Metabolically Healthy Obesity and the Risk of Cardiovascular Disease in the Elderly Population

The effect of obesity phenotype changes on cardiovascular outcomes in adults older than 40 years in the prospective cohort of the Tehran lipids and glucose study (TLGS): joint model of longitudinal and time-to-event data

BACKGROUND

Obesity is a worldwide health concern with serious clinical effects, including myocardial infarction (MI), stroke, cardiovascular diseases (CVDs), and all-cause mortality. The present study aimed to assess the association of obesity phenotypes and different CVDs and mortality in males and females by simultaneously considering the longitudinal and survival time data.

METHODS

In the Tehran Lipid and Glucose Study (TLGS), participants older than three years were selected by a multi-stage random cluster sampling method and followed for about 19 years. In the current study, individuals aged over 40 years without a medical history of CVD, stroke, MI, and coronary heart disease were included. Exclusions comprised those undergoing treatment for CVD and those with more than 30% missing information or incomplete data. Joint modeling of longitudinal binary outcome and survival time data was applied to assess the dependency and the association between the changes in obesity phenotypes and time to occurrence of CVD, MI, stroke, and CVD mortality. To account for any potential sex-related confounding effect on the association between the obesity phenotypes and CVD outcomes, sex-specific analysis was carried out. The analysis was performed using packages (JMbayes2) of R software (version 4.2.1).

RESULTS

Overall, 6350 adults above 40 years were included. In the joint modeling of CVD outcome among males, literates and participants with a family history of diabetes were at lower risk of CVD compared to illiterates and those with no family history of diabetes in the Bayesian Cox model. Current smokers were at higher risk of CVD compared to non-smokers. In a logistic mixed effects model, odds of obesity phenotype was higher among participants with low physical activity, family history of diabetes and older age compared to males with high physical activity, no family history of diabetes and younger age. In females, based on the results of the Bayesian Cox model, participants with family history of diabetes, family history of CVD, abnormal obesity phenotype and past smokers had a higher risk of CVD compared to those with no history of diabetes, CVD and nonsmokers. In the obesity varying model, odds of obesity phenotype was higher among females with history of diabetes and older age compared to those with no history of diabetes and who were younger. There was no significant variable associated with MI among males in the Bayesian Cox model. Odds of obesity phenotype was higher in males with low physical activity compared to those with high physical activity in the obesity varying model, whereas current smokers were at lower odds of obesity phenotype than nonsmokers. In females, risk of MI was higher among those with family history of diabetes compared to those with no history of diabetes in the Bayesian Cox model. In the logistic mixed effects model, a direct and significant association was found between age and obesity phenotype. In males, participants with history of diabetes, abnormal obesity phenotype and older age were at higher risk of stroke in the Bayesian Cox model compared to males with no history of diabetes, normal obesity phenotype and younger persons. In the obesity varying model, odds of obesity phenotype was higher in males with low physical activity, family history of diabetes and older age compared to those with high physical activity, no family history of diabetes and who were younger. Smokers had a lower odds of obesity phenotype than nonsmokers. In females, past smokers and those with family history of diabetes were at higher risk of stroke compared to nonsmokers and females with no history of diabetes in the Bayesian Cox model. In the obesity varying model, females with family history of diabetes and older ages had a higher odds of obesity phenotype compared to those with no family history of diabetes and who were younger. Among males, risk of CVD mortality was lower in past smokers compared to nonsmokers in the survival model. A direct and significant association was found between age and CVD mortality. Odds of obesity phenotype was higher in males with a history of diabetes than in those with no family history of diabetes in the logistic mixed effects model.

CONCLUSIONS

It seems that modifications to metabolic disorders may have an impact on the heightened incidence of CVDs. Based on this, males with obesity and any type of metabolic disorder had a higher risk of CVD, stroke and CVD mortality (excluding MI) compared to those with a normal body mass index (BMI) and no metabolic disorders. Females with obesity and any type of metabolic disorder were at higher risk of CVD(, MI and stroke compared to those with a normal BMI and no metabolic disorders suggesting that obesity and metabolic disorders are related. Due to its synergistic effect on high blood pressure, metabolic disorders raise the risk of CVD.

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.

BMI trajectory in adulthood in relation to all-cause and cause-specific mortality: A retrospective cohort study in Taiwan

A dynamic change of weight over time has been known as an important factor that impacts mortality risk. The aims of this study were to identify the heterogeneity of BMI trajectory groups and to examine the association of the trajectories of BMI and all-cause and cause-specific mortality. The data for this study were obtained from a large prospective cohort study in Taiwan between 1998 and 2019 that was linked to the National Death Registry for death information. The participants were stratified into four groups by age and gender; self-reported demographics and measured BMI data were used. We used group-based trajectory analysis to identify the distinct trajectories of changes in BMI. A Cox proportional hazards model was used to assess the hazard ratio (HR) of all-cause and cause-specific mortality risk. Data were analyzed in April 2020 and included 89,886 participants. Four trajectory groups were identified by the pattern of BMI change over time. Our study shows that different trajectories were associated with mortality. Our findings suggest that the mortality risk differs in each trajectory group and in each age and gender stratification. It appears that obesity is a protective factor in cancer-related mortality in females but not in males in group of old age participants; low-normal weight is a risk factor in respiratory-related mortality in all participants. Our findings can be used to suggest the appropriate BMI in each age and gender groups and thereby earlier health interventions can be taken to avoid mortality.

The association between chemical constituents of ambient fine particulate matter and obesity in adults: A large population-based cohort study

OBJECTIVES

Current evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM2.5 and its constituents and obesity in adults.

METHODS

We included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM2.5 and its constituents were evaluated by linking pollutant estimates to the geocoded residential addresses. Obesity was defined as body mass index (BMI) ≥ 28 kg/m2. Logistic regression was used to examine the relationship between PM2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM2.5 and its constituents and the relative contribution of each constituent.

