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Article

Associations Between Perceived Physical Literacy and DXA-Measured Body Composition in Spanish Adolescents: The ENERGYCO Study

by
Emilio Villa-González
1,
Pablo Campos-Garzón
2,*,
Manuel Ávila-García
3,4,
Ana Ramírez-Osuna
1,
David Rodriguez-Sanchez
1,
José Manuel Segura-Díaz
5 and
Víctor Manuel Valle-Muñoz
1
1
Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, 18071 Granada, Spain
2
Faculty of Health Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
3
La Inmaculada Teacher Training Centre, Sport and Health University Research Institute (iMUDS), University of Granada, 18013 Granada, Spain
4
Faculty of Sport Sciences, Universidad Isabel I, 09003 Burgos, Spain
5
Department of Human Movement and Sport Performance, University of Seville, 41013 Seville, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(2), 807; https://doi.org/10.3390/app16020807
Submission received: 12 December 2025 / Revised: 7 January 2026 / Accepted: 9 January 2026 / Published: 13 January 2026
(This article belongs to the Special Issue Health Promotion Through Physical Activity and Diet)
Review Reports Versions Notes

Abstract

Background: Physical literacy is a multidimensional construct that may be relevant for promoting active lifestyles and healthy development during adolescence. However, the association between perceived physical literacy (PPL) and body composition assessed by dual-energy X-ray absorptiometry (DXA) remains underexplored. Objective: To examine the association between PPL and DXA-derived body composition parameters in Spanish adolescents. Methods: This cross-sectional study included 56 adolescents (13.2 ± 1.27 years, 28.6% girls). PPL was assessed using the validated Spanish version of the Perceived Physical Literacy Instrument (S-PPLI). Body composition was measured by DXA. Associations between PPL and body composition outcomes were examined using general linear models, adjusting for sex, age, and device-measured moderate-to-vigorous physical activity (MVPA) and sedentary time. Results: Higher PPL was significantly associated with greater lean body mass (β = 0.81; p = 0.02), lean mass index (β = 0.22; p = 0.01), and fat-free mass (β = 0.85; p = 0.01), as well as with higher body mass index (BMI) (β = 0.24; p = 0.03). Conclusions: Higher PPL is associated with more favorable lean-related body composition outcomes in Spanish adolescents, whereas no associations were found with adiposity or bone parameters. These findings highlight PPL as a relevant correlation of lean body composition during adolescence. Given the cross-sectional design, causal inferences cannot be drawn, and future longitudinal and interventional studies are warranted.

