypertension, diabetes, hypercholesterolemia and hyperlipidaemia. It has been associated with an increased risk of colorectal neoplasia. This systematic review and meta-analysis assessed the association between MetS and (i) recurrence of adenomas or occurrence of CRC in patients with prior adenomas, and (ii) survival in patients with CRC.

METHOD

MEDLINE, Embase, Scopus and Web of Science were searched up to 22 November 2019. Two authors independently conducted title and abstract screening; full text of eligible studies was evaluated. Where ≥3 studies reported effect measures for a specific outcome, meta-analysis using random effects model was conducted. I² was used to assess between-study heterogeneity. Quality appraisal was undertaken with the Newcastle-Ottawa Score.

RESULTS

The search identified 1,764 articles, 55 underwent full text screening, resulting in a total of 15 eligible studies. Five studies reported on metachronous neoplasia, with differing outcomes precluded a meta-analysis. No consistent relationship between MetS and metachronous neoplasia was found. Ten studies reported on survival outcomes. MetS was associated with poorer CRC-specific survival (HR = 1.8, 95% CI: 1.04-3.12, I²  = 92.7%, n = 3). Progression-free survival was also worse but this did not reach statistical significance (HR = 1.12, 95% CI: 0.89-1.42, I²  = 85.6%, n = 3). There was no association with overall survival (HR = 1.04, 95% CI: 0.94-1.15, I²  = 43.7%, n = 7). Significant heterogeneity was present but subgroup analysis did not account for this.

CONCLUSION

MetS is associated with poorer CRC-specific survival, but evidence is inconsistent on metachronous neoplasia. Further research is warranted to better understand the impact of MetS on the adenoma-carcinoma pathway.

Metabolic Obesity in People with Normal Body Weight (MONW)-Review of Diagnostic Criteria

Disorders of metabolic obesity with normal body weight (MONW) are widely recognized risk factors for the development of cardiovascular diseases and type 2 diabetes. Despite this, MONW is not diagnosed in clinical practice. There is no consensus on the definition of MONW, and measuring the degree of insulin resistance or obesity among apparently healthy, non-obese patients is not widely applicable. The awareness of the relationship between metabolic disorders such as MONW and a higher risk of mortality from cardiovascular causes and other related diseases prompts the need for action to be taken aimed at creating appropriate diagnostic models that will allow for the effective detection of those with metabolic abnormalities among people with normal body weight. Such actions are decisive in the prevention and treatment of diseases. Therefore, the purpose of this article is to review the MONW diagnostic criteria used over the years.

The Relationship Between Obesity and Depression Is Partly Dependent on Metabolic Health Status: A Nationwide Inpatient Sample Database Study

OBJECTIVE

Some studies have demonstrated a bidirectional association between obesity and depression, whereas others have not. This discordance might be due to the metabolic health status. We aimed to determine whether the relationship between obesity and depression is dependent on metabolic health status.

METHODS

In total, 9,022,089 participants were enrolled and classified as one of four obesity phenotypes: metabolically healthy nonobesity (MHNO), metabolically unhealthy nonobesity (MUNO), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). We then divided the population into eight phenotypes based on obesity and the number of metabolic risk factors. Furthermore, the associations of eight phenotypes, based on obesity and specific metabolic risk factors, with depression were assessed.

RESULT

Among all participants, a higher risk of depression was observed for MUNO, MHO and MUO than for MHNO. The risk was highest for MUO (OR = 1.442; 95% CI = 1.432, 1.451). However, the association between MHO and depression was different for men and women (OR = 0.941, men; OR = 1.132, women). The risk of depression increased as the number of metabolic risk factors increased. Dyslipidemia was the strongest metabolic risk factor. These relationships were consistent among patients ≥ 45 years of age.

CONCLUSIONS

The increased risk of obesity-related depression appears to partly depend on metabolic health status. The results highlight the importance of a favorable metabolic status, and even nonobese populations should be screened for metabolic disorders.

Does Proteomic Mirror Reflect Clinical Characteristics of Obesity?

Obesity is a frightening chronic disease, which has tripled since 1975. It is not expected to slow down staying one of the leading cases of preventable death and resulting in an increased clinical and economic burden. Poor lifestyle choices and excessive intake of “cheap calories” are major contributors to obesity, triggering type 2 diabetes, cardiovascular diseases, and other comorbidities. Understanding the molecular mechanisms responsible for development of obesity is essential as it might result in the introducing of anti-obesity targets and early-stage obesity biomarkers, allowing the distinction between metabolic syndromes. The complex nature of this disease, coupled with the phenomenon of metabolically healthy obesity, inspired us to perform data-centric, hypothesis-generating pilot research, aimed to find correlations between parameters of classic clinical blood tests and proteomic profiles of 104 lean and obese subjects. As the result, we assembled patterns of proteins, which presence or absence allows predicting the weight of the patient fairly well. We believe that such proteomic patterns with high prediction power should facilitate the translation of potential candidates into biomarkers of clinical use for early-stage stratification of obesity therapy.

