The 24-hour day is spent engaging in activities that include light-physical activity (LPA), moderate-vigorous physical activity (MVPA), sedentary time (i.e., sitting/lying/reclining posture with energy expenditure <1.5 METs, while awake), and sleep. These behaviors are mutually exclusive and time spent in one behavior affects the time spent in another. The time among these 24-hour behaviors is also associated with cardiometabolic health outcomes, including adiposity. Assessing specific behavioral contexts and their relationship within the 24-hour day is underdeveloped, this includes recreational sedentary screen time (rSST). rSST is sedentary time with televisions, computers, smartphones, tablets, inactive video games, and its relationship with other 24-hour behaviors is underdeveloped. This dissertation works evaluates the relationship between rSST and 24-hour behaviors, and adiposity in adults. The first study reviewed the existing observational and experimental evidence for rSST and its relationship with 24-hour behaviors by conducting a scoping review. From the 75 experimental and observational studies included, the evidence supported an overall positive association between rSST and non-screen sedentary behavior, an overall negative association between rSST with physical activity, and overall positive and negative associations between rSST with various sleep variables. The second study assessed the daily associations between rSST and 24-hour behaviors and how associations are influenced by age, sex, chronotype, and week- or weekend days. The findings include significant negative associations at between- and within-person levels for rSST with non-screen sedentary time, standing, LPA, MVPA, and sleep that were differentially influenced by age, chronotype, and week- or weekend day. The third study examined reallocating time between rSST and 24-hour behaviors and the associations with adiposity (i.e., body mass index, body fat percentage, and waist circumference). The results showed significant associations of replacing non-screen sedentary time with MVPA for both body fat percentage and waist circumference; and no significant associations between rSST and 24-hour behaviors for body mass index. Overall, this dissertation work provides important insights into the relationships between rSST and 24-hour behaviors and their relation to adiposity. These findings can be used to inform future intervention development targeting multiple behavior changes and improving health outcomes.

This body of research sought to explore relationships between cognitive function and physical activity (PA), sedentary behavior (SB), and sleep, independently and in conjunction, in mid-life to older adults with no known cognitive impairment. Aging is associated with cognitive decline, and lifestyle behaviors such as PA, SB, and sleep, may mitigate this decline. First, a systematic review and meta-analysis was conducted to examine the effect of aerobic PA interventions on memory and executive function in sedentary adults. Second, a longitudinal study was conducted to examine the association between SB and odds of incident cognitive impairment, and SB and cognitive decline in older adults. Last, a cross-sectional study was conducted to examine the joint associations between different levels of sleep with levels of PA, and sleep with levels of sedentary time on memory and executive function. This body of research provided evidence to support the association between aerobic PA and improved cognitive function, SB and incident cognitive impairment and cognitive function declines, and the joint association of sleep and different levels of PA and ST on cognitive function by hypertension status.

No studies have evaluated the impact of tracking resting energy expenditure (REE) and modifiable health behaviors on gestational weight gain (GWG). In this controlled trial, pregnant women aged >18 years (X=29.8±4.9 years) with a gestational age (GA) <17 weeks were randomized to Breezing™ (N=16) or control (N=12) for 13 weeks. The Breezing™ group used a real-time metabolism tracker to obtain REE. Anthropometrics, diet, and sleep data were collected every 2 weeks. Rate of GWG was calculated as weight gain divided by total duration. Early (GA weeks 14-21), late (GA weeks 21-28), and overall (GA week 14-28) changes in macronutrients, sleep, and GWG were calculated. Mediation models were constructed using SPSS PROCESS macro using a bootstrap estimation approach with 10,000 samples. The majority of women were non-Hispanic Caucasian (78.6%). A total of 35.7% (n=10), 35.7% (n=10), and 28.6% (n=8) were normal weight, overweight, and obese, respectively, with 83.3% (n=10) and 87.5% (n=14) of the Control and Breezing™ groups gaining above IOM GWG recommendations. At baseline, macronutrient consumption did not differ. Overall (Breezing™ vs. Control; M diff=-349.08±150.77, 95% CI: -660.26 to -37.90, p=0.029) and late (M diff=-379.90±143.89, 95% CI:-676.87 to -82.93, p=0.014) changes in energy consumption significantly differed between the groups. Overall (M diff=-22.45±11.03, 95% CI: -45.20 to 0.31, p=0.053), late (M diff=-23.16±11.23, 95% CI: -46.33 to 0.01, p=0.05), and early (M diff=20.3±10.19, 95% CI: -0.74 to 41.34, p=0.058) changes in protein differed by group. Nocturnal total sleep time differed by study group (Breezing vs. Control; M diff=-32.75, 95% CI: -68.34 to 2.84, p=0.069). There was a 11.5% increase in total REE throughout the study. Early changes in REE (72±211 kcals) were relatively small while late changes (128±294 kcals) nearly doubled. Interestingly, early changes in REE demonstrated a moderate, positive correlation with rates of GWG later in pregnancy (r=0.528, p=0.052), suggesting that REE assessment early in pregnancy may help predict changes in GWG. Changes in macronutrients did not mediate the relationship between the intervention and GWG, nor did sleep mediate relationships between dietary intake and GWG. Future research evaluating REE and dietary composition throughout pregnancy may provide insight for appropriate GWG recommendations.