Can You Trust Bioimpedance To Measure Your Body Fat Percentage?

We have covered body composition methodologies on DN previously HERE, HERE, and HERE.

Today, we are going scorched earth on bioimpedance-based body composition data. DEXA is also going to catch some strays. They all will.

You will need to go to the site for the presentation or interactive charts to work. They will not work inside of the email.

Downloadable audio HERE

Bioimpedance analyzer precision & least significant change

Compiled from published precision studies. LSC (95%) = 2.77 × SEM. A measured change must exceed the LSC to be 95% confident a real biological change occurred.

Good Moderate Poor — caution

Same-day technical precision under controlled conditions — the best-case scenario for each device.

Device	Population	Measure	SEM / RMS SD	LSC (95%)	Author (year)
InBody 770	Healthy adults, n=67	%BF	SEM 0.77%	2.13%	Nickerson (2020)
InBody 770	Healthy adults	FM	SEM 0.54 kg	1.50 kg	Nickerson (2020)
InBody 770	Healthy adults	FFM	SEM 0.58 kg	1.61 kg	Nickerson (2020)
InBody 370S	Healthy adults, n=67	%BF	SEM 0.99%	2.73%	Nickerson (2020)
InBody 370S	Healthy adults	FM	SEM 0.87 kg	2.41 kg	Nickerson (2020)
InBody 370S	Healthy adults	FFM	SEM 0.84 kg	2.32 kg	Nickerson (2020)
InBody 230	Healthy adults, n=67	%BF	SEM 0.82%	2.27%	Nickerson (2020)
InBody 230	Healthy adults	FM	SEM 0.59 kg	1.63 kg	Nickerson (2020)
InBody 230	Healthy adults	FFM	SEM 0.62 kg	1.72 kg	Nickerson (2020)
BIS (general)	Athletic males, n=32, same-day	FM	~841 g	2,331 g	Farley (2021)
BIS (general)	Athletic males, same-day	FFM	~822 g	2,276 g	Farley (2021)
10 BIA devices^†	Healthy adults, n=73	%BF	PE 0.14–0.49%	0.38–1.36%	Siedler (2022)

Device	Population	Measure	SEM / RMS SD	LSC (95%)	Author (year)
InBody 770	Military, n=14, standardized	Mass (within-day)	0.0–0.2 kg	~0.6 kg	Looney (2024)
InBody 770	Military, standardized	Mass (between-day)	0.1–0.7 kg	~1.9 kg	Looney (2024)
InBody 770	Active adults, n=117, unstd.	Total FM	SD_diff 2.41 kg	4.72 kg	Potter (2025)
InBody 770	Active adults, unstandardized	Total FFM	SD_diff 4.08 kg	7.99 kg	Potter (2025)
InBody 770	Active adults, unstandardized	%BF	SD_diff 1.28%	2.51%	Potter (2025)
InBody 720	Healthy adults, n=80	%BF (same-day)	CV 2.97%	~8.2% rel.	McLester (2018)
InBody 720	Healthy adults	%BF (2-day)	CV 4.24%	~11.7% rel.	McLester (2018)
InBody 720	Rec. athletes, n=18, 24h std.	FFM, FM, TBW	Within ≈ between	No sig. diff.	Kasper (2023)
BIS (general)	Athletic males, consecutive-day	FM	~1,302 g	3,607 g	Farley (2021)
BIS (general)	Athletic males, consecutive-day	FFM	~1,432 g	3,966 g	Farley (2021)

Device	Population	Measure	Precision	LSC (95%)	Author (year)
InBody 270	Children 10–12y, n=127	Body comp	TEM 0.04–1.9%	ICC 0.98–1.00	Toselli (2021)
InBody 370	Pediatric obesity, n=43	%BF	—	1.5%	Harshman (2024)
InBody 370	Pediatric obesity	FMI	—	0.5 kg/m²	Harshman (2024)
InBody 370	Pediatric obesity	FFMI	—	0.3 kg/m²	Harshman (2024)
InBody S10	Healthy adults, n=55	Limb muscle	ICC 0.996–0.998	Excellent	Uchida (2025)
InBody S10	Healthy adults	Trunk PhA	ICC 0.854	Poor	Uchida (2025)
Smartwatch BIA	Adults, n=75	FFM	CV 1.3%	~3.6% rel.	Shepherd (2022)

InBody 230 ≈ InBody 770

Portable 230 is nearly indistinguishable from research-grade 770 on precision (Nickerson 2020)

No InBody 380 data exists

No published precision study for this model. Expect performance between 230 and 770.

LSC (95%) = 2.77 × SEM. Where only %CV was reported, absolute LSC depends on the individual's compartment mass. Values marked "~" are calculated from reported precision metrics rather than directly stated. Consecutive-day BIS LSC in athletes is 50% worse than same-day, confirming biological variability as the dominant error source. Sources: Nickerson (2020), Farley (2021), Tinsley (2022), Looney (2024), Potter (2025), McLester (2018), Kasper (2023), Toselli (2021), Harshman (2024), Uchida (2025), Shepherd (2022). ^†10 of 15 BIA devices in Siedler & Tinsley (2022); 5 foot-to-foot scales excluded for caching results on immediate retest (see Fig. 1).

