SciELO - Scientific Electronic Library Online

 
vol.112 número3Estimulação Ventricular Programada no Manejo de Pacientes com Síndrome de BrugadaAdiposidade Abdominal e Espessura Médio-Intimal das Carótidas: Uma Associação índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

  • texto em Português
  • nova página do texto(beta)
  • Inglês (pdf) | Português (pdf)
  • Artigo em XML
  • Como citar este artigo
  • SciELO Analytics
  • Curriculum ScienTI
  • Tradução automática

Indicadores

Links relacionados

Compartilhar


Arquivos Brasileiros de Cardiologia

versão impressa ISSN 0066-782Xversão On-line ISSN 1678-4170

Arq. Bras. Cardiol. vol.112 no.3 São Paulo mar. 2019  Epub 07-Jan-2019

https://doi.org/10.5935/abc.20180273 

Original Article

Indicators of Abdominal Adiposity and Carotid Intima-Media Thickness: Results from the Longitudinal Study of Adult Health (ELSA-Brazil)

Michaela Eickemberg1  2 
http://orcid.org/0000-0002-3625-2221

Leila Denise Alves Ferreira Amorim1 

Maria da Conceição Chagas de Almeida3 

Estela Maria Leão de Aquino1 

Maria de Jesus Mendes da Fonseca4 

Itamar de Souza Santos5 

Dora Chor4 

Maria de Fátima Sander Diniz6 

Sandhi Maria Barreto6 

Sheila Maria Alvim de Matos1 

1Universidade Federal da Bahia, Salvador, BA - Brazil

2Escola Bahiana de Medicina e Saúde Pública, Salvador, BA - Brazil

3Centro de Pesquisas Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, BA - Brazil

4Escola Nacional de Saúde Pública - Fiocruz, Rio de Janeiro, RJ - Brazil

5Universidade de São Paulo, São Paulo, SP - Brazil

6Universidade Federal de Minas Gerais, Belo Horizonte, MG - Brazil


Abstract

Background:

Abdominal adiposity is a risk factor for cardiovascular disease.

Objective:

To determine the magnitude of the association between abdominal adiposity, according to five different indicators, and the carotid intima-media thickness (CIMT).

Methods:

Data from 8,449 participants aged 35 to 74 years from the ELSA-Brazil study were used. The effect of waist circumference (WC), waist-to-hip ratio (WHR), conicity index (C index), lipid accumulation product (LAP) and visceral adiposity index (VAI) on CIMT were evaluated. Data were stratified by gender and analyzed using multivariate linear and logistic regressions. A significance level of 5% was considered.

Results:

Participants with CIMT > P75 showed a higher frequency of abdominal adiposity (men >72% and women >66%) compared to those with CIMT < P75. Abdominal adiposity was associated with the mean CIMT, mainly through WC in men (0.04; 95%CI: 0.033; 0.058). The abdominal adiposity identified by the WC, WHR, LAP, and VAI indicators in women showed an effect of 0.02 mm on the CIMT (WC: 0.025, 95%CI: 0.016, 0.035; WHR: 0.026, 95%CI: 0.016, 0.035; LAP: 0.024, 95%CI: 0.014; 0.034; VAI: 0.020, 95%CI: 0.010, 0.031). In the multiple logistic regression, the abdominal adiposity diagnosed by WC showed an important effect on the CIMT in both genders (men: OR = 1.47, 95%CI: 1.22-1.77, women: OR = 1.38; 95%CI: 1.17-1.64).

Conclusion:

Abdominal adiposity, identified through WC, WHR, LAP, and VAI, was associated with CIMT in both genders, mainly for the traditional anthropometric indicator, WC.

Keywords: Cardiovascular Diseases; Risk Factors; Metabolism; Metabolic Syndrome; Abdominal Obesity; Atherosclerosis; Carotid Intima-Media Thickness

Resumo

Fundamento:

A adiposidade abdominal é um fator de risco para doença cardiovascular.

Objetivo:

Determinar a magnitude da associação entre a adiposidade abdominal, segundo cinco diferentes indicadores, e a espessura médio-intimal de carótidas (EMI-C).

Métodos:

Usou-se dados de 8.449 participantes de 35 a 74 anos do ELSA-Brasil. Foi avaliado o efeito da circunferência da cintura (CC), razão cintura quadril (RCQ), índice de conicidade (Índice C), produto da acumulação lipídica (LAP) e índice de adiposidade visceral (IAV) sobre EMI-C. Os dados foram estratificados por sexo e analisados por meio de regressões linear e logística multivariadas. Foi adotado nível de significância de 5%.

Resultados:

Participantes com EMI-C acima do P75 mostraram maior frequência de adiposidade abdominal (homens acima de 72% e mulheres acima de 66%) em comparação aos participantes com EMI-C abaixo do P75. A adiposidade abdominal foi associada com a média da EMI-C, principalmente por meio da CC entre homens (0,04 IC95%: 0,033; 0,058). A adiposidade abdominal identificada pelos indicadores CC, RCQ, LAP e IAV entre as mulheres mostrou efeito de 0,02 mm sobre a EMI-C (CC: 0,025 IC95%: 0,016; 0,035; RCQ: 0,026 IC95%: 0,016; 0,035; LAP: 0,024 IC95%: 0,014; 0,034; IAV: 0,020 IC95%: 0,010; 0,031). Na regressão logística múltipla a adiposidade abdominal diagnosticada pela CC mostrou importante efeito sobre a EMI-C em ambos os sexos (homens: OR = 1,47; IC95%: 1,22-1,77; mulheres: OR = 1,38; IC95%: 1,17-1,64).

