Volume 2, Issue 1 (February 2017)                   JNFS 2017, 2(1): 85-86 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Shahraki M. In Search of the Best Candidate for Detection of Metabolically Obese Normal-Weight Phenotype. JNFS. 2017; 2 (1) :85-86
URL: http://jnfs.ssu.ac.ir/article-1-56-en.html
PhD Department of Nutrition, School of Medicine & Children and Adolescent Health Research Center, Zahedan University of Medical Sciences, Zahedan, Iran
Full-Text [PDF 266 kb]   (224 Downloads)     |   Abstract (HTML)  (664 Views)
Full-Text:   (6 Views)
 
In Search of the Best Candidate for Detection of Metabolically
Obese Normal-Weight Phenotype

 
Mansour Shahraki; PhD1
 
1 Department of Nutrition, School of Medicine & Children and Adolescent Health Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
 
ARTICLE INFO    
LETTER to the EDITOR    Corresponding author:
Department of Nutrition , School of Medicine &  Children and Adolescent Health Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
shahrakimansour@yahoo.com
 
Postal code: 981674315
Tel: +98 9155421310
Article history:
Received: 25 Nov 2016
Revised: 27 Dec 2016
Accepted: 20 Jan 2017
 
 
 
Nowadays, it is widely accepted that obese individuals have a worse metabolic profile than their normal weight counterparts. Despite this fact, there is a subgroup of non-obese individuals who represent some metabolic abnormalities such as high visceral adiposity, dyslipidemia, hyper insulinemia, or hypertension (Teixeira et al., 2015). These individuals who are entitled as Metabolically Obese Normal-Weight (MONW), like the obese subjects, have more susceptibility to obesity-associated disorders such as cardiovascular diseases and diabetes mellitus (Aung et al., 2014). The global prevalence of MONW phenotype is estimated at 20 % among adults (Wang et al., 2015). In Iranian population, the prevalence of this phenotype was reported 9.9 % and 11% in adults men and women, respectively (Hadaegh et al., 2007). Also, in the
first issue of JNFS, a study by Karandish et al., had nicely addressed the distribution of metabolic abnormalities among Iranian pediatrics with different obesity phenotypes. They reported that 5.4 % of participants were MONW phenotype and had a higher percentage of abnormalities in triglycerides (TG) and high density lipoprotein cholesterol (HDL-c) levels compared to individuals with other obesity phenotypes (Karandish et al., 2016).
Individuals with MONW phenotype are typically not considered at high risk of cardiometabolic disorders due to the normal values of body mass index (BMI). Although, a potential limitation of BMI is the lack of ability to distinguish fat mass, which is generally elevated in MONW subjects, from fat free mass (Wells and Fewtrell, 2006). Therefore, searching for new indices that can cover the limitations of BMI in the identification of MONW phenotype is necessary. Previous reports have shown a positive correlation between body fat percentage and abnormal metabolic profile in individuals with MONW phenotype. They suggested that body fat percentage measured by dual-energy x-ray absorptiometry or bioelectrical impedance analysis is a good indicator of MONW phenotype (Marques-Vidal et al., 2010, Shea et al., 2012). While these methods estimate fat mass more precisely than others, they usually have strict procedures to follow which may limit their usefulness for routine screening programs (Wells and Fewtrell, 2006). Recently, a study by Du et al., assessed the predictive value of two new indices including lipid accumulation product (LAP) and visceral adiposity index (VAI) for identification of MONW individuals. A combination of Waist Circumference (WC) and TG values were used to calculate LAP index. While VAI was calculated based on using both metabolic profile (TG and HDL-C) and anthropometric indices (BMI and WC) values. The researchers found a strong correlation  between both LAP and VAI with  MONW phenotype regardless of  different diagnosis criteria of the phenotype (Du et al., 2015) .In addition, Hosseinpanah et al., showed that LAP index was a strong predictor of cardiovascular risk factors among a  large group of Iranian adults with normal weight (Hosseinpanah et al., 2016).
Taken together, findings from aforementioned studies can partially answer the question of which index or indices have more ability to detect individuals with MONW phenotype. Due to the novelty of this topic, more researches are demanded especially among children, as it was noted that early-age health conditions can potentially affect the progression of atherosclerotic cardiovascular events during adulthood (Karandish et al., 2016). It is reported that MONW individuals, generally response better to the therapeutic lifestyle changes including dietary modifications and physical activity engagement compared to the obese subjects (Teixeira et al., 2015). Therefore, it is promising that early identification of MONW individuals by using an appropriate method will help health professionals to implement effective interventions at early stages to reduce or prevent from the progression of metabolic disorders among these high risk individuals.
 
