0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Contribution |

Prevalence and Cardiovascular Disease Correlates of Low Cardiorespiratory Fitness in Adolescents and Adults FREE

Mercedes R. Carnethon, PhD; Martha Gulati, MD, MS; Philip Greenland, MD
[+] Author Affiliations

Author Affiliations: Department of Preventive Medicine (Drs Carnethon, Gulati, and Greenland) and Division of Cardiology, Department of Medicine (Drs Gulati and Greenland), Feinberg School of Medicine, Northwestern University, Chicago, Ill.

More Author Information
JAMA. 2005;294(23):2981-2988. doi:10.1001/jama.294.23.2981.
Text Size: A A A
Published online

Context Population surveys indicate that physical activity levels are low in the United States. One consequence of inactivity, low cardiorespiratory fitness, is an established risk factor for cardiovascular disease (CVD) morbidity and mortality, but the prevalence of cardiorespiratory fitness has not been quantified in representative US population samples.

Objectives To describe the prevalence of low fitness in the US population aged 12 through 49 years and to relate low fitness to CVD risk factors in this population.

Design, Setting, and Participants Inception cohort study using data from the cross-sectional nationally representative National Health and Nutrition Examination Survey 1999-2002. Participants were adolescents (aged 12-19 years; n = 3110) and adults (aged 20-49 years; n = 2205) free from previously diagnosed CVD who underwent submaximal graded exercise treadmill testing to achieve at least 75% to 90% of their age-predicted maximum heart rate. Maximal oxygen consumption (O2max) was estimated by measuring the heart rate response to reference levels of submaximal work.

Main Outcome Measures Low fitness defined using percentile cut points of estimated O2max from existing external referent populations; anthropometric and other CVD risk factors measured according to standard methods.

Results Low fitness was identified in 33.6% of adolescents (approximately 7.5 million US adolescents) and 13.9% of adults (approximately 8.5 million US adults); the prevalence was similar in adolescent females (34.4%) and males (32.9%) (P = .40) but was higher in adult females (16.2%) than in males (11.8%) (P = .03). Non-Hispanic blacks and Mexican Americans were less fit than non-Hispanic whites. In all age-sex groups, body mass index and waist circumference were inversely associated with fitness; age- and race-adjusted odds ratios of overweight or obesity (body mass index ≥25) ranged from 2.1 to 3.7 (P<.01 for all), comparing persons with low fitness with those with moderate or high fitness. Total cholesterol levels and systolic blood pressure were higher and levels of high-density lipoprotein cholesterol were lower among participants with low vs high fitness.

Conclusion Low fitness in adolescents and adults is common in the US population and is associated with an increased prevalence of CVD risk factors.

Figures in this Article

There is strong and consistent evidence from observational studies that physical inactivity and poor cardiorespiratory fitness (ie, fitness) are associated with higher morbidity and mortality from all causes, including cardiovascular disease (CVD) and cancer.1 United States population reports describe an increasingly less physically active society, with marked downturns in reported physical activity during adolescence and young adulthood.13 Physical activity has been described in the population and in relation to health outcomes; however, prior to the current National Health and Nutrition Examination Survey (NHANES),4 data were not available to quantify objectively determined cardiorespiratory fitness in the US population.

A recently published large international case-control study attributed 12.2% of myocardial infarction in the world's population to physical inactivity.5 The extent to which physical inactivity affects the risk of heart disease through its negative impact on cardiorespiratory fitness, which is associated with a high prevalence of other CVD risk factors, is not known at the population level. The objectives of this report are to describe the prevalence of low fitness in the US population of adolescents and adults younger than 50 years and to relate low fitness to CVD risk factors in this population.

Population

The NHANES is a nationally representative sample of the noninstitutionalized civilian US population. Race/ethnicity was self-reported, and participants were identified using a complex, stratified, multistage probability cluster design that oversampled non-Hispanic blacks, Mexican Americans, persons aged 60 years and older, and low-income individuals so that nationally representative estimates of health could be generated in these often understudied population groups. Beginning in 1999, NHANES became a continuous biannual survey rather than the periodic survey that it had been in the past. This report includes survey years 1999-2000 and 2001-2002. A detailed description of the study design and sampling methodology for NHANES is available.6,7

The overall response rate for those who completed the household interview was 81.9% (9965/12 160), and the response rate for those examined in mobile examination units was 76.3% (9282/12 160). Participants aged 12 through 49 years without existing medical conditions, diagnosed CVD, physical limitations, or abnormal hemodynamic parameters (ie, systolic blood pressure >180 mm Hg, diastolic blood pressure >100 mm Hg, or heart rate >100/min) were eligible to participate in the cardiovascular fitness component of NHANES. Of the 8457 participants in the age range for the cardiovascular fitness examination, 5315 (3110 adolescents [12-19 years] and 2205 adults [20-49 years]) completed the examination. Further details of the exclusion criteria are available.6,8 The NHANES protocol was reviewed and approved by the National Center for Health Statistics institutional review board. All participants provided written informed consent at the time of the household interview and the mobile clinic examination; additional parental consent was required for adolescents younger than 18 years.

