- 作者列表："Litwin SE","Coles A","Hill CL","Alhanti B","Pagidipati N","Lee KL","Pellikka PA","Mark DB","Udelson JE","Cooper L","Tardif JC","Hoffmann U","Douglas PS","PROMISE investigators.
OBJECTIVES:To test the relationship between increasing severity of obesity, calculated risk and observed outcomes. METHODS:Patients with symptoms suggestive of coronary artery disease (CAD) (n=10 003) were stratified according to body mass index (BMI). We compared risk factors, pooled risk scores and physicians' perception of risk. Cox regression tested the association between BMI and (1) presence of obstructive CAD and (2) composite clinical endpoints (death, cardiovascular death, unstable angina hospitalisation and myocardial infarction). RESULTS:BMI was ≥30 kg/m2 in 48% of patients and ≥35 in 20%. Increasingly obese patients were younger, female and non-smoking but with higher prevalence of hypertension, diabetes, black race and sedentary lifestyle. Pooled risk estimates of CAD were highest in those with mid-range BMI. In contrast, physicians' estimation of the likelihood of significant CAD based on clinical impression increased progressively with BMI. For a 10% increase in the Diamond-Forrester probability of CAD, the adjusted OR for obstructive CAD was 1.5 (95% CI 1.4 to 1.5) in patients with BMI <35, but only 1.2 (95% CI 1.1 to 1.3) in those with BMI ≥35 (interaction p<0.001). Framingham Risk Score increased across increasing BMI categories. However, there was a strong and consistent inverse relationship between degree of obesity and all three composite clinical endpoints over a median 25 months of follow-up. CONCLUSIONS:Despite perceptions of higher risk and higher risk scores, increasingly obese patients had obstructive CAD less frequently than predicted and had fewer adverse clinical outcomes. There is a need for risk assessment tools and guidelines that account for obesity. TRIAL REGISTRATION NUMBER:NCT01174550.
目的: 测试肥胖严重程度增加、计算风险和观察结果之间的关系。 方法: 根据体重指数 (BMI) 对 10 003 例提示冠心病 (CAD) 的患者进行分层。我们比较了风险因素、汇总风险评分和医生的风险感知。Cox 回归分析了 BMI 与 (1) 存在阻塞性 CAD 和 (2) 复合临床终点 (死亡、心血管死亡、不稳定型心绞痛住院和心肌梗死) 之间的相关性。 结果: 30千克的患者 BMI ≥ 48%/m2，20% 的患者 BMI ≥ 35。肥胖患者越来越年轻，女性和不吸烟，但高血压，糖尿病，黑人种族和久坐的生活方式的患病率较高。中度 BMI 者 CAD 的合并风险估计值最高。相比之下，医生根据临床印象对显著 CAD 可能性的估计随着 BMI 的增加而逐渐增加。对于 CAD 的 Diamond-Forrester 概率增加 10%，在 BMI <35 的患者中，阻塞性 CAD 的校正 OR 为 1.5 (95% CI 1.4 ~ 1.5),但 BMI ≥ 35 者仅占 1.2 (95% CI 1.1 ~ 1.3) (相互作用 p<0.001)。Framingham 风险评分在增加的 BMI 类别中增加。然而，在中位 25 个月的随访中，肥胖程度与所有三个复合临床终点之间存在强而一致的反比关系。 结论: 尽管对高风险和高风险评分有看法，但越来越多的肥胖患者发生梗阻性 CAD 的频率低于预测，不良临床结局更少。需要解释肥胖的风险评估工具和指南。 试用注册号: nct01174550。
METHODS:Maintaining adequate daily protein intake is important to maintain muscle mass throughout the lifespan. In this regard, the overnight period has been identified as a window of opportunity to increase protein intake in the elderly. However, it is unknown whether pre-sleep protein intake affects next-morning appetite and, consequently, protein intake. Therefore, the purpose of the current study was to investigate the effects of a pre-sleep protein drink on next-morning appetite, energy intake and metabolism. Twelve older individuals (eight males, four females; age: 71.3 ± 4.2 years) took part in a single-blind randomised cross-over study. After a standardised dinner, participants consumed either a 40-g protein drink, isocaloric maltodextrin drink, or placebo water control before bedtime. Next-morning appetite, energy intake, resting metabolic rate (RMR), respiratory exchange rate (RER), and plasma acylated ghrelin, leptin, glucose, and insulin concentrations were assessed. No between-group differences were observed for appetite and energy intake at breakfast. Furthermore, RMR, RER, and assessed blood markers were not significantly different between any of the treatment groups. Pre-sleep protein intake does not affect next-morning appetite and energy intake and is therefore a viable strategy to increase daily protein intake in an older population.
