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Yahya R, Jainandunsing S, Rashid M, van der Zee L, Touw A, de Rooij FWM, Sijbrands EJG, Verhoeven AJM, Mulder MT. HDL associates with insulin resistance and beta-cell dysfunction in South Asian families at risk of type 2 diabetes. J Diabetes Complications 2021; 35:107993. [PMID: 34384708 DOI: 10.1016/j.jdiacomp.2021.107993] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 06/23/2021] [Accepted: 07/12/2021] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Dyslipidemia precedes type 2 diabetes (T2D) and worsens with increasing glucose intolerance. First degree relatives of T2D patients have an increased risk to develop dyslipidemia and glucose intolerance. The aim of the present study was to assess the relation between the development of dyslipidemia and glucose intolerance in first-degree relatives of T2D patients. RESEARCH DESIGN AND METHODS Fasting lipoprotein profiles were determined by density gradient ultracentrifugation in T2D patients and their first-degree relatives (42 Caucasians and 33 South Asians), and in 29 normoglycemic controls from non-T2D families. Glucose tolerance, insulin sensitivity index (ISI) and insulin disposition index (DI) were assessed by an extended, frequently sampled oral glucose tolerance test (OGTT), and fractional insulin synthesis rate (FSR) was measured by 13C-leucine enrichment in urinary C-peptide during the OGTT. RESULTS Of the first-degree relatives, 40, 16 and 19 had NGT, prediabetes and T2D, respectively. NGT family members had lower plasma HDL-cholesterol (HDLC) (1.34 ± 0.07 vs 1.58 ± 0.06 mmol/L; p = 0.015), HDL2-C (0.41 ± 0.05 vs 0.57 ± 0.05 mmol/L; p = 0.021) and HDL3-C (0.62 ± 0.03 vs 0.72 ± 0.02 mmol/L; p = 0.043) than controls. HDL2-C levels tended to decrease with increasing glucose intolerance state. In South Asians, buoyant LDL-C levels decreased with increasing glucose intolerance state (p = 0.006). In South Asian families, HDL-C correlated with both ISI and DI (β 0.42; p = 0.04 and β 0.53; p = 0.01, respectively), whereas HDL2-C and HDL3-C levels correlated with DI (β 0.64; p = 0.002 and β 0.57; p = 0.005, respectively). HDL2-C and plasma triglyceride correlated with FSR (β 0.48; p = 0.033 and β -0.50; p = 0.029, respectively). CONCLUSIONS Low HDL2-C and HDL3-C levels are present in NGT first-degree relatives of T2D patients, and HDL2-C tend to decrease further with increasing glucose intolerance. In South Asian families HDL2-C and HDL3-C levels linked predominantly to deteriorating beta cell function.
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Affiliation(s)
- R Yahya
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - S Jainandunsing
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - M Rashid
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - L van der Zee
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - A Touw
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - F W M de Rooij
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - E J G Sijbrands
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - A J M Verhoeven
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands.
| | - M T Mulder
- Department of Internal Medicine, Section Pharmacology, Vascular Medicine, Cardiovascular Research School COEUR, Erasmus MC, University Medical Center Rotterdam, the Netherlands
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Nieto-Martínez R, González-Rivas JP, Mechanick JI. Cardiometabolic risk: New chronic care models. JPEN J Parenter Enteral Nutr 2021; 45:85-92. [PMID: 34519362 DOI: 10.1002/jpen.2264] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/23/2021] [Accepted: 09/08/2021] [Indexed: 11/10/2022]
Abstract
Cardiometabolic risk factors and the chronic cardiovascular diseases (CVD) that result from them are highly prevalent in the U.S. and amenable to clinical nutrition interventions. This creates an urgency to develop comprehensive care models that incorporate prevention-based actions by improving lifestyle routines. Such care models should account for social determinants of health, ethnocultural variables, and challenges to sustainability. The relevance of these newly designed chronic care models are to inform and facilitate early intervention, primarily consisting of lifestyle change and healthy nutrition, which mitigates progression from one stage to subsequent, higher morbidity stages to a greater extent than late intervention. In this paper, the mechanistic drivers and ethno-cultural validation of the Cardiometabolic-Based Chronic Disease (CMBCD) model are reviewed. Main findings are that in CMBCD, primary (genetics, environment, and behavior) and metabolic (obesity as Adiposity-Based Chronic Disease [ABCD], type 2 diabetes as Dysglycemia-Based Chronic Disease [DBCD], hypertension, and dyslipidemia) drivers initiate and perpetuate the progression of CVD. Epidemiological findings and molecular mechanisms support intra ABCD/DBCD, as well as ABCD to DBCD stage progression culminating in CVD. The ABCD definition overcomes weight stigma and BMI underperformance by considering adiposity amount, distribution, and function; and the DBCD definition overcomes criticisms of prediabetes and an exclusive glucocentric approach by considering insulin resistance and residual vascular risk along a clinical spectrum. In conclusion, clinicians should approach patients using the CMBCD model to incorporate lifestyle change as early as possible to optimally mitigate the burden of CVD. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Ramfis Nieto-Martínez
- LifeDoc Health, Memphis, TN, USA.,Department of Global Health and Population. Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts, USA.,Foundation for Clinic, Public Health, and Epidemiological Research of Venezuela (FISPEVEN), Caracas, Venezuela
| | - Juan P González-Rivas
- Department of Global Health and Population. Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts, USA.,Foundation for Clinic, Public Health, and Epidemiological Research of Venezuela (FISPEVEN), Caracas, Venezuela.,International Clinical Research Center (ICRC), St. Ann's University Hospital Brno (FNSUA), Czech Republic
| | - Jeffrey I Mechanick
- The Marie-Josée and Henry R. Kravis Center for Cardiovascular Health at Mount Sinai Heart, and Division of Endocrinology, Diabetes and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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53
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Justice AE, Young K, Gogarten SM, Sofer T, Graff M, Love SAM, Wang Y, Klimentidis YC, Cruz M, Guo X, Hartwig F, Petty L, Yao J, Allison MA, Below JE, Buchanan TA, Chen YDI, Goodarzi MO, Hanis C, Highland HM, Hsueh WA, Ipp E, Parra E, Palmas W, Raffel LJ, Rotter JI, Tan J, Taylor KD, Valladares A, Xiang AH, Sánchez-Johnsen L, Isasi CR, North KE. Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL. Hum Mol Genet 2021; 30:2190-2204. [PMID: 34165540 PMCID: PMC8561424 DOI: 10.1093/hmg/ddab166] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 01/02/2023] Open
Abstract
Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P < 1 × 10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed four novel loci (P < 0.05 and consistent direction of effect, and P < 5 × 10-8 after meta-analysis), including two for WHRadjBMI (rs13301996, rs79478137); one for WCadjBMI (rs3168072) and one for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI, 10 for WCadjBMI and 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity susceptibility that may be ancestry-specific.
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Affiliation(s)
- Anne E Justice
- Department of Population Health Sciences, Geisinger Health System, Danville, PA 17822, USA,Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA,To whom correspondence should be addressed at: Department of Population Health Sciences, Geisinger Health System, Danville, PA 17822, USA. Tel: +1 5702141009; Fax: +1 5702143071;
| | - Kristin Young
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | | | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Misa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Shelly Ann M Love
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Yann C Klimentidis
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ 85724, USA
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI (CMNSXX1)-IMSS, Mexico City 06720, Mexico
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Fernando Hartwig
- Center for Epidemiological Research, Universidade Federal de Pelotas, Pelotas 96020, Brazil
| | - Lauren Petty
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Matthew A Allison
- Division of Preventive Medicine, Department of Family Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jennifer E Below
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Thomas A Buchanan
- Department of Medicine, Keck School of Medicine and Diabetes and Obesity Research Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Craig Hanis
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Willa A Hsueh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, OH 43210, USA
| | - Eli Ipp
- Department of Medicine, Endocrinology, Diabetes & Metabolism, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Esteban Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Walter Palmas
- Department of Medicine, Columbia University Medical Center, New York, NY 10032, USA
| | - Leslie J Raffel
- Department of PediatrIcs, Division of Genetic and Genomic Medicine, University of California, Irvine, CA 92868, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Adan Valladares
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI (CMNSXX1)-IMSS, Mexico City 06720, Mexico
| | - Anny H Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA 91101, USA
| | - Lisa Sánchez-Johnsen
- Department of Family Medicine, Rush University Medical Center, Chicago, IL 60612, USA
| | - Carmen R Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY 10467, USA,Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10467, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
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Chen J, Li M, Hao B, Cai Y, Li H, Zhou W, Song Y, Wang S, Liu H. Waist to height ratio is associated with an increased risk of mortality in Chinese patients with heart failure with preserved ejection fraction. BMC Cardiovasc Disord 2021; 21:263. [PMID: 34049494 PMCID: PMC8164240 DOI: 10.1186/s12872-021-02080-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 05/24/2021] [Indexed: 12/13/2022] Open
Abstract
Background Abdominal obesity as a predominant comorbidity has played a key role in the incidence and worsening of heart failure with preserved ejection fraction (HFpEF), and waist-to-height ratio (WHtR) behaves better than waist circumference or body mass index in evaluating abdominal obesity. While the association between WHtR and all-cause death in Chinese patients with HFpEF remains unclear. Methods Patients with stable HFpEF (N = 2041) who presented to our hospital from January 2008 to July 2019 were divided into low-WHtR (< 0.5, N = 378) and high-WHtR (≥ 0.5, N = 1663). Multivariable Cox proportional-hazard models were used to examine the association of WHtR with all-cause death. Results The average age was 76.63 ± 11.44 years, and the mean follow-up was 4.53 years. During follow-up, 185 patients (9.06%) reached the primary outcome of all-cause death. As for the secondary outcome, 79 patients (3.87%) experienced cardiovascular death, 106 (5.19%) had non-cardiovascular death, and 94 (4.61%) had heart failure rehospitalization. After multivariable adjustment, a higher WHtR was significantly associated with the increased risks of all-cause death [adjusted hazard ratios (HR) 1.91, 95% confidence interval (CI) 1.06–3.45, p = 0.032], cardiovascular death (adjusted HR 2.58; 95% CI 1.01–6.67, p = 0.048), and HF rehospitalization (adjusted HR 3.04; 95% CI 1.26–7.31, p = 0.013). Conclusions Higher WHtR is an independent risk factor for all-cause death in Chinese patients with HFpEF. Supplementary Information The online version contains supplementary material available at 10.1186/s12872-021-02080-9.
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Affiliation(s)
- Jianqiao Chen
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China
| | - Man Li
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China
| | - Benchuan Hao
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China
| | - Yulun Cai
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China
| | - Huiying Li
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China
| | - Wenli Zhou
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China
| | - Yujian Song
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China
| | - Shiqi Wang
- General Department of Zhengzhou First People's Hospital, #56 Dong Dajie, Guancheng Hui District, Zhengzhou City, 450000, Henan Province, China
| | - Hongbin Liu
- Geriatric Cardiology Department of The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, #28 Fuxing Road, Beijing, 100853, China.
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Powell-Wiley TM, Poirier P, Burke LE, Després JP, Gordon-Larsen P, Lavie CJ, Lear SA, Ndumele CE, Neeland IJ, Sanders P, St-Onge MP. Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation 2021; 143:e984-e1010. [PMID: 33882682 PMCID: PMC8493650 DOI: 10.1161/cir.0000000000000973] [Citation(s) in RCA: 990] [Impact Index Per Article: 330.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The global obesity epidemic is well established, with increases in obesity prevalence for most countries since the 1980s. Obesity contributes directly to incident cardiovascular risk factors, including dyslipidemia, type 2 diabetes, hypertension, and sleep disorders. Obesity also leads to the development of cardiovascular disease and cardiovascular disease mortality independently of other cardiovascular risk factors. More recent data highlight abdominal obesity, as determined by waist circumference, as a cardiovascular disease risk marker that is independent of body mass index. There have also been significant advances in imaging modalities for characterizing body composition, including visceral adiposity. Studies that quantify fat depots, including ectopic fat, support excess visceral adiposity as an independent indicator of poor cardiovascular outcomes. Lifestyle modification and subsequent weight loss improve both metabolic syndrome and associated systemic inflammation and endothelial dysfunction. However, clinical trials of medical weight loss have not demonstrated a reduction in coronary artery disease rates. In contrast, prospective studies comparing patients undergoing bariatric surgery with nonsurgical patients with obesity have shown reduced coronary artery disease risk with surgery. In this statement, we summarize the impact of obesity on the diagnosis, clinical management, and outcomes of atherosclerotic cardiovascular disease, heart failure, and arrhythmias, especially sudden cardiac death and atrial fibrillation. In particular, we examine the influence of obesity on noninvasive and invasive diagnostic procedures for coronary artery disease. Moreover, we review the impact of obesity on cardiac function and outcomes related to heart failure with reduced and preserved ejection fraction. Finally, we describe the effects of lifestyle and surgical weight loss interventions on outcomes related to coronary artery disease, heart failure, and atrial fibrillation.
