Dataset Information

Predictive value of relative fat mass algorithm for incident hypertension: a 6-year prospective study in Chinese population.

ABSTRACT: OBJECTIVES:Individuals with obesity especially excessive visceral adiposity have high risk for incident hypertension. Recently, a new algorithm named relative fat mass (RFM) was introduced to define obesity. Our aim was to investigate whether it can predict hypertension in Chinese population and to compare its predictive power with traditional indices including body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR). DESIGN:A 6-year prospective study. SETTING:Nine provinces (Hei Long Jiang, Liao Ning, Jiang Su, Shan Dong, He Nan, Hu Bei, Hu Nan, Guang Xi and Gui Zhou) in China. PARTICIPANTS:Those without hypertension in 2009 survey and respond in 2015 survey. INTERVENTION:Logistic regression were performed to investigate the association between RFM and incident hypertension. Receiver operating characteristic (ROC) analysis was performed to compare the predictive ability of these indices and define their optimal cut-off values. MAIN OUTCOME MEASURES:Incident hypertension in 2015. RESULTS:The prevalence of incident hypertension in 2015 based on RFM quartiles were 14.8%, 21.2%, 26.8% and 35.2%, respectively (p for trend <0.001). In overall population, the OR for the highest quartile compared with the lowest quartile for RFM was 2.032 (1.567-2.634) in the fully adjusted model. In ROC analysis, RFM and WHtR had the highest area under the curve (AUC) value in both sexes but did not show statistical significance when compared with AUC value of BMI and WC in men and AUC value of WC in women. The performance of the prediction model based on RFM was comparable to that of BMI, WC or WHtR. CONCLUSIONS:RFM can be a powerful indictor for predicting incident hypertension in Chinese population, but it does not show superiority over BMI, WC and WHtR in predictive power.

SUBMITTER: Yu P

PROVIDER: S-EPMC7569915 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predictive value of relative fat mass algorithm for incident hypertension: a 6-year prospective study in Chinese population.

Yu Peng P Huang Teng T Hu Senlin S Yu Xuefeng X

BMJ open 20201016 10

<h4>Objectives</h4>Individuals with obesity especially excessive visceral adiposity have high risk for incident hypertension. Recently, a new algorithm named relative fat mass (RFM) was introduced to define obesity. Our aim was to investigate whether it can predict hypertension in Chinese population and to compare its predictive power with traditional indices including body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR).<h4>Design</h4>A 6-year prospective study.<h4>S ...[more]

PMID: 33067286

Similar Datasets

Project description:Body-mass index (BMI), waist circumference, and waist-hip ratio are commonly used anthropometric indices of adiposity. However, over the past 10 years, several new anthropometric indices were developed, that more accurately correlated with body fat distribution and total fat mass. They include relative fat mass (RFM), body-roundness index (BRI), weight-adjusted-waist index and body-shape index (BSI). In the current study, we included 8295 adults from the PREVEND (Prevention of Renal and Vascular End-Stage Disease) observational cohort (the Netherlands), and sought to examine associations of novel as well as established adiposity indices with incident heart failure (HF). The mean age of study population was 50 ± 13 years, and approximately 50% (n = 4134) were women. Over a 11 year period, 363 HF events occurred, resulting in an overall incidence rate of 3.88 per 1000 person-years. We found that all indices of adiposity (except BSI) were significantly associated with incident HF in the total population (P < 0.001); these associations were not modified by sex (P interaction > 0.1). Amongst adiposity indices, the strongest association was observed with RFM [hazard ratio (HR) 1.67 per 1 SD increase; 95% confidence interval (CI) 1.37-2.04]. This trend persisted across multiple age groups and BMI categories, and across HF subtypes [HR: 1.76, 95% CI 1.26-2.45 for HF with preserved ejection fraction; HR 1.61, 95% CI 1.25-2.06 for HF with reduced ejection fraction]. We also found that all adiposity indices (except BSI) improved the fit of a clinical HF model; improvements were, however, most evident after adding RFM and BRI (reduction in Akaike information criteria: 24.4 and 26.5 respectively). In conclusion, we report that amongst multiple anthropometric indicators of adiposity, RFM displayed the strongest association with HF risk in Dutch community dwellers. Future studies should examine the value of including RFM in HF risk prediction models.

