Training Science
The science of resistance and cardio training — progressive overload, training to failure, frequency, rest intervals, periodization, RPE, VO₂max, and sarcopenia.
Progressive Overload & Resistance Training Volume
Umbrella review of 14 meta-analyses (4,784 participants). Established that ≥10 sets/week/muscle group is optimal for hypertrophy, progressive overload is essential even in trained athletes, and volume is the primary prescription variable.
RCT showing both load (weight) progression and repetition progression produce equivalent hypertrophy over 8 weeks. Validates sets × reps × weight tracking as a proxy for progressive overload.
Meta-regression of 67 studies (2,058 participants). 100% posterior probability that increasing weekly volume increases both hypertrophy and strength, with each additional set yielding ~0.24% more hypertrophy. Validates volume tracking in the app.
Cardio — Calorie Expenditure & Zone Training
Training Science
How does the app turn an activity into a calorie estimate?
About this study
Activities cataloged
1,000+ activities
New in 2024
303 activities
The canonical MET reference standard maintained since 1993, now in its third update. Researchers screened 32,173 abstracts and added 303 newly-measured activities, with MET values derived from indirect calorimetry.
The finding
Every physical activity has an established MET (metabolic equivalent) value. The 2024 update is the broadest catalog yet — over 1,000 activities — and underpins how fitness apps and research convert "20 minutes of running" into a calorie number.
The answer
1,000+ activities cataloged
MET values from 1.0 (sleep) to 23.0 (running 14 mph) · 303 new activities added in 2024
When you log a 20-minute run without heart-rate data, the app uses the MET value for that activity (running 5 mph ≈ 8 METs) and computes bw_70kg × 8 METs × 0.33 hr ≈ 184 kcal. The Compendium is the source of those MET values. More accurate than generic per-minute estimates because it accounts for activity-specific intensity.
Training Science
How does heart rate during exercise predict calories burned?
About this study
People
115 adults
Intensity tested
35–80% VO₂max
115 regularly exercising adults (ages 18-45) tested on cycle ergometer and treadmill at multiple submaximal intensities. Researchers derived sex-specific equations predicting energy expenditure from heart rate, body weight, age, and VO₂max.
The finding
Heart rate alone isn't enough to estimate calorie burn accurately — but combined with weight, age, sex, and aerobic fitness, it gives a reasonable estimate for steady-state submaximal exercise.
The answer
HR-based when HR data available
Validated 35–80% VO₂max · Accuracy degrades for all-out sprints
When you log a cardio session with heart-rate data, the app uses Keytel's sex-specific regression to estimate calories: combining your average HR, weight, age, and (optionally) VO₂max. The equation works best for steady submaximal sessions — easy runs, zone-2 rides, moderate intervals. For all-out work, the model under- or over-shoots; the app falls back to MET-based estimation in those cases.
Training Science
Is HIIT really better than steady cardio for fitness?
About this study
Reviews pooled
11 overviews
Primary studies
179 trials
Researchers synthesized 11 systematic reviews covering 179 unique primary studies on training-intensity effects on maximal oxygen uptake (VO₂max). Participants ranged from sedentary to athletic, ages 18-70+.
The finding
Both high-intensity and moderate-intensity training reliably improve aerobic fitness. The advantage of HIIT over steady cardio is real but often small — sometimes trivial. Older and less-fit people benefit most from the high-intensity bias.
The answer
Both work
HIT vs CON: SMD 0.57–1.81 · HIT vs MICT: SMD 0.04–0.64 (small to trivial)
For a beginner or middle-aged adult building aerobic fitness, both steady zone-2 cardio and short HIIT sessions work. The HIIT advantage shows up clearest in older adults and less-fit beginners doing long-interval (2-4 min) work or high-volume sessions (≥15 min total). If you'd rather run easy than do intervals, the gap is small enough that it doesn't matter much.
Training Science
How much does HIIT actually raise VO₂max?
About this study
People
334 adults
Studies pooled
37 trials
Healthy sedentary or recreationally active adults under 45 (334 across 37 studies). Researchers measured VO₂max change after 6-13 weeks of structured high-intensity interval training (3+ days/week).
The finding
High-intensity interval training reliably increases maximal aerobic capacity by about 0.5 L/min — a large effect by training-adaptation standards. Effects held across the studied age and fitness ranges.