Maybe the most damning sub-analysis I have ever done. BIA in unstandardized to unstandardized conditions is worse than worthless.

Field LSC: InBody 770 vs DXA under real-world conditions

Derived from Potter et al. (2025) — 1,000 US Marines, 117 retested at 5–7 days, unstandardized conditions

ICC reported

0.994

→

Actual field LSC

4.72 kg

An ICC of 0.994 for total fat sounds nearly perfect — but it translates to a field LSC of 4.72 kg. The ICC is inflated by pooling men + women (huge between-subject variance). The SD of differences is the actionable number.

Conversion: Field PE = SD_diff / √2 → Field LSC (95%) = 2.77 × PE = 1.96 × SD_diff

Good Moderate Poor — caution

Compartment	Unit	ICC	SD_diff	Field PE	Field LSC	Meaning
Arm fat	kg	0.995	0.43	0.30	0.84	> 0.8 kg = real
Leg fat	kg	0.990	0.78	0.55	1.53	> 1.5 kg = real
Trunk fat	kg	0.993	1.48	1.05	2.90	> 2.9 kg = real
Relative %BF	%	0.993	1.28	0.91	2.51	> 2.5% BF = real
VAT	cm²	0.993	6.23	4.41	12.2	> 12 cm² = real
Total fat	kg	0.994	2.41	1.70	4.72	> 4.7 kg = real
Total FFM	kg	0.994	4.08	2.89	7.99	> 8.0 kg = real
TBW	L	0.995	2.59	1.83	5.07	> 5.1 L = real
ICW	L	0.996	1.57	1.11	3.08	> 3.1 L = real
ECW	L	0.993	1.12	0.79	2.19	> 2.2 L = real

Compartment	Unit	ICC	SD_diff	Field PE	Field LSC	Meaning
Arm fat	kg	0.990	0.15	0.11	0.29	> 0.3 kg = real
Leg fat	kg	0.990	0.47	0.33	0.92	> 0.9 kg = real
Trunk fat	kg	0.997	0.48	0.34	0.94	> 0.9 kg = real
Relative %BF	%	0.996	0.95	0.67	1.86	> 1.9% BF = real
VAT	cm²	0.995	6.45	4.56	12.6	> 12.6 cm² = real
Total fat	kg	0.998	0.61	0.43	1.19	> 1.2 kg = real
Total FFM	kg	0.995	1.52	1.07	2.98	> 3.0 kg = real

Compartment	DXA LSC	InBody LSC	Ratio	Practical meaning
Arm fat	0.29 kg	0.84 kg	2.9×	BIA needs ~3× more change
Leg fat	0.92 kg	1.53 kg	1.7×	BIA needs ~2× more change
Trunk fat	0.94 kg	2.90 kg	3.1×	BIA needs ~3× more change
%BF	1.86%	2.51%	1.3×	Comparable — closest match
VAT	12.6 cm²	12.2 cm²	1.0×	Nearly identical (both poor vs MRI)
Total fat	1.19 kg	4.72 kg	4.0×	BIA needs 4× more change
Total FFM	2.98 kg	7.99 kg	2.7×	BIA needs ~8 kg change

Data derived from Table 3 of Potter et al. (2025), European Journal of Clinical Nutrition. n = 117 (100M, 17W), 5–7 day retest, unstandardized conditions. InBody 770 vs GE Lunar iDXA. Field LSC = 2.77 × (SD_diff / √2).

Let's cherry-pick the other way...kind of.

Within-lab precision: 14 body composition methods

Same-session duplicate test reliability from Tinsley et al. (2021). Resistance-trained males, n=18. TEM = technical error of measurement (RMS-SD method). LSC (95%) = 2.77 × TEM. All assessments standardised (overnight fasted, rested) with repositioning between duplicates.

<0.5 kg / <0.5% 0.5–1.0 kg / 0.5–1.0% >1.0 kg / >1.0%

Fat-free mass precision — sorted by TEM (best to worst).

Method	Category	ICC	TEM (kg)	LSC (kg)	%CV
BIS (SFB7)	Bioimpedance	1.000	0.04	0.11	0.09%
Seca mBCA 515	MF-BIA	1.000	0.14	0.39	0.26%
InBody 770	MF-BIA	1.000	0.19	0.53	0.37%
SFBIA (RJL)	SF-BIA	0.999	0.30	0.83	0.56%
Non-bioimpedance comparators
DXA (GE Lunar)	X-ray	0.999	0.42	1.16	0.76%
4C model	Criterion	0.999	0.44	1.22	0.83%
ADP (BOD POD)	Plethysmography	0.999	0.47	1.30	0.90%
3DO Styku	3D scan	0.999	0.41	1.14	0.73%
3DO SizeStream	3D scan	0.997	0.58	1.61	1.11%
3DO Fit3D	3D scan	0.999	0.88	2.44	0.75%
DoD/Army eq.	Anthropometry	0.994	0.93	2.58	1.55%

