- Email: [email protected]
Development of Global Reference Standards for Directly Measured Cardiorespiratory Fitness: A Report From the Fitness Registry and Importance of Exercise National Database (FRIEND)
ORIGINAL ARTICLE
Development of Global Reference Standards for Directly Measured Cardiorespiratory Fitness: A Report From the Fitness Registry and Importance of Exercise National Database (FRIEND) James E. Peterman, PhD; Ross Arena, PhD; Jonathan Myers, PhD; Susan Marzolini, PhD; Robert Ross, PhD; Carl J. Lavie, MD; Ulrik Wisløff, PhD; Dorthe Stensvold, PhD; and Leonard A. Kaminsky, PhD Abstract Objective: To begin the process of developing global reference standards for adults from directly measured cardiorespiratory fitness (CRF). Methods: Percentiles of maximal oxygen consumption (VO2max) for men and women were determined for each decade from 20 through 79 years of age using International data from the Fitness Registry and Importance of Exercise: A National Database (FRIEND-I) along with previously published data from seven studies. FRIEND-I data from January 1, 2014, through January 1, 2019, included 11,678 maximal treadmill tests from three countries, whereas the previously published reports included 32,329 maximal treadmill tests from six countries. Results: FRIEND-I data revealed significant differences between sex and age groups for VO2max (P<0.01). For the 20- to 29-years of age group, the 50th percentile VO2max in men and women were 49.5 mLO2,kg-1,min-1 and 40.6 mLO2,kg-1,min-1, respectively. VO2max declined an average of 9% per decade with the 50th percentile for the 70- to 79-years of age group having a VO2max of 30.8 mLO2,kg-1,min-1 in men and 25.0 mLO2,kg-1,min-1 in women. These results were similar in magnitude and direction to the previously published literature. Within both the FRIEND-I and previously published data there were CRF differences between countries. Conclusion: This report begins to establish global reference standards for CRF. Continued development of FRIEND-I will increase global representation providing an improved ability to identify and stratify CRF risk categories. ª 2019 Mayo Foundation for Medical Education and Research
ardiorespiratory fitness (CRF) is an important marker for health and quality of life. Greater levels of CRF are associated with decreased allcause, cardiovascular disease (CVD), and cancer mortality.1-7 Furthermore, greater levels of CRF are associated with decreased risks for numerous chronic diseases, such as depression, diabetes, obesity, CVD, and even some forms of cancer.4,8,9 As such, a recent American Heart Association (AHA)
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Scientific Statement concluded that CRF should be considered a clinical vital sign that is regularly assessed similar to other established chronic disease risk factors.10 Increasing the recognition of CRF as an important clinical vital sign has been limited by a lack of uniform standards for interpretation. This was the impetus for an AHA policy statement which suggested establishing a national CRF database.10 This policy statement was the impetus for the creation of the
Mayo Clin Proc. n XXX 2019;nn(n):1-10 n https://doi.org/10.1016/j.mayocp.2019.06.013 www.mayoclinicproceedings.org n ª 2019 Mayo Foundation for Medical Education and Research
From the Fisher Institute of Health and Well-Being, Ball State University, Muncie, IN (J.E.P., L.A.K.); Department of Physical Therapy and Integrative Physiology Laboratory, College of Applied Science, University of Illinois, Affiliations continued at the end of this article.
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Fitness Registry and the Importance of Exercise: A National Database (FRIEND).11 The data within FRIEND includes only directly measured CRF from exercise tests that meet objectively verified criteria for maximal effort. These reference standards assist clinicians and other health professionals with interpreting and communicating CRF results to patients in a meaningful way. In the initial FRIEND reports12,13 CRF reference standards for men and women of different ages from the United States were compared with published standards from Norway,14,15 Finland,16 and Lithuania.17 Additional evidence, including a FRIEND report on nonexercise prediction equations, has also included CRF comparisons between the United States and Brazil.18,19 These comparisons clearly revealed the presence of international heterogeneity in CRF values, and thus underline the need for developing global CRF reference standards. Recently, Nauman et al.20 presented global reference standards using estimated CRF as there was no database of directly measured global CRF values. However, the estimated CRF global standards were higher than those presented in large cohort studies in which CRF was directly measured.12-15,18,21-23 These differences could be due to differences in study subject characteristics or the wellknown errors associated with predicting CRF from non-exercise test variables.24,25 Therefore, a global normative CRF reference standard based on directly measured CRF is needed to provide more accurate standards of comparison for researchers and clinicians who directly measure CRF. A registry of global CRF data will also provide an opportunity to improve non-exercise algorithms that can then be used to estimate CRF in clinical settings when direct measure is not possible or feasible. Whereas the original goal of FRIEND was to create a US registry for adults,11 the International data from the FRIEND (FRIEND-I) cohort now includes data from several international sources. Publications with reported reference values from international sites provide an additional opportunity to compare international CRF values. 2
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Thus, the purpose of the present analysis is to begin the process of establishing global reference standards for directly measured CRF using data from FRIEND-I along with previously published data. This report will focus on data obtained from directly measured CRF using cardiopulmonary exercise testing (CPX) with the treadmill as the mode of exercise. METHODS The data collection and management for the FRIEND registry has been reported previously.12 Briefly, the FRIEND registry is composed of data from high-quality laboratories performing CPX administered by experienced personnel. Although laboratories varied in terms of equipment, protocols, and definitions of CRF (eg, maximum oxygen consumption [VO2max] determined from different time averages), all laboratories conducted testing in accordance with published guidelines.26 Each contributing laboratory obtained local research ethics board approval before submitting deidentified, coded data to the data coordinating center at Ball State University. From Ball State University, data were forwarded to the core laboratory at the University of Illinois at Chicago, which has institutional review board approval for maintaining the database. Data from each contributing laboratory were reviewed by both the coordinating center and core laboratory to ensure CRF values were within expected normal ranges before the data were added to FRIEND-I. FRIEND-I Cohort The present analysis includes 11,678 treadmill tests from 14 participating laboratories (see Acknowledgments). Geographic representation includes three countries: Canada (n¼1431), Norway (n¼3668), and the United States (n¼6588). Whereas FRIENDI includes data from individuals with a range of characteristics, specific inclusion criteria were used to create the present cohort. Inclusion criteria were: (1) no pre-existing diagnosis of CVD; (2) no pre-existing chronic obstructive pulmonary disease; (3) maximal CPX performed on a treadmill; XXX 2019;nn(n):1-10
