Metabolically healthy obesity and risk of mortality: does the definition of metabolic health matter?

Metabolically healthy obesity and risks of cardiovascular disease and all-cause mortality, a matched cohort study: the Shizuoka study

BACKGROUND

Metabolically healthy obesity is not always a benign condition. It is associated with an increased incidence of cardiovascular disease and all-cause mortality. We investigated the prognostic significance of metabolically healthy obesity by comparing clinical profile-matched metabolically healthy obesity and non-obesity groups.

METHODS

We analyzed a health insurance dataset with annual health checkup data from Japan. The analyzed data included 168,699 individuals aged <65 years. Obesity was defined as ≥25 kg/m2 body mass index. Metabolically healthy was defined as ≤1 metabolic risk factor (high blood pressure, low high-density lipoprotein cholesterol, high low-density lipoprotein cholesterol, or high hemoglobin A1c). Incidence rates of stroke, myocardial infarction, and all-cause mortality identified from the insurance data were compared between metabolically healthy obesity and non-obesity groups (n = 8644 each) using a log-rank test.

RESULTS

The stroke (obesity: 9.2 per 10,000 person-years; non-obesity: 10.5; log-rank test p = 0.595), myocardial infarction (obesity: 3.7; non-obesity: 3.1; p = 0.613), and all-cause mortality (obesity: 26.6; non-obesity: 23.2; p = 0.304) incidence rates did not differ significantly between the metabolically healthy obesity and non-obesity groups, even when the abdominal obesity was considered in the analysis. The lack of association was also observed in the comparison between the metabolically unhealthy obesity and non-obesity groups (n = 10,965 each). The population with metabolically healthy obesity reported negligibly worse metabolic profiles than the population with non-obesity at the 5.6-year follow-up.

CONCLUSION

Obesity, when accompanied by a healthy metabolic profile, did not increase the risk of cardiovascular outcomes and all-cause mortality.

Association between BMI-based metabolic phenotypes and prevalence of intracranial atherosclerotic stenosis: a cross-sectional study

BACKGROUND

Obesity and metabolic syndrome (MetS) have been acknowledged to commonly co-exist and lead to increased risks of stroke, whereas the association between various BMI-based metabolic phenotypes and development of intracranial atherosclerotic stenosis (ICAS) remained controversial.

METHODS

A total of 5355 participants were included from the Asymptomatic Polyvascular Abnormalities Community (APAC) study. Participants were categorized into six groups according to their body mass index (BMI) and MetS status. ICAS was assessed using transcranial Doppler (TCD) Ultrasonography. Logistic regression was employed to evaluate the association between BMI-based metabolic phenotypes and ICAS.

RESULTS

704 participants were diagnosed with ICAS. Compared to the metabolic healthy normal weight (MH-NW) group, the metabolic unhealthy normal weight (MUH-NW) group demonstrated a higher risk of ICAS (full-adjusted odds ratio [OR], 1.91; 95% confidence interval [CI], 1.42-2.57), while no significant association was observed in the metabolic unhealthy obesity (MUO) group (full-adjusted OR, 1.07; 95% CI, 0.70-1.65) and other metabolic healthy groups regardless of BMI. The results were consistent across gender, age, smoking, alcohol intake, and physical activity subgroups.

CONCLUSION

The present study suggested that MUH-NW individuals had a significant association with increased risk of ICAS compared with MH-NW individuals.

Non-Pharmacological Treatment for Cardiovascular Risk Prevention in Children and Adolescents with Obesity

In younger generations, excess weight has reached very alarming levels. Excess weight in adults is associated with increased mortality and morbidity from cardiovascular disease. However, it is not easy to distinguish to what extent these effects are the result of obesity itself or how much is due to the various cardiovascular risk factors that often accompany excess weight. Several risk factors, such as hypertension, dyslipidemia, hyperuricemia, glucose intolerance, and type 2 diabetes mellitus, are already present in pediatric age. Therefore, early intervention with the goal of correcting and/or eliminating them is particularly important. In the child and adolescent with obesity, the first approach to achieve weight reduction and correct the risk factors associated with severe excess weight should always be non-pharmacologic and based on changing poor eating habits and unhealthy lifestyles. The purpose of this review is to give an update on non-pharmacological interventions to be implemented for cardiovascular prevention in children and adolescents with obesity, and their effectiveness. In particular, interventions targeting each individual cardiovascular risk factor will be discussed.

Metabolic obesity phenotypes and all-cause mortality among the Chinese oldest-old population: a prospective cohort study

BACKGROUND

The obesity paradox has been reported among older adults. However, whether the favorable effect of obesity is dependent on metabolic status remains largely unknown. We aimed to explore the association of metabolic obesity phenotypes and their changes with all-cause mortality among the Chinese oldest-old population.

METHODS

This prospective cohort study included 1207 Chinese oldest old (mean age: 91.8 years). Metabolic obesity phenotypes were determined by central obesity and metabolic status, and participants were classified into metabolically healthy obesity (MHO), metabolically unhealthy obesity (MUO), metabolically healthy non-obesity (MHN), and metabolically unhealthy non-obesity (MUN). The hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated by Cox regression models.

RESULTS

During 5.3 years of follow-up, 640 deaths were documented. Compared with non-obesity, obesity was associated with a decreased mortality risk among participants with metabolically healthy (HR, 0.75; 95% CI, 0.63-0.91) while this association was insignificant among metabolically unhealthy. Compared to MHO, MHN (HR, 1.27; 95% CI, 1.06-1.53) and MUN (HR, 1.49; 95% CI, 1.10-2.02) were significantly associated with an increased mortality risk. Compared to those with stable MHO, those transited from MHO to MUO demonstrated a higher mortality risk (HR, 1.81; 95% CI, 1.06-3.11).

CONCLUSIONS

MHO predicts better survival among the Chinese oldest-old population. These findings suggest that ensuring optimal management of metabolic health is beneficial and taking caution in weight loss based on the individual body weight for the metabolically healthy oldest-old adults.

The Relationship between Dietary Patterns and Metabolic Phenotypes: A Cross-Sectional Study in a Representative Sample of Iranian Industrial Employees

Background and Aim: There is limited evidence to support the relationship between dietary patterns and metabolic phenotypes. Therefore, this study aimed to assess the association of dietary patterns with metabolic phenotypes among a large sample of Iranian industrial employees. Methods: This cross-sectional study was conducted among 3,063 employees of Esfahan Steel Company, Iran. Using exploratory factor analysis, major dietary patterns were obtained from a validated short form of food frequency questionnaire. The metabolic phenotypes were defined according to Adult Treatment Panel III guidelines. The independent-sample t-test, one-way analysis of variance, χ2 test, and multivariable logistic regression were applied to analyze data. Results: Three major dietary patterns were identified by factor analysis: the Western dietary pattern, the healthy dietary pattern, and the traditional dietary pattern. After controlling for potential confounders, subjects in the highest tertile of Western dietary pattern score had a higher odds ratio (OR) for metabolically healthy obese (MHO; OR 1.58, 95% confidence interval [CI]: 1.29-1.94), metabolically unhealthy normal weight (OR 1.93, 95% CI 1.08-3.45), and metabolically unhealthy obese (MUHO) phenotypes (OR 2.87, 95% CI 2.05-4.03) than those in the lowest tertile. Also, higher adherence to traditional dietary pattern was positively associated with a higher risk of MHO (OR 1.91, 95% CI 1.56-2.34) and MUHO phenotypes (OR 2.33, 95% CI 1.69-3.22) in the final model. Conclusion: There were significant associations between dietary patterns and metabolic phenotypes, suggesting the necessity of nutritional interventions in industrial employees to improve metabolic phenotype, health outcomes, and, therefore, job productivity in the workforce population.

Impact of bariatric surgery on carotid intima-media thickness and arterial stiffness in metabolically healthy obesity: a prospective study

PURPOSE

Cardiovascular disease is one of the leading causes of mortality in patients with obesity. Metabolically healthy obesity (MHO), in which people do not have metabolic disorders, is a transient state of obesity. However, over the long term, a proportion of individuals with MHO develop metabolic syndrome (MetS). We aimed to investigate the effect of substantial weight loss following bariatric surgery in MHO on carotid intima-media thickness (CIMT) and pulse-wave velocity (PWV), which are independent predictors of subclinical atherosclerosis.

METHODS

This prospective study included 38 patients (34 women, four men) undergoing bariatric surgery who had severe obesity but without comorbidities (hypertension, diabetes, and hyperlipidemia), and 28 control individuals who were matched for age and sex. CIMT and PWV of the left common carotid artery were measured. At 12-month follow-up after bariatric surgery, measurements were repeated in the 38 patients with obesity.

RESULTS

Mean baseline body mass index (BMI) in the MHO group was 40.55 ± 3.59 kg/m2, which decreased by 33.1% after bariatric surgery. Compared with controls, CIMT and PWV were increased in MHO (543.53 ± 55.29 vs. 407.82 ± 53.09 μm, 6.70 ± 1.22 vs. 5.45 ± 0.74 m/s, respectively; all P < 0.001). At 12 months post-bariatric surgery, CIMT in MHO was lower than baseline (466.79 ± 53.74 vs. 543.53 ± 55.29 μm, P = 0.009), but PWV was not significantly different from baseline (6.27 ± 0.86 vs. 6.70 ± 1.22 m/s, P = 0.132). Multivariate regression showed that BMI was an independent predictor of CIMT (β = 0.531, P < 0.001).

