Are young Iranian women with metabolically healthy obesity at increased risk of CVD incidence?

Jovens iranianas obesas metabolicamente saudáveis têm maior risco de incidência de DCV?

Seyed Ahmad Hosseini Vahideh Aghamohammadi Damoon Ashtary-Larky Meysam Alipour Matin Ghanavati Nasrin Lamuchi-Deli About the authors

Abstract

Background

The association between the Metabolically Healthy Obese (MHO) phenotype in the absence of metabolic syndrome and subsequent cardiovascular disease remains unclear.

Objectives

We examined the association between MHO and CVD risk in young Iranian women.

Methods

We studied 183 women aged 20-35 years from a population of 308 candidates. We classified participants into 4 phenotypes. We measured body composition, blood pressure, and biochemical factors in all participants.

Results

The Metabolically Healthy Normal Weight (MHNW) and Normal Weight Obese (NWO) phenotypes had no statistical differences in any biochemistry variables. FBS, TG, LDL/HDL, Cholesterol/HDL, hs-CRP, and atherogenic index of plasma (AIP) were all higher in Metabolically Unhealthy Obese (MUO) than MHO individuals, whereas HDL was higher in MHO than in MUO individuals. LDL/HDL and hs-CRP were higher in MHO participants than MHNW participants, whereas HDL-c was higher in MHNW than MHO.

Conclusions

Results of the present study demonstrate that young women displaying the MHO phenotype have a favorable metabolic profile as shown by lower FBS, TG, LDL-c/HDL, Cho/HDL, hs-CRP, and AIP and higher HDL levels than the MUO phenotype. However, MHO individuals were still at greater risk of CVD incidence (lower HDL and higher hs-CRP levels) than MHNW individuals.

Keywords:
metabolically healthy obese; atherogenic index of plasma; cardiovascular disease

Resumo

Contexto

A associação entre o fenótipo obeso metabolicamente saudável (OMS) na ausência de síndrome metabólica e doença cardiovascular subsequente permanece incerta.

Objetivos

Examinamos a associação entre o fenótipo OMS e risco de DCV em jovens iranianas.

Métodos

Analisamos 183 mulheres com idade de 20-35 anos de uma população de 308 candidatas. Classificamos as participantes em quatro fenótipos. Mensuramos composição corporal, pressão arterial e fatores bioquímicos em todas as participantes.

Resultados

Os fenótipos com peso normal metabolicamente saudável (PNMS) e obeso com peso normal não apresentaram diferenças estatísticas em nenhuma das variáveis bioquímicas. Os níveis de glicemia sanguínea em jejum (GSJ), triglicerídeos (TG), relação LDL/HDL, HDL, proteína C reativa ultrassensível (PCR-us) e índice aterogênico do plasma (IAP) foram mais elevados em obesas metabolicamente não saudáveis (OMNS) do que em indivíduos OMSs, enquanto o HDL foi maior em OMSs do que em indivíduos OMNSs. A relação LDL/HDL e o nível de PCR-us foram mais elevados em participantes OMSs do que em participantes com PNMS, enquanto o HDL foi maior naquelas com PNMS do que nas OMSs.

Conclusões

Os resultados do presente estudo demonstram que mulheres jovens com o fenótipo OMS têm um perfil metabólico favorável, conforme demonstrado pelos níveis menores de GSJ, TG, relação LDL/HDL, HDL, PCR-us e IAP e pelos níveis maiores de HDL em comparação às mulheres com o fenótipo OMNS. Entretanto, indivíduos OMSs ainda apresentavam maior risco de DCV incidente (níveis menores de HDL e maiores de PCR-us) do que indivíduos com PNMS.

Palavras-chave:
obeso metabolicamente saudável; índice aterogênico do plasma; doença cardiovascular

INTRODUCTION

Obesity is a key risk factor for cardiovascular diseases (CVD), diabetes, hypertension, various types of cancer, mental health, and increased mortality. The obesity rate has tripled over the last two decades in developing countries, including Iran.11 Kolahi AA, Moghisi A, Soleiman Ekhtiari Y. Socio-demographic determinants of obesity indexes in Iran: findings from a nationwide STEPS survey. Health Promot Perspect. 2018;8(3):187-94. http://dx.doi.org/10.15171/hpp.2018.25. PMid:30087841.
http://dx.doi.org/10.15171/hpp.2018.25...
,22 Tabrizi JS, Sadeghi-Bazargani H, Farahbakhsh M, Nikniaz L, Nikniaz Z. Prevalence and associated factors of overweight or obesity and abdominal obesity in iranian population: a population-based study of Northwestern Iran. Iran J Public Health. 2018;47(10):1583-92. PMid:30524990.

