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Exercise and Sport Sciences Reviews   ( ESSR ) ,  a quarterly review publication. ESSR provides premier, peer-reviewed reviews of contemporary scientific, medical and research-based topics emerging in the field of sports medicine and exercise science. ESSR strives to provide the most relevant, topical information to students, professors, clinicians, scientists, and professionals for practical and research applications

Exercise and Sport Sciences Reviews  consists of articles for readers with a broad interest in scientific issues related to exercise, movement, physical activity and/or sport.

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Journal Impact Factor: 5.7 – 6th of 87 in Sports Sciences ISBN: 0091-6331 PubMed Abbreviation:  Exerc Sport Sci Rev . Common Misspellings: Exercise and Sport Science Reviews, Exercise and Sports Sciences Reviews

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Exercise Physiology From 1980 to 2020: Application of the Natural Sciences

The field of exercise physiology has enjoyed tremendous growth in the past 40 years. With its foundations in the natural sciences, it is an interdisciplinary field that is highly relevant to human performance and health. The focus of this review is on highlighting new approaches, knowledge, and opportunities that have emerged in exercise physiology over the last four decades. Key among these is the adoption of advanced technologies by exercise physiologists to address fundamental research questions, and the expansion of research topics to range from molecular to organismal, and population scales in order to clarify the underlying mechanisms and impact of physiological responses to exercise in health and disease. Collectively, these advances have ensured the position of the field as a partner in generating new knowledge across many scientific and health disciplines.

The past 40 years have been a period of explosive growth in knowledge and application for the field of exercise physiology. This growth is reflected by the volume of research performed and the expansion of exercise physiology principles into interdisciplinary and translational research. Figure 1 illustrates the increase in publications in exercise physiology since 1980, as well as its representation in highly regarded scientific and clinical journals such as the Proceedings of the National Academy of Sciences and the Journal of the American Medical Association , respectively. While the number of publications in all scientific fields likely follows a similar growth pattern over the same period, it is notable that “exercise physiology” has shown strong growth overall and in its breadth of applications in scientific and clinical journals that are not strictly focused on exercise.

Number of publications including the term “exercise physiology” indexed in PubMed between 1980 and 2020. (a) Total number of “exercise physiology” publications indexed in PubMed, (b) number of “exercise physiology” publications in Proceedings of the National Academy of Sciences indexed in PubMed, and (c) number of publications in the Journal of the American Medical Association indexed in PubMed. Arrows indicate apparent inflection points beyond which the rate of publications increased in representative basic and clinical science journals.

Where did we leave off? 40 years ago, critical questions in the field were largely focused on understanding how energy is generated to support exercise. At that time, these questions concentrated on the kinetics of oxygen consumption and fuel selection during various exercise protocols, as well as the interplay between “aerobic” and “anaerobic” metabolism ( Faulkner & White, 1981 ). The drive to understand the limits to human physical performance was strong, and these studies helped establish the critical features of exceptional human performance as well as the boundaries within which subsequent research has applied these same approaches and concepts to understanding the mechanisms that support human health and function in a range of populations.

The discipline of exercise physiology has both pushed and been pushed by technological advances (of course!). Our ability to identify molecular factors associated with specific responses and adaptations to exercise in addition to being able to visualize protein interactions, understand cellular biochemistry, and investigate in vivo structure and function are but a few examples of how technological developments have enhanced our ability to ask increasingly sophisticated questions related to physiology and the response to exercise.

From the beginning, exercise physiology has been an integrative science; understanding the physiological responses to acute or chronic exercise in the whole organism requires an acknowledgement of the influence of variables such as the mechanical, neural, environmental, psychological, hormonal, diurnal, and nutritional factors that affect our exercise responses. This necessary integration has become even more apparent as we join with researchers in other disciplines within kinesiology (e.g., biomechanics, neuroscience), the STEM fields, and clinical researchers in the health professions (medicine and public health). Indeed, Faulkner and White (1981) discussed the importance of placing graduate students into high-caliber postdoctoral positions in basic sciences in order to increase the rigor and impact of exercise physiology studies. A quick evaluation of current fundings by the National Institutes of Health (NIH) suggests that this advice has been followed: there are currently 26 funded individual and institutional training grants and another 477 research grants that include the search term “exercise physiology.” The number of funded NIH grants grows to over 47,000 when the word “exercise” is in the search term. While clearly not a systematic analysis, these numbers provide some indication of the extent to which exercise physiology has made its way into mainstream biomedical research in the past 40 years.

It must be noted that, until relatively recently, a substantial limitation to existing studies in exercise physiology has been the nearly exclusive use of healthy, young, White males as study participants. Indeed, even studies using animal models were historically performed only on young male animals. As a result of this limitation, there are significant knowledge gaps regarding the generalizability of the results of these earlier studies to most of the population; those who are non-White, nonmale, or >65 years of age. In recent years, biomedical researchers have begun to address this problem, in part through requirements by agencies that fund research to be inclusive of persons from underrepresented groups, including racial and ethnic minorities, women, children, and older adults. Given the clear disparities in health outcomes in various portions of the population, studies that are inclusive and diverse are essential to advancing the field.

The intent of this review is to highlight some of the new methods, knowledge, and opportunities that have been developed in the field of exercise physiology in the last 40 years. The examples discussed are meant to provide an understanding of the breadth and depth of scientific endeavor in the field. Indeed, a clear theme that has emerged is the position of exercise physiology at the intersection of research from multiple fields that are related to human performance and health. While a full discussion of the many important discoveries in our field is beyond the scope of this review, readers are directed to the excellent journal Exercise and Sport Sciences Reviews . Published by the American College of Sports Medicine and under the direction of Editor-in-Chief Roger Enoka, this quarterly journal is an outstanding resource for those interested in learning about innovative, timely, and high-impact research in physiology and exercise science.

New Tools and Approaches

In the last 40 years, technology and innovation have advanced the field of exercise physiology in remarkable ways. Imaging techniques have evolved to allow visualization of molecular, cellular, and physiological phenomena. An explosion in wearable sensor technology has allowed researchers to collect rich data sets of physical activity and metabolic variables both inside and outside of the laboratory. Genetic advances created the opportunity for exercise physiologists to delve into genomic, epigenomic, transcriptomic, and metabolomic mechanisms that underpin physiological responses to exercise. The quantity of data that can be obtained has created opportunities for the use of advanced analytical techniques in the field, including meta-analysis and computational modeling, to create and interpret powerful data reflecting a wide range of physiological variables and responses.

Visualizing Physiological Processes

Classical electron and light microscopy techniques have been used by exercise physiologists to understand the form of skeletal muscle since the 1950s ( Porter & Palade, 1957 ). As early as the 1960s, light microscopy was being used to show changes in the arrangements of myofilaments during muscular contraction as evidence for the “sliding filament theory” of skeletal muscle contraction ( Huxley, 1969 ). In the many years since, advances in single-molecule approaches and X-ray crystallography led to the eventual development of the “swinging lever-arm model” to explain actomyosin interactions during muscle contraction ( Geeves et al., 2005 ; Spudich, 2001 ). In fact, the current depth of understanding of actomyosin interactions in the generation of force, velocity, and power is an excellent example of the multidisciplinary nature of exercise physiology, as experts from classical molecular biology, genetics, biophysics, biochemistry, and physiology have all contributed to the current understanding of skeletal muscle contraction at the molecular level.

