Longitudinal impact of physical activity on visceral adiposity, recovery, and costs in severe mental disorders: a 15-month quasi-experimental study in a community setting

Longitudinal impact of physical activity on visceral adiposity, recovery, and costs in severe mental disorders: a 15-month quasi-experimental study in a community setting | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Longitudinal impact of physical activity on visceral adiposity, recovery, and costs in severe mental disorders: a 15-month quasi-experimental study in a community setting Adolfo J. Cangas, María Jesús Lirola, Juan Leandro Cerezuela, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8531325/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Purpose Severe mental disorders (SMD) are associated with marked physical comorbidity, premature mortality, and substantial healthcare utilisation. Although physical activity (PA) is increasingly recommended as an adjunctive intervention, long-term real-world evidence linking PA participation with both clinical outcomes and healthcare costs in community psychiatric settings remains limited. This study examined longitudinal associations between engagement in a structured PA programme and health-related and economic outcomes among individuals with SMD. Methods A 15-month quasi-experimental longitudinal study was conducted with 156 adults diagnosed with SMD receiving routine community mental health care. Participants either enrolled in a structured PA programme (n = 78) or received treatment as usual (TAU; n = 78), with groups matched on key demographic and clinical variables. Outcomes included body composition, physical fitness, mental well-being (WEMWBS), health-related quality of life (WHOQOL-BREF), and direct healthcare costs derived from psychiatric hospitalisations and psychotropic medication use. Results Over the 15-month follow-up, participation in the PA programme was associated with greater improvements in cardiorespiratory fitness, body composition—including reductions in visceral adiposity—and psychological well-being compared with TAU (p < .001). Participants in the PA group also exhibited higher gains in quality of life and more favourable behavioural profiles. In parallel, lower observed direct healthcare expenditures were recorded in the PA group, primarily reflecting reduced psychiatric hospitalisation and medication costs, although cost analyses were exploratory in nature. Conclusion In a real-world community setting, sustained engagement in structured physical activity was associated with clinically meaningful improvements in physical and psychological outcomes among individuals with SMD, alongside lower healthcare utilisation over time. These findings support the potential role of structured PA as a scalable component of recovery-oriented mental health services, while highlighting the need for controlled trials to confirm causality and formally evaluate cost-effectiveness. Severe Mental Disorder Physical Activity Healthcare Costs Economic Evaluation Quality of Life Longitudinal Study Introduction Severe Mental Disorders (SMD)—encompassing schizophrenia spectrum disorders, bipolar disorder, and other chronic psychiatric conditions—are defined by persistent functional impairment and high levels of healthcare utilization [ 1 ]. Beyond individual morbidity, SMD pose a formidable public health challenge, driven by a well-documented 'physical health gap.' Individuals with SMD face a 15–20 year reduction in life expectancy compared to the general population, largely due to preventable cardiovascular and metabolic diseases [ 2 , 3 ]. This long-term risk is underscored by recent evidence from a 25-year follow-up study, which identified that physical health comorbidities and lifestyle factors remain the primary predictors of mortality from the first episode of psychosis [ 4 ]. Traditional management has historically focused on pharmacological stabilization and psychosocial rehabilitation. However, despite these interventions, high relapse rates and frequent psychiatric hospitalizations continue to strain mental health systems [ 5 ]. Recent evidence from network meta-analyses further supports a shift in this paradigm, demonstrating that various exercise modalities are significantly effective in reducing psychiatric symptomatology, particularly in patients with schizophrenia [ 6 , 7 ]. Within this context, physical activity (PA) has emerged not merely as a lifestyle adjunct, but as a core component of recovery-oriented frameworks. Evidence suggests that regular PA can mitigate cardiometabolic risk while simultaneously improving emotional regulation and perceived quality of life [ 8 , 9 ]. In this line, recent research has confirmed the strong relationship between lifestyle, body composition, and psychological well-being in individuals with severe mental disorders [ 10 ]. Crucially, recovery in SMD is increasingly viewed as a multidimensional process involving personal agency and social participation. This is vital, as recent evidence highlights that elevated psychotic symptoms can lead to impaired social functioning specifically through loneliness [ 11 ]. PA interventions may support these goals by enhancing functional autonomy and subjective well-being [ 12 , 13 ]. Yet, a significant research-to-practice gap remains. Most existing studies are limited by short intervention durations, small sample sizes, and a narrow focus on isolated clinical symptoms rather than comprehensive, real-world assessments [ 14 , 15 ]. Furthermore, identifying the specific benefits, facilitators, and barriers is crucial for the successful implementation of physical activity programs in this population [ 16 ]. Perhaps most importantly, the economic implications of PA in SMD populations are vastly under-researched. While healthcare costs in this group are primarily driven by inpatient stays and long-term medication use, few longitudinal studies have integrated rigorous economic evaluations alongside clinical and recovery outcomes [ 17 ]. Understanding whether structured PA can lead to tangible reductions in service utilization is essential for the sustainability of public mental health strategies. The present study addresses these limitations by evaluating a 15-month structured PA program in a large community-based sample of individuals with SMD in southern Spain. By integrating physical health indicators, psychological well-being, and healthcare expenditure over an extended period, we aim to examine the longitudinal associations between structured PA and multidimensional recovery, providing evidence on the clinical and economic feasibility of exercise-based interventions in real-world psychiatric care. Method Participants A total of 311 adults diagnosed with Severe Mental Disorders (SMD) were initially recruited from the Fundación Pública Andaluza para la Integración Social de Personas con Enfermedad Mental (FAISEM; Andalusian Public Foundation for the Social Integration of People with Mental Illness) across the eight provinces in Southern Spain. This multicenter recruitment strategy ensured territorial representativeness within the regional psychiatric population. Following eligibility screening, 289 individuals were enrolled. Due to the longitudinal nature of the 15-month study, natural attrition resulted in a final analytical sample of 156 participants, divided equally into experimental (n = 78) and control (n = 78) cohorts. The sample age ranged from 30 to 67 years (M = 49.76; SD = 7.90), with a male predominance (78.21%), aligning with the established demographic profile of institutionalized SMD services. The diagnostic composition was primarily defined by schizophrenia spectrum disorders (72.4%), followed by bipolar disorder (14.8%), major depressive disorder (7.7%), and other chronic psychiatric conditions (5.1%). Eligibility was determined by the following inclusion criteria: (i) a diagnosis of schizophrenia spectrum, bipolar, or other chronic SMD according to DSM-5-RT or ICD-11 criteria; (ii) a minimum illness duration of ≥ 2 years; (iii) age between 18 and 68 years; and (iv) medical clearance for moderate-intensity physical exertion. Exclusion criteria comprised recent adjustments to psychotropic medication (< 3 months), medical contraindications for exercise, or current participation in other structured physical programs. Based on these parameters, 22 individuals were excluded prior to enrollment. Study Design and Group Allocation Owing to clinical and organizational constraints within the community health network, a quasi-experimental design was adopted. Group allocation was determined by the regional availability of structured physical activity programs. The experimental group consisted of individuals who voluntarily enrolled in the intervention, while the control group was established via purposive matching based on province, age, sex, primary diagnosis, and illness duration to mitigate potential selection bias, specifically through rigorous purposive matching. While a randomized controlled trial (RCT) remains the gold standard, this quasi-experimental design was selected to prioritize ecological validity, reflecting the real-world sustainability of exercise programs in community clinical practice. At baseline, all participants had been sedentary for \geq 24 months, a period coinciding with COVID-19 mobility restrictions. Standard psychiatric and psychosocial care remained consistent for both groups throughout the 15-month observation period. Instruments and Measures Physical fitness Physical fitness was evaluated through standardized field-based protocols derived from the PREFIT battery [ 18 ]. Lower-body explosive power was determined using the standing long jump test; participants were instructed to jump horizontally as far as possible from a stationary position, maintaining a bilateral take-off and landing behind a clearly demarcated baseline. Cardiorespiratory fitness (CRF) was assessed via the 20-meter Shuttle Run Test (20m-SRT; [ 19 ], an incremental aerobic field test utilized to derive a predictive index of maximal oxygen uptake (VO 2 max). All assessments were conducted by calibrated clinical staff following the strict administrative and scoring criteria established by the PREFIT consortium to ensure inter-rater consistency and procedural fidelity. Body composition Body composition was assessed at the Andalusian Sports Medicine Center utilizing multi-frequency bioelectrical impedance analysis (BIA). The primary metrics extracted for analysis included body fat percentage, lean mass percentage, and the visceral fat index. To ensure data reliability and minimize metabolic interference, all measurements were conducted under strictly controlled conditions: participants were required to maintain a 48-hour abstinence from vigorous physical exertion, observe a 12-hour fast, and ensure bladder voiding immediately prior to the assessment, in alignment with manufacturer-validated protocols. Clinical interpretation of these parameters was contextualized using established