1401
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Brown P. Waist circumference in primary care. Prim Care Diabetes 2009; 3:259-261. [PMID: 19879205 DOI: 10.1016/j.pcd.2009.09.006] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2009] [Revised: 09/22/2009] [Accepted: 09/30/2009] [Indexed: 10/20/2022]
Abstract
Current literature suggests that waist circumference may be marginally better than BMI as a surrogate marker for total body fat and can identify thinner people with increased visceral adipose tissue and increased cardiometabolic risk. This commentary explores the use of WC in primary care, including how and when to measure, and how to use the results.
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Affiliation(s)
- Pam Brown
- Grove Medical Centre, 6 Uplands Terrace, Swansea SA2 0GU, United Kingdom.
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1402
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Vettor R, Milan G, Franzin C, Sanna M, De Coppi P, Rizzuto R, Federspil G. The origin of intermuscular adipose tissue and its pathophysiological implications. Am J Physiol Endocrinol Metab 2009; 297:E987-98. [PMID: 19738037 DOI: 10.1152/ajpendo.00229.2009] [Citation(s) in RCA: 198] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The intermuscular adipose tissue (IMAT) is a depot of adipocytes located between muscle bundles. Several investigations have recently been carried out to define the phenotype, the functional characteristics, and the origin of the adipocytes present in this depot. Among the different mechanisms that could be responsible for the accumulation of fat in this site, the dysdifferentiation of muscle-derived stem cells or other mesenchymal progenitors has been postulated, turning them into cells with an adipocyte phenotype. In particular, muscle satellite cells (SCs), a heterogeneous stem cell population characterized by plasticity and self-renewal that allow muscular growth and regeneration, can acquire features of adipocytes, including the abilities to express adipocyte-specific genes and accumulate lipids. Failure to express the transcription factors that direct mesenchymal precursors into fully differentiated functionally specialized cells may be responsible for their phenotypic switch into the adipogenic lineage. We proved that human SCs also possess a clear adipogenic potential that could explain the presence of mature adipocytes within skeletal muscle. This occurs under some pathological conditions (i.e., primary myodystrophies, obesity, hyperglycemia, high plasma free fatty acids, hypoxia, etc.) or as a consequence of thiazolidinedione treatment or simply because of a sedentary lifestyle or during aging. Several pathways and factors (PPARs, WNT growth factors, myokines, GEF-GAP-Rho, p66(shc), mitochondrial ROS production, PKCβ) could be implicated in the adipogenic conversion of SCs. The understanding of the molecular pathways that regulate muscle-to-fat conversion and SC behavior could explain the increase in IMAT depots that characterize many metabolic diseases and age-related sarcopenia.
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Affiliation(s)
- Roberto Vettor
- Dept. of Medical and Surgical Sciences, Univ. of Padua, via Ospedale, 105, 35128 Padua, Italy.
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1403
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Affiliation(s)
- Vojtech Hainer
- Institute of Endocrinology, Prague, Czech Republic. Vojtech Hainer,
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1404
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1405
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Kolle E, Steene-Johannessen J, Holme I, Andersen LB, Anderssen SA. Secular trends in adiposity in Norwegian 9-year-olds from 1999-2000 to 2005. BMC Public Health 2009; 9:389. [PMID: 19828037 PMCID: PMC2765441 DOI: 10.1186/1471-2458-9-389] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2009] [Accepted: 10/14/2009] [Indexed: 11/10/2022] Open
Abstract
Background Due to the negative health consequences of childhood obesity monitoring trends in body mass and adiposity is essential. The purpose of this study was to describe secular trends in the prevalence of overweight and obesity among 9-year-old children, and to study changes in adiposity and fat distribution by investigating changes in waist circumference (WC) and skinfold thicknesses. Methods A total of 859 9-year-olds were included in two cross-sectional studies conducted in 1999-2000 and 2005. Measurements of body mass index (BMI; in kg/m2), WC and skinfold thicknesses were taken by trained investigators. The International Obesity Task Force cut-offs were used to define overweight and obese subjects. Results The overall prevalence of overweight (including obesity) did not change over the five year period. However, a shift may have occurred as the prevalence of overweight (including obesity) increased by 6.4% in girls and 5.5% in boys over the five year period. In both study periods, logistic regression analyses revealed that children of non-Western origin had 2 times higher odds of being overweight/obese than those of Western origin. However, neither the children of Western origin nor the children of non-Western origin showed a significant increase in the prevalence of overweight over the five-year period. No changes were observed for mean BMI, while a significant increase in WC was reported for both girls and boys, and an increase in all skinfold measurements was observed in girls only. Shifts in percentile distribution were observed for BMI, WC and sum of 4 skinfold thickness, however, the shift appeared to be faster in the upper end of the population distribution (p < 0.001 for interactions). Conclusion From 1999-2000 to 2005, there have been increases in 9-year-olds measures of adiposity even though the BMI did not change. The results indicate the need of a large-scale monitoring of adiposity, in addition to BMI, in children.
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Affiliation(s)
- Elin Kolle
- Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway.
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1406
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Kang C, Cascino GD. The effect of preoperative body mass index on outcome after temporal lobe epilepsy surgery. Epilepsy Res 2009; 87:272-6. [PMID: 19828293 DOI: 10.1016/j.eplepsyres.2009.09.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2009] [Revised: 08/10/2009] [Accepted: 09/20/2009] [Indexed: 10/20/2022]
Abstract
PURPOSE The increasing prevalence of obesity is a significant health care concern. Individuals with obesity, i.e., a body mass index (BMI)>or=30, may have significant comorbid conditions that may increase the risk of general anesthesia and operative procedures. The rationale for the present investigation is to evaluate the importance of obesity on operative outcome in patients with intractable temporal lobe epilepsy undergoing surgical treatment. METHODS This study involved a retrospective analysis of 244 adult patients who underwent epilepsy surgery at Mayo Clinic in Rochester, Minnesota between 1990 and 1996. The mean age of patients at surgery was 35 years (range, 18-68 years). There were 108 male patients (44%). Seventy-three patients (30%) were overweight (BMI 26-29), 56 patients (23%) were obese (BMI 30-39), and nine patients (4%) had extreme obesity (BMI>or=40) at the time of surgery. RESULTS The BMI was not predictive of the duration of intensive care unit or hospital stay following surgery, perioperative morbidity, or long-term seizure control following epilepsy surgery. Fifteen deaths occurred in the study period remote from the surgical procedure. The mortality during follow-up was increased for patients with extreme obese (p<0.007). CONCLUSIONS The perioperative morbidity and seizure outcome following epilepsy surgery was independent of the patient's body weight. However, long-term mortality was significantly increased in the individuals with extreme obesity. The effect of morbid obesity on long-term quality of life after epilepsy surgery may need to be considered in selecting operative candidates.
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Affiliation(s)
- Caroline Kang
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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1407
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Abstract
UNLABELLED The aim of this study was to investigate the effect of a 12-month moderate-to-vigorous exercise program combining aerobic and muscle strength training on body composition among sedentary, postmenopausal women. METHODS A randomized controlled trial was conducted. A total of 189 sedentary postmenopausal women (age 50-69 y, body mass index 22-40 kg/m2) were randomly assigned to an exercise (n = 96) or a control group (n = 93). Study parameters measured at baseline, 4 months, and 12 months were as follows: body weight and body height (body mass index), waist and hip circumference (body fat distribution), and dual-energy x-ray absorptiometry (total body fat and lean mass). Differences in changes in study parameters between exercise and control group were examined with generalized estimating equations analysis. RESULTS The exercise program did not result in significant effects on weight, body mass index, and hip circumference. The exercise group experienced a statistically significant greater loss in total body fat, both absolute (-0.33 kg) (borderline) as in a percentage (-0.43%) compared with the control group. In addition, lean mass increased significantly (+0.31 kg), whereas waist circumference (-0.57 cm) decreased significantly compared with the control group. CONCLUSIONS We conclude that a 12-month exercise program combining aerobic and muscle strength training did not affect weight but positively influenced body composition of postmenopausal women. Affecting body fat distribution and waist circumference may have important health implications because it is an independent risk factor in obese but also in nonobese people. Therefore, this study gives further credence to efforts of public health and general practitioners aiming to increase physical activity levels of postmenopausal women.