Fitness Estimation

The cardiovascular fitness component of NHANES was implemented in 1999 to provide nationally representative data on cardiovascular fitness and its relation to health conditions.8 Because it was not feasible to conduct maximal exercise tests in a population sample this size at multiple examination sites, a submaximal treadmill exercise protocol was used. The initial goal of the submaximal test was to elicit 75% of the age-predicted maximum heart rate (220 − age). During the course of data collection the protocol was modified to allow adolescents and adults to achieve up to 90% and 85%, respectively, of their age-predicted maximum heart rate. To achieve this goal within the allotted test time of 8 minutes (2-minute warm-up and two 3-minute stages), the protocol was designed to administer test protocols of varying difficulty (ie, speed, grade)8 to participants based on age, sex, body mass index (BMI), and self-reported participation in physical activities.

All tests were supervised by trained technicians. Participants walked or ran on treadmills. Heart rate was measured at the end of warm-up and each minute during recovery using an automated monitor with 4 electrodes connected to the thorax and abdomen. At the end of each stage, heart rate and blood pressure were measured. Maximal oxygen consumption (O2max) was estimated by measuring the heart rate response to reference levels of submaximal work. Higher O2max is indicative of more favorable cardiorespiratory fitness. Details of the protocols and fitness calculation formulas are available.8

Although submaximal exercise testing is used clinically to diagnose CVD, it is less than ideal for estimating high fitness, as truly fit persons may not have been asked to perform to their highest level.9 Thus, we focused our report on “low fitness” in the population by using categorizations of low, moderate, and high fitness based on reference percentile cut points as recommended in the NHANES fitness assessment manual.8 Low (<20th percentile), moderate (20th-59th percentiles), and high (≥60th percentile) fitness was defined for adults based on published data from the Aerobics Center Longitudinal Study9,10 and for adolescents based on the FITNESSGRAM program.11,12

Other Measures

Data were collected at all study sites by trained personnel according to standardized procedures.6 Sociodemographic information (ie, age, sex, race/ethnicity, educational attainment, personal and family medical history) was collected during the household interview. Physical examinations and laboratory measurements were performed in a mobile examination center. Weight and height were measured using standard methods and digitally recorded. Body mass index was calculated as weight in kilograms divided by the square of height in meters. Waist circumference was measured horizontally at the uppermost border of the ilium at the end of a normal expiration. Blood pressure was measured 3 to 4 times (first measurement was excluded) with participants in the seated position using a mercury sphygmomanometer.

Blood specimens were processed locally, then stored and shipped to central laboratories for analysis. Levels of total serum cholesterol and triglycerides (measured in the morning examination session only) were measured enzymatically, levels of high-density lipoprotein cholesterol (HDL-C) were measured using precipitation, and levels of low-density lipoprotein cholesterol (LDL-C) were calculated using the Friedewald equation.13 Plasma glucose levels (morning examination session only) were processed using the reference analytic method.14,15 Glycosylated hemoglobin (HbA1c) values were standardized to the method used in the Diabetes Control and Complications Trial.16

Overweight and obesity were identified in adults and adolescents by the World Health Organization BMI criterion.17 While participants with previously diagnosed hypertension and elevated resting blood pressure at the time of examination were excluded from participating in the fitness test,8 we identified previously undetected hypertension in adults according to modified guidelines (identification in this survey was based on a single measurement) from the Report of the Seventh Joint National Committee.18 Hypertension in adolescents was identified as the 90th percentile of systolic or diastolic blood pressure based on age, sex, and height.19 Glucose level was categorized according to cut points defined by the 2004 American Diabetes Association guidelines.20 The metabolic syndrome was determined in adults by National Cholesterol Education Program Adult Treatment Panel III guidelines21 in the subset of adults with measured levels of glucose and triglycerides. The metabolic syndrome was identified in adolescents with 3 or more of the following: triglycerides level of 110 mg/dL (1.4 mmol/L) or greater, HDL-C level of 40 mg/dL (1.0 mmol/L) or less (girls and boys), waist circumference greater than or equal to the sex-specific 90th percentile, fasting glucose level greater than 100 mg/dL (5.6 mmol/L), or hypertension as defined above.19

Statistical Analysis

All analyses were stratified by age category (adolescent and adult) and sex. Participant characteristics were described using means and proportions and their 95% confidence intervals (CIs). The age-adjusted estimated population prevalence (and its 95% CI) of low fitness in the sample was compared across ethnicity using χ2 tests. To evaluate the pattern of association between fitness and CVD risk factors, we categorized estimated O2max into age- and sex-specific deciles and plotted the age- and race-adjusted means of each CVD risk factor. Next, we calculated age- and race-adjusted means and 95% CIs by categories of fitness and compared the low- and moderate-fitness categories with the high-fitness category using F tests. Logistic regression modeling was used to calculate odds ratios and 95% CIs for each of the categorical risk factors (eg, hypertension), comparing participants with low fitness with those in the moderate- or high-fitness categories. SAS version 9.1 (SAS Institute Inc, Cary, NC) and SUDAAN version 9.0.1 (Research Triangle Institute, Research Triangle Park, NC) were used to conduct all analyses; SUDAAN was used to account for the complex sampling design and to apply sampling weights to produce national estimates.7 Statistical significance was determined at P<.05.

