An Overview and Update on Obesity and the Obesity Paradox in Cardiovascular Diseases

doi:10.1016/j.pcad.2018.07.003

Progress in Cardiovascular Diseases

Volume 61, Issue 2, July–August 2018, Pages 142-150

https://doi.org/10.1016/j.pcad.2018.07.003 Get rights and content

Highlights

•
The obesity paradox seems strongest in those who are overweight or mildly (class I) obese.
•
Many unfavorable physiologic and hemodynamic changes associated with obesity are reversible with weight loss.
•
CRF is a better predictor of CVD outcomes and independently reduces mortality, regardless of BMI.
•
"Metabolically healthy" obese patients should be treated as an "at risk" population to prevent development of CVD.

Abstract

Obesity increases a number of cardiovascular disease (CVD) risk factors, but patients with many types of CVD may have a better prognosis if classified as overweight or obese, a phenomenon known as the “obesity paradox”. This paradoxical benefit of a medically unfavorable phenotype is particularly strong in the overweight and class I obesity, and less pronounced in the more severe or morbidly obese populations (class II–III and greater). Rather than an obesity paradox, it is possible that this phenomenon may represent a “lean paradox”, in which individuals classified as normal weight or underweight may have a poorer prognosis with respect to CVD, as a result of a progressive catabolic state and lean mass loss.

Cardiorespiratory fitness (CRF) is a fundamental part of this discussion. A greater CRF is associated with lower CVD risk, regardless of body mass index (BMI). Also, the assessment of body composition compartments (i.e., fat mass, fat-free mass, lean mass) and the presence of metabolic derangements may be better indicators of CVD risk than BMI alone.

The focus of this review is to summarize the current evidence of the obesity paradox. Moreover, we discuss the utility and limitations of BMI for cardiometabolic risk stratification, in addition to concepts such as “metabolically healthy obesity” (MHO) and the “fat but fit” phenomenon, which describe patients who are diagnosed with obesity using BMI, but without major metabolic derangements and with greater CRF, respectively. Finally, we propose that obese patients presenting with an excess body fat, yet without metabolic abnormalities, should still be viewed as an “at risk” population, and as such should receive advice to change their lifestyle to improve their CRF and to prevent the development of impaired fasting glucose, diabetes mellitus and other CVD risk factors as a form of primary prevention.

Introduction

The prevalence of overweight and obesity has reached epidemic proportions in Western countries,¹ and is the second leading cause of preventable death following tobacco use.² Although the etiology of the obesity epidemic has been intensely debated, it is widely accepted that increased body weight and overall adiposity are the result of a chronic positive energy balance, with energy intake exceeding energy expenditure.³ Obesity is a major independent risk factor for cardiovascular (CV) disease (CVD), such as hypertension (HTN), coronary heart disease (CHD), atrial fibrillation (AF) and heart failure (HF).³^,⁴

While obesity increases a number of the established CVD risk factors, it has been shown that many types of CVD may have a better prognosis in the overweight or obese population compared to their leaner counterparts,³ and this phenomenon is referred to as the “obesity paradox”. An obesity paradox is seen in many forms of CVD,⁵ in addition to other diseases, such as end-stage renal disease, human immunodeficiency virus and various pulmonary diseases.⁶^,⁷ Although the obesity paradox has been observed for most CVD, it most likely applies to the overweight and class I obesity, and less for class II and greater (Table 1).⁴

The focus of this review is to evaluate the current evidence regarding the obesity paradox in CVD and to understand its clinical implications. Concepts such as the “fat but fit” phenomenon, “normal weight obesity” (NWO) and “metabolically healthy obesity” (MHO) will also be discussed, as well as the critical importance of physical activity (PA), cardiorespiratory fitness (CRF) and metabolic derangements in the overweight and obese.