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1408
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Mombelli G, Zanaboni AM, Gaito S, Sirtori CR. Large waist circumference with normal BMI identifies a significant subset of Italian female patients with the metabolic syndrome—A high risk presentation? Atherosclerosis 2009; 206:340-2. [DOI: 10.1016/j.atherosclerosis.2009.02.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2008] [Revised: 02/05/2009] [Accepted: 02/17/2009] [Indexed: 10/21/2022]
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1409
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Abstract
Fifty years of the Gastroenterological Society of Australia have witnessed the changing appearance of Australians. Asian immigration has transformed the dominant urban culture from European to Eurasian, with some unique Australian attributes. Meanwhile, global conditions have altered body shape, and our sports-proud country is now fat! Thus, as in North America, Europe, China, and affluent Asia-Pacific countries, prosperity and lifestyle, cheap processed foods coupled with reduced physical activity have created an epidemic of over-nutrition resulting in overweight/obesity. Additional genetic factors are at the core of the apple shape (central obesity) that typifies over-nourished persons with metabolic syndrome. Indigenous Australians, once the leanest and fittest humans, now have exceedingly high rates of obesity and type 2 diabetes, contributing to shorter life expectancy; Asian Australians are also at higher risk. Like non-steroidal anti-inflammatory drugs (NSAIDs) and cigarette smoking, obesity now contributes much to gastrointestinal morbidity and mortality (gastroesophageal reflux disease, cancers, gallstones, endoscopy complications). This review focuses on Australian research about fatty liver, particularly roles of central obesity/insulin resistance in non-alcoholic fatty liver disease/steatohepatitis (NAFLD/NASH). The outputs include many highly cited original articles and reviews and the first book on NAFLD. Studies have identified community prevalence, clinical outcomes, association with insulin resistance, metabolic syndrome and hypoadiponectinemia, developed and explored animal models for mechanisms of inflammation and fibrosis, conceptualized etiopathogenesis, and demonstrated that NASH can be reversed by lowering body weight and increasing physical activity. The findings have led to development of regional guidelines on NAFLD, the first internationally, and should now inform daily practice of gastroenterologists.
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1410
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Leslie WD. Prediction of body composition from spine and hip bone densitometry. J Clin Densitom 2009; 12:428-33. [PMID: 19766030 DOI: 10.1016/j.jocd.2009.06.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2009] [Revised: 06/17/2009] [Accepted: 06/17/2009] [Indexed: 11/28/2022]
Abstract
Body mass index (BMI) is used to assess overweight and obesity, but it does not account for the distribution or composition of excess weight. Dual-energy X-ray absorptiometry (DXA) is widely used for the assessment of osteoporosis. We hypothesized that measures of regional fat tissue composition from spine and hip DXA done for osteoporosis assessment could be used to estimate body composition more accurately than with BMI. We identified 427 adult patients who underwent DXA evaluation of the lumbar spine, hip, and whole body at the same visit. The population was randomly divided into 2 equal-sized subgroups: one used to derive prediction equations for whole-body fat tissue, whole-body lean tissue, and trunk fat tissue, and the other for independent validation. The estimates were compared with the actual measurements from the whole-body scans. In all analyses, prediction using the regional DXA scans outperformed prediction using BMI or its component variables, height and weight. When the predicted and actual measurements were compared in the validation cohort, regression slopes did not differ significantly from unity and the intercepts did not differ significantly from zero. We conclude that regional DXA scans of the spine and hip can be used to accurately measure body composition. Further research is needed to see whether these measures can in turn predict the metabolic complications associated with overweight and obesity.
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Affiliation(s)
- William D Leslie
- Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada.
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1411
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Bauer F, Elbers CC, Adan RA, Loos RJ, Onland-Moret NC, Grobbee DE, van Vliet-Ostaptchouk JV, Wijmenga C, van der Schouw YT. Obesity genes identified in genome-wide association studies are associated with adiposity measures and potentially with nutrient-specific food preference. Am J Clin Nutr 2009; 90:951-9. [PMID: 19692490 DOI: 10.3945/ajcn.2009.27781] [Citation(s) in RCA: 157] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND New genetic loci, most of which are expressed in the brain, have recently been reported to contribute to the development of obesity. The brain, especially the hypothalamus, is strongly involved in regulating weight and food intake. OBJECTIVES We investigated whether the recently reported obesity loci are associated with measures of abdominal adiposity and whether these variants affect dietary energy or macronutrient intake. DESIGN We studied 1700 female Dutch participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Their anthropometric measurements and intake of macronutrients were available. Genotyping was performed by using KASPar chemistry. A linear regression model, with an assumption of an additive effect, was used to analyze the association between genotypes of 12 single nucleotide polymorphisms (SNPs) and adiposity measures and dietary intake. RESULTS Seven SNPs were associated (P < 0.05) with weight, body mass index (BMI), and waist circumference (unadjusted for BMI). They were in or near to 6 loci: FTO, MC4R, KCTD15, MTCH2, NEGR1, and BDNF. Five SNPs were associated with dietary intake (P < 0.05) and were in or near 5 loci: SH2B1 (particularly with increased fat), KCTD15 (particularly with carbohydrate intake), MTCH2, NEGR1, and BDNF. CONCLUSIONS We confirmed some of the findings for the newly identified obesity loci that are associated with general adiposity in a healthy Dutch female population. Our results suggest that these loci are not specifically associated with abdominal adiposity but more generally with obesity. We also found that some of the SNPs were associated with macronutrient-specific food intake.
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Affiliation(s)
- Florianne Bauer
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, Utrecht, Netherlands
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1412
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Optimal waist:height ratio cut-off point for cardiometabolic risk factors in Turkish adults. Public Health Nutr 2009; 13:488-95. [DOI: 10.1017/s1368980009991637] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
AbstractObjectiveTo identify the optimal waist:height ratio (WHtR) cut-off point that discriminates cardiometabolic risk factors in Turkish adults.DesignCross-sectional study. Hypertension, dyslipidaemia, diabetes, metabolic syndrome score ≥2 (presence of two or more metabolic syndrome components except for waist circumference) and at least one risk factor (diabetes, hypertension or dyslipidaemia) were categorical outcome variables. Receiver-operating characteristic (ROC) curves were prepared by plotting 1 − specificity on the x-axis and sensitivity on the y-axis. The WHtR value that had the highest Youden index was selected as the optimal cut-off point for each cardiometabolic risk factor (Youden index = sensitivity + specificity − 1).SettingTurkey, 2003.SubjectsAdults (1121 women and 571 men) aged 18 years and over were examined.ResultsAnalysis of ROC coordinate tables showed that the optimal cut-off value ranged between 0·55 and 0·60 and was almost equal between men and women. The sensitivities of the identified cut-offs were between 0·63 and 0·81, the specificities were between 0·42 and 0·71 and the accuracies were between 0·65 and 0·73, for men and women. The cut-off point of 0·59 was the most frequently identified value for discrimination of the studied cardiometabolic risk factors. Subjects classified as having WHtR ≥ 0·59 had significantly higher age and sociodemographic multivariable-adjusted odds ratios for cardiometabolic risk factors than subjects with WHtR < 0·59, except for diabetes in men.ConclusionsWe show that the optimal WHtR cut-off point to discriminate cardiometabolic risk factors is 0·59 in Turkish adults.
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1413
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Yun KE, Park HS, Song YM, Cho SI. Increases in body mass index over a 7-year period and risk of cause-specific mortality in Korean men. Int J Epidemiol 2009; 39:520-8. [PMID: 19762478 DOI: 10.1093/ije/dyp282] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The association between increased body mass index (BMI) and subsequent mortality remains unclear in Asians. This study investigated the associations between BMI increases and cause-specific mortality in middle-aged Korean men. METHODS We conducted a retrospective cohort study of 473 358 Korean men aged 30-64 years, who had undergone health examinations in both 1992 and 1998 and were followed up during 1998-2004. Cox proportional hazards for cause-specific 7-year mortality in relation to BMI changes after stratification of baseline BMI status were analysed. RESULTS Mortality from cardiovascular disease (CVD) was associated with BMI in both 1992 and 1998. Non-CVD mortality was inversely associated with BMI in both 1992 and 1998. We cross-classified participants into groups based on their baseline BMI levels and percent BMI changes during follow-up; men with the lowest BMI level at baseline (BMI in 1992 <21 kg/m(2)) and stable BMI during follow-up (percent change in BMI <5%) were included in the reference category. Compared with the reference group, CVD mortality was higher in initially obese men (BMI in 1992 > or =25 kg/m(2)) with any increase of BMI, and in initially lean men (BMI in 1992 <21 kg/m(2)) or initially overweight men (BMI in 1992 23-24.9 kg/m(2)) with BMI increases of > or =10%. BMI increases of 5.0-9.9% in men with baseline BMI <25 kg/m(2) and stable BMI in men with baseline BMI > or =21 kg/m(2) appeared to lower the risk for non-CVD or all-cause mortality, to below the levels seen in the reference group. CONCLUSIONS Among middle-aged Korean men, obesity or severe weight gain was detrimental to CVD mortality. An increase in BMI appeared to have a predictive value for CVD mortality, especially when used in combination with baseline BMI level. In contrast, moderate weight gain in non-obese men seemed to protect against non-CVD and all-cause mortality.
