Search Results (46)

Objective: This narrative review summarizes current evidence on the associations between ultra-processed food (UPF) consumption, childhood and adolescent obesity, and functional gastrointestinal disorders (FGIDs), and examines the metabolic, inflammatory, microbial, and gut–brain mechanisms underlying these links. Methods: A comprehensive search of PubMed and Scopus identified articles published between January 2010 and September 2025. Eligible studies included human research in individuals aged 0–18 years; adult studies were considered when contributing relevant mechanistic insights. Of 335 records screened, 112 studies met the inclusion criteria and were synthesized narratively according to methodological appropriateness. Results: High UPF intake was consistently associated with increased adiposity, metabolic dysregulation, and greater cardiometabolic risk in youth. Children with overweight or obesity showed a higher prevalence of FGIDs compared with their normal-weight peers. Mechanistic evidence suggests that UPFs, rich in refined carbohydrates, unhealthy fats, and additives, may promote gut microbiota dysbiosis, impair intestinal barrier integrity, alter motility, and induce low-grade inflammation, thereby disrupting gut–brain signaling and contributing to FGID symptoms. Early-life and maternal UPF exposure may further increase susceptibility to metabolic and gastrointestinal disturbances through epigenetic and microbiome-mediated pathways. Conclusions: UPFs emerge as a shared etiological factor for obesity and FGIDs in childhood. This review contributes an integrated synthesis of epidemiological and mechanistic data while highlighting key research gaps, particularly the need for standardized methodologies and pediatric interventional studies to strengthen the evidence base. Full article

Obesity has traditionally been considered a major risk factor for numerous metabolic disorders and diseases. However, a subset of individuals with obesity, classified as having “metabolically healthy obesity” (MHO), display relatively normal metabolic parameters despite excess adiposity. This review critically examines the current knowledge surrounding MHO, including its various definitions, prevalence, clinical characteristics, contributing factors, and long-term outcomes. While MHO carries lower health risks compared to metabolically unhealthy obesity (MUO), evidence consistently demonstrates increased disease risk compared to metabolically healthy normal-weight individuals, particularly for type 2 diabetes, cardiovascular disease, chronic kidney disease, and certain cancers. MHO prevalence ranges from 10 to 30% among individuals with obesity globally, varying by sex, age, BMI, and ethnicity. Multiple factors contribute to the MHO phenotype, including beneficial adipose tissue distribution patterns, enhanced adipocyte function, favorable genetic profiles, and lifestyle factors. Recent single-cell transcriptomic analyses have identified specific cell populations, particularly mesothelial cells, as key drivers of metabolic health in visceral adipose tissue. The discovery of persistent epigenetic memory of obesity provides molecular evidence for why MHO often represents a transient state, with many individuals progressing to MUO over time. Emerging evidence also reveals differential therapeutic responses to GLP-1 receptor agonists between MHO and MUO phenotypes, highlighting the need for precision medicine approaches. The concept of MHO has important clinical implications for risk stratification and personalized treatment approaches. This review synthesizes current evidence while highlighting knowledge gaps and future research directions in this rapidly evolving field. Full article

Obesity is currently one of the major medical problems affecting humans and companion animals, including cats; however, a detailed understanding of the metabolic processes altered in feline obesity remains limited. This study aimed to investigate obesity-related changes in the serum metabolome of three groups of cats, metabolically healthy normal-weight (MHN) cats, metabolically healthy overweight (MHO) cats, and metabolically unhealthy overweight (MUO) cats. Metabolome changes were assessed using LC-MS (untargeted), LC-MS (targeted), and FIA-MS (targeted) methods. Untargeted analysis detected 141 significant annotated features, while targeted approach identified 48 metabolites significantly associated with obesity. Both untargeted and targeted analyses showed lower kynurenine levels in the MUO group compared to the MHN group. Targeted LC-MS analysis identified 11 significant metabolites, whereas the FIA-MS approach detected 37. Four metabolites—glycine, citrulline, and two phosphatidylcholines—were found at lower levels in the MHO group compared to the MHN group. Arginine and proline metabolism, along with methionine metabolism, were significantly altered pathways, while thyroid hormone synthesis was independently altered with the highest enrichment ratio. The obtained results suggest that cats with a healthy phenotype exhibit an intermediate-metabolic-risk profile and provide new insights into the metabolic mechanisms and pathways underlying feline obesity. Full article

