Introduction
Aging represents a growing challenge in public health, including the early detection of malnutrition in older adults. This condition, frequently underdiagnosed, negatively impacts functionality, quality of life, and clinical prognosis. Traditional methods of nutritional assessment, focused on body mass index (BMI), medical history and anthropometry, are insufficient to identify metabolic and cellular alterations in subclinical stages. In this context, multi-frequency bioimpedance (mfBIA) emerges as an objective, reproducible and non-invasive tool that allows body composition to be assessed more accurately.
Clinical and epidemiological rationale for BIA-based screening
Malnutrition in older adults is a prevalent and underdiagnosed condition, with clinical implications ranging from loss of functionality to increased mortality. Studies such as the ELAN (Correia et al., 2020) have shown that more than 30% of hospitalized patients in Latin America have some degree of malnutrition, and that this figure may be even higher in geriatric contexts.
BIA represents an accessible and non-invasive tool for nutritional and metabolic screening in the elderly. Its ability to estimate parameters such as fat-free mass, fat mass, total body water and its intra- and extracellular distribution, as well as the phase angle, allows early identification of alterations in body composition and cellular integrity that precede the clinical manifestation of malnutrition. In this way, the BIA provides objective and complementary information that guides the early detection of nutritional risk, facilitating timely decision-making and integration with other clinical and physical performance tests when necessary.
Physiological Changes in Aging and Their Nutritional Impact
During aging, structural and functional modifications occur that affect active cell mass (CAM), water distribution, and fat mass ratio. These alterations are not necessarily reflected in body weight or BMI, which can lead to misdiagnosis, especially in cases of sarcopenic obesity or hidden malnutrition. Recent studies have shown that parameters such as phase angle (AF°), fat-free mass index (FFMI), skeletal mass index (ASMI), and impedance radius (IR) offer greater sensitivity for detecting nutritional risk in older adults (Sánchez-Sánchez et al., 2022; Zhang et al., 2023; Cederholm et al., 2022).
Limitations of BMI and the need for functional indicators
The body mass index (BMI), although useful as a population indicator, has serious limitations in older adults. It does not distinguish between fat mass and muscle mass, nor does it reflect water redistributions associated with aging or chronic pathologies.
For example, a BMI within the normal range may mask a significant loss of active cell mass or expansion of the extracellular compartment, resulting in increased metabolic and functional risk. In this sense, the use of indicators such as phase angle, impedance radius, and FFMI allows for a more accurate and personalized evaluation (Norman et al., 2021).
Key functional indicators in mfBIA
- Phase Angle (AF°): Reflects the integrity of cell membranes and the amount of active cell mass. Values below 5° in men and 4.5° in women over 65 years of age are associated with a higher risk of malnutrition, inflammation and mortality. Its usefulness as a clinical predictor has been validated in geriatric cohorts (Sánchez-Sánchez et al., 2022).
- Impedance radius (IR): Calculated as z200/z5, indicates water redistribution and cellular deterioration. A high RI suggests extracellular water expansion and intracellular mass loss, being useful in patients with chronic diseases (Zhang et al., 2023).
- Active cell mass (ACM): Represents the metabolically active compartment. Its decrease is related to sarcopenia and risk of disability. Low FFMI values (<15 kg/m² in women, <17 kg/m² in men) and ASMI (<5.5 kg/m² in women, <7.0 kg/m² in men) are indicators of nutritional risk (Cederholm et al., 2022).
- Water balance: The AEC/AIC ratio allows the identification of metabolic stress and fluid retention. An increase in this relationship precedes the appearance of clinical edema and is associated with malnutrition (Barazzoni et al., 2021).
- Body proteins: Estimates of total and active proteins correlate with immune function and metabolic risk. Its decrease predicts clinical complications regardless of BMI (Poulia et al., 2023).
- ASMI (Appendicular Muscle Mass Index): This indicator reflects the amount of muscle mass in the extremities, being essential for the diagnosis of sarcopenia. Values below 7.0 kg/m² in men and 5.5 kg/m² in women over 65 years of age are associated with a higher risk of disability, falls and loss of functional autonomy. Its measurement by mfBIA allows for rapid and reproducible assessment, and should be considered alongside FFMI for more accurate classification of nutritional status (Cederholm et al., 2022; Norman et al., 2021).