[Obesity without diabetes: the role of hormonal regulation]

AIM

Obese patients without diabetes present an interesting phenotype to explore protective mechanisms against type 2 diabetes (T2D) development. In our study we looked for specific hormonal features of obese patients without T2D.

MATERIALS AND METHODS

We included 6 groups of patients with different metabolic profiles (n=212): controls with BMI25 kg/m2, HbA1c6%, age 30 years; patients with 25BMI30 kg/m2and HbA1c6%; patients with 25BMI30 kg/m2and HbA1c6%; patients with BMI30 kg/m2and HbA1c6% (+ Obesity - T2D) obese patients without T2D or prediabetes; patients with BMI30 kg/m2and newly-diagnosed T2D/prediabetes, HbA1c6%; patients with known history of T2D on glucose-lowering drugs with BMI30 kg/m2. Insulin, GLP-1, GIP were measured during glucose-tolerance test at 0, 30 and 120 minutes; insulin resistance (IR) was assessed by HOMA-IR.

RESULTS

Waist circumference was bigger in patients with obesity despite their metabolic profile comparing to patients without obesity (p0.001). Waist-to-hip ratio was similar in patients with different metabolic status. According to IR + Obesity - T2D group had intermediate position: IR was higher in that group comparing to people without obesity, but was less that in patients with obesity and HbA1c6% (p0.001). + Obesity - T2D group had the most potent baseline insulin secretion, assessed by НОМА-%band the highest postprandial secretion, measured by insulinogenic index among all patient groups with obesity (p0.001). There was no significant difference in GLP-1 secretion; GIP secretion was higher in patients with BMI30 kg/m2comparing to people with BMI30 kg/m2(p0.01).

Therapeutic potential of cPLA2 inhibitor to counteract dilated-cardiomyopathy in cholesterol-treated H9C2 cardiomyocyte and MUNO rat

BACKGROUND AND PURPOSE

The pathogenesis of cardiomyopathy in metabolically unhealthy obesity (MUO) has been well studied. However, the pathogenesis of cardiomyopathy typically associated with high cholesterol levels in metabolically unhealthy nonobesity (MUNO) remains unclear. We investigated whether cholesterol-generated LysoPCs contribute to cardiomyopathy and the role of cytosolic phospholipase A2 (cPLA2) inhibitor in cholesterol-induced MUNO.

EXPERIMENTAL APPROACH

Cholesterol diet was performed in Sprague-Dawley rats that were fed either regular chow (C), or high cholesterol chow (HC), or HC diet with 10 % fructose in drinking water (HCF) for 12 weeks. LysoPCs levels were subsequently measured in rats and in MUNO human patients. The effects of cholesterol-mediated LysoPCs on cardiac injury, and the action of cPLA2 inhibitor, AACOCF3, were further assessed in H9C2 cardiomyocytes.

KEY RESULTS

HC and HCF rats fed cholesterol diets demonstrated a MUNO-phenotype and cholesterol-induced dilated cardiomyopathy (DCM). Upregulated levels of LysoPCs were found in rat myocardium and the plasma in MUNO human patients. Further testing in H9C2 cardiomyocytes revealed that cholesterol-induced atrophy and death of cardiomyocytes was due to mitochondrial dysfunction and conditions favoring DCM (i.e. reduced mRNA expression of ANF, BNP, DSP, and atrogin-1), and that AACOCF3 counteracted the cholesterol-induced DCM phenotype.

CONCLUSION AND IMPLICATIONS

Cholesterol-induced MUNO-DCM phenotype was counteracted by cPLA2 inhibitor, which is potentially useful for the treatment of LysoPCs-associated DCM in MUNO.

Sleep Duration, Lipid Profile and Insulin Resistance: Potential Role of Lipoprotein(a)

