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

Relationship Between Zinc, Selenium, and Magnesium Status and Markers of Metabolically Healthy and Unhealthy Obesity Phenotypes

Our objective was to investigate the relationship between zinc, selenium, and magnesium status and markers of metabolically healthy and unhealthy obesity phenotypes. This was a cross-sectional study with 140 women: metabolically healthy obese women (n = 35), metabolically unhealthy obese women (n = 28), and normal-weight women (n = 77). We have calculated the body mass index, waist-hip ratio, waist-height ratio and some adiposity indices. Additionally, we evaluated endocrine-metabolic parameters and estimated the dietary intake of energy, macronutrients, zinc, selenium, and magnesium. The mineral concentrations in plasma, erythrocytes, and urine were assessed. In obese patients, there was a significant decrease in dietary zinc, selenium, and magnesium intake per kilogram of body weight, as well as lower mineral concentrations in both plasma and erythrocytes. Additionally, these patients exhibited higher urinary mineral levels compared to the control group, regardless of whether they had healthy or unhealthy phenotypes. We observed a significant correlation between deficiencies in zinc, selenium, and magnesium and obesity-associated metabolic disorders, including dyslipidemias and redox status disturbances. This study highlights a connection between deficiencies in zinc, selenium, and magnesium and metabolic disorders linked to obesity, including dyslipidemias, alterations in redox status, and thyroid hormonal dysfunction.

The prevalence of metabolically healthy obesity and its transition into the unhealthy state: A 5-year follow-up study

People with metabolically healthy obesity (MHO) are at risk of developing cardiometabolic diseases. We investigated the prevalence of MHO and factors influencing its transition into a metabolically unhealthy state (MUS). This study was conducted as part of the Kerman Coronary Artery Disease Risk Factor Study (KERCADRS). From 2014 to 2018, 9997 people were evaluated. The obesity and metabolic status of the MHO participants were re-examined after 5 years of their initial participation in the study. Out of 347 MHO, 238 individuals were accessed at follow-up. Twenty-nine (12.2%) had metabolic unhealthy normal weight (MUNW), 169 (71.0%) had metabolic unhealthy obesity (MUO), and the others had healthy metabolic state. Among age, total cholesterol, diastolic blood pressure and triglyceride (TG) variables, the baseline serum TG level was associated with a significant increase in the risk of developing MUS during 5 years (p <.05). The TG level optimal cut-off point for predicting the development into MUS was 107 mg/dL with 62.1% sensitivity and 77.5% specificity (AUC = 0.734, p <.001). A high percentage of MHO people transit into MUS during 5 years. A TG level higher than 107 mg/dL can help to identify people at a higher risk of developing into MUS.

Risk of Cardiovascular Events in Metabolically Healthy Overweight or Obese Adults: Role of LDL-Cholesterol in the Stratification of Risk

The objective of this study was to investigate the longitudinal association of metabolically healthy overweight/obese adults with major adverse cardiovascular events (MACE) and the effect of LDL-cholesterol levels on this association. This study was conducted with 15,904 participants from the URRAH study grouped according to BMI and metabolic status. Healthy metabolic status was identified with and without including LDL-cholesterol. The risk of MACE during 11.8 years of follow-up was evaluated with multivariable Cox regressions. Among the participants aged <70 years, high BMI was associated with an increased risk of MACE, whereas among the older subjects it was associated with lower risk. Compared to the group with normal weight/healthy metabolic status, the metabolically healthy participants aged <70 years who were overweight/obese had an increased risk of MACE with an adjusted hazard ratio of 3.81 (95% CI, 1.34-10.85, p = 0.012). However, when LDL-cholesterol < 130 mg/dL was included in the definition of healthy metabolic status, no increase in risk was found in the overweight/obese adults compared to the normal weight individuals (hazard ratio 0.70 (0.07-6.71, p = 0.75). The present data show that the risk of MACE is increased in metabolically healthy overweight/obese individuals identified according to standard criteria. However, when LDL-cholesterol is included in the definition, metabolically healthy individuals who are overweight/obese have no increase in risk.

Physical activity in relation to metabolic health and obesity: The Feel4Diabetes study

AIM

To examine physical activity levels in association with metabolic health and estimate the stability of metabolically healthy obese (MHO) phenotypes over a 2-year period.

METHODS

In total, 2848 men and women from families at risk of the development of diabetes were recruited. Participants were classified as obese or non-obese and metabolic health was defined using five existing definitions. Physical activity was estimated with the International Physical Activity Questionnaire and pedometers.

RESULTS

Prevalence of the MHO phenotype varied among definitions (0% to 20.2%). Overall, the MHO were more active than the metabolically unhealthy obese (MUO). Daily sitting hours (odds ratio [OR] = 1.055, 95% confidence interval [CI]: 1.009-1.104) and daily steps (per 500; OR = 0.934, 95% CI: 0.896-0.973) were remarkable predictors of metabolic health in individuals with obesity; and likewise, in individuals without obesity. After 2 years, 44.1% of baseline MHO adults transitioned to MUO, while 84.0% of the MUO at baseline remained at the same phenotype. Although physical activity was not a major determinant in phenotype transitioning, daily steps were associated with the maintenance of metabolic health over time in the non-obese group.

CONCLUSION

A universally accepted definition for MHO is needed. Being physically active can contribute to a metabolically healthy profile even in the presence of obesity; still, MHO is a transient condition and physical activity alone may not be an adequate factor for its maintenance.

Exploring metabolically healthy obesity: prevalence, characteristics, and cardiovascular risk in the Iranian population based on the STEPS 2021

Background

Regarding the rapidly increasing prevalence of obesity throughout the globe, it remains a serious public health concern. A subgroup of obesity that does not meet metabolic syndrome criteria is called metabolically healthy obesity (MHO). However, whether the MHO phenotype increases cardiovascular disease (CVD) risk is controversial. This study aimed to evaluate the prevalence of MHO and its 10-year CVD risk in Iranian populations.

Methods

Based on the STEPS 2021 project in Iran, we collected data on 18119 Iranians 25 years and older from all 31 provinces after applying many statistical factors. Using the Framingham score, we evaluated the 10-year cardiovascular risk associated with the various MHO definition criteria for Iranian populations.

Results

The prevalence of MHO was 6.42% (5.93-6.91) at the national level according to the AHA-NHLBI definition, and 23.29% of obese women and 24.55% of obese men were classified as MHOs. Moreover, the MHO group was younger than the metabolically unhealthy obesity (MUO) group based on all definitions (p < 0.001). The odds ratio of MUO individuals being classified as high-risk individuals by the Framingham criteria for CVD was significantly higher than that of MHO individuals by all definitions, with a crude odds ratio of 3.55:1 based on AHA-NHLBI definition.

Conclusion

This study reveals a significant prevalence of MHO in the Iranian population, with approximately 25% of obese individuals classified as MHO. While MHO is associated with a lower risk of cardiovascular disease compared to MUO, MHO carries the potential for transitioning to an unhealthy state.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01364-5.

Rising Trends in Metabolically Healthy Obesity in Cancer Patients and Its Impact on Cardiovascular Events: Insights from a Contemporary Nationwide Analysis in the USA (2016-2020)

Background: Obesity or overweight raises the risk of developing 13 types of cancer, representing 40% of all cancers diagnosed in the United States annually. Given the ongoing debate surrounding the impact of metabolically healthy obesity (MHO) on cardiovascular outcomes, it is crucial to comprehend the incidence of Major Adverse Cardiovascular and Cerebrovascular Events (MACCEs) and the influence of MHO on these outcomes in cancer patients. Methods: Data of hospitalized cancer patients with and without obesity were analyzed from the National Inpatient Sample 2016-2020. Metabolically healthy patients were identified by excluding diabetes, hypertension, and hyperlipidemia using Elixhauser comorbidity software, v.2022.1. After that, we performed a multivariable regression analysis for in-hospital MACCEs and other individual outcomes. Results: We identified 3,111,824 cancer-related hospitalizations between 2016 and 2020. The MHO cohort had 199,580 patients (6.4%), whereas the MHnO (metabolically healthy non-obese) cohort had 2,912,244 patients (93.6%). The MHO cohort had a higher proportion of females, Blacks, and Hispanics. Outcomes including in-hospital MACCEs (7.9% vs. 9.5%; p < 0.001), all-cause mortality (6.1% vs. 7.5%; p < 0.001), and acute myocardial infarction (AMI) (1.5% vs. 1.6%; p < 0.001) were lower in the MHO cohort compared to the MHnO cohort. Upon adjusting for the baseline characteristics, the MHO group had lower odds of in-hospital MACCEs [adjusted odds ratio (AOR) = 0.93, 95% CI (0.90-0.97), p < 0.001], all-cause mortality [AOR = 0.91, 95% CI (0.87-0.94); p < 0.001], and acute ischemic stroke (AIS) [AOR = 0.76, 95% CI (0.69-0.84); p < 0.001], whereas there were higher odds of acute myocardial infarction (AMI) [AOR = 1.08, 95% CI (1.01-1.16); p < 0.001] and cardiac arrest (CA) [AOR = 1.26, 95% CI (1.01-1.57); p = 0.045] in the MHO cohort compared to the MHnO cohort. Conclusions: Hospitalized cancer patients with MHO exhibited a lower prevalence of in-hospital MACCEs than those with MHnO. Additional prospective studies and randomized clinical trials are imperative to validate these findings, particularly in stratifying MHO across various cancer types and their corresponding risks of in-hospital MACCEs.

