Smart Scales. How Accurate Are Bioelectrical Impedance Devices for Body Composition?
- Alastair Hunt
- Jun 5
- 7 min read
Updated: 6 days ago
Assessing body composition accurately is vital not only for clinical care but also for health-conscious individuals and athletes aiming to monitor nutrition, performance or treatment outcomes. With the rising popularity of home-use smart scale devices and clinical tools like bioelectrical impedance analysis (BIA), many are left wondering: how accurate are these methods and which can we trust?
As ever, please talk to your doctor or medical practitioner most familiar with your medical history before implementing any changes in diet, exercise or lifestyle, especially if you are under treatment. Links to all studies at bottom of page.
What Is Bioelectrical Impedance Analysis (BIA)?
BIA estimates body composition by sending a small electrical current through the body. Because water, muscle and fat conduct electricity differently, the resistance and reactance (how well your body’s cells store and respond to a small electrical signal) measured can be used to estimate fat mass, fat-free mass and other parameters such as total body water and body cell mass. However, accuracy depends heavily on the prediction equations embedded in the device software - and these equations vary widely.
Advanced forms of BIA offer deeper insights:
Segmental BIA measures different parts of the body (arms, legs, trunk) independently, helping identify regional variations in muscle or fat.
Localised BIA (L-BIA) focuses on specific areas—such as a recovering muscle—to assess healing and inflammation.
Bioelectrical Impedance Vector Analysis (BIVA) visualises raw impedance values on a graph to assess hydration and body cell mass, independent of prediction equations.
Phase angle (PhA), derived from resistance and reactance, reflects the integrity of cell membranes and fluid distribution. These advanced tools are increasingly used in sports science, rehabilitation, and clinical monitoring.
Consumer Smart Scales: Widespread Use, Mixed Evidence
Recent years have seen a rapid expansion in consumer-grade smart scales with BIA capabilities. A 2023 review by Johannessen et al. examined 165 smart scales from 72 brands, identifying that nearly all incorporated BIA to estimate fat, muscle, bone, and water mass. These devices, often paired with mobile apps, offer trend tracking and convenience that appeal to the general public.
However, accuracy remains a key concern. The review did not evaluate or rank brands based on measurement precision. Instead, it provided a broad overview of features and connectivity trends over time. Notably, Withings smart scales were the most frequently used in research (appearing in 13 studies), followed by Fitbit (used in 7 studies). Their popularity in research is likely due to data integration, connectivity, and availability—rather than demonstrated accuracy, which the review did not assess directly.
Supporting this, a 2021 study published in JMIR Mhealth Uhealth assessed three specific consumer smart scales: Body Partner (Téfal), DietPack (Terraillon), and Body Cardio (Nokia Withings). All three measured weight with high accuracy (within ±0.3 kg of DEXA), but showed significant errors in body composition estimates. Fat mass was typically underestimated, and muscle mass was inconsistently reported—overestimated in some models and underestimated in others. The study concluded that while these scales may be valuable for monitoring trends and self-motivation, they are not sufficiently accurate to replace clinical tools for body composition assessment.
Prediction Equations: The Underlying Variable That Matters
A major reason for variability in BIA accuracy is the prediction equation used to estimate body composition. These equations convert electrical impedance data into values like body fat percentage or muscle mass—but their reliability depends on how closely the person using the device resembles the population the equation was based on.
A 2024 systematic review identified over 100 validated BIA equations, many developed using healthy adult populations. Devices like the InBody 720 and Tanita models often embed these equations. However, not all devices disclose which equation they use. This matters because an equation developed for athletes, the elderly, or people with obesity might misrepresent body composition in someone who is fit, middle-aged, and generally healthy.
For healthy individuals, particularly those with a BMI between 20 and 30 and without extreme muscle mass or chronic illness, many commercial BIA devices can give reasonably accurate trend data. Johannessen et al. noted that major variables like fat percentage and muscle mass have remained consistent in smart scale designs since 2015, reinforcing their relevance for broad health tracking—though not for diagnostic precision.
For Older Women: Validation with DXA Offers Encouragement
A study involving older Mexican women found that multi-frequency BIA can provide fat mass estimates within 1% of DEXA values in women of average height (≥145 cm). This suggests that for middle-aged and older adults, BIA can be a valid tool for monitoring changes over time, especially when height and hydration status are taken into account.
Anthropometric equations (like those using BMI or waist circumference) performed less consistently in the same population. BIA offered a more accurate and accessible alternative, reinforcing its value for tracking changes due to lifestyle or ageing.
BIA for Athletes: Modern Tools, Clearer Data
Until 2016, most BIA equations were derived from general populations, leading to less accurate body composition estimates in athletes—whose higher muscle mass and lower fat levels often fall outside standard reference ranges. A 2021 narrative review highlighted how newer athlete-specific prediction equations, validated against DXA and isotope dilution, now offer improved accuracy.
Segmental and localised BIA tools enable precise tracking of muscle development, recovery, and asymmetries. BIVA and phase angle (PhA) are now common in sports labs for assessing hydration, cellular health, and readiness to train. These metrics are especially useful during intensive training or competition periods when overtraining and fatigue are risks.