However, not all obese individuals show an increased risk of mortality. The metabolically healthy obesity (MHO) phenotype has been recognized since the 1980s and encompasses obese individuals who are metabolically healthy despite having an excessive store of body fat and elevated BMI.33 Ruderman NB, Schneider SH, Berchtold P. The “metabolically-obese,” normal-weight individual. Am J Clin Nutr. 1981;34(8):1617-21. http://dx.doi.org/10.1093/ajcn/34.8.1617. PMid:7270486.
http://dx.doi.org/10.1093/ajcn/34.8.1617...
Individuals with MHO exhibit a favorable metabolic profile that is determined by a high level of insulin sensitivity, lack of hypertension, and favorable lipid, and inflammatory profiles.33 Ruderman NB, Schneider SH, Berchtold P. The “metabolically-obese,” normal-weight individual. Am J Clin Nutr. 1981;34(8):1617-21. http://dx.doi.org/10.1093/ajcn/34.8.1617. PMid:7270486.
http://dx.doi.org/10.1093/ajcn/34.8.1617...
,44 Seo MH, Rhee EJ. Metabolic and cardiovascular implications of a metabolically healthy obesity phenotype. Endocrinol Metab. 2014;29(4):427-34. http://dx.doi.org/10.3803/EnM.2014.29.4.427. PMid:25559571.
http://dx.doi.org/10.3803/EnM.2014.29.4....
The MHO phenotype is the result of various underlying mechanisms and interactions between genetic, behavioral, and environmental agents that have not been elucidated.55 Jung CH, Lee WJ, Song KH. Metabolically healthy obesity: a friend or foe? Korean J Intern Med. 2017;32(4):611-21. http://dx.doi.org/10.3904/kjim.2016.259. PMid:28602062.
http://dx.doi.org/10.3904/kjim.2016.259...
The results of previous studies evaluating the effect of MHO on health outcomes remain controversial.66 Stefan N, Haring HU, Hu FB, Schulze MB. Metabolically healthy obesity: epidemiology, mechanisms, and clinical implications. Lancet Diabetes Endocrinol. 2013;1(2):152-62. http://dx.doi.org/10.1016/S2213-8587(13)70062-7. PMid:24622321.
http://dx.doi.org/10.1016/S2213-8587(13)...

7 Samocha-Bonet D, Dixit VD, Kahn CR, et al. Metabolically healthy and unhealthy obese: the 2013 Stock Conference report. Obes Rev. 2014;15(9):697-708. http://dx.doi.org/10.1111/obr.12199. PMid:25059108.
http://dx.doi.org/10.1111/obr.12199...
-88 Blüher M. Are metabolically healthy obese individuals really healthy? Eur J Endocrinol. 2014;171(6):R209-19. http://dx.doi.org/10.1530/EJE-14-0540. PMid:25012199.
http://dx.doi.org/10.1530/EJE-14-0540...
There is no consensus on unique criteria that can be used to define MHO and consequently prevalence rates of the MHO phenotype differ considerably among studies (6 to 40% in the obese population).99 Phillips CM. Metabolically healthy obesity: definitions, determinants and clinical implications. Rev Endocr Metab Disord. 2013;14(3):219-27. http://dx.doi.org/10.1007/s11154-013-9252-x. PMid:23928851.
http://dx.doi.org/10.1007/s11154-013-925...
The main obstacles to estimating the true prevalence of MHO are related to the criteria used to define it, the study design, and other factors such as ethnicity, sex, age, and lifestyle.66 Stefan N, Haring HU, Hu FB, Schulze MB. Metabolically healthy obesity: epidemiology, mechanisms, and clinical implications. Lancet Diabetes Endocrinol. 2013;1(2):152-62. http://dx.doi.org/10.1016/S2213-8587(13)70062-7. PMid:24622321.
http://dx.doi.org/10.1016/S2213-8587(13)...

7 Samocha-Bonet D, Dixit VD, Kahn CR, et al. Metabolically healthy and unhealthy obese: the 2013 Stock Conference report. Obes Rev. 2014;15(9):697-708. http://dx.doi.org/10.1111/obr.12199. PMid:25059108.
http://dx.doi.org/10.1111/obr.12199...
-88 Blüher M. Are metabolically healthy obese individuals really healthy? Eur J Endocrinol. 2014;171(6):R209-19. http://dx.doi.org/10.1530/EJE-14-0540. PMid:25012199.
http://dx.doi.org/10.1530/EJE-14-0540...
Considering the number of serious health problems associated with obesity, research studying the MHO phenotype may help to identify at-risk obese individuals, support development of better interventions for obese patients, and lead to a novel comprehension of the pathophysiology of obesity.

