Anatomic fat depots and cardiovascular risk: a focus on the leg fat using nationwide surveys (KNHANES 2008–2011)

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Abstract

Background

Although central fat is a well-known risk factor for cardiovascular disease (CVD) and cardiometabolic disorders, the effect of other regional fats or muscle distribution on CVD risk has not been fully investigated.

Methods

This was a cross-sectional study using nationally representative samples of 15,686 subjects from the 2008–2011 Korea National Health and Nutrition Examination Survey. Individual CVD risk was evaluated in adults aged ≥20 without prior CVD, using atherosclerotic cardiovascular disease (ASCVD) risk equations according to the 2013 ACC/AHA guidelines. Body composition was assessed by dual X-ray absorptiometry.

Results

Ratio of leg fat to total fat (LF/TF ratio) was the most predictive for CVD among body fat or muscle distribution parameters (AUC = 0.748, 95% CI 0.741–0.755). ASCVD risk score was gradually increased with decreased LF/TF ratio (P < 0.001), and individuals whose LF/TF ratio in lowest tertile tended to belong to the high-risk (10-year risk >10%) group compared to those in the highest tertile (OR = 6.25, 95% CI 5.60–6.98). Subjects in the lowest tertile showed increased risk of cardiometabolic risk factor components including obesity, hypertension, diabetes, dyslipidemia, chronic kidney disease, and albuminuria (OR range 2.57–11.24, all P < 0.001). In addition, a higher LF/TF ratio was associated with decreased ASCVD risk, even in subjects with multiple CVD risk factors. Multiple logistic regression analyses also demonstrated this association (OR = 1.85, 95% CI 1.36–2.52).

Conclusions

Among various body composition parameters, LF/TF ratio was superior in predicting higher CVD risk and a higher LF/TF ratio was independently associated with decreased risk of CVD and each cardiometabolic risk factor.

Electronic supplementary material

The online version of this article (doi:10.1186/s12933-017-0536-4) contains supplementary material, which is available to authorized users.

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Most cited references 31

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General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

Ralph B. D’Agostino, Ramachandran S. Vasan, Michael J. Pencina … (2008)

Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.

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Gluteofemoral body fat as a determinant of metabolic health.

K. N. Manolopoulos, F Karpe, K. Frayn (2010)

Body fat distribution is an important metabolic and cardiovascular risk factor, because the proportion of abdominal to gluteofemoral body fat correlates with obesity-associated diseases and mortality. Here, we review the evidence and possible mechanisms that support a specific protective role of gluteofemoral body fat. Population studies show that an increased gluteofemoral fat mass is independently associated with a protective lipid and glucose profile, as well as a decrease in cardiovascular and metabolic risk. Studies of adipose tissue physiology in vitro and in vivo confirm distinct properties of the gluteofemoral fat depot with regards to lipolysis and fatty acid uptake: in day-to-day metabolism it appears to be more passive than the abdominal depot and it exerts its protective properties by long-term fatty acid storage. Further, a beneficial adipokine profile is associated with gluteofemoral fat. Leptin and adiponectin levels are positively associated with gluteofemoral fat while the level of inflammatory cytokines is negatively associated. Finally, loss of gluteofemoral fat, as observed in Cushing's syndrome and lipodystrophy is associated with an increased metabolic and cardiovascular risk. This underlines gluteofemoral fat's role as a determinant of health by the long-term entrapment of excess fatty acids, thus protecting from the adverse effects associated with ectopic fat deposition.

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Sarcopenia is associated with significant liver fibrosis independently of obesity and insulin resistance in nonalcoholic fatty liver disease: Nationwide surveys (KNHANES 2008-2011).