1. Introduction

Physical inactivity is a major threat to global health [1], especially among adolescents, where more than 80% of young people aged 11 to 17 do not meet the recommended levels of physical activity (PA) [2]. The lack of PA can contribute to excess body fat and the development of obesity [1]. Although obesity is characterized as a multifactorial condition, it can trigger significant health risks such as type 2 diabetes, dyslipidemia, liver disease, mental disorders, and social stigmatization [3]. Globally, it is estimated that by 2025 there will be 206 million children and adolescents with obesity, a figure that could rise to 254 million by 2030 [4]. In Spain, the PASOS study (2022–2023) reported that 33.2% of adolescents are overweight, including 21.6% classified as overweight and 11.6% as obese, according to the criteria of the World Health Organization (WHO) [5]. In this context, previous studies have reported that higher fat mass is associated with an increased risk of cardiovascular diseases, whereas greater lean mass may be beneficial to health [6]. Beyond increasing fat mass, obesity is also associated with skeletal muscle atrophy and dysfunction, driven by impaired insulin signaling, inflammation, and mitochondrial alterations, which compromise force production and movement efficiency [7]. Moreover, excess adiposity can adversely affect bone metabolism and microarchitecture, potentially increasing fracture risk despite normal or increased bone mineral density (BMD), which reflects the concentration of mineral per unit of bone area and is commonly used as an indicator of bone strength [8]. Together, these alterations highlight the relevance of simultaneously considering fat, muscle, and bone compartments when examining body composition in adolescents, particularly in relation to functional capacity and engagement in PA, as BMD during childhood and adolescence plays a vital role in preventing osteoporosis later in life [9].
In this context, previous studies have reported that higher fat mass is associated with an increased risk of cardiovascular diseases, whereas greater lean mass may be beneficial to health [10,11]. Within this framework, regular engagement in PA plays a central role, and in this context, physical literacy (PL) has emerged as a key concept to promote an active and sustainable lifestyle over time [12]. According to the International Physical Literacy Association (IPLA), it is defined as “the motivation, confidence, physical competence, knowledge and understanding to value and take responsibility for engaging in physical activities for life” [13]. From this perspective, this multidimensional approach encompasses not only physical aspects (e.g., fundamental motor skills) but also cognitive components (e.g., knowledge and understanding) and affective elements (e.g., motivation and self-efficacy) [14]. Empirical evidence has shown that individuals with higher PL levels engage in more PA, achieve optimal sleep duration, and report lower levels of sedentary behavior [15,16]. Consistent with these findings, among Spanish adolescents, perceived physical literacy (PPL) has been associated with greater muscular strength, better academic performance, higher adherence to the 24 h movement guidelines, and a lower risk of overweight or obesity [17,18,19,20]. Moreover, higher levels of PL have been associated with better social well-being and more favorable psychosocial correlation among adolescents [21]. Taken together, these findings suggest that PL can be considered an indirect determinant of health, as it facilitates greater engagement in PA and its associated benefits, including potential improvements in body composition and long-term bone health [12,22].
Building on this evidence, previous research examining the relationship between PL and body composition in young people has generally reported positive associations, with higher PL linked to more favorable body composition profiles. Specifically, several studies have shown associations with lower body fat percentage and obesity-related indicators, while evidence suggesting a relationship with higher skeletal muscle mass has been reported in a more limited subset of the literature [16,23,24]. However, despite these promising results, a key limitation of previous findings lies in the assessment tools used, which have predominantly relied on indirect methods such as body mass index (BMI), multi-frequency bioelectrical impedance, OMRON portable scales, or Tanita BC-545 devices. Although these tools are useful for large-scale studies, their lower accuracy compared with reference techniques may limit the precision of the observed associations. In contrast, dual-energy X-ray absorptiometry (DXA) is widely used and considered the gold standard for the assessment of body composition in adolescents, as it provides precise estimates of fat mass, lean mass, and bone mineral content (BMC), which refers to the total amount of mineral in the bones [25,26,27]. Nevertheless, despite its extensive application in adolescent body-composition research, DXA has been rarely employed in studies specifically examining PL, highlighting an important gap that the present study seeks to address.
In the present study, we sought to address the limited use of reference techniques such as DXA in research examining PL, particularly in adolescents, despite its widespread application in body composition research. Therefore, this study aims to explore the association between PPL and a comprehensive set of DXA-derived body composition and bone-related parameters in Spanish adolescents. The assessment will include BMI, waist circumference, lean body mass, lean mass index, fat-free mass, fat mass, fat mass index, body fat percentage, visceral adipose tissue, BMC, and BMD. We hypothesize that higher levels of PPL will be associated with more favorable body composition and bone-related profiles, without implying causality given the cross-sectional design of the study. By addressing this gap in the current literature, the present study is expected to provide objective evidence on the relationship between PPL and body composition during adolescence, which may be informative for future research and for the development of public health strategies aimed at promoting PL and improving adolescent health.

2. Materials and Methods

2.1. Study Design and Population

This cross-sectional and descriptive study is a secondary analysis of data from the ENERGYCO project (ClinicalTrials.gov ID: NCT06414668), which was approved by the Human Research Ethics Committee of the University of Granada (Reference: 2496/CEIH/2021) [28]. Participant recruitment took place between February 2023 and January 2024 and targeted adolescents from the city of Granada, its surrounding areas, and other nearby municipalities. All procedures conducted in this study followed the ethical principles outlined in the Declaration of Helsinki. Written informed consent was obtained from the legal guardians of the participants, and all adolescents provided their voluntary assent after receiving detailed information about the study objectives and the procedures involved.
Participant recruitment was guided by feasibility considerations rather than by priori statistical power calculation. Recruitment strategies primarily included mass email invitations and social media advertisements, as outlined in the protocol [28]. The number of participants that could be enrolled was constrained by the cost and logistical demands of DXA assessments in adolescents, which are time-consuming and require specialized equipment and trained personnel. In addition, ethical and practical barriers (e.g., exposure to low-dose radiation, the need for parental consent, and the availability of adolescents willing to complete a protocol including accelerometry and laboratory visits) further limited recruitment. Therefore, the final sample size reflects the maximum number of participants that could be feasibly assessed within these constraints. The findings should be interpreted considering these limitations, and future studies with larger samples are warranted to confirm the observed associations. The study enrolled adolescents who met the following inclusion criteria: (1) age between 12 and 18 years; (2) provision of written informed consent from parents or legal guardians; and (3) availability of complete data for the main study variables, including PPL and accelerometry-based PA. Exclusion criteria were: the presence of any medical condition that limited participation in PA or required special care. Recruitment, enrollment, and data collection were conducted on a rolling basis at the University Research Institute for Sport and Health (iMUDS), University of Granada, Spain. A total of 59 adolescents from Granada and Málaga initially agreed to participate in the study. However, due to missing accelerometry-based PA data, the final analysis included 56 participants (28.6% of girls). To enhance the internal validity of the study and minimize potential sources of bias, several procedures were adopted, including broad recruitment strategies, the use of validated and objective assessment tools, standardized measurement protocols performed by trained personnel, and statistical adjustment for age, sex, device-measured sedentary time and MVPA.