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Affiliation(s)
- Kyung Eun Yun
- Department of Family Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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1414
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Cordeiro AC, Qureshi AR, Stenvinkel P, Heimburger O, Axelsson J, Barany P, Lindholm B, Carrero JJ. Abdominal fat deposition is associated with increased inflammation, protein-energy wasting and worse outcome in patients undergoing haemodialysis. Nephrol Dial Transplant 2009; 25:562-8. [DOI: 10.1093/ndt/gfp492] [Citation(s) in RCA: 101] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
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1415
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The Mediterranean diet protects against waist circumference enlargement in 12Ala carriers for the PPARγ gene: 2 years' follow-up of 774 subjects at high cardiovascular risk. Br J Nutr 2009; 102:672-9. [DOI: 10.1017/s0007114509289008] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The PPARγ gene regulates insulin sensitivity and adipogenesis. The Pro12Ala polymorphism of this gene has been related to fat accumulation. Our aim was to analyse the effects of a 2-year nutritional intervention with Mediterranean-style diets on adiposity in high-cardiovascular risk patients depending on the Pro12Ala polymorphism of the PPARγ gene. The population consisted of a substudy (774 high-risk subjects aged 55–80 years) of the Prevención con Dieta Mediterránea (PREDIMED) randomised trial aimed at assessing the effect of the Mediterranean diet for CVD prevention. There were three nutritional intervention groups: two of them of a Mediterranean-style diet and the third was a control group advised to follow a conventional low-fat diet. All the participants were genotyped by PCR-restriction fragment length polymorphism (RFLP). The results showed that carriers of the 12Ala allele allocated to the control group had a statistically significant higher change in waist circumference (adjusted difference coefficient = 2·37 cm; P = 0·014) compared with wild-type subjects after 2 years of nutritional intervention. This adverse effect was not observed among 12Ala carriers allocated to both Mediterranean diet groups. In diabetic patients a statistically significant interaction between Mediterranean diet and the 12Ala allele regarding waist circumference change was observed ( − 5·85 cm; P = 0·003). In conclusion, the Mediterranean diet seems to be able to reduce waist circumference in a high-cardiovascular risk population, reversing the negative effect that the 12Ala allele carriers of the PPARγ gene appeared to have. The beneficial effect of this dietary pattern seems to be higher among type 2 diabetic subjects.
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1416
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Pedersen BK. The diseasome of physical inactivity--and the role of myokines in muscle--fat cross talk. J Physiol 2009; 587:5559-68. [PMID: 19752112 DOI: 10.1113/jphysiol.2009.179515] [Citation(s) in RCA: 389] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Type 2 diabetes, cardiovascular diseases, colon cancer, breast cancer, dementia and depression constitute a cluster of diseases, which defines 'a diseasome of physical inactivity'. Both physical inactivity and abdominal adiposity, reflecting accumulation of visceral fat mass, are associated with the occurrence of the diseases within the diseasome. Physical inactivity appears to be an independent and strong risk factor for accumulation of visceral fat, which again is a source of systemic inflammation. Chronic inflammation is involved in the pathogenesis of insulin resistance, atherosclerosis, neurodegeneration and tumour growth. Evidence suggests that the protective effect of exercise may to some extent be ascribed to the anti-inflammatory effect of regular exercise, which can be mediated via a reduction in visceral fat mass and/or by induction of an anti-inflammatory environment with each bout of exercise. The finding that muscles produce and release myokines provides a conceptual basis to understand the mechanisms whereby exercise influences metabolism and exerts anti-inflammatory effects. According to our theory, contracting skeletal muscles release myokines, which work in a hormone-like fashion, exerting specific endocrine effects on visceral fat. Other myokines work locally within the muscle via paracrine mechanisms, exerting their effects on signalling pathways involved in fat oxidation.
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Affiliation(s)
- Bente K Pedersen
- Centre of Inflammation and Metabolism, Rigshospitalet - Section 7641, Blegdamsvej 9, DK-2100, Copenhagen, Denmark.
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1417
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Leisure-time physical activity and high-risk fat: a longitudinal population-based twin study. Int J Obes (Lond) 2009; 33:1211-8. [PMID: 19721451 DOI: 10.1038/ijo.2009.170] [Citation(s) in RCA: 71] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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1418
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Lapice E, Maione S, Patti L, Cipriano P, Rivellese AA, Riccardi G, Vaccaro O. Abdominal adiposity is associated with elevated C-reactive protein independent of BMI in healthy nonobese people. Diabetes Care 2009; 32:1734-6. [PMID: 19587368 PMCID: PMC2732149 DOI: 10.2337/dc09-0176] [Citation(s) in RCA: 65] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE There is debate over the most appropriate adiposity markers of obesity-associated health risks. We evaluated the relationship between fat distribution and high-sensitivity C-reactive protein (hs-CRP), independent of total adiposity. RESEARCH DESIGN AND METHODS We studied 350 people with abdominal adiposity (waist-to-hip ratio [WHR] > or =0.9 in male and > or =0.85 in female subjects) and 199 control subjects (WHR <0.9 in male and <0.85 in female subjects) matched for BMI and age. We measured hs-CRP and major cardiovascular risk factors. RESULTS Participants with abdominal adiposity had BMI similar to that in control subjects (24.8 +/- 2.5 vs. 24.7 +/- 2.2 kg/m(2), respectively), but significantly higher waist circumference (96.4 +/- 6.0 vs. 83.3 +/- 6.7 cm; P < 0.01) and WHR (1.07 +/- 0.08 vs. 0.85 +/- 0.05; P < 0.001). Compared with the control subjects, participants with abdominal adiposity had an adverse cardiovascular risk factor profile, significantly higher hs-CRP (1.96 +/- 2.60 vs. 1.53 +/- 1.74 mg/dl; P < 0.01), and a twofold prevalence of elevated CRP values (>3 mg/dl). CONCLUSIONS In nonobese people, moderate abdominal adiposity is associated with markers of subclinical inflammation independent of BMI.
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Affiliation(s)
- Emanuela Lapice
- Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy
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1419
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Hierarchical analysis of anthropometric indices in the prediction of 5-year incidence of hypertension in apparently healthy adults: The ATTICA study. Atherosclerosis 2009; 206:314-20. [DOI: 10.1016/j.atherosclerosis.2009.02.030] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2008] [Revised: 01/31/2009] [Accepted: 02/18/2009] [Indexed: 11/20/2022]
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1420
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Mehta SK, Richards N, Lorber R, Rosenthal GL. Abdominal Obesity, Waist Circumference, Body Mass Index, and Echocardiographic Measures in Children and Adolescents. CONGENIT HEART DIS 2009; 4:338-47. [DOI: 10.1111/j.1747-0803.2009.00330.x] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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1421
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Turk MW, Tuite PK, Burke LE. Cardiac health: primary prevention of heart disease in women. Nurs Clin North Am 2009; 44:315-25. [PMID: 19683093 DOI: 10.1016/j.cnur.2009.06.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Heart disease is the number one cause of death among women. Although 450,000 women die annually from heart disease, this fact is unknown to many women. Because heart disease is frequently preventable, increasing awareness of personal risk and preventative measures is a key element of health care for women. Nurse clinicians can evaluate, educate, and counsel women regarding their risk for this pervasive disease and promote behavior changes that will decrease that risk. Research evidence supports that lifestyle behaviors are the cornerstone of heart disease prevention. This article presents current evidence for the prevention of heart disease related to dietary intake, physical activity, weight management, smoking cessation, blood pressure control, and lipid management. Guidelines for implementing findings in clinical practice are discussed.
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1422
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Cameron AJ, Dunstan DW, Owen N, Zimmet PZ, Barr ELM, Tonkin AM, Magliano DJ, Murray SG, Welborn TA, Shaw JE. Health and mortality consequences of abdominal obesity: evidence from the AusDiab study. Med J Aust 2009; 191:202-8. [DOI: 10.5694/j.1326-5377.2009.tb02753.x] [Citation(s) in RCA: 60] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2008] [Accepted: 04/01/2009] [Indexed: 11/17/2022]
Affiliation(s)
| | | | - Neville Owen
- School of Population Health, University of Queensland, Brisbane, QLD
| | - Paul Z Zimmet
- Baker IDI Heart and Diabetes Institute, Melbourne, VIC
| | | | - Andrew M Tonkin
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC
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1423
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1424
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Lear SA, James PT, Ko GT, Kumanyika S. Appropriateness of waist circumference and waist-to-hip ratio cutoffs for different ethnic groups. Eur J Clin Nutr 2009; 64:42-61. [DOI: 10.1038/ejcn.2009.70] [Citation(s) in RCA: 152] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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1425
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O'Keefe JH, Carter MD, Lavie CJ. Primary and secondary prevention of cardiovascular diseases: a practical evidence-based approach. Mayo Clin Proc 2009; 84:741-57. [PMID: 19648392 PMCID: PMC2719528 DOI: 10.1016/s0025-6196(11)60525-9] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Despite the fact that we possess highly effective tools for the primary and secondary prevention of myocardial infarction and other complications of atherosclerosis, coronary heart disease remains the most common cause of death in our society. Arterial inflammation and endothelial dysfunction play central roles in the pathogenesis of atherosclerosis and adverse cardiovascular (CV) events. Therapeutic lifestyle changes in conjunction with an aggressive multidrug regimen targeted toward the normalization of the major CV risk factors will neutralize the atherogenic milieu, reduce vascular inflammation, and markedly decrease the risk of adverse CV events and need for revascularization procedures. Specific CV risk factors and optimal therapies for primary and secondary prevention are discussed.
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Affiliation(s)
- James H O'Keefe
- Mid America Heart Institute and University of Missouri-Kansas City, Missouri, USA.
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1426
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O'Keefe JH, Carter MD, Lavie CJ. Primary and secondary prevention of cardiovascular diseases: a practical evidence-based approach. Mayo Clin Proc 2009; 84:741-57. [PMID: 19648392 PMCID: PMC2719528 DOI: 10.4065/84.8.741] [Citation(s) in RCA: 82] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Despite the fact that we possess highly effective tools for the primary and secondary prevention of myocardial infarction and other complications of atherosclerosis, coronary heart disease remains the most common cause of death in our society. Arterial inflammation and endothelial dysfunction play central roles in the pathogenesis of atherosclerosis and adverse cardiovascular (CV) events. Therapeutic lifestyle changes in conjunction with an aggressive multidrug regimen targeted toward the normalization of the major CV risk factors will neutralize the atherogenic milieu, reduce vascular inflammation, and markedly decrease the risk of adverse CV events and need for revascularization procedures. Specific CV risk factors and optimal therapies for primary and secondary prevention are discussed.