Yong-ho Lee, Seung Up Kim, Kijun Song … (2016)

Sarcopenia is associated with nonalcoholic fatty liver disease (NAFLD). This study investigated whether sarcopenia is associated with significant liver fibrosis in subjects with NAFLD. Data from the Korean National Health and Nutrition Examination Surveys 2008-2011 database were analyzed. NALFD was defined by NAFLD liver fat score, comprehensive NAFLD score, or hepatic steatosis index. Degree of liver fibrosis was assessed by NAFLD fibrosis score (NFS), FIB-4, and Forns index. Significant liver fibrosis was defined as FIB-4 ≥2.67 and the highest quartile values of NFS and Forns index. Sarcopenia index (= total appendicular skeletal muscle mass [kg]/body mass index (kg/m(2) ]) was calculated using dual-energy X-ray absorptiometry. Using the NAFLD liver fat score, NAFLD was identified in 2761 (28.5%) of 9676 subjects. Of subjects with NAFLD, sarcopenia was identified in 337 (12.2%). Sarcopenia was significantly associated with significant liver fibrosis assessed in fibrosis prediction models (all P < 0.05). In subgroups stratified according to body mass index and homeostasis model assessment of insulin resistance, a significant association between sarcopenia and significant liver fibrosis by NFS was consistently present (odds ratio = 1.76-2.68 depending on the subgroup, all P < 0.05). Multivariate logistic regression analysis demonstrated an independent association between SI and significant liver fibrosis by NFS after adjusting for other confounders (odds ratio = 0.52-0.67, all P < 0.01). Other NAFLD (comprehensive NAFLD score, hepatic steatosis index) and fibrosis prediction models (FIB-4 and Forns index) produced similar results.

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Author and article information

Contributors

Eugene Han: jinsjins85@gmail.com

Yong-ho Lee:

ORCID: http://orcid.org/0000-0002-6219-4942

+82-2-2228-1943 , yholee@yuhs.ac

Byung-Wan Lee: BWANLEE@yuhs.ac

Eun Seok Kang: edgo@yuhs.ac

In-Kyu Lee: leei@knu.ac.kr

Bong-Soo Cha: bscha@yuhs.ac

Journal

Journal ID (nlm-ta): Cardiovasc Diabetol

Journal ID (iso-abbrev): Cardiovasc Diabetol

Title: Cardiovascular Diabetology

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2840

Publication date (Electronic): 26 April 2017

Publication date PMC-release: 26 April 2017

Publication date Collection: 2017

Volume: 16

Electronic Location Identifier: 54

Affiliations

[1 ]ISNI 0000 0004 0470 5454, GRID grid.15444.30, Division of Endocrinology, Department of Internal Medicine, , Yonsei University College of Medicine, ; 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722 South Korea

[2 ]ISNI 0000 0004 0470 5454, GRID grid.15444.30, Graduate School, , Yonsei University College of Medicine, ; Seoul, South Korea

[3 ]ISNI 0000 0004 0470 5454, GRID grid.15444.30, Institue of Endocrine Research, , Yonsei University College of Medicine, ; Seoul, South Korea

[4 ]ISNI 0000 0001 0661 1556, GRID grid.258803.4, Division of Endocrinology, Department of Internal Medicine, , Kyungpook National University School of Medicine, ; Daegu, South Korea

[5 ]ISNI 0000 0001 0669 3109, GRID grid.412091.f, Division of Endocrinology, Department of Internal Medicine, , Keimyung University School of Medicine, ; Daegu, South Korea

Author information

Yong-ho Lee http://orcid.org/0000-0002-6219-4942

Article

Publisher ID: 536

DOI: 10.1186/s12933-017-0536-4

PMC ID: 5405479

PubMed ID: 28441953

SO-VID: e342c8b8-b42b-4d08-8058-a7e7897993ea

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 8 February 2017

Date accepted : 18 April 2017

Funding

Funded by: Korea Healthcare Technology Research Development

Award ID: HI14C2476

Award ID: HI16C1501

Award Recipient : Yong-ho Lee

Custom metadata

ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: cardiovascular disease risk factors,risk score,obesity,metabolic syndrome

Data availability:

ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: cardiovascular disease risk factors, risk score, obesity, metabolic syndrome

Anatomic fat depots and cardiovascular risk: a focus on the leg fat using nationwide surveys (KNHANES 2008–2011)

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Karger: Nutrition and Dietetics

Most cited references 31

General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

Gluteofemoral body fat as a determinant of metabolic health.

Sarcopenia is associated with significant liver fibrosis independently of obesity and insulin resistance in nonalcoholic fatty liver disease: Nationwide surveys (KNHANES 2008-2011).

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