scholarly journals Body Composition Indices and Predicted Cardiovascular Disease Risk Profile among Urban Dwellers in Malaysia

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Tin Tin Su ◽  
Mohammadreza Amiri ◽  
Farizah Mohd Hairi ◽  
Nithiah Thangiah ◽  
Maznah Dahlui ◽  
...  

Objectives. This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia.Methods. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index.Results. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females.Conclusions. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions.

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Zonglei Zhou ◽  
Kunpeng Li ◽  
Xianzhi Li ◽  
Rongsheng Luan ◽  
Ruzhen Zhou

Abstract Background Previous reports regarding the predictive power of adiposity indices remain inconsistent, and longitudinal studies on this top are limited. The associations of hyperuricemia risk with changes in obesity status, as well as the joint effects of baseline adiposity indices and body adiposity change on hyperuricemia risk are not fully elucidated. This study aimed to explore the independent and joint associations of baseline adiposity indicators and body adiposity change with hyperuricemia risk among middle-aged and older population in China. Methods A total of 2895 participants aged ≥ 45 years from the baseline survey of the China Health and Retirement Longitudinal Study were followed up for 4 years. Anthropometric parameters (weight, height, and waist circumference) and serum uric acid were obtained using standard devices. Adjusted odds ratio and 95% confidential interval were calculated to estimate the associations between predictor variables and hyperuricemia risk using multivariate logistic regression. Results Of the 2895 participants, 293 (10.12%) cases of hyperuricemia were identified. Increased baseline body mass index (BMI), waist circumference, and waist-height ratio (WHtR) were significantly associated with higher risks of hyperuricemia. A slightly greater but non-significant area under the curve value was observed for waist circumference (0.622) than for BMI (0.611) and WHtR (0.614) (P = 0.447). Compared to subjects with stable adiposity status, participants with weight loss of ≥ 4 kg or waist circumference loss of ≥ 6 cm had a 56% or 55% lower risk of hyperuricemia, and those with weight gain of > 4 kg had a 1.62-fold higher risk of hyperuricemia. Compared to those without obesity, participants with incident or persistent obesity were more likely to develop hyperuricemia. Additionally, regardless of stable or increased weight/waist circumference during follow-up, individuals with obesity at baseline had a higher risk of incident hyperuricemia. Conclusion This study demonstrates that BMI, waist circumference, and WHtR equally predict the development of hyperuricemia, and weight loss and waist circumference reduction are favorable in preventing hyperuricemia.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1422.1-1422
Author(s):  
S. Hannawi ◽  
H. Hannawi ◽  
M. Alamadi ◽  
R. Sultan ◽  
I. Al Salmi

Background:Risk of rheumatoid arthritis (RA) had been reported in overweight obese compared with normal weight people. More, obesity is associated with high prevalence of cardiovascular disease (CVD) risk factors in RA. No previous publications have examined the detailed body composition parameters among RA, or its relation to CVD in RA.Objectives:This study looked at the body composition and the body mass index and correlated it with the subclinical cardiovascular disease as manifested by carotid intima media thickness (cIMT).Methods:During 2019, a cross-sectional study was carried out to recruit cases that met the 2010 American College of Rheumatology/EULAR criteria for diagnosis of RA. All the patients were free of cardiovascular and or cerebrovascular disease. Patients with clinical diagnosis of hypertension, diabetes, renal disease, dyslipidemia, thyroid disorder and pregnant female were excluded. None of the participants is smoker or had history of smoking.cMIT ultrasound (US) measures were obtained using a real-time US scanner equipped with a 7.5 MHz linear probe by a single sonographer. Patients underwent a detailed body composition analysis within the same week of the cIMT measurement. The body composition analysis involved assessing the level of total body water, protein, minerals, body fat mass, intra- and extracellular water, basal metabolic rate, waist hip ratio, visceral fat level, obesity degree, bone mineral content, body cell mass, arm and arm muscle circumference, detailed muscle fat analysis, obesity analysis, segmental lean analysis, weight control parameters, and segmental fat analysis.Results:During 2019, 35 female RA patients were recruited that met the inclusion criteria. The mean (SD) of the age was 52 (10) with a minimum of 20 and maximum of 72 years old. The mean (SD) of cIMT was 0.59 (0.098) mm with a minimum of 0 .38 and maximum of 0.87. The mean (SD) of the BMI was 30.7 (7.0) with a minimum of 20 and maximum of 56.9 Kg/m2. Mean systolic blood pressure was 126 (19) with a minimum of 91 and maximum of 140 mmHg. Also, the mean diastolic blood pressure was mmHg 74 (11) with a minimum of 49 and maximum of 96.The correlation of cIMT with the parameters of the body composition in a linear regression analysis showed a positive linear relationship between cIMT and each of the Body fat mass (kg): P=0.045, CI 0.000-0.004), BMI (p=0.029, CI: 0.001, 0 .009), the target weight (p=0.040, CI: 0.000- 0.001), extracellular water (P=0.033, CI: 0.002, 0.034) and bone mineral content (p=0.031, CI: 0.009, 0.192).The Multiple linear regression analysis showed persistence of the relationship between the cIMT and the age of the participants (p=0.049, CI:0.001-0.007) and the BMI (p=0.031, CI: 0.002- 0.032), with R2of the model was 0.38.Conclusion:To the best of our knowledge, this is the first paper to examine the detailed body composition parameters among RA and found a good correlation with subclinical cardiovascular disease as manifested by cIMT. More research with larger study population is needed to look at the association between body mass index and CVD risk factor in RA.References:[1]Body mass index and the risk of rheumatoid arthritis: a systematic review and dose-response meta-analysis. Qin B, Yang M, Fu H, Ma N, Wei T, Tang Q, Hu Z, Liang Y, Yang Z, Zhong R. Arthritis Res Ther. 2015; 17(1): 86. doi: 10.1186/s13075-015-0601-x[2]Body Mass Index and the Risk of Rheumatoid Arthritis: An Updated Dose-Response Meta-Analysis. Feng X, Xu X, Shi Y, Liu X, Liu H, Hou H, Ji L, Li Y, Wang W, Wang Y, Li D. Biomed Res Int. 2019; 2019: 3579081. doi: 10.1155/2019/3579081Disclosure of Interests:None declared


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