Screening Athletes for Low Energy Availability: A Clinical Protocol

Energy availability (EA) is the single most under-screened clinical variable in sports nutrition. Most RDs working in performance settings know the term, can quote the 30 kcal/kg FFM threshold, and have read the IOC consensus on Relative Energy Deficiency in Sport. Far fewer have a structured, repeatable protocol for catching low energy availability before it becomes a referral.

This is the protocol I use. It is built for a sports RD with a roster of 30–150 athletes, working alongside performance staff, with limited time per athlete. It assumes you cannot DEXA every athlete every month and you cannot send every menstrual irregularity to the team physician.

What Energy Availability Actually Is

Energy Availability = (Energy Intake − Exercise Energy Expenditure) / Fat-Free Mass

Three numbers, one ratio, expressed in kcal/kg FFM/day.

The thresholds, drawn from the Loucks lab work and reinforced by the IOC and IAAF consensus statements:

• 45 kcal/kg FFM/day: optimal for adaptation, performance, and reproductive function
• 30–45 kcal/kg FFM/day: subclinical "grey zone" — measurable physiological compensation begins here
• <30 kcal/kg FFM/day: low energy availability, the threshold for RED-S risk

The number itself is not the diagnosis — it is the screen. A single estimate is noisy. A pattern across two or three checkpoints, paired with clinical symptoms, is what drives action.

The Three-Layer Screen

Every athlete on your roster moves through three layers, in order of effort: a flag screen, a quantitative estimate, and a clinical workup.

### Layer 1: The Flag Screen (every athlete, every visit)

Five yes/no questions. Ninety seconds. If two or more come back yes, the athlete moves to Layer 2.

1. Body mass change >5% in the last 6 months without a planned weight intervention?

2. Any menstrual cycle irregularity in the last 12 months (female athletes) — defined as cycle length <21 or >35 days, missed cycles, or new oligomenorrhea?

3. Any stress fracture or bone stress injury in the last 24 months?

4. Self-reported low energy, mood disturbance, or training performance decline that is not explained by load?

5. Subjective restriction — does the athlete report intentionally avoiding food groups, skipping meals to control weight, or not eating after evening sessions?

These map closely to the LEAF-Q and RED-S CAT screening tools but are short enough to live inside a standard nutrition visit. Document each answer in the Subjective section of the SOAP note.

### Layer 2: The Quantitative Estimate (flagged athletes, monthly)

For any athlete who flags, you need an EA estimate. The barrier here is data quality — three numbers, all imperfect.

Energy Intake (EI). A 7-day food log via the platform. Athletes hate this. The compliance trick is to ask for 4 training days and 3 rest days, photo-based, with a single dietitian review session at the end of the week to clarify ambiguous entries. Expect roughly 80% of stated intake — under-reporting is the rule, not the exception, and your protocol should account for it.

Exercise Energy Expenditure (EEE). This is the messiest input. Best practice is session-by-session estimation using either (a) heart-rate-based caloric expenditure from the athlete's wearable, (b) MET values for the activity multiplied by duration and body mass, or (c) for resistance training, a flat 5–7 kcal/min for the working portion of the session. Subtract resting metabolic-rate-equivalent kcal for the exercise duration to avoid double-counting.

Fat-Free Mass (FFM). DEXA is the reference. BIA on a research-grade device (InBody 770, Seca mBCA) is acceptable. Skinfolds with ISAK technique work if you have a trained tester. For monthly tracking, use the same method, same tester, same time of day, same [hydration state](/blog/hydration-status-assessment-in-clinical-workflow). Do not mix methods across visits.

Compute the ratio. Track it in the clinical chart. A single value below 30 is a flag. Two consecutive monthly values below 30, or any value below 25, escalates immediately.

### Layer 3: The Clinical Workup (escalated athletes, immediate)

When Layer 2 escalates, you are no longer the only clinician on the case. The Plan section of your SOAP note should include:

• Referral to the team physician for menstrual history, baseline labs (CBC, CMP, ferritin, transferrin saturation, 25-OH vitamin D, TSH, LH, FSH, estradiol for females; total and free testosterone, SHBG for males), and consideration of DEXA bone density. The [iron-status workup](/blog/iron-status-workup-in-female-athletes) details the three-marker primary panel (ferritin + TSAT + Ret-He) for female athletes and the contraceptive-method-appropriate monitoring cadence
• Consideration of psychology referral — disordered eating screen via EAT-26 or SCOFF
• A documented fueling intervention: target intake, target EA, and a specific food-by-food behavioral plan to close the gap
• A check-in cadence (weekly for the first month, biweekly thereafter) until two consecutive estimates exceed 35 kcal/kg FFM

The RD does not diagnose RED-S. The RD identifies low energy availability, documents the clinical reasoning, and runs the nutrition arm of the multidisciplinary plan.

Where the Common Mistakes Happen

Mistake 1: Treating EA as a single number. A 28 kcal/kg FFM estimate from a 7-day food log with three missing entries and a wrist-based EEE figure is not a diagnosis. It is a flag. Pair it with symptoms before acting.

Mistake 2: Skipping the flag screen for male athletes. Male athletes develop LEA at meaningful rates — endurance running, cycling, weight-class combat sports, lightweight rowing — and the screen is shorter for them (no menstrual question) but no less important. Stress fracture history and unexplained performance decline are the highest-yield items.

Mistake 3: Confounding EA with body composition. An athlete with stable body composition can still be in LEA if training load increased and intake did not. Conversely, an athlete losing weight by design (weight-class sport, planned cut) is not in LEA if intake matches the periodized target.

Mistake 4: Not documenting the screen. If the screen is not in the chart, it did not happen. The Subjective section captures the flag screen. The Objective captures Layer 2 numbers. The Assessment captures the clinical interpretation. The Plan captures the intervention — or the rationale for not intervening.

What the Workflow Looks Like in Practice

A 60-athlete roster running this protocol generates roughly:

• 60 × 90-second flag screens per visit cycle (~90 minutes of total dietitian time)
• 8–12 athletes flagged for Layer 2 quantitative estimates per cycle
• 1–3 athletes escalated to Layer 3 per quarter

The bottleneck is Layer 2. Without platform support, each Layer 2 estimate is 30–45 minutes of food log review, EEE calculation, FFM lookup, ratio computation, and chart documentation. With dashboard-level food log aggregation, automated kcal totals, integrated wearable data, and a saved EA calculator template, that drops to 8–10 minutes per athlete.

That math — roughly four hours of clinical time per cycle versus eighteen — is the difference between running this protocol on every flagged athlete and running it on the loudest two.

The Bottom Line

Low energy availability is identifiable, screenable, and treatable. The framework is well-established. What is missing in most sports practices is a repeatable workflow that catches it early, documents it cleanly, and routes the right athletes to the right care.

If your current LEA screening protocol is "I keep an eye on it," your protocol is not a protocol. Build the three-layer screen, embed it in your SOAP template, and audit your roster against it once a quarter.

[Calsanova's Dietitian plan](/signup?role=dietitian) includes integrated food log dashboards with automated kcal aggregation, a built-in EA calculator, and SOAP note templates that bake the flag screen into every visit. Start your 30-day free trial and put the protocol on rails.