Lipoprotein (a) (Lp(a)) is considered a genetic factor for cardiovascular disease playing an important role in atherogenesis and thrombosis, but the evidence about its association with sleep duration is controversial. We evaluated the relation between self-reported sleep duration and Lp(a). Among 1600 participants of the population-based sample, we selected 1427 subjects without previously known cardiovascular events, who answered the questions about their sleep duration; had valid lipid profile results (total cholesterol, low- and high-density lipoproteins, Lp(a), apolipoprotein AI (ApoAI), ApoB, and ApoB/ApoAI); and did not take lipid-lowering drugs (mean age 46 ± 12 years). We performed a structured interview, which included questions about lifestyle, medical history, complaints, and sleep duration (How long have you been sleeping per night during the last month?). Sleep duration was classified as follows: <6 h/night—short, 6–9 h/night—normal, and ≥10 h/night—long. Overall, 73 respondents (5.2%) were short-sleepers and 69 (4.8%) long-sleepers. Males were slightly more prevalent among short-sleepers. The groups matched by age, body mass index, blood pressure, diabetes mellitus, and hypertension rate. Short-sleepers had lower rates of high total cholesterol (≥5.0 mmol/L), lower Lp(a) levels and lower rates of increased Lp(a) ≥0.5 g/L, and higher insulin and insulin resistance (assessed by the homeostatic model assessment for insulin resistance (HOMA-IR)). ApoAI, ApoB, their ratio, and other lab tests were similar in the groups. The multinomial logistic regression demonstrated that only the short sleep duration was independently (odds ratio (OR) 0.29, 95% confidence interval (CI) (0.09–0.91), p = 0.033) associated with Lp(a) (χ² = 41.58, p = 0.003). Other influencing factors were smoking and HOMA-IR. Such an association was not found for long-sleepers. In conclusion, a short-sleep duration is associated with Lp(a). The latter might mediate the higher insulin resistance and higher cardiometabolic risks in short-sleepers.

Physiological and Lifestyle Traits of Metabolic Dysfunction in the Absence of Obesity

PURPOSE OF REVIEW

Individuals with metabolically unhealthy normal weight (MUNW) have an adverse cardiometabolic risk factor profile in the absence of excess body weight, and increased risk for diabetes and heart disease. We critically review some physiological traits and lifestyle characteristics of the MUNW phenotype.

RECENT FINDINGS

The prevalence of MUNW varies considerably around the world and among ethnicities, partly because of different definitions; on average, this phenotype affects about ~ 30% of normal weight persons globally. Most studies have recruited MUNW subjects who, although within the normal weight range, are significantly "more obese" than their metabolically healthy lean peers (greater body mass index or total body fat); hence one cannot ascertain whether observed differences are true traits of the MUNW phenotype of simply secondary to greater relative adiposity within the normal range. Carefully matched studies have indicated that MUNW can exist in the absence of excess total body fat. These subjects have a preferential accumulation of fat in the upper body (abdominal subcutaneous and visceral adipose tissues) and the liver, but not skeletal muscle; perhaps surprisingly, this predominantly "android" fat distribution does not translate into increased waist circumference. The MUNW phenotype is associated with lower aerobic fitness and muscle mass and strength, but whether this is simply due to inadequate regular physical activity is not entirely clear. Likewise, no consistent associations have been found between any dietary factors and the development of MUNW phenotype, but diet-induced modest weight loss facilitates its resolution. Delineating the mechanisms leading to metabolic dysfunction in the absence of increased body weight and body fat will likely reveal important targets for improving metabolic health and eventually for reducing the burden of cardiometabolic disease, not only in individuals with normal body weight but also in people with obesity.

Biobanking as a necessary tool for research in the field of personalized medicine in the scientific medical center

The National Medical Research Center for Preventive Medicine of Russia (NMRCPM) conducts epidemiological and clinical research for the development of personalized medicine. This is why NMRCPM has faced the problem of how to standardize preanalytical conditions for all biospecimens from various scientific projects and of how to provide long-term responsible standardized regulated safe storage of blood and its derivatives. This article describes various aspects of establishing a biobank in a large medical center dedicated to integrating the biomarkers research activities of different departments. To date, >205,000 serum/plasma/whole blood specimens have been stored. Collaboration with >25 scientific projects as well as the biobank’s own research project has been organized. The availability of this biobank became a platform for the establishment of the Personalized Medicine Center in NMRCPM.

Prevalence and clinical characteristics of metabolically unhealthy obesity in an Iranian adult population

PURPOSE

The incidence of obesity is globally increasing and it is a predisposing factor for morbidity and mortality. This study assessed the prevalence of metabolically unhealthy (MU) individuals and its determinants according to body mass index (BMI).

MATERIALS AND METHOD

In our cross-sectional study, 891 persons aged 30 years or older participated. Participants were classified as obese (BMI ≥30 kg/m²), overweight (BMI 25-<30 kg/m² and normal weight (BMI <25 kg/m²). Metabolic health status was defined using four existing cardio-metabolic abnormalities (elevated blood pressure, elevated serum concentrations of triglyceride and fasting glucose and a low serum concentration of high density lipoprotein cholesterol). Then, two phenotypes were defined: healthy (existence of 0-1 cardio-metabolic abnormalities) and unhealthy (presence of 2 or more cardio-metabolic abnormalities).