RESULTS

Per-SD increase in PM2.5 (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.37-1.49), black carbon (BC) (1.42, 1.36-1.48), ammonium (1.43, 1.37-1.49), nitrate (1.44, 1.38-1.50), organic matter (OM) (1.45, 1.39-1.51), sulfate (1.42, 1.35-1.48), and soil particles (SOIL) (1.31, 1.27-1.36) were positively associated with obesity, and SS (0.60, 0.55-0.65) was negatively associated with obesity. The overall effect (OR = 1.34, 95% CI: 1.29-1.41) of the PM2.5 and its constituents was positively associated with obesity, and ammonium made the most contribution to this relationship. Participants who were older, female, never smoked, lived in urban areas, had lower income or higher levels of physical activity were more significantly adversely affected by PM2.5, BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals.

CONCLUSION

Our study revealed that PM2.5 constituents except SS were positively associated with obesity, and ammonium played the most important role. These findings provided new evidence for public health interventions, especially the precise prevention and control of obesity.

Elevated Chinese visceral adiposity index increases the risk of stroke in Chinese patients with metabolic syndrome

Introduction

Patients with Metabolic Syndrome (MetS) are considered at high-risk for incident stroke. An indicator of visceral adiposity dysfunction, the Chinese Visceral Adiposity Index (CVAI) is used to evaluate the dysfunction of visceral fat. Given the impact of visceral adiposity dysfunction on elevating cardiovascular hazards, this study aimed to examine the association between CVAI and stroke risk in MetS patients.

Method

Between November 2017 and December 2018, a total of 18,974 individuals aged ≥40 underwent standardized in-person clinical interviews in Hunan Province, with 6,732 meeting the criteria for MetS. After the baseline survey was completed, subsequent surveys were conducted biennially. The study was split into two stages performed at baseline and after two years. During the former, receiver-operating characteristic curves were used to assess the accuracy of using baseline CVAI in diagnosing MetS. After two years, we examined the association between CVAI and incident stroke in MetS patients using logistic regression, subgroup analysis, and restricted cubic spline (RCS) analysis.

Result

As evidenced by a higher AUC (AUC:0.741), CVAI demonstrated superior diagnostic performance relative to body mass index (AUC:0.631) and waist circumference (AUC:0.627) in diagnosing MetS. After a 2-year follow-up, 72 MetS patients had a stroke event. There was a robust positive correlation between incident stroke and CVAI in patients with MetS. Each 1 SD increase in CVAI was associated with a 1.52-fold higher risk of stroke after adjustment for confounding factors (aOR=1.52, 95%CI: 1.18-1.95). The RCS demonstrated a reduced risk of stroke for MetS patients when the CVAI was below 110.91. However, no significant correlation was detected between CVAI and stroke in non-MetS patients.

Conclusion

Our findings recommend CVAI as a superior screening tool for detecting MetS and suggest that reducing CVAI can mitigate the risk of stroke in patients with MetS.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Overweight or obesity increases the risk of cardiovascular disease among older Australian adults, even in the absence of cardiometabolic risk factors: a Bayesian survival analysis from the Hunter Community Study

OBJECTIVE

To estimate the risk of cardiovascular disease (CVD) in older adults with overweight or obesity without metabolic risk factors using a Bayesian survival analysis.

DESIGN

Prospective cohort study with median follow-up of 9.7 years.

SETTING

Newcastle, New South Wales, Australia.

PARTICIPANTS

A total of 2313 community-dwelling older men and women.

INTERVENTION/EXPOSURE

Participants without known CVD and with a body mass index (BMI) ≥ 18.5 kg m² were stratified by BMI and metabolic risk to create six BMI-metabolic health categories. Metabolic risk was defined according to the International Diabetes Federation criteria for metabolic syndrome. 'Metabolically healthy' was defined as absence of metabolic risk factors. Bayesian survival analysis, incorporating prior information from a previously published meta-analysis was used to assess the effect of BMI-metabolic health categories on time from recruitment to CVD.

MAIN OUTCOME

Incident physician-diagnosed CVD, defined as fatal or nonfatal myocardial infarction, fatal or nonfatal stroke, angina, or coronary revascularisation procedure, was determined by linkage to hospital admissions records and Medicare Australia data. Secondary outcomes were cardiovascular mortality and all-cause mortality.

RESULTS

From 2313 adults with complete metabolic health data over a median follow-up of 9.7 years, 283 incident CVD events, 58 CVD related deaths and 277 deaths from any cause occurred. In an adjusted Bayesian survival model of complete cases with informative prior and metabolically healthy normal weight as the reference group, the risk of CVD was increased in metabolically healthy overweight (HR = 1.52, 95% credible interval 0.96-2.36), and in metabolically healthy obesity (HR = 1.86, 95% credible interval 1.14-3.08). Imputation of missing metabolic health and confounding data did not change the results.

CONCLUSION

There was increased risk of CVD in older adults with overweight or obesity, even in the absence of any metabolic abnormality. This argues against the notion of 'metabolically healthy' overweight or obesity.

Metabolically unhealthy phenotype in normal weight population and risk of mortality and major adverse cardiac events: A meta-analysis of 41 prospective cohort studies

BACKGROUND AND AIMS

It is still debatable whether metabolic status in normal weight population increases the risk of mortality (all-cause mortality (ACM), cardiovascular mortality (CVM)) and major adverse cardiac events (MACE) as compared to the obese population. Therefore, this meta-analysis aims to evaluate the association of the metabolically unhealthy normal weight (MUH-NW) phenotype with all-cause mortality, cardiovascular mortality, and MACE in comparison to metabolically healthy obesity (MH-O), along with the association of metabolically unhealthy obesity (MUH-O) phenotype regarding the same outcomes compared to MUH-NW.

METHODS

A systematic literature search was conducted using online databases from inception to June 20, 2022, to comprehensively search all prospective cohort studies comprising three variables including adults aged ≥18 years, obesity and four metabolic phenotypes, and interest outcomes (ACM, CVM, and MACE).

