Dr. Aarti Javeri-Mehta is a Lifestyle Medicine physician and internal medicine specialist with more than 12 years of clinical experience. A thought leader in women’s health, she founded Sustain Health to bridge the gap between conventional medicine and lifestyle-focused care, empowering women through non-judgemental coaching, evidence-based education, and programs designed to deliver measurable, sustainable results. Through real-time tracking tools — Apple Watch included — she helps women understand their physiology, improve performance, and build habits rooted in compassion rather than stress.

— How accurate are wearables for measuring HRV, RHR, and VO₂ max compared to clinical tools? Where should athletes trust their watch — and where should they trust their body instead?

— Wearables have rapidly closed the gap with clinical tools. Studies comparing Apple Watch sensors with ECG-based HR and lab-grade HRV show strong correlation for trends and moderate-to-high accuracy for absolute values. VO₂ max estimation using the Watch’s submaximal exercise algorithms has been validated against cardiopulmonary exercise tests, showing reliable directional accuracy.

Still, physiology is complex: hydration status, caffeine, stress, alcohol, travel, and menstrual phase all influence numbers. Athletes should use the Watch for decision-making, not diagnosis, trends matter more than one-day readings.

— From all the data wearable gadgets give us — HRV, RHR, VO₂ max, HR zones, sleep score — which ones are genuinely important for improving athletic performance, and which ones are just “nice to have”?

— For example, the Apple Watch Ultra 3 provides dozens of data points, and while I argue they are all equally important or interconnected in some way to athletic performance, the ones most validated by sports physiology include: heart rate variability, resting heart rate and heart-rate zones. These reflect autonomic balance, recovery capacity, and cardiovascular load. Studies show that day-to-day HRV and RHR trends correlate strongly with markers like cortisol, inflammatory cytokines, and training readiness. Sleep score and VO₂ max are valuable, but they function best as trend-based indicators. A single night of poor sleep or one off VO₂ reading has limited predictive value; but rather a long-term pattern of understanding sleep score will help determine whether or not that will affect your athletic performance.

— Why are women's metrics not the same as men's? How does the menstrual cycle influence training performance? What changes naturally occur in metrics like sleep score, RHR, HRV, and recovery across the different phases of the cycle?

— Women’s physiology is dynamic across the menstrual cycle. Estrogen and progesterone don’t just affect fertility but they influence thermoregulation (how your body adapts to temperature), metabolic rate, cardiovascular output, mitochondrial efficiency, glucose utilisation, and neuromuscular performance thus affecting stamina, performance and so much more. Because of this, metrics like HRV, RHR, and sleep architecture naturally shift across phases. HRV often increases during the follicular phase, when oestrogen rises and parasympathetic tone improves, and decreases in the late luteal phase, when progesterone elevates body temperature and increases cardiorespiratory strain. Wearable data repeatedly shows that women experience predictable, cyclical patterns that differ fundamentally from men’s more stable physiology.

— Why do women often see extreme HRV drops during PMS and menstruation? How should female athletes interpret low HRV days — rest, modify training, or ignore it?

— Vagal tone, reflected physiologically through HRV, is a critical marker in women’s health because stronger parasympathetic regulation is associated with lower systemic inflammation, better hormonal balance via more stable hypothalamic-pituitary-ovarian axis function, and reduced risk of stress-related conditions such as PMS, PMDD, anxiety, and metabolic dysfunction.

In women, HRV predictably drops during PMS and early menstruation due to a number of reasons (inflammation, activation of the sympathetic nervous system, altered pain sensation) and so much more. HRV also alters chronic women’s health conditions.

For female athletes, low HRV during PMS doesn’t stop women from training and research shows women often remain capable of high performance if they adjust load and recovery expectations. The key is understanding your own pattern and modifying training rather than avoiding it entirely.

— What does a rising RHR tell us about hormonal shifts, inflammation, fatigue, or undereating? How can women differentiate “normal cycle changes” from actual red flags?

— RHR rises in the luteal phase due to progesterone-driven increases in metabolic rate and core temperature. But persistent elevation outside of this window can indicate under-fueling, infection, elevated cortisol, poor sleep, or subclinical inflammation. Women in high-stress or low-energy availability states often show a combination of rising RHR, reduced HRV, plateauing performance, poorer deep-sleep metric and ‘off watch.' This typically shows up as increased fatigue, irritability, mood swings, reduced concentration, heavier cravings, disrupted cycles, and a higher susceptibility to illness or injury. Differentiating “normal hormonal variation” from true red flags comes from tracking month-to-month patterns for which the Apple Watch is uniquely suited for this because of its consistent daily trend capture.

— How should women adjust training intensity (Zone 2 vs Zones 4/5) during follicular, ovulatory, and luteal phases? What does the watch show that helps guide these adjustments?

— Although interest in menstrual-cycle training is increasing, the scientific evidence is still mixed. Some studies suggest women may feel stronger or recover better in the follicular phase and experience slightly higher exertion or temperature strain in the late luteal phase, but overall effects are small and vary widely between individuals. The most effective approach is to pair watch-based trends like HRV, resting heart rate, and sleep with subjective cues such as energy, mood, and motivation, adjusting training based on how a woman feels rather than relying on strict cycle-phase rules.