Method	Category	ICC	TEM (kg)	LSC (kg)	%CV
BIS (SFB7)	Bioimpedance	1.000	0.04	0.11	0.29%
Seca mBCA 515	MF-BIA	0.999	0.14	0.39	0.92%
InBody 770	MF-BIA	0.999	0.20	0.55	1.32%
SFBIA (RJL)	SF-BIA	0.997	0.30	0.83	2.05%
Non-bioimpedance comparators
DXA (GE Lunar)	X-ray	0.994	0.37	1.02	2.40%
4C model	Criterion	0.995	0.44	1.22	2.90%
ADP (BOD POD)	Plethysmography	0.994	0.47	1.30	3.16%
3DO Styku	3D scan	0.992	0.44	1.22	4.23%
3DO SizeStream	3D scan	0.986	0.58	1.61	3.89%
3DO Fit3D	3D scan	0.992	0.84	2.33	2.59%
DoD/Army eq.	Anthropometry	0.977	0.94	2.60	6.45%

Method	Category	ICC	TEM (%)	LSC (%)
BIS (SFB7)	Bioimpedance	1.000	0.06	0.17
Seca mBCA 515	MF-BIA	0.999	0.20	0.55
InBody 770	MF-BIA	0.999	0.29	0.80
SFBIA (RJL)	SF-BIA	0.997	0.30	0.83
Non-bioimpedance comparators
DXA (GE Lunar)	X-ray	0.996	0.54	1.50
4C model	Criterion	0.995	0.64	1.77
ADP (BOD POD)	Plethysmography	0.994	0.71	1.97
3DO Fit3D	3D scan	0.993	0.57	1.58
3DO Styku	3D scan	0.994	0.73	2.02
3DO SizeStream	3D scan	0.986	0.85	2.35
DoD/Army eq.	Anthropometry	0.978	1.17	3.24

Method	ΔFFM	ΔFM	ΔBF%	Verdict
DXA (GE Lunar)	p=0.44	p=0.33	p=0.58	ROBUST 3/3
DoD/Army eq.	p=1.00	p=0.18	p=0.41	ROBUST 3/3
SFBIA (RJL)	p=0.004	p=0.59	p=0.59	PARTIAL 2/3
3DO Styku	p=0.98	p<0.001	p<0.001	PARTIAL 1/3
3DO SizeStream	p=0.64	p<0.001	p<0.001	PARTIAL 1/3
Sensitive to standardisation (all 3 compartments distorted)
BIS (SFB7)	p<0.001	p<0.001	p<0.001	SENSITIVE 0/3
Seca mBCA 515	p<0.001	p<0.001	p<0.001	SENSITIVE 0/3
InBody 770	p<0.001	p<0.001	p<0.001	SENSITIVE 0/3
4C model	p<0.001	p=0.003	p=0.001	SENSITIVE 0/3
ADP (BOD POD)	p=0.012	p=0.022	p=0.022	SENSITIVE 0/3
3DO Fit3D	p=0.037	p<0.001	p<0.001	SENSITIVE 0/3

BIS « standing BIA

Supine BIS TEM is 3–5× lower than standing MF-BIA for FM and FFM. This reflects the supine electrode protocol eliminating postural fluid shifts.

InBody 770 ≈ Seca mBCA

Both research-grade octapolar devices produce sub-0.6 kg LSC for FM and FFM. InBody 770 is slightly noisier for %BF (0.80 vs 0.55%).

BIA beats DXA on same-session precision

All 4 bioimpedance devices had lower same-session TEM than DXA for FM and FFM. DXA’s advantage appears in field/multi-day robustness, not technical repeatability.

3DO & anthropometry are noisiest

3D optical scanners and the DoD body-fat equation show the widest LSC ranges, likely due to posture variation and measurement site inconsistency.

Source: Tinsley et al. (2021) “Tracking changes in body composition: comparison of methods and influence of pre-assessment standardisation.” Br J Nutr 127:1656–1674. Table 1. Resistance-trained males, n=18. TEM = √(ΣD²/2n). LSC (95%) = 2.77 × TEM. Duplicate tests with repositioning on a single standardised visit. The 4C criterion model uses ADP body volume + BIS total body water + DXA bone mineral. This table excludes the three multi-component sub-models (4C_DXA, 3C_Siri, 3C_Loh) which had TEM 0.40–0.62 kg.

All of them in one chart!

Cross-method body composition precision & LSC

Compiled from published precision studies across BIA, DXA, 3D optical, skinfolds, ultrasound, and MRI. LSC (95%) = 2.77 × SEM. A measured change must exceed the LSC to confirm real biological change at 95% confidence.

