Glycemic variability is a more sensitive assessment of glycemic health as opposed to traditional clinical measurements. It considers all blood glucose concentrations over a given period to better account for glucose oscillations that occur and provides clinicians with insight into how individuals regulate and/or maintain their glycemic health. The advancement of continuous glucose monitoring (CGM) allows for the measurement of free-living glucose concentrations while providing a more reliable assessment of treatment of dysregulated glycemic. CGM coupled with management of lifestyle behavioral factors, such as reduced sedentary behavior and increased physical activity and regular exercise, potentially offers a previously untapped method for promoting improved glycemic health through greater regulation of glucose concentrations. The aim of this review is to critically evaluate the evidence regarding the measurement of glycemic variability and summarize the current understanding of the relationship between glycemic variability, sedentary behavior, physical activity, the influence of a single exercise session or repeated exercise sessions, and exercise training. This review considers information pertaining to the strengths and limitations for measuring glycemic variability and provides insight into future study designs aimed at evaluating the relationship between sedentary behavior and physical activity with, as well as the influence of exercise on, glycemic variability as a primary outcome.

Understanding women’s perceptions of eating behaviors and dietary patterns can inform the ‘teachable moment’ model of pregnancy. Our objectives were to describe eating behaviors and dietary patterns in pregnancy. This was a cross-sectional, national electronic survey. Women were ≥18 years of age, living in the United States, currently pregnant or less than two years postpartum, and had internet access. Age, education, race, and marriage were included as covariates in ordinal and binary logistic regressions (significance p < 0.05). Women (n = 587 eligible) made positive or negative changes to their diets, while others maintained pre-existing eating behaviors. The majority of women did not try (84.9 to 95.1% across diets) and were unwilling to try (66.6 to 81%) specific dietary patterns during pregnancy. Concerns included not eating a balanced diet (60.1 to 65.9%), difficulty in implementation without family (63.2 to 64.8%), and expense (58.7 to 60.1%). Helpful strategies included being provided all meals and snacks (88.1 to 90.6%) and periodic consultations with a dietitian or nutritionist (85 to 86.7%). Responses differed across subgroups of parity, body mass index, and trimester, notably in women with obesity who reported healthier changes to their diet (p < 0.05). Our study underscores the importance of tailoring care early to individual needs, characteristics, and circumstances.

Physical activity during pregnancy is an important health behavior. However, many pregnant individuals are provided with little-to-no guidance to adequately engage in physical activity. The purpose of this quantitative and quasi-qualitative study of currently or previously pregnant women was to examine physical activity behaviors in pregnancy and understand barriers and facilitators to achieving physical activity recommendations. Overall, 431 women (18+ years), White/Caucasian (84.5%), married (84.9%), and currently pregnant (66.6%), completed an online survey study. Most women (69.4%) reported engaging in cardio-based physical activity and willing to engage in physical activity to meet guidelines between 2 and 5 days per week (77.4 –88.8%). The most frequently reported barriers were feeling too tired (72.8%) or uncomfortable (71.8%) and childcare needs (57.8%). Being able to choose time of day (96.0%), accessing home workouts (92.9%), and having a personalized prescription (95.6%) were the most reported facilitators. Open comment feedback resulted in additional barriers, such as ensuring proper energy intake, while motivation and support from other pregnant individuals were fundamental facilitators. Individualized physical activity prescription is lacking in routine prenatal care. To support pregnant individuals to achieve physical activity recommendations, developing a prescription with suitable modalities, at-home options, and consideration for physical activity timing are required.

Introduction/Purpose Overweight or obese adults spend more time sedentary and less time performing physical activity (PA) and are at an increased risk for developing impaired glycemic health. Free-living environments may provide insight into glycemic health in addition to clinical assessments. The purpose of this study was to examine the relationship between PA and glycemic health assessed by continuous glucose monitoring (CGM). Methods Twenty-eight overweight or obese adults each wore an accelerometer and CGM over the same 7 consecutive days. Average daily time (minutes and metabolic-equivalent minutes (MET-minutes)) and associated energy expenditure performing light (LPA), moderate-to-vigorous (MVPA), total PA, and standard deviation (SD) across days were calculated. Average daily 24-h and waking glycemia, mean glucose concentration, glycemic variability measured as the continuous overlapping net glycemic action, mean amplitude of glycemic excursions, and mean of daily difference were assessed. Results LPA MET-minutes per day was positively associated with 24-h and waking glycemia time-in-range and negatively associated with 24-h and waking time in hyperglycemia. Total PA time and the SD of MVPA and total PA time were negatively associated with 24-h mean glucose concentration. Individual-level analysis identified that most participants (50%–71%) expressed negative associations between LPA and MVPA time with 24-h mean glucose concentration, mean amplitude of glycemic excursion, and 4-h continuous overlapping net glycemic action. Conclusions Expectedly, greater total PA time and intensity-specific PA time were associated with lower 24-h and waking mean glucose concentration, greater glycemia time-in-range, and less time in hyperglycemia. The relationship between glucose concentrations and PA time SD was unexpected, whereas most participants expressed hypothesized relationships, which necessitates further exploration.