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Reducing sedentary behavior in the workplace has become an important public health priority; however, some employers have expressed concerns regarding the potential for reduced productivity if employees are not seated while at work. Therefore, the aim of this study was to determine the relationship between workplace sedentary behavior (sitting time) and work productivity among full-time office-based employees, and further to investigate other potential factors associated with productivity. A 19-item online self-report survey was completed by 2068 government employees in Kansas. The survey assessed workplace sedentary behavior, work productivity, job satisfaction, and fatigue. Overall, office workers reported high levels of sedentary time (mean > 78%). The primary results indicated that sitting time was not significantly associated with productivity (β = 0.013, p = 0.519), but job satisfaction and fatigue were positively (β = 0.473, p 91% of the time) reported lower job satisfaction and greater fatigue as compared with the lowest level of sitting time (<75% of the time). Taken together, these results offer promising support that less sitting time is associated with positive outcomes that do not seem to come at the expense of productivity.

Purpose: There is scant published research regarding nutrition and insulin strategies for athletic performance in collegiate distance runners with type 1 diabetes mellitus (CDRT1). Acute carbohydrate supplementation (CHOsup) and insulin reduction used to minimize hypoglycemia during exercise may result in deteriorated glycemic control post exercise in CDRT1. The present case study of a CDRT1 investigated outcomes associated with a moderate-carbohydrate (ModCHO) diet and 24 h insulin adjustment during recovery phases for improved glycemic control and reduced use of acute strategies. Methods: During an 8-day period, a female CDRT1 followed a ModCHO (~4 g/kg/day) nutrition program. Recovery phase adjustments to insulin doses were made using an equation developed to estimate reduced insulin needs post exercise, as a function of exercise intensity and duration. Daily training was performed in the fasted state at 6:00 a.m. and included additional exercise strategies to reduce glycemic variability when needed. Daily blood glucose time-in-range (TIR) and use of CHOsup were assessed. Athlete well-being was determined using the Student-Athlete Well-Being Scale (SAWS)TM at baseline, and days 1, 3, and 7. Results: Throughout the 8-day period, mean TIR increased (77% versus < 50%) and the magnitude of glycemic excursions decreased (~3.8–15 versus ~3.0–26 mmol/L) relative to a prior comparison period. Minimal pre-exercise CHOsup was employed and CHOsup during exercise was not required. Additionally, the athlete achieved a new lifetime best in the 5000 m run and maintained positive well-being. Conclusion: The present case study provides examples of recovery phase strategies (i.e., ModCHO diet and 24 h insulin adjustments) that may support glycemic control and athletic performance in CDRT1 and provides potential considerations for nutrition and insulin strategies for use by athletes and coaches.

Purpose: To evaluate the effectiveness of in-person versus online Girl Scout leader wellness training for implementation of wellness-promoting practices during troop meetings (phase I) and to assess training adoption and current practices across the council (phase II). Design: Pragmatic superiority trial (phase 1) followed by serial cross-sectional study (phase II). Setting: Girl Scout troop meetings in Northeast Kansas. Participants: Eighteen troop leaders from 3 counties (phase 1); 113 troop leaders from 7 counties (phase II). Intervention: Phase I: Troop leaders attended 2 wellness training sessions (first in groups, second individually), wherein leaders set wellness-promoting practice implementation goals, self-monitored progress, and received guidance and resources for implementation. Leaders received the intervention in person or online. Measures: Phase I: At baseline and postintervention, leaders completed a wellness-promoting practice implementation questionnaire assessing practices during troop meetings (max score = 11). Phase II: Leaders completed a survey about typical troop practices and interest in further training. Analysis: Phase I: Generalized linear mixed modeling. Results: Phase I: In-person training increased wellness-promoting practice implementation more than online training (in person = 2.1 ± 1.8; online = 0.2 ± 1.2; P = .022). Phase II: Fifty-six percent of leaders adopted the training. For 8 of 11 wellness categories, greater than 50% of leaders employed wellness-promoting practices. Conclusion: In-person training was superior to online training for improvements in wellness-promoting practices. Wellness training was adopted by the majority of leaders across the council.