At the cellular level, advances in biotechnology have allowed for the novel identification and visualization of cells and proteins involved in the response to exercise. For example, exercise physiologists routinely use antibodies to label proteins on either the cell surface or within the cytosol of cells. Antibodies can be fluorescently conjugated for visualization via microscopy or flow cytometry. These labeled proteins provide information about the identity of cells within a tissue in innumerable contexts; including by providing information about the junctions that form between cells or about the types of cells that become activated to promote adaptations to exercise. Specifically, significant work has been done to understand skeletal muscle responses to exercise and disease ( Tidball, 2011 ). Much of this work has been fueled by advances in visualizing cells that infiltrate damaged, injured, or diseased skeletal muscle. Satellite cells, in addition to vascular, perivascular, and immune cells, have been implicated in the regenerative response to skeletal muscle damage and disease ( Hyldahl et al., 2013 ). Understanding the complexities of skeletal muscle repair and regeneration is another prime example of scientists from across disciplines, including immunology, cardiovascular biology, molecular and cellular biology, and physiology, pursuing research questions alongside exercise physiologists.

At the physiological level, imaging techniques, including magnetic resonance imaging and spectroscopy (MRS), near-infrared spectroscopy (NIRS), and positron emission tomography (PET), have informed exercise physiologists about the structure and metabolic function of skeletal muscle, cardiac muscle, and the brain before, during, and after exercise. Magnetic resonance imaging and spectroscopy use a static magnetic field and radiofrequency pulses to encode metabolite-specific information that produces anatomical images or biochemical information (energy compounds, blood flow, etc.), respectively. MRS can be used to detect a variety of lipids and metabolites, such as glycogen, adenosine triphosphate (ATP), phosphocreatine, inorganic phosphate, deoxymyoglobin, and acetylcarnitine in human skeletal muscle ( Kushmerick, 1986 ); (see below). As MRS technology has improved through advances in magnet capabilities, electronics, and data computing, we can now gather even richer biochemical information and resolve the concentrations of metabolites that were previously undetectable, including nicotinamide adenine dinucleotide, and various phosphomonoesters and phosphodiesters ( Meyerspeer et al., 2021 ). Furthermore, ATP flux can be calculated through oxidative and nonoxidative metabolic pathways ( Boska, 1991 ; Kemp et al., 1993 ). This information is used to understand metabolic responses to exercise across the lifespan and the healthspan, including understanding how aging and disease affect energy metabolism ( Fitzgerald et al., 2016 ; Krumpolec et al., 2020 ).

Other imaging techniques that have been important in the last 40 years are NIRS and PET. NIRS is used in exercise physiology for assessing tissue oxygenation noninvasively using optical sensors (Britton Chance et al., 1988 ; Hamaoka et al., 2011 ). Advances in NIRS have provided the flexibility to assess tissue oxygenation using portable systems for a wide variety of experimental conditions ( Ryan et al., 2013 ; Shiga et al., 1995 ). In the future, NIRS will continue to prove useful in the field of exercise physiology due to its potential to be integrated into clothing or other wearable sensors, thus providing continuous data both in the laboratory and in free-living settings.

In contrast to the relative portability of NIRS, PET produces images of metabolic processes and blood flow by detecting the decay of isotope tracers. These tracers are available for amino acids, water, lactate, and glucose, to name a few substances important in exercise metabolism. In exercise physiology, PET is most commonly used to detect glucose metabolism using a fluoridated analog of glucose. When combined with computed tomography or magnetic resonance imaging, this technique can be used to evaluate both the amount and anatomical location of active glucose metabolism ( Rudroff et al., 2015 ). Another advantage of PET is that it can be used to monitor the amount and spatial distribution of muscle activity that occurred during various exercise conditions in a free-living environment ( Rudroff et al., 2015 ).

Advances in wearable technologies have greatly expanded the capabilities of exercise scientists to understand human metabolism in health and disease. By the mid-1990s, exercise physiologists were using physical activity monitors to objectively determine the physical activity behaviors of adults and children ( Matthews & Freedson, 1995 ; Melanson et al., 1996 ). What started as bulky monitors are now sleek and sophisticated research grade and consumer devices that can be worn on the body or integrated into our everyday devices, like watches and cell phones. This allows exercise physiologists to quantify type, duration, and intensity of activity that occurs outside of the lab in a free-living setting. This information about physical activity behaviors compliments and enhances the understanding of physiological responses to exercise by providing context about participants’ physical activity and sedentary behaviors ( Wright et al., 2017 ).

In addition to providing extensive data about physical activity, there are wearable technologies that are designed to sample sweat, tears, saliva, and interstitial fluid to monitor a variety of metabolic analytes, including lactate, glucose, sodium, potassium, and hydrogen ions ( Gao et al., 2018 ). These technologies can be applied to understanding the physiological response to exercise in wartime fighters, firefighters, athletes, and clinical populations. Perhaps the most utilized wearable technology for the monitoring of metabolites is the continuous glucose monitor. Continuous glucose monitors measure glucose in the interstitial fluid at regular intervals and transmit the information to a receiver for storage and analysis. An advantage of continuous glucose monitors is that researchers can use them to understand glucose metabolism in free-living situations during the late postexercise and nocturnal periods. Continuous glucose monitoring has also been used in athletes with and without diabetes to determine metabolic responses to exercise and carbohydrate requirements during racing ( Ishihara et al., 2020 ; Ortega et al., 2020 ). In the future, we expect that continuous glucose monitoring will continue to be important in understanding the glucose response to exercise in people with and without diabetes. Future glucose sensors will be paired with sensors for other analytes to provide an even richer understanding of the metabolic effects of physical activity. This information will be useful for researchers, coaches, and medical professionals to aid in the optimization of performance and health for exercising people.

Genetic Advances

The fields of cellular and molecular biology have naturally integrated with exercise physiology in the investigation of the mechanisms of physiological phenomena. In the late 1980s, the Federation of American Societies for Experimental Biology held a symposium to introduce molecular biology to physiologists ( Chien & Gargus, 1987 ); and in 1988, Booth published the first review highlighting the importance of molecular biology specifically to exercise physiologists ( Booth, 1988 ). Since then, exercise physiologists have utilized genomic, epigenetic, transcriptomic, and metabolomic approaches as they have become available to examine the mechanisms of physiological responses to exercise, as well as the mechanisms for exercise-induced health benefits ( Gomes et al., 2020 ; Neufer et al., 2015 ).

Genomics is the study of the genome, which encompasses all genes encoded by deoxyribonucleic acid. Exercise physiologists have utilized genomics tools to understand the genetic underpinnings of many facets of exercise, including the genetic basis of physical activity behavior, athletic performance, cardiorespiratory fitness, body composition, metabolism, and hemodynamic traits ( Sarzynski et al., 2016 ). Genome-wide association studies are one of the most common genomic tools that exercise physiologists have utilized. Using Genome-wide association studies, genetic variants can be identified and associated with a specific outcome, such as a propensity to engage in leisure-time physical activity ( Aasdahl et al., 2021 ) or the trainability of cardiorespiratory fitness ( Williams et al., 2017 ). Genomic data provide key information about the expression of protein-encoding genes that transduce the physiological effects of exercise, but genomics does not provide a complete picture of the molecular mechanisms at play in the cell.