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Affiliation(s)
- James H O'Keefe
- Mid America Heart Institute and University of Missouri-Kansas City, Missouri, USA.
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1427
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Abstract
BACKGROUND Clinicians and health professionals are increasingly challenged to understand and consider the different health needs of women and men. The increase of gender awareness and the expanding science of gender medicine will affect more and more clinical practice. This review addresses gender-specific aspects in metabolic disorders and related complications, which represent an increasing burden of this century and a great challenge to public health. DESIGN There is increasing evidence of gender-related differences in risk factors, clinical manifestation and sequelae of obesity and diabetes and increasing knowledge that prevention, detection and therapy of illness affect men and women differently. RESULTS Some gender-specific aspects, especially regarding cardiovascular disease, have been studied in more detail, but for many complications sex-related analyses of the results of both clinical trials and basic science are still missing or disregarded. Impaired glucose and lipid metabolism as well as dysregulation of energy balance and body fat distribution have a great impact on overall health via neuroendocrine changes and inflammatory pathways and deteriorate the course of many diseases with particular harm for women. Metabolic diseases dramatically affect life of men and women from infancy up to old age and are a major challenge for women during pregnancy. Great impact is attached to the intrauterine period and the lifelong implications of fetal programming. CONCLUSIONS Initiation of prospective studies on the impact of gender as primary outcome and investigation of gender-related pathophysiological mechanisms of chronic diseases will help to improve patient care and to implement evidence-based gender-specific prevention programs and clinical recommendations in future.
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Affiliation(s)
- A Kautzky-Willer
- Department of Internal Medicine III, Division of Endocrinology & Metabolism, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria.
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1428
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Dhaliwal SS, Welborn TA. Measurement error and ethnic comparisons of measures of abdominal obesity. Prev Med 2009; 49:148-52. [PMID: 19589354 DOI: 10.1016/j.ypmed.2009.06.023] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2009] [Revised: 06/23/2009] [Accepted: 06/26/2009] [Indexed: 10/20/2022]
Abstract
BACKGROUND Methods of estimating central obesity are important because of the increasing frequency of obesity related diseases worldwide. Here we evaluate the precision of measuring waist circumference and the waist to hip ratio with comparisons across ethnic groups. METHODS The third Australian Risk Factor Prevalence Study (1989) of 9279 adults recorded height, weight, and Body Mass Index together with duplicate measurements of the waist and hip circumferences, the waist to hip ratio, and blood pressure levels using clearly defined survey techniques. Measurement error and precision for these variables were calculated, and comparisons were made across ethnic groups. RESULTS Coefficients of variation for the waist circumference and the waist to hip ratio were less than 1% indicating good precision in comparison with quite large variability for systolic and diastolic pressure readings. Waist circumference showed increased variability in subjects with larger body build in comparison with waist to hip ratio. Equivalence tests across ethnic groups indicated that the waist to hip ratio was independent of ethnicity. CONCLUSION Waist to hip ratio provides a superior measure of central obesity with low measurement error, high precision, and no bias over a wide range of ethnic groups. We believe that it is essential to standardize methods in the assessment of central obesity. Assessment criteria should be based on waist to hip ratio rather than waist circumference.
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Affiliation(s)
- Satvinder S Dhaliwal
- School of Public Health, Curtin Health Innovation Research Institute, Australian Technology Network Centre for Metabolic Fitness, Curtin University of Technology, Bentley, Western Australia, Australia.
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1429
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Frija-Orvoën E. [Which complementary studies and metabolic monitoring must be performed in OSAS? For which patients?]. REVUE DE PNEUMOLOGIE CLINIQUE 2009; 65:254-260. [PMID: 19789052 DOI: 10.1016/j.pneumo.2009.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Characterised by abnormal breathing during sleep, obstructive sleep apnea (OSA) is strongly associated with obesity. Visceral obesity is a component of metabolic syndrome with insulin resistance, hypertension and dyslipidemia. OSA may also represent an independent risk factor for cardiovascular disease, especially hypertension, diabetes mellitus and dyslipidemia. Abdominal adiposity is an important factor for the development of OSA and associated metabolic disorders. Diagnosis of metabolic syndrome can be made using usual markers like waist circumference, arterial pressure measurement, fasting blood glucose, fasting cholesterol, triglyceride and HDL-cholesterol. Those parameters should be systematically evaluated in case of OSA.
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Affiliation(s)
- E Frija-Orvoën
- Pathologies du sommeil, hôpital de la Pitié-Salpêtrière, 47-83, boulevard de l'Hôpital, 75651 Paris cedex 13, France.
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1430
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Waist circumference and waist/hip ratio in relation to all-cause mortality, cancer and sleep apnea. Eur J Clin Nutr 2009; 64:35-41. [PMID: 19639001 DOI: 10.1038/ejcn.2009.71] [Citation(s) in RCA: 141] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Abdominal obesity assessed by waist or waist/hip ratio are both related to increased risk of all-cause mortality throughout the range of body mass index (BMI). The relative risks (RRs) seem to be relatively stronger in younger than in older adults and in those with relatively low BMI compared with those with high BMI. Absolute risks and risk differences are preferable measures of risk in a public health context but these are rarely presented. There is a great lack of studies in ethnic groups (groups of African and Asian descent particularly). Current cut-points as recommended by the World Health Organization seem appropriate, although it may be that BMI-specific and ethnic-specific waist cut-points may be warranted. Waist alone could replace both waist-hip ratio and BMI as a single risk factor for all-cause mortality. There is much less evidence for waist to replace BMI for cancer risk mainly because of the relative lack of prospective cohort studies on waist and cancer risk. Obesity is also a risk factor for sleep apnoea where neck circumference seems to give the strongest association, and waist-hip ratio is a risk factor especially in severe obstructive sleep apnoea syndrome. The waist circumference and waist-hip ratio seem to be better indicators of all-cause mortality than BMI.
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1431
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Hernández-Mijares A, Solá-Izquierdo E, Ballester-Mechó F, Marí-Herrero MT, Gilabert-Molés JV, Gimeno-Clemente N, Morales-Suárez-Varela M. Obesity and overweight prevalences in rural and urban populations in East Spain and its association with undiagnosed hypertension and Diabetes Mellitus: a cross-sectional population-based survey. BMC Res Notes 2009; 2:151. [PMID: 19635126 PMCID: PMC2726152 DOI: 10.1186/1756-0500-2-151] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2009] [Accepted: 07/27/2009] [Indexed: 01/05/2023] Open
Abstract
Background An increase in the number of overweight and obese subjects in the general population has been observed. The aim of this study was to determine the prevalence of overweight and obese subjects in the general population and its association with undiagnosed pathologies, such as diabetes mellitus [DM] and hypertension [HT], by taking age, gender and place of residence [rural or urban] into account. Findings A cross-sectional population-based survey was conducted in Castellón, East Spain in 2005–2006. The sample included 2,062 participants aged 18–94 years. Weight, height, blood pressure and glycaemia values were recorded, and information about gender, age and place of residence was obtained. Overweight, obesity, and undiagnosed HT and DM prevalences were calculated. Multiple regression analyses were done to assess the association of overweight/obesity with undiagnosed HT and DM by adjusting for age, gender and place of residence. The overall overweight, obesity, and undiagnosed HT and DM prevalences were 39.9% [95% CI:37.3–42.0], 25.9% [95% CI:24.0–27.9], 9.0% [95% CI:7.8–10.4] and 12.6% [95% CI:11.2–14.1], respectively. We identified various independent risk factors; those relating to overweight were increasing age, male gender and rural residential area, while that relating to obesity was increasing age. Compared to normal weight adults, the Relative Prevalence Ratio (RPR) for subjects who were overweight and had HT was 2.00 [95% CI:1.21–3.32]; that for obesity and HT was 1.91 [95% CI:1.48–2.46], and it was 1.50 [95% CI:1.25–1.81] for obesity and DM. Conclusion Overweight and obesity prevalences, and their association with undiagnosed DM and HT, are high in our study population.
