Predictors of incident obesity phenotype in nonobese healthy adults

Association of Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet and metabolically unhealthy overweight/obesity phenotypes among Iranian women: a cross sectional study

PURPOSE

Paradoxes have been found in obesity, including individuals with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO), and diet may be one of the reasons for the creation of these metabolic phenotypes. Hence, the purpose of the present study was to investigate the association of the Mediterranean-DASH intervention for neurodegenerative delay (MIND) diet with metabolically unhealthy overweight/obesity (MUHOW/O) phenotypes.

METHODS

In this cross-sectional study, 229 overweight and obese women (body mass index (BMI) ≥ 25 kg/m2) aged 18-48 years were examined. Anthropometric measures and biochemical parameters were collected from all participants. The body composition of each participant was assessed using a bioelectrical impedance analyzer (BIA). The MIND diet score was determined based on 15 components using a valid and reliable food frequency questionnaire (FFQ) containing 147 items. Karelis criteria was used to determine metabolically healthy/unhealthy phenotype (MH/MUH).

RESULTS

Among the participants, 72.5% of individuals were identified as MUH and 27.5% as MH, with a mean ± standard deviation (SD) age of 36.16 (8.33) years. The results of our analysis showed that after controlling for age, energy intake, BMI, and physical activity, there was no significant association observed between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.01, 95% CI: 0.86-4.17, P-value = 0.10), T3 (OR: 1.89, 95% CI: 0.86-4.17, P-value = 0.11) of MIND score, and only the odds of MUH relative to MH with a marginal significant decreasing trend was observed from the second to the third tertile (1.89 vs. 2.01) (P - trend = 0.06). Also, after additional adjustment for marital status, the nonsignificant association between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.13, 95% CI: 0.89-5.10, P-value = 0.08), T3 (OR: 1.87, 95% CI: 0.83-4.23, P-value = 0.12) of MIND score remained, and the odds of MUH relative to MH with a significant decreasing trend was observed with increasing tertiles (P-trend = 0.04).

CONCLUSIONS

In conclusion, no significant associations were found between adherence to MIND diet with MUH, and only a significant downward trend in the odds of MUH was observed with increasing tertiles. We suggest further studies in this field.

Associations between Breastfeeding Duration and Obesity Phenotypes and the Offsetting Effect of a Healthy Lifestyle

Background: Additional metabolic indicators ought to be combined as outcome variables when exploring the impact of breastfeeding on obesity risk. Given the role of a healthy lifestyle in reducing obesity, we aimed to assess the effect of breastfeeding duration on different obesity phenotypes according to metabolic status in children and adolescents, and to explore the offsetting effect of healthy lifestyle factors on the associations between breastfeeding duration and obesity phenotypes. Methods: A total of 8208 eligible children and adolescents aged 7–18 years were recruited from a Chinese national cross-sectional study conducted in 2013. Anthropometric indicators were measured in the survey sites, metabolic indicators were tested from fasting blood samples, and breastfeeding duration and sociodemographic factors were collected by questionnaires. According to anthropometric and metabolic indicators, obesity phenotypes were divided into metabolic healthy normal weight (MHNW), metabolic unhealthy normal weight (MUNW), metabolic healthy obesity (MHO), and metabolic unhealthy obesity (MUO). Four common obesity risk factors (dietary consumption, physical activity, screen time, and sleep duration) were used to construct a healthy lifestyle score. Scores on the lifestyle index ranged from 0 to 4 and were further divided into unfavorable lifestyles (zero or one healthy lifestyle factor), intermediate lifestyles (two healthy lifestyle factors), and favorable lifestyle (three or four healthy lifestyle factors). Multinomial logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (95% CI) for the associations between breastfeeding duration and obesity phenotypes. Furthermore, the interaction terms of breastfeeding duration and each healthy lifestyle category were tested to explore the offsetting effect of lifestyle factors. Results: The prevalence of obesity among Chinese children and adolescents aged 7–18 years was 11.0%. Among the children and adolescents with obesity, the prevalence of MHO and MUO was 41.0% and 59.0%, respectively. Compared to the children and adolescents who were breastfed for 6–11 months, prolonged breastfeeding (≥12 months) increased the risks of MUNW (OR = 1.35, 95% CI: 1.19–1.52), MHO (OR = 1.61, 95% CI: 1.27–2.05), and MUO (OR = 1.46, 95% CI: 1.20–1.76). When stratified by healthy lifestyle category, there was a typical dose–response relationship between duration of breastfeeding over 12 months and MUNW, MHO, and MUO, with an increased risk of a favorable lifestyle moved to an unfavorable lifestyle. Conclusions: Prolonged breastfeeding (≥12 months) may be associated with increased risks of MUNW, MHO, and MUO, and the benefits of breastfeeding among children and adolescents may begin to wane around the age of 12 months. The increased risks may be largely offset by a favorable lifestyle.