RESULTS

Forty-one prospective cohort studies with a total of 4,028,750 participants was included in this study. Compared to MH-O, MUH-NW had a substantially higher risk of ACM (RR = 1.47 (95%CI = 1.32-1.64); P < 0.001; I² = 89.8%,P-heterogeneity<0.001), CVM (RR = 2.37 (95%CI = 1.97-2.86); P < 0.001; I² = 83.7%,P-heterogeneity<0.001), and MACE (RR = 1.73 (95%CI = 1.49-2.00); P < 0.001; I² = 74.3%,P-heterogeneity<0.001). Moreover, MUH-O did not have a significantly elevated risk of ACM (RR = 0.97 (95%CI = 0.82-1.15); P = 0.736; I² = 98.3%,P-heterogeneity<0.001), CVM (RR = 0.96 (95%CI = 0.88-1.05); P = 0.394; I² = 77.0%,P-heterogeneity<0.001), and MACE (RR = 0.95 (95%CI = 0.80-1.13); P = 0.570; I² = 92.2%,P-heterogeneity<0.001) compared to MUH-NW.

CONCLUSION

In conclusion, MUH-NW was superior but not inferior to MH-O and MUH-O in terms of increased risk of interest outcomes, refuting the notion that normal weight population is a benign condition. Hence, in normal weight population, metabolic screening is highly suggested to measure the baseline of obesity and metabolic phenotypes, thus preventing the risk of CVD and mortality in the future.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Heterogeneity of abdominal obesity in patients with cardiovascular diseases

Aim: To assess the content of visceral adipose tissue (VAT) in patients with abdominal obesity and its relationship with metabolic disorders.

Material and methods. Patients with abdominal obesity (n=107) were included in the study. All participants had an assessment of anthropometric parameters (height, weight), calculation of body mass index (BMI), proportion of total adipose tissue and VAT (bioimpedance analyzer), high-density lipoprotein cholesterol (HDL-c) levels, triglycerides, fasting blood glucose, epicardial thickness adipose tissue (two-dimensional echocardiography).

Results. The median share of VAT (bioimpedance method) was 13%. Patients with abdominal obesity are divided by VAT into 2 groups: ≥14% or ≤13%. Patients with VAT≥14% had significantly higher levels of triglycerides (1.76 [1.27; 2.38] mmol / L) and glucose (6.33 [5.78; 7.87] mmol / L), and below HDL-c levels (0.95 [0.85; 1.21] mmol / L) compared with patients with VAT≤13% (1.32 [1.02; 1.50], 5.59 [5, 11; 6.16] and 1.31 [1.07; 1.58] mmol / L, respectively; p<0.001 for all three comparisons). A significant correlation was found between VAT and triglyceride, glucose and HDL-c levels (r=0.40; r=0.40; r=-0.31, respectively; p<0.001).

Conclusion. Persons with abdominal obesity are heterogeneous in the proportion of VAT. The proportion of VAT above the median is associated with metabolic disorders that are significant for the development and progression of atherosclerosis. An increase in BMI in obese individuals is not associated with an increase in VAT and an increase in the severity of metabolic disorders.

Association between metabolically healthy obesity/overweight and cardiovascular disease risk: A representative cohort study in Taiwan

Objectives

To investigate the relationship between metabolically healthy obesity and cardiovascular disease risk in Taiwanese individuals.

Methods

Taiwanese individuals were recruited from a nationwide, representative community-based prospective cohort study and classified according to body mass index as follows: normal weight (18.5–23.9 kilogram (kg)/meter(m)²) and obesity/overweight (≥24 kg/m²). Participants without diabetes, hypertension, and hyperlipidemia and who did not meet the metabolic syndrome without waist circumference criteria were considered metabolically healthy. The study end points were cardiovascular disease morbidity and mortality. Multivariable adjusted hazard ratios and 95% confidence intervals were obtained from a Cox regression analysis.

Results

Among 5 358 subjects (mean [standard deviation] age, 44.5 [15.3] years; women, 48.2%), 1 479 were metabolically healthy with normal weight and 491 were metabolically healthy with obesity. The prevalence of metabolically healthy obesity/overweight was 8.6% in the Taiwanese general population, which included individuals who were >20 years old, not pregnant, and did not have CVD (n = 5,719). In the median follow-up period of 13.7 years, 439 cardiovascular disease events occurred overall and 24 in the metabolically healthy obesity group. Compared with the reference group, the metabolically healthy obesity group had a significantly higher cardiovascular disease risk (adjusted hazard ratio: 1.74, 95% confidence interval: 1.02, 2.99).

Conclusions

Individuals with metabolically healthy obesity have a higher risk of cardiovascular disease and require aggressive body weight control for cardiovascular disease control.

Agreement between laboratory methods and the 4-compartment model in assessing fat mass in obese older Hispanic-American adults

BACKGROUND/OBJECTIVES

Densitometry (Siri's and Brožek's equations), hydrometry (by the deuterium dilution technique), and dual-energy X-ray absorptiometry (DXA) are three methods for estimating body composition. However, because they are all based on certain assumptions, they may not be applicable to aged and obese subjects due to changes in their body composition. Hence, the validity of these "laboratory methods" could be affected in obese older people. The main aim was to assess the agreement between densitometry, hydrometry, and DXA with the 4-compartment (4C) model to estimate fat mass (FM) in obese older Hispanic-American adults. As secondary goals, we explored whether the bias in densitometry and hydrometry results could be improved by modifying the assumptions regarding fat-free mass (FFM) density and hydration factor (HF) values, respectively. In the case of DXA, we explored the factors that contribute to bias.

SUBJECTS/METHODS

This is a cross-sectional study based on a sample of 171 obese subjects aged ≥60 years from 3 regions of northern Mexico. Body composition was assessed by the 4C model as the reference method and by all three laboratory methods. Agreement of the latter with the 4C model was probed by Bland and Altman analysis, a paired sample t-test, and simple linear regression analyses. In addition, the mean FFM density estimated in this sample, and HF values (published previously) of 0.737 and 0.753 for obese older Hispanic-American men and women, respectively, were considered as ethnic- and gender-specific values. These values were used to modify the densitometric and hydrometric equations in order to improve their bias. Finally, we tested whether the hydration status and indirect markers of adiposity are contributing factors to the bias of DXA using multiple linear regression analysis.

RESULTS

Siri's equation overestimated FM by 0.57 kg (p < 0.01), while Brožek's equation, hydrometry, and DXA underestimated it by 1.24 kg, 0.89 kg, and 0.79 kg (p < 0.01), respectively, compared to the 4C model. The bias in the densitometry and hydrometry results was eliminated by substituting the ethnic- and gender-specific values into the equations. Finally, we found that hip circumference contributes to the bias in DXA.