Obesity is currently one of the most critical public health problems. Although there is no doubt that obesity is a significant risk factor for developing metabolic disorders, this relationship is not completely straightforward. On the one hand, some patients affected by obesity are metabolically unhealthy, while others are metabolically healthy; on the other hand, metabolic syndrome (MetS) can also occur in people with a normal body weight. A commonly used tool for diagnosing obesity is the body mass index (BMI), but the search for better anthropometric measures is ongoing due to the significant limitations of this measure. Obesity can lead to MetS and cardiovascular diseases (CVDs). Adipose tissue dysfunction is the fundamental mechanism linking obesity and cardiometabolic diseases, which is rooted in the disturbed secretion of adipokines. The visceral adiposity index (VAI) is calculated based on the BMI, waist circumference (WC), blood triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) concentrations. It was proposed in 2010 by Amato et al. as a parameter indicating adipose tissue dysfunction and cardiometabolic risk. According to the research conducted so far, some data confirm a relationship between the VAI value and the risk of developing prediabetes, diabetes, insulin resistance, fatty liver disease, MetS, CVD, and chronic kidney disease. Further research is needed to support the implementation of VAI assessment in routine clinical practice. The purpose of this paper is to present the results of a narrative literature review summarizing current knowledge regarding the VAI and its usefulness in clinical practice for assessing cardiometabolic risk. Full article

Metabolic syndrome (MetS) and its associated cardiometabolic phenotypes significantly contribute to the global burden of cardiovascular disease (CVD), especially in individuals with type 2 diabetes mellitus (T2DM) and prediabetes. This study aimed to explore the association between cardiometabolic phenotypes—specifically, metabolically unhealthy normal weight (MUHNW) and metabolically unhealthy obese (MUHO)—and various cardiovascular risk indices including the triglyceride-glucose (TyG) index and its derivatives, the atherogenic index of plasma (AIP), the cardiometabolic index (CMI), and the cardiac risk ratio (CRR). A total of 300 participants were evaluated (100 with prediabetes and 200 with T2DM). Anthropometric, biochemical, and lifestyle parameters were assessed and stratified across phenotypes. The results demonstrated that cardiovascular risk indices were significantly elevated in the MUHO compared to MUHNW phenotypes, with T2DM patients consistently exhibiting higher risk profiles than their prediabetic counterparts. TyG-derived indices showed strong correlations with BMI, waist–hip ratio (WHR), waist–height ratio (WHtR), and body fat percentage (%BF). The findings suggest that cardiometabolic phenotypes are more strongly associated with elevated cardiometabolic risk indices than body weight alone. These indices may enhance early risk stratification and intervention efforts. The study investigates the association of cardiometabolic phenotypes with surrogate cardiovascular risk indices, not direct CVD outcomes, However, the cross-sectional design and population homogeneity limit the generalizability of the results and preclude causal inference. Full article