References

Aung K, Lorenzo C, Hinojosa MA & Haffner SM 2014. Risk of developing diabetes and cardiovascular disease in metabolically unhealthy normal-weight and metabolically healthy obese individuals. The Journal of clinical endocrinology and metabolism. 99 (2): 462-468.
Du T, Yu X, Zhang J & Sun X 2015. Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype. Acta diabetologica. 52 (5): 855-863.
Hadaegh F, Zabetian A, Harati H & Azizi F 2007. Metabolic syndrome in normal-weight Iranian adults. Annals of Saudi medicine. 27 (1): 18-24.
Hosseinpanah F, et al. 2016. Lipid accumulation product and incident cardiovascular events in a normal weight population: Tehran Lipid and Glucose Study. European journal of preventive cardiology. 23 (2): 187-193.
Karandish M, Hosseinpour M, Rashidi H, Latifi SM & Moravej Aleali A 2016. Comparison of Components of Metabolic Syndrome among Metabolically Obese Normal Weight, Metabolically Benign Normal Weight, and Metabolically Abnormal Obese Iranian Children and Adolescents in Ahvaz. Journal of Nutrition and Food Security. 1 (1): 9-15.
Marques-Vidal P, et al. 2010. Normal weight obesity: relationship with lipids, glycaemic status, liver enzymes and inflammation. Nutrition, metabolism, and cardiovascular diseases : NMCD. 20 (9): 669-675.
Shea JL, King MT, Yi Y, Gulliver W & Sun G 2012. Body fat percentage is associated with cardiometabolic dysregulation in BMI-defined normal weight subjects. Nutrition, metabolism, and cardiovascular diseases : NMCD. 22 (9): 741-747.
Teixeira TF, Alves RD, Moreira AP & Peluzio Mdo C 2015. Main characteristics of metabolically obese normal weight and metabolically healthy obese phenotypes. Nutrition reviews. 73 (3): 175-190.
Wang B, et al. 2015. Prevalence of Metabolically Healthy Obese and Metabolically Obese but Normal Weight in Adults Worldwide: A Meta-Analysis. Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme. 47 (11): 839-845.
Wells JC & Fewtrell MS 2006. Measuring body composition. Archives of disease in childhood. 91 (7): 612-617.
Type of article: letter to the editor | Subject: public specific
Received: 2016/11/25 | Accepted: 2017/01/21 | Published: 2017/02/1

References
1. Aung K, Lorenzo C, Hinojosa MA & Haffner SM 2014. Risk of developing diabetes and cardiovascular disease in metabolically unhealthy normal-weight and metabolically healthy obese individuals. The Journal of clinical endocrinology and metabolism. 99 (2): 462-468.
2. Du T, Yu X, Zhang J & Sun X 2015. Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype. Acta diabetologica. 52 (5): 855-863.
3. Hadaegh F, Zabetian A, Harati H & Azizi F 2007. Metabolic syndrome in normal-weight Iranian adults. Annals of Saudi medicine. 27 (1): 18-24.
4. Hosseinpanah F, et al. 2016. Lipid accumulation product and incident cardiovascular events in a normal weight population: Tehran Lipid and Glucose Study. European journal of preventive cardiology. 23 (2): 187-193.
5. Karandish M, Hosseinpour M, Rashidi H, Latifi SM & Moravej Aleali A 2016. Comparison of Components of Metabolic Syndrome among Metabolically Obese Normal Weight, Metabolically Benign Normal Weight, and Metabolically Abnormal Obese Iranian Children and Adolescents in Ahvaz. Journal of Nutrition and Food Security. 1 (1): 9-15.
6. Marques-Vidal P, et al. 2010. Normal weight obesity: relationship with lipids, glycaemic status, liver enzymes and inflammation. Nutrition, metabolism, and cardiovascular diseases : NMCD. 20 (9): 669-675.
7. Shea JL, King MT, Yi Y, Gulliver W & Sun G 2012. Body fat percentage is associated with cardiometabolic dysregulation in BMI-defined normal weight subjects. Nutrition, metabolism, and cardiovascular diseases : NMCD. 22 (9): 741-747.
8. Teixeira TF, Alves RD, Moreira AP & Peluzio Mdo C 2015. Main characteristics of metabolically obese normal weight and metabolically healthy obese phenotypes. Nutrition reviews. 73 (3): 175-190.
9. Wang B, et al. 2015. Prevalence of Metabolically Healthy Obese and Metabolically Obese but Normal Weight in Adults Worldwide: A Meta-Analysis. Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme. 47 (11): 839-845.
10. Wells JC & Fewtrell MS 2006. Measuring body composition. Archives of disease in childhood. 91 (7): 612-617.

Add your comments about this article : Your username or Email:
CAPTCHA code

© 2015 All Rights Reserved | Journal of Nutrition and Food Security

Designed & Developed by : Yektaweb