Clinical characteristics (ie, lipid levels, glycemia measures, and blood pressure) of the sample were generally within the normal reference ranges, and the prevalence of newly identified hypertension and diabetes was low (Table 1). While the percentage of adolescents reporting no vigorous or moderate physical activity in the previous 30 days was below 15%, more than a quarter of adult men and women reported no activity. Among adults, the mean BMI (26.8) indicated overweight, and nearly a fifth (19%) of adults had the metabolic syndrome.

Table Graphic Jump LocationTable 1. Characteristics of US Adolescents Aged 12-19 Years and Adults Aged 20-49 Years, NHANES 1999-2002

Nineteen percent (19.2%) of the surveyed population—an estimated 16 million adolescents and adults younger than 50 years—were in the low fitness category, and 33.6% of adolescents (approximately 7.5 million US adolescents) and 13.9% of adults (approximately 8.5 million US adults) had low fitness. Among adolescents, the prevalence of low fitness was similar between females (34.4%) and males (32.9%) (χ2 = 0.73; P = .40), but among adults the prevalence of low fitness was significantly higher in females (16.2%) compared with males (11.8%) (χ2 = 5.2; P = .03). Figure 1 shows the prevalence of low fitness by racial/ethnic group. Low fitness was more prevalent across age groups and sex in blacks, Mexican Americans, and those reporting “other” ethnicities than in non-Hispanic whites.

Figure 1. Estimated Prevalence of Low Fitness in the US Population, by Sex and Race/Ethnicity in US Adolescents (12-19 Years) and Adults (20-49 Years), NHANES 1999-2002
Graphic Jump Location

NHANES indicates National Health and Nutrition Examination Survey. See Table 1 footnote for definition of “other” race/ethnicity. Error bars indicate 95% confidence intervals.

Figure 2 displays the association between deciles of fitness estimated by O2max and selected CVD risk factors across age-sex groups. Anthropometric measures, ie, BMI and waist circumference, demonstrated the most consistent inverse associations with fitness. Total cholesterol levels demonstrated a graded inverse association with fitness among adolescents, whereas among adults a trend was less evident. There was a graded positive association between HDL-C levels and fitness in adolescent and adult males, whereas a similar pattern could not be observed in females. Systolic blood pressure was highest among adults and adolescent males in the lowest fitness category, but there was no association in adolescent females. Although participants in the lowest fitness decile had correspondingly higher HbA1c values than those in the highest decile, association across deciles was not graded.

Figure 2. Age- and Race-Adjusted Means of Cardiovascular Disease (CVD) Risk Factors, by Deciles of Estimated Fitness in Female and Male US Adolescents (12-19 Years) and Adults (20-49 Years), NHANES 1999-2002
Graphic Jump Location

For fitness deciles, 1 = low and 10 = high. Fitness estimated by maximal oxygen consumption. BMI indicates body mass index; HbA1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; METs, metabolic equivalent tasks; and NHANES, National Health and Nutrition Examination Survey. To convert mg/dL of total cholesterol and HDL-C to mmol/L, multiply values by 0.0259.

When fitness was categorized into 3 levels, participants across age-sex groups with low fitness had overall significantly higher mean BMIs and waist circumferences than those with high fitness (Table 2). Mean systolic blood pressures and total cholesterol levels showed a similar pattern by fitness categories, but some trends did not achieve statistical significance in adult females (systolic blood pressure) and adult males (total cholesterol). Diastolic blood pressures were significantly higher, while HDL-C levels were significantly lower, among adults with low vs high fitness. Comparable patterns were evident for HDL-C levels in adolescent males, but there was no association in adolescent females. The inverse associations between fitness category and mean values of triglycerides, glucose, and HbA1C did not universally achieve statistical significance.

Table Graphic Jump LocationTable 2. Age- and Race-Adjusted Means of Cardiovascular Disease Risk Factors, by Fitness Status Among Female and Male US Adolescents (12-19 Years) and Adults (20-49 Years), NHANES 1999-2002

Adolescents and adults with low fitness were 2 to 4 times more likely to be overweight or obese than were participants in the moderate or high fitness categories (Table 3). Adolescents who were less fit were more likely to have hypercholesterolemia and the metabolic syndrome, though the association with the metabolic syndrome achieved statistical significance only in adolescent males. Newly identified hypertension, low HDL-C levels, and hypercholesterolemia (among women only) were more prevalent among adults with low vs moderate or high fitness. Nonsignificant increases in prevalence of the metabolic syndrome were observed among the least-fit participants.

Table Graphic Jump LocationTable 3. Age- and Race- Adjusted Odds of Having Cardiovascular Disease Risk Factors in Female and Male US Adolescents (12-19 Years) and Adults (20-49 Years) With Low (vs Moderate or High) Fitness Status, NHANES 1999-2002

Findings from this report indicate that low cardiorespiratory fitness affects approximately 1 out of 5 persons aged 12 through 49 years in the US population—with a disproportionate impact on adolescents, adult females, and nonwhite minorities. The most striking indication of the health burden of low fitness in the US population is the strong association among low fitness, obesity, and CVD risk factors that is already present in adolescents and young adults.

Who Is at Risk?

