Abstract
Modern healthcare systems prioritize diagnostic technologies such as blood tests, imaging, and genetic screening, while systematically neglecting the fundamental human capacity for movement. This paradox is especially striking given that movement is the primary evolutionary function of the human body and a powerful predictor and determinant of health outcomes across the lifespan. Growing evidence suggests that limitations in movement capacity initiate a cascade of physiological deterioration that manifests as frailty, cognitive impairment, and premature mortality. Yet despite its centrality to healthy human function and lifespan, movement remains peripheral in clinical practice, often evaluated informally or only after a significant decline has occurred. Here, we argue for a movement-centered healthcare infrastructure that places mobility assessment and intervention at the core of clinical decision-making. We examine the scientific rationale, economic consequences, and broad societal benefits of prioritizing locomotion alongside traditional diagnostics. Ultimately, we propose that movement analysis should be elevated to the level of routine, sophisticated practice—on par with today’s laboratory diagnostics—restructuring healthcare around the proactive enhancement and lifelong preservation of human mobility.
1 Introduction: the paradox of sedentary medicine
In stillness, the body forgets its purpose; in movement, it remembers its power.
Contemporary healthcare operates within a profound structural contradiction. While our diagnostic capabilities have expanded dramatically—enabling detection of subtle biochemical shifts, high-resolution anatomical changes, and single-nucleotide genomic variations—we systematically overlook assessment of the most foundational human function: movement (1, 2). This is not merely a clinical blind spot but a conceptual failure to recognize that health expresses itself not only in molecules and images, but in coordinated, adaptive action. The irony is stark: we can sequence entire genomes within hours, yet lack standardized methods to evaluate the complex, integrated behavior those genes ultimately support. Movement is not peripheral to human physiology—it is its primary evolutionary purpose and a central determinant of health across the lifespan (3, 4). Yet it remains marginal in both diagnostic protocols and care pathways.
The human body evolved over millions of years under relentless selective pressure specifically for locomotion. Every physiological system—from cardiovascular networks delivering oxygen to working muscles, to neurological pathways coordinating complex motor patterns—has been shaped by the imperative to move efficiently across varied terrain (5–8). Yet our medical infrastructure treats movement as peripheral, relegating it to rehabilitation services accessed only after pathology manifests and decline begins (9, 10). In privileging molecular and anatomical insights over functional assessment, we have built clinical systems around a core misunderstanding: that human beings are biochemical systems to be corrected rather than moving organisms to be sustained. Healthcare without movement assessment is as incomplete as cardiology without electrocardiograms.
Our argument applies most directly to non-communicable diseases constituting over 70% of global mortality—cardiovascular disease, metabolic syndrome, neurodegenerative conditions, and cancers of affluence (11). Yet implications extend further. Even in acute contexts—infectious disease, surgical recovery, trauma—baseline movement capacity directly shapes outcomes (12, 13). The cancer patient’s chemotherapy tolerance, the elderly patient’s pneumonia survival, the trauma victim’s rehabilitation trajectory: each is mediated by functional reserve built over a lifetime of movement (14, 15). We do not propose that movement replace antibiotics or chemotherapy, but that it occupy the central organizing role in a healthcare infrastructure currently built around reactive, disease-specific intervention.
2 The biological primacy of movement
Six million years of running. Sixty years of sitting. The body has not forgotten for which it was made.
Human evolution occurred exclusively in environments demanding extensive daily movement for survival, shaping every aspect of our biological architecture over millions of years. Our ancestors engaged in complex locomotor behaviors for 6–8 hours daily—walking, running, climbing, carrying, and manipulating objects across terrain that would challenge modern athletes (16–19). This evolutionary heritage established an obligatory relationship between physical activity and health. The human genome itself represents a blueprint optimized for movement, with thousands of genes dedicated to supporting locomotor function (20–22)—genes that remain active, awaiting the mechanical signals that walking and running once reliably provided.
Evolutionary mismatch provides a powerful framework for understanding why modern sedentary lifestyles generate widespread health consequences across populations. When organisms encounter environments dramatically different from those that shaped their evolution, dysfunction results as biological systems fail to operate within their evolved parameters (5–8). Sedentary lifestyles represent perhaps the most significant mismatch in human experience, violating the basic assumptions upon which our physiology operates. This mismatch operates at every level of biological organization, from cellular metabolism to organ system function. The result is a disproportion that puzzles intuition: how can the mere absence of movement—the most passive state imaginable—produce such aggressive pathology?
2.1 Mechanotransduction: the cellular requirement for mechanical input
The answer partly lies in mechanobiology, a field revealing how cells depend on mechanical stimulation to maintain normal function. Cells do not passively await chemical signals; they actively sense and respond to physical forces through mechanotransduction (23, 24). Mechanosensitive proteins—including integrins at cell-matrix junctions, Piezo ion channels in cell membranes, and YAP/TAZ transcriptional regulators shuttling between cytoplasm and nucleus—convert physical deformation into biochemical signals governing gene expression, metabolic activity, and cell fate (25, 26). This is not peripheral regulation; it is fundamental to cellular function.
When mechanical stimulation ceases, mechanotransduction pathways fall silent, and the cellular processes they regulate begin to degrade (3, 27). Mitochondrial biogenesis slows (28, 29). Inflammatory signaling shifts toward chronic activation (30, 31). Muscle protein synthesis decreases while proteolytic pathways accelerate (32, 33). Bone-forming osteoblasts reduce activity while bone-resorbing osteoclasts continue unabated (34, 35). These are not gradual accommodations but pathological cascades initiated by loss of signals cells have evolved to expect. The emerging field of mechanomedicine positions mechanical forces as key modulators of health and disease, with therapeutic implications spanning oncology, cardiovascular medicine, and neurodegeneration (36–38). At the molecular level, the body does not merely benefit from movement—it requires it.
2.2 Myokines: muscle as an endocrine organ
The discovery that skeletal muscle functions as an endocrine organ explains why movement exerts such broad systemic effects (39, 40). When muscles contract, they release myokines—a family now including hundreds of signaling proteins, peptides, and metabolites—that travel through the bloodstream to communicate with brain, liver, adipose tissue, pancreas, bone, and immune system (41). This muscle–organ crosstalk provides a molecular explanation for otherwise inexplicable phenomena: how contracting leg muscles simultaneously reduce depression, improve insulin sensitivity, modulate immune function, and suppress tumor growth.
Muscle is far more than mechanical tissue for generating force; it is a master regulatory organ whose secretome orchestrates systemic physiology. Interleukin-6, released during contraction, enhances glucose uptake, stimulates fat oxidation, and exerts anti-inflammatory effects distinct from pro-inflammatory IL-6 produced in chronic disease (42, 43). Brain-derived neurotrophic factor promotes neuroplasticity and neurogenesis (44, 45). Irisin induces browning of white adipose tissue, increasing energy expenditure (46, 47). Myostatin, whose expression decreases with exercise, normally inhibits muscle growth—its suppression permits hypertrophy and metabolic improvement (48, 49). These signals create a molecular language through which muscle contraction communicates the body’s activity state to every organ.
Inactivity silences this network. When muscles do not contract, myokine secretion diminishes, and distant organs are deprived of signals they evolved to expect (50, 51). The sedentary body is not merely under-exercised but under-signaled, its organs operating without the regulatory input that coordinates their function. This reframes physical inactivity not as a lifestyle choice with health consequences but as a form of endocrine deficiency affecting every organ system (3).
2.3 Systemic integration: why movement affects everything
Movement functions as a master regulator of human physiology because mechanotransduction and myokine signaling operate across every major biological system simultaneously. At the metabolic level, regular physical activity governs glucose homeostasis, lipid oxidation, insulin sensitivity, and mitochondrial biogenesis through pathways requiring continual activation (52, 53). The cardiovascular system depends on consistent mechanical loading for cardiac output, vascular elasticity, and endothelial health (54). The brain requires movement-induced increases in cerebral perfusion, BDNF secretion, and neurogenesis to maintain cognitive function and emotional regulation (55, 56). The musculoskeletal system remodels continuously in response to mechanical loading as described by Frost's mechanostat (34). The immune system calibrates its inflammatory tone based on signals from contracting muscle (57).
Because these systems are deeply interconnected, movement deficiency does not stay local—it spreads across physiology. Muscular weakness propagates into metabolic dysregulation; cardiovascular strain compounds neurological vulnerability; immune dysregulation accelerates tissue degeneration. The failures cascade (58). Cardiorespiratory fitness shows dose-response relationships with protection against multiple cancer types, cognitive decline, and all-cause mortality—effects remaining significant even after adjustment for adiposity and traditional risk factors (59–61). Movement is not a lifestyle choice modulating health at the margins. It is a biological requirement, and the body enforces this requirement whether we acknowledge it or not.
3 Movement decline as the primary aging pathway
Aging begins not when cells divide slowly, but when steps grow short.
The aging process may be initiated not by molecular wear or isolated organ dysfunction, but by an early, often subtle, decline in movement capacity. This movement-centered model reframes senescence not as disease-specific pathology but as a systemic trajectory of functional loss unfolding predictably across physiological systems (62–64). From this perspective, aging is not inevitable multiorgan degeneration but the consequence of progressive disruption in mobility—a function central to our evolutionary design. This reconceptualization challenges the current compartmentalized approach to aging, positioning movement not as a late-stage casualty but as its earliest driver and clearest signal—and therefore the primary target for intervention.
The clinical syndrome of frailty—characterized by slowness, weakness, low physical activity, and exhaustion—exemplifies this movement-centric decline. Rather than emerging abruptly, frailty evolves through a self-reinforcing cycle triggered by any event that reduces physical activity: injury, illness, pain, or gradual deconditioning. This reduction initiates sarcopenia, the rapid loss of muscle mass and strength, which can begin within days of inactivity and accelerates with ongoing disuse (65–68). As capacity declines, individuals reduce activity further, compounding weakness and diminishing resilience across cardiovascular, metabolic, and neurological systems. What appears clinically as sudden frailty is the endpoint of years of subclinical deterioration.
This cascade is increasingly recognized as disuse syndrome—a systemic physiological deterioration directly attributable to insufficient mechanical loading (69–71). Disuse precipitates cardiovascular deconditioning, reducing maximal oxygen uptake and cardiac output by up to 25% within weeks (72, 73). Simultaneously, muscle atrophy proceeds at 0.5%–1% per day under immobilization (33). Bone loss accelerates by an order of magnitude compared to normal aging trajectories (74, 75). The metabolic consequences are equally pronounced, with impaired glucose tolerance and lipid metabolism emerging as regulatory mechanisms degrade with inactivity.
The speed and breadth of these changes highlight the fragility of human physiological equilibrium and the central role of movement in preserving it. Bed rest studies in healthy young adults show significant physiological deterioration within days. Cardiovascular fitness, muscle mass, bone density, and insulin sensitivity all decline rapidly, often requiring extended rehabilitation to recover (76). Notably, these losses occur much faster than gains achievable through exercise, revealing a biological asymmetry that favors decline over recovery (77, 78). The asymmetry is stark: three days of bed rest can undo three weeks of training. The imbalance only worsens with age.