Following the boom of genomics research in the field of exercise physiology in the early 2000s and 2010s, epigenetic research has more recently exploded to gain a more detailed view of the molecular basis of exercise physiology. Epigenetics provide information about the transcriptional regulation of genes, including modifications that control and alter gene expression without changing the underlying deoxyribonucleic acid ( McGee & Hargreaves, 2019 ). In this way, exercise physiologists can use epigenetics to understand not only a predisposition to a certain attribute, as with genetics, but also can assess an epigenetic response to a stimulus, such as exercise. In the field of exercise physiology, there is interest in the epigenetic regulation of skeletal muscle adaptations to exercise, metabolism, and inflammatory processes ( Jacques et al. 2019 ), with much left to explore.

Transcriptomics and metabolomics are even newer fields than epigenomics, and they stand to further extend our knowledge of the molecular underpinnings of exercise physiology. Transcriptomics is the study of ribonucleic acid products in the cell. Transcriptomic signatures may be used by exercise physiologists to identify novel cell populations that are important for exercise adaptations in health and disease ( Cho & Doles, 2017 ). On the other hand, metabolomics examines how the genome, epigenome, and transcriptome interact to produce the downstream metabolites that affect physiological responses to exercise. This branch of “omics” uses a systematic approach to quantify all metabolites in a sample, including lipids, carbohydrates, nucleotides, and small molecules. For example, exercise physiologists can utilize metabolomics to elucidate the time course of metabolic responses to exercise, which has public health implications for understanding the different health outcomes associated with lifelong exercise compared with acute training programs ( Gomes et al., 2020 ; Kelly et al., 2020 ). Transcriptomics and metabolomics will likely remain hot topics in exercise physiology, especially as a means to identify cells and biomarkers that might characterize individual responses to training, nutrition, or timing of exercise.

Analytical Approaches

As technological advances have pushed the field of exercise physiology, analytical advances have also been important to generating and interpreting new knowledge. Increases in computing power have made modeling physiological phenomena a useful tool to exercise physiologists. Computational modeling provides exercise physiologists with an alternative to human and animal studies while also generating unique information that experimental research alone cannot produce. Importantly, models also serve to guide hypothesis-generation for future experimental research. There are endless applications for computational modeling in exercise physiology. For example, computational models can be used to understand the mechanisms of muscle fatigue in aging ( Callahan et al., 2016 ), muscle energetics during locomotion ( Umberger & Rubenson, 2011 ), and injury risk in various types of athletes ( Hadid et al., 2018 ).

Statistical analyses also have advanced our ability to understand the totality of research in a given area of investigation. The sheer volume of exercise physiology publications has necessitated the need for rigorous, quantitative synthesis of research results to supplement narrative research reviews. Meta-analysis in exercise physiology started to gain momentum in the early 1990s and is widely utilized today. In one of the earliest meta-analyses in the field of exercise physiology, Lokey et al. (1991) evaluated the effect of physical activity on pregnancy outcomes. At the time, the American College of Obstetricians and Gynecologists recommended that pregnant women engage in at least 3 days per week of exercise at a heart rate of up to 140 beats per minute for <15 min. Narrative reviews had thus far been unable to resolve whether additional intensity, duration, and modes of exercise were also safe during pregnancy. The results of the meta-analysis indicated that longer exercise bouts as well as modes of exercise including jogging and weight bearing were not unsafe for pregnant women ( Lokey et al., 1991 ). While exercise during pregnancy is currently widely accepted as safe, meta-analysis is still being used to understand how exercise affects pregnancy complications, including gestational diabetes ( Ming et al., 2018 ). Meta-analyses have also shown that exercise reduces the rates of falls in older adults ( Sherrington et al., 2019 ), may be useful for the treatment of depression ( Stanton & Reaburn, 2014 ), and can improve physical functioning and fatigue symptoms in breast cancer patients ( Juvet et al., 2017 ).

New Knowledge

A complete listing of the key new concepts in exercise physiology is beyond the scope of this review, but several exciting areas of research are highlighted in this section. Fortunately, the creation of the internet and associated search engines, databases, and electronicallyavailable primary research reports and materials allow us to explore these and other topics extensively.

In 1977, M. Joan Dawson and colleagues reported the first use of MRS for the study of muscle bioenergetics—the production and use of ATP to power muscular contractions—during contractions in excised whole frog and toad muscles ( Dawson et al., 1977 ). Shortly after that, research groups from the University of Pennsylvania and Oxford University became the first to use noninvasive MRS techniques to study cellular bioenergetics in vivo in resting and exercising human muscle ( Chance et al., 1980 ; Chance et al., 1981 ), thus laying the groundwork for the rich explorations into bioenergetics that have continued since that time. In the late 1980s, Ron Meyer and others ( Arnold et al., 1984 ; Meyer, 1988 ) built on the work of Doris Taylor et al. (1983) to develop the phosphocreatine recovery protocol as a robust means of quantifying muscle oxidative capacity in vivo. This approach has been used to determine the effects of exercise training, aging, and disease on muscle mitochondrial function in a variety of muscle groups. The use of MRS to quantify ATP flux directly from the creatine kinase reaction, as well as through glycolysis and oxidative phosphorylation ( Boska, 1991 ), have led to a number of discoveries related to the interactions between oxidative and nonoxidative energy production under various conditions ( Lanza et al., 2006 ). The role of glycogen stores and perfusion have also been used to answer important questions about substrate-level metabolism and the impact of oxygen delivery on muscle function ( Brillault-Salvat et al., 1997 ).

Also beginning in the 1980s, George Brooks and colleagues began a relentless pursuit of clarifying the details of lactate metabolism in resting ( Donovan & Brooks, 1983 ) and exercising ( Stanley et al., 1988 ) skeletal muscle, demonstrating in the process that lactate production is indeed driven not by anoxia in muscle cells, but rather in response to increases in energy demand that are met through higher glycolytic flux. This work led to Brooks’ development of the lactate shuttle hypothesis which posits that lactate is shuttled from sites of production in the cytosol of working muscle to other regions within the cell and other tissues (e.g., heart, brain, liver, skeletal muscle) that then use that lactate for energy and gluconeogenesis ( Brooks, 1991 ). This concept has been important to interpreting the “anaerobic” or “lactate” threshold in that the shuttling and use of lactate as fuel in various tissues renders invalid the concept that the lactate threshold (rapid increase in the accumulation of blood lactate as the rate of production exceeds the clearance rate) occurs due to insufficient oxygen in exercising muscle ( Poole et al., 2021 ). The on-going interest in this topic remains clear in the literature.

The 1990s saw an increased interest in understanding the mechanisms of muscle fatigue, defined as the fall of force in response to muscular contractions. Building on the work of Brenda Bigland-Ritchie and others in the 1980s ( Bigland-Ritchie, 1981 ; Cooke & Pate, 1985 ; Edwards et al., 1977 ), investigators explored the neural ( Enoka & Stuart, 1992 ) and metabolic ( Miller et al., 1987 ) bases of muscle fatigue in vivo. Careful work at the cellular level provided insight about the intracellular sources of muscle fatigue, including the deleterious effects of changes in calcium kinetics, and accumulation of inorganic phosphate and hydrogen ions on contractile function on muscle force and velocity ( Lännergren & Westerblad, 1991 ). Subsequently, the roles of inorganic phosphate and acidosis on contractile failure and fatigue were clearly demonstrated at the molecular ( Debold et al., 2008 ), cellular ( Fitts, 2008 ; Knuth et al., 2006 ) and in vivo , whole-muscle levels ( Lanza et al., 2006 ).