2.2. Procedures

2.2.1. Perceived Physical Literacy

PPL was assessed using the PPL instrument for adolescents in its Spanish adaptation as S-PPLI, which is a valid and reliable instrument for measuring PPL among Spanish adolescents (Cronbach’s α = 0.87) [29,30]. This instrument consists of 9 items scored on a 5-point Likert scale, from 1 (strongly disagree) to 5 (strongly agree), grouped into 3 factors (3 items each): knowledge and understanding; self-expression and communication with others; and sense of self and self-confidence (see Supplementary Material Tables S1 and S2). To calculate the total score, the scores of all items are added together, resulting in a value that can range from a minimum of 9 to a maximum of 45 points.

2.2.2. Body Composition and Anthropometric Measures

Body composition was evaluated using DXA. For this purpose, a Hologic Series Discovery QDR scanner (Bedford, MA, USA) and APEX software (version 4.0.2) were used to obtain information on total lean body mass, lean mass index, fat-free mass, fat mass index, body-fat percentage, visceral adipose tissue, BMC, and BMD. All scans were performed by trained operators following standardized protocols in accordance with established DXA best-practice guidelines (International Society for Clinical Densitometry, ISCD). Participants were scanned in the supine position, wearing light clothing and with all metal objects removed. To minimize biological variability, participants were instructed to attend the assessment in a fast and well-hydrated state, to avoid vigorous PA for at least 24 h prior to the scan, and to void their bladder immediately before measurement. Scans were conducted at a consistent time of day whenever possible. The DXA device was calibrated using the manufacturer’s phantom according to standard quality-control procedures.
Body mass and height were measured twice by a trained professional with a degree in PA and Sport Sciences, with participants wearing light clothing and barefoot, using a SECA scale and a stadiometer (models 876 and 213, respectively, Electronic Column Scale, Hamburg, Germany). Standing body mass and height were measured to the nearest 0.1 kg, and BMI was calculated by dividing body mass by height squared (kg/m2). Waist circumference was also assessed by the same trained evaluator following standardized anthropometric protocols, using a Lufkin Executive Thinline W606PM measuring tape (Querétaro, Mexico), with two consecutive measurements averaged.

2.3. Covariates

PA was objectively assessed using an ActiGraph GT3x+ accelerometer (ActiLife, version 6.11.7). The research team secured the accelerometer to each participant’s right hip using an elastic belt and provided verbal and written instructions for proper care and use. Participants were instructed to wear the device for 24 h per day for 7 consecutive days, except during bathing, water-based activities, and sleeping hours. Accelerometer data were processed using the open-source R package GGIR (version 3.1–2) [31]. A valid day was defined as at least 10 h of wear time during waking hours, and participants with a minimum of 4 valid days, including at least one weekend day, were included in the analyses. The GGIR pipeline included: (i) automatic calibration of raw acceleration signals to local gravity; (ii) detection and imputation of non-wear time; and (iii) calculation of acceleration-based activity counts, derived as the average dynamic acceleration (expressed in milli-g) within each 15 s epoch from data recorded at 90 Hz, following the algorithm proposed by Neishabouri et al. [32]. For the purposes of the present study, these counts were expressed as time-based variables, representing the accumulated time spent above the selected activity thresholds. A threshold of 574 counts per 15 s was used to define MVPA, based on established cut-points [33]. Daily MVPA was summarized as the average minutes per day (min/day) across all valid monitoring days and normalized to wear time to account for inter-individual differences in device use. In the statistical analyses, accelerometer-derived MVPA (min/day) was used as a covariate alongside age and sex.

2.4. Statistical Analysis

All statistical analyses were performed using R (version 4.4.0). Descriptive statistics are presented as means and standard deviation for continuous variables and as frequencies and percentages for categorical variables. Distributional characteristics of continuous variables were examined using graphical diagnostics (histograms and Q–Q plots) to identify severe departures from symmetry or the presence of influential observations. For descriptive comparisons of participant characteristics, continuous variables were compared between groups using Welch’s t-test. Categorical variables were compared using Pearson’s chi-square test or Fisher’s exact test, as appropriate based on expected cell counts. Regarding the main aim of the current study, associations between PPL score and DXA-derived body composition outcomes (i.e., BMI, waist circumference, lean body mass, lean mass index, fat-free mass, fat mass, fat mass index, body fat, visceral adipose tissue, bone mineral content, bone mineral density) were examined using general linear models. PPL score was entered as a continuous predictor, while sex, age, and device-measured sedentary time and MVPA were included as covariates in all models. Therefore, adjusted regression coefficients (β), 95% confidence intervals (CI), and p-values are reported. The magnitude of the associations was quantified using partial Cohen’s f2 as a measure of effect size for each predictor of interest, reflecting the independent contribution of PPL after adjustment for covariates. Effect sizes (partial f2) were interpreted as small (0.02), medium (0.15), and large (0.35), in accordance with conventional benchmarks. In addition, potential multicollinearity among covariates was assessed using the variance inflation factor (VIF), with values > 5 considered indicative of problematic collinearity. All statistical tests were two-sided, and statistical significance was set at p < 0.05.