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Kammerlander AA, Lyass A, Mahoney TF, Massaro JM, Long MT, Vasan RS, Hoffmann U. Sex Differences in the Associations of Visceral Adipose Tissue and Cardiometabolic and Cardiovascular Disease Risk: The Framingham Heart Study. J Am Heart Assoc 2021; 10:e019968. [PMID: 33998254 PMCID: PMC8483556 DOI: 10.1161/jaha.120.019968] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Men and women are labeled as obese on the basis of a body mass index (BMI) using the same criterion despite known differences in their fat distributions. Subcutaneous adipose tissue and visceral adipose tissue (VAT), as measured by computed tomography, are advanced measures of obesity that closely correlate with cardiometabolic risk independent of BMI. However, it remains unknown whether prognostic significance of anthropometric measures of adiposity versus VAT varies in men versus women. Methods and Results In 3482 FHS (Framingham Heart Study) participants (48.1% women; mean age, 50.8±10.3 years), we tested the associations of computed tomography–based versus anthropometric measures of fat with cardiometabolic and cardiovascular disease (CVD) risk. Mean follow‐up was 12.7±2.1 years. In men, VAT, as compared with BMI, had a similar strength of association with incident cardiometabolic risk factors (eg, adjusted odds ratio [OR], 2.36 [95% CI, 1.84–3.04] versus 2.66 [95% CI, 2.04–3.47] for diabetes mellitus) and CVD events (eg, adjusted hazard ratio [HR], 1.32 [95% CI, 0.97–1.80] versus 1.74 [95% CI, 1.14–2.65] for CVD death). In women, however, VAT, when compared with BMI, conferred a markedly greater association with incident cardiometabolic risk factors (eg, adjusted OR, 4.51 [95% CI, 3.13–6.50] versus 2.33 [95% CI, 1.88–3.04] for diabetes mellitus) as well as CVD events (eg, adjusted HR, 1.85 [95% CI, 1.26–2.71] versus 1.19 [95% CI, 1.01–1.40] for CVD death). Conclusions Anthropometric measures of obesity, including waist circumference and BMI, adequately capture VAT‐associated cardiometabolic and cardiovascular risk in men but not in women. In women, abdominal computed tomography–based VAT measures permit more precise assessment of obesity‐associated cardiometabolic and cardiovascular risk.
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Affiliation(s)
- Andreas A Kammerlander
- Cardiovascular Imaging Research Center Massachusetts General HospitalHarvard Medical School Boston MA.,Division of Cardiology Medical University of Vienna Vienna Austria
| | - Asya Lyass
- Department of Mathematics and Statistics Boston University Boston MA
| | - Taylor F Mahoney
- Department of Biostatistics Boston University School of Public Health Boston MA
| | - Joseph M Massaro
- Department of Biostatistics Boston University School of Public Health Boston MA
| | - Michelle T Long
- Section of Gastroenterology Evans Department of Medicine Boston University School of Medicine Boston MA
| | - Ramachandran S Vasan
- Department of Internal Medicine Boston Medical CenterBoston University School of Medicine Boston MA.,Department of Epidemiology Boston University School of Public Health Boston MA.,The Boston University and the National Heart, Lung, and Blood Institute's Framingham Heart Study Framingham MA
| | - Udo Hoffmann
- Cardiovascular Imaging Research Center Massachusetts General HospitalHarvard Medical School Boston MA
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Wang C, Fu W, Cao S, Xu H, Tian Q, Gan Y, Guo Y, Yan S, Yan F, Yue W, Lv C, Lu Z. Association of adiposity indicators with hypertension among Chinese adults. Nutr Metab Cardiovasc Dis 2021; 31:1391-1400. [PMID: 33812733 DOI: 10.1016/j.numecd.2021.01.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 01/01/2021] [Accepted: 01/05/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND AND AIMS Obesity has been linked to the development of hypertension, but the comparison of relationships between different obesity parameters with hypertension are scarcely studied with nationally representative Chinese adults samples. We sought to compare the predictive strengths of different obesity indicators to hypertension. METHODS AND RESULTS Data in this study were obtained from the Chinese National Stroke Prevention Project with a nationally representative sample of Chinese aged 40 years and older. A total of 162,880 individuals were included. Multi-level analyses and Receiver Operating Characteristic (ROC) curves were used to examine the risk of hypertension in relation to different obesity parameters, including body mass index (BMI), waist circumference (WC), lipid accumulation product index (LAP), visceral adiposity index (VAI), and body adiposity index (BAI). As results, the BMI, WC, LAP, VAI, and BAI were positively associated with the risk of hypertension (P < 0.001). In total, BMI had the strongest association with hypertension when compared with other obesity indicators, and one SD up of BMI would increase the risk of hypertension by 53.9% (95% CI: 1.514-1.566). For men, WC was most associated with hypertension, and one SD up of WC would increase the risk of hypertension by 73.3% (95% CI: 1.685-1.782). For women, BMI showed the strongest predictive power, one SD up of BMI would increase the risk of hypertension by 51.0% (95% CI: 1.479-1.543). CONCLUSIONS BMI, WC, LAP, VAI, and BAI are all positively corrected to hypertension, but gender disparities should be considered in predicting hypertension by obesity indicators.
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Affiliation(s)
- Chao Wang
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenning Fu
- School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shiyi Cao
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongbin Xu
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qingfeng Tian
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yong Gan
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yingying Guo
- Children's Healthcare Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shijiao Yan
- School of International Education, Hainan Medical University, Haikou, China
| | - Feng Yan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Wei Yue
- Neurology Department, Tianjin Huanhu Hospital, Tianjin, China
| | - Chuanzhu Lv
- Emergency and Trauma College, Hainan Medical University, Haikou, China; Department of Emergency, The Second Affiliated Hospital of Hainan Medical University, Haikou, China.
| | - Zuxun Lu
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Ma GX, Bhimla A, Zhu L, Beeber M, Aczon F, Tan Y, Quinn SB, Khan O, Gadegbeku CA. Development of an Intervention to Promote Physical Activity and Reduce Dietary Sodium Intake for Preventing Hypertension and Chronic Disease in Filipino Americans. J Racial Ethn Health Disparities 2021; 8:283-292. [PMID: 32495306 PMCID: PMC7710586 DOI: 10.1007/s40615-020-00781-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 05/19/2020] [Accepted: 05/22/2020] [Indexed: 10/24/2022]
Abstract
Hypertension is a common chronic health condition affecting Filipino Americans. This pilot study examined the feasibility of addressing high rates of hypertension among Filipino Americans through the implementation of a culturally tailored education intervention. Filipino Americans living in the Greater Philadelphia Area were recruited through community-based organizations for participation and were engaged using a community-based participatory research (CBPR) framework. The study included pre- and post-intervention blood pressure measurements, self-reported body mass index, and questionnaires about physical activity and salt intake. The intervention to promote physical activity and reduce salt intake was conducted through two educational sessions and was accompanied by follow-up at 3 months and by the collection of urine samples for 24-h urinary sodium intake biomarker analysis. Following intervention, a non-statistically significant decrease in urine sodium was observed in both the intervention and the control groups. For systolic blood pressure, a reduction of 12.6 mmHg and an increase in 5.3 mmHg was observed in the intervention and control groups, respectively. Diastolic pressure decreased 3.8 mmHg for the intervention group and increased 5.6 mmHg among controls. The culturally tailored education intervention reported here represents a promising tool for blood pressure reduction in high-risk ethnic populations. The methods used were effective for the recruitment and retention of ethnic minorities in a community-based setting.
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Affiliation(s)
- Grace X Ma
- Center for Asian Health, Lewis Katz School of Medicine, Temple University, 3440 N Broad St., Suite 320, Kresge East Bldg, Philadelphia, PA, 19140, USA.
- Department of Clinical Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA.
| | - Aisha Bhimla
- Center for Asian Health, Lewis Katz School of Medicine, Temple University, 3440 N Broad St., Suite 320, Kresge East Bldg, Philadelphia, PA, 19140, USA
| | - Lin Zhu
- Center for Asian Health, Lewis Katz School of Medicine, Temple University, 3440 N Broad St., Suite 320, Kresge East Bldg, Philadelphia, PA, 19140, USA
| | - Maayan Beeber
- Hunter College, The City University of New York (CUNY), New York, NY, USA
| | - Ferdinand Aczon
- Filipino American Society of South Jersey Inc., Mount Laurel, NJ, 08084, USA
| | - Yin Tan
- Center for Asian Health, Lewis Katz School of Medicine, Temple University, 3440 N Broad St., Suite 320, Kresge East Bldg, Philadelphia, PA, 19140, USA
| | - Sally Boyle Quinn
- Division of Nephrology, Temple University School of Medicine, Philadelphia, PA, 19140, USA
| | - Omar Khan
- Center for Asian Health, Lewis Katz School of Medicine, Temple University, 3440 N Broad St., Suite 320, Kresge East Bldg, Philadelphia, PA, 19140, USA
| | - Crystal A Gadegbeku
- Division of Nephrology, Temple University School of Medicine, Philadelphia, PA, 19140, USA
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Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Cheng S, Delling FN, Elkind MSV, Evenson KR, Ferguson JF, Gupta DK, Khan SS, Kissela BM, Knutson KL, Lee CD, Lewis TT, Liu J, Loop MS, Lutsey PL, Ma J, Mackey J, Martin SS, Matchar DB, Mussolino ME, Navaneethan SD, Perak AM, Roth GA, Samad Z, Satou GM, Schroeder EB, Shah SH, Shay CM, Stokes A, VanWagner LB, Wang NY, Tsao CW. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation 2021; 143:e254-e743. [PMID: 33501848 DOI: 10.1161/cir.0000000000000950] [Citation(s) in RCA: 3098] [Impact Index Per Article: 1032.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease. RESULTS Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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60
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Saeed A, Virani SS, Mulukutla S, Chow CK. Dyslipidemia and Cardiovascular Disease Prevention in South Asians: A Review and Discussion of Causes, Challenges and Management Strategies. Curr Diabetes Rev 2021; 17:e011221190238. [PMID: 33438542 DOI: 10.2174/1573399817999210112192419] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 09/29/2020] [Accepted: 10/03/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND South Asians are at a significantly increased risk of atherosclerotic cardiovascular disease (ASCVD). For a major portion of the South Asian population, the cardiovascular disease events occur at a relatively younger age, are associated with worse outcomes, and have potentially more severe socioeconomic implications compared to their western counterparts. METHODS The term "South Asian" typically constitutes individuals from India, Pakistan, Nepal, Bhutan, Bangladesh, Sri Lanka, and Maldives, including expatriates as well as their families from these countries. Based on this, South Asians form approximately 25% of the world's population, with a high ASCVD burden in this group. In this review, we discuss the pathophysiological factors underlying ASCVD in South Asians, the dyslipidemia types and management, and discuss approaches to improve the overall ASCVD prevention efforts in this large subset population of the world. Although the pathophysiological mechanisms underlying the excess risk of cardiovascular disease in South Asians are multifactorial, dyslipidemia is a primary risk factor for the incidence and prevalence of this disease. The traditional "South Asian" dyslipidemia pattern includes levels of low-density lipoprotein cholesterol (LDL-C) in the normal range with a high concentration of LDL particles, elevated triglycerides, low levels of high-density lipoprotein cholesterol (HDL-C) with dysfunctional HDL particles, and high levels of lipoprotein(a). CONCLUSION While combined efforts to study the expatriate South Asians in western countries have been able to identify South Asian specific dyslipidemias, causal associations and optimal management remain relatively less explored. Larger scale studies are needed to better quantify the relationship of each lipid parameter with ASCVD risk among South Asians as well as optimal lipid targets and management strategies to reduce morbidity and mortality in this high-risk group.
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Affiliation(s)
- Anum Saeed
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States
| | - Salim S Virani
- Department of Health Policy, Quality and Informatics Program, Michael E. DeBakey Veterans Affairs Medical Center Health Services Research and Development Center for Innovations, Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, TX, United States
| | - Suresh Mulukutla
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States
| | - Clara K Chow
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Department of Cardiology, Westmead Hospital, The George Institute, Sydney, Australia
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61
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Sikand G, Severson T. Top 10 dietary strategies for atherosclerotic cardiovascular risk reduction. Am J Prev Cardiol 2020; 4:100106. [PMID: 34327475 PMCID: PMC8315554 DOI: 10.1016/j.ajpc.2020.100106] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 10/09/2020] [Accepted: 10/13/2020] [Indexed: 01/30/2023] Open
Abstract
Poor dietary quality has surpassed all other mortality risk factors, accounting for 11 million deaths and half of CVD deaths globally. Implementation of current nutrition recommendations from the American Heart Association (AHA), American College of Cardiology (ACC) and the National Lipid Association (NLA) can markedly benefit the primary and secondary prevention of atherosclerotic cardiovascular disease (ASCVD). These include: 1) incorporate nutrition screening into medical visits; 2) refer patients to a registered dietitian nutritionist (RDN) for medical nutrition therapy, when appropriate, for prevention of ASCVD; 3) follow ACC/AHA Nutrition and Diet Recommendations for ASCVD prevention and management of overweight/obesity, type 2 diabetes and hypertension; 4) include NLA nutrition goals for optimizing low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) and reducing ASCVD risk; 5) utilize evidence-based heart-healthy eating patterns for improving cardiometabolic risk factors, dyslipidemia and ASCVD risk; 6) implement ACC/AHA/NLA nutrition and lifestyle recommendations for optimizing triglyceride levels; 7) understand the impact of saturated fats, trans fats, omega-3 and omega-6 polyunsaturated fats and monounsaturated fats on ASCVD risk; 8) limit excessive intake of dietary cholesterol for those with dyslipidemia, diabetes and at risk for heart failure; 9) include dietary adjuncts such as viscous fiber, plant sterols/stanols and probiotics; and 10) implement AHA/ACC and NLA physical activity recommendations for the optimization of lipids and prevention of ASCVD. Evidence on controversies pertaining to saturated fat, processed meat, red meat, intermittent fasting, low-carbohydrate/very-low-carbohydrate diets and caffeine are discussed.
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Chirinos DA, Llabre MM, Goldberg R, Gellman M, Mendez A, Cai J, Sotres-Alvarez D, Daviglus M, Gallo LC, Schneiderman N. Defining Abdominal Obesity as a Risk Factor for Coronary Heart Disease in the U.S.: Results From the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Diabetes Care 2020; 43:1774-1780. [PMID: 32669410 PMCID: PMC7372049 DOI: 10.2337/dc19-1855] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 04/29/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Various organizations have highlighted the need to examine whether abdominal obesity cut points are appropriate for identification of cardiovascular risk among ethnic minority adults, particularly Hispanic/Latino adults living in Western societies. This study aimed 1) to establish optimal definitions for abdominal obesity among Hispanics/Latinos and 2) to determine the level of agreement between the presence of metabolic syndrome diagnosed by the current Joint Interim Statement (JIS) definition and an updated definition with optimal abdominal obesity cut points. RESEARCH DESIGN AND METHODS The sample included 16,289 adults who self-identified as Hispanic/Latino ages 18-74 years enrolled in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Receiver operating characteristic curves were used to derive sensitivity and specificity values. The largest sum of sensitivity plus specificity was used to determine appropriate cut points. RESULTS Among U.S. Hispanic/Latino adults, waist circumference cut points of >102 cm in men (in line with current JIS criteria) and >97 cm (9 points higher than JIS criteria) in women provide optimal discrimination for cardiovascular risk as judged by the presence of coronary heart disease. When using these cut points to create an updated metabolic syndrome definition among women, we found disagreement between our updated definition and the current JIS criteria. The prevalence of the metabolic syndrome was overestimated by ∼5 percentage points among women based on JIS criteria in comparison with our definition. CONCLUSIONS Our results suggest that the current recommendations for waist circumference cut points may not be appropriate for U.S. Hispanic/Latino women.