Another new concept that emerged in the 1990s and was expanded upon in the 2000s was based on the demonstration of substantial positive adaptations to aerobic energy metabolism in response to “high-intensity interval training” ( Perry et al., 2008 ; Sperlich et al., 2010 ). Until that time, it was generally considered that “aerobic” adaptations such as increased capillary and mitochondrial density, maximal rates of oxidative phosphorylation, and maximal oxygen consumption during whole-body exercise required months of long-duration (several approximately 60-min exercise bouts per week) “endurance” training. This approach was sometimes termed “long, slow distance” training. However, studies by several investigators showed that, in fact, substantial modifications to the structures that support oxidative metabolism, as well as peak values of oxygen consumption, can be made with 6–8 short (approximately 30 s), maximal bursts of exercise repeated following brief (approximately 4 min) periods of recovery. Remarkably, significant improvements in these key variables could be elicited in as little as 6 training sessions carried out over 2 weeks ( Larsen et al., 2014 ). The results of these studies have sparked a revolution in training programs for people of all ages whose goals range from general fitness to high-level athletic performance.

During this same time, an appreciation by exercise physiologists developed for the important role of bone metabolism in health and the role of exercise in maintaining bone mass. At the time, it was well understood that bone remodeling followed the dictates of Wolffe’s Law, that is, that bone density and strength will adapt based on the loads imposed on it, in much the same way that muscles do. However, additional factors emerged as important to changes in bone health. The effects of hormonal status, energy balance and type of exercise training, in populations ranging from postmenopausal women to highly-trained male cyclists, were the focus of a series of studies by Wendy Kohrt and colleagues (e.g., Barry & Kohrt, 2007 ; Gozansky et al., 2005 ). Overall, physical inactivity, menopause and older age, and negative energy balance can all be detrimental to bone health. Nontraditional forms of exercise or loading interventions have also been examined. T’ai Chi is a form of exercise that may have beneficial effects on bone physiology ( Zhou et al., 2021 ), although the most efficacious protocols have not yet been determined. Likewise, the use of whole-body vibration as a treatment for osteoporosis also seems promising ( Verschueren et al., 2003 ). On-going research in the area of exercise and optimal bone health will be an important focus in exercise physiology in the years to come.

In the 2000s, the term “metabolic flexibility” was introduced to describe the interplay between fat and carbohydrate as substrates for energy metabolism in response to fasting or feeding ( Goodpaster & Kelley, 2002 ; Hood et al., 2006 ). Exercise physiologists have used exercise as a probe for understanding the etiology and reversibility of metabolic inflexibility, which is a problem most evident in the context of obesity and insulin resistance. The associations between metabolic inflexibility—generally measured as insulin resistance or impaired fatty acid metabolism—and mitochondrial function have been established in a number of studies ( Dubé et al., 2014 ; Stephenson & Hawley, 2014 ). Notably, Meex et al. (2010) showed that exercise training can reverse this problem in part through an improvement in mitochondrial capacity.

Finally, a remarkable new area of research opening up in the last 10 years is focused on understanding how the gut microbiome influences disease, and the mechanisms by which exercise might modulate these effects ( O’Sullivan et al., 2015 ). In addition to innovative work in humans (cf. Cook et al., 2016 ), studies using animal models are addressing these questions, as well. For example, recent research paradigms have imposed changes in the microbiome that appear to reverse the impaired vascular function typically associated with aging ( Brunt et al., 2019 ). A report by Welly et al. (2016) evaluated how exercise compared with negative energy balance in improving the gut microbiome and markers of metabolic health in obesity prone rats, and found exercise to have significant positive effects. Certainly, this will be an area of intense investigation in the future.

These are but a glimpse into some of the exciting research that has taken place in exercise physiology over the past 40 years. No doubt the breadth and depth of knowledge in this field will continue to grow as investigators around the world probe further into understanding the mechanisms and limitations of maximal human performance and optimal health. The next section highlights a few areas of scientific inquiry that are certain to provide continued opportunities for exploration by exercise physiologists.

Current and Future Opportunities

A survey of the contributions that researchers in exercise physiology have made in the past 40 years reveals the extent to which this field has been integrated with other STEM and health disciplines. This recognition of and respect for exercise physiology by researchers in fields well beyond its own are a testament to its impact on science and public health. Indeed, as various disciplines become increasingly interwoven, it will be important to ensure that exercise physiology retains recognition as a field of endeavor in its own right! A few of the areas that we can expect to have continued opportunities for important discoveries in the future are highlighted below.

Perhaps one of the best examples of the extent to which exercise physiology has been assimilated into the health sciences is the concept of “Exercise is Medicine,” a term that appears to have first been introduced into the scientific literature by Douglas Hoffman (1993) . The basic concept is that physical activity and exercise promote beneficial physiological adaptations that support health and well-being and, as such, can be prescribed to mitigate inactivity-related disease. In this way, following appropriate assessment, the core principles of exercise physiology are used to design therapeutic treatments, in much the same way as pharmaceutical interventions are typically used. A seminal study that paved the way for this concept was that reported by Steven Blair et al. (1989) , which identified the association between low fitness level and high mortality, particularly in men. A very active period of research related to exercise as an intervention for good health has followed ( Kraus et al., 2019 ; Nicolucci et al., 2011 ). In 2007, the “Exercise is Medicine” concept was formalized into a program jointly sponsored by the American College of Sports Medicine and the American Medical Association. This program has grown to become a Global Health Initiative that endorses the approach of using evidence-based information to create personalized physical activity and exercise prescriptions to optimize individual and population health. Clearly, the importance of fitness and physical activity in the promotion of good health has been a major contribution of exercise physiology over the past 40 years.

Large-scale longitudinal studies designed to understand or mitigate societal problems such as aging-related declines in physical function ( Ferrucci, 2008 ; Pahor et al., 2014 ) or the impact of lifestyle interventions like exercise on the management and progression of Type 2 diabetes ( Johansen et al., 2017 ) are but two examples of the importance of understanding on a population scale what the interactions are between disease and exercise or physical inactivity. As the critical variables in these associations are identified, smaller-scale mechanistic studies can be designed to pursue a deeper understanding of the problem and develop evidence-based interventions to correct them. In addition, while these large studies are generally associative and therefore cannot assign causality, technological advances are allowing mechanistic measures to be added to these studies over time. In combination with new methods for managing and interpreting “big data,” opportunities for high-impact discoveries from these types of studies are expected to grow rapidly in the coming years.

Exercise physiologists are typically part of a large team of investigators in projects such those mentioned above, which might also include clinicians, epidemiologists, statisticians, and data management experts. In fact, a parallel development in recent years is the concept of applying “Team Science” approaches to research, which recognize that the potential contributions of these large, interdisciplinary projects to generating new scientific knowledge is far more than the sum of its parts ( Cooke & Hilton, 2015 ). One principle of Team Science is that laboratories both large and small can combine to produce exciting new work, as can teamwork between laboratories focused on very different aspects or scales of a given problem ( Bennett & Gadlin, 2012 ). It will be exciting to see where this powerful approach takes the field of exercise physiology in the future.