RESULT

Overall, 10.9% (95% confidence interval (CI): 8.8-13.0) and 7.2% (95% CI: 5.5-8.9) of participants were MU obese and metabolically healthy obese, respectively. The prevalence of MU was higher in overweight (55.6%; 95% CI: 50.6-60.6, p<0.001) and obese (60.2%; 95% CI: 52.8-67.6, p=0.001) subjects than in individuals with a normal weight (37.5%; 95% CI: 29.4-42.6). Multiple logistic regression analysis showed an association of a MU state with age and dyslipidaemia in the BMI subgroups and with female sex in the normal weight individuals.

CONCLUSION

The prevalence of a MU state increased with increasing BMI. Ageing and dyslipidaemia were associated with an unhealthy metabolic state in normal weight, overweight and obese subjects and with the female sex in normal weight subjects.

Social jetlag and metabolic control in non-communicable chronic diseases: a study addressing different obesity statuses

Social jetlag – a measure of disruption of the circadian system – has been linked to obesity, but its association with metabolic complications in non-communicable chronic diseases (NCCDs) is unknown in the literature. We examined the associations between social jetlag and obesity status and metabolic parameters among individuals with NCCDs. Patients (n = 792) with NCCDs (obesity, systemic arterial hypertension, type 2 diabetes mellitus or dyslipidaemia) attended clinics of the public health service of the city of Uberlândia, Minas Gerais State, Brazil. They were classified in three obesity statuses: non-obese: BMI < 30 kg/m²; metabolically healthy obese (MHO): BMI ≥ 30 kg/m² and less than three high-risk biomarkers for metabolic syndrome; and metabolically unhealthy obese (MUO): BMI ≥ 30 kg/m² and with high-risk values on three or more biomarkers for metabolic syndrome. After adjustments for confounding variables, social jetlag was positively associated with fasting glucose levels among all subjects (β = 0.08, p = 0.03) and MUO subjects (β = 0.32, p < 0.001). Patients with social jetlag (>1 h) presented a significant odds ratio (OR) of being overweight (OR = 2.0, confidence interval (CI) = 1.2–3.6, p = 0.006) and MUO (OR = 1.8, CI = 1.1–2.8, p = 0.01). These results suggest that social jetlag is associated with a higher risk of overweight and related metabolic complications in individuals with NCCDs.

Insulin-sensitive and insulin-resistant obese and non-obese phenotypes: role in prediction of incident pre-diabetes in a longitudinal biracial cohort

OBJECTIVE

We measured insulin sensitivity with euglycemic clamp (Si-clamp) in initially normoglycemic African Americans (AA) and European Americans (EA), to probe the existence of subphenotypes of obesity and leanness, and their impact on incident dysglycemia during longitudinal follow-up.

RESEARCH DESIGN AND METHODS

320 healthy subjects (176 AA, 144 EA; mean age 44.2±10.6 years) underwent baseline assessments, including Si-clamp and homeostasis model of insulin resistance (HOMA-IR) and were stratified into: insulin-resistant obese (IRO) (body mass index (BMI) >30 kg/m², Si-clamp <0.1, HOMA-IR >2.5); insulin-sensitive obesity (ISO) (BMI >30 kg/m², Si-clamp >0.1, HOMA-IR <2.5); insulin-resistant non-obese (IRN) (BMI <28 kg/m², Si-clamp <0.1, HOMA-IR >2.5); insulin-sensitive non-obese (ISN) (BMI <28 kg/m², Si-clamp >0.1, HOMA-IR <2.5). Outcome measures were cardiometabolic risks and incident pre-diabetes/type 2 diabetes (T2D) during 5.5 years.

RESULTS

Compared with IRO, subjects with ISO had lower abdominal fat, triglycerides and high-sensitivity C reactive protein and higher adiponectin (p=0.015 to <0.0001). IRN subjects had higher cardiometabolic risk markers than ISN (p=0.03 to <0.0001). During 5.5-year follow-up, incident pre-diabetes/T2D was lower in ISO (31.3% vs 48.7%) among obese subjects and higher in IRN (47.1% vs. 26.0%) among non-obese subjects (p=0.0024). Kaplan-Meier analysis showed significantly different pre-diabetes/T2D survival probabilities across insulin sensitivity/adiposity phenotypes (p=0.0001).

CONCLUSIONS

Insulin sensitivity predicts ~40% decrease in the relative risk of incident pre-diabetes/T2D among obese persons, whereas insulin resistance predicts ~80% increased risk among non-obese persons. This is the first documentation of healthy and unhealthy phenotypes of obesity and leanness in a prospective biracial cohort, using rigorous measurement of insulin sensitivity.