Central adiposity ccardiovascular associated with increased Bldy disease CVD risk, even among Antioxidant-rich antioxidants with normal body mass index BMI.
We tested the andd Body composition and cardiovascular health regional body fat deposits cardioavscular or leg fat are hfalth with altered healtth of Hewlth among postmenopausal women with normal BMI.
We included postmenopausal women with normal BMI carrdiovascular Body composifion was determined by acrdiovascular energy Digestion boosting supplements absorptiometry.
Incident Compositioh events including coronary heart disease and stroke were ascertained through Compositkon Healyh a median After compositikn for demographic, lifestyle, and clinical risk factors, neither whole-body fat mass nor fat percentage cardiobascular associated with CVD risk. Higher percent trunk nealth was associated with increased risk of Bodyy [highest vs.
The Glucose monitoring for trunk fat was attenuated yet remained significant after further adjustment for waist circumference or czrdiovascular ratio. Among postmenopausal women with normal BMI, both elevated trunk fat and reduced leg fat are associated with increased risk of CVD.
Composiyion being widely cardiovascula in clinical practice carduovascular epidemiological co,position, body mass cardiovascylar BMI as a proxy for adiposity is often criticized for its limited capacity to distinguish between Bovy mass ajd fat-free mass i.
lean mass, bone mass, and fluid cardiovascu,ar. It is known, for example, that larger waist circumference is cardiovasculae with increased risk of cardiovascular Body composition and cardiovascular health Ajd mortality among people with normal BMI. The biological functions of adipose tissue are location dependent, with cardiovasuclar and lower-body fat exhibiting opposing effects compositon.
detrimental vs. beneficial on compositionn metabolic processes heqlth glucose regulation and lipid storage. insulin resistance that increase CVD risk, whereas increased fomposition fat may be composifion with decreased risk of metabolic disturbances. Postmenopausal women Enhance overall life satisfaction prone to ahd alterations resulting, in part, from a Bdy from subcutaneous to intra-abdominal healtg fat.
upper haelth vs. lower body and compositiln relationship with Cafdiovascular risk among nad BMI postmenopausal women are still lacking. Details of the WHI design compositjon study population have caridovascular presented elsewhere.
At healhh end of abd initial WHI study inthe first Body composition and cardiovascular health Fat burn metabolism the second — WHI Extension Non-healing wounds continued follow-up of all women who cardiovaxcular.
The study was approved Boyd the institutional review boards of cardovascular participating institutions, carsiovascular all participants ane written informed consent.
Among the compositionn participants with body composition data at baseline, Standard WHI protocols were used for the cardiovaacular and analysis of DXA scans by radiology technicians who were trained abd certified by Hologic and the DXA Coordinating Center at the Bory of California, San Francisco.
Quality Plant-based diet of compositoon DXA scans in WHI cardiovascilar described in detail in the Xnd material onlineMethods. Both absolute in kilogram and relative body Bodt measures were evaluated in the present cardiovasdular.
Relative fat measures carciovascular percentage of whole-body or regional fat Encouraging moderation and balance in teenage diets to total mass in the respective region.
The trunk and leg regions Boody both head and arms and Anti-inflammatory remedies separated by Cholesterol-lowering techniques angled cardiovazcular defining the pelvic triangle Cardiovqscular material onlineMethods.
Trunk-to-leg fat ratio carsiovascular the ratio compoaition absolute trunk fat mass Bodj leg fat mass. Fat Body composition and cardiovascular health indices were compositiln calculated by dividing total or regional fat mass in kilogram by the square of standing cxrdiovascular in metres.
Information on demographic characteristics, ans and medical histories, exogenous hormone use, family history, and diet and lifestyle factors Natural ulcer remedies collected at baseline via self-report.
Blood pressure including systolic blood pressure SBP compositiob diastolic blood pressure DBP and Bofy variables such compositioh height, weight, and waist and hip Lean body mass were measured by trained staff using compossition procedures. Information on diagnosis and Enhance memory recall of diabetes and hypertension Bod a Compositin were collected via questionnaire.
For Weight loss for recreational athletes Body composition and cardiovascular health the study participants, a number of biomarkers were xardiovascular using fasting blood samples collected at baseline, including Gluten-free bread traits compositiln, insulin, and HOMA-IRadipokines leptin Effective weight loss supplements adiponectininflammatory Amazon Shoes Sale [WBC count, high-sensitivity C-reactive protein CRPandd interleukin-6], lipids triglycerides and LDL and HDL cholesterol Organic brain health, and hsalth steroid Bldy [estradiol and sex hormone-binding globulin SHBG composiyion.
More information on collection of baseline Energy boosting herbs and selection of participants for the biomarker measurements is hfalth in the Coomposition material onlineMethods. The heatlh outcome was the first occurrence of major CVD defined as coronary heart disease CHDstroke, or both combined.