sex-specific reference ranges, 6–24% for men and 14–31% for women, while a threshold of < 12 was utilized to define the normative range for visceral adiposity. Eating behaviours Dietary patterns were screened using a 45-item Food Frequency Questionnaire (FFQ) [ 20 ], designed to quantify consumption frequency across core nutritional domains over the preceding month. Given the critical role of nutrition in the metabolic profile of individuals with SMD, the analysis specifically targeted the intake of ultra-processed foods (UPFs) and high-glycemic products, including sugar-sweetened beverages, commercial confectionery, and energy drinks. These items were prioritized due to their established association with pro-inflammatory states and cardiometabolic dysregulation in psychiatric populations. Scoring and data processing followed the standardized algorithmic procedures established by the instrument’s developers to ensure internal validity. Weekly physical activity level Motivational readiness for exercise was assessed using the transtheoretical model-based algorithm proposed by Marcus and Owen [ 21 ]. This psychometric instrument stratifies participants into five distinct stages of behavioral change: precontemplation, contemplation, preparation, action, and maintenance. Within this framework, exercise was operationally defined as any structured or unstructured physical activity, such as brisk walking, swimming, or cycling, maintained for at least 20 minutes per session. To meet the clinical threshold for "regular engagement" (indicative of the action or maintenance stages), participants were required to complete three sessions per week over the preceding six-month period. This measure offers a validated, parsimonious framework for evaluating longitudinal behavioral shifts and has demonstrated high utility in clinical trials monitoring intervention adherence within psychiatric cohorts. Psychological variables Mental well-being was quantified using the Warwick–Edinburgh Mental Well-being Scale (WEMWBS), utilizing the Spanish validation by Castellví et al. [ 22 ]. This 14-item instrument is designed to capture eudaimonic and hedonic constructs, including affective-emotional states, cognitive-evaluative dimensions, and interpersonal functioning over the preceding two weeks. Items are scored on a 5-point Likert scale (ranging from 1 = never to 5 = always ), with higher aggregate scores reflecting superior psychological functioning. Health-related quality of life (HRQoL) was evaluated via the WHOQOL-BREF [ 23 ], Spanish adaptation by Lucas [ 24 ]. This 26-item multidimensional instrument yields profiles across four primary domains: physical health, psychological health, social relationships, and environment, in addition to global health ratings. Responses are recorded on a 5-point scale; for clinical interpretation, global score were stratified into three functional tiers: poor (0–2.99), acceptable (3–3.99), and high (4–5), in accordance with established normative criteria for psychiatric cohorts. Healthcare expenditure Direct healthcare costs were estimated as a mean monthly per-capita expenditure, incorporating both psychiatric inpatient care and psychotropic pharmacotherapy. Inpatient service utilization was valued according to the standardized tariff schedule of the Andalusian Health Department, applying a degressive cost model: €200/day for the initial seven days of acute stabilization and €150/day for subsequent days (8–30). Pharmacological expenditures were derived from integrated electronic health records provided by the Andalusian Mental Health System and FAISEM. These data were cross-referenced with the official reference pricing database of the Spanish Agency for Medicines and Health Products (AEMPS) and the National Health System (NHS) nomenclature to ensure accurate unit cost valuation. All economic variables were computed in Euros (€) and treated as continuous data for the longitudinal comparative analysis. Procedure The study protocol was submitted to and approved by the Bioethics Committee of the University of Almería. Following ethical approval, potential participants from a regional public foundation for social integration were informed about the study objectives, procedures, and requirements for participation, including baseline and follow-up assessments and the 15-month physical activity intervention. All participants provided written informed consent, and the study was conducted in accordance with the principles of the Declaration of Helsinki. Participants were allocated to either the experimental or control group based on their stated preferences, consistent with the quasi-experimental pre–post design employed in this study. Initial data collection included all outcome measures, physical fitness, body composition, psychological well-being, quality of life, and healthcare expenditure, administered as a baseline assessment (pre-test). Participants in the experimental group then engaged in a structured physical activity programme over 15 months, consisting of at least two 60-minute supervised sessions per week. The programme targeted multiple physical domains, including cardiovascular endurance, muscular strength, agility, speed, and flexibility, through a combination of functional exercises and dynamic athletic activities adapted to participants’ abilities. Exercise intensity and complexity were progressively increased to promote sustained physiological improvements and adherence. Participants in the control group continued their standard psychiatric and psychosocial care without participation in structured physical activity, maintaining their habitual activity levels. At the end of the 15-month intervention, all outcome measures were reassessed (post-test) to evaluate changes in physical, psychological, and economic outcomes. Statistical Analysis Data analysis was performed using IBM SPSS Statistics (version 29.0). Preliminary analyses included descriptive statistics to characterize the sample’s sociodemographic profile (age and sex). The normality of the data was verified using the Kolmogorov-Smirnov test. Baseline differences between the experimental and control groups were examined using independent-samples Student’s t-tests. To explore the baseline relationships between body composition, physical fitness, and patient-reported outcomes (well-being and quality of life), Pearson’s or Spearman’s bivariate correlations were calculated as appropriate. Although non-parametric alternatives were considered when assumptions were violated, all variables met normality criteria; therefore, only parametric results were reported. To determine the effectiveness of the 15-month intervention, a series of mixed-design Analyses of Variance (ANOVA) were conducted. These models included "Group" (Experimental vs. Control) as the between-subjects factor and "Time" (Pre-test vs. Post-test) as the within-subjects factor; given the two-level within-subjects factor, the assumption of sphericity was inherently satisfied. The primary focus of the analyses was the Group x Time interaction effect, which indicated whether changes over the 15-month period differed significantly between the intervention and treatment-as-usual (TAU) groups. For significant interactions, post-hoc pairwise comparisons with Bonferroni adjustments were applied. Effect sizes were reported using partial eta-squared (η²p). Statistical significance was maintained at p < .05. Results Baseline descriptive statistics and between-group comparisons are presented in Table 1 . At study entry, the experimental and control groups were broadly comparable across most anthropometric, psychological, and healthcare cost variables. However, significant baseline differences were observed in selected domains. Specifically, the experimental group demonstrated higher cardiorespiratory endurance and weekly physical activity levels, as well as lower processed food consumption compared to the control group ( p < .01). No statistically significant differences were found between groups in lean mass, visceral fat, psychological well-being, quality of life, or healthcare costs at baseline. Table 1 Baseline characteristics and between-group comparisons using Student´s t -tests. Variable Experimental Group (n = 78) M (SD) Control Group (n = 78) M (SD) t p Anthropometrics Body fat (%) 28.44 (8.43) 30.41 (9.11) 1.17 .246 Lean mass (%) 57.81 (10.08) 56.80 (10.67) -0.506 .614 Visceral fat 12.15 (5.48) 12.59 (5.14) 0.425 .672 Physical Fitness Endurance (s) 297.15 (238.53) 195.79 (148.72) -3.185 .002 Standing long jump (m) 1.12 (0.36) 1.05 (0.33) -1.273 .205 Lifestyle & Behavior Weekly physical activity 4.14 (1.25) 2.63 (1.23) -7.605 < .001 Processed food (servings/week) 14.30 (9.24) 19.52 (11.03) 2.954 .004 Tobacco use (cigarettes/day) 8.94 (9.92) 11.77 (10.52) 1.731 .085 Psychological Outcomes Mental well-being (WEMWBS) 3.57 (0.76) 3.51 (0.77) -0.523 .602 Quality of life (WHOQOL) 3.39 (0.51) 3.30 (0.53) -1.185 .238 Healthcare Costs (€) Medication costs 225.63 (220.26) 225.94 (166.18) 0.010 .992 Hospitalization costs 76.92 (337.36) 148.08 (668.17) 0.840 .402 [PLEASE INSERT Table 1 ABOUT HERE] Since all variables satisfied the criteria for normal distribution, Pearson’s r coefficients were calculated to explore baseline relationships. As shown in Table 2 , adiposity markers (body fat and visceral fat) were inversely associated with physical performance, specifically cardiorespiratory endurance and explosive strength ( p < .001). Weekly physical activity levels correlated positively with endurance (r = 0.380, p < .001) and quality of life (r = 0.320, p < .001), while being negatively associated with visceral fat (r = -0.425, p < .001). Regarding dietary habits, processed food consumption was positively related to body fat (r = 0.197, p < .01) and visceral fat (r = 0.201, p < .01). Finally, a robust positive correlation was observed between mental well-being and quality of life (r = 0.816, p < .001), confirming the internal consistency of the patient-reported outcomes. Table 2 Bivariate Pearson correlations among baseline variables. Variable 1 2 3 4 5 6 7 8 9 10 1. Body fat (%) - 2. Lean mass (%) − .048 - 3. Visceral fat .516*** .191** - 4. Endurance − .298*** .143* − .299** - 5. Long jump − .301*** .167* − .210** .471*** - 6. Weekly PA − .240*** .178** − .425*** .254*** .209** - 7. Processed food .197** .033 .201** − .102 − .079 − .196** - 8. Tobacco .005 .113 .109* − .073 − .014 − .058 .008 - 9. Mental well-being − .070 .011 − .217** .097 .063 .380*** .060 − .032 - 10. Quality of life − .015 .050 − .136* .044 .001 .320*** .090 − .017 .816*** - [PLEASE INSERT Table 2 ABOUT HERE] A mixed-design analysis of variance (ANOVA) was conducted to evaluate longitudinal changes over the 15-month study period (Time) and to determine whether these trajectories differed as a function of the intervention. As detailed in Table 3 , significant main effects of Time were observed across the majority of parameters, indicating overall improvements in body composition, cardiorespiratory