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(4) participants were ages 20 to 79 years; and (5) there was a peak respiratory exchange ratio of greater than or equal to 1.10 to indicate a maximal effort. Literature Cohort The literature cohort was created from previously published studies with the following criteria: (1) subject pool of apparently healthy individuals with no CVD; (2) reported VO2max via cardiopulmonary gasexchange measurement from a maximal exercise test performed on a treadmill; and (3) reported VO2max separated by sex and age grouped by decade (ie, 20 to 29 years, 30 to 39 years, etc). Given that exercise mode influences the determination of VO2max,27 two studies were excluded as the authors combined treadmill and cycling data.28,29 Seven published studies were included in the literature cohort, representing six different countries: Brazil,18 Canada,21 Israel,23 Japan,22 Norway,14,15 and the United States.12 Inclusion and exclusion criteria were specific to each study (details provided in Supplemental Table); however, participants in each study were reported as being in good general health. The majority of studies presented CRF reference values in a table.12,14,15,18,21 However, the study from Japan provided reference values in the form of regression equations,22 which were used to calculate CRF based on the middle of each age range (ie, 25 years old, 35 years old, etc) for comparison in this report. Also, the study from Israel23 included no table of reference values for those aged 31 to 60 years and the provided regression equations were not legible. Therefore, the CRF for age groups within this range were estimated by drawing lines connecting age and absolute VO2max on the manuscript figures. The estimated absolute VO2max was then divided by the average body weight for each group. Additionally, age groups in the study from Israel were different by þ1 year but were still used within the age grouping of the present study. In the case of Norway, in which there were two studies, weighted averages were used to calculate a national average. To Mayo Clin Proc. n XXX 2019;nn(n):1-10 www.mayoclinicproceedings.org
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obtain weighted averages within each age and sex category, CRF values from each individual study were multiplied by their respective sample size, added together, and then divided by the combined sample size. Weighted averages were also used to determine a second global reference standard to compare to the reference values from within the FRIEND-I database. Statistical Analysis All statistical analyses were performed using SPSS software (version 25, IBM Corporation, Armonk, NY). Two-way analysis of variance was used to compare differences in CRF values between sex groups and across age groups within the FRIEND dataset. When significant differences were detected, the Tukey test was used for post hoc analysis. Statistical significance was designated at the P less than 0.05 level. Continuous data are presented throughout the paper as mean SD whereas categorical data are reported as frequencies (percentages). RESULTS The FRIEND-I cohort used for the CRF analysis included tests on 6457 men and 5219 women, across an age range of 20 to 79 years. Descriptive characteristics of the cohort, by sex and age groups, are provided in Table 1. Summaries of the values from each country are provided in Table 2. In both men and women, the highest CRF values reaching statistical significance were from Norway (P<.01), averaging 43% higher than Canadian values and 28% higher than US values. The literature cohort included tests on 21,391 men and 10,938 women (Table 3). Summaries of the reference values from previously published literature for treadmill tests are presented in Table 3. As individual data from each study were not available, statistical comparisons were not made. Observationally, however, for both men and women, CRF values from Norway were consistently the highest across all age groups, averaging 11% higher than the next highest country. Additionally, the Israeli study23 only reported data with men; these
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TABLE 1. Descriptive Characteristics of the FRIEND-I Cohort for the Treadmill Analysisa Age group, y Sex
20-29
30-39
40-49
50-59
60-69
70-79
Men Age, y Height, cm Weight, kg
(n¼756) 24.03.0 179.77.5 80.714.9
(n¼1128) 35.22.9 179.36.6 87.116.5
(n¼1606) 44.52.9 178.87.2 87.815.7
(n¼1409) 54.42.8 178.08.2 88.916.0
(n¼924) 63.82.7 176.68.9 87.616.0
(n¼634) 72.62.3 176.09.4 81.311.6
(n¼562)
(n¼909)
(n¼1272)
(n¼1226)
(n¼678)
(n¼572)
24.32.7 166.66.5 66.914.4
35.32.8 165.96.1 71.617.2
44.82.8 164.96.3 73.017.0
54.32.8 163.58.0 74.816.7
63.92.7 162.66.1 73.714.4
72.72.3 162.46.2 67.811.4
Women Age, y Height, cm Weight, kg a
FRIEND-I ¼ International data from the Fitness Registry and the Importance of Exercise: A National Database.
CRF values averaged 16% lower than the next lowest country. Reference standards using FRIEND-I data and the literature data are provided in Table 4. The previously published global reference standards using estimated CRF20 are presented as a comparison. There were significant differences between sex and age groups for treadmill VO2max from the FRIEND-I dataset (P<.001), with men having on average a 26% greater VO2max than women. The highest CRF was in the 20- to 29- yearold age group; within FRIEND-I, average
VO2max was 49.39.9 mLO2,kg-1,min-1 for men and 40.29.2 mLO2,kg-1,min-1 for women. For men, both the FRIEND-I and literature cohorts had an average rate of decline of 9% per decade. For women, CRF decreased by 9% per decade in the FRIENDI cohort whereas the literature cohort decreased by 10%. Observationally, the global reference using estimated CRF was greater than either the FRIEND-I or literature cohort determinations. Box plots of the FRIEND-I data by age and sex are presented in the Figure.
TABLE 2. Comparison of CRF Reference Values Determined From a Treadmill Test Within the FRIEND-Ia Dataset, Separated by Country (MeanSD)b Age group, y Sex
20-29
Men Canada
30-39
40-49
50-59
60-69
70-79
34.18.0
29.47.2
28.66.3
26.76.0
23.65.3
(n¼43)
(n¼89)
48.97.6
46.67.2
(n¼144)
(n¼207)
(n¼64)
42.27
38.86.3
33.26.3
Norway
54.37.7 (n¼184)
(n¼286)
(n¼413)
(n¼350)
(n¼210)
(n¼441)
United States
47.610.0
42.39.9
38.39.1
33.78.7
29.67.4
26.76.5
(n¼572)
(n¼799)
(n¼1104)
(n¼915)
(n¼507)
(n¼129)
28.06.4
27.16.1
25.05.0
23.25.1
20.44.1
(n¼88)
(n¼217)
(n¼280)
(n¼212)
(n¼76)
39.96.5
38.16.7
34.85.7
31.65.2
27.75.5
Women Canada
a
Norway
43.27.6 (n¼184)
(n¼326)
(n¼401)
(n¼327)
(n¼147)
(n¼399)
United States
38.79.6
31.38.2
28.57.7
24.56.0
21.75.2
19.53.7
(n¼378)
(n¼495)
(n¼654)
(n¼619)
(n¼319)
(n¼97)
FRIEND-I ¼ International data from the Fitness Registry and the Importance of Exercise: A National Database. Values reported in mLO2,kg-1,min-1.
b
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TABLE 3. Comparison of CRFa Reference Values Determined From a Treadmill Test in Previously Published Literature, Separated by Country (MeanSD)b Age group, y Sex Men Brazil18 Canada21 Israel23,c Japan22,d Norway14,15,e United States12
20-29
30-39
40-49
50-59
60-69
70-79
45.07.5
43.57.9
41.67.8
38.67.9
33.77.1
28.76.7
(n¼1201)
(n¼4427)
(n¼4383)
(n¼1728)
(n¼362)
(n¼48)
d
40.67.3
38.47.0
35.26.5
31.64.2
d
(n¼141)
(n¼398)
(n¼235)
(n¼42)
37.67.4
34.3
31.2
26.9
25.05.0
(n¼98)
(n¼603)
(n¼492)
(n¼188)
(n¼43)
48.3
43.2
38.2
33.1
28
22.9
(n¼18)
(n¼26)
(n¼17)
(n¼16)
(n¼17)
(n¼8)
53.5
48.6
46.5
41.7
37.7
34.1
d
(n¼237)
(n¼398)
(n¼617)
(n¼554)
(n¼383)
(n¼100)
47.611.3
43.09.9
38.89.6
33.89.1
29.47.9
25.87.1
(n¼513)
(n¼963)
(n¼1327)
(n¼1078)
(n¼593)
(n¼137)
Women Brazil18 Japan22,c Norway14,15,d United States12
36.96.6
36.07.0
34.77.1
31.46.5
26.55.7
23.45.9
(n¼732)
(n¼2028)
(n¼1985)
(n¼624)
(n¼128)
(n¼14)
35.5
33.4
31.3
29.2
27.1
25.1
(n¼19)
(n¼14)
(n¼18)
(n¼19)
(n¼25)
(n¼7)
42.6
39.6
37.6
33.8
30.6
26.2
(n¼252)
(n¼422)
(n¼579)
(n¼507)
(n¼299)
(n¼94)
37.610.2
30.98.0
27.97.7
24.26.1
20.75.0
18.33.6
(n¼410)
(n¼608)
(n¼843)
(n¼805)
(n¼408)
(n¼98)