3. Results

The descriptive characteristics of the study sample stratified by sex are presented in Table 1. A total of 56 adolescents were included (mean age: 13.2 ± 1.27 years), of whom 28.6% were girls. No significant age differences were observed between boys and girls (p = 0.14). Regarding PPL, girls showed significantly higher overall PPL scores than boys (39.10 ± 3.46 vs. 36.56 ± 4.08; t(24.1) = 2.19, p = 0.04). Among the PPL subdomains, a significant difference was observed only for self-expression and communication with others, with higher scores in boys compared with girls (12.50 ± 1.49 vs. 11.31 ± 1.54; t(26.9) = 2.64, p = 0.01). In terms of body composition, boys presented a significantly higher BMI than girls (20.16 ± 2.61 vs. 18.16 ± 2.29 kg/m2; t(24.7) = −2.67, p = 0.01). No other body composition indicators differed significantly between sexes. With respect to PA, girls accumulated significantly more MVPA than boys (82.06 ± 37.23 vs. 45.17 ± 29.06 min/day; t(25.3) = 3.46, p = 0.002). Similarly, girls also showed higher MPA compared with boys (49.13 ± 21.51 vs. 32.79 ± 18.30 min/day; t(14.7) = 2.28, p = 0.038). No significant sex differences were observed for the remaining PPL subdomains, other body composition variables, light or vigorous PA, or sedentary time.
The results of the multiple linear regression analyses examining the associations between PPL and body composition outcomes are presented in Table 2. Collinearity was assessed using VIF, with values > 5 indicating multicollinearity. No evidence of collinearity was observed in any of the models (VIF range: 1.03–1.90). After adjustment for sex, age, and device-measured sedentary time and MVPA, higher PPL was significantly associated with greater BMI (β = 0.24, SE = 0.11, 95% CI 0.02 to 0.46; p = 0.03; partial f2 = 0.13), lean body mass (β = 0.81, SE = 0.36, 95% CI 0.09 to 1.54; p = 0.02; partial f2 = 0.14), lean mass index (β = 0.22, SE = 0.07, 95% CI 0.07 to 0.37; p = 0.01; partial f2 = 0.25), and fat-free mass (β = 0.85, SE = 0.38, 95% CI 0.09 to 1.61; p = 0.01; partial f2 = 0.14). The magnitude of these associations ranged from small to moderate across the significant models (partial f2 = 0.13–0.25), suggesting a modest but meaningful independent contribution of PPL to lean-related body composition outcomes. No significant associations were observed between PPL and waist circumference, fat mass, fat mass index, body fat percentage, visceral adipose tissue, BMC, or BMD (all p > 0.05).