Movement-based metrics have emerged as exceptionally sensitive and integrative indicators of overall health status and long-term longevity. Gait speed, often called the “sixth vital sign,” shows strong and consistent correlations with survival rates, hospitalization risk, functional independence, and quality of life—often outperforming conventional clinical diagnostics (79–81). A 0.1 m/s decrement in walking speed is associated with a 12% increase in mortality risk (81). Similarly, grip strength—a low-cost, rapid test of muscular function—predicts mortality as accurately as, or better than, conventional cardiovascular markers such as blood pressure (85–87). The exceptional prognostic value of these simple measures suggests something profound: a six-minute walk test may reveal what an MRI cannot—whether the body’s systems are working together or falling apart.
4 The diagnostic gap: movement assessment in healthcare
We measure the chemistry of blood with precision, yet ignore the poetry of motion that sustains life.
Modern healthcare operates within a diagnostic paradigm shaped by reductionist assumptions—fragmenting the human body into discrete systems, organs, and biomarkers while routinely neglecting integrated function (88). Standard evaluations include extensive blood chemistry panels quantifying lipids, glucose, inflammatory cytokines, hormones, and vitamins with molecular precision. Imaging modalities—radiography, CT, MRI, ultrasound—offer high-resolution anatomical insights, while genetic sequencing reveals disease predispositions and guides pharmacogenomic interventions. Functional diagnostics such as electrocardiography, cardiac stress testing, and pulmonary function assessments complete a technologically sophisticated diagnostic arsenal capable of detecting subtle early deviations from physiological norms across multiple systems.
Yet within this diagnostic infrastructure, a critical omission persists: systematic evaluation of movement is absent from routine medical care across nearly all clinical domains (89). Sophisticated tools for analyzing movement—motion capture, force platforms, wearable sensors—exist in biomechanics laboratories and elite sports facilities but remain siloed from primary care and general medicine. This disconnect is especially paradoxical given that movement metrics can rival or surpass conventional biomarkers in predicting morbidity, mortality, and functional independence, while requiring no invasive procedures, expensive reagents, or ionizing radiation (79–87). The healthcare system can detect microvariations in enzyme levels but fails to assess gait, posture, or physical adaptability—functions at the heart of human health. The oversight runs deeper than workflow or equipment; it reflects what medicine implicitly believes bodies are for.
This diagnostic blind spot is rooted in foundational healthcare delivery structures that prioritize disease identification and pharmaceutical intervention over prevention and functional optimization. Medical curricula dedicate disproportionate attention to pathophysiology and pharmacology, offering little formal education in movement science, exercise physiology, or functional assessment. A systematic review from 2002 found that only 13% of U.S. medical schools included physical activity curricula, with most programs offering fewer than four hours of instruction across the entire medical education (90). More recently, a 2022 consensus statement from sports medicine physicians outlined comprehensive curricular recommendations—including exercise prescription, motivational interviewing, and community resource navigation—yet implementation remains inconsistent (91). Clinicians graduate with robust training in disease mechanisms but limited capacity to evaluate or prescribe movement-based interventions. This epistemic gap fosters a healthcare culture in which movement is addressed reactively—after injury or illness, not proactively as a central health determinant. The net effect is a workforce prepared to prescribe a panoply of drugs but untrained in leveraging one of the most powerful therapeutic tools available: movement itself.
Movement assessment is not entirely absent from healthcare. The International Classification of Functioning, Disability, and Health (ICF), endorsed by all 191 WHO Member States in 2001, provides conceptual architecture for understanding functioning through a biopsychosocial lens (92). World Physiotherapy adopted the ICF framework in 2003, and rehabilitation medicine has incorporated functional assessment into specialty practice. Yet these frameworks remain confined to post-hoc settings, accessed only after disease or injury has manifested. They have not been integrated into primary care as a routine evaluation. A 2023 survey of athletic trainers found that 51.9% had never learned about the ICF framework, with low implementation across all assessment categories (93). A 2024 study concluded that ICF education alone does not translate into clinical implementation without specific practical training (94). The ICF offers architecture; what we lack is construction.
When movement is assessed clinically, it is typically reduced to imprecise proxies such as self-reported activity or isolated functional tests administered only in specialized settings (95–97). In contrast to precision in other health domains, movement is crudely measured, if at all. Meanwhile, advanced methods—three-dimensional kinematics, kinetic force analyses, surface electromyography—remain underutilized in clinical practice despite their availability and technical maturity (98–100). Validated wearable devices offer additional promise by enabling continuous, real-world movement monitoring (101, 102), yet they too are rarely integrated into routine clinical workflows. These technologies could revolutionize health assessment, transforming how we detect risk, monitor recovery, and tailor interventions. That such technologies exist yet remain largely excluded from medical decision-making constitutes a striking missed opportunity. Clinicians assess lipid panels to two decimal places while remaining unable to describe how their patients walk (103–105).
This diagnostic vacuum is no longer a technological necessity—it is an infrastructural choice. The past decade has witnessed a revolution in wearable sensor technology, transforming devices once limited to step counts and heart rate into clinical-grade instruments capable of capturing subtle movement dysfunction signatures. The Mobilise-D consortium has validated 24 digital mobility outcomes across six clinical cohorts spanning Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture recovery, heart failure, and healthy aging—demonstrating that real-world gait speed, stride variability, and walking bout characteristics can be measured with accuracy approaching laboratory gold standards (106, 107). Consumer-grade devices now achieve sufficient precision for meaningful clinical applications, with systematic reviews confirming acceptable validity for gait parameters in both controlled and free-living conditions (108). Technology has solved the measurement problem. What remains is the will to use it.
5 Economic and social dimensions of movement suppression
The architecture of our cities shapes the biology of our bodies, one sedentary choice at a time.
The suppression of movement in modern society goes beyond individual choices or clinical neglect. It is a systemic condition, deeply embedded in the design of our cities, the structure of our economies, the rhythms of our work, and the values of our culture. It reflects a multilayered ecosystem of constraints producing what researchers term “obesogenic” or “pathogenic” environments: social and physical contexts that actively promote sedentary behavior, physiological dysfunction, and widespread disease (109–112). Technologies intended to enhance human well-being have paradoxically constructed ecosystems that erode the behaviors most essential to health.
Urban design provides one of the manifestations of this paradox. Over the past century, planning decisions have privileged motorized transportation at the expense of human-powered mobility, producing sprawling suburbs and car-dependent cities that render walking and cycling impractical, unsafe, or socially marginalized (113, 114). The built environment becomes a silent architect of chronic disease. In such contexts, movement becomes an optional, time-consuming activity segregated into narrowly defined “exercise sessions” (115–117)—a pattern that violates the integrated functional movement for which our physiology evolved. When environments are built to restrict movement, even the most motivated individuals struggle to sustain health-supporting behaviors.
Economic structures reinforce these constraints through sweeping shifts in occupational patterns. The transition from labor-intensive manufacturing and agriculture to knowledge- and service-based economies has transformed most workplaces into sedentary spaces where prolonged sitting is the norm and physical activity is both unnecessary and logistically difficult (118–120). For many adults, the workplace is where most waking hours are spent, and those hours are increasingly defined by inactivity—often in ergonomically suboptimal environments designed for productivity rather than physiological well-being (121, 122). The modern economy systematically violates human evolutionary imperatives in exchange for productivity, generating health problems that the same system must then pay to treat.
The economic consequences of movement suppression are staggering. The WHO’s 2022 Global Status Report on Physical Activity estimated that physical inactivity will cost global healthcare systems $300 billion by 2030 if current prevalence remains unchanged (124), with 74% of new diabetes cases and 76% of new ischemic heart disease cases attributable to insufficient activity occurring in low- and middle-income countries—yet 63% of direct healthcare costs will be borne by high-income nations (123). Yet direct medical costs represent only a fraction of the broader economic burden. Indirect costs—lost productivity, absenteeism, presenteeism, disability, and premature mortality—exert even greater strain, siphoning human potential and reducing collective well-being at scale (125). The burden falls disproportionately on economically and socially marginalized populations, exacerbating existing inequities in health, income, and opportunity. Movement suppression functions as both a public health crisis and a structural determinant of inequality.
Cultural norms and social expectations compound these structural challenges by reinforcing the desirability of convenience, efficiency, and technological substitution for physical effort. Sedentary behaviors are valorized as signals of productivity or prestige, while physical exertion is often stigmatized as burdensome, inefficient, or unnecessary (126–128). The medicalization of aging-related mobility decline frequently results in premature activity restriction over proactive interventions to maintain or restore function, thereby hastening physical deterioration through well-intentioned but misguided caution (129–131). Meanwhile, the pervasive influence of digital entertainment and algorithmically optimized platforms has created unprecedented competition for attention, making the delayed benefits of physical activity pale in comparison to instant gratification offered by screens. The result is a culture that systematically devalues movement while promoting the behaviors most predictive of chronic disease and functional decline across the lifespan (132–134).
Movement suppression is not simply a medical oversight—it is a systemic pathology embedded in the scaffolding of modern life, and addressing it will require coordinated reform across infrastructure, economics, and culture.
6 Evidence base for movement-centered interventions
In the laboratory of human experience, movement is both the hypothesis and the proof.
The scientific foundation for such reform has grown across virtually every domain of medicine, demonstrating not only wide-ranging clinical efficacy but also the ability to address multiple physiological systems simultaneously—often with fewer risks and greater reach than conventional pharmacological interventions. Movement interventions have shown effectiveness in preventing and treating chronic diseases, improving mental health and cognitive function, reducing cancer risk, enhancing musculoskeletal integrity, and optimizing sleep—all while incurring minimal side effects. Unlike most medical therapies, which act on narrow physiological targets, physical activity exerts global regulatory effects on human biology, reflecting its evolutionary centrality. Despite the consistency and breadth of the evidence, movement remains underutilized in clinical settings—revealing a gap not in knowledge but in implementation. Bridging this divide is among the most urgent challenges facing modern healthcare systems.
Cardiovascular disease prevention is perhaps the clearest domain where movement interventions rival or exceed pharmacologic strategies. Regular physical activity reduces cardiovascular risk by 30%–50% across populations, with benefits evident even at modest activity levels and increasing with greater intensity and duration in a clear dose-response pattern (135–138). These effects operate through multiple pathways—lipid metabolism, blood pressure regulation, endothelial function, insulin sensitivity, and inflammatory modulation. Physical inactivity is now recognized as a modifiable risk factor on par with smoking, hypertension, and dyslipidemia (139, 140). The consistent efficacy of movement across age, sex, and comorbidity profiles underscores its suitability as a first-line cardiovascular intervention. The prescription pad has room for one more line.
The case for movement in diabetes prevention and management is similarly compelling. The Diabetes Prevention Program demonstrated that lifestyle interventions emphasizing physical activity reduced diabetes incidence by 58%, outperforming metformin, which yielded only a 31% reduction (141). Beyond glucose regulation, exercise improves cardiovascular health, quality of life, and physical capacity, while enabling reductions in medication use and their associated costs and side effects (142, 143). These results have elevated structured physical activity to a core component of professional guidelines for type 2 diabetes. The breadth of additional benefits and absence of adverse effects make movement a uniquely potent and underutilized factor in metabolic disease management.