CRF ¼ cardiorespiratory fitness. Values reported in mLO2,kg-1,min-1. c Values for ages 30-59 years are estimated as described in the Methods. Original study did not present meanSD for ages 31-60 years in table form; also, age group classifications were 20-30, 31-40, 41-50, 51-60, and 61-70 years. d Study did not present meanSD. Values presented were estimated as described in the Methods. e Weighted averages from Loe et al14 and Edvardsen et al15 used to determine national mean. a
b
DISCUSSION The present analysis begins to establish global normative reference values from directly measured CRF. Reference values were created based on FRIEND-I as well as the previously published literature. Little difference was observed between the literature and FRIEND-I cohort values. Within FRIEND-I, men had a VO2max which was 26% higher compared with women whereas the literature cohort suggests a difference of 25%. The age-related rate of decline in CRF was also similar between the literature and FRIEND-I cohort values, averaging a decrease of 9% to 10% per decade. Although the literature cohort had a greater global Mayo Clin Proc. n XXX 2019;nn(n):1-10 www.mayoclinicproceedings.org
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representation, the current FRIEND-I database includes data from two of the seven previously published studies,12,14 which could contribute to the similarities between values. Nonetheless, these similarities suggest data within FRIEND-I are representative of weighted averages from the literature cohort. This report also highlights the international heterogeneity in directly measured CRF similar to a previous report using estimated CRF.20 The CRF values from Norway14,15 were consistently higher compared with other countries. Additionally, whereas men and women from Brazil, Canada, and Norway had age-related CRF declines of 8% to 9% per decade, greater declines were
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TABLE 4. Normative Reference Standards for Treadmill Tests From the FRIEND-Ia Cohort, the Literature Cohort, and Nauman et al (2017)20 (Estimated CRF)b Age group, y Sex
20-29
Men FRIEND cohort
49.39.9
43.79.9
(n¼756)
(n¼1128)
46.3
42.8
(n¼2067)
Literature cohort Nauman et al20,c
30-39
40-49
50-59
60-69
70-79
40.09.6
35.39.1
31.18.1
30.97.2
(n¼1606)
(n¼1409)
(n¼924)
(n¼634)
40.6
36.9
32.6
29.1
(n¼6558)
(n¼7234)
(n¼3799)
(n¼1,440)
(n¼245)
56.3
53.7
50.8
47.7
44.6
40.6
40.29.2
34.18.7
31.38.5
27.47.2
24.36.4
25.46.2
(n¼562)
(n¼909)
(n¼1272)
(n¼1226)
(n¼678)
(n¼572)
38.1
35.5
33.5
29.0
25.2
22.3
(n¼1413)
(n¼3072)
(n¼3425)
(n¼1955)
(n¼860)
(n¼199)
45.1
42.5
40.4
37.5
34.8
31.3
Women FRIEND cohort Literature cohort Nauman et al20,c
CRF ¼ cardiorespiratory fitness; FRIEND ¼ Fitness Registry and the Importance of Exercise: A National Database; FRIEND-I ¼ International data from the Fitness Registry and the Importance of Exercise: A National Database. b Values reported in mlO2,kg-1,min-1. c Sample sizes not provided by Nauman et al20 for each group. a
observed for Japanese men (14% per decade) and both sexes in the US data (11% to 13% per decade). There are a multitude of potential reasons for the international heterogeneity in CRF. Physical activity habits are a significant determinant of CRF30 and, as such, international differences in physical activity could explain these disparities. However, Brazil had the lowest prevalence of physical activity of the countries within the literature analysis,31 yet does not have the lowest CRF values, suggesting other factors may also be important. It is also possible that the smaller sample sizes and geographic representation for studies from some countries, such as Canada, may have biased the CRF values. Another potential contributor to the heterogeneity in CRF is the health status of the cohorts. Whereas the literature cohort included apparently healthy individuals, the definitions varied (Supplemental Table [available online at http://www. mayoclinicproceedings.org]). For example, in the Norwegian studies, Edvardsen et al15 excluded individuals with two or more CVD risk factors when participants were older than 49 years of age and Loe et al14 excluded those taking blood pressure 6
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medications. More lenient criteria were used in the study from the United States in that participants could have CVD risk factors but not actual CVD and participants were not excluded based on medications.12 Furthermore, within the FRIEND-I data, body mass index differed between the countries, with Canada having the highest (29.9 kg,m-2) and Norway having the lowest (25.6 kg,m-2). These differences suggest the cohorts from Norway may have been healthier which may have contributed to higher CRF values. Methodological limitations associated with comparing CRF highlight the need to continue developing a global registry of CRF data to reduce potential bias of national CRF values and to improve international comparisons. The AHA recommends that CRF be considered a clinical vital sign.10 To improve the prognostic utility of CRF, it is important to establish objective CRF reference standards from cases directly measured by CPX, rather than relying on estimated CRF reference standards. For example, both the FRIEND and literature cohort values were lower than those reported by Nauman et al20 using estimated CRF with differences XXX 2019;nn(n):1-10
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VO2max (mlO2·kg–1·min–1)
80 70 60 50 40 30 20 10 0
A 80 VO2max (mlO2·kg–1·min–1)
increasing in magnitude with age. In the 70- to 79-year-old age group, reference values for both men and women using estimated CRF were ~34% higher than the directly measured CRF values, which could alter treatment plans from clinicians or other health professionals. The higher estimated CRF values could be due to data collection methods with volunteers participating as they were more interested in CRF and consequently had a higher CRF. Estimated values could also be higher due to errors associated with prediction equations.24,25 A database of directly measured CRF would improve global reference standards and also provide an opportunity for future research to improve non-exercise algorithms for estimating CRF in settings when direct measure is not feasible. Epidemiologic research has often identified a CRF threshold of 5 to 6 metabolic equivalents (METs) below which the risk for all-cause mortality greatly increases.10 However, a nonspecific CRF threshold can be problematic32 as the meaning of 6 METs (ie, 21 mLO2,kg-1,min-1) is markedly different depending on the age and sex of an individual. For example, using the percentile data, a VO2max of 21 mLO2,kg1 ,min-1 would place a 65-year-old man into the 10th percentile, a 65-year-old woman into the 30th percentile, and a 25-year-old man below the first percentile. Thus, using reference standards by age and sex, as presented in this study, enhances the interpretation of CRF by researchers or clinicians. Additionally, it is important to recognize that these standards are based on directly measured CRF from CPX. A CRFderived risk threshold may also vary between countries. For example, it was not uncommon across the age groups for CRF values to vary between countries by -1 -1 e 3.5 mLO2,kg ,min , or 1 MET. This 1 MET difference has previously been shown to be associated with decreased health care costs,33 and a decreased risk (8% to 35%) for mortality1,10,34-36 and could partly explain the lower noncommunicable disease mortality rates observed for Norway.37 CRF is inversely associated with mortality in
70 60 50 40 30 20 10 0 20-29
B
30-39
40-49 50-59 Age group (y)
60-69
70-79
FIGURE. Box plots of measured maximal oxygen uptake (VO2max) in the International data from the Fitness Registry and the Importance of Exercise: A National Database for men (A) and women (B). Values are reported in mLO2,kg-1,min-1.