4. Discussion

This study extends current evidence by examining the association between PPL and DXA-derived body composition outcomes in Spanish adolescents. Our findings indicate that higher PPL is significantly associated with greater lean-related body composition parameters, even after adjustment for sex, age, and device-measured sedentary time and MVPA. Specifically, higher PPL was associated with greater lean body mass, lean mass index, and fat-free mass, as well as with a higher BMI. Importantly, this positive association with BMI appears to be driven by increases in lean tissue rather than adiposity, as no significant associations were observed with fat mass, fat mass index, or body fat percentage. The magnitude of these associations was small to moderate, indicating a modest yet relevant relationship between PPL and lean tissue development during adolescence. Together, these findings suggest that higher levels of PPL are linked to a more favorable lean body composition profile in adolescence. However, given the cross-sectional design of the study, causal inferences cannot be drawn.
This observation aligns with the conceptual model proposed by Cairney et al. [34], which posits that PL functions as a key determinant of health through its influence on both physical behavior and biological systems, including musculoskeletal function. According to this model, PL not only facilitates greater engagement in physical activities but also acts on physiological mechanisms that can promote a healthier and more functional body structure during adolescent development. In this context, our results reveal that adolescents with higher PPL exhibit a more robust profile across the cognitive, social, and affective domains of PL, encompassing greater knowledge and understanding, enhanced self-expression and communication with others, and a stronger sense of self and self-confidence. This multidimensional advantage supports the framework proposed by Faigenbaum and Rial-Rebullido [35], who describe PL as an integrated construct that develops along a continuum shaped by the quantity and quality of MVPA experiences. Consistent with this view, youth with higher PPL appear more likely to display greater motor competence and confidence, which in turn fosters more frequent and engaged participation in diverse physical activities, ultimately contributing to the acquisition and maintenance of a healthy and functional body composition.
Our results are consistent with previous evidence linking higher levels of PPL with more favorable body composition in adolescents. For example, Nezondet et al. [36] reported positive correlations between PPL and fat-free mass (r = 0.42; p < 0.05) and negative correlations with body fat percentage (r = −0.46; p < 0.05). Complementarily, Domínguez-Martín et al. [19] observed a clear downward trend in all obesity indicators (BMI, waist circumference, waist-to-height ratio, and skinfold thickness) as PPL increased, with significant differences between low-, medium-, and high-PPL groups. Similarly, Muñoz-Urtubia et al. [37] reported that adolescents more motivated toward PA, as assessed by the CAPL-2, presented healthier BMI values, while Mendoza-Muñoz et al. [17] found significant inverse correlations between most PL domains and body composition indicators. In contrast to these findings, our results showed a positive association between PPL and BMI. However, this association does not appear to reflect greater adiposity, as PPL was not related to fat mass, fat mass index, or body fat percentage, but was strongly associated with lean body mass, lean mass index, and fat-free mass. Taken together, these results suggest that, in our sample, a higher BMI associated with greater PPL may be driven by increased lean tissue rather than by excess fat, highlighting the limitations of BMI as a proxy for adiposity in physically literate adolescents. Importantly, none of the studies used DXA, whereas in the present study this technique allowed precise and simultaneous assessment of both fat and lean compartments. Our use of DXA as the gold standard provides stronger evidence compared to previous studies that relied on indirect methods [38]. The use of DXA as a reference method therefore provides more robust evidence regarding the nature of the association between PPL and body composition, supporting the notion that higher PPL is linked to a more favorable lean body composition profile across the continuum of PPL values.
Although our study found no significant differences in fat-related variables, this is consistent with previous evidence indicating that lean mass is a stronger and more consistent predictor of BMD than fat mass in children and adolescents [39]. In Norwegian adolescents (15–17 years), lean mass explained much of the variability in hip BMD, whereas fat mass was a secondary and sex-dependent predictor [40]. Similar results were observed in an Iranian population, where lean mass showed a strong correlation with BMD (r = 0.78, p < 0.001) compared to an almost null association with body fat percentage (r = 0.03, p = 0.44) [41]. A systematic review and meta-analysis of 31 studies involving more than 21,000 participants confirmed that lean mass presents moderate-to-high correlations with BMD (β = 0.53–0.74, p < 0.05), while fat mass showed weaker correlations (β = 0.10–0.50, p < 0.05) and only a weak association with femoral neck BMD (β = 0.07, p < 0.05) [39]. Moreover, body fat percentage was negatively associated with BMD (β = −0.54 to −0.04, p < 0.05) [38]. Taken together, the evidence supports the notion that positive bone adaptations depend primarily on lean body components, which may explain the results observed.
Regarding bone health, our results did not show significant associations between PPL and DXA-derived bone parameters, including BMC and BMD, after adjustment for relevant covariates. These findings contrast with our initial expectations and suggest that, in this sample of Spanish adolescents, PPL may not be independently related to bone mineralization. To our knowledge, few studies have directly examined the relationship between PPL and bone health in adolescents, which limits direct comparisons. However, previous evidence has consistently highlighted the importance of PA for skeletal development. For instance, large observational studies such as the HELENA study reported higher BMC and BMD values among adolescents engaging in higher levels of MVPA [42], and meta-analyses have shown positive associations between lean mass and BMD (r = 0.42; p < 0.001) [39]. In addition, systematic reviews have confirmed the beneficial effects of school-based, weight-bearing exercise programs on bone health in youth [43]. Furthermore, Proia et al. [44] emphasized that PA and adequate dietary habits act synergistically to promote bone health during childhood and adolescence. In this context, the absence of significant associations in our study may indicate that PPL alone, as a multidimensional construct reflecting motivation, confidence, and perceived competence, may be insufficient to capture the specific osteogenic stimuli required to influence bone outcomes, which are more directly related to the type, intensity, and mechanical loading characteristics of PA, as well as nutritional factors. These findings underscore the need for future longitudinal studies to further explore the potential pathways linking PPL, movement behaviors, and skeletal health during adolescence.
However, these results should be interpreted with caution. In the present sample, adolescents accumulated relatively high levels of MVPA, with an average of approximately 72 min/day of MVPA, which exceeds current public health recommendations. This generally active profile may have attenuated potential differences in body composition associated with perceived PPL, as most participants were already exposed to sufficient volumes of PA. Nevertheless, our findings suggest that PPL may still be linked to more favorable lean-related outcomes independently of overall MVPA volume, supporting the notion that factors beyond the amount of activity performed, such as motivation, confidence, and perceived competence, may play a role in shaping movement behaviors and their physiological correlations. This interpretation is consistent with Melby et al. [45], who reported a limited mediating role of total MVPA in the relationship between PL and physical well-being, emphasizing that the quality, diversity, and mechanical characteristics of activities may be more influential than volume alone. In line with Öztürk et al. [46] and Yan et al. [47], adolescents with higher PPL may be more likely to engage in varied, skill-based, and weight-bearing activities, such as vigorous exercise, resistance training [48], or impact sports, which could contribute more effectively to lean mass development than uniform or lower-intensity activities, even within an overall physically active sample.
The mechanisms linking PPL and body composition appear to be multifactorial. Biological maturation is likely to modulate this relationship. As described by Chulani and Gordon [49], adolescence involves profound endocrine changes, mediated by the hypothalamic–pituitary–gonadal axis and insulin-like growth factor 1 (IGF-1), that drive the development of lean and bone mass as well as the redistribution of fat. These processes differ by sex: boys generally gain leaner and bone mass, while girls accumulate more subcutaneous fat. Consequently, adolescents approaching or surpassing peak height velocity (PHV) may exhibit structural advantages unrelated to PPL, which could confound cross-sectional analyses. In this context, the positive association observed between PPL and BMI in our study may reflect maturational increases in lean tissue rather than greater adiposity. This reinforces the notion that BMI during adolescence may be strongly influenced by growth- and maturation-related changes in body composition and should be interpreted with caution when used as a proxy for adiposity in physically active and physically literate youth.
Furthermore, due to its holistic nature, PPL encompasses physical competence, which is closely related to physical fitness. Evidence supports positive relationships between PPL and fitness in youth. Higher PPL has been associated with greater self-perceived fitness and better physical performance in adolescents [50,51]. Since fitness components such as lean mass and strength are strong predictors of cardiometabolic health and weight control [52], they may mediate the connection between PPL and body composition. Therefore, higher levels of PPL during adolescence may be relevant from a public health perspective, as they are associated with more favorable body composition profiles and with behaviors linked to healthier lifestyle patterns [53]. However, given the cross-sectional design of the present study, these findings should be interpreted as associative rather than indicative of direct or indirect causal effects over time.

Limitations and Strengths

While the findings of this study are relevant and help address a significant gap in the literature regarding PPL and body composition in adolescents, they should be interpreted with caution due to certain methodological limitations. First, the cross-sectional design of the study prevents the establishment of causal relationships between PPL and DXA-derived body composition parameters. Although statistically significant associations were observed in key lean-related variables, it cannot be determined with certainty whether higher PPL leads to improvements in body composition or whether a more favorable body composition positively influences one’s perception of PL. To clarify this causal direction, longitudinal studies and targeted interventions are needed. Additionally, the relatively small total number of participants (n = 56) limits the statistical power of certain analyses and the ability to conduct broader sensitivity or subgroup analyses, particularly by sex or age. The low proportion of girls (28.6%) further restricts the generalizability of the findings by sex. Therefore, future studies with larger and more balanced samples are warranted to confirm and extend the present results.
Despite these limitations, this study also has several important strengths. Notably, the use of DXA provided highly accurate and reliable measurements of fat mass, lean mass, and bone parameters, enabling a precise evaluation of the associations between PPL and objectively assessed body composition. Furthermore, to our knowledge, this is the first study to explore the relationship between PPL and bone mineralization in adolescents, representing a novel contribution to literature. However, it should be acknowledged that PPL was assessed using the S-PPLI, a valid and reliable instrument that captures adolescents’ subjective perceptions of their PL rather than objective components such as directly measured motor competence or physical performance. Therefore, the observed associations should be interpreted as relationships between PPL and body composition outcomes, and not as reflecting objective PL per se, which may limit the extent to which these findings can be generalized to other dimensions of the construct. In addition, although MVPA was included as a continuous covariate in the general linear models to account for differences in PA levels, MVPA is conceptually related to both PPL and body composition, and residual confounding cannot be ruled out. Moreover, while age and sex were included as covariates, these variables do not fully capture inter-individual differences in biological maturation during puberty, particularly for lean mass and bone-related outcomes that differ markedly between males and females. The absence of a specific indicator of maturation status (e.g., pubertal stage or maturity offset) should therefore be considered a limitation, and the degree of developmental adjustment achieved by the models may be limited. Finally, future studies using longitudinal designs, larger and more diverse samples, and objective assessments of both PL and maturation status are warranted to further clarify the nature of the associations between PPL and body composition and to inform the development of interventions aimed at promoting optimal PL and health outcomes during adolescence.

