Healthy Normal Weight Individuals Research Articles

Abstract TMP100: Acute Ischemic Stroke in Young Adults: A Comparative Analysis of Outcomes and Mortality in Metabolically Healthy Obese vs. Normal Weight Individuals, 2016-2019 Cohort

Introduction: Rising obesity rates and the increasing prevalence of stroke in the metabolically healthy obese (MHO) necessitate examining its association in younger (18-44 year) populations. Analyzing acute ischemic stroke (AIS) trends and outcomes in MHO vs. metabolically healthy normal weight (MH-NW). Methods: Data from the National Inpatient Sample (2016-2019) was analyzed to identify young MHO and MH-NW AIS patients using ICD-10 codes. Demographics, trends, and outcomes were compared using multivariable statistical approaches. Results: Of 26,949,310 young metabolically healthy individuals studied between 2016 and 2019, 47,795 had AIS, 4,985 were MHO, and 42,810 were MH-NW. The median AIS patient age was 35. The MHO cohort was primarily female, white, in the lowest income quartile, with private insurance. Most were hospitalized in southern US urban teaching hospitals. Notably, the MHO cohort had higher rates of specific comorbidities like depression, chronic pulmonary disease, and obstructive sleep apnea but lower rates of drug abuse and peripheral vascular disease. The in-hospital mortality rate was significantly lower in MHO patients (6.0% vs. 8.6%). Hospitalization length and cost did not significantly differ between groups. From 2016 to 2019, AIS incidence rose slightly, significant only for the MH-NW cohort. Adjusted multivariable odds ratios revealed no significant difference in AIS occurrence between MHO and MH-NW overall (aOR: 1.02, p=0.701), in males (aOR: 0.88, p=0.161) or females (aOR: 1.06, p=0.363). However, MHO-associated AIS had lower odds of in-hospital mortality than MH-NW (aOR: 0.60, p=0.021). Conclusion: AIS incidence was consistent across young metabolically healthy groups regardless of obesity status. However, we noted a paradoxical 40% reduction in in-hospital mortality in the MHO cohort. This underscores the complex MHO-stroke relationship in young adults, signaling a need for in-depth research and tailored interventions.

Metabolically Healthy Overweight and Obesity, Transition to Metabolically Unhealthy Status and Cognitive Function: Results from the Framingham Offspring Study.

To evaluate the association between metabolically healthy overweight/obesity (MHO) status and longitudinal cognitive function while also considering the stability of the condition. In total, 2892 participants (mean age 60.7 (9.4) years) from Framingham Offspring Study completed health assessments every four years since 1971. Neuropsychological testing was repeated every four years starting from 1999 (Exam 7) to 2014 (Exam 9) (mean follow-up: 12.9 (3.5) years). Standardized neuropsychological tests were constructed into three factor scores (general cognitive performance, memory, processing speed/executive function). Healthy metabolic status was defined as the absence of all NCEP ATP III (2005) criteria (excluding waist circumference). MHO participants who scored positively for one or more of NCEP ATPIII parameters in the follow-up period were defined as unresilient MHO. No significant difference on the change in cognitive function over time was observed between MHO and metabolically healthy normal weight (MHN) individuals (all p > 0.05). However, a lower processing speed/executive functioning scale score was observed in unresilient MHO participants compared to resilient MHO participants (β = -0.76; 95% CI = -1.44, -0.08; p = 0.030). Retaining a healthy metabolic status over time represents a more important discriminant in shaping cognitive function compared to body weight alone.

Risk of Heart Failure between Different Metabolic States of Health and Weight: A Meta-Analysis of Cohort Studies.