Mental health is another domain where movement interventions are redefining therapeutic norms. Exercise shows antidepressant and anxiolytic effects on par with—or in some cases superior to—pharmacological treatments, especially when adherence and side effect profiles are considered (144). Meta-analyses consistently report reductions in symptoms of depression and anxiety across demographic groups and clinical contexts (145–147). Mechanistically, movement enhances neuroplasticity, modulates neurotransmitter systems, and fosters social connection and stress resilience—all critical for sustained psychological health. Given the limitations and escalating use of psychiatric medications, movement-based approaches offer something increasingly rare: a low-cost, high-access intervention that addresses root causes rather than masking symptoms.
Physical activity shapes cognitive function and brain health across the lifespan. Exercise enhances executive function, memory, and processing speed, with effect sizes comparable to cognitive training interventions (148, 149). Underlying mechanisms include increased brain-derived neurotrophic factor, enhanced cerebral blood flow, reduced neuroinflammation, and stimulation of hippocampal neurogenesis (150, 151). These effects position physical activity as the most promising non-pharmacological strategy for preventing or delaying cognitive decline and dementia. This is especially urgent given the global rise in age-related neurodegenerative diseases and the limited efficacy of current pharmaceutical treatments.
The evidence base for cancer prevention and survivorship has been substantially strengthened by recent meta-analytic work. Regular physical activity reduces the risk of several major cancers, including breast, colorectal, lung, and prostate, with relative risk reductions of 10%–25% depending on type and dose (152–154). A 2025 systematic review in the British Journal of Sports Medicine analyzing 42 studies with over 46,000 cancer patients demonstrated that high muscle strength and cardiorespiratory fitness were associated with 31%–46% reduced risk of all-cause mortality across cancer types—including in patients with advanced disease stages (155). Critically, each one-MET increment in cardiorespiratory fitness was associated with an 18% reduction in cancer-specific mortality. These magnitudes rival or exceed those achieved by many oncological therapies, yet movement interventions remain peripheral in cancer care pathways. For individuals undergoing treatment, movement improves chemotherapy tolerance, mitigates fatigue, and enhances physical and emotional quality of life (156, 157). Post-treatment, it may also improve survival outcomes through mechanisms such as immune modulation, reduced systemic inflammation, hormonal regulation, and enhanced physical resilience. These benefits make the case plainly: in oncology, movement is not supportive care. It is care.
Musculoskeletal health offers perhaps the clearest illustration of movement’s preventive and restorative power. Resistance training and weight-bearing exercises increase bone density, muscle mass, and neuromuscular coordination even in very elderly populations (158–160). These adaptations reduce fracture risk and enhance mobility, independence, and quality of life. Falls prevention programs based on strength and balance training consistently reduce fall incidence by 20%–30% in high-risk populations (161–163). As pharmacologic approaches to sarcopenia and osteoporosis remain limited and often poorly tolerated, movement remains the most accessible and effective strategy for preserving structural resilience and preventing disability in aging populations.
Sleep, often underappreciated as a clinical endpoint, improves with regular movement. Physical activity reduces sleep onset latency, improves sleep efficiency, and enhances sleep quality while reducing dependence on sedatives and other sleep aids that carry side effects and addiction risks (164–166). Improved sleep, in turn, amplifies daytime energy, cognitive function, immune regulation, and emotional well-being (167–169). Better nights beget better days; the cycle is virtuous.
The COVID-19 pandemic provided a striking real-world demonstration of movement’s protective role beyond chronic disease. Systematic reviews demonstrated that physical inactivity was strongly associated with worse COVID-19 outcomes—hospitalization, ICU admission, and death (2). More strikingly, Long COVID—the post-acute syndrome affecting millions worldwide—manifests primarily as exercise intolerance, fatigue, and functional limitation. A 2024 meta-analysis found that exercise-based rehabilitation improved symptom severity, physical fitness, and quality of life in patients with Long COVID (170). The syndrome reveals what evolutionary biology predicts: an infectious insult becomes a chronic disability precisely when movement capacity is compromised, and recovery proceeds through the restoration of functional movement.
A necessary caveat accompanies this evidence. Like any intervention, movement carries risks that must be managed through individualized assessment, prescription, and monitoring. A 2024 review on exercise intensity prescription in cardiac rehabilitation emphasized that optimizing intensity is crucial to maximize clinical benefits while minimizing complications—too little yields subtherapeutic effects, while too much may precipitate adverse events in vulnerable populations (171). An umbrella review examining exercise prescription variables in musculoskeletal pain identified significant evidence gaps regarding optimal dosing parameters, underscoring that movement interventions require the same methodological rigor as pharmacotherapy (172). This is precisely our argument: not that movement is a panacea without risk, but that its professionalization within healthcare would ensure the same systematic attention to dosing, contraindications, and monitoring currently afforded to pharmaceutical agents. The risks of movement are real but bounded; the risks of inactivity are systemic and cumulative.
These domains highlight the unmatched therapeutic versatility of movement across the continuum of health and disease. Few, if any, clinical interventions offer such widespread, evidence-based benefit with such minimal risk. The evidence is settled. What remains is recognition, funding, prescription, and the clinical seriousness we already extend to pharmaceuticals.
7 Toward movement-centered healthcare infrastructure
The future of medicine lies not in treating disease, but in cultivating the movement that prevents it.
Reorienting healthcare around this evidence demands fundamental rethinking of clinical practice, professional training, health financing, and care delivery models. This transformation extends beyond technical development of movement diagnostics—it necessitates systemic changes that address the structural, cultural, and institutional barriers that have long marginalized movement science within mainstream healthcare. The scope of this shift is not incremental but paradigmatic, requiring coordinated action across multiple levels of the healthcare ecosystem—from individual provider encounters to institutional workflows and national policy frameworks (173–175). Overcoming decades of professional silos and institutional inertia is essential—but so is something simpler: learning to see movement as central to medicine rather than incidental to it.
At the core of this infrastructure is developing standardized, clinically valid movement assessment protocols that achieve the reliability and diagnostic power of contemporary laboratory tests (176–178). These protocols must capture multidimensional aspects of movement—quality, efficiency, capacity—through validated instruments that yield interpretable and actionable clinical data. Emerging wearable sensors, smartphone-based monitoring, and AI-driven analytics now offer unprecedented opportunities to extend precision assessment capabilities from biomechanics laboratories into routine clinical settings (101, 102).
A comprehensive movement assessment should encompass multiple domains of locomotor function. Basic measures such as gait speed, balance, and coordination offer prognostic insights across populations and conditions (79, 81–84). Muscle strength and power assessments provide critical data on functional reserve and injury risk, while cardiorespiratory fitness remains one of the most direct and integrative evaluations of physiological health under stress (179, 180). Flexibility and joint range of motion assessments identify biomechanical constraints, asymmetries, and neuromuscular inefficiencies—often before pain or disability emerges (181, 182). Together, these components form the foundation of a comprehensive functional profile that rivals conventional diagnostic paradigms in breadth and clinical utility.
Educational transformation is equally essential. Medical education at all levels must be restructured to position movement science and functional assessment as core competencies rather than elective topics (183, 184). This shift requires redefining what it means to be a competent healthcare provider in the 21st century: not only a diagnostician of disease but a steward of function.
Financial infrastructure must also evolve to support movement-based care. Current reimbursement models overwhelmingly favor acute treatment and procedural interventions while disincentivizing preventive, behaviorally rooted strategies (185, 186). Value-based payment models should reward providers for preserving function, preventing decline, and improving quality of life—not just for managing disease after it has compromised health. Reform at the institutional, state, and federal levels is necessary to align economic incentives with the biological realities of human health.
Service delivery models should reflect this emphasis on movement by embedding movement professionals—physical therapists, exercise physiologists, kinesiologists—within interdisciplinary care teams (187–189). Movement expertise should be a frontline resource embedded in preventive care, not a specialty accessed only after decline. This integration will require new professional roles, collaborative scopes of practice, and shared decision-making frameworks that break down longstanding disciplinary boundaries while preserving accountability (190, 191).
Finally, digital infrastructure must treat movement data as first-class clinical information. Electronic health records should capture, analyze, and visualize movement metrics with the same granularity currently afforded to laboratory values and imaging reports (192–194). Clinical decision support, telehealth-based movement coaching, and population-level functional surveillance all depend on this foundation (195–197). The key design principle is interoperability; movement data must be seamlessly embedded in clinical workflows—as foundational infrastructure, not afterthoughts grafted onto existing systems.
8 Implementation strategies and future directions
The science of movement is still writing its first chapter—but already it rewrites the story of medicine.
Implementing movement-centered healthcare is a multidimensional challenge demanding coordination across all layers of the healthcare system. From the micro-level of patient–clinician encounters to the macro-level of national policy reform, this transformation requires aligning technical, educational, economic, and cultural systems in service of a radically different paradigm of care (198–200). Success will depend not only on overcoming institutional inertia but also on articulating a clear value proposition—one demonstrating measurable improvements in health outcomes, provider effectiveness, and system-level cost savings. Early implementation efforts must be strategic, targeted, and sequenced to generate momentum through achievable wins while laying groundwork for broader systemic change. Without such deliberate efforts, healthcare will remain locked in a reactive model that treats the consequences of movement loss rather than preventing its onset.
A pragmatic starting point is developing and deploying pilot programs within health systems that have the infrastructure and leadership readiness to serve as demonstration sites. These pilots should focus on integrating standardized, high-quality movement assessment protocols—efficient, scalable, and comparable in reliability to existing clinical diagnostics (201–205). Protocols should be designed for use by a range of healthcare professionals, require minimal equipment, and be sensitive enough to detect early signs of functional decline. Ideal pilot settings include institutions with interdisciplinary teams, digital health infrastructure, and a culture open to innovation. Evidence generated from these pilots will be instrumental in validating clinical utility and economic feasibility, providing the proof points needed for expansion to more complex or resource-constrained environments.
Early-stage implementation should also prioritize populations where movement interventions deliver the most pronounced impact. Older adults, who face high risks of hospitalization, institutionalization, and functional decline, constitute an ideal focus given substantial evidence supporting movement interventions to improve independence and quality of life (206, 207). Similarly, individuals with chronic conditions—type 2 diabetes, cardiovascular disease, depression—often experience outcomes from movement-based interventions that rival or exceed those of pharmacologic treatment (208, 209). These high-need populations offer both compelling clinical returns and strong economic justification, especially in value-based care models (210, 211). Demonstrating success in these groups strengthens the case for policy support, payer investment, and broader population-level implementation.
Provider education is a critical enabler of long-term sustainability. Current professional training remains heavily skewed toward disease recognition and pharmacologic management, with minimal emphasis on functional assessment or physical activity counseling (212, 213). Medical, nursing, and allied health curricula must be restructured to integrate movement science not as an elective but as a core competency. This includes practical instruction in gait assessment, strength testing, and exercise prescription, supported by evidence-based frameworks and rigorous competency evaluation (214, 215). Continuing education must also address the substantial knowledge gap among practicing clinicians never trained in movement-focused approaches. Interprofessional training environments that bring together physicians, nurses, therapists, and exercise professionals are particularly valuable for fostering collaboration and dismantling the professional silos that impede integrated care (216, 217).