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1432
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Auyeung TW, Lee JSW, Leung J, Kwok T, Leung PC, Woo J. Survival in older men may benefit from being slightly overweight and centrally obese--a 5-year follow-up study in 4,000 older adults using DXA. J Gerontol A Biol Sci Med Sci 2009; 65:99-104. [PMID: 19628635 DOI: 10.1093/gerona/glp099] [Citation(s) in RCA: 96] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Whether overweight in old age is hazardous remains controversial. Body mass index (BMI) overestimates adiposity and fails to measure central adiposity. We used dual-energy x-ray absorptiometry (DXA) to measure adiposity and hypothesized that overall adiposity, distribution of adiposity, and muscle mass might individually affect survival. METHODS We recruited 2000 men and 2000 women aged 65 years or older. Baseline BMI, waist-hip ratio (WHR), body fat index (BFI = total body fat/height square), relative truncal fat (RTF = trunk fat/total body fat), and body muscle mass index (BMMI = total body muscle mass/height square) were measured. Mortality was ascertained by death registry after 63.3 (median) months. RESULTS Two hundred and forty-two men and 78 women died. In men, mortality hazard ratio (HR) decreased consistently by 0.85 (p < .005), 0.86 (p < .005), and 0.86 (p < .005) per every quintile increase in BMI, BFI, and BMMI, respectively. A J-shaped relationship was observed in central adiposity (RTF and WHR) quintiles; the minimum values were at the 3rd WHR quintile (0.92-0.94) and 4th RTF quintile (mean WHR, 0.94). When RTF was tested with BFI, both high and low central adiposity were unfavorable while general adiposity became marginally insignificant (p = 0.062). When BFI and BMMI were tested together, increasing adiposity rather than muscle mass favored survival (BFI quintile, HR 0.97, p .015; BMMI quintile, HR 1.00, p .997). CONCLUSIONS Older men were resistive to hazards of overweight and adiposity; and mild-grade overweight, obesity, and even central obesity might be protective. This may bear significant implication on the recommended cutoff values for BMI and WHR in the older population.
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Affiliation(s)
- Tung Wai Auyeung
- Department of Medicine and Geriatrics, Tuen Mun Hospital, Tuen Mun, Hong Kong, China.
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1433
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Effects of switching from lopinavir/ritonavir to atazanavir/ritonavir on muscle glucose uptake and visceral fat in HIV-infected patients. AIDS 2009; 23:1349-57. [PMID: 19474651 DOI: 10.1097/qad.0b013e32832ba904] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To determine the effects of switching from lopinavir/ritonavir (LPV/r) to atazanavir/ritonavir (ATV/r) on muscle glucose uptake, glucose homeostasis, lipids, and body composition. METHODS Fifteen HIV-infected men and women on a regimen containing LPV/r and with evidence of hyperinsulinemia and/or dyslipidemia were randomized to continue LPV/r or to switch to ATV/r (ATV 300 mg and ritonavir 100 mg daily) for 6 months. The primary endpoint was change in thigh muscle glucose uptake as measured by positron emission tomography. Secondary endpoints included abdominal visceral adipose tissue, fasting lipids, and safety parameters. The difference over time between treatment groups (treatment effect of ATV/r relative to LPV/r) was determined by repeated measures ANCOVA. RESULTS After 6 months, anterior thigh muscle glucose uptake increased significantly (treatment effect +18.2 +/- 5.9 micromol/kg per min, ATV/r vs. LPV/r, P = 0.035), and visceral adipose tissue area decreased significantly in individuals who switched to ATV/r (treatment effect -31 +/- 11 cm, ATV/r vs. LPV/r, P = 0.047). Switching to ATV/r significantly decreased triglyceride (treatment effect -182 +/- 64 mg/dl, ATV/r vs. LPV/r, P = 0.02) and total cholesterol (treatment effect -23 +/- 8 mg/dl, ATV/r vs. LPV/r, P = 0.01), whereas high-density lipoprotein and low-density lipoprotein did not change significantly. Fasting glucose also decreased significantly following switch to ATV/r (treatment effect -15 +/- 4 mg/dl, ATV/r vs. LPV/r, P = 0.002). CONCLUSION Switching from LPV/r to ATV/r significantly increases glucose uptake by muscle, decreases abdominal visceral adipose tissue, improves lipid parameters, and decreases fasting glucose over 6 months.
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1434
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Leone N, Zureik M. Visceral Obesity and Different Phenotypes of COPD. Am J Respir Crit Care Med 2009. [DOI: 10.1164/ajrccm.180.2.193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Nathalie Leone
- INSERM U700
Faculté de Médecine Xavier Bichat
Paris, France
| | - Mahmoud Zureik
- INSERM U700
Faculté de Médecine Xavier Bichat
Paris, France
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1435
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Srikanthan P, Seeman TE, Karlamangla AS. Waist-hip-ratio as a predictor of all-cause mortality in high-functioning older adults. Ann Epidemiol 2009; 19:724-31. [PMID: 19596204 DOI: 10.1016/j.annepidem.2009.05.003] [Citation(s) in RCA: 71] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2009] [Revised: 05/06/2009] [Accepted: 05/10/2009] [Indexed: 11/18/2022]
Abstract
PURPOSE The relationship between obesity and mortality in older adults is debated, with concern that body mass index (BMI) may be an imperfect measure of obesity in this age group. We assessed the relationship between three measures of obesity and all-cause mortality in a group of healthy older adults. METHODS We analyzed data from the MacArthur Successful Aging Study, a longitudinal study of high-functioning men and women, ages 70-79 years at baseline. We examined 12-year, all-cause mortality risk by BMI, waist circumference, and waist-to-hip circumference ratio (WHR). Proportional hazards regression was used to adjust for gender, race, baseline age, and smoking status. We tested for obesity interactions with gender, race, and smoking status and conducted stratified analyses based on the results of interaction testing. RESULTS There was no association between all-cause mortality and BMI or waist circumference in either unadjusted or adjusted analyses. In contrast, all-cause mortality increased with WHR. There was an interaction with sex, so that there was a graded relationship between WHR and mortality in women (relative hazard, 1.28 per 0.1 increase in WHR; 95% confidence interval, 1.05-1.55) and a threshold relationship in men (relative hazard 1.75 for WHR>1.0 compared to WHR< or =1.0; 95% confidence interval, 1.06-2.91). CONCLUSION WHR rather than BMI appears to be the more appropriate yardstick for risk stratification of high-functioning older adults.
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1436
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Kaysen GA, Kotanko P, Zhu F, Sarkar SR, Heymsfield SB, Kuhlmann MK, Dwyer T, Usvyat L, Havel P, Levin NW. Relationship between adiposity and cardiovascular risk factors in prevalent hemodialysis patients. J Ren Nutr 2009; 19:357-64. [PMID: 19596588 DOI: 10.1053/j.jrn.2009.04.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2008] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVE Increased body mass index (BMI) is associated with reduced all-cause and cardiovascular (CV) mortality in hemodialysis (HD) patients, whereas CV risk increases with BMI in the general population. In the general population, obesity is associated with inflammation, decreased high-density lipoprotein (HDL) cholesterol, increased low-density lipoprotein (LDL) cholesterol, and triglycerides (TGs), all risk factors for CV disease. Low-density lipoprotein cholesterol does not predict CV risk in HD, whereas increased C-reactive protein and interleukin-6 (IL-6), low HDL and apolipoprotein (apo) AI, and increased fasting TGs do predict risk. Renal failure is associated with dyslipidemia and inflammation in normal-weight patients. We hypothesized that the effects of obesity may be obscured by renal failure in HD. METHODS We explored the relationship between adipose tissue pools and distribution, i.e., subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) (measured by magnetic resonance imaging) and measures of inflammation (C-reactive protein, IL-6, ceruloplasmin, and alpha1 acid glycoprotein), HDL and LDL cholesterol, total TGs, apo AI, apo B, apo CII (an activator of lipoprotein lipase), apo CIII (an inhibitor of lipoprotein lipase), and the adipokines, leptin and adiponectin, in 48 patients with prevalent HD. RESULTS AND CONCLUSIONS Total TG concentrations were positively correlated with VAT controlled for age, sex, and weight. Both apo CII and apo CIII were correlated only with VAT. Adiponectin was inversely correlated with VAT, and leptin was positively associated with SAT. C-reactive protein and alpha1 acid glycoprotein were weakly associated with SAT, whereas ceruloplasmin was strongly associated with VAT according to multiple regression analysis. In contrast, apo B, LDL, apo AI, HDL, and IL-6 were not correlated with any measure of body composition, potentially mitigating the effects of obesity in HD.
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1437
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Williams PT, Hoffman KM. Optimal body weight for the prevention of coronary heart disease in normal-weight physically active men. Obesity (Silver Spring) 2009; 17:1428-34. [PMID: 19553927 PMCID: PMC3778502 DOI: 10.1038/oby.2008.680] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Although 36% of US men are normal weight (BMI <25 kg/m(2)), the health benefits of greater leanness in normal-weight individuals are seldom acknowledged. To assess the optimal body weight with respect to minimizing coronary heart disease (CHD) risk, we applied Cox proportional hazard analyses of 20,525 nonsmoking, nondiabetic, normal-weight men followed prospectively for 7.7 years, including 20,301 who provided follow-up questionnaires. Two-hundred and forty two men reported coronary artery bypass graph (CABG) or percutaneous transluminal coronary angioplasty (PTCA) and 82 reported physician-diagnosed incident myocardial infarction (267 total). The National Death Index identified 40 additional ischemic heart disease deaths. In these normal-weight men, each kg/m(2) decrement in baseline BMI was associated with 11.2% lower risk for total CHD (P = 0.005), 13.2% lower risk for nonfatal CHD (P = 0.002), 19.0% lower risk for nonfatal myocardial infarction (P = 0.01), and 12.2% lower risk for PTCA or CABG (P = 0.007). Compared to men with BMI between 22.5 and 25 kg/m(2), those <22.5 kg/m(2) had 24.1% lower total CHD risk (P = 0.01), 27.9% lower nonfatal CHD risk (P = 0.01), 37.8% lower nonfatal myocardial infarction risk (P = 0.05), and 27.8% lower PTCA or CABG risk (P = 0.02). In nonabdominally obese men (waist circumference <102 cm), CHD risk declined linearly with declining waist circumference. CHD risk was unrelated to change in waist circumference between 18 years old and baseline except as it contributed to baseline circumference. These results suggest that the optimal BMI for minimizing CHD risk lies somewhere <22.5 kg/m(2), as suggested from our previous analyses of incident diabetes, hypertension, and hypercholesterolemia in these men.