CONCLUSION

The densitometry, hydrometry, and DXA methods are not interchangeable with the 4C model for assessing fat mass in obese, older Hispanic-American adults. The lack of agreement could indicate that the assumptions of each method do not apply to this population.

Asymptomatic Hyperuricemia and Metabolically Unhealthy Obesity: A Cross-Sectional Analysis in the Tianning Cohort

OBJECTIVE

The relationship between obesity and hyperuricemia has been demonstrated by many studies. However, whether or to what extent metabolic condition influents the association between obesity and hyperuricemia was not clear. Here, we aimed to examine the association between obese-metabolic phenotype and hyperuricemia in a large sample of Chinese adults.

METHODS

According to BMI and metabolic syndrome, obese-metabolic phenotype was defined as metabolically unhealthy obesity (MUO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically healthy non-obesity (MHNO)in the Tianning cohort (N=5072). We conducted a cross-sectional analysis between obese-metabolic phenotype and hyperuricemia, followed by a Mendelian Randomization analysis using GWAS summary data to confirm the causality between uric acid and BMI.

RESULTS

The average level of serum UA showed 41.87-higher μmol/L in participants with MHO (β=41.87, P<0.001) and 63.18-higher μmol/L in participants with MUO (β=63.18, P<0.001), compared to those with MHNO. Compared to participants with MHNO, those with MUO had the highest likelihood to have hyperuricemia (OR=4.56, P<0.001), followed by those with MHO (OR=3.32, P<0.001). Mendelian randomization analysis indicated that uric acid was more likely to be a consequence of BMI (β=0.059, P=6.54×10^-154).

CONCLUSION

MUO, in comparison with MHO, was significantly associated with hyperuricemia in Chinese adults.

Metabolically healthy overweight/obesity are associated with increased risk of cardiovascular disease in adults, even in the absence of metabolic risk factors: A systematic review and meta-analysis of prospective cohort studies

This review examined the risk of cardiovascular disease in adults with metabolically healthy overweight/obesity. A systematic review and meta-analysis using data from Medline, EMBASE, SCOPUS and Cochrane Library searched from inception up to 31st October 2019. We included prospective cohort studies of adults who are metabolically healthy or unhealthy. Outcomes were fatal and nonfatal cardiovascular events, all-cause mortality. Pooled relative risk was calculated for each outcome in populations with metabolically healthy overweight and metabolically healthy obesity using metabolically healthy normal weight as reference. A random-effects model was used for meta-analysis, and risk of bias assessment tool for nonrandomized studies assessed risk of bias within each study. Twenty-three prospective cohort studies with 4,492,723 participants were included. Cardiovascular disease risk was increased in metabolically healthy groups with overweight (RR = 1.34, CI: 1.23-1.46, n = 20, I² = 90.3%) and obesity (RR = 1.58, CI: 1.34-1.85, n = 21, I² = 92.2) compared with a reference group with metabolically healthy normal weight. Cardiovascular disease risk was similar irrespective of the number of risk factors used to define metabolically healthy and the risk remained in the group with no metabolic risk factors. Cardiovascular disease risk is increased in populations with overweight and obesity classified as metabolically healthy even when there were no metabolic risk factors.

Are young Iranian women with metabolically healthy obesity at increased risk of CVD incidence?

Background

The association between the Metabolically Healthy Obese (MHO) phenotype in the absence of metabolic syndrome and subsequent cardiovascular disease remains unclear.

Objectives

We examined the association between MHO and CVD risk in young Iranian women.

Methods

We studied 183 women aged 20-35 years from a population of 308 candidates. We classified participants into 4 phenotypes. We measured body composition, blood pressure, and biochemical factors in all participants.

Results

The Metabolically Healthy Normal Weight (MHNW) and Normal Weight Obese (NWO) phenotypes had no statistical differences in any biochemistry variables. FBS, TG, LDL/HDL, Cholesterol/HDL, hs-CRP, and atherogenic index of plasma (AIP) were all higher in Metabolically Unhealthy Obese (MUO) than MHO individuals, whereas HDL was higher in MHO than in MUO individuals. LDL/HDL and hs-CRP were higher in MHO participants than MHNW participants, whereas HDL-c was higher in MHNW than MHO.

Conclusions

Results of the present study demonstrate that young women displaying the MHO phenotype have a favorable metabolic profile as shown by lower FBS, TG, LDL-c/HDL, Cho/HDL, hs-CRP, and AIP and higher HDL levels than the MUO phenotype. However, MHO individuals were still at greater risk of CVD incidence (lower HDL and higher hs-CRP levels) than MHNW individuals.

Metabolically Healthy Obesity: Criteria, Epidemiology, Controversies, and Consequences

PURPOSE OF REVIEW

To present a comprehensive overview regarding criteria, epidemiology, and controversies that have arisen in the literature about the existence and the natural course of the metabolic healthy phenotype.

RECENT FINDINGS

The concept of metabolically healthy obesity (MHO) implies that a subgroup of obese individuals may be free of the cardio-metabolic risk factors that commonly accompany obese subjects with adipose tissue dysfunction and insulin resistance, known as having metabolic syndrome or the metabolically unhealthy obesity (MUO) phenotype. Individuals with MHO appear to have a better adipose tissue function, and are more insulin sensitive, emphasizing the central role of adipose tissue function in metabolic health. The reported prevalence of MHO varies widely, and this is likely due the lack of universally accepted criteria for the definition of metabolic health and obesity. Also, the natural course and the prognostic value of MHO is hotly debated but it appears that it likely evolves towards MUO, carrying an increased risk for cardiovascular disease and mortality over time. Understanding the pathophysiology and the determinants of metabolic health in obesity will allow a better definition of the MHO phenotype. Furthermore, stratification of obese subjects, based on metabolic health status, will be useful to identify high-risk individuals or subgroups and to optimize prevention and treatment strategies to compact cardio-metabolic diseases.

Beta-Cell Function, Self-rated Health, and Lifestyle Habits in 64-Year-Old Swedish Women with Metabolically Healthy Obesity Phenotype

Background

A subset of obese individuals do not present metabolic abnormalities that commonly define the metabolic syndrome (MetS). This is referred to as a metabolically healthy obese (MHO) phenotype. The aim of the present study was to evaluate the prevalence of the MHO phenotype and its relationship with beta cell dysfunction by measuring C-peptide and proinsulin, anthropometric-, metabolic- and lipid appearance, as well as lifestyle behaviors and self-rated health in a cohort of 64-year-old Swedish women.