Technology development constitutes a particularly transformative priority. The same devices that enabled our sedentary confinement now offer instruments of liberation. Wearable sensors and mobile health platforms have matured from consumer novelties to clinical-grade technologies capable of gathering continuous, real-time movement data outside laboratory settings, enabling early detection of decline and ongoing monitoring of intervention effectiveness (101, 102). As the Mobilise-D consortium’s validation across diverse clinical populations confirms, the technical infrastructure for movement-centered healthcare already exists (106). What remains is the will to deploy it.
More striking is the emerging convergence of biophysical and biochemical monitoring within single wearable platforms. Next-generation devices now enable continuous, minimally invasive analysis of sweat, interstitial fluid, breath, tears, and saliva—capturing inflammatory markers, metabolic substrates, pharmacokinetic profiles, and pathogen signatures alongside movement metrics (218). This convergence mirrors the body’s own systemic coherence: not separate streams of motion and molecular data, but a unified portrait of human function in real time. The diabetic patient’s gait variability can be correlated with continuous glucose fluctuations; the cancer survivor’s fatigue mapped against rhythms of inflammatory cytokines; the aging adult’s fall risk contextualized by hydration status and medication absorption. The devices themselves increasingly embody the holistic vision this manuscript advocates.
Artificial intelligence can process these high-volume, high-dimensional data streams to identify risk trajectories, predict outcomes, and optimize individualized prescriptions with sophistication no human clinician could achieve unaided (219–221). Digital biomarkers derived from passive smartphone and wearable data have demonstrated capacity to predict cognitive decline, detect early depression, and stratify cardiovascular risk—often with sensitivity exceeding traditional clinical assessments (222, 223). These technologies should be positioned not as replacements for human care but as decision support systems extending expert-level functional assessment into primary care and community health settings—democratizing access to sophisticated movement evaluation currently confined to research laboratories and elite rehabilitation facilities (224–226).
Parallel to technical innovation, policy research must address systemic constraints that currently marginalize movement in clinical care. Most healthcare financing models fail to reimburse evidence-based movement interventions, creating powerful disincentives to adopt them—even when they outperform pharmacological or surgical alternatives. Research should explore how revised reimbursement frameworks, value-based care models, and bundled payments could support a shift toward prevention and function-centered care. Movement assessment, exercise counseling, and physical activity prescription must be recognized and reimbursed as core clinical services rather than optional wellness add-ons.
The role of the built environment—sidewalks, parks, public transit access—in shaping population movement patterns must be rigorously studied. Behavior does not occur in a vacuum; movement is enabled or constrained by social and physical environments, and policies must reflect that reality. Governance frameworks for technology-induced sedentary behavior—including the respective roles of healthcare systems, employers, and individuals in promoting movement—represent another priority as evidence regarding screen time, remote work, and algorithmic engagement accumulates. Regulatory frameworks will be essential in defining credentials, scope, and accountability of movement professionals as they integrate into clinical teams. Addressing movement inequality—the unequal distribution of opportunities, access, and support for physical activity—should be treated as a priority on par with other public health disparities.
Personalization of movement prescriptions represents a critical frontier. Future research should investigate how individual factors—genomics, baseline motor patterns, comorbidities—can tailor exercise interventions with the precision seen in pharmacology or oncology. Experimental evaluation of integrated care models that embed movement professionals alongside traditional providers is urgently needed to determine how interdisciplinary teams can maximize functional outcomes. Cost-effectiveness studies should accompany these efforts to generate the economic evidence required for widespread adoption. Successful integration will require workflow redesign, shared communication platforms, and outcome-tracking systems that enable movement professionals and medical providers to coordinate care seamlessly. The challenge will be ensuring clinical-grade accuracy, interoperability with electronic health records, and equitable access across socio-demographic groups, languages, and levels of digital literacy.
Together, these priorities point toward a broader reimagining of healthcare itself. The evidence supports a vision in which movement is not just a therapeutic target but a vital sign, a functional biomarker, and a systems-level intervention. The human body evolved to move; its optimal function depends on movement; and when that movement is supported, health across domains—metabolic, musculoskeletal, neurological—improves at a scale rarely matched by conventional interventions. Systems that fail to assess or prescribe movement operate at odds with biological reality. Movement-centered care offers not only improved clinical outcomes but enhanced quality of life, reduced healthcare costs, and deeper alignment between medical practice and human design.
The human body is not a vessel that houses movement; it is movement crystallized in form. Every structure—bone curvature, muscle architecture, neural pathway—exists because our ancestors moved relentlessly across millions of years of evolutionary time. The genome has not changed; the mismatch is entirely of our construction. To build healthcare systems that ignore this fundamental truth is not merely misguided—it is tragic.
Yet the body remembers what the institution has forgotten. In every step, every reach, every act of rising and moving through space, the human organism expresses an evolutionary inheritance that no policy can repeal and no technology can replace. The task before us is not to invent something new but to recover something ancient—to realign our systems of care with the biological imperatives that shaped us. A healthcare system that embraces movement does not simply treat disease; it honors what the human body was built to do.
The movement imperative is, ultimately, an invitation: to build medicine worthy of the bodies it serves.
Statements
Author contributions
MM: Writing – original draft, Writing – review & editing. JF: Writing – original draft, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. We gratefully acknowledge financial support from the National Science Foundation (NSF) EPSCoR Program (Grant No. OIA-2044049) and the Nebraska Collaborative Initiative, both awarded to M.M. We also acknowledge institutional support from the Center for Research in Human Movement Variability and the Center for Cardiovascular Research in Biomechanics (CRiB) at the University of Nebraska at Omaha, which are funded by the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) under Grant Nos. P30GM159554 and P20GM152301. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NSF or the NIH/NIGMS.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
1.
LobeloFRohm YoungDSallisRGarberMDBillingerSADuperlyJ, et al. Routine assessment and promotion of physical activity in healthcare settings: a scientific statement from the American Heart Association. Circulation. (2018) 137:e495–522. 10.1161/CIR.0000000000000559
2.
SallisRYoungDRTartofSYSallisJFSallJLiQ, et al. Physical inactivity is associated with a higher risk for severe COVID-19 outcomes: a study in 48 440 adult patients. Br J Sports Med. (2021) 55:1099–105. 10.1136/bjsports-2021-104080
3.
BoothFWRobertsCKLayeMJ. Lack of exercise is a major cause of chronic diseases. Compr Physiol. (2012) 2:1143–211. 10.1002/j.2040-4603.2012.tb00425.x
4.
BrownSPMillerWCEasonJM. Exercise Physiology: Basis of Human Movement in Health and Disease. Philadelphia: Lippincott Williams & Wilkins (2006).
5.
BrambleDMLiebermanDE. Endurance running and the evolution of Homo. Nature. (2004) 432:345–52. 10.1038/nature03052
6.
CordainLEatonSBSebastianAMannNLindebergSWatkinsBA, et al. Origins and evolution of the western diet: health implications for the 21st century. Am J Clin Nutr. (2005) 81:341–54. 10.1093/ajcn.81.2.341
7.
GluckmanPDHansonMAMitchellMD. Developmental origins of health and disease: reducing the burden of chronic disease in the next generation. Genome Med. (2010) 2:14. 10.1186/gm135
8.
LiebermanDE. The Story of the Human Body: Evolution, Health, and Disease. New York: Vintage (2014).
9.
FriesJF. The compression of morbidity. Milbank Mem Fund Q Health Soc. (1983) 61:397–419. 10.2307/3349864
10.
TinettiMEWilliamsCS. The effect of falls and fall injuries on functioning in community-dwelling older persons. J Gerontol Ser A Biol Sci Med Sci. (1998) 53:M112–9. 10.1093/gerona/53A.2.M112
11.
World Health Organization. Noncommunicable diseases country profiles 2018. Geneva, Switzerland: World Health Organization (2018).
12.
MakaryMASegevDLPronovostPJSyinDBandeen-RocheKPatelP, et al. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg. (2010) 210:901–8. 10.1016/j.jamcollsurg.2010.01.028
13.
WestMALoughneyLLythgoeDBarbenCPAdamsVLBimsonWE, et al. The effect of neoadjuvant chemoradiotherapy on whole-body physical fitness and skeletal muscle mitochondrial oxidative phosphorylation in vivo in locally advanced rectal cancer patients – an observational pilot study. PLoS One. (2014) 9:e111526. 10.1371/journal.pone.0111526
14.
JonesLWCourneyaKSMackeyJRMussHBPituskinENScottJM, et al. Cardiopulmonary function and age-related decline across the breast cancer survivorship continuum. J Clin Oncol. (2012) 30:2530–7. 10.1200/JCO.2011.39.9014
15.
TanBHLBrammerKRandhawaNWelchNTParsonsSLJamesEJ, et al. Sarcopenia is associated with toxicity in patients undergoing neo-adjuvant chemotherapy for oesophago-gastric cancer. Eur J Surg Oncol. (2015) 41:333–8. 10.1016/j.ejso.2014.11.040
16.
HillKHurtadoAMWalkerRS. High adult mortality among Hiwi hunter-gatherers: implications for human evolution. J Hum Evol. (2007) 52:443–54. 10.1016/j.jhevol.2006.11.003
17.
MarloweF. The Hadza: Hunter-Gatherers of Tanzania. Berkeley: University of California Press (2010).
18.
PontzerHDurazo-ArvizuRDugasLRPlange-RhuleJBovetPForresterTE, et al. Constrained total energy expenditure and metabolic adaptation to physical activity in adult humans. Curr Biol. (2016) 26:410–7. 10.1016/j.cub.2015.12.046
19.
WoodBMHarrisJARaichlenDAPontzerHSayreKSancilioA, et al. Gendered movement ecology and landscape use in Hadza hunter-gatherers. Nat Hum Behav. (2021) 5:436–46. 10.1038/s41562-020-01002-7
20.
BouchardCSarzynskiMARiceTKKrausWEChurchTSSungYJ, et al. Genomic predictors of the maximal uptake response to standardized exercise training programs. J Appl Physiol Respir Environ Exerc Physiol. (2011) 110:1160–70. 10.1152/japplphysiol.00973.2010
21.
MacArthurDGNorthKN. Genes and human elite athletic performance. In: Pitsiladis Y, Bale J, Sharp C, Noakes T, editors. East African Running. New York, NY: Routledge (2007). p. 241–57.
22.
TimmonsJAKnudsenSRankinenTKochLGSarzynskiMJensenT, et al. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. J Appl Physiol Respir Environ Exerc Physiol. (2010) 108:1487–96. 10.1152/japplphysiol.01295.2009
23.
WangNTytellJDIngberDE. Mechanotransduction at a distance: mechanically coupling the extracellular matrix with the nucleus. Nat Rev Mol Cell Biol. (2009) 10:75–82. 10.1038/nrm2594
24.
JaaloukDELammerdingJ. Mechanotransduction gone awry. Nat Rev Mol Cell Biol. (2009) 10:63–73. 10.1038/nrm2597
25.
DupontSMorsutLAragonaMEnzoEGiulittiSCordenonsiM, et al. Role of YAP/TAZ in mechanotransduction. Nature. (2011) 474:179–83. 10.1038/nature10137
26.
CosteBMathurJSchmidtMEarleyTJRanadeSPetrusMJ, et al. Piezo1 and Piezo2 are essential components of distinct mechanically activated cation channels. Science. (2010) 330:55–60. 10.1126/science.1193270
27.