There is a high prevalence of low fitness in adolescents and a strong correlation between fitness and the presence of CVD risk factors. The relatively higher prevalence of low fitness in adolescents compared with adults in this report may be due in part to study exclusion criteria and the method for defining low fitness. Adults with existing hypertension or other clinical CVDs, which are rare conditions in adolescents, did not participate in the treadmill component of the examination. This potentially biased the sample of adults toward being more fit. Alternatively, because aerobic capacity declines with age,22,23 the standards for defining adequate fitness in adolescents are higher than those for adults. The categories of fitness used in this study were derived from an external reference standard for adolescents that was based on a smaller select sample.11,12 Our data suggest that few adolescents in an ethnically diverse representative US sample meet these fitness expectations.

Although adolescents are not generally considered at risk for having clinical CVD events in the short term, the development of risk factors during adolescence and young adulthood sets the stage for heart disease in the middle and older ages. Much of this evidence has come from longitudinal studies such as the Coronary Artery Risk Development in Young Adulthood (CARDIA) study,24 the Bogalusa Heart Study,25 the Amsterdam Growth and Health Longitudinal Study (AGHLS),26 and the Cardiovascular Risk in Young Finns Study.27 With the exception of CARDIA and the AGHLS, these studies have not investigated the relationship between objectively determined fitness and development of CVD risk factors, and only the AGHLS measured fitness during adolescence. While we are unable to relate adolescent fitness to the subsequent development of risk factors in this cross-sectional survey, we can extrapolate from previous research to suggest that a large segment of US youth who are unfit and overweight are at risk for negative cardiovascular consequences as they age.

Low fitness is more prevalent among females compared with males, and among females, disparities by race/ethnicity were apparent. Absolute levels of cardiorespiratory fitness differ between females and males,22 but fitness categorizations in this study were made based on a sex-specific referent population. Because physical activity, the health behavior most strongly associated with fitness, is consistently lower among women,2 our findings of lower fitness among women are not surprising. Racial/ethnic differences in fitness may also be explained by comparatively lower levels of activity in nonwhites vs whites. Sex and racial/ethnic differences in low fitness nearly parallel the prevalence of obesity in the population28 and may account for the higher prevalence of overweight and obesity in females compared with males.29 The relatively higher prevalence of diabetes and hypertension in racial/ethnic minorities may be attributable, in part, to poorer fitness and physical inactivity in these subgroups. The notable exception that may not be due to health behaviors is the generally higher levels of HDL-C reported among females and blacks.

Fitness and CVD

Numerous studies in adult men and women10,3036 report an association between low fitness and increased mortality from cardiovascular and other causes, including cancer.1,37,38 The relationship between low fitness and cardiovascular mortality in particular is proposed to be mediated by the development of CVD risk factors including hypertension, diabetes, dyslipidemia, and the metabolic syndrome.24,39 Further, physical activity training in efforts to improve fitness have been shown to lower the risk of developing risk factors, independent of changes in weight.40

Obesity and overweight could be described as the seminal public health problem today.41 Body mass index and waist circumference, which are estimates of overall and central adiposity, respectively, demonstrated the most consistent association with fitness in this study, as evidenced by the highest mean values among the least-fit persons that decreased in a nearly graded fashion with increasing fitness. While the correlation between low fitness and other CVD risk factors was not as consistent or dose-dependent, patterns indicated a generally worse cardiovascular profile among the least-fit participants. We attempted to relate low fitness to the 10-year CVD risk using the Framingham Risk Score among adults, but scores were generally too low in this relatively young population sample selected to be at low risk. Despite this, evidence of higher BMI, total cholesterol level, and blood pressure with lower fitness status suggests that less fit persons are at risk for developing CVD if these deleterious patterns persist.

Strengths and Limitations

To our knowledge, this is the first attempt to characterize fitness, determined by objective treadmill testing, in adolescents and adults at the population level. However, these findings are not without limitations. In this sample of US adults, fitness was estimated from a submaximal treadmill test protocol.42 In contrast to symptom-limited maximal protocols with or without direct measurement of oxygen consumption, submaximal testing is inferior for determining fitness because of its reliance on prediction formulas.9,42 These prediction formulas, which are based on estimates of predicted maximum heart rate that are often too low for physically fit persons43 and may not apply to women,22 further compound the risk of error. We were less confident in the ability of the submaximal protocol to accurately estimate “high” fitness. Consequently, we chose not to focus on the prevalence of this protective factor in the population and were unable to quantify the level of fitness that correlated with favorable CVD risk factor levels in the population. Thus, recommendations for achieving specific levels of fitness cannot be made based on this report.

Although treadmill testing is generally considered a safe diagnostic test when conducted in the presence of trained medical personnel, there remains a small risk of death during exercise. To balance the need for public health information about fitness with risks to the individual survey participants, we surveyed a population at very low risk for complications from exercise. Besides the obvious exclusion of older adults who are at higher risk for CVD, individuals with previously diagnosed hypertension were potentially the largest additional group of high-risk individuals who were not tested. An important consequence of this restriction is that we are unable to make generalizations to the population at greatest risk for CVD and the complications of low fitness—ie, older adults and individuals with existing risk factors for CVD. As a result, these data likely represent an underestimate of the true prevalence of low fitness in the population. There remains a paucity of population-level research on the distribution of fitness in older persons and persons with comorbid CVD.