both the United States1 and Norway,38 despite CRF differences between the two countries. Thus, relative CRF changes within countries may be more important than absolute changes in determining health risk and risk thresholds for CRF may be countrydependent. The strength of the present study is that it presents international CRF comparisons and begins to establish global normative CRF reference values derived from CPX, the gold-standard assessment of exercise capacity. There were, however, some limitations that should be addressed. The determination of the global reference values was based on a relatively small number of
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countries and the ethnicity was predominantly white (e89%). This is due to the limited range of ethnicities available in the literature as well as within FRIEND-I. Further, within FRIEND-I and the literature, data come primarily from developed countries, although the actual educational and economic status of participants is either unknown or not reported. Despite small sample sizes and estimates of CRF, data from Israel and Japan were included to increase the geographic representation of the literature cohort. The health status of individuals within FRIEND-I may also not be representative of countries as the body mass index for Canadian adults within FRIEND-I (29.9 kg,m-2) is higher than the country average presented in a recent report (27.2 kg,m-2).37 The global representation of FRIEND-I will improve with continued development of the registry. Additionally, although all data were from experienced laboratories and test effort was objectively determined, differing testing protocols, equipment, and definitions of test effort could have impacted the determination of CRF. Individual data were also not available from the literature cohorts, so statistical tests were not performed, and only observational comparisons were made for the different countries. Also, as the CRF data is presented as VO2max normalized to body weight, it is possible the observed differences between countries and ages are influenced by variations in body weight. Certainly, further study of the potential role of differences in body weight on differences in CRF is warranted. Lastly, cycling is another mode of exercise used when determining CRF and can result in different values.13,27 Future research is needed to create global reference values for cycling tests. CONCLUSION International heterogeneity exists in directly measured CRF and suggests the need for global normative CRF reference values. FRIEND was created with a focus on establishing normative reference values for the United States, but with the addition of international data, is now well positioned to 8
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meaningfully contribute to developing global reference standards. Certainly, reference standards created using the data within FRIEND-I are similar to those created when using data from the literature, although potential limitations exist. Continued development of FRIEND-I is needed to provide greater representation from around the world. The beginnings of global normative CRF reference values presented will assist with continued investigations of international CRF and health comparisons as well as provide researchers and clinicians with improved reference standards to assist with classification and treatment of patient populations. ACKNOWLEDGMENTS FRIEND-I Consortium Contributors are as follows: Ball State University (Leonard Kaminsky), Brooke Army Medical Center (Kenneth Leclerc), Cone Health (Paul Chase), Johns Hopkins University (Kerry Stewart), Pennington Biomedical Research Center (Timothy Church), Southern Connecticut State University (Robert Axtell), University of Illinois at Chicago (Jacob Haus), University of Tennessee, Knoxville (David Bassett), Taylor University (Erik Hayes), University of Kansas Medical Center (Sandy Billinger), Brigham and Women’s Hospital (Amil Shah), Queens University (Robert Ross), KITE, Toronto RehabUniversity Health Network (Susan Marzolini, Rene Belliard, and Noah Koblinsky), the Nord-Trøndelag Health Study (HUNT) which is a collaboration between the HUNT Research Centre (Faculty of Medicine and Health Sciences at the Norwegian University of Science and Technology), the Nord-Trøndelag County Council, Central Norway Health Authority and the Norwegian Institute of Public Health (Ulrik Wisløff), and the Norwegian University of Science and Technology (Dorthe Stensvold, Ulrik Wisløff). SUPPLEMENTAL ONLINE MATERIAL Supplemental material can be found online at http://www.mayoclinicproceedings.org. XXX 2019;nn(n):1-10
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Supplemental material attached to journal articles has not been edited, and the authors take responsibility for the accuracy of all data. Abbbreviations and Acronyms: AHA = American Heart Association; CRF = cardiorespiratory fitness; CVD = cardiovascular disease; CPX = cardiopulmonary exercise testing; FRIEND = Fitness Registry and the Importance of Exercise: A National Database; FRIEND-I = International data from the Fitness Registry and the Importance of Exercise: A National Database; MET = metabolic equivalent; VO2max = maximal oxygen consumption Affiliations (Continued from the first page of this article.): Chicago, IL (R.A.); Division of Cardiology, Veterans Affairs Palo Alto Healthcare System and Stanford University, CA (J.M.); KITE, Toronto Rehab-University Health Network, Ontario, Canada (S.M.); School of Medicine, Department of Endocrinology and Metabolism, Faculty of Health Sciences, Queens University, Kingston, Ontario, Canada (R.R.); John Ochsner Heart and Vascular Institute, Ochsner Clinical School, The University of Queensland School of Medicine, New Orleans, LA (C.J.L.); and the Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway (U.W., D.S.).
Potential Conflicts of Interest: The authors report no conflicts of interest. Grant Support: Partial support for this project was provided by TKC Global (L.K.; grant number GS04T11BFP0001). This project was also partially supported by Central Norway Regional Health Authority, St Olav Hospital, Trondheim, Norway, Research Council of Norway, and The K.G. Jebsen foundation for medical research, Norway. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Correspondence: Address to Leonard A. Kaminsky, PhD, Fisher Institute of Health and Well-Being, Ball State University, 2000 W. University Ave, Muncie, IN 47306 ([email protected]).
REFERENCES 1. Imboden MT, Harber MP, Whaley MH, Finch WH, Bishop DL, Kaminsky LA. Cardiorespiratory fitness and mortality in healthy men and women. J Am Coll Cardiol. 2018;72(19):2283-2292. 2. Blair SN, Kohl HW 3rd, Paffenbarger RS Jr, Clark DG, Cooper KH, Gibbons LW. Physical fitness and all-cause mortality. A prospective study of healthy men and women. JAMA. 1989;262(17):2395-2401. 3. Wei M, Kampert JB, Barlow CE, et al. Relationship between low cardiorespiratory fitness and mortality in normal-weight, overweight, and obese men. JAMA. 1999;282(16):1547-1553. 4. Ozemek C, Laddu DR, Lavie CJ, et al. An update on the role of cardiorespiratory fitness, structured exercise and lifestyle physical activity in preventing cardiovascular disease and health risk. Prog Cardiovasc Dis. 2018;61(5-6):484-490. 5. de Lannoy L, Sui X, Lavie CJ, Blair SN, Ross R. Change in submaximal cardiorespiratory fitness and all-cause mortality. Mayo Clin Proc. 2018;93(2):184-190.
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6. Sui X, Ott J Jr, Becofsky K, et al. Cardiorespiratory fitness and all-cause mortality in men with emotional distress. Mayo Clin Proc. 2017;92(6):918-924. 7. Nauman J, Nes BM, Lavie CJ, et al. Prediction of cardiovascular mortality by estimated cardiorespiratory fitness independent of traditional risk factors: the HUNT study. Mayo Clin Proc. 2017; 92(2):218-227. 8. Pedersen BK, Saltin B. Exercise as medicine d evidence for prescribing exercise as therapy in 26 different chronic diseases. Scand J Med Sci Sports. 2015;25(suppl 3):1-72. 9. Kokkinos PF, Faselis C, Myers J, et al. Cardiorespiratory fitness and incidence of major adverse cardiovascular events in US veterans: a cohort study. Mayo Clin Proc. 2017;92(1):39-48. 10. Ross R, Blair SN, Arena R, et al. Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign: a scientific statement from the American Heart Association. Circulation. 2016;134(24):e653-e699. 11. Kaminsky LA, Arena R, Beckie TM, et al. The importance of cardiorespiratory fitness in the United States: the need for a national registry: a policy statement from the American Heart Association. Circulation. 2013;127(5):652-662. 12. Kaminsky LA, Arena R, Myers J. Reference Standards for cardiorespiratory fitness measured with cardiopulmonary exercise testing: data from the Fitness Registry and the Importance of Exercise National Database. Mayo Clin Proc. 2015;90(11): 1515-1523. 13. Kaminsky LA, Imboden MT, Arena R, Myers J. Reference standards for cardiorespiratory fitness measured with cardiopulmonary exercise testing using cycle ergometry: data from the Fitness Registry and the Importance of Exercise National Database (FRIEND) registry. Mayo Clin Proc. 2017;92(2):228-233. 14. Loe H, Rognmo O, Saltin B, Wisloff U. Aerobic capacity reference data in 3816 healthy men and women 20-90 years. PLoS One. 2013;8(5):e64319. 15. Edvardsen E, Hansen BH, Holme IM, Dyrstad SM, Anderssen SA. Reference values for cardiorespiratory response and fitness on the treadmill in a 20- to 85-year-old population. Chest. 2013;144(1):241-248. 16. Hakola L, Komulainen P, Hassinen M, et al. Cardiorespiratory fitness in aging men and women: the DR's EXTRA study. Scand J Med Sci Sports. 2011;21(5):679-687. 17. Grigaliuniene A, Ramonas A, Celutkiene J, et al. Cardiorespiratory parameters of exercise capacity in a healthy Lithuanian population: the pilot study. Hellenic J Cardiol. 2013;54(2): 107-118. 18. Rossi Neto JM, Tebexreni AS, Alves ANF, et al. Cardiorespiratory fitness data from 18,189 participants who underwent treadmill cardiopulmonary exercise testing in a Brazilian population. PLoS One. 2019;14(1):e0209897. 19. de Souza ESCG, Kaminsky LA, Arena R, et al. A reference equation for maximal aerobic power for treadmill and cycle ergometer exercise testing: Analysis from the FRIEND registry. Eur J Prev Cardiol. 2018;25(7):742-750. 20. Nauman J, Tauschek LC, Kaminsky LA, Nes BM, Wisloff U. Global fitness levels: findings from a web-based surveillance report. Prog Cardiovasc Dis. 2017;60(1):78-88. 21. Nelson MD, Petersen SR, Dlin RA. Effects of age and counseling on the cardiorespiratory response to graded exercise. Med Sci Sports Exerc. 2010;42(2):255-264. 22. Itoh H, Ajisaka R, Koike A, et al. Heart rate and blood pressure response to ramp exercise and exercise capacity in relation to age, gender, and mode of exercise in a healthy population. J Cardiol. 2013;61(1):71-78. 23. Inbar O, Oren A, Scheinowitz M, Rotstein A, Dlin R, Casaburi R. Normal cardiopulmonary responses during incremental exercise in 20- to 70-yr-old men. Med Sci Sports Exerc. 1994;26(5):538-546. 24. Whaley MH, Kaminsky LA, Dwyer GB, Getchell LH. Failure of predicted VO2peak to discriminate physical fitness in epidemiological studies. Med Sci Sports Exerc. 1995;27(1):85-91.