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Affiliation(s)
- Paul T Williams
- Donner Laboratory, Life Sciences Division, Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, California, USA.
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1438
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Kullberg J, Johansson L, Ahlström H, Courivaud F, Koken P, Eggers H, Börnert P. Automated assessment of whole-body adipose tissue depots from continuously moving bed MRI: A feasibility study. J Magn Reson Imaging 2009; 30:185-93. [DOI: 10.1002/jmri.21820] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
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1439
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Brown DE, Hampson SE, Dubanoski JP, Murai AS, Hillier TA. Effects of ethnicity and socioeconomic status on body composition in an admixed, multiethnic population in Hawaii. Am J Hum Biol 2009; 21:383-8. [PMID: 19213005 DOI: 10.1002/ajhb.20889] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
This study determined ethnic differences in anthropometric measures of a sample of adults in Hawaii, examining the effects of differing degrees of ethnic admixing and socioeconomic status (SES) on the measures. Adults who had attended elementary school in Hawaii underwent anthropometric measurements and answered questionnaires about their educational attainment, income, age, cultural identity, ethnic ancestry, and health. Individuals reporting Asian American cultural identity had significantly lower mean body mass index (BMI) and waist circumference (WC) than others, whereas those with Hawaiian/Pacific Islander cultural identity had significantly higher BMI and WC. Educational attainment, but not reported family income and age, was significantly related to BMI and WC, and differences in educational attainment accounted for the increased mean BMI and WC in Hawaiian/Pacific Islanders, but did not account for the lower mean BMI and WC among Asian Americans. Higher percentage of Asian ancestry was significantly correlated with lower BMI and WC, whereas higher percentage of Hawaiian/Pacific Islander ancestry was significantly correlated with increased BMI and WC. Differences in education accounted for the significantly increased BMI in participants with a higher percentage of Hawaiian/Pacific Islander ancestry, but did not entirely account for the lower BMI in individuals with a higher percentage of Asian American ancestry. These results suggest that the high rate of obesity and its sequelae seen in Pacific Islanders may be more a result of socioeconomic status and lifestyle than of genetic propensity, whereas the lower rates of obesity observed in Asian American populations are less directly influenced by socioeconomic factors.
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Affiliation(s)
- Daniel E Brown
- Department of Anthropology, University of Hawaii at Hilo, 200 W. Kawili Street, Hilo, HI 96720-4091, USA.
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1440
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Proper KI, Hildebrandt VH. Overweight and obesity among Dutch workers: differences between occupational groups and sectors. Int Arch Occup Environ Health 2009; 83:61-8. [PMID: 19506894 DOI: 10.1007/s00420-009-0438-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2008] [Accepted: 05/26/2009] [Indexed: 02/07/2023]
Abstract
PURPOSE To describe the prevalence of overweight and obesity among different occupational groups and sectors in a representative sample of the Dutch working population, and to test whether these differences still exist after adjustment for socio-demographic variables. METHODS Cross-sectional data among 7,588 working adults were used. Univariate analyses of variance was performed to test differences in body mass index (BMI) values between occupational groups (n = 7) and sectors (n = 28). Adjusted analyses were carried out to examine the role of socio-demographic factors in the differences in overweight and obesity between occupational groups and sectors. RESULTS On average, the mean BMI was 24.3 kg/m(2) with 31% being overweight and 6% being obese. Those working in trade, industrial, or transportation occupations as well as the legislators and senior managers had the highest BMI and a relatively high prevalence of overweight (36.7 and 35.5%, respectively) and obesity (6.9 and 7.5%, respectively). In contrast, those working in scientific and artistic professions had the most favorable BMI profile with 25.7% being overweight and 4.2% being obese. After adjusting for sex, age, and education, the proportion of variance changed from about 0.01 to 0.10 with age being the main contributor of the differences in overweight and obesity. CONCLUSIONS BMI profile and prevalence of overweight and obesity differs between occupations and sectors. Despite the differences are explained partly by socio-demographic factors, based on a given distribution of age, sex, and education within each occupational group and sector, occupational group- and sector-specific strategies to prevent and reduce overweight are recommended.
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Affiliation(s)
- Karin I Proper
- Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands.
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1441
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Improvement of metabolic syndrome following intragastric balloon: 1 year follow-up analysis. Obes Surg 2009; 19:1084-8. [PMID: 19506981 DOI: 10.1007/s11695-009-9879-6] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2009] [Accepted: 05/07/2009] [Indexed: 12/13/2022]
Abstract
OBJECTIVE This study aimed to assess the impact of intragastric balloon (IGB)-induced body weight loss on metabolic syndrome in obese patients and evaluate what happens during 1-year follow-up. METHODS To this end, data were collected on 143 obese patients (body mass index (BMI) 36.2+/-5.7 kg/m2) who underwent IGB insertion between January 2000 and December 2005. Outcomes were recorded at BioEnterics Intragastric Balloon removal time (t0) and at 6-month (t6) and 12-month (t12) follow-up. RESULTS Significant BMI, excess body weight loss percentage, and body weight loss percentage (BWL%) were observed at t0 (29.6+/-4.6 kg/m2; 29.3+/-4.8%; 14.1+/-5.7%), followed by partial weight regain at t12 (32.4+/-4.3 kg/m2; 26.1+/-4.9%; 11.2+/-4.6%). Incidence of metabolic syndrome dropped from 34.8% (pre-IGB value) to 14.5% (t0) and 11.6% (t12). Likewise, type 2 diabetes mellitus (DM), hypertriglyceridemia, hypercholesterolemia, and blood hypertension (BH) incidence decreased from 32.6%, 37.7%, 33.4%, and 44.9% (pre-IGB values) to 20.9%, 14.5%, 16.7%, and 30.4% at t0 and 21.3%, 17.4%, 18.9%, and 34.8% at t12. HbA1c blood concentration shifted from an initial value of 7.5+/-2.1% to 5.7+/-1.9% (t0), 5.6+/-0.7% (t6), and 5.5+/-0.9% (t12). Patients suffering from DM or BH stopped or diminished relative drug consumption at t12. Negligible modifications were reported as regards HDL cholesterol and hyperuricemia. CONCLUSION Weight regain is commonly observed during long-term follow-up after IGB removal. Nevertheless, the maintenance of at least 10% of the BWL%, as reported at 1-year follow-up, is associated with an improvement in metabolic syndrome.
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Lavie CJ, Milani RV, Ventura HO. Obesity and cardiovascular disease: risk factor, paradox, and impact of weight loss. J Am Coll Cardiol 2009; 53:1925-32. [PMID: 19460605 DOI: 10.1016/j.jacc.2008.12.068] [Citation(s) in RCA: 1491] [Impact Index Per Article: 93.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2008] [Revised: 12/02/2008] [Accepted: 12/09/2008] [Indexed: 12/14/2022]
Abstract
Obesity has reached global epidemic proportions in both adults and children and is associated with numerous comorbidities, including hypertension (HTN), type II diabetes mellitus, dyslipidemia, obstructive sleep apnea and sleep-disordered breathing, certain cancers, and major cardiovascular (CV) diseases. Because of its maladaptive effects on various CV risk factors and its adverse effects on CV structure and function, obesity has a major impact on CV diseases, such as heart failure (HF), coronary heart disease (CHD), sudden cardiac death, and atrial fibrillation, and is associated with reduced overall survival. Despite this adverse association, numerous studies have documented an obesity paradox in which overweight and obese people with established CV disease, including HTN, HF, CHD, and peripheral arterial disease, have a better prognosis compared with nonoverweight/nonobese patients. This review summarizes the adverse effects of obesity on CV disease risk factors and its role in the pathogenesis of various CV diseases, reviews the obesity paradox and potential explanations for these puzzling data, and concludes with a discussion regarding the current state of weight reduction in the prevention and treatment of CV diseases.
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Affiliation(s)
- Carl J Lavie
- Cardiac Rehabilitation, Exercise Laboratories, Ochsner Medical Center, New Orleans, Louisiana 70121-2483, USA.