Despite these limitations, this report indicates that low fitness is a prevalent and important public health problem in the US population. The consequences of declines in physical activity over time are now evident by the large proportion of society with low levels of fitness. The correlations we report between low fitness and CVD risk factors suggest a potential trend of increasing morbidity and mortality from chronic diseases—the first sign of which is the burgeoning obesity epidemic. Historical evidence from the campaign to educate about the dangers of cigarette smoking indicates that education efforts, particularly among youth, can retard and reverse these negative health behaviors. Thus, it is plausible that a similar education campaign about the health benefits of physical activity to improve cardiorespiratory fitness, in combination with changes in health care policy to make environments more conducive to physical activity, could begin to reverse this serious public health problem.

Corresponding Author: Mercedes R. Carnethon, PhD, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, 680 N Lake Shore Dr, Suite 1102, Chicago, IL 60611 (carnethon@northwestern.edu).

Author Contributions: Dr Carnethon had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Carnethon, Gulati.

Analysis and interpretation of data: Carnethon, Gulati, Greenland.

Drafting of the manuscript: Carnethon.

Critical revision of the manuscript for important intellectual content: Gulati, Greenland.

Statistical analysis: Carnethon, Gulati.

Obtained Funding: Carnethon, Greenland.

Financial Disclosures: None reported.

Funding/Support: Financial support for data collection was provided by the National Center for Health Statistics (NCHS), a part of the Centers for Disease Control and Prevention, Department of Health and Human Services. Dr Carnethon was supported in part by a career development award from the National Heart, Lung, and Blood Institute, National Institutes of Health (5 K01 HL73249-02).

Role of the Sponsor: All data used in this study were collected by the NCHS; the NCHS had no role in the design and conduct of the study; the analysis and interpretation of the data; or the preparation, review, or approval of the manuscript.

