Physical Activity and Public Health: Four Decades of Progress

in Kinesiology Review

Over the past 40 years, physical activity (PA) and public health has been established as a field of study. A robust evidence base has emerged demonstrating that participation in recommended amounts of PA results in a wide array of physical and mental health benefits. This led to the establishment of federal and global PA guidelines and surveillance programs. Strong evidence supports the efficacy of individual-level (e.g., goal setting) and environmental (e.g., policies) interventions to promote PA. There has also been progress in establishing a skilled and diverse workforce to execute the work of PA and public health. Looking forward, major challenges include stemming the obesity and chronic disease epidemics, addressing health inequities, and diversifying the workforce. Given the known benefits of PA and the availability of evidence-based interventions, efforts now must focus on implementing this knowledge to improve population health and reduce inequities through PA.

More than 2,000 years ago, Hippocrates of Kos, the father of medicine, stated, “If we could give every individual the right amount of nourishment and exercise, not too little and not too much, we would have found the safest way to health.” Five hundred years ago, Bernardino Ramazzini, the father of occupational medicine, observed that specific diseases and conditions disproportionately affected those with differing occupations. He recommended that “they [sedentary workers] should be advised to take physical exercise . . . and so to some extent counteract the harm done by many days of sedentary lifestyle” (Ramazzini, 2001). Nearly 70 years ago, Jeremy Morris and colleagues found that bus drivers, who spent the day sitting, were at increased risk of myocardial infarction compared with conductors, who spent the day walking to collect tickets on double-decker buses (Morris & Heady, 1953; Morris et al., 1953). The benefits of both occupational and leisure-time physical activity (PA) for preventing premature mortality and heart disease were subsequently confirmed and extended in landmark longitudinal studies (Paffenbarger et al., 1970; Paffenbarger et al., 1978). These elegant studies were the foundation of the field of PA and public health (PAPH), a critical application area in kinesiology that is focused on improving population-level health. Despite the longstanding recognition of the importance of PA for individual health, the academic discipline of PAPH is relatively new and was not included in Brooks’ publication, Perspectives on the Academic Discipline of Physical Education (Brooks, 1981).

PAPH combines two disciplines: kinesiology—the study of human movement—and public health—the science of protecting and improving the health of people and their communities. In the past 40 years, there has been tremendous progress in establishing PAPH as a field of study. Presently, physical inactivity is recognized as a leading modifiable risk factor for noncommunicable diseases and has been declared a global epidemic by the World Health Organization, and there are surveillance systems to track trends in PA in more than 122 countries (Bull et al., 2020; Hallal et al., 2012; Troiano et al., 2020). It is estimated that physical inactivity results in 5.3 million premature deaths and costs the global economy US$314–446 billion per year (Hafner et al., 2020; Lee et al., 2012). The U.S. Department of Health and Human Services issued PA guidelines for Americans, which led to a National PA Plan for implementation of evidence-based interventions and policies to promote PA. The World Health Organization issued a Global Action Plan on PA to reduce global levels of inactivity by 15% by 2030 (World Health Organization, 2018).

The American Public Health Association classifies public health services into three broad categories (American Public Health Association, 2020): (a) assessment, which includes investigating root causes of health hazards (e.g., quantifying a dose–response relationship between PA and a disease outcome) and surveillance, the monitoring of population health trends; (b) health promotion and policy development, such as interventions to improve and promote activity, communication strategies to inform and educate, and the implementation of policies, plans, laws, and other legal and regulatory actions; and (c) assurance, including the development and maintenance of organizational infrastructure for public health, building a diverse and skilled workforce, and the assurance of equitable access to public health resources. Following, we provide an overview of progress in each of these core areas of PAPH over the past 40 years. We conclude with an overview of challenges facing the field in the coming decades.

Part 1: Assessment

Development of PA Guidelines

The PA Guidelines are evidence-based recommendations for the amount, type, and duration of activity that should be undertaken by the population. The intended audience is health professionals and policy makers, and these guidelines become the target for health promotion efforts (Physical Activity Guidelines Committee, 2008). In the past 40 years, the purpose and contents of the guidelines have evolved (Blair et al., 2004; Troiano et al., 2020). In 1975, the American College of Sports Medicine (ACSM) published the first Guidelines for Graded Exercise Testing and Prescription, which recommended that adults engage in 20–45 min/day of vigorous exercise (70–90% of heart rate reserve) 3–5 days per week to improve cardiorespiratory fitness (American College of Sports Medicine, 1975). Subsequently, evidence accumulated demonstrating that broad health benefits could be achieved with PA intensities lower than the amount recommended to improve cardiorespiratory fitness (e.g., Hakim et al., 1998). In 1995, ACSM and the Centers for Disease Control and Prevention jointly issued Guidelines that, for the first time, focused on health benefits of PA rather than fitness (Pate et al., 1995). The ACSM/Centers for Disease Control and Prevention Guidelines recommended 30 min of moderate-intensity activity on most, if not all, days of the week. Moderate intensity was defined as 3–5.99 metabolic equivalents of task, equivalent to a brisk walk at approximately 3.0 mph (Pate et al., 1995).