Section snippets

Utility of BMI

Overweight and obesity are generally defined by Body mass index (BMI) in clinical practice (Table 1).⁴ The modern definition of BMI comes originally from the Quetelet index in 1832, named after a Belgian astronomer and statistician who used height and weight to assess individuals in the French and Scottish armies.⁸ However, the World Health Organization defines obesity as excess body fat that impairs health, and further suggest that BMI is a rough guide of body composition since individuals

Physiologic impact of overweight/obesity

Increasing adiposity is associated with neurohormonal activation and metabolic abnormalities, including renin-angiotensin-aldosterone system activation, sympathetic system activation, hyperleptinemia and dysregulation of growth factors, such as insulin-like growth factor.² These homeostatic aberrations induce increased sodium retention, vascular reactivity and hyperinsulinemia, and each contribute to the development of HTN in obesity.²² Adipose tissue, while previously viewed as a storage

CVD risk of obesity

Certainly, obesity is associated with worsening physiologic parameters that promote the development and progression of CVD, including dyslipidemia, high blood glucose, low-grade systemic inflammation and the MetS/DM.²^,²⁹ Overweight and obese patients consistently have a higher prevalence of CHD, and the Framingham study showed that 23% of CHD in men and 15% of CHD in women was attributable to excess adiposity.³⁰ Another analysis of patients from the Framingham cohort study with follow-up of up

HF

The Framingham study³² was the largest to assess the risk of HF in obesity; every 1 kg/m² increase in BMI increased the risk of HF by 7% in women and 5% in men. While obesity significantly increases the risk of HF,²⁹ Pandey et al.³³ have demonstrated that the increase in HF with reduced ejection fraction is lower compared to the markedly increased risk for HF with preserved ejection fraction. Furthermore, the risk of HF associated with obesity is independent of other risk factors as well as CRF

CHD

The major effect of obesity on CHD risk is attributable to atherogenic dyslipidemia and MetS/DM.² This is supported by evidence from the INTERHEART study,⁴⁶ which assessed 30,000 patients in 52 countries, finding that over 90% of the risk for acute myocardial infarction (MI) was attributable to nine modifiable risk factors; dyslipidemia being the leading factor, which could account for approximately 50% of the risk of developing acute MI. Despite having relatively normal total low-density

Following revascularization

The prevalence of patients undergoing percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) surgery who are overweight or obese may be as high as 70%.² A review of 26 PCI studies found that underweight patients had the highest rates of all-cause death, CVD death and MI with mean follow-up of approximately 1.7 years compared with normal BMI.⁵¹ In the same study, overweight patients had the lowest risk of these outcomes, with significant reductions in all-cause and CVD

HTN

The Physicians' Health Study demonstrated a strong association between higher BMI and the risk of HTN with approximately 8% increase per 1-unit increase in BMI.⁵³ Interestingly, several studies have demonstrated that patients with HTN who are overweight or obese have a better prognosis than leaner patients with HTN, even in those with less optimal BP control and more LV geometric abnormalities.² Patients with obesity and HTN typically respond favorably to diuretics and calcium channel blockers,

AF

Along with obesity, the prevalence of AF has been increasing and is expected to increase 3.5-fold during the next 30 years.⁵⁹ Obesity is an independent risk factor for AF,⁶⁰ and obese patients have been shown to have a 50% increased risk for developing AF.⁶¹ Another study showed that every 1-unit increase in BMI has been associated with an almost 4% increased risk of AF.⁶² Obesity may also be a risk factor for progression of paroxysmal to persistent AF, which carries higher morbidity and

Lean paradox

Some have argued that the observation of worse clinical outcomes in CVD in those with low BF% and low BMI may be suggestive of a “lean paradox” even more so than an obesity paradox.³^,⁶⁵^,⁶⁶ Low BF% and low BMI are independent predictors of worse outcomes, and those with both have demonstrated increased mortality rates.¹⁴

Unintentional weight loss carries an extremely high burden of morbidity and mortality for most medical conditions, especially for HF.⁴^,⁶⁷ None of the major HF societies recommend