METHODS:Leptin (LEP) regulates glucose metabolism and energy storage in the body. Osteoarthritis (OA) is associated with the upregulation of serum LEP. LEP promoter methylation is associated with obesity. So far, few studies have explored the association of BMI and OA with LEP methylation. We assessed the interaction between body mass index (BMI) and OA on LEP promoter methylation. Data of 1114 participants comprising 583 men and 558 women, aged 30−70 years were retrieved from the Taiwan Biobank Database (2008−2015). Osteoarthritis was self-reported and cases were those who reported having ever been clinically diagnosed with osteoarthritis. BMI was categorized into underweight, normal weight, overweight, and obesity. The mean LEP promoter methylation level in individuals with osteoarthritis was 0.5509 ± 0.00437 and 0.5375 ± 0.00101 in those without osteoarthritis. The interaction between osteoarthritis and BMI on LEP promoter methylation was significant (p-value = 0.0180). With normal BMI as the reference, the mean LEP promoter methylation level was significantly higher in obese osteoarthritic individuals (β = 0.03696, p-value = 0.0187). However, there was no significant association between BMI and LEP promoter methylation in individuals without osteoarthritis, regardless of BMI. In conclusion, only obesity was significantly associated with LEP promoter methylation (higher levels) specifically in osteoarthritic patients.
METHODS:Background For the same BMI, South Asians have a higher body fat percentage, a higher liver fat content and a more adverse metabolic profile than whites. South Asians may have a lower fat oxidation than whites, which could result in an unfavorable metabolic profile when exposed to increased high-fat foods consumption and decreased physical activity as in current modern lifestyle. Objective To determine substrate partitioning, liver fat accumulation and metabolic profile in South Asian and white men in response to overfeeding with high-fat diet under sedentary conditions in a respiration chamber. Design Ten South Asian men (BMI, 18–29 kg/m^2) and 10 white men (BMI, 22–33 kg/m^2), matched for body fat percentage, aged 20–40 year were included. A weight maintenance diet (30% fat, 55% carbohydrate, and 15% protein) was given for 3 days. Thereafter, a baseline measurement of liver fat content (1H-MRS) and blood parameters was performed. Subsequently, subjects were overfed (150% energy requirement) with a high-fat diet (60% fat, 25% carbohydrate, and 15% protein) over 3 consecutive days while staying in a respiration chamber mimicking a sedentary lifestyle. Energy expenditure and substrate use were measured for 3 × 24-h. Liver fat and blood parameters were measured again after the subjects left the chamber. Results The 24-h fat oxidation as a percentage of total energy expenditure did not differ between ethnicities ( P = 0.30). Overfeeding increased liver fat content ( P = 0.02), but the increase did not differ between ethnicities ( P = 0.64). In South Asians, overfeeding tended to increase LDL-cholesterol ( P = 0.08), tended to decrease glucose clearance ( P = 0.06) and tended to elevate insulin response ( P = 0.07) slightly more than whites. Conclusions Despite a similar substrate partitioning and similar accretion of liver fat, overfeeding with high-fat under sedentary conditions tended to have more adverse effects on the lipid profile and insulin sensitivity in South Asians.