CONCLUSION

Carotid artery structure and function were impaired in MHO, and improved carotid artery structure was associated with weight loss in MHO after bariatric surgery.

Cardiometabolic profiles and proteomics associated with obesity phenotypes in a longitudinal cohort of young adults

To assess cardiometabolic profiles and proteomics to identify biomarkers associated with the metabolically healthy and unhealthy obesity. Young adults (N = 156) enrolled were classified as not having obesity, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) based on NCEP ATP-III criteria. Plasma proteomics at study entry were measured using Olink Cardiometabolic Explore panel. Linear regression was used to assess associations between proteomics and obesity groups as well as cardiometabolic traits of glucose, insulin, and lipid profiles at baseline and follow-up visits. Enriched biological pathways were further identified based on the significant proteomic features. Among the baseline 95 (61%) and 61 (39%) participants classified as not having obesity and having obesity (8 MHO and 53 MUHO), respectively. Eighty of the participants were followed-up with an average 4.6 years. Forty-one proteins were associated with obesity (FDR < 0.05), 29 of which had strong associations with insulin-related traits and lipid profiles (FDR < 0.05). Inflammation, immunomodulation, extracellular matrix remodeling and endoplasmic reticulum lumen functions were enriched by 40 proteins. In this study population, obesity and MHO were associated with insulin resistance and dysregulated lipid profiles. The underlying mechanism included elevated inflammation and deteriorated extracellular matrix remodeling function.

Non-linear associations of HOMA2-IR with all-cause mortality in general populations: insights from NHANES 1999-2006

BACKGROUND

The association between homeostatic model assessment (HOMA2-IR) and mortality in obese and non-obese populations has not been clearly explained.

METHODS

A total of 7,085 individuals aged ≥ 20 years from the 1999-2006 National Health and Nutrition Examination Survey were included in the study. Study endpoints were all-cause and cardiovascular mortality. Multivariate Cox proportional hazards regression models with restricted cubic spline analysis were used for analysis.

RESULTS

In the study populations, a total of 1666 all-cause deaths and 555 cardiovascular (CV) deaths were recorded during a mean follow-up of 195.53 months. Notably, a significant difference in obesity was observed in the association between HOMA2-IR and mortality. After adjustment for multiple variables, HOMA2-IR was positively associated with all-cause mortality in all participants, in those with normal BMI, and in those with obesity. Conversely, tertile 2 of HOMA2-IR was associated with a lower risk of all-cause mortality in participants with obesity compared with tertile 1 (adjusted hazard ratio, 0.68; 95% confidence interval, 0.52-0.89; P = 0.005). Results from restricted cubic spline analysis showed a J-shaped association between HOMA2-IR and all-cause and CV mortality. In addition, a nonlinear U-shaped correlation with all-cause (P for nonlinear < 0.001) and CV (P for nonlinear = 0.002) mortality was observed in the population with obesity, with inflection points of HOMA2-IR identified at 1.85 and 1.75. Below the inflection point of 1.85, a negative relationship between HOMA2-IR and all-cause mortality was observed.

CONCLUSIONS

Elevated HOMA2-IR showed a notable correlation with increased risk of all-cause mortality. It was noteworthy that excessively reduced levels of insulin resistance showed a distinct association with increased mortality in individuals with obesity.

Differences in the levels of inflammatory markers between metabolically healthy obese and other obesity phenotypes in adults: A systematic review and meta-analysis

AIMS

The aim of this study was to systematically review and analyze differences in the levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) comparing metabolically healthy but obese (MHO) with metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) subjects.

DATA SYNTHESIS

We searched PubMed, Embase, Web of Science, and Scopus for studies that matched the relevant search terms. Differences in inflammatory marker levels between MHO and the other three phenotypes were pooled as standardized mean differences (SMD) or differences of medians (DM) using a random-effects model. We included 91 studies reporting data on 435,007 individuals. The CRP levels were higher in MHO than in MHNO subjects (SMD = 0.63, 95% CI: 0.49, 0.76; DM = 0.83 mg/L, 95% CI: 0.56, 1.11). The CRP levels were higher in MHO than in MUNO subjects (SMD = 0.16, 95% CI: 0.05, 0.28; DM = 0.39 mg/L, 95% CI: 0.09, 0.69). The CRP levels were lower in MHO than in MUO individuals (SMD = -0.43, 95% CI: -0.54, -0.31; DM = -0.82 mg/L, 95% CI: -1.16, -0.48). The IL-6 levels in MHO were higher than in MHNO while lower than in MUO subjects. The TNF-α levels in MHO were higher than in MHNO individuals.

CONCLUSIONS

This review provides evidence that CRP levels in MHO are higher than in MHNO and MUNO subjects but lower than in MUO individuals. Additionally, IL-6 levels in MHO are higher than in MHNO but lower than in MUO subjects, and TNF-α levels in MHO are higher than in MHNO individuals.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO number: CRD42021234948.

The mediatory role of inflammatory markers on the relationship between the NOVA classification system and obesity phenotypes among obese and overweight adult women: a cross-sectional study

Background

Diet and inflammation both play important roles in the occurrence of obesity. We aimed to investigate the role of inflammation in the development of both metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO) individuals.

Methods

This cross-sectional study included 221 overweight and obese women aged 18-56 years. The study assessed the metabolic health phenotypes of the participants using the Karelis criterion score. Additionally, dietary intakes were evaluated using a 147-item semi-quantitative questionnaire and the NOVA classification system (comprising 37 food groups and beverages). The study also collected and analyzed the blood parameters, as well as biochemical and anthropometric indices, for all participants.

Results

Among the women included in the study, 22.9% had MHO phenotypes but 77.1% had MUHO phenotypes. A significant association between the third quartile of the NOVA classification system and the increased likelihood of having the MUHO phenotype was observed (OR = 1.40, 95% CI = 1.09-4.92, p = 0.04). Regarding the potential role of inflammatory markers, high-sensitivity C-reactive protein (hs-CRP) (p = 0.84), transforming growth factor-β (TGF-β) (p = 0.50), monocyte chemoattractant protein-1 (MCP-1) (p = 0.49), plasminogen activator inhibitor-1 (PAI-1) (p = 0.97), and homeostatic model assessment for insulin resistance (HOMA-IR) (p = 0.92) were found to be mediators.

Conclusion

We observed a significant positive association between ultra-processed food (UPF) consumption and the MUHO phenotype in overweight and obese women. This association appeared to be mediated by some inflammatory markers, such as hs-CRP, TGF-β, MCP-1, PAI-1, and HOMA-IR. Additional studies are needed to validate these findings.

All-cause mortality risk with different metabolic abdominal obesity phenotypes: the Rural Chinese Cohort Study

We aimed to investigate the association of metabolic obesity phenotypes with all-cause mortality risk in a rural Chinese population. This prospective cohort study enrolled 15 704 Chinese adults (38·86 % men) with a median age of 51·00 (interquartile range: 41·00-60·00) at baseline (2007-2008) and followed up during 2013-2014. Obesity was defined by waist circumference (WC: ≥ 90 cm for men and ≥ 80 cm for women) or waist-to-height ratio (WHtR: ≥ 0·5). The hazard ratio (HR) and 95 % CI for the risk of all-cause mortality related to metabolic obesity phenotypes were calculated using the Cox hazards regression model. During a median follow-up of 6·01 years, 864 deaths were identified. When obesity was defined by WC, the prevalence of participants with metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO) at baseline was 12·12 %, 2·80 %, 41·93 % and 43·15 %, respectively. After adjusting for age, sex, alcohol drinking, smoking, physical activity and education, the risk of all-cause mortality was higher with both MUNO (HR = 1·20, 95 % CI 1·14, 1·26) and MUO (HR = 1·20, 95 % CI 1·13, 1·27) v. MHNO, but the risk was not statistically significant with MHO (HR = 0·99, 95 % CI 0·89, 1·10). This result remained consistent when stratified by sex. Defining obesity by WHtR gave similar results. MHO does not suggest a greater risk of all-cause mortality compared to MHNO, but participants with metabolic abnormality, with or without obesity, have a higher risk of all-cause mortality. These results should be cautiously interpreted as the representation of MHO is small.

Relevance of body composition in phenotyping the obesities

Obesity is the most extended metabolic alteration worldwide increasing the risk for the development of cardiometabolic alterations such as type 2 diabetes, hypertension, and dyslipidemia. Body mass index (BMI) remains the most frequently used tool for classifying patients with obesity, but it does not accurately reflect body adiposity. In this document we review classical and new classification systems for phenotyping the obesities. Greater accuracy of and accessibility to body composition techniques at the same time as increased knowledge and use of cardiometabolic risk factors is leading to a more refined phenotyping of patients with obesity. It is time to incorporate these advances into routine clinical practice to better diagnose overweight and obesity, and to optimize the treatment of patients living with obesity.

The Prevalence of Metabolically Unhealthy Normal Weight and Its Influence on the Risk of Diabetes

CONTEXT

Diabetes is a major health problem and metabolically unhealthy is an important risk factor.

OBJECTIVE

To conduct the first nationally representative study on epidemiological data of metabolically unhealthy normal weight (MUNW) focused only on nondiabetic subjects and determine the predictive effect on diabetes in China.