We conducted a systematic review of cohort studies comparing the risk of heart failure in people with differing metabolic health and obesity statuses. We searched three electronic databases (PubMed, Web of Science, Scopus), where the studies of the relationships of metabolic health and obesity statuses with heart failure were included. Fixed-effects or random-effects models were used to estimate the summary relative risks [RRs]. Ten cohort studies were selected. Compared with individuals with normal metabolic health and body mass, the pooled RRs (95% confidence intervals) for heart failure were 1.23 (1.17, 1.29) for metabolic healthy overweight individuals, 1.52 (1.40, 1.64) for metabolic healthy individuals with obesity, 1.56 (1.30, 1.87) for metabolically unhealthy normal-weight individuals, 1.75 (1.55, 1.98) for metabolically unhealthy overweight individuals, and 2.28 (1.96, 2.66) for metabolic unhealthy individuals with obesity. A sensitivity analysis suggested that no single study had a substantial effect on the results. The Egger's and Begg's tests showed no evidence of publication bias. People with overweight or obesity were at a higher risk of heart failure, even if metabolically healthy. In addition, compared with metabolically healthy normal-weight individuals; metabolically unhealthy normal-weight individuals, and those with overweight or and obesity, were at higher risk of heart failure.

Brain Responses to Food Choices and Decisions Depend on Individual Hedonic Profiles and Eating Habits in Healthy Young Women.

The way different food consumption habits in healthy normal-weight individuals can shape their emotional and cognitive relationship with food and further disease susceptibility has been poorly investigated. Documenting the individual consumption of Western-type foods (i.e., high-calorie, sweet, fatty, and/or salty) in relation to psychological traits and brain responses to food-related situations can shed light on the early neurocognitive susceptibility to further diseases and disorders. We aimed to explore the relationship between eating habits, psychological components of eating, and brain responses as measured by blood oxygen level-dependent functional magnetic resonance imaging (fMRI) during a cognitive food choice task and using functional connectivity (FC) during resting-state fMRI (rsfMRI) in a population of 50 healthy normal-weight young women. A Food Consumption Frequency Questionnaire (FCFQ) was used to classify them on the basis of their eating habits and preferences by principal component analysis (PCA). Based on the PCA, we defined two eating habit profiles, namely, prudent-type consumers (PTc, N = 25) and Western-type consumers (WTc, N = 25), i.e., low and high consumers of western diet (WD) foods, respectively. The first two PCA dimensions, PCA1 and PCA2, were associated with different psychological components of eating and brain responses in regions involved in reward and motivation (striatum), hedonic evaluation (orbitofrontal cortex, OFC), decision conflict (anterior cingulate cortex, ACC), and cognitive control of eating (prefrontal cortex). PCA1 was inversely correlated with the FC between the right nucleus accumbens and the left lateral OFC, while PCA2 was inversely correlated with the FC between the right insula and the ACC. Our results suggest that, among a healthy population, distinct eating profiles can be detected, with specific correlates in the psychological components of eating behavior, which are also related to a modulation in the reward and motivation system during food choices. We could detect different patterns in brain functioning at rest, with reduced connectivity between the reward system and the frontal brain region in Western-type food consumers, which might be considered as an initial change toward ongoing modified cortico-striatal control.

Metabolically healthy obesity: Is it really healthy for type 2 diabetes mellitus?

Metabolically healthy obese (MHO) individuals are reported to have a lower risk of developing cardiovascular diseases in comparison with individuals with metabolic syndrome. However, the association between MHO and type 2 diabetes (T2DM) is still controversial. Some studies indicated that MHO is a favorable phenotype for T2DM, but more studies showed that MHO individuals have an increased risk of developing T2DM compared with metabolically healthy normal-weight individuals, especially among those who would acquire metabolically unhealthy obesity. This has been supported by finding insulin resistance and low-grade inflammatory responses in MHO individuals with a tendency for impaired beta-cell dysfunction. Studies also showed that liver fat accumulation increased the risk of incidence of T2DM in MHO. Here, we reviewed current literature on the relationship between MHO and T2DM, discussed the determinants for the development of diabetes in MHO, and summarized the measures for the prevention of T2DM in MHO.