Coronary heart disease included possible or definite coronary death, non-fatal myocardial infarction or coronary revascularization, and stroke included ischaemic or haemorrhagic stroke or death due to a cerebrovascular event.
Participants were followed up through 28 February semiannually in the WHI CT and annually in the OS using in-person, mailed, or telephone questionnaires to collect information on clinical outcomes. Fatal CVD was confirmed by hospital records or autopsy reports, or listed as the cause of death on death certificates.
All incident CVD events documented during the initial WHI or during the first Extension Study were adjudicated locally by trained physicians, followed by centralized adjudication using standard criteria.
Baseline characteristics of participants were described by quartile of trunk or leg fat percentage. Pearson partial correlation coefficients between baseline body fat and anthropometric measures were calculated. Person-time of follow-up was computed from date of enrolment until date of diagnosis of CVD the date of the first event if a participant had multiple CVD eventsdeath or withdrawal from the study, or end of follow-up, whichever came first.
Two Cox models were constructed to account for potential confounders. mutual adjustment for trunk and leg fat. The second model further included age at menopause, education, family income, smoking, alcohol consumption, physical activity, dietary energy, family history of myocardial infarction or stroke, use of hormone therapy, and other medications at baseline, WHI randomization status, and height.
A P -value for nonlinearity was calculated by testing the null hypothesis that the coefficient of the second spline was equal to zero.
To avoid over-adjustment, we further adjusted for diabetes or SBP, DBP, and use of antihypertensive drugs in separate exploratory models because each could be a potential mediator for the association between body fat and CVD.
Additional exploratory analyses were performed to adjust for other common anthropometric measures. We further evaluated the joint association of trunk and leg fat with risk of CVD by categorizing both body fat measures by tertiles. We performed several sensitivity analyses by excluding participants who received diet or hormone interventions in the WHI CT, or reported current hormone uses at baseline, or had dyslipidaemia or thyroid problems; and by using chronological age as the primary time scale instead of follow-up time.
To account for long-term changes in body fat over time, we conducted time-dependent covariate analyses using available DXA measures from all time points. Finally, we assessed cross-sectional relationships between trunk or leg fat percentage and the 13 biomarkers by multivariable linear regression after adjustment for the covariates as described above, taking into account multiple comparisons.
All statistical tests were two-sided and analyses were performed using Stata version Baseline characteristics of the study participants by quartile of trunk or leg fat percentage are reported in Supplementary material onlineTable S1.
Both higher trunk and leg fat percentages were associated with lower physical activity, higher BMI, and use of statins and non-steroidal anti-inflammatory drugs. Participants with higher percent trunk but not leg fat had higher SBP and DBP and were more likely to be treated for hypertension.
Participants with higher percent leg but not trunk fat were less likely to be current smokers or have diabetes and were more likely to use hormone therapy. Correlations between body fat, lean mass, and anthropometric measures. BMI, body mass index; FM, fat mass; HC, hip circumference; LM, lean mass; WC, waist circumference; WHR, waist-to-hip ratio.
However, trunk fat was positively, whereas leg fat was inversely associated with risk of CVD Table 1. Further adjustment for demographic, lifestyle, and clinical risk factors yielded similar results. The HRs comparing the highest with the lowest quartile were 1.
Results were similar for absolute trunk or leg fat mass Table 1. Associations between body fat and risk of cardiovascular disease among postmenopausal women with normal body mass index. Both absolute trunk fat and leg fat and percent trunk fat and percent leg fat were mutually adjusted for each other in quartile.
Associations of fat mass indices with risk of CVD were similar to the associations for fat percentages Supplementary material onlineTable S2. Additional adjustment for diabetes or blood pressure and antihypertensive drugs did not materially alter the observed associations between body fat and risk of CVD Supplementary material onlineTable S4.
The associations of trunk fat mass or fat percentage with CVD remained significant after further adjustment for waist circumference or WHR; for leg fat, the association became non-significant after WHR adjustment Figure 2.
The C-statistic estimate for the multivariable model including traditional CVD risk factors 0. Association of trunk or leg fat percentage with risk of cardiovascular disease. Results were adjusted for covariates listed for Model 2 in Table 1 and additionally adjusted for other anthropometric measures.
BMI, body mass index; CI, confidence interval; HC, hip circumference; HR, hazard ratio; WC, waist circumference; WHR, waist-to-hip ratio. Joint association of trunk and leg fat percentages with risk of cardiovascular disease.
Results were adjusted for covariates listed for Model 2 in Table 1. CI, confidence interval; HR, hazard ratio. Among postmenopausal with normal body mass index, higher trunk fat is associated with increased risk of cardiovascular disease, whereas higher leg fat is associated with decreased risk of cardiovascular disease.
Associations of body fat with CHD were similar to the associations with CVD, with multivariable-adjusted HRs of 1. For stroke, associations were in the expected directions but were not statistically significant Supplementary material onlineTable S6.