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Mishra BM, Bhatnagar D. Nutrition and metabolism. Curr Opin Lipidol 2009; 20:252-3. [PMID: 19433920 DOI: 10.1097/mol.0b013e32832b717a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Lindgren CM, Heid IM, Randall JC, Lamina C, Steinthorsdottir V, Qi L, Speliotes EK, Thorleifsson G, Willer CJ, Herrera BM, Jackson AU, Lim N, Scheet P, Soranzo N, Amin N, Aulchenko YS, Chambers JC, Drong A, Luan J, Lyon HN, Rivadeneira F, Sanna S, Timpson NJ, Zillikens MC, Zhao JH, Almgren P, Bandinelli S, Bennett AJ, Bergman RN, Bonnycastle LL, Bumpstead SJ, Chanock SJ, Cherkas L, Chines P, Coin L, Cooper C, Crawford G, Doering A, Dominiczak A, Doney ASF, Ebrahim S, Elliott P, Erdos MR, Estrada K, Ferrucci L, Fischer G, Forouhi NG, Gieger C, Grallert H, Groves CJ, Grundy S, Guiducci C, Hadley D, Hamsten A, Havulinna AS, Hofman A, Holle R, Holloway JW, Illig T, Isomaa B, Jacobs LC, Jameson K, Jousilahti P, Karpe F, Kuusisto J, Laitinen J, Lathrop GM, Lawlor DA, Mangino M, McArdle WL, Meitinger T, Morken MA, Morris AP, Munroe P, Narisu N, Nordström A, Nordström P, Oostra BA, Palmer CNA, Payne F, Peden JF, Prokopenko I, Renström F, Ruokonen A, Salomaa V, Sandhu MS, Scott LJ, Scuteri A, Silander K, Song K, Yuan X, Stringham HM, Swift AJ, Tuomi T, Uda M, Vollenweider P, Waeber G, Wallace C, Walters GB, Weedon MN, Witteman JCM, Zhang C, Zhang W, Caulfield MJ, Collins FS, Davey Smith G, Day INM, Franks PW, Hattersley AT, Hu FB, Jarvelin MR, Kong A, Kooner JS, Laakso M, Lakatta E, Mooser V, Morris AD, Peltonen L, Samani NJ, Spector TD, Strachan DP, Tanaka T, Tuomilehto J, Uitterlinden AG, van Duijn CM, Wareham NJ, Watkins for the PROCARDIS consortia H, Waterworth DM, Boehnke M, Deloukas P, Groop L, Hunter DJ, Thorsteinsdottir U, Schlessinger D, Wichmann HE, Frayling TM, Abecasis GR, Hirschhorn JN, Loos RJF, Stefansson K, Mohlke KL, Barroso I, McCarthy for the GIANT consortium MI. Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution. PLoS Genet 2009; 5:e1000508. [PMID: 19557161 PMCID: PMC2695778 DOI: 10.1371/journal.pgen.1000508] [Citation(s) in RCA: 374] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2009] [Accepted: 05/06/2009] [Indexed: 12/24/2022] Open
Abstract
To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
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Affiliation(s)
- Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
| | - Iris M. Heid
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
- Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Joshua C. Randall
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
| | - Claudia Lamina
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | | | - Lu Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Elizabeth K. Speliotes
- Department of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Metabolism Initiative and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States of America
| | | | - Cristen J. Willer
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Blanca M. Herrera
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
- Oxford Centre for Diabetes, Department of Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Anne U. Jackson
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Noha Lim
- Medical Genetics, Clinical Pharmacology and Discovery Medicine, King of Prussia, Pennsylvania, United States of America
| | - Paul Scheet
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Nicole Soranzo
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Yurii S. Aulchenko
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - John C. Chambers
- Department of Epidemiology and Public Health, Imperial College London, London, United Kingdom
| | - Alexander Drong
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Helen N. Lyon
- Metabolism Initiative and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States of America
- Divisions of Genetics and Endocrinology, Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Serena Sanna
- Istituto di Neurogenetica e Neurofarmacologia, Consiglio Nazionale delle Ricerche, Cagliari, Italy
| | - Nicholas J. Timpson
- The MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, United Kingdom
| | - M. Carola Zillikens
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Peter Almgren
- Department of Clinical Sciences, Diabetes, and Endocrinology Research Unit, University Hospital Malmö, Lund University, Malmö, Sweden
| | | | - Amanda J. Bennett
- Oxford Centre for Diabetes, Department of Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Richard N. Bergman
- Physiology and Biophysics, University of Southern California School of Medicine, Los Angeles, California, United States of America
| | - Lori L. Bonnycastle
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | | | - Stephen J. Chanock
- Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America
| | - Lynn Cherkas
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Peter Chines
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Lachlan Coin
- Department of Epidemiology and Public Health, Imperial College London, London, United Kingdom
| | - Cyrus Cooper
- MRC Epidemiology Resource Centre, University of Southampton, Southampton, United Kingdom
| | - Gabriel Crawford
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Angela Doering
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - Anna Dominiczak
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom
| | - Alex S. F. Doney
- Diabetes Research Group, Division of Medicine and Therapeutics, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom
| | - Shah Ebrahim
- Department of Social Medicine, University of Bristol, Bristol, United Kingdom
| | - Paul Elliott
- Department of Epidemiology and Public Health, Imperial College London, London, United Kingdom
| | - Michael R. Erdos
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Karol Estrada
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Guido Fischer
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - Nita G. Forouhi
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - Christopher J. Groves
- Oxford Centre for Diabetes, Department of Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Scott Grundy
- Centre for Human Nutrition, University of Texas Southwestern Medical Centre, Dallas, Texas, United States of America
| | - Candace Guiducci
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - David Hadley
- Division of Community Health Sciences, St George's University of London, London, United Kingdom
| | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Rolf Holle
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - John W. Holloway
- MRC Epidemiology Resource Centre, University of Southampton, Southampton, United Kingdom
- Division of Human Genetics, University of Southampton, Southampton, United Kingdom
| | - Thomas Illig
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - Bo Isomaa
- Folkhälsan Research Center, Malmska Municipal Health Center and Hospital, Jakobstad, Finland
| | - Leonie C. Jacobs
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Karen Jameson
- MRC Epidemiology Resource Centre, University of Southampton, Southampton, United Kingdom
| | | | - Fredrik Karpe
- Oxford Centre for Diabetes, Department of Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Johanna Kuusisto
- Department of Medicine, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
| | | | | | - Debbie A. Lawlor
- The MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, United Kingdom
- Department of Social Medicine, University of Bristol, Bristol, United Kingdom
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Wendy L. McArdle
- Department of Social Medicine, University of Bristol, Bristol, United Kingdom
| | - Thomas Meitinger
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - Mario A. Morken
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
| | - Patricia Munroe
- The William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Narisu Narisu
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Anna Nordström
- Department of Surgical and Perioperative Sciences, Section for Sports Medicine, Umeå University, Umeå, Sweden
- Department of Community Medicine and Rehabilitation, Section of Geriatrics, Umeå University Hospital, Umeå, Sweden
| | - Peter Nordström
- Department of Surgical and Perioperative Sciences, Section for Sports Medicine, Umeå University, Umeå, Sweden
- Department of Community Medicine and Rehabilitation, Section of Geriatrics, Umeå University Hospital, Umeå, Sweden
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Colin N. A. Palmer
- Population Pharmacogenetics Group, Biomedical Research Centre, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom
| | - Felicity Payne
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - John F. Peden
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
- Department of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom
| | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
| | - Frida Renström
- Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Section for Medicine, Umeå University Hospital, Umeå, Sweden
| | - Aimo Ruokonen
- Department of Clinical Chemistry, University of Oulu, Oulu, Finland
| | | | - Manjinder S. Sandhu
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge, United Kingdom
| | - Laura J. Scott
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Angelo Scuteri
- Unita' Operativa Geriatrica, Instituto Nazionale Ricovero e Cura per Anziani (INRCA) IRCCS, Rome, Italy
| | - Kaisa Silander
- Department of Molecular Medicine, National Public Health Institute, Helsinki, Finland
| | - Kijoung Song
- Medical Genetics, Clinical Pharmacology and Discovery Medicine, King of Prussia, Pennsylvania, United States of America
| | - Xin Yuan
- Medical Genetics, Clinical Pharmacology and Discovery Medicine, King of Prussia, Pennsylvania, United States of America
| | - Heather M. Stringham
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Amy J. Swift
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Tiinamaija Tuomi
- Department of Medicine, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
- Research Program of Molecular Medicine, University of Helsinki, Helsinki, Finland
| | - Manuela Uda
- Istituto di Neurogenetica e Neurofarmacologia, Consiglio Nazionale delle Ricerche, Cagliari, Italy
| | - Peter Vollenweider
- Department of Medicine and Internal Medicine, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Gerard Waeber
- Department of Medicine and Internal Medicine, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Chris Wallace
- The William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | | | - Michael N. Weedon
- Genetics of Complex Traits, Institute of Biomedical and Clinical Science, Peninsula Medical School, Exeter, United Kingdom
| | | | | | - Cuilin Zhang
- Division of Epidemiology, Statistics, and Prevention Research, National Institute of Child Health and Human Development, Bethesda, Maryland, United States of America
| | - Weihua Zhang
- Ealing Hospital, Ealing Hospital National Health Service Trust, Southall, London, United Kingdom
| | - Mark J. Caulfield
- The William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Francis S. Collins