Low-carbohydrate dietary score and the incidence of metabolically unhealthy phenotype based on BMI status: a cohort study

There is scarce research focusing on the relationship between the low-carbohydrate dietary score and the development of a metabolically unhealthy phenotype. Therefore, this cohort study was designed to assess the association between the low-carbohydrate dietary score and the risk of metabolically unhealthy phenotypes (MUP). This study included 1299 adults with healthy metabolic profiles who were followed for 5.9 years. Results indicated an inverse association between the second tertile of the low-carbohydrate dietary score and the risk of developing metabolically unhealthy obesity (MUO) (HR: 0.76, 95% CI: 0.59-0.98). In addition, we found an inverse association between the healthy low-carbohydrate dietary score and the risk of MUO (HR: 0.77, 95% CI: 0.60-0.99). Our results revealed a nonlinear inverse association between the low-carbohydrate dietary score and the risk of MUP only in subjects with overweight or obesity. This relationship was independent of animal protein and fat intake. Also, we found that a lower intake of unhealthy carbohydrates was associated with a lower risk of MUP only in subjects with overweight or obesity.

Healthy overweight and obesity in the young: Prevalence and risk of major adverse cardiovascular events

AIMS

To investigate the prevalence of metabolically healthy overweight/obesity and to study its longitudinal association with major adverse cardiovascular and renal events (MARCE).

METHODS AND RESULTS

The study was conducted in 1210 young-to-middle-age subjects grouped according to their BMI and metabolic status. The risk of MARCE was evaluated during 17.4 years of follow-up. Forty-eight-percent of the participants had normal weight, 41.9% had overweight, and 9.3% had obesity. Metabolically healthy status was found in 31.1% of subjects with normal weight and in 20.0% of those with overweight/obesity. During the follow-up, there were 108 MARCE. In multivariate Cox analysis adjusted for confounders and risk factors, no association was found between MARCE and overweight/obesity (p = 0.49). In contrast, metabolic status considered as a two-class variable (0 versus at least one metabolic abnormality) was a significant predictor of MARCE (HR, 2.11; 95%CI, 1.21-3.70, p = 0.009). Exclusion of atrial fibrillation from MARCE (N = 87) provided similar results (HR, 2.11; 95%CI, 1.07-4.16, p = 0.030). Inclusion of average 24 h BP in the regression model attenuated the strength of the associations. Compared to the group with healthy metabolic status, the metabolically unhealthy overweight/obesity participants had an increased risk of MARCE with an adjusted HR of 2.33 (95%CI, 1.05-5.19, p = 0.038). Among the metabolically healthy individuals, the CV risk did not differ according to BMI group (p = 0.53).

CONCLUSION

The present data show that the risk of MARCE is not increased in young metabolically healthy overweight/obesity suggesting that the clinical approach to people with high BMI should focus on parameters of metabolic health rather than on BMI.

Metabolically healthy obesity and health risks - a review of meta-analyses

OBJECTIVE

This article briefly summarizes the results of existing research on metabolically healthy obesity in the context of health risks.

METHODS

The PubMed database was searched for relevant meta-analyses addressing metabolically healthy obesity in the context of health risks.

RESULTS

We included a total of 17 relevant meta-analyses in this review. The results of the studied meta-analyses showed that metabolically healthy obesity may be only a transient condition associated with an increased risk of developing metabolic abnormalities in the future. People with obesity without metabolic abnormalities have an increased risk of type 2 diabetes, cardiovascular disease, cancer, chronic kidney disease, and depressive syndrome. In addition, all people with obesity are at risk of pathogenesis resulting from the mechanical stress caused by presence of abnormal adipose tissue, such as sleep apnoea syndrome or skin problems.

CONCLUSION

Based on the results of meta-analyses, we recommend motivating all obese patients to change their lifestyle regardless of the presence of metabolic defects.

Phenotyping obesity: A focus on metabolically healthy obesity and metabolically unhealthy normal weight

Over the past 4 decades, research has shown that having a normal body weight does not automatically imply preserved metabolic health and a considerable number of lean individuals harbour metabolic abnormalities typically associated with obesity. Conversely, excess adiposity does not always equate with an abnormal metabolic profile. In fact, evidence exists for the presence of a metabolically unhealthy normal weight (MUHNW) and a metabolically healthy obese (MHO) phenotype. It has become increasingly recognised that different fat depots exert different effects on the metabolic profile of each individual by virtue of their location, structure and function, giving rise to these different body composition phenotypes. Furthermore, other factors have been implicated in the aetiopathogenesis of the body composition phenotypes, including genetics, ethnicity, age and lifestyle/behavioural factors. Even though to date both MHO and MUHNW have been widely investigated and documented in the literature, studies report different outcomes on long-term cardiometabolic morbidity and mortality. Future large-scale, observational and population-based studies are required for better profiling of these phenotypes as well as to further elucidate the pathophysiological role of the adipocyte in the onset of metabolic disorders to allow for better risk stratification and a personalised treatment paradigm.

Metabolically healthy obese individuals are still at high risk for diabetes: Application of the marginal structural model

AIM

To assess the effect of obesity phenotype on the incidence of diabetes, considering phenotype as a time-varying exposure.

METHODS

We used community-based cohort data from the Korean Genome and Epidemiology Study, with a 16-year follow-up period. Obesity phenotype was determined using body mass index and metabolic syndrome criteria. The influence of obesity phenotype on the occurrence of diabetes was evaluated using a Cox proportional hazard model and a marginal structural model (MSM).

RESULTS

Obesity phenotypes were defined in 6265 individuals, with diabetes identified in 903 (14.4%) during the follow-up period. Individuals with metabolically healthy obesity (MHO) exhibited a higher risk of diabetes compared to those with metabolically healthy normal weight (MHNW), with a hazard ratio (HR) of 1.48 (95% confidence interval [CI] 1.15-1.90). This association remained significant after applying the MSM (HR 1.49, 95% CI 1.01-2.20). Moreover, various sensitivity analyses consistently demonstrated a higher risk of diabetes in individuals with MHO compared to those with MHNW.

CONCLUSIONS

Even when obesity phenotype was treated as a time-varying exposure, individuals with MHO were still at higher risk for developing diabetes than those with MHNW. Consequently, such individuals should aim to avoid transitioning to a metabolically unfavourable state and strive to reduce their body weight to a normal range.

Instability of Healthy Overweight and Obesity Phenotypes over the Long Term in Young Participants in the HARVEST Study: Influence of Sex

BACKGROUND

Whether healthy metabolic status is stable or only temporary is still controversial. The aim of the present study was to determine the frequency of the transition from metabolically healthy to metabolically unhealthy status, or vice versa, over the long term.

METHODS

We examined 970 individuals of 18 to 45 years of age. The participants' mean age was 33.1 ± 8.6 years and mean BP was 145.5 ± 10.6/93.5 ± 5.7 mmHg. Participants were classified into four groups according to whether they had normal weight or overweight/obesity (OwOb) and were metabolically healthy or unhealthy. After 7.5 years, 24.3% of men and 41.9% of women in the metabolically healthy normal-weight group remained metabolically healthy (p < 0.0001). Among the metabolically healthy OwOb participants, 31.9% remained metabolically healthy, with a similar frequency in men and women. However, more OwOb women (19.1%) than men (5.7%) achieved normal weight (p < 0.0001). Among the metabolically unhealthy OwOb subjects, 81.8% of men and 69.3% of women remained metabolically unhealthy, 7.4% of men and 12.0% of women transitioned to OwOb healthy status, and 10.7% of men and 18.7% of women achieved normal weight (men versus women, p < 0.0001). Predictors of transition to unhealthy status were high BP, high BMI, and smoking. Male sex was a borderline predictor of progression to unhealthy status in OwOb participants (p = 0.073).

CONCLUSION

These data show that metabolically healthy status is a highly unstable condition in both normal-weight and OwOb individuals. The impairment of metabolic status was more frequent in men than in women. Lifestyle counseling produced beneficial effects in almost one-third of metabolically unhealthy OwOb women and in less than one-fifth of men.