Conclusão:

A adiposidade abdominal, identificada por meio da CC, RCQ, LAP e IAV, foi associada à EMI-C em ambos os sexos, com destaque para o tradicional indicador antropométrico CC.

Palavras-chave: Doenças Cardiovasculares; Fatores de Risco; Metabolismo; Síndrome Metabólica; Obesidade abdominal; Aterosclerose; Espessura Íntima-Média Carotídea

Introduction

Abdominal obesity is a traditional risk factor for cardiovascular diseases.1 In Brazil, the prevalence of abdominal obesity, estimated by the National Health Survey (Pesquisa Nacional de Saúde), according to the cut-off points for waist circumference (WC) of the World Health Organization,2 was 52.1% for women and 21.8% for men in 2013.3

Several mechanisms have attempted to explain how abdominal adiposity becomes a risk factor for cardiovascular disease. It is a consensus that abdominal adipose tissue has complex metabolic functions and produces numerous mediators that trigger specific, dynamic and inflammatory reactions.4

Atherosclerotic lesions increase the risk for cardiovascular diseases. The carotid intima-media thickness (CIMT) is a marker of subclinical atherosclerosis and a predictor of myocardial infarction and cerebrovascular accident.5 The association between abdominal adiposity and subclinical atherosclerosis has been documented in different populations.6,7 However, even though the CIMT is associated with abdominal adiposity, it is yet to be fully established how much this adiposity, measured by different clinical and other unusual indicators, is associated with subclinical atherosclerosis.

Studies have suggested that WC, waist-to-hip ratio (WHR) and visceral adiposity index (VAI) may predict subclinical atherosclerosis.6,8,9 Most studies on this subject were performed in Europe, Asia and the United States, and use the WC and WHR to define abdominal adiposity and its association with cardiovascular diseases. Indicators that provide indirect information on lipid overaccumulation and visceral fat function associated with cardiovascular events, such as VAI10 and the lipid accumulation product (LAP)11, need to be further explored. The conicity index (C index) stands out as a discriminator of high coronary risk in Brazilian studies, especially when a black population is being investigated.12 On the other hand, there are no studies that investigated the effect of adiposity diagnosed by this index on CIMT.

The aim of this study was to determine the magnitude of the association between abdominal adiposity, according to different diagnostic indicators (WC, WHR, C Index), and between indexes that reflect visceral adipose tissue dysfunction (LAP and VAI) and CIMT among the participants of ELSA-Brazil.

Methods

Study design and population

The ELSA-Brasil study included in its baseline 15,105 civil servants, aged 35-74 years, connected to six teaching and research institutions in three Brazilian regions (South, Southeast and Northeast). More details on the study methodology can be found in an earlier publication.13

Interviews and collection of anthropometric and biochemical measurements were carried out by a trained and certified team. A more detailed publication is available on the standardization and quality assurance procedures and the quality of uniformization regarding the conducts adopted in the ELSA-Brazil.14

Exclusion Criteria

In order to keep a healthy sample and to avoid biases related to CIMT, of the 10,943 participants with a valid image for both common carotid arteries, we excluded 569 patients who declared having cardiovascular disease, 36 with serum triglycerides > 800 mg/dL, 1,974 patients using lipid-lowering medication, 144 with BMI > 40 kg/m2 and 120 who underwent bariatric surgery. To avoid biases related to abdominal fat measurement, 32 participants with body dystrophies and abdominal hernias were excluded. We also excluded the participants who self-declared as having Asian and Native Brazilian ethnicity/skin color due to the small number (297 and 136, respectively), 150 participants who did not declare ethnicity/ skin color and 15 without information on indicators of abdominal adiposity. The final sample consisted of 8,449 participants (Figure 1). Some participants had more than one condition for exclusion.

Figure 1 Study sample selection flowchart. Note: Percentage of exclusion (sample with valid images and final sample): 23%. 

Carotid intima-media thickness (CIMT)

All the research centers collected the CIMT measurement using a standardized method, utilizing an Aplio XG(tm), Toshiba equipment, with a 7.5 MHz linear transducer. The technique used in the study has been published elsewhere.15,16 For this article, CIMT was defined as the mean of the mean values of the right and left carotid arteries. The 75th percentile was used to dichotomize this variable according to gender (male: 0.69 mm, female: 0.64 mm). The 75th percentile was based on technical consensuses and previous studies.17

Indicators of abdominal adiposity

Anthropometric measurements were obtained using standardized equipment and techniques. The WC was measured at midpoint between the inferior border of the costal arch and the iliac crest, at the median axillary line and at the hip circumference at the maximal protrusion of the gluteal muscles, over the trousers of the study clothing. These circumferences were used to calculate the WHR. The C index was calculated using the formula: WCm/0.109xWeightkg/Heightm .18

The LAP19 was calculated using gender-specific equations: Men:WCcm65xtriglyceridesmmol/L;Women:WCcm58xtriglyceridesmmol/L , as well as the VAI:19 Men:WCcm/39.68+1.88xbodymassindexkg/m2xtriglyceridesmmol/L/0.81x1.31/HDLcholesterolmmol/L;WomenWCcm/36.58+1.89xbodymassindexkg/m2xtriglyceridesmmol/L/0.81x1.52/HDLcholesterolmmol/L .

