Comparison of Metabolic Characteristics of Metabolically Healthy but Obese (MHO) Middle-Aged Men According to Different Criteria

Yoo, Ho Kwon; Choi, Eun Young; Park, Eal Whan; Cheong, Yoo Seock; Bae, Ri Ah

doi:10.4082/kjfm.2013.34.1.19

Cited by 38 publications

(34 citation statements)

References 12 publications

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“…The prevalence of obesity phenotypes varied considerably with age in the current study. This was not in agreement with a study focusing on middle-aged men from Yoo et al [48]. One explanation for this inconsistency might be the age difference.…”

Section: Discussioncontrasting

confidence: 96%

The Prevalence of Metabolically Healthy and Unhealthy Obesity according to Different Criteria

et al. 2019

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Objective: Obesity-related disease risks may vary depending on whether the subject has metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO). At least 5 definitions/criteria of obesity and metabolic disorders have been documented in the literature, yielding uncertainties in a reliable international comparison of obesity phenotype prevalence. This report aims to compare differences in MHO and MUO prevalence according to the 5 most frequently used definitions. Methods: A random sample of 4,757 adults aged 35 years and older (male 51.1%) was enrolled. Obesity was defined either according to body mass index or waist circumference, and the definitions of metabolic abnormalities were derived from 5 different criteria. Results: In MHO, the highest prevalence was obtained when using the homeostasis model assessment (HOMA) criteria (13.6%), followed by the Chinese Diabetes Society (11.4%), Adult Treatment Panel III (10.3%), Wildman (5.2%), and Karelis (4.2%) criteria; however, the MUO prevalence had an opposite trend to MHO prevalence. The magnitude of differences in the age-specific prevalence of MHO and MUO varied greatly and ranked in different orders. The proportion of insulin resistance for MHO and MUO individuals differed significantly regardless of which metabolic criterion was used. Conclusion: The prevalence of MHO and MUO in the Chinese population varies according to different definitions of obesity and metabolic disorders.

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Section: Discussioncontrasting

confidence: 96%

The Prevalence of Metabolically Healthy and Unhealthy Obesity according to Different Criteria

et al. 2019

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“…6 Nevertheless, people vary in their susceptibility to the cardio-metabolic consequences of excessive weight gain. 7,8 Hypertriglyceridemia is a heritable trait, with sib-pair concordance of ≈0. 18 9 and broad-sense heritability estimates of ≈0.72 in younger twins and ≈0.28 in older twins.…”

mentioning

confidence: 99%

Do Genetic Factors Modify the Relationship Between Obesity and Hypertriglyceridemia?

Ali

Varga

Stojkovic

et al. 2016

Circ Cardiovasc Genet

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M ore than 600 million people are estimated to be obese worldwide, 1 which is thought to be primarily a consequence of lifestyles characterized by consumption of energy-dense foods with poor nutritional content and lack of physical activity in the workplace and at home. The high prevalence of obesity is of considerable concern owing to the plethora of its life-threatening sequelae, including type 2 diabetes mellitus, coronary heart disease, and cerebrovascular disease.2 Accumulation of triglycerides in adipose, muscle, liver, and blood cells can impair cellular insulin action and glucose uptake and promote the accumulation of atherosclerotic arterial plaques.3,4 Therefore, elevated triglycerides and triglyceride-rich lipoproteins are important intermediate risk factors for type 2 diabetes mellitus and are causal Background-Obesity is a major risk factor for dyslipidemia, but this relationship is highly variable. Recently published data from 2 Danish cohorts suggest that genetic factors may underlie some of this variability. was associated with 1.5% higher triglyceride concentrations in normal weight and 2.4% higher concentrations in overweight/obese participants (P interaction =0.056). Meta-analyses of results from the Swedish cohorts yielded a statistically significant WGRS TG ×BMI interaction effect (P interaction =6.0×10 -4 ), which was strengthened by including data from the Danish cohorts (P interaction =6.5×10 -7 ). In the meta-analysis of the Swedish cohorts, nominal evidence of a 3-way interaction (WGRS TG ×BMI×sex) was observed (P interaction =0.03), where the WGRS TG ×BMI interaction was only statistically significant in females. Using protein-protein interaction network analyses, we identified molecular interactions and pathways elucidating the metabolic relationships between BMI and triglyceride-associated loci. Conclusions-Our findings provide evidence that body fatness accentuates the effects of genetic susceptibility variants in hypertriglyceridemia, effects that are most evident in females. (Circ Cardiovasc Genet. 2016;9:162-171.

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“…Physical activity influences the prevalence of a healthy cardiometabolic profile (Velho et al, 2010;Wildman, 2009;Yoo et al, 2013). Moderate regular physical activity is associated with higher insulin sensitivity, an improved lipid profile, and a decrease in components of metabolic syndrome (Caro et al, 2013) and this fact can explain the lower probability of being obese and metabolically not healthy among women who practice any kind of physical exercise.…”

Section: Discussionmentioning

confidence: 99%

Healthy excessive weight in Portuguese women 4years after delivery of a liveborn

Henriques

Santos

Guimarães

et al. 2015

Preventive Medicine

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Objective. To quantify the prevalence of healthy excessive weight and determinants of metabolic profile, considering women's reproductive life.Methods. We evaluated 1847 mothers of a birth cohort assembled after delivery and reevaluated 4 years later. A healthy profile was defined as the absence of hypertension, diabetes, dyslipidemia, C-reactive protein b 3 mg/l and being below the second tertile of HOMA-IR. Adjusted odds ratios (OR) and confidence intervals (95% CI) were computed using multinomial logistic regression, taking women with normal BMI as the reference category of the outcome.Results. Four years after delivery, 47% of women had normal BMI, 33% were overweight and 20% obese. In each BMI class, 61%, 33% and 12% presented a healthy metabolic profile, respectively. Family history of CVD/ cardiometabolic risk factors was associated with a higher probability of obesity with a not healthy metabolic profile (OR = 1.39 95% CI: 0.98-1.98). Women who breastfed the enrolled child for N 26 weeks and practiced physical exercise were less likely to be obese and metabolically unhealthy (OR = 0.39 95% CI: 0.23-0.68; OR = 0.48 95% CI: 0.33-0.70, respectively), with no effect on healthy excessive weight.Conclusions. These results support the existence of a healthy excessive weight phenotype in women after motherhood, influenced by anthropometrics, genetic and lifestyles characteristics.

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Comparison of Metabolic Characteristics of Metabolically Healthy but Obese (MHO) Middle-Aged Men According to Different Criteria

Cited by 38 publications

References 12 publications

The Prevalence of Metabolically Healthy and Unhealthy Obesity according to Different Criteria

The Prevalence of Metabolically Healthy and Unhealthy Obesity according to Different Criteria

Do Genetic Factors Modify the Relationship Between Obesity and Hypertriglyceridemia?

Healthy excessive weight in Portuguese women 4years after delivery of a liveborn

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