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Affiliation(s)
- Diana A Chirinos
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Maria M Llabre
- Behavioral Medicine Research Center, University of Miami, Coral Gables, FL
| | - Ronald Goldberg
- Behavioral Medicine Research Center, University of Miami, Coral Gables, FL
| | - Marc Gellman
- Behavioral Medicine Research Center, University of Miami, Coral Gables, FL
| | - Armando Mendez
- Behavioral Medicine Research Center, University of Miami, Coral Gables, FL
| | - Jianwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Daniela Sotres-Alvarez
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Marta Daviglus
- College of Medicine, University of Illinois at Chicago, Chicago, IL
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, CA
| | - Neil Schneiderman
- Behavioral Medicine Research Center, University of Miami, Coral Gables, FL
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63
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Beasley JM, Wagnild JM, Pollard TM, Roberts TR, Ahkter N. Effectiveness of diet and physical activity interventions among Chinese-origin populations living in high income countries: a systematic review. BMC Public Health 2020; 20:1019. [PMID: 32600296 PMCID: PMC7322842 DOI: 10.1186/s12889-020-08805-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 04/29/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND This review examines the effectiveness of diet and physical activity interventions to reduce cardiometabolic risk among Chinese immigrants and their descendants living in high income countries. The objective of this review is to provide information to help build future interventions aimed at improving diet and increasing physical activity levels among Chinese immigrants. METHODS Outcomes included BMI, weight, waist circumference (WC), waist-hip ratio (WHR), cholesterol (LDL, HDL), systolic and diastolic blood pressure (SBP, DBP), hemoglobin A1c (HgbA1c), fasting blood glucose (FBG), and HOMA-IR. Six databases were systematically searched from database inception to date of search (February 2020). Meta-analyses used random effect models to estimate pooled effects of outcomes with 95% confidence intervals. The outcomes assessed were changes in mean outcomes (post-intervention versus baseline) among the intervention group versus control groups. RESULTS Twenty-one articles were included for synthesis, and eight of these were included in the meta-analysis. Among children/adolescents, there were no significant effects of intervention for any of the outcomes having sufficient data for meta-analysis (BMI, WHR, SBP, and DBP). Among adults, the pooled effect including three studies showed significant changes in BMI (effect size = - 1.14 kg/m2; (95% CI: - 2.06, - 0.21), I2 = 31%). There were also significant effects of intervention among adults in terms of changes in SBP and DBP, as the pooled effect across three studies was - 6.08 mmHg (95% CI - 9.42, - 2.73), I2 = 0% and - 3.81 mmHg (95% CI: - 6.34, - 1.28), I2 = 0%, respectively. Among adults there were no other significant effects among the meta-analyses conducted (weight, WC, LDL, HgbA1c, and FBG). CONCLUSIONS This review is the first to summarize the effectiveness of diet and physical activity interventions specifically designed for Chinese immigrants living in high income countries. There were clinically meaningful changes in BMI and blood pressure among adults, but evidence was weak for other cardiometabolic outcomes (weight, WC, LDL, HgbA1c, and FBG), and among children, there was no evidence of effect for any cardiometabolic outcomes. Given our mixed findings, more work is needed to support the design of successful interventions, particularly those targeting children and their families. TRIAL REGISTRATION The systematic review protocol was registered in PROSPERO on December 17, 2018, the international prospective register of systematic reviews (registration number: CRD42018117842 ).
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Affiliation(s)
- Jeannette M. Beasley
- Department of Medicine, NYU Grossman School of Medicine, 462 First Avenue CD 673, New York, NY 10016 USA
| | - Janelle M. Wagnild
- Department of Anthropology, Durham University, South Road, Durham, DH1 3LE UK
| | - Tessa M. Pollard
- Department of Anthropology, Durham University, South Road, Durham, DH1 3LE UK
| | - Timothy R. Roberts
- NYU Health Sciences Library, NYU Grossman School of Medicine, 550 First Avenue, New York, NY 10016 USA
| | - Nasima Ahkter
- Department of Anthropology, Durham University, South Road, Durham, DH1 3LE UK
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Elechalawar CK, Hossen MN, McNally L, Bhattacharya R, Mukherjee P. Analysing the nanoparticle-protein corona for potential molecular target identification. J Control Release 2020; 322:122-136. [PMID: 32165239 PMCID: PMC7675788 DOI: 10.1016/j.jconrel.2020.03.008] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 03/05/2020] [Accepted: 03/06/2020] [Indexed: 12/18/2022]
Abstract
When nanoparticles are introduced into biological systems, host proteins tend to associate on the particle surface to form a protein layer termed the "protein corona" (PC). Identifying the proteins that constitute the PC can yield useful information about nanoparticle processing, bio-distribution, toxicity and clearance. Similarly, characterizing and identifying proteins within the PC from patient samples provides opportunities to probe disease proteomes and identify molecules that influence the disease process. Thus, nanoparticles represent unique probing tools for discovery of molecular targets for diseases. Here, we report a first review on target identification using nanoparticles in biological samples based on analysing physico chemical interactions. We also summarize the evolution of the PC surrounding various nano-systems, comment on PC signature, address PC complexity in fluids, and outline challenges associated with analysing the PC. In addition, the influence on PC formation of various nanoparticle parameters is summarized; nanoparticle characteristics considered include size, charge, temperature, and surface modifications for both organic and inorganic nanomaterials. We also discuss the advantages of nanotechnology, over other more invasive and laborious methods, for identifying potential diagnostic and therapeutic targets.
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Affiliation(s)
| | - Md Nazir Hossen
- Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Lacey McNally
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | - Resham Bhattacharya
- Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Priyabrata Mukherjee
- Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Peggy and Charles Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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Bae JC, Cho NH, Kim JH, Hur KY, Jin SM, Lee MK. Association of Body Mass Index with the Risk of Incident Type 2 Diabetes, Cardiovascular Disease, and All-Cause Mortality: A Community-Based Prospective Study. Endocrinol Metab (Seoul) 2020; 35:416-424. [PMID: 32615726 PMCID: PMC7386102 DOI: 10.3803/enm.2020.35.2.416] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 05/14/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Type 2 diabetes and cardiovascular disease (CVD) are the most important sequelae of obesity and the leading cause of death. We evaluated the association between body mass index (BMI) and the risk of incident type 2 diabetes, CVD, and all-cause mortality in a prospective study of a Korean population. METHODS The shapes of the associations were modeled by restricted cubic splines regression analysis. After categorizing all subjects (n=8,900) into octiles based on their BMI levels, we estimated the hazard ratio (HR) for the association of categorized BMI levels with the risk of incident CVD and type 2 diabetes using a Cox's proportional hazard analysis. RESULTS The mean age of participants was 52 years and 48% were men. Of the subjects at baseline, 39.0% of men and 45.6% of women were classified as obese (BMI ≥25 kg/m2). Over a mean follow-up of 8.1 years, CVD events occurred in 509 participants; 436 died; and 1,258 subjects developed type 2 diabetes. The increased risk of incident diabetes began to be significant at BMI 23 to 24 kg/m2 in both sexes (HR, 1.8). For CVD events, the risk began to increase significantly at BMI 26 to 28 kg/m2 (HR, 1.6). We found a reverse J-shaped relationship between BMI and all-cause mortality, with an increased risk among individuals with BMI values in lower range (BMI <21 kg/m2). CONCLUSION These results suggest that the BMI cut-off points for observed risk were varied depending on the diseases and that the BMI classification of obesity need to be revised to reflect differential risk of obesity-related diseases.
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Affiliation(s)
- Ji Cheol Bae
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon,
Korea
| | - Nam H. Cho
- Department of Preventive Medicine, Ajou University School of Medicine, Suwon,
Korea
| | - Jae Hyeon Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Kyu Yeon Hur
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Sang-Man Jin
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Moon-Kyu Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Soonchunhyang University Gumi Hospital, Soonchunhyang University College of Medicine, Gumi,
Korea
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66
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Zou P, Stinson J, Parry M, Dennis CL, Yang Y, Lu Z. A Smartphone App (mDASHNa-CC) to Support Healthy Diet and Hypertension Control for Chinese Canadian Seniors: Protocol for Design, Usability and Feasibility Testing. JMIR Res Protoc 2020; 9:e15545. [PMID: 32238343 PMCID: PMC7316441 DOI: 10.2196/15545] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 11/12/2019] [Accepted: 12/09/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND This proposed study aims to translate the Dietary Approach to Stop Hypertension with Sodium (Na) Reduction for Chinese Canadians (DASHNa-CC), a classroom-based, antihypertensive, dietary educational intervention, to an innovative smartphone app (mDASHNa-CC). This study will enable Chinese Canadian seniors to access antihypertensive dietary interventions anytime, regardless of where they are. It is hypothesized that senior Chinese Canadians will be satisfied with their experiences using the mDASHNa-CC app and that the use of this app could lead to a decrease in their blood pressure and improvement in their health-related quality of life. OBJECTIVE The goal of this study is to design and test the usability and feasibility of a smartphone-based dietary educational app to support a healthy diet and hypertension control for Chinese Canadian seniors. METHODS A mixed-method two-phase design will be used. The study will be conducted in a Chinese immigrant community in Toronto, Ontario, Canada. Chinese Canadian seniors, who are at least 65 years old, self-identified as Chinese, living in Canada, and with elevated blood pressure, will be recruited. In Phase I, we will design and test the usability of the app using a user-centered approach. In Phase II, we will test the feasibility of the app, including implementation (primary outcomes of accrual and attrition rates, technical issues, acceptability of the app, and adherence to the intervention) and preliminary effectiveness (secondary outcomes of systolic and diastolic blood pressure, weight, waist circumference, health-related quality of life, and health service utilization), using a pilot, two-group, randomized controlled trial with a sample size of 60 participants in a Chinese Canadian community. RESULTS The study is supported by the Startup Research Grant from Nipissing University, Canada. The research ethics application is under review by a university research ethics review board. CONCLUSIONS The study results will make several contributions to the existing literature, including illustrating the rigorous design and testing of smartphone app technology for hypertension self-management in the community, exploring an approach to incorporating traditional medicine into chronic illness management in minority communities and promoting equal access to current technology among minority immigrant senior groups. TRIAL REGISTRATION Clinicaltrials.gov NCT03988894; https://clinicaltrials.gov/ct2/show/NCT03988894. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/15545.
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Affiliation(s)
- Ping Zou
- School of Nursing, Nipissing University, Toronto, ON, Canada
| | - Jennifer Stinson
- Lawrence Bloomberg Faculty of Nursing, University of Toronto, Hospital for Sick Children, Toronto, ON, Canada
| | - Monica Parry
- Lawrence Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada
| | - Cindy-Lee Dennis
- Lawrence Bloomberg Faculty of Nursing and Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Yeqin Yang
- School of Nursing, Wenzhou Medical University, Wenzhou, China
| | - Zhongqiu Lu
- School of Nursing, Wenzhou Medical University, Wenzhou, China
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67
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Xi B, Zong X, Kelishadi R, Litwin M, Hong YM, Poh BK, Steffen LM, Galcheva SV, Herter-Aeberli I, Nawarycz T, Krzywińska-Wiewiorowska M, Khadilkar A, Schmidt MD, Neuhauser H, Schienkiewitz A, Kułaga Z, Kim HS, Stawińska-Witoszyńska B, Motlagh ME, Ruzita AT, Iotova VM, Grajda A, Ismail MN, Krzyżaniak A, Heshmat R, Stratev V, Różdżyńska-Świątkowska A, Ardalan G, Qorbani M, Świąder-Leśniak A, Ostrowska-Nawarycz L, Yotov Y, Ekbote V, Khadilkar V, Venn AJ, Dwyer T, Zhao M, Magnussen CG, Bovet P. International Waist Circumference Percentile Cutoffs for Central Obesity in Children and Adolescents Aged 6 to 18 Years. J Clin Endocrinol Metab 2020; 105:5625521. [PMID: 31723976 PMCID: PMC7059990 DOI: 10.1210/clinem/dgz195] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Accepted: 11/12/2019] [Indexed: 01/26/2023]
Abstract
CONTEXT No universal waist circumference (WC) percentile cutoffs used have been proposed for screening central obesity in children and adolescents. OBJECTIVE To develop international WC percentile cutoffs for children and adolescents with normal weight based on data from 8 countries in different global regions and to examine the relation with cardiovascular risk. DESIGN AND SETTING We used pooled data on WC in 113,453 children and adolescents (males 50.2%) aged 4 to 20 years from 8 countries in different regions (Bulgaria, China, Iran, Korea, Malaysia, Poland, Seychelles, and Switzerland). We calculated WC percentile cutoffs in samples including or excluding children with obesity, overweight, or underweight. WC percentiles were generated using the general additive model for location, scale, and shape (GAMLSS). We also estimated the predictive power of the WC 90th percentile cutoffs to predict cardiovascular risk using receiver operator characteristics curve analysis based on data from 3 countries that had available data (China, Iran, and Korea). We also examined which WC percentiles linked with WC cutoffs for central obesity in adults (at age of 18 years). MAIN OUTCOME MEASURE WC measured based on recommendation by the World Health Organization. RESULTS We validated the performance of the age- and sex-specific 90th percentile WC cutoffs calculated in children and adolescents (6-18 years of age) with normal weight (excluding youth with obesity, overweight, or underweight) by linking the percentile with cardiovascular risk (area under the curve [AUC]: 0.69 for boys; 0.63 for girls). In addition, WC percentile among normal weight children linked relatively well with established WC cutoffs for central obesity in adults (eg, AUC in US adolescents: 0.71 for boys; 0.68 for girls). CONCLUSION The international WC cutoffs developed in this study could be useful to screen central obesity in children and adolescents aged 6 to 18 years and allow direct comparison of WC distributions between populations and over time.