The indicators were categorized in the presence and absence of abdominal adiposity, according to the cut-off points defined by Eickemberg et al.,20 Respectively, the following values were used for white, brown and black individuals: WC: men 89.9 cm; 90.2 cm and 91.7 cm; women 80.4 cm; 82.7 cm and 85.4 cm; WHR: men 0.92; 0.92 and 0.90; women 0.82; 0.83 and 0.84; C index: men 1.24; 1.24 and 1.24; women 1,20; 1.22 and 1.19; LAP: men 29.81; 32.39 and 33.08; women 22,64; 30.27 and 27.12; VAI: men 1.74; 2.08 and 1.68; women 1.44; 2.16 and 1.65. We chose to use the term "adiposity" instead of obesity for the five indicators, considering that LAP and VAI reflect the function of visceral fat, and not only the accumulation of abdominal fat, such as WC, WHR and C index.10,11

Covariates

Ethnicity/skin color was self-attributed and categorized as white, brown and black. The level of schooling was categorized as complete college/university education, complete high school and incomplete and complete elementary school. Smoking was stratified as nonsmokers, ex-smokers, and current smokers.

Weight and height were measured with participants wearing the study clothing, without shoes and accessories. A Toledo scale and a Seca stadiometer were used for the measurements of weight and height, respectively. These variables were used to calculate adiposity indexes.

Blood samples were collected by venipuncture after 12 hours of fasting. Triglyceride and HDL-cholesterol tests were performed by colorimetric enzymatic and homogeneous enzymatic colorimetric methods without precipitation, respectively. LDL-cholesterol levels were obtained using Friedewald's formula. Triglycerides and HDL-cholesterol were used to calculate the LAP and VAI.

Arterial hypertension was defined with a mean systolic blood pressure ≥ 140 mmHg and a mean diastolic ≥ 90 mmHg; or if the individual was undergoing antihypertensive treatment. Blood pressure was measured three times, considering the mean of the last two measurements for calcualtion.15

Statistical analysis

A data descriptive analysis was carried out to evaluate the distribution of participants according to the characteristics of interest. Due to the asymmetric distribution of some variables it was decided to show the continuous variables as median and interquartile range. Categorical variables were expressed as absolute and relative frequencies.

The frequency of high CIMT (≥75th percentile) and abdominal adiposity through WC, WHR, C index, LAP and VAI indicators were estimated. Regression coefficients and odds ratios (OR), with their respective 95% confidence intervals, were calculated using linear regression and multivariate logistic analyses, respectively. Regression analyses were used to identify the magnitude of the effect of the abdominal adiposity presence, measured by the indicators in a categorical scale, on the mean of the CIMT in the linear model and on the diagnosis of high CIMT in the logistic analysis.

Due to the asymmetric distribution, CIMT values were transformed into natural logarithm for linear regression. For the logistic regression, the dichotomized CIMT was used in the 75th percentile of the distribution. The main independent variables (abdominal adiposity indicators) were introduced separately in five models for each regression analysis (linear and logistic) by gender. All models were adjusted for age, ethnicity/skin color, level of schooling, smoking status, HDL-cholesterol, LDL-cholesterol, and arterial hypertension, chosen for their proximity to the atherosclerosis condition.21

An effect modification analysis was performed to test the variables gender and ethnicity/skin color in all proposed models using the maximum likelihood ratio test. No effect modification was detected; however, we maintained the analyses stratified by gender based on theoretical references.5,22 A diagnostic evaluation of the multiple linear regression models was carried out through graphic analysis of residues, evaluation of influential points and multicollinearity. The Hosmer-Lemeshow test, goodness-of-fit test using the Pearson's residuals and Deviance residues, McFadden's Adjusted R2 and ROC curve, were used to diagnose logistic model adjustment. A significance level of 5% was established and the Stata 12 software (Stata Corporation, College Station, Texas, USA) was used for the analyses.

Results

The sample characteristics are shown in Table 1. Men and women with high CIMT had an older median age (47 and 48 years versus 57 years) and a higher frequency of abdominal adiposity (men 71.9% to 78.4%; and women 66% to 73.1%).