Since the association between presence of MHO in the absence of metabolic syndrome and subsequent cardiovascular disease remains unclear, we examined the association between MHO and CVD risk in young Iranian women.

METHODS

Participants

The present cross-sectional study was carried out with subjects who were referred to a nutrition clinic, in Ahvaz, Iran. We studied 183 women aged 20-35 years who were selected from a population of 308 candidates. We excluded 125 women who met exclusion criteria including pregnancy, breastfeeding, consumption of any drugs, eating disorders, diabetes, cardiovascular disease, kidney disorders, thyroid disorders, digestive and respiratory diseases, cancer, consumption of more than 300 mg of caffeine daily, and moderate or severe physical activity). Inclusion criteria were regular 28-d menstrual cycles, no physical activity, no smoking, no alcohol consumption, no use of any supplements, and no weight changes in the preceding 6 months. All 183 women signed written informed consent forms. The study protocol was approved by the Ethics Committee at the Ahvaz Jundishapur University of Medical Sciences (IR.AJUMS.REC.1394.489). Participants with metabolic syndrome were diagnosed according to the NCEP ATP III definition, i.e., meeting at least three of the following criteria: waist circumference ≥ 35 inches (women), blood pressure ≥ 130/85 mmHg, fasting triglyceride (TG) level ≥ 150 mg/dL, fasting high-density lipoprotein (HDL) cholesterol level less than 50 mg/dL (for women), and fasting blood sugar (FBS) ≥ 100 mg/dL.1010 Huang PL. A comprehensive definition for metabolic syndrome. Dis Model Mech. 2009;2(5-6):231-7. http://dx.doi.org/10.1242/dmm.001180. PMid:19407331.
http://dx.doi.org/10.1242/dmm.001180...
We classified participants according to 4 phenotypes based on body mass index (BMI) and metabolic syndrome criteria (Table 1).

Table 1
Criteria used for diagnosis of metabolically obese phenotypes.

Measurements

A direct segmental multi-frequency bioelectrical impedance method (Inbody 270, Biospace, Korea) was used to calculate body weight and body composition. Waist circumference (WC) was determined in the standing position using a tape with an accuracy of 1.0 cm, above the iliac crest and just below margin of the lowest rib, at the end of the normal expiration. For the hip circumference measurement, the tape was put around the point with the maximum circumference over the buttocks.1111 Ashtary-Larky D, Daneghian S, Alipour M, et al. Waist circumference to height ratio: better correlation with fat mass than other anthropometric indices during dietary weight loss in different rates. Int J Endocrinol Metab. 2018;16(4):e55023. http://dx.doi.org/10.5812/ijem.55023. PMid:30464770.
http://dx.doi.org/10.5812/ijem.55023...
The waist-to-hip ratio (WHR) was calculated as waist measurement divided by hip measurement (W/H). Blood pressure was determined using an automatic blood pressure monitor (BM65, Beurer, Germany) after subjects had been at rest for more than 10 minutes. Measurements were taken in triplicate and the mean was considered for each subject. In this study, RMR was measured by indirect calorimetry (FitMate, Cosmed, Rome, Italy), using resting oxygen uptake (VO2).

For biochemical measurements, 8 cc fasting blood samples were drawn from each subject between days 8 and 12 of their preovulation phase. Blood glucose, total cholesterol, LDL-c, HDL-c, and triglycerides were quantified by enzymatic methods with kits from Pars- Azmoon (Tehran, Iran). Insulin concentration and high-sensitivity C-reactive protein (hsCRP) were measured with ELISA kits (Diaplus Inc., Canada). Homeostasis model assessment – insulin resistance (HOMA-IR) was determined using the following formula:

f a s t i n g g l u c o s e m g / d L × f a s t i n g i n s u l i n μ u / m L / 405

QUICKI was measured with the following formula =

1 / l o g f a s t i n g i n s u l i n μ U m L + l o g f a s t i n g g l u c o s e m g / d L 20 / f a s t i n g C p e p t i d e × f a s t i n g p l a s m a g l u c o s e

12 12 Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004;27(6):1487-95. http://dx.doi.org/10.2337/diacare.27.6.1487. PMid:15161807.
http://dx.doi.org/10.2337/diacare.27.6.1...