The next major milestone for the field was the release of the U.S. Department of Health and Human Services PA Guidelines for Americans in 2008 (referred to as Guidelines; Physical Activity Guidelines Committee, 2008). These seminal federal guidelines focused on identifying the dose of activity that produces substantial health benefits for most children and adults. Key messages from the 2008 Guidelines were that some activity is better than none and that, to produce substantial health benefits, American adults should engage in at least 150–300 min/week of moderate and/or 75–150 min of vigorous activity (6+ metabolic equivalents of task) in addition to two sessions of muscle strengthening activities per week (Physical Activity Guidelines Committee, 2008). In 2018, the updated PA Guidelines expanded the list of physical and mental benefits of PA based on strong empirical evidence and maintained the same recommended dose of aerobic activity and strength training as in 2008. Two major changes were (a) recommendations to “sit less, move more” and (b) removal of the criterion that moderate to vigorous intensity PA (MVPA) be accumulated in 10-min bouts as evidence accumulated that health benefits could be derived from “non-exercise” physical activities, including short bouts of moderate-intensity activity (<10 min; Piercy et al., 2018). The most recent Guidelines are from the World Health Organization, which further expand the known list of diseases and conditions linked with inactivity and provide recommendations for future research (Bull et al., 2020; DiPietro et al., 2020).

PA Surveillance

Surveillance is the ongoing, systematic collection, analysis, and interpretation of health-related data. It is considered the cornerstone of public health and essential to planning, implementation, and evaluation of population level adherence to Guidelines (Troiano et al., 2020). Within the United States, PA trends are monitored through several surveillance systems, including the National Health Interview Survey, which has assessed PA annually since 1975 (National Center for Health Statistics, 2021). The National Health and Nutrition Examination Survey contains a comprehensive battery of health measures and first collected device data on PA from 2003 to 2006, making it among the first large scale deployments of wearable devices and the first to provide a description of device-assessed PA and sedentary time in a nationally representative sample of the United States (Matthews et al., 2008; Troiano et al., 2008).

The story told by these surveillance systems regarding PA and chronic disease is telling. Forty years ago, American adults had lower levels of overweight and obesity (Ellis et al., 2014) and chronic disease (e.g., 3.5% diabetes rate in 1990 vs. 11% in 2018; Geiss et al., 2014). They were much more physically active than today’s adults in terms of overall PA energy expenditure. Declines in overall PA have been driven by increases in screen time and decreases in occupational, household, and transportation activity (Church et al., 2011; Du et al., 2019). Globally, PA trends have stagnated with 27.5% of the population insufficiently active and minimal progress toward global PA targets (Guthold et al., 2018). Within the United States, there is evidence for modest increases in leisure-time PA among adults with 43% of adults meeting aerobic PA guidelines in 2006, which rose to 53% in 2017 (National Center for Health Statistics, 2017). For combined muscle strengthening and aerobic guidelines, the percentage adhering to Guidelines remained low from 2008 to 2017 but increased from 19% to 25% among urban residents and from 13% to 20% among rural residents (Whitfield et al., 2019). Unfortunately, leisure-time PA remains a small part of PA over the course of a 24-hr day, and with the growth of sedentary behaviors, surveillance systems will need to adapt (Troiano et al., 2020).

Current and Future Challenges in Assessment

The Emergence of Sedentary Behavior as a Risk Factor

After many years of research focusing on MVPA, research on the negative health impact of too much sedentary behavior (i.e., sitting/lying with low energy expenditure while awake) has emerged rapidly in the past 10–15 years (Keadle et al., 2017; Owen et al., 2010). Western populations spend an average of 9 hr/day sedentary (Hamer et al., 2020; Matthews et al., 2008). The 2018 Guidelines Committee report stated that there was strong evidence that sedentary behavior increased risk for all-cause and cardiovascular disease mortality, incident cardiovascular disease, and Type 2 diabetes and moderate evidence for endometrial and colon and lung cancer. However, quantitative recommendations on the amount of sedentary behavior that is associated with poor health was not possible due, in part, to poor measures of sedentary behavior (Katzmarzyk et al., 2019). Importantly, the detrimental impact of too much sedentary behavior is strongest among physically inactive people (i.e., those not achieving public health recommendations for MVPA).

The emergence of sedentary behavior as a risk factor leads to questions about what types of activities should be recommended to replace sedentary behavior and achieve improvements in health. Determining the replacement effects of sedentary behavior requires consideration of the full spectrum of activity types and intensities over the 24-hr day (Rosenberger et al., 2019). One approach that has proven useful is the use of isotemporal substitution models that allow researchers to estimate the health effects of replacing an equal amount of time in one type of activity with an equal amount of time in another while holding the effects of each type of activity and total time constant (Mekary & Ding, 2019). As device data accrues (described later), more complex statistical models and studies that can identify mechanisms underlying the health impact of sedentary behavior and PA across the 24-hr cycle will be needed (DiPietro et al., 2020).