Another acknowledgment of the important role of exercise physiology in human health and performance is an initiative launched in 2016 by the NIH titled Molecular Transducers of Physical Activity in Humans ( NIH, 2020 ). In many ways, this initiative was the culmination of work by Frank Booth and others who worked tirelessly in the early 2000’s to promote the need for research designed to understand and apply the molecular basis for how physical inactivity exacerbates disease in humans ( Booth et al., 2000 ). The goal of this innovative and ambitious project, which is supported by NIH’s Common Fund and managed by a consortium of institutions and investigators, is to identify the precise mechanisms by which physical activity and exercise evoke their positive effects on human health ( NIH, 2020 ; Neufer et al., 2015 ). This is a prospective, large-scale intervention study in humans in which participants complete a 12 week, supervised exercise training study ( Sanford et al., 2020 ). Parallel studies are being performed in animal models to investigate mechanisms that are not feasible to obtain in humans. Approximately 2,600 males and females of all ages, races, and ethnic backgrounds are being studied. This is the largest and most expensive exercise training program to date that will examine basic mechanisms of physiological adaptations and their associated impact on physical function and health.

An exciting opportunity that will continue to grow in coming years is that of investigations related to the exercise physiology of microgravity and long-duration space flight. The goal of landing people on Mars as well as the expansion of space exploration into the private sector and by many countries means that greater numbers of people are being exposed to prolonged periods of time in zero gravity. Understanding the consequences of these missions on various human physiological systems—including those systems that support exercise—will be critical to ensuring the health of future astronauts. It will be exciting to follow this line of research as it builds upon the classic early studies in this area, which began in the mid-1960s. In addition to studies of the impact of space flight on humans ( Grigoriev, 1983 ) and small animals ( Mondon et al., 1983 ), bedrest has been used as a surrogate for the unloading associated with microgravity, thus enabling a wider range of studies than are possible only with spaceflight ( Greenleaf, 1989 ; Katkovsky & Pomyotov, 1976 ). Collectively, profound effects on cardiovascular, respiratory, neuromuscular, and bone physiology have been observed in response to zero or micro-gravity ( Edgerton & Roy, 1994 ). Exercise countermeasures to the deleterious effects of space were introduced in the 1970s ( Klein et al., 1977 ). The on-going challenge will be to develop countermeasures that are feasible and effective in preventing the negative effects of prolonged missions in space. As with other aspects of technological advances driven by space exploration, we can expect the new knowledge generated about exercise physiology in zero- and micro-gravity to have carry-over effects into the health and performance capabilities of the general population.

Additional on-going and emerging opportunities for scientific investigation involving exercise physiology include understanding the multiple roles (e.g., energy production, signaling) of mitochondria in supporting health and performance ( Glancy et al., 2015 ), understanding how aging affects the neuromuscular system ( Hepple & Rice, 2016 ), determining the mechanisms by which exercise supports brain health and function ( Tyndall et al., 2018 ), the interplay between engineered solutions to limb loss and enhancing mobility performance and resistance to fatigue ( Grimmer et al., 2019 ), and the limits of human performance in extreme conditions ( Burnley & Jones, 2018 ; Sullivan-Kwantes et al., 2020 ). Fundamental questions related to how the sex hormones influence and are influenced by exercise performance will be important to address in order to optimize performance and health throughout the lifespan in all humans.

Over the past 40 years, concepts and approaches in exercise physiology have become woven into the larger fabric of scientific investigation into human health and performance, from molecules to populations. The investigations by exercise physiologists drive the development of new tools and techniques to answer increasingly novel and impactful research questions. Exercise physiologists also embrace the newly developed methodologies from other biomedical disciplines. Technological advances will continue to be key for exercise physiologists in their pursuit to uncover a deeper understanding of the physiological basis of human health, performance, and disease.

The evolution of the field has moved it toward a position of centrality in the natural sciences. Notably, however, this centrality means there is also risk of a loss of identity as these topics are absorbed into other disciplines. This risk can be mitigated by the continued rigorous training of exercise physiologists in our colleges and universities. A solid foundation in biochemistry, physics, molecular biology, and computer sciences will be increasingly important for future exercise physiologists who want to contribute to generating new knowledge about how humans and other animals respond to acute and chronic exercise. Likewise, training students to be critical components of scientific teams will allow them to flourish in the realm of integrative research and thought. There is clearly a need for research and application of holistic, physiological studies that can place “basic” studies in the context of the entire organism and how it moves in its environment. The future is bright, and the opportunities are immense for exercise physiologists in the next 40 years.

Acknowledgment

Financial support was provided by NIH R01 AG058607 (K.L. Hayes).

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• Research article
• Open access
• Published: 16 November 2020

Exercise/physical activity and health outcomes: an overview of Cochrane systematic reviews

• Pawel Posadzki 1 , 2 ,
• Dawid Pieper   ORCID: orcid.org/0000-0002-0715-5182 3 ,
• Ram Bajpai 4 ,
• Hubert Makaruk 5 ,
• Nadja Könsgen 3 ,
• Annika Lena Neuhaus 3 &
• Monika Semwal 6  

BMC Public Health volume  20 , Article number:  1724 ( 2020 ) Cite this article

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Sedentary lifestyle is a major risk factor for noncommunicable diseases such as cardiovascular diseases, cancer and diabetes. It has been estimated that approximately 3.2 million deaths each year are attributable to insufficient levels of physical activity. We evaluated the available evidence from Cochrane systematic reviews (CSRs) on the effectiveness of exercise/physical activity for various health outcomes.

Overview and meta-analysis. The Cochrane Library was searched from 01.01.2000 to issue 1, 2019. No language restrictions were imposed. Only CSRs of randomised controlled trials (RCTs) were included. Both healthy individuals, those at risk of a disease, and medically compromised patients of any age and gender were eligible. We evaluated any type of exercise or physical activity interventions; against any types of controls; and measuring any type of health-related outcome measures. The AMSTAR-2 tool for assessing the methodological quality of the included studies was utilised.

Hundred and fifty CSRs met the inclusion criteria. There were 54 different conditions. Majority of CSRs were of high methodological quality. Hundred and thirty CSRs employed meta-analytic techniques and 20 did not. Limitations for studies were the most common reasons for downgrading the quality of the evidence. Based on 10 CSRs and 187 RCTs with 27,671 participants, there was a 13% reduction in mortality rates risk ratio (RR) 0.87 [95% confidence intervals (CI) 0.78 to 0.96]; I 2  = 26.6%, [prediction interval (PI) 0.70, 1.07], median effect size (MES) = 0.93 [interquartile range (IQR) 0.81, 1.00]. Data from 15 CSRs and 408 RCTs with 32,984 participants showed a small improvement in quality of life (QOL) standardised mean difference (SMD) 0.18 [95% CI 0.08, 0.28]; I 2  = 74.3%; PI -0.18, 0.53], MES = 0.20 [IQR 0.07, 0.39]. Subgroup analyses by the type of condition showed that the magnitude of effect size was the largest among patients with mental health conditions.

