scholarly journals Trajectories of body mass index before the diagnosis of cardiovascular disease: a latent class trajectory analysis

2016 ◽  
Vol 31 (6) ◽  
pp. 583-592 ◽  
Author(s):  
Klodian Dhana ◽  
Joost van Rosmalen ◽  
Dorte Vistisen ◽  
M. Arfan Ikram ◽  
Albert Hofman ◽  
...  
Author(s):  
Laura M. Raffield ◽  
Annie Green Howard ◽  
Misa Graff ◽  
Dan‐Yu Lin ◽  
Susan Cheng ◽  
...  

Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self‐reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60, P <0.0001) and with heart failure (HR 1.41, 95% CI 1.22, 1.63, P <0.0001), stroke (HR 1.53, 95% CI 1.22, 1.92, P =0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63, P =0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90, P <0.0001), despite higher body mass index at baseline. The rapid increase latent class was associated with a higher risk of heart failure versus the stable/slow decline latent class (HR 1.34, 95% CI 1.10, 1.62, P =0.004). Conclusions Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision‐oriented view of CVD risk.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Barbara Iyen ◽  
Stephen Weng ◽  
Yana Vinogradova ◽  
Ralph K. Akyea ◽  
Nadeem Qureshi ◽  
...  

Abstract Background Although obesity is a well-recognised risk factor for cardiovascular disease (CVD), the impact of long-term body mass index (BMI) changes in overweight or obese adults, on the risk of heart failure, CVD and mortality has not been quantified. Methods This population-based cohort study used routine UK primary care electronic health data linked to secondary care and death-registry records. We identified adults who were overweight or obese, free from CVD and who had repeated BMI measures. Using group-based trajectory modelling, we examined the BMI trajectories of these individuals and then determined incidence rates of CVD, heart failure and mortality associated with the different trajectories. Cox-proportional hazards regression determined hazards ratios for incident outcomes. Results 264,230 individuals (mean age 49.5 years (SD 12.7) and mean BMI 33.8 kg/m2 (SD 6.1)) were followed-up for a median duration of 10.9 years. Four BMI trajectories were identified, corresponding at baseline, with World Health Organisation BMI classifications for overweight, class-1, class-2 and class-3 obesity respectively. In all four groups, there was a small, stable upwards trajectory in BMI (mean BMI increase of 1.06 kg/m2 (± 3.8)). Compared with overweight individuals, class-3 obese individuals had hazards ratios (HR) of 3.26 (95% CI 2.98–3.57) for heart failure, HR of 2.72 (2.58–2.87) for all-cause mortality and HR of 3.31 (2.84–3.86) for CVD-related mortality, after adjusting for baseline demographic and cardiovascular risk factors. Conclusion The majority of adults who are overweight or obese retain their degree of overweight or obesity over the long term. Individuals with stable severe obesity experience the worst heart failure, CVD and mortality outcomes. These findings highlight the high cardiovascular toll exacted by continuing failure to tackle obesity.


Author(s):  
Matthias Pierce ◽  
Sally McManus ◽  
Holly Hope ◽  
Matthew Hotopf ◽  
Tamsin Ford ◽  
...  

Stroke ◽  
2005 ◽  
Vol 36 (7) ◽  
pp. 1377-1382 ◽  
Author(s):  
Renzhe Cui ◽  
Hiroyasu Iso ◽  
Hideaki Toyoshima ◽  
Chigusa Date ◽  
Akio Yamamoto ◽  
...  

2019 ◽  
Vol 29 (2) ◽  
pp. 135-143 ◽  
Author(s):  
J. Rodríguez-Carrio ◽  
A. Martínez-Zapico ◽  
I. Cabezas-Rodríguez ◽  
L. Benavente ◽  
Á.I. Pérez-Álvarez ◽  
...  

Author(s):  
Maria J. Iglesias ◽  
Larissa D. Kruse ◽  
Laura Sanchez-Rivera ◽  
Linnea Enge ◽  
Philip Dusart ◽  
...  

Objective: Endothelial cell (EC) dysfunction is a well-established response to cardiovascular disease risk factors, such as smoking and obesity. Risk factor exposure can modify EC signaling and behavior, leading to arterial and venous disease development. Here, we aimed to identify biomarker panels for the assessment of EC dysfunction, which could be useful for risk stratification or to monitor treatment response. Approach and Results: We used affinity proteomics to identify EC proteins circulating in plasma that were associated with cardiovascular disease risk factor exposure. Two hundred sixteen proteins, which we previously predicted to be EC-enriched across vascular beds, were measured in plasma samples (n=1005) from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study) pilot. Thirty-eight of these proteins were associated with body mass index, total cholesterol, low-density lipoprotein, smoking, hypertension, or diabetes. Sex-specific analysis revealed that associations predominantly observed in female- or male-only samples were most frequently with the risk factors body mass index, or total cholesterol and smoking, respectively. We show a relationship between individual cardiovascular disease risk, calculated with the Framingham risk score, and the corresponding biomarker profiles. Conclusions: EC proteins in plasma could reflect vascular health status.


2020 ◽  
Author(s):  
Dipender Gill ◽  
Verena Zuber ◽  
Jesse Dawson ◽  
Jonathan Pearson-Stuttard ◽  
Alice R Carter ◽  
...  

Background: Higher body-mass index (BMI) and waist-to-hip ratio (WHR) increase the risk of cardiovascular disease, but the extent to which this is mediated by blood pressure, diabetes, lipid traits and smoking is not fully understood. Methods: Using consortia and UK Biobank genetic association summary data from 140,595 to 898,130 participants predominantly of European ancestry, MR mediation analysis was performed to investigate the degree to which genetically predicted systolic blood pressure (SBP), diabetes, lipid traits and smoking mediated an effect of genetically predicted BMI and WHR on risk of coronary artery disease (CAD), peripheral artery disease (PAD) and stroke. Results: The 49% (95% confidence interval [CI] 39%-60%) increased risk of CAD conferred per 1-standard deviation increase in genetically predicted BMI attenuated to 34% (95% CI 24%-45%) after adjusting for genetically predicted SBP, to 27% (95% CI 17%-37%) after adjusting for genetically predicted diabetes, to 47% (95% CI 36%-59%) after adjusting for genetically predicted lipids, and to 46% (95% CI 34%-58%) after adjusting for genetically predicted smoking. Adjusting for all the mediators together, the increased risk attenuated to 14% (95% CI 4%-26%). A similar pattern of attenuation was observed when considering genetically predicted WHR as the exposure, and PAD or stroke as the outcomes. Conclusions: Measures to reduce obesity will lower risk of cardiovascular disease primarily by impacting on downstream metabolic risk factors, particularly diabetes and hypertension. Reduction of obesity prevalence alongside control and management of its mediators is likely to be most effective for minimizing the burden of obesity.


2008 ◽  
Vol 47 (1) ◽  
pp. 66-70 ◽  
Author(s):  
Satoshi Funada ◽  
Taichi Shimazu ◽  
Masako Kakizaki ◽  
Shinichi Kuriyama ◽  
Yuki Sato ◽  
...  

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