Impact of Device-Based Data on the Field

Historically, self-report questionnaires were the only feasible tool to assess physical activities in large studies. These questionnaires typically ask participants to recall the time spent engaging in bouts of MVPA over the past 7–30 days. However, they are less accurate for unstructured PA (i.e., not in bouts of 10 min) and sedentary and light-intensity activity and are prone to measurement error and social desirability bias (Silsbury et al., 2015). Wearable devices, defined as electronic devices worn on the body, have fundamentally changed PA assessment over the past 20 years (Burchartza et al., 2020). The most common sensor is an accelerometer that measures body movement in one or more planes, though other sensors like heart rate, gyroscope, and skin temperature are increasingly common. The time-stamped nature of the wearable sensor data enables minute-to-minute and day-to-day evaluation of behavioral patterns, providing unprecedented detail on the length of MVPA bouts needed or the number of days with MVPA required to improve longevity (Chomistek et al., 2016; Evenson et al., 2017). Device-based measures also provided the first indications that light-intensity physical activities increased longevity (Lee et al., 2018; Matthews et al., 2016). The use of wearable sensors has become widespread, and data collection is on-going in over 400,000 participants in prospective cohort studies and clinical trials globally (e.g., Doherty et al., 2017; German National Cohort Committee, 2014; Lee & Shiroma, 2014).

Although device data have clear advantages, self-report questionnaires will continue to be widely used in the future due to their low cost and ability to assess contextual information (e.g., walking for transportation vs. leisure) and some behaviors that devices cannot assess well (e.g., strength training, yoga; Troiano et al., 2020). Thus, a major challenge to the field moving forward is reconciling data from devices versus self-report measures, which some have argued are measuring completely different constructs (Troiano et al., 2014). For example, a person completing a self-report questionnaire may state that they played basketball for 1 hr. The device will only record actual movement during that hour, so if they played for 20 min, then sat for 20 min, then played for a final 20 min, the device would record at most 40 min, although the person reporting is not “wrong” that they played basketball for 60 min. Estimates of adherence to Guidelines not only vary between devices and self-report measures but also vary dramatically within device-based measures depending on the type of device and data processing method used to estimate time spent in activity intensity categories (Troiano et al., 2008, 2014). It has been argued that adherence to PA guidelines, which were based predominantly on self-report data, should not be quantified using devices; however as device data inform current and future versions of Guidelines, there is a need to effectively integrate devices into surveillance efforts (Troiano et al., 2014, 2020).

To date, a few studies have compared self-reported and device-assessed PA with promising results. The shape of the inverse dose–response relationship between increasing activity and lower risk of mortality is consistent between questionnaire and device-based measures, although the magnitude of risk reduction is greater using devices (Evenson et al., 2017). Two studies that estimated mortality reductions associated with replacement of sedentary behavior also reached similar conclusions. Among less active individuals, using a self-report questionnaire, replacing 1 hr/day of sitting with 1 hr/day of exercise reduced mortality risk by 42% and replacing sitting with 1 hr/day of light-intensity activity resulted in a 20% risk reduction (Matthews et al., 2015). Using device data, the magnitude of risk reduction for replacing sedentary behavior was almost identical (Matthews et al., 2016). Two meta-analyses, one with devices and one with self-report questionnaires, examined data on the joint effects of sedentary time and PA (Ekelund et al., 2016, 2020). Using self-report questionnaires in a sample of 1.4 million participants, high amounts of activity (60–75 min of walking/day) were sufficient to eliminate the detrimental effects of sedentary time (Ekelund et al., 2016). Similarly, according to device-based data in 44,370 individuals, those who were both highly sedentary and had low activity were at highest risk, and 30–40 min of device-assessed MVPA attenuated the association between amounts of sedentary time and mortality (Ekelund et al., 2020). Although reconciling device and questionnaire data remains a challenge to for future surveillance efforts and etiologic studies, it is promising that the fundamental relationships appear similar between assessment methods.

Part 2: Health Promotion

Understanding how much PA is needed to achieve health benefits is not sufficient to realize these benefits in the population. In 2018, the U.S. PA Guidelines Advisory Committee recognized this by publishing, for the first time, evidence-based reviews of strategies to promote regular PA across the lifespan. The bulk of evidence focused on modifying individual-level beliefs and attitudes to promote PA. There is moderate to strong evidence that these theory-based interventions increase PA in youth, adults, and older adults (Physical Activity Guidelines Committee, 2018). These approaches primarily focus on “choice-enabling” theories and frameworks, including the theory of planned behavior/reasoned action, transtheoretical model, behavioral economics, and social cognitive theory—all theories that have arisen in the past 40 years (King et al., 2002). However, recent years have brought increasing attention to multilevel, multitheory approaches. The social ecological model (SEM) has become especially prominent and posits that behaviors are influenced by social and cultural factors (e.g., social norms, social support, and group dynamics), physical environments (e.g., functional features, safety features, esthetic features, and destination features), and policy environments (e.g., physical education, access to facilities, and transportation and urban planning policies). Through this perspective, it takes both individual-level and environmental/policy-level interventions to change behavior at the population level (Sallis et al., 2015). In the last two decades, we have advanced our evidence substantively on modifying the physical environment and public health policies and promoting PA via “remote” media, including information technologies.