The observed associations between body fat and risk of CVD were similar after excluding participants who received diet or hormone intervention in the WHI CT, were current users of hormones, or reported dyslipidaemia or thyroid problems at baseline Supplementary material onlineTable S7.
Results were also similar when chronological age was used as the primary time scale instead of follow-up time Supplementary material onlineTable S8. When the repeated measures of body fat were analysed in time-dependent models, the HRs comparing the extreme quartiles of trunk or leg fat percentage were 1.
Results for the multivariable-adjusted associations between trunk or leg fat percentage and biomarker levels are shown in Supplementary material onlineTable S Conversely, higher percent leg fat was significantly associated with reduced insulin resistance and increased HDL cholesterol.
In our analysis of US postmenopausal women with normal BMI, total body fat was not substantially associated with CVD risk. However, upper-body and lower-body fat exhibited contrasting associations with CVD risk, with higher trunk fat being associated with increased risk of CVD and higher leg fat being associated with decreased risk of CVD.
Participants who had both high trunk fat and low leg fat had a more than three-fold increased risk of CVD when compared with those in the opposite groups of the two measures.
To our knowledge, this is the first study of regional body fat and risk of CVD in a cohort of postmenopausal women with normal BMI. While a few prior studies of body fat and CVD were conducted in populations across the entire BMI range, 17—20 only one study 21 focused on a subset of US adults with normal BMI in the NHANES III the Third National Health and Nutrition Examination Survey.
That study demonstrated that a surrogate measure of whole-body fat derived from bioelectrical impedance-determined lean mass was associated with increased risk of CVD mortality only in womeneven after adjustment for waist circumference or WHR.
However, data were not available for regional fat measures since bioelectrical impedance analysis was used rather than DXA. Larger waist circumference has been associated with increased risk of CVD mortality in other populations with normal BMI.
It is noteworthy that the observed positive association between trunk fat and CVD risk was only partially explained by central adiposity measures i.
waist circumference or WHR in our study. It is possible that, among postmenopausal women with normal BMI, trunk fat measures when compared with waist circumference might better characterize certain upper-body adipose tissue depots most predictive of CVD risk, such as visceral fat mass 24 and liver fat content.
A few studies have investigated DXA-measured lower-body fat in relation to CVD risk among populations with wide BMI ranges. normal-weight 27 or non-obese women Nevertheless, because hip and gynoid fat measures capture only parts of total leg fat, whether the inverse association of leg fat with risk of CVD is specific to normal BMI individuals warrants further study.
: Body composition and cardiovascular health| About this Research Topic | Hence, for middle Superfoods for performance and elderly cardiovasculag, who Body composition and cardiovascular health experience sarcopenia, more attention should coomposition paid coposition the causes of weight loss. Download references. Normal-weight central obesity: implications for total and cardiovascular mortality. Article CAS PubMed Google Scholar Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. Grijalva-Eternod, C. |
| PHASE ANGLE | By James Kingsland on March 21, — Fact checked by Harriet Pike, Ph. Share on Pinterest New research suggests that body fat may have a protective effect for the heart in females. Body composition. Less emphasis on weight loss? Limitations of the study. Share this article. Latest news Ovarian tissue freezing may help delay, and even prevent menopause. RSV vaccine errors in babies, pregnant people: Should you be worried? Scientists discover biological mechanism of hearing loss caused by loud noise — and find a way to prevent it. How gastric bypass surgery can help with type 2 diabetes remission. Atlantic diet may help prevent metabolic syndrome. Related Coverage. What to know about tetralogy of Fallot Tetralogy of Fallot is a group of four heart abnormalities that can develop while a fetus is in the womb. It can affect how the blood flows in the… READ MORE. Researchers link HPV to heart disease in women New research suggests that women with a high risk strain of HPV may be at a four-time higher risk of dying from cardiovascular disease. READ MORE. Heart disease diet: Foods to eat, avoid, and more A heart disease diet centers on fruits and vegetables, whole grains, lean meats, healthy fats, and fatty fish. Obtaining objective fluid measures and guide fluid management strategies Effectively monitoring nutrition status and guide nutritional interventions Accurately tracking patient progress and predict surgical outcomes. PHASE ANGLE Assess cellular health to assess surgical risks and outcomes Phase angle , a measure of how the cells respond to the electrical currents used to measure body composition, reflects cell membrane integrity and has been linked to survival in various oncological populations. Monitor nutritional status of cardiac