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Physical Activity to Combat Chronic Diseases and Escalating Health Care Costs

2008· article· en· W2312857660 on OpenAlexaboutno aff
Barry A. Franklin

Bibliographic record

VenueCurrent Sports Medicine Reports · 2008
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePain medicineMEDLINEHealth carePhysical activityChronic diseaseIntensive care medicineMedical emergencyPhysical therapyAnesthesiologyPsychiatry

Abstract

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INTRODUCTION Although there has been general agreement that the health care costs associated with physical inactivity and/or reduced aerobic fitness are substantial (1), recent studies suggest that modulating these variables may have a profound effect upon curbing health care utilization. This commentary addresses these issues, with specific reference to our increasingly hypokinetic lifestyle, the impact of physical inactivity upon chronic diseases and escalating health care costs, and the role that structured exercise programs, increased lifestyle physical activity, improved cardiorespiratory fitness, or combinations thereof may have upon reducing health care expenditures. TECHNOLOGY'S SEDENTARY SEDUCTION Modern technological advances have increasingly emphasized comfort and convenience with the development of time-saving and labor-saving devices, focused on speed, rapid communication, improved efficiency, and increased productivity (2). In the contemporary work environment, we are generally paid to think, to provide specific sedentary skills, and to communicate or process information. The increased reliance on technology has resulted in constant pressure toward positive energy balance by discouraging physical activity. Automobiles, elevators, remote controls, and energy-saving devices such as washing machines, dishwashers, microwave ovens, self-propelled lawn mowers, automatic garage door openers, and online ordering/bill paying have helped to engineer physical activity out of daily life. Moreover, physically demanding work has been largely ousted from the workplace. Much of our days involve extended driving time, desk work, sitting on or waiting for airplanes, meetings, teleconferences, computer interactions, or operating machines or conveyors that have replaced physically demanding work. Cellular phones, dictaphones, and laptop computers have become part of our vocational garb, exacerbating our hypokinetic state (2). Relative to our leisure-time activities, popular sedentary pastimes include watching television, viewing college and professional sports, listening to mp3 players, using cell phones, engaging DVD players, playing video games, e-mailing others, searching the internet, and gambling. Recent physical activity prevalence data are particularly troubling. The prevalence of no reported leisure-time physical activity remained fairly constant from 1990 to 1996, but more recently has declined slightly among U.S. men and women (3). In 2005, approximately 24% of U.S. adults reported no leisure-time activity (4), and less than half (49%) met the U.S. Centers for Disease Control and Prevention (CDC) and the American College of Sports Medicine recommendation (i.e., "Every U.S. adult should accumulate 30 min or more of moderate-intensity physical activity on most, preferably all, days of the week.") (5). Younger people (18-24 yr of age) were more likely to meet the recommendation than were older people (65 yr and older), as were white individuals and persons with a college degree, as compared with other racial or ethnic groups or individuals with less formal education. PHYSICAL INACTIVITY: A MAJOR PUBLIC HEALTH BURDEN Hill et al. (6) suggest that the most likely explanation for the current obesity epidemic is a continued decline in energy expenditure that has not been matched by an equivalent reduction in energy intake. Other epidemiological and clinical investigations have identified physical inactivity, increased calorie consumption, and excess body weight and fat stores as common risk factors for both type II diabetes and coronary artery disease (CAD). This triad also forms the environmental stimulus for the metabolic and insulin resistance syndromes (1). According to recent estimates, physical inactivity increases the relative risk of CAD by 45%, stroke by 60%, hypertension by 30%, and osteoporosis by 59% (7). Our sedentary lifestyle annually produces ~334,000 deaths in the United States and more than 2 million deaths worldwide, representing one of the 10 leading global causes of death and disability (8). Using such information, the CDC identified physical inactivity as an actual cause of the two leading killers of all people in the United States, that is, CAD and malignant neoplasms, along with tobacco use and poor nutrition (9). Although the underlying mechanisms require additional clarification, it has been suggested that the human genome evolved within an environment of high physical activity for survival (10). In the current hypokinetic state, inherited metabolic pathways