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - George Davey Smith
- The MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, United Kingdom
- Department of Social Medicine, University of Bristol, Bristol, United Kingdom
| | - Ian N. M. Day
- Bristol Genetic Epidemiology Laboratories, Department of Social Medicine, University of Bristol, Bristol, United Kingdom
| | - Paul W. Franks
- Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Section for Medicine, Umeå University Hospital, Umeå, Sweden
- Department of Public Health and Clinical Medicine, Section for Nutritional Research (Umeå Medical Biobank), Umeå University, Umeå, Sweden
| | - Andrew T. Hattersley
- Genetics of Complex Traits, Institute of Biomedical and Clinical Science, Peninsula Medical School, Exeter, United Kingdom
| | - Frank B. Hu
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Public Health, Imperial College London, London, United Kingdom
- Institute of Health Sciences, University of Oulu, Biocenter Oulu, University of Oulu, Oulu, Finland
- Department of Child and Adolescent Health, National Public Health Institute, Oulu, Finland
| | | | - Jaspal S. Kooner
- National Heart and Lung Institute, Imperial College London Hammersmith Hospital, London, United Kingdom
| | - Markku Laakso
- Department of Medicine, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
| | - Edward Lakatta
- Gerontology Research Center, National Institute on Aging, Baltimore, Maryland, United States of Ameica
| | - Vincent Mooser
- Medical Genetics, Clinical Pharmacology and Discovery Medicine, King of Prussia, Pennsylvania, United States of America
| | - Andrew D. Morris
- Diabetes Research Group, Division of Medicine and Therapeutics, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom
| | - Leena Peltonen
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - David P. Strachan
- Division of Community Health Sciences, St George's University of London, London, United Kingdom
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, United States of America
- Medstar Research Institute, Baltimore, Maryland, United States of America
| | - Jaakko Tuomilehto
- Diabetes Unit, Department of Epidemiology and Health Promotion, National Public Health Institute, Helsinki, Finland
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Hugh Watkins for the PROCARDIS consortia
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
- Department of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom
| | - Dawn M. Waterworth
- Medical Genetics, Clinical Pharmacology and Discovery Medicine, King of Prussia, Pennsylvania, United States of America
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Panos Deloukas
- Institute of Metabolic Science, Addenbrookes Hospital, Cambridge, United Kingdom
| | - Leif Groop
- Department of Clinical Sciences, Diabetes, and Endocrinology Research Unit, University Hospital Malmö, Lund University, Malmö, Sweden
- Department of Medicine, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
| | - David J. Hunter
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Broad Institute of MIT and Harvard, Boston, Massachusetts, United States of America
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - David Schlessinger
- Gerontology Research Center, National Institute on Aging, Baltimore, Maryland, United States of Ameica
| | - H.-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München, National Research Center for Environment and Health, Neuherberg, Germany
| | - Timothy M. Frayling
- Genetics of Complex Traits, Institute of Biomedical and Clinical Science, Peninsula Medical School, Exeter, United Kingdom
| | - Gonçalo R. Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Joel N. Hirschhorn
- Metabolism Initiative and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States of America
- Divisions of Genetics and Endocrinology, Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Kari Stefansson
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Mark I. McCarthy for the GIANT consortium
- Wellcome Trust Centre for Human Genetics, University of Oxford, , Oxford, United Kingdom
- Oxford Centre for Diabetes, Department of Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
- National Institute for Health Research, Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
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Beulens JWJ, Monninkhof EM, Verschuren WMM, van der Schouw YT, Smit J, Ocke MC, Jansen EHJM, van Dieren S, Grobbee DE, Peeters PHM, Bueno-de-Mesquita HB. Cohort Profile: The EPIC-NL study. Int J Epidemiol 2009; 39:1170-8. [PMID: 19483199 DOI: 10.1093/ije/dyp217] [Citation(s) in RCA: 157] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Affiliation(s)
- Joline W J Beulens
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
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Fletcher GF. Central obesity--more weight in cardiovascular disease prevention. Am J Cardiol 2009; 103:1408-10. [PMID: 19427437 DOI: 10.1016/j.amjcard.2009.01.350] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2009] [Revised: 01/23/2009] [Accepted: 01/23/2009] [Indexed: 11/24/2022]
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Chavez AO, Gastaldelli A, Guardado-Mendoza R, Lopez-Alvarenga JC, Leland MM, Tejero ME, Sorice G, Casiraghi F, Davalli A, Bastarrachea RA, Comuzzie AG, DeFronzo RA, Folli F. Predictive models of insulin resistance derived from simple morphometric and biochemical indices related to obesity and the metabolic syndrome in baboons. Cardiovasc Diabetol 2009; 8:22. [PMID: 19389241 PMCID: PMC2674590 DOI: 10.1186/1475-2840-8-22] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2009] [Accepted: 04/23/2009] [Indexed: 12/13/2022] Open
Abstract
Background Non-human primates are valuable models for the study of insulin resistance and human obesity. In baboons, insulin sensitivity levels can be evaluated directly with the euglycemic clamp and is highly predicted by adiposity, metabolic markers of obesity and impaired glucose metabolism (i.e. percent body fat by DXA and HbA1c). However, a simple method to screen and identify obese insulin resistant baboons for inclusion in interventional studies is not available. Methods We studied a population of twenty baboons with the euglycemic clamp technique to characterize a population of obese nondiabetic, insulin resistant baboons, and used a multivariate linear regression analysis (adjusted for gender) to test different predictive models of insulin sensitivity (insulin-stimulated glucose uptake = Rd) using abdominal circumference and fasting plasma insulin. Alternatively, we tested in a separate baboon population (n = 159), a simpler model based on body weight and fasting plasma glucose to predict the whole-body insulin sensitivity (Rd/SSPI) derived from the clamp. Results In the first model, abdominal circumference explained 59% of total insulin mediated glucose uptake (Rd). A second model, which included fasting plasma insulin (log transformed) and abdominal circumference, explained 64% of Rd. Finally, the model using body weight and fasting plasma glucose explained 51% of Rd/SSPI. Interestingly, we found that percent body fat was directly correlated with the adipocyte insulin resistance index (r = 0.755, p < 0.0001). Conclusion In baboons, simple morphometric measurements of adiposity/obesity, (i.e. abdominal circumference), plus baseline markers of glucose/lipid metabolism, (i.e. fasting plasma glucose and insulin) provide a feasible method to screen and identify overweight/obese insulin resistant baboons for inclusion in interventional studies aimed to study human obesity, insulin resistance and type 2 diabetes mellitus.
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Affiliation(s)
- Alberto O Chavez
- Department of Medicine, Diabetes Division, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
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Whitlock G, Lewington S, Sherliker P, Clarke R, Emberson J, Halsey J, Qizilbash N, Collins R, Peto R. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet 2009; 373:1083-96. [PMID: 19299006 PMCID: PMC2662372 DOI: 10.1016/s0140-6736(09)60318-4] [Citation(s) in RCA: 3175] [Impact Index Per Article: 198.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND The main associations of body-mass index (BMI) with overall and cause-specific mortality can best be assessed by long-term prospective follow-up of large numbers of people. The Prospective Studies Collaboration aimed to investigate these associations by sharing data from many studies. METHODS Collaborative analyses were undertaken of baseline BMI versus mortality in 57 prospective studies with 894 576 participants, mostly in western Europe and North America (61% [n=541 452] male, mean recruitment age 46 [SD 11] years, median recruitment year 1979 [IQR 1975-85], mean BMI 25 [SD 4] kg/m(2)). The analyses were adjusted for age, sex, smoking status, and study. To limit reverse causality, the first 5 years of follow-up were excluded, leaving 66 552 deaths of known cause during a mean of 8 (SD 6) further years of follow-up (mean age at death 67 [SD 10] years): 30 416 vascular; 2070 diabetic, renal or hepatic; 22 592 neoplastic; 3770 respiratory; 7704 other. FINDINGS In both sexes, mortality was lowest at about 22.5-25 kg/m(2). Above this range, positive associations were recorded for several specific causes and inverse associations for none, the absolute excess risks for higher BMI and smoking were roughly additive, and each 5 kg/m(2) higher BMI was on average associated with about 30% higher overall mortality (hazard ratio per 5 kg/m(2) [HR] 1.29 [95% CI 1.27-1.32]): 40% for vascular mortality (HR 1.41 [1.37-1.45]); 60-120% for diabetic, renal, and hepatic mortality (HRs 2.16 [1.89-2.46], 1.59 [1.27-1.99], and 1.82 [1.59-2.09], respectively); 10% for neoplastic mortality (HR 1.10 [1.06-1.15]); and 20% for respiratory and for all other mortality (HRs 1.20 [1.07-1.34] and 1.20 [1.16-1.25], respectively). Below the range 22.5-25 kg/m(2), BMI was associated inversely with overall mortality, mainly because of strong inverse associations with respiratory disease and lung cancer. These inverse associations were much stronger for smokers than for non-smokers, despite cigarette consumption per smoker varying little with BMI. INTERPRETATION Although other anthropometric measures (eg, waist circumference, waist-to-hip ratio) could well add extra information to BMI, and BMI to them, BMI is in itself a strong predictor of overall mortality both above and below the apparent optimum of about 22.5-25 kg/m(2). The progressive excess mortality above this range is due mainly to vascular disease and is probably largely causal. At 30-35 kg/m(2), median survival is reduced by 2-4 years; at 40-45 kg/m(2), it is reduced by 8-10 years (which is comparable with the effects of smoking). The definite excess mortality below 22.5 kg/m(2) is due mainly to smoking-related diseases, and is not fully explained.
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Affiliation(s)
- Francisco Lopez-Jimenez
- Division of Cardiovascular Diseases, Mayo Clinic College of Medicine, Mayo Foundation, Rochester, MN 55905, USA.
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