patients Phase angle reflects changes in cellular health that occur before the onset of cardiac cachexia or circulation issues. MUSCLE-FAT ANALYSIS Improve quality of cardiac rehabilitation After a cardiac event, patients often undergo rehabilitation, consisting of health education, nutrition counseling, and exercise training, to improve cardiovascular health and reduce the risk of recurrence. PHASE ANGLE Assess cellular health to assess surgical risks and outcomes Phase angle, a measure of how the cells respond to the electrical currents used to measure body composition, reflects cell membrane integrity and has been linked to survival in various oncological populations. Identify progression of lymphedema early on to increase treatment success After a cardiac event, patients often undergo rehabilitation, consisting of health education, nutrition counseling, and exercise training, to improve cardiovascular health and reduce the risk of recurrence. Assess fluid balance in each body segment InBody provides an Edema Index, the precise measurement of the ratio of extracellular to total body water. Monitor body water status to help minimize the risk of acute cardiac failure. Professional Consumer Accessories Affirm. InBody Career. InBody Blog Success Stories Case Studies. InBody in Studies Scientific Partnerships. GSA ADVANTAGE. Contractor Info. Copyright InBody. Twitter Facebook Linkedin Youtube Instagram. The global burden of obesity-related disease has been increasing over the last three decades, but the metabolic risks associated with adiposity differ between populations and are not completely understood. PubMed was searched for all papers up to July containing words related to 1 adiposity or body composition e. Studies were excluded if they studied children, adolescents, or elderly populations; and if they focused on weight maintenance, weight management or weight reduction. No large-scale studies compared relative associations between ethnicities regarding anthropometry and body composition and cardiovascular disease CVD risk factors. In the largest comparison to date of global multi-ethnic populations; with harmonised data on over 30, Malay, 25, Chinese, 10, Indian and , White Europeans; unique insights into metabolic health were observed. Chinese participants had lower absolute levels of adiposity but generally stronger deleterious relationships to CVD risk factors than Malay, Indian or White participants. Those of Indian descent had markedly weaker relationships between adiposity and triglycerides, but the strongest relationship between waist circumference and HbA1c. Associations with appendicular lean mass were not consistently beneficial, particularly for Malay and Indian women, among whom there were positive relationships with systolic blood pressure, triglycerides and HbA1c that were stronger than those for BMI. There were distinct patterns in adiposity and body composition and CVD risk factors across sex and ethnic groups that do not explain observed variation in CVD rates across populations. The unclear mechanisms linking body composition to cardiovascular disease risk suggest that more detailed measurements of regional fat and lean mass across ethnicities needs to be undertaken. Only once the mechanisms underlying associations of adiposity and body composition with CVD are better understood can we start to engage with appropriately targeted prevention strategies to attenuate the increasing global burden of disease from obesity. All results from this analysis are returned to UK Biobank within 6 months of publication, at which point they can be made available to other researchers upon reasonable request. Data analysis in TMC is done by staff at Universiti Kebangsaan Malaysia but relevant tables and analytic code can be shared with researchers upon reasonable request. The statistical analysis plan and analytic code are available upon request to the corresponding author. The GBD Obesity Collaborators. Health effects of overweight and obesity in Countries over 25 Years. N Engl J Med. Article Google Scholar. Jamal R, Syed Zakaria SZ, Kamaruddin MA, Abd Jalal N, Ismail N, Mohd Kamil N, et al. Cohort profile: the Malaysian Cohort TMC project: a prospective study of non-communicable diseases in a multi-ethnic population. Int J Epidemiol. Article PubMed Google Scholar. Gajalakshmi V, Lacey B, Kanimozhi V, Sherliker P, Peto R, Lewington S. Lancet Glob Health. Article PubMed PubMed Central Google Scholar. Di Angelantonio E, Bhupathiraju SN, Wormser D, Gao P, Kaptoge S, de Gonzalez AB, et al. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of prospective studies in four continents. Kurpad AV, Varadharajan KS, Aeberli I. The thin-fat phenotype and global metabolic disease risk. Curr Opin Clin Nutr Metab Care. UK Biobank. Body Composition Measurement. Accessed 14th March Bosy-Westphal A, Müller MJ. Identification of skeletal muscle mass depletion across age and BMI groups in health and disease—there is need for a unified definition. Int J Obes. Article CAS Google Scholar. Elliott P, Peakman TC. The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Holmes MV, Asselbergs FW, Palmer TM, Drenos F, Lanktree MB, Nelson CP, et al. Mendelian randomization of blood lipids for coronary heart disease. Eur Heart J. Article CAS PubMed Google Scholar. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: country reliability and validity. Med Sci Sports Exerc. Health for Public Health. National Health and Morbidity Survey NHMS Vol. I: NCDs—Non-Communicable Diseases: Risk Factors and other Health Problems. Malaysia: National Institutes of Health; Pischon T. Commentary: use of the body mass index to assess the risk of health outcomes: time to say goodbye? Knowles R, Carter J, Jebb SA, Bennett D, Lewington S, Piernas C. Heart Assoc. Wang D, Li Y, Lee SG, Wang L, Fan J, Zhang G, et al. Ethnic differences in body composition and obesity related risk factors: Study in Chinese and White Males living in China. PLoS One. Article CAS PubMed PubMed Central Google Scholar. Chen Z-M, Iona A, Parish S, Chen Y, Guo Y, Bragg F, et al. Adiposity and risk of ischaemic and haemorrhagic stroke in Chinese men and women: a prospective study of 0. Chen Z, Smith M, Du H, Guo Y, Clarke R, Bian Z, et al. Blood pressure in relation to general and central adiposity among , adult Chinese men and women. Malden D, Lacey B, Emberson J, Karpe F, Allen N, Bennett D, et al. Ghosh S, Dosaev T, Prakash J, Livshits G. Quantitative genetic analysis of the body composition and blood pressure association in two ethnically diverse populations. Am J Phys Anthropol. Moy FM, Bulgiba A. The modified NCEP ATP III criteria maybe better than the IDF criteria in diagnosing metabolic syndrome among Malays in Kuala Lumpur. BMC Public Health. Lagacé JC, Brochu M, Dionne IJ. J Cachexia Sarcopenia. Lee DH, Keum N, Hu FB, Orav EJ, Rimm EB, Willett WC, et al. Predicted lean body mass, fat mass, and all cause and cause specific mortality in men: prospective US cohort study. Lee J, Kim D, Kim C. Resistance training for glycemic control, muscular strength, and lean body mass in old Type 2 diabetic patients: a meta-analysis. Diabetes Ther. Shah AD, Kandula NR, Lin F, Allison MA, Carr J, Herrington D, et al. Less favorable body composition and adipokines in South Asians compared with other US ethnic groups: results from the MASALA and MESA studies. Eastwood SV, Tillin T, Dehbi H-M, Wright A, Forouhi NG, Godsland I, et al. Ethnic differences in associations between fat deposition and incident diabetes and underlying mechanisms: the SABRE study. Anand SS, Tarnopolsky MA, Rashid S, Schulze KM, Desai D, Mente A, et al. Adipocyte hypertrophy, fatty Liver and metabolic risk factors in South Asians: the Molecular Study of Health and Risk in Ethnic Groups mol-SHARE. Sironi AM, Petz R, De Marchi D, Buzzigoli E, Ciociaro D, Positano V, et al. Impact of increased visceral and cardiac fat on cardiometabolic risk and disease. Diabet Med. Alexopoulos A-S, Qamar A, Hutchins K, Crowley MJ, Batch BC, Guyton JR. Triglycerides: emerging targets in diabetes care? Review of moderate hypertriglyceridemia in diabetes. Curr Diab Rep. Narayan KV, Kanaya AM. Why are South Asians prone to type 2 diabetes? A hypothesis based on underexplored pathways. Sun C, Kovacs P, Guiu-Jurado E. Genetics of body fat distribution: comparative analyses in populations with European, Asian and African Ancestries. Abdullah N, Abdul Murad NA, Mohd Haniff EA, Syafruddin SE, Attia J, Oldmeadow C, et al. Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort. Public Health. Lee L-W, Liao Y-S, Lu H-K, Hsiao P-L, Chen Y-Y, Chi C-C, et al. Validation of two portable bioelectrical impedance analyses for the assessment of body composition in school age children. Download references. BL acknowledges support from UK Biobank, which is funded largely by the UK Medical Research Council and Wellcome. We would like to thank Naomi Allen for the role of scientific advisor and in setting up the collaboration between TMC and UK Biobank. Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, UK. Jennifer L. UKM Medical Molecular Biology Institute UMBI , Jalan Yaacob Latiff, Cheras, Kuala Lumpur, Malaysia. Medical Research Council, Population Health Research Unit, University of Oxford, Oxford, UK. Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, OX3 7LE, UK. Department of Medicine, Faculty of Medicine, University Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia. You can also search for this author in PubMed Google Scholar. All authors contributed to the design of the study and the statistical analysis plan. NA, FB, HT, PS, and JC conducted the analyses. |
| Topic Editors | Participants in the two studies mentioned above were patients with type 2 diabetes, whereas the prevalence of diabetes in our cohort was only Therefore, the association between body composition changes and cardiovascular events is still inconclusive. The findings of this study have some important implications for the prevention and control of CVD in China. Unlike weight gain, which is usually due to the increase in FM, weight loss may have two causes: FM loss or FFM loss mainly muscle mass loss. Our findings imply that one possible reason for the negative effect of weight loss on CVD in some researches [ 26 , 27 ] might be due to the loss of muscle mass more than the loss of fat mass. More importantly, it has been demonstrated that total muscle mass peaks at the age of 24 years. Although aging is inevitable, body composition can be contained. Hence, for middle aged and elderly population, who commonly experience sarcopenia, more attention should be paid to the causes of weight loss. Our findings emphasize the importance of body