Methods

The National Cholesterol Education Program definition was used to assess MetS. We defined normal weight as body mass index (BMI) 18.5–24.9 kg/m² and obesity as BMI ≥30 kg/m² to categorize participants as metabolically healthy normal weight, MHO, and metabolically unhealthy obese.

Results

The MHO phenotype represented 36.3% of obese participants and 16.3% of total participants. The MHO group were at greater risk of having proinsulin levels >11 pmol/L, indicating impaired beta cell function. Further, homeostatic model assessment for insulin resistance, fasting plasma levels of insulin, and C-peptide showed significant trends, with the MHO phenotype group having intermediate levels among three groups. Health behaviors such as leisure time physical activity and alcohol intake were also intermediate in individuals with the MHO phenotype.

Conclusion

In this study, we demonstrate that over a third of the obese women in our sample were MHO. Further, women with the MHO phenotype showed intermediate profiles considering beta cell function and insulin resistance, as well as metabolic variables, and tended to rate their general health as worse than otherwise similar individuals of normal weight.

Circuit Training Improvements in Korean Women with Sarcopenia

Sarcopenia is defined as an age-related decrease in muscle mass, strength, and function. We investigated the effect of circuit training on body composition, balance, muscle mass and strength, and pulmonary function in Korean women with sarcopenia. We randomly assigned 26 Korean women with sarcopenia (M_age = 74.9, SD = 4.5 years) to either an exercise group (EG) (n = 13) or a control group (CG) (n = 13). The EG performed 25-75 minutes of circuit exercise training (gradually increasing time periods) three times per week over 12 weeks, while the CG maintained their usual daily lifestyle during the intervention period. We measured body weight, body mass index, percent body fat, free fat mass, balance ability, peak torque in shoulder, knee, and lumbar joints normalized for bodyweight (BW), forced vital capacity, percentage of forced expiratory volume in one second, and forced expiratory flow 25-75% before and after the intervention. The EG showed improved body composition (i.e., body mass index, fat-free body mass, fat mass; all p < .032, η²> 0.180), balance (i.e., right and left of static and dynamic balance and fast 10-m walk; all p < .050, η²> 0.151), muscular function (i.e., 90°/s and 180°/s peak power per kilogram BW, 90°/s average power per kilogram BW, 180°/s total work, and 180°/s endurance ratio; all p < .045, η²> 0.157), and pulmonary function (all p < .005, η²> 0.292). On the other hand, the CG showed no significant changes. Circuit exercise training improves muscle mass and strength, body composition, balance, and pulmonary function in women with sarcopenia.

Transition from metabolically benign to metabolically unhealthy obesity and 10-year cardiovascular disease incidence: The ATTICA cohort study

BACKGROUND/OBJECTIVES

Metabolically benign obesity remains a scientific field of considerable debate. The aim of the present work was to evaluate whether metabolically healthy obese (MHO) status is a transient condition which propagates 10-year cardiovascular disease (CVD) onset.

METHODS

A prospective longitudinal study was conducted during 2001-2012, the ATTICA study studying 1514 (49.8%) men and 1528 (50.2%) women (aged >18 years old) free of CVD and residing in the greater Athens area, Greece. Follow-up assessment of first combined CVD event (2011-2012) was achieved in n = 2020 participants; of them, 317 (15.7%) incident cases were identified. Obesity was defined as body mass index ≥30 kg/m² and healthy metabolic status as absence of all NCEP ATP III (2005) metabolic syndrome components (excluding waist circumference).

RESULTS

The MHO prevalence was 4.8% (n = 146) with 28.2% of obese participants presenting metabolically healthy status at baseline. Within this group, 52% developed unhealthy metabolic status during the 10-year follow up. MHO vs. metabolically healthy non-obese participants had a higher likelihood of presenting with 10-year CVD events, yet only the subset of them who lost their baseline status reached the level of significance (Hazard Ratio (HR) = 1.43, 95% Confidence Interval (95% CI) 1.02, 2.01). Sensitivity analyses revealed that MHO status was independently associated with elevated CVD risk in women and participants with low adherence to the Mediterranean diet, low grade inflammation, and insulin resistance.

CONCLUSIONS

MHO status is a transient condition where weight management is demanded to prevent the establishment of unhealthy cardiometabolic features. The existence of obese persons who remain "longitudinally" resilient to metabolic abnormalities is an emerging area of future research.

Metabolically healthy versus metabolically unhealthy obesity

Obesity-related disease complications reduce life quality and expectancy and increase health-care costs. Some studies have suggested that obesity not always entails metabolic abnormalities and increased risk of cardiometabolic complications. Because of the lack of universally accepted criteria to identify metabolically healthy obesity (MHO), its prevalence varies widely among studies. Moreover, the prognostic value of MHO is hotly debated, mainly because it likely shifts gradually towards metabolically unhealthy obesity (MUO). In this review, we outline the differential factors contributing to the metabolic heterogeneity of obesity by discussing the behavioral, genetic, phenotypical, and biological aspects associated with each of the two metabolic phenotypes (MHO and MUO) of obesity and their clinical implications. Particular emphasis will be laid on the role of adipose tissue biology and function, including genetic determinants of body fat distribution, depot-specific fat metabolism, adipose tissue plasticity and, particularly, adipogenesis. Finally, the emerging role of gut microbiota in obesity and adipose tissue dysfunction as well as the search for novel biomarkers for the obesity-related metabolic traits and associated diseases will be briefly presented. A better understanding of the main determinants of a healthy metabolic status in obesity would allow promotion of this favorable condition by targeting the relevant pathways.

The long-term prognosis of heart diseases for different metabolic phenotypes: a systematic review and meta-analysis of prospective cohort studies

PURPOSE

This meta-analysis aimed to assess the association of different categories of weight and metabolic status with risk of heart diseases including myocardial infarction (MI), cardiovascular diseases (CVDs), and heart failure (HF).