Table 1 Baseline characteristics, according to the carotid intima-media thickness and gender. ELSA-Brazil, 2008-2010 

Male Female
CIMT < P75 CIMT > P75 CIMT < P75 CIMT > P75
n = 2,779 n = 958 n = 3,503 n =1,209
Age, median (IQR) 48 (43-54) 57 (51-63) 47 (43-53) 57 (51-62)
Ethnicity/skin color, n (%)
White 1,562 (56.2) 545 (56.8) 2,010 (57.3) 705 (58.3)
Brown 836 (30.0) 266 (27.7) 883 (25.2) 306 (25.3)
Black 381 (13.7) 147 (15.3) 610 (17.4) 198 (16.3)
Level of schooling, n (%)
Complete College/University 1,352 (48.6) 420 (43.8) 1,976 (56.4) 613 (50.7)
Complete High School 1,049 (37.7) 310 (32.3) 1,292 (36.8) 413 (34.1)
Incomplete + complete Elementary School 378 (13.6) 228 (23.8) 235 (6.7) 183 (15.1)
Smoking status, n (%)
Never smoked 1,588 (57.1) 366 (38.2) 2,284 (65.2) 695 (57.4)
Former smoker 811 (29.1) 404 (42.2) 803 (22.9) 334 (27.6)
Current smoker 380 (13.6) 187 (19.5) 416 (11.8) 180 (14.8)
HDL-cholesterol, median (IQR) 49 (43-57) 49 (43-57) 60 (52-71) 59 (51-70)
LDL-cholesterol, median (IQR) 130 (110-152) 138.5 (117-161) 127 (106-149) 140 (119-164)
Arterial hypertension, n (%) 709 (25.5) 499 (52.1) 644 (18.3) 540 (44.7)
Mean BMI (IQR) 26.0 (23.6-28.5) 27.2 (24.6-29.9) 25.3 (22.7-29.5) 27.3 (24.1-30.4)
Abdominal adiposity, median (IQR)
Waist circumference 92.3 (85.5-99.4) 96.6 (89.4-104.1) 83.2 (76.5-91.4) 88.9 (81-97.3)
Waist-to-hip ratio 0.93 (0.88-0.97) 0.96 (0.92-1.00) 0.82 (0.78-0.87) 0.86 (0.81-0.91)
Conicity index 1.26 (1.21-1.30) 1.29 (1.24-1.34) 1.19 (1.14-1.25) 1.23 (1.18-1.29)
Lipid accumulation product 38.8 (22.1-65.3) 51.2(30.4-82.2) 26.48 (15.3-44.4) 39.9 (23.4-63.3)
Visceral adiposity index 2.41 (1.47-3.95) 2.91 (1.74-4.66) 1.62(1.06-2.61) 2.15 (1.37-3.43)
Abdominal adiposity, n (%)
Waist circumference 1,599 (57.5) 690 (72.0) 1,939 (55.3) 884 (73.1)
Waist-to-hip ratio 1,628 (58.5) 751 (78.3) 1,744 (49.7) 847 (70.0)
Conicity index 1,740 (62.6) 738 (77.0) 1,657 (47.3) 798 (66.0)
Lipid accumulation product 1,670 (60.0) 715 (74.6) 1,834 (52.3) 865 (71.5)
Visceral adiposity index 1,774 (63.8) 708 (73.9) 1,733 (49.4) 799 (66.0)

The sum of observations may differ in some variables due to data loss; CIMT: carotid intima-media thickness; P75: 75th percentile; IQR: interquartile range; n (%): number of observations (frequency); BMI: body mass index.

The values of abdominal adiposity indicators were higher in men and in men and women with CIMT > 75th percentile. The men had a median CIMT of 0.59 mm (0.52-0.69), and women of 0.56 mm (0.50-0.64) (data not shown).

In both genders, the adiposity measured by the five indicators was associated with the mean log of CIMT. The C index showed the smallest effect (Table 2).

Table 2 Multivariate linear regression analysis between abdominal adiposity, measured by five indicators alone, and CIMT, according to gender. ELSA-Brazil 2008-2010 

Male Female
n = 3,737 n = 4,712
β (SE) 95%CI β (SE) 95%CI
Waist circumference 0.045 (0.006) 0.033;0.058 0.025 (0.004) 0.016;0.035
Waist-to-hip ratio 0.032 (0.006) 0.019;0.045 0.026 (0.004) 0.016;0.035
Conicity index 0.016 (0.006) 0.003;0.029 0.011 (0.004) 0.002;0.020
Lipid accumulation product 0.030 (0.006) 0.016;0.043 0.024 (0.004) 0.014;0.034
Visceral adiposity index 0.022 (0.007) 0.007;0.037 0.020 (0.005) 0.010;0.031

The models were adjusted for age, ethnicity/skin color, level of schooling, smoking status, HDL-cholesterol, LDL-cholesterol and arterial hypertension.

According to the multivariate logistic regression analysis (Table 3), there was an association between the diagnosis of adiposity by WC, WHR, LAP and VAI with CIMT in both genders. The adiposity diagnosed by WC showed a greater effect on CIMT in both genders. According to the diagnostic analyses of the models, there were no assumption violations, indicating the models' adequacy.

Table 3 Odds ratio and respective 95% confidence intervals for the association between abdominal adiposity, diagnosed by five indicators alone, with CIMT, according to gender. ELSA-Brazil 2008-2010 

Male Female
n = 3,737 n = 4,712
OR (95%CI) OR (95%CI)
Waist circumference 1.47 (1.22;1.77) 1.38 (1.17;1.64)
Waist-to-hip ratio 1.37 (1.12;1.67) 1.33 (1.13;1.57)
Conicity index 1.02 (0.83;1.24) 1.12 (0.95;1.32)
Lipid accumulation product 1.39 (1.13;1.69) 1.28 (1.08;1.53)
Visceral adiposity index 1.42 (1.13;1.77) 1.31 (1.08;1.59)

The models were adjusted for age, ethnicity/skin color, level of schooling, smoking status, HDL-cholesterol, LDL-cholesterol and arterial hypertension.