METHODS

A longitudinal study was conducted using data from the Rich Healthcare Group in China. Metabolic status was determined by the revised National Cholesterol Education Program Adult Treatment Panel III criteria, and individuals with 2 or more criteria were categorized as MUNW and diagnosed with metabolic syndrome (MetS) if they met 3 or more.

RESULTS

Of a total of 63 830 nondiabetic normal-weight individuals, 8935 (14.0%) were classified as MUNW and 1916 (3.00%) were diagnosed with MetS. After adjusting for potential confounders, individuals with MUNW had a greater diabetes risk (4.234, 95% CI 3.089-5.803) than those without MUNW during an average of 3.10 years of follow-up. Also, the multivariable-adjusted hazard ratios for developing diabetes were 3.069 (95% CI 1.790-5.263), 7.990 (95% CI 4.668-13.677), and 11.950 (95% CI 6.618-21.579) for participants with 1, 2, and 3 or more components, respectively, compared with those without any components. Further analyses suggested that the number of MetS components present is associated with the risk of diabetes, especially in metabolically unhealthy normal-weight young male adults. Multivariable-adjusted hazard ratios (95% CI) for incident diabetes among individuals with 1, 2, and at least 3 components were 4.45 (1.45-13.72), 9.82 (3.05-31.64), and 15.13 (3.70-61.84) for participants aged ≤44 years, and 3.55 (1.81-6.97), 8.52 (4.34-16.73), and 13.69 (6.51-28.77) for male participants, respectively.

CONCLUSIONS

The prevalence of MUNW is 14% in Chinese normal-weight nondiabetic individuals, and active intervention is necessary for this category of people. The presence of MUNW significantly increases the risk of diabetes, and the risk of diabetes is associated with the number of MetS components present in the patient.

The association between dietary pattern and visceral adiposity index, triglyceride-glucose index, inflammation, and body composition among Iranian overweight and obese women

The aim of the present study was to investigate the association between dietary patterns, derived through latent class analysis (LCA), with visceral adiposity index (VAI), Triglyceride-Glucose Index (TyG), inflammation biomarkers, and body composition in overweight and obese Iranian women. For this cross-sectional study, dietary exposure was assessed using a validated 147-item semi-quantitative food frequency questionnaire (FFQ). Dietary patterns were derived through LCA. Binary logistic was performed to test the associations of dietary patterns with VAI, TyG, inflammation biomarkers, and body composition. Health centers in Tehran, Iran. 376 obese and overweight women, aged > 18 years. Two dietary patterns were identified using LCA modeling: healthy and unhealthy. Women in the unhealthy class were characterized by higher consumption of fast food, sweetened beverages, grains, unhealthy oils, butter and margarine, and snacks. Compared with the healthy class, the unhealthy class was associated with an increased risk of higher fasting blood sugar (FBS) (OR = 6.07; 95% CI: 1.33-27.74, P value = 0.02), c-reactive protein (CRP) (OR = 1.72; 95% CI: 1.05-2.80; P value = 0.02), and lower fat free mass index (FFMI) (OR = 0.56; 95% CI: 0.35-0.88, P value = 0.01), after adjusting for confounders. We found that adherence to an unhealthy dietary pattern was associated with decreased FFMI and increased FBS and CRP using LCA, but not with the rest of the variables. Further studies should be conducted to confirm the veracity of these findings.

A novel criterion of metabolically healthy obesity could effectively identify individuals with low cardiovascular risk among Chinese cohort

Background and objective

Obesity has become a serious public health problem and brings a heavy burden of cardiovascular disease. Metabolically healthy obesity (MHO) is defined as individuals with obesity with no or only minor metabolic complications. Whether individuals with MHO have a lower cardiovascular risk remains controversial. In this study, a new criterion was used to define MHO and assess its predictive value for cardiovascular events and death. At the same time, the new criterion and the traditional criterion are compared to analyze the differences between different diagnostic criteria.

Methods

A prospective cohort was established in northeast rural China from 2012 to 2013. Follow-up was conducted in 2015 and 2018 to investigate the incidence of cardiovascular events and survival. Subjects were grouped according to the metabolic health and obesity status. Kaplan-Meier curves were drawn to describe the cumulative risk of endpoint events in the four groups. Cox regression analysis model was constructed to evaluate the risk of endpoint events. Analysis of variance and post hoc analyses were used to calculate and compare differences in metabolic markers between MHO subjects diagnosed by novel and traditional criteria.

Results

A total of 9345 participants 35 years of age or older without a history of cardiovascular disease were included in this study. After a median follow-up of 4.66 years, the data showed that participants in the MHO group had no significant increase in the risk of composite cardiovascular events and stroke, but had a 162% increase in the risk of coronary heart disease (HR: 2.62; 95%CI: 1.21-5.67). However, when using conventional criteria for metabolic health, mMHO group had a 52% increase in combined CVD risk (HR: 1.52; 95%CI: 1.14-2.03). By comparing the differences of metabolic indicators between MHO subjects diagnosed by the two criteria, MHO subjects diagnosed by the new criterion had higher WC, WHR, TG, FPG, and lower HDL-C levels except for lower blood pressure, showing more exposure to cardiovascular risk factors.

Conclusions

The risk of combined CVD and stroke was not increased in MHO subjects. The new metabolic health criterion is superior to the traditional criterion and can effectively identify individuals with obesity with a lower risk of combined CVD. Blood pressure levels may be responsible for the inconsistent risk of combined CVD in MHO subjects diagnosed with both criteria.

Metabolically healthy obesity: Misleading phrase or healthy phenotype?

Obesity is a heterogenous condition with multiple different phenotypes. Among these a particular subtype exists named as metabolically healthy obesity (MHO). MHO has multiple definitions and its prevalence varies according to study. The potential mechanisms underlying the pathophysiology of MHO include the different types of adipose tissue and their distribution, the role of hormones, inflammation, diet, the intestinal microbiota and genetic factors. In contrast to the negative metabolic profile associated with metabolically unhealthy obesity (MUO), MHO has relatively favorable metabolic characteristics. Nevertheless, MHO is still associated with many important chronic diseases including cardiovascular disease, hypertension, type 2 diabetes, chronic kidney disease as well as certain types of cancer and has the risk of progression into the unhealthy phenotype. Therefore, it should not be considered as a benign condition. The major therapeutic alternatives include dietary modifications, exercise, bariatric surgery and certain medications including glucagon-like peptide-1 (GLP-1) analogs, sodium-glucose cotransporter-2 (SGLT-2) inhibitors and tirzepatide. In this review, we discuss the significance of MHO while comparing this phenotype with MUO.

The Metabolic Health Index Identifies Patients That Will Benefit From Metabolic Surgery

INTRODUCTION

Metabolic syndrome is a modern world's major health hazard related to comorbidities like type 2 diabetes and cardiovascular disease. Bariatric surgery is well known to lower this health risk in patients with obesity. There is a need for an objective measure to assess the intended reduction in health hazard and indirectly the eligibility for bariatric surgery. The Metabolic Health Index (MHI) quantitatively summarizes the cumulative impact of the metabolic syndrome on health status on a scale from 1 to 6. This study describes the use of the MHI as a supportive tool in the decision for and outcome assessment of bariatric surgery.

METHODS

The general usability of the MHI was tested by extending its application to patient data of five other bariatric centers in the Netherlands. Retrospective laboratory and national bariatric quality registry data of 11,501 patients were collected.

RESULTS

The quantification of (improvement in) metabolic health burden as measured by the MHI was independent of the dataset that was used to derive the MHI model. Patients with MHI > 2.8 prior to surgery improved significantly more in MHI 12 mo after surgery compared to patients with MHI ≤ 2.8 (1.1 compared to 0.4 MHI points, respectively; P < 0.001).

CONCLUSIONS

The MHI is robust between centers and is suitable for general use in clinical decision-making. As changes in MHI over time reflect metabolic health alterations, it is suitable as an outcome measure of surgery. An MHI cut-off value of 2.8 helps to predict the likelihood of significant improvement after surgery, independent of body mass index and known metabolic comorbidities.

Association of Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet and metabolically unhealthy overweight/obesity phenotypes among Iranian women: a cross sectional study

PURPOSE

Paradoxes have been found in obesity, including individuals with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO), and diet may be one of the reasons for the creation of these metabolic phenotypes. Hence, the purpose of the present study was to investigate the association of the Mediterranean-DASH intervention for neurodegenerative delay (MIND) diet with metabolically unhealthy overweight/obesity (MUHOW/O) phenotypes.

METHODS

In this cross-sectional study, 229 overweight and obese women (body mass index (BMI) ≥ 25 kg/m2) aged 18-48 years were examined. Anthropometric measures and biochemical parameters were collected from all participants. The body composition of each participant was assessed using a bioelectrical impedance analyzer (BIA). The MIND diet score was determined based on 15 components using a valid and reliable food frequency questionnaire (FFQ) containing 147 items. Karelis criteria was used to determine metabolically healthy/unhealthy phenotype (MH/MUH).