CRF and the “fat but fit” phenomenon

The importance of CRF has often been neglected for CVD risk stratification, despite the fact that it correlates with overall health status and is a potent predictor of an individual's future risk of CVD.⁷² High levels of CRF largely neutralize the adverse effects of excess adiposity and other CVD risk factors, which has led to what is described as the “fat but fit” phenomenon.⁷³^,⁷⁴ Substantial evidence suggests that CRF remains very predictive and largely negates the adverse effects of body

MHO

MHO is generally defined as BMI ≥ 30 kg/m² without HTN, glucose abnormalities or dyslipidemia.⁷ Because there is no official definition for MHO, Ortega et al.⁶⁵ have proposed a definition, in short, BMI ≥ 30 kg/m² and meeting 0 of the MetS criteria (excluding WC). As discussed earlier, obesity is associated with multiple CVD risk factors, and some authors have argued that obesity should never be considered “healthy”. Supporting this notion, a meta-analysis by Kramer et al.⁹³ found that in

Weight loss

Although an obesity paradox exists, it may not apply to more morbid obesity in which prognosis is adversely affected in CHD, cardiac revascularization (both PCI as well as CABG) and HF.¹⁴ While arguments have been made for the “fat but fit” phenomenon, CRF assessment of the morbidly obese may be technically challenging. Many changes in cardiac performance and morphology associated with obesity are reversible with purposeful weight loss,² as purposeful weight loss reduces total and central blood

Confounders

Mechanisms for an obesity paradox are not well understood, and it has been argued that this observation may be due to confounding variables,¹⁸ or biases such as lead time, confounding or publication biases.¹¹⁰ Typically, the overweight/obese patients are significantly younger than patients with normal BMI in most observational cohorts, and this may be an age confounder.⁶⁰ A lead time bias due to earlier detection of CVD in the overweight and obese population (due to higher pretest probability

Conclusion

There is much evidence to suggest that increased PA and CRF may be more important and effective treatment methods rather than weight loss alone for CVD, considering the fallibility of BMI. Although the use of BMI to assess adiposity is flawed, it is a good marker of excess body weight, and seems to be a better marker of CVD risk than more expensive, cumbersome and precise measurements of adiposity, as we recently described.¹⁷

Obesity is associated with multiple unfavorable physiologic and

Statement of Conflicts of Interest

Salvatore Carbone is supported by a Mentored Clinical & Population Research Award 16MCPRP31100003 from the American Heart Association, by the VCU. DOIM Pilot Project Grant Program 2017 and by the VCU Pauley Heart Center Pilot Project Grant Program 2017. All other authors report no conflicts of interest.

References (111)

C.J. Lavie et al.
Obesity and prevalence of cardiovascular diseases and prognosis-the obesity paradox updated
Prog Cardiovasc Dis
(2016)
C.J. Lavie et al.
Update on obesity and obesity paradox in heart failure
Prog Cardiovasc Dis
(2016)
C.J. Lavie
Obesity and prognosis-just one of many cardiovascular paradoxes?
Prog Cardiovasc Dis
(2014)
J. Park et al.
Obesity paradox in end-stage kidney disease patients
Prog Cardiovasc Dis
(2014)
D. Gallagher et al.
Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index
Am J Clin Nutr
(2000)
S. Carbone et al.
Obesity and heart failure: focus on the obesity paradox
Mayo Clin Proc
(2017)
C.J. Lavie et al.
Obesity and cardiovascular diseases: implications regarding fitness, fatness, and severity in the obesity paradox
J Am Coll Cardiol
(2014)
E. Oliveros et al.
The concept of normal weight obesity
Prog Cardiovasc Dis
(2014)
R. See et al.
The association of differing measures of overweight and obesity with prevalent atherosclerosis. The dallas heart study
J Am Coll Cardiol
(2007)
F.B. Ortega et al.
Body mass index, the most widely used but also widely criticized index Would a criterion standard measure of total body fat be a better predictor of cardiovascular disease mortality?
Mayo Clin Proc
(2016)

P. Parto et al.

Obesity and cardiovascular diseases

Curr Probl Cardiol

(2017)

E. Braunwald

Heart failure

JACC Heart Fail

(2013)

C.J. Lavie et al.