Statistical analyses

All statistical analyses were carried out using IBM SPSS Statistics software version 24 (IBM SPSS Statistics, Armonk, USA). The normality of variables was established using the Kolmogorov- Smirnov test. ANOVA was applied to test differences within groups. Comparisons of variables that were different between groups were performed using the Tukey test for post-hoc analyses. A p value less than 0.05 was considered to be statistically significant.

RESULTS

Table 2 lists anthropometric characteristics of the participants included in the analysis. A total of 44.8% of the participants had normal weight, and 55.2% were overweight or obese. There were no significant differences in age, height, diastolic blood pressure, or heart rate between groups. Weight, BMI, WC, HC, WHR, and RMR were highest in MUO, followed by MHO, NWO, and MHNW in that order. Total body water was significantly higher in obese groups (MUO, MHO) than in normal weight individuals. Systolic blood pressure was significantly higher in MUO than in the other three groups (Table 2). As shown in Tables 3 and Table 4, the amount of fat in all parts of the body was higher in NWO than in MHNW, but this difference was not observed for LBMs. Body fat and LBM of all body parts was higher in obese groups (MUO and MHO) than in normal weight groups (NWO and MHNW). Also, body fat and LBM (expect fat free mass, left and right foot) were higher in MUO than MHO (Table 3 and Table 4). As shown in Tables 5 and Table 6, there were no significant differences between NHNW and NWO in lipid profile, glycemic status, or liver enzymes. The MUO group had significantly higher values for TG, VLDL, LDL/HDL, Cholesterol/HDL, AIP, FBS, and hsCRP than the other three groups. Furthermore, the lowest level of HDL was observed in the MUO group. LDL/HDL and hs-CRP were higher in MHO participants than in MHNW participants, whereas HDL-c was higher in MHNW than MHO.

Table 2
Anthropometric status by group.
Table 3
Body composition by group.
Table 4
Body fat status by group.
Table 5
Lipid profiles by group.
Table 6
Biochemical factors by group.

DISCUSSION

Our analysis revealed that MHO individuals were at increased risk of CVD incidents, compared with normal weight individuals without metabolic syndrome. However, MHO individuals display a partially more favorable metabolic profile than MUO individuals. Despite the increasing number of studies evaluating MHO, investigations of the association between metabolically healthy obesity and CVD risk have reported controversial results. Several studies have observed no elevated risk of CVD in MHO individuals, whereas some other studies have shown an elevated risk of CVD in this phenotype.1313 Song Y, Manson JE, Meigs JB, Ridker PM, Buring JE, Liu S. Comparison of usefulness of body mass index versus metabolic risk factors in predicting 10-year risk of cardiovascular events in women. Am J Cardiol. 2007;100(11):1654-8. http://dx.doi.org/10.1016/j.amjcard.2007.06.073. PMid:18036364.
http://dx.doi.org/10.1016/j.amjcard.2007...