5. Conclusions

In conclusion, the present study shows that higher levels of PPL are associated with more favorable lean-related body composition outcomes in Spanish adolescents, including greater lean body mass, lean mass index, and fat-free mass, as well as with higher BMI. Importantly, these associations were not accompanied by higher adiposity, as no significant relationships were observed with fat mass, fat mass index, or body fat percentage. These findings suggest that the positive association between PPL and BMI is likely to reflect greater lean tissue rather than excess fat. By using DXA as a reference method, this study provides objective evidence that extends previous research based mainly on indirect measures of body composition. Although no significant associations were found between PPL and bone-related parameters, our results highlight PPL as a relevant correlation of lean body composition during adolescence. Given the cross-sectional design, causal inferences cannot be drawn. However, these findings underscore the potential relevance of PPL in relation to health-related body composition characteristics in youth. From a practical perspective, fostering higher levels of PPL may be meaningful in educational and community settings, as it may be linked to healthier lean mass development during this critical stage of growth. Future longitudinal and interventional studies are warranted to clarify the directionality of these relationships and to determine whether enhancing PPL can contribute to improvements in body composition and overall adolescent health.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app16020807/s1, Table S1: Original version of Perceived Physical Literacy Instrument (PPLI) for adolescents. Table S2: Adjusted group means for body composition variables by PL cluster.

Author Contributions

E.V.-G. is the principal investigator of the ENERGYCO project and contributed to the conceptualization, design, data collection, discussion, and review of the manuscript. V.M.V.-M. was the lead author of this article, contributing to conceptualization, research design, data analysis, and manuscript writing. M.Á.-G. was responsible for conceptualization, data collection, data analysis, and manuscript writing. P.C.-G. was responsible for data analysis and for drafting the results section. J.M.S.-D., D.R.-S. and A.R.-O. contributed to the interpretation of the article’s data and to writing the discussion section. All authors have read and agreed to the published version of the manuscript.

Funding

V.M.V.-M. is supported by an FPU Predoctoral Research Fellowship from the Spanish Ministry of Universities (grant number FPU23/01608). A.R.-O is supported by an FPU Predoctoral Research Fellowship from the Spanish Ministry of Universities (grant number FPU23/02201). D.S.-R is supported by an FPU Predoctoral Research Fellowship from the Spanish Ministry of Universities (grant number FPU23/02198). This study was also supported by MCIN/AEI/10.13039/501100011033 and by the European Union through the “ERDF A way ofmaking Europe” program (ENERGYCO Project; Reference PID2021-126126OA-I00). Additionally, this study has been carried out thanks to funding from the University of Granada Plan Propio de Investigación 2016—Excellence Actions: Unit of Excellence on Exercise and Health (UCEES)—and from the Junta de Andalucía, Consejería de Conocimiento, Investigación y Universidades, co-financed by the European Regional Development Fund (Reference SOMM17/6107/UGR).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Human Research Ethics Committee of the University of Granada (Reference: 2496/CEIH/2021) for studies involving human.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated and analyzed during the current study are not publicly available due to confidentiality issues but are available from the principal investigator upon reasonable request.

Acknowledgments

The author would like to its members from the Sport and Health University Research Institute at the University of Granada who contributed to this study. This study is part of a doctoral dissertation conducted within the Doctoral Program in Educational Sciences at the University of Granada, Spain.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
PAPhysical Activity
PLPhysical Literacy
PPLPerceived Physical Literacy
BMIBody Mass Index
DXADual-energy X-ray Absorptiometry
BMCBone Mineral Content
BMDBone Mineral Density
MVPAModerate-to-vigorous physical activity
VPAVigorous Physical Activity
MPAModerate Physical Activity.
LPALight Physical Activity