US Department of Health and Human Services.  Physical Activity and Health: A Report of the Surgeon GeneralAtlanta, Ga: Centers for Disease Control and Prevention, National Center for Chronic Disease Control and Prevention; 1996
Caspersen CJ, Pereira MA, Curran KM. Changes in physical activity patterns in the United States, by sex and cross-sectional age.  Med Sci Sports Exerc. 2000;32:1601-1609
PubMed   |  Link to Article
Centers for Disease Control and Prevention.  Prevalence of physical activity, including lifestyle activities among adults—United States, 2000-2001.  MMWR Morb Mortal Wkly Rep. 2003;52:764-769
PubMed
Duncan GE, Li SM, Zhou XH. Cardiovascular fitness among US adults: NHANES 1999-2000 and 2001-2002.  Med Sci Sports Exerc. 2005;37:1324-1328
Link to Article
Yusuf S, Hawken S, Ounpuu S.  et al.  Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study.  Lancet. 2004;364:937-952
PubMed   |  Link to Article
National Center for Health Statistics.  NHANES 1999-2000 Data Files. Available at: http://www.cdc.gov/nchs/about/major/nhanes/currentnhanes.htm. Accessed September 14, 2004
National Center for Health Statistics.  Analytic Guidelines. June 2004. Available at: http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf. Accessed September 14, 2004
National Center for Health Statistics.  NHANES Cardiovascular Fitness Procedure Manual. Available at: http://www.cdc.gov/nchs/data/nhanes/cv.pdf. 2004. Accessibility verified October 13, 2005
American College of Sports Medicine.  ACSM's Guidelines for Exercise Testing and Prescription6th ed. Baltimore, Md: Lippincott Williams & Wilkins; 2000
Blair SN, Kohl HW III, 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;262:2395-2401
PubMed   |  Link to Article
Cureton KJ, Warren GL. Criterion-referenced standards for youth health-related fitness tests: a tutorial.  Res Q Exerc Sport. 1990;61:7-19
PubMed   |  Link to Article
Institute for Aerobics Research.  FITNESSGRAM: The Test Administration ManualDallas, Tex: Institute for Aerobics Research; 1994
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preoperative centrifuge.  Clin Chem. 1972;18:499-502
Fluckiger R, Woodtli T, Berger W. Quantitation of glycosylated hemoglobin by boronate affinity chromatography.  Diabetes. 1984;33:73-76
Link to Article
Gould BJ, Hall PM, Cook JG. A sensitive method for the measurement of glycosylated plasma proteins using affinity chromatography.  Ann Clin Biochem. 1984;21:(pt 1)  16-21
 The relationship of glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the Diabetes Control and Complications trial.  Diabetes. 1995;44:968-983
Link to Article
Expert Panel on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults.  Executive summary of the clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults.  Arch Intern Med. 1998;158:1855-1867
PubMed   |  Link to Article
Chobanian AV, Bakris GL, Black HR.  et al. National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report.  JAMA. 2003;289:2560-2571[published correction appears in JAMA. 2003;290:197].
PubMed   |  Link to Article
Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the Third National Health and Nutrition Examination Survey, 1988-1994.  Arch Pediatr Adolesc Med. 2003;157:821-827
PubMed   |  Link to Article
American Diabetes Association.  Diagnosis and classification of diabetes mellitus.  Diabetes Care. 2004;27(suppl 1):S5-S10
PubMed
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults.  Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III).  JAMA. 2001;285:2486-2497
PubMed   |  Link to Article
Gulati M, Black H, Shaw L.  et al.  The prognostic value of a nomogram for exercise capacity in women.  N Engl J Med. 2005;353:468-475
PubMed   |  Link to Article
Morris CK, Myers J, Froelicher VF, Kawaguchi T, Ueshima K, Hideg A. Nomogram based on metabolic equivalents and age for assessing aerobic exercise capacity in men.  J Am Coll Cardiol. 1993;22:175-182
PubMed   |  Link to Article
Carnethon MR, Gidding SS, Nehgme R, Sidney S, Jacobs DR Jr, Liu K. Cardiorespiratory fitness in young adulthood and the development of cardiovascular disease risk factors.  JAMA. 2003;290:3092-3100
PubMed   |  Link to Article
Gustat J, Srinivasan SR, Elkasabany A, Berenson GS. Relation of self-rated measures of physical activity to multiple risk factors of insulin resistance syndrome in young adults: the Bogalusa Heart Study.  J Clin Epidemiol. 2002;55:997-1006
Link to Article
Ferreira I, Twisk JW, Van Mechelen W, Kemper HC, Stehouwer CD. Current and adolescent levels of cardiopulmonary fitness are related to large artery properties at age 36: the Amsterdam Growth and Health Longitudinal Study.  Eur J Clin Invest. 2002;32:723-731
PubMed   |  Link to Article
Raitakari OT, Taimala S, Porkka KV.  et al.  Associations between physical activity and risk factors for coronary heart disease: the Cardiovascular Risk in Young Finns Study.  Med Sci Sports Exerc. 1997;29:1055-1061
Link to Article
Mokdad AH, Ford ES, Bowman BA.  et al.  Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001.  JAMA. 2003;289:76-79
PubMed   |  Link to Article
Laaksonen DE, Atalay M, Niskanen LK.  et al.  Aerobic exercise and the lipid profile in type 1 diabetic men: a randomized controlled trial.  Med Sci Sports Exerc. 2000;32:1541-1548
PubMed
Ekelund LG, Haskell WL, Johnson JL, Whaley FS, Criqui MH, Sheps DS. Physical fitness as a predictor of cardiovascular mortality in asymptomatic North American men: the Lipid Research Clinics Mortality Follow-up Study.  N Engl J Med. 1988;319:1379-1384
PubMed   |  Link to Article
Blair SN, Kohl HW III, Barlow CE, Paffenbarger RS Jr, Gibbons LW, Macera CA. Changes in physical fitness and all-cause mortality: a prospective study of healthy and unhealthy men.  JAMA. 1995;273:1093-1098
PubMed   |  Link to Article
Blair SN, Kampert JB, Kohl HW III.  et al.  Influences of cardiorespiratory fitness and other precursors on cardiovascular disease and all-cause mortality in men and women.  JAMA. 1996;276:205-210
PubMed   |  Link to Article
Gulati M, Pandey DK, Arnsdorf MF.  et al.  Exercise capacity and the risk of death in women: the St James Women Take Heart Project.  Circulation. 2003;108:1554-1559
PubMed   |  Link to Article
Sandvik L, Erikssen J, Thaulow E, Erikssen G, Mundal R, Rodahl K. Physical fitness as a predictor of mortality among healthy, middle-aged Norwegian men.  N Engl J Med. 1993;328:533-537
PubMed   |  Link to Article
Slattery ML, Jacobs DR Jr. Physical fitness and cardiovascular disease mortality: the US Railroad Study.  Am J Epidemiol. 1988;127:571-580
PubMed
Wei M, Kampert JB, Barlow CE.  et al.  Relationship between low cardiorespiratory fitness and mortality in normal-weight, overweight, and obese men.  JAMA. 1999;282:1547-1553
PubMed   |  Link to Article
Evenson KR, Stevens J, Cai J, Thomas R, Thomas O. The effect of cardiorespiratory fitness and obesity on cancer mortality in women and men.  Med Sci Sports Exerc. 2003;35:270-277
PubMed   |  Link to Article
Lee CD, Blair SN. Cardiorespiratory fitness and smoking-related and total cancer mortality in men.  Med Sci Sports Exerc. 2002;34:735-739
PubMed   |  Link to Article
Laaksonen DE, Lakka H-M, Salonen JT, Niskanen LK, Rauramaa R, Lakka TA. Low levels of leisure-time physical activity and cardiorespiratory fitness predict development of the metabolic syndrome.  Diabetes Care. 2002;25:1612-1618
PubMed   |  Link to Article
Diabetes Prevention Program Research Group.  Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.  N Engl J Med. 2002;346:393-403
PubMed   |  Link to Article
Olshansky SJ, Passaro DJ, Hershow RC.  et al.  A potential decline in life expectancy in the United States in the 21st century.  N Engl J Med. 2005;352:1138-1145
PubMed   |  Link to Article
Jackson AS, Blair SN, Mahar MT, Wier LT, Ross RM, Stuteville JE. Prediction of functional aerobic capacity without exercise testing.  Med Sci Sports Exerc. 1990;22:863-870
PubMed
Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited.  J Am Coll Cardiol. 2001;37:153-156
PubMed   |  Link to Article

Figures

Figure 1. Estimated Prevalence of Low Fitness in the US Population, by Sex and Race/Ethnicity in US Adolescents (12-19 Years) and Adults (20-49 Years), NHANES 1999-2002
Graphic Jump Location

NHANES indicates National Health and Nutrition Examination Survey. See Table 1 footnote for definition of “other” race/ethnicity. Error bars indicate 95% confidence intervals.

