Association of dietary patterns with obesity and metabolically healthy obesity phenotype in Chinese population: a cross-sectional analysis of China Multi-Ethnic Cohort Study

Metabolically healthy obesity (MHO) might be an alternative valuable target in obesity treatment. We aimed to assess whether alternative Mediterranean (aMED) diet and Dietary Approaches to Stop Hypertension (DASH) diet were favorably associated with obesity and MHO phenotype in a Chinese Multi-Ethnic population. We conducted this cross-sectional analysis using the baseline data of the China Multi-Ethnic Cohort (CMEC) study that enrolled 99 556 participants from seven diverse ethnic groups. Participants with self-reported cardiometabolic diseases were excluded to eliminate possible reverse causality. Marginal structural logistic models were used to estimate the associations, with confounders determined by directed acyclic graph (DAG). Among 65 699 included participants, 11.2% were with obesity. MHO phenotype was present in 5.7% of total population and 52.7% of population with obesity. Compared with the lowest quintile, the highest quintile of DASH diet score had 23% decreased odds of obesity (OR = 0.77, 95% CI: 0.71-0.83, Ptrend <0.001), and 27% increased odds of MHO (OR = 1.27, 95% CI: 1.10-1.48, Ptrend =0.001) in population with obesity. However, aMED diet showed no obvious favorable associations. Further adjusting for BMI did not change the associations between diet scores and MHO. Results were robust to various sensitivity analyses. In conclusion, DASH diet rather than aMED diet is associated with reduced risk of obesity and presents BMI-independent metabolic benefits in this large population-based study. Recommendation for adhering to DASH diet may benefit the prevention of obesity and related metabolic disorders in Chinese population.

Association between being metabolically healthy/unhealthy and metabolic syndrome in Iranian adults

Introduction The prevalence of metabolically healthy obesity (MHO) varies based on different criteria. We assessed the prevalence of MHO and metabolic unhealthiness based on body mass index (BMI) and their association with metabolic syndrome (MetS) in a nation-wide study. Methods Data were taken from the STEPs 2016 study, from 18,459 Iranians aged ≥25 years. Demographic, metabolic, and anthropometric data were collected. Subjects were stratified by BMI, metabolic unhealthiness, and having MetS. The latter was defined based on National Cholesterol Education Program Adult Treatment Panel III 2004 (NCEP ATP III), was then assessed. Results The prevalence of MHO and metabolic unhealthiness in obese subjects was 7.5% (about 3.6 million) and 18.3% (about 8.9 million), respectively. Most of the metabolic unhealthy individuals were female (53.5%) or urban residents (72.9%). Low physical activity was significantly and positively associated (Odds Ratio: 1.18, 95% CI: 1.04–1.35) with metabolic unhealthiness, while being a rural residence (0.83, 0.74–0.93), and having higher education (0.47, 0.39–0.58) significantly but negatively affected it. Dyslipidemia was the most frequent MetS component with a prevalence rate of 46.6% (42.1–51.1), 62.2% (60.8–63.6), 76.3% (75.1–77.5), and 83.4% (82.1–84.6) among underweight, normal weight, overweight and obese phenotypes, respectively. Conclusion BMI aside, an additional set of criteria such as metabolic markers should be taken into account to identify normal weight but metabolically unhealthy individuals. Given the highest prevalence of dyslipidemia among obese subjects, further interventions are required to raise public awareness, promote healthy lifestyles and establish lipid clinics.

Association of Metabolically Healthy and Unhealthy Obesity Phenotype with Markers Related to Obesity, Diabetes among Young, Healthy Adult Men. Analysis of MAGNETIC Study