How to Use BIA Devices Effectively: Practical Guidance for Everyday Users
If you're considering a BIA device—whether as part of a fitness routine, health management plan, or simple curiosity—there are several ways to ensure your experience is as accurate and useful as possible.
1. Know What You’re Measuring Understand that BIA provides estimates, not clinical diagnostics. Key outputs include body fat percentage, lean mass, water content, and sometimes bone or visceral fat estimates.
2. Use Consistent Testing Conditions To reduce variability, always measure under the same conditions—ideally in the morning, fasted, after using the toilet, and before exercise.
3. Choose the Right Device Foot-to-hand or segmental models are more reliable than foot-to-foot designs. Multi-frequency models offer greater insight, especially if you want to track fluid shifts or monitor training impact.
4. Interpret Trends, Not Absolutes Don’t fixate on single readings. Instead, use BIA to track changes over weeks or months. Improvements in body composition should align with lifestyle changes and performance goals.
5. Be Aware of Limitations Hydration, food intake, and exercise can all skew readings. BIA should not be used to diagnose health conditions or determine exact fat or muscle mass.
6. Supplement with Lifestyle Context BIA is most powerful when interpreted alongside other indicators: energy levels, performance, mood, and even how your clothes fit.
7. Avoid Overpromising Features Claims around visceral fat, "protein mass," or segmental analysis can be misleading if the underlying equations or methods are not transparent. Use these metrics for motivation, not diagnosis.
Final Thoughts
Bioelectrical impedance devices can be reliable and practical, especially when used with the right technology and equations. Clinical applications - from cancer to critical care - highlight BIA’s potential, but these studies also affirm its everyday utility. For healthy adults, particularly those between the ages of 25 and 65, BIA provides a non-invasive, accessible way to monitor body composition trends over time.
In short, BIA won’t replace clinical-grade assessments, but for the general population aiming to live healthier, it offers an easy and informative window into body composition.
Changing health for the better is about progress, not perfection, and even small changes can have a powerful and positive effect on health. For most people, improving health is about finding motivation and prioritising self-care - with an ultimate goal of taking action. If you want to take effective and targeted steps that fit into your unique lifestyle and circumstances, The Whole Health Practice is here to help.
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Alastair
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Related Studies and Resources
Campa F, Coratella G, Cerullo G, Noriega Z, Francisco R, Charrier D, Irurtia A, Lukaski H, Silva AM, Paoli A. High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review. J Transl Med. 2024 May 29;22(1):515. doi: 10.1186/s12967-024-05272-x. PMID: 38812005; PMCID: PMC11137940.
Branco MG, Mateus C, Capelas ML, Pimenta N, Santos T, Mäkitie A, Ganhão-Arranhado S, Trabulo C, Ravasco P. Bioelectrical Impedance Analysis (BIA) for the Assessment of Body Composition in Oncology: A Scoping Review. Nutrients. 2023 Nov 15;15(22):4792. doi: 10.3390/nu15224792. PMID: 38004186; PMCID: PMC10675768.
Johannessen E, Johansson J, Hartvigsen G, Horsch A, Årsand E, Henriksen A. Collecting health-related research data using consumer-based wireless smart scales. Int J Med Inform. 2023 May;173:105043. doi: 10.1016/j.ijmedinf.2023.105043. Epub 2023 Mar 14. PMID: 36934610.
Sardinha LB, Rosa GB. Phase angle, muscle tissue, and resistance training. Rev Endocr Metab Disord. 2023 Jun;24(3):393-414. doi: 10.1007/s11154-023-09791-8. Epub 2023 Feb 10. PMID: 36759377; PMCID: PMC10140117.
Velázquez-Alva MC, Irigoyen-Camacho ME, Zepeda-Zepeda MA, Rangel-Castillo I, Arrieta-Cruz I, Mendoza-Garcés L, Castaño-Seiquer A, Flores-Fraile J, Gutiérrez-Juárez R. Comparison of body fat percentage assessments by bioelectrical impedance analysis, anthropometrical prediction equations, and dual-energy X-ray absorptiometry in older women. Front Nutr. 2022 Dec 21;9:978971. doi: 10.3389/fnut.2022.978971. PMID: 36618693; PMCID: PMC9812576.
Campa F, Toselli S, Mazzilli M, Gobbo LA, Coratella G. Assessment of Body Composition in Athletes: A Narrative Review of Available Methods with Special Reference to Quantitative and Qualitative Bioimpedance Analysis. Nutrients. 2021 May 12;13(5):1620. doi: 10.3390/nu13051620. PMID: 34065984; PMCID: PMC8150618.
Moonen HPFX, Van Zanten ARH. Bioelectric impedance analysis for body composition measurement and other potential clinical applications in critical illness. Curr Opin Crit Care. 2021 Aug 1;27(4):344-353. doi: 10.1097/MCC.0000000000000840. PMID: 33967207; PMCID: PMC8270506.
Frija-Masson J, Mullaert J, Vidal-Petiot E, Pons-Kerjean N, Flamant M, d'Ortho MP. Accuracy of Smart Scales on Weight and Body Composition: Observational Study. JMIR Mhealth Uhealth. 2021 Apr 30;9(4):e22487. doi: 10.2196/22487. PMID: 33929337; PMCID: PMC8122302.
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