Adipose composition and heart failure prognosis: paradox or not?

J Am Coll Cardiol

(2017)

A. Pandey et al.

Relationship between physical activity, body mass index, and risk of heart failure

J Am Coll Cardiol

(2017)

A. Pandey et al.

Body mass index and cardiorespiratory fitness in mid-life and risk of heart failure hospitalization in older age: findings from the cooper center longitudinal study

JACC Heart Fail

(2017)

A. Oreopoulos et al.

Body mass index and mortality in heart failure: a meta-analysis

Am Heart J

(2008)

A. Sharma et al.

Meta-analysis of the relation of body mass index to all-cause and cardiovascular mortality and hospitalization in patients with chronic heart failure

Am J Cardiol

(2015)

A.L. Clark et al.

Waist circumference, body mass index, and survival in systolic heart failure: the obesity paradox revisited

J Card Fail

(2011)

A.L. Clark et al.

The obesity paradox in men versus women with systolic heart failure

Am J Cardiol

(2012)

R. Shah et al.

Body mass index and mortality in acutely decompensated heart failure across the world: A global obesity paradox

J Am Coll Cardiol

(2014)

C.J. Lavie et al.

The obesity paradox in heart failure: is it all about fitness, fat, or sex?

JACC Heart Fail

(2015)

A.R. Vest et al.

The heart failure overweight/obesity survival paradox: the missing sex link

JACC Heart Fail

(2015)

A.L. Clark et al.

Obesity and the obesity paradox in heart failure

Prog Cardiovasc Dis

(2014)

M. Cicoira et al.

Skeletal muscle mass independently predicts peak oxygen consumption and ventilatory response during exercise in noncachectic patients with chronic heart failure

J Am Coll Cardiol

(2001)

S. Yusuf et al.

Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case control study

Lancet

(2004)

A. Romero-Corral et al.

Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies

Lancet

(2006)

C.J. Lavie et al.

An obesity paradox with myocardial infarction in the elderly

Nutrition

(2018)

A. Sharma et al.

Relationship of body mass index with total mortality, cardiovascular mortality, and myocardial infarction after coronary revascularization: evidence from a meta-analysis

Mayo Clin Proc

(2014)

R.P. Gelber et al.

A prospective study of body mass index and the risk of developing hypertension in men

Am J Hypertens

(2007)

S. Uretsky et al.

Obesity paradox in patients with hypertension and coronary artery disease

Am J Med

(2007)

M.A. Agarwal et al.

Relationship between obesity and survival in patients hospitalized for hypertensive emergency

Mayo Clin Proc

(2018)

M. Agarwal et al.

Relation between obesity and survival in patients hospitalized for pulmonary arterial hypertension (from a Nationwide inpatient sample database 2003 to 2011)

Am J Cardiol

(2017)

B. Zafrir et al.

The association between obesity, mortality and filling pressures in pulmonary hypertension patients; the “obesity paradox.”

Respir Med

(2013)

A.D. Poms et al.

Comorbid conditions and outcomes in patients with pulmonary arterial hypertension: a reveal registry analysis

Chest

(2013)

C.J. Lavie et al.

Obesity and cardiovascular disease. Risk factor, paradox, and impact of weight loss

J Am Coll Cardiol

(2009)

C.J. Lavie et al.

Obesity and atrial fibrillation prevalence, pathogenesis, and prognosis: effects of weight loss and exercise

J Am Coll Cardiol

(2017)

N. Wanahita et al.

Atrial fibrillation and obesity-results of a meta-analysis

Am Heart J

(2008)

A. Pandey et al.

Association of body mass index with care and outcomes in patients with atrial fibrillation: results from the ORBIT-AF registry

JACC Clin Electrophysiol

(2016)

C.J. Lavie et al.