14 Hinnouho GM, Czernichow S, Dugravot A, et al. Metabolically healthy obesity and the risk of cardiovascular disease and type 2 diabetes: the Whitehall II cohort study. Eur Heart J. 2015;36(9):551-9. PMid:24670711.
-1515 Karelis AD, Faraj M, Bastard J-P, et al. The Metabolically Healthy but Obese Individual Presents a Favorable Inflammation Profile. J Clin Endocrinol Metab. 2005;90(7):4145-50. http://dx.doi.org/10.1210/jc.2005-0482. PMid:15855252.
http://dx.doi.org/10.1210/jc.2005-0482...
In one study of women aged 45 years and over, with 10 years of follow-up, no increased CVD risk for MHO phenotypes was observed.1313 Song Y, Manson JE, Meigs JB, Ridker PM, Buring JE, Liu S. Comparison of usefulness of body mass index versus metabolic risk factors in predicting 10-year risk of cardiovascular events in women. Am J Cardiol. 2007;100(11):1654-8. http://dx.doi.org/10.1016/j.amjcard.2007.06.073. PMid:18036364.
http://dx.doi.org/10.1016/j.amjcard.2007...
In another study, in adults aged 35-55 years, it was shown that MHO individuals were at increased risk of CVD incidents, compared with MHNW individuals.1414 Hinnouho GM, Czernichow S, Dugravot A, et al. Metabolically healthy obesity and the risk of cardiovascular disease and type 2 diabetes: the Whitehall II cohort study. Eur Heart J. 2015;36(9):551-9. PMid:24670711. Karelis et al.1515 Karelis AD, Faraj M, Bastard J-P, et al. The Metabolically Healthy but Obese Individual Presents a Favorable Inflammation Profile. J Clin Endocrinol Metab. 2005;90(7):4145-50. http://dx.doi.org/10.1210/jc.2005-0482. PMid:15855252.
http://dx.doi.org/10.1210/jc.2005-0482...
indicated that postmenopausal women displaying the MHO phenotype also have a favorable inflammation profile, as shown by lower CRP and α-1 antitrypsin levels compared with insulin-resistant women. These authors suggested that a satisfactory inflammation profile, as verified by low CRP levels, could play a role in the protective profile of the MHO individual and that this may be related metabolically to a lower risk of cardiovascular disease.1515 Karelis AD, Faraj M, Bastard J-P, et al. The Metabolically Healthy but Obese Individual Presents a Favorable Inflammation Profile. J Clin Endocrinol Metab. 2005;90(7):4145-50. http://dx.doi.org/10.1210/jc.2005-0482. PMid:15855252.
http://dx.doi.org/10.1210/jc.2005-0482...
Also, we found that a low inflammation state was a part of the protective profile of the MHO subgroup, when compared to the MUO subgroup. We observed a lower hs-CRP concentration in MHO participants than MUO participants (4.09 ± 5.18 vs 6.64 ± 5.54, respectively). However, the MHO subgroup’s mean hs-CRP level was higher than the JUPITER threshold, ≥2mg/L and also higher than that of the MHNW subgroup.1616 Blaha MJ, Rivera JJ, Budoff MJ, et al. Association between obesity, high-sensitivity C-reactive protein ≥2 mg/L, and subclinical atherosclerosis: implications of JUPITER from the Multi-Ethnic Study of Atherosclerosis. Arterioscler Thromb Vasc Biol. 2011;31(6):1430-8. http://dx.doi.org/10.1161/ATVBAHA.111.223768. PMid:21474823.
http://dx.doi.org/10.1161/ATVBAHA.111.22...
The second favorable aspect of the MHO metabolic profile compared to the MUO profile was a higher HDL level, and lower levels of fasting TG, LDL/HDL, and Cholesterol/HDL. An adequate lipid profile has been reported as a protective factor for cardiovascular disease.1717 Kutkiene S, Petrulioniene Z, Laucevicius A, et al. Cardiovascular risk profile of patients with atherogenic dyslipidemia in middle age Lithuanian population. Lipids Health Dis. 2018;17(1):208. http://dx.doi.org/10.1186/s12944-018-0851-0. PMid:30185180.
http://dx.doi.org/10.1186/s12944-018-085...
Another variable associated with a more favorable metabolic profile in MHO in compared to MUO was FBS. We also found that young MHO women had no increased risk of developing type 2 diabetes compared with MHNW. Finally, one other protective variable was lower AIP in MHO participants compared with MUO subjects. This variable was not statistically different between MHO and MHNW or NWO participants. In a study by Koborová et al.,1818 Koborová I, Gurecká R, Csongová M, et al. Association between metabolically healthy central obesity in women and levels of soluble receptor for advanced glycation end products, soluble vascular adhesion protein-1, and the activity of semicarbazide-sensitive amine oxidase. Croat Med J. 2017;58(2):106-16. http://dx.doi.org/10.3325/cmj.2017.58.106. PMid:28409494.
http://dx.doi.org/10.3325/cmj.2017.58.10...
AIP was significantly lower in metabolically healthy obese women than in unhealthy centrally obese women, which is similar to our findings. Also, a study by Chhezom showed that obese individuals had a significantly higher atherogenic index of plasma compared to normal weight and overweight individuals.1919 Chhezom K, Arslan MI, Hoque MM, Biswas SK. Biomarkers of cardiovascular and metabolic diseases in otherwise healthy overweight subjects in Bangladesh. Diabetes Metab Syndr. 2017;11(Suppl Suppl 1):S381-4. http://dx.doi.org/10.1016/j.dsx.2017.03.021. PMid:28285989.
http://dx.doi.org/10.1016/j.dsx.2017.03....
Recently, AIP was identified as a useful and novel marker for the risk of atherosclerosis and cardiovascular disease.2020 Cure E, Icli A, Uslu AU, et al. Atherogenic index of plasma: a useful marker for subclinical atherosclerosis in ankylosing spondylitis. Clin Rheumatol. 2018;37(5):1273-80. http://dx.doi.org/10.1007/s10067-018-4027-0. PMid:29435680.
http://dx.doi.org/10.1007/s10067-018-402...
This marker reflects the delicate metabolic interactions within the whole lipoprotein complex and is a better predictor of atherogenic risk than triglyceride and HDL-C levels evaluated separately.2121 Dobiás̆ová M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate inapob-lipoprotein-depleted plasma (FERHDL). Clin Biochem. 2001;34(7):583-8. http://dx.doi.org/10.1016/S0009-9120(01)00263-6. PMid:11738396.
http://dx.doi.org/10.1016/S0009-9120(01)...