Environmental, Policy, and Sociocultural Contexts

Although a full review of the broad influence of environmental factors on PA is beyond the scope of this article, we focus here on interventions that specifically target PA behaviors at the environmental level. These types of interventions typically have a small but broad impact of behaviors given that they target whole environments/communities, but they also have promise for long-term sustained impact given their placement as environmental modifications. Point-of-decision prompts to promote stair use are a classic example of environmental interventions. These prompts include signage at stairs or escalators or elevators to promote stair use or stairwell beautification to include music, artwork, or other means to increase attractiveness. The efficacy of these approaches has been described in two meta-analyses (Jennings et al., 2017; Reynolds et al., 2014). Broader strategies include modifying environmental characteristics (e.g., walkability, land-use mix, or destinations) and implementing programs that support active transportation (e.g., walking to school, biking to work).

A landmark natural experiment called RESIDE in Australia followed individuals who self-selected into housing developments with a mix of improved urban design features. The researchers found that transport-related walking increased when individuals moved to neighborhoods with greater access to destinations, whereas recreational walking increased in neighborhoods with greater attractiveness and more access to green space and outdoor recreation facilities (Giles-Corti et al., 2013). Meanwhile, there is moderate evidence for programs such as Safe Routes to Schools (Fraser & Lock, 2011). Such programs focus on policies that support active transportation and the design of urban planning features (e.g., provision of parks or trails, bike paths) that facilitate walking to school among children and biking to work among adults (Lubans & Sylva, 2006).

Communication Contexts (i.e., Information Technology)

Not surprisingly, as smartphones and wearable technologies have grown in use over the past decade, their use to promote PA has also increased. These technological advances, however, are built upon more established “remote” interventions, including telephone-assisted interventions as well as web-based and mail- or email-based interventions tailored to the individual via automated means. Telephone and web-based interventions have shown strong efficacy in both adult and older adult populations with much evidence regarding clinical populations, including individuals with Type 2 diabetes and with musculoskeletal disorders (Bossen et al., 2014; Goode et al., 2012). These programs are significant because they have served as the basis for current mobile health interventions and have introduced the concept of adapting intervention content to the needs of the individual. Tailoring intervention content to the needs of the individual is now a hallmark of most effective approaches for improving PA (Short et al., 2011). There is increasing evidence for the efficacy of more contemporary mobile health approaches, including the use of consumer-grade activity monitors (de Vries et al., 2016; Mansi et al., 2014; Ridgers et al., 2016), text messaging interventions (Buchholz et al., 2013), and “app” based interventions that may integrate activity monitors, text, education, social support, and other interactive and theory-based targets (Blackman et al., 2013; Fanning et al., 2012). It is important to note that although each of these approaches carries some evidence for behavior change, the most effective interventions are multicomponent in nature and leverage behavioral theory drawn from social cognitive theory and SEM frameworks in their designs to change behavior (Franssen et al., 2020).

Future Directions for Health Promotion Through PA

Collectively, current PA guidelines encourage sitting less and moving more and incorporating movement in many forms and modalities across the waking day. There is strong evidence for interventions that deliver multilevel approaches to reduce sedentary behavior in the workplace (Commissaris et al., 2016; Shrestha et al., 2015) as well as moderate evidence for youth-focused interventions to reduce screen time in school-based settings (Friedrich et al., 2014; van Grieken et al., 2012). There is less evidence for reducing sedentary behavior in other populations, overall sedentary time, and other context-specific forms of sedentary behavior (e.g., sedentary screen time in adults, transport-related sitting). As discussed previously, there is now greater recognition for the “24 Hour Day” and the dynamic and interconnected nature of sleep, sedentary behavior, and PA (Rosenberger et al., 2019). This is not just in terms of the collective health benefits of sleep, sedentary behavior, and PA but also the synergistic nature in which these behaviors can be changed. Combining PA behavior change with other behaviors (e.g., PA + diet, PA + smoking cessation) has demonstrated efficacy as well; however, there are few examples of interventions that collectively target the full 24-hr day. Reducing sedentary time creates opportunities to promote replacement behaviors, such as light-intensity PA, MVPA, or even sleep. Furthermore, improving sleep duration and/or quality can increase daily perceptions of energy and reduce fatigue, which in turn, can be harnessed to promote active behaviors during the waking day (Atoui et al., 2021). Future research should leverage these potential synergies in health promotion interventions that are in line with more comprehensive national and global guidelines for PA.

Dissemination and Implementation Science

Dissemination and implementation science has rapidly evolved to study the factors and models that influence how evidence can be translated to the field. It is important to distinguish between the terms dissemination and implementation to understand the science this field advances. Dissemination science is the study of the targeted distribution of information and intervention materials to a specific public health or clinical practice audience. The intent is to understand how best to spread and sustain knowledge and the associated evidence-based interventions. Implementation science, on the other hand, is the study of the use of strategies to adopt and integrate evidence-based health interventions into clinical and community settings to improve patient outcomes and benefit population health (Department of Health and Human Services, 2020). Although the sciences of dissemination and implementation are distinct, they borrow from a range of fields, including communication, public affairs, engineering, and technology, among others, and collectively are needed to effectively “scale up” the evidence generated in PA intervention science for population health impact.