RESULTS

Among the participants, 72.5% of individuals were identified as MUH and 27.5% as MH, with a mean ± standard deviation (SD) age of 36.16 (8.33) years. The results of our analysis showed that after controlling for age, energy intake, BMI, and physical activity, there was no significant association observed between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.01, 95% CI: 0.86-4.17, P-value = 0.10), T3 (OR: 1.89, 95% CI: 0.86-4.17, P-value = 0.11) of MIND score, and only the odds of MUH relative to MH with a marginal significant decreasing trend was observed from the second to the third tertile (1.89 vs. 2.01) (P - trend = 0.06). Also, after additional adjustment for marital status, the nonsignificant association between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.13, 95% CI: 0.89-5.10, P-value = 0.08), T3 (OR: 1.87, 95% CI: 0.83-4.23, P-value = 0.12) of MIND score remained, and the odds of MUH relative to MH with a significant decreasing trend was observed with increasing tertiles (P-trend = 0.04).

CONCLUSIONS

In conclusion, no significant associations were found between adherence to MIND diet with MUH, and only a significant downward trend in the odds of MUH was observed with increasing tertiles. We suggest further studies in this field.

The impact of insulin resistance on the association between metabolic syndrome and lung function: the Kangbuk Samsung Health Study

BACKGROUND/OBJECTIVE

Metabolic syndrome (MS) is related to lung dysfunction. However, its impact according to insulin resistance (IR) remains unknown. Therefore, we evaluated whether the relation of MS with lung dysfunction differs by IR.

SUBJECT/METHODS

This cross-sectional study included 114,143 Korean adults (mean age, 39.6 years) with health examinations who were divided into three groups: metabolically healthy (MH), MS without IR, and MS with IR. MS was defined as presence of any MS component, including IR estimated by HOMA-IR ≥ 2.5. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for lung dysfunction were obtained in MS, MS without IR, and MS with IR groups compared with the MH (reference) group.

RESULTS

The prevalence of MS was 50.7%. The percent predicted forced expiratory volume in 1 s (FEV1%) and forced vital capacity (FVC%) showed statistically significant differences between MS with IR and MH and between MS with IR and MS without IR (all P < 0.001). However, those measures did not vary between MH and MS without IR (P = 1.000 and P = 0.711, respectively). Compared to MH, MS was not at risk for FEV1% < 80% (1.103 (0.993-1.224), P = 0.067) or FVC% < 80% (1.011 (0.901-1.136), P = 0.849). However, MS with IR was clearly associated with FEV1% < 80% (1.374 (1.205-1.566) and FVC% < 80% (1.428 (1.237-1.647) (all p < 0.001), though there was no evident association for MS without IR (FEV1%: 1.078 (0.975-1.192, P = 0.142) and FVC%: 1.000 (0.896-1.116, p = 0.998)).

CONCLUSION

The association of MS with lung function can be affected by IR. However, longitudinal follow-up studies are required to validate our findings.

An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case-control study

OBJECTIVES

To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways.

METHODS

We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications.

RESULTS

We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome.

CONCLUSIONS

The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.

Relationship between obesity severity, metabolic status and cardiovascular disease in obese adults

BACKGROUND

Evidence about the associations between obesity severity, metabolic status and risk of incident cardiovascular disease (CVD) in adults with obesity remains limited.

METHODS

The study included 109,301 adults with obesity free of prior CVD based on the UK Biobank cohort. Metabolic status was categorized into metabolically healthy obesity (MHO; free of hypertension, hypercholesterolemia and diabetes) and metabolically unhealthy obesity (MUO). Obesity severity was classified into three levels: class I (body mass index of 30.0-34.9 kg/m² ), II (35.0-39.9) and III (≥40.0). Cox proportional hazards models were used for analyses.

RESULTS

There were 8059 incident CVD events during a median follow-up of 8.1 years. MUO was significantly associated with a 74% increased CVD risk compared with MHO (HR = 1.74, 95% CI: 1.62-1.83). There was a significant interaction between obesity severity and metabolic status on an additive scale regarding CVD risk. When taking class I obesity as reference, class II was nonsignificantly associated with an increased risk of CVD in the MHO group (HR = 1.07, 95% CI: 0.90-1.27), while class III was significantly related to increased risks of CVD (HR = 1.48, 95% CI: 1.12-1.96). In the MUO group, both classes II and III were significantly related to increased risks of CVD. Significant subgroup effects of age (p = .009) and sex (p = .047) were observed among participants with MUO but not in the MHO group.

CONCLUSIONS

Both elevated obesity severity and MUO were significantly associated with increased risks of CVD in adults with obesity, while metabolic status could modify the relationship between obesity severity and CVD risk. More research is needed to further clarify the relationship.

Metabolically Healthy Obesity: Are Interventions Useful?

PURPOSE OF REVIEW

This review aims to detail the current global research state of metabolically healthy obesogenesis with regard to metabolic factors, disease prevalence, comparisons to unhealthy obesity, and targeted interventions to reverse or delay progression from metabolically healthy to unhealthy obesity.

RECENT FINDINGS

As a long-term condition with increased risk of cardiovascular, metabolic, and all-cause mortality risks, obesity threatens public health on a national level. The recent discovery of metabolically healthy obesity (MHO), a transitional condition during which obese persons carry comparatively lower health risks, has added to confusion about the true effect of visceral fat and subsequent long-term health risks. In this context, the evaluation of fat loss interventions, such as bariatric surgery, lifestyle changes (diet/exercise), and hormonal therapies require re-evaluation in light of evidence that progression to high-risk stages of obesity relies on metabolic status and that strategies to protect the metabolism may be useful in the prevention of metabolically unhealthy obesity. Typical calorie-based exercise and diet interventions have failed to reduce the prevalence of unhealthy obesity. Holistic lifestyle, psychological, hormonal, and pharmacological interventions for MHO, on the other hand, may at least prevent progression to metabolically unhealthy obesity.

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.

Derivation and Validation of a New Visceral Adiposity Index for Predicting Short-Term Mortality of Patients with Acute Ischemic Stroke in a Chinese Population

The visceral adiposity index (VAI) is related to the occurrence of various cardiometabolic diseases, atherosclerosis, and stroke. However, few studies have analyzed the impact on the short-term prognosis of stroke. We assessed the effect of VAI on short-term prognoses in patients with acute ischemic stroke through a retrospective cohort study of 225 patients with acute stroke who were admitted to the neurological intensive care unit of our hospital. We collected metabolic indicators (blood pressure, fasting glucose, lipids), National Institutes of Health Stroke Scale (NIHSS) scores, symptomatic intracranial hemorrhage, and other disease evaluation indicators on 197 patients who were screened for inclusion. VAI was calculated by using baseline data (sex, height, weight, waist circumference (WC)). We assessed functional recovery according to modified Rankin scale scores after 90 days. The receiver operating characteristic (ROC) curve was used to calculate the VAI cutoff value that affects short-term outcomes. A nomogram that can predict the risk of short-term mortality in patients with acute ischemic stroke was drawn. In total, 28 patients died within 90 days. Those patients had higher VAI (p = 0.000), higher triglyceride (TG) (p = 0.020) and NIHSS scores (p = 0.000), and lower high-density lipoprotein cholesterol (HDL-C) (p = 0.000) than patients who survived. VAI had higher predictive value of short-term mortality than did body mass index (BMI), body fat mass index (BFMI), and WC. VAI and NIHSS scores were independent risk factors for the short-term mortality of patients with stroke. Patients with a VAI > 2.355 had a higher risk of short-term mortality. VAI has a predictive value higher than that of traditional metabolic indicators such as BMI, BFMI, and WC. The nomogram, composed of NIHSS, VAI, HDL-C, and TG, may predict the short-term mortality of cerebral infarction patients.

Visceral Adiposity Index and Lipid Accumulation Product as Effective Markers of Different Obesity Phenotypes in Korean Adults: A Cross-Sectional Analysis

PURPOSE

The visceral adiposity index (VAI) and lipid accumulation product (LAP) are useful for assessing visceral obesity. However, these indices were developed for Caucasians, and it is necessary to confirm whether the VAI and LAP are appropriate indicators for identifying obesity phenotypes in Asians. This study investigated whether the VAI and LAP are effective indicators for diagnosing four obesity phenotypes in South Korean adults.

PATIENTS AND METHODS

This cross-sectional study enrolled 23,310 adult participants (age ≥20 years) who had undergone a health checkup at a general hospital in Gyeonggi-do, South Korea from January 2017 to December 2020. VAI and LAP were calculated based on the presented mathematical model according to sex. According to the metabolic health status and presence or absence of obesity, the obesity phenotypes were classified into 4 groups: metabolically healthy non-obese (N=14,240, 61.1%), metabolically unhealthy non-obese (N=477, 2.0%), metabolically healthy obese (MHO; N=6796, 29.2%), and metabolically unhealthy obesity (MUO; N=1797, 7.7%).

RESULTS

The receiver operating characteristics curve analysis showed VAI best predicted MUO among the four obesity phenotypes, whereas the LAP showed excellent discriminating ability for the MUO group (area under the curve 0.877, 0.849, and 0.921 and 0.923, 0.907, and 0.954 for all participants, men, and women, respectively). The optimal VAI cutoff values for identifying the MUO group were 1.83 in men and 1.58 in women, and the optimal cutoff values for the LAP were 41.45 in men and 23.83 in women, with a higher value for men. After adjusting for potential confounding factors, the VAI and LAP were associated with an increased risk in the MHO and MUO groups among the obesity phenotypes in both sexes.

CONCLUSION

In South Korean adults, the VAI and LAP are closely related to the MUO phenotype in both sexes and are effective indices for predicting the MUO phenotype.