Discussion

Using data from the ELSA-Brasil study, associations were observed between abdominal adiposity measurements and CIMT, a noninvasive marker of subclinical atherosclerosis capable of predicting cardiovascular disease.23 It has been documented, in a study carried out in Southeast Brazil, the definition of CIMT as the thickening of the intima-media complex starting from 1.0mm.24 Considering this value, in our study, the presence of abdominal adiposity diagnosed by WC, WHR, LAP and VAI showed an important effect, with a variation of 0.02 mm to 0.04 mm in the log of CIMT in both genders. Polack et al.,23 using data from the Framingham offspring cohort study, found that an annual change in CIMT > 0.02 mm was associated with a more than two-fold risk of cerebrovascular accident.23

Few studies have compared different indicators of adiposity with CIMT, and the present study is the first one that separately investigated the contribution of different indicators of abdominal adiposity. Previous studies also carried out with ELSA-Brazil data also evaluated the association between traditional risk factors and CIMT.25,26 WC, WHR, waist-to-height ratio (WHtR) and neck circumference (NC) were included in the analysis. The latter indicator had the strongest association with CIMT. The authors suggest that the local effect produced by neck fat acts directly on the carotid arteries.25,26 Our study did not include neck circumference; however, the measures used in the study are relatively simple and reflect important information about the risk of developing cardiovascular diseases, at individual and population levels.27

Most studies that evaluated the association between abdominal adiposity and CIMT used visceral fat measured by imaging tests. In these studies, visceral fat was strongly associated with CIMT,28,29 but the comparison with these findings is limited by the different methods used to identify abdominal and visceral fat. The association between abdominal adiposity and subclinical atherosclerosis is possibly related to the visceral component of abdominal fat. The indicators evaluated in the present study are indirect measures of this component, but they show good correlation with visceral fat and are accessible to the overall population.27

The WC was the indicator most strongly associated with CIMT. Similar to our data, other studies have also found an association between WC and CIMT in healthy 45- to 65-year-old Dutch adults, hospitalized Irish adults, and hospitalized subjects aged 21-83 years in China.7,30,31 WC is described as an indicator of abdominal adiposity with a greater capacity to predict metabolic alterations and cardiovascular diseases, being one of the measures that most closely approximates to visceral fat measured by imaging tests.27

In this study, WHR also showed an important association with CIMT between men and women. Large epidemiological studies have described the strongest associations not only between adiposity diagnosed by WHR and CIMT, but also with the prevalence of myocardial infarction, incidence of coronary artery disease, high coronary risk and coronary events.6,32,33 However , evidence shows that the gluteofemural region consists mainly of subcutaneous adipose tissue. This tissue does not seem to play an important role in the pathogenesis of cardiovascular disease. By including hip measurement, WHR reflects the effect of total adiposity as a risk factor for atherosclerosis and other cardiovascular outcomes.32 Thus, WHR can be useful as a simple and consistent indicator by reflecting the combination of total and abdominal adiposity.

The C index was the indicator that showed the lowest effect of abdominal adiposity on the CIMT in this study. No studies were found that investigated this indicator in relation to subclinical atherosclerosis. Previous publications have observed the association of this indicator with high coronary risk in Brazilians from the Northeast region34 and metabolic alterations in Indian civil servants.35 Although the C index is not a new indicator, it remains little explored and there is no consensus on ideal cutoff points for the Brazilian population. As it considers weight and height, similar to the WHR, it may be useful to demonstrate the combination of total and abdominal adiposities on cardiovascular outcomes. One hypothesis for the absence of association in this study is the large percentage of participants of white ethnicity/skin color, since the performance of this indicator as a discriminator of coronary risk works better in black populations.34

VAI is an indicator originally proposed to identify the distribution and function of adipose tissue, indirectly expressing cardiovascular risk. Due to the inclusion of physical and metabolic parameters (anthropometric measures and biochemical tests), this indicator may reflect the altered production of adipocytokines, increase in lipolysis and free fatty acids in plasma.10

Evidence indicates that VAI was independently associated with cardiovascular (OR = 2.45, 95%CI: 1.52, 3.95) and cerebrovascular events (OR = 1.63, 95%CI: 1.06, 2.50) in healthy and non-obese Italians.10 The only study found that evaluated the association between VAI and a subclinical measure of atherosclerosis - the CAC - coronary artery calcium score - was carried out with 33,468 Koreans with a mean age of 42 years. Similar to the present findings, but with a lower magnitude of association, the highest chance of having subclinical atherosclerosis (OR = 1.26, 95%CI: 1.14, 1.38) was shown in individuals with the highest tertile of VAI.9 It was found in the current study that the chance of men and women with abdominal adiposity assessed by VAI of having high CIMT was 42% and 31%, respectively. This difference between the studies was possibly observed due to the characteristics of the investigated populations (healthy participants versus patients from a Korean university hospital).9

