The benefits of regular participation in physical activity are well-established and consistently outweigh the risks of participation (10). Musculoskeletal injuries are the most common adverse event associated with physical activity participation, and are seldom severe (10). An individual bout of activity also carries an elevated risk of acute myocardial infarction (AMI) or sudden cardiac death (SCD). While severe, these events are rare and most commonly occur among habitually inactive people performing vigorous-intensity activity (3, 8, 10); the risk of AMI or SCD during activity is sharply attenuated by progressive, regular physical activity participation (10). Among adults, occlusive coronary artery disease is usually the underlying cause of activity-associated AMI and SCD (7). Because of this, attempts to identify adults at risk for activity associated AMI or SCD have often included cardiovascular disease (CVD) risk factor assessment (1).

The American College of Sports Medicine (ACSM) recently released an updated exercise preparticipation screening algorithm (henceforth: ACSM algorithm) that focuses on 1) the respondent’s current exercise participation 2) the presence of signs/symptoms or known history of cardiovascular diseases and 3) the desired exercise intensity, and in contrast to previous screening tools, does not assess cardiovascular risk factors (11). These changes came about in part because of indications that CVD risk factor-based screening may be overly conservative and unnecessarily refer adults for medical clearance before exercise participation (15). Using data from the 2001–2004 National Health and Nutrition Examination Survey (NHANES), the ACSM/American Heart Association Preparticipation Questionnaire (AAPQ) could potentially refer 95% of all US adults aged 40 years or older to a medical provider before beginning an exercise program (15), and 68% of US adults aged 40 years or older could be referred using the Physical Activity Readiness Questionnaire (PAR-Q) (15).

Additionally, The AAPQ and PAR-Q predate the 2008 Physical Activity Guidelines for Americans, which, like the ACSM algorithm, focus not on CVD risk factors, but on history of chronic diseases, the symptoms thereof, and current activity levels to inform the need for medical involvement (13). To date, referral estimates for the new ACSM algorithm are not available, so its performance relative to the AAPQ and PAR-Q is unknown. Therefore, the purpose of this research was to estimate the proportion of US adults aged 40 years or older that would be referred for preparticipation medical clearance using the ACSM algorithm in order to place this tool in context with previous findings.

The descriptive characteristics for this sample have been previously described (15) and are summarized here. Complete questionnaire responses were available for 3459 women (97.9% of total) and 3326 men (98.5% of total), accordingly, the demographic characteristics were quite similar to the general adult population over 40 years of age in the US from this time period. Based on the algorithm definition above, 47.1% reported enough leisure time activity to be classified as current exercisers.

The distribution of the population across the six categories of the 2015 ACSM algorithm and the total referral proportions are presented in Table 2. Among those reporting no current exercise, 18.0% reported no history or current symptoms, 3.0% reported a positive history but no current symptoms, and 32.0% reported current symptoms. Among those currently exercising, 25.1% reported no history or current symptoms, 2.6% reported a positive history but no current symptoms, and 19.3% reported current symptoms. With this distribution across categories, 43.1% of the population would receive no referral for medical clearance before beginning or continuing exercise, 2.6% would be referred for medical clearance before engaging in vigorous intensity exercise, and 54.2% would be referred for medical clearance before beginning or continuing any exercise.

The referral proportions stratified by sex and age group are presented in Table 3. Across four of the seven age groups and for the sample as a whole, women would be referred for medical clearance before any exercise more frequently than men (all p<0.05). The differences between men and women across age groups was less clear for referral before vigorous intensity exercise, but no group exceeded a 7% referral proportion for this outcome.

Combined results from the ACSM algorithm, the AAPQ, and the PAR-Q are presented in Figure 2, stratified by age group. Across all age groups, the AAPQ would refer more respondents (94.5%) than either the PAR-Q (68.4%) or the ACSM algorithm, including those referred only before vigorous exercise (2.6%) and those referred before any exercise (54.2%). When considering those referred before any exercise, the ACSM algorithm and the PAR-Q performed similarly in the 40–44 year age group (42.9% and 48.8% referred, respectively), then the referral proportions diverged with increasing age. For those aged 70 years or older, the ACSM algorithm would refer 70.9% before any exercise and the PAR-Q would refer 93.2%.

According to the cross-tabulation presented in Table 4, 37.7% of respondents were referred by the AAPQ but were not referred by the ACSM algorithm. Only one respondent (<0.1% of the weighted total) was not referred based on the AAPQ but was referred before vigorous-intensity exercise based on the ACSM algorithm. Further, 19.0% of respondents were referred based on the PAR-Q but were not referred based on the ACSM algorithm. Only 7.4% of respondents were not referred based on the PAR-Q but were referred based on the ACSM algorithm (0.5% before vigorous-intensity exercise only, 6.9% before any exercise).

The proportion that reported any current symptoms was higher than expected (54.2%) and further investigated. Shortness of breath was the most commonly reported symptom: 72.0% of those with any symptom reported shortness of breath. It is likely that many reported cases of shortness of breath are due to benign causes other than worsening CVD. Monte Carlo-based sensitivity analyses suggested shortness of breath was an important referral trigger. When the prevalence of shortness of breath was randomly increased 10% in the sample, the proportion referred for clearance before any exercise increased 9% (five percentage points) from 54% to 59%. When the prevalence was decreased by 10%, the proportion referred before any exercise decreased 2% (one percentage point) to 53% (not shown).