Project description:ObjectiveThis study aimed to evaluate the value of odors in the olfactory identification (OI) test and other known risk factors for predicting incident dementia in the prospective Shanghai Aging Study.MethodsAt baseline, OI was assessed using the Sniffin' Sticks Screening Test 12, which contains 12 different odors. Cognition assessment and consensus diagnosis were conducted at both baseline and follow-up to identify incident dementia. Four different multivariable logistic regression (MLR) models were used for predicting incident dementia. In the no-odor model, only demographics, lifestyle, and medical history variables were included. In the single-odor model, we further added one single odor to the first model. In the full model, all 12 odors were included. In the stepwise model, the variables were selected using a bidirectional stepwise selection method. The predictive abilities of these models were evaluated by the area under the receiver operating characteristic curve (AUC). The permutation importance method was used to evaluate the relative importance of different odors and other known risk factors.ResultsSeventy-five (8%) incident dementia cases were diagnosed during 4.9 years of follow-up among 947 participants. The full and the stepwise MLR model (AUC = 0.916 and 0.914, respectively) have better predictive abilities compared with those of the no- or single-odor models. The five most important variables are Mini-Mental State Examination (MMSE) score, age, peppermint detection, coronary artery disease, and height in the full model, and MMSE, age, peppermint detection, stroke, and education in the stepwise model. The combination of only the top five variables in the stepwise model (AUC = 0.901 and sensitivity = 0.880) has as a good a predictive ability as other models.ConclusionThe ability to smell peppermint might be one of the useful indicators for predicting dementia. Combining peppermint detection with MMSE, age, education, and history of stroke may have sensitive and robust predictive value for dementia in older adults.

Project description:IntroductionThe interaction between fatness, fitness, and C-reactive protein (CRP) in adolescents is not well characterized but may be important to prevent low grade inflammation. The purpose of this study was to assess the relationship between adiposity, different expressions of fitness, and CRP in late adolescence using direct measures of fitness and fatness.MethodsAnthropometric measurements were taken on 245 eighteen-year-old participants (116 girls). Fasting CRP, glucose, and insulin were measured and homeostatic model assessment (HOMA) calculated. Body composition was estimated via dual energy X-ray absorptiometry. Fitness was assessed with maximal oxygen uptake (VO2max) during a treadmill test and also expressed relative to the fat-free mass (VO2maxFFM).ResultsPrevalence of overweight/obesity based on body mass index (BMI) was 20.7% and 25.6% among girls and boys, respectively (p = 0.407), but 42.5% and 58.1% when based on body fat percentage (%fat, p = 0.015). Higher proportion of boys (81.3%) than girls (54.5%) were highly fit (p<0.001), but the percentage of girls with high levels of CRP was greater (12.1% vs 6.2%, p = 0.028). Adiposity, indicated with BMI, waist circumference, fat mass, android fat mass (aFM), or %fat, was positively associated with CRP independent of VO2max (r = 0.13-0.18, p<0.05) and VO2maxFFM (r = 0.24-0.32, p<0.001). VO2max, was negatively associated with CRP independent only of BMI and waist circumference (r = -0.21, p = 0.001), but not %fat, fat mass or aFM (r = -0.08 to -0.12, p>0.05). VO2maxFFM was unrelated to CRP with (r = -0.07 to -0.11, p>0.05) or without (r = -0.10, p = 0.142) adjustment for adiposity. Additional adjustment for HOMA did not change any of the relationships, although the coefficients were attenuated.ConclusionsFatness has a greater association with CRP than fitness in late adolescence. However, VO2maxFFM, which is truly independent of adiposity, is unrelated to CRP, indicating that the effects of fitness might be mediated via the fatness component embedded in fitness expressed relative to body mass.

Dataset Information

Predictive value of relative fat mass algorithm for incident hypertension: a 6-year prospective study in Chinese population.

Publications

Predictive value of relative fat mass algorithm for incident hypertension: a 6-year prospective study in Chinese population.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure