Lucas Bertoluci Zuquieri
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Lucas Bertoluci Zuquieri has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Cassiano Merussi Neiva
Universidade Estadual Paulista, Brazil
1 shared publication - Dalton Muller Pessoa Filho
Department of Physical Education, School of Sciences (FC), São Paulo State University (UNESP), Bauru 17033-360, Brazil
1 shared publication - Danilo Alexandre Massini
Department of Physical Education, School of Sciences, São Paulo State University (UNESP), Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, Vargem Limpa, Bauru 17033-360, SP, Brazil
1 shared publication - Eliane Aparecida Castro
Graduate Programme in Human Development and Technology, São Paulo State University (UNESP), Rio Claro 13506-900, Brazil
1 shared publication - Gabriel de Souza Zanini
Department of Physical Education, School of Sciences (FC), São Paulo State University (UNESP), Bauru 17033-360, Brazil
1 shared publication - Pedro Jose Benito
LFE Research Group, Department of Health and Human Performance, Faculty of Physical Activity and Sport Science (INEF), Universidad Politécnica de Madrid, Madrid, Spain
1 shared publication
Latest Publications
- Open Access
- 27 February 2026
- Published by MDPI AG in Journal of Functional Morphology and Kinesiology
- Vol. 11 (1) , 101
Body Composition’s Association with Resting Energy Expenditure Prediction in a Large Population Sample from Different Age Groups, Sex, and Physical Activity Levels
Background: Resting energy expenditure (REE) represents 60–75% of total daily energy expenditure and is mainly determined by fat-free mass (FFM). Indeed, the predictive equations vary according to FFM techniques and population characteristics. Therefore, this study aimed to explore the influence of dual-energy X-ray absorptiometry (DXA)-derived FFM on REE prediction by different predictive equations in a large and diverse cohort. Methods: A total of 1987 active and sedentary participants of both sexes (43.8 ± 19.4 years) underwent body composition assessment by DXA. REE was predicted using the Harris–Benedict, Schofield, Mifflin–St Jeor (weight- and height-based), and Mifflin (FFM-based) equations. Statistical analyses included Kruskal–Wallis, Spearman correlations, and linear regression. Results: Men presented higher absolute FFM, whereas women exhibited higher relative fat mass (FM) (p < 0.01). Across age groups, FFM declined progressively, while FM increased (p < 0.01). The REE differed significantly (p < 0.001) between equations, with the lowest values predicted from the FFM-based model, while the Harris–Benedict and Schofield equations showed the highest REE, especially in women. Strong correlations were observed between FFM and REE (r = 0.77–0.98; p < 0.01) for all age groups and equations, whereas FM showed strong correlations (r = 0.77–0.85; p < 0.01) only for the ≥60 years group. REE tended to be higher in active than sedentary participants, with the correlations to FFM and FM exhibiting a similar profile to that observed for the whole group. Conclusions: FFM showed a strong association with the estimate of REE in active and sedentary participants from both sexes and different age groups, but FM showed a similar trend in older participants only. Therefore, the increase or the maintenance of FFM with an active lifestyle is important to keep REE at high and efficient levels regardless of sex and age.
- 27 February 2026
- Published by MDPI AG in Journal of Functional Morphology and Kinesiology
- Vol. 11 (1) , 101
Open AccessBody Composition’s Association with Resting Energy Expenditure Prediction in a Large Population Sample from Different Age Groups, Sex, and Physical Activity Levels
Background: Resting energy expenditure (REE) represents 60–75% of total daily energy expenditure and is mainly determined by fat-free mass (FFM). Indeed, the predictive equations vary according to FFM techniques and population characteristics. Therefore, this study aimed to explore the influence of dual-energy X-ray absorptiometry (DXA)-derived FFM on REE prediction by different predictive equations in a large and diverse cohort. Methods: A total of 1987 active and sedentary participants of both sexes (43.8 ± 19.4 years) underwent body composition assessment by DXA. REE was predicted using the Harris–Benedict, Schofield, Mifflin–St Jeor (weight- and height-based), and Mifflin (FFM-based) equations. Statistical analyses included Kruskal–Wallis, Spearman correlations, and linear regression. Results: Men presented higher absolute FFM, whereas women exhibited higher relative fat mass (FM) (p < 0.01). Across age groups, FFM declined progressively, while FM increased (p < 0.01). The REE differed significantly (p < 0.001) between equations, with the lowest values predicted from the FFM-based model, while the Harris–Benedict and Schofield equations showed the highest REE, especially in women. Strong correlations were observed between FFM and REE (r = 0.77–0.98; p < 0.01) for all age groups and equations, whereas FM showed strong correlations (r = 0.77–0.85; p < 0.01) only for the ≥60 years group. REE tended to be higher in active than sedentary participants, with the correlations to FFM and FM exhibiting a similar profile to that observed for the whole group. Conclusions: FFM showed a strong association with the estimate of REE in active and sedentary participants from both sexes and different age groups, but FM showed a similar trend in older participants only. Therefore, the increase or the maintenance of FFM with an active lifestyle is important to keep REE at high and efficient levels regardless of sex and age.