Figure 2. Age- and Race-Adjusted Means of Cardiovascular Disease (CVD) Risk Factors, by Deciles of Estimated Fitness in Female and Male US Adolescents (12-19 Years) and Adults (20-49 Years), NHANES 1999-2002
Graphic Jump Location

For fitness deciles, 1 = low and 10 = high. Fitness estimated by maximal oxygen consumption. BMI indicates body mass index; HbA1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; METs, metabolic equivalent tasks; and NHANES, National Health and Nutrition Examination Survey. To convert mg/dL of total cholesterol and HDL-C to mmol/L, multiply values by 0.0259.

Tables

Table Graphic Jump LocationTable 1. Characteristics of US Adolescents Aged 12-19 Years and Adults Aged 20-49 Years, NHANES 1999-2002
Table Graphic Jump LocationTable 2. Age- and Race-Adjusted Means of Cardiovascular Disease Risk Factors, by Fitness Status Among Female and Male US Adolescents (12-19 Years) and Adults (20-49 Years), NHANES 1999-2002
Table Graphic Jump LocationTable 3. Age- and Race- Adjusted Odds of Having Cardiovascular Disease Risk Factors in Female and Male US Adolescents (12-19 Years) and Adults (20-49 Years) With Low (vs Moderate or High) Fitness Status, NHANES 1999-2002

