ABSTRACT
The aim of the study was to verify relationships between isolated and grouped clinical conditions (Type 2 Diabetes Mellitus [T2DM] and Peripheral Arterial Disease [PAD]) with the skin temperature of the plantar region of the feet (Tskin_Feet). Twenty-four elderly women participated, divided into three groups: GT2DM + PAD (n = 8; 69.6 ± 8.0 years-old; 148 ± 5 cm; 63.8 ± 8.9 kg), GT2DM (n = 8, 69.3 ± 7.8 years-old, 151 ± 6 cm; 66.3 ± 10.8 kg), and control group (CG) (n = 8; 69.3 ± 6.6 years old; 148 ± 6 cm; 58.0 ± 5.3 kg). The T2DM was diagnosed based on HbA1C concentrations, and PAD was assessed using the Ankle-Brachial Index. Thermographic images were captured for both feet using the Flir thermal camera (model T420®) and analyzed using Flir Tools® software. The Inner canthus (IC) measurement was used as an indicator of core body temperature. Five regions of interest (ROIs) were determined for each image. The difference (Δ) between the temperature at the IC (average among right and left side) and of the each of the five ROIs in the plantar region (right foot and left foot) was calculated, where lower values indicated a closer proximity to the core body temperature. The one-way ANOVA was performed to verify differences between groups of clinical conditions. A significance level of 5% was assumed. The GT2DM group exhibited higher Tskin_Feet absolute values than the CG for all ROIs. However, just for ROI4 (hindfoot) of the right foot plantar was significant (p = 0.027). On the other hand, when analyzing the values difference between the average temperature at the IC of the temperature in the five evaluated ROIs on the right and left foot, the GT2DM group showed significantly lower values than the CG for for ROI 2 (forefoot) p = 0.0429 and ROI 4 (hindfoot) p = 0.009 on the right foot and for ROI 1 (forefoot) p = 0.0338; ROI 2 (forefoot) p = 0.0392 and ROI 5 (hindfoot) p = 0.0377 on the left foot. In conclusion, GT2DM presented a Tskin_Feet closer to the core temperature (IC) indicating a higher temperature. The presence of PAD appears to attenuate skin overheating.
ABSTRACT
OBJECTIVES: This cross-sectional study aimed to examine the relationships of sleep timing and sleep variability with depressive symptoms, health-related quality of life (HRQoL), daytime sleepiness, and body mass index (BMI) in adolescents. METHODS: Adolescents from three schools (n = 571, 56% female, 16.3 ± 1.0 years) had their sleep examined by actigraphy, their anthropometrics assessed, and answered a survey. Sleep timing was examined by combining groups of median-dichotomized onset and wakeup times (early onset and early wakeup; early onset and late wakeup; later onset and early wakeup; later onset and later wakeup); sleep variability was based on within-participant standard deviations of onset and wakeup; and sleep duration as the length of time between onset and wakeup. The sleep variables were separated for weekdays and weekend. Mixed linear models were fitted to compare each sleep variable with health-related outcomes. RESULTS: Higher values of daytime sleepiness were observed in adolescents from the late-early and late-late timing group during the week. Greater sleep midpoint and wakeup variability on weekdays were related with higher daytime sleepiness. Adolescents in the late-late and early-late groups showed higher daytime sleepiness. Increased of all sleep variability variables was related with greater daytime sleepiness. Higher depressive symptoms scores were found among adolescents in the late-early subgroup and with the increase of sleep variability. Participants with greater sleep onset variability and sleep midpoint variability reported less HRQoL. CONCLUSIONS: Not only sleep duration, but sleep timing and variability also relate to health outcomes, and should be addressed by policies and interventions among adolescents.