Predictive equations for fat mass in older Hispanic adults with excess adiposity using the 4‐compartment model as a reference method

González-Arellanes, Rogelio; Urquídez-Romero, René; Rodríguez-Tadeo, Alejandra; Esparza-Romero, Julián; Mendez‐Estrada, Rosa Olivia; Ramírez-López, Erik; Robles-Sardín, Alma E.; Pacheco-Moreno, Bertha-Isabel; Alemán-Mateo, Heliodoro

doi:10.1038/s41430-022-01171-w

Cited by 6 publications

(4 citation statements)

References 44 publications

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“…In one of the papers, body composition was derived from predictive equations based on anthropometric variables instead of multicomponent models based on measurements including body mass, body volume, total body water and bone mass, the basis of the gold standard 4-component model. In a cross-sectional study in nearly 400 participants, age ≥ 60 y and excess adiposity, anthropometric variables explained 80 to 90 per cent of the variation in fat mass [12]. The predictive equation thus derived was concluded to be interchangeable with the 4-component model in the population of study.…”

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confidence: 88%

Challenges in measuring energy balance and body composition

Soares

2023

Eur J Clin Nutr

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confidence: 88%

Challenges in measuring energy balance and body composition

Soares

2023

Eur J Clin Nutr

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“…Therefore, RM diagnosed by the MNA-LF can be used with individuals with normal fat mass, while RM diagnosed by the MNA-SF can be used with people who have excess fat mass, as long as the aim is to confirm MNA as a predictor of the incidence of sarcopenia. Before applying this instrument, however, it is advisable to estimate fat mass with any predictive model published in the study region that is exact and precise for older adults ( 78 , 79 ). Once determined, fat mass should be divided by height 2 in meters to obtain the FMI and classify subjects using the cut-off points cited in the methodology section for subjects with normal and excess fat mass.…”

Section: Conclusion and Clinical Implicationsmentioning

confidence: 99%

Association between the risk of malnutrition and sarcopenia at 4.2 years of follow-up in community-dwelling older adults

Vidaña-Espinoza,

López-Teros,

Esparza-Romero

et al. 2024

Front. Med.

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IntroductionCurrently, there is only scarce evidence of a causal association between risk of malnutrition (RM) by the mini-nutritional assessment (MNA) and the incidence of sarcopenia. This study was designed to assess such an association at 4.2 years of follow-up in community-dwelling subjects over 60 years old.MethodsThe data used were from the FraDySMex cohort study. The exposition variables were RM diagnosed by the long forma of the MNA (MNA-LF) and short form (MNA-SF). The last one included the body mass index and calf circumference at baseline, while sarcopenia was diagnosed by the EWGSOP2 at follow-up and taken as the response variable. Several covariates involved in the association were also considered. A multiple logistic regression analysis was performed to test the association.ResultsAt baseline, 27.0 and 37.9% of subjects had RM by the MNA-LF and MNA-SF, respectively. The incidence of sarcopenia was 13.7%. The fat mass variable significantly modified the association, so it was tested in each stratum. Two independent models showed that subjects with RM by the MNA-LF in the normal fat mass stratum were at a higher risk for developing sarcopenia at follow-up than those without RM (OR 9.28; IC 95% 1.57–54.76) after adjusting for age, sex, and waist circumference. No association was found for the excess fat mass stratum subjects. Subjects with RM by the MNA-SF in the excess fat mass stratum were more likely to develop sarcopenia at follow-up than those without RM by the MNA-SF (OR 3.67; IC 95% 1.29–10.43). This association was not found in the subjects in the normal fat mass stratum.ConclusionThe association was dependent on the variable fat mass. The two forms of the MNA should not be applied indistinctly with older adults. Based on these results, it is clear that the risk of malnutrition precedes the onset of sarcopenia.

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“…However, since many published anthropometric and BIA equations are available to accurately estimate fat mass and fat-free mass in older adults, and DXA could be an effective method for assessing fat mass and total lean tissue in older populations, it may be possible to overcome this limitation. The early measurement of fat mass and fat-free mass using ethnic-and gender-specific BIA, anthropometric equations [49][50][51], or TLT by DXA will help researchers and clinicians identify people with excess fat mass or low TLT, before this is reflected in MNA-LF scores.…”

Section: Previous Studies Related To the Causality Of Risk Of Malnutr...mentioning

confidence: 99%

Incidence of the Risk of Malnutrition and Excess Fat Mass, Low Total Lean Tissue, and Gait Speed as Independent Associated Factors in Community-Dwelling Older Adults

López Teros,

Vidaña-Espinoza,

Esparza-Romero

et al. 2023

Preprint

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Background and aims: Only one cohort study exists on the incidence of the risk of malnutrition (RM) in older adults, though numerous cross-sectional –and that cohort research– have reported several risk factors associated with the prevalence and incidence of this condition. However, alterations of body composition and impaired physical performance as exposition variables of RM have not been explored. This study assessed the incidence of RM and determined its association with excess fat mass, low total lean tissue, gait speed, and handgrip strength as exposition variables for RM in community-dwelling older adults. Methods: This is a secondary analysis in older adults (≥60 years old) derived from the study “Frailty, dynapenia, and sarcopenia in Mexican adults (FraDySMex)” a prospective cohort project conducted from 2014 to 2019 in Mexico City. At baseline, volunteers underwent body composition analysis and physical performance tests. Several covariates were identified through comprehensive geriatric assessment. At baseline and follow-up, RM was assessed using the long form of the mini nutritional assessment (MNA-LF) scale. Associations between the exposition variables and RM were assessed by multiple logistic regression. Results: The cohort included 241 subjects. Average age was 75.6±7.8 years; 83.4% were women. The mean follow-up period was 4.1 years, during which 28.6% of subjects developed RM. This condition was less likely to occur in subjects with excess fat mass index, even after adjusting for several covariates. RM was also more likely to occur in subjects with low total lean tissue index, according to both an unadjusted model and after adjusting for the corresponding variables. Regarding the association between RM and gait speed, RM was also more likely to occur in subjects with low gait speed according to both the unadjusted and adjusted models. Similar results were found for RM in relation to low handgrip strength; however, after adjusting for the associated covariates, models 1 and 2 no longer reached the level of significance. Conclusion: The risk of malnutrition diagnosed by MNA-LF was significantly less likely to occur among subjects with excess fat mass, but possibility was significantly higher in those with low total lean tissue and low gait speed after 4.1 years of follow-up in community-dwelling older adults. These results highlight that excess fat mass, low total lean tissue, and low gait speed are first than risk of malnutrition and not vice versa.

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Predictive equations for fat mass in older Hispanic adults with excess adiposity using the 4‐compartment model as a reference method

Cited by 6 publications

References 44 publications

Challenges in measuring energy balance and body composition

Challenges in measuring energy balance and body composition

Association between the risk of malnutrition and sarcopenia at 4.2 years of follow-up in community-dwelling older adults

Incidence of the Risk of Malnutrition and Excess Fat Mass, Low Total Lean Tissue, and Gait Speed as Independent Associated Factors in Community-Dwelling Older Adults

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