endurance, and psychological metrics ( p < .05). Table 3 Mixed-design ANOVA (Time × Group) for physiological, behavioral, and psychological variables Variable Time F(1, 182) p η²p ​ Time × Group F(1, 182) p η²p ​ Body fat (%) 50.98 < .001 .110 176.86 < .001 .301 Lean mass (%) 5.23 .023 .028 33.49 < .001 .115 Visceral fat 30.03 < .001 .144 190.62 < .001 .516 Endurance 6.57 .011 .021 53.32 < .001 .146 Standing long jump (m) 11.10 .001 .034 39.38 < .001 .112 Weekly PA 4.92 .027 .016 76.38 < .001 .197 Processed food 20.06 < .001 .074 15.67 < .001 .059 Tobacco 2.26 .134 .007 14.81 < .001 .045 Mental well-being 18.56 < .001 .056 37.12 < .001 .106 Quality of life 54.12 < .001 .148 83.27 < .001 .211 Medication costs (€) .41 .522 .003 12.63 < .001 .076 However, the analysis revealed robust and consistent Time × Group interaction effects across nearly all domains, with effect sizes ranging from small to large (η²p = .045 to .516). These interactions demonstrate that the experimental group achieved significantly greater clinical and behavioral gains compared to the control group. Notably, large interaction effects were identified for visceral fat (η²p = .516), body fat percentage (η²p = .301), and quality of life (η²p = .211). Furthermore, while lean mass initially exhibited higher variability, the final analysis showed a moderate interaction effect favoring the intervention (η²p = .115). [PLEASE INSERT Table 3 ABOUT HERE] Behavioral patterns also shifted significantly; tobacco consumption showed no significant main effect of Time ( p = .134), yet a significant interaction was found (p < .001), suggesting that smoking reduction was primarily concentrated within the experimental cohort. Regarding economic outcomes, medication-related expenditures did not decrease significantly for the sample as a whole ( p = .522). Nevertheless, the interaction term confirmed a meaningful reduction in pharmacological costs for the intervention group relative to controls (F(1, 182) = 12.63, p < .001, η²p = .076). Overall, the healthcare expenditure analysis showed that the experimental group achieved total savings of €9,903.73, equivalent to €126.97 per person per month. These lower expenditures were largely attributable to observed differences in psychiatric hospitalization frequency and medication costs between the two groups. In relative terms, this represents nearly a one-third decrease in total healthcare expenses compared to the control group, which did not demonstrate comparable financial improvements. Hospitalizations accounted for approximately 56% of total savings, while reductions in medication costs contributed the remaining 44%, underscoring the multifaceted economic benefit of the intervention (Table 4 ). These economic observations are exploratory and reflect resource utilisation patterns within this specific community context. Table 4 Healthcare Cost Savings (Control vs. Experimental Group, n = 78 per group) Category Control Group (€) Experimental Group (€) Total Savings (€) Savings per person (€) Medication costs (Pre-test) 17,623.70 17,599.28 – – Medication costs (Post-test) 20,193.37 15,815.21 – – Medication savings 2,569.66 -1,784.07 4,353.73 – Hospitalization savings 11,550.00 6,000.00 5,550.00 – Total Healthcare Savings – – 9,903.73 126.97 Note: p/p = per person per month. [PLEASE INSERT Table 4 ABOUT HERE] Discussion This 15-month study provides longitudinal evidence that structured PA interventions facilitate multidimensional recovery in individuals with SMD, impacting physical health, psychological resilience, and healthcare utilization. Our findings align with previous literature demonstrating that consistent physical activity (PA) leads to significant reductions in adiposity [ 8 , 9 ]. Specifically, the efficacy of resistance and strength training in reducing body fat percentage and visceral fat has been robustly supported by recent meta-analyses even in healthy populations, underlining its value as a primary metabolic intervention [ 26 ]. In the present study, the observed decrease in visceral fat is of paramount clinical importance, as visceral adiposity is a primary driver of metabolic syndrome and systemic inflammation in psychiatric populations—factors that directly contribute to the 15–20 year life expectancy gap [ 2 ]. By targeting this specific fat depot, structured PA may serve as a significant metabolic modifier, potentially offering cardioprotective benefits and mitigating the side effects common to long-term psychotropic treatment. These physiological gains were accompanied by sustained improvements in cardiorespiratory endurance and muscular strength (Table 3 ), further narrowing the "physical health gap" that characterizes SMD [ 3 ]. The observed improvements in mental well-being and quality of life (QoL) scores further support the integration of exercise into recovery-oriented frameworks [ 9 ]. This is particularly significant as recent evidence suggests that stress has a direct and cumulative effect on psychotic symptoms in daily life [ 27 ]; thus, the stress-buffering effects of structured PA may be a key mechanism behind the clinical stabilization observed in our experimental group.This approach is also consistent with current research protocols that emphasize the importance of co-production and feasibility to ensure that physical activity interventions are sustainable within community mental health settings [ 28 ]. Beyond symptom mitigation, the community-based delivery of the program likely fostered personal agency and social connectedness, potentially acting as a buffer against the social withdrawal and stigma often associated with SMD [ 29 ]. Addressing loneliness is particularly urgent, as recent evidence highlights that social adversity and loneliness are deeply interconnected drivers of poor outcomes in early psychosis [ 30 ]. This social dimension is of critical importance, as recent large-scale evidence identifies social exclusion as a major independent determinant of excess mortality in both schizophrenia and bipolar disorders [ 31 ], suggesting that by integrating patients into group activities, we are directly addressing a key mortality risk factor. Furthermore, this shift toward subjective well-being is consistent with contemporary models of psychiatric care that prioritize functional autonomy and social participation [ 13 ]. A distinctive contribution of this research is the quantification of economic outcomes, a dimension frequently overlooked in PA literature [ 17 ]. The experimental group demonstrated a mean monthly saving of €126.97 per participant, representing a reduction of approximately one-third in direct healthcare expenditures compared to the control group (Table 6). These savings were primarily driven by decreased psychiatric hospitalization frequency and optimized medication use. Specifically, while medication costs remained stable for the control cohort, the intervention group demonstrated a significant downward trajectory in pharmacological expenditure, as evidenced by the robust interaction effect (F = 12.63) despite the lack of a general time effect. This decrease in pharmacological expenditure was primarily driven by the significant clinical stabilization observed in the experimental group. As participants achieved better symptomatic control and psychological well-being through structured exercise, there was a reduced clinical need for high-dose psychotropic regimens and SOS (as-needed) medications. Our results suggest that structured PA is a potentially sustainable strategy capable of alleviating some of the financial burden SMD imposes on public health systems [ 32 ], although formal cost-effectiveness analyses are required to confirm this. Furthermore, our correlation analyses (Table 2 ) suggest that health gains are maximized when PA is part of a broader lifestyle shift. Specifically, the association between increased PA and reduced consumption of ultra-processed foods suggests a 'spillover effect', wherein engagement in structured exercise acts as a gateway to improved self-regulation and healthier dietary choices. This is further supported by our finding that smoking reduction was exclusive to the intervention group, as indicated by the significant interaction effect (p < .001) despite the absence of a general time trend for the whole sample. This phenomenon is particularly relevant in SMD, where poor nutritional habits and tobacco dependence often compound the metabolic risks of sedentary behavior. Our findings reinforce the need for holistic, multi-domain interventions that address the syndemic nature of physical and mental illness [ 33 ]. The 15-month follow-up period represents a significant strength of this research, substantially exceeding the duration of the majority of existing longitudinal studies in the field of exercise and severe mental illness. However, several limitations warrant consideration. The quasi-experimental design and preference-based allocation, while reflective of real-world clinical practice, preclude definitive causal inferences. A key limitation is the potential for selection bias; participants who chose to join the PA group may have possessed higher baseline motivation or better functional status than those in the control group. While we matched participants on key variables to mitigate this, future Randomized Controlled Trials (RCTs) are necessary to isolate the physiological impact of exercise from these confounding psychological factors. Furthermore, while the study captured direct healthcare expenditures, future research should incorporate indirect costs—such as caregiver burden and productivity losses—to provide a more comprehensive assessment of the intervention's full societal value. Adherence rates also fluctuated among participants, influenced by individual motivation and contextual barriers [34], which may affect the generalizability of the findings to more acute psychiatric populations. Despite these constraints, the integration of clinical and economic data provides a comprehensive perspective on the utility of exercise in psychiatric care, leading to the following conclusions. Conclusions The present 15-month longitudinal study provides robust evidence that a structured physical activity (PA) program is a potent catalyst for both clinical recovery and economic efficiency in the management of Severe Mental Disorders (SMD). Beyond the significant improvements in cardiometabolic health, particularly the reduction in visceral adiposity, and psychological well-being, the intervention yielded a substantial reduction in direct healthcare expenditures. The observed lower healthcare expenditures among PA participants suggest that structured exercise may contribute to the financial sustainability of public health services. These results argue for a shift in community mental health: structured PA should be considered a core, reimbursable component of holistic care to bridge the existing physical health gap. Declarations Funding: This work has been financed with the support of a project of the Andalusian Knowledge Agency (Ref. P20_00232). Competing interests : The authors have no relevant financial or non-financial interests to disclose. Ethics approval : This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the University of Almería. Consent to participate: Informed consent was obtained from all individual participants included in the study. Data availability : The data supporting the findings of this study are available from the corresponding author upon reasonable requestThe data supporting the findings of this study are available from the corresponding author upon reasonable request. Author Contribution A.J.C: Conceptualization, Methodology, Supervision, Writing – review & editing, Funding acquisition. M.J.L: Investigation, Formal analysis, Data curation, Writing – original draft, Visualization. J.L.C: Investigation, Data curation, Validation. A.L.P: Project administration, Resources, Methodology, Writing – review & editing. All authors read and approved the final manuscript Acknowledgement The authors would like to thank the staff and participants of the Andalusian Public Foundation for the Social Integration of People with Mental Illness (FAISEM) for their collaboration and support throughout the 15-month study period. Data Availability The data supporting the findings of this study are available from the corresponding author upon reasonable requestThe data supporting the findings of this study are available from the corresponding author upon reasonable request. References National Institute of Mental Health (2024) Mental illness. 