Bifidobacterium animalis subsp. lactis BB-12 Has Effect Against Obesity by Regulating Gut Microbiota in Two Phases in Human Microbiota-Associated Rats

Bifidobacterium animalis subsp. lactis BB-12 (BB-12) is an extensively studied probiotics species, which has been reported to improve the human gut microbiota. This study aimed to confirm the effects of BB-12 on high-fat diet (HFD)-induced gut microbiota disorders. The probiotic BB-12 was consumed by human microbiota-associated rats and changes in gut microbiota were compared using next generation sequencing of the fecal samples collected from the normal chow group, the HFD group, and the BB-12-supplemented group. The enterotypes switched from Prevotella dominant to Akkermansia dominant as a result of switching diet from normal chow to HFD. BB-12 conferred protection on the gut microbiota composition of the rats by increasing the abundance of Prevotella and decreasing the abundance of Clostridium, Blautia, and Bacteroides in 0-3 weeks. In addition, Prevotella-dominant enterotype was maintained, which provides improve obesity effects. A decrease in body weight and the Firmicutes/Bacteroidetes ratio were also observed at week 3. While in 4-8 weeks, the enrichment of short-chain fatty acids-producing bacteria such as Eubacterium and Parabacteroides and probiotics such as Bifidobacterium was observed. The results revealed that BB-12 against obesity by regulating gut microbiota in two phases. After a short-term intervention, BB-12 supplementation suppressed the transition from the healthy to obesity state by protecting Prevotella-dominant enterotype, whereas after a long-term intervention, BB-12 ameliorates obesity by enriching beneficial bacteria in the gut.

Incidence of Obesity at 1 and 3 Years Among Community Dwelling Adults: A Population-Based Study

OBJECTIVE

This study determined the incidence rates for obesity among adult patients ages 20 and older empaneled in primary care practice in Midwest United States to potentially identify an optimum timeframe for initiating intervention.

BACKGROUND

Primary care practice patients are likely to reflect underlying community trends in overweight and obesity; however, data on overweight and obesity in primary care patients is limited. While childhood incidence rates of obesity have been well reported, there is still a paucity of data on the incidence of obesity among adult population; literature has mainly focused on its prevalence.

METHODS

Medical record review of identified cohort with BMI data was conducted. Population was stratified by age and sex and overweight category was subdivided into tertiles.

RESULTS

Majority of 40 390 individuals who comprised the final population and had follow-up data, consisted of adults ages 40 to 69 years (47.5%), female (59.8%) of non-Hispanic ethnicity (95.9%) with 21 379 (52.8%) falling in weight category of overweight. Incidence of obesity was 7% at 1 year and 16% at 3 years follow-up. Highest percentages of individuals who became obese at 1 and 3 years were in age category of 40 to 69 years among men and 20 to 39 years among women. In Cox regression analysis, there was statistically significant association to developing obesity among all tertile groups in the overweight category. Age and particularly gender appeared to be modifying factors to likelihood of developing obesity.

CONCLUSION

Study results suggest that while obesity incidence is higher among certain age groups in both genders, middle-aged women, and men in all tertiles of overweight category are at highest risk and may be the optimum population to target for weight loss interventions. Findings support the initiation of population-based interventions before onset of obesity.

