Circadian misalignment, as occurs in shiftwork, is associated with numerous negative health outcomes. Here, we sought to improve data labeling accuracy from wearable technology using a novel data pre-processing algorithm in 27 police trainees during shiftwork. Secondarily, we explored changes in four metabolic salivary biomarkers of circadian rhythm during shiftwork. Using a two-group observational study design, participants completed in-class training during dayshift for 6 weeks followed by either dayshift or nightshift field-training for 6 weeks. Using our novel algorithm, we imputed labels of circadian misaligned sleep episodes that occurred during daytime, which were previously were mislabeled as non-sleep by Garmin, supported by algorithm performance analysis. We next assessed changes to resting heart rate and sleep regularity index during dayshift versus nightshift field-training. We also examined changes in field-based assessments of salivary cortisol, uric acid, testosterone, and melatonin during dayshift versus nightshift. Compared to dayshift, nightshift workers experienced larger changes to resting heart rate, sleep regularity index (indicating reduced sleep regularity), and alterations in sleep/wake activity patterns accompanied by blunted salivary cortisol. Salivary uric acid and testosterone did not change. These findings show wearable technology combined with specialized data pre-processing can be used to monitor changes in behavioral patterns during shiftwork.
Patients with rheumatoid arthritis (RA) remain at an increased risk for cardiovascular disease (CVD) and mortality. RA CVD results from a combination of traditional risk factors and RA‐related systemic inflammation. One hypothetical means of improving overall RA CVD risk is through reduction of excess body weight and increased physical activity. Together, weight loss and physical activity can improve traditional cardiometabolic health through fat mass loss, while also improving skeletal muscle health. Additionally, disease‐related CVD risk may improve as both fat mass loss and exercise reduce systemic inflammation. To explore this hypothesis, 26 older persons with RA and overweight/obesity will be randomized to 16 weeks of a usual care control arm or to a remotely Supervised Weight Loss Plus Exercise Training (SWET) program. A caloric restriction diet (targeting 7% weight loss) will occur via a dietitian‐led intervention, with weekly weigh‐ins and group support sessions. Exercise training will consist of both aerobic training (150 minutes/week moderate‐to‐vigorous exercise) and resistance training (twice weekly). The SWET remote program will be delivered via a combination of video conference, the study YouTube channel, and study mobile applications. The primary cardiometabolic outcome is the metabolic syndrome Z score, calculated from blood pressure, waist circumference, high‐density lipoprotein cholesterol, triglycerides, and glucose. RA‐specific CVD risk will be assessed with measures of systemic inflammation, disease activity, patient‐reported outcomes, and immune cell function. The SWET‐RA trial will be the first to assess whether a remotely supervised, combined lifestyle intervention improves cardiometabolic health in an at‐risk population of older individuals with RA and overweight/obesity.
Night shift work, characterized by behavioral circadian disruption, increases cardiometabolic disease risk. Our long-term goal is to develop a novel methodology to quantify behavioral circadian disruption in field-based settings and to explore relations to four metabolic salivary biomarkers of circadian rhythm. This pilot study enrolled 36 police academy trainees to test the feasibility of using wearable activity trackers to assess changes in behavioral patterns. Using a two-group observational study design, participants completed in-class training during dayshift for six weeks followed by either dayshift or nightshift field-training for six weeks. We developed a novel data-post processing step that improves sleep detection accuracy of sleep episodes that occur during daytime. We next assessed changes to resting heart rate (RHR) and sleep regularity index (SRI) during dayshift versus nightshift field training. Secondarily, we examined changes in field-based assessments of salivary cortisol, uric acid, testosterone, and melatonin during dayshift versus nightshift. Compared to dayshift, nightshift workers experienced larger changes to resting heart rate, sleep regularity index (indicating reduced sleep regularity), and alternations to sleep/wake activity patterns accompanied by blunted salivary cortisol. Salivary uric acid, testosterone, and melatonin did not change. These findings show that nightshift work-a form of behavioral circadian rhythm disruption-was detectable in police trainees using activity trackers alone and in combination with a specialized data analysis methodology.
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