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Affiliation(s)
- Bo Xi
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China
- Correspondence and Reprint Requests: Bo Xi, Department of Epidemiology, School of Public Health, Shandong University, Jinan, China. E-mail: OR
| | - Xin’nan Zong
- Department of Growth and Development, Capital Institute of Pediatrics, Beijing, China
| | - Roya Kelishadi
- Department of Pediatrics, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mieczysław Litwin
- Department of Nephrology and Arterial Hypertension, The Children’s Memorial Health Institute, Warsaw, Poland
| | - Young Mi Hong
- Department of Pediatrics, Ewha Womans University School of Medicine, Seoul, Korea
| | - Bee Koon Poh
- Nutritional Sciences Programme and Centre for Community Health Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesotas School of Public Health, Minneapolis, USA
| | - Sonya V Galcheva
- Department of Pediatrics, Varna Medical University, Varna, Bulgaria
| | - Isabelle Herter-Aeberli
- Institute of Food, Nutrition and Health, Human Nutrition Laboratory, ETH Zurich, Zürich, Switzerland
| | - Tadeusz Nawarycz
- Department of Biophysics, Chair of Experimental and Clinical Physiology, Medical University of Lodz, Lodz, Poland
| | | | - Anuradha Khadilkar
- Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India
| | - Michael D Schmidt
- Department of Kinesiology, University of Georgia, Athens, Georgia, USA
| | - Hannelore Neuhauser
- Department of Epidemiology and Health Monitoring, Robert Koch Institute, 12101 Berlin, Germany and DZHK (German Center for Cardiovascular Research), partner site Berlin, Berlin, Germany
| | - Anja Schienkiewitz
- Department of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin, Germany
| | - Zbigniew Kułaga
- Department of Public Health, The Children’s Memorial Health Institute, Warsaw, Poland
| | - Hae Soon Kim
- Department of Pediatrics, Ewha Womans University School of Medicine, Seoul, Korea
| | - Barbara Stawińska-Witoszyńska
- Department of Epidemiology and Hygiene, Chair of Social Medicine, Poznan University of Medical Sciences, Poznan, Poland
| | | | - Abd Talib Ruzita
- Nutritional Sciences Programme and Centre for Community Health Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Violeta M Iotova
- Department of Pediatrics, Varna Medical University, Varna, Bulgaria
| | - Aneta Grajda
- Department of Public Health, The Children’s Memorial Health Institute, Warsaw, Poland
| | - Mohd Noor Ismail
- Faculty of Social Sciences and Leisure Management, Taylor’s University, Subang Jaya, Selangor, Malaysia
| | - Alicja Krzyżaniak
- Department of Epidemiology and Hygiene, Chair of Social Medicine, Poznan University of Medical Sciences, Poznan, Poland
| | - Ramin Heshmat
- Department of Epidemiology, Chronic Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Velin Stratev
- Department of Internal Medicine, Varna Medical University, Varna, Bulgaria
| | | | - Gelayol Ardalan
- Department of Pediatrics, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mostafa Qorbani
- Non-communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran
| | - Anna Świąder-Leśniak
- Department of Anthropometry, The Children’s Memorial Health Institute, Warsaw, Poland
| | - Lidia Ostrowska-Nawarycz
- Department of Biophysics, Chair of Experimental and Clinical Physiology, Medical University of Lodz, Lodz, Poland
| | - Yoto Yotov
- Department of cardiology, Medical University Varna, Varna, Bulgaria
| | - Veena Ekbote
- Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India
| | - Vaman Khadilkar
- Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India
| | - Alison J Venn
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Terence Dwyer
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
- George Institute for Global Health, Oxford Martin School and Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, UK
| | - Min Zhao
- Departments of Nutrition and Food Hygiene, School of Public Health, Shandong University, Jinan, China
| | - Costan G Magnussen
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Pascal Bovet
- Department of Epidemiology and Health Services, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
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Zhu L, Gu S, Wang Q, Zhou X, Wang S, Fu C, Yang W, Wetzl J, Yan F. Left ventricular myocardial deformation: a study on diastolic function in the Chinese male population and its relationship with fat distribution. Quant Imaging Med Surg 2020; 10:634-645. [PMID: 32269924 DOI: 10.21037/qims.2020.01.16] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Obesity has become an epidemic in China with its increased prevalence, especially in the male population. Disparities in fat distribution rather than increasing body mass index (BMI) confer the risk of different diseases, including cardiac abnormalities. Therefore, early detection of cardiac abnormalities is important for treatment to reverse the progression to heart failure. Nowadays, strain analysis based on cardiac magnetic resonance (CMR) imaging has been established to assess myocardial function in diverse cardiac diseases. We aimed to assess the relationship between fat distribution and subclinical diastolic dysfunction in obese Chinese men assessed by deformation registration algorithm (DRA)-based myocardial strain rate (SR) analysis. Methods A total of 115 male participants with different BMI underwent CMR scanning using a 1.5T MAGNETOM Aera (Siemens Healthcare, Erlangen, Germany) and computed tomography (CT) scan. All the participants were enrolled from September 2017 to April 2018. They were classified into 3 groups according to their BMIs with 23 and 27.5 kg/m2 being the cutoff values. A Trufi-Strain prototype software (version 2.0, Siemens Healthcare, Erlangen, Germany) was used to quantify SR in both early and late diastole from CMR cine images. Ratios of early and late SRs were calculated. Areas of epicardial and pericardial adipose tissue (EAT and PAT) were measured on a single 4-chamber-view slice of cine images. Volumes of visceral and subcutaneous adipose tissue (VAT and SAT) were acquired semi-automatically from CT images using the dedicated software Cardiac Risk2.0 (Siemens Healthcare). Waist and hip circumferences were manually measured (WC and HC). Analysis of variance or nonparametric tests, along with correlation and stepwise multivariate regression analysis models, was applied for statistical analysis. Results Peak late diastolic SRs were higher in obese men compared with their lean counterparts [-36.25±10.46 vs. -29.46±8.17, 66.97±18.58 vs. 45.62 (42.44, 55.96), and 56.81±15.07 vs. 41.40±6.41 for radial, circumferential, and longitudinal SRs, respectively; P<0.05]. All SR ratios in the obese subgroups were lower than those of lean men (3.12±1.14 vs. 4.63±1.24, 2.12±0.58 vs. 2.96±0.62 and 1.63±0.50 vs. 2.20±0.63 for radial, circumferential, and longitudinal directions, respectively; P<0.05). EAT was a significant predictor of diastolic function assessed by radial and circumferential SR ratios (β=-0.439 and -0.337 respectively; all P<0.001), while VAT was a significant predictor of circumferential and longitudinal SR ratios (β=-0.216 and -0.355, respectively, P<0.05). Conclusions Decreased LV diastolic function assessed by DRA-based SR analysis in obesity is associated with fat distribution. Furthermore, EAT and VAT might be better predictors of a decrease of diastolic function in obese Chinese men than BMI.
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Affiliation(s)
- Lan Zhu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Shengjia Gu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Qingrou Wang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xiaoyue Zhou
- Collaboration, Siemens Healthcare Ltd., Shanghai 201318, China
| | - Simin Wang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Caixia Fu
- Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen 518057, China
| | - Wenjie Yang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | | | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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69
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Burroughs Peña MS, Mbassa RS, Slopen NB, Williams DR, Buring JE, Albert MA. Cumulative Psychosocial Stress and Ideal Cardiovascular Health in Older Women. Circulation 2020; 139:2012-2021. [PMID: 30813768 DOI: 10.1161/circulationaha.118.033915] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Research implicates acute and chronic stressors in racial/ethnic health disparities, but the joint impact of multiple stressors on racial/ethnic disparities in cardiovascular health is unknown. METHODS In 25 062 women (24 053 white; 256 Hispanic; 440 black; 313 Asian) articipating in the Women's Health Study follow-up cohort, we examined the relationship between cumulative psychosocial stress (CPS) and ideal cardiovascular health (ICH), as defined by the American Heart Association's 2020 strategic Impact Goals. This health metric includes smoking, body mass index, physical activity, diet, blood pressure, total cholesterol, and glucose, with higher levels indicating more ICH and less cardiovascular risk (score range, 0-7). We created a CPS score that summarized acute stressors (eg, negative life events) and chronic stressors (eg, work, work-family spillover, financial, discrimination, relationship, and neighborhood) and traumatic life event stress reported on a stress questionnaire administered in 2012 to 2013 (score range, 16-385, with higher scores indicating higher levels of stress). RESULTS White women had the lowest mean CPS scores (white: 161.7±50.4; Hispanic: 171.2±51.7; black: 172.5±54.9; Asian: 170.8±50.6; Poverall<0.01). Mean CPS scores remained higher in Hispanic, black, and Asian women than in white women after adjustment for age, socioeconomic status (income and education), and psychological status (depression and anxiety) ( P<0.01 for each). Mean ICH scores varied by race/ethnicity ( P<0.01) and were significantly lower in black women and higher in Asian women compared with white women (β-coefficient [95% CI]: Hispanics, -0.02 [-0.13 to -0.09]; blacks, -0.34 [-0.43 to -0.25]; Asians, 0.34 [0.24 to 0.45]); control for socioeconomic status and CPS did not change these results. Interactions between CPS and race/ethnicity in ICH models were not significant. CONCLUSIONS Both CPS and ICH varied by race/ethnicity. ICH remained worse in blacks and better in Asians compared with whites, despite taking into account socioeconomic factors and CPS.
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Affiliation(s)
- Melissa S Burroughs Peña
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology, Department of Medicine, University of California, San Francisco (M.S.B.P., R.S.M., M.A.A.)
| | - Rachel S Mbassa
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology, Department of Medicine, University of California, San Francisco (M.S.B.P., R.S.M., M.A.A.)
| | - Natalie B Slopen
- Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park (N.B.S.)
| | - David R Williams
- Department of Social and Behavioral Sciences (D.R.W.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Julie E Buring
- Department of Epidemiology (J.E.B.), Harvard T.H. Chan School of Public Health, Boston, MA.,Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital (J.E.B.), Boston, MA
| | - Michelle A Albert
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology, Department of Medicine, University of California, San Francisco (M.S.B.P., R.S.M., M.A.A.)
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Dietary Patterns in Chinese Americans are Associated with Cardiovascular Disease Risk Factors, the Chinese American Cardiovascular Health Assessment (CHA CHA). J Immigr Minor Health 2020; 21:1061-1069. [PMID: 30097786 DOI: 10.1007/s10903-018-0800-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Little is known about the dietary patterns of Chinese Americans. Understanding their dietary patterns can provide insights for addressing cardiovascular disease (CVD) risk among Chinese American immigrants. The objective of this study was to identify dietary patterns among Chinese American immigrants living in New York City (NYC) and to describe associations with demographic and CVD risk factors. A validated Food Frequency Questionnaire assessed usual dietary intake in Chinese American immigrants living in NYC as part of the Chinese American Cardiovascular Health Assessment (CHA CHA) in 2010-2011 (n = 1973, age range 21-89 years). Principal components analysis with varimax rotation retaining three factors with eigenvalues > 1.5 identified dietary patterns. Multivariable linear regression models tested associations between CVD risk factors and dietary pattern scores. In multivariable analyses, each unit of increase in the Sweets factor was associated with 0.76 ± 0.33 (mean ± SD) mg/dL higher HDL cholesterol and a 6.2 ± 2.7% increase in HOMA-IR. In contrast, each unit increase in the Fried Noodles factor was associated with a 0.27 ± 0.11 inch greater waist circumference, - 0.89 ± 0.40 mg/dL lower HDL cholesterol, and also a 6.9 ± 2.6% increase in HOMA-IR. Each unit increase in the Vegetables factor was associated with a - 1.40 ± 0.43 mmHg and - 0.95 ± 0.27 mm Hg decrease in systolic and diastolic blood pressure, respectively. Dietary patterns are significantly associated with CVD risk factors among Chinese American immigrants in NYC. Future work will inform how dietary patterns relate to level of acculturation in order to guide the development of dietary interventions to reduce CVD risk.
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71
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Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Shay CM, Spartano NL, Stokes A, Tirschwell DL, VanWagner LB, Tsao CW. Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association. Circulation 2020; 141:e139-e596. [PMID: 31992061 DOI: 10.1161/cir.0000000000000757] [Citation(s) in RCA: 4856] [Impact Index Per Article: 1214.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals. RESULTS Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Das SR, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Jordan LC, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, O'Flaherty M, Pandey A, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Spartano NL, Stokes A, Tirschwell DL, Tsao CW, Turakhia MP, VanWagner LB, Wilkins JT, Wong SS, Virani SS. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation 2019; 139:e56-e528. [PMID: 30700139 DOI: 10.1161/cir.0000000000000659] [Citation(s) in RCA: 5336] [Impact Index Per Article: 1067.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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73
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Association of general and central adiposity with blood pressure among Chinese adults: results from the China National Stroke Prevention Project. J Hypertens 2019; 36:2406-2413. [PMID: 30020239 DOI: 10.1097/hjh.0000000000001852] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND The American Heart Association concluded that waist circumference was a better predictor of blood pressure risk than BMI in Asians. However, data are inconsistent and information in Chinese, the largest global population group, is limited. METHODS Data was obtained from the Chinese National Stroke Prevention Project Survey of a nationally representative sample of middle-aged and older Chinese adults. A total of 135 825 individuals not taking any antihypertensive drugs were included in this study. Multiple linear regression analyses were conducted to examine the association between blood pressure and parameters of general adiposity, including BMI, height-adjusted weight, and parameters of central adiposity, including waist circumference, hip circumference, waist-hip ratio, and waist-height ratio. Results were shown as mean difference in blood pressure associated with one standard deviation higher level of adiposity. RESULTS The overall means ± standard deviation of BMI and waist circumference were 24.3 ± 3.18 kg/m and 84.0 ± 8.88 cm, respectively. BMI seemed more strongly associated with SBP/DBP (4.22 mmHg/SD; 2.60 mmHg/SD) than central adiposity markers. In addition, there were sex differences. For men, waist circumference showed a stronger association with SBP/DBP than BMI (4.04 vs. 3.79, P < 0.05; 2.26 vs. 2.13, P < 0.05). For women, BMI was more closely related to SBP/DBP than central adiposity parameters, such as waist circumference (4.59 vs. 3.41, P < 0.05; 2.98 vs. 2.24, P < 0.05). Additionally, in both urban and rural areas, waist circumference was mostly associated with SBP/DBP among men, whereas it was BMI among women. CONCLUSION Compared with central adiposity, blood pressure is more strongly associated with general adiposity in Chinese adults. Interestingly, there are significant sex differences in the relationship of blood pressure with general and central adiposity. Waist circumference is the strongest predictor for men but suboptimal for women, and BMI tend to a better predictor of blood pressure for women. In addition, our results for men are consistent with the recommendation of the American Heart Association in 2015 that waist circumference could be used for assessing the risk of blood pressure.
