Introduction: Scientists and consumer products are increasingly employing light-based photoplethysmography (PPG) instead of electrocardiography (ECG) assuming it accurately quantifies heart rate variability (HRV). Recent studies, however, have demonstrated that pulse rate variability (PRV) derived from PPG is not equivalent to HRV-derived from ECG. This study investigated the agreement between PPG-PRV and ECG-HRV in a beat-to-beat analysis in 931 adults recruited from a tertiary academic medical center in the southeastern United States.Methods: Participants wore two (chest and bicep) Warfighter Monitor™ devices (Tiger Tech Solutions, Inc.). Heart rate (HR), pulse rate (PR) and three time-domain indices for PPG-PRV and ECG-HRV were measured. ECG-derived RR and noise-filtered NN intervals were extracted to compute HR, SDNN (standard deviation of NN intervals), rMSSD (root mean square of successive differences), and pNN50 (percentage of successive NN intervals differing by >50 ms). PPG-derived pulse-wave peaks were detected to calculate corresponding PR/PRV metrics. Pearson correlation, Bland–Altman, and one-way ANOVA analyses assessed linear association, bias, and mean differences across select chronic diseases.Results: Significant disagreement and differences were observed between ECG-HRV and PPG-PRV (p < 0.001 for all). For rMSSD: cardiovascular: 3.04 ms, 95% CI: 1.33, 4.75, endocrine: 2.85 ms, 95% CI: 0.52, 5.18, and neurological: 4.39 ms, 95% CI: 1.39, 7.39). For SDNN: cardiovascular: 8.50 ms, 95% CI: 5.25, 11.74, endocrine: 8.43 ms, 95% CI: 3.97, 12.90, neurological: 11.84 ms, 95% CI: 6.02, 17.67, and respiratory: 7.23 ms, 95% CI: 1.83, 12.62). For pNN50: cardiovascular: 2.48%, 95% CI: 1.67, 3.3, endocrine: 2.21% 95% CI: 1.12, 3.29, neurological: 2.91%, 95% CI: 1.25, 4.32, and respiratory: 1.46%, 95% CI: 0.15, 2.77).Discussion: PPG-PRV is a poor surrogate for ECG- HRV as it significantly underestimated SDNN, rMSSD, and pNN50 across select chronic diseases. Given the widespread use of PPG-based devices and ubiquitous, incorrect assumption that PRV accurately reflects HRV, researchers, clinicians, and manufacturers must clearly distinguish between PRV and HRV in studies and product claims.

Military aviators endure high cognitive loads and hypoxic environments during flight operations, impacting the autonomic nervous system (ANS). The synergistic effects of these exposures on the ANS, however, are less clear. This study investigated the simultaneous effects of mild hypoxia and high cognitive load on the ANS in military personnel. This study employed a two-factor experimental design. Twenty-four healthy participants aged between 19 and 45 years were exposed to mild hypoxia (14.0% O₂), normoxia (21.0% O₂), and hyperoxia (33.0% O₂). During each epoch (n = 5), participants continuously performed one 15 min and one 10 min series of simulated, in-flight tasks separated by 1 min of rest. Exposure sequences (hypoxia–normoxia and normoxia–hyperoxia) were separated by a 60 min break. Heart rate (HR), heart rate variability (HRV), and O₂ saturation (SpO₂) were continuously measured via an armband monitor (Warfighter Monitor^TM, Tiger Tech Solutions, Inc., Miami, FL, USA). Paired and independent t-tests were used to evaluate differences in HR, HRV, and SpO₂ within and between exposure sequences. Survival analyses were performed to assess the timing and magnitude of the ANS responses. Sympathetic nervous system (SNS) activity during hypoxia was highest in epoch 1 (HR: +6.9 bpm, p = 0.002; rMSSD: −9.7 ms, p = 0.003; SDNN: −11.3 ms, p = 0.003; SpO₂: −8.4%, p < 0.0000) and appeared to slightly decline with non-significant increases in HRV. During normoxia, SNS activity was heightened, albeit non-significantly, in epoch 1, with higher HR (68.5 bpm vs. 73.0 bpm, p = 0.06), lower HRV (rMSSD: 45.1 ms vs. 38.7 ms, p = 0.09 and SDNN: 52.5 ms vs. 45.1 ms, p = 0.08), and lower SpO₂ (−0.7% p = 0.05). In epochs 2–4, HR, HRV, and SpO₂ trended towards baseline values. Significant between-group differences in HR, HRV, and O₂ saturation were observed. Hypoxia elicited significantly greater HRs (+5.0, p = 0.03), lower rMSSD (−7.1, p = 0.03), lower SDNN (−8.2, p = 0.03), and lower SpO₂ (−1.4%, p = 0.002) compared to normoxia. Hyperoxia appeared to augment the parasympathetic reactivation reflected by significantly lower HR, in addition to higher HRV and O₂ relative to normoxia. Hypoxia induced a greater ANS response in military personnel during the simultaneous exposure to high cognitive load. The significant and differential ANS responses to varying O₂ levels and high cognitive load observed highlight the importance of continuously monitoring multiple physiological parameters during flight operations.

Exercise and polyunsaturated fatty acid (PUFA) supplementation independently improve lipid profiles. The influence of both exercise and PUFAs on lipids during pregnancy remains unknown. This study evaluated exercise, docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) concentrations on lipids during pregnancy. Participants were randomized to aerobic exercise or control groups. From 16 weeks gestation until delivery, groups met 3x/week; exercisers performed moderate-intensity aerobic activity, controls performed low-intensity stretching and breathing. At 16 and 36 weeks’ gestation, maternal blood was analyzed for lipids (total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG)), DHA and EPA. In intent-to-treat analysis, the aerobic group (n = 20), relative to controls (n = 10), exhibited a higher HDL change across gestation (p = 0.03). In a per protocol analysis, the aerobic group, relative to controls, exhibited 21.2% lower TG at 36 weeks (p = 0.04). After controlling for 36-week DHA and EPA, exercise dose predicts 36 weeks’ TG (F (1,36) = 6.977, p = 0.012, r² = 0.16). Aerobic exercise normalizes late pregnancy TG. During pregnancy, exercise dose controls the rise in TG, therefore maintaining normal levels. DHA and EPA do not have measurable effects on lipids. Regardless of PUFA levels, exercise at recommended levels maintains appropriate TG levels in pregnant women. Normal TG levels are critical for pregnancy outcomes, and further studies are warranted to investigate this association in broader populations.

Purpose: This study evaluated the effects of a goal setting intervention on aerobic fitness (AF) in 6th to 8th grade students.Method: Students at the intervention school received a lesson on SMART goal setting. Students in the comparison school served as a measurement-only group. AF was assessed via the PACER multistage shuttle run test pre and post intervention. Between-group differences for change in AF were assessed using a RM ANCOVA.Results: A significant group by time interaction was observed for PACER performance, F(1,263) = 39.9, p < .0001. Intervention students increased PACER performance from 40.6 to 45.9 laps, while comparison students exhibited a decline from 30.2 to 23.4 laps. Intervention students were 10 times as likely as those in the comparison school to maintain Healthy Fitness Zone status or progress from Needs Improvement Zone to Healthy Fitness Zone.Discussion: Educating middle school students about SMART goal setting may be an effective strategy for improving aerobic fitness.