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25. Myers J, Kaminsky LA, Lima R, Christle JW, Ashley E, Arena R. A Reference equation for normal standards for VO2 max: analysis from the Fitness Registry and the Importance of Exercise National Database (FRIEND registry). Prog Cardiovasc Dis. 2017;60(1):21-29. 26. Myers J, Arena R, Franklin B, et al. Recommendations for clinical exercise laboratories: a scientific statement from the American Heart Association. Circulation. 2009;119(24):3144-3161. 27. Riebe DEJK, Liguori G, Magal M. ACSM’s Guidelines for Exercise Testing and Prescription. 10th ed. Philadelphia, PA: Wolters Kluwer; 2018. 28. Fitzgerald MD, Tanaka H, Tran ZV, Seals DR. Age-related declines in maximal aerobic capacity in regularly exercising vs. sedentary women: a meta-analysis. J Appl Physiol (1985). 1997;83(1):160-165. 29. Shvartz E, Reibold RC. Aerobic fitness norms for males and females aged 6 to 75 years: a review. Aviat Space Environ Med. 1990;61(1):3-11. 30. Garber CE, Blissmer B, Deschenes MR, et al. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc. 2011; 43(7):1334-1359. 31. Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled
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32.
33.
34.
35.
36.
37.
38.
analysis of 358 population-based surveys with 1$9 million participants. Lancet Glob Health. 2018;6(10):e1077-e1086. Kokkinos P, Myers J, Franklin B, Narayan P, Lavie CJ, Faselis C. Cardiorespiratory fitness and health outcomes: a call to standardize fitness categories. Mayo Clin Proc. 2018; 93(3):333-336. Myers J, Doom R, King R, et al. Association between cardiorespiratory fitness and health care costs: the Veterans Exercise Testing Study. Mayo Clinic Proc. 2018;93(1):48-55. Mandsager K, Harb S, Cremer P, Phelan D, Nissen SE, Jaber W. Association of Cardiorespiratory Fitness With Long-term Mortality Among Adults Undergoing Exercise Treadmill Testing. JAMA Netw Open. 2018;1(6):e183605. Wang Y, Chen S, Zhang J, et al. Nonexercise Estimated Cardiorespiratory Fitness and All-Cancer Mortality: the NHANES III study. Mayo Clin Proc. 2018;93(7):848-856. McAuley PA, Keteyian SJ, Brawner CA, et al. Exercise capacity and the obesity paradox in heart failure: the FIT (Henry Ford Exercise Testing) project. Mayo Clinic Proc. 2018;93(6):701-708. World Health Organization. Global Status Report on Noncommunicable Diseases 2014. Geneva, Switzerland: World Health Organization; 2014. Letnes JM, Dalen H, Vesterbekkmo EK, Wisloff U, Nes BM. Peak oxygen uptake and incident coronary heart disease in a healthy population: the HUNT Fitness Study. Eur Heart J. 2019;40(20):1633-1639.
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Development of Global Reference Standards for Directly Measured Cardiorespiratory Fitness: A Report From the Fitness Registry and Importance of Exercise National Database (FRIEND) James E. Peterman, PhD; Ross Arena, PhD; Jonathan Myers, PhD; Susan Marzolini, PhD; Robert Ross, PhD; Carl J. Lavie, MD; Ulrik Wisløff, PhD; Dorthe Stensvold, PhD; and Leonard A. Kaminsky, PhD Abstract Objective: To begin the process of developing global reference standards for adults from directly measured cardiorespiratory fitness (CRF). Methods: Percentiles of maximal oxygen consumption (VO2max) for men and women were determined for each decade from 20 through 79 years of age using International data from the Fitness Registry and Importance of Exercise: A National Database (FRIEND-I) along with previously published data from seven studies. FRIEND-I data from January 1, 2014, through January 1, 2019, included 11,678 maximal treadmill tests from three countries, whereas the previously published reports included 32,329 maximal treadmill tests from six countries. Results: FRIEND-I data revealed significant differences between sex and age groups for VO2max (P<0.01). For the 20- to 29-years of age group, the 50th percentile VO2max in men and women were 49.5 mLO2,kg-1,min-1 and 40.6 mLO2,kg-1,min-1, respectively. VO2max declined an average of 9% per decade with the 50th percentile for the 70- to 79-years of age group having a VO2max of 30.8 mLO2,kg-1,min-1 in men and 25.0 mLO2,kg-1,min-1 in women. These results were similar in magnitude and direction to the previously published literature. Within both the FRIEND-I and previously published data there were CRF differences between countries. Conclusion: This report begins to establish global reference standards for CRF. Continued development of FRIEND-I will increase global representation providing an improved ability to identify and stratify CRF risk categories. ª 2019 Mayo Foundation for Medical Education and Research
ardiorespiratory fitness (CRF) is an important marker for health and quality of life. Greater levels of CRF are associated with decreased allcause, cardiovascular disease (CVD), and cancer mortality.1-7 Furthermore, greater levels of CRF are associated with decreased risks for numerous chronic diseases, such as depression, diabetes, obesity, CVD, and even some forms of cancer.4,8,9 As such, a recent American Heart Association (AHA)
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Scientific Statement concluded that CRF should be considered a clinical vital sign that is regularly assessed similar to other established chronic disease risk factors.10 Increasing the recognition of CRF as an important clinical vital sign has been limited by a lack of uniform standards for interpretation. This was the impetus for an AHA policy statement which suggested establishing a national CRF database.10 This policy statement was the impetus for the creation of the
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From the Fisher Institute of Health and Well-Being, Ball State University, Muncie, IN (J.E.P., L.A.K.); Department of Physical Therapy and Integrative Physiology Laboratory, College of Applied Science, University of Illinois, Affiliations continued at the end of this article.