A data-driven computational model for obesity-driven diabetes onset and remission through weight loss

Obesity is a major risk factor for the development of type 2 diabetes (T2D), where a sustained weight loss may result in T2D remission in individuals with obesity. To design effective and feasible intervention strategies to prevent or reverse T2D, it is imperative to study the progression of T2D and remission together. Unfortunately, this is not possible through experimental and observational studies. To address this issue, we introduce a data-driven computational model and use human data to investigate the progression of T2D with obesity and remission through weight loss on the same timeline. We identify thresholds for the emergence of T2D and necessary conditions for remission. We explain why remission is only possible within a window of opportunity and the way that window depends on the progression history of T2D, individual's metabolic state, and calorie restrictions. These findings can help to optimize therapeutic intervention strategies for T2D prevention or treatment.

Diagnostic accuracy of anthropometric indices for metabolically healthy obesity in child and adolescent population

BACKGROUND

A variable percentage of children and adolescents with obesity do not have cardiometabolic comorbidities. A phenotype called metabolically healthy obese (MHO) has emerged to describe this population subgroup. Early identification of this condition may prevent the progression to metabolically unhealthy obesity (MUO).

MATERIAL AND METHODS

A cross-sectional descriptive study of 265 children and adolescents from Cordoba (Spain) conducted in 2018. The outcome variables were MHO, established based on three criteria: International Criterion, HOMA-IR, and a combination of the previous two.

RESULTS

The prevalence of MHO ranged from 9.4% to 12.8% of the study population, between 41% and 55.7% of the sample with obesity. The highest agreement was reached between the HOMA-IR definitions and the combined criteria. The waist-to-height ratio (WHtR) was the indicator with the highest discriminant capacity for MHO in 2 of the three criteria, with its best cut-off point at 0.47 for both.

CONCLUSION

The prevalence of MHO in children and adolescents differed according to the criteria used for diagnosis. The anthropometric variable with the most remarkable discriminating capacity for MHO was WHtR, with the same cut-off point in the three criteria analysed.

IMPACT STATEMENT

This research work defines the existence of metabolically healthy obesity through anthropometric indicators in children and adolescents. Definitions that combine cardiometabolic criteria and insulin resistance are used to identify metabolically healthy obesity, as well as the prediction of this phenomenon through anthropometric variables. The present investigation helps to identify metabolically healthy obesity before metabolic abnormalities begin.

Clinical Classification of Obesity and Implications for Metabolic Dysfunction-Associated Fatty Liver Disease and Treatment

Obesity,and metabolic dysfunction-associated fatty liver disease (MAFLD) have reached epidemic proportions globally. Obesity and MAFLD frequently coexist and act synergistically to increase the risk of adverse clinical outcomes (both hepatic and extrahepatic). Type 2 diabetes mellitus (T2DM) is the most important risk factor for rapid progression of steatohepatitis and advanced fibrosis. Conversely, the later stages of MAFLD are associated with an increased risk of T2DM incident. According to the proposed criteria, MAFLD is diagnosed in patients with liver steatosis and in at least one in three: overweight or obese, T2DM, or signs of metabolic dysregulation if they are of normal weight. However, the clinical classification and correlation between obesity and MAFLD is more complex than expected. In addition, treatment for obesity and MAFLD are associated with a reduced risk of T2DM, suggesting that liver-based treatments could reduce the risk of developing T2DM. This review describes the clinical classification of obesity and MAFLD, discusses the clinical features of various types of obesity and MAFLD, emphasizes the role of visceral obesity and insulin resistance (IR) in the development of MAFLD,and summarizes the existing treatments for obesity and MAFLD that reduce the risk of developing T2DM.

Adherence to the Mediterranean diet as a possible additional tool to be used for screening the metabolically unhealthy obesity (MUO) phenotype

BACKGROUND

The terms metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) categorize subjects with obesity based on the presence or absence of cardio-metabolic risk factors. Detecting MUO phenotype is crucial due to the high risk of cardio-metabolic complications, requiring tailored and intensive follow-up. However, diagnosing MUO is time-consuming and costly. Thus, we aimed to investigate the role of Mediterranean diet (MD) in determining MHO/MUO phenotypes and whether adherence to MD could serve as an additional screening tool for MUO phenotype.

METHODS

The study population of this cross-sectional observational study consisted of 275 subjects with obesity. We assessed their lifestyle habits (physical activity and smoking habits), anthropometric measurements (weight, height, waist circumference, body mass index), blood pressure, metabolic parameters, inflammatory marker (high sensitivity C reactive protein levels), adherence to MD (by PREvención con DIetaMEDiterránea (PREDIMED) questionnaire), and MHO/MUO phenotypes.

RESULTS

The study included 275 individuals with obesity (256F/19M; 34.0 ± 10.5 years; BMI 38.3 ± 5.95 kg/m2). Among them, 114 (41.5%) exhibited MHO phenotype, while 161 (58.5%) had MUO phenotype. MHO phenotype exhibited favorable anthropometric and cardio-metabolic profiles, characterized by lower waist circumference (p < 0.001), BMI (p < 0.001), insulin resistance (p < 0.001), blood pressure (p < 0.001), inflammation (p < 0.001), and lipid levels (p < 0.001) compared to MUO phenotype. Notably, we found that MHO phenotype had higher adherence to MD (p < 0.001) and consumed more extra virgin olive oil (EVOO) (p < 0.001), vegetables (p < 0.001), fruits (p < 0.001), legumes (p = 0.001), fish (p < 0.001), wine (p = 0.008), and nuts (p = 0.001), while reporting lower intake of red/processed meats (p < 0.001), butter, cream, margarine (p = 0.008), soda drinks (p = 0.006), and commercial sweets (p = 0.002) compared to MUO phenotype. Adherence to MD (p < 0.001) and EVOO (p = 0.015) intake were identified as influential factors in determining the presence of MUO/MHO phenotypes. Furthermore, a PREDIMED score < 5 proved to be the most sensitive and specific cut-point value for predicting the presence of MUO phenotype (p < 0.001).

CONCLUSION

High adherence to MD was associated with MHO phenotype. Moreover, we suggest that a specific cut-off of the PREDIMED score could be an indicator to discriminate patients with MUO/MHO phenotypes and therefore help in identifying patients at higher cardiovascular risk who will require specific dietary intervention.

Associations of obesity phenotypes with weight change, cardiometabolic benefits, and type 2 diabetes incidence during a lifestyle intervention: results from the PREVIEW study

BACKGROUND/OBJECTIVES

Some individuals with overweight/obesity may be relatively metabolically healthy (MHO) and have a lower risk of cardiovascular disease than those with metabolically unhealthy overweight/obesity (MUO). We aimed to compare changes in body weight and cardiometabolic risk factors and type 2 diabetes incidence during a lifestyle intervention between individuals with MHO vs MUO.

METHODS

This post-hoc analysis included 1012 participants with MHO and 1153 participants with MUO at baseline in the randomized trial PREVIEW. Participants underwent an eight-week low-energy diet phase followed by a 148-week lifestyle-based weight-maintenance intervention. Adjusted linear mixed models and Cox proportional hazards regression models were used.

RESULTS

There were no statistically significant differences in weight loss (%) between participants with MHO vs MUO over 156 weeks. At the end of the study, weight loss was 2.7% (95% CI, 1.7%-3.6%) in participants with MHO and 3.0% (2.1%-4.0%) in those with MUO. After the low-energy diet phase, participants with MHO had smaller decreases in triglyceride (mean difference between MHO vs MUO 0.08 mmol·L-1 [95% CI, 0.04-0.12]; P < 0.001) but similar reductions in fasting glucose and HOMA-IR than those with MUO. However, at the end of weight maintenance, those with MHO had greater reductions in triglyceride (mean difference -0.08 mmol·L-1 [-0.12--0.04]; P < 0.001), fasting glucose, 2-hour glucose (difference -0.28 mmol·L-1 [-0.41--0.16]; P < 0.001), and HOMA-IR than those with MUO. Participants with MHO had smaller decreases in diastolic blood pressure and HbA1c and greater decreases in HDL cholesterol after weight loss than those with MUO, whereas the statistically significant differences disappeared at the end of weight maintenance. Participants with MHO had lower 3-year type 2 diabetes incidence than those with MUO (adjusted hazard ratio 0.37 [0.20-0.66]; P < 0.001).

CONCLUSIONS

Individuals with MUO had greater improvements in some cardiometabolic risk factors during the low-energy diet phase, but had smaller improvements during long-term lifestyle intervention than those with MHO.

Adiposity, hepatic steatosis, and metabolic health transitions in people with obesity: Influences of age and sex

BACKGROUND AND AIMS

Metabolically healthy (MHO) and unhealthy obesity (MUO) may be transient conditions. This study aimed to quantify and identify predictive factors of metabolic transitions in obesity, exploring influences of age and sex.