Gut microbiota of adults with different metabolic phenotypes

OBJECTIVE

The aim of this study was to investigate the gut microbiota of individuals with different metabolic phenotypes and to compare their characteristics.

METHODS

This was a cross-sectional study with 109 adults, classified according to metabolic status, by body mass index, and homeostasis model assessment. Anthropometric and biochemical characteristics and blood pressure were evaluated. Level of physical activity was evaluated by means of a questionnaire, and dietary consumption was evaluated using a 3-d food record. Feces samples were collected from each participant, and gut microbiota profile was analyzed by sequencing of the 16S rRNA gene. The Kruskal-Wallis and χ² tests were used, according to the scale of measurement of the variables, on the statistical program SPSS version 25, with significance level of 5%.

RESULTS

Significantly lower values of saturated fat intake and fasting glycemia were observed in metabolically healthy individuals who were overweight and obese compared with their unhealthy counterparts. Diversity and richness of bacterial communities were lower in individuals who were obese and in the unhealthy phenotype. The genus Eubacterium rectale and genera of the family Prevotellaceae were more abundant in the metabolically healthy obese and metabolically healthy overweight groups than in the metabolically healthy normal weight one, whereas Bifidobacterium was more abundant in the metabolically healthy normal weight group. The genera Coprococcus and Ruminococcus were more abundant in the metabolically healthy overweight group than in the metabolically unhealthy overweight one.

CONCLUSIONS

We observed distinct characteristics in the gut microbiota of different metabolic phenotypes. The intestines of individuals with unhealthy phenotypes hosted inflammation-associated microbiota, with lower butyrate production potential and reduced bacterial diversity.

The Association Between Different Obesity Phenotypes and Liver Fibrosis Scores in Elderly Individuals with Fatty Liver in Taiwan

PURPOSE

To examine the association between different phenotypes of obesity or metabolic syndromes and liver fibrosis score in a Taiwanese elderly population with fatty liver.

PATIENTS AND METHODS

This cross-sectional study included 1817 participants aged ≥65 years with fatty liver diagnosed by sonography. We used ethnicity-specific criteria for body mass index and metabolic syndrome, and to define obesity phenotypes as metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Correlated fibrosis severity was calculated using the nonalcoholic fatty liver disease (NAFLD) fibrosis score (NFS) and Fibrosis-4 (FIB-4). Fibrosis severity was divided into two categories according to NFS (no-to-mild fibrosis and advanced fibrosis, defined as NFS ≤ 0.676 and >0.676, respectively) and FIB-4 score (no-to-mild fibrosis and advanced fibrosis, defined as FIB-4 score ≤2.67 and >2.67, respectively).

RESULTS

Compared with that in the MHNO group, the associated risk (odds ratio [OR], 95% confidence interval [CI]) of advanced fibrosis by NFS was 2.43 (1.50-3.93), 2.35 (1.25-4.41), and 6.11 (3.90-9.59), whereas that of advanced fibrosis by FIB-4 score was 1.34 (0.83-2.18), 2.37 (1.36-4.13), and 1.38 (0.82-2.31) in the MUNO, MHO, and MUO groups, respectively.

CONCLUSION

Both metabolic syndrome and obesity were positively associated with more advanced fibrosis according to NFS. The detrimental effect of obesity appears to be more than metabolic abnormalities per se in the elderly with more advanced fibrosis severity according to the FIB-4 score.

Transition Patterns of Weight Status and Their Predictive Lipid Markers Among Chinese Adults: A Longitudinal Cohort Study Using the Multistate Markov Model

BACKGROUND

Obesity is well recognized as a risk factor for cardiometabolic diseases. The development of obesity is a dynamic process that can be described as a multistate process with an emphasis on transitions between weight states. However, it is still unclear what convenient biomarkers predict transitions between weight states. The aim of this study was to show the dynamic nature of weight status in adults stratified by age and sex and to explore blood markers of metabolic syndrome (MetS) that predict transitions between weight states.