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Fitness Registry and the Importance of Exercise: A National Database (FRIEND).11 The data within FRIEND includes only directly measured CRF from exercise tests that meet objectively verified criteria for maximal effort. These reference standards assist clinicians and other health professionals with interpreting and communicating CRF results to patients in a meaningful way. In the initial FRIEND reports12,13 CRF reference standards for men and women of different ages from the United States were compared with published standards from Norway,14,15 Finland,16 and Lithuania.17 Additional evidence, including a FRIEND report on nonexercise prediction equations, has also included CRF comparisons between the United States and Brazil.18,19 These comparisons clearly revealed the presence of international heterogeneity in CRF values, and thus underline the need for developing global CRF reference standards. Recently, Nauman et al.20 presented global reference standards using estimated CRF as there was no database of directly measured global CRF values. However, the estimated CRF global standards were higher than those presented in large cohort studies in which CRF was directly measured.12-15,18,21-23 These differences could be due to differences in study subject characteristics or the wellknown errors associated with predicting CRF from non-exercise test variables.24,25 Therefore, a global normative CRF reference standard based on directly measured CRF is needed to provide more accurate standards of comparison for researchers and clinicians who directly measure CRF. A registry of global CRF data will also provide an opportunity to improve non-exercise algorithms that can then be used to estimate CRF in clinical settings when direct measure is not possible or feasible. Whereas the original goal of FRIEND was to create a US registry for adults,11 the International data from the FRIEND (FRIEND-I) cohort now includes data from several international sources. Publications with reported reference values from international sites provide an additional opportunity to compare international CRF values. 2
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Thus, the purpose of the present analysis is to begin the process of establishing global reference standards for directly measured CRF using data from FRIEND-I along with previously published data. This report will focus on data obtained from directly measured CRF using cardiopulmonary exercise testing (CPX) with the treadmill as the mode of exercise. METHODS The data collection and management for the FRIEND registry has been reported previously.12 Briefly, the FRIEND registry is composed of data from high-quality laboratories performing CPX administered by experienced personnel. Although laboratories varied in terms of equipment, protocols, and definitions of CRF (eg, maximum oxygen consumption [VO2max] determined from different time averages), all laboratories conducted testing in accordance with published guidelines.26 Each contributing laboratory obtained local research ethics board approval before submitting deidentified, coded data to the data coordinating center at Ball State University. From Ball State University, data were forwarded to the core laboratory at the University of Illinois at Chicago, which has institutional review board approval for maintaining the database. Data from each contributing laboratory were reviewed by both the coordinating center and core laboratory to ensure CRF values were within expected normal ranges before the data were added to FRIEND-I. FRIEND-I Cohort The present analysis includes 11,678 treadmill tests from 14 participating laboratories (see Acknowledgments). Geographic representation includes three countries: Canada (n¼1431), Norway (n¼3668), and the United States (n¼6588). Whereas FRIENDI includes data from individuals with a range of characteristics, specific inclusion criteria were used to create the present cohort. Inclusion criteria were: (1) no pre-existing diagnosis of CVD; (2) no pre-existing chronic obstructive pulmonary disease; (3) maximal CPX performed on a treadmill; XXX 2019;nn(n):1-10
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(4) participants were ages 20 to 79 years; and (5) there was a peak respiratory exchange ratio of greater than or equal to 1.10 to indicate a maximal effort. Literature Cohort The literature cohort was created from previously published studies with the following criteria: (1) subject pool of apparently healthy individuals with no CVD; (2) reported VO2max via cardiopulmonary gasexchange measurement from a maximal exercise test performed on a treadmill; and (3) reported VO2max separated by sex and age grouped by decade (ie, 20 to 29 years, 30 to 39 years, etc). Given that exercise mode influences the determination of VO2max,27 two studies were excluded as the authors combined treadmill and cycling data.28,29 Seven published studies were included in the literature cohort, representing six different countries: Brazil,18 Canada,21 Israel,23 Japan,22 Norway,14,15 and the United States.12 Inclusion and exclusion criteria were specific to each study (details provided in Supplemental Table); however, participants in each study were reported as being in good general health. The majority of studies presented CRF reference values in a table.12,14,15,18,21 However, the study from Japan provided reference values in the form of regression equations,22 which were used to calculate CRF based on the middle of each age range (ie, 25 years old, 35 years old, etc) for comparison in this report. Also, the study from Israel23 included no table of reference values for those aged 31 to 60 years and the provided regression equations were not legible. Therefore, the CRF for age groups within this range were estimated by drawing lines connecting age and absolute VO2max on the manuscript figures. The estimated absolute VO2max was then divided by the average body weight for each group. Additionally, age groups in the study from Israel were different by þ1 year but were still used within the age grouping of the present study. In the case of Norway, in which there were two studies, weighted averages were used to calculate a national average. To Mayo Clin Proc. n XXX 2019;nn(n):1-10 www.mayoclinicproceedings.org
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obtain weighted averages within each age and sex category, CRF values from each individual study were multiplied by their respective sample size, added together, and then divided by the combined sample size. Weighted averages were also used to determine a second global reference standard to compare to the reference values from within the FRIEND-I database. Statistical Analysis All statistical analyses were performed using SPSS software (version 25, IBM Corporation, Armonk, NY). Two-way analysis of variance was used to compare differences in CRF values between sex groups and across age groups within the FRIEND dataset. When significant differences were detected, the Tukey test was used for post hoc analysis. Statistical significance was designated at the P less than 0.05 level. Continuous data are presented throughout the paper as mean SD whereas categorical data are reported as frequencies (percentages). RESULTS The FRIEND-I cohort used for the CRF analysis included tests on 6457 men and 5219 women, across an age range of 20 to 79 years. Descriptive characteristics of the cohort, by sex and age groups, are provided in Table 1. Summaries of the values from each country are provided in Table 2. In both men and women, the highest CRF values reaching statistical significance were from Norway (P<.01), averaging 43% higher than Canadian values and 28% higher than US values. The literature cohort included tests on 21,391 men and 10,938 women (Table 3). Summaries of the reference values from previously published literature for treadmill tests are presented in Table 3. As individual data from each study were not available, statistical comparisons were not made. Observationally, however, for both men and women, CRF values from Norway were consistently the highest across all age groups, averaging 11% higher than the next highest country. Additionally, the Israeli study23 only reported data with men; these
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TABLE 1. Descriptive Characteristics of the FRIEND-I Cohort for the Treadmill Analysisa Age group, y Sex
20-29
30-39
40-49
50-59
60-69
70-79
Men Age, y Height, cm Weight, kg
(n¼756) 24.03.0 179.77.5 80.714.9
(n¼1128) 35.22.9 179.36.6 87.116.5
(n¼1606) 44.52.9 178.87.2 87.815.7
(n¼1409) 54.42.8 178.08.2 88.916.0
(n¼924) 63.82.7 176.68.9 87.616.0
(n¼634) 72.62.3 176.09.4 81.311.6
(n¼562)
(n¼909)
(n¼1272)
(n¼1226)
(n¼678)
(n¼572)
24.32.7 166.66.5 66.914.4
35.32.8 165.96.1 71.617.2
44.82.8 164.96.3 73.017.0
54.32.8 163.58.0 74.816.7
63.92.7 162.66.1 73.714.4
72.72.3 162.46.2 67.811.4
Women Age, y Height, cm Weight, kg a
FRIEND-I ¼ International data from the Fitness Registry and the Importance of Exercise: A National Database.
CRF values averaged 16% lower than the next lowest country. Reference standards using FRIEND-I data and the literature data are provided in Table 4. The previously published global reference standards using estimated CRF20 are presented as a comparison. There were significant differences between sex and age groups for treadmill VO2max from the FRIEND-I dataset (P<.001), with men having on average a 26% greater VO2max than women. The highest CRF was in the 20- to 29- yearold age group; within FRIEND-I, average
VO2max was 49.39.9 mLO2,kg-1,min-1 for men and 40.29.2 mLO2,kg-1,min-1 for women. For men, both the FRIEND-I and literature cohorts had an average rate of decline of 9% per decade. For women, CRF decreased by 9% per decade in the FRIENDI cohort whereas the literature cohort decreased by 10%. Observationally, the global reference using estimated CRF was greater than either the FRIEND-I or literature cohort determinations. Box plots of the FRIEND-I data by age and sex are presented in the Figure.