Good Moderate Poor Same-day Consec/field

Method	Sample	n	Sex	Measure	SEM / PE	LSC (95%)	Condition	Author (year)
DXA
DXA	Resistance-trained athletes	32	M	FM	PE 435 g	1,204 g	Same-day	Farley (2021)
DXA	Resistance-trained athletes	32	M	FM	PE 583 g	1,615 g	Consec-day	Farley (2021)
DXA	Resistance-trained athletes	32	M	FFM	PE 527 g	1,461 g	Same-day	Farley (2021)
DXA	Resistance-trained athletes	32	M	FFM	PE 710 g	1,967 g	Consec-day	Farley (2021)
DXA	Resistance-trained athletes	21	M/F	FM	PE 660 g	1,829 g	Same-day	Zemski (2019)
DXA	Resistance-trained athletes	21	M/F	FM	PE 1,261 g	3,493 g	Consec-day	Zemski (2019)
DXA	Resistance-trained athletes	21	M/F	LM	PE 617 g	1,709 g	Same-day	Zemski (2019)
DXA	Resistance-trained athletes	21	M/F	LM	PE 2,083 g	5,770 g	Consec-day	Zemski (2019)
DXA (iDXA)	Healthy subjects	30	M/F	FM	CV 0.40–0.88%	484 g	Same-day	Henriksen (2021)
DXA (iDXA)	Healthy subjects	30	M/F	LM	—	618 g	Same-day	Henriksen (2021)
DXA (iDXA)	Active adults, unstd.	117	86M/17F	%BF	SD 0.95%	1.86%	Field	Potter (2025)
DXA (iDXA)	Active adults, unstd.	117	86M/17F	FM	SD 0.61 kg	1,190 g	Field	Potter (2025)
DXA (iDXA)	Active adults, unstd.	117	86M/17F	FFM	SD 1.52 kg	2,980 g	Field	Potter (2025)
BIA / BIS
InBody 770	Healthy adults	67	31M/36F	%BF	SEM 0.77%	2.13%	Same-day	Nickerson (2020)
InBody 770	Healthy adults	67	31M/36F	FM	SEM 0.54 kg	1,500 g	Same-day	Nickerson (2020)
InBody 770	Healthy adults	67	31M/36F	FFM	SEM 0.58 kg	1,610 g	Same-day	Nickerson (2020)
InBody 770	Military, standardized	14	M/F	All comps	ICC ≥0.999	~0.6 kg	Same-day	Looney (2024)
InBody 770	Active adults, unstd.	117	100M/17F	%BF	SD 1.28%	2.51%	Field	Potter (2025)
InBody 770	Active adults, unstd.	117	100M/17F	FM	SD 2.41 kg	4,720 g	Field	Potter (2025)
InBody 770	Active adults, unstd.	117	100M/17F	FFM	SD 4.08 kg	7,990 g	Field	Potter (2025)
InBody 370S	Healthy adults	67	31M/36F	%BF	SEM 0.99%	2.73%	Same-day	Nickerson (2020)
InBody 230	Healthy adults	67	31M/36F	%BF	SEM 0.82%	2.27%	Same-day	Nickerson (2020)
BIS (general)	Athletic males	32	M	FM	~841 g	2,331 g	Same-day	Farley (2021)
BIS (general)	Athletic males	32	M	FM	~1,302 g	3,607 g	Consec-day	Farley (2021)
BIS (general)	Athletic males	32	M	FFM	~822 g	2,276 g	Same-day	Farley (2021)
BIS (general)	Athletic males	32	M	FFM	~1,432 g	3,966 g	Consec-day	Farley (2021)
10 BIA devices^†	Healthy adults	73	M/F	%BF	PE 0.14–0.49%	0.38–1.36%	Same-day	Tinsley (2022)
3D optical
3DO (4 scanners)	Healthy adults	139	M/F	%BF	RMS-CV 2.3–4.3%	~6.4–11.9%	Same-day	Tinsley (2020)
3DO (4 scanners)	Healthy adults	139	M/F	FM	RMS-CV 2.5–4.3%	~6.9–11.9%	Same-day	Tinsley (2020)
3DO (4 scanners)	Healthy adults	139	M/F	FFM	RMS-CV 0.7–1.4%	~1.9–3.9%	Same-day	Tinsley (2020)
3DO (Styku)	Healthy adults	188	102F/86M	FM	RMSE 0.41 kg	~1,140 g	Same-day	Shepherd (2021)
3DO (Styku)	Healthy adults	188	102F/86M	%BF	RMSE 0.60%	~1.66%	Same-day	Shepherd (2021)
3DO (shape PCs)	Healthy adults	407	M/F	FM	RMSE 0.81 kg (M)	~1.8–2.2 kg	Same-day	Heymsfield (2019)
3DO+BIA (5C)	Adults + athletes	67	31F/36M	FFM	RMSE 0.73 kg	~2,020 g	Same-day	Graybeal (2023)
3DO (Fit3D)	Intervention studies	133	45F/88M	FM change	RMSE 1.98–2.31 kg	—	Field	Harty (2022)
Skinfolds
Skinfolds (SA)	Athletic males	32	M	FM	—	586 g	Same-day	Farley (2021)
Skinfolds (SA)	Athletic males	32	M	FM	—	442 g	Consec-day	Farley (2021)
Skinfolds (SA)	Athletic males	32	M	FFM	—	568 g	Same-day	Farley (2021)
Skinfolds (SA)	Athletic males	32	M	FFM	—	1,159 g	Consec-day	Farley (2021)
Skinfolds (caliper)	Healthy adults	49	M/F	%BF	SEM 0.63%	~1.75%	Same-day	Totosy de Zepetnek (2021)
Skinfolds (inter-rater)	Mixed	20	M/F	%BF	ICC 0.62–0.91	Variable	Same-day	Lohman (1987)
Ultrasound
B-mode US (IOC)	Elite athletes	76	39F/37M	Σ8 SAT	LOA 1.2 mm	~0.2 kg FM	Field	Wagner (2019)
A-mode US (BM)	Healthy adults	144	81M/63F	%BF	TEM 0.89–1.07%	2.47–3.43%	Same-day	Júnior (2020)
A-mode US (BM)	NCAA D-I athletes	45	22M/23F	%BF	ICC ≥0.996	TE 4.4%	Same-day	Smith-Ryan (2016)
A-mode US (BM)	Healthy adults	49	M/F	%BF	SEM 0.78%	~2.16%	Same-day	Totosy de Zepetnek (2021)
US (novice inter-rater)	College students	80	48M/32F	%BF	ICC 0.975–0.990	—	Same-day	Rodriguez (2020)
MRI
MRI (3T Dixon)	Postmenopausal women	36	F	Fat comps	CV 1.1–1.5%	—	Same-day	West (2018)
MRI (3T Dixon)	Postmenopausal women	36	F	Muscle groups	CV 0.8–1.9%	—	Same-day	West (2018)
MRI (multi-scanner)	Healthy adults	18	M/F	VAT	Rep. 13 cL	Repro. 24 cL	Same-day	Leinhard (2020)
MRI (multi-scanner)	Healthy adults	18	M/F	Thigh muscle	Rep. 17 cL	Repro. 31 cL	Same-day	Leinhard (2020)
MRI (UK Biobank)	Adults	4,905	M/F	VAT/SAT/SM	CoV ≤3.8%	ICC ≥0.96	Same-day	Wilkinson (2025)
MRI (0.55T)	Healthy adults	10	5M/5F	VAT	CV 2.2%	Rep. 11.8 cL	Same-day	Chaudhari (2023)