METHODS AND RESULTS

We retrospectively evaluated adults with obesity who underwent routine health evaluation. In a cross-sectional analysis of 12,118 individuals (80% male, age 44.3 ± 9.9 years), 16.8% had MHO. In a longitudinal evaluation of 4483 participants, 45.2% of individuals with MHO at baseline had dysmetabolism after a median follow-up of 3.0 (IQR 1.8-5.2) years, whereas 13.3% MUO participants became metabolically healthy (MH). Development of hepatic steatosis (HS, ultrasound) was an independent predictor of MHO conversion to dysmetabolism (OR 2.36; 95% CI 1.43, 3.91; p < 0.001), while HS persistence was inversely associated with transition from MUO to MH status (OR 0.63; 95% CI 0.47, 0.83; p = 0.001). Female sex and older age were associated with a lower chance of MUO regression. A 5% increment in body mass index (BMI) over time increased the likelihood of metabolic deterioration by 33% (p = 0.002) in females and 16% (p = 0.018) in males with MHO. A 5% reduction in BMI was associated with a 39% and 66% higher chance of MUO resolution in females and males, respectively (both p < 0.001).

CONCLUSION

The findings support a pathophysiological role of ectopic fat depots in metabolic transitions in obesity and identify female sex as an aggravating factor for adiposity-induced dysmetabolism, which has implications for personalized medicine.

[Relationship between skeletal muscle mass index and metabolic phenotypes of obesity in adolescents]

OBJECTIVES

To study the relationship between skeletal muscle mass index (SMI) and metabolic phenotypes of obesity in adolescents, and to provide a basis for the prevention and control of adolescent obesity and related metabolic diseases.

METHODS

A total of 1 352 adolescents aged 12 to 18 years were randomly selected by stratified cluster sampling in Yinchuan City from October 2017 to September 2020, and they were surveyed using questionnaires, physical measurements, body composition measurements, and laboratory tests. According to the diagnostic criteria for metabolic abnormalities and the definition of obesity based on the body mass index, the subjects were divided into four metabolic phenotypes: metabolically healthy normal weight, metabolically healthy obesity, metabolically unhealthy normal weight, and metabolically unhealthy obesity. The association between SMI and the metabolic phenotypes was analyzed using multivariate logistic regression.

RESULTS

The SMI level in the metabolically unhealthy normal weight, metabolically healthy obesity, and metabolically unhealthy obesity groups was lower than that in the metabolically healthy normal weight group (P<0.001). Multivariate logistic regression analysis showed that after adjusting for gender and age, a higher SMI level was a protective factors for adolescents to develop metabolic unhealthy normal weight, metabolically healthy obesity, and metabolically unhealthy obesity phenotypes (OR=0.74, 0.60, and 0.54, respectively; P<0.001).

CONCLUSIONS

Increasing SMI can reduce the risk of the development of metabolic unhealthy/obesity.

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.

Association of metabolically healthy obesity in young adulthood with myocardial structure and function

BACKGROUND

Obesity is major cause of cardiovascular diseases. Metabolically healthy obesity (MHO) may increase heart failure risk early in life, and may be reflected in impaired cardiac structure and function. Therefore, we aimed to examine the relationship between MHO in young adulthood and cardiac structure and function.

METHODS

A total of 3066 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study were included, who completed echocardiography in young adulthood and middle age. The participants were grouped by obesity status (body mass index ≥30 kg/m²) and poor metabolic health (≥2 criteria for metabolic syndrome) into four metabolic phenotypes as follows: metabolically healthy non-obesity (MHN), MHO, metabolically unhealthy non-obesity (MUN), metabolically unhealthy obesity (MUO). The associations of the metabolic phenotypes (MHN serving as the reference) with left ventricular (LV) structure and function were evaluated using multiple linear regression models.

RESULTS

At baseline, mean age was 25 years, 56.4% were women, and 44.7% were black. After a follow-up 25 years, MUN in young adulthood was associated with worse LV diastolic function (E/é ratio, β [95% CI], 0.73 [0.18, 1.28]), worse systolic function (global longitudinal strain [GLS], 0.60 [0.08, 1.12]) in comparison with MHN. MHO and MUO were associated with LV hypertrophy (LV mass index, 7.49 g/m² [4.63, 10.35]; 18.23 g/m² [12.47, 23.99], respectively), worse diastolic function (E/é ratio, 0.67 [0.31, 1.02]; 1.47 [0.79, 2.14], respectively), and worse systolic function (GLS, 0.72 [0.38, 1.06]; 1.35 [0.64, 2.05], respectively) in comparison with MHN. These results were consistent in several sensitivity analyses.

CONCLUSIONS

In this community-based cohort using data from the CARDIA study, obesity in young adulthood was significantly associated with LV hypertrophy, worse systolic and diastolic function regardless of metabolic status. Relationship of Baseline Metabolic Phenotypes with Young Adulthood and Midlife Cardiac Structure and Function. Adjusted for year 0 covariates: age, sex, race, educational level, smoking status, drinking status, and physical activity; metabolically healthy non-obesity was used as a reference category for comparison. ^† Criteria for metabolic syndrome are listed in Supplementary Table S6. MUN metabolically unhealthy non-obesity, MHO metabolically healthy obesity, LVMi left ventricular mass index, LVEF left ventricular ejection fraction, E/A early to late peak diastolic mitral flow velocity ratio, E/é mitral inflow velocity to early diastolic mitral annular velocity, CI confidence interval.

Histological Skin Assessment of Patients Submitted to Bariatric Surgery: A Prospective Longitudinal Cohort Study

BACKGROUND

Obesity is a stigmatizing disease that can cause dermatological aberrations, such as sagging after rapid weight loss.

OBJECTIVE

This study is to evaluate the effects of obesity and massive weight loss following bariatric surgery on collagen and elastic fibers of the extracellular matrix of the skin.

METHODS

Thirty-three skin biopsies were collected from patients prior to bariatric surgery and one year after surgery. Histological analyses were performed using hematoxylin-eosin and Weigert's resorcin-fuchsin staining for collagen and elastic and elaunin fibers, respectively. Differences between means were submitted to the Student's t-test or Mann-Whitney U test, with p < 0.05 significant.

RESULTS

The study demonstrated an architectural alteration of the skin 1 year after bariatric surgery. In the histological analysis of the skin samples, a significant difference in the thickness of the epidermis was found 1 year after surgery in all age groups as well as in the 38-to-68-kg weight loss group (p < 0.0001). In addition to laxity, disorganization of collagen was found, with an apparent decrease in quantity and an increase in elastic fibers, although fragmented (p < 0.0001).

CONCLUSION

Obesity and massive weight loss following bariatric surgery cause the disorganization of collagen fibers and the fragmentation of elastic fibers of the extracellular matrix of the skin.

Whole-Genome Transcriptomics of PBMC to Identify Biomarkers of Early Metabolic Risk in Apparently Healthy People with Overweight-Obesity and in Normal-Weight Subjects

SCOPE

Peripheral blood mononuclear cells (PBMC) provide a useful and minimally invasive source of biomarkers. Here to identify PBMC transcriptomic biomarkers predictive of metabolic impairment related to increased adiposity is aimed.

METHODS AND RESULTS

The study analyzed the global PBMC transcriptome in metabolically healthy (normoglycemic) volunteers with overweight-obesity (OW-OB, n = 12), and in subjects with metabolically obese normal-weight (MONW, n = 5) phenotype, in comparison to normal-weight (NW, n = 12) controls. The study identifies 1072 differentially expressed genes (DEGs) in OW-OB versus NW and 992 in MONW versus NW. Hierarchical clustering of the top 100 DEGs clearly distinguishes OW-OB and MONW from NW. Remarkably, the OW-OB and MONW phenotypes share 257 DEGs regulated in the same direction. The top up-regulated gene CXCL8, coding for interleukin 8, with a role in obesity-related pathologies, is of special interest as a potential marker for predicting increased metabolic risk. CXCL8 expression is increased mainly in the MONW group and correlated directly with C-reactive protein levels.

CONCLUSIONS

PBMC gene expression analysis of CXCL8 or a pool of DEGs may be used to identify early metabolic risk in an apparently healthy population regardless of their BMI, i.e., subjects with OW-OB or MONW phenotype and to apply adequate and personalized nutritional preventive strategies.

Association of physical activity and trajectories of physical activity with cardiovascular disease

INTRODUCTION

Prolonged sedentary life existence is associated with increased incidence of cardiovascular disease (CVD), coronary heart disease (CHD), obesity, type 2 diabetes mellitus (T2DM), hypertension, heart failure (HF), and all-cause mortality. On the contrary, regular exercise is known from antiquity to be associated with beneficial cardiovascular (CV) effects and decreased mortality.

AREAS COVERED

The cardiovascular (CV) benefits of exercise have been confirmed by many studies, but the trajectories of the different modes of PA are not well recognized. In order to examine the different modalities of exercise and its long-term trajectories, a Medline search of the English literature was conducted between 2015 and 2022 and 60 pertinent papers were selected for review.