Association of Body Shape Index with Cerebral Small Vessel Disease

INTRODUCTION

A body shape index (ABSI) is an anthropometric index designed to reflect the influence of visceral fat. ABSI has been previously associated with various atherosclerosis, metabolic diseases, and cardiovascular diseases; however, relatively few studies have been conducted on cerebrovascular disease. In this study, we evaluated the association between ABSI and cerebral small vessel disease (cSVD) in health check-up participants.

METHODS

We evaluated consecutive health check-up participants between January 2006 and December 2013. As subtypes of cSVD, we quantitatively measured the volume of white matter hyperintensity (WMH) and qualitatively measured the presence of silent brain infarct (SBI) and cerebral microbleed (CMB). ABSI was calculated according to the following formula: ABSI (m11/6/kg-2/3) = waist circumference (m)/(body mass index [kg/m2]2/3 × height [m]1/2).

RESULTS

A total of 3,219 health check-up participants were assessed (median age, 56 years; male sex, 54.0%). In the multivariable analysis, ABSI was significantly associated with WMH volume (β = 0.107, 95% confidence interval [CI] = 0.013-0.200), SBI (adjusted odds ratio [aOR] = 1.62, 95% CI = 1.14-2.31), and CMB (aOR = 1.64, 95% CI = 1.16-2.33) after adjusting for confounders (per 100 m11/6/kg-2/3). Furthermore, ABSI showed a dose-response relationship with the burden of each cSVD pathology.

CONCLUSIONS

High ABSI was associated with a higher burden of cSVD in health check-up participants. As ABSI showed close associations with all subtypes of cSVD, visceral fat may be a common risk factor penetrating cSVD pathologies.

Differences of Regional Fat Distribution Measured by Magnetic Resonance Imaging According to Obese Phenotype in Koreans

Background: Obesity is commonly associated with a high risk of metabolic disorders, and obesity-related metabolic abnormalities are affected by some specific obesity phenotypes, regional fat distribution, and body mass index. However, few studies have investigated the relationship between obesity phenotypes and regional fat distribution in Korean subjects. This study aimed to assess regional fat distribution by gender using magnetic resonance imaging (MRI), and to identify a link between fat distribution and metabolic disorders in Korean subjects. Methods: This study included 35 Korean subjects (20 women, 15 men) who were classified into two groups by gender, and further divided into two groups based on their obesity phenotype: a metabolically abnormal obesity (MAO) and metabolically healthy obesity (MHO) group. Fat distribution was measured using MRI. The blood parameters were measured using a commercially available kit. Results: Women in the MAO group had more risk factors for metabolic abnormalities than those in the MHO group. Serum glucose, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels were also significantly higher in women with MAO than in those with MHO. The intermuscular adipose tissue (IMAT) of women with MAO was significantly higher than that of women with MHO. Serum HDL-C level was negatively correlated with IMAT, whereas leptin showed a positive correlation with IMAT in all subjects. Conclusions: Metabolic abnormalities according to obesity phenotype posed a higher risk in women than that in men. These findings suggest that an understanding of gender differences in relation to the association between obesity and metabolic risk would be helpful to reduce the prevalence of obesity.

Evaluation of the predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotype in overweight and obese women

Purpose

Predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotypes in overweight and obese women is still unclear. This study aimed to evaluate the predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotypes in overweight and obese women.

Methods

A total of 290 overweight and obese women were included in this cross-sectional study. Food intake was assessed using a semi-quantitative food frequency questionnaire (FFQ). Dietary antioxidant capacity was calculated using valid databases of antioxidant value. The receiver operating characteristic (ROC) curve method was used to evaluate the predictive value of antioxidant capacity indices, including dietary antioxidant quality score (DAQS), ferric reducing ability of plasma (FRAP), total reactive antioxidant potential (TRAP), and trolox equivalent antioxidant capacity (TEAC).

Results

The results showed that the highest area under the ROC curve for predicting metabolically healthy obesity (MHO) belongs to the TRAP method (area under the curve (AUC) = 0.53). In addition, this method had the highest AUC for predicting inflammatory marker of C-reactive protein (hs-CRP) (AUC = 0.54) and the index of the homeostatic model assessment for insulin resistance (HOMA-IR) (AUC = 0.59). The highest AUC for triglyceride prediction was related to the DAQS method (AUC = 0.56). Moreover, a significant correlation of FRAP (r = -0.15, P = 0.02), TRAP (r = -0.19, P < 0.001), TEAC (r = -0.18, P< 0.001) with HOMA-IR was reached.

Conclusion

The findings of this study show that the best way to predict the status of MHO is TRAP method. This method is also the best predictor of hs-CRP and HOMA-IR. DAQS method is the best predictor for TG.

Dairy intake in relation to metabolic health status in overweight and obese adolescents

There was a lack of evidence on the association between dairy intake and metabolic health status in overweight/obese adolescents. This study evaluated the association between dairy intake and metabolic health status in overweight/obese Iranian adolescents. Overweight/obese adolescents (n = 203; 101 boys and 102 girls) selected by a multistage cluster random sampling method have participated in this cross-sectional study. Dietary intake was assessed using a validated 147-item food frequency questionnaire. Anthropometric indices, blood pressure, fasting glucose, insulin, and lipid profile were measured. Participants were categorized to metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) according to International Diabetes Federation (IDF) criteria and a combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR) criteria. The frequency of MUO based on IDF, and IDF/HOMA-IR definitions was 38.9% and 33.0%, respectively. In fully-adjusted model, participants in the highest tertile of dairy intake had 61% lower odds of MUO based on IDF criteria (OR = 0.39, 95% CI 0.15-0.99). Higher dairy intake was associated with a non-significant lower risk of MUO according to IDF/HOMA-IR definition in the maximally-adjusted model (OR = 0.44, 95% CI 0.17-1.16). Stratifies analysis by sex and body mass index revealed that the association was stronger in girls and overweight subjects. Furthermore, higher intake of low-fat dairy was related to a reduced likelihood of MUO, while higher intake of high-fat dairy was related to increased odds of MUO. This community-based cross-sectional study revealed that higher intake of dairy was associated with a significant lower odd of MUO among Iranian adolescents, especially in girls and overweight subjects.

Association of dietary phytochemical index with metabolically unhealthy overweight/obesity phenotype among Iranian women: A cross-sectional study

Background

Phytochemicals have been recently studied as adjuvants for the treatment of obesity. No study has investigated the association of phytochemical-rich foods with metabolically unhealthy overweight/obesity phenotype (MUOW/O). This study aimed to determine the association of dietary phytochemical index (DPI) with MUOW/O based on Karelis criteria among Iranian female adults.

Methods

In this cross-sectional study, a total of 228 overweight and obese women aged 18–48 years were included. Anthropometric measurements were evaluated for all participants. A validated 147-item Food Frequency Questionnaire (FFQ) was used for dietary assessment. DPI was calculated as [dietary energy derived from phytochemical-rich foods (kcal)/total daily energy intake (kcal)] × 100. Participants’ body composition and biochemical parameters of Karelis criteria [triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), insulin, and high-sensitivity C-reactive protein (hs-CRP)] were determined.

Results

The mean age of the study participants was 36.69 ± 9.20, and the mean DPI score was 26.23 ± 9.48 among participants with MUOW/O phenotype. After controlling for potential confounders, women in the highest tertile of DPI had lower odds for MUOW/O phenotype [odds ratio (OR): 0.23, 95% confidence interval (CI): 0.07–0.68, P = 0.008] compared to the lowest tertile. Among the components of Karelis criteria, homeostatic model assessment for insulin resistance (HOMA-IR) was significantly associated with MUOW/O phenotype in the fully adjusted model (OR: 0.29, 95% CI: 0.10–0.79, P = 0.01).

Conclusion

We found a significant association between DPI and MUOW/O phenotype in Iranian women. Prospective studies are needed to confirm these findings.

Body fat and muscle were associated with metabolically unhealthy phenotypes in normal weight and overweight/obesity in Yi people: A cross-sectional study in Southwest China

This study aimed to determine the association between the absolute mass, distribution, and relative ratio of body fat and muscle with the metabolically unhealthy (MU) phenotypes in normal weight and overweight/obesity in Yi people in China. The cross-sectional data from the Yi Migrants Study was used, which included 3,053 Yi people aged 20-80 years from the rural and urban sets. Participants were classified according to body mass index and metabolic status. Body composition including body fat percentage (BFP), fat mass index (FMI), visceral fat grade (VFG), muscle mass index (MMI), and muscle/fat ratio (M/F) were measured by bioelectrical impedance analysis. Restricted cubic spline and logistics regression models were used to test the associations between body composition parameters with MU phenotypes. Receiver-operating characteristic curves (ROC) were used to analyze the predictive value of MU phenotypes. Among the normal weight and overweight/obesity, 26.31% (497/1,889) and 52.15% (607/1,164) were metabolically unhealthy. Stratified by BMI, covariance analysis showed higher body fat (BFP, FMI, and VFG) and MMI in MU participants than in healthy participants. BFP, FMI, VFG, and MMI were positively associated with MU phenotypes both in normal weight and overweight/obesity after adjustment. M/F was significantly lower than MU participants and was negatively associated with MU phenotypes. BFP, FMI, VFG, and M/F could better predict MU phenotypes than BMI. We concluded that BFP, FMI, and VFG were positively associated with MU phenotypes, while M/F was negatively associated with MU phenotypes across the BMI categories in Yi people. Body fat and muscle measurement could be a valuable approach for obesity management.