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Soc Psychiatry Psychiatr Epidemiol 60:1335–1345. https://doi.org/10.1007/s00127-024-02754-7 Hassan J, Shannon S, Tully MA, McCartan C, Davidson G, Bunn R, Breslin G (2022) Systematic review of physical activity interventions assessing physical and mental health outcomes on patients with severe mental illness (SMI) within secure forensic settings. J Psychiatr Ment Health Nurs 29:630–646. https://doi.org/10.1111/jpm.12832 Peckham E, Tew G, Lorimer B, Bailey L, Beeken R, Cooper C et al (2023) Interventions to increase physical activity and reduce sedentary behaviour in severe mental ill health: How effective are they? A systematic review. Ment Health Phys Act 25:100547. https://doi.org/10.1016/j.mhpa.2023.100547 Méndez-Aguado C, Cangas AJ, Aguilar JM, Lirola MJ (2023) Benefits, facilitators and barrier reductions in physical activity programmes for people with severe mental disorder: A systematic review. Healthcare 11:1215. https://doi.org/10.3390/healthcare11091215 Alhusseini N, Lin TK, Werner K, Lin G, Altwaijri Y, Baattaiah BA et al (2025) Cost-effectiveness of physical activity-oriented interventions for improving mental health: A systematic review. BMC Public Health 25:1766. https://doi.org/10.1186/s12889-025-22207-3 Ortega FB, Cadenas-Sánchez C, Sánchez-Delgado G, Mora-González J, Martínez-Téllez B, Artero EG et al (2015) Systematic review and proposal of a field-based physical fitness-test battery in preschool children: the PREFIT battery. Sports Med 45:533–555. https://doi.org/10.1007/s40279-014-0281-8 Olds T, Tomkinson G, Léger L, Cazorla G (2006) Worldwide variation in the performance of children and adolescents: An analysis of 109 studies of the 20-m shuttle run test in 37 countries. J Sports Sci 24:1025–1038. https://doi.org/10.1080/02640410500432193 Trinidad I, Fernández J, Cucó G, Biarnés E, Arija V (2008) Validación de un cuestionario de frecuencia de consumo alimentario corto: Reproducibilidad y validez. Nutr Hosp 23:242–252 Marcus BH, Owen N (1992) Motivational readiness, self-efficacy and decision-making for exercise. J Appl Soc Psychol 22:3–16. https://doi.org/10.1111/j.1559-1816.1992.tb01518.x Castellví P, Forero GG, Codony M, Vilagut G, Brugulat P, Medina A, Alonso J (2014) The Spanish version of the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS) is valid for use in the general population. Qual Life Res 23:857–868. https://doi.org/10.1007/s11136-013-0513-7 The WHOQOL Group (1998) Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychol Med 28:551–558. https://doi.org/10.1017/s0033291798006667 Lucas R (1998) Versión Española del WHOQOL. Editorial Ergón, Madrid Wewege MA, Desai I, Honey C et al (2022) The Effect of Resistance Training in Healthy Adults on Body Fat Percentage, Fat Mass and Visceral Fat: A Systematic Review and Meta-Analysis. Sports Med 52:287–300. https://doi.org/10.1007/s40279-021-01562-2 Cavelti M, Kaeser JM, Sele S, Berger T, Kaess M, Kindler J, Michel C (2025) The relationship between stress and clinical high-risk symptoms of psychosis in daily life: Impact of contemporaneous paths on cross-lagged effects. Psychol Med 55:e68. https://doi.org/10.1017/S0033291725000364 Jones G, Bailey L, Beeken RJ, Brady S, Cooper C, Copeland RJ et al (2024) Supporting physical activity through co-production in people with severe mental ill health (SPACES): protocol for a randomised controlled feasibility trial. Pilot Feasibility Stud 10:32. https://doi.org/10.1186/s40814-024-01460-0 Deenik J, Kruisdijk F, Tenback D, Braakman-Jansen A, van Harten P, Vancampfort D (2019) Implementation of a lifestyle enhancement program among people with severe mental illness in a mental health care setting: A process evaluation. BMC Psychiatry 19:109. https://doi.org/10.1186/s12913-021-07391-3 Botello R, Gandhi A, Grunfeld G et al (2025) Social adversity and loneliness in first episode psychosis. Soc Psychiatry Psychiatr Epidemiol 60:2735–2745. https://doi.org/10.1007/s00127-025-02958-5 Das-Munshi J, Cybulski L, Byrne P, Dewey M, Hildersley R, Markham S et al (2025) Social exclusion as a determinant of excess mortality in people with schizophrenia-spectrum and bipolar disorders: Retrospective cohort study in 0.5 million people. Psychol Med 55:e375. https://doi.org/10.1017/S0033291725102110 Firth J, Carney R, Stubbs B, Teasdale SB, Vancampfort D, Ward PB (2017) The effects of physical exercise on cardiovascular risk factors in people with schizophrenia: A systematic review and meta-analysis. Schizophr Res 191:110–115. https://doi.org/10.1016/j.schres.2017.03.012 Lewis K, Roden-Lui G, Faulkner G, Gibbon S, Hewitt C, Hughes E et al (2025) Barriers and facilitators to increasing physical activity in medium secure mental health settings: An exploration of staff perceptions. Ment Health Phys Act 28:100663. https://doi.org/10.1016/j.mhpa.2024.100663 Firth J, Rosenbaum S, Stubbs B, Gorczynski P, Yung AR, Vancampfort D (2016) Motivating factors and barriers towards exercise in severe mental illness: a systematic review and meta-analysis. Psychol Med 46:2869–2881. https://doi.org/10.1017/S0033291716001732 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 14 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviews received at journal 02 Mar, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers agreed at journal 08 Feb, 2026 Reviewers invited by journal 08 Feb, 2026 Editor assigned by journal 03 Feb, 2026 Submission checks completed at journal 07 Jan, 2026 First submitted to journal 06 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Cangas","email":"","orcid":"","institution":"University of Almería","correspondingAuthor":false,"prefix":"","firstName":"Adolfo","middleName":"J.","lastName":"Cangas","suffix":""},{"id":589323753,"identity":"1ca2d163-f7f5-4764-a991-29b8a9067593","order_by":1,"name":"María Jesús Lirola","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqUlEQVRIiWNgGAWjYDACdgYG459/bMAMIgEzA0MxY0MamEG8ls+MDYdJ0KLbzJ24uXDH+cT+ZgbGhz+I0WJ2mHez8cwztxNnHGZgNuYhUss2Ax6224lAt7FJE+UwoJbtP3jYziXOP8zA/pNYh20w5m07kLgBaAsDsQ7bYDjjTLLxxsOMzdLEaTneu8HgQ4Wd7LzjzQc/EuUwJMDYQKKGUTAKRsEoGAU4AQC7mTOedlbc0QAAAABJRU5ErkJggg==","orcid":"","institution":"University of Almería","correspondingAuthor":true,"prefix":"","firstName":"María","middleName":"Jesús","lastName":"Lirola","suffix":""},{"id":589323754,"identity":"94419369-ac56-4ecc-8d12-192b91f80e45","order_by":2,"name":"Juan Leandro Cerezuela","email":"","orcid":"","institution":"University of Almería","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"Leandro","lastName":"Cerezuela","suffix":""},{"id":589323755,"identity":"10cdae9e-7256-400e-aad2-b3d0a65713d3","order_by":3,"name":"Andrés López Pardo","email":"","orcid":"","institution":"FAISEM","correspondingAuthor":false,"prefix":"","firstName":"Andrés","middleName":"López","lastName":"Pardo","suffix":""}],"badges":[],"createdAt":"2026-01-06 12:24:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8531325/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8531325/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102747064,"identity":"ffae4460-3331-485d-b79b-9d42499bc887","added_by":"auto","created_at":"2026-02-16 09:03:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":905906,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8531325/v1/3c4e9312-f351-410b-80d6-6f9ba2073863.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Longitudinal impact of physical activity on visceral adiposity, recovery, and costs in severe mental disorders: a 15-month quasi-experimental study in a community setting","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSevere Mental Disorders (SMD)\u0026mdash;encompassing schizophrenia spectrum disorders, bipolar disorder, and other chronic psychiatric conditions\u0026mdash;are defined by persistent functional impairment and high levels of healthcare utilization [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Beyond individual morbidity, SMD pose a formidable public health challenge, driven by a well-documented 'physical health gap.' Individuals with SMD face a 15\u0026ndash;20 year reduction in life expectancy compared to the general population, largely due to preventable cardiovascular and metabolic diseases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This long-term risk is underscored by recent evidence from a 25-year follow-up study, which identified that physical health comorbidities and lifestyle factors remain the primary predictors of mortality from the first episode of psychosis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTraditional management has historically focused on pharmacological stabilization and psychosocial rehabilitation. However, despite these interventions, high relapse rates and frequent psychiatric hospitalizations continue to strain mental health systems [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Recent evidence from network meta-analyses further supports a shift in this paradigm, demonstrating that various exercise modalities are significantly effective in reducing psychiatric symptomatology, particularly in patients with schizophrenia [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Within this context, physical activity (PA) has emerged not merely as a lifestyle adjunct, but as a core component of recovery-oriented frameworks. Evidence suggests that regular PA can mitigate cardiometabolic risk while simultaneously improving emotional regulation and perceived quality of life [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In this line, recent research has confirmed the strong relationship between lifestyle, body composition, and psychological well-being in individuals with severe mental disorders [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCrucially, recovery in SMD is increasingly viewed as a multidimensional process involving personal agency and social participation. This is vital, as recent evidence highlights that elevated psychotic symptoms can lead to impaired social functioning specifically through loneliness [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. PA interventions may support these goals by enhancing functional autonomy and subjective well-being [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Yet, a significant research-to-practice gap remains. Most existing studies are limited by short intervention durations, small sample sizes, and a narrow focus on isolated clinical symptoms rather than comprehensive, real-world assessments [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, identifying the specific benefits, facilitators, and barriers is crucial for the successful implementation of physical activity programs in this population [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePerhaps most importantly, the economic implications of PA in SMD populations are vastly under-researched. While healthcare costs in this group are primarily driven by inpatient stays and long-term medication use, few longitudinal studies have integrated rigorous economic evaluations alongside clinical and recovery outcomes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Understanding whether structured PA can lead to tangible reductions in service utilization is essential for the sustainability of public mental health strategies.\u003c/p\u003e \u003cp\u003eThe present study addresses these limitations by evaluating a 15-month structured PA program in a large community-based sample of individuals with SMD in southern Spain. By integrating physical health indicators, psychological well-being, and healthcare expenditure over an extended period, we aim to examine the longitudinal associations between structured PA and multidimensional recovery, providing evidence on the clinical and economic feasibility of exercise-based interventions in real-world psychiatric care.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA total of 311 adults diagnosed with Severe Mental Disorders (SMD) were initially recruited from the \u003cem\u003eFundaci\u0026oacute;n P\u0026uacute;blica Andaluza para la Integraci\u0026oacute;n Social de Personas con Enfermedad Mental\u003c/em\u003e (FAISEM; Andalusian Public Foundation for the Social Integration of People with Mental Illness) across the eight provinces in Southern Spain. This multicenter recruitment strategy ensured territorial representativeness within the regional psychiatric population. Following eligibility screening, 289 individuals were enrolled. Due to the longitudinal nature of the 15-month study, natural attrition resulted in a final analytical sample of 156 participants, divided equally into experimental (n\u0026thinsp;=\u0026thinsp;78) and control (n\u0026thinsp;=\u0026thinsp;78) cohorts. The sample age ranged from 30 to 67 years (M\u0026thinsp;=\u0026thinsp;49.76; SD\u0026thinsp;=\u0026thinsp;7.90), with a male predominance (78.21%), aligning with the established demographic profile of institutionalized SMD services. The diagnostic composition was primarily defined by schizophrenia spectrum disorders (72.4%), followed by bipolar disorder (14.8%), major depressive disorder (7.7%), and other chronic psychiatric conditions (5.1%).\u003c/p\u003e \u003cp\u003eEligibility was determined by the following inclusion criteria: (i) a diagnosis of schizophrenia spectrum, bipolar, or other chronic SMD according to DSM-5-RT or ICD-11 criteria; (ii) a minimum illness duration of \u0026ge;\u0026thinsp;2 years; (iii) age between 18 and 68 years; and (iv) medical clearance for moderate-intensity physical exertion. Exclusion criteria comprised recent adjustments to psychotropic medication (\u0026lt;\u0026thinsp;3 months), medical contraindications for exercise, or current participation in other structured physical programs. Based on these parameters, 22 individuals were excluded prior to enrollment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design and Group Allocation\u003c/h3\u003e\n\u003cp\u003eOwing to clinical and organizational constraints within the community health network, a quasi-experimental design was adopted. Group allocation was determined by the regional availability of structured physical activity programs. The experimental group consisted of individuals who voluntarily enrolled in the intervention, while the control group was established via purposive matching based on province, age, sex, primary diagnosis, and illness duration to mitigate potential selection bias, specifically through rigorous purposive matching. While a randomized controlled trial (RCT) remains the gold standard, this quasi-experimental design was selected to prioritize ecological validity, reflecting the real-world sustainability of exercise programs in community clinical practice. At baseline, all participants had been sedentary for \\geq 24 months, a period coinciding with COVID-19 mobility restrictions. Standard psychiatric and psychosocial care remained consistent for both groups throughout the 15-month observation period.\u003c/p\u003e\n\u003ch3\u003eInstruments and Measures\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePhysical fitness\u003c/h2\u003e \u003cp\u003ePhysical fitness was evaluated through standardized field-based protocols derived from the PREFIT battery [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Lower-body explosive power was determined using the standing long jump test; participants were instructed to jump horizontally as far as possible from a stationary position, maintaining a bilateral take-off and landing behind a clearly demarcated baseline. Cardiorespiratory fitness (CRF) was assessed via the 20-meter Shuttle Run Test (20m-SRT; [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], an incremental aerobic field test utilized to derive a predictive index of maximal oxygen uptake (VO\u003csub\u003e2\u003c/sub\u003emax). All assessments were conducted by calibrated clinical staff following the strict administrative and scoring criteria established by the PREFIT consortium to ensure inter-rater consistency and procedural fidelity.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBody composition\u003c/h3\u003e\n\u003cp\u003eBody composition was assessed at the Andalusian Sports Medicine Center utilizing multi-frequency bioelectrical impedance analysis (BIA). The primary metrics extracted for analysis included body fat percentage, lean mass percentage, and the visceral fat index. To ensure data reliability and minimize metabolic interference, all measurements were conducted under strictly controlled conditions: participants were required to maintain a 48-hour abstinence from vigorous physical exertion, observe a 12-hour fast, and ensure bladder voiding immediately prior to the assessment, in alignment with manufacturer-validated protocols. Clinical interpretation of these parameters was contextualized using established sex-specific reference ranges, 6\u0026ndash;24% for men and 14\u0026ndash;31% for women, while a threshold of \u0026lt;\u0026thinsp;12 was utilized to define the normative range for visceral adiposity.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEating behaviours\u003c/h2\u003e \u003cp\u003eDietary patterns were screened using a 45-item Food Frequency Questionnaire (FFQ) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], designed to quantify consumption frequency across core nutritional domains over the preceding month. Given the critical role of nutrition in the metabolic profile of individuals with SMD, the analysis specifically targeted the intake of ultra-processed foods (UPFs) and high-glycemic products, including sugar-sweetened beverages, commercial confectionery, and energy drinks. These items were prioritized due to their established association with pro-inflammatory states and cardiometabolic dysregulation in psychiatric populations. Scoring and data processing followed the standardized algorithmic procedures established by the instrument\u0026rsquo;s developers to ensure internal validity.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWeekly physical activity level\u003c/h3\u003e\n\u003cp\u003eMotivational readiness for exercise was assessed using the transtheoretical model-based algorithm proposed by Marcus and Owen [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This psychometric instrument stratifies participants into five distinct stages of behavioral change: precontemplation, contemplation, preparation, action, and maintenance. Within this framework, exercise was operationally defined as any structured or unstructured physical activity, such as brisk walking, swimming, or cycling, maintained for at least 20 minutes per session. To meet the clinical threshold for \"regular engagement\" (indicative of the action or maintenance stages), participants were required to complete three sessions per week over the preceding six-month period. This measure offers a validated, parsimonious framework for evaluating longitudinal behavioral shifts and has demonstrated high utility in clinical trials monitoring intervention adherence within psychiatric cohorts.\u003c/p\u003e\n\u003ch3\u003ePsychological variables\u003c/h3\u003e\n\u003cp\u003eMental well-being was quantified using the Warwick\u0026ndash;Edinburgh Mental Well-being Scale (WEMWBS), utilizing the Spanish validation by Castellv\u0026iacute; et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This 14-item instrument is designed to capture eudaimonic and hedonic constructs, including affective-emotional states, cognitive-evaluative dimensions, and interpersonal functioning over the preceding two weeks. Items are scored on a 5-point Likert scale (ranging from 1\u0026thinsp;=\u0026thinsp;\u003cem\u003enever\u003c/em\u003e to 5\u0026thinsp;=\u0026thinsp;\u003cem\u003ealways\u003c/em\u003e), with higher aggregate scores reflecting superior psychological functioning.\u003c/p\u003e \u003cp\u003eHealth-related quality of life (HRQoL) was evaluated via the WHOQOL-BREF [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Spanish adaptation by Lucas [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This 26-item multidimensional instrument yields profiles across four primary domains: physical health, psychological health, social relationships, and environment, in addition to global health ratings. Responses are recorded on a 5-point scale; for clinical interpretation, global score were stratified into three functional tiers: poor (0\u0026ndash;2.99), acceptable (3\u0026ndash;3.99), and high (4\u0026ndash;5), in accordance with established normative criteria for psychiatric cohorts.