EXPERT OPINION

Careful review of the selected papers showed that the beneficial CV effects of PA are mediated through several favorable modifications of molecular and clinical factors. Also, any type of physical activity in conjunction with lifestyle adjustments is associated with decreased incidence of CVD, CHD, obesity, T2DM, hypertension, HF, and all-cause mortality. In addition, the long-term trajectories regarding the duration and the level of exercise are associated with greater beneficial CV effects, with even the resumption of discontinued exercise can lead to beneficial CV effects.

Comparing Effects of Bariatric Surgery on Body Composition Changes in Metabolically Healthy and Metabolically Unhealthy Severely Obese Patients: Tehran Obesity Treatment Study (TOTS)

BACKGROUND

Among two popular obesity phenotypes, metabolically healthy severely obese (MHSO) and metabolically unhealthy severely obese (MUSO), it is important to clarify whether or not those with MHSO phenotype would benefit from bariatric surgery in terms of an improvement in body composition parameters.

METHODS

A prospective cohort was conducted on a total of 4028 participants (1404 MHSO and 2624 MUSO) who underwent bariatric surgery; MHSO was defined as having abnormalities in none or one of these four parameters: systolic blood pressure and/or diastolic blood pressure, triglycerides, fasting plasma glucose, and high-density lipoprotein. Otherwise, the definition of MUSO was met. Body composition analysis was performed at the baseline and 6-, 12-, 24-, and 36-month post-surgery using bioelectrical impedance analyzer.

RESULTS

Both phenotypes showed a significant decrease in fat mass (FM) and fat-free mass (FFM) and a significant increase in EWL% and TWL% (P_trend < 0.05). FFM, FM%, and excess weight loss (EWL%) were significantly different between the two phenotypes (P_between < 0.05) during the follow-up. Multivariate linear regression demonstrated that compared to MUSO patients, MHSO individuals experienced a greater increase in total weight loss (TWL%) and EWL% at 12- and 24-month and in EWL% at 36-month post-surgery and also a lower decrease in the FFML/WL% after 12 months.

CONCLUSION

Despite a lower decrease of FFML/WL% and a greater increase in TWL and EWL in MHSO phenotype at some time points, there were no clinically significant differences between the study groups in terms of body composition changes throughout the follow-up period.

The risk for chronic kidney disease in metabolically healthy obese patients: A systematic review and meta-analysis

BACKGROUND

Chronic kidney disease (CKD) is associated with obesity and metabolic syndrome. Nevertheless, the association of CKD with phenotype referred as metabolically healthy obese or overweight is unclear. In this this systematic review and meta-analysis, we investigate the relationships between obesity and CKD independent of metabolic syndrome by appraising published evidence in studies focusing on metabolically healthy obese people.

MATERIALS AND METHODS

We performed a literature search through three databases Embase (Elsevier), the Cochrane Central Register of Controlled Trials (Wiley) and PubMed/Medline Web of Science up to March 2022 with the following terms: "chronic kidney disease", "kidney function", "obesity", "metabolic syndrome", "metabolically healthy obesity", "metabolically healthy overweight". Metabolically unhealthy was defined an individual having at least 3 of the following: abdominal obesity, high blood pressure, hypertriglyceridemia, low HDL cholesterol and hyperglycaemia. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for reporting. Prospective, retrospective, randomized and nonrandomized studies fitting the search criteria were included in our results.

RESULTS

Our final analysis included 16 studies with a total number of 4.965.285 participants. There is considerable heterogeneity in terms of study design, participant characteristics and number of participants across individual studies. In comparison to healthy normal weight patients, the risk was progressively higher in overweight (RR 1.29, 95% CI 1.27 to 1.32, p < 0.001) and obese patients (RR 1.47, 95% CI 1.31 to 1.65, p < 0.001).

CONCLUSION

Metabolically healthy overweight and obese individuals have higher risk of CKD compared to individuals without weight excess.

Is There a Link between Obesity Indices and Skin Autofluorescence? A Response from the ILERVAS Project

There is controversial information about the accumulation of advanced glycation end-products (AGEs) in obesity. We assessed the impact of total and abdominal adiposity on AGE levels via a cross-sectional investigation with 4254 middle-aged subjects from the ILERVAS project. Skin autofluorescence (SAF), a non-invasive assessment of subcutaneous AGEs, was measured. Total adiposity indices (BMI and Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE)) and abdominal adiposity (waist circumference and body roundness index (BRI)) were assessed. Lean mass was estimated using the Hume index. The area under the receiver operating characteristic (ROC) curve was evaluated for each index. Different cardiovascular risk factors (smoking, prediabetes, hypertension and dyslipidemia) were evaluated. In the study population, 26.2% showed elevated SAF values. No differences in total body fat, visceral adiposity and lean body mass were detected between patients with normal and high SAF values. SAF levels showed a very slight but positive correlation with total body fat percentage (estimated by the CUN-BAE formula) and abdominal adiposity (estimated by the BRI). However, none of them had sufficient power to identify patients with high SAF levels (area under the ROC curve <0.52 in all cases). Finally, a progressive increase in SAF levels was observed in parallel with cardiovascular risk factors in the entire population and when patients with normal weight, overweight and obesity were evaluated separately. In conclusion, total obesity and visceral adiposity are not associated with a greater deposit of AGE. The elevation of AGE in obesity is related to the presence of cardiometabolic risk.

Long-term metabolic fate and mortality in obesity without metabolic syndrome

BACKGROUND

Obesity and metabolic syndrome (MetS) are known to expose to atrial fibrillation (AF), cardiovascular diseases (CVD) and mortality. Metabolically healthy obesity refers to obesity without MetS. This study aimed to investigate how obesity and MetS modify the risk of CVD, AF and mortality in very long-time follow-up.

METHODS

Finnish middle-aged subjects (n = 1045) were grouped into four subgroups according to the presence of obesity and MetS. CVD events and AF were followed for 24 years and total mortality for 30 years. Moreover, 600 available patients had a follow-up visit for metabolic examinations after approximately 22 years.

RESULTS

One-hundred and sixty-two (30%) subjects without obesity or MetS died during the follow-up. Ninety-two (17%) of the patients in this group had a CVD event and 58 (11%) were diagnosed with AF. As compared to them, obese subjects without MetS had similar metabolic fate and mortality (mortality 26 (38%), p = .143; CVD event 12 (18%), p = .858 and AF 7 (10%), p = .912, respectively), whereas subjects with obesity and MetS had greater mortality (102 (49%), p < .001), more CVD (71 (34%), p < .001) and AF (49 (23%), p < .001). Non-obese individuals with MetS had greater rates of mortality (96 (44%), p < .001) and CVD (80 (37%), p < .001), but not of AF (26 (12%), p = .606). Of the 40 subjects with obesity but without MetS at baseline and available for the follow-up visit, 15 (38%) were metabolically healthy at the follow-up visit.

CONCLUSIONS

In the present long-term follow-up study, the presence of MetS, but not obesity only, implies a greater risk of mortality and CVD. The risk of AF is increased only in subjects with both obesity and MetS. However, obesity without MetS tends to progress eventually to obesity with MetS. Key messagesThe presence of metabolic syndrome (MetS), but not obesity only, entails a greater risk of mortality and cardiovascular diseases.The risk of atrial fibrillation is increased only in subjects with both obesity and MetS.Obesity without MetS tends to progress eventually to obesity with MetS.

Diagnostic accuracy of the waist-to-height ratio and other anthropometric indices for metabolically healthy obesity in the working population

Approximately one-third of overweight individuals, and half of those with obesity, do not have cardiometabolic disorders. For this reason, a phenotype called metabolically healthy obese (MHO) has emerged to describe this population group. The early detection of this situation could save costs associated with the development of comorbidities or pharmacological interventions. Therefore, the aim is to know the prevalence of MHO in the working population and propose variables for its detection. Cross-sectional descriptive study of 635 workers of the Cordoba City Council was carried out based on the results of the 2016 health surveillance. The outcome variables were the MHO, established based on the criteria of the IDF, NCEP—ATP III, and Aguilar—Salinas. In addition, the degree of agreement between the different MHO criteria was studied using Cohen's kappa (k), and the predictive capacity of the anthropometric variables was assessed with Receiver Operator Curves. The prevalence of MHO ranged from 6.6 to 9%. The highest agreement was reached between the IDF and NCEP-ATP III definitions (k = 0.811; 95% CI 0.724–0.898; p &lt; 0.001). The waist-to-height ratio (WHtR) showed the highest discriminant capacity for MHO, with its best cut-off point at 0.55 for all criteria used. Sensitivity ranged from 84 to 93%. The prevalence of MHO in the working population differed according to the criteria used for diagnosis. The anthropometric variable with the highest discriminant capacity for MHO was WHtR, presenting the same cut-off point in the three criteria analyzed. Therefore, WHtR is the variable that best detects the presence of MHO.