Background/Objectives: Individuals with childhood obesity exhibit significant metabolic heterogeneity, necessitating precise biomarkers for risk stratification and assessment. This multi-omics investigation characterizes metabolic and microbial signatures underlying divergent metabolic phenotypes in the context of pediatric obesity. Methods: We analyzed 285 Chinese children (5–7 years) stratified into five groups: wasting (WAS, n = 55), metabolically healthy/unhealthy and normal weight (MHWH, n = 54; MUWH, n = 67), and metabolically healthy/unhealthy obesity (MHO, n = 36; MUO, n = 73). Untargeted metabolomics (Orbitrap ID-X Tribrid™) and 16S rRNA sequencing were integrated with multivariate analyses (OPLS-DA with VIP > 1, FDR < 0.05; Maaslin 2 with TSS normalization and BH correction, FDR < 0.10). Results: Analysis identified 225 differential metabolites and 12 bacterial genera. The proportion of steroids and their derivatives among differential metabolites in the MUO/MHO group was significantly lower than that in the OVOB/NOR and OVOB/WAS groups (2.12% vs. 7.9–14.1%). MUO displayed elevated C17 sphinganine and LysoPC (O-18:0) levels but reduced PI (16:0/14:1) levels. In contrast, OVOB showed upregulated glycerol phospholipids (LPCs and PSs) and downregulated PE species (e.g., PE(16:0/16:0)) as well as gut microbiota dysbiosis characterized by a higher Firmicutes/Bacteroidetes (F/B) ratio (2.07 vs. 1.24 in controls, p = 0.009) and reduced α diversity (Ace index, Chao1 index, and Shannon index values were lower in the OVOB group, Shannon index: 2.96 vs. 3.45, p = 0.03). SCFA-producing genera were negatively correlated with the OVOB group, while positively associated with PE(16:0/16:0). Internal validation showed differential metabolites had potential predictive efficacy for MUO/MHO (AUC = 0.967) and OVOB/NOR (AUC = 0.888). Conclusions: We identified distinct lipid disruptions characterizing obesity subtypes, including steroid/terpene deficits and sphingolipid/ether lipid dysregulation in the MUO/MHO groups as well as phospholipid imbalance (↑LPC/PS↓PE) in the OVOB/NOR groups. The gut microbiota exhibited a profile characterized by low diversity, an increased F/B ratio, and a reduced abundance of SCFA-producing genera. These findings suggest potential biomarkers for childhood obesity stratification, though further validation is warranted. Full article

Background: The etiology of obesity has been associated with genetic and epigenetic factors, hormonal changes, unhealthy lifestyle habits, and infectious agents such as human adenovirus-36 (HAdV-36). Viral infections induce reactive oxygen species, and the imbalance between oxidative stress/antioxidant results in fat accumulation. In the Mexican population, little is known about the frequency of HAdV-36 and its effect on the balance between antioxidants and oxidants, inflammation, and metabolic markers. The purpose of our study was to evaluate the frequency of HAdV-36 seroprevalence and its relation to body mass index (BMI), lipid profiles, glucose levels, inflammation, and levels of antioxidants and oxidative stress in a representative sample. A cross-sectional study was carried out on 112 healthy adults between 18 and 28 years old, who were divided into four groups according to their BMI: underweight (BMI < 18.5); normal weight (BMI 18.5–24.9); overweight (BMI ≥ 25); and obese (BMI ≥ 30). Blood samples were taken to evaluate lipid and glucose profiles, as well as antioxidant and oxidative stress status, using colorimetric techniques. Seropositivity for HAdV-36 and levels of TNF-α, IL-6, and cortisol were determined using an enzyme-linked immunosorbent assay. The HAdV-36 frequency was 15.6% in underweight subjects, 18.7% in the normal-weight subjects, 34.37% in the overweight subjects, and 31.24% in the obese subjects. The subjects who were positive for HAdV-36 seroprevalence had increased levels of IL-6, cortisol, and oxidative stress, independently of BMI. The HAdV-36-positive subjects had reduced LDL-C and HDL-C levels only in the low-weight groups. Glutathione and SOD levels increased in the underweight and normal-weight subjects with positive HAdV-36 seroprevalence, while catalase levels decreased in the normal-weight, overweight, and obese subjects. In conclusion, for the first time, an HAdV-36 seroprevalence in the adult Mexican population is reported which was higher and had a relation with the presence of inflammation, alterations in the lipid profile, and imbalance between oxidative stress and antioxidant status, regardless of BMI. The oxidative stress/antioxidant imbalance could be participating in the stimulation of white adipose tissue deposition. Full article