Metabolic phenotypes and risk of colorectal cancer: a systematic review and meta-analysis of cohort studies

BackgroundThe association of obesity with colorectal cancer (CRC) may vary depending on metabolic status.ObjectiveThis meta-analysis aimed to investigate the combined impacts of obesity and metabolic status on CRC risk.MethodsThe Scopus, PubMed, and web of sciences databases were systematically searched up to Jun 2021 to find all eligible publications examining CRC risk in individuals with metabolically unhealthy normal-weight (MUHNW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUHO) phenotypes.ResultsA total of 7 cohort studies with a total of 759,066 participants were included in this meta-analysis. Compared with healthy normal-weight people, MUHNW, MHO, and MUHO individuals indicated an increased risk for CRC with a pooled odds ratio of 1.19 (95% CI = 1.09–1.31) in MUHNW, 1.14 (95% CI = 1.06–1.22) in MHO, and 1.24 (95% CI = 1.19–1.29) in MUHO subjects. When analyses were stratified based on gender, associations remained significant for males. However, the elevated risk of CRC associated with MHO and MUHO was not significant in female participants.ConclusionsThe individuals with metabolic abnormality, although at a normal weight, have an increased risk for CRC. Moreover, obesity is associated with CRC irrespective of metabolic status.

Metabolically healthy obesity, transition to unhealthy phenotypes, and type 2 diabetes in 0.5 million Chinese adults: the China Kadoorie Biobank.

ObjectivesTo prospectively assess the association of metabolic health status and its transition with incident diabetes risk across BMI categories.DesignCohort study based on the China Kadoorie Biobank (CKB).MethodsThe CKB study enrolled 512 715 adults aged 30–79 years from ten diverse areas in China during 2004–2008. After exclusion, 432 763 participants were cross-classified by BMI categories and the metabolic status was followed up for incident diabetes disease. The changes in BMI and metabolic health status were defined from baseline to the second resurvey.ResultsType 2 diabetes risk is higher for metabolically healthy obese (MHO) subjects than metabolically healthy normal weight (MHN) individuals (HR: 3.97, 95% CI: 3.64–3.66), and it is highest for those affected by metabolically unhealthy obese (MUO) (HR: 6.47, 95% CI: 6.17–6.79). About 15.26% of participants with MHN converted to metabolically healthy overweight or obesity (MHOO), whereas 48.40% of MHOO remained unconverted throughout the follow-up. In obese or overweight people, the conversion from metabolically healthy to unhealthy might increase the chances of developing diabetes as compared to those with a stable metabolic healthy state (HR: 3.70, 95% CI: 2.99–4.59), while those with persistent metabolic disorders are most likely to have diabetes (HR: 8.32, 95% CI: 7.08–9.78).ConclusionsMetabolic healthy is a transient state, and individuals converted from metabolically healthy status to unhealthy phenotypes across all BMI categories might raise the risk of diabetes.

Do Metabolically Healthy People with Obesity Have a Lower Health-Related Quality of Life? A Prospective Cohort Study in Taiwan.

The association between metabolically healthy obesity (MHO) and health-related quality of life (HRQOL) has not been thoroughly evaluated. This study enrolled 906 adult participants aged 35–55 years between 2009 and 2010 in Northern Taiwan; 427 participants were followed up after eight years. Normal weight, overweight, and obesity were evaluated via body mass index. Metabolic health was defined as the absence of cardiometabolic diseases and having ≤1 metabolic risk factor. HRQOL was evaluated using the 36-Item Short Form Health Survey (SF-36), Taiwan version. Generalized linear mixed-effects models were used to analyze the repeated, measured data with adjustment for important covariates. Compared with metabolically healthy normal weight individuals, participants with metabolically unhealthy normal weight and obesity had a significantly poorer physical component summary score (β (95% CI) = −2.17 (−3.38–−0.97) and −2.29 (−3.70–−0.87), respectively). There were no significant differences in physical and mental component summary scores among participants with metabolically healthy normal weight, overweight, and obesity. This study showed that metabolically healthy individuals with obesity and normal weight had similar HRQOL in physical and mental component summary scores. Maintaining metabolic health is an ongoing goal for people with obesity.

Transitions in Metabolic Health and Associations With Arterial Stiffness Progression Across Body Mass Index Categories.

