How to best assess abdominal obesity

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Abstract

<div class="section"> <a class="named-anchor" id="S1">  </a> <h5 class="section-title" id="d5023326e137">Purpose of review</h5> <p id="P1">Abdominal obesity, especially the increase of visceral adipose tissue (VAT), is closely associated with increased mortality related to cardiovascular disease, diabetes, and fatty liver disease. This review provides an overview of the recent advances for abdominal obesity measurement. </p> </div><div class="section"> <a class="named-anchor" id="S2">  </a> <h5 class="section-title" id="d5023326e142">Recent findings</h5> <p id="P2">Compared to simple waist circumference, emerging three-dimensional (3D) body-scanning techniques also measure abdominal volume and shape. Abdominal dimension measures have been implemented in bioelectrical impedance analysis to improve accuracy when estimating VAT. Geometrical models have been applied in ultrasound to convert depth measurement into VAT area. Only computed tomography (CT) and MRI can provide direct measures of VAT. Recent advances in imaging allow for evaluating functional aspects of abdominal fat such as brown adipose tissue and fatty acid composition. </p> </div><div class="section"> <a class="named-anchor" id="S3">  </a> <h5 class="section-title" id="d5023326e147">Summary</h5> <p id="P3">Waist circumference is a simple, inexpensive method to measure abdominal obesity. CT and MRI are reference methods for measuring VAT. Further studies are needed to establish the accuracy for dual-energy X-ray absorptiometry in estimating longitudinal changes of VAT. Further studies are needed to establish whether bioelectrical impedance analysis, ultrasound, or 3D body scanning is consistently superior to waist circumference in estimating VAT in different populations. </p> </div>

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Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents

Neil Murphy, George Smith (2017)

Summary Background Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up. Methods Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4–14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5–<25·0 kg/m2. Findings All-cause mortality was minimal at 20·0–25·0 kg/m2 (HR 1·00, 95% CI 0·98–1·02 for BMI 20·0–<22·5 kg/m2; 1·00, 0·99–1·01 for BMI 22·5–<25·0 kg/m2), and increased significantly both just below this range (1·13, 1·09–1·17 for BMI 18·5–<20·0 kg/m2; 1·51, 1·43–1·59 for BMI 15·0–<18·5) and throughout the overweight range (1·07, 1·07–1·08 for BMI 25·0–<27·5 kg/m2; 1·20, 1·18–1·22 for BMI 27·5–<30·0 kg/m2). The HR for obesity grade 1 (BMI 30·0–<35·0 kg/m2) was 1·45, 95% CI 1·41–1·48; the HR for obesity grade 2 (35·0–<40·0 kg/m2) was 1·94, 1·87–2·01; and the HR for obesity grade 3 (40·0–<60·0 kg/m2) was 2·76, 2·60–2·92. For BMI over 25·0 kg/m2, mortality increased approximately log-linearly with BMI; the HR per 5 kg/m2 units higher BMI was 1·39 (1·34–1·43) in Europe, 1·29 (1·26–1·32) in North America, 1·39 (1·34–1·44) in east Asia, and 1·31 (1·27–1·35) in Australia and New Zealand. This HR per 5 kg/m2 units higher BMI (for BMI over 25 kg/m2) was greater in younger than older people (1·52, 95% CI 1·47–1·56, for BMI measured at 35–49 years vs 1·21, 1·17–1·25, for BMI measured at 70–89 years; pheterogeneity<0·0001), greater in men than women (1·51, 1·46–1·56, vs 1·30, 1·26–1·33; pheterogeneity<0·0001), but similar in studies with self-reported and measured BMI. Interpretation The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations. Funding UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.

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Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe

Mika Kivimäki, Eeva Kuosma, Jane Ferrie … (2017)

Summary Background Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight. Methods We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m2), overweight (25·0–29·9 kg/m2), class I (mild) obesity (30·0–34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (<20 kg/m2) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis. Findings Participants were 120 813 adults (mean age 51·4 years, range 35–103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973–2012). During a mean follow-up of 10·7 years (1995–2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7–2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5–5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1–21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9–2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1–17·9) for vascular disease followed by diabetes, 18·6 (16·6–20·9) for diabetes only, and 29·8 (21·7–40·8) for diabetes followed by vascular disease. Interpretation The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes. Funding NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.

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Associations of visceral and abdominal subcutaneous adipose tissue with markers of cardiac and metabolic risk in obese adults

Ian Neeland, Colby Ayers, Anand K. Rohatgi … (2013)

Visceral (VAT) and abdominal subcutaneous (SAT) adipose tissues contribute to obesity but may have different metabolic and atherosclerosis risk profiles. Among obese participants in the Dallas Heart Study, we examined the cross-sectional associations of abdominal VAT and SAT mass, assessed by magnetic resonance imaging (MRI) and indexed to body surface area (BSA), with circulating biomarkers of insulin resistance, dyslipidemia, and inflammation (n=942); and with aortic plaque and liver fat by MRI and coronary calcium by computed tomography (n=1200). Associations of VAT/BSA and SAT/BSA were examined after adjustment for age, sex, race, menopause, and body mass index. In multivariable models, VAT significantly associated with the homeostasis model assessment of insulin resistance (HOMA-IR), lower adiponectin, smaller LDL and HDL particle size, larger VLDL size, and increased LDL and VLDL particle number (p<0.001 for each). VAT also associated with prevalent diabetes, metabolic syndrome, hepatic steatosis, and aortic plaque (p<0.001 for each). VAT independently associated with C-reactive protein but not with any other inflammatory biomarkers tested. In contrast, SAT associated with leptin and inflammatory biomarkers, but not with dyslipidemia or atherosclerosis. Associations between SAT and HOMA-IR were significant in univariable analyses but attenuated after multivariable adjustment. In conclusion, VAT associated with an adverse metabolic, dyslipidemic, and atherogenic obesity phenotype. In contrast, SAT demonstrated a more benign phenotype, characterized by modest associations with inflammatory biomarkers and leptin, but no independent association with dyslipidemia, insulin resistance, or atherosclerosis in obese individuals. These findings suggest that abdominal fat distribution defines distinct obesity sub-phenotypes with heterogeneous metabolic and atherosclerosis risk.

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Author and article information

Journal

Title: Current Opinion in Clinical Nutrition & Metabolic Care

Publisher: Ovid Technologies (Wolters Kluwer Health)

ISSN (Print): 1363-1950

Publication date Created: 2018

Publication date (Print): September 2018

Volume: 21

Issue: 5

Pages: 360-365

Article

DOI: 10.1097/MCO.0000000000000485

PMC ID: 6299450

PubMed ID: 29916924

SO-VID: b47bc8c0-acf8-4413-b99b-c45250182219

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