Body composition and coronary heart disease mortality—an obesity or a lean paradox?

Mayo Clin Proc

(2011)

T. Bekfani et al.

Sarcopenia in patients with heart failure with preserved ejection fraction: impact on muscle strength, exercise capacity and quality of life

Int J Cardiol

(2016)

K. Kamiya et al.

Complementary role of arm circumference to body mass index in risk stratification in heart failure

JACC Heart Fail

(2016)

C.J. Lavie et al.

Bulking up skeletal muscle to improve heart failure prognosis

JACC Heart Fail

(2016)

A.A. Oktay et al.

The interaction of cardiorespiratory fitness with obesity and the obesity paradox in cardiovascular disease

Prog Cardiovasc Dis

(2017)

V.W. Barry et al.

Fitness vs. fatness on all-cause mortality: a meta-analysis

Prog Cardiovasc Dis

(2014)

P.A. McAuley et al.

The obesity paradox, cardiorespiratory fitness, and coronary heart disease

Mayo Clin Proc

(2012)

P.A. McAuley et al.

Contribution of cardiorespiratory fitness to the obesity paradox

Prog Cardiovasc Dis

(2014)

P.A. McAuley et al.

Exercise capacity and the obesity paradox in heart failure: the FIT (Henry Ford exercise testing) project

Mayo Clin Proc

(2018)

T. Moholdt et al.

Sustained physical activity, not weight loss, associated with improved survival in coronary heart disease

J Am Coll Cardiol

(2018)

R.K. Pathak et al.

Impact of CARDIOrespiratory FITness on arrhythmia recurrence in obese individuals with atrial fibrillation the CARDIO-FIT study

J Am Coll Cardiol

(2015)

S. Uretsky et al.

The interaction of exercise ability and body mass index upon long-term outcomes among patients undergoing stress-rest perfusion single-photon emission computed tomography imaging

Am Heart J

(2013)

Cited by (467)