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHealthcare expenditure\u003c/h2\u003e \u003cp\u003eDirect healthcare costs were estimated as a mean monthly per-capita expenditure, incorporating both psychiatric inpatient care and psychotropic pharmacotherapy. Inpatient service utilization was valued according to the standardized tariff schedule of the Andalusian Health Department, applying a degressive cost model: \u0026euro;200/day for the initial seven days of acute stabilization and \u0026euro;150/day for subsequent days (8\u0026ndash;30). Pharmacological expenditures were derived from integrated electronic health records provided by the Andalusian Mental Health System and FAISEM. These data were cross-referenced with the official reference pricing database of the Spanish Agency for Medicines and Health Products (AEMPS) and the National Health System (NHS) nomenclature to ensure accurate unit cost valuation. All economic variables were computed in Euros (\u0026euro;) and treated as continuous data for the longitudinal comparative analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cp\u003e The study protocol was submitted to and approved by the Bioethics Committee of the University of Almer\u0026iacute;a. Following ethical approval, potential participants from a regional public foundation for social integration were informed about the study objectives, procedures, and requirements for participation, including baseline and follow-up assessments and the 15-month physical activity intervention. All participants provided written informed consent, and the study was conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003eParticipants were allocated to either the experimental or control group based on their stated preferences, consistent with the quasi-experimental pre\u0026ndash;post design employed in this study. Initial data collection included all outcome measures, physical fitness, body composition, psychological well-being, quality of life, and healthcare expenditure, administered as a baseline assessment (pre-test).\u003c/p\u003e \u003cp\u003eParticipants in the experimental group then engaged in a structured physical activity programme over 15 months, consisting of at least two 60-minute supervised sessions per week. The programme targeted multiple physical domains, including cardiovascular endurance, muscular strength, agility, speed, and flexibility, through a combination of functional exercises and dynamic athletic activities adapted to participants\u0026rsquo; abilities. Exercise intensity and complexity were progressively increased to promote sustained physiological improvements and adherence. Participants in the control group continued their standard psychiatric and psychosocial care without participation in structured physical activity, maintaining their habitual activity levels.\u003c/p\u003e \u003cp\u003eAt the end of the 15-month intervention, all outcome measures were reassessed (post-test) to evaluate changes in physical, psychological, and economic outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData analysis was performed using IBM SPSS Statistics (version 29.0). Preliminary analyses included descriptive statistics to characterize the sample\u0026rsquo;s sociodemographic profile (age and sex). The normality of the data was verified using the Kolmogorov-Smirnov test. Baseline differences between the experimental and control groups were examined using independent-samples Student\u0026rsquo;s t-tests. To explore the baseline relationships between body composition, physical fitness, and patient-reported outcomes (well-being and quality of life), Pearson\u0026rsquo;s or Spearman\u0026rsquo;s bivariate correlations were calculated as appropriate. Although non-parametric alternatives were considered when assumptions were violated, all variables met normality criteria; therefore, only parametric results were reported.\u003c/p\u003e \u003cp\u003eTo determine the effectiveness of the 15-month intervention, a series of mixed-design Analyses of Variance (ANOVA) were conducted. These models included \"Group\" (Experimental vs. Control) as the between-subjects factor and \"Time\" (Pre-test vs. Post-test) as the within-subjects factor; given the two-level within-subjects factor, the assumption of sphericity was inherently satisfied. The primary focus of the analyses was the Group x Time interaction effect, which indicated whether changes over the 15-month period differed significantly between the intervention and treatment-as-usual (TAU) groups. For significant interactions, \u003cem\u003epost-hoc\u003c/em\u003e pairwise comparisons with Bonferroni adjustments were applied. Effect sizes were reported using partial eta-squared (η\u0026sup2;p). Statistical significance was maintained at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eBaseline descriptive statistics and between-group comparisons are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. At study entry, the experimental and control groups were broadly comparable across most anthropometric, psychological, and healthcare cost variables. However, significant baseline differences were observed in selected domains. Specifically, the experimental group demonstrated higher cardiorespiratory endurance and weekly physical activity levels, as well as lower processed food consumption compared to the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01). No statistically significant differences were found between groups in lean mass, visceral fat, psychological well-being, quality of life, or healthcare costs at baseline.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics and between-group comparisons using Student\u0026acute;s \u003cem\u003et\u003c/em\u003e-tests.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExperimental Group (n\u0026thinsp;=\u0026thinsp;78) M (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl Group (n\u0026thinsp;=\u0026thinsp;78) M (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthropometrics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.44 (8.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.41 (9.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLean mass (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.81 (10.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.80 (10.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisceral fat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.15 (5.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.59 (5.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical Fitness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndurance (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e297.15 (238.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e195.79 (148.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStanding long jump (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.12 (0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.05 (0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLifestyle \u0026amp; Behavior\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.14 (1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.63 (1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcessed food (servings/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.30 (9.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.52 (11.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco use (cigarettes/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.94 (9.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.77 (10.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychological Outcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental well-being (WEMWBS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.57 (0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.51 (0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuality of life (WHOQOL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.39 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.30 (0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealthcare Costs (\u0026euro;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e225.63 (220.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e225.94 (166.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.992\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76.92 (337.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e148.08 (668.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.402\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e[PLEASE INSERT Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eSince all variables satisfied the criteria for normal distribution, Pearson\u0026rsquo;s r coefficients were calculated to explore baseline relationships. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, adiposity markers (body fat and visceral fat) were inversely associated with physical performance, specifically cardiorespiratory endurance and explosive strength (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Weekly physical activity levels correlated positively with endurance (r\u0026thinsp;=\u0026thinsp;0.380, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and quality of life (r\u0026thinsp;=\u0026thinsp;0.320, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), while being negatively associated with visceral fat (r = -0.425, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Regarding dietary habits, processed food consumption was positively related to body fat (r\u0026thinsp;=\u0026thinsp;0.197, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01) and visceral fat (r\u0026thinsp;=\u0026thinsp;0.201, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01). Finally, a robust positive correlation was observed between mental well-being and quality of life (r\u0026thinsp;=\u0026thinsp;0.816, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), confirming the internal consistency of the patient-reported outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate Pearson correlations among baseline variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Body fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Lean mass (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Visceral fat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.516***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.191**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Endurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.298***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.143*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.299**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Long jump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.301***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.167*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.210**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.471***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Weekly