The answer
+0.51 L/min VO₂max
95% CI 0.43–0.60 L/min · Standardized effect: 0.86 SD
A typical untrained or recreationally active adult under 45 who runs structured HIIT for 6-13 weeks adds about 0.51 L/min to their VO₂max. That's roughly equivalent to moving up one fitness percentile — a meaningful improvement. The effect held across protocols (interval lengths varied) and was consistent enough across studies to give high confidence in the average.
Training Science
Why does the app use your TDEE instead of generic METs?
About this study
People
105 adults
Conventional 1-MET error
6.6–11.3 % MAPE
105 adults (57 women, 48 men; ages 18-40; about half endurance-trained, half active controls). Researchers measured resting metabolic rate via indirect calorimetry and VO₂max via spiroergometry, then compared the conventional 3.5 mL/kg/min "1-MET" value to each person's individualized RMR-derived MET.
The finding
The standard 1-MET (3.5 mL/kg/min) consistently overestimates resting metabolic rate in most adults and underestimates activity energy expenditure by 6-11%. Individualized values are meaningfully more accurate.
The answer
6–11% error in standard MET
Overestimates RMR (p<0.01) · Underestimates AEE in most adults
The standard MET formula assumes everyone has the same resting metabolic rate per kilogram — but your actual RMR can vary by 6-11% from that average. For someone burning ~2,000 kcal/day, that's a 120-220 kcal daily error compounded over time. The app uses your individualized TDEE (computed from Mifflin-St Jeor + activity factor) alongside MET-based activity estimates so the math lines up.
Training Science
What heart-rate zone actually burns the most fat?
About this study
People
300 adults
Sex split
157 / 143 M / F
Venables and colleagues had 300 healthy adults perform an incremental treadmill test to exhaustion, using indirect calorimetry to track fat oxidation across intensities and find each person's "Fatmax".
The finding
Fat oxidation peaks at moderate intensity, then drops as exercise gets harder. On average that peak sat at about 48% of VO2max, or 61.5% of maximum heart rate. Women peaked at a higher relative intensity than men, and individual peaks ranged hugely — some people maxed out burning a fifth of a gram of fat per minute, others over a gram.
The answer
~62% max heart rate
On average: 48% VO2max ≈ 61.5% max HR. Women peak around 52% VO2max, men around 45%. Individual MFO range: 0.18 – 1.01 g/min.
The "fat-burning zone" idea isn't fitness folklore — fat oxidation really does peak at moderate intensity. For most people, that's around 60 – 65% of their max heart rate. Above that, the body shifts toward carbohydrate. Your personal Fatmax can be quite different from the average, and total calories still matter more than zone choice for body-fat change over time.
Training Science
How do you train and eat to burn the most fat?
About this study
Type
Narrative review
Achten and Jeukendrup's narrative review of fat-oxidation physiology, synthesising training and dietary determinants of how much fat the body actually burns during exercise.
The finding
Two clear levers control how much fat you burn during cardio: intensity and pre-exercise carbs. Fat oxidation peaks at moderate intensity — lower in untrained people, higher in endurance athletes — and drops fast at hard efforts. Eating carbs before exercise reliably blunts fat oxidation compared with training fasted.
The answer
47 – 64% VO2max
General population: 47 – 52% VO2max. Endurance-trained: 59 – 64% VO2max. Pre-exercise carbs lower fat oxidation; fasted state (>6 h) raises it.
If maximising fat burn per session is the goal, train at moderate intensity — the harder you go, the more the fuel mix shifts to carbohydrate. Endurance-trained people can hold higher absolute intensities while still burning fat. Eating carbs right before cardio suppresses fat oxidation; training fasted does the opposite. Note: total daily calorie balance still matters more than session-by-session fat oxidation for body composition over weeks.
Training to Failure vs. Not to Failure
Meta-analysis of 15 studies finding no significant difference between training to failure and not to failure for either strength (ES = −0.09) or hypertrophy (ES = 0.22) — establishing that proximity to failure, not the act of reaching failure itself, is the key stimulus variable, directly informing the app's rep programming and RPE-based guidance.
Meta-analysis of 15 studies finding a trivial advantage (ES = 0.19) for training to failure vs. non-failure for hypertrophy — concluding that leaving 2–4 reps in reserve (RIR) is likely sufficient to drive hypertrophy while reducing cumulative fatigue, validating RPE/RIR-based programming in the app.