TABLE 2. Comparison of CRF Reference Values Determined From a Treadmill Test Within the FRIEND-Ia Dataset, Separated by Country (MeanSD)b Age group, y Sex
20-29
Men Canada
30-39
40-49
50-59
60-69
70-79
34.18.0
29.47.2
28.66.3
26.76.0
23.65.3
(n¼43)
(n¼89)
48.97.6
46.67.2
(n¼144)
(n¼207)
(n¼64)
42.27
38.86.3
33.26.3
Norway
54.37.7 (n¼184)
(n¼286)
(n¼413)
(n¼350)
(n¼210)
(n¼441)
United States
47.610.0
42.39.9
38.39.1
33.78.7
29.67.4
26.76.5
(n¼572)
(n¼799)
(n¼1104)
(n¼915)
(n¼507)
(n¼129)
28.06.4
27.16.1
25.05.0
23.25.1
20.44.1
(n¼88)
(n¼217)
(n¼280)
(n¼212)
(n¼76)
39.96.5
38.16.7
34.85.7
31.65.2
27.75.5
Women Canada
a
Norway
43.27.6 (n¼184)
(n¼326)
(n¼401)
(n¼327)
(n¼147)
(n¼399)
United States
38.79.6
31.38.2
28.57.7
24.56.0
21.75.2
19.53.7
(n¼378)
(n¼495)
(n¼654)
(n¼619)
(n¼319)
(n¼97)
FRIEND-I ¼ International data from the Fitness Registry and the Importance of Exercise: A National Database. Values reported in mLO2,kg-1,min-1.
b
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TABLE 3. Comparison of CRFa Reference Values Determined From a Treadmill Test in Previously Published Literature, Separated by Country (MeanSD)b Age group, y Sex Men Brazil18 Canada21 Israel23,c Japan22,d Norway14,15,e United States12
20-29
30-39
40-49
50-59
60-69
70-79
45.07.5
43.57.9
41.67.8
38.67.9
33.77.1
28.76.7
(n¼1201)
(n¼4427)
(n¼4383)
(n¼1728)
(n¼362)
(n¼48)
d
40.67.3
38.47.0
35.26.5
31.64.2
d
(n¼141)
(n¼398)
(n¼235)
(n¼42)
37.67.4
34.3
31.2
26.9
25.05.0
(n¼98)
(n¼603)
(n¼492)
(n¼188)
(n¼43)
48.3
43.2
38.2
33.1
28
22.9
(n¼18)
(n¼26)
(n¼17)
(n¼16)
(n¼17)
(n¼8)
53.5
48.6
46.5
41.7
37.7
34.1
d
(n¼237)
(n¼398)
(n¼617)
(n¼554)
(n¼383)
(n¼100)
47.611.3
43.09.9
38.89.6
33.89.1
29.47.9
25.87.1
(n¼513)
(n¼963)
(n¼1327)
(n¼1078)
(n¼593)
(n¼137)
Women Brazil18 Japan22,c Norway14,15,d United States12
36.96.6
36.07.0
34.77.1
31.46.5
26.55.7
23.45.9
(n¼732)
(n¼2028)
(n¼1985)
(n¼624)
(n¼128)
(n¼14)
35.5
33.4
31.3
29.2
27.1
25.1
(n¼19)
(n¼14)
(n¼18)
(n¼19)
(n¼25)
(n¼7)
42.6
39.6
37.6
33.8
30.6
26.2
(n¼252)
(n¼422)
(n¼579)
(n¼507)
(n¼299)
(n¼94)
37.610.2
30.98.0
27.97.7
24.26.1
20.75.0
18.33.6
(n¼410)
(n¼608)
(n¼843)
(n¼805)
(n¼408)
(n¼98)
CRF ¼ cardiorespiratory fitness. Values reported in mLO2,kg-1,min-1. c Values for ages 30-59 years are estimated as described in the Methods. Original study did not present meanSD for ages 31-60 years in table form; also, age group classifications were 20-30, 31-40, 41-50, 51-60, and 61-70 years. d Study did not present meanSD. Values presented were estimated as described in the Methods. e Weighted averages from Loe et al14 and Edvardsen et al15 used to determine national mean. a
b
DISCUSSION The present analysis begins to establish global normative reference values from directly measured CRF. Reference values were created based on FRIEND-I as well as the previously published literature. Little difference was observed between the literature and FRIEND-I cohort values. Within FRIEND-I, men had a VO2max which was 26% higher compared with women whereas the literature cohort suggests a difference of 25%. The age-related rate of decline in CRF was also similar between the literature and FRIEND-I cohort values, averaging a decrease of 9% to 10% per decade. Although the literature cohort had a greater global Mayo Clin Proc. n XXX 2019;nn(n):1-10 www.mayoclinicproceedings.org
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representation, the current FRIEND-I database includes data from two of the seven previously published studies,12,14 which could contribute to the similarities between values. Nonetheless, these similarities suggest data within FRIEND-I are representative of weighted averages from the literature cohort. This report also highlights the international heterogeneity in directly measured CRF similar to a previous report using estimated CRF.20 The CRF values from Norway14,15 were consistently higher compared with other countries. Additionally, whereas men and women from Brazil, Canada, and Norway had age-related CRF declines of 8% to 9% per decade, greater declines were
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TABLE 4. Normative Reference Standards for Treadmill Tests From the FRIEND-Ia Cohort, the Literature Cohort, and Nauman et al (2017)20 (Estimated CRF)b Age group, y Sex
20-29
Men FRIEND cohort
49.39.9
43.79.9
(n¼756)
(n¼1128)
46.3
42.8
(n¼2067)
Literature cohort Nauman et al20,c
30-39
40-49
50-59
60-69
70-79
40.09.6
35.39.1
31.18.1
30.97.2
(n¼1606)
(n¼1409)
(n¼924)
(n¼634)
40.6
36.9
32.6
29.1
(n¼6558)
(n¼7234)
(n¼3799)
(n¼1,440)
(n¼245)
56.3
53.7
50.8
47.7
44.6
40.6
40.29.2
34.18.7
31.38.5
27.47.2
24.36.4
25.46.2
(n¼562)
(n¼909)
(n¼1272)
(n¼1226)
(n¼678)
(n¼572)
38.1
35.5
33.5
29.0
25.2
22.3
(n¼1413)
(n¼3072)
(n¼3425)
(n¼1955)
(n¼860)
(n¼199)
45.1
42.5
40.4
37.5
34.8
31.3
Women FRIEND cohort Literature cohort Nauman et al20,c
CRF ¼ cardiorespiratory fitness; FRIEND ¼ Fitness Registry and the Importance of Exercise: A National Database; FRIEND-I ¼ International data from the Fitness Registry and the Importance of Exercise: A National Database. b Values reported in mlO2,kg-1,min-1. c Sample sizes not provided by Nauman et al20 for each group. a
observed for Japanese men (14% per decade) and both sexes in the US data (11% to 13% per decade). There are a multitude of potential reasons for the international heterogeneity in CRF. Physical activity habits are a significant determinant of CRF30 and, as such, international differences in physical activity could explain these disparities. However, Brazil had the lowest prevalence of physical activity of the countries within the literature analysis,31 yet does not have the lowest CRF values, suggesting other factors may also be important. It is also possible that the smaller sample sizes and geographic representation for studies from some countries, such as Canada, may have biased the CRF values. Another potential contributor to the heterogeneity in CRF is the health status of the cohorts. Whereas the literature cohort included apparently healthy individuals, the definitions varied (Supplemental Table [available online at http://www. mayoclinicproceedings.org]). For example, in the Norwegian studies, Edvardsen et al15 excluded individuals with two or more CVD risk factors when participants were older than 49 years of age and Loe et al14 excluded those taking blood pressure 6
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medications. More lenient criteria were used in the study from the United States in that participants could have CVD risk factors but not actual CVD and participants were not excluded based on medications.12 Furthermore, within the FRIEND-I data, body mass index differed between the countries, with Canada having the highest (29.9 kg,m-2) and Norway having the lowest (25.6 kg,m-2). These differences suggest the cohorts from Norway may have been healthier which may have contributed to higher CRF values. Methodological limitations associated with comparing CRF highlight the need to continue developing a global registry of CRF data to reduce potential bias of national CRF values and to improve international comparisons. The AHA recommends that CRF be considered a clinical vital sign.10 To improve the prognostic utility of CRF, it is important to establish objective CRF reference standards from cases directly measured by CPX, rather than relying on estimated CRF reference standards. For example, both the FRIEND and literature cohort values were lower than those reported by Nauman et al20 using estimated CRF with differences XXX 2019;nn(n):1-10
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VO2max (mlO2·kg–1·min–1)
80 70 60 50 40 30 20 10 0
A 80 VO2max (mlO2·kg–1·min–1)