Examining the scale effect of nearby residential green space on residents’ BMI: A case study of Guangzhou, China
2024, Urban Forestry and Urban Greening
Green spaces are closely related to the quality of the urban environment and public health. However, studies have rarely paid attention to nearby residential green space which is more closely connected to residents’ daily lives. Does nearby residential green space have a scale effect on the body mass index (BMI) of residents? What type of green space has a more significant effect? Does this effect differ for residents living in central urban areas and suburban areas? To answer these questions, this study first measured three scales of nearby residential green space accessibility of 1398 samples of 18 neighborhoods’ survey data in Guangzhou, China, combined with the application of the TIQS (Travel O-D point Intelligent Query System). And then, multilevel mixed-effects models were developed to examine the scale effect of nearby residential green space accessibility on residents’ BMI. The results show that nearby residential green space has a scale effect on individual BMI and the effect of the 10-minute walking scale is the most significant. Within a 10-minute walking distance from the residence, the larger the green space and the more accessible it is, the lower the individual’s BMI. Parks are the green spaces that are most correlated to residents’ BMI, but their effect is somewhat different between the central urban areas and suburban areas. These findings give us a better understanding of the association between nearby residential green space and public health, as well as providing implications for the improvement of the urban green space system and policy development for healthy cities.
Visceral adiposity associated with incidence and development trajectory of cardiometabolic diseases: A prospective cohort study
2024, Nutrition, Metabolism and Cardiovascular Diseases
There is a lack of literature concerning the effects of visceral adipose on the development of first cardiometabolic disease (FCMD) and its subsequent progression to cardiometabolic multimorbidity (CMM) and mortality.
423,934 participants from the UK Biobank with different baseline disease conditions were included in the analysis. CMM was defined as the simultaneous presence of coronary heart disease, T2D, and stroke. Visceral adiposity was estimated by calculating the visceral adiposity index (VAI). Multistate models were used to assess the effect of visceral adiposity on the development of CMM. During a median follow-up of 13.5 years, 50,589 patients had at least one CMD, 6131 were diagnosed with CMM, whereas 24,634 patients died. We observed distinct roles of VAI with respect to different disease transitions of CMM. HRs (95 % CIs) of high VAI were 2.35 (2.29–2.42) and 1.64 (1.50–1.79) for transitions from healthy to FCMD and from FCMD to CMM, and 0.97 (0.93–1.02) for all-cause mortality risk from healthy, FCMD and CMM, respectively.
Our study provides the first evidence that visceral adipose may contribute to the development of FCMD and CMM in healthy participants. However, visceral adipose may confer resistance to all-cause mortality in participants with existing CMD or CMM. A better understanding of the relationship between visceral adipose and CMM can focalize further investigations on patients with CMD with high levels of visceral fat and help take targeted preventive measures to reduce the medical burden on individual patients and society.
The influence of serum selenium in differential epigenetic and transcriptional regulation of CPT1B gene in women with obesity
2024, Journal of Trace Elements in Medicine and Biology
The increasing prevalence of obesity has become a major health problem worldwide. The causes of obesity are multifactorial and could be influenced by dietary patterns and genetic factors. Obesity has been associated with a decrease in micronutrient intake and consequently decreased blood concentrations. Selenium is an essential micronutrient for human health, and its metabolism could be affected by obesity, especially severe obesity. This study aimed to identify differential methylation genes associated with serum selenium concentration in women with and without obesity.
Thirty-four patients were enrolled in the study and divided into two groups: Obese (Ob) n = 20 and Non-Obese (NOb) n = 14, according to the Body Mass Index (BMI). Anthropometry, body composition, serum selenium, selenium intake, and biochemical parameters were evaluated. DNA extraction and bisulfite conversion were performed to hybridize the samples on the 450k Methylation Chip Infinium Beadchip (Illumina). Bioinformatics analysis was performed using the R program and the Champ package. The differentially methylated regions (DMRs) were identified using the Bumphunter method. In addition, logarithmic conversion was performed for the analysis of serum selenium and methylation.
In the Ob group, the body weight, BMI, fat mass, and free fat mass were higher than in the NOb group, as expected. Interestingly, the serum selenium was lower in the Ob than in the NOb group without differences in selenium intake. One DMR corresponding to the CPT1B gene, involved in lipid oxidation, was related to selenium levels. This region was hypermethylated in the Ob group, indicating that the intersection between selenium deficiency and hypermethylation could influence the expression of the CPT1B gene. The transcriptional analysis confirmed the lower expression of the CPT1B gene in the Ob group.
Studies connecting epigenetics to environmental factors could offer insights into the mechanisms involving the expression of genes related to obesity and its comorbidities. Here we demonstrated that the mineral selenium might play an essential role in lipid oxidation via epigenetic and transcriptional regulation of the CPT1B gene in obesity.
Machine learning-based prognostication of mortality in stroke patients
2024, Heliyon
Predicting stroke mortality is crucial for personalized care. This study aims to design and evaluate a machine learning model to predict one-year mortality after a stroke.
Data from the National Multiethnic Stroke Registry was utilized. Eight machine learning (ML) models were trained and evaluated using various metrics. SHapley Additive exPlanations (SHAP) analysis was used to identify the influential predictors.