Intervention development and adaptation frameworks make the process of intervention development feasible, consistent, and of high quality (Bartholomew et al., 1998; Czajkowski et al., 2015). These frameworks have aided in developing evidence-based interventions to increase PA that can be adapted to the population of interest. There are more than 200 such programs and strategies available for public utilization through searchable web portals and repositories, and these sites have been visited millions of times (Sanchez et al., 2012). However, the challenge remains that individuals, communities, and organizations are adopting and sustaining programs at low rates. Our ability to rapidly translate evidence-based knowledge and programs into practice is often hindered not by the strength of the evidence but on the ability of the innovation to be adopted in real-world settings, the ability to train practitioners to deliver it, and the access to populations that can receive it (Glasgow et al., 1999). The public health impact of a given intervention (e.g., policy, program, guideline, environmental change) has been proposed to be the product of its effectiveness (the impact that it has on a given outcome per person) and the number of people that participate in it (Velicer & DiClemente, 1993). Exercise training studies maximize internal validity on health outcomes (the dependent variables) by harnessing all possible resources to make the largest possible gap between groups in PA (the independent variable). For this reason, and because they are often developed and implemented in lab settings, they struggle to be implemented in the field (Glasgow et al., 2012). There is not a clear audience ready to adopt and sustain these programs, and the curricula themselves require more time and resources than most potential adoptees can muster (e.g., equipment, staff expertise, participant compensation, etc.).

An important advancement in the field of dissemination and implementation research has been the proliferation of models and frameworks to guide the dissemination and implementation of programs. The most common framework to evaluate PA intervention programs has been the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework (Glasgow et al., 1999). RE-AIM provides guidance for evaluating the public health impact of an evidence-based program, including how well the program reaches the intended population (reach), the impact the program has on important health outcomes (effectiveness or efficacy), the number and quality of settings and/or delivery agents that are willing to adopt the program (adoption), the fidelity of intervention delivery (implementation), and the ability of the program to sustain effects in individuals and settings over time (maintenance).

By way of example, Ory et al. (2020) reported on the implementation of a 12-month diabetes education program offered in 14 of 27 South Texas counties. The program followed American Diabetes Association best practice guidelines, including goal setting for regular PA. In addition to reporting traditional effectiveness outcomes (e.g., blood glucose, body mass index), the authors also reported reach (i.e., proportion and representativeness of individuals from the target population) and retention (population representativeness over time); adoption rates of the program, which included the tracking of adoption of regional headquarters and community sites and agencies surrounding the delivery hubs; implementation outcomes, which included quality control outcomes for intervention delivery to ensure that they were delivered according to American Diabetes Association guidelines along with cost of the intervention; and finally, maintenance, which included individual-level maintenance of blood glucose levels over 12 months and the likelihood of the program being maintained, including direct financial support from private and public sources and legislative commitment to maintain the operation of the regional hubs.

Dissemination and implementation science has developed more mechanistic frameworks that seek to advance how interventions are optimally implemented into real-world settings, including strategies for adapting programs to maintain effectiveness and ensuring flexibility relative to the needs of given practice settings. The Consolidated Framework for Implementation Research provides practical and setting-specific strategies for adapting interventions for delivery into specific practice settings (Damschroder et al., 2009). The Promoting Action on Research Implementation in Health Services is a framework to characterize program adherence and competence. Promoting Action on Research Implementation in Health Services constructs include innovation, recipient, context, and facilitation (Harvey & Kitson, 2016). As the academic discipline of kinesiology pivots toward promoting PA in the population, the increased focus on health promotion and intervention science has coincided with efforts to train a skilled, diverse workforce to help grow and implement this knowledge.

Part 3: Assurance

With regard to assurance, PAPH has focused on two areas: (a) training a skilled workforce and (b) diversity, equity, and inclusion. The emphasis on diversity, equity, and inclusion has arisen in response to recognition that (a) overall obesity, chronic disease, and physical inactivity epidemics are driven by extreme values within population subgroups (Murray et al., 2006); (b) these extreme values are driven by modifiable structural and cultural forces (Marmot & Wilkinson, 2005); (c) the scientific process can be applied to generate effective interventions within population subgroups (Bartholomew et al., 1998; Czajkowski et al., 2015); and (d) success in this end will require a skilled workforce with representation from affected communities (Bustamante et al., 2019; Evenson et al., 2015).

Diversity refers to the presence of socially meaningful differences among members of a group (Cunningham, 2015). In kinesiology, the focus has been on the diversity of the workforce and whether individuals from historically underrepresented groups have opportunities to participate. Inclusion is a closely related concept that refers to the degree to which people feel free to express their individuated selves and have a sense of connectedness and belonging to a group (Cunningham, 2015). The concept speaks to the experiences of group members. For example, are all individuals (regardless of their backgrounds) able to compete and belong in the workforce while being their genuine and authentic selves? Or do they have to hide who they are to participate?

Equity is defined as the quality of being fair and impartial. In the PAPH context, the focus has been on “health equity,” an ideal that is achieved when every person has the opportunity to “attain his or her full health potential and no one is disadvantaged from achieving this potential because of their social position or other socially determined circumstance” (Braveman, 2003). The term health equity is distinct from similar constructs, such as health disparities (i.e., absolute health differences between sociodemographic groups). Health inequities are a subset of health disparities in which the differences between groups are attributable to structural and cultural forces stemming from social advantage. By way of example, older adults have higher chronic disease rates than children; these differences are correctly classified as disparities, but they are not inequities—biology is the culprit, not social disadvantage. Hence, a health inequity is a health difference between groups that is unnecessary, avoidable, unfair, and unjust (Whitehead, 1992).