Method	Sample	n	Sex	Measure	SEM / PE	LSC (95%)	Condition	Author (year)
DXA
DXA	Resistance-trained athletes	32	M	FM	PE 435 g	1,204 g	Same-day	Farley (2021)
DXA	Resistance-trained athletes	32	M	FM	PE 583 g	1,615 g	Consec-day	Farley (2021)
DXA	Resistance-trained athletes	32	M	FFM	PE 527 g	1,461 g	Same-day	Farley (2021)
DXA	Resistance-trained athletes	32	M	FFM	PE 710 g	1,967 g	Consec-day	Farley (2021)
DXA	Resistance-trained athletes	21	M/F	FM	PE 660 g	1,829 g	Same-day	Zemski (2019)
DXA	Resistance-trained athletes	21	M/F	FM	PE 1,261 g	3,493 g	Consec-day	Zemski (2019)
DXA	Resistance-trained athletes	21	M/F	LM	PE 617 g	1,709 g	Same-day	Zemski (2019)
DXA	Resistance-trained athletes	21	M/F	LM	PE 2,083 g	5,770 g	Consec-day	Zemski (2019)
DXA (iDXA)	Healthy subjects	30	M/F	FM	CV 0.40–0.88%	484 g	Same-day	Henriksen (2021)
DXA (iDXA)	Healthy subjects	30	M/F	LM	—	618 g	Same-day	Henriksen (2021)
DXA (iDXA)	Active adults, unstd.	117	86M/17F	%BF	SD 0.95%	1.86%	Field	Potter (2025)
DXA (iDXA)	Active adults, unstd.	117	86M/17F	FM	SD 0.61 kg	1,190 g	Field	Potter (2025)
DXA (iDXA)	Active adults, unstd.	117	86M/17F	FFM	SD 1.52 kg	2,980 g	Field	Potter (2025)

Method	Sample	n	Sex	Measure	SEM / PE	LSC (95%)	Condition	Author (year)
BIA / BIS
InBody 770	Healthy adults	67	31M/36F	%BF	SEM 0.77%	2.13%	Same-day	Nickerson (2020)
InBody 770	Healthy adults	67	31M/36F	FM	SEM 0.54 kg	1,500 g	Same-day	Nickerson (2020)
InBody 770	Healthy adults	67	31M/36F	FFM	SEM 0.58 kg	1,610 g	Same-day	Nickerson (2020)
InBody 770	Military, standardized	14	M/F	All comps	ICC ≥0.999	~0.6 kg	Same-day	Looney (2024)
InBody 770	Active adults, unstd.	117	100M/17F	%BF	SD 1.28%	2.51%	Field	Potter (2025)
InBody 770	Active adults, unstd.	117	100M/17F	FM	SD 2.41 kg	4,720 g	Field	Potter (2025)
InBody 770	Active adults, unstd.	117	100M/17F	FFM	SD 4.08 kg	7,990 g	Field	Potter (2025)
InBody 370S	Healthy adults	67	31M/36F	%BF	SEM 0.99%	2.73%	Same-day	Nickerson (2020)
InBody 230	Healthy adults	67	31M/36F	%BF	SEM 0.82%	2.27%	Same-day	Nickerson (2020)
BIS (general)	Athletic males	32	M	FM	~841 g	2,331 g	Same-day	Farley (2021)
BIS (general)	Athletic males	32	M	FM	~1,302 g	3,607 g	Consec-day	Farley (2021)
BIS (general)	Athletic males	32	M	FFM	~822 g	2,276 g	Same-day	Farley (2021)
BIS (general)	Athletic males	32	M	FFM	~1,432 g	3,966 g	Consec-day	Farley (2021)
10 BIA devices^†	Healthy adults	73	M/F	%BF	PE 0.14–0.49%	0.38–1.36%	Same-day	Tinsley (2022)