increasing in magnitude with age. In the 70- to 79-year-old age group, reference values for both men and women using estimated CRF were ~34% higher than the directly measured CRF values, which could alter treatment plans from clinicians or other health professionals. The higher estimated CRF values could be due to data collection methods with volunteers participating as they were more interested in CRF and consequently had a higher CRF. Estimated values could also be higher due to errors associated with prediction equations.24,25 A database of directly measured CRF would improve global reference standards and also provide an opportunity for future research to improve non-exercise algorithms for estimating CRF in settings when direct measure is not feasible. Epidemiologic research has often identified a CRF threshold of 5 to 6 metabolic equivalents (METs) below which the risk for all-cause mortality greatly increases.10 However, a nonspecific CRF threshold can be problematic32 as the meaning of 6 METs (ie, 21 mLO2,kg-1,min-1) is markedly different depending on the age and sex of an individual. For example, using the percentile data, a VO2max of 21 mLO2,kg1 ,min-1 would place a 65-year-old man into the 10th percentile, a 65-year-old woman into the 30th percentile, and a 25-year-old man below the first percentile. Thus, using reference standards by age and sex, as presented in this study, enhances the interpretation of CRF by researchers or clinicians. Additionally, it is important to recognize that these standards are based on directly measured CRF from CPX. A CRFderived risk threshold may also vary between countries. For example, it was not uncommon across the age groups for CRF values to vary between countries by -1 -1 e 3.5 mLO2,kg ,min , or 1 MET. This 1 MET difference has previously been shown to be associated with decreased health care costs,33 and a decreased risk (8% to 35%) for mortality1,10,34-36 and could partly explain the lower noncommunicable disease mortality rates observed for Norway.37 CRF is inversely associated with mortality in
70 60 50 40 30 20 10 0 20-29
B
30-39
40-49 50-59 Age group (y)
60-69
70-79
FIGURE. Box plots of measured maximal oxygen uptake (VO2max) in the International data from the Fitness Registry and the Importance of Exercise: A National Database for men (A) and women (B). Values are reported in mLO2,kg-1,min-1.
both the United States1 and Norway,38 despite CRF differences between the two countries. Thus, relative CRF changes within countries may be more important than absolute changes in determining health risk and risk thresholds for CRF may be countrydependent. The strength of the present study is that it presents international CRF comparisons and begins to establish global normative CRF reference values derived from CPX, the gold-standard assessment of exercise capacity. There were, however, some limitations that should be addressed. The determination of the global reference values was based on a relatively small number of
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countries and the ethnicity was predominantly white (e89%). This is due to the limited range of ethnicities available in the literature as well as within FRIEND-I. Further, within FRIEND-I and the literature, data come primarily from developed countries, although the actual educational and economic status of participants is either unknown or not reported. Despite small sample sizes and estimates of CRF, data from Israel and Japan were included to increase the geographic representation of the literature cohort. The health status of individuals within FRIEND-I may also not be representative of countries as the body mass index for Canadian adults within FRIEND-I (29.9 kg,m-2) is higher than the country average presented in a recent report (27.2 kg,m-2).37 The global representation of FRIEND-I will improve with continued development of the registry. Additionally, although all data were from experienced laboratories and test effort was objectively determined, differing testing protocols, equipment, and definitions of test effort could have impacted the determination of CRF. Individual data were also not available from the literature cohorts, so statistical tests were not performed, and only observational comparisons were made for the different countries. Also, as the CRF data is presented as VO2max normalized to body weight, it is possible the observed differences between countries and ages are influenced by variations in body weight. Certainly, further study of the potential role of differences in body weight on differences in CRF is warranted. Lastly, cycling is another mode of exercise used when determining CRF and can result in different values.13,27 Future research is needed to create global reference values for cycling tests. CONCLUSION International heterogeneity exists in directly measured CRF and suggests the need for global normative CRF reference values. FRIEND was created with a focus on establishing normative reference values for the United States, but with the addition of international data, is now well positioned to 8
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meaningfully contribute to developing global reference standards. Certainly, reference standards created using the data within FRIEND-I are similar to those created when using data from the literature, although potential limitations exist. Continued development of FRIEND-I is needed to provide greater representation from around the world. The beginnings of global normative CRF reference values presented will assist with continued investigations of international CRF and health comparisons as well as provide researchers and clinicians with improved reference standards to assist with classification and treatment of patient populations. ACKNOWLEDGMENTS FRIEND-I Consortium Contributors are as follows: Ball State University (Leonard Kaminsky), Brooke Army Medical Center (Kenneth Leclerc), Cone Health (Paul Chase), Johns Hopkins University (Kerry Stewart), Pennington Biomedical Research Center (Timothy Church), Southern Connecticut State University (Robert Axtell), University of Illinois at Chicago (Jacob Haus), University of Tennessee, Knoxville (David Bassett), Taylor University (Erik Hayes), University of Kansas Medical Center (Sandy Billinger), Brigham and Women’s Hospital (Amil Shah), Queens University (Robert Ross), KITE, Toronto RehabUniversity Health Network (Susan Marzolini, Rene Belliard, and Noah Koblinsky), the Nord-Trøndelag Health Study (HUNT) which is a collaboration between the HUNT Research Centre (Faculty of Medicine and Health Sciences at the Norwegian University of Science and Technology), the Nord-Trøndelag County Council, Central Norway Health Authority and the Norwegian Institute of Public Health (Ulrik Wisløff), and the Norwegian University of Science and Technology (Dorthe Stensvold, Ulrik Wisløff). SUPPLEMENTAL ONLINE MATERIAL Supplemental material can be found online at http://www.mayoclinicproceedings.org. XXX 2019;nn(n):1-10
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Supplemental material attached to journal articles has not been edited, and the authors take responsibility for the accuracy of all data. Abbbreviations and Acronyms: AHA = American Heart Association; CRF = cardiorespiratory fitness; CVD = cardiovascular disease; CPX = cardiopulmonary exercise testing; FRIEND = Fitness Registry and the Importance of Exercise: A National Database; FRIEND-I = International data from the Fitness Registry and the Importance of Exercise: A National Database; MET = metabolic equivalent; VO2max = maximal oxygen consumption Affiliations (Continued from the first page of this article.): Chicago, IL (R.A.); Division of Cardiology, Veterans Affairs Palo Alto Healthcare System and Stanford University, CA (J.M.); KITE, Toronto Rehab-University Health Network, Ontario, Canada (S.M.); School of Medicine, Department of Endocrinology and Metabolism, Faculty of Health Sciences, Queens University, Kingston, Ontario, Canada (R.R.); John Ochsner Heart and Vascular Institute, Ochsner Clinical School, The University of Queensland School of Medicine, New Orleans, LA (C.J.L.); and the Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway (U.W., D.S.).
Potential Conflicts of Interest: The authors report no conflicts of interest. Grant Support: Partial support for this project was provided by TKC Global (L.K.; grant number GS04T11BFP0001). This project was also partially supported by Central Norway Regional Health Authority, St Olav Hospital, Trondheim, Norway, Research Council of Norway, and The K.G. Jebsen foundation for medical research, Norway. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Correspondence: Address to Leonard A. Kaminsky, PhD, Fisher Institute of Health and Well-Being, Ball State University, 2000 W. University Ave, Muncie, IN 47306 ([email protected]).
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