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Yang DY, Nie ZQ, Liao LZ, Zhang SZ, Zhou HM, Sun XT, Zhong XB, Du ZM, Zhuang XD, Liao XX. Phenomapping of subgroups in hypertensive patients using unsupervised data-driven cluster analysis: An exploratory study of the SPRINT trial. Eur J Prev Cardiol 2019; 26:1693-1706. [PMID: 31213079 DOI: 10.1177/2047487319856733] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
BACKGROUND Hypertensive patients are highly heterogeneous in cardiovascular prognosis and treatment responses. A better classification system with phenomapping of clinical features would be of greater value to identify patients at higher risk of developing cardiovascular outcomes and direct individual decision-making for antihypertensive treatment. METHODS An unsupervised, data-driven cluster analysis was performed for all baseline variables related to cardiovascular outcomes and treatment responses in subjects from the Systolic Blood Pressure Intervention Trial (SPRINT), in order to identify distinct subgroups with maximal within-group similarities and between-group differences. Cox regression was used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for cardiovascular outcomes and compare the effect of intensive antihypertensive treatment in different clusters. RESULTS Four replicable clusters of patients were identified: cluster 1 (index hypertensives); cluster 2 (chronic kidney disease hypertensives); cluster 3 (obese hypertensives) and cluster 4 (extra risky hypertensives). In terms of prognosis, individuals in cluster 4 had the highest risk of developing primary outcomes. In terms of treatment responses, intensive antihypertensive treatment was shown to be beneficial only in cluster 4 (HR 0.73, 95% CI 0.55-0.98) and cluster 1 (HR 0.54, 95% CI 0.37-0.79) and was associated with an increased risk of severe adverse effects in cluster 2 (HR 1.18, 95% CI 1.05-1.32). CONCLUSION Using a data-driven approach, SPRINT subjects can be stratified into four phenotypically distinct subgroups with different profiles on cardiovascular prognoses and responses to intensive antihypertensive treatment. Of note, these results should be taken as hypothesis generating that warrant further validation in future prospective studies.
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Affiliation(s)
- Da-Ya Yang
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
| | - Zhi-Qiang Nie
- Guangdong Cardiovascular Institute, Guangdong Provincial Hospital, China
| | - Li-Zhen Liao
- Department of Health, Guangdong Pharmaceutical University, China
| | - Shao-Zhao Zhang
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
| | - Hui-Min Zhou
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
| | - Xiu-Ting Sun
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
| | - Xiang-Bin Zhong
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
| | - Zhi-Min Du
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
| | - Xiao-Dong Zhuang
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
| | - Xin-Xue Liao
- Department of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, China.,NHC Key Laboratory on Assisted Circulation, Sun Yat-Sen University, China
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019; 139:e1082-e1143. [PMID: 30586774 PMCID: PMC7403606 DOI: 10.1161/cir.0000000000000625] [Citation(s) in RCA: 1174] [Impact Index Per Article: 234.8] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Scott M Grundy
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Neil J Stone
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Alison L Bailey
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Craig Beam
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Kim K Birtcher
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Roger S Blumenthal
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Lynne T Braun
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sarah de Ferranti
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Faiella-Tommasino
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel E Forman
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Ronald Goldberg
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Paul A Heidenreich
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Mark A Hlatky
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel W Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Donald Lloyd-Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Nuria Lopez-Pajares
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Chiadi E Ndumele
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carl E Orringer
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carmen A Peralta
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph J Saseen
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sidney C Smith
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Laurence Sperling
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Salim S Virani
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Yeboah
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
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Thomas SC, Umer A, Commodore-Mensah Y, Davidov D, Abildso CG. Length of Residence and Cardiovascular Health among Afro-Caribbean Immigrants in New York City. J Racial Ethn Health Disparities 2019; 6:487-496. [PMID: 30547300 PMCID: PMC6500463 DOI: 10.1007/s40615-018-00547-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 10/31/2018] [Accepted: 11/22/2018] [Indexed: 01/16/2023]
Abstract
Cardiovascular disease (CVD) disproportionately affects non-Hispanic blacks (NHB) in the United States (U.S.). Afro-Caribbean (AC) immigrants comprise over 50% of the immigrant black population and are critical in understanding the health trajectories of blacks in the U.S. We assessed the relationship between length of residence (proxy measure for acculturation) and cardiovascular health (CVH) based on the American Heart Association's (AHA) seven ideal cardiovascular health components among AC immigrants in New York City (NYC). CVH scores were categorized into poor/intermediate CVH (0-3 components) or ideal CVH (≥ 4 components). Multivariable logistic regression was used to examine the association between length of residence in the U.S. and poor/intermediate CVH. In adjusted models, the odds of poor/intermediate CVH were significantly higher for Guyanese (OR = 3.51; 95% CI 1.03-11.95) and Haitian immigrants (OR = 8.02; 95% CI 1.88-34.12) residing in the U.S. for ≥ 10 years than for those living in the U.S. for < 10 years. Length of residence was not significantly associated with CVH among Jamaican immigrants. We found evidence of ethnic differences in the association between acculturation and CVH among AC immigrants in a major metropolitan city. Culturally tailored interventions are needed to improve the CVH of AC immigrants as they become integrated into the U.S., with special consideration of country of birth.
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Affiliation(s)
- Sabena C Thomas
- Department of Social and Behavioral Sciences, West Virginia University School of Public Health, 64 Medical Center Drive, P.O. Box 9190, Morgantown, WV, 26506-9190, USA
| | - Amna Umer
- Department of Pediatrics, West Virginia University School of Medicine, 64 Medical Center Drive, P.O. Box 9214, Morgantown, WV, 26506-9214, USA
| | | | - Danielle Davidov
- Department of Social and Behavioral Sciences, West Virginia University School of Public Health, 64 Medical Center Drive, P.O. Box 9190, Morgantown, WV, 26506-9190, USA
| | - Christiaan G Abildso
- Department of Social and Behavioral Sciences, West Virginia University School of Public Health, 64 Medical Center Drive, P.O. Box 9190, Morgantown, WV, 26506-9190, USA.
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77
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol. J Am Coll Cardiol 2019; 73:e285-e350. [DOI: 10.1016/j.jacc.2018.11.003] [Citation(s) in RCA: 1113] [Impact Index Per Article: 222.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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78
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Borja-Hart N, Graff JC, Nolan VG, Wang J, Cooper-DeHoff RM, Ancheta IB. Atherosclerotic cardiovascular disease risk assessment and predictors of statin use in Filipino-American Women. J Clin Pharm Ther 2019; 44:632-639. [PMID: 30963623 DOI: 10.1111/jcpt.12837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 02/28/2019] [Accepted: 03/11/2019] [Indexed: 11/26/2022]
Abstract
WHAT IS KNOWN AND OBJECTIVE Race and gender disparities in the context of appropriate treatment with lipid-lowering therapies do exist. The 2013 American College of Cardiology (ACC)/American Heart Association (AHA) guidelines outlined four groups, three for primary prevention and one for secondary prevention, whom would benefit from statin therapy to target atherosclerotic cardiovascular disease (ASCVD). The application of these recommendations in Filipino women living in the United States is unknown; however, this population is known to have elevated cardiovascular risk. Socio-economic and clinical characteristics that predict statin utilization of this Asian American subgroup need to be explored. METHODS This was an exploratory analysis of data collected during a cross-sectional study of Filipino-American Women (FAW). The Pooled Cohort equation was used to estimate 10-year ASCVD risk. Bivariate analysis was employed to determine the association between statin treatment and clinical and socio-economic factors. Data were analysed using SAS® 9.4; statistical significance was set at P < 0.05. RESULTS AND DISCUSSION A total of 384 women (mean age 56.3 years) were included in the original study, and the average 10-year ASCVD risk was 3.5 ± 3.7%. Upon applying the 2013 ACC/AHA guidelines, 97 FAW were categorized into one of the primary prevention groups. Women considered to benefit from a statin based on the guideline criteria but were not prescribed a statin were considered the not statin treated group (n = 55). From the original cohort, 93 FAW reported current statin therapy use and were categorized as statin treated. The clinical characteristics associated with not being statin treated were as follows: untreated blood pressure (P = 0.012), higher diastolic blood pressure (P = 0.015), higher total cholesterol (P < 0.001), higher triglycerides (P = 0.041), higher low-density lipoprotein (P < 0.001) and higher glucose (P = 0.011). The socio-economic factor associated with not being statin treated was having two or more insurance payers (P = 0.005). Overall, this population had a waist circumference and body mass index (BMI) that exceeds guidelines for Asian women (31.5 or 80 cm). WHAT IS NEW AND CONCLUSION Predictors of statin utilization in FAW are not well documented in the literature. These findings emphasize room for improvement for the prescribing of statins in primary prevention for this study population. Applying culturally appropriate screening strategies to identify cardiovascular risk factors early such as BMI or waist circumference may assist with quantifying patients into one of the statin benefit groups if eligible.
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Affiliation(s)
- Nancy Borja-Hart
- Department of Clinical Pharmacy and Translational Science, College of Pharmacy, The University of Tennessee Health Science Center, Nashville, Tennessee
| | - J Carolyn Graff
- Nursing Science Program, College of Nursing, The University of Tennessee Health Science Center, Memphis, Tennessee
| | - Vikki G Nolan
- School of Public Health, The University of Memphis, Memphis, Tennessee
| | - Jiajing Wang
- Department of Preventive Medicine, The University of Tennessee Health Science Center, Memphis, Tennessee
| | - Rhonda M Cooper-DeHoff
- Division of Cardiovascular Medicine, Department of Pharmacotherapy and Translational Research, Colleges of Pharmacy and Medicine, University of Florida, Gainesville, Florida
| | - Irma B Ancheta
- Department of Medicine, University of Florida, Jacksonville, Florida
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79
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2018; 139:e1046-e1081. [PMID: 30565953 DOI: 10.1161/cir.0000000000000624] [Citation(s) in RCA: 254] [Impact Index Per Article: 42.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Scott M Grundy
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Neil J Stone
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Alison L Bailey
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Craig Beam
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Kim K Birtcher
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Roger S Blumenthal
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Lynne T Braun
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sarah de Ferranti
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Faiella-Tommasino
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel E Forman
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Ronald Goldberg
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Paul A Heidenreich
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Mark A Hlatky
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel W Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Donald Lloyd-Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Nuria Lopez-Pajares
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Chiadi E Ndumele
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carl E Orringer
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carmen A Peralta
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph J Saseen
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sidney C Smith
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Laurence Sperling
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Salim S Virani
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Yeboah
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
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80
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2018; 73:3168-3209. [PMID: 30423391 DOI: 10.1016/j.jacc.2018.11.002] [Citation(s) in RCA: 996] [Impact Index Per Article: 166.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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81
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Sajja AP, Joshi AA, Teague HL, Dey AK, Mehta NN. Potential Immunological Links Between Psoriasis and Cardiovascular Disease. Front Immunol 2018; 9:1234. [PMID: 29910818 PMCID: PMC5992299 DOI: 10.3389/fimmu.2018.01234] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 05/16/2018] [Indexed: 12/12/2022] Open
Abstract
Preclinical and clinical research provide strong evidence that chronic, systemic inflammation plays a key role in development and progression of atherosclerosis. Indeed, chronic inflammatory diseases, such as psoriasis, are associated with accelerated atherosclerosis and increased risk of cardiovascular events. Contemporary research has demonstrated plausible mechanistic links between immune cell dysfunction and cardiometabolic disease in psoriasis. In this review, we describe the role of potential common immunological mechanisms underlying both psoriasis and atherogenesis. We primarily discuss innate and adaptive immune cell subsets and their contributions to psoriatic disease and cardiovascular morbidity. Emerging efforts should focus on understanding the interplay among immune cells, adipose tissue, and various biomarkers of immune dysfunction to provide direction for future targeted therapy.
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Affiliation(s)
| | | | | | | | - Nehal N. Mehta
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
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82
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He X, Liu C, Chen Y, He J, Dong Y. Overweight Without Central Obesity, Cardiovascular Risk, and All-Cause Mortality. Mayo Clin Proc 2018; 93:709-720. [PMID: 29656788 DOI: 10.1016/j.mayocp.2018.01.027] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Revised: 01/23/2018] [Accepted: 01/29/2018] [Indexed: 12/24/2022]
Abstract
OBJECTIVE To assess the association of overweight without central obesity with risks of mortality. PATIENTS AND METHODS We included 14,299 participants in the Third National Health and Nutrition Examination Survey (from October 18, 1988, through October 15, 1994). According to their body mass index and waist circumference, participants were categorized into 7 anthropometric groups. Logistic regression models were used to assess the relation of cardiovascular risk factors (hypertension, diabetes, or hypercholesterolemia) and 10-year cardiovascular risk to anthropometric groups. Cox proportional hazards models were used to assess the risk of all-cause mortality, and competing-risks regression models were used for calculating cardiovascular and noncardiovascular mortality. RESULTS Compared with those with normal body mass index and waist circumference, overweight men without central obesity were more likely to have all 3 cardiovascular risk factors and a high cardiovascular risk, whereas women in this anthropometric group were more likely to have hypercholesterolemia. In proportional hazards models, overweight without central obesity was associated with lower all-cause mortality among men in the population with cardiovascular risk factors (hazard ratio, 0.71; 95% CI, 0.56-0.89; P=.004) and the general population (hazard ratio, 0.72; 95% CI, 0.60-0.87; P=.001), whereas results of these comparisons among women were not significant (P>.05). In competing risk analyses, overweight men without central obesity had a lower risk of noncardiovascular mortality, but not cardiovascular mortality. CONCLUSION Although overweight without central obesity was associated with cardiovascular risk factors and a high cardiovascular risk among men, men in this anthropometric group had a lower mortality risk.