Method	Sample	n	Sex	Measure	SEM / PE	LSC (95%)	Condition	Author (year)
3D optical
3DO (4 scanners)	Healthy adults	139	M/F	%BF	RMS-CV 2.3–4.3%	~6.4–11.9%	Same-day	Tinsley (2020)
3DO (4 scanners)	Healthy adults	139	M/F	FM	RMS-CV 2.5–4.3%	~6.9–11.9%	Same-day	Tinsley (2020)
3DO (4 scanners)	Healthy adults	139	M/F	FFM	RMS-CV 0.7–1.4%	~1.9–3.9%	Same-day	Tinsley (2020)
3DO (Styku)	Healthy adults	188	102F/86M	FM	RMSE 0.41 kg	~1,140 g	Same-day	Shepherd (2021)
3DO (Styku)	Healthy adults	188	102F/86M	%BF	RMSE 0.60%	~1.66%	Same-day	Shepherd (2021)
3DO (shape PCs)	Healthy adults	407	M/F	FM	RMSE 0.81 kg (M)	~1.8–2.2 kg	Same-day	Heymsfield (2019)
3DO+BIA (5C)	Adults + athletes	67	31F/36M	FFM	RMSE 0.73 kg	~2,020 g	Same-day	Graybeal (2023)
3DO (Fit3D)	Intervention studies	133	45F/88M	FM change	RMSE 1.98–2.31 kg	—	Field	Harty (2022)

Method	Sample	n	Sex	Measure	SEM / PE	LSC (95%)	Condition	Author (year)
Skinfolds
Skinfolds (SA)	Athletic males	32	M	FM	—	586 g	Same-day	Farley (2021)
Skinfolds (SA)	Athletic males	32	M	FM	—	442 g	Consec-day	Farley (2021)
Skinfolds (SA)	Athletic males	32	M	FFM	—	568 g	Same-day	Farley (2021)
Skinfolds (SA)	Athletic males	32	M	FFM	—	1,159 g	Consec-day	Farley (2021)
Skinfolds (caliper)	Healthy adults	49	M/F	%BF	SEM 0.63%	~1.75%	Same-day	Totosy de Zepetnek (2021)
Skinfolds (inter-rater)	Mixed	20	M/F	%BF	ICC 0.62–0.91	Variable	Same-day	Lohman (1987)

Method	Sample	n	Sex	Measure	SEM / PE	LSC (95%)	Condition	Author (year)
Ultrasound
B-mode US (IOC)	Elite athletes	76	39F/37M	Σ8 SAT	LOA 1.2 mm	~0.2 kg FM	Field	Wagner (2019)
A-mode US (BM)	Healthy adults	144	81M/63F	%BF	TEM 0.89–1.07%	2.47–3.43%	Same-day	Júnior (2020)
A-mode US (BM)	NCAA D-I athletes	45	22M/23F	%BF	ICC ≥0.996	TE 4.4%	Same-day	Smith-Ryan (2016)
A-mode US (BM)	Healthy adults	49	M/F	%BF	SEM 0.78%	~2.16%	Same-day	Totosy de Zepetnek (2021)
US (novice inter-rater)	College students	80	48M/32F	%BF	ICC 0.975–0.990	—	Same-day	Rodriguez (2020)

Method	Sample	n	Sex	Measure	SEM / PE	LSC (95%)	Condition	Author (year)
MRI
MRI (3T Dixon)	Postmenopausal women	36	F	Fat comps	CV 1.1–1.5%	—	Same-day	West (2018)
MRI (3T Dixon)	Postmenopausal women	36	F	Muscle groups	CV 0.8–1.9%	—	Same-day	West (2018)
MRI (multi-scanner)	Healthy adults	18	M/F	VAT	Rep. 13 cL	Repro. 24 cL	Same-day	Leinhard (2020)
MRI (multi-scanner)	Healthy adults	18	M/F	Thigh muscle	Rep. 17 cL	Repro. 31 cL	Same-day	Leinhard (2020)
MRI (UK Biobank)	Adults	4,905	M/F	VAT/SAT/SM	CoV ≤3.8%	ICC ≥0.96	Same-day	Wilkinson (2025)
MRI (0.55T)	Healthy adults	10	5M/5F	VAT	CV 2.2%	Rep. 11.8 cL	Same-day	Chaudhari (2023)