There is a plethora of CSRs evaluating the effectiveness of physical activity/exercise. The evidence suggests that physical activity/exercise reduces mortality rates and improves QOL with minimal or no safety concerns.

Trial registration

Registered in PROSPERO ( CRD42019120295 ) on 10th January 2019.

Peer Review reports

The World Health Organization (WHO) defines physical activity “as any bodily movement produced by skeletal muscles that requires energy expenditure” [ 1 ]. Therefore, physical activity is not only limited to sports but also includes walking, running, swimming, gymnastics, dance, ball games, and martial arts, for example. In the last years, several organizations have published or updated their guidelines on physical activity. For example, the Physical Activity Guidelines for Americans, 2nd edition, provides information and guidance on the types and amounts of physical activity that provide substantial health benefits [ 2 ]. The evidence about the health benefits of regular physical activity is well established and so are the risks of sedentary behaviour [ 2 ]. Exercise is dose dependent, meaning that people who achieve cumulative levels several times higher than the current recommended minimum level have a significant reduction in the risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events [ 3 ]. Benefits of physical activity have been reported for numerous outcomes such as mortality [ 4 , 5 ], cognitive and physical decline [ 5 , 6 , 7 ], glycaemic control [ 8 , 9 ], pain and disability [ 10 , 11 ], muscle and bone strength [ 12 ], depressive symptoms [ 13 ], and functional mobility and well-being [ 14 , 15 ]. Overall benefits of exercise apply to all bodily systems including immunological [ 16 ], musculoskeletal [ 17 ], respiratory [ 18 ], and hormonal [ 19 ]. Specifically for the cardiovascular system, exercise increases fatty acid oxidation, cardiac output, vascular smooth muscle relaxation, endothelial nitric oxide synthase expression and nitric oxide availability, improves plasma lipid profiles [ 15 ] while at the same time reducing resting heart rate and blood pressure, aortic valve calcification, and vascular resistance [ 20 ].

However, the degree of all the above-highlighted benefits vary considerably depending on individual fitness levels, types of populations, age groups and the intensity of different physical activities/exercises [ 21 ]. The majority of guidelines in different countries recommend a goal of 150 min/week of moderate-intensity aerobic physical activity (or equivalent of 75 min of vigorous-intensity) [ 22 ] with differences for cardiovascular disease [ 23 ] or obesity prevention [ 24 ] or age groups [ 25 ].

There is a plethora of systematic reviews published by the Cochrane Library critically evaluating the effectiveness of physical activity/exercise for various health outcomes. Cochrane systematic reviews (CSRs) are known to be a source of high-quality evidence. Thus, it is not only timely but relevant to evaluate the current knowledge, and determine the quality of the evidence-base, and the magnitude of the effect sizes given the negative lifestyle changes and rising physical inactivity-related burden of diseases. This overview will identify the breadth and scope to which CSRs have appraised the evidence for exercise on health outcomes; and this will help in directing future guidelines and identifying current gaps in the literature.

The objectives of this research were to a. answer the following research questions: in children, adolescents and adults (both healthy and medically compromised) what are the effects (and adverse effects) of exercise/physical activity in improving various health outcomes (e.g., pain, function, quality of life) reported in CSRs; b. estimate the magnitude of the effects by pooling the results quantitatively; c. evaluate the strength and quality of the existing evidence; and d. create recommendations for future researchers, patients, and clinicians.

Our overview was registered with PROSPERO (CRD42019120295) on 10th January 2019. The Cochrane Handbook for Systematic Reviews of interventions and Preferred Reporting Items for Overviews of Reviews were adhered to while writing and reporting this overview [ 26 , 27 ].

Search strategy and selection criteria

We followed the practical guidance for conducting overviews of reviews of health care interventions [ 28 ] and searched the Cochrane Database of Systematic Reviews (CDSR), 2019, Issue 1, on the Cochrane Library for relevant papers using the search strategy: (health) and (exercise or activity or physical). The decision to seek CSRs only was based on three main aspects. First, high quality (CSRs are considered to be the ‘gold methodological standard’) [ 29 , 30 , 31 ]. Second, data saturation (enough high-quality evidence to reach meaningful conclusions based on CSRs only). Third, including non-CSRs would have heavily increased the issue of overlapping reviews (also affecting data robustness and credibility of conclusions). One reviewer carried out the searches. The study screening and selection process were performed independently by two reviewers. We imported all identified references into reference manager software EndNote (X8). Any disagreements were resolved by discussion between the authors with third overview author acting as an arbiter, if necessary.

We included CSRs of randomised controlled trials (RCTs) involving both healthy individuals and medically compromised patients of any age and gender. Only CSRs assessing exercise or physical activity as a stand-alone intervention were included. This included interventions that could initially be taught by a professional or involve ongoing supervision (the WHO definition). Complex interventions e.g., assessing both exercise/physical activity and behavioural changes were excluded if the health effects of the interventions could not have been attributed to exercise distinctly.

Any types of controls were admissible. Reviews evaluating any type of health-related outcome measures were deemed eligible. However, we excluded protocols or/and CSRs that have been withdrawn from the Cochrane Library as well as reviews with no included studies.

Data analysis

Three authors (HM, ALN, NK) independently extracted relevant information from all the included studies using a custom-made data collection form. The methodological quality of SRs included was independently evaluated by same reviewers using the AMSTAR-2 tool [ 32 ]. Any disagreements on data extraction or CSR quality were resolved by discussion. The entire dataset was validated by three authors (PP, MS, DP) and any discrepant opinions were settled through discussions.

The results of CSRs are presented in a narrative fashion using descriptive tables. Where feasible, we presented outcome measures across CSRs. Data from the subset of homogeneous outcomes were pooled quantitatively using the approach previously described by Bellou et al. and Posadzki et al. [ 33 , 34 ]. For mortality and quality of life (QOL) outcomes, the number of participants and RCTs involved in the meta-analysis, summary effect sizes [with 95% confidence intervals (CI)] using random-effects model were calculated. For binary outcomes, we considered relative risks (RRs) as surrogate measures of the corresponding odds ratio (OR) or risk ratio/hazard ratio (HR). To stabilise the variance and normalise the distributions, we transformed RRs into their natural logarithms before pooling the data (a variation was allowed, however, it did not change interpretation of results) [ 35 ]. The standard error (SE) of the natural logarithm of RR was derived from the corresponding CIs, which was either provided in the study or calculated with standard formulas [ 36 ]. Binary outcomes reported as risk difference (RD) were also meta-analysed if two more estimates were available. For continuous outcomes, we only meta-analysed estimates that were available as standardised mean difference (SMD), and estimates reported with mean differences (MD) for QOL were presented separately in a supplementary Table  9 . To estimate the overall effect size, each study was weighted by the reciprocal of its variance. Random-effects meta-analysis, using DerSimonian and Laird method [ 37 ] was applied to individual CSR estimates to obtain a pooled summary estimate for RR or SMD. The 95% prediction interval (PI) was also calculated (where ≥3 studies were available), which further accounts for between-study heterogeneity and estimates the uncertainty around the effect that would be anticipated in a new study evaluating that same association. I -squared statistic was used to measure between study heterogeneity; and its various thresholds (small, substantial and considerable) were interpreted considering the size and direction of effects and the p -value from Cochran’s Q test ( p  < 0.1 considered as significance) [ 38 ]. Wherever possible, we calculated the median effect size (with interquartile range [IQR]) of each CSR to interpret the direction and magnitude of the effect size. Sub-group analyses are planned for type and intensity of the intervention; age group; gender; type and/or severity of the condition, risk of bias in RCTs, and the overall quality of the evidence (Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria). To assess overlap we calculated the corrected covered area (CCA) [ 39 ]. All statistical analyses were conducted on Stata statistical software version 15.2 (StataCorp LLC, College Station, Texas, USA).

