Get Blue Member Improves Sleep Quality 15% and HRV 12%

Although standard recommendations for a runner in her position suggest reducing training volume and increasing food intake, her calorie intake was already sufficient. Rather than adding more food, Get Blue recommended a subtle adjustment: shifting her daily caloric intake to earlier hours.

MEMBER STORY

FEMALE | 40 YEARS OLD

Before using Get Blue, a member was frustrated by recovery scores that kept sliding while her training stayed consistent. Her overnight HRV read Low or Unbalanced and her sleep score wouldn’t budge. Most perplexing to her were her frequent night awakenings, since her sleep discipline was excellent: a fixed bedtime, a wind down routine, a dark cool room and no evening screen time. Running 35 miles per week and lifting weights twice weekly, she maintained a substantial, nutrient-dense diet and had recently received a comprehensive lab panel showing virtually normal results.

By analyzing her lab results alongside meal timing and wearable metrics, Get Blue uncovered a within-day energy deficiency pattern. Her total daily intake was sufficient, yet her fueling schedule failed to support her morning energy demands. Waking at 5:20 AM, she completed a fasted run, managed the family routine, and started work—delaying her first real meal until around noon. Consequently, nearly 60% of her daily calories were consumed after 5:00 PM. While her overall intake met her daily needs, the timing did not. Identifying that the lack of progress stemmed from caloric distribution rather than total volume, Get Blue recommended shifting her caloric intake earlier in the day instead of increasing overall consumption.

LAB RESULTS

RESULTS WITHIN RANGE OR SLIGHTLY BELOW

Initial labs ruled out disease: normal inflammation (hs-CRP 0.7), thyroid (TSH 2.60, FT4 1.3, FT3 3.6), negative antibodies, normal metabolic and liver panels, HbA1c 5.2, and no anemia (Hct 40.8, Hgb 12.9). These standard markers provided no diagnostic explanation for her declining recovery.

However, several markers clustered at the lower threshold: leptin at 1.0 ng/mL, white blood cells at 3.8 K/µL, ferritin at 24, and estradiol at 38. Low ferritin, low WBC and variable estradiol occur commonly in female runners, so none confirms low energy availability on its own; the grouping was notable alongside her healthy baseline and unresolved symptoms. Leptin prompted investigation because it drops quickly during energy deficits, though lean body mass can also lower it. Meanwhile, adrenal and thyroid markers remained stable (FT3 upper-normal, TSH mid-range, morning cortisol 10.3 mcg/dL).

Recognizing this combination of behavioral patterns and metabolic indicators, Get Blue recommended adjusting her nutritional timing alongside a formal consultation with her physician. Integrating her fueling patterns, sleep disruptions, and biomarker clusters, Get Blue suggested asking her doctor about early stage Relative Energy Deficiency in Sport (REDs). Designed as an evidence-informed insights tool, this recommendation complemented, but did not replace, her physician's medical direction.

THE PROTOCOL

SAME TOTAL INTAKE  |  DIFFERENT HOURS

Adjusting her intake timeline elevated morning fueling to nearly 40% of her daily total—a major pivot from relying solely on coffee with milk and collagen peptides. In turn, evening intake decreased proportionally. Although total caloric intake shifted by less than 2% over four weeks, aligning energy delivery with energy expenditure made all the difference.

RESULTS OVER 4 WEEKS

WEARABLE DATA

Seven of the first eight readings were Low or Unbalanced, below her baseline. From week two on, all readings were Balanced, and her 7-day average rose 12% (65 ms to 73 ms) on identical calories. Each point reflects a 7-day rolling average.

Night wakings shifted first. In week one, her sleep score varied from 54 to 85 despite a consistent bedtime routine. By week four, scores leveled to 75–96. Get Blue traced the issue to fasted training and delayed post-workout fueling—not poor sleep hygiene.

THE SCIENCE AND LONG-TERM IMPACT

WHAT RED-S IS

Relative Energy Deficiency in Sport (RED-S) occurs when an athlete’s caloric intake fails to adequately match their combined expenditure from physical training and basal metabolic demands, leading to compromised physiological function. In its 2023 consensus statement, the IOC updated this terminology to REDs², highlighting its widespread impacts across endocrine and immune function, bone density, metabolism, cardiovascular health, menstrual cycles, sleep, and athletic performance. Driven fundamentally by low energy availability, REDs requires professional clinical evaluation and cannot be diagnosed by wearable devices alone.

WHY THE LEPTIN READING MATTERED

Research conducted with active women demonstrates that low energy availability — rather than physical exercise stress — drives the suppression of leptin’s daily rhythm¹. Consequently, a significantly reduced reading in a weight-stable athlete warrants investigation as a fueling question rather than a training-volume one. It remains a prompt rather than a diagnostic test, since leptin also correlates strongly with total fat mass.

WHY NUTRIENT TIMING MATTERS

Energy availability is usually calculated across a full day, which can conceal long stretches of deficit inside it. Research on within-day energy deficiency³ measures energy balance in hourly blocks and reports metabolic and endocrine differences between athletes who spend many hours in deficit and athletes with the same 24 hour intake spread more evenly. A large evening intake does not retroactively cover a fasted morning run.

BEYOND RECOVERY

Note that these findings reflect population-level data rather than this individual member’s outcome. Chronic low energy availability extends well beyond immediate recovery issues. Among its most recognized long-term risks, the IOC consensus highlights compromised bone mineral density and a heightened susceptibility to stress fractures. Additionally, comparative studies of amenorrheic and eumenorrheic athletes with similar training volumes demonstrate impaired endothelial function and adverse lipid profiles in those experiencing amenorrhea. In contrast, this member’s evaluation revealed normal thyroid and adrenal function, an hs-CRP of 0.7, and a healthy lipid profile—underscoring why early detection of this pattern is so vital.

THE READ WINDOW

HRV and sleep architecture respond to autonomic load, and a single night says very little. A 7-day rolling average across four weeks is long enough for a timing change to separate from ordinary variation and short enough to act on. Without a defined read window there is no way to tell a protocol that is working from one that is not.

SOURCES