and maladaptive responses may produce metabolic derangements and varied chronic diseases (1,7,11,12). HEALTH CARE COSTS ATTRIBUTED TO PHYSICAL INACTIVITY Although numerous studies have attempted to evaluate the impact of physical inactivity upon health care costs, the results have varied widely due to differing populations and methodology. Colditz searched the Medline database to assess the economic costs of inactivity (including those attributable to obesity), along with the cost of illness (13). The direct costs of lack of physical activity, defined conservatively as absence of leisure-time physical activity, were $24 billion or 2.4% of U.S. health care expenditures. Katzmarzyk and associates conducted a systematic review of the literature and calculated the direct health care costs attributable to physical inactivity in Canada, with specific reference to CAD, stroke, colon cancer, breast cancer, type II diabetes mellitus, hypertension, and osteoporosis (14). Their analysis reveals that $2.1 billion, or about 2.5% of the direct health care costs in Canada in 1999, were attributable to physical inactivity. Further, the authors report that a 10% reduction in the prevalence of physical inactivity could potentially reduce direct health care expenditures by $150 million a year. More recently, Chakravarthy and Booth estimated that the health care costs of physical inactivity in the United States include at least $150 billion per year in direct and indirect expenditures (1). Collectively, these data convincingly support the need for additional cost-effectiveness studies, in view of the links among chronic diseases, escalating health care costs, and physical inactivity. SKYROCKETING HEALTH CARE EXPENDITURES By several indices, health care spending continues to rise at the fastest rate in our history. In 2005, total national health expenditures rose 6.9%, corresponding to twice the rate of inflation (15). Total health care spending was $2 trillion in 2005, or $6,700 per person, representing 16% of the gross domestic product (16). This trend is expected to increase at similar levels over the next decade, reaching $4 trillion in 2015, or 20% of the gross domestic product. In 2006, employer health insurance premiums increased by 7.7%, or twice the rate of inflation. The annual premium for an employer's health plan providing single coverage or coverage for a family of four averaged over $4,200 and nearly $11,500, respectively (17). If these trends continue, health care may become unaffordable, unless we find ways to implement effective preventive interventions (e.g., medications, weight reduction, healthier eating practices, and regular physical activity) to combat the rampant progression of chronic diseases (1). CARDIORESPIRATORY FITNESS, PHYSICAL ACTIVITY INTERVENTIONS, AND HEALTH CARE COSTS Until recently, few data were available to answer the following questions: 1) Does cardiorespiratory fitness correlate with the magnitude of subsequent health care expenditures, and 2) if fitness improves via a structured exercise program, increased lifestyle physical activity, or both, does the annual incidence of overnight hospital stays or physician visits decrease? Most of the previously published cost-effectiveness data were derived from reviews and analytical models, using varied populations, methodology, assumptions, and estimates, rather than via a direct evaluation of the effect of measured exercise capacity upon health care costs. To test the hypothesis that higher levels of exercise capacity would be associated with lower subsequent health care expenditures, Weiss and associates evaluated the 1-yr total medical treatment costs for 881 consecutive patients (mean age = 59 yr; 95% men) who were referred for diagnostic treadmill testing (18). In unadjusted analysis, inpatient and outpatient health care costs are incrementally lower by an average of 5.4% per metabolic equivalent (MET; 1 MET = 3.5 mL O2·kg−1·min−1) increase (P < 0.001) (Fig. 1). Multivariable analysis further demonstrates that the peak METs achieved during exercise testing proved to be the most significant predictor of cost. Collectively, these data demonstrate that a higher exercise capacity is associated with lower health care costs.Figure 1: Relationship between exercise capacity, expressed as METs, and 1-yr total health care costs in the year following the treadmill test. The fitness categories were selected at basic intervals of METs to maintain roughly equivalent patient numbers in each group (∼150-200). The data shown are the median (horizontal line) with 25th and 75th percentiles. [Adapted from Weiss J.P., V.F. Froelicher, J.N. Myers, et al. Health-care costs and exercise capacity. Chest 126:608Y613, 2004. Copyright * 2004 The American College of Chest Physicians. Used with permission.] MET, metabolic equivalent.Similarly, researchers at the Cooper Clinic/Institute conducted a prospective study of 6679 men (mean ± SD age = 44.8 ± 9.1 yr; 97% white) to examine the relationship between cardiorespiratory fitness, estimated from total treadmill test