The searches generated 280 potentially relevant CRSs. After removing of duplicates and screening, a total of 150 CSRs met our eligibility criteria [ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 ] (Fig.  1 ). Reviews were published between September 2002 and December 2018. A total of 130 CSRs employed meta-analytic techniques and 20 did not. The total number of RCTs in the CSRs amounted to 2888; with 485,110 participants (mean = 3234, SD = 13,272). The age ranged from 3 to 87 and gender distribution was inestimable. The main characteristics of included reviews are summarised in supplementary Table  1 . Supplementary Table  2 summarises the effects of physical activity/exercise on health outcomes. Conclusions from CSRs are listed in supplementary Table  3 . Adverse effects are listed in supplementary Table  4 . Supplementary Table  5 presents summary of withdrawals/non-adherence. The methodological quality of CSRs is presented in supplementary Table  6 . Supplementary Table  7 summarises studies assessed at low risk of bias (by the authors of CSRs). GRADE-ings of the review’s main comparison are listed in supplementary Table  8 .

Study selection process

There were 54 separate populations/conditions, considerable range of interventions and comparators, co-interventions, and outcome measures. For detailed description of interventions, please refer to the supplementary tables . Most commonly measured outcomes were - function 112 (75%), QOL 83 (55%), AEs 70 (47%), pain 41 (27%), mortality 28 (19%), strength 30 (20%), costs 47 (31%), disability 14 (9%), and mental health in 35 (23%) CSRs.

There was a 13% reduction in mortality rates risk ratio (RR) 0.87 [95% CI 0.78 to 0.96]; I 2  = 26.6%, [PI 0.70, 1.07], median effect size (MES) = 0.93 [interquartile range (IQR) 0.81, 1.00]; 10 CSRs, 187 RCTs, 27,671 participants) following exercise when compared with various controls (Table 1 ). This reduction was smaller in ‘other groups’ of patients when compared to cardiovascular diseases (CVD) patients - RR 0.97 [95% CI 0.65, 1.45] versus 0.85 [0.76, 0.96] respectively. The effects of exercise were not intensity or frequency dependent. Sessions more than 3 times per week exerted a smaller reduction in mortality as compared with sessions of less than 3 times per week RR 0.87 [95% CI 0.78, 0.98] versus 0.63 [0.39, 1.00]. Subgroup analyses by risk of bias (ROB) in RCTs showed that RCTs at low ROB exerted smaller reductions in mortality when compared to RCTs at an unclear or high ROB, RR 0.90 [95% CI 0.78, 1.02] versus 0.72 [0.42, 1.22] versus 0.86 [0.69, 1.06] respectively. CSRs with moderate quality of evidence (GRADE), showed slightly smaller reductions in mortality when compared with CSRs that relied on very low to low quality evidence RR 0.88 [95% CI 0.79, 0.98] versus 0.70 [0.47, 1.04].

Exercise also showed an improvement in QOL, standardised mean difference (SMD) 0.18 [95% CI 0.08, 0.28]; I 2  = 74.3%; PI -0.18, 0.53], MES = 0.20 [IQR 0.07, 0.39]; 15 CSRs, 408 RCTs, 32,984 participants) when compared with various controls (Table 2 ). These improvements were greater observed for health related QOL when compared to overall QOL SMD 0.30 [95% CI 0.21, 0.39] vs 0.06 [− 0.08, 0.20] respectively. Again, the effects of exercise were duration and frequency dependent. For instance, sessions of more than 90 mins exerted a greater improvement in QOL as compared with sessions up to 90 min SMD 0.24 [95% CI 0.11, 0.37] versus 0.22 [− 0.30, 0.74]. Subgroup analyses by the type of condition showed that the magnitude of effect was the largest among patients with mental health conditions, followed by CVD and cancer. Physical activity exerted negative effects on QOL in patients with respiratory conditions (2 CSRs, 20 RCTs with 601 patients; SMD -0.97 [95% CI -1.43, 0.57]; I 2  = 87.8%; MES = -0.46 [IQR-0.97, 0.05]). Subgroup analyses by risk of bias (ROB) in RCTs showed that RCTs at low or unclear ROB exerted greater improvements in QOL when compared to RCTs at a high ROB SMD 0.21 [95% CI 0.10, 0.31] versus 0.17 [0.03, 0.31]. Analogically, CSRs with moderate to high quality of evidence showed slightly greater improvements in QOL when compared with CSRs that relied on very low to low quality evidence SMD 0.19 [95% CI 0.05, 0.33] versus 0.15 [− 0.02, 0.32]. Please also see supplementary Table  9 more studies reporting QOL outcomes as mean difference (not quantitatively synthesised herein).

Adverse events (AEs) were reported in 100 (66.6%) CSRs; and not reported in 50 (33.3%). The number of AEs ranged from 0 to 84 in the CSRs. The number was inestimable in 83 (55.3%) CSRs. Ten (6.6%) reported no occurrence of AEs. Mild AEs were reported in 28 (18.6%) CSRs, moderate in 9 (6%) and serious/severe in 20 (13.3%). There were 10 deaths and in majority of instances, the causality was not attributed to exercise. For this outcome, we were unable to pool the data as effect sizes were too heterogeneous (Table 3 ).

In 38 CSRs, the total number of trials reporting withdrawals/non-adherence was inestimable. There were different ways of reporting it such as adherence or attrition (high in 23.3% of CSRs) as well as various effect estimates including %, range, total numbers, MD, RD, RR, OR, mean and SD. The overall pooled estimates are reported in Table 3 .

Of all 16 domains of the AMSTAR-2 tool, 1876 (78.1%) scored ‘yes’, 76 (3.1%) ‘partial yes’; 375 (15.6%) ‘no’, and ‘not applicable’ in 25 (1%) CSRs. Ninety-six CSRs (64%) were scored as ‘no’ on reporting sources of funding for the studies followed by 88 (58.6%) failing to explain the selection of study designs for inclusion. One CSR (0.6%) each were judged as ‘no’ for reporting any potential sources of conflict of interest, including any funding for conducting the review as well for performing study selection in duplicate.

In 102 (68%) CSRs, there was predominantly a high risk of bias in RCTs. In 9 (6%) studies, this was reported as a range, e.g., low or unclear or low to high. Two CSRs used different terminology i.e., moderate methodological quality; and the risk of bias was inestimable in one CSR. Sixteen (10.6%) CSRs did not identify any studies (RCTs) at low risk of random sequence generation, 28 (18.6%) allocation concealment, 28 (18.6%) performance bias, 84 (54%) detection bias, 35 (23.3%) attrition bias, 18 (12%) reporting bias, and 29 (19.3%) other bias.