HambrechtRGielenSLinkeAFiehnEYuJWaltherC, et al. Effects of exercise training on left ventricular function and peripheral resistance in patients with chronic heart failure: a randomized trial. JAMA. (2000) 283:3095–101. 10.1001/jama.283.23.3095
28.
HoodDAUguccioniGVainshteinAD’souzaD. Mechanisms of exercise-induced mitochondrial biogenesis in skeletal muscle: implications for health and disease. Compr Physiol. (2011) 1:1119–34. 10.1002/j.2040-4603.2011.tb00370.x
29.
WrightDCHanDHGarcia-RovesPMGeigerPCJonesTEHolloszyJO. Exercise-induced mitochondrial biogenesis begins before the increase in muscle PGC-1 expression. J Biol Chem. (2007) 282:194–9. 10.1074/jbc.m606116200
30.
PetersenAMWPedersenBK. The anti-inflammatory effect of exercise. J Appl Physiol Respir Environ Exerc Physiol. (2005) 98:1154–62. 10.1152/japplphysiol.00164.2004
31.
WoodsJAWilundKRMartinSAKistlerBM. Exercise, inflammation and aging. Aging Dis. (2011) 3:130–40.
32.
GloverEIPhillipsSMOatesBRTangJETarnopolskyMASelbyA, et al. Immobilization induces anabolic resistance in human myofibrillar protein synthesis with low and high dose amino acid infusion. J Physiol. (2008) 586:6049–61. 10.1113/jphysiol.2008.160333
33.
WallBTDirksMLVan LoonLJC. Skeletal muscle atrophy during short-term disuse: implications for age-related sarcopenia. Ageing Res Rev. (2013) 12:898–906. 10.1016/j.arr.2013.07.003
34.
FrostHM. Bone’s mechanostat: a 2003 update. Anat Rec A Discov Mol Cell Evol Biol. (2003) 275:1081–101. 10.1002/ar.a.10119
35.
RubinJRubinCJacobsCR. Molecular pathways mediating mechanical signaling in bone. Gene. (2006) 367:1–16. 10.1016/j.gene.2005.10.028
36.
HumphreyJDDufresneERSchwartzMA. Mechanotransduction and extracellular matrix homeostasis. Nat Rev Mol Cell Biol. (2014) 15:802–12. 10.1038/nrm3896
37.
VogelVSheetzM. Local force and geometry sensing regulate cell functions. Nat Rev Mol Cell Biol. (2006) 7:265–75. 10.1038/nrm1890
38.
WangZWangWLuoQSongG. High matrix stiffness accelerates migration of hepatocellular carcinoma cells through the integrin 1-Plectin-F-actin axis. BMC Biol. (2025) 23:8. 10.1186/s12915-025-02113-1
39.
PedersenBKFebbraioMA. Muscles, exercise and obesity: skeletal muscle as a secretory organ. Nat Rev Endocrinol. (2012) 8:457–65. 10.1038/nrendo.2012.49
40.
SchnyderSHandschinC. Skeletal muscle as an endocrine organ: PGC-1, myokines and exercise. Bone. (2015) 80:115–25. 10.1016/j.bone.2015.02.008
41.
HoffmannCWeigertC. Skeletal muscle as an endocrine organ: the role of myokines in exercise adaptations. Cold Spring Harb Perspect Med. (2017) 7:a029793. 10.1101/cshperspect.a029793
42.
FebbraioMAPedersenBK. Contraction-induced myokine production and release: is skeletal muscle an endocrine organ?Exerc Sport Sci Rev. (2005) 33:114–9. 10.1097/00003677-200507000-00003
43.
PedersenBKFebbraioMA. Muscle as an endocrine organ: focus on muscle-derived interleukin-6. Physiol Rev. (2008) 88:1379–406. 10.1152/physrev.90100.2007
44.
CotmanCWBerchtoldNCChristieLA. Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends Neurosci. (2007) 30:464–72. 10.1016/j.tins.2007.06.011
45.
WrannCDWhiteJPSalogiannnisJLaznik-BogoslavskiDWuJMaD, et al. Exercise induces hippocampal BDNF through a PGC-1/FNDC5 pathway. Cell Metab. (2013) 18:649–59. 10.1016/j.cmet.2013.09.008
46.
BoströmPWuJJedrychowskiMPKordeAYeLLoJC, et al. A PGC1--dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature. (2012) 481:463–8. 10.1038/nature10777
47.
LeePLindermanJDSmithSBrychtaRJWangJIdelsonC, et al. Irisin and FGF21 are cold-induced endocrine activators of brown fat function in humans. Cell Metab. (2014) 19:302–9. 10.1016/j.cmet.2013.12.017
48.
LeeSJ. Regulation of muscle mass by myostatin. Annu Rev Cell Dev Biol. (2004) 20:61–86. 10.1146/annurev.cellbio.20.012103.135836
49.
SeverinsenMCKPedersenBK. Muscle–organ crosstalk: the emerging roles of myokines. Endocr Rev. (2020) 41:594–609. 10.1210/endrev/bnaa016
50.
PedersenBK. The diseasome of physical inactivity–and the role of myokines in muscle–fat cross talk. J Physiol. (2009) 587:5559–68. 10.1113/jphysiol.2009.179515
51.
SteensbergAVan HallGOsadaTSacchettiMSaltinBPedersenBK. Production of interleukin-6 in contracting human skeletal muscles can account for the exercise-induced increase in plasma interleukin-6. J Physiol. (2000) 529:237–42. 10.1111/j.1469-7793.2000.00237.x
52.
HawleyJAHargreavesMJoynerMJZierathJR. Integrative biology of exercise. Cell. (2014) 159:738–49. 10.1016/j.cell.2014.10.029
53.
BoothFWRobertsCKThyfaultJPRuegseggerGNToedebuschRG. Role of inactivity in chronic diseases: evolutionary insight and pathophysiological mechanisms. Physiol Rev. (2017) 97:1351–402. 10.1152/physrev.00019.2016
54.
GreenDJHopmanMTEPadillaJLaughlinMHThijssenDH. Vascular adaptation to exercise in humans: role of hemodynamic stimuli. Physiol Rev. (2017) 97:495–528. 10.1152/physrev.00014.2016
55.
VossMWHeoSPrakashRSEricksonKIAlvesHChaddockL, et al. The influence of aerobic fitness on cerebral white matter integrity and cognitive function in older adults: results of a one-year exercise intervention. Hum Brain Mapp. (2013) 34:2972–85. 10.1002/hbm.22119
56.
RosenbaumSTiedemannASherringtonCCurtisJWardPB. Physical activity interventions for people with mental illness: a systematic review and meta-analysis. J Clin Psychiatry. (2014) 75:964–74. 10.4088/jcp.13r08765
57.
GleesonMBishopNCStenselDJLindleyMRMastanaSSNimmoMA. The anti-inflammatory effects of exercise: mechanisms and implications for the prevention and treatment of disease. Nat Rev Immunol. (2011) 11:607–15. 10.1038/nri3041
58.
MyersJKokkinosPNyelinE. Physical activity, cardiorespiratory fitness, and the metabolic syndrome. Nutrients. (2019) 11:1652. 10.3390/nu11071652
59.
WeeldreyerNRDe GuzmanJCPatersonCAllenJDGaesserGAAngadiSS. Cardiorespiratory fitness, body mass index and mortality: a systematic review and meta-analysis. Br J Sports Med. (2025) 59:339–46. 10.1136/bjsports-2024-108748
60.
KokkinosPMyersJFaselisCPanagiotakosDBDoumasMPittarasA, et al. Exercise capacity and mortality in older men: a 20-year follow-up study. Circulation. (2010) 122:790–7. 10.1161/CIRCULATIONAHA.110.938852
61.
MandsagerKHarbSCremerPPhelanDNissenSEJaberW. Association of cardiorespiratory fitness with long-term mortality among adults undergoing exercise treadmill testing. JAMA Netw Open. (2018) 1:e183605. 10.1001/jamanetworkopen.2018.3605
62.
CleggAYoungJIliffeSRikkertMORockwoodK. Frailty in elderly people. Lancet. (2013) 381:752–62. 10.1016/s0140-6736(12)62167-9
63.
FriedLPTangenCMWalstonJNewmanABHirschCGottdienerJ, et al. Frailty in older adults: evidence for a phenotype. J Gerontol Ser A Biol Sci Med Sci. (2001) 56:M146–57. 10.1093/gerona/56.3.M146
64.
WalstonJHadleyECFerrucciLGuralnikJMNewmanABStudenskiSA, et al. Research agenda for frailty in older adults: toward a better understanding of physiology and etiology: summary from the american geriatrics society/national institute on aging research conference on frailty in older adults. J Am Geriatr Soc. (2006) 54:991–1001. 10.1111/j.1532-5415.2006.00745.x
65.
BergHELarssonLTeschPA. Lower limb skeletal muscle function after 6 wk of bed rest. J Appl Physiol Respir Environ Exerc Physiol. (1997) 82:182–8. 10.1152/jappl.1997.82.1.182
66.
Cruz-JentoftAJBaeyensJPBauerJMBoirieYCederholmTLandiF, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European working group on sarcopenia in older people. Age Ageing. (2010) 39:412–23. 10.1093/ageing/afq034
67.
EnglishKLPaddon-JonesD. Protecting muscle mass and function in older adults during bed rest. Curr Opin Clin Nutr Metab Care. (2010) 13:34–9. 10.1097/MCO.0b013e328333aa66
68.
SuettaCHvidLGJustesenLChristensenUNeergaardKSimonsenL, et al. Effects of aging on human skeletal muscle after immobilization and retraining. J Appl Physiol Respir Environ Exerc Physiol. (2009) 107:1172–80. 10.1152/japplphysiol.00290.2009
69.
Bortz IIWM. The disuse syndrome. West J Med. (1984) 141:691–4.
70.
ConvertinoVA. Cardiovascular consequences of bed rest: effect on maximal oxygen uptake. Med Sci Sports Exerc. (1997) 29:191–6. 10.1097/00005768-199702000-00005
71.
Paddon-JonesDRasmussenBB. Dietary protein recommendations and the prevention of sarcopenia. Curr Opin Clin Nutr Metab Care. (2009) 12:86–90. 10.1097/MCO.0b013e32831cef8b
72.
ConvertinoVHungJGoldwaterDDeBuskRF. Cardiovascular responses to exercise in middle-aged men after 10 days of bedrest. Circulation. (1982) 65:134–40. 10.1161/01.CIR.65.1.134
73.
SaltinB. Response to exercise after bed rest and after training. Circulation. (1968) 38:VII1–78. 10.1161/01.CIR.38.6.1104
74.
LeBlancASchneiderVShackelfordLWestSOganovVBakulinA, et al. Bone mineral and lean tissue loss after long duration space flight. J Musculoskelet Neuronal Interact. (2000) 1:157–60.
75.
ZerwekhJERumlLAGottschalkFPakCYC. The effects of twelve weeks of bed rest on bone histology, biochemical markers of bone turnover, and calcium homeostasis in eleven normal subjects. J Bone Miner Res. (1998) 13:1594–601. 10.1359/jbmr.1998.13.10.1594
76.