It is likely that MHO is a transient condition.55 Jung CH, Lee WJ, Song KH. Metabolically healthy obesity: a friend or foe? Korean J Intern Med. 2017;32(4):611-21. http://dx.doi.org/10.3904/kjim.2016.259. PMid:28602062.
http://dx.doi.org/10.3904/kjim.2016.259...
,2222 Lee SK, Kim SH, Cho GY, et al. Obesity phenotype and incident hypertension: a prospective community-based cohort study. J Hypertens. 2013;31(1):145-51. http://dx.doi.org/10.1097/HJH.0b013e32835a3637. PMid:23079679.
http://dx.doi.org/10.1097/HJH.0b013e3283...
Thus, in MHO individuals, sustaining factors such as a healthy diet, smoking cessation, preservation of metabolic health, and physical activity may prevent progression to the MUO phenotype.44 Seo MH, Rhee EJ. Metabolic and cardiovascular implications of a metabolically healthy obesity phenotype. Endocrinol Metab. 2014;29(4):427-34. http://dx.doi.org/10.3803/EnM.2014.29.4.427. PMid:25559571.
http://dx.doi.org/10.3803/EnM.2014.29.4....

5 Jung CH, Lee WJ, Song KH. Metabolically healthy obesity: a friend or foe? Korean J Intern Med. 2017;32(4):611-21. http://dx.doi.org/10.3904/kjim.2016.259. PMid:28602062.
http://dx.doi.org/10.3904/kjim.2016.259...

6 Stefan N, Haring HU, Hu FB, Schulze MB. Metabolically healthy obesity: epidemiology, mechanisms, and clinical implications. Lancet Diabetes Endocrinol. 2013;1(2):152-62. http://dx.doi.org/10.1016/S2213-8587(13)70062-7. PMid:24622321.
http://dx.doi.org/10.1016/S2213-8587(13)...
-77 Samocha-Bonet D, Dixit VD, Kahn CR, et al. Metabolically healthy and unhealthy obese: the 2013 Stock Conference report. Obes Rev. 2014;15(9):697-708. http://dx.doi.org/10.1111/obr.12199. PMid:25059108.
http://dx.doi.org/10.1111/obr.12199...
Dhana et al.2323 Dhana K, Koolhaas CM, Van Rossum EF, et al. Metabolically healthy obesity and the risk of cardiovascular disease in the elderly population. PLoS One. 2016;11(4):e0154273. http://dx.doi.org/10.1371/journal.pone.0154273. PMid:27100779.
http://dx.doi.org/10.1371/journal.pone.0...
suggested that the metabolic status of MHO individuals should be reassessed on a regular basis.

We employed a cross-sectional approach, so we couldn’t establish relationships of causality. Despite this limitation, our results are strengthened by measurement of body composition, liver function enzymes, complete lipid profile, glycemic indexes and inflammatory markers in young Iranian women.

In conclusion, results of the present study demonstrate that young women displaying the MHO phenotype have a favorable metabolic profile as shown by lower FBS, TG, LDL-c/HDL-c, Cho/HDL-c, hs-CRP, and AIP, and higher HDL-c levels than those with the MUO phenotype. However, MHO individuals were nevertheless at increased risk of CVD incident (lower HDL-C and more hs-CRP level), compared with MHNW individuals. As mentioned above, the inconsistent definition of MHO among studies is the main obstacle to advancing our understanding of the MHO phenotype. It is therefore necessary to standardize the definition of MHO.