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Spinal segment ranges of motion, movement coordination, and three-dimensional kinematics during occupational activities in normal-weight and obese individuals

Measurements of spinal segment ranges of motion (RoMs), movement coordination, and three-dimensional kinematics during occupational activities have implications in occupational/clinical biomechanics. Due to the large amount of adipose tissues, obese individuals may have different RoMs, lumbopelvic coordination, and kinematics than normal-weight ones. We aimed to measure/compare trunk, lumbar, and pelvis primary RoMs in all anatomical planes/directions, lumbopelvic ratios (lumbar to pelvis rotations at different trunk angles) in all anatomical planes/directions and three-dimensional spine kinematics during twelve symmetric/asymmetric statics load-handling activities in healthy normal-weight and obese individuals. Kinematics/motion data were collected from nine healthy young male normal-weight and nine age/height/sex matched obese individuals via a ten-camera Vicon motion capture system. Obese individuals had significantly smaller (p < 0.05) lumbar flexion (~9° in average) and larger pelvis right lateral bending (~5°) RoMs as well as smaller lumbopelvic ratios (~37%) in lateral bending and axial rotation movements as compared to normal-weight individuals. Moreover, the two groups had generally non-significant different segmental orientations (<20° and in most cases < 10°) in load-handling tasks that depended on the magnitude of load asymmetry angle (p < 0.05). Differences were larger for tasks performed near the floor, away from body, and at larger load asymmetry angles. Biomechanical models simulating pure lateral bending, axial rotation, or tasks involving large load asymmetry may therefore need subject-specific, rather than population-based, motion analysis due to the effects from body weight. In clinical applications, it should be noted that healthy obese individuals may have different RoMs and lumbopelvic rhythms than healthy normal-weight individuals in some anatomical planes/directions.

Characteristics of the colonic microbiome in patients with different obesity phenotypes (the original article)

Introduction. The concept of heterogeneity in obesity depending on the risk of developing cardiometabolic complications has garnered attention in recent decades, since not everyone with obesity goes on to develop metabolic dysfunction.The aim of the work is to study specific characteristics of colonic microbial communities in patients with different obesity phenotypes and in healthy individuals by employing metagenomics methods.Materials and methods. A total of 265 individuals (44 men and 221 women; mean age 47.1 ± 4.8 years) were enrolled in the study. They were further divided into clinical groups: Healthy normal-weight individuals (n = 129); patients with obesity (n = 136), including metabolically healthy obesity (n = 40) and metabolically unhealthy obesity (n = 55). Quantitative and qualitative assessment of the intestinal microbiome was based on metagenomic analysis. Fecal samples were used to isolate DNA and perform sequencing of the variable v3-v4 region of the 16S rRNA gene.Results. The study revealed statistically significant (p 0.05) differences between quantitative and qualitative variables in studied phylotypes of colonic microorganisms in healthy individuals without obesity and in patients with different obesity phenotypes.Discussion. Patients with obesity had higher levels of Bacteroidetes, Proteobacteria and lower levels of Actinobacteria, Firmicutes, TM7 (Saccharibacteria), Fusobacteria, and more frequently detected phyla Tenericutes, Planctomycetes and Lentisphaerae compared to healthy individuals. Metabolically healthy obese patients had more rarely detected phylum Lentisphaerae in their colonic microbiome, increased numbers of Firmicutes and reduced numbers of Bacteroidetes compared to metabolically unhealthy obese patients.Conclusion. The findings demonstrate alterations in the colonic microbiome in patients with different obesity phenotypes.

Metabolically Healthy/Unhealthy Overweight/Obesity Associations With Incident Heart Failure in Postmenopausal Women: The Women's Health Initiative.

