Impact of physical activity, diet quality and stress on cardiometabolic health in school employees.

Among school employees, it has been reported that poor physical and mental health, as well as high stress and large workloads, have resulted in high absenteeism and low retention. The consequences of unhealthy behaviors and stress can extend to students, impacting academic achievement and school costs. Our objective was to examine the impact of school employees' physical activity (PA), diet quality and perceived occupational stress on cardiometabolic health, and explore how stress may influence the impact of PA and diet on health. In this cross-sectional study, employees from lower-income Massachusetts schools participated in Wellness Assessments (2015-2016), including measured height, weight, and lipids [total (TC), high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C)]. Self-administered surveys were used to collect demographic, stress, PA and 24-hour food intake data. Linear regression models were used to examine the relationship among health behaviors (PA and diet), stress and cardiometabolic health. An interaction between stress and health behaviors was also explored. Seventy-four employees (66% teachers) participated. Overweight/obesity (mean BMI: 25.6 kg/m2), high TC and LDL-C were observed in 47%, 4%, and 34%, respectively, and moderate-to-vigorous PA (MVPA) was low (median: 17 min/day). Positive associations were identified between MVPA and cardiometabolic health, but not diet. The effect of MVPA on BMI was modified by stress (p-for-interaction = 0.001), with higher levels of stress associated with a diminished protective association between MVPA and BMI. Higher levels of PA were associated with more favorable cardiometabolic health, with increasing levels of stress minimizing the beneficial effect of PA on BMI.

A Qualitative Investigation of Factors that Influence School Employee Health Behaviors: Implications for Wellness Programming.

BACKGROUND: Employee health promotion in the elementary school setting can support students' health and academic success. School employees can serve as role models, yet evidence suggests poor health in this population. We identified factors that influence school employee health behaviors to inform subsequent development of employee wellness programs. METHODS: Focus groups (10 groups, total N = 62) and interviews (N = 5) were conducted with school employees. Participants were recruited from schools in socioeconomically disadvantaged, racially diverse districts in Massachusetts. We used a socioecological framework to identify multi-level factors that influence employee health behaviors. Factors were characterized as supports (+) or barriers (-) to health-promoting behaviors. RESULTS: Eight themes highlighted the importance of an organizational culture that sustains successful employee wellness programming. Intrapersonal themes included: High Stress (+/-), Desire to Adopt Healthy Behaviors (+), and Sufficient Health Knowledge (+). Interpersonal themes included: Strong Social Network (+) and a Desire to Role Model (+). Organizational themes included: Demanding Job (-), Lack of Wellness Culture (-), and Unhealthy Food (-). CONCLUSIONS: Our findings suggest that this population would be receptive to wellness programming. Promising strategies include supporting a dedicated wellness champion and creating recognizable top down wellness support for employees.

Relationship between muscle strength and dyslipidemia, serum 25(OH)D, and weight status among diverse schoolchildren: a cross-sectional analysis.

BACKGROUND: The relationship between muscle strength and cardiometabolic risk factors in youth, and the potential influence of vitamin D status on this relationship, is not well understood. This study examined associations between muscle strength and dyslipidemia, serum 25-hydroxyvitamin D [25(OH)D], and weight status in diverse schoolchildren. METHODS: Measures of hand-grip strength (standardized for sex and body weight), anthropometrics (height and weight converted to BMI z-score [BMIz]), sociodemographics, and fasting blood concentrations of plasma HDL-C and triglycerides and serum 25(OH)D were collected from 350 4th-8th grade schoolchildren (11.2 ± 1.3 y, 49.4% female, 56.3% non-white/Caucasian). Logistic regression was used to measure associations between standardized tertiles of grip strength and blood lipids, 25(OH)D, and weight status along with associations between 25(OH)D and dyslipidemia and weight status. RESULTS: Children with higher grip strength had lower odds of overweight/obesity (OR: 0.03, 95% CI: 0.01-0.06, in the highest tertile of grip strength vs. lowest, p for trend< 0.0001), borderline/low HDL-C (OR: 0.28, 95% CI: 0.16-0.50, p for trend< 0.0001), and borderline/high triglycerides (OR: 0.48, 95% CI: 0.25-0.92, p for trend< 0.05), adjusting for covariates. Associations between blood lipids and grip strength became non-significant after further adjustment for BMIz. No association was observed between grip strength and 25(OH)D, nor between 25(OH)D and borderline/low HDL-C or weight status; however, vitamin D sufficiency was associated with lower odds of borderline/high triglycerides compared with vitamin D deficiency (OR: 0.26, 95% CI: 0.09-0.74, p for trend< 0.05) before BMIz adjustment. CONCLUSION: Among racially/ethnically diverse children, muscle strength was associated with lower dyslipidemia. Longitudinal studies are needed to explore whether changes in muscle strength impact this relationship in children, independent of weight status. TRIAL REGISTRATION: This study was registered at www.clinicaltrials.gov (No. NCT01537809 ) on February 17, 2012.

Predicting metabolic rate across walking speed: one fit for all body sizes?

We formulated a "one-size-fits-all" model that predicts the energy requirements of level human walking from height, weight, and walking speed. Our three-component model theorizes that the energy expended per kilogram per stride is independent of stature at mechanically equivalent walking speeds. We measured steady-state rates of oxygen uptake of 78 subjects who spanned a nearly twofold range of statures (1.07-2.11 m) and sevenfold range of body masses (16-112 kg) at treadmill speeds from 0.4 to 1.9 m/s. We tested the size independence of the model by deriving best-fit equations in the form of the model on four stature groups (n ≥ 15): short, moderately short, moderately tall, and tall. The mean walking metabolic rates predicted by these four independently derived equations for the same set of reference subjects (n = 16; stature range: 1.30-1.90 m) agreed with one another to within an average of 5.2 ± 3.7% at the four intermediate speeds in our protocol. We next evaluated the model's gross predictive accuracy by dividing our 78 subjects into 39 stature-matched pairs of experimental and validation group subjects. The model best-fit equation derived on the experimental group subjects predicted the walking metabolic rates of the validation group subjects to within an average of 8.1 ± 6.7% (R(2) = 0.90; standard error of estimate = 1.34 ml O2·kg(-1)·min(-1)). The predictive error of the American College of Sports Medicine equation (18.0 ± 13.1%), which does not include stature as a predictor, was more than twice as large for the same subject group. We conclude that the energy cost of level human walking can be accurately predicted from height, weight, and walking speed.