First continuous dose-response meta-regression on proximity to failure using RIR quantification — finding a non-linear relationship where training in the 0–4 RIR range maximizes hypertrophic stimulus while sets performed with >6 RIR show substantially diminished returns, providing the most precise guidance available for programming rep ranges relative to failure.
Training Frequency per Muscle Group
Landmark meta-analysis of 25 studies finding that when weekly volume is equated, training frequency does not significantly impact hypertrophy — allowing individuals to choose 1–6 sessions per week per muscle based on personal preference, schedule, and recovery capacity. Validates the app's flexible frequency programming.
Bayesian network meta-analysis of 178 strength studies and 119 hypertrophy studies (5,097 and 3,364 participants respectively) finding a 95% probability that ≥2 sessions per week increases both strength and hypertrophy significantly — establishing the minimum effective training frequency for the app's program generation.
Systematic review finding 12–20 weekly sets per muscle group is the optimum range for hypertrophy in trained individuals, with no additional benefit confirmed beyond 20 sets — directly informing the app's volume prescription recommendations and upper volume limits.
Rest Intervals Between Sets
The most comprehensive and methodologically rigorous meta-analysis on rest intervals for hypertrophy, finding a trend (74% probability) favoring rest intervals ≥60 seconds over shorter rests, with differences relatively small — concluding that longer rest intervals (2–3 min) may provide modest hypertrophy advantages while clearly allowing greater volume per session. Validates the app's rest timer recommendations.
Foundational review establishing that 3–5 minutes between sets produces greater absolute strength gains due to higher volume capacity. The paper proposed that shorter rest (30–60 s) may maximize acute metabolic stress — a theory since challenged by more recent evidence (see Singer et al. 2024 above) showing longer rests are at least as good for hypertrophy by enabling greater per-session volume. The 3–5 min prescription for strength-focused work remains well-supported.
Rep Ranges & Load for Hypertrophy
Definitive network meta-analysis confirming that muscle hypertrophy is load-independent when sets are performed to volitional failure — low (>15 RM), moderate (9–15 RM), and high load (≤8 RM) all produce equivalent hypertrophy — while high-load training produces superior strength gains. Establishes the scientific basis for the app's "any rep range builds muscle" guidance.
Meta-analysis confirming no significant difference between low-load and high-load training on type I or type II muscle fiber hypertrophy when both are performed to failure — providing fiber-type specificity evidence for the load-independence of hypertrophy and validating diverse rep range programming.
Warm-Up, Stretching & Mobility
Updated multilevel meta-analysis of 83 studies (2,012 participants) confirming that static stretching >60 seconds acutely impairs isolated maximal strength, but neither explosive performance tasks (jumping, sprinting) nor dynamic warm-up routines incorporating stretching show significant performance decrements — resolving the "don't stretch before training" debate and supporting the app's dynamic warm-up protocols.
Network meta-analysis finding that combined static + dynamic stretching (MD = 1.80 cm jump height) and dynamic stretching alone (MD = 1.60 cm) significantly outperform control (no warm-up) for explosive performance — establishing dynamic warm-up as a mandatory component of pre-training protocols and validating the app's warm-up video recommendations.
Foam Rolling & Myofascial Release
Comprehensive meta-analysis establishing that foam rolling produces a clear beneficial acute effect on range of motion, appears useful for recovery from exercise-induced muscle damage, and has no detrimental effect on athletic performance measures — concluding that foam rolling can be safely incorporated into warm-up and recovery protocols without performance cost. Validates the app's foam rolling recommendations.
2024 meta-analysis confirming foam rolling is effective in relieving post-exercise muscle soreness via both visual analogue scale (VAS) and pressure-pain threshold (PPT) measures — establishing foam rolling as a validated DOMS management strategy with practical daily recovery applications.
Mind-Muscle Connection & Attentional Focus
Foundational RCT establishing that resistance-trained individuals can selectively increase activation of target muscles (pectoralis major or triceps brachii) during bench press at loads up to 60% 1RM using internal attentional focus — but this effect disappears above 60–80% 1RM, establishing a practical threshold: internal focus benefits hypertrophy work at moderate loads while heavy strength work benefits from external focus on movement.
The only long-term RCT on mind-muscle connection training adaptation, finding 12.4% greater elbow flexor thickness in the internal focus group vs. 6.9% in the external focus group over 8 weeks — providing the most direct longitudinal evidence that mind-muscle connection produces meaningfully greater hypertrophy in targeted muscle groups when applied during moderate-load training.