In 114 (76%) CSRs, limitation of studies was the main reason for downgrading the quality of the evidence followed by imprecision in 98 (65.3%) and inconsistency in 68 (45.3%). Publication bias was the least frequent reason for downgrading in 26 (17.3%) CSRs. Ninety-one (60.7%) CSRs reached equivocal conclusions, 49 (32.7%) reviews reached positive conclusions and 10 (6.7%) reached negative conclusions (as judged by the authors of CSRs).

In this systematic review of CSRs, we found a large body of evidence on the beneficial effects of physical activity/exercise on health outcomes in a wide range of heterogeneous populations. Our data shows a 13% reduction in mortality rates among 27,671 participants, and a small improvement in QOL and health-related QOL following various modes of physical activity/exercises. This means that both healthy individuals and medically compromised patients can significantly improve function, physical and mental health; or reduce pain and disability by exercising more [ 190 ]. In line with previous findings [ 191 , 192 , 193 , 194 ], where a dose-specific reduction in mortality has been found, our data shows a greater reduction in mortality in studies with longer follow-up (> 12 months) as compared to those with shorter follow-up (< 12 months). Interestingly, we found a consistent pattern in the findings, the higher the quality of evidence and the lower the risk of bias in primary studies, the smaller reductions in mortality. This pattern is observational in nature and cannot be over-generalised; however this might mean less certainty in the estimates measured. Furthermore, we found that the magnitude of the effect size was the largest among patients with mental health conditions. A possible mechanism of action may involve elevated levels of brain-derived neurotrophic factor or beta-endorphins [ 195 ].

We found the issue of poor reporting or underreporting of adherence/withdrawals in over a quarter of CSRs (25.3%). This is crucial both for improving the accuracy of the estimates at the RCT level as well as maintaining high levels of physical activity and associated health benefits at the population level.

Even the most promising interventions are not entirely risk-free; and some minor AEs such as post-exercise pain and soreness or discomfort related to physical activity/exercise have been reported. These were typically transient; resolved within a few days; and comparable between exercise and various control groups. However worryingly, the issue of poor reporting or underreporting of AEs has been observed in one third of the CSRs. Transparent reporting of AEs is crucial for identifying patients at risk and mitigating any potential negative or unintended consequences of the interventions.

High risk of bias of the RCTs evaluated was evident in more than two thirds of the CSRs. For example, more than half of reviews identified high risk of detection bias as a major source of bias suggesting that lack of blinding is still an issue in trials of behavioural interventions. Other shortcomings included insufficiently described randomisation and allocation concealment methods and often poor outcome reporting. This highlights the methodological challenges in RCTs of exercise and the need to counterbalance those with the underlying aim of strengthening internal and external validity of these trials.

Overall, high risk of bias in the primary trials was the main reason for downgrading the quality of the evidence using the GRADE criteria. Imprecision was frequently an issue, meaning the effective sample size was often small; studies were underpowered to detect the between-group differences. Pooling too heterogeneous results often resulted in inconsistent findings and inability to draw any meaningful conclusions. Indirectness and publication bias were lesser common reasons for downgrading. However, with regards to the latter, the generally accepted minimum number of 10 studies needed for quantitatively estimate the funnel plot asymmetry was not present in 69 (46%) CSRs.

Strengths of this research are the inclusion of large number of ‘gold standard’ systematic reviews, robust screening, data extractions and critical methodological appraisal. Nevertheless, some weaknesses need to be highlighted when interpreting findings of this overview. For instance, some of these CSRs analysed the same primary studies (RCTs) but, arrived at slightly different conclusions. Using, the Pieper et al. [ 39 ] formula, the amount of overlap ranged from 0.01% for AEs to 0.2% for adherence, which indicates slight overlap. All CSRs are vulnerable to publication bias [ 196 ] - hence the conclusions generated by them may be false-positive. Also, exercise was sometimes part of a complex intervention; and the effects of physical activity could not be distinguished from co-interventions. Often there were confounding effects of diet, educational, behavioural or lifestyle interventions; selection, and measurement bias were inevitably inherited in this overview too. Also, including CSRs only might lead to selection bias; and excluding reviews published before 2000 might limit the overall completeness and applicability of the evidence. A future update should consider these limitations, and in particular also including non-CSRs.

Conclusions

Trialists must improve the quality of primary studies. At the same time, strict compliance with the reporting standards should be enforced. Authors of CSRs should better explain eligibility criteria and report sources of funding for the primary studies. There are still insufficient physical activity trends worldwide amongst all age groups; and scalable interventions aimed at increasing physical activity levels should be prioritized [ 197 ]. Hence, policymakers and practitioners need to design and implement comprehensive and coordinated strategies aimed at targeting physical activity programs/interventions, health promotion and disease prevention campaigns at local, regional, national, and international levels [ 198 ].

Availability of data and materials

Data sharing is not applicable to this article as no raw data were analysed during the current study. All information in this article is based on published systematic reviews.

Abbreviations

Adverse events

Cardiovascular diseases

Cochrane Database of Systematic Reviews

Cochrane systematic reviews

Confidence interval

Grading of Recommendations Assessment, Development and Evaluation

Hazard ratio

Interquartile range

Mean difference

Prediction interval

Quality of life

Randomised controlled trials

Relative risk

Risk difference

Risk of bias

Standard error

Standardised mean difference

World Health Organization

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There was no funding source for this study. Open Access funding enabled and organized by Projekt DEAL.

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Pawel Posadzki

Nanyang Technological University, Singapore, Singapore

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Dawid Pieper, Nadja Könsgen & Annika Lena Neuhaus

School of Medicine, Keele University, Staffordshire, UK

Jozef Pilsudski University of Physical Education in Warsaw, Faculty Physical Education and Health, Biala Podlaska, Poland

Hubert Makaruk

Health Outcomes Division, University of Texas at Austin College of Pharmacy, Austin, USA

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PP wrote the protocol, ran the searches, validated, analysed and synthesised data, wrote and revised the drafts. HM, NK and ALN screened and extracted data. MS and DP validated and analysed the data. RB ran statistical analyses. All authors contributed to writing and reviewing the manuscript. PP is the guarantor. The authors read and approved the final manuscript.

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Supplementary Information

Additional file 1:.

Supplementary Table 1. Main characteristics of included Cochrane systematic reviews evaluating the effects of physical activity/exercise on health outcomes ( n  = 150). Supplementary Table 2. Additional information from Cochrane systematic reviews of the effects of physical activity/exercise on health outcomes ( n  = 150). Supplementary Table 3. Conclusions from Cochrane systematic reviews “quote”. Supplementary Table 4 . AEs reported in Cochrane systematic reviews. Supplementary Table 5. Summary of withdrawals/non-adherence. Supplementary Table 6. Methodological quality assessment of the included Cochrane reviews with AMSTAR-2. Supplementary Table 7. Number of studies assessed as low risk of bias per domain. Supplementary Table 8. GRADE for the review’s main comparison. Supplementary Table 9. Studies reporting quality of life outcomes as mean difference.

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Posadzki, P., Pieper, D., Bajpai, R. et al. Exercise/physical activity and health outcomes: an overview of Cochrane systematic reviews. BMC Public Health 20 , 1724 (2020). https://doi.org/10.1186/s12889-020-09855-3

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Received : 01 April 2020

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Published : 16 November 2020

DOI : https://doi.org/10.1186/s12889-020-09855-3

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