Obesity is associated with an increased risk of heart failure (HF); however, how metabolic weight groups relate to HF risk, especially in postmenopausal women, has not been demonstrated. We included 19 412 postmenopausal women ages 50 to 79 without cardiovascular disease from the Women's Health Initiative. Normal weight was defined as a body mass index ≥18.5 and <25 kg/m2 and waist circumference <88 cm and overweight/obesity as a body mass index ≥25 kg/m2 or waist circumference ≥88 cm. Metabolically healthy was based on <2 and unhealthy ≥2 cardiometabolic traits: triglycerides ≥150 mg/dL, systolic blood pressure ≥130 mm Hg or diastolic blood pressure ≥85 mm Hg or blood pressure medication, fasting glucose ≥100 mg/dL or diabetes medication, and HDL-C (high-density lipoprotein cholesterol) <50 mg/dL. Risk factor-adjusted Cox regression examined the hazard ratios (HRs) for incident hospitalized HF among metabolically healthy normal weight (reference), metabolically unhealthy normal weight, metabolically healthy overweight/obese, and metabolically unhealthy overweight/obese. Among our sample, 455 (2.34%) participants experienced HF hospitalizations over a mean follow-up time of 11.3±1.1 years. Compared with metabolically healthy normal weight individuals, HF risk was greater in metabolically unhealthy normal weight (HR, 1.66 [95% CI, 1.01-2.72], P=0.045) and metabolically unhealthy overweight/obese individuals (HR, 1.95 [95% CI, 1.35-2.80], P=0.0004), but not metabolically healthy overweight/obese individuals (HR, 1.15 [95% CI, 0.78-1.71], P=0.48). Subdividing the overweight/obese into separate groups showed HRs for metabolically unhealthy obese of 2.62 (95% CI, 1.80-3.83; P<0.0001) and metabolically healthy obese of 1.52 (95% CI, 0.98-2.35; P=0.06). Metabolically unhealthy overweight/obese and metabolically unhealthy normal weight are associated with an increased risk of HF in postmenopausal women.

Metabolically healthy obesity and risk of stroke: a meta-analysis of prospective cohort studies.

BackgroundMetabolic healthy obesity (MHO) is a unique subgroup of overweight and obese individuals with normal metabolic characteristics. Its association with the risk of stroke remains unclear. We aimed to examine the risk of stroke in MHO individuals and the further associations between stroke and metabolic abnormalities under different bodyweight conditions.MethodsWe systematically searched PubMed, Embase and Cochrane Library from December 1946 to January 2019, and only included prospective cohort studies. Random effects models were used to evaluate the pooled risk ratios (RR) and 95% confidence intervals (95% CI) of incident stroke.ResultsA total of eight studies comprising 4,256,888 participants were included in the meta-analysis. MHO individuals had an increased risk of stroke compared with metabolically healthy normal weight (MH-NW) individuals (RR =1.17, 95% CI: 1.11–1.23). However, the stroke risk of metabolically healthy overweight individuals was the same (RR =1.02, 95% CI: 0.84–1.23). All groups with unhealthy metabolism had a similarly elevated risk: normal weight (RR =1.83, 95% CI: 1.57–2.14), overweight (RR =1.93, 95% CI: 1.44–2.58), and obesity (RR =2.00, 95% CI: 1.40–2.87).ConclusionsThe meta-analysis confirms a positive association between MHO phenotype and the risk of stroke. Individuals with metabolic abnormalities under different bodyweight conditions are at elevated risk.

Dysregulation of endocannabinoid concentrations in human subcutaneous adipose tissue in obesity and modulation by omega-3 polyunsaturated fatty acids.