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Affiliation(s)
- Xin He
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, and Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China
| | - Chen Liu
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, and Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China
| | - Yili Chen
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, and Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China
| | - Jiangui He
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, and Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China
| | - Yugang Dong
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, and Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China.
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Chen Z, Iona A, Parish S, Chen Y, Guo Y, Bragg F, Yang L, Bian Z, Holmes MV, Lewington S, Lacey B, Gao R, Liu F, Zhang Z, Chen J, Walters RG, Collins R, Clarke R, Peto R, Li L. Adiposity and risk of ischaemic and haemorrhagic stroke in 0·5 million Chinese men and women: a prospective cohort study. Lancet Glob Health 2018; 6:e630-e640. [PMID: 29773119 PMCID: PMC5960068 DOI: 10.1016/s2214-109x(18)30216-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 02/13/2018] [Accepted: 03/29/2018] [Indexed: 01/05/2023]
Abstract
BACKGROUND China has high stroke rates despite the population being relatively lean. Uncertainty persists about the relevance of adiposity to risk of stroke types. We aimed to assess the associations of adiposity with incidence of stroke types and effect mediation by blood pressure in Chinese men and women. METHODS The China Kadoorie Biobank enrolled 512 891 adults aged 30-79 years from ten areas (five urban and five rural) during 2004-08. During a median 9 years (IQR 8-10) of follow-up, 32 448 strokes (about 90% confirmed by neuroimaging) were recorded among 489 301 participants without previous cardiovascular disease. Cox regression analysis was used to produce adjusted hazard ratios (HRs) for ischaemic stroke (n=25 210) and intracerebral haemorrhage (n=5380) associated with adiposity. FINDINGS Mean baseline body-mass index (BMI) was 23·6 kg/m2 (SD 3·2), and 331 723 (67·8%) participants had a BMI of less than 25 kg/m2. Throughout the range examined (mean 17·1 kg/m2 [SD 0·9] to 31·7 kg/m2 [2·0]), each 5 kg/m2 higher BMI was associated with 8·3 mm Hg (SE 0·04) higher systolic blood pressure. BMI was positively associated with ischaemic stroke, with an HR of 1·30 (95% CI 1·28-1·33 per 5 kg/m2 higher BMI), which was generally consistent with that predicted by equivalent differences in systolic blood pressure (1·25 [1·24-1·26]). The HR for intracerebral haemorrhage (1·11 [1·07-1·16] per 5 kg/m2 higher BMI) was less extreme, and much weaker than that predicted by the corresponding difference in systolic blood pressure (1·48 [1·46-1·50]). Other adiposity measures showed similar associations with stroke types. After adjustment for usual systolic blood pressure, the positive associations with ischaemic stroke were attenuated (1·05 [1·03-1·07] per 5 kg/m2 higher BMI); for intracerebral haemorrhage, they were reversed (0·73 [0·70-0·77]). High adiposity (BMI >23 kg/m2) accounted for 14·7% of total stroke (16·5% of ischaemic stroke and 6·7% of intracerebral haemorrhage). INTERPRETATION In Chinese adults, adiposity was strongly positively associated with ischaemic stroke, chiefly through its effect on blood pressure. For intracerebral haemorrhage, leanness, either per se or through some other factor (or factors), might increase risk, offsetting the protective effects of lower blood pressure. FUNDING UK Wellcome Trust, UK Medical Research Council, British Heart Foundation, Cancer Research UK, Kadoorie Charitable Foundation, Chinese Ministry of Science and Technology, Chinese National Natural Science Foundation.
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Affiliation(s)
- Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK,Correspondence to: Prof Zhengming Chen, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Andri Iona
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Sarah Parish
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK,Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK,Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing, China
| | - Fiona Bragg
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK,Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Zheng Bian
- Chinese Academy of Medical Sciences, Beijing, China
| | - Michael V Holmes
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK,Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Sarah Lewington
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK,Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Ben Lacey
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Ruqin Gao
- Qingdao Centre for Disease Control and Prevention, Qingdao, China
| | - Fang Liu
- Suzhou Centre for Disease Control and Prevention, Suzhou, China
| | - Zengzhi Zhang
- Qingdao Shinan District Centre for Disease Control and Prevention, Shinan District, Qingdao, China
| | - Junshi Chen
- National Center for Food Safety Risk Assessment, Beijing, China
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Richard Peto
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
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Rocca B, Fox KAA, Ajjan RA, Andreotti F, Baigent C, Collet JP, Grove EL, Halvorsen S, Huber K, Morais J, Patrono C, Rubboli A, Seljeflot I, Sibbing D, Siegbahn A, Ten Berg J, Vilahur G, Verheugt FWA, Wallentin L, Weiss TW, Wojta J, Storey RF. Antithrombotic therapy and body mass: an expert position paper of the ESC Working Group on Thrombosis. Eur Heart J 2018; 39:1672-1686f. [PMID: 29509886 DOI: 10.1093/eurheartj/ehy066] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 02/08/2018] [Indexed: 02/11/2024] Open
Affiliation(s)
- Bianca Rocca
- Institute of Pharmacology, Catholic University School of Medicine, Largo Francesco Vito 1, 00168 Rome, Italy
| | - Keith A A Fox
- Centre for Cardiovascular Science, University and Royal Infirmary of Edinburgh, 51 Little France Cres, Edinburgh EH16 4SA, UK
| | - Ramzi A Ajjan
- Leeds Institute for Cardiovascular and Metabolic Medicine, the LIGHT Laboratories, University of Leeds, Leeds LS2?9JT, UK
| | - Felicita Andreotti
- Cardiovascular Department, Catholic University Hospital, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Colin Baigent
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF, UK
| | - Jean-Philippe Collet
- Institute of Cardiology, Pitié-Salpêtrière Hospital (AP-HP), Sorbonne Université Paris 06 (UPMC), ACTION Study Group, INSERM UMR_S 1166, Groupe Hospitalier Pitié-Salpêtrière, 47-83 Bd de l'hopital, 75013 Paris, France
| | - Erik L Grove
- Department of Cardiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200 Aarhus, Denmark
- Department of Clinical Medicine, Faculty of Health, Aarhus University, Palle Juul-Jensens Boulevard 82, 8200 Aarhus; Denmark
| | - Sigrun Halvorsen
- Department of Cardiology, Oslo University Hospital Ulleval and University of Oslo, P.O. Box 1171 Blindern, 0318 Oslo, Norway
| | - Kurt Huber
- 3rd Department of Medicine, Cardiology and Intensive Care Medicine, Wilhelminenhospital, Montleartstrasse 37, A-1160 Vienna and Sigmund Freud University, Medical School, Kelsenstrasse 2, A-1030 Vienna, Austria
| | - João Morais
- Division of Cardiology, Leiria Hospital Center, R. de Santo André, 2410-197 Leiria, Portugal
| | - Carlo Patrono
- Institute of Pharmacology, Catholic University School of Medicine, Largo Francesco Vito 1, 00168 Rome, Italy
| | - Andrea Rubboli
- Division of Cardiology, Laboratory of Interventional Cardiology, Ospedale Maggiore, Largo Nigrisoli 2, 40133 Bologna, Italy
| | - Ingebjorg Seljeflot
- Department of Cardiology, Center for Clinical Heart Research, Oslo University Hospital Ullevål and University of Oslo, P.O. Box 1171 Blindern, 0318 Oslo, Norway
| | - Dirk Sibbing
- Department of Cardiology, Munich University Clinic, Ludwig-Maximilians-Universität, Munich, Germany
- DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Marchioninistrasse 15, 81377 Munich, Germany
| | - Agneta Siegbahn
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, 751 85 Uppsala, Sweden
| | - Jurrien Ten Berg
- Department of Cardiology, St Antonius Hospital, Koekoekslaan 1, 3435 CM Nieuwegein, The Netherlands
| | - Gemma Vilahur
- Cardiovascular Science Institute-ICCC, IIB-Sant Pau, CiberCV, Hospital de Sant Pau, Avda. S. Antoni M. Claret 167, 08025 Barcelona, Spain
| | - Freek W A Verheugt
- Department of Cardiology, Onze Lieve Vrouwe Gasthuis (OLVG), Oosterpark 9, 1091 AC Amsterdam, The Netherlands
| | - Lars Wallentin
- Department of Medical Sciences, Cardiology, Uppsala University & Uppsala Clinical Research Center, Uppsala Science Park, MTC, Dag Hammarskjölds väg 14B, SE-752 37 Uppsala, Sweden
| | - Thomas W Weiss
- 3rd Department of Medicine, Cardiology and Intensive Care Medicine, Wilhelminenhospital, Montleartstrasse 37, A-1160 Vienna and Sigmund Freud University, Medical School, Kelsenstrasse 2, A-1030 Vienna, Austria
| | - Johann Wojta
- Department of Internal Medicine II, Medical University Vienna, Vienna, Austria
- Core Facilities, Medical University Vienna, Vienna, Austria
- Ludwig Boltzmann Cluster for Cardiovascular Research, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Robert F Storey
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Beech Hill Road, Sheffield, South Yorkshire S10 2RX, UK
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85
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Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, Chiuve SE, Cushman M, Delling FN, Deo R, de Ferranti SD, Ferguson JF, Fornage M, Gillespie C, Isasi CR, Jiménez MC, Jordan LC, Judd SE, Lackland D, Lichtman JH, Lisabeth L, Liu S, Longenecker CT, Lutsey PL, Mackey JS, Matchar DB, Matsushita K, Mussolino ME, Nasir K, O'Flaherty M, Palaniappan LP, Pandey A, Pandey DK, Reeves MJ, Ritchey MD, Rodriguez CJ, Roth GA, Rosamond WD, Sampson UKA, Satou GM, Shah SH, Spartano NL, Tirschwell DL, Tsao CW, Voeks JH, Willey JZ, Wilkins JT, Wu JH, Alger HM, Wong SS, Muntner P. Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association. Circulation 2018; 137:e67-e492. [PMID: 29386200 DOI: 10.1161/cir.0000000000000558] [Citation(s) in RCA: 4513] [Impact Index Per Article: 752.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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86
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Jarrah M, Hammoudeh AJ, Khader Y, Tabbalat R, Al-Mousa E, Okkeh O, Alhaddad IA, Tawalbeh LI, Hweidi IM. Reality of obesity paradox: Results of percutaneous coronary intervention in Middle Eastern patients. J Int Med Res 2018; 46:1595-1605. [PMID: 29468911 PMCID: PMC6091834 DOI: 10.1177/0300060518757354] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Objective The aim of this study was to assess the baseline clinical characteristics, coronary angiographic features, and adverse cardiovascular events during hospitalization and at 1 year of follow-up in obese patients compared with overweight and normal/underweight patients. Methods A prospective, multicenter study of consecutive patients undergoing percutaneous coronary intervention was performed. Results Of 2425 enrolled patients, 699 (28.8%) were obese, 1178 (48.6%) were overweight, and 548 (22.6%) were normal/underweight. Obese patients were more likely to be female and to have a higher prevalence of diabetes, hypertension, hypercholesterolemia, or previous percutaneous coronary intervention. Acute coronary syndrome was the indication for percutaneous coronary intervention in 77.0% of obese, 76.4% of overweight, and 77.4% of normal/underweight patients. No significant differences in the prevalence of multi-vessel coronary artery disease or multi-vessel percutaneous coronary intervention were found among the three groups. Additionally, no significant differences were found in stent thrombosis, readmission bleeding rates, or cardiac mortality among the three groups during hospitalization, at 1 month, and at 1 year. Conclusion The major adverse cardiovascular event rate was the same among the three groups throughout the study period. Accordingly, body mass index is considered a weak risk factor for cardiovascular comorbidities in Arab Jordanian patients.