  • How to cite: Hosseini SA, Aghamohammadi V, Ashtary-Larky D, Alipour M, Ghanavati M, Lamuchi-Deli N. Are young Iranian women with metabolically healthy obesity at increased risk of CVD incidence? J Vasc Bras. 2020;19:e20190106. https://doi.org/10.1590/1677-5449.190106
  • Financial support: None.
  • The study was carried out at Hyperlipidemia Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

REFERENCES

  • 1
    Kolahi AA, Moghisi A, Soleiman Ekhtiari Y. Socio-demographic determinants of obesity indexes in Iran: findings from a nationwide STEPS survey. Health Promot Perspect. 2018;8(3):187-94. http://dx.doi.org/10.15171/hpp.2018.25 PMid:30087841.
    » http://dx.doi.org/10.15171/hpp.2018.25
  • 2
    Tabrizi JS, Sadeghi-Bazargani H, Farahbakhsh M, Nikniaz L, Nikniaz Z. Prevalence and associated factors of overweight or obesity and abdominal obesity in iranian population: a population-based study of Northwestern Iran. Iran J Public Health. 2018;47(10):1583-92. PMid:30524990.
  • 3
    Ruderman NB, Schneider SH, Berchtold P. The “metabolically-obese,” normal-weight individual. Am J Clin Nutr. 1981;34(8):1617-21. http://dx.doi.org/10.1093/ajcn/34.8.1617 PMid:7270486.
    » http://dx.doi.org/10.1093/ajcn/34.8.1617
  • 4
    Seo MH, Rhee EJ. Metabolic and cardiovascular implications of a metabolically healthy obesity phenotype. Endocrinol Metab. 2014;29(4):427-34. http://dx.doi.org/10.3803/EnM.2014.29.4.427 PMid:25559571.
    » http://dx.doi.org/10.3803/EnM.2014.29.4.427
  • 5
    Jung CH, Lee WJ, Song KH. Metabolically healthy obesity: a friend or foe? Korean J Intern Med. 2017;32(4):611-21. http://dx.doi.org/10.3904/kjim.2016.259 PMid:28602062.
    » http://dx.doi.org/10.3904/kjim.2016.259
  • 6
    Stefan N, Haring HU, Hu FB, Schulze MB. Metabolically healthy obesity: epidemiology, mechanisms, and clinical implications. Lancet Diabetes Endocrinol. 2013;1(2):152-62. http://dx.doi.org/10.1016/S2213-8587(13)70062-7 PMid:24622321.
    » http://dx.doi.org/10.1016/S2213-8587(13)70062-7
  • 7
    Samocha-Bonet D, Dixit VD, Kahn CR, et al. Metabolically healthy and unhealthy obese: the 2013 Stock Conference report. Obes Rev. 2014;15(9):697-708. http://dx.doi.org/10.1111/obr.12199 PMid:25059108.
    » http://dx.doi.org/10.1111/obr.12199
  • 8
    Blüher M. Are metabolically healthy obese individuals really healthy? Eur J Endocrinol. 2014;171(6):R209-19. http://dx.doi.org/10.1530/EJE-14-0540 PMid:25012199.
    » http://dx.doi.org/10.1530/EJE-14-0540
  • 9
    Phillips CM. Metabolically healthy obesity: definitions, determinants and clinical implications. Rev Endocr Metab Disord. 2013;14(3):219-27. http://dx.doi.org/10.1007/s11154-013-9252-x PMid:23928851.
    » http://dx.doi.org/10.1007/s11154-013-9252-x
  • 10
    Huang PL. A comprehensive definition for metabolic syndrome. Dis Model Mech. 2009;2(5-6):231-7. http://dx.doi.org/10.1242/dmm.001180 PMid:19407331.
    » http://dx.doi.org/10.1242/dmm.001180
  • 11
    Ashtary-Larky D, Daneghian S, Alipour M, et al. Waist circumference to height ratio: better correlation with fat mass than other anthropometric indices during dietary weight loss in different rates. Int J Endocrinol Metab. 2018;16(4):e55023. http://dx.doi.org/10.5812/ijem.55023 PMid:30464770.
    » http://dx.doi.org/10.5812/ijem.55023
  • 12
    Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004;27(6):1487-95. http://dx.doi.org/10.2337/diacare.27.6.1487 PMid:15161807.
    » http://dx.doi.org/10.2337/diacare.27.6.1487
  • 13
    Song Y, Manson JE, Meigs JB, Ridker PM, Buring JE, Liu S. Comparison of usefulness of body mass index versus metabolic risk factors in predicting 10-year risk of cardiovascular events in women. Am J Cardiol. 2007;100(11):1654-8. http://dx.doi.org/10.1016/j.amjcard.2007.06.073 PMid:18036364.