Obesity is believed to be associated with a dysregulated endocannabinoid system which may reflect enhanced inflammation. However, reports of this in human white adipose tissue (WAT) are limited and inconclusive. Marine long-chain omega-3 polyunsaturated fatty acids (LC n-3 PUFAs) have anti-inflammatory actions and therefore may improve obesity-associated adipose tissue inflammation. Therefore, fatty acid (FA) concentrations, endocannabinoid concentrations, and gene expression were assessed in subcutaneous WAT (scWAT) biopsies from healthy normal weight individuals (BMI 18.5-25 kg/m2) and individuals living with metabolically healthy obesity (BMI 30-40 kg/m2) prior to and following a 12-week intervention with 3 g fish oil/day (1.1 g eicosapentaenoic acid (EPA) + 0.8 g DHA) or 3 g corn oil/day (placebo). WAT from individuals living with metabolically healthy obesity had higher n-6 PUFAs and EPA, higher concentrations of two endocannabinoids (anandamide (AEA) and eicosapentaenoyl ethanolamide (EPEA)), higher expression of phospholipase A2 Group IID (PLA2G2D) and phospholipase A2 Group IVA (PLA2G4A), and lower expression of CNR1. In response to fish oil intervention, WAT EPA increased to a similar extent in both BMI groups, and WAT DHA increased by a greater extent in normal weight individuals. WAT EPEA and docosahexaenoyl ethanolamide (DHEA) increased in normal weight individuals only and WAT 2-arachidonyl glycerol (2-AG) decreased in individuals living with metabolically healthy obesity only. Altered WAT fatty acid, endocannabinoid, and gene expression profiles in metabolically healthy obesity at baseline may be linked. WAT incorporates n-3 PUFAs when their intake is increased which affects the endocannabinoid system; however, effects appear greater in normal weight individuals than in those living with metabolically healthy obesity.

Daily Consumption of Stevia Drops Effects on Glycemia, Body Weight and Energy Intake: Results from a 12-Week, Open-Label, Randomized Controlled Trial in Healthy Adults

Abstract Objectives Stevia is a non-nutritive sweetener providing sweet taste with zero calories that could constitute an effective strategy toward sugar reduction. This study tested the effects of daily consumption of stevia drops on glycemia, body weight (BW) and energy intake in healthy normal weight adults, non-habitual consumers of non-nutritive sweeteners. Methods Twenty eight healthy participants were randomly assigned to the stevia group (n = 14, mean age: 25 ± 5.5 y, mean body mass index: 22 ± 1.8 kg/m2) and were required to consume 5 drops of a commercially available stevia extract twice daily along with their habitual drinks, or to the control group (n = 14, 25 ± 4.2 y, 21 ± 1.5 kg/m2) and were instructed not to change anything in their diet for 12 weeks. Both groups were encouraged to maintain their usual diet and physical activity habits. At baseline and week 12, glucose response to an oral glucose tolerance test (OGTT) was measured; BW and energy intake were assessed at baseline, week 6 and week 12. Results There was no significant difference in glucose response to the OGTT over the 12 weeks in any study group. However, there was a significant main effect of participant group on BW change over the 12 weeks (F(1, 26) = 5.56, P = 0.026), showing that stevia consumption prevented weight gain (ΔWeight at week 12 = −0.22 ± 0.32 kg for stevia, +0.89 ± 0.39 kg for the control group). Energy intake was significantly decreased between baseline and week 12 in the stevia group (ΔEnergy at week 12 = −344 ± 80.6 kcal, P = 0.003), however no change in energy intake was found in the control group (ΔEnergy = +13.6 ± 125 kcal, P = 0.973). Conclusions These results suggest that daily consumption of stevia in real-life doses does not affect glycemia in healthy normal-weight individuals, but could aid toward weight maintenance and moderation of energy intake. More research is warranted to explore these promising findings further in individuals with overweight/obesity and/or individuals with impaired glucose tolerance (i.e., pre-diabetes/diabetes). Clinicaltrial.gov identifier: NCT03993418. Funding Sources This project has received a N8 AgriFood Pump Priming Award. Ms Stamataki has a BBSRC DTP Case Studentship.

Fat-to-muscle ratio as a predictor of insulin resistance and metabolic syndrome in Korean adults.