Training a Skilled and Diverse Workforce

There has been a consistent push to train a skilled work force to carry out the work in kinesiology and PAPH since the beginnings of the field, and this has expanded greatly in recent decades. In 1995, the University of South Carolina began its PAPH course for researchers and practitioners, and it has been offered 20 times since. The 7-day research course is designed to develop research competencies related to PAPH, and the 4-day practitioner course is designed for those involved or interested in community-based initiatives to promote PA. The course has enrolled 20–40 participants per year, and a 2015 survey of 322 alumni found that 98% reported that it had a positive impact on their work. At that point in time, 82 alumni had received 117 National Institutes of Health grants and 11/14 PA journals had at least 1 fellow on staff as editor, associate editor, or editorial board member (Evenson et al., 2015).

Federally funded training programs have also emerged to train early-stage investigators to research health inequities and to conduct behavioral intervention research. In 2016, the National Institute of Minority Health founded the Health Disparities Research Institute that aims to support the research career development of promising early-career minority health/health disparities research scientists and to stimulate research in the disciplines supported by health disparities science (National Institutes of Health, 2021). The National Institute of Health Office of Behavioral and Social Sciences Research offers a host of short summer courses through its funding opportunity titled Short Courses on Innovative Methodologies in the Behavioral and Social Sciences (R25; Office of Behavioral and Social Sciences Research, 2021).

Concurrently, there has been a large push to diversify the field. This push stems from both ethical and practical considerations. Here again, principles of equity apply. We expect that individuals who work harder and produce more should receive greater gains, and in this respect, we expect to see large variability in professional achievement across individuals; a select few achieve fellowship or are voted in as officers of international PA-focused professional organizations, such as the National Academy of Kinesiology (NAK) and the ACSM. However, we also see that individuals from gender, disability, and racial/ethnic minority groups are vastly underrepresented at these levels (if present at all).

The ACSM is the world’s largest PA-focused professional organization with more than 50,000 members and certified professionals from 90 countries. The ACSM has had 64 presidents since 1954; the current (and 64th) president, Dr. NiCole R. Keith, is the 9th female president and the first racial/ethnic minority president (American College of Sports Medicine, 2021). The NAK is our field’s most prestigious honorary organization, composed exclusively of fellows who have made significant contributions to the fields of kinesiology and physical education. There have been only 598 fellows since its founding in 1926, and very few have been from racial/ethnic backgrounds underrepresented in science and medicine (National Academy of Kinesiology, 2021a). The NAK has had 81 presidents to date, 24 of whom have been women; we are not aware of any NAK president who was from a racial/ethnic minority background (National Academy of Kinesiology, 2021b). It is simply not the case that no one (or only a handful of individuals) from socially disadvantaged groups has had the talent to compete at this level, the size of the population is too large for that to be true. Rather, the absence of some groups speaks to structural and cultural barriers to participation, who has been permitted to compete and who has not. The removal of these barriers and extending the opportunity to compete to all—the pursuit of equity—has been undertaken with vigor by ACSM, NAK, and the field at large. This not only appeals to our sense of fairness and ethics but it is also adaptive for the performance of the field—opening competition to more people will allow us the opportunity to recruit and retain more talent.

The ACSM recently published its member and fellowships demographics in the context of its efforts to diversify its organization over the past decade (Bustamante et al., 2019). The first year that demographic data were collected was 2008, and findings suggested that of its 20,007 members, 45% were female but only 237 of ACSM’s 1,329 fellows were women (18%). Among members reporting race/ethnicity, 8% were Asian, 5% were Hispanic, 4% were African American, and fewer than 1% were Arabic, Hawaiian, or Native American. Since 2003, six elected ACSM presidents have made diversity their primary presidential platform; ACSM has undertaken a concerted and sustained effort to diversify its membership and leadership, including 10 large-scale initiatives (e.g., mentorship programs, an annual diversity reception, trustee positions) aimed at promoting diversity, equity, and inclusion. By 2019, the number of members rose to 22,128 and the proportion of female members rose to 50%. Among members reporting race/ethnicity in 2019, there were modest increases in most racial/ethnic groups compared to 2008, but numbers remain well below the breakdown of the general population; the number of fellows rose to 1,472, and the number of female fellows rose to 355, a 33% increase (Bustamante et al., 2019).

The experiences of NAK, ACSM, and the kinesiology field are not unique; they mirror the experience of the scientific enterprise in the United States broadly. The National Science Foundation continually monitors the participation of women, minorities, and persons with disabilities in science and engineering. The results show that individuals from underrepresented racial/ethnic minority backgrounds earned 4% of PhDs in science and engineering in 1996, and that number has risen to 9% as of 2016 (National Science Foundation, 2017). Over the past decade, national programs aimed at addressing these disparities have proliferated and include the National Research Mentoring Network (Sorkness et al., 2017) and The National Center for Faculty Development & Diversity (Ermes et al., 2008).