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Affiliation(s)
- Mohamad Jarrah
- 1 Cardiology Section, Internal Medicine Department, King Abdullah University Hospital, Irbid, Jordan
| | | | - Yousef Khader
- 3 Allied Medical Sciences School, 37251 Jordan University of Science and Technology , Irbid, Jordan
| | - Ramzi Tabbalat
- 4 Cardiology Department, Khalidi Medical Center, Amman, Jordan
| | - Eyas Al-Mousa
- 2 Cardiology Department, Istishari Hospital, Amman, Jordan
| | - Osama Okkeh
- 5 Cardiology Department, Arab Medical Center, Amman, Jordan
| | - Imad A Alhaddad
- 6 Cardiology Department, Jordan Hospital Medical Center, Amman, Jordan
| | | | - Issa M Hweidi
- 8 Faculty of Nursing, 37251 Jordan University of Science and Technology , Irbid, Jordan
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87
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Impact of Body Mass Index on Heart Failure by Race/Ethnicity From the Get With The Guidelines-Heart Failure (GWTG-HF) Registry. JACC-HEART FAILURE 2018; 6:233-242. [PMID: 29428434 DOI: 10.1016/j.jchf.2017.11.011] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 11/27/2017] [Accepted: 11/28/2017] [Indexed: 12/15/2022]
Abstract
OBJECTIVES This study sought to evaluate the influence of race/ethnicity on the relationship between body mass index (BMI) and mortality in heart failure with preserved ejection fraction (HFpEF) and HF with reduced EF (HFrEF) patients. BACKGROUND Prior studies demonstrated an "obesity paradox" among overweight and obese patients, where they have a better HF prognosis than normal weight patients. Less is known about the relationship between BMI and mortality among diverse patients with HF, particularly given disparities in obesity and HF prevalence. METHODS The authors used Get With The Guidelines-Heart Failure data to assess the relationship between BMI and in-hospital mortality by using logistic regression modeling. The authors assessed 30-day and 1-year rates of all-cause mortality following discharge by using Cox regression modeling. RESULTS A total of 39,647 patients with HF were included (32,434 [81.8%] white subjects; 3,809 [9.6%] black subjects; 1,928 [4.9%] Hispanic subjects; 544 [1.4%] Asian subjects; and 932 [2.3%] other subjects); 59.7% of subjects had HFpEF, and 30.7% were obese. More black and Hispanic patients had Class I or higher obesity (BMI ≥30 kg/m2) than whites, Asians, or other racial/ethnic groups (p < 0.0001). Among subjects with HFpEF, higher BMI was associated with lower 30-day mortality, up to 30 kg/m2 with a small risk increase above 30 kg/m2 (BMI: 30 vs. 18.5 kg/m2), hazard ratio (HR) of 0.63 (95% confidence interval [CI]: 0.54 to 0.73). A modest relationship was observed in HFrEF subjects (BMI: 30 vs. 18.5 kg/m2; HR: 0.73; 95% CI: 0.60 to 0.89), with no risk increase above 30 kg/m2. There were no significant interactions between BMI and race or ethnicity related to 30-day mortality (p > 0.05). CONCLUSIONS This work is one of the first suggesting the obesity paradox for 30-day mortality exists at all BMI levels in HFrEF but not in patients with HFpEF. Higher BMI was associated with lower 30-day mortality across racial/ethnic groups in a manner inconsistent with the J-shaped relationship noted for coronary artery disease. The differential slope of obesity and mortality among HFpEF and patients with HFrEF potentially suggests differing mechanistic factors, requiring further exploration.
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88
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Diemer FS, Brewster LM, Haan YC, Oehlers GP, van Montfrans GA, Nahar-van Venrooij LMW. Body composition measures and cardiovascular risk in high-risk ethnic groups. Clin Nutr 2017; 38:450-456. [PMID: 29249531 DOI: 10.1016/j.clnu.2017.11.012] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 11/01/2017] [Accepted: 11/19/2017] [Indexed: 01/06/2023]
Abstract
BACKGROUND & AIMS Cardiovascular disease (CVD) is highly prevalent in Suriname, a middle-income country with predominantly people of African and Asian ancestry. We examined whether the more comprehensive body composition measures determined by bioelectrical impedance analysis (BIA) are superior to the more traditional BMI and waist measures in relation to cardiovascular risk. METHODS Data from the cross-sectional Healthy Life in Suriname (HELISUR) study were used to calculate BMI, waist-hip ratio, waist-to-height ratio, and waist circumference. BIA was used to estimate fat percentage, fat-free mass index, and fat-to-fat-free mass ratio. High cardiovascular risk was defined as 1) a 10-year Framingham coronary heart disease risk score ≥10% in African-Surinamese and ≥12% in Asian-Surinamese, and 2) an increased arterial stiffness (pulse wave velocity >10 m/s). Using logistic regression analysis, we pre-selected the strongest correlate (i.e. lowest p-value below 0.05) of all body composition items for both outcomes of cardiovascular risk separately, and subsequently, used forward logistic regression modelling to determine whether other measures added value to the initial model with the strongest correlate (-2 log-likelihood (-2LL) of initial model minus -2LL of new model, χ-square statistic >3.841, 1 df). Analyses were adjusted for sex, age and ethnicity. RESULTS We examined 691 participants (65% women; 48% African-Surinamese) with a mean age of 42 (SD 14) years. Waist circumference was the strongest correlate for high 10-year CVD risk in the total group, in men and African-Surinamese. In Asian-Surinamese, fat-free mass index was the strongest correlate of high 10-year CVD risk. Increased arterial stiffness was most strongly related with waist-to-height ratio in the total group and in African-Surinamese, and with BMI in men. None of the measures were significantly associated in women (for both outcomes) and Asian-Surinamese (for increased arterial stiffness). Forward selection showed that only BMI added value next to waist-to-height ratio in the total group in relation to increased arterial stiffness. CONCLUSIONS Waist measures, in particular waist circumference and waist-to-height ratio, and BMI should be used in African and Asian-Surinamese to identify who is at increased cardiovascular risk. Overall, we found little advantage in using BIA measures rather than simple anthropometric measures.
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Affiliation(s)
- F S Diemer
- Department of Cardiology, Academic Hospital of Paramaribo, Suriname; Department of Cardiology, Academic Medical Center, Amsterdam, The Netherlands.
| | - L M Brewster
- Department of Internal Medicine, Academic Medical Center, Amsterdam, The Netherlands; Department of Public Health, Faculty of Medical Sciences, Anton de Kom University of Suriname, Paramaribo, Suriname
| | - Y C Haan
- Department of Vascular Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - G P Oehlers
- Department of Cardiology, Academic Hospital of Paramaribo, Suriname
| | - G A van Montfrans
- Department of Internal Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - L M W Nahar-van Venrooij
- Department of Public Health, Faculty of Medical Sciences, Anton de Kom University of Suriname, Paramaribo, Suriname
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89
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Rivers JP, Powell-Wiley TM, Dey AK, Rodante JA, Chung JH, Joshi AA, Natarajan B, Sajja AP, Chaturvedi A, Rana A, Harrington CL, Teague HL, Lockshin BN, Ahlman MA, Yao J, Playford MP, Gelfand JM, Mehta NN. Visceral Adiposity in Psoriasis is Associated With Vascular Inflammation by 18F-Fluorodeoxyglucose Positron-Emission Tomography/Computed Tomography Beyond Cardiometabolic Disease Risk Factors in an Observational Cohort Study. JACC Cardiovasc Imaging 2017; 11:349-357. [PMID: 29055628 DOI: 10.1016/j.jcmg.2017.08.014] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 08/15/2017] [Accepted: 08/16/2017] [Indexed: 02/06/2023]
Abstract
OBJECTIVES The authors sought to examine the relationship between visceral adipose tissue (VAT) and vascular inflammation (VI) by 18F-Fluorodeoxyglucose (18F-FDG) positron-emission tomography (PET)/computed tomography (CT) in psoriasis (PSO). Furthermore, we evaluated whether treatment of PSO modulated VAT and VI. BACKGROUND PSO, a chronic inflammatory skin disease, is associated with VI by 18F-FDG PET/CT and increased cardiometabolic risk including adipose tissue dysregulation. Recently, VI was associated with future cardiovascular events; however, the relationship of visceral and subcutaneous adiposity with VI in PSO has yet to be evaluated. METHODS Consecutive PSO patients (N = 77) underwent 18F-FDG PET/CT scans to measure VI and abdominal adiposity. A subset of PSO patients with severe skin disease was scanned at 1 year following PSO treatment (N = 13). RESULTS The cohort was middle aged (51.8 ± 12.6 years), predominantly male (n = 44, 57%), had low cardiovascular risk by Framingham 10-year risk (median 4 years [interquartile range (IQR): 2 to 7 years]), and mild-to-moderate skin disease (5.2 [IQR: 3.0 to 8.5]). PSO disease severity associated with VAT (β = 0.33; p = 0.004) beyond SAT (β = 0.30; p = 0.005). VAT (β = 0.55; p < 0.001), but not SAT (β = 0.15; p = 0.11), associated with VI beyond cardiovascular risk factors. We followed a subset of severe PSO patients treated aggressively for PSO and observed improvement in PSO severity and VAT, which was associated with an improvement in VI at 1 year beyond cardiovascular risk factors (β = 0.53; p = 0.049). CONCLUSIONS Volume-based CT measurement of VAT may capture metabolic risk associated with VI compared to subcutaneous adipose tissue in PSO. PSO treatment associated with a decrease in VAT as well as decrease in VI suggesting VAT as a relevant biomarker related to VI in PSO.
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Affiliation(s)
- Joshua P Rivers
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Tiffany M Powell-Wiley
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Amit K Dey
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Justin A Rodante
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Jonathan H Chung
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Aditya A Joshi
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Balaji Natarajan
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Aparna P Sajja
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Abhishek Chaturvedi
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Anshuma Rana
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Charlotte L Harrington
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Heather L Teague
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | | | - Mark A Ahlman
- Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Research Center, Bethesda, Maryland
| | - Jianhua Yao
- Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Research Center, Bethesda, Maryland
| | - Martin P Playford
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Joel M Gelfand
- Department of Dermatology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Nehal N Mehta
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland.
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90
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Sohn M, Cho KH, Han KD, Choi M, Kim YH. Sitting Time and Obesity or Abdominal Obesity in Older South Koreans: Korean National Health and Nutrition Examination Survey 2013. Behav Med 2017; 43:251-258. [PMID: 26808482 DOI: 10.1080/08964289.2015.1135101] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
We examined relationships between sitting time and obesity or abdominal obesity according to sex and socioeconomic status in elderly people. We analyzed data from the Korean National Health and Nutrition Examination Survey 2013, and 1565 participants were included in the study. Multivariate logistic regression analysis was used to examine relationships between sitting time and obesity or abdominal obesity according to sex and socioeconomic status. Sitting time was positively correlated with body mass index in men and women and waist circumference in men. When considering socioeconomic factors, men who sat for 5 hours or longer and fell within the lowest income were more likely to have obesity and abdominal obesity relative to men who sat for 5 hours or shorter and earned higher incomes (odds ratio [95% confidence interval] = 1.80 [1.14-2.84] and 1.63 [1.02-2.61] respectively), and women who sat for 5 hours or longer and fell within the lowest educational level were more likely to have obesity relative to women who sat for 5 hours or less and were educated to a higher level (1.24 [1.01-1.85]). Strategies to reduce sedentary behavior would help to prevent obesity in older men who earn low incomes and women with lower levels of educational attainment.
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Affiliation(s)
- Minsung Sohn
- a Department of Public Health Science , Graduate School, BK21Plus Program in Public Health Science, Korea University
| | - Kyung-Hwan Cho
- b Department of Family Medicine , Anam Hospital, Korea University College of Medicine
| | - Kyung-Do Han
- c Department of Medical Statistics , Catholic University College of Medicine
| | - Mankyu Choi
- a Department of Public Health Science , Graduate School, BK21Plus Program in Public Health Science, Korea University
| | - Yang-Hyun Kim
- b Department of Family Medicine , Anam Hospital, Korea University College of Medicine
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Lopez-Cepero A, Frisard CF, Lemon SC, Rosal MC. Association of Dysfunctional Eating Patterns and Metabolic Risk Factors for Cardiovascular Disease among Latinos. J Acad Nutr Diet 2017; 118:849-856. [PMID: 28774505 DOI: 10.1016/j.jand.2017.06.007] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Accepted: 06/06/2017] [Indexed: 12/16/2022]
Abstract
BACKGROUND Latinos are at high risk for cardiovascular disease (CVD). Identifying behavioral factors associated with CVD risk in this population may provide novel targets for further research to reduce chronic disease disparities. Dysfunctional eating patterns (emotional eating [EE], uncontrolled eating [UE], and cognitive restraint of eating [CR]) may be associated with CVD risk but little is known about this relationship in Latinos. OBJECTIVE The aim of this study was to examine associations between dysfunctional eating patterns and metabolic risk factors for CVD in Latinos. DESIGN The study used a cross-sectional design. PARTICIPANTS/SETTING Latino individuals (n=602), aged 21 to 84 years, were enrolled in the study from September 2011 to May 2013 from a community health center that serves 80% to 85% of the Latino population in Lawrence, MA. Individuals with complete data were included in this analysis (n=578). MEASURES Dysfunctional eating patterns were measured with the Three Factor Eating Questionnaire-R18V2. CVD risk factors examined included obesity assessed by body mass index and waist circumference and diagnoses of type 2 diabetes, hypertension, and hyperlipidemia abstracted from electronic health records. STATISTICAL ANALYSIS Multivariable logistic and Poisson regressions adjusting for age, sex, perceived income, employment, education, physical activity, and perceived stress were performed. The no dysfunctional eating category (ie, no EE, no UE, or no CR) was used as the reference category in all analyses. RESULTS High EE was associated with greater odds of obesity (odds ratio [OR] 2.19, 95% CI 1.38 to 3.45) and central obesity (OR 2.97, 95% CI 1.81 to 4.87), and diagnosis of type 2 diabetes (OR 1.99, 95% CI 1.13 to 3.48) and hypertension (OR 2.01, 95% CI 1.16 to 3.48). High UE was associated with obesity (OR 1.96, 95% CI 1.20 to 3.21) and central obesity (OR 2.33, 95% CI 1.38 to 3.94). Low and high CR were associated with obesity (OR 2.26, 95% CI 1.43 to 3.56 and OR 2.77, 95% CI 1.75 to 4.37, respectively) and central obesity (OR 2.04, 95% CI 1.25 to 3.32 and 2.51, 95% CI 1.54 to 4.08, respectively) and diagnosis of type 2 diabetes (OR 1.83, 95% CI 1.05 to 3.16 and OR 2.73, 95% CI 1.58 to 4.70, respectively) and hyperlipidemia (OR 1.94, 95% CI 1.16 to 3.24 and OR 2.14, 95% CI 1.28 to 3.55, respectively). Lastly, high EE and low and high CR were associated with increased odds of having a greater number of metabolic CVD risk factors (incidence-rate ratio [IRR] 1.33, 95% CI 1.13 to 1.58; IRR 1.34, 95% CI 1.13 to 1.58; and IRR 1.44, 95% CI 1.22 to 1.71, respectively). CONCLUSIONS Dysfunctional eating patterns were positively associated with metabolic CVD risk factors in this Latino sample, with dose-response relationships for some associations. Future studies are needed to determine whether dysfunctional eating patterns influence CVD risk factors among Latinos.
