Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Tabatabaei-Malazy O

PROVIDER: S-EPMC8735615 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and Objective: Functional disturbances of gastric myoelectrical activity (GMA) might exist in obesity. However, studies on its association with the gastric hormones in obesity phenotypes are lacking. The objective was to study the association of GMA with the serum levels of key gastric hormones in different obesity phenotypes. Methods: A total of 139 adults (31.00 ± 11.12 years) were classified into different metabolic phenotypes of obesity: 1) normal weight-lean (NWL group): BMI <25 kg/m2 and the fat-mass index (FMI) ≤9.7 kg/m2 in females and ≤6.3 kg/m2 in males; 2) metabolically obese normal weight (MONW group): BMI <25 kg/m2 and FMI >9.7 kg/m2 in females and >6.3 kg/m2 in males; 3) metabolically healthy obese (MHO group): BMI ≥25 and FMI ≤9.7 kg/m2 in females and ≤6.3 kg/m2 in males; and 4) metabolically unhealthy obese (MUO group): BMI ≥25 and FMI >9.7 kg/m2 in females and >6.3 kg/m2 in males. The GMA was measured at the baseline and post-prandial state using a multichannel electrogastrography with a water load satiety test. The average power distribution by the frequency region and the average dominant frequency were used for analysis. Anthropometric measurements and bioelectric impedance analysis were performed to calculate the FMI and fat-free mass index (FFMI). Serum levels of ghrelin, gastrin, and irisin were measured by ELISA kits according to the manufacturer's protocol. Results: Compared to the NWL group, gastrin and ghrelin levels were significantly low in the MUO participants, while irisin was significantly high. The EGG showed significantly lower baseline and 20-min normogastria frequencies in the MHO and MUO groups. In the MHO group, baseline duodenal frequency was positively correlated with the gastrin level, while normogastria times were positively associated with the irisin level and negatively associated with the ghrelin level. In the MUO group, percentages of bradygastria frequencies at 10, 20, and 30 min were positively correlated with the BMI and FFMI. This bradygastria was correlated positively with the irisin level and negatively with the ghrelin level. Conclusion: The EGG patterns might be associated with obesity-related gastric hormones in different obesity phenotypes. EGG may be a promising clinical tool in obesity assessment. The association of the EGG patterns with hormonal levels needs further investigation for potential practical uses.

Project description:ObjectiveRelated evidences of metabolically unhealthy profile of adults with normal weight are not well characterized in the Chinese population. This is because they cannot be effectively identified by regular measurements (such as body mass index [BMI]). To overcome this gap in literature, this study aimed at investigating the association between body composition and metabolically unhealthy profile in Chinese adults with normal weight.MethodsA total of 5427 individuals with normal-weight were recruited from 15820 people living in Ningxia Hui Autonomous Region in Northwest China. Normal-weight was defined as a BMI of 18.5-23.9 kg/m2. Metabolically unhealthy profile was assessed by the National Cholesterol Education Program Adult Treatment Panel III (ATP III). Metabolically unhealthy normal-weight (MUHNW) profile was defined in individuals who had normal weight and at least two cardiometabolic risk factors. Generalized linear model was used to investigate the association between body composition measured by bioelectrical impedance and metabolically unhealthy profile in adults with normal-weight.ResultsThe percentage of metabolically unhealthy profile was 35.86% in adults with normal weight. Different MUHNW distributions were found between males and females depending on age. The percentage of the MUHNW profile significantly increased in women after the age of 55, contrary to men. The association between body composition and MUHNW was affected by age and sex. The increased adiposity indices (fat mass index [FMI], visceral fat level [VFL], waist circumference [WCF]), and reduced skeletal muscle mass ratio [SMR] showed significant differences between MUHNW and metabolically healthy with normal weight (MHNW) (p < 0.05).ConclusionThe distribution of MUHNW differed between ages and sexes. FMI, VFL, WCF and SMR could be responsible for the MUHNW adults, providing a new insight into the potential metabolic risks for the adults with normal weight in China. This directs us in the management of the MUHNW for their early prevention.

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