METHODS

Data from relevant studies were identified systematically by searching PubMed and Scopus search engines up to 29 May 2018. Prospective studies were included in the analyses with metabolically healthy normal weight (MHNW) as the reference. Pooled RRs and 95% CI were calculated using random-effects or fixed-effect models when appropriate. Subgroup analysis was applied to define possible sources of heterogeneity.

RESULTS

Overall, 21 studies (n = 778,401 participants) were eligible for the present meta-analysis. Generally, the risk of CVDs for all metabolic phenotypes in metabolically unhealthy obese increased compared with the MHNW group. A significant positive association between all metabolic phenotypes and the risk of HF was also observed expect for MHOW (RR = 1.10, 95% CI: 0.60-2.00, P = 0.76) and MHO phenotypes (RR = 0.96, 95% CI: 0.25-3.77, P = 0.95). Moreover, MUHO phenotype was associated with greater risk of MI compared with the MHNW phenotype (RR = 1.82, 95% CI: 1.50-2.22, P < 0.001, respectively).

CONCLUSIONS

Our findings showed that all metabolically unhealthy phenotypes in different categories of weight were associated with increased incident of CVDs/HF and MI. Furthermore, healthy overweight and obese subjects had increased risk of CVDs.

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

BACKGROUND

Epidemiologic evidence on metabolically healthy obese (MHO) phenotype and cardiovascular diseases (CVD) risk remains controversial.

AIMS

We aim to examine the relationship between MHO and risk of CVD among the Chinese population.

METHODS

The 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.

RESULTS

During 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.

CONCLUSIONS

MHO individuals are associated with the increased risk of cardiovascular diseases among the Chinese population.

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

PURPOSE

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

MATERIALS AND METHOD

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

RESULT

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

CONCLUSION

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

Lifetime predictors of stroke in subjects without a diagnosis of hypertension: the aerobics center longitudinal study

BACKGROUND AND PURPOSE

Although several studies have assessed the importance of traditional risk factors in predicting stroke, none have concurrently addressed the stroke-predicting ability of these risk factors across the lifespan of subjects without a hypertension (HTN) diagnosis. Thus, this study aimed to assess the importance of blood-pressure-related risk indicators, cardiorespiratory fitness (CRF), weight status, diabetes mellitus (DM), and lifestyle factors as predictors of stroke in different stages of life among non-hypertensive subjects.

MATERIALS AND METHODS

This study was a long-term follow-up study including 33,254 men and 10,598 women from the Aerobics Center Longitudinal Study (ACLS) who were 18-100 years old and did not have a HTN diagnosis at baseline. Logistic regression models were constructed using forward selection procedures for each age category, with stroke occurrence as the dependent variable, and pulse pressure (PP), mean arterial pressure (MAP), systolic blood pressure (SBP), smoking status, CRF, drinking behavior, DM status, and weight status as potential predictors.

RESULTS

In total, 507 subjects had a stroke during an average follow-up period of 17 years (range=1-34 years). Logistic regression models showed that MAP values (P=0.043) in those aged 19-39 years; SBP (P<0.001), CRF (P=0.001), weight status (P=0.005), and alcohol consumption (P=0.001) in those 40-60 years old; and CRF (P=0.002), weight status (P=0.005), and DM status (P=0.037) in those over 60 years old were predictors of stroke.

CONCLUSION

These findings suggest that, among individuals without a baseline HTN diagnosis, classic modifiable risk factors for stroke change across different stages of life.

Association between the metabolically healthy obese phenotype and the risk of myocardial infarction: results from the Kailuan study

Objective This study aimed to determine if the metabolically healthy obese (MHO) is associated with an increased risk of myocardial infarction (MI) in Chinese population. Design The Kailuan study is a community-based prospective cohort study. Methods BMI and metabolic syndrome (MetS) were assessed in 91 866 participants without a history of MI or stroke. Participants were categorised into six mutually exclusive groups according to the BMI-MetS status: normal weight (BMI: ≤ 18.5to < 24.0 kg/m2) without MetS (MH-NW), normal weight with MetS (MUH-NW), overweight (BMI: ≤ 24.0to < 28.0 kg/m2) without MetS (MH-OW), overweight with MetS (MUH-OW), obese (BMI ≥ 28.0 kg/m2) without MetS (MHO) and obese with MetS (MUO). The hazard ratio (HR) with 95% CI was calculated for the incidence of MI using a multivariable Cox model. Results A total of 6745 (7.34%) individuals were classified as MHO. During a median 8-year follow-up, 1167 (1.27%) participants developed MI. The MHO group had an increased risk of MI (HR: 1.76, 95% CI: 1.37-2.25) in comparison with the MH-NW group after adjusting for potential confounding variables. After a similar adjustment, the risk of MI was significantly elevated in the MUH-NW (HR: 1.62, 95% CI: 1.28-2.05), MUH-OW (HR: 1.98, 95% CI: 1.67-2.35) and MUO group (HR: 2.06, 95% CI: 1.70-2.49). Conclusions MHO subjects showed a substantially higher risk of MI in comparison with MH-NW subjects. That said, even without measurable metabolic abnormalities, obesity was associated with a higher risk of MI.

Metabolically Healthy Obesity, Transition to Metabolic Syndrome, and Cardiovascular Risk

BACKGROUND

Debate over the cardiometabolic risk associated with metabolically healthy obesity (MHO) continues. Many studies have investigated this relationship by examining MHO at baseline with longitudinal follow-up, with inconsistent results.

OBJECTIVES

The authors hypothesized that MHO at baseline is transient and that transition to metabolic syndrome (MetS) and duration of MetS explains heterogeneity in incident cardiovascular disease (CVD) and all-cause mortality.

METHODS

Among 6,809 participants of the MESA (Multi-Ethnic Study of Atherosclerosis) the authors used Cox proportional hazards and logistic regression models to investigate the joint association of obesity (≥30 kg/m2) and MetS (International Diabetes Federation consensus definition) with CVD and mortality across a median of 12.2 years. We tested for interaction and conducted sensitivity analyses for a number of conditions.