The final analysis included 9840 patients diagnosed with stroke were included in the study. The XGBoost algorithm exhibited optimal performance with high accuracy (94.5%) and AUC (87.3%). Core predictors encompassed National Institutes of Health Stroke Scale (NIHSS) at admission, age, hospital length of stay, mode of arrival, heart rate, and blood pressure. Increased NIHSS, age, and longer stay correlated with higher mortality. Ambulance arrival and lower diastolic blood pressure and lower body mass index predicted poorer outcomes.
This model's predictive capacity emphasizes the significance of NIHSS, age, hospital stay, arrival mode, heart rate, blood pressure, and BMI in stroke mortality prediction. Specific findings suggest avenues for data quality enhancement, registry expansion, and real-world validation. The study underscores machine learning's potential for early mortality prediction, improving risk assessment, and personalized care. The potential transformation of care delivery through robust ML predictive tools for Stroke outcomes could revolutionize patient care, allowing for personalized plans and improved preventive strategies for stroke patients. However, it is imperative to conduct prospective validation to evaluate its practical clinical effectiveness and ensure its successful adoption across various healthcare environments.
Steatotic liver disease predicts cardiovascular disease and advanced liver fibrosis: A community-dwelling cohort study with 20-year follow-up
2024, Metabolism: Clinical and Experimental
Steatotic liver disease (SLD) has emerged as new nomenclature to increase awareness and reflect the pathophysiology of the disease better. We investigated the risk of advanced fibrosis and cardiovascular disease (CVD) in SLD using data derived from a Korean prospective cohort.
We defined SLD using the fatty liver index (FLI) and identified advanced fibrosis with the age-adjusted Fibrosis-4 Index. SLD was further subcategorized into metabolic dysfunction-associated SLD (MASLD), MASLD with increased alcohol intake (MetALD), and alcohol-associated liver disease (ALD).
The Ansung–Ansan cohort of the Korean Genome and Epidemiology study, following 9497 participants from 2002 to 2020, included 3642 (38.3%) with MASLD, 424 (4.5%) with MetALD, and 207 (2.1%) with ALD. During the median follow-up of 17.5 years, CVD risk was higher in those with MASLD (hazard ratio [HR], 1.27; 95% confidence interval [CI], 1.12–1.45; P < 0.001), MetALD (HR, 1.88; 95% CI, 1.33–2.65; P < 0.001), and ALD (HR, 1.95; 95% CI, 1.01–3.77; P < 0.001) than in those without SLD, after adjusting for conventional risk factors. Notably, CVD risk was higher in the MetALD than in the MASLD group (P = 0.027). In the MASLD group, the number of cardiometabolic risk factors (CMRFs) correlated positively with CVD risk (HR, 1.34; 95% CI, 1.24–1.45; P < 0.001 for trend). Among the CMRFs, hypertension (HR, 1.94; 95% CI, 1.63–2.31; P < 0.001) was the predominant contributor to CVD. The MASLD (HR, 1.39; 95% CI, 1.25–1.55; P < 0.001), MetALD (HR, 1.75; 95% CI, 1.38–2.23; P < 0.001), and ALD (HR, 2.00; 95% CI, 1.30–3.07; P = 0.002) groups had a higher risk of advanced fibrosis than did the non-SLD group (P < 0.001 for trend).
Our study provides new insight into hepatic and cardiovascular outcomes related to SLD subtypes. The risk of CVD increased in the order of no SLD, MASLD, and MetALD. The SLD subcategories, considering CMRFs and alcohol intake, outperformed traditional fatty liver categorizations in predicting CVD risk. The proposed SLD terminology could impact clinical practice, warranting further exploration of the heterogeneity of clinical outcomes among SLD subtypes.
Impact of Serum Albumin Levels and Body Mass Index on Outcomes of Open Abdominal Aortic Aneurysm Repair in Korean Population
2024, Annals of Vascular Surgery
Although obese patients seem to be susceptible to chronic diseases, obesity paradox has been observed in the field of vascular surgery, in which many previous studies have reported that overweight patients have good postoperative outcomes and underweight patients have poor postoperative outcomes. The purpose of our study is to evaluate the impact of body mass index (BMI) and serum albumin levels, which are evaluated as indicators of nutritional status, on outcomes of open abdominal aortic aneurysm (AAA) repair.
We reviewed the vascular surgery database of a single tertiary referral center for all patients who underwent open AAA repair due to degenerative etiology from 1996 to 2021. To analyze the effect of BMI, patients were classified into 4 groups according to the Asian-Pacific classification of BMI: underweight (UW) (<18.5 kg/m²), normal weight (NW) (18.5–22.9 kg/m²), overweight (OW) (23–24.9 kg/m²), and obese (OB) (≥25 kg/m²). The χ², Fisher's exact, and Kruskal-Wallis tests were used to compare demographics, comorbidities, radiologic findings, surgical details, and 1-year mortality rates between the 4 groups. We also compared the preoperative serum albumin levels of each group to assess nutritional status indirectly. Cox's proportional hazards model was performed to determine factors associated with mortality. A Kaplan-Meier survival analysis was performed, and the differences were analyzed by a log-rank test. We did not perform an analysis for 30-day mortality because cases of 30-day mortality in UW patients were rare due to the unbalanced distribution of the number of patients in the 4 groups.
Among a total of 678 patients, 22 were classified as UW (3.2%), 200 as NW (29.5%), 183 as OW (27.1%), and 273 as OB (40.1%). The median age was 70 (64–75) years and 577 of 678 (85.1%) patients were male gender. Higher serum albumin level was associated with decreased 1-year mortality (hazard ratio [HR], 0.3; 95% confidence interval [CI], 0.15–0.63; P = 0.001). UW patients had a higher 1-year mortality rate than NW patients (HR, 3.67; 95% CI, 1.02–13.18; P = 0.046). OB patients had a lower overall mortality rate than NW patients (HR, 0.73; 95% CI, 0.53–1; P = 0.05).
Low BMI (<18.5 kg/m²) and low serum albumin level were associated with poor 1-year survival after elective open AAA repair. These patients also need more careful preoperative intervention, like weight gain or nutritional support, for better outcomes. The obesity paradox existed in our study; high BMI (≥25 kg/m²) was associated with better overall survival after elective open AAA repair.