There is a field of research dedicated to understanding the effect of diversity on organizational performance (Page, 2008). Broad takeaways from this literature include that individuals tend to be happier (e.g., less conflict, more respect and trust) in more homogenous groups and that diverse groups often outperform ostensibly more skilled but homogenous groups on tasks related to prediction and problem solving where the experiences of the more diverse group are relevant to the challenge at hand (Hong & Page, 2004). Consider, then, the challenge of inequities in PA and health. Are the experiences of people from underserved and vulnerable communities relevant to addressing physical inactivity and chronic disease epidemics? Certainly, given that, in many cases, the epidemics are driven by disproportionately high rates in these same communities. It will be difficult to address chronic disease and inactivity in underserved communities without their involvement on research and medical teams. The power of diversity comes from bringing new perspectives to bear on problems and then harnessing those perspectives.

Research Describing Disparities in PA and Health

In the United States, data consistently show disparities in comorbid conditions that are linked with physical inactivity (e.g., diabetes, obesity) and direct inequities in rates of PA; for example, 54% of Latina women in the United States report engaging in no leisure-time PA, whereas only 31% of non-Latina White women report the same (Marquez et al., 2010). Historically, these differences were largely attributed to individual characteristics or experiences (e.g., habits, knowledge, confidence, competence, motivation) and genetics (e.g., impulsivity, executive function, energy levels, metabolism; Epstein & Roemmich, 2001; Friedman et al., 2008; Luke et al., 2001). In 2021, exclusive individual/personal responsibility arguments still dominate the public discourse in lay circles. Their enduring popularity derives from their simplicity, intuitiveness, and empowerment of individuals to succeed. However, their exclusivity is no longer consistent with the available evidence.

Individual responsibility explains much of the variance between individuals within groups, but it cannot explain large and consistent disparities between sociodemographic groups at a given moment in time or large changes within groups over time. Today’s American children are the literal genetic recombination of the preceding generation of Americans—they cannot be the genetic inferiors of their ancestors in terms of individual characteristics such as intelligence, impulsivity, and metabolism—there must be other forces affecting obesity. Similarly, socioeconomic status and race/ethnicity are socially defined factors not genetically defined ones. The only genetic factors that racial/ethnic categories differ on are the esthetic features (e.g., skin color, hair) on which they are sorted (Feldman et al., 2003). That large disparities in health consistently follow the same sociodemographic lines as disparities in other life domains (e.g., education, employment, socioeconomic status) demands explanations that go beyond individual responsibility. As empowering as personal responsibility arguments are at the individual level, they are as disempowering at the population level.

Research Explaining Inequities in PA and Health

The past 40 years have brought greater understanding of how environments shape behavior and health. This area of research—termed social determinants of health (Marmot & Wilkinson, 2005)—provides the conceptual foundation for health inequities (i.e., health disparities that are attributable to social disadvantage). At the center of social determinants of health and health inequities research are health behavior theories from psychology and public health. SEMs that depict dynamic relationships between individuals, groups, and environments (Bronfenbrenner, 1992; described in detail earlier) have proven critical in health equity research (Sallis et al., 2006). By way of example, a personal responsibility interpretation of disparities in PA between two communities focuses on whether members of the higher risk community lack knowledge or intelligence or do not culturally value PA. An SEM approach may point out that the physical environment differs—the low risk community features green space and safe areas to play, whereas the high risk area does not. The personal responsibility interpretation limits the response of policymakers to preaching that individuals must do better, whereas the SEM interpretation empowers policymakers to change policies and/or physical environments (Furr-Holden et al., 2020). The latter will effectively dissolve structural and cultural forces that led to the disparity, moving the two communities closer to a state of health equity. In this state, we expect to see large variability in PA between individuals within each group based on their individual characteristics and decisions but not large variability between these communities. In this way, the achievement of health equity is the triumph of personal responsibility.

Health behaviors, including PA, are only one means by which health inequities arise. Research also investigates how structural violence (e.g., racism, poverty, xenophobia), neighborhood context and processes, and individual social status directly affect health (Kim et al., 2020). Ongoing work focuses on allostatic load (i.e., the wear and tear of the body in response to chronic stress; McEwen, 1998), psychoneuroimmunology (i.e., the interaction between psychology and the nervous and immune systems; Kiecolt-Glaser et al., 2002), and gut microbiome (i.e., the microorganisms, bacteria, viruses, protozoa, and fungi that live in the human gastrointestinal tract; Shreiner et al., 2015). Specific to PA, researchers also explore relationships between PA and resilience (i.e., capacity to thrive despite exposure to adversity; Jefferies et al., 2019; Martinek & Hellison, 1997) and how PA may buffer individuals from the iatrogenic effects of chronic stress (Sothmann et al., 1996).

Research Addressing Inequities in PA and Health

As described in Section II, there is now widespread recognition that the traditional program and curricula utilized in explanatory lab-based PA intervention trials are not well equipped to address health inequities in the field (Glasgow et al., 2012). This is especially true in underserved and vulnerable populations that face additional obstacles to adoption and implementation. In addition, many PA educational resources are at a readability level that is too high for most U.S. adults to read and understand (Thomas et al., 2018). To address these obstacles, health disparities intervention researchers focus on external validity and community engagement. Community-based participatory research (Wallerstein & Duran, 2006) has become especially prominent. Community-based participatory research speaks to the principle of engaging target settings as equal partners in research from the outset to ensure fit between the intervention and the setting and to ensure that there is an audience ready to adopt the program. Hence, it is increasingly common for schools, hospitals, businesses, and churches serving underserved and vulnerable populations to be equal partners with scientists in the conceptualization, development, implementation, and evaluation of interventions (Wallerstein & Duran, 2006).