Background: The relationship between overweight or obesity and depressive symptoms in individuals with or without cardio-metabolic abnormalities is unclear. In a cross-sectional study we examined the odds of experiencing depressive symptoms in overweight or obese older adults with or without metabolic abnormalities. Methods: The participants included 3318 older adults from the Hunter Community Study Cohort with a Body Mass Index (BMI) ≥ 18.5 kgm², stratified by BMI and metabolic health risk. Obesity was defined as BMI ≥ 30 kgm² and metabolically healthy as the absence of metabolic risk factors, according to International Diabetic Federation criteria for metabolic syndromes. Moderate to severe depressive symptoms were defined as a Centre for Epidemiological Studies Depression Scale (CES-D) score ≥ 16. Results: Compared to the metabolically healthy normal weight (MHNW) group, the odds of experiencing moderate/severe depressive symptoms were higher in those classified as a metabolically unhealthy normal weight (MUNW) (odds ratio (OR) = 1.25, 95% Confidence Interval (CI): 0.76–2.06) or metabolically unhealthy obesity (MUO) (OR = 1.48, 95% CI: 1.00–2.19), but not in those classified as metabolically unhealthy overweight (MUOW) (OR = 0.96, 95% CI: 0.63–1.45), metabolically healthy overweight (MHOW) (OR = 0.80, 95% CI: 0.51–1.26), and metabolically healthy obesity (MHO) (OR = 1.03, 95% CI: 0.65–1.64). Compared with MHNW males, the odds of moderate/severe depressive symptoms were increased in all other BMI category–metabolic health groups for males and females. Limitations: Our relatively small sample size and cross-sectional design did not allow us to robustly establish causality. Conclusion: The odds of experiencing moderate/severe depressive symptoms were increased in metabolically unhealthy older adults regardless of normal weight or obesity, with the odds of having moderate/severe depressive symptoms being higher in females than in males. Full article

Background: Diet and lifestyle play important roles in preventing and improving chronic diseases, and evaluating behavioral risk factors in these pathologies allows for efficient management. Methods: A clinical study by screening biochemical parameters and pulmonary function was carried out to evaluate behavioral risk factors in obstructive pulmonary disease associated with metabolic syndrome. Results: Of the total of 70 patients included in the clinical study, 46 were men and 24 were women (χ² = 3.9, p = 0.168). Forty-eight patients presented at least three met risk criteria associated with the metabolic syndrome (19 women and 29 men). Regarding the assessment of lung function, only 7 of the patients presented normal spirometry values (χ² = 75.28, p < 0.001), and the other 63 patients presented with ventilatory dysfunction; most (over 80%) declared that they were smokers or had smoked in the past (χ² = 5.185, p = 0.075). In terms of body weight, 45 of the patients are overweight or obese, most of them declaring that they do not consume enough vegetable products, they consume large amounts of foods of animal origin (meat, milk, eggs) but also super processed foods (food products type of junk food), do not hydrate properly, and are predominantly sedentary people (54 of the patients do no physical activity at all; χ² = 2.12, p = 0.713). Conclusion: From the statistical processing of the data, it is noted that insufficient hydration, low consumption of vegetables, increased consumption of hyper-caloric food products rich in additives, sedentary lifestyle, and smoking are the main disruptive behavioral factors that worsen the health status in lung disease associated with the metabolic syndrome. An important conclusion emerging from the study is that the imbalances that aggravate obstructive lung diseases are generated by unhealthy food and an unbalanced lifestyle. Full article

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. Full article

Obesity and unfavorable metabolic profiles increase the risk for cardiovascular complications in adults. Although it is important to distinguish different metabolic health states at an early stage, there are limited data on the related value of biomarkers in childhood. We aimed to identify biomarkers for the detection of different metabolic health states in children with and without obesity. The serum levels of metabolic regulators (fibroblast growth factor 21 [FGF21], leptin, adiponectin and insulin-like growth factor binding protein 1) and vascular indices (flow-mediated dilation [FMD] and carotid intima-media thickness) were assessed in 78 children. Differences between the metabolically healthy and unhealthy state within children with normal weight (MHN vs. MUN), and within children with overweight/obesity (MHO vs. MUO) were investigated; the discriminatory power of the biomarkers was studied. Both MUN and MUO groups expressed altered lipid and glucose homeostasis compared to their healthy counterparts. The metabolic unhealthy state in children with normal weight was linked to higher FGF21 levels which had good discriminatory ability (area under the curve [AUC]: 0.71, 95% CI: 0.54–0.88; p = 0.044). In overweight/obese children, leptin was increased in the metabolically unhealthy subgroup (AUC: 0.81, 95% CI: 0.68–0.95; p = 0.01). There was a decrease in FMD indicating worse endothelial function in overweight/obese children versus those with normal weight. Distinct states of metabolic health exist in both children with normal weight and overweight/obese children. FGF21 and leptin may help to identify the metabolic unhealthy state in children with normal weight and in overweight/obese children, respectively, early in life. Full article