Association of Lifelines Diet Score (LLDS) and metabolically unhealthy overweight/obesity phenotypes in women: a cross-sectional study

Background

Previous studies have shown the association of a number of dietary quality scores with metabolically phenotypes of obesity. Recently, the Lifelines Diet Score (LLDS), which is a fully food-based score based on the 2015 Dutch dietary guidelines and underlying international literature, has been proposed as a tool for assessing the quality of the diet. Therefore, this study was performed to investigate the association between LLDS and metabolically healthy/unhealthy overweight and obesity (MHO/MUHO) phenotypes.

Methods

This study was performed on 217 women, aged 18–48 years old. For each participant anthropometric values, biochemical test and body composition were evaluated by standard protocols and methods. The LLDS was determined based on 12 components using a valid and reliable food frequency questionnaire (FFQ) containing 147 items. The metabolically healthy (MH) was evaluated using the Karelis criteria.

Results

Among the total participants in this study, 31.3% of the subjects were MHO while 68.7% were MUHO. After adjustment for potential confounding variables (age, energy intake, and physical activity), participants in highest LLDS tertile had a lower odds of MUHO compared with those in the lowest tertile (OR: 1.18; 95% CI: 0.23, 5.83; P-trend = 0.03). Also, after further adjustment with BMI, provided only small changes in "OR" and did not attenuate the significance (OR: 1.28; 95% CI: 0.23, 6.91; P-trend = 0.02).

Conclusions

The present evidence indicates that individuals with higher adherence to the LLDS had lower odds of metabolically unhealthy (MUH).

Dietary total antioxidant capacity in relation to metabolic health status in overweight and obese adolescents

Background

Although several studies evaluated the relationship between individual dietary antioxidants and metabolic health conditions, data on the association between dietary total antioxidant capacity and metabolic health among children and adolescents is limited. This study investigated the relationship between dietary total antioxidant capacity and metabolic health status in Iranian overweight/obese adolescents.

Methods

This cross-sectional study was conducted on 203 overweight/obese adolescents. Dietary intakes were evaluated by a validated food frequency questionnaire. Ferric Reducing-Antioxidant Power (FRAP) was considered to indicate dietary total antioxidant capacity. Anthropometric parameters and blood pressure status were measured. Fasting blood samples were obtained to determine circulating insulin, glucose, and lipid profile. Two different methods (modified International Diabetes Federation (IDF) criteria and IDF criteria along with insulin resistance) were applied to classify participants as metabolically healthy obese (MHO) or metabolically unhealthy obese (MUO).

Results

According to IDF and IDF/HOMA definitions, a total of 79 (38.9%) and 67 (33.0%) adolescents were respectively defined as MUO. Considering IDF criteria, the highest tertile of FRAP was related to lower odds of being MUO in the maximally-adjusted model (OR: 0.40; 95%CI: 0.16–0.96), compared to the lowest tertile. However, based on the IDF/HOMA-IR criteria, no significant relation was found between FRAP and odds of MUO (OR: 0.49; 95%CI: 0.19–1.23) after considering all possible confounders.

Conclusions

Adolescents with higher intakes of dietary antioxidants have a lower possibility of being MUO based on IDF criteria. However, no substantial relation was found considering HOMA-IR/IDF definition. Further prospective cohort studies need to be done to confirm these findings.

New metabolic health definition might not be a reliable predictor for mortality in the nonobese Chinese population

Background

Recently, a new metabolic health (MH) definition was developed from NHANES-III. In the origin study, the definition may stratify mortality risks in people who are overweight or normal weight. We aimed to investigate the association between the new MH definition and all-cause mortality in a nonobese Chinese population.

Methods

The data were collected in 1992 and then again in 2007 from the same group of 1157 participants. The association between the new MH definition and all-cause mortality were analyzed by Cox regression models with overlap weighting according to propensity score (PS) as primary analysis.

Results

At baseline in 1992, 920 (79.5%) participants were categorized as MH, and 237 (20.5%) participants were categorized as metabolically unhealthy (MUH) based on this new definition. During a median follow-up of 15 years, all-cause mortality occurred in 17 (1.85%) participants in MH group and 13 (5.49%) in MUH group, respectively. In the crude sample, Kaplan–Meier analysis demonstrated a significantly higher all-cause mortality in MUH group when compared to MH group (log-rank p = 0.002), and MUH was significantly associated with increased all-cause mortality when compared to MH with HR at 3.04 (95% CI: 1.47–6.25, p = 0.003). However, Kaplan–Meier analysis with overlap weighting showed that the cumulative incidence of all-cause mortality was not significantly different between MH and MUH groups (adjusted p = 0.589). Furthermore, in the primary multivariable Cox analysis with overlap weighting, adjusted HR for all-cause mortality was 1.42 (95% CI: 0.49—4.17, p = 0.519) in MUH group in reference to MH group. Other additional PS analyses also showed the incidence of all-cause mortality was not significantly different between the two groups.

Conclusion

The new MH definition may be not appropriate for mortality risk stratification in non-obese Chinese people. Further investigations are needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14062-3.

Pathogenesis, Murine Models, and Clinical Implications of Metabolically Healthy Obesity

Although obesity is commonly associated with numerous cardiometabolic pathologies, some people with obesity are resistant to detrimental effects of excess body fat, which constitutes a condition called “metabolically healthy obesity” (MHO). Metabolic features of MHO that distinguish it from metabolically unhealthy obesity (MUO) include differences in the fat distribution, adipokine types, and levels of chronic inflammation. Murine models are available that mimic the phenotype of human MHO, with increased adiposity but preserved insulin sensitivity. Clinically, there is no established definition of MHO yet. Despite the lack of a uniform definition, most studies describe MHO as a particular case of obesity with no or only one metabolic syndrome components and lower levels of insulin resistance or inflammatory markers. Another clinical viewpoint is the dynamic and changing nature of MHO, which substantially impacts the clinical outcome. In this review, we explore the pathophysiology and some murine models of MHO. The definition, variability, and clinical implications of the MHO phenotype are also discussed. Understanding the characteristics that differentiate people with MHO from those with MUO can lead to new insights into the mechanisms behind obesity-related metabolic derangements and diseases.

Arterial Stiffness, Biomarkers of Liver Fat, and the Development of Metabolic Dysfunction in Metabolically Healthy Population: A Prospective Study

Background

Metabolic dysfunction is known to be associated with arterial stiffness. However, the risks of metabolic syndrome and diabetes due to arterial stiffness and the potential mechanism remain unclear. We aimed to investigate the association of arterial stiffness with the risk of metabolic syndrome and diabetes, and determine whether this association is mediated by liver fat.

Methods

A prospective study was conducted with 4,139 Chinese adults who were metabolically healthy at baseline. Arterial stiffness was measured by brachial–ankle pulse wave velocity (baPWV). Obesity was defined as body mass index ≥25 kg/m2. The primary outcomes were incident metabolic syndrome and diabetes.

Results

During a median follow-up of 4.4 years, 1,022 (24.7%) and 354 (9.5%) participants developed metabolic syndrome and diabetes, respectively. Compared with those in the lowest quartile of baPWV, participants in the highest quartile had 85 and 91% higher risks of metabolic syndrome and diabetes [risk ratio (RR) 1.85, 95% confidence interval (CI) 1.41, 2.42 for metabolic syndrome; RR 1.91, 95% CI 1.16, 3.15 for diabetes]. Mediation analyses indicated that fatty liver significantly mediated the association of arterial stiffness with metabolic syndrome and diabetes risk. Specifically, 18.4% of metabolic syndrome and 12.6% of diabetes risk due to arterial stiffness were mediated through fatty liver.

Conclusions

Arterial stiffness was associated with higher risks of metabolic syndrome and diabetes in individuals with obesity. This association may be partially mediated by fatty liver.

Obese Individuals With and Without Phlegm-Dampness Constitution Show Different Gut Microbial Composition Associated With Risk of Metabolic Disorders

Background

Obesity is conventionally considered a risk factor for multiple metabolic diseases, such as dyslipidemia, type 2 diabetes, hypertension, and cardiovascular disease (CVD). However, not every obese patient will progress to metabolic disease. Phlegm-dampness constitution (PDC), one of the nine TCM constitutions, is considered a high-risk factor for obesity and its complications. Alterations in the gut microbiota have been shown to drive the development and progression of obesity and metabolic disease, however, key microbial changes in obese patients with PDC have a higher risk for metabolic disorders remain elusive.

Methods

We carried out fecal 16S rRNA gene sequencing in the present study, including 30 obese subjects with PDC (PDC), 30 individuals without PDC (non-PDC), and 30 healthy controls with balanced constitution (BC). Metagenomic functional prediction of bacterial taxa was achieved using PICRUSt.