View all citing articles on Scopus

^☆: Statement of Conflict of Interest: see page 148.

View full text

An Overview and Update on Obesity and the Obesity Paradox in Cardiovascular Diseases☆

Highlights

Abstract

Introduction

Section snippets

Utility of BMI

Physiologic impact of overweight/obesity

CVD risk of obesity

HF

CHD

Following revascularization

HTN

AF

Lean paradox

CRF and the “fat but fit” phenomenon

MHO

Weight loss

Confounders

Conclusion

Statement of Conflicts of Interest

Prog Cardiovasc Dis

Prog Cardiovasc Dis

Prog Cardiovasc Dis

Prog Cardiovasc Dis

Am J Clin Nutr

Mayo Clin Proc

J Am Coll Cardiol

Prog Cardiovasc Dis

J Am Coll Cardiol

Mayo Clin Proc

Curr Probl Cardiol

JACC Heart Fail

J Am Coll Cardiol

J Am Coll Cardiol

JACC Heart Fail

Am Heart J

Am J Cardiol

J Card Fail

Am J Cardiol

J Am Coll Cardiol

JACC Heart Fail

JACC Heart Fail

Prog Cardiovasc Dis

J Am Coll Cardiol

Lancet

Lancet

Nutrition

Mayo Clin Proc

Am J Hypertens

Am J Med

Mayo Clin Proc

Am J Cardiol

Respir Med

Chest

J Am Coll Cardiol

J Am Coll Cardiol

Am Heart J

JACC Clin Electrophysiol

Mayo Clin Proc

Int J Cardiol

JACC Heart Fail

JACC Heart Fail

Prog Cardiovasc Dis

Prog Cardiovasc Dis

Mayo Clin Proc

Prog Cardiovasc Dis

Mayo Clin Proc

J Am Coll Cardiol

J Am Coll Cardiol

Am Heart J