Effect of nuts on components of metabolic syndrome in healthy adults with overweight/obesity: A systematic review and meta-analysis

AIMS

Randomized controlled trials evaluating the effects of nut consumption on the metabolic profile of healthy adults with overweight/obesity have yielded conflicting results. This systematic review and meta-analysis aimed to summarize the effects of incorporating nuts into the diet on serum lipid profile, glycemic markers, and blood pressure in healthy adults with overweight/obesity.

DATA SYNTHESIS

PubMed, Embase, Scopus, Web of Science, and Cochrane Library were searched up to April 2021. The random-effects model was used to determine the pooled effect sizes expressed as weighted mean difference (WMD) with % 95 confidence intervals (CIs). Ten eligible RCTs (with 12 arms) were included in the meta-analysis. The meta-analysis revealed that nut intake significantly decreased serum triglycerides (TG) (WMD: -13.19 mg/dL, 95% CI: - 25.90, - 0.48). Furthermore, subgroup analysis showed a significant reduction in serum LDL-cholesterol (LDL-C) following adherence to normocaloric, nut-enriched diets (WMD: - 4.56 mg/dL, 95% CI: - 8.24, - 0.88). However, nuts did not affect serum total cholesterol, high-density lipoprotein cholesterol, glycemic markers, and blood pressure.

CONCLUSIONS

Overall, incorporating nuts into the diet of healthy adults with overweight/obesity have favorable effects on serum TG and LDL-C. Thus, nuts might exert protective effects against dyslipidemia in this population.

REGISTRY NUMBER

PROPSPERO CRD42021250662.

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.

Recruiting and Engaging Women of Reproductive Age with Obesity: Insights from A Mixed-Methods Study within A Trial

Engaging women with obesity in health-related studies during preconception is challenging. Limited data exists relating to their participation. The aim of this study is to explore the experiences and opinions of women participating in a weight-related, preconception trial. This is an explanatory sequential (quan-QUAL) mixed-methods Study Within A Trial, embedded in the GetGutsy randomized controlled trial (ISRCTN11295995). Screened participants completed an online survey of eight questions (single or multiple choice and Likert scale) on recruitment, motivations and opinions on study activities. Participants with abdominal obesity (waist circumference ≥ 80 cm) were invited to a subsequent semi-structured, online focus group (n = 2, 9 participants) that was transcribed and analyzed using inductive thematic analysis, with a pragmatic epistemological approach. The survey (n = 102) showed the main research participation motivations were supporting health research (n = 38, 37.3%) and wanting health screening (n = 30, 29.4%). Most participants were recruited via email (n = 35, 34.7%) or social media (n = 15, 14.7%). In the FGs, participants valued flexibility, convenience and. research methods that aligned with their lifestyles. Participants had an expanded view of health that considered emotional well-being and balance alongside more traditional medical assessments. Clinical trialists should consider well-being, addressing the interconnectedness of health and incorporate a variety of research activities to engage women of reproductive age with obesity.

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).

Trends in the Prevalence of Obesity and Its Phenotypes Based on the Korea National Health and Nutrition Examination Survey from 2007 to 2017 in Korea

This study used data from the Korea National Health and Nutrition Examination Survey IV-VII from 2007 to identify the prevalence of obesity and its phenotypes (metabolically unhealthy obesity [MUO] and metabolically healthy obesity [MHO]) and their secular changes. The prevalence of obesity in Korea increased with significant secular changes observed (β=0.326, P trend <0.01) between 2007 and 2017, and especially in men (β=0.682, P trend <0.001) but not in women. The changes in the prevalence of obesity during the study period were different between men and women (P=0.001). The prevalence of MUO significantly increased only in men (β=0.565, P trend <0.01), while that of MHO increased only in women (β=0.179, P<0.05), especially in the younger age group (β=0.308, P<0.01).

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.

Methodological Aspects in Study of Fat Stigma in Social Media Contexts: A Systematic Literature Review

With increased obesity rates worldwide and the rising popularity in social media usage, we have witnessed a growth in hate speech towards fat/obese people. The severity of hate content has prompted researchers to study public perceptions that give rise to fat stigma from social media discourses. This article presents a systematic literature review of recent literature published in this domain to gauge the current state of research and identify possible research gaps. We have examined existing research (i.e., peer-reviewed articles that were systematically included using the EBSCO discovery service) to study their methodological aspects by reviewing their context, domain, analytical methods, techniques, tools, features and limitations. Our findings reveal that while recent studies have explored fat stigma content in social media, these mostly acquired manual analytical methods regardless of the evolved machine learning, natural language processing and deep learning methods. Although fat stigma in social media has gained enormous attention in current socio-psychological research, there exists a gap between how such research is conducted and what technologies are being applied, which limits in-depth investigations of fat stigma discussions.

Adherence to the Mediterranean Diet and Risk of Metabolically Unhealthy Obesity in Women: A Cross-Sectional Study

Some obese individuals do not present any metabolic alteration and are considered metabolically healthy (MHO). Adherence to high-quality dietary pattern may favor this phenotype. We aimed to evaluate the association between the adherence to the Mediterranean diet and risk of metabolically unhealthy obesity (MUO) in women. We conducted a cross-sectional study on 2,115 obese women. All patients underwent a medical examination, anthropometric evaluation, bioelectrical impedance, ultrasound measurements of abdominal visceral (VAT) and subcutaneous (SAT) fat, blood sampling and evaluation of adherence to the Mediterranean diet through MEDAS questionnaire. The diagnosis of MHO and MUO was made using the harmonized criteria. A multivariable logistic regression adjusted for age, BMI, fat free mass, ultrasound-estimated VAT:SAT ratio, marital status, education, past diet, antidepressant use, family history of diabetes and cardiovascular disease, menopausal status, smoking, and physical activity was used to assess the association between Mediterranean diet and MUO risk. The prevalence of MHO was 21.2% (N = 449). Compared to MUO women, MHO women were younger, had lower BMI and VAT, and had higher fat free mass and SAT. In the multivariable model, the adherence to the Mediterranean diet was not associated with the risk of MUO (OR = 0.91, 95%CI: 0.62; 1.34, P = 0.624). Given the impact of menopause on metabolic health we also carried out the analysis in pre- and post-menopausal women separately. Higher adherence to the Mediterranean diet was associated with a lower risk of MUO in postmenopausal women (OR = 0.55, 95%CI: 0.31; 0.96, P = 0.034). No association was found in premenopausal women (OR = 1.18, 95%CI: 0.70; 1.99, P = 0.532). In conclusion, adherence to the Mediterranean diet was associated with a better metabolic health in postmenopausal women. Further studies are needed to confirm the ability of the Mediterranean diet in promoting maintenance of the healthy phenotype and reversion from MUO.

Clinical monitored in subjects metabolically healthy and unhealthy before and during a SARS-CoV-2 infection– A cross-sectional study in Mexican population

The COVID-19 disease has forced us to consider the physiologic role of obesity and metabolically healthy and unhealthy status in response to SARS-CoV-2 infection. Hematological, coagulation, biochemical, and immunoinflammatory changes have been informed with a disparity in morbidity and mortality. Therefore, we aimed to investigate the influence of metabolic health on clinical features in a cross-sectional study in Mexican subjects with and without SARS-CoV-2 infection in non-severe stages after a rigorous classification of obese and non-obese subjects who were metabolically healthy and unhealthy. Four groups were formed: 1) metabolically healthy with normal BMI (MHN); 2) metabolically unhealthy with normal BMI (MUN); 3) metabolically healthy obese (MHO); 4) metabolically unhealthy obese (MUO). Serum proinflammatory (TNF-α, MCP-1, IL-1β, and IL-6) and anti-inflammatory (TGF-β, IL-1Ra, IL-4, and IL-10) cytokines, hematological parameters, coagulation, and acute phase components were evaluated. Our results showed that MHO people live with inflammaging. Meanwhile, MUN and MUO subjects develop metaflammation. Both inflammaging and metaflammation cause imperceptible modifications on hematological parameters, mainly in leukocyte populations and platelets, as well as acute phase and coagulation components. The statistical analysis revealed that many clinical features are dependent on metabolic health. In conclusion, MHO subjects seem to be transitioning from metabolically healthy to unhealthy, which is accelerated in acute processes, such as SARS-CoV-2 infection. Meanwhile, metabolically unhealthy subjects independently of BMI have a deteriorating immunometabolic status associated with a hyperinflammatory state leading to multi-organ dysfunction, treatment complications, and severe COVID-19 disease.