Results

Obese individuals with PDC had higher BMI, waist circumference, hip circumference, and altered composition of their gut microbiota compared to non-PDC obese individuals. At the phylum level, the gut microbiota was characterized by increased abundance of Bacteroidetes and decreased levels of Firmicutes and Firmicutes/Bacteroidetes ratio. At the genus level, Faecalibacterium, producing short-chain fatty acid, achieving anti-inflammatory effects and strengthening intestinal barrier functions, was depleted in the PDC group, instead, Prevotella was enriched. Most PDC-associated bacteria had a stronger correlation with clinical indicators of metabolic disorders rather than more severe obesity. The PICRUSt analysis demonstrated 70 significantly different microbiome community functions between the two groups, which were mainly involved in carbohydrate and amino acid metabolism, such as promoting Arachidonic acid metabolism, mineral absorption, and Lipopolysaccharide biosynthesis, reducing Arginine and proline metabolism, flavone and flavonol biosynthesis, Glycolysis/Gluconeogenesis, and primary bile acid biosynthesis. Furthermore, a disease classifier based on microbiota was constructed to accurately discriminate PDC individuals from all obese people.

Conclusion

Our study shows that obese individuals with PDC can be distinguished from non-PDC obese individuals based on gut microbial characteristics. The composition of the gut microbiome altered in obese with PDC may be responsible for their high risk of metabolic diseases.

Obesity is an important determinant of severity in newly defined metabolic dysfunction-associated fatty liver disease

BACKGROUND

The recently proposed definition of metabolic dysfunction-associated fatty liver disease (MAFLD) is based on the co-existence of hepatic steatosis with other metabolic disorders, including obesity and metabolic risk abnormalities such as hyperglycemia, high blood pressure and dyslipidemia. This study aimed to assess MAFLD severity according to the presence of metabolic abnormalities and obesity.

METHODS

Using transient elastography, hepatic steatosis and fibrosis severity were assessed by measuring the controlled attenuation parameter and liver stiffness measurement. A total of 1163 patients with MAFLD were categorized into the following four groups according to metabolic risk abnormalities and obesity presence: non-obese without metabolic risk abnormality group (Group 1; reference group); non-obese with metabolic risk abnormality group (Group 2); obese without metabolic risk abnormality group (Group 3); and obese with metabolic risk abnormality group (Group 4). A multiple logistic regression analysis was performed to determine severe hepatic steatosis and fibrosis risk in each group in both unadjusted and adjusted models.

RESULTS

In the adjusted model, the odds ratios (ORs) [95% confidence interval (CI)] for severe hepatic steatosis in Groups 2, 3, and 4 were 1.07 (0.61-1.88), 2.43 (1.44-4.08), and 4.07 (2.56-6.48), respectively (P_trend < 0.001). For liver fibrosis, compared with Group 1, Group 2 showed no significant increases in OR, whereas Groups 3 and 4 (obese groups) showed significant increases (OR = 4.70, 95% CI: 1.24-17.82 and OR = 6.43, 95% CI: 1.88-22.02, respectively).

CONCLUSIONS

Obesity, rather than metabolic abnormality, is the principal determinant of severe hepatic steatosis and fibrosis in patients with MAFLD.

Changes in body size phenotypes from childhood to adulthood and the associated cardiometabolic outcomes

AIM

To examine the effects of changes in body size phenotypes between childhood and adulthood on risks of diabetes and left ventricular hypertrophy (LVH) in adulthood.

METHODS

We included 3,351 individuals who participated as both children and adults in the Bogalusa Heart Study.

RESULTS

Compared with participants with persistently metabolically healthy normal weight (MHNW) from childhood to adulthood, MHNW children who became metabolically unhealthy in adulthood had increased diabetes burden and LVH risk in adulthood; Metabolically unhealthy normal weight (MUNW) children who became MHNW or metabolically healthy obese (MHO) as adults and individuals with persistent MHO from childhood to adulthood were not at increased risks of diabetes or LVH. The risks were increased if MHO during childhood transitioned to metabolically unhealthy obesity (MUO) by adulthood or MUO stayed from childhood to adulthood. MUO children who became MHO or MHNW as adults had decreased diabetes burden and LVH risk in adulthood.

CONCLUSIONS

Individuals maintained MHO from childhood to adulthood and MUNW children who became MHO as adults had a diabetes burden and LVH risk similar to individuals with persistent MHNW. Progression to metabolically unhealthy status and maintenance of metabolically unhealthy status, regardless of childhood BMI status, were associated with increased cardiometabolic outcomes.

Independent and joint effects of body mass index and metabolic health in mid- and late-life on all-cause mortality: a cohort study from the Swedish Twin Registry with a mean follow-up of 13 Years

BACKGROUND

There is robust evidence that in midlife, higher body mass index (BMI) and metabolic syndrome (MetS), which often co-exist, are associated with increased mortality risk. However, late-life findings are inconclusive, and few studies have examined how metabolic health status (MHS) affects the BMI-mortality association in different age categories. We, therefore, aimed to investigate how mid- and late-life BMI and MHS interact to affect the risk of mortality.

METHODS

This cohort study included 12,467 participants from the Swedish Twin Registry, with height, weight, and MHS measures from 1958-2008 and mortality data linked through 2020. We applied Cox proportional hazard regression with age as a timescale to examine how BMI categories (normal weight, overweight, obesity) and MHS (identification of MetS determined by presence/absence of hypertension, hyperglycemia, low HDL, hypertriglyceridemia), independently and in interaction, are associated with the risk of all-cause mortality. Models were adjusted for sex, education, smoking, and cardiovascular disease.

RESULTS

The midlife group included 6,252 participants with a mean age of 59.6 years (range = 44.9-65.0) and 44.1% women. The late-life group included 6,215 participants with mean age 73.1 years (65.1-95.3) and 46.6% women. In independent effect models, metabolically unhealthy status in midlife increased mortality risks by 31% [hazard ratio 1.31; 95% confidence interval 1.12-1.53] and in late-life, by 18% (1.18;1.10-1.26) relative to metabolically healthy individuals. Midlife obesity increased the mortality risks by 30% (1.30;1.06-1.60) and late-life obesity by 15% (1.15; 1.04-1.27) relative to normal weight. In joint models, the BMI estimates were attenuated while those of MHS were less affected. Models including BMI-MHS categories revealed that, compared to metabolically healthy normal weight, the metabolically unhealthy obesity group had increased mortality risks by 53% (1.53;1.19-1.96) in midlife, and across all BMI categories in late-life (normal weight 1.12; 1.01-1.25, overweight 1.10;1.01-1.21, obesity 1.31;1.15-1.49). Mortality risk was decreased by 9% (0.91; 0.83-0.99) among those with metabolically healthy overweight in late-life.

CONCLUSIONS

MHS strongly influenced the BMI-mortality association, such that individuals who were metabolically healthy with overweight or obesity in mid- or late-life did not carry excess risks of mortality. Being metabolically unhealthy had a higher risk of mortality independent of their BMI.

Metabolically healthy versus unhealthy obese phenotypes in relation to hypertension incidence; a prospective cohort study

Background

Although obesity increases the risk of hypertension, the effect of obesity based on metabolic status on the incidence of hypertension is not known. This study aimed to determine the association between obesity phenotypes including metabolically unhealthy obesity (MUO) and metabolically healthy obesity (MHO) and the risk of hypertension incidence.

Methods

We conducted a prospective cohort study on 6747 adults aged 35–65 from Ravansar non-communicable diseases (RaNCD) study. Obesity was defined as body mass index above 30 kg/m² and metabolically unhealthy was considered at least two metabolic disorders based on the International Diabetes Federation criteria. Obesity phenotypes were categorized into four groups including MUO, MHO, metabolically unhealthy non obesity (MUNO), and metabolically healthy non obesity (MHNO). Cox proportional hazards regression models were applied to analyze associations with hypertension incidence.

Results

The MHO (HR: 1.37; 95% CI: 1.03–1.86) and MUO phenotypes (HR: 2.44; 95% CI: 1.81–3.29) were associated with higher hypertension risk compared to MHNO. In addition, MUNO phenotype was significantly associated with risk of hypertension incidence (HR: 1.65; 95% CI: 1.29–2.14).

Conclusions

Both metabolically healthy and unhealthy obesity increased the risk of hypertension incidence. However, the increase in metabolically unhealthy phenotype was higher.

Advances in Phenotyping Obesity and in Its Dietary and Pharmacological Treatment: A Narrative Review

In recent times, it has become evident that there are individuals who, from a metabolic point of view, are affected by obesity but have a normal body mass index. There are also metabolically healthy individuals with a high body mass index who are thus are considered as to be affected by obesity obese. Understanding that individuals with obesity are phenotypically heterogeneous is a relatively novel concept which, although present in the scientific literature, unfortunately has not yet had an impact in clinical practice. However, common dietary approaches are not effective in treating large numbers of obese patients with obesity. This narrative review, based on the material searched via PubMed and the Web of Science up to October 2021, proposes a downsizing of the role of the body mass index in identifying the individual with "true obesity" since it is only partially useful, and suggests a new approach which also integrates the body composition and assessment of metabolic parameters. This approach leads to personalized therapies that work best for each obesity phenotype in reducing the risk of non-communicable diseases.

Illness perceptions and health-related quality of life in individuals with overweight and obesity

INTRODUCTION

To understand how individuals (self-)manage obesity, insight is needed into how patients perceive their condition and how this perception translates into health outcomes (e.g., health-related quality of life, HRQOL). Our objectives were (1) to examine illness perceptions in individuals with overweight and obesity, and (2) to investigate associations of these perceptions with physical and mental HRQOL.