- FFMI (Fat-Free Mass Index): The FFMI stands for height-adjusted fat-free mass, it is a direct indicator of the body’s protein reserve. Values below 17 kg/m² in men and 15 kg/m² in women over 65 years of age are associated with an increased risk of clinical complications, hospitalization, and mortality, even in the presence of normal BMI. Its usefulness has been validated in geriatric cohorts and is recommended as a complementary diagnostic criterion in nutritional screening protocols (Cederholm et al., 2022; Norman et al., 2021).
It should be remembered that mfBIA is a tool for the early detection of functional risks, not a definitive diagnostic method. Its value lies in identifying subclinical alterations in body composition that precede the clinical manifestation of malnutrition or sarcopenia. However, to establish a formal diagnosis, it must be complemented with other clinical, functional and biochemical parameters, such as manual grip strength, gait speed, MNA, SARC-F, and markers such as albumin, prealbumin or C-reactive protein. The integration of these elements allows for a more complete nutritional assessment, in line with international guidelines such as ESPEN and EWGSOP2 (Cederholm et al., 2022; Barazzoni et al., 2021).
Applicability in community contexts and primary care
The mfBIA is not only useful in hospital or specialized settings, but can also be integrated into community programs for the care of the elderly. Its portability, speed and low operating cost make it viable for screening days, home visits and primary care centers.
In addition, it allows the generation of longitudinal databases that facilitate the monitoring of nutritional status and the evaluation of the impact of interventions. This community applicability has been validated in experiences such as the HELENA study in Europe (Poulia et al., 2023), and can be adapted to Latin American contexts with criteria of cultural and epidemiological relevance.
Proposed Clinical Protocol for Nutritional Screening
Phase 1: Patient Preparation
- Light fasting for 3 hours
- No intense physical activity in the last 12 hours
- Prior urination
- Standardized position per manufacturer guidelines
- No contact with metals
- Avoid measurement in cases of generalized edema or advanced cachexia, unless evaluating PA° and IR exclusively
Phase 2: Parameter Recording
- Phase angle (PA°)
- FFMI and ASMI
- ECW/ICW ratio
- Impedance ratio (IR)
- Bone mineral content and dry fat-free mass
Phase 3: Nutritional Risk Classification
- Low risk: all parameters within normal ranges
- Moderate risk: one or two altered parameters
- High risk: three or more altered parameters
Phase 4: Referral and Intervention
- Low risk: reassessment in 6–12 months
- Moderate risk: educational intervention and 3-month follow-up
- High risk: referral to nutritionist, functional evaluation, and monthly follow-up
Phase 5: Clinical Integration
Results should be incorporated into the clinical record and complemented with validated scales such as MNA or SARC-F. This approach enables early detection, avoids overtreatment, and optimizes clinical resources.
Research Perspectives and Regional Standardization
Implementing mfBIA-based protocols opens opportunities for multicenter research in aging, nutrition, and functionality. The creation of regional observatories such as ObBIA Latam, led by Clínica Nutricional Virtual (CNV), would allow for normative data consolidation, validation of cut-off points specific to Latin American populations, and evidence generation for adapted clinical guidelines. Additionally, analyzing parameters such as bone mineral content, fat-free dry mass, and active proteins may contribute to the development of new nutritional biomarkers with predictive and therapeutic value.
Conclusions
mfBIA offers a superior alternative to BMI for early detection of malnutrition in older adults. Its ability to identify functional alterations before clinical manifestation makes it a strategic tool in primary care, geriatrics, and community programs. Implementing a standardized protocol based on functional parameters improves diagnosis, guides timely interventions, and contributes to better quality of life in the geriatric population.
At Aminogram, we are committed to developing and manufacturing high-quality multifrequency bioimpedance devices that are accessible to professionals around the world. Our mission is to democratize access to advanced technologies, enabling the integration of functional assessments like this one into everyday clinical practice—making precision, prevention, and transformative nutrition a global reality
References
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