BloomfieldSAMysiwWJJacksonRD. Bone mass and endocrine adaptations to training in spinal cord injured individuals. Bone. (1996) 19:61–8. 10.1016/8756-3282(96)00109-3
77.
CoyleEFJoynerMJHagbergJMHolloszyJO. Time course of loss of adaptations after stopping prolonged intense endurance training. J Appl Physiol Respir Environ Exerc Physiol. (1984) 57:1857–64. 10.1152/jappl.1984.57.6.1857
78.
MujikaIPadillaS. Detraining: loss of training-induced physiological and performance adaptations. Part I: short term insufficient training stimulus. Sports Med. (2000) 30:79–87. 10.2165/00007256-200030020-00002
79.
HardySEPereraSRoumaniYFChandlerJMStudenskiSA. Improvement in usual gait speed predicts better survival in older adults. J Am Geriatr Soc. (2007) 55:1727–34. 10.1111/j.1532-5415.2007.01413.x
80.
MyersJPrakashMFroelicherVDoDPartingtonSAtwoodJE. Exercise capacity and mortality among men referred for exercise testing. New Engl J Med. (2002) 346:793–801. 10.1056/NEJMoa011858
81.
StudenskiSPereraSPatelKRosanoCFaulknerKInzitariM, et al. Gait speed and survival in older adults. JAMA. (2011) 305:50–8. 10.1001/jama.2010.1923
82.
CesariMKritchevskySBPenninxBWNicklasBJSimonsickEMNewmanAB, et al. Prognostic value of usual gait speed in well-functioning older people—results from the health, aging and body composition study. J Am Geriatr Soc. (2005) 53:1675–80. 10.1111/j.1532-5415.2005.53501.x
83.
HardySEKangYStudenskiSADegenholtzHB. Ability to walk 1/4 mile predicts subsequent disability, mortality, and health care costs. J Gen Intern Med. (2011) 26:130–5. 10.1007/s11606-010-1543-2
84.
Van KanGARollandYAndrieuSBauerJBeauchetOBonnefoyM, et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an international academy on nutrition and aging (IANA) task force. J Nutr Health Aging. (2009) 13:881–9. 10.1007/s12603-009-0246-z
85.
LeongDPTeoKKRangarajanSLopez-JaramilloPAvezumAOrlandiniA, et al. Prognostic value of grip strength: findings from the prospective Urban rural epidemiology (PURE) study. Lancet. (2015) 386:266–73. 10.1016/s0140-6736(14)62000-6
86.
RantanenTGuralnikJMFoleyDMasakiKLeveilleSCurbJD, et al. Midlife hand grip strength as a predictor of old age disability. JAMA. (1999) 281:558–60. 10.1001/jama.281.6.558
87.
SyddallHCooperCMartinFBriggsRAihie SayerA. Is grip strength a useful single marker of frailty?Age Ageing. (2003) 32:650–6. 10.1093/ageing/afg111
88.
EngelGL. The need for a new medical model: a challenge for biomedicine. Psychodyn Psychiatry. (2012) 40:377–96. 10.1521/pdps.2012.40.3.377
89.
AinsworthBCahalinLBumanMRossR. The current state of physical activity assessment tools. Prog Cardiovasc Dis. (2015) 57:387–95. 10.1016/j.pcad.2014.10.005
90.
GarryJPDiamondJJWhitleyTW. Physical activity curricula in medical schools. Acad Med. (2002) 77:818–20. 10.1097/00001888-200208000-00011
91.
AsifIThorntonJSCarekSMilesCNayakMNovakM, et al. Exercise medicine and physical activity promotion: core curricula for US medical schools, residencies and sports medicine fellowships: developed by the American medical society for sports medicine and endorsed by the Canadian academy of sport and exercise medicine. Br J Sports Med. (2022) 56:369–75. 10.1136/bjsports-2021-104819
92.
World Health Organization. International Classification of Functioning, Disability, and Health: Children & Youth Version: ICF-CY. Geneva, Switzerland: World Health Organization (2007).
93.
MilletNJSnyder ValierAREbermanLERiveraMJWinkelmannZK. The knowledge and use of the international classification of functioning, disability and health (ICF) framework in athletic training. Int J Environ Res Public Health. (2023) 20:5401. 10.3390/ijerph20075401
94.
PaltamaaJvan LingenEHaumerCKidritschAAertsIMutanenL. Specific ICF training is needed in clinical practice: ICF framework education is not enough. Front Rehabil Sci. (2024) 5:1351564. 10.3389/fresc.2024.1351564
95.
PrinceSAAdamoKBHamelMEHardtJGorberSCTremblayM. A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. Int J Behav Nutr Phys Act. (2008) 5:56. 10.1186/1479-5868-5-56
96.
SallisJFSaelensBE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. (2000) 71:1–14. 10.1080/02701367.2000.11082780
97.
ShephardRJ. Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med. (2003) 37:197–206. 10.1136/bjsm.37.3.197
98.
BakerR. Gait analysis methods in rehabilitation. J Neuroeng Rehabil. (2006) 3:4. 10.1186/1743-0003-3-4
99.
SchwartzMHRozumalskiA. The gait deviation index: a new comprehensive index of gait pathology. Gait Posture. (2008) 28:351–7. 10.1016/j.gaitpost.2008.05.001
100.
WrenTALGorton IIIGEOunpuuSTuckerCA. Efficacy of clinical gait analysis: a systematic review. Gait Posture. (2011) 34:149–53. 10.1016/j.gaitpost.2011.03.027
101.
Cadmus-BertramLAMarcusBHPattersonREParkerBAMoreyBL. Randomized trial of a Fitbit-based physical activity intervention for women. Am J Prev Med. (2015) 49:414–8. 10.1016/j.amepre.2015.01.020
102.
MiguelesJHCadenas-SanchezCEkelundUDelisle NyströmCMora-GonzalezJLöfM, et al. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sports Med. (2017) 47:1821–45. 10.1007/s40279-017-0716-0
103.
BlairSN. Physical inactivity: the biggest public health problem of the 21st century. Br J Sports Med. (2009) 43:1–2.
104.
PedersenBKSaltinB. Evidence for prescribing exercise as therapy in chronic disease. Scand J Med Sci Sports. (2006) 16:3–63. 10.1111/j.1600-0838.2006.00520.x
105.
WarburtonDERNicolCWBredinSSD. Health benefits of physical activity: the evidence. Can Med Assoc J. (2006) 174:801–9. 10.1503/cmaj.051351
106.
Micó-AmigoMEBonciTParaschiv-IonescuAUllrichMKirkCSoltaniA, et al. Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium. J Neuroeng Rehabil. (2023) 20:78. 10.1186/s12984-023-01198-5
107.
RochesterLMazzàCMuellerACaulfieldBMcCarthyMBeckerC, et al. A roadmap to inform development, validation and approval of digital mobility outcomes: the mobilise-D approach. Digit Biomarkers. (2020) 4:13–27. 10.1159/000512513
108.
GuBKimHSKimHYooJI. Advancements in wearable sensor technologies for health monitoring in terms of clinical applications, rehabilitation, and disease risk assessment: systematic review. JMIR Mhealth Uhealth. (2026) 14:e76084. 10.2196/76084
109.
FrankLDAndresenMASchmidTL. Obesity relationships with community design, physical activity, and time spent in cars. Am J Prev Med. (2004) 27:87–96. 10.1016/j.amepre.2004.04.011
110.
LakeATownshendT. Obesogenic environments: exploring the built and food environments. J R Soc Promot Health. (2006) 126:262–7. 10.1177/1466424006070487
111.
PapasMAAlbergAJEwingRHelzlsouerKJGaryTLKlassenAC. The built environment and obesity. Epidemiol Rev. (2007) 29:129–43. 10.1093/epirev/mxm009
112.
SwinburnBEggerGRazaF. Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev Med. (1999) 29:563–70. 10.1006/pmed.1999.0585
113.
DuanyAPlater-ZyberkESpeckJ. Suburban Nation: The Rise of Sprawl and the Decline of the American Dream. New York: Macmillan (2000).
114.
FrumkinHFrankLJacksonR. Urban Sprawl and Public Health: Designing, Planning, and Building for Healthy Communities. Washington, D.C.: Island Press (2004).
115.
OwenNHumpelNLeslieEBaumanASallisJF. Understanding environmental influences on walking: review and research agenda. Am J Prev Med. (2004) 27:67–76. 10.1016/j.amepre.2004.03.006
116.
SaelensBESallisJFFrankLD. Environmental correlates of walking and cycling: findings from the transportation, urban design, and planning literatures. Ann Behav Med. (2003) 25:80–91. 10.1207/S15324796ABM2502_03
117.
SallisJBaumanAPrattM. Environmental and policy interventions to promote physical activity. Am J Prev Med. (1998) 15:379–97. 10.1016/S0749-3797(98)00076-2
118.
BrownsonRCBoehmerTKLukeDA. Declining rates of physical activity in the United States: what are the contributors?Annu Rev Public Health. (2005) 26:421–43. 10.1146/annurev.publhealth.26.021304.144437
119.
ChurchTSThomasDMTudor-LockeCKatzmarzykPTEarnestCPRodarteRQ, et al. Trends over 5 decades in us occupation-related physical activity and their associations with obesity. PLoS One. (2011) 6:e19657. 10.1371/journal.pone.0019657
120.
NgSWPopkinBM. Time use and physical activity: a shift away from movement across the globe. Obes Rev. (2012) 13:659–80. 10.1111/j.1467-789X.2011.00982.x
121.
PronkNPKatzASLowryMPayferJR. Reducing occupational sitting time and improving worker health: the take-a-stand project, 2011. Prev Chronic Dis. (2012) 9:E154. 10.5888/pcd9.110323
122.
ThorpAAHealyGNOwenNSalmonJOBallKShawJE, et al. Deleterious associations of sitting time and television viewing time with cardiometabolic risk biomarkers: Australian diabetes, obesity and lifestyle (AusDiab) study 2004–2005. Diabetes Care. (2010) 33:327–34. 10.2337/dc09-0493
123.
SantosACWillumsenJMeheusFIlbawiABullFC. The cost of inaction on physical inactivity to public health-care systems: a population-attributable fraction analysis. Lancet Glob Health. (2023) 11:e32–9. 10.1016/S2214-109X(22)00464-8
124.
World Health Organization. Global Status Report on Physical Activity 2022: Country Profiles. Geneva, Switzerland: World Health Organization (2022).
125.
PronkNPGoodmanMJO’ConnorPJMartinsonBC. Relationship between modifiable health risks and short-term health care charges. JAMA. (1999) 282:2235–9. 10.1001/jama.282.23.2235
126.
MarshallSJBiddleSJHGorelyTCameronNMurdeyI. Relationships between media use, body fatness and physical activity in children and youth: a meta-analysis. Int J Obes. (2004) 28:1238–46. 10.1038/sj.ijo.0802706
127.
RobinsonTN. Reducing children’s television viewing to prevent obesity: a randomized controlled trial. JAMA. (1999) 282:1561–7. 10.1001/jama.282.16.1561
128.