Similar to VAI, the LAP showed an association between the presence of abdominal adiposity and CIMT. No previous evidence was found on the association between LAP and subclinical atherosclerosis. The LAP was developed to reflect combined metabolic and physical alterations, using WC and triglycerides. Therefore, it measures lipid overaccumulation and stands out as a cardiovascular risk factor in adults. This indicator has been investigated in the context of metabolic and cardiovascular diseases and mortality. An American cohort study with approximately 5,000 subjects treated at a cardiologic clinic between 1995-2006 showed an association between LAP and cardiovascular mortality (HR: 1.52 95%CI: 1.27, 1.82), adjusted for age, gender, smoking, diabetes, blood pressure, LDL-cholesterol and HDL-cholesterol.36

However, more studies are needed, especially in Brazil, to broaden the knowledge of less popular indicators such as VAI and LAP. Evidence suggests that information not only on the fatty tissue accumulated in the abdominal region is provided through LAP and VAI, but also on fat deposition in areas such as the liver, muscle, heart and arteries. This lipid overaccumulation causes changes in intracellular metabolism and contributes to the occurrence of cardiovascular disease, including atherogenesis and death.19

In the present study the associations between adiposity measures and CIMT were more significant for men than for women. Women have more total body fat (and subcutaneous), often in the legs and buttocks and, especially, before menopause. Men tend to accumulate fat in the abdominal region throughout life, so they are at higher risk for developing cardiovascular outcomes,22 including atherosclerosis.

Evidence shows differences in the progression of CIMT and adiposity due to the ethnicity/ skin color.37 The cut-off points used in this study incorporated the differences between gender and ethnicity/skin color20 and, perhaps because of that, no effect modification was detected.

Through the coefficients of determination (R2), the linear regression model variables, including each indicator alone, explained approximately 30% of the total CIMT variability. In our study, the models were adjusted for age, ethnicity/skin color, level of schooling, smoking, HDL-cholesterol, LDL-cholesterol and arterial hypertension. The study carried out by Santos et al.,25 using the ELSA-Brazil sample, found coefficients of determination (R2) close to 40% when investigating the association of risk factors with CIMT through the variables: blood pressure, glucose metabolism, lipid profile and adiposity (body mass index, WC, hip circumference, WHR, waist-to-height ratio, neck circumference). It is noteworthy that, in addition to adiposity patterns, geographic, genetic, environmental and behavioral characteristics are also associated with the occurrence of atherosclerosis.

The 75th percentile of the distribution was used to categorize CIMT in the logistic regression analysis. Other values for this classification might have yielded more consistent results. However, studies show subjects with CIMT values above the 75th percentile with a higher risk of developing cardiovascular disorders.17,38 It is known that the atheroma plaques may be more representative of atherosclerosis than CIMT.39 However, our population is relatively young, and when CIMT was dichotomized at 1.5 mm, a proposed classification for atheroma plaque according to the international consensus,5 it showed a low frequency of participants with this condition (4% in men and 2% in women) (data not shown).

The use of a stringent protocol for image acquisition and quality control provided reliable and accurate data of CIMT measurements in this study. To reduce the influence of the evaluator, the reading of all images was centralized, and the automated measurements were performed by software. Although we did not adjust the models by body mass index, we excluded subjects with class III obesity and those who underwent bariatric surgery from the analysis, aiming to filter the effect of abdominal adiposity without influence of excessive total body fat.

This study has limitations. Data on menopause were not considered. When women reach menopause they lose the protection provided by the hormone estrogen and, as they get older, there is a greater accumulation of abdominal fat, as well as an increase in the occurrence of cardiovascular problems.22 The literature is clear about the effect of age on atherosclerosis.5 Although the analyzes were adjusted for age in this article, it did not allow the observation of the effect of adiposity on CIMT at different age groups. It is not possible to affirm causality due to the cross-sectional design of this study; however, it seems unlikely that arterial thickening occurs before the high accumulation of abdominal fat. ELSA-Brazil is an occupational cohort and generalizations for the Brazilian population are limited, despite similarities in the prevalence indicators observed in ELSA-Brasil and VIGITEL studies.40

Conclusion

The observed results reinforce the importance of abdominal adiposity for the condition of subclinical atherosclerosis. Abdominal adiposity, identified through WC, WHR, LAP and VAI, was associated with CIMT in both genders, with the traditional WC anthropometric indicator standing out. WC, when compared to the other indicators, and men, when compared to women, showed the most significant effects.

Sources of Funding

This study was funded by Ministério da Saúde e Ministério da Ciência and Tecnologia do Brasil.

Study Association

This article is part of the thesis of Doctoral submitted by Michaela Eickemberg, from Universidade Federal da Bahia.

Ethics approval and consent to participate

This study was approved by the Ethics Committee of the ISC/UFBA, da FIOCRUZ, do Hospital Universitário-USP, da UFMG, do Centro de Ciências de Saúde da UFES, do Hospital de Clinicas de Porto Alegre under the protocol number 027/06, 343/06, 669/06, 186/06, 041/06, 194/06 respectively. All the procedures in this study were in accordance with the 1975 Helsinki Declaration, updated in 2013. Informed consent was obtained from all participants included in the study.