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Abstract
The treatment of essential hypertension is one of the most critical interventions to decrease cardiovascular morbidity and mortality. The prevalence of hypertension in the US varies across race/ethnicity with African Americans having the highest prevalence and overall less control among racial/ethnic minorities compared with non-Hispanic whites. Therapeutic lifestyle modifications are the bedrock of essential hypertension control, but most patients with hypertension will require pharmacotherapy, usually with multiple medications often in combination. Overall, the principal drug classes recommended as initial pharmacotherapy are thiazide-type diuretics, calcium channel blockers, and angiotensin-converting enzyme inhibitors or angiotensin receptor blockers.
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Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, de Ferranti SD, Floyd J, Fornage M, Gillespie C, Isasi CR, Jiménez MC, Jordan LC, Judd SE, Lackland D, Lichtman JH, Lisabeth L, Liu S, Longenecker CT, Mackey RH, Matsushita K, Mozaffarian D, Mussolino ME, Nasir K, Neumar RW, Palaniappan L, Pandey DK, Thiagarajan RR, Reeves MJ, Ritchey M, Rodriguez CJ, Roth GA, Rosamond WD, Sasson C, Towfighi A, Tsao CW, Turner MB, Virani SS, Voeks JH, Willey JZ, Wilkins JT, Wu JH, Alger HM, Wong SS, Muntner P. Heart Disease and Stroke Statistics-2017 Update: A Report From the American Heart Association. Circulation 2017; 135:e146-e603. [PMID: 28122885 PMCID: PMC5408160 DOI: 10.1161/cir.0000000000000485] [Citation(s) in RCA: 6083] [Impact Index Per Article: 869.0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Kahn HS, Bullard KM. Indicators of abdominal size relative to height associated with sex, age, socioeconomic position and ancestry among US adults. PLoS One 2017; 12:e0172245. [PMID: 28248983 PMCID: PMC5332027 DOI: 10.1371/journal.pone.0172245] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Accepted: 02/01/2017] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND/OBJECTIVES The supine sagittal abdominal diameter (SAD) and standing waist circumference (WC) describe abdominal size. The SAD/height ratio (SADHtR) or WC/height ratio (WHtR) may better identify cardiometabolic disorders than BMI (weight/height2), but population-based distributions of SADHtR and WHtR are not widely available. Abdominal adiposity may differ by sociodemographic characteristics. SUBJECTS/METHODS Anthropometry, including SAD by sliding-beam caliper, was performed on 9894 non-pregnant adults ≥20 years in the US National Health and Nutrition Examination Surveys of 2011-2014. Applying survey design factors and sampling weights, we estimated nationally representative SADHtR and WHtR distributions by sex, age, educational attainment, and four ancestral groups. RESULTS The median (10th percentile, 90th percentile) for men's SADHtR was 0.130 (0.103, 0.165) and WHtR 0.569 (0.467, 0.690). For women, median SADHtR was 0.132 (0.102, 0.175) and WHtR 0.586 (0.473, 0.738). Medians for SADHtR and WHtR increased steadily through age 79. The median BMI, however, reached maximum values at ages 40-49 (men) or 60-69 (women) and then declined. Low educational attainment, adjusted for age and ancestry, was associated with elevated SADHtR more strongly than elevated BMI. While non-Hispanic Asians had substantially lower BMI compared to all other ancestral groups (adjusted for sex, age and education), their relative reductions in SADHtR and WHtR, were less marked. CONCLUSIONS These cross-sectional data are consistent with monotonically increasing abdominal adipose tissue through the years of adulthood but decreasing mass in non-abdominal regions beyond middle age. They suggest also that visceral adipose tissue, estimated by SADHtR, expands differentially in association with low socioeconomic position. Insofar as Asians have lower BMIs than other populations, employing abdominal indicators may attenuate the adiposity differences reported between ancestral groups. Documenting the distribution and sociodemographic features of SADHtR and WHtR supports the clinical and epidemiologic adoption of these adiposity indicators.
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Affiliation(s)
- Henry S. Kahn
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Kai McKeever Bullard
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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Going flat: examining heterogeneity in the soda-obesity relationship by subgroup and place of birth among Asian Americans. Public Health Nutr 2017; 20:1380-1387. [PMID: 28233506 DOI: 10.1017/s1368980017000106] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVE To determine if the association between soda consumption and obesity is uniform among Asian-American population subgroups. DESIGN We conducted multivariate logistic regression analyses on odds of being obese among seven Asian subgroups and by place of birth using data from the 2009 California Health Interview Survey. SETTING An omnibus population-based health survey. SUBJECTS Non-institutionalized adults, aged 18 years or over, residing in California (n 36 271). RESULTS Despite low levels of soda consumption in several Asian-American ethnic groups, soda consumption increased the odds of being obese among Chinese, Koreans and Other Asians but not for Whites. Obesity risk varied across Asian subgroups and by place of birth within these subgroups. CONCLUSIONS More public health efforts addressing soda consumption in Asian-American communities are needed as a strategy for not only preventing chronic diseases but also disparities, considering the varying levels of soda intake across subgroups. Results support the growing body of literature critiquing acculturation theory in immigrant health research by documenting inconsistent findings by place of birth. Future research should take into account the heterogeneity among Asian Americans to advance our understanding of health outcomes and disparities.
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96
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Lerman JB, Parness IA, Shenoy RU. Body Weights in Adults With Congenital Heart Disease and the Obesity Frequency. Am J Cardiol 2017; 119:638-642. [PMID: 27931725 DOI: 10.1016/j.amjcard.2016.10.050] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Revised: 10/17/2016] [Accepted: 10/17/2016] [Indexed: 12/15/2022]
Abstract
Obesity may associate with greater cardiovascular risk in adults with congenital heart disease (ACHD) than in the general population. As ACHD often have exercise limitations, they may be uniquely predisposed to obesity. Nevertheless, obesity prevalence in ACHD, compared with the general population, has not been quantified in a large US cohort. Hence, we sought to determine the prevalence of obesity (30 ≤ body mass index <40) and morbid obesity (body mass index ≥40), in a large cohort of ACHD, compared with matched controls. Retrospective analysis was thus performed on all ACHD seen in an academic system in 2013. CHD severity was classified as simple, complex, or unclassified, using recently published criteria. A control group without CHD was randomly generated matching for age, gender, and race/ethnicity; 1,451 ACHD met inclusion criteria; 59.5% of ACHD were overweight to morbidly obese. Compared with controls, ACHD had similar prevalence of overweight (odds ratio [OR] 1.04, 95% confidence interval [CI] 0.89 to 1.22, p = 0.63) and obesity (OR 0.96, 95% CI 0.81 to 1.15, p = 0.69) but lower prevalence of morbid obesity (OR 0.24, 95% CI 0.16 to 0.34, p <0.001). These relationships were not attenuated by adjustment for CHD severity. In conclusion, ACHD are at equal risk as their matched peers to be overweight and obese. This is the largest study of obesity in US ACHD and the highest reported obesity prevalence in ACHD to date. As obesity is associated with significant cardiovascular risk, our findings indicate a need for improved lifestyle counseling in patients with CHD of all ages.
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97
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Many GM, Kendrick Z, Deschamps CL, Sprouse C, Tosi LL, Devaney JM, Gordish-Dressman H, Barfield W, Hoffman EP, Houmard JA, Pescatello LS, Vogel HJ, Shearer J, Hittel DS. Genetic characterization of physical activity behaviours in university students enrolled in kinesiology degree programs. Appl Physiol Nutr Metab 2016; 42:278-284. [PMID: 28177749 DOI: 10.1139/apnm-2016-0441] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Studies of physical activity behaviours have increasingly shown the importance of heritable factors such as genetic variation. Nonsynonymous polymorphisms of alpha-actinin 3 (ACTN3) and the β-adrenergic receptors 1 and 3 (ADRB1 and ADRB3) have been previously associated with exercise capacity and cardiometabolic health. We thus hypothesized that these polymorphisms are also related to physical activity behaviours in young adults. To test this hypothesis we examined relationships between ACTN3 (R577X), ARDB1 (Arg389Gly), ADRB3 (Trp64Arg), and physical activity behaviours in university students. We stratified for student enrollment in kinesiology degree programs compared with nonmajors as we previously found this to be a predictor of physical activity. We did not identify novel associations between physical activity and ACTN3. However, the minor alleles of ADRB1 and ADRB3 were significantly underrepresented in kinesiology students compared with nonmajors. Furthermore, carriers of the ADRB1 minor allele reported reduced participation in moderate physical activity and increased afternoon fatigue compared with ancestral allele homozygotes. Together, these findings suggest that the heritability of physical activity behaviours in young adults may be linked to nonsynonymous polymorphisms within β-adrenergic receptors.
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Affiliation(s)
- Gina M Many
- a Genetic Medicine, Children's National Medical Center, Washington, DC, USA.,f Departments of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Zachary Kendrick
- a Genetic Medicine, Children's National Medical Center, Washington, DC, USA
| | | | - Courtney Sprouse
- a Genetic Medicine, Children's National Medical Center, Washington, DC, USA
| | - Laura L Tosi
- a Genetic Medicine, Children's National Medical Center, Washington, DC, USA
| | - Joseph M Devaney
- a Genetic Medicine, Children's National Medical Center, Washington, DC, USA
| | | | - Whitney Barfield
- a Genetic Medicine, Children's National Medical Center, Washington, DC, USA
| | - Eric P Hoffman
- a Genetic Medicine, Children's National Medical Center, Washington, DC, USA
| | - Joseph A Houmard
- c Department of Kinesiology, East Carolina University, Greenville, NC, USA
| | | | - Hans J Vogel
- e Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Jane Shearer
- b Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada.,e Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Dustin S Hittel
- e Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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98
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Dong B, Arnold LW, Peng Y, Wang Z. Ethnic differences in cardiometabolic risk among adolescents across the waist–height ratio spectrum: National Health and Nutrition Examination Surveys (NHANES). Int J Cardiol 2016; 222:622-628. [DOI: 10.1016/j.ijcard.2016.07.169] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Accepted: 07/27/2016] [Indexed: 01/19/2023]
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99
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Dong B, Wang Z, Arnold LW, Song Y, Wang HJ, Ma J. Simplifying the screening of abdominal adiposity in Chinese children with waist-to-height ratio. Am J Hum Biol 2016; 28:945-949. [PMID: 27569411 DOI: 10.1002/ajhb.22894] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2016] [Revised: 04/13/2016] [Accepted: 06/11/2016] [Indexed: 11/11/2022] Open
Abstract
OBJECTIVES The current age- and sex-specific waist circumference (WC) reference for defining abdominal adiposity in Chinese children is quite complex. This study aimed to evaluate the optimal waist-to-height ratio (WHtR) thresholds based on the estimated WC references. METHODS A cross-sectional analysis of data from 121,025 Chinese children aged 7-18 years collected in 2010 was performed. Optimal WHtR thresholds were selected by Youden's index using receiver operating characteristic (ROC) curve analysis, with the estimated references of WC in Chinese children used as the gold standard. RESULTS The optimal cut-off values for identifying abdominally overweight and obese children were 0.44 and 0.46, respectively. Across the different sex and age groups, the proposed thresholds revealed high negative predictive values and areas under the ROC curve (≥0.857), and moderate to high sensitivity, specificity, and positive predictive values, ranging from 0.48 to 1.00. CONCLUSIONS The proposed WHtR thresholds reduce the number of cut-off values from 48 to 2, and have a high discriminatory ability to identify abdominal adiposity in Chinese children. Am. J. Hum. Biol. 28:945-949, 2016. © 2016Wiley Periodicals, Inc.
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Affiliation(s)
- Bin Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China.,Centre for Chronic Disease, School of Medicine, The University of Queensland, Herston, Queensland, Australia
| | - Zhiqiang Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China.,Centre for Chronic Disease, School of Medicine, The University of Queensland, Herston, Queensland, Australia
| | - Luke W Arnold
- Centre for Chronic Disease, School of Medicine, The University of Queensland, Herston, Queensland, Australia
| | - Yi Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China
| | - Hai-Jun Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China
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Capers PL, Kinsey AW, Miskell EL, Affuso O. Visual Representation of Body Shape in African-American and European American Women: Clinical Considerations. CLINICAL MEDICINE INSIGHTS. WOMEN'S HEALTH 2016; 9:63-70. [PMID: 27478392 PMCID: PMC4955976 DOI: 10.4137/cmwh.s37587] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Revised: 04/26/2016] [Accepted: 05/03/2016] [Indexed: 01/04/2023]
Abstract
BACKGROUND Body mass index (BMI) has been used widely among clinicians to assess obesity in their patients due to its ease and availability. However, BMI has some diagnostic limitations and other measures related to health risks; in particular, body shape may be of greater relevance to health outcomes. OBJECTIVE The objective of this study was to illustrate the importance of body shape assessments above and beyond BMI and its relationship to health risk among a sample of African-American and European American women. METHODS African-American and European American women aged 19–78 years (n = 552) in Birmingham, Alabama, were recruited and stratified by menopausal status (ie, pre- or postmenopausal). Pictorial body shapes were derived from digital photographs, while body fat distribution defined by android–gynoid ratio (AGR) and body composition were obtained from dual-energy X-ray absorptiometry. RESULTS Images of BMI and age-matched women illustrate variability in fat distribution. Among both menopausal status groups, more than 50% of women had a pear body shape (AGR < 1). An apple body shape was associated with higher odds of having diabetes (unadjusted odds ratio [OR]: 4.1, 95% confidence interval [CI]: 1.9–9.3), hypertension (unadjusted OR: 3.1, 95% CI: 2.0–4.7), and high cholesterol (unadjusted OR: 3.0, 95% CI: 1.8–5.1). CONCLUSION Use of visual cues alongside traditional methods of weight status assessment may help to facilitate weight management conversations between physicians and female patients. However, next steps should include the validation of visual assessments of body shape in women for use by physicians.
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Affiliation(s)
- Patrice L Capers
- Office of Energetics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.; Nutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Amber W Kinsey
- Nutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL, USA.; Department of Nutrition Sciences, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Edrika L Miskell
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Olivia Affuso
- Nutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL, USA.; Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.; Center for Exercise Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
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