Prolonged or Transition to Metabolically Unhealthy Status, Regardless of Obesity Status, Is Associated with Higher Risk of Cardiovascular Disease Incidence and Mortality in Koreans

The risk of chronic disease and mortality may differ by metabolic health and obesity status and its transition. We investigated the risk of cardiovascular disease (CVD) and cancer incidence and mortality according to metabolic health and obesity status and their transition using the nationally representative Korea National Health and Nutrition Examination Survey (KNHANES) and the Ansan-Ansung (ASAS) cohort of the Korean Genome and Epidemiology Study. Participants that agreed to mortality linkage (n = 28,468 in KNHANES and n = 7530 adults in ASAS) were analyzed (mean follow-up: 8.2 and 17.4 years, respectively). Adults with no metabolic risk factors and BMI <25 or ≥25 kg/m2 were categorized as metabolically healthy non-obese (MHN) or metabolically healthy obese (MHO), respectively. Metabolically unhealthy non-obese (MUN) and metabolically unhealthy obese (MUO) adults had ≥1 metabolic risk factor and a BMI < or ≥25 kg/m2, respectively. In KNHANES participants, MUN, and MUO had higher risks for cardiovascular mortality, but not cancer mortality, compared with MHN adults. MHO had 47% and 35% lower risks of cancer mortality and all-cause mortality, respectively, compared to MHN. Similar results were observed in the ASAS participants. Compared to those persistently MHN, the risk of CVD was greater when continuously MUN or MUO. Transitioning from a metabolically healthy state to MUO also increased the risk of CVD. Few associations were found for cancer incidence. Using a nationally representative cohort and an 18-year follow-up cohort, we observed that the risk of CVD incidence and mortality and all-cause mortality, but not cancer incidence or mortality, increases with a continuous or a transition to an unhealthy metabolic status in Koreans.

Factors related to overweight and obese populations maintaining metabolic health

Background

For people who are overweight or obese, maintaining a metabolically healthy status can decrease the risks of developing cardiovascular diseases and Type 2 diabetes. Despite this, only a limited amount of research has discussed the metabolically healthy overweight and obesity (MHOO) population in Asia and the factors associated with them maintaining their metabolic health.

Methods

This study enrolled 195 MHOO participants from communities in northern Taiwan during 2009-2010 (baseline). Of the 195 participants, 89 completed the follow-up assessment after a median follow-up time of nine years. Body type was determined by body mass index (BMI, kg/m²). We defined overweight as a BMI ≥ 24 kg/m² and <27 kg/m² and defined obese as a BMI ≥ 27 kg/m². Metabolic health was defined as the absence of cardiometabolic diseases and the presence of ≤1 of the cardiometabolic risk factors, namely hypertension, hyperglycemia, hypertriglyceridemia, and low serum high-density lipoprotein cholesterol. Metabolic health, BMI, and other covariates were evaluated at both baseline and follow-up. Generalized estimating equations (GEE) models were used to analyze the factors associated with maintenance of metabolic health during the follow-up period.

Results

At baseline, the mean age of the study participants was 47.4 (SD 5.3) years and 46 (51.7%) of the participants were women. There were 51 (57.3%) individuals who maintained their metabolic health status at the time of the nine-year follow-up. The detrimental factors pertaining to metabolic health included older age, longer duration until follow-up, BMI ≥ 27 kg/m², and increase in waist circumference. No significant relationships were observed between sociodemographic factors and lifestyle factors, such as sex, level of education, cigarette smoking, alcohol consumption, and physical activity, and sustained metabolic health among MHOO individuals.

Conclusions

To maintain metabolic health and prevent negative changes in health status, control of bodyweight and waist circumference should remain a priority for MHOO individuals even when there are no metabolic disorders present.

Short-term Effects of Eating Behavior Modification on Metabolic Syndrome-Related Risks in Overweight and Obese Korean Adults

Background

We investigated whether eating behavior modification improves metabolic syndrome (MetS)-related risks in overweight/obese Korean adults, and identified dietary factors that improve metabolic status.

Methods

Among 159 volunteers, 71 with a body mass index ≥23 kg/m² and without other chronic diseases participated in the 8-week intervention, among which 54 participants who completed the intervention were included in the analyses. At baseline, patients were categorized either metabolically healthy obese (MHO; <3 MetS risk factors, n=42) or metabolically unhealthy obese (MUHO; ≥3 MetS risk factors, n=12), and then educated regarding how to choose healthy foods and meals.

Results

Lipid profiles and anthropometric and glycemic parameters were significantly improved among all participants after the intervention. Changes in waist circumference (P=0.025), and glycemic parameters (glucose, P=0.046, insulin, P=0.005, C-peptide, P=0.041) were positively correlated with changes in calorie intake from snacks. Changes in visceral fat area were negatively correlated with changes in total calorie intake (P=0.046), and positively correlated with those in calorie intake from dietary fats (P=0.039). In addition, changes in insulin (P=0.013) and C-peptide (P=0.008) concentrations were negatively correlated with changes in dietary fiber intake at dinner. After the intervention, 83.3% of initially MUHO participants became MHO and 16.7% of MHO participants became MUHO.

Conclusion

Eating behavior modification may be an important strategy to improve metabolic factors in overweight/obese people.

Selected Organ and Endocrine Complications According to BMI and the Metabolic Category of Obesity: A Single Endocrine Center Study

Obesity is a chronic and complex disease associated with metabolic, organ and endocrine complications. In the study, we analyzed a group of 105 patients suffering from obesity without any other previously recognized serious disorders who had been referred to a single endocrine center. The study aimed to assess the prevalence of selected organ and endocrine complications by subdividing the group, firstly according to body mass index (BMI) and secondly with regard to metabolic syndrome (MetS), pre-MetS and the metabolically healthy obesity (MHO) category. We have observed that in our groups, the prevalence of hyperlipidemia, hypertension, asthma, obstructive sleep apnea (OSA) depended on BMI category, whereas the incidence of hyperlipidemia, hypertension, OSA, hypothyroidism, non-alcoholic fatty liver disease, prediabetes, and type 2 diabetes was related to the metabolic category. We concluded that the distribution of particular organ and endocrine complications change significantly with increased BMI and with the shift from MHO to pre-MetS and MetS. Thus, to determine the risk of organ and endocrine complications more effectively, BMI and metabolic status should be assessed during the examination of patients with obesity.

The Association Between Metabolic Status and Risk of Cancer Among Patients With Obesity: Metabolically Healthy Obesity vs. Metabolically Unhealthy Obesity

Background

Controversial evidence about the association between cancer risk and metabolic status among individuals with obesity has been reported, but pooled data remain absent. This study aims to present pooled data comparing cancer risk between patients with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO).

Methods

The current study systematically searched pieces of literature on January 4, 2021, of prospective cohorts that compare the incidence of cancer between MHO and MUO. The quality of included studies was assessed using Newcastle-Ottawa scale, and publication bias was evaluated using funnel plots.

Results

Eleven high-quality studies were eventually selected. Quantitative analysis indicates that a lower cancer incidence exists for MHO phenotype than that for MUO (odds ratio [OR], 0.71; 95% confidential interval [CI], 0.61-0.84). Consistent outcomes are presented by subgroup analyses, which are grouped by cohort region (western population: [OR, 0.84; 95% CI, 0.75-0.93]; Asian population: [OR, 0.64; 95% CI, 0.54-0.77]); definition of metabolic unhealthiness (≥3 metabolic abnormalities: [OR, 0.62; 95% CI, 0.54-0.71]; ≥1 metabolic abnormality: [OR, 0.76; 95% CI, 0.62-0.94]); and definition of obesity (body mass index (BMI), ≥30 kg/m2: [OR, 0.84; 95% CI, 0.73-0.98]; BMI, ≥25 kg/m2: [OR, 0.53; 95% CI, 0.52-0.55]).

Conclusion

In conclusion, this study suggests a reduced cancer risk for MHO compared to MUO regardless of population heterogeneity, or the definitions of obesity and metabolic status.

The Interplay of Obesity, Dyslipidemia and Immune Dysfunction: A Brief Overview on Pathophysiology, Animal Models, and Nutritional Modulation

Obesity has emerged as a leading global health concern. It is characterized by chronic low-grade inflammation, which impairs insulin signaling, lipid metabolism and immune function. Recent findings from animal and clinical studies have begun to elucidate the underlying mechanisms of immune dysfunction seen in the context of obesity. Here, we provide a brief review on the current understanding of the interplay between obesity, dyslipidemia and immunity. We also emphasize the advantages and shortcomings of numerous applicable research models including rodents and large animal swine that aim at unraveling the molecular basis of disease and clinical manifestations. Although there is no perfect model to answer all questions at once, they are often used to complement each other. Finally, we highlight some emerging nutritional strategies to improve immune function in the context of obesity with a particular focus on choline and foods that contains high amounts of choline.