References

1 Gast KB, den Heijer M, Smit JWA, Widya RL, Lamb HJ, de Roos A, et al. Individual contributions of visceral fat and total body fat to subclinical atherosclerosis: The NEO study. Atherosclerosis. 2015;241(2):547-54. [ Links ]

2 World Health Organization.(WHO). Waist circumference and waist-hip ratio. Report of a WHO expert consultation. Geneva;2008. P.8-11. [ Links ]

3 Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa nacional de saúde 2013: Ciclos de vida - Brasil e grandes regiões. 2015. [ Links ]

4 Almeida-Pititto B, Ribeiro-Filho FF, Santos IS, Lotufo PA, Bensenor IM, Ferreira SR. Association between carotid intima-media thickness and adiponectin in participants without diabetes or cardiovascular disease of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Eur J Prev Cardiol. 2017;24(2):116-22. [ Links ]

5 Nezu T, Hosomi N, Aoki S, Matsumoto M. Carotid intima-media thickness for atherosclerosis. J Atheroscler Thromb. 2016;23(1):18-31. [ Links ]

6 Yan RT, Yan AT, Anderson TJ, Buithieu J, Charbonneau F, Title L, et al. The differential association between various anthropometric indices of obesity and subclinical atherosclerosis. Atherosclerosis. 2009;207(1):232-8. [ Links ]

7 Zhang L, Shen Y, Zhou J, Pan JM, Yu HY, Chen HB, et al. Relationship between waist circumference and elevation of carotid intima-media thickness in newly-diagnosed diabetic patients. Biomed Environ Sci. 2014;27(5):335-42. [ Links ]

8 Zhang F, Feng L, Chen Y, Geng Z, Xu X. Relationship between carotid artery intima-media thickness and cardiovascular risk factors in Chinese Uygur population. Int J Clin Exp Med. 2014;7(12):5412-20. [ Links ]

9 Park HJ, Kim J, Park SE, Park CY, Lee WY, Oh KW, et al. Increased risk of subclinical atherosclerosis associated with high visceral adiposity index in apparently healthy Korean adults: the Kangbuk Samsung Health Study. Ann Med. 2016;48(6):410-6. [ Links ]

10 Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, et al. VAI: A reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care. 2010;33(4):920-2. [ Links ]

11 Kahn HS. The Lipid Accumulation Product Is Better Than BMI for Identifying Diabetes. Diabetes Care. 2006;29(1):151-3. [ Links ]

12 Roriz AK, Passos LC, de Oliveira CC, Eickemberg M, Moreira PD, Sampaio LR. Evaluation of the accuracy of anthropometric clinical indicators of visceral fat in adults and elderly. PLoS One. 2014;9(7): e103499. [ Links ]

13 Aquino EM, Barreto SM, Bensenor IM, Carvalho MS, Chor D, Duncan BB, et al. Brazilian Longitudinal Study of Adult health (ELSA-Brasil): Objectives and design. Am J Epidemiol. 2012;175(4):315-24. [ Links ]

14 Schmidt MI, Griep RH, Passos VM, Luft VC, Goulart AC, Menezes GM de S, et al. Estrategias e desenvolvimento de garantia e controle de qualidade no ELSA-Brasil. Rev Saude Publica. 2013;47(Supl 2):105-12. [ Links ]

15 Mill JG, Pinto K, Griep RH, Goulart A, Foppa M, Lotufo P, et al. Medical assessments and measurements in ELSA-Brasil. Rev Saude Publica. 2013;47(2):54-62. [ Links ]

16 Santos IS, Bittencourt MS, Oliveira IRS, Souza AG, Meireles DP, Rundek T, et al. Carotid intima-media thickness value distributions in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Atherosclerosis. 2014;237(1):227-35. [ Links ]

17 Rosvall M, Persson M, Östling G, Nilsson PM, Melander O, Hedblad B, et al. Risk factors for the progression of carotid intima-media thickness over a 16-year follow-up period: The Malmö Diet and Cancer Study. Atherosclerosis. 2015;239(2):615-21. [ Links ]

18 Valdez R, Seidell JC, Ahn YI, Weiss KM. A new index of abdominal adiposity as an indicator of risk for cardiovascular disease. A cross-population study. Int J Obes. 1993;17(77):77-82. [ Links ]

19 Kahn HS. The "lipid accumulation product" performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison. BMC Cardiovasc Disord. 2005;5:26. [ Links ]

20 Eickemberg M, Amorim LDAF, Pitanga FJG, Aquino EML de, Fonseca M de JM da, Maria da Conceição Chagas de Almeida, et al. Obesidade abdominal no Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil): avaliação da acurácia de indicadores diagnósticos na ausência de padrão ouro. [ Links ]

21 Qu B, Qu T. Causes of changes in carotid intima-media thickness: a literature review. Cardiovasc Ultrasound. 2015;13:46. [ Links ]

22 Palmer BF, Clegg DJ. The sexual dimorphism of obesity. Mol Cell Endocrinol. 2015 Feb 15;402:113-9. [ Links ]

23 Polak JF, Pencina MJ, Pencina KM, O'Donnell CJ, Wolf PA, D'Agostino RB. Carotid-Wall Intima-Media Thickness and Cardiovascular Events. N Engl J Med. 2011;365(3):213-21. [ Links ]

