Department of Epidemiology, Mailman School of Public Health Columbia University Irving Medical Center New York NY.
College of Health Solutions Arizona State University Tempe AZ.
J Am Heart Assoc. 2021 Sep 21;10(18):e022024. doi: 10.1161/JAHA.121.022024. Epub 2021 Sep 6.
Background Sleep variability and social jetlag are associated with adverse cardiometabolic outcomes via circadian disruption. Variable eating patterns also lead to circadian disruption, but associations with cardiometabolic health are unknown. Methods and Results Women (n=115, mean age: 33±12 years) completed a 1-week food record using the Automated Self-Administered 24-Hour Dietary Assessment Tool at baseline and 1 year. Timing of first and last eating occasions, nightly fasting duration, and %kcal consumed after 5 pm (%kcal 5 pm) and 8 pm (%kcal 8 pm) were estimated. Day-to-day eating variability was assessed from the SD of these variables. Eating jetlag was defined as weekday-weekend differences in these metrics. Multivariable-adjusted linear models examined cross-sectional and longitudinal associations of day-to-day variability and eating jetlag metrics with cardiometabolic risk. Greater jetlag in eating start time, nightly fasting duration, and %kcal 8 pm related to higher body mass index and waist circumference at baseline (<0.05). In longitudinal analyses, a 10% increase in %kcal 8 pm SD predicted increased body mass index (β, 0.52; 95% CI, 0.23-0.81) and waist circumference (β, 1.73; 95% CI, 0.58-2.87); greater %kcal 8 pm weekday-weekend differences predicted higher body mass index (β, 0.25; 95% CI, 0.07-0.43). Every 30-minute increase in nightly fasting duration SD predicted increased diastolic blood pressure (β, 0.95; 95% CI, 0.40-1.50); an equivalent increase in nightly fasting duration weekday-weekend differences predicted higher systolic blood pressure (β, 0.58; 95% CI, 0.11-1.05) and diastolic blood pressure (β, 0.45; 95% CI, 0.10-0.80). Per 10% increase in %kcal 5 pm SD, there were 2.98 mm Hg (95% CI, 0.04-5.92) and 2.37mm Hg (95% CI, 0.19-4.55) increases in systolic blood pressure and diastolic blood pressure; greater %kcal 5 pm weekday-weekend differences predicted increased systolic blood pressure (β, 1.83; 95% CI, 0.30-3.36). For hemoglobin A1c, every 30-minute increase in eating start and end time SD and 10% increase in %kcal 5 pm SD predicted 0.09% (95% CI, 0.03-0.15), 0.06% (95% CI, 0.001-0.12), and 0.23% (95% CI, 0.07-0.39) increases, respectively. Conclusions Variable eating patterns predicted increased blood pressure and adiposity and worse glycemic control. Findings warrant confirmation in population-based cohorts and intervention studies.
睡眠变异性和社会时差与昼夜节律紊乱有关,进而导致不良的心血管代谢结果。进食模式的变化也会导致昼夜节律紊乱,但与心血管代谢健康的关系尚不清楚。
女性(n=115,平均年龄:33±12 岁)在基线和 1 年时使用自动自我管理 24 小时膳食评估工具完成了 1 周的食物记录。首次和最后一次进食时间、夜间禁食持续时间以及晚上 5 点(%kcal5pm)和晚上 8 点(%kcal8pm)后摄入的卡路里百分比(%kcal8pm)的估计值。这些变量的标准差用于评估日间进食变异性。进食时差定义为这些指标的工作日-周末差异。多变量调整线性模型分别检测日间变异性和进食时差指标与心血管代谢风险的横断面和纵向关联。夜间禁食时间和晚上 8 点的进食时间和%kcal 8pm 的时差越大,与基线时的体重指数和腰围越大有关(<0.05)。在纵向分析中,%kcal8pm SD 增加 10%预测体重指数增加(β,0.52;95%CI,0.23-0.81)和腰围增加(β,1.73;95%CI,0.58-2.87);%kcal8pm 工作日-周末差异增加预测体重指数增加(β,0.25;95%CI,0.07-0.43)。夜间禁食时间 SD 每增加 30 分钟,预测舒张压增加(β,0.95;95%CI,0.40-1.50);夜间禁食时间工作日-周末差异增加预测收缩压升高(β,0.58;95%CI,0.11-1.05)和舒张压升高(β,0.45;95%CI,0.10-0.80)。%kcal5pm SD 每增加 10%,收缩压和舒张压分别增加 2.98mmHg(95%CI,0.04-5.92)和 2.37mmHg(95%CI,0.19-4.55);%kcal5pm 工作日-周末差异越大,收缩压越高(β,1.83;95%CI,0.30-3.36)。对于糖化血红蛋白,进食开始和结束时间 SD 每增加 30 分钟和%kcal5pm SD 增加 10%,预测糖化血红蛋白分别增加 0.09%(95%CI,0.03-0.15)、0.06%(95%CI,0.001-0.12)和 0.23%(95%CI,0.07-0.39)。
进食模式的变化可预测血压升高、肥胖和血糖控制恶化。这些发现需要在基于人群的队列和干预研究中进一步证实。