VandelanotteCSpathonisKMEakinEGOwenN. Website-delivered physical activity interventions: a review of the literature. Am J Prev Med. (2007) 33:54–64. 10.1016/j.amepre.2007.02.041
129.
ClarkeAEShimJKMamoLFosketJRFishmanJR. Biomedicalization: technoscientific transformations of health, illness, and US biomedicine. Am Sociol Rev. (2003) 68:161–94. 10.1177/000312240306800201
130.
ConradP. The Medicalization of Society: On the Transformation of Human Conditions Into Treatable Disorders. Baltimore: Johns Hopkins University Press (2007).
131.
ZolaIK. Medicine as an institution of social control. Sociol Rev. (1972) 20:487–504. 10.1111/j.1467-954X.1972.tb00220.x
132.
OwenNHealyGNMatthewsCEDunstanDW. Too much sitting: the population health science of sedentary behavior. Exerc Sport Sci Rev. (2010) 38:105–13. 10.1097/JES.0b013e3181e373a2
133.
TremblayMSColleyRCSaundersTJHealyGNOwenN. Physiological and health implications of a sedentary lifestyle. Appl Physiol Nutr Metab. (2010) 35:725–40. 10.1139/H10-079.
134.
YoungDRHivertMFAlhassanSCamhiSMFergusonJFKatzmarzykPT, et al. Sedentary behavior and cardiovascular morbidity and mortality: a science advisory from the American heart association. Circulation. (2016) 134:e262–79. 10.1161/CIR.0000000000000440
135.
LavieCJOzemekCCarboneSKatzmarzykPTBlairSN. Sedentary behavior, exercise, and cardiovascular health. Circ Res. (2019) 124:799–815. 10.1161/CIRCRESAHA.118.312669
136.
MorrisJNHeadyJARafflePABRobertsCGParksJW. Coronary heart-disease and physical activity of work. Lancet. (1953) 262:1111–20. 10.1016/S0140-6736(53)91495-0
137.
NoconMHiemannTMüller-RiemenschneiderFThalauFRollSWillichSN. Association of physical activity with all-cause and cardiovascular mortality: a systematic review and meta-analysis. Eur J Prev Cardiol. (2008) 15:239–46. 10.1097/HJR.0b013e3282f55e09
138.
SattelmairJPertmanJDingELKohl IIIHWHaskellWLeeIM. Dose response between physical activity and risk of coronary heart disease: a meta-analysis. Circulation. (2011) 124:789–95. 10.1161/CIRCULATIONAHA.110.010710
139.
LeeIMShiromaEJLobeloFPuskaPBlairSNKatzmarzykPT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. (2012) 380:219–29. 10.1016/s0140-6736(12)61031-9
140.
WenCPWaiJPMTsaiMKYangYCChengTYDLeeMC, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet. (2011) 378:1244–53. 10.1016/s0140-6736(11)60749-6
141.
Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. (2002) 346:393–403. 10.1056/NEJMoa012512
142.
SigalRJKennyGPWassermanDHCastaneda-SceppaCWhiteRD. Physical activity/exercise and type 2 diabetes: a consensus statement from the American diabetes association. Diabetes Care. (2006) 29:1433–8. 10.2337/dc06-9910
143.
UmpierreDRibeiroPABKramerCKLeitaoCBZucattiATNAzevedoMJ, et al. Physical activity advice only or structured exercise training and association with HbA1c levels in type 2 diabetes: a systematic review and meta-analysis. JAMA. (2011) 305:1790–9. 10.1001/jama.2011.576
144.
BlumenthalJABabyakMADoraiswamyPMWatkinsLHoffmanBMBarbourKA, et al. Exercise and pharmacotherapy in the treatment of major depressive disorder. Psychosom Med. (2007) 69:587–96. 10.1097/psy.0b013e318148c19a
145.
GordonBRMcDowellCPHallgrenMMeyerJDLyonsMHerringMP. Association of efficacy of resistance exercise training with depressive symptoms: meta-analysis and meta-regression analysis of randomized clinical trials. JAMA Psychiatry. (2018) 75:566–76. 10.1001/jamapsychiatry.2018.0572
146.
KandolaAAshdown-FranksGHendrikseJSabistonCMStubbsB. Physical activity and depression: towards understanding the antidepressant mechanisms of physical activity. Neurosci Biobehav Rev. (2019) 107:525–39. 10.1016/j.neubiorev.2019.09.040
147.
SchuchFBVancampfortDFirthJRosenbaumSWardPBSilvaES, et al. Physical activity and incident depression: a meta-analysis of prospective cohort studies. Am J Psychiatry. (2018) 175:631–48. 10.1176/appi.ajp.2018.17111194
148.
EricksonKIVossMWPrakashRSBasakCSzaboAChaddockL, et al. Exercise training increases size of hippocampus and improves memory. Proc Natl Acad Sci. (2011) 108:3017–22. 10.1073/pnas.1015950108
149.
SmithPJBlumenthalJAHoffmanBMCooperHStraumanTAWelsh-BohmerK, et al. Aerobic exercise and neurocognitive performance: a meta-analytic review of randomized controlled trials. Psychosom Med. (2010) 72:239–52. 10.1097/PSY.0b013e3181d14633
150.
HillmanCHEricksonKIKramerAF. Be smart, exercise your heart: exercise effects on brain and cognition. Nat Rev Neurosci. (2008) 9:58–65. 10.1038/nrn2298
151.
KramerAFEricksonKI. Capitalizing on cortical plasticity: influence of physical activity on cognition and brain function. Trends Cogn Sci. (2007) 11:342–8. 10.1016/j.tics.2007.06.009
152.
FriedenreichCMOrensteinMR. Physical activity and cancer prevention: etiologic evidence and biological mechanisms. J Nutr. (2002) 132:3456S–64S. 10.1093/jn/132.11.3456S
153.
MooreSCLeeIMWeiderpassECampbellPTSampsonJNKitaharaCM, et al. Association of leisure-time physical activity with risk of 26 types of cancer in 1.44 million adults. JAMA Intern Med. (2016) 176:816–25. 10.1001/jamainternmed.2016.1548
154.
WolinKYCarsonKColditzGA. Obesity and cancer. Oncologist. (2010) 15:556–65. 10.1634/theoncologist.2009-0285
155.
BettarigaFGalvaoDATaaffeDRBishopCLopezPMaestroniL, et al. Association of muscle strength and cardiorespiratory fitness with all-cause and cancer-specific mortality in patients diagnosed with cancer: a systematic review with meta-analysis. Br J Sports Med. (2025) 59:722–32. 10.1136/bjsports-2024-108671
156.
FriedenreichCMStoneCRCheungWYHayesSC. Physical activity and mortality in cancer survivors: a systematic review and meta-analysis. JNCI Cancer Spectrum. (2020) 4:pkz080. 10.1093/jncics/pkz080
157.
SpeckRMCourneyaKSMâsseLCDuvalSSchmitzKH. An update of controlled physical activity trials in cancer survivors: a systematic review and meta-analysis. J Cancer Surviv. (2010) 4:87–100. 10.1007/s11764-009-0110-5
158.
Martyn-St JamesMCarrollS. A meta-analysis of impact exercise on postmenopausal bone loss: the case for mixed loading exercise programmes. Br J Sports Med. (2009) 43:898–908. 10.1136/bjsm.2008.052704
159.
NikanderRSievänenHHeinonenADalyRMUusi-RasiKKannusP. Targeted exercise against osteoporosis: a systematic review and meta-analysis for optimising bone strength throughout life. BMC Med. (2010) 8:47. 10.1186/1741-7015-8-47
160.
ZhaoRZhangMZhangQ. The effectiveness of combined exercise interventions for preventing postmenopausal bone loss: a systematic review and meta-analysis. J Orthop Sports Phys Ther. (2017) 47:241–51. 10.2519/jospt.2017.6969
161.
GillespieLDRobertsonMCGillespieWJSherringtonCGatesSClemsonL, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. (2012) 9:CD007146. 10.1002/14651858.CD007146.pub3
162.
SherringtonCMichaleffZAFairhallNPaulSSTiedemannAWhitneyJ, et al. Exercise to prevent falls in older adults: an updated systematic review and meta-analysis. Br J Sports Med. (2017) 51:1750–8. 10.1136/bjsports-2016-096547
163.
TriccoACThomasSMVeronikiAAHamidJSCogoEStriflerL, et al. Comparisons of interventions for preventing falls in older adults: a systematic review and meta-analysis. JAMA. (2017) 318:1687–99. 10.1001/jama.2017.15006
164.
KelleyGAKelleyKS. Exercise and sleep: a systematic review of previous meta-analyses. J Evid Based Med. (2017) 10:26–36. 10.1111/jebm.12236
165.
KredlowMACapozzoliMCHearonBACalkinsAWOttoMW. The effects of physical activity on sleep: a meta-analytic review. J Behav Med. (2015) 38:427–49. 10.1007/s10865-015-9617-6
166.
HartescuIMorganKStevinsonCD. Increased physical activity improves sleep and mood outcomes in inactive people with insomnia: a randomized controlled trial. J Sleep Res. (2015) 24:526–34. 10.1111/jsr.12297
167.
DriverHSTaylorSR. Exercise and sleep. Sleep Med Rev. (2000) 4:387–402. 10.1053/smrv.2000.0110
168.
ReidKJBaronKGLuBNaylorEWolfeLZeePC. Aerobic exercise improves self-reported sleep and quality of life in older adults with insomnia. Sleep Med. (2010) 11:934–40. 10.1016/j.sleep.2010.04.014
169.
YoungstedtSD. Effects of exercise on sleep. Clin Sports Med. (2005) 24:355–65. 10.1016/j.csm.2004.12.003
170.
ChengXCaoMYeungWFCheungDST. The effectiveness of exercise in alleviating long COVID symptoms: a systematic review and meta-analysis. Worldviews Evid Based Nurs. (2024) 21:561–74. 10.1111/wvn.12743
171.
MilaniJGPOMilaniMVerbovenKCipriano JrGHansenD. Exercise intensity prescription in cardiovascular rehabilitation: bridging the gap between best evidence and clinical practice. Front Cardiovasc Med. (2024) 11:1380639. 10.3389/fcvm.2024.1380639
172.
AroraNKDonathLOwenPJMillerCTSaueressigTWinterF, et al. The impact of exercise prescription variables on intervention outcomes in musculoskeletal pain: an umbrella review of systematic reviews. Sports Med. (2024) 54:711–25. 10.1007/s40279-023-01966-2
173.
DamschroderLJAronDCKeithREKirshSRAlexanderJALoweryJC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. (2009) 4:1–15. 10.1186/1748-5908-4-50
174.
DzewaltowskiDAGlasgowREKlesgesLMEstabrooksPABrockERE-AIM. Evidence-based standards and a web resource to improve translation of research into practice. Ann Behav Med. (2004) 28:75–80. 10.1207/s15324796abm2802_1
175.
FixsenDLNaoomSFBlaseKAFriedmanRMWallaceF, Implementation Research: A Synthesis of the Literature. Tampa: University of South Florida (2005).
176.
BeanJFKielyDKHermanSLeveilleSGMizerKFronteraWR, et al. The relationship between leg power and physical performance in mobility-limited older people. J Am Geriatr Soc. (2002) 50:461–7. 10.1046/j.1532-5415.2002.50111.x
177.