time, and health care costs (i.e., incidence of physician office visits and overnight hospital stays) during the 1-yr period before each of two preventive medicine exams (19). A subset (n = 2974) also was evaluated to assess whether improvements in fitness were associated with reduced health care expenditures. Categorization of subjects by fitness into quartiles (Q1 = least fit, Q4 = most fit) revealed an inverse relationship between fitness and health care utilization, even after adjustment for potential confounding variables. Moreover, the subset that improved their fitness by the time of the second examination had a decreased number of overnight hospital stays, as compared with those who remained unfit (Fig. 2). Fit men (Q4) as well as those who became fit demonstrated health care utilization trends that approximated a 53% reduction in direct medical costs (from overnight hospital stays).Figure 2: Inverse relationship between overnight hospital stays (per 1000 person-years) and increasing levels of fitness, after adjustment for potential confounding variables. Men who became fit also were less likely to have overnight hospital stays, as compared with their counterparts who remained unfit. [Adapted from Mitchell T.L., L.W. Gibbons, S.M. Devers, et al. Effects of cardiorespiratory fitness on healthcare utilization. Med. Sci. Sports Exerc. 36:2088Y2092, 2004. Copyright * 2004 Lippincott, Williams and Wilkins. Used with permission.]In recent years, several studies in older adults also have examined the effects of structured exercise and increased leisure-time physical activity upon health care costs. After controlling for potential confounding variables associated with medical costs, both interventions reduced the likelihood of using health care services (20,21). In another study, Medicare-eligible enrollees of a large health maintenance organization who participated in a community-based exercise program had smaller increases in annual total health care costs than similar enrollees who did not participate (+$642 vs +$1175; P = 0.05) (22). CONCLUSION Epidemiological data indicate that habitually sedentary individuals have an increased prevalence of 25 chronic diseases (8,11). The phrase "sedentary death syndrome" has been promulgated to highlight the emerging entity of sedentary lifestyle-mediated unhealthy conditions, almost all of which are chronic diseases or risk factors for chronic diseases that ultimately result in increased mortality (1). On the other hand, each 1 MET increase in exercise capacity is associated with an 8%-17% reduction in mortality (23), whereas an approximate 1000 kcal·wk−1 increase in energy expenditure appears to confer the equivalent survival benefit (24). Iestra et al. reviewed the literature regarding the effects of generally accepted lifestyle recommendations and cardioprotective medications upon mortality in patients with CAD (25). Prospective cohort studies and randomized, controlled trials of patients with documented CAD were included if they reported all-cause mortality and had at least 6 months of follow-up. Increased physical activity was associated with a statistically significant risk reduction (25%), the magnitude of which was similar to or greater than that observed with low-dose aspirin (18%), statins (21%), ß-blockers (23%), and angiotensin converting enzyme inhibitors (26%) after myocardial infarction. Today, many in the medical community embrace a common response in the battle against modern chronic diseases, that is, the extrapolation of contemporary pharmacotherapies and technologies as a first-line strategy to stabilize overt cardiovascular disease. This approach sends the wrong message to the population at large - that there is a "quick fix" for cardiovascular health in the form of a magic bullet. Unfortunately, the independent and additive benefits of lifestyle modification are often overlooked and underemphasized (26). Because drug therapy and coronary revascularization have been largely unsuccessful in halting and reversing the epidemic of cardiovascular disease, more emphasis must be placed on novel approaches to implement current primary/secondary prevention guidelines (27,28), which require attacking conventional risk factors and their underlying environmental causes (e.g., physical inactivity). The challenge for physicians and other health care providers is to refer increasing numbers of patients to home, club, or medically based exercise programs so that many more individuals may realize the cardioprotective and general health benefits that regular physical activity can provide (29). Not doing so constitutes a direct violation of one of the central tenets of the Hippocratic oath, that is, do no harm (1). Exercise is medicine, and for the ~70% of U.S. adults who are not regularly physically active, the prescription remains unfilled.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.344
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations17
Published2008
Admission routes1
Has abstractyes

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