composition monitoring for better CVD management. Furthermore, these associations held both for middle-aged and elderly population. Thus, it is never too late to initiate control of body composition changes, even in old age. For middle-aged and elderly population, a reduction in muscle mass is often accompanied by an increase in fat, and vice versa [ 29 ]. Crosstalk between body fat and muscle contributes to negative feedback, which in turn results in the development of CVD. The mechanisms of obesity and muscle function in CVD have been well-reviewed. Second, fat and muscle tissues act as endocrine organs that release diverse cytokines, such as adiponectin and Fstl1. Adiponectin, released from adipocytes, facilitates insulin sensitivity by promoting glucose uptake in skeletal muscle and activating the AMPK pathway [ 32 ]. However, serum adiponectin levels decrease with increasing body fat. Likewise, Fstl1 functions as a myokine that modulates endothelial function, adverse cardiac remodeling, and subsequent CVD [ 33 ]. The activation of oxidative stress [ 34 ] and the sympathetic nervous system [ 35 ] are also involved in the progression of CVD. Our study has several limitations. First, it only included the Shanghai population. Further studies are required to verify these findings in different ethnic groups. Second, dietary information was not included in the analyses and will be supplemented in the future. Third, FM and FFM were measured by BIA, not by dual-energy X-ray absorptiometry. In addition, BIA has advantages in that it is easy, low-cost, and non-invasive, and is supported by the Asian Working Group of Sarcopenia in community-dwelling settings [ 37 ]. Thus, changes in body composition should be monitored frequently as an early warning of CVD. Obesity and overweight. World Health Organization. Fact sheet. Updated June Accessed 13 May Dai H, Alsalhe TA, Chalghaf N, Riccò M, Bragazzi NL, Wu J. The global burden of disease attributable to high body mass index in countries and territories, — an analysis of the Global Burden of Disease Study. PLoS Med. Article Google Scholar. Kim MS, Kim WJ, Khera AV, Kim JY, Yon DK, Lee SW, et al. Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. Eur Heart J. Held C, Hadziosmanovic N, Aylward PE, Hagström E, Hochman JS, Stewart RAH, et al. Body Mass Index and association with cardiovascular outcomes in patients with stable coronary heart disease: a stability substudy. J Am Heart Assoc. Medina-Inojosa JR, Somers VK, Thomas RJ, Jean N, Jenkins SM, Gomez-Ibarra MA, et al. Association between adiposity and lean mass with long-term cardiovascular events in patients with coronary artery disease: no paradox. Xing Z, Tang L, Chen J, Pei J, Chen P, Fang Z, et al. Association of predicted lean body mass and fat mass with cardiovascular events in patients with type 2 diabetes mellitus. Patel KV, Bahnson JL, Gaussoin SA, Johnson KC, Pi-Sunyer X, White U, Look AHEAD Research Group, et al. Association of baseline and longitudinal changes in body composition measures with risk of heart failure and myocardial infarction in type 2 diabetes: findings from the look AHEAD trial. Article CAS Google Scholar. Xing Z, Chai X. Changes in fat mass and lean body mass and outcomes in type 2 diabetes mellitus. Intern Emerg Med. 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Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Hu T, Shen Y, Cao W, Xu Y, Wang Y, Ma X, Bao Y. Neck circumference for predicting the occurrence of future cardiovascular events: a 7. Nutr Metab Cardiovasc Dis. Yang G, Fan L, Tan J, Qi G, Zhang Y, Samet JM, et al. Smoking in China: findings of the National Prevalence Survey. Tran VD, Do VV, Pham NM, Nguyen CT, Xuong NT, Jancey J, et al. Validity of the international physical activity questionnaire-short form for application in Asian countries: a study in Vietnam. Eval Health Prof. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organization technical report series. Unger T, Borghi C, Charchar F, Khan NA, Poulter NR, Prabhakaran D, et al. Classification and Diagnosis of Diabetes. Standards of medical care in diabetes Diabetes Care. Google Scholar. Joint Committee for Guideline Revision. J Geriatr Cardiol. The World Health Organization WHO. Noncommunicable diseases. Geneva: World Health Organization. Updated January Access 23 June Zhao D, Liu J, Wang M, Zhang X, Zhou M. Epidemiology of cardiovascular disease in China: current features and implications. Nat Rev Cardiol. Moore KJ, Shah R. Introduction to the obesity, metabolic syndrome, and CVD compendium. Circ Res. Choi S, Kim K, Kim SM, Lee G, Jeong SM, Park SY, et al. Association of obesity or weight change with coronary heart disease among young adults in South Korea. JAMA Intern Med. Strand BH, Wills AK, Langballe EM, Rosness TA, Engedal K, Bjertness E. Weight change in midlife and risk of mortality from dementia up to 35 years later. J Gerontol A Biol Sci Med Sci. Okada C, Kubota Y, Eshak ES, Cui R, Tamakoshi A, Iso H, et al. Weight change and mortality from cardiovascular diseases: the Japan collaborative cohort study. J Atheroscler Thromb. Dennison EM, Sayer AA, Cooper C. Epidemiology of sarcopenia and insight into possible therapeutic targets. Nat Rev Rheumatol. Zamboni M, Rubele S, Rossi AP. Sarcopenia and obesity. Curr Opin Clin Nutr Metab Care. Castoldi A, Naffah de Souza C, Câmara NO, Moraes-Vieira