GuralnikJMSimonsickEMFerrucciLGlynnRJBerkmanLFBlazerDG, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. (1994) 49:M85–94. 10.1093/geronj/49.2.M85
178.
PereraSModySHWoodmanRCStudenskiSA. Meaningful change and responsiveness in common physical performance measures in older adults. J Am Geriatr Soc. (2006) 54:743–9. 10.1111/j.1532-5415.2006.00701.x
179.
BaladyGJArenaRSietsemaKMyersJCokeLFletcherGF, et al. Clinician’s guide to cardiopulmonary exercise testing in adults: a scientific statement from the American heart association. Circulation. (2010) 122:191–225. 10.1161/CIR.0b013e3181e52e69
180.
FletcherGFAdesPAKligfieldPArenaRBaladyGJBittnerVA, et al. Exercise standards for testing and training: a scientific statement from the American heart association. Circulation. (2013) 128:873–934. 10.1161/CIR.0b013e31829b5b44
181.
ChorbaRSChorbaDJBouillonLEOvermyerCALandisJA. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports Phys Ther. (2010) 5:47–54.
182.
KieselKPliskyPJVoightML. Can serious injury in professional football be predicted by a preseason functional movement screen?N Am J Sports Phys Ther. (2007) 2:147–58.
183.
JoyELBlairSNMcBridePSallisR. Physical activity counselling in sports medicine: a call to action. Br J Sports Med. (2013) 47:49–53. 10.1136/bjsports-2012-091620
184.
WeilerRChewSCoombsNHamerMStamatakisE. Physical activity education in the undergraduate curricula of all UK medical schools. Are tomorrow’s doctors equipped to follow clinical guidelines?Br J Sports Med. (2012) 46:1024–6. 10.1136/bjsports-2012-091380
185.
AndersonGHorvathJ. The growing burden of chronic disease in America. Public Health Rep. (2004) 119:263–70. 10.1016/j.phr.2004.04.005
186.
GoetzelRZOzminkowskiRJVillagraVGDuffyJ. Return on investment in disease management: a review. Health Care Financ Rev. (2005) 26:1–19.
187.
BodenheimerTWagnerEHGrumbachK. Improving primary care for patients with chronic illness: the chronic care model, Part 2. JAMA. (2002) 288:1909–14. 10.1001/jama.288.15.1909
188.
GlasgowREVogtTMBolesSM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. (1999) 89:1322–7. 10.2105/AJPH.89.9.1322
189.
WagnerEHAustinBTDavisCHindmarshMSchaeferJBonomiA. Improving chronic illness care: translating evidence into action. Health Aff. (2001) 20:64–78. 10.1377/hlthaff.20.6.64
190.
BakerDPDayRSalasE. Teamwork as an essential component of high-reliability organizations. Health Serv Res. (2006) 41:1576–98. 10.1111/j.1475-6773.2006.00566.x
191.
ZwarensteinMGoldmanJReevesS. Interprofessional collaboration: effects of practice-based interventions on professional practice and healthcare outcomes. Cochrane Database Syst Rev. (2009) 3:CD000072. 10.1002/14651858.CD000072.pub2
192.
BatesDWKupermanGJWangSGandhiTKittlerAVolkL, et al. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc. (2003) 10:523–30. 10.1197/jamia.M1370
193.
BlumenthalDTavennerM. The “meaningful use” regulation for electronic health records. N Engl J Med. (2010) 363:501–4. 10.1056/NEJMp1006114
194.
ChaudhryBWangJWuSMaglioneMMojicaWRothE, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. (2006) 144:742–52. 10.7326/0003-4819-144-10-200605160-00125
195.
BashshurRShannonGKrupinskiEGrigsbyJ. The taxonomy of telemedicine. Telemed e-Health. (2011) 17:484–94. 10.1089/tmj.2011.0103
196.
EkelandAGBowesAFlottorpS. Effectiveness of telemedicine: a systematic review of reviews. Int J Med Inform. (2010) 79:736–71. 10.1016/j.ijmedinf.2010.08.006
197.
KruseCSKrowskiNRodriguezBTranLVelaJBrooksM. Telehealth and patient satisfaction: a systematic review and narrative analysis. BMJ Open. (2017) 7:e016242. 10.1136/bmjopen-2017-016242
198.
NilsenP. Making sense of implementation theories, models, and frameworks. In: Albers B, Shlonsky A, Mildon R, editors. Implementation Science 3.0. Cham, Switzerland: Springer (2020). p. 53–79.
199.
PowellBJWaltzTJChinmanMJDamschroderLJSmithJLMatthieuMM, et al. A refined compilation of implementation strategies: results from the expert recommendations for implementing change (ERIC) project. Implement Sci. (2015) 10:1–14. 10.1186/s13012-015-0209-1
200.
ProctorESilmereHRaghavanRHovmandPAaronsGBungerA, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health Ment Health Serv Res. (2011) 38:65–76. 10.1007/s10488-010-0319-7
201.
CraigPDieppePMacintyreSMichieSNazarethIPetticrewM. Developing and evaluating complex interventions: the new medical research council guidance. BMJ. (2008) 337:a1655. 10.1136/bmj.a1655
202.
EldridgeSMLancasterGACampbellMJThabaneLHopewellSColemanCL, et al. Defining feasibility and pilot studies in preparation for randomised controlled trials: development of a conceptual framework. PLoS One. (2016) 11:e0150205. 10.1371/journal.pone.0150205
203.
MooreGFAudreySBarkerMBondLBonellCHardemanW, et al. Process evaluation of complex interventions: medical research council guidance. BMJ. (2015) 350:h1258. 10.1136/bmj.h1258
204.
De VetHCWTerweeCBMokkinkLBKnolDL. Measurement in Medicine: A Practical Guide. Cambridge, UK: Cambridge University Press (2011).
205.
MokkinkLBTerweeCBPatrickDLAlonsoJStratfordPWKnolDL, et al. The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. J Clin Epidemiol. (2010) 63:737–45. 10.1016/j.jclinepi.2010.02.006
206.
ChaseJAD. Interventions to increase physical activity among older adults: a meta-analysis. Gerontologist. (2015) 55:706–18. 10.1093/geront/gnu090
207.
LiuCKFieldingRA. Exercise as an intervention for frailty. Clin Geriatr Med. (2011) 27:101–10. 10.1016/j.cger.2010.08.001
208.
ColbergSRSigalRJYardleyJERiddellMCDunstanDWDempseyPC, et al. Physical activity/exercise and diabetes: a position statement of the American diabetes association. Diabetes Care. (2016) 39:2065–79. 10.2337/dc16-1728
209.
MeekumsBKarkouVNelsonEA. Dance movement therapy for depression. Cochrane Database Syst Rev. (2015) 2015:CD009895. 10.1002/14651858.CD009895.pub2
210.
LosinaESmithKCPaltielADCollinsJESuterLGHunterDJ, et al. Cost-effectiveness of diet and exercise for overweight and obese patients with knee osteoarthritis. Arthritis Care Res. (2019) 71:855–64. 10.1002/acr.23716
211.
Müller-RiemenschneiderFReinholdTNoconMWillichSN. Long-term effectiveness of interventions promoting physical activity: a systematic review. Prev Med. (2008) 47:354–68. 10.1016/j.ypmed.2008.07.006
212.
FrankJRSnellLSCateOTHolmboeESCarraccioCSwingSR, et al. Competency-based medical education: theory to practice. Med Teach. (2010) 32:638–45. 10.3109/0142159X.2010.501190
213.
FrenkJChenLBhuttaZACohenJCrispNEvansT, et al. Health professionals for a new century: transforming education to strengthen health systems in an interdependent world. Lancet. (2010) 376:1923–58. 10.1016/s0140-6736(10)61854-5
214.
Ten CateOScheeleF. Competency-based postgraduate training: can we bridge the gap between theory and clinical practice?Acad Med. (2007) 82:542–7. 10.1097/ACM.0b013e31805559c7
215.
van der VleutenCPMSchuwirthLWTDriessenEWDijkstraJTigelaarDBaartmanLKJ, et al. A model for programmatic assessment fit for purpose. Med Teach. (2012) 34:205–14. 10.3109/0142159X.2012.652239
216.
ReevesSFletcherSBarrHBirchIBoetSDaviesN, et al. A BEME systematic review of the effects of interprofessional education: BEME Guide No. 39. Med Teach. (2016) 38:656–68. 10.3109/0142159X.2016.1173663
217.
ThistlethwaiteJEBartleEChongAALDickMLKingDMahoneyS, et al. A review of longitudinal community and hospital placements in medical education: BEME Guide No. 26. Med Teach. (2013) 35:e1340–64. 10.3109/0142159X.2013.806981
218.
BrasierNWangJGaoWSempionattoJRDincerCAtesHC, et al. Applied body-fluid analysis by wearable devices. Nature. (2024) 636:57–68. 10.1038/s41586-024-08249-4
219.
ChenJHAschSM. Machine learning and prediction in medicine—beyond the peak of inflated expectations. N Engl J Med. (2017) 376:2507–9. 10.1056/NEJMp1702071
220.
RajkomarADeanJKohaneI. Machine learning in medicine. N Engl J Med. (2019) 380:1347–58. 10.1056/NEJMra1814259
221.
TopolEJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. (2019) 25:44–56. 10.1038/s41591-018-0300-7
222.
ButlerPMYangJBrownRHobbsMBeckerAPenalver-AndresJ, et al. Smartwatch-and smartphone-based remote assessment of brain health and detection of mild cognitive impairment. Nat Med. (2025) 31:829–39. 10.1038/s41591-024-03475-9
223.
PowellDAdamsSAMullinDWelsteadMHarrisonJERitchieC. Exploring the potential of digital biomarkers as a measure of brain health “capital”. npj Digit Med. (2025) 8:334. 10.1038/s41746-025-01675-2
224.
BrightTJWongADhurjatiRBristowEBastianLCoeytauxRR, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. (2012) 157:29–43. 10.7326/0003-4819-157-1-201207030-00450
225.
GargAXAdhikariNKJMcDonaldHRosas-ArellanoMPDevereauxPJBeyeneJ, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. (2005) 293:1223–38. 10.1001/jama.293.10.1223
226.
KawamotoKHoulihanCABalasEALobachDF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. (2005) 330:765. 10.1136/bmj.38398.500764.8F
Summary
Keywords
aging, exercise prescription, frailty, functional assessment, movement-centered healthcare, physical activity
Citation
Mangalam M and Fabianiak J (2026) The movement imperative: reimagining healthcare through the lens of human movement. Front. Sports Act. Living 8:1667847. doi: 10.3389/fspor.2026.1667847
Received
18 July 2025
Revised
15 February 2026
Accepted
26 March 2026
Published
07 May 2026
Volume
8 - 2026
Edited by
Giuseppe Caminiti, Università Telematica San Raffaele, Italy
Reviewed by
Oleksandr P Romanchuk, Lesya Ukrainka Volyn National University, Ukraine
Maria-Elissavet Nikolaidou, National and Kapodistrian University of Athens, Greece
Updates
Copyright
© 2026 Mangalam and Fabianiak.
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*Correspondence: Madhur Mangalam mmangalam@unomaha.edu
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