Deload Weeks & Supercompensation
The first controlled RCT directly testing a one-week deload, finding comparable hypertrophy and endurance between continuous training and deload groups — but the continuous training group showed greater strength gains. Deloading did not provide the expected supercompensation benefit, suggesting deload weeks are better justified by fatigue management than by evidence of enhanced anabolism. Provides honest, balanced guidance for the app's periodization recommendations.
International Delphi expert consensus establishing that deloading is widely practiced and recommended primarily for fatigue management and injury prevention rather than performance enhancement — with 1–2 weeks of reduced volume (40–60% reduction) recommended every 4–8 training weeks for advanced trainees. Provides the practitioner consensus framework that the app's deload scheduling recommendations are built upon.
Eccentric Training
2025 meta-analysis confirming eccentric training produces a modest but measurable advantage for muscle hypertrophy (ES = 0.60) over concentric-only training (ES = 0.55), with eccentric loading also producing superior tendon stiffness, fascicle length adaptations, and collagen synthesis — directly validating the inclusion of controlled lowering phases (2–4 second negatives) in the app's exercise programming.
Comprehensive 2025 meta-analysis finding eccentric training produced moderate-to-strong effects on muscle strength, power, and hypertrophy across diverse populations including athletes and clinical populations — confirming that eccentric overload (via flywheel, supramaximal loading, or controlled negatives) is a uniquely effective stimulus for both hypertrophy and injury rehabilitation that complements the standard concentric-eccentric protocols tracked in the app.
Periodization of Resistance Training
Meta-analysis of 35 RCTs finding that periodized resistance training outperforms non-periodized programmes for strength (ES 0.31), and that undulating periodization (DUP/WUP) produces greater 1RM gains than linear periodization in trained individuals. Hypertrophy outcomes were similar across periodization models when volume was equated — validating progressive overload and volume tracking as the primary driver of adaptation, with periodization style as a secondary modulator.
Meta-analysis confirming that periodized programmes produce significantly greater strength gains than non-periodized protocols — supporting the scientific rationale for structured, planned variation in training load and intensity over time rather than ad-hoc programming.
Systematic review and meta-analysis finding no significant difference in hypertrophy outcomes between linear periodization (LP) and daily undulating periodization (DUP) when volume is matched. The key variable is consistent progressive overload, not the specific periodization model — supporting the app's volume-first tracking approach.
RPE & Autoregulation
Network meta-analysis ranking four load prescription strategies: Autoregulated Progressive Resistance Exercise (APRE, SUCRA 93%), RPE-based (67%), velocity-based (27%), and percentage-based (13%). All three autoregulation methods outperformed fixed percentage-based training for maximal strength, with APRE ranking highest — providing scientific support for effort-based and RIR-guided set logging over rigid percentage targets.
Systematic review finding that autoregulated load prescription (via RPE or RIR) produces equivalent or superior strength and hypertrophy outcomes versus fixed percentage-based loading, with the primary advantage being better management of day-to-day readiness variation — supporting effort-based tracking rather than rigid percentage targets.
Scoping review establishing that RIR (Repetitions in Reserve) scales are feasible, trainable, and reliably used by intermediate-to-advanced athletes for intensity selection. Accuracy improves with experience and feedback. RIR is now widely considered a practical alternative to percentage-based loading for programming and logging resistance training.
VO₂ Max & Cardiovascular Longevity
Training Science
How does my VO₂max compare to my age and sex group?
About this study
CPET tests pooled
22,379 measurements
Age range
20–89 years
A normative-reference dataset of 22,379 cardiopulmonary exercise tests from apparently healthy U.S. adults, stratified by decade of age and sex for both treadmill and cycle ergometer testing. This is the second-generation FRIEND standard (2015 → 2022), with revised values reflecting a larger and more diverse cohort.
The finding
The reference standards provide age-decade and sex-stratified percentile values for VO₂max in mL O₂/kg/min, on both treadmill and cycle ergometer. Compared to the prior 2015 FRIEND standards, the updated values are 1.5–4.6 mL O₂/kg/min lower — meaning percentile rankings have shifted, and a value that previously placed someone at the 50th percentile may now place them slightly higher. Interpretation requires age and sex stratification: a single number divorced from those variables is not interpretable.