References

US Department of Health and Human Services.  Physical Activity and Health: A Report of the Surgeon GeneralAtlanta, Ga: Centers for Disease Control and Prevention, National Center for Chronic Disease Control and Prevention; 1996
Caspersen CJ, Pereira MA, Curran KM. Changes in physical activity patterns in the United States, by sex and cross-sectional age.  Med Sci Sports Exerc. 2000;32:1601-1609
PubMed   |  Link to Article
Centers for Disease Control and Prevention.  Prevalence of physical activity, including lifestyle activities among adults—United States, 2000-2001.  MMWR Morb Mortal Wkly Rep. 2003;52:764-769
PubMed
Duncan GE, Li SM, Zhou XH. Cardiovascular fitness among US adults: NHANES 1999-2000 and 2001-2002.  Med Sci Sports Exerc. 2005;37:1324-1328
Link to Article
Yusuf S, Hawken S, Ounpuu S.  et al.  Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study.  Lancet. 2004;364:937-952
PubMed   |  Link to Article
National Center for Health Statistics.  NHANES 1999-2000 Data Files. Available at: http://www.cdc.gov/nchs/about/major/nhanes/currentnhanes.htm. Accessed September 14, 2004
National Center for Health Statistics.  Analytic Guidelines. June 2004. Available at: http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf. Accessed September 14, 2004
National Center for Health Statistics.  NHANES Cardiovascular Fitness Procedure Manual. Available at: http://www.cdc.gov/nchs/data/nhanes/cv.pdf. 2004. Accessibility verified October 13, 2005
American College of Sports Medicine.  ACSM's Guidelines for Exercise Testing and Prescription6th ed. Baltimore, Md: Lippincott Williams & Wilkins; 2000
Blair SN, Kohl HW III, 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;262:2395-2401
PubMed   |  Link to Article
Cureton KJ, Warren GL. Criterion-referenced standards for youth health-related fitness tests: a tutorial.  Res Q Exerc Sport. 1990;61:7-19
PubMed   |  Link to Article
Institute for Aerobics Research.  FITNESSGRAM: The Test Administration ManualDallas, Tex: Institute for Aerobics Research; 1994
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preoperative centrifuge.  Clin Chem. 1972;18:499-502
Fluckiger R, Woodtli T, Berger W. Quantitation of glycosylated hemoglobin by boronate affinity chromatography.  Diabetes. 1984;33:73-76
Link to Article
Gould BJ, Hall PM, Cook JG. A sensitive method for the measurement of glycosylated plasma proteins using affinity chromatography.  Ann Clin Biochem. 1984;21:(pt 1)  16-21
 The relationship of glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the Diabetes Control and Complications trial.  Diabetes. 1995;44:968-983
Link to Article
Expert Panel on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults.  Executive summary of the clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults.  Arch Intern Med. 1998;158:1855-1867
PubMed   |  Link to Article
Chobanian AV, Bakris GL, Black HR.  et al. National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report.  JAMA. 2003;289:2560-2571[published correction appears in JAMA. 2003;290:197].
PubMed   |  Link to Article
Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the Third National Health and Nutrition Examination Survey, 1988-1994.  Arch Pediatr Adolesc Med. 2003;157:821-827
PubMed   |  Link to Article
American Diabetes Association.  Diagnosis and classification of diabetes mellitus.  Diabetes Care. 2004;27(suppl 1):S5-S10
PubMed
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults.  Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III).  JAMA. 2001;285:2486-2497
PubMed   |  Link to Article
Gulati M, Black H, Shaw L.  et al.  The prognostic value of a nomogram for exercise capacity in women.  N Engl J Med. 2005;353:468-475
PubMed   |  Link to Article
Morris CK, Myers J, Froelicher VF, Kawaguchi T, Ueshima K, Hideg A. Nomogram based on metabolic equivalents and age for assessing aerobic exercise capacity in men.  J Am Coll Cardiol. 1993;22:175-182
PubMed   |  Link to Article
Carnethon MR, Gidding SS, Nehgme R, Sidney S, Jacobs DR Jr, Liu K. Cardiorespiratory fitness in young adulthood and the development of cardiovascular disease risk factors.  JAMA. 2003;290:3092-3100
PubMed   |  Link to Article
Gustat J, Srinivasan SR, Elkasabany A, Berenson GS. Relation of self-rated measures of physical activity to multiple risk factors of insulin resistance syndrome in young adults: the Bogalusa Heart Study.  J Clin Epidemiol. 2002;55:997-1006
Link to Article
Ferreira I, Twisk JW, Van Mechelen W, Kemper HC, Stehouwer CD. Current and adolescent levels of cardiopulmonary fitness are related to large artery properties at age 36: the Amsterdam Growth and Health Longitudinal Study.  Eur J Clin Invest. 2002;32:723-731
PubMed   |  Link to Article
Raitakari OT, Taimala S, Porkka KV.  et al.  Associations between physical activity and risk factors for coronary heart disease: the Cardiovascular Risk in Young Finns Study.  Med Sci Sports Exerc. 1997;29:1055-1061
Link to Article
Mokdad AH, Ford ES, Bowman BA.  et al.  Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001.  JAMA. 2003;289:76-79
PubMed   |  Link to Article
Laaksonen DE, Atalay M, Niskanen LK.  et al.  Aerobic exercise and the lipid profile in type 1 diabetic men: a randomized controlled trial.  Med Sci Sports Exerc. 2000;32:1541-1548
PubMed
Ekelund LG, Haskell WL, Johnson JL, Whaley FS, Criqui MH, Sheps DS. Physical fitness as a predictor of cardiovascular mortality in asymptomatic North American men: the Lipid Research Clinics Mortality Follow-up Study.  N Engl J Med. 1988;319:1379-1384
PubMed   |  Link to Article
Blair SN, Kohl HW III, Barlow CE, Paffenbarger RS Jr, Gibbons LW, Macera CA. Changes in physical fitness and all-cause mortality: a prospective study of healthy and unhealthy men.  JAMA. 1995;273:1093-1098
PubMed   |  Link to Article
Blair SN, Kampert JB, Kohl HW III.  et al.  Influences of cardiorespiratory fitness and other precursors on cardiovascular disease and all-cause mortality in men and women.  JAMA. 1996;276:205-210
PubMed   |  Link to Article
Gulati M, Pandey DK, Arnsdorf MF.  et al.  Exercise capacity and the risk of death in women: the St James Women Take Heart Project.  Circulation. 2003;108:1554-1559
PubMed   |  Link to Article
Sandvik L, Erikssen J, Thaulow E, Erikssen G, Mundal R, Rodahl K. Physical fitness as a predictor of mortality among healthy, middle-aged Norwegian men.  N Engl J Med. 1993;328:533-537
PubMed   |  Link to Article
Slattery ML, Jacobs DR Jr. Physical fitness and cardiovascular disease mortality: the US Railroad Study.  Am J Epidemiol. 1988;127:571-580
PubMed
Wei M, Kampert JB, Barlow CE.  et al.  Relationship between low cardiorespiratory fitness and mortality in normal-weight, overweight, and obese men.  JAMA. 1999;282:1547-1553
PubMed   |  Link to Article
Evenson KR, Stevens J, Cai J, Thomas R, Thomas O. The effect of cardiorespiratory fitness and obesity on cancer mortality in women and men.  Med Sci Sports Exerc. 2003;35:270-277
PubMed   |  Link to Article
Lee CD, Blair SN. Cardiorespiratory fitness and smoking-related and total cancer mortality in men.  Med Sci Sports Exerc. 2002;34:735-739
PubMed   |  Link to Article
Laaksonen DE, Lakka H-M, Salonen JT, Niskanen LK, Rauramaa R, Lakka TA. Low levels of leisure-time physical activity and cardiorespiratory fitness predict development of the metabolic syndrome.  Diabetes Care. 2002;25:1612-1618
PubMed   |  Link to Article
Diabetes Prevention Program Research Group.  Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.  N Engl J Med. 2002;346:393-403
PubMed   |  Link to Article
Olshansky SJ, Passaro DJ, Hershow RC.  et al.  A potential decline in life expectancy in the United States in the 21st century.  N Engl J Med. 2005;352:1138-1145
PubMed   |  Link to Article
Jackson AS, Blair SN, Mahar MT, Wier LT, Ross RM, Stuteville JE. Prediction of functional aerobic capacity without exercise testing.  Med Sci Sports Exerc. 1990;22:863-870
PubMed
Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited.  J Am Coll Cardiol. 2001;37:153-156
PubMed   |  Link to Article

Letters

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 134

Related Content

Customize your page view by dragging & repositioning the boxes below.

See Also...
Articles Related By Topic
Related Collections
PubMed Articles
JAMAevidence.com

The Rational Clinical Examination EDUCATION GUIDES
Clubbing