LSC (95%) = 2.77 × SEM. Values marked ~ are derived from reported CV or SD_diff. Color reflects practical utility: green ≤ 2 kg or ≤ 2.5% BF; amber ≤ 4 kg or ≤ 4% BF; red > 4 kg or > 4% BF. Condition: same-day = controlled technical precision; consec-day/field = includes biological variability. Sources: Farley (2021), Zemski (2019), Henriksen (2021), Potter (2025), Nickerson (2020), Looney (2024), Tinsley (2020, 2022). ^†10 of 15 devices; 5 foot-to-foot scales excluded for caching results on immediate retest (Siedler & Tinsley 2022, Fig. 1), Shepherd (2021), Heymsfield (2019), Graybeal (2023), Harty (2022), Totosy de Zepetnek (2021), Lohman (1987), Wagner (2019), Júnior (2020), Smith-Ryan (2016), West (2018), Leinhard (2020), Wilkinson (2025), Chaudhari (2023).

If you are an athlete, a lot of these studies are not you, and the modeling equations are not built on data that represents you. So below is a calculator that you can use to calculate your own technical and biological variance. It involves taking two back-to-back measurements for at least five days.

I would run some iteration of this on both sides of an intervention, which we have covered HERE in an Excel sheet.

LSC calculator

Enter two back-to-back measurements per day for up to 10 days. The calculator derives your device’s precision error and the minimum change needed to confirm a real biological change.

Compartment label

Unit

Confidence

Day	Scan 1	Scan 2	Diff
1			—
2			—
3			—
4			—
5			—
6			—
7			—
8			—
9			—
10			—

Enter at least 2 complete pairs to calculate.

ISCD-recommended RMS-SD method. Technical error: RMS-SD of within-pair differences; SEM_tech = RMS-SD / √2. Biological variation: σ²_bio = Var(daily pair means) − σ²_tech/2 (requires ≥3 days). Total field SEM = √(σ²_tech + σ²_bio). LSC multipliers: 80% = 1.81, 95% = 2.77, 99% = 3.64. If biological variance estimate is negative (tech error dominates), SD_bio is set to 0.

Additionally, a lot of people also aren't running these on standardized conditions even when they might think they are. If you run body comp testing at the end of a cut compared to the beginning and carb intake is not the same...not the same conditions. In this scenario, if you are attempting to pick up small changes, I would recommend spending some time refeeding to maintenance before re-testing.

So can you trust bioimpedance to measure your body fat percentage?

Perhaps, and it depends on your use case/degree of change, your ability to standardize the measurement, and the device in question.

TL;DR - You can use this article as a place to start when assessing how and when to use different body composition assessment technologies based on your potential adaptation and the time domain. The goal of this entire deep dive was to help people bring intentionality to how they collect and interpret this data. Whenever possible, I would recommend calculating one's own LSC based on how stable the metric is for them and utilizing raw data over models that are likely not built on an athletic population.

REFERENCES:

Chaudhari AS, Huo D, Broseus A, et al. Low-field MRI body composition: validation against 3.0T and potential for broad clinical use. Magn Reson Med. 2023;90(4):1478-1492. doi:10.1002/mrm.29746

Farley A, Slater GJ, Hind K. Short-term precision error of body composition assessment methods in resistance-trained male athletes. Int J Sport Nutr Exerc Metab. 2021;31(1):55-65. doi:10.1123/ijsnem.2020-0061

Graybeal AJ, Brandner CF, Engel AK, et al. Combining three-dimensional optical imaging and bioelectrical impedance analysis: validation of a novel five-component body composition model. Clin Nutr. 2023;42(11):2171-2179. doi:10.1016/j.clnu.2023.09.011

Harshman SG, Hall KD, Engel AK, et al. Validation of bioelectrical impedance analysis for body composition assessment in children with obesity. J Clin Densitom. 2024;27(2):101478. doi:10.1016/j.jocd.2024.101478

Harty PS, Sieglinger B, Rodriguez C, et al. Comparison of three-dimensional optical scanning for longitudinal body composition assessment. Am J Clin Nutr. 2022;115(3):874-884. doi:10.1093/ajcn/nqab381

Henriksen HB, Alavi DH, Blomhoff R. Precision of Lunar dual-energy X-ray absorptiometry (iDXA) in measuring body composition among colorectal cancer patients and healthy subjects. Clin Nutr ESPEN. 2021;44:443-449. doi:10.1016/j.clnesp.2021.05.016

Heymsfield SB, Bourgeois B, Ng BK, Sommer MJ, Li J, Shepherd JA. Digital anthropometry: a critical review. Eur J Clin Nutr. 2018;72(5):680-687. doi:10.1038/s41430-017-0072-0

Hind K, Slater G, Oldroyd B, et al. Interpretation of dual-energy X-ray absorptiometry-derived body composition change in athletes: a review and recommendations for best practice. J Clin Densitom. 2018;21(3):429-443. doi:10.1016/j.jocd.2018.01.002

Kasper AM (Herberts T, Slater GJ, Farley A, Hogarth L, Areta JL, Paulsen G, Garthe I). Protocol standardization may improve precision error of InBody 720 body composition analysis. Int J Sport Nutr Exerc Metab. 2023;33(4):222-229. doi:10.1123/ijsnem.2022-0219

Leinhard OD (Borga M, Ahlgren A, Romu T, Widholm P, Dahlqvist Leinhard O, West J). Reproducibility and repeatability of MRI-based body composition analysis. Magn Reson Med. 2020;84(6):3146-3156. doi:10.1002/mrm.28387

Lohman TG. Skinfolds and body density and their relation to body fatness: a review. Hum Biol. 1981;53(2):181-225.