PA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.240***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.178**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.425***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.254***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.209**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Processed food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.197**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.201**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.196**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Tobacco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.109*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9. Mental well-being\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.217**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.380***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10. Quality of life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.136*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.320***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.816***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e[PLEASE INSERT Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eA mixed-design analysis of variance (ANOVA) was conducted to evaluate longitudinal changes over the 15-month study period (Time) and to determine whether these trajectories differed as a function of the intervention. As detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, significant main effects of Time were observed across the majority of parameters, indicating overall improvements in body composition, cardiorespiratory endurance, and psychological metrics (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMixed-design ANOVA (Time \u0026times; Group) for physiological, behavioral, and psychological variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003cp\u003eF(1, 182)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eη\u0026sup2;p ​\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTime \u0026times; Group F(1, 182)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eη\u0026sup2;p ​\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e176.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLean mass (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisceral fat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e190.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.516\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStanding long jump (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly PA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcessed food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental well-being\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuality of life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication costs (\u0026euro;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHowever, the analysis revealed robust and consistent Time \u0026times; Group interaction effects across nearly all domains, with effect sizes ranging from small to large (η\u0026sup2;p\u0026thinsp;=\u0026thinsp;.045 to .516). These interactions demonstrate that the experimental group achieved significantly greater clinical and behavioral gains compared to the control group. Notably, large interaction effects were identified for visceral fat (η\u0026sup2;p\u0026thinsp;=\u0026thinsp;.516), body fat percentage (η\u0026sup2;p\u0026thinsp;=\u0026thinsp;.301), and quality of life (η\u0026sup2;p\u0026thinsp;=\u0026thinsp;.211). Furthermore, while lean mass initially exhibited higher variability, the final analysis showed a moderate interaction effect favoring the intervention (η\u0026sup2;p\u0026thinsp;=\u0026thinsp;.115).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e[PLEASE INSERT Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eBehavioral patterns also shifted significantly; tobacco consumption showed no significant main effect of Time (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.134), yet a significant interaction was found \u003cem\u003e(p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), suggesting that smoking reduction was primarily concentrated within the experimental cohort. Regarding economic outcomes, medication-related expenditures did not decrease significantly for the sample as a whole (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.522). Nevertheless, the interaction term confirmed a meaningful reduction in pharmacological costs for the intervention group relative to controls (F(1, 182)\u0026thinsp;=\u0026thinsp;12.63, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, η\u0026sup2;p\u0026thinsp;=\u0026thinsp;.076).\u003c/p\u003e \u003cp\u003eOverall, the healthcare expenditure analysis showed that the experimental group achieved total savings of \u0026euro;9,903.73, equivalent to \u0026euro;126.97 per person per month. These lower expenditures were largely attributable to observed differences in psychiatric hospitalization frequency and medication costs between the two groups. In relative terms, this represents nearly a one-third decrease in total healthcare expenses compared to the control group, which did not demonstrate comparable financial improvements. Hospitalizations accounted for approximately 56% of total savings, while reductions in medication costs contributed the remaining 44%, underscoring the multifaceted economic benefit of the intervention (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These economic observations are exploratory and reflect resource utilisation patterns within this specific community context.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHealthcare Cost Savings (Control vs. Experimental Group, n\u0026thinsp;=\u0026thinsp;78 per group)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl Group (\u0026euro;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExperimental Group (\u0026euro;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal Savings (\u0026euro;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSavings per person (\u0026euro;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication costs (Pre-test)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,623.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17,599.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication costs (Post-test)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,193.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,815.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication savings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,569.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1,784.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,353.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization savings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,550.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,000.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,550.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Healthcare Savings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,903.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e126.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote: p/p\u0026thinsp;=\u0026thinsp;per person per month.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e[PLEASE INSERT Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis 15-month study provides longitudinal evidence that structured PA interventions facilitate multidimensional recovery in individuals with SMD, impacting physical health, psychological resilience, and healthcare utilization.\u003c/p\u003e \u003cp\u003eOur findings align with previous literature demonstrating that consistent physical activity (PA) leads to significant reductions in adiposity [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Specifically, the efficacy of resistance and strength training in reducing body fat percentage and visceral fat has been robustly supported by recent meta-analyses even in healthy populations, underlining its value as a primary metabolic intervention [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In the present study, the observed decrease in visceral fat is of paramount clinical importance, as visceral adiposity is a primary driver of metabolic syndrome and systemic inflammation in psychiatric populations\u0026mdash;factors that directly contribute to the 15\u0026ndash;20 year life expectancy gap [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. By targeting this specific fat depot, structured PA may serve as a significant metabolic modifier, potentially offering cardioprotective benefits and mitigating the side effects common to long-term psychotropic treatment. These physiological gains were accompanied by sustained improvements in cardiorespiratory endurance and muscular strength (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), further narrowing the \"physical health gap\" that characterizes SMD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe observed improvements in mental well-being and quality of life (QoL) scores further support the integration of exercise into recovery-oriented frameworks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This is particularly significant as recent evidence suggests that stress has a direct and cumulative effect on psychotic symptoms in daily life [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]; thus, the stress-buffering effects of structured PA may be a key mechanism behind the clinical stabilization observed in our experimental group.This approach is also consistent with current research protocols that emphasize the importance of co-production and feasibility to ensure that physical activity interventions are sustainable within community mental health settings [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond symptom mitigation, the community-based delivery of the program likely fostered personal agency and social connectedness, potentially acting as a buffer against the social withdrawal and stigma often associated with SMD [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Addressing loneliness is particularly urgent, as recent evidence highlights that social adversity and loneliness are deeply interconnected drivers of poor outcomes in early psychosis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This social dimension is of critical importance, as recent large-scale evidence identifies social exclusion as a major independent determinant of excess mortality in both schizophrenia and bipolar disorders [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], suggesting that by integrating patients into group activities, we are directly addressing a key mortality risk factor. Furthermore, this shift toward subjective well-being is consistent with contemporary models of psychiatric care that prioritize functional autonomy and social participation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA distinctive contribution of this research is the quantification of economic outcomes, a dimension frequently overlooked in PA literature [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The experimental group demonstrated a mean monthly saving of \u0026euro;126.97 per participant, representing a reduction of approximately one-third in direct healthcare expenditures compared to the control group (Table\u0026nbsp;6). These savings were primarily driven by decreased psychiatric hospitalization frequency and optimized medication use. Specifically, while medication costs remained stable for the control cohort, the intervention group demonstrated a significant downward trajectory in pharmacological expenditure, as evidenced by the robust interaction effect (F\u0026thinsp;=\u0026thinsp;12.63) despite the lack of a general time effect. This decrease in pharmacological expenditure was primarily driven by the significant clinical stabilization observed in the experimental group. As participants achieved better symptomatic control and psychological well-being through structured exercise, there was a reduced clinical need for high-dose psychotropic regimens and SOS (as-needed) medications. Our results suggest that structured PA is a potentially sustainable strategy capable of alleviating some of the financial burden SMD imposes on public health systems [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], although formal cost-effectiveness analyses are required to confirm this.