The answer
Use age + sex norms not a single number
Treadmill: revised values 1.5–4.6 mL/kg/min lower than 2015 standards · Decade and sex stratified
There is no single VO₂max number that is "good" or "bad" — interpretation requires comparing against your age decade and sex. The current FRIEND standards are the largest U.S. reference dataset for healthy adults (22,379 tests), and the updated 2022 values are 1.5–4.6 mL/kg/min lower than the prior 2015 standards. The app reports your raw value rather than collapsing it into a category, because the same absolute number means very different things at age 25 versus age 65, and on a treadmill versus a cycle ergometer.
Training Science
How strongly does cardiorespiratory fitness predict longevity?
About this study
Meta-analyses pooled
26 reviews
Total observations
20.9M across 199 cohorts
An overview of 26 meta-analyses synthesizing data from 199 unique cohort studies and over 20.9 million observations, examining the relationship between cardiorespiratory fitness and a range of health outcomes (mortality, cardiovascular disease, cancer, diabetes, depression).
The finding
High versus low CRF was associated with halved all-cause mortality (HR 0.47, 95% CI 0.39–0.56), heart failure risk reduced by ~70% (HR 0.31), and cardiovascular mortality reduced by ~73% (HR 0.27). The dose-response signal: each 1-MET increase in VO₂max corresponded to an 11–17% reduction in all-cause mortality. The authors' own confidence statement is more measured than headline framings suggest — they rated the underlying GRADE evidence quality as "very low-to-moderate," and concluded only that there is "consistent evidence that high CRF is strongly associated with lower risk."
The answer
Strongly authors hedge on certainty
All-cause mortality HR 0.47 · 11–17% mortality reduction per 1-MET · GRADE quality: very low-to-moderate
The directional finding is unambiguous: people with higher cardiorespiratory fitness die less and develop fewer chronic diseases, and the dose-response is consistent across 199 cohorts. The honest caveat the headlines often miss: the authors graded the underlying evidence as very low to moderate quality under GRADE — observational data is vulnerable to confounding (people who are fit are also wealthier, better-educated, and less likely to have undiagnosed disease) and reverse causation (pre-clinical illness reduces VO₂max before it kills you). The signal is real and large; the certainty is somewhat lower than the effect size alone would suggest.
Training Science
Does being fit protect against the risks of higher BMI?
About this study
Studies pooled
20 cohorts
Total observations
398,716
A systematic review and meta-analysis of 20 cohort studies (398,716 observations) examining the joint relationship between cardiorespiratory fitness, BMI category, and mortality. Sample is 67% male and predominantly Caucasian/US-based. Most underlying studies used dichotomous CRF cutoffs (often ≥20th percentile = "fit") rather than continuous measures.
The finding
Compared to normal-weight-fit reference, the overweight-fit group showed no statistically significant increase in CVD mortality (HR 1.50, 95% CI 0.82–2.76) or all-cause mortality (HR 0.96, 95% CI 0.61–1.50). Obese-fit similarly showed no significant elevation. By contrast, all unfit categories showed 2–3× elevated mortality: normal-weight-unfit (CVD HR 2.04, all-cause HR 1.92), overweight-unfit (CVD HR 2.58, all-cause HR 1.82), obese-unfit (CVD HR 3.35, all-cause HR 2.04). The authors' framing is specifically that CRF "attenuates" — not eliminates — the risks of higher BMI, and they explicitly state "we do not think weight loss attempts should be discouraged."
The answer
Largely attenuates, not eliminates
Overweight-fit all-cause HR 0.96 · Obese-fit all-cause HR 1.11 · All unfit groups 2–3× elevated risk
The mortality risk associated with higher BMI is largely attenuated — but not perfectly eliminated — when cardiorespiratory fitness is in the normal-or-above range. Across BMI categories, unfit individuals carried 2–3× elevated mortality risk; fit individuals across all BMI categories were statistically indistinguishable from normal-weight-fit reference. Important honest caveats: the sample is 67% male and mostly Caucasian, the underlying studies used dichotomous "fit" cutoffs (often just being above the 20th percentile counted as fit), and the authors themselves explicitly recommend CRF-focused approaches as complementary to weight management — not as a reason to ignore BMI.
Sarcopenia & Older Adult Training
Training Science
How is sarcopenia diagnosed under the current European consensus?