METHODS

This study involved 9795 individuals aged 18 to 56 at study entry who underwent at least two health check-ups in the eight-year period of study in the health check-up centre of our institution. Weight, height and biochemical indices were measured at each check-up. The participants were divided into four groups based on age and sex (young male, middle-aged male, young female and middle-aged female groups). A multistate Markov model containing 3 states (healthy weight, overweight and obesity) was adopted to study the longitudinal weight data.

RESULTS

Young people were more likely to transit between weight states than middle-aged people, and middle-aged people were more resistant to recover from worse states. The mean sojourn time in obesity was greatest in the middle-aged male group (6.23 years), and the predicted rate of obesity beginning with healthy weight was greatest in the young male group (13.7%). In multivariate models, age group and triglyceride (TG) and high-density lipoprotein cholesterol (HDL) levels were significant for specific transitions in females, whereas age group and HDL levels were significant in males. In females, if HDL levels increased 1 mmol/L, the probability of progression from healthy weight to overweight decreased by 37.0% (HR= 0.63), and the probabilities of recovery (overweight to healthy weight and obesity to overweight) increased by 62.0% (HR= 1.62) and 1.23-fold (HR= 2.23), respectively. In males, if TG levels increased 1 mmol/L, the risk of progression from healthy weight to overweight increased by 24.0% (HR= 1.24). Each unit increase in HDL levels was associated with a 0.99-fold (HR= 1.99) increase in the chance of recovery from overweight to healthy weight and with a 0.37-fold (HR= 0.63) decrease in the risk of progression from healthy weight to overweight.

CONCLUSION

The weight status of young people was less stable than that of middle-aged people. Males were more likely to become overweight and more resistant to recover from worse states than females. Young males with healthy weight were more likely to develop obesity than other healthy weight groups. Blood lipid levels, especially HDL, were predictors of weight transitions in adults. Prevention and intervention measures should be applied early.

Genetic markers and continuity of healthy metabolic status: Tehran cardio-metabolic genetic study (TCGS)

Obese individuals can be categorized as “healthy obese” (MHO) and “unhealthy obese” (MUO) based on the presence or absence of metabolic abnormality. This study sets out to assess potential genetic causes behind persistence of healthy metabolic status in individuals categorized as “healthy obese”. This study was conducted in the framework of the Tehran cardio-metabolic genetic study (TCGS). 766 MHO subjects at the start of the study followed up 15 years for occurrence of metabolic unhealthy status. These two groups (persistent MHO, MUO) were compared regarding the presence or absence of 16 single nucleotide polymorphisms (SNPs) identified as being associated with obesity phenotype in previous studies. We used logistic regression model for assessing the association between MHO/MUO with candidate SNPs. By the end of the follow up, 206 (27%) were categorized as the persistent MHO and 560 (73%) as MUO groups. Considering interaction effect between some SNP and sex, a sex stratification analysis was applied. When the analysis was performed by gender, rs1121980 associated with a decrease, and rs7903146 with an increase in the likelihood of persistent MHO individuals. Another analysis was separately performed on postmenopausal women from both groups; it showed that rs13107325 was associated with an increase in the likelihood of persistent MHO status in this subgroup of woman. In all cases, the markers had dominant inheritance. This findings suggest that the expression of some genetic markers are associated with persistence of healthy metabolic status, in female obese individuals.

Dietary determinants of unhealthy metabolic phenotype in normal weight and overweight/obese adults: results of a prospective study

We aimed to investigate associations of dietary intakes with unhealthy metabolic phenotype development, in normal weight and overweight/obese adults separately. A total of 1114 individuals, aged ≥19 years, with healthy phenotype in the third examination cycle of Tehran Lipid and Glucose Study were followed until the fifth examination. Dietary intakes were estimated using the food frequency questionnaires, collected during the study. The participants were grouped as normal weight and overweight/obese according to the baseline body mass index (BMI). Unhealthy metabolic status was determined as having more than one component of metabolic syndrome using the Joint Interim Statement. Regardless of BMI, higher intakes of magnesium, dairy products, poultry, apples/pears, citrus fruits, and tea/coffee decreased the risk of developing unhealthy phenotype, while higher intakes of fast foods, organ meats, and potatoes increased the risk. Food intake can influence the transition to unhealthy phenotype in metabolically healthy adults, irrespective of the BMI status.

