Impact of Normal Weight Central Obesity on Clinical Outcomes in Male Patients With Premature Acute Coronary Syndrome

Abstract

There is a lack of studies that evaluate the association between normal weight central obesity and subsequent outcomes in patients with premature acute coronary syndrome (ACS). We evaluated 338 consecutive male patients (aged ≤ 55 years) with premature ACS. The primary outcomes were all-cause mortality and major adverse cardiac and cerebrovascular events (MACCE). We compared the hazard ratios (HRs) in patients with and without normal weight central obesity using multivariable Cox proportional hazard models. All-cause mortality (16.8%) of patients with normal weight central obesity was much higher than those (7.1%) without normal weight central obesity ( P = .008). The incidence of MACCE in patients with and without normal weight central obesity were 40.7 and 23.6% ( P = .001), respectively. After multivariable adjustment, the risks of all-cause mortality and MACCE were significantly higher in patients with normal weight central obesity than those without normal weight central obesity (adjusted HR: 1.83; 95% confidence interval [CI]: 1.04-3.31; P = .004 and adjusted HR: 1.62; 95% CI: 1.18-2.27; P = .017, respectively). In conclusion, the risks of all-cause mortality and MACCE were significantly higher in male patients with premature ACS with normal weight central obesity than in those without normal weight central obesity.

Trajectories of Waist-to-Hip Ratio and Adverse Outcomes in Heart Failure with Mid-Range Ejection Fraction

“…In particular, we found that subjects who maintained a "heavy" trajectory had the highest mortality, whereas those who remained on a "lean" trajectory had the lowest risk of death. Previous studies have demonstrated that a higher WHR trajectory pattern was one of the predictors of all-cause mortality [13,19]. In a prospective cohort from Scotland, a higher WHR predicted a higher all-cause mortality risk in female patients with HF [13]; however, the authors did not adopt a trajectory modeling approach to minimize reverse causation.…”

“…Several possible explanations have been proposed. First, patients with HFmrEF frequently suffer from multiple comorbidities, including hypertension, diabetes, obesity, coronary artery disease, and metabolic syndrome [13,19,37]. On account of these coexisting conditions, clinical trials have emphasized that an increase in WHR was a major contributor to a systemic proinflammatory state, which is involved in myocardial fibrosis, hypertrophy, and pathological remodeling, ultimately promoting left ventricular dysfunction [13,38].…”

“…The detailed medical histories and relevant baseline clinical assessments (including baseline demographics and laboratory results) of each patient were recorded. All monthly assessments of waist and hip circumference were performed thrice by trained medical technologists in accordance with a standardized protocol described elsewhere [13,19], and the average result was recorded. Waist circumference divided by hip circumference defined the WHR [13,20].…”

“…Waist circumference divided by hip circumference defined the WHR [13,20]. A high WHR was ≥0.90 for men and ≥0.85 for women [13,19,20]. We evaluated the body composition parameters yearly, using an automated body composition scan (Karada Scan HBF-701; Omron, Tokyo, Japan).…”

Ethnicity and the Evaluation of Anthropometric Measurements

“…When we interpret the baseline characteristics using standard deviations (Table 1 in the paper by Wan et al 1 ), it seems that there is an issue with selection of the study population. For example, the normal BMI with low WHR group had some participants older than 55 years.…”