RESULTS

Compared with metabolically healthy normal weight, baseline MHO was not significantly associated with incident CVD; however, almost one-half of those participants developed MetS during follow-up (unstable MHO). Those who had unstable MHO had increased odds of CVD (odds ratio [OR]: 1.60; 95% confidence interval [CI]: 1.14 to 2.25), compared with those with stable MHO or healthy normal weight. Dose response for duration of MetS was significantly and linearly associated with CVD (1 visit with MetS OR: 1.62; 95% CI: 1.27 to 2.07; 2 visits, OR: 1.92; 95% CI: 1.48 to 2.49; 3+ visits, OR: 2.33; 95% CI: 1.89 to 2.87; p value for trend <0.001) and MetS mediated approximately 62% (44% to 100%) of the relationship between obesity at any point during follow-up and CVD.

CONCLUSIONS

Metabolically healthy obesity is not a stable or reliable indicator of future risk for CVD. Weight loss and lifestyle management for CVD risk factors should be recommended to all individuals with obesity.

Metabolically Healthy or Metabolically Unhealthy Obese HIV-Infected Patients: Mostly a Matter of Age?

Background: Life expectancy of HIV-infected patients has increased with antiretroviral treatment (ART). Chronic diseases associated with aging, including metabolic and cardiovascular diseases are becoming more prevalent in this population. We aimed to evaluate the association of obesity and aging with cardiometabolic comorbidities and metabolic health status among patients with HIV infection. Methods: We evaluated 580 HIV-1 infected patients (71.7% male, mean age of 47.7 ± 11.5 years). We analyzed the association of age and obesity (defined by and by central obesity) with gender, duration of HIV infection, and ART, anthropometric parameters, cardiometabolic comorbidities, Framingham risk score (FRS), blood pressure, lipid profile, uric acid, liver biochemical tests, and glycemic profile. Furthermore, we analyzed the above-mentioned associations according to the category and central obesity into the metabolically healthy (MH) and unhealthy (MUH) categories. To evaluate the association of anthropometric parameters with cardiometabolic comorbidities, we performed unadjusted and adjusted logistic regression models. Results: The prevalence of excessive weight and cardiometabolic comorbidities increased with age. Patients with normal weight were younger and there was a higher proportion of female patients in the obesity group. The prevalence of hypertension and metabolic syndrome were higher among patients who were overweight or with obesity. The FRS was higher among patients with obesity. The proportion of MUH patients was higher among patients with excessive weight and central obesity. MUH patients had more cardiometabolic comorbidities and a higher FRS. In the normal weight group, MUH patients were older, and in the obesity group they were more likely to be male. The anthropometric parameter most associated with metabolic syndrome was waist circumference and that most associated with hypertension was waist-to-height ratio. The anthropometric parameter most associated with diabetes and FRS was waist-to-hip ratio. Conclusion: Patients with HIV present a high prevalence of obesity and related comorbidities. Ageing significantly contributes to metabolic dysfunction in this population. The proportion of MUH patients is higher among groups with excessive weight and central obesity, with those patients presenting a higher cardiovascular risk. Our results highlight the importance of evaluating and addressing obesity in patients with HIV, as well as metabolic comorbidities and cardiovascular risk.

Hypertension, diabetes and obesity are associated with lower cognitive performance in community-dwelling elderly: Data from the FIBRA study

Background

Systemic hypertension (SH), diabetes mellitus (DM) and abdominal obesity may negatively impact cognitive performance.

Objective

To evaluate the association between SH, DM and abdominal obesity and cognitive performance among cognitively unimpaired elderly.

Methods

A cross-sectional study of individuals aged 65+ from seven Brazilian cities was conducted. SH and DM diagnoses were self-reported and abdominal circumference was objectively measured. Individuals who scored below the education-adjusted cutoff scores on the Mini-Mental State Examination (MMSE) were excluded.

Results

Among 2,593 elderly, 321 (12.38%) had SH, DM and abdominal obesity concomitantly (Group I) and 421 (16.23%) had none of the three diseases (Group II). Group I had a higher proportion of individuals that were women, aged 70-74 years, illiterate and with lower income. Group I had a higher number of participants with low cognitive performance (28.04% vs. 17.58% in Group II). Variables associated with poor cognitive performance were: female gender (OR: 2.43, p < 0.001); and lower education (OR: 0.410, p < 0.001). The presence of the three diseases and age were not significant in the education-adjusted model.

Conclusion

There was an association between cognition and the presence of SH, DM and obesity. However, education seems to be decisive in determining cognitive performance in the presence of these three conditions.

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

BACKGROUND

We conducted a systematic review and meta-analysis to firstly obtain a reliable estimation of the prevalence of metabolically healthy obese (MHO) individuals in obesity, then assessed the risk of developing metabolic abnormalities (MA) among MHO individuals. At last, we evaluated the effects of traditional lifestyle interventions on metabolic level for MHO subjects.

METHODS

A systematic review and meta-analysis (PRISMA) guideline were conducted, and original studies were searched up to December 31, 2016. The prevalence of MHO in obesity from each study was pooled using random effects models. The relative risks (RRs) were pooled to determine the risk of developing MA for MHO compared with metabolically healthy normal-weight (MHNW) subjects. For the meta-analysis of intervention studies, the mean difference and standardized mean differences were both estimated for each metabolic parameter within each study, and then pooled using a random-effects model.

RESULTS

Overall, 40 population-based studies reported the prevalence of MHO in obesity, 12 cohort studies and 7 intervention studies were included in the meta-analysis. About 35.0% obese individuals were metabolically healthy in the obese subjects. There were dramatic differences in the prevalence among different areas. However, 0.49 (95% confidence intervals [CI]: 0.38 to 0.60) of the MHO individuals would develop one or more MA within 10 years. Compared with MHNW subjects, the MHO subjects presented higher risk of incident MA (pooled RR = 1.80, 95%CI: 1.53-2.11). Following intervention, there was certain and significant improvement of metabolic state for metabolically abnormal obesity (MAO) subjects. Only diastolic blood pressure had reduced for MHO individuals after intervention.

CONCLUSIONS

Almost one-third of the obese individuals are in metabolic health. However, they are still at higher risk of advancing to unhealthy state. Therefore, it is still needed to advise MHO individuals to maintain or adopt a healthy lifestyle, so as to counterbalance the adverse effects of obesity.