The ambiguous role of obesity in oncology by promoting cancer but boosting antitumor immunotherapy

Obesity is nowadays considered a pandemic which prevalence's has been steadily increasingly in western countries. It is a dynamic, complex, and multifactorial disease which propitiates the development of several metabolic and cardiovascular diseases, as well as cancer. Excessive adipose tissue has been causally related to cancer progression and is a preventable risk factor for overall and cancer-specific survival, associated with poor prognosis in cancer patients. The onset of obesity features a state of chronic low-grade inflammation and secretion of a diversity of adipocyte-derived molecules (adipokines, cytokines, hormones), responsible for altering the metabolic, inflammatory, and immune landscape. The crosstalk between adipocytes and tumor cells fuels the tumor microenvironment with pro-inflammatory factors, promoting tissue injury, mutagenesis, invasion, and metastasis. Although classically established as a risk factor for cancer and treatment toxicity, recent evidence suggests mild obesity is related to better outcomes, with obese cancer patients showing better responses to treatment when compared to lean cancer patients. This phenomenon is termed obesity paradox and has been reported in different types and stages of cancer. The mechanisms underlying this paradoxical relationship between obesity and cancer are still not fully described but point to systemic alterations in metabolic fitness and modulation of the tumor microenvironment by obesity-associated molecules. Obesity impacts the response to cancer treatments, such as chemotherapy and immunotherapy, and has been reported as having a positive association with immune checkpoint therapy. In this review, we discuss obesity's association to inflammation and cancer, also highlighting potential physiological and biological mechanisms underlying this association, hoping to clarify the existence and impact of obesity paradox in cancer development and treatment.

Metabolically healthy obesity in children enrolled in the CANadian Pediatric Weight management Registry (CANPWR): An exploratory secondary analysis of baseline data

Our study purpose was to determine the prevalence of metabolically healthy obesity (MHO) and examine factors associated with MHO in children with obesity. This cross-sectional study was a secondary, exploratory analysis of data that included 2-17 years old with a body mass index (BMI) ≥85th percentile from the CANadian Pediatric Weight management Registry. Children were classified as having MHO or metabolically unhealthy obesity (MUO) using consensus-based criteria. Those with MHO had normal triglycerides, high-density lipoprotein cholesterol, blood pressure, and fasting glucose. Logistic regression was used to examine factors associated with MHO, which included calculating odds ratios (ORs) and 95% confidence intervals (CIs). In total, 945 children were included (mean age: 12.3 years; 51% female). The prevalence of MHO was 31% (n = 297), with lower levels across increasing age categories (2-5 years [n = 18; 43%], 6-11 years [n = 127; 35%], 12-17 years [n = 152; 28%]). Children with MHO were younger, weighed less, and had lower BMI z-scores than their peers with MUO (all p < 0.01). MHO status was positively associated with physical activity (OR: 1.18; 95% CI: 1.01-1.38), skim milk intake (OR: 1.10; 95% CI: 1.01-1.19), and fruit intake (OR: 1.12; 95% CI: 1.01-1.24) and negatively associated with BMI z-score (OR: 0.69; 95% CI: 0.60-0.79), total screen time in hours (OR: 0.79; 96% CI: 0.68-0.92), and intake of fruit flavoured drinks (OR: 0.91; 95% CI: 0.84-0.99). These findings may help guide clinical decision-making regarding obesity management by focusing on children with MUO who are at relatively high cardiometabolic risk.

Wrist circumference as a novel predictor of transition from metabolically healthy to unhealthy phenotype in overweight/obese adults: a gender-stratified 15.5-year follow-up

BACKGROUND

Individuals with transition from metabolically healthy overweight/obese (MHO) to metabolically unhealthy overweight/obese (MUO) phenotype are significantly predisposed to greater risks of cardiovascular events compared to those with a persistent MHO phenotype. The aim of this study was to evaluate the predictive performance of wrist circumference for this transition in adults over a 15.5-year follow-up.

METHODS

We included 309 males and 821 females with the age of ≥18 years old, body mass index ≥25 kg/m², and metabolically healthy status according to the criteria of the Joint Interim Statement. The incidence of MUO phenotype was evaluated for each gender, across tertiles wrist circumference, using Cox-proportional hazard models.

RESULTS

The overall rate of transition from MHO to MUO phenotype was 87.1% in males and 77.5% in females. The hazard ratios (HRs) with 95% CI across second and third tertiles of wrist circumference were 0.89 (0.64-1.24) and 1.31 (0.99-1.73) in men (P for trend =0.027); and 1.34 (1.09-1.66) and 1.61 (1.30-2.00) in women (P for trend <0.001), respectively. After multivariable adjustment, HRs across second and third tertiles of wrist circumference were 0.92 (0.64-1.32) and 1.18 (0.83-1.67) in males (p for trend =0.352), and 1.32 (1.05-1.65) and 1.34 (1.06-1.96) in females (p for trend =0.025), respectively.

CONCLUSIONS

Wrist circumference significantly predicts the transition from MHO to MUO phenotype in adults of both genders. However, it is an independent predictor of the transition only in females. Future studies are warranted to clarify the role of wrist circumference mechanisms on metabolic risk deterioration.

Prevalence of metabolically unhealthy obesity, overweight, and normal weight and the associated risk factors in a southern coastal region, Iran (the PERSIAN cohort study): a cross-sectional study

Background

Obesity is a substantial risk factor for cardiovascular and metabolic diseases. Epidemiologic studies have shown that some obese and overweight individuals are metabolically healthy. We aimed to determine the prevalence of metabolically unhealthy obesity (MUO), metabolically unhealthy overweight (MUOW), and metabolically unhealthy normal weight (MUNW) in a southern coastal area of Iran, Bandare-Kong Non-Communicable Diseases (BKNCD) Cohort Study.

Methods

This population-based study included the participants of BKNCD, as part of the Prospective Epidemiological Research Studies in IrAN (PERSIAN). Metabolic health was defined as not fulfilling the metabolic syndrome (MetS) criteria.

Results

Among the 3917 participants in this study with the mean age of 48.29 ± 9.39 years, including 1691 (43.2%) males, the age- and sex-standardized prevalence of MUO, MUOW, and MUNW was 13.9, 16.8, and 6.4%, respectively. Binary logistic regression analysis revealed that the adjusted odds of all metabolically unhealthy states were higher in older age groups, except for MUO whose adjusted odds were lower in the 65–70 age group compared to the 55–64 age group. Illiteracy was significantly correlated with MUOW (adjusted OR: 1.43, 95% CI 1.09–1.87, P = 0.010); however, it was not associated with MUO or MUNW. Higher body mass index (BMI) was significantly correlated with MUNW but it was not associated with MUOW or MUO. Higher waist circumference (WC) was also significantly associated with all metabolically unhealthy states.

Conclusion

The age- and sex-standardized prevalence of MUO, MUOW, and MUNW was 13.9, 16.8, and 6.4%, respectively in the current study. Advanced age and higher WC were significantly correlated with all metabolically unhealthy states, while illiteracy and higher BMI were only associated with MUOW and MUNW, respectively. Metabolic health rather than weight loss should be the focus and objective of public prevention programs.

Metabolically healthy and unhealthy obesity and the progression of liver fibrosis: A cross-sectional study

BACKGROUND

The development of liver fibrosis is the most important predictor of adverse outcomes in patients with non-alcoholic fatty liver disease (NAFLD). Little is known regarding the risk factors for the progression of NAFLD to liver fibrosis. The present cross-sectional study aimed to examine the association of liver fibrosis with metabolically healthy and unhealthy obesity among patients with NAFLD.

METHODS

The severity of fatty liver was examined using ultrasonography. We used the NAFLD fibrosis score to determine the severity of liver fibrosis. Anthropometric indices, physical activity, and body composition were assessed. Blood samples were collected to determine serum metabolic parameters. Participants without any component of metabolic syndrome and homeostasis model assessment of insulin resistance (HOMA-IR) <2.5 were considered as metabolically healthy. To examine the association of liver fibrosis with metabolically healthy and unhealthy obesity, multivariable-adjusted odds ratios (ORs) were applied.

RESULTS

The current study included a total of 246 patients with NAFLD and low probability of fibrosis. 46.3% of subjects were metabolically healthy and 53.7% were metabolically unhealthy. Among metabolically healthy subjects, multivariable-adjusted ORs (CIs) for worsening of NAFLD fibrosis score comparing body mass indexes (BMIs) 23.0-24.9, 25-29.9, and ≥30 with a BMI=18.5-22.9 kg/m² were 1.28 (1.09-1.56), 1.99 (1.49-2.63), and 3.96 (2.89-4.71), respectively. The corresponding ORs (95% CIs) among metabolically unhealthy subjects were 1.39 (1.32-1.64), 2.27 (1.98-2.49), and 4.11 (3.12-4.93), respectively. Moreover, in both healthy and unhealthy individuals, higher percentages of body fat and waist circumference were significantly associated with worsening of NAFLD fibrosis score.

CONCLUSION

Excess body fat contributes to the progression of liver fibrosis regardless of metabolic health status.