METHODS

In a cross-sectional analysis of the Netherlands Epidemiology of Obesity Study (n = 6432; 52% women), illness perceptions were assessed using the Brief Illness Perception Questionnaire, and HRQOL was assessed using the 36-Item Short-Form Health Survey. Illness perceptions were calculated for different categories of overall, abdominal, and metabolically unhealthy obesity. We investigated associations of illness perceptions with HRQOL using BMI-stratified multivariable linear regression analyses.

RESULTS

Compared to individuals with normal weight, individuals with obesity believed to a higher extent that their condition had more serious consequences [Mean Difference (95%CI): 1.8 (1.6-2.0)], persisted for a longer time [3.4 (3.2-3.6)], manifested in more symptoms [3.8 (3.6-4.0)], caused more worry [4.2 (3.9-4.4)] and emotional distress [2.0 (1.8-2.2)], but was more manageable with medical treatment [3.1 (2.9-3.4)]. They perceived to a lesser extent that they had personal control [-2.2 (-2.4, -2.0)] and understanding [-0.3 (-0.5, -0.1)] regarding their condition. These negative perceptions were less pronounced in individuals with abdominal obesity. Behaviour/Lifestyle was attributed by 73% of participants to be the cause of their obesity. Stronger negative illness perceptions were associated with impaired HRQOL, particularly the physical component.

CONCLUSION

Individuals with obesity perceived their conditions as threatening, and this seemed somewhat stronger in individuals with overall obesity than those with abdominal obesity. Behaviour/Lifestyle is a crucial target intervention and empowering self-management behaviour to achieve a healthy body weight may deliver promising results. In addition, strategies that aim to change negative perceptions of obesity into more adaptive ones may improve HRQOL.

Trends in Obesity and Metabolic Status in Northern and Southern China Between 2012 and 2020

Background: The trends of obesity-associated metabolic status in Chinese are lacking, especially those from different regions.

Objectives: To examine the trends of obesity and metabolic status among Chinese population in 2012–2020.

Methods: In a series cross-sectional study, data on 256,782 participants surveyed between 2014 and 2020 in Beijing, northern China, and 697,170 participants surveyed between 2012 and 2020 in Hunan, southern China were analyzed. Anthropometrics, blood pressure measurements, and blood tests were performed according to standard protocols. Trends in obesity and metabolic status were evaluated using the Joinpoint software.

Results: Based on age- and sex-standardized values, the mean BMI values in northern and southern participants were 23.94 (95% CI: 23.93, 23.95) and 23.68 (95% CI: 23.67, 23.69) kg/m², respectively. Between 2014 and 2020, the overall obesity prevalence among northern participants increased from 12.70% (95% CI: 12.17, 13.23%) to 14.33% (95% CI: 13.97, 14.70%) (P = 0.009), mainly derived by the 20–39 and 40–59 age groups. Moreover, the prevalence of metabolically healthy obese significantly increased from 2.07% (95% CI: 1.84, 2.30%) to 4.33% (95% CI: 4.13, 4.53%) in Northerners. Between 2012 and 2020, no significant trend in obesity was found among overall southern participants, but the prevalence of metabolically unhealthy obese significantly increased from 5.36% (95% CI: 5.18, 5.54%) to 7.35% (95% CI: 7.11, 7.58%), mainly derived by the 20–39 and 40–59 age groups.

Conclusions: The trends in obesity and metabolic status were different between southern and northern Chinese. A national weight control plan is needed in China, focusing on young and middle-aged population.

Commentary—fat but fit…and cold? Potential evolutionary and environmental drivers of metabolically healthy obesity

As global obesity rates continue to rise, it is important to understand the origin, role and range of human variation of body mass index (BMI) in assessing health and healthcare. A growing body of evidence suggests that BMI is a poor indicator of health across populations, and that there may be a metabolically healthy obese phenotype. Here, we review the reasons why BMI is an inadequate tool for assessing cardiometabolic health. We then suggest that cold climate adaptations may also render BMI an uninformative metric. Underlying evolutionary and environmental drivers may allow for heat conserving larger body sizes without necessarily increasing metabolic health risks. However, there may also be a potential mismatch between modern obesogenic environments and adaptations to cold climates, highlighting the need to further investigate the potential for metabolically healthy obese phenotypes among circumpolar and other populations as well as the broader meaning for metabolic health.

Perinatal socio-behavioral and obstetric predictors of metabolically healthy and unhealthy obesity in adult offspring

OBJECTIVE

The purpose of this study was to investigate whether obstetric and perinatal socio-behavioral characteristics at the time of pregnancy predict obesity phenotypes of adult offspring.

METHODS

The Jerusalem Perinatal Study was conducted among 17,003 deliveries during 1974 to 1976. Follow-up studies were conducted during 2007 to 2009 and 2017 to 2019 among 1,440 offspring undergoing examinations. Offspring were classified into four phenotypes according to obesity and metabolic status: metabolically healthy normal weight (MHNW, reference group), unhealthy normal weight, healthy obesity (MHO), and unhealthy obesity (MUO). Regression models were carried out to identify perinatal predictors for risk phenotypes at age 30 to 35 years, emphasizing the differentiation between socio-behavioral and obstetric features.

RESULTS

A total of 15.7% of participants were classified as MUO, and 5.4% were classified as MHO. Low socioeconomic status was associated with both obesity phenotypes (e.g., odds ratio [OR]_MHO/MHNW = 2.98, p < 0.001). High socioeconomic status was associated with MUO (OR_MUO/MHNW = 1.93, p = 0.002). Maternal low education was also associated with both obesity phenotypes (OR_MUO/MHNW = 2.46, p < 0.001, OR_MHO/MHNW = 2.45, p = 0.005). Participants with MUO were more likely to have a smoking father (OR_MUO/MHNW = 1.48, p = 0.021).

CONCLUSIONS

Perinatal socio-behavioral characteristics are associated with adult obesity phenotypes. The findings point to possible mechanisms underlying the development of obesity in young adults and, thus, contribute toward identifying high-risk groups that would mostly benefit from obesity risk-reduction interventions.

Chinese famine exposure in early life and metabolic obesity phenotype in middle age: Results from the China health and retirement longitudinal study

OBJECTIVE

To assess the association between early life exposure to famine and the risk of metabolic obesity phenotypes among adults in middle age.

METHODS

The study selected two comparison groups. Comparison A consisted of a non-exposed group born between 1963-1965 from the China Health and Retirement Longitudinal Study (CHARLS) 2015 wave (N=862) and a fetal-exposed group born between 1959-1961 from the 2011 wave (N=507). Comparison B consisted of an early childhood-exposed group born between 1955-1957 from the 2011 wave (N=830) and a fetal-exposed group born between 1959-1961 from the 2015 wave (N=552). Multivariable logistic regressions were conducted to explore the associations between different periods of famine exposure and obesity, metabolic health status, and metabolic obesity phenotypes, with stratification by sex.

RESULTS

Compared with the non-exposed group, participants exposed to famine in the fetal period had a significantly lower risk of overweight/obesity (OR: 0.78, 95%CI: 0.63-0.97) and a higher risk of metabolically unhealthy status (OR: 1.73, 95%CI: 1.34-2.23) and metabolically unhealthy non-obesity (MUNO) (OR: 2.12, 95%CI: 1.46-3.08) at the age of 50-52 years. In the sex-stratified analysis, males exposed to famine in the fetal period had a significantly lower risk of overweight/obesity (OR: 0.59, 95%CI: 0.43-0.80) and metabolically healthy obesity (MHO) (OR: 0.56, 95%CI: 0.37-0.85), while such associations were not found in females. Compared with the early childhood exposure group, participants in the fetal exposure group had a significantly lower risk of metabolic unhealthy status (OR: 0.65, 95%CI: 0.51-0.85) and MUNO (OR: 0.50, 95%CI: 0.35-0.72). Those associations were observed in both males and females.

CONCLUSION

Exposure to famine in early life increased the risk of metabolically unhealthy status in adulthood. Different metabolic subtypes should be identified at an early stage and followed by classification, intervention, and treatment.

Exploring the Link between Leaky-Gut-Related Markers and Metabolic Health in a Large Dutch Adult Population

A leaky gut can trigger chronic inflammation and poses a primary risk for metabolic diseases. This study established a relationship between intestinal integrity (leaky gut) and metabolic health in a general population. Leaky-gut markers (LGMs) were studied in a large population of Dutch adults with a broad spectrum of metabolic health. This study enrolled 500 individuals selected within the NQplus cohort study (n = 2048) by stratified randomization, based on waist circumference, fasting glucose, and high-density lipoprotein (HDL) cholesterol to obtain a representative and balanced population in terms of metabolic health parameters, sex (male/female), and age (<54/≥54 years). LGMs-zonulin, lipopolysaccharide-binding protein (LBP), and soluble CD14 (sCD14)-were measured in EDTA plasma or serum. Zonulin was most strongly associated with metabolic health. Zonulin and LBP were most strongly associated with the inflammatory marker C-reactive protein (CRP). The quartile analysis for zonulin and LBP showed that most metabolic health parameters and CRP levels increased from Q1 to Q4, with significant differences between quartiles, except for markers related to glucose homeostasis (glucose and glycated hemoglobin A1c (HbA1c)). Associations between LGMs and metabolic health parameters in this large Dutch adult population indicate that LGMs are valuable markers for identifying people at risk of a leaky gut and subsequent chronic inflammation linked to metabolic disorders.