\u003c/p\u003e \u003cp\u003eFurthermore, our correlation analyses (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) suggest that health gains are maximized when PA is part of a broader lifestyle shift. Specifically, the association between increased PA and reduced consumption of ultra-processed foods suggests a 'spillover effect', wherein engagement in structured exercise acts as a gateway to improved self-regulation and healthier dietary choices. This is further supported by our finding that smoking reduction was exclusive to the intervention group, as indicated by the significant interaction effect (p\u0026thinsp;\u0026lt;\u0026thinsp;.001) despite the absence of a general time trend for the whole sample. This phenomenon is particularly relevant in SMD, where poor nutritional habits and tobacco dependence often compound the metabolic risks of sedentary behavior. Our findings reinforce the need for holistic, multi-domain interventions that address the syndemic nature of physical and mental illness [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe 15-month follow-up period represents a significant strength of this research, substantially exceeding the duration of the majority of existing longitudinal studies in the field of exercise and severe mental illness. However, several limitations warrant consideration. The quasi-experimental design and preference-based allocation, while reflective of real-world clinical practice, preclude definitive causal inferences. A key limitation is the potential for selection bias; participants who chose to join the PA group may have possessed higher baseline motivation or better functional status than those in the control group. While we matched participants on key variables to mitigate this, future Randomized Controlled Trials (RCTs) are necessary to isolate the physiological impact of exercise from these confounding psychological factors.\u003c/p\u003e \u003cp\u003eFurthermore, while the study captured direct healthcare expenditures, future research should incorporate indirect costs\u0026mdash;such as caregiver burden and productivity losses\u0026mdash;to provide a more comprehensive assessment of the intervention's full societal value. Adherence rates also fluctuated among participants, influenced by individual motivation and contextual barriers [34], which may affect the generalizability of the findings to more acute psychiatric populations.\u003c/p\u003e \u003cp\u003eDespite these constraints, the integration of clinical and economic data provides a comprehensive perspective on the utility of exercise in psychiatric care, leading to the following conclusions.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present 15-month longitudinal study provides robust evidence that a structured physical activity (PA) program is a potent catalyst for both clinical recovery and economic efficiency in the management of Severe Mental Disorders (SMD). Beyond the significant improvements in cardiometabolic health, particularly the reduction in visceral adiposity, and psychological well-being, the intervention yielded a substantial reduction in direct healthcare expenditures.\u003c/p\u003e \u003cp\u003eThe observed lower healthcare expenditures among PA participants suggest that structured exercise may contribute to the financial sustainability of public health services. These results argue for a shift in community mental health: structured PA should be considered a core, reimbursable component of holistic care to bridge the existing physical health gap.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work has been financed with the support of a project of the Andalusian Knowledge Agency (Ref. P20_00232). \u003cb\u003eCompeting interests\u003c/b\u003e: The authors have no relevant financial or non-financial interests to disclose. \u003cb\u003eEthics approval\u003c/b\u003e: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the University of Almer\u0026iacute;a. Consent to participate: Informed consent was obtained from all individual participants included in the study. \u003cb\u003eData availability\u003c/b\u003e: The data supporting the findings of this study are available from the corresponding author upon reasonable requestThe data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.J.C: Conceptualization, Methodology, Supervision, Writing \u0026ndash; review \u0026amp; editing, Funding acquisition. M.J.L: Investigation, Formal analysis, Data curation, Writing \u0026ndash; original draft, Visualization. J.L.C: Investigation, Data curation, Validation. A.L.P: Project administration, Resources, Methodology, Writing \u0026ndash; review \u0026amp; editing. All authors read and approved the final manuscript\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank the staff and participants of the Andalusian Public Foundation for the Social Integration of People with Mental Illness (FAISEM) for their collaboration and support throughout the 15-month study period.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author upon reasonable requestThe data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNational Institute of Mental Health (2024) Mental illness. 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Psychol Med 46:2869\u0026ndash;2881. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0033291716001732\u003c/span\u003e\u003cspan address=\"10.1017/S0033291716001732\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Severe Mental Disorder, Physical Activity, Healthcare Costs, Economic Evaluation, Quality of Life, Longitudinal Study","lastPublishedDoi":"10.21203/rs.3.rs-8531325/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8531325/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eSevere mental disorders (SMD) are associated with marked physical comorbidity, premature mortality, and substantial healthcare utilisation. Although physical activity (PA) is increasingly recommended as an adjunctive intervention, long-term real-world evidence linking PA participation with both clinical outcomes and healthcare costs in community psychiatric settings remains limited. This study examined longitudinal associations between engagement in a structured PA programme and health-related and economic outcomes among individuals with SMD.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA 15-month quasi-experimental longitudinal study was conducted with 156 adults diagnosed with SMD receiving routine community mental health care. Participants either enrolled in a structured PA programme (n\u0026thinsp;=\u0026thinsp;78) or received treatment as usual (TAU; n\u0026thinsp;=\u0026thinsp;78), with groups matched on key demographic and clinical variables. Outcomes included body composition, physical fitness, mental well-being (WEMWBS), health-related quality of life (WHOQOL-BREF), and direct healthcare costs derived from psychiatric hospitalisations and psychotropic medication use.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOver the 15-month follow-up, participation in the PA programme was associated with greater improvements in cardiorespiratory fitness, body composition\u0026mdash;including reductions in visceral adiposity\u0026mdash;and psychological well-being compared with TAU (p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Participants in the PA group also exhibited higher gains in quality of life and more favourable behavioural profiles. In parallel, lower observed direct healthcare expenditures were recorded in the PA group, primarily reflecting reduced psychiatric hospitalisation and medication costs, although cost analyses were exploratory in nature.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn a real-world community setting, sustained engagement in structured physical activity was associated with clinically meaningful improvements in physical and psychological outcomes among individuals with SMD, alongside lower healthcare utilisation over time. These findings support the potential role of structured PA as a scalable component of recovery-oriented mental health services, while highlighting the need for controlled trials to confirm causality and formally evaluate cost-effectiveness.\u003c/p\u003e","manuscriptTitle":"Longitudinal impact of physical activity on visceral adiposity, recovery, and costs in severe mental disorders: a 15-month quasi-experimental study in a community setting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 11:27:11","doi":"10.21203/rs.3.rs-8531325/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-14T14:50:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-04T03:03:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T11:15:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-02T11:30:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237991500231982320818615989220514828375","date":"2026-02-11T03:35:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"252537526035148006703738110394786169266","date":"2026-02-10T00:51:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3316033066499808891363113748645140998","date":"2026-02-08T20:20:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-08T20:14:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-03T10:55:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-07T13:00:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Social Psychiatry and Psychiatric Epidemiology","date":"2026-01-06T12:03:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7b6b46cb-3214-4521-b925-3a67deb08eee","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-29T21:53:11+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 11:27:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8531325","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8531325","identity":"rs-8531325","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}