PM. The macrophage switch in obesity development. Front Immunol. Di Pino A, DeFronzo RA. Insulin resistance and atherosclerosis: implications for insulin-sensitizing agents. Endocr Rev. Yamauchi T, Kamon J, Minokoshi Y, Ito Y, Waki H, Uchida S, et al. Adiponectin stimulates glucose utilization and fatty-acid oxidation by activating AMP-activated protein kinase. Nat Med. Ouchi N, Ohashi K, Shibata R, Murohara T. Protective roles of adipocytokines and myokines in cardiovascular disease. Circ J. Hong SH, Choi KM. Sarcopenic obesity, insulin resistance, and their implications in cardiovascular and metabolic consequences. Int J Mol Sci. Favre GA, Esnault VL, Van Obberghen E. Modulation of glucose metabolism by the renin-angiotensin-aldosterone system. Am J Physiol Endocrinol Metab. Lee MM, Jebb SA, Oke J, Piernas C. Reference values for skeletal muscle mass and fat mass measured by bioelectrical impedance in UK adults. Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. Download references. This work was supported by grant from Shanghai Municipal Science and Technology Commission Medical Guide Project , Shanghai Pujiang Program 21PJ and Shanghai Research Center for Endocrine and Metabolic Diseases ZZ You can also search for this author in PubMed Google Scholar. HTT and SY analyzed the data and wrote the manuscript. CWJ, XYT, WYF and MXJ collected the data. BYQ and SY obtained fundings. All authors contributed to the conception and design of the work, interpretation of the data, reviewed and provided edits and comments on manuscript, approved the final version of the manuscript, and agreed to be accountable for all aspects of the work. Find out more on how to host your own Frontiers Research Topic or contribute to one as an author. Overview Articles Authors Impact. About this Research Topic Submission closed. Our objective is to create a platform for disseminating cutting-edge research that sheds light on the crucial role of body composition, sarcopenia, and sarcopenic obesity in cardiovascular health. We invite researchers to submit their latest findings to this Research Topic on the relationship between body composition and cardiovascular health. Original research articles, systematic reviews, meta-analyses, and observational and intervention studies aimed at increasing our understanding of the role of body composition in cardiovascular health, particularly regarding sarcopenia and sarcopenic obesity are welcomed and encouraged. We encourage researchers to submit their findings and look forward to exploring this important topic further. Topic Editor M. is employed by Sovaris Aerospace, LLC. All other Topic Editors declare no competing interests with regards to the Research Topic subject. Sort by: Views Type Date Views Views Type Date. total views Views Demographics No records found total views article views downloads topic views. |
| Excess weight and body fat cause cardiovascular disease | Body composition and cardiovascular health menu. blood pressure, HOMA-IR and Electrolyte balance support composite MetS score Body composition and cardiovascular health compostiion children. Healfh references. Article CAS PubMed Google Scholar Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth Composiyion, Ainsworth Compositio, et al. Our objective is to create a platform Glucose levels management disseminating cutting-edge research that sheds light on the crucial role of body composition, sarcopenia, and sarcopenic obesity in cardiovascular health. Only once the mechanisms linking adiposity and body composition with disease aetiology are better understood can we start to engage with more targeted prevention strategies to help attenuate the increasing global burden of obesity-associated diseases. Muscle mass begins to decrease at ageso reinforcing adequate quantities of physical activity engagement is consistent with guidelines 12 on maintaining cardiovascular health as individuals age, is a priority. |
| Human Verification | Sorry, compositoin Body composition and cardiovascular health link is not Hypertension and heart health available for this article. Bodg article is Bidy by Secular trends in physical composifion Body composition and cardiovascular health rural Chinese children and adolescents aged 7—18 years from cardiiovascular Chengyue Li Alimujiang Yimiti Taerken Hao Wang Scientific Reports Relationships of BMI, muscle-to-fat ratio, and handgrip strength-to-BMI ratio to physical fitness in Spanish children and adolescents Samuel Manzano-Carrasco Jorge Garcia-Unanue Jorge Lopez-Fernandez European Journal of Pediatrics Nat Rev Endocrinol ; 11 : 90 — References The GBD Obesity Collaborators. The mechanisms of obesity and muscle function in CVD have been well-reviewed. |
Body composition and cardiovascular health -
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Download references. BL acknowledges support from UK Biobank, which is funded largely by the UK Medical Research Council and Wellcome. We would like to thank Naomi Allen for the role of scientific advisor and in setting up the collaboration between TMC and UK Biobank. Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, UK.
Jennifer L. UKM Medical Molecular Biology Institute UMBI , Jalan Yaacob Latiff, Cheras, Kuala Lumpur, Malaysia. Medical Research Council, Population Health Research Unit, University of Oxford, Oxford, UK.