BackgroundThe present study evaluated the associations of the fat‐to‐muscle ratio (FMR) with metabolic syndrome (MetS) and insulin resistance (IR) in Korean adults using nationally representative survey data.MethodsA two‐stage stratified sampling method was reflected in a cross‐sectional study involving a total of 13 032 participants aged ≥ 19 years who participated in the fourth and fifth Korea National Health and Nutrition Examination Surveys. The homeostasis model assessment for IR (HOMA‐IR) was used to evaluate IR and was calculated as follows: [fasting plasma glucose level (mg/dL) × fasting plasma insulin level (uIU/mL)]/405. MetS was defined using the 2006 International Diabetes Federation criteria, and FMR was measured using whole‐body dual‐energy X‐ray absorptiometry and calculated as follows: total fat mass (kg) divided by total lean mass (kg). In addition, the optimal FMR cut‐off values for detecting MetS and the odds ratios (ORs) for MetS risk were determined according to the FMR quartile and sex.ResultsAmong all participants, the proportion of women was 58.4%, and the mean age was 44.22 ± 0.26 years. The FMR significantly differed between men and women (0.30 ± 0.002 vs. 0.53 ± 0.003, respectively, P < 0.001), and the prevalence of MetS and IR gradually increased as FMR increased (P for trend: <0.001). The optimal FMR cut‐off value for detecting MetS was higher in women than in men (0.555 vs. 0.336, respectively). The negative predictive value was the highest in normal‐weight participants (0.9992 in women and 0.9986 in men), while the positive predictive value was the highest in obese participants (0.5994 in women and 0.5428 in men). Based on the derived cut‐off FMR, a high FMR was associated with poor outcomes in terms of cardiometabolic risk markers (P < 0.001). The multivariable‐adjusted ORs for MetS, abdominal obesity, and IR (HOMA‐IR ≥ 3) were 5.35 [95% confidence interval (CI): 4.39–6.52], 7.67 (95% CI: 6.33–9.30), and 3.25 (95% CI: 2.70–3.92), respectively, in men and 5.59 (95% CI: 4.66–6.72), 7.48 (95% CI: 6.35–8.82), and 2.55 (95% CI: 2.17–3.00), respectively, in women.ConclusionsIn the present study, a high FMR was significantly associated with the prevalence of MetS and IR. The present findings also showed that FMR can be a novel indicator for detecting the absence or presence of MetS, particularly in metabolically healthy normal‐weight individuals and metabolically obese obese‐weight individuals.

Metabolically healthy obesity increased diabetes incidence in a middle-aged and elderly Chinese population.

We examined the association between metabolically healthy obese (MHO) and diabetes incidence in a middle-aged and elderly population and whether the association differed by the presence of nonalcoholic fatty liver disease (NAFLD). We examined 17 801 participants without diabetes at study entry (7980 males and 9821 females with a mean age of 63.2 years) derived from the Dongfeng-Tongji cohort study (median follow-up: 4.6 years). Participants were divided into six groups based on BMI (normal weight, overweight, or obese) and metabolic health (healthy/unhealthy) defined by the Adult Treatment Panel III criteria. The MHO was defined as BMI greater than 28.0 kg/m2 with 0 or 1 of four metabolic abnormalities (elevated blood pressure, triglyceridaemia, hyperglycaemia, low HDL cholesterol). The hazard ratio (HR) and 95% confidence interval (CI) for incident diabetes were derived from the Cox proportional hazard regression model. During 79 843 person-years of follow-up, 1453 individuals developed diabetes. Compared with metabolically healthy normal weight (MH-NW) individuals, the multivariable-adjusted HRs (95% CI) were 1.74 (1.16-2.59) for MHO and 2.15 (1.65-2.81) for metabolically unhealthy obese subjects after adjusting for age, sex, smoking, alcohol drinking, physical activity, fruit and vegetable consumption, family history of diabetes, fasting glucose, waist circumference, and NAFLD. Among those without NAFLD, MHO individuals showed higher incidence of diabetes (multivariate-adjusted HR = 2.71, 95% CI: 1.47-5.00) than MH-NW individuals. The MHO phenotype was associated with increased incidence of diabetes in a middle-aged and elderly population, and the association did not differ by the presence or absence of NAFLD.

Metabolic phenotypes of obese, overweight, and normal weight individuals and risk of chronic kidney disease: a systematic review and meta-analysis.