    » http://dx.doi.org/10.1016/j.amjcard.2007.06.073
  • 14
    Hinnouho GM, Czernichow S, Dugravot A, et al. Metabolically healthy obesity and the risk of cardiovascular disease and type 2 diabetes: the Whitehall II cohort study. Eur Heart J. 2015;36(9):551-9. PMid:24670711.
  • 15
    Karelis AD, Faraj M, Bastard J-P, et al. The Metabolically Healthy but Obese Individual Presents a Favorable Inflammation Profile. J Clin Endocrinol Metab. 2005;90(7):4145-50. http://dx.doi.org/10.1210/jc.2005-0482 PMid:15855252.
    » http://dx.doi.org/10.1210/jc.2005-0482
  • 16
    Blaha MJ, Rivera JJ, Budoff MJ, et al. Association between obesity, high-sensitivity C-reactive protein ≥2 mg/L, and subclinical atherosclerosis: implications of JUPITER from the Multi-Ethnic Study of Atherosclerosis. Arterioscler Thromb Vasc Biol. 2011;31(6):1430-8. http://dx.doi.org/10.1161/ATVBAHA.111.223768 PMid:21474823.
    » http://dx.doi.org/10.1161/ATVBAHA.111.223768
  • 17
    Kutkiene S, Petrulioniene Z, Laucevicius A, et al. Cardiovascular risk profile of patients with atherogenic dyslipidemia in middle age Lithuanian population. Lipids Health Dis. 2018;17(1):208. http://dx.doi.org/10.1186/s12944-018-0851-0 PMid:30185180.
    » http://dx.doi.org/10.1186/s12944-018-0851-0
  • 18
    Koborová I, Gurecká R, Csongová M, et al. Association between metabolically healthy central obesity in women and levels of soluble receptor for advanced glycation end products, soluble vascular adhesion protein-1, and the activity of semicarbazide-sensitive amine oxidase. Croat Med J. 2017;58(2):106-16. http://dx.doi.org/10.3325/cmj.2017.58.106 PMid:28409494.
    » http://dx.doi.org/10.3325/cmj.2017.58.106
  • 19
    Chhezom K, Arslan MI, Hoque MM, Biswas SK. Biomarkers of cardiovascular and metabolic diseases in otherwise healthy overweight subjects in Bangladesh. Diabetes Metab Syndr. 2017;11(Suppl Suppl 1):S381-4. http://dx.doi.org/10.1016/j.dsx.2017.03.021 PMid:28285989.
    » http://dx.doi.org/10.1016/j.dsx.2017.03.021
  • 20
    Cure E, Icli A, Uslu AU, et al. Atherogenic index of plasma: a useful marker for subclinical atherosclerosis in ankylosing spondylitis. Clin Rheumatol. 2018;37(5):1273-80. http://dx.doi.org/10.1007/s10067-018-4027-0 PMid:29435680.
    » http://dx.doi.org/10.1007/s10067-018-4027-0
  • 21
    Dobiás̆ová M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate inapob-lipoprotein-depleted plasma (FERHDL). Clin Biochem. 2001;34(7):583-8. http://dx.doi.org/10.1016/S0009-9120(01)00263-6 PMid:11738396.
    » http://dx.doi.org/10.1016/S0009-9120(01)00263-6
  • 22
    Lee SK, Kim SH, Cho GY, et al. Obesity phenotype and incident hypertension: a prospective community-based cohort study. J Hypertens. 2013;31(1):145-51. http://dx.doi.org/10.1097/HJH.0b013e32835a3637 PMid:23079679.
    » http://dx.doi.org/10.1097/HJH.0b013e32835a3637
  • 23
    Dhana K, Koolhaas CM, Van Rossum EF, et al. Metabolically healthy obesity and the risk of cardiovascular disease in the elderly population. PLoS One. 2016;11(4):e0154273. http://dx.doi.org/10.1371/journal.pone.0154273 PMid:27100779.
    » http://dx.doi.org/10.1371/journal.pone.0154273

Publication Dates

  • Publication in this collection
    14 Sept 2020
  • Date of issue
    2020

History

  • Received
    22 Aug 2019
  • Accepted
    20 Apr 2020
Sociedade Brasileira de Angiologia e de Cirurgia Vascular (SBACV) Rua Estela, 515, bloco E, conj. 21, Vila Mariana, CEP04011-002 - São Paulo, SP, Tel.: (11) 5084.3482 / 5084.2853 - Porto Alegre - RS - Brazil
E-mail: secretaria@sbacv.org.br