Obesity and Cardiometabolic Defects in Heart Failure Pathology

Obesity is a major global epidemic that sets the stage for diverse multiple pathologies, including cardiovascular disease. The obesity-related low-grade chronic inflamed milieu is more pronounced in aging and responsive to cardiac dysfunction in heart failure pathology. Metabolic dysregulation of obesity integrates with immune reservoir in spleen and kidney network. Therefore, an integrative systems biology approach is necessary to delay progressive cardiac alternations. The purpose of this comprehensive review is to largely discuss the impact of obesity on the cardiovascular pathobiology in the context of problems and challenges, with major emphasis on the diversified models, and to study cardiac remodeling in obesity. The information in this article is immensely helpful in teaching advanced undergraduate, graduate, and medical students about the advancement and impact of obesity on cardiovascular health. © 2017 American Physiological Society. Compr Physiol 7:1463-1477, 2017.

Visceral adiposity index is strongly associated with hyperuricemia independently of metabolic health and obesity phenotypes

Visceral adiposity index (VAI) is a novel sex-specific index for visceral adipose function; however the association between VAI and hyperuricemia in China is unknown. We aimed to investigate this association, also whether it was independent of metabolic health and obesity phenotypes. 7632 adult subjects from the China Health and Nutrition Survey 2009 were retained. Subjects were categorized into four obesity phenotypes based on a cross-classification of BMI and metabolic health status by two representative criteria. VAI was the best predictors for hyperuricemia irrespective of obesity phenotypes, with area under curve (AUC) ranging 0.665–0.719. The odd ratio (OR) for hyperuricemia in the highest quartile of the VAI were 6.93 (95% CI 5.79–8.29) after adjusting for age and gender. Following further adjustments for metabolic obesity phenotypes and lifestyle confounders, the ORs were 4.88 (3.92–6.09) and 5.65 (4.68–6.82) according to these two criteria, respectively. A similar significant pattern was still found even after adjustment for blood pressure and other cardiovascular risks. Within each metabolic obesity phenotype, the significant association between VAI and hyperuricemia was consistently evident. In conclusion, the association of the VAI with hyperuricemia was significant, especially this association was independent of metabolic health and obesity phenotypes in the Chinese population.

Gut Dysbiosis and Adaptive Immune Response in Diet-induced Obesity vs. Systemic Inflammation

A mutual interplay exists between adaptive immune system and gut microbiota. Altered gut microbial ecosystems are associated with the metabolic syndrome, occurring in most obese individuals. However, it is unknown why 10–25% of obese individuals are metabolically healthy, while normal weight individuals can develop inflammation and atherosclerosis. We modeled these specific metabolic conditions in mice fed with a chow diet, an obesogenic but not inflammatory diet—mimicking healthy obesity, or Paigen diet—mimicking inflammation in the lean subjects. We analyzed a range of markers and cytokines in the aorta, heart, abdominal fat, liver and spleen, and metagenomics analyses were performed on stool samples. T lymphocytes infiltration was found in the aorta and in the liver upon both diets, however a significant increase in CD4+ and CD8+ cells was found only in the heart of Paigen-fed animals, paralleled by increased expression of IL-1, IL-4, IL-6, IL-17, and IFN-γ. Bacteroidia, Deltaproteobacteria, and Verrucomicrobia dominated in mice fed Paigen diet, while Gammaproteobacteria, Delataproteobacteria, and Erysipelotrichia were more abundant in obese mice. Mice reproducing human metabolic exceptions displayed gut microbiota phylogenetically distinct from normal diet-fed mice, and correlated with specific adaptive immune responses. Diet composition thus has a pervasive role in co-regulating adaptive immunity and the diversity of microbiota.

Atrial fibrillation risk in metabolically healthy obesity: A nationwide population-based study

BACKGROUND

Metabolically healthy obese (MHO) individuals are reported to have a marginal increase in cardiovascular risk; however, their atrial fibrillation (AF) risk is unclear. We aimed to assess AF risk in MHO individuals and identify whether AF development is associated with obesity or influenced by metabolic comorbidities.

METHODS

A retrospective cohort of 389,321 individuals (age, 45.6±14.5years; male, 52.1%) was extracted from the Korean National Health Insurance sample database between 2004 and 2006 and followed-up for new-onset AF until 2013. Subjects with diabetes mellitus, hypertension, and/or dyslipidemia were classified as "metabolically unhealthy." The cohort was stratified into four groups according to obesity and metabolic healthiness: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), MHO, and metabolically unhealthy obese (MUO).

RESULTS

AF was newly diagnosed in 5106 (1.3%) individuals during a mean follow-up of 7.5±1.5years. The AF incidence rates for the MHNO, MUNO, MHO, and MUO groups were 0.76, 2.66, 1.10, and 2.88 per 1000 person-years, respectively. Compared with the MHNO group, the MHO group had increased AF risk (adjusted hazard ratio, 1.30; 95% CI, 1.14-1.48) on multivariate analysis. One fourth of the MHO cohort became metabolically unhealthy, contributing to increased AF risk. Obesity was an independent risk factor for AF, and increased AF risk by 20%. Metabolic unhealthiness increased AF risk by around 40%, and of its components, hypertension contributed the most.

CONCLUSIONS

MHO individuals are at increased risk for AF development, and obesity was independently associated with elevated AF risk.

Metabolic Syndrome: An Evolving Clinical Construct

Metabolic syndrome (MetS), a clustering of metabolic risk factors, identifies individuals at increased risk of diabetes and cardiovascular disease (CVD). Measurement of waist circumference, high-density lipoprotein-cholesterol, triglycerides, blood pressure and fasting blood glucose are easily obtained in the clinic. At any level of low-density lipoprotein-cholesterol, presence of MetS increases the risk of adverse CVD outcomes including bothatherosclerotic CVD and atrial fibrillation. The MetS construct should focus the clinician on recommending behavioral lifestyle modification as this improves all of its components. The challenge, however, has been the lack of a standardized approach to achieve effective and sustained lifestyle modification in clinical practice. We briefly review various approaches useful to the clinician in counseling such patients. These include group lifestyle programs and emerging mobile technology. Technology alone may not be sufficient, but as an adjunct has the promise to improve low rates of behavioral change currently seen with traditional programs.