Adipose tissue secretes many regulatory factors called adipokines. Adipokines affect the metabolism of lipids and carbohydrates. They also influence the regulation of the immune system and inflammation. The current study aimed to evaluate the association between markers related to obesity, diabesity and adipokines and metabolically healthy and unhealthy obesity in young men. The study included 98 healthy participants. We divided participants into three subgroups based on body mass index and metabolic health definition: 49 metabolically healthy normal-weight patients, 27 metabolically healthy obese patients and 22 metabolically unhealthy obese patients. The 14 metabolic markers selected were measured in serum or plasma. The analysis showed associations between markers related to obesity, diabesity and adipokines in metabolically healthy and unhealthy obese participants. The decreased level of adipsin (p < 0.05) was only associated with metabolically healthy obesity, not with metabolically unhealthy obesity. The decreased level of ghrelin (p < 0.001) and increased level of plasminogen activator inhibitor-1 (p < 0.01) were only associated with metabolically unhealthy obesity, not with metabolically healthy obesity. The decreased level of adiponectin and increased levels of leptin, c-peptide, insulin and angiopoietin-like 3 protein were associated with metabolically healthy and unhealthy obesity. In conclusion, our data show that metabolically healthy obesity was more similar to metabolically unhealthy obesity in terms of the analyzed markers related to obesity and diabesity.

Metabolically healthy obesity was significantly associated with increased risk of gallstones

Objective The risk of gallstones among metabolically healthy obesity (MHO) individuals is largely unexplored. Therefore, the present study investigated the association between MHO and gallstones in a health check-up cohort of Chinese adults. Design A prospective cohort study. Methods Participants included 58,862 individuals from the MJ health check-up cohort aged ≥ 18 years without history of gallstones at baseline. Gallstones were diagnosed using abdominal B-type ultrasound. Metabolically healthy was defined as not having any one of the components of metabolic syndrome. Obesity was identified by body mass index (BMI) and waist circumference (WC). Participants were cross-classified at baseline by metabolic health and obesity. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of gallstones across BMI categories were estimated with Cox proportional hazard regression models. Results During a median follow-up of 3.0 (interquartile range, 1.6-6.1) years, 1,269 participants developed gallstones. Individuals with MHO (HR: 1.95, 95% CI: 1.23, 3.09 for BMI criteria; HR: 1.74, 95% CI: 1.37, 2.21 for WC criteria) had significantly higher risk of gallstones than those with metabolically healthy normal weight. In metabolically healthy individuals, BMI and WC both displayed linear dose-response relationships with gallstones (P for non-linearity > 0.05). The association between MHO and gallstones remained unchanged when using different criteria for metabolic health and obesity. Conclusions MHO was significantly associated with gallstones, suggesting that obesity can independently contribute to gallstones development, even among metabolically healthy individuals. These findings emphasize that metabolically healthy individuals may still benefit from maintaining normal body weight to prevent gallstones.

Proteomic and Metabolomic Characterization of Metabolically Healthy Obesity: A Descriptive Study from a Swedish Cohort

Background/Aims. Obesity is a well-established risk factor for the development of numerous chronic diseases. However, there is a small proportion of obese individuals that seem to escape these aforementioned conditions—Metabolically Healthy Obesity (MHO). Our aim was to do a metabolic and biomarker profiling of MHO individuals. Method. Associations between different biomarkers (proteomics, lipidomics, and metabolomics) coupled to either MHO or metabolically unhealthy obese (MUO) individuals were analyzed through principal component analysis (PCA). Subjects were identified from a subsample of 416 obese individuals, selected from the Malmö Diet and Cancer study—Cardiovascular arm (MDCS-CV, n = 3,443). They were further divided into MHO (n = 143) and MUO (n = 273) defined by a history of hospitalization, or not, at baseline inclusion, and nonobese subjects (NOC, n = 3,027). Two distinctive principle components (PL2, PP5) were discovered with a significant difference and thus further investigated through their main loadings. Results. MHO individuals had a more metabolically favorable lipid and glucose profile than MUO subjects, that is, lower levels of traditional blood glucose and triglycerides, as well as a trend of lower metabolically unfavorable lipid biomarkers. PL2 (lipidomics, p = 0.02 ) showed stronger associations of triacylglycerides with MUO, whereas phospholipids correlated with MHO. PP5 (proteomics, p = 0.01 ) included interleukin-1 receptor antagonist (IL-1ra) and leptin with positive relations to MUO and galanin that correlated positively to MHO. The group differences in metabolite profiles were to a large extent explained by factors included in the metabolic syndrome. Conclusion. Compared to MUO individuals, corresponding MHO individuals present with a more favorable lipid metabolic profile, accompanied by a downregulation of potentially harmful proteomic biomarkers. This unique and extensive biomarker profiling presents novel data on potentially differentiating traits between these two obese phenotypes.