Chronic kidney disease (CKD) risk is inconsistent in the normal-weight, overweight, and obese individuals due to the heterogeneity of metabolic status. This meta-analysis aimed to examine the combined effects of body mass index (BMI) and metabolic status on CKD risk. The MEDLINE, EMBASE, and Web of Knowledge databases were systematically searched up to March 2019 to identify all eligible studies investigating the CKD risk (defined as GFR < 60 mL/min per 1.73 m2 and/or microalbuminuria or proteinuria) associated with the body size phenotypes which are known as metabolically unhealthy normal-weight (MUNW), metabolically healthy overweight (MHOW), metabolically unhealthy overweight, metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO). The classification of subjects in included studies as metabolically unhealthy was based on the presence of three components of metabolic syndrome. BMI categorization was based on the criteria of included studies. The risk estimates and 95% confidence intervals (CIs) were extracted and pooled using random effects analysis. A total of 9 prospective cohort studies with 128773 participants and 4797 incident cases were included in the meta-analysis. Compared with healthy normal-weight individuals as reference, MUNW and MHO subjects showed an increased risk for CKD events with a pooled RR of 1.58 (95% CI = 1.28-1.96) in MUNW and 1.55 (95% CI = 1.34-1.79) in MHO persons. Also, MHOW was at increased risk for CKD (RR = 1.34, 95% CI = 1.20-1.51). MUHO individuals were at the highest risk for the development of CKD (RR = 2.13, 95% CI = 1.66-2.72). Individuals with metabolic abnormality, although at normal-weight, have an increased risk for CKD. Healthy overweight and obese individuals had higher risk; refuting the notion that metabolically healthy overweight and obese phenotypes are benign conditions.

Effects of Mood Induction Using Movie Watching on Food Intake and Hormone Levels

There is a complex connection between emotional states and food intake. The purpose of this study was to investigate the impact of short-term emotion induction on food intake and ghrelin, cortisol, and insulin levels in healthy normal-weight individuals without eating disorders. Eighty-nine participants were divided into 2 groups (drama and comedy movies). After 50 minutes of watching, the movie was stopped and blood samples were collected, and then participants were offered a snack to eat. The visual analog scale showed that the movie watching had significant effects on mood induction. However, there was no significant relationship between the kind of movie the participants had watched and their choice of food, its calorie content, or the amount of food (eg, grams) that was consumed. This parallel-design study found that a 50-minute exposure to either a dramatic or a comedy movie affected ghrelin, cortisol, and insulin levels. However, these hormonal changes were not associated with intake of food from a buffet during the last minutes of viewing.

Metabolically healthy obese phenotype and risk of cardiovascular disease: Results from the China Health and Retirement Longitudinal Study

BackgroundEpidemiologic evidence on metabolically healthy obese (MHO) phenotype and cardiovascular diseases (CVD) risk remains controversial. AimsWe aim to examine the relationship between MHO and risk of CVD among the Chinese population. MethodsThe China Health and Retirement Longitudinal Study is a prospective cohort study of 7849 participants aged ≥45 years without CVD at baseline. Metabolic health status was assessed based on blood pressure, triglycerides, high-density lipoprotein cholesterol, glycated hemoglobin, fasting glucose, and C-reactive protein. A cutoff point of body mass index of 24.0 kg/m2 was used to define over-weight/obesity (≥24.0 kg/m2) or normal weight (<24.0 kg/m2). CVD was based on self-reported doctor’s diagnosis of heart problems and stroke. Incidence rate ratio (IRR) with 95% confidence interval (CI) was deduced from modified Poisson regression. ResultsDuring a mean 3.6 years of follow-up, 880 incident CVD events were recorded. 789 (10.05%) were identified MHO among 3321 (42.3%) obese individuals. Compared with metabolically healthy normal weight individuals, the multivariable adjusted IRR of CVD was 1.33 (95%CI: 1.19–1.49) for MHO, 1.29 (95%CI: 1.22–1.38) for metabolically unhealthy normal weight, and 1.61 (95%CI: 1.51–1.75) for metabolically unhealthy obese in the full adjusted model. ConclusionsMHO individuals are associated with the increased risk of cardiovascular diseases among the Chinese population.