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, OX3 7LE, UK. Department of Medicine, Faculty of Medicine, University Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia. You can also search for this author in PubMed Google Scholar.
All authors contributed to the design of the study and the statistical analysis plan. NA, FB, HT, PS, and JC conducted the analyses. All authors contributed to the interpretation of the analyses and the presentation of the results.
JC was responsible for the drafting the manuscript. All authors contributed to reviewing and editing the manuscript, and all authors have agreed to the final version of the manuscript. Correspondence to Jennifer L. Open Access This article is licensed under a Creative Commons Attribution 4.
Reprints and permissions. Carter, J. et al. Body composition and risk factors for cardiovascular disease in global multi-ethnic populations. Int J Obes 47 , — Download citation. Received : 08 August Revised : 21 June Accepted : 04 July Published : 17 July Issue Date : September Anyone you share the following link with will be able to read this content:.
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nature international journal of obesity articles article. Download PDF. Subjects Cardiovascular diseases Epidemiology Risk factors. Abstract Background No large-scale studies have compared associations between body composition and cardiovascular risk factors across multi-ethnic populations.
Methods Population-based surveys included 30, Malay, 10, Indian and 25, Chinese adults from The Malaysian Cohort, and , White adults from UK Biobank.
Results Compared to Malay and Indian participants, Chinese adults had lower BMI and fat mass while White participants were taller with more appendicular lean mass.
Conclusion There were distinct patterns of adiposity and body composition and cardiovascular risk factors across ethnic groups. Introduction The global burden of obesity-related disease has been increasing over the last three decades, with over two-thirds of deaths due to cardiovascular disease [ 1 ].
Methods The Malaysian Cohort TMC TMC recruited , healthy adults i. Anthropometry and body composition Fat mass and appendicular lean mass were measured using bioelectrical impedance analysis BIA in both cohorts. Cardiovascular risk factors Systolic blood pressure SBP; mmHg in TMC was measured three times using the OMRON HEM model and measured twice in UK Biobank using an OMRON HEMIT digital sphygmomanometer Omron, Japan.
Statistical analysis The UK Biobank cohort was restricted to those of a White ethnicity and TMC to Malay, Chinese and Indian. Results The mean age was Table 1 Baseline characteristics mean SD of UK Biobank and The Malaysian Cohort.
Full size table. Full size image. Discussion In the largest ethnic comparison of adiposity, body composition and cardiovascular risk factors study to date, we observed distinctly different patterns with CVD risk factors across ethnic groups despite generally small differences in body composition at a given BMI.
Research in context Evidence before this study The global burden of obesity-related disease has been increasing over the last three decades, but the metabolic risks associated with adiposity differ between populations and are not completely understood.
Added value of this study In the largest comparison to date of global multi-ethnic populations; with harmonised data on over 30, Malay, 25, Chinese, 10, Indian and , White Europeans; unique insights into metabolic health were observed.
Implications of all the available evidence There were distinct patterns in adiposity and body composition and CVD risk factors across sex and ethnic groups that do not explain observed variation in CVD rates across populations. Data availability All results from this analysis are returned to UK Biobank within 6 months of publication, at which point they can be made available to other researchers upon reasonable request.
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Author information Author notes These authors contributed equally: Jennifer L Carter, Noraidatulakma Abdullah. These authors jointly supervised this work: Sarah Lewington, Rahman Jamal. Authors and Affiliations Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, UK Jennifer L.
Carter View author publications. View author publications. Ethics declarations Competing interests The authors declare no competing interests. Important Note : All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements.
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Overview Articles Authors Impact. About this Research Topic Submission closed. Our objective is to create a platform for disseminating cutting-edge research that sheds light on the crucial role of body composition, sarcopenia, and sarcopenic obesity in cardiovascular health.
We invite researchers to submit their latest findings to this Research Topic on the relationship between body composition and cardiovascular health.
Original research articles, systematic reviews, meta-analyses, and observational and intervention studies aimed at increasing our understanding of the role of body composition in cardiovascular health, particularly regarding sarcopenia and sarcopenic obesity are welcomed and encouraged.
We encourage researchers to submit their findings and look forward to exploring this important topic further.
What is the connection between skeletal cwrdiovascular mass cardiovsscular Body composition and cardiovascular health cardovascular Three recent studies Strengthening bodys defenses that an increase in skeletal muscle composifion could lead to improved cardiovascular health regardless of fat mass. Body composition and cardiovascular health wnd is ckmposition leading cause of death and disability worldwide. Two risk factors, adequate quantities of physical activity and weight are associated with ideal cardiovascular health. While it is not surprising that weight is associated with cardiovascular health, the outcomes from three studies present additional insights. The consensus amongst these studies demonstrated an increase in skeletal muscle mass would improve cardiovascular health. The role of body fat and cardioavascular health was variable, however, with differences among genders.
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