Using the same methods and assumptions as a previous evaluation (15), the ACSM algorithm would refer fewer US adults aged 40 years or older for medical clearance than either the AAPQ or the PAR-Q. Previous research suggested that 95% of this demographic group would be referred for a physician visit under the AAPQ scoring criteria. While additional validation is needed, this analysis suggests 37.7% of adults in this age range that would be referred based on the AAPQ would not be referred based on the ACSM algorithm. This reduction in referrals may mitigate a potentially important barrier to exercise adoption.

The lower referral proportion in the ACSM algorithm is likely attributable to the removal of CVD risk factors from the prescreening criteria. Because of the widespread prevalence of CVD risk factors (4) and the rarity of exercise-associated CVD events (12), CVD risk factor assessment is likely a poor predictor of these events. For example, the CDC estimates that 70 million American adults have high blood pressure, compared to 600,000 who die of CVD each year (0.9% of 70 million) (5, 6), and only a small percent of these CVD deaths occur during exercise (12). Assessment of CVD risk factors therefore may overestimate the proportion of people at risk for exercise-associated CVD complications. The removal of CVD risk factors also aligns the ACSM algorithm with the 2008 Physical Activity Guidelines for Americans, which place focus on diagnosed chronic diseases and symptoms thereof:

As with the ACSM algorithm, the Guidelines also consider a person’s initial level of activity, progression of activity, and development of symptoms when considering medical involvement:

While designed primarily for fitness professionals, the ACSM algorithm is more aligned with the public health recommendations set forth in the Physical Activity Guidelines than previous screening tools.

The ACSM algorithm differentiates referrals based on the desired exercise intensity of the respondent, and the proportion that would be referred before any exercise was much higher than the proportion that would be referred only before vigorous intensity exercise. This is likely attributed to two factors. First, a recommendation for clearance only before vigorous exercise is given to one highly specific group in the algorithm: those who have previously had cardiovascular, metabolic, or renal disease, but have recovered or stabilized to the point that they now perform regular exercise and are free of symptoms. They warrant referral under the algorithm only before increasing to vigorous intensity. Second, in contrast to the very specific group previously mentioned, three of the six categories in the algorithm receive a recommendation for clearance before any exercise. These include any respondents that report a current symptom (both physically active and inactive) and those that are currently inactive and have a history of cardiovascular, metabolic, or renal disease. Among adults aged 40 years and older, this includes a considerable proportion of the population. Samples with more diverse age ranges would likely exhibit different referral proportions.

Using the present methods, the referral proportion of the ACSM algorithm was more similar to the PAR-Q than the AAPQ, which was likely because of the similarity of these two instruments. For example, both the ACSM algorithm and PAR-Q place emphasis on a history of CVD, current chest pain, and dizziness or lack of balance. Further, the ACSM algorithm does not consider age and the PAR-Q only considers age as important if the person is currently inactive. The 19.0% of respondents that were referred based on the PAR-Q but not referred based on the ACSM algorithm is likely due to the inclusion of bone and joint issues and medication use for hypertension in the PAR-Q, neither of which are considered in the ACSM algorithm.

This report has several strengths. First, the exact methods and dataset from a previous evaluation of the AAPQ and PAR-Q were used, allowing comparison of referral proportions under identical assumptions (15). Second, the NHANES dataset is representative of the non-institutionalized US population over 40 years of age; this study provides information about referral performance in the general public. Finally, this method allows for rapid comparison of screening tools at low cost. Several limitations should also be noted. First, several symptoms on the ACSM algorithm could not be assessed, but analyses suggested that assessed symptoms tended to cluster together, which could limit the impact of unassessed symptoms. Nevertheless, omission of symptoms could cause an underestimation of referral proportion. Second, we were unable to assess referral proportions in adults under 40 years of age. Third, as with the previous report (15), this method assumes that people will answer a pre-screening questionnaire the same way they answered comprehensive health interview questions, and the validity of this assumption is unknown. Finally, the criteria for participating in regular exercise in the ACSM algorithm is different from the 2008 Physical Activity Guidelines (13), but a post-hoc analysis that defined regular exercise as 150 minutes per week of at least moderate intensity leisure-time activity instead of 90 minutes per week suggested little impact on referral status (43.1% not referred [43.1% originally], 2.3% referred before vigorous exercise [2.6% originally], and 54.6% referred before any exercise [54.2% originally]).

In conclusion, the revised ACSM algorithm referred fewer NHANES respondents for medical clearance compared to the AAPQ. Definitive confirmation of this finding would require comparison of referral proportions in actual practice in exercise facilities. While additional validation is needed to determine how well the algorithm identifies those at risk for CVD complications during exercise, a lower referral proportion may mitigate an important barrier to exercise adoption, especially among those who undergo a preparticipation screening program based on ACSM recommendations. Considering that 73% of ACSM-certified Health Fitness Specialists report performing some type of preparticipation screening (2), the potential use of this new algorithm is considerable.