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Table 1. Descriptive characteristics of the study sample by sex.
Table 1. Descriptive characteristics of the study sample by sex.
VariableAll
(n = 56)		Male
(n = 40)		Female
(n = 16)		p-Value
Age (years)13.20 (1.27)13.62 (1.36)13.03 (1.21)0.14
Physical literacy
PPL 1 (scores)38.38 (3.79)36.56 (4.08)39.10 (3.46)0.04
Knowledge and understanding13.98 (1.17)14.13 (1.07)13.63 (1.36)0.20
Self-expression and communication with others12.16 (1.58)12.50 (1.49)11.31 (1.54)0.01
Sense of self and self-confidence12.48 (1.89)11.63 (1.93)10.89 (1.37)0.15
Body composition
Body mass index (kg/m2)18.73 (2.53)20.16 (2.61)18.16 (2.29)0.01
Waist circumference (cm)49.65 (10.93)52.43 (8.60)48.54 (11.65)0.18
Lean body mass (kg)36.19 (8.72)37.24 (5.62)35.76 (9.75)0.48
Lean mass index (kg/m2)13.66 (1.87)14.31 (1.40)13.39 (1.99)0.06
Fat free mass (kg)37.9 (9.16)39.05 (5.94)37.43 (10.22)0.47
Fat mass (kg)10.89 (4.30)12.55 (3.74)10.2 (4.37)0.05
Fat mass index
(kg/m2)		4.23 (1.56)4.84 (1.48)3.98 (1.54)0.06
Body fat percentage (%)22.52 (6.59)24.04 (5.03)21.9 (7.10)0.22
Visceral adipose tissue (cm2)145.77 (64.49)80.11 (47.37)172.7 (49.65)0.43
Bone mineral content (kg)1.71 (0.46)1.8 (0.37)1.67 (0.49)0.28
Bone mineral density (g/cm2)0.98 (0.12)1.02 (0.10)0.96 (0.13)0.07
Physical activity
MVPA 2 (min/day)72 (38.62)45.17 (29.06)82.06 (37.23)0.01
LPA 3 (min/day)257.29 (82.68)221.39 (72.31)267.09 (83.61)0.13
MPA 4 (min/day)45.63 (21.74)32.79 (18.30)49.13 (21.51)0.04
VPA 5 (min/day) 29.38 (17.64)23.48 (12.98)30.99 (18.55)0.18
Sedentary time (min/day) 515.08 (113.45)552.84 (84.50)500.92 (120.67)0.12
Data are presented as mean (standard deviation) for continuous variables and percentages for categorical outcomes. 1 PPL = physical literacy perceived; 2 MVPA = moderate-to-vigorous physical activity; min/day = minutes per day. 3 LPA = light physical activity; 4 MPA = moderate physical activity; 5 VPA = vigorous physical activity.
Table 2. Associations between perceived physical literacy composite score and body composition outcomes.
Table 2. Associations between perceived physical literacy composite score and body composition outcomes.
VariableβSE95% CI (Lower)95% CI
(Upper)		p-ValuePartial f2
Body mass index (kg/m2)0.240.110.020.460.030.13
Waist circumference (cm)0.870.47−0.071.810.060.09
Lean body mass (kg)0.810.360.091.540.020.14
Lean mass index (kg/m2)0.220.070.070.370.010.25
Fat-free mass (kg)0.850.380.091.610.010.14
Fat mass (kg)−0.000.22−0.440.440.990.01
Fat mass index (kg/m2)0.010.08−0.150.160.880.01
Body fat (%)−0.220.34−0.920.480.520.01
Visceral adipose tissue (cm2)−1.282.69−6.724.170.630.01
Bone mineral content (kg)0.030.02−0.000.070.070.09
Bone mineral density (g/cm2)0.010.01−0.000.020.120.07
Physical literacy perceived was entered as the main predictor in all models. All models were adjusted for sex, age, and device-measured sedentary time and MVPA. β = unstandardized regression coefficient; SE = Standard Error; CI = confidence interval; partial f2 = (0.02 = small, 0.15 = medium, and 0.35 = large effect size).
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Villa-González, E.; Campos-Garzón, P.; Ávila-García, M.; Ramírez-Osuna, A.; Rodriguez-Sanchez, D.; Segura-Díaz, J.M.; Valle-Muñoz, V.M. Associations Between Perceived Physical Literacy and DXA-Measured Body Composition in Spanish Adolescents: The ENERGYCO Study. Appl. Sci. 2026, 16, 807. https://doi.org/10.3390/app16020807

AMA Style

Villa-González E, Campos-Garzón P, Ávila-García M, Ramírez-Osuna A, Rodriguez-Sanchez D, Segura-Díaz JM, Valle-Muñoz VM. Associations Between Perceived Physical Literacy and DXA-Measured Body Composition in Spanish Adolescents: The ENERGYCO Study. Applied Sciences. 2026; 16(2):807. https://doi.org/10.3390/app16020807

Chicago/Turabian Style

Villa-González, Emilio, Pablo Campos-Garzón, Manuel Ávila-García, Ana Ramírez-Osuna, David Rodriguez-Sanchez, José Manuel Segura-Díaz, and Víctor Manuel Valle-Muñoz. 2026. "Associations Between Perceived Physical Literacy and DXA-Measured Body Composition in Spanish Adolescents: The ENERGYCO Study" Applied Sciences 16, no. 2: 807. https://doi.org/10.3390/app16020807

APA Style

Villa-González, E., Campos-Garzón, P., Ávila-García, M., Ramírez-Osuna, A., Rodriguez-Sanchez, D., Segura-Díaz, J. M., & Valle-Muñoz, V. M. (2026). Associations Between Perceived Physical Literacy and DXA-Measured Body Composition in Spanish Adolescents: The ENERGYCO Study. Applied Sciences, 16(2), 807. https://doi.org/10.3390/app16020807

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