However, in the follicular and ovulatory phases estrogen enhances muscle recovery, reduces perceived exertion, increases fat oxidation, and supports higher-intensity training. In the luteal phase, higher progesterone increases ventilation, core temperature, and carbohydrate needs, Zone 2 work and strength maintenance may feel more sustainable. The Apple Watch’s heart-rate zones, recovery trends, and sleep integration allow women to adapt their training in real time, preventing both under-training and unnecessary fatigue.

— VO₂ max is often used as a status metric — but how meaningful is it for women? Can menstrual phases affect VO₂ readings? And can women realistically improve it as effectively as men?

— VO₂ max is often treated as a “badge of fitness,” but physiologically, women start with lower baseline values because of lower haemoglobin concentration, lower cardiac output, and smaller lung volumes. This doesn’t limit potential but it simply means women should focus more on relative improvement rather than comparing absolute numbers to men. Women can improve VO₂ max through high-intensity interval training (HIIT), particularly intervals performed at 90–100% of maximal heart rate, which research shows can raise VO₂ max by 10–20% over 8–12 weeks. Integrating these sessions during phases of the menstrual cycle when energy, recovery, and perceived exertion are optimal, typically the late follicular to ovulatory window, can enhance performance and adherence. Consistent Zone 2 aerobic training (60–70% max HR) builds mitochondrial density and supports long-term aerobic gains, while strength training 2–3 times per week improves running economy and oxygen utilisation throughout the cycle.

Beyond training, VO₂ max is strongly influenced by lifestyle factors: 7–9 hours of high-quality sleep, adequate recovery days, and appropriate fueling. Ensuring sufficient carbohydrate intake (3–6 g/kg/day for most active women) and protein (1.2–1.6 g/kg/day) supports the metabolic and muscular adaptations necessary for increasing VO₂ max. Research shows that VO₂ max can fluctuate during the cycle, especially in the luteal phase where higher core temperature and elevated respiratory rate reduce oxygen extraction efficiency. The Apple Watch measures VO₂ max through validated submaximal protocols that track progress reliably for women.

— What early signals of overtraining syndrome or RED-S (Relative Energy Deficiency in Sport) show up first on wearable data for women? Low HRV? Elevated HR? Poor sleep metrics? Cycle disruption?

— Relative Energy Deficiency in Sport (RED-S) is a serious condition that occurs when energy intake is insufficient to support the body’s physiological demands. It can affect multiple systems, including hormonal regulation, bone health, cardiovascular function, metabolism, and immune function. In women, RED-S often leads to menstrual irregularities, low bone density, chronic fatigue, impaired recovery, and increased injury risk, making early detection through both subjective symptoms and wearable data essential for long-term health and performance.

Some early indicators of it may include persistently low HRV not tied to cycle timing, elevated resting heart rate, reduced deep and REM sleep, higher-than-normal heart rate at submaximal loads, longer recovery after training, and cycle irregularities are serious warning signs in female athletes. These changes indicate disruptions across multiple physiological systems, including the hypothalamic-pituitary-ovarian axis, energy metabolism, and inflammatory balance. Such alterations often appear well before performance declines, making them critical early markers of overtraining, low energy availability, or systemic stress, and highlighting the need for careful monitoring and intervention.

— How do lifestyle factors like stress, poor sleep, under-fueling, and birth control influence the data? What should women know about interpreting “bad” metrics on stressful weeks?

— Stress, sleep, and energy availability are tightly interconnected and have profound effects on female physiology. Chronic stress elevates cortisol, which suppresses parasympathetic activity, reduces HRV, and fragments sleep architecture. Sleep deprivation itself raises resting heart rate, lowers HRV, and impairs glucose metabolism, creating a feedback loop that amplifies stress responses. Under-fueling further increases sympathetic activation, decreases deep sleep, and elevates resting heart rate, while hormonal contraception can flatten HRV patterns and shift baseline temperature and heart rate. In women, a “bad” metric often reflects this complex interplay of physiological strain rather than failure.

When tracking health or performance metrics, it is important to interpret the data with compassion rather than letting numbers drive your mood or decisions. Metrics like HRV, resting heart rate, sleep, and training load are influenced by stress, recovery, hormones, and daily life factors, so single readings rarely tell the full story. Focusing on trends over time, alongside subjective feelings of energy, motivation, and wellbeing, allows for smarter adjustments and helps prevent anxiety, guilt, or overtraining driven by one isolated number.

— If you had to design a simple, daily “watch checklist” for women — three metrics that actually matter — which would you choose and why? And how should women use this information to avoid burnout and improve long-term performance?

— If I were using just three metrics daily, I would focus on sleep score, HRV, and resting heart rate. Sleep score provides insight into overall recovery quality, including deep and REM sleep, which are critical for hormonal balance, cognitive function, and tissue repair. HRV trends reflect autonomic nervous system regulation, systemic inflammation, and readiness to handle training stress, helping to guide intensity adjustments. Resting heart rate is highly sensitive to stress, illness, under-recovery, and low energy availability, offering an early warning for physiological strain. Together, these three metrics give a clear, integrated picture of recovery, readiness, and long-term health, allowing women to optimize training, prevent burnout, and support menstrual-cycle and metabolic health.