Conclusions and Future Directions

This article has provided an overview of the progress in establishing PAPH as an academic discipline over approximately 40 years and major developments in each of the three core areas of public health. Looking forward, PAPH remains a critical application area of kinesiology. The core areas of kinesiology, including physiology and biomechanics, provide the mechanistic evidence that underlies public health guidelines regarding PA doses (i.e., frequency, intensity, duration, and mode) and health outcomes (Powell et al., 2011). Principles of exercise physiology and prescription will continue to inform future PA Guidelines, which we expect to rapidly evolve to integrate device data. We will refine our understanding of how the full 24-hr day, including temporal patterns and activity at the lower end of the activity spectrum, relates to health on both a mechanistic and population level, which will raise new opportunities (and challenges) in surveillance (Troiano et al., 2020). As a result, we expect that the coming years will bring increasingly tailored and comprehensive guidelines for specific populations and health outcomes.

A robust evidence base has emerged demonstrating that participation in recommended amounts of PA results in a wide array of physical and mental health benefits, and there are available evidence-based strategies to promote PA (Piercy et al., 2018). Simultaneously, obesity and other chronic disease rates have increased dramatically. There have been modest increases in rates of engaging in purposeful exercise but secular declines in nonleisure PA and increases in sedentary behavior. Therefore, to achieve the primary goal of public health, we need to focus on the implementation of evidence-based strategies to promote activity. Effectively changing population levels of activity will require an interdisciplinary collaboration within and across sectors and large-scale coordinated approaches, such as the National PA Plan, that move us past the fragmented, uncoordinated efforts of individual research teams.

In addition, narrowly framing PA as medicine (i.e., of sole value for its innate health benefits) may ultimately limit the potential population health impact of guidelines because the audience of individuals and organizations that value health as a major priority is limited. Most individuals and organizations have limited time and resources and their own main goals. For schools, these goals may be academic performance; for businesses, profit or market share; for faith institutions, service; and for hospitals, readmission rates. A potential way forward is to align guidelines with the main goals of settings. For example, a school principal may be provided guidance on using PA to improve attendance, math performance, or parent engagement, and a business owner may be provided guidance on using PA to reduce absenteeism or improve group cohesion. Where guidelines align with main goals, we are likely to see greater adherence, even in difficult circumstances (Bustamante et al., 2021).

Major challenges also remain with regard to addressing health inequities and training a diverse and skilled workforce. First, the pursuit of the environmental changes necessary to address health inequities will require broad political support and will be met with fierce resistance (Frieden, 2010). Second, most PA intervention research focuses on helping people to be physically active within environments that do not naturally support PA, that is, to empower them with tools to overcome their environment. This is analogous to trying to train swimmers to successfully swim upstream. This begs the question, will this ever be enough? Or do we need to broaden our focus by targeting the fundamental causes of inequities and emphasize a need for policy and environmental changes in disadvantaged communities?

A final (predictable) challenge pertains to technology. Modern technologies, such as mobile internet, smartphones, remote activity trackers, and social media, provide more potential for scalability of tailored intrapersonal- and interpersonal-level interventions than ever before. Unfortunately, they also provide this same opportunity to forces that discourage PA (e.g., inactive video games, traditional media, social media), and so far, these forces have proven more adept at applying science to change behavior than the forces of health promotion. Finally, regarding diversifying the workforce, it remains to be seen whether the field can be diversified without first addressing inequities in the primary, secondary, and postsecondary school pipelines that lead into graduate school and professional practice. Where this is achieved, considerably more attention will need to be paid to how we best harness new perspectives to address inequities and promote PA and health broadly (Bustamante et al., 2019).

As we conclude with a look forward to the next 40 years in PAPH, we are amid a public health emergency in response to the COVID-19 pandemic (Huang et al., 2020). This event has changed how we work, socialize, and interact in fundamental ways. Consistent with the early messages of Hippocrates, we, once again, have confirmed the importance of PA during the pandemic. Compared with those meeting PA guidelines, those who are consistently inactive have more than two times the risk of hospitalizations and death due to COVID-19 (Sallis et al., 2021). In other ways, how COVID-19 affects PAPH is less clear. Global levels of PA have declined, screen time is up, and whether we will return to the status quo for workforce participation remains unclear, which has implications for transportation and occupation-related activity rates and policies (Tison et al., 2020). It will be important to monitor the longer term impact of this event and consider whether additional and/or novel strategies to promote activity are needed to overcome declining levels of activity. We are assured by the availability of evidence-based interventions and policies, which we now must focus on implementing to improve population-level health through PA.

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Keadle is with the Dept. of Kinesiology and Public Health, California Polytechnic State University, San Luis Obispo, CA, USA. Bustamante is with the Dept. of Kinesiology and Nutrition, University of Illinois, Chicago, IL, USA. Buman is with the College of Health Solutions, Arizona State University, Phoenix, AZ, USA.

Keadle (skeadle@calpoly.edu) is corresponding author.
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