24 Casella IB, Sotelo FJB, Yamazaki Y, Presti C, Vassoler A, Melo HAH. Comparison of common carotid artery intima-media thickness between Brazilian Euro-descendants and Afro-descendants with atherosclerosis risk factors. Clinics. 2009;64(7):657-64. [ Links ]

25 Santos IS, Alencar AP, Rundek T, Goulart AC, Barreto SM, Pereira AC, et al. Low impact of traditional risk factors on carotid intima-media thickness: The ELSA-brasil cohort. Arterioscler Thromb Vasc Biol. 2015;35(9):2054-9. [ Links ]

26 Baena CP, Lotufo PA, Santos IS, Goulart AC, Bittencourt MS, Duncan BB, et al. Neck circumference is associated with carotid intimal-media thickness but not with coronary artery calcium: Results from The ELSA-Brasil. Nutr Metab Cardiovasc Dis. 2016;26(3):216-22. [ Links ]

27 Carneiro Roriz AK, Santana Passos LC, Cunha de Oliveira C, Eickemberg M, de Almeida Moreira P, Barbosa Ramos L. Anthropometric clinical indicators in the assessment of visceral obesity?: an update. Nutr Clín Diet Hosp. 2016;36(2):168-79. [ Links ]

28 Rallidis LS, Baroutsi K, Zolindaki M, Karagianni M, Varounis C, Dagres N, et al. Visceral adipose tissue is a better predictor of subclinical carotid atherosclerosis compared with waist circumference. Ultrasound Med Biol. 2014;40(6):1083-8. [ Links ]

29 Oike M, Yokokawa H, Fukuda H, Haniu T, Oka F, Hisaoka T, et al. Association between abdominal fat distribution and atherosclerotic changes in the carotid artery. Obes Res Clin Pract. 2014;8(5):e448-58. [ Links ]

30 Maher V, O'Dowd M, Carey M, Markham C, Byrne A, Hand E, et al. Association of central obesity with early Carotid intima-media thickening is independent of that from other risk factors. Int J Obes. 2009;33(1):136-43. [ Links ]

31 Gast KB, Smit JWA, Heijer M den, Middeldorp S, Rippe RCA, le Cessie S, et al. Abdominal adiposity largely explains associations between insulin resistance, hyperglycemia and subclinical atherosclerosis: The NEO study. Atherosclerosis. 2013;229(2):423-9. [ Links ]

32 Canoy D. Distribution of body fat and risk of coronary heart disease in men and women. Ischemic Heart Dis. 2008;23(6):591-600. [ Links ]

33 Pitanga FJG, Lessa I. Associação entre indicadores antropométricos de obesidade e risco coronariano em adultos na cidade de Salvador, Bahia, Brasil. Rev Bras Epidemiol. 2007;10(2):239-48. [ Links ]

34 Pitanga JFG, Lessa I. Indicadores antropométricos de obesidade como instrumento de triagem para risco coronariano elevado em adultos na cidade de Salvador - Bahia. Arq Bras Cardiol. 2005;85(1):26-31. [ Links ]

35 Ghosh A, Bose K, Das Chaudhuri AB. Association of food patterns, central obesity measures and metabolic risk factors for coronary heart disease (CHD) in middle aged Bengalee Hindu men, Calcutta, India. Asia Pac J Clin Nutr. 2003;12(2):166-71. [ Links ]

36 Ioachimescu AG, Brennan DM, Hoar BM, Hoogwerf BJ. The lipid accumulation product and all-cause mortality in patients at high cardiovascular risk: a PreCIS database study. Obesity (Silver Spring). 2010;18(9):1836-44. [ Links ]

37 Goh LGH, Dhaliwal SS, Welborn TA, Lee AH, Della PR. Ethnicity and the association between anthropometric indices of obesity and cardiovascular risk in women?: a cross-sectional study. BMJ Open. 2014;4(5):e004702. [ Links ]

38 Goulart AC, Santos IS, Bittencourt MS, Lotufo PA, Benseñor IM. Migraine and subclinical atherosclerosis in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Cephalalgia. 2016;36(9):840-8. [ Links ]

39 Spence JD. Carotid plaque measurement is superior to IMT. Atherosclerosis. 2012;220(1):34-5. [ Links ]

40 Brasil. Ministério da Saúde. Departamento de Análise de Situação de Saúde. Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico, Vigitel, 2010. Brasília; 2011. [ Links ]

Received: April 11, 2018; Revised: July 23, 2018; Accepted: July 23, 2018

Mailing Address: Michaela Eickemberg, Rua Basílio da Gama, 316. Postal Code 40110-040, Canela, Salvador, BA - Brazil. E-mail: mieickemberg@yahoo.com.br, mieickemberg@gmail.com

Author contributions

Conception and design of the research, analysis and interpretation of the data, statistical analysis and writing of the manuscript: Eickemberg M, Amorim LDAF, Matos SMA; critical revision of the manuscript for intellectual content: Amorim LDAF, Almeida MCC, Aquino EML, Fonseca MJM, Santos IS, Diniz MFS, Barreto SM, Matos SMA

Potential Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Creative Commons License This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.