Gestational obesity, defined as obesity during pregnancy or a pre-pregnancy BMI ≥30, is a growing global health challenge with profound implications for both maternal and offspring health. This narrative review synthesizes current evidence on the mechanistic pathways by which maternal obesity affects pregnancy outcomes and intergenerational health trajectories. For mothers, gestational obesity increases the risk of gestational diabetes, hypertensive disorders, cesarean delivery, and postpartum weight retention. Offspring exposed to maternal obesity face higher risks of obesity, metabolic syndrome, cardiovascular disease, and neurodevelopmental disorders, many of which persist across the lifespan. The underlying mechanisms include metabolic dysregulation, insulin resistance, chronic inflammation, oxidative stress, and alterations in placental function. Epigenetic modifications, such as DNA methylation, histone changes, and non-coding RNA expression, play central roles in fetal programming, while maternal gut dysbiosis and alterations in breast milk microbiota further shape infant health outcomes. Importantly, maternal obesity not only influences pregnancy and early life but also perpetuates an intergenerational cycle of obesity and related comorbidities. Preventive strategies targeting preconception and prenatal health, combined with interventions to optimize lactation and maternal diet, may mitigate long-term risks. Future research should prioritize longitudinal and mechanistic studies to refine interventions aimed at disrupting the transmission of obesity-related disease across generations.

Background/Objective: Instantaneous, accurate assessment of hydration and sweat loss has potential to optimize athlete performance and reduce risks associated with excessive exercise-related fluid loss. Reusable wearable hydration monitors, such as hDrop monitors, are an emerging non-invasive, quick, and easy to use alternative to existing methods. Purpose: To assess the accuracy of the hDrop wearable sweat monitors for estimating sweat loss and hydration status compared to established field-based measures, including body mass change and urine indices. Methods: Division I male collegiate soccer athletes contributed repeated training-session observations (38 total observations; 18 complete observations for sweat-loss analyses and 36 for hydration-score–USG analyses). They completed training sessions during which pre- and post-exercise body mass, fluid intake, urine output, and urine samples were collected. Sweat loss was calculated using changes in body mass adjusted for fluid balance. hDrop-derived estimates of sweat loss and hydration status were compared to criterion measures using mean bias, percent of criterion, mean absolute percent error (MAPE), repeated-measures Bland–Altman analysis, and generalized estimating equations accounting for observations clustered within athletes. Associations between hydration scores and urine-based markers were assessed using generalized estimating equations accounting for observations clustered within athletes. Results: The hDrop generated a sweat-loss estimate for 18 of 38 training-session observations (47.4%). Repeated-measures mean bias for sweat loss was −0.423 L (95% CI −1.106 to 0.259 L). The hDrop estimates averaged 106.2 ± 64.8% of criterion while MAPE was 50.3%, reflecting large individual error. In the repeated-measures analysis, criterion-measured sweat loss was positively associated with hDrop-estimated sweat loss (B = 0.204, 95% CI 0.018 to 0.391, p = 0.032). Significant proportional bias was present (slope = −0.790, 95% CI −1.438 to −0.143, p = 0.020), indicating greater underestimation at higher sweat-loss values. In repeated-measures GEE analyses, USG was not significantly associated with the hDrop hydration score either before practice (B = −407.9, 95% CI −1008.7 to 192.8, p = 0.183) or after practice (B = −135.0, 95% CI −803.8 to 533.7, p = 0.692). Conclusions: The hDrop generated sweat-loss estimates in fewer than half of training-session observations and demonstrated substantial individual-level error and significant proportional bias when estimates were available. Although the instantaneous hydration score decreased following exercise, its lack of association with USG leaves its physiological meaning and criterion validity uncertain. These findings do not support use of the hDrop as an interchangeable substitute for established methods of individualized sweat-loss or hydration assessment.