The association of Dietary Approach to Stop Hypertension (DASH) diet with metabolic healthy and metabolic unhealthy obesity phenotypes

The current study aimed at investigating the association between Dietary Approach to Stop Hypertension (DASH) diet and odds of obesity phenotypes, is a cross sectional study conducted on 3218 Iranian overweight or obese participants (BMI >25 kg/m²), aged ≥20 years, who participated in the fourth phase (2009–2011) of the Tehran Lipid and Glucose Study. Using a valid and reliable food-frequency questionnaire, DASH diet scores between 8 and 40 points were determined. Obesity phenotypes including metabolic unhealthy obesity (MUHO) and metabolic healthy obesity (MHO) were defined using criteria of the Joint International statement(JIS) for metabolic syndrome. Multivariable logistic regression was used to determine the odds ratio (OR) for obesity phenotypes according to the tertiles of the DASH diet. Mean ± SD age of participants (43.5% male) was 39.2 ± 9.5 years and median (25–75 interquartile range) DASH diet score was 24 (21–27); percentages of MHO and MUHO subjects were 33.4 and 66.6%, respectively. In the multivariable adjusted model, after controlling for age, sex, BMI, physical activity, smoking status, socioeconomic status, and energy intake, participants in the highest tertile of DASH diet had lower odds of MUHO (OR:0.79;95%CI:0.64–0.98), in comparison to those in the lowest one (P for trend = 0.040). Our findings indicate that adherence to DASH diet may be favourable in prevention of metabolic abnormalities in overweight and obese individuals.

The Relationship between Metabolically Healthy Obesity and the Risk of Cardiovascular Disease: A Systematic Review and Meta-Analysis

Cardiovascular disease (CVD) risk in individuals with metabolically healthy obesity (MHO) is unclear. We searched databases from inception to May 2019. Data were pooled using a random effects model. Newcastle-Ottawa Scale assessment was performed. Primary and secondary outcomes were CVD risk and all-cause mortality. Forty-three studies involving 4,822,205 cases were included. The median percentage of females, age and duration of follow-up was 52%, 49.9 years and 10.6 years, respectively. The mean Newcastle-Ottawa Scale score of the articles was 7.9 ± 1.0. Compared to individuals with a metabolically healthy normal weight, individuals with MHO had higher adjusted risk of CVD and all-cause mortality. We identified a significant linear dose-response relationship between body mass index (BMI) and CVD risk among metabolically healthy individuals (p < 0.001); every unit increase in BMI increased the CVD risk. Multivariate meta-regression analysis showed that an increased proportion of women and age resulted in the risk of CVD affected by MHO reduction (p = 0.014, p = 0.030, respectively). Age and sex explained the observed heterogeneity and reported the adjusted R². MHO resulted in a significantly increased risk for CVD; therefore, long-term weight loss should be encouraged.

Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population

The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). The analysis was performed in two stages (training and test sets). Model A was designed with only clinical information (age, sex, body mass index, smoking status, alcohol consumption status, and exercise status), and for model B, genetic information (for 10 polymorphisms) was added to model A. Of the 7,502 nonobese participants, 647 (8.6%) had MS. In the test set analysis, for the maximum sensitivity criterion, NB showed the highest sensitivity: 0.38 for model A and 0.42 for model B. The specificity of NB was 0.79 for model A and 0.80 for model B. In a comparison of the performances of models A and B by NB, model B (area under the receiver operating characteristic curve [AUC] = 0.69, clinical and genetic information input) showed better performance than model A (AUC = 0.65, clinical information only input). We designed a prediction model for MS in a nonobese population using clinical and genetic information. With this model, we might convince nonobese MS individuals to undergo health checks and adopt behaviors associated with a preventive lifestyle.