About this study
Type
expert consensus
Endorsed by
5 scientific orgs
The 2018 EWGSOP2 (European Working Group on Sarcopenia in Older People) revised consensus statement, endorsed by five major European scientific organizations: EuGMS, ESCEO, ESPEN, IAGG-ER, and IOF. The paper redefines sarcopenia from its earlier mass-centric definition.
The finding
EWGSOP2 makes low muscle strength the primary diagnostic parameter — verbatim: "muscle strength is presently the most reliable measure of muscle function." Probable sarcopenia is identified by low strength alone; confirmed sarcopenia adds low muscle quantity or quality; severe sarcopenia adds impaired physical performance. The diagnostic pathway is Find–Assess–Confirm–Severity (SARC-F screening → grip/chair stand → DXA/BIA → physical performance tests). The paper acknowledges that BIA prediction models are population-specific and that age and ethnicity should be considered, but does not provide an overall prevalence figure or specify a first-line treatment.
The answer
Strength first then mass + function
Primary criterion: low muscle strength · Confirmed: + low quantity/quality · Severe: + impaired performance
EWGSOP2 inverts the older mass-centric definition: low muscle strength is now the primary diagnostic parameter, with muscle quantity/quality and physical performance added for confirmed and severe categories. The diagnostic pathway uses the SARC-F screening questionnaire, grip strength or chair-stand testing, DXA or BIA for body composition, and physical performance tests for severity grading. The paper explicitly endorses considering age and ethnicity differences in BIA reference populations.
Training Science
What exercise modality works best for sarcopenia?
About this study
RCTs pooled
42 trials
Participants
3,728 median age 72.9
A network meta-analysis (which simultaneously compares all interventions in a single statistical model) of 42 randomized controlled trials of exercise interventions for sarcopenia, totaling 3,728 older adults at a median age of 72.9 years.
The finding
The clearest pattern is that combination interventions outperform single modalities. Resistance training with or without nutrition was strong, but the highest-ranked specific protocols paired resistance with balance training: handgrip strength was best improved by resistance + balance + nutrition (MD 4.19 kg), and gait speed by resistance + balance training (MD 0.16 m/s). The authors used GRADE to rate certainty by outcome — high-to-moderate overall, with high certainty specifically for the 5-repetition chair-stand test (a functional lower-body measure).
The answer
Resistance + balance often + nutrition
Handgrip MD 4.19 kg · Gait speed MD 0.16 m/s · GRADE: high-to-moderate certainty by outcome
The honest read of this network meta-analysis: resistance training is the foundation, but the strongest evidence is for protocols that combine resistance with balance training, and often with nutrition support. Pure resistance training works, but combination protocols achieved the largest improvements in handgrip strength, gait speed, and functional measures. The takeaway for older clients: a strength-only program is good, but adding balance work (and addressing protein intake) compounds the benefit.
Training Science
How effective is resistance training specifically for sarcopenic older adults?
About this study
RCTs pooled
22 trials
Participants
959 sarcopenic older adults
A meta-analysis of 22 randomized controlled trials (959 participants) testing resistance training specifically in older adults with diagnosed sarcopenia — a narrower and more clinically relevant population than the broader "older adults" literature.
The finding
Resistance training in sarcopenic older adults produced a large effect on handgrip strength (SMD 0.83) and a small effect on relative muscle mass (SMD 0.25). On the biomarker side, the picture is split: anti-inflammatory IL-10 (SMD 0.61) and the anabolic IGF-1 (SMD 0.70) both improved meaningfully, but RT did not significantly affect pro-inflammatory markers. The authors' subgroup analysis identified the optimal training protocol as 3 sets per session, 8–12 weeks duration, slower contraction speed, and moderate intensity (60–70% of 1RM) — notably not the high-intensity loading the broader resistance-training literature emphasizes for younger populations.
The answer
Strongly at moderate loads
Handgrip SMD 0.83 · Mass SMD 0.25 · Optimal: 3 sets, 60–70% 1RM, 8–12 weeks, slower tempo
Resistance training works for sarcopenic older adults — strongly for grip strength, modestly for muscle mass. The protocol that produced the largest gains in this meta-analysis isn't the high-intensity prescription often associated with younger lifters: it's 3 sets per session at moderate loads (60–70% 1RM), slower contraction speed, sustained over 8–12 weeks. Biomarker findings split: the anabolic and anti-inflammatory signals (IGF-1, IL-10) both improved, but pro-inflammatory markers were unaffected.