Looney DP, Schafer EA, Chapman CL, Pryor RR, Potter AW, Roberts BM, Friedl KE. Reliability, biological variability, and accuracy of multi-frequency bioelectrical impedance analysis for measuring body composition components. Front Nutr. 2024;11:1491931. doi:10.3389/fnut.2024.1491931

McLester CN, Nickerson BS, Kliszczewicz BM, McLester JR. Reliability and agreement of various InBody body composition analyzers as compared to dual-energy X-ray absorptiometry in healthy men and women. J Clin Densitom. 2020;23(3):443-450. doi:10.1016/j.jocd.2018.10.008

Miclos-Balica M, Muntean P, Schick F, et al. Reliability of body composition assessment using A-mode ultrasound in a heterogeneous sample. Eur J Clin Nutr. 2021;75:482-488. doi:10.1038/s41430-020-00743-y

Potter AW, Nindl LJ, Soto LD, et al. Multi-frequency bioelectrical impedance analysis as a surrogate for dual-energy X-ray absorptiometry body composition assessment: a military field study. US Army USARIEM Technical Report. 2025.

Rodriguez C (Wagner DR, Teramoto M). Interrater reliability of novice examiners using A-mode ultrasound and skinfolds to measure subcutaneous body fat. PLoS One. 2020;15(12):e0244019. doi:10.1371/journal.pone.0244019

Shepherd JA, Ng BK, Sommer MJ, et al. Body composition by DXA and 3D optical surface scanning. Obesity (Silver Spring). 2021;29(8):1377-1385. doi:10.1002/oby.23199

Shepherd JA, Sommer MJ, Engel AK, et al. Smartwatch bioelectrical impedance analysis for body composition assessment. Eur J Clin Nutr. 2022;76(11):1586-1593.

Siedler MR, Rodriguez C, Stratton MT, et al. Assessing the reliability and cross-sectional and longitudinal validity of fifteen bioelectrical impedance analysis devices. Br J Nutr. 2023;130(5):827-840. doi:10.1017/S0007114522003749

Smith-Ryan AE, Blue MNM, Trexler ET, Hirsch KR. Utility of ultrasound for body fat assessment: validity and reliability compared to a multicompartment criterion. Clin Physiol Funct Imaging. 2018;38(2):220-226. doi:10.1111/cpf.12402

Tinsley GM, Harty PS, Stratton MT, Smith RW, Rodriguez C, Siedler MR. Tracking changes in body composition: comparison of methods and influence of pre-assessment standardisation. Br J Nutr. 2022;127(11):1656-1674. doi:10.1017/S0007114521002579

Tinsley GM, Moore ML, Benavides ML, et al. 3-Dimensional optical scanning for body composition assessment: a 4-component model comparison of four commercially available scanners. Clin Nutr. 2020;39(10):3160-3167. doi:10.1016/j.clnu.2020.02.008

Toselli S, Campa F, Maietta Latessa P, et al. Accuracy and reliability of the InBody 270 multi-frequency body composition analyser in 10-12-year-old children. PLoS One. 2021;16(3):e0248304. doi:10.1371/journal.pone.0248304

Totosy de Zepetnek JO, Lee JJ, Boateng T, et al. Test-retest reliability and validity of body composition methods in adults. Clin Physiol Funct Imaging. 2021;41(5):417-425. doi:10.1111/cpf.12716

Uchida K, et al. Reliability of segmental bioelectrical impedance analysis with InBody S10 in healthy adults. 2025.

Wagner DR, Teramoto M. B-mode ultrasound body composition assessment: IOC protocol precision in elite athletes. Sports Med. 2019;49(4):533-543.

West J, Romu T, Thorell S, et al. Precision of MRI-based body composition measurements of postmenopausal women. PLoS One. 2018;13(2):e0192495. doi:10.1371/journal.pone.0192495

Wilkinson T, et al. Automated MRI body composition quantification in the UK Biobank imaging study. Abdom Radiol. 2025.

Zemski AJ, Hind K, Keating SE, Broad EM, Marsh DJ, Slater GJ. Same-day vs consecutive-day precision error of dual-energy X-ray absorptiometry for interpreting body composition change in resistance-trained athletes. J Clin Densitom. 2019;22(1):104-114. doi:10.1016/j.jocd.2018.10.005

Dr. Ben House

House has a PhD in Nutritional Sciences from UT-Austin and has been working in nutrition and fitness for over 15 years. He has numerous publications in peer-reviewed scientific journals.

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