Obesity is a characteristic disease of the twenty-first century that is affecting an increasing percentage of society. Obesity expresses itself in different phenotypes: normal-weight obesity (NWO), metabolically obese normal-weight (MONW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). A range of pathophysiological mechanisms underlie the occurrence of obesity, including inflammation, oxidative stress, adipokine secretion, and other processes related to the pathophysiology of adipose tissue (AT). Body mass index (BMI) is the key indicator in the diagnosis of obesity; however, in the case of the NWO and MONW phenotypes, the metabolic disturbances are present despite BMI being within the normal range. On the other hand, MHO subjects with elevated BMI values do not present metabolic abnormalities. The MUO phenotype involves both a high BMI value and an abnormal metabolic profile. In this regard, attention has been focused on the variety of molecules produced by AT and their role in the development of obesity. Nesfatin-1, neuregulin 4, myonectin, irisin, and brain-derived neurotrophic factor (BDNF) all seem to have protective effects against obesity. The primary mechanism underlying the action of nesfatin-1 involves an increase in insulin sensitivity and reduced food intake. Neuregulin 4 sup-presses lipogenesis, decreases lipid accumulation, and reduces chronic low-grade inflammation. Myonectin lowers the amount of fatty acids in the bloodstream by increasing their absorption in the liver and AT. Irisin stimulates the browning of white adipose tissue (WAT) and consequently in-creases energy expenditure, additionally regulating glucose metabolism. Another molecule, BDNF, has anorexigenic effects. Decorin protects against the development of hyperglycemia, but may also contribute to proinflammatory processes. Similar effects are shown in the case of visfatin and chemerin, which may predispose to obesity. Visfatin increases adipogenesis, causes cholesterol accumulation in macrophages, and contributes to the development of glucose intolerance. Chemerin induces angiogenesis, which promotes the expansion of AT. This review aims to discuss the role of adipokines and myokines in the pathogenesis of the different obesity phenotypes. Full article

Environmental factors play a role in increasing or decreasing the risk of metabolic syndrome (MetS) in adolescents. We analyzed the impact of physical activity (PA), dietary habits, and mental and socioeconomic status on MetS prevalence in 2143 (boys: 1113, girls: 1030, age: 13–18 years) Korean middle- and high-school students. Metabolically healthy obesity and metabolically unhealthy normal weight were also evaluated. MetS occurred in 215 participants (10.0%), and boys had a higher MetS rate than girls. There was no significant difference in alcohol consumption and smoking experience between individuals with and those without MetS. The odds ratio (OR) for high-school students was 1.33 (95%CI, 1.001–1.789, p = 0.043) times that of middle-school students. Depression, low aerobic PA, and high sedentary time increased the ORs to 1.64 (95%CI, 1.059–2.539, p = 0.020), 1.52 (95%CI, 1.092–2.203, p = 0.003), and 1.86 (95%CI, 1.342–2.587, p < 0.001), respectively. Higher energy intake and low weekly breakfast consumption frequency yielded ORs of 1.46 (95%CI, 1.046–2.555, p = 0.025) and 1.70 (95%CI, 1.244–2.339, p = 0.011), respectively. Strength training, stress, suicidal ideation, dining out frequency, and household income did not impact MetS prevalence. Despite obesity, MetS decreased by 29.7% with high aerobic PA and 37.9% with high weekly breakfast consumption frequency. In conclusion, MetS risk was higher for men, individuals with depression, and high-school students. Low aerobic activity, high calorie intake, and low weekly breakfast consumption frequency increased MetS risk. Despite obesity, high aerobic activity, low sedentary time, and breakfast consumption was associated with lower MetS risk. Full article

Background: Obesity and hidradenitis suppurativa (HS) are related through meta-inflammation and are both associated with increased cardiometabolic risk. Notwithstanding, cardiometabolic pathology is not uniform in obesity and a subset of individuals with excess adiposity exhibit a healthy metabolic profile. Whilst the incidence of cardiometabolic endpoints and transitions across different adiposity-related body composition phenotypes within several populations and across different ethnicities have been investigated, data regarding metabolic health (MetH) and body composition phenotypes in individuals with HS are lacking. The objective of this study was to evaluate the relationship between different body composition phenotypes in individuals with HS. Methods: This was a cross-sectional study of 632 individuals with and without HS from a population with a high prevalence of both obesity and HS. A total of four body composition phenotypes were generated based on BMI and metabolic status (defined using either the metabolic syndrome definition or the homeostasis model of insulin resistance (HOMA-IR)): metabolically healthy overweight/obese (MHOWOB), metabolically unhealthy overweight/obese (MUOWOB), metabolically healthy normal weight (MHNW), and metabolically unhealthy normal weight (MUNW). Results: Generally, subjects with HS exhibited a worse metabolic profile with higher levels of indices of central adiposity measures (including Visceral Adiposity Index and waist circumference), systolic blood pressure and markers of insulin resistance, as well as a higher prevalence of the metabolic syndrome. Moreover, when sub-stratified into the different body composition phenotypes, individuals with HS typically also demonstrated adverse metabolic characteristics relative to controls matched for both adiposity and metabolic health, particularly in the normal weight category and despite being classified as metabolically healthy. Being metabolically unhealthy in addition to being overweight/obese increases an individual’s risk of HS. Conclusions: Metabolic risk-assessment should be prioritized in the clinical management of individuals with HS even in those who are lean. Patients attending HS clinics provide a valuable opportunity for targeted cardiovascular risk reduction with respect to the management of both obesity and metabolic health. Full article

Obesity has been associated with increased intraocular pressure (IOP), but the results are inconsistent. Recently, a subgroup of obese individuals with good metabolic profiles were suggested to have better clinical outcomes than normal-weight individuals with metabolic diseases. The relationships between IOP and different combinations of obesity and metabolic health status have not been investigated. Therefore, we investigated the IOP among groups with different combinations of obesity status and metabolic health status. We examined 20,385 adults aged 19 to 85 years at the Health Promotion Center of Seoul St. Mary’s Hospital between May 2015 and April 2016. Individuals were categorized into four groups according to obesity (body mass index (BMI) ≥ 25 kg/m²) and metabolic health status (defined based on prior medical history or abdominal obesity, dyslipidemia, low high-density lipoprotein cholesterol, high blood pressure, or high fasting blood glucose levels upon medical examination). ANOVA and ANCOVA were performed to compare the IOP among the subgroups. The IOP of the metabolically unhealthy obese group (14.38 ± 0.06 mmHg) was the highest, followed by that of the metabolically unhealthy normal-weight group (MUNW, 14.22 ± 0.08 mmHg), then, the metabolically healthy groups (p < 0.001; 13.50 ± 0.05 mmHg and 13.06 ± 0.03 mmHg in the metabolically healthy obese (MHO) and metabolically healthy normal-weight groups, respectively). Subjects who were metabolically unhealthy showed higher IOP compared to their counterparts who were metabolically healthy at all BMI levels, and there was a linear increase in IOP as the number of metabolic disease components increased, but no difference between normal-weight vs. obese individuals. While obesity, metabolic health status, and each component of metabolic disease were associated with higher IOP